Drift Degradation Analysis REV 03

ANL-EBS-MD-000027

September 2004 


EXECUTIVE SUMMARY 
Degradation of underground openings as a function of time is a natural and expected occurrence 
for any subsurface excavation. Over time, changes occur to both the stress condition and the 
strength of the rock mass due to several interacting factors. Once the factors contributing to 
degradation are characterized, the effects of drift degradation can typically be mitigated through 
appropriate design and maintenance of the ground support system. However, for the 
emplacement drifts of the geologic repository at Yucca Mountain, it is necessary to characterize 
drift degradation over a 10,000-year period, which is well beyond the functional period of the 
ground support system. This document provides an analysis of the amount of drift degradation 
anticipated in repository emplacement drifts for discrete events and time increments extending 
throughout the 10,000-year regulatory period for postclosure performance. This revision of the 
drift degradation analysis was developed to support the license application and fulfill specific 
agreement items between the U.S. Nuclear Regulatory Commission (NRC) and the U.S. 
Department of Energy (DOE). 
The earlier versions of Drift Degradation Analysis (BSC 2001 [DIRS 156304]) relied primarily 
on the DRKBA numerical code, which provides for a probabilistic key-block assessment based 
on realistic fracture patterns determined from field mapping in the Exploratory Studies Facility 
(ESF) at Yucca Mountain. A key block is defined as a critical block in the surrounding rock 
mass of an excavation, which is removable and oriented in an unsafe manner such that it is likely 
to move into an opening unless support is provided. However, the use of the DRKBA code to 
determine potential rockfall data at the repository horizon during the postclosure period has 
several limitations: 
 The DRKBA code cannot explicitly apply dynamic loads due to seismic ground motion. 
 The DRKBA code cannot explicitly apply loads due to thermal stress. 
 The DRKBA code, which determines structurally controlled key-block failure, is not 
applicable for stress-controlled failure in the lithophysal units. 
To address these limitations, additional numerical codes have been included that can explicitly 
apply seismic and thermal loads, providing significant improvements to the analysis of drift 
degradation and extending the validity of drift degradation models. 
KEY COMPONENTS OF REPOSITORY ROCKFALL MODELING 
Rock Mass CharacterizationThe repository horizon is located in both lithophysal (lower 
lithophysal [Tptpll] and upper lithophysal [Tptpul] zones) and nonlithophysal (middle 
nonlithophysal [Tptpmn] and lower nonlithophysal [Tptpln] zones) rock units in the Topopah 
Spring Tuff. These two rock types are expected to have fundamentally different modes of failure 
under static and dynamic loading, and require different analysis methods. The nonlithophysal 
rocks, which comprise roughly 15 percent of the emplacement area, are hard, strong; jointed rock 
masses; whereas the lithophysal rocks, which comprise approximately 85 percent of the 
emplacement area, are relatively more deformable with lower compressive strength. 
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Drift Degradation Analysis 
The geologic structure and rock strength defines the failure mode in the Tptpmn. The failure 
mode in the Tptpmn is due to gravity drop of rock blocks resulting from stress-induced yield in 
either the intact rock or the joint surfaces. The analysis of the failure mechanism is complicated 
somewhat by the fact that the jointing in the Tptpmn is of relatively short continuous trace length 
and is discontinuous in nature, thus forming fewer kinematically removable blocks. This type of 
jointing results in an inherently stronger rock mass as opposed to typical blocky rock masses 
where the block structure is well defined by multiple, continuous joint sets. 
The Tptpll is characterized by about 10 to 30 percent lithophysal cavities by volume. This unit 
has abundant small-scale fractures between lithophysae that result in the relatively weaker nature 
of the material. Rock mass failure in the Tptpll is controlled by the transient ground motion 
induced stress concentrations that occur around the excavation. The mode of failure is primarily 
via tension from rarefaction of vertically traveling compression waves. 
Seismic Ground MotionSite-specific ground motions have been determined based on results 
from a probabilistic seismic hazard analysis. For a suite of ground motion measures, the 
probabilistic seismic hazard analysis determined the annual probability that various levels of 
ground motion would be exceeded. For an annual probability of exceedance of interest, a site 
response model modifies the ground motion from the probabilistic seismic hazard analysis by 
taking into account the effect of local site materials. Peak ground velocity determined from the 
site response model is used to develop seismic time histories (typically fifteen three-component 
sets) for postclosure rockfall analysis. The time histories are developed such that observed 
randomness among time histories, for a given peak ground velocity, is maintained. The time 
histories thus appropriately reflect variability in ground motion estimation for Yucca Mountain. 
Thermal StressOnce the waste packages are placed within the emplacement drifts, heat will be 
released as a part of the process of the radioactive materials in the waste packages becoming less 
radioactive over time. This heat will transfer to the rock mass and thermally induced stresses 
will be generated by thermal expansion of the rock mass. Thermal stresses at any location 
depend on the proximity and timing of waste emplacement, the amount of heat generated, the 
age of the waste, packaging and emplacement configuration, ventilation of the emplacement 
drifts, and the thermal-mechanical properties of the rock mass. Thermal stresses are 
time-dependent and are calculated over the 10,000-year regulatory period for postclosure 
performance. 
Time-Dependent Degradation of Rock StrengthThe rock mass surrounding the emplacement 
drifts may undergo over-stressing from thermal heating or time-dependent damage associated 
with static fatigue resulting from stress corrosion mechanisms. This damaged material may 
result in a slow unraveling (lithophysal rock) or block fallout (nonlithophysal rock). In the 
nonlithophysal rocks, static fatigue failure of roughness along fracture surfaces is possible and 
could result in gravitationally induced block failures. Static fatigue of hard rocks typically is 
associated with stress levels on the order of 80 percent or greater of the uniaxial compressive 
strength. This means that fatigue failure would presumably initiate along asperities on fracture 
surfaces, reducing their effective friction angle. In the case of the lithophysal rocks, the 
compressive stress concentrations along the immediate rib springline of the emplacement drifts 
will be near the uniaxial compressive strength so static fatigue failure is a distinct possibility. 
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Drift Degradation Analysis 
ROCKFALL MODELING OF NONLITHOPHYSAL TUFF 
A nonlithophysal rockfall model was developed using the three-dimensional discontinuum code, 
3DEC. This model includes the development of fracture patterns generated from multiple 
sampling from a synthetic rock mass volume that contains a realistic fracture population based 
on field mapping data. Site-specific ground motion time histories appropriate for both the 
preclosure and postclosure time periods, are included in the model. 
Degradation in the nonlithophysal units is primarily controlled by geologic structure. Preclosure 
ground motion results in minor drift damage due to rockfall. It should be noted that the results 
presented in this report are based on unsupported drift openings. The rockfall estimate during 
the preclosure period should be conservative, because the rockfall models do not consider ground 
support, while ground support will in fact be included to prevent rockfall. Postclosure ground 
motion results in varying extent of drift damage due to rockfall, with localized areas of rock 
failure sufficient to cover the drip shield. 
Thermal-mechanical analyses were conducted using both a base case set of thermal properties 
and a sensitivity case considering the values for thermal conductivity and specific heat one 
standard deviation smaller than the mean. The transient temperature field around the repository 
was calculated using 90- and 70-percent ventilation heat removal efficiencies. There was 
minimal rockfall predicted at any time for the thermal only scenario (i.e., no seismic loading) for 
the cases analyzed. When thermal stresses were considered in combination with the stresses 
resulting from postclosure seismic ground motion, it is clearly shown that thermal loading 
significantly reduces the amount of rockfall. 
Drift stability due to the effect of time-dependent rock joint degradation is assessed based on a 
reduction of joint cohesion and friction angle. The reduced joint strength parameters are 
estimated to be in the range of the residual state with joint cohesion reduced to zero and the joint 
friction angle reduced to 30 degrees. Dilation angle is also reduced to zero considering that the 
asperities on fracture surfaces had been sheared off. The degraded joint strength and dilational 
properties were applied for several selected cases, including the worst cases (cases with the most 
rockfall), the typical case, and the no rockfall case observed with postclosure seismic ground 
motion. While a slight increase in rockfall is predicted for the degradated state, joint strength 
degradation has a minor impact on drift stability. 
ROCKFALL MODELING OF LITHOPHYSAL TUFF 
A lithophysal rockfall model was developed using the two-dimensional discontinuum code, 
UDEC. In this model, the rock mass is represented as an assembly of polygonal, elastic blocks 
in which the bond strength of the blocks is calibrated such that the overall mechanical behavior 
of the mass is consistent with the material model developed for the lithophysal rock. The 
lithophysal rockfall model allows for the formation of fractures between blocks (i.e., the 
formation of internal fracturing), separation, and instability (under action of gravity) of the rock 
mass around the drift. Site-specific ground motion time histories appropriate for both the 
preclosure and postclosure periods, are included in the model. Thermal-mechanical analyses 
were conducted using both a base case set of thermal properties and a sensitivity case 
considering the values for thermal conductivity and specific heat one standard deviation smaller 
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Drift Degradation Analysis 
than the mean. The transient temperature field around the repository was calculated using 90and 
70-percent ventilation heat removal efficiencies. The analysis was done for five categories 
of rock mass qualities, which represents the variability in lithophysal rock mechanical properties 
expected on the repository level. The lowest quality categories (1 and 2) represent the rock mass 
with 20 percent or greater lithophysal porosity, and make up less than about 10 percent of the 
repository host rock. Category 1, which represents the lowest quality/highest porosity rock, 
makes up less than 5 percent of the rock mass and thus represents localized conditions of high 
porosity rock found primarily near the top of the Tptpll. Categories 3, 4, and 5, which are 
representative of the rock mass with approximately 10 to 20 percent lithophysal porosity, are of 
higher geomechanical quality. Category 3, which represents rock with lithophysal porosity of 
approximately 15 to 20 percent, represents a typical rock quality condition. 
Preclosure degradation in the lithophysal units is primarily controlled by stress conditions. The 
analyses show that the drifts are stable after excavation with fracturing extending to a maximum 
depth of less than 0.5 m in the drift walls for the poorest quality rock. No significant rockfall is 
predicted, due to heating, for any of the five rock mass categories irrespective of the considered 
ventilation efficiency (70 or 90 percent) and the selection of rock mass thermal properties. There 
is also no significant rockfall due to preclosure ground motion for rock mass Categories 1 
through 5. A relatively minor amount of rockfall is predicted for preclosure seismic loading for 
the lowest quality, Category 1 rock mass. Little or no rockfall is predicted for other rock 
qualities for preclosure ground motions. Again, it should be noted that the modeled rockfall in 
the Tptpll is based on unsupported drift openings. The absence of ground support in the 
lithophysal rockfall model leads to a conservative rockfall estimate during the preclosure period, 
because the preclosure ground support will be designed to prevent rockfall. 
The analyses of the available static fatigue data indicate that an approximate 40 percent reduction 
in cohesive strength occurs over a 20,000-year period. The nominal case for drift degradation 
(i.e., considering thermal and time-dependent effects, but excluding seismic effects) results in 
only partial collapse of the emplacement drifts at 20,000 years. The lower bound rock mass 
quality is represented as rock mass Category 2, which is considered to be less than 10 percent of 
the rock mass. A combination of the thermally induced stresses with time-dependent strength 
degradation results in time-dependent fracturing and a deterioration of the emplacement drift 
walls for Category 2, however, the drip shield is not expected to be covered during the 
postclosure period. As rock mass quality increases to categories 3 to 5, rockfall becomes less in 
volume with little change in drift profile. Coupling preclosure seismic ground motion with both 
time-dependent strength degradation and thermal load causes additional, but not significant, 
rockfall as a result of shaking down already loose, broken ground. Thus, the nominal scenario 
considers negligible drift degradation occurs over the postclosure period. 
Postclosure ground motions cause drift collapse irrespective of rock mass quality or particular 
case of ground motion. The extreme conditions of drift deterioration due to rock mass strength 
degradation were analyzed. Cohesive strength (cohesion and tensile strength) was gradually 
reduced to zero and resulting rockfall was monitored. The model was set to achieve conservative 
conditions of bulking of the caved rock mass (i.e., such that larger vertical pressures are 
imposed). The resulting average vertical pressures of the rock on the drip shield are, with few 
exceptions, in the range between 150 kN/m2 and 200 kN/m2. The vertical and lateral pressures 
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Drift Degradation Analysis 
associated with complete collapse of the emplacement drifts are conservatively used as input 
loading parameters for the design of the drip shield. 
RESOLUTION OF KEY TECHNICAL ISSUES REGARDING ROCKFALL 
The drift degradation models and analyses documented in this report address the requirements of 
NRC/DOE agreement items regarding rockfall and related issues to support the resolution of 
NRCs key technical issue (KTI) on Repository Design and Thermal-Mechanical Effects. 




Drift Degradation Analysis 
1. PURPOSE 
The purpose of this report is to document the scientific analysis and modeling of the behavior of 
the rock mass surrounding the emplacement drifts of the geologic repository at Yucca Mountain. 
Drift degradation has the potential to affect drip shield integrity, waste package integrity, and 
thermal-hydrologic environments within drifts. The results of this modeling and analysis activity 
provide: 
 Data on rockfall (size distribution, velocity, impact energy and impact location) in 
response to the combined effects of in situ, thermal and seismic loading to support 
structural analyses of the ground support system, the drip shield, and waste package. 
 Transient change in drift profile (size and shape) due to combined in situ, thermal and 
seismic loading and due to nominal time-dependent change in rock mechanical 
properties, which supports analyses of groundwater seepage into the emplacement drift 
during the period of compliance for postclosure performance. 
 Quasi-static load distribution to the drip shield from accumulated rubble for structural 
analysis of drip shield stability. 
 Support for the assessment of in-drift temperature and humidity resulting from the 
presence of rubble within the emplacement drift. 
Figure 1-1 is a schematic that depicts the required inputs supporting the drift degradation 
analysis along with the primary users of the results of this study. In addition to acquired data 
from field mapping (i.e., fracture geometry) and laboratory testing (i.e., rock strength properties), 
the following analysis and modeling reports provide developed data inputs for this report: 
 Geologic Framework Model (GFM2000) (BSC 2004 [DIRS 170029]) 
 Development of Earthquake Ground Motion Input for Preclosure Seismic Design and 
Postclosure Performance Assessment of a Geologic Repository at Yucca Mountain, NV 
(BSC 2004 [DIRS 170027]) 
 Multiscale Thermohydrologic Model (BSC 2004 [DIRS 169565]) 
 Thermal Conductivity of the Potential Repository Horizon (BSC 2004 [DIRS 169854]) 
 Thermal Conductivity of Non-Repository Lithostratigraphic Layers (BSC 2004 
[DIRS 170033]) 
 Heat Capacity and Thermal Expansion Coefficients Analysis Report (BSC 2003 
[DIRS 164670]) 
 Sampling of Stochastic Input Parameters for Rockfall Calculations and for Structural 
Response Calculations Under Vibratory Ground Motion (BSC 2004 [DIRS 169999]). 
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Drift Degradation Analysis 
The outputs from the drift degradation analysis support scientific analyses, models, and design 
calculations, including the following: 
 Abstraction of Drift Seepage 
 Seismic Consequence Abstraction 
 Structural Stability of a Drip Shield Under Quasi-Static Pressure 
 Drip Shield Structural Response to Rock Fall. 
This report has been developed in accordance with Technical Work Plan for: Regulatory 
Integration Modeling of Drift Degradation, Waste Package and Drip Shield Vibratory Motion 
and Seismic Consequences (BSC 2004 [DIRS 171520]). The drift degradation analysis includes 
the development and validation of rockfall models that approximate phenomenon associated with 
various components of rock mass behavior anticipated within the repository horizon. Two drift 
degradation rockfall models have been developed: the rockfall model for nonlithophysal rock 
and the rockfall model for lithophysal rock. These models reflect the two distinct types of 
tuffaceous rock at Yucca Mountain. The output of this modeling and analysis activity 
documents the expected drift deterioration for drifts constructed in accordance with the 
repository layout configuration (BSC 2004 [DIRS 164519]). 
1.1 BACKGROUND 
Information on the Geologic Setting and Repository Subsurface DesignThe repository site 
at Yucca Mountain is located approximately 300 m below ground surface within the Topopah 
Spring formationa densely welded, laterally-expansive tuff unit comprised of a number of 
subunits that dip gently from west to east (BSC 2004 [DIRS 170029], Section 6.5.1.4). These 
subunits can be divided into two broad physical and mechanical categories: nonlithophysal and 
lithophysal1 welded tuffs. The basic matrix material of these two subunits is similar in most 
respects (mineralogical, textural, mechanical properties). However, due to varying cooling 
histories and as a result of position within the flow, they are, structurally (and therefore 
thermomechanically), significantly different in character. The nonlithophysal rocks (the middle 
and lower nonlithophysal units) are hard, strong, fine-grained and fractured volcanic rocks whose 
mechanical behavior is strongly controlled by the geometry and surface characteristics of its 
fracturing. The lithophysal rocks (the upper and lower lithophysal units) are composed of the 
same strong, hard matrix material, but have porosity in the form of lithophysal cavities ranging 
from about 10 percent to 30 percent by volume. The presence of these cavities results in 
significantly different mechanical behavior (i.e., in the deformability and strength) of the rock 
mass. 
LithophysaeA hollow, bubble like cavity in a volcanic rock that is surrounded by a porous rim formed by 
fine-grained alkali feldspar, quartz, and other minerals. Lithophysae are typically a few centimeters to a few 
decimeters in diameter; however, they can be as small as 1 mm in diameter or less to as large as 1 m or more in 
diameter (BSC 2003 [DIRS 166660]). 
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Drift Degradation Analysis 
joi..tiS 
DEVELOPMENT 
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INPUTMODELS & ANALYSES 
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Drp ShieldWaste Package 
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Figure 1-1. Drift Degradation Analysis 
The proposed repository layout and the Topopah Spring Tuff subunits within which the 
excavations are located are shown in Figure 1-2. The repository consists of a series of 
emplacement panels that are accessed via ramps and access mains from the ground surface. The 
emplacement drifts are circular in the cross-section with a diameter of 5.5 m (BSC 2003 
[DIRS 165572], Table 8), and driven at 81-m spacing (Williams 2002 [DIRS 159916]). This 
layout results in approximately 85 percent of the emplacement area to be within the lithophysal 
rocks, and about 15 percent within the nonlithophysal units (BSC 2003 [DIRS 165572], 
Table II-2). 
Waste packages will be delivered to the emplacement drift from the surface facilities on steel 
pallets. The waste package assembly will be placed, using remote handling equipment, on a steel 
framework and crushed tuff drift invert at a nominal 10 cm end-to-end spacing. The nominal 
waste package heat output and spacing result in a maximum thermal loading density of 
1.45 kW/m of drift length (BSC 2004 [DIRS 167369]). The waste packages will be ventilated 
for a minimum of 50 years using forced ventilation air at a nominal delivery rate of 15 m3/sec per 
emplacement drift (BSC 2004 [DIRS 169862], Section 4.1.10). This ventilation air removes 
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Drift Degradation Analysis 
approximately 80 to 90 percent of the heat generated by the waste packages along the typical 
600-m nominal emplacement drift length (BSC 2004 [DIRS 169862], Section 6.6, Figure 6-7) 
during the ventilation period, with resulting drift wall temperatures being approximately 80C 
(BSC 2004 [DIRS 169862], Section 6.6, Figure 6-5). Closure of the repository is considered to 
occur within 100 years after emplacement of the first waste package. Closure involves placing 
drip shields in a continuous covering over the waste packages, backfilling of the access drifts, 
and cessation of forced ventilation. Drift wall temperatures will rapidly rise, reaching a 
maximum at approximately 160C about 20 years after closure, followed by a slow decay over 
time. The drift wall temperature will remain above 100C for approximately 1,000 years (see 
Section 6.2, Figure 6-25). 
Source: Underground Layout Configuration (BSC 2003 [DIRS 165572], Figure II-2). 
NOTE: Numbered labels refer to emplacement panel numbers (BSC 2003 [DIRS 165572], Section 8.1). 
Figure 1-2. Proposed Repository Layout in Plan View Showing Intersections of Geologic Sub-units With 
Emplacement Drifts 
Preclosure and Postclosure Periods and Objectives of Mechanical Degradation Analyses 
Ground support will be functional and maintained during the preclosure period. After closure, 
the ground support will corrode and lose its function over the period of perhaps tens to hundreds 
of additional years. Thus, the emplacement drifts will essentially be unsupported through a 
greater part of the postclosure period. 
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Drift Degradation Analysis 
During the postclosure period, the emplacement drifts will be subjected to the following loading 
conditions (Figure 1-3): 
 In situ gravitational stress state 
 Transient thermally induced stresses due to expansion of the rock mass2 
 Seismic stresses due to potential earthquake shaking. 
In addition, the rock mass strength, particularly in lithophysal rock, will exhibit a degree of 
time-dependency as a result of typical stress corrosion mechanisms3. The impact of these in situ 
and induced stress components is the potential for rock mass yield in the immediate region 
around the tunnels and some degree of rockfall. The rockfall has potential performance impacts 
on the following systems: 
 Mechanical degradation effects on engineered barriers 
- Effects include possible rock particle impacts and dynamic loading of the drip shield, 
either under gravitational or earthquake-induced accelerations. The dynamic loading 
from rock impact derived from this document provides input to Drip Shield Structural 
Response to Rock Fall, which is a calculation providing a structural damage 
assessment due to rockfall impacts. 
- Quasi-static loading and contact from rock particles resting on the drip shield 
following rockfall. The quasi-static loading from rubble derived from a degraded 
emplacement drift presented in this document provides input to Structural Stability of 
a Drip Shield Under Quasi-Static Pressure, which is a calculation providing a 
structural stability assessment of the drip shield under rubble loading. 
 Mechanical degradation effects on in-drift environment 
- Rockfall of sufficient volume could result in an insulating blanket surrounding the 
drip shield (and waste package), impairing heat transfer to the rock mass, and 
increasing waste package temperatures. The importance of this effect on heat transfer 
is dependent on the timing of the rockfall. For example, if significant amounts of 
rockfall occur relatively early in the postclosure period when the waste package is 
still outputting significant heat energy, then there will be a greater impact on waste 
package temperature. Conversely, if significant rockfall occurs in later periods of the 
postclosure period when the waste package has lost most of its energy, then there will 
be a less significant impact on temperature distributions. Additionally, rock particles 
within the drift can potentially alter the in-drift humidity environment and, therefore, 
need to be accounted for in drip shield and waste package corrosion. The impact of a 
complete collapse of an emplacement drift at various times in the postclosure period 
2 A large portion of the thermally induced strains and stress are recoverable as the rock mass cools over time. 
3 Stress Corrosion is a term used for time-dependent, sub-critical crack growth that occurs when existing material 
flaws in the rock are subjected to stresses that are near the failure state of the material. This process, which occurs at 
a more rapid rate in the presence of moisture, may result in damage and yield at applied stresses that are less than the 
short-term strength. Corrosion here does not refer to corrosion of metals. 
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Drift Degradation Analysis 
on in-drift temperature and humidity is analyzed in Multiscale Thermohydrologic 
Model (BSC 2004 [DIRS 169565]). 
 Mechanical degradation effects on seepage of groundwater into the drift 
- Drift degradation could result in temporal changes to the size and shape of the 
emplacement drifts, as well as impact to the capillary flow barrier provided by the 
drift itself. These effects could alter the seepage flow to the drift. Impacts of seepage 
are accounted for in the seismic scenario class and are described in Seismic 
Consequence Abstraction and in Abstraction of Drift Seepage. 
Figure 1-3. Potential Postclosure Performance Impacts of Rockfall on Engineered Barriers, In-Drift 
Environment, and Groundwater Seepage into Drifts 
The primary objectives of the drift degradation analyses discussed in this analysis and model 
report are to provide postclosure estimates of the temporal development of both rockfall and drift 
dimension changes, which are input to the seismic consequences and drift seepage abstractions 
for eventual inclusion into the total system performance assessment (TSPA) modeling. 
Summary of Approach to Addressing Mechanical Degradation IssuesThe approach to 
addressing the mechanical degradation issues described above was presented in Resolution 
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Drift Degradation Analysis 
Strategy for Geomechanically-Related Repository Design and Thermal-Mechanical Effects 
(RDTME) (Board 2003 [DIRS 165036]). A basic factor in the approach described in that report 
is that the repository host rock mass may be subdivided into two general thermomechanical 
units: lithophysal and nonlithophysal rocks, as was described previously. This subdivision is 
made as the mechanical properties and behavior of these units are distinctly different, and, thus, 
the response requires different testing and modeling strategies. In the case of the nonlithophysal 
subunit, the rock mass response is largely controlled by the fracturing; whereas, in the 
lithophysal rock, the mechanical response is highly dependent on the lithophysal porosity and its 
variability. It is recognized that, due to the impact of the geologic structure on the rock mass 
performance, detailed geotechnical characterization is required as a basic building block in 
formulating the rock mass properties, applicable modeling techniques, and analysis procedures. 
The approach (Figure 1-4), which forms the basis of the analyses presented in this report, 
involves the progressive development of a knowledge of the mechanical behavior of lithophysal 
and nonlithophysal rock through: 
 Detailed geotechnical characterization of the rock structure, laboratory, and field testing 
and estimation of rock mass properties 
 Development and validation of numerical modeling tools for estimation of mechanical 
degradation processes 
 Performance analyses of mechanical degradation in response to in situ, thermal, and 
seismic loading. 
This report presents data and analyses in these three broad areas: 
 Geological characterization of the lithophysal and nonlithophysal rock mass and 
development of rock mass properties and their variability 
- Description and analysis of the variability of rock mass fracturing and lithophysae 
characteristics obtained from field mapping in the ESF and Enhanced 
Characterization of the Repository Block (ECRB) Cross-Drift (Sections 6.1 and 
Appendix B describe fracture characteristics, and Sections 7.3 and Appendix O 
describe lithophysal characteristics) 
- Laboratory and in situ testing database of thermal-mechanical and time-dependent 
material properties for the intact rock matrix, lithophysal rock, and fractures 
(Section 4 and Appendix E describe the rock properties database) 
- Estimation of the effect of geologic structure (fractures and lithophysae) and its 
variability on rock mass properties (Section 7.3 and Appendix E) 
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NOTE: Process starts with compilation and analysis of basic geotechnical mapping, followed by laboratory and field 
testing and model validation to develop rock mass property estimates for design and performance sensitivity 
studies. 
Figure 1-4. General Approach to Resolution of the Repository Design and Thermal-Mechanical Effects 
KTIs 
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Drift Degradation Analysis 
 Development and validation of numerical modeling tools 
- Determination or development of appropriate models for sensitivity studies of 
excavation stability and rockfall under gravitational, thermal, and seismic loading as 
well as time-dependent strength changes (Sections 6.3, 6.4, 7, and Appendices S, T, 
U, W, and Y). Specific issues related to selection of appropriate modeling techniques 
addressed in these sections of the report include: 
--Continuum versus discontinuum modeling 
--Two versus three-dimensional models 
--Appropriate initial and boundary conditions 
--Inclusion of time-dependency in the models 
 Mechanical degradation performance analyses and feeds of model output to engineered 
barrier system and drift seepage abstractions to the TSPA model 
- Stability analysis and rockfall estimates for nonlithophysal and lithophysal subunits 
under the action of in situ, thermal, and seismic loading (Section 6) 
- Assessment of long-term stability and rockfall in tunnels subject to time-dependent 
rock mass strength degradation and in situ, thermal, and seismic loading 
(Appendix S). 
1.2 OBJECTIVES 
The specific objectives of the drift degradation analysis are to: 
 Provide validated modeling methods that adequately represent: 
- The mechanical response of the rock mass structure (fractures and lithophysae) 
surrounding the emplacement drift 
- The applied in situ, thermal, and seismic loading conditions and time-dependent rock 
strength degradation mechanisms. 
 Provide a statistical description of block sizes and rockfall volume resulting from 
stress-induced rockfall around the emplacement drifts for the lithologic units of the 
repository host horizon. 
 Provide dynamic and static load distributions to the drip shield resulting from rockfall 
and rubble accumulation in the emplacement drifts 
 Estimate transient changes in emplacement drift profiles resulting from in situ, thermal, 
and seismic stressing and time-dependent rock strength degradation. 
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Drift Degradation Analysis 
1.3 SCOPE OF MODEL DOCUMENTATION 
Activities documented in this report involve developing models, using analytical methods, and 
performing calculations and statistical analyses to determine the expected quantities, locations, 
size distributions, and frequencies of rockfall, based on the repository layout configuration (BSC 
2004 [DIRS 164519]). Drift profiles, including the predicted deterioration as a result of rockfall, 
have been determined. This analysis has examined unsupported drifts with no backfill, and 
applied static, thermal, and seismic loading conditions. 
The scope of model documentation required for analyzing the degradation anticipated in the 
repository emplacement drifts includes the following activities: 
 Conduct a thermal-mechanical assessment of the repository block at Yucca Mountain to 
determine thermal stress inputs to the drift degradation models. 
 Conduct a fracture degradation assessment to account for long-term strength 
degradation. This assessment provides strength degradation inputs to the drift 
degradation models. 
 Develop a drift degradation structural model for nonlithophysal rock that includes 
thermal and seismic loading. 
 Develop a drift degradation lithophysal model that includes thermal and seismic loading. 
Revision 1 ICN 1 of this analysis (BSC 2001 [DIRS 156304]) considered various emplacement 
drift orientations, with the drift azimuth varied in appropriate increments to examine the effect of 
orientation on key block size and frequency. The results from this drift orientation study have 
not been included in this revision, and only the current emplacement drift orientation (BSC 2004 
[DIRS 164519]) has been considered in this report. 
1.4 ANALYSIS/MODEL APPLICABILITY AND LIMITATIONS 
The drift degradation results with seismic and thermal consideration, including the drift profiles, 
are applicable for 5.5-m-diameter emplacement drifts oriented at an azimuth of 72 in accordance 
with the repository underground layout configuration (BSC 2004 [DIRS 164519]; BSC 2004 
[DIRS 168489]; BSC 2003 [DIRS 165572]). The model results presented in this report are 
applicable to the lithophysal and nonlithophysal rock units of the repository host horizon. 
Uncertainties associated with the data available for model development are described in Section 
6.5. The rockfall models presented in this report are valid for conditions anticipated within the 
repository over the 10,000-year regulatory period for both preclosure and postclosure 
performance, including increased loads due to seismic ground motion and thermal stress, and 
decreased rock strength due to time-dependent strength degradation. 
ANL-EBS-MD-000027 REV 03 1-10 September 2004 

Drift Degradation Analysis 
2. QUALITY ASSURANCE 
This analysis and modeling report and the supporting modeling activities are subject to the 
Office of Civilian Radioactive Waste Management quality assurance program, as indicated in 
Technical Work Plan for: Regulatory Integration Modeling of Drift Degradation, Waste Package 
and Drip Shield Vibratory Motion and Seismic Consequences (BSC 2004 [DIRS 171520], 
Section 8). Approved QA procedures identified in the technical work plan (BSC 2004 
[DIRS 171520], Section 4) have been used to conduct and document the activities described in 
this analysis and model report. The technical work plan also identifies the methods used to 
control the electronic management of data (BSC 2004 [DIRS 171520], Section 8) during 
modeling and documentation activities. 
To ensure accuracy and completeness of the information generated by this report, access to the 
information on the personal computer used to develop this report is controlled with password 
protection. The personal computer files are stored on a network drive that is backed up daily per 
Yucca Mountain Project (YMP) standards. Upon completion of this work, the files are 
transferred to a suitable media, appropriately labeled, and verified by examining the file listing. 
Visual checks are conducted on printouts. The electronic files generated by this report are 
transmitted to Document Control for transfer to the Records Processing Center. During the 
checking process, accuracy and completeness of the data retrieved and reported in this document 
is verified against the information placed in the Records Processing Center and YMP 
information databases, as applicable. 
This model report examines the properties of natural or engineered barriers that are classified in 
the Q-List (BSC 2004 [DIRS 168361]) as Safety Category because they are important to waste 
isolation, as defined in AP-2.22Q, Classification Analyses and Maintenance of the Q-List. It 
contributes to the analysis and modeling data used to support performance assessment. The 
conclusions of this model report do not affect the proposed repository design or engineered 
features important to safety, as defined in AP-2.22Q. 
ANL-EBS-MD-000027 REV 03 2-1 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 2-2 September 2004 

Drift Degradation Analysis 
3. USE OF SOFTWARE 
3.1 QUALIFIED COMPUTER SOFTWARE 
All controlled and baselined software used in the development of the drift degradation analysis is 
identified in Table 3-1, including the software tracking number, version, operating environment, 
and range of use. Table 3-1 also includes a discussion of why the software was selected and 
describes any limitations on outputs from the software. The software documented in this section 
is appropriate for the applications used in this drift degradation analysis, and is consistent with its 
intended use. Each software item was obtained from Software Configuration Management in 
accordance with LP-SI.11Q-BSC. All software was used only within the range of its validation 
as specified in the software qualification documentation, in accordance with LP-SI.11Q-BSC. 
The input and output files for each software item used in this analysis have been submitted to the 
Technical Data Management System as noted in Appendix A. 
Table 3-1. List of Qualified Software Supporting the Drift Degradation Analysis 
Software Operating Environment 
Software 
Title/Version 
Tracking 
Number 
(Platform/Operating 
System) 
Brief Description of Software 
(Range of Use/Selection/Limitations) 
UDEC was used to analyze the seismic and 
thermal effects on block movement in the 
UDEC V3.1 
(BSC 2002 
[DIRS 161949]) 
10173-3.1-00 PC/Windows 2000 
lithophysal rock units (Section 6.4). UDEC was 
selected for its capability of modeling block slip 
and block separation in plane strain condition. 
Also, it is capable of thermal and dynamic 
simulation. There are no known limitations on 
outputs. 
3DEC was used to analyze the seismic and 
thermal effects on block movement in the 
3DEC V2.01 
(BSC 2002 
[DIRS 161930]) 
10025-2.01-00 PC/Windows 2000 
nonlithophysal rock units (Section 6.3). 3DEC 
was selected for its capability of modeling of 
wedge type of rockfall with consideration of 
block slip and block separation in three-
dimensional space. Also, it is capable of 
thermal and dynamic simulation. There are no 
known limitations on outputs. 
FLAC was used in the thermal-mechanical 
calculation to define the distribution of stresses 
FLAC V4.0 
(BSC 2002 
[DIRS 161953]) 
10167-4.0-00 PC/Windows 2000 
around the drifts due to the progressive 
heating of the repository area (Section 6.2). 
FLAC was selected as an efficient code to run 
thermal-mechanical analysis. There are no 
known limitations on outputs. 
FLAC3D was used in the thermal-mechanical 
calculation to define the distribution of stresses 
FLAC3D V2.1 
(BSC 2002 
[DIRS 161947]) 
10502-2.1-00 PC/Windows 2000 
around the drifts due to the progressive 
heating of the repository area (Appendix C). 
FLAC3D was selected as an efficient code to 
run thermal-mechanical analysis for the 
regional scale and drift scale. There are no 
known limitations on outputs. 
ANL-EBS-MD-000027 REV 03 3-1 September 2004 

Drift Degradation Analysis 
Table 3-1. List of Qualified Software Supporting the Drift Degradation Analysis (Continued) 
Software 
Software 
Tracking 
Operating Environment 
(Platform/Operating Brief Description of Software 
Title/Version Number System) (Range of Use/Selection/Limitations) 
PFC2D was used to characterize rock mass 
PFC2D V2.0 
(BSC 2002 
[DIRS 161950]) 
10828-2.0-00 PC/Windows 2000 
behavior, including the analysis of long-term 
strength degradation (Section 7 and 
Appendix S). PFC2D was selected for its 
capability of modeling behaviors of a rock 
material by combining behaviors of individual 
grain particles to simulate complicated nonlinear 
deformation of a rock material including 
long-term mechanical strength degradation 
and rock mass deformation with voids. There 
are no known limitations on outputs from 
PFC2D. 
This version of PFC2D was used to run impact 
analyses to confirm the initial PFC2D results 
(using software tracking number 
10828-2.0-00), as documented in Appendix Q. 
PFC2D V2.0 
(BSC 2004 
[DIRS 169930]) 
10828-2.0-01 PC/Windows 2000 
The initial PFC2D software qualification did not 
specifically identify the library of support 
functions (known as Fish functions) that are 
used within the code. This new version 
(software tracking number 10828-2.0-01) 
specifically qualifies FishTank 041b, which is 
the library of Fish functions included within the 
code. The impact assessments in Appendix Q 
confirm that the results are identical using 
either the initial or new version of PFC2D. 
PFC3D was used to characterize rock mass 
PFC3D V2.0 
(BSC 2002 
[DIRS 160612]) 
10830-2.0-00 PC/Windows 2000 
behavior, including the analysis of long-term 
strength degradation (Section 7 and 
Appendix S). PFC3D was selected for its 
capability of modeling behaviors of a rock 
material by combining behaviors of individual 
grain particles to simulate complicated nonlinear 
deformation of a rock material including 
long-term mechanical strength degradation 
and rock mass deformation with voids. There 
are no known limitations on outputs from 
PFC3D. 
This version of PFC3D was used to run impact 
analyses to confirm the initial PFC3D results 
(using software tracking number 
10830-2.0-00), as documented in Appendix Q. 
PFC3D V2.0 
(BSC 2004 
[DIRS 169931]) 
10830-2.0-01 PC/Windows 2000 
The initial PFC3D software qualification did not 
specifically identify the library of support 
functions (known as Fish functions) that are 
used within the code. This new version 
(software tracking number 10830-2.0-01) 
specifically qualifies FishTank 041b, which is 
the library of Fish functions included within the 
code. The impact assessments in Appendix Q 
confirm that the results are identical using 
either the initial or new version of PFC3D. 
ANL-EBS-MD-000027 REV 03 3-2 September 2004 

Drift Degradation Analysis 
Table 3-1. List of Qualified Software Supporting the Drift Degradation Analysis (Continued) 
Software 
Software 
Tracking 
Operating Environment 
(Platform/Operating Brief Description of Software 
Title/Version Number System) (Range of Use/Selection/Limitations) 
DRKBA Version 
DRKBA was used to analyze block 
development and failure in the nonlithophysal 
rock units (Appendix D). DRKBA was selected 
to assess the impact of small-scale fractures 
on rockfall because it has an efficient 
3.31 (BSC 2002 
[DIRS 161946]) 
10071-3.31-00 PC/Windows 2000 key-block simulation algorithm. DRKBA was 
also selected as an alternative numerical code 
to verify the results from 3DEC. DRKBA does 
not directly apply seismic and thermal loads, 
and therefore was not selected as the primary 
code for rockfall analyses. 
FracMan V2.512 
(USGS 1999 
[DIRS 160577]) 
10114-2.511-
00 PC/Windows NT 
FracMan was used to replicate the fracture 
geometry observed in the ESF to develop a 
representative volume of jointed rock mass 
(Section 6.1.6). FracMan was selected for its 
capability of discrete fracture data analysis, 
geologic fracture network construction, spatial 
analysis, and visualization. There are no 
known limitations on outputs. 
NUFT was used to simulate heat transfer 
NUFT V3.0s 
(LLNL 2002 
[DIRS 157280]) 
10088-3.0s-01 SUN/SUN O.S. 5.7 
around the emplacement drift (Section 6.2). 
NUFT was selected for its capability of 
modeling thermal-hydrology of an unsaturated 
zone including subsurface heat and fluid flow. 
There are no known limitations on outputs 
from NUFT. 
EarthVision was used to extract stratigraphic 
unit thickness and cross-sections from the 
EarthVision V.5.1 
(Dynamic 
Graphics 2000 
[DIRS 167994]) 
10174-5.1-00 SGI/IRIX 6.5 
Geological Framework Model (GFM2000) 
(Appendix M). EarthVision was selected for its 
capability of extracting specific data from 
GFM2000 and presenting the data in a 
common graphical format. EarthVision was 
not used to perform data manipulation in this 
report. There are no known limitations on 
outputs based on the range of use in this 
report. 
UNWEDGE V2.3 
(CRWMS M&O 
1998 
[DIRS 145366]) 
30053 V2.3 PC/DOS Emulation 
UNWEDGE was used as a reference-only 
example of a deterministic method for 
key-block analysis (Appendix D). UNWEDGE 
was selected for its common usage on static 
block analysis for the geotechnical and mining 
industries. There are no known limitations on 
outputs. 
Clustran V.1.1 
Clustran was used to analyze fracture data in 
Section 6.1.6. Clustran was selected for its 
(BSC 2004 
[DIRS 169203]) 
11162-1.1-00 PC/Windows 2000 common usage on fracture orientation analysis 
for the geotechnical and mining industries. 
There are no known limitations on outputs. 
ANL-EBS-MD-000027 REV 03 3-3 September 2004 

Drift Degradation Analysis 
Table 3-1. List of Qualified Software Supporting the Drift Degradation Analysis (Continued) 
Software 
Software 
Tracking 
Operating Environment 
(Platform/Operating Brief Description of Software 
Title/Version Number System) (Range of Use/Selection/Limitations) 
Read DXF was used to read fracture data files 
Read DXF V.1.0 
(BSC 2004 
[DIRS 169204]) 
11159-1.0-00 PC/Windows 2000 
in DXF format and extract polyline data with 
associated strike/dip tags for input into 
FracMan (Section 6.1.6). Read DXF was 
specifically developed to extract fracture data 
from full periphery geologic maps to facilitate 
the comparison of field fracture data to 
synthetic FracMan fracture data. There are no 
known limitations on outputs. 
3.2 OTHER SOFTWARE 
In addition to the above listed items, the standard functions of commercial off-the-shelf software, 
including both Microsoft Excel 97 SR-2 and Mathcad 2001i Professional, were used. These 
software items were used to perform support calculation activities as described in Section 6.3, 
Section 6.4, and associated Appendices. Appendix A provides a listing of the calculation files 
(Table A-1), including the location in this report where specific details of the calculation can be 
found. Microsoft Excel was used to calculate joint cohesion degradation, excavation orientation 
inputs, joint description input, and mean rock property values. Additionally, Microsoft Excel 
was used to process and summarize rockfall data and to provide graphical presentation of the 
block size distribution data. Mathcad was used to calculate joint cohesion degradation, joint 
description input parameters, and rock property values. Microsoft Excel 97 SR-2 and Mathcad 
2001i Professional are exempted software applications in accordance with LP-SI.11Q-BSC, 
Section 2.1. 
Appendices D, E, I, J, K, L, O, and T have been provided with this report to document the use of 
standard functions of commercial off-the-shelf software in sufficient detail to allow independent 
repetition of the software in accordance with AP-SIII.10Q, Attachment 2. Specifically, these 
Appendices provide: 
 The formula or algorithm used 
 A listing of the inputs to the formula or algorithm 
 A listing of the outputs from the formula or algorithm 
 Narrative to describe the calculation(s). 
These Appendices document the following calculations: 
 Calculation of joint parameter inputs to DRKBA (Appendix D) 
 Calculation of joint cohesion reduction for thermal and time-dependent effects in 
DRKBA analyses (Appendix D) 
 Calculation of the plane equations to describe the excavation opening as input to 
DRKBA (Appendix D) 
ANL-EBS-MD-000027 REV 03 3-4 September 2004 

Drift Degradation Analysis 
 Calculation of rock property values (Appendix E) 
 Random selection of 3DEC modeling region (Appendix J) 
 Study of the sufficiency of the number of 3DEC simulations to represent the rockfall 
characteristics (Appendix K) 
 Conversion of FracMan fracture output to 3DEC input (Appendix L) 
 Calculation of descriptive statistics of lithophysal abundance and characteristics 
(Appendix O) 
 Projection of lithophysal cavity porosity to a vertical cross section (Appendix T) 
 Calculation of Power Spectral Density and summary of ground motion parameters 
(Appendix X) 
DIPS Version 4.03 (CRWMS M&O 1997 [DIRS 149839]) was used solely for graphical 
presentation of fracture data in Sections 6.1, 6.3, and Appendix B, and is an exempted software 
application in accordance with LP-SI.11Q-BSC, Section 2.1. 
ANL-EBS-MD-000027 REV 03 3-5 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 3-6 September 2004 

Drift Degradation Analysis 
4. INPUTS 
4.1 DIRECT INPUT 
The geotechnical parameters used as direct input for drift degradation analyses include data and 
information collected either by field mapping or by laboratory testing. Input data include 
 Joint geometry 
 Joint mechanical properties 
 Intact rock physical and mechanical properties 
 Rock mass mechanical properties 
 Seismic ground motion 
 Rock thermal properties 
 Repository layout information. 
These data and parameters are summarized in Table 4-1 and described below. Uncertainties in 
input data and parameters are discussed in Section 6.5. 
4.1.1 Fracture Geometry Data 
The development of fracture geometry parameters is based on mapping data collected from the 
ESF, including the main loop (which is composed of the North Ramp, Main Drift, South Ramp) 
and the ECRB Cross-Drift. Qualified joint mapping data in the ESF were collected from the 
following lithologic units: the Topopah Spring Tuff crystal poor upper lithophysal zone 
(Tptpul), the Topopah Spring Tuff crystal poor middle nonlithophysal zone (Tptpmn), the 
Topopah Spring Tuff crystal poor lower lithophysal zone (Tptpll), and the Topopah Spring Tuff 
crystal poor lower nonlithophysal zone (Tptpln). 
Mapping data from the ESF being used in the analysis include both U.S. Geological Survey/U.S. 
Bureau of Reclamation full periphery geologic maps and the detailed line survey. Source data 
tracking numbers (DTNs) for the full periphery geologic maps and the detailed line survey data 
are listed in Table 4-1. 
ANL-EBS-MD-000027 REV 03 4-1 September 2004 

Drift Degradation Analysis 
Table 4-1. Input Data and Parameters for the Drift Degradation Analysis 
Parameter Value Range Source/Supporting Information a Application 
Fracture 
geometry 
Fracture type  from detailed 
line survey 
(Location, Strike, Dip, Length) 
See files Tptpmn 
DLS pole plot.xls 
and Tptpll cu# & 
rad dist plots.xls in 
FracMan Inputs & 
Outputs (Appendix 
A) 
Data summary 
provided by 
Table 6-2 
(Tptpmn); 
Appendix B, 
Table B-1 (Tptpll) 
See files Tptpmn 
DLS pole plot.xls 
and Tptpll cu# & 
rad dist plots.xls in 
FracMan Inputs & 
Outputs (Appendix 
A) 
Data summary 
provided by 
Table 6-2 
(Tptpmn); 
Appendix B, 
Table B-1 (Tptpll) 
GS971108314224.025 DIRS 106025] 
GS960708314224.008 DIRS 105617] 
GS000608314224.004 [DIRS 152573] 
GS960708314224.010 [DIRS 106031] 
GS960908314224.014 [DIRS 106033] 
GS970208314224.003 [DIRS 106048] 
GS970808314224.010 [DIRS 106050] 
GS971108314224.028 [DIRS 106047] 
GS990408314224.001 [DIRS 108396] 
GS990408314224.002 [DIRS 105625] 
Rockfall Model for 
Nonlithophysal Rock 
(Sections 6.1.6, 
6.3.1.2.2, 
Appendix D) 
Full periphery 
geologic maps 
provided by the 
source DTNs 
Full periphery 
geologic maps 
provided by the 
source DTNs 
GS960908314224.020 [DIRS 106059] 
GS000608314224.006 [DIRS 152572] 
GS960908314224.015 [DIRS 108372] 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4.3, 
Appendix B) 
Fracture type  from full 
periphery geologic map 
Data summary 
provided by 
Table 6-2 
(Tptpmn); 
Appendix B, 
Table B-1 (Tptpll) 
Data summary 
provided by 
Table 6-2 
(Tptpmn); 
Appendix B, 
Table B-1 (Tptpll) 
GS960908314224.016 [DIRS 107373] 
GS960908314224.017 [DIRS 108376] 
GS970108314224.002 [DIRS 107490] 
GS990408314224.004 [DIRS 108405] 
GS990408314224.005 [DIRS 108408] 
GS990408314224.006 [DIRS 108409] 
Small-scale 
fracture 
geometry 
Fracture type  from detailed 
line survey 
(Location, Strike, Dip, Length) 
See Appendix A, 
calculation file, 
small trace 
filtering.xls 
Data summary 
provided by 
See Appendix A, 
calculation file, 
small trace 
filtering.xls 
Data summary 
provided by 
GS040108314224.001 [DIRS 169591] 
Rockfall Model for 
Nonlithophysal Rock 
(Sections 6.1.4.1, 
6.3.3) 
Table 6-37 and Table 6-37 and 
Figure 6-105 Figure 6-105 
ANL-EBS-MD-000027 REV 03 4-2 September 2004 

Drift Degradation Analysis 
Table 4-1. Input Data and Parameters for the Drift Degradation Analysis (Continued) 
Parameter Value Range Source/Supporting Information a Application 
Fracture 
strength 
Rotary 
shear 
tests 
Joint normal 
stress, s (MPa); 
Joint peak shear 
stress, tp (MPa); 
Joint dilation (deg) 
See Appendix E, 
Table E-3 
See Appendix E, 
Table E-3 
SNL02112293001.003 [DIRS 108412], 
Olsson and Brown 1997 [DIRS 106453]; 
SNL02112293001.005 [DIRS 108413], 
SNL 1996 [DIRS 165408]; 
SNL02112293001.007 [DIRS 108414], 
SNL 1996 [DIRS 165410] 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.1, 
6.3.1.6.2; 
Appendix E, 
Section E2) 
Joint normal 
stiffness, Kn 
(MPa/mm); 
Joint shear 
stiffness, Ks 
(MPa/mm) 
See Appendix E, 
Table E-4 
See Appendix E, 
Table E-4 
Direct 
shear 
tests 
Joint cohesion 
(MPa); 
Joint friction angle 
(deg); 
Joint dilation 
(deg); 
Joint shear 
stiffness, Ks 
(MPa/mm) 
See Appendix E, 
Table E-5 
See Appendix E, 
Table E-5 
BSC 2003 [DIRS 166660], 
Tables 8-47 and 8-52 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.6.2; 
Appendix E, 
Section E2) 
ANL-EBS-MD-000027 REV 03 4-3 September 2004 

Drift Degradation Analysis 
Table 4-1. Input Data and Parameters for the Drift Degradation Analysis (Continued) 
Parameter Value Range Source/Supporting Information a Application 
Intact rock 
strength for 
nonlithophysal 
rock 
Youngs modulus (GPa); 
Poissons ratio 
See Appendix E, 
Table E-6 
See Appendix E, 
Table E-6 MO0402DQRIRPPR.003 [DIRS 168901] 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.1; 
Appendix E, 
Section E3) 
Tensile strength (MPa) See Appendix E, 
Table E-7 
See Appendix E, 
Table E-7 MO0401DQRIRPTS.003 [DIRS 168905] 
Ultimate differential strength 
(MPa) (also referred to as 
compressive strength, intact 
rock triaxial compressive 
strength, or intact rock 
See Appendix E, 
Table E-8 
See Appendix E, 
Table E-8 MO0311RCKPRPCS.003 [DIRS 166073] 
uniaxial compressive 
strength); 
Confining pressure, s3 (MPa) 
Compressive strength (MPa) 
Rock mass 
strength for 
lithophysal 
rock 
(also referred to as ultimate 
differential strength, intact 
rock triaxial compressive 
strength, or intact rock 
uniaxial compressive 
strength); 
Youngs modulus (GPa); 
Poissons ratio 
See Appendix E, 
Table E-9 
See Appendix E, 
Table E-9 
SN0208L0207502.001 [DIRS 161871] 
SN0211L0207502.002 [DIRS 161872] 
MO0311RCKPRPCS.003 [DIRS 166073] 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4.1.2; 
Appendix E, 
Section E4.1) 
Long-term strength 
(static fatigue) 
See Appendix S, 
Table S-1, 
Figure S-1, 
Figure S-2 
See Appendix S, 
Table S-1, 
Figure S-1, 
Figure S-2 
Martin et al. (1997a [DIRS 165960]) b 
Schmidtke and Lajtai (1985 
[DIRS 164774]) b 
Lau et al. (2000 [DIRS 164769]) b 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4.2.4; 
Appendix S, 
Section S2 
ANL-EBS-MD-000027 REV 03 4-4 September 2004 

Drift Degradation Analysis 
Table 4-1. Input Data and Parameters for the Drift Degradation Analysis (Continued) 
Parameter Value Range Source/Supporting Information a Application 
GS950508314224.003 [DIRS 107488], 
Singleton 1995 [DIRS 107044]; 
GS000608314224.005 [DIRS 166002], 
USGS 1996 [DIRS 169024]; 
GS960408314224.001 [DIRS 168135], 
USGS 1996 [DIRS 169025]; 
GS960408314224.003 [DIRS 168136], 
USGS 1996 [DIRS 169026]; 
GS960708314224.009 [DIRS 168137], 
USGS 1996 [DIRS 169027]; 
GS000608314224.006 [DIRS 152572], 
USGS 1996 [DIRS 169029]; 
GS960908314224.015 [DIRS 108372], 
USGS 1996 [DIRS 169030], and USGS 
1996 [DIRS 169031]; 
Rock mass 
strength for 
thermalmechanical 
units 
Q system 
input 
parameters 
from tunnel 
mapping in 
the ESF 
Rock quality 
designation 
(RQD), 
Jn, 
Jr, 
Ja 
See Appendix A, 
calculation file, 
rock mass 
strength v2.xls, 
worksheet Spatial 
Data 
See Appendix A, 
calculation file, 
rock mass 
strength v2.xls, 
worksheet Spatial 
Data 
GS960908314224.016 [DIRS 108373], 
USGS 1996 [DIRS 169032], and USGS 
1996 [DIRS 169033]; 
GS960908314224.017 [DIRS 108376], 
USGS 1996 [DIRS 169034]; 
GS970108314224.002 [DIRS 107490], 
USGS 1996 [DIRS 169035]; 
Thermal-Mechanical 
Calculation 
(Section 6.2; 
Appendix C; 
Appendix E, 
Section E4.3) 
GS970208314224.004 [DIRS 107492], 
USGS 1997 [DIRS 169036]; 
GS970808314224.009 [DIRS 107494], 
USGS 1997 [DIRS 169037]; 
GS970808314224.011 [DIRS 107495], 
USGS 1997 [DIRS 169038]; 
GS970808314224.013 [DIRS 107497], 
USGS 1997 [DIRS 169039]; 
GS990408314224.003 [DIRS 108404], 
USGS 1999 [DIRS 169018]; 
GS990408314224.004 [DIRS 108405], 
USGS 1999 [DIRS 169019]; 
GS990408314224.005 [DIRS 108408], 
USGS 1999 [DIRS 169020]; 
GS990408314224.006 [DIRS 108409], 
USGS 1999 [DIRS 169021] 
ANL-EBS-MD-000027 REV 03 4-5 September 2004 

Drift Degradation Analysis 
Table 4-1. Input Data and Parameters for the Drift Degradation Analysis (Continued) 
Parameter Value Range Source/Supporting Information a Application 
Rock mass 
strength for 
thermalmechanical 
units 
Intact unconfined 
compressive strength for 
thermal-mechanical units, sci 
(MPa) (also referred to as 
intact rock uniaxial 
compressive strength or 
ultimate differential strength) 
See Appendix A, 
calculation file, 
rock mass 
strength v2.xls, 
worksheet Intact 
Strength 
See Appendix A, 
calculation file, 
rock mass 
strength v2.xls, 
worksheet Intact 
Strength 
MO0311RCKPRPCS.003 [DIRS 166073] 
SNL02030193001.001 [DIRS 120572] 
SN0306L0207502.008 [DIRS 165015] Thermal-Mechanical 
Calculation 
(Section 6.2; 
Appendix C; 
Appendix E, 
Section E4.3)
Intact Poissons ratio for 
thermal-mechanical units; 
Intact Youngs modulus for 
thermal-mechanical units 
(GPa) 
See Appendix A, 
calculation file, 
rock mass 
strength v2.xls, 
worksheet Intact 
Strength 
See Appendix A, 
calculation file, 
rock mass 
strength v2.xls, 
worksheet Intact 
Strength 
MO0402DQRIRPPR.003 [DIRS 168901]] 
SN0306L0207502.008 [DIRS 165015] 
Q system 
input RQD, 
parameters 
from tunnel 
mapping in 
the Heated 
Jn, 
Jr, 
Ja 
See Appendix E, 
Table E-13 
See Appendix E, 
Table E-13 
GS970608314224.007 [DIRS 158430], 
USGS 1997 [DIRS 169040] 
Drift Rockfall Model for 
Rock mass 
strength in the 
Heated Drift 
Nonlithophysal Rock 
(Section 6.3.1.6.4; 
Appendix E, Section 
E4.2) 
Ultimate differential strength 
(MPa) (also referred to as 
compressive strength, intact 
rock triaxial compressive 
strength, or intact rock 
uniaxial compressive 
strength) 
See Appendix E, 
Table E-14 
See Appendix E, 
Table E-14 MO0311RCKPRPCS.003 [DIRS 166073] 
material constant for intact 
rock, mi 
33.87  BSC 2003 [DIRS 166660], Table 8-39 
Block strength 
for 
nonlithophysal 
rock 
Uniaxial compressive 
strength (sax)u (MPa) (also 
referred to as intact rock 
uniaxial compressive strength 
or ultimate differential 
strength) 
See Appendix E, 
Table E-17 
See Appendix E, 
Table E-17 MO0311RCKPRPCS.003 [DIRS 166073] 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.6.4; 
Appendix E, Section 
E4.4) 
ANL-EBS-MD-000027 REV 03 4-6 September 2004 

Drift Degradation Analysis 
Table 4-1. Input Data and Parameters for the Drift Degradation Analysis (Continued) 
Parameter Value Range Source/Supporting Information a Application 
Thermal conductivity (W/mC) See Appendix E, 
Table E-18 
See Appendix E, 
Table E-18 
SN0303T0503102.008 [DIRS 162401], 
BSC 2004 [DIRS 170033]; 
SN0404T0503102.011 [DIRS 169129], 
BSC 2004 [DIRS 169854] Thermal-Mechanical 
Calculation 
(Section 6.2; 
Appendix C; 
Appendix E, 
Section E5) 
Rock specific heat (J/kgC) See Appendix E, 
Table E-19 
See Appendix E, 
Table E-19 SN0307T0510902.003 [DIRS 164196] 
Thermal expansion coefficient (/C) See Appendix E, 
Table E-20 
See Appendix E, 
Table E-20 SNL01B05059301.006 [DIRS 129168] 
Initial heat load (kW/m) 1.45 kW/m  BSC 2004 [DIRS 167369] 
Thermal-Mechanical 
Rock density 
Rock density for thermalmechanical 
units 
See Appendix E, 
Table E-1 
See Appendix E, 
Table E-1 
SN0303T0503102.008 [DIRS 162401], 
BSC 2004 [DIRS 170033]; 
SN0404T0503102.011 [DIRS 169129], 
BSC 2004 [DIRS 169854] 
Calculation 
(Section 6.2; 
Appendix C; 
Appendix E, 
Section E1) 
Rock density at the repository 
horizon 
See Appendix E, 
Table E-2 
See Appendix E, 
Table E-2 SNL02030193001.027 [DIRS 108410] 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.1; 
Appendix E, 
Section E1) 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4) 
Thermal-Mechanical 
In situ stress 
Intermediate principal stress, 
s2 (MPa) (horizontal) 
2.9 MPa 
N15E (Direction) 
 0.4 MPa 
 14
 
SNF37100195002.001 [DIRS 131356] 
Calculation 
(Appendix C) 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.1) 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4) 
Minor principal stress, s3 
(MPa) (horizontal) 
1.7 MPa 
N75W (Direction) 
 0.1 MPa 
 14
 
ANL-EBS-MD-000027 REV 03 4-7 September 2004 

Drift Degradation Analysis 
Table 4-1. Input Data and Parameters for the Drift Degradation Analysis (Continued) 
Parameter Value Range Source/Supporting Information a Application 
Thermal-Mechanical 
Regional geology - stratigraphic thickness 
See Appendix E, 
Tables E-1, E-18, 
E-19 
 MO0012MWDGFM02.002 
[DIRS 153777] 
Calculation 
(Appendix C; 
Appendix E, 
Sections E1 and E5) 
Repository layout 
See Appendix C, 
Sections C2 and 
C3 
See Appendix C, 
Sections C2 and 
C3 
BSC 2004 [DIRS 164519], 
BSC 2003 [DIRS 165572] 
Thermal-Mechanical 
Calculation 
(Appendix C) 
Emplacement drift orientation 72 drift azimuth  
BSC 2004 [DIRS 164519], 
BSC 2003 [DIRS 165572] 
Rockfall Model for 
Emplacement drift diameter (m) 5.5 m  BSC 2004 [DIRS 168489] Nonlithophysal Rock 
(Section 6.3.1.1) 
Rockfall Model for 
Drip shield, waste package, and invert 
See Appendix Y, 
Table Y-1; 
Appendix A, 
calculation file,  
BSC 2004 [DIRS 169220], 
BSC 2004 [DIRS 168489], 
Lithophysal Rock 
(Section 6.4.2.2, 
Appendix Y) 
geometry impact velocity 
bounding cal for 
preclosure rockfall 
rev1.mcd 
BSC 2004 [DIRS 169472], 
BSC 2004 [DIRS 169503] 
510-4 per year MO0407TMHIS104.003 [DIRS 170599] 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.2, 
Appendix X) 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4.2.2) 
110-4 per year See Section See Section MO0306SDSAVDTH.000 [DIRS 164033] 
Seismic 110-5 per year 6.3.1.2.1 6.3.1.2.1 MO0402AVDTM105.001 [DIRS 168890] 
ground motion 
110-6 per year c 
(Tables 6-5, 6-6, 
6-7; Figure 6-36), 
Appendix X 
(Tables 6-5, 6-6, 
6-7; Figure 6-36), 
Appendix X 
MO0403AVDSC106.001 [DIRS 168891] 
MO0301TMHIS106.001 [DIRS 161868]; 
110-7 per year MO0403AVTMH107.003 [DIRS 168892] 
ANL-EBS-MD-000027 REV 03 4-8 September 2004 

Table 4-1. Input Data and Parameters for the Drift Degradation Analysis (Continued) 
Parameter Value Range Source/Supporting Information a Application 
Sampling of Stochastic Input Parameters 
See Section 
6.3.1.2.2 
(Table 6-8) and 
Section 6.4.2.2 
(Table 6-44) 
See Section 
6.3.1.2.2 
(Table 6-8) and 
Section 6.4.2.2 
(Table 6-44) 
MO0301SPASIP27.004 [DIRS 161869] 
Rockfall Model for 
Nonlithophysal Rock 
(Section 6.3.1.2) 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4.2.2) 
Lithophysal abundance See Appendix O See Appendix O 
GS021008314224.002 [DIRS 161910] 
GS040608314224.001 [DIRS 171367] 
Rockfall Model for 
Lithophysal Rock 
(Section 6.4) 
a 
The italicized supplemental references listed along with the source DTNs provide either summary or supporting information that is linked to the source DTN, 
b 
and provide direct input for this analysis and model report. 
Long-term strength data are provided by outside sources and qualified for use in this report (Appendix S, Section S2.1.2) in accordance with the requirements 
of AP-SIII.10Q, Section 5.2. 
Note that two sets of 110-6 time histories are provided. The difference in these sets is described in DTN: MO0403AVDSC106.001 [DIRS 168891], file 10-6 
TH memo.doc. The original set (i.e., DTN: MO0301TMHIS106.001 [DIRS 161868]) is used in Section 6.4.2.2. Since this ground motion results in complete 
drift collapse for lithophysal rock, it was not necessary to repeat the analyses using the revised set (i.e., DTN: MO0403AVDSC106.001 [DIRS 168891]. 
Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 4-9 September 2004 

Drift Degradation Analysis 
DRKBA Fracture Geometry InputsStudies by the U.S. Geological Survey/U.S. Bureau of 
Reclamation have generated data on small-scale fractures with trace lengths less than 1 m 
(DTN: GS040108314224.001 [DIRS 169591]). These data were collected at six locations in the 
Tptpmn (2 locations), Tptpll (3 locations), and Tptpln (1 location). These data are used in this 
analysis to provide an assessment of the impact of the small trace length fracture data on rockfall 
development (Section 6.3.3). 
3DEC Fracture Geometry InputsThe 3DEC software uses source fracture geometry inputs 
provided in Table 4-1. These inputs are then developed to produce a 100-m x 100-m x 100-m 
rock mass volume that contains a three-dimensional generation of fracture data derived from the 
field mapping data using a Poisson process (Section 6.1.6). Fractures are generated within this 
volume as circular disks with their size, dip, and dip direction determined based on field data. 
The location of each fracture plane within the three dimensional space is also provided. Details 
for sampling within this rock mass volume to select fracture patterns for 3DEC modeling are 
provided in Section 6.3.1.2.2. 
4.1.2 Fracture Mechanical Properties Data 
Fracture strength is characterized by cohesion, friction angle, dilation, and stiffness. Joint 
cohesion (Cj) and friction angle (fj) values were developed in Appendix E based on laboratory 
shear strength test data from core specimens (see Appendix E, Table E-3). Mean value and 
standard deviation are required as the inputs for the DRKBA and 3DEC structural analyses. The 
calculation of mean values in Appendix E (Section E2) is consistent with Yucca Mountain Site 
Geotechnical Report (CRWMS M&O 1997 [DIRS 103564], p. 5-143). Joint stiffness values (Kn 
and Ks) are required as inputs for 3DEC, and are documented in Appendix E (Table E-4) based 
on laboratory shear strength test data from core specimens. Joint dilation data are provided 
based on the laboratory shear strength test data from core specimens (see Appendix E, 
Table E-3). Note that for 3DEC analyses, dilation was conservatively selected to be zero, 
resulting in a higher estimation of rockfall (see Section 6.3.1.1). 
4.1.3 Intact Rock Physical and Mechanical Properties Data 
The mean rock density value used in rockfall modeling (Sections 6.3 and 6.4) was calculated 
based on data from laboratory tests performed on rock cores from the North Ramp geotechnical 
and the systematic drilling boreholes (see Appendix E, Table E-2). The saturated bulk density 
(.) of 2.41 g/cc (see Appendix E, Table E-2) for the Tptpln unit was used in each of the rockfall 
models in this analysis. This value is in agreement with the mean Tptpln saturated bulk density 
reported in the Yucca Mountain Site Geotechnical Report (CRWMS M&O 1997 [DIRS 103564], 
p. 5-26). That document also indicates that the mean density for the Tptpln unit is the highest 
mean value compared to other units of the repository horizon (i.e., the Tptpul, Tptpmn, Tptpll, 
and Tptpln) (CRWMS M&O 1997 [DIRS 103564], pp. 5-25 and 5-26). The use of the mean 
density for the Tptpln unit to represent the density of the rock units in this analysis results in a 
larger mass of rock blocks, and is, therefore, conservative. The thermal-mechanical calculation 
(Section 6.2) uses density inputs grouped according to thermal-mechanical units. The 
calculation of mean density values for each thermal-mechanical unit is also documented in 
Appendix E (Table E-1). 
ANL-EBS-MD-000027 REV 03 4-10 September 2004 

Drift Degradation Analysis 
Mean elastic rock properties from the TSw2 thermal-mechanical unit, including a Youngs 
modulus (E) of 33.6 GPa and a Poissons ratio (.) of 0.20, were used in this analysis for 
modeling nonlithophysal rock as calculated in Appendix E (Table E-6). Elastic rock properties 
were determined from laboratory tests performed on rock cores from the North Ramp 
geotechnical and the systematic drilling boreholes. The calculation of mean values in Appendix 
E is consistent with Yucca Mountain Site Geotechnical Report (CRWMS M&O 1997 
[DIRS 103564], pp. 5-88 and 5-96). Intact bulk modulus (K) and intact shear modulus (G) for 
nonlithophysal rock were calculated based on the mean values of E and . using Equations E-2 
and E-3, respectively, as documented in Appendix E (Section E3). 
Tensile strength data for the TSw2 thermal-mechanical unit were obtained from indirect tensile 
strength tests performed by the Brazilian Test method using core specimens (Appendix E, 
Table E-7). The mean tensile strength from this data is 8.9 MPa. 
Triaxial strength data (see Appendix E, Table E-8) are used to calculate intact cohesion and 
friction angle of the nonlithophysal rocks. The calculation of cohesion and friction angle is 
documented in Appendix E, resulting in a cohesion of 36 MPa and a friction angle of 50 degrees. 
4.1.4 Rock Mass Properties Data 
4.1.4.1 Strength of Lithophysal Rock 
Mechanical properties for lithophysal rock were determined based on available laboratory testing 
data on large rock cores from drilling in the ECRB Cross-Drift and Busted Butte (Appendix E, 
Section E4.1.3 and Table E-9). Values of cohesion (C), bulk modulus (K), and shear modulus 
(G) for lithophysal rock were calculated based on values of unconfined compressive strength 
(sc), Youngs modulus (E), and Poissons ratio (.) as documented in Appendix E (Section E4.1). 
4.1.4.2 Rock Mass Elastic Properties for Thermal-Mechanical Units 
The rock mass properties data used in this report include modulus of deformation and Poissons 
ratio for each of the thermal-mechanical units (see Appendix E, Table E-16). The rock mass 
properties data were calculated based on the intact rock data from laboratory testing and the 
Q system input parameters from tunnel mapping in the ESF identified in Table 4-1. Note that 
Q system parameters Jn, Jr, and Ja are provided by the supplemental sources cited in Table 4-1 
(see italicized references in Table 4-1). Since the verified source DTNs providing the Q values 
have been calculated using the parameters Jn, Jr, and Ja, the supplemental sources providing the 
Q system data are also qualified and verified. 
The rock mass modulus of deformation data is provided for five rock mass categories 
representing the range of rock mass conditions encountered in ESF tunnels. The five rock mass 
categories correspond to 5 percent, 20 percent, 40 percent, 70 percent, and 90 percent 
probabilities of occurrence, and are provided to be consistent with geotechnical design analyses 
(BSC 2004 [DIRS 170292], Section 3.1.4). Mid-range values corresponding to a 40 percent 
probability of occurrence were used in this analysis, which provides an approximate estimate of 
the mean value. This data is appropriate for its use in the thermal-mechanical calculation 
(Section 6.2), which provides an assessment of the regional stresses anticipated within the rock 
ANL-EBS-MD-000027 REV 03 4-11 September 2004 

Drift Degradation Analysis 
mass. Poissons ratio for the rock mass was determined to be equal to the Poissons ratio from 
intact laboratory tests based on recent field testing (see Appendix E, Table E-16). 
4.1.4.3 Rock Mass Properties for the Heated Drift in the ESF 
Rock mass properties for the Heated Drift are calculated using the Hoek-Brown failure criterion 
(Hoek et al. 2002 [DIRS 162204]) as documented in Appendix E (Section E4.2). The inputs 
needed include rock mass classification data using the Q system as provided in Appendix E 
(Table E-13). Additionally, intact unconfined compressive strength (sci) is required input for the 
Hoek-Brown method (Table E-14). The calculated rock mass properties using these data are 
provided in Appendix E (Table E-15). 
4.1.4.4 Block Strength of Nonlithophysal Rock 
The strength of large-scale intact rock block material (i.e., between joints) for nonlithophysal 
rock is calculated based on available size-effect laboratory compression test data from Price 
(1986 [DIRS 106589]). The size-effect data are presented in Appendix E (Table E-17). The 
approach for extrapolating this data to the block scale is documented in Appendix E 
(Section E4.4). 
4.1.5 Seismic Ground Motion Data 
Seismic ground motion time history data were provided for the following hazard levels: 
510-4 per year, 110-4 per year, 110-6 per year, and 110-7 per year. DTNs for each of these 
ground motion levels are listed in Table 4-1. The ground motion data for the postclosure ground 
motion levels (i.e., 110-6 and 110-7) each include 15 sets (three components) of time histories 
at the repository horizon. The sets were developed by scaling recorded motions such that their 
integrated peak particle velocities match expected point repository horizon particle velocities for 
the hazard level under consideration. Additionally, a desirable feature of the 15 sets is a 
magnitude distribution reflective of the horizontal component peak particle velocity 
deaggregation. This ensures a reasonable and defensible distribution of spectral shapes and time 
history durations. Conditioning on expected peak particle velocity alone was considered 
desirable as damage to underground structures is most strongly correlated with this point 
measurement, recognizing that underground (at-depth) spectral shapes are generally not identical 
to surficial or outcrop spectral shapes due to the effects of down going wave fields (BSC 2004 
[DIRS 170027], Section 6.3.2). 
The ground motion data for preclosure annual exceedance probabilities (i.e., 510-4 and 110-4) 
consist of a single three-component set of time histories. These sets were developed such that 
the response spectra of the time histories match the design response spectra for the hazard level 
at the repository horizon. 
ANL-EBS-MD-000027 REV 03 4-12 September 2004 

Drift Degradation Analysis 
4.1.6 Rock Thermal Properties Data 
A regional thermal-mechanical calculation has been developed as part of this drift degradation 
analysis (Section 6.2), and uses the following thermal properties data (see Table 4-1 and 
Appendix E, Section E5 for parameter values and source DTNs): 
 Thermal conductivity (W/mK) 
 Rock specific heat (J/kgK) 
 Thermal expansion (/C) 
 Heat decay curve. 
4.1.7 Repository Layout Information 
Repository layout information (Table 4-1), including emplacement drift diameter and azimuth, is 
provided by repository design and performance assessment information exchange drawings 
(BSC 2004 [DIRS 164519]; BSC 2004 [DIRS 168489]) and Underground Layout Configuration 
(BSC 2003 [DIRS 165572], Sections 5.1.4 and 8.7). 
4.1.8 Matrix and Fracture Hydrologic Properties Data 
A temperature-history calculation has been developed as part of this analysis (Section 6.2) based 
on a two-dimensional drift scale thermohydrologic model from Multiscale Thermohydrologic 
Model (BSC 2004 [DIRS 169565]) and DTN: LL030808623122.036 [DIRS 165790]. Matrix 
and fracture hydrologic properties data used in the calculation are provided in 
DTN: LL030808623122.036 [DIRS 165790] as a part of the NUFT input files 
(i.e., file dkm-afc-1Dds-mc-mi-04). Summaries of the matrix and fracture hydrologic 
properties data are also available in DTN: LB0205REVUZPRP.001 [DIRS 159525] and 
DTN: LB0208UZDSCPMI.002 [DIRS 161243]. 
4.1.9 In Situ Stress Data 
In situ stress data were determined by hydraulic fracturing in a borehole located in the Tptpmn 
unit in the Thermal Test Facility in the ESF (DTN: SNF37100195002.001 [DIRS 131356]; 
CRWMS M&O 1997 [DIRS 147458], pp. 15, 19, and 20). The in situ stress measurements 
included a series of five hydraulic fracturing tests, resulting in an estimate of the state of stress in 
the ESF as shown in Table 4-1. The vertical stress shown in Table 4-1 was calculated based on 
the depth of cover in the Thermal Test Facility at the test borehole location. The in situ stress for 
each emplacement drift will vary depending on the cover depth on top of the drift. The 
approximated values assigned for the in situ stress for the rockfall modeling activities in Sections 
6.3 and 6.4 are adequate and insensitive to the results judging the magnitude of the induced 
seismic and thermal stress. 
4.2 CRITERIA 
This model report addresses acceptance criteria from Sections 2.2.1.3.1.3 and 2.2.1.3.2.3 of 
Yucca Mountain Review Plan, Final Report (NRC 2003 [DIRS 163274]) regarding the 
degradation of engineered barriers and the mechanical disruption of engineered barriers. 
ANL-EBS-MD-000027 REV 03 4-13 September 2004 

Drift Degradation Analysis 
Acceptance criteria from the Yucca Mountain Review Plan include the following: 
 AC1: System description and model integration are adequate 
 AC2: Data are sufficient for model justification 
 AC3: Data uncertainty is characterized and propagated through the model abstraction 
 AC4: Model uncertainty is characterized and propagated through the model abstraction 
 AC5: Model abstraction output is supported by objective comparison. 
The Yucca Mountain Review Plan criteria are based on meeting the requirements of 
10 CFR 63.114(a)(c) and (e)(g), relating to the degradation and mechanical disruption of 
engineered barriers model abstractions. A mapping between the Acceptance Criteria and 
subcriteria and where they are addressed in this document is provided in Section 8.2 (see 
Table 8-1). 
Similarly, the Project Requirements Document (Canori and Leitner 2003 [DIRS 166275], 
Table 2-3) expresses these requirements as follows: 
 PRD-002/T-014 Performance Objectives for the Geologic Repository After Permanent 
Closure (traceable to 10 CFR 63.113) 
 PRD-002/T-015 Requirements for Performance Assessment (traceable to 10 
CFR 63.114) 
This report was therefore prepared to comply with subparts of the NRC high-level waste rule, 
10 CFR Part 63. Relevant requirements for performance assessment from Section 114 of that 
document are: 
Any performance assessment used to demonstrate compliance with Sec. 63.113 
must: (a) Include data related to the geology, hydrology, and geochemistry ... used to 
define parameters and conceptual models used in the assessment. (b) Account for 
uncertainties and variabilities in parameter values and provide for the technical basis 
for parameter ranges, probability distributions, or bounding values used in the 
performance assessment. ... (g) Provide the technical basis for models used in the 
performance assessment such as comparisons made with outputs of detailed 
process-level models and/or empirical observations (e.g., laboratory testing, field 
investigations, and natural analogs). 
4.3 CODES, STANDARDS, AND REGULATIONS 
There are no codes and standards applicable to this drift degradation analysis. The regulation 
that is applicable to the development of this document is 10 CFR Part 63 [DIRS 156605], 
specifically 10 CFR 63.113 and 10 CFR 63.114. 
ANL-EBS-MD-000027 REV 03 4-14 September 2004 

Drift Degradation Analysis 
5. ASSUMPTIONS 
The following assumptions have been used in this drift degradation analysis. 
5.1 THERMAL-MECHANICAL CALCULATION 
5.1.1 Simultaneous Emplacement 
Assumption: The thermal-mechanical calculation in this report assumes that generation of heat 
from the waste packages occurs simultaneously throughout the repository. The entire repository 
begins heating at the same time because sequential emplacement of waste packages has not been 
considered. 
Basis: This assumption is necessary because design information is available only for the 
emplacement drift layout (BSC 2004 [DIRS 164519]), and not for the emplacement schedule. 
Confirmation Status: This assumption does not require further confirmation, because results 
from the thermal-mechanical calculation should be the most conservative based on this 
assumption (i.e., the assumption produces increased heat and greater stresses in the rock mass). 
Sequential emplacement may cause an additional internal stress between the emplacement drifts 
and the remaining drifts. This internal stress will be insignificant during the preclosure period, 
because the majority of the heat load will be removed from the emplacement drifts due to 
ventilation (Section 5.1.2). The effects of the internal stress are expected to be minor during the 
postclosure period, because the waste packages will cool down significantly during the 
preclosure period, and the repository temperature is expected to be homogenized due to heat 
conduction between the drifts during the preclosure period. A range of temperatures has been 
considered in the rockfall analyses presented in this report (Sections 6.3.1.3 and 6.4.2.3), and the 
rockfall results are relatively insensitive to the temperature changes evaluated. 
Use in the Analysis/Model: This assumption is used in the thermal-mechanical calculation of 
regional (repository-scale) and local (drift scale) temperature and thermal stress (Sections 6.2, 
6.3.1, and 6.4.2; Appendix C). 
5.1.2 Ventilation Heat Removal Ratio 
Assumption: During the ventilated preclosure period, 90 percent of the decay heat output is 
removed from the emplacement drift system. 
Basis: The basis of this assumption is provided from the ventilation model supporting a license 
application (BSC 2004 [DIRS 169862]), which has integrated heat removal ratios (averaged 
spatially and temporally) of 88 percent and 90 percent for the 50-year preclosure ventilation 
period and 600-m long drifts (MO0306MWDASLCV.001 [DIRS 165695] and 
MO0306MWDALAFV.000 [DIRS 163961], respectively). 
Confirmation Status: No further confirmation is needed for this assumption because sensitivity 
calculation regarding the heat removal ratio was conducted covering the heat removal ratio down 
to 70 percent (Section 6.2). The calculation showed that the results of rockfall analyses are not 
sensitive to heat removal ratio over this range. Heat removal ratio that is a function of time and 
ANL-EBS-MD-000027 REV 03 5-1 September 2004 

Drift Degradation Analysis 
distance from the drift inlet was considered in an impact analyses (Appendix Q). The impact 
analyses also showed that the results of rockfall analyses are not sensitive to the heat removal 
ratio. 
Use in the Analysis/Model: This assumption is used in the preclosure thermal-mechanical 
calculations except the ventilation sensitivity calculation (Sections 6.2, 6.3.1, and 6.4.2; 
Appendix C). Because of this assumption it is accurate to model the preclosure period by simply 
reducing the decay heat output to 10 percent of its non-ventilated rate. 
5.1.3 Thermal Expansion 
Assumption: Thermal expansion values used in the underlying layers (CHn1 and CHn2) under 
the repository units (TSw2) are assumed to be equal to those for the repository layers. 
Basis: This assumption is necessary because the test data from core samples are limited. 
Confirmation Status: This assumption does not require further confirmation because temperature 
increase in the underlying layers is insignificant and thermally induced stresses are negligible. 
Use in the Analysis/Model: This assumption is used in the thermal-mechanical calculations 
throughout the report (Sections 6.3.1 and 6.4.2; Appendix C). 
5.2 ROCKFALL MODELING 
5.2.1 Joint Position Parameter in DRKBA 
Assumption: The positioning parameter required as joint parameter input is assumed to be the 
offset measured from the center of the trace length to the scan line of the detailed line survey. 
Basis: This is the best available way to represent the positioning parameter because the 
determination of the true positioning parameter requires the three dimensional information of the 
joint plane that is not available. 
Confirmation Status: This assumption does not require further confirmation. This approach is 
considered conservative because the offset measured from the one-dimensional scan line is 
smaller than the true offset in three-dimensional space (the probability of forming a key block is 
higher with a smaller offset value). The DRKBA rockfall results are used for confirmation only. 
This assumption does not impact the rockfall output documented in this report. 
Use in the Analysis/Model: This assumption is used in Section 6.3.3 and Appendix D. 
5.2.2 Block Size Distribution for Potential Rockfall in Lithophysal Units 
Assumption: Block size distribution is assumed as a function of inter-lithophysal fracture density 
and lithophysae spacing. 
Basis: This assumption is needed because the size of rock particles that are created from the 
lithophysal rocks is estimated from geologic and empirical evidence. 
ANL-EBS-MD-000027 REV 03 5-2 September 2004 

Drift Degradation Analysis 
Confirmation Status: This assumption does not require further confirmation. The relatively 
abundant uniformly distributed lithophysae combined with fracturing fabric provide natural 
breaking surfaces. Observation in the ECRB Cross-Drift for block sizes on the order of a few 
inches in diameter supports this assumption (Appendix O). 
Use in the Analysis/Model: This assumption is used in Section 6.4. 
ANL-EBS-MD-000027 REV 03 5-3 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 5-4 September 2004 

Drift Degradation Analysis 
6. MODEL DISCUSSION AND ANALYSIS RESULTS 
This section documents the models and analyses conducted to predict the postclosure drift 
degradation resulting from thermally induced stresses, seismically induced rockfall, and possible 
time-dependent static fatigue mechanisms. 
The potential exists for rockfall to occur as a result of shaking induced by earthquakes. The 
models and analyses described in this section quantify possible seismically induced rockfall over 
the 10,000-year regulatory postclosure period. Geologic mapping is used to define a synthetic 
or representative rock mass that is sampled randomly to create possible rock masses in which the 
tunnel is simulated. Numerical models (two- or three-dimensional, depending on the lithology in 
question), with input geometry and properties based on the geologic variability, are used to make 
rockfall estimates for ground motion levels whose amplitude is based on the probability of 
occurrence in terms of annual exceedance frequency. For each annual exceedance frequency, a 
number of probabilistically based, site-specific ground motions have been developed and used to 
provide the transient boundary conditions to the models. The resulting rockfall, in terms of the 
tonnage of the maximum size rock particle, total tonnage for a given simulated length of tunnel, 
and the velocity of rock particles, has been determined. 
The rock mass surrounding the excavations may undergo damage from thermally induced 
stresses or time-dependent damage associated with static fatigue resulting from stress corrosion 
mechanisms. This damaged material may result in a slow unraveling (Tptpll) or block fallout 
(Tptpmn) mode of failure with some extent of drift filling. The effect of thermal stress on rock 
failure extent has been examined using the numerical techniques discussed in the subsequent 
sections. 
Time-dependent degradation (i.e., rockfall from a tunnel or other unsupported excavation over 
long time periods) is not currently well understood, particularly in hard, strong rocks. It is 
expected that time-related rockfall will be more prominent in heavily fractured rocks such as the 
Tptpll, and will be related to the ratio of induced stress to rock mass strength. The analyses 
presented in this section provide a reasonable estimate of the propensity for yield and rockfall as 
a function of the induced stress levels and time. 
Ground support is not considered in the rockfall models presented in this report. The rock blocks 
predicted in this model report are, therefore, blocks that fail in an unsupported opening. This 
modeling approach leads to a conservative prediction of blocks for the preclosure period 
(i.e., more blocks will be predicted to fail in the model than would otherwise be supported and 
remain stable with ground support). During the postclosure period, ground support will degrade 
and eventually fail. Not including ground support in the rockfall models is realistic for the 
postclosure period. 
All direct inputs used to develop the rockfall models are listed in Table 4-1. 
Corroborating/ supporting data, models, and product output that are used to develop the rockfall 
models include the following: 
 Rock mass characteristics of the repository horizon (Section 6.1) 
- Albin et al. 1997 [DIRS 101367] 
ANL-EBS-MD-000027 REV 03 6-1 September 2004 

Drift Degradation Analysis 
- Barton et al. 1974 [DIRS 101541] 
- Bieniawski 1989 [DIRS 101715] 
- Broxton et al. 1993 [DIRS 107386] 
- Buesch 2003 [DIRS 162271] 
- Buesch 2003 [DIRS 163729] 
- Buesch and Spengler 1998 [DIRS 101433] 
- Buesch et al. 1996 [DIRS 100106] 
- Byers et al. 1976 [DIRS 104639] 
- Christiansen et al. 1977 [DIRS 157236] 
- CRWMS M&O 1999 [DIRS 108441] 
- Day et al. 1998 [DIRS 100027] 
- Dershowitz and Herda (1992 [DIRS 104893] 
- Flint 1998 [DIRS 100033] 
- Gibson et al. 1990 [DIRS 157245] 
- Goodman and Shi 1985 [DIRS 150094] 
- Hoek 2000 [DIRS 160705] 
- Lipman et al. 1966 [DIRS 100773] 
- Mongano et al. 1999 [DIRS 149850] 
- Munsell Color Company 1994 [DIRS 106399] 
- Ortiz et al. 1985 [DIRS 101280] 
- Peterman and Cloke 2002 [DIRS 162576] 
- Sawyer et al. 1994 [DIRS 100075] 
- Schuraytz et al. 1989 [DIRS 107248] 
- Scott 1990 [DIRS 106751] 
- Scott and Bonk 1984 [DIRS 104181] 
- Terzaghi 1966 [DIRS 105805] 
 Thermal-mechanical calculation (Section 6.2) 
- BSC 2003 [DIRS 164670] 
- BSC 2004 [DIRS 169565] 
- Itasca Consulting Group 2002 [DIRS 160331] 
 Rockfall in the nonlithophysal units (Section 6.3) 
- Albin et al. 1997 [DIRS 101367] 
- BSC 2003 [DIRS 166183] 
- BSC 2003 DIRS [166660] 
- Buesch and Lung 2003 [DIRS 170297] 
- Carlos et al. 1995 [DIRS 101326] 
- CRWMS M&O 1998 [DIRS 102679] 
- Duan 2003 [DIRS 163586] 
- Goodman 1980 [DIRS 101966] 
- Itasca Consulting Group 2002 [DIRS 160331] 
ANL-EBS-MD-000027 REV 03 6-2 September 2004 

Drift Degradation Analysis 
 Rockfall in the lithophysal units (Section 6.4) 
- Bauer et al. 1991 [DIRS 161775] 
- Bieniawski 1989 [DIRS 101715] 
- Brace et al. 1966 [DIRS 101990] 
- Brekke et al. 1999 [DIRS 119404] 
- Brown 2003 [DIRS 169527] 
- BSC 2003 [DIRS 166660] 
- BSC 2004 [DIRS 169131] 
- BSC 2004 [DIRS 169183] 
- BSC 2004 [DIRS 168993] 
- BSC 2004 [DIRS 169999] 
- BSC 2004 [DIRS 169565] 
- Byrne et al. 1990 [DIRS 168921] 
- Charles 1959 [DIRS 170308] 
- Duncan et al. 1980 [DIRS 161776] 
- Fruchtbaum 1988 [DIRS 161774] 
- Goodman 1980 [DIRS 101966] 
- Hoek 2000 [DIRS 160705] 
- Hoek and Brown 1982 [DIRS 120981] 
- Itasca Consulting Group 2002 [DIRS 160331] 
- Lefebvre et al. 1976 [DIRS 168919] 
- Martin 1972 [DIRS 169721] 
- Martin and Durham 1975 [DIRS 170301] 
- MRD 1995 [DIRS 169719] 
- Newmark 1965 [DIRS 169515] 
- Potyondy and Cundall 2001 [DIRS 156895] 
- Scholz 1972 [DIRS 169724] 
- SN0406L0212303.002 [DIRS 170289] 
- Terzaghi 1943 [DIRS 162180] 
- Wiederhorn 1968 [DIRS 170309] 
 Uncertainties and Limitations (Section 6.5) 
- Potyondy 2003 [DIRS 165550] 
 Drift Degradation FEPs (Section 6.6) 
- Freeze et al. 2001 [DIRS 154365] 
- MO0407SEPFEPLA.000 [DIRS 170760] 
 Documentation of Alternative Conceptual Models (Section 6.7) 
- Chen 1987 [DIRS 101800] 
- CRWMS M&O 1998 [DIRS 102723] 
- Hudson and Priest 1979 DIRS 104915] 
ANL-EBS-MD-000027 REV 03 6-3 September 2004 

Drift Degradation Analysis 
 Resolution of key technical issues (Section 6.8) 
- BSC 2003 [DIRS 166660] 
- NRC 2002 [DIRS 159538] 
- Reamer and Williams 2001 [DIRS 154348] 
6.1 ROCK MASS CHARACTERISTICS OF REPOSITORY HOST HORIZON 
The purpose of this section is to provide a background discussion of rock mass characteristics 
that are important in understanding fundamental rock mass behavior. Specific rock mass 
parameters that are input to the rockfall models developed in this report are identified in 
Sections 6.3 and 6.4. Two systems of stratigraphic nomenclature are used in this 
report: thermal-mechanical (Ortiz et al. 1985 [DIRS 101280]) and lithostratigraphic (Buesch et 
al. 1996 [DIRS 100106]). Correlation between these two systems is provided in Figure 6-1. 
6.1.1 Regional Geology 
Yucca Mountain lies in southern Nevada, in the Great Basin, which is part of the Basin and 
Range structural/physiographic province. In the Yucca Mountain area, pre-Tertiary rocks 
(consisting of a thick sequence of Proterozoic and Paleozoic sedimentary rocks) underlie 
approximately 1,000 to 3,000 m of Miocene volcanic rocks (Gibson et al. 1990 [DIRS 157245]). 
The Miocene volcanic sequence exposed at Yucca Mountain includes units of the Paintbrush and 
Timber Mountain Groups (Sawyer et al. 1994 [DIRS 100075]) and the entire section dips 5 to 10 
degrees east (Day et al. 1998 [DIRS 100027]). The Paintbrush Group consists of pyroclastic 
rocks and lavas that originate from the Claim Canyon caldera (approximately 6 km north of the 
study area) and are from 12.7 to 12.8 million years old (Byers et al. 1976 [DIRS 104639]; 
Sawyer et al. 1994 [DIRS 100075]). The Paintbrush Group includes a sequence of four 
formations: the Tiva Canyon, Yucca Mountain, Pah Canyon, and Topopah Spring Tuffs, each of 
which consist primarily of large-volume, pyroclastic-flow deposits with minor amounts of 
pyroclastic-fall deposits (Byers et al. 1976 [DIRS 104639]; Christiansen et al. 1977 
[DIRS 157236]; Broxton et al. 1993 [DIRS 107386]; Buesch et al. 1996 [DIRS 100106]) 
(Figure 6-1). At Yucca Mountain, two of these formations, the Topopah Spring and Tiva 
Canyon Tuffs, are voluminous, mostly densely welded, compositionally zoned, outflow sheet, 
pyroclastic-flow deposits (also referred to as ignimbrites) that grade upward from rhyolite 
composition to quartz latite composition (Lipman et al. 1966 [DIRS 100773]; Byers et al. 1976 
[DIRS 104639]; Schuraytz et al. 1989 [DIRS 107248]). The formations of the Paintbrush Group 
are interbedded with bedded tuffs, which consist of thinner pyroclastic-flow and pyroclastic-fall 
deposits, and, locally, a few lava flows (Byers et al. 1976 [DIRS 104639]; Christiansen et al. 
1977 [DIRS 157236]; Broxton et al. 1993 [DIRS 107386]; Buesch et al. 1996 [DIRS 100106]; 
Day et al. 1998 [DIRS 100027]). The 11.45 to 11.6 million year old rocks of the Timber 
Mountain Group were erupted from Timber Mountain caldera complex and consist of the 
Ammonia Tanks and Rainer Mesa Tuffs (Sawyer et al. 1994 [DIRS 100075]) and interbedded 
tuffaceous rocks and lava flows. 
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Drift Degradation Analysis 
Figure 6-1. Simplified Lithostratigraphic Column of Paintbrush Group and the Rock Units that Form the 
Repository Host Horizon 
The central block of Yucca Mountain is bounded by the Yucca Wash to the north, by the 
Solitario Canyon fault to the west, and the Bow Ridge fault to the east (Figure 6-2). 
Alluvium-filled structural valleys, consisting mostly of alluvial fan deposits (fluvial and colluvial 
sediments) and some thin eolian deposits, lie adjacent to the Bow Ridge and Solitario Canyon 
faults on the east and west sides, respectively. The Yucca Mountain area is cut by steeply 
dipping, northsouth-striking normal faults, which separate the Tertiary volcanic rocks into 
blocks one to four km wide (Scott 1990 [DIRS 106751]; Day et al. 1998 [DIRS 100027]). The 
Solitario Canyon and Ghost Dance faults dip steeply toward the west, and displacement, amount 
of brecciation, and number of associated splays vary considerably along their trace (Scott and 
Bonk 1984 [DIRS 104181]; Day et al. 1998 [DIRS 100027]). The Solitario Canyon fault has 
normal down-to-the-west displacement of about 260 m in the vicinity of the repository block 
(Mongano et al. 1999 [DIRS 149850], p. 60). The Ghost Dance fault is in the central part the 
repository block and is a generally north-striking normal fault zone, with down to the west 
displacement. The Sundance fault is located in the north-central portion of the repository block. 
It is a northwest-striking, east-dipping normal fault with a maximum cumulative 
down-to-the-northeast displacement of 6 to 11 m (Day et al. 1998 [DIRS 100027]). Numerous 
smaller faults and fault zones are present throughout the repository block, generally 
north-trending with offsets less than 5 m (Mongano et al. 1999 [DIRS 149850]). 
ANL-EBS-MD-000027 REV 03 6-5 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-6 September 2004 
Drill HoleWash FaultPagany Wash FaultSever Wash Fault755,000760,000765,000770,000775,000555,000560,000565,000570,000NBow Ridge FaultSolitario Canyon FaultGhost DanceFaultSundance 
FaultDiabolus 
Ridge 
FaultSplit WashAntler 
RidgeLIve Yucca R.
ESFExplanationQuaternaryAlluvium & Colluvium 
TertiaryRainier Mesa Tuff 
Comb Peak Rhyolite 
Topopah Spring TuffCrystal - rich member 
Crystal - poor memberTiva Canyon TuffCrystal - rich member 
Crystal - poor member 
Pah Canyon, Yucca 
Mountain Tuffs - undividedBedrock Geologic Map of the 
Central Block Area, 
Yucca Mountain, Nevada 
(simplified from Day et al., 1998) 
Tiva Canyon & Topopah 
Spring Tuff (lenses in fault zone ) 
01 kmECRBcross drift 
Source: Day et al. 1998 [DIRS 100027]. 
Figure 6-2. Geology of the Central Block at Yucca Mountain and Location of the ESF, Including the 
ECRB Cross-Drift 
6.1.2 Lithostratigraphy at the Repository Horizon 
All of the rocks of the repository host horizon lie within the Topopah Spring Tuffspecifically 
within the crystal-poor memberand geochemically these rocks have a very uniform 
composition of rhyolite (Peterman and Cloke 2002 [DIRS 162576]). The repository host horizon 
includes rocks from the lower part of the upper lithophysal zone (Tptpul) of the TSw1 
thermal-mechanical unit and the TSw2 thermal-mechanical unit, including the middle 
nonlithophysal zone (Tptpmn), the lower lithophysal zone (Tptpll), and the lower nonlithophysal 
zone (Tptpln) (Figure 6-1). These lithostratigraphic units are described in this section and are 
based on Mongano et al. (1999 [DIRS 149850]) unless otherwise indicated. 
In the densely welded and crystallized rocks of the Topopah Spring Tuff, the zones and many of 
the subzones are identified on the basis of the abundance, size, and distribution (or lack thereof) 
of lithophysae, which are cavities in the rock formed during welding from the accumulation of 
the vapor phase. Lithophysae, spots (which are similar to the rims on lithophysae, but there is no 
cavity), and many fractures have similar characteristics, such as rims, borders, and possibly 
vapor-phase mineral coatings (Figure 6-3). 

Drift Degradation Analysis 
NOTE: Porosity values for the matrix-groundmass are by Flint (1998 [DIRS 100033]), and the values for rims, 
borders, and vapor-phase mineral coatings are estimates by Buesch (2003 [DIRS 162271]). The 
nomenclature for color (e.g., pale red purple is 5RP6/2), is based on soil color charts (Munsell Color 
Company 1994 [DIRS 106399]). 
Figure 6-3. Lithostratigraphic Features Related to Lithophysae and Fractures 
TptpulThe Tptpul is exposed in both the ESF main loop and ECRB Cross-Drift. In the ESF 
main loop, the upper lithophysal zone is exposed from Stations 17+97 to 27+20, 63+08 to 
64+55, 67+91 to 68+47, and 71+68 to 73+02. The ECRB Cross-Drift begins in the upper central 
portion of the zone and it exposes rocks of the middle and lower portions of the zone from 
Stations 0+00 to 10+15. The upper portion of the upper lithophysal zone is also exposed in the 
hanging wall of the eastern strand of the Solitario Canyon fault zone from Stations 25+90 to 
26+57.5. The unit is densely welded, crystallized, lithophysal, and has various amounts of 
vapor-phase corrosion and mineralization. The rock contains 1 to 5 percent crystal fragments, 
0 to 5 percent lithic fragments, 0 to 15 percent pumice fragments, 3 to 60 percent lithophysae, 
and 40 to 92 percent matrix-groundmass. The matrix-groundmass is a variable mix of pale to 
grayish red-purple (5RP5-7/1-2 to 5RP4/2), light brown (5YR6/3-4) to pale reddish brown 
(10R5/4), and pale red (5-10R6/2) crystallized material. The matrix-groundmass contains 3 to 
50 percent white to very light gray (N-9 to N6) to grayish pink (5-10R8/2-1) spots, veinlets, 
streaks, rims on fractures, stringers, and vapor-phase partings of crystallized materials. 
TptpmnThe Tptpmn is exposed in both the ESF main loop and ECRB Cross-Drift. The ESF 
main loop is excavated in the middle nonlithophysal zone from Stations 27+21 to 57+29, 58+78 
to 63+08, and from 70+58 to 71+68. The middle nonlithophysal zone contains an intensely 
fractured zone exposed in the ESF main loop from Stations 42+00 to 51+50 (Albin et al. 1997 
[DIRS 101367]). This intensely fractured zone has been treated separately in the analyses 
ANL-EBS-MD-000027 REV 03 6-7 September 2004 

Drift Degradation Analysis 
presented in this report. The ECRB Cross-Drift exposes the middle nonlithophysal zone from 
Stations 10+15 to 14+44. In general, the rocks are densely welded, crystallized, and have 
various amounts of vapor-phase corrosion and mineralization. The rock contains 1 to 2 percent 
crystal fragments, 1 to 5 percent lithic fragments, 1 to 15 percent pumice fragments, 0 to 
3 percent lithophysae, and 76 to 97 percent matrix-groundmass. The matrix-groundmass has two 
main colors that appear to result from variations in the types of crystallization, but locally there 
are gradations between these two types that form a heterogeneous mix of colors and 
crystallization products. One type of rock is a mix of grayish orange-pink (5YR7/2), grayish red 
(5R4/2), and grayish red-purple (5RP4-5/2) that locally has small veinlets and stringers. The 
other type of rock is pale brown (5YR6/2), light brown (5YR6/3-4), and moderate brown 
(5YR4/3), grayish brown (5YR6/1), or pale red (5-10R6/2). The matrix-groundmass contains 
0 to 25 percent, white (N9), very light gray (N8), and light gray (N7) to grayish pink (5R8/2) 
spots, veinlets, streaks, rims on fractures, stringers, and vapor-phase partings of crystallized 
materials. Smooth, high-angle fractures are typical of the zone, but it also contains some low-
angle, continuous shears and cooling joints. Another feature characteristic of the Tptpmn is the 
presence of concentrations of vapor-phase minerals along vapor-phase partings and these 
features appear as low-angle continuous partings subparallel to the dip of the unit. The 
lithophysae-bearing subzone (Tptpmn2) described by Buesch et al. (1996 [DIRS 100106]) occurs 
in the ECRB Cross-Drift and has 1 to 3 percent lithophysae (Mongano et al. 1999 
[DIRS 149850]), but this subzone does not occur in the Main Drift of the ESF (Mongano et al. 
1999; Buesch and Spengler 1998 [DIRS 101433]). 
TptpllThe Tptpll is exposed in both the ESF main loop and ECRB Cross-Drift. The ESF main 
loop exposes the uppermost few meters of the lower lithophysal zone from Stations 57+29 to 
58+78. The lower lithophysal zone is exposed along the ECRB Cross-Drift from 
Stations 14+44 to 23+26. The rocks are densely welded, crystallized, lithophysal, and have 
various amounts of vapor-phase corrosion and mineralization. The rocks are composed of 
1 to 2 percent crystal fragments, 1 to 5 percent lithic fragments (locally 12 to 15 percent), 
0 to 7 percent pumice fragments (locally 10 to 35 percent), 5 to 30 percent lithophysae (locally 
1 to 5 percent), and 56 to 93 percent matrix-groundmass. The matrix-groundmass is a mottled 
mix of pale red (5R6/2, 5R5/2, 10R6/2-3) and pale to light brown (5YR6/2; 5YR6/3; 5YR6/4), 
and moderate brown (5YR4-5/4) with variable amounts of pale to grayish red-purple 
(5RP5-7/1-2 to 5RP4/2), and locally it is dusky yellowish brown (10YR3/2). The matrix-
groundmass contains 3 to 20 percent (locally 15 to 40 percent) grayish orange-pink (5YR7/2) or 
pinkish gray (5R8/2; 10R8/2) to light or very light gray (N7; N8) spots, veinlets, streaks, rims on 
fractures, stringers, and vapor-phase partings of crystallized materials. Lithophysae vary in size 
from a few centimeters to greater than 1 m in diameter. 
TptplnThe Tptpln is not exposed in the ESF main loop, but is exposed in the ECRB 
Cross-Drift from Stations 23+26 to 25+85. The rocks are densely welded, crystallized 
pyroclastic-flow material and typically are composed of 1 to 2 percent crystal fragments, 3 to 7 
percent lithic fragments, 3 to 20 percent pumice fragments, 0 to 5 percent lithophysae, and 66 to 
93 percent matrix-groundmass. Rocks of the lower nonlithophysal zone vary from a 
heterogeneous mix of grayish red and grayish orange pink (5YR7/2) matrix-groundmass to 
comparatively homogeneous pale red, light brown, pale brown, or grayish brown (5YR6/4) 
matrix-groundmass. Veinlets, streaks, and stringers form a minor component of the rock in some 
portions of the unit. In proximity to the Solitario Canyon fault zone, the unit is brecciated and 
ANL-EBS-MD-000027 REV 03 6-8 September 2004 

Drift Degradation Analysis 
altered. In this area, the breccia matrix varies from moderate reddish brown to grayish orange 
pink. Some breccia clasts adjacent to the fault plane are very light gray. 
6.1.3 Geotechnical Characterization 
Geotechnical data were collected based on two empirical rock mass classification systems: the 
Norwegian Geotechnical Institute rock quality system (Q system) (Barton et al. 1974 
[DIRS 101541]) and the Geomechanics Rock Mass Rating (RMR) system (Bieniawski 1989 
[DIRS 101715]). Ratings are assigned to a 5-m length of tunnel using both rock classification 
systems. The use of this relatively short rating length may have the disadvantage of introducing 
variations in some evaluated parameters, which may be expected to be stable, yet it has the 
advantage of capturing expected variations in more unstable parameters. For example, using the 
Q system, the number of joint sets could be considered constant over a long reach of tunnel. 
Using a 5-m rating length permits evaluation of the actual occurrence of a particular joint set; 
therefore, the rating value for the number of joint sets may vary within a 10-m reach of tunnel. 
On the other hand, the 5-m rating length permits a description of the changes in fracture 
frequency represented by the rock quality designation (RQD). Overall, the 5-m rating length 
emphasizes changes in rock quality from one length to the next. When longer reaches of the 
tunnel or various stratigraphic units are compared, differences in the trends of the 5-m ratings 
and differences in the average ratings are meaningful. The geotechnical characterization of 
lithostratigraphic units is described in this section and is based on Mongano et al. 
(1999 [DIRS 149850]). It must be recognized that application of geotechnical characterization 
methods and determination of rock quality is problematic in lithophysal rocks since these 
classification systems are based on the presence of fractures as the primary structural features 
and have no provision for lithophysal cavities. Therefore, it was considered that the RQD rating 
accounts for the presence of lithophysal cavities. The difficulty inherent in correspondence of 
RQD based on cross-cutting fractures and RQD based on isolated cavities in a solid rock matrix 
tends to downplay the utility of rock mass classifications in lithophysal rock. 
TptpulThe Tptpul (Stations 0+00 to 10+15 and Stations 23+26 to 25+85), the longest reach of 
the ECRB Cross-Drift, has the lowest RQD rating (36 [poor]), yet the highest Q system rating 
(14 good). The Tptpul RMR value (57 fair) equals the RMR value of the Tptpll and its 
lithophysae content ranges from 10 to 40 percent by volume. These cavities average 10 cm in 
diameter. Fractures are difficult to distinguish, with an average of only one joint set. No key 
blocks are expected to form within this unit; however, there are occasionally some horizontal 
cooling joints. It has 11 faults, 1 fault zone, and 25 shears or shear zones. 
TptpmnThe Tptpmn (Stations 10+15 to 14+44) has a mean horizontal RQD rating of 60 (fair) 
including lithophysae, and 62 (fair) excluding lithophysae. The tunnel-calculated Q rating is 
12.7 (good). The RMR system rates the Tptpmn and the Tptpln as the highest, with a rating of 
60 (fair). The unit is generally characterized by less than 3 percent lithophysae by volume. The 
Tptpmn has 430 m of exposure in the ECRB Cross-Drift and has the least amount of fault/shear 
activity with a total of 1 fault zone, 6 faults, and 13 shears. It has an average of three to three+ 
random joint sets. The horizontal joint sets, or vapor-phase partings, cause the formation of key 
blocks at Stations 10+80 to 11+55 and Stations 13+10 to 13+15. 
ANL-EBS-MD-000027 REV 03 6-9 September 2004 

Drift Degradation Analysis 
TptpllThe Tptpll (Stations 14+44 to 23+26) has a horizontal RQD rating of 42 (poor). Its 
tunnel-calculated Q rating is 7.9 (fair), the lowest in the ECRB Cross-Drift. The RMR system 
estimates this unit at 57 (fair). The Tptpll is generally characterized by lithophysae of 5 to 
30 percent by volume and that range in size from 5 to 130 cm. The larger lithophysal cavities 
tend to be irregular or ellipsoidal features that exhibit prismatic fracturing. The unit has an 
average of two+ random joint sets; however, no key-block problems are apparent. The Tptpll 
has 4 faults and 30 shears exposed in 882 m of rated tunnel. 
TptplnThe Tptpln (Stations 23+26 to 25+85) has the best horizontal RQD ratings: 62 (fair) 
including lithophysae, and 67 (fair) excluding the lithophysal cavities. Its tunnel-calculated 
Q rating is 12.3 (good). The RMR system rates this unit at 60 (fair). This unit is characterized 
by generally less than 3 percent lithophysal cavities by volume. The Tptpln has an average of 
three joint sets, with no significant key-block occurrences, and has 6 faults and 36 shear or shear 
zones. 
6.1.4 Discussion of Engineering Characteristics of Rock Mass Important to 
Geomechanical Performance 
The structure of the rock mass plays an important role in defining the structural response of the 
repository to thermal and mechanical loading. In particular, the fracture geometry and properties 
and the amount of lithophysal porosity are the primary geologic structures of importance. 
Extensive geotechnical mapping of fractures has been performed in the entire ESF main loop and 
the ECRB Cross-Drift (CRWMS M&O 1998 [DIRS 102679]; Mongano et al. 1999 
[DIRS 149850]). Figure 6-4 shows a schematic of the Topopah Spring Tuff illustrating the 
general occurrence of fracturing and lithophysae in the various zones of the formation. The 
occurrence of fractures and lithophysae are roughly inversely proportional. This is illustrated 
schematically in Figure 6-4 and demonstrated quantitatively in Figure 6-5, where the fracture 
density (fractures with trace length greater than 1 m), determined from detailed line mapping 
(i.e., the detailed line survey), and the approximate percentage of lithophysal porosity in the 
ECRB Cross-Drift are shown. The density of fractures with trace length greater than 1 m is 
significantly larger in the Tptpmn and Tptpln (20-35 fractures/10 m), as compared to five 
fractures/10 m or less in the Tptpul and Tptpll. 
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Drift Degradation Analysis 
Source: Buesch et al. 1996 [DIRS 100106], Appendix 2; Mongano et al. 1999 [DIRS 149850], pp. 12 to 43. 
Figure 6-4. Schematic Illustration of the Structure of the Topopah Spring Tuff 
ANL-EBS-MD-000027 REV 03 6-11 September 2004 

Drift Degradation Analysis 
Source: Mongano et al. 1999 [DIRS 149850], Figure 13. 
Figure 6-5. Fractures and Lithophysal Abundance in the ECRB Cross-Drift from Stations 0+00 to 27+00 
6.1.4.1 Fracturing 
The discussion of fracturing presented in this section is based on Mongano et al. 
(1999 [DIRS 149850]). Full periphery geologic mapping and detailed line surveys (consisting of 
a description of orientation, trace length, small and large scale roughness, and end terminations 
for fractures with trace lengths of greater than or equal to 1 m) were performed in the drifts. The 
database consists of over 35,000 entries and is recorded on CAD drawings as well as 
spreadsheets. There are, in general, four sets of fractures in the Tptpmn with the characteristics 
identified in Table 6-1. 
The fractures have relatively short continuous trace lengths (Figure 6-6), with ends often 
terminating either against other fractures or in solid rock, leaving a solid rock bridge between 
joint tracks. Full periphery geologic maps that logged the fracture traces with lengths greater 
than 1 m were created behind the tunnel boring machine as the ESF main loop and the ECRB 
Cross-Drift were driven. A typical full periphery geologic fracture map is shown in Figure 6-7. 
Figure 6-8 provides a photograph typical of the wall of the ECRB Cross-Drift within the 
Tptpmn, and shows the discontinuous nature of the fractures in each joint set. The fracture traces 
were painted during the detailed line mapping (Figure 6-8). Each fracture termination was 
logged as being against another fracture, within solid rock, or continuous. The photo shows the 
common occurrence of fractures that terminate in solid rock (T-junctions) as opposed to 
continuous structures (arrowheads). The sub-vertical fractures, in particular, often have curved 
surfaces with large-amplitude (dozens of centimeters) asperities and wavelength of meters. 
Fractures sometimes terminate in solid rock with discontinuous interconnection to adjacent joint 
tracks (i.e., a rock bridge) or terminate against other joints. 
ANL-EBS-MD-000027 REV 03 6-12 September 2004 

Drift Degradation Analysis 
Table 6-1. General Characteristics of Fracture Sets in the Middle Nonlithophysal Unit 
Set 
Mean 
Azimuth/Dip 
Median 
Spacing (m) 
Median Trace 
Length (m) Comment 
1 120/84 0.48 3.3 Rough to smooth, planar 
2 215/88 1.08 2.8 Smooth but curved 
3 302/38 3.40 3.7 Random fractures with generally flat to moderate dip 
4 329/14 2.46 3.5 Vapor-phase partings, rough, cohesive with coating 
minerals, planar 
Source: Median spacing and trace length are from tunnel mapping data (see Table 6-2). 
Source: Mongano et al. 1999 [DIRS 149850], Figure 14. 
Figure 6-6. Fracture Trace Length from Detailed Line Surveys as a Function of Stationing Along the 
ECRB Cross-Drift 
ANL-EBS-MD-000027 REV 03 6-13 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-14 September 2004 
Source: DTN: GS990408314224.004 [DIRS 108405]. 
NOTE: The purpose of this figure is to illustrate the geologic structure contained on a full periphery geologic map. 
The annotated information on this figure is not intended to be legible. An enlarged, legible map is available 
through the source DTN. 
Figure 6-7. Illustrative Example of a Full Periphery Geologic Map from the ESF, Tptpmn 

Drift Degradation Analysis 
NOTE: T-junctions on fractures indicate terminations; arrowheads show continuous features. 
Figure 6-8. Fractures in Wall of the ECRB Cross-Drift in the Tptpmn 
The sub-horizontal vapor-phase partings (Figure 6-9) are relatively continuous structures seen 
throughout the Tptpmn. These continuous, but anastomosing fractures are sub-parallel to the dip 
of the rock unit, and are filled with concentrations of vapor-phase minerals (primarily tridymite 
and cristobalite). The surfaces are rough on a small scale and, as a result of the mineral filling, 
they have cohesion (unlike the sub-vertical fractures). 
The nature of the fracture geometry is extremely important to estimates of the stability of the 
rock mass, particularly under seismic shaking, as well as to estimates of the support function and 
level of required ground support. Most rock mass classification schemes are based on 
experience of rock masses with continuous joint sets that create regular, blocky masses 
(e.g., Hoek 2000 [DIRS 160705]). In the Tptpmn, the relatively short trace lengths and 
non-persistent joints create relatively few kinematically removable blocks. This sparseness is 
evidenced by the fact that only a very small number of rock blocks have actually been removed 
in the ECRB Cross-Drift. Those blocks removed actually occurred under the action of the tunnel 
boring machine or were scaled out of the back and walls. 
Short-length fractures (less than 1-m trace length), coupled with the lithophysae, are the most 
important features that govern stability in the Tptpll because they impact the rock mass strength 
as described in Appendix E (Section E4). Whereas the Tptpul tends to have some small-scale 
fractures in the matrix-groundmass between lithophysae, and a few that intersect lithophysae 
(Figure 6-10a), the Tptpll has abundant fractures. Figure 6-10b, from the upper portion of the 
Tptpll, shows the intensive fracturing of the matrix-groundmass between lithophysae, several 
circum-lithophysal fractures (fractures that formed around or parallel to the margins of 
lithophysae), and very few fractures that actually intersect the lithophysae. The fractures, which 
exist throughout the Tptpll, have a primary vertical orientation, and have lateral spacing of a few 
centimeters. 
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Drift Degradation Analysis 
Small-scale fracture traverses in the Tptpll confirm the close spacing and short trace lengths of 
fractures in this zone. The intensity and short trace lengths of fractures in this zone create a 
texture that severely limits the potential block size in this zone. By comparing the detailed line 
survey (fracture greater than 1m) and the small-scale surveys, this intensity is clearly due to 
small-scale fractures (less than 1m trace length). The detailed line survey sampled almost 880 m 
of tunnel in the ECRB Cross-Drift. There are 300 fractures recorded over this run of tunnel that 
have a trace length greater than 1 m. The small-scale survey in the Tptpll can be combined into 
18 m of horizontal sampling. There are 376 fractures recorded over this 18 m of sampling. 
In some cases, it is difficult to distinguish whether these fractures have been disturbed by mining 
or induced by in situ stresses, or whether they are newly created by mining along a weakness 
fabric in the rock. However, it is clear that the middle portion of the Tptpll has a ubiquitous 
fracture fabric that is most evident when large diameter core is removed from boreholes 
(see Figure 7-1a). The core, although competent, has numerous fractured surfaces that break into 
small blocks when stressed. Lithophysae and occasional horizontal fractures tend to create 
blocks with dimensions on the order of about 10 cm or less on a side. Thin section analyses of 
the fracturing in the Tptpll and the Tptpmn show rims on many of the fracture surfaces within 
the rock mass away from the tunnel wall, indicating there are numerous natural fractures 
(i.e., not mining-induced) and were formed during the cooling process (Buesch 2003 
[DIRS 163729]). 
Figure 6-9. Low-Angle Vapor-Phase Partings in Nonlithophysal Units in the ESF 
ANL-EBS-MD-000027 REV 03 6-16 September 2004 

Drift Degradation Analysis 
NOTE: The Tptpul (a) is characterized by a relatively few fractures in the matrix-groundmass between lithophysae 
whereas the Tptpll (b) has abundant, natural, short-length fractures in the matrix-groundmass, some of 
which intersect or connect lithophysae. Spacing of the fractures in the Tptpll is generally less than 5 cm. 
Figure 6-10. Comparison of Lithophysae and Fracturing in the Tptpul and Tptpll 
6.1.4.2 Lithophysae 
Although the character of the lithophysae varies between the Tptpul and Tptpll as shown in 
Figure 6-10, the mineralogy of the matrix material within both of these units is generally the 
ANL-EBS-MD-000027 REV 03 6-17 September 2004 

Drift Degradation Analysis 
same as in the nonlithophysal units, based on the rock unit descriptions provided by Mongano et 
al. (1999 [DIRS 149850]). 
Compositionally and mineralogically the rocks in lithophysal and nonlithophysal zones are 
similar, but there can be variations in the amounts of quartz, cristobalite, and tridymite; however, 
the main difference is in the abundance of lithophysae and features formed by crystallization in 
the presence of the vapor phase (rims, spots, etc.). The upper and lower lithophysal zones share 
many characteristics, but there are also numerous distinctions (Mongano et al. 1999 
[DIRS 149850]), and these general characteristics are as follows. 
The lithophysae in the Tptpul: 
 Tend to be smaller (roughly 1 to 10 cm in diameter) compared to the Tptpll 
 Are more uniform in size and distribution within the unit compared to the Tptpll 
 Vary in infilling and rim thicknesses 
 Have a volume percentage that varies consistently with stratigraphic position 
 Are stratigraphically predictable. 
The lithophysae in the Tptpll: 
 Are highly variable in size, from less than 1 cm to 1.8 m in size 
 Have shapes that are highly variable and are described as simple (elliptical 
cross-sections and spherical to ellipsoidal shapes), irregular, cuspate, merged (two or 
more lithophysae joined into one large one), and extension-crack lithophysae 
 Have infilling and rim thickness that vary greatly with vertical and horizontal spacing 
 Have volume percentages that vary consistently with stratigraphic position 
 Are stratigraphically predictable. 
With the large amount of the repository located in the lower lithophysal zone, a detailed study of 
the lithostratigraphic features in the lower lithophysal zone exposed in the ECRB Cross-Drift has 
been completed (DTNs: GS021008314224.002 [DIRS 161910] and GS040608314224.001 
[DIRS 171367]). The data package documents the distributions of size, shape, and abundance of 
lithophysal cavities, rims, spots, and lithic clasts, and these data can be displayed and analyzed as 
local variations, along the tunnel (a critical type of variation), and as values for the total zone. A 
detailed description of lithophysal abundance and lithophysal characteristics is provided in 
Appendix O. 
In addition to the along-the-tunnel variation in the abundance of features such as lithophysae, 
there are variations in the sizes, shapes, and distances between features. These types of 
variations are most easily observed with panel map data (Figure 6-11). Locations of the panel 
maps were positioned to capture representative variations in the rocks along the tunnel. 
Additional details on the development of these panel maps are provided in Appendix O. 
ANL-EBS-MD-000027 REV 03 6-18 September 2004 

Drift Degradation Analysis 
NOTE: 
Lithophysae have red L identifiers with cavities outlined in red and rims in green. Spots have blue S identifiers with cyan outlines. Lithic clasts have 
orange C identifiers with gold outlines. 
Figure 6-11. Lithophysae, Spots, and Clasts of Tptpll in Panel Map 1493 Located on the Right Rib from Stations 14+93 to 14+96 
ANL-EBS-MD-000027 REV 03 6-19 September 2004 

Drift Degradation Analysis 
Using the approach described in Appendix O, the total porosity of the component features of the 
lithophysal rock mass (i.e., the porosity of the lithophysal cavities, rims, and spots) has been 
calculated. The porosity variation along the ECRB Cross-Drift is shown in Figure 6-12, with 
total porosity typically ranging from 20 to 35 percent. 
0 
5 
10 
15 
20 
25 
30 
35 
40 
(m) 
Percent (vol.) (%) 
() Ri) (fi) ) () 
() 
1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 
StationCavitiesfittedms (fit t edSpot st t edMGM (fit tedT otalfittedL-Litho5-mLithostrat . contact Bulkheads Equipment 
a. Porosity Along the Tunnel Displayed in Five Components (Excluding the 5-m Averaged Large-Lithophysae). 
b. Porosity Along the Tunnel Displayed in Three Components (Lithophysal Cavities and Large-Lithophysae Inventory 
are Combined, and Rims and Spots are Combined). 
NOTE: Source file provided in DTN: MO0408MWDDDMIO.002, file Drift Deg AMR AF T-A-P Fit V1.xls. 
Figure 6-12. Calculated Porosity of Lithophysal Cavities, Rims, Spots, Matrix-Groundmass, and the 
Total Porosity in the Tptpll Exposed Along the ECRB Cross-Drift 
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Drift Degradation Analysis 
6.1.5 Field Observation of Key Blocks 
Key blocks are critical blocks in the surrounding rock mass of an excavation which are 
kinematically removable and oriented in an unsafe manner so that they are likely to move into an 
opening unless support is provided (Goodman and Shi 1985 [DIRS 150094], pp. 98 and 99). 
The failure of a key block opens up the excavation surface for further potential failures by 
subsequent blocks. Key blocks are formed by the intersection of three or more planes of 
structural discontinuities as shown in Figure 6-13. Key blocks in the 5-m diameter ECRB 
Cross-Drift are first evident in the crown at about Station 10+50 in the Tptpmn unit (note that 
metric stationing is used throughout the ESF; i.e., Station 10+50 is located 1050 m from the start 
of the tunnel). Most of the key blocks in this region are of minor size and typically fall 
immediately after excavation prior to ground support installation. Key blocks are possible in this 
area because of the increased presence of the plane of weakness (i.e., a vapor-phase parting) in 
the near horizontal orientation that intersects with two opposing near-vertical joint planes. 
Fallout from these key blocks during excavation is typical of the rock in the middle 
nonlithophysal zone (Tptpmn) of the TSw2 thermal-mechanical unit. The largest resultant void 
is possibly 0.5 cubic meters at approximately Station 11+55 as shown in Figure 6-14. No 
unstable key blocks were observed in the field. Documentation of key blocks observed in the 
ECRB Cross-Drift is provided in Appendix F. 
ANL-EBS-MD-000027 REV 03 6-21 September 2004 

ANL-EBS-MD-000027 REV 03 6-22 September 2004 
Drift Degradation Analysis 
KeyBlockFormedbytheIntersectionofanExcavationwithThreeFracturePlanesTunnelExcavation235/87338/12NESW133/83StereographicProjectionofKey-Block-FormingFracturePlanes 
Figure 6-13. Illustration of a Typical Key Block and Associated Fracture Planes 

Drift Degradation Analysis 
Figure 6-14. Evidence of Key-Block Occurrence in the ECRB Cross-Drift, Station 11+55 
While ground support monitoring in the ESF main loop has provided long-term evidence 
indicating stable rock support performance, there are several sections in the ESF where raveling 
and block fallout have occurred. These typically corresponded to the 3.01X areas, and most 
often occurred in fault zones and in the TCw and TSw2 thermal-mechanical units. The 3.01X 
areas refer to sections of the ESF main loop that were constructed under Section 3.01X of the 
subsurface general construction specification (BSC 2002 [DIRS 161707], p. 17). The 
specification indicates that special actions may be necessary to continue excavation in the event 
ANL-EBS-MD-000027 REV 03 6-23 September 2004 

Drift Degradation Analysis 
that adverse ground conditions prevent normal tunnel boring machine operations. The location 
of 3.01X areas is provided by South Ramp 3.01.X Area Ground Support Analysis (CRWMS 
M&O 1999 [DIRS 108441], Section 1). A typical opening profile in a 3.01X area is shown in 
Figure 6-15. This profile is indicative of the worst case ground conditions in the Tptpmn 
lithologic unit of the ESF main loop. 
1.4 
1.1 
0.44 
0.38 
Source: CRWMS M&O 1999 [DIRS 108441], p. 29. 
NOTE: Dimensions are in meters. 
Figure 6-15. Opening Profile at ESF Main Loop Station 60+24.70 (Steel Set #1272, Tptpmn 
Lithostratigraphic Unit) Based on Field Survey Data 
6.1.6 Generation of Representative Rock Volumes Using FracMan 
6.1.6.1 Background 
Analysis of seismic response and rockfall in emplacement drifts in fractured, nonlithophysal rock 
is, in general, a three-dimensional problem requiring the rock mass to be represented as an 
explicitly fractured assemblage. To achieve this objective, the 3DEC three-dimensional 
discontinuum program (see Section 6.3.1) is used to model the mechanical response of a rock 
block assemblage subjected to in situ, thermal, and seismic loads. The 3DEC program allows 
direct input of the fracture geometry in creation of a synthetic rock mass composed of an 
ANL-EBS-MD-000027 REV 03 6-24 September 2004 

Drift Degradation Analysis 
assemblage of blocks within which emplacement drifts may be simulated. The details of the 
3DEC model are described in Section 6.3.1.1. 
The blocks of nonlithophysal rock are significantly stronger than the in situ and thermally 
induced stresses, and thus the problem of modeling this material is essentially one of elastic 
blocks separated by fracture surfaces. Therefore, in modeling of the stability of the tunnels and 
the rockfall that may occur from the applied load, the fracture geometry and surface properties 
become of primary importance. A methodology for defining statistically representative fractures 
is therefore required as an input to the 3DEC program for development of the rock block 
structure. In particular, the input fracture geometry must provide an adequate representation of 
the orientation, length (area), spacing and continuity of fractures and their variability, as this 
controls the size and number of kinematically removable blocks that surround the tunnel. 
Additionally, the surface characteristics, including roughness, planarity, and alteration/infilling 
define the shearing and tensile resistance of the fractures under load. In the following section, 
the generation of a statistically representative network of fractures for describing the repository 
host horizon subunits is described. In particular, the fracturing within the Tptpmn unit is given 
since this unit represents the largest emplacement area of nonlithophysal rock. 
6.1.6.2 FracMan Program Approach to Fracture Geometry Analysis 
The development of a stochastically defined fracture system, representative of the host horizon 
rock mass is accomplished using the FracMan program (USGS 1999 [DIRS 160577]). FracMan 
is a special-purpose fracture-analysis tool that was developed for the creation of synthetic 
fracture representations for use in hydrologic modeling, reservoir engineering, and rock 
mechanics applications. It has been used for preliminary hydrologic modeling of Yucca 
Mountain (Anna 1998 [DIRS 144421] and Anna 1998 [DIRS 138501]) for estimation of rock 
mass permeability. 
The existing fracture mapping database (see fracture geometry data in Table 4-1) provides the 
basic input to the FracMan program, which develops sets of planar, circular fractures whose 
geometric parameters conform to the statistical variability of the geometric characteristics of the 
input data. Statistical models are fitted to the various geometric characteristics of each fracture 
set in the database, followed by generation of representative fracture sets. These representative 
fractures are then back-checked against the statistical variability and geologic realism of the 
original sets (i.e., field data) to achieve an acceptable facsimile. The FracMan simulations are not 
intended to replicate actual field conditions but to create a reasonable facsimile of these 
conditions based on the observed data. 
The use of the FracMan program for providing a calibrated set of fractures representative of the 
repository host horizon is considered to be a scientific analysis governed by procedure 
AP-SIII.9Q. The definition of a scientific analysis in this procedure is (pg. 6): 
A documented study that 1) defines, calculates, or investigates scientific 
phenomena or parameters; 2) evaluates performance of components or aspects of 
the overall geologic repository; or 3) solves a mathematical problem by formula, 
algorithm, or other numerical method. A scientific analysis may involve 
numerical manipulations that are not part of a previously developed and 
ANL-EBS-MD-000027 REV 03 6-25 September 2004 

Drift Degradation Analysis 
validated mathematical model (per AP-SIII.10Q,, Models) if the choice of method 
is evident from standard scientific practice, approach, or method. 
Use of FracMan as a scientific analysis is justified based on the following considerations: 
 FracMan is used to investigate and evaluate the stochastic variability of fracture 
geometry only. FracMan is not used to model a physical process (e.g., rockfall) that 
involves prediction or extrapolation of physical response. 
 FracMan is used only to provide a reasonable facsimile of the occurrence and variability 
of fracturing in the Tptpmn and Tptpll units. To provide this facsimile, the model is 
calibrated against the existing field data in such a way that the statistical variability of 
the dip, dip direction, spacing (intensity) and trace length can be verified to be 
quantitatively similar. 
 The FracMan analysis is not used for extrapolation purposes, but only to provide a 
calibrated representation of the fracture geometry represented by the database from 
which it is derived. This database is obtained from detailed line survey and full 
periphery geologic mapping in the ESF and ECRB Cross-Drift. The ESF provides a 
North-South sampling over a substantial length of the Tptpmn along the eastern 
boundary of panels 1 and 2 of the proposed repository, and the ECRB Cross-Drift cuts 
across all repository host horizon units on a NE-SE azimuth through the center of the 
repository (see Figure 1-2). It is considered that this total sampling reasonably 
represents the range of fracture geometries with trace lengths of 1 m or longer, to be 
expected within the repository and the Tptpmn in particular. Therefore, the FracMan 
representation, calibrated to the complete fracture database provides a similar 
representation of the fracture variability in the Tptpmn in particular. In this manner, 
FracMan is not used to extrapolate fracture geometry to new regions since it is implicit 
in this approach that the fracture database provides a reasonable representation of the 
fracture variability throughout the repository host horizon. 
 FracMan is a fracture geometry simulation program that is commonly used in industrial 
and scientific practice. 
Based on these considerations, model validation, as described in procedure AP-SIII.10Q, 
Models, is not required for the fracture simulation analysis described in this section. 
The FracMan simulations consist of development of cubical regions of fractures, 100-meter 
on-a-side, representing the Tptpmn and Tptpll lithostratigraphic zones of the repository horizon. 
The regions are populated with simulated fracture networks to represent the rock mass of the 
respective zones. Data from the detailed line survey and full periphery geologic mapping are 
used as a basis for constructing the representative fracture networks in these regions. As 
previously discussed, these data consist of fractures with trace lengths of one meter or greater. 
Each fracture is described by its centroid coordinate, dip, dip direction, and radius. These 
geometric properties are used as input to the 3DEC program for development of a block 
geometry within which emplacement drifts can be randomly excavated. Development of the 
Tptpmn FracMan cube is described in this section to represent the modeling approach used for 
ANL-EBS-MD-000027 REV 03 6-26 September 2004 

Drift Degradation Analysis 
nonlithophysal rock. Details for the analysis of the Tptpll long-fracture network, which 
represents the lithophysal rock within the repository, are provided in Appendix B. 
6.1.6.3 Fracture Studies in the ESF and ECRB Cross-Drift 
6.1.6.3.1 Data Sources 
There are two primary data sources for subsurface fractures within the repository horizon at 
Yucca Mountain: the detailed line survey and the full-periphery geologic mapping (Beason et al. 
1996 [DIRS 101191]; Barr et al. 1996 [DIRS 100029]; Albin et al. 1997 [DIRS 101367]; Eatman 
et al. 1997 [DIRS 101219], Mongano et al. 1999 [DIRS 149850]). The detailed line survey 
presents a detailed inventory of fractures and fracture attributes as measured in the ESF and 
ECRB Cross-Drift. The survey was conducted using a traverse located 0.9 m below the right-rib 
springline in the ESF (Albin et al. 1997 [DIRS 101367], p. 10; Eatman et al. 1997 
[DIRS 101219], p. 8) and at the left-rib springline in the ECRB Cross-Drift (Mongano et al. 1999 
[DIRS 149850], p. 9). Data collected by the detailed line survey included information on 
fracture location (i.e., station), orientation, trace length, width, roughness, among others. The full 
periphery geologic mapping presents a rolled-out record of geologic conditions encountered 
during tunnel excavation activities. The maps are hinged at the crownline and unrolled to 
produce flat maps of the tunnel periphery at 100-m intervals. The maps record lithostratigraphic 
contacts and structural discontinuities (i.e., fractures, faults, and shears) with trace lengths longer 
than 1 m, as well as engineered features (e.g., rock bolts, steel sets, and installed lagging). 
As previously discussed, both the detailed line survey and the full periphery geologic map 
methods exhibit an inherent sampling bias in that fractures approaching the orientation of the 
survey line will be underrepresented. Various methods exist for evaluating this bias. The 
Terzaghi correction (Terzaghi 1966) is a commonly used method to evaluate this directional bias 
in these types of linear surveys. However, the need for bias correction is avoided in the FracMan 
model, because the simulations are constructed to reproduce the statistical variability of the field 
data. As a result the output from a FracMan detailed line survey, similarly oriented to a 
comparable ESF detailed line survey, will automatically recreate the same bias as exists in the 
field data, confirming the accurate reproduction of field conditions in the FracMan simulations. 
In other words the same bias encountered in collecting the observed data is sampled in the 
synthetic data allowing a valid comparison without necessitating bias correction for the observed 
fractures. For this reason there is no requirement to apply corrections to evaluate bias. 
Comparisons of simulated detailed line surveys to the actual field surveys are presented in 
Section 6.1.6.4. 
6.1.6.3.2 Representativeness of ESF and ECRB Cross-Drift Data of the Tptpmn Across 
the Repository Emplacement Area 
Fracture data from the existing ESF and ECRB Cross-Drift excavations has been used for 
developing the FracMan analysis. Although the excavations traverse a large portion of the 
subsurface area being considered for the repository, they do not extend to the limits of the 
proposed repository area (Figure 1-2). To investigate changes in the geometry and character of 
fractures outside the existing excavations, studies of fractures were implemented in surface 
exposures of Topopah Spring Tuff at various locations around Yucca Mountain. These studies 
ANL-EBS-MD-000027 REV 03 6-27 September 2004 

Drift Degradation Analysis 
examined the significant outcrops of the repository host horizon in the vicinity of the site. These 
areas included Solitario Canyon (west of the proposed repository area), WT-11 wash (south of 
the site), Windy Wash (northwest of the site), and Yucca Wash (north of the site). 
In each of these areas, the purpose of the data collection was to determine how fracture 
orientation might vary with distance from the repository area. Orientation data was collected, 
along with some fracture characteristics and notes, from the four zones in the repository host 
horizon (i.e., the Tptpul, Tptpmn, Tptpll, and Tptpln). The bulk of the data was collected in the 
Tptpmn, as this unit is the most erosion resistant. Comparing the fracturing in the Tptpmn from 
around the periphery of the site allows a relatively easy evaluation of the changes in fracture 
orientation. Useable outcrops of the other zones  Tptpul, Tptpll, and Tptpln  are sparse in the 
Yucca Mountain area. 
Note that fracture orientation data is only a portion of the fracture data used to develop fracture 
sets in the FracMan analysis. The analysis has used a hierarchical approach to develop the 
fracture geometry in FracMan. This approach starts with fracture length, based on the 
consideration that the long fractures formed first, shorter fractures thereafter. An orientational 
analysis was then done of the different length fractures to determine the orientation of the 
fracture sets. Fracture length however, is not easily collected on a systematic basis at outcrop, so 
a comparison of orientations has been used here for simplicity. 
Data from the various Tptpmn outcrops around the Yucca Mountain area show remarkable 
consistency in fracture orientation. Measurements from the Tptpmn in Solitario Canyon, even 
far south of the repository area show essentially identical fracture orientations to those observed 
in the ESF and ECRB Cross-Drift (DTN: GS020908314224.001 [DIRS 171038]). Data from the 
far southern outcrops in WT-11 Wash show a slight rotation of fractures in that area in 
comparison with those farther north (along Solitario Canyon). Fractures along the Solitario 
Canyon fault show similar orientations to those collected in the ESF and ECRB Cross-Drift. 
Fractures in Windy Wash (DTN: GS040308314224.002 [DIRS 171039]), northwest of the 
proposed repository, also show similar orientations to those in the underground. These data from 
widely dispersed locales indicate that fracturing in the Tptpmn is similar across the repository 
site, and that variations observed underground (such as the intensely fractured zone) generally 
bound the variations observed in outcrop. 
It has been long understood that the fractures at Yucca Mountain and in particular the fractures in 
the repository host horizon are stratabound (Mongano et al. 1999 [DIRS 149850]). Data from 
the ECRB Cross-Drift show that fracture orientation in the nonlithophysal Tptpmn and Tptpln 
are similar in orientation (Mongano et al. 1999 [DIRS 149850]). While not identical, the 
orientation, frequency, and infilling were found to be quite similar in the two nonlithophysal 
units. Using the relative frequency and orientation differences seen between the lithophysal and 
nonlithophysal zones in the ESF Main Drift, South Ramp, and ECRB Cross-Drift, a general 
understanding can be developed of the density and character of fractures in the lithophysal units 
as compared to the over- and underlying nonlithophysal zones. Outcrops in Windy Wash, 
Solitario Canyon, and WT-11 Wash (near Iron Ridge) display similar relationships between 
lithophysal and nonlithophysal zones. Fracture densities and orientations in Tptpmn outcrops at 
all locations (except at Prow Pass and Yucca Wash) display 3 to 4 closely spaced sets of 
fractures, a significant percentage of which are cooling joints. Where the contacts with the 
ANL-EBS-MD-000027 REV 03 6-28 September 2004 

Drift Degradation Analysis 
adjacent lithophysal units are exposed, the fracture characteristics change. This change across 
lithostratigraphic boundaries has been observed at the locations where the rock is exposed. The 
most dramatic of these exposures are underground such as the Tptpmn/Tptpll contact at station 
14+44 in the ECRB Cross-Drift (Mongano et al. 1999 [DIRS 149850]) and the same contact at 
the southern end of the Main Drift at station 57+29 (Eatman et al. 1997 [DIRS 101219]). At 
both these locations, the fracture sets that are clearly exposed in the base of the Tptpmn 
terminate within 1 to 2 m of penetrating into the underlying lithophysal rock of the Tptpll. 
Similar changes are observed at the Tptpul/Tptpmn and the Tptpll/Tptpln contacts. In each case, 
the transition from lithophysal to nonlithophysal rock results in a significant increase in long, 
recognizable fractures. This same relationship is also clearly exposed in surface outcrops. 
Wherever the contact is visible between lithophysal and nonlithophysal zones, fracture attributes 
display consistent differences at such contacts (see Figure 6-4). 
Fractures in the Yucca Wash area are the only exception to the uniformity of fractures around 
Yucca Mountain. The area where most of the fractures were measured was west of where the 
Solitario Canyon fault enters the Yucca Wash drainage. The lithostratigraphic zones of the 
Topopah Spring Tuff in this area differ considerably in thickness and characteristics from the rest 
of the mountain (DTN: MO0012MWDGFM02.002 [DIRS 153777]). This change in 
lithostratigraphy may result from thickness increases in the underlying Calico Hills, specifically 
the presence of lava flows that extend to the southeast. The rocks in the repository host horizon 
at this locale differ from the rest of the mountain such that Day et al. (1998 [DIRS 100027]) 
mapped this area breaking out only the crystal-rich/crystal-poor members, rather than the zones 
recognized elsewhere. This change causes the fractures in this region to have significantly 
different orientations and characteristics from those observed elsewhere at Yucca Mountain, and 
represents the boundary of where present fracture analyses can be used with confidence. 
6.1.6.4 Construction Techniques used in Generating the FracMan Simulations 
6.1.6.4.1 Hierarchy of Fracture Formation in the Topopah Spring Tuff 
Fractures in the densely welded and crystallized tuffs at Yucca Mountain, for example the 
lithophysal and nonlithophysal zones of the Topopah Spring Tuff, can be divided into two 
petrogenetic groups: those associated with cooling processes, and those associated with tectonic 
processes. Because the timing of fracture formation determines the geometry of the fracture 
network (i.e., trace length and truncations), and thus the size and position of potential rock 
blocks, it is important to understand the general sequence of fracture formation based on these 
processes. 
All fractures have been described on the basis of geometric relations (strike, dip, trace length, 
planarity, truncations, etc.) and features such as tubular structures, rims (the light gray 
crystallized area along the edge of the fracture that is similar to what surrounds lithophysal 
cavities), and mineral or material filling of the fractures. Tubular structures, rims, and 
vapor-phase mineralization are indicative of features that formed very early in the cooling 
history of the deposit (possibly during the first 100 years), and are characteristic of cooling joints 
(Buesch and Spengler 1998 [DIRS 101433]; Buesch et al. 1999 [DIRS 165483]). Early-formed 
and even late-formed cooling fractures (referred to as Type 1 and Type 2 fractures in Buesch et 
al. 1999 [DIRS 165483]) typically have long trace lengths, are the fractures into which shorter 
ANL-EBS-MD-000027 REV 03 6-29 September 2004 

Drift Degradation Analysis 
trace-length fractures typically truncate, and form the initial geometric framework for the 
fracture network. Included in these cooling fractures are (1) vapor-phase partings, which are 
characteristically long, anastomosing to planar, low-angle discontinuities (i.e., dips less than 
20), and (2) typically long, smooth (i.e., planar), high-angle (i.e., steeply dipping) fractures. As 
cooling progressed, shorter trace-length fractures formed, which typically truncate into the 
earlier formed and longer fractures. These smaller fractures can have any orientation (shallowly, 
moderately, or steeply dipping), but typically have similar orientations as the longer fractures, 
and may or may not have rims or vapor-phase mineralization. After the rocks had cooled, and in 
the 12.8 million years since the time of cooling, some fractures, shears (discontinuities with less 
than 0.1 m of separation), and faults formed as a result of structural tilting and faulting of the 
mountain. These post-cooling fractures typically have shorter trace lengths and are not as 
smooth (i.e., are rougher) as cooling fractures. Many shears appear to be reactivated cooling 
joints or an integration of cooling joints, although some might have formed in conjunction with 
development of the fracture itself. Some faults can be fairly simple and somewhat planar 
discontinuities, but many are an integration of short-trace-length fractures to form irregular and 
rough discontinuities, and some are complex zones of deformation (Mongano et al. 1999 
[DIRS 149850]). Many faults and shears, especially those with separations of less than 
four meters, have similar strikes and dips to the fractures (Mongano et al. 1999 [DIRS 149850]). 
6.1.6.4.2 Hierarchical Construction of Fractures in the FracMan Model 
Construction of the FracMan network starts with the low-angle vapor phase features. Because 
these features form first in the cooling process their truncation by other features is minimal. The 
truncation probability value (i.e., the probability that a fracture that intersects another fracture 
will be terminated against that fracture) for these features used in FracMan is set to 0 percent as 
qualitatively estimated from fracture terminations from the full periphery geologic maps. To 
continue the construction of the FracMan network, the remaining fractures, having a dip greater 
than 20 degrees are separated into two classes. The first class includes those fractures that 
formed about the same time as the vapor-phase partings. These fractures are referred to as 
cooling joints and have long trace lengths with some truncation occurring against the 
vapor-phase partings and themselves. A truncated power law distribution is used for these 
features. A large max/min fracture length is used along with a termination probability value of 
15 percent, again based on qualitative examination of the terminations in the full periphery 
geologic maps. The second class includes the fractures that have a shorter trace length. The 
length distribution can be separated into two populations; those with trace length below 7 to 
8 meters (short trace length) and those with trace length greater than 7 to 8 m (long trace 
length fractures). This separation is based on a break in slope of the trace length frequency as 
shown in Figure 6-16. These fractures are considered to be later cooling and tectonic fractures. 
These fractures are generated into a network comprised of vapor-phase partings and long 
high-angle cooling fractures and are truncated more severely than the earlier fractures. A shorter 
max/min fracture length is used along with a termination probability value of 10 percent (as 
qualitatively estimated from full periphery geologic maps). 
ANL-EBS-MD-000027 REV 03 6-30 September 2004 

Drift Degradation Analysis 
25 
20
Frequency Percent 
15 
10 
5 
0 
0 5 10152025303540455055 
ling 
ic 
ly 
iLater 
cooand 
tectonfractures 
Earcoolng 
fractures 
Trace Length (meters) 
Figure 6-16. Trace Length Distribution of the Tptpmn Fractures with Dips > 20 
Based on the observed data, four fracture sets are defined in the Tptpmn. The great circles for 
these sets are displayed in Figure 6-17. The fracture analysis of the Tptpmn begins with defining 
the first forming discontinuities. Based on a hierarchical distribution of discontinuities, the first 
forming features are the low angle (less than 20 degrees) vapor-phase partings and the long 
high-angle fractures. 
The hierarchical or sequential method of construction is significantly different from a 
construction with sets solely identified on the basis of orientation. Observations of 
mineralization and truncation relations (Mongano et al. 1999 [DIRS 149850]) suggest that the 
current sequential construction is more appropriate to generate a representative rock volume 
since short fractures truncate against longer fractures. This construction does not create a 
replicate of the actual fracture geometries observed in the limited sampling afforded by the 
detailed line surveys and the full periphery geologic maps. The objective is to provide a 
generalized, representative fracture network for evaluation of the Tptpmn rock mass as a whole. 
The output from FracMan is a fracture network whose geometry is conditioned from evaluation 
of the detailed line survey and full periphery geologic map data. Special geologic features are 
not represented in this effort. For example, in a given segment of tunnel mapping there may be a 
small section that shows an increased amount of fractures from a given set. The developer may 
decide to represent this zone by developing a specific distribution for this occurrence1. However, 
1A zone within the Tptpmn that was given specific treatment and not included in the general fracture characteristics 
for FracMan development is the intensely fractured zone. The intensely fractured zone, a 1000-m zone with 
anomalously high Set 1 fracture frequency (i.e., the mean and median joint spacing for the predominant 
Set 1 fractures were calculated to be 0.24 m and 0.12 m, respectively), is not modeled with FracMan, but is treated 
as an anomalous zone of ubiquitous fracturing with the Set 1 orientation as described in Section 6.3.2. 
ANL-EBS-MD-000027 REV 03 6-31 September 2004 

Drift Degradation Analysis 
for this report an average geometry is used to describe the simulation because the fracture 
network developed does not represent a specific section of the mapped area, but is representative 
of the general condition of the rock mass. Zones that display anomalous geometries in each 
lithostratigraphic unit are averaged into the simulation when the decision is made that adding this 
input helps represent the rock mass correctly (in an overall sense) with the data that is available. 
Because this output is not a replicate, a single constant fracture intensity is imposed for each set 
in each lithostratigraphic unit. 
Source: DTN: GS971108314224.025 [DIRS 106025]; GS000608314224.004 [DIRS 152573] 
GS960708314224.008 [DIRS 105617]; GS960708314224.010 [DIRS 106031]; GS990408314224.001 
[DIRS 108396]. 
NOTE: Data from the intensely fractured zone are not included in this pole plot. Orientations are given in strike and 
dip of mean poles. 
Figure 6-17. Pole Plot of Tptpmn Detailed Line Survey Data from the ESF Main Loop and ECRB 
Cross-Drift 
6.1.6.4.3 Fracture Trace Length 
Correct fracture size (trace length and area) is critical to the construction of a representative 
network. Unfortunately, the radius of a fracture cannot be measured from sampling of the 
fracture network along the surface of a tunnel. If the fractures are considered circular disks, the 
centers of those disks do not have to coincide with the sampling surface. The observed trace 
length is then typically not the disk diameter because the centers of the fracture disks do not 
coincide with the sample surface. In a tunnel surface sampling, observed trace length could be 
longer or shorter depending on the position of the center of the fracture. 
ANL-EBS-MD-000027 REV 03 6-32 September 2004 

Drift Degradation Analysis 
To get an intuitive feel for the radius distribution and how it relates to the observed trace length 
distribution consider a single fracture of radius R oriented perpendicular to the sampling plane. 
If the fracture intersects the plane, the observed trace length can vary from 0.0 to 2.0R. 
The trace length, T, is a function of the distance from the sampling plane, z, and the fracture 
radius, R, and is defined based on standard geometric relationships (see Figure D-11): 
2 0.5 
T=2 (R2-z) (Eq. 6-1) 
The mean observed trace length Tm is then 
R
T
m = 1 .0 
2(R 2 - z 2 ) 5.0 dz (Eq. 6-2) 
R 
Tm = pR/2 or R = Tm 2/p (Eq. 6-3) 
indicating that the mean fracture radius is about 2/3 of the mean trace length observed. 
This means that the expected distribution of trace lengths is equal to the distribution of the 
intersecting fractures times a constant factor p/2. In a log-log plot, multiplication of a power law 
by a constant does not change the slope, so that the scaling exponent of trace lengths is the same 
as the scaling exponent of the radius distribution of intersecting fractures. 
The radii distributions are compared to a distribution formed from the trace lengths observed 
multiplied by two-thirds to adjust the trace lengths to approximate radii. This is not a perfect 
adjustment because the dip of the fractures as well as their persistence will influence the number 
two-thirds. The trace lengths are observed with a sampling surface or detailed line survey. 
Additional effects may be present when comparing the radii in the 100-m cube synthetic fracture 
region generated by FracMan with the surface or line sampling. Individual plots of these 
distributions are included in each of the following sections for the lithostratigraphic units. 
Overall, the fits are good to excellent. 
After the sequence of formation is defined and the length distribution selected, orientation is 
evaluated to further subdivide the fractures into sets based on analysis of stereonet pole plots. 
Fractures with a dip greater than 20 degrees are used for this analysis because the orientations of 
the longer fractures and the shorter fractures are coincident. Once this is accomplished, the 
actual inputs for FracMan are developed. 
6.1.6.4.4 Fracture Geometry 
The following is a brief description of the inputs required to begin the generation of simulated 
fracture geometries. The fracture geometry data for each lithostratigraphic unit are converted to 
the parameters needed for FracMan. The input values for the FracMan model of each 
lithostratigraphic unit are derived from the detailed line survey data and used to develop an input 
data form. The FracMan input sheet for the Tptpmn is shown in Figure 6-18. Sets are based on 
ANL-EBS-MD-000027 REV 03 6-33 September 2004 

FracMan/FracWorks 
Project Tptpmn Task Drift Degradation Date 03/04 Modeler Lung-Fahy 
Seed #: 1 Fracmeter Unit: 50 Truncation mode Region View Center 0,0,0 
Direction Scale % displayed 100 Orientation = Pole or Dip Pole # frac sides 6 
NN factor NN export: WZ inten: WZ parall: WZ large: WZ close Frac Dim (LL,FB)(.5-5.) 
Spherical/ 
Zone Thick Fracs # iterations Frac Dim (POCS) Ampl Shaper Fac (POCS) Box Frac Dim Exp 
Variogram Semivariogram Sill Corr Length 
.FDT (Binary. Cannot port to non DOS computers. Cannot be edited in standard word processing.
)
.BAB (Babylonian ASCII version of FDT. Only fracture data stored. Can be ported to non DOS computers. No standard word processing.
.DCM (Standard ASCII version of FDT. Only fracture data stored. Can be ported to most computers. Can be edited by standard 
word processing. Large files.
)
.SAM (ASCII) .ORS (ASCII) .PCS (ASCII, for conditioned data)
.F2D (ASCII, fracture trace data)
ANL-EBS-MD-000027 REV 03 6-34 September 2004 
Frac. 
Set 
Model 
Type 
Generation 
Region & 
Dimension 
Orientation 
Trend, Plunge 
Dist. 
Type 
K or 
K1/K2 
dispersion 
Size 
Eqv. 
Radius 
Dist. 
Type 
Mean 
SD 
Max. 
Min. Elongation Aspect 
Ratio 
Termin. 
% Intensity 
S1s BART 100x100x100 035/06 BiBing -39.5/-4.5 1.00 
TPow 
(3.5) 8/1 NA NA 10 0.40 
S2s BART 100x100x100 124/04 BiBing -11.8/-6.2 1.00 
TPow 
(3.5) 8/1 NA NA 10 0.30 
S3s BART 100x100x100 209/47 BiBing -72.6/-8.8 1.00 
TPow 
(3.5) 8/1 NA NA 10 0.10 
VPP Baecher 100x100x100 237/82 Fisher 05 1.00 
Power 
(3.5) NA NA NA 0 0.16 
S1l BART 100x100x100 035/06 BiBing -39.5/-4.5 1.00 
TPow 
(3.5) 50/4 NA NA 15 0.2 
S2l BART 100x100x100 124/04 BiBing -11.8/-6.2 1.00 
TPow 
(3.5) 50/4 NA NA 15 0.2 
S3l BART 100x100x100 209/47 BiBing -72.6/-8.8 1.00 
TPow 
(3.5) 50/4 NA NA 15 0.15 
NOTE: 
See Figure 6-17 for detailed line survey source DTNs. The parameter, K or K1/K2 dispersion is determined using CLUSTRAN (with the exception of 
VPP, or vapor-phase parting, which is determined visually by comparing simulated stereonets to observed stereonets). The parameter, Size Eqv. 
Radius is the mean radius (m). The power law distribution is used for the parameter, Dist. Type. The power law is selected because the fracture 
process generally follows power law physics, such that the number of fractures greater than a given length (x) is proportional to 1/x raised to the power 
law exponent. The parameter, Intensity is selected to maintain the proportion of fractures in each set. 
Figure 6-18. FracMan Input Sheet for the Tptpmn 
Drift Degradation Analysis 

Drift Degradation Analysis 
length in a hierarchical model. A truncated power law is used because the short and long 
fractures are defined for a given window of trace length (Figure 6-16). Vapor-phase partings are 
not subjected to a truncated power law distribution, because they are first-occurring features with 
a long trace length. The other sets are developed using Baecher Revised Terminations model 
type in order to simulate the truncation probability. 
Based on the long fractures, the trend and plunge of the poles are used to set the mean 
orientations for each of the sets. CLUSTRAN (Shanley and Mahtab 1974 [DIRS 169199]), a 
structural geology statistical software application, is used to determine both mean pole values 
and dispersion of fractures around the mean. CLUSTRAN is a computer program that analyzes 
fracture data using stereographic projection techniques. Stereographic projection involves the 
projection of points from a spherical surface (typically the lower hemisphere of the surface) to a 
planar surface (the stereographic plot surface). The purpose of the CLUSTRAN program is to 
plot and analyze the orientations of fracture directional data sets for the purpose of identification 
and analysis of clusters of poles from which sets and their dispersion can be identified. 
Conventional identification of fracture sets involves plotting of the fracture poles onto a 
stereographic net, followed by contouring of the poles and use of the concentrations of data to 
identify clusters that indicate numbers of sets and directional trends. The use of CLUSTRAN 
eliminates the conventional visual interpretation of data, presenting a more objective 
interpretation through evaluation of set clusters and dispersion directly using statistical 
evaluation techniques. 
CLUSTRAN statistically analyzes the identified longer fractures for non-randomness. The 
program locates clustered subsets of the data by using an algorithm described by Shanley and 
Mahtab 1974 [DIRS 169199]). This algorithm uses an iterative process to identify the 
statistically optimal data clusters. In the algorithm, dense points (those data points that have at 
least n neighbors within a cluster radius R) are first identified. The remaining non-dense points 
are then allocated to the nearest dense point. Finally, the dense points are grouped into clusters 
by chaining them together by segments of length R or less. In the original algorithm developed 
by Shanley and Mahtab (1974 [DIRS 169199], p. 2), both variables R and n had to be selected by 
the user. In CLUSTRAN, the integer n is calculated from a Poisson statistical model such that 
the probability of n points occurring within the radius R by chance alone is no more than 
5 percent. Because a data set can be clustered many different ways depending on the cluster 
radius, Shanley and Mahtab (1974 [DIRS 169199], p. 3) developed an objective function, F(P), 
as a tool for selecting the best clustering of the data set. This function is the sum of the 
within-cluster distances squared with the between-cluster distances squared. The best partition, 
and best value of R, occurs where the F(P) is minimum. This condition means that the distances 
have been minimized by trading off within-cluster distances with between-cluster distances. 
Thus, the CLUSTRAN cluster analysis process is iterative. The user selects a trial value for the 
cluster radius, R. CLUSTRAN identifies the clusters based on this R and evaluates for the 
objective function, F(P). Other values of R are tried over a broad range until the lowest 
objective function value is found. CLUSTRAN will evaluate the iterative runs and select the 
correct R to use based on the lowest F(P) value. 
Once clusters have been identified from the data set, CLUSTRAN carries out statistical analysis 
on each cluster. First, moment-of-inertia analysis is carried out. This analysis treats each data 
point as a point of mass on a unit hemisphere. The maximum moment-of-inertia goes through 
ANL-EBS-MD-000027 REV 03 6-35 September 2004 

Drift Degradation Analysis 
the center of the cluster, the intermediate moment parallels the long axis, and the minimum 
moment is perpendicular to the long axis. The Bingham probability distribution is applicable to 
moment-of-inertia analysis (DOE 2004 [DIRS 170474]). It provides two concentration 
parameters, K1 and .2, that describe the shape and concentration of the data set. Then, using the 
output from the Bingham distribution, the test for circular symmetry is performed to yield 
bipolar and girdle test statistics. 
If the distribution is symmetric according to these previous tests, then additional tests are 
performed. The Dimroth-Watson distribution (the circularly symmetric form of the Bingham 
distribution) yields a concentration parameter to describe the data cluster (DOE 2004 
[DIRS 170474]). If the concentration parameter is near zero the distribution is random, whereas 
if the concentration parameter is large, the points are concentrated. Further, if the parameter is 
less than zero the distribution is symmetric bipolar, and if the parameter is greater than zero the 
distribution is a symmetric girdle. 
If the cluster is symmetric and bipolar, the vector mean and associated Fisher statistics are also 
calculated. The Fisher distribution (equivalent to a normal distribution in univariate statistics) 
does not apply to moment-of-inertia analyses, but to vector analyses (DOE 2004 
[DIRS 170474]). It is also strictly applicable to the polar distribution, but bipolar distribution 
may be treated by using the axis ends nearest each other. The Fisher mean is the vector sum of 
the directions, where each fracture pole direction is treated as a unit vector. These parameters, 
mean orientation and dispersion, are inputs into the FracMan code. Just as one would set the 
variance of a univariate parameter, distributions of structural geology vectors are described by a 
mean orientation and a dispersion about the mean direction. 
Several comparisons are made to confirm that the results of the FracMan output are producing a 
simulated fracture geometry that resembles the actual rock mass. Comparison is made between 
the detailed line survey data pole plots and the FracMan data pole plots. Correct selection of the 
mean orientation as well as the correct dispersion, K, is key to obtaining an acceptable 
distribution of poles on the stereonet. The results of this comparison are presented in the 
following section for the Tptpmn. Stereonets generated by the FracMan realization and 
stereonets from the observed detailed line survey data show reasonable comparisons for both the 
mean orientation and dispersion about the mean (Figure 6-19). There are several methodologies 
to modeling the dispersion of real fracture data. One is to completely encompass the full range 
of observed data. When fitting the dispersion in this style the dispersion factor is small, typically 
less than 20 for a Fisher K value. However the range of variability is large. An alternative 
method focuses on a tighter description of the observed data, considering that the extent of the 
observed data is below the level of significance for data on the stereonet. For example, with 
100 data points, a 1 percent count circle needs to have encompassed approximately four data 
points in order for the level of significance to be distinguishable from a random data set. There 
are no random sets in nature so we wish to depict sets that meet the nonrandomness criteria. A 
larger K value will accomplish this. Larger K values depict a smaller dispersion about the mean 
orientation. This is the style of fit used for these analyses. 
Comparison of the observed to synthetic fracture geometry for each set is given qualitatively in 
the stereonet plots of poles given in Figure 6-19 and quantitatively in Table 6-2. The criteria for 
adequate agreement of the fracture geometry from observed to synthetic models are: 1) that the 
ANL-EBS-MD-000027 REV 03 6-36 September 2004 

Drift Degradation Analysis 
mean orientation is adequately estimated, and 2) that a large portion of the observed data 
dispersion is encompassed but not every pole. Analysis of data on the stereonet requires that sets 
are identified from data that are significantly different from a uniform distribution on the 
stereonet. The outer portions of a distribution are similar to the tail of a univariate distribution. 
The goal was to simulate the main portion of the distribution and not the tail of the distribution. 
Therefore, the synthetic data pole plots are more tightly clustered than the observed pole plots for 
this reason (Figure 6-19). 
The goal of the orientation comparison is, therefore, to represent the major sets with reasonable 
conformance to the observed mean orientations and the observed spread or dispersion about the 
mean. Not every fracture observed will be represented in the FracMan realizations since the 
synthetic model represents a reasonable facsimile of the rock mass, but not a replicate. 
More fractures will be displayed in the 100-m on a side FracMan cube than are observed in the 
detailed line survey data. The detailed line survey data samples a small surface area compared to 
full periphery geologic mapping and considerably fewer fractures are observed than are present 
in the 100-m cube. The primary comparison to make between the rock mass geometry and the 
FracMan geometry is to compare full periphery geologic maps. The FracMan geometry allows 
for the same kind of sampling as the original data. For each of the following sections a direct 
comparison is presented to confirm that the FracMan geometry resembles the observed 
geometry. Intensity controls the number of fractures and the check for intensities relies on the 
comparison of FracMan full periphery geologic maps to the observed full periphery geologic 
maps for validation. If the intensity from the FracMan full periphery geologic maps and the 
observed full periphery geologic maps are similar and trace length comparisons are good, the 
validation is considered satisfactory. 
ANL-EBS-MD-000027 REV 03 6-37 September 2004 

Drift Degradation Analysis 
NOTE: The Tptpmn FracMan data include 15 samples, or excavations, extracted from the FracMan cube at 
random locations resulting in 2313 fractures. The Tptpmn mapping data was selected by sampling the full 
periphery geologic maps until a similar number of fractures could be compared to the FracMan data. The 
source DTNs for the full periphery geologic map are: GS960908314224.020, GS000608314224.006, 
GS960908314224.015, GS960908314224.016. 
Figure 6-19. Comparison of the Observed Tptpmn Fracture Poles to the FracMan Fracture Poles 
ANL-EBS-MD-000027 REV 03 6-38 September 2004 

Drift Degradation Analysis 
Table 6-2. Comparison of Data from Underground Mapping and FracMan for the Tptpmn 
Set 
Number 
Observed 
Orientation 
Strike/Dip 
(Trend/Plunge) 
FracMan 
Orientation 
(Strike/Dip) 
Inter-Fracture Median 
Distance (m) 
Trace Length 
Median from Full 
Periphery Geologic 
Maps (m) 
Trace Length 
Median from 
FracMan (m) Observed FracMan 
Set 1 120/84 (030/06) 125/84 0.48 0.79 3.3 2.8 
Set 2 215/88 (125/02) 214/86 1.08 1.29 2.8 3.1 
Set 3 302/38 (212/52) 299/43 3.40 3.16 3.7 3.6 
Vapor-
Phase 329/14 (239/76) 327/08 2.46 1.48 3.5 3.4 
Parting 
Source: DTNs for tunnel mapping include: GS960908314224.020 [DIRS 106059]; GS000608314224.006 
[DIRS 152572]; GS960908314224.015 [DIRS 108372]; GS960908314224.016 [DIRS 108373]; 
GS971108314224.025 [DIRS 106025]; GS960708314224.008 [DIRS 105617]; GS000608314224.004 
[DIRS 152573]; GS960708314224.010 [DIRS 106031]; GS960908314224.014 [DIRS 106033]; 
GS970208314224.003 [DIRS 106048]; GS970808314224.010 [DIRS 106050]; and 
GS971108314224.028 [DIRS 106047]. 
NOTE: Trace length medians are taken from a compilation of tunnel mapping and synthetic tunnel samples from
FracMan (see Figure 6-23 for the trace-length distribution). 
6.1.6.4.5 Fracture Intensity 
A number of fracture intensity (e.g., the relationship of fracture spacing, orientation and areal 
extent within a rock mass) measures are typically used for quantification of field measurements. 
These include (Dershowitz and Herda 1992 [DIRS 104893]): 
 P
102  the number of fractures/length of a scanline 
 P21  the length of fracture traces/area of exposure from a full periphery map 
 P32  area of fractures/volume of the rock mass 
Thus, P10 represents a linear measurement of fracture intensity, P21 an areal measurement and P32 
is a volumetric measure. The first two measures of intensity can be made from available detailed 
line surveys and full periphery geologic maps. The P32 measure is the most accurate measure of 
fracture intensity, but must be estimated since it is impossible in practice to provide a volumetric 
measurement since sampling is via a line or tunnel surface mapping. 
The general relationship between the fracture intensity P32 and the mean fracture spacing, S, 
along a line is given by Dershowitz and Herda (1992): 
P32 = C/S = C P10 (Eq. 6-4) 
where C is a constant that depends on the orientation distribution of the fractures. Dershowitz 
and Herda (1992, p. 763) suggested a range of expected values for C between 1.0 and 3.0 and a 
value of 2.0 for a uniform distribution of orientations. 
2 The term P stands for persistence. 
ANL-EBS-MD-000027 REV 03 6-39 September 2004 

Drift Degradation Analysis 
Equation 6-4 has been derived for the simplified case where the orientation distribution is 
constant. For different orientation distributions, the equation becomes inaccurate for large 
variations about the mean pole orientation. In the general case, the P32 value can be expressed 
as: 
C
P
32 
(Eq. 6-5) 
=
sin( )f( )d 
....
... 
. 
p
.
0 
..
. 
 
1
d 
.
.
where d is the inter-fracture distance along a line, and f(.) is the orientation probability density 
function. 
In this report, the FracMan model uses a constant P32 for each set of fractures, which is based on 
the consideration that there is no spatial heterogeneity in intensity. There are a few discrete 
changes in intensity observed in the detailed line survey and full periphery geologic map data, 
but for the most part, the average intensity is constant as depicted by a linear cumulative 
fracture number versus stationing plot for each of the lithostratigraphic units. As shown in 
Figure 6-20, a plot of the cumulative number of fractures versus distance along the ESF for the 
Tptpmn is given based on detailed line survey data. This data shows that a roughly linear 
relationship exists between fracture frequency and distance for the Tptpmn within the ESF at a 
slope of approximately 2 fractures per meter. A distinct break in slope occurs over a 1000-m 
section termed the intensely fractured zone in which the fracture frequency roughly doubles. 
This zone is considered to be anomalous as it is not observed in any other locations in the 
underground excavations, and is excluded from FracMan. Modeling studies (see Section 6.3.2.1) 
examine stability of the intensely fractured zone using continuum-based modeling methods. The 
linear character of the cumulative fracture frequency plot demonstrates that little spatial 
heterogeneity of the fracture intensity exists in the Tptpmn overall. 
ANL-EBS-MD-000027 REV 03 6-40 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-41 September 2004 
ESF0100020003000400050006000700080009000100002000300040005000600070008000Stationing (m)
Cumulative Number of Fractures~2 fractures/mIntensely-fractured zone, 
~4.5 fractures/m~2 fractures/m 
NOTE: The fracture frequency shows a break in slope from approximately 2 fractures per meter to over 4 fractures 
per meter over an approximately 1000-m section of the ESF. This region is termed the intensely fractured 
zone and is not observed in the ECRB Cross-Drift. 
Figure 6-20. Cumulative Number of Fractures Versus Stationing for Detailed Line Surveys Along the ESF 
6.1.6.4.6 Comparison of FracMan Synthetic Fracture Geometry and Field Data 
Comparison of the FracMan-generated synthetic fracture geometry to the field fracture data is 
performed both qualitatively and quantitatively. From a qualitative standpoint, the FracMan 
program is used to create equivalent full periphery geologic maps by creation of virtual tunnels 
parallel to the ESF within the FracMan synthetic rock mass. Visual comparison is made between 
the FracMan and field full periphery maps are performed to ensure that the model produces the 
primary structural features evident in the field data. Quantitative comparisons of fracture trace 
length, spacing and orientation are made by comparison of the statistical distributions. 
Qualitative ComparisonTo insure that the synthetic fracture network is not only statistically 
representative, a qualitative comparison of random full periphery geologic maps from the ESF 
and FracMan synthetic full periphery geologic maps created at the same orientation are visually 
compared (Figure 6-21). This is a direct comparison between actual full periphery geologic 
maps from the ESF to synthetic full periphery geologic maps from FracMan. The comparison is 
made to evaluate the general fracture intensity and length with the same biases inherent in the 
field full periphery geologic mapping. Based on the professional expertise and experience of 
project geologists, the FracMan full periphery geologic maps are acceptably conditioned to be 
visually similar to observed full periphery geologic mapping. 

Drift Degradation Analysis 
Quantitative ComparisonThe detailed line survey data and full periphery geologic maps are 
used to condition FracMan to develop representative fracture trace lengths and inter-fracture 
distance. The same comparisons of the mapping data and FracMan output apply to this 
realization. Table 6-2 provides a quantitative comparison of the orientation of the sets and trace 
lengths from the full periphery geologic maps and samples from FracMan. Intensity 
(inter-fracture distance) from FracMan and inter-fracture distance from the detailed line surveys 
is also compared. Because no line surveys were conducted on the full periphery geologic maps, 
detailed line survey data were used for generating inter-fracture distance data, which was 
compared to 1 m diameter (synthetic) boreholes randomly drilled in the same orientation in the 
FracMan rock mass. By sampling the FracMan rock mass in the same orientation as the detailed 
line survey data, the need for a correction to either data set is eliminated. Distribution 
comparisons of inter-fracture distance from both FracMan and detailed line survey data are 
shown in Figure 6-22, show a reasonable comparison, both in the univariate statistical mean as 
well as the general shape of the distributions. 
The comparison in Figure 6-23 confirms that a reasonable conformance exists between the trace 
length distribution from FracMan and the observed trace length distribution. To develop a true 
comparison of trace length between the observed and the synthetic data, length data from 
observed and synthetic full periphery geologic maps are compared. As with the inter-fracture 
distance comparisons, the full periphery geologic maps from FracMan are sampled on the same 
orientation as the observed data to eliminated the need to correct either data set. The orientation 
comparison was previously presented in Figure 6-19. 
In summary, a FracMan fracture region was constructed which is calibrated to the observed data 
for orientation and its dispersion, size and its distribution, and intensity (as measured by 
interfracture distance) and its distribution on a set by set basis. In addition, any biases due to 
sampling were effectively removed by using the same sampling style as the observed data 
collection when comparing the synthetic and the observed data sets. 
ANL-EBS-MD-000027 REV 03 6-42 September 2004 

Drift Degradation Analysis 
Source: 
DTNs: GS990408314224.004 [DIRS 108405]; GS000608314224.006 [DIRS 152572]; GS960908314224.015 [DIRS 108372]; GS960908314224.016 
[DIRS 108373]; GS960908314224.017 [DIRS 108376]; GS970108314224.002 [DIRS 107490]. 
NOTE: 
The purpose of this figure is to illustrate the geologic structure contained on a full periphery geologic map. The annotated information on this figure is not 
intended to be legible. 
Figure 6-21. 
Comparison of (a) Full Periphery Geologic Maps from the Tptpmn in the ESF (b) with Simulated Full Periphery Geologic Maps from 
the FracMan Cube 
ANL-EBS-MD-000027 REV 03 6-43 September 2004 

60 
iObserved ESF Data 
Synthetc FracMan Data 
30 
50 
25 
iObserved ESF Data 
Synthetc FracMan Data 
0 
5 
10 
15 
20 
25 
30 
i0 
5 
10 
15 
20 
25 
30 
iFrequency Percent 
Observed ESF DATA 
Synthetc FracMan Data 
Frequency Percent 
Observed ESF Data 
Synthetc FracMan Data 
ANL-EBS-MD-000027 REV 03 6-44 September 2004 
Frequency Percent 
Frequency Percent 
40 
20 
15
30 
10
20 
5
10 
0
0 
0 5 10152025 0 5 10152025 
Inter-Fracture Distance (m) Inter-Fracture Distance (m) 
a. Set 
1 
b. Set 2 
0 5 10 15 20 25 0 5 10152025 
Inter-Fracture Distance (m) Inter-Fracture Distance (m) 
c. Set 
3 
d. Vapor-Phase Parting 
Source: 
DTNs for the detailed line survey data include GS971108314224.025 [DIRS 106025]; GS960708314224.008 [DIRS 105617]; GS000608314224.004 
[DIRS 152573]; GS960708314224.010 [DIRS 106031]; GS960908314224.014 [DIRS 106033]; GS970208314224.003 [DIRS 106048]; 
GS970808314224.010 [DIRS 106050]; GS971108314224.028 [DIRS 106047]. 
Figure 6-22. Distribution Comparisons of Inter-Fracture Distance 
Drift Degradation Analysis 

30 
iObserved ESF Data 
Synthetc Fracman Data 
35 
30
25 
25 
Observed ESF Data 
Synthetic FracMan Data 
0 
5 
10 
15 
20 
25 
30 
Frequency Percenti0 
5 
10 
15 
20 
25 
Frequency PercentObserved ESF Data 
Synthetc FracMan Data 
Observed ESF Data 
Synthetic FracMan Data 
ANL-EBS-MD-000027 REV 03 6-45 
September 2004 
Frequency Percent
Frequency Percent
20 
20 
15 
15 
10 
10 
5 
5 
0 
0 
0 5 1015202530 0 5 1015202530 
Trace Length (m) Trace Length (m) 
a. Set 1 b. Set 2 
0 5 10 15 20 25 0 5 10 15 20 25 30 
Trace Length (m) Trace Length (m) 
c. Set 3 d. Vapor-Phase Parting 
Source: The source DTNs for the full periphery geologic map are: GS960908314224.020, GS000608314224.006, GS960908314224.015, GS960908314224.016. 
Figure 6-23. Comparison of Sampled Fracture Trace Lengths from the FracMan Cube and Full Periphery Geologic Maps from the ESF for 
the Tptpmn 
Drift Degradation Analysis 

Drift Degradation Analysis 
6.2 THERMAL-MECHANICAL CALCULATION 
Coupled thermal-mechanical processes in the rock mass surrounding the geologic repository at 
Yucca Mountain are examined in this section. This thermal-mechanical calculation investigates 
the temperature history throughout the preclosure and postclosure periods of the repository, and 
stress changes, .sij, due to temperature change, according to the following relation (Itasca 
Consulting Group 2002 [DIRS 160331], Manuals/3DEC/Optional Features/Section 1: Thermal 
Option, Section 1.2.3): 
.sij =dij 3Ka.T (Eq. 6-6) 
where dij is the Kronecker d (unit matrix), a is the coefficient of thermal expansion (C-1), K is 
the bulk modulus (Pa), and .T is the change in temperature (C). The coupled 
thermal-mechanical calculation was conducted by two sets of calculations: the drift scale 
(described in this section) and the coupled regional and drift scale calculations (described in 
Appendix C). 
The drift scale thermal-mechanical calculation consists of the temperature history (thermal) 
calculation and the thermal stress (mechanical) calculation. The thermal part of the drift scale 
calculation was performed by the NUFT thermohydrology software simulating two-dimensional 
drift scale thermal-hydrologic behavior. The temperature history results from the NUFT code 
were imported to the UDEC discrete-element software and the FLAC finite-difference software 
to calculate the thermal stress around the emplacement drift (see Appendix U). UDEC and 
3DEC (the three-dimensional equivalent of UDEC) were used to model the effects of the thermal 
stress and to conduct a rockfall analysis associated with the previous thermal stress calculation. 
Details of the thermal stress calculation and the rockfall analysis for nonlithophysal and 
lithophysal units are presented in Sections 6.3.1.3 and 6.4.1.2, respectively. 
The drift scale calculations (both thermal and mechanical) consider an infinite extent 
(perpendicular and in the direction of the drifts) of the repository; consequently, they are 
two-dimensional (a single drift included in the calculation), with a symmetry boundary condition 
on a plane halfway between the emplacement drifts3. The coupled regional and drift scale 
thermal-mechanical calculation (Appendix C) was planned and conducted to support this drift 
scale calculation by assessing repository-scale effects, including edge effects and the effects of 
finite repository size and depth on predicted temperatures and stresses. These calculations are 
three-dimensional, and analysis was carried out in two steps. First, the regional scale 
thermal-mechanical calculation was used to determine temperature and stress changes on the 
scale of the entire mountain. In the next step, the drift scale thermal-mechanical analysis was 
performed such that boundary conditions for temperature and stress fields (functions of time) 
were determined from the regional scale calculation. Thus, this calculation did not use any 
simplifying assumptions (e.g., infinite extent of the repository) for the boundary conditions. 
Both components of the regional and drift scale thermal-mechanical calculations were performed 
using FLAC3D. Because the goal of the calculation was to support the drift scale calculation, 
details of the calculation and results are presented in Appendix C. A comparison of temperatures 
3 The symmetry boundary condition results in zero displacements perpendicular to the boundary and zero heat flux 
across the boundary. 
ANL-EBS-MD-000027 REV 03 6-46 September 2004 

Drift Degradation Analysis 
and stresses as calculated by the drift scale and the coupled regional and drift scale calculations 
is presented at the end of this section. 
The thermal part of the drift scale calculation was performed by the NUFT thermohydrology 
software, applying a two-dimensional line-averaged heat source, drift scale, thermohydrologic 
(LDTH) sub-model, which is described in Multiscale Thermohydrologic Model (BSC 2004 
[DIRS 169565]). The LDTH sub-model is a part of the multiscale thermohydrologic model that 
is created by the NUFT software. The LDTH sub-model accounts for hydrologic effects in the 
rock mass, and conductive and radioactive heat transfer mechanisms around the drift. Effects of 
the preclosure forced ventilation are accounted for by removing a percentage of the heat given 
off by the waste package (Section 5.1.2). A non-backfilled and mean infiltration version of the 
LDTH sub-model L2C3 (coordinates: E170731, N234973) was selected and extracted among the 
31 LDTH sub-models. The L2C3 LDTH sub-model is used to compute temperature history of 
the emplacement drift and surrounding areas throughout the preclosure and postclosure periods. 
The L2C3 LDTH sub-model location selected has the following characteristics of interest: 
 Approximately the geometric center of the license application reference repository 
layout (BSC 2004 [DIRS 164519]). 
 The repository horizon is located approximately 281 m below the ground surface and 
327 m above the water table. This elevation puts the repository horizon at 
approximately 1057 m above sea level. 
 The repository horizon is located in the Tptpll with approximately 34 m of Tptpll above 
the repository horizon and 68 m of Tptpll below the repository horizon. 
 The mean infiltration conditions have surface infiltration rates of 12.0 mm/year during 
the first 600 years of emplacement (present day climate), 40.8 mm/year from 600 years 
to 2000 years (monsoonal climate), and 63.2 mm/year from 2,000 years on (glacial 
transition climate). 
 The ground surface temperature is fixed at 16.9C, and the water table temperature is 
fixed at 29.2C. 
In addition to the LDTH sub-model, updated thermal and hydrologic properties were used for the 
repository and non-repository rock units. The thermal and hydrologic properties are presented in 
Section 4.1.6 and 4.1.8, respectively. Details of the data preparation for input files of the LDTH 
sub-model are described in Multiscale Thermohydrologic Model (BSC 2004 [DIRS 169565]). 
Three major cases of the drift scale thermal calculation were carried out, including: 
 Case 1: Base case calculation with 1.45 kW/m initial heat load and 50 years preclosure 
ventilation (90 percent heat removal ratio, Section 5.1). 
 Case 2: Sensitivity calculation for thermal properties of repository rock material 
(Tptpll) with 1.45 kW/m initial heat load, 50 years preclosure ventilation, and 90 percent 
ANL-EBS-MD-000027 REV 03 6-47 September 2004 

Drift Degradation Analysis 
heat removal ratio. Values of thermal conductivity and specific heat one standard 
deviation less than the mean values were used: 
- Thermal Conductivity (DTN: SN0404T0503102.011 [DIRS 169129]): 1.64 W/m-K 
(= 1.89 W/m-K  one standard deviation [0.25 W/m-K]) for wet conditions and 1.03 
W/m-K (= 1.28 W/m-K  one standard deviation [0.25 W/m-K]) for dry conditions. 
- Heat Capacity: 811 J/kg-K (= 954 J/kg-K  one standard deviation [143 J/kg-K]). 
 Case 3: Sensitivity calculation for heat removal ratio. 70 percent heat removal ratio was 
used for the preclosure ventilation (Section 5.1). 
The LDTH sub-model that was used in the thermal-mechanical analysis presented in this 
document has been superseded by a new LDTH sub-model (DTN: LL030808623122.036 
[DIRS 165790]). The new LDTH sub-model updated several input parameters including rock 
mass thermal property data and preclosure ventilation efficiency data. The heat capacity data 
used in the thermal analyses were preliminary and have been superseded by Heat Capacity and 
Thermal Expansion Coefficients Analysis Report (BSC 2003 [DIRS 164670], Table 6-5) and 
DTN: SN0307T0510902.003 [DIRS 164196] (see Appendix E, Table E-16). In this document, 
heat capacity values for the range of T = 95C only were utilized for the thermal calculations 
using the LDTH sub-model (Table E-16). Because consideration of latent heat effects above the 
boiling point is built into the NUFT code, the high heat capacity value at the temperature range 
of 95 to 114C (Table E-16) were not used in the thermal calculations in this document. The 
new LDTH sub-model uses a drift location-dependent and time-dependent heat removal ratio 
(DTN: MO0306MWDALAFV.000 [DIRS 163961]) instead of a constant heat removal ratio 
(Section 5.1.2) as was assumed in the rock mass temperature calculations performed in this 
document. This new logic considers that ventilation air will have a varying heat removal 
capacity as it travels from the entrance to the exit of an emplacement drift. The heat removal 
capacity will also vary as a function of time as both the waste package power output and rock 
mass temperature change (BSC 2004 [DIRS 169862]). These changes could potentially cause a 
significant difference in drift wall temperature during the preclosure period. Further details of 
the new LDTH sub-model can be found in Multiscale Thermohydrologic Model (BSC 2004 
[DIRS 169565]). 
Impact analyses were conducted regarding the new LDTH sub-model and are presented in 
Appendix Q (Section Q2). The impact analyses show that the use of the new LDTH sub-model 
primarily impacts preclosure temperature. The impact on the prediction of rock mass stress and 
drift degradation is insignificant. 
Decay curves of the linear heat load used in the calculation cases are presented in Figure 6-24. 
The original linear heat decay curve (no ventilation) was obtained from D&E/PA/C IED 
Subsurface Facilities (BSC 2004 [DIRS 167369]). Ninety percent of the constant ventilation 
heat removal ratio (Section 5.1) was applied for Cases 1 and 2, while 70 percent of constant heat 
removal ratio (Section 5.1) was used in Case 3. 
ANL-EBS-MD-000027 REV 03 6-48 September 2004 

Drift Degradation Analysis 
Temperature histories at the drift crown for the cases of the drift scale thermal calculations are 
presented in Figure 6-25. The results exhibited the temperature increase from base case (Case 1) 
to sensitivity calculations (Cases 2 and 3). In particular, Case 3 showed a significant temperature 
increase at the preclosure period. The peak temperate for Case 1 was 138C at around 75 years, 
while Cases 2 and 3 were 161C and 153C at around 75 years, respectively.
Linear Heat Load (W/m) 
1600 
1400 
1200 
1000 
800 
600 
400 
200 
0 
0.1 1 10 100 1000 10000 
Time (years) 
lion l) l)no ventiatCases 1 & 2 (90 % heat removaCase 3 (70 % heat remova
Source File: DTN: MO0408MWDDDMIO.002, file Heat_Decay_Cal_LA1450.xls. 
NOTE: The no ventilation curve is from BSC 2004 [DIRS 167369]. Cases 1 and 2 use the 90 percent heat removal 
curve while Case 3 uses the 70 percent heat removal curve. 
Figure 6-24. Heat Decay Curves for Thermal Calculations 
ANL-EBS-MD-000027 REV 03 6-49 September 2004 

Drift Degradation Analysis 
Temperature-History at Drift Crown 
1.45 kW/m linear heat load, 50 years pre-closure ventilation 
180 
Temperature (oC) 
160
140
120
100
80
60
40
20
0 
1 10 100 1000 10000 100000 
Years 
Case 1 Case 2 Case 3 
Source File: DTN: MO0408MWDDDMIO.002, file LA1450_NUFT_Temp_crss-sctn3.xls. 
Figure 6-25. Temperature History at the Drift Crown Due to the Linear Heat Load Presented in 
Figure 6-24 
A comparison of temperature histories in the drift crown for Case 1, as determined in the drift 
scale calculation (NUFT) and the coupled regional and drift scale calculations (FLAC3D) for the 
conditions in the middle of the repository, is shown in Figure 6-26. The agreement between 
histories is quite good. With the exception of the state at 10,000 years after waste emplacement, 
the temperature differences between the two calculations are less than 10C. 
ANL-EBS-MD-000027 REV 03 6-50 September 2004 

Drift Degradation Analysis 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-26. Comparison of Temperature Histories at Tunnel Crown for Case 1 Calculated Using NUFT 
and FLAC3D 
Stresses in the drift wall and crown for conditions in the middle of the repository, as predicted by 
two calculations (drift scale [NUFT-FLAC] and coupled regional and drift scale [FLAC3D]), are 
shown for 10 years, 100 years, and 1,000 years after waste emplacement in Figures 6-27, 28, and 
29, respectively. NUFT-FLAC results are presented from the calculation for lithophysal rock 
mass Category 4 (discussed in Section 6.4), which has the same Youngs modulus as the value 
used in the coupled regional and drift scale calculation. Agreement of the tangential stresses in 
the crown is excellent at the three times presented. As expected, the two-dimensional calculation 
(NUFT-FLAC) predicts a slightly higher tangential stress in the crown after 1,000 years of 
heating. The most significant difference between the two calculations is the vertical stress after 
100 and 1,000 years. The coupled regional and drift scale calculations (FLAC3D) show an 
increase in the vertical stress (in the wall after 100 years and 1,000 years, but also throughout the 
repository horizon after 1,000 years) because of the effect of the finite repository size and elastic 
restoring stresses caused by the heat-induced deformation. This effect could not be accounted 
for in the drift scale calculation in which the average vertical stress is determined by the weight 
of the overburden. The drift scale calculation stress predictions are justified for use in the 
analysis of drift degradation, because the increase in the vertical stress in the wall (not accounted 
for in the two-dimensional calculation) is not significant. 
ANL-EBS-MD-000027 REV 03 6-51 September 2004 

Drift Degradation Analysis 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-27. Comparison of Stresses Around the Drift Between the NUFT-FLAC and FLAC3D 
Predictions After 10 Years of Heating 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-28. Comparison of Stresses Around the Drift Between the FLAC and FLAC3D Predictions After 
100 Years of Heating 
ANL-EBS-MD-000027 REV 03 6-52 September 2004 

Drift Degradation Analysis 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-29. Comparison of Stresses Around the Drift Between the NUFT-FLAC and FLAC3D 
Predictions After 1,000 Years of Heating 
The drift stability analysis presented in this report was carried out for temperature and stress 
conditions in the middle of the repository. However, the temperatures and stresses for the 
conditions at the edge of the repository are investigated using the coupled regional and drift scale 
(FLAC3D) calculations (the actual location considered and other details are described in 
Appendix C). The temperature history from the coupled calculations for the edge of the 
repository, compared with the NUFT results for the center of the repository, are shown in 
Figure 6-30. As expected, the temperatures at the edge of the repository will be smaller than 
temperatures in the middle of the repository. 
The stress profiles around the emplacement drift located at the edge of the repository10, 
100 and 1,000 years after waste emplacementare shown in Figures 6-31 through 6-33. 
Stresses at the edge of the repository are, in general, smaller than in the middle of the repository. 
Smaller vertical stress at the repository edge is due to smaller overburden. However, the most 
significant difference between stress conditions at the edge and in the middle is in the horizontal 
stress 1,000 years after waste emplacement. The horizontal stress is approximately 5 MPa 
smaller at the edge compared to the middle of the repository (Figure 6-32). After a heating time 
when the drifts start to thermally interact with each other, conditions of almost complete 
confinement (idealized in two-dimensional models by symmetry conditions on the plane 
half-way between the drifts) exist in the middle of the repository, leading to increased horizontal 
stresses. The confinement and temperatures at the edge are smaller (than in the middle of the 
repository) resulting in smaller horizontal stresses. It appears from these results that limiting the 
drift degradation analysis to thermally induced stresses in the middle of the repository is 
justified. 
ANL-EBS-MD-000027 REV 03 6-53 September 2004 

Drift Degradation Analysis 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-30. Comparison of Temperature Histories at Tunnel Crown for Case 1 Calculated Using NUFT 
(at the Center of the Repository) and FLAC3D (for the Edge of the Repository) 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-31. Comparison of Stresses Around the Drift Between the NUFT-FLAC and FLAC3D 
Calculations for Edge of the Repository After 10 Years of Heating 
ANL-EBS-MD-000027 REV 03 6-54 September 2004 

Drift Degradation Analysis 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-32. Comparison of Stresses Around the Drift Between the NUFT-FLAC and FLAC3D 
Calculations for Edge of the Repository After 100 Years of Heating 
Source File: DTN: MO0408MWDDDMIO.002, FLAC 3D Inputs & Outputs\TM model. 
Figure 6-33. Comparison of Stresses Around the Drift Between the NUFT-FLAC and FLAC3D 
Calculations for Edge of the Repository After 1,000 Years of Heating 
ANL-EBS-MD-000027 REV 03 6-55 September 2004 

Drift Degradation Analysis 
6.3 ROCKFALL IN THE NONLITHOPHYSAL UNITS 
The assessment of rockfall in the nonlithophysal units is primarily based on a three-dimensional 
discontinuum analysis (3DEC analysis). This analysis is adequate for the wedge-type failure in a 
jointed rock mass, which has been validated in Section 7.7. A description of this set of analyses 
and a presentation of the results are provided in Section 6.3.1. An intensely fractured zone was 
observed in the ESF main loop between Stations 42+00 and 51+50 (Albin et al. 1997 
[DIRS 101367], p. 58). A 3DEC analysis is not suited for such highly fractured rock. Therefore, 
a three-dimensional continuum analysis with a ubiquitous joint model (FLAC3D analysis) was 
adopted to account for the effect of the highly fractured and anisotropic behavior of the rock 
mass in this limited zone as described in Section 6.3.2. The aforementioned analyses consider 
only fractures with trace lengths greater than 1 m. The impact of small-scale fractures (less than 
1-m trace length) for block forming is assessed using the key-block code DRKBA. A 
comparison of the results for including and excluding the small-scale fractures is provided in 
Section 6.3.3. The drift profile predictions considering wedge-type failure are provided in 
Section 6.3.4. 
It should be noted that in previous versions of this document (BSC 2001 [DIRS 156304]), 
rockfall in the nonlithophysal units was based on a Discrete Region Key Block Analysis 
(DRKBA). In this report, DRKBA analyses primarily provide a confirmatory role in the 
assessment of drift degradation. DRKBA analyses are documented in Appendix D. 
6.3.1 Three-Dimensional Discontinuum Analysis of Jointed Rock Mass for Wedge-Type 
Rockfall 
The three-dimensional discontinuum analysis is used for simulation of the mechanical behavior 
of the jointed rock mass in the nonlithophysal units for loading conditions with which stability 
response will be controlled by the fractures. 3DEC was selected for its capability of simulating 
fractured rock masses under both thermal and seismic loadings. The fractured rock mass is 
represented as a number of intact rock blocks that are separated by interface planes whose 
mechanical behavior is represented by a standard Coulomb slip criterion. The intact blocks are 
subdivided into tetrahedral finite difference zones and can be assigned suitable mechanical 
constitutive law (Itasca Consulting Group 2002 [DIRS 160331]). Due to the high intact rock 
strength in the nonlithophysal units, rock blocks are considered to behave elastically. 
It is important in the 3DEC analysis to include field fracture geometric data for modeling the 
nonlithophysal units. Because the fractures within the Tptpmn may be non-persistent in nature 
(with median trace lengths of approximately 3 m [see Table 6-2], which is smaller than the 
diameter of the tunnel), many fractures are of insufficient length to form a regular block. The 
fracture geometries used as input to 3DEC are derived from FracMan simulations as discussed in 
Section 6.1.6. Modifications to the 3DEC program have been made to accommodate the 
FracMan output; namely, the discontinuous nature of the fractures. In versions of the 3DEC 
program developed prior to the use described here, fractures are modeled as continuous in nature 
and thus it was impossible to have a fracture that ends in solid rock. The program was modified 
to provide the capability to allow contact points along a fracture trace to be assigned a particular 
material property. In other words, portions of a fracture plane could be assigned a standard 
Coulomb slip behavior, whereas others could be bonded to the opposing surface with the 
ANL-EBS-MD-000027 REV 03 6-56 September 2004 

Drift Degradation Analysis 
strength of the adjacent rock blocks, thereby creating fractures that have rock bridges along 
their surface. In this case, the rock bridge acts as a strong location along the fracture surface, but 
can still fail in shear or tension if the stresses so dictate. In this manner, it is possible to represent 
a discontinuous fracture system, but one in which breakage of solid rock can occur. 
Other enhancements added to 3DEC for rockfall modeling include: 
 Implementation of the free field boundary to provide a quiet or non-reflecting 
boundary for dynamic analysis with superposition of the P and S wave motions 
 Partial density scaling for dynamic analysis. 
Descriptions for these enhancements are provided in Appendix H. 
For each simulated fracture, the FracMan program provides the centroid, radius (fractures are 
considered to be circular), dip and dip direction for input to 3DEC which then generates the 
fracture by cutting the block(s) in which the fracture lies. The coordinate systems adopted in 
FracMan and 3DEC are different; requiring a conversion of the outputs from FracMan to inputs 
in 3DEC (Appendix L). To account for the stochastic nature of the jointed medium, a total of 50 
fracture geometries were selected by generating random tunnel centroid locations within the 
100-m-cube simulated FracMan rock mass. A representative tunnel volume, approximately two 
tunnel diameters around the tunnel centroid and 25 m in length, is created at each of these 
locations to contain fractures generated in FracMan. This volume is considered sufficient to 
contain the limits of damaged rock, and of sufficient length (approximately five times the tunnel 
diameter and about 10 times the median trace lengths) to provide a representative volume of 
rockfall (see Figure 6-34 for 3DEC model region). 
The combination of computer runs considering fracture geometry, seismic ground motion, 
material properties variation, and thermal loading scenario are immense. In order to complete 
the task in a timely fashion, several techniques were used to speed up the calculation. These 
techniques are described in Appendix H. 
6.3.1.1 3DEC Model Set Up 
Figure 6-34 shows the base case 3DEC model geometry with fracture modeling region #38. The 
model is slightly larger than a 25-m x 25-m x 25-m cube with the 5.5-m diameter tunnel oriented 
at 75 degrees azimuth4. The region with detailed fractures imported from FracMan is one tunnel 
diameter at the side of the tunnel and two diameters on top of the tunnel. Three cross-section 
views are included in Figure 6-34 to illustrate the fractures and blocks around the excavation. 
That portion of the rock mass that does not form blocks is shown with a green color, while 
distinct blocks are identified as areas with different colors. Some of the fractures shown in the 
cross-section views are artificial, i.e., they were generated during the block cutting process or to 
facilitate mesh generation. A detailed description of mesh generation with artificial fractures is 
4 The emplacement drift azimuth of 72 (see Table 4-1) was modeled in this document with drifts trending 75. This 
3-degree difference between the modeled and actual drift alignment is acceptable given the variability of joint set 
orientations captured in the model (see Section 6.1.6). The 3-degree difference does not significantly effect the 
results from this analysis. 
ANL-EBS-MD-000027 REV 03 6-57 September 2004 

Drift Degradation Analysis 
provided in the 3DEC manual (Itasca Consulting Group 2002 [DIRS 160331]). The dimension 
of the model is selected to optimize the time required for analysis and the ability of the model to 
predict rockfall accurately. Sensitivity of the model dimension to the outcome of rockfall 
prediction is provided in Section 6.3.1.6. The drip shield is represented as a stiff, rectangular 
block fixed to the invert of the drift, based on a simplified drip shield geometry (BSC 2004 
[DIRS 169220]). The drip shield block is placed to collect information on the locations and 
relative velocities of the rockfall impact. 
Input properties for the distinct block 3DEC model involve both the fracture and block (intact) 
properties. Table 6-3 lists the base case properties used in 3DEC. The selected input properties 
were derived as the best estimates at the time of analysis. These values may have slight 
deviation from the statistics mean or median presented in Appendix E. Sensitivity analyses on 
these input parameters to the outcome of rockfall prediction were conducted and the results are 
presented in Section 6.3.1.6. 
A linear elastic model is used for the block material, whereas Coulomb slip criterion is used to 
present joint mechanical behavior. A linear elastic model is used as the intact block constitutive 
model for the 3DEC analysis. This approach is used to obtain a conservative (i.e., increased) 
estimate of the block volume. Breaking and spalling of the rock inside the blocks are expected 
considering the large amplitude of seismic waves for postclosure ground motions. This 
mechanism is addressed in Section 6.3.1.6 with a two-dimensional discontinuum model 
representing the rock mass (UDEC analysis). Although the shallow-dipping vapor-phase parting 
consists of higher cohesive material, a single set of joint mechanical properties are used for the 
joint sets for conservatism (i.e., more rockfall will be produced). Coulomb slip criterion is also 
used for the intact bridges between adjacent fractures, as the intact cohesion and friction is 
assigned for the bridge strength. Sensitivity analyses of the joint strength properties, dilation 
angle, and joint stiffness were conducted to evaluate their impact to rockfall, the range of 
properties, and their impacts to the analysis results are presented in Section 6.3.1.6. 
The initial state of stress was included at the model consolidation stage. From the in situ stress 
measurement using the hydraulic fracturing technique (DTN: SNF37100195002.001 
[DIRS 131356]), the horizontal components of in situ stress are provided: maximum 2.9 MPa 
acting N15E and minimum 1.7 MPa acting N105E (Table 4-1). The vertical component of in 
situ stress was calculated based on the weight of the overburden at the depth of the test from the 
surface. First, the coordinates of borehole ESF-AOD-HDRFR#1 (i.e., the hydraulic fracturing 
test borehole) were estimated based on the layout of the ESF and the Thermal Test Facility, 
starting from known coordinates at Main Drift Station 28+04 (BSC 2003 [DIRS 165572], Figure 
3; CRWMS M&O 1997 [DIRS 147458], MOL.19970717.0008, Appendix 6). The estimated 
coordinates of the borehole ESF-AOD-HDRFR#1 are NS 234025 and WE 171440. Next, the 
overburden stratigraphic unit thickness at the borehole location was extracted from 
DTN: MO0012MWDGFM02.002 [DIRS 153777] using EarthVison (see Appendix M for 
input/output details and Table M-1 for the overburden unit thickness). The overburden unit 
thickness and the mean unit densities in Table E-1 are used to calculate an overburden load of 
4.7 MPa at the depth of the test (Table M-1). The calculated vertical stress is in agreement with 
the initially estimated vertical stress at the location of the hydraulic fracturing test 
(CRWMS M&O 1997 [DIRS 147458], MOL.19970717.0008, Table 4). Therefore, the direction 
of the intermediate principal stress is N15E with a ratio to major principal stress 
ANL-EBS-MD-000027 REV 03 6-58 September 2004 

Drift Degradation Analysis 
of 0.617 (= 2.9 MPa  4.7 MPa), whereas the direction of the minor principal stress is N105E 
with a ratio to major principal stress of 0.361 (= 1.7 MPa  4.7 MPa). 
The vertical component of in situ stress (the major principal stress) is approximated as 7 MPa 
considering an overburden depth of 300 m (BSC 2003 [DIRS 166183], Section 4.2.1) and an 
overburden density of 2.41 g/cc (Section 4.1.3) (i.e., vertical 
stress = 300 m  9.81 m/sec2  2.41 g/cc  7 MPa). The horizontal components of in situ stress 
(the minor and intermediate principal stresses) are simplified to be 3.5 MPa based on an average 
horizontal-to-vertical stress ratio of 0.5 (i.e., the average of 0.617 and 0.361 as described above). 
The in situ stress for each emplacement drift will vary depending on the cover depth on top of 
the drift. The approximated values assigned for the in situ stress are adequate and insensitive to 
the results judging the magnitude of the induced seismic and thermal stress. 
The boundary conditions for various stages of the analysis are presented in Table 6-4. At the 
initial consolidation stage and the later thermal loading period, fixed velocity boundaries were 
used to ensure the boundary effect does not affect the stress distribution around the opening. For 
the seismic analysis, non-reflecting boundaries are used for both the top and bottom of the 
model, whereas free-field boundaries are imposed at the perimeter of the model as shown in 
Figure 6-35. The free-field boundaries ensure that plane waves propagating upward suffer no 
distortion at the boundary. A description of the free-field boundary is provided in Appendix H. 
Dynamic loading was applied at the bottom of the model as a prescribed stress boundary, and 
propagated vertically upwards. The conversion of the ground motion velocity to input seismic 
stress is discussed in Section 6.4.2.2 (Equation 6-7). 
6.3.1.2 Seismic Consideration in Nonlithophysal Units 
6.3.1.2.1 Site Specific Ground Motions 
Site-specific ground motions for five levels of annual probability of exceedance, 510-4, 110-4, 
110-5, 110-6, and 110-7, are included in this study (see Table 4-1 for source DTNs). 
Development of the ground motion time histories following use of a probabilistic seismic hazard 
analysis and Yucca Mountain site response model can be found in BSC 2004 [DIRS 170027]. 
The 510-4 and 110-4 ground motions are for preclosure consideration, while the 110-5, 110-6 
and 110-7 ground motions are for postclosure. The preclosure ground motion levels are 
provided in this section for comparison to the postclosure levels. For higher-frequency spectral 
accelerations (5 to 10 Hz) and an annual exceedance probability of 510-4, results of the 
probabilistic seismic hazard analysis for Yucca Mountain indicate the ground motion hazard 
derives primarily from earthquakes in the magnitude range of 5.0 to 6.5 occurring at distances 
less than 15 km from the site. For lower-frequency spectral accelerations (1 to 2 Hz) at the same 
annual exceedance probability, the hazard shows, in addition to nearby sources, a significant 
contribution from earthquakes in the magnitude range of 7.0 to 8.0 occurring at an epicentral 
distance of about 50 km. For annual exceedance probabilities of 110-6 and 110-7, nearby 
earthquakes in the magnitude range 5.5 to 7.0 are the dominant sources contributing to ground 
motion hazard at both higher and lower spectral acceleration frequency ranges. 
ANL-EBS-MD-000027 REV 03 6-59 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-60 September 2004 
(c) Section V1(d) Section V2(e) Section V3Section V1Section V3Section V2(b) top view(f) Section H1(g) Section H2(h) Section H3(i) Section H4(j) Section H5(a) perspective viewSection H1Section H2Section H3Section H4Section H5N 
Figure 6-34. 3DEC Model Geometry and Cross-Sections 

Drift Degradation Analysis 
Table 6-3. Base Case Material Properties for 3DEC Analysis 
Parameter Value 
Joint strength properties 
Joint cohesion (MPa) 0.1 
Joint friction (deg) 41 
Joint dilation (deg) 0 
Joint normal stiffness, Kn (MPa/m) 5.0E+04 
Joint shear stiffness, Ks (MPa/m) 5.0E+04 
Intact rock deformation properties 
Youngs Modulus (GPa) 33.03 
Poissons ratio 0.21 
Bulk modulus (GPa) 19.2 
Shear modulus (GPa) 13.6 
Intact bridge strength properties 
Cohesion (MPa) 47.2 
Friction angle (deg) 42 
Tensile strength (MPa) 11.56 
NOTE: The selected input properties were derived as the best estimates at the time of analysis. These values 
may have slight deviation from the statistics mean or median presented in Appendix E. Sensitivity 
analyses on these input parameters to the outcome of rockfall prediction were conducted and the results 
are presented in Section 6.3.1.6. 
Table 6-4. Boundary Conditions for 3DEC Analysis 
Boundary 
Initial Consolidation and 
Excavation Stage Thermal Analysis Stage Dynamic Analysis Stage 
Lateral Fixed at the direction normal 
to the face 
Fixed at the direction normal 
to the face Free-Field boundary 
Bottom Fixed at the vertical direction Fixed at the vertical direction Non-reflecting boundary 
Top Fixed at the vertical direction Fixed at the vertical direction Non-reflecting boundary 
ANL-EBS-MD-000027 REV 03 6-61 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-62 September 2004 
(a) Free-Field Boundaries 
(Perspective View)
(b) Free-Field Boundaries 
(Top View) 
Figure 6-35. Illustration of Free-Field Boundaries in 3DEC Model 
A total of 15 sets of Point B ground motions (i.e., ground motions developed at repository 
horizon) were selected for each annual postclosure hazard level. The multiple sets ensure a 
reasonable distribution of spectral shapes and time history durations. For each set of ground 
motions, two horizontal components (H1 and H2) and one vertical component (V) of 
acceleration, velocity, and displacement are supplied. Figure 6-36 shows the H1 velocity time 
history for four annual hazard levels. Only one ground motion was provided for the preclosure 
hazard levels because of the deterministic-based approach for preclosure consideration. The 

Drift Degradation Analysis 
amplitude of the peak ground acceleration, velocity, and displacement, and the seismic induced 
far field stress for one of the ground motion sets from each hazard level, are provided in 
Table 6-5. The induced stresses are calculated based on the intact material properties for 
nonlithophysal rock. This table is used to demonstrate the typical ground motion parameters for 
the three hazard levels considered. It is apparent that the preclosure ground motions have lower 
amplitude vibrations and, hence, lower induced stresses compared with the postclosure ground 
motions. 
The peak values for each ground motion set provided for postclosure hazard level varies 
significantly and can be highly conservative, particularly for the 110-6 and 110-7 probability 
levels as summarized in Table 6-5 (see Appendix X for a complete listing of ground motion 
parameters). Arias intensity (an estimate of energy delivered to structures) for each set of ground 
motions is listed in Table 6-6. A large variation of energy within the same hazard level is 
observed. The 15 sets of ground motions were combined with fracture patterns for probabilistic 
analysis. The combining of ground motion and fracture patterns is described in 
Section 6.3.1.2.2. 
Although not taken into account in the base-case calculations provided in this document, a study 
addressing the conservative, and potential physically-unrealizable peak ground velocities 
associated with these low hazard levels has been developed (BSC 2004 [DIRS 170137]). 
Geologic evidence gained from panel mapping of lithophysae and fractures in the Tptpll 
(Appendix O) has shown that the rock mass has not been subjected to shear strain levels 
sufficient to result in fracture between lithophysal cavities since the rock mass was deposited and 
cooled (the existing fractures can be shown to have occurred as a result of cooling). As shown 
by the large-core laboratory testing (Appendix E), this strain level is approximately 0.1 to 
0.35 percent. Therefore, in the approximately 12.8 million years since the Topopah Spring Tuff 
was deposited, an earthquake sufficient to produce a peak shear strain of this level has not 
occurred. Since peak ground velocity (PGV) can be directly related to strain, these observations 
can provide an indication of the maximum PGV that has occurred in this time period. The peak 
ground velocity study (BSC 2004 [DIRS 170137]) has subsequently been used to develop a 
conservative estimate that the horizontal PGV varies as a uniform distribution with lower and 
upper limits of 1.5 and 5 m/sec which, in turn, has been used to develop a modified hazard curve 
(the relationship between PGV and annual exceedance probability). 
The base-case modeling performed in this document does not limit the highly conservative PGV 
values generated from the site response model, and thus the estimates of rockfall and drift 
damage generated by the postclosure ground motions (e.g., 110-5, 110-6 and 110-7) are 
correspondingly conservative. However, the abstraction of damage to Engineered Barrier 
System components for the seismic scenario, presented in the Seismic Consequence Abstraction 
(BSC 2004 [DIRS 169183]), is based on relating damage (e.g., area of stress corrosion cracking 
on drip shield or waste package) to PGV, and, in turn, to probability based on the hazard curve. 
The seismic consequence abstraction uses the hazard curve, modified by bounding PGV limits, 
to define damage. 
ANL-EBS-MD-000027 REV 03 6-63 September 2004 

Drift Degradation Analysis 
Table 6-5. Peak Ground Motion Parameters 
Peak Seismic Induced Stress 
Annual 
Hazard Level 
Ground Motion 
Component 
Peak 
Acceleration (g) 
Peak Velocity 
(cm/sec) 
Displacement 
(cm) 
Corresponding to Peak 
Velocity (MPa) 
H1 0.19 19.00 12.86 1.09 
510-4 H2 0.18 17.72 12.37 1.02 
V 0.22 17.73 11.34 1.68 
H1 0.39 38.38 44.44 2.20 
110-4 H2 0.37 43.78 45.30 2.51 
V 0.47 47.51 31.73 4.50 
110-5 Ground 
Motion Set 1 
H1 2.77 104.58 20.06 6.00 
H2 2.50 83.31 14.37 4.78 
V 2.63 70.88 13.00 6.71 
110-6 Ground 
Motion Set 1 
H1 7.42 244.14 16.76 14.009 
H2 6.74 195.41 26.78 11.21 
V 4.90 111.29 13.75 10.54 
110-7 Ground 
Motion Set 1 
H1 16.28 535.26 58.68 30.0 
H2 14.79 428.42 58.72 24.57 
V 13.15 298.44 36.86 28.25 
Source: DTNs: MO0407TMHIS104.003 [DIRS 170599]; MO0306SDSAVDTH.000 [DIRS 164033]; 
MO0402AVDTM105.001 [DIRS 168890]; MO0403AVDSC106.001 [DIRS 168891]; 
MO0403AVTMH107.003 [DIRS 168892]. 
NOTES: Native data files (available as ASCII text files) containing the acceleration, velocity, and displacement 
time-history data can be downloaded from the source DTNs. 
Seismic induced stress (column six) is calculated based on elastic wave equations (Itasca Consulting 
Group 2002 [DIRS 160331], Manuals/3DEC/Optional Features/Section 2: Dynamic Analysis, Section 2.5). 
Peak ground motion parameters for the ground motion sets are provided in Appendix X. 
In running the 3DEC seismic simulation, the duration of the seismic time histories was truncated 
to that portion of the records displaying the majority of the energy. Initially, records were 
truncated to a duration bracketed by the 5 percent and 95 percent points in the energy buildup as 
measured by the Arias Intensity. For each three-component set of ground motions, these points 
were determined for each component (H1, H2, and V) and then the earliest 5 percent point and 
the latest 95 percent point were used to define the duration for that set of ground motions. 
Because preliminary analyses showed that rockfall continued in some cases beyond the 
95 percent energy buildup point, additional time was added for analyses to ensure that the 
simulated duration covered the rockfall. Table 6-7 presents the total duration of each set of time 
histories and the 5 percent and 95 percent points. The sensitivity of rockfall to the duration of 
seismic ground motion is examined in Section 6.3.1.6. 
6.3.1.2.2 Combinations of Ground Motion and Fracture Pattern 
Rockfall is part of the seismic scenario calculations in support of the Total System Performance 
Assessment for the License Application. The analysis results provide inputs to the drip shield 
structural response calculation for assessment of the structural integrity of drip shields. To 
ensure that the ultimate performance measure of interest (i.e., damaged surface area of the drip 
shield) can be tracked to the underlying uncertain inputs in a consistent fashion, a sampling 
ANL-EBS-MD-000027 REV 03 6-64 September 2004 

Drift Degradation Analysis 
strategy was developed to include a consistent set of pointers for the sampled parameters 
(i.e., ground motions and fracture modeling regions in rockfall analysis). A detailed description 
of the sampling strategy is provided in DTN: MO0301SPASIP27.004 [DIRS 161869]. 
As described in Section 6.1, a 100-m cube was constructed for providing the fracture network 
required in 3DEC analysis. A random selection of 105 centroid locations was conducted. These 
105 centroid locations combined with the 15 sets of ground motions served as the pointers for 
sampling. The process of random generation and the coordinate of the centroid locations in the 
100-m cube are provided in Appendix J. A simple Latin Hypercube sampling scheme was used 
for the paring of ground motion and fracture modeling region (DTN: MO0301SPASIP27.004 
[DIRS 161869]). Table 6-8 lists the 50 sets of analyses conducted for seismic consideration. 
The adequacy of 50 sets of 3DEC analyses representing the rockfall characteristics for the 
non-lithophysal rock is presented in Appendix K. 
6.3.1.2.3 Results for Seismic Analysis Subjected to 110-5 Annual Probability of 
Exceedance Ground Motions 
The results for a complete set of 3DEC analyses, as tabulated in Table 6-8, subjected to the 
postclosure hazard level of 110-5 annual probability of exceedance ground motions are 
presented in this section. Figure 6-37 compares the input ground motion for the first horizontal 
component (H1, Ground Motion Set 10) with the recorded velocities at the base of the model and 
at the center of the model. The results confirm the correct wave inputs and proper wave 
propagation in the 3DEC model. As described in Section 6.3.1.1, a drip shield block anchored at 
the invert is included in the model to record the information of the locations and relative 
velocities for the rockfall impact. Figure 6-38 shows a typical block impacting the drip shield in 
the 3DEC dynamic simulation. Note that fallen blocks are subsequently deleted after impacting 
the drip shield. The deletion is to facilitate the recording of all possible rockfall on the drip 
shield. If the blocks are not deleted for the heavy rockfall cases, the drip shield will be covered 
with fallen rocks so that some of the rockfall at the later part of seismic shaking will not impact 
the drip shield. The simulation without deletion of the rock block after the impact is presented in 
Section 6.3.1.6. The results indicate less rockfall impact without the deletion scheme. For 
certain conditions, the algorithm for accounting and deletion of the blocks may lead to deleting 
stable blocks with corner and/or edge in the near vicinity of the drift shield at the floor. Blocks 
are not accounted as rockfall for these conditions. 
Time histories of normal and shear stresses for joints close to the opening were recorded during 
the seismic shaking in the 3DEC model. Figure 6-39 shows normal and shear stress time 
histories at selected fracture subcontacts taken from 3DEC simulation #16 with ground motion 
set #11. Peak seismic loading appears to occur at the time of 4 to 6 seconds, consistent with the 
input ground motion. Information of the subcontacts is provided in Figure 6-40. Subcontact a 
represents the true fracture while subcontacts b and c are for the rock bridge in between the 
fracture segments. The stress paths of the fracture subcontacts are plotted against the fracture 
Coulomb slip criterion and rock bridge shear or tensile strength criterion, as shown in 
Figure 6-41. The in situ normal and shear stress state along the fracture is also included as the 
orange square for each subcontact in the figure. The in situ stress state at subcontact a is very 
close to the Coulomb slip criterion. The fracture containing this subcontact has apparently 
undergone yielding during seismic motions. The stress paths for rock bridges containing 
ANL-EBS-MD-000027 REV 03 6-65 September 2004 

Drift Degradation Analysis 
subcontacts b and c are well under the rock shear or tensile strength criterion and representative 
of most of the rock mass. 
The percentages of the area of joint slip/separation versus the total area of joint planes for the 
selected cases were calculated as a stability indicator for the fracture system around the opening. 
A total of 8 cases are presented in Table 6-9. Total joint and bridge areas contained in the model 
were first calculated. The bridge area is around 20 percent of the total joint area for the selected 
cases. A large portion of fractures (greater than 70 percent) has undergone shear slip or tensile 
separation when subjected to 110-5 ground motions. The percentage of shear and tensile failure 
is transient during the seismic shaking. Tensile mode can dominate for one instance and then 
change to shear mode for the next instance. However, shear failure becomes the dominant mode 
when approaching to the end of shaking. In addition to joint slip/separation, bridge damage 
percentage was also calculated. The results are presented in Table 6-9. In general, less than 
1 percent bridge area is predicted to be damaged by shaking. However, for certain large ground 
motions (e.g., ground motion #3 for Case 38), higher damage percentage is predicted. 
Correlation of the bridge damage percentage versus peak ground velocity shows a strong 
relationship between the two. A detailed discussion on the bridge damage is provided in 
Section 6.3.1.6.3. 
The results of the 50 3DEC simulations are summarized in Table 6-10. Approximately two 
thirds of the simulations predicted rockfall under seismic shaking. A total of 1,767 blocks have 
been identified from the analyses. The associated impact parameters for these blocks from the 
analyses include the following: 
 Rock block volume falling on the drip shields (unit in m3) 
 Relative impact velocity of rock block to the drip shields (unit in m/sec) 
 Impact location. 
ANL-EBS-MD-000027 REV 03 6-66 September 2004 

Drift Degradation Analysis 
Sources: DTNs: MO0306SDSAVDTH.000 [DIRS 164033]; MO0402AVDTM105.001 [DIRS 168890]; 
MO0403AVDSC106.001 [DIRS 168891]; and MO0403AVTMH107.003 [DIRS 168892]. 
NOTES: The 510-4 time history is not presented due to its small magnitude. Native data files (available as ASCII 
text files) containing the velocity time-history data can be downloaded from the source DTN. 
Figure 6-36. Examples of Ground Velocity Time Histories (H1) with Truncated Duration for Analysis 
ANL-EBS-MD-000027 REV 03 6-67 September 2004 

Drift Degradation Analysis 
Table 6-6. Arias Intensity (m/sec) for Each Ground Motion Set 
Annual Hazard Level Ground Motion Set H1 H2 V Total Sum 
110 -5 Annual Probability of Exceedance 
1 33 34 36 103 
2 31 38 123 192 
3 34 48 48 130 
4 12 15 20 48 
5 16 11 13 41 
6 7 5 18 30 
7 4 4 49 57 
8 8 13 16 37 
9 22 52 139 213 
10 9 4 14 26 
11 8 7 15 30 
12 4 4 7 15 
13 9 16 26 51 
14 3 2 7 12 
16 3 2 7 11 
110 -6 Annual Probability of Exceedance 
1 235 253 114 602 
2 206 250 413 869 
3 120 153 135 408 
4 178 219 141 538 
5 78 52 29 159 
6 69 56 79 204 
7 63 61 467 590 
8 71 109 61 241 
9 169 352 465 986 
10 59 26 57 141 
11 57 45 45 146 
12 58 59 46 163 
13 98 170 123 390 
14 63 73 119 255 
16 23 15 34 72 
110 -7 Annual Probability of 
Exceedance 
1128 1215 820 3163 
989 1202 2972 5163 
577 735 971 2283 
856 1052 1013 2921 
373 252 205 830 
331 271 566 1168 
303 291 3357 3951 
343 524 437 1304 
813 1691 3340 5844 
282 125 409 816 
ANL-EBS-MD-000027 REV 03 6-68 September 2004 

Drift Degradation Analysis 
Table 6-6. Arias Intensity (m/sec) for Each Ground Motion Set (Continued) 
Annual Hazard Level Ground Motion Set H1 H2 V Total Sum 
110 -7 Annual 
Probability ofExceedance 
11 272 214 321 808 
12 277 284 332 893 
13 469 815 881 2165 
14 302 351 854 1507 
16 112 72 244 428 
510-4 Annual Probability of Exceedance 0.59 0.67 0.46 1.72 
110-4 Annual Probability of Exceedance 4.21 4.51 8.97 17.69 
Sources: DTNs: MO0407TMHIS104.003 [DIRS 170599]; MO0306SDSAVDTH.000 [DIRS 164033]; 
MO0402AVDTM105.001 [DIRS 168890]; MO0403AVDSC106.001 [DIRS 168891]; 
MO0403AVTMH107.003 [DIRS 168892]. 
NOTES: A total of 17 sets of ground motions was developed for each postclosure level. Ground motion sets #15 
and #17 were not used. The selection of ground motion sets is documented in Sampling of Stochastic 
Input Parameters for Rockfall Calculations and for Structural Response Calculations Under Vibratory 
Ground Motion (BSC 2004 [DIRS 169999]). Native data files (available as ASCII text files) containing the 
Arias intensity data can be downloaded from the source DTNs (see file Dur.zip). Arias intensity is the total 
energy (m/sec) over the full duration (0 to 100 percent energy). 
Table 6-7. Seismic Analysis Duration and Complete Time History Duration 
Annual Hazard Ground Duration of Time 
Level Motion Set History (sec) 5 % Time (sec) 95 % Time (sec) 
110 -5 Annual Probability of Exceedance 
Set 1 20.60 1.34 8.22 
Set 2 20.60 0.80 8.58 
Set 3 20.01 1.76 4.62 
Set 4 26.13 1.57 17.90 
Set 5 20.01 1.70 10.27 
Set 6 20.01 2.62 10.73 
Set 7 16.27 3.76 12.17 
Set 8 20.60 1.21 7.48 
Set 9 29.98 0.75 8.83 
Set 10 20.02 1.68 10.26 
Set 11 20.60 2.07 10.93 
Set 12 40.02 2.27 17.53 
Set 13 39.96 2.05 20.33 
Set 14 40.00 5.49 24.85 
Set 16 32.01 3.80 11.63 
110 -6 Annual Probability of 
Exceedance 
Set 1 20.60 1.28 7.47 
Set 2 20.60 0.80 7.40 
Set 3 20.01 1.75 4.73 
Set 4 26.13 1.48 17.29 
Set 5 20.01 1.69 8.78 
Set 6 20.01 2.44 10.57 
Set 7 16.27 3.55 12.23 
Set 8 20.60 1.21 6.48 
ANL-EBS-MD-000027 REV 03 6-69 September 2004 

Drift Degradation Analysis 
Table 6-7. Seismic Analysis Duration and Complete Time History Duration (Continued) 
Annual Hazard Ground Duration of Time 
Level Motion Set History (sec) 5 % Time (sec) 95 % Time (sec) 
110 -6 Annual 
Probability ofExceedance 
Set 9 29.98 0.76 8.00 
Set 10 20.02 1.67 9.58 
Set 11 20.60 2.08 10.30 
Set 12 40.02 2.17 15.66 
Set 13 39.96 1.90 19.53 
Set 14 40.00 5.37 23.94 
Set 16 32.01 3.43 10.43 
110 -7 Annual Probability of Exceedance 
Set 1 20.60 1.28 7.47 
Set 2 20.60 0.80 7.40 
Set 3 20.01 1.75 4.73 
Set 4 26.13 1.48 17.29 
Set 5 20.01 1.69 8.78 
Set 6 20.01 2.44 10.57 
Set 7 16.27 3.55 12.23 
Set 8 20.60 1.21 6.48 
Set 9 29.98 0.76 8.00 
Set 10 20.02 1.67 9.58 
Set 11 20.60 2.08 10.30 
Set 12 40.02 2.17 15.66 
Set 13 39.96 1.90 19.53 
Set 14 40.00 5.37 23.94 
Set 16 32.01 3.43 10.43 
510-4 Annual Probability of Exceedance 40.96 3.46 28.67 
110-4 Annual Probability of Exceedance 75.00 9.78 58.79 
Sources: DTNs: MO0407TMHIS104.003 [DIRS 170599]; MO0306SDSAVDTH.000 [DIRS 164033]; 
MO0402AVDTM105.001 [DIRS 168890]; MO0403AVDSC106.001 [DIRS 168891]; 
MO0403AVTMH107.003 [DIRS 168892]. 
NOTES: A total of 17 sets of ground motions was developed for each postclosure level. Ground motion sets #15 
and #17 were not used. The selection of ground motion sets is documented in Sampling of Stochastic 
Input Parameters for Rockfall Calculations and for Structural Response Calculations Under Vibratory 
Ground Motion (BSC 2004 [DIRS 169999]). Native data files (available as ASCII text files) containing 
time-history duration can be downloaded from the source DTNs (see file Dur.zip). Data are extracted 
from the 5 to 95 percent energy range. The earliest 5 percent point and the latest 95 percent point for 
each component (H1, H2, and V) are used to define the duration of each ground motion set. 
ANL-EBS-MD-000027 REV 03 6-70 September 2004 

Drift Degradation Analysis 
Table 6-8. Combinations of Ground Motion and Fracture Modeling Region of 3DEC Analyses 
3DEC Simulation 
Number 
Ground Motion Time History 
Number Fracture Pattern 
14 7 22 
15 11 21 
16 11 30 
17 16 27 
18 14 26 
19 13 10 
20 5 19 
21 10 9 
22 5 23 
23 12 5 
24 3 6 
25 3 17 
27 6 14 
28 7 25 
29 13 3 
31 16 79 
32 12 7 
33 1 102 
34 16 75 
35 11 33 
36 5 78 
38 3 29 
39 5 37 
40 6 99 
41 16 42 
42 6 24 
43 4 59 
44 9 65 
45 10 39 
46 6 50 
48 16 35 
49 5 57 
50 9 67 
51 10 63 
52 9 82 
53 12 4 
54 1 83 
55 12 16 
56 3 98 
57 14 28 
ANL-EBS-MD-000027 REV 03 6-71 September 2004 

Drift Degradation Analysis 
Table 6-8. Combinations of Ground Motion and Fracture Modeling Region of 3DEC Analyses 
(Continued) 
3DEC Simulation 
Number 
Ground Motion Time History 
Number Fracture Pattern 
58 4 8 
59 2 74 
60 11 80 
61 12 81 
62 12 71 
63 11 96 
64 14 49 
65 7 20 
66 3 62 
67 9 41 
Source: DTN: MO0301SPASIP27.004 [DIRS 161869]. 
NOTES: 3DEC simulation numbers 14 through 29 are from the corresponding realization numbers from the first 
sampling in the nonlithophysal zone provided by the source DTN. 
3DEC simulation numbers 31 through 67 are from the second sampling (realization numbers 1 through 
60) in the nonlithophysal zone provided by the source DTN. 
Duplicate fracture modeling regions (i.e., synthetic fracture pattern numbers) occurring in both the first 
and second samplings were not used as part of the base case for rockfall modeling. 
Simulation Number 26, 37, and 47 were not used due to numerical difficulties for 3DEC block 
generation. 
0 5 15 20 25 
li/
iion 
-1.00 
-0.50 
0.00 
0.50 
1.00 
1.50 
10 
Time (sec) 
Ground Veocty (msec) 
Input Sesmic Wave 
Recorded Mot
NOTE: The ground motion was recorded at the drip shield block during 3DEC simulation. 
Figure 6-37. Comparison of Input Seismic Wave and Recorded Velocities in 3DEC Model (Ground 
Motion Set 4, H1) 
ANL-EBS-MD-000027 REV 03 6-72 September 2004 

Drift Degradation Analysis 
Figure 6-38. Illustration of the Simulation of Rockfall Impact to the Drip Shield 3DEC Simulation #44, 
110-5 Ground Motion # 9, at t = 3.6 sec 
Stress on Fracture (Pa) 
1.6E+07 
1.4E+07 
1.2E+07 
1.0E+07 
8.0E+06 
6.0E+06 
4.0E+06 
2.0E+06 
0.0E+00 
normal stress at subcontact a 
normal stress at subcontact b 
normal stress at subcontact c 
shear stress at subcontact a 
shear stress at subcontact b 
shear stress at subcontact c 
0 2 4 6 81012 
Tim e (s ec) 
Figure 6-39. Time Histories for Normal and Shear Stress at Selected Fracture Subcontacts for 110-5 
Annual Probability of Exceedance Hazard (Simulation 16, Ground Motion Set 11) 
ANL-EBS-MD-000027 REV 03 6-73 September 2004 

Drift Degradation Analysis 
xy 
z 
iiiew 
ix (m) ) ) 
dip 
i) 
dip 
) 
l jSubcontact a 
Subcontact c Subcontact b 
Subcontact a 
Subcontact b 
Subcontact c 
Side Vew 
Perspectve VSubcontact Informaton 
y (mz (mdirecton 
(degree(degreecontact type 
Subcontact a 3.311 2.879 -1.257 305.97 82.36 actuaoint 
Subcontact b 2.189 3.288 -1.041 54.56 82.7 rock bridge 
Subcontact c 3.434 2.19 -1.348 317.73 5.82 rock bridge 
Figure 6-40. Information for the Selected Fracture Subcontacts 
ANL-EBS-MD-000027 REV 03 6-74 September 2004 

Drift Degradation Analysis 
l) 
) 
a 
b 
c 
iliiiiii0.0E+00 
1.0E+07 
2.0E+07 
3.0E+07 
4.0E+07 
5.0E+07 
6.0E+07 
7.0E+07 
-1.5E+07 -1.0E+07 -5.0E+06 0.0E+00 5.0E+06 1.0E+07 1.5E+07 2.0E+07 
Norma Stress (PaShear Stress (PaSubcontactSubcontactSubcontactJont Coulomb sp crteron 
Rock brdge strength crteron 
Figure 6-41. Normal and Shear Stress Path at Selected Fracture Subcontacts for 110-5 Annual 
Probability of Exceedance Hazard (Simulation 16, Ground Motion Set 11) 
Table 6-9. Summary of Joint Slip/Separation and Bridge Damage for 110-5 Ground Motions for 
Selected Cases 
Parameter Case 38 Case 40 Case 66 Case 23 Case 48 Case 45 Case 63 Case 31 
Total Joint Area (m2) 4319 4251 2583 3026 4260 4737 1911 3400 
Total Bridge Area (m2) 862 885 592 550 923 1054 425 720 
Percentage of Joint 
Slip/Separation 94.98% 90.94% 96.24% 77.07% 82.09% 70.80% 79.33% 73.59% 
Percentage of Bridge 
Damaged 14.62% 1.00% 10.14% 0.24% 0.06% 0.00% 0.47% 0.06% 
ANL-EBS-MD-000027 REV 03 6-75 September 2004 

Drift Degradation Analysis 
Table 6-10. Summary of 3DEC Rockfall Prediction for 110-5 Annual Probability of Exceedance Hazard 
Parameter Value 
Simulations Completed 50 
Number of Simulations Predicting No Rockfall 1 
Total Number of Rockfall 1767 
Total Volume of Rockfall (m3) 255.4 
Total Length of Drift Simulated (m) 1250 
Number of Blocks per km 1414 
Volume of Rockfall per km (m3) 204.3 
A detailed listing of the impact information for each recorded block is provided in an output 
DTN of this document (DTN: MO0408MWDDDMIO.002, file nonlith rockfall characteristics 
in emplacement drifts with 1e-5 gm.xls). The impact locations are provided as the coordinates 
based on the drip shield local coordinate system (Figure 6-42). The distribution of the data for 
each parameter (i.e., block mass, relative impact velocity, impact angle, impact momentum, and 
impact energy) is presented using histograms (Figures 6-43 to 6-47). Also included in each 
histogram plot is the cumulative frequency of occurrence. Due to the gravity effect, most of the 
rockfall will occur in the range of 48 degrees to 132 degrees as confirmed in Figure 6-45. The 
impact momentum and impact energy, both functions of block mass and impact velocity, were 
calculated as the required outputs for drip shield structural response calculation. Summary 
statistics for these parameters are provided in Table 6-11. The maximum rockfall block mass 
predicted is 19.07 metric tons with median block size of 0.12 metric tons. The predicted results 
(Table 6-11) show large variance and high skewness with the exception of impact velocity, as 
confirmed by the shape of the histograms (Figures 6-43 to 6-47). The block mass, impact angle, 
impact momentum, and impact energy show the trend of exponential distribution with most of 
the data concentrated on the low end of the data range. The impact velocity shows a typical bell 
shape for the normal distribution. The distribution centers around 3 m/sec with a standard 
deviation of approximately 1.5 m/sec. The relative low impact velocities indicate that block 
fall-out is mainly due to free fall. Differential acceleration or energy trapping to induce high 
ejection velocity is not observed. 
Table 6-11. Statistic Summary of the Rockfall Impact Parameters, 110-5 Annual Probability of 
Exceedance Hazard 
Parameter 
Block Mass 
(tonnes) 
Relative Impact 
Velocity (m/sec) 
Impact Angle 
(degree) 
Impact Momentum 
(kg*m/sec) 
Impact Energy 
(Joules) 
Mean 0.35 2.69 144.74 964 1814 
Median 0.12 2.57 127.13 276 357 
Standard Deviation 0.93 1.48 99.69 3789 11430 
Skewness 10.03 0.74 0.75 24 32 
Range 19.04 9.38 359.74 128809 435077 
Minimum 0.02 0.04 0.18 3 0 
Maximum 19.07 9.42 359.92 128812 435077 
Sum 615.97 NA NA 1703088 3205138 
NA = Not Applicable 
ANL-EBS-MD-000027 REV 03 6-76 September 2004 

Drift Degradation Analysis 
X 
z 
y 
Y 
Z 
Impact angle 
(measured counterclockwise from z axis 
Figure 6-42. Definition of Impact Angle and Drip Shield Block Local Coordinate System 
ANL-EBS-MD-000027 REV 03 6-77 September 2004 

Drift Degradation Analysis 
i0 
01412i (i) 
0% 
l1E-5 Ground Motons 
100 
200 
300 
400 
500 
600 
700 
800 
900 
0.20.40.60.81.41.82.5More 
block szemetrc tonFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-43. Histogram for Block Mass (110-5 Annual Probability of Exceedance Hazard) 
i0 
012345678910l/) 
0% 
l1E-5 Ground Motons 
100 
200 
300 
400 
500 
600 
More 
Impact Veocity (msecFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-44. Histogram for Relative Impact Velocity (110-5 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-78 September 2004 

Drift Degradation Analysis 
i0 
50 
03060900% 
i1E-5 Ground Motons 
100 
150 
200 
250 
300 
350 
120 
150 
180 
210 
240 
270 
300 
330 
360 
Impact Angle 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-45. Histogram for Impact Angle (110-5 Annual Probability of Exceedance Hazard) 
i0 
0 
(/) 
0% 
i1E-5 Ground Motons 
200 
400 
600 
800 
1000 
1200 
1400 
1600 
2000 4000 6000 8000 10000 12000 14000 More 
Impact Momentum kg.msecFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-46. Histogram for Impact Momentum (110-5 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-79 September 2004 

Drift Degradation Analysis 
i0 
0 
(J) 
0% 
l1E-5 Ground Motons 
200 
400 
600 
800 
1000 
1200 
1400 
1600 
4000 8000 12000 16000 2000024000 28000 More 
Impact Energy 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-47. Histogram for Impact Energy (110-5 Annual Probability of Exceedance Hazard) 
6.3.1.2.4 Results for Seismic Analysis Subjected to 110-6 Annual Probability of 
Exceedance Ground Motions 
The results for a complete set of 3DEC analyses subjected to the postclosure hazard level of 
110-6 annual probability of exceedance ground motions are presented in this section. 
Figure 6-48 compares the input ground motion for the second horizontal component (H2, Ground 
Motion Set 6) with the recorded velocities at the center of the model. As for the case of 
110-6 annual probability of exceedance hazard, the results confirm the correct wave inputs and 
proper wave propagation in the 3DEC model. 
Figure 6-49 shows a perspective view of blocks impacting drip shield in 3DEC dynamic 
simulation. Time histories of normal and shear stresses for fractures and rock bridges close to 
the opening were recorded during the seismic shaking in the 3DEC model. Figure 6-50 shows 
normal and shear stress time histories at the same selected fracture subcontacts as presented for 
the 110-5 annual probability of exceedance ground motions (3DEC simulation #16 with ground 
motion set #11). Peak normal stress at subcontact c reaches approximately 20 MPa at around 
4 seconds. Information of the subcontacts is provided in Figure 6-40. The stress paths of the 
fracture subcontacts are plotted against the fracture Coulomb slip criterion and rock bridge 
strength criterion, as shown in Figure 6-51. The in situ normal and shear stress state along the 
fracture is also included as the orange square for each subcontact in the figure. As in the 
110-5 ground motion case, the fracture containing subcontact a yielded during seismic motions. 
The stress paths for rock bridges containing subcontacts b and c are still under the rock strength 
criterion when subjected to 110-6 ground motion. 
The percentages of the area of joint slip/separation versus the total area of joint planes for the 
selected cases were calculated and presented in Table 6-12. The majority of fractures (greater 
ANL-EBS-MD-000027 REV 03 6-80 September 2004 

Drift Degradation Analysis 
than 95 percent for most cases) have undergone shear slip or tensile separation when subjected to 
110-6 ground motions. Bridge damage percentages are also presented in Table 6-12. It is 
predicted that, for the majority of cases, around 5 percent bridge area would be damaged by 
shaking of 110-6 ground motions. However, for certain large ground motions (e.g., ground 
motion #3 for Case 38), higher damage percentage is predicted. Correlation of the bridge 
damage percentage versus peak ground velocity shows a strong relationship between the two. A 
detailed discussion on the bridge damage is provided in Section 6.3.1.6.3. 
0 5 10 15 20 
() 
lity () 
iiion 
-1.50 
-1.00 
-0.50 
0.00 
0.50 
1.00 
1.50 
25 
TimesecGround Veocm/secInput Sesmc Wave 
Recorded Mot
NOTE: The ground motion was recorded at the drip shield block during 3DEC simulation. 
Figure 6-48. Comparison of Input Seismic Wave and Recorded Velocities in 3DEC Model for 110-6 
Annual Probability of Exceedance Ground Motion (Ground Motion Set 6, H2) 
ANL-EBS-MD-000027 REV 03 6-81 September 2004 

Drift Degradation Analysis 
Figure 6-49. Illustration of the Simulation of Rockfall Impact to the Drip Shield (3DEC Simulation # 22, 
110-6 Ground Motion # 5, at t = 5.24 sec) (Simulation 16, Ground Motion Set 11) 
0 2 4 6 8 
() 
) -5.0E+06 
0.0E+00 
5.0E+06 
1.0E+07 
1.5E+07 
2.0E+07 
2.5E+07 
10 12 
TimesecStress on Fracture (Panormal stress at subcontact a shear stress at subcontact a 
normal stress at subcontact b shear stress at subcontact b 
normal stress at subcontact c shear stress at subcontact c 
NOTE: Information for the subcontacts is presented in Figure 6-40. 
Figure 6-50. Time Histories for Normal and Shear Stress at Selected Fracture Subcontacts for 110-6 
Annual Probability of Exceedance Hazard 
ANL-EBS-MD-000027 REV 03 6-82 September 2004 

Drift Degradation Analysis 
l) 
) 
iliiiiii0.0E+00 
1.0E+07 
2.0E+07 
3.0E+07 
4.0E+07 
5.0E+07 
6.0E+07 
7.0E+07 
-1.5E+07 -1.0E+07 -5.0E+06 0.0E+00 5.0E+06 1.0E+07 1.5E+07 2.0E+07 2.5E+07 
Norma Stress (PaShear Stress (PaSubcontact a 
Subcontact b 
Subcontact c 
Jont Coulomb sp crteron 
Rock brdge strength crteron 
NOTE: Information for the subcontacts is presented in Figure 6-40. 
Figure 6-51. Normal and Shear Stress Path at Selected Fracture Subcontacts for 110-6 Annual 
Probability of Exceedance Hazard (Simulation 16, Ground Motion Set 11) 
The results of the 50 3DEC simulations are summarized in Table 6-13. A total of 2,797 blocks 
have been identified from the analyses. A detailed listing of the impact information for each 
recorded block is included in an output DTN of this document 
(DTN: MO0408MWDDDMIO.002, file nonlith rockfall characteristics in emplacement drifts 
with 1e-6 gm.xls). Summary statistics for these parameters are provided in Table 6-14. The 
maximum rockfall block mass predicted is 28.22 metric tons. The median block size is 
0.13 metric tons, very similar to the value predicted for the 110-5 annual probability of 
exceedance hazard. Figures 6-52 to 6-56 present the histograms and the cumulative frequency of 
occurrence for the five impact parameters. The distribution of each parameter is similar to that 
for the 110-5 annual probability of exceedance hazard. 
ANL-EBS-MD-000027 REV 03 6-83 September 2004 

Drift Degradation Analysis 
Table 6-12. Summary of Joint Slip/Separation and Bridge Damage for 110-6 Ground Motions for 
Selected Cases 
Parameter Case 38 Case 40 Case 66 Case 23 Case 48 Case 45 Case 63 Case 31 
Total Joint Area (m2) 4319 4251 2583 3026 4260 4737 1911 3400 
Total Bridge Area (m2) 862 885 592 550 923 1054 425 720 
Percentage of Joint 
Slip/Separation 93.70% 97.13% 96.36% 97.06% 96.74% 95.33% 95.40% 96.50% 
Percentage of Bridge 
Damaged 32.60% 6.07% 28.89% 4.28% 4.14% 2.66% 2.82% 2.31% 
Table 6-13. Summary of 3DEC Rockfall Prediction for 110-6 Annual Probability of Exceedance Hazard 
Parameter Value 
Simulations Completed 50 
Total Number of Rockfall 2797 
Total Volume of Rockfall (m3) 497.7 
Total Length of Drift Simulated (m) 1250 
Number of Blocks per km 2238 
Volume of Rockfall per km (m3) 398.2 
Table 6-14. Statistic Summary of the Rockfall Impact Parameters, 110-6 Annual Probability of 
Exceedance Hazard 
Parameter 
Block Mass 
(tonnes) 
Relative Impact 
Velocity (m/sec) 
Impact Angle 
(degree) 
Impact 
Momentum 
(kg*m/sec) 
Impact Energy 
(Joules) 
Mean 0.43 3.23 136 1217 2350 
Median 0.13 2.97 124 377 576 
Standard Deviation 1.30 1.74 93 3464 7704 
Skewness 11.61 1.06 0.87 11 12 
Range 28.19 12.03 359 79001 163657 
Minimum 0.02 0.07 0 2 0 
Maximum 28.22 12.10 360 79003 163657 
Sum 1200.43 NA* NA* 3403555 6573633 
* Not Applicable 
ANL-EBS-MD-000027 REV 03 6-84 September 2004 

Drift Degradation Analysis 
i0 
200 
400 
600 
800 
1000 
1200 
1400 
01412i (i0% 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
l1E-6 ground motons 
0.20.40.60.81.41.82.5More 
block szemetrc ton) 
Frequency 
Frequency 
Cumuative % 
Figure 6-52. Histogram for Block Mass (110-6 Annual Probability of Exceedance Hazard) 
i0 
0 1 2 3 4 5 6 7 8 9 
lity () 
0% 
l1E-6 Ground Motons 
100 
200 
300 
400 
500 
600 
700 
800 
10 More 
Impact Veocm/secFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-53. Histogram for Relative Impact Velocity (110-6 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-85 September 2004 

Drift Degradation Analysis 
i0 
0 
0 
90120150180210240270300330360 
0% 
i1E-6 Ground Motons 
100 
200 
300 
400 
500 
600 
30 
6Impact Angle 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-54. Histogram for Impact Angle (110-6 Annual Probability of Exceedance Hazard) 
i0 
0 
(/) 
0% 
l1E-6 Ground Motons 
500 
1000 
1500 
2000 
2500 
2000 4000 6000 8000 10000 12000 14000 More 
Impact Momentum kg.msecFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-55. Histogram for Impact Momentum (110-6 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-86 September 2004 

Drift Degradation Analysis 
i0 
0 
(J) 
0% 
i1E-6 Ground Motons 
500 
1000 
1500 
2000 
2500 
4000 8000 12000 160002000024000 28000 More 
Impact Energy 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-56. Histogram for Impact Energy (110-6 Annual Probability of Exceedance Hazard) 
6.3.1.2.5 Results for Seismic Analysis Subjected to 110-7 Annual Probability of 
Exceedance Ground Motions 
The results for a complete set of 3DEC analyses subjected to the postclosure hazard level of 
110-7 annual probability of exceedance ground motions are presented in this section. 
Figure 6-57 compares the input ground motion for the vertical component (V, Ground Motion 
Set 3) with the recorded velocities at the center of the model. The results confirm the correct 
wave inputs and proper wave propagation in the 3DEC model. 
Figure 6-58 shows a perspective view of blocks impacting the drip shield in the 3DEC dynamic 
simulation. Extensive rockfall is observed for many simulations for this level of ground motion. 
Numerical difficulties were encountered for several simulations due to the extremely large 
inertial force applied to the discontinuum. A total of 44 simulations were completed for this 
level of ground motion (Simulations 19, 24, 25, 28, 38, and 52 were not completed due to 
numerical difficulties). The sufficiency of 44 simulations to capture the rockfall characteristics 
for this level of ground motion is documented in Appendix K. 
Time histories of normal and shear stresses for fractures and rock bridges close to the opening 
were recorded during the seismic shaking in the 3DEC model. Figure 6-59 shows normal and 
shear stress time histories at the same selected fracture subcontacts as presented for the 110-5 
annual probability of exceedance ground motions (3DEC simulation #16 with ground motion set 
#11). Peak normal stress at subcontacts a and c reaches approximately 25 MPa and 30 MPa 
respectively, while the peak shear stress reaches to 25 MPa (information of the subcontacts is 
provided in Figure 6-40). The stress paths of the fracture subcontacts are plotted against the 
fracture Coulomb slip criterion and rock bridge strength criterion, as shown in Figure 6-60. The 
in situ normal and shear stress state along the fracture is identified as the orange square for each 
ANL-EBS-MD-000027 REV 03 6-87 September 2004 

Drift Degradation Analysis 
subcontact in the figure. As with other postclosure level ground motions, the fracture containing 
subcontact a yielded during seismic motions. However, the stress paths for rock bridges 
containing subcontacts b and c are under the rock strength criterion when subjected to 110-7 
ground motion. 
The percentages of the area of fracture slip/separation versus the total area of joint planes for the 
selected cases were calculated and presented in Table 6-15. Most of the fractures (greater than 
95 percent for most cases) have undergone shear slip or tensile separation when subjected to 
110-7 ground motions. Bridge damage percentages are also presented in Table 6-15. It is 
predicted that, for the majority of the cases, around 20 percent bridge area would be damaged by 
shaking of 110-7 ground motions. However, for certain large ground motions (e.g., ground 
motion #3 for Case 38), damage percentage goes up to approximately 60 percent. Correlation of 
the bridge damage percentage versus peak ground velocity shows a strong relationship between 
the two. A detailed discussion on the bridge damage is provided in Section 6.3.1.6.3. 
The results of the 44 3DEC simulations are summarized in Table 6-16. A total of 3,387 blocks 
have been identified from the analyses. A detailed listing of the impact information for each 
recorded block is included in an output DTN of this document 
(DTN: MO0408MWDDDMIO.002, file nonlith rockfall characteristics in emplacement drifts 
with 1e-7 gm.xls). Summary statistics for these parameters are provided in Table 6-17. The 
maximum rockfall block mass predicted is 28.29 metric tons, which is similar to the prediction 
for the 110-6 annual probability of exceedance ground motions. The median block size is 
0.15 metric tons, similar to the value predicted for the 110-5 and 110-6 annual probability of 
exceedance hazards. Figures 6-61 to 6-65 present the histograms and the cumulative frequency 
of occurrence for the five impact parameters. 
() 
li (m/) 
iiion 
-20.00 
-15.00 
-10.00 
-5.00 
0.00 
5.00 
10.00 
15.00 
0.00E+00 5.00E+00 1.00E+01 1.50E+01 2.00E+01 2.50E+01 
TimesecGround VeoctysecInput Sesmc Wave 
Recorded Mot
NOTE: The ground motion was recorded at the drip shield block during 3DEC simulation. 
Figure 6-57. Comparison of Input Seismic Wave and Recorded Velocities in 3DEC Model for 110-7 
Annual Probability of Exceedance Ground Motion (Ground Motion Set 3, Vertical Motion) 
ANL-EBS-MD-000027 REV 03 6-88 September 2004 

Drift Degradation Analysis 
Figure 6-58. Illustration of the Simulation of Rockfall Impact to the Drip Shield (3DEC Simulation # 64, 
110-7 Ground Motion # 14, at t = 7.37 sec) 
0 2 4 6 8 
() 
(-5.0E+06 
0.0E+00 
5.0E+06 
1.0E+07 
1.5E+07 
2.0E+07 
2.5E+07 
3.0E+07 
3.5E+07 
10 12 
TimesecStress on FracturePa) 
normal stress at subcontact a shear stress at subcontact a 
normal stress at subcontact b shear stress at subcontact b 
normal stress at subcontact c shear stress at subcontact c 
NOTE: Information for the Subcontacts is presented in Figure 6-40. 
Figure 6-59. Time Histories for Normal and Shear Stress at Selected Fracture Subcontacts for 110-7 
Annual Probability of Exceedance Hazard (Simulation 16, Ground Motion Set 11) 
ANL-EBS-MD-000027 REV 03 6-89 September 2004 

Drift Degradation Analysis 
l) 
)
iliiiiii0.0E+00 
1.0E+07 
2.0E+07 
3.0E+07 
4.0E+07 
5.0E+07 
6.0E+07 
7.0E+07 
8.0E+07 
-2.0E+07 -1.0E+07 0.0E+00 1.0E+07 2.0E+07 3.0E+07 4.0E+07 
Norma Stress (PaShear Stress (PaSubcontact a 
Subcontact b 
Subcontact c 
Jont Coulomb sp crteron 
Rock brdge strength crteron 
NOTE: Information for the Subcontacts is presented in Figure 6-40. 
Figure 6-60. Normal and Shear Stress Path at Selected Fracture Subcontacts for 110-7 Annual 
Probability of Exceedance Hazard (Simulation 16, Ground Motion Set 11) 
Table 6-15. Summary of Joint Slip/Separation and Bridge Damage for 110-7 Ground Motions for 
Selected Cases 
Parameter Case 40 Case 66 Case 23 Case 48 Case 45 Case 63 Case 31 
Total Joint Area (m2) 4251 2583 3026 4260 4737 1911 3400 
Total Bridge Area (m2) 885 592 550 923 1054 425 720 
Percentage of Joint 
Slip/Separation 97.18% 92.26% 97.88% 97.11% 97.91% 98.53% 98.32% 
Percentage of Bridge 
Damaged 27.78% 61.99% 29.07% 21.99% 18.22% 20.47% 16.92% 
ANL-EBS-MD-000027 REV 03 6-90 September 2004 

Drift Degradation Analysis 
Table 6-16. Summary of 3DEC Rockfall Prediction for 110-7 Annual Probability of Exceedance Hazard 
Parameter Value 
Simulations Completed 44 
Total Number of Rockfall 3387 
Total Volume of Rockfall (m3) 705.2 
Total Length of Drift Simulated (m) 1100 
Number of Blocks per km 3079 
Volume of Rockfall per km (m3) 641.1 
Table 6-17. Statistic Summary of the Rockfall Impact Parameters, 110-7 Annual Probability of 
Exceedance Hazard 
Parameter 
Block Mass 
(tonnes) 
Relative Impact 
Velocity (m/sec) 
Impact Angle 
(degree) 
Impact 
Momentum 
(kg*m/sec) 
Impact Energy 
(Joules) 
Mean 0.50 4.17 135 1676 4146 
Median 0.15 3.78 124 528 1022 
Standard Deviation 1.43 2.47 92 5293 16749 
Skewness 8.81 1.21 0.94 20 26 
Range 28.26 20.90 359 199976 706914 
Minimum 0.02 0.04 0 3 0 
Maximum 28.29 20.94 359 199979 706914 
Sum 1699.57 NA NA 5677385 14044153 
NA = Not Applicable 
i0 
01412) 
0% 
l1E-7 Ground Motons 
200 
400 
600 
800 
1000 
1200 
1400 
1600 
0.20.40.60.81.41.82.5More 
Block Size (metric tonFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-61. Histogram for Block Mass (110-7 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-91 September 2004 

Drift Degradation Analysis 
i0 
0 1 2 3 4 5 6 7 8 9 
lity () 
0% 
i1E-7 Ground Motons 
100 
200 
300 
400 
500 
600 
700 
10 More 
Im pact Veocm /secFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-62. Histogram for Relative Impact Velocity (110-7 Annual Probability of Exceedance Hazard) 
i0 
03060900% 
i1E-7 Ground Motons 
100 
200 
300 
400 
500 
600 
700 
120 
150 
180 
210 
240 
270 
300 
330 
360 
Impact Angle 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-63. Histogram for Impact Angle (110-7 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-92 September 2004 

Drift Degradation Analysis 
i0 
0 
(/) 
0% 
i1E-7 Ground Motons 
500 
1000 
1500 
2000 
2500 
2000 4000 6000 8000 1000012000 14000 More 
Impact Momentum kg.msecFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-64. Histogram for Impact Momentum (110-7 Annual Probability of Exceedance Hazard) 
i0 
0 
(J) 
0% 
l1E-7 Ground Motons 
500 
1000 
1500 
2000 
2500 
4000 8000 12000 16000 20000 24000 28000 More 
Impact Energy 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-65. Histogram for Impact Energy (110-7 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-93 September 2004 

Drift Degradation Analysis 
6.3.1.2.6 Results for Seismic Analysis Subjected to Preclosure Ground Motion 
The results for the preclosure hazard level of 110-4 annual probability of exceedance ground 
motion are presented in this section. The 510-4 annual probability of exceedance ground 
motion was not included due to the relatively small amount of rockfall predicted for the 
110-4 motion. As described in Section 6.3.1.2.1, only a single set of ground motion is 
considered in the rockfall analysis for preclosure seismic level for the deterministic design 
approach. Due to the much lower amplitude of ground motion considered for the preclosure 
hazard level and, hence, much less rockfall hazard anticipated, only 32 simulations were 
conducted for preclosure cases compared to 50 cases for postclosure. The sufficiency of 32 
simulations to capture the rockfall characteristics for the preclosure ground motion is 
documented in Appendix K. 
Figure 6-66 compares the input ground motion for the first horizontal component (H1) with the 
recorded velocities at the center of the model. The results confirm that the correct wave inputs 
were used and proper wave propagation occurs in the 3DEC preclosure seismic analyses. 
Figure 6-67 shows rockfall impacting a drip shield in the 3DEC dynamic simulation. Blocks are 
small and sporadic in most of the simulations. 
Time histories of normal and shear stresses for fractures and rock bridges close to the opening 
were recorded during the seismic shaking in the 3DEC model. Figure 6-68 shows normal and 
shear stress time histories at the same selected fracture subcontacts as presented in Figure 6-40. 
The stress paths of the fracture subcontacts are plotted against the fracture Coulomb slip criterion 
and rock bridge strength criterion, as shown in Figure 6-69. The in situ normal and shear stress 
states along the fracture are identified as the orange squares for each subcontact in the figure. As 
with the postclosure level ground motions, the fracture containing subcontact a yielded during 
seismic motions. However, the stress paths for rock bridges containing subcontacts b and c are 
under both the Coulomb slip criterion and the rock strength criterion when subjected to 
110-4 ground motion. 
The percentages of the area of fracture slip/separation versus the total area of fracture planes 
under 110-4 ground motion for the selected cases were calculated and presented in Table 6-18. 
Contrary to the postclosure earthquake results, only around 20 percent of total fractures have 
undergone shear slip or tensile separation when subjected to 110-4 ground motions. Limited 
rock bridge damage is observed for this level of ground motion, as presented in Table 6-18. 
The results of the 32 3DEC preclosure simulations are summarized in Table 6-19. 
Approximately half of the simulations predicted rockfall under seismic shaking. A total of 
428 blocks were identified from the analyses. 
The associated impact parameters due to rockfall on the drip shield are included in an output 
DTN of this document (DTN: MO0408MWDDDMIO.002, file nonlith rockfall characteristics 
in emplacement drifts with 1e-4 gm.xls). Summary statistics for these parameters are provided in 
Table 6-20. The maximum rockfall block mass predicted for preclosure case is 2.72 metric tons 
with a median block size of 0.10 metric ton. Most of the estimated parameters are considerably 
smaller than predicted for postclosure cases. Figures 6-70 to 6-74 present the histograms and the 
cumulative frequency of occurrence for the five parameters. The relatively low impact 
ANL-EBS-MD-000027 REV 03 6-94 September 2004 

Drift Degradation Analysis 
velocities, as shown in Figure 6-71, indicate that block fall-out is mainly due to free fall. 
Differential acceleration or energy trapping to induce high ejection velocity is not observed. 
The bounding impact velocity for preclosure rockfall is required for characterization of credible 
rockfalls of the preclosure period (BSC 2004 [DIRS 168508]). Calculation of the bounding 
velocity is based on the drop height of the fallen rock at one drift diameter above the drift crown. 
The approach is based on the observation of drift profiles at areas with rockfall in 3DEC 
simulations. Detailed description of the bounding calculation is provided in file, impact velocity 
bounding calculation for preclosure rockfall rev1.mcd, listed in Appendix A (Table A-1). The 
bounding impact velocity is calculated to be 14 m/sec, which is approximately two times the 
maximum impact velocity listed in Table 6-20. 
0 
0 
() 
lity () 
ii-0.5 
-0.4 
-0.3 
-0.2 
-0.1 
0.1 
0.2 
0.3 
0.4 
0.5 
10 20 30 40 50 60 70 80 
TimesecGround Veocm/secInput Sesmc Wave 
Recorded Motion 
Figure 6-66. Comparison of Input Seismic Wave and Recorded Velocities in 3DEC Model for 110-4 
Annual Probability of Exceedance Ground Motion (H1) 
ANL-EBS-MD-000027 REV 03 6-95 September 2004 

Drift Degradation Analysis 
NOTE: The ground motion was recorded at the drip shield block during 3DEC simulation. 
Figure 6-67. Illustration of the Simulation of Rockfall Impact to the Drip Shield (3DEC Simulation for 
110-4 Preclosure Run 21, at t = 32.5 sec) 
0 
() 
) 
-1.0E+06 
1.0E+06 
3.0E+06 
5.0E+06 
7.0E+06 
9.0E+06 
1.1E+07 
1.3E+07 
1.5E+07 
10 20 30 40 50 60 70 
TimesecStress on Fracture (Panormal stress at subcontact a shear stress at subcontact a 
normal stress at subcontact b shear stress at subcontact b 
normal stress at subcontact c shear stress at subcontact c 
NOTE: Subcontact Information is presented in Figure 6-40. 
Figure 6-68. Time Histories for Normal and Shear Stress at Selected Fracture Subcontact for 110-4 
Annual Probability of Exceedance Hazard (Simulation 16) 
ANL-EBS-MD-000027 REV 03 6-96 September 2004 

Drift Degradation Analysis 
l) 
) 
a 
b 
c 
iliiiiii0.0E+00 
1.0E+07 
2.0E+07 
3.0E+07 
4.0E+07 
5.0E+07 
6.0E+07 
7.0E+07 
-1.5E+07 -1.0E+07 -5.0E+06 0.0E+00 5.0E+06 1.0E+07 1.5E+07 2.0E+07 
Norma Stress (PaShear Stress (PaSubcontactSubcontactSubcontactJont Coulomb sp crteron 
Rock brdge strength crteron 
NOTE: Subcontact Information is presented in Figure 6-40. 
Figure 6-69. Normal and Shear Stress Path at Selected Fracture Subcontact for 110-4 Annual 
Probability of Exceedance Hazard (Simulation 16) 
Table 6-18. Summary of Joint Slip/Separation and Bridge Damage for 110-4 Ground Motions for 
Selected Cases 
Parameter Case 40 Case 23 Case 45 Case 31 
Total Joint Area (m2) 4251 3026 4737 3400 
Total Bridge Area (m2) 885 550 1054 720 
Percentage of Joint Slip/Separation 26.68% 17.68% 26.73% 14.35% 
Percentage of Bridge Damaged 0.00% 0.19% 0.00% 0.02% 
ANL-EBS-MD-000027 REV 03 6-97 September 2004 

Drift Degradation Analysis 
Table 6-19. Summary of 3DEC Rockfall Prediction for 110-4 Annual Probability of Exceedance Hazard 
Parameter Value 
Simulations Completed 32 
Total Number of Rockfall 428 
Total Volume of Rockfall (m3) 39.4 
Total Length of Drift Simulated (m) 800 
Number of Blocks per km 535 
Volume of Rockfall per km (m3) 49.3 
Table 6-20. Statistical Summary of the Rockfall Impact Parameters, 110-4 Annual Probability of 
Exceedance Hazard 
Block Mass 
(tonnes) 
Relative Impact 
Velocity (m/sec) 
Impact Angle 
(degree) 
Impact Momentum 
(kgm/sec) 
Impact Energy 
(Joules) 
Mean 0.22 2.43 169.15 601 1022 
Median 0.10 2.25 141.29 213 232 
Standard Deviation 0.33 1.38 108.31 1092 2224 
Skewness 3.47 0.54 0.36 4 5 
Range 2.69 7.17 357.12 9273 20358 
Minimum 0.02 0.03 2.70 1 0 
Maximum 2.72 7.20 359.82 9274 20358 
Sum 95.00 NA NA 257069 437350 
NA = Not Applicable 
i0 
50 
0 1 2 3 4 5 6 7 8 
(i0% 
l1E-4 Ground Moton 
100 
150 
200 
250 
300 
350 
400 
450 
Rockfall mass metrc ton) 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-70. Histogram for Block Mass (110-4 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-98 September 2004 

Drift Degradation Analysis 
i0 
20 
40 
60 
80 
0 1 2 3 4 5 6 7 8 9 
lity () 
0% 
l1E-4 Ground Moton 
100 
120 
140 
10 More 
Impact Veocm/secFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumuative % 
Figure 6-71. Histogram for Impact Velocity (110-4 Annual Probability of Exceedance Hazard) 
ion 
0 
10 
20 
30 
40 
50 
60 
70 
0306090) 
0% 
i1E-4 Ground Mot120 
150 
180 
210 
240 
270 
300 
330 
360 
Impact Angle (degreeFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-72. Histogram for Impact Angle (110-4 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-99 September 2004 

Drift Degradation Analysis 
i0 
50 
0 
(/) 
0% 
i1E-4 Ground Moton 
100 
150 
200 
250 
300 
350 
400 
2000 4000 6000 8000 10000 12000 14000 More 
Impact Momentum kg.msecFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-73. Histogram for Impact Momentum (110-4 Annual Probability of Exceedance Hazard) 
i0 
50 
0 
(J) 
0% 
i1E-4 Ground Moton 
100 
150 
200 
250 
300 
350 
400 
4000 8000 1200016000200002400028000 More 
Impact Energy 
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Frequency 
Cumulatve % 
Figure 6-74. Histogram for Impact Energy (110-4 Annual Probability of Exceedance Hazard) 
ANL-EBS-MD-000027 REV 03 6-100 September 2004 

Drift Degradation Analysis 
6.3.1.3 Thermal Consideration in Nonlithophysal Units 
The extensive analysis of drift stability in nonlithophysal units discussed in Section 6.3.1.2 has 
been conducted considering an in situ stress state perturbed by the excavation of the 
emplacement drifts only. The effects of the thermally generated stresses in the rock mass 
surrounding the repository were not taken into account. This section provides the results for the 
analyses including thermal consideration. 
3DEC was not used for the thermal-mechanical analysis of the drift in the nonlithophysal units 
because it has a simplistic model of heat conduction based on analytic solutions. The analytic 
solutions deal with complicated boundaries in an approximate way. Instead, the analysis for the 
nonlithophysal units was done as a three-step process. Variation of temperatures throughout the 
rock mass due to heating was calculated using NUFT (Section 6.2), which generated temperature 
fields for a number of times after waste emplacement. This implies that the mechanical models 
that use those temperature fields will be subjected to discrete temperature and, consequently, 
stress changes when moving from one temperature state to another. In reality, those changes are 
continuous. Because the mechanical models of drift stability are non-linear, their results are 
path-dependent. To ensure that the model results are not affected by discrete stress changes, the 
temperature increment was limited to around 5C. It was difficult to perform thermal stress 
calculations in the 3DEC model because it is limited to a certain region around the drift. Also, 
the model axes are oblique relative to the drift axis, making it very difficult to extend the model 
to the plane of symmetry between the drifts, which is necessary for stress calculation due to 
heating. Therefore, the stress changes due to the temperature changes, as calculated by NUFT 
and described in Section 6.2, were calculated using the continuum code FLAC. In the next step, 
elastic stress states are imported from FLAC into 3DEC in a sequential manner. For each elastic 
stress change due to temperature change, 3DEC is first run elastically to equilibrium (all joints 
were elastic). Subsequently, the finite strength was assigned to the joints, and the new 
equilibrium was determined. 
Thermal-mechanical analysis was conducted for two sets of thermal rock mass properties 
(discussed in Section 6.2): 
 Base case, using the mean values of thermal conductivity and specific heat 
 Thermal sensitivity case, using the values for thermal conductivity and specific heat one 
standard deviation smaller than the mean. 
The values for the sensitivity case thermal properties are provided in Section 6.2. 
The fracture patterns included for thermal-mechanical analysis were selected based on the 
rockfall results from seismic analyses of 110-5 annual probability of exceedance. Three fracture 
patterns, corresponding to the cases with most rockfall (Case 38 with Fracture Pattern 29), the 
median rockfall (Case 45 with Fracture Pattern 39), and the least rockfall (Case 63 with Fracture 
Pattern 96), were selected. The results for these fracture patterns with other levels of ground 
motion also indicate the selected patterns are adequate to represent the range of rockfall. 
ANL-EBS-MD-000027 REV 03 6-101 September 2004 

Drift Degradation Analysis 
Rockfall induced by thermal loading are found to be minor. Tables 6-21 and 6-22 present the 
rockfall predictions considering only thermal loading for the thermal base case and sensitivity 
case respectively. The results are presented for the beginning of heating (1 year), at the peak of 
temperature (80 years), and at the end of the regulatory period (10,000 years). The block size for 
rockfall induced by thermal effect is small with a mean size less than 0.2 metric ton. The impact 
of thermal properties on rockfall is insignificant considering the close amount of rockfall 
predicted for the base case and sensitivity case. The stress paths (shear stress versus normal 
stress) on the fractures around the drift (in the wall and the roof) for Case 63 with Fracture 
Pattern 96 considering the base case thermal properties, are shown in Figures 6-75 and 6-76. 
Stress paths at similar locations for other cases considered in the thermal-mechanical analyses 
have also been generated and reviewed. For most of the points (particularly in the wall), the 
stress paths move away from the slip surface, indicating increasing block stability. The analysis 
is carried out considering the blocks to be elastic. To demonstrate that heating will not induce 
stress levels inside the blocks sufficient to cause damage, stress paths from the linearly elastic 
model (for nonlithophysal rock stiffness) are shown in Figures 6-77 and 6-78 relative to the 
Mohr-Coulomb yield surface (using an unconfined compressive strength of 70 MPa and a 40 
friction angle). The unconfined compressive strength of 70 MPa is the recommended rock mass 
strength value presented in Figure E-22. The friction angle of 40 is a conservative estimate 
based on the range of rock mass friction angle reported in Subsurface Geotechnical Report 
(BSC 2003 DIRS [166660], Table 8-41). In both the wall and the roof, thermally induced stress 
variations are well within the elastic region. The approach of linear block behavior during 
thermal loading is justified. Stress paths for Case 63 considering the thermal properties one 
standard deviation smaller than the mean, are presented in Figures 6-79 and 6-80. The paths are 
similar to the base case results presented in Figures 6-75 and 6-76 with normal and shear stresses 
slightly magnified. The effect of seismic shaking, in addition to thermal loading, is discussed in 
Section 6.3.1.4. 
Table 6-21. Rockfall in Nonlithophysal Rock Due to Heating, Base Case of Thermal Properties 
Case 
1 yr 80 yr 10,000 yr 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
38 15 0.50 28 0.88 28 0.88 
45 0 0.00 20 0.79 25 0.80 
63 1 0.09 1 0.09 3 0.13 
Table 6-22. Rockfall in Nonlithophysal Rock Due to Heating, Sensitivity Case of Thermal Properties 
Case 
1 yr 80 yr 10,000 yr 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
38 11 0.40 34 2.49 35 2.50 
45 0 0.00 18 0.60 20 0.62 
63 2 0.10 2 0.10 3 0.13 
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Drift Degradation Analysis 
6.3.1.4 Combined Seismic and Thermal Effects in Nonlithophysal Units 
The effect of the thermal stresses on seismic drift stability depends on how the stress state, 
throughout the rock mass and on the pre-existing fractures, changes in the stress space relative to 
the failure surface. If the stress state (particularly in the vicinity of the drifts) predominantly 
moves away from the failure surface due to stress changes caused by heating, the rock mass 
becomes more stable and resistant to ground shaking. However, if the stress state predominantly 
moves toward, or reaches, the yield surface (i.e., rock mass yields during the heating), there will 
be more rockfall caused by ground motion. It is difficult to determine a single index or condition 
that characterizes this effect in an integrated way for the entire rock mass. 
1.0 E +07 
shear stress (Pa) 
8.0 E +06 
6.0 E +06 
4.0 E +06 
2.0 E +06 
0.0 E +00 
1radius from wall 
0.75*ra dius from wal0.5*rad ius from wall 
0.25*ra dius from wal0.1*rad ius from wall 
l 
l 
S lip condition 
0 .0E +0 4.0 E +6 8.0E+6 1.2E+7 1.6E+7 
norm al stress (Pa) 
Figure 6-75. Stress Paths at Selected Fractures in the Drift Wall: Case 63 with Fracture Pattern 96 
shear stress (Pa) 
iiiSliion 
0.0E+00 
2.0E+06 
4.0E+06 
6.0E+06 
8.0E+06 
1.0E+07 
1radus from roof 
0.75*radus from roof 
0.5*radius from roof 
0.25*radus from roof 
0.1*radius from roof 
p condit
0.0E+0 4.0E+6 8.0E+6 1.2E+7 1.6E+7 2.0E+7 2.4E+7 
norm al stress (Pa) 
Figure 6-76. Stress Paths at Selected Fractures in the Drift Roof: Case 63 with Fracture Pattern 96 
ANL-EBS-MD-000027 REV 03 6-103 September 2004 

Drift Degradation Analysis 
Figure 6-77. Stress Paths in the Drift Wall: Elastic Model 
Figure 6-78. Stress Paths in the Drift Roof: Elastic Model 
ANL-EBS-MD-000027 REV 03 6-104 September 2004 

Drift Degradation Analysis 
Temperatures around the emplacement drift will increase for a certain period of time after 
emplacement of the waste; however, as a result of decay of the released heat, the temperatures 
will also decrease. Consequently, the stress state around the repository during the regulatory 
period will be transient. A simplified approach was adopted in which rockfall caused by ground 
shaking was estimated for the most critical stress state during the regulatory period. Stress 
paths at a number of locations on the joints surrounding the drift were recorded during the 
temperature changes. The critical state (or time after waste emplacement) was determined by 
qualitative inspection of those stress paths. The model in the most critical state during the 
regulatory period was then subjected to a ground motion corresponding to 110-5 probability of 
annual occurrence. 
The effect of seismic shaking combined with thermal-mechanical effects was considered for the 
three cases presented in Section 6.3.1.3. Stress paths at five points on fractures in the wall and 
the roof of the drift (shown in Figures 6-75 and 6-76) move away, in general, from the yield. 
The critical state seems to be the in situ stress state (marked with a square at the beginning of 
each curve) for which extensive seismic stability analysis had been conducted. Another state of 
interest was the other extreme point on the stress path curves (also marked with a square), which, 
for Case 63 represented in Figures 6-75 and 6-76, corresponds to 80 years after waste 
emplacement. Comparison of rockfall with seismic shaking at the in situ stress state and at 
80 years after waste emplacement is provided in Table 6-23. It is apparent that heating 
significantly reduces the amount of rockfall. 
Comparison of rockfall with seismic shaking at the in situ stress state and at 80 years after waste 
emplacement for the thermal sensitivity case is provided in Table 6-24. These results are 
consistent with the base case prediction presented in Table 6-23. 
The results of rockfall thermal-mechanical and seismic analyses indicate that the condition with 
seismic shaking at in situ state (the cases considered in Section 6.3.1.2) is conservative since a 
higher number of unstable blocks and a larger amount of rockfall are predicted for the in situ 
state. Temperatures throughout the regulatory period will be higher than in situ temperatures. 
Table 6-23. Rockfall in Nonlithophysal Rock Due to 10-5 Ground Motion Combined with Thermal-
Mechanical Effects, Base Case of Thermal Properties 
Ground 
Time of Earthquake at 0 yr Time of Earthquake at 80 yr 
Rockfall Volume Rockfall Volume 
Case Motion Number of Rockfall (m3) Number of Rockfall (m3) 
38 3 173 42.03 56 13.59 
45 10 14 2.49 5 1.07 
63 11 0 0.00 2 5.93 
ANL-EBS-MD-000027 REV 03 6-105 September 2004 

Drift Degradation Analysis 
Table 6-24. Rockfall in Nonlithophysal Rock Due to 10-5 Ground Motion Combined with Thermal-
Mechanical Effects, Sensitivity Case of Thermal Properties 
Ground 
Time of Earthquake at 0 yr Time of Earthquake at 80 yr 
Rockfall Volume Rockfall Volume 
Case Motion Number of Rockfall (m3) Number of Rockfall (m3) 
38 3 173 42.03 43 11.41 
45 10 14 2.49 6 1.63 
63 11 0 0.00 3 7.93 
shear stress (Pa) 
1.4E+07
1.2E+07
1.0E+07
8.0E+06
6.0E+06
4.0E+06
2.0E+06
0.0E+00
1radius from wall 
0.75*radius from wall 
0.5*radius from wall 
0.25*radius from wall 
S0.1*radius from walip condition 
ll 
0.0E+0 4.0E+6 8.0E+6 1.2E+7 1.6E+7 2.0E+7 
normal stress (Pa) 
Figure 6-79. Stress Paths at Selected Fractures in the Drift Wall: Case 63 with Fracture Pattern 96, 
Thermal Sensitivity Case 
ANL-EBS-MD-000027 REV 03 6-106 September 2004 

Drift Degradation Analysis 
1.0E+07 
shear stress (Pa) 
8.0E+06 
6.0E+06 
4.0E+06 
2.0E+06 
0.0E+00 
0.0E+0 4.0E+6 8.0E+6 1.2E+7 1.6E+7 2.0E+7 2.4E+7 2.8E+7 3.2E+7 
i0.75*radi0.25*radi1radus from roof 
us from roof 
0.5*radius from roof 
us from roof 
0.1*radius from roof 
Slip condition 
normal stress (Pa) 
Figure 6-80. Stress Paths at Selected Fractures in the Drift Roof: Case 63 with Fracture Pattern 96, 
Thermal Sensitivity Case 
6.3.1.5 Rock Joint Degradation in Nonlithophysal Units 
Degradation Due to Time-Dependent Alteration of Rock Matrix or Joint Filling Materials 
from Postclosure Thermal and Moisture ConditionsThe rock mass surrounding the 
excavations may undergo over-stressing from thermal heating and/or time-dependent damage 
associated with static fatigue resulting from stress corrosion mechanisms. Another likely 
long-term effect includes the increasing amounts of moisture/air induced weathering along the 
joints close to the tunnels. This damaged and/or weathered material may result in block fallout 
in the nonlithophysal units. 
The time-to-failure for intact nonlithophysal rock blocks shows significantly less time 
dependency than for the lithophysal rock described in Appendix S (see Figure S-17). Therefore, 
insignificant time-related fracture growth is expected in the intact rock blocks. However, the 
potential exists for time-dependent yield of roughness (asperities) on fracture surfaces subjected 
to long-term shear stress. Time-related degradation of tunnels due to wetting and drying cycles 
is an important factor for drift stability in some rock types. These rock types are typically those 
in which highly-altered rock, or rock with significant swelling clay along fracture planes occurs. 
In the case of the host repository horizon at Yucca Mountain, these issues are not particularly 
important. Clay is not a common mineral in the crystallized rocks of the repository host horizon, 
nor are clay minerals a volumetrically significant fracture-coating material. Data to support this 
observation are described below. 
A number of detailed geological studies have been conducted at the Yucca Mountain site to 
define the basic mineralogy of the rocks, and the petrologic and geochemical processes that 
ANL-EBS-MD-000027 REV 03 6-107 September 2004 

Drift Degradation Analysis 
occurred during the formation of the Topopah Spring Tuff, and have continued from that time. 
These studies have included a detailed description of the mineralogy of the repository host 
horizon from samples and observations developed from surface-based core holes through the 
repository block, as well as from the ESF and ECRB Cross-Drift. From the standpoint of 
mechanical degradation of the rock mass, these studies show: 
 The Topopah Spring Tuff is largely composed of fine-grained feldspars and 
silicate-based rocks that formed during the cooling of the rock mass shortly after 
deposition. Clay-forming minerals were typically not formed during the petrogenesis of 
the repository host horizon. 
 Clays typically do not form significant fracture-fill materials in the crystallized rocks of 
the Topopah Spring Tuff. 
 There are limitations on the environmental conditions needed to form clays and indicate 
the minimum likelihood that clays might form along fractures in the near field of a 
repository. Therefore, mineral alteration during the postclosure is considered negligible. 
The following discussion summarizes the data obtained from a number of studies that support the 
above points. 
1. Mineralization in the Repository Host HorizonThe Topopah Spring Tuff is a 
compositionally zoned pyroclastic flow deposit. High-silica rhyolite forms 
approximately the lower two-thirds of the section and trachyte (or quartz latite) in the 
upper one-third of the section. The crystallized rocks that formed during the cooling 
of the deposit consist primarily of very fine-grained intergrowths of feldspar and silica 
polymorphs of quartz and cristobalite. These minerals typically crystallized from 
volcanic glass at temperatures of approximately 800 C. X-ray diffraction analyses of 
444 core samples from 13 boreholes that penetrate 3.5 km of the crystallized Topopah 
Springs Tuff indicate that there are different ratios of feldspar and silica polymorphs in 
the crystal-rich rocks (DTNs LADB831321AN98.002 [DIRS 109003], 
LADV831321AQ97.001 [DIRS 107142], LADV831321AQ99.001 [DIRS 109044], 
LA000000000086.002 [DIRS 107144]). In the crystal-rich member, 93 samples have 
mean percentages of feldspar (69.1percent), quartz (2.4 percent), cristobalite 
(13.3 percent), and tridymite (11.2 per cent), and in the crystal-poor member, 351 
samples have mean percentages of feldspar (55.7 per cent), quartz (15.8 per cent), 
cristobalite (19.3 percent), and tridymite (5.1 percent). The total of the percentages 
cited for these two members do not sum to 100 percent because there are minor 
amounts of other minerals in many of these rocks. Smectite values vary from trace 
amounts to 15 percent with a mean value of 3.1 percent. These compositions of rocks 
form the walls of fractures where the minerals are very fine-grained and form various 
textures; however, the minerals are relatively uniformly distributed at scales of 
millimeters to centimeters. These data indicate that concentrations of smectite 
minerals along fractures do not occur as a result of crystallization during cooling. 
2. Clay Infillings Are Rarely Observed Along Fractures in the ESF and ECRB 
Cross-DriftDetailed line survey data collected in the ECRB Cross-Drift indicate that 
ANL-EBS-MD-000027 REV 03 6-108 September 2004 

Drift Degradation Analysis 
of the 1,816 fractures in the 2.66-km long tunnel, only 10 (or 0.4per cent) of 
the discontinuities such as fractures, shears, and faults have some amount 
of clay (DTNs GS990408314224.001 [DIRS 108396], GS990408314224.002 
[DIRS 105625]). These 10 discontinuities are filled (or partially filled) with clay and 
broken or crushed rock or sand. Detailed studies of the clast textures, structures, and 
architectures of the broken or crushed rock or sand fill materials have not been 
completed, but general observations indicate many of these features do not show 
evidence of mechanical degradation and shear. Buesch and Lung (2003 
[DIRS 170297]) describe volcaniclastic tuffaceous sandstone and claystone as 
fracture-fill material in the crystallized rocks of the Tiva Canyon and Topopah Spring 
Tuff. They proposed that volcanic glass particles settled by gravity along open 
fractures from the superjacent nonwelded bedded tuffs, and the clay formed in place 
(possibly millions of years later) by water seeping along the fractures and reacting 
with the glass. This mechanism is entirely consistent with occurrences of clays in the 
ECRB Cross-Drift detailed line survey data. Detailed line survey data from the 
crystallized Topopah Spring Tuff in the ESF Main Drift indicate that only 4 per cent of 
the fractures recorded have clay as filling material. 
The Integrated Issue Resolution Status Report of NRC (NRC 2002 [DIRS 159538], 
Section 2.1.7.3.3.2, pp. 2.1.7-19 and 2.1.7-20) specifically discussed the work by 
Carlos et al. (1995 [DIRS 101326]) in regard to fracture fillings. Carlos et al. (1995 
DIRS 101326]) described the qualitative amount of materials in the fractures only, but 
typically they did not describe the amount or thickness of the mineral coatings. For 
example, if a mineral such as clay (smectite) is listed as major abundance, then this 
means that greater than 20 percent of the minerals in the fractures, but the mineral 
coating might be less than 1-mm thick. Only for mordenite in the crystallized 
Topopah Spring Tuff did Carlos et al. (1995 DIRS 101326]) describe about 1 percent 
of the fractures with this mineral and the amount increased with depth to more than 
20 percent (and more than 50 percent in some boreholes). The relevant point for this 
discussion is that selective fractures were sampled and the intention was not to 
quantify the relative proportion of fractures with specific minerals, nor to quantify the 
thickness or continuity of the mineral coatings. However, there is one detailed study 
of mineral coatings on fracture walls in core with descriptions of the percentages of 
the amount of mineral coatings and thickness of the coatings 
(DTN: LA9912SL831151.001 [DIRS 146447]). Borehole ESF-HD-TEMP-2 is a 60 m 
(200-ft) long, horizontal borehole in the Heated Drift Test, and the rocks are in the 
middle nonlithophysal (Tptpmn) zone of the Topopah Spring Tuff. Only fractures in 
two 1.3 m (4.3-ft) long segments of core were described [7.6 to 8.9 m (25.0 to 29.3 ft) 
and 18.9 to 20.3 m (62.15 to 66.45 ft)]. Clay forms localized deposits on the fracture 
surfaces that typically are less than 5 percent of the fracture surface area with 
thickness typically about 0.1 mm and a few deposits as much as 0.5-mm thick. These 
descriptions demonstrate that clay does not form continuous coatings on fracture walls 
and that the coats are very thin. 
3. Alteration of Repository Host Rocks is Not Expected in the Repository 
EnvironmentConditions such as temperature, chemistry of water, and amount of 
water needed for the alteration of feldspars in the crystallized host rock to form clay 
ANL-EBS-MD-000027 REV 03 6-109 September 2004 

Drift Degradation Analysis 
and other sheet silicate minerals (sericite) are not considered to have been present 
within the Topopah Spring Tuff since its formation. Sericite is a general term for very 
fine-grained sheet silicates (illites) that form with other alteration products in 
hydrothermal systems at temperatures near or above 400C, typically in acidic 
aqueous solutions (Jackson 1997 [DIRS 109119]). As pointed out by the predicted 
temperature conditions expected in the repository environment (e.g., Figure 6-25), 
these conditions are not anticipated in the near-field environment of the repository. 
Even in samples from the Drift Scale Test boreholes, the clays on fractures appeared to 
have been there prior to the test and were not affected by the experimental conditions. 
In summary, these petrologic and empirical relations indicate that clays typically do not form 
significant fracture-fill materials in the crystallized rocks of the Topopah Spring Tuff. They also 
indicate that the expected repository environmental conditions are not conducive to formation of 
clays during the postclosure period. Therefore, the impact of geochemical alteration within the 
postclosure environment is expected to have a negligible impact on drift degradation processes. 
3DEC Analysis for Time-Dependent Joint DegradationDrift stability due to the effect of 
time-dependent rock joint strength degradation is assessed based on a conservative estimate of 
the reduction of joint cohesion and friction angle. The reduced joint strength parameters are 
estimated to be represented by the residual state (after joint shear) with joint cohesion reduced to 
0 and the joint friction angle reduced to 30. The reduced friction angle is a typical value for a 
smooth joint reported by Goodman (1980 [DIRS 101966], p. 158) and is consistent with the 
observation of the cooling joints from direct shear test results (Table E-5). Dilation angle is also 
conservatively presumed to be zero considering the asperities on fracture surfaces had been 
sheared off, resulting in greater rockfall. The degradated joint strength and dilatational 
properties were applied in 110-5 seismic motion Cases 38, 45, and 63. These three cases cover 
the range of rockfall condition from the most rockfall to the least rockfall. The predicted number 
of rockfall and the total rockfall volume are presented in Table 6-25 with a comparison to the 
results of the base case. Approximately 30 to 40 percent rockfall increase is observed for the 
high rockfall case (Case 38), while the results were very similar for the median rockfall case 
(Case 45). The maximum block sizes are the same for the base case and the degraded joint case. 
As for the least rockfall case, limited rockfall is also observed even with degraded joints. In all, 
the degraded joint state results in higher rockfall prediction, but the amount of rockfall stays 
within the same order of magnitude as the base case. 
Table 6-25. Predicted Rockfall for Degraded Joints with Comparison to the Base Case Results 
Case 
Degradated State 
(cohesion = 0, friction angle = 30, dilation 
angle = 0) 
Base Case 
(cohesion = 0.1 MPa, friction angle = 41, 
dilation angle = 0) 
Number of 
Blocks 
Maximum 
Block (m3) 
Rockfall 
Volume (m3) 
Number of 
Blocks 
Maximum 
Block (m3) 
Rockfall 
Volume (m3) 
38 233 3.53 59.23 173 3.53 42.03 
45 16 0.84 2.21 14 0.84 2.49 
63 7 0.13 0.39 0 0 0.00 
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Drift Degradation Analysis 
6.3.1.6 Sensitivity Study of the Parameters 
There are four major variable sets included in the three-dimensional discontinuum analysis: 
ground motion, joint geometrical properties, joint and intact mechanical properties, and thermal 
stress history. For the ground motion parameters, four levels of annual probability of exceedance 
(110-4, 110-5, 110-6, and 110-7) are included, and 15 sets of ground motions were used for 
each hazard level in the postclosure consideration. The description of the ground motions used is 
provided in Section 6.3.1 and Appendix X. Results for the sensitivity study on the probability 
level, peak ground velocities, energy contents, and orientation of horizontal motions in the 3DEC 
model to the rockfall prediction are presented in Section 6.3.1.6.1. 
The variability of joint geometrical properties is incorporated into the application of FracMan to 
generate a 100-m cube fracture network. A total of 50 drift locations were selected from the 
100-m cube fractured rock mass for the 3DEC analyses. Results from the analyses of 50 drift 
locations (or fracture patterns) cover the variability of joint geometrical properties as verified in 
Appendix K. 
The results presented in previous sections are based on the base case material properties 
presented in Table 6-3. The impact of the variability of joint properties to rockfall prediction is 
described in Section 6.3.1.6.2. Variation of the rock bridge strength is considered in 
Section 6.3.1.6.3. A linear elastic material is used as the intact block material for the base case. 
The likelihood of breaking and spalling of the intact rock subject to vibratory ground motions is 
discussed in Section 6.3.1.6.4. Other sensitivity and uncertainty studies include model 
dimension and block deletion after impacting the drip shield. These are addressed in 
Sections 6.3.1.6.5 and 6.3.1.6.6, respectively. 
Sensitivity analyses were conducted using the representative cases with 110-5 annual probability 
of exceedance ground motions except for the consideration of block deletion in Section 6.3.1.6.6. 
Similar to the thermal-mechanical analyses, three cases corresponding to the case with most 
rockfall (Case 38 with Fracture Pattern 29 and Ground Motion 3), the case with the median 
rockfall (Case 45 with Fracture Pattern 39 and Ground Motion 10), and the case with least 
rockfall (Case 63 with Fracture Pattern 96 and Ground Motion 11), were selected. 
6.3.1.6.1 Ground Motion Parameters 
The ground motion time histories were truncated at 5 percent and 95 percent energy content to 
shorten the time required to conduct the dynamic analyses. The analyses show that the majority 
of the rockfall occurs coincident with the arrival of the strong motion, which is typically within 
the first 15 seconds of shaking. The truncating of the ground motion appears to have minor 
impact on the amount of rockfall. 
Four levels of annual probability of exceedance (110-4, 110-5, 110-6, and 110-7) plus 15 sets 
of ground motions for each postclosure level were included in the drift degradation study to 
ensure a reasonable distribution of spectral shapes and time history durations. Results for the 
sensitivity study on the probability level, peak ground velocities, energy contents, and orientation 
of horizontal motions in the 3DEC model to the rockfall prediction are presented in this section. 
ANL-EBS-MD-000027 REV 03 6-111 September 2004 

Drift Degradation Analysis 
Probability LevelsThe predicted rockfall results for each level of ground motions are presented 
in the subsections of Section 6.3.1.2. The results are summarized and compared in this section to 
observe the trend of rockfall versus ground motions with various annual probability of 
exceedance. Figure 6-81 shows the comparison of histograms of block mass for the ground 
motions considered. The rockfall number increases as the frequency of occurrence of ground 
motion gets lower. Figure 6-82 presents the cumulative percentage of block size distribution 
with block mass in a logarithmic scale. Essentially, the results show that the motions result in 
the same general negative exponential distribution of block sizes. As expected, a higher portion 
of large blocks is predicted for lower frequency ground motions. 
A comparison of the rockfall statistics is provided in Tables 6-26 and 6-27. The number and 
volume of blocks per km increase substantially in going from the preclosure motion to 
postclosure motions. The predicted rockfall volume per km for 110-7 ground motions is 
approximately 12 times of that for 110-4 ground motions. The predicted mean, median, and 
maximum block size also show a large increase from the preclosure motion to postclosure 
motions. However, the differences of the block size statistics in between the postclosure motions 
are relatively minor, especially for the results of 110-6 and 110-7 ground motions. 
Table 6-26. Comparison of Rockfall Statistics for Preclosure and Postclosure Events 
Statistic 
Ground Motion 
10-4 10-5 10-6 10-7 
Runs Completed 32 50 50 44 
Total Number of Rockfall 428 1764 2797 3387 
Total Volume of Rockfall (m3) 39.4 255.4 497.7 705.2 
Total Length of Drift Simulated (m) 800 1250 1250 1100 
Number of Blocks per km 535 1414 2238 3079 
Volume of Rockfall per km (m3/km) 49.3 204.3 398.2 641.1 
Table 6-27. Statistic Summary of the Block Size (metric ton) for Preclosure and Postclosure Events 
Statistic 
Ground Motion 
10-4 10-5 10-6 10-7 
Mean 0.22 0.35 0.43 0.50 
Median 0.10 0.12 0.13 0.15 
Standard Deviation 0.33 0.93 1.30 1.43 
Skewness 3.47 10.03 11.61 8.81 
Range 2.69 19.04 28.19 28.26 
Minimum 0.02 0.02 0.02 0.02 
Maximum 2.72 19.07 28.22 28.29 
Sum 95.00 615.97 1200.43 1699.57 
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Drift Degradation Analysis 
0 
0.20.40.60.81 
1.4 
2.54 
12 
0 
1.8 
More 
200 
400 
600 
800 
1000 
1200 
1400 
Frequency 
Block Mass (metric ton) 
1e-4 events 
1e-5 events 
1e-6 events 
1e-7 events 
Figure 6-81. Comparison of Histograms of Block Mass from Preclosure and Postclosure Ground Motions 
1 10 
l.00% 
10.00% 
20.00% 
30.00% 
40.00% 
50.00% 
60.00% 
70.00% 
80.00% 
90.00% 
100.00% 
0.1 100 
Block Mass (metric ton) 
Cumuative Percentage 
1e-4 events 
1e-5 events 
1e-6 events 
1e-7 events 
Figure 6-82. Comparison of Block Size Distribution from Preclosure and Postclosure Ground Motions 
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Drift Degradation Analysis 
Peak Ground Velocities and Energy ContentsCorrelation of the rockfall volume per 3DEC 
simulation with the peak ground velocity and energy content in terms of Arias Intensity is 
presented in Figures 6-83 and 6-84. The three levels of postclosure ground motions are included. 
At any given level of PGV, the variability in rockfall based on the variability in fracture pattern 
and ground motion frequency characteristics results in a fairly wide distribution in response. 
Although no strong relationship is observed between rockfall volume and PGV, a roughly linear 
relationship exists between the upper bound to rockfall volume and PGV on this semi-log plot. 
It appears that the predominant mechanism for variability in rockfall at a given level of PGV is 
the fracture pattern. 
70 
Rockfall Volume per Simulation (m^3) 
60 
50 
40 
30 
20 
10 
0 
1e-5 motions 
1e-6 motions 
1e-7 motions 
10 100 1000 10000 
Peak Ground Velocity (cm/s) 
Figure 6-83. Rockfall Volume vs. Peak Ground Velocity 
70 
Rockfall Volume per Simulation (m^3) 
60 
50 
40 
30 
20 
10 
0 
1e-5 motions 
1e-6 motions 
1e-7 motions 
10 100 1000 10000 
Arias Intensity (m/s ) 
Figure 6-84. Rockfall Volume vs. Arias Intensity 
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Drift Degradation Analysis 
Orientation of Horizontal MotionsThe orientation of horizontal motions is conveniently 
specified as H1 parallel to the x-axis and H2 parallel to the z-axis (the North direction) in the 
3DEC model (3DEC coordinate system is shown in Figure L-1). An alternative approach with 
H1 parallel to the z-axis (North) and H2 parallel to the x-axis was used to check the sensitivity of 
the orientation. Table 6-28 presents the comparison of the predicted rockfall with the two 
approaches. In general the difference is minor because the amplitudes of the peak motions are 
similar for the two horizontal components of the ground motion. 
Table 6-28. Rockfall in Nonlithophysal Rock Due to 10-5 Ground Motion Combined with Thermal-
Mechanical Effects, Base Case of Thermal Properties 
Ground 
Original Approach (H2 in North) Alternative Approach (H1 in North) 
Rockfall Volume Rockfall Volume 
Case Motion Number of Rockfall (m3) Number of Rockfall (m3) 
38 3 173 42.03 170 39.04 
45 10 14 2.49 18 2.92 
63 11 0 0.00 0 0.00 
6.3.1.6.2 Joint Mechanical Properties 
Joint mechanical properties in 3DEC modeling consist of cohesion, friction angle, dilation angle, 
normal stiffness, and shear stiffness. The base case joint mechanical properties, listed in 
Table 6-3, were based on the rotary shear tests of the cored specimen as derived in Appendix E. 
With limited joint test results available and the fact that the use of rotary shear devices in rock 
mechanics is limited, some of the parameters in the base case, such as cohesion and dilation 
angle, were scaled down from the testing results for conservatism, to allow for potential 
over-prediction of rockfall. 
The direct shear test results (Table E-5) are used to provide the range of variation in the 
sensitivity study. A range of joint mechanical properties, as shown in Table 6-29, was selected 
for the sensitivity study. Three categories were included to cover the possible range of variation. 
Category 1 represents the weakest fractures observed, whereas Category 3 represents the 
strongest fractures. The values of friction angle were established based on the residual friction 
angle of 30 (see Section 6.3.1.5) and three tiers of dilation angles. The dilation angles were 
selected based on the empirical estimate of peak dilation angle for the Yucca Mountain joint set 
(Duan 2003 [DIRS 163586], p.41). The ranges of the peak friction and dilation angle are 
selected to be consistent with the reported direct shear test results presented in Appendix E 
(Table E-5). A conservative estimate of cohesion of 0.1 MPa remained the same as the base 
case. 
The joint stiffness values were taken from both the rotary shear test and direct shear test results. 
The mean and standard deviation of the shear stiffness values for the cooling joint from the direct 
shear tests (Table E-5) were used to estimate the values presented in Table 6-29. Shear stiffness 
for Category 2 joint is set to be equivalent to the mean value, whereas the shear stiffness values 
for Category 1 and 3 joints is estimated to be the mean value minus one standard deviation and 
the mean value plus one standard deviation respectively. Because the normal stiffness is not 
reported from the direct shear tests, the mean and standard deviation of the normal stiffness value 
ANL-EBS-MD-000027 REV 03 6-115 September 2004 

Drift Degradation Analysis 
from rotary shear tests (Table E-4) were used to estimate the values used for the three categories. 
The same approach is adopted for normal stiffness as for shear stiffness with the mean value 
assigned for Category 2 joints and the standard deviation as the range of variation. 
The results for the sensitivity of joint properties to the rockfall prediction are presented in 
Table 6-30. Results for the three categories are quite similar irrespective of the variation of the 
mechanical properties used for each category. In general, the results are also similar to those for 
the base case. The exception is Case 38 with approximately 50 percent more rockfall for the 
sensitivity cases compared to the base case. It was observed that the blocks jammed at the roof 
preventing additional rockfall, was due to the large amount of rockfall that occurred in a short 
time for this case. Jamming appears to occur at earlier time for the base case than other 
sensitivity cases, this contributes to less rockfall for the base case. Comparison of the size 
distribution of the base case and sensitivity cases for Case 38 are shown in Figure 6-85. The 
distributions are similar, with the distributions for the base case and joint Categories 2 and 3 
nearly identical. The results show that the mechanical properties variation for rockfall is a 
secondary effect compared to the variation of fracture pattern. 
Table 6-29. Three Categories of Joint Properties Used in the Sensitivity Study 
Joint Cohesion Joint Peak Friction Joint Normal Joint Shear Stiffness 
Joint Category (Pa) Dilation Angle Angle Stiffness (Pa/m) (Pa/m) 
1 1.0E+5 1.4 31.4 7.20E+10 5.30E+09 
2 1.0E+5 4.4 34.4 9.40E+10 1.10E+10 
3 1.0E+5 11 41 1.16E+11 1.67E+10 
Table 6-30. Sensitivity of Joint Properties for Rockfall Prediction 
Case 
Base Case Joint Category 1 Joint Category 2 Joint Category 3 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
38 173 42.03 237 78.95 257 66.48 251 65.45 
45 14 2.49 16 2.21 12 2.07 16 2.37 
63 0 0 3 0.12 6 0.35 3 0.19 
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Drift Degradation Analysis 
1 
) 
l0.0% 
10.0% 
20.0% 
30.0% 
40.0% 
50.0% 
60.0% 
70.0% 
80.0% 
90.0% 
100.0% 
10 100 
Block Mass (metric tonCumuative Percentage 
Base Case 
Category 1 
Category 2 
Category 3 
Figure 6-85. Comparison of Block Size Distribution for Variation of Joint Mechanical Properties 
(Case 38) 
6.3.1.6.3 Rock Bridge Strength Parameters 
Rock bridges were generated as the extension of finite trace length fractures to form the distinct 
blocks in the 3DEC model (see Figure H-1 in Appendix H). The strength parameters of the rock 
bridges used for the base case (listed in Table 6-3) are the best estimate of the intact rock 
strength. Rock bridge damage appears to have a strong relationship with peak ground velocity. 
In general, less than 1 percent of the bridge area is damaged when subjected to 110-5 ground 
motions, with about 5 percent bridge damage for 110-6 ground motions, reaching to 20 percent 
bridge damage for 110-7 ground motions. However, for certain large ground motions (such as 
ground motion #3), much higher damage percentage is expected. Figure 6-86 shows the 
correlation between the damage percentage and the peak ground velocity. As shown in the 
figure, the coefficient of determination (R2) is estimated to be around 0.95, indicating a strong 
relationship. Note that over 60 percent of the bridge area could be damaged with the extremely 
conservative 16 m/sec peak ground velocity seismic shaking. 
A range of bridge strength parameters, in terms of cohesion, friction angle, and tensile strength, 
as shown in Table 6-31, was selected for the sensitivity study. Three categories were included to 
cover the possible range of variation. The base case joint strength parameters are used for 
Category 1 to represent the extreme case where the bridges are sheared off to become fractures. 
The extreme case could be interpreted as a simulation where the jointed rock mass has been 
previously subjected to a ground motion greater than 16 m/sec. The mean values of the intact 
strength parameters listed in Table E-7 (tensile strength for TSw2) and Figure E-2 (cohesion and 
friction angle) are used for Category 2. The mean plus one standard deviation values are 
assigned as the strength parameters for Category 3 representing the upper bound for the rock 
bridge strength. 
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Drift Degradation Analysis 
R20% 
Briy = 0.0449x - 0.0535 
= 0.9469 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
dge Damage Percentage 
0 2 4 6 8 1012141618 
Peak Ground Velocity (m/sec) 
Figure 6-86. Correlation of Rock Bridge Damage Percentage and Peak Ground Velocity 
Table 6-31. Three Categories of Rock Bridge Strength Parameters Used in the Sensitivity Study 
Rock Bridge Category Cohesion (Pa) Friction Angle Tensile Strength (Pa) 
1 1.00E+5 41 0 
2 3.60E+7 50 8.90E+6 
3 4.00E+7 56 1.22E+7 
The results for the sensitivity of rock bridge strength parameters to the rockfall prediction when 
subjected to 110-5 ground motions are presented in Table 6-32. Increase of rockfall is predicted 
for Category 1, representing the extreme case with the bridges sheared off. Significant increase 
is observed for the median rockfall case (Case 45) and minor increase is detected for the most 
(Case 38) and least (Case 63) rockfall cases. Results for Categories 2 and 3 are similar to the 
base case. The results show that within the range of variation for the intact strength parameters 
(Categories 2 and 3), rock bridge strength parameters have an insignificant impact on rockfall 
prediction. However, if the rock bridges are sheared off as represented by Category 1, a 
significant increase of rockfall is likely. 
Since the damage percentage varies with different levels of ground motions, additional analyses 
for the median rock fall case (Case 45) subjected to 110-6 and 110-7 ground motions were also 
ANL-EBS-MD-000027 REV 03 6-118 September 2004 

Drift Degradation Analysis 
conducted. Table 6-33 presents the results with lower probability ground motions. In general, 
the trend for rockfall is similar to the results for 110-5 ground motions. 
Table 6-32. Sensitivity of Rock Bridge Strength Parameters for Rockfall Prediction 
Case 
Base Case Rock Bridge Category 1 Rock Bridge Category 2 Rock Bridge Category 3 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
38 173 42.03 221 61.08 184 45.97 201 56.99 
45 14 2.49 47 8.92 14 2.49 13 2.34 
63 0 0 6 0.27 1 0.09 0 0 
Table 6-33. Sensitivity of Rock Bridge Strength Parameters for Case 45 with 110-6 and 110-7 Ground 
Motions 
Ground 
Motion 
Level 
Base Case Rock Bridge Category 1 Rock Bridge Category 2 Rock Bridge Category 3 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
Number of 
Rockfall 
Rockfall 
Volume (m3) 
110-6 29 4.19 97 19.75 34 5.52 23 3.29 
110-7 86 14.27 219 47.64 94 15.49 97 16.01 
6.3.1.6.4 Intact Block Failure Response Under Low-Probability Ground Motions 
6.3.1.6.4.1 Introduction 
At the lower probability levels, the ground motions show extreme peak ground velocities levels, 
ranging from 2.44 m/sec at the 110-6 to 5.35 m/sec at the 110-7 annual exceedance 
probabilities. The previous calculations and estimates of dislodged block masses and volumes 
assumed that the rock blocks were, in general, elastic. The only block failure that was allowed 
was breakage of solid rock bridges that occur along the extension of fracture planes, between 
the end of the fracture and its possible termination against adjacent fractures. Thus, in the 
current model, it is possible for a block to split into several smaller blocks if the seismic stresses 
are sufficient to fail the rock bridge in shear or in tension. The following discussion provides a 
simplified analysis of a more general failure mechanism of intact blocks in shear or in tension. 
The average principal stresses in blocks surrounding the emplacement drift are examined for the 
110-6 and 110-7 cases to determine if widespread block failure is possible at these hazard 
levels. If so, then either the amount of rockfall or the size of dislodged rock masses derived from 
the previous calculations could be in error. Initially, a discussion is given on analyses aimed at 
providing a physical bound to peak ground velocities experienced at the Yucca Mountain site. 
Although no bounds on the PGV of time histories have been used in the damage assessments 
made from analyses presented in this document, an estimate of the maximum PGV is useful here 
to determine whether the modeling approach needs to include intact block failure mechanisms. 
An analysis of the peak stress conditions in blocks surrounding the emplacement drift is then 
conducted to determine the extent of potential shear or tensile failure mechanisms. 
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Drift Degradation Analysis 
6.3.1.6.4.2 Bounding of the Peak Ground Velocity 
The ground motion hazard determined in the Probabilistic Seismic Hazard Assessment expert 
elicitation is unbounded. Because the ground motion experts characterized aleatory variability in 
ground motion using unbounded lognormal distributions, as the Probabilistic Seismic Hazard 
Assessment calculations are extended to lower and lower annual probabilities of exceedence, the 
mean ground motions increase without bound, eventually reaching levels that are not credible. 
These levels of ground motion are not credible in that they eventually result in seismic strains 
that would cause the rock mass (in absence of any excavation) to fail through formation of 
fractures, an effect that is not observed at Yucca Mountain. As stated in 10 CFR 63.102(J) 
[DIRS 156605] with respect to events that are to be included in the TSPA, the event class for 
seismicity includes the range of credible earthquakes for the Yucca Mountain site. Therefore, to 
ensure the ground motions considered in the Seismic Consequence Abstraction (BSC 2004 
[DIRS 169183]) and TSPA are credible, an analysis was conducted to determine a bound to PGV 
at the repository level. This analysis, presented in Peak Ground Velocities for Seismic Events at 
Yucca Mountain, Nevada (BSC 2004 [DIRS 170137], estimates an upper bound to the ground 
motions at the Yucca Mountain site based on the shear strain increments (relative to the in situ 
stress state) required to damage (fracture) the Tptpll5. The analysis presented argues that, since 
seismic induced fracturing is not observed in subsurface exposures of the Tptpll, ground motions 
equal to or greater than that which would produce shear strains equal to the fracturing limit have 
not occurred since the Topopah Spring unit was erupted and cooled, some 12.8 million years 
ago. The shear strain limits are defined from the large core lithophysal rock compression testing 
and from numerical extrapolation using the PFC and UDEC programs similar to that described in 
Appendix E, Section E4. Even though bounding peak ground velocities have been estimated, 
they have not been used explicitly in the calculations of seismic damage presented in this 
document. In other words, damage has been assessed for time histories with PGVs in excess of 
the bounding values defined in Peak Ground Velocities for Seismic Events at Yucca Mountain, 
Nevada (BSC 2004 [DIRS 170137]). Instead, the damage to EBS components is bounded within 
the Seismic Consequence Abstraction (BSC 2004 [DIRS 169183], Section 6.4.4); i.e., damage 
associated with PGVs in excess of 5 m/sec is bounded at the 5 m/sec level. 
The details of the derivation of the bounding PGVs based on shear strain limits of the Tptpll can 
be found in the PGV study (BSC 2004 [DIRS 170137]). The result of the analyses presented 
there are two potential bounding distributions of horizontal PGV at the repository level  one 
based on the assumption of a uniform distribution and one based on a triangular distribution 
(Figure 6-87). The lower and upper limits for the distributions are assessed at 150 and 500 cm/s, 
respectively, based on the range of shear-strain increments at yield derived from the combined 
laboratory testing and numerical simulations and the corresponding horizontal PGV values that 
produce these shear strain increments. To translate the shear-strain threshold probability 
distribution into a distribution for horizontal PGV at the waste emplacement level, the results of 
the ground-motion site-response modeling were used. The average horizontal PGV values 
Tensile strains may also be induced by the vertically propagating wave associated with the seismic event. A 
number of the ground motion time histories at the 110-5, 110-6 and 110-7 annual exceedance probabilities are 
characterized by a vertical component that is larger than the horizontal component. The tensile strain limit of the 
rock is less than the shear strain limit, which is used to derive the bounded horizontal PGV. Therefore, using shear 
strain limit will result in larger bounded ground motions than use of both shear and tensile strain limits. The 
bounded PGVs based on a shear strain limit alone are thus conservative in nature. 
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Drift Degradation Analysis 
associated with the average shear-strain values from the site-response results are used to 
transpose the shear-strain threshold probability distribution. The average horizontal PGV values 
calculated, assuming PGV values are normally distributed, yield higher PGVs than those 
calculated for a lognormal distribution. The resulting distribution for horizontal PGV departs 
slightly from a triangular shape because the relation between shear-strain threshold and 
horizontal PGV is not linear. This distribution ranges from a minimum value of 151 cm/s to a 
maximum value of 451 cm/s and has a mode of 236 cm/s. The uniform distribution of bounding 
PGVs is used in the Seismic Consequence Abstraction (BSC 2004 [DIRS 169183]) to bound 
mechanical damage to EBS components since it produces a more conservative approach with an 
upper bound of 5 m/sec to the horizontal PGV at the repository level. 
In summary, the PGV at the repository level has been shown, based on physical strain limitations 
of the lithophysal rock mass, to be, at most, 5 m/sec. Depending of the distribution assumed, the 
maximum could also be as low as approximately 4.5 m/sec with a mode of 2.36 m/sec. 
Source: BSC 2004 [DIRS 170137]. 
Figure 6-87. Probability Density Functions for the Bound to Horizontal Peak Ground Velocity at the 
Waste Emplacement Level 
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Drift Degradation Analysis 
6.3.1.6.4.3 Analysis of Intact Block Failure Mechanism 
Tensile stresses in the rock mass are induced by both the shear (horizontal component) and 
during the reversal of the compression (vertical component). The tensile strength of the rock 
mass is a consequence of the tensile strength of the solid rock bridges that occur between 
discontinuous fracture traces. Therefore, as the rock mass is loaded in a transient tensile fashion 
by the combined effect of the shear and compression waves, the intact blocks could be split into 
a number of smaller blocks through tensile (or shear) failure of the rock bridges. These smaller 
blocks can then become unstable under the successive shaking of the ground motion, with 
subsequent collapse into the drift. 
To examine the potential for intact block breakage, the analyses conducted to examine the 
impact of rock bridge failure are reviewed here. The base case 110-6 and 110-7 nonlithophysal 
3DEC model, described in Section 6.3.1 are based on fracture geometries (i.e., the orientation, 
radius and spacing distribution) obtained from a synthetic fracture representation developed from 
field mapping. A general result of this fracture representation is a distinct block system that is 
formed by solid rock bridges and finite trace fractures as shown in Appendix H (Figure H-1). In 
the base case analyses, the strength of the solid rock bridges, which is represented as bonded 
patches along fracture planes, is governed by the shear and tensile strength of the solid 
Tptpmn, as given in Table 6-3 (cohesion of 47.2 MPa, friction angle of 42o and tensile strength 
of 11.56 MPa). During a simulation, the stress conditions acting on these solid rock bridges are 
monitored, and failure in shear or tension can occur. If failure occurs, the cohesive and tensile 
strength of the bridge is reduced to zero, and the bonded patch is fractured. Thus, the block 
within which the bridge is located can be fractured into multiple blocks. As described in Section 
6.3.1.6.3, less than 1 percent of the rock bridges are damaged during the 110-5 ground motions, 
about 5 percent during the 110-6 ground motions, and about 20 percent for the 110-7 ground 
motions. Figure 6-86 presented the rock bridge damage percentage estimated from the 3DEC 
modeling as a function of the PGV of the ground motion. As seen in this figure, the damage to 
rock bridges is approximately 20 percent or less (for PGVs less than 5 m/s) in terms of total 
rockfall, with the results presented in Tables 6-9, 6-12 and 6-15 for the 110-5, 110-6, and 
110-7 cases, respectively. 
A sensitivity study of rock bridge strength, presented in Section 6.3.1.6.3 provides a conservative 
assessment of the case in which the tensile strength of the rock bridges is assumed to be zero. 
This case effectively represents the condition in which the tensile strength of the rock mass is 
conservatively assumed to be zero as no rock bridges exist. These analyses indicate that the 
rockfall volume (for the median rockfall case 45) increases between 3 to 5 times for the 110-6 
and the 110-7 cases (summarized in Table 6-33). The ground motion time histories for the 
median rockfall condition (Case 45) for the 110-6 and the 110-7 annual exceedance 
probabilities are shown in Figure 6-88. The rockfall for Case 45, for the base case rock bridge 
strength and the case in which the rock bridge tensile strength is set to zero are shown in 
Figures 6-89 to 6-90 for the 110-6 and the 110-7 ground motions. As seen in these figures, the 
rockfall increases significantly with the assumption of zero rock bridge tensile strength, but total 
collapse is not evident. 
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Drift Degradation Analysis 
1e-6 Ground Motion, Set 10 
300 
250 
200 
150 
100 
V 
H1 
H2 
Velocity (cm/s) 
50 
0 
-50 
-100 
-150 
-200 
-250 
0 5 10 152025 
Time (Seconds) 
a) 
i0 
0 5 15 20 25 
Ti () 
/s) 
V 
H1 
H2 
1e-7 Ground Moton, Set 10 
-600 
-400 
-200 
200 
400 
600 
10 
meSecondsVelocity (cm
b) 
Figure 6-88. 1x10-6 (a) and the 1x10-7 (b) Ground Motion Time Histories in Terms of Peak Ground 
Velocity for Median Rockfall Condition, Case 45 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-124 September 2004 
Side ViewTop ViewPerspective View 
a) 
Side ViewTop ViewPerspective View 
b) 
NOTE: Base case rock bridge strength properties given by cohesion of 47.2 MPa, friction angle of 42 and tensile 
strength of 11.56 MPa. Low rock bridge strength properties given by by cohesion of 0.1 MPa, friction angle 
of 41 and tensile strength of 0. 
Figure 6-89. Three-dimensional Visualization of Rockfall for the Median Rockfall Condition (Case 45), 
and Base Case (a) and Low (b) Rock Bridge Strength Properties, 1x10-6 Ground Motion 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-125 September 2004 
Side ViewTop ViewPerspective View 
a) 
Side ViewTop ViewPerspective View 
b) 
NOTE: Base case rock bridge strength properties given by cohesion of 47.2 MPa, friction angle of 42 and tensile 
strength of 11.56 MPa. Low rock bridge strength properties given by cohesion of 0.1 MPa, friction angle of 
41 and tensile strength of 0. 
Figure 6-90. Three-dimensional Visualization of Rockfall for the Median Rockfall Condition (Case 45), 
and Base Case (a) and Low (b) Rock Bridge Strength Properties, 1x10-7 Ground Motion 
In summary, the rock mass tensile strength is a function of the strength of the solid rock bridges 
occurring along pre-existing fractures, as well as the geometry of the fractures themselves. The 
impact of fracture of the solid rock blocks as a potential mechanism in the nonlithophysal rocks 
was examined via a sensitivity study of the shear and tensile strength of the solid rock bridges. 
This sensitivity study showed that the damage to rock bridges is an approximate linear function 

Drift Degradation Analysis 
of the PGV of the ground motion (Figure 6-86), with a maximum damage for base case rock 
bridge properties of about 20 percent. The impact of assumption of a conservative rock mass 
tensile strength was examined by assuming the rock bridges had zero tensile strength. 
Significantly more rockfall occurs for this case, but total drift collapse in the nonlithophysal rock 
is still not indicated for any of the ground motions examined. 
6.3.1.6.5 Model Dimension 
As described in Section 6.3.1.1, the 3DEC base case model is slightly larger than a 25-m cube 
(the actual size is 25 m x 27.5 m x 25 m) with the tunnel oriented at 75 degrees azimuth. The 
region with detail fractures imported from FracMan is one diameter at the side of the tunnel 
(dimension s) and two diameters on top of the tunnel for the base case (dimension t). Additional 
analyses with various modeling dimensions were conducted to investigate the sensitivity of 
model dimension to rockfall prediction. Table 6-34 lists the additional three model dimensions 
used for the sensitivity runs. The length along the X-axis (15 degrees clockwise from the drift 
axis) remains constant at 25 m for all cases (3DEC coordinate system is shown in Figure L-1). 
Table 6-34. Various Model Dimension for Sensitivity Study 
Model Size Model Dimension (m) s (m) t (m) 
Small 252525 2.75 5.5 
base case 2527.525 5.5 11 
large 1 2533.7530 8 16.5 
large 2 2538.7537.5 11 22 
s = horizontal distance away from the side wall; t = vertical distance away from the roof 
Cases 38, 45, and 63 with 110-5 ground motions were selected for the sensitivity study to cover 
the range of rockfall prediction. Figure 6-91 shows the cross-sectional views of Case 45 (the 
median rockfall case) for the four various dimensions. The predicted rockfall for the four model 
dimensions are presented in Table 6-35. In general, the four models predict a similar amount of 
rockfall. The exception is the small model for Case 38 that predicts approximately 40 percent 
less rockfall than the base case. In all, the base case appears to be adequate to provide a 
reasonable estimate for rockfall. 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-127 September 2004 
Small (25x25x25)Large 1 (25x33.75x30)
Base Case (25x27.5x25)Large 2 (25x38.75x37.5) 
Figure 6-91. Cross Section of the Four Model Dimensions Selected for Sensitivity Study, Case 45 

Drift Degradation Analysis 
Table 6-35. Predicted Rockfall for Various Model Dimensions 
Model Model 
Case 38 Case 45 Case 63 
Number of Rockfall Number of Rockfall Number of Rockfall 
Size Dimension Blocks Volume (m3) Blocks Volume (m3) Blocks Volume (m3) 
small 252525 157 27.33 13 2.29 0 0 
base case 2527.525 173 42.03 14 2.49 0 0 
large 1 2533.7530 179 54.61 15 2.51 6 0.68 
large 2 2538.7537.5 154 34.29 14 2.38 3 0.41 
6.3.1.6.6 Block Deletion 
As described in Section 6.3.1.1, a drip shield block anchored at the invert is included in the 
model to record the information of the locations and relative velocities for the rockfall impact. 
An algorithm was developed to delete the fallen block after the impact. The deletion is to 
facilitate the recording of all possible rockfall on the drip shield. If the blocks are not deleted for 
the heavy rockfall cases, the drip shield will be covered with fallen rocks so that some of the 
rockfall at the later part of seismic shaking will not directly impact the drip shield. The two 
cases with the most rockfall subjected to 110-7 ground motions (Case 64 [Fracture Pattern 
49 and Ground Motion 14] and Case 40 [Fracture Pattern 99 and Ground Motion 6]) are selected 
to assess the impact of no deletion to rockfall prediction. 
Figures 6-92 and 6-93 show the two selected cases in which the block deletion algorithm is not 
included. As expected, with the fallen blocks piled on the drip shield, the blocks on top do not 
directly impact the drip shield. Table 6-36 compares the results for rockfall prediction with and 
without the block deletion algorithm. Rockfall volume for the cases without block deletion is 
approximately half of the amount for the cases with block deletion. The effect of blocks not 
directly impacting the drip shield will be the dead load added onto the drip shield. The 
accumulation of dead load on top of the drip shield for the fallen rock is addressed in 
Section 6.4.2.5. 
Table 6-36. Predicted Rockfall With and Without Block Deletion After Impact 
Case 
With Block Deletion Without Block Deletion 
Number of Blocks 
Rockfall Volume 
(m3) Number of Blocks 
Rockfall Volume 
(m3) 
64 269 58.93 186 28.69 
40 120 51.29 69 20.49 
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Drift Degradation Analysis 
Figure 6-92. Blocks Accumulated Above the Drip Shield Without Implementing Block Deletion Algorithm, 
Case 64, Fracture Pattern 49, 110-7 Ground Motion Set #14 
Figure 6-93. Blocks Accumulated Above the Drip Shield Without Implementing Block Deletion Algorithm, 
Case 40, Fracture Pattern 99, 110-7 Ground Motion Set #6 
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Drift Degradation Analysis 
6.3.2 Consideration of Intensely Fractured Zone 
6.3.2.1 Introduction 
An intensely fractured zone is observed at ESF main loop Stations 42+00 to 51+50 with an 
approximate 1000-m length. A description of this fracture zone is provided in Geology of the 
Main Drift - Station 28+00 to 55+00, Exploratory Studies Facility, Yucca Mountain Project, 
Yucca Mountain, Nevada (Albin et al. 1997 [DIRS 101367], p. 58): 
The fracture zone between Sta. 42+00 and 51+50 is a zone of intense 
Set 1 fracturing. This zone appears to be strata bound within the Tptpmn. The 
zone does not crop out on the surface. Down-hole video from drill hole SD-12, 
located 39.4 m west of tunnel Sta. 46+49, shows a similar zone of intensely 
fractured rock only within the Tptpmn. The Main Drift in the area of the fracture 
zone is parallel to the Ghost Dance Fault and is approximately 100 m west of and 
in the hanging wall of the fault. It is not known whether the fracture zone is 
continuous across the Ghost Dance fault as only limited information exists east of 
the Main Drift. 
According to Albin et al. (1997 [DIRS 101367]), the two likely hypotheses for the origin of this 
zone are tectonic and/or cooling of the ash-flow sheet. Figures 6-94 and 6-95 show the intensely 
fractured rock mass with a predominant joint set of 134/83 (strike/dip). Set 2 and Set 3 fractures 
are sparse compared to Set 1 fractures. The mean and median joint spacing for the predominant 
Set 1 fractures were calculated to be 0.24 m and 0.12 m, respectively. 
Figure 6-94. Photo Showing the Intensely Fractured Zone in ESF Main Drift 
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Drift Degradation Analysis 
Source: CRWMS M&O 1998 [DIRS 102679], p. II-66. 
Figure 6-95. Fracture Analysis for the Intensely Fractured Zone 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-132 September 2004 
6.3.2.2 Numerical Modeling 
A 3DEC analysis, which is used for rockfall modeling of the nonlithophysal jointed rock mass, is 
not suitable for such highly fractured rock. A three-dimensional continuum analysis with 
ubiquitous joint model (FLAC3D analysis) was adopted to account for the highly fractured and 
anisotropic nature of the rock mass in this zone. The ubiquitous joint model is ideal for 
conditions with one predominant fracture set in the rock mass. 
Figure 6-96 shows a 25-m cube FLAC3D model constructed for the analysis. To simplify the 
model, the tunnel axis was oriented parallel to the y-axis and the input fracture orientation was 
adjusted based on the coordinate system shown in Figure 6-96. The intact rock deformation 
properties and joint strength properties used in the model are identical to the 3DEC base case 
model presented in Table 6-3. A typical modeling sequence was simulated with initial 
consolidation and tunnel excavation. The lateral and bottom boundaries were fixed at the 
direction normal to the boundary surface, whereas the in situ static pressure was applied to the 
top boundary for the consolidation and excavation stages. Both the preclosure seismic motion 
(510-4 seismic ground motion) and the postclosure seismic motion (110-6 seismic ground 
motion Set 1 (DTN MO0301TMHIS106.001, see Appendix X)) were applied to the model with 
free-field boundary condition imposed. These analyses do not include thermal loading. 
XYZXYZNTunnel Axis (Y Axis) - 75 degree AzimuthPredominant Fracture Set (134/83) 
Figure 6-96. FLAC3D Model Mesh and Fracture Orientation 

Drift Degradation Analysis 
Figures 6-97 to 6-99 show the yield state, in-plane shear stress contours, and principal stress 
tensor for the 510-4 preclosure seismic analysis after approximately 29 seconds of ground 
motion. The same set of figures for the postclosure seismic analysis is presented in 
Figures 6-100 to 6-102. Yielding is confined within an element around the opening for the 
510-4 preclosure analysis as shown in Figure 6-97. The drift appears to be stable for the entire 
duration of seismic shaking in this case. However, extensive yielding is observed in the model 
region for both the 110-4 preclosure and postclosure seismic analyses. The extensile stresses 
imposed by the large amplitude of seismic motion exceed the in situ compressive stress on the 
ubiquitous joint planes, tensile and shear failure is observed at these planes. The stress path of 
shear and normal stresses at the roof projected onto the predominant joint plane are presented in 
Figures 6-103 and 6-104 for the preclosure (510-4 seismic ground motion) and postclosure 
(110-6 seismic ground motion set 1) analyses, respectively. Perturbation of stresses is minor in 
the preclosure case, whereas large stress variation is observed in the postclosure case. The stress 
states at the predominant joint plane reach the Mohr-Coulomb failure envelope under the 
postclosure seismic motion as shown in Figure 6-104. 
Figure 6-97. Yield State Prediction - 510-4 Preclosure Ground Motion at 29 Seconds 
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Drift Degradation Analysis 
Figure 6-98. In-Plane Shear Stress Contours - 510-4 Preclosure Ground Motion at 29 Seconds 
Figure 6-99. Principal Stress Tensor - 510-4 Preclosure Ground Motion at 29 Seconds 
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Drift Degradation Analysis 
Figure 6-100. Yield State Prediction - Postclosure Ground Motion at Two Seconds 
Figure 6-101. In-Plane Shear Stress Contours - Postclosure Ground Motion at Two Seconds 
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Drift Degradation Analysis 
Figure 6-102. Principal Stress Tensor - Postclosure Ground Motion at Two Seconds 
5.00E+06 
shear stress (Pa) 
0.00E+00 
5.00E+05 
1.00E+06 
1.50E+06 
2.00E+06 
2.50E+06 
3.00E+06 
3.50E+06 
4.00E+06 
4.50E+06 
-1.00E+06 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 5.00E+06 
normal stress (Pa) 
Figure 6-103. Stress Path at Roof Under Preclosure Seismic Motion 
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Drift Degradation Analysis 
4.00E+07 
shear stress (Pa) 
0.00E+00 
5.00E+06 
1.00E+07 
1.50E+07 
2.00E+07 
2.50E+07 
3.00E+07 
3.50E+07 
-1.00E+07 0.00E+00 1.00E+07 2.00E+07 3.00E+07 4.00E+07 
normal stress (Pa) 
Figure 6-104. Stress Path at Roof Under Postclosure Seismic Motion 
The ubiquitous joint model used in the analysis considers through-going joints in the model 
region. However, rock bridges do exist and will provide additional strength to resist the 
extensile and shear strains induced by the seismic motions. The prediction of yielding in the 
model region for the postclosure ground motion is therefore conservative. Based on the 
FLAC3D analysis results presented in this section, and the spalling type of failure predicted in 
Section 6.3.1.6, extensive failure around the drift opening is likely. 
6.3.3 Impact of Small-Scale Fractures on Rockfall in Nonlithophysal Units 
Small-scale fractures were mapped in six 6-m panels (DTN: GS040108314224.001 
[DIRS 169591]) as described in Section 6.1.4.1. Two of the six panels are located in the Tptpmn 
unit (Stations 11+15 and 13+00). The small-scale fracture data in these two panels are used in 
this study to determine their impact to block formation. The ranges of fracture traces mapped in 
these two panels are tabulated in Table 6-37 and presented in Figure 6-105. As shown in Figure 
6-105, the fracture trace length distributions are the typical negative exponential nature with the 
concentration in the range of 10 cm to 20 cm. The fractures with trace lengths longer than 1 m 
account for less than 20 percent of the fractures mapped in these two panels. 
Due to the extraordinary computational effort, it is not practical to incorporate the small trace 
length fractures into a distinct block code, such as 3DEC used in the seismic and thermal 
analysis presented in Section 6.3.1. The probabilistic key-block code DRKBA, with an efficient 
key-block simulation algorithm, is therefore selected to assess the impact of small-scale fractures 
to rockfall. The assessment is based on a static condition with comparison of the results of 
two cases: including the small-scale fractures and excluding the small-scale fractures. 
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Drift Degradation Analysis 
Table 6-37. Range of Fracture Traces in Panels 11+15 and 13+00 
Trace Length Bin(m) Frequency Cumulative % 
0 0 .00% 
0.1 87 22.25% 
0.2 112 50.90% 
0.3 53 64.45% 
0.4 31 72.38% 
0.5 12 75.45% 
0.6 9 77.75% 
0.7 5 79.03% 
0.8 3 79.80% 
0.9 7 81.59% 
1 8 83.63% 
1.1 10 86.19% 
1.2 2 86.70% 
1.3 6 88.24% 
1.4 0 88.24% 
1.5 4 89.26% 
2 12 92.33% 
2.5 9 94.63% 
3 7 96.42% 
More 14 100.00% 
NOTE: See small scale filtering.xls file in Appendix A. 
Because the fractures with trace lengths greater than 1 m have already been accounted for in the 
existing joint data for DRKBA analysis, the fractures included in the 6-m panels were first 
filtered out. Additionally, fractures with trace lengths less than 15 cm are filtered out to reduce 
the computational effort for key-block analysis. This criterion is reasonable because the block 
volume formed by small traces less than 15 cm would be too small to be considered relevant to 
the damage of waste package or drip shield. The orientation of the remaining small-scale 
fractures is presented in the fracture pole plot as shown in Figure 6-106. 
6.3.3.1 DRKBA Comparative Analysis 
For the comparative analysis, the primary excavation is a horizontal 3-m diameter drift trending 
75 degrees. The region around the excavation has been modeled with a grid consisting of 
2,744,000 nodes. The nodes are spaced 15 cm (0.5 ft) apart, with each node representing 
0.0035 cubic meters (0.125 cubic foot) of the rock mass. The smaller size tunnel is used because 
of the excessive computer memory required for the mesh compatible to 5.5-m diameter drift. 
Because of the comparative nature of the analysis, and the focus of small-scale fractures in this 
analysis, the smaller size tunnel is justified. 
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Drift Degradation Analysis 
0 
20 
40 
60 
80 
100 
120 
0 
0.1 
0.2 
0.3 
0.40.5 
0.6 
0.70.8 
0.9 
1 
1.1 
1.2 
1.3 
1.41.5 
2 
2.5 
3More 
(m) 
lHistogram 
Fracture Trace LengthFrequency 
.00% 
10.00% 
20.00% 
30.00% 
40.00% 
50.00% 
60.00% 
70.00% 
80.00% 
90.00% 
100.00% 
Frequency 
Cumuative % 
NOTE: See small scale filtering.xls file in Appendix A. 
Figure 6-105. Histogram Fracture Traces in Panels 11+15 and 11+30 
For each Monte Carlo simulation, an 18.3-m long (60-ft) tunnel has been modeled in 
three-dimensional space. Eighteen plane equations were used to describe the circumference of 
the circular tunnel. In addition, two plane equations were used to describe each end of the 
tunnel. Random joint patterns are generated with joint centers positioned in three-dimensional 
space, considering each joint set in sequence for each Monte Carlo simulation. The forming of 
key blocks is therefore different in each Monte Carlo simulation. Four hundred Monte Carlo 
simulations were used in this analysis. 
In addition to the four joint sets identified based on the mapped fractures data with trace length 
greater than 1m (Section 6.1), a random set representing the small-scale fractures is included in 
the DRKBA analysis for the case considering the small-scale fractures. The required input 
parameters for each individual joint set and its derivation are provided in Appendix D. Cohesion 
and friction angle of the joints are simulated with the bivariate normal distribution. Mean and 
standard deviation for the cohesion and friction angle are provided in Appendix E. Cohesion 
values were conservatively reduced, providing increased rockfall (Appendix D, Section D2). 
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Drift Degradation Analysis 
Figure 6-106. Pole Plots for the Filtered Small-Scale Fractures 
6.3.3.2 Comparison of Analysis Results 
Figure 6-107 presents the key-block analysis results in the format of cumulative frequency of 
occurrence for both cases. The cumulative frequencies of occurrence corresponding to 
50-, 75-, 90-, 95-, and 98-percentile block volume for each unit are listed in Table 6-38. The 
maximum block sizes predicted from the analyses are also presented in this table. In general, the 
block size predicted considering the small-scale fractures is smaller than the case without 
including the small-scale fractures as shown in Table 6-38. The maximum block predicted is 
7.4 cubic meters for the case without small-scale fractures compared with 3.25 cubic meters for 
the case including the small-scale fractures. The results also show that by considering the 
small-scale fractures, more blocks would form. Three hundred and forty-seven blocks were 
generated in the case with inclusion of the small-scale fractures, compared to 325 blocks 
predicted in the case without the small-scale fractures. The results are summarized in 
Table 6-39. Approximately 10 percent more blocks are predicted when considering the 
small-scale fractures. It is therefore concluded that small-scale fractures have a minor impact on 
key-block development in the nonlithophysal units. 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-141 September 2004 
Impact of Small Scale Fractures to the Block Size Distribution0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
0.0010.0100.1001.00010.000100.000Block Volume (m3)
Cumulative Frequency of OccurrenceWithout Small ScaleFracturesWith Small ScaleFractures 
Figure 6-107. Block Size Distribution Predicted from DRKBA Analyses 
Table 6-38. Block Volume (in cubic meter) Corresponding to Various Levels of Predicted Cumulative 
Frequency of Occurrence 
Cumulative Frequency of 
Occurrence Without Small-Scale Fractures With Small-Scale Fractures 
50% 0.01 0.01 
75% 0.05 0.05 
90% 0.20 0.19 
95% 0.45 0.42 
98% 0.90 0.97 
100% 7.36 3.25 
NOTE: Calculation of block volumes documented in Appendix D (Section D11). 
Table 6-39. Summary of Results for DRKBA Comparative Analysis 
Without Small-Scale Fractures With Small-Scale Fractures 
Total Number of Blocks 325 347 
Number of Blocks per km 44 47 
Total Volume of Blocks (m3) 38.0 32.0 
Volume of Blocks per km (m3/km) 5.2 4.4 
NOTE: Calculation of block information is documented in Appendix D, Section D11; and Appendix A (small scale 
fracture results.xls). 

Drift Degradation Analysis 
6.3.4 Drift Profile and Block Geometry Prediction in Nonlithophysal Units 
The distinct block approach applied in this analysis has provided an assessment of existing 
fracture data to determine probable occurrences of rock blocks that would fall onto the drip 
shield in the absence of ground support. The 3DEC approach considers progressive block 
failure, such that when an initial rock block fails and is removed, an additional failure surface 
may open up allowing other blocks to fall. Progressive block failure continues until the crown 
becomes geometrically and mechanically stable, and no additional blocks can fall. The final 
progressive failure surface provides the basis for the drift profile predictions presented in this 
section. 
The deteriorated drift profiles from selected simulations are shown in Figures 6-108 to 6-114. 
These profiles were the outcome of the 3DEC analysis with the rock mass and opening subject to 
in situ and seismic loadings. In general, the drifts are more stable under the thermal loading as 
shown in Sections 6.3.1.3 and 6.3.1.4; the drift profiles for the cases considering thermal loading 
are not included. 
The selected drift profiles include the profiles with the greatest and median rockfall cases for the 
110-5, 110-6, and 110-7 hazard levels (Figures 6-108 and 6-111). In addition, the greatest 
rockfall profile for the preclosure consideration (110-4 hazard level) is shown in Figure 6-114. 
The median case profile is selected as the 50 percentile among the simulations predicting rockfall 
for the given hazard level. The median case profile ranking was based on the total rockfall 
volume within the simulation. Due to the limited amount of rockfall predicted for the 110-4 
seismic hazard, only the greatest rockfall profile is presented. The total rockfall volume and the 
number of blocks predicted for each simulation presented are listed in Table 6-40. The profile 
for each simulation includes the side view and perspective view of the drift with predicted fallen 
blocks. Also included are selected cross sections at the locations indicated in the side view 
figure. Failure of intact rock bridges may occur for the postclosure level of ground motions as 
described in Section 6.3.1.6. Additional break up of rock around the opening is likely when 
subject to postclosure level of ground motions. 
The drift profile for the intensely fractured zone cannot be directly obtained from the FLAC3D 
ubiquitous joint model (described in Section 6.3.2) because the model is a continuum. 
Considering the small yield zone shown in Figure 6-97 for the preclosure ground shaking, minor 
spalling is expected along the sidewall for the preclosure period. However, severe spalling is 
likely for the seismic shaking due to postclosure ground motions with an extensive yield zone 
shown in Figure 6-100. It is estimated that the likely profile for the intensely fractured zone with 
the postclosure consideration will be similar to Figure 6-90. 
There are many different sizes and shapes of rock blocks predicted to impact the drip shield. 
Because block geometry information is mainly used for drip shield impact calculations, the 
geometry of large blocks is provided in this section. A total of 7 blocks simulated were selected, 
each with a volume greater than 6 metric tons. The block geometric information for each 
individual block is presented in Appendix I (Figures I-1 to I-7). 
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Drift Degradation Analysis 
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Side ViewTop ViewA1A2A3A4A5Perspective ViewSection A1Section A2Section A3Section A4Section A5 
Figure 6-108. Drift Profile for 110-7 Hazard Level, Case with Greatest Amount of Rockfall 

Drift Degradation Analysis 
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Side ViewTop ViewA1A2A3Perspective ViewSection A1Section A2Section A3 
Figure 6-109. Drift Profile for 110-7 Hazard Level, Median Rockfall Case 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-145 September 2004 
Side ViewTop ViewA1A2A3A4A5Perspective ViewSection A1Section A2Section A3Section A4Section A5 
Figure 6-110. Drift Profile for 110-6 Hazard Level, Case with Greatest Amount of Rockfall 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-146 September 2004 
iTop Vew 
Perspective View 
A1 A2 Side View A3 
Section A1 Section A2 Section A3 
Figure 6-111. Drift Profile for 110-6 Hazard Level, Median Rockfall Case 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-147 September 2004 
Side ViewTop ViewA3A1A4A2A5Perspective ViewSection A1Section A2Section A3Section A4Section A5 
Figure 6-112. Drift Profile for 110-5 Hazard Level, Case with Greatest Amount of Rockfall 

iiANL-EBS-MD-000027 REV 03 6-148 September 2004 
Side Vew 
Top Vew 
Perspective View 
A1 A2 
Section A1 Section A2 
Figure 6-113. Drift Profile for 110-5 Hazard Level, Median Rockfall Case 
Drift Degradation Analysis 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-149 September 2004 
Side ViewTop ViewA2A1A4A3A5Perspective ViewSection A1Section A2Section A3Section A4Section A5 
Figure 6-114. Drift Profile for 110-4 Hazard Level, Case with Greatest Amount of Rockfall

Drift Degradation Analysis 
Table 6-40. Predicted Number of Rockfall and Volume for the Presented Drift Profile 
Simulation Number of Blocks Total Volume (m3 ) 
110-7 hazard, worst case profile 269 58.93 
110-7 hazard, median case profile 77 10.43 
110-6 hazard, worst case profile 167 63.33 
110-6 hazard, median case profile 36 5.19 
110-4 hazard, worst case profile 62 7.17 
6.4 ROCKFALL IN THE LITHOPHYSAL UNITS 
6.4.1 Problem Approach 
6.4.1.1 Estimate of Block Size 
Analysis of rockfall in the lithophysal units presents a significantly different problem than that 
given in the previous section with regard to nonlithophysal rocks. In general, the nonlithophysal 
rocks are composed of strong, intact blocks of welded tuff that are separated by fracture planes. 
The fracture surfaces provide the primary weaknesses in the system and control the failure mode 
and resulting rock block dimensions. For this reason, it is necessary that the fracture planes be 
explicitly represented within the model to allow estimation of block dimensions, masses, and 
velocities. 
Lithophysal units, particularly the Tptpll, are characterized by lithophysal voids interconnected 
by intense fracturing. Fracture sets are not as clearly defined as in the Tptpmn. Average fracture 
spacing is less than 1 m and, at certain locations, this spacing is much smaller, on the order of 
0.1 to 0.3 m (as discussed in Section 6.1.4.1). In addition to fracturing on different scales, the 
lithophysal rock mass is characterized by the presence of almost uniformly distributed holes 
(lithophysae) of varying size (from less than 1-cm to greater than 1-m in diameter). The 
lithophysae account for up to about 30 percent of the rock mass volume (see Section 6.1.4.2 for a 
detailed discussion on lithophysae). It is assumed in the following analyses that, when stressed 
beyond its strength limits, the lithophysal rock mass will break into relatively small block sizes 
controlled by the spacing of natural fractures (Section 5.2.2). Therefore, as opposed to the 3DEC 
modeling of the Tptpmn, the modeling of the lithophysal rock does not attempt to calculate the 
block sizes resulting from yield but considers them to be on the order of 0.1 to 0.3 m (or smaller) 
in dimension. The models developed here are discontinuum models in which the rock mass is 
discretize into random block sizes with dimensions on the order of 0.1 to 0.2 m. 
6.4.1.2 Approach to Modeling of Lithophysal RockHomogeneity and Bounding Rock 
Mass Properties Estimates 
Lithophysal Porosity and Consideration of a Homogeneous Rock MassThe size of the 
internal lithophysae structure and fracture spacing is much smaller than the drift size (i.e., 5.5-m 
diameter). There is no preferred direction in the fracture or lithophysae orientation that would 
justify introduction of anisotropy into drift scale modeling. As discussed in Appendices E, O, 
and T, lithophysal porosity varies in a bedded or stratiform fashion with layering orientation 
ANL-EBS-MD-000027 REV 03 6-150 September 2004 

Drift Degradation Analysis 
coincident with the dip of the Tptpll. For example, the areas of highest lithophysal porosity (i.e., 
greater than about 20 percent) lie in a thin band in the upper portion of the Tptpll unit, just below 
the contact with the Tptpmn. Here, the largest lithophysae are also found. The lowest levels of 
lithophysal porosity are found near the bottom of the Tptpll where it grades into the 
nonlithophysal Tptpln. Figure 6-115 is a histogram that shows the variability in lithophysal 
porosity for the entire Tptpll as obtained from angular traverse measurements in the ECRB 
Cross-Drift. 
0 
10 
20 
30 
40 
50 
60 
70Lil (%) 
Observations 
0% 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
ions 
l 
25-30 20-25 15-20 10-15 <10 
thophysa Porosity100% 
Cumulative Distribution 
ObservatCumuative % 
NOTE: Lithophysal porosity data are from ECRB Cross-Drift station 14+44 to 23+26 (Appendix O, Section O6.6; 
see Microsoft Excel file, Drift Deg AMR AF T-A-P Fit.xls, worksheet Volume Percent - Stats, which can be 
accessed through the Technical Data Management System using DTN: MO0408MWDDDMIO.002). 
Figure 6-115. Histogram of the Percentage of Lithophysal Porosity as Determined from Field 
Measurements in the ECRB Cross-Drift Taken on 5-m Intervals 
This figure shows that about 10 percent of the Tptpll is composed of a rock mass with 
lithophysal porosity levels greater than 20 percent. These levels tend to be concentrated near the 
top of the unit. Approximately 25 percent of the Tptpll has lithophysal porosity between 15 and 
20 percent, approximately 35 percent with lithophysal porosity between 10 and 15 percent, and 
approximately 30 percent with lithophysal porosities less than 10 percent. 
As discussed in Appendix E, the lithophysal rock mass strength and Youngs modulus are 
dependent on the percentage of lithophysal porosity. The initial base case approach taken to 
modeling of this rock mass, is to subdivide the rock mass strength and modulus into a series of 
categories based on lithophysal porosity percentage. The rock mass strength and modulus are 
determined from large-diameter core testing of lithophysal rocks as well as numerical 
extrapolations using the Particle Flow Code program (PFC). The process of estimation of rock 
mass properties is given in detail in Appendix E. 
Parameter studies are then conducted to examine the mechanical response of emplacement drifts 
to in situ, thermal, and seismic stressing considering homogeneous rock mass properties (i.e., 
constant lithophysal porosity) for a given drift cross section. Since the modeling is conducted for 
the complete range of properties represented by the categories, the full range of response is 
examined. To examine the conservatism inherent in this approach (i.e., the use of parametric 
ANL-EBS-MD-000027 REV 03 6-151 September 2004 

Drift Degradation Analysis 
studies based on the consideration of a homogeneous rock mass and a range of rock mass 
properties) additional analyses are conducted in which the spatial variability of the rock mass 
lithophysal porosity is taken into account. Appendix T describes a model of the spatial 
variability of lithophysal porosity within the Tptpll, based on field mapping studies. This 
three-dimensional geometric model of the Tptpll lithophysal porosity is sampled to create 
two-dimensional cross section representations that can be used for investigation of spatial 
variability on both rock mass properties and drift stability. As discussed in Appendix E, these 
representations are used for investigation of the impact of spatial variability of porosity on the 
ultimate strength and modulus of the rock mass. The discussion in Appendix E compares the 
laboratory test data to these spatial variability examinations. It is confirmed that the lowest 
ranges of strength categories based on lithophysal porosities greater than 20 percent, do yield 
conservative estimates of rock mass strength. Full drift scale modeling presented in 
Section 6.4.2.2, again using two dimensional cross sections taken from the geometrical spatial 
variability representations, is used for comparison of conservatism to the base case models that 
consider homogeneous rock property ranges. 
Base Case Rock Mass PropertiesAs discussed above, the assessment of rock mass properties 
for lithophysal rock is documented in Appendix E (Section E4.1). Large diameter room-dry and 
saturated laboratory testing is supplemented by numerical model extrapolations to examine the 
impact of in situ lithophysal porosities, shapes, sizes, and distributions on the rock mass 
mechanical properties. This information is used to define a set of base case mechanical 
properties and estimates of ranges of these properties for parameter analysis. Five base case 
categories were developed to represent the range of rock mass properties as summarized in 
Table 6-41. The validity of this approach to represent the lithophysal rock mass is discussed in 
Section 7.3. Categories 1 through 5 represent variability of rock mass quality throughout the 
repository emplacement level. These categories can be related approximately to levels of 
lithophysal porosity in the Tptpll (see Table 6-41). 
Table 6-41. Categories of the Lithophysal Rock Mass Selected for Analysis 
Bounding Unconfined 
Category 
Base Case Properties Compressive Strength 
Estimated 
Lithophysal 
Porosity 
Unconfined 
Compressive 
Strength 
(MPa) 
Youngs 
Modulus, E 
(GPa) 
Bulk 
Modulus, K 
(GPa) 
Shear 
Modulus, 
G (GPa) 
Lower 
Bound 
(MPa) 
Upper 
Bound 
(MPa) 
1 10 1.9 1.07 0.80 10 11 35 
2 15 6.4 3.54 2.65 10 23 28 
3 20 10.8 6.01 4.51 10 32 21 
4 25 15.3 8.48 6.36 13 40 13 
5 30 19.7 10.95 8.21 16 47 7 
NOTE: The calculation of rock strength properties is documented in Appendix E (Section E4.1). 
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Drift Degradation Analysis 
6.4.2 UDEC Discontinuum Analysis of the Lithophysal Rock Mass 
6.4.2.1 Model Development 
The objective of the analysis presented in this section is to predict the amount of rockfall in the 
emplacement drifts due to: 
 Drift excavation 
 Stresses induced by the heat released from the waste packages 
 Seismic ground motions with varying probabilities of occurrence 
 Time-dependent strength degradation. 
The standard approach in geotechnical engineering for solving problems of stability of 
underground excavations is through the use of models based on continuum mechanics. Such an 
approach is quite effective if the main interest is estimating stress redistribution around an 
opening or solving for tunnel wall displacements. However, difficulties are encountered if a 
continuum model is used for prediction of instability. Continuum approaches use constitutive 
models to describe the mechanical behavior of a material. A linearly elastic-perfectly plastic 
Mohr-Coulomb constitutive model is often used to represent mechanical behavior of a rock mass 
(i.e., see Hoek 2000 [DIRS 160705]). The material strength of a perfectly plastic 
Mohr-Coulomb model does not decrease as a function of plastic (i.e., post-yield) deformation. 
This, combined with the use of a continuum-based modeling approach,6 means that the model of 
a drift may show indications of material yielding (i.e., plastic deformation) in different portions 
of the model, but will never actually predict rockfall. It was decided, based on these 
considerations, to use UDEC, a two-dimensional discontinuum program (Section 3.1) for drift 
stability analysis in lithophysal rock. In the UDEC lithophysal rockfall model, the rock mass is 
represented as an assembly of polygonal elastic blocks. As described in Section 7.6 of this 
report, the objective of the UDEC lithophysal rock mass model is to provide a model in which 
the rock mass has the proper deformability and strength characteristics of the rock mass, and will 
respond elastically for stresses up to its peak strength. However, after the peak strength is 
reached, the model must be capable of representing the failure process, including fracturing and 
dislodging of blocks under quasi-static and dynamic loading. This can be accomplished by 
subdivision of the rock mass into many blocks of approximately the same size as those that may 
ultimately be formed during yielding, due to the inherent ubiquitous fracturing within the Tptpll. 
These fractures can be bonded by the strength and stiffness values that allow correct 
representation of the rock mass strength and modulus given by the strength categories in 
Table 6-41. Prior to yielding, the fractures in the rock mass are essentially invisible or 
incipient and the rock mass will behave in an elastic, isotropic fashion during loading and 
unloading. However, once the shear or tension strength of the incipient fractures is reached, the 
rock mass can realistically fail through propagation of fractures and form unstable rock blocks 
that are free to dislodge and fall into the excavation as the forces dictate. An important aspect of 
6 A continuum model is one in which the elements used to discretize the rock mass are intimately connected at their 
nodal points. These elements can represent yielding in an indirect way via the use of non-linear constitutive models 
that relate stress to strain, but cannot fracture apart or separate as may occur in reality. Thus, partial or total collapse 
of a tunnel and the specific volume or mass of rockfall occurring during a simulation cannot be estimated with 
reliability. 
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Drift Degradation Analysis 
this approach is that the fracture properties must be calibrated to reproduce the desired overall 
rock mass strength and modulus for each of the rock strength categories in Table 6-41. 
The entire rock mass domain is discretized into blocks using a technique referred to as Voronoi 
tessellations7 (Itasca Consulting Group 2002 [DIRS 160331]), to achieve randomly-shaped 
blocks of roughly uniform size. The initially-bonded fractures between blocks represent the 
approximate spacing and ubiquitous and random nature of the existing fracturing within the 
Tptpll (see Section 5.2.2), and are considered to be linearly elastic-brittle. The elastic behavior 
of fractures (and thus the rock mass deformability) is controlled by their normal and shear 
stiffnesses (fracture stiffness is constant). The initially-bonded fractures can sustain a finite 
tensile stress as prescribed by their tensile strength. The Coulomb slip condition governs the 
onset of shear failure as a function of fracture cohesion and friction angle. If a bonded fracture 
fails, either in tension or shear, its tensile strength, friction coefficient, and cohesion are reset to 
residual values. This model allows for the formation of broken fractures between blocks, and 
possible subsequent separation and instability (under action of gravity) of portions of rock mass 
around a drift. No ground support was considered in the analyses as it was considered to be 
non-functional in the postclosure period. The cases of thermal and seismic loading considered in 
this section were also analyzed using a continuum, linearly elastic approximation. The analyses 
were done using the finite difference code FLAC (Section 3.1) to provide both a check against 
the UDEC lithophysal rockfall model, and to provide an elastic-based reference for gaining 
insight into interpretation of the results from the complex UDEC lithophysal rockfall model. 
Additional details for the justification and calibration of the lithophysal rockfall model are 
provided in Section 7.6. The calibration process of the UDEC block model requires calibration 
of the mechanical properties of the initially-bonded fractures so they reproduce the desired rock 
mass properties of the lithophysal rock. As stated previously, the rock mass properties are 
subdivided into five rock strength and modulus categories that span the range of expected 
lithophysal rock mass porosity. It is therefore necessary that the bonded fractures of the 
lithophysal rock mass be calibrated to each of these five rock mass categories. In addition, two 
average block sizes are examined for representation of the Tptpll fractures0.2 m and 0.3 m. 
Because the rock mass properties are a function of the fracture spacing, it is necessary to 
calibrate the bonded fracture properties for each of these representations. The calibrated 
properties of the bonded fractures are listed in Tables 6-42 and 6-43 for UDEC lithophysal 
rockfall models with average block sizes of 0.2 m and 0.3 m, respectively. Note that, if not 
indicated otherwise, the analysis was done using a block size of 0.3 m. 
The geometry of the UDEC lithophysal rockfall model is shown in Figure 6-116. As indicated, 
only the region around the drift where inelastic deformation is expected is discretized into 
Voronoi blocks. The rest of the model is composed of a few large, elastic blocks that act to 
transmit forces from the boundaries to the inner portions of the model. Verification of the proper 
extent of the thermo-mechanical boundary conditions of the model can be found in Appendix U. 
The overall stiffness of the discretized portion of the model (i.e., stiffness of blocks and joints 
together) is the same as the stiffness of the large elastic blocks, which represent far-field 
behavior. This provides mechanical compatibility of the inner and outer portions of the model. 
7 The Voronoi tessellation is simply a block discretization method available within the UDEC program that allows a 
rock mass to be subdivided into a number of randomly-shaped blocks that have a specified average dimension. 
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Drift Degradation Analysis 
Table 6-42. Calibrated Properties of the Bonded Fractures and Intact Blocks in the Model with 0.2 m 
Block Size 
Residual 
Friction Friction Normal Shear Block Bulk Block Shear 
Category 
Angle 
(deg) 
Angle 
(deg) 
Cohesion 
(MPa) 
Tension 
(MPa) 
Stiffness 
(GPa/m) 
Stiffness 
(GPa/m) 
Modulus 
(GPa) 
Modulus 
(GPa) 
1 35 15 3.91 1.56 13.40 6.69 13.00 9.75 
2 35 15 5.86 2.34 45.10 22.50 43.60 32.80 
3 35 15 7.82 3.12 76.20 38.00 73.60 55.40 
4 35 15 9.77 3.90 108.00 53.90 104.00 78.50 
5 35 15 11.70 4.68 139.00 69.40 134.00 101.00 
NOTE: Residual cohesion and tensile strength are zero. See Section 7.6 for calibration methodology. 
Table 6-43. Calibrated Properties of the Bonded Fractures and Intact Blocks in the Model with 0.3 m 
Block Size 
Residual 
Friction Friction Normal Shear Block Bulk Block Shear 
Category 
Angle 
(deg) 
Angle 
(deg) 
Cohesion 
(MPa) 
Tension 
(MPa) 
Stiffness 
(GPa/m) 
Stiffness 
(GPa/m) 
Modulus 
(GPa) 
Modulus 
(GPa) 
1 35 15 3.83 1.53 9.34 4.67 9.03 6.80 
2 35 15 5.85 2.34 31.48 15.72 30.44 22.88 
3 35 15 7.94 3.18 53.08 26.57 51.37 38.60 
4 35 15 10.09 4.03 74.90 37.60 72.80 54.70 
5 35 15 12.30 4.92 97.00 48.40 93.60 70.50 
NOTE: Residual cohesion and tensile strength are zero. See Section 7.6 for calibration methodology. 
6.4.2.2 Seismic Consideration in Lithophysal Units 
Ground MotionsDrift stability was analyzed for different conditions of ground motion: 
 Ground motion with 510-4 probability of annual occurrence (preclosure earthquake, 
DTN: MO0407TMHIS104.003 [DIRS 170599]) 
 Ground motion with 110-4 probability of annual occurrence (preclosure earthquake, 
DTN: MO0306SDSAVDTH.000 [DIRS 164033]) 
 Ground motion with 110-5 probability of annual occurrence (postclosure earthquake, 
DTN: MO0402AVDTM105.001 [DIRS 168890]) 
 Ground motion with 110-6 probability of annual occurrence (postclosure earthquake, 
DTN: MO0301TMHIS106.001 [DIRS 161868]). 
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Drift Degradation Analysis 
NOTE: Simplified drip shield geometry is based on BSC 2004 [DIRS 169220]. 
Figure 6-116. Geometry and Initial Conditions of the UDEC Lithophysal Rockfall Model 
The ground motions are discussed in detail in Section 6.3.1.2.1. Fifteen ground motions 
(two horizontal and one vertical component of motion) were considered in the analysis for 110-5 
and 110-6 probabilities of annual occurrence. Only one ground motion was considered for each 
preclosure level (i.e., 510-4 and 110-4 probabilities of annual occurrence). Because there is just 
one ground motion case for each preclosure level, the 510-4 and 110-4 probabilities of annual 
occurrence ground motions were analyzed for the five rock mass categories. 
For the 110-5 ground motion, three rock strength categories that span the range of lithophysal 
porosities were chosen (Categories 1, 3, and 5). For each of these categories, the 15 ground 
motion sets were analyzed. Because the 110-5 analyses show a large range in damage level 
depending on the rock strength and ground motion set, more extensive examination was made. 
Analyses were conducted for each of the three categories lower bound values (Table 6-41) in 
addition to the base case values. Analyses using a model with simulated spatial variability in 
lithophysal porosity (and thus spatial variability in mechanical properties) were also conducted 
as a check against the base case models that consider constant properties. 
Instead of simulating all possible combinations of the 15 cases of ground motion for 110-6 
probability with five rock mass categories, only 15 realizations shown in Table 6-44 were 
simulated (note that 15 ground motions are numbered 1 through 14 in sequence, and 16). Based 
on Latin Hypercube sampling (see Sampling of Stochastic Input Parameters for Rockfall 
Calculations and for Structural Response Calculations Under Vibratory Ground Motion 
(BSC 2004 [DIRS 169999]) and DTN: MO0301SPASIP27.004 [DIRS 161869]), realizations 
from Table 6-44 are selected as representative of the possible realizations. Combinations in 
Table 6-44 include rock mass Categories 1 through 5, as representative of the variability of 
lithophysal rock mass quality on the repository level. It was planned to conduct simulations of 
ANL-EBS-MD-000027 REV 03 6-156 September 2004 

Drift Degradation Analysis 
drift stability for ground motions with 110-7 probability of annual occurrence. However, the 
results of analyses for 110-6 probability of annual occurrence (complete collapse of the 
emplacement drifts) determined such an analysis unnecessary. 
Table 6-44. Simulated Combinations of 10-6 Ground Motions and Rock Mass Categories 
Realization Number 
Ground Motion Time 
History Number 
Rock Mass Category 
Number 
1 4 3 
2 8 5 
3 16 4 
4 12 1 
5 2 3 
6 8 1 
7 14 2 
8 4 4 
9 10 2 
10 6 3 
11 9 1 
12 1 1 
13 1 3 
14 7 4 
15 11 4 
Source: DTN: MO0301SPASIP27.004 [DIRS 161869]. 
NOTE: Realization numbers 1 through 15 are from the sampling in the 
lithophysal zone provided by the source DTN. 
Model Initial and Boundary ConditionsAn in situ (before excavation) stress state, defined by 
7 MPa vertical and 3.5 MPa horizontal stresses, is used throughout the simulations, which is 
consistent with the 3DEC modeling in Section 6.3. The vertical stress represents the stress state 
at a depth of 300 m, and the lateral stress represents the horizontal component projected in the 
plane perpendicular to the emplacement drifts, whose azimuth is oriented at 72 degrees east of 
north. The equilibrium state of the model after excavation of a drift represents the initial 
condition for the dynamic analysis. This equilibrium state is achieved by performing a 
quasi-static simulation (because the mathematical formulation of UDEC is fully dynamic in 
nature) in which the in situ stresses are applied to the model that is allowed to equilibrate. The 
geometry and the boundary and initial conditions used in the initial quasi-static simulation 
preceding the dynamic simulation are illustrated in Figure 6-117. 
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Drift Degradation Analysis 
Figure 6-117. Dynamic Model, Initial and Boundary Conditions: Initial Quasi-Static Simulation 
The boundary conditions as used in the dynamic analysis are illustrated in Figure 6-118. Quiet 
boundaries (indicated in Figure 6-118 as viscous boundaries) were used on the outside 
boundaries of the models. These boundaries prevent reflection of outgoing seismic waves back 
into the model. Quiet boundaries were combined with free-field boundaries on the vertical 
outside boundaries. The free-field boundaries perform a one-dimensional simulation of 
vertically-propagating plane waves representing motion of a truncated, semi-infinite medium, 
thereby preventing distortion of vertically-propagating plane waves along the quiet boundaries. 
Dynamic loading was applied at the bottom of the model to provide vertically propagating shear 
and compression waves. Although the dynamic loading was specified as velocity time-histories, 
it was applied at the bottom model boundary as a time-varying stress boundary condition. This 
is possible because there is a direct correspondence between velocity and induced stress for plane 
waves in elastodynamics, and, therefore, time-varying velocity or stress boundary conditions are 
equivalent. The relationships used are given as follows (Itasca Consulting Group 2002 
[DIRS 160331], Manuals/3DEC/Optional Features/Section 2: Dynamic Analysis, Section 2.6): 
s= 2.Cv
y pv 
s
xy =2.Cvh 
(Eq. 6-7) 
s 
where .is rock density; Cp and Cs are P and S wave velocities, respectively; and .v and .h are 
vertical and horizontal velocity components. The factor 2 in Equation 6-7 is due to correction 
for the quiet boundaries. Figure 6-119 shows specified component 1 of the horizontal 
velocity history for ground motion 4 of 110-6 probability. Velocity histories at the bottom and 
the top of the model (shown in Figure 6-119), recorded during the simulation, confirm that the 
applied stress boundary condition results in ground motion velocity time histories that are the 
same as the specified velocity boundary condition. Comparison of the velocities at the top and 
bottom of the model (identical histories slightly offset in time) confirms that the free-field 
boundaries operate correctly in elimination of boundary effects. 
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Drift Degradation Analysis 
Figure 6-118. Model Boundary Conditions for Dynamic Simulation 
Source: DTN: MO0301TMHIS106.001 [DIRS 161868] provides the specified horizontal velocity. 
NOTE: The horizontal velocities recorded at the top and at the bottom of the model coincide with the specified 
velocity. 
Figure 6-119. Horizontal Velocity, Component 1 for Ground Motion 4 of 110-6 Probability 
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Drift Degradation Analysis 
6.4.2.2.1 Analysis of Drift Response to Preclosure Ground Motion 
The analyses indicate that preclosure ground motion levels (i.e., with probabilities of annual 
occurrence of 510-4 and 110-4) will not induce any rockfall for rock mass strength 
Categories 2 through 5. A relatively small amount of rockfall from the drift walls (shown in 
Figure 6-120) is expected for unsupported excavations in Category 1, which represents less than 
5 percent of the Tptpll (see Figure 6-115 and Appendix E). The elastic stress paths from the 
110-4 preclosure ground motion simulation for the Category 1 rock mass (shown in 
Figures 6-121 and 6-122 in the wall and roof, respectively), and the Category 5 rock mass 
(shown in Figures 6-123 and 6-124 in the wall and roof, respectively), indicate that this level of 
ground motion causes small oscillations of the stress state relative to the initial equilibrium. 
With the exception of the monitoring location at the drift wall for the Category 1 rock mass, the 
stress states are within the elastic region throughout the duration of the 110-4 preclosure ground 
motion. The observed rockfall is a consequence of regions that are above the yield limit after 
excavation of the drift (i.e., the wall in the Category 1 rock mass) being shaken down in the 
absence of ground support. 
a) 5x10-4 ground motion 
b) 1x10-4 ground motion 
NOTE: Rock mass Categories 2 to 5 show no damage. Red lines indicate block bonds that have failed in shear or 
tension. 
Figure 6-120. Geometry of the Model after Simulation for Preclosure Ground Motions: Rock Mass 
Category 1 
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Drift Degradation Analysis 
2.0E+7 
Maximum Principal Stress (Pa) 
1.5E+7 
1.0E+7 
5.0E+6 
0.0E+0 
Yield Zone far field 
1.28 m from wall 
0.17 m from wall 
failure envelope 
Elastic Zone 
0.0E+0 1.0E+6 2.0E+6 3.0E+6 4.0E+6 
Minimum Principal Stress (Pa) 
Figure 6-121. Elastic Stress Paths in the Drift Wall Due to 110-4 Preclosure Ground Motion: Category 1 
1.5E+7 
Maximum Principal Stress (Pa) 
1.0E+7 
5.0E+6 
0.0E+0 
Yield Zone far field 
1.28 m from roof 
0.17 m from roof 
failure envelope 
Elastic Zone 
0.0E+0 1.0E+6 2.0E+6 3.0E+6 4.0E+6 
Minimum Principal Stress (Pa) 
Figure 6-122. Elastic Stress Paths in the Drift Roof Due to 110-4 Preclosure Ground Motion: Category 1 
ANL-EBS-MD-000027 REV 03 6-161 September 2004 

Drift Degradation Analysis 
iiil () 
ld 
ll 
ll 
illYi0.0E+0 
1.0E+7 
2.0E+7 
3.0E+7 
4.0E+7 
Maxmum Prncpa StressPafar fie1.28 m from wa0.17 m from wafaure enveope 
eld Zone 
Elastic Zone 
0.0E+0 1.0E+6 2.0E+6 3.0E+6 4.0E+6 5.0E+6 
Minimum Principal Stress (Pa) 
Figure 6-123. Elastic Stress Paths in the Drift Wall Due to 110-4 Preclosure Ground Motion: Category 5 
il() 
ield 
illYi0.0E+0 
1.0E+7 
2.0E+7 
3.0E+7 
4.0E+7 
Maximum Prncipa Stress Pafar f1.28 m from roof 
0.17 m from roof 
faure enveope 
eld Zone 
Elastic Zone 
0.0E+0 1.0E+6 2.0E+6 3.0E+6 4.0E+6 5.0E+6 
Minimum Principal Stress (Pa) 
Figure 6-124. Elastic Stress Paths in the Drift Roof Due to 110-4 Preclosure Ground Motion: Category 5 
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Drift Degradation Analysis 
6.4.2.2.2 Analysis of Drift Response to Postclosure Ground Motions 
6.4.2.2.2.1 Analysis of 110-5 Ground Motions 
The 110-5 annual exceedance frequency is described by 15 sets of three ground motionsone 
vertical and two horizontal. These ground motions were developed by scaling horizontal 
component 1 to a repository level target peak ground velocity (PGV), and scaling other 
components to maintain inter-component variability. For a detailed discussion of the 
development of the ground motion time histories see Development of Earthquake Ground 
Motion Input for Preclosure Seismic Design and Postclosure Performance Assessment of a 
Geologic Repository at Yucca Mountain, NV (BSC 2004 [DIRS 170027]). Table 6-45 
summarizes the peak ground velocities for each of the motions. 
Table 6-45. Summary of 10-5 Ground Motion Characteristics 
Ground Motion 
Horizontal 
Component 1 
PGV (cm/sec) 
Horizontal 
Component 2 
PGV (cm/sec) 
Vertical 
Component PGV 
(cm/sec) 
Set 1 104.58 83.31 70.88 
Set 2 104.58 125.02 145.25 
Set 3 104.58 262.05 398.11 
Set 4 104.59 100.41 152.27 
Set 5 104.58 166.71 106.52 
Set 6 104.54 45.61 173.88 
Set 7 104.51 89.33 333.16 
Set 8 104.56 152.20 98.16 
Set 9 104.59 357.76 281.76 
Set 10 104.60 31.81 50.16 
Set 11 104.60 126.04 120.31 
Set 12 104.54 70.34 100.60 
Set 13 104.58 103.75 318.01 
Set 14 104.62 40.87 92.78 
Set 15 104.56 67.43 137.53 
Source: DTN: MO0402AVDTM105.001 [DIRS 168890]. 
The vertical (V) and horizontal component 1 (H1) are applied at the base of the cross-sectional 
UDEC lithophysal rockfall model for consistency with three-dimensional waste package 
vibratory motion models in which the H1 component acts in the drift cross-sectional plane and 
H2 acts along the axis of the tunnel (BSC 2004 [DIRS 167083]). As seen in Table 6-45, 
approximately 25 percent (4 of 15) of the ground motion sets have a largest associated PGV in 
excess of 300 cm/sec, approximately 60 percent (9 of 15) with largest associated PGV of 100 to 
approximately 150 cm/sec, and approximately 15 percent (2 of 15) with largest associated PGV 
between 150 and 175 cm/sec. In a significant number of the ground motion sets, the vertical 
component has the largest associated PGV. 
Parametric AnalysesAll 15 motion sets were applied to base case rock mass strength 
Categories 1, 3, and 5 to cover the range of rock qualities. As discussed previously, 
Category 1 (and Category 2) is viewed as a condition of localized, high porosity (possibly 
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large lithophysae) and represents less than 10 percent of the Tptpll. Category 3 (and Category 4) 
is viewed as a typical condition encountered in the Tptpll, representing approximately 60 percent 
of the Tptpll, and Category 5 viewed as the higher rock mass quality areas in the Tptpll, 
representing approximately 30 percent of the Tptpll. The sequencing of modeling initially 
involved application of in situ stresses to the rock mass and the unsupported emplacement drift, 
and allowed the system to equilibrate with any associated rockfall. Each ground motion is 
applied to the base of the model in the form of the time-varying vertical and horizontal motions, 
which are allowed to run through to the cutoff time of 95 percent of total energy. 
ResultsThe level of damage induced by the ground motion is quantified here by the area 
(volume) of the rock that is detached from the surrounding rock mass and falls into the tunnel. 
Because the model is two dimensional, it essentially represents a 1-m thick slice of material 
parallel to the axis of the drift. The damage is thus given in terms of volume/m of emplacement 
drift, or m3/m. This could be converted to metric tons by multiplying by the density, which, for 
the lithophysal rock, is approximately 2 tons/m3 (the matrix density is approximately 
2.5 tons/m3). 
Figures 6-125 to 6-127 show representative examples of the mechanism and level of damage 
induced for rock strength Categories 1, 3, and 5 for ground motions 12 (104 cm/sec PGV), 
4 (152 cm/sec PGV), and 7 (333 cm/sec PGV). These ground motions cover the approximate 
range of PGVs for the 15 motions. The damage levels are further plotted for each rock mass 
strength category as a function of PGV in Figure 6-128. The analyses show that the damage 
appears to be primarily related to the magnitude of PGV, but is highly variable, particularly at 
large PGV, presumably due to the variability in the time histories and their impact on the energy 
(or power) contained in the waveform. An approximate linear upper bound to the damage can be 
seen in this plot in a fashion similar to that shown in Figure 6-83 for rockfall as a function of 
PGV in nonlithophysal rock. The variability in the response is a function of the properties of the 
ground motion time histories, not the rock properties, since constant modulus and strength are 
considered for a given category. 
To investigate further the correlation to energy content of the ground motion, the vertical time 
history for each ground motion was run through a Fast Fourier Transform. The Fast Fourier 
Transform performs an integration of the square of the velocity over the duration of the time 
history, thus producing a power spectral density for velocity. This term is proportional to the 
integrated kinetic energy [kinetic energy = (mv2)] of the time history. The damage as a 
function of the velocity power spectral density for the vertical ground motion for each of the 
45 analyses is plotted in Figure 6-129. This plot shows that the damage is linearly related to the 
energy associated with the velocity time history. Therefore, although PGV appears to be 
reasonably associated with the damage level and provides a means of bounding the response, the 
energy in the time history is a better indicator of the potential damage. 
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NOTE: (upper left) Rock Strength Category 1 (5.6 m2/m drift length), (upper right) Category 3 (0.02 m2/m), 
(lower left) Category 5 (0.1 m2/m), and (lower right) Ground Motion History 12, PGV=104 cm/sec. 
Figure 6-125. Example of Comparison of Damage Levels for Lower End of PGV (104 cm/sec) for 110-5 
Annual Exceedance Level 
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NOTE: (upper left) Rock Strength Category 1 (3.3 m2/m drift length), (upper right) Category 3 (2.2 m2/m), 
(lower left) Category 5 (0.3 m2/m), and (lower right) Ground Motion History 4, PGV=152 cm/sec. 
Figure 6-126. Example of Comparison of Damage Levels for PGV of 152 cm/sec for 110-5 Annual 
Exceedance Level 
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NOTE: (upper left) Rock Strength Category 1 (40.6 m2/m drift length), (upper right) Category 5 (19.7 m2/m), 
(lower left) Category 3 (15.4 m2/m), and (lower right) Ground Motion History 7, PGV=333 cm/sec. 
Figure 6-127. Example of Comparison of Damage Levels for Upper End of PGV (333 cm/sec) for 
110-5 m/sec 
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NOTE: Damage levels for the 15 ground motions are given. Results for spatially variable lithophysal porosity are 
also given for comparison. 
Figure 6-128. Estimate 110-5 Damage Level, Expressed as m2/m of Emplacement Drift Length for 
Rock Strength Categories 1, 3, and 5 for the 15 Ground Motion Time Histories 
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NOTE: The power spectral density is obtained by integrating the square of the velocity time history, producing a 
value proportional to the kinetic energy. 
Figure 6-129. Rockfall Damage as a Function of the Energy Associated With the Vertical Velocity Time 
History 
DiscussionThe drift damage mechanism consists primarily of shear failure at the springlines of 
the tunnel coinciding with passage of the compressive stress increase associated with PGV peaks 
in the time history. The in situ stress field has major vertical and secondary horizontal stress 
components. The vertical compression or horizontal shear wave essentially results in a free field 
dynamic stress increase as shown in Equation 6-7 (note that the correction factor of 2 in 
Equation 6-7 is for boundary conditions only, and therefore is not required). These dynamic 
components are superimposed on the existing in situ stress field to cause additional stressing or 
relaxation of the rock mass surrounding the drift. The end-result of this superposition is that the 
stress tensor rotates about the general vertical axis as the ground velocities oscillate over the 
duration of the strong ground motion. If the addition of dynamic plus in situ stress is large 
enough, shear failure occurs primarily at the springlines, resulting in development of an elliptic 
shape of the opening as the rock mass yields and rockfall occurs and falls along the sides of the 
drip shield. The extent of shear failure and rockfall around the circumference of the tunnel, up 
and down from the springline, is due to both the general ratio of rock mass strength to stress, but 
also to the ratio of the vertical to horizontal PGV. The greater the horizontal component, the 
greater the rotation of the stress tensor, which results in greater inclination of the major principal 
stress. Generally, this shear failure mechanism occurs with the arrival of the PGV peaks. 
Compressive stresses also appear responsible for some cases in which roof slabbing is observed 
where the rock mass strength and stiffness are larger (i.e., Category 5). A second failure 
mechanism observed includes tensile failure of the rock mass resulting from the reversal of the 
ground motion and inducement of dynamic tensile straining in the rock mass. 
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In general, it appears that the rock mass failure and the rockfall occur simultaneously with the 
arrival of velocity peaks in the time histories. In a similar fashion, the peak ground velocity has 
been recognized by many authors as the primary contributing factor to dynamic rock mass failure 
in mine tunnels, slopes, and dams (e.g., MRD 1995 [DIRS 169719], Volume 2, Section 6.2.3; 
Newmark 1965 [DIRS 169515]). In the present case, the shear or tensile failure mechanism 
results in a predicted creation of blocks resulting from fracture of the rock mass along the 
ubiquitous fracture network of the material. The blocks that contact the drip shield are relatively 
small in size, and governed by the inherent fracture network and lithophysae spacing. The 
UDEC lithophysal rockfall model studies have primarily used a 0.3-m average fracture spacing 
in developing the block structure, although simulations with 0.2-m spacing have also been 
conducted. In each case, the transient dynamic stress changes, in addition to pre-existing in situ 
stresses, result in breakage of the bonds between the blocks in the rockfall zone around the 
tunnel. In other words, the stressing does not create large blocks that impact the drip shield, but 
small component blocks defined by the inherent fracturing of the Tptpll. 
Although the damage levels appear to correlate somewhat better to the energy content of the time 
history, correlation to PGV provides a simpler method for interpretation of the results. 
Correlation to PGV is also consistent with that used in waste package and drip shield vibratory 
motion damage abstractions (Seismic Consequence Abstraction, BSC 2004 [DIRS 169183]). An 
approximate relationship of damage level to PGV in terms of both m3/m of drift length and 
physical interpretation can be roughly approximated as follows: 
 Peak ground velocities below about 1 m/sec result in relatively minor damage to 
unsupported drifts. 
 Peak ground velocities below about 1.5 m/sec result in an approximate damage level 
below 5 m3/m. This damage level is characterized by a range from minor spalling to 
damage characterized by rock particles filling the invert along the sides of the drip shield 
(see Figure 6-125). 
 Peak ground velocities from approximately 1.5 to 2 m/sec result in damage levels from 5 
to 15 m3/m. This damage level is characterized by rock particles covering the sides of 
the drip shield to, approximately, the height of the drip shield, and may cover the top of 
the drip shield (see Figure 6-126). 
 Peak ground velocities in excess of about 2 m/sec result in damage levels above 
15 m3/m. This damage level is characterized by complete collapse of the tunnel (see 
Figure 6-127). 
Dynamic Drip Shield Loading From 110-5 Ground MotionsCollapse of a tunnel in 
lithophysal rock results in loading applied to the drip shield. The rock loads fall under three 
primary categories: 
 Dynamic loading from the rock particles striking the drip shield 
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 Quasi-static loading of the drip shield due to the dead weight of the fallen rock at rest on 
the drip shield 
 Dynamic loading of the drip shield due to rockfall induced by drift collapse. 
In this section, the dynamic loading of the drip shield due to rockfall induced by drift collapse 
from the 110-5 ground motion, is examined. The quasi-static load on the drip shield once the 
seismic shaking stops and the system comes to force equilibrium, is discussed in Section 6.4.2.5. 
In these analyses, the drip shield is considered deformable, with the geometry consistent with 
Seismic Consequence Abstraction (BSC 2004 [DIRS 169183]; and see Figure 6-130). The drip 
shield is idealized as a two-dimensional model of the actual geometry and deformability of the 
drip shield using the standard UDEC element structure. The drip shield is subdivided into 30 
total segments of equal length. The elements are considered to be elastic, and, thus, no potential 
yield response is modeled. The purpose of these analyses is to provide estimates of both 
dynamic and quasi-static structural loading to the detailed dynamic analysis of drip shield 
structural response using the LS-DYNA three-dimensional finite element model (Drip Shield 
Structural Response to Rock Fall, BSC 2004 [DIRS 168993]). Because the UDEC lithophysal 
rockfall model is two-dimensional and does not attempt to model the detailed structure of the 
drip shield, the stiffness of the elements must be adjusted to provide an equivalent overall 
deformability to the actual three-dimensional structure. The stiffness of the UDEC elements has 
been calibrated against the three-dimensional LS-DYNA model to reproduce the deformability 
of the actual drip shield design (see Appendix Y). The dynamic loading from detached rock 
particles during the seismic shaking (includes the effect of relative velocity of between the drip 
shield and the falling rock) is examined here. 
NOTE: Case with drift collapse for Rock Mass Category 1 and Ground Motion Set 9 with PGV of 2.82 m/sec. 
Figure 6-130. Representation of the Drip Shield as a Deformable Structure With Actual Geometries and 
Footings That are Either Free to Slide or to Slide and Separate From the Invert 
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An example of the dynamic impact loading from side and top impacts to the deformable drip 
shield resulting from the 110-5 ground motion (PGV=3.33 m/sec case) are given in 
Figure 6-131.8 In this figure, the average pressure across an element (in Pa) is given as a 
function of time (in seconds). In general, the transient stress at any given element is 
approximately one order of magnitude greater than the eventual dead weight load of bulked rock 
for the case of a completely-collapsed tunnel at equilibrium (see Section 6.4.2.5). However, due 
to the relatively small size of the rock particles developed in the lithophysal rock (in comparison 
to the much larger blocks in the nonlithophysal material), the nonlithophysal dynamic impact 
loading to the drip shield provides a more conservative, bounding case. Therefore, the 
nonlithophysal rockfall case provides the primary input for dynamic impact loading for the 
damage analysis and design of the drip shield. Dead weight quasi-static loading of the drip 
shield as described in Section 6.4.2.5 is felt to be a more important loading mechanism in the 
lithophysal rock mass. 
6.4.2.2.2.2 Analysis of 110-6 Ground Motions 
Drift Failure Response - Ground motions with a probability of an annual occurrence of 110-6 
cause complete collapse of the emplacement drifts irrespective of the rock mass category and 
ground motion case. The model geometries after simulations of realization numbers 1 through 6 
from Table 6-44 are shown in Figure 6-132. Elastic stress paths (for ground motion case 1) 
shown in Figures 6-133 and 6-134, for the Category 1 rock mass, and Figures 6-135 and 6-136, 
for the Category 5 rock mass, demonstrate different mechanisms of drift collapse depending on 
the rock mass quality. In poor quality rock masses (e.g., Category 1), far-field stress (unaffected 
by the drift) is mostly elastic during the history of the ground shaking. However, stress 
amplifications and concentrations around the drift cause intense yielding in tension and shear, 
which eventually causes the drift to collapse. In the case of better rock mass quality (e.g., 
Category 5), the rock mass fails in tension even for far-field conditions (away from the drift), and 
tensile fractures propagate throughout the rock mass. The drift creates an open space into which 
the loose blocks collapse. 
Dynamic Drip Shield Loading From 110-6 Ground MotionsCollapse of a tunnel in 
lithophysal rock results in loading applied to the drip shield. The dynamic loading of the drip 
shield due to rockfall induced by drift collapse from the 110-6 ground motion is examined and 
presented in Appendix P (Figures P-29 to P-31). The quasi-static load on the drip shield once the 
seismic shaking stops and the system comes to force equilibrium, is discussed in Section 6.4.2.5. 
The dynamic loading of the drip shield by small rock blocks from the Tptpll determined from 110-5 ground 
motions is considered to be reasonable for the ground motions that cause complete collapse since the rock blocks 
fall from the same height under gravity. 
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NOTE: Segments 110 are found along the wall, starting at the footing. 
Figure 6-131. Example of Dynamic Impact Loading with 110-5 Ground Motions to the Right Wall (top) 
and Roof (bottom) of Deformable Drip Shield With Arched Roof 
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NOTE: Blocks are colored by magnitude of displacement (m). 
Figure 6-132. Geometry of the Model After Simulations for Postclosure Ground Motions (Probability 
110-6): Realizations 1 Through 6 from Table 6-44 
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Figure 6-133. Elastic Stress Paths in the Drift Wall Due to Postclosure Ground Motion No. 1: Category 1 
Figure 6-134. Elastic Stress Paths in the Drift Roof Due to Postclosure Ground Motion No. 1: Category 1 
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Figure 6-135. Elastic Stress Paths in the Drift Wall Due to Postclosure Ground Motion No. 1: Category 5 
Figure 6-136. Elastic Stress Paths in the Drift Roof Due to Postclosure Ground Motion No. 1: Category 5 
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6.4.2.2.3 Sensitivity of Mechanical Properties to Rockfall Prediction 
The base case and bounding case rock mechanical properties are presented in Table 6-41. 
Uncertainties for the range of rock properties are considered in the previous sections with 
5 categories of rock mass properties which cover the strength range of 10 to 30 MPa. 
Consideration was also given to the likely scatterness of the strength within the same category 
(the lower and upper bounds column in Table 6-41). This section presents the results for the 
analyses based on lower bound strength properties. The upper bound with higher strength will 
yield more stable drift conditions compared with the base case and hence is not considered in the 
sensitivity study. The region of analyses is simplified as homogeneous material for the base case 
and lower bound case. Sensitivity of spatial variation within the model region is also considered. 
6.4.2.2.3.1 Consideration of Lower Bound Strength 
Based on the assessment of rock mass properties documented in Appendix E (Section E4.1), the 
lower bound strength ranges from 10 MPa to 16 MPa for the 5 categories compared with the 
range of 10 MPa to 30 MPa for the base case. In fact, 10 MPa lower bound strength was 
assigned to categories 1 to 3 (Table 6-41). Categories 3 and 5 were selected for the seismic 
analysis sensitivity consideration. Since rockfall results presented in the previous sections 
indicate that minor spalling or no damage is predicted for the preclosure ground motion and drift 
collapse predicted for the 110-6 ground motions, the sensitivity case only considers 110-5 
ground motions. The 15 ground motions were applied to categories 3 and 5 rock. Collapse of 
the drift is observed for most of the cases even with category 5 rock. Figure 6-137 shows the 
results for category 5 rock subject to ground motion set 12 (PGV = 104 cm/sec), 
set 4 (PGV = 152 cm/sec), and set 7 (PGV = 333 cm/sec), the same selection as presented in 
Figures 6-125 to 6-127. The results represent a very conservative for the nominal case with the 
consideration in that the surrounding rock is homogeneous and entirely biased to the 
low-strength end of the distribution within its category. Since the lower bound is estimated 
based on the saturated samples as shown in Figure E-18, the results indicate that the saturated 
drift environment is likely to collapse when subject to 110-5 ground motions. But for nominal 
case with relatively dry condition, spatial variation of rock around the drift is most realistic and 
should be considered. This is described in the following subsection. 
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a) ground motion set 12, peak ground motion = 104 cm/sec 
b) ground motion set 4, peak ground motion = 152 cm/sec 
c) ground motion set 7, peak ground motion = 333 cm/sec 
Figure 6-137. Drift Damage for Category 5 Lower Bound Strength Subject to 110-5 Ground Motions 
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6.4.2.2.3.2 Impact of Spatial Variability on Drift Stability 
In the previous analyses, the rock mass properties were considered homogeneous for a given 
drift cross-section. Here, the impact of considering actual spatial variability of lithophysal 
porosity on damage from 110-5 ground motions is examined. A representative section of the 
Tptpll was extracted from the upper portion of the lithophysal porosity model as described in 
Appendix T. This model contains a wide range of lithophysal porosity averaging approximately 
15 percent, but ranging from greater than 20 percent to less than 10 percent. The resulting 
UDEC lithophysal rockfall model showing spatially variable porosity is given in Figure 6-138. 
NOTE: Lithophysal porosity variability derived from Appendix T, Figure T-5. 
Figure 6-138. Contours of Lithophysal Porosity Contoured on the UDEC Spatial Variability Model 
Rock mass strength properties for Categories 1 to 5 were assigned to regions within the model 
based on the lithophysal porosity levels (Table E-10), achieving spatial variability in strength and 
moduli. This model was subjected to the 15 110-5 ground motions, and damage levels were 
determined. The results of the dynamic simulations, in terms of damage versus PGV, are shown 
in Figure 6-128. The damage levels are approximately within the range of that predicted for 
Category 3 rock mass, as expected, because the mean lithophysal porosity of the model falls 
within the range of the Category 3 levels. This analysis indicates that the use of homogenous 
rock properties that span the range of strength categories does span the range of expected 
response, including conservative damage for the low strength categories. 
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6.4.2.2.4 Estimation of Drift Profile for Feeds to the Abstraction of Drift Seepage 
The analyses presented here have provided an estimate of the extent of drift degradation due 
seismic shaking as a function of annual probability of exceedance. A summary of the resulting 
drift profiles extracted from the UDEC lithophysal rockfall modeling is provided in output 
DTN: MO0306MWDDPPDR.000 [DIRS 164736] for the worst case for preclosure and 
postclosure damage from seismic loading. The drift profile exhibiting the greatest breakout 
resulting from preclosure ground motion is shown in Figure 6-120. The drift profile exhibiting 
the greatest breakout resulting from 110-6 postclosure ground motion is shown in Figure 6-132, 
which shows complete collapse of the drift opening. The 110-7 postclosure ground motion also 
results in complete drift collapse. 
Among other factors, the seepage flux depends on both the size and geometry of the drift and the 
capillary strength of the fractured rock surrounding the drift opening (BSC 2004 [DIRS 169131], 
Section 6.4.2.4). In partially or fully collapsed drifts, the larger size and potentially different 
crown shape after collapse will reduce the potential for flow diversion compared to the initial 
drift geometry; furthermore, the larger footprint of the collapsed drift leads to an increase in the 
total amount of percolation flux arriving at the drifts, which, in turn, can affect the total amount 
of seepage. In addition, the capillary-barrier behavior at the drift wall can be affected by the 
rubble rock particles filling the opening, as the capillary strength inside the opening will be 
different from the zero capillarity condition in the initially-open drift. Thus, the geometry of the 
degraded drift and the capillary strength of the rubble material inside the drift are of importance 
in the abstraction of drift seepage. 
Appendix R includes the drift profiles for strength Category 1 rock with consideration of seismic 
loading, thermal loading (discussed in Section 6.4.2.3), and strength degradation (discussed in 
Sections 6.4.2.4 and 6.4.2.5). Thirty scenarios are provided. Appendix R also provides 
information for degraded rock mass characteristics around the opening that may be of potential 
importance from a seepage or capillary strength standpoint. The information consists of the 
stress tensor for UDEC zones, aperture change along the joints, and averaged volumetric strain. 
6.4.2.3 Thermal Consideration in Lithophysal Units 
6.4.2.3.1 Thermal Loading 
Geometry and boundary conditions used in the model for predictions of thermally induced 
rockfall are shown in Figure 6-139. A detailed discussion of the boundary conditions for the 
thermal-mechanical model is provided in Appendix W. The model does not perform complete 
thermal-mechanical simulations. Instead, temperature fields calculated with the code NUFT, for 
1.45 kW/m and 50 years of forced ventilation, are imported into UDEC (thermal calculation 
described in Section 6.2, see Appendix U for methodology for importing temperatures). 
Two cases of ventilation efficiency were considered: 90 and 70 percent. Stresses are calculated 
for each new temperature state based on the temperature increment (from the previous 
temperature state) and the coefficient of thermal expansion. For the considered cases, the same 
coefficient of thermal expansion as a function of temperature, was used. To have gradual 
evolution of stresses during the simulated time, 45 temperature fields (corresponding to different 
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times after waste emplacements) were imported from NUFT to UDEC. For each new 
temperature field, a simulation was conducted in two steps: 
 The model was run to equilibrium elastically (i.e., the unbroken bonds were made 
infinitely strong) 
 After the model had reached equilibrium, the actual strength was assigned to the 
unbroken bonds and the model was run again to the equilibrium. 
The reason for the two-step approach was to reduce the impact of non-gradual stress changes due 
to incremental changes of the temperature state. The entire analysis was conducted considering 
that rock mass strength does not degrade with time. Any observed damage and rockfall are 
consequences of the thermally induced stresses only. The three cases of thermal calculation 
(described in Section 6.2) were considered for the drift stability analysis in lithophysal rock 
mass: 
 Base case (average thermal properties and 90 percent ventilation efficiency) 
 Case 2, sensitivity calculation for thermal properties (thermal properties one standard 
deviation smaller than the average properties) 
 Case 3, sensitivity calculation for the heat removal ratio (average thermal properties and 
70 percent ventilation efficiency). 
Figure 6-139. Thermal-Mechanical Model Initial and Boundary Conditions 
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The simulation was conducted for the five mechanical properties categories of the rock mass. It 
is observed that the amount of thermally induced rockfall is generally small. The temperature 
and stress fields for rock mass Category 1 with the base case thermal properties and 90 percent 
ventilation efficiency are shown in Figure 6-140. The figure shows the model state after 80 and 
10,000 years of heating for the consideration of no time-dependent change in rock strength. 
There is no significant rockfall or damage induced by heating. Conditions are similar for other 
rock mass categories. Elastic stress paths during 10,000 years of temperature variation are 
shown in Figures 6-141 and 6-142, for rock mass Category 1 in the wall and roof, respectively; 
and in Figures 6-143 and 6-144, for rock mass Category 5 in the wall and roof, respectively. The 
elastic stress paths confirm the results of the UDEC lithophysal rockfall model. The drift wall in 
the Category 1 rock mass is in the yielding state after drift excavation. Heating does not increase 
damage significantly (Figure 6-141). The stress state in the drift roof in Category 1 (shown in 
Figure 6-142) moves closer to the yield surface during heating, but it remains elastic. The 
thermal stress increase in the drift roof in the Category 5 rock mass (Youngs modulus of 
19.7 MPa) moves the stress state barely above the yield surface (Figure 6-144) during the 
relatively short period when the temperature reaches the maximum, around 80 years after waste 
emplacement. This is consistent with observation of minor rockfall from the drift roof in rock 
mass Category 5. 
The rockfall simulations using temperatures from Cases 2 and 3 of the thermal calculation do not 
show any increase in rockfall compared to the base case. 
6.4.2.3.2 Combined Seismic and Thermal Effect in Lithophysal Units 
Stability of the emplacement drifts located in the lithophysal rock units was investigated for both 
thermal and seismic loading conditions independently for both seismic and thermal loading 
conditions in Sections 6.4.2.2 and 6.4.2.3.1, respectively. The initial condition for the seismic 
analysis discussed in Section 6.4.2.2 was in situ stress state perturbed by excavation of the drifts 
only. An additional analysis, presented in this section, was done to assess the effect of changing 
thermal stress in the rock mass around the repository after waste emplacement as an initial 
condition for seismic ground shaking. Using a similar approach as for the nonlithophysal rock 
(Section 6.3.1.4), stress paths during the regulatory period of 10,000 years were recorded at a 
number of locations around the drift. Temperatures from the thermal calculations for the base 
case and the sensitivity calculation for the heat removal ratio (case 3 in Section 6.2) were 
considered. The critical state was qualitatively determined from those paths, based on locations 
of stress states along that path relative to the yield surface. The critical state was used as an 
initial condition for the seismic analysis. Because the ground motion with 110-6 probability of 
annual occurrence results in complete drift collapse, it was not of particular interest to investigate 
the effect of that level of ground motion combined with thermally induced initial stresses. 
Instead, ground motions with 110-4 and 110-5 probability of annual occurrence were 
considered. Since the predicted temperatures are similar for the base case and the sensitivity 
case 2 at preclosure period, the sensitivity case 2 is not considered for the evaluation of the 
combined seismic and thermal effect. Rock mass categories 1 and 5 were considered in this 
analysis. 
Stress paths (transient change in principal stresses) at 14 different locations around the drifts in 
rock mass category 5 during the regulatory period of 10,000 years are shown in Figures 6-141, 
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Drift Degradation Analysis 
6-142, and 6-143. A yield condition corresponding to 30 MPa uniaxial compressive strength, 
and a friction angle of 40 is also indicated in the figures. The stress state at a point close to the 
drift springline (shown in Figure 6-141), is above the yield surface, indicating yielding. Because 
those stresses are at the points inside the elastic blocks (inelastic behavior of this model is due to 
inelastic deformation of joints only), it is possible that they lie outside the yielding surface. The 
initial stress state and the state after 80 years of heating, selected as critical on the stress path, are 
marked on the plots with the squares. 
Figure 6-140. Thermally Induced Rockfall and Stresses After 80 and 10,000 years of Heating in Rock 
Mass Category 1 
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Drift Degradation Analysis 
Figure 6-141. Elastic Stress Paths in the Drift Wall Due to Temperature History: Category 1 
Figure 6-142. Elastic Stress Paths in the Drift Roof Due to Temperature History: Category 1 
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Drift Degradation Analysis 
Figure 6-143. Elastic Stress Paths in the Drift Wall Due to Temperature History: Category 5 
Figure 6-144. Elastic Stress Paths in the Drift Roof Due to Temperature History: Category 5 
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Drift Degradation Analysis 
Seismic analysis after 80 years of heating for rock mass category 1 resulted in an increased 
rockfall compared to rockfall from the seismic shaking of the rock mass at an in situ stress state 
(see Figure 6-145 for results with 110-4 ground motion). Very little rockfall is induced in rock 
mass category 5 in the case of 70 percent ventilation efficiency. For the cases with 80 years 
heating and 110-5 ground motions shaking, 3 sets of ground motions were considered: (a) set 
10 with peak ground velocity = 104.6 cm/sec, (b) set 6 with peak ground 
velocity = 173.88 cm/sec, and (c) set 13 with peak ground velocity = 318.01 cm/sec. The results 
are presented in Figures 6-146 to 6-148. Rockfall with set 10 ground motion are similar to the 
results for preclosure ground motions. However, more extensive rockfall is observed for ground 
motion sets 6 and 13. The results show increase of rockfall for category 5 rock mass when 
comparing with seismic only scenario with large ground motions as shown in Figure 6-127. 
The result of an increase in rockfall for lithophysal rock mass category 1 with thermal loading is 
in an apparent contradiction with the results of the same analysis for the nonlithophysal units. 
Thermal stresses in the case of nonlithophysal rock resulted in reduced rockfall. However, the 
mechanism of rockfall is completely different for these two cases. In the case of the 
nonlithophysal rock mass, rockfall is due to sliding of blocks along the pre-existing joints, and an 
increase in the initial stress increases confinement on the joints, thereby increasing their 
resistance to sliding. In the case of the lithophysal rock mass, ground motion with 110-4 
probability of annual occurrence causes rockfall by shaking down already damaged rock mass 
around the drift. Therefore, the heating induces additional damage (compared to damage caused 
by drift excavation), which does not necessarily result in a rockfall under static loading 
conditions, but is shaken down by the 110-4 ground motion. 
a) category 1 
b) category 5 
Figure 6-145. Rockfall and Fractures Induced Around a Drift by 1  10-4 Preclosure Ground Motion 
After the Peak Thermal Condition Occurring at 80 Years of Heating (30 Years after 
Closure) in Rock Mass Categories 1 and 5 
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Drift Degradation Analysis 
a) Category 1
b) Category 5
Figure 6-146. Rockfall and Fractures Induced Around a Drift by 110-5 Earthquake Set 10 (peak ground 
velocity = 104.6 cm/sec) After 80 Years of Heating in Rock Mass Categories 1 and 5 
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Drift Degradation Analysis 
a) Category 1
b) Category 5
Figure 6-147. Rockfall and Fractures Induced Around a Drift by 110-5 Earthquake Set 6 (peak ground
velocity = 173.88 cm/sec) After 80 Years of Heating in Rock Mass Categories 1 and 5 
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Drift Degradation Analysis 
a) Category 1 
b) Category 5 
Figure 6-148. Rockfall and Fractures Induced Around a Drift by 110-5 Earthquake Set 13 (peak ground 
velocity = 318.01 cm/sec) After 80 Years of Heating in Rock Mass Categories 1 and 5 
6.4.2.4 Time-Dependent Consideration in Lithophysal Units 
Underground and surface excavations, which are designed to be stable after excavation, degrade 
with time, and some eventually collapse completely. The degradation of excavations in hard 
rocks has not been studied extensively, because most underground excavations have service lives 
of 100 years or less and are maintained as required. However, there are many examples of 
stable, unsupported excavations associated with mining, and civil construction or 
ANL-EBS-MD-000027 REV 03 6-189 September 2004 

Drift Degradation Analysis 
naturally-occurring caves in numerous rock types that are stable, or have suffered only minor 
instability for hundreds or even thousands of years. Thus, there is no certainty that collapse of 
unsupported excavations, particularly those subjected to low stress, relatively dry conditions, is 
inevitable. 
The primary reason for eventual yield and collapse is that a hard rock mass, exposed to humidity 
and temperature of the open atmosphere, may undergo strength decay with time when it is loaded 
to stress levels higher than about 50 to 60 percent of its short-term strength. The rate of strength 
decay depends on, among other parameters, rock type (particularly the mineralogy and grain 
structure), stress state, relative humidity, and temperature. Stress corrosion is considered the 
primary mechanism causing strength degradation of hard rocks (Potyondy and Cundall 2001 
[DIRS 156895], Section 3). 
The emplacement drifts at Yucca Mountain will be stable under existing conditions (in situ 
stresses and rock mass strength) with ground support as demonstrated by the ESF and ECRB 
Cross-Drift observations. However, it is expected that the ground support will completely lose 
its integrity during the 10,000-year regulatory period, and drift degradation, to some extent, will 
occur due to strength decay of the rock mass. Drift degradation is an important issue for 
repository design and performance because drifts must remain stable during the preclosure 
operational period and, eventually, rubble resulting from degradation could impact in-drift 
environmental conditions, seepage, and the integrity and performance of the drip shields. 
Estimation of the rate of drift degradation for the duration of the 10,000-year regulatory period 
is, therefore, required. 
6.4.2.4.1 Empirical Observations of Degradation and Collapse of Excavations 
6.4.2.4.1.1 Unsupported Excavation Spans and Stand-Up Time 
There is currently no accepted methodology for estimating the time-dependent degradation 
behavior of tunnels in hard rocks. However, a number of empirical correlations have been 
developed for providing a means of estimating maximum stable spans of unsupported 
excavations and the length of time that an unsupported excavation may remain open and still 
provide a safe working environment (termed stand-up time) (Bieniawski 1989 [DIRS 101715]). 
Because these correlations are often used in estimating the time of instability of excavations, this 
appendix discusses their applicability to the postclosure stability of emplacement drifts at Yucca 
Mountain. 
Emplacement drifts for the repository are 5.5 m in diameter, are separated from one another by a 
center-to-center distance of 81 m, and are located at a nominal depth of 300 m below ground 
surface. The large ratio of drift diameter to spacing and diameter to depth means that each 
emplacement drift is mechanically isolated from one another and from the effects of the ground 
surface. Eventually there is thermal interaction between tunnels, but the local mechanical effects 
related to isolated tunnels is of greatest importance to short-term and long-term stability. 
Comparison of the maximum unsupported span from mining practice to the span of the proposed 
emplacement drifts is a reasonable means of estimating collapse potential. 
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Drift Degradation Analysis 
As the span of an excavation is made larger, there eventually becomes a point when instability 
and unsafe working conditions result. Empirical correlations (e.g., Hoek and Brown 1982 
[DIRS 120981], p. 287) of the maximum safe unsupported span and the time that this span may 
remain unsupported have been developed to assist tunneling engineers in planning excavations 
that are safe for tunnel construction workers. These correlations, which are typically based on 
some measure of rock mass quality, are inherently conservative in nature due to their purpose: to 
ensure personnel safety. The correlations are not based on case histories of actual collapse. For 
example, stand-up time is typically projected to be on the order of hours or days, even for good 
quality rock masses and may be only on the order of years (e.g., Hoek and Brown 1982 
[DIRS 120981], Figure 6). Examples of the existing tunnels at the Yucca Mountain site and 
Hoover Dam indicate that stand-up time is a worker-safety-related indicator and is not relevant to 
predictions of degradation or collapse time. These remarks indicate that construction-related 
span and stand-up time correlations have only limited application to postclosure predictions of 
drift degradation at the Yucca Mountain site. 
Stand-up time curves provide an estimate for potential of rockfall as a function of span, 
rock-mass quality, and time after excavation. The stress state around an excavation (e.g., depth 
of the excavation) is not a parameter that affects the stand-up time estimate. The stress state in 
the rock mass around the excavation, scaled to the short-term strength of the rock mass, is one of 
the most important factors controlling stability of the rock mass and evolution of stability as a 
function of time. Stand-up time curves were developed based on empirical evidence of 
instability of excavations in particular stress conditions (e.g., deep South African mines), and 
their application to completely different conditions is not relevant. 
6.4.2.4.1.2 Evidence of Maximum Unsupported Span from Mining Case Examples 
The mining industry, on the other hand, routinely drives unsupported excavations to large spans 
with the express purpose of inducing collapse for caving of ore bodies. Therefore, empirical 
evidence of maximum unsupported spans from mining case examples is more relevant to the 
estimation of the actual spans of excavations that induce degradation and ultimate collapse. The 
span of an excavation required to induce caving and collapse has been the topic of extensive 
study in the mining industry because certain types of mining methods (e.g., block and 
panel caving) are predicated to induce caving when a rock mass is undercut. Brown (2003 
[DIRS 169527]) provides a summary of worldwide caving operations and the spans of 
excavations necessary to induce collapse as a function of the rock mass quality (i.e., strength). 
Figure 6-149 provides a summary of worldwide experience in excavation span and collapse 
potential for cave mining. The plot provides a correlation between rock mass quality rating 
(in terms of rock mass rating) and the hydraulic radius (plan view area/perimeter) of excavations 
that produce: (1) stable spans, (2) transitional excavations in which instability may begin but 
caving is not yet occurring, and (3) caving. As the rock mass quality rating decreases, the spans 
at which collapse occurs also decrease. To apply these data to emplacement tunnels at Yucca 
Mountain, an estimate of the rock mass quality is required. The case of lithophysal rock is 
presented here because it is the weakest of the host horizon units. As described in Subsurface 
Geotechnical Parameters Report (BSC 2003 [DIRS 166660], Section 9.2.5), the estimated rock 
mass quality rating in terms of Geologic Strength Index or Rock Mass Rating (GSI or RMR) for 
the lithophysal rocks at Yucca Mountain is in the range of approximately 50 to 60. For this 
range of RMR, the hydraulic radius of a flat-roofed excavation required for caving is in the range 
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Drift Degradation Analysis 
of approximately 25 to 35 m (Figure 6-149). A transitional zone between stable excavations and 
caving for the lithophysal rock RMR range occurs for hydraulic radii of 15 to 20 m. For the 
proposed 5.5-m diameter emplacement drifts, the hydraulic radius is simply equal to the radius 
(2.75 m). Therefore, field practice indicates that the stable to transitional cavingstable state is 
characterized by a hydraulic radius for lithophysal tuff in the range of 15 to 20 m. The boundary 
between transitional stable/caving to a caving state is characterized by a hydraulic radius in the 
range of approximately 25 to 35 m. Note that the typical mining undercut has a flat roof, which 
promotes instability, while the shape of the emplacement drifts is circular, which promotes 
stability. The emplacement drift hydraulic radius is, therefore, approximately 5 to 7 times below 
what would be considered to be a transitional state between stable and caving conditions. Based 
on field experience in caving, the hydraulic radius of the emplacement drifts is well below the 
level of the hydraulic radius estimated to be in a transitional state of collapse and even further 
below the level for assurance of complete collapse. Therefore, it is not surprising that the 
existing ESF and ECRB Cross-Drift (7.62- and 5-m diameter, respectively) are stable and show 
no evidence of degradation nearly a decade after excavation, even though the ground support is 
minimal. 
100 
90 
80 
70 
60 
50 
40 
30 
20 
10 
0 
itional 
ilitiiTransZone 
Stable 
Transition 
Cavng 
Not Specif ied 
Stabe Zone 
Transon Zone 
Cavng Zone 
YMP RMR 
Range 
0 1020304050607080 
Hydraulic Radius (m) 
Source: Brown 2003 [DIRS 169527], Figure 3.1. 
NOTE: Caving potential is expressed in terms of the modified rock mass rating and hydraulic radius. Modified rock 
mass rating is equivalent to rock mass rating in case of Yucca Mountain excavations. Stable and caving 
regions are separated by a transition zone. 
Figure 6-149. Excavation Dimensions Required for Caving Gained from Field Experience in Block and 
Panel Caving Mines 
Modified Rock Mass Rating 
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Drift Degradation Analysis 
6.4.2.4.1.3 Observations of Yucca Mountain Tunnels and Excavations at Hoover Dam 
Unsupported or lightly supported tunnels (although perhaps not considered safe from a personnel 
standpoint) can stand in a stable condition for long time periods, particularly in good quality rock 
masses. For example, the ESF (7.62 m diameter) and ECRB Cross-Drift (5 m diameter) tunnels 
at the Yucca Mountain site were constructed in 1995 to 1997 and in 1998, respectively. 
Although the ESF main loop is located largely in the Tptpmn, the ECRB Cross-Drift cuts 
through and exposes all of the repository host horizon units. The tunnels are, in general, lightly 
supported with friction rock bolts and light wire mesh in the tunnel roof, with occasional friction 
bolts in the tunnel walls. There is no evidence of significant deterioration or degradation of the 
rock mass, and no significant episodes of rockfall have occurred. 
An external review panel convened to examine Yucca Mountain drift stability (Brekke et al. 
1999 [DIRS 119404]) found that excavations of the North Ramp through the upper lithophysal 
zone and the ECRB Cross-Drift through the lower lithophysal zone show that both zones have 
properties that are favorable for stability with minimum ground support. The panel also found 
that rock conditions in the lower lithophysal zone in the ECRB Cross-Drift were similar to those 
observed in the upper lithophysal zone in the North Ramp; that continuous joints were not 
apparent, and there was almost no overbreak or loosening of the slabs or blocks; and that zones 
with more frequent short fractures were present and could be described as fracture zones, but 
even in these areas, overbreak and block loosening were largely absent. Tunnel deformation 
measurements have been regularly monitored since excavation, showing stable conditions. The 
conclusion is that the tunnels in both the lithophysal and nonlithophysal rock masses are in a 
stable and self-supporting mode with no obvious deterioration in 5 to 8 years. Additionally, the 
Drift Scale Test involved heating a representative repository-scale tunnel in the nonlithophysal 
rock mass, first, to postclosure temperature distributions, followed by a thermal overdrive 
experiment to test rock strength limits. The experiment, now well into its cool-down phase, 
showed stable and predictable conditions at expected repository peak temperature conditions. 
Overdrive to approximately 200C drift-wall temperatures showed predictable, minor spalling of 
a small portion of the center of the crown of the drift (Section 7.6.5.3). Cool-down has showed 
no observable loosening or instability of the tunnel. This experiment confirmed modeling 
estimates of stable drift conditions for expected repository temperature and combined in situ and 
thermal stress conditions. 
The Hoover Dam, with abutments excavated in Tertiary pyroclastic flows, was completed by the 
Bureau of Reclamation in 1936. Along with the construction of the dam itself are a series of 
tunnels and adits (Figure 6-150) that were excavated to accommodate the various penstocks, 
valves, access ways, spillways, and river bypasses. With the exception of the visitor center 
elevator shaft (completed in the 1990s), the excavations were completed with simple drill and 
blast methods (simple meaning here that no smooth-wall blasting techniques were used). 
Some of the larger openings, generally those more than 6 m (20 ft) high, were excavated using 
heading-and-bench methods to develop the full size of the openings. Many of the tunnels and 
adits were excavated to greater than 12 m (40 ft) in diameter. While some of the penstock and 
spillway tunnels were lined with concrete, many of the adits and access ways remain unlined. 
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Drift Degradation Analysis 
NOTE: Construction adit, shown at right, is approximately 40 ft high. 
Figure 6-150. Excavation for Nevada Canyon Wall Outlet Works (Top) Showing Construction Adit in 
1933 and (Bottom) in 2004 
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Drift Degradation Analysis 
The rock at the site is the tuff of Hoover Dam, a fairly localized unit composed of andesitic to 
dacitic pyroclastic flows and breccias. At the dam, the volcanics are slightly to densely welded, 
and slightly weathered to unweathered. At the penstock adits, the rock is moderately hard to 
hard and contains abundant lithic fragments and occasional corroded pumice fragments. The 
rock is slightly to moderately fractured, with most fractures devoid of fracture filling. Many of 
the discontinuities exposed in the adits are frequently shears and small faults displaying distinct 
slickensides. Where the adits extend below the phreatic surface, occasional calcium carbonate 
precipitate is present adjacent to active or old seeps. 
The adits were excavated downstream of the power plant to allow insertion of large, steel 
penstock sections into tunnels that paralleled the canyon walls. The adits are in still in use, 
housing the sewage treatment system and other support utilities necessary to the function of the 
dam. The adits are approximately 40 ft (12 m) high by 35 ft (10.7 m) wide (Figure 6-151) 
becoming slightly taller with depth. After the drill and blast excavation, the adits were left 
unlined and unsupported, and continue to be unsupported to the present time. Rock fall in the 
adits has been limited to very occasional centimeter-size fragments, even without ground 
support. 
Additionally, there are numerous access ways throughout the lower canyon walls in and around 
the Hoover Dam power plant. These smaller tunnels, 6 to 15 ft (1.8 to 4.6 m) in diameter, allow 
access by personnel and tourists to various areas of the power plant and penstocks. Few of these 
tunnels are supported either by rock bolts or mesh. No steel supports are visible in the Hoover 
excavations. As with the adits, rock in the access ways and tunnels has been limited to rare 
centimeter-size fragments that are removed by the janitorial staff. 
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Drift Degradation Analysis 
NOTE: Irregular tunnel walls resulting from drill-and-blast excavations (top) and close-up view of the tunnel crown 
showing evidence of drill half-barrels (bottom). 
Figure 6-151. 2004 Photographs of Unsupported Construction Adit at Hoover Dam, Excavated in 1931 
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Drift Degradation Analysis 
6.4.2.4.2 Mechanics-Based Approach to Analysis of Time-Dependent Degradation of 
Repository Excavations 
6.4.2.4.2.1 Background on Time Dependent Characteristics of Brittle Rocks 
One of the most striking characteristics of brittle rocks is that at temperatures well below the 
melting point, a rock subjected to a constant load exhibits a continuous increase in strain with 
time. This time-dependent deformation is termed creep. Studies on creep indicate that the 
observed strain depends upon the applied stress, the temperature, the partial pressure of water, 
and the confining pressure (e.g., Martin 1972 [DIRS 169721]). Moreover, the same mechanism 
responsible for the strain of brittle rocks in constant strain-rate tests is also operative in creep. 
That is, cracking, both along grain boundaries and through individual grains, produces the 
observed strain (e.g., Brace et al. 1966 [DIRS 101990]). Above approximately one half to 
two-thirds of the compressive strength, the dominant mode of deformation for brittle rocks is the 
opening and growth of cracks parallel to the major principal stress direction or axial orientation 
in unconfined compression. It is typically considered that the strain rate of hard rocks in creep is 
related to the time-dependent growth of these cracks. 
Verification of the relationship between time-dependent crack growth and creep strain rate in 
brittle rock is performed through laboratory testing. Experimental results indicate that stable 
time-dependent crack growth at a constant compressive load or at a constant stress intensity 
factor occurs in quartz and glass in the presence of water vapor. Moreover, the rate of crack 
growth depends on the applied stress, the temperature, and the partial pressure of water in the 
atmosphere surrounding the crack. The relative weakening of quartz or silicate glass, reflected 
by an increase in the rate of crack growth with an increase in any of the three variables, is 
consistent with the general theory of stress corrosion in silicates proposed by Charles (1959 
[DIRS 170308]). He postulated that the velocity of a slowly propagating crack with a high 
tensile stress at the crack tip is proportional to the rate of the hydration reaction at the crack tip. 
The following equation (Martin 1972 [DIRS 169721]) quantifies the general relationship for 
environment-sensitive crack growth. 
. 
. FV
-
* s
..
RT .
.
Vm 
.
.
= 
. P
0
n 
(Eq. 6-8)
+
exp
.
. 
RT
where . is the rate of crack growth, . 0 is the initial flaw size, P is the partial pressure of water, 
. F is the activation energy for the process, T is temperature, R is the universal gas constant, V* 
is the activation volume, s is stress, . is the surface energy of the solid, Vm is the molar volume 
of the solid, . is the radius of curvature of the crack tip, and  and n are constants. 
If the partial pressure of water, the temperature, and the applied stress are constant, a constant 
crack propagation velocity will be observed. When any one of the thermodynamic variables is 
increased, the crack velocity increases. This expression has been verified with experimental 
studies (Wiederhorn 1968 [DIRS 170309]; Martin 1972 [DIRS 169721]; Scholz 1972 
[DIRS 169724]). 
The validation of Equation 6-8 is extremely important. First, it establishes a rate-dependent 
process for the propagation of cracks in quartz and silicate glass. If the same behavior is 
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Drift Degradation Analysis 
observed in rocks then it implies that time can be scaled from very short times to extremely long 
times in the absence of other competing mechanisms. Specifically, if moisture-assisted stable 
crack growth is the primary mechanism of creep in brittle rocks, measurements made at 
laboratory scales of up to 106 seconds can be extrapolated to much longer scales on the order of 
1011 to 1014 seconds. Presently there are no other independent data that suggest other competing 
mechanisms for time dependent deformation in brittle rocks at temperatures below 300C. 
Based on these results and verifications by other experimenters, there is confidence that 
Equation 6-8 accurately represents the behavior of the rate of crack growth at the crack tip for 
brittle silicate materials at temperatures below 300C. 
Next, the behavior of brittle rocks can be examined during creep and compared to the 
observations of stable, time-dependent crack growth gained from tests on quartz and glass. A 
creep test is conducted by rapid application of uniaxial or triaxial load to a rock sample to a 
given differential stress, followed by holding the load constant while monitoring the longitudinal 
and lateral strains. Typically, creep is reported in terms of three distinct phases: (1) primary or 
transient creep, (2) secondary or steady-state creep, and (3) tertiary or accelerating creep 
(Figure 6-152). 
Source: Martin et al. 1997 [DIRS 165960], Figure 4. 
NOTE: Specimen failed at tertiary creep phase. 
Figure 6-152. Example of Creep Strain Plotted as a Function of Time for a Static Fatigue Test 
Conducted on a Sample of Topopah Spring Tuff at a Constant Differential Stress of 132.8 
MPa, a Confining Pressure of 5.0 MPa, a Pore Pressure of 1 MPa, and a Temperature of 
150C. 
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Drift Degradation Analysis 
Transient creep has been reported for a variety of rock types over a wide range of temperatures 
and pressures. The strain in this region decelerates rapidly and is often reported as proportional 
to the logarithm of time. Moreover, both the lateral and the longitudinal strains exhibit this 
logarithmic time dependence. 
At low stresses, transient creep may account for the observed strain. However, at high stresses, 
secondary creep is often observed. Generally, in secondary creep, often called steady-state 
creep, the strain is proportional to time. The total strain caused by both primary and secondary 
creep is often represented by an equation of the form 
e= A + B log t + Ct (Eq. 6-9) 
where e is strain, t is time, and A, B, and C are constants. 
If secondary creep is allowed to continue, eventually the strain rate increases (tertiary creep) and 
the rock fails. The three stages of creep have been observed in granite, quartzite, and tuff 
(Martin 1972 [DIRS 169721]; Martin et al. 1997 [DIRS 165960]). A typical creep curve for a 
specimen of welded tuff from the middle nonlithophysal unit of the Topopah Spring (Tptpmn) is 
shown in Figure 6-152. The three stages of creep are clearly evident. 
Stable crack growth in quartz reported by Martin (1972 [DIRS 169721]) and Martin and Durham 
(1975 [DIRS 170301]), illustrated specific characteristics that are related to creep deformation. 
In these studies, the specimens were loaded to a fixed compressive stress and the growth of a 
crack parallel to the applied load was observed. Each specimen was tested in a controlled 
environment and the change in crack length was noted as a function of time. A typical data set 
obtained on a single specimen of quartz tested at a temperature of 241C and a partial pressure of 
water of 4.5  10-2 kPa is shown in Figure 6-153. The test specimen geometry is shown in the 
upper left portion of the graph. At a stress of 66 MPa, the change in crack length with time is 
very similar to that observed in the creep of brittle crystalline rocks. The crack exhibits an initial 
period of rapidly decelerating growth followed by a quasi-linear or secondary segment. After 
6.3  104 seconds, the stress was increased to 74 MPa. Immediately, the rate of crack growth 
increased. The same characteristics observed at the lower stress were exhibited for the 74 MPa 
segment. There was a strong transient followed by a secondary or quasi-linear crack growth 
segment. At approximately 8  104 seconds, the stress was increased to 83 MPa. The rate of 
crack growth increased dramatically; and the experiment was terminated when the crack length 
reached 3.7 mm. These data are consistent with Equation 6-8; that is, the rate of crack growth 
increased with increasing stress and nearly vanishes at low stresses. Additional experiments 
showed that increasing either the partial pressure of water surrounding the crack or the 
temperature also results in an increase in the rate of crack growth. 
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Drift Degradation Analysis 
Source: Martin 1972 [DIRS 169721]. 
NOTE: The experiment was conducted at 241C and a partial pressure of water of 4.05  10-2 kPa. 
Figure 6-153. Crack Length as a Function of Time for an Axial Crack Growth Experiment in Single 
Crystal Quartz 
The above discussion points out that creep experiments with complex, silicate rocks display the 
same basic time-dependent response as demonstrated by crack-growth studies in single crystals 
of quartz and glass. From a practical standpoint, it is advantageous to define the ultimate 
time-to-failure in terms of the stress, temperature and partial pressure of water, rather than in 
terms of crack growth. Time-to-failure is typically defined using the creep test to determine the 
static fatigue of a material. Static fatigue refers to the failure time of a rock or single crystal at 
constant stress, temperature, confining pressure, and partial pressure of water without regard to 
the strain history. Scholz (1972 [DIRS 169724]) conducted a series of static fatigue tests in 
compression on single crystal quartz. He observed that the mean time to failure, <t >, depended on 
the partial pressure of water (P ), stress (s), activation energy (.F ), and temperature (T ) 
according to: 
t = P t -aexp.
. .F - K 's.
. (Eq. 6-10) 
0 
. RT . 
where a and K ' are constants. 
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Drift Degradation Analysis 
The foregoing discussion demonstrates that: 
 The strength of brittle silicate rocks such as tuff is not a single-valued function of any 
parameter, but is a complex continuum that depends on the state of stress, the saturation 
(pore pressure), the temperature, and the time (including strain rate). 
 Studies of the basic growth of single fractures and the creep strain resulting from 
microcrack growth in complex silicate rocks demonstrate that the same basic stress 
corrosion mechanism is responsible for time-dependent crack growth and the ultimate 
time-to-failure of the material. 
 The stress corrosion mechanism gives rise to a logarithmic relationship of time-to-failure 
as a function of the state of stress, the temperature, and the pore pressure. 
 As a result of the basic understanding of the static fatigue mechanism in brittle rocks, it 
is possible to extrapolate long-term failure response from relatively short-term static 
fatigue experiments in the laboratory. 
Since the effects of time-dependent fracture development on weakening of tuff and its impact on 
drift degradation may be important in the postclosure repository environment, creep experiments 
on tuff samples have been conducted to determine its static fatigue response under appropriate 
environmental conditions. 
6.4.2.4.2.2 Static Fatigue Testing to Define Time-Dependent Behavior of Welded Tuff 
The typical way to define the time-dependent strength of rock is to establish the time required for 
failure of heated, saturated rock samples that are subjected to an applied constant axial stress. 
Creep test experiments are conducted to determine the static fatigue strength of the rock 
associated with tertiary creep rupture. These tests, typically conducted in uniaxial or triaxial 
compression, involve rapidly increasing the applied axial stress to a given percentage of the 
estimated compressive strength of the same size rock samples. The stress is then held constant 
until the sample spontaneously fails due to time-dependent rupture. A plot of the logarithm of 
the time-to-failure versus the ratio of the applied stress to the unconfined compressive strength is 
developed. The plot is typically linear, reflecting the basic mechanisms of stress corrosion as 
described above. Rock samples subjected to stress levels that are small in comparison to the 
compressive strength (i.e., below about 50 to 60 percent) result in excessively long times to 
failure and cannot be tested practically in the lab due to the long test duration. However, these 
loading conditions are not of interest for drift stability in the postclosure time frame of hundreds 
to thousands of years. The loading conditions of interest to time-dependent degradation at Yucca 
Mountain are those in which the applied stresses from in situ and thermal loading in the drift 
wall periphery are a high percentage of the rock strength (e.g., greater than approximately 60 to 
70 percent). Here, the time to failure may result in significant degradation in hundreds to 
thousands of years. In this case, relatively short-term laboratory experiments (on the order of 
days to weeks) can supply time constants capable of describing the stress corrosion process. 
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A series of triaxial static fatigue experiments were conducted on heated and saturated 
nonlithophysal cores from the Tptpmn in 1997 (Martin et al. 1997 [DIRS 169721]) and in 2004 
(DTN: SN0406L0212303.002 [DIRS 170289]). Triaxial experiments on 50.8 mm diameter 
cores with a confining pressure of 5 MPa and pore water pressure of 4.5 MPa were conducted so 
that pore water of the saturated samples would remain in a liquid state as the temperatures were 
increased over boiling (125C and 150C). The resulting effective stress (the confining pressure 
minus the pore water pressure) was approximately 0.5 MPa, or essentially a state of uniaxial 
compression. This procedure was used to ensure a conservative state in which saturated samples 
were maintained at postclosure rock temperatures. Figure 6-154 shows a typical specimen ready 
for testing. 
The results of the testing on nonlithophysal cores of Tptpmn, as well as those from similar 
testing of Lac du Bonnet granite performed for the Canadian high-level radioactive waste 
program (Schmidtke and Lajtai 1985 [DIRS 164774]; Lau et al. 2000 [DIRS 164769]) are given 
in Figure 6-155. Granite results are included as a means of comparing the effects of rock type 
and for demonstrating the similarity in the general nature of the time-to-failure data for different 
rock types. Scatter in the data is due to sample inhomogeneity, as well as the fact that the 
driving stress ratio (the horizontal axis) uses an estimated value for the unconfined compressive 
strength (adjusted for sample porosity) for normalizing the applied stress level. 
Since there is significant variability in the unconfined compressive strength of each sample, there 
will be a scatter in the resulting plot of time-to-failure versus driving stress ratio. As seen in 
Figure 6-155, the welded tuff has a significantly slower time static fatigue failure than granite, as 
evidenced by the steeper slope of the linear fit to the data. This slower time-to-failure is 
presumably a result of the relatively homogeneous, fine-grained, high silica content nature of the 
tuff, as opposed to the heterogeneous nature of the grain structure of granite. 
Figure 6-154. Triaxial Static Fatigue Experimental Setup and Posttest Sample for Heated, Saturated, 
50.8 mm Diameter Samples of Tptpmn 
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Source: Schmidtke and Lajtai 1985 [DIRS 164774] (Lac du Bonnet data); Martin et al. 1997 [DIRS 165960] (tuff 
1997 data); DTN: SN0406L0212303.002 [DIRS 170289] (tuff 2004 data). 
NOTE: Tests of Lac du Bonnet granite were conducted at 25C. The driving stress ratio is defined as the ratio of 
applied constant test stress to the estimated unconfined compressive strength. 1997 tuff tests were 
conducted at 150C, 2004 tuff tests were conducted at 125C. LdB = Lac du Bonnet. Linear fits to 1997 
Lac du Bonnet only and 1997 and 2004 tuff tests are shown. Samples that did not fail are also shown but 
not used in developing linear fits to data. 
Figure 6-155. Static-Fatigue Data for Unconfined and Triaxial Compression of Heated, Saturated 
Welded Tuff and Lac du Bonnet Granite 
Linear fits to the unconfined compression data of Lac du Bonnet granite and to the tuff 1997 data 
only and to the welded tuff data (including both 1997 and 2004 data) are given. The fits to both 
sets of welded tuff data are given because the analysis of drift degradation presented in the 
following section was conducted based on fits to only the 1997 data. After these analyses were 
completed, the additional 2004 data were collected. The linear fits to the data sets show the 
general consistency of the overall slope of the fits, although there is considerably more scatter in 
the 2004 test results. Due to data uncertainty, a lower bound for the slope of the time-to-failure 
curve based on the Lac du Bonnet data, was also used in numerical modeling estimates. The 
static fatigue testing was performed on saturated tuff cores at elevated temperature, ensuring that 
the impact of water on time-dependent yielding was accounted for in the estimation of 
time-dependent effects on drift stability. 
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6.4.2.4.2.3 Development of a Mechanical Model for Simulating Time-Dependency in 
Nonlithophysal and Lithophysal Rock 
After an estimate of the relationship of stress level to time-to-failure for nonlithophysal tuff has 
been defined through testing, it is necessary to establish the impact of lithophysal porosity on the 
time dependence and to generalize the results into a time-dependent strength model that can be 
used to estimate drift stability. The methodology for development of a mechanical model for 
representing time-dependent degradation effects in welded tuff is described below. 
The particle flow code PFC2D (BSC 2002 [DIRS 161950]) and PFC3D (BSC 2002 
[DIRS 160612]) discontinuum numerical modeling tools were used for understanding the impact 
of lithophysal porosity on time-to-failure as a function of applied stress. A modification to the 
basic particle flow code program was developed for simulation of time-dependent, stress 
corrosion cracking of rock. This model, termed the particle flow code stress corrosion model, 
was used for simulating time-dependent tunnel fracturing of Lac du Bonnet granite for the 
Canadian waste disposal research program. In this model, time-dependent intergranular bond 
fracture strength was developed based on the general concept of a stress corrosion mechanism. 
The long-term behavior is controlled by three particle flow code stress corrosion model 
parameters, 1, 2, and sa. The terms 1 and 2 (rate constants) and sa (microactivation stress) 
do not affect short-term material properties. These material parameters are derived from 
calibration against the time-to-failure data supplied by static fatigue testing (e.g., Figure 6-155). 
The particle flow code stress corrosion model has been extensively documented and calibrated 
against static fatigue testing of Lac du Bonnet granite and validated against time-dependent 
tunnel breakout observed at the Underground Research Laboratory in Manitoba, Canada 
(Potyondy and Cundall 2001 [DIRS 156895]). Details of the stress corrosion model in particle 
flow code and its calibration are presented in Appendix S. 
Prior to representing time dependency, it was necessary to demonstrate that the particle flow 
code model can reproduce the basic, non-time-dependent mechanical behavior of nonlithophysal 
and lithophysal tuff. The calibration of the model against laboratory compression data from 
small cores of nonlithophysal tuff and from large cores of lithophysal tuff from the Tptpul and 
Tptpll was described in Section 7.5. The same basic particle flow code model, incorporating a 
time-dependent particle bonding strength, was then calibrated to reproduce the time-to-failure 
dependent response of nonlithophysal tuff determined from the static fatigue testing. The 
calibration of the model is carried out by conducting simulated creep tests on nonlithophysal 
samples in exactly the same way they are performed in the laboratory. Figure 6-156 presents a 
typical simulated creep test in which axial load is applied to the particle flow code sample and 
held constant at 80 percent of its unconfined compressive strength. Tensile fractures (cracks) 
develop spontaneously in the model as a function of time based on the time-dependent bond 
strength of the constituent grains. The plot shows the development of a network of tensile stress 
corrosion cracks that accumulate and propagate within the sample until a macroscopic shear 
failure mechanism develops with resulting brittle rupture during the tertiary creep stage. The 
simulated creep test shows the three stages of creep: transient, secondary and tertiary, and 
reproduces the typical response of creep experiments in tuff (e.g., Figure 6-152). 
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NOTE: Numerical simulation of creep test run by holding applied axial stress constant at 0.8 times the unconfined 
compressive strength. The damage, in terms of new crack growth, is displayed at various times along the 
creep curve. Brittle failure of the sample occurs when sufficient time-dependent crack growth results in 
failure mechanism. 
Figure 6-156. Example of Simulated Creep Curve and Brittle Rupture Calibration for Nonlithophysal 
Tuff, (in This Case, Providing a Lower-Bound Estimate by Using Lac du Bonnet Granite 
Time-to-Failure Curve) Static-Fatigue Test at Driving-Stress Ratio (Ratio of Applied 
Stress to Unconfined Compression Strength) of 0.8 
A large number of particle flow code simulations of static fatigue tests of nonlithophysal rock 
was run at a wide range of driving stress ratios, and two particle flow code stress corrosion 
parameters were calibrated, so that the model was able to reproduce the basic time-to-failure fits 
shown in Figure 6-155 for tuff and granite. The third stress corrosion parameter, the activation 
stress, was conservatively considered to be 0. The consequence of this consideration is that the 
long-term strength of the particle flow code synthetic material is 0. It is well known that real 
rocks have long-term (true) strength that is on the order of 50 percent of the short-term strength. 
In other words, if the load is less than long-term strength, the rock will never fail, irrespective of 
duration of the load. The model was then used to investigate the impact of lithophysal porosity 
on the rate of time dependence. It is considered that time-dependent behavior of the matrix is the 
same for both lithophysal and nonlithophysal rocks. A series of simulated creep experiments for 
lithophysal porosities of 11 percent and 20 percent were conducted, resulting in the generation of 
a set of time-to-failure versus driving stress ratio plots for various levels of lithophysal porosity 
(Figure 6-157). 
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NOTE: The time dependency has approximately the same slope for the void porosities for the straight-line fit. 
Lithophysae are simulated as circles with a diameter of 90 mm. mS50 is the designation for the material 
properties of the matrix derived from nonlithophysal calibrations. 
Figure 6-157. Example Particle Flow Code Specimens with Void Porosities of 0.107 and 0.204 (a) and 
Effect of Void Porosity on Time-to-Failure Response for Lithophysal Tuff Material, in This 
Case, Providing a Lower Bound Estimate by Using Lac du Bonnet Granite 
Time-to-Failure Curve (0% to 20% Void Porosity, nv) (b) 
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6.4.2.4.2.4 Drift-Scale Model for Simulation of Time-Degradation of Emplacement 
Drifts 
The particle flow code model for time dependency of lithophysal rock, shown in Figure 6-157, is 
computationally very large and is difficult to apply on the scale of a complete emplacement drift. 
To overcome these computational limitations, a drift-scale model using the UDEC discontinuum 
program was developed for investigation of non-time-dependent drift degradation analyses in 
lithophysal rocks as presented in the previous sections. The same model is used for 
time-dependent drift-scale analyses with the exception that the strength properties of the model 
are adjusted as a function of time. The relationships for time-to-failure as a function of 
lithophysal porosity developed from the laboratory testing and particle flow code extrapolations 
are used to define time-dependent strength properties for the drift-scale UDEC model. The 
approach to definition of time-dependent effects on strength in UDEC is simplistic in that it 
relates rock mass damage resulting from stress corrosion cracking directly to a loss of cohesion 
and tensile strength of the rock mass. The degree of strength loss was determined by 
(1) conducting a series of particle flow code numerical creep tests at different values of driving 
stress ratio and (2) interrupting the particle flow code creep test simulations at various times 
during a simulated test and conducting numerical compression and tensile strength tests on the 
damaged sample. For example, Figure 6-156 shows four snapshots of the crack-damaged state 
of a simulated rock sample at various times along the creep curve. The strength properties of 
these damaged states were determined, and the resulting cohesion and tensile strength defined as 
a function of time for a given driving stress ratio. The strength loss was generalized into a 
damage coefficient that varies from 0 to 1 (0 indicates no strength loss, while 1 is complete 
strength loss). The cohesion and tensile strength of the rock is multiplied by this coefficient to 
derive the strength properties of the rock mass as a function of time. Essentially, this approach 
relates the reduction in strength properties (shear and tensile strength) to the increase in fracture 
density or damage to the rock mass. Figure 6-158a shows the form of the damage coefficient as 
a function of time for various driving stress ratios as derived from the particle flow code stress 
corrosion model for a nonlithophysal simulation. As seen in this plot, damage occurs in a brittle 
fashion with abrupt failure near the peak strength. The amount of damage accumulated prior to 
the abrupt failure (as shown by the damage coefficient) is less than 10 percent for high driving 
stress ratios (e.g., >0.6), whereas damage accumulation is significantly larger for low driving 
stress ratios (e.g., <0.6). A simplified representation of the damage coefficient evolution in 
terms of time is shown in Figure 6-158b. 
The UDEC drift-scale model is composed of many small elastic blocks that are bonded across 
incipient, ubiquitous fractures with shear and tensile strength components. While the 
non-time-dependent UDEC drift-scale model considers constant strength properties for the 
incipient fractures, the time-dependent damage model is transient in nature and assigns cohesion 
and tensile strength based on the damage coefficient as a function of time after excavation 
(i.e., Figure 6-158b). 
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NOTE: Each curve has a vertical asymptote at a time-to-failure for a given driving-stress ratio, which is provided by 
the best fit to tuff (1997 data) given in Figure S-27 (Appendix S). Plot (a) was developed by using the Lac 
du Bonnet granite time-to-failure curve. 
Figure 6-158. Time Evolution of Damage Due to Strength Degradation Coefficient for Nonlithophysal 
Tuff Material During Static-Fatigue Tests at Driving-Stress Ratios Ranging from 0.2 to 0.8 
(a) and Idealized Damage Coefficient as a Function of Time for a Range of Applied 
Stress Conditions (b) 
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6.4.2.4.2.5 Time-Dependent Drift Degradation Analyses for In Situ Stress Only 
A series of parametric drift degradation simulations were conducted for the range of potential 
lithophysal rock mass strength categories in the Tptpll. Time-dependent drift degradation 
analyses for the postclosure time frame were conducted for each of these strength categories. 
When performing a time-dependent drift degradation analysis, the cohesion and tensile strength 
at each incipient fracture location is adjusted as a function of time, with yield considered to occur 
in a brittle fashion when the time-to-failure is reached (Figure 6-158). Thus, as the drift is 
excavated and as transient thermal stresses develop, time-dependent yield and fracture can occur 
around the excavation, resulting in redistribution of stress and possible propagation of drift 
breakout, collapse, and rockfall. 
The model was run by first excavating the emplacement drift under in situ stresses only, 
followed by application of the transient rock mass temperature conditions. The time-dependent 
fracture state and drift stability was examined at 1, 5, 10, 100, 1,000, and 10,000 years during the 
heating and cooling phases of the postclosure period. Additional analyses were conducted to 
examine the effect of seismic loading with the application of the 10-4 annual exceedance level 
ground motion time histories (approx. 0.5 m/s peak ground velocity). This ground motion was 
applied to the time-degraded model at the time of peak thermal stress (approximately 30 years 
after closure), at 1,000 years, and at 10,000 years. The 10-4 event was chosen to determine if the 
added seismic stress and shaking would be sufficient to dislodge time-degraded, fractured, and 
loosened rock that may still be in place on tunnel walls. 
The resulting time-dependent drift degradation estimates for mechanical property categories 
1, 2, 3, and 5 for loading by in situ stresses only for 1 to 10,000 years are presented in 
Figures S-37 to S-40 in Appendix S. The results for the lowest rock qualities (categories 1 
and 2) show significant deterioration of the drifts would be expected soon after excavation as a 
result of in situ stress loading only. Observations in the ECRB Cross-Drift and the ESF, which 
have been excavated for 6 or more years, show no progressive raveling or overbreak 
(e.g., Brekke et al. 1999 [DIRS 119404], p. 2-5). This observation holds even in those areas of 
high lithophysal porosity found near the top of the Tptpll. Categories 3 and 5 show little 
time-dependent effect from in situ stressing only. These results point out that the best estimate 
of tuff time dependence, coupled with the considerations of brittle rock failure and constant, 
homogeneous properties within a given model cross section produces conservative damage 
estimates. Category 3 is considered to represent an average condition of lithophysal porosity for 
the Tptpll and shows little overbreak with time. Analyses presented in Section 6.4.2.2.3 examine 
the impact of spatially variable rock properties within a given model section based on the 
mapped variability of lithophysal porosity in the ECRB Cross-Drift. The spatially variable 
model has a range of rock categories distributed throughout the cross section, and results of 
analyses show time-dependent drift degradation response similar to that shown for 
category 3 mechanical properties. An important conclusion from these initial in-situ-stress-only 
analyses is that best estimate time-dependent fracture growth within the tuff matrix is not 
expected to lead to collapse modes and significant drift degradation. 
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6.4.2.4.2.6 Time-Dependent Drift Degradation Analyses for Combined Thermal and 
Time-Dependent Effects 
Throughout the regulatory period of 10,000 years, the emplacement drifts and surrounding rock 
mass will be subject to a heating cycle. Time-dependent strength degradation will happen 
concurrently with transient, thermally induced stress changes. Increased stresses around the 
excavation will accelerate the process of strength degradation. The results of numerical 
simulation of drift degradation as a result of these two processes are shown in Figures S-42 to 
S-44 in Appendix S. Time-dependent strength degradation is assessed using the tuff best-fit 
static-fatigue line. As expected, most rockfall occurs in category 2 rock mass, as shown in 
Figure S-42. Initially, most of the rockfall comes from the walls, which are loaded almost to a 
yielding state for this rock mass category under in situ stress conditions only. Strength 
degradation combined with a temperature increase, which at early times increases the hoop stress 
in the walls (not only in the roof), results in some rockfall from the wall at 5 and 10 years after 
emplacement of the waste. The large increase in the temperature and, consequently, in the 
stresses after the forced ventilation stops causes additional rockfall (at 80 years). At this stage, 
stress increase is predominantly in the roof. Therefore, some rockfall comes from the roof. It is 
counterintuitive that more rockfall is predicted in category 5 (Figure S-44) than in 
category 3 (Figure S-43). However, a large stiffness of category 5 lithophysal rock mass causes 
a large (larger than in category 3) increase in the hoop stress and yielding in the roof, even 
considering the short-term yield strength of the rock mass. 
It should be noted that static-fatigue curves are temperature dependent. This dependence is not 
explicitly included in the analysis. However, the tuff data are obtained from tests conducted at 
150C, which is larger than the maximum temperature of the rock mass anticipated throughout 
the repository for postclosure. Consequently, the results obtained in this analysis, although for 
isothermal static-fatigue curves, are conservative. 
6.4.2.4.2.7 Time-Dependent Drift Degradation Analyses for Combined Seismic, 
Thermal and Time-Dependent Effects 
The 10-4 ground motion was applied to category 2 and 5 rock mechanical property cases at two 
time periods: (1) at the time peak thermal stress state (nominally at 80 years after emplacement, 
or 30 years after cessation of 50 years of forced ventilation) and (2) at 10,000 years at the 
completion of the postclosure heating and cooling cycle. Figures 6-159 and 6-162 show the 
resulting predicted degraded drift states for these cases. Essentially, the application of the 
10-4 ground motion (peak ground velocity of approximately 0.5 m/s) dislodges any fractured and 
loosened rock created by the thermal stress and time dependency. As seen in these figures, the 
impact of time dependency of strength properties is to widen the diameter of the emplacement 
drifts in the lower quality (category 2) rock due to progressive shear failure at the sidewalls. In 
the highest quality (category 5) rock, additional progressive yield of the roof is evident. Roof 
yield in higher quality rock is due to the higher modulus of the rock mass and, thus, higher 
roof-parallel thermally induced stresses during the heating cycle. This is similar to the roof 
crown spalling effect observed in the Drift Scale Test. 
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(a) before earthquake (b) after earthquake 
NOTE: Displacement magnitudes are in meters. 
Figure 6-159. Effect of 10-4 Ground Motion After 80 Years of Heating in Category 2: Blocks Colored by 
Contours of Displacement Magnitude 
(a) before earthquake (b) after earthquake 
Figure 6-160. Effect of 10-4 Ground Motion After 80 Years of Heating in Category 5: Blocks Colored by 
Contours of Displacement Magnitude 
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(a) before earthquake (b) after earthquake 
Figure 6-161. Effect of 10-4 Ground Motion After 10,000 Years of Heating in Category 2: Blocks 
Colored by Contours of Displacement Magnitude 
(a) before earthquake (b) after earthquake 
Figure 6-162. Effect of 10-4 Ground Motion After 10,000 Years of Heating in Category 5: Blocks 
Colored by Contours of Displacement Magnitude 
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6.4.2.4.3 Summary of Time-Dependent Consideration 
6.4.2.4.3.1 Summary of Empirical Observations 
The safety-related empirical correlations for maximum unsupported span and stand-up time of 
excavations developed for the tunneling industry are not relevant for prediction of long-term 
response of repository excavations. The span of the emplacement drifts is significantly less than 
that required to initiate collapse, as indicated by practice in the mining industry. The excavations 
will be developed using nonblasting methods (i.e., using a tunnel boring machine) and with a 
circular shape that minimizes overbreak and promotes stability. Observations of existing tunnels 
in the repository host horizon at the Yucca Mountain site as well as in similar rock at Hoover 
Dam show stable conditions with minimal or no ground support. 
6.4.2.4.3.2 Effect of Drift Collapse on the In-Drift Environment 
Estimates of the coupled thermal-hydrologic behavior of the rock mass in the near vicinity of the 
drifts is examined in Multiscale Thermohydrologic Model (BSC 2004 [DIRS 169565]). 
Numerical parameter analyses of the impact of waste heating on fluid pressures on fractures and 
infiltration into the emplacement drifts were conducted using the multiscale thermal-hydrologic 
model. For the range of hydrologic properties of the four host-rock units, the fracture 
permeability is sufficiently large and fractures are sufficiently well connected to allow 
gravity-driven drainage of water to occur in an unrestricted fashion. Thus, percolation flux, not 
fracture permeability, is the rate-limiting quantity governing the magnitude of gravity-driven 
liquid-phase flow to the boilingdryout zone. Additionally, the analyses show that potential 
pressure buildup along fractures due to vapor pressure from boiling of water is also negligible 
due to the free-draining nature of the fractured rock mass. From a mechanical stability 
standpoint, this means that fluid pressure on fractures during the drying and rewetting phases of 
the postclosure period has a negligible effect on drift stability. These predictions are borne out 
by the Drift Scale Test in which no mechanical drift instabilities occurred for thermal conditions 
representative of repository postclosure conditions. 
A parameter study was conducted to examine the impact of drift collapse on in-drift 
thermal-hydrologic parameters (BSC 2004 [DIRS 169565]). The multiscale thermal-hydrologic 
model was used to examine the effect of a rubble-filled drift on waste package and invert 
temperature and relative humidity at the waste package and invert. The drift was considered to 
collapse (instantaneously) to twice the initial diameter (i.e., 11 m collapsed diameter) and is 
filled with rubble with a bulking factor of 0.231. The thermal conductivity of the rubble (Kth) is 
defined as the intact rock thermal conductivity of the Tptpll multiplied by the factor 
(1/(1 + bulking factor)). Two thermal conductivity values (a high case calculated as defined 
above for a bulking factor of 0.231, and a low case, which is taken to be one-half the high case 
value) of the dry and wet rubble thermal conductivity were used in the analyses, as shown in 
Table 6-46. 
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Table 6-46. Thermal Conductivity of Rubble 
Property 
Intact Host-Rock 
Property Value Host-Rock Rubble Property Value 
Basis for Rubble Property 
Value 
Bulk dry thermal 
conductivity 
1.28 W/mK 1 W/mK (High-Kth case)a 
0.5 W/mK (Low-Kth case) 
Intact Value  1/(1 + BF) 
(High-Kth rubble value)/2 
Bulk wet thermal 
conductivity 
1.89 W/mK 1.515 W/mK (High-Kth case)b 
0.7575 W/mK (Low-Kth case) 
Intact Value  1/(1 + BF) 
(High-Kth rubble value)/2 
Source: BSC 2004 [DIRS 169565], Table 6.2-3. 
a 
This value is rounded down slightly. 
b Value is close to, but slightly less than, the value obtained from the Intact Value x 1/(1 + BF), in order to be 
consistent with the slight reduction made to the dry Kth value, which was rounded down. 
Figure 6-163 shows the in-drift thermal-hydrologic parameters as functions of time from 
repository closure for the case of the hottest waste package, which is the 21-PWR Absorber Plate 
waste package. These plots show three cases: (1) an open, noncollapsed drift, (2) a collapsed, 
rubble-filled drift with high Kth for the rubble, and (3) a collapsed, rubble-filled drift with low 
Kth. The temperature (or any of the other environmental parameters plotted) will follow the 
intact drift curve until the time of collapse. At that point, the temperature (or other parameters) 
will translate vertically to one of the other curves, depending on the thermal conductivity of the 
rubble. 
Examination of the waste package temperature curve (Figure 6-163a) shows that significant 
impact to peak waste package temperature results only if drift collapse occurs within the first 
100 to 200 years after closure. After that time, the waste package temperature will always be 
below the peak temperature for the intact drift case, which occurs within about 20 to 30 years 
after closure. The total time at which the waste package surface remains above boiling for the 
hottest waste package case is approximately 1,000 years for the intact drift, 1,500 years for the 
high Kth case, and 2,000 years for the low Kth case. The relative humidity at the waste package 
decreases significantly for collapsed cases. 
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Source: BSC 2004 [DIRS 169565], Figure 6.3-56. 
NOTE: The cases are: (1) intact-drift (nominal) case, (2) low-probability-seismic collapsed drift with high-Kth host-
rock rubble, and (3) low-probability-seismic collapsed drift with low-Kth rubble. The plotted variables are (a) 
waste package temperature, (b) invert temperature, (c) waste package relative humidity, (d) invert liquid-
phase saturation, and (e) matrix liquid-phase saturation of the rubble surrounding the drip shield. 
Figure 6-163. Thermal-Hydrologic Variables for the Hottest Waste Package (21-PWR Absorber Plate 
Waste Package) at the P2WR5C10 Location in the Tptpll (tsw35) Unit for the Mean 
Infiltration Flux Case 
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6.4.2.5 Quasi-Static Drip Shield Loading from Rockfall 
6.4.2.5.1 Introduction 
Two types of drip shield loading cases are examined: 
 Dynamic impact loading due to rockfall resulting from the seismic event or simple 
gravity fall 
 Quasi-static loading of the drip shield once rockfall has come to rest and the weight of 
the rock lies on the crown and sides of the drip shield. 
Loading in the dynamic case is discussed in Section 6.4.2.2 for the case of lithophysal rock, and 
in Section 6.3.1.2 for nonlithophysal rock. Since the rock block size estimated in the 
nonlithophysal rock is substantially larger than that projected for the lithophysal units, it is 
considered that the estimates of impact energy from those calculations will provide an upper 
bound to the dynamic loading in lithophysal rocks. In lithophysal rocks, a potentially more 
important drip shield loading mechanism is from quasi-static load developed from the 
accumulated weight of rubble on the drip shield. Although the discussion here centers on the 
lithophysal units, the rock blocks resulting from failure in nonlithophysal rocks are expected to 
result in similar ultimate dead weight loading. 
As the lithophysal rock mass fails, pre-existing and new fractures will break, forming block sizes 
of relatively small volume (estimated to be on the order of cm on a side). The falling rock blocks 
will come to rest on the invert of the tunnel and the drip shield. Because the fallen blocks do not 
perfectly fit together as they did in the in situ rock mass, there will be an overall increase in 
volume (termed bulking). Eventually, if the failure process continues, the tunnel will 
completely fill with bulked rock and will choke off further failure because the backpressure 
provided by the rubble will stabilize further yield. 
To determine the ultimate load on the drip shield, it is necessary to estimate the amount of 
bulking that will take place, and the shape of the resulting failed excavation profile. These two 
factors define the height and density of the rock load that lies on the drip shield. The vertical 
weight of the accumulated rubble will rest on the drip shield roof, with load transferred to the 
invert via its vertical supports. Lateral loading, developed from the vertical weight of the rubble, 
as well as from passive loading in response to drip shield deformation, will also act on the 
sidewalls of the drip shield structure. The most conservative consideration of loading is that rock 
rubble acts as a fluid with the density of the bulked rock, and that the overlying height simply 
rests downward on the drip shield. The rubble is, in fact, a coarse, frictional and dilatant material 
that has shear strength, and is able to carry load itself. Therefore, realistic estimates of load need 
to account for the interaction of the rubble and the deformability of the drip shield itself. As the 
drip shield deforms during loading, an equilibrium state will be reached in which the rubble itself 
and the drip shield will share in load bearing. The load carried by the rubble and transmitted to 
the solid rock invert of the tunnel is termed arching. Measurements of strain in cut-and-cover 
tunnels with thin-conduit arched liners have verified the significant effect of arching and the 
conservatism inherent in assumptions of full-column height, dead weight loading (e.g., Lefebvre 
et. al. 1976 [DIRS 168919]; Byrne et. al. 1990 [DIRS 168921]). 
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Drift Degradation Analysis 
In the following discussion the bulking of rock is discussed and a review of analytical and 
numerical methods for estimating the drip shield loading are described and compared. The 
preferred methodology for estimating the drip shield load is to use the same UDEC discontinuum 
numerical modeling method used previously to simulate the process of rock mass failure, rubble 
bulking, and interaction of the rubble and the deformable drip shield. In this fashion, the process 
is modeled naturally and assumptions regarding ultimate failed height and shape of the 
excavation are unnecessary, as they are when using analytical approaches. The purpose of this 
section is to provide estimates of the rock rubble loading to the drip shield. Calculations of the 
structural response of the drip shield to this loading is addressed in Structural Stability of a Drip 
Shield Under Quasi-Static Pressure. 
6.4.2.5.2 Bulking of the Rubble 
When the rock mass above underground openings collapses, it increases volume (i.e., it bulks). 
During the collapse, either sudden or gradual, rock mass disintegrates in a number of pieces 
(blocks), which fall separately rotating along the way. When blocks equilibrate after caving, 
they do not fit together, resulting in increased porosity and overall volume. Rock mass of 
volume V in the in situ conditions has volume VB after caving, where: 
VB = (1 + B)V (Eq. 6-11) 
where B is the bulking factor. 
Amount of bulking (i.e., the bulking factor, B) depends on, among other things, the lithology, 
pre-existing internal structure (jointing, bedding), and the mechanism of collapse. For example, 
density of crushed limestone is in the range between 1360 kg/m3 and 1440 kg/m3, while density 
of the crushed dolomite is in the range between 1280 kg/m3 and 1600 kg/m3 (Fruchtbaum 1988 
[DIRS 161774], Section 14). Considering that the specific gravity of limestones and dolomites is 
approximately 2.6 (Bauer et al. 1991 [DIRS 161775], Tables 10 and 11), and using an in situ 
porosity of 20 percent (Goodman 1980 [DIRS 101966], Section 2.3), the in situ density of 
limestones and dolomites is approximately 2200 kg/m3. Consequently, bulking of these rocks 
from in situ state to a crushed state is between 37.5 and 72 percent. Duncan et al. (1980 
[DIRS 161776], Table 5) reported that porosity of the rock fill for dams is between 23 and 
36 percent. The rock fill used for dams is crushed to satisfy certain size requirements and is 
compacted during construction, which leads to reduction of its porosity. It appears from this 
discussion that bulking factor for the caved rock can be conservatively selected to be in the range 
between 0.2 and 0.4. 
Caving of the underground excavations is a self-limiting process in many situations. At a certain 
stage of caving, due to bulking, the volume of the caved rock completely fills the volume of the 
original excavation and the volume occupied by the collapsed rock before onset of collapse. 
When the cave is completely filled, the broken rock provides the backpressure, which prevents 
further collapse of the rock mass. 
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Drift Degradation Analysis 
6.4.2.5.3 Estimation of Collapse Dimensions and Drift Profile 
Analytical Models of Collapse HeightAnalytical methods consider that the cave above the 
emplacement drift grows until it becomes filled with the broken rock. The extent of the caved 
rock is calculated as a function of the bulking factor, B, considering that the cave stabilizes only 
when it is completely filled with the broken rock. In addition to the bulking factor, the shape of 
the cave must also be considered. In these analyses, neither the in situ stress conditions, nor the 
rock mass mechanical properties enter into the solutionthe results are governed simply by the 
modeling considerations and kinematic solutions. Two extreme conditions illustrated in 
Figures 6-164 and 6-165 and were considered. 
Figure 6-164. Piping Type of Caving Mechanism 
Figure 6-165. Terzaghi Type of Caving Mechanism 
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Drift Degradation Analysis 
The piping mode of roof collapse (shown in Figure 6-164) is typical for conditions when the 
rock mass is bedded and there is a relatively large ratio of the span of the excavation to its depth. 
This type of roof collapse is typical for coal mines (with bedded sediments as overburden) using 
the longwall mining method, and almost always occurs suddenly. Roof piping collapse is highly 
unlikely as a potential mode of drift collapse at the Yucca Mountain site for the following 
reasons: 
 None of the rock mass units are layered 
 Drifts are deep below the ground surface (i.e., the depth is >> the diameter of the 
tunnels) 
 Drift collapse due to strength decay will evolve gradually over a long period of time, 
rather than form as a sudden mechanism. 
The piping mechanism is considered here as an unlikely and conservative extreme condition and 
is a mechanism that results in the largest vertical extent of the cave, H. 
The other extreme condition of the rock mass collapse around the underground opening (shown 
in Figure 6-165) corresponds to the limit equilibrium conditions around a shallow tunnel, which 
Terzaghi (1943 [DIRS 162180]) used as a basis for calculation of the load on tunnel supports. 
Slip lines, related to plastic yield in the rock, extend from the drift walls at an angle of 
45 degreesf /2 from the vertical direction, where f is the friction angle. 
The cave height, H, is calculated for both of these cases as a function of the bulking factor, B. 
The vertical pressure of the collapsed rock exerted on the drip shield is calculated considering 
that the rock filling the cave acts on the drip shield as a dead weight. Expressions for the height 
of the cave are shown in Equations 6-12 and 6-13 for the piping and Terzaghi failure 
mechanisms, respectively, which have been derived based on the consideration of the geometries 
shown in Figures 6-164 and 6-165: 
H 1 .p bh 
= dd -.
. 1-
p.. 
(Eq. 6-12) 
4 ..
..
2R 2 .
. 2B 
- 
2BR 2 . 
p bhbW V
+
dd - s
h + 
R2H =B 
- 
BR22R2 
(Eq. 6-13) 
2R 2 W 
R 
where 
b .p f. 
= cos 2 . -.
R . 42 . 
h.p f. 
= 1 + sin. -. (Eq. 6-14) 
R . 42 . 
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Drift Degradation Analysis 
W . .pf. . .pf.. .pf.. 
= cos 2 . - .+. 1 + sin. -.. tan. -..
.
R .. 42 .. . 42 .. . 42 .. 
3pf .pf. .pf.
V
s = -+ cos 2 . -. sin. -. 
R 2 42 . 42 .. 42 . 
The predictions of the ultimate cave height are shown in Figure 6-166 for the range of bulking 
factors between 0.2 and 0.4. As expected, the cave height is larger in the case of the piping 
mechanism than in the case of the Terzaghi failure mechanism. The cave height varies (for the 
two cases considered and for the bulking factor in the range between 0.2 and 0.4) between 
approximately 1 and 2.5 drift diameters. 
The vertical pressure of the broken rock on the drip shield is calculated from the following 
equation, also derived based on the consideration of the geometries shown in Figures 6-164 
and 6-165: 
p =( H + R - t ). g (Eq. 6-15) 
1+B 
where t is the height of the upper surface of the drip shield above the drift centerline. Calculated 
vertical pressure on the drip shield as a function of the bulking factor is shown in Figure 6-167. 
Figure 6-166. Cave Height as a Function of Bulking Factor: Analytical Solution 
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Drift Degradation Analysis 
Figure 6-167. Vertical Load on the Drip Shield as a Function of Bulking Factor: Analytical Solutions 
Numerical Continuum ApproachThe analytical methods described previously in this section 
require an estimation of both the bulking factor and the ultimate shape of the collapsed zone that 
forms. A continuum-based numerical assessment of caving provides the next level of 
sophistication of analysis beyond analytical methods in that they take into account the rock mass 
strength properties and stress state while automatically estimating the ultimate cave shape. The 
bulking factor and friction angle of the caved rock must still be considered in this analysis, 
although the potential effect of stress arching within the broken rock is accounted for in 
determination of the ultimate load of the broken rock resting on the drip shield. A simplistic 
methodology was used in implementing caving into the numerical model. A model of the drift in 
a Mohr-Coulomb rock mass was developed using the FLAC continuum numerical code. 
Roller boundary conditions were used on the vertical and the bottom model boundaries. A 
stress boundary condition was applied on the top model boundary. The model uses symmetry 
conditions along the vertical plane through the drift center. The model width was set equal to 10 
drift radii. The total model height is either 16 or 25 drift radii, depending on vertical extent of 
the zone of the caved rock mass. The model bottom boundary is 4.8 radii below the drift center. 
The estimated strength of the lithophysal rock mass was used initially for solution of the 
equilibrium state under in situ stress conditions (strength properties are from Table E-10, 
Category 1, with a friction angle of 40 degrees). After initial equilibrium, the cohesion and 
tensile strength of the rock mass were reduced gradually, in steps, to induce collapse and 
formation of the caved zone. In this case, the bulking factor is estimated, but the model is 
allowed to achieve the cave shape and dimension dictated by the rock mass properties and stress 
conditions. At each stage of strength reduction, the model was run until either equilibrium was 
achieved, or there was clear indication that equilibrium could not be achieved (i.e., the rock mass 
around the drift was collapsing as evidenced by continued deformation). 
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Drift Degradation Analysis 
The onset of collapse was detected by monitoring the deformations of the excavation (an 
example is shown in Figure 6-168). When collapse is detected, the model simulation is 
interrupted, and the cave height calculated based on the estimated bulking factor and the volume 
of the rock mass within the destabilized region. The accumulation of rubble is represented by 
filling the previously empty drift and the caved region with elements with the estimated 
properties of caved rock. The properties of the caved rock were selected to have no cohesion or 
tensile strength, and its density accounting for the bulking factor. The simulation is then 
continued, allowing excavation collapse to progress. Equilibrium will eventually be achieved 
when the caved rock elements provide a back-pressure to the excavation surface sufficient to 
prevent further yielding. The ultimate vertical pressures induced by the caved rock can be 
extracted from the model at the drip shield location. As was the case with the analytical 
solutions, the numerical model can be used to examine loads from two limiting mechanisms: 
 A piping mechanism (shown in Figure 6-169, where the caved region is assigned zero 
cohesion), in which the cave width was limited to the drift width 
 A Terzaghi mechanism (shown in Figure 6-170), in which cave width coincides with the 
width of the destabilized region of the rock mass. 
Figure 6-168. Failure Mechanism of a Deep Tunnel in Cohesionless, Mohr-Coulomb Material as 
Predicted by the FLAC Continuum Model 
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Drift Degradation Analysis 
Figure 6-169. Piping Failure Mechanism Represented in the in the FLAC Continuum Model: Bulking 
Factor B = 0.2 
Figure 6-170. Terzaghi Failure Mechanism Represented in the FLAC Continuum Model: Bulking 
Factor B = 0.1 
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Drift Degradation Analysis 
Subsequently, the drift and the caved region were filled with zones (caved rock selected to have 
no cohesion or tensile strength, and density accounting for the bulking), and the model was run 
to the equilibrium to determine the load on the drip shield. 
Clearly, the failure mechanism shown in Figure 6-168 is not a realistic mechanism of the drift 
collapse at Yucca Mountain. This mechanism is more typical for the shallow tunnels in a 
soil-like media where shearing is the predominant mechanism of inelastic deformation. For 
emplacement drifts, collapse of the rock mass from the roof will occur much before the 
deep-seated shear failure in the walls can be mobilized. 
Results of the continuum analysis of rock pressure on the drip shield as a function of the bulking 
factor and different failure mechanism types are summarized in Table 6-47. 
Table 6-47. Summary of Pressures on the Drip Shield Calculated from the Continuum Model 
Case 
Property 
Category Failure Type Bulking 
Pressure (kN/m2) 
Top of Drip Shield Side of Drip Shield 
1 1 Terzaghi 0.1 269.2 47.1 
2 1 pipe 0.1 403.3 39.6 
3 1 Terzaghi 0.2 203.6 27.3 
4 1 pipe 0.2 295.6 28.3 
5 1 Terzaghi 0.4 117.9 20.1 
6 1 pipe 0.4 161.6 17.8 
Source: DTN: MO0408MWDDDMIO.002, file FLAC drip shield pressures.xls. 
Numerical Discontinuum ApproachThe analytical and continuum modeling representations 
of the collapse zone and drip shield loading discussed previously are considered to be overly 
conservative in the predictions of the resulting cavity size and transfer of the load through the 
caved rock. Consequently, predicted loads on the drip shield are quite large. The conservatism 
arises due to the considerations inherent in these methods. To attempt to achieve more realistic 
rubble loading of the drip shield, the problem was solved using the UDEC two-dimensional 
discontinuum numerical code. As in Section 6.4.1, the rock mass was represented as an 
assembly of polygonal blocks of random shape, but with a defined average dimension. The size 
and the shape of the blocks were the same as used in the previous stability analyses, and were 
chosen to be approximately the size expected to form during yielding of the Tptpllwithin the 
range of approximately 0.2 to 0.3 m. The blocks are much smaller than the diameter of the drift, 
and therefore do not affect the collapse mode of the drift or its ultimate shape. The same rock 
mass material model as used in Section 6.4.1, which was calibrated to strength categories 1 to 
5 of the rock mass (associated micro properties are shown in Tables 6-42 and 6-43), is used in 
these analyses of drift collapse. 
The simulations are initiated at the in situ stress equilibrium state for a given rock mass strength 
value. Since the goal of these studies is to understand the maximum ultimate shape of the cavity 
and associated rubble load, the tunnel is forced to collapse in the numerical model. To force 
collapse of the tunnel, shear (cohesion) and tensile strength of the rock mass were subsequently 
reduced in a series of five increments, each equal to 20 percent of the initial strength. For each 
step of strength reduction, the model was run to equilibrium, allowing development of shear or 
tensile fractures in the rock mass and subsequent loosening, detachment, and gravity-fall of 
ANL-EBS-MD-000027 REV 03 6-224 September 2004 

Drift Degradation Analysis 
blocks. At the end of the simulation, when cohesion and tensile strength were completely 
reduced to zero, the model provides an estimate of the maximum extent of the collapsed rock 
mass, the maximum pressures on the drip shield, and the ultimate shape of the collapse drift. An 
example of the evolution of rockfall and the cave size for as a function of strength degradation is 
shown in Figure 6-171. The model shows that in this case (lithophysal rock mass Category 1 and 
rectangular, rigid, drip shield) the emplacement drift begins significant degradation after about 
50 percent reduction in the cohesive strength of the rock mass.1 The drift is completely filled 
with caved rock after 80 percent degradation of the cohesive rock strength for the poorest rock 
quality case shown here (Figure 6-171). In the analyses shown here, complete collapse of the 
drifts was forced. The amount of strength degradation required to produce collapse 
(e.g., 80 percent) depends on the initial strength level. For example, in the case of rock mass 
Category 5 (not shown), which has an unconfined compressive strength of 30 MPa 
(or three times more than the uniaxial compressive strength for Category 1), there will be some 
rockfall from the walls, but the drifts will generally remain open even after 80 percent strength 
degradation. 
This modeling approach differs from the analytical and continuum-based methods in that the 
bulking of the caved rock is not a model parameter but is a result of the modeling. The bulking 
in reality depends on the size and the shape of the falling blocks, which are predetermined by the 
size and the shape of the randomly shaped blocks in the model. An average block dimension of 
0.2 m was selected for two reasons: 
 This dimension is consistent with the spacing of fractures in the Tptpll, and represents a 
reasonable estimate of the expected block dimensions on failure 
 The use of 0.2 m blocks results in bulking factors of approximately 16 to 17 percent 
which is on the low end of observed field bulking factors in rock and is therefore 
considered to yield a conservative result of both cave height and drip shield load. 
Six realizations of different random block geometries with average dimension of 0.2 m were run 
to achieve complete collapse. In each case, a deformable drip shield was considered in which the 
contacts of the footings to the invert were free to slide (frictional) or to separate from the invert 
as the forces dictate (for details of the drip shield formulation and verification, see Appendix Y). 
The drip shield is considered to be elastic with stiffness calibrated to be equivalent to the 
deformability of the three-dimensional frame structure as derived from the LS-DYNA finite 
element model2 (Appendix V). The drip shield is represented by 30 elements starting at element 
number 1 at the right hand footing, and numbered counterclockwise to the left side footing. 
Figure 6-172 shows an example of the final collapsed shape of the tunnel and the rubble lying on 
This agrees, in general, with the predictions of little time-dependent collapse in the previous section. The static 
fatigue data does not indicate that a reduction in strength of the rock mass of 50 percent occurs in the regulatory 
period. 
2 The purpose of the two-dimensional UDEC analyses is to determine rubble loading to the drip shield, but not to 
perform a structural analysis of the drip shield itself. The loads are fed to a detailed three-dimensional structural 
analysis of the drip shield described in a separate calculation. However, it is important to account for the 
deformability of the drip shield in determination of the interaction of the rubble and the structure and the subsequent 
loads that develop. Therefore, the two-dimensional UDEC model of the drip shield was calibrated to provide the 
proper equivalent stiffness and deformability through comparison to a series of simple loading problems from 
LS-DYNA as described in Appendix Y. 
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Drift Degradation Analysis 
the drip shield. Figure 6-173 provides contours of displacement of the rock mass and rubble to 
illustrate the ultimate collapse height of the tunnel. As seen, the height of collapse is 
approximately 6 m or slightly more than 1 diameter above the roof of the drip shield. The 
bulking factor of the rubble is approximately 19 percent in this case (see Appendix V for 
discussion of calculation of bulking factors from model results). The resultant pressure on each 
element at quasi-static equilibrium for each element for the six realizations, along with the 
average for the realizations, is given in Figure 6-174. As seen in this plot the average loads on 
the right- and left-hand sides are approximately the same, while the average pressure on the top 
of the drip shield is about 50 percent higher. 
NOTE: Displacement contours are given to assist in visualizing the collapsed area vs. the surrounding undisturbed 
rock mass. Displacement scale is in meters. Other strength categories will require larger percent strength 
reduction to produce similar profiles, although the ultimate caved profile will be similar. 
Figure 6-171. Evolution of the Cave as a Function of the Cohesive Strength, Category 1 Rock Mass 
Strength 
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Drift Degradation Analysis 
Figure 6-172. Realization 1 for Quasi-static Drift Degradation, Rock Mass Category 1, 0.2 m Block Size: 
Equilibrium State for Deformable Drip Shield 
Figure 6-173. Quasi-static Drift Degradation, Rock Mass Category 1, 0.2 m Block Size: Contours of 
Displacement (m) Magnitude for Deformable Drip Shield Showing Approximate Collapse 
Height of 7 m (about 6 m above top of drip shield crown) 
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Drift Degradation Analysis 
8.00E+05 
Pressure on Element (Pa) 
7.00E+05 
6.00E+05 
5.00E+05 
4.00E+05 
3.00E+05 
2.00E+05 
1.00E+05 
0.00E+00 
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 
ideiRealization 1 
Realization 2 
Realization 3 
Realization 4 
Realization 5 
Realization 6 
Average 
Left STop Right Sde 
Drip Shield Segment Number 
NOTE: Average pressure on each segment is shown for the six realizations plus average for the six realizations 
combined. Segment numbering starts at 1 at right side footing and continues counterclockwise to the left 
footing. Those elements on the right, top, and left sides of the drip shield are shown in the figure. This data 
provided in output DTN: MO0407MWDDSLCR.000 (file final drip shield quasi-static pressures.xls). 
Figure 6-174. Quasi-static Pressure on Drip Shield Segments for Six Realizations for Random, 
0.2m Block Geometries 
The effect of point-loads on the drip shield by rock blocks can be seen in Figure 6-174. 
Occasional, isolated point loads (as well as locations where the segment is not in contact with 
rock blocks) occur that may be several times larger than neighboring segments. The average 
pressure on the crown of the drip shield is approximately 0.15 MPa, with a peak pressure on the 
crown at about 0.7 MPa. The pressure distributions given in Figure 6-174 are used as direct 
feeds to a sensitivity analysis of quasi-static structural analysis of the drip shield as described in 
Structural Stability of a Drip Shield Under Quasi-Static Pressure. These analyses are considered 
to be base case conditions for drip shield load. 
An examination of the ultimate load-bearing capacity of the drip shield is provided in Structural 
Stability of a Drip Shield Under Quasi-Static Pressure. That analysis requires that increased 
levels of load be applied to the drip shield until a failure mechanism develops. The UDEC 
model was used to define increasing rubble pressures applied to the drip shield as input to this 
analysis. Larger gravitational rubble pressures were simulated in the model by increasing the 
density of the rock particles that comprise the rubble, and allowing the model to come to 
equilibrium while the increased rubble pressures on the drip shield are monitored. This method 
allows simulation of the effect of increased vertical pressure on the drip shield (due to larger 
heights of the caved zone) while also estimating the associated effect of increased vertical 
ANL-EBS-MD-000027 REV 03 6-228 September 2004 

Drift Degradation Analysis 
pressure on the lateral loads. The result of these calculations, considering rock rubble density 
Pressure on Element (Pa) 
increases of 1.5, 2, 2.5, 3 and 4 times is shown in Figure 6-175. This plot shows the pressure 
distribution around the drip shield, as averaged from six realizations at each level of density, 
along with the base case given in Figure 6-174. The increase in average vertical pressure across 
the top of the drip shield can be roughly related to an equivalent height of failed rock. 
Drip Shield Loading for Base Case Loading and for Increased Density of Rubble 
700000 
600000 
500000 
400000 
300000 
200000 
100000 
0 
1234567 89 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 
iiiiiRiDensty x 4 
Densty x 3 
Densty x 2.5 
Densty x 2 
Densty x 1.5 
Base case 
Left Side Top ght Side 
Drip Shield Segment Number 
NOTE: Each curve represents the averaging of 6 realizations of rubble distribution. This data provided in output 
DTN: MO0407MWDDSLCR.000 (file drip shield quasi-static pressures fs 4.xls). 
Figure 6-175. Drip Shield Pressures for Base Case and for Consideration of Increase in the Density of 
the Rubble 
Effect of Seismic Ground Shaking on Bulking Factor and Stress Arching in Rubble from 
Previously-Collapsed DriftVibratory shaking may cause settlement (irreversible deformation) 
of granular materials due to packing of grains. This phenomenon is the primary reason for 
liquefaction of water saturated granular media during seismic shaking. Seismic events occurring 
after potential collapse of the emplacement drifts may cause additional compaction of the caved 
rock inside the drift and, consequently, could reduce the positive arching effect within the rubble 
and increase the load of the caved rock mass on the drip shield. To investigate this effect, the 
state of the model of the emplacement drift degradation after total collapse of the drift (with 
rigid, rectangular drip shield) is subjected to shaking by the ground motion with 110-4 
ANL-EBS-MD-000027 REV 03 6-229 September 2004 

Drift Degradation Analysis 
probability of annual recurrence (10,000 year ground motion).3 A rigid drip shield was 
considered in this simulation as it will conservatively overestimate stress transfer to the drip 
shield when additional compaction of the fill occurs. 
Figure 6-176. Contours of Displacement Magnitudes (M) for Previously Collapsed Drift After Subsequent 
Shaking by Ground Motions With 110-4 Probability Of Annual Recurrence 
The state of the model and the load of the caved rock mass on the drip shield before and after 
ground shaking are compared. The contours of displacement magnitudes (relative to the 
displacement of the model base, which is not zero at the end of the simulation) after the shaking 
of the model are shown in Figure 6-176. It can be concluded, comparing Figures 6-171f and 
6-176, that the size and the shape of the region of the caved rock do not change significantly 
after dynamic load. Such a result is expected since the 10,000-year ground motion does not 
cause significant damage of an open drift, and the rubble provides a stabilizing support to the 
interior of the cave. Therefore, little additional rock mass damage takes place when the drift is 
already filled with broken rock. The plot of the stress tensor field in the caved blocks around the 
drip shield before and after ground shaking shows the stress arching formed within the caved 
rock and the effect of shaking on the stress transmission in the rubble (Figure 6-177). The model 
indicates that this level of ground shaking does affect arching to some extent. 
Observations from the plot of stress arching in the caved rock mass are confirmed in 
Figure 6-178 and Table 6-48. There is significant increase in the load on the right side of the 
drip shield as rock blocks come into point contact with the drip shield. In this case, since the 
drip shield is rigid and footings rigidly attached to the invert, no sliding occurs to more equally 
distribute loads on opposing sides of the drip shield. However, the increase in the load on the top 
of the drip shield is relatively smallless than 10 percent. There is practically no change in the 
bulking factor, because shaking does not create any additional collapse. 
3 Only one ground motion was supplied for the 110-4 annual recurrence level. 
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Drift Degradation Analysis 
Stress Scale (Pa) 
0.000E+ 00 2.000E+ 06 
-2.000E+ 06 0.000E+ 00 
-4.000E+ 06 -2.000E+ 06 
-6.000E+ 06 -4.000E+ 06 
-8.000E+ 06 -6.000E+ 06 
-1.000E+ 07 -8.000E+ 06 
-1.200E+ 07 -1.000E+ 07 
-1.400E+ 07 -1.200E+ 07 
-1.600E+ 07 -1.400E+ 07 
NOTE: Stress arching is shown by the stress tensor field colored by the magnitudes of the major principal stress. 
Somewhat greater stress transfer to the drip shield is shown after shaking. 
Figure 6-177. Stress Arching (stress tensor field colored by the magnitudes of the major principal 
stress) Before and After Shaking, Showing Somewhat Greater Stress Transfer to the Drip 
Shield 
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Drift Degradation Analysis 
NOTE: Outside outline of the drip shield is divided into 30 segments (10 per height and 10 per width), which are 
numbered from 1 to 30 starting from lower right end in the counter-clockwise direction. 
Figure 6-178. Pressures on the Rigid, Rectangular Drip Shield After Shaking by the Seismic Event With 
110-4 Probability of Annual Recurrence 
Table 6-48. Effect of Seismic Shaking on Load of Caved Rock on the Rigid, Rectangular Drip Shield 
Loading 
Condition 
Pressure (kN/m2) 
Bulking Factor Left Side Top Right Side 
before shaking 62.6 179.2 44.8 0.19 
after shaking 70.2 193.9 125.1 0.21 
Summary of Quasi-static Loading of the Drip ShieldThe predictions of the average vertical 
pressure of the caved rock on the drip shield by the three modeling approaches are summarized 
in Figure 6-179. As expected, the analytical models yield the largest loads due to the 
conservative considerations of dead weight on the drip shield and no stress arching in the rubble. 
The continuum numerical model accounts more accurately for transfer of load by friction from 
the caved rock to the surrounding stable rock mass. Consequently, predicted loads for small 
bulking factors and large cavity size are much smaller than analytical predictions. When the 
bulking factor is large, the height of the cave becomes small. Stress arching cannot be realized 
within the small column of the caved rock and, consequently, prediction between analytical and 
continuum models are identical. The most accurate approach, using the discontinuum model, 
does not use an imposed condition about the shape of the caved region or the bulking factor of 
the rubble. It also correctly accounts for load transfer through the caved rock. The predictions 
of the pressures on the drip shield using this approach are smaller than the predictions of the 
analytical and continuum models for the values of the bulking factor. The non-uniform and 
averaged quasi-static drip shield pressure distribution, illustrated in Figure 6-174, as well as the 
ANL-EBS-MD-000027 REV 03 6-232 September 2004 

Drift Degradation Analysis 
increased pressures for estimation of the ultimate load bearing capacity of the drip shield are 
used as a direct feed to the structural analysis of the drip shield as provided in Structural Stability 
of a Drip Shield Under Quasi-Static Pressure. Further compaction of the rubble during 
subsequent seismic events may result in re-adjustment of point loads to the lining, but does not 
appear to result in reduction in bulking factor of the rubble material. 
NOTE: Two different sizes of the randomly shaped blocks used in the discontinuum analyses were used to produce 
a range of bulking factors. 
Figure 6-179. Summary of Vertical Load on the Drip Shield as a Function of Bulking Factor 
6.4.3 Investigation of Potential Key Blocks in Lithophysal Units 
The stability analyses of the lithophysal rock mass presented thus far consider that the ubiquitous 
fracture fabric in this unit will control failure mode, resulting in raveling of small rock particles. 
However, a set of widely spaced, longer trace length cooling fractures exists that are not 
truncated by the small-scale fractures. It is possible that, in addition to the raveling mode of 
failure, that larger rock blocks (key blocks) are formed by these longer fractures. This section 
describes the probability of key-block existence, or the possibility that wedge-type failure may 
occur in the lithophysal units. The general approach used for analyses of wedge-type failure in 
the nonlithophysal units, as described in Section 6.3.1, is also applied in this study. The 
three-dimensional discontinuum code 3DEC is used for the mechanical analysis of the jointed 
rock mass simulated by FracMan. Since small-scale fractures have minor effect on wedge 
formation as confirmed in Section 6.3.3, only the fractures with trace lengths greater than or 
equal to 1 m long are included here. 
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Drift Degradation Analysis 
In a similar manner as that used for examination of the nonlithophysal base case, a total of 
50 fracture modeling regions were selected from the 100-m cube simulated FracMan fractured 
rock mass for the Tptpll unit (Appendix B). Because the coordinates of the 50 fracture modeling 
regions selected for the nonlithophysal units were randomly generated, they were also used in the 
lithophysal units. For conservatism and efficiency, fracture strength parameters (cohesion and 
friction angle) were reduced to small values to evaluate the probability of key-block existence. 
With strength parameter values assigned as 0, the predicted rockfall is equivalent to the blocks 
that are kinematically admissible to fall regardless of the frictional resistance of fracture surfaces. 
The summary of the analyses is presented in Table 6-49. Twenty-one distinct rock blocks are 
formed by the longer fractures in the 50 simulations. Notice that the distinct blocks are all of the 
blocks that exist in the rock mass regardless of whether the blocks are kinematically or 
mechanically suitable to fall. A typical cross section of the analysis with prediction of the 
distinct block is provided in Figure 6-180. Only two blocks were predicted to fall into the drift 
with block volume of 0.16 m3 and 0.08 m3. With only two blocks predicted for 1.25 km of drift 
simulated while using extremely conservative (i.e., low) fracture strength properties, the 
probability of key-block occurrence in lithophysal units is very low and not considered further. 
This analysis confirms that raveling of small blocks is expected to be the dominant potential 
failure mode of drifts in lithophysal rocks. 
Table 6-49. Summary of 3DEC Rockfall Prediction for Lithophysal Units 
Parameter Value 
Simulations Completed 50 
Number of Simulations Predicting No Rockfall 48 
Number of Simulations Predicting No Distinct Block 37 
Total Number of Rockfall 2 
Total Volume of Rockfall (m3) 0.24 
Total Length of Drift Simulated (m) 1250 
Number of Blocks per km 1.6 
Volume of Rockfall per km (m3/km) 0.19 
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Drift Degradation Analysis 
NOTE: The fracture traces shown in this cross section do not necessarily form a coherent block in 
three-dimensions. The only distinct block formed in this cross section is shown in yellow, and is obviously 
not removable. 
Figure 6-180. Cross Section of a Typical Simulated Lithophysal Rock Mass in 3DEC 
6.5 UNCERTAINTIES AND LIMITATIONS 
The task of predicting and characterizing drift degradation anticipated within repository 
emplacement drifts throughout the 10,000-year period of compliance for postclosure 
performance has several inherent uncertainties and limitations. These uncertainties are 
associated with both the modeling methods and the model inputs. To provide a meaningful 
assessment of drift degradation, the uncertainties must be identified and adequately represented 
within the model. The uncertainties associated with modeling methods are addressed with model 
validation (Section 7). Additionally, a discussion of alternative conceptual models has been 
provided (Section 6.7), which provides justification for use of the modeling methods employed 
in this document, thereby demonstrating that the drift degradation models presented in this report 
are adequate to account for the uncertainties and limitations. 
This section provides a discussion of uncertainties associated with model inputs. The discussion 
below has been rank-ordered according to importance in control of drift degradation under in 
situ, thermal, and seismic loading. That is, the parameters and their associated uncertainty that 
have the most significant impact on model results are discussed first. In general, those 
uncertainties associated with drift degradation in lithophysal rocks are considered to be most 
significant due to the relatively larger amount of emplacement area located in them. The rock 
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Drift Degradation Analysis 
mass properties for lithophysal rock and fracture geometry in nonlithophysal rock have the 
greatest impact on drift degradation. The seismic ground motions, particularly those at low 
annual probability levels, have a large impact on stability of both nonlithophysal and lithophysal 
rock masses. 
Rock Mass Mechanical Properties DataRock mass mechanical properties data for 
nonlithophysal rock are calculated using rock mass classification data collected from field 
mapping within the ESF and intact rock properties data collected from laboratory testing. The 
uncertainties associated with the intact rock properties data are described above. The 
uncertainties associated with the rock mass classification data are epistemic, and are assessed to 
be low because an abundance of data has been collected based on established, industry-accepted 
methods. There is a moderate degree of epistemic uncertainty associated with the calculation 
approach for assessing rock mass properties, since they are based on empirical methods and have 
an inherent characteristic of imprecision. This uncertainty has been accounted for by using two 
separate empirical calculation methods and demonstrating that the results are similar. The rock 
mass properties data are primarily used in the thermal-mechanical calculation to determine 
stresses within the model as described in Section 6.2, and are a relatively insensitive parameter to 
the stress calculations. 
Rock mass mechanical properties data for lithophysal rock are based on large-diameter uniaxial 
compression test data and in situ slot test data (Appendix E, Section E4.1). The epistemic 
uncertainty associated with this rock mass data for lithophysal rock is assessed to be high. To 
account for this uncertainty in the rockfall model for lithophysal rock, five categories of rock 
properties were included in the model to assess the impact of the ranges in rock mass properties 
data. Additionally, the PFC numerical model was calibrated to reproduce the large-core 
laboratory mechanical properties data and its dependency on lithophysal porosity as well as the 
observed failure mechanisms. The model was then used to build confidence in the understanding 
of the bounding ranges of lithophysal rock mass properties through numerical extrapolations to 
examine the effect of lithophysal cavity porosity, size, shape and distribution variability as 
defined by field mapping. This work is described in detail in Appendix E, Section E4.1. The 
impact of use of the range of rock properties on drift degradation and rockfall was explored 
through use of sensitivity studies in Section 6.4. 
Seismic Ground Motion DataThe seismic time histories used to evaluate rockfall reflect a 
number of variabilities, including epistemic uncertainty and randomness (aleatoric uncertainty). 
Epistemic uncertainties (due to incomplete knowledge) in the characterization of seismic sources 
and median ground motion attenuation, along with randomness in seismic ground motion, were 
explicitly incorporated into the probabilistic seismic hazard analysis. The mean results of that 
analysis form the basis for the site-specific ground motions used in this report. At annual 
probabilities of exceedance lower than about 110-6, the mean hazard exceeds the 85th percentile 
of the hazard uncertainty distribution. 
Development of site-specific ground motions incorporates additional epistemic uncertainty in the 
velocity and dynamic properties of site materials. Observed randomness of site materials is also 
addressed. Finally, randomness in the spectral content and duration of time histories that 
produce the same peak ground motion is accommodated in the drift degradation analyses through 
the use of 15 sets of time histories for each of the two postclosure hazard levels considered. The 
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Drift Degradation Analysis 
earthquake magnitudes and epicentral distances of the recorded strong motion data that form an 
input to these time histories, reflect the range of magnitudes and distances contributing most 
strongly to seismic hazard at the site for the given annual probabilities of ground motion 
exceedance. 
While the seismic ground motion inputs developed in this manner fully account for the 
underlying uncertainties and randomness, the result is that for annual exceedance probabilities of 
about 110-6 and lower, some realizations of ground motion are larger than the largest ground 
motions observed and may not be physically realizable. Nonetheless, these ground motions are 
consistent with and demonstrate fully the current state of uncertainty and randomness in deriving 
ground motion inputs for very low annual probabilities of exceedance. Lacking a technical basis 
to limit such ground motions to smaller values, these inputs are used in the analyses supporting 
TSPA-license application (LA) 4. 
Static Fatigue and Long-Term Strength DataThe long-term strength predictions 
(Section 6.4.2.4 and Appendix S) are based on very limited static-fatigue test data, which provide 
time-dependent strength behavior of the lithophysal rock. A static-fatigue (creep) test involves 
applying a constant compressive stress to a specimen, and recording the time to failure 
(Potyondy 2003 [DIRS 165550], Section 1.4). One of the main limitations of the predictions of 
time-dependent behavior of excavations in a rock mass for a period of 10 years or longer after 
excavation, is that existing static-fatigue testing (for any rock) is typically performed for no more 
than a few months. Predictions for longer time frames are based on extrapolation of existing 
testing data, and involve a significant level of uncertainty. The static-fatigue curve is usually 
considered to be a straight line in a logarithm plot of time-to-failure versus driving-stress ratio, 
which is fitted to experimental data. However, it appears from available data for Lac du Bonnet 
granite (see Appendix S, Figure S-27) that the fitted static-fatigue curve underestimates 
time-to-failure compared to experimental data in the range of driving-stress ratios between 0.65 
and 0.70 (which corresponds to the longest measured times-to-failure). It seems that a curved 
line (instead of straight line) would be a better fit for long times-to-failure. Consequently, 
predictions obtained using the straight line are conservative, because the straight line appears to 
under-predict time-to-failure for low values of the driving stress. 
Failure times and the evolution of the damage of the rock are provided by standard creep (i.e., 
strain versus time) plots derived from the laboratory static-fatigue test. The PFC stress corrosion 
model was calibrated to reproduce the time-evolution of damage response as determined from 
these laboratory tests. The sensitivity of the PFC stress corrosion predictions to damage rate has 
been investigated to determine how damage rates affect the final result of the model (i.e., the 
rockfall induced by time-dependent strength degradation). Damage curves were generated for 
tuff best fit static-fatigue (see Appendix S, Figure S-29), where the damage rates for the driving 
stress levels are considered to be the same, equal to the maximum rate predicted by the PFC 
4 An analysis to provide an estimate of the bounding peak ground velocity for the Yucca Mountain site has been 
developed (BSC 2004, [DIRS 170137]). This estimate is based on examination of the maximum shear strain that the 
lithophysal rock can withstand, and relating this to the peak ground velocity that will produce this strain. Since no 
seismic-related shear damage can be observed in the field in the lithophysal rocks, it is argued that no seismic event 
has occurred with peak ground velocity exceeding this failure limit in the approximately 12.8 million years since the 
Topopah Spring tuff has been deposited and cooled. However, non-bounded ground motion time histories were 
used in the analyses presented in this document. 
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Drift Degradation Analysis 
stress corrosion model. The rockfall predictions due to time-dependent strength reduction using 
a range of damage curves have been compared, and it is clear that the considered variation of 
damage rates has no practical effect on predicted rockfall (see Appendix S, Figure S-31). The 
time-to-failure is the main factor controlling evolution of the rockfall due to time-dependent 
strength reduction. Consequently, UDEC predictions are not very sensitive to the damage rate 
input from the PFC stress corrosion model. 
Further investigation of uncertainty in the time-dependent UDEC modeling of drift degradation 
was performed by using the time-dependent strength degradation obtained from extensive Lac du 
Bonnet granite as a lower bound to the time-dependent strength loss of Topopah Spring tuff. 
Although the extent of drift degradation is greater when using these lower bound considerations, 
the overall conclusions regarding extent of collapse and timing of collapse are not significantly 
different (Appendix S). 
Fracture Geometry Data for Nonlithophysal RockThe natural variability of fractures within 
a rock mass represents epistemic uncertainty (i.e., uncertainty due to incomplete knowledge) in 
the design of structures in rock. The large amount of fracture data collected at the YMP provides 
a very good representation of the range of fracture geometry anticipated at the emplacement drift 
horizon. The range of fracture geometry variability from tunnel mapping has been captured in 
the rockfall model for nonlithophysal rock through multiple simulations of the rock mass. 
Section 6.1.6 describes the generation of representative rock volumes using FracMan with the 
consideration of the natural variability of fracture geometry. The representativeness of the 
FracMan-generated rock volume is verified in Section 6.1.6 through comparison of the FracMan 
synthetic fracture network to the statistical variability of the fractures as measured by field 
mapping. Section 6.3.1.2.2 documents the random selection of the fracture-modeling region in 
the rockfall analyses to cover the uncertainties associated with fracture orientation, intensity and 
length. The fracture geometry is concluded to be the dominant factor for wedge-type rockfall in 
nonlithophysal rock. The uncertainty associated with joint geometry data in the rockfall models 
is assessed to be low. 
Intact Rock Physical and Mechanical Properties DataA sufficient amount of intact rock 
physical and mechanical properties data has been collected for the nonlithophysal rock units. 
The epistemic uncertainty associated with this intact data for nonlithophysal rock is assessed to 
be low. Conversely, the amount of intact rock physical and mechanical properties data for the 
lithophysal units is limited. The epistemic uncertainty associated with this intact data for 
lithophysal rock is assessed to be high. To account for this uncertainty in the rockfall model for 
lithophysal rock, five categories of rock properties were included in the model to assess the 
impact of the ranges in intact properties data. The difference of rockfall prediction for the range 
of properties considered is provided in Section 6.4. 
Fracture Mechanical Properties DataThe amount of fracture mechanical properties data for 
both the nonlithophysal and lithophysal rock units is limited; therefore, the uncertainty 
associated with this data is epistemic, and is relatively high. To account for this uncertainty in 
the rockfall models, sensitivity analyses for the possible range of fracture strength parameters, 
dilation angle, and fracture stiffness were conducted and the results are presented in 
Section 6.3.1.6. Fracture mechanical properties are judged to have a secondary effect on rockfall 
compared with fracture geometry data. 
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Drift Degradation Analysis 
Rock Thermal Properties DataA sufficient amount of rock thermal properties data has been 
collected for the nonlithophysal rock units. The epistemic uncertainty associated with this 
thermal properties data for nonlithophysal rock is assessed to be low. Conversely, the amount of 
rock thermal properties data for the lithophysal units is limited. Therefore, the epistemic 
uncertainty associated with this thermal properties data for lithophysal rock is assessed to be 
high. Uncertainty assessments are provided in the data source documentation identified in 
Table 4-1 and in Appendix E (Section E5). Sensitivity calculations for thermal properties were 
conducted with one standard deviation less values used for thermal conductivity and specific 
heat as described in Section 6.2, Section 6.3.1.3, and Section 6.4.2.3. The sensitivity case results 
in approximately 23C higher peak temperature comparing with the base case but with minor 
impact to the rockfall prediction. 
Repository Layout InformationThe repository layout data are based on design information, 
which is currently in the preliminary design stage. This design information is subject to change 
before being finalized. The model results documented in this report are applicable for the 
emplacement drift diameter and emplacement drift alignment provided by repository design and 
performance assessment information exchange drawings (BSC 2004 [DIRS 164519]; BSC 2004 
[DIRS 168489]) and Section 5.1.4 and 8.7 of Underground Layout Configuration (BSC 2003 
[DIRS 165572]). The rockfall models are sensitive to both emplacement drift diameter and 
alignment. While no changes are expected to the emplacement drift diameter and alignment, and 
any change to this design information would require reevaluation. 
6.6 DRIFT DEGRADATION FEPS 
The development of a comprehensive list of features, events, and processes (FEPs) potentially 
relevant to postclosure of the repository is an ongoing, iterative process based on site-specific 
information, design, and regulations. The approach for developing an initial list of FEPs was 
documented by The Development of Information Catalogued in REV00 of the YMP FEP 
Database (Freeze et al. 2001 [DIRS 154365]). To support TSPA-LA, the FEP list was 
re-evaluated and is provided by DTN: MO0407SEPFEPLA.000 [DIRS 170760]. Table 6-50 
provides a list of FEPs addressed in this model document that have been included in TSPA-LA 
(based on MO0407SEPFEPLA.000 [DIRS 170760]), and provides specific references to sections 
within this document. Additionally, Table 6-51 provides a list of FEPs addressed in this model 
document that have been excluded in TSPA-LA (based on MO0407SEPFEPLA.000 
[DIRS 170760]). 
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Table 6-50. Included FEPs Addressed by This Model Report 
Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 6-240 September 2004 
FEP No. FEP Name Section Where the FEP is Discussed 
1.2.03.02.0A Seismic ground 
motion 
damages EBS 
components 
This report provides rockfall models that are based on site characterization data, including joint geometry and rock 
strength data, coupled with anticipated thermal stresses and seismic ground motion. Based on the analyses presented in 
this report (Section 6.3 and 6.4), postclosure ground motion levels are sufficient to produce collapse of drifts in the 
lithophysal rock units (which represent approximately 85 percent of the emplacement drifts). Minor to moderate 
degradation or collapse of drift is anticipated in the nonlithophysal rock units throughout the regulatory period for 
postclosure performance. 
1.2.03.02.0B Seismic-
induced rockfall 
damages EBS 
components 
This report provides rockfall models that are based on site characterization data. Probabilistic descriptions of rock size 
and rockfall frequency are provided for use in engineering design analyses (Sections 6.3 and 6.4). The block size 
distributions presented in this report are similar to the block size distributions developed using the approach in the previous 
version of this document (Section 7.7.5). However, the frequency of blocks has increased with the larger ground motions 
used in this report compared to the previous approach (Section 7.7.5). 
1.2.03.02.0C Seismic induced 
drift collapse 
damages EBS 
components 
This report provides rockfall models that are based on site characterization data, including joint geometry and rock 
strength data, coupled with anticipated thermal stresses and seismic ground motion. Based on the analyses presented in 
this report (Section 6.3 and 6.4), minor degradation or collapse of drift is anticipated for the static (i.e., no seismic) case 
and during the preclosure period. The mechanical degradation or collapse of drift predicted for the static case and during 
the preclosure period is similar to the results from the previous approach using DRKBA (Section 7.7.5). Based on the 
analyses presented in this report (Section 6.3 and 6.4), postclosure ground motion levels are sufficient to produce collapse 
of drifts in the lithophysal rock units (which represent approximately 85 percent of the emplacement drifts). Minor to 
moderate degradation or collapse of drift is anticipated in the nonlithophysal rock units throughout the regulatory period for 
postclosure performance. 
1.2.03.02.0D Seismic induced 
drift collapse 
alters in-drift 
thermohydrology 
This report provides rockfall models that are based on site characterization data, including joint geometry and rock 
strength data, coupled with anticipated thermal stresses and seismic ground motion. Based on the analyses presented in 
this report (Section 6.3 and 6.4), minor degradation or collapse of drift is anticipated for the static (i.e., no seismic) case 
and during the preclosure period. The mechanical degradation or collapse of drift predicted for the static case and during 
the preclosure period is similar to the results from the previous approach using DRKBA (Section 7.7.5). Based on the 
analyses presented in this report (Section 6.3 and 6.4), postclosure ground motion levels are sufficient to produce collapse 
of drifts in the lithophysal rock units (which represent approximately 85 percent of the emplacement drifts). Minor to 
moderate degradation or collapse of drift is anticipated in the nonlithophysal rock units throughout the regulatory period for 
postclosure performance. 
NOTE: The screening decision to determine the include/exclude status of the FEP is documented in MO0407SEPFEPLA.000 [DIRS 170760]. 

Table 6-51. Excluded FEPs Addressed by This Model Report 
Drift Degradation Analysis 
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FEP No. FEP Name Section Where the FEP is Discussed 
1.1.02.00.0B Mechanical 
effects of 
excavation/ 
construction in 
EBS 
This report provides rockfall models that are based on observation of rock characteristics representing the as-built (postexcavation) 
condition, so that potential excavation effects, if any, are considered. For example, the field mapping data of 
geologic features presented in Section 6.1.4 were collected post-excavation in the ESF, and therefore include excavation 
effects. Similarly, the calculation of rock mass properties in Appendix E (Section E4) inherently includes these excavation 
effects. Therefore, the effects of excavation on rock mass response are reflected in the results presented in this report. 
2.1.06.02.0A Mechanical 
effects of rock 
reinforcement 
materials in 
EBS 
In this model report, no credit is taken for ground support in rockfall models (Section 6.0). Therefore, the consideration of 
the mechanical effects of rock reinforcement is implicit in the modeling approaches discussed in Sections 6.3 and 6.4. The 
rockfall models presented in this report (Sections 6.3 and 6.4) provide a bounding scenario in the analysis of the effects of 
rock reinforcement on drift degradation. 
2.1.07.01.0A Rockfall This report provides rockfall models that are based on site characterization data. Probabilistic descriptions of rock size 
and rockfall frequency are provided for use in engineering design analyses (Sections 6.3 and 6.4). The block size 
distributions and frequency of blocks presented in this report for static (i.e., no seismic) and preclosure ground motion are 
similar to the block size data developed using the approach in the previous version of this document (Section 7.7.5). 
2.1.07.02.0A Drift collapse This report provides rockfall models that are based on site characterization data. Based on the analyses presented in this 
report (Section 6.3 and 6.4), minor degradation or collapse of drift is anticipated for the static (i.e., no seismic) case and 
during the preclosure period. The mechanical degradation or collapse of drift predicted for the static case and during the 
preclosure period is similar to the results from the previous approach using DRKBA (Section 7.7.5). 
2.1.11.07.0A Thermal 
expansion/ 
stress of in-drift 
EBS 
components 
This report provides rockfall models that include the potential impact of thermally induced stress changes in the rock mass 
(Section 6.2). The effects of thermally induced stress changes on drift degradation are documented in Sections 6.3.1.3 
(nonlithophysal rock) and 6.4.2.3 (lithophysal rock). 
NOTE: The screening decision to determine the include/exclude status of the FEP is documented in MO0407SEPFEPLA.000 [DIRS 170760]. 

Drift Degradation Analysis 
6.7 DOCUMENTATION OF ALTERNATIVE CONCEPTUAL MODELS 
Alternative conceptual models are based on assumptions and simplifications that are different 
from those employed in the base case models (i.e., the rockfall model for nonlithophysal rock 
(Section 6.3) and the rockfall model for lithophysal rock (Section 6.4)). An important reason for 
considering alternative conceptual models is to help build confidence that changes in modeling 
assumptions or simplifications will not change conclusions regarding subsystem and total system 
performance. Conceptual model uncertainty results from sparse observational data and a lack of 
available information to corroborate or refute plausible alternative interpretations of the 
subsystem and the processes occurring within the subsystem. 
The alternative conceptual models considered in this analysis of drift degradation are 
summarized in Table 6-52. 
Table 6-52. Alternative Conceptual Models Considered 
Alternative 
Conceptual Model Key Assumptions 
Screening Assessment 
and Basis 
Continuum model of 
lithophysal rock 
Lithophysae and fractures 
are smeared into the 
elements in the equivalent 
continuum representation of 
the rock mass. Rock 
damage is expressed as 
element yielding following 
the selected failure criterion. 
The continuum model, such as FLAC or FLAC3D, is capable 
of modeling the material yielding behavior with elasto-plastic 
constitutive model. Yielding occurs when the stress state 
within the element reach the strength criterion specified by 
the constitutive law, the yielding of elements in the 
continuum, however, is not equivalent to rockfall. To 
estimate the extent of rockfall based on the depth of yielding 
is not realistic. Therefore, this alternative conceptual model 
is excluded from further evaluation. 
Continuum model of 
nonlithophysal rock 
Fractures are smeared into 
the elements in the 
equivalent continuum 
representation of the rock 
mass. Element contains the 
The compliant joint model (Chen 1987 [DIRS 101800]) is 
capable of analyzing jointed media behavior with fractures 
smeared into the elements. The model includes a 
continuum approximation based on average discontinuous 
displacements across joint planes within a representative 
weak plane information for 
potential shear slipping. 
elementary volume. The model also includes a material 
constitutive description based on linear elastic matrix 
material behavior and nonlinear normal and shear joint 
behavior between joint planes. The continuum model 
provides global rock mass response with predominant weak 
plane orientation, but cannot predict wedge-type failure. 
Therefore, this alternative conceptual model is excluded 
from further evaluation. 
Hudson and Priest 
(1979 DIRS 104915]) 
model of 
nonlithophysal rock 
for estimating block 
size distribution 
All joint planes are assumed 
to be perfectly planar, 
persistent, and extend 
throughout the rock volume 
of interest. The distribution 
of joint spacing values along 
a line is assumed to be of 
negative exponential form. 
The approach to determine block size distribution using the 
Hudson and Priest approach has been documented by 
Preliminary Block Size Calculation (CRWMS M&O 1998 
[DIRS 102723], Section 5.3). This approach provides a 
generalized statistical representation of the joint geometry. 
In particular, the assumption of continuous joints is not 
consistent with the discontinuous joints observed in the 
ESF. Since joint geometry is a primary factor in the 
assessment of block development, the generalized 
approach by Hudson and Priest does not provide the level of 
detail required to accurately model drift degradation. 
Therefore, this alternative conceptual model is excluded 
from further evaluation. 
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Drift Degradation Analysis 
6.8 RESOLUTION OF KEY TECHNICAL ISSUES 
The NRC is conducting an ongoing review of the information provided by the YMP to allow 
early identification and resolution of potential licensing issues. The NRC has identified several 
key technical issues (KTIs) and associated sub-issues, along with acceptance criteria for 
resolution of the issue. The drift degradation analysis provides information that is directly 
related to the KTI on Repository Design and Thermal-Mechanical Effects (NRC 2002 
[DIRS 159538]). To provide a clear understanding of the technical issues, a NRC/DOE 
Technical Exchange and Management Meeting on Repository Design and Thermal-Mechanical 
Effects was held in February of 2001. As a result of this meeting, a number of agreements 
between the NRC and DOE were formally adopted (Reamer and Williams 2001 [DIRS 154348]), 
outlining the plan for resolution of the technical issues. The agreement items addressed in this 
report are presented verbatim as follows: 
 RDTME 3.04Provide in the Design Parameter Analysis Report (or some other 
document) site-specific properties of the host rock, as a minimum those included in the 
NRC handout, together with the spatial and temporal variations and uncertainties in such 
properties, as an update to the information contained in the March 1997 Yucca Mountain 
Site Geotechnical Report. The DOE will: (1) evaluate the adequacy of the currently 
available measured and derived data to support the potential repository licensing case 
and identify areas where available data may warrant additional field measurements or 
testing to reduce uncertainty. DOE will provide a design parameters analysis report 
(or other document) that will include the results of these evaluations, expected to be 
available to NRC in FY 2002; and (2) acquire data and/or perform additional analyses as 
necessary to respond to the needs identified in 1 above. The DOE will provide these 
results prior to any potential license application. 
 RDTME 3.05Provide the Rock Mass Classification Analysis (or some other document) 
including the technical basis for accounting for the effects of lithophysae. The DOE will 
provide a rock mass classification analysis (or other document), including the technical 
basis for accounting for the effects of lithophysae, expected to be available to NRC in 
FY 2002. 
 RDTME 3.07 The DOE should account for the effect of sustained loading on intact 
rock strength or provide justification for not accounting for it. The DOE will assess the 
effects of sustained loading on intact rock strength. The DOE will provide the results of 
this assessment in a design parameters analysis report (or other document), expected to 
be available to NRC in FY 2002. 
 RDTME 3.10Provide technical basis for the assessment that two-dimensional modeling 
for emplacement drifts is considered to be adequate, considering the fact that neither the 
in-situ stress field nor the principle fracture orientation are parallel or perpendicular to 
emplacement drift orientation. The DOE will provide the technical bases for the 
modeling methods used in ground control analysis in a revision to the Ground Control 
for Emplacement Drifts for site recommendation, ANL-EBS-GE-000002 (or other 
document) supporting any potential license application. This is expected to be available 
to NRC in FY 2003. 
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Drift Degradation Analysis 
 RDTME 3.15Provide field data and analysis of rock bridges between rock joints that 
are treated as cohesion in DRKBA modeling together with a technical basis for how a 
reduction in cohesion adequately accounts for thermal effects. The DOE will provide 
clarification of the approach and technical basis for how reduction in cohesion 
adequately accounts for thermal effects, including any additional applicable supporting 
data and analyses. Additionally, the adequacy of the cohesion reduction approach will 
be verified according to the approach described in Subissue 3, Agreement 22 
[RDTME 3.19], of the Repository Design and Thermal-Mechanical Effects Technical 
Exchange. This will be documented in a revision to the Drift Degradation Analysis, 
ANL-EBS-MD-000027, expected to be available to NRC in FY 2003. 
 RDTME 3.16Provide a technical basis for the DOE position that the method used to 
model joint planes as circular discs does not under-represent the smaller trace-length 
fractures. The DOE will analyze the available small trace-length fracture data from the 
Exploratory Studies Facility and Enhanced Characterization of the Repository Block, 
including their effect on block development. This will be documented in a revision to 
the Drift Degradation Analysis, ANL-EBS-MD-000027, expected to be available to 
NRC in FY 2003. 
 RDTME 3.17Provide the technical basis for effective maximum rock size including 
consideration of the effect of variation of the joint dip angle. The DOE will provide the 
technical basis for effective maximum rock size including consideration of the effect of 
variation of the joint dip angle. This will be documented in revisions to the Drift 
Degradation Analysis, ANL-EBS-MD-000027, and the Rockfall on Drip Shield, 
CAL-EBS-ME-000001, expected to be available to NRC in FY 2003. 
 RDTME 3.19The acceptability of the process models that determine whether rockfall 
can be screened out from performance assessment abstractions needs to be substantiated 
by the DOE by doing the following: (1) provide revised DRKBA analyses using 
appropriate range of strength properties for rock joints from the Design Analysis 
Parameters Report, accounting for their long-term degradation; (2) provide an analysis 
of block sizes based on the full distribution of joint trace length data from the Fracture 
Geometry Analysis Report for the Stratigraphic Units of the Repository Host Horizon, 
including small joints trace lengths; (3) verify the results of the revised DRKBA 
analyses using: (a) appropriate boundary conditions for thermal and seismic loading; 
(b) critical fracture patterns from the DRKBA Monte Carlo simulations (at least 
two patterns for each rock unit); (c) thermal and mechanical properties for rock blocks 
and joints from the Design Analysis Parameters Report; (d) long-term degradation of 
rock block and joint strength parameters; and (e) site-specific ground motion time 
histories appropriate for post-closure period; provide a detailed documentation of the 
analyses results; and (4) in view of the uncertainties related to the rockfall analyses and 
the importance of the outcome of the analyses to the performance of the repository, 
evaluate the impacts of rockfall in performance assessment calculations. DOE believes 
that the Drift Degradation Analysis is consistent with current understanding of the 
Yucca Mountain site and the level of detail of the design to date. As understanding of 
the site and the design evolve, DOE will: (1) provide revised DRKBA analyses using 
appropriate range of strength properties for rock joints from a design parameters analysis 
ANL-EBS-MD-000027 REV 03 6-244 September 2004 

Drift Degradation Analysis 
report (or other document), accounting for their long-term degradation; (2) provide an 
analysis of block sizes based on the full distribution of joint trace length data from the 
Fracture Geometry Analysis for the Stratigraphic Units of the Repository Host Horizon, 
ANL-EBS-GE-000006, supplemented by available small joint trace length data; 
(3) verify the results of the revised DRKBA analyses using: (a) appropriate boundary 
conditions for thermal and seismic loading; (b) critical fracture patterns from the 
DRKBA Monte Carlo simulations (at least two patterns for each rock unit); (c) thermal 
and mechanical properties for rock blocks and joints from a design parameters analysis 
report (or other document); (d) long-term degradation of joint strength parameters; and 
(e) site-specific ground motion time histories appropriate for post-closure period. 
This will be documented in a revision to the Drift Degradation Analysis, 
ANL-EBS-MD-000027, expected to be available to NRC in FY 2003. Based on the 
results of the analyses above and subsequent drip shield calculation revisions, DOE will 
reconsider the screening decision for inclusion or exclusion of rockfall in performance 
assessment analysis. Any changes to screening decisions will be documented in 
analyses prior to any potential license application 
The contribution toward fulfillment of these agreement items provided by this model report is 
identified in Table 6-53. 
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Drift Degradation Analysis 
Table 6-53. Repository Design and Thermal-Mechanical Effects KTI Agreement Items Addressed in This Model Report 
Agreement 
Item Approach and Section Reference Status of Agreement 
RDTME 3.04 Geotechnical data to support the drift degradation analyses documented in this report are identified in 
Section 4, Section 7, and Appendix E. Discussions of data adequacy are provided throughout Sections 6, 7, 
and 8. Newly acquired data from lithophysal rocks have been used to develop the lithophysal rockfall model, 
including data from laboratory compression testing on large-diameter cores. Note that the primary document 
addressing this agreement item is Subsurface Geotechnical Parameters Report (BSC 2003 [DIRS 166660]). 
The data and information 
provided in this model report 
contributes to the closure of 
this agreement. 
RDTME 3.05 The technical basis for accounting for the effects of lithophysae is presented in Section 6.4. The validity of 
this approach is discussed in Sections 7.3 and 7.4. Note that the primary document addressing this 
agreement item is Subsurface Geotechnical Parameters Report (BSC 2003 [DIRS 166660]). 
The data and information 
provided in this model report 
contributes to the closure of 
this agreement. 
RDTME 3.07 The technical basis for accounting for the effects of time-dependent degradation is presented in 
Sections 6.3.1.5, 6.4.2.4, and Appendix S. 
The data and information 
provided in this model report 
are intended to fully address 
the requirements of this 
agreement. 
RDTME 3.10 The assessment of an appropriate approach to model the rock mass is a function of the specific repository 
host rock type: lithophysal or nonlithophysal rock (Section 7.1). 
For nonlithophysal rock, jointing controls the mechanical response, which is generally anisotropic in nature. 
Therefore, two-dimensional modeling of nonlithophysal rock is not realistic for rockfall modeling, and a three-
dimensional modeling approach must be used. 
Conversely, lithophysal rock is characterized by the presence of more-or-less uniformly distributed voids 
(lithophysae) of varying size. Additionally, in the Tptpll, short trace length interlithophysae fracturing exists. 
Under these conditions, the representation of lithophysal rock as a homogeneous, isotropic rock mass is 
appropriate. Therefore, in models of drift stability, the use of a two-dimensional model in the plane 
perpendicular to the axis is adequate. 
The data and information 
provided in this model report 
are intended to fully address 
the requirements of this 
agreement. 
RDTME 3.15 Additional clarification of the approach and technical basis for how reduction in cohesion adequately 
accounts for thermal effects in the DRKBA analyses is provided in Appendix D. However, the DRKBA 
analyses now provide a confirmatory role in the assessment of drift degradation. The drift degradation 
analyses are primarily conducted using UDEC and 3DEC, in which thermal loads have been explicitly 
modeled (Sections 6.3 and 6.4). The adequacy of the methods to account for thermal effects on drift 
degradation is validated in Section 7.8. 
The data and information 
provided in this model report 
are intended to fully address 
the requirements of this 
agreement. 
RDTME 3.16 The available small trace-length fracture data have been analyzed and included in this report, documenting 
their effect on block development (Section 6.3.3). 
The data and information 
provided in this model report 
are intended to fully address 
the requirements of this 
agreement. 
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Drift Degradation Analysis 
Table 6-53. Repository Design and Thermal-Mechanical Effects KTI Agreement Items Addressed in This Model Report (Continued) 
Agreement 
Item Approach and Section Reference Status of Agreement 
RDTME 3.17 The approach for determining the effective maximum rock size has been revised in this model report. The 
approach of varying the joint geometry input to UNWEDGE is no longer applied. The maximum rock size 
and shape is taken directly from the 3DEC output, which includes the variation in joint strike, dip, spacing, 
and persistence. The variation of joint geometry parameters is based on field mapping data from the ESF, 
which has been input into the rockfall model (Sections 6.1.6 and 6.3). 
The data and information 
provided in this model report 
are intended to fully address 
the requirements of this 
agreement. 
RDTME 3.19 (1) In this revision of this model report, the DRKBA analyses provide a confirmatory role in the assessment of 
drift degradation. The primary analysis for degradation of nonlithophysal rock is provided using 3DEC 
(Section 6.3), while lithophysal rock is analyzed using UDEC (Section 6.4). An appropriate range of joint 
strength properties has been applied as documented in Section 6.3.1.6. Long-term degradation has been 
accounted for as documented in Section 6.3.1.5. 
(2) An analysis of block sizes based on the full distribution of joint trace length data has been included in this 
report (Sections 6.1.4 and 6.1.6), including the available small joint trace length data (Section 6.3.3). 
(3) As indicated above, the DRKBA results now provide a confirmatory role in the assessment of drift 
degradation. 3DEC has replaced DRKBA as the primary code for analyzing structural block development in 
the nonlithophysal rock units. The 3DEC and DRKBA results are in good agreement (Section 7.7.5). 
(a) Appropriate boundary conditions for thermal and seismic loading have been included in 3DEC as 
documented in Section 6.3.1.1. 
(b) A total of 50 fracture patterns have been analyzed, which were drawn from the same fracture population 
used in the DRKBA analyses (Section 6.3.1.1). 
(c) Thermal and mechanical properties for rock blocks and joints are available in the Technical Data 
Management System as documented in Section 4.1. 
(d) Long-term degradation of joint strength has been included as documented in Section 6.3.1.5. 
(e) Site-specific ground motion time histories appropriate for postclosure period have been modeled as 
documented in Sections 6.3.1.2 and 6.4.2.2. 
The data and information 
provided in this model report 
are intended to fully address 
the requirements of this 
agreement. 
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7. VALIDATION 
7.1 INTRODUCTION 
This section contains a discussion of the activities that were conducted to validate the mechanical 
material models and their implementation within qualified discontinuum numerical programs for 
mechanical representation of the repository host rocks. It is noted that the term model here 
refers first to the development and validation of the mechanical material models or 
representations for the two specific repository host rock types: lithophysal and nonlithophysal 
rocks. Secondly, validation refers to the examination of the implementation of these material 
models in a general numerical modeling scheme. In the case of the lithophysal rock, it is 
necessary to first discuss the existing laboratory database as a precursor to discussion of the 
implementation of this data in a numerical scheme. Validation of this implementation is 
addressed through comparison examples of the models to field and laboratory data. 
Corroborating/supporting data, models, and information that are used to complete the model 
validation activities include the following: 
 Confidence Building During Model Development to Establish Scientific Basis and 
Accuracy for Intended Use (Section 7.2.1) 
- Cundall and Strack 1979 [DIRS 162194] 
- Itasca Consulting Group 2002 [DIRS 160331] 
- Konietzky 2003 [DIRS 162198] 
 Confidence Building During Development of a Mechanical Material Model for 
Lithophysal Rocks and Selection of Input Parameters (Sections 7.3 and 7.4) 
- Hoek 2000 [DIRS 160705] 
- Itasca Consulting Group 2002 [DIRS 160331] 
- Potyondy and Cundall 2001 [DIRS 156895] 
- Price et al. 1985 [DIRS 106602] 
 Confidence Building During PFC Model Development (Section 7.5.1) 
- Itasca Consulting Group 2002 [DIRS 160331] 
- Price 1986 [DIRS 106589] 
- Price et al. 1985 [DIRS 106602] 
 Post-Development Validation for the PFC Model (Section 7.5.2) 
- Potyondy 2003 [DIRS 165550] 
- Potyondy and Cundall 2001 [DIRS 156895] 
 Confidence Building During Development of the Lithophysal Rockfall Model 
(Sections 7.6.1 and 7.6.4) 
- Itasca Consulting Group 2002 [DIRS 160331] 
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Drift Degradation Analysis 
 Post-Development Validation for Lithophysal Rock (Section 7.6.5) 
- Hoek 2000 [DIRS 160705] 
- MO0001SEPDSTPC.000 [DIRS 153836] 
- MO0002ABBLSLDS.000 [DIRS 147304] 
- MO0007SEPDSTPC.001 [DIRS 153707] 
- MO0107SEPDSTPC.003 [DIRS 158321] 
- MO0202SEPDSTTV.001 [DIRS 158320] 
- MO9807DSTSET01.000 [DIRS 113644] 
- MO9906DSTSET03.000 [DIRS 113673] 
- Price 1986 [DIRS 106589] 
- Price et al. 1985 [DIRS 106602] 
- Senseny 1993 [DIRS 162017] 
- Williams 2001 [DIRS 159516] 
 Post-Development Validation for Nonlithophysal Rock (Section 7.7) 
- Itasca Consulting Group 2002 [DIRS 160331] 
- GS030283114222.001 [DIRS 161913] 
- Senseny and Pucik 1999 [DIRS 168479] 
The scope of the validation and the order of presentation are as follows: 
 Lithophysal rocks 
- Mechanical Material BehaviorA discussion of the mechanical behavior of the 
lithophysal rocks is presented as the basis for development of the mechanical material 
model. The properties of this rock are controlled by the degree of lithophysal 
porosity as well as the interlithophysal fracturing. The lithophysae vary in size, 
shape, and in porosity vertically within the flow, but are distributed relatively 
uniformly locally within each unit. Since the diameter of the lithophysae are 
generally much less than the tunnel diameter, and, further, because they are uniformly 
distributed, a two-dimensional, isotropic equivalent mechanical material model can 
be used to describe their response to gravitational, thermal, and seismic loading. The 
mechanical material properties of the upper (Tptpul) and lower (Tptpll) lithophysal 
units of the Topopah Spring formation have been determined from laboratory 
compression testing on large (11.5-in and 10.5-in diameter) cores, and from in situ 
flatjack (slot) compression testing in the ESF main loop and ECRB Cross-Drift. 
- Particle Flow Model of Rock Mass BehaviorThe purpose of the PFC program is 
primarily as a simulation tool for developing a detailed understanding of the effects of 
lithophysal porosity on rock mass behavior. The program is used to supplement 
limited field testing by providing a means for examining the effects of lithophysae 
variability on rock mass properties (i.e., as a supplement to laboratory and field 
testing). A mechanical material model for representing the elasticity and yield of 
these rocks is developed from the basic laboratory data using a micromechanical 
numerical model (i.e., PFC). The PFC model predictions are compared to laboratory 
measured rock properties as a means of validation. The drift degradation analyses 
ANL-EBS-MD-000027 REV 03 7-2 September 2004 

Drift Degradation Analysis 
include time-dependent rock mass behavior modeled using the PFC model that 
incorporates a stress corrosion cracking representation. The PFC stress corrosion 
modeling approach provides a representation of subcritical crack growth in rocks that 
embraces both the microscopic processes of reactions and thermal activation at crack 
tips and the more mesoscopic processes of microcrack-microstructure-macrocrack 
interaction. 
- Lithophysal Rockfall Mechanical Model Component ValidationAlthough the PFC 
program could theoretically be used to model tunnel-scale stability issues, the 
simulation times are too long for existing computer resources. Therefore, it is 
necessary to develop a simpler, engineering-based approach to represent the potential 
yielding and fracturing behavior of lithophysal rock. This is done by creating an 
equivalent lithophysal mechanical model, which is implemented in the UDEC 
discontinuum program. The equivalent model is first calibrated such that it 
reproduces the basic laboratory mechanical response (as well as the PFC model 
response). Post-development model validation is accomplished via comparison to 
laboratory data, field observation of ECRB Cross-Drift tunnel mechanical response, 
and field thermal testing and brittle yield observed in the Drift Scale Thermal Test in 
the ESF. A continuum approach using different constitutive models is included to 
validate the UDEC Voronoi block model of lithophysal rock. Additionally, a 
comparison of the mathematical model implemented in the UDEC program to a 
number of other dynamic jointed rock models for modeling of blast-related, lined 
tunnel stability conducted for the Defense Nuclear Agency is also given as a 
confidence-building exercise. These blasting simulations provide a difficult 
challenge for the models. The UDEC code itself is commercial software that is 
widely used internationally for design and research in rock engineering. The program 
has been extensively validated against analytic solutions and design problems that are 
documented in the Users Manual (Itasca Consulting Group 2002 [DIRS 160331]). 
This validation provides a comparison of UDEC to several discontinuum and 
continuum-based programs for solution of tunnels subjected to dynamic loading. 
 Nonlithophysal rocks 
- Nonlithophysal Rockfall Model ValidationThe 3DEC discontinuum program is used 
to model the mechanical response of the fracture-rock block system in three 
dimensions. Fracture mechanical property data, in the form of shear strength and 
stiffness properties, are derived from rotary and direct shear test measurements as 
well as empirical correlations derived from underground mapping. Validation of the 
ability of the nonlithophysal rockfall model implemented in the 3DEC program to 
represent this direct shear response for fractures as derived from laboratory direct 
shear testing of large cores is presented. Validation of the dynamic stability of a 
jointed rock mass through comparison of 3DEC to instrumented field tests is also 
provided. Specific, well-documented field examples of tunnels subjected to 
earthquake loading that would be suitable as validation examples were not identified. 
Therefore, the validation of the mathematical model for nonlithophysal rock 
implemented in the 3DEC program is performed through corroboration with an 
alternative numerical model (i.e., the key-block software, DRKBA) to validate the 
ANL-EBS-MD-000027 REV 03 7-3 September 2004 

Drift Degradation Analysis 
model results on block size distribution and rockfall frequency, and through use of an 
external technical review to validate the overall modeling approach. The 3DEC code 
itself is commercial software that has been used in international rock engineering 
practice for nearly 20 years. 
7.2 MODEL VALIDATION LEVEL AND CRITERIA FOR VALIDATION BASED ON 
INTENDED USE 
The drift degradation analysis provides input to the Seismic Consequence Abstraction which, in 
turn, supplies input to the Seismic Scenario Class in the TSPA. The input to the Seismic 
Consequence Abstraction falls into two general areas: 
1. Rockfall  Damage to emplacement drifts as a function of peak ground velocity. The 
damage takes the form dynamic impact of rock blocks to the drip shield, and static 
load of the accumulated rubble on the drip shield following partial or complete 
collapse of the drift. 
2. Drift Profile Change  Breakout and enlargement of the emplacement drifts as a 
function of peak ground velocity for lithophysal and nonlithophysal units. 
Rockfall masses, velocities and drip shield impact locations, output from the drift degradation 
analyses, are used for structural stability and damage estimates of the drip shield. The Seismic 
Consequence Abstraction conservatively assumes that complete collapse of drifts in the 
lithophysal rocks occurs coincident with the 110-4 (approximate PGV of 0.5 m/sec) event. 
Static load from accumulated rubble was determined for the assumption of complete collapse of 
the emplacement drifts. The load distributions at 30 elements around the drip shield from six 
different complete collapse simulations (using the UDEC program) are used as input to structural 
analysis of the drip shield. 
The drift profile changes estimated from collapse of the drifts are used in the Abstraction of Drift 
Seepage to estimate changes in seepage flux to emplacement drifts in the event of a seismic 
event. Again, since complete collapse is assumed for the 110-4 level, then drift profile changes 
to two times the original diameter. 
Based on the intended use described above, the Technical Work Plan for: Regulatory Integration 
Modeling of Drift Degradation, Waste Package and Drip Shield Vibratory Motion and Seismic 
Consequences (BSC 2004 [DIRS 171520], Section 2.2.1) requires Level III Validation. 
7.2.1 Confidence Building During Model Development to Establish Scientific Basis and 
Accuracy for Intended Use 
Section 2.2.1.4 of the Technical Work Plan for: Regulatory Integration Modeling of Drift 
Degradation, Waste Package and Drip Shield Vibratory Motion and Seismic Consequences 
(BSC 2004 [DIRS 171520], Section 2.2.2) specifies criteria for confidence building during 
model development. Additionally, the development of the model should be documented in 
accordance with the requirements of Section 5.3.2(b) of AP-SIII.10Q. The development of the 
drift degradation models for lithophysal and nonlithophysal rock types have been conducted 
according to these criteria, as follows: 
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Drift Degradation Analysis 
1. Selection of input parameters and/or input data, and a discussion of how the selection 
process builds confidence in the model. [AP-SIII.10 Q 5.3.2(b) (1) and AP-2.27Q Attachment 
3 Level I (a)] 
The types and quality of the data selected as input builds confidence in the model. The 
geotechnical parameters and information that are inputs to the drift degradation analyses 
are site specific and have been collected by either field mapping or laboratory testing. 
The site specific geotechnical information includes: 
a. Fracture geometry 
b. Fracture mechanical properties 
c. Intact rock physical and mechanical properties 
d. Rock mass mechanical properties 
e. Seismic ground motion 
f. Rock thermal properties 
g. Repository layout information. 
Section 4.1 provides a discussion of the inputs and Table 4-1 identifies the data and 
design parameters used. A detailed discussion of the mineralogy, texture, fracturing, and 
porosity are given in Section 6.1.4 and in Appendix O. Further justification for the bases 
of selection of input parameters for the mechanical model for lithophysal rocks is covered 
in Section 7.3.2. Discussions of parameter ranges and uncertainties are covered in 
Section 6.5. Model assumptions have been described in Section 5. Thus, this 
requirement can be considered satisfied. 
2. Description of calibration activities, and/or initial boundary condition runs, and/or run 
convergences, simulation conditions set up to span the range of intended use and avoid 
inconsistent outputs, and a discussion of how the activity or activities build confidence in 
the model. Inclusion of a discussion of impacts of any non-convergence runs. 
[(AP-SIII.10Q 5.3.2(b)(2) and AP-2.27Q Attachment 3 Level I (e)] 
A general discussion of the overall model domain, rock mass characteristics, and 
generation of representative rock volumes are described in Section 6.1. Additional 
discussions are provided in section 7.4, 7.5, 7.6, and 7.7. The set-up of the 
thermal-mechanical simulations is described in Section 6.2 and Appendix C. The set-up 
of the three-dimensional simulations of drift degradation in the nonlithophysal units is 
described in Section 6.3 and Appendix C. The set-up of the simulations for drift 
degradation in the lithophysal units is discussed in Section 6.4. Calibration activities for 
the models are described in Sections 7.5.1 and 7.6.4. The input and output files for the 
simulations (all simulations completed and therefore converged) are listed in 
Appendix A. The simulation conditions accounted for the rock types encountered at the 
repository horizon (lithophysal and nonlithophysal units), account for the effects of 
thermal-mechanical coupling, and addressed the seismic loading using site-specific 
ground motions for the preclosure and postclosure periods. Therefore, the drift 
degradation analyses have addressed the conditions that span the range of its intended 
use. This requirement can be considered satisfied. 
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Drift Degradation Analysis 
3. Discussion of the impacts of uncertainties to the model results including how the model 
results represent the range of possible outcomes consistent with important uncertainties. 
[(AP-SIII.10 Q 5.3.2(b)(3) and AP-2.27Q Attachment 3 Level 1 (d) and (f)]. 
Treatment of uncertainty is discussed in Section 6.5. Uncertainties associated with model 
inputs are listed in the order of their impact on model results as follows: 
a. Rock mass mechanical properties data 
b. Seismic ground motion data 
c. Static fatigue and long-term strength data 
d. Fracture geometry data 
e. Intact rock physical and mechanical properties data 
f. Fracture mechanical properties data 
g. Rock thermal properties data 
Sensitivity studies that represent the range of possible outcomes of these parameters can 
be found in Sections 6.3.1 and Sections 6.4.2. An evaluation of alternative conceptual 
models can be found in Section 6.7. These criteria can be considered satisfied. 
4. Formulation of defensible assumptions and simplifications. [AP-2.27Q Attachment 3 
Level I (b)]. 
Discussions of assumptions are provided in Section 5. Simplifications required for the 
set-up of the three-dimensional analyses of the nonlithophysal units are discussed in 
Section 6.3.1. Discussions of the simplifications necessary for the two-dimensional 
analyses of lithophysal units are provided in Sections 6.4.1 and 7.6.2. 
5. Consistency with physical principles, such as conservation of mass, energy, and 
momentum. [AP-2.27Q Attachment 3 Level I (c)] 
Consistency with physical principles, such as conservation of mass, energy, and 
momentum is maintained through the selection and use of the appropriate geotechnical 
codes identified in Section 3. The numerical models discussed are commercially 
available software codes that have been extensively and rigorously tested. The programs 
have extensive Users Manuals that provide detailed derivation of the implementation of 
the governing equations, the mathematical description of the constitutive models, and 
verification of the accuracy and limitations of the programs through comparison of results 
to analytical solutions and example problems. These derivations and verification of 
ability to satisfy equilibrium and energy conservation are provided in the software Users 
Manual (Itasca Consulting Group 2002 [DIRS 160331]). Additional discussion can also 
be found in Section 7.6.7.2 regarding the use of UDEC and accounting for thermally 
induced expansion and stresses. 
The UDEC and 3DEC programs have been commercially marketed for approximately 
20 years, and are used extensively in the civil construction, mining, waste disposal, and 
geotechnical industries. The UDEC program, originally developed under contract to the 
U.S. Army Corps of Engineers Waterways Experiment Station in the mid-1970s, was 
initially used as a publicly available research tool in geomechanics. The predecessor of 
ANL-EBS-MD-000027 REV 03 7-6 September 2004 

Drift Degradation Analysis 
UDEC, the Rigid Block Model, was developed in the early 1970s (Itasca Consulting 
Group 2002 [DIRS 160331]). Both UDEC and 3DEC have been used for design studies 
and analysis of field experiments on nuclear waste repository projects in the 
United States, Canada, Sweden, United Kingdom, France, and Finland. The PFC 
program has been available commercially for approximately eight years, although its 
initial development as a program for research in soil and granular materials mechanics 
dates to the late 1970s (Cundall and Strack 1979 [DIRS 162194]). Currently, PFC is 
being used extensively as a research and design tool in geomechanics, powder 
compaction, structural geology and tectonics, oil production, etc. A recent symposium 
dedicated to use of PFC (Konietzky 2003 [DIRS 162198]) provides a description of the 
extent of application of this approach. 
7.2.2 Confidence Building After Model Development to Support the Scientific Basis of 
the Model 
Post-development model validation is to be performed using two or more methods as described 
in Section 5.3.2c of AP-SIII.10Q, Models, consistent with Level III model validation 
expectations. Validation of drift degradation models is accomplished by the following methods: 
 Corroboration with laboratory measurements or relevant observations not previously 
used to develop or calibrate the model 
 Corroboration with results of alternative mathematical models developed independently 
 Corroboration with data published in refereed journals or literature 
 Technical review by reviewers independent of the development, checking, and 
interdisciplinary review of the model documentation. 
The model validation activities discussed in this report follow the Level III validation 
requirements given in AP-SIII.10Q, at a minimum, while exceeding these requirements in some 
instances. No further activities are needed to complete this model validation for its intended use. 
7.2.3 Validation Criteria 
The prediction of rockfall requires that the models be able to represent: 
 The geologic structure that creates rock blocks surrounding the tunnels needs to be 
developed from field geologic mapping and represented in a realistic fashion in the 
numerical rockfall model. 
 The rock mass transient stresses induced by heating or ground motions 
 The interaction of the stresses and geologic structure, including, in the lithophysal rock, 
the potential for intact rock mass failure, fracturing, and formation of rock blocks that 
can detach themselves from the surrounding rock mass. 
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Drift Degradation Analysis 
With these points in mind, the criteria for a Level III validation of the drift degradation models, 
which address both adequacy of the scientific basis and accuracy of the model, are as follows: 
For mechanical models of nonlithophysal rock: 
 The geometry and variability of geologic structure need to be represented in the rockfall 
(3DEC) model in a qualitatively reasonable fashion. The synthetic fracture 
geometries and their variability developed by FracMan and used as input to 3DEC needs 
to be quantitatively calibrated against field-measured geometry data from detailed line 
surveys and full periphery geologic maps. This calibration, presented in Section 6.1.6 
ensures that the resulting block geometries will reflect in situ block structure. 
 The mechanical constitutive model of the fractures in 3DEC needs to be validated 
against the laboratory direct shear testing data. 
 The ability of the numerical model to accurately represent seismic boundary conditions 
and wave transmission through the rock mass needs to be verified. 
 The overall ability of the model to adequately represent the dynamic stressing effects of 
the ground motion on tunnel stability needs to be validated. 
For mechanical models of lithophysal rock: 
 The material model and analyses must account for the variability of rock mass properties 
resulting from variability of porosity in the lithophysal rock. 
 The material model and its numerical implementation must provide the ability to 
represent, in a realistic fashion, the yielding response of lithophysal rock in laboratory 
specimens and around tunnels, and the associated fracturing into blocks that can detach 
themselves from the surrounding rock. 
 The model must account for dynamic boundary conditions properly, and the subsequent 
interaction of dynamic stresses with rock mass yielding. 
7.3 DEVELOPMENT OF A MECHANICAL MATERIAL MODEL FOR 
LITHOPHYSAL ROCKS AND SELECTION OF INPUT PARAMETERS 
7.3.1 Introduction 
Prior to presentation of validation exercises for the lithophysal rockfall model, a description of 
the development of the model is given. This is done so that the basic considerations inherent in 
the model development that impact validation methods can be understood. 
7.3.2 Description of the Lithophysal Rocks 
The Tptpul and Tptpll comprise roughly 85 percent of the repository emplacement area. A 
detailed description of the mineralogy, texture, fracturing, and porosity are given in Section 6.1.4 
and in Appendix O. A review of the aspects of the geology important to the mechanical behavior 
ANL-EBS-MD-000027 REV 03 7-8 September 2004 

Drift Degradation Analysis 
is provided in this section. From a mechanical standpoint, the lithophysal rocks are composed of 
two distinct components: the matrix groundmass (including fracturing) and the porosity. The 
matrix groundmass is mineralogically, similar to the matrix of the nonlithophysal rocks. The 
primary difference in the groundmass of the Tptpll and Tptpul is in the type and extent of 
fractures. The Tptpll is intensely fractured with short-length, rough, and interlocking 
inter-lithophysal fractures which have a predominant vertical orientation with spacing on the 
order of centimeters. Figure 7-1a is a photograph of a 12-in. diameter core sample removed from 
the Tptpll showing the intensely fractured nature of this unit, creating intact block sizes a 
centimeters on a side. The rough and interlocking nature of the fractures is an important feature 
in that the periphery of excavations are stable under in situ conditions without failure along 
fracture boundaries. This is contrasted by Figure 7-1b showing the wall of an alcove in the 
Tptpul, off the ECRB Cross-Drift, showing the typical unfractured matrix groundmass in this 
unit. 
The rock mass porosity in the lithophysal units has been shown to be the primary physical factor 
that governs elastic and strength properties (Price et al. 1985 [DIRS 106602]). The porosity is 
found in three basic components: the matrix grain to grain porosity, which averages around 
10 percent in the Topopah Spring sub-units (Price et al. 1985 [DIRS 106602]); the lithophysal 
void porosity; and the porosity of alteration, which includes lithophysal rims and spots. 
Figure 7-2 shows the variation in lithophysal cavity percentage within the Tptpll in the ECRB 
Cross-Drift as determined by direct tape and angular measurement (Appendix O). This plot 
shows that the lithophysal cavity porosity varies from approximately 10 to 30 percent with 
variability on a scale of 5 to 10 m. 
The lithophysal cavities vary in size and shape, with characteristics that are somewhat different 
in the Tptpul and Tptpll. 
The lithophysae in the Tptpul: 
 Tend to be smaller (roughly 1 to 10 cm in diameter) 
 Are more uniform in size and distribution within the unit 
 Vary in infilling and rim thicknesses 
 Have a volume percentage that varies consistently with stratigraphic position 
 Are stratigraphically predictable. 
In contrast, the lithophysae in the Tptpll: 
 Tend to be highly variable in size, from roughly 1 cm to 1.8 m in size 
 Have shapes that are highly variable from smooth and spherical to irregular and sharp 
boundaries 
 Have infilling and rim thickness that vary widely with vertical and horizontal spacing 
 Have volume percentages that vary consistently with stratigraphic position 
 Are stratigraphically predictable. 
ANL-EBS-MD-000027 REV 03 7-9 September 2004 

Drift Degradation Analysis 
a) 
b) 
NOTE: The core (top photo) was drilled with water and the porous rims and fractures (many of which have rims) 
retain water and appear dark, whereas the matrix-groundmass, which has minimal porosity, dries in a 
relatively short amount of time. 
Figure 7-1. (a) Matrix Fracturing in the Tptpll in 12-in-Diameter Core and (b) Lack of Fracturing in Matrix 
of Tptpul as Seen in the Wall of Alcove 8 off the ECRB Cross-Drift 
ANL-EBS-MD-000027 REV 03 7-10 September 2004

Drift Degradation Analysis 
In general, the lithophysae diameter is much less than the diameter of the emplacement drifts 
(5.5 m). As shown in Figure 7-2, the variability of the porosity along the ECRB Cross-Drift is 
on the order of 5 m (additional data analysis is provided in Appendix O). In representing the 
mechanical response of the lithophysal rocks, it is judged to be adequate to use a 
two dimensional, cross-sectional modeling approach in which the rock mass is considered to be 
of constant porosity, homogeneous and isotropic within that section. 
7.3.3 Model Requirements for Drift Degradation Prediction 
To represent drift degradation mechanisms and rockfall, the mechanical model and the numerical 
method in which it is embedded must have the following capabilities: 
 The model must provide a general capability of modeling in situ stress and thermal and 
seismic loading of the rock mass. 
 The model must represent the effects of porosity and matrix pre-existing fracturing on 
the elastic and strength properties of the material. 
The model must allow internal fracturing and detachment of the rock mass (i.e., rockfall) to 
occur in response to gravity, thermal effects, and seismic shaking. 
) 
0 
10 
20 
30 
40 
50 
60 
Percent cavities from line (tape and angularsurveys 
1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 
Station 
Percen t 
Tape Percent Tape 10-maverage Tape 20-m average Angular Percent 
Source: Tape percent and Angular percent from DTN: GS021008314224.002 [DIRS 161910]; Tape 10-m average 
and Tape 20-m average from DTN: MO0408MWDDDMIO.002, file Drift Deg AMR AC T-Trav.xls. 
Figure 7-2. Variation in Lithophysal Cavities in the Tptpll in the ECRB Cross-Drift from Top (Left) to 
Bottom of the Sub-Unit as Estimated by Tape and Angular Measurement Collected at 5-m 
Intervals 
ANL-EBS-MD-000027 REV 03 7-11 September 2004 

Drift Degradation Analysis 
The above model requirements imply the necessity of use of a discontinuum approach to 
representation of the rock mass, as described in Sections 6.3.1 and 6.4.2. 
7.3.4 Laboratory and Field Database for Constitutive Model Development 
The development of the laboratory and field database of material properties for lithophysal rocks 
is presented in detail in Appendix E, Section E.4. This section describes large core laboratory 
testing program that has been used to define the relationship of compressive strength and 
Youngs modulus to lithophysal porosity content. The use of the PFC model (described later) to 
extrapolate the impact of lithophysae size, shape and distribution on the mechanical properties is 
also presented, and the proposed bounding ranges determined. The rock mass mechanical 
properties ranges are subdivided into five equally divided categories for subsequent sensitivity 
studies as described in Section 6.4. These properties provide the basis for the model 
development described in Section 7.4. 
7.4 STRATEGY FOR DEVELOPMENT OF A MECHANICAL MATERIAL MODEL 
FOR LITHOPHYSAL ROCKS (CONFIDENCE BUILDING DURING MODEL 
DEVELOPMENT) 
7.4.1 Continuum-Based Approach to Representing Rock Masses 
The objective of the drift degradation analyses presented in this report is to predict the amount 
and particle size distribution of rockfall in the repository drifts due to stresses induced by the 
heat released by the emplaced waste, due to seismically related ground motions, and due to 
time-dependent strength loss of the rock mass. A standard approach for solving excavation 
stability problems in geotechnical engineering is the use of numerical models based on 
continuum mechanics (Figure 7-3). This alternative conceptual model is discussed in 
Section 6.7. Such an approach is quite effective if the rock mass, in response to stressing, 
eventually arrives at a state of mechanical stability and where the primary purpose of the 
modeling is the computation of stress redistribution around an opening or determination of the 
final displacement profiles. However, difficulties are encountered if a continuum model is used 
for prediction of a mechanical system (i.e., a tunnel) that does not arrive at stable condition. 
Continuum models use constitutive relations to describe the mechanical behavior of a material. 
In rock, the mechanical effects of fractures and other features are lumped into the constitutive 
model, often using empirically based methods that take into account the spacing and continuity 
of the fractures, the roughness and alteration of the fracture surfaces, and the 
laboratory-determined properties of the intact rock blocks (e.g., Hoek 2000 [DIRS 160705]). 
ANL-EBS-MD-000027 REV 03 7-12 September 2004 

Drift Degradation Analysis 
NOTE: The continuum approach models yield of the rock through use of a material model that enforces plasticity 
relations (note marked elements). Rock breakage and separation is not possible in this approach. The 
discontinuum approach also represents the rock mass using similar material models, but provides the 
capability for the rock mass to fracture and break apart on potential fracture surfaces. 
Figure 7-3. Schematic Illustration of Continuum (Left) and Discontinuum (Right) Approaches to Modeling 
Drift Stability 
A linearly elasticperfectly plastic material model with Mohr-Coulomb yield criteria is a 
constitutive model often used to represent mechanical behavior of a rock mass. Because the 
material strength of a perfectly plastic, Mohr-Coulomb model does not decrease as a function of 
plastic deformation, this model will show indications of material yielding (i.e., plastic 
deformation) in different portions of the model, but will never actually predict the instability or 
rockfall. To be able to predict rockfall, it is necessary to use some kind of strain-softening 
constitutive model, in which strength degrades as a function of deformation after the 
peak-strength of material has been reached. However, the strain-softening model, within the 
framework of continuum mechanics, is the subject of much research and debate, and not 
applicable with any degree of certainty to estimates of physical fracture and rockfall as required 
here. For this reason, continuum modeling methods are not used to represent rockfall. 
7.4.2 Discontinuum Approach to Representing Rock Masses 
The estimation of rockfall requires that the modeling technique and mechanical material model 
be capable of representing physical fracture of the rock mass and separation of the intact rock 
mass into blocks of material. In particular, an estimate of the size distribution of particles is 
desired. This requires the use of a discontinuum numerical method (i.e., a method in which slip 
and separation of contacting rock blocks can be estimated [Figure 7-3]). The following strategy 
is based on use of discontinuum methods for development of a material model for lithophysal 
rocks. 
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Drift Degradation Analysis 
7.4.3 Strategy for Discontinuum Material Model Development 
Typically, development of a mechanical material model for a rock mass is based on extensive 
laboratory testing of rock core, determination of strength and moduli reduction factors via in situ 
mapping of rock quality, followed by validation against field measurement. Such an approach to 
development of a material model for the lithophysal rocks presents a number of challenges. As 
discussed in the previous section, it is problematic to conduct an extensive mechanical properties 
testing program on lithophysal rocks due to the need to obtain and test large cores or to create 
large in situ samples from sawing or drilling. Additionally, direct determination of the true 
triaxial stress behavior of samples is difficult since pressure vessels to provide confinement to 
large core samples are not available. It is also not possible to conduct testing on a wide range of 
lithophysae shapes and size distributions. Finally, geotechnical classification systems are not 
particularly applicable to the lithophysal rocks due to a lack of contemporary experience in 
construction and testing in this type of rock mass. 
As described previously, the database available for model development includes: 1) uniaxial and 
triaxial compression and direct pull tensile testing of nonlithophysal rock; and, 2) uniaxial 
compression testing of large scale cores and in situ blocks of lithophysal tuff. To overcome 
these sampling and testing limitations, an alternative strategy is used here, as illustrated in 
Figure 7-4. In this section, an approach is described in which a physics-based 
micromechanical, discontinuum numerical modeling programthe PFC program (Itasca 
Consulting Group 2002 [DIRS 160331]; Potyondy and Cundall 2001 [DIRS 156895])is used 
as a numerical laboratory to simulate and test the basic deformation and failure response 
mechanisms of lithophysal tuff. The PFC program was chosen due to its ability to simulate the 
physics of deformation and fracture of a bonded granular matrix that contains void space of 
varying shape, size and porosity. The program is first validated against the existing laboratory 
compression data. Specifically, it is demonstrated that a detailed understanding of the basic 
physical mechanisms of the rock mass behavior can be obtained without resorting to empiricism 
or complex constitutive modeling. The model is then used to extend the laboratory data by 
conducting numerical experiments on simulated samples of lithophysal tuffs at various physical 
conditions of porosity, lithophysae shape and distribution, as well as various levels of 
confinement and applied stress. From this modeling, it is possible to understand the size-scaling 
and variability issues introduced by lithophysae shape and distribution, and their impact on rock 
mass properties and failure criteria. 
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Drift Degradation Analysis 
Laboratory Uniaxial 
Compression/Tension Non-
Lithophysal Tuff 
Calibrate PFC Synthetic Matrix 
Material Model 
Predict Effect of Lithopohysal 
Porosity on Material Response 
Laboratory Uniaxial 
Compression/Tension 
Lithophysal Tuff 
In Situ Compression Slot 
Testing 
Validate Lithophysal Model 
Against Lab and In Situ 
Compression and Tension 
Data 
Extrapolate Triaxial 
Compression Response and 
Develop Yield Criteria Using 
PFC as Numerical Laboratory 
Embed Constitutive Model into 
UDEC for Drift Scale 
Validate UDEC Model Against: 
Degradation Analyses 
ECRB Observations in Lower 
Lithophysal Unit 
Drift Scale Thermal Test Roof 
Slabbing 
Laboratory Compression Data 
from Lithophysal Rocks 
Figure 7-4. General Approach to Validation of Mechanical Material Model for Lithophysal Rocks 
Although possible, it is impractical to use the PFC program as a general modeling tool to 
investigate drift degradation due to the extensive computing demands that result from large-scale 
problems. Instead, the material model developed from the testing and PFC extrapolation is 
embedded in the UDEC discontinuum program, which has been used efficiently to examine 
tunnel-scale seismic, heating and time-degradation issues (see Section 6.4.2). 
7.5 VALIDATION OF THE PFCA MICROMECHANICAL MODEL 
REPRESENTATION OF THE MECHANICAL BEHAVIOR OF LITHOPHYSAL 
ROCK 
7.5.1 The PFC Model (Confidence Building During Model Development) 
The Particle Flow Code has been qualified for use as indicated in Section 3. The PFC approach 
(Figure 7-5) represents rock as a number of small, rigid, spherical grains that are bonded together 
at their contacts with a shear and tensile strength, as well as a grain to grain friction angle after 
the contact bond has been broken. If cementing exists between grains, it can be represented 
with a parallel bond that provides a rotational resistance as well. Details on the mechanics of 
the PFC program are provided in Itasca SoftwareCutting Edge Tools for Computational 
Mechanics (Itasca Consulting Group 2002 [DIRS 160331]). The deformability of the contacts 
between particles is represented by a normal and shear stiffness at the contact point. Porosity is 
ANL-EBS-MD-000027 REV 03 7-15 September 2004 

Drift Degradation Analysis 
developed naturally in the model by control of the shape and size of void space between chains 
of bonded grains. The contact properties and porosity distribution are referred to as 
microstructural properties. Thus, the input conditions necessary for the model are very simple, 
only contact strength and stiffness. However, as shown below, extremely rich constitutive 
behavior may develop naturally based on porosity and the few straightforward input properties 
and their variability throughout the rock. 
When load is applied to the grain assembly, forces are transmitted across contacts. If the shear 
or tensile strength of the contact is reached, failure will occur, and the adjacent particles are free 
to slide past one another, or to separate. In either case, a fracture is formed and the forces must 
reorient in some fashion, thus redistributing loads. Realistic failure mechanisms may then 
develop which can be compared to those observed in the laboratory. Calibration of the model 
against laboratory testing is necessary via sensitivity studies in which the contact strength and 
stiffness values are varied and the macroscopic stress-strain response is compared to that 
monitored. 
A discussion of the PFC calibration and extrapolations is provided in this section, including a 
summary of the approach and results. The PFC program in both two- and three-dimensions was 
calibrated first against laboratory strength tests of nonlithophysal rocks. Since it is considered 
that the matrix or groundmass material of the Tptpul, Tptpmn, and Tptpll is essentially the same, 
both mineralogically and mechanically, it is necessary to first make certain the PFC model can 
represent the mechanical response of the material without lithophysal voids. Once the matrix 
material response is identified, then representation of the mechanical behavior of the lithophysal 
material is possible with the simple addition of void space (assuming the consideration of similar 
matrix is correct). 
The tuff can be divided into lithophysal and nonlithophysal types. These two rock types differ 
significantly in their microstructural and mechanical properties. In the lithophysal tuff, the vast 
majority of the porosity is concentrated in lithophysae and surrounding vapor-phase altered 
material, whereas in the nonlithophysal tuffs porosity is more evenly distributed throughout the 
material. The nonlithophysal tuffs have effective porosities that range from approximately 0.1 to 
0.4 (Price et al. 1985 [DIRS 106602], Figure 15). The high-porosity nonlithophysal tuffs have 
large effective porosities because of the voids between grains, whereas similar effective 
porosities in lithophysal tuffs arise from the presence of lithophysae and vapor-phase altered 
material (Price et al. 1985 [DIRS 106602], pp. 25-28). The matrix fabric of the lithophysal tuff 
is microscopically identical to that of moderately to densely welded nonlithophysal tuff. Price 
et. al. (1985 [DIRS 106602]) divide the lithophysal tuff into the following three components: a 
fine-grained matrix (M), large lithophysae (L), and vapor-phase altered material (A) surrounding 
the lithophysae. Based on the approach described by Price et al. (1985 [DIRS 106602]) for 
determining bulk properties of lithophysal tuff, the porosity of component-i is denoted by 
(V.)
fi = 
Vi 
i , i = {M, A, L} (Eq. 7-1) 
ANL-EBS-MD-000027 REV 03 7-16 September 2004 

Drift Degradation Analysis 
and the volume fraction of component-i by 
Pi = Vi i = {M, A, L} (Eq. 7-2) 
V , 
where (V.)i is the void volume of component-i, Vi is the solid volume of component-i and V is 
the total volume. The total porosity can be expressed as 
() +(VV 
) +(V.)L =fMPM L
f=
V. M . A +fAPA +f PL (Eq. 7-3) 
The PFC material models lithophysal tuff as a base material with discrete voids. The base 
material represents both the matrix (M) and the vapor-phase altered material (A) in a smeared 
fashion, and the discrete voids represent the lithophysae (L). The void porosity, nv, defined by 
Equation 7-1, of the PFC model corresponds with the volume fraction, Pi, of the lithophysal tuff. 
The relative distributions of these components for the lithophysal tuff and the PFC model are 
shown in Figure 7-6. Note that the PFC base material has an inherent porosity (approximately 
0.17 and 0.36, for PFC2D and PFC3D, respectively) that does not correspond with that of the 
tuff; the tuff microstructure at this small-scale is not reproduced by the PFC material. Only the 
void porosity of the PFC material can be compared with the lithophysal volume fraction. Also 
note that PA as a function of PL is not known, but PA must approach zero as PL approaches zero. 
The microproperties of the PFC material are kept constant for the values of nv = Pi , and thus, the 
PFC materials with low void porosity are overestimating the weakening effect of the vapor-phase 
altered material. One approach to incorporate this effect in the PFC models would be to modify 
the PFC microproperties as a function of nv such that they match the laboratory data for the 
lithophysal tuff in the non-zero range of nv and match the nonlithophysal tuff when nv = 0. This 
approach has not been adopted here. 
The void-filled PFC material can be calibrated by matching the variation of modulus and 
strength with volume fraction of lithophysal tuff. The laboratory data used for calibration is that 
shown in Appendix E (Table E-9). The nonlithophysal tuff exhibits a size effect such that larger 
specimens are weaker with unconfined compressive strength values ranging from approximately 
190 to 90 MPa as specimen diameter ranges from 25 to 230 mm (Price 1986 [DIRS 106589]). 
The form of a size effect for lithophysal tuff has not been identified, but is considered to be 
similar to that of the nonlithophysal tuff. The effect of specimen size is not investigated for the 
PFC models; instead, the PFC models are either 1:1 or 2:1 aspect ratio specimens of one-meter 
diameter, and microproperties are chosen to match the laboratory data. 
ANL-EBS-MD-000027 REV 03 7-17 September 2004 

Drift Degradation Analysis 
NOTE: Mechanical response in the PFC program is governed by the strength and deformability relationships of the 
bonds between rigid particles. Two bond types are provided: a simple contact bond (left), and a parallel 
bond (right), which simulates cement between particles that resists moments as well as shear and normal 
loads. 
Fn = normal contact force .Us = relative shear displacement increment 
kn = 
Un = 
normal stiffness 
relative normal displacement 
.MI = 
= bending moment increment for bond 
moment of inertia of the bond cross-section 
.Fs = 
ks = 
shear contact force increment 
shear stiffness 
.. = 
Fs = 
increment of rotational angle 
shear contact force 
.Us = relative shear displacement increment  = contact friction coefficient 
n.F = axial-directed force increment for bond smax = maximum tensile stress acting on the bond 
nk = bond normal stiffness 
periphery 
tmax = maximum shear stress acting on the bond 
A = area of bond cross-section periphery 
.Un = relative normal displacement increment R = particle radius 
s.F = shear-directed force increment for bond nF = axial-directed force for bond 
sk = bond shear stiffness sF = shear-directed force for bond 
Figure 7-5. The Basic Mechanics of the PFC Program 
ANL-EBS-MD-000027 REV 03 7-18 September 2004 

Drift Degradation Analysis 
0.356 
Figure 7-6. Relative Distributions of the Three Components of Lithophysal Tuff for (a) Real Material 
(Price et al. 1985 [DIRS 106602]) and (b) PFC Materials 
7.5.2 Validation Exercises for the PFC Model 
The PFC model of lithophysal rock is used to extrapolate both quasi-static and time-dependent 
compression data from existing laboratory test data to examine the impacts of variable size, 
shape and distribution of lithophysae. This extrapolated information is used to assist in defining 
the bounding ranges of in situ properties of lithophysal rocks. These ranges are, in turn, used as 
input to drift-scale calculations of emplacement drift stability resulting from in situ, thermal and 
seismic loading as well as time-dependent strength loss. Since the PFC model provides input to 
drift degradation studies, it is considered to require a Level III validation, which requires at least 
two post-development validation exercises. The following section provides three 
post-development exercises. The first example tests the ability of the PFC model to provide a 
reasonable reproduction of the mechanical response of lithophysal rock as determined from large 
core laboratory testing. The second validation example tests the ability of the PFC model to 
reproduce the basic creep response of the nonlithophysal matrix material through comparison of 
the model output to the primary, secondary and tertiary creep response as observed from 
laboratory creep experiments. The third validation exercise presented is an external technical 
review of the PFC model for representation of the time-dependent response of Topopah Spring 
tuff. 
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Drift Degradation Analysis 
7.5.2.1 PFC Post-development Validation Exercise 1  Simulation of the Stress-Strain 
Behavior of Nonlithophysal and Lithophysal Rock in Compression and Tension 
The PFC2D and 3D models were first calibrated against laboratory strength and modulus data 
from large diameter core testing at an approximate mean lithophysal porosity of 15 percent using 
an idealized model that represented lithophysae as circular voids that are uniformly distributed 
through the samples. The purpose of the calibration is to set an approximate value for the 
particle bond strength and stiffness. This calibration was followed by validation through 
prediction and comparison of the model to the entire large-core compression testing from cores 
obtained from the Tptpll and Tptpll in the ECRB Cross-Drift and from the Busted Butte site 
(see Section E.4). Additionally, the mode of failure of rock samples in compression must be 
similar to that observed in the laboratory. 
A sensitivity analysis of the PFC model is then conducted using model samples developed from 
field panel maps created in the Tptpll in the ECRB Cross-Drift. These panel maps 
(see Appendix O) are used to create PFC samples by stenciling the irregular shapes and 
distributions from 18 panel maps to create realistic lithophysae geometries for the PFC test 
samples. These samples are then used to conduct simulated uniaxial compression tests to 
examine the impact of realistic lithophysae geometries on variability in mechanical properties. 
Figures 7-7 and 7-8 show PFC2D and PFC3D models of several lithophysal rock samples at 
increasing void ratios that are used to conduct numerical laboratory experiments. Particles are 
removed to create circular or spherical voids with random location. 
Examples of the predicted stress-strain behavior and post-test fracturing response of simulated 
uniaxial compression simulations for nonlithophysal and lithophysal samples with circular voids 
and void porosities of 0, 10 and 20 percent are shown in Figures 7-9 to 7-11. The models show 
numerous physical features that correspond well to those observed in laboratory response. The 
nonlithophysal samples fail through formation of conjugate shear fractures composed of 
coalescing tensile bond breakages. The response is highly elastic to the point of brittle failure 
(i.e., there is little observable hysteresis on load-unload cycles directly up to the yield limit). 
This behavior is a function of the uniform grain structure and welding of the matrix material. 
The addition of lithophysal voids results in significant decreases in both the strength and 
modulus. The failure mechanism in this case is a function of tensile splitting between adjacent 
lithophysal voids due to induced tensile stresses in the thin webbing between voids. The PFC 
model shows that the failure strength is simply governed by the ratio of void span to webbing 
thickness. With voids randomly distributed, the thinnest of webbing will fail first, shunting load 
to other solid webs, resulting in progressive failure of the weakest link. The resulting 
stress-strain behavior becomes less brittle in nature due to this progressive failure mode. 
ANL-EBS-MD-000027 REV 03 7-20 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 7-21 September 2004 
NOTE: Circular Voids; Radius = 83 mm; nv = 0.05, 0.10, and 0.20. 
Figure 7-7. PFC2D Unconfined Compressive Strength Test Specimens 
NOTE: Spherical voids; Radius = 83 mm; nv = 0.05, 0.10, and 0.20. 
Figure 7-8. PFC3D Unconfined Compressive Strength Test Specimens 

Drift Degradation Analysis 
Axial 
Axial Stress 
NOTE: Final sample damage state is plotted with bond failures in tension (red) and shear (blue). Samples fail with 
typical conjugate shear fractures. Two confining pressures are shown: 0.1 MPa (top) and 3 MPa (bottom). 
The primary impact of confinement is slightly increased peak and residual strength. 
Figure 7-9. PFC2D Simulation of Confined Compression of 2:1 L:D (Length:Diameter) Samples of 
Nonlithophysal Material (nv = 0) Composed of Several Thousand Bonded Particles 
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Drift Degradation Analysis 
Axial 
Axial Stress 
NOTE: Final sample damage state is plotted with bond failures in tension (red) and shear (blue). Two confining 
pressures are shown: 0.1 MPa (top) and 3 MPa (bottom). Samples fail in an axial splitting mode which is 
most pronounced in the low confinement model at left. Note that confinement increases peak strength with 
increased residual strength. 
Figure 7-10. PFC2D Simulation of Confined Compression of 2:1 L:D (Length:Diameter) Samples of 
Lithophysal Material (nv = 0.10) Composed of Several Thousand Bonded Particles 
ANL-EBS-MD-000027 REV 03 7-23 September 2004 

Drift Degradation Analysis 
Axial 
Axial Stress 
NOTE: Final sample damage state is plotted with bond failures in tension (red) and shear (blue). Two confining 
pressures are shown: 0.1 MPa (top) and 3 MPa (bottom). Samples fail due to tensile splitting between 
adjacent voids in the low confinement model at left. Note that confinement results in a slight increase in 
peak strength with increased residual strength at high values of void porosity. 
Figure 7-11. PFC2D Simulation of Confined Compression of 2:1 L:D (Length:Diameter) Samples of 
Lithophysal Material (nv = 0.20) Composed of Several Thousand Bonded Particles 
ANL-EBS-MD-000027 REV 03 7-24 September 2004 

Drift Degradation Analysis 
The impact of lithophysae on direct tension strength follows the same general mechanism: the 
voids result in less area of solid rock for any given cross-section . For a constant applied force, 
the stress in the remaining solid will be higher, thus reducing the overall averaged tensile 
strength of the sample. Particles are removed to create circular or spherical voids with random 
location subject to the constraint that no two voids are closer than one-half of the void radius 
(17.1 mm mean void diameter and 41.5 mm minimum bridge length). 
The properties of the lithophysal tuff samples (i.e., Youngs modulus and unconfined 
compressive strength) from the ESF main loop and ECRB Cross-Drift (Appendix E, Table E-9) 
are plotted along with those of the circular-void PFC model in Figures 7-12 and 7-13, as a 
function of lithophysal porosity. Figure 7-14 presents the same laboratory and numerical test 
results in the form of unconfined compressive strength versus Youngs modulus. Both PFC 
models provide reasonable correspondence to the large core laboratory data. The PFC models 
show the same general decrease in both strength and modulus with lithophysal porosity. The 
PFC models are performed for circular, constant diameter lithophysal voids. As described in 
Appendix E, Section E4.1.4.1, the scatter in the laboratory data is a result of the variability in 
size, shape and distribution of the lithophysal voids. The PFC model was used to simulate 
compression testing of in situ variability of lithophysal voids on actual field-mapped sections of 
the Tptpll in the ECRB Cross-Drift. Figure 7-15 shows PFC test samples stenciled from field 
panel maps, and the corresponding stress-strain curves obtained from test simulations. The 
impact of actual lithophysal shape, size and distribution on the variability of uniaxial 
compression strength and modulus results in the same general trend of strength and modulus 
decrease with lithophysal porosity, but introduces a considerable scatter in the range of results. 
This scatter is primarily due to the distribution of the voids within a test sample, and, in 
particular, the non-uniformity of the voids. The distribution of thickness of the solid rock 
bridge between voids weakens the samples as the bridge size decreases. Figure 7-16 shows a 
comparison of the laboratory test data against the PFC modeling of test samples from field panel 
maps. It is seen here that, when the variability of the actual lithophysae structure and distribution 
are taken into account, the scatter in PFC model results fall within the range of the large core 
laboratory test results. Bounding ranges, as described in Section E.4, can then be assigned for 
the complete range of expected lithophysal mechanical response. 
This validation exercise shows that: 
 The PFC model can reproduce the general failure mechanism observed in the laboratory 
 i.e., tensile splitting between adjacent lithophysae 
 The PFC model can reproduce the general trend of strength and modulus as functions of 
the lithophysal porosity as seen in the test data 
 The PFC model successfully provides an explanation for the observed scatter in the 
strength and modulus as functions of the lithophysal porosity. The model shows that the 
variability is a result of the shape and distribution of the lithophysae within a sample 
volume. 
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Drift Degradation Analysis 
R2 =
R20 
5 
10 
15 
20 
25 
l) 
l(y = 20.245e-4.1815x 
0.9779 
y = 17.866e-3.457x 
= 0.9981 
Young's Moduus, E (GPaLithophysa Tuff DTNs: SN0208L0207502.001, 
SN0211L0207502.002) 
PFC2D 
PFC3D 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 
Void Porosity, nv 
Figure 7-12. Youngs Modulus Versus Void Porosity for Lithophysal Tuff and PFC Materials 
R2R20 
10 
20 
30 
40 
50 
iiu) 
l (y = 52.167e-5.9159x 
= 0.943 
y = 38.467e-4.792x 
= 0.9898 
Unconfned Compressve Strength, q (MPaLithophysaTuffDTNs: MO0301RCKPRPCS.001, 
SN0208L0207502.001, SN0211L0207502.002) 
PFC2D 
PFC3D 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 
Void Porosity, nv 
Figure 7-13. Unconfined Compressive Strength Versus Void Porosity for Lithophysal Tuff and PFC 
Materials 
ANL-EBS-MD-000027 REV 03 7-26 September 2004 

Drift Degradation Analysis 
50
Unconfined Compressive Strength, qu (MPa)
40
30
20
10
0
0 5 101520
Young's Modulus, E (GPa)
R2R2R2l (
y = 10.004e0.0579x 
= 0.6479 
y = 4.1467e0.1394x 
= 0.9687 
y = 5.9798e0.1067x 
= 0.984 
LithophysaTuf fDTNs: SN0208L0207502.001, 
SN0211L0207502.002) 
PFC2D 
PFC3D 
Figure 7-14. Unconfined Compressive Strength Versus Youngs Modulus for Lithophysal Tuff and PFC 
Materials 
ANL-EBS-MD-000027 REV 03 7-27 September 2004 

Drift Degradation Analysis 
Stress-Strain 
((Pa) 
(m/m) 
(m/m) 
Response 
Tensile 
Fractures 
Axial Stress Pa) Axial Stress 
Strain 
Strain 
Applied Axial Stress 
NOTE: Specimen is composed of several thousand bonded particles. Red lines are tensile fractures that have 
propagated between lithophysae to ultimately form a failure mechanism. Superimposed stress-strain curve 
illustrates impact of lithophysae distribution on strength, modulus and post-peak failure mechanism. Vertical 
axis is axial stress in Pa; horizontal axis is strain in m/m. 
Figure 7-15. Examples of Particle Flow Code Compression Tests Using Simulated Rock Specimens 
Developed by Stenciling Field Panel Maps in the Enhanced Characterization of the 
Repository Block 
ANL-EBS-MD-000027 REV 03 7-28 September 2004 

Drift Degradation Analysis 
10 
0 
0 5 1015202530 
20 
30 
40 
4 
5 
3 
2 
1 
Lith. tuff lab tests, room dry 
Lith. tuff lab tests, saturated 
Panel Map PFC2D data 
Base case properties 
characteristic 
Upper Bound 
Estimate 
Mean of Upper and 
Lower Bounds 
Lower Bound 
Estimate 
Young's Modulus (GPa) 
NOTE: Approximate upper and lower bounds are shown. 
Figure 7-16. Unconfined Compressive Strength Versus Youngs Modulus Showing Large Core Data and 
Results from PFC Panel Map Lithophysae Shape Study 
7.5.2.2 PFC Post-Development Validation Exercise 2  Comparison of PFC Stress 
Corrosion Model Ability to Reproduce Typical Primary, Secondary and 
Tertiary Creep Response of the Tptpmn 
The drift degradation analyses include time-dependent rock mass behavior modeled using the 
PFC model that incorporates a stress corrosion cracking representation. The PFC stress 
corrosion modeling approach provides a representation of subcritical crack growth in rocks that 
embraces both the microscopic processes of reactions and thermal activation at crack tips and the 
more mesoscopic processes of microcrack-microstructure-macrocrack interaction. The PFC 
stress corrosion model is described in detail by Potyondy (2003 [DIRS 165550]) and reviewed in 
Appendix S. The PFC stress corrosion model is calibrated by adjusting the particle bond 
strength and radius as a function of time to provide a match to the time-to-failure curve produced 
by performing a series of laboratory static fatigue tests (Appendix S, Figure S-27). The PFC 
stress corrosion model bypasses the need to idealize the rock in the classical Linear Elastic 
Fracture Mechanics sense, yet can itself reproduce the Linear Elastic Fracture Mechanics 
behavior. That is, to model static-fatigue behavior, there is no need to begin with a Linear 
Elastic Fracture Mechanics material, which is an elastic body with classical sharp cracks. Such 
discrete cracks form naturally in the PFC material as the result of bond breakages. The PFC 
Uniaxial Compressive Strength (MPa) 
ANL-EBS-MD-000027 REV 03 7-29 September 2004 

Drift Degradation Analysis 
material is comprised of complex grain-scale discontinuities, which induce the micro-tensions 
that drive the stress-corrosion process, and these discontinuities are not necessarily the same as 
the discontinuities in an elastic body with classical sharp cracks. This suggests that the PFC 
stress corrosion model may be more appropriate for use in modeling the physical behavior 
mechanisms of rock than a more idealized Linear Elastic Fracture Mechanics material. 
Much of the development of the PFC stress corrosion model was funded by Atomic Energy of 
Canada Limited and Ontario Power Generation during the years 1995-2001 as part of a joint 
thermal-mechanical stability study (Potyondy and Cundall 2001 [DIRS 156895]). One aim of 
this model development was to improve the fundamental understanding of short- and long-term 
rock-mass behavior around underground openings at ambient and elevated temperatures. The 
study was conducted in tunnels constructed in the Lac du Bonnet granites (Manitoba, Canada) as 
part of the joint Atomic Energy of Canada Limited and Ontario Power Generation Underground 
Research Laboratory project. 
The result of this work was the development and verification of the Bonded-Particle Model for 
Rock  a mechanistically based numerical model used for predicting excavation-induced 
rock-mass damage and long-term strength (by incorporating a damage process based on a 
stress-corrosion mechanism) in Lac du Bonnet granite (Potyondy and Cundall 2001 
[DIRS 156895]). 
A validation of the PFC stress corrosion model is to compare the general nature of 
time-dependency of the strain of rock samples when subjected to constant axial load. This test is 
typically termed a creep test, and involves rapid application of axial load to a rock sample to a 
specific load level that is typically greater than 80 or 90 percent of the considered strength of the 
material. This load is held constant while axial and lateral strain in the sample is monitored as a 
function of time. The sample will typically undergo three stages of creep that can easily be 
discerned from the strain versus time curve. These are the initial primary or transient creep stage 
that exhibits rapidly-decelerating strain, followed by the secondary or steady-state creep stage in 
which strain occurs at a constant rate for extended time periods. The steady state creep stage is 
characterized by slow growth of microcracks either along or through grain boundaries. Finally, 
as the sample reaches its static fatigue limit, brittle materials will enter another stage of rapid 
strain rate increase leading to brittle failure. During this stage of deformation, the microcracks 
form major through-going fractures, which results in formation of a macroscopic failure 
mechanism. An example of a typical creep test for the Tptpmn is given in Section 6.4.2.4 (see 
Figure 6-152). Each creep stage can clearly be seen from this curve. 
The PFC stress corrosion model adjusts the particle bond strength properties and radius to 
represent the basic time-dependent weakening effects resulting from stress corrosion. The 
bonding properties are calibrated to reproduce the slope of the time-to-failure plots derived from 
static fatigue experiments. However, the model should also reproduce the general 
time-dependent creep response of the Tptpmn, and should be able to show equivalent transient, 
steady-state and tertiary creep phases. Figure 7-17 shows a typical PFC-generated creep curve 
from a simulated constant load (at 80 percent of the uniaxial compressive strength) creep 
experiment. The time-to-failure (i.e., the point of tertiary creep rupture at t/tf) is set via 
calibration to static fatigue experiments, thus establishing a match of the specific time of creep 
rupture. Tensile fractures (cracks) develop spontaneously in the model as a function of time 
ANL-EBS-MD-000027 REV 03 7-30 September 2004 

Drift Degradation Analysis 
based on the time-dependent bond strength of the constituent grains. The plot shows the 
development of a network of tensile stress corrosion cracks that accumulate and propagate within 
the sample until a macroscopic shear failure mechanism develops with resulting brittle rupture 
during the tertiary creep stage. The simulated creep test shows the three stages of creep: 
transient, secondary and tertiary, and reproduces the typical response of creep experiments in tuff 
(e.g., Figure 6-152). 
Source: Appendix S, Figure S-13. 
NOTE: Numerical simulation of creep test run by holding applied axial stress constant at 0.8 times the unconfined 
compressive strength. The damage, in terms of new crack growth, is displayed at various times along the 
creep curve. Brittle failure of the sample occurs when sufficient time-dependent crack growth results in 
failure mechanism. 
Figure 7-17. Simulated Creep Curve and Brittle Rupture Calibration for Nonlithophysal Tuff, 
Static-Fatigue Test at Driving-Stress Ratio (Ratio of Applied Stress to Unconfined 
Compression Strength) of 0.8 
In conclusion, the PFC stress corrosion model is shown to spontaneously reproduce the observed 
primary, secondary and tertiary stages of creep observed in laboratory. The approximate 
evolution of each stage and the proportionate length of each stage is reasonably similar to that 
observed in the laboratory. 
7.5.2.3 PFC Post-Development Validation Exercise 3  Model Validation by Technical 
Review 
Two outside expert technical reviews were conducted as a means of validation, as discussed in 
procedure AP-SIII.10Q, Models. The first independent technical review is provided by Dr. Jaak 
Daemen, Professor of Mining Engineering and Department Chair at the University of Nevada, 
Reno. Dr. Daemen received his Ph.D. in Geological Engineering from the University of 
Minnesota where his research involved development of the analytical and numerical solutions for 
ANL-EBS-MD-000027 REV 03 7-31 September 2004 

Drift Degradation Analysis 
ground support  rock mass interaction. His current research involves time-dependent testing of 
joints and intact tuff from the Yucca Mountain nuclear waste disposal site. 
The second independent technical review is provided by Mr. Ronald Price and Dr. Randolph 
Martin. Mr. Price is a Senior Member of Technical Staff at Sandia National Laboratories in 
Albuquerque, New Mexico. He has a M.S. in Geology from the Center for Tectonophysics at 
Texas A&M University. Since his arrival at Sandia in 1980, Mr. Price has planned, carried out 
and published results from laboratory studies on many different rock types and for many 
applications, with special emphasis on Yucca Mountain tuffs, for over 22 years. Dr. Martin is 
the President of and Principal Scientist at New England Research, Inc. in White River Junction, 
Vermont. He has a Ph.D. from MIT and has a wide range of experience managing and 
performing both field and laboratory rock mechanics projects, specifically including 
time-dependent crack growth and creep of rocks. Dr. Martins seminal work in the area of static 
fatigue, coupled with Mr. Prices depth of knowledge of tuff rheological properties, makes them 
particularly valuable in the review of this material. 
The technical review reports are provided in Appendix S (Section S5). In general, the technical 
reviews find the PFC stress corrosion approach to be adequate for the simulation of long-term 
drift degradation. The model approach, data selection and ranges were found to be adequate. 
The model boundary conditions and methodology for application of the static-fatigue test data 
were also felt to be proper. The reviewers noted that limited test data to build confidence in the 
model is the models primary limitation. Since the technical reviews have been completed, 
additional time-dependent testing data has been provided and is included in the analysis of 
time-dependent drift degradation (Section 6.4.2.4.2). 
7.5.2.4 Conclusion from Particle Flow Code (PFC) Model Validation - Comparison to 
Criteria 
Consistent with the stated level of confidence required for the model, the above PFC studies have 
shown the following: 
 The PFC model is able to reproduce the basic failure mechanisms observed in the 
laboratory for nonlithophysal and lithophysal rocks (lithophysal rock validation criteria, 
Section 7.2.3). 
 The model provides information that allows understanding of the detailed mechanism of 
failure in lithophysal rocks and accounts for the strength and moduli reduction 
mechanism with increasing lithophysal void percentage. The presence of voids in a 
sample under compression creates stress concentrations around the voids, promoting 
tensile splitting phenomena between voids. The result is a weakening effect that 
increases as a function of increasing void volume, and decreasing web thickness 
between voids (lithophysal rock validation criteria, Section 7.2.3). 
 The strength and modulus reduction with void porosity predicted by the model compares 
reasonably well with that observed in the laboratory. Thus, the PFC model is able to 
capture the impact of lithophysal porosity variability on strength and deformability 
properties (lithophysal rock validation criteria, Section 7.2.3). 
ANL-EBS-MD-000027 REV 03 7-32 September 2004 

Drift Degradation Analysis 
 The PFC model is able to spontaneously reproduce the basic time-dependency behavior 
of the tuff as determined from creep testing. The model is able to reasonably reproduce 
the primary, secondary and tertiary phases of creep, and provides an understanding of 
the underlying mechanism of stress corrosion-based microcrack propagation. 
7.6 DEVELOPMENT AND VALIDATION OF A DRIFT-SCALE MODELING 
METHOD FOR LITHOPHYSAL ROCK USING THE UDEC PROGRAM 
As was noted in Section 7.1, the PFC program is computationally intensive and, therefore, not 
particularly practical for use as a modeling tool for drift-scale analyses as required. The method 
used here is to calibrate a similar modeling approach based on the UDEC (Section 3.1) 
discontinuum program to the laboratory data and then validate this approach against: 
 Observations of failure mechanism in the laboratory 
 Field observations of tunnel response in the ECRB Cross-Drift 
 Thermally induced fracture development in the Drift Scale Test within the Tptpmn unit 
 Literature data from related field experiments in which blast-induced yield of a jointed 
rock mass and large deformations of a scaled, lined tunnel are induced. 
 Comparison of the output predictions of rock mass stress and yield around emplacement 
drifts using the UDEC discontinuum model of lithophysal rock model to alternative 
continuum-based representations of the mechanical response of lithophysal rock. 
Figure 7-4 provides a flow chart illustrating the calibration and validation strategy for UDEC. 
The following section describes the validation of the UDEC lithophysal rockfall model and 
exploration of its limitations. 
7.6.1 Qualification of the UDEC Program (Confidence Building During Model 
Development) 
The UDEC program has been qualified as documented in Section 3. The software 
documentation contained in the UDEC users manuals (Itasca Consulting Group 2002 
[DIRS 160331]) provides details of the analytical development of the program and the 
mechanical basis for the material constitutive models that it uses. Extensive documentation 
(Itasca Consulting Group 2002) is dedicated to verification of the ability of the model to solve 
analytical solutions that test the various aspects of the model (e.g., mechanical, thermal, porous 
media flow, dynamics). 
7.6.2 Justification for a Two-Dimensional Isotropic Model of the Lithophysal Rock 
(Confidence Building During Model Development) 
As was discussed in Section 7.3, the lithophysal units, particularly lower lithophysal zone 
(Tptpll), are characterized by the presence of more-or-less uniformly distributed voids 
(lithophysae) of varying size (from centimeter size to over 1 m in diameter). The lithophysae 
account for up to about 30 percent of the rock mass. Additionally, in the Tptpll, intense, short 
ANL-EBS-MD-000027 REV 03 7-33 September 2004 

Drift Degradation Analysis 
trace length interlithophysae fracturing exists. Average joint spacing is on the order of cm to dm, 
creating block dimensions on the order of the fracture spacings, or cm to dm in dimension. 
Under such conditions, representation of lithophysal rock units, in the models of drift stability, as 
a homogeneous, isotropic rock mass is appropriate. The size of the internal structure and spacing 
is much smaller than the drift size (i.e., 5.5-m diameter). There is no preferred direction in the 
orientation that would justify introduction of anisotropy. Heterogeneity was considered on the 
scale of the repository. The analysis was conducted using different properties of the rock mass 
to investigate the effect of varying quality of rock mass on drift stability. However, properties 
inside each model were considered homogeneous. Under such conditions, when there is no 
internal structure in the model, and properties are isotropic and homogeneous, the drift stability 
analysis was conducted using a two-dimensional model in the plane perpendicular to the drift 
axis. The model results of rockfall prediction (in a cross-section characterized by particular rock 
mass properties) are then used for estimating overall rockfall in the entire repository based on 
estimated distribution of different rock mass qualities throughout the repository. 
7.6.3 Rock Mass Properties for Model Calibration 
The rock mass properties for lithophysal rock mass were determined based on: 
 Laboratory testing on 10.5-in diameter cores of Tptpll from Busted Butte 
 Laboratory testing on 11.5-in diameter cores of Tptpll and Tptpul from ESF main loop 
and ECRB Cross-Drift 
 PFC and UDEC extrapolations of mechanical response under triaxial stress conditions. 
The division of rock mass properties into five categories based on the lithophysal porosity and 
size effect is described in Appendix E, Section E.4 and is shown graphically in Figure 7-16. 
7.6.4 Model Calibration (Confidence Building During Model Development) 
The two-dimensional distinct element code, UDEC (Section 3.1), is used here for drift stability 
analysis. The rock mass is represented as an assembly of polygonal, elastic blocks (Figure 7-18) 
that are bonded together across their boundaries to form a coherent solid. The goal is to provide 
a rock mass in which the overall mechanical behavior of the mass is consistent with the material 
model developed for the lithophysal rock, yet allow internal fracturing to form and blocks to 
loosen and detach as the evolving stress state dictates. In other words, the fractures are 
invisible to the model until yielding begins. 
ANL-EBS-MD-000027 REV 03 7-34 September 2004 

Drift Degradation Analysis 
NOTE: Blocks are bonded at their contacts with a cohesion and tensile strength. When these break, the contacts 
become purely frictional. Specimen is sampled from equivalent rock mass representing the Tptpll. 
Figure 7-18. UDEC Lithophysal Rock Specimen Composed of Many Irregular Blocks with Roughly 
Equi-Dimensional Side Lengths 
ANL-EBS-MD-000027 REV 03 7-35 September 2004 

Drift Degradation Analysis 
Since the block boundaries can fail in tension and shear, they act as potential or incipient 
fracture locations should the stresses dictate that fracture is possible. It is important that the 
block assemblage contain blocks that are sufficiently small such that the model does not dictate 
where and how fractures can form and propagate. The entire tunnel domain is discretized into 
small blocks (using Voronoi tessellations, see Itasca Consulting Group 2002 [DIRS 160331]) 
that are roughly consistent with the maximum block size expected from core fracture spacings. 
The potential fractures between blocks are considered to behave mechanically according to a 
linearly elastic-perfectly plastic model. The elastic behavior of potential fractures is controlled 
by constant normal and shear stiffness, and are consistent with the Youngs modulus of the intact 
rock blocks. The possible failure modes of the rock mass are controlled by the strength of the 
fractures. The fractures can sustain a finite tensile stress, whereas a Coulomb slip condition 
governs the onset of slip, as a function of joint cohesion and friction angle. If a potential fracture 
fails, either in tension or shear, tensile strength and cohesion are set to zero, whereas the friction 
angle is set to the residual value. This model allows for the formation of fractures between 
blocks, separation and instability (under action of gravity) of portions of the rock mass around a 
drift. 
The blocks used in the UDEC lithophysal rockfall model do not represent the actual internal 
structure of the lithophysal rock mass. They are a tool in the numerical model used to simulate 
damage and fracturing of the rock mass (i.e., the potential fractures in this model do not 
correspond to actual features). Therefore, it is not possible to directly obtain the potential 
fracture properties in the UDEC lithophysal rockfall model to results of laboratory or field 
testing on samples of lithophysal rock. To assure that an assembly of Voronoi blocks behaves as 
a lithophysal rock mass, it has to be calibrated. Calibration is done by numerical simulation of 
tests (e.g., unconfined compressive strength tests), which are actually conducted in the laboratory 
or the field, and for which the test results are available. During the numerical experiment 
(calibration), the model parameters (i.e., potential fracture properties) are varied until 
macro-properties of the rock mass important for the drift stability analysis (e.g., Youngs 
modulus and unconfined compressive strength) are matched with measurements from the actual 
tests. When the calibration is completed it is possible to say that the synthetic material 
(i.e., the assembly of Voronoi blocks) behaves (on the scale of a drift) equivalently to the 
lithophysal rock mass. Following calibration, the model can be used to conduct additional 
simulations under biaxial compression and tension to produce the yield criteria for the material. 
These yield criteria can be compared to typical empirically derived yield criteria for other rock 
types as a means of verification of the model. 
The following parameters characterize the mechanical behavior of the UDEC Voronoi model: 
 The block size scaled to the model size, or a number of blocks in the model. 
 Elastic properties of blocks (Em , .m). 
 Properties of joints, both elastic (normal stiffness, kn, and shear stiffness, ks) and plastic 
(tensile strength, tm, cohesion, cm, and friction, fm). Note that plastic joint parameters are 
functions of shear and tensile plastic strains. In the simulations presented in this report, 
it is considered that cohesion and tensile strength soften to zero at the onset of yield. 
ANL-EBS-MD-000027 REV 03 7-36 September 2004 

Drift Degradation Analysis 
The micro properties are illustrated in Figure 7-19. Because of the geometrical complexity of the 
model, a direct functional correlation between micro- and macro-properties (model response on a 
large scale) does not exist. Therefore, to match model macro-behavior, it is necessary to 
calibrate the model. During the calibration, which is done during simulation of simple uniaxial 
and biaxial experiments, the micro-properties are adjusted until the desired macro-behavior is 
matched. The calibration uses a trial-and-error approach, but some understanding of the model 
mechanics and previous experience can expedite convergence of the iterative process. 
Figure 7-19. Micro Properties of the UDEC Voronoi Model 
Elastic and strength properties can be decoupled during the iteration process (i.e., model 
deformability and strength can be calibrated separately). It is common to calibrate model elastic 
parameters first. Clearly, calibration of the elastic properties is a problem with a non-unique 
solution. The two elastic macro-properties (E and .) are functions of block size and four micro 
properties (kn, ks, Em, and .m). The block size is determined based on observed fracture spacing 
and the condition that the ratio between the drift radius and the block size is sufficiently large 
(>15). The Poissons ratio of the blocks is selected to be equal to the macro Poissons ratio, such 
m
that .= .. The additional requirement needed to match the macro Poissons ratio is that the 
ratio between normal and shear joint stiffnesses is larger than 1. Simulations confirm that a 
Poissons ratio of 0.2 is matched when kn / ks  2. It is reasonable that the contribution of joints 
to model deformability is larger than the contribution of blocks, but it is desirable, from the 
perspective of convergence of the numerical model, that stiffnesses of blocks and joints are of 
the same order of magnitude. Therefore, based on guidance in the UDEC Users Manual (Itasca 
Consulting Group 2002 [DIRS 160331], Manuals/UDEC/Users Guide/Section 3: Problem 
Solving, Section 3.2.3), it was selected that 
4 m
Km + G 
5 < 3 <10 (Eq. 7-4) 
bk
n 
where b is the average block size, and Km and Gm are the bulk and shear moduli of the blocks, 
respectively. With these considerations, there is a single independent elastic micro-parameter 
(e.g., kn). The proper macro deformability of the model is than matched by rescaling of the 
elastic micro-properties (kn, ks, Km, and Gm). 
ANL-EBS-MD-000027 REV 03 7-37 September 2004 

Drift Degradation Analysis 
Calibration of strength micro properties involves matching macro failure envelope and post-peak 
behavior by adjusting strength micro-properties. Note that model plastic deformation appears to 
be a function of the size and shape of blocks. The failure envelope, which, in general, is a 
surface in the principal stress space, reduces to a line if it is considered that the failure envelope 
is not a function of the intermediate principal stress. Test runs have proven that the micro 
friction angle, which is initially equal to 35 and softens in a brittle fashion to 15, results in the 
desired post-peak behavior and strength increase as a function of confinement. In order to match 
the observed mode of failure of non-lithophysal tuff under unconfined loading conditions 
(i.e., axial splitting), the micro tensile strength is assigned to be less than 50 percent of the micro 
cohesion. After these relations are established, the proper peak strength is matched by rescaling 
micro cohesion and tensile strength. 
Stress-strain curves obtained from numerical experiments with different conditions of 
confinement (unconfined, 1-MPa confinement, and 3-MPa confinement) and loading (tension 
and compression) are shown in Figure 7-20. The mode of failure is also illustrated for each case 
by a plot of displacement vectors at the final state of the model. The model matches unconfined 
compressive strength of 10 MPa and Youngs modulus of 1.9 GPa for Category 1 (Table E-10). 
Laboratory testing data on the post-peak behavior of lithophysal rock is inconclusive. However, 
the model exhibits qualitatively reasonable post-peak behavior. The response for low 
confinement is brittle (see unconfined compressive strength curve in Figure 7-20). As 
confinement increases the response becomes more ductile, almost perfectly plastic for 3-MPa 
confinements (Figure 7-20). The mode of sample failure in the case of unconfined compressive 
strength is axial splitting, similarly to observations from laboratory experiments. The mode of 
failure for confined cases becomes more of the shear band type. 
Figure 7-20. Numerical Experiment, Category 1: Stress-Strain Curves and Modes of Failure for 
Different Confinements and Loading Conditions 
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Drift Degradation Analysis 
The failure envelope in the principal stress space, constructed based on numerical tests at 
different confinement levels, is shown in Figure 7-21. The failure envelope is curvilinear, as 
expected for a rock mass (similar to Hoek-Brown failure criterion). The initial friction angle 
(in the range of confining stress, s3, between 0 and 1 MPa) is 33, but it decreases for larger 
confinement. The ratio between uniaxial compressive and tensile strengths is larger than 10. 
The volumetric deformation of the model during the experiments is illustrated in Figure 7-22, 
which shows curves of volumetric strain versus axial strain. In general, these curves are bilinear. 
Initially, while the sample behaves elastically, its volume reduces due to the Poissons effect. 
The initial slope of the curves is a function of the Poissons ratio. Thus, the Poissons ratio, ., of 
the synthetic material can be calculated from the initial slope of the curve, se, according to the 
following formula derived from elasticity theory: 
.= 1 - se (Eq. 7-5) 
2 - se 
Figure 7-21. Numerical Experiment, Category 1: Failure Envelope 
ANL-EBS-MD-000027 REV 03 7-39 September 2004 

Drift Degradation Analysis 
Figure 7-22. Numerical Experiment, Category 1: Volumetric Strain Versus Axial Strain for Different 
Confinements and Loading Conditions 
As the material yields and starts plastic deformation, it usually dilates (increases volume). 
Consequently the curves in Figure 7-22 change the slope. Initially negative slopes, indicating 
contraction, become positive, indicating dilation. The slope of the curves during plastic 
deformation is a function of the dilation angle, which is the parameter used to characterize plastic 
volumetric deformation. The dilation angle, ., of the synthetic material can be calculated from 
the post-peak slope of the curve, sp, according to the following formula, which was derived from 
Mohr-Coulomb plastic flow equations in Itasca SoftwareCutting Edge Tools for Computational 
Mechanics (Itasca Consulting Group 2002 [DIRS 160331]): 
..
.
2
...
. 
(Eq. 7-6) 
s 
p
=
.
arcsin 
s 
p
+
. 
The synthetic material clearly exhibits a very large dilation angle for unconfined compressive 
strength. Such behavior is expected because micro damage of the material during unconfined 
compressive strength testing is predominantly tensile fracturing, which results in extremely large 
dilation. 
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Drift Degradation Analysis 
7.6.5 Post-Development Validation Strategy 
Once calibrated, the UDEC lithophysal rockfall model and properties require validation against 
field observations and testing. The model is also validated against laboratory failure mechanisms 
and drift scale response by: 
 Comparison of lithophysal sample failure mechanisms in the laboratory 
 Comparison of the prediction of drift scale fracturing in the Tptpll at ECRB Cross-Drift 
depth to observations of tunnel sidewall fracturing in the ECRB Cross-Drift 
 Comparison of roof spalling in the Drift Scale Heater Test in the Tptpmn during thermal 
overdrive experiments to UDEC lithophysal rockfall model predictions 
 Comparison of several different numerical modeling techniques to UDEC for a field 
simulation of steel tube-reinforced tunnel to dynamic loading from a blast 
 Additionally, the capabilities of the UDEC program for representing dynamic response 
of jointed or fractured media is demonstrated by code-to-code comparisons conducted 
through past dynamic tunnel stability analysis for the Defense Nuclear Agency. 
7.6.5.1 UDEC Post-Development Validation Exercise 1 - Comparison of Predicted 
Failure Modes to Laboratory Observations (Corroboration with Relevant 
Observations) 
The UDEC potential fracture model is formulated to allow fractures to form as the stresses 
dictate. An initial and simple validation is to compare the predictions of the model to 
observations and common knowledge from laboratory testing. In uniaxial compression, with 
2:1 length-to-diameter specimens, the failure mode is typically in the form of axial splitting, or 
coalescence of axially oriented fractures observable on the surface of the sample. Figure 7-23 
presents a typical UDEC plot of predicted fracturing (red tensile cracks) that forms axial to the 
sample axis. The block structure of the sample was previously shown in Figure 7-18, but is not 
shown in Figure 7-23 so that the formed cracks are clearly seen. The typical laboratory failure 
response is shown in the associated photograph of a large core sample from the Tptpul after 
testing. The axial fractures are clearly visible in this photo. The UDEC lithophysal rockfall 
model further is able to produce typical tensile fracture orientation from a simulated direct 
tension test (Figure 7-24). The model will seek out a unique fracture path composed of 
coalescing potential fractures to form a distinct separation plane. 
ANL-EBS-MD-000027 REV 03 7-41 September 2004 

Drift Degradation Analysis 
Applied Axial Load 
pg pppAxial slittinarallel to alied stress 
NOTE: The model predicts axial splitting when no confinement is applied as seen by the red tensile block boundary 
breakages (fractures) formed and by the velocity vectors that show the sidewall spalling. Core photo shows 
similar axial splitting phenomena. 
Figure 7-23. UDEC Discontinuum Model of Failure of Lithophysal Tuff Specimen Under Uniaxial 
Compression 
ANL-EBS-MD-000027 REV 03 7-42 September 2004 

Drift Degradation Analysis 
NOTE: A distinct tensile fracture formed from coalescence of individual breakages. 
Figure 7-24. Predicted Failure Mode of UDEC Sample in Direct Tension Test 
7.6.5.2 UDEC Post-Development Validation Exercise 2 - Comparison of Model 
Predictions to Observations in the ECRB Cross-Drift (Corroboration with Field 
Observations) 
The proposed modeling approach was verified by comparison of predicted in situ stress-induced 
damage to the minor damage observed in sidewalls of ESF main loop and ECRB Cross-Drift in 
the lowest quality Tptpll. Additionally, no sidewall damage is observed in drifts in higher 
quality Tptpul at shallower depth. Tunnels in all rock units are stable after excavation, 
regardless of depth or rock quality. However, some damage, in the form of wall parallel 
fractures (opening of existing fracture fabric) at the springline (the point of highest shearing 
stress), can be observed in the sidewalls of the tunnels at greater depth in the Tptpll. Figure 7-25 
shows formation/opening of wall-parallel fractures observed in 12-in. diameter boreholes drilled 
for geomechanical sampling in the sidewalls of the ESF main loop and ECRB Cross-Drift at the 
tunnel springline. The wall-parallel fractures are typical of stress-induced yield in tunnels. The 
boreholes drilled in the relatively low quality Tptpll at depths of 300 to 350 m show sidewall 
fracturing to depths of approximately 0.5 to 0.6 m. Holes drilled into relatively high quality 
Tptpul at depths of approximately 200 to 250 m show no fracturing. 
ANL-EBS-MD-000027 REV 03 7-43 September 2004 

Drift Degradation Analysis 
NOTE: Top photo shows sidewall fracturing/opening of preexisting wall-parallel fractures in a 12 diameter 
horizontal borehole drilled in the springline of the ESF in low quality Tptpll (approximately Category 1). 
Overburden depth is approximately 325 m. Depth of fracturing is approximately 1.5 to 2 ft (0.46 to 0.61m). 
The bottom photo shows a horizontal, 12-in diameter borehole drilled in the springline in good quality Tptpul 
(approximately Category 5) in ESF near site of slot test 2 showing no sidewall damage. The depth of 
overburden is approximately 250 m. 
Figure 7-25. Observed Rock Mass Conditions at the Tunnel Springline in Lithophysal Rock in the ESF 
ANL-EBS-MD-000027 REV 03 7-44 September 2004 

Drift Degradation Analysis 
The presence of these fractures and their depth into the drift wall, observed in large hole drilling, 
is a convenient feature from which an estimate of the rock mass strength properties and 
validation of the model can be made. A parametric study of drift stability and rock yield depth 
was conducted using the UDEC lithophysal model for the five strength categories (Appendix E, 
Section E.4) and imposed overburden depths of 250, 300, and 350 m, corresponding to the Tptpll 
and Tptpul. As seen in Figures 7-26 and 7-27, the model reproduces the approximate depth and 
orientation of drift wall-parallel fractures observed underground for strength Category 1. The 
failure of the rock is contained to the immediate springline due to the stress concentration 
resulting from the vertical maximum stress (vertical stress in MPa = 0.024  depth (m), 
horizontal/vertical stress = 0.36 to 0.62 (SNF37100195002.001 [DIRS 131356])). The model 
results indicate that the rock adjacent to the drift wall yields in a state of uniaxial compression 
since the minimum stress at or near the drift wall is zero or small since the radial stress 
component is zero. The depth of fracturing is clearly visible in these models as the zone where 
stress relaxation has occurred. The models also show that, for the range of potential lithophysal 
rock properties, there is no drift wall yield at the depth of the Tptpul from strength Category 1. 
In conclusion, this validation exercise shows that: 
 The model is able to represent the observed wall fracturing at the Tptpll depth for a 
range of rock strengths that agree with laboratory measurements of uniaxial compressive 
strength (i.e., the observed yield is consistent with laboratory measured values). 
 The model shows that reduction of depth to that of the Tptpul results in no yield of the 
drift wall, and thus no fracturing as observed. 
7.6.5.3 UDEC Post-Development Validation Exercise 3 - Comparison of Model to Drift 
Scale Experiment in the Tptpmn (Corroboration with Field Experiments) 
The Drift Scale Heater Test was conducted in the Tptpmn unit, primarily as a fluid migration 
experiment (Williams 2001 [DIRS 159516]). This test involved driving a 5-m  5-m drift, 50-m 
in length completely within the Tptpmn. The drift was heated using simulated electrically heated 
canisters within the drift itself, as well as horizontally placed borehole heaters in the springline of 
the tunnel to additionally raise the ambient rock mass temperature (Figure 7-28). Heating was 
started in 1997 and lasted for four years until 2001. The experiment is currently in the 
cool-down phase. After three years of heating (from 1997 to 2000), the heater power was raised 
to provide a thermal overstressing condition. The rock temperature level was driven to 
approximately 200C, or a maximum 180C temperature rise. Spalling of rock was first 
observed in late 1999 as small chips of rock on the tunnel invert, however there was no 
observation of obvious larger rock fragments or bulking in the welded wire fabric. Therefore, it 
is unknown if these small particles are related to thermal stress effects. In April 2001, obvious 
loose rock was observed at several locations in the crown of the tunnel, contained behind the 
wire mesh (Figure 7-29). At least four zones of loosened rock were observed along the tunnel 
crown, using the rail mounted remote camera. It is not clear that these are all of the zones of 
spalling due to the difficulty in observation using this camera technique, however, it is clear that 
they are largely congregated along the tunnel crown. The rock plates held within the welded 
wire fabric from about 5 to 20 cm. This type of slabbing is typical of hard, brittle rock masses 
subjected to horizontal stresses in the crown that exceed their uniaxial compressive strength. 
ANL-EBS-MD-000027 REV 03 7-45 September 2004 

Drift Degradation Analysis 
NOTE: Upper figure for Category 1 shows predicted fracturing to a depth of approximately 0.5 m in the sidewall of 
ECRB Cross-Drift. Lower picture shows stress vectors (in Pa) colored by the magnitude of the stress 
component. Depth of yield for Category 1 is limited to about 0.5 m in the immediate springline area. The 
model for Category 5 shows elastic rock mass response (i.e., no yield). Stress vectors in lower figure also 
shows elastic stress distributions with no readjustment due to yielding. 
Figure 7-26. Estimate of Rock Mass Fracturing and Stress State Under In Situ Loading Only, Depth of 
300 m, Tptpll, Strength Category 1 (Low-Strength Characteristics) and 5 (High-Strength 
Characteristics) 
ANL-EBS-MD-000027 REV 03 7-46 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 7-47 September 2004 
a) ob) oc) o 
Figure 7-27. Estimate of Stress-Induced Rock Mass Fracturing (seen as red block contacts) as a 
Function of Overburden Between 250 m and 350 m, Tptpll, Strength Category 1 
(Low-Strength Characteristics) 
(a) Overburden at 250 m 
(c) Overburden at 350 m 
(b) Overburden at 300 m 

Drift Degradation Analysis 
HD = Heated Drift; AOD = Access/Observation Drift 
NOTE: Numbered boreholes contain rock mass monitoring instrumentation. Canister heaters are placed in the 
Heated Drift. 
Figure 7-28. Perspective View of Heated Drift Scale Test Showing Wing Heaters 
It is the goal of this validation exercise to demonstrate that the UDEC lithophysal rockfall model 
with random block subdivision is capable of reproducing thermal fracturing response at the 
proper approximate temperature and thermally induced stress levels as observed in the Drift 
Scale Heater Test. The first step in the validation is to calibrate the UDEC potential fracture 
properties against laboratory compression data. A compilation of the results of uniaxial 
compression strength test data for a range of sample sizes as described by Price 
(1986 [DIRS 106589]) is provided in Appendix E (Figure E-22). The sample sizes vary from 
25 mm to approximately 230 mm, resulting in a curve that describes compressive strength as a 
function of sample size. Since the Drift Scale Heater Test represents in situ sample size, the 
UDEC lithophysal rockfall model is calibrated to the predicted field scale, represented by a 
sample size scale of approximately 1-m size, or 70 to 75 MPa, or about 50 percent of the strength 
of a standard 50-mm diameter sample (Figure E-22). This size-strength relationship compares 
quite favorably with suggestions for other rock types as used in common practice for rock 
engineering design purposes. Hoek (2000 [DIRS 160705]) suggests that the rock mass strength 
for a 1-m sample size approaches an approximate value of about 50 to 60 percent of the uniaxial 
compressive strength of 50-mm cores samples. 
ANL-EBS-MD-000027 REV 03 7-48 September 2004 

Drift Degradation Analysis 
Zone of 
spalling in 
center of 
crown 
NOTE: Rock spalling is contained by 3-in  3-in wire mesh and Swellex bolts. Top view shows general spalled 
region. Bottom view is a close up along the camera rail showing slabbing into small, flat pieces. 
Figure 7-29. Minor Superficial Slabbing in the Center of the Roof Span Observed During Thermal 
Overstressing of the Heated Drift Scale Test 
ANL-EBS-MD-000027 REV 03 7-49 September 2004 

Drift Degradation Analysis 
The UDEC lithophysal rockfall model was calibrated based on a sample uniaxial compressive 
strength of approximately 50 to 70 MPa, using an average Youngs modulus of 30 GPa. The 
mean measured Youngs modulus for Tptpmn data is 33.6 GPa  6.5 GPa from laboratory data 
(see Appendix E, Table E-6). Figure 7-30 shows the representative calibration of the UDEC 
equivalent Tptpmn material showing linear elastic behavior to peak strength, followed by a 
brittle post-peak failure mode. The term representative is used since the calibration is performed 
for a specific value of strength and modulus, whereas the data span a wide range of possible 
values. The rock mass surrounding the Drift Scale Heater Test drift was formed using randomly 
shaped, roughly spherical blocks using the Voronoi generation technique described in 
Section 6.4.2.1. The in situ stress state was selected to be 7 MPa vertical stress and 3.5 MPa 
lateral stress. 
Figure 7-30. UDEC Sample Calibration to Size-Effect Strength Data for an Approximate 1-m Sample 
Size, Tptpmn 
The model in situ stresses are applied and allowed to equilibrate prior to drift excavation. 
After excavation, the measured temperatures at thermocouple locations 
(DTNs: MO9807DSTSET01.000 [DIRS 113644]; MO9906DSTSET03.000 [DIRS 113673]; 
MO0001SEPDSTPC.000 [DIRS 153836]; MO0007SEPDSTPC.001 [DIRS 153707]; 
MO0107SEPDSTPC.003 [DIRS 158321]; MO0202SEPDSTTV.001 [DIRS 158320]; and 
MO0002ABBLSLDS.000 [DIRS 147304]) for a representative tunnel cross-section are used to 
linearly interpolate temperatures at UDEC lithophysal rockfall model gridpoints at successive 
one-year intervals. At each of these intervals, the model is allowed to equilibrate, developing 
thermally induced stresses that are added to the mining-induced stress conditions. The rock mass 
is free to fracture and deform under the influence of the stresses. 
ANL-EBS-MD-000027 REV 03 7-50 September 2004 

Drift Degradation Analysis 
Figures 7-31 to 7-36 show the temperatures, major and minor principal stresses and predicted 
fracturing for the time period of 1997 to 2002. Initially, under mining-induced stresses only 
(1997), no fracturing of the rock mass has occurred. As early as 1998, the temperature rise in the 
rock mass exceeds 130C around the drift periphery, and approximately 150C along the wall 
heater holes. The vertically symmetric temperature field induces a significant tangential 
compression to the crown of the tunnel, which is approximately equal to the projected uniaxial 
compressive strength of the rock mass. A very small amount of non-coherent fracturing is 
predicted in the crown at this stage. At the year 2000, the rock mass temperature in the 
immediate crown reaches approximately 190C, and slabbing occurs (as seen in the upper right 
hand portion of figure as red fractured contact planes between blocks). The roof-parallel 
slabbing (or spalling) occurs largely in the crown over a span of perhaps 2 meters, and rapidly 
equilibrates and dies out into the roof where the confinement is sufficient to suppress this 
response. A seen in these figures, a number of particles detach themselves and fall onto the 
invert. The spalling phenomenon appears to occur in much the same fashion as axial splitting of 
samples in uniaxial compression in the laboratory. The rock adjacent to the free surface is 
subjected to the tangential compression and radial tension which results in the fracturing parallel 
to the minimum principal stress. 
The model response can be compared to field observations: 
 With the selected strength parameters, the model shows no spalling behavior due to in 
situ mining-induced stresses only. No spalling is observed in the field. 
 Small-scale fracture development can be observed early on in both the model and field. 
Small particles were observed on the drift floor as early as 1999 in the field while 
non-coherent fractures develop in the model in the crown as early as 1998. 
 Large-scale spalling in the model is observed when the heater power is raised in the year 
2000, thus creating a large change in thermally induced tangential compression and 
radial tension in the roof (Figure 7-34). A change in roof spalling and rock plates lying 
on the floor of the drift are observed in the Drift Scale Heater Test in early 2001. Depth 
of the spalling in the field is unknown at present as it is held in place by the rock 
support. However, the general location (restricted to the immediate crown) and lateral 
extent (a meter or two) of the simulated spalling (Figure 7-34) is consistent with field 
observation. 
 The model spalling occurs when the rock stresses roughly equal the proposed uniaxial 
compressive strength of the rock mass, confirming the selection and calibration of the 
rock strength and its relationship to in situ modulus. 
Obviously, the strength and moduli of the Tptpmn rock mass varies in situ. This validation 
exercise shows that, for rock mass properties within the ranges defined by Price et al. (1985 
[DIRS 106602]), the model is able to produce thermally induced fracturing response similar in 
nature and extent to that observed at the proper temperature and thus thermally induced stress 
levels. 
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Drift Degradation Analysis 
)(MPa
Source: DTNs: MO9807DSTSET01.000 [DIRS 113644]; MO9906DSTSET03.000 [DIRS 113673]; 
MO0001SEPDSTPC.000 [DIRS 153836]; MO0007SEPDSTPC.001 [DIRS 153707]; 
MO0107SEPDSTPC.003 [DIRS 158321]; MO0202SEPDSTTV.001 [DIRS 158320], 
MO0002ABBLSLDS.000 [DIRS 147304]. 
NOTE: Clockwise from upper left: temperatures, fractures, minimum principal stress, and maximum principal 
stress. Temperatures obtained from field thermal measurements; fracture and stress levels predicted from 
UDEC lithophysal rockfall model. 
Figure 7-31. Results from Heated Drift Analysis with 1997 Temperature Conditions 
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Drift Degradation Analysis 
)(MPa
Source: DTNs: MO9807DSTSET01.000 [DIRS 113644]; MO9906DSTSET03.000 [DIRS 113673]; 
MO0001SEPDSTPC.000 [DIRS 153836]; MO0007SEPDSTPC.001 [DIRS 153707]; 
MO0107SEPDSTPC.003 [DIRS 158321]; MO0202SEPDSTTV.001 [DIRS 158320]; 
MO0002ABBLSLDS.000 [DIRS 147304]. 
NOTE: Clockwise from upper left: temperatures, fractures, minimum principal stress, and maximum principal 
stress. Temperatures obtained from field thermal measurements; fracture and stress levels predicted from 
UDEC lithophysal rockfall model. Conditions represent 1 year of heating in the Heated Drift. 
Figure 7-32. Results from Heated Drift Analysis with 1998 Temperature Conditions 
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Drift Degradation Analysis 
)(MPa
Source: DTNs: MO9807DSTSET01.000 [DIRS 113644]; MO9906DSTSET03.000 [DIRS 113673]; 
MO0001SEPDSTPC.000 [DIRS 153836]; MO0007SEPDSTPC.001 [DIRS 153707]; 
MO0107SEPDSTPC.003 [DIRS 158321]; MO0202SEPDSTTV.001 [DIRS 159320]; 
MO0002ABBLSLDS.000 [DIRS 147304]. 
NOTE: Clockwise from upper left: temperatures, fractures, minimum principal stress, and maximum principal stress. 
Temperatures obtained from field thermal measurements; fracture and stress levels predicted from UDEC 
lithophysal rockfall model. Conditions represent 2 years of heating in the Heated Drift. 
Figure 7-33. Results from Heated Drift Analysis with 1999 Temperature Conditions 
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Drift Degradation Analysis 
)(MPa
Source: DTNs: MO9807DSTSET01.000 [DIRS 113644]; MO9906DSTSET03.000 [DIRS 113673]; 
MO0001SEPDSTPC.000 [DIRS 153836]; MO0007SEPDSTPC.001 [DIRS 153707]; 
MO0107SEPDSTPC.003 [DIRS 158321]; MO0202SEPDSTTV.001 [DIRS 159320]; 
MO0002ABBLSLDS.000 [DIRS 147304]. 
NOTE: Clockwise from upper left: temperatures, fractures, minimum principal stress, and maximum principal 
stress. Temperatures obtained from field thermal measurements; fracture and stress levels predicted from 
UDEC lithophysal rockfall model. Conditions represent 3 years of heating in the Heated Drift. 
Figure 7-34. Results from Heated Drift Analysis with 2000 Temperature Conditions 
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Drift Degradation Analysis 
)(MPa
Source: DTNs: MO9807DSTSET01.000 [DIRS 113644]; MO9906DSTSET03.000 [DIRS 113673]; 
MO0001SEPDSTPC.000 [DIRS 153836]; MO0007SEPDSTPC.001 [DIRS 153707]; 
MO0107SEPDSTPC.003 [DIRS 158321]; MO0202SEPDSTTV.001 [DIRS 159320]; 
MO0002ABBLSLDS.000 [DIRS 147304]. 
NOTE: Clockwise from upper left: temperatures, fractures, minimum principal stress, and maximum principal 
stress. Temperatures obtained from field thermal measurements; fracture and stress levels predicted from 
UDEC lithophysal rockfall model. Conditions represent 4 years of heating in the Heated Drift. 
Figure 7-35. Results from Heated Drift Analysis with 2001 Temperature Conditions 
ANL-EBS-MD-000027 REV 03 7-56 September 2004 

Drift Degradation Analysis 
)(MPa
Source: DTNs: MO9807DSTSET01.000 [DIRS 113644]; MO9906DSTSET03.000 [DIRS 113673]; 
MO0001SEPDSTPC.000 [DIRS 153836]; MO0007SEPDSTPC.001 [DIRS 153707]; 
MO0107SEPDSTPC.003 [DIRS 158321]; MO0202SEPDSTTV.001 [DIRS 159320]; 
MO0002ABBLSLDS.000 [DIRS 147304]. 
NOTE: Clockwise from upper left: temperatures, fractures, minimum principal stress, and maximum principal 
stress. Temperatures obtained from field thermal measurements; fracture and stress levels predicted from 
UDEC lithophysal rockfall model. Conditions represent the cool-down period in the Heated Drift. 
Figure 7-36. Results from Heated Drift Analysis with 2002 Temperature Conditions 
7.6.5.4 UDEC Post-Development Validation Exercise 4 - Comparison of UDEC Voronoi 
Block Model with Continuum Constitutive Models (Corroboration of Results 
with Alternative Mathematical Models) 
A UDEC model in which the rock mass is represented as an assembly of polygonal blocks is 
used to analyze the stability of the emplacement drifts located in the lithophysal rock. The main 
reason for using this approach, which is uncommon in engineering practice, was the requirement 
for the analysis to predict the rockfall. The Voronoi block model has an advantage over the 
continuum models in that fracturing of the rock mass, formation of loose blocks, and their 
rockfall can be simulated in a straightforward manner within the same model. However, the 
Voronoi block model must be calibrated in order to ensure that it behaves mechanically 
equivalent to the simulated rock mass. Another way of validating the UDEC Voronoi block 
model of lithophysal rock is to compare its results with those of the continuum approach using 
different constitutive models. The comparison is presented in this section. 
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Drift Degradation Analysis 
Elastic Models of Drift ExcavationThe Voronoi block model behaves as a linearly elastic 
model before fracturing occurs. Stress redistribution and deformation around the emplacement 
drift for the in situ stress state, in which the vertical stress is 7 MPa and the horizontal stress is 
3.5 MPa, are analyzed using continuum, linearly elastic constitutive models in FLAC and the 
UDEC Voronoi block model. In order to ensure linearly elastic behavior of the UDEC Voronoi 
block model, the strength of the contact bonds between the blocks was considered to be infinitely 
large. The problem was solved using two different geometries of the Voronoi block model, with 
average block sizes of 0.2 m and 0.3 m. Comparison of stresses and displacements calculated 
using the different methods is presented in Figures 7-37 to 7-42. Stress profiles calculated in 
UDEC show more scatter because of the discontinuous nature of the model. However, the 
agreement, in general, is rather good. The systematic difference in the horizontal and vertical 
displacements shown in Figures 7-39 and 7-42 is due to the different outer boundary sizes of the 
UDEC and FLAC models. The smaller FLAC model results in larger vertical displacements, 
because a stress boundary condition was used on the top model boundary. 
Figure 7-37. Elastic Models of Drift Excavation: Vertical Normal Stress Along the Horizontal Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-38. Elastic Models of Drift Excavation: Horizontal Normal Stress Along the Horizontal Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
Figure 7-39. Elastic Models of Drift Excavation: Horizontal Displacement Along the Horizontal Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-40. Elastic Models of Drift Excavation: Horizontal Normal Stress Along the Vertical Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
Figure 7-41. Elastic Models of Drift Excavation: Vertical Normal Stress Along the Vertical Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-42. Elastic Models of Drift Excavation: Vertical Displacement Along the Vertical Profile Through 
the Center of Tunnel (Distance is measured from the tunnel center) 
Inelastic Models of the Emplacement DriftThe results of damage, stress redistribution and 
deformation around the emplacement drift predicted using the UDEC Voronoi block model are 
compared with results obtained using the continuum approach and different considerations of 
constitutive behavior of the lithophysal rock mass. The micro properties of the joints and blocks 
in the UDEC model are calibrated to the stiffness and strength of lithophysal rock mass, 
Category 1, as determined from unconfined compression tests. The resulting constitutive 
behavior of the UDEC Voronoi block model is very complex, as illustrated by plots of failure 
envelope, stress-strain curves for different confinements and volumetric strain as a function of 
axial strain, shown in Figures 7-20 to 7-22. Unfortunately, the number and types of laboratory 
and in situ experiments was insufficient to describe the complete constitutive behavior of the 
lithophysal tuff with a high level of confidence, particularly in the post-peak strain range and for 
confined conditions. The mechanical behavior exhibited by the synthetic Voronoi block model 
seems to be quite reasonable and typical for hard, brittle rocks like the Topopah Spring. For 
unconfined conditions, the UDEC synthetic model softens in a rather brittle manner after 
reaching the peak stress. As confinement increases, the post-peak behavior becomes mode 
ductile; for 3-MPa confinement, it is almost perfectly plastic (i.e., there is no strength decrease 
for a considerable plastic strain). Because of the large uncertainty in the post-peak behavior of 
the rocks, simple continuum constitutive models are used commonly in engineering practice. The 
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Drift Degradation Analysis 
following continuum constitutive models were selected for analyzing (using FLAC) stability of 
emplacement drifts under in situ stresses and thermal loads: 
 Associated (dilation angle equal to friction angle), perfectly plastic Mohr-Coulomb 
model 
 Associated Mohr-Coulomb with cohesion at yield softening in a brittle manner to 
50 percent of its initial value 
 Nonassociated (no dilation) Mohr-Coulomb with cohesion at yield softening in a brittle 
manner to 50 percent of its initial value 
 Associated Mohr-Coulomb with complete loss of cohesion at yield in a brittle manner 
 Cohesion softening  friction hardening model. In this model the cohesion softens to 
25 percent of its initial value after 0.2 percent of plastic strain, while the friction angle 
increase from 0 to 40 after 0.5 percent of plastic strain. 
The selected models certainly bound possible behavior of the lithophysal rock mass. The 
perfectly plastic Mohr-Coulomb model most likely will represent a lower bound of damage and 
deformation; perfectly brittle Mohr-Coulomb with complete loss of cohesion at yield is certainly 
a conservative case, an upper bound of damage and deformation around the emplacement drift. 
Stability of the emplacement drift was analyzed for in situ and thermal stresses after 80 years of 
heating. Damage predicted around the emplacement drifts by different models at two states (after 
excavation and after 80 years of heating) is illustrated in Figure 7-43. Green and red crosses 
around the drift in the continuum models indicate locations in the model where plastic 
deformation took place. Green crosses indicate locations of plastic deformation that occurred 
sometimes in the past; red crosses indicate locations that currently are deforming plastically. Red 
lines in the plot from the UDEC model (at the bottom of Figure 7-43) represent the positions of 
microcracksi.e., where the bonds between blocks are broken in tension or shear. Both the 
model with no residual cohesion and the cohesion softening  friction hardening model clearly 
overestimate the damage and deformation around the emplacement drifts. Conditions predicted 
by these two models do not exist anywhere inside the ESF or ECRB Cross-Drift. There is very 
good agreement between the damage predicted by the UDEC Voronoi model and two models 
with cohesion softening to 50 percent of its initial value. Also, predictions of these three models 
for Category 1 is consistent with fracturing observed in the boreholes drilled in the walls of the 
ECRB Cross-Drift in the poorest-quality estimated for the Tptpll. The UDEC model shows a 
number of fractures randomly scattered throughout the model. Those fractures are a consequence 
of the discontinuous nature of the model. As long as they are distributed and orientated 
randomly, they should be considered to be artifacts of the numerical method. The aligned and 
concentrated fractures in the drift wall represent stress-induced damage. 
Stresses and displacements along the different profiles, as calculated by the different models, are 
shown in Figures 7-44 to 7-49 for the state after excavation of the emplacement drift and in 
Figures 7-50 to 7-55 for the state after 80 years of heating. Drift stability after excavation was 
analyzed with the UDEC Voronoi block model using 0.2-m and 0.3-m block sizes. Drift stability 
ANL-EBS-MD-000027 REV 03 7-62 September 2004 

Drift Degradation Analysis 
after 80 years of heating was analyzed with the UDEC Voronoi block model using a 0.3-m block 
size only. In these cases, the UDEC Voronoi block predictions (for both stress and displacement 
predictions) fall inside the range of predictions by different continuum models. 
Figure 7-43. Damage Around the Emplacement Drifts Predicted Using Different Inelastic Models 
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Drift Degradation Analysis 
Figure 7-44. Inelastic Models of Drift Excavation: Vertical Normal Stress Along the Horizontal Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center.) 
Figure 7-45. Inelastic Models of Drift Excavation: Horizontal Normal Stress Along the Horizontal Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-46. Inelastic Models of Drift Excavation: Horizontal Displacement Along the Horizontal Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
Figure 7-47. Inelastic Models of Drift Excavation: Horizontal Normal Stress Along the Vertical Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-48. Inelastic Models of Drift Excavation: Vertical Normal Stress Along the Vertical Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
Figure 7-49. Inelastic Models of Drift Excavation: Vertical Displacement Along the Vertical Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-50. Inelastic Models After 80 Years of Heating: Vertical Normal Stress Along the Horizontal 
Profile Through the Center of Tunnel (Distance is measured from the tunnel center) 
Figure 7-51. Inelastic Models After 80 Years of Heating: Horizontal Normal Stress Along the Horizontal 
Profile Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-52. Inelastic Models After 80 Years of Heating: Horizontal Displacement Along the Horizontal 
Profile Through the Center of Tunnel (Distance is measured from the tunnel center) 
Figure 7-53. Inelastic Models After 80 Years of Heating: Horizontal Normal Stress Along the Vertical 
Profile Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
Figure 7-54. Inelastic Models After 80 Years of Heating: Vertical Normal Stress Along the Vertical Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
Figure 7-55. Inelastic Models After 80 Years of Heating: Vertical Displacement Along the Vertical Profile 
Through the Center of Tunnel (Distance is measured from the tunnel center) 
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Drift Degradation Analysis 
ConclusionAlthough stability analysis of underground excavations using the UDEC Voronoi 
block model is uncommon in engineering practice, it is used to predict rockfall in a lithophysal 
rock mass because of its clear advantages for this type of analysis (rockfall prediction) compared 
to standard, continuum-based approaches. However, it is demonstrated in this section that many 
results (i.e., extent of damage, stress and displacement profiles) of the UDEC Voronoi block 
model are very comparable to the results of continuum models which are commonly used for 
modeling of excavation stability in rock. 
7.6.5.5 UDEC Post-Development Validation Exercise 5  Comparison of the 
Mathematical Model Implemented in the UDEC Program to other Numerical 
Approaches in Solving Dynamic Tunnel Stability Problems in Fractured Rock 
(Corroboration with Information Published in the Literature) 
The Defense Nuclear Agency conducted a comparison of a number of dynamic numerical 
modeling approaches for examination of their utility in simulating the effects of dynamic stress 
wave loading of fractured rock and tunnels in fractured rock (Senseny 1993 [DIRS 162017]). A 
series of five problems of increasing complexity were posed to five organizations using 
five distinct computer programs utilizing different assumptions and solution procedures. The 
input parameters and boundary and initial conditions were given, and the calculators were asked 
to provide their results to an independent reviewer for analysis and comparison. In other words, 
this test, termed a benchmark calculation exercise provided a blind comparison of various 
methods for modeling of a complex dynamic problem involving highly non-linear response. 
The ultimate problem to be solved was that of a tunnel in explicitly jointed rock subjected to a 
spherically diverging wave initiated by a blast source (Figure 7-56). The intact rock is treated as 
a linearly elastic/perfectly plastic material, whereas the slip joint is treated as Coulomb frictional 
response. Thus, this problem has many aspects in common with the dynamic stability problems 
of importance for seismically induced rockfall. The principal difference with the present 
problem is that the dynamic source is different (a spherically diverging wave from a point source 
rather than shear and compression wave loading), although many of the same mechanical issues 
are faced in both types of problems. 
To solve this overall problem, a series of smaller problems were first posed to test proper 
solution of fundamental components of the larger problem. These fundamental problems had 
analytical expressions that could be derived and used for comparison to the model output. The 
final two problems, which involve determination of the dynamic stressing and yielding of a 
circular, steel-lined tunnel in a jointed rock mass is complex and has no analytical solution. The 
problems are reviewed in Table 7-1. 
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NOTE: The stress characteristics of the source are shown at right (Senseny 1993 [DIRS 162017]). 
Figure 7-56. Problem Geometry of the Mechanical Response of a 5-m Diameter Tunnel in Jointed Rock 
Subjected to a Spherically Expanding Blasting Source 
Table 7-1. Code-to-Code Comparison Problems 
Problem 
Number Description Comments 
1 Testing of intact rock sample to spherically 
divergent strain path in intact rock. 
Quasi-static strain path that simulates passage of a 
shock front in intact rock (i.e., demonstrates the 
model accounts properly for propagation in intact 
media). 
2 One-dimensional compression of a 5 m by 4 m 
sample of jointed rock, exercising the joints in 
normal deformation. 
Tests that the model is able to produce proper 
pressure vs. volumetric strain response for jointed 
rock and for intact rock components. 
3 Compression of a jointed block, joint in shear 
while maintaining a homogenous strain rate in 
the intact rock. 
Tests ability of model to produce proper 
deformations on slipping joint in shear when 
subjected to complex deformation path. 
4 Deformation and stress changes in a wedge-
shaped jointed rock mass subjected to 
spherically divergent wave (same as 
Problem 5, but without tunnel present). 
Ability to properly reproduce rock mass strains in the 
free field. 
5 Deformation and yield of a tunnel in a jointed 
rock mass subjected to a spherically divergent 
blast wave. Prediction of stress in rock mass 
around tunnel. 
Complex problem of a jointed rock mass subjected 
to a triangular blast wave. Highly non-linear 
response of tunnel as joints shear and large 
deformations of tunnel occur. No analytic 
solution  code to code comparison. 
Source: Senseny 1993 [DIRS 162017]. 
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Drift Degradation Analysis 
These problems tested a number of aspects of the programs that are used in the current drift 
degradation work, including: 
 Ability to represent wave transmission through intact and jointed rock 
 Ability to represent the mechanical response of joints to normal and shear loading 
 Ability to represent non-reflecting boundaries 
 Ability to represent a non-linear, joint-controlled tunnel deformation mode under 
dynamic loading. 
The numerical programs used to conduct the calculations covered a wide range of techniques and 
methodologies (Table 7-2). With the exception of the PRONTO code, the simulations were 
conducted by the organization that developed the programs, and thus, the issue of having 
ill-informed users was removed from the benchmark study. For each problem, the boundary and 
initial conditions and rock properties were provided and fully specified. The calculator then used 
their particular model to solve the problem and submit the solutions in a blind fashion. 
Table 7-2. Programs and Modeling Participants in the Benchmark Study 
Organization Abbreviation Code 
California Research and Technology 
Division, the Titan Corporation 
CRT EXCALIBUR 
(Finite Element, Joints modeled explicitly or 
via constitutive model) 
Itasca Consulting Group 
Itasca 
UDEC 
(Distinct Element/Finite Difference, joints 
modeled explicitly) 
Lawrence Livermore National 
Laboratory LLNL 
DIBS 
(Distinct Element, Rigid Block Formulation) 
RE/SPEC, Inc. RE/SPEC 
PRONTO 
(From Sandia National Laboratory, Finite 
Difference) 
Weidlinger Associates WA 
FLEX 
(Finite Element, Joints modeled explicitly or 
via constitutive model) 
Source: Senseny 1993 [DIRS 162017]. 
LLNL = Lawrence Livermore National Laboratory
ResultsThe UDEC program, as described in detail in Senseny (1993 [DIRS 162017]), provided 
good agreement to analytic solutions for problems 1 to 3. Only the results of Problems 4 and 
5 are discussed in greater detail here. Figure 7-57 shows the comparative results of radial stress 
and radial velocity at the centroid of the tunnel (not yet excavated) in problem 4. As seen in 
Figure 7-57, the overall solution of the stress and velocity predictions are quite similar for the 
various methods, primarily because there is little variation in the stresses or velocities over the 
computational grid with the exception of temporal offsets in the input function which is 
consistent with the wavespeed. The distortion, evident in at least one of the models is a result of 
boundary reflection due to ineffective non-reflecting boundaries. The Lawrence Livermore 
National Laboratory modeling approach, which has no deformability of the intact material, was 
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Drift Degradation Analysis 
found to perform poorly for the given source wavelength characteristics. UDEC was found to 
compare favorably with the finite element approaches, which appear to account properly for both 
non-reflecting boundaries, and free field straining and energy dissipation due to plastic yield. 
The final problem of tunnel stability under the divergent wave loading provides a significant 
numerical test. As stated in Senseny (1993 [DIRS 162017]), the conventional wisdom assumes 
that after peak stressing, the radial outward motion causes a rapid tangential loading while 
resulting in a loss of radial confinement and a reduced failure strength than would be assumed 
for uniaxial loading of the tunnel. The UDEC program was found to provide a reasonable match 
to crown and invert tunnel closures with other numerical approaches (Figure 7-58) with the 
exception of the RE/SPEC and Lawrence Livermore National Laboratory models, which 
provided contrary results (and were later determined to not have provided credible solutions). 
The tangential and radial stresses for various radial lines around the tunnel at peak free field 
stress arrival time are given in Figures 7-59 and 7-60. The calculations are compared to the 
static analytic solution for an orthotropic elastic material. All of the programs show a relatively 
close agreement to one another, and demonstrate that the effect of the tunnel is to relieve the 
radial stress component and greatly increase the tangential stresses in comparison to the 
equivalent free field values. Radial stresses approaching about 8 MPa at the tunnel wall is the 
result of confinement provided by the steel tunnel liner. Comparison of tunnel deformation 
modes indicate that significant springline yield and closure (displacements exaggerated by a 
factor of 10), resulting from slip on joints and intact rock plastic failure occurs in the models 
with the exception of the Lawrence Livermore National Laboratory rigid block model, again 
illustrating the importance of internal block deformability and yield. 
As concluded by Senseny (1993 [DIRS 162017]), Three of the five participants (CRT, WA, 
Itasca) obtained numerical solutions whichwhere comparisons were possibleagree with each 
other in most practical respects. All of these solutions appear credible, based on the significant 
body of evidence available: 
1. Use of rational continuum models to represent the rock 
2. Use of physically based models for the joints 
3. Compatibility of results with basic understanding of wave propagation processes 
4. Absence of obvious numerical artifacts such as spurious reflections 
5. Comparison of stresses and strains with complete and partial analytic solutions in all 
the benchmark problems. 
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Source: Senseny 1993 [DIRS 162017]. 
Figure 7-57. Radial Stress (Top) and Radial Velocity (Bottom) at the Centroid of the Future Tunnel 
Location in Problem 4 
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Source: Senseny 1993 [DIRS 162017]. 
Figure 7-58. Comparison of Predicted Tunnel Invert-Crown (Top) and Springline (Bottom) Closure for 
Problem 5 
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Source: Senseny 1993 [DIRS 162017]. 
Figure 7-59. Comparison of Radial Stress Along Radial Lines at Peak Free Field Stress Arrival Time, 
Problem 5 
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Source: Senseny 1993 [DIRS 162017]. 
Figure 7-60. Comparisons of Exaggerated Tunnel Shapes (10) at Equilibrium, Problem 5 
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7.6.6 Conclusions from UDEC Lithophysal Rockfall Model ValidationComparison to 
Criteria 
Consistent with the stated level of confidence required for the model, the above validation 
problems satisfy the criteria for mechanical models of lithophysal rock (Section 7.2.3) and 
demonstrate the following: 
A. The mechanical model, implemented within the UDEC program has been calibrated 
against laboratory compression tests to reproduce the basic deformability and strength 
properties of the lithophysal rock. To account for variability introduced by lithophysal 
porosity, the rock properties range has been subdivided into a number of categories 
that cover the entire deformability/strength range. This is done in lieu of a statistical 
treatment of the test data due to the relatively small number of large-core tests. The 
base model was calibrated to reproduce the moduli and strength for each of these 
categories. 
B. The resulting model was applied to several boundary value problems to demonstrate 
reasonable ability to predict failure mode and failure extent. The first problem was use 
of the model to represent laboratory testing. The results show an ability to reproduce 
the basic failure mechanisms observed in the laboratory testing, which includes axial 
fracture development in uniaxial compression and localization of a single fracture 
plane normal to the core axis in uniaxial tension. The model was then applied to 
represent tunnel response of the ECRB Cross-Drift at various depths. Sidewall 
springline fracturing and yield occur in the model for the lower end of the calibrated 
strength range for depths of around 300 to 350 m. The model predicts sidewall 
fracturing, parallel to the tunnel surface developing at the springline region and 
extending less than 1 m into the sidewall. This agrees qualitatively to observations of 
springline fracturing in boreholes and alcoves observed in the lower lithophysal 
exposures in the ECRB Cross-Drift and ESF main loop, in the mid- to lower-portions 
of the tunnel. Observations show that wall-parallel fractures in the springline extend 
approximately 0.5 m in depth. The model and observation agree that no fracturing 
should exist in the Tptpul which, although of the same general strength range as the 
Tptpll, the shallower depth of burial results in stresses insufficient to fail the rock 
mass. Finally, a qualitative comparison of the modeling approach to predict thermally 
induced rock fracture was demonstrated through comparison of the model to field 
observation of the Drift Scale Heater Test in the Tptpmn. This validation showed that 
the general technique is able to reproduce, qualitatively, the development of 
roof-parallel spalling fractures induced by the thermally overdriven horizontal stresses 
in the immediate crown of the drift. The model is able to reproduce the timing 
(i.e., the stress level), extent and general mechanism of the failure (i.e., splitting 
parallel to the free surface). 
C. The UDEC model has been shown to produce rock mass stress, displacement and yield 
around a heated emplacement drift that are quite similar to those produced from an 
alternative, continuum-based modeling approach for both elastic and inelastic rock 
mass constitutive models. 
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D. The ability of the model to properly represent complex dynamic boundary conditions 
is demonstrated in the UDEC Users Manual, but was further demonstrated in the 
validation exercise in which comparisons were made between UDEC and other 
numerical methods (Senseny 1993 [DIRS 162017]). In this work, conducted for the 
Defense Nuclear Agency, a rigorous code-to-code comparison was conducted in which 
test problems of increasing complexity were analyzed in a blind calculation and 
comparison exercise. The simplest of the problems involved problems that tested the 
codes ability to properly reproduce the mechanical response of the basic building 
blocks of the model (i.e., the fractures, the intact blocks, and the ability to properly 
account for boundary conditions and complex load paths). The final test was a full 
comparison of the models to a large scale field experiment of a lined tunnel in a 
fractured rock mass subjected to dynamic loading sufficient to fail the material and 
deform the tunnel lining. Of interest was that the answer was not known in advance; 
the predictions made were blind and the comparison of the results with various 
models was performed by an outside agency. The UDEC lithophysal rockfall model, 
as shown, compared very favorably with the problems and demonstrated the ability of 
the program to reasonably represent the dynamic response of a fractured media. 
7.6.7 UDEC Lithophysal Rockfall Model Limitations 
7.6.7.1 Impact of Block Discretization Level 
As was discussed previously, the discretization of the UDEC lithophysal rockfall model into 
Voronoi blocks does not represent actual internal structure of the lithophysal material. The block 
structure is merely a device that allows the formation of potential fractures within the rock mass, 
thus allowing it to fail and form independent blocks when stressed. There are two important 
points regarding the level of discretization of the blocks: 
 The block dimensions must be small enough that they do not have an overriding 
influence on the failure extent or mechanical behavior 
 The block dimensions should be commensurate to or smaller than the size of the 
expected rock particles to be formed (see Section 6.4.1). 
Therefore, it is necessary to show that the mechanical behavior of the synthetic material is 
independent of the block size. Selection of the block size for simulation is an optimization 
process. Very small block size (e.g., 100 times smaller than the drift diameter, the characteristic 
dimension of the problem) will certainly ensure that the problem solution would be practically 
independent of the block size, but would lead to very long calculation times. The block size was 
selected based on the criteria of small differences in rockfall prediction as the block size is 
reduced, and reasonable calculation time for problem solution. A comparison of the fracturing 
predictions due to drift excavation in rock mass Category 1 for 300 m overburden from 
two models considering average block edges of 0.3 m (5.4 percent of the drift diameter, or 
roughly 18 blocks across a drift diameter) and 0.2 m (3.6 percent) is shown in Figure 7-61. The 
in situ stress state is characterized with a vertical to horizontal stress ratio of 2:1. The results, 
shown in Figure 7-61, compare the failure (i.e., sidewall fracturing, for two different cases). As 
seen, the overall end-result of the calculation shows that mechanism of sidewall spalling is 
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roughly the same for both cases. There is some small difference in the amount and location of 
fracturing, depending on the block geometry. However, the cases show the same general 
behavior and the same general depth of damage in the sidewalls. Also, the effect of 
three different realizations of geometry of blocks (maintaining the same average block size of 
0.3 m) was investigated and results (for Category 1 rock mass an 350 m overburden) are shown 
in Figure 7-62. Clearly, the realization of block geometry effects a particular realization of 
cracking. But more importantly, the general characterization of cracking (density, depth) is not 
affected by the particular geometry of blocks. If the block size is too large, the effect of a 
particular geometry of Voronoi blocks on the model results would be more pronounced. From 
parametric analyses of block size, a block size of 0.3 m produced satisfactory results while 
optimizing model run time. 
NOTE: The general behavior of the drift is similar in each case. A small portion of the sidewalls fails to a depth of 
approximately 0.5 m, while the depth of fracturing is similar. Note that the failure response is not symmetric 
due to the random block patterns. 
Figure 7-61. Block Size Effect: Behavior of the Rock Mass (Rock Mass Category 1, 300-m Overburden) 
Under Vertical and Horizontal Stress at Ratio of 2:1 
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Figure 7-62. Effect of Voronoi Block Realization: Behavior of the Rock Mass (Rock Mass Category 1, 
350-m Overburden) Under Vertical and Horizontal Stress at Ratio of 2:1 
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7.6.7.2 Impact of Inertial Forces in Quasi-Static Loading 
The UDEC program uses an explicit finite difference method for solving Newtons Laws of 
Motion utilizing a fully dynamic formulation. A viscous damping scheme is used to remove 
energy from the model to achieve quasi-static equilibrium. When modeling quasi-static 
problems, such as thermal loading, it is important not to apply temperatures in too large an 
increment to avoid dynamic effects. In the modeling conducted in this study for the lithophysal 
rocks, temperatures are input from the NUFT program (see Section 3) to UDEC, which, in turn, 
calculates thermally induced expansions and stresses. Sensitivity studies indicated that the 
change in temperature applied to the UDEC program should be kept to less than 5C to avoid 
dynamic effects. 
7.6.7.3 Consideration of Homogenous and Isotropic Response of the Lithophysal Rock 
Mass 
The modeling method employed for representing lithophysal rock considers that the rock mass is 
homogeneous and isotropic, and thus a two-dimensional, cross-sectional analysis is sufficient for 
model tunnel response to heating and dynamic stressing. Essentially, this consideration means 
that the region around the tunnel that could contribute to yielding has lithophysal porosity that is 
uniformly distributed. In other words, at any given location, a tunnel driven at any azimuth 
would encounter roughly the same lithophysal porosity variation. Data on lithophysal porosity 
variation from Section 6.1.4.2 and Appendix O indicate that lithophysal porosity varies over a 
range of perhaps 10 m. 
7.6.7.4 Lack of Confined Compression Tests in the Lithophysal Rock 
No experimental data are available for large diameter lithophysal rock under confined 
conditions. This is because it is very difficult to carry out triaxial tests on samples from the 
lithophysal rock mass, since the membrane used for application of the confinement on the 
sample would deform into the lithophysae exposed on the circumference of the cylinder and 
most likely be punctured. Additionally, very large triaxial pressure vessels are rare. To 
overcome this potential issue, the PFC and UDEC lithophysal rockfall models were used to 
model the lithophysal rock as a solid matrix with internal holes. These models were calibrated 
against laboratory data on large core unconfined compression tests to verify that that relationship 
of strength and modulus to lithophysal porosity, and failure mechanisms was reasonably 
reproduced. 
As discussed in Section 9.2.3.2 of the Subsurface Geotechnical Parameters Report 
(BSC 2003 [DIRS 166660]), the calibrated PFC and UDEC lithophysal rockfall models were 
used to simulate triaxial compression tests on lithophysal rock samples of various porosity. 
The results of these numerical experiments were then used to construct expected failure 
envelopes for the lithophysal rock mass. Figure 7-63 and Table 7-3 provide a summary of the 
results of these analyses. 
Model results show that damage (due to excavation, thermally induced stresses, seismically 
induced preclosure ground motion, or time-dependent effect) is mostly confined to the drift 
boundary, and takes place under almost uniaxial loading conditions. For these conditions, 
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Drift Degradation Analysis 
correct behavior of the rock mass under confinement is not essential for proper simulation of 
damage and rockfall. 
NOTE: Several realizations of UDEC analyses were conducted at each minor principal (confining) stress level. 
Non-linear Hoek-Brown failure envelopes have been fit to each dataset. 
Figure 7-63. Sample UDEC Simulation of Triaxial Response for 23.8% Lithophysal Porosity (top) and 
Hoek-Brown Failure Criteria Fits for Lithophysal Rocks Determined from UDEC Lithophysal 
Rockfall model Triaxial Numerical Test Analysis 
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Table 7-3. Estimated Lithophysal Rock Mass Properties as Estimated from UDEC Triaxial Test 
Simulations 
Lithophysa 
l Porosity 
(%) 
UCS 
(MPa) 
Youngs 
Modulus 
(GPa) 
Friction 
Angle 
(degree) 
Cohesion 
(MPa) 
Tensile 
Strength 
(MPa) 
Hoek-
Brown sci 
(MPa) 
Hoek-
Brown mi 
0 58.7 19.8 36 14.9 4.4 58.5 6.6 
10 25.1 14.2 36 6.4 2.1 25.1 7.7 
17 15.5 11.2 35 4.1 1.7 16.5 7.3 
24 13.2 9.3 29 3.9 1.5 14 5.0 
Source: Table 9-3, Subsurface Geotechnical Parameters Report (BSC 2003 [DIRS 166660], Table 9-3). 
UCS = uniaxial compressive strength 
The derived rock mass friction angles from the UDEC lithophysal rockfall models in this table 
can be compared to laboratory measurements of friction angles measured on small samples of 
nonlithophysal rock are more than 40 (Appendix E, Section E.3). 
7.7 MODEL VALIDATION FOR REPRESENTATION OF NONLITHOPHYSAL 
ROCK 
7.7.1 Introduction 
As stated in Section 7.1, modeling of the nonlithophysal rock requires use of a 
three-dimensional, discontinuum modeling approach. A validation strategy was adopted based 
on demonstrating that the mechanical response of the fractures, which control the stability of the 
tunnel under shaking, function properly by corroboration with laboratory data. The rockfall 
component results from 3DEC are compared to an explosively loaded, scaled tunnel stability 
experiment in jointed rock. Additionally, results from the nonlithophysal rockfall model are 
compared to an alternative numerical model. Finally, an external expert technical review is used 
as a method for validation of the overall modeling approach for representation of nonlithophysal 
rock. 
7.7.2 Verification of Initial Conditions and Dynamic Boundary Conditions (Confidence 
Building During Model Development) 
Section 6.3.1.2 provides verification that the initial stress conditions and the dynamic boundary 
conditions were modeled properly within the 3DEC program. A test case was run in which the 
ground motion is applied at the base of the model and monitored at the mid-point of the model to 
ascertain that the method of ground motion application at the boundary (by applying equivalent 
stresses) properly converts the stress history to the velocity history. The test case also verified 
that no distortion of the waveform (which could result from insufficient model element 
discretization) occurred. 
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7.7.3 3DEC Post-Development Validation Exercise 1  Validation of the Fracture 
Mechanical Representation  Comparison to Laboratory Direct Shear Testing 
(Corroboration with Laboratory Data) 
7.7.3.1 Introduction 
This validation example is given to demonstrate the ability of the 3DEC program, and the joint 
constitutive model used to reproduce the joint direct shear test data from large-scale testing of 
Tptpmn samples (DTN: GS030283114222.001 [DIRS 161913]). 
7.7.3.2 Direct Shear Data 
A number of direct shear tests were run on joints obtained from 11.5-in diameter core samples 
that were drilled at a low angle to either the smooth, sub-vertical cooling joints, or the rough, 
sub-horizontal vapor-phase alterations. The cores were obtained from the Tptpmn unit. The 
tests were run by setting (in hydrostone) the two halves of the core sample containing the 
fracture in opposing halves of a steel direct shear box. The opposing halves of the fracture are 
then reconstructed and placed in a large direct shear machine. A sequence of direct shear tests 
were then run by first applying a normal stress of 1 MPa to the sample which is then slowly 
sheared by applying a lateral stress to the upper half of the sample. The sample fracture surface 
is then cleaned by compressed air, reconstructed and the test run again with normal stresses of 
4 MPa and 7 MPa (approximate) normal stresses. A final re-test at the initial 1 MPa normal 
stress level is run to document damage to the joint. One possible limitation of these tests is that 
successive damage is done to the joint surfaces by re-running the tests at increasing normal 
loads. However, with limited large sample availability, it was decided to get the greatest amount 
of information from each sample. From these tests, it is possible to plot the shear stress-shear 
displacement and normal stress-normal displacement behavior as well as the Coulomb slip 
envelope, from which the cohesion and friction angle can be calculated. The joint shear stiffness 
and dilation angle can be determined from the shear stress-shear displacement and normal 
displacement-shear displacement data, respectively. The test data for two representative tests are 
given in Figures 7-64 and 7-65 (DTN: GS030283114222.001 [DIRS 161913]). Figure 7-64 
shows the test results for a typical sub-horizontal vapor-phase parting, and Figure 7-65 shows the 
test results for the sub-vertical cooling fracture. The plots superimpose the results from the 
normal stresses as well as the re-test at the 1 MPa stress level. 
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Source: DTN: GS030283114222.001 [DIRS 161913]. 
NOTES: Cohesion is 0.3 MPa, and friction angle of the surface is 47.4. Legend shows normal stress (lbs/in2). The 
data can be accessed through the Records Processing Center Package # MOY-030226-41-01 
(MOL.20030226.0038, pp. 2-5) associated with the source DTN. 
Figure 7-64. Direct Shear Test Results for a Rough, Sub-Horizontal Vapor-Phase Parting 
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Source: DTN: GS030283114222.001 [DIRS 161913]. 
NOTES: Cohesion is zero and friction angle of the surface is 33.6. Legend shows normal stress (lbs/in2). The data 
can be accessed through the Records Processing Center Package # MOY-030226-41-01 
(MOL.20030226.0039, pp. 2-6) associated with the source DTN. 
Figure 7-65. Direct Shear Test Results for a Smooth, Sub-Vertical Cooling Joint 
7.7.3.3 Analysis 
In this validation, the 3DEC program is used to recreate the direct shear test numerically. The 
results of the model and test for the calculated surface friction angle and cohesion are compared. 
Figure 7-66 shows the 3DEC model with a horizontal fracture plane. The bottom block is fixed 
along its vertical and lower horizontal surfaces to represent the shear box. A vertical pressure is 
applied to the top of the upper block, while the lateral expansion is held fixed. A velocity is then 
applied to one of the vertical faces, forcing the top block to shear over the lower block. 
Figure 7-67 shows a cross-section through the block with superimposed shear slip vectors after it 
has begun slipping. 
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(i) 
l iilBSC 
3DEC Verson 2.01VPP, 1 MPa normastress, ks= 2e9, frc= 45.7, coh= 0.72 MPa, d= 7.1 
NOTE: Lower (blue) block has surface displacements fixed on the vertical and bottom faces to represent the fixed 
block of the direct shear test. The upper (green) block has two vertical faces fixed, one vertical face free 
and one vertical face with a prescribed horizontal velocity representing the shear displacement of the test 
machine. A constant stress is applied to the upper surface to provide the normal stress to the joint surface. 
Figure 7-66. Perspective View of 3DEC Model of Direct Shear Test of Joint 
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(i) 
l iilBSC 
3DEC Verson 2.01VPP, 1 MPa normastress, ks= 2e9, frc= 45.7, coh= 0.72 MPa, d= 7.1 
Max shear in plane = 7.108E-03 
0.000E+00 1.250E-03 1.250E-03 2.500E-03 2.500E-03 3.750E-03 3.750E-03 5.000E-03 5.000E-03 6.250E-03 6.250E-03 7.500E-03 min max interval = 1.250E-03 Color by S-Disp mag. 
Cross section plot: 
NOTE: Cross-section is taken parallel to shear movement applied by machine. 
Figure 7-67. Cross-Sectional View Through Model Showing Relative Shear Displacement of Joint 
Surfaces 
Analyses were performed for two cases: the sub-vertical, smooth cooling joint shown in 
Figure 7-65, and the sub-horizontal vapor-phase parting illustrated in Figure 7-64. Two basic 
types of joint shear constitutive models based on a standard Coulomb slip condition are available 
in the 3DEC program. The first model, the default in 3DEC (JCONS=1), considers that once slip 
is initiated, the cohesive strength of the joint is broken, and drops to zero. From that point, the 
joint reaches a residual strength based only on the friction and dilation angles of the surfaces. 
The second model (JCONS=2) considers that the cohesion of the surfaces remains constant, 
resulting in a typical elastic-perfectly plastic response. The seismic and thermal analyses 
discussed in Section 6.3 of this report use the default constitutive model. 
The JCONS=1, or default, model is applicable to both the vapor-phase partings and the cooling 
fractures. First, the rough, vapor-phase partings (which are anastomosing structures) are 
cohesive structures that have surfaces weakly bonded in situ by minerals such as cristobalite and 
tridymite. Once this bond is broken, it is sensible that the surfaces reach a residual state of 
strength based primarily on friction. The cooling joints, however, have smooth surfaces with no 
apparent cohesion or tensile resistance. Therefore, there is no difference in JCONS 1 
or 2. Figures 7-68 and 7-69 show a comparison of the 3DEC direct shear simulations to the 
laboratory tests. As seen in Figure 7-68, the comparison of model to laboratory is qualitatively 
quite reasonable, particularly for the first test conducted at 1 MPa normal stress, in which the 
joint is in an undamaged state. The comparison is still reasonable for the higher confinements, 
ANL-EBS-MD-000027 REV 03 7-89 September 2004

Drift Degradation Analysis 
but it must be realized that the model is using the average friction angle and dilation angle 
Shear Stress (MPa)
determined for the tests. The re-test at 1 MPa normal load shows virtually the same results as for 
the initial test, indicating that there is little surface damage from the previous testing. This 
makes sense since the joint has less than 2 dilation angle, and thus very little surface irregularity 
(roughness) that can be permanently damaged. The shear stiffness used in this simulation is 
determined from the tangent value (the initial loading slope). The stiffness departs from this 
approach only near its peak strength. 
5.0 
4.0 
3.0 
2.0 
1.0 
0.0 
-1.0 
lllll/m 
3EC, normal stress=1MPa 
3DEC, norma stress=4MPa 
3DEC, norma stress=6.8MPa 
Lab data, norma stress=1MPa 
Lab data, norma stress=4MPa 
Lab data, norma stress=6.8MPa 
ks = 5e9 Pa
-0.002 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.020 
Shear Displacement (m) 
NOTE: Joint sample is a subvertical, smooth cooling joint (see Figure 7-65). 
Figure 7-68. Comparison of 3DEC Mohr-Coulomb Joint Constitutive Model to Laboratory Direct Shear 
Testing for Sample 643, Hole ERCB-GTEC-CS1250-13 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 7-91 September 2004 
-1.00.01.02.03.04.05.06.07.08.09.0-0.0010.0000.0010.0020.0030.0040.0050.0060.0070.0080.0090.010Shear Displacement (m)
Shear Stress (MPa)
3DEC, normal stress=1MPa, ks=2e9 Pa/m, JCONS=13DEC, normal stress=1MPa, ks=2e9 Pa/m, JCONS=23DEC, normal stress=1MPa, ks=1e10 Pa/m, JCONS=13DEC, normal stress=1MPa, ks=1e10 Pa/m, JCONS=23DEC, normal stress=4MPa, ks=2e9 Pa/m, JCONS=13DEC, normal stress=4MPa, ks=2e9 Pa/m, JCONS=23DEC, normal stress=4MPa, ks=1e10 Pa/m, JCONS=13DEC, normal stress=4MPa, ks=1e10 Pa/m, JCONS=23DEC, normal stress=6.8MPa, ks=2e9 Pa/m, JCONS=13DEC, normal stress=6.8MPa, ks=2e9 Pa/m, JCONS=23DEC, normal stress=6.8MPa, ks=1e10 Pa/m, JCONS=13DEC, normal stress=6.8MPa, ks=1e10 Pa/m, JCONS=2Lab Data, normal stress=1MPaLab Data normal stress=4MPaLab Data normal stress=6.8MPa 
NOTE: The laboratory data are the plots displayed with symbols and the 3DEC results are shown as lines. Three 
tests are shown for three different normal stress levels. Each of these tests is compared to four different 
3DEC results that use the same friction and dilation angles as calculated from laboratory test results. Since 
3DEC uses a linear shear stiffness consideration, two different shear stiffness values have been used to 
bound the laboratory data: a tangent value (Ks=1e10 Pa/m) that represents the initial loading, and a secant 
value (Ks=2e9 Pa/m) that represents the shear displacement at peak strength. 
Figure 7-69. Comparison of 3DEC Simulation of Direction Shear Testing of a Vapor-Phase Parting (see 
Figure 7-64) 
In Figure 7-69, the comparison of the 3DEC results for both JCONS 1 and 2 shows the 
laboratory data. The vapor-phase partings, being very rough joints with high dilation angle 
(approximately 13), show a non-linear shear stiffness that is seen as the curvature in the loading 
portion of the curve. This is contrasted to the largely linear loading slope for the previous 
smooth cooling joint case. The 3DEC joint model considers a simple, linear loading slope 
characterized by a constant shear stiffness. Therefore, the approach taken in the tunnel modeling 
discussed in Section 6.3 of this report is to examine the effect of variable shear (and normal) 
stiffness on the global response. The validation of the 3DEC model examines two shear stiffness 
values: the tangential slope defined by the initial loading prior to its departure from linearity, 
and the secant slope determined from the displacement at peak shear strength. For each of these 
shear stiffness values, simulations are run for the JCONS=1 (softening model) and for 

Drift Degradation Analysis 
JCONS=2 (elastic-perfectly plastic model with no strength loss). Thus, for each level of normal 
stress (1, 4, and 7 MPa), four simulations are conducted. Each of the simulations considers a 
constant friction angle and dilation angle derived from the laboratory test data. 
As seen in Figure 7-69, the laboratory data are fit reasonably well with the selection of a secant 
shear stiffness and no post-peak softening of the material response. The tangent stiffness 
consideration, coupled with the post-peak softening model (JCONS=1) is conservative in that 
peak strength is reached after a smaller level of shear displacement, and that the strength drops to 
a slightly smaller residual value when cohesion of the surface is considered to be destroyed. The 
tunnel scale modeling is conducted with values of shear stiffness (1e10 Pa/m  default, and 
2e9 Pa/m) that bound the prospective range. It was shown in Section 6.3.1.6.2 that sensitivity 
studies of shear stiffness have a minor effect on the calculation of rockfall. 
7.7.4 3DEC Post-Development Validation Exercise 2  Validation of the Nonlithophysal 
Rockfall Model Implemented in 3DEC by Comparison to an Explosively Loaded, 
Scaled Tunnel Stability Experiment in Jointed Rock (Corroboration with 
Information Published in the Literature) 
In this example, data from a Defense Nuclear Agency-sponsored explosive tunnel stability field 
experiment conducted in a simulated jointed rock mass is used as a validation test for the 
3DEC program. This problem tests a number of aspects of 3DEC that are used in the current 
drift degradation model, including: 
 The ability of 3DEC for representation of wave transmission through intact and jointed 
rock 
 The ability of 3DEC for representation of the mechanical response of joints to dynamic 
normal and shear loading 
 The ability of 3DEC for representation of a non-linear, joint controlled tunnel 
deformation under dynamic loading. 
Details of the physical experiment are described in detail in Senseny and Pucik 
(1999 [DIRS 168479]), and summarized here. The test involved blast-induced dynamic loading 
of a scaled, lined cylindrical tunnel in a simulated jointed rock, and was described in 
Section 7.6.5.5. The purpose of the test was to provide a realistic experiment at a relatively large 
scale for validation of and comparison of a number of numerical modeling programs capable of 
representing tunnel failure under dynamic loading. 
The experiment consisted of a simulated rock mass composed of over 4000 limestone blocks, 
each being 51 mm square by 0.6 m or 1.2 m in length (Figure 7-70). The bricks were stacked 
into a nearly cubical specimen measuring 2.1 m square and 2.4 m in length with a central 0.4 m 
diameter cylindrical hole (the tunnel) that was lined with a thin aluminum tube. Instrumentation 
included 46 gauges for monitoring velocity, stress, joint slip and tunnel closure. 
The entire sample was placed in a pit and covered with concrete. The midline of the concrete 
surface was formed in a half-cylinder to allow application of a cylindrically-diverging blast wave 
ANL-EBS-MD-000027 REV 03 7-92 September 2004 

Drift Degradation Analysis 
generated by explosives. The resulting stress wave had a radius of 4.4 m, a rise time of about 
500 m, a peak stress of about 100 MPa and peak particle velocity of about 14 m/sec, a total 
radial displacement of about 25 mm, and peak circumferential strain of about 0.6 percent. This 
divergent dynamic environment was sufficient to cause joint slip, intact rock fracture and 
permanent deformation of the lined opening. 
A number of calculators were presented with the model boundary and initial conditions, the 
block geometry and laboratory-measured rock and joint properties. A blind validation of a 
number of two-dimensional numerical models (including the UDEC program), which used 
different methods for simulating joint surfaces, was then conducted as discussed in 
Section 7.6.5.5. The term blind here refers to fact that the numerical analysts were asked to 
produce model predictions of the system response without knowledge of the experiment 
outcome. Analysts were provided the basic intact and joint material testing data, test geometry 
and boundary and initial conditions. They subsequently formulated the analysis methodology, 
conducted the numerical analyses and submitted the results to a separate group whose purpose 
was to perform code-to-experiment and code-to-code comparisons. Senseny and Pucik 
(1999 [DIRS 168479]) gathered the results of the simulations and performed code-to-experiment 
and code-to-code comparisons from the various calculators. Here, the results of the same 
experiment are compared to numerical predictions made by the 3DEC program. 
7.7.4.1 Rock Properties Data 
The rock chosen for this test was a porous limestone from the Salem formation. Intact 
specimens were tested in triaxial compression and triaxial extension. The reported data shown in 
Figure 7-71 indicate very little variation between tests, and the results were consistent between 
three different testing laboratories. 
Seen in Figure 7-72, failure envelopes developed from the triaxial compression and triaxial 
extension tests. Tests also were conducted on joints to determine their shear strength and 
stiffness. Special specimen preparation procedures were employed to ensure that the joint 
surfaces in the laboratory tests were similar to those in the jointed-rock tests. The normal 
compressibility of the joint surfaces was determined by unconfined compression tests on 
specimens with a single joint oriented at 90o to the specimen axis. Each specimen was loaded to 
approximately 75 percent of its unconfined strength and then unloaded. Figure 7-73(a) shows 
typical joint normal-direction compressibility data. Under normal loading, the joints are fully 
closed after approximately 0.05 mm displacement. 
The shear strength of the joints was determined by a series of triaxial compression tests on 
cylindrical specimens, each containing a single joint oriented at 30o to the specimen axis. The 
confining pressure in these tests ranged from 1 MPa to 35 MPa. At confining pressures up to 
30 MPa, the specimens failed by sliding of the joints at approximately constant stress. When 
loaded at a confining pressure of 35 MPa, the intact portion of the test specimen failed without 
sliding along the joint. Figure 7-73(b) plots peak shear stress on the joint as a function of normal 
stress on the joint for tests performed at confining pressures up to 30 MPa. The joint strength 
data are well represented by a straight line passing through the origin with a 38.3o friction angle. 
ANL-EBS-MD-000027 REV 03 7-93 September 2004 

Drift Degradation Analysis 
7.7.4.2 Constitutive Models 
Limestone Intact and Joint Constitutive ModelsThe constitutive model used for intact 
limestone in the 3DEC program is an elastic-plastic, strain-softening model (no cap on the yield 
surface) using a Mohr-Coulomb shear failure surface with tension cutoff. Greater detail on the 
Mohr-Coulomb strain-softening plasticity model can be found in the 3DEC Users Manual 
(Itasca Consulting Group 2002 [DIRS 160331]). The strains are subject to a non-associated flow 
with zero dilatancy in shear and associated flow in tension. The strain softening is controlled via 
isotropic softening of the intact material cohesion and tensile strength. No rate dependence of 
material properties is considered. The joint model used considered Coulomb slip with constant 
shear and normal stiffness based on the data shown in Figure 7-73, and given in Table 7-4. The 
constitutive model for the aluminum liner was an isotropic-hardening Tresca model with 
properties given in Table 7-4. 
Source: Senseny and Pucik 1999 [DIRS 168479]. 
Figure 7-70. Geometry of the 2.1-m Square (2.4 m Long) Joint Rock Experiment Showing Internal 
Tunnel and Instrument Locations 
ANL-EBS-MD-000027 REV 03 7-94 September 2004 

Drift Degradation Analysis 
Source: Senseny and Pucik 1999 [DIRS 168479]. 
Figure 7-71. Stress Strain Curves for Salem Limestone: (a) Unconfined Compression and (b) Triaxial 
Compression 
Source: Senseny and Pucik 1999 [DIRS 168479]. 
Figure 7-72. Comparison of Extension and Compression Strength Envelopes for Salem Limestone 
ANL-EBS-MD-000027 REV 03 7-95 September 2004 

Drift Degradation Analysis 
Source: Senseny and Pucik 1999 [DIRS 168479]. 
Figure 7-73. Compressibility and Strength in Salem Limestone: (a) Normal-Load Compressibility and (b) 
Shear Strength Envelope 
Table 7-4. Properties of the Limestone Rock Mass and Aluminum Liner 
Internal 
Bulk Shear Angle of Tension 
Component 
Modulus 
(GPa) 
Modulus 
(GPa) 
Friction 
(degrees) 
Cohesion 
(MPa) 
Strength 
(MPa) 
Density 
(kg/m3) 
Limestone Intact Rock 
Properties 21.5 12.3 56.7 8 5.4 2340 
Limestone Joint Properties 500 100 38.3 0 0 N/A 
Aluminum Liner 69.4 25.9 0 27.5 55 2700 
Source: Senseny and Pucik 1999 [DIRS 168479]. 
NOTE: Limestone is considered to strain-soften via a post-peak reduction in cohesion and tensile strength. 
Cohesion is reduced linearly from 8 MPa to 3 MPa over 0.2 percent plastic strain. Tensile strength is 
reduced linearly from 5.4 MPa to 0 over 0.2 percent plastic strain. Aluminum is considered to behave as 
a strain-hardening material via a post-yield linear in cohesion and tensile strength. Cohesion increases 
linearly from 27.5 to 60 MPa over 2.9 percent plastic strain. Tensile strength increases linearly from 55 to 
120 MPa over 2.9 percent plastic strain. 
Block ModelThe 3DEC model incorporated information about the effective vertical and 
horizontal gaps between the limestone bricks as measured in the actual experiment. The width of 
these gaps was determined using an indirect technique that relied on careful measurements of the 
overall dimensions of the stack of blocks in both directions. The contribution of the solid 
material to these measurements (i.e., the values that would be expected in the absence of 
gaps) was estimated by multiplying the number of bricks by the average brick thickness. The 
differences between these numbers and the actual measurements then provided an estimate of the 
total effective gap width. Dividing these differences by the number of joints then provides an 
estimate of the average effective gap thickness in each direction. 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 7-97 September 2004 
Since post-test measurements of the test specimen showed that the deformation was symmetric 
about a vertical plane through the tunnel mid-length and was nearly constant in the middle half 
of the specimen (Senseny and Pucik 1999 [DIRS 168479]), the problem can reasonably be 
represented using a two-dimensional, plane strain simulation. Therefore the 3DEC model 
(Figure 7-74) can be simplified to represent a thin slice parallel to the tunnel axis. The tunnel 
lies in the z-direction, with Figure 7-74 depicting the x-y plane. The boundary conditions 
applied include: 
 Fixed displacements on the x-y plane outer surfaces to represent the plane-strain 
condition perpendicular to the tunnel axis 
 A roller boundary along the left hand y-z surface to represent a symmetry plane 
 Fixed displacements on the lower x-z and outer y-z surfaces 
 Free upper surface with application of the input waveform above the symmetry line. 
XYFixed boundaryx-y faces fixed 
boundary surfacesat out-of-plane directionsPoint of particle velocity history applicationRoller boudary -
fixed in x-directionFixed boundaryFree boundary 
Figure 7-74. 3DEC Half-Symmetry Model Used in the Simulation Showing Boundary Conditions 

Drift Degradation Analysis 
The measured particle velocity time histories induced by the input blast at its application point 
were used as a time-dependent boundary condition at the symmetry line at the top of the model 
above the tunnel. The subsequent stress and deformation induced in the stack of blocks were 
monitored during the test at the gauge locations shown in Figure 7-70: the stress history 
measured at two locations above the crown and at three locations laterally from the springlines; 
deformation of the tunnel crown-invert; and springline diameters. The 3DEC model output is 
compared to the time histories of these measurements. 3DEC output is also compared to the 
deformed shape of the aluminum tunnel liner as determined by measurement after the test was 
completed. Data concerning slip at the joint slip meter gauges were not recorded in 3DEC, as 
the movements in the actual test were outside the resolution of the installed instrumentation. 
Seen in Figure 7-75, the predicted deformation of the thin tunnel liner. In the experiment, the 
closure instrumentation that was to be used to measure the tunnel liner movements failed, and 
thus there is no time history of tunnel deformation available for model-test comparison. 
Therefore, Figure 7-75 shows only the final roof-to-floor and wall-to-wall closures of the liner 
(on the right edge of the figure) as measured after the test. The predicted and actual final 
displacements of the crown and springline displacements show close agreement. 
Seen in Figure 7-76, the predicted and measured stresses at the two gauges located on the 
specimen centerline above the tunnel crown (FP 24 and 27). The 3DEC stresses were monitored 
in the blocks adjacent to the actual stress measurement locations, which were directly on the 
symmetry line. The adjacent block, was chosen for comparison purposes as the symmetry line 
boundary conditions in 3DEC impose a condition of no rotation of the half-blocks along this line. 
The symmetry condition simplifies the model and the associated computing time, but locally 
results in solution inaccuracy. Since this consideration will affect the modeled stresses at this 
location, the adjacent block, which is free to translate or rotate provides a better comparison 
point. As seen in Figure 7-76, the stresses in the blocks directly adjacent to the measurement 
show good correlation to the measured values. 
As seen in Figure 7-77, the predicted and measured stresses at the six gauges are located adjacent 
to the springlines (FP 23, 25, 26, 28 and 29). Because of symmetry in the experiment, the 
gauges on each side of the tunnel measure similar stress histories and, therefore, provide a 
measure of precision. As the figure shows, the precision in these stress measurements is very 
good. 3DEC predicts the wave arrival time accurately. The magnitude of the 3DEC prediction 
at stress points FP23/28 and FP25/26 are lower than those measured in the experiment. At stress 
point FP29/22, the magnitude is similar to the measured stresses. In each case along the 
springline, there is a dip in the stresses after approximately 1.8 ms. This is a result of a wave 
reflection from the bottom of the model and could be avoided by using non-reflecting 
boundaries. However, this simulation was done using the same conditions as were prescribed for 
the numerical experiments as outlined in Senseny and Pucik (1999 [DIRS 168479]). 
After the test, the tunnel liner was recovered and measured to determine more information than 
was obtained from the crown-invert and springline diameter changes alone. The shape of the 
liner was measure at three different locations. 
As seen in Figure 7-78, the magnified, measured, and predicted shape shows the deformed 
aluminum liner. Over the entire perimeter, the liner displacements as predicted by 3DEC lie 
ANL-EBS-MD-000027 REV 03 7-98 September 2004 

Drift Degradation Analysis 
within the variability of the actual measurements. 3DEC accurately predicts the diametral 
closure along the centerline and the diametric expansion along the springline. 
5.0 
Crown - Invert Closure (%)
4.0 
3.0 
2.0 
1.0 
0.0 
3DEC 
Experiment 
Experiment 
Experiment 
01 23 
Tim e (m s) 
2.0 
1.0 
0.0 
-1.0 
-2.0 
-3.0 
3DEC 
Experiment 
Experiment 
Experiment 
Sprinline Closure (%) 
0 123 
Tim e (m s) 
Source: DTN: MO0408MWDDDMIO.002, file mighty_north_2.xls. 
Figure 7-75. Predicted (3DEC) and Measured Final Deformation (Exp) of the Crown-Invert and 
Springline Tunnel Diameters at Three Locations Along the Tunnel Length 
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Drift Degradation Analysis 
150 
100 
50 
Vertical Stress (MPa) 
Vertical Stress (MPa) 
0 
01234 
FP24 
3DEC 
3DEC B 
Tim e (m s) 
150 
100 
50 
0 
01234 
FP27 
3DEC 
3DEC B 
Tim e (m s) 
Source: DTN: MO0408MWDDDMIO.002, file mighty_north_2.xls. 
NOTE: The points labeled 3DEC are taken from the model at the exact reported stress gauge location, and 
3DEC A and 3DEC B in the 3DEC blocks immediately to the left and right of the reported location, 
respectively. 
Figure 7-76. Predicted Stresses in Block Adjacent to Measured Stresses (Gauges FP24 and FP27) 
Above the Tunnel Crown 
ANL-EBS-MD-000027 REV 03 7-100 September 2004 

Drift Degradation Analysis 
Vertical Stress (MPa) 
Vertical Stress (MPa) 
150 
100 
50 
0 
FP23 
FP28 
3DEC 
3DEC A 
3DEC B 
01234 
Tim e (m s) 
150 
100 
50 
0 
FP25 
FP26 
3DEC 
3DEC A 
3DEC B 
01234 
Tim e (m s) 
Source: DTN: MO0408MWDDDMIO.002, file mighty_north_2.xls. 
NOTE: The points labeled 3DEC are taken from the model at the exact reported stress gauge location, and 
3DEC A and 3DEC B in the 3DEC blocks immediately to the left and right of the reported location, 
respectively. 
Figure 7-77. Predicted and Measured Stresses Adjacent to the Tunnel Springline 
liOrigina Shape 
3DEC 
Experment 
Source: DTN: MO0408MWDDDMIO.002, file mighty_north_2.xls. 
Figure 7-78. Measured and Predicted Shape of the Deformed Aluminum Liner (Displacements are 
Magnified by 10) 
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Drift Degradation Analysis 
7.7.5 3DEC Post-Development Validation Exercise 3 - Nonlithophysal Rockfall Model 
Validation by Corroboration with Alternative Numerical Model 
The probabilistic key-block software DRKBA is used as an alternative numerical model to 
validate the 3DEC model results on block size distribution and rockfall frequency. The DRKBA 
code employs a numerical technique with Monte-Carlo simulation to account for the statistical 
variation of the joint system. A description of DRKBA approach and the input data for the 
probabilistic key-block analysis are provided in Appendix D. 
The results of DRKBA analyses for the 110-4 seismic hazard are presented in Figure 7-79. Size 
distributions are compared with the 3DEC results, including both 110-4 and 110-7 seismic 
hazards. The frequency of blocks for both DRKBA and 3DEC is also provided in Figure 7-79. 
The size distribution curves show that the 3DEC results predict smaller size blocks for the same 
level of cumulative percentiles compared to the DRKBA results. The frequency of rockfall from 
the 3DEC results is much higher compared to the DRKBA results. 
While both the DRKBA and 3DEC approaches have used the same fracture data inputs based on 
tunnel mapping in the ESF and ECRB Cross-Drift, the respective methods for developing 
synthetic fracture geometries are different. The DRKBA joint geometry generator produces 
larger joint planes concentrated about the center of the three-dimensional model space. The 
3DEC joint generator (i.e., FracMan) develops a more realistic sizing of joint planes with an 
improved distribution throughout the model space, resulting in a higher frequency of smaller 
blocks compared to DRKBA. 
The shape and range of the DRKBA and 3DEC rockfall distributions are generally similar. The 
DRKBA method resulted in a maximum block size of 34 tons, which is similar the 29 ton 
maximum block from the 3DEC results for the 110-7 seismic hazard. 
7.7.6 3DEC Post-Development Validation Exercise 4 - Model Validation by Expert 
Technical Review 
An outside expert technical review was conducted as a means of validation, as discussed in 
procedure AP-SIII.10Q, Models. Dr. John Tinucci of the PanTechnica Corporation in 
Minneapolis, Minnesota, was contracted for this purpose. Dr. Tinucci is a Professional Engineer 
and has a Ph.D. from the University of California, Berkeley, where his thesis research was in the 
area of analysis of the stability of blocky rock masses, and, in particular, in the development of 
key-block methods for tunnel stability assessment. He has extensive experience in the use of the 
3DEC program for surface and underground stability assessment. Particularly valuable 
experience for the present application is his use of 3DEC to model dynamic stability of deep 
underground mine openings. 
Dr. Tinucci was provided with a number of reports and presentations detailing the geology, 
laboratory properties, modeling methodology and preliminary results of the FracMan and 
3DEC modeling work prior to visiting the site. A site visit of three days was then conducted in 
which discussions were held with YMP engineers and geologists regarding the FracMan and 
3DEC work. A visit to the ESF main loop and ECRB Cross-Drift was conducted to view the 
rock mass conditions in situ. 
ANL-EBS-MD-000027 REV 03 7-102 September 2004 

Drift Degradation Analysis 
Dr. Tinuccis review report is provided in Appendix N. In general, the technical review finds the 
3DEC and FracMan approaches to be adequate for simulation of the rockfall problem in the 
nonlithophysal rocks. The model approach, data selection and ranges were found to be adequate. 
The model boundary conditions and methodology for application of the ground motions were 
also felt to be proper. 
7.7.7 Conclusions and Comparison to Validation Criteria 
The following discussion of comparison of validation criteria is given. 
A. Analyses presented in Sections 6.3 and 7.7.4 indicate that the 3DEC program is able to 
represent dynamic boundary conditions and wave transmission through the material in 
an accurate fashion. 
B. The comparison of the 3DEC program to the results of direct shear testing on fractures 
from the Tptpmn shows that 3DEC is able to adequately reproduce the shear 
constitutive response of the cooling and vapor-phase altered fractures. Use of 
sensitivity analyses to bound fracture shear stiffnesses in the vapor-phase altered 
fractures is warranted, although the analysis shown here indicates that the use of 
tangent stiffnesses and a softening joint mechanical model (the default used in 
Section 6.3 analyses) appears to be conservative in nature, resulting in more rockfall. 
C. The ability of 3DEC to represent the complex problem of an explosively-loaded tunnel 
in jointed rock was tested via comparison to a scaled field experiment in limestone. 
The field experiment tested several capabilities of the program, including: 
 The predictive capability of the nonlithophysal rockfall model as implemented in 
3DEC for structures in jointed rock was demonstrated by comparing predictions 
with the results of a large jointed-rock precision test specimen that that involved 
dynamic loading and large strain of a lined cylindrical opening. Based on this 
validation case, 3DEC can reasonably simulate the wave transmission through the 
jointed rock, the stress change in the rock mass resulting from the dynamic 
excitation, and the large strain and permanent deformation of a tunnel in jointed 
rock and its internal support. 
 3DEC demonstrated the ability to represent complex dynamic boundary conditions. 
 3DEC accurately predicted the final shape of the deformed liner. 
 3DEC accurately predicted the arrival time of the stress waves, thus validating the 
wave transmission simulation through the jointed rock. 
 3DEC accurately predicted the stress magnitudes and wave shape at several of the 
monitoring points. Wave reflections disturbed this prediction in some locations. 
Note that the inclusion of random gaps in the model adds difficulty in matching the 
stresses at specific locations. 
ANL-EBS-MD-000027 REV 03 7-103 September 2004 

Drift Degradation Analysis 
Cumulative Frequency of Occurrence
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0% 
0 1 2 3 4 5 6 7 8 9101112131415 
Block Size (tonnes) 
0.1 0.1 0.15 
4 1 2 
maximum block simulated 34 3 29 
55 535 2926 
DRKBA 1E-4 
3DEC 1E-4 
3DEC 1E-7 
Block Size (tonnes) DRKBA 1E-4 3DEC 1E-4 3DEC 1E-7 
50th percentile (median) 
95th percentile 
frequency (blocks/km) 
Figure 7-79. Comparison of Rockfall Results from 3DEC and DRKBA 
 The 3DEC model as shown compared very favorably with the physical experiment 
and demonstrated the ability to represent reasonably the dynamic response of a 
fractured media. 
D. The overall adequacy of the modeling approach and the specification of property 
ranges have been validated by corroboration with the results of an alternative 
numerical model and by external technical review. 
7.8 VALIDATION SUMMARY 
The drift degradation models for lithophysal and nonlithophysal rocks have been validated by 
applying acceptance criteria based on an evaluation of the models relative importance to the 
potential performance of the repository system. The validation requirements defined in the 
Technical Work Plan for: Regulatory Integration Modeling of Drift Degradation, Waste Package 
ANL-EBS-MD-000027 REV 03 7-104 September 2004 

Drift Degradation Analysis 
and Drip Shield Vibratory Motion and Seismic Consequences (BSC 2004 [DIRS 171520], 
Section 2.2.1) have been fulfilled. This includes: 
 Corroboration with laboratory measurements or relevant observations not previously 
used to develop or calibrate the models 
 Corroboration of results with alternative mathematical models 
 Corroboration with data published in referred journals or literature 
 Technical review by reviewers independent of the model development, checking, and 
interdisciplinary review. 
Requirements for confidence building during model development have also been satisfied. The 
model development activities and post-development validation activities described establish the 
scientific bases for the drift degradation models. Based on this, the drift degradation models are 
considered to be sufficiently accurate and adequate for the intended purpose and to the level of 
confidence required by the models relative importance to the potential performance of the 
repository system. 
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Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK
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Drift Degradation Analysis 
8. CONCLUSIONS 
8.1 SUMMARY 
This report was developed to document the degradation of the rock mass surrounding the 
emplacement drifts of a geologic repository at Yucca Mountain. The factors leading to drift 
degradation include the stresses induced by the heat released by the emplaced waste, the stresses 
due to seismically related ground motions, and the strength loss of the rock mass due to 
time-dependent strength degradation. These factors have been modeled and analyzed, resulting 
in the prediction of the amount and size distribution of rockfall in the repository drifts during 
both the preclosure and postclosure regulatory periods. The data developed and documented in 
this model report have been entered into the Technical Data Management System 
(DTNs: MO0408MWDDDMIO.002, MO0408MWDRNLRA.002, MO0306MWDDPPDR.000, 
MO0404MWD3DRFA.000, MO0407MWDDSLCR.000, MO0407SPAMTSHR.000, and 
MO0403MWDRPNLR.000). 
The following statements summarize the results from this drift degradation modeling and 
analysis activity and present the key conclusions: 
 The rock mass at the repository host horizon has been geologically characterized to 
support the rockfall modeling activities presented in this report. Drift degradation 
models have been developed for both nonlithophysal and lithophysal rock. A detailed 
description of the rock mass characteristics of the repository host horizon is provided in 
Section 6.1. The available rock mass geotechnical data, including fracture geometry 
(Section 6.1.4.1, Section 6.1.6, and Appendix B), lithophysal abundance and geometric 
characteristics (Section 6.1.4.2 and Appendix O), and geotechnical rock properties 
(Section 6.1.3 and Appendix E), are sufficient to support detailed drift degradation 
analyses using both continuum and discontinuum approaches. 
 The drift-scale temperature history was calculated throughout the preclosure and 
postclosure periods of the repository as documented in Section 6.2. The temperature 
history was used to calculate the thermal stress state that develops within the rock mass 
due to the heat energy released from the stored nuclear waste, and appropriate boundary 
conditions for thermal loading have been applied (Sections 6.2, 6.3.1.3, and 6.4.2.3). 
Appropriate thermal properties have been used in the thermal-mechanical calculation as 
provided in Section 4.1 and Appendix E (Section E5). 
 A nonlithophysal rockfall model was developed using the three-dimensional 
discontinuum code, 3DEC, with the following features: 
- Appropriate boundary conditions are provided for thermal and seismic loading 
(Sections 6.3.1.2 and 6.3.1.3). 
- Critical fracture patterns are included from multiple sampling from a synthetic 
rock mass volume that contains a realistic fracture population based on field 
mapping data (Section 6.1.6). 
ANL-EBS-MD-000027 REV 03 8-1 September 2004 

Drift Degradation Analysis 
- Appropriate thermal and mechanical properties of rock blocks and joints are 
used (Appendix E). 
- Long-term degradation of joint strength parameters is considered 
(Section 6.3.1.5). 
- Site-specific ground motion time histories appropriate for both the preclosure 
( 510-4 and 110-4 hazard levels) and postclosure (110-5, 110-6, and 110-7 
hazard levels) time periods are included in the model (Section 4.1.5). 
 A lithophysal rockfall model was developed using the two-dimensional discontinuum 
code, UDEC, with the following features: 
- Appropriate boundary conditions are provided for thermal and seismic loading 
(Sections 6.4.2.1 and 6.4.2.2). 
- The rock mass is represented as an assembly of polygonal, elastic blocks in 
which the bond strength of the blocks is calibrated such that the overall 
mechanical behavior of the mass is consistent with the material model 
developed for the lithophysal rock (Section 7.6.4). 
- The lithophysal rockfall model allows for the formation of stress-induced 
fractures between blocks (i.e., the formation of internal fracturing), separation 
and instability (under the action of gravity or seismic shaking) of the rock mass 
around the drift (Section 6.4.2). 
- Appropriate thermal and mechanical properties of rock blocks and joints are 
used (Appendix E). 
- Long-term degradation of rock mass strength is considered (Section 6.4.2.4). 
- Site-specific ground motion time histories appropriate for both the preclosure 
( 510-4 and 110-4 hazard levels) and postclosure (110-5 and 110-6 hazard 
levels) time periods are included in the model (Section 4.1.5). 
 Model validation activities include (1) validating the mechanical material models or 
representations for the two specific repository host rock types (i.e., lithophysal and 
nonlithophysal rocks), and (2) validating the implementation of these material models in 
general numerical modeling schemes (Section 7). 
 The results for the nonlithophysal units are summarized as follows: 
- Preclosure ground motion results in minor drift damage due to rockfall. 
- Postclosure ground motion results in varying extent of drift damage due to 
rockfall, with localized areas of rock failure sufficient to cover the drip shield. 
ANL-EBS-MD-000027 REV 03 8-2 September 2004 

Drift Degradation Analysis 
- Thermal effects have a minor impact on rockfall. 
- Time-dependent strength degradation has a minor impact on rockfall. 
 The results for the lithophysal units are summarized as follows: 
- Degradation is primarily controlled by stress conditions. 
- Preclosure ground motion results in minor drift damage due to rock failure. 
- Damage to the host rock is not significantly accumulating from multiple 
preclosure ground motions (Section S3.4.3). That is, a preclosure seismic 
event is shaking loose rock fragments that have already failed by strength 
degradation and thermal stress; no new fractures and failures are caused by this 
low amplitude ground motion. 
- Postclosure ground motion results in collapse of the drift, with fragmented rock 
particle sizes on the order of centimeters to decimeters. 
- Thermal and time-dependent effects can result in localized to significant areas 
of rock failure, depending on the selection of the degree of strength loss of the 
rock mass with time. The analyses of the available static-fatigue test data 
indicate that an approximate 40 percent reduction in cohesive strength occurs 
over a 20,000 year period. The nominal case for drift degradation 
(i.e., considering thermal and time-dependent effects, but excluding seismic 
effects) results in only partial collapse of the drift at 20,000 years, as depicted 
by Figures S-41 through S-44. The analyses of the available static-fatigue test 
data indicate that the lower bound quality rock mass can be represented as rock 
mass Category 2, which represents only about 10 percent of the total 
lithophysal rock mass in the emplacement drifts. A combination of the 
thermally induced stresses with time-dependent strength degradation results in 
a deterioration of the walls for Category 2. As rock mass quality increases, 
there is less rockfall from the walls and more rockfall from the drift roof. 
Preclosure seismic ground motion causes additional, but not significant, 
rockfall as a result of shaking down already loose, broken ground. 
 The drift degradation models and analyses documented in this report address the 
requirements of NRC/DOE agreements items regarding rockfall and related issues to 
support the resolution of NRCs KTI on Repository Design and Thermal-Mechanical 
Effects (Section 6.8). 
8.2 ASSESSMENT 
The drift degradation and modeling activities presented in this report address the criteria 
identified in Section 4.2 as summarized in Table 8-1. The rockfall models have adequately 
captured the physical phenomena associated with the various components of rock mass behavior 
anticipated within the repository horizon. Appropriate boundary and initial conditions have been 
ANL-EBS-MD-000027 REV 03 8-3 September 2004 

Drift Degradation Analysis 
applied, and the technical bases for the development of these rockfall models have been 
adequately documented. Sufficient data have been collected to adequately model the drift 
degradation processes. The technical bases and ranges of data used in the rockfall models are 
documented. Data uncertainty (Section 6.5) has been characterized through parameter sensitivity 
studies in the rockfall models. Model uncertainty has been characterized through an evaluation 
of alternative conceptual models, and the model results have been validated by comparison to 
field and laboratory data, alternative numerical approaches, and industry experience through 
external technical review. The most significant uncertainties impacting the results of the rockfall 
models are the uncertainties associated with the postclosure ground motion and time-dependent 
strength degradation. Some of the ground motions provided are larger than the largest ground 
motions observed and may not be physically realizable. Therefore, predictions of complete drift 
collapse with postclosure ground motion may be unrealistic. Without a technical basis to limit 
such ground motions to smaller values, these inputs represent the best available information to 
support this work. Prediction of time-dependent strength degradation for the duration of the 
regulatory period of 10,000 years is a highly approximate task. A significant program of 
static-fatigue testing of Tptpmn core specimens is currently being conducted. A part of this 
static-fatigue data has been included in this document (Section 6.4.2.4.2). This present work will 
be updated as additional long-term testing data are developed. 
8.3 RECOMMENDATIONS 
The drift degradation and modeling activities presented in this report are sufficient to support a 
license application. Specifically, the drift degradation results presented in Sections 6.3 and 6.4 
are sufficient to provide input to drip shield and waste package design calculations, consequence 
models for the seismic scenario for TSPA-LA, and seepage abstraction models for TSPA-LA. 
ANL-EBS-MD-000027 REV 03 8-4 September 2004 

Drift Degradation Analysis 
Table 8-1. Mapping of Yucca Mountain Review Plan Acceptance Criteria and Drift Degradation Analysis 
Acceptance 
Criteria Subcriteria Paraphrase of Subcriteria Sections Where Addressed 
1 Total system performance 
incorporates important aspects of 
model 
1.1  Background 
6.3.1.2  Rockfall in nonlithophysal units 
feed to SCAa 
6.4.2  Rockfall in lithophysal units and 
quasi-static drip shield loads  feed to SCA 
6.4.2.2.4  Drift profile change to DSAb 
7.2  Level of importance to TSPA for 
model validation 
8  Conclusions 
2 Description of geological and 
engineering aspects that may affect 
design, couplings, of mechanical 
disruption 
1.1  Background 
6.1  Rock mass characteristics and 
discussion of geologic parameters of 
importance 
AC1: 6.2  Thermal mechanical calculations that 
System 
description and 
model 
integration are 
adequate 
provide thermal environment 
6.3.1.2, 6.4.2  Rockfall parameters for 
drip shield evaluation 
6.4.2  Drip shield loading parameters and 
drift profile change parameters for SCAa 
and DSAb 
3 Description of assumptions and 
technical bases consistent with 
other abstractions 
4  Inputs, includes data and parameters, 
criteria and codes and standards 
5  Assumptions 
6.1  Geology and rock mass 
characterization consistent with other 
abstractions 
4 Boundary and initial conditions 
propagated through abstractions 
4  Input  In situ stress, thermal loading 
and ground motion data 
6.3, 6.4  Boundary conditions specific to 
model described 
Appendix W  Thermal and mechanical 
boundary condition verification 
5 Sufficient data for assessment of 
FEPs 
4  Input data 
5  Assumptions 
6.5  Uncertainties and limitations 
6.6  FEPs discussion 
6 Criticality Not relevant to this document 
1 Geological and engineering values 4  Input data 
AC2: used are adequately justified 5  Assumptions 
Data are 6.5  Uncertainties and limitations 
sufficient for 
model 
7.4, 7.5, 7.6  Development and validation 
of material model and numerical model for 
justification lithophysal rock 
Appendix E  Rock properties 
ANL-EBS-MD-000027 REV 03 8-5 September 2004 

Drift Degradation Analysis 
Table 8-1. Mapping of Yucca Mountain Review Plan Acceptance Criteria and Drift Degradation 
Analysis (Continued) 
Acceptance 
Criteria Subcriteria Paraphrase of Subcriteria Sections Where Addressed 
2 Sufficient data has been collected 
to establish boundary conditions 
4  Input data 
Appendix C  Verification of topographic 
effects on thermal and stress initial and 
boundary conditions 
AC2: 
Data are 
sufficient for 
Appendix W  Thermal and mechanical 
boundary conditions verification 
3 Data on geology based on 
appropriate techniques 
4  Input 
6.1  Rock mass characteristics of the 
model 
justification 
repository 
6.3.1, 6.4.2 , 7.3, 7.4, 7.5, 7.6  Methods 
for incorporation of geology into 
degradation models 
6.5  Uncertainties and limitations 
Appendix E  Rock properties 
Appendix O  Lithophysal characterization 
4 Engineered barrier mechanical 6.3.1, 6.4.2  Rockfall parameters for feed 
failure models appropriate to drip shield stability modeling 
1 Models use parameter values, 
ranges, bounding assumptions that 
are technically defensible 
4  Input 
6.1  Describes variability of fractures and 
lithophysae upon which models are based 
6.2  Thermal analysis and range of 
thermal properties on temperature 
prediction 
AC3: 
Data 
uncertainty is 
characterized 
and 
propagated 
through the 
model 
abstraction 
6.3 and 6.2  Provide implementation of 
geologic variability into models via 
stochastic representation of fractures and 
bounding ranges for lithophysal rock 
properties 
Appendix E  Rock properties  Ranges of 
rock properties used in analyses 
2 Process models represent and do 
not underestimate mechanically 
disruptive events 
6.2  Thermal modeling  Determines 
thermal stress for range of thermal 
properties 
6.3, 6.4  Provides rockfall and drift 
degradation for seismic events derived from 
conservative PSHAc process; time-
dependent drift degradation based on 
bounding of static fatigue behavior of 
welded tuff 
3 Uncertainty is adequately 
represented via sensitivity analyses 
or conservative limits 
6.3, 6.4  Rockfall in nonlithophysal units 
represented conducting many analyses of 
stochastically defined fracture conditions, 
rockfall in lithophysal units determined from 
bounding ranges of rock properties 
6.5  Uncertainties and limitations 
Appendix E  Development of rock 
properties ranges 
4 Use of expert elicitation 6.3, 6.4  Ground motion inputs based on 
expert elicitation via PSHAc process 
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Drift Degradation Analysis 
Table 8-1. Mapping of Yucca Mountain Review Plan Acceptance Criteria and Drift Degradation 
Analysis (Continued) 
Acceptance 
Criteria Subcriteria Paraphrase of Subcriteria Sections Where Addressed 
1 Alternative modeling approaches 
considered as well as uncertainties 
and limitations 
6.3  Alternative, conservative approach to 
defining fracture bridges used for rockfall in 
nonlithophysal 
6.4  Alternative numerical and analytical 
approaches used for estimation of drip 
shield static loading 
6.5  Uncertainties and limitations 
AC4: 
7.7.5  Alternative modeling approach 
(DRKBA) considered for rockfall in 
nonlithophysal units 
Model 
uncertainty is 
characterized 
and 
propagated 
through the 
model 
abstraction 
2 Conceptual model is consistent 
with available site characterization 
data including lab experiments and 
field measurements 
1.1  Background describes 
interrelationships between data, model 
development and validation 
6.1  Fracture and lithophysae field 
mapping consistent with model 
6.3, 7.7, Appendix E  Nonlithophysal 
model development based on field geologic 
mapping 
6.4, 7.3, 7.4, 7.5, 7.6, Appendix E, 
Appendix O  Lithophysal model is 
consistent with field mapping, laboratory 
data and field observations 
6.5  Uncertainties and limitations 
3 Alternative models used to assess 
uncertainties and limitations 
6.4  Alternative approaches for rock 
loading to drip shield in lithophysal rock 
6.5  Uncertainties and limitations 
7.7.5  DRKBA model used as alternative 
for rockfall in nonlithophysal rock 
1 Models used in TSPA are 
consistent with abstractions in 
current model 
1.1 Background  Describes approach to 
providing information to TSPA 
6.3.1.2  Rockfall in nonlithophysal units 
feed to SCAa 
6.4.2 - Rockfall in lithophysal units and 
quasi-static drip shield loads  Feed to 
SCAa 
AC5: 6.4.2.2.4  Drift profile change to DSAb 
Model 
abstraction 
7.2  Level of importance to TSPA for 
model validation 
output is 
supported by 
objective 
comparison 
8  Conclusions 
2 Outputs of mechanical disruption of 
engineered barrier abstractions 
reasonably produce bound of 
process model abstractions 
6.3.1.2  Rockfall in nonlithophysal units 
feed to SCAa 
6.4.2  Rockfall in lithophysal units and 
quasi-static drip shield loads  Feed to 
SCAa 
6.4.2.2.4  Drift profile change to DSAb 
7.2  Level of importance to TSPA for 
model validation 
8  Conclusions 
ANL-EBS-MD-000027 REV 03 8-7 September 2004 

Drift Degradation Analysis 
Table 8-1. Mapping of Yucca Mountain Review Plan Acceptance Criteria and Drift Degradation 
Analysis (Continued) 
Acceptance 
Criteria Subcriteria Paraphrase of Subcriteria Sections Where Addressed 
3 Well-documented, accepted 
procedures are provided to support 
TSPA abstractions 
6.2, 6.3 and 6.4  Use of industry standard 
acquired software in modeling analyses 
7  Validation of models includes 
documentation as per validation 
procedures, including outside expert 
technical review 
9.2  Describes codes, standards and 
AC5: 
procedures followed in development of this 
report 
Model 
abstraction 
output is 
supported by 
objective 
comparison 
4 Sensitivity analyses are used to 
support the TSPA abstraction that 
covers ranges of data obtained 
from field and laboratory 
measurements 
1.1  Background describes 
interrelationships between data, model 
development and validation 
6.1  Fracture and lithophysae field 
mapping consistent with model 
6.3, 7.7, Appendix E  Nonlithophysal 
model development based on field geologic 
mapping 
6.4, 7.3, 7.4, 7.5, 7.6, Appendix E, 
Appendix O  Lithophysal model is 
consistent with field mapping, laboratory 
data and field observations 
6.5  Uncertainties and limitations 
a 
b 
SCA = Seismic Consequence Abstraction 
DSA = Drift Seepage Abstraction 
PSHA = Probabilistic Seismic Hazard Assessment 
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Drift Degradation Analysis 
9. INPUTS AND REFERENCES 
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Senseny, P.E. and Pucik, T.A. 1999. Development and Validation of Computer 168479 
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John Wiley & Sons. TIC: 253795. 
Shanley, R.J. and Mahtab, M.A. [1974]. A Computer Program for Clustering Data 169199 
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Earthquakes. Engineering Geology, 30, (3/4), 263-276. Amsterdam, [The 
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Singleton, B. 1995. Data Report Package, Supporting Information. Memorandum 107044 
from B. Singleton (U.S. Bureau of Reclamation) to C. Miller-Corbett (U.S.Geological 
Survey), July 20, 1995, with attachments. ACC: MOL.19960731.0235. 
SNL (Sandia National Laboratories) 1996. Mechanical Properties of Fractures in 165408 
Specimens from Drillhole USW SD-9. Albuquerque, New Mexico: Sandia National 
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SNL (Sandia National Laboratories) 1996. Mechanical Properties of Fractures in 165410 
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Stevens, P.R. 1977. A Review of the Effects of Earthquakes on Underground Mines. 154501 
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Analytical and a Numerical Approach to Probabilistic Keyblock Analysis. Rock 
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Probabilistic Method of Key Block Analysis. Rock Mechanics as a Multidisciplinary 
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ANL-EBS-MD-000027 REV 03 9-14 September 2004 

Drift Degradation Analysis 
USGS (U.S. Geological Survey) 1996. Geotechnical Report for Station 4+00 to 8+00, 169024 
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USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169030 
Ratings, Main Drift of the Exploratory Studies Facility (ESF), Station 30+00 to 35+00. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970106.0347. 
USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169031 
Ratings, Main Drift of the Exploratory Studies Facility (ESF), Station 35+00 to 40+00. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970106.0348. 
USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169032 
Ratings, Main Drift of the Exploratory Studies Facility (ESF), Station 40+00 to 45+00. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970106.0392. 
USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169033 
Ratings, Main Drift of the Exploratory Studies Facility (ESF), Station 45+00 to 50+00. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970106.0393. 
USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169034 
Ratings, Main Drift of the Exploratory Studies Facility (ESF), Station 50+00 to 55+00. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970106.0422. 
USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169035 
Ratings, Main Drift of the Exploratory Studies Facility (ESF), Station 55+00 to 60+00. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970804.0153. 
USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169029 
Ratings, North Ramp and Main Drift of the Exploratory Studies Facility (ESF), Station 
26+00 to 30+00. Denver, Colorado: U.S. Geological Survey. 
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USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169026 
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18+00. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970618.0552. 
USGS 1996. Supplemental and Supporting Information for Rock Mass Quality 169027 
Ratings, North Ramp of the Exploratory Studies Facility (ESF), Station 18+00 to 
26+00. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970106.0276. 
ANL-EBS-MD-000027 REV 03 9-15 September 2004 

Drift Degradation Analysis 
USGS 1997. Supplemental and Supporting Information for Rock Mass Quality 169040 
Ratings, Alcove #5, Cross Drift & Heated Drift of the Exploratory Studies Facility 
(ESF). Denver, Colorado: U.S. Geological Survey. ACC: MOL.19980203.0461. 
USGS 1997. Supplemental and Supporting Information for Rock Mass Quality 169036 
Ratings, South Ramp of the Exploratory Studies Facility (ESF), Station 60+00 to 
65+00. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970804.0164 
USGS 1997. Supplemental and Supporting Information for Rock Mass Quality 169037 
Ratings, South Ramp of the Exploratory Studies Facility (ESF), Station 65+00 to 
70+00. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19980216.0348. 
USGS 1997. Supplemental and Supporting Information for Rock Mass Quality 169038 
Ratings, South Ramp of the Exploratory Studies Facility (ESF), Station 70+00 to 
75+00. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19980216.0359. 
USGS 1997. Supplemental and Supporting Information for Rock Mass Quality 169039 
Ratings, South Ramp of the Exploratory Studies Facility (ESF), Station 75+00 to 
78+77. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19980216.0299. 
USGS 1999. Supplemental and Supporting Information for Rock Mass Quality 169018 
Ratings, ECRB Cross Block Drift, Station 00+00 to 10+00. Denver, Colorado: 
U.S. Geological Survey. ACC: MOL.20000209.0203. 
USGS 1999. Supplemental and Supporting Information for Rock Mass Quality 169019 
Ratings, ECRB Cross Block Drift, Station 10+00 to 15+00. Denver, Colorado: 
U.S. Geological Survey. ACC: MOL.20000209.0212. 
USGS 1999. Supplemental and Supporting Information for Rock Mass Quality 169020 
Ratings, ECRB Cross Block Drift, Station 15+00 to 20+00. Denver, Colorado: 
U.S. Geological Survey. ACC: MOL.20000209.0221. 
USGS 1999. Supplemental and Supporting Information for Rock Mass Quality 169021 
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Wang, J-M. 1985. The Distribution of Earthquake Damage to Underground Facilities 151821 
During the 1976 Tang-Shan Earthquake. Earthquake Spectra, 1, (4), 741-757. 
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Warburton, P.M. 1981. Vector Stability Analysis of an Arbitrary Polyhedral Rock 150093 
Block with Any Number of Free Faces. International Journal of Rock Mechanics and 
Mining Science & Geomechanics Abstracts, 18, (5), 415-427. New York, New York: 
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ANL-EBS-MD-000027 REV 03 9-16 September 2004 

Drift Degradation Analysis 
Wiederhorn, S.M. 1968. Moisture Assisted Crack Growth in Ceramics. 170309 
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White Paper: Scaling Along the Roof of the Heated Drift. Letter from N.H. Williams 
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enclosure. ACC: MOL.20010622.0252. 
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Interoffice memorandum from N.H. Williams (BSC) to Distribution, 
September 16, 2002, 0911024159, with enclosures. ACC: MOL.20021008.0141. 
9.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 156605 
Repository at Yucca Mountain, Nevada. Readily available. 
AP-2.22Q, Rev. 1, ICN 1. Classification Analyses and Maintenance of the Q-List. Washington, 
D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040714.0002. 
AP-3.15Q, Rev. 4, ICN 5. Managing Technical Product Inputs. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040812.0004. 
AP-SIII.9Q, Rev. 1, ICN 6. Scientific Analyses. Washington, D.C.: U.S. Department of Energy, 
Office of Civilian Radioactive Waste Management. ACC: DOC.20040805.0003. 
AP-SIII.10Q, Rev. 2, ICN 6. Models. Washington, D.C.: U.S. Department of Energy, Office of 
Civilian Radioactive Waste Management. ACC: DOC.20040805.0005. 
AP-SIII.2Q, Rev. 1, ICN 2. Qualification of Unqualified Data. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040127.0008. 
AP-SIII.3Q, Rev. 2, ICN 1. Submittal and Incorporation of Data to the Technical Data 
Management System. Washington, D.C.: U.S. Department of Energy, Office of Civilian 
Radioactive Waste Management. ACC: DOC.20040226.0001. 
LP-SI.11Q-BSC, Rev. 0. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20040225.0007. 
YMP-USGS-GP-20, Rev. 1. Estimating Abundance of Fractures in Core and in Outcrops, 
Including Lithophysae, Spots, Clasts, and Fractures. Denver, Colorado: U.S. Geological Survey. 
ACC: MOL.19960129.0372. 
ANL-EBS-MD-000027 REV 03 9-17 September 2004 

Drift Degradation Analysis 
9.3 SOFTWARE 
BSC 2002. Software Code: 3DEC. V2.01. PC WINDOWS 2000/NT 4.0. 161930 
10025-2.01-00. 
BSC 2002. Software Code: DRKBA. V3.31. PC WINDOWS 2000/NT 4.0. 161946 
10071-3.31-00. 
BSC 2002. Software Code: F LAC. V4.0. PC WINDOWS 2000/NT 4.0 161953 
10167-4.0-00. 
BSC 2002. Software Code: FLAC3D. V2.1. PC WINDOWS 2000/NT 4.0. 161947 
10502-2.1-00. 
BSC 2002. Software Code: PFC2D. V2.0. PC WINDOWS 2000/NT 4.0. 161950 
10828-2.0-00. 
BSC 2002. Software Code: PFC3D. V.2.0. PC. 10830-2.0-00. 160612 
BSC 2002. Software Code: UDEC. V3.1. PC WINDOWS 2000/NT 4.0. 10173-3.1-00. 161949 
BSC 2004. Software Code: Clustran. V. 1.1. PC, Windows 2000. 11162-1.1-00. 169203 
BSC 2004. Software Code: PFC2D. V 2.0. PC, Windows 2000. 10828-2.0-01. 169930 
BSC 2004. Software Code: PFC3D. V 2.0. PC, Windows 2000. 10830-2.0-01. 169931 
BSC 2004. Software Code: Read DXF. V. 1.0. PC, Windows 2000. 11159-1.0-00. 169204 
CRWMS M&O 1997. Software Code: DIPS. V4.03. 30017 V4.03. 149839 
CRWMS M&O 1998. Software Code: UNWEDGE V2.3. V2.3. 30053 V2.3. 145366 
Dynamic Graphics 2000. Software Code: EARTHVISION. 5.1. SGI/IRIX 6.5. 167994 
10174-5.1-00. 
LLNL (Lawrence Livermore National Laboratory) 2002. Software Code: NUFT. 157280 
V3.0s. Sun, SunO.S. 5.6 & 5.7. 10088-3.0s-01. 
USGS 1999. Software Code: FracMAN. V.2.512. PC, Windows NT. 10114-2.511-00. 160577 
9.4 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
GS000608314224.004. Provisional Results: Geotechnical Data for Station 35+00 to 152573 
Station 40+00, Main Drift of the ESF. Submittal date: 06/20/2000. 
ANL-EBS-MD-000027 REV 03 9-18 September 2004 

Drift Degradation Analysis 
GS000608314224.005. Provisional Results: Geotechnical Data - Full Periphery Maps 166002
for the North Ramp of the Exploratory Studies Facility, Stations 4+00 to 8+00. 
Submittal date: 06/28/2000. 
GS000608314224.006. Provisional Results: Geotechnical Data for Station 26+00 to 152572
30+00, North Ramp and Main Drift of the ESF, Full-Periphery Geotechnical Maps 
(Drawings OA-46-222 through OA-46-226) and Rock Mass Quality Ratings Report. 
Submittal date: 06/28/2000. 
GS020908314224.001. Supplemental Fracture Study Traverses 1 through 16 at WT-11 171038
Wash and Solitario Canyon Starting in WT-11 Wash along Iron Ridge. Submittal date: 
10/23/2002. 
GS021008314224.002. Lithophysal Data Study from the Tptpll in the ECRB from 161910
Stations 14+44 to 23+26. Submittal date: 01/28/2003. 
GS030283114222.001. Direct Shear Data from Selected Samples of the Topopah 161913
Spring Tuff. Submittal date: 02/20/2003. 
GS030483351030.001. Bulk Density, Rock-Particle Density, Porosity Properties of 163440
Core Samples of Spot, Rim & Matrix-Groundmass from 17 Boreholes in the Upper & 
Lower Lithophysal Zones of the Topopah Spring Tuff from the ESF & ECRB Cross 
Drift. Submittal date: 04/24/2003. 
GS040108314224.001. Detailed Line Survey Data for Horizontal and Vertical 169591
Traverses, ECRB. Submittal date: 02/27/2004. 
GS040308314224.002. Supplemental Fracture Study Traverses 17 through 23 at Prow 171039
Pass in the Yucca and Windy Washes. Submittal date: 05/05/2004. 
GS040608314224.001. Large-Lithophysal Inventory Data from the Tptpll and Tptpln 171367
in the ECRB from Stations 14+44 to 25+35. Submittal date: 08/19/2004.
GS950508314224.003. Provisional Results: Geotechnical Data - Full Periphery Map 107488
Data from North Ramp of the Exploratory Studies Facility, Stations 0+60 to 4+00. 
Submittal date: 05/24/1995. 
GS960408314224.001. Provisional Results: Geotechnical Data  Full Periphery 168135
Geotechnical Maps of the North Ramp, Exploratory Studies Facility, Station 8+00 to 
10+00, Plots OA-46-201, -202, -203; Geotechnical Report  Rock Mass Quality 
Ratings. Submittal date: 06/24/1996. 
GS960408314224.003. Provisional Results: Geotechnical Data  Full-Periphery 168136
Geotechnical Maps (Drawing OA-46-204 through -212) and Rock Mass Quality 
Ratings from North Ramp of the Exploratory Studies Facility, Stations 10+00 to 
18+00. Submittal date: 08/29/1996.
ANL-EBS-MD-000027 REV 03 9-19 September 2004 

Drift Degradation Analysis 
GS960708314224.008. Provisional Results: Geotechnical Data for Station 30 + 00 to 105617 
Station 35 + 00, Main Drift of the ESF. Submittal date: 08/05/1996. 
GS960708314224.009. Provisional Results: Geotechnical Data for Station 18+00 to 168137 
26+00, North Ramp of the ESF, Full-Periphery Geotechnical Maps and Rock Mass 
Quality Ratings Report. Submittal date: 09/09/1996. 
GS960708314224.010. Provisional Results: Geotechnical Data for Station 40+00 to 106031 
Station 45+00, Main Drift of the ESF. Submittal date: 08/05/1996. 
GS960908314224.014. Provisional Results - ESF Main Drift, Station 50+00 to Station 106033 
55+00. Submittal date: 09/09/1996. 
GS960908314224.015. Provisional Results: Geotechnical Data for Stations 30+00 to 108372 
40+00, Main Drift of the ESF, Full-Periphery Geotechnical Maps and Rock Mass 
Quality Ratings Report. Submittal date: 09/09/1996. 
GS960908314224.016. Provisional Results: Geotechnical Data for Station 40+00 to 108373 
50+00, Main Drift of the ESF, Full-Periphery Geotechnical Maps and Rock Mass 
Quality Ratings Report. Submittal date: 09/09/1996. 
GS960908314224.017. Provisional Results: Geotechnical Data for Stations 50+00 to 108376 
55+00, Main Drift of the ESF, Full-Periphery Geotechnical Maps and Rock Mass 
Quality Ratings Report. Submittal date: 09/09/1996. 
GS960908314224.020. Analysis Report: Geology of the North Ramp - Stations 4+00 106059 
to 28+00 and Data: Detailed Line Survey and Full-Periphery Geotechnical Map - 
Alcoves 3 (UPCA) and 4 (LPCA), and Comparative Geologic Cross Section - Stations 
0+60 to 28+00. Submittal date: 09/09/1996. 
GS970108314224.002. Geotechnical Data for Station 55+00 to Station 60+00, Main 107490 
Drift of the ESF, Full Periphery Geotechnical Maps. Submittal date: 01/31/1997. 
GS970208314224.003. Geotechnical Data for Station 60+00 to Station 65+00, South 106048 
Ramp of the ESF. Submittal date: 02/12/1997. 
GS970208314224.004. Geotechnical Data for Station 60+00 to Station 65+00, South 107492 
Ramp of the ESF. Submittal date: 02/12/1997. 
GS970608314224.007. Provisional Results: Geotechnical Data for the Exploratory 158430 
Studies Facility, Main Drift, Alcove 5 (DWFA): Heated Drift and Cross Drift Full 
Periphery Geotechnical Map (Drawing OA-46-300) and Rock Mass Quality Ratings 
Report. Submittal date: 06/24/1997. 
ANL-EBS-MD-000027 REV 03 9-20 September 2004 

Drift Degradation Analysis 
GS970808314224.009. Provisional Results: Geotechnical Data for Station 65+00 to 107494 
Station 70+00, South Ramp of the ESF; Full-Periphery Geotechnical Maps (Drawings 
0A-46-269 through 0A-46-274) and Rock Mass Quality Ratings Report. Submittal 
date: 08/18/1997. 
GS970808314224.010. Provisional Results: Geotechnical Data for Station 70+00 to 106050 
Station 75+00, South Ramp of the ESF. Submittal date: 08/25/1997. 
GS970808314224.011. Provisional Results: Geotechnical Data for Station 70+00 to 107495 
Station 75+00, South Ramp of the ESF. Submittal date: 08/25/1997. 
GS970808314224.013. Provisional Results: Geotechnical Data for Station 75+00 to 107497 
Station 78+77, South Ramp of the ESF. Submittal date: 08/25/1997. 
GS971108314224.025. Revision 1 of Detailed Line Survey Data, Station 26+00 to 106025 
Station 30+00, North Ramp and Main Drift, Exploratory Studies Facility. Submittal 
date: 12/03/1997. 
GS971108314224.028. Revision 1 of Detailed Line Survey Data, Station 55+00 to 106047 
Station 60+00, Main Drift and South Ramp, Exploratory Studies Facility. Submittal 
date: 12/03/1997. 
GS990408314224.001. Detailed Line Survey Data for Stations 00+00.89 to 14+95.18, 108396 
ECRB Cross Drift. Submittal date: 09/09/1999. 
GS990408314224.002. Detailed Line Survey Data for Stations 15+00.85 to 26+63.85, 105625 
ECRB Cross Drift. Submittal date: 09/09/1999. 
GS990408314224.003. Full-Periphery Geologic Maps for Station -0+10 to 10+00, 108404 
ECRB Cross Drift. Submittal date: 09/09/1999. 
GS990408314224.004. Full-Periphery Geologic Maps for Station 10+00 to 15+00, 108405 
ECRB Cross Drift. Submittal date: 09/09/1999. 
GS990408314224.005. Full-Periphery Geologic Maps for Station 15+00 to 20+00, 108408 
ECRB Cross Drift. Submittal date: 09/09/1999. 
GS990408314224.006. Full-Periphery Geologic Maps for Station 20+00 to 26+81, 108409 
ECRB Cross Drift. Submittal date: 09/09/1999. 
LA000000000086.002. Mineralogic Variation in Drill Core UE-25 UZ#16 Yucca 107144 
Mountain, Nevada. Submittal date: 03/28/1995. 
LA9912SL831151.001. Fracture Mineralogy of Drill Core ESF-HD-TEMP-2. 146447 
Submittal date: 01/05/2000. 
ANL-EBS-MD-000027 REV 03 9-21 September 2004 

Drift Degradation Analysis 
LADB831321AN98.002. Revised Mineralogic Summary of Yucca Mountain, Nevada. 109003
Submittal date: 05/26/1998. 
LADV831321AQ97.001. Mineralogic Variation in Drill Holes. Submittal date: 107142
05/28/1997. 
LADV831321AQ99.001. Quantitative XRD Results for the USW SD-6 and USW 109044
WT-24 Drill Core Samples. Submittal date: 04/16/1999. 
LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed from 159525
Field Data. Submittal date: 05/14/2002. 
LB0208UZDSCPMI.002. Drift-Scale Calibrated Property Sets: Mean Infiltration Data 161243
Summary. Submittal date: 08/26/2002. 
LL030808623122.036. Input and Output Files for NUFT MSTHM Sub-Models 165790
Supporting LA Multi-Scale Analyses. Submittal date: 09/11/2003. 
MO0001SEPDSTPC.000. Drift Scale Test (DST) Temperature, Power, Current, and 153836
Voltage Data for June 1, 1999 through October 31, 1999. Submittal date: 01/12/2000. 
MO0002ABBLSLDS.000. As-Built Borehole Locations and Sensor Locations for the 147304
Drift Scale Test Given in Local (DST) Coordinates. Submittal date: 02/01/2000. 
MO0004QGFMPICK.000. Lithostratigraphic Contacts from 152554
MO9811MWDGFM03.000 to be Qualified Under the Data Qualification Plan, 
TDP-NBS-GS-000001. Submittal date: 04/04/2000. 
MO0007SEPDSTPC.001. Drift Scale Test (DST) Temperature, Power, Current, and 153707
Voltage Data for November 1, 1999 through May 31, 2000. Submittal date: 
07/13/2000. 
MO0012MWDGFM02.002. Geologic Framework Model (GFM2000). Submittal 153777
date: 12/18/2000. 
MO0107SEPDSTPC.003. Drift Scale Test (DST) Temperature, Power, Current, and 158321
Voltage Data for December 1, 2000 through May 31, 2001. Submittal date: 
07/06/2001. 
MO0202SEPDSTTV.001. Drift Scale Test (DST) Temperature, Power, Current, and 158320
Voltage Data for June 1, 2001 through January 14, 2002. Submittal date: 02/28/2002.
MO0301SPASIP27.004. Sampling of Stochastic Input Parameters for Rockfall 161869
Calculations and for Structural Response Calculations Under Vibratory Ground 
Motions. Submittal date: 01/15/2003. 
ANL-EBS-MD-000027 REV 03 9-22 September 2004 

Drift Degradation Analysis 
MO0301TMHIS106.001. Acceleration, Velocity, and Displacement Time Histories 161868
for the Repository Level at 10-6 Annual Exceedance Frequency. 
Submittal date: 01/28/2003. 
MO0306MWDALAFV.000. ANSYS-La-Fine Ventilation. Submittal date: 163961
06/23/2003. 
MO0306MWDASLCV.001. ANSYS-LA-Coarse Ventilation. 
165695 
Submittal date: 07/01/2003. 
MO0306SDSAVDTH.000. Seismic Design Spectra and Acceleration, Velocity, and 164033
Displacement Time Histories for the Emplacement Level at 10-4 Annual Exceedance 
Frequency. Submittal date: 06/26/2003. 
MO0311RCKPRPCS.003. Intact Rock Properties Data on Uniaxial and Triaxial 166073
Compressive Strength. Submittal date: 11/04/2003. 
MO0401DQRIRPTS.003. Data Summary for Intact Rock Properties Data on Tensile 168905
Strength. Submittal date: 01/07/2004. 
MO0402AVDTM105.001. Acceleration, Velocity, and Displacement Time Histories 168890
for the Repository Level at 10-5 Annual Exceedance Frequency. 
Submittal date: 02/09/2004. 
MO0402DQRIRPPR.003. Intact Rock Properties Data on Poisson's Ratio and Young's 168901
Modulus. Submittal date: 02/19/2004. 
MO0403AVDSC106.001. Acceleration, Velocity, and Displacement Time Histories 168891
for the Repository Level at 10-6 Annual Exceedance Frequency. Submittal date: 
03/09/2004. 
MO0403AVTMH107.003. Acceleration, Velocity, and Displacement Time Histories 168892
for the Repository Level at 10-7 Annual Exceedance Frequency. Submittal date: 
03/22/2004. 
MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 170760
MO0407TMHIS104.003. Acceleration, Velocity and Displacement Time Histories for 170599
the Emplacement Level (Point B) at 5X10-4 Annual Exceedance Frequency. Submittal 
date: 07/15/2004. 
MO9807DSTSET01.000. Drift Scale Test (DST) Temperature, Power, Current, 113644
Voltage Data for November 7, 1997 through May 31, 1998. Submittal date: 
07/09/1998. 
ANL-EBS-MD-000027 REV 03 9-23 September 2004 

Drift Degradation Analysis 
MO9906DSTSET03.000. Drift Scale Test (DST) Temperature, Power, Current, 113673
Voltage Data for September 1, 1998 through May 31, 1999. 
Submittal date: 06/08/1999. 
SN0108SD821723.001. Uniaxial and Triaxial Compression Test Data on Samples 159959
from USW G-1 (VA Supporting Data). Submittal date: 08/09/2001. 
SN0208F4102102.002. Rock Mass Mechanical Properties, Slot Test #1, Location 161874
57+77 in the ESF. Submittal date: 08/27/2002. 
SN0208L0207502.001. Mechanical Properties of Lithophysal Tuff, Batch #1 (Test 161871
Dates: July 31, 2002 through August 16, 2002). Submittal date: 08/20/2002. 
SN0211L0207502.002. Mechanical Properties of Lithophysal Tuff, Batch #2 (Test 161872
Dates: October 22, 2002 through October 25, 2002). Submittal date: 11/13/2002. 
SN0212F4102102.004. Rock Mass Mechanical Properties, Slot Test #2, Location 161875
63+83 in the ESF. Submittal date: 12/17/2002. 
SN0301F4102102.006. Rock Mass Mechanical Properties, Slot Test #3, Location 161876
21+25 in the ECRB. Submittal date: 01/14/2003. 
SN0302L0207502.003. Mechanical Properties of Lithophysal Tuff, Room 165014
Temperature Batch #4, Set 1 (Test Dates: 01/21/03 through 01/23/03). 
Submittal date: 02/25/2003. 
SN0303T0503102.008. Revised Thermal Conductivity of the Non-Repository Layers 162401
of Yucca Mountain. Submittal date: 03/19/2003. 
SN0305L0207502.004. Mechanical Properties of Lithophysal Tuff, Batch #4, Set 2 165013
(Test Dates: March 5, 2003 through March 13, 2003). Submittal date: 05/01/2003. 
SN0305L0207502.005. Material Abundances from Point Counts on Laboratory 163373
Mechanical Property Specimens for Batch #1 and Batch #2. 
Submittal date: 05/20/2003. 
SN0306L0207502.008. Revised Mechanical Properties of Welded Tuff from the 165015
Lower Lithophysal Zone of the Topopah Spring Tuff, Batch #3 (Test Dates: March 6, 
2003 through April 18, 2003). Submittal date: 06/20/2003. 
SN0307T0510902.003. Updated Heat Capacity of Yucca Mountain Stratigraphic 164196
Units. Submittal date: 07/15/2003.
SN0404T0503102.011. Thermal Conductivity of the Potential Repository Horizon 169129
Rev 3. Submittal date: 04/27/2004.
ANL-EBS-MD-000027 REV 03 9-24 September 2004 

Drift Degradation Analysis 
SN0406L0212303.002. Static Fatigue Data from New England Research (NER) 170289 
(Test Dates: 1/2/2004 through 2/25/2004. Submittal date: 06/08/2004. 
SNF37100195002.001. Hydraulic Fracturing Stress Measurements in Test 
131356 
Hole: ESF-AOD-HDFR1, Thermal Test Facility, Exploratory Studies Facility at 
Yucca Mountain. Submittal date: 12/18/1996. 
SNL01B05059301.006. Laboratory Thermal Expansion Data for Boreholes UE25 129168 
NRG-4, NRG-5; USW NRG-6 and NRG-7/7A. Submittal date: 02/07/1996. 
SNL02030193001.001. Mechanical Properties Data for Drillhole USW NRG-6 120572 
Samples from Depth 22.2 ft. to 328.7 ft. Submittal date: 05/17/1993. 
SNL02030193001.002. Mechanical Properties Data for Drillhole USW NRG-6 120575 
Samples from Depth 22.2 ft. to 427.0 ft. Submittal date: 06/25/1993. 
SNL02030193001.003. Mechanical Properties Data for Drillhole UE-25 NRG-2 120578 
Samples from Depth 150.5 ft. to 200.0 ft. Submittal date: 07/07/1993. 
SNL02030193001.004. Mechanical Properties Data for Drillhole USW NRG-6 108415 
Samples from Depth 462.3 ft. to 1085.0 ft. Submittal date: 08/05/1993 
SNL02030193001.005. Mechanical Properties Data for Drillhole UE-25 NRG#3 122545 
Samples from Depth 15.4 ft. to 297.1 ft. Submittal date: 09/23/1993. 
SNL02030193001.006. Mechanical Properties Data for Drill Hole UE-25 NRG#2A 120579 
Samples from Depth 90.0 ft. to 254.5 ft. Submittal date: 10/13/1993. 
SNL02030193001.007. Mechanical Properties Data for Drill Hole UE-25 NRG#3 120582 
Samples from Depth 263.3 ft. to 265.7 ft. Submittal date: 10/20/1993. 
SNL02030193001.008. Mechanical Properties Data for Drill Hole USW NRG-6 120597 
Sample 416.0 ft. Submittal date: 10/20/1993. 
SNL02030193001.009. Mechanical Properties Data for Drillhole UE25 NRG-5 109614 
Samples from Depth 781.0 ft. to 991.9 ft. Submittal date: 11/18/1993. 
SNL02030193001.012. Mechanical Properties Data for Drillhole UE25 NRG-5 108416 
Samples from Depth 847.2 ft. to 896.5 ft. Submittal date: 12/02/1993. 
SNL02030193001.013. Mechanical Properties Data for Drillhole UE25 NRG-2B 120614 
Samples from Depth 2.7 ft. to 87.6 ft. Submittal date: 12/02/1993. 
SNL02030193001.014. Mechanical Properties Data for Drillhole UE25 NRG-4 109609 
Samples from Depth 378.1 ft. to 695.8 ft. Submittal date: 01/31/1994. 
SNL02030193001.015. Mechanical Properties Data for Drillhole UE25 NRG-4 120617 
Samples from Depth 527.0 ft. Submittal date: 02/16/1994. 
ANL-EBS-MD-000027 REV 03 9-25 September 2004 

Drift Degradation Analysis 
SNL02030193001.016. Mechanical Properties Data for Drillhole USW NRG-7/7A 120619
Samples from Depth 18.0 ft. to 472.9 ft. Submittal date: 03/16/1994. 
SNL02030193001.018. Mechanical Properties Data for Drillhole USW NRG-7/7A 109611
Samples from Depth 344.4 ft. Submittal date: 04/11/1994.
SNL02030193001.019. Mechanical Properties Data for Drillhole USW NRG-7/7A 108431
Samples from Depth 507.4 ft. to 881.0 ft. Submittal date: 06/29/1994.
SNL02030193001.020. Mechanical Properties Data for Drillhole USW NRG-7/7A 108432
Samples from Depth 554.7 ft. to 1450.1 ft. Submittal date: 07/25/1994.
SNL02030193001.021. Mechanical Properties Data (Ultrasonic Velocities, Static 108433
Elastic Properties, Triaxial Strength, Dry Bulk Density & Porosity) for Drillhole USW
NRG-7/7A Samples from Depth 345.0 ft. to 1408.6 ft. Submittal date: 02/16/1995.
SNL02030193001.022. Mechanical Properties Data for Drill Hole USW NRG-6 109613
Samples from Depth 5.7 ft. to 1092.3 ft. Submittal date: 02/27/1995. 
SNL02030193001.023. Mechanical Properties Data (Ultrasonic Velocities, Static 108435
Elastic Properties, Unconfined Strength, Triaxial Strength, Dry Bulk Density & 
Porosity) for Drillhole USW SD-12 Samples from Depth 16.1 ft. to 1300.3 ft. 
Submittal date: 08/02/1995. 
SNL02030193001.026. Mechanical Properties Data (Ultrasonic Velocities, Elastic 108436
Moduli and Fracture Strength) for Borehole USW SD-9. Submittal date: 02/22/1996. 
SNL02030193001.027. Summary of Bulk Property Measurements Including Saturated 108410
Bulk Density for NRG-2, NRG-2A, NRG-2B, NRG-3, NRG-4, NRG-5, NRG-6, NRG-
7/7A, SD-9, and SD12. Submittal date: 08/14/1996. 
SNL02112293001.003. Results from Shear Stress Experiments on Natural Fractures 108412
from NRG-4 & NRG-6. Submittal date: 03/13/1995. 108413 
SNL02112293001.005. Mechanical Properties of Fractures in Specimens from 108413
Drillhole USW SD-9. Submittal date: 07/15/1996. 
SNL02112293001.007. Mechanical Properties of Fractures in Specimens from 108414
Drillholes USW NRG-7/7A and USW SD-12. Submittal date: 08/08/1996. 
SNSAND83164600.000. Experimental Data of Fully Saturated and Wet Samples; 160009
Static Mechanical Properties of GU-3 760.9 Samples; Ultrasonic Velocity Data; and 
Dynamic Elastic Model of GU-3 760.9 Samples Compression Test. Submittal date: 
04/24/1992. 
SNSAND84110100.000. Uniaxial and Triaxial Compression Test Series on Topopah 160016
Spring Tuff from USW G-4, Yucca Mountain, Nevada. Submittal date: 02/01/1986.
ANL-EBS-MD-000027 REV 03 9-26 September 2004 

Drift Degradation Analysis 
SNSAND85070300.000. Uniaxial and Triaxial Compression Test Series on the 160020 
Topopah Spring Member from USW G-2, Yucca Mountain, Nevada. Submittal date: 
09/24/1987. 
SNSAND85070900.000. Effects of Sample Size on the Mechanical Behavior of the 160022 
Topopah Spring Tuff. Submittal date: 12/16/1998. 
SNSAND85076200.000. Bulk, Thermal, and Mechanical Properties of the Topopah 160024 
Spring Member of the Paintbrush Tuff, Yucca Mountain, Nevada. Submittal date: 
10/17/1987. 
SNSAND86113100.000. Petrologic and Mechanical Properties of Outcrop Samples of 159594 
the Welded, Devitrified Topopah Spring Member of the Paintbrush Tuff. Submittal 
date: 06/11/1987. 
9.5 DEVELOPED DATA, LISTED BY DATA TRACKING NUMBER 
MO0306MWDDPPDR.000. Drift Profile Prediction and Degraded Rock Mass Characteristics in 
Lithophysal Units. Submittal date: 06/18/2003. 
MO0403MWDRPNLR.000. Rock Properties for Nonlithophysal Rock. 
Submittal date: 03/31/2004. 
MO0404MWD3DRFA.000. Input and Output file for 3DEC Rockfall Analyses with 1E-4 
Ground Motion. Submittal date: 04/08/2004. 
MO0407MWDDSLCR.000. Drip Shield Load in Collapsed Lithophysal Rock. 
Submittal date: 07/21/2004. 
MO0407SPAMTSHR.000. Modeled Thermal Stresses Within the Host Rock at Three 
Graduated Points in Time. Submittal date: 07/20/2004. 
MO0408MWDRNLRA.002. Results from Nonlithophysal Rockfall Analyses for Emplacement 
Drifts with 1E-4 Ground Motion. Submittal date: 08/19/2004. 
MO0408MWDDDMIO.002. Drift Degradation Model Inputs and Outputs. Submittal date: 
08/31/2004. 
ANL-EBS-MD-000027 REV 03 9-27 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 9-28 September 2004 

Drift Degradation Analysis 
APPENDIX A 
DRIFT DEGRADATION ANALYSIS COMPUTER FILES 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
DRIFT DEGRADATION ANALYSIS COMPUTER FILES 
The computer files developed for this model report can be accessed through the Technical Data 
Management System (TDMS) (DTN: MO0408MWDDDMIO.002), and include the inputs and 
outputs for the following computer rendered simulations: 
 3DEC Inputs & Outputs 
 DRKBA Inputs & Outputs 
 EarthVision Inputs & Outputs 
 FLAC 3D Inputs & Outputs 
 FLAC Inputs & Outputs 
 FracMan Inputs & Outputs 
 NUFT Inputs & Outputs 
 PFC Inputs & Outputs 
 UDEC Inputs & Outputs. 
Archive file descriptions are provided in DTN: MO0408MWDDDMIO.002 for each software 
item to explain the format of the input and output sub-directories within the DTN. 
Calculation files were developed in this model report to perform support calculation activities as 
described in Section 6.2, Section 6.3, Section 6.4, and associated appendices. These calculations 
use the standard functions of commercial off-the-shelf software, including both Microsoft Excel 
97 SR-2 and Mathcad 2001i Professional. Additionally, DIPS Version 4.03 (see Section 3.2) 
was used for graphical presentation of fracture data. Table A-1 provides a listing of the 
calculation files, including the location in this report where specific details of the calculation can 
be found. The calculation files listed in Table A-1 can be accessed through the TDMS 
(DTN: MO0408MWDDDMIO.002). 
Microsoft Excel 97 SR-2 and Mathcad 2001i Professional were used to perform support 
calculations to process the nonlithophysal rockfall output from 3DEC for preclosure ground 
motion (110-4 annual probability of exceedance). Excel was used to tabulate the rockfall 
results, including rock block velocity and impact location. Mathcad was used to calculate the 
impact bounding velocity for preclosure rockfall. The results from nonlithophysal rockfall 
analyses with 110-4 ground motion can be accessed through the TDMS 
(DTN: MO0408MWDRNLRA.002). Excel was also used to perform support calculations to 
process the nonlithophysal rockfall output from 3DEC for postclosure ground motions, including 
110-5, 110-6, and 110-7 annual probabilities of exceedance. Excel was used to tabulate the 
rockfall results, calculate the rockfall mass, velocity, impact angle, impact momentum, and 
impact energy associated with each rock block. These files can be accessed through the TDMS 
(DTN: MO0408MWDDDMIO.002). 
ANL-EBS-MD-000027 REV 03 A-1 September 2004 

Drift Degradation Analysis 
Output files for drift profile prediction and degraded rock mass characteristics in lithophysal 
units can be accessed through the TDMS (DTN: MO0306MWDDPPDR.000). Input and output 
files for 3DEC rockfall analyses using 110-4 ground motion are provided in 
DTN: MO0404MWD3DRFA.000. Drip shield load results are provided in 
DTN: MO0407MWDDSLCR.000. The profile of thermal stresses at different times after waste 
emplacement (extracted from FLAC 3D) is provided in DTN: MO0407SPAMTSHR.000. Intact 
rock properties used in parts of the drift degradation analyses are summarized in 
DTN: MO0403MWDRPNLR.000. 
ANL-EBS-MD-000027 REV 03 A-2 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files 
File Name File Type Brief Description References 
3DEC lith analysis 
results.xls 
Microsoft Excel 97 SR-2 Calculation file to tabulate the 
rockfall results for the 3DEC 
N/A 
lithophysal rockfall analysis 
(Section 6.4.3) 
impact velocity Mathcad 2001i Calculation file to determine the BSC 2004 [DIRS 168489], BSC 2004 [DIRS 169503], BSC 2004 
bounding cal for Professional bounding impact velocity for [DIRS 169472], Dowding 1979 [DIRS 101977] 
preclosure rockfall preclosure rockfall 
rev1.mcd (Section 6.3.1.2.6) 
nonlith 1e-4 motion Microsoft Excel 97 SR-2 Calculation file to determine the N/A 
sufficiency number of simulation sufficient for 
study.xls rockfall analyses (Appendix K) 
nonlith 1e-5 motion Microsoft Excel 97 SR-2 Calculation file to determine the N/A 
sufficiency number of simulation sufficient for 
study.xls rockfall analyses (Appendix K) 
nonlith 1e-6 motion Microsoft Excel 97 SR-2 Calculation file to determine the N/A 
sufficiency number of simulation sufficient for 
study.xls rockfall analyses (Appendix K) 
nonlith 1e-7 motion Microsoft Excel 97 SR-2 Calculation file to determine the N/A 
sufficiency number of simulation sufficient for 
study.xls rockfall analyses (Appendix K) 
nonlith rockfall 
characteristics in 
Microsoft Excel 97 SR-2 Calculation file to tabulate the 
rockfall results, calculate the 
N/A 
emplacement drifts 
with 1e-4 gm.xls 
rockfall mass, velocity, impact 
angle, impact momentum, and 
impact energy associated with 
each rock block. These data are 
for preclosure ground motion with 
an annual probability of 
exceedance of 1x 10-4 
(Section 6.3.1.2.6) 
ANL-EBS-MD-000027 REV 03 A-3 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
nonlith rockfall 
characteristics in 
Microsoft Excel 97 SR-2 Calculation file to tabulate the 
rockfall results, calculate the 
N/A 
emplacement drifts 
with 1e-5 gm.xls 
rockfall mass, velocity, impact 
angle, impact momentum, and 
impact energy associated with 
each rock block. These data are 
for preclosure ground motion with 
an annual probability of 
exceedance of 1x 10-5 
(Section 6.3.1.2.3) 
nonlith rockfall 
characteristics in 
Microsoft Excel 97 SR-2 Calculation file to tabulate the 
rockfall results, calculate the 
N/A 
emplacement drifts 
with 1e-6 gm.xls 
rockfall mass, velocity, impact 
angle, impact momentum, and 
impact energy associated with 
each rock block. These data are 
for preclosure ground motion with 
an annual probability of 
exceedance of 1x 10-6 
(Section 6.3.1.2.4) 
nonlith rockfall 
characteristics in 
Microsoft Excel 97 SR-2 Calculation file to tabulate the 
rockfall results, calculate the 
N/A 
emplacement drifts 
with 1e-7 gm.xls 
rockfall mass, velocity, impact 
angle, impact momentum, and 
impact energy associated with 
each rock block. These data are 
for preclosure ground motion with 
an annual probability of 
exceedance of 1x 10-7 
(Section 6.3.1.2.5) 
Cavingnew.mcd Mathcad 2001i 
Professional 
Calculation file for analytical 
solution for lithophysal rock mass 
degradation (Section 6.4.2.5). 
N/A 
drift degradation-
V1.xls 
Microsoft Excel 97 SR-2 Calculation file for summarizing 
drip shield pressure including both 
analytical and numerical solutions 
(Section 6.4.2). 
N/A 
ANL-EBS-MD-000027 REV 03 A-4 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
FLAC drip shield Microsoft Excel 97 SR-2 Summary drip shield pressures N/A 
pressures.xls calculated using FLAC 
(Section 6.4.2.5) 
UDEC drip shield Microsoft Excel 97 SR-2 Summary drip shield pressures N/A 
pressures.xls calculated using UDEC 
(Section 6.4.2.5) 
Cohesion 
Degradation V1.xls 
Microsoft Excel 97 SR-2 Calculation file for cohesion 
degradation due to time and 
thermal effects. Application: 
DRKBA analyses of 
nonlithophysal rock. Calculation 
details provided in Appendix D 
(Section D5). 
N/A 
exca vectors V2.xls Microsoft Excel 97 SR-2 Calculation file for plane equations 
to describe the 5.5-m-diameter 
N/A 
excavation opening. Application: 
DRKBA analyses of 
nonlithophysal rock. Calculation 
details provided in Appendix D 
(Section D10). 
mcs sensitivity 
study Tptpmn 
v1.xls 
Microsoft Excel 97 SR-2 Calculation file for rock blocks 
cumulative frequency of 
occurrence, Monte Carlo 
N/A 
simulations varied. Application: 
DRKBA analyses of 
nonlithophysal rock. Calculation 
details provided in Appendix D 
(Section D8). 
New_Beta_Tptpmn 
V1.xls 
Microsoft Excel 97 SR-2 Calculation file for beta distribution 
parameters (a, b, p, q) for joint 
spacing, trace length, and 
location. Application: DRKBA 
analyses of nonlithophysal rock. 
Calculation details provided in 
Appendix D (Section D7). 
Derman, et al. 1973 [DIRS 108444] 
ANL-EBS-MD-000027 REV 03 A-5 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
New-K-Tptpmn 
V2.mcd 
Mathcad 2001i 
Professional 
Calculation file for K factor of joint 
orientation. Application: DRKBA 
analyses of nonlithophysal rock. 
Calculation details provided in 
Appendix D (Section D7). 
N/A 
Orient-Tptpmn .xls Microsoft Excel 97 SR-2 Calculation file for components for 
the orientation matrix. 
N/A 
Application: DRKBA analyses of 
nonlithophysal rock. Calculation 
details provided in Appendix D 
(Section D7). 
Thermal curve 
V1.xls 
Microsoft Excel 97 SR-2 Calculation file for ratio of effective 
shear stress for thermal effect. 
N/A 
Application: DRKBA analyses of 
nonlithophysal rock. Calculation 
details provided in Appendix D 
(Section D5). 
Time thermal 
cohesion 
degradation 
V1.mcd 
Mathcad 2001i 
Professional 
Calculation file for cohesion 
degradation due to time and 
thermal effects. Application: 
DRKBA analyses of 
nonlithophysal rock. Calculation 
details provided in Appendix D 
(Section D5). 
N/A 
tpmn seismic 75 
res v2.xls 
Microsoft Excel 97 SR-2 Calculation file for rock blocks 
cumulative percentage of 
occurrence. Application: DRKBA 
analyses of nonlithophysal rock. 
Calculation details provided in 
Appendix D (Section D6). 
N/A 
Tptpll- FracMan 
Generated Fracture 
Data.xls 
Microsoft Excel 97 SR-2 Calculation file for converting 
FracMan fracture output to 3DEC 
input. Application: rockfall 
models. Calculation details 
N/A 
provided in Appendix L. 
ANL-EBS-MD-000027 REV 03 A-6 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
3DEC-
S1shtA_TPO.xls 
Microsoft Excel 97 SR-2 Calculation file for converting 
FracMan fracture output to 3DEC 
input. Application: rockfall 
models. Calculation details 
N/A 
provided in Appendix L. 
3DEC-
S1shtB_TPO.xls 
Microsoft Excel 97 SR-2 Calculation file for converting 
FracMan fracture output to 3DEC 
input. Application: rockfall 
models. Calculation details 
N/A 
provided in Appendix L. 
3DEC-
s2sht_TPO.xls 
Microsoft Excel 97 SR-2 Calculation file for converting 
FracMan fracture output to 3DEC 
input. Application: rockfall 
models. Calculation details 
N/A 
provided in Appendix L. 
3DEC-
s3_sht_TPO.xls 
Microsoft Excel 97 SR-2 Calculation file for converting 
FracMan fracture output to 3DEC 
input. Application: rockfall 
models. Calculation details 
N/A 
provided in Appendix L. 
3DEC-VPPLONG_ 
TPO.xls 
Microsoft Excel 97 SR-2 Calculation file for converting 
FracMan fracture output to 3DEC 
input. Application: rockfall 
models. Calculation details 
N/A 
provided in Appendix L. 
Drift Deg AMR AA 
PMap.xls 
Microsoft Excel 97 SR-2 Calculation file for descriptive 
statistics for lithophysal 
abundance and lithophysal 
characteristics in the ECRB 
N/A 
(Enhanced Characterization of the 
Repository Block) Cross-Drift. 
Application: lithophysal rockfall 
model. Calculation details 
provided in Appendix O 
(Section O6). 
ANL-EBS-MD-000027 REV 03 A-7 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
Drift Deg AMR AB 
A-Trav.xls 
Microsoft Excel 97 SR-2 Calculation file for descriptive 
statistics for lithophysal 
abundance and lithophysal 
characteristics in the ECRB 
GS021008314224.002 [DIRS 161910] 
Cross-Drift. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix O (Section O6). 
Drift Deg AMR AC 
T-Trav.xls 
Microsoft Excel 97 SR-2 Calculation file for descriptive 
statistics for lithophysal 
abundance and lithophysal 
characteristics in the ECRB 
GS021008314224.002 [DIRS 161910] 
Cross-Drift. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix O (Section O6). 
Drift Deg AMR AD 
L-Litho V1.xls 
Microsoft Excel 97 SR-2 Calculation file for descriptive 
statistics for lithophysal 
abundance and lithophysal 
characteristics in the ECRB 
GS021008314224.002 [DIRS 161910] 
Cross-Drift. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix O (Section O6). 
Drift Deg AMR AE 
Mongano.xls 
Microsoft Excel 97 SR-2 Calculation file for descriptive 
statistics for lithophysal 
abundance and lithophysal 
characteristics in the ECRB 
Mongano et al 1999 [DIRS 149850] 
Cross-Drift. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix O (Section O6). 
ANL-EBS-MD-000027 REV 03 A-8 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
Drift Deg AMR AF 
T-A-P Fit V1.xls 
Microsoft Excel 97 SR-2 Calculation file for descriptive 
statistics for lithophysal 
abundance and lithophysal 
characteristics in the ECRB 
GS021008314224.002 [DIRS 161910] 
GS040608314224.001 [DIRS 171367] 
Cross-Drift. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix O (Section O6). 
lith porosity 3D.xls Microsoft Excel 97 SR-2 Calculation file for projecting 
lithophysal porosity in three 
dimensions. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix T. 
N/A 
Lithophysal 
projection to 
vertical plane.xls 
Microsoft Excel 97 SR-2 Calculation file for projecting 
lithophysal porosity in three 
dimensions. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix T. 
Buesch and Spengler 1998 [DIRS 101433], Buesch et al. 1996 
[DIRS 100106], Mongano et al. 1999 [DIRS 149850] 
intact strength 
nonlith v2.xls 
Microsoft Excel 97 SR-2 Calculation file for intact rock 
strength parameters. Application: 
MO0311RCKPRPCS.003 [DIRS 166073], MO0401DQRIRPTS.003 
[DIRS 168905], MO0402DQRIRPPR.003 [DIRS 168901], 
nonlithophysal rockfall model. 
Calculation details provided in 
Appendix E (Section E3). 
SN0108SD821723.001 [DIRS 159959], SN0306L0207502.008 
[DIRS 165015], SNL02030193001.004 [DIRS 108415], 
SNL02030193001.009 [DIRS 109614], SNL02030193001.012 
[DIRS 108416], SNL02030193001.019 [DIRS 108431], 
SNL02030193001.020 [DIRS 108432], SNL02030193001.021 
[DIRS 108433], SNL02030193001.023 [DIRS 108435], 
SNL02030193001.026 [DIRS 108436], SNSAND83164600.000 
[DIRS 160009], SNSAND84110100.000 [DIRS 160016], 
SNSAND85070300.000 [DIRS 160020], SNSAND85070900.000 
[DIRS 160022], SNSAND85076200.000 [DIRS 160024], 
SNSAND86113100.000 [DIRS 159594] 
joint strength v2.xls Microsoft Excel 97 SR-2 Calculation file for joint strength 
parameters. Application: 
nonlithophysal rockfall model. 
Calculation details provided in 
Appendix E (Section E2). 
SNL02112293001.003 [DIRS 108412], Olsson and Brown 1997 
[DIRS 106453]; SNL02112293001.005 [DIRS 108413], SNL 1996 
[DIRS 165408]; SNL02112293001.007 [DIRS 108414], SNL 1996 
[DIRS 165410]; GS030283114222.001[DIRS 161913], BSC 2003 
([DIRS 166660], Sections 8.6.4 and 8.6.5) 
ANL-EBS-MD-000027 REV 03 A-9 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
rock mass strength 
v2.xls 
Microsoft Excel 97 SR-2 Calculation file for rock mass 
strength properties. Application: 
thermal-mechanical calculation 
GS000608314224.005 [DIRS 166002], USGS 1996 [DIRS 169024]; 
GS000608314224.006 [DIRS 152572], USGS 1996 [DIRS 169029]; 
GS950508314224.003 [DIRS 107488], Singleton 1995 [DIRS 107044]; 
and rockfall models. Calculation 
details provided in Appendix E 
(Section E4). 
GS960408314224.001 [DIRS 168135], USGS 1996 [DIRS 169025]; 
GS960408314224.003 [DIRS 168136], USGS 1996 [DIRS 169026]; 
GS960708314224.009 [DIRS 168137], USGS 1996 [DIRS 169027]; 
GS960908314224.015 [DIRS 108372], USGS 1996 [DIRS 169030] and 
USGS 1996 [DIRS 169031]; GS960908314224.016 [DIRS 108373], USGS 
1996 [DIRS 169032] and USGS 1996 [DIRS 169033]; 
GS960908314224.017 [DIRS 108376], USGS 1996 [DIRS 169034]; 
GS970108314224.002 [DIRS 107490], USGS 1996 [DIRS 169035]; 
GS970208314224.004 [DIRS 107492], USGS 1997 [DIRS 169036]; 
GS970608314224.007 [DIRS 158430], USGS 1997 [DIRS 169040]; 
GS970808314224.009 [DIRS 107494], USGS 1997 [DIRS 169037]; 
GS970808314224.011 [DIRS 107495], USGS 1997 [DIRS 169038]; 
GS970808314224.013 [DIRS 107497], USGS 1997 [DIRS 169039]; 
GS990408314224.003 [DIRS 108404], USGS 1999 [DIRS 169018]; 
GS990408314224.004 [DIRS 108405], USGS 1999 [DIRS 169019]; 
GS990408314224.005 [DIRS 108408], USGS 1999 [DIRS 169020]; 
GS990408314224.006 [DIRS 108409], USGS 1999 [DIRS 169021]; 
MO0004QGFMPICK.000 [DIRS 152554], MO0311RCKPRPCS.003 [DIRS 
166073], Price et al. 1985 [DIRS 106602], SN0108SD821723.001 [DIRS 
159959], SN0208F4102102.002 [DIRS 161874], SN0208L0207502.001 
[DIRS 161871], SN0211L0207502.002 [DIRS 161872], 
SN0212F4102102.004 [DIRS 161875], SN0301F4102102.006 [DIRS 
161876], SN0305L0207502.005 [DIRS 163373], SN0306L0207502.008 
[DIRS 165015], SNL02030193001.001 [DIRS 120572], 
SNL02030193001.002 [DIRS 120575], SNL02030193001.003 [DIRS 
120578], SNL02030193001.004 [DIRS 108415], SNL02030193001.005 
[DIRS 122545], SNL02030193001.006 [DIRS 120579], 
SNL02030193001.007 [DIRS 120582], SNL02030193001.008 [DIRS 
120597], SNL02030193001.012 [DIRS 108416], SNL02030193001.013 
[DIRS 120614], SNL02030193001.014 [DIRS 109609], 
SNL02030193001.015 [DIRS 120617], SNL02030193001.016 [DIRS 
120619], SNL02030193001.018 [DIRS 109611], SNL02030193001.019 
[DIRS 108431], SNL02030193001.020 [DIRS 108432], 
SNL02030193001.021 [DIRS 108433], SNL02030193001.022 [DIRS 
109613], SNL02030193001.023 [DIRS 108435], SNL02030193001.026 
[DIRS 108436], SNSAND83164600.000 [DIRS 160009], 
SNSAND84110100.000 [DIRS 160016], SNSAND85070300.000 [DIRS 
160020], SNSAND85070900.000 [DIRS 160022], SNSAND85076200.000 
[DIRS 160024], SNSAND86113100.000 [DIRS 159594]. 
thermal properties Microsoft Excel 97 SR-2 Calculation file for thermal SN0307T0510902.003 [DIRS 164196], SN0303T0503102.008 [DIRS 
ANL-EBS-MD-000027 REV 03 A-10 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
TM units v2.xls properties. Application: thermalmechanical 
calculation and 
rockfall models. Calculation 
162401], SN0404T0503102.11 [DIRS 169129], SNL01B05059301.006, 
Brodsky et al. 1997.([DIRS 100653], Table 4-4). 
details provided in Appendix D 
(Sections D1 and D5). 
lith-summary-
062104.xls 
Microsoft Excel 97 SR-2 Summary of lithophysal rock 
properties. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix S. 
Price et al. 1985 [DIRS 106602], SN0208L0207502.001 [DIRS 161871], 
SN0211L0207502.002 [DIRS 161872] 
modified lith-
current.xls 
Microsoft Excel 97 SR-2 Summary of lithophysal rock 
properties. Application: 
lithophysal rockfall model. 
Calculation details provided in 
Appendix S. 
Price et al. 1985 [DIRS 106602], SN0208L0207502.001 [DIRS 161871], 
SN0211L0207502.002 [DIRS 161872] 
Beta-small 
scale.xls 
Microsoft Excel 97.SR-2 Calculation file for beta distribution 
parameters (a, b, p, q) for joint 
spacing, trace length, and 
location. Application: DRKBA 
analysis of nonlithophysal rock. 
Calculation details provided in 
Appendix D (Section D7 
Derman, et al. 1973 [DIRS 108444] 
K-small scale.mcd Mathcad 2001i 
Professional 
Calculation file for K factor of joint 
orientation. Application: DRKBA 
analyses of nonlithophysal rock. 
Calculation details provided in 
Appendix D (Section D7). 
N/A 
small scale 
fractures results 
rev1.xls 
Microsoft Excel 97 SR-2 Calculation file for rock blocks 
cumulative percentage of 
occurrence. Application: DRKBA 
analyses of nonlithophysal rock. 
Calculation details provided in 
Appendix D. 
N/A 
ANL-EBS-MD-000027 REV 03 A-11 September 2004 

Drift Degradation Analysis 
Table A-1. List of Drift Degradation Calculation Files (Continued) 
File Name File Type Brief Description References 
small trace 
filtering.xls 
Microsoft Excel 97 SR-2 Calculation file for small-scale 
joint orientation data. Application: 
DRKBA analyses of 
nonlithophysal rock. Calculation 
details provided in Appendix D 
(Section D7). 
N/A 
small.dip DIPS Version 4.03 Calculation file for the graphical 
presentation of fracture data. 
Application: DRKBA analyses of 
small trace length fracture data. 
Calculation details provided in 
Section 6.3.3 and Appendix D. 
N/A 
Heat_Decay_Cal_L 
A1450.xls 
Microsoft Excel 97 SR-2 Calculation file for heat decay 
curves. Application: thermalmechanical 
calculation. 
N/A 
Calculation details provided in 
Section 6.2. 
LA1450_NUFT_Te 
mp_crss-sctn3.xls 
Microsoft Excel 97 SR-2 Calculation file for temperature 
histories at the drift crown. 
Application: thermal-mechanical 
calculation. Calculation details 
N/A 
provided in Section 6.2. 
LA1450_R5C10_N 
UFT_Temp_crss-
sctn.xls 
Microsoft Excel 97 SR-2 Calculation file for temperature 
histories at the drift crown. 
Application: impact analyses on 
LDTH sub-model. Calculation 
N/A 
details provided in Appendix Q 
(Section Q1). 
ground motion Microsoft Excel 97 SR-2 Summary of ground motion MO0407TMHIS104.003 [DIRS 170599]; MO0306SDSAVDTH.000 
parameters.xls parameters (Sections 6.3.1.2.1, [DIRS 164033]; MO0402AVDTM105.001 [DIRS 168890]; 
6.4.2.2, and Appendix X) MO0403AVDSC106.001 [DIRS 168891]; MO0403AVTMH107.003 
[DIRS 168892]; MO0301TMHIS106.001 [DIRS 161868] 
* power cal.mcd Mathcad 2001i Calculation file for power spectral N/A 
(* represents Professional density using the fast Fourier 
multiple files with transform function in Mathcad. 
the ground motion Application: ground motion 
set indicated) sensitivity (Section 6.4.2.2). 
ANL-EBS-MD-000027 REV 03 A-12 September 2004 

Drift Degradation Analysis 
APPENDIX B 
DEVELOPMENT OF JOINT DATA FOR THE TPTPLL ZONE 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
DEVELOPMENT OF JOINT DATA FOR THE Tptpll ZONE 
A description of the generation of representative rock volume using FracMan is presented in 
Section 6.1.6. This appendix provides details for the development of FracMan rock volume for 
the Tptpll (lithophysal rock) zone. The FracMan output data for this zone is provided in the file 
Tptpll-Fracman Generated Fracture Data.xls (Table A-1). 
To begin the analysis of the Tptpll, the observed vapor-phase partings are identified in the 
detailed line survey data. This is done by sorting the observed data with respect to dip and 
identifying those fractures that have a dip of less than 45 degrees. For the Tptpll there are 
20 vapor-phase partings. The mean pole orientation is 239/76. Figure B-1 shows the Great 
Circle for the mean orientation of the vapor-phase partings. The poles for the other sets are also 
plotted. 
N 
S 
EW 
04/100 
08 
15/ 
0 
008 
5/0 
239/76 
Tptpll - Pole Plot of all DLS 
Data with Great Circles for 
Orientation Distribution 
Pollile s 
Equa Area 
Lo wer Hem sph ere 
30 0 P oes 
Source: DTN: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105625]. 
Figure B-1. Tptpll Pole Plot Showing Great Circles for the Tptpll Fractures 
The remaining fracture trace lengths are plotted on a histogram and the trace length distribution 
is evaluated. The distribution is polymodal. A break is defined to separate the long fractures 
from the short fractures. For the Tptpll, this break occurs at approximately 3 m (Figure B-2). 
The distribution of poles for both the cooling and later cooling/tectonic fractures is shown in 
Figure B-1. The set attributes developed from the detailed line survey are provided in Table B-1. 
ANL-EBS-MD-000027 REV 03 B-1 September 2004 

Drift Degradation Analysis 
In Figure B-3, the values used as input to the FracMan simulation are shown. Table B-2 is a 
direct comparison of the observed detailed line survey data with the FracMan output with respect 
to the number of fractures in each set as well as the proportions of the total in each set. The 
proportions of fracture types are very important to establish a representative FracMan network. 
The actual number of fractures is not relevant because the sampling areas are not comparable. 
Source: DTN: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105625]. 
Figure B-2. Trace Length Distribution of the Tptpll Fractures (>45) 
Table B-1. Summary Statistics of the Tptpll Detailed Line Survey Data 
Strike & Dip Trace Length 
Set (Trend & Plunge) (mean) Number of Fractures 
Vapor-Phase Partings 
329/14 
(239/76) 
7.2m 20 
1st Generation Cooling Joints 
130/80 & 175/80 
(040/10 & 085/10) 
9.5m 71 
2nd Generation Cooling and Tectonic 
Joints 
130/80, 175/80, 278/85 
(040/10, 085/10, 008/05) 
1.6m 209 
Source: DTNs: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105625]. 
NOTE: Strike and dip values were determined graphically using the stereonet shown in Figure B-1. 
The most critical comparison is presented in Figure B-4. This is the direct comparison between 
actual full periphery geologic maps from the ECRB Cross-Drift to synthetic full periphery 
geologic maps from FracMan. The synthetic full periphery geologic maps are not a replicate, but 
based on professional expertise and judgment, the FracMan full periphery geologic maps are 
adequately similar to the observed full periphery geologic maps both for intensity and lengths. 
ANL-EBS-MD-000027 REV 03 B-2 September 2004 

Drift Degradation Analysis 
Source: 
DTN: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105625]. 
NOTE: 
The parameter, k dispersion is determined visually by comparing simulated stereonets to observed stereonets. The parameter, size eqv. radius is the 
mean radius (m). The power law distribution is used for the parameter, dist. type. The power law is selected because the fracture process generally 
follows power law physics, such that the number of fractures greater than a given length (x) is proportional to 1/x raised to the power law exponent. The 
parameter, intensity is selected to maintain the proportion of fractures in each set. 
Figure B-3. FracMan Input Sheet for the Tptpll 
ANL-EBS-MD-000027 REV 03 B-3 September 2004 

Drift Degradation Analysis 
Table B-2. Relative Proportions of Fractures from the Detailed Line Survey Versus FracMan 
Output for the Tptpll 
Detailed Line Survey FracMan 
Number of Number of 
Feature fractures Proportion Feature Fractures Proportion 
Vapor-Phase Partings 20 6% Vapor-Phase Partings 647 7% 
1st Generation 
Cooling Joints 71 24% 1st Generation Cooling Joints 2494 25% 
2nd Generation 
Cooling and Tectonic 
Joints 
209 70% 2nd Generation Cooling and 
Tectonic Joints 6738 68% 
Total 300 100% Total 9879 100% 
Source: DTNs: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105625]. 
The orientation comparison is presented in Figure B-5. Pole plots for the detailed line survey 
data and the FracMan output are compared to ensure that the clusters from the detailed line 
survey are correctly simulated in FracMan. For the Tptpll this comparison demonstrates that the 
FracMan output is adequately similar to the observed data. The means are similar and the spread 
of the data about the mean is similar. Not all observed fractures are simulated because the 
FracMan output has less scatter and is not a replicate. 
Figure B-6 provides confirmation that the radius distribution of fractures from FracMan matches 
reasonably well with the observed trace lengths. Figure B-7 shows that fracture intensity, that is 
the slope, is nearly constant until approximately Station 21+50. At this point a sequence of small 
offset faults occurs causing the intensity to increase. 
ANL-EBS-MD-000027 REV 03 B-4 September 2004 

Drift Degradation Analysis 
Source: DTN: GS990408314224.004 [DIRS 108405]; GS990408314224.005 [DIRS 108408]; GS990408314224.006 [DIRS 108409]. 
NOTE: The purpose of this figure is to illustrate the geologic structure contained on a full periphery geologic map. The annotated information on this figure is not 
intended to be legible. (a) from the Tptpll in the ECRB Cross-Drift; (b) with Simulated Full Periphery Geologic Maps from the FracMan Cube. 
Figure B-4. Comparison of Full Periphery Geologic Maps 
ANL-EBS-MD-000027 REV 03 B-5 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 B-6 September 2004 
NSEWPolesEqual AreaLower Hemisphere300 PolesNSEWPolesEqual AreaLower Hemisphere9880 PolesTptpll FracMan DataTptpll DLS Data 
Source: DTN: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105625]. 
NOTE: The FracMan data is representative of the entire rock mass, and is not a replicate of the detailed line survey 
data. Therefore, the number of poles in FracMan is expected to be much greater than the detailed line 
survey data. The location of the poles should agree, which is shown by this figure. 
Figure B-5. Comparison of the Observed Tptpll Fracture Poles to the FracMan Fracture Poles 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 B-7 September 2004 
Radius Distribution Plot for the Tptll0204060801000.010.1110100Radius (m)
Cumulative PercentageFracture Radii (Fracman)
Two-Thirds Trace Length(Observed) 
Source: DTN: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105652]. 
NOTE: This figure compares fracture radii from FracMan to observed trace length data scaled by two-thirds. This is 
based on the relationship between fracture trace length and radius (see Figure D-11 and Equation 6-3). The 
mean fracture radius should be about two thirds of the mean trace length observed. 
Figure B-6. Comparison of the Observed Trace Length Distribution (Scaled by Two Thirds) to the 
FracMan Radii Distribution for Tptpll 
Cumulative Fracture Number for the Tptpll050100150200250140016001800200022002400Stationing (m)
Cumulative NumberLater Cooling/TectonicCoolingVapor-Phase Parting 
Source: DTN: GS990408314224.001 [DIRS 108396]; GS990408314224.002 [DIRS 105625]. 
NOTE: Constant slope indicates constant intensity. 
Figure B-7. Evaluation of Constant Intensity for Tptpll 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 B-8 September 2004 

Drift Degradation Analysis 
APPENDIX C 
REGIONAL AND LOCAL SCALE THERMAL-MECHANICAL ANALYSIS OF THE 
ROCK MASS SURROUNDING WASTE EMPLACEMENT DRIFTS 
AT YUCCA MOUNTAIN 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
REGIONAL AND LOCAL SCALE THERMAL-MECHANICAL ANALYSIS OF THE 
ROCK MASS SURROUNDING WASTE EMPLACEMENT DRIFTS 
AT YUCCA MOUNTAIN 
C1. INTRODUCTION 
This appendix summarizes the results of a three-dimensional thermal-mechanical analysis of the 
repository site at Yucca Mountain using the finite difference code FLAC3D. 
The analysis supports the NUFT drift-scale thermal calculation and to evaluate the edge effect 
described in Section 6.2 by defining the distribution of stresses around drifts due to progressive 
heating of the repository area. Unlike the NUFT calculation that simulated complex heat transfer 
physics (Section 6.2), only the thermal conduction into the rock mass was considered in the 
analysis in order to compute the thermal stresses around the drifts. Simulation of the rock mass 
behavior due to excavation and heating of the drifts has been carried out in two steps. 
First, a regional scale (small-scale, for instance 1/10,000) calculation of the Yucca Mountain site 
was constructed. This calculation includes details of topography, stratigraphy and two structural 
faults. Figure C-1a shows an aerial view of Yucca Mountain, together with a digital elevation 
calculation generated for the purposes of this calculation. Figure C-1b shows the FLAC3D mesh 
constructed from the digital elevation calculation and available geological information. In the 
regional calculation, the heat sources act uniformly distributed over the area delimited by the 
repository boundaries (see Figure C-1). 
Second, a detailed local scale (large-scale, for instance 1/100) calculation has been constructed at 
the specified locations at the center (considered to be the hottest) and edge within the proposed 
repository area (see Figure C-2). This local scale calculation allows the study of induced stresses 
and displacements on the rock mass surrounding a central drift due to simultaneous application 
of heat sources in this drift and in neighboring ones. 
C2. DESCRIPTION OF THE REGIONAL (SMALL) SCALE CALCULATION 
A topographical plan shown of the Yucca Mountain site (the coordinates in the plan view 
correspond to N-S and W-E geographical system in meters) is seen in Figure C-3. The figure 
indicates the location of the proposed repository area (red lines), access tunnels (blue lines) and 
location of available geological cross-sections (black lines). The location of boreholes from 
where thickness of the strata and in situ stresses have been measured is also shown on this figure. 
In the regional scale calculation, the repository area is considered to lie on a horizontal plane at 
an elevation of 1073 meters (averaged from BSC 2003 [DIRS 164519]). From the available 
geological information, the two faults, the Solitario Canyon fault in the west and the Ghost 
Dance fault in the east, have been outlined (the green lines in Figure C-3 represent the traces of 
the faults on the horizontal plane containing the repository at the 1,073 meter elevation). The 
spatial location of the faults, as measured and interpreted from the available geological maps 
(BSC 2004 [DIRS 170029]) and cross-sections extracted from DTN: MO0012MWDGFM02.002 
[DIRS 153777] (i.e., Figures M-1, M-2 and M-3), is defined in Table C-1 and depicted in 
Figure C-4. The details of the cross-section extraction are provided in Appendix M. 
ANL-EBS-MD-000027 REV 03 C-1 September 2004 

Drift Degradation Analysis 
NOTE: a) Aerial View of the Yucca Mountain Site and Digital Elevation Calculation Created from Topographic 
Information. 
b) View of the Regional Scale FLAC3D Calculation Constructed from the Digital Elevation Calculation and 
Available Geological Information. 
Figure C-1. Yucca Mountain Repository Site 
ANL-EBS-MD-000027 REV 03 C-2 September 2004 

Drift Degradation Analysis 
Figure C-2. Local (Large) Scale Calculation in the Central Part of the Repository 
ANL-EBS-MD-000027 REV 03 C-3 September 2004 

Drift Degradation Analysis 
Figure C-3. Topographical Plan View of the Yucca Mountain Site and Main Elements Considered in the 
Regional Scale Calculation 
ANL-EBS-MD-000027 REV 03 C-4 September 2004 

Drift Degradation Analysis 
Table C-1. Spatial Location of the Tectonic Faults Considered in the Analysis 
Name of the fault 
Dip direction/Dip angle [degrees] 
(Direction measured from the North) 
Coordinates of a point on the fault 
[meters] 
(coordinates are N-S, W-E and altitude) 
Solitario Canyon 276/60 (232000, 169730, 1084) 
Ghost Dance 273/85 (232000, 171324, 1084) 
Four mechanical units have been identified and used based on Ortiz et al. (1985 [DIRS 101280]). 
The units at the cross-sections S3, S7 and S10 in Figure C-3 are represented in 
Figures C-4a, C-4b, and C-4c, respectively. The spatial location of the geological units, as 
interpreted from geological maps, is indicated in Table C-2. 
Table C-2. Spatial Location of the Stratigraphic Units Contracts Considered in the Calculation 
Contact between units 
Dip direction/Dip angle [degrees] 
(Direction from North) 
Coordinates of a point on the contact 
[m] 
(coordinates are N-S, W-E and altitude) 
TCw-PTn & TSw1 090/06 (232674, 170693, 1372) 
TSw1 & TSw2-TSw3 090/06 (232674, 170693, 1260) 
TSw2-TSw3 & Underlying 090/06 (232674, 170693, 1060) 
Strata 
The cross-sections in Figure C-4 indicate that the repository level (i.e., at the elevation 
1073 meters) lies mostly in the TSw2-TSw3 unit. 
Figure C-5 shows the FLAC3D regional scale calculation constructed based on the basis of the 
information described above. Figures C-5a and C-5b correspond to the sections S3 and S10 in 
Figures C-4a and C-4c. Figure C-5c is a N-S cross-section along the E-W coordinate 170500 in 
Figure C-3. 
Figure C-6, shows a vertical cross-section at the N-S coordinate 232000 meters and a plan view 
of the FLAC3D calculation at the repository level (i.e., at the elevation 1073 meters). The 
calculation consists of three regions of decreasing zone density. A near region where the 
repository is located is made up of zones of characteristic length 75 meters in both the 
North-South and East-West directions and 50 meters in the vertical direction (the near region has 
110,592 zones). The middle region is made up of zones that have twice the characteristic 
length as those in the near region and the far region has zones that are twice the characteristic 
length of those in the middle region (the middle region has 51,840 zones and the far region has 
72,912 zones; the regional scale calculation has 235,344 zones). The two faults 
(Solitario Canyon fault on the west and Ghost Dance fault on the east) are represented as 
interfaces. 
The mechanical properties considered for the four units (TCw-PTn, TSw1, TSw2-TSw3, and 
underlying strata indicated in Figure C-4) were computed based on Ground Control for 
Emplacement Drifts for SR (BSC 2001 [DIRS 155187], Section 4.1). The original mechanical 
properties (available for every stratigraphic unit at Yucca Mountain) have been averaged based 
on the thickness of the different units included in each of the four units considered in this 
calculation (Figure C-4). The properties are summarized in Table C-3. 
ANL-EBS-MD-000027 REV 03 C-5 September 2004 

Drift Degradation Analysis 
NOTE: Fault displacements are not shown on the simplified cross-sections depicted in this figure. Detailed 
cross-sections including fault displacements are provided in Appendix M. 
Figure C-4. Cross-Sections Showing the Four Thermal-Mechanical Units and Faults at the Locations 
Indicated as S3, S7, and S10 in Figure C-3 
ANL-EBS-MD-000027 REV 03 C-6 September 2004 

Drift Degradation Analysis 
b) 
a) 
c) 
Figure C-5. E-W Cross-Sections S3 and S10 of Figures C-3 and C-4 and N-S Cross-Section Through 
the FLAC3D Calculation 
ANL-EBS-MD-000027 REV 03 C-7 September 2004 

Drift Degradation Analysis 
a) 
b) 
NOTE: a) Cross-Section at the North Coordinate 232,000 Meters. 
b) Plan View of the FLAC3D Calculation at the Elevation 1073 Meters. 
Figure C-6. Repository Grid 
ANL-EBS-MD-000027 REV 03 C-8 September 2004 

Drift Degradation Analysis 
Table C-3. Mechanical Properties Considered for the Rock Mass in the Regional and Local Scale 
Calculations 
Property TCw-PTn TSw1 TSw2-TSw3 Underlying 
Young Modulus [MPa] 2540 15210 15840 15840 
Poissons ratio 0.2 0.2 0.2 0.2 
Density [kg/m3] 1613 1983 2086 1545 
NOTE: These data are based on preliminary results that are similar to the information provided in Appendix E 
(Tables E-1 and E-16). The results from the thermal-mechanical calculation presented in this appendix 
are not sensitive to minor changes in mechanical properties. 
The fault interfaces are calculated as cohesion-less Coulomb contacts. The friction angle is 
considered to be 34 (Bauer et al. 1992 [DIRS 162227]) and the stiffness (in both normal and 
shear directions) is computed, based on the characteristic size of the surrounding zones, so as to 
simulate the effect of a highly stiff contact. Values of 275 MN/m have been considered for the 
stiff contact based on Equation 3.4 of Theoretical Background Manual of the FLAC3D (Itasca 
Consulting Group 2002 [DIRS 160331]). 
The thermal properties considered for the four units (TCw-PTn, TSw1, TSw2-TSw3, and 
underlying strata indicated in Figures C-4 and C-5) were also computed by taking averages from 
the detailed stratigraphic unit information (Appendix E, Section E5). The thermal properties are 
listed in Table C-4. The specific heat values between 95C and 114C are exceptionally high 
compared to the values of other temperature ranges (Table C-4). The high specific heat values 
are based on the analytical solutions presented by Nimick and Connolly (1991 [DIRS 100690]). 
The primary NUFT thermal calculation that is used to support the drift degradation analyses 
(presented in Section 6.2) does not use the high specific heat values, since consideration of latent 
heat effects above the boiling point is built into the NUFT code. 
Table C-4. Thermal Properties Considered for the Rock Mass in the Regional and Local Scale 
Calculations 
Property Condition TCw-PTn TSw1 TSw2-TSw3 Underlying 
Conductivity k <100C 1.015 1.771 1.925 1.201 
[W/mC] = 100C 0.525 1.220 1.328 0.581 
Specific heat Cv < 95C 1,158 939 937 1,304 
[J/kg C] 95C = Cv <114C 11,135 5,791 5,714 15,775 
= 114C 1,010 991 990 1,016 
Thermal expansion at <50C 4.46x10-6 6.56x10-6 7.14x10-6 7.14x10-6 
[/C] 50C = at <75C 4.46x10-6 6.56x10-6 7.47x10-6 7.47x10-6 
75C = at <100C 4.46x10-6 6.56x10-6 7.46x10-6 7.46x10-6 
= 100C 4.46x10-6 6.56x10-6 9.07x10-6 9.07x10-6 
The heat capacity data used in the thermal property calculation (Table C-4) were preliminary 
data superseded by DTN: SN0307T0510902.003 [DIRS 164196] (Table E-19). Therefore, an 
impact analyses was conducted regarding the preliminary data and presented in Appendix Q2. 
The impact analyses indicates there are insignificant impacts on the below 95C and over 114 C 
ranges, and only minor impact on the 95 to 114C range for the local scale thermal-mechanical 
calculation (Section C3). An additional local scale calculation is not necessary since the local 
ANL-EBS-MD-000027 REV 03 C-9 September 2004 

Drift Degradation Analysis 
scale calculation was only used to support the main thermal-mechanical calculation in 
Section 6.2. Both an initial state of stress and an initial state of temperature are considered for 
the regional scale calculation. The initial temperature in the rock mass is needed to compute the 
temperature-dependent thermal properties listed earlier. 
The vertical component of in situ stress is considered to be a major principal stress, s1 (see 
Section 6.3.1.1). It is considered to be lithostatic (i.e., computed as the weight of the overburden 
from the topography and density values described earlier). Figure C-7 shows contours of vertical 
stress in a cross-section of NS coordinate 232000 meters. The intermediate and minor principal 
stresses (s2 and s3 respectively) are horizontal (see Section 4, Table 4-1). The direction of the 
intermediate principal stress s2 is N15E. The ratio of intermediate to major principal stress is 
taken to be s2/ s 1 = 0.617 based on the data developed in Section 6.3.1.1. This is based on 
values of the in situ stresses measured at the location shown in Figure C-3 (see Section 6.3.1.1). 
The direction of the minor principal stress s 3 is N105E (or E15S). The ratio of minor to major 
principal stress is taken s3/ s1 = 0.361 (also from the values of measured in situ stresses provided 
in Section 4, Table 4-1, and developed in Section 6.3.1.1). 
The initial state of temperature is considered to vary linearly with depth below the surface (i.e., 
as defined by the topography shown in Figure C-1). The initial temperature is considered to be 
fixed and equal to 18C at ground surface and equal to 34C at the level of the permanent 
groundwater table. At the elevations of 1231 and 730 meters, time-averaged temperatures based 
on UZ Flow Models and Submodels [BSC 2004 [DIRS 169861], Section 6.3]) were considered. 
Note the temperature values are different from the boundary temperatures of the NUFT thermal 
calculation in the Section 6.2 (16.9C for the ground surface and 29.2C for the water table 
temperature), since the initial temperature is considered for the entire repository layout 
(BSC 2004 [DIRS 169861], Section 6.3). For points above the water table, the initial 
temperature is linearly interpolated from the fixed values at the ground surface and water table 
level. For points below the water table, the initial temperature is considered to be constant and 
equal to 34C. 
Thermal loading of the repository area is considered to be the only source of stress redistribution 
and induced displacement within the rock mass (the regional scale calculation does not take into 
account the excavation of drifts within the repository area). This thermal load is considered to be 
uniformly distributed within the boundary limits of the repository. In the present calculation, all 
panels comprising the repository (see Figure C-3) are considered to be activated at once (i.e., the 
calculation assumes an instantaneous emplacement of the waste in all panels of the repository; 
see Section 5.1). 
The thermal load is computed considering a linear heat power source equal to 1450 W/m that 
acts along each drift and a separation between the axes of adjacent drifts of 81 meters (i.e., the 
value of distributed heat power, before any correction is made due to radioactive decay and 
ventilation, is equal to q o = 1450/81 = 17.9 W/m2). 
ANL-EBS-MD-000027 REV 03 C-10 September 2004 

Drift Degradation Analysis 
The heat output is considered to vary in time according to the following equation, which is 
derived directly from fundamental physics: 
(
t q ) =d(t) [1-. (t)]q (Eq. C-1) 
ve 0 
where t is the time in years, d(t) is a radioactive decay correction factor, and .ve(t) is a correction 
factor for ventilation. 
The graphical representation of the function d(t), calculated from D&E / PA/C IED Typical 
Waste Package Components Assembly (BSC 2004 [DIRS 167369]), is shown in Figure C-8a. 
Figure C-7. Contours of the In Situ Vertical Stress s2 = s1 and Direction of the Horizontal (Principal) 
Stresses s2 and s3 
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Drift Degradation Analysis 
Figure C-8. Heat Source Correction Functions for a) Radioactive Decay and b) Ventilation 
ANL-EBS-MD-000027 REV 03 C-12 September 2004 

Drift Degradation Analysis 
The graphical representation of the function .ve(t) is shown in Figure C-8b. Note that forced 
ventilation is considered for a pre-closure period of 50 years. Throughout this period of time, 
ventilation efficiency is constant and equal to 90 percent. 
Values of temperature change at specific points within thermal sectors have been determined (the 
points are indicated by the small circles g1 through g5 in Figure C-9). Figure C-10 shows the 
evolution of temperature at these points after 10,000 years of heating. Figure C-10a shows 
temperature as a function of time, and Figure C-10b presents the same results using a logarithmic 
time scale. 
Heating of the repository area induces changes in stresses (with respect to the initial stresses 
described earlier) and displacements. Changes in stresses and displacements have been recorded 
for different stages of heating in the regional calculation (information is available for the 
sequence 1, 10, 20, 50, 100, 200, 300, 400, 500, 750, 1000, 2000, 3000, 4000, 5000, 7500, and 
10,000 years). 
For example, Figures C-11 and C-12 show the change in temperature along a cross-section of the 
calculation after 10, 100, 1000 and 10,000 years. 
Figures C-13a and C-13b show contours of magnitude of induced displacement after 100 and 
1000 years of heating. 
C3. DESCRIPTION OF THE LOCAL (LARGE) SCALE CALCULATIONS 
The purpose of the local-scale calculation is to analyze the effect of heating at a drift scale. 
The locations of the local-scale calculation seen in Figure C-14 are with respect to the regional 
calculation. The center of the calculation is located at coordinates 170730, 234913, 
1073 (W-E, N-S, and altitude in meters), while the edge of the calculation is at coordinates 
170126, 233439, 1073 (W-E, N-S, and altitude in meters). The axes of the drifts in Figure C-14 
are oriented N72E with respect to the North. The center location is considered to be the hottest 
location of the calculation. 
A plan view of the local-scale seen in Figure C-15 center calculation is at the repository level. 
The figure also shows two vertical cross-sections taken parallel and perpendicular to the axis of 
the drift. From Figure C-15, it is seen that the local scale calculation extends 200 meters 
vertically, 200 meters horizontally along the axes of the drifts, and 404 meters horizontally 
perpendicular to the axes of the drifts. From the vertical cross-sections, it is seen that the central 
drift (radius 2.75 meters) is simulated explicitly as a tunnel of this dimension. The surrounding 
drifts, separated a distance of 81 meters from the central drift and from each other, are not 
represented as voids, but rather as linear sources subject to thermal load. The local-scale edge 
calculation is similar to the center calculation except consideration of the repository edge 
location. 
The local-scale calculation shown in Figures C-15 works in coordination with the 
regional-scale calculation described earlier. Thermal-mechanical properties, in situ temperatures 
and stresses, thermal loads, decay and ventilation functions are considered to be the same as 
those used in the regional scale calculations. 
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Drift Degradation Analysis 
NOTE: Points g1 through g5 indicate the location where temperatures have been recorded in the calculation. 
These points do not relate to repository emplacement panel nomenclature. 
Figure C-9. Plan View of the Repository Area Showing Boundaries of Uniformly Distributed Heating 
Sections 
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Drift Degradation Analysis 
NOTE: a) Time in Years; b) Logarithm of Time in Years, for the Locations g1 through g5 Indicated in Figure C-9. 
Figure C-10. Evolution of Temperature Increase as a Function 
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Drift Degradation Analysis 
NOTE: a) after 10 years of heating; b) after 100 years of heating. 
Figure C-11. Contours of Mean Temperature Change (= 100 Years) 
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Drift Degradation Analysis 
NOTE: a) after 1,000 years of heating; b) after 10,000 years of heating. 
Figure C-12. Contours of Mean Temperature Change (= 1,000 Years) 
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Drift Degradation Analysis 
NOTE: a) after 100 years of heating; b) after 1000 years of heating. 
Figure C-13. Contours of Magnitude of Induced Displacements (= 100 Years) 
ANL-EBS-MD-000027 REV 03 C-18 September 2004 

Drift Degradation Analysis 
Figure C-14. Geographical Location of the Local Scale Calculation 
ANL-EBS-MD-000027 REV 03 C-19 September 2004 

Drift Degradation Analysis 
Figure C-15. Isometric and Plan View, and Cross-Sections of the Local Scale Center Calculation 
The regional scale calculations provide the boundary conditions (i.e., temperature and stresses at 
the boundaries) needed to run the thermal-mechanical simulation. Transfer of temperatures and 
stresses from the regional-scale calculation to the local-scale calculations are performed by a 
series of interpolation functions. These functions compute the values of temperatures and 
stresses at the grid points and the zones of the regional scale calculation at specified times in the 
simulation (e.g., 1, 10, 100, 200, 300 . . . 10,000 years) and interpolate these to the grid points 
and zones of the local scale calculations. 
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Drift Degradation Analysis 
The thermal-mechanical simulation at the local-scale is intended to determine the distribution of 
temperatures and stresses around the central drift (see Figure C-15). A linear thermal load of 
1450 W/m (the same as used in the regional scale calculation) with the decay and ventilation 
functions shown in Figure C-8 is applied along the drifts represented in the calculations. 
Results for the local-scale center calculation are represented in Figures C-16 through C-18. 
Figure C-16 represents the evolution of temperature at points surrounding the drifts on a vertical 
plane that passes through the center of the calculation and runs perpendicular to the axis of the 
drift (i.e., it has a direction of 162 from the North). Figure C-17 shows contours of temperature 
on this plane after 50 and 500 years of heating. Figure C-18 shows contours of the vertical 
stress sz after 50 and 500 years of heating. 
Results for the local-scale edge calculation are also represented in Figures C-19 through C-21. 
Figure C-19 represents the evolution of temperature at points surrounding the drifts on a vertical 
plane that passes through the center of the calculation and runs perpendicular to the axis of the 
drift. Figure C-20 shows contours of temperature on this plane after 50 and 500 years of heating. 
Figure C-21 shows contours of the vertical stress sz after 50 and 500 years of heating. 
ANL-EBS-MD-000027 REV 03 C-21 September 2004 

Drift Degradation Analysis 
Figure C-16. Evolution of (Induced) Temperatures at Different Locations Around the Central Drift in the 
Local Scale Center Calculation 
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Drift Degradation Analysis 
NOTE: Years of heating: a) 50 years; b) 500 years. 
Figure C-17. Contours of Induced Temperatures in the Local Scale Center Calculation on Heating 
ANL-EBS-MD-000027 REV 03 C-23 September 2004 

Drift Degradation Analysis 
NOTE: Years of heating: a)50 years; b) 500 years. 
Figure C-18. Contours of Induced Vertical Stress sz for the Local Scale Center Calculation on Heating 
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Drift Degradation Analysis 
Figure C-19. Evolution of (Induced) Temperatures at Different Locations Around the Drift in the Local 
Scale Edge Calculation 
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Drift Degradation Analysis 
NOTE: After heating: a) 50 years; b) 500 years. 
Figure C-20. Contours of Induced Temperatures in the Local Scale Edge Calculation on Heating 
ANL-EBS-MD-000027 REV 03 C-26 September 2004 

Drift Degradation Analysis 
NOTE: After heating: a) 50 years; b) 500 years of heating.
Figure C-21. Contours of Induced Vertical Stress sz for the Local Scale Edge Calculation on Heating 
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Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
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Drift Degradation Analysis 
APPENDIX D 
DRKBA ANALYSIS OF NONLITHOPHYSAL ROCK
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Drift Degradation Analysis 
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Drift Degradation Analysis 
DRKBA ANALYSIS OF NONLITHOPHYSAL ROCK
The DRKBA analysis approach involves the use of probabilistic key-block theory through the 
numerical code, DRKBA V3.31 (see Section 3.1). This method is based on an industry-accepted 
approach for analyzing geotechnical problems. Prior to initially purchasing the DRKBA 
software, technical literature sources were reviewed for the purpose of determining the most 
appropriate approach to be used in the development of a key-block analysis for the YMP. 
In summary, the issue of key-block analysis in underground excavations located in jointed rock 
masses has been considered in a number of design situations. Deterministic methods of block 
theory in rock engineering were advanced by Warburton (1981 [DIRS 150093]) and Goodman 
and Shi (1985 [DIRS 150094]). The UNWEDGE software (UNWEDGE V2.3, 30053 V2.3) is 
an example of a deterministic method that calculates the maximum block size given the spacing 
and orientation of three joint sets, and the excavation size and orientation. Subsequently Hoerger 
and Young (1990 [DIRS 151814]), Tyler et al. (1991 [DIRS 151818]), Kuszmaul and Goodman 
(1995 [DIRS 151816]) and Stone et al. (1996 [DIRS 150437]) have been orientated toward 
probabilistic risk assessment of key-block failure. Stone et al. (1996 [DIRS 150437]) reports on 
the use of DRKBA. These latest methods are considered suitable for the analysis of densely 
jointed and faulted rock masses where planar joint surfaces can reasonably be considered. These 
conditions typically exist at the YMP. 
D1. DRKBA APPROACH 
DRKBA is a commercially available acquired software product (described in Section 3). The 
software simulates structural discontinuities as circular discs placed in the rock mass according 
to probabilistic distributions determined from tunnel mapping data. Joint planes are simulated by 
a Monte Carlo technique from probability distributions representing the orientation, spacing, and 
trace length of the corresponding joint set. DRKBA determines where joint planes intersect to 
form blocks, and then analyzes these blocks to determine if they are geometrically feasible 
(i.e., the shape of the block is such that it is physically possible to slide or fall into the tunnel 
opening). If the blocks are geometrically feasible, DRKBA then determines if they are 
mechanically stable (i.e., the gravitational forces that cause the block to move into the tunnel 
opening are less than the frictional forces on the block sliding surfaces). DRKBA does not 
include a ground support element. 
A probabilistic key-block analysis using DRKBA requires four sets of data. The required data 
are stored in data files having extensions .mkg, .exc, .den, and .prb, and contain information for 
the grid, excavation, rock density, and joint sets, respectively. The make grid file (.mkg) 
includes the information required for building a grid of nodal points for the mesh. The 
excavation data file (.exc) contains the information for defining an excavation in 
three-dimensional space. The density file (.den) holds the information for the rock density data. 
The probabilistic joint data file (.prb) includes the required information for generating fracture 
space from the given fracture probability distributions. 
The DRKBA software employs a bipolar Watson distribution for joint orientation data. The 
principal axis orientation and a concentration factor k are the required inputs for the bipolar 
Watson distribution. The concentration factor k is an index of the concentration. The larger the 
value of k, the more the distribution is concentrated towards the principal axis orientation. Joints 
ANL-EBS-MD-000027 REV 03 D-1 September 2004 

Drift Degradation Analysis 
are represented as circular discs in the DRKBA analysis. Joint radii, spacings, and positioning 
are simulated with beta distributions. The beta distribution is a four-parameter distribution with 
the parameters a, b, p, and q. Parameters a and b represent the ends of the closed interval upon 
which the beta distribution is defined. The parameters p and q determine the shape of the 
distribution curve, their values were calculated from the mean and standard deviation of the 
transformed data. The transformed data were obtained by normalizing the data with the 
maximum value. The cohesion and friction angle of the joints are simulated as a bivariate 
normal distribution. Inputs for the mean and standard deviation of the joint strength parameters 
are required. 
D2. STATISTICAL REPRESENTATION OF JOINT DATA 
The DRKBA software uses joint geometry inputs provided in Table 4-1, and which are described 
in Fracture Geometry Analysis for the Stratigraphic Units of the Repository Host Horizon 
(CRWMS M&O 2000 [DIRS 152286]). These developed fracture data include joint set 
orientation, joint spacing, joint trace length, and joint offset from the detailed line survey. Joint 
sets were identified in Fracture Geometry Analysis for the Stratigraphic Units of the Repository 
Host Horizon (CRWMS M&O 2000 [DIRS 152286], Section 6.4.1) based on clustering of the 
data from joint normal vectors plotted on stereonets as shown in Figure D-1 for the Tptpmn unit. 
A scatter plot, contour plot, strike rosette, and major planes are included in this figure. The 
major joint plane is expressed using the strike/dip format in this figure. The joint orientation is 
expressed in dip direction/dip format in Table D-1. In addition to the primary joint sets listed in 
Table D-1, a random joint set has also been simulated to account for any joint that is present in 
the rock mass but not accounted for in the primary sets. The dispersion of the individual joints 
about their associated joint set axes was modeled by a Watson bipolar distribution for axial data. 
This probability distribution is characterized by a unit normal vector representing the mean 
direction about which the data is clustered and a concentration factor k representing the degree to 
which the data is clustered about the mean direction. The concentration factors were calculated 
based on the eigenvalues and eigenvectors of the orientation matrix (Fisher et al. 1987 
[DIRS 108447]). The calculated concentration factors are also listed in Table D-1. The process 
to calculate the concentration factors is included in the electronic files, New-K-Tptpmn V1.mcd 
and K-small scale.mcd (DTN: MO0408MWDDDMIO.002). 
Joint radii, spacings, and positioning (see Section 5.2.1) are simulated with beta distributions. 
The offset measured from the center of the trace length to the scan line was used as the 
positioning parameter. The parameters a, b, p and q for the Tptpmn unit are listed in Table D-2, 
with the details for the calculation of each parameter provided in the electronic files, 
New-Beta-Tptpmn V1.xls and Beta-small scale.xls (DTN: MO0408MWDDDMIO.002). An 
example for calculating the distribution parameters with the fracture data of the first joint set for 
Tptpmn unit is provided in Section D6. 
Cohesion and friction angle of the joints are simulated with the bivariate normal distribution. 
The laboratory shear strength tests indicate the mean cohesion value of 0.6 MPa with a range of 
0.2 to 0.9 MPa (Appendix E, Section E2). Due to the wide range of values, the joint cohesion 
used in the nonlithophysal rockfall models is conservatively initialized as 0.1 MPa, resulting in 
increased rockfall. 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 D-3 September 2004 
ESNESWNESWNESWNESWNumber of Poles Plotted: 21501SCATTER PLOTCONTOUR PLOTMAJOR PLANESSTRIKE ROSE PLOTSSNumber of PolesContour Interval10.50-13.108.75-10.507.00-8.755.25-7.003.50-5.251.75-3.50<1.75Number of PolesPlane Orientation0 - 702703-14041405-21062107-28082808-3510209/83329/09131/84125 - 4950 - 7475 - 99100 - 124125 - 149150 - 174175 - 199200 - 224225 - 249 
Source: CRWMS M&O 2000 [DIRS 152286], Figure III-2. 
Figure D-1. Determination of Primary Joint Sets, Tptpmn 

Drift Degradation Analysis 
Table D-1. Joint Set Orientation Data and Concentration Factorsa 
Mean Dip 
Directionb Mean Dipb 
Concentration 
Lithologic Unit Joint Set Number (degrees) (degrees) Factor k 
1 221 84 31.586 
2 299 83 26.143 
Tptpmn 3 59 9 18.210 
Random (> 1-m trace) 267 79 2.896 
Random (< 1-m trace) 293 64 1.833 
a 
Calculation details provided in DTN: MO0408MWDDDMIO.002, files New-K-Tptpmn V1.mcd and K-small 
scale.mcd and described in Section D7. 
b 
The derivation of the joint set orientation data is shown in Figure D-1. The joint set orientation data for small 
trace length fractures (i.e., < 1 m trace) is documented in the file, small scale filtering.xls 
(DTN: MO0408MWDDDMIO.002) as the mean of the azimuth and dip data. 
Table D-2. Beta Distribution Parameters for Tptpmn Unita 
Joint Set a b 
Number Parameters (m) (m) p q 
Spacing 0.0008 13.9199 0.2322 5.1372 
1 Radius 1.8200 108.0000 0.6554 20.7171 
Positioning 0.0000 9.1500 0.7569 10.2825 
Spacing 0.0033 16.5306 0.4098 3.0879 
2 Radius 1.6400 141.0600 0.2024 7.2515 
Positioning 0.0000 9.1500 0.3292 4.0327 
Spacing 0.0018 15.2606 0.2010 5.2988 
3 Radius 0.3200 101.6000 0.5503 8.5360 
Positioning 0.0150 9.1500 0.6369 4.6763 
Random 
(> 1 m trace) 
Spacing 0.0100 15.1900 0.5279 7.6008 
Radius 1.3000 60.6000 0.6333 9.2812 
Positioning 0.0000 9.1500 0.5735 7.6186 
Random 
(< 1 m trace) 
Spacing 0.0100 0.9900 0.5119 3.9947 
Radius 0.3000 1.9400 0.3850 1.3472 
Positioning 0.0050 0.4550 0.8316 3.0687 
a 
Calculation details provided in DTN: MO0408MWDDDMIO.002, files New-Beta-Tptpmn V1.xls and Beta-small 
scale.xls are described in Section D7. 
D3. EXCAVATION MODELING 
The excavation in this analysis is a horizontal 5.5 m diameter emplacement drift trending 75 in 
accordance with the repository design description (BSC 2003 [DIRS 165572], Sections 5.1.4 
and 8.7). It should be noted that the actual emplacement drift azimuth is 72. This 3 difference 
between the modeled and actual drift alignment is acceptable since given the variability of joint 
set orientations captured in the model, the alignment difference does not significantly affect the 
results from this analysis. 
ANL-EBS-MD-000027 REV 03 D-4 September 2004 

Drift Degradation Analysis 
For each Monte Carlo simulation, a 24.4 m long (80-ft) tunnel has been modeled in a 
three-dimensional space. A circular tunnel opening without backfill was modeled using 18 plane 
equations to describe the circumference of the circular tunnel, and 2 plane equations were used to 
describe each end of the tunnel. The selection for the length of the tunnel modeled and the 
number of planes for simulation of the circular opening were based on the computer run time and 
the accuracy of the simulation. Calculations for the plane equations are included in the 
electronic file, exca vectors V2.xls (DTN: MO0408MWDDDMIO.002). The region around the 
excavation has been modeled with a grid consisting of 681,472 nodes. The nodes are spaced 
0.3 m (1 ft) apart, with each node representing 0.028 cubic meters (1 cubic foot) of the rock 
mass. 
D4. SEISMIC CONSIDERATION 
Natural analogues for the effect of seismic events on rockfall are provided in Appendix G. 
Underground openings are constrained by the surrounding medium, and it is unlikely that 
underground openings could move to any significant extent independently of the medium or be 
subjected to vibration amplification. Two potential causes of block movement during seismic 
events were observed. The first is related to the differential acceleration in the rock blocks 
surrounding the tunnel due to seismic excitation (Dowding 1979 [DIRS 101977], p. 19). The 
second cause is the increase of the tangential force from seismic loading along the sliding 
surfaces of the rock block (Kaiser et al. 1996 [DIRS 108453], p. 8-3). 
A high-frequency seismic wave is required for the possibility of block movement due to 
differential acceleration (Dowding 1979 [DIRS 101977], p. 19). For a case with shear wave 
velocity of 2000 m/sec intersecting a 5.5 m diameter drift in the repository host rock, the 
frequency that would produce the differential acceleration was calculated to be approximately 
90 Hz. This frequency of concern is very high compared to the principal frequencies (1 to 
10 Hz) with major earthquakes. Block movement due to differential acceleration is therefore not 
considered in this analysis. 
With a relatively high ratio of wavelength to opening diameter, the surrounding rock mass and 
the opening itself move nearly as a rigid body with free-field acceleration. A simplified 
quasi-static approach was used in this analysis to account for the increase of the force along the 
sliding surfaces. Due to the limitation of DRKBA, seismic loads cannot be directly applied to 
the opening in the numerical simulation. An alternative method with reduction of joint strength 
parameters was used to account for the seismic effect. The reduced joint strength parameters are 
listed in Table D-3. 
The following equation was derived using basic laws of motion for a sliding block (Figure D-2), 
and used to calculate the reduced friction angle in the alternative method: 
.f= atan(PGA /1g) (Eq. D-1) 
where PGA is the peak ground acceleration of the shear wave with unit in g. The tangential 
forces (T1 and T2) and normal forces (N1 and N2) in Figure D-2 are defined as follows: 
T1 = Mg  sin. (Eq. D-2) 
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Drift Degradation Analysis 
Table D-3. Reduced Joint Strength Parameters to Account for Seismic Effect 
Loading Case 
Peak Ground 
Acceleration (g) Joint Cohesion (Pa) Joint Friction Angle (degree) 
Static  99,873 41 
Seismic 1 10-3 0.14 21,282 34 
Seismic 1 10-4 0.47 10,776 18 
NOTE: Peak ground acceleration for 1 10-4 ground motion was selected based on DTN: MO0306SDSAVDTH.000 
[DIRS 164033] (see Table 6-5). Peak ground acceleration for 1 10-3 ground motion was selected based on 
preliminary data and is used for comparison only. Static joint cohesion and friction angle values are 
provided in Appendix E (Section E2). Seismic joint cohesion and friction angle values are calculated as 
described in this section. Note that static joint cohesion is conservatively scaled down to 0.1 MPa from 0.6 
MPa (see Section D2). 
T2 = Ma  cos. (Eq. D-3) 
N1 = Mg  cos. (Eq. D-4) 
N2 = - Ma  sin. (Eq. D-5) 
where M, a, g, and . are defined in Figure D-2. At the incipience of block sliding, the tangential 
force is equal to the resisting frictional force: 
T1 + T2 = (N1 + N2)  tanf (Eq. D-6) 
where f is defined in Figure D-2. Substituting Equations D-2 through D-5 into Equation D-6 
yields 
Mg  sin. + Ma  cos. = (Mg  cos. -Ma  sin. )  tanf (Eq. D-7) 
Equation D-7 can be arranged to the following form: 
g 
a= 
f.. 
.f. 
tansincos 
sintancos = 
+ 
- 
f. 
.f 
tantan1 
tantan 
+ 
- 
(Eq. D-8) 
Equation D-8 can be rewritten based on the trigonometric relationship for the tangent function: 
a
= tan(. f ) = tan(.f ) (Eq. D-9) 
- 
g 
Equation D-1 is therefore derived as: 
= . atan( a ) (Eq. D-10) f
g 
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Drift Degradation Analysis 
.Mg 
Ma 
T1 
T2 
N1 
N2 M = blga iiifile 
ock mass 
= gravity 
= sesmc acceleraton 
= frction ang
Figure D-2. Illustrative Example of Derivation of Equation D-1 
where a = PGA in Equation D-1. Note that this approach is not applicable for large ground 
motions in which the PGA exceeds 0.86 g, since with an initial static friction angle of 41 , 
Equation D-1 would produce negative friction angles. 
This method is illustrated by the simple examples presented in Figure D-3. The stable joint 
plane example is presented in Figure D-3a. In this example, the alternative method (i.e., a 
reduced friction angle) predicts a stable condition, which is the same as the approach with the 
seismic load included. The unstable joint plane example is presented in Figure D-3b. The 
alternative reduced friction angle method is capable of predicting the unstable joint condition as 
shown. 
D5. THERMAL AND FRACTURE - DEGRADATION CONSIDERATION 
The induced thermal stress and the potential degradation of joint mechanical properties are the 
concerns for the thermal effect to the block movement. Due to the lateral confinement of the 
rock, the predicted thermal stress is highest in the horizontal direction. The high horizontal 
thermal stress provides a locking effect for the blocks formed by the predominant vertical joint 
sets during the heating period, thus preventing rockfall. Due to the limitation of the applying 
external loads using DRKBA, this locking effect, which reduces rockfall, was conservatively 
ignored in this analysis. 
The site-specific time-dependent behavior of joint strength parameters for the host rock is not 
available at this time. An approach based on the time-dependent degradation work by Kemeny 
(1991 [DIRS 108455]) is used in this study. The approach considers that the degradation occurs 
mainly due to the reduction of joint cohesion. Joint cohesion exists due to the asperities along 
the joint surface. These asperities may shear off with time and they may shear off due to the 
increased shear stress caused by the thermal effect. By using the numerical analysis results for 
the thermally induced shear stress and some site-specific data, the joint cohesion degradation 
with time can be quantified based on the approach reported by Kemeny and Cook (1986 
[DIRS 108454]). 
The equation for the mode II stress intensity factor (KII) for a single asperity under shear and 
normal stresses can be expressed in the following (Kemeny and Cook 1986 [DIRS 108454]): 
f
K
II 
(t-s 2)) tan( w
n
=
t a ) 
(Eq. D-11) 
p ( 
ANL-EBS-MD-000027 REV 03 D-7 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 D-8 September 2004 
sn =normal stressss1 =shear stressss2 =seismic induced shear stresssT =combined stress.1 =joint friction angle.2 =reduced joint friction angle(.2 = .1  atan(ss2/sn))
ss1ss2.1ss1ss2.1ss1ss1.2.2snsnsnsnsTsTsTsT 
a. Stable Condition b. Unstable Condition 
Figure D-3. Illustrative Examples for the Alternative Method to Account for Seismic Effect 
where t is the shear stress, sn is the normal stress, and f is the friction angle. The geometrical 
parameters w and a are shown in Figure D-4. 
Critical stress intensity factor of the mode II fracture, KIIC, of 0.5 MPa m1/2 is selected based on 
data from the direct shear tests (Table E-3) and the Linear Elastic Fracture Mechanics (LEFM) 
theory. In the LEFM, the KIIC is (Jaeger and Cook 1979 [DIRS 106219]): 
EGKcIIC= (Eq. D-12) 
where GC is the strain energy release rate (J m-2) and E is the Youngs modulus (GPa). The strain 

Drift Degradation Analysis 
energy release rate, GC, could be estimated from the energy stored during the direct shear tests: 
1
G =d C (Eq. D-13) 
c 20 c 
where C0 is the cohesion (peak shear strength at zero normal stress), and dc is the displacement at 
the peak shear strength. While dc is considered as 0.5 mm from the displacement at the peak 
shear strength of the lowest normal stress, 2.5 MPa (see the first row of Table E-3 and Figure 6 
of Olsson and Brown 1997 [DIRS 106453]), cohesion and Youngs modulus are utilized as 
0.1 MPa (Section D.2) and 33.6 GPa (Table E-6), respectively. The resulting KIIC value is 
0.92 MPa m1/2. However, a value of 0.5 MPa m1/2 is selected for this analysis, since the Youngs 
modulus varies from 13.4 to 47.3 GPa (Table E-6) and the resulting KIIC varies from 0.58 to 
1.09 MPa m1/2. The selected value is conservative, since the input cohesion and Youngs 
modulus values are conservative. 
It is considered that shear crack growth will occur when the mode II stress intensity factor, KII 
reaches the KIIC. Setting KII = KIIC and rearranging Equation D-11 for t gives the following: 
t=KIIC pa +s tanf (Eq. D-14) 
n
2w 
Equation D-14 is the failure criterion for the discontinuity, and is made up of two terms, a 
cohesion term and a frictional term. The first term on the right hand side of the equation is the 
joint cohesion due to the asperity: 
t a ) (Eq. D-15) 
K 
IIC p (
C0 = 
where C0 is the joint cohesion. 2w 
The cohesion of 0.1 MPa is predicted using the parameters KIIC = 0.5 MPa m1/2, w = 0.5 m, and a0 
is equal to 0.0127 m. These parameters are therefore used as the initial parameters before 
time-dependent crack growth occurs. As the asperity size decreases due to time-dependent crack 
growth, the cohesion will decrease as given by Equation D-15. 
2w 
2a 
n 
n 
Figure D-4. Parameters Used for Calculation of Mode II Stress Intensity Factor 
ANL-EBS-MD-000027 REV 03 D-9 September 2004 

Drift Degradation Analysis 
The time-dependent crack growth can be expressed using the following equation (Kemeny 1991 
[DIRS 108455]): 
n
.
.
t a d ))
(( 
K
II
=
A 
(Eq. D-16) 
.
.
.
.
dt 
K
IIC 
where A and n are subcritical crack growth parameters. 
Combining Equations D-11 and D-16, the time-dependent crack growth can be written as: 
n 
t a d ))
(( 
dt 
=
2
n 
A
-
p
n 
/2
.
..
.
.
IIC)( 
f 
K t a 
)) tan( 
w(s t 
- 
(Eq. D-17) 
n
..
.
10
Previous studies of the Yucca Mountain area have used n = 25 and A ranging from 10-6 to 
-4 m/sec (Kessler et al. 1996 [DIRS 100558]). A value for A of 10-5 m/sec is used in this 
analysis. 
The effective shear stress, (t -sn tanf), is time-dependent due to the thermal loading by the 
canisters. The thermal loading can cause horizontal stresses as high as 50 MPa in the backs of 
the underground drifts, decreasing the stability of some joints and increasing the stability of 
others. On average, it is found that the effective shear stress along the joints (t -sn tanf) 
increases by as much as 16 percent in the time period where heating of the rock occurs. The 
curve-fit function used to describe the additional effective shear stress due to thermal heating is 
as follows: 
t f )
(
=
1
+
* 60000104455.0
e
(120-t )/50 2
t 
(Eq. D-18) 
This function is presented graphically in Figure D-5. The figure shows that the shear stresses are 
increased by approximately 10 percent in the period between 50 and 200 years. Adding this 
function to Equation D-17, the time-dependent crack growth expression is now: 
n 
t a d ))
(( 
dt 
=
31536000
*
2
n
-
p
A 
n 
/2
.
..
.
.
(120
-
t )/50 2
t 
IIC.
. 
.)( 
f(Eq. D-19)
K t a 
1))( tan( 
-
w(s t 
* 60000104455.0 
)
+
e
n 
The nonlinear differential equation was solved numerically using the fourth order Runge-Kutta 
method in Mathcad (file: Time thermal cohesion degradation V1.mcd). The calculation results 
in an asperity versus time relationship. This relationship is then used in conjunction with 
Equation D-15 to obtain the cohesion values for various times (Table A-1, file: Time thermal 
cohesion degradation V1.mcd). 
ANL-EBS-MD-000027 REV 03 D-10 September 2004 

Drift Degradation Analysis 
1.18 
Ratio of Effective Shear Stress 
1.16 
1.14 
1.12 
1.10 
1.08 
1.06 
1.04 
1.02 
1.00 
0.98 
0 100 200 300 400 500 600 
Time (year) 
Appendix A-1, file Thermal curve V1.xls 
Figure D-5. Function of the Additional Shear Stress Due to Thermal Loading 
Numerical analysis made for the in situ stress state give a range of effective shear stresses 
(t -sn tanf) that range from 0.04 to 0.06 MPa. Calculations were made with effective shear 
stresses of 0.04, 0.0425, 0.045, 0.0475, 0.05, 0.0525, 0.055, 0.0575, and 0.06 MPa, and the 
results were averaged. This approach results in a stepped cohesion reduction over time as shown 
in Figure D-6. 
D6. ANALYSIS RESULTS 
The prediction of key blocks forming at the emplacement drifts located in the Tptpmn unit is 
presented in this section. The results are presented for both a static key-block assessment and a 
quasi-static key-block assessment to account for seismic, thermal, and time effects on key-block 
development. 
In the DRKBA analysis, random joint patterns are generated with joint centers positioned in 
three-dimensional space, considering each joint set in sequence for each Monte Carlo simulation. 
The forming of key blocks is therefore different in each Monte Carlo simulation. Test runs were 
conducted to determine an adequate number of Monte Carlo simulations for the analyses as 
described in Section D8. Based on the test run results, 400 Monte Carlo simulations are 
adequate for the Tptpmn unit. 
The method used for the quasi-static analysis to simulate the seismic effect is described in 
Section D4. Two levels of earthquake representing a 1,000-year event (110-3) and a 10,000 
year event (110-4) are considered. An emplacement drift orientation with an azimuth of 75 is 
the primary orientation for the quasi-static analysis. The inputs and outputs related to the 
quasi-static analysis are listed in Table A-1. 
ANL-EBS-MD-000027 REV 03 D-11 September 2004 

Drift Degradation Analysis 
Cohesion (Pa) 
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0 
0 2000 4000 6000 8000 10000 
Time (yr) 
Source: Table A-1, file Cohesion Degradation V1.xls. 
Figure D-6. Degradation of Joint Cohesion with Respect to Time 
Figure D-7 presents the key-block size distribution for a 5.5 m diameter emplacement drift with a 
75-drift orientation. The cumulative frequency of occurrence corresponding to 50, 75, 90, 95, 
and 98 percentile block volume for each unit is listed in Table D-4. The maximum block size 
predicted from the analyses is included in this table. Additional details for the calculation of 
block size distribution data based on DRKBA output data are provided in Section D11. 
The predicted number of key blocks per unit length of drift is listed in Table D-5. The results 
show that there is an insignificant impact for a 1,000-year event earthquake (110-3) on the 
number of rockfalls, and only a minor impact for a 10,000-year event (110-4). 
Table D-4. Block Volume Corresponding to Various Levels of Predicted Cumulative Frequency of 
Occurrence, 75-Azimuth Emplacement Drift in Tptpmn Unit, with Seismic Consideration 
Cumulative Frequency of 
Occurrence (%) Static 
Static Plus Seismic (m3) 
1000-Year (110-3) 10,000-Year (110-4) 
50% 0.04 0.04 0.04 
75% 0.21 0.21 0.24 
90% 0.55 0.55 0.67 
95% 1.06 1.35 1.51 
98% 1.85 2.31 2.99 
maximum 14.29 14.29 14.29 
Source: Table A-1, file: tpmn seismic 75 res v2.xls.
NOTE: in cubic meters. 
ANL-EBS-MD-000027 REV 03 D-12 September 2004 

Drift Degradation Analysis 
0% 
lie 
ic 
iiiiANL-EBS-MD-000027 REV 03 D-13 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Cumuatve Frequency of OccurrencStat1e-3 Sesmc Event 
1e-4 Sesmc Event 
September 2004 
0.01 
0.1 1 10 100 
Block Volume (m3) 
Source: Table A-1, file: tpmn seismic 75 res v2.xls. 
Figure D-7. Cumulative Key-block Size Distribution for Seismic Consideration in the Tptpmn Unit, 75-Azimuth 

Drift Degradation Analysis 
Table D-5. Predicted Number of Key Blocks per Unit Length (km) Along 75-Azimuth Emplacement Drift, 
with Seismic Consideration 
Lithologic Unit Static 
Static Plus Seismic 
1000-Year (110-3) 10,000-Year (110-4) 
Tptpmn 50 51 55 
Source: Table A-1, file: tpmn seismic 75 res v2.xls. 
D7. CALCULATION EXAMPLE FOR JOINT PARAMETERS USED 
IN DRKBA ANALYSIS (TPTPMN, JOINT SET 1) 
An example is provided in this appendix to describe the process of calculating the required joint 
geometrical parameters. These parameters include the concentration factor k of a bipolar Watson 
distribution for joint set orientation and a, b, p, and q parameters of the beta distribution for joint 
radii, spacings, and positioning. The first joint set identified in the Tptpmn unit is used as the 
example. 
The joint spacing, radii (two times the mapped trace lengths), and positioning (offset) were first 
sorted in the fracture database. Parameters a and b represent the ends of the closed interval upon 
which the beta distribution is defined. The smallest and largest joint parameters observed were 
assigned as a and b parameters. The values of p and q were calculated based on the technique 
presented by Derman et al. (1973 [DIRS 108444], pp. 398 to 403). In order to determine p and 
q, the joint data were transformed to the unit interval [0,1] by interpolation between the smallest 
and largest values encountered. The parameters p and q were then calculated from the mean and 
standard deviation of the transformed data by means of the following equations: 
p =  [ (1-) / s2  1 ] (Eq. D-20) 
q = (1-) [ (1-) / s2  1 ] (Eq. D-21) 
where  is the mean of the transformed data and s2 is the variance of the transformed data. The 
calculations are included in Table D-6. 
To calculate the concentration factor, the orientation matrix of the joint data has to be first 
determined (Fisher et al. 1987 [DIRS 108447], pp. 33, 175, and 176). The orientation matrix T 
is defined in the following: 
2
.. xi . y x . z x i . 
.
ii i 
2
T= .. y x . y . z y 
. (Eq. D-22) 
iii ii . 
.
.. z x i . z y . zi 
2 
.
. 
i ii 
where (xi, yi, zi) is the unit normal vector of a joint plane and i ranges from 1 to n (the number of 
fractures collected in the joint sets). The components of the orientation matrix are calculated in 
Table D-7. 
ANL-EBS-MD-000027 REV 03 D-14 September 2004 

Drift Degradation Analysis 
Table D-6. Calculation of the a, b, p, and q Parameters for Joint Spacing, Radii, and Positioning 
Joint Set #1 Dip= 84 Dip Direction = 221 
Sorted Joint 
Spacing (m)
Sorted Trace 
Length (m) 
Joint Offset 
(m)
Joint Offset 
(all positive, 
m)
Sorted Joint 
Offset (m)
Joint Radius 
(m)
Transformed 
Spacing 
Transformed 
Radius 
Transformed 
Offset 
13.92 54.00 -0.65 0.65 9.15 108.00 1.0000 1.0000 1.0000 
13.60 25.54 -0.04 0.04 9.15 51.08 0.9773 0.4639 1.0000 
12.44 23.16 -1.30 1.30 9.15 46.32 0.8938 0.4191 1.0000 
12.40 22.85 0.11 0.11 9.15 45.70 0.8910 0.4133 1.0000 
11.22 20.74 0.02 0.02 8.87 41.48 0.8063 0.3735 0.9694 
11.02 17.90 0.21 0.21 8.34 35.80 0.7915 0.3200 0.9115 
10.73 17.70 0.11 0.11 8.05 35.40 0.7707 0.3163 0.8798 
10.14 17.32 0.78 0.78 7.49 34.64 0.7284 0.3091 0.8186 
9.97 17.17 -0.37 0.37 7.38 34.34 0.7163 0.3063 0.8060 
9.81 17.02 0.41 0.41 6.90 34.04 0.7046 0.3034 0.7536 
9.79 17.00 -0.85 0.85 6.50 34.00 0.7035 0.3031 0.7104 
9.71 16.71 -0.72 0.72 6.48 33.42 0.6979 0.2976 0.7077 
9.43 15.60 -0.01 0.01 6.42 31.20 0.6776 0.2767 0.7011 
9.10 15.60 0.36 0.36 6.15 31.20 0.6538 0.2767 0.6721 
8.97 15.25 -0.16 0.16 5.98 30.50 0.6442 0.2701 0.6530 
8.93 14.90 -0.69 0.69 5.65 29.80 0.6416 0.2635 0.6169 
8.87 14.60 -0.64 0.64 5.15 29.20 0.6374 0.2579 0.5628 
8.75 14.21 0.60 0.60 5.00 28.42 0.6283 0.2505 0.5464 
8.64 14.20 -0.26 0.26 4.90 28.40 0.6204 0.2503 0.5355 
8.54 13.42 -0.09 0.09 4.73 26.84 0.6135 0.2356 0.5164 
8.53 13.31 0.12 0.12 4.64 26.62 0.6126 0.2336 0.5071 
8.46 13.05 -0.75 0.75 4.63 26.10 0.6075 0.2287 0.5060 
8.37 12.05 -0.34 0.34 4.60 24.10 0.6013 0.2098 0.5027 
7.99 11.56 -0.73 0.73 4.20 23.12 0.5742 0.2006 0.4590 
7.96 11.52 -0.64 0.64 4.20 23.04 0.5719 0.1998 0.4590 
7.90 10.99 0.36 0.36 4.15 21.98 0.5674 0.1899 0.4530 
7.70 10.91 0.32 0.32 4.06 21.82 0.5533 0.1884 0.4437 
Data truncated  see DTN MO0408MWDDDMIO.002, file: New-Beta-Tptpmn V1.xls, for 
complete data set 
0.00 1.00 4.15 4.15 0.00 2.00 0.0000 0.0017 0.0000 
0.00 1.00 0.02 0.02 0.00 2.00 0.0000 0.0017 0.0000 
0.00 0.94 0.54 0.54 0.00 1.88 0.0000 0.0006 0.0000 
0.91 1.53 1.53 0.00 1.82 0.0000 0.0000 
Mean 0.60 2.54   0.63 5.08 0.0433 0.0307 0.0686 
Standard 
Deviation 1.12 1.94   0.67 3.87 0.0806 0.0365 0.0728 
Minimum (a) 0.00 0.91   0.00 1.82    
Maximum (b) 13.92 54.00   9.15 108.00    
p  0.2322 0.6554 0.7569 
q  5.1372 20.7171 10.2825 
ANL-EBS-MD-000027 REV 03 D-15 September 2004 

Drift Degradation Analysis 
Table D-7. Calculation of the Components for the Orientation Matrix 
Dip Vector Strike Vector Pole VectorStation (m)
AzimuthDipComponent Component Component 
xixi xiyi xizi yiyi yizi zizixd yd zd xs ys zs xi yi zi 
2723.27 129 85 -0.055 -0.068 -0.996 -0.777 0.629 0.000 0.627 0.774 -0.087 0.3930 0.4854 -0.0546 0.5994 -0.0675 0.0076 
2723.85 142 81 -0.123 -0.096 -0.988 -0.616 0.788 0.000 0.778 0.608 -0.156 0.6058 0.4733 -0.1218 0.3698 -0.0951 0.0245 
2730.01 116 81 -0.069 -0.141 -0.988 -0.899 0.438 0.000 0.433 0.888 -0.156 0.1875 0.3844 -0.0677 0.7881 -0.1389 0.0245 
2733.73 124 72 -0.173 -0.256 -0.951 -0.829 0.559 0.000 0.532 0.788 -0.309 0.2828 0.4193 -0.1643 0.6217 -0.2436 0.0955 
2735.12 129 86 -0.044 -0.054 -0.998 -0.777 0.629 0.000 0.628 0.775 -0.070 0.3941 0.4867 -0.0438 0.6010 -0.0541 0.0049 
2735.56 299 84 0.051 0.091 -0.995 0.875 -0.485 0.000 -0.482 -0.870 -0.105 0.2325 0.4194 0.0504 0.7566 0.0909 0.0109 
2736.15 148 83 -0.103 -0.065 -0.993 -0.530 0.848 0.000 0.842 0.526 -0.122 0.7085 0.4427 -0.1026 0.2766 -0.0641 0.0149 
2738.56 141 87 -0.041 -0.033 -0.999 -0.629 0.777 0.000 0.776 0.628 -0.052 0.6023 0.4877 -0.0406 0.3950 -0.0329 0.0027 
2742.16 124 76 -0.135 -0.201 -0.970 -0.829 0.559 0.000 0.543 0.804 -0.242 0.2944 0.4365 -0.1313 0.6471 -0.1946 0.0585 
2742.34 137 79 -0.140 -0.130 -0.982 -0.682 0.731 0.000 0.718 0.669 -0.191 0.5154 0.4806 -0.1370 0.4482 -0.1277 0.0364 
2743.08 119 87 -0.025 -0.046 -0.999 -0.875 0.485 0.000 0.484 0.873 -0.052 0.2344 0.4229 -0.0253 0.7629 -0.0457 0.0027 
2753 115 88 -0.015 -0.032 -0.999 -0.906 0.423 0.000 0.422 0.906 -0.035 0.1784 0.3826 -0.0147 0.8204 -0.0316 0.0012 
2756.75 117 83 -0.055 -0.109 -0.993 -0.891 0.454 0.000 0.451 0.884 -0.122 0.2030 0.3985 -0.0549 0.7821 -0.1078 0.0149 
2759.11 295 75 0.109 0.235 -0.966 0.906 -0.423 0.000 -0.408 -0.875 -0.259 0.1666 0.3574 0.1057 0.7664 0.2266 0.0670 
2762.21 138 90 0.000 0.000 -1.000 -0.669 0.743 0.000 0.743 0.669 0.000 0.5523 0.4973 0.0000 0.4477 0.0000 0.0000 
2767.3 138 72 -0.230 -0.207 -0.951 -0.669 0.743 0.000 0.707 0.636 -0.309 0.4995 0.4498 -0.2184 0.4050 -0.1967 0.0955 
2768.07 118 77 -0.106 -0.199 -0.974 -0.883 0.469 0.000 0.457 0.860 -0.225 0.2093 0.3935 -0.1029 0.7401 -0.1935 0.0506 
2772.04 145 84 -0.086 -0.060 -0.995 -0.574 0.819 0.000 0.815 0.570 -0.105 0.6637 0.4647 -0.0852 0.3254 -0.0596 0.0109 
2774.87 127 76 -0.146 -0.193 -0.970 -0.799 0.602 0.000 0.584 0.775 -0.242 0.3410 0.4525 -0.1413 0.6005 -0.1875 0.0585 
2775.37 138 88 -0.026 -0.023 -0.999 -0.669 0.743 0.000 0.743 0.669 -0.035 0.5516 0.4967 -0.0259 0.4472 -0.0233 0.0012 
2777.34 124 76 -0.135 -0.201 -0.970 -0.829 0.559 0.000 0.543 0.804 -0.242 0.2944 0.4365 -0.1313 0.6471 -0.1946 0.0585 
2777.59 119 82 -0.067 -0.122 -0.990 -0.875 0.485 0.000 0.480 0.866 -0.139 0.2305 0.4158 -0.0668 0.7501 -0.1205 0.0194 
Data truncated  see DTN MO0408MWDDDMIO.002, file: Orient-Tptpmn V1.xls, for complete data set 
1437.69 115 86 -0.029 -0.063 -0.998 -0.906 0.423 0.000 0.422 0.904 -0.070 0.1777 0.3812 -0.0294 0.8174 -0.0631 0.0049 
1440.02 125 86 -0.040 -0.057 -0.998 -0.819 0.574 0.000 0.572 0.817 -0.070 0.3274 0.4676 -0.0399 0.6677 -0.0570 0.0049 
1441.27 128 73 -0.180 -0.230 -0.956 -0.788 0.616 0.000 0.589 0.754 -0.292 0.3466 0.4437 -0.1721 0.5679 -0.2203 0.0855 
1442.28 123 80 -0.095 -0.146 -0.985 -0.839 0.545 0.000 0.536 0.826 -0.174 0.2877 0.4430 -0.0931 0.6822 -0.1434 0.0302 
SUM 2075.5 2290.83 -360.26 2803.2 -402.52 103.36 
ANL-EBS-MD-000027 REV 03 D-16 September 2004 

Drift Degradation Analysis 
The solution for the concentration factor k can be approximated based on the largest eigenvalue 
(t3) of the orientation matrix T (Fisher et al. 1987 [DIRS 108447], pp. 175 and 176). The 
solution is: 
3.75  (3t3  1) if 0.333 < t3 = 0.38 
k = 
3.34  (3t3  1) if 0.38 < t3 = 0.65 
0.7 + 1/(1 - t3) if 0.65 < t3 = 0.99 
1/(1 - t3) if t3 = 0.99 
Calculations of the eigenvalues and k factor were conducted using Mathcad and are presented in 
Table D-8. 
D8. DETERMINATION OF THE NUMBER OF DRKBA MONTE CARLO 
SIMULATIONS 
In the DRKBA analysis, random joint patterns are generated with joint centers positioned in 
three-dimensional space, considering each joint set in sequence for each Monte Carlo simulation. 
The forming of key blocks is therefore different in each Monte Carlo simulation. To determine 
the adequate number of Monte Carlo simulations for the analyses, test runs were first conducted. 
The criteria used to determine the adequate number of Monte Carlo simulations include: 
(1) consistent prediction of the block size distribution, (2) consistent prediction of the number of 
blocks per 10 simulations, and (3) consistent prediction of the maximum block size. 
For the Tptpmn unit, test runs with 100, 200, 400, 600, and 800 Monte Carlo simulations were 
conducted. Figure D-8 shows the block size distribution curves for the five cases. The 
prediction of block size distribution for 200 simulations is similar to the results from 
400 simulations. The predicted numbers of blocks per 10 simulations for the five cases are 
presented in Figure D-9. The results show that the number of blocks increases with the number 
of simulations until 400 simulations is reached. For 400 simulations or higher, the predicted 
numbers of blocks per 10 simulations converges to about 12 and remains fairly constant. The 
maximum block sizes predicted for the five cases are shown in Figure D-10. The maximum 
blocks predicted for 400, 600, and 800 simulations are identical. It was determined that 
400 simulations are adequate for the DRKBA analyses for Tptpmn unit. 
ANL-EBS-MD-000027 REV 03 D-17 September 2004 

Drift Degradation Analysis 
Table D-8. Calculation of the Concentration Factor k for Joint Orientation 
k 31.586=
k 0.333 t3<0.38=if 
k2 0.38 t3<0.65=if 
k3 0.65 t3<0.99=if 
k4 t3 0.99=if 
:=
k4 
1 
1 t3-():=k3 0.7 
1 
1 t3-()+:=
k2 t3 1-():=k1 t3 1-():=
t3 ():=cn 
0.024 
7.942 10 3-
0.968 
.....
.
.
.
=cn 
c 
n 
:=
n c0 c1+c2+:=
c 
121.739 
39.566 
4.821 103
.....
.
.
.
=c ():=
T 
xx 
xy 
xz 
xy 
yy 
yz 
xz 
yz 
zz 
....
.
.
:=
zz 103.3607:=
yz 402.518yy 2803.184:=
xz 360.263xy 2290.832:=
xx 2075.455:=
Tptpmn, Joint Set 1 
Concentration Factor (k) Calculation for Watson Bipolar Distribution: 
(xx, xy,xz,yy,yz,zz calculated in EXCEL worksheet 
) 
k1 
3.34 3 3.75 3 
max cneigenvals T-:=
-:=
Orient-Tptpmn V1.xls
NOTE: New-K-Tptpmn V2.mcd. 
ANL-EBS-MD-000027 REV 03 D-18 September 2004 

Drift Degradation Analysis 
0% 
1 10 
l () 
lie 
20% 
40% 
60% 
80% 
100% 
0.01 0.1 100 
Block Voumem^3Cumuatve Frequency of Occurrencmcs 100 
mcs 200 
mcs 400 
mcs 600 
mcs 800 
Tptpmn 
Figure D-8. Block Size Distributions for the Test Runs, Tptpmn Unit 
li0 
2 
4 
6 
8 
10 
12 
14 
0 
ili) 
ilDRKBA Resuts, Tptpmn, 75 degree azmuth 
100 200 300 400 500 600 700 800 900 
Number of Monte Carlo Smuaton (mcsPredcted Number of Bocks per 10 mcs 
Figure D-9. Predicted Number of Key Blocks Per 10 Monte Carlo Simulations, Tptpmn Unit 
ANL-EBS-MD-000027 REV 03 D-19 September 2004 

Drift Degradation Analysis 
DRKBA Results, Tptpmn, 75 degree azimuth 
16 
Block Size (cubic meter) 
14 
12 
10 
8 
6 
4 
2 
0 
mcs 100 mcs 200 mcs 400 mcs 600 mcs 800 
Number of Monte Carlo Simulation (mcs) 
Figure D-10. Predicted Number of Maximum Block Size, Tptpmn Unit 
D9. ASSESSMENT OF JOINT PLANE REPRESENTATION IN THE DRKBA 
ROCKFALL MODEL 
This section presents the results of a sensitivity calculation for the extent of the modeled joint 
plane based on the mapped joint trace length. It is recognized that the actual extent of a joint 
plane cannot be fully known based on field mapping data. The mapped trace length of a joint 
represents some portion of the overall joint plane. Under representing the extent of the joint 
plane would not be conservative in a key-block analysis. Since the underrepresented joint planes 
may not extent or connect to adjacent joint planes, under representation would limit the number 
of blocks otherwise generated in the model. Conversely, overstating the extent of the joint plane 
would increase connectivity among joint planes, thus creating more blocks in the model and 
resulting in an increased, or conservative, estimate of block development. However, infinite 
joint planes would not be an accurate representation of the jointed rock mass. This appendix 
develops the basis to sufficiently model the extent of the joint plane based on the available field 
data. 
Joint planes are represented as circular discs in the DRKBA rockfall model with the radius of the 
joint plane equal to twice the mapped trace length. Figure D-11 shows a top view of a circular 
fracture disc intersecting an opening. Figure D-11 depicts three parameters used for the 
sensitivity calculation, including joint trace length (T), joint radius (R), and the shortest distance 
(Z) from the center of the joint disc to the fracture trace. 
50 percentile block 
75 percentile block 
90 percentile block 
95 percentile block 
98 percentile block 
maximum block 
ANL-EBS-MD-000027 REV 03 D-20 September 2004 

Drift Degradation Analysis 
Ciisc 
R 
Z 
Tlrcular Fracture DRock Mass 
Trace Pane 
Opening 
R: radius of the circular fracture disc; 
T: trace length of the mapped fracture; 
Z: shortest distance from center of the 
disc to the fracture trace 
Figure D-11. Top View of a Circular Fracture Disc Intersecting an Opening 
The multiplier, M, is used to obtain the radius of the circular fracture disc from the trace length, 
such that the radius parameter, R, as depicted in Figure D-11, is defined as: 
R =M * T (Eq. D-23) 
Based on standard trigonometric relationships for triangles, the shortest distance from the center 
of the disc to the fracture trace can be derived as follows: 
Z = (R2 - (T /2)2)1/ 2 = (M 2 -1/4)1/ 2 *T (Eq. D-24) 
It is reasoned that the location where the circular disc intersects the opening (i.e., the intersection 
point of line Z and trace T) is uniformly distributed at any point from the center of disc to the 
periphery of the disc. In other words, the opening can be located with equal probability to intersect 
any points of the disc. Therefore, the probability for the radius of the disc to be larger than the 
value derived from Equation D-14 can be simply expressed as a function of Z/R, such that: 
1/ 2/ M
P =%100 - Z / R = %100 - (M 2 -1/ 4) (Eq. D-25) 
where P is the probability that R > M  T. 
The probabilities for various multipliers, M, are listed in Table D-9. For a circular joint plane 
described using a radius equal to twice the mapped trace length (i.e., M=2) as used in this 
analysis, there is an approximate 3 percent probability that the actual joint radius is greater than 
the modeled value. Therefore, the use of a multiplier, M, of 2 in this analysis is conservative. 
Table D-9. Probability of R>MT for Various Multipliers 
Multiplier (M) 0.5 0.6 0.7 0.8 1 1.5 2 3 5 
Probability of 
R>MxT 100.0% 44.7% 30.0% 21.9% 13.4% 5.7% 3.2% 1.4% 0.5% 
ANL-EBS-MD-000027 REV 03 D-21 September 2004 

Drift Degradation Analysis 
D10. CALCULATION OF THE PLANE EQUATIONS TO DESCRIBE THE 
EXCAVATION OPENING AS INPUT TO DRKBA 
The method employed by the DRKBA code to represent excavation openings involves 
specification of sets of infinite planes that approximate the opening geometry. The infinite 
planes are defined using unit normal vectors and the shortest distance from the origin. For a 
circular opening without backfill (exca vectors V2.xls), a total of 20 planes were used to 
represent an 80-ft long cylinder as shown in Figure D-12. 
Inputs for the calculation include the azimuth of tunnel axis (Cell D1, exca vectors V2.xls) and 
angle measured from horizontal axis for each plane (Cells P5 to P22, exca vectors V2.xls). 
The equations for the rotation of unit vectors and axes presented in Fisher et al. (1987 
[DIRS 108447], p. 32) were used to calculate the unit normal vector for each plane. The rotation 
matrix A is shown below: 
.
cos cos 
sin 
f
.
cos sin 
cos 
f
.
.
a11 a12 a13
-
sin
...
.
...
.
...
.
.....
cos 
,
A(f . )
=
f
f
2122 23
-
0 
(Eq. D-26) 
a 
a 
a
=
sin
f.
cos
f.
sin
3132 33 
sin
a 
a 
a
.
.
.
where (., f) are the polar coordinates of a unit vector measured relative to a pole in the direction 
(0,0). The rotation of the tunnel axis sets f equal to the azimuth and . as 0. Cells contained in 
Columns F to N are the elements of the rotation matrix. Calculation of the unit vector of the 
infinite plane on the local coordinate (coordinate axes shown in Figure D-12) is based on the 
following equation: 
a
sini 
0
...
.
....
...
.
...
.
x 
y 
(Eq. D-27) 
u
=
=
i 
.a
cos i
z
.
.
.
The x, y, and z components of the unit vector are calculated in Columns Q to S. Finally, the 
rotated unit normal vector on the global coordinate (East as x axis and North as y axis) are 
computed using the equation 
x'
...
.
...
. 
...
. 
...
.
x 
y
A(f 
.)
,
' 
(Eq. D-28) 
y
=
z' 
z
.
.
.
.
The x, y, and z components are calculated in Columns U to W. The last two rows in 
Columns U to W are for the end plane (shown in Figure D-12). The end plane normal vector is 
in the horizontal direction with x equal to sinf and y equal to cosf. 
ANL-EBS-MD-000027 REV 03 D-22 September 2004 

Drift Degradation Analysis 
X 
Y Z 
Pl (
Pl (
Cross Section A 
ane 19end plane) 
ane 20end plane) 
Plane 5 
PlPlPlPlPlX 
Z 
Plane 1 
ane 2 
Plane 3 
Plane 4 Plane 6 
ane 7 
Plane 8 
Plane 9 
Plane 10 
Plane 11 
ane 12 
Plane 13 
ane 14 
Plane 15 
Plane 16 
ane 17 
Plane 18 
Cross Section A 
Figure D-12. Opening Representation - No Backfill 
ANL-EBS-MD-000027 REV 03 D-23 September 2004 

Drift Degradation Analysis 
D11. CALCULATION OF KEY-BLOCK SIZE DISTRIBUTION 
The key-block output files *.bsd (DTN: MO0408MWDDDMIO.002) from DRKBA contain the 
information on key-block size distribution in a histogram format which provides the number of 
blocks in each bin the user specified in the DRKBA input files. Two spreadsheet files (files 
tpmn seismic 75 res v2.xls and small scale fractures results.xls, 
DTN: MO0408MWDDDMIO.002) were generated to provide the key-block distribution in 
cumulative frequency of occurrence format presented in Sections D6 and 6.3.3. 
There are three calculation worksheets contained in each of the two spreadsheet files. The 
worksheets are entitled results, cum, and percentile. The first worksheet results 
includes the imported block size data from DRKBA output files and the calculated percentage 
results within each block size bin. The second worksheet cum calculates the cumulative 
percentage corresponding to the various block sizes. The third worksheet percentile provides 
the results for the 50 percentile, 75 percentile, 90 percentile, 95 percentile, 98 percentile, and 
maximum size blocks. 
Column A of the results worksheet lists the bin value for the block volume in cubic meters. 
These values are the converted values from the English unit outputs of DRKBA. The number of 
blocks predicted in DRKBA for each block volume bin is listed in the columns of the results 
worksheet identified in Table D-10. The values are imported from the *.bsd output files of the 
DRKBA analysis. The total number of blocks was calculated in Row 6 using the Microsoft 
Excel sum function for each case. The percentage columns adjacent to the input block number 
columns listed in Table D-10 were then calculated using the individual block number in each bin 
and the total number of blocks. The values in the percentage columns represent the probabilistic 
density of rockfall within each block size bin. 
Table D-10. Structure of Spreadsheet Files for Key-Block Size Distribution 
File 
Column 
B D F 
tpmn seismic 75 res v2.xls Static Seismic Level 110-3 Seismic Level 110-4 
small scale fractures results.xls Without Small-Scale With Small-Scale Not applicable 
Worksheet cum was constructed from worksheet results by changing the columns identified 
in Table D-10 from number of blocks to cumulative number of blocks. The iterative formula to 
calculate the cumulative number of block is given below: 
CNBi = CNBi-1 + NBI (Eq. D-29) 
where CNBi = the cumulative number of block at block size bin i 
CNBi-1 = the cumulative number of block at block size bin i-1 
NBi = the number of block at block size bin i. 
ANL-EBS-MD-000027 REV 03 D-24 September 2004 

Drift Degradation Analysis 
The cumulative percentage was then obtained from the cumulative number of blocks and the 
total number of blocks. Same as in worksheet results, the total number of blocks is recorded in 
Row 6. 
In order to locate the 50 percentile, 75 percentile, 90 percentile, 95 percentile, 98 percentile, and 
maximum size blocks efficiently, the Microsoft Excel vlookup function was used in worksheet 
percentile. Cells C8 to G2509 for file tpmn seismic 75 res v2.xls and cells C8 to E2509 for 
small scale fractures results.xls were set up as the table_array for the vlookup function. 
The cumulative percentage values in these cells are the replicate of cells in the worksheet cum. 
The block sizes are expressed in cubic feet in the table_array. The blocks for the cumulative 
frequency of occurrence at 50, 75, 90, 95, and 98 percent, and the maximum blocks (in cubic 
feet) are calculated in Cells C2517 to E2522 for file tpmn seismic 75 res v2.xls and Cells L5 to 
O10 for file small scale fractures results.xls. The block sizes were converted to cubic meter in 
Cells C2526 to E2531 for file tpmn seismic 75 res v2.xls and Cells Q5 to T10 for file small scale 
fractures results.xls. 
The number of blocks per kilometer is calculated by dividing the total number of key blocks by 
the total simulated length. The total simulated length is determined as the number of simulations 
(i.e., 400 simulations) times the length of simulation (e.g., 80 ft/simulation  0.0348 m/ft  
0.001 km/m). 
ANL-EBS-MD-000027 REV 03 D-25 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 D-26 September 2004 

Drift Degradation Analysis 
APPENDIX E 
CALCULATION OF ROCK PROPERTIES
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
CALCULATION OF ROCK PROPERTIES
This appendix documents the calculation of rock property values based on source data provided 
in the TDMS. The rock properties include density, joint strength properties, intact rock 
properties, rock mass strength properties, and thermal properties. The use of these properties in 
this analysis is described in Section 4.1. 
E1. ROCK DENSITY 
The rock densities used in the thermal mechanical calculation of stresses at Yucca Mountain due 
to heating and cooling of the repository (Section 6.2) are provided in Table E-1. These data 
include dry bulk density values for the various lithostratigraphic and thermal-mechanical units of 
the Yucca Mountain rock strata. The mean values for thermal-mechanical units are determined 
by averaging the densities of the lithostratigraphic units within each thermal-mechanical unit, 
weighted according to the thickness of each lithostratigraphic unit. Additional details are 
provided in the Microsoft Excel file thermal properties TM units v2.xls (Table A-1). 
For conservatism, saturated bulk density data from the Tptpln unit have been used in rockfall 
modeling (see Section 4.1.3). The saturated bulk density data are provided in Table E-2. The 
mean density value for these data is 2410 kg/m3. 
E2. JOINT STRENGTH PROPERTIES 
Data from rotary shear stress experiments using core from the nonlithophysal units (i.e., Tptpmn 
and Tptpln) are provided in Table E-3. These data include pairs of normal stress (s) and shear 
stress (tp) values determined from shear testing of various core specimens. The data pairs were 
plotted (Figure E-1) and a linear fit of the data was determined. The calculation of the linear fit 
is documented in Microsoft Excel file joint strength v2.xls (Table A-1). The equation for the 
linear fit is: 
tp = tanfj s + Cj (Eq. E-1) 
where tp = peak shear stress (MPa), 
tanfj = coefficient of friction, 
fj = joint friction angle (degree), 
s = normal stress (MPa), and 
Cj = joint cohesion (MPa). 
Based on this linear fit, the following joint strength parameters were determined: 
 Joint cohesion = 0.6 MPa 
 Coefficient of friction = 0.90 
 Joint friction angle = 42. 
ANL-EBS-MD-000027 REV 03 E-1 September 2004 

Drift Degradation Analysis 
Table E-1. Density Data for Various Thermal Mechanical Units and Associated Lithostratigraphic Units 
Thermal Mechanical 
Unit Stratigraphic Unit Thicknessa (m) 
Dry Bulk Density 
(kg/m3) DTNb 
Tpcpv3 0.0 2310 
SN0303T0503102.008 
[DIRS 162401] 
Tpcpv2 5.1 1460 
Tpcpv1 2.4 1460 
Tpbt4 0.5 1460 
Tpy 3.8 1460 
TCw / PTn Tpbt3 3.8 1460 
Tpp 5.1 1460 
Tpbt2 8.3 1460 
Tptrv3 1.9 1460 
Tptrv2 1.2 1460 
Mean (weighted by unit thickness) 1460 
Tptrv1 1.2 2310 
Tptrn 35.6 2190 
TSw1 Tptrl 6.1 2190 
Tptpul 66.8 1834 
SN0404T0503102.011 
[DIRS 169129] 
Mean (weighted by unit thickness) 1974 
Tptpmn 38.3 2148 
Tptpll 95.6 1979 
TSw2 / TSw3 Tptpln 55.1 2211 
Tptpv3 12.0 2310 
SN0303T0503102.008 
[DIRS 162401] 
Mean (weighted by unit thickness) 2095 
Tptpv2 4.7 1460 
Tptpv1 15.4 1460 
CHn1 / CHn2 
Tpbt1 2.0 1460 
Calico 45.5 1670 
Calicobt 15.9 1670 
Mean (weighted by unit thickness) 1614 
a 
Thickness of units extracted from DTN: MO0012MWDGFM02.002 [DIRS 153777]. The details of this extraction 
b 
are provided in Appendix M. 
Mean values are calcu
lated in this report and not provided by the DTNs listed in this table. Data extracted from 
DTN: SN0404T0503102.11 [DIRS 169129] are summarized in BSC 2004 [DIRS 169854], Table 7-10. Data 
extracted from DTN: SN0303T0503102.008 [DIRS 162401] are summarized in BSC 2004 [DIRS 170033], 
Table 6-13. 
ANL-EBS-MD-000027 REV 03 E-2 September 2004 

Drift Degradation Analysis 
Table E-2. Density Data from the Tptpln Unit 
Borehole Sample Number Saturated Bulk Density (kg/m3) 
NRG-7a NRG-7a-1230.2-SNL 2395 
NRG-7a NRG-7a-1236.7-SNL 2393 
NRG-7a NRG-7a-1252.3-SNL 2369 
NRG-7a NRG-7a-1257.8-SNL 2421 
NRG-7a NRG-7a-1259.1-SNL 2420 
NRG-7a NRG-7a-1265.2-SNL 2426 
NRG-7a NRG-7a-1314.8-SNL 2418 
NRG-7a NRG-7a-1399.1-A-SNL 2409 
NRG-7a NRG-7a-1400.5-B-SNL 2428 
NRG-7a NRG-7a-1230.2-SNL 2339 
NRG-7a NRG-7a-1263.7-SNL 2416 
NRG-7a NRG-7a-1263.7-SNL 2396 
NRG-7a NRG-7a-1263.7-SNL 2421 
NRG-7a NRG-7a-1307.0-SNL 2414 
NRG-7a NRG-7a-1307.0-SNL 2411 
NRG-7a NRG-7a-1348.8-SNL 2440 
NRG-7a NRG-7a-1348.8-SNL 2424 
NRG-7a NRG-7a-1353.7-SNL 2388 
NRG-7a NRG-7a-1363.5-SNL 2442 
NRG-7a NRG-7a-1385.0-SNL 2424 
NRG-7a NRG-7a-1385.0-SNL 2419 
NRG-7a NRG-7a-1402.7-SNL 2358 
NRG-7a NRG-7a-1409.0-SNL 2450 
SD-12 SD-12-1073.3-SNL 2415 
SD-12 SD-12-1077.1-SNL 2426 
SD-12 SD-12-1107.1-SNL 2416 
SD-12 SD-12-1112.1-SNL 2400 
SD-12 SD-12-1118.9-SNL 2372 
SD-12 SD-12-1209.0-SNL 2423 
SD-9 NRG-SD-9-1243-SNL 2418 
SD-9 NRG-SD-9-1298-SNL 2439 
SD-9 NRG-SD-9-1346.5-SNL 2419 
Mean Density Value 2411 
Source: DTN: SNL02030193001.027 [DIRS 108410]. 
ANL-EBS-MD-000027 REV 03 E-3 September 2004 

Drift Degradation Analysis 
Table E-3. Data from Shear Stress Experiments on Natural Fractures from the Nonlithophysal Units of 
the Repository Horizon 
Source DTN 
SpecimenNumber (alsoreferred to as 
Sample Number)
LithostratigraphicUnitNormal Stress, 
s (MPa)
Peak Shear 
Stress, tp (MPa) 
Joint Dilation 
(deg) 
Source Reports a 
SNL02112293001.003 
[DIRS 108412] NRG-6-782.3-782.6-SNL Tptpmn 2.5 1.9 1.1 Olsson and Brown 1997 
[DIRS 106453] (Table 1) 
SNL02112293001.005 
[DIRS 108413] 
SD-9-1254.7-1255.2-A Tptpln 10.0 7.7 33.4 
SNL1996 [DIRS 165408] 
(Tables 1 and 3) SD-9-1255.9-1256.3 Tptpln 2.5 2.4 8.5 
SD-9-1254.7-1255.2-B Tptpln 10.0 9.0 18.4 
SD-12-688.4-688.7 Tptpmn 2.5 3.6 14.2 
SNL 1996 
[DIRS 165410] (Tables 1 
and 3) 
SNL02112293001.007 SD-12-1072.5-1073.0-A Tptpln 2.5 3.3 13.7 
[DIRS 108414] SD-12-1072.5-1073.0-B Tptpln 5.0 6.6 15.1 
SD-12-778.1-780.0 Tptpmn 10.0 12.0 17.7 
a 
Data can be accessed through the source reports available via Records Processing Center Packages linked to the 
Source DTN. 
15 
10 
5 
0 
0246 81012 
Normal Stress, s (MPa) 
) 
() 
iiiitpsftpsftpsfPeak Shear Stress Data (MPaMean Peak Shear Stress at Normal Stress LevelMPa
 1 Standard Devation Error Bars 
Linear Ft of  1 Standard Devation 
Linear Ft of Mean Peak Shear Stress Data 
= 0.90 + 0.56 
C = 0.6 MPa 
= 42  
= 0.71 + 0.24 
C = 0.2 MPa 
= 35  
= 1.09 + 0.88 
C = 0.9 MPa 
= 47  
Source: Data provided in Table E-3. 
Figure E-1. Plot of Shear Strength Test Data from the TSw2 Thermal Mechanical Unit 
Peak Shear Stress, tp (MPa) 
ANL-EBS-MD-000027 REV 03 E-4 September 2004 

Drift Degradation Analysis 
To determine the range of the joint strength parameters (cohesion and friction angle), a statistical 
analysis was conducted as documented in file joint strength v2.xls (Table A-1). The mean 
shear stress was calculated at each normal stress level. A linear fit of the  one standard 
deviation about the mean data was used to determine the range of cohesion and friction angle 
(Figure E-1). Cohesion ranges from 0.2 to 0.9 MPa, while friction angle varies from 35 to 47. 
Joint dilation data from rotary shear tests for the nonlithophysal units are presented in Table E-3. 
The mean joint dilation is 15.3 , with a standard deviation of 9.2 . The range of joint stiffness 
data from rotary shear tests is presented in Table E-4 together with the mean values. The joint 
stiffness data presented are consistent with Subsurface Geotechnical Parameters Report (BSC 
2003 [DIRS 166660], Tables 8-50 and 8-51). 
Direct shear test data have recently been collected as documented in the Subsurface 
Geotechnical Parameters Report (BSC 2003 [DIRS 166660], Tables 8-47 and 8-52). For these 
tests, cooling joints have been distinguished from vapor phase partings. Results for cohesion, 
friction angle, dilation, and shear stiffness are shown in Table E-5. With the exception of the 
shear stiffness, the direct shear results (Table E-5) are similar to the rotary shear results 
(Tables E-3, E-4, and Figure E-1). Shear stiffness values determined from the direct shear tests 
are similar to the empirical estimations of joint shear stiffness (Duan 2003 [DIRS 163586], 
Tables 5.2 and 5.3). Normal joint stiffness values from direct shear tests were not available. 
E3. INTACT ROCK PROPERTIES FOR NONLITHOPHYSAL ROCK 
Elastic rock properties data for nonlithophysal rock (i.e., the Tptpmn and Tptpln units), including 
Youngs modulus, E, and Poissons ratio, . , from laboratory tests on core specimens are shown 
in Table E-6. The mean Youngs modulus from this data is 33.6 GPa, and the mean Poissons 
ratio is 0.20. Bulk modulus, K, and shear modulus, G, are calculated as follows (Jaeger and 
Cook 1979 [DIRS 106219], p. 111): 
E
K= (Eq. E-2) 
(1
3 -  2. ) 
E
G= (Eq. E-3) 
(1
2 +  . ) 
Plugging the mean values of E and . into Equations E-2 and E-3 results in a bulk modulus value 
of 18.7 GPa, and a shear modulus value of 14.0 GPa. 
Tensile strength data for the TSw2 unit were obtained from indirect tensile strength tests 
performed by the Brazilian Test method using core specimens as shown in Table E-7. The mean 
tensile strength from this data for the nonlithophysal units is 10.9 MPa for the Tptpmn and 
7.9 MPa for the Tptpln. The lower lithophysal unit (i.e., Tptpll) has a mean tensile strength of 
8.3 MPa. For the small Brazilian test samples, lithophysal cavities are not represented. The 
matrix rock material for the Tptpmn, Tptpll, and Tptpln Brazilian samples is therefore the same, 
and has a mean tensile strength of 8.9 MPa (Table E-7). 
ANL-EBS-MD-000027 REV 03 E-5 September 2004 

Drift Degradation Analysis 
Table E-4. Normal and Shear Stiffness Data from Shear Stress Experiments on Natural Fractures from 
the Nonlithophysal Units of the Repository Horizon a 
Source DTN 
Specimen Number 
(also referred to asSample Number)
LithostratigraphicUnitTest ID 
Tangent Normal 
Stiffness at 5 MPa 
(MPa/mm)
Tangent Shear 
Stiffness (Maximum) 
(MPa/mm) 
Source Reports a 
SNL02112293001.003 
[DIRS 108412] NRG-6-782.3-782.6-SNL Tptpmn YM9 NA 45 
Olsson and Brown 
1997 [DIRS 106453], 
Figure 6 
SNL02112293001.005 
[DIRS 108413] 
SD-9-1254.7-1255.2-A Tptpln YM23 105 100 SNL1996 [DIRS 
165408], p. A-2 
SD-9-1255.9-1256.3 Tptpln YM24 NA 145 SNL1996 [DIRS 
165408], p. A-5 
SD-9-1254.7-1255.2-B Tptpln YM25 115 180 SNL1996 [DIRS 
165408], p. A-8 
SNL02112293001.007 
[DIRS 108414] 
SD-12-688.4-688.7 Tptpmn YM33 NA 45 SNL 1996 [DIRS 
165410], p. A-2 
SD-12-1072.5-1073.0-A Tptpln YM34 NA 23 SNL 1996 [DIRS 
165410], p. A-4 
SD-12-1072.5-1073.0-B Tptpln YM35 90 115 SNL 1996 [DIRS 
165410], p. A-6 
SD-12-778.1-780.0 Tptpmn YM36 65 120 SNL 1996 [DIRS 
165410], p. A-8 
Mean 94 97 
Standard Deviation 22 55 
 
a 
Data can be accessed through the source reports available via Records Processing Center Packages linked to the 
source DTN. 
ANL-EBS-MD-000027 REV 03 E-6 September 2004 

Drift Degradation Analysis 
Table E-5. Summary Statistics of Direct Joint Shear Test Results 
Property Statistic Vapor Phase Parting Cooling Joint 
Joint Cohesion (MPa) 
Mean 0.7 0.0 
Standard Deviation 0.1 0.1 
Minimum 0.7 -0.0 
Maximum 0.8 0.1 
Count 3 2 
Joint Friction Angle 
(degree) 
Mean 44 33 
Standard Deviation 2 0 
Minimum 42 33 
Maximum 46 34 
Count 3 2 
Joint Dilation (degree) 
Mean 14 2 
Standard Deviation 2 4 
Minimum 12 -1 
Maximum 16 4 
Count 3 2 
Joint Shear Stiffness 
(MPa/mm) 
Mean 13 11 
Standard Deviation 6 6 
Minimum 8 7 
Maximum 20 15 
Count 3 2 
Source: BSC 2003 [DIRS 166660], Tables 8-47 and 8-52. 
ANL-EBS-MD-000027 REV 03 E-7 September 2004 

Drift Degradation Analysis 
Table E-6. Elastic Properties Data from the Nonlithophysal Units of the Repository Horizon a 
Litho- Specimen Number (also Youngs 
stratigraphic 
Unit Location 
referred to as Sample 
Number) 
Modulus 
(GPa) 
Poissons 
Ratio Original Source DTN 
10/AE/2/Z 28.7 0.17 
SNSAND85076200.000 
[DIRS 160024] 
10/AE/46/Z 34.2 0.18 
10/AE/9/Z 31.5 0.20 
10-AE-3Y 18.6 0.07 
10-AE-6X 28.6 0.14 
10-AE-8X 21.7 0.11 
10X12 34.6 0.21 
SNSAND85070900.000 
[DIRS 160022] 
10Y47 35.9 0.20 
10Z15 37.4 0.20Busted Butte 
12A2 45.8 0.22 
12A3 44.2 0.21 
13A2 34.9 0.21 
26A1 45.7 0.20 
26B1 34.6 0.21 
26C1 47.3 0.19 
Tptpmn 
26D1 42.5 0.14 
26E1 47.2 0.19 
28A2 34.6 0.20 
USW G-4 
G4-686.6-A 36.2 0.18 
SNSAND84110100.000 
[DIRS 160016] 
G4-686.6-D 40.7 0.17 
G4-686.6-G 33.1 0.21 
G4-742.75-E 35.6 0.21 
G4-742.75-F 36.8 0.21 
G4-742.75-G 34.6 0.21 
G4-748.6-A 32.2 0.16 
G4-748.6-B 32.3 0.21 
G4-749.0-A 33.5 0.29 
G4-749.0-B 34.1 0.27 
USW GU-3 
GU-3 760.9/1A 30.2 0.19 
SNSAND83164600.000 
[DIRS 160009] 
GU-3 760.9/1B 28.6 0.29 
GU-3 760.9/2A 29.0 0.22 
GU-3 760.9/2B 30.2 0.22 
ANL-EBS-MD-000027 REV 03 E-8 September 2004 

Drift Degradation Analysis 
Table E-6. Elastic Properties Data from the Nonlithophysal Units of the Repository Horizon (Continued)a 
Litho- 
stratigraphic 
Unit Location 
Specimen Number (also 
referred to as Sample 
Number) 
Youngs 
Modulus 
(GPa) 
Poissons 
Ratio Original Source DTN 
GU-3 760.9/3A 30.6 0.23 
SNSAND83164600.000 
[DIRS 160009] 
GU-3 760.9/3B 30.8 0.21 
GU-3 760.9/4A 29.3 0.19USW GU-3 
GU-3 760.9/4B 28.1 0.16 
GU-3 760.9/5A 30.7 0.22 
GU-3 760.9/5B 30.0 0.21 
NRG-5-847.2-SNL-A 35.2 0.21 
SNL02030193001.012 
[DIRS 108416] 
NRG-5-849.4-SNL-A 37.0 0.19 
NRG-5-861.2-SNL-A 17.1 0.23 
NRG-5-873.4-SNL-A 13.4 0.30UE-25 NRG #5 
NRG-5-887.2-SNL-A 40.5 0.20 
NRG-5-888.8-SNL-A 39.4 0.19 
NRG-5-891.9-SNL-A 38.3 0.15 
NRG-5-896.5-SNL-A 39.1 0.10 
NRG-6-720.7-SNL-A 37.1 0.19 
SNL02030193001.004 
[DIRS 108415] 
NRG-6-742.3-SNL-A 30.6 0.20 
NRG-6-742.9-SNL-A 32.4 0.22 
NRG-6-762.9-SNL-A 29.2 0.18USW NRG-6 
NRG-6-773.5-SNL-A 36.2 0.23 
Tptpmn NRG-6-784.8-SNL-A 29.7 0.17 
NRG-6-785.6-SNL-A 30.1 0.16 
NRG-6-806.8-SNL-A 31.7 0.16 
NRG-7/7A-777.0-SNL-A 32.9 0.22 
SNL02030193001.019 
[DIRS 108431] 
NRG-7/7A-806.3-SNL-A 36.7 0.19 
NRG-7/7A-818.5-SNL-A 33.1 0.20 
NRG-7/7A-859.2-SNL-A 38.8 0.20USW NRG-7a 
NRG-7/7A-865.4-SNL-I 34.3 0.20 
NRG-7/7A-865.4-SNL-J 33.5 0.19 
NRG-7/7A-865.4-SNL-K 34.9 0.22 
NRG-7/7A-865.4-SNL-L 35.7 0.21 
SD-12-734.7-SNL-B 31.9 0.18 SNL02030193001.023 
[DIRS 108435] USW SD-12 
SD-12-781.1-SNL-B 36.7 0.21 
SD-9-761.5-SNL-A 33.9 0.21 
SNL02030193001.026 
[DIRS 108436] 
SD-9-768.7-SNL-A 36.9 0.20 
SD-9-771.7-SNL-A 34.8 0.19 
USW SD-9 SD-9-774.6-SNL-B 16.8 0.19 
SD-9-826.7-SNL-A 31.9 0.21 
SD-9-832.8-SNL-C 29.8 0.19 
SD-9-842.1-SNL-E-1 36.3 0.20 
Tptpln USW G-4 
G4-1307.2-A 30.2 0.23 SNSAND84110100.000 
[DIRS 160016] G4-1307.2-C 22.8 0.20 
ANL-EBS-MD-000027 REV 03 E-9 September 2004 

Drift Degradation Analysis 
Table E-6. Elastic Properties Data from the Nonlithophysal Units of the Repository Horizon (Continued) a 
Litho- 
stratigraphic 
Unit Location 
Specimen Number (also 
referred to as Sample 
Number) 
Youngs 
Modulus 
(GPa) 
Poissons 
Ratio Original Source DTN 
G4-1307.2-D 20.0 0.30 
Tptpln 
USW G-4 G4-1307.2-E 16.6 0.24 SNSAND84110100.000 
[DIRS 160016] 
G4-1307.2-F 34.9 0.20 
USW GU-3 
GU-3 1050.4/1 35.5 0.18 
SNSAND83164600.000 
[DIRS 160009] 
GU-3 1050.4/2 36.1 0.19 
GU-3 1050.4/3 36.3 0.19 
GU-3 1067.8/3 32.7 0.24 
GU-3 1067.8/4 32.1 0.24 
USW NRG-7a 
NRG-7/7A-1265.2-SNL-A 40.7 0.21 
SNL02030193001.020 
[DIRS 108432] 
NRG-7/7A-1257.8-SNL-A 41.8 0.20 
NRG-7/7A-1259.1-SNL-A 40.6 0.21 
NRG-7/7A-1314.8-SNL-A 37.7 0.21 
NRG-7/7A-1252.3-SNL-A 30.4 0.14 
USW SD-12 
SD-12-1107.1-SNL-B 34.5 0.23 SNL02030193001.023 
[DIRS 108435] SD-12-1209.0-SNL-B 31.9 0.28 
USW SD-9 
SD-9-1243.0-SNL-A 35.9 0.19 
SNL02030193001.026 
[DIRS 108436] SD-9-1298.0-SNL-A 39.9 0.25 
SD-9-1346.5-SNL-A 44.4 0.25 
Mean property values 33.6 0.20  
a 
Elastic properties data are qualified and summarized in DTN: MO0402DQRIRPPR.003 [DIRS 168901]. The data 
can be found by downloading the data file from this DTN, and searching for the data using the Specimen Number. 
The elastic properties data have been selected according to test conditions to provide a consistent data set. Data 
with the following test conditions were selected: ambient temperature conditions, saturated samples, unconfined 
-1
(confining pressure = 0 or 0.1 MPa), nominal strain rate of 10-5 s, with sample diameters ranging from 25.4 to 
50.8 mm. 
Table E-7. Tensile Strength Data from the TSw2 Thermal Mechanical Unit a 
Borehole 
Specimen Number (also 
referred to as Sample 
Number) 
Tensile Strength 
(MPa) Original Source DTN Lithostratigraphic Unit 
NRG-5-788.6-SNL-A 4.3 
SNL02030193001.009 
[DIRS 109614] 
Tptpmn 
NRG-5-832.9-SNL-A 7.7 
NRG-5 
NRG-5-847.2-SNL-B 5.7 
NRG-5-887.2-SNL-B 16.8 
NRG-5-888.8-SNL-B 15.9 
NRG-5-891.9-SNL-B 12.9 
NRG-6-742.3-SNL-B 14.5 
SNL02030193001.004 
[DIRS 108415] 
NRG-6-742.9-SNL-B 13.0 
NRG-6 NRG-6-773.5-SNL-B 7.9 
NRG-6-784.8-SNL-B 12.5 
NRG-6-785.6-SNL-B 14.1 
ANL-EBS-MD-000027 REV 03 E-10 September 2004 

Drift Degradation Analysis 
a
Table E-7. Tensile Strength Data from the TSw2 Thermal Mechanical Unit (Continued)
Borehole 
Specimen Number (also 
referred to as Sample 
Number) 
Tensile 
Strength (MPa) Original Source DTN Lithostratigraphic Unit 
NRG-7a 
NRG-7/7A-762.1-SNL-A 9.3 
SNL02030193001.019 
[DIRS 108431] TptpmnNRG-7/7A-828.4-SNL-A 6.1 
NRG-7/7A-855.0-SNL-A 11.6 
Mean 10.9 
Summary Statistics for Tptpmn 
Count 14 
Standard Deviation 4.0 
Minimum 4.3 
Maximum 16.8 
NRG-6 
NRG-6-848.0-SNL-B 7.9 
SNL02030193001.004 
[DIRS 108415] 
Tptpll 
NRG-6-908.2-SNL-A 8.8 
NRG-6-934.0-SNL-A 10.8 
NRG-6-934.0-SNL-B 4.0 
NRG-6-956.8-SNL-A 5.3 
NRG-6-963.3-SNL-B 3.2 
NRG-6-969.3-SNL-A 7.5 
NRG-6-971.4-SNL-B 11.7 
NRG-7a 
NRG-7/7A-879.2-SNL-A 14.3 
SNL02030193001.019 
[DIRS 108431] NRG-7/7A-879.2-SNL-B 11.0 
NRG-7/7A-881.0-SNL-A 12.1 
NRG-7/7A-958.7-SNL-A 11.2 
SNL02030193001.020 
[DIRS 108432] 
NRG-7/7A-958.7-SNL-B 11.5 
NRG-7/7A-976.4-SNL-A 5.5 
NRG-7/7A-976.4-SNL-B 6.3 
NRG-7/7A-979.6-SNL-A 5.2 
NRG-7/7A-1046.8-SNL-A 6.2 
NRG-7/7A-1090.3-SNL-A 10.4 
NRG-7/7A-1090.3-SNL-B 10.2 
NRG-7/7A-1098.3-SNL-A 6.6 
NRG-7/7A-1129.3-SNL-A 7.0 
NRG-7/7A-1180.0-SNL-A 5.3 
NRG-7/7A-1188.7-SNL-A 8.6 
NRG-7/7A-1230.2-SNL-B 9.2 
Mean 8.3 
Summary Statistics for Tptpll 
Count 24 
Standard Deviation 2.9 
Minimum 3.2 
Maximum 14.3 
NRG-7a 
NRG-7/7A-1263.7-SNL-A 13.7 
SNL02030193001.020 
[DIRS 108432] TptplnNRG-7/7A-1263.7-SNL-B 9.9 
NRG-7/7A-1263.7-SNL-C 9.0 
ANL-EBS-MD-000027 REV 03 E-11 September 2004 

Drift Degradation Analysis 
a
Table E-7. Tensile Strength Data from the TSw2 Thermal Mechanical Unit (Continued)
Borehole 
Specimen Number (also 
referred to as Sample 
Number) 
Tensile 
Strength (MPa) Original Source DTN Lithostratigraphic Unit 
NRG-7a 
NRG-7/7A-1307.0-SNL-A 10.9 
SNL02030193001.020 
[DIRS 108432] TptplnNRG-7/7A-1307.0-SNL-B 8.8 
NRG-7/7A-1348.8-SNL-A 4.8 
NRG-7/7A-1348.8-SNL-B 5.9 
NRG-7/7A-1353.7-SNL-A 7.6 
NRG-7/7A-1363.5-SNL-A 7.6 
NRG-7/7A-1385.0-SNL-A 6.1 
NRG-7/7A-1385.0-SNL-B 6.3 
NRG-7/7A-1402.7-SNL-A 4.8 
NRG-7/7A-1409.0-SNL-A 7.6 
Mean 7.9 
Summary Statistics for Tptpll 
Count 13 
Standard Deviation 2.5 
Minimum 4.8 
Maximum 13.7 
Mean 8.9 
Summary Statistics for TSw2 
Count 51 
Standard Deviation 3.3 
Minimum 3.2 
Maximum 16.8 
a 
Tensile strength data are qualified and summarized in DTN: MO0401DQRIRPTS.003 [DIRS 168905]. 
The tensile strength of intact rock material is typically an order of magnitude lower than its 
compressive strength (compare the mean tensile strength of 10.9 MPa for the Tptpmn unit 
[Table E-7] to the mean compressive strength of 188.8 MPa for the Tptpmn unit [see 
Section E4.2, Table E-14]). The tensile strength of a rock mass is often considered to be zero 
since discontinuities offer little or no resistance to tensile stresses. However, compressive 
stresses are most prevalent in geotechnical problems, so the emphasis in geotechnical design is 
typically placed on the compressive and shear strength of rock (Brady and Brown 1985 
[DIRS 126811], pp. 86-87). 
Triaxial strength data (Table E-8) are used to calculate intact cohesion and friction angle of the 
nonlithophysal rocks. The triaxial data includes sets of confining pressure data paired with the 
corresponding axial stress at failure, as plotted in Figures E-2 and E-3. The Mohr-Coulomb 
approach for calculating cohesion and friction angle is used (Jaeger and Cook 1979 
[DIRS 106219], pp. 87 to 93). A least-square linear fit of the axial stress (s1) and the confining 
ANL-EBS-MD-000027 REV 03 E-12 September 2004 

Drift Degradation Analysis 
pressure (s3) data sets was performed (Figure E-2) and plotted in the form: 
s1 = . s3 + sC (Eq. E-4) 
where s1 = axial stress, or the strength of the rock at failure, 
s3 = confining pressure, 
sC = unconfined compressive strength, 
.= confinement factor. 
The relationship between the linear equation above and the Mohr-Coulomb parameters, cohesion 
(C) and friction angle (f), is given by the following (Jaeger and Cook 1979 [DIRS 106219], 
p. 93): 
t = C + sntanf (Eq. E-5) 
where t = sheer stress, 
C = cohesion, 
sn = normal stress 
f = friction angle. 
Cohesion and friction angle are calculated based on their relationship to N and sc as follows 
(Jaeger and Cook 1979 [DIRS 106219], pp. 88 to 91): 
s
c 
C = 
(Eq. E-6) 
2  N 
f = 2 (tan-1 N  45). (Eq. E-7) 
The calculation of cohesion and friction angle using the approach described above is documented 
in Microsoft Excel file, intact strength nonlith v2.xls (Table A-1), resulting in a mean cohesion 
of 36 MPa and a friction angle of 50 for the Tptpmn unit from borehole samples located near 
the ESF (Table E-8). The mean value of cohesion and friction angle is within the range of the 
values provided in the Subsurface Geotechnical Parameters Report (BSC 2003 
[DIRS 166660], Table 8-40). 
To evaluate the range of the intact strength parameters, cohesion and friction angle, using the 
data from Table E-8, a statistical analysis was conducted as documented in Table A-1, file: intact 
strength nonlith v2.xls. The mean axial stress was calculated at each confining stress level. A 
linear fit of the  one standard deviation about the mean data was used to determine the range of 
cohesion and friction angle. Cohesion ranges from 32 to 40 MPa, while friction angle varies 
from 41 to 56 (Figure E-2). 
ANL-EBS-MD-000027 REV 03 E-13 September 2004 

Drift Degradation Analysis 
Table E-8. Uniaxial and Triaxial Test Data from the Tptpmn Lithostratigraphic Unit a 
Location 
Specimen Number (also 
referred to as Sample 
Number) 
Confining 
Pressure, 
s3 (MPa)
UltimateDifferentialStrength (also 
referred to as 
Compressive 
Strength) (MPa) 
Axial Stress b , 
s1 (MPa) 
Original Source DTN 
GU-3 760.9-1A 0 210.3 210.3 
SNSAND83164600.000 
[DIRS 160009] 
GU-3 760.9-1B 0 234.4 234.4 
GU-3 760.9-2A 0 215.5 215.5 
GU-3 760.9-3A 0 245.2 245.2 
USW GU-3 GU-3 760.9-5A 0 229.7 229.7 
GU-3 760.9-5B 0 226.4 226.4 
GU-3 760.9-2B 0 221.4 221.4 
GU-3 760.9-3B 0 222.2 222.2 
GU-3 760.9-4A 0 205.2 205.2 
GU-3 760.9-4B 0 183.5 183.5 
NRG-5-847.2-SNL-A 0 84.2 84.2 
SNL02030193001.012 
[DIRS 108416] 
NRG-5-849.4-SNL-A 0 240.8 240.8 
NRG-5-861.2-SNL-A 0 55.3 55.3 
UE-25 NRG #5 NRG-5-873.4-SNL-A 0 38.4 38.4 
NRG-5-887.2-SNL-A 0 240.9 240.9 
NRG-5-888.8-SNL-A 0 288.9 288.9 
NRG-5-891.9-SNL-A 0 253.5 253.5 
NRG-5-896.5-SNL-A 0 184.7 184.7 
NRG-6-720.7-SNL-A 0 235.5 235.5 
SNL02030193001.004 
[DIRS 108415] 
NRG-6-742.3-SNL-A 0 162.3 162.3 
NRG-6-742.9-SNL-A 0 212.8 212.8 
USW NRG-6 NRG-6-762.9-SNL-A 0 112.1 112.1 
NRG-6-773.5-SNL-A 0 117.4 117.4 
NRG-6-784.8-SNL-A 0 223.0 223.0 
NRG-6-785.6-SNL-A 0 218.6 218.6 
NRG-6-806.8-SNL-A 0 261.9 261.9 
NRG-7/7A-777.0-SNL-A 0 143.8 143.8 
SNL02030193001.019 
[DIRS 108431] 
NRG-7/7A-800.2-SNL-A 0 179.2 179.2 
NRG-7/7A-806.3-SNL-A 0 225.4 225.4 
NRG-7/7A-818.5-SNL-A 0 126.3 126.3 
USW NRG-7a NRG-7/7A-859.2-SNL-A 0 118.8 118.8 
NRG-7/7A-865.4-SNL-I 0 215.8 215.8 
NRG-7/7A-865.4-SNL-J 0 232.0 232.0 
NRG-7/7A-865.4-SNL-K 0 239.1 239.1 
NRG-7/7A-865.4-SNL-L 0 248.5 248.5 
USW SD-12 SD-12-734.7-SNL-B 0 193.3 193.3 SNL02030193001.023 
[DIRS 108435] SD-12-781.1-SNL-B 0 198.2 198.2 
SD-9-761.5-SNL-A 0 231.5 231.5 
SNL02030193001.026 
[DIRS 108436] USW SD-9 SD-9-768.7-SNL-A 0 254.5 254.5 
SD-9-771.7-SNL-A 0 160.8 160.8 
SD-9-774.6-SNL-B 0 60.1 60.1 
ANL-EBS-MD-000027 REV 03 E-14 September 2004 

Drift Degradation Analysis 
Table E-8. Uniaxial and Triaxial Test Data from the Tptpmn Lithostratigraphic Unit (Continued) a 
Location 
Specimen Number (also 
referred to as Sample 
Number) 
Confining 
Pressure, 
s3 (MPa)
UltimateDifferentialStrength (also 
referred to as 
Compressive 
Strength) (MPa) 
Axial Stress b , 
s1 (MPa) 
Original Source DTN 
SD-9-826.7-SNL-A 0 224.9 224.9 
SNL02030193001.026 
[DIRS 108436] USW SD-9 SD-9-832.8-SNL-C 0 183.3 183.3 
SD-9-842.1-SNL-E-1 0 208.9 208.9 
G4-686.6-G 0.1 180.0 180.1 
SNSAND84110100.000 
[DIRS 160016] 
G4-749.0-A 0.1 268.0 268.1 
G4-749.0-B 0.1 188.0 188.1 
G4-686.6-A 0.1 270.0 270.1 
G4-686.6-D 0.1 326.0 326.1 
USW G-4 
G4-742.75-E 0.1 235.0 235.1 
G4-742.75-F 0.1 256.0 256.1 
G4-742.75-G 0.1 279.0 279.1 
G4-748.6-B 0.1 190.0 190.1 
G4-748.6-A 0.1 196.0 196.1 
G4-686.6-B 5 156.0 161.0 
G4-686.6-E 5 87.0 92.0 
NRG-7/7A-865.4-SNL-C 5 254.8 259.8 
SNL02030193001.019 
[DIRS 108431] 
NRG-7/7A-865.4-SNL-F 5 317.3 322.3 
USW NRG-7a NRG-7/7A-865.4-SNL-G 5 250.1 255.1 
NRG-7/7A-865.4-SNL-H 5 226.6 231.6 
NRG-7/7A-861.7-SNL-A 5 245.8 250.8 SNL02030193001.021 
[DIRS 108433] 
USW SD-12 SD-12-745.6-SNL-B 5 330.7 335.7 SNL02030193001.023 
[DIRS 108435] 
USW G-4 
G4-686.6-C 10 344.0 354.0 SNSAND84110100.000 
[DIRS 160016] G4-686.6-F 10 360.0 370.0 
NRG-7/7A-865.4-SNL-A 10 315.2 325.2 
SNL02030193001.019 
[DIRS 108431] 
NRG-7/7A-865.4-SNL-B 10 344.0 354.0 
USW NRG-7a 
NRG-7/7A-865.4-SNL-D 10 225.5 235.5 
NRG-7/7A-865.4-SNL-E 10 306.7 316.7 
NRG-7/7A-805.6-SNL-A 10 137.1 147.1 SNL02030193001.021 
DIRS 108433] NRG-7/7A-827.4-SNL-A 10 125.3 135.3 
USW SD-12 SD-12-762.6-SNL-B 10 272.8 282.8 SNL02030193001.023 
[DIRS 108435] 
a 
Uniaxial and triaxial test data are qualified and summarized in DTN: MO0311RCKPRPCS.003 [DIRS 166073]. 
The data can be found by downloading the data file from this DTN, and searching for the data using the Specimen 
Number. The uniaxial and triaxial test data have been selected according to test conditions to provide a consistent 
data set. Borehole data with the following test conditions were selected: ambient temperature conditions, 
-1
saturated samples, nominal strain rate of 10-5 s, with sample diameters ranging from 25.4 to 50.8 mm. 
b 
Axial Stress (s1) is not provided in the DTN. Axial Stress = s1 = s3 + Ultimate Differential Strength. 
ANL-EBS-MD-000027 REV 03 E-15 September 2004 

Drift Degradation Analysis 
200 
150 
100 
50 
0 
0 24 6 81012 
ial ini () 
i 
() 
iiiial 
s1s3f 
s1s3f 
s1s3f  
Mean AxStress at Conf ng Stress LevelMPa
 1 Standard Devation Error Bars 
Axial Stress DataMPaLinear Ft of  1 Standard Devation 
Linear Ft of Mean AxStress Data 
= 10.65 + 263.34 
C = 40 MPa 
= 56 
= 7.72 + 201.93 
C = 36 MPa 
= 50 
= 4.78 + 140.53 
C = 32 MPa 
= 41 
Confining Pressure, s3 (MPa) 
Figure E-2. Uniaxial and Triaxial Test Data from Borehole Samples Near the ESF for the Tptpmn 
Lithostratigraphic Unit 
E4. ROCK MASS PROPERTIES 
E4.1 ASSESSMENT OF LITHOPHYSAL ROCK STRENGTH 
E4.1.1 Introduction 
The following section provides a discussion of the development of estimates of the rock mass 
mechanical properties of the lithophysal units of the Topopah Spring tuff. A description of the 
small and large core laboratory testing database is provided. The large core mechanical testing 
(including room dry and saturated conditions) was used to relate strength and modulus to 
lithophysal porosity, which is the primary factor in control of variability of mechanical properties 
in this rock. An initial set of base case strength and modulus values (termed rock strength 
categories) are developed as from the most-recent large core testing that span the entire range 
of lithophysal porosity conditions observed in the ECRB Cross-Drift. These base case values are 
used as a basis for a series of parametric analyses of emplacement drift stability under in situ, 
thermal and seismic loading described in Section 6.4. These analyses consider homogenous rock 
properties for each rock strength category with the lower strength categories leading to 
conservative results. Additional discussion on lithophysal rock strength is provided in 
Lithophysal Rock Mass Mechanical Properties of the Repository Host Horizon (BSC 2004 
[DIRS 168970]). 
Axial Stress, 1 (MPa) 
400 
350 
300 
250 
ANL-EBS-MD-000027 REV 03 E-16 September 2004 

Drift Degradation Analysis 
The large core laboratory data set is necessarily limited in scope due to the variability and 
difficulty in sampling and testing large volume samples of the lithophysal rock mass. Therefore, 
discontinuum numerical models (PFC and UDEC), calibrated to reproduce the basic mechanical 
response of the laboratory test results, are used here to supplement the data base and clarify 
understanding of the mechanical response of lithophysal rock. The PFC model is used to explore 
the impact of lithophysal porosity, size, shape and distribution on the variability of mechanical 
properties, and thus establish upper and lower property bounds. The UDEC model is used to 
conduct drift-scale simulated compression analyses to examine the effect of spatial variability of 
in situ lithophysal porosity on rock mass strength variability. Conclusions are given as to the 
base case mechanical properties data set and the variability of the rock mass mechanical 
properties for use in performance analyses. 
E4.1.2 Small Core Mechanical Properties Data Base 
A large number of compression and tension tests have been conducted on small diameter (1-in to 
2-in [25 mm to 50 mm]) cores from the Tptpul and Tptpll. This data is described in detail in the 
Subsurface Geotechnical Parameters Report (BSC 2003 [DIRS 166660]), and the results 
reviewed here. 
Testing on small cores from the Topopah Spring subunits indicates a distinct control of both 
compressive strength and elastic modulus based on the total porosity of the sample (Figure E-3). 
The total porosity of these samples, due to their small size, is primarily composed of matrix 
ground mass porosity1. On the scale of the emplacement drifts, the total porosity is the sum of 
the matrix porosity (approximately 10 percent) plus lithophysal void porosity (approximately 10 
to 25 percent). The additional porosity of vapor phase altered material may form rims or fill 
lithophysal voids (generally less than 5 percent). Estimates of the component porosity within the 
Tptpll derived from field mapping in the ECRB Cross-Drift are discussed in Appendix O. The 
impact of lithophysal voids (and the inability to sample them) with small core samples is evident 
as the maximum total lithophysal porosities are typically less than 20 percent (see Figure O-15). 
E4.1.3 Large Core Unconfined Compression Testing 
E4.1.3.1 Sample Gathering 
The small diameter cores (e.g., 1-in or 2-in diameter) do not accurately reflect the true strength 
or elastic properties of the lithophysal rock since the diameter precludes a reasonable sampling of 
the lithophysal voids. Therefore, reliance is placed on measurements from large diameter core 
samples that contain multiple lithophysal cavities in a given sample. To this end, an extensive 
drilling program was undertaken in the ESF main loop and ECRB Cross-Drift in 2002 to provide 
large-diameter (11.5-in.) core samples of lithophysal rock from the Tptpul and Tptpll that 
contain a reasonable lithophysal sampling. 
1 Matrix groundmass porosity is that pore space generally less than 2m in size, and totaling approximately 10 
percent of volume in densely welded tuffs (BSC 2003 [DIRS 166660], Section 8.2.3.2, p. 8-9). This porosity is 
considered to be an intrinsic property of the matrix groundmass for the subunits of the Topopah Spring, and is 
distinguished from lithophysal porosity, which is formed from gas collection in the matrix during the cooling 
process. 
ANL-EBS-MD-000027 REV 03 E-17 September 2004 

Drift Degradation Analysis 
i)Unconfned Compressive Strength (MPa
Source: BSC 2003 [DIRS 166660] (Figures 8-22 and 8-11). 
NOTE: Porosity is composed of matrix and lithophysal porosity. The measurements are from a 50.8 mm diameter 
core. Note that small cores from lithophysal zones generally contain only small amounts of lithophysal 
porosity, and thus the above tests are not indicative, in general, of properties of the lower and upper 
lithophysal units. 
Figure E-3. Intact Uniaxial Compressive Strength and Youngs Modulus for Topopah Spring Subunits as 
a Function of Effective Porosity for 50.8 mm Diameter Samples 
ANL-EBS-MD-000027 REV 03 E-18 September 2004 

Drift Degradation Analysis 
Figure E-4 shows a plan view of the ESF main loop and ECRB Cross-Drift and the locations 
from which core samples were retrieved (see Figure 7-1 for a photograph of one of the core 
lengths obtained from the Tptpll in the ECRB Cross-Drift). A total of nineteen 11.5-in. 
(290 mm) cores at least 12 in. (304 mm) in length was obtained. Of these, 13 had a length to 
diameter (L:D) ratio of 1.7 or greater, with one additional sample with L:D of 1.5. These were 
felt to be sufficiently close to the recommended 2:1 length-to-diameter ratio to allow for 
unconfined compression testing. Figure E-5 shows a photograph of some of the large cores and 
an unconfined compression test in progress. The remaining core sections were under-cored to 
provide sixteen additional 5.7-in. (146 mm) test samples. Although these samples are not judged 
to be sufficiently large to represent in situ properties, the data is, nonetheless useful as additional 
information for establishing the impact of porosity on strength and modulus and for estimating 
sample size effects. This data was supplemented by previous testing by Price et al. (1985 
[DIRS 106602]) on 10.5-in. (267 mm) diameter cores taken from an outcrop of the Tptpul at 
Busted Butte (directly adjacent to and south of Yucca Mountain). 
Sample Locations 
Tptpul 
Tptpmn 
Tptpll 
Tptpln 
North Ramp 
South Ramp 
Main Drift 
ECRB Cross-Drift 
Figure E-4. Plan View of the ESF Main Loop and ECRB Cross-Drift Showing the Topopah Spring Rock 
Units and Location of 11.5-in Core Samples Taken in the Tptpul and Tptpll 
ANL-EBS-MD-000027 REV 03 E-19 September 2004 

Drift Degradation Analysis 
NOTE: a) from the Tptpll and Tptpul; b) a sample in unconfined compression. 
Figure E-5. Photographs of Large Lithophysal Core Samples (290-mm/11.5-in. Diameter) 
A program of laboratory compression testing to examine the matrix properties of the Tptpll (and 
comparison to previous testing in the Tptpmn) was undertaken as well. A large boulder from the 
lower portion of the Tptpll, containing few lithophysae, was collected and cut into samples of 
varying size (see Section E4.1.4.3). These samples were used for size effect and anisotropy 
examination in the Tptpll matrix material. 
ANL-EBS-MD-000027 REV 03 E-20 September 2004 

Drift Degradation Analysis 
A primary source document that compiles the testing data on Topopah Spring tuff is the 
Subsurface Geotechnical Parameters Report (BSC 2003 [DIRS 166660]). Some of the specific 
data sources used here on lithophysal rock include: 
 Uniaxial compression and Brazilian tensile strength tests on 2-in (50 mm) cores from 
North Ramp geotechnical boreholes (DTNs: SNL02030193001.004 [DIRS 108415]; 
SNL02030193001.019 [DIRS 108431]; SNL02030193001.020 [DIRS 108432]) 
 Uniaxial compression tests on 10.5-in (267-mm) diameter core samples of Tptpul from 
Busted Butte (Price et al. 1985 [DIRS 106602]) (DTN: MO0311RCKPRPCS.003 
[DIRS 166073]) 
 Uniaxial compression tests on 11.5-in (290 mm) and 5.7-in. (146 mm) diameter core 
samples from the Tptpul and Tptpll drilled from exposures in the ESF main loop and 
ECRB Cross-Drift (Table E-9) (DTNs: SN0208L0207502.001 [DIRS 161871]; 
SN0211L0207502.002 [DIRS 161872]; SN0302L0207502.003 [DIRS 165014]; 
SN0305L0207502.004 [DIRS 165013]) 
 Uniaxial compression tests on 1, 2, 3.2 and 4.7-in (26, 51, 82, and 121 mm) diameter 
samples of the Tptpll from a Busted Butte outcrop boulder 
(DTN: SN0306L0207502.008 [DIRS 165015]) 
 Uniaxial compression experiments on wire-sawed samples (8-in square [200 mm] 
parallelpipeds) from a non-lithophysal boulder of Tptpll obtained from Busted Butte 
(DTN: SN0306L0207502.008 [DIRS 165015]). 
E4.1.3.2 Large Core Test Results and Analysis of Data 
The results of compression testing on 11.5-in. samples from the Tptpul and Tptpll from the ESF 
main loop and ECRB Cross-Drift (described above) and 10.5-in. samples from the Tptpul at 
Busted Butte form the basis for the development of mechanical property ranges. The data from 
these tests are provided in Table E-9. 
Unconfined compression strength and Youngs modulus as functions of approximate lithophysal 
porosity for the 10.5 and 11.5-in. samples of the Tptpll and Tptpul are shown in Figure E-6. 
Although significant scatter exists in the data, a best-fit exponential function has been 
superimposed on the data for room dry and saturated sample conditions. The data shows little 
average impact of saturation level on Youngs Modulus, but results in a general reduction in 
unconfined compressive strength (UCS) as would be expected. Histograms of the distribution of 
UCS and Youngs Modulus, given in Figure E-7, show a mean strength of 18.0 MPa and a mean 
modulus of 12.3 GPa for the samples. 
It is useful to define the relationship of the UCS and Youngs Modulus in a fashion that is 
independent of the lithophysal porosity. The UCS and Youngs Modulus are the primary 
mechanical input properties, and representing their interrelationship on a single diagram allows 
one to more easily develop a base set of input properties that will define the pairing of these 
parameters across the entire range of potential in situ porosity conditions. Each of the 
mechanical properties pairs (UCS and Youngs Modulus) can be related to an approximate 
ANL-EBS-MD-000027 REV 03 E-21 September 2004 

Drift Degradation Analysis 
lithophysal porosity range, which can, in turn, be related to field mapping in the ESF main loop 
and ECRB Cross-Drift. 
Table E-9. Mechanical Properties of Lithophysal Tuff from Large-Diameter Samples 
Test ID 
Lithostratigraphic Unit 
L:D RatioaSaturationTemperature (C) 
Ultimate Strength (MPa) 
Youngs Modulus (GPa) 
Poissons Ratio 
Estimated Lithophysal 
Porosityc 
DTNb 
YMPLL49A Tptpll 1.1 : 1 Dry 195 32.2 7.1  11.7 SN0211L0207502.002 
[DIRS 161872] 
YMPLL43A Tptpll 1.1 : 1 Dry 200 31.1 6.5  20.3 SN0211L0207502.002 
[DIRS 161872] 
YMPLL23A Tptpll 1.8 : 1 Room Dry 24 28.7 9.2  19.2 SN0211L0207502.002 
[DIRS 161872] 
YMPLL24A Tptpll 1.8 : 1 Room Dry 24 13.3 5.0  22.2 SN0211L0207502.002 
[DIRS 161872] 
YMPLL46A Tptpll 1.8 : 1 Room Dry 24 21.7 8.5  28.4 SN0211L0207502.002 
[DIRS 161872] 
YMPLL87A Tptpll 1.9 : 1 Saturated 24 15.7 5.3  14.5 SN0211L0207502.002 
[DIRS 161872] 
YMPUL59B Tptpul 1.2 : 1 Dry 190 19.6 7.3  39.4 SN0208L0207502.001 
[DIRS 161871] 
YMPUL67A Tptpul 1.3 : 1 Dry 190 34.8 9.9  6.2 SN0208L0207502.001 
[DIRS 161871] 
YMPUL62B Tptpul 1.0 : 1 Dry 200 37.0 13.7  19.3 SN0208L0207502.001 
[DIRS 161871] 
YMPUL50A Tptpul 1.5 : 1 Room Dry 24 22.1 14.9 0.21 28.5 SN0211L0207502.002 
[DIRS 161872] 
YMPUL59A Tptpul 2.0 : 1 Room Dry 24 13.5 5.8 0.39 30.3 SN0208L0207502.001 
[DIRS 161871] 
YMPUL61A Tptpul 1.9 : 1 Room Dry 24 17.7 8.8  23.9 SN0208L0207502.001 
[DIRS 161871] 
YMPUL62A Tptpul 1.8 : 1 Room Dry 24 25.9 13.7  12.7 SN0208L0207502.001 
[DIRS 161871] 
YMPUL64A Tptpul 1.7 : 1 Room Dry 24 33.5 20.5  12.8 SN0208L0207502.001 
[DIRS 161871] 
YMPUL65A Tptpul 2.0 : 1 Room Dry 24 26.2 19.5  11.9 SN0208L0207502.001 
[DIRS 161871] 
YMPUL66A Tptpul 1.7 : 1 Room Dry 24 16.5 12.4  16.7 SN0208L0207502.001 
[DIRS 161871] 
YMPUL60A Tptpul 1.8 : 1 Saturated 24 12.7 6.7  18.6 SN0208L0207502.001 
[DIRS 161871] 
YMPUL63A Tptpul 1.9 : 1 Saturated 24 9.4 5.0 0.24 20.0 SN0208L0207502.001 
[DIRS 161871] 
ANL-EBS-MD-000027 REV 03 E-22 September 2004 

Drift Degradation Analysis 
Table E-9. Mechanical Properties of Lithophysal Tuff from Large-Diameter Samples (Continued) 
Test ID 
Lithostratigraphic Unit 
L:D RatioaSaturationTemperature (C) 
Ultimate Strength (MPa) 
Youngs Modulus (GPa) 
Poissons Ratio 
Estimated Lithophysal 
Porosityc 
DTNb 
YMPUL68A Tptpul 2.1 : 1 Saturated 24 11.6 5.9 0.03 25.8 SN0208L0207502.001 
[DIRS 161871] 
1B Tptpul 2.0 : 1 Saturated 22 14.5 14.2  17.3 MO0311RCKPRPCS.003 
[DIRS 166073] 
1D Tptpul 2.0 : 1 Saturated 22 10.3 10.9  22.2 MO0311RCKPRPCS.003 
[DIRS 166073] 
2A Tptpul 2.0 : 1 Saturated 22 12.4 11.9  14.1 MO0311RCKPRPCS.003 
[DIRS 166073] 
3A Tptpul 2.0 : 1 Saturated 22 12.0 12.9  14.0 MO0311RCKPRPCS.003 
[DIRS 166073] 
8A Tptpul 2.0 : 1 Saturated 22 18.2 16.6  13.5 MO0311RCKPRPCS.003 
[DIRS 166073] 
8B Tptpul 2.0 : 1 Saturated 22 17.4 16.8  14.2 MO0311RCKPRPCS.003 
[DIRS 166073] 
8C Tptpul 2.0 : 1 Saturated 22 18.5 15.8  17.9 MO0311RCKPRPCS.003 
[DIRS 166073] 
8D Tptpul 2.0 : 1 Saturated 22 17.5 18.3  21.4 MO0311RCKPRPCS.003 
[DIRS 166073] 
8E Tptpul 2.0 : 1 Saturated 22 13.8 15.8  19.3 MO0311RCKPRPCS.003 
[DIRS 166073] 
8F Tptpul 2.0 : 1 Saturated 22 27.8 21.5  12.6 MO0311RCKPRPCS.003 
[DIRS 166073] 
a 
b 
Specimen length-to-diameter ratio. 
Specific data are located in rows 737 to 746 from DTN: MO0311RCKPRPCS.003 [DIRS 166073]. Additional test 
descriptions for the data in DTN: MO0311RCKPRPCS.003 [DIRS 166073] are provided by Price et al. (1985 
[DIRS 106602]). 
Lithophysal porosity data for tests documented in DTNs SN0208L0207502.001 [DIRS 161871] and 
SN0211L0207502.002 [DIRS 161872] are provided by DTN: SN0305L0207502.005 [DIRS 163373]. Lithophysal 
property data for tests documented in DTN: MO0311RCKPRPCS.003 [DIRS 166073] are provided by Price et al. 
(1985 [DIRS 106602], Table 4). 
ANL-EBS-MD-000027 REV 03 E-23 September 2004 

Drift Degradation Analysis 
0 
10 
20 
30 
40 
50 
60 
70 
) 
i)
Lith. tuff lab tests, room dry 
Lith. tuff lab tests, saturated 
Expon. (Lith. tuff lab tests, room dryExpon. (Lith. tuff lab tests, saturated) 
L:D = 1.5 
Unconfned Compressive Strength (MPa
0.10 0.15 0.20 0.25 0.30 0.35 
Lithophysal Void Fraction 
(a) 
0 
5 
10 
15 
20 
25 
30 
35 
)
) 
Lith. tuff lab tests, room dry 
Lith. tuff lab tests, saturated 
Expon. (Lith. tuff lab tests, room dryExpon. (Lith. tuff lab tests, saturated) 
L:D = 1.5 
Youngs Modulus (GPa
0.10 0.15 0.20 0.25 0.30 0.35 
(b) 
Lithophysal Void Fraction 
NOTE: (a) Unconfined Compressive Strength; (b) Youngs Modulus as a Function of the Lithophysal Void Fraction 
and Saturation Level for 10.5-in. and 11.5-in. 
Figure E-6. Variation in Diameter Cores from the Tptpul and Tptpll 
ANL-EBS-MD-000027 REV 03 E-24 September 2004 

Drift Degradation Analysis 
0 
1 
2 
3 
4 
5 
6 
Number 
All 
Saturated 
Room Dry 
0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 More 
Unconfined Compressive Strength (MPa) 
(a) 
0 
1 
2 
3 
4 
5 
6 
7 
8 
Number 
All 
Saturated 
Room Dry 
0 5 10152025 
Young's Modulus (GPa) 
(b) 
NOTE: (a) Unconfined Compressive Strength; (b) Youngs Modulus for the 10.5-in. and 11.5-in. 
Figure E-7. Histograms of Diameter Core Samples of Lithophysal Tuff 
ANL-EBS-MD-000027 REV 03 E-25 September 2004 

Drift Degradation Analysis 
The UCS and modulus data for each large core test, presented in Figure E-6, is plotted in the 
form of UCS versus Youngs modulus in Figure E-8. The data shows that a reasonably linear 
relationship exists between these mechanical properties. The large core data has been subdivided 
into two sets  the 11.5-in. data (room-dry and saturated) collected in 2002 and the 10.5-in. 
saturated samples from Busted Butte  and linear relations fit to each set. As seen in this plot, 
the saturated samples tend to form a lower bound to the room dry strengths. 
A parametric bounding analysis approach is developed initially in which the base case set of the 
11.5-in. values of UCS and Youngs modulus are defined from the linear fit to the data as shown 
in Figure E-8. The entire range of UCS is subdivided into a series of five evenly-distributed rock 
mass strength categories that reflect the approximate range of lithophysal porosity as observed 
in the field mapping (Table E-10 and Figure E-9). The categories encompass the range in UCS 
values from 10 MPa (lowest) to 30 MPa (highest). The modulus corresponding to each strength 
value is determined from the linear fit of the 11.5-in. data as shown. The initial or base case 
analysis of emplacement drift stability in lithophysal rock, as discussed in Section 6.4 of this 
document, use these rock strength categories and the consideration of a homogeneous rock mass 
for the parametric analyses. As discussed later, analyses are presented in which the impact of 
estimated in situ lithophysal porosity spatial variability on rock mass properties and drift stability 
is examined. The results are used to verify the conservative nature of the homogeneous rock 
mass consideration and the bounding calculation approach. 
An estimate of the overall distribution of these rock mass strength categories within the Tptpll 
can be obtained from the lithophysal porosity mapping studies conducted in the ECRB 
Cross-Drift (see Appendix O, Figure O-15). The histogram given in Figure E-10 shows the 
abundance (frequency) and cumulative frequency distributions of lithophysal porosity, averaged 
over 5 m intervals in the ECRB Cross-Drift from stations 14+44 to 23+26 (essentially the top to 
bottom of the Tptpll). This plot subdivides the abundance of lithophysal porosity into 5-percent 
intervals that roughly correspond to those lithophysal porosity ranges for the various rock mass 
categories given in Table E-10. It is seen that the most abundant rock mass lithophysal porosity 
ranges found in situ are 10 to 20 percent, or corresponding roughly to rock mass strength 
Categories 3 and 4. Observations in the range of 10 to 15 percent lithophysal porosity are most 
common, and correspond to the Category 4 range. Observations of lithophysal porosity above 
20 percent (Categories 1 and 2) are uncommon, representing about 10 percent of the entire 
Tptpll. Observations of lithophysal porosities greater than 20 percent are most common near the 
top of the Tptpll, around stations 15+50 to 16+00 (Figure 6-12). 
Using the calculated Youngs modulus values in Table E-10, corresponding values of bulk 
modulus, K, and shear modulus, G, were calculated according to Equations E-2 and E-3. 
A Poissons ratio value of 0.2 was used for these calculations, which is based on both the 
laboratory test data (Table E-9) and data from the in situ slot tests 
(DTNs: SN0208F4102102.002 [DIRS 161874]; SN0212F4102102.004 [DIRS 161875]; 
SN0301F4102102.006 [DIRS 161876]). Cohesion (Table E-10) was calculated for a range of 
ANL-EBS-MD-000027 REV 03 E-26 September 2004 

Drift Degradation Analysis 
friction angles using Equations E-6 and E-7, such that 
s
C
=
c 
. 

5.0 
f
..
(Eq. E-8) 
tan
+
45o
..
2
Unconfined Compressive Strength (MPa) 
40.0 
35.0 
30.0 
25.0 
20.0 
15.0 
10.0 
5.0 
0.0 
R2R2iin. 
iKey 
lit 
lit 
1 42 53 
y = 1.1245x + 7.8369 
= 0.6716 
y = 1.4632x - 6.3963 
= 0.861 
UL RD, 11.5-in. 
UL Sat, 11.5-in. 
LL RD, 11.5-n. 
LL Sat, 11.5-
UL Sat,10.5-n. 
UL = Upper Lithophysa UnLL = Lower Lithophysa UnRD = Room Dry 
Sat = Saturated L:D = 1.5 
0 5 10152025 
Young's Modulus (GPa) 
NOTE: Source DTNs are provided in Table E-9. The 11.5-in. room-dry sample data has been subdivided into a 
series of categories for base-case calculations. 
Figure E-8. Relationship of Unconfined Compressive Strength to Youngs Modulus for Room-Dry and 
Saturated 10.5-in. and 11.5-in. Core Samples from the Tptpul and Tptpll 
ANL-EBS-MD-000027 REV 03 E-27 September 2004 

Drift Degradation Analysis 
Table E-10. Suggested Range of Mechanical Properties Developed from 11.5-in. Core Testing, 
Selected for Base-Case Design and Performance Analyses 
Rock 
Mass 
Category 
Unconfined 
Compressive 
Strength 
(MPa) 
Estimated 
Youngs 
Modulusa 
(GPa) 
Cohesionc (MPa) 
Bulk 
Modulusc , 
K (GPa) 
Shear 
Modulusc , 
G (GPa) 
Approximate 
Lithophysal 
Porosity From 
Laboratory 
Testsb 
(%)f=50 f=45 f=40 
1 10 1.9 1.82 2.07 2.33 1.07 0.80 35  8 
2 15 6.4 2.73 3.11 3.50 3.54 2.65 28  6 
3 20 10.8 3.64 4.14 4.66 6.01 4.51 21  4 
4 25 15.3 4.55 5.18 5.83 8.48 6.36 13  5 
5 30 19.7 5.46 6.21 7.00 10.95 8.21 7  7 
Source: DTNs provided in Table E-9. 
a 
Youngs Modulus estimated from linear fit to 11.5-in. core data given in Figure E-8. 
b Approximated lithophysal porosity and ranges are from BSC 2004 [DIRS 168970], Table 6.6-1. 
Cohesion is calculated using Equation E-8. Bulk and shear modulus values are calculated based on 
Equations E-2 and E-3. 
ANL-EBS-MD-000027 REV 03 E-28 September 2004 

Drift Degradation Analysis 
NOTE: Section 16+41 (top), Section 14+93 (center) and Section 21+24 (bottom). (see Appendix O): Category 3 
(Top) With Lithophysal Porosity of Approximately 19 Percent, Category 4 (Center) With Lithophysal Porosity 
of 13.3 Percent, and Category 5 (Bottom) With Lithophysal Porosity of 8.5 Percent. 
Figure E-9. Examples of Approximate Rock Strength Category Levels Taken from 1x3-m Panel Maps 
ANL-EBS-MD-000027 REV 03 E-29 September 2004 

Drift Degradation Analysis 
0 
10 
20 
30 
40 
50 
60 
70 
Lility (%) 
0% 
liil25-30 20-25 15-20 10-15 <10 
thophysa PorosFrequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Cumuative Dstrbution 
Frequency 
Cumuative % 
NOTE: Lithophysal porosity data are from ECRB Cross-Drift station 14+44 to 23+26 (Appendix O, Section O6.6; 
see Microsoft Excel file, Drift Deg AMR AF T-A-P Fit.xls, worksheet Volume Percent - Stats, which can be 
accessed through the TDMS using DTN: MO0408MWDDDMIO.002). 
Figure E-10. Distribution of Lithophysal Porosity Abundance (Frequency) for the Tptpll in the Enhanced 
Characterization of the Repository Block Cross-Drift 
E4.1.4 Investigation of Impact of Lithophysal Variability on Rock Mass Properties 
The Tptpll rock mass is characterized by lithophysal porosity that varies with position in the rock 
mass. The Topopah Spring unit was laid down rapidly in thin, but laterally-extensive sheets. 
The formation of lithophysae, which is a phenomenon resulting from movement of vapor within 
the rock mass during the cooling process, results in a similar layering effect of lithophysal 
porosity. The mapping presented in Appendix O and analysis of spatial variability presented in 
Appendix T shows that the lithophysal porosity occurs in thin, laterally-extensive sheets with 
variability occurring primarily within the plane perpendicular to dip of the units. The approach 
to assessment of drift stability described in Section 6.4.2 uses parametric analyses based on the 
consideration of a homogenous rock mass characterized by constant rock properties. To 
represent the inherent variability of the rock mass, a series of discrete constant property levels, 
linked to lithophysal porosity, are used to represent (approximately) the lowest, highest and 
median in situ conditions. The likelihood of occurrence of these particular conditions is based on 
the percentage of a given strength category to exist in the Tptpll. This simplistic approach 
(as opposed to attempting to model spatial variability directly) was taken to facilitate modeling. 
The rock mass porosity is, in reality, spatially-variable over a relatively small length scale 
(on the order of meters  see Appendix O). Therefore, the rock mass rarely consists of uniformly 
weak or strong material, but consists of small regions of varying strength and modulus. 
Appendix T presents a model that produces a synthetic representation of the spatial variability of 
the lithophysal porosity in the Tptpll, based on field mapping as described in Appendix O. 
Therefore, the consideration of a homogenous rock mass will tend to over predict the failure 
ANL-EBS-MD-000027 REV 03 E-30 September 2004 

Drift Degradation Analysis 
potential of drifts in the weakest rock mass classifications and will under predict the yield in the 
highest rock mass classifications. The impact of actual lithophysae geometry and spatial 
variability on the rock mass properties and the relation to conservatism in the strength category 
bounding methodology is discussed below. 
E4.1.4.1 Effect of Variability of Lithophysal Porosity, Size and Shape on Mechanical 
Properties  Estimation of Upper and Lower Bounds for Lithophysal 
Mechanical Properties 
The large core laboratory testing is a relatively small sampling of the lithophysae conditions that 
exist in the field, although the approximate porosities of the cores encompass the range of most 
field-measured conditions. To extend the laboratory data base to account for the in situ 
variability in lithophysal porosity (i.e., shape, size, and distribution) a numerical study was 
conducted using the calibrated Particle Flow Code (PFC) model. The basic calibration and 
validation of the PFC model is described in Section 7.5 of this document. In this calibration, 
lithophysae were represented in simulated tuff samples as circular holes that were randomly 
distributed to produce a given porosity. It was shown that the numerical model was able to 
reasonably account for the failure mechanisms of lithophysal and nonlithophysal rock specimens 
as observed in the laboratory, and could reproduce the general effect of lithophysal porosity on 
UCS and Youngs Modulus. 
The same calibrated model is used here to conduct a shape study in which the impacts of 
lithophysal porosity, shape, size and distribution on rock property variability were examined.2 
In this study, simulated samples of the lithophysal rock mass were developed directly from field 
panel map lithophysae distributions (Appendix O) by overlaying (stenciling) the panel map 
directly onto the PFC model to create the void geometry. Figure E-11 shows an example of the 
result of simulated UCS tests on two samples of PFC models with stenciled lithophysae 
distributions. The figures show the tensile cracking between lithophysae at failure, and the 
impact of the specific distribution on failure mechanism and the associated stress-strain behavior. 
Approximately 80 simulated unconfined compression cases of actual lithophysae distributions 
were modeled, and the results in terms of UCS and Youngs Modulus as functions of the 
lithophysal porosity given in Figure E-12. The results are compared to the 11.5-in. laboratory 
test data as well as the previous PFC modeling using idealized circular lithophysae. The 
introduction of actual lithophysae shapes and distributions has two distinct effects with regard to 
the use of circular voids. 
 The actual lithophysae shapes and distributions introduce significant variability into the 
strength or modulus for a given porosity. This variability is a function of the distribution 
of solid bridge length between lithophysae, which are, in turn, a function of the porosity 
and nature of the distribution of that porosity. 
 The actual lithophysae shapes and distributions provide a lower bound to the strength 
and modulus to that given by the circular lithophysae shapes and to the laboratory data. 
2 This study is documented in detail in the Subsurface Geotechnical Parameters Report (BSC 2003 [DIRS 166660], 
Section 9.1). 
ANL-EBS-MD-000027 REV 03 E-31 September 2004 

Drift Degradation Analysis 
The PFC shape study extrapolations are superimposed on the previous figure (Figure E-8) of 
UCS vs. Youngs Modulus to estimate bounding values (Figure E-13). Upper and lower bounds 
to the data are estimated, and a mean value between these bounds shown which falls 
approximately along the original base case linear extrapolation for the 11.5-in. test results. The 
portion of the bounding curves that fall outside (below) the laboratory measurement range is 
dashed indicating that this extrapolation is not based on measurements. The base case rock mass 
property categories are shown in Figure E-13, illustrating the estimated upper and lower 
bounding values of UCS associated with each value of Youngs Modulus. 
The impact of the bounding values on yield and performance are discussed in Section 6.4. In 
these studies, the rock mass was considered to be homogeneous with constant rock mass 
mechanical properties consisting of the lower bound of strength at the respective values of 
Youngs Modulus (i.e., the intersection of the vertical category bar and the lower bound line in 
Figure E-13). The analyses involved examine stability of the emplacement drifts under in situ 
and thermal loading for the lower bound values for the categories. This modeling showed that 
UCS values less than approximately 10 MPa (i.e., the lower bound of Categories 1 and 2) result 
in predicted extensive sidewall failure of emplacement tunnels under in situ stresses only 
(Figure E-14). This is obviously not observed in the ECRB Cross-Drift or ESF main loop where 
tunnels are in stable and excellent condition with minimal ground support in the crown and 
generally no ground support in the sidewalls. The laboratory database shows that minimum UCS 
values, even for lithophysal porosities in excess of 30 percent, are approximately 10 MPa. 
An explanation of why the rock mass UCS may have a lower bound of approximately 10 MPa is 
the inherent spatial variability of lithophysal porosity, and thus local variability in rock mass 
mechanical properties. The consideration of a homogeneous, high porosity rock mass, as used in 
the Category 1 and 2 cases, is conservative since spatial variability of porosity will result in a 
higher rock mass strength. 
ANL-EBS-MD-000027 REV 03 E-32 September 2004 

Drift Degradation Analysis 
Stress-Strain 
(
(m/m) 
(m/m) 
Response 
Tensile 
Fractures 
Axial StressPa) Axial Stress (Pa) 
Strain 
Strain 
Applied Axial Stress 
NOTE: Specimen is composed of several thousand bonded particles. Red lines are tensile fractures that have 
propagated between lithophysae to ultimately form a failure mechanism. Superimposed stress-strain 
curve illustrates impact of lithophysae distribution on strength, modulus and post-peak failure mechanism. 
Vertical axis is axial stress in Pa; horizontal axis is strain in m/m. 
Figure E-11. Examples of Particle Flow Code Compression Tests Using Simulated Rock Specimens 
Developed by Stenciling Field Panel Maps in the Enhanced Characterization of the 
Repository Block 
ANL-EBS-MD-000027 REV 03 E-33 September 2004 

Drift Degradation Analysis 
70 
Young's Modulus (GPa) 
UCS (MPa) 
60
50
40
30
20
10
0
(
1m X 1m)
Lith. tuff lab tests, room dry 
PFC2D Davg=17.1 mm, 166-mm circles) 
PFC2D (Stenciled lithophysae from panel maps, 
Lith. tuff lab tests, saturated 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 
Lithophysal Void Fraction 
35
30
25
20
15
10
5
0
( 
(
Lith. tuff lab tests, room dry 
PFC2D Davg=17.1 mm, 166-mm circles) 
PFC2DStenciled lithophysae from panel 
maps, 1m X 1m) 
Lith. tuff lab tests, saturated 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 
Lithophysal Void Fraction 
NOTE: Test data from large-core lithophysal tests -Table E-9. 
Figure E-12. Plots Showing Data from Large Core Compression Testing of Tptpul and Tptpll Compared 
to Particle Flow Code Simulations Using Circular and Triangular Shaped Lithophysae as 
Well as Actual Stenciled Shapes from Enhanced Characterization of the Repository Block 
Panel Maps 
ANL-EBS-MD-000027 REV 03 E-34 September 2004 

Drift Degradation Analysis 
60 
20 
30 
40 
4 
5 
3 
2 
1 
Lith. tuff lab tests, room dry 
Lith. tuff lab tests, saturated 
Panel Map PFC2D data 
Base case properties 
characteristic 
Upper Bound 
Estimate 
Mean of Upper and 
Lower Bounds 
Lower Bound 
Estimate 
50 
Uniaxial Compressive Strength (MPa) 
10 
0 
0 5 1015202530 
Young's Modulus (GPa) 
NOTE: Approximate upper and lower bounds are shown. 
Figure E-13. Unconfined Compressive Strength Versus Youngs Modulus Showing Large Core Data and 
Results from PFC Panel Map Lithophysae Shape Study 
ANL-EBS-MD-000027 REV 03 E-35 September 2004 

Drift Degradation Analysis 
r 
UCS = 4.5 MPa, E=5 GPa UCS = 5.9 MPa, E=6.7 GPa 
extensive sidewall sheafailure and fall-out 
minor yield along sidewall 
UCS = 7.2 MPa, E=8 GPa UCS = 9.9 MPa, E=11.7 GPa 
NOTE: Drift exhibits extensive sidewall failure under in situ load only for UCS values less than approximately 
10 MPa. This behavior is not observed in the ESF main loop or ECRB Cross-Drift and lower bound 
properties (UCS < approximately 10 MPa) under predict in situ strength values. See Figure E-13. 
Figure E-14. Emplacement Drift Stability Analysis Under In Situ Loading for Combinations of UCS and 
Youngs Modulus Along the Lower Bound Properties Line 
E4.1.4.2 Investigation of Lithophysal Porosity Spatial Variability on Rock Mass 
Properties 
To investigate the impact of spatial variability of porosity on the lower bound and mean rock 
mass properties, a numerical investigation was carried out using the calibrated UDEC Voronoi 
drift scale model1. The purpose of the analyses is to determine the rock mass stress-strain 
response for an inhomogeneous rock mass composed of spatially-varying lithophysal porosity, 
1 See Section 7.6.4 for details of UDEC model calibration methodology and Section 6.4.1 for resulting calibrated 
rock mass properties by strength category. 
ANL-EBS-MD-000027 REV 03 E-36 September 2004 

Drift Degradation Analysis 
and thus spatially-varying rock mass UCS and Youngs Modulus. The goal of the modeling is to 
conduct numerical compression tests on simulated rock mass samples that are sufficiently 
large to contain the variability of lithophysal porosity that will affect the emplacement drift scale. 
This requires a geometric model of the spatial variability of lithophysal porosity as a function of 
position within the Tptpll as well as the UDEC model. 
Appendix T of this document presents a methodology for simulating the spatial variability of 
lithophysal porosity based on field measurements in the Tptpll in the ECRB Cross-Drift. The 
model is used to statistically represent lithophysal porosity in a series of 40 m long (along the 
axis of the ECRB Cross-Drift) by 50 m high (vertical) by 200 m wide parallelepipeds along the 
ECRB Cross-Drift axis from top to bottom of the Tptpll. The parallelepipeds are subdivided into 
a number of small (meter-scale) cubical grids within which the lithophysal porosity is estimated 
as a function of vertical and horizontal position. Figure T-5 (reproduced below in Figure E-15) 
presents examples of two vertical planes perpendicular to the drift axis centered at locations in 
the upper and lower portions of the Tptpll. These two planes correspond to the higher porosity 
zones at the top of the Tptpll and the lower porosity material near the contact with the Tptpln. 
Thirty rock mass samples measuring 10 m high by 5 m wide (drift scale) were randomly 
selected both vertically and horizontally within each of the parallelepipeds. Each of the porosity 
grids of the parallelepiped that are found within the boundaries of each of these 10 m  5 m rock 
mass samples have a value of lithophysal porosity associated with them. This porosity is used to 
assign the associated rock mass category and, in turn, its associated UCS and modulus (and the 
calibrated cohesion2, friction angle and stiffness representing the strength and modulus) to the 
elements within that particular grid. The resulting sample thus contains spatially variable UCS 
and modulus that represents the in situ variability of lithophysal porosity. Figure E-15 shows an 
example of the geometry of one of the 10 m  5 m UDEC samples composed of Voronoi 
blocks and the contours of the resulting lithophysal porosity captured from the simulated Tptpll 
parallelepipeds. The mean, maximum and minimum lithophysal porosities in each of the 
samples are plotted in Figure E-16, showing that the samples from the upper block, as expected, 
contain a greater proportion of lithophysal material with porosities in excess of 25 percent. The 
means of the samples show and average lithophysal porosity for the upper block of 15.3 percent 
and 12.8 percent for the lower block. These are consistent with the field measurements 
presented in Appendix O. 
2 See Table E-11 for relationship of approximate lithophysal porosity to rock mass category and Table 6-43 for 
calibrated rock mass Mohr-Coulomb properties for each rock mass category. 
ANL-EBS-MD-000027 REV 03 E-37 September 2004 

Drift Degradation Analysis 
0 
5 
10 
15 
20 
25 
30 
1450 1650 1750 1850 1950 2050 2150 2350 
(m) 
3 3 ) 
) 
=5 
= 10 
= 15 
= 20 
= 25 
> 25 
Lithophysal cavities in model section 
1550 2250 
StationPorosity (cm/cmCavit y (fit t ed0-5 win. 
5-10 win. 
10-15 win. 
15-20 win. 
20-25 win. 
25-30 win. 
30-35 win. 
35-40 win. 
40-45 win. 
45-50 win. 
Model section 
Percent Porosity 
SECTION A AT STATION 17+56 
Section A 
UDEC Voronoi 
10-m  5-m 
Sample 
Superimpose 
Porosity on Sample 
to Represent Spatial 
Variability 
NOTE: 
A series of 10 m  5 m test sample locations are chosen randomly in three-dimensional space. Spatial variability of porosity within the sample is 
overlaid onto the UDEC Voronoi test specimen and material properties associated with porosities are assigned to model elements to represent spatial 
variability of properties. Compression testing is performed to estimate the impact of spatial variability on UCS and Youngs modulus. See Appendix T for 
details of the porosity model. Presented in Appendix T. 
Figure E-15. Schematic Illustration of the Process of Sampling and Modeling Spatial Variability Using Lithophysal Porosity Simulation Model 
ANL-EBS-MD-000027 REV 03 E-38 September 2004 

Drift Degradation Analysis 
UDEC simulations of compression tests were conducted for 30 samples from each of the upper 
and lower cross sections. For each sample, for rock mass strengths for each strength category 
were defined by two sets of values  the base case properties, and the lower bound rock mass 
properties, both illustrated in Figure E-16 and summarized in Table E-11. The upper bound 
values are not examined as they are irrelevant since the base case analyses of drift stability 
presented in Section 6.4 are conservative  higher strengths will only result in greater stability. 
Table E-11. Base Case and Lower Bound Strength Values for Rock Categories Used in UDEC 
Analyses of Spatial Variability 
Rock Mass 
Category 
Unconfined Compressive 
Strength (MPa) 
Estimated 
Youngs 
Modulusa 
(GPa) 
Approximate Lithophysal 
Porosity From 
Laboratory Testsb 
(%)Base Case Lower Bound 
1 10 2.0 1.9 35  8 
2 15 5.6 6.4 28  6 
3 20 9.2 10.8 21  4 
4 25 12.8 15.3 13  5 
5 30 16.3 19.7 7  7 
Source: DTNs provided in Table E-9. 
a 
Youngs Modulus estimated from linear fit to 11.5-in. core data given in Figure E-8 
b 
Estimated from correlations of strength and modulus to lithophysal porosity in Figure E-6. Porosity ranges are 
based on BSC 2004 [DIRS 168970], Table 6.6-1. 
The numerical compression tests typically show that the samples fail as expected in an axial 
splitting mode (Figure E-17). The results of these analyses are summarized in Figure E-18 in 
terms of the relationship of UCS and Youngs Modulus. Here, the laboratory and PFC shape 
study analyses are plotted along with the results of the numerical compression experiments for 
base case and lower bound properties. Several conclusions from this work can be made, 
including: 
1. The variability in porosity distribution inherent in the samples results in UCS values 
that roughly equal or exceed 10 MPa. As seen in Figure E-18, the spatial variability in 
rock mass strength naturally results in sample strengths that gravitate toward that of 
the average porosity (i.e., around 15 percent). It is difficult, considering variable rock 
mass porosity, to produce average rock mass strength values that are at the low end of 
the category range. This agrees with observations in the ESF main loop and ECRB 
Cross-Drift of stable, lightly supported excavations in the lithophysal units that show 
little or no signs of instability. 
ANL-EBS-MD-000027 REV 03 E-39 September 2004 

Drift Degradation Analysis 
0 
5 
10 
15 
20 
25 
30 
Lithophysal Porosity (%) 
a) 
Minimum 
Mean 
Maximum 
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 
Sample Number 
0 
5 
10 
15 
20 
25 
) 
b) 
Lithophysal Porosity (%
Minimum 
Mean 
Maximum 
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 
Sample Number 
NOTE: Mean, minimum, and maximum refer to those values of lithophysal porosity in the particular sample. (a) the 
upper cross-section; (b) the lower cross-section of the Tptpll. 
Figure E-16. Spatial Variability in Lithophysal Porosity in Each of 30 Samples Taken 
ANL-EBS-MD-000027 REV 03 E-40 September 2004 

Drift Degradation Analysis 
Axial Stress (Pa) 
Strain (m/m) 
Axial Compression 
Axial fractures 
opening 
NOTE: Estimated modulus and peak strength are determined from stress-strain curve. Sample is same as shown 
in Figure E-18. Sample fails in axial splitting mode as seen by black, axially oriented macro-fractures. Red 
block contacts indicate yield in either tension or shear. 
Figure E-17. Example of Unconfined Compression Test Results on 10 m  5 m Rock Mass Sample 
Containing Spatially Variable Lithophysal Porosity 
ANL-EBS-MD-000027 REV 03 E-41 September 2004 

Drift Degradation Analysis 
10 
0 
0 5 1015202530 
20 
30 
40 
l4 
5 
3 
2 
1 
y 
Lith. tuff lab tests, room dry 
Lith. tuff lab tests, saturated 
Panel Map PFC2D data 
Lower Bound Cutoff 
10mX5m Tests, upper 70% Tptpll & lower bound 
10mX5m Tests, upper 70% Tptpl & ave properties 
10mX5m Tests, lower 70% Tptpll & lower bound 
10mX5m Tests, lower 70% Tptpll & ave properties 
Spatial-VariabilitBase Case and 
Lower Bound 
Estimates 
Young's Modulus (GPa) 
NOTE: The results derived from base case and lower bound rock properties estimates. Note that a lower bound 
strength cut-off exists at approximately 10 MPa as a result of spatial variability of porosity. 
Figure E-18. Relationship of UCS to Youngs Modulus Showing the Results of Modeling Estimates of 
Properties for Spatially-Variable Lithophysal Rock Mass 
2. The distribution of sample UCS and moduli for both base case and lower bound 
properties naturally fall within the range of rock mass strength categories 3 to 4. This 
is in agreement with the in situ distribution of lithophysal porosities 
(e.g., Figure O-15) that show the most common values lie in the Category 3 to 4 range. 
This confirms the consideration that the typical rock mass properties for the 
lithophysal units lie in the Category 3 to 4 range, and that the occurrence of Category 1 
or 2 rocks is typically as localized regions of high porosity, potentially accompanied 
by large lithophysae. 
3. The results verify that the consideration of homogenous rock mass properties used in 
the base case rock strength categories is conservative in nature. 
Based on these calculations, the range of lithophysal rock mass properties are considered to have 
a lower bound strength of 10 MPa, with the lower bound following the saturated rock strength 
estimate for strengths greater than 10 MPa. 
E4.1.4.3 Size Effect and Anisotropy of the Matrix of the Lithophysal Rock 
To further explore the effect of sample size for nonlithophysal material, a single large block of 
material from the nonlithophysal section of the Tptpll near its lower boundary with the Tptpln 
was obtained from Busted Butte (Figure E-19). 
60 
50 
Unconfined Compressive Strength (MPa) 
ANL-EBS-MD-000027 REV 03 E-42 September 2004 

Drift Degradation Analysis 
A total of 110 samples with sizes ranging from 1-in to 8.8-in. (26 mm to 223 mm) diameter were 
cut and tested to examine both size effect and mechanical anisotropy. The mechanical 
anisotropy studies included testing of 2-in to 2.4-in. (51 mm to 62 mm) samples drilled at three 
mutually perpendicular directions from the same block of material. The results of the sample 
size on UCS are shown in Figure E-20. In this figure, the UCS is plotted as a function of the 
sample volume (as a log-log plot), and is compared to the test data for the Tptpmn given in Price 
1986 [DIRS 106589]. The vertical offset of the two lines is indicative of the slightly different 
average strength of the Tptpll and Tptpmn matrix material, although the size effect is virtually 
identical. The mechanical anisotropy is demonstrated in terms of the average values for the 
Youngs moduli from each of the perpendicular orientations. As seen in Figure E-21, there is a 
maximum anisotropy of approximately 10.6 percent in the average matrix moduli, which is 
considered to be a second order effect in comparison to lithophysal and fracturing effects. 
NOTE: Block from nonlithophysal portion of the Tptpll near its lower boundary with the Tptpln, Busted Butte. 
Figure E-19. Development of Rectangular Specimens for Matrix Size Effect and Anisotropy Study 
A series of tests were run on 2-in. (51 mm) nonlithophysal Tptpll samples from the same outcrop 
boulder to examine the impact of saturation level on uniaxial compressive strength. It is 
impossible to accurately control moisture content at specific levels of saturation for a rock 
sample, so a number of tests aimed at fully drying and saturating and allowing the samples to 
equilibrate at room humidity conditions were run as shown in Table E-12. As seen in this table, 
the presence of moisture has a significant effect on compressive strength, particularly whether 
the samples are under heated-dry or exposed to humid air conditions. Complete drying of 
samples increases the mean strength of the samples tested by approximately 20 percent. This 
strength decrease in the presence of moisture is consistent with other testing of silicic rocks and 
is typical stress-corrosion mechanism involving chemical alterations due to moisture in flaws 
within the samples. The compression test data reported here is, unless otherwise noted, at room 
humidity conditions. Following a conservative design approach, performance calculations 
performed for ground support or postclosure effects consider average strength conditions from 
room temperature testing, with data ranges to cover fully saturated conditions. 
ANL-EBS-MD-000027 REV 03 E-43 September 2004 

Drift Degradation Analysis 
Table E-12. Impact of Moisture Conditions on Uniaxial Compressive Strength of Nonlithophysal Tptpll 
Samples 
Test Condition Moisture Condition Mean Strength (MPa) 
1 Samples dried by slow heating to 200C, tested at 200C 213 
2 
Samples dried by slow heating to 200C, then slowly cooled 
in dry environment, exposed to room humidity for about 30 
minutes and tested at room temperature 
176 
3 Samples allowed to equilibrate with room humidity, tested at 
room temperature 158 
4 Samples water saturated, tested at room temperature 149 
NOTE: Strengths are mean values from testing of 51 mm diameter samples at each moisture condition. 
NOTE: Results from the 2003 testing of Tptpln/Tptpll samples (DTN: SN0306L0207502.008 [DIRS 165015]) are 
compared to previous testing of samples from the Tptpmn (Price 1986 [DIRS 106589]). 
Figure E-20. Results of Size Effect Study Showing Variation in Sample Uniaxial Compressive Strength 
as a Function of Sample Volume 
ANL-EBS-MD-000027 REV 03 E-44 September 2004 

Drift Degradation Analysis 
50 
40 
Young's Modulus (GPa) 
30 
20 
10 
0 
123 
34.3 33.6 
37.1 
Group 
Source: Developed from source data provided by DTN: SN0306L0207502.008. 
NOTE: Four block samples were used in the mechanical anisotropy study (see Figure E-19), including a total of 57 
specimens cored from these samples in three mutually perpendicular directions. For each of the four 
blocks, an average Youngs modulus was determined for each direction. This provides the orientation with 
the largest, medium, and smallest Youngs modulus value for each block. Group 1 is the average of the 
largest values from each block, Group 2 is the average of the medium values from each block, and Group 3 
is the average of the smallest values from each block. The averages of the 57 specimens show a maximum 
of 10.6 percent anisotropy in the average Youngs modulus. 
Figure E-21. Anisotropy in Youngs Modulus of Nonlithophysal Tptpll Matrix for Three Mutually 
Perpendicular Coring Directions 
E4.2 ASSESSMENT OF ROCK MASS PROPERTIES FOR THE HEATED DRIFT 
The calculation of rock mass properties for the Heated Drift in the ESF is described in this 
section, and also documented in the Microsoft Excel file, rock mass strength v2.xls, worksheet 
Heated Drift (Table A-1). Rock mass properties are calculated using the Hoek-Brown failure 
criterion (Hoek et al. 2002 [DIRS 162204], Section 2), which is expressed as 
.a
.
s =s3 +sci .. mb 
s3 + s .. (Eq. E-9) 
1
.sci . 
where s1 and s3 are the major and minor effective principle stresses at failure 
sci is the uniaxial compressive strength of the intact rock material 
mb, s, and a are material constants. 
This approach uses the Geological Strength Index (GSI) to characterize rock mass strength 
(Hoek et al. 2000 [DIRS 160539], pp. 91 to 97). Rock mass classification data using the Q 
system has been collected in the Heated Drift (Table E-13). To apply Q system data to estimate 
the strength of jointed rock masses, the Q system parameters related to stress (i.e., Jw and SRF) 
ANL-EBS-MD-000027 REV 03 E-45 September 2004 

Drift Degradation Analysis 
should be set equal to 1, which is equivalent to a dry rock mass subjected to medium stress 
conditions (Hoek et al. 2000 [DIRS 160539], pp. 96 to 97), such that: 
GSI = 9 lnQ + 44 (Eq. E-10) 
.
.
.
..
RQD
J
..
..
..
where Q= 
(Eq. E-11) 
r

J 
J
.
n 
a 
RQD = rock quality designation 
Jn = joint set number 
Jr = joint roughness number 
Ja = joint alteration number. 
The material constants mb, s, and a are given by 
GSI
-
100
..
.
..
. 
(Eq. E-12) 
m 
mi exp
=
b 
D
28
-
14 
GSI
-
100
...
exp
..
. 
(Eq. E-13) 
s
=
D
9
-
3 
1 
1 
15 
GSI
3 
20
-
-
..
. 
...
- 
(Eq. E-14) 
+
a 
e 
e
=
26
where mi is the value of mb for intact rock and is determined based on laboratory triaxial test 
data, and D is a factor that depends on the degree of disturbance to which the rock mass has been 
subjected by blast damage and stress relaxation. D is 0 for the mechanically excavated tunnels in 
the ESF. 
Following the approach by Hoek et al. (2002 [DIRS 162204], Section 3), the rock mass modulus 
of deformation is given by 
D
(GSI 
40)10-
..
.
..
.

10
E 
1
-
for s ci > 100 MPa (Eq. E-15)
=
m 
2 
cis
D
(GSI 
40)10-
for sci = 100 MPa (Eq. E-16)
..
.
..
.
E 
1
-
10
=

m 
2 
100 
where Em is the rock mass modulus of deformation in GPa. 
ANL-EBS-MD-000027 REV 03 E-46 September 2004 

Drift Degradation Analysis 
The global rock mass strength is determined as 
a 1
- 
m
b 
4 
...
)
...
(
m
b
+
4
s
-
m a 
( 
b
-
8)
+
s
s 
cm ci 
1 2 
Table E-13. Q System Rock Mass Classification Data from the Heated Drift 
(
s
s
= 
. (Eq. E-17) 
2
(
)
)
+
+
a 
a 
Tunnel 
Station 
Interval 
(m) 
Lithostratigraphic 
Unit 
Thermal-
Mechanical Unit 
Q System Parameters 
RQD Jn Jr Ja 
0 5 Tptpmn TSw2 80 12 3 2 
5 10 Tptpmn TSw2 Not rated due to plate loading niche. 
10 15 Tptpmn TSw2 78 9 1 2 
15 20 Tptpmn TSw2 69 12 1 2 
20 25 Tptpmn TSw2 90 12 3 2 
25 30 Tptpmn TSw2 76 9 3 2 
30 35 Tptpmn TSw2 77 9 3 2 
35 40 Tptpmn TSw2 67 9 3 2 
40 45 Tptpmn TSw2 83 15 3 2 
45 50 Tptpmn TSw2 58 15 3 2 
50 55 Tptpmn TSw2 59 15 2 2 
55 60 Tptpmn TSw2 54 15 2 2 
Source: DTN: GS970608314224.007 [DIRS 158430]. 
NOTE: Q system parameters can be accessed through USGS 1997 [DIRS 169040], which is linked to the Source 
DTN. 
The calculation of the mean intact rock strength, sci, is documented in Table E-14. The value of 
the material constant for intact rock, mi, is 33.87, which is documented in the Subsurface 
Geotechnical Parameters Report (BSC 2003 [DIRS 166660], Table 8-39). 
The results of the calculation of rock mass properties for the Heated Drift using the approach 
described above are provided in Table E-15, with additional documentation provided in the 
Microsoft Excel file, rock mass strength v2.xls (Table A-1). 
Table E-14. Intact Compressive Strength Data for the Tptpmn Unit a 
Number 
1 
Specimen Number 
(also referred to as Sample 
Number) 
NRG-6-720.7-SNL-A 
Ultimate Differential Strength 
(also referred to as 
Compressive Strength) (MPa) 
235.5 
Original Source DTN 
2 
3 
4 
NRG-6-742.3-SNL-A 
NRG-6-742.9-SNL-A 
NRG-6-762.9-SNL-A 
162.3 
212.8 
112.1 
SNL02030193001.004 
[DIRS 108415] 
5 NRG-6-773.5-SNL-A 117.4 
ANL-EBS-MD-000027 REV 03 E-47 September 2004 

Drift Degradation Analysis 
Table E-14. Intact Compressive Strength Data for the Tptpmn Unit a (Continued) 
Number 
Specimen Number 
(also referred to as Sample 
Number) 
Ultimate Differential Strength 
(also referred to as 
Compressive Strength) (MPa) Original Source DTN 
6 NRG-6-784.8-SNL-A 223.0 
SNL02030193001.004 
[DIRS 108415] 
7 NRG-6-785.6-SNL-A 218.6 
8 NRG-6-806.8-SNL-A 261.9 
9 NRG-5-847.2-SNL-A 84.2 
SNL02030193001.012 
[DIRS 108416] 
10 NRG-5-849.4-SNL-A 240.8 
11 NRG-5-861.2-SNL-A 55.3 
12 NRG-5-873.4-SNL-A 38.4 
13 NRG-5-887.2-SNL-A 240.9 
SNL02030193001.012 
[DIRS 108416] 
14 NRG-5-888.8-SNL-A 288.9 
15 NRG-5-891.9-SNL-A 253.5 
16 NRG-5-896.5-SNL-A 184.7 
17 NRG-7/7A-777.0-SNL-A 143.8 
SNL02030193001.019 
[DIRS 108431] 
18 NRG-7/7A-800.2-SNL-A 179.2 
19 NRG-7/7A-806.3-SNL-A 225.4 
20 NRG-7/7A-818.5-SNL-A 126.3 
21 NRG-7/7A-859.2-SNL-A 118.8 
22 NRG-7/7A-865.4-SNL-I 215.8 
23 NRG-7/7A-865.4-SNL-J 232.0 
24 NRG-7/7A-865.4-SNL-K 239.1 
25 NRG-7/7A-865.4-SNL-L 248.5 
26 SD-12-734.7-SNL-B 193.3 SNL02030193001.023 
[DIRS 108435] 27 SD-12-781.1-SNL-B 198.2 
28 SD-9-761.5-SNL-A 231.5 
SNL02030193001.026 
[DIRS 108436] 
29 SD-9-768.7-SNL-A 254.5 
30 SD-9-771.7-SNL-A 160.8 
31 SD-9-774.6-SNL-B 60.1 
32 SD-9-826.7-SNL-A 224.9 
33 SD-9-832.8-SNL-C 183.3 
34 SD-9-842.1-SNL-E-1 208.9 
35 GU-3 760.9/1A 210.3 
SNSAND83164600.000 
[DIRS 160009] 
36 GU-3 760.9/1B 234.4 
37 GU-3 760.9/2A 215.5 
38 GU-3 760.9/2B 221.4 
39 GU-3 760.9/3A 245.2 
40 GU-3 760.9/3B 222.2 
41 GU-3 760.9/4A 205.2 
42 GU-3 760.9/4B 183.5 
43 GU-3 760.9/5A 229.7 
44 GU-3 760.9/5B 226.4 
45 10/AE/2/Z 109.0 SNSAND85076200.000 
ANL-EBS-MD-000027 REV 03 E-48 September 2004 

Drift Degradation Analysis 
Table E-14. Intact Compressive Strength Data for the Tptpmn Unit a (Continued) 
Number 
Specimen Number 
(also referred to as Sample 
Number) 
Ultimate Differential Strength 
(also referred to as 
Compressive Strength) (MPa) Original Source DTN 
46 10/AE/46/Z 143.0 [DIRS 160024] 
47 10/AE/9/Z 153.0 
48 10-AE-3Y 53.7 
49 10-AE-6X 107.0 
50 10-AE-8X 62.4 
51 G4-686.6-A 270.0 SNSAND84110100.000 
[DIRS 160016] 52 G4-686.6-D 326.0 
53 G4-686.6-G 180.0 
SNSAND84110100.000 
[DIRS 160016] 
54 G4-742.75-E 235.0 
55 G4-742.75-F 256.0 
56 G4-742.75-G 279.0 
57 G4-748.6-A 196.0 
58 G4-748.6-B 190.0 
59 G4-749.0-A 268.0 
60 G4-749.0-B 188.0 
61 10X12 126.8 
SNSAND85070900.000 
[DIRS 160022] 
62 10Y47 143.2 
63 10Z15 158.4 
64 12A2 203.2 
65 12A3 132.2 
66 13A2 113.3 
67 26A1 200.5 
68 26B1 111.7 
69 26C1 274.3 
70 26D1 198.6 
71 26E1 241.3 
72 28A2 104.3 
Mean 188.8 
 
Standard Deviation 63.7 
a 
Intact compressive strength data are qualified and summarized in DTN: MO0311RCKPRPCS.003 [DIRS 166073]. 
The data can be found by downloading the data file from this DTN, and searching for the data using the Specimen 
Number. The intact compressive strength data from the Tptpmn unit have been selected according to test 
conditions to provide a consistent data set. Data with the following test conditions were selected: ambient 
temperature conditions, saturated samples, nominal strain rate of 10-5 S-1, with sample diameters ranging from 
about 25.4 mm to 50.8 mm. 
ANL-EBS-MD-000027 REV 03 E-49 September 2004 

Drift Degradation Analysis 
Table E-15. Calculated Rock Mass Properties for the Heated Drift 
Tunnel 
Station 
Interval 
(m) 
Lithostratigraphic Unit 
Thermal-Mechanical Unit 
Mean Intact Unconfined 
Compressive Strengtha 
(MPa)
Intact Material Constantb 
Q GSI 
Rock Mass Material 
Constants 
Global Rock Mass 
Compressive Strength 
(MPa)
Rock Mass Modulus of 
Deformation (GPa) 
sci mi mb s a scm Em 
0 5 Tptpmn TSw2 189 33.87 10.00 64.7 9.61 0.02 0.50 80.03 23.34 
5 10 Tptpmn TSw2 189 33.87 Not rated due to plate loading niche. 
10 15 Tptpmn TSw2 189 33.87 4.33 57.2 7.34 0.01 0.50 68.83 15.13 
15 20 Tptpmn TSw2 189 33.87 2.88 53.5 6.44 0.01 0.50 63.99 12.24 
20 25 Tptpmn TSw2 189 33.87 11.25 65.8 9.98 0.02 0.50 81.78 24.81 
25 30 Tptpmn TSw2 189 33.87 12.67 66.9 10.37 0.03 0.50 83.59 26.38 
30 35 Tptpmn TSw2 189 33.87 12.83 67.0 10.41 0.03 0.50 83.80 26.56 
35 40 Tptpmn TSw2 189 33.87 11.17 65.7 9.96 0.02 0.50 81.67 24.71 
40 45 Tptpmn TSw2 189 33.87 8.30 63.0 9.05 0.02 0.50 77.35 21.19 
45 50 Tptpmn TSw2 189 33.87 5.80 59.8 8.07 0.01 0.50 72.51 17.60 
50 55 Tptpmn TSw2 189 33.87 3.93 56.3 7.12 0.01 0.50 67.65 14.39 
55 60 Tptpmn TSw2 189 33.87 3.60 55.5 6.92 0.01 0.50 66.60 13.75 
Average Rock Mass Properties for the Heated Drift 75.25 20.01 
a 
b 
Mean intact compressive strength is from Table E-14. 
The intact material constant, m
i, is from the Subsurface Geotechnical Parameters Report (BSC 2003 
[DIRS 166660], Table 8-39). 
E4.3 ASSESSMENT OF ROCK MASS ELASTIC PROPERTIES FOR THERMAL 
MECHANICAL UNITS 
Rock mass modulus of deformation was calculated using the approach described above 
(Section E4.2), with the rock mass modulus calculated using either Equation E-15 or E-16, 
depending on the intact rock strength. The thermal-mechanical units evaluated include the TCw, 
PTn, TSw1, and TSw2. The required input data include Q system input parameters RQD, Jn, Jr, 
and Ja. These data were collected in five-meter intervals throughout the ESF, and are 
documented in the Microsoft Excel file, rock mass strength v2.xls, in worksheet Spatial Data 
(Table A-1). The mean intact unconfined compressive strength sci is used to determine the 
appropriate equation for rock mass modulus (see Equations E-15 and E-16). The calculation of 
mean intact unconfined compressive strength values for each thermal-mechanical unit is 
documented in the Microsoft Excel file, rock mass strength v2.xls, in worksheet Intact Strength 
(Table A-1). The calculation of rock mass modulus of deformation for each five-meter tunnel 
interval throughout the ESF is documented in the Microsoft Excel file, rock mass strength v2.xls, 
in worksheet Spatial Data (Table A-1). Using the standard data functions of Microsoft Excel, 
these data were sorted by thermal-mechanical unit, rank-ordered by rock mass modulus, and 
placed in the worksheet, Sorted by TM Unit. The cumulative frequency of occurrence was 
ANL-EBS-MD-000027 REV 03 E-50 September 2004 

Drift Degradation Analysis 
calculated in this worksheet, and five rock mass quality categories were identified for each 
thermal-mechanical unit to represent the range of property values, corresponding to cumulative 
frequencies of occurrence of 5, 20, 40, 70, and 90 percent. The calculated rock mass modulus 
values for each thermal-mechanical unit are summarized in Table E-16. The rock mass modulus 
data in Table E-16 were adjusted so that the upper bound limit did not exceed the mean intact 
Youngs modulus. Mean intact Youngs modulus values for thermal-mechanical units are 
calculated in the Microsoft Excel file, rock mass strength v2.xls, in worksheet Intact Strength 
(Table A-1). Rock mass modulus values corresponding to rock mass category 3 were selected 
for use in the thermal-mechanical assessment of stress within the rock mass (Section 6.2). 
Empirical relationships to estimate rock mass Poissons ratio from rock mass classification data 
are not available, and in situ test Poissons ratio data are limited. It is considered that the mean 
values for intact rock from each thermal-mechanical unit are representative of the rock mass 
Poissons ratio (Table E-16). 
E4.4 ASSESSMENT OF BLOCK STRENGTH FOR NONLITHOPHYSAL ROCK 
The strength of large-scale intact rock block material (i.e., between joints) for nonlithophysal 
rock is calculated based on available size-effect laboratory compression test data from Price 
(1986 [DIRS 106589]). The size-effect data are presented in Table E-17, and plotted in 
Figure E-22. Figure E-22 also shows a best-fit curve of the size effect data developed by Price 
(1986 [DIRS 106589], p. 7) together with the Hoek and Brown (1982 [DIRS 120981], p. 156) 
relationship between unconfined compressive strength and specimen diameter. The equation by 
Price (1986 [DIRS 106589]) for the best-fit curve was used to extrapolate the size-effect data to a 
sample size of 3 m (Figure E-22). Based on this extrapolation, a strength of 70 MPa was 
selected as representative of the large-scale intact rock block material for nonlithophysal rock. 
Table E-16. Rock Mass Poissons Ratio and Modulus of Deformation Values for Thermal Mechanical 
Units 
Data Range 
Rock Mass 
Thermal-Mechanical 
Unit 
Rock Mass Poissons 
Ratioa 
Rock Mass Modulus of 
Deformation (GPa) 
Modulus of 
Deformation, Em 
(GPa) 
Rock Mass 
Quality 
Category 
7.3 1 
12.9 2 
TCw 0.22 16.1 16.1 3 
23.2 4 
27.8 5 
2.2 1 
2.2 2 
PTn 0.23 2.2 2.2 3 
2.2 4 
2.2 5 
ANL-EBS-MD-000027 REV 03 E-51 September 2004 

Drift Degradation Analysis 
Table E-16. Rock Mass Poissons Ratio and Modulus of Deformation Values for Thermal Mechanical 
Units (Continued) 
Data Range 
Rock Mass 
Thermal-Mechanical 
Unit 
Rock Mass Poissons 
Ratioa 
Rock Mass Modulus of 
Deformation (GPa) 
Modulus of 
Deformation, Em 
(GPa) 
Rock Mass 
Quality 
Category 
8.6 1 
12.8 2 
TSw1 0.25 17.3 17.3 3 
23.5 4 
23.5 5 
9.4 1 
12.9 2 
TSw2 0.21 15.8 15.8 3 
21.5 4 
28.0 5 
a 
Recent field test data in the Tptpll that indicate a mean rock mass Poissons ratio of 0.2 
(DTN: SN0208F4102102.002 [DIRS 161874]) compared to a mean intact Poissons ratio of 0.21 (CRWMS M&O 
1997 [DIRS 103564], Table 5-27). Therefore, rock mass Poissons ratio values in this table are based on 
laboratory test data. The calculation of mean Poissons ratio values is documented in the Microsoft Excel file, 
rock mass strength v2.xls, in worksheet Intact Strength (Table A-1). 
Table E-17. Size-Effect Laboratory Compression Test Data for Nonlithophysal Rock 
Row # Test Specimen Number 
Specimen Diameter 
(mm) 
Uniaxial Compressive 
Strength, (sax)u (MPa) 
1 1 12A2 25.4 203.2 
2 1 12A3 25.4 132.2 
3 1 13A2 25.4 113.3 
4 2 26C1 25.4 274.3 
5 2 26D1 25.4 198.6 
6 2 26E1 25.4 241.3 
Mean value 193.82 
7 1 10X12 50.8 126.8 
8 1 10Y47 50.8 143.2 
9 1 10Z15 50.8 158.4 
10 2 26A1 50.8 200.5 
11 2 26B1 50.8 111.7 
12 2 28A2 50.8 104.3 
Mean value 140.82 
13 1 10E3 82.6 141.7 
14 1 10E4 82.6 99.8 
15 1 11A1 82.6 130.6 
16 1 11A2 82.6 87.7 
ANL-EBS-MD-000027 REV 03 E-52 September 2004 

Drift Degradation Analysis 
Table E-17. Size-Effect Laboratory Compression Test Data for Nonlithophysal Rock (Continued) 
Row # Test Specimen Number 
Specimen Diameter 
(mm) 
Uniaxial Compressive 
Strength, (sax)u (MPa) 
17 1 11C1 82.6 124.3 
18 1 11D1 82.6 131.8 
19 2 211 82.6 160.7 
20 2 231 82.6 140.7 
21 2 271 82.6 58.9 
Mean value 119.57 
22 1 10A1 127.0 59.9 
23 1 10A2 127.0 84.3 
24 1 10C1 127.0 92.4 
25 1 10C2 127.0 98.2 
26 1 10D1 127.0 89.8 
27 1 10D2 127.0 69.7 
28 2 221 127.0 134.3 
29 2 234 127.0 85.8 
30 2 261 127.0 170.8 
31 2 281 127.0 90.4 
32 2 282 127.0 98.8 
Mean value 97.67 
33 2 222 228.6 86.9 
34 2 282 228.6 93.4 
Mean value 90.14 
Source: DTN: MO0311RCKPRPCS.003 [DIRS 166073] (see native data file, DTN SEP data file revised2.xls, 
rows 519-528, 532-533, and 542-563, from worksheet basic data DTN). 
ANL-EBS-MD-000027 REV 03 E-53 September 2004 

Drift Degradation Analysis 
Compressive Strength (MPa) 
300 
250 
200 
150 
100 
50
0 50 100 150 200
Sample Size (mm)
l () l() 
(sax)ui193.82 
140.82 
119.57 
97.67 
90.14 
Mean vaueMPa fromaboratory test data 
Sample Size (mm) Compressive Strength 
MPa500 79.62 
1000 75.13 
2000 72.63 
3000 71.72 
Size Effect Extrapolated to Block Scale 
Recommended 
Block Strength 70 MPa 
= 1944 D-0.846 + 69.5 
Hoek-Brown 
equaton 
Source: Laboratory test data provided in Table E-17. Hoek-Brown equation based on Hoek and Brown (1982 
[DIRS 120981], p. 156). 
Figure E-22. Sample Size Effect on Compressive Strength Based on Laboratory Test Data for 
Nonlithophysal Rock 
E5. THERMAL PROPERTIES 
The thermal properties used in the thermal mechanical calculation of stresses at Yucca Mountain 
due to heating and cooling of the repository (Section 6.2), are provided in this section. These 
data include thermal conductivity (Table E-18), specific heat (Table E-19), and thermal 
expansion for saturated rock (Table E-20) for the various lithostratigraphic and 
thermal-mechanical units of the Yucca Mountain rock strata. The mean values for 
thermal-mechanical units are determined by averaging the thermal properties of the 
lithostratigraphic units within each thermal-mechanical unit, weighted according to the thickness 
of each lithostratigraphic unit. Additional details are provided in the Microsoft Excel file, 
thermal properties TM units v2.xls (Table A-1). 
ANL-EBS-MD-000027 REV 03 E-54 September 2004 

Drift Degradation Analysis 
Table E-18. Thermal Conductivity for Various Thermal Mechanical Units and Associated 
Lithostratigraphic Units 
Thermal Conductivityb 
Thermal Mechanical 
Unit Stratigraphic Unit Thicknessa (m) 
(W/mK) 
DTNcT = 100 C T > 100 C 
Tpcpv3 0.0 0.80 0.69 
SN0303T0503102.008 
[DIRS 162401] 
Tpcpv2 5.1 1.06 0.49 
Tpcpv1 2.4 1.06 0.49 
Tpbt4 0.5 1.06 0.49 
Tpy 3.8 1.06 0.49 
TCw / PTn Tpbt3 3.8 1.06 0.49 
Tpp 5.1 1.06 0.49 
Tpbt2 8.3 1.06 0.49 
Tptrv3 1.9 1.06 0.49 
Tptrv2 1.2 1.06 0.49 
Mean (weighted by unit thickness) 1.06 0.49 
Tptrv1 1.2 0.80 0.69 
Tptrn 35.6 1.81 1.30 
TSw1 Tptrl 6.1 1.81 1.30 
Tptpul 66.8 1.77 1.18 
SN0404T0503102.011 
[DIRS 169129] 
Mean (weighted by unit thickness) 1.77 1.22 
Tptpmn 38.3 2.07 1.42 
Tptpll 95.6 1.89 1.28 
TSw2 / TSw3 Tptpln 55.1 2.13 1.49 
Tptpv3 12.0 0.80 0.69 
SN0303T0503102.008 
[DIRS 162401] 
Mean (weighted by unit thickness) 1.92 1.33 
Tptpv2 4.7 1.06 0.49 
Tptpv1 15.4 1.06 0.49 
CHn1 / CHn2 
Tpbt1 2.0 1.06 0.49 
Calico 45.5 1.26 0.60 
Calicobt 15.9 1.26 0.60 
Mean (weighted by unit thickness) 1.21 0.57 
a 
Thickness of units extracted from DTN: MO0012MWDGFM02.002 [DIRS 153777]. The details of this extraction 
bare provided in Appendix M. 
T = temperature. 
Mean values are calculated in this report and not provided by the DTNs listed in this table. Data extracted from 
DTN: SN0404T0503102.11 [DIRS 169129] are summarized in BSC 2004 [DIRS 169854] , Table 7-10. Data 
extracted from DTN: SN0303T0503102.008 [DIRS 162401] are summarized in BSC 2004 [DIRS 170033], 
Table 6-13. 
ANL-EBS-MD-000027 REV 03 E-55 September 2004 

Drift Degradation Analysis 
Table E-19. Specific Heat for Various Thermal Mechanical Units and Associated Lithostratigraphic Units 
Thermal 
Mechanical 
Unit 
Stratigraphic 
Unit Thicknessa (m) 
Specific Heatb (J/kgK) 
DTNcT = 95C95C<T<114CT> 114C 
Tpcpv3 0.0 1.2E+03 8.4E+03 1.0E+03 
SN0307T0510902.003 
[DIRS 164196] 
Tpcpv2 5.1 1.2E+03 8.4E+03 1.0E+03 
Tpcpv1 2.4 1.3E+03 9.1E+03 1.0E+03 
Tpbt4 0.5 1.3E+03 9.1E+03 1.0E+03 
Tpy 3.8 1.3E+03 9.1E+03 1.0E+03 
TCw / PTn Tpbt3 3.8 1.3E+03 9.1E+03 1.0E+03 
Tpp 5.1 1.3E+03 9.1E+03 1.0E+03 
Tpbt2 8.3 1.3E+03 9.1E+03 1.0E+03 
Tptrv3 1.9 1.3E+03 9.1E+03 1.0E+03 
Tptrv2 1.2 1.3E+03 9.1E+03 1.0E+03 
Mean (weighted by unit thickness) 1.3E+03 9.0E+03 1.0E+03 
Tptrv1 1.2 8.9E+02 1.8E+03 9.9E+02 
Tptrn 35.6 8.9E+02 2.7E+03 9.9E+02 
TSw1 Tptrl 6.1 8.9E+02 2.7E+03 9.9E+02 
Tptpul 66.8 9.4E+02 3.6E+03 9.9E+02 
Mean (weighted by unit thickness) 9.2E+02 3.2E+03 9.9E+02 
Tptpmn 38.3 9.1E+02 3.0E+03 9.9E+02 
Tptpll 95.6 9.3E+02 3.3E+03 9.9E+02 
TSw2 / TSw3 Tptpln 55.1 9.0E+02 2.8E+03 9.9E+02 
Tptpv3 12.0 9.1E+02 1.7E+03 1.0E+03 
Mean (weighted by unit thickness) 9.1E+02 3.0E+03 9.9E+02 
Tptpv2 4.7 1.1E+03 5.1E+03 1.0E+03 
Tptpv1 15.4 1.2E+03 6.4E+03 1.1E+03 
CHn1 / CHn2 
Tpbt1 2.0 1.2E+03 6.4E+03 1.1E+03 
Calico 45.5 1.4E+03 9.8E+03 1.1E+03 
Calicobt 15.9 1.2E+03 7.6E+03 1.1E+03 
Mean (weighted by unit thickness) 1.3E+03 8.4E+03 1.1E+03 
a Thickness of units provided in Appendix M. 
b 
T = temperature. 
c Mean values are calculated in this report and not provided by the DTNs listed in this table. 
Table E-20. Thermal Expansion for Various Thermal Mechanical Units 
Thermal 
Mechanical Unit 
Thermal Expansion Coefficient (/C) 
25C < T = 50C 50C < T = 75C 75C < T = 100C 100C < T = 125C 
TCw 7.0910-6 7.6210-6 8.0810-6 10.3410-6 
PTn 4.4610-6 4.2810-6 -1.4510-6 -30.4210-6 
TSw1 6.5610-6 7.3210-6 6.8310-6 6.9210-6 
TSw2 7.1410-6 7.4710-6 7.4610-6 9.0710-6 
T = temperature 
NOTE: Source data provided by DTN: SNL01B05059301.006 [DIRS 129168]. Thermal expansion data are for 
saturated rock. The calculation of mean data is documented in Brodsky et al. (1997 [DIRS 100653], 
Table 4-4). 
ANL-EBS-MD-000027 REV 03 E-56 September 2004 

Drift Degradation Analysis 
APPENDIX F 
FIELD OBSERVATION OF KEY BLOCKS IN THE ECRB CROSS-DRIFT 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
FIELD OBSERVATION OF KEY BLOCKS IN THE ECRB CROSS-DRIFT 
This appendix documents the observation of key blocks in the ECRB Cross-Drift, including the 
Tptpul unit (Stations 0+00 to 10+15), the Tptpmn unit (Stations 10+15 to 14+44), the Tptpll unit 
(Stations 14+44 to 23+26), and the Tptpln unit (Stations 23+26 to 25+85) (Mongano et al. 1999 
[DIRS 149850], pp. 105 and 106). Additional descriptions of key blocks in the ECRB 
Cross-Drift are provided in Section 6.1.5. Portions of the full periphery geologic maps 
containing key blocks are presented in Figures F-1 through F-14. An explanation of symbols on 
the full periphery geologic maps is provided in Figure F-1. The potential key blocks are 
identified on these maps as exposed fracture faces bounded by joints. The number of blocks per 
kilometer observed in the ECRB Cross-Drift (Table F-1) was determined by identifying the 
number of key blocks in each lithologic unit as indicated in Figures F-2 through F-14 over the 
total length of drift in the unit. 
Table F-1. Number of Key Blocks Observed in the ECRB Cross-Drift 
Lithologic Unit 
Metric Stationinga 
(m) 
Length of Driftb 
(km) Number of Blocksc 
Blocks per 
Kilometer 
Tptpul 0+00 to 10+15 1.02 3 3 
Tptpmn 10+15 to 14+44 0.43 17 40 
Tptpll 14+44 to 23+26 0.88 0 0 
Tptpln 23+26 to 25+85 0.26 2 8 
a 
b 
Mongano et al. (1999 [DIRS 149850], pp. 105 and 106). 
Based on metric stationing (e.g., for the Tptpmn unit, length = (1444 m - 1015 m) / 1000 = 0.43 km). 
The observation of key blocks is documented in Figures F-2 through F-14. 
ANL-EBS-MD-000027 REV 03 F-1 September 2004 

Drift Degradation Analysis 
Figure F-1. Explanation of Symbols on Full Periphery Geologic Maps 
Key-block location 
ANL-EBS-MD-000027 REV 03 F-2 September 2004 

ANL-EBS-MD-000027 REV 03 F-3 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.003 [DIRS 108404]. 
Figure F-2. Key-Block Location, Tptpul Unit, ECRB Cross-Drift Stations 8+60 to 9+00 

ANL-EBS-MD-000027 REV 03 F-4 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.003 [DIRS 108404]. 
Figure F-3. Key-Block Location, Tptpul Unit, ECRB Cross-Drift Stations 9+00 to 9+30 

ANL-EBS-MD-000027 REV 03 F-5 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.003 [DIRS 108404]. 
Figure F-4. Key-Block Location, Tptpul Unit, ECRB Cross-Drift Stations 9+64 to 10+00 

ANL-EBS-MD-000027 REV 03 F-6 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-5. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 10+30 to 10+60 

ANL-EBS-MD-000027 REV 03 F-7 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-6. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 10+60 to 11+00 

ANL-EBS-MD-000027 REV 03 F-8 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-7. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 11+00 to 11+30 

ANL-EBS-MD-000027 REV 03 F-9 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-8. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 11+30 to 11+60 

ANL-EBS-MD-000027 REV 03 F-10 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-9. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 11+60 to 12+00 

ANL-EBS-MD-000027 REV 03 F-11 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-10. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 12+00 to 12+30 

ANL-EBS-MD-000027 REV 03 F-12 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-11. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 13+00 to 13+30 

ANL-EBS-MD-000027 REV 03 F-13 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-12. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 13+60 to 14+00 

ANL-EBS-MD-000027 REV 03 F-14 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.004 [DIRS 108405]. 
Figure F-13. Key-Block Location, Tptpmn Unit, ECRB Cross-Drift Stations 14+00 to 14+30 

ANL-EBS-MD-000027 REV 03 F-15 September 2004 
Drift Degradation Analysis 
Source: GS990408314224.006 [DIRS 108409]. 
Figure F-14. Key-Block Location, Tptpln Unit, ECRB Cross-Drift Stations 23+65 to 24+00 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 F-16 September 2004 

Drift Degradation Analysis 
APPENDIX G 
NATURAL ANALOGUES OF THE EFFECT OF SEISMIC EVENTS ON THE 
DEGRADATION OF UNDERGROUND STRUCTURES 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
NATURAL ANALOGUES OF THE EFFECT OF SEISMIC EVENTS ON THE 
DEGRADATION OF UNDERGROUND STRUCTURES 
G1. ANALOGUES OF MAJOR EARTHQUAKES 
On July 28, 1976, a magnitude 7.8 earthquake occurred in Tang-Shan, China, a city with both 
substantial mining and industrial facilities. Surface shaking intensities at Tang-Shan were such 
that in the area where the strongest shaking occurred, 80 to 90 percent of the surface structures 
collapsed. However, for important engineered structures immediately below the surface, there 
was generally no serious damage regardless of the depth or size of the structure (Wang 1985 
[DIRS 151821], p. 741). 
The USGS reported in the lessons and conclusions of the Alaskan earthquake on March 28, 1964 
that no significant damage was reported to underground facilities, including mines and tunnels, 
as a result of the earthquake, although some rocks were shaken loose in places. The epicenter of 
the earthquake is shown in Figure G-1. Included in this analysis were studies of the coal mines 
in the Matanuska Valley, which were undamaged; the railroad tunnels near Whittie; the tunnel 
and penstocks at the Eklutna Hydroelectric Project; and the Chugach Electric Association tunnel 
between Cooper Lake and Kenai Lake. There were also no reports of damage to the oil and gas 
wells in and along Cook Inlet. The reports of no damage from the Alaskan earthquake are 
significant. With a moment magnitude is 9.2 (Kanamori 1977 [DIRS 167797], p. 2982), this 
earthquake was one of the largest to occur in this country, and surface damage was extreme 
(Pratt et al. 1978 [DIRS 151817], p. 32). 
G2. ANALOGUE OF A RECENT EARTHQUAKE 
An example of a more recent earthquake can be found in the January 16, 1995, earthquake in 
Kobe, Japan, which had a magnitude of 6.9 (Bolt 1997 [DIRS 167798], p. 273). In this 
earthquake, tunnels in the epicentral region experienced no major damage (partial or total 
collapse) for peak ground accelerations measured at the surface of approximately 0.6 g (Savino 
et al. 1999 [DIRS 148612]). 
G3. ANALOGUE OF A SITE-SPECIFIC EARTHQUAKE 
On June 29, 1992, a magnitude 5.6 earthquake occurred at Little Skull Mountain about 20 km 
from Yucca Mountain. Within days of the earthquake, a team of scientists examined the interior 
of the tunnel 125 meters deep in the epicentral region of the earthquake. The team reported no 
evidence of damage in the tunnel that could be associated with the earthquake (Savino et al. 1999 
[DIRS 148612]). 
ANL-EBS-MD-000027 REV 03 G-1 September 2004 

Drift Degradation Analysis 
Source: Eckel 1970 [DIRS 157493]. 
Figure G-1. Epicenter of the 1964 Alaskan Earthquake 
ANL-EBS-MD-000027 REV 03 G-2 September 2004 

Drift Degradation Analysis 
G4. DISCUSSION 
Underground facilities in general are less prone to seismic damage than surface facilities. 
In fact, earthquake design features are low on the list of design priorities for underground 
construction projects (Rowe 1992 [DIRS 156898]). Nevertheless, case studies where 
underground facilities subjected to earthquake received significant damage have been reported 
(Sharma and Judd 1991 [DIRS 154505]; Rowe 1992 [DIRS 156898]; Raney 1988 
[DIRS 147173]). These cases are in general characterized by either shallow overburden (Sharma 
and Judd 1991 [DIRS 154505]), poor ground condition (Rowe 1992 [DIRS 156898]), fault 
intersection (Stevens 1977 [DIRS 154501]; Rowe 1992 [DIRS 156898]), or are near the 
epicenter (Stevens 1977 [DIRS 154501]; Raney 1988 [DIRS 147173]). Sharma and Judd (1991 
[DIRS 154505]) generated an extensive database of seismic damage to underground structures 
using 192 case histories. They reported that there is considerably less damage at depths greater 
than 50 m, and no heavy damage below 300 m. Rowe (1992 [DIRS 156898]) stated that total 
collapse of a civil engineering tunnel is invariably associated with the movement of an 
intersecting fault, and tunneling in soft, poor-quality ground is more susceptible to damage from 
earthquakes than those constructed in hard, competent rock. Stevens (1977 [DIRS 154501]) 
concluded that severe damage is inevitable when a mine or tunnel intersects a fault along which 
movement occurs and mines in the epicentral region of strong motions may suffer severe damage 
by shaking. Raney (1988 [DIRS 147173]) reported the effects of selected earthquakes in the 
western North American intermontane region and provided the observation of subsurface 
damages for 28 earthquakes. No damage was reported in 22 earthquakes and minor damage with 
spalling reported for 3 earthquakes. For the 3 cases with reporting damage, a considerable 
portion of mine tunnels was caved at Kennedy, Nevada near the epicenter for the 1915 Pleasant 
Valley, Nevada earthquake. No details were provided for the other 2 cases: the Quality Mine 
after the 1934 Excelsior Mountains earthquake (southeast of Hawthorne, Nevada) and Kraken 
Hill Mine after the 1983 Borah Peak, Idaho earthquake. 
ANL-EBS-MD-000027 REV 03 G-3 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
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Drift Degradation Analysis 
APPENDIX H 
3DEC PROGRAM MODIFICATION AND MODEL OPTIMIZATION 
FOR ROCKFALL ANALYSIS 
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Drift Degradation Analysis 
3DEC PROGRAM MODIFICATION AND MODEL 
OPTIMIZATION FOR ROCKFALL ANALYSIS 
H1. INTRODUCTION 
Although 3DEC is fully capable for dynamic rockfall calculations, program modifications and 
optimization of the computer model are required in order to solve complex rockfall problems 
within a reasonable time frame. The complexity of the rockfall problems includes: 
 Incorporating field fracture geometries with relatively short trace length 
 Subjecting the rock mass to postclosure ground motion time histories 
 Subjecting the rock mass to thermal stresses induced from emplaced waste 
 Conducting a large number of analyses to obtain a statistically meaningful rockfall 
frequency and size distribution. 
H2. 3DEC PROGRAM MODIFICATION 
Modifications of the 3DEC program for rockfall analyses include: (1) free-field boundaries, 
(2) partial density scaling for dynamic analysis, and (3) variable mechanical properties within a 
contact. A detailed description of the implementation and verification of these enhancements is 
provided by Lemos and Damjanac (2002 [DIRS 162058]). These modifications are included in 
the qualified version of 3DEC (Version 2.01). The areas of modification were validated during 
software qualification process. This appendix provides a brief description of these modifications 
and their relevance to rockfall analyses. 
H2.1 FREE-FIELD BOUNDARIES 
The free-field boundaries ensure that plane waves propagating upward suffer no distortion at the 
boundary because the free-field grid supplies conditions that are identical to those in an infinite 
model. In order to apply a free-field boundary in 3DEC, the model must be oriented such that 
the base is horizontal and its normal is in the direction of the y-axis, and the sides are vertical and 
their normals are in the direction of either the x-axis or z-axis. 
The free-field model consists of four plane free-field grids on the side boundaries of the model 
and four column free-field grids at the corners. The four corner free-field columns act as 
free-field boundaries for the plane free-field grids. The plane free-field grids are 
two-dimensional models that consider infinite extension in the direction normal to the plane. 
The column free-field grids are one-dimensional models that consider infinite extension in both 
horizontal directions. Both the plane and column grids consist of standard 3DEC zones, which 
have gridpoints constrained in such a way to achieve the infinite extension consideration. The 
zoning of free-field blocks is similar to the model side faces. The side free-field blocks have two 
gridpoints across the thickness that are linked to move together. The corner free-field meshes 
have four gridpoints at each elevation, also linked to move together. 
ANL-EBS-MD-000027 REV 03 H-1 September 2004 

Drift Degradation Analysis 
H2.2 PARTIAL DENSITY SCALING FOR DYNAMIC ANALYSIS 
Density scaling is a technique used in 3DEC in quasi-static calculations that substantially 
improves the efficiency of obtaining solutions. For the case of complex jointing models, zones 
with edge lengths much smaller than the average zone edge length are created during the 
automatic meshing procedure. These zones require very small time steps for numerical stability 
of the explicit algorithm. The critical time step is proportional to the smallest zone edge length. 
This makes the dynamic solution extremely time consuming. Density scaling only for those very 
small zones (a couple of orders of magnitude smaller than the average zone size) for dynamic 
analysis eliminates the very small time steps. The accuracy of the solution is preserved by 
keeping the change of the system inertia negligible. This scheme of partial density scaling is 
implemented in 3DEC in such a way that the user controls the amount of scaling to be 
introduced. 
H2.3 VARIABLE MECHANICAL PROPERTIES WITHIN A CONTACT 
A contact between two blocks in 3DEC is subdivided into a number of sub-contacts if the blocks 
involved in the contact are deformable. The sub-contacts are determined based on discretization 
of the block faces that create the contact. Discretization of contact into sub-contacts allows 
representation of variation of contact forces and deformation in the plane. In earlier versions of 
3DEC, mechanical properties (e.g., normal and shear stiffness, shear strength) of sub-contacts 
were assigned based on material properties of the contact they belong to. A modification of the 
code allows assignment of material properties to the sub-contacts independent of the material 
properties of the contact (to which sub-contact belongs to). This capability allows the program 
to model the finite trace length fractures from FracMan. Figure H-1 shows an example of the 
finite trace length fractures with extension of the rock bridges (i.e., the dashed lines in 
Figure H-1) to form the distinct blocks in 3DEC. 
A 
B 
C 
D 
E 
F 
G 
H 
I 
J 
K 
L 
Finite trace length fractures: AB, CD, and EF 
Rock bridges generated for block forming: 
GA, BH, IC, DJ, KE, and FL 
Figure H-1. Block Forming with Finite Trace Length Fractures and Rock Bridges in 3DEC 
ANL-EBS-MD-000027 REV 03 H-2 September 2004 

Drift Degradation Analysis 
H3. 3DEC MODEL OPTIMIZATION 
Model optimization involves two aspects: reducing the model size and increasing the time step. 
3DEC is based on a dynamic (time domain) algorithm that solves the equations of motion of the 
block system by an explicit finite difference method. A time step must be chosen that is smaller 
than some critical time step but is reasonable for solution time. 
H3.1 REDUCING THE MODEL SIZE 
The following methods are used to reduce the model size: 
A. Joints are generated within a limited domain as a representative volume around the 
drift. The representative volume extends one diameter at the side and two diameters 
on the top of the opening as shown in Figure 6-34 in Section 6.3.1.1. A sensitivity 
study of the size of the representative volume to rockfall prediction is presented in 
Section 6.3.1.6.5. 
B. Only blocks intersected by circular joints are cut during joint generation. Joints are 
sorted based on their trace length in a descending order. An algorithm is placed in the 
block cutting process to hide the blocks that are not intersected by the joint considered. 
C. Blocks that have face-face contact and their contact properties are completely solid are 
joined. That is, several blocks are merged to one if their contacts are solid. Blocks 
that have partial cracks between them are not joined. This approach allows for an 
analysis of the potential for crack extension. 
H3.2 INCREASING THE TIME STEP 
3DEC is based on a dynamic (time domain) algorithm that solves the equations of motion of the 
block system by an explicit finite difference method. The solution scheme used for the distinct 
element method is conditionally stable if the selected limiting time step satisfies both the stability 
criterion for calculation of internal block deformation as well as that for inter-block relative 
displacement. Even though explicit calculations execute very rapidly per time step, some way of 
increasing the time step is desirable in order to reduce computer time. 
The following methods are used to increase the time step: 
A. Calculation of the time steps is a function of the minimum length (zone edge length) 
and stiffness (Itasca Consulting Group 2002 [DIRS 160331], Manual/3DEC). Cutting 
blocks with random joints results in very small block edge lengths. Blocks with a 
small volume (i.e., less than 0.01m3) are deleted in the model to eliminate part of the 
blocks with small zone edge lengths. However, blocks of large volume may contain 
one or two small edges. An algorithm was developed that alters the geometry of these 
blocks and removes small edges less than 10 cm in length. The blocks were first 
detected and their geometry is stored in a data structure before they were deleted. 
New blocks are constructed within the bounds of the original blocks. In most cases, 
two close vertices are contracted into a single vertex. Faces that have both vertices 
lose one vertex. If the face already has only three vertices, then the entire face is 
ANL-EBS-MD-000027 REV 03 H-3 September 2004 

Drift Degradation Analysis 
deleted. On faces that have only one of two vertices, a new face with co-planarity of 
vertices is created. The flow chart for the algorithm is shown in Figure H-2. 
B. The method of partial density scaling was adopted for dynamic analysis. Partial 
density scaling was implemented for dynamic analysis in 3DEC as described in 
Section H2.2. A time step of 310-5 seconds is set for the analysis, which satisfies the 
stability criteria for calculation and provides a solution in a reasonable time. This 
results in an increase of system mass ranging from 1 to 4 percent. The amount of 
increase is consistent with the verification problem provided by Lemos and Damjanac 
(2002 [DIRS 162058]). The accuracy of the solution is therefore preserved by keeping 
the change of the system inertia negligible. 
ANL-EBS-MD-000027 REV 03 H-4 September 2004 

Drift Degradation Analysis 
Select block, select 
face, examine the edge 
length 
Is the edge length < 10 cm ? 
noNo modification 
required 
yes 
Block data stored in a 
separate data structure 
before deletion 
Contract the two 
vertices into one vertex 
for the identified small 
edge 
l 
iplyes 
no 
>3Check the faces including the 
affected vertices, determine the 
number of vertices for alfaces 
Face deleted 
Does the face contan both vertices 
for the small edge length ? 
New face with new 
ane based on 
co-planarity of 
vertices 
New face with one 
less vertex but 
same plane 
=3 
Figure H-2. Flow Chart for Treating the Small Edge Length Block 
ANL-EBS-MD-000027 REV 03 H-5 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
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Drift Degradation Analysis 
APPENDIX I 
BLOCK SIZE GEOMETRY 
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Drift Degradation Analysis 
BLOCK SIZE GEOMETRY 
The predicted rock blocks impacting the drip shield have many different sizes and shapes. Since 
the block geometry information is mainly used for drip shield impact calculations, the geometry 
of large blocks is provided in this appendix. A total of 7 blocks with volume greater than 2.5 m3 
(6 metric tons) was selected for presentation. Blocks with high impact energy were considered 
during the selection process. The block geometric information for each individual block is 
presented in Figures I-1 to I-7 respectively. Six different views are provided for each block to 
illustrate the complex geometry observed for most large blocks. Most of the blocks consist of 
many surfaces and some of them have highly irregular shapes that are the end result of a 
non-persistent fracture network. 
ANL-EBS-MD-000027 REV 03 I-1 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 I-2 September 2004 
Block ID #1 
Simulation Case 42 for 110-7 events 
Block Size (tons) 28.3 
Figure I-1. Block Geometry Information for Block #1 
EAST VIEWBOTTOM VIEWTOP VIEWNORTH VIEWSOUTH VIEWWEST VIEW1 m

Drift Degradation Analysis 
Block ID #2 
Simulation Case 40 for 110-5,110-6, and 110-7 events 
Block Size (tons) 19.1 
EAST VIEW WEST VIEW 
NORTH VIEW SOUTH VIEW 
TOP VIEW BOTTOM VIEW 
1 m 
Figure I-2. Block Geometry Information for Block #2 
ANL-EBS-MD-000027 REV 03 I-3 September 2004 

Drift Degradation Analysis 
Block ID #3 
Simulation Case 42 for 110-7 events 
Block Size (tons) 14.8 
EAST VIEW WEST VIEW 
NORTH VIEW SOUTH VIEW 
1 m 
BOTTOM VIEW TOP VIEW 
Figure I-3. Block Geometry Information for Block #3 
ANL-EBS-MD-000027 REV 03 I-4 September 2004 

Drift Degradation Analysis 
Block ID 
#4 
Simulation 
Case 63 for 110-7 events 
Block Size (tons) 
12.2 
EAST VIEW WEST VIEW 
NORTH VIEW SOUTH VIEW 
TOP VIEW 
BOTTOM VIEW 
1 m 
Figure I-4. Block Geometry Information for Block #4 
ANL-EBS-MD-000027 REV 03 I-5 September 2004 

Drift Degradation Analysis 
Block ID 
#5 
Simulation 
Case 60 for 110-6 and 110-7 events 
Block Size (tons) 
11.0 
EAST VIEW WEST VIEW 
NORTH VIEW SOUTH VIEW 
IBOTTOM VEW TOP VIEW 
1 m 
Figure I-5. Block Geometry Information for Block #5 
ANL-EBS-MD-000027 REV 03 I-6 September 2004 

Drift Degradation Analysis 
Block ID 
#6 
Simulation 
Case 51 for 110-7 events 
Block Size (tons) 
8.0 
EAST VIEW WEST VIEW 
NORTH VIEW SOUTH VIEW 
BOTTOM VIEW TOP VIEW 
1 m 
Figure I-6. Block Geometry Information for Block #6 
ANL-EBS-MD-000027 REV 03 I-7 September 2004 

Drift Degradation Analysis 
Block ID 
#7 
Simulation 
Case 15 for 110-5,110-6, and 110-7 events 
Block Size (tons) 
6.0 
EAST VIEW WEST VIEW 
NORTH VIEW SOUTH VIEW 
TOP VIEW BOTTOM VIEW 
1 m 
Figure I-7. Block Geometry Information for Block #7 
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Drift Degradation Analysis 
APPENDIX J 
RANDOM SELECTION OF 3DEC MODELING REGION IN A 100-M CUBE 
FRACTURE NETWORK GENERATED BY FRACMAN 
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Drift Degradation Analysis 
RANDOM SELECTION OF 3DEC MODELING REGION IN A 100-M 
CUBE FRACTURE NETWORK GENERATED BY FRACMAN 
A random selection of the 3DEC modeling region within a 100 m FracMan fracture network 
cube was conducted using the random number generation function provided in Microsoft Excels 
spreadsheet analysis tools. Each 3DEC modeling region was uniquely determined by choosing 
the centroid of the modeling block. A random number generator with a uniform distribution in 
the range of -32.5 to 32.5 was used to generate the x-, y-, and z-coordinates. The range was 
selected so that the selected region was free of edge effects. The Microsoft Excel inputs for 
random number generation are shown in Figure J-1. 
Table J-1 lists the 105 selected centroid locations. The centroids are projected to the X-Y, X-Z, 
and Y-Z planes as shown in Figures J-2 to J-4. 
Figure J-1. Microsoft Excel Inputs for Random Number Generation 
ANL-EBS-MD-000027 REV 03 J-1 September 2004 

Drift Degradation Analysis 
ion 
10.0 
X 
Y 
X-Y Project-50.0 
-40.0 
-30.0 
-20.0 
-10.0 
0.0 
10.0 
20.0 
30.0 
40.0 
50.0 
-50.0 -30.0 -10.0 30.0 50.0 
Figure J-2. Centroid Locations Projected to X-Y Plane 
X-Z Projection 
50.0 
Z 
40.0 
30.0 
20.0 
10.0 
0.0 
-30.0 -10.0 10.0 30.0 
-10.0 
-20.0 
-30.0 
-40.0 
-50.0 
-50.0 
50.0 
X 
Figure J-3. Centroid Locations Projected to X-Z Plane 
ANL-EBS-MD-000027 REV 03 J-2 September 2004 

Drift Degradation Analysis 
Y-Z Projection 
50.0 
Z 
40.0 
30.0 
20.0 
10.0 
0.0 
-30.0 -10.0 10.0 30.0 
-10.0 
-20.0 
-30.0 
-40.0 
-50.0 
-50.0 
50.0 
Y 
Figure J-4. Centroid Locations Projected to Y-Z Plane 
Table J-1. Listing of Fracture Model Region Centroid Coordinates 
Model Region 
Centroid of Fracture Model Region 
Xc Yc Zc 
1 -2.8 29.5 26.0 
2 -23.7 2.4 1.5 
3 29.5 -26.7 -26.1 
4 -16.7 4.5 32.2 
5 28.5 8.3 29.6 
6 -4.4 -20.8 -17.4 
7 -20.2 -3.1 -12.1 
8 -23.6 24.4 -17.7 
9 -7.2 -32.0 -27.0 
10 22.4 16.2 0.4 
11 -17.2 -14.2 -18.1 
12 -9.7 -27.1 -26.0 
13 -21.1 17.5 -4.2 
14 24.9 -10.4 10.8 
15 19.5 28.3 19.4 
16 -15.3 5.5 -12.3 
17 -28.1 0.3 -31.2 
18 10.6 9.8 31.5 
19 -2.3 30.2 32.4 
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Drift Degradation Analysis 
Table J-1. Listing of Fracture Model Region Centroid Coordinates (Continued) 
Model Region 
Centroid of Fracture Model Region 
Xc Yc Zc 
20 14.8 -17.7 9.0 
21 -15.6 2.9 6.9 
22 -25.3 15.5 -13.6 
23 -16.8 -11.2 -2.6 
24 18.3 0.0 -15.0 
25 17.1 10.3 32.0 
26 31.9 -12.6 31.3 
27 27.6 -18.6 -5.8 
28 21.6 -5.8 -31.9 
29 -23.6 14.0 -5.9 
30 6.6 32.3 -31.4 
31 -3.1 20.7 15.4 
32 -11.1 20.0 -17.7 
33 -29.4 26.2 -16.9 
34 -1.4 10.0 -31.0 
35 -31.5 26.1 10.7 
36 4.8 -11.1 23.7 
37 6.9 5.7 18.8 
38 29.6 -31.4 -29.3 
39 -25.1 -1.1 -29.3 
40 16.0 14.2 -8.6 
41 29.2 -4.1 -11.0 
42 26.8 22.2 -24.3 
43 -13.3 1.5 14.4 
44 14.4 14.2 24.3 
45 -29.2 23.4 -24.2 
46 5.5 24.4 -21.1 
47 18.0 26.9 24.4 
48 19.8 -14.9 0.3 
49 -18.1 -6.9 10.6 
50 14.9 12.9 -6.8 
51 11.7 9.5 29.1 
52 29.3 -18.2 -25.5 
53 -15.3 -25.5 19.6 
54 -29.5 23.5 12.3 
55 -25.6 -1.0 30.9 
56 4.3 -15.1 -14.1 
57 16.7 8.5 -27.5 
58 -22.7 -11.6 -15.7 
59 15.7 31.8 25.6 
60 0.6 -8.0 -29.1 
61 -4.8 25.4 23.7 
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Drift Degradation Analysis 
Table J-1. Listing of Fracture Model Region Centroid Coordinates (Continued) 
Model Region 
Centroid of Fracture Model Region 
Xc Yc Zc 
62 31.2 7.7 27.9 
63 -16.1 -16.7 15.0 
64 -9.6 -10.4 -32.4 
65 -25.9 -22.5 6.9 
66 29.0 18.6 -11.7 
67 -23.0 -25.1 -19.7 
68 1.0 16.8 -16.4 
69 -20.6 -1.4 23.4 
70 12.7 -4.4 -3.4 
71 -9.8 -5.8 6.8 
72 -8.8 -24.7 -28.2 
73 -24.6 -22.7 -9.9 
74 20.7 32.2 22.4 
75 -19.0 16.4 7.1 
76 23.9 -19.0 2.8 
77 24.1 -18.8 16.3 
78 -9.4 7.9 20.0 
79 -24.1 1.9 15.2 
80 26.2 3.9 -28.7 
81 17.5 10.8 -2.7 
82 -5.2 8.9 23.2 
83 5.3 16.8 -23.1 
84 19.4 -19.3 31.9 
85 22.4 -1.6 31.4 
86 20.6 -27.4 32.1 
87 11.6 -18.2 9.5 
88 -17.6 -9.2 -4.0 
89 31.6 25.8 -14.4 
90 31.2 -14.7 24.5 
91 -28.5 11.6 -8.8 
92 -30.6 -8.7 -9.7 
93 29.7 -12.2 10.5 
94 -28.2 26.5 -2.4 
95 -13.0 4.3 -26.2 
96 -29.8 1.6 23.9 
97 15.5 -26.1 4.6 
98 4.9 4.3 -14.7 
99 1.4 29.3 17.8 
100 4.8 -27.6 -17.1 
101 -23.6 9.7 23.7 
102 -12.7 -18.5 19.9 
103 0.8 -23.8 -30.4 
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Drift Degradation Analysis 
Table J-1. Listing of Fracture Model Region Centroid Coordinates (Continued) 
Model Region 
Centroid of Fracture Model Region 
Xc Yc Zc 
104 5.5 -29.0 -22.3 
105 -22.0 -23.3 25.8 
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Drift Degradation Analysis 
APPENDIX K 
SUFFICENCY OF THE NUMBER OF 3DEC SIMULATIONS TO REPRESENT THE 
ROCKFALL CHARACTERISTICS 
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Drift Degradation Analysis 
SUFFICENCY OF THE NUMBER OF 3DEC SIMULATIONS 
TO REPRESENT THE ROCKFALL CHARACTERISTICS 
This appendix addresses the issue on the sufficiency of the number of 3DEC simulations to 
represent the likely rockfall characteristics, such as block size, relative impact velocity, and 
impact energy of the rock to the drip shield. Summary statistics of the rockfall characteristics 
was compiled after each 5-run increment. The statistics, such as mean, median, maximum, and 
standard deviation, was then observed for the trend. The block size distribution was also 
observed to ensure the analyses results capture the proper rockfall size distribution. 
Figures K-1 to K-3 shows the trend of the statistics for the analyses considering the 110-4 
annual probability of exceedance ground motion with a total of 32 3DEC simulations. The 
corresponding numeric values for the statistics are tabulated in Tables K-1 to K-3. The 
maximum values of the block size, impact velocity, and impact energy occur between the 11th 
and 15th simulation. The trend shows that the statistics of rockfall characteristics approaches to 
asymptotic value approximately 15 to 20 runs of 3DEC simulation. Figure K-4 presents the 
block size cumulative distribution for the evolution of the analyses, the distribution also shows 
that approximately 15 to 20 runs of 3DEC simulation provide adequate representation of the size 
distribution. 
Table K-1. Summary Statistics of Block Size (metric ton) for 110-4 Preclosure Ground Motion 
Summary Statistics 1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs All 32 runs 
Median 0.09 0.09 0.10 0.10 0.11 0.10 
Mean 0.14 0.20 0.22 0.21 0.23 0.22 
Maximum 0.69 2.04 2.72 2.72 2.72 2.72 
Standard Deviation 0.14 0.29 0.35 0.33 0.35 0.33 
Table K-2. Summary Statistics of Impact Velocity (m/sec) for 110-4 Preclosure Ground Motion 
Summary Statistics 1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs All 32 runs 
Median 2.40 2.30 2.36 2.22 2.36 2.25 
Mean 2.51 2.47 2.58 2.47 2.57 2.43 
Maximum 6.38 6.38 7.20 7.20 7.20 7.20 
Standard Deviation 1.36 1.38 1.54 1.46 1.40 1.38 
Table K-3. Summary Statistics of Impact Energy (J) for 110-4 Preclosure Ground Motion 
Summary Statistics 1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs All 32 runs 
Median 303 290 316 249 310 232 
Mean 676 933 1196 1030 1161 1022 
Maximum 6127 10304 20358 20358 20358 20358 
Standard Deviation 1113 1828 2664 2424 2430 2224 
ANL-EBS-MD-000027 REV 03 K-1 September 2004 

Drift Degradation Analysis 
Al 
() 
i0.00 
0.50 
1.00 
1.50 
2.00 
2.50 
3.00 
1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs l 32 runs 
Block Sizemetric tonsmedan 
mean 
max 
st.dev 
Figure K-1. Summary Statistics of Block Size (metric ton) for 110-4 Preclosure Ground Motion 
() 
0.00 
1.00 
2.00 
3.00 
4.00 
5.00 
6.00 
7.00 
8.00 
1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs All 32 runs 
Impact Velocitym/secmedian 
mean 
max 
st.dev 
Figure K-2. Summary Statistics of Impact Velocity (m/sec) for 110-4 Preclosure Ground Motion 
ANL-EBS-MD-000027 REV 03 K-2 September 2004 

Drift Degradation Analysis 
0 
(J) 
5000 
10000 
15000 
20000 
25000 
1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs All 32 runs 
Impact Energymedian 
mean 
max 
st.dev 
Figure K-3. Summary Statistics of Impact Energy (J) for 110-4 Preclosure Ground Motion 
1 
Bli (ii40.00% 
50.00% 
60.00% 
70.00% 
80.00% 
90.00% 
100.00% 
0.1 10 
ock Szemetrc ton) 
Cumulatve Percentage 
1st 5 runs 
1st 10 runs 
1st 15 runs 
1st 20 runs 
1st 25 runs 
all 32 runs 
Figure K-4. Block Size Distribution for 110-4 Preclosure Ground Motion 
ANL-EBS-MD-000027 REV 03 K-3 September 2004 

Drift Degradation Analysis 
Figures K-5 to K-7 shows the trend of the statistics for the analyses considering the 110-5 
annual probability of exceedance ground motion with a total of 50 3DEC simulations. The 
corresponding numeric values for the statistics are tabulated in Tables K-4 to K-6. The 
maximum values of the block size, impact velocity, and impact energy occur between the 20th 
and 25th simulation. The trend shows that the statistics of rockfall characteristics approaches to 
asymptotic value approximately 25 to 30 runs of 3DEC simulation. Figure K-8 present the block 
size cumulative distribution for the evolution of the analyses, the distribution also shows that 
approximately 25 to 30 runs of 3DEC simulation provide adequate representation of the size 
distribution. 
Table K-4. Summary Statistics of Block Size (metric ton) for 110-5 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Median 0.09 0.10 0.12 0.11 0.13 0.12 0.12 0.12 0.12 0.12 
Mean 0.26 0.26 0.31 0.30 0.40 0.37 0.37 0.36 0.35 0.35 
Maximum 6.01 6.01 8.94 8.94 19.07 19.07 19.07 19.07 19.07 19.07 
Standard 
Deviation 0.59 0.51 0.73 0.69 1.08 0.99 0.98 0.96 0.95 0.93 
Table K-5. Summary Statistics of Impact Velocity (m/sec) for 110-5 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Median 2.58 2.55 2.52 2.51 2.60 2.53 2.60 2.60 2.55 2.57 
Mean 2.48 2.51 2.59 2.58 2.70 2.62 2.67 2.69 2.66 2.69 
Maximum 5.35 5.81 9.05 9.05 9.42 9.42 9.42 9.42 9.42 9.42 
Standard 
Deviation 1.22 1.22 1.48 1.43 1.50 1.50 1.43 1.45 1.44 1.48 
Table K-6. Summary Statistics of Impact Energy (J) for 110-5 Preclosure Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Median 288 271 318 326 391 355 364 358 343 357 
Mean 1005 1020 1190 1141 2260 2055 1899 1903 1839 1814 
Maximum 17557 19410 20913 20913 435077 435077 435077 435077 435077 435077 
Standard 
Deviation 2443 2356 2518 2414 16028 14585 12752 12346 12081 11430 
ANL-EBS-MD-000027 REV 03 K-4 September 2004 

Drift Degradation Analysis 
all 50 
(
i0.00 
5.00 
10.00 
15.00 
20.00 
25.00 
1st 5 runs 1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs runs 
Block Sizemetric ton) 
medan 
mean 
max 
st.dev 
Figure K-5. Summary Statistics of Block Size (metric ton) for 110-5 Ground Motion 
i () 
0.00 
1.00 
2.00 
3.00 
4.00 
5.00 
6.00 
7.00 
8.00 
9.00 
10.00 
1st 5 runs 1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
all 50 
runs 
Block Szemetric tonmedian 
mean 
max 
st.dev 
Figure K-6. Summary Statistics of Impact Velocity (m/sec) for 110-5 Ground Motion 
ANL-EBS-MD-000027 REV 03 K-5 September 2004 

Drift Degradation Analysis 
0 
i () 
50000 
100000 
150000 
200000 
250000 
300000 
350000 
400000 
450000 
500000 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
all 50 
runs 
Block Szemetric tonmedian 
mean 
max 
st.dev 
Figure K-7. Summary Statistics of Impact Energy (J) for 110-5 Ground Motion 
1 
Bli(i) 
li40.00% 
50.00% 
60.00% 
70.00% 
80.00% 
90.00% 
100.00% 
0.1 10 100 
ock Sze metrc tonCumuatve Percentage 
1st 5 runs 
1st 10 runs 
1st 15 runs 
1st 20 runs 
1st 25 runs 
1st 30 runs 
1st 35 runs 
1st 40 runs 
1st 45 runs 
all 50 runs 
Figure K-8. Block Size Distribution for 110-5 Ground Motion 
ANL-EBS-MD-000027 REV 03 K-6 September 2004 

Drift Degradation Analysis 
Figures K-9 to K-11 shows the trend of the statistics for the analyses considering the 110-6 
annual probability of exceedance ground motion with a total of 50 3DEC simulations. The 
corresponding numeric values for the statistics are tabulated in Tables K-7 to K-9. The 
maximum block size occurs in between the 30th and 35th simulation, whereas the maximum 
impact velocity and impact energy occurs in between the 20th and 25th simulation. The trend 
shows that the statistics of rockfall characteristics approaches to asymptotic value approximately 
30 to 35 runs of 3DEC simulation. Figure K-12 present the block size cumulative distribution 
for the evolution of the analyses, the distribution shows that approximately 25 to 30 runs of 
3DEC simulation provide adequate representation of the size distribution. 
Table K-7. Summary Statistics of Block Size (metric ton) for 110-6 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Median 0.09 0.10 0.12 0.12 0.13 0.13 0.13 0.12 0.12 0.13 
Mean 0.35 0.34 0.35 0.36 0.44 0.41 0.43 0.43 0.43 0.43 
Maximum 10.75 10.75 10.75 11.50 19.07 19.07 28.22 28.22 28.22 28.22 
Standard 
Deviation 1.01 0.85 0.85 0.91 1.16 1.06 1.37 1.35 1.35 1.30 
Table K-8. Summary Statistics of Impact Velocity (m/sec) for 110-6 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 
30 
runs 
1st 
35 
runs 
1st 
40 
runs 
1st 45 
runs 
All 50 
runs 
Median 2.97 3.01 3.10 3.06 3.11 3.02 2.97 2.98 2.98 2.97 
Mean 3.08 3.17 3.30 3.27 3.36 3.26 3.23 3.22 3.21 3.23 
Maximum 7.09 8.08 8.77 8.77 12.09 12.09 12.10 12.10 12.10 12.10 
Standard 
Deviation 1.32 1.44 1.64 1.59 1.69 1.69 1.71 1.72 1.70 1.74 
Table K-9. Summary Statistics of Impact Energy (J) for 110-6 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Median 407 475 582 563 678 574 556 550 548 576 
Mean 1455 1625 1868 1974 2521 2368 2296 2275 2288 2350 
Maximum 36584 36584 60585 60585 163657 163657 163657 163657 163657 163657 
Standard 
Deviation 3428 3743 4277 4794 7788 7868 7600 7349 7786 7704 
ANL-EBS-MD-000027 REV 03 K-7 September 2004 

Drift Degradation Analysis 
(
0.00 
5.00 
10.00 
15.00 
20.00 
25.00 
30.00 
1st 5 runs 1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Block Sizemetric ton) 
median 
mean 
max 
st.dev 
Figure K-9. Summary Statistics of Block Size (metric ton) for 110-6 Ground Motion 
i () 
0.00 
2.00 
4.00 
6.00 
8.00 
10.00 
12.00 
14.00 
1st 5 runs 1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Block Szemetric tonmedian 
mean 
max 
st.dev 
Figure K-10. Summary Statistics of Impact Velocity (m/sec) for 110-6 Ground Motion 
ANL-EBS-MD-000027 REV 03 K-8 September 2004 

Drift Degradation Analysis 
0 
i () 
20000 
40000 
60000 
80000 
100000 
120000 
140000 
160000 
180000 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
1st 45 
runs 
All 50 
runs 
Block Szemetric tonmedian 
mean 
max 
st.dev 
NOTE: J = Joule. 
Figure K-11. Summary Statistics of Impact Energy (J) for 110-6 Ground Motion 
1 
Bli(i) 
li40.00% 
50.00% 
60.00% 
70.00% 
80.00% 
90.00% 
100.00% 
0.1 10 100 
ock Sze metrc tonCumuatve Percentage 
1st 5 runs 
1st 10 runs 
1st 15 runs 
1st 20 runs 
1st 25 runs 
1st 30 runs 
1st 35 runs 
1st 40 runs 
1st 45 runs 
all 50 runs 
Figure K-12. Block Size Distribution for 110-6 Ground Motion 
ANL-EBS-MD-000027 REV 03 K-9 September 2004 

Drift Degradation Analysis 
Figures K-13 to K-15 shows the trend of the statistics for the analyses considering the 110-7 
annual probability of exceedance ground motion with a total of 44 3DEC simulations. The 
corresponding numeric values for the statistics are tabulated in Tables K-10 to K-12. The 
maximum block size and impact energy occurs in between the 20th and 25th simulation, whereas 
the maximum impact velocity occurs in between the 40th and 44th simulation. The trend shows 
that the statistics of rockfall characteristics approaches to asymptotic value approximately 30 to 
35 runs of 3DEC simulation. Figure K-16 present the block size cumulative distribution for the 
evolution of the analyses, the distribution shows that approximately 20 to 25 runs of 3DEC 
simulation provide adequate representation of the size distribution. 
Table K-10. Summary Statistics of Block Size (metric ton) for 110-7 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
All 44 
runs 
Median 0.12 0.12 0.13 0.14 0.14 0.14 0.14 0.14 0.15 
Mean 0.47 0.49 0.50 0.53 0.52 0.51 0.50 0.50 0.50 
Maximum 14.58 14.58 14.58 19.05 28.29 28.29 28.29 28.29 28.29 
Standard 
Deviation 1.29 1.25 1.29 1.39 1.57 1.50 1.44 1.44 1.43 
Table K-11. Summary Statistics of Impact Velocity (m/sec) for 110-7 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 
30 
runs 
1st 
35 
runs 
1st 
40 
runs 
All 44 
runs 
Median 4.35 4.16 4.11 3.75 3.97 3.85 3.82 3.83 3.78 
Mean 4.38 4.25 4.31 4.04 4.26 4.18 4.19 4.17 4.17 
Maximum 11.67 11.67 13.58 13.58 20.53 20.53 20.53 20.53 20.94 
Standard 
Deviation 2.20 2.07 2.22 2.16 2.42 2.35 2.40 2.37 2.47 
Table K-12. Summary Statistics of Impact Energy (J) for 110-7 Ground Motion 
Summary 
Statistics 
1st 5 
runs 
1st 10 
runs 
1st 15 
runs 
1st 20 
runs 
1st 25 
runs 
1st 30 
runs 
1st 35 
runs 
1st 40 
runs 
All 44 
runs 
Median 1163 1127 1176 981 1077 1020 1005 1004 1022 
Mean 3786 3890 4005 3666 4301 4240 4099 4069 4146 
Maximum 80283 80283 80283 80283 706914 706914 706914 706914 706914 
Standard 
Deviation 8419 8294 8457 8003 20139 18558 17649 17526 16749 
ANL-EBS-MD-000027 REV 03 K-10 September 2004 

Drift Degradation Analysis 
ll 
() 
i0.00 
5.00 
10.00 
15.00 
20.00 
25.00 
30.00 
1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs 1st 30 runs 1st 35 runs 1st 40 runs A 44 runs 
Block Sizemetric tonmedan 
mean 
max 
st.dev 
Figure K-13. Summary Statistics of Block Size (metric ton) for 110-7 Ground Motion 
ll 
(m/
0.00 
5.00 
10.00 
15.00 
20.00 
25.00 
1st 5 runs 1st 10 runs 1st 15 runs 1st 20 runs 1st 25 runs 1st 30 runs 1st 35 runs 1st 40 runs A 44 runs 
Impact Velocitysec) 
median 
mean 
max 
st.dev 
Figure K-14. Summary Statistics of Impact Velocity (m/sec) for 110-7 Ground Motion 
ANL-EBS-MD-000027 REV 03 K-11 September 2004 

Drift Degradation Analysis 
800000 
700000 
600000 
median 
mean 
max 
st.dev 
Impact Energy (J)
500000 
400000 
300000 
200000 
100000 
0 
1st 5 runs 1st 10 1st 15 1st 20 1st 25 1st 30 1st 35 1st 40 All 44 runs 
runs runs runs runs runs runs runs 
NOTE: J = Joule. 
Figure K-15. Summary Statistics of Impact Energy (J) for 110-7 Ground Motion
1 
Bli(i) 
li40.00% 
50.00% 
60.00% 
70.00% 
80.00% 
90.00% 
100.00% 
0.1 10 100 
ock Sze metrc tonCumuatve Percentage 
1st 5 runs 
1st 10 runs 
1st 15 runs 
1st 20 runs 
1st 25 runs 
1st 30 runs 
1st 35 runs 
1st 40 runs 
all 44 runs 
Figure K-16. Block Size Distribution for 110-7 Ground Motion 
ANL-EBS-MD-000027 REV 03 K-12 September 2004 

Drift Degradation Analysis 
APPENDIX L 
CONVERSION OF FRACMAN FRACTURE OUTPUT TO 3DEC INPUT 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
CONVERSION OF FRACMAN FRACTURE OUTPUT TO 3DEC INPUT 
The coordinate systems used for FracMan and 3DEC are shown in Figure L-1. The FracMan 
system is a right-hand system with North pointing to the negative x-axis, whereas the 3DEC 
system uses a left-hand system with North parallel to the z-axis. The conversion is accomplished 
by using the following equations: 
x 
3DEC = y FracMan (Eq. L-1) 
z 
3DEC = -x FracMan (Eq. L-2) 
y 3DEC = z FracMan (Eq. L-3) 
This conversion was done in the Microsoft Excel spreadsheet files 3DEC-S1shtA_TPO.xls, 
3DEC-S1shtB_TPO.xls, 3DEC-s2sht_TPO.xls, 3DEC-s3_sht_TPO.xls, 3DEC-
VPPLONG_TPO.xls, and Tptpll- Fracman Generated Fracture Data.xls (Table A-1). The x-, y-, 
and z-coordinates in worksheet 3DEC input were obtained based on the original coordinate 
values in worksheet Fracman output and Equations L-1 to L-3. The dip, dip direction, and 
radius inputs in 3DEC were a direct copy from FracMan outputs. Additional worksheets, which 
sort the fracture data listing based on the descending order for radius, are included in the 
spreadsheet files. This sorted fracture data is used for 3DEC model optimization as described in 
Appendix H. 
z 
y
-x (North) 
z (North) 
y 
x 
x 
FracMan Coordinate System 3DEC Coordinate 
Figure L-1. Coordinate System Adopted in FracMan and 3DEC 
ANL-EBS-MD-000027 REV 03 L-1 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 L-2 September 2004 

Drift Degradation Analysis 
APPENDIX M 
GFM2000 INPUT AND OUTPUT FILES FOR STRATIGRAPHIC 
UNIT THICKNESS DATA AND CROSS-SECTIONS 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
GFM2000 INPUT AND OUTPUT FILES FOR STRATIGRAPHIC 
UNIT THICKNESS DATA AND CROSS-SECTIONS 
M1. INTRODUCTION 
Stratigraphic unit thickness and cross-sections for the thermal-mechanical calculation were 
extracted from DTN: MO0012MWDGFM02.002 [DIRS 153777]. The extracted stratigraphic 
unit thickness was used in calculating mean rock properties for the thermal-mechanical units, 
while the cross-sections were utilized to create three-dimensional mesh used in the 
thermal-mechanical calculation. The detailed calculation, data, and mesh description are 
presented in Appendices C and E. 
The extraction of the unit thickness and cross-sections was conducted on the geologic data from 
the TDMS (DTN: MO0012MWDGFM02.002 [DIRS 153777]), using EarthVision V.5.1 
software (see Section 3). The EarthVision V.5.1 software was qualified for three-dimensional 
geologic modeling and was used within its range of validation. The stratigraphic unit thickness 
was extracted at the location of NS 232674 m and WE 170693 m, which is approximately the 
center of the repository (Appendix C, Figure C-3), while the three cross-sections were extracted 
at the locations of NS 231637 m, NS 234075 m, and NS 235904 m (Appendix C, Figure C-3). 
An additional stratigraphic unit thickness was extracted at the location of NS 234025 m and 
WE 171440 m, which is the location of the in situ stress measurements 
(DTN: SNF37100195002.001 [DIRS 131356]) at borehole ESF-AOD-HDRFR#1 
(Section 6.3.1.1 and Figure C-3). The unit thickness data were used to calculate the overburden 
stress at the depth of the in situ measurement from the surface. 
All the input and output files from the EarthVision software for the extraction of the unit 
thickness and the cross-section are presented in the following sections. 
M2. EARTHVISON INPUT AND OUTPUT FILES 
The input files (central.dat, hope_01.sh, and combine.sh) and output file (alldata_01_2.dat) for 
the extraction of the unit thickness at the location of WE 170693 m and NS 232674 m are 
available in the TDMS (DTN: MO0408MWDDDMIO.002). 
The input files for the extraction of the three cross-sections at the locations of NS 231637 m 
(S3), NS 234075 m (S7), and NS 235904 m (S10) are also available in the TDMS 
(DTN: MO0408MWDDDMIO.002). The resulting cross-sections (output files s3.dxf, s7.dxf, 
and s10.dxf) are shown in Figures M-1 to M-3. 
The input files (hfdr1.dat, hope_02.sh, and combine.sh) and output file (alldata.dat) for the 
extraction of the unit thickness at the location of NS 234025 m and WE 171440 m are available 
in the TDMS (DTN: MO0408MWDDDMIO.002). 
ANL-EBS-MD-000027 REV 03 M-1 September 2004 

Drift Degradation Analysis 
Figure M-1. Cross-Section Extracted at the Location of S3 (NS 231637 m), Using the EarthVision 
Software 
ANL-EBS-MD-000027 REV 03 M-2 September 2004 

Drift Degradation Analysis 
Figure M-2. Cross-Section Extracted at the Location of S7 (NS 234075 m), Using the EarthVision 
Software 
ANL-EBS-MD-000027 REV 03 M-3 September 2004 

Drift Degradation Analysis 
Figure M-3. Cross-Section Extracted at the Location of S10 (NS 235904 m), Using the EarthVision 
Software 
M3. OVERBURDEN STRESS AT THE DEPTH OF THE IN SITU TEST 
The vertical stress due to the weight of overburden at the depth of the in situ test from the surface 
was calculated from the stratigraphic unit thickness at the in situ test location and the mean 
stratigraphic unit density presented in Table E-1 (i.e., vertical stress = overburden thickness [m] 
 9.81 m/sec2  density [kg/m3]). Based on the supporting information for 
DTN: SNF37100195002.001 [DIRS 131356], the elevation of the in situ measurement is 
1033.3 m (CRWMS M&O 1997 [DIRS 147458], MOL.19970717.0008, Table 5). Details of the 
calculation and the resulting overburden load of 4.7 MPa are presented in Table M-1. 
ANL-EBS-MD-000027 REV 03 M-4 September 2004 

Drift Degradation Analysis 
Table M-1. Overburden Load at the Depth of the In Situ Test 
Unit 
Thickness 
(m) 
Elevation at 
Top 
(m) 
Elevation at 
Bottom 
(m) 
Densitya 
(kg/m3) 
Overburden 
Thicknessb 
(m) 
Overburden 
Load 
(MPa) 
Tpcpv3 0.0 1285.1 1285.1 2310 0.0 0.0 
Tpcpv2 4.9 1285.1 1280.2 1460 4.9 0.1 
Tpcpv1 4.2 1280.2 1275.9 1460 4.2 0.1 
Tpbt4 1.4 1275.9 1274.6 1460 1.4 0.0 
Tpy 10.4 1274.6 1264.1 1460 10.4 0.1 
Tpbt3 4.3 1264.1 1259.8 1460 4.3 0.1 
Tpp 20.8 1259.8 1239.0 1460 20.8 0.3 
Tpbt2 8.2 1239.0 1230.8 1460 8.2 0.1 
Tptrv3 2.8 1230.8 1227.9 1460 2.8 0.0 
Tptrv2 0.8 1227.9 1227.2 1460 0.8 0.0 
Tptrv1 1.0 1227.2 1226.2 2310 1.0 0.0 
Tptrn 54.4 1226.2 1171.8 2190 54.4 1.2 
Tptrl 9.1 1171.8 1162.7 2190 9.1 0.2 
Tptpul 74.8 1162.7 1087.9 1834 74.8 1.3 
Tptpmn 36.8 1087.9 1051.1 2148 36.8 0.8 
Tptpll 102.6 1051.1 948.5 1979 17.8 0.3 
In Situ Vertical Stress 4.7 
a 
The mean stratigraphic unit density is from Table E-1. 
b The overburden thickness is from the elevation of the in situ test, which is 1033.3 m (CRWMS M&O 1997 
[DIRS 147458], MOL.19970717.0008, Table 5). 
ANL-EBS-MD-000027 REV 03 M-5 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 M-6 September 2004 

Drift Degradation Analysis 
APPENDIX N 
MODEL VALIDATION REVIEW  3DEC MODELING OF 
SEISMIC GROUND MOTION-INDUCED ROCKFALL 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
MODEL VALIDATION REVIEW  3DEC MODELING OF 
SEISMIC GROUND MOTION-INDUCED ROCKFALL 
An outside expert technical review was conducted as a means of validating the 3DEC model for 
representation of nonlithophysal rock (see Section 7.7.6). Dr. John Tinucci of the PanTechnica 
Corporation in Minneapolis, Minnesota, was contracted for this purpose. Dr. Tinucci is a 
Professional Engineer and has a Ph.D. from the University of California, Berkeley, where his 
thesis research was in the area of analysis of the stability of blocky rock masses, and, in 
particular, in the development of key-block methods for tunnel stability assessment. He has 
extensive experience in the use of the 3DEC program for surface and underground stability 
assessment. Particularly valuable experience for the present application is his use of 3DEC to 
model dynamic stability of deep underground mine openings. Dr. Tinuccis review report is 
provided in this appendix. 
Dr. Tinucci provides a summary of specific 3DEC model assumptions and abstractions, 
including recommendations for changes or other issues that should be considered (see 
Recommendations on p. 19/20 and Table 1, pp. 7/20 through 9/20, of the review report in this 
appendix). A response to Dr. Tinuccis recommendations is provided as follows: 
 Recommendation #1 (from Table 1, p. 7/20): Reexamine the magnitude of input ground 
motions. 
- Response: A limitation study of ground motions is ongoing, which reexamines 
ground motion magnitudes. Any impacts to this report due to changes to ground 
motion data as a result of the limitation study would be documented in a future 
revision. The current input ground motions (see Section 4.1) are the best available 
source of site-specific ground motion data. 
 Recommendation #2 (from Table 1, p. 7/20): Values of joint cohesion, joint friction, 
and joint dilation should depend on other joint strength parameters. 
- Response: Sensitivity analyses were conducted using three additional joint categories 
that consider a range of joint strength parameters (Section 6.3.1.6.2). 
 Recommendation #3: Due to the complexity of the FISH functions within 3DEC model, 
it is highly recommended that the functions be independently checked by another 
engineer to ensure accuracy. 
- Response: FISH functions have been independently checked (by the technical 
checker) as part of the checking of the 3DEC input files. 
 Recommendation #4 (from Table 1, p. 8/20): Compute blocks based on local spacing 
(approximately 0.5 m) to determine block volume change. 
- Response: The recommendation was provided for the original FracMan results. The 
synthetic fracture network from FracMan has since been revised to provide a better 
quantitative comparison with mapped fracture data (based on joint spacing, trace 
length, and orientation). The current synthetic FracMan fracture geometry provides a 
ANL-EBS-MD-000027 REV 03 N-1 September 2004 

Drift Degradation Analysis 
relatively good fit of the underground mapping fracture geometry data, as shown in 
Table 6-2. 
 Recommendation #5 (from Table 1, p. 8/20): Include references for other known studies 
that employ similar approaches. 
- Response: Additional validation based on data from a Defensive Nuclear 
Agency-sponsored explosive tunnel stability field experiment has been included, 
which builds confidence in the simulation of dynamic blocky systems (Section 7.7.4). 
Reference for other Yucca Mountain applications using FracMan have been added in 
Section 6.1.6.2. 
 Recommendation #6 (from Table 1, p. 8/20): Include sensitivity runs for natural 
damping of the rock mass. 
- Response: Although damping is not explicitly specified in the 3DEC input, it is 
considered with the simulation of joint slip, joint separation, and bridge damage 
during seismic shaking. The current approach is considered reasonable and yet not 
overly conservative. 
 Recommendation #7 (from Table 1, p. 8/20): Check sub-contacts for several cases for 
failure along bridges, and then re-assess the need for using finer discretization. 
- Response: Bridge damage during seismic shaking is discussed in Section 6.3.1. In 
general, less than 1 percent bridge area is damaged when subjected to 110-5 ground 
motions. Bridge area damage increases to about 4 percent with 110-6 ground 
motions, and 30 percent for 110-7 ground motions. Since only a relatively small 
portion of the surface area of the unstable blocks was formed by the damaged bridge, 
it was not necessary to conduct additional sensitivity studies using a more refined 
grid. 
 Recommendation #8 (from Table 1, p. 8/20): Run one case with a much larger fractured 
volume including the floor. 
- Response: The sensitivity of model sizes is provided in Section 6.3.1.6.5. The 
base-case model (25 m  25 m  25 m) was determined to be adequate for rockfall 
prediction. 
 Recommendation #9 (from Table 1, p. 9/20): Should qualitatively compare blocks 
formed with those formed from simulated fractures. 
- Response: The identification of blocks observed in the ECRB Cross-Drift is provided 
in Appendix F. For simulating an actual joint geometry using 3DEC, the difficulty of 
generating joints in the rock mass not exposed at the tunnel surface prevents a 
solution with credible geometry. The quantitative comparison of the joint 
geometrical parameters from mapping data and from FracMan as discussed in 
Section 6.1.6 provides a similar confirmation for the adequacy of the fracture system. 
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Drift Degradation Analysis 
 Recommendation #10 (from Table 1, p. 9/20): De-emphasize DRKBA results in the 
final report. 
- Response: The DRKBA results have been de-emphasized, appearing primarily in 
Appendix D. This report focuses on the use of 3DEC and UDEC as documented in 
Sections 6.3 and 6.4. The DRKBA results are primarily used as confirmation for the 
3DEC results (Section 7.7.5). 
The following errata are provided for Dr. Tinuccis report: 
 Page 1/20: The report was submitted to the Engineered Barrier System Department. 
 Page 2/20: G. Neider-Westerman, 2000 refers to CRWMS M&O 2000 
[DIRS 152286]. 
 Page 2/20: N. Barton, 2002 refers to Duan 2003 [DIRS 163586]. 
 Page 7/20: In Table 1, Small Joints are discussed on p. 11/20. 
 Page 8/20: In Table 1, Sub-horizontal Joint Spacing is discussed on p. 12/20. 
 Page 8/20: In Table 1, Joint Strength Degradation is discussed on p. 13/20. 
 Page 8/20: In Table 1, Fractured Rock Boundaries are discussed on p. 14/20. 
 Page 8/20: In Table 1, Fractures in Floor are discussed on p. 14/20. 
 Page 9/20: In Table 1, Event Orientation is discussed on p. 15/20. 
 Page 9/20: In Table 1, Removing Unstable Blocks is discussed on p. 15/20. 
 Page 9/20: In Table 1, Support System is discussed on p. 17/20. 
 Page 11/20: In the Ground Motion discussion, the three probable events are the 1 in 
2000 year event, the 1 in 1 million year event, and the 1 in 10 million year event. 
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Drift Degradation Analysis 
MODEL VALIDATION REVIEW 
3DEC MODELING OF SEISMIC GROUND MOTION-INDUCED ROCKFALL 
Submitted to 
Engineers Barrier Group 
Bechtel/SAIC 
Review by 
John P. Tinucci, PE, PhD 
PanTechnica Corporation 
INTRODUCTION 
The 3DEC program is currently being used for simulation of mechanical response of the Middle 
Non-Lithophysal unit to seismic shaking induced by seismic ground motions. The objective of this 
modeling is to provide estimates of the size, shape and number of rocks that may be dislodged and 
fall into the emplacement drifts as a function of the level of the estimated ground motions. The 
ground motions (for various annual exceedence probability levels) are supplied by others within the 
project. This review is to be used as a portion of the validation requirements for model analysis 
given in procedure AP-SIII.10Q 
Review CriteriaThe documentation regarding the use of the 3DEC program for representing 
rockfall work has been reviewed using the following criteria: 
1. Is this information presented accurately using applicable methods, assumptions, and 
recognized techniques? 
2. Does existing model documentation provide adequate confidence required by the models 
relative importance to the potential performance of the repository system to support model 
validation for its intended purpose and stated limitations? 
Associated Documentation for ReviewThe following documents have been provided for review. 
It is understood that several of these documents are work-in-progress whose final content will be 
different upon submittal. 
1. 3DEC V2.01 software qualification reports and Itasca 3DEC V2.01 addendum. 
2. PowerPoint presentations of rockfall analyses. 
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3. Geology of the ECRB Cross DriftExploratory Studies Facility, Yucca Mountain Project, 
Yucca Mountain, Nevada, Mongano, et al, 1999. 
4. Fracture Geometry Analysis for the Stratigraphic Units of the Repository Host Horizon, 
G. Neider-Westerman, 2000. 
5. Draft of preliminary work (draft report to date, Excel Spreadsheets for results summary, input 
files). 
6. An Application of Rock Mass Characterization and Rock Joint Empirical Models at Yucca 
Mountain, To Assist in the Disposal Tunnel Design Studies, N. Barton, 2002 
Modeling ObjectivesThe original Drift Degradation Analysis documentation for these analyses was 
reviewed by NRC in 2001. The NRC identified four items related to rockfall analysis that must be 
resolved to close the Repository Design and Thermal-Mechanical Effects key technical issue. The four 
items, in annotated form, are: 
 Provide clarification for how reduction in cohesion adequately accounts for thermal effects. 
 Analyze small trace-length fracture data from the ESF and ECRB to assess their effect on block 
development. 
 Provide basis for effective maximum rock size including consideration of the effect of variation 
of the joint dip angle. 
 1) Revise DRKBA analyses using appropriate joints strengths accounting for their long-term 
degradation. 2) Analyze block sizes based on joint trace length data supplemented by available 
small joint trace length data. 3) Verify DRKBA analyses using (a) thermal and seismic boundary 
conditions, (b) fracture patterns simulations, (c) thermal and mechanical properties for rock 
blocks and joints, (d) long-term degradation of joint strength, and (e) site-specific ground motion. 
The 3DEC analyses are intended to address several of these items and this review includes comments on 
the applicable portions. The stated objectives of the drift degradation analysis, in annotated form are to: 
 model jointing around the drifts, 
 provide a statistical description of block sizes around the drifts, 
 estimate changes in drift profile resulting from deterioration of the drifts, and 
 provide an estimate of the time required for significant drift deterioration to occur. 
Site VisitOn January 28 -30, 2003, a site visit was made to both the Bechtel/SAIC facilities and ESF 
facilities. Time spent at the Bechtel/SAIC facilities was to review the input data, model setup and 
analysis results which had been performed to date. Engineers Mark Board, Ming Lin, Dwayne 
P r ep a r ed fo r 
B e c h te l/S A I C on be h a l f of 2/ 20 19 Fe br u a r y 2 0 0 3 
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Drift Degradation Analysis 
Kicker and Rob Lung were involved in discussions. Part of one day involved an underground tour of 
the ESF facilities. The purpose of this trip was to examine actual rock conditions for which the 
3DEC analyses were to represent. Both ESF and ECRB drifts were examined in the Lithophysal and 
Non-Lithophysal zones. 
GENERAL OBSERVATIONS ON MODELING APPROACH 
The conceptual model that is used for these analyses is that a finite volume of rock containing the 
emplacement drift starts in an unsupported, equilibrium condition. Then a seismic event is applied to 
the model and blocks are shaken loose falling on the drip shield. Simulated fractures are used to 
compute blocks formed by their intersection and the rockmass is descretized in the numerical model. 
The program 3DEC is used to solve the system of equations. 3DEC uses a distinct element method 
to solve for the interaction between blocks. An explicit finite difference solution scheme is use to 
solve the equations of motion and deformability of the rock. 
Conceptual Model ComponentsThere are three key components of this conceptual model that 
have been included to represent realistic conditions. First the represented rock contains simulated 
fractures to capture the discontinuum behavior of the expected blocky rockmass. Second, the 
fractures have been generated using statistical data from mapped fractures, which produce realistic 
trace maps similar to traces mapped by the geologists underground. Finally, the in situ conditions of 
gravitational stresses, excavation-induced stresses and thermally-induced stresses have been included 
to represent static loading conditions, plus a stress wave is propagated through the model to represent 
dynamic loading conditions. These essential components define a model that is appropriate for the 
described purposes. 
Representation AccuracyAs with any modeling analysis, the model is an accurate representation 
of actual expected rock behavior only when it represents conditions that lie within the known 
limitations. The mathematical tools employed (FRACMAN and 3DEC) are known to have 
limitations. However, upon review of the model, it does not appear that the conceptual model lies 
beyond the applicable mathematical representations of underground conditions and rock behavior. 
What has been implemented in these analyses is consistent with state-of-the-art numerical modeling 
techniques in the geomechanics industry. 
Judging the accuracy of the model is very difficult because of the lack of measured data. The 
mathematical model only generally represents the underlying conceptual model. That isthere are 
no real underground drifts oriented the same as what was modeled to compare static results to. The 
fractures were only simulated since there is no way to map joints until the excavations are made. 
Rock and joint properties were only estimated from conditions with sufficient accuracy required to 
estimate the four objectives of the analysis: effects of jointing, statistical representation of block 
sizes, changes in drift profile, and time required for drift deterioration to occur. We may never know 
how accurate the model results are, however, we do know that the approach adopted has been known 
to produce reasonably accurate results for analyses for which accuracy is known. 
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The analyses have done a reasonable job of quantifying where accuracy is required when additional, 
more accurate, analyses are preformed. The sensitivity study has identified that joint strength 
(especially dilation and cohesion), and joint frequency and orientation are critical parameters for 
predicting unstable block volumes. By identifying the sources of uncertainties and impacts of 
uncertainties on model output, the authors of this study are able to defend their current estimates and 
are knowledgeable about improving the model to reduce the uncertainties. More importantly, this 
study provides a basis for collecting additional field and laboratory data for resolving an important 
NRC key technical issue. 
Mathematical Model ConfidenceDue to the complexity of the analysis, the process used to 
establish confidence that the mathematical model produces reasonable results was broken down in 
parts. First the inputs, or initial conditions, were checked prior to simulating the seismic event. The 
volume of unstable blocks under static conditions was examined for reasonableness. Since the 
analysis did not examine actual ESF or ECRB drift block geometries, it was not possible to compare 
the model results to unstable blocks observed underground. The next confidence check of the model 
was to pass a simple undamped wave to the model, applied at the bottom of the model. The output 
response at the top of the model was examined for reasonableness. This confirmed that the model 
was capable of passing waves without energy loss at boundaries and internally to the model. The 
model was then checked for result reasonableness by applying sequentially larger seismic events. 
This confirmed that larger seismic loading produced larger volumes of unstable blocks. Finally the 
sensitivity study was used to confirm the parameters having the greatest influence on the results. 
This was done to demonstrate the reasonableness of the base case conditions. 
Alternative AlgorithmsThe overall approach of using FRACMAN to generate fracture, and 3DEC 
to compute the block and solve the equations of motions is not the only approach available for 
assessing block stability. There are alternative algorithms of simulating fractures, but none are 
known to so robustly address stochastic simulation, plus FRACMAN is the most widely used fracture 
simulation program in the petroleum, mining and nuclear waste industries. An alternative approach 
to simulating fractures was examined through the DRKBA rockfall analyses performed prior to this 
work. The simulation algorithm is not considered as robust as that implemented by FRACMAN. 
Similarly there are alternative block stability analysis methods available besides using the 3DEC 
program. The DRKBA program was used which makes use of limit equilibrium solution to stability. 
It is considered not as accurate as 3DEC since in situ stress, thermal stress, and seismic loading are 
not explicitly represented. An alternative numerical approach to 3DEC program is the 3-D DDA 
program. 3-D DDA is a distinct element method that solves the equations of motion and can account 
for in situ stress, thermal stress and seismic loading. Its limitation, as currently implemented is that 
blocks are simply deformable and the program has not been qualified for use in the quality 
assurance aspects of nuclear waste program. Therefore, the overall approach to solving the 
mathematical models (i.e. FRACMAN and 3DEC combination) is the best that the geomechanics 
industry has to offer. The 3DEC program has been through the process of being qualified for use 
from the quality assurance point of view. 
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Input Data ReasonablenessThere are two classes of information used to develop the mathematical 
models: input data for assigning values to parameters and professional judgment for assembling the 
model. Great effort has been focused on using representative laboratory and field data to assign to 
parameters. A table in the report has been developed which identifies the source of inputs and how 
the magnitudes were determined. The only data that is unsubstantiated is the low probability seismic 
events (i.e. 1e-6, 1). In the absence of historic data, it is my opinion that these motions are too large 
and it needs to be demonstrated that the ground can geologically store and release such energy. 
Model AbstractionsThere is no doubt that some of the professional judgments used to develop the 
model have influence on the results. These judgments are treated differently because they are not a 
statement that is taken to be true in the absence of confirming data, as an assumption would do. 
Rather, these judgments are made to simplify the mathematical model, and thus are abstractions. 
There are trade- offs between accuracy and simplifications in order to compute results. The central 
constraint on these analyses is that the numerical model required to accurately represent the 
conceptual model can be excessively large and computationally intensive. Significant effort has been 
placed on reducing the mathematical model to a manageable size while having minimal impact on 
the accuracy of results. Judgments were necessary to optimize the number of blocks, the number of 
finite different zones, the boundary distance from the tunnel, constitutive behavior of intact rock and 
joints, time-step for dynamic loading, etc. The professional judgments used to simplify the model to 
a manageable size are logical and not inconsistent with what is commonly practiced in modeling 
underground tunnels in blocky ground conditions. Several of the simplifications can be argued as to 
their impact on results accuracy. However, their impact is minimal compared to the impact of the 
assumptions, especially in regards to the assumed seismic ground motions. 
Intended Use of ResultsIt is understood that the output data is intended to be used for two general 
purposes: to estimate the force magnitude and location of blocks impacting the drip shield, and the 
profile of the degraded drift. These results could only represent typical best estimates given that 
none of the real drifts currently exist and the fractures have not been mapped. Collectively, the 
assumptions and simplifications serve to provide results that are thought to be conservative; that is 
one would expect that fewer blocks than are predicted by the model results would become unstable 
and fall when subjected to these conditions. However, these results are not considered to be upper 
bound estimates because even more conservative assumptions and simplifications could be made 
and yet they would not be considered unreasonable. For example, it would have been reasonable to 
use 2-D UDEC models to provide estimates of unstable blocks. Therefore, the modeling approach 
adopted is reasonable (and rather novel) when compared to the intended use of the results. 
Appropriate Confidence LevelCriteria for ensuring the appropriate level of confidence in the 
model results has been obtained is governed by two sets of criteria: appropriateness of the seismic 
events and appropriateness of the drift degradation analysis. 
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As mentioned before, I have serious concerns about the applicability of the low probability seismic 
records (i.e. 1e-6 and 1e-7 probability events) supplied as input to appropriately represent the 
expected ground motion. It has not been shown that such motions are sustainable by the geology, 
although the mathematical modeling techniques used to estimate the motion are consistent with 
common practice. Those techniques have not been shown to be applicable to low probability events. 
Other aspects of the seismic portion of the analysis (i.e. motion application, free field boundaries, 
event duration, etc.) appear to be appropriate. In order not to bias the results to an extreme type of 
seismic event, 17 real records were scaled to 3 expected magnitudes (i.e. 15 events implemented in 
combinations of various fracture realizations for a total of 105 simulations). This approach to 
examining various scenarios is appropriate given the lack of information on extremely infrequent 
historic seismic events. 
Confidence in the other parts of the model related to simulating ground conditions (i.e. fracture 
simulation, application of various stress conditions, model discretization, removal of fallen blocks, 
etc.) are adequate given the intended use of the results. The criterion that data uncertainty be 
characterized and propagated through the model abstraction appears to be adequately addressed by 
the sensitivity studies. The need for the model to be compared to known conditions also appears to 
be adequately addressed by the fracture map comparisons, the pre-event conditions comparisons, and 
3DEC results comparisons to DRKBA results. It is important to note that confidence in the model is 
based only on visual examination of expected conditions since no measurements or recordings were 
made as part of this analysis. 
SPECIFIC OBSERVATIONS ON MODEL ASSUMPTIONS AND ABSTRACTIONS 
Given the above general discussion on the adequacy of the overall model results, there are aspects of 
the analysis that deserve specific comments. The purpose of this section is to address specific 
assumptions and abstractions that were necessary to assemble the conceptual and mathematical 
models. 
Table 1 is a summary of each modeling issue. The table includes a summary of what aspect of that 
issue is important and the approach that was adopted in the analysis. Also tabulated is a summary of 
whether the approach is reasonable and any recommendations for changes or other issues that need to 
be considered. 
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Table 1. Summary Model Assumption and Abstraction Issues 
Approach Page 
Issue Aspect Approach Reasonableness Recommendation Discussed 
Joint 
Cohesion 
Assumption  
Magnitude of 
values 
Mean minus 1 std 
dev, Zero in 
sensitivity 
Reasonable, 
sensitivity will likely 
over-predict 
unstable blocks 
Values should depend on 
other joint strength 
parameters. 
10 
Joint Friction 
Assumption  
Peak vs. 
Residual 
values 
Mean peak, Residual 
in sensitivity 
Slightly 
conservative/slightly 
conservative 
See above. 10 
Joint Dilation 
Assumption  
not coupled w/ 
Friction 
Zero, mean in 
sensitivity 
Base case of zero 
combined with peak 
friction values is not 
reasonable 
See above. 10 
Joint 
Stiffness 
Assumption  
low normal & 
shear 
magnitudes 
Similar normal & 
shear stiffness 
Low values but 
acceptable since 
magnitude has 
minor impact on 
results 
10 
Intact Blocks 
Behavior 
Abstraction  
No rockmass 
failure 
All elastic except 
glued joints with high 
strength 
Reasonable since 
inelastic blocks 
would not change 
results 
11 
Ground 
Motion 
Assumption  
extreme 
probabilities 
Extrapolate using 
standard methods 
1e-6 and 1e-7 events 
appear 
unreasonably large, 
not completely 
rational 
Reexamine the 
magnitude of input 
ground motions 
11 
Simulated 
Fracture 
Volume 
Abstraction  
Single 
realization in 
large volume 
Random tunnel 
location within volume 
for different 
realizations 
Reasonable given 
the limited of 
mapped data 
11 
Small Joints 
Abstraction  
small joints 
pulled from 
analysis 
database 
Less than 1m length 
not included in 
statistics 
Reasonable since 
they have low 
probability of 
forming blocks. 
11 
Non-Abstraction  Convex-blocks glued Reasonable given 
Concave 
Blocks 
Cutting non-
joint area 
& given intact 
strength 
that intact strength 
is much greater 12 
than joint strengths. 
Fracture Size Abstraction  Simulation based on Reasonable since 
Realness of 
simulation 
area of joints per unit 
volume instead of 
samples from 
simulation 12 
length & spacing compared well to 
maps. 
Terezaghi 
Correction 
Abstraction  
Correct for 
Neglect correction Reasonable given 
data collected from 
joints subparallel 
to 
tunnel 
variable tunnel 
orientations & large 
tunnel size 
12 
compared to joint 
spacing. 
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Issue Aspect Approach 
Approach 
Reasonableness Recommendation 
Page 
Discussed 
Sub-horizontal. 
Joint Spacing 
Abstraction  
Localized 
variations 
Include all data to 
determine average 
Locally not very 
conservative, but 
quite reasonable on 
overall repository 
scale. 
Compute blocks on local 
spacing (~0.5m) to see 
block volume change  
dynamic runs not 
necessary. 
12 
Damping 
Abstraction  
natural damping 
of rock mass 
None, 5% in 
sensitivity study 
Reasonable given 
real value is not 
known and jointing 
provides some 
motion damping 
Include a couple 
sensitivity runs 13 
Bridge Failure 
Abstraction  
Bridge is only 
inelastic portion 
of block 
Joints used intact 
rock strengths 
Reasonable given 
rock strength is 
much greater than 
induced stress field 
Check sub-contacts for 
several cases for failure 
along bridge and then 
re-assess need for using 
finer discretization. 
13 
Joint Strength 
Degradation 
Assumption  
Previous seismic 
loading of joint 
system 
No degradation, 
Residual friction. in 
sensitivity study 
Unknown influence, 
but reasonable 
approach given 
sensitivity analysis 
is lower bound 
13 
condition. 
Similar Analysis 
Approach 
Abstraction  
Acceptableness 
of approach 
None globally, 
Portions have been 
performed before 
Collectively the 
approach is novel, 
but various parts 
are common to that 
done by others and 
thus overall 
Include references for 
other known studies that 
employ similar 
approaches. 14 
approach is 
reasonable. 
Fractured Rock Abstraction  Identify blocks Unknown impact, Run one case with a 
Boundaries Sufficient Block 
Volume 
along tunnel 
surface 
but issue with low 
probability seismic 
much larger fractured 
volume including floor 14 
25m, 35, & 45m in 
sensitivity study 
events, which are 
already suspect. 
Fractures in 
Floor 
Abstraction  
Tunnel 
Deformability 
Neglect blocks in 
floor 
Reasonable given 
size of model and 
interest focused on 
falling rocks. 
See above. 15 
In Situ Stress 
Assumption  
Lithostatic stress 
field 
Mean values, 
high stress ratio in 
sensitivity study 
Reasonable, little 
impact on results 
since stresses 
would need to be 
much lower. 
15 
Event Duration Abstraction  5%/95% energy cut Reasonable, little 
Length of off by time impact on results 
shaking motion since significant 15 
energy would need 
to be excluded. 
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Table 1. Summary Model Assumption and Abstraction Issues (Continued) 
Issue Aspect Approach 
Approach 
Reasonableness Recommendation 
Page 
Discussed 
Event 
Orientation 
Abstraction  
Compare to least 
stable block 
forces 
Flip H1 & H2 along 
X&Y axes in 
sensitivity 
Reasonable, little 
impact since 
horizontal 
components are 
similar in 
15 
magnitude. 
Removing 
Unstable blocks 
Abstraction  
Bulking 
stabilizes chain 
blocks 
Deleted on contact, 
left in contact with 
drip shield in 
sensitivity study 
Over predicts 
volume of unstable 
blocks, but provides 
a broader 
simulation of 
16 
rockfall on drip 
shield 
Comparison to Abstraction  No comparisons Unknown impact Should qualitatively 
Real Blocks Observable 
validation 
made since no real 
seismic response 
compare blocks formed 
with those formed from 16 
data exists simulated fractures. 
DRKBA Abstraction  Of minor Stability part does De-emphasize DRKBA 
Analyses Comparison to importance since not provide reliable results in final report 
another 
approach 
analysis had major 
limitations 
comparison 
because no stress 
16 
& no motion 
Pore Pressures 
Abstraction  
Strength 
reduction during 
shaking 
Neglect Reasonable since 
not saturated 17 
Thermal 
Stresses 
Abstraction  
Additional forces 
on blocks 
Decoupled thermal 
and mechanical 
Reasonable since 
boundary conditions 
for cooling are 
unknown 
17 
Reflecting 
Boundaries 
Abstraction  
Wave 
interference due 
to close 
boundaries 
Implemented free-
field non-reflecting 
boundaries 
Reasonable 17 
Support System 
Abstraction  
Effectiveness for 
additional 
support 
Neglected 
Reasonable since 
nobody knows how 
effective they will be 
in long-term 
17 
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Joint CohesionThe approach adopted for joint cohesive strength was to use the mean value minus 
one standard deviation from laboratory data. It is not clear for these calculations how much of the 
cohesion can be relied on in the long-term. For most dam stability analyses (USACOE & USBR) the 
designers would assume no long-term cohesion. However, during trip underground the joints were 
observed to be very tight, with the only observable open joints at the springline, most likely 
associated with tunnel excavation disturbance. Overall, this approach to cohesion is reasonable and 
yet not overly conservative. It is recommended that joint cohesion be considered in conjunction with 
the other joint strength parameters, per Bartons recommendation. See Table 1. 
Joint FrictionFriction angle values have been taken as mean peak total friction for the base 
calculations (while assuming dilation is zero). Residual friction values were used in the sensitivity 
studies. The combinations of cohesion, friction and dilation for estimating rock strength should all 
be inter-connected and not be treated as independent cases. The base case (i.e. fri. = peak fri. & dil. 
= 0) is not logical since laboratory tests did not show zero dilation when peak friction is attained. 
The case with residual friction and no dilation makes physical sense as a state that could exist after 
disturbance has occurred. It is recommended that joint friction be considered in conjunction with the 
other joint strength parameters. See Table 1. 
Joint DilationDilation angles other than zero were run in the sensitivity study. Results suggest 
dilation has a large influence on the stability of blocks. The laboratory values used for dilation are 
probably on the low side given the tightness of joints observed during the underground visit. 
Dilation plays an important role in these analyses partly because of the presence of low apex angle 
blocks formed by the intersection of the high angle joints. That is, the dominant joints intersect to 
form large sliver-shaped blocks whose apex angle is between 10 - 20. Removable blocks require 
roughness (or dilation) angle if less than  the apex angle  in the range of 5 - 10 in order to be 
removable. This range is close to values reported for the laboratory tests. Therefore, by assuming 
dilation angle of zero would conservatively predict the number of removable blocks as well as a 
lower composite joint strength. It is recommended that joint dilation be considered in conjunction 
with the other joint strength parameters. See Table 1. 
Joint StiffnessJoint stiffness were taken as mean values from laboratory data. Shear stiffness 
normally is expected to be less than normal stiffness, by about 1-2 orders of magnitude. However, 
joint normal and shear stiffness were the same value in the analysis, which were 6 orders of 
magnitude less than the stiffness of the intact blocks. Their magnitude seems low given the tightness 
of joints. The implication of this is that most of the deformation around the tunnel will be taken up 
by the joint system. When combined with the low cohesion and medium friction angles used for 
joint strengths, much of the block deformation will be in the form of joint slip. Stiffer joints would 
mean more of the deformation would be from joint slip instead of slip. Stiffer joints would mean 
more of the deformation would be from joint slip instead of compression. The approach adopted to 
assign joint stiffness is not expected to have significant influence on the number of unstable blocks. 
Thus, the approach to adopting joint stiffness is reasonable and yet not overly conservative. See 
Table 1. 
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Drift Degradation Analysis 
Intact Blocks BehaviorElastic blocks have been assumed in this analysis. This implies that the 
intact rock in infinitely strong. Sidewall fractures near springline in the tunnel were observed in the 
lower non-lithophysal unit during the underground visit. However, beyond a distance of about  m 
the rock showed minimal observable damage, even in the jointing. The strength of the nonlithophysal 
rocks is estimated at about 70 MPa, yet the maximum stresses around the tunnel are about 
21 MPa (i.e. 3 times s1). During dynamic loading some localized sidewall spalling could be 
expected. By ignoring the energy loss associated with minor spalling more energy is transmitted to 
the joint system. This might slightly over estimate the number of unstable blocks. This approach to 
intact rock strength is quite reasonable, but might result in conservative results (i.e. too large unstable 
block volumes). It is recommended that a sensitivity case be run with inelastic blocks to see if the 
low probability seismic events produce stress spikes sufficient to local sidewall spalling. See 
Table 1. 
Ground MotionGround motion input data represents three probable events: the 1 in 10,000 year 
event, the 1 in 1 million year event and the 1 in 10 million year event. Peak motions are reasonable 
for the 5e-4 event (PPV = 19 cm/s, PPA = 0.19 g). However, they appear high for the other 2 events 
(1e-6 : PPV = 2.44 m/s, PPA = 10.46 g and 1e-7 : PPV = 5.35 m/s, PPA = 16.28 g). If such ground 
motions had been experienced underground, there is expected to be geologic evidence of damage, 
especially in the weaker lithophysal zone. Yet nothing has been reported by site geologists. When 
these large ground motions are input to the 3DEC model, the results indicate that all removable 
blocks become unstable. The results appear excessively conservative. See Table 1. 
Simulated Fracture VolumeSimulated joints have been used to generate the jointing geometry that 
the blocks are computed from. Statistical parameters from scanline mapping data were computed 
and input to FRACMAN program to simulate a single realization of the 3-D joint system. The 
volume of rocks simulated was a 100 m x 100 m x 100 m cube oriented parallel the emplacement 
drifts (00/073 as X axis,). A 25m x 25m x 25m of rock surrounding the tunnel was then randomly 
located within the cube. The 3DEC model was cut depending on the relative location of joints 
within the volume. Given the lack of real data in the emplacement drifts (as they are unmined to 
date) this is a very reasonable approach to estimate the jointing that might be there when the tunnels 
are excavated. See Table 1. 
Small JointsIt is understood that statistics were computed (length, spacing, dip, dip direction, 
termination, etc.) with only mapped joints longer than 1m. Ignoring small joints will have minimal 
impact on the stability results because 1) it can be shown thatsmall joints have a low probability of 
intersecting to form blocks and 2) such small blocks have a high probability of being nested in 
larger removable blocks. Thus, the approach to neglecting short joints in the FRACMAN simulation 
is reasonable and does not produce overly conservative results. In fact the inclusion of such short 
joints is expected to produce a large number of isolated joints whose impact would be to soften the 
overall rockmass, likely reducing the number of unstable blocks for a given ground motion. This 
could be verified by making a sensitivity run but is not necessarily recommended at this time given 
the purpose of the analyses. See Table 1. 
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Non-concave Blocks3DEC is limited to using non-concave blocks. When fractures are input they 
must cut completely through a given block. The approach adopted was to overcome this limitation 
by gluing joints back together for the portion of the joint beyond the radius of the simulated joint. 
Complex FISH functions were written to allow this on a block by block basis. Although this 
approach is quite clever, it is recommended that these functions be carefully checked for errors due to 
their complexity. This approach has been used by others in programs like UDEC; however, I am not 
aware of it being used in 3-D. Although gluing cut blocks using intact rock properties is a 
common practice in 3DEC analyses, this application of gluing partially cut blocks in novel. This 
approach is a very reasonable and is capable of producing realistic block geometries and fractured 
rockmass geometries. See Table 1. 
Fracture SizeFracture size is handled in FRACMAN by using trace length and spacing data to 
compute a statistical area of fractures required in the given volume of rock. The simulation generates 
a fracture radius and location for a given set while checking the area-to-volume ratio. Each set is 
simulated separately and then superimposed to compute truncations. The reasonableness of this 
approach is checked by generating unrolled simulated fracture maps of fractures as they intersect the 
tunnel walls. These maps were compared to actual unrolled fracture maps recorded underground. 
The FRACMAN results produce reasonable maps that look realistic when compared to recorded 
unrolled maps. See Table 1. 
Terezaghi CorrectionThe FRACMAN analysis has made no adjustments in the data for fractures 
oriented sub-parallel to the tunnel. It is common for fractures mapped in smaller diameter openings, 
such as boreholes, to be biased in the number of fractures recorded sub-parallel to the opening. A 
Terezaghi correction would normally be applied to the data to correct for this. In the case of the ESF, 
there is a sub-horizontal joint set sub-parallel to the plunge of the tunnel. However, the project 
geologists that did the mapping felt that due to a) the large diameter of the tunnel when compared to 
the observed spacing of the sub-horizontal set and b) the mapped tunnels traversed a range of 
orientations, it is not likely that a significant number of sub-horizontal fractures were not accounted 
for in the overall database of joints. Thus, the approach of not applying a Terezaghi correction to the 
sub-horizontal joint set data is reasonable. See Table 1. 
Sub-Horizontal Joint SpacingThe spacing of sub-horizontal jointing was observed to vary along 
the length of the tunnel in the non-lithophysal zone. In some locations it appeared to be on the order 
of  m spacing (longer joints) while in other areas it was in excess of 4m spacing (shorter joints). 
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Results from the joint statistics report an average spacing of 4.2 m. It is likely that the statistics 
smear the spacing to this larger value. It is this sub-horizontal plane that typically forms the 
release plane on blocks formed by the intersection on the other 3 joint sets. By not directly 
accounting for the m spacing long sub-horizontal joints, only very large blocks become removable. 
It is these large blocks where de-stressing around the tunnel has little impact on their stability. Had 
this closer spacing been used, more blocks nearer the tunnel surface would have been formed and 
thus a larger unstable volume predicted in certain areas of the tunnel. The approach adopted is 
reasonable on the scale of the repository, but might under predict unstable blocks locally. It is 
recommended that other FRACMAN simulations be performed to check the effect on the distribution 
of removable blocks. It is probably not necessary to perform additional dynamic analyses unless 
block size distributions are vastly different. See Table 1. 
DampingAll of the dynamic analyses have been performed with a motion damping coefficient of 
zero. This implies that the only damping in the system is the energy loss due to interaction between 
blocks brought about by the open/close shaking of joints. It is common practice to use some minor 
amount of damping (2% - 5%) to account for natural damping of the rock mass. The impact of not 
damping the motion is expected to be more high-frequency energy being available at block 
boundaries and more vibration of the joints. This would lead to more joint slip and, thus, more 
unstable blocks. To neglect damping is reasonable and yet not overly conservative. It is 
recommended that a couple sensitivity runs be made to verify how conservative this assumption is. 
See Table 1. 
Bridge FailureThe way blocks are formed in the model required that the joint extend beyond the 
simulated radius, but the non-real area of the joint was glued back using intact rock strengths 
(see item Non-Concave Blocks above). This glued area simulates an intact bridge of rock. When 
combined with the elastic blocks, any differential motion across the isolated joint will result in 
significant stress concentrations in the glued portion nearest the joint. Since the intact rock 
strength was used for simulate the gluing, this is the only place in the model where the intact rock 
could fail. Given a) the large strength difference between the joints and the intact rock, b) the rapid 
load change of the applied seismic event, and c) no applied damping in the system, there could be 
artificially high stresses generated at the glued contacts nearest the joint contacts. It is not known 
what percent of the reported unstable blocks had originally glued joints that had broken during the 
seismic event. The percentage of unstable blocks with partially glued faces might be sensitive to 
the number of sub-contacts along the glued joints. If this is the case, the reported volume of unstable 
blocks could be over estimated for a modeling discretization reasons. It is recommended that the 
unstable blocks from a few runs be checked to see if a large portion of their face area were from 
glued sub-contacts. If this is true, a sensitivity run should be made with a more finely descretized 
grid. See Table 1. 
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Joint Strength DegradationThe strength of joints were held constant for all seismic events. 
However, blocks exposed to low probability events will also have experienced higher probability 
events. This repetitive loading will result in shaking damage to the joint system (e.g., on average for 
every 10-7 event the rock will have experienced 10 of the 10-6 events). This shaking damage should 
manifest itself as a reduction in strength. This behavior was not simulated in the base case analysis. 
The sensitivity study includes a case with residual joint strengths, which would represent a lower 
bound condition for this behavior. It is unlikely that accounting for this behavior would improve the 
reliability of the results since no laboratory data is available to estimate the magnitude of joint 
strength degradation. Thus, the approach adopted of examining results from residual strength runs is 
reasonable. See Table 1. 
Similar Analysis ApproachThe entire analysis approach adopted for this study is thought to be 
unique. The reviewer knows of no other complete set of analyses that have been published in the 
literature that approach the magnitude or complexity of this study. However, others have adopted 
aspects of the analyses. For example, the use of FRACMAN to simulate a volume of fractures based 
on line mapping data has been documented. The same is true of the use of 3DEC to simulate seismic 
ground motion. The novel portions of the model development (i.e. gluing blocks in non-joint 
regions, selectively cutting blocks to minimize the numbers of blocks, etc.) is not unique and has 
been documented. However, it is their automation via FISH functions that has not been published 
else where to the reviewers knowledge. Rockfall analyses of waste repository drifts have been 
studied in the Finish waste program, although the approach was to analyze block stability using static 
loading and limit equilibrium solutions. Dynamic analyses of rockfall conditions have been 
performed for South African deep-mining rockburst problems. Given the uniqueness of these 
analysis requirements, it is the reviewers opinion, sufficient aspects of the adopted modeling 
techniques have been documented by other researchers that the overall approach to estimating 
seismic rockfall volumes is reasonable. All other known similar analyses would be sufficiently more 
conservative than those presented here. It is recommended that the final report contain references to 
known published analyses. See Table 1. 
Fractured Rockmass BoundariesA 25m x 25m x 25m volume of rock was used to compute 
discrete blocks in 3DEC, even though 100m x 100m x 100m was simulated in FRACMAN. The 
sensitivity of results to this volume has been examined by computing blocks in 35m x 35m x 35m 
volume and 45m x 45m x 45m volume. Results indicate less unstable blocks at 35m and more at 
45m. The reason for this is not explained. The reason for using the original 25m was to keep the 
computations to a manageable size. In the reviewers opinion the sensitivity study does not address 
whether the 25m volume is adequate. It is recommended that one large block model (60m x 60m x 
60m of fractured rocks) with the tunnel centered in the volume be computed with fine zone 
discretization. This model would simulate blocks more than 10 tunnel diameters extending beyond 
the major zone of excavation-induced stress region. See Table 1. 
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Fractures in FloorThe model did not simulate any blocks in the floor of the tunnel, yet fractures 
are known to exist there. The reason was that the analysis focuses on gravitational rockfall after 
being dislodged. The impact of neglecting fractures in the floor is less deformability of the tunnel 
and more motion-energy is likely transmitted to the joint system. This approach allows a reduction 
in the computational size of the model. The approach is reasonable, yet would produce a larger 
volume of unstable blocks than had the floor been represented as fractured. It is recommended one 
large block model be computed that includes fractures in the floor (see Fractured Rockmass 
Boundaries). See Table 1. 
In Situ StressPre-excavation in situ stresses used in the analyses were taken from mean 
measurement values. A sensitivity run was made with a higher stress ratio (th : tv). Given the small 
expected variations in the stress field, there is little influence on the results. In situ stress is 
considered a minor variable in the analyses and thus the approach adopted is reasonable. See 
Table 1. 
Event DurationThe decision was made to truncate the duration of the seismic record due to 
excessive computational time required to complete the analysis. The approach was to compute the 
applied energy over time and cut the record duration so that the first 5% and last 5% of the energy 
was neglected. This is a common practice in numerical modeling of seismic events in such high 
strength materials because only small changes occur in the model with late-time motion. This would 
not be the case if pore pressure dissipation was thought to be an issue for block stability. An 
alternative approach that is used in similar analyses is to perform frequency filtering where high 
frequencies are filtered since they contain little energy. This was not necessary for these analyses for 
two reasons: a) the critical time-step is governed by the minimum block and zone sizes capable of 
transmitting the wave motion, and b) automatic inertial mass scaling was implemented into 3DEC. 
Additionally, the peak energy is applied early in the record so loose blocks will have had sufficient 
time to fall, and thus the length of the event is expected to have little impact on the final rockfall 
volume results. This approach to shorting the record duration is reasonable. See Table 1. 
Event OrientationGround motion was applied to the model parallel the model boundaries with .v 
vertically in Z axis, .H1 horizontally in X axis and .H2 horizontally in Y axis. In the sensitivity 
study H1 and H2 motion components were reversed. This method does not necessarily produce the 
worst case motion on individual blocks. However, the combination of forces critical for block 
stability will be different for each block since each block is comprised of joints of different 
orientations. Given the near random shape of blocks (and thus their critical force vector orientation) 
and the fact that H1 and H2 components are of similar magnitude, the net impact on the predicted 
volume of unstable blocks is expected to be minimal. Therefore the approach of performing a 
sensitivity computation where the H1 and H2 components are reversed is reasonable. See Table 1. 
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Removing Unstable BlocksThe base case analysis adopted the approach of removing blocks from 
the analysis after they had made contact with the simulated drip shield. This was done to estimate 
potential impact of subsequently unstable blocks that might hit the drip shield. In actuality, large 
blocks would likely stay in contact with the drip shield preventing other blocks from impacting it. 
For large collapse zones, large blocks might even prevent other blocks from falling. The other 
blocks would loosen but not have space to fall freely. In the sensitivity analysis a case was run 
where no unstable blocks were deleted in order to check this approach. The approach of removing 
the blocks by deleting them after they contact the drip shield is reasonable. See Table 1. 
Comparison to Real BlocksAll of the analyses were performed with block geometries determined 
from the FRACMAN-simulated joint volume. No real blocks in the underground tunnels were 
analyzed. Although the actual geometry is not known because they extend back into the Rockmass, 
fewer modeling assumptions are required to generate the blocks (i.e. their location, orientation and 
tunnel trace length are known). Such an analysis would provide a comparison between the volume of 
unstable simulated-blocks and the volume of unstable real-blocks. Comparisons of unstable blocks 
from real and simulated fracture sections are not expected to be the same; however, the ratio of stable 
to unstable volume of blocks should be similar. It is recommended for purposes of model calibration 
that 3DEC blocks be generated from the FRACMAN volume for comparison to specific sections of 
tunnel. If the block volumes are similar then there will be more confidence in the approach used to 
simulate blocks for emplacement drift orientations. There would be no need at this time to compute 
the seismic response unless the block volumes were vastly different. See Table 1. 
DRKBA AnalysesThe original rockfall study was comprised exclusively of results from DRKBA 
limit equilibrium analyses. Those analyses were limited by the following assumptions: 
 In situ stresses were neglected. 
 The seismic motion was represented by changing joint cohesive strengths. 
 Thermal stresses were neglected. 
 Fracture simulation was based on joint length and spacing only along tunnel surface and 
assumed infinite into the Rockmass. 
 Small trace length data was included producing significantly more volume of small blocks 
The first 3 of these are considered major limitations (the 2nd is considered not completely rational as 
it applies to resisting forces instead of driving forces). Although there are these limitations, the 
analyses results provide an alternative approach to the 3DEC numerical model results. It is 
recommended that the DRKBA results discussion in the original report on be moved to an attachment 
and they be de-emphasized. See Table 1. 
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Pore PressuresPore pressure in the rockmass generated as a result of the seismic shaking were 
neglected in these analyses. This is reasonable since the rock mass is only partly saturated and the 
build up of pore pressures is unlikely. See Table 1. 
Thermal StressesThermal strains induced by the waste heating the drifts will generally serve to 
increase the stresses on the blocks. As the repository cools over time, these stresses will dissipate. 
The cooling impact on the local joint system is unknown as joints may either stay closed in 
compression or open due to tension. Either way, this effect is expected to extend only locally around 
the peripheral of the drift where the radial stresses are low. Larger blocks would remain clamped by 
the thermal stresses. The approach adopted in the analysis was to decouple the thermal calculations 
from the mechanical calculations. This is reasonable since the rock is treated as elastic and all the 
strains (including thermally induced) are fully recoverable. The only irrecoverable deformations 
occur as joints slip. Thermal calculations were sequenced by computing: thermal equilibrium, static 
mechanical equilibrium, and then dynamic loading. This approach is reasonable because it allows 
the blocks to come to static equilibrium prior to seismic loading. See Table 1. 
Non-Reflecting BoundariesOne of the problems in modeling seismic events is that the applied 
wave reaches the boundary of the model and is reflected back into the area of interest before the 
complete wave has passed through the area of interest. This would result in an amplification of the 
motion. The 3DEC program was modified specifically for these analyses to include non-reflecting 
boundaries. This prevents reflected motion from propagating back through the grid. It is reasonable 
that an equivalent dynamic stress was applied to the base of the model propagating upwards to 
simulate the seismic event. Vertical free-field boundaries were applied consisting of a row of zones 
that simulate non-reflecting boundaries. This approach is common for dynamic analyses. See 
Table 1. 
Support SystemNo ground support was included in the model. Although support is expected to be 
installed in the drifts, it is reasonable to assume that they will not contribute significant support in the 
long-term. See Table 1. 
CONCLUSIONS 
The modeling effort represented by this work is some of the most extensive rockfall analyses in 
blocky rockmass known to be performed to date. The mathematical model makes use of several 
novel techniques for representing fractures and then creating a blocky rockmass. 
The simulation work done with FRACMAN is theoretically sound and produces a realistic fracture 
pattern similar to trace maps recorded by the geologists. Although local fracturing (i.e. lengths, 
spacing, orientation relative to the drift, etc.) might be different than average values computed from 
the entire database, the simulated fractures appear very reasonable. Even the technique of simulating 
one set of fractures in a large volume and then sampling from random locations within the volume to 
create the 3DEC block model is a rational approach, 
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The combination of joint strength properties (i.e. cohesion, friction angle and dilation angle) for the 
base case has not been considered collectively. Rather, as independent parameters they represent 
conditions that do not make sense (i.e. peak friction and no dilation). 
Joint stiffness values are low but, since their magnitude has minor impact on results, the approach is 
acceptable. In agreeing with Dr. Barton (Introduction: Reference #6, above), the normal stiffness 
should be stiffer than the shear stiffness, although I am not sure I agree with Dr Barton on the orders 
of magnitude. 
The low probability seismic events (i.e. 1e-6 and 1e-7) appear unreasonably large as input ground 
motion. It should be demonstrated that the geology can store such energy before such events are 
used in analysis. No geologic evidence, to the reviewers knowledge, has been presented which 
suggests that such large events have occurred in the geologic past. There is no doubt that this is the 
single most influential parameter in the analysis due to the large range of acceleration and velocity 
variations. 
The manner in which sub-horizontal fracture spacing was treated results in predications not very 
conservative on a local level where average spacing of long fractures is significantly less. However, 
on an overall repository scale the approach is reasonable because there are other local areas where 
the sub-horizontal fracture spacing is significantly more than average. This is another reason that the 
study results apply overall conditions and not locally. 
The DRKBA stability analysis performed for the original rockfall study does not provide reliable 
comparison to these analyses because no stress was included nor was ground motion properly 
represented. However since there are not many other discontinuum block analyses techniques that 
can be use to compare the FRACMAN/3DEC analyses to, a summary of the DRKBA results should 
be left in the report because they are of comparison value. 
Finally, it is important to note that the analyses presented in this study have been well conceived. 
Given the complexity of mathematical models and the limited data available, the team has developed 
an analysis procedure which is state-of-the-art. They have combined techniques in a way that 
provides realistic estimates of rockfall volumes and impact on the drip shield. Undoubtedly, as more 
data become available this approach can be refined to provide more accurate estimates. I do not 
believe it is worthwhile spending the effort to provide more accurate estimates at this time since data 
uncertainty is still large. 
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Recommendations 
There are several techniques that can be used to improve the accuracy of these analyses with the 
current uncertainty in data. The following recommendations should be considered as part of the 
work scope for producing a final document for this work. The recommendations are in order of 
decreasing importance. 
1. As mentioned throughout this review the large seismic events are suspect. It is 
recommended that the input motions be reexamined. Although review of the seismology 
work was not part of this review scope, more convincing arguments need to be presented 
which demonstrates that the geology can actually store this energy and sustain such 
motion. 
2. The base case values for joint strength parameters should be examined through a 
sensitivity study to be consistent with each of cohesion, fraction angle and dilation angle. 
3. Due to the complexity of the FISH functions within 3DEC model, it is highly 
recommended that all the functions be independently checked by another engineer to 
ensure accuracy. This might include more detailed comments/documentation of those 
functions. 
4. A sensitivity case should be included where a block system is compute on local spacing 
(~0.5m) of sub-horizontal joints to see block volume change. It would not be necessary to 
perform the dynamic runs. This will provide a feel for variations in the unstable block 
volumes. 
5. The documentation of these analyses should include references for other known studies 
that employ similar approaches to solving this type problem. This will significantly boost 
the readers confidence that the adopted approach has been published elsewhere. 
6. A sensitivity case should be included were several damping values are used to estimate the 
uncertainty in neglecting damping in the model. 
7. Unstable blocks should be checked for sub-contacts to have been broken along the 
bridge portion of the block. The results should then be reassessed to see if a sensitivity 
case is needed with finer discretization provides the same results. 
8. A sensitivity case should be developed that uses a much larger fractured volume which 
includes the floor. This will provide confidence that block stability is not biased by the 
limited number of blocks simulated in the model. 
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9. To provide confidence that the simulated fracture set provides stability results similar to 
that obtained from real mapped fractures, a sensitivity case should be run using specific 
jointing mapped in the ESF or ECRB drifts. This will qualitatively compare the volume 
of blocks formed with those formed from simulated fractures and provide confidence that 
the analyses are not excessively conservative in predicting unstable blocks. 
10. The final documentation should de-emphasize DRKBA results by moving them to an 
attachment and provide a succinct summary of their results. 
I hope that BSC finds this 3DEC modeling review to be beneficial. If you have questions on the 
findings I can be reached at 952-368-3079 or jtinucci@pantechnica.com. 
Respectfully submitted 
John P. Tinucci, PE, PhD 
President PanTechnica Corporation 
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APPENDIX O 
DESCRIPTION OF LITHOPHYSAL ABUNDANCE AND LITHOPHYSAL 
CHARACTERISTICS IN THE ECRB CROSS-DRIFT 
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Drift Degradation Analysis 
DESCRIPTION OF LITHOPHYSAL ABUNDANCE AND LITHOPHYSAL 
CHARACTERISTICS IN THE ECRB CROSS-DRIFT 
With the large volume of the proposed repository located in the lower lithophysal zone, a 
detailed study of the lithostratigraphic features in the lower lithophysal zone exposed in the 
ECRB Cross-Drift has been completed (DTNs: GS021008314224.002 [DIRS 161910] and 
GS040608314224.001 [DIRS 171367]). The data package documents the distributions of size, 
shape, and abundance of lithophysal cavities, rims, spots, and lithic clasts, and these data can be 
displayed and analyzed as (1) local variations, (2) along the tunnel (a critical type of variation), 
and (3) as values for the total zone. The percent of lengths and areas of features on the tunnel 
wall are typically referred as abundance. Because of the variations in scale of the features 
from lengths measured in millimeters to meters and variations in similar rock characteristics 
from tens to hundreds of meters, a variety of methods have been used to document the features in 
the rocks (Table O-1). Full Peripheral Maps, Detailed Line Surveys, and Small-Scale Fracture 
Surveys are primarily to document fractures, although lithophysae are described or annotated in 
some of these products. 
Table O-1. Methods Used to Document the Distribution of Lithostratigraphic Features in the Lower 
Lithophysal Zone of the Topopah Spring Tuff in the ECRB Cross-Drift 
Method Location Procedure/Configuration Data Collected 
Full peripheral 
mapping 
ECRB Cross-Drift, 
continuous (14+44 to 
23+26) 
Map visible tunnel surfaces Discontinuities >1 m, 
contacts, tunnel supports 
Detailed line surveys 
ECRB Cross-Drift, 
continuous (14+44 to 
23+26) 
Tape line along one side of 
tunnel Discontinuities >1 m 
Small-scale fracture 
surveys 
ECRB Cross-Drift, 6 
selected locations 
(11+15 to 24+30) 
Each 6 meter long horizontal 
traverse intersects three 2 
meter long vertical traverses 
Discontinuities <1 m 
Panel maps 
ECRB Cross-Drift, 18 
selected locations 
(14+93 to 22+94) 
1 x 3 meter maps, 1:10 scale, 
overlays on photographs 
Lithophysae, rims, spots, 
lithic clasts 
Tape traverses 
ECRB Cross-Drift, 187 
selected locations at 5 
meter intervals (14+05 
to 23+35) 
Traverses across tunnel, 
measured with tape attached 
to pole 
Lithophysae cavities only 
Angular traverses 
ECRB Cross-Drift, 22 
selected locations 
(14+60 to 22+00) 
Traverses across tunnel, laser-
prism measurements with 
geometric solutions 
Length of lithophysal cavities, 
rims, spots, stringers, lithic 
clasts, and matrix-
groundmass 
Large-lithophysae 
inventory 
ECRB Cross-Drift, 
continuous (14+40 to 
17+55) 
528 Lithophysae with long axis 
0.5 m and greater 
Long axis, short axis, station, 
wall position 
O1. TAPE AND ANGULAR TRAVERSE DATA 
Tape and angular traverses, which are variations in linear or one-dimensional measurement 
techniques, include data from the upper half of the tunnel (typically from the compressed air pipe 
on one side to the top of the conveyor belt on the other side, Figure O-1). In linear traverses, 
ANL-EBS-MD-000027 REV 03 O-1 September 2004 

Drift Degradation Analysis 
total abundance (percent) of a type of feature is the sum of lengths of the features divided by the 
total length of the traverse. Tape traverses include the measured length of lithophysal cavities 
along the traverse, length of the traverse, and a visual estimate of the abundance of rims and 
spots; therefore, tape data are discontinuous data (not all features are mapped). The advantage of 
tape traverses is that these data are every 5 m along the tunnel and indicate variations in the 
lithophysal cavity abundance along the tunnel (Figure O-2; see Section O6.3), but abundance 
values are typically greater than those documented with angular traverses and panel maps. There 
are 22 angular traverses, but they consist of continuous data (specific lengths of each lithophysal 
cavity, rim, spot, lithic clast, and matrix-groundmass), and measurements are to the nearest 5 to 
10 mm. Angular traverses consist of continuous data (all features are mapped) and provide a 
similar resolution of data to that of panel maps. Abundance of lithophysal cavities determined in 
angular traverses is similar to, or slightly less than, the abundance determined with tape traverses 
(Figure O-2). Angular traverse data (Table O-2; see Section O6.2) can be used to adjust the 
lithophysal cavity, rim, and spot data from tape traverses (Section O6.6). 
ie 
cm 
iib 
lt 
A) 
25 cm 
Rail road t250 cm 175 
Compressed air ppe 
Left rRight rib 
Crown 
Invert 
Top of conveyor be
.
cm 
cm 
(
) 
(
) 
e 
f) 
C)B) 
250 cm 200 
100 
15 degrees 
of arc 
0, 2.0) 
(0, 00, 2.5) 
(g, h(j, karc obstructed 
by vent line 
50 cm 
NOTE: 
A) Cross-section view of tunnel (looking toward the heading) showing parts of the tunnel (crown, ribs, and invert), 
positions of the compressed air pipe, conveyor belt, railroad ties, and position of the laser-prism (175 cm above 
railroad tie). The shaded area is the most typically measured part of the tunnel. 
B) Tape traverse data are discontinuous in that only the length of the lithophysal cavities is measured. 
C) Angular traverse data are continuous in that the edges of the features are measured and lengths are calculated 
with analytical geometric relations. 
Figure O-1. Geometric Relations of Tape and Angular Traverse Data from the Tptpll 
ANL-EBS-MD-000027 REV 03 O-2 September 2004 

Drift Degradation Analysis 
0 
10 
20 
30 
40 
50 
60 
1400 1500 1600 1800 2100 2300 
Abundance 
1700 1900 2000 2200 
Station 
Tape Percent Tape 10-m average Tape 20-m average Angular Percent 
NOTE: Abundance (percent of traverse length) of cavities are from tape and angular traverse data. These data are 
from DTN: GS021008314224.002 [DIRS 161910] and have not been adjusted as they are in Figure O-9. 
Figure O-2. Abundance of Lithophysal Cavities from Angular Traverse data and Tape Traverse Data 
Collected at 5 m Intervals from the Tptpll in the ECRB Cross-Drift with 10 m and 20 m 
Moving Averages 
O2. PANEL MAP DATA 
In addition to the along-the-tunnel variation in the abundance of features such as lithophysae, 
there are variations in the sizes, shapes, and distances between features. These types of 
variations are most easily observed with the panel map data (Figures O-3 to O-8). Locations of 
the panel maps were positioned to capture representative variations in the rocks along the tunnel, 
and they were not positioned to capture a specific feature such as the largest lithophysae. The 
tunnel walls at panel map locations were washed prior to photographing and mapping the site. 
At each panel map location, three photographs were taken at 90 to the wall and with low-angle 
illumination to accentuate the relief of the wall caused by cavities (and fractures). The three 
photographs are merged (to form a mosaic) of an area about 1.6  4.3 m and the 1  3 m map 
area is positioned to minimize the number and amount of partially included features. The panel 
maps, which have a 1:10 scale, are two-dimensional, continuous data because the features are 
mapped and documented. Boundaries of the features were drawn on the photographs in the field. 
During the mapping, the mapper attempted to represent the projected intersection of the feature 
with the tunnel wall, so there might be a slight difference in the mapped shape of the feature 
compare to the perceived shape in the photograph. On the panel maps, the boundaries of 
lithophysal cavities, rims, spots, and lithic clasts are depicted with different colors (red, green, 
blue, and gold respectively) and the alphanumeric labels of the features are L (lithophysal 
cavities and rims), S (spots), and C (clasts). 
ANL-EBS-MD-000027 REV 03 O-3 September 2004 

Drift Degradation Analysis 
Table O-2. Summary of Traverse Lengths and Abundance (Percentage) of Lithophysal Cavities, Rims, 
Spots, Lithic Clasts and Matrix-Groundmass Based on Angular Traverses from Stations 
14+60 to 22+00 in the ECRB Cross-Drift 
Station (m)
Station (m)
(numerical) 
Total arc length of 
traverse (degrees) 
Total length of 
traverse (mm) 
Total length of 
visible traverse (mm) 
Matrix-Groundmass(percent) 
Lithophysal cavities 
(percent) 
Rims (percent)
Spots (percent) 
Lithic Clasts 
(percent) 
14+60 1460 228.50 10851 7829 64.2 7.9 11.0 16.8 0.2 
14+95 1495 232.33 11003 8967 62.0 18.7 7.2 12.1 0.0 
15+25 1525 202.00 9784 7457 59.1 17.4 7.2 15.8 0.5 
15+53 1553 202.08 9786 7759 59.9 22.5 8.0 9.6 0.0 
16+10 1610 209.58 10095 7393 53.5 26.5 7.0 13.0 0.0 
16+42 1642 360.00 15081 11614 70.7 13.1 6.3 8.8 1.1 
16+58 1658 206.25 9960 7932 68.0 14.4 8.1 9.5 0.0 
16+75 1675 192.25 9369 7316 49.6 30.7 13.7 6.0 0.0 
17+00 1700 196.92 9569 7281 63.0 14.6 11.0 11.4 0.0 
17+27 1727 208.33 10044 7958 68.2 16.1 8.0 7.7 0.0 
17+50 1750 184.17 9016 6916 69.8 14.4 10.6 4.0 1.2 
17+70 1770 233.67 10980 8989 74.9 15.0 6.9 3.2 0.0 
18+00 1800 191.50 9292 7111 64.0 21.1 10.2 4.8 0.0 
19+00 1900 195.08 9450 7046 60.8 17.7 13.9 6.6 1.0 
19+20 1920 194.08 9404 7424 67.0 11.1 19.6 2.3 0.0 
20+00 2000 192.25 9314 7353 70.3 13.7 6.4 7.2 7.2 
20+70 2070 193.83 9387 7049 68.6 20.4 7.5 3.1 0.5 
21+00 2100 180.08 9513 7367 66.1 17.8 10.5 5.5 5.5 
21+25 2125 193.67 9372 7396 78.6 5.6 8.8 7.0 0.0 
21+70 a 2170 a 176.67 8826 5731 57.9 12.0 5.7 24.3 0.0 
21+75 a 2175 a 171.58 8532 6470 68.0 2.2 8.3 20.9 0.0 
22+00 2200 198.00 9628 9196 67.2 3.9 4.8 23.5 0.6 
Source: DTN: GS021008314224.002 [DIRS 161910] (Table from file Tptpll Lithop SEP Data File.xls, worksheet 
SEP-Angular Trav. Data.) 
a 
Only cavity data was collected in the angular traverse; however, the amounts of rims and spots were estimated in 
the field and the values were recalculated to 100 percent. 
ANL-EBS-MD-000027 REV 03 O-4 September 2004 

Drift Degradation Analysis 
Source: Photograph and map are from DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Meter scale is on the left. Red rectangle is the 1x3 m panel map area. Lithophysae have red L identifiers with cavities outlined in red and rims in green. 
Spots have blue S identifiers with cyan outlines. Lithic clasts have orange C identifiers with gold outlines. 
Figure O-3. Lithophysae, Spots, and Clasts of Tptpll in Panel Map 1493 Located on the Right Rib from Station 14+93 to 14+96 
ANL-EBS-MD-000027 REV 03 O-5 September 2004 

Drift Degradation Analysis 
Source: Photograph and Map are from DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Meter scale is on the left. Red rectangle is the 1x3 m panel map area. Lithophysae have red L identifiers with cavities outlined in red and rims in green. 
Spots have blue S identifiers with cyan outlines. Lithic clasts have orange C identifiers with gold outlines. 
Figure O-4. Lithophysae, Spots, and Clasts of Tptpll in Panel Map 1641 Located on the Left rib from Station 16+41 to 16+44 
ANL-EBS-MD-000027 REV 03 O-6 September 2004 

Drift Degradation Analysis 
Source: Photograph and map are from DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Meter scale is on the left. Red rectangle is the 1x3 m panel map area. Lithophysae have red L identifiers with cavities outlined in red and rims in green. 
Spots have blue S identifiers with cyan outlines. Lithic clasts have orange C identifiers with gold outlines. 
Figure O-5. Lithophysae, Spots, and Clasts of Tptpll in Panel Map 1641 Located on the Right Rib from Station 16+41 to 16+44 
ANL-EBS-MD-000027 REV 03 O-7 September 2004 

Drift Degradation Analysis 
Source: Photograph and map are from DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Meter scale is on the left. Red rectangle is the 1x3 m panel map area. Lithophysae have red L identifiers with cavities outlined in red and rims in green. 
Spots have blue S identifiers with cyan outlines. Lithic clasts have orange C identifiers with gold outlines. 
Figure O-6. Lithophysae, Spots, and Clasts of Tptpll in Panel Map 1726 Located on the Left Rib from Station 17+26 to 17+29 
ANL-EBS-MD-000027 REV 03 O-8 September 2004 

Drift Degradation Analysis 
Source: Photograph and map are from DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Meter scale is on the left. Red rectangle is the 1x3 m panel map area. Lithophysae have red L identifiers with cavities outlined in red and rims in green. 
Spots have blue S identifiers with cyan outlines. Lithic clasts have orange C identifiers with gold outlines. 
Figure O-7. Lithophysae, Spots, and Clasts of Tptpll in Panel Map 2124 Located on the Left Rib from Station 21+24 to 21+27 
ANL-EBS-MD-000027 REV 03 O-9 September 2004 

Drift Degradation Analysis 
Source: Photograph and map are from DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Meter scale is on the left. Red rectangle is the 1x3 m panel map area. Lithophysae have red L identifiers with cavities outlined in red and rims in green. 
Spots have blue S identifiers with cyan outlines. Lithic clasts have orange C identifiers with gold outlines. 
Figure O-8. Lithophysae, Spots, and Clasts of Tptpll in Panel Map 2232 Located on the Left Rib from Station 22+32 to 22+35 
ANL-EBS-MD-000027 REV 03 O-10 September 2004 

Drift Degradation Analysis 
The selected panel maps (Figures O-3 to O-8) display good examples of many of the 
lithostratigraphic features. Some of these features are listed below. 
 Simple lithophysae: L25, L26, and L34 on Figure O-3; L34 on Figure O-4; L4 and 
L41 on Figure O-6 
 Merged lithophysae: L2 on Figure O-4 
 Lithophysae with extension cracks where small cracks occur along the cavity wall: L44 
on Figure O-3 
 Extension-crack lithophysae where the expansion cracks dominate the geometry of the 
cavity wall: L17 and L25 on Figure O-4; L7, L12, L21, and L24 on Figure O-5 
 Backfilled lithophysae (some partial): L26 on Figure O-4; L2 on Figure O-7 
 Large-lithophysae (> 50 cm diameter): L2, L25, and L26 on Figure O-4; L7, L12, L21, 
L24, and L42 on Figure O-5 
 Vapor-phase partings (and stringers): Figure O-6 (lower half) 
 Spots: Any map, but especially Figure O-7 and Figure O-8 
 Fractures mapped with detailed line survey: Red lines in Figure O-8 
 Small-scale fractures: Any map, especially the left side of Figure O-5 and the right side 
of Figure O-6. 
Panel maps provide 2-dimensional (area) data for specific features or as the total of the map area 
(DTN: GS021008314224.002 [DIRS 161910], Table O-3). Additionally, the Data files for the 
panel maps in the data package include 3-dimensional measurements (height, width, and depth) 
from which an equivalent ellipsoid can be calculated. The methods used in making panel maps 
and point-counting the areas of features result in values accurate to about 2 to 5 percent of the 
listed value (DTN: GS021008314224.002 [DIRS 161910]). To test the influence of positioning 
the map area, the panel map for 16+41 on the left wall was used to compare the reported values 
with values from four alternative positions. The descriptive statistics on the area percent 
determined from the five map positions indicate the matrix-groundmass and lithophysal cavities 
have 95 percent confidence levels of less than 4 percent and the rims, spots, and lithic clasts have 
95 percent confidence levels of less than 0.5 percent (DTN: GS021008314224.002 
[DIRS 161910], see data summary documentation in the records package). 
ANL-EBS-MD-000027 REV 03 O-11 September 2004 

Drift Degradation Analysis 
Table O-3. Summary of Abundance (Percentage) of Lithophysal Cavities, Rims, Spots, and 
Matrix-Groundmass Based on Panel Maps in the ECRB CROSS-DRIFT from Stations 14+93 
to 22+94 
Station 
(m) 
Station (m) 
(numerical) 
Panel 
Maps 
Matrix / 
Groundmass 
(percent) 
Lithophysal 
Cavities 
(percent) 
Rims 
(percent) 
Spots 
(percent) 
Lithic Clasts 
(percent) 
14+93 1493 14+93L 69.5 13.3 13.3 3.7 0.2 
15+51 1551 15+51L 77.3 15.8 3.6 2.0 1.3 
16+10 1610 16+10R 78.2 15.3 3.6 2.8 0.1 
16+24 1624 16+24R 72.6 13.4 11.3 2.6 0.1 
16+41 1641 16+41L 71.6 19.0 5.7 3.5 0.1 
16+41 1641 16+41R 80.4 12.6 5.9 1.0 0.1 
16+56 1656 16+56L 75.6 13.2 7.3 3.7 0.1 
17+26 1726 17+26L 81.9 16.4 0.9 0.7 0.0 
17+68 1768 17+68L 83.2 13.6 2.1 0.9 0.1 
17+68 1768 17+68R 84.5 10.1 4.6 0.6 0.1 
18+05 1805 18+05L 76.7 14.0 5.6 3.5 0.2 
18+86 1886 18+86L 73.8 17.4 5.4 3.0 0.3 
19+19 1919 19+19L 83.6 12.8 2.1 1.3 0.3 
20+18 2018 20+18L 77.5 15.3 4.9 2.1 0.2 
20+69 2069 20+69L 83.8 9.2 3.9 3.0 0.2 
21+24 2124 21+24L 78.2 8.5 9.7 3.2 0.5 
22+32 2232 22+32L 62.4 5.3 7.4 24.6 0.2 
22+94 2294 22+94L 86.1 7.5 0.3 5.7 0.4 
Source: DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Table is from file Tptpll Lithop SEP Data File.xls, worksheet SEP - Panel Map Data. 
O3. VARIATION IN ABUNDANCE IN LITHOPHYSAL CAVITIES, RIMS, AND 
SPOTS ALONG THE TUNNEL 
The abundance of lithophysal cavities varies along the Cross-Drift partially from actual 
variations in the rocks and in part resulting from the methods used to collect the data (i.e., tape or 
angular traverses or panel maps) (Figure O-9). The abundance of cavities determined from the 
panel maps and angular traverses have not been adjusted. However, the original abundance 
values for lithophysal cavities from tape data (Figure O-2) have been corrected using a typical 
traverse length, a 15 m moving average, and a linear equation of correlation for collocated tape 
and angular traverse data (Sections O6.3 and O6.6). Numerous correlation equations were 
examined (Section O6.6), and a linear equation fitted to the collocated data and having an 
intercept at 0, with an R2 of 0.6204 was the best correlation and resulted in the corrected curve 
Ct in Figure O-9. A set of cavity values was calculated for each location with two or more 
types of data using the ratios 60:30:10 (panel:angular:tape) where the three data occur and 
60:40 (panel:tape or angular:tape) where there are only two types of data (Cpat fit in 
Figure O-9). These weighting ratios are empirically determined based on the relative detail of 
each type of data. The tape data was corrected one last time using an empirically determined 
proportional adjustment (i.e., corrected value [Ctc] equals tape value [Ct] plus the tape value [Ct] 
times a percent) (Section O6.6). The percents used include -0.05 from 14+05 to 21+40, -0.35 
from 21+45 to 22+70, and -0.70 from 22+75 to 23+35. These percents, especially the larger 
ANL-EBS-MD-000027 REV 03 O-12 September 2004 

Drift Degradation Analysis 
amounts from 21+45 to 23+35, were used to correct large cavity abundance values inherited 
from the original tape data that resulted from initially identifying the abundant spots (some with 
thin veinlets in them) as lithophysal cavities. This correction of the tape data is warranted on the 
basis of comparisons with the angular traverse and panel map data (there are no angular traverse 
data from 22+00 to 23+35) and estimates of lithophysae described in Mongano et al. (1999 
[DIRS 149850]) (Figure O-9; see Section O6.5). 
Abundance (length) (%) 
40 
35 
30 
25 
20 
15 
10 
5 
0 
1450 1550 1650 1750 1850 1950 2050 2150 2250 2350 
Station (m) 
Cp Ca Ct )Cpat fit Ct c Lit hop (M
Source: DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Ct data has been corrected based on an equation for correlation of tape and angular data. Cpat fit is the 
calculated value where two or more types of data occur together (map, angular, or tape data). Ctc has 
been corrected, especially from Station 21+25 to 23+35, to emulate the smaller amounts of lithophysal 
cavities determined from panel maps and angular traverses. Correlations and calculations for Ct, Cpat fit, 
and Ctc are described in Section O6.6. The results are compared to the cavity values (Lithop M) from 
Mongano et al. (1999 [DIRS 149850]). The data and curves are presented in file 
Drift Deg AMR AF T-A-P fit V1.xls, worksheet Length - Fit and Stats (See Table A-1). 
Figure O-9. Abundance of Lithophysal Cavities from Panel Maps (Cp) and Angular and Tape Traverses 
(Ca and Ct, Respectively) 
Similar to the lithophysal cavity data, the abundance of rims and spots varies along the ECRB 
Cross-Drift partially from actual variations in the rocks and in part resulting from the methods 
used to collect the data (i.e., tape or angular traverses or panel maps) (Figure O-10). The 
abundance of rims and spots determined from the panel maps and angular traverses have not 
been adjusted. However, the original visual estimates of rims plus spots in the tape traverses 
(see Section O6.3 and RSt in Figure O-10) have been corrected using 5-m and a 2nd-order 
polynomial equation of correlation for collocated tape and angular traverse data (Section O6.6). 
Numerous correlation equations were examined, but in the end, a 2nd-order polynomial equation 
(which because of the very small x2 value approximates a linear equation) was fitted to the 
collocated data from 17+60 to 22+00, and although the Y-axis intercept is +11.086, the R2 is 
0.7973 (Section O6.6). As with the lithophysal cavity data, a set of rim+spot values were 
ANL-EBS-MD-000027 REV 03 O-13 September 2004 

Drift Degradation Analysis 
calculated for each location with two or more types of data using the empirically determined 
ratios of 60:30:10 (panel:angular:tape) where the three data occur and 60:40 (panel:tape or 
angular:tape) where there are only two types of data. These values were used during curve 
fitting, but are not displayed in Figure O-10. The totals of rims plus spots from the panel and 
angular data have been calculated and compare well to the corrected rim plus spot: tape values 
(R+Sp, R+Sa, and RStc, respectively in Figure O-10). There are no visual estimates of rims plus 
spots in the tape traverse data from 22+00 to 23+35, so these values are estimated from the panel 
map data and descriptions from Mongano et al. (1999 [DIRS 149850]) (Sections O6.3, O6.5, 
and O6.6). The sharp decrease in spots depicted in curves RStc and Spot (M) (Figures O-10 
and O-11) result from changes in the abundance of spots across a fault at 22+38 (Mongano et al. 
1999 [DIRS 149850]). 
0 
4 
8 
12 
16 
20 
24 
28 
32 
36 
40 
(%)Abundance (length)
1450 1550 1650 1750 1850 1950 2050 2150 2250 2350 
Station (m) 
Rp Ra (M)RSt R+Sp R+Sa RSt c Spot s
Source: DTN: GS021008314224.002 [DIRS 161910]. 
NOTES: R+Sp is rims plus spot values in panel maps. R+Sa is rims plus spot values in angular traverses. 
RStc is the corrected tape values based on an equation for correlation of tape and angular data. 
Correlations and calculations for R+Sp, R+Sa, and RStc are described in Section O6.6. Spot values from 
Mongano et al. (1999 [DIRS 149850]) are described in Section O6.5. The data and curves are presented 
in file Drift Deg AMR AF T-A-P fit V1.xls, worksheet Length - Fit and Stats (See Table A-1). 
Figure O-10. Abundance of Rims From Panel Maps (Rp) and Angular (Ra) and the Combined Rim and 
Spot Values from Tape Traverses (Rt) 
The rim plus spot values from the corrected tape data was separated into rim and spot values 
based on the general ratios of each feature in the panel and angular traverse data respectively. 
These proportions are not the same along the tunnel, so a series of proportions were empirically 
determined. The ratios of rims to spots include 0.50 from 14+45 to 15+35, 0.40 from 15+40 to 
16+52, 0.53 from 16+55 to 17+35, 0.55 from 17+40 to 21+25, and 0.22 from 21+30 to 23+35. 
The total corrected rim plus spot (RStc) was multiplied by these ratios to calculate the amount 
of rims, and the amount of spots was determined by difference (Rtc and Stc, respectively in 
Figure O-11). 
ANL-EBS-MD-000027 REV 03 O-14 September 2004 

Drift Degradation Analysis 
0 
4 
8 
12 
16 
20 
24 
28 
32 
36 
40 
(m) 
(%) 
Rp Sp Ra Sa (M) 
1450 1550 1650 1750 1850 1950 2050 2150 2250 2350 
StationAbundance (length)
RSt Rt c St c Spot s
Source: DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: Rtc represents fitted rim values from the corrected RStc (Figure O-10) based on the ratio of rim and spot 
values in panels and angular data. Stc represents fitted spot values from the corrected RStc 
(Figure O-10) based on the ratio of rim and spot values in panels and angular data. Correlations and 
calculations for Rtc and Stc are described in Section O6.6. Spot values from Mongano et al. (1999 
[DIRS 149850]) are described in Section O6.5. The data and curves are presented in file Drift Deg AMR AF 
T-A-P fit V1.xls, worksheet Length - Fit and Stats (See Table A-1). 
Figure O-11. Abundance of Rims and Spots from Panel Maps (Rp and Sp), Angular (Ra and Sa), and 
the Original Estimated Combined Rim and Spot Values from Tape Traverses (RSt) 
O4. LARGE LITHOPHYSAE 
The large-lithophysae inventory was designed to document the large lithophysae (those with a 
minimum diameter of 50 cm) in the ECRB Cross-Drift from Station 14+00 to 17+56. The initial 
phase of the inventory stopped at 17+56 because of a closed bulkhead 
(DTNs: GS021008314224.002 [DIRS 161910]), and the second phase of the inventory was 
completed from 17+60 to 25+35 after the bulkhead was opened (GS040608314224.001 
[DIRS 171367]). A few large lithophysae were documented (entirely or partially) in the tape and 
angular traverses and panel maps, but most were not included in these other techniques because 
of the scales and locations at which the other measurements were made. The long and short axis 
exposed on the wall of the tunnel was measured (with the same tape on a pole technique used in 
the tape traverses), and the station and position on the tunnel wall was recorded 
(DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]). There 
are accurately surveyed station, northing, easting, and elevation values for the large lithophysae 
(DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]). The 
large-lithophysae data can be displayed by station along the tunnel as discrete features and 5 m 
abundance (simply the number count) (Figure O-12), or a cumulative frequency and frequency 
plots of axis length and area (Figure O-13). 
ANL-EBS-MD-000027 REV 03 O-15 September 2004 

Drift Degradation Analysis 
Source: DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]. 
NOTE: Diagram of tunnel cross-section shows the nomenclature used to identify the position of large lithophysae. 
The small inserted table lists the average number of large lithophysae per meter of tunnel for the left and 
right walls (LW and RW, positions 2 and 6, respectively) and the crown (C, position 4) from Stations 14+70 
to 17+56. 
Figure O-12. Abundance (Number of Large Lithophysae) per 5 m Intervals, Locations, Areas, and Long 
and Short Axes of Large Lithophysae in the Tptpll and Tptpln from ECRB Cross-Drift 
Station 14+50 to 25+00 
ANL-EBS-MD-000027 REV 03 O-16 September 2004 

Drift Degradation Analysis 
Source: DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]. 
NOTE: The data and curves are presented in file Drift Deg AMR AD L-Litho V1.xls, worksheet Tptpll Large-Litho 
Sum Graphs (See Table A-1). 
Figure O-13. Frequency and Cumulative Frequency of the Long Axes and Areas of Large Lithophysae 
in the Tptpll in the Cross-Drift 
O5. CALCULATED POROSITY OF LITHOPHYSAL CAVITIES, RIMS, SPOTS AND 
TOTAL POROSITY ALONG THE TUNNEL 
The corrected tape traverse data for lithophysal cavities, rims, and spots results in fitted 
abundance curves and indicates substantial variations along the tunnel in these features 
(Figure O-14). Using these fitted abundance curves for lithophysal cavities, rims, and spots, 
and (by difference) the matrix-groundmass (and ignoring the trace amount of lithic clasts), the 
porosity of these features and the total porosity along the tunnel can be calculated (Figure O-15). 
The porosities of each of the component features are variably constrained. Lithophysal cavities 
have a porosity of 1.00 cm3/cm3. Samples from the upper and lower lithophysal zone in the 
ECRB Cross-Drift have been used to determine the porosities of the matrix-groundmass, rim, 
and spot features (DTN: GS030483351030.001 [DIRS 163440]). Measured porosity values of 
ANL-EBS-MD-000027 REV 03 O-17 September 2004 

Drift Degradation Analysis 
the matrix-groundmass in samples from the lower lithophysal zone in the ECRB Cross-Drift 
range from 0.09 to 0.14 cm3/cm3, and rims and spots in these same samples range from 0.23 to 
0.37 cm3/cm3, so calculations of porosity in this report use a mean porosity of 0.104 cm3/cm3 for 
matrix-groundmass and 0.30 cm3/cm3 for rims and spots (Otto and Buesch 2003 [DIRS 170727]; 
DTN: GS030483351030.001 [DIRS 163440]). Additionally, inclusion of the large lithophysae 
can locally contribute as much as 9.4 percent to the total porosity (see station 16+10 in 
Figure O-15b). In several other sections of the tunnel, the large lithophysae contribute from 3 to 
6 percent, with other sections having 0 to 2 percent (Figure O-15b). Although for many purposes 
it is appropriate to describe the distributions and porosities of each type of feature (lithophysal 
cavities, large-lithophysal cavities, rims, spots, and matrix-groundmass), these features can be 
combined into similar associations (small and large lithophysal cavities, rims plus spots, and 
matrix-groundmass) (Figure O-16). 
ANL-EBS-MD-000027 REV 03 O-18 September 2004 

Drift Degradation Analysis 
Source: 
DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]. 
NOTE: 
Additional details provided in Section O6.6 and file Drift Deg AMR AF T-A-P fit V1.xls, worksheet Length - Fit and Stats (See Table A-1). Estimates of 
lithophysae (Lithop M) and spots (Spots M) are from Mongano et al. (1999 [DIRS 149850]). 
Figure O-14. 
Abundance Curves of Lithophysal Cavities, Rims, and Spots (Determined by Combining Panel Map and Tape and Angular Traverse 
Data), Large-Lithophysae Based on 5 m Segments of the Tunnel, and Estimates of Lithophysae and Spots 
ANL-EBS-MD-000027 REV 03 O-19 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 O-20 September 2004 
a) 
b) 
Source: DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]. 
NOTES: Porosity of the 5 m averaged large-lithophysae inventory is not included in the total in the upper graph (a). The large-lithophysae values are included in 
the lower graph (b). Additional details provided in Section O6.6 and file Drift Deg AMR AF T-A-P fit V1.xls (See Table A-1). 
Figure O-15. 
Calculated Porosity of Lithophysal Cavities, Rims, Spots, Matrix-Groundmass, and the Total Porosity in the Tptpll Exposed Along 
the ECRB Cross-Drift 

Drift Degradation Analysis 
Source: DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]. 
NOTE: Additional details provided in Section O6.6 and file Drift Deg AMR AF T-A-P fit V1.xls, worksheet Volume 
Percent  Stats (See Table A-1). 
Figure O-16. Calculated Porosity of Lithophysal Cavities (Including Large Lithophysae), the Combination 
of Rims and Spots, Matrix-Groundmass (MGM), and the Total Porosity in the Tptpll 
Exposed in the ECRB Cross-Drift from Station 14+44 to 23+30 
O6. DESCRIPTIVE STATISTICS FOR THE TOTAL LOWER LITHOPHYSAL ZONE 
In addition to the along-the-tunnel variations in abundance, size, and shape of lithophysal 
cavities, rims, and spots, the distributions of these features can be summarized for the total lower 
lithophysal zone. For example, using the tape traverse data, the abundance of cavities in each 
traverse has a mean of 18 to 19 percent depending on the length of tunnel used in the calculation 
(Table O-4, Figure O-17, and Section O6.3). The tape data used in this figure has been adjusted 
to the typical traverse length but has not been corrected with the several correlation 
functions described previously and in Section O6.6. Similarly, the abundance (percent) of 
individual lithophysal cavities within a traverse indicates most lithophysal cavities form about 
2 percent of a traverse length (Table O-5, Figure O-18, and Section O6.3), and the typical length 
of lithophysal cavities along the traverses is about 150 mm (Table O-6, Figure O-19, and 
Section O6.3). Descriptive statistics comparing the 5 m traverse data with 10 m, 15 m, 20 m, 
25 m, and 30 m moving averages indicates no effective change in the mean of 18.9 percent 
lithophysal cavities, but many of the statistics decrease with increasing length of the moving 
average (Table O-7 and Section O6.3). However, the most significant change in the statistics 
for the abundance of lithophysal cavities, especially in the standard deviation and sample 
variance, occurs from the 5 m to 10 m or 15 m data (Table O-7 and Section O6.3). The typical 
abundance of rims plus spots from the tape traverse data is about 8 percent depending on the 
length of tunnel used in the calculation (Table O-8 and Section O6.3). 
ANL-EBS-MD-000027 REV 03 O-21 September 2004 

Drift Degradation Analysis 
Table O-4. Descriptive Statistics for the Abundance of Lithophysal Cavities in Individual Tape Traverses 
for Various Lengths of Tunnel in the Tptpll in the Cross-Drift 
Statistic Data Package Revised 
Stations 2335 to 1405 2335 to 1405 2326 to 1444 2320 to 1460 2200 to 1460 
Length along tunnel (m) 930 930 882 860 740 
Mean 19.4 18.0 18.7 18.9 18.9 
Standard Error 0.7 0.7 0.7 0.7 0.7 
Median 18.8 17.6 17.8 17.8 17.8 
Mode 15.2 16.2 16.2 16.2 16.6 
Standard Deviation 10.2 9.3 8.8 8.7 8.7 
Sample Variance 103.3 86.7 76.9 74.8 75.4 
Kurtosis 0.1 -0.1 0.0 0.1 0.2 
Skewness 0.4 0.3 0.5 0.6 0.6 
Range 53.9 48.4 47.2 47.2 47.2 
Minimum 0.0 0.0 1.2 1.2 1.2 
Maximum 53.9 48.4 48.4 48.4 48.4 
Sum 3,608 3,355 3,298 3,254 2,793 
Count 186 186 176 172 148 
Confidence Level (95.0%) 1.5 1.3 1.3 1.3 1.4 
NOTE: Data in Data Package column from DTN: GS021008314224.002 [DIRS 161910]. The Revised data are in 
Drift Deg AMR AC T-Trav.xls, worksheet Tape data (mm) (see Table A-1). 
0% 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
0 4 8 
li) 
0 
5 
10 
15 
20 
25 
Frequency 
12 16 20 24 28 32 36 40 44 48 52 
Percent of lithophysa cavties in 5-m spaced traverses 
Cumulative Frequency (%
Cum % - DT N 
Cum.% - All 
Cum..% - T runc. 
Freq - DT N 
Freq. - All 
Freq. - T runc. 
NOTE: Data submitted in the original data package (DTN: GS021008314224.002 [DIRS 161910]) is indicated by 
DTN. The All and trunc. data are from the adjusted length traverses (see Section O6.3 and file Drift 
Deg AMR AC T-Trav.xls, worksheet Tape data (percent) [Table A-1]). Truncated data designated as 
Trunc. 
Figure O-17. Frequency (Number) and Cumulative Frequency of the Abundance (Percent) Lithophysal 
Cavities from Tape Traverses in the Tptpll of the ECRB Cross-Drift from 14+05 to 23+35 
(All) and 14+60 to 22+00 (Truncated Data) 
ANL-EBS-MD-000027 REV 03 O-22 September 2004 

Drift Degradation Analysis 
Table O-5. Descriptive Statistics for the Abundance of Individual Lithophysal Cavities in Individual Tape 
Traverses for Various Lengths of Tunnel in the Tptpll in the Cross-Drift 
Statistic Data Package Revised 
Stations 2335 to 1405 2335 to 1405 2326 to 1444 2320 to 1460 2200 to 1460 
Length along tunnel (m) 930 930 882 860 740 
Mean 2.17 2.02 2.02 2.06 2.00 
Standard Error 0.05 0.05 0.05 0.05 0.05 
Median 1.49 1.34 1.34 1.46 1.34 
Mode 1.49 1.33 1.33 1.33 1.33 
Standard Deviation 1.99 1.85 1.83 1.82 1.84 
Sample Variance 3.96 3.43 3.35 3.32 3.38 
Kurtosis 6.32 6.05 6.13 6.16 6.34 
Skewness 2.03 2.01 2.00 2.00 2.03 
Range 17.91 16.09 16.09 16.09 16.09 
Minimum 0.00 0.00 0.00 0.00 0.00 
Maximum 17.91 16.09 16.09 16.09 16.09 
Sum 3607.71 3355.24 3297.95 3254.38 2792.89 
Count 1664 1664 1630 1583 1393 
Confidence Level (95.0%) 0.10 0.09 0.09 0.09 0.10 
NOTE: Data in Data Package column from DTN: GS021008314224.002 [DIRS 161910]. The Revised data are in 
Drift Deg AMR AC T-Trav.xls, worksheet Tape data (percent) (see Table A-1). 
0% 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
0 1 2 3 4 5 6 7 8 9 11 12 14 15 16 18 
0 
50 
ll 
l 
10 13 17 
Percent of individual lithophysal cavities in 5-m spaced traverses 
Cumulative Frequency (%) 
100 
150 
200 
250 
300 
350 
Frequency 
Cum. % - DT N 
Cum. % - ACum. % - T runc. 
Freq. - DT N 
Freq. - AlFreq. - T runc. 
NOTE: Data submitted in the original data package (DTN: GS021008314224.002 [DIRS 161910]) is indicated by 
DTN. The All and Trunc. data are from the adjusted length traverses (see Section O6.3 and file Drift 
Deg AMR AC T-Trav.xls, worksheet Tape data (percent) [Table A-1]). Truncated data designated as 
Trunc. 
Figure O-18. Frequency (Number) and Cumulative Frequency of the Abundance (Percent) of Individual 
Lithophysal Cavities from Tape Traverses in the Tptpll in the Cross-Drift from 14+05 to 
23+35 (All) and 14+60 to 22+00 (Truncated Data) 
ANL-EBS-MD-000027 REV 03 O-23 September 2004 

Drift Degradation Analysis 
Table O-6. Descriptive Statistics for the Lengths (mm) of Individual Lithophysal Cavities in Individual 
Tape Traverses for Various Lengths of Tunnel in the Tptpll zone in the Cross-Drift 
Statistic Data Package Revised 
Stations 2335 to 1405 2335 to 1405 2326 to 1444 2320 to 1460 2200 to 1460 
Length along tunnel (m) 930 930 882 860 740 
Mean 152.6 152.6 152.9 155.4 151.6 
Standard Error 3.4 3.4 3.4 3.4 3.7 
Median 100 100 110 110 100 
Mode 100 100 100 100 100 
Standard Deviation 138.6 138.6 137.0 136.3 137.6 
Sample Variance 19208.3 19208.3 18757.0 18586.5 18926.2 
Kurtosis 6.0 6.0 6.1 6.1 6.3 
Skewness 2.0 2.0 2.0 2.0 2.0 
Range 1200 1200 1190 1190 1190 
Minimum 0 0 10 10 10 
Maximum 1200 1200 1200 1200 1200 
Sum 251723 251723 247413 244143 209393 
Count 1650 1650 1618 1571 1381 
Confidence Level (95.0%) 6.69 6.69 6.67 6.74 7.26 
NOTE: Data in Data Package column from DTN: GS021008314224.002 [DIRS 161910]. The Revised data are in 
Drift Deg AMR AC T-Trav.xls, worksheet Tape data (mm) (see Table A-1). 
0% 
0 100 400 900 
()
l(%) 
0 
5010% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
200 300 500 600 700 800 1000 1100 1200 
Lengthsmm of individual lithophysal cavities in 5-m spaced traverses 
Cumuative Frequency 
100 
150 
200 
250 
300 
350 
400 
450 
Frequency 
Cum. % - DT N 
Cum. % - All 
Cum. % - T runc. 
Freq. - DT N 
Freq. - All 
Freq. - T runc. 
NOTE: Data submitted in the original data package (DTN: GS021008314224.002 [DIRS 161910]) is indicated by 
DTN The All and Trunc. data are from the adjusted length traverses (see Section O6.3 and file Drift 
Deg AMR AC T-Trav.xls, worksheet Tape data (mm) [Table A-1]). Truncated data designated as Trunc. 
Figure O-19. Frequency (Number) and Cumulative Frequency of the Lengths (mm) of Individual 
Lithophysal Cavities from Tape Traverses in the Tptpll of the ECRB Cross-Drift from 14+05 
to 23+35 (All) and 14+60 to 22+00 (Truncated Data) 
ANL-EBS-MD-000027 REV 03 O-24 September 2004 

Drift Degradation Analysis 
Table O-7. Descriptive Statistics for the Abundance of Lithophysal Cavities in Tape Traverses Calculated 
with 10 m, 15 m, 20 m, 25 m, and 30 m moving averages for the Total Tptpll in the ECRB 
Cross-Drift 
Statistic Value 
Stations 2200 to 1460 
Length along tunnel (m) 5-m 
traverses 
10-m 
average 
15-m 
average 
20-m 
average 
25-m 
average 
30-m 
average 
Mean 18.9 18.9 18.9 18.9 18.9 18.9 
Standard Error 0.7 0.6 0.5 0.5 0.5 0.5 
Median 17.8 18.3 18.1 18.3 18.1 18.3 
Mode 16.6 16.7 15.5 23.3 11.8 22.0 
Standard Deviation 8.7 7.0 6.5 6.1 5.9 5.7 
Sample Variance 75.4 48.6 41.8 37.6 35.3 33.0 
Kurtosis 0.2 0.29 0.20 0.00 -0.15 -0.14 
Skewness 0.6 0.55 0.59 0.56 0.49 0.48 
Range 47.2 39.0 31.4 27.9 26.6 27.0 
Minimum 1.2 3.4 7.6 8.9 8.4 8.1 
Maximum 48.4 42.4 39.0 36.8 35.0 35.1 
Sum 2,793 2,890.5 2,887.6 2,890.4 2,897.1 2,897.0 
Count 148 153 153 153 153 153 
Confidence Level (95.0%) 1.4 1.10 1.02 0.97 0.94 0.91 
NOTE: Data in Drift Deg AMR AC T-Trav.xls, worksheet Tape data (percent) (see Table A-1). 
Table O-8. Descriptive Statistics for the Abundance of Rims Plus Spots in Individual Tape Traverses for 
Various Lengths of Tunnel in the Tptpll of the ECRB Cross-Drift 
Statistic Data Package Revised 
Stations 2200 to 1405 2200 to 1405 2200 to 1460 
Length along tunnel (m) 795 795 740 
Mean 8.0 8.0 8.4 
Standard Error 0.6 0.6 0.6 
Median 5.0 5.0 7.5 
Mode 7.5 7.5 7.5 
Standard Deviation 7.1 7.1 7.1 
Sample Variance 50.1 50.1 50.5 
Kurtosis 3.3 3.3 3.1 
Skewness 1.9 1.9 1.9 
Range 32.0 32.0 31.5 
Minimum 0.5 0.5 1.0 
Maximum 32.5 32.5 32.5 
Sum 1257 1257 1233 
Count 157 157 146 
Confidence Level (95.0%) 1.1 1.1 1.2 
NOTE: Data in Data Package column from DTN: GS021008314224.002 [DIRS 161910]. The Revised data are 
in Drift Deg AMR AC T-Trav.xls, worksheet Tape data (percent) (see Table A-1). 
ANL-EBS-MD-000027 REV 03 O-25 September 2004 

Drift Degradation Analysis 
Comparison of the descriptive statistics for abundance of lithophysal cavities, rims, and spots in 
panel maps, angular traverses, and corrected tape traverses in the lower lithophysal zone indicate 
the corrected tape values are consistent with the values determined from the other methods 
(Table O-9 and Section O6.6). These relations are also consistent for various lengths of the 
tunnel such as comparing the segments from 14+60 to 23+20 and 14+60 to 22+00 (Table O-9; 
Section O6.6). The prime section of the tunnel for the lower lithophysal zone is from 14+60 to 
23+20 where the tunnel is entirely within the lower lithophysal zone (i.e., there is no mixing 
from the adjacent rock units). The more restricted section from 14+60 to 22+00 is better to use 
for many detailed descriptions and comparative statistics because there is good overlap of the 
various types of data (panel maps and angular and tape traverses) and there is minimal need to 
extrapolate and convert some of the data. The abundance values for each of the lithostratigraphic 
features can be converted into rock-mass porosity values (using the porosity values of each 
component). Using the porosities of 1.00 cm3/cm3 for lithophysal cavities, 0.25 cm3/cm3 for rims 
and spots, and 0.13 cm3/cm3 for the matrix-groundmass (Flint 1998 [DIRS 100033], Table 7), the 
lower lithophysal zone (as a whole and not including the large lithophysae) averages 
13.1 percent lithophysal cavities, 1.4 percent rims, 1.9 percent spots, and 10.9 percent 
matrix-groundmass for a total porosity of 27.3 percent (Table O-10). Alternatively, using the 
porosities of 1.00 cm3/cm3 for lithophysal cavities, 0.30 cm3/cm3 for rims and spots, 
0.104 cm3/cm3 for the matrix-groundmass (Otto and Buesch 2003 [DIRS 170727]), and 
including the large-lithophysal cavities, the lower lithophysal zone averages 13.1 percent 
lithophysal cavities, 2.0 percent large-lithophysal cavities, 1.7 percent rims, 2.3 percent spots, 
and 8.4 percent matrix-groundmass for a total porosity of 27.5 percent (Table O-11). 
O6.1 DESCRIPTIVE STATISTICS FOR LITHOPHYSAL CAVITIES, RIMS, SPOTS, 
AND LITHIC CLASTS IN PANEL MAPS IN THE Tptpll OF THE ECRB 
CROSS-DRIFT FROM STATIONS 14+93 TO 22+97 
The descriptive statistics for lithophysal cavities, rims, spots, and lithic clasts in panel maps in 
the Tptpll of the ECRB Cross-Drift from Stations 14+93 to 22+97 were determined to support 
the distribution of size and abundance of lithostratigraphic features as described in Sections O2 
and O6.6. Descriptive statistics were determined using data provided in 
DTN: GS021008314224.002 [DIRS 161910] and are reproduced in Table A-1. Descriptive 
statistics are provided for the sizes (actually areas in mm2) and percent of the total area for 
lithostratigraphic features including lithophysal cavities, rims, spots, and lithic clasts. The 
descriptive statistics were determined with the standard functions of commercial off-the-shelf 
software Microsoft Excel 97 SR-2, and are documented in the Microsoft Excel file, 
Drift Deg AMR AA PMap.xls (Table A-1), which can be accessed through the TDMS 
(DTN: MO0408MWDDDMIO.002). 
O6.2 DESCRIPTIVE STATISTICS FOR LITHOPHYSAL CAVITIES, RIMS, SPOTS, 
AND LITHIC CLASTS IN ANGULAR TRAVERSES IN THE Tptpll OF THE 
ECRB CROSS-DRIFT FROM STATIONS 14+60 TO 22+00 
The descriptive statistics for lithophysal cavities, rims, spots, lithic clasts, and 
matrix-groundmass in angular traverses in the Tptpll of the ECRB Cross-Drift from Stations 
14+60 to 22+00 were determined to support the distribution of size and abundance of 
lithostratigraphic features as described in Sections O1 and O6.6. Descriptive statistics were 
ANL-EBS-MD-000027 REV 03 O-26 September 2004 

Drift Degradation Analysis 
determined on data provided in DTN: GS021008314224.002 [DIRS 161910], and were 
determined in support of this report. Descriptive statistics are provided for the sizes (actually 
lengths in mm) and percent of the total lengths for lithostratigraphic features including 
lithophysal cavities, rims, spots, lithic clasts, and the matrix-groundmass. The descriptive 
statistics were determined with the standard functions of commercial off-the-shelf software 
Microsoft Excel 97 SR-2, and are documented in the Microsoft Excel file,Drift Deg AMR AB 
A-Trav.xls (Table A-1), which can be accessed through the TDMS 
(DTN: MO0408MWDDDMIO.002). 
ANL-EBS-MD-000027 REV 03 O-27 September 2004 

Table O-9. Descriptive Statistics for Abundance of Lithophysal Cavities, Rims, and Spots in Panel Maps, Angular Traverses, and Corrected Tape 
Traverses in the Tptpll Exposed in the ECRB Cross-Drift from Stations 14+60 to 23+20 and 14+60 to 22+00 
Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 O-28 September 2004 
Descriptive 
Statistics 
1460 to 2320 m 
1460 to 
2200 m 1460 to 2320 m 
1460 to 
2200 m 1460 to 2320 m 
1460 to 
2200 m 
Cp Ca Ct Ctc LLm5 Ctc-m Rp Ra Rtc Rtc-m Sp Sa Stc Stc-m 
Mean 12.9 15.5 15.0 13.1 1.9 14.0 5.4 9.1 5.6 6.0 3.8 10.1 7.8 7.4 
Standard Error 0.8 1.2 0.4 0.4 0.1 0.4 0.8 0.7 0.2 0.2 1.3 1.4 0.5 0.5 
Median 13.4 15.0 14.6 12.9 1.8 13.6 5.2 8.1 5.2 5.3 2.9 8.3 5.7 5.7 
Mode N/A 15.0 17.9 17.0 0.0 17.0 2.1 11.0 3.0 3.0 3.5 N/A 2.4 2.4 
Standard Deviation 3.6 6.3 5.0 5.3 1.7 5.1 3.4 3.3 3.0 2.9 5.4 6.5 6.2 5.7 
Sample Variance 12.9 39.8 24.7 28.6 2.8 26.0 11.9 11.2 9.2 8.5 28.7 42.3 38.4 32.4 
Kurtosis -0.1 0.8 0.1 -0.2 1.2 0.1 0.4 3.5 0.0 0.0 15.5 0.1 1.3 1.7 
Skewness -0.5 0.0 0.5 0.4 1.0 0.3 0.8 1.6 0.7 0.8 3.8 1.0 1.5 1.5 
Range 13.7 28.5 24.7 25.2 9.4 25.2 13.0 14.8 12.5 11.7 24.0 22.0 23.5 23.0 
Minimum 5.3 2.2 6.0 4.0 0.0 4.0 0.3 4.8 0.9 1.7 0.6 2.3 1.4 1.4 
Maximum 19.0 30.7 30.7 29.2 9.4 29.2 13.3 19.6 13.4 13.4 24.6 24.3 25.0 24.4 
Sum 232.7 418.7 2693.3 2352.8 329.8 2182.9 97.5 200.8 1005.7 934.8 68.1 223.1 1402.7 1151.6 
Count 18 27 180 180 170 156 18 22 179 155 18 22 179 155 
Confidence Level 
(95.0%) 
1.7 2.4 0.7 0.8 0.3 0.8 1.6 1.4 0.4 0.5 2.5 2.7 0.9 0.9 
N/A indicates Not Applicable. 
Source: DTNs: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]. 
NOTE: 
Symbols Cp, Ca, Ct, Ctc are defined in the caption for Figure O-9. LLm5 is Large Lithophysae in 5-m intervals and Ctc-m is Cavities in the 
converted tape data in the main (or prime) part of the tunnel from 1460 to 2200 m. Symbols Rp, Ra, Rt, Rtc are defined in the caption for 
Figure O-11, and Rtc-m are the Rims in the converted tape data in the main (or prime) part of the tunnel from 1460 to 2200 m. Symbols Sp, Sa, 
St, Stc are defined in the caption for Figure O-11, and Stc-m are the Spots in the converted tape data in the main (or prime) part of the tunnel 
from 1460 to 2200 m. The data are presented in Drift Deg AMR AF T-A-P fit V1.xls (See Table A-1). 

Table O-10. Descriptive Statistics for Porosity of Lithophysal Cavities, Rims, and Spots in Panel Maps, Angular Traverses and Corrected Tape 
Traverses in the Tptpll Exposed in the ECRB Cross-Drift from Stations 14+60 to 23+20 (without Large Lithophysae) 
Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 O-29 September 2004 
Rim-
Descriptive Statistic 
Cavities 
(panel) 
Rims 
(panel) 
Spots 
(panel) 
Cavities 
(angular) 
Rims 
(angular) 
Spots 
(angular) 
Cavities 
(tape) 
Spot 
(tape) 
MGM 
(fitted) 
Cavities 
(fitted) 
Rims 
(fitted) 
Spots 
(fitted) 
Total 
(fitted) 
Mean 12.9 1.4 0.9 15.3 2.3 2.5 16.4 2.1 10.9 13.1 1.4 1.9 27.3 
Standard Error 0.8 0.2 0.3 1.5 0.2 0.3 0.4 0.1 0.1 0.4 0.1 0.1 0.3 
Median 13.4 1.3 0.7 14.8 2.0 2.1 16.0 1.6 10.8 12.9 1.3 1.4 27.4 
Mode N/A 0.5 0.9 N/A 2.8 N/A 16.2 1.3 10.5 17.0 0.7 0.6 30.0 
Standard Deviation 3.6 0.9 1.3 6.9 0.8 1.6 4.8 1.7 0.7 5.3 0.8 1.6 4.5 
Sample Variance 12.9 0.7 1.8 47.2 0.7 2.6 22.9 2.9 0.5 28.6 0.6 2.4 20.2 
Kurtosis -0.14 0.42 15.49 0.37 3.45 0.08 0.14 3.58 0.66 -0.17 0.00 1.26 0.66 
Skewness -0.51 0.76 3.82 0.10 1.63 0.98 0.44 1.99 -0.42 0.42 0.67 1.48 0.42 
Range 13.7 3.2 6.0 28.5 3.7 5.5 27.0 7.8 3.5 25.2 3.3 6.2 23.2 
Minimum 5.3 0.1 0.2 2.2 1.2 0.6 5.5 0.3 8.7 4.0 0.0 0.0 18.5 
Maximum 19.0 3.3 6.2 30.7 4.9 6.1 32.5 8.1 12.2 29.2 3.3 6.2 41.7 
Sum 232.7 24.4 17.0 336.8 50.2 55.8 2894.3 311.4 1955.9 2352.8 251.4 350.7 4910.7 
Count 18 18 18 22 22 22 177 150 180 180 180 180 180 
Confidence Level (95.0%) 1.7 0.4 0.6 2.9 0.3 0.7 0.7 0.3 0.1 0.8 0.1 0.2 0.7 
N/A indicates Not Applicable. 
Source: 
DTN: GS021008314224.002 [DIRS 161910]. 
NOTE: 
Porosity of the Rim and Spot material was calculated with a mean values of 0.25 cm3/cm3 and matrix-groundmass (MGM) was calculated with a mean 
value of 0.13 cm3/cm3, and Rim-Spot (tape data) is only from 14+60 to 22+00. The data are presented in file 
Drift Deg AMR AF T-A-P fit V1.xls, worksheet Volume Percent  Stats (See Table A-1). 

Table O-11. Descriptive Statistics for Porosity of Lithophysal Cavities, Rims, and Spots in Panel Maps, Angular Traverses and Corrected Tape 
Traverses and the Large Lithophysae Inventory in the Tptpll Exposed in the ECRB Cross-Drift from Stations 14+60 to 23+20 
Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 O-30 September 2004 
Rim-
Descriptive 
Statistic 
Cavities 
(panel) 
Rims 
(panel) 
Spots 
(panel) 
Cavities 
(angular) 
Rims 
(angular) 
Spots 
(angular) 
Cavities 
(tape) 
Spot(tape) 
MGM 
(fitted) 
Cavities 
(fitted) 
Rims 
(fitted) 
Spots 
(fitted) 
L-Litho 
(5m) 
Total 
(fitted) 
Mean 12.9 1.6 1.1 15.3 2.7 3.0 15.0 4.0 8.4 13.1 1.7 2.3 2.0 27.5 
Standard Error 0.8 0.2 0.4 1.5 0.2 0.4 0.4 0.2 0.0 0.4 0.1 0.1 0.1 0.4 
Median 13.4 1.5 0.9 14.8 2.4 2.5 14.6 3.0 8.4 12.9 1.6 1.7 1.8 27.3 
Mode N/A 0.6 1.1 N/A 3.3 N/A 17.9 1.6 7.9 17.0 0.9 0.7 0.0 31.9 
Standard Deviation 3.6 1.0 1.6 6.9 1.0 2.0 5.0 2.3 0.6 5.3 0.9 1.9 1.7 5.6 
Sample Variance 12.9 1.1 2.6 47.2 1.0 3.8 24.7 5.2 0.4 28.6 0.8 3.5 2.9 31.3 
Kurtosis -0.14 0.4 15.5 0.37 3. 5 0.1 0.1 -0.6 0.7 -0.2 0.0 1.3 0.9 0.7 
Skewness -0.51 0.8 3.8 0.10 1.6 1.0 0.5 0.7 -0.6 0.4 0.7 1.5 0.9 0.6 
Range 13.7 3.9 7.2 28.5 4.4 6.6 24.7 9.4 3.3 25.2 4.0 7.5 9.4 28.9 
Minimum 5.3 0.1 0.2 2.2 1.4 0.7 6.0 0.0 6.3 4.0 0.0 0.0 0.0 16.6 
Maximum 19.0 4.0 7.4 30.7 5.9 7.3 30.7 9.4 9.7 29.2 4.0 7.5 9.4 45.4 
Sum 232.7 29.2 20.4 336.8 60.2 66.9 2693.3 625.9 1514.8 2352.8 301.7 420.8 359.0 4949.1 
Count 18 18 18 22 22 22 180 156 180 180 180 180 178.0 180.0 
Confidence Level 
(95.0%) 1.7 0.5 0.7 2.9 0.4 0.8 0.7 0.4 0.1 0.8 0.1 0.3 0.3 0.8 
N/A indicates Not Applicable. 
Source: DTN: GS021008314224.002 [DIRS 161910]; GS040608314224.001 [DIRS 171367]. 
NOTE: 
Porosity of the Rim and Spot material was calculated with a mean values of 0.30 cm3/cm3 and matrix-groundmass (MGM) was calculated with a 
mean value of 0.104 cm3/cm3 (Section O5 and O6.6), and Rim-Spot (tape data) is only from 14+60 to 22+00. The data are presented in file Drift Deg 
AMR AF T-A-P fit V1.xls, worksheet Volume Percent  Stats (See Table A-1). 

Drift Degradation Analysis 
O6.3 DESCRIPTIVE STATISTICS FOR LITHOPHYSAL CAVITIES, RIMS, SPOTS, 
AND LITHIC CLASTS IN TAPE TRAVERSES IN THE Tptpll OF THE ECRB 
CROSS-DRIFT FROM STATIONS 14+05 TO 23+35 
The descriptive statistics for lithophysal cavities, rims, spots, and lithic clasts in tape traverses in 
the Tptpll of the ECRB Cross-Drift from Stations 14+05 to 23+35 were determined to support 
the distribution of size and abundance of lithostratigraphic features as described in Sections O1 
and O6.6. Descriptive statistics were determined on data provided in 
DTN: GS021008314224.002 [DIRS 161910], and were determined in support of this report. 
The lengths of the tape traverses in the original data package (DTN: GS021008314224.002 
[DIRS 161910]) were longer or shorter than those determined at the same locations with the 
angular traverses, so the tape traverse lengths were corrected using the angular traverse lengths 
and resulted in typical traverse lengths. The typical traverse lengths used to determine the 
abundance of lithophysal cavities are 7.46 m from 14+20 to 17+55 (double vent line), and 
7.53 m from 17+65 to 23+35 (single vent line). Descriptive statistics and histograms are 
provided for the sizes (actually lengths in mm) and percent of the individual and total lengths for 
lithophysal cavities and the total percent of the visually estimated amounts of rims plus spots. 
Descriptive statistics were determined for individual traverses, 10 m, 15 m, 20 m, 25 m, and 
30 m running averages and for total lithophysal cavities. The descriptive statistics and 
histograms were determined with the standard functions of commercial off-the-shelf software 
Microsoft Excel 97 SR-2, and are documented in the Microsoft Excel file, 
Drift Deg AMR AC T-Trav.xls (Table A-1), which can be accessed through the TDMS 
(DTN: MO0408MWDDDMIO.002). 
Adjustments were made to the tape data in the Microsoft Excel file, 
Drift Deg AMR AC T-Trav.xls (Table A-1), for the calculation of moving averages where there 
is a gap in the data. A gap occurs where a tape traverse was not made including the locations 
of a few panel maps. A description of the calculation of moving averages includes the 
following: 
A. Running averages of tape traverse data were made for 10, 15, 20, 25, and 30 meters. 
These cells (Microsoft Excel file, Drift Deg AMR AC T-Trav.xls [Table A-1]) have no 
color fill. 
B. The standard averaging practice includes: 
 10 m: value averaged with next value below (down tunnel to next station) 
 15 m: value averaged with value above and value below 
 20 m: value averaged with value above and next 2 values below 
 25 m: value averaged with 2 values above and 2 values below 
 30 m: value averaged with 2 values above and next 3 values below. 
C. Where a gap in data occurs, the affected cell contains a comment, and may be 
color-coded. A gray color-coded cell indicates a null value was adjusted by averaging 
values of adjacent cells. Gray cells may indicate adjustments of null values on 5 m 
increments or on less than 5 m increments. 
ANL-EBS-MD-000027 REV 03 O-31 September 2004 

Drift Degradation Analysis 
D. In some cases where a gap in data occurs in an adjacent cell on an increment less than 
5 m, the affected cell was not color coded, but a comment was included indicating a 
default to standard averaging practice using the next 5 m increment. Where a gap in 
data occurs on a 5 m increment, adjustments were made, and affected cells were 
colored light turquoise. 
E. The standard adjustment (rule 1) for data gaps consists of: 
 10 m: two values below null value averaged 
 15 m: one value above and 2 values below null value are averaged 
 20 m: one value above and 3 values below null value are averaged 
 25 m: two values above and 3 values below null value are averaged 
 30 m: two values above and 4 values below null value are averaged. 
F. A light yellow cell located in the first 12 rows indicates a gap in the data. A light 
yellow cell located in the running average section indicates a situation where rule 1 
was altered to avoid using null values in adjacent cells. In an effort to lessen the effect 
of data spikes in the tape traverse data, the above procedure (rule 1) for adjustments 
was departed to capture a smaller value in place of a larger value where the choice was 
available. (light green cells). 
Sample variance of the summed lengths of lithophysal cavities in the 5 m data and the 10 m to 
30 m moving average data indicates (1) variations along the tunnel and (2) the most significant 
minimization in variance in the 10 m and 15 m moving average data. Sample variance is a 
measure of the variability of the values relative to the mean value, so variations in the variance 
provide insight into the internal lithostratigraphic features of the lower lithophysal zone. Sample 
variance along the tunnel indicates there are segments (from Stations 15+00 to 18+05 and 19+90 
to 21+80) that have significantly greater amounts of cavities than is typical for the 
lithostratigraphic unit as a whole (Figure O-20). As discussed in Section O3, the amounts of 
lithophysal cavities measured behind the bulkhead at 22+01 are probably over estimates, so the 
larger variances from 22+45 to 23+35 must be viewed with caution. Comparison of the variance 
in the 5 m data and 10 m to 30 m moving average data provides a measure of length scales across 
which the data have large or small variations. The 5 m data has the largest variation in values 
and progressively longer moving average values have smaller variations, but regardless of 
moving average or not, the data maintain the along-the-tunnel variations in the abundance of 
lithophysal cavities (Figure O-20). Differences in sample variance pairs of data at each station 
indicate the greatest step in minimizing the variance is with the 10 m or 15 m moving averages 
(Figure O-21). For example, subtracting the 10 m moving average value from the 5 m data 
results in numerous values larger or small than 4,000, and subtracting the 15 m moving average 
value from the 10 m moving average value results in only a few values larger or smaller 
than 2,000. 
ANL-EBS-MD-000027 REV 03 O-32 September 2004 

Drift Degradation Analysis 
0 
(m) 
Sample Variance20000 
40000 
60000 
80000 
100000 
120000 
140000 
160000 
1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 
Station5 m data 
10-m ave. 
15-m ave. 
20-m ave. 
25-m ave. 
30-m ave. 
NOTE: Data and graph are from the adjusted length traverses (see Table A-1, Drift Deg AMR AC T-Trav.xls, 
worksheet Tape data (mm)). 
Figure O-20. Sample Variance in the Summed Length of Lithophysal Cavities Based on 5 m Data 
and 10 m to 30 m Moving Average Data from Tape Traverses in the Tptpll of the ECRB 
Cross-Drift from 14+05 to 23+35 
ANL-EBS-MD-000027 REV 03 O-33 September 2004 

Drift Degradation Analysis 
0 
1400 1500 2300 
(m) 
-100000 
-80000 
-60000 
-40000 
-20000 
20000 
40000 
60000 
80000 
100000 
1600 1700 1800 1900 2000 2100 2200 
StationDifference in sample variance 
5m - 10m 
10m -15m 
15m -20m 
20m -25m 
25m -30m 
NOTE: Data and graph are from the adjusted length traverses (see Table A-1, Drift Deg AMR AC T-Trav.xls, 
worksheet Tape data (mm)). 5 m to10 m is the difference in sample variance at each station of the 5 m 
data minus the variance of 10 m data. 
Figure O-21. Differences in Sample Variance in the Summed Length of Lithophysal Cavities with Pairs of 
Various Moving Average Data from Tape Traverses in the Tptpll of the ECRB Cross-Drift 
from 14+05 to 23+35 
O6.4 DESCRIPTIVE STATISTICS FOR LARGE LITHOPHYSAE FROM THE 
LARGE-LITHOPHYSAL INVENTORY IN THE Tptpll OF THE ECRB CROSSDRIFT 
FROM STATIONS 14+50 TO 17+56 
The descriptive statistics for lithophysal cavities, rims, spots, and lithic clasts in large-lithophysal 
inventory in the Tptpll of the ECRB Cross-Drift from Stations 14+50 to 17+56 were determined 
to support the distribution of size and abundance of lithostratigraphic features as described in 
Sections O5 and O6.6. Descriptive statistics were determined on data provided in 
DTN: GS021008314224.002 [DIRS 161910], and were determined in support of this report. 
Descriptive statistics are provided for the sizes (actually areas in mm2) and percent of the 
individual and total area for lithophysal cavities for 5 m long and 10 m long tunnel segments. 
The descriptive statistics were determined with the standard functions of commercial 
off-the-shelf software Microsoft Excel 97 SR-2, and are documented in the Microsoft Excel file, 
Drift Deg AMR AD L-Litho V1.xls (Table A-1), which can be accessed through the TDMS 
(DTN: MO0408MWDDDMIO.002). 
ANL-EBS-MD-000027 REV 03 O-34 September 2004 

Drift Degradation Analysis 
O6.5 DESCRIPTIVE STATISTICS FOR ABUNDANCE OF LITHOPHYSAE AND 
SPOTS IN THE Tptpll ALONG THE ECRB CROSS-DRIFT FROM STATIONS 
14+05 TO 23+35 
The descriptive statistics for the abundance of lithophysae and spots in the Tptpll of the ECRB 
Cross-Drift from Stations 14+05 to 23+25 were compiled in support of the calculation of the 
distribution of the abundance of lithostratigraphic features as described in Sections O4 and O6.6. 
Descriptive statistics were determined from (and are consistent with) values described in 
Mongano et al. (1999 [DIRS 149850], Tables 3 and 4). The descriptions presented in Mongano 
et al. (1999 [DIRS 149850], Tables 3 and 4) are summarized in the Microsoft Excel file, Drift 
Deg AMR AE Mongano.xls (Table A-1), and specific values for drift segments presented in 
Tables 3 and 4 (Mongano et al. 1999 [DIRS 149850]) are listed in 5 m station increments to 
facilitate plotting of and determining descriptive statistics for the data. The estimated median 
and maximum values are summarized in Table O-12 where the median values do not include 
local maximum values and the maximum values include only the maximum values. The 
descriptive statistics were determined with the standard functions of commercial off-the-shelf 
software Microsoft Excel 97 SR-2. The Microsoft Excel file, Drift Deg AMR AE Mongano.xls 
(Table A-1), can be accessed through the TDMS (DTN: MO0408MWDDDMIO.002). 
O6.6 CORRELATIONS AND CORRECTIONS TO TAPE TRAVERSE DATA AND 
DETERMINATION OF BEST FIT VALUES OF LITHOPHYSAL CAVITIES, 
RIMS, SPOTS, AND MATRIX-GROUNDMASS IN THE Tptpll ALONG THE 
ECRB CROSS-DRIFT 
To produce the best fit values for lithophysal cavities, rims, spots, and matrix-groundmass 
located every 5 m along the ECRB Cross-Drift, the tape traverse data output for cavities and 
rims plus spots were initially corrected to the angular traverse data, then panel map data, and 
finally with one more set of empirical correction factors. The panel map and angular traverse 
data are not corrected and are from the original lithophysal study data package 
(DTN: GS021008314224.002 [DIRS 161910]) and the tape traverse data are from the file Drift 
Deg AMR AC T-Trav.xls (Table A-1). The basic data including 10 m to 30 m moving averages 
of tape data, correlation equations, and empirical corrections are included in the Microsoft Excel 
file, Drift Deg AMR AF T-A-P Fit V1.xls (Table A-1), and can be accessed through the TDMS 
(DTN: MO0408MWDDDMIO.002). The descriptive statistics in the Length - Fit and Stats 
and Volume Percent - Stats worksheets were determined with the standard functions of 
commercial off-the-shelf software Microsoft Excel 97 SR-2. A description of the worksheets 
contained in Drift Deg AMR AF T-A-P Fit V1.xls (Table A-1) is provided as follows: 
A. The T-A-P Cav Fit worksheet contains lithophysal cavity data from the tape and 
angular traverses and panel maps, and compares and correlates the tape and angular 
traverse data using equations of correlation. The abundance of cavities is calculated 
using the tape data and correlation equation and results in values every 5 m along the 
tunnel (symbol Ct). The Ct values are used in the Length - Fit and Stats 
worksheet. 
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Drift Degradation Analysis 
Table O-12. Descriptive Statistics for Median and Maximum Abundance (Percent) of Lithophysal 
Cavities and Spots in the Tptpll Exposed in the ECRB Cross-Drift from Stations 14+44 to 
23+26 
Descriptive Statistics 
1444 to 2326 1460 to 2320 
Lithop (M) Spots (M) 
Spot 
(M Por) Lithop (M) Spots (M) 
Spot 
(M Por) 
Estimated Mean Values 
Mean 8.67 13.52 3.38 8.81 13.35 3.34 
Standard Error 0.33 0.89 0.22 0.34 0.90 0.23 
Median 7.50 7.00 1.75 7.50 7.00 1.75 
Mode 10.00 6.00 1.50 10.00 6.00 1.50 
Standard Deviation 4.56 12.15 3.04 4.57 12.14 3.03 
Sample Variance 20.82 147.63 9.23 20.84 147.31 9.21 
Kurtosis 3.21 -0.58 -0.58 3.18 -0.47 -0.47 
Skewness 1.53 1.09 1.09 1.52 1.14 1.14 
Range 23.00 37.00 9.25 23.00 36.00 9.00 
Minimum 2.00 3.00 0.75 2.00 4.00 1.00 
Maximum 25.00 40.00 10.00 25.00 40.00 10.00 
Sum 1612.00 2514.50 628.63 1586.00 2403.50 600.88 
Count 186 186 186 180 180 180 
Confidence Level(95.0%) 0.66 1.75 0.44 0.67 1.77 0.44 
Estimated Maximum Values 
Mean 12.27 12.27 4.20 12.48 16.63 4.16 
Standard Error 0.40 0.40 0.24 0.40 0.99 0.25 
Median 10.00 10.00 2.50 10.00 10.00 2.50 
Mode 15.00 15.00 1.75 15.00 7.00 1.75 
Standard Deviation 5.39 5.39 3.33 5.35 13.27 3.32 
Sample Variance 29.05 29.05 11.06 28.59 176.00 11.00 
Kurtosis 1.78 1.78 -0.95 1.82 -0.86 -0.86 
Skewness 1.13 1.13 0.87 1.15 0.92 0.92 
Range 27.00 27.00 9.25 27.00 35.00 8.75 
Minimum 3.00 3.00 0.75 3.00 5.00 1.25 
Maximum 30.00 30.00 10.00 30.00 40.00 10.00 
Sum 2283.00 2283.00 781.75 2247.00 2994.00 748.50 
Count 186 186 186 180 180 180 
Confidence Level(95.0%) 0.77 0.77 0.48 0.78 1.94 0.48 
Source: Mongano et al. 1999 [DIRS 149850], Tables 3 and 4. 
NOTE: Data from Mongano et al. 1999 [DIRS 149850] (Tables 3 and 4) utilized for 5 m station increments. See Drift 
Deg AMR AE Mongano.xls (Table A-1). 
B. The T-A-P R-S Fit worksheet contains estimated rims plus spot data from the tape 
traverses and angular traverse and panel map data, and compares and correlates the 
tape and angular traverse data using equations of correlation. The abundance of rims 
plus spots is calculated using the tape data and correlation equation and results in 
values every 5 m along the tunnel. These calculated tape values are adjusted to the 
angular traverse and panel map values by empirically determined correction factors 
and result in best fit values Rims+Spots (tape-cor). The Rims+Spots (tape-cor) 
values are used in the Length - Fit and Stats worksheet. 
ANL-EBS-MD-000027 REV 03 O-36 September 2004 

Drift Degradation Analysis 
C. The Length - Fit and Stats worksheet summarize lithophysal cavity, rim, and spot 
data from the corrected tape traverses and the angular traverses and panel maps, and is 
used to develop fitted abundance along the tunnel. The Ct values are from the 
T-A-P Cav Fit worksheet, and the Rims+Spots (tape-cor) values are from the 
T-A-P R-S Fit worksheet. Fitted cavity, rim, and spot curves are developed using 
corrected tape values that are adjusted by to the angular traverse and panel map values 
with empirically determined correction factors. Descriptive statistics for abundance of 
cavities, rims, and spots are determined for data along the tunnel from Stations 
14+60 to 23+20, the best technical data from 14+60 to 22+00, and as a average 
for the entire Tptpll zone. 
D. The Volume Percent - Stats worksheet replicates the Length - Fit and Stats 
worksheet, but the porosity is calculated every 5 m along the tunnel and is averaged 
for the total length of the Tptpll zone. The amount of matrix-groundmass is 
determined by difference (100 minus the sum of cavities, rims, and spots). Based on 
the description of lithostragraphic features related to lithophysae (Figure 6-3), the 
porosity of lithophysal cavities is considered to be 1.00 (cm3/cm3), rims and spots are 
0.30 (cm3/cm3), and the matrix-groundmass is 0.104 (cm3/cm3). Descriptive statistics 
for the porosity of cavities, rims, and spots are determined for data along the tunnel 
from Stations 14+60 to 23+20, the best technical data from 14+60 to 22+00, and as 
an average for the entire Tptpll zone. 
This report provides alternative methods for both the calculation of the porosity of 
features and the inclusion of the large lithophysal inventory data, and the differences 
in these approaches is shown by the fitted mean porosity values in Table O-13. 
Relative to Method A in Table O-13, an increase in mean porosity of the rims and spot 
material results in slight increases in the fitted rims and spots, and the decrease in 
the mean porosity of the matrix-groundmass material results in a decrease in the 
fitted matrix-groundmass. A cumulative effect of these changes in the mean 
porosity of the rim, spot, and matrix-groundmass materials is that the total fitted 
porosity decreased by 1.6 percent resulting primarily from the larger amount of 
matrix-groundmass than rim and spot materials (see Method B in Table O-13). The 
inclusion of the large lithophysal cavities slightly reduced the fitted 
matrix-groundmass to 8.4 percent because the large lithophysal cavity porosity is 
subtracted at each station and increased the total fitted porosity to 27.5 percent (see 
Method C in Table O-13). 
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Drift Degradation Analysis 
Table O-13. Mean Porosity of Lithophysal Cavities, Large-Lithophysal Cavities, Rims, Spots, Matrix-
groundmass, and Total Porosity in the Tptpll Exposed in the ECRB Cross-Drift from 
Stations 14+60 to 23+20 Using Three Methods 
Fitted Features 
Method A: Excluding 
Large Lithophysae 
(from Table O-10) a 
Method B: Excluding 
Large Lithophysae with 
Modified Calculation of 
Porosity Features b 
Method C: Including 
Large Lithophysae with 
Modified Calculation of 
Porosity Features (from 
Table O-11) c 
Cavities 13.1 13.1 13.1 
Large-lithophysae N/A N/A 2.0 
Rims 1.4 1.7 1.7 
Spots 1.9 2.3 2.3 
Matrix-groundmass 10.9 8.6 8.4 
Total 27.3 25.7 27.5 
N/A indicates Not Applicable. 
a 
Mean porosity of the matrix-groundmass is 0.13 cm3/cm. The mean porosity of the rims and spots is estimated 
to range from 0.20 to 0.30 cm3/cm3 (with a mean porosity of 0.25 cm3/cm3). The large lithophysae data are not 
included. The full table of descriptive statistics is provided in Table O-10. 
b 
Mean porosity of the matrix-groundmass is 0.104 cm3/cm3. The mean porosity of the rims and spots is 0.30 
3
cm/cm3, and the large lithophysae data are included (DTN: MO0408MWDDDMIO.002, file Drift Deg AMR 
AF T-A-P V1.xls, worksheet Volume Percent  Stats (see Table A-1).
c 
Mean porosity of the matrix-groundmass is 0.104 (cm3/cm3). The mean porosity of the rims and spots is 0.30 
3
cm/cm3. The large lithophysae data are included. The full table of descriptive statistics is provided in 
Table O-11.
O6.7 ACCURACY OF MEASURED AND CALCULATED VALUES 
The accuracy of measured values must be understood in the context of three conditions: (1) the 
specific measurements made on features, (2) conditions that affect the measurements, and 
(3) how well the measurements and the summed and calculated values represent the 
three-dimensional distributions of the features. 
Accuracy of Measured Data for Each of the Four Data Collection MethodsThe panel maps 
are at a 1:10 scale and measurements are recorded to the nearest millimeter. Individual 
measurements in the panel maps can be accurate to 1 or 2 mm for small or narrow features; 
however, large, irregularly shaped objects (those with dimensions of several decimeters) can be 
accurate to 10 to 50 mm depending on how the data collector identifies the long and short axes. 
Angular traverses are measured in degrees and minutes, and the recorded values are rounded to 
the nearest 5 minutes. In the ECRB Cross-Drift, an arc of 5 minutes calculates to about 4 mm on 
the tunnel wall, and this is also about the diameter of the laser beam. Pragmatically, the 
identification of the edge of a feature is a function of how sharp (or gradational) is the edge and 
the conditions in the tunnel. The edges of most features including lithophysal cavities, rims, and 
spots are relatively sharp (can be identified to less than 2 mm in width) with close examination. 
However for most features, the distance from the data collector to the tunnel wall was 1 to 3.5 m, 
so even with binoculars, the accuracy of the measurement is about 15 minutes (about 10 mm). 
The conditions in the tunnel during collection of the angular traverse data included the need to 
wear safety glasses (and at times a respirator), irregular distribution of tunnel illumination, dust 
cover on the tunnel walls, irregularities (breakouts) along the tunnel walls, and obstructions to 
ANL-EBS-MD-000027 REV 03 O-38 September 2004 

Drift Degradation Analysis 
the line of sight and the need to estimate positions of features. With these various conditions, a 
practical accuracy is probably 5 to 40 minutes (about 4 to 30 mm) for any given measurement. 
The tape (stadia rod) used for the tape traverses is divided into decimeters and centimeters, and 
the data can be recorded to the nearest 1 cm. However, based on the projection of the cavity 
walls to the tape, the difficulties in positioning the tape along the wall result in a practical 
accuracy of probably 2 to 10 cm for any given measurement. 
Similar to the tape traverse measurements, the tape (stadia rod) used in the large-lithophysae 
inventory is divided into decimeters and centimeters, and the data can be recorded to the nearest 
1 cm. However, based on the projection of the cavity walls to the tape, the difficulties in 
positioning the tape along the wall result in a practical accuracy probably 2 to 10 cm for any 
given measurement. 
Conditions that Affect the Accuracy and Use of MeasurementsIn the panel maps there are 
three main conditions that can affect the accuracy of the values (others are described in the data 
package for DTN: GS021008314224.002 [DIRS 161910]): 
1. The boundaries of features in the panel maps are based on photographic interpretation, 
hand-drawn maps compiled in the tunnel, and values measured in the tunnel and 
recorded in the Excel workbooks. Boundaries of features are typically sharp (as 
described above); however, the portrayal of the boundaries, regardless of being 
observations in the tunnel or as photographic interpretation, is a bit subjective; 
therefore, it can affect the accuracy of the feature boundaries. The subjective aspects 
typically arise where the edge of a feature does not occur on the tunnel wall (i.e., in a 
broken out lithophysal cavity or block bounded by fractures). The attempted balance 
used by the mapper is to project the contact to the plane of the tunnel wall, which is 
the plane on which the map is made, but also depict the contact where it appears to 
be on the photograph and would be viewed by other users. In part, this is an issue of 
perspective, but it does not affect the total percent of features by more than 1 to 
3 percent. 
2. A few of the panels from 17+63 to 23+00 were not washed as well as the ones from 
14+90 to 17+63; therefore, the photographs of the tunnel walls were not as helpful for 
mapping the features. One result of the incomplete washing was that some of the 
features were more difficult to identify in the photograph than in other locations. 
A second result was that some of the lithophysal cavities that had been backfilled with 
rock flour from the tunnel boring machine were not cleaned out; therefore, they were 
excavated by hand and hammer. Because the photographs were taken before this 
additional excavation, the edges of the lithophysae were approximated and drawn on 
the photograph. 
3. Rocks in the panel maps have distributions in the sizes and spatial positions of 
lithostratigraphic features; therefore, the position of the map-area (1x3 m) box can 
result in variations in areas. Panel map 1641-44L was used to compare the original 
position of the map area (that which is included in the data package) and four other 
alternative positions. The alternative positions were selected such that one position is 
ANL-EBS-MD-000027 REV 03 O-39 September 2004 

Drift Degradation Analysis 
to the upper left of the original position, and the other alternative positions are to the 
upper right, lower right, and lower left (respectively) of the original position. 
Descriptive statistics on the percent areas determined from the five map positions 
indicate the matrix-groundmass and lithophysal cavities have 95 percent confidence 
levels of less than 4 percent and the rims, spots, and lithic clasts have 95 percent 
confidence levels of less than 0.5 percent (Table O-14). 
Table O-14. Comparative Values from the Original Position of the Panel Map and Four 
Alternative-Position Maps 
Map positions No. of Objects MGM % L-cavities % L-rims % Spots % C-Lithic % 
OP 117 71.61 19.01 5.75 3.49 0.14 
AP1 90 70.35 21.70 5.13 2.77 0.05 
AP2 110 75.69 15.52 5.01 3.54 0.24 
AP3 106 76.75 14.45 4.91 3.65 0.24 
AP4 99 75.77 15.89 5.20 3.08 0.05 
Descriptive statistics No. of Objects MGM % L-cavities % L-rims % Spots % C-Lithic % 
Mean 104.40 74.03 17.31 5.20 3.31 0.15 
Standard Error 4.63 1.28 1.33 0.15 0.17 0.04 
Median 106.00 75.69 15.89 5.13 3.49 0.14 
Standard Deviation 10.36 2.85 2.98 0.33 0.37 0.09 
Sample Variance 107.30 8.15 8.89 0.11 0.14 0.01 
Range 27.00 6.40 7.25 0.84 0.88 0.19 
Minimum 90.00 70.35 14.45 4.91 2.77 0.05 
Maximum 117.00 76.75 21.70 5.75 3.65 0.24 
Confidence Level(95.0%) 12.86 3.54 3.70 0.40 0.46 0.12 
Source: DTN: GS021008314224.002 [DIRS 161910], Table S03045_001, file Tptpll Lithop Data Sum Sheet 
15Nov02.doc. 
NOTE: OP = original position, AP = alternative position, MGM = matrix-groundmass, L-cavities = lithophysal 
cavities, L-rims = rims on lithophysae, C-Lithic = lithic clasts. 
In the tape traverse data there are three main conditions that can affect the accuracy of the values 
(others are described in the data package for DTN: GS021008314224.002 [DIRS 161910]): 
1. In the data package, the amounts of lithophysal cavities in the tape traverses from 
21+25 to 23+35 are greater than (and from 22+01 to 23+35 much greater than) those 
documented in panel maps and angular traverses. This segment of the tunnel was the 
first to have data collected and it contains abundant spots. Re-examination of the 
exposures from 21+25 to 22+01 indicates many of the initially identified lithophysae 
are spots, although some spots have a thin stringer or veinlet inside, and this appears to 
have lead to the identification as lithophysae. 
2. Tape traverse data were collected by three collectors, and there appears to be a slight 
variation in the estimated amounts of rims and spots depending on the different 
collectors. There are slightly smaller estimates in the section from 14+00 to 17+63 
compared to the section from 17+63 to 22+01. Additionally, some of the 
measurements of rims and spots from the panel maps and angular traverses in these 
ANL-EBS-MD-000027 REV 03 O-40 September 2004 

Drift Degradation Analysis 
sections of the tunnel appear to confirm the smaller visual estimates determined in the 
tape traverse. However, other panel map and angular traverse data appears to indicate 
the visual estimates determined in the tape traverse are underestimated. Adjustments 
of the tape data are described in Sections O4 and O6. 
3. In the tape traverse data, one component used in calculating the abundance of 
lithophysal cavities is the total length of the traverse. The length of the traverse results 
from the amount of construction materials in the tunnel and the height of the 
laser-prism above the invert (see Figure O-1 and the data package for 
DTN: GS021008314224.002 [DIRS 161910] for a detailed discussion). The traverses 
began at the top of the compressed air pipe and ended at the top of the conveyor belt, 
and the construction materials that affected the length include pipes, electrical lines, 
steel sets, vent lines, the conveyor belt and frame, and other equipment. Although the 
influence of the laser-prism height on the length was discussed by investigators, it was 
never specified and not explicitly recorded. Initially (from Station 22+00 to 19+80), 
the total and visible lengths were measured for each traverse with a wheel on the end 
of the extension rod/handle. At Station 19+80 the compiler determined that most 
measured lengths and tunnel conditions were similar enough that the visible length of 
6.7 m was used as the standard value for the remainder of the traverses to Station 
14+05. Some of the angular traverses were measured at the same locations as the tape 
traverses, and the calculated visible lengths vary from 7.0 to 7.8 m (these values do not 
include the traverses where there is no vent line or conveyor). This comparison 
indicates the 6.7 m visible length is probably too short for most of the tape traverses. 
The amount of difference in the calculated percent based on the total length of the 
traverse is proportional to the amount of cavities measured such that a traverse with 
only a few percent cavities is barely affected whereas the traverse with the most 
cavities is affected the most. For example, the greatest effect occurs in the traverse at 
16+00 with 3.6 m length of cavities, so with a 6.7 m length, the cavities form 
53.9 percent of the tunnel wall. If the visible length of the tape traverse is adjusted to 
7.2 m, the calculated abundance of lithophysal cavities locally decreases by much as 
3.7 percent (a 6.9 percent decrease). Additionally, and if the adjusted visible length is 
7.4 m, the cavity value decreases by as much as 5.8 percent (a 10.7 percent decrease). 
The correction of tape data is described more in Sections O4 and O6. 
Qualitatively, there are reasonably good comparisons of values measured with different 
techniques, and some data can be compared quantitatively. Differences in the values measured 
by the three methods (panel maps, angular traverses, and tape traverses) are expected because of 
how the data are collected, and these relations are implicit in the need to design three methods of 
data collection. The lithophysal cavity values from the tape traverses tend to be 1 to 3 times 
greater than in adjacent or collocated panel map and/or angular traverse values. The angular 
traverse values (for lithophysal cavities, rims, spots, and clasts) tend to be slightly greater than 
those for the panel maps; however, locally the panel map values can be greater. The average 
lithophysal-cavity value that is fully within the lower lithophysal zone (from Station 14+60 to 
23+20) is 18.9 percent from tape traverses (nonadjusted values from Table O-4) compared to 
15.5 percent from angular traverses and 12.9 percent from panel maps (Table O-9). 
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Drift Degradation Analysis 
How Well Measurements Represent the Three-Dimensional Distributions of the Features 
Determining the 3-dimensional size, shape, and distribution of features and objects is one of the 
ultimate results of the measurements described in this appendix. Most measurements in solid 
objects that cannot be disaggregated (such as rocks) are made with 2-dimensional cross sections 
and 1-dimensional traverses, so it is important to appreciate the geometric relations of the 
three-dimensional objects with respect to how they are measured. For example, an ellipsoid 
consisting of three axes (A is the longest, B is intermediate in length, and C is the shortest) can 
be cut along many planes to create various two dimensional cross-sections (Figure O-22). The 
smallest cross sectional area is for a plane through the B-C axes, an intermediate cross sectional 
area is through the A-C axes, and the maximum cross sectional area is through the A-B axes. An 
ellipsoid is a simplified rendition of many lithostratigraphic features, especially where a foliation 
is well developed such as rocks in the lower lithophysal zone exposed in the ECRB Cross-Drift. 
With respect to the lower lithophysal zone in the tunnel, the left and right ribs approximate cuts 
along planes parallel to the one that contains the A-C axes, and the crown and invert approximate 
cuts along planes parallel to the one that contain the A-B axes. Cross sections that contain the 
primary axes and transect the center of the ellipsoid have the maximum area (for example, a and 
c in Figure O-22). However, any plane cut parallel to the primary plane (for example A-C) that 
does not transect the center of the ellipsoid has the same cross sectional shape, but the axes are 
shorter (a2 and c2) and the area is smaller. If a 1-dimensional linear traverse transects an object, 
then the maximum length of the intercept occurs only if the transect is along the primary axis 
(for example, c in Figure O-22). However, if the transect is parallel to the C axis, but does not 
intersect the center of the ellipsoid, then the length of the intercept is less than the length of the 
axis (for example, c and c2 in Figure O-22). These relations are the basis of the observation in 
technical procedure, YMP-USGS-GP-20, R1 (Estimating Abundance of Features in Core and in 
Outcrop, Including Lithophysae, Spots, Clasts, and Fractures) that 2- and 1-dimensional 
measurements typically result in under estimates of the true measurements of a feature. This 
review of geometric relations of measurements indicates that even with the methods used and 
documentation of measurements and correlations of values between the various techniques, the 
actual values at a specific location or the descriptive statistics are judged to represent minimum 
values. 
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Drift Degradation Analysis 
NOTE: The a axis is the longest axis, the b axis is the intermediate length, and the c axis is the shortest. 
Figure O-22. Geometric Relations of Three-Dimensional Ellipsoid with Two-Dimensional Cross Sections 
and One-Dimensional Transects 
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Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
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Drift Degradation Analysis 
APPENDIX P 
PRESSURES ON THE DRIP SHIELD 
CALCULATED FROM THE DISCONTINUUM MODEL 
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Drift Degradation Analysis 
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Drift Degradation Analysis 
PRESSURES ON THE DRIP SHIELD CALCULATED FROM 
THE DISCONTINUUM MODEL 
P1. INTRODUCTION 
The drip shield loads (i.e., impact and static loads of the caved rock) in the lithophysal rock mass 
were first assessed considering that the drip shield is rectangular (with geometry approximately 
corresponding to the outline of the actual shape), rigid, and slaved to the free-field ground 
motion (i.e., the motion unaffected by interaction of the seismic waves with the drift). Those 
considerations were used in the initial analysis because they are conservative, resulting in 
overprediction of the caved rock-mass loads on the drip shield. The rectangular drip-shield 
shape reduces the potential for stress arching through the caved rock mass above the drip shield. 
Stress redistribution through the multi-component system is a function of ratios between 
stiffnesses of different components. If the drip shield is considered to be infinitely stiff, it 
certainly will reduce the positive stress arching in the caved rock mass, resulting in increased 
loads on the drip shield. In order to demonstrate the level of conservatism in those results and to 
obtain more realistic estimates of the drip shield loads, an improved model of the drip shield has 
been developed that includes better representation of geometry and has stiffness that 
approximates the actual drip-shield stiffness. (The model used in the UDEC drift collapse 
analysis is two-dimensional. The geometry of the drip shield is three-dimensional.) 
Development and validation of the drip-shield model is discussed in Appendix Y. 
In Section P2, the effects of the shape and stiffness of the drip shield on the drip shield loads are 
analyzed for different loading conditions (i.e., seismic shaking and quasi-static drift collapse). 
Detailed analysis of the drip shield loads (using the new model) and the results are presented in 
Sections P3 to P5. 
P2. EFFECT OF DRIP-SHIELD SHAPE AND STIFFNESS 
The effect of drip-shield stiffness and shape on the drip shield loads, both impact and static, due 
to rockfall is analyzed for seismic shaking with probability of annual recurrence of 110-5 and 
for quasi-static drift degradation. None of the actual static loads (e.g., in situ or thermal stresses) 
are expected to cause total drift collapse even for the long-term strength of the rock mass (i.e., 
accounting for time-dependent strength degradation). The quasi-static drift degradation is 
considered here to represent an extreme case of the static load on the drip shield. It is considered 
that the rock mass completely losses its cohesive strength and that total drift collapse takes place 
under the action of in situ stresses and gravitational forces. 
P2.1 SEISMIC SHAKING 
Case 11 (i.e., ground motion 9 and rock mass category 1, see Table 6-44) with 110-5 ground 
motion was used in this analysis since this case couples a high-energy ground motion (see 
Table 6-6) with the lowest strength rock category. The initial analyses were performed using the 
original drip-shield model (rectangular and rigid drip shield) shown in Figure P-1 and the model 
shown in Figure P-2, in which the drip shield has an arched top and is deformable, but pinned 
(i.e., free rotation, fixed translation) at the bottom of both sides. The pinned points are slaved to 
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Drift Degradation Analysis 
the free-field motion in a similar way the entire drip shield was slaved in the original model. 
(The invert, the pallet, and the waste canisters are not represented in these two models.) 
Figures P-1 and P-2 show the segment ID and the final configuration of the models when 
equilibrium is achieved after the shaking. This ground motion does not result in total drift 
collapse. The calculated loads on the drip shield, shown in Figure P-3, and the average pressures 
(for the sides and the top), listed in Table P-1, are fairly similar for these two cases and are 
insignificant with regard to the stability of the drip shield. 
Segment 20 Se gment 11 
Segment ID 
1 
10 
1120 
21 
30 Segment 1 
Segment 10 
Segm ent 30 
Segm ent 21 
Figure P-1. Ground Motion 10-5, Case 11: Equilibrium State for Rigid, Rectangular Drip Shield 
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Drift Degradation Analysis 
Segment 20 Segment 11 
Se gment 21 
1 
10 
1120 
21 
30
Segment 10 
Segment 1 
Se gment 30 
Segment ID 
Figure P-2. Ground Motion 10-5, Case 11: Equilibrium State for Deformable Drip Shield With Arched 
Top, Pinned Bottom, No Invert 
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Drift Degradation Analysis 
Figure P-3. Ground Motion 10-5, Case 11: Loads On the Drip Shield For Cases Without the Invert 
Table P-1. Ground motion 10-5, Case 11: Average Loads On the Drip Shield For Cases Without the 
Invert 
Case Left Top Right 
kN/m2 kN/m2 kN/m2 
rigid, rectangular 15.4 47.63 20.03 
deformable, arched top, pinned 
sides 10.62 49.13 13.25 
The drip shield will rest on the invert under its own weight. The load by the rockfall, in addition 
to deforming it, may also move the entire drip shield by sliding it along the invert and by lifting 
it from the invert. Also, the inertial forces during seismic shaking can cause movement of the 
drip shield. It is expected that movement of the drip shield will have an effect on the load of the 
caved rock on the drip shield. For example, it is observed in the case of the rigid drip shield that 
there is often a significant imbalance between the horizontal forces acting on the drip shield. If 
the drip shield is free to move horizontally, the imbalance should be relatively small, less than 
the frictional force between the drip shield and the invert. 
Case 11 was then run with the invert presented as a horizontal slab (shown in Figure P-4). It was 
considered in the simulations that the invert is rigid, slaved to the free-field motion of the rock 
mass. The friction angle between the drip shield and the invert is 22 degrees, which corresponds 
to the friction coefficient of 0.4. The pallet and the waste package also are included in the model 
and are modeled as rigid, slaved to the free-field motion of the rock mass. The presence of the 
invert affects the rockfall. The invert provides horizontal support at its elevation and affects the 
volume of the initial drift cross-section that can be filled with the caved rock, resulting in earlier 
build-up of the back-pressure by the caved rock, compared to the cases in which the caved rock 
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Drift Degradation Analysis 
also fills the space below the invert (as shown in Figure P-2). Consequently, the results of the 
models with the invert cannot be compared with the results of the models without the invert. 
Three cases (all of which include the invert) are considered. The model shown in Figure P-4 
(The model configuration in the equilibrium state after seismic shaking is shown.) is for a rigid 
drip shield slaved to the invert (i.e., the drip shield has the same motion as the free-field). In the 
model shown in Figure P-5, the drip shield can slide freely on the invert, but it cannot separate 
from the invert. The most realistic conditions of interaction between the drip shield and the 
invert are represented in the case shown in Figure P-6. In this case, the drip shield can slide, but 
it also can detach from the invert. (It is shown in Figure P-6 that the left side of the drip shield 
has lifted off the invert.) 
The amount of the rockfall in the three cases is less than in the cases without the invert. The drip 
shield is not completely covered with caved rock. Therefore, the example is not good for 
assessing the effect of the deformability of the drip shield on the stress arching in the caved rock 
mass above the drip shield. The static loads on the drip shield (shown in Figure P-7 and 
summarized in Table P-2) are relatively small. However, the effect of the drip shield sliding on 
the invert on the horizontal forces acting on the drip shield can be noticed. The imbalance 
between the forces on the left and right sides of the drip shield is much smaller for the cases in 
which the drip shield is allowed to slide (Some imbalance still exists even for those two cases 
because of the frictional forces and the reaction between the drip shield and the pallet when the 
drip shield comes in the contact with the pallet, as shown in Figure P-6.). The histories of the 
impact loads during the rockfall for the case shown in Figure P-6 are shown in Figures P-8, P-9, 
and P-10 for the left side, the top, and the right side of the drip shield, respectively. Relatively 
large impact loads are recorded; in this case, the maximum impact pressures are of the order of 
5 MPa. 
Figure P-4. Ground Motion 10-5, Case 11: Equilibrium State for Rigid Drip Shield With Arched Top, 
Bottom Fixed to the Invert 
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Drift Degradation Analysis 
Figure P-5. Ground Motion 10-5, Case 11: Equilibrium State for Deformable Drip Shield With Arched 
Top, Bottom Slides On the Invert 
Figure P-6. Ground Motion 10-5, Case 11: Equilibrium State for Deformable Drip Shield With Arched 
Top, Bottom Rests On the Invert 
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Drift Degradation Analysis 
Figure P-7. Ground Motion 10-5, Case 11: Loads On The Drip Shield for Cases With the Invert 
Table P-2. Ground Motion 10-5, Case 11: Average Loads On the Drip Shield for Cases With Invert 
Case Left Top Right 
kN/m2 kN/m2 kN/m2 
rigid, arched top, bottom fixed to 
invert 37.40 15.25 4.28 
deformable, arched top, bottom 
slides on invert 24.72 14.46 17.28 
deformable, arched top, bottom 
rests on invert 21.26 12.99 9.00 
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Drift Degradation Analysis 
Figure P-8. Ground Motion 10-5, Case 11: Dynamic Loads On the Right Side for Deformable Drip 
Shield With Arched Top, Bottom Rests On the Invert 
Figure P-9. Ground Motion 10-5, Case 11: Dynamic Loads On The Top for Deformable Drip Shield With 
Arched Top, Bottom Rests On the Invert 
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Drift Degradation Analysis 
Figure P-10. Ground Motion 10-5, Case 11: Dynamic Loads On the Left Side for Deformable Drip Shield 
With Arched Top, Bottom Rests On the Invert 
P2.2 QUASI-STATIC DEGRADATION 
The quasi-static drift degradation was analyzed for both 0.2-m and 0.3-m sizes of the Voronoi 
blocks. 
P2.2.1 Block Size 0.3 m 
The final geometries of the models without the invert are shown for the rectangular, rigid drip 
shield in Figure P-11 and for the deformable drip shield pinned at the bottom of two sides in 
Figure P-12. The summary of the drip shield loads is provided in Figure P-13 and Table P-3. In 
this particular case deformability of the drip shield does not seem to have a significant effect on 
the vertical load on the drip shield. In fact, the load on the deformable drip shield is 
approximately 10 percent larger than on the rigid, rectangular drip shield (The increase in the 
load on the top is probably due to randomness in the response of this system.). However, the 
horizontal loads on the sides of the drip shield in the model with the deformable drip shield are 
much less than in the model with the rigid drip shield. The imbalance between the horizontal 
forces in the case of the deformable drip shield is because the bottom on both sides of the 
deformable drip shield is pinned. That boundary condition resulted in very large force at the 
lower left end (i.e., segment 30 in Figure P-13) of the drip shield. 
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Drift Degradation Analysis 
Figure P-11. Quasi-Static Drift Degradation, 0.3 m Block Size: Equilibrium State for Rigid, Rectangular 
Drip Shield 
Figure P-12. Quasi-Static Drift Degradation, 0.3-m Block Size: Equilibrium State for Deformable Drip 
Shield With Arched Top, Pinned Bottom, No Invert 
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Drift Degradation Analysis 
Figure P-13. Quasi-Static Drift Degradation, 0.3 m Block Size: Loads On the Drip Shield for Cases 
Without Invert 
Table P-3. Quasi-Static Drift Degradation, 0.3 m Block Size: Average Loads On the Drip Shield For 
Cases Without the Invert 
Case Left Top Right 
kN/m2 kN/m2 kN/m2 
rigid, rectangular 303.18 194.18 326.70 
deformable, arched top, pinned 
sides 216.06 216.65 15.82 
If the invert, the pallet, and the waste package are included in the model, the extent of the caved 
region is reduced as shown in Figures P-14 and P-15. Stable arches are formed, with a gap 
between the caved rubble and the stable rock mass, due to the finite size of the rock blocks 
considered here despite the fact that the cohesive strength of the joints (contacts between the 
blocks) is reduced to zero. Two cases are considered here. The case with the rigid drip shield is 
shown in Figure P-14; the case with the drip shield resting under gravity on the invert is shown 
in Figure P-15 (When resting under gravity, the drip shield is allowed to slide and detach from 
the invert.). The results for the drip shield loads (shown in Figure P-16 and Table P-4) are 
completely dominated by the reduced size of the cave above the emplacement drift. The 
pressures are relatively small, and the effect of deformability of the drip shield is not apparent. 
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Drift Degradation Analysis 
Figure P-14. Quasi-Static Drift Degradation, 0.3 m Block Size: Equilibrium State for Rigid Drip Shield 
With Arched Top, Bottom Fixed To the Invert 
Figure P-15. Quasi-static Drift Degradation, 0.3 m Block Size: Equilibrium State for Deformable Drip 
Shield With Arched Top, Bottom Rests On the Invert 
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Drift Degradation Analysis 
Figure P-16. Quasi-Static Drift Degradation, 0.3 m Block Size: Loads On the Drip Shield for Cases With 
the Invert 
Table P-4 Quasi-Static Drift Degradation, 0.3 m Block Size: Average Loads On the Drip Shield For 
Cases With Invert 
Case Left Top Right 
kN/m2 kN/m2 kN/m2 
rigid, arched top, bottom fixed to invert 39.70 58.56 30.09 
deformable, arched top, bottom rests on 
invert 35.04 59.85 29.79 
P2.2.2 Block Size 0.2 m 
Quasi-static drift degradation using the smaller, 0.2 m Voronoi block size, generally results in 
more conservative predictions of the load on the drip shield. The smaller block size yields better 
packing and smaller bulking of the caved rock. Also, the potential for formation of stable arches 
when the cohesive strength of the joints between the blocks is reduced to zero becomes smaller 
as the block size is decreased. 
The equilibrium model configurations for the cases without the invert are shown for the rigid, 
rectangular drip shield in Figure P-17 and for the deformable drip shield pinned at the bottom in 
Figure P-18. The contours of displacement magnitudes, which indicate the extent of the caved 
rock, are shown in Figure P-19 for the model with deformable drip shield. The stress tensor 
field, shown in Figure P-20 for the same model, illustrates how the stress arches are formed in 
the caved rock above the drip shield. There is a significant component of randomness in the 
response of such systems. The correlation between the stress trajectories (shown in Figure P-20) 
and the static loads on the drip shield (shown in Figure P-21) can be established easily. The 
large drip shield loads for segments 3 and 13 are consequences of the localized stress trajectories 
ANL-EBS-MD-000027 REV 03 P-13 September 2004 

Drift Degradation Analysis 
of large stress magnitudes directed toward segments 3 and 13. (The segments are numbered 
from the lower right corner of the drip shield in the counter-clockwise direction.) 
The summary of the drip shield loads in Figure P-21 and Table P-5 indicates that the vertical 
load on the drip shield is reduced for the deformable drip shield. However, there is a significant 
component of the imbalance in the horizontal forces acting on the deformable drip shield because 
of the boundary condition used at the bottom of the drip shield. 
Figure P-17. Quasi-Static Drift Degradation, 0.2-m Block Size: Equilibrium State for Rigid, Rectangular 
Drip Shield 
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Drift Degradation Analysis 
Figure P-18. Quasi-Static Drift Degradation, 0.2 m Block Size: Equilibrium State for Deformable 
Drip Shield With Arched Top, Pinned Bottom, No Invert 
Figure P-19. Quasi-Static Drift Degradation, 0.2 m Block Size: Contours of Displacement (m) 
Magnitude for Deformable Drip Shield With Arched Top, Pinned Bottom, No Invert 
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Drift Degradation Analysis 
NOTE: Pa = Pascal. 
Figure P-20. Quasi-Static Drift Degradation, 0.2 m Block Size: Stress Tensor Field (Pa) for Deformable 
Drip Shield With Arched Top, Pinned Bottom, No Invert 
Figure P-21. Quasi-Static Drift Degradation, 0.2 m Block Size: Loads on the Drip Shield for Cases 
Without the Invert 
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Drift Degradation Analysis 
Table P-5. Quasi-Static Drift Degradation, 0.2 m Block Size: Average Loads On the Drip Shield For 
Cases Without the Invert 
Case 
Left Top Right 
kN/m2 kN/m2 kN/m2 
rigid, rectangular 62.61 179.16 44.78 
deformable, arched top, pinned sides 35.75 136.04 89.52 
The results for the cases with the invert, the pallet, and the waste packages included in the model 
are shown in Figures P-22 through P-26, and Table P-6. Two cases are considered: the rigid drip 
shield; and the deformable drip shield, free to slide and detach from the invert. The more 
realistic model of the drip shield results in reduction (approximately 25 percent) of the vertical 
load on the drip shield and more balanced horizontal loads (see Table P-6). 
Figure P-22. Quasi-Static Drift Degradation, 0.2 m Block Size: Equilibrium State for Rigid Drip Shield 
With Arched Top, Bottom Fixed to the Invert 
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Drift Degradation Analysis 
Figure P-23. Quasi-Static Drift Degradation, 0.2 m Block Size: Contours of Displacement (m) Magnitude 
for Rigid Drip Shield With Arched Top, Bottom Fixed to the Invert 
Figure P-24. Quasi-Static Drift Degradation, 0.2 m Block Size: Equilibrium State for Deformable Drip 
Shield With Arched Top, Bottom Rests On the Invert 
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Drift Degradation Analysis 
Figure P-25. Quasi-Static Drift Degradation, 0.2 m Block Size: Contours of Displacement (m) Magnitude 
for Deformable Drip Shield With Arched Top, Bottom Rests On the Invert 
Figure P-26. Quasi-static Drift Degradation, 0.2 m Block Size: Loads On the Drip Shield for Cases With 
the Invert 
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Drift Degradation Analysis 
Table P-6. Quasi-Static Drift Degradation, 0.2 m Block Size: Average Loads On the Drip Shield For 
Cases With Invert 
Case 
Left Top Right 
kN/m2 kN/m2 kN/m2 
rigid, arched top, bottom fixed to invert 66.45 144.15 11.28 
deformable, arched top, bottom rests on 
invert 41.54 108.92 58.76 
P3. IMPACT AND STATIC LOADS DUE TO STRONG GROUND 
MOTION SEISMIC SHAKING 
Impact and static loads on the drip shield are assessed for ground motions with 110-6 and 110-7 
probability of annual recurrence. Another objective of these simulations was to investigate if the 
drip shield could be overturned during strong ground motions. Ground motions 3, 7, 9, and 13 
were analyzed for both levels of probability. Those particular ground motions were selected 
based on different criteria (i.e., peak ground velocity, total power in the velocity spectrum, Arias 
intensity) for intensity of ground motion, as the four strongest ground motions from the sets of 
15 ground motions for both 110-6 and 110-7 levels of probability. Category 3 lithophysal rock 
mass was considered in the simulations. 
Although the seismic shaking for 8 simulated ground motions causes large displacements of the 
entire model, and large displacement of the drip shield relative to its original position inside the 
emplacement drift (as shown in Figure P-27), the drip shield does not get overturned at the end 
of the simulations. The model equilibrium configurations for ground motion 3 from 110-6 and 
110-7 sets are shown in Figures P-28 and P-33, respectively. The model reached the 
equilibrium configuration with drip shield in an upright position in both cases. For these strong 
ground motions, the collapse of the drift occurs very quicklyin some cases backfilling the drip 
shield within a second after the onset of strong ground motion (The strong ground motion for the 
model shown in Figure P-27 started at 1.75 s. At the state shown in Figure P-27, which is at 
2.74 s, the drift is already backfilled.). Once the drip shield is backfilled, it is difficult to 
overturn it, because the caved rock provides the back-pressure and constrains the motion of the 
drip shield. 
The pressure histories for the segments of the drip shield are shown in Figures P-29 through P-31 
for 110-6 ground motion, and in Figures P-34 through P-36 for 110-7 ground motion. The 
maximum transient pressures are relatively large, up to 10 MPa for 10-6 ground motion and up to 
40 MPa for 110-7 ground motion. The average block mass in these simulations is 
approximately 200 kg. (The characteristic block size in the plane of the model is 0.3 m.) If the 
maximum impact velocity in the case of 110-6 ground motion is approximately 8 m/s, the 
maximum impact energy for a single block is 6.4 kJ/m. During these strong ground motions, the 
rock mass shatters before reaching the drip shield. Consequently, the drip shield is subjected to 
series of small energy impacts by small blocks, instead of impacts by large blocks (as is the case 
in the model of drift stability in the non-lithophysal rock mass). Duration of the impact by a 
single block in the case of 110-6 ground motion is of the order of one millisecond. 
ANL-EBS-MD-000027 REV 03 P-20 September 2004 

Drift Degradation Analysis 
The static pressures on the drip shield are summarized in Figure P-32 and Table P-7 for 110-6 
ground motion and in Figure P-37 and Table P-8 for 110-7 ground motion. 
Figure P-27. Ground Motion 10-6 Number 3: Model Configuration After 2.75 s of Shaking 
Figure P-28. Ground Motion 10-6 Number 3: Model Configuration in the Equilibrium State After Shaking 
ANL-EBS-MD-000027 REV 03 P-21 September 2004 

Drift Degradation Analysis 
Figure P-29. Ground Motion 10-6 Number 3: Dynamic Loads On the Right Side 
Figure P-30. Ground Motion 10-6 Number 3: Dynamic Loads On the Top 
ANL-EBS-MD-000027 REV 03 P-22 September 2004 

Drift Degradation Analysis 
Figure P-31. Ground Motion 10-6 Number 3: Dynamic Loads On the Left Side 
Figure P-32. Static Loads On The Drip Shield After Shaking With Four Different 10-6 Ground Motions 
ANL-EBS-MD-000027 REV 03 P-23 September 2004 

Drift Degradation Analysis 
Table P-7. Four Different 10-6 Ground Motions: Average Loads On the Drip Shield 
Ground motion 
Left Top Right 
kN/m2 kN/m2 kN/m2 
3 10.77 80.44 58.92 
7 99.78 85.42 60.19 
9 8.03 134.34 38.46 
13 28.29 90.15 39.57 
Figure P-33. Ground Motion 10-7 Number 3: Model Configuration in the Equilibrium State After Shaking 
ANL-EBS-MD-000027 REV 03 P-24 September 2004 

Drift Degradation Analysis 
Figure P-34. Ground Motion 10-7 Number 3: Dynamic Loads On the Right Side 
Figure P-35. Ground Motion 10-7 Number 3: Dynamic Loads On the Top 
ANL-EBS-MD-000027 REV 03 P-25 September 2004 

Drift Degradation Analysis 
Figure P-36. Ground Motion 10-7 Number 3: Dynamic Loads On the Left Side 
Figure P-37. Static Loads On the Drip Shield After Shaking With Four Different 10-7 Ground Motions 
ANL-EBS-MD-000027 REV 03 P-26 September 2004 

Drift Degradation Analysis 
Table P-8. Four Different 10-7 Ground Motions: Average Loads On the Drip Shield 
Ground motion 
Left Top Right 
kN/m2 kN/m2 kN/m2 
3 91.32 44.50 80.78 
7 23.71 180.27 6.39 
9 62.27 109.59 16.07 
13 104.16 48.63 70.31 
P4. MULTIPLE REALIZATIONS OF QUASI-STATIC DRIFT DEGRADATION 
The drift collapse and the drip shield loads are expected to be random. The rockfall will vary 
considerably along the drifts, even within the same units, mostly because of variability in 
mechanical properties throughout the repository horizon. Even in the sections in which the 
emplacement drifts collapsed in a similar way, the load on the drip shield can vary significantly 
from one cross-section to another. The reason for this variability is the stochastic nature of 
rockfall, which involves formation of the blocks of irregular shapes and different sizes and their 
rockfall, during which the blocks undergo large translations and rotations. In such systems, a 
small change in the initial conditions or block geometry can result in a very different outcome of 
the rockfall in terms of position and orientation of the block. Consequently, the load on the drip 
shield will vary significantly (along the drip shield, but also in the cross-section). The UDEC 
model of drift stability mimics this variability in the rockfall and in loads on the drip shield. To 
assess dependence of the drip shield loads on the different realizations of Voronoi block 
geometry, the problem of quasi-static drift collapse was solved for five additional realizations. 
The base case, realization 1, is the model of the deformable drip shield resting on the invert and 
the particular realization of the Voronoi block geometry discussed in Section P2.2.2. The results 
for the six cases are summarized in Table P-9 and Figure P-38. The bulking factors for the caved 
rock mass are also calculated and listed in Table P-9. The variability of the load in the 
cross-section (for each realization and from one realization to another) is very large. The 
average pressure distribution is calculated for the six realizations and included as the solid line in 
Figure P-38. After averaging, the pressure variability in the cross-section is reduced. The 
average pressures on the top of the drip shield vary in the range between 110 kN/m2 and 
155 kN/m2 (Table P-9). 
Table P-9. Quasi-Static Drift Degradation, 0.2 m Block Size, Multiple Realizations of Voronoi Block 
Geometry: Average Loads On the Drip Shield 
Realization 
Left Top Right 
Bulking 
factor kN/m2 kN/m2 kN/m2 
1 41.54 108.92 58.76 0.24 
2 19.15 147.07 19.33 0.19 
3 31.35 154.80 6.69 0.25 
4 57.23 129.76 128.82 0.20 
5 69.69 112.73 105.43 0.22 
6 32.97 113.87 52.19 0.21 
ANL-EBS-MD-000027 REV 03 P-27 September 2004 

Drift Degradation Analysis 
Figure P-38. Static Loads On The Drip Shield After Quasi-Static Drift Degradation For Six Realizations 
Of Voronoi Block Geometry 
P5. EFFECT OF SEISMIC SHAKING OF COLLAPSED DRIFT 
The effect of seismic shaking of the collapsed drift on the drip shield loads in the case of the 
rigid, rectangular drip shield is presented in Appendix V. The same analysis is carried out again 
for the more realistic drip shield model described in Section P2, and for a wider range of ground 
motionsi.e., ground motions with 110-4, 110-5 and 110-6 probability of annual recurrence. 
Ground motions number 9, from the set of 110-5 ground motions, and number 1, from the set of 
110-6 ground motions, were used in these simulations. The pressure (of the caved rock on the 
drip shield) histories for the segments during 110-4 and 110-6 ground shaking are shown in 
Figures P-39 through P-44. The static pressures on the drip shield after the models are 
equilibrated are summarized in Figure P-45 and Table P-10. The pressures on the drip shield 
vary during the shaking, sometimes resulting in transient pressures that are up to an order of 
magnitude larger than the original static pressures. For example, the static pressure for segment 
10 in Figure P-42 is approximately 0.5 MPa, but it increases to approximately 5 MPa at 2.4 s of 
110-6 ground motion. The static pressure in the equilibrium state after shaking increases 
compared to the static pressures in the equilibrium state before shaking. In Table P-10, the trend 
is apparent from the average pressures on the top of the drip shield. The average pressure 
increases for each level of ground motion, and the increase becomes larger for stronger ground 
motions. Associated with pressure increase is reduction in the bulking factor. The shaking 
results in compaction (i.e., irreversible volume reduction) of the caved rock. The bulking factor 
decreases more for stronger ground motions. 
ANL-EBS-MD-000027 REV 03 P-28 September 2004 

Drift Degradation Analysis 
Figure P-39. Already Collapsed Drift, Ground Motion 10-4: Dynamic Loads On the Right Side 
Figure P-40. Already Collapsed Drift, Ground Motion 10-4: Dynamic Loads On the Top 
ANL-EBS-MD-000027 REV 03 P-29 September 2004 

Drift Degradation Analysis 
Figure P-41. Already Collapsed Drift, Ground Motion 10-4: Dynamic Loads On the Left Side 
Figure P-42. Already Collapsed Drift, Ground Motion 10-6 Number 1: Dynamic Loads On the Right Side 
ANL-EBS-MD-000027 REV 03 P-30 September 2004 

Drift Degradation Analysis 
Figure P-43. Already Collapsed Drift, Ground Motion 10-6 Number 1: Dynamic Loads On the Top 
NOTE: Pa = Pascal. 
Figure P-44. Already Collapsed Drift, Ground Motion 10-6 Number 1: Dynamic Loads On The Left Side 
ANL-EBS-MD-000027 REV 03 P-31 September 2004 

Drift Degradation Analysis 
NOTE: Pa = Pascal. 
Figure P-45. Effect Of Seismic Shaking After Quasi-Static Collapse On Drip Shield Loads 
Table P-10. Effect of Seismic Shaking After Quasi-Static Collapse: Average Loads On the Drip Shield 
Case 
Left Top Right Bulking 
Factor kN/m2 kN/m2 kN/m2 
quasi-static collapse 41.54 108.92 58.76 0.24 
10-4 shaking 13.94 154.39 55.90 0.20 
10-5 shaking 24.08 172.32 96.08 0.14 
10-6 shaking 72.18 240.05 78.14 0.10 
P6. CONCLUSION 
The drip shield loads are estimated and compared using different models. The most realistic 
drip-shield model, which generally resulted in the smallest loads, is used for further 
investigations of drip shield loads for different conditions of drift collapse and seismic loading 
subsequent to the collapse. Strong ground motions with 110-6 and 110-7 probability of annual 
recurrence, cause drift collapse within a second after onset of strong ground motion. The caved 
rock backfills the drift, providing a constraint to the motion of the drip shield and preventing the 
drip shield from being overturned. The rock mass is fragmented into small pieces (The model 
predicts disintegration of the rock mass into the original Voronoi blocks.) before they impact the 
drip shield. Large blocks, of the size similar to the size of the block created in the 
non-lithophysal rock mass, are not expected to impact the drip shield located in lithophysal rock 
mass. However, the transient impact pressures can be quite large, of the order of tens of 
megapascals. The drip shield load after quasi-static drift collapse was estimated for six different 
realization of the Voronoi block geometry. The average pressures on the top of the drip shield 
vary in the range 110 kN/m2 and 155 kN/m2. The seismic shaking subsequent to the drift 
collapse results in an increase of the load on the drip shield. For strong ground motions, that 
increase can be more than 100 percent. 
ANL-EBS-MD-000027 REV 03 P-32 September 2004 

Drift Degradation Analysis 
APPENDIX Q 
IMPACT ANALYSES 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
IMPACT ANALYSES 
Q1. IMPACT ANALYSES ON LDTH (LINE-AVERAGED HEAT SOURCE, 
DRIFT-SCALE, THERMOHYDROLOGIC) SUB-MODEL 
An impact analysis was conducted for the drift-scale thermal calculation performed by the NUFT 
thermohydrology software employing a two-dimensional, line-averaged heat source, drift-scale, 
thermohydrologic (LDTH) sub-model. The LDTH sub-model is a part of the multiscale 
thermohydrologic model created by the NUFT software, which is described in Multiscale 
Thermohydrologic Model (BSC 2004 [DIRS 163056]). An LDTH sub-model, P2WR5C10 
(coordinates: E 170730, N 234913), was selected from the new 108 LDTH sub-models 
(DTN: LL030808623122.036 [DIRS 165790]) for this impact review. The P2WR5C10 LDTH 
sub-model location selected has the following characteristics of interest compared to the L2C3 
LDTH sub-model (Section 6.2): 
 Approximately the geometric center of the license application reference repository 
layout (BSC 2003 [DIRS 164519]). 
 The repository horizon is located approximately 310 m below the ground surface and 
279 m above the water table. This elevation puts the repository horizon at 
approximately 1053 m above sea level (DTN: LL030808623122.036 [DIRS 165790]). 
 The repository horizon is located in the Tptpll with approximately 45 m of Tptpll above 
the repository horizon and 59 m of Tptpll below the repository horizon 
(DTN: LL030808623122.036 [DIRS 165790]). 
 The mean infiltration conditions have surface infiltration rates of 4.7 mm/year during the 
first 600 years of emplacement (present day climate), 14.6 mm/year from 600 years to 
2000 years (monsoonal climate), and 22.1 mm/year from 2000 years on (glacial 
transition climate) (DTN: LL030808623122.036 [DIRS 165790]). 
 The ground surface temperature is fixed at 16.9C, and the water table temperature is 
fixed at 28.3C (DTN: LL030808623122.036 [DIRS 165790]). 
The preclosure forced ventilation has a varying heat removal capacity from the air inlet to exit of 
an emplacement drift due to temperature change of the airflow. The heat removal ratio is also a 
function of time as the waste package power output and rock mass temperature changes 
(BSC 2004 [DIRS 169862]). The heat removal ratio at 600 m from inlet1, as shown in 
Table Q-1, was obtained from DTN: MO0306MWDALAFV.000 [DIRS 163961] and was used 
for calculating temperature during the preclosure period. 
Emplacement drifts in the repository average approximately 600 m in length (BSC 2003 [DIRS 165572]). 
ANL-EBS-MD-000027 REV 03 Q-1 September 2004 

Drift Degradation Analysis 
Table Q-1. Preclosure Ventilation Heat Removal Ratio at 600 m from Inlet 
Time (year) Heat Removal Ratio (%) 
0.00 0.0 
0.01 38.4 
0.02 39.1 
0.05 36.4 
0.1 35.8 
0.167 59.7 
0.5 67.7 
1 70.1 
2 74.0 
5 78.2 
7 79.3 
10 80.7 
20 84.3 
30 86.0 
50 90.2 
Source: DTN MO0306MWDALAFV.000 [DIRS 163961]. 
The temperature history at the drift crown from this thermal calculation based on the revised 
LDTH sub-model is presented in Figure Q-1, and is compared to the three cases of thermal 
calculations (Section 6.2) previously reported in this document. The new thermal calculation 
results (termed Case 1 impact) vary from the previous Case 1 base-case calculation, primarily 
in the preclosure period. Maximum temperature differences are about 35C and 9C for the 
preclosure and postclosure periods, respectively. The temperature increase during the preclosure 
period is caused by the time-dependent ventilation heat removal ratio (Table Q-1) that is lower 
than 90 percent (Section 5.1.2) used in the previous preclosure calculations. Note that the 
temperature from the revised thermal calculation is slightly higher than the three previous cases 
after 2000 years. The temperature increase is due to a lower seepage infiltration ratio of the new 
LDTH sub-model (see Section 6.2 and this appendix). 
The primary impact of this change in temperature on drift degradation is the impact on thermally 
induced stresses in the near-field of the emplacement drift. A simple, yet conservative, estimate 
of the impact on thermal stresses can be made based on the maximum additional postclosure 
temperature in the revised analyses, the rock mass thermal expansion coefficient and the bulk 
modulus. The results of these calculations are presented in Table Q-2. The approximate thermal 
stress increase due to the revised thermal calculation is based on Equation 6-6 (Section 6.2) and 
on the maximum temperature increase of 9C during the postclosure period (Figure Q-1). The 
bulk modulus, K, is calculated from rock mass Youngs modulus and Poissons ratio of the 
TSw2 thermal-mechanical unit based on Equation E-2 (Appendix E). The increase of thermal 
stress is about 1.5 MPa for the Tptpll Category 3 (Table E-10) that has a representative rock 
mass Youngs modulus and Poissons ratio, while the Tptpmn from the Heated Drift 
(Table E-15) has a thermal stress increase of 2.8 MPa. The thermal stress increase of the Tptpll 
is less than 10 percent of the rock mass strength of the Tptpll Category 3 (20 MPa, Table E-10). 
Also, the thermal stress increase of the Tptpmn is less than 10 percent of the rock mass strength 
of the Tptpmn (75.25 MPa, Table E-15), which has a higher rock quality than the Tptpll. 
ANL-EBS-MD-000027 REV 03 Q-2 September 2004 

Drift Degradation Analysis 
Temperature-History at Drift Crown 
1.45 kW/m heat load, 50 years pre-closure ventilation 
0 
20 
40 
60 
80 
100 
120 
140 
160 
180 
Temperature 
1 10 100 1000 10000 
Years 
Case 1 Case 2 Case 3 Case 1 impact 
File source: DTN: MO0408MWDDDMIO.002, file LA1450_R5C10_NUFT_Temp_crss-sctn.xls. 
Figure Q-1. Temperature History at the Drift Crown up to 10000 Years 
Table Q-2. Maximum Increase of Thermal Stress during the Postclosure 
Thermal 
Youngs 
Modulus Poissons 
Expansion 
Coefficientd Bulk 
Modulus 
Maximum 
Temperature 
Increase of 
Thermal 
Rock Mass (Pa) Ratioc (/C) (Pa) Increase (C) Stress (Pa) 
Tptpll 
Category 3a 1.08E+10 0.21 9.07E-06 6.21E+09 9 1.52E+06 
TSw2 
Category 5b 2.01E+10 0.21 9.07E-06 1.16E+10 9 2.83E+06 
a 
Obtained from Table E-10. 
b Obtained from Table E-15. 
Obtained from Table E-16. 

d Obtained from Table E-20; TSw2 and 100 C < T = 125 C. 
The thermal stress increase from the revised LDTH sub-model (Table Q-2), although it is less 
than 10 percent of the rock mass strength, could potentially have some impact on thermal 
degradation and thermal/seismic combined degradation. However, the revised thermal 
calculation for the postclosure period is bounded by the Case 2 and Case 3 sensitivity calculation 
(Figure Q-1). Based on the rockfall analysis for the nonlithophysal rock (Sections 6.3.1.3 and 
6.3.1.4) and the lithophysal rock (Section 6.4.2.3), the Case 2 and Case 3 sensitivity calculation 
demonstrated that the temperature increase from the Case 1 base case did not induce any 
significant additional rockfall (Section 6.3.1.3 and Section 6.4.2.3), and even generated less 
rockfall for Tptpmn (Table 6-24). Therefore, the temperature increase from the revised LDTH 
sub-model during the postclosure period is already covered by the previous rockfall analysis, 
ANL-EBS-MD-000027 REV 03 Q-3 September 2004 

Drift Degradation Analysis 
and it is concluded that there is no impact to the rockfall prediction by using the new thermal 
calculation for the postclosure period. An additional analysis with thermal consideration, and 
combined thermal and seismic consideration for the drift degradation is not necessary for the 
postclosure period. 
The temperature increase due to the revised LDTH sub-model during the preclosure period is 
much more significant than the postclosure period (Figure Q-2). However, the temperature itself 
is much lower compared to the postclosure period (below 75C), and it is still bounded by the 
Case 3 sensitivity calculation. The rockfall analysis for the lithophysal rock (Section 6.4.2.3) 
considered the Case 3 sensitivity case, and concluded temperature increase from the Case 1 base 
case did not induce any significant additional rockfall (Section 6.4.2.3). Therefore, it is also 
concluded that the temperature increase from the new LDTH sub-model during the preclosure 
period has no impact on the rockfall prediction by using the new thermal calculation for the 
preclosure period. 
Drift deterioration analysis due to the time-dependent rock mass degradation is presented in 
Section 6.4.2.4 and Appendix S. Combined effects of the thermal and time-dependent 
degradation are presented in Appendix S3.4.2 based on the Case 1 base-case calculation. The 
results show minor spalling around the drift (Figures S-42, S-43, and S-44) and only a small 
increase in spalling compared to the time-dependent consideration case (Figure S-38, S-39, and 
S-40). While the temperature effects combined with the time-dependant degradation accelerated 
and increased drift degradation especially after the emplacement drift closure (see 80 years plots 
in Figure S-42, S-43, and S-44), the amount of rockfall is still small and the damage is limited to 
vicinity of the emplacement drift. The increase of temperature due to the revised thermal 
calculation (Case 1 impact) could potentially result in some additional deterioration of 
emplacement drift. 
Time-dependent strength degradation combined with revised thermal load was evaluated for the 
Category 2 and 5 lithophysal rocks (Figures Q-3 and Q-4). The impact runs considered the 
higher temperatures of the revised LDTH NUFT model (Figure Q-1) for both the preclosure and 
postclosure periods. The spalling and damage due to the revised thermal and time-dependent 
degradation were slightly different from the previous coupled thermal and time-dependent 
damage analysis (Figures S-42 and S-44). However, the amount of spalling and damage was 
generally remained same for the Category 2 and 5 rocks compared to the previous coupled 
thermal and time-dependent damage. Therefore, it is concluded that the temperature increase 
from the revised LDTH sub-model has no significant impact on the rockfall prediction of 
combined thermal and time-dependent effects. 
Based on the previous observation, the same conclusion that there is no significant impact could 
be attained for the coupled seismic, thermal, and time-dependent damage analysis 
(Appendix S3.4.3), and an additional analysis for the coupled seismic, thermal, and 
time-dependent damage is not necessary. 
ANL-EBS-MD-000027 REV 03 Q-4 September 2004 

Drift Degradation Analysis 
Temperature-History at Drift Crown 
Temperature 
180
160
140
120
100
80
60
40
20
0
1.45 kW/m heat load, 50 years pre-closure ventilation 
0 1020304050607080
Years 
Case 1 Case 2 Case 3 Case 1 impact 
Source: DTN: MO0408MWDDDMIO.002, file LA1450_R5C10_NUFT_Temp_crss-sctn.xls. 
Figure Q-2. Temperature History at the Drift Crown up to 80 Years 
ANL-EBS-MD-000027 REV 03 Q-5 September 2004 

Drift Degradation Analysis 
1 years 
5 years 
10 years 
80 years 
1000 years 
10000 years 
Figure Q-3. Evolution of Damage Due to Strength Degradation and with Revised Thermal Load for 
Category 2 - Tuff Best-fit Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 Q-6 September 2004 

Drift Degradation Analysis 
1 years 
5 years 
10 years 
80 years 
1000 years 
10000 years 
Figure Q-4. Evolution of Damage Due to Strength Degradation and with Revised Thermal Load for 
Category 5 - Tuff Best-fit Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 Q-7 September 2004 

Drift Degradation Analysis 
Q2. IMPACT ANALYSES ON HEAT CAPACIY 
The regional and local scale thermal-mechanical calculations used the weight-averaged thermal 
property values for the four thermal-mechanical units (Table C-4). The heat capacity data used 
in the thermal property calculation were preliminary data superseded by 
DTN: SN0307T0510902.003 [DIR 164196] (Table E-19). The revised specific heat values for 
the thermal-mechanical units are presented in Table Q-3. Only small changes of the values occur 
in the below 95C range, especially in the repository units (2 percent decrease in TSw1 and 
3 percent decrease in TSw2-TSw3). The impacts of the thermal properties for the below 95C 
range are estimated as minor for the FLAC3D thermal-mechanical calculation, since the value 
changes in the repository units (TSw1 and TSw2-TSw3) are less than 3 percent. Based on the 
equation defined heat capacity at constant pressure (Brodsky et al. 1997 [DIRS 100653], p. 20): 
C = 1.Q (Eq. Q-1) 
p 
m .T 
where m is the mass of the specimen (kg), .Q is the increment of heat added to the subject (J), 
and .T is the change of specimen temperature (K), the change of the temperature is also 
estimated to be about 3 percent. 
The impact of the revised heat capacity for the over 114C range is also considered insignificant 
since change of the heat capacity value is irrelevant (less than 0.2 percent) for the TSw2-TSw3 
repository unit. 
Large heat capacity value changes occur in the 95C to 114C range (almost 50 percent decrease 
in the TSw2-TSw3 unit, as shown in Table Q-3). The 95C to 114C range is not substantial for 
the regional scale FLAC3D thermal-mechanical calculation, since the calculated temperatures in 
Appendix C were well below 95C (Figure C-10). For the local scale calculation, the resulting 
temperature and thermally induced stress using the revised specific heat should be under some 
impact as a result of the its low heat capacity value, especially for the central drift (Figure C-16). 
However, the rock volume for temperatures over 95C is localized adjacent to the drift wall, and 
the time duration over 95C is also limited to several hundred years. Also, the local scale 
thermal-mechanical calculation was only served to support and add confidence to the main 
thermal-mechanical calculation presented in Section 6.2. The resulting data from Section 6.2 
(not from Appendix C) were used in the subsequent analyses of this document. Therefore, an 
additional local scale thermal-mechanical calculation is not necessary. 
Table Q-3. Specific Heat Considered for the Rock Mass in the Regional and Local Scale 
Thermal-Mechanical Calculations (Appendix C) 
Property Condition TCw-PTn TSw1 TSw2-TSw3 Underlying 
Preliminary < 95C 1,158 939 937 1,304 
specific heat Cv 95C = Cv <114C 11,135 5,791 5,714 15,775 
[J/kg C] = 114C 1,010 991 990 1,016 
< 95C 1,300 920 910 1,300 
Updated specific 
heata Cv [J/kg C] 
95C = Cv <114C 
= 114C 
9,000 
1,000 
3,200 
990 
3,000 
990 
8,400 
1,100 
a 
The mean values are calculated from DTN: SN0307T0510902.003 [DIRS 164196]. 
ANL-EBS-MD-000027 REV 03 Q-8 September 2004 

Drift Degradation Analysis 
Q3. IMPACT ANALYSES FOR USE OF PFC2D AND PFC3D FISHTANK 
PFC2D V.2.0 and PFC3D V.2.0 (Section 3.1) were used for the study of rock mass strength and 
long-term strength degradation in Section 7.6 and Appendix S. 
The PFC models of rock mass strength and long-term strength degradation used FishTank 04lb. 
FishTank is a library of Fish functions that is technically supported and updated by the PFC 
software vendor, Itasca. FishTank can be downloaded from the Itasca website 
(www.itascacg.com). PFC2D V.2.0 and PFC3D V.2.0 install FishTank 03a and 04c 
automatically during the software installation, respectively. Since qualification of PFC2D and 
PFC3D did not specifically identify FishTank in their qualification processes, the usage of 
FishTank 04lb is outside of the range of PFC2D and PFC3D software validation. 
PFC2D V.2.0 and PFC3D V.2.0 with FishTank 04lb (STN: 10828-2.0-01 and 10830-2.0-01 
respectively) were qualified in accordance with LP-SI.11Q-BSC, Software Management, and 
LP-SI-12Q-BSC, Qualification of Level A Software. An impact review was conducted on the 
PFC models in the Section 7.6 and Appendix Q using the newly qualified PFC2D and PFC3D 
software. 
A typical static fatigue model, sA_mS50eXu_tC0p1-sf, was re-run for exploring impacts of 
PFC2D V.2.0 with FishTank 04lb. The model is a representative case of the static fatigue test 
simulation in Appendix S, which has 0.1 MPa of confining stress and 10 percent of void 
(lithophysal) porosity. Results of the re-run were identical with the previous run calculated from 
the previous version of PFC2D. Figure Q-5 presents the strain energy stored during the static 
fatigue simulations for both runs, which shows identical results for the runs. In addition to the 
results, their log files, sA_mS50e10u_tC0p1_n-sf.log, that contained the information regarding 
numerical calculation were identical, with the exception of header, dates, and times (Figure Q-6). 
A PFC3D biaxial model, sB1_mKvbX_tA, was re-run in order to investigate impacts of PFC3D 
V.2.0 with FishTank 04lb. Figure Q-7 shows the axial and confining stresses during the biaxial 
simulation, which have identical values. Also, Figure Q-8 shows that their log files, 
sB1_mKvB2_tAy.log, that contain the information regarding numerical calculation are identical 
except for header, dates, and times. 
Based on the impact evaluation, it is concluded there is no impact to the re-qualification of 
PFC2D and PFC3D. 
ANL-EBS-MD-000027 REV 03 Q-9 September 2004 

Drift Degradation Analysis 
a) 
b) 
NOTE: a) previous run and b) impact run using re-qualified PFC2D. 
Figure Q-5. Strain Energy Stored During the Static Fatigue Simulations 
ANL-EBS-MD-000027 REV 03 Q-10 September 2004 

Drift Degradation Analysis 
a) 
b) 
NOTE: a) previous run; b) impact run using re-qualified PFC2D. 
Figure Q-6. Log Files from PFC2D 
ANL-EBS-MD-000027 REV 03 Q-11 September 2004 

Drift Degradation Analysis 
a) 
b) 
NOTE: a) previous run; b) impact run using re-qualified PFC3D. 
Figure Q-7. Axial (wsyy) and Confining Stresses (wsxx and wszz) During the Biaxial Simulations 
ANL-EBS-MD-000027 REV 03 Q-12 September 2004 

Drift Degradation Analysis 
a) 
b) 
NOTE: a) previous run; b) impact run using re-qualified PFC3D. 
Figure Q-8. Log Files from PFC3D 
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Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
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Drift Degradation Analysis 
APPENDIX R 
DRIFT PROFILE PREDICTION AND DEGRADED ROCK MASS 
CHARACTERISTICS IN LITHOPHYSAL UNITS 
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Drift Degradation Analysis 
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Drift Degradation Analysis 
DRIFT PROFILE PREDICTION AND DEGRADED ROCK MASS 
CHARACTERISTICS IN LITHOPHYSAL UNITS 
To a large extent, deformation of the rock mass occurs as a result of deformation of pre-existing 
joints or creation and deformation of new fractures, resulting in a change in rock mass 
permeability. It is observed that both normal (opening and closure) and shear (slip) deformation 
of joints affect joint permeability. However, because joint slip results in joint opening (due to 
dilatancy), joint permeability can be considered to be a function of joint opening only. If rockfall 
occurs, which is a consequence of rock mass deformation, the size and the shape of the 
emplacement drifts will change. Changes in permeability and drift geometry will affect 
percolation of groundwater around the drifts and potential for water seepage into the drifts. 
The results for drift degradation and rock mass deformation from seismic loading (for preclosure 
and postclosure ground motions), thermal loading, and time-dependent drift degradation are 
generated as input data for seepage analysis. Results for a total of 30 scenarios of UDEC 
lithophysal modeling cases are provided. The blocks used in the UDEC Voronoi block model do 
not represent the actual internal structure of the lithophysal rock mass. The blocks are a tool in 
the numerical model used to simulate damage and fracturing of the rock mass (i.e., the potential 
fractures in this model do not correspond to actual features observed in the lithophysal units) as 
documented in Section 7.6.4. The joint data from the Voronoi block model presented in this 
appendix are provided to assess the overall degraded rock mass response. A description of each 
scenario is provided Table R-1. For each scenario, the following results are generated and 
included: 
1. Plot of the geometry of the model (see Figures R-1 through R-30). The drift profile is 
generated deleting blocks that moved more than 0.15 m. 
2. ASCII text with values of stress tensor components (sxx, sxy, syy, and szz) at UDEC 
grid points (provided by coordinates x and y). 
3. ASCII text with Voronoi block model joint data (coordinates of center, x and y, normal 
displacement, length and orientation; i.e., a unit vector, n, normal to the joint) for the 
joints in the UDEC Voronoi block model. 
4. ASCII text with averaged volumetric strain from fracture deformation as calculated in 
the UDEC Voronoi block model. 
The UDEC model keeps track of all joints (i.e., contacts between the blocks) with joint aperture 
smaller than a predefined tolerance. In the simulations carried out for this report the contact 
tolerance is 0.0055 m. When the contact aperture becomes larger than the tolerance, the contact 
is deleted because the blocks involved in the contact are no longer interacting with each other. 
However, the joints with large openings (i.e., larger than 0.0055 m) are relevant for the seepage 
analysis and needs to be included in the list of joints created in the model due to deformation, 
and taken into account in calculation of the volumetric strain. An algorithm is developed which 
detects large-opening joints based on distance and co-linearity of block edges. The blocks in the 
vicinity of block edges (within a distance of 0.5 m and 0.7 m for block size of 0.2 m and 0.3 m, 
respectively) are checked for large apertures. Edges around the blocks are treated as co-linear if 
ANL-EBS-MD-000027 REV 03 R-1 September 2004 

Drift Degradation Analysis 
the angle between them is smaller than 10. The list of joints based on the UDEC contact list is 
supplemented with the list of joints with large apertures. 
In the simulations carried out for this report, contact deformation in the UDEC model includes 
deformation due to the in situ stress state prior to excavation of the drift and any other 
subsequent loading. However, for the seepage analysis, it is of interest to have joint deformation 
and volumetric strain due to drift excavation and subsequent loading only. Therefore, in situ 
joint deformation is calculated analytically and subtracted from cumulative joint deformation. 
o 
The in situ stress is characterized by the horizontal ( sxx= 3.5 MPa) and the vertical principal 
o 
stresses (syy= 7.0 MPa) acting in the plane of the model. The normal traction acting on a joint 
with a unit normal vector, n, is: 
oo o 
22
sn =sxx nx +syy ny (Eq. R-1) 
where nx is the x-component of n, and ny is the y-component of n. Consequently, the in situ joint 
deformation is (Itasca Consulting Group 2002 [DIRS 160331]) 
oo 
. un =kn sn (Eq. R-2) 
where k is the joint normal stiffness. 
n 
The volumetric strain is calculated on a rectangular grid with horizontal and vertical spacing of 
0.25 m based on joint deformation and area of the blocks. At each point of the grid, the joints 
within a predefined distance (i.e., a circle with a radius of 0.5 m and 0.75 m for block size of 
N 
0.2 m and 0.3 m, respectively) are detected. Areas of the joints within the circle, . Aj , and area 
j =1 
M 
of the blocks that form those joints, . Ab , are calculated. Thus, the volumetric strain is 
b=1 
N 
. Aj 
j =1
e= M . (Eq. R-3) 
v 
. Ab 
b=1 
The information presented in this appendix, which is obtained as direct output from UDEC, is 
provided in DTN: MO0306MWDDPPDR.000. 
ANL-EBS-MD-000027 REV 03 R-2 September 2004 

Drift Degradation Analysis 
Table R-1. Considered Scenarios for Drift Profile and Degraded Rock Mass Characteristics 
Scenario Brief Description of the Scenario 
1 seismic with 510-4 probability of exceedance ground motion, rock mass category 1, Voronoi block size 
0.3 m 
2 seismic with 110-6 probability of exceedance ground motion, rock mass category 1, ground motion #12, 
Voronoi block size 0.3 m (Table 6-44, realization number 4) 
3 seismic with 110-6 probability of exceedance ground motion, rock mass category 1, ground motion #8, 
Voronoi block size 0.3 m (Table 6-44, realization number 6) 
4 seismic with 110-6 probability of exceedance ground motion, rock mass category 1, ground motion #9, 
Voronoi block size 0.3 m (Table 6-44, realization number 11) 
5 seismic with 110-6 probability of exceedance ground motion, rock mass category 1, ground motion #1, 
Voronoi block size 0.3 m (Table 6-44, realization number 12) 
6 thermal at 10,000 years, rock mass category 1, Voronoi block size 0.3 m 
7 degradation consideration, 0% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #1 
8 degradation consideration, 20% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #1 
9 degradation consideration, 40% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #1 
10 degradation consideration, 60% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #1 
11 degradation consideration, 80% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #1 
12 degradation consideration, 100% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #1 
13 degradation consideration, 0% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #2 
14 degradation consideration, 20% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #2 
15 degradation consideration, 40% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #2 
16 degradation consideration, 60% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #2 
17 degradation consideration, 80% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #2 
18 degradation consideration, 100% cohesion reduction, Voronoi block size 0.3 m, and random block 
generation seed #2 
19 degradation consideration, 0% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #1 
20 degradation consideration, 20% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #1 
21 degradation consideration, 40% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #1 
22 degradation consideration, 60% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #1 
23 degradation consideration, 80% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #1 
24 degradation consideration, 100% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #1 
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Drift Degradation Analysis 
Table R-1. Considered Scenarios for Drift Profile and Degraded Rock Mass Characteristics (Continued) 
Scenario Brief Description of the Scenario 
25 degradation consideration, 0% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #2 
26 degradation consideration, 20% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #2 
27 degradation consideration, 40% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #2 
28 degradation consideration, 60% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #2 
29 degradation consideration, 80% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #2 
30 degradation consideration, 100% cohesion reduction, Voronoi block size 0.2 m, and random block 
generation seed #2 
Figure R-1. Drift Profile for Scenario 1: Seismic with 510-4 Probability of Exceedance Ground Motion, 
Rock Mass Category 1, Voronoi Block Size 0.3 m 
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Drift Degradation Analysis 
Figure R-2. Drift Profile for Scenario 2: Seismic with 110-6 Probability of Exceedance Ground Motion, 
Rock Mass Category 1, Ground Motion #12, Voronoi Block Size 0.3 m 
Figure R-3. Drift Profile for Scenario 3: Seismic with 110-6 Probability of Exceedance Ground Motion, 
Rock Mass Category 1, Ground Motion #8, Voronoi Block Size 0.3 m 
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Drift Degradation Analysis 
Figure R-4. Drift Profile for Scenario 4: Seismic with 110-6 Probability of Exceedance Ground Motion, 
Rock Mass Category 1, Ground Motion #9, Voronoi Block Size 0.3 m 
Figure R-5. Drift Profile for Scenario 5: Seismic with 110-6 Probability of Exceedance Ground Motion, 
Rock Mass Category 1, Ground Motion #1, Voronoi Block Size 0.3 m 
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Drift Degradation Analysis 
Figure R-6. Drift Profile for Scenario 6: Thermal at 10,000 Years, Rock Mass Category 1, Voronoi Block 
Size 0.3 m 
Figure R-7. Drift Profile for Scenario 7: Degradation Consideration, 0% Cohesion Reduction, Voronoi 
Block Size 0.3 m, and Random Block Generation Seed #1 
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Drift Degradation Analysis 
Figure R-8. Drift Profile for Scenario 8: Degradation Consideration, 20% Cohesion Reduction, Voronoi 
Block Size 0.3 m, and Random Block Generation Seed #1 
Figure R-9. Drift Profile for Scenario 9: Degradation Consideration, 40% Cohesion Reduction, Voronoi 
Block Size 0.3 m, and Random Block Generation Seed #1 
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Drift Degradation Analysis 
Figure R-10. Drift Profile for Scenario 10: Degradation Consideration, 60% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #1 
Figure R-11. Drift Profile for Scenario 11: Degradation Consideration, 80% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #1 
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Drift Degradation Analysis 
Figure R-12. Drift Profile for Scenario 12: Degradation Consideration, 100% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #1 
Figure R-13. Drift Profile for Scenario 13: Degradation Consideration, 0% Cohesion Reduction, Voronoi 
Block Size 0.3 m, and Random Block Generation Seed #2 
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Drift Degradation Analysis 
Figure R-14. Drift Profile for Scenario 14: Degradation Consideration, 20% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #2 
Figure R-15. Drift Profile for Scenario 15: Degradation Consideration, 40% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #2 
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Drift Degradation Analysis 
Figure R-16. Drift Profile for Scenario 16: Degradation Consideration, 60% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #2 
Figure R-17. Drift Profile for Scenario 17: Degradation Consideration, 80% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #2 
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Drift Degradation Analysis 
Figure R-18. Drift Profile for Scenario 18: Degradation Consideration, 100% Cohesion Reduction, 
Voronoi Block Size 0.3 m, and Random Block Generation Seed #2 
Figure R-19. Drift Profile for Scenario 19: Degradation Consideration, 0% Cohesion Reduction, Voronoi 
Block Size 0.2 m, and Random Block Generation Seed #1 
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Drift Degradation Analysis 
Figure R-20. Drift Profile for Scenario 20: Degradation Consideration, 20% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #1 
Figure R-21. Drift Profile for Scenario 21: Degradation Consideration, 40% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #1 
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Drift Degradation Analysis 
Figure R-22. Drift Profile for Scenario 22: Degradation Consideration, 60% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #1 
Figure R-23. Drift Profile for Scenario 23: Degradation Consideration, 80% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #1 
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Drift Degradation Analysis 
Figure R-24. Drift Profile for Scenario 24: Degradation Consideration, 100% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #1 
Figure R-25. Drift Profile for Scenario 25: Degradation Consideration, 0% Cohesion Reduction, Voronoi 
Block Size 0.2 m, and Random Block Generation Seed #2 
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Drift Degradation Analysis 
Figure R-26. Drift Profile for Scenario 26: Degradation Consideration, 20% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #2 
Figure R-27. Drift Profile for Scenario 27: Degradation Consideration, 40% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #2 
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Drift Degradation Analysis 
Figure R-28. Drift Profile for Scenario 28: Degradation Consideration, 60% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #2 
Figure R-29. Drift Profile for Scenario 29: Degradation Consideration, 80% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #2 
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Drift Degradation Analysis 
Figure R-30. Drift Profile for Scenario 30: Degradation Consideration, 100% Cohesion Reduction, 
Voronoi Block Size 0.2 m, and Random Block Generation Seed #2 
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INTENTIONALLY LEFT BLANK 
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Drift Degradation Analysis 
APPENDIX S 
ESTIMATING LONG-TERM DAMAGE FORMATION SURROUNDING 
EMPLACEMENT DRIFTS 
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Drift Degradation Analysis 
ESTIMATING LONG-TERM DAMAGE FORMATION SURROUNDING 
EMPLACEMENT DRIFTS 
S1. INTRODUCTION 
Predicting the time evolution of the drift profile and damage (fracturing) of the rock mass are 
necessary for assessing repository performance. The analysis of time-dependent drift 
degradation described in Section 6.4.2.4 is simplified and does not relate damage and 
deformation to time after drift excavation. Instead, rockfall and damage of the rock mass are 
calculated as functions of the level of cohesive strength reduction with no time scale being 
associated with this strength reduction. In the analysis presented in this appendix, the limited 
existing data (for Lac du Bonnet granite and nonlithophysal tuff) on time-dependent rock mass 
strength is used to predict the evolution of the drift profile as a function of time. The PFC stress 
corrosion model (Potyondy 2003 [DIRS 165550]) is used to assess the influence of confinement 
and lithophysal void porosity on the static-fatigue curves of lithophysal rock, and to generate 
curves of damage increase as a function of time for static-fatigue tests performed at different 
load levels. These curves are then used in the UDEC models of the drift for predictions of 
time-dependent damage and rockfall. 
Additional time-dependent testing is currently underway. New data from this testing has been 
included in the analysis of time-dependent drift degradation (Section 6.4.2.4.2). The 
uncertainties and limitations associated with the static-fatigue test data and the modeling of 
time-dependent drift degradation are discussed in Section 6.5. 
S2. LONG-TERM BEHAVIOR OF ROCK AND PFC MATERIAL 
S2.1 STATIC-FATIGUE BEHAVIOR OF GRANITE AND TUFF 
S2.1.1 Summary of Test Data 
Static-fatigue data for Lac du Bonnet granite (LdB) is shown in Figure S-1. Potyondy and 
Cundall (2001 [DIRS 156895]) discuss the assumptions that went into the generation of these 
curves and provide additional data for Lac du Bonnet granite, Lac du Bonnet granodiorite and 
Barre granite. During the static-fatigue tests, environmental conditions of moisture and 
temperature were held constant and direct measurements were made of applied creep stress (s1), 
applied confinement (Pc) and time to failure (tf).2 Figure S-1 shows four data sets produced by 
two different investigators; the data set of Schmidtke and Lajtai (1985 [DIRS 164774]) is labeled 
LdB1, and the data sets of Lau et al. (2000 [DIRS 164769]) are labeled LdB2. The Schmidtke 
and Lajtai (1985 [DIRS 164774]) specimens (2:1 aspect-ratio right circular cylinders of 31.7 mm 
diameter) were saturated before testing and kept submerged during testing at 25C. Load 
The following notation is employed to describe the results of static-fatigue tests. The applied load in the axial 
direction and the confining pressure are denoted by s1 
and Pc, respectively. The axial load at failure during a 
short-term test is denoted by sf. The stress difference maintained during a static-fatigue test conducted at a 
confining pressure of Pc is s= s1 
 Pc. The stress difference at failure during a short-term test is sc 
= sf 
 Pc. To 
facilitate comparison between different data sets, we generate a static-fatigue curve by plotting the logarithm of 
time-to-failure, tf, versus the driving-stress ratio given by s/sc 
= (s1 
 Pc) / (sf 
 Pc). The peak strength, sf, is not 
known for a tested specimen. Different schemes to estimate this value have been employed by the different 
investigators (Potyondy and Cundall 2001 [DIRS 156895], pp. 114 to 115). 
ANL-EBS-MD-000027 REV 03 S-1 September 2004 

Drift Degradation Analysis 
application was rapid, with full static-fatigue load being reached in about two seconds. The Lau 
et al. (2000 [DIRS 164769]) specimens (2.5:1 aspect-ratio right circular cylinders of 61 mm 
diameter) were saturated before testing and tested in a triaxial cell under drained conditions (i.e., 
water from a saturated sample is allowed to freely flow in or out of the sample during loading) at 
25C. Load application was slow, with full load being reached at a constant rate of 
0.75 MPa/sec. For unconfined conditions, both data sets have a similar slope when fit with a 
straight line. While confined static-fatigue tests are limited, confinements of 5 MPa and 10 MPa 
increase the slope, and also increase the time-to-failure for s/sc 
< 0.8. 
LdB tests at T=25C 
Logarithm of Time-to-Failure, tf (sec)
6 
4 
2 
0 
R2R2R2R2il 
) 
)l 
y = -13.541x + 13.503 
= 0.738 
y = -24.386x + 23.491 
= 0.8779 
y = -14.943x + 15.723 
= 0.7841 
y = -28.487x + 27.629 
= 0.9786 
LdB1 (Pc=0) 
LdB2 (Pc=0) 
LdB2 (Pc=0), no faLdB2 (Pc=5 MPa) 
LdB2 (Pc=10 MPaLdB2 (Pc=10 MPa, no fai
0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
Source: LdB1 data from Schmidtke and Lajtai (1985 [DIRS 164774]); LdB2 data from Lau et al. (2000 
[DIRS 164769]). 
Figure S-1. Static-Fatigue Data for Lac du Bonnet Granite (Confinements of 0, 5, and 10 MPa) 
Martin et al. (1997 [DIRS 165960] and 1997 [DIRS 148875]) present static-fatigue results for a 
total of 16 specimens of welded (lithophysae poor) tuff from borehole NRG-7/7A at Yucca 
Mountain and from Busted Butte boulders taken from the same block of rock.3 The specimens 
were 2:1 aspect-ratio right circular cylinders of 50.8 mm diameter. Load application was rapid, 
with full load being reached in less than 10 seconds. The 7 borehole specimens drained and 
vented to the atmosphere were tested at a temperature of 225C and a confining pressure of 
10 MPa at differential stresses ranging from 40 MPa to 130 MPa. None of these specimens had 
failed after loading for times ranging from 2.5  106 to 5.9  106 seconds. The nine (9) Busted 
Butte specimens were tested at a pore water pressure (Pp) of 4.5 MPa, a temperature of 150C 
and a confining pressure of 5 MPa at differential stresses ranging from 115 MPa to 150 MPa, and 
Martin et al. (1997 [DIRS 148875]) is the Sandia report describing the tests on the borehole specimens, and 
additional scoping studies are reported in Martin et al. (1995 [DIRS 100159]). 
ANL-EBS-MD-000027 REV 03 S-2 September 2004 

Drift Degradation Analysis 
the test results are summarized in Table S-1. Six of these specimens failed at times less than 
2  106 seconds, while the remaining three specimens (BB-9392-H, -G, and -J) did not fail 
during the testing period. The times-to-failure for these six tests can be plotted versus applied 
load; however, the peak strength must be estimated in order to plot them versus driving-stress 
ratio for comparison with the Lac du Bonnet granite data in Figure S-2. For these purposes, the 
peak strength at a effective confinement of 0.5 MPa (Pc-Pp) is estimated to be 151 MPa to give a 
failure time of one second for a driving-stress ratio of unity.4 
Table S-1. Static-Fatigue Data for Busted Butte Specimens 
Specimen 
Confining 
Pressure, 
Pc (MPa) 
Stress Difference 
Maintained 
During Test, 
s (MPa) 
Time-to-
Failure, tf 
(sec) 
Logarithm of 
Time-to-
Failure, log(tf) 
(sec) 
Peak 
Strength, sf 
(MPa) 
Driving-
Stress 
Ratio, s/sc 
BB-9392-K 5 149.0 1.2 0.08 151 0.99 
BB-9392-N 5 141.0 4 0.60 151 0.94 
BB-9392-E 5 134.6 250 2.40 151 0.89 
BB-9392-C 5 134.2 636 2.80 151 0.89 
BB-9392-F 5 132.8 5848 3.77 151 0.88 
BB-9392-B 5 127.8 1960000 6.29 151 0.85 
BB-9392-H 5 131.4 1180000 6.07 151 0.87 
BB-9392-G 5 131.3 732000 5.86 151 0.87 
BB-9392-J 5 115.0 2000000 6.30 151 0.76 
NOTE: See footnote 1 in this Appendix for a discussion of the notation used in this table. Specimens were 
saturated and tested at a pore water pressure of 4.5 Pa and temperature of 150C. Specimens were 
loaded directly to creep stress (s1) in less than 10 seconds. Specimen diameter is 50.8 mm. 
Specimens BB-9392-H, BB-9392-G, and BB-9392-J did not fail during the test. Confining pressure is 
the effective value from the applied confining stress (5 MPa) and pore pressure (4.5 MPa). See Martin 
et al. 1997 [DIRS 165960]. 
It is noted that there is a difference in test temperature for the granite and tuff data (i.e., 25C and 
150C, respectively). Based on a postulated physical mechanism for stress corrosion, which is a 
chemical reaction that increases its rate with increased temperature, it is determined that 
increasing temperature should decrease the time-to-failure for a fixed driving-stress ratio (s/sc). 
S2.1.2 Suitability of Static-Fatigue Data for Estimating the Long-Term Behavior of the 
Rock Mass Surrounding the Emplacement Drifts 
The static-fatigue test data for granite (Schmidtke and Lajtai 1985 [DIRS 164774]; Lau et al. 
2000 [DIRS 164769]) and tuff (Martin et al. 1997 [DIRS 165960]) were obtained from outside 
sources. In accordance with AP-SIII.10Q (Section 5.2), these data are considered qualified for 
use within this analysis and model report based on the reliability of the data sources, the 
qualifications of the organizations generating the data, and the availability of corroborating data, 
as documented in this section. 
4 The unconfined compressive strength values from Martin et al. (1993) for six saturated 50.8 mm diameter Busted 
Butte specimens tested at a strain rate of 10-5 s-1 ranged from approximately 105 MPa to 200 MPa, with a mean of 
approximately 128 MPa for the five weakest specimens. 
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Drift Degradation Analysis 
Extent to Which the Data Demonstrate Properties of InterestThese data have been collected 
as part of thermal-mechanical stability studies in both the United States and Canada with the 
purpose of improving the fundamental understanding of long-term rock mass behavior around 
underground openings. This information represents the best available data for assessing 
long-term strength of tuff at Yucca Mountain. The granite data from the Canadian 
thermal-mechanical studies (i.e., Schmidtke and Lajtai 1985 [DIRS 164774) and Lau et al. 2000 
[DIRS 164769]) provide a means of comparing the effects of rock type and demonstrating the 
similarity of the general nature of the time-to-failure data for different rock types. Additionally, 
corroborating data (described in this section) confirm the general consistency and similarity of 
the data sets for providing the long-term strength of rock. 
Lau et al. (2000 [DIRS 164769])Data from long-term loading tests on granite were developed 
by the CANMET Mining and Mineral Sciences Laboratories within Natural Resources Canada, 
which is a federal government department specializing in earth sciences. The mining group at 
CANMET has established a team of specialists in geomechanics, numerical modeling, and 
mechanical rock property testing. Their laboratories include state-of-the-art rock mechanics 
testing systems. Specimen preparation, test apparatus, test procedures, data collection, and 
analysis of data are well documented, providing a reliable source of data from long-term loading 
tests. 
Schmidtke and Lajtai (1985 [DIRS 164774])Data from long-term loading tests on granite 
were also developed by the Departments of Civil and Geological Engineering the University of 
Manitoba under the sponsorship of the Atomic Energy of Canada. This work was conducted by 
Dr. Emery Lajtai, Professor Emeritus of Civil Engineering at the University of Manitoba. 
Dr. Lajtai specializes in the fracture and deformation of rocks. 
Martin et al. (1997 [DIRS 165960])Creep and static-fatigue data for welded tuff from Yucca 
Mountain were developed by the combined efforts of New England Research, Inc. and Sandia 
National Laboratories. Sandia National Laboratories, with the support of New England 
Research, Inc., has been a primary developer of rock mechanics testing data within the Office of 
Civilian Radioactive Waste Management quality assurance program at Yucca Mountain. The 
collection of the creep and static-fatigue data for tuff, while completed independently from YMP 
sponsorship, was developed using YMP quality standards. The principal author of the creep and 
static-fatigue data for tuff, Dr. Randolph Martin, is the President of and Principal Scientist at 
New England Research, Inc. He has a Ph.D. from MIT, where his thesis research was entitled, 
Time-Dependent Crack Growth in Quartz and Its Application to the Creep of Rocks. 
Dr. Martin has a wide range of experience managing and performing both field and laboratory 
rock mechanics projects, including designing/building high-pressure equipment, testing rocks at 
elevated pressures and temperatures, and analyzing data with various (e.g. empirical, analytical, 
and numerical) techniques. The co-author of this data, Mr. Ronald Price, is a Senior Member of 
Technical Staff at Sandia National Laboratories. Mr. Price has had a central focus on the 
mechanical properties of tuffs, with special emphasis on Yucca Mountain tuffs, for over 
22 years. His depth of knowledge of tuff rheological properties is particularly valuable for the 
present application. 
ANL-EBS-MD-000027 REV 03 S-4 September 2004 

Drift Degradation Analysis 
Corroborating DataNew static-fatigue data for tuff (DTN: SN0406L0212303.002 
[DIRS 170289], tuff 2004 data) have recently been collected and are used to corroborate the 
1997 test data for tuff (Martin et al. 1997 [DIRS 165960]). The static-fatigue data are provided 
in Section 6.4.2.4 (Figure 6-155). Granite results are included as a means of comparing the 
effects of rock type and for demonstrating the similarity in the general nature of the 
time-to-failure data for different rock types. Scatter in the data is due to sample in homogeneity, 
as well as the fact that the driving stress ratio (the horizontal axis) uses an estimated value for the 
unconfined compressive strength (adjusted for sample porosity) for normalizing the applied 
stress level. 
Since there is significant variability in the unconfined compressive strength of each sample, there 
will be a scatter in the resulting plot of time-to-failure versus driving stress ratio. As seen in 
Figure 6-155, the welded tuff has a significantly slower time static fatigue failure than granite, as 
evidenced by the steeper slope of the linear fit to the data. This slower time-to-failure is 
presumably a result of the relatively homogeneous, fine-grained, high silica content nature of the 
tuff, as opposed to the heterogeneous nature of the grain structure of granite. 
Linear fits to the unconfined compression data of Lac du Bonnet granite and to the tuff 1997 data 
only and to the welded tuff data (including both 1997 and 2004 data) are given 
(Figure 6-155). Although there is considerably more scatter in the 2004 test results, the linear 
fits to the data sets show the general consistency of the overall slope of the fits. 
S2.2 STATIC-FATIGUE BEHAVIOR OF PFC2D MATERIAL FOR LITHOPHYSAL 
TUFF 
The PFC stress corrosion model is described in Potyondy (2003 [DIRS 165550]), and only the 
model behavior when applied to simulating lithophysal tuff is described here.5 
S2.2.1 PFC2D Base Material and Specimen (Short-Term Behavior) 
The PFC model for lithophysal tuff is described in Section 7.5 and in Subsurface Geotechnical 
Parameters Report (BSC 2003 [DIRS 166660], Section 9.1). This PFC2D model (consisting of 
circular voids within a well-connected base material) has the microproperties and void geometry 
given in Table S-2, and provides the base material for which the stress-corrosion behavior is 
measured. Determination of the appropriate model conditions requires balancing many factors 
such as (1) behavior of previous models, (2) appropriate resolution of voids and bridges, and (3) 
ability to perform a simulation in a reasonable amount of time. 
5 Much of the development of the model has been funded by Atomic Energy of Canada Limited and Ontario Power 
Generation during the years 1995-2001 as part of its Thermal-Mechanical Stability Study, one aim of which has 
been to improve our fundamental understanding of short- and long-term rock-mass behavior around underground 
openings at ambient and elevated temperatures. The result of this work has been the development and verification 
of the Bonded-Particle Model for Rock - a mechanistically based numerical model for predicting excavation-
induced rock-mass damage and long-term strength (by incorporating a damage process based on a stress-corrosion 
mechanism) in Lac du Bonnet granite (Potyondy and Cundall 2001 [DIRS 156895]). 
ANL-EBS-MD-000027 REV 03 S-5 September 2004 

Drift Degradation Analysis 
LdB tests at T=25oC, tuff tests at T=150oC 
Logarithm of Time-to-Failure, tf (sec)
6 
4 
2 
0 
R2 
( 
( 
(l 
(
tuff () 
tuf)il 
sfy = -42.204x + 40.954 
= 0.8505 
LdB1Pc=0 MPa) 
LdB2Pc=0 MPa) 
LdB2Pc=0 MPa), no faiLdB2Pc=5 MPa) 
Pc=5, Pp=4.5 MPaf (Pc=5, Pp=4.5 MPa, no fa 
= 151 MPa 
0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
Sources: LdB1 from Schmidtke and Lajtai (1985 [DIRS 164774]); LdB2 from Lau et al. (2000 [DIRS 164769]); tuff 
from Martin et al. (1997 [DIRS 165960]). 
Figure S-2. Static-Fatigue Data for Welded Tuff and Lac du Bonnet Granite 
The properties of the PFC2D material are obtained by testing 1:1 aspect-ratio specimens of 
one-meter diameter, with circular voids of 90 mm diameter and a 41.5 mm minimum bridge 
length. The use of 1:1 aspect-ratio specimens is justified due to frictionless boundary conditions. 
It is noted that the modulus and strength versus void porosity relations are similar for both 1:1 
and 2:1 aspect-ratio specimens  the 2:1 aspect-ratio specimens are only slightly weaker than 
the 1:1 aspect-ratio specimens (see Figures S-3 and S-4). 
The resolutions of previous PFC materials are shown in Table S-3. The materials in the first two 
columns are 2:1 aspect ratio specimens that were used to obtain the initial relations between 
modulus, strength and void porosity (see Figures 7-12 and 7-13). These 2D and 3D materials 
have average particle diameters of 17.1 mm and 52.3 mm, respectively, and the macroproperties 
of the 2D material are shown in Figures S-3 through S-5. The materials in the third and fourth 
columns are 1:1 aspect ratio specimens that differ only in the size of the circular voids. This 2D 
material has an average particle diameter of 9.9 mm, and the macroproperties of these 2D 
materials are shown in Figures S-3 through S-5. The material in the fourth column is used for 
the present work. 
ANL-EBS-MD-000027 REV 03 S-6 September 2004 

Drift Degradation Analysis 
Table S-2. PFC2D Material for Lithophysal Tuff (Microproperties and Void Geometry) 
Grains Cement 
. = 2510 kg/m3 N/A 
(Dmax / Dmin) = 1.5 
Davg varies 
. 
= 1 
Ec = 14.8 GPa E c = 14.8 GPa 
(kn / ks) = 2.1 (kn / ks) = 2.1 
 = 0.5 s c = t c = mean  standard deviation = 48.11  11 MPa 
Void Geometry: circular, Dv varies, Bmin = 41.5 mm 
Young's Modulus (GPa) 
NOTE: The PFC microproperties in this table were obtained by calibration of the PFC model to match the
macro-behavior of tuff, as described in Section 7.6.3. .= grain density, Dmax = maximum particle 
diameter (mm), Dmin = minimum particle diameter (mm), Davg = average particle diameter (mm), 
Ec = Youngs modulus of the grains, Ec = Youngs modulus of the cement, kn = particle normal

stiffness, ks = particle shear stiffness,  = grain friction coefficient, .= bond-radius multiplier of 
cemented contact, kn = normal stiffness of cemented contact, ks = shear stiffness of cemented 
 c = tensile strength of cemented contact, t
contact, s c = shear strength of cemented contact, Dv = void 
diameter (mm), Bmin = minimum bridge length. 
25 
20 
15 
10 
5 
0 
R2R2R2y = 19.067e-3.6915x 
= 0.9884 
y = 20.065e-3.9172x 
= 0.9797 
y = 20.245e-4.1815x 
= 0.9779 
Lithophysal tuff data, room dry (see Table E-9) 
2:1, Dp=17.1 mm, Dv=166 mm 
1:1, Dp=9.9 mm, Dv=166 mm 
1:1, Dp=9.9 mm, Dv=90 mm 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 
Void Porosity, nv 
Figure S-3. Youngs Modulus Versus Void Porosity for Lithophysal Tuff and PFC2D Models of Randomly 
Distributed Circular Voids 
ANL-EBS-MD-000027 REV 03 S-7 September 2004 

Drift Degradation Analysis 
R2R2R20 
10 
20 
30 
40 
50 
60 
70 
Unconfined Compressive Strength (MPa) 
Liy = 54.597e-5.3977x 
= 0.9546 
y = 52.482e-5.1493x 
= 0.9434 
y = 52.167e-5.9159x 
= 0.943 
thophysal tuff data, room dry (see Table E-9) 
2:1, Dp=17.1 mm, Dv=166 mm 
1:1, Dp=9.9 mm, Dv=166 mm 
1:1, Dp=9.9 mm, Dv=90 mm 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 
Void Porosity, nv 
Figure S-4. Unconfined Compressive Strength Versus Void Porosity for Lithophysal Tuff and PFC2D 
Models of Randomly Distributed Circular Voids 
R2R2R20 
10 
20 
30 
40 
50 
60 
70 
Lily = 4.6377e0.1363x 
= 0.9649 
y = 5.9043e0.1225x 
= 0.9635 
y = 4.1467e0.1394x 
= 0.9687 
Unconfined Compressive Strength (MPa) 
thophysal tuff data, room dry (see Tabe E-9) 
2:1, Dp=17.1 mm, Dv=166 mm 
1:1, Dp=9.9 mm, Dv=166 mm 
1:1, Dp=9.9 mm, Dv=90 mm 
0 5 101520 
Young's Modulus (GPa) 
Figure S-5. Youngs Modulus Versus Unconfined Compressive Strength for Lithophysal Tuff and PFC2D 
Models of Randomly Distributed Circular Voids 
ANL-EBS-MD-000027 REV 03 S-8 September 2004 

Drift Degradation Analysis 
Table S-3. PFC Resolutions for Lithophysal Tuff Specimens 
Resolution 
(Ds = 1000 mm) 
PFC3D 
2:1 cyl. 
PFC2D 
2:1 
PFC2D 
1:1 
PFC2D 
1:1 
Davg (mm) 52.3 17.1 9.9 9.9 
Dv (mm) 166 166 166 90 
specimen, .s 
= Ds / Davg 19.1 58.5 101 101 
void, .v 
= Dv / Davg 3.2 9.7 16.8 9.1 
bridge, .B = Bmin / Davg 0.8 2.4 4.2 4.2 
NOTE: Ds = specimen diameter (mm), .s 
= specimen resolution, .v 
= void resolution, .B = bridge resolution. 
All other parameters defined in Table S-2. Bmin = 41.5 mm. 
S2.2.2 PFC2D Base Material and Specimen (Long-Term Behavior) 
The long-term behavior of the PFC2D material is characterized by performing a series of 
numerical static-fatigue tests on the PFC2D lithophysal-tuff model using the microproperties in 
Table S-4. The long-term behavior is controlled by the three PFC stress corrosion model 
parameters of 1, 2, and s
 a. These parameters do not affect the short-term behavior. The 
properties of the PFC2D material are obtained by testing 1:1 aspect-ratio specimens of one-meter 
diameter with void porosities of 0, 0.1, and 0.2 under static-fatigue conditions at confinements of 
0.1 and 5 MPa. The PFC2D materials have average particle diameters ranging from 10 mm to 
40 mm, giving the specimen, void, and bridge resolutions shown in Table S-5. The results 
presented here were produced for the mS50 specimens (average particle diameter of 20 mm), 
which provide a specimen resolution of 50 particles across a one-meter diameter specimen. The 
specimens with non-zero void porosities are shown in Figure S-6. 
Table S-4. PFC2D Material for Lithophysal Tuff (Short- and Long-Term Microproperties and Void 
Geometry) 
Grains Cement 
. = 2510 kg/m3 N/A 
(Dmax / Dmin) = 1.5 
Davg varies (10, 20, or 40 mm) . 
= 1 
Ec = 14.8 GPa E c = 14.8 GPa 
(kn / ks) = 2.1 (kn / ks) = 2.1 
 = 0.5 s c = t c = mean  standard deviation = 48.11  11 MPa 
N/A 1 = 5  10-15 m/sec s a = 0 MPa 
2 = 30 fr = 1  10-4 , ns = 4, fs = 2 
Void Geometry: circular, Dv = 90 mm, Bmin = 41.5 mm 
NOTE: 
1 = rate constant (m/sec), 2 = rate constant (dimensionless), s
 a = micro-activation stress, fr = 
equilibrium ratio limit, ns = number of steps until the first bond breaks, fs = time step multiplier. All other 
parameters defined in Table S-2. 
ANL-EBS-MD-000027 REV 03 S-9 September 2004 

Drift Degradation Analysis 
Table S-5. PFC2D Resolutions for Current Lithophysal Tuff Specimens 
Resolution mS100 mS50 mS25 
(Ds = 1000 mm) (fine) (medium) (coarse) 
specimen, .s 
= Ds / Davg 100 50 25 
void, .v 
= Dv / Davg 9.0 4.5 2.3 
bridge, .B = Bmin / Davg 4.2 2.1 1.0 
NOTE: All parameters defined in Tables S-2 and S-3. 
NOTE: Void porosities of 0.107 and 0.204. 
Figure S-6. PFC2D Specimens of mS50 Material 
S2.2.3 Selection of Stress Corrosion Algorithm-Control Parameters 
The equilibrium ratio limit, fr, defines when the system has returned to static equilibrium after 
each stress-corrosion step. This study uses PFC2D version 2.0, for which the equilibrium ratio is 
taken as the ratio of maximum unbalanced force over maximum contact force. Numerical 
static-fatigue tests were performed on the mS50 material with no holes and with s
 a = 19 MPa at 
driving-stress ratios ranging from 0.25 to 0.90. The fr was varied over three orders of magnitude 
from 1  10-3 to 1  10-6 while keeping the other algorithm-control parameters fixed at ns = 2 and 
fs = 2.0. The failure times were 4.91  105, 3.66  105, 3.85  105, and 3.66  105 seconds, 
respectively. A plot showing the total number of cracks6 versus time for a driving-stress ratio of 
0.75 is displayed in Figure S-7. These results suggest that the cracking during primary and 
secondary creep is not affected by the equilibrium ratio limit, but that cracking during the tertiary 
creep stage and the corresponding failure time is affected by the equilibrium ratio limit. Further 
study is required to determine what is the equilibrium ratio limit below which the failure time is 
constant. The results presented here demonstrate that values less than 1  10-3 produce similar 
primary and secondary creep. Therefore, to ensure similar primary and secondary creep, the 
results in this report were produced using an equilibrium ratio of 1  10-4. 
6 The term crack is used throughout this appendix to refer to bond breakages in the PFC material. 
ANL-EBS-MD-000027 REV 03 S-10 September 2004 

Drift Degradation Analysis 
250 
Total Cracks 
200 
150 
100 
50 
0 
0.0E+00 1.0E+05 2.0E+05 3.0E+05 4.0E+05 5.0E+05 
Time (sec) 
liio limis/scEffect of equibrium ratt, =0.75 
fr = 1e-3 
fr = 1e-4 
fr = 1e-5 
fr = 1e-6 
Figure S-7. Number of Cracks Versus Time for Different Equilibrium Ratio Limits 
By default, the subinterval factor, ns, is set to 2. The effect of increasing this value (and 
therefore decreasing the initial size of each stress-corrosion time step) is examined here. 
Numerical static-fatigue tests were performed on the mS50 material with no holes at 
driving-stress ratios of 0.4 and 0.8, and ns was varied from 2 to 32 while keeping the other 
algorithm-control parameters fixed at fr = 1  10-4 and fs = 2.0. The failure times are normalized 
by the corresponding failure time for ns = 32 and plotted versus the subinterval factor in 
Figure S-8. Increasing the subinterval factor reduces the size of each stress-corrosion time step, 
which reduces the error associated with considering that the forces remain constant during each 
step, and is in keeping with the conclusion that as .t . 0, the true macroscopic time-to-failure is 
approached from above. The creep response is similar for different subintervals as seen in 
Figure S-9. The results in this report were produced using a subinterval factor of 4. The 
subinterval factor of 4 results in an error of approximately 5 percent. This error is considered as 
acceptable with the level of uncertainty in this type of model. 
ANL-EBS-MD-000027 REV 03 S-11 September 2004 

Drift Degradation Analysis 
Effect of subinterval factor 
yR2y =
R2t f / t f 32 
iiiitf32 (
tf32 ( 
= 1.1162x-0.0333 
= 0.9131 
1.1397x-0.043 
= 0.827 
0.90 
0.95 
1.00 
1.05 
1.10 
1.15 
Normalized Failure Time, 
drivng stress rato = 0.8 
drivng stress rato = 0.4 
= 4.825e03 sec0.8) 
= 2.072e08 sec0.4) 
0 5 10 15 20 25 30 35 
Subinterval Factor, ns 
NOTE: Driving-stress ratios of 0.8 and 0.4. 
Figure S-8. Normalized Time-to-Failure Versus Subinterval Factor for mS50 Material for Numerical 
Static-Fatigue Tests (0.1 MPa Confinement) 
PFC2D (90-mm diam. circles, nv = 0) 
(%) 
iviiiviitf(ns = 4) 
tf(ns) 
0.27 
0.28 
0.29 
0.30 
0.31 
0.32 
0.33 
Axial Straindrng stress rato = 0.8, subinterval factor = 4 
drng stress rato = 0.8, subinterval factor = 32 
= 5.086e03 sec 
= 4.825e03 sec = 32
0.E+00 1.E+03 2.E+03 3.E+03 4.E+03 5.E+03 6.E+03 
Time-to-Failure, tf (sec) 
creep curve, Pc = 0.1 MPa 
NOTE: Driving-stress ratio of 0.8. 
Figure S-9. Effect of Subinterval Factor on Creep Curves for mS50 Material for Numerical Static-Fatigue 
Tests (0.1 MPa Confinement) 
ANL-EBS-MD-000027 REV 03 S-12 September 2004 

Drift Degradation Analysis 
S2.2.4 Typical Model Behavior During a Static-Fatigue Test 
Numerical static-fatigue tests at a confinement of 0.1 MPa were performed upon the mS50 
material with no voids to produce the static-fatigue curve shown in Figure S-10. The PFC stress 
corrosion model parameters of 1 
and 2 
were chosen to match the LdB1 data set in the range 
0.6 = 
s/sc = 1.0. The bump in the curve for 0.885 = 
s/sc = 0.890 is caused by a change in the 
failure mode of the specimen as shown in Figure S-10. The micro-activation stress, s
 a, controls 
the minimum driving-stress ratio for which the time-to-failure becomes infinite. This lower limit 
for time-dependent failure is called the static-fatigue limit. There is, as yet, no scientific 
consensus on the value of the static-fatigue limit, although exponential extrapolation of the LdB1 
data set by Schmidtke and Lajtai (1985 DIRS [164774]) gives a value of 0.45. Because the 
mS50 material is being used to generate damage curves to serve as input to the UDEC model, the 
 a = 0 is used. A zero value of sconservative consideration that s a means that stress corrosion 
will continue until the micro-tensile forces in the material have been removed. It is found that 
the time-to-failure is indeed finite for driving-stress ratios larger than 0.2, and that the 
static-fatigue curve is nearly linear for small driving-stress ratios (see Figure S-11).1 
Logarithm of Time-to-Failure, tf (sec) 
6 
4 
2 
0 
-2 
R2R2 
( 
() 
iiliilLdB tests at T=25C 
y = -13.541x + 13.503 
= 0.738 
y = -14.924x + 14.749 
= 0.883 
LdB1Pc=0) 
mS50, nv=0Pc=0.1 MPacracks durng f aure 
cracks durng f aure 
0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
NOTE: Data set LdB1 from Figure S-1. 
Figure S-10. Static-Fatigue Curve (0.1 MPa Confinement) for mS50 Material for Numerical 
Static-Fatigue Tests Compared with the Data and Curve for Lac du Bonnet Granite 
1A better fit to the mS50 data would bend strongly downwards for driving-stress ratios that approach one (because 
the time-to-failure must approach zero), and would bend slightly downwards for driving-stress ratios that approach 
zero. Such a fit is used in Appendix S2.2.5. 
ANL-EBS-MD-000027 REV 03 S-13 September 2004 

Drift Degradation Analysis 
LdB tests at T=25C 
14
Logarithm of Time-to-Failure, tf (sec) 
10 
6 
2 
-2 
R2R2 
( 
(
iiy = -13.541x + 13.503 
= 0.738 
y = -14.924x + 14.749 
= 0.883 
LdB1Pc=0) 
mS50, nv=0Pc=0.1 MPa) 
3.17 mllion years 
317 years 
3.2 years 
2.8 hours 
1.7 mnutes 
1 second 
11.6 days 
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
NOTE: Data set LdB1 from Figure S-1. 
Figure S-11. Static-Fatigue Curve (0.1 MPa Confinement) for mS50 Material for Numerical 
Static-Fatigue Tests Compared with the Data and Curve for Lac du Bonnet Granite  
Expanded Scales 
Representative creep curves are shown in Figure S-12, where the axial strain is plotted versus 
normalized time-to-failure. The general behavior is one of primary, secondary and tertiary creep. 
The creep response is produced by the reduction of parallel-bond radii and by the formation of 
microcracks as can be seen in Figure S-13. 
ANL-EBS-MD-000027 REV 03 S-14 September 2004 

Drift Degradation Analysis 
PFC2D (90-mm diam. circles, nv = 0)
0.35 
0.30 
driviidriviidriviit f () 
t f () 
t f () 
ng stress rato = 0.8 
ng stress rato = 0.4 
ng stress rato = 0.2 
= 5.086e03 sec 0.8= 2.175e08 sec 0.4= 3.191e10 sec 0.2
Axial Strain (%) 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 
Normalized Time-to-Failure, t / tf 
creep curves, Pc = 0.1 MPa
NOTE: Driving-stress ratios of 0.2, 0.4 and 0.8. 
Figure S-12. Creep Curves for mS50 Material for Numerical Static-Fatigue Tests (0.1 MPa 
Confinement) 
(iiln v) 
(%) 
iit f = ) 
PFC2D90-mm dam. crces, = 00.27 
0.28 
0.29 
0.30 
0.31 
0.32 
0.33 
Axial Straindrivng stress rato = 0.8 
5.086e03 sec (0.835 cracks 
110 cracks 
155 cracks 
203 cracks 
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 
Normalized Time-to-Failure, t / t f 
creep curve, P c = 0.1 MPa 
NOTE: Driving-stress ratios of 0.8. 
Figure S-13. Creep Curve and Damage in mS50 Material for Static-Fatigue Test (0.1 MPa Confinement) 
ANL-EBS-MD-000027 REV 03 S-15 September 2004 

Drift Degradation Analysis 
S2.2.5 Effect of Void Porosity and Confinement on Static-Fatigue Curves 
The effect of void porosity on the static-fatigue curves of the mS50 material is shown in 
Figures S-14 and S-15. While the slope of the curves varies slightly, it is generally observed that 
increasing the void porosity reduces the time-to-failure for the same driving-stress ratio, and the 
static-fatigue curves are similar. It seems that the curves for various void porosities may be 
converging for very small driving-stress ratios. Note that in these figures, the data is fit with a 
fourth-order polynomial instead of a straight line (see Figures S-16 and S-17). Based on the 
definition of a static-fatigue curve, the time to failure should be zero for a driving-stress ratio of 
one. The polynomial fit approximates this trend, whereas a linear fit does not. The polynomial 
fit is used for most figures in this section; however, a linear fit has been used in the remainder of 
the report. The exact form of the static-fatigue curve is not known, because of a lack of 
laboratory data for driving-stress ratios below 0.65; thus, for extrapolation purposes, a linear fit 
was deemed acceptable. 
PFC2D (90-mm diameter circles) 
6 
4 
2 
0 
-2 
432432432 
( 
( 
(
sc (n v) 
sc (n vsc (n vy = -72.8x + 127.52x -76.768x + 7.6901x + 11.152 
y = -12.281x + 3.859x + 10.478x - 18.784x + 13.269 
y = -74.785x + 154.41x -111.29x + 17.521x + 9.8533 
mS50, nv=0Pc=0.1 MPa) 
mS50, nv=0.11Pc=0.1 MPa) 
mS50, nv=0.20Pc=0.1 MPa) 
= 65.2 MPa = 0= 26.2 MPa = 0.11) 
= 14.6 MPa = 0.20) 
0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
Figure S-14. Effect of Void Porosity on Static-Fatigue Curves (0.1 MPa Confinement) for mS50 Material 
Logarithm of Time-to-Failure, tf (sec) 
ANL-EBS-MD-000027 REV 03 S-16 September 2004 

Drift Degradation Analysis 
PFC2D (90-mm diameter circles) 
Logarithm of Time-to-Failure, tf 
(sec) 
14 
10 
6 
2 
-2 
432432432 
(
scn v) 
scn v) 
scn v) 
iiy = -72.8x + 127.52x -76.768x + 7.6901x + 11.152 
y = -12.281x + 3.859x + 10.478x - 18.784x + 13.269 
y = -74.785x + 154.41x - 111.29x+ 17.521x + 9.8533 
mS50, nv=0 Pc=0.1 MPa) 
mS50, nv=0.11 (Pc=0.1 MPa) 
mS50, nv=0.20 (Pc=0.1 MPa) 
= 65.2 MPa ( = 0 
= 26.2 MPa ( = 0.11 
= 14.6 MPa ( = 0.203.17 mllion years 
317 years 
3.2 years 
2.8 hours 
1.7 mnutes 
1 second 
11.6 days 
0.0 0.2 0.4 0.6 0.8 1.0 
Driving-Stress Ratio, s/sc 
Figure S-15. Effect of Void Porosity on Static-Fatigue Curves (0.1 MPa Confinement) for mS50 
Material  Expanded Scales 
PFC2D (90-mm diameter circles) 
R2R2R2-2 
0 
2 
4 
6 
iiilt f) 
() 
) 
) 
scn v = 0) 
scn v) 
scn v) 
y = -14.924x + 14.749 
= 0.883 
y = -15.724x + 13.981 
= 0.9601 
y = -15.627x + 13.353 
= 0.9917 
Logarthm of Tme-to-Faure, (secmS50, nv=0Pc=0.1 MPamS50, nv=0.11 (Pc=0.1 MPamS50, nv=0.20 (Pc=0.1 MPa 
= 65.2 MPa ( 
= 26.2 MPa ( = 0.11 
= 14.6 MPa ( = 0.20
0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
Figure S-16. Effect of Void Porosity on Static-Fatigue Curves (0.1-MPa Confinement) for mS50 Material 
(Straight-Line Fit) 
ANL-EBS-MD-000027 REV 03 S-17 September 2004 

Drift Degradation Analysis 
PFC2D (90-mm diameter circles) 
Logarithm of Time-to-Failure, tf (sec) 
14 
10 
6 
2 
-2 
R2R2R2 
(
) 
) 
sc (nv) 
sc (nv) 
sc (nv) 
iiy = -14.924x + 14.749 
= 0.883 
y = -15.724x + 13.981 
= 0.9601 
y = -15.627x + 13.353 
= 0.9917 
mS50, nv=0Pc=0.1 MPa) 
mS50, nv=0.11 (Pc=0.1 MPamS50, nv=0.20 (Pc=0.1 MPa 
= 65.2 MPa = 0 
= 26.2 MPa = 0.11 
= 14.6 MPa = 0.203.17 mllion years 
317 years 
3.2 years 
2.8 hours 
1.7 mnutes 
1 second 
11.6 days 
0.0 0.2 0.4 0.6 0.8 1.0 
Driving-Stress Ratio, s/sc 
Figure S-17. Effect of Void Porosity on Static-Fatigue Curves (0.1 MPa Confinement) for mS50 Material 
(Straight-Line Fit)  Expanded Scales 
If the linear fit is used for time-to-failure results obtained using PFC for different percentages of 
lithophysal porosity, the slope of the line is considered independent of the lithophysal 
porosity. The main effect of lithophysal porosity is translation of the time-to-failure 
line. Consequently, the line for 20 percent porosity intersects the horizontal line corresponding 
to 1 s time-to-failure for driving stress ratio of 0.85 (see Figure S-15). The strength after 1 s of 
loading time is considered to represent the short-term strength of a rock. This implies that if the 
lines in Figure S-15 are scaled with strength of the rock after 1 s loading time, the lines would 
coincide with each other. However, the consideration of time-dependent behavior contributes to 
an additional short-term strength reduction of approximately 15 percent (it is accounted for in the 
short-term strength reduction because it happens over a time period on the order of a second). In 
the calculation of time-dependent drift degradation, it is considered that time-to-failure curves 
are independent of lithophysal porosity. The effect of lithophysal porosity on short-term strength 
is accounted for because 5 different categories were analyzed. Variation of short-term strength 
between categories 1 and 5 is from 10 MPa to 30 MPa. The effect of time-dependency, within 
one or a few seconds, on short-term strength (of the order of 15 percent) is taken into account by 
the consideration of a wide range of strength variation. Although the time-to-failure curves for 
different lithophysal porosities are the same, the effect of lithophysal porosity on time-dependent 
drift degradation is significant. For example, uniaxial compressive elastic stress in the drift wall 
is estimated to be 17.5 MPa, which is derived considering that the vertical in situ stress (sv) is 
7 MPa and the horizontal-to-vertical stress ratio (k) is 0.5 (see Section 6.3.1.1), using the relation 
.
s1 
= sv (3  k) (Hoek and Brown 1982 [DIRS 120981], p. 105). Using the time-to-failure curve 
for tuff (Figure S-2), time to failure in category 2 corresponding to 28 percent porosity (such that 
UCS = 20 MPa resulting in a driving stress ratio of 0.875) is approximately 3 hours, while 
ANL-EBS-MD-000027 REV 03 S-18 September 2004 

Drift Degradation Analysis 
time-to-failure in category 3 corresponding to 21 percent porosity (such that UCS = 25 MPa 
resulting in a driving stress ratio of 0.7) is approximately 8,200 years. 
The effect of confinement on the static-fatigue curves of the mS50 material is shown in 
Figures S-18 and S-19. Increasing the confinement increases the time-to-failure for the same 
driving-stress ratio, and the static-fatigue curves are similar. The effect of void porosity on the 
static-fatigue curves of the mS50 material at 5 MPa confinement, is shown in Figures S-20 and 
S-21. Increasing the void porosity reduces the time-to-failure for the same driving-stress ratio; 
however, the effect is not seen for void porosities greater than 0.11. Based on this numerical 
assessment, it appears that the effect of void porosity on time-to-failure is reduced as 
confinement increases, and that there is a limiting void porosity above which no further 
reduction occurs. 
The effect of voids on time-to-failure was investigated numerically (e.g., Figure S-20). The 
increase in porosity results in shorter time-to-failure. However, the slopes of the lines of 
time-to-failure versus driving stress ratio are practically the same. That implies that if the 
driving stress ratio is normalized with the strength for one minute of load duration, the lines 
would be the same. Thus, the time to failure is independent of the lithophysal porosity if plotted 
versus normalized driving stress ratio. The evolution of damage as a function of driving stress 
ratio and time normalized with time-to-failure is similar. Particularly for large driving stress 
ratios (greater than 0.5), which are of interest because they result in failure for time-scales of 
10,000 years or less, there is very little damage increase until time-to-failure is reached when 
damage suddenly increases resulting in the collapse. 
PFC2D (90-mm diameter circles) 
Logarithm of Time-to-Failure, tf (sec) 
6 
4 
2 
0 
-2 
432432 
( 
(
scscy = -72.8x + 127.52x - 76.768x + 7.6901x + 11.152 
y = -47.672x + 83.372x - 51.247x+ 0.4025x + 13.94 
mS50, nv=0Pc=0.1 MPa) 
mS50, nv=0Pc=5 MPa) 
= 65.2 MPa (Pc=0.1 MPa) 
= 73.1 MPa (Pc=5 MPa) 
0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
Figure S-18. Effect of Confinement on Static-Fatigue Curves for mS50 Material 
ANL-EBS-MD-000027 REV 03 S-19 September 2004 

Drift Degradation Analysis 
PFC2D (90-mm diameter circles) 
432432-2 
2 
6 
10 
14 
iiilt f) 
( 
(
sc) 
sciy = -72.8x + 127.52x - 76.768x + 7.6901x + 11.152 
y = -47.672x + 83.372x - 51.247x + 0.4025x + 13.94 
Logarthm of Tme-to-Faure, (secmS50, nv=0Pc=0.1 MPa) 
mS50, nv=0Pc=5 MPa) 
= 65.2 MPa (Pc=0.1 MPa 
= 73.1 MPa (Pc=5 MPa) 
3.17 million years 
317 years 
3.2 years 
2.8 hours 
1.7 mnutes 
1 second 
11.6 days 
0.0 0.2 0.4 0.6 0.8 1.0 
Driving-Stress Ratio, s/sc 
Figure S-19. Effect of Confinement on Static-Fatigue Curves for mS50 Material  Expanded Scales 
PFC2D (90-mm diameter circles) 
432432432-2 
0 
2 
4 
6 
iilt f) 
sc (nv) 
sc (nvsc (nvy = -47.672x + 83.372x - 51.247x + 0.4025x + 13.94 
y = -32.416x + 49.276x - 20.384x - 11.822x + 13.507 
y = 40.434x - 110.05x + 94.792x - 42.525x + 15.923 
Logarithm of Tme-to-Faure, (secmS50, nv=0 (Pc=5 MPa) 
mS50, nv=0.11 (Pc=5 MPa) 
mS50, nv=0.20 (Pc=5 MPa) 
= 73.1 MPa = 0= 29.6 MPa = 0.11) 
= 18.5 MPa = 0.20) 
0.6 0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
Figure S-20. Effect of Void Porosity on Static-Fatigue Curves (5 MPa Confinement) for mS50 Material 
ANL-EBS-MD-000027 REV 03 S-20 September 2004 

Drift Degradation Analysis 
PFC2D (90-mm diameter circles) 
Logarithm of Time-to-Failure, tf (sec) 
14 
10 
6 
2 
-2 
432y432 -
432 
(
(
(
sc (nv) 
sc (nvsc (nviiy = -47.672x + 83.372x - 51.247x + 0.4025x + 13.94 
= -32.416x + 49.276x - 20.384x 11.822x + 13.507 
y = 40.434x - 110.05x + 94.792x- 42.525x + 15.923 
mS50, nv=0Pc=5 MPa) 
mS50, nv=0.11 Pc=5 MPa) 
mS50, nv=0.20 Pc=5 MPa) 
= 73.1 MPa = 0= 29.6 MPa = 0.11) 
= 18.5 MPa = 0.20) 
3.17 m llion years 
317 years 
3.2 years 
2.8 hours 
1.7 mnutes 
1 second 
11.6 days 
0.0 0.2 0.4 0.6 0.8 1.0 
Driving-Stress Ratio, s/sc 
Figure S-21. Effect of Void Porosity on Static-Fatigue Curves (5-MPa Confinement) for mS50 
Material  Expanded Scales 
S2.3 QUANTIFYING DAMAGE DURING A STATIC-FATIGUE TEST 
The axial load at failure (peak strength) during a short-term test performed at an elapsed time, t, 
* *
since the start of a static-fatigue test is denoted by s*
f = sf (t). The values of sf are bounded by 
s
*
f (0) = sf 
s
*
f (tf) = (s/sc ) (sf - Pc) + Pc (Eq. S-1) 
where the notation is defined in the first footnote of Section S2.1. The values of s*
f for times 
0 < t < tf are found by stopping the static-fatigue test at the desired time and measuring the peak 
strength. 
The strength degradation is quantified by means of a damage coefficient 
D = 1 -s*
c /sc (Eq. S-2) 
*
where s*
c = sf - Pc is the stress difference at failure. Substituting values from Equation S-1 into 
this expression provides the following bounds for the damage coefficient: 
D(0) = 0 
D(tf) = 1 - (s/sc ) (Eq. S-3) 
The time evolution of the damage coefficient for the mS50 material tested at a confinement of 
0.1 MPa is shown in Figure S-22, which was produced by performing 11 compression tests 
ANL-EBS-MD-000027 REV 03 S-21 September 2004 

Drift Degradation Analysis 
during the four numerical static-fatigue tests at driving-stress ratios of 0.8, 0.6, 0.4 and 0.2. 
Typical model responses during some of the compression tests are shown in Figures S-23 to 
S-25. It is noted that the curve for t/tf = 0.975 in Figure S-23 results in a higher axial stress 
compared to the other curves. This behavior is a result of complex interactions in the model (and 
in actual rock). The peak strength in an unconfined compressive strength test is a measure of a 
critical state forming, and if a very slightly different critical state forms, a slightly different 
strength will be measured. This means that there is no reason why it is not possible that the 
addition of a few additional cracks (and reduced parallel bond radii in the PFC the stress 
corrosion model) might not increase the strength. The critical state at peak is very complex, and 
a minor change in rearrangements of force chains (i.e., trajectories of magnified principal 
stresses) might lead to a small increase in strength. Most damage occurs during the final stages 
of a static-fatigue test, and tests performed at lower driving-stress ratios produce an earlier (in 
terms of normalized times-to-failure) onset of damage. 
PFC2D (90-mm diameter circles, nv = 0) 
Damage Coefficient 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
iiiiiiiit f ) 
t f ) 
t f ) 
drivng stress rato = 0.8 
drivng stress rato = 0.6 
drivng stress rato = 0.4 
drivng stress rato = 0.2 
203 cracks 
418 cracks 
= 5.086e03 sec (0.8= 2.175e08 sec (0.4= 3.191e10 sec (0.2314 cracks 
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 
Normalized Time-to-Failure, t / tf
damage curves, Pc = 0.1 MPa
NOTE: Driving-stress ratios ranging from 0.2 to 0.8. 
Figure S-22. Time Evolution of Damage Coefficient for mS50 Material During Numerical Static-Fatigue 
Tests (0.1 MPa Confinement) 
ANL-EBS-MD-000027 REV 03 S-22 September 2004 

Drift Degradation Analysis 
70 
PFC2D (90-mm diameter circles, nv = 0) 
compression test on original material 
60 (stress corrosion not active) 
Axial Stress (MPa)
50 
tf = 5.086e03 sec (0.8) 
40 4 compression tests at 
dif ferent times during 
30 static-f atigue test. 
normalized time-to-failure = 0.25 
20 normalized time-to-failure = 0.50 
normalized time-to-failure = 0.75 
10 normalized time-to-failure = 0.975 
compression test (Pc = 0.1 MPa) 
0 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 
Axial Strain (%) 
stress-strain curves, s/sc = 0.8 
NOTE: Driving-stress ratio of 0.8. 
Figure S-23. Stress-Strain Curves for mS50 Material at Different Times During Static-Fatigue Test 
(0.1 MPa Confinement) 
PFC2D (90-mm diameter circles, nv = 0)
70
compression test on original material
(stress corrosion not active)
60 
Axial Stress (MPa)
50 
tf = 2.175e08 sec (0.4) 
40 
30 
normalized time-to-failure = 0.25 
20 
normalized time-to-failure = 0.50 
4 compression tests at 
normalized time-to-failure = 0.75 
dif f erent times during
10 
normalized time-to-failure = 0.975 
static-f atigue test. 
compression test (Pc = 0.1 MPa)
0
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 
Axial Strain (%) 
stress-strain curves, s/sc = 0.4 
NOTE: Driving-stress ratio of 0.4. 
Figure S-24. Stress-Strain Curves for mS50 Material at Different Times During Static-Fatigue Test 
(0.1 MPa Confinement) 
ANL-EBS-MD-000027 REV 03 S-23 September 2004 

Drift Degradation Analysis 
Axial Stress (MPa) 
PFC2D (90-mm diameter circles, nv = 0)
70 
compression test on original material 
(stress corrosion not active)
60 
50 
tf = 3.191e10 sec (0.2) 
40 
30 
normalized time-to-failure = 0.25 
20 
normalized time-to-failure = 0.50 
normalized time-to-failure = 0.75 
4 compression tests at 
10 
normalized time-to-failure = 0.975 
dif f erent times during 
static-f atigue test. compression test (Pc = 0.1 MPa) 
0 
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 
Axial Strain (%) 
stress-strain curves, s/sc = 0.2 
NOTE: Driving-Stress Ratio of 0.2. 
Figure S-25. Stress-Strain Curves for mS50 Material at Different Times During Static-Fatigue Test 
(0.1 MPa Confinement) 
S3. MODELING TUNNEL STABILITY WITH UDEC 
The objective of the analysis presented in this section is to predict the amount of rockfall in the 
emplacement drifts due to long-term (approximately 10,000 years) strength degradation caused 
by stress corrosion of the lithophysal rock units combined with thermal and seismic loads. 
The two-dimensional distinct element code UDEC (Version 3.1) was used to investigate drift 
degradation based upon the time evolution of damage due to strength degradation for different 
driving-stress ratios (s/sc). 
S3.1 UDEC MODEL FOR DRIFT DEGRADATION 
The same UDEC model validated and used to predict the amount of rockfall in the emplacement 
drifts (as documented in Sections 6.4 and 7.6) was used to investigate the long-term degradation 
caused by stress corrosion of the lithophysal rock units. 
In the UDEC model, the rock mass is represented as an assembly of polygonal, elastic blocks. 
The entire domain is discretized into blocks using Voronoi tessellations (Itasca Consulting Group 
2002 [DIRS 160331]). The joints between the blocks are considered to be linearly elastic-brittle. 
The elastic behavior of the joints is controlled by normal and shear stiffness. The joints can 
sustain finite tensile stress as prescribed by a tensile strength. The Coulomb slip condition 
governs the onset of slip as a function of joint cohesion and friction angle. If a joint fails either 
in tension or shear, tensile strength, friction and cohesion are reset to residual values. The model 
ANL-EBS-MD-000027 REV 03 S-24 September 2004 

Drift Degradation Analysis 
allows for the formation of joints between blocks, separation and instability (under gravity) of 
portions of the rock mass around the drift. The average size of the Voronoi blocks is 0.3 m. No 
ground support was considered in the analysis. 
The geometry of the UDEC model is shown in Figure 6-116. Only the region around the drift 
(where inelastic deformation is expected) is discretized into Voronoi blocks. The remainder of 
the model is composed of a few large elastic blocks. 
Four different categories of the lithophysal rock mass were used to investigate the long-term 
degradation caused by stress corrosion. The categories investigated were 1, 2, 3, and 5. The 
calibrated UDEC micro-properties for those categories are listed in Table 6-43. 
S3.2 STATIC-FATIGUE CURVES AND THE EVOLUTION OF DAMAGE DUE TO 
STRENGTH DEGRADATION 
The static-fatigue behavior of Lac du Bonnet granite and welded lithophysal tuff forms the basis 
of the UDEC model for stress corrosion around a drift. The static-fatigue curves provide the 
time-to-failure (tf) of the material at a particular driving-stress ratio (s/sc). 
The static-fatigue data for Lac du Bonnet granite at 0 and 5 MPa confinement, tuff at 5 MPa 
confinement, and 4.5 MPa pore pressure, are shown in Figure S-2. Each data set was fit with a 
straight line, and the line was extrapolated to encompass driving-stress ratios ranging from zero 
to one. This is a conservative consideration, because the curves most likely approach infinity at 
a driving-stress ratio greater than zero (see the discussion in Appendix S2.2.4). Three lines for 
the tuff data are shown in Figure S-26. The blue line in the figure is the least-square linear fit 
through the tuff data, while the purple line (labeled tuff, best fit through origin) is the best fit 
for the tuff data with the origin (i.e., logarithm of time-to-failure = 0) set at a driving-stress ratio 
of one. Since the tuff data are limited and are for confined conditions (effective confining stress 
of 0.5 MPa) only, the UDEC model has used a simplified best fit (red line) for the tuff best-fit 
curve. 
The two sets of extended curves that were used as input to the UDEC analyses are shown in 
Figure S-27: one set based on the Lac du Bonnet data and the other set based on tuff data. 
ANL-EBS-MD-000027 REV 03 S-25 September 2004 

Drift Degradation Analysis 
tuff tests at T=150C 
Logarithm of Time-to-Failure, tf (sec)
6 
4 
2 
0 
yiigin 
lit 
li 
() 
()il 
igin 
lsf 
= -31.277x + 31.277 
best ft through ory = -42.204x + 40.954 
east square best fy = -30.000x + 30.000 
mode best ft curve 
tuffPc=5, Pp=4.5 MPatuffPc=5, Pp=4.5 MPa, no fatuff, bes t fit through ortuff, m ode best fit curve 
tuff, leas t s quare bes t fit 
= 151 MPa 
0.7 0.8 0.9 1.0 
Driving-Stress Ratio, s/sc 
Source: Tuff data from Martin et al. (1997 [DIRS 165960]). 
Figure S-26. Static-Fatigue Data for Welded Tuff and Best-Fit Lines 
R20 
2 
4 
6 
8 
10 
12 
14 
Logarithm of Time-to-Failure, t f (sec) 
LdB (
LdB ( 
(
LdB (it 
y = -30.000x + 30.000 
Tuff best fit 
y = -13.541x + 13.503 
= 0.738 
Pc=0) 
Pc=5 MPa) 
Tuf fPc=5, Pp=4.5 MPa) 
Tuff, best fit 
Pc=0), best f 
0.40 0.50 0.60 0.70 0.80 0.90 1.00 
Driving-Stress Ratio, s/sc 
Source: LdB data from Schmidtke and Lajtai (1985 [DIRS 164774]) and Lau et al. (2000 [DIRS 164769]); tuff data 
from Martin et al. (1997 [DIRS 165960]). 
Figure S-27. Static-Fatigue Curves Used as Input to the UDEC Analyses 
ANL-EBS-MD-000027 REV 03 S-26 September 2004 

Drift Degradation Analysis 
An understanding of the evolution of damage due to strength degradation during a static-fatigue 
test prior to the time-to-failure enables a modeling methodology to be developed whereby the 
strength of material is degraded with time based upon the local driving-stress ratio. The 
evolution of damage due to strength degradation for the static-fatigue curve (unconfined Lac du 
Bonnet granite) was developed using the PFC stress corrosion model and is shown in 
Figure S-22 for Lac du Bonnet granite. The evolution of damage for tuff (i.e., unconfined 
best-fit tuff) was not obtained by conducting a PFC simulation, but by changing the time scale of 
the relation between damage and time for the Lac du Bonnet granite. These damage curves were 
simplified (as shown in Figures S-28 and S-29), and then used along with the static-fatigue 
curves in Figure S-27 to provide the degradation input properties used in the UDEC analyses. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0
0 2 4 6 8101214
driviidrividriviidrividriviidrividriviidrividriviing-stress ratio = 0.1 
nterpolated 
ng-stress ratio = 0.2 
PFC 
ng-stress ratio = 0.3 
nterpolated 
ng-stress ratio = 0.4 
PFC 
ng-stress ratio = 0.5 
nterpolated 
ng-stress ratio = 0.6 
PFC 
ng-stress ratio = 0.7 
nterpolated 
ng-stress ratio = 0.8 
PFC 
ng-stress ratio = 0.9 
nterpolated 
Logarithm of Time (sec) 
NOTE: Each curve has a vertical asymptote at a time-to-failure for a given driving-stress ratio, which is provided by 
the LdB (Pc = 0) curve from Figure S-27. The evolution of damage up to the vertical asymptote (i.e., the 
failure time) is provided by the PFC stress corrosion model. Pc = 0. 
Figure S-28. Damage Curves Used as Input to the UDEC LdB Analyses 
Damage Coefficient 
ANL-EBS-MD-000027 REV 03 S-27 September 2004 

Drift Degradation Analysis 
Damage Coefficient 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0
0 2 4 6 8 101214 161820 222426 2830
driviidriviidriviidriviidriviidriviidriviidriviidriviing-stress ratio = 0.1 
nterpolated 
ng-stress ratio = 0.2 
nterpolated 
ng-stress ratio = 0.3 
nterpolated 
ng-stress ratio = 0.4 
nterpolated 
ng-stress ratio = 0.5 
nterpolated 
ng-stress ratio = 0.6 
nterpolated 
ng-stress ratio = 0.7 
nterpolated 
ng-stress ratio = 0.8 
nterpolated 
ng-stress ratio = 0.9 
nterpolated 
Logarithm of Time (sec) 
NOTE: Each curve has a vertical asymptote at a time-to-failure for a given driving-stress ratio, which is provided by 
the tuff best fit (Pc = 0) curve from Figure S-27. The evolution of damage up to the vertical asymptote (i.e., 
the failure time) was not provided by the PFC stress corrosion model, but was obtained by changing time 
scales for each curve proportional to the relation between damage and time for the Lac du Bonnet granite 
(Figure S-28). Pc = 0. 
Figure S-29. Damage Curves Used as Input to the UDEC Tuff Best-Fit Analyses 
Two parameters control the UDEC predictions of time-dependent strength degradation, and 
eventually the predictions of rockfall: a) time-to-failure, and b) damage rate before 
time-to-failure. The evolution of damage before failure can be approximated with a constant 
damage rate. Time-to-failure as a function of the stress state (i.e., the driving stress) is 
determined from the static-fatigue lines constructed by interpolation and extrapolation of testing 
results (obtained on tuff and Lac du Bonnet granite). Damage rates at different stress levels are 
generated using the PFC stress corrosion model. To address the concern about the level of 
uncertainty in PFC predictions, and how the damage rates affect the final result of the model 
(i.e., the rockfall induced by time-dependent strength degradation), the sensitivity of the model 
predictions to the damage rate was investigated. New damage curves are generated for tuff 
best-fit static-fatigue (shown in Figure S-30), where the damage rates for the driving stress levels 
are considered to be the same, equal to the maximum rate predicted by PFC. 
The rockfall predictions due to time-dependent strength reduction, using damage curves from 
Figure S-30, are shown in Figure S-31. It is clear that the considered variation of damage rates 
has no practical effect on predicted rockfall. The time-to-failure is the main factor controlling 
evolution of the rockfall due to time-dependent strength reduction. Consequently, UDEC 
predictions are not very sensitive to the input from the PFC stress corrosion model. 
ANL-EBS-MD-000027 REV 03 S-28 September 2004 

Drift Degradation Analysis 
Damage Coefficient 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
driviiidriviiidriviiidriviiidriviiidriviiidriviiidriviiidriviiing-stress rato = 0.1 
nterpolated 
ng-stress rato = 0.2 
nterpolated 
ng-stress rato = 0.3 
nterpolated 
ng-stress rato = 0.4 
nterpolated 
ng-stress rato = 0.5 
nterpolated 
ng-stress rato = 0.6 
nterpolated 
ng-stress rato = 0.7 
nterpolated 
ng-stress rato = 0.8 
nterpolated 
ng-stress rato = 0.9 
nterpolated 
0 2 4 6 8 10 12141618 20222426 2830
Logarithm of Time (sec)
Figure S-30. Damage Curves for Sensitivity Analysis of Damage Rate 
ANL-EBS-MD-000027 REV 03 S-29 September 2004 

Drift Degradation Analysis 
Tuff best fit static fatigue and damage rate sensitivity at 100 years 
Tuff best fit static fatigue and damage rate sensitivity at 10000 years 
Figure S-31. The Effect of the Damage Rate on Rockfall Predictions Due to Time-Dependent Strength 
Degradation After 100 Years and 10,000 Years 
S3.3 UDEC STRESS CORROSION MODELING 
The long-term strength degradation caused by stress corrosion of the lithophysal rock units was 
implemented in the UDEC model by incrementally referencing a series of evolution of damage 
due to strength degradation tables from the PFC stress corrosion model (shown in Figures S-28 
and S-29). Based upon the local driving-stress ratio at the Voronoi block contacts within the 
UDEC model, the strength of the contact in the model is degraded as a function of time. The 
times considered were 1, 5, 10, 50, 100, 500, 1000, 5000 and 10,000 years. 
ANL-EBS-MD-000027 REV 03 S-30 September 2004 

Drift Degradation Analysis 
Time-dependent strength degradation in the UDEC model is generalized by a damage 
coefficient, D, which is, in general, in the range between 0 and 1. The cohesion and tensile 
strength of the material are considered to be functions of time: 
c(t) = c0D(t) 
T(t) = T0D(t) (Eq. S-4) 
where c0 and T0 are the cohesion and tensile strength of joints in the UDEC model. The 
short-term strength of the UDEC synthetic model of the rock mass (large scale) is proportional to 
the cohesion and tensile strength of joints, c0 and T0, respectively. Consequently, the 
time-dependent strength of the UDEC synthetic model of lithophysal rock mass will decay 
proportionally to D(t). 
It is considered that in the general case: 
dD 
=f (F, D) (Eq. S-5) 
dt 
where F, a function of stress state and material strength, defines the load level (driving stress). 
For unconfined stress conditions (i.e., Pc = 0), the function F must be identical to the ratio of the 
axial load and the unconfined short-term strength: F(Pc = 0) =s/sf . The load at failure during 
1
a short-term test is calculated as follows (Jaeger and Cook 1979 [DIRS 106219], pp. 95 to 97): 
sf= N Pf+ 2cNf
c 
(Eq. S-6) 
1+ sinf 
=
Nf 
1- sinf 
where c and f are the rock mass cohesion and friction angle, respectively. It is considered that if 
time-to-failure for two different stress states is the same, then evolution of damage due to 
strength degradation for both states as a function of time is the same, irrespective of the 
confinement. Based on the existing data (Lau et al. 2000 [DIRS 146749]; Schmidtke and Lajtai 
1985 [DIRS 164774]), it can be concluded that the confinement affects the slope, 
k(Pc) = .(s/sc ) / .log(tf), of the static-fatigue line. For example, the slopes of the static-fatigue 
lines for LdB granite (Figure S-1) are: 
k(0) = 0.074 1/log(sec) 
k(5 MPa) = 0.041 1/log(sec) (Eq. S-7) 
Because static-fatigue lines are available for only two values of confining stress (0 and 5 MPa) it 
was considered that the dependence of slope k on confinement Pc is linear. This consideration is 
not a consequence of limitation of the implementation, but due to limited data. The form of the 
function F used in the UDEC model is as follows: 
F= 1 - k(0)...
1 - 
s 
..
. 
(Eq. S-8) 
P k c) .sc .
( 
ANL-EBS-MD-000027 REV 03 S-31 September 2004 

Drift Degradation Analysis 
The damage evolution D(F;t) was generated using PFC2D for values of function F in the range 
between 0 and 1 (see Figure S-22), and used as the UDEC input data in a tabular form (see 
Figure S-28.). Interpolation was carried out for stress states in the model during the simulation 
for which function F did not coincide with values for which the tables were provided. 
It is realistic for implementation that the damage increment in Equation S-5 depends implicitly 
on stress history. The damage increment depends on accumulated damage, which is a function 
of the stress history. Although the stress state at a point can undergo complex history as a 
function of time (due to stress redistribution), it is sufficient in the simulation to keep track of 
accumulated damage only. 
The calculation of the damage increment in the UDEC simulation was carried out in the 
following way. For a given time increment, .t, it is considered that the stress state and the stress 
function, F, at a given point in the model are constant, F = Fi. The table of damage evolution 
D(F;t) is selected or interpolated based on tables provided. A point on the damage evolution 
curve corresponding to accumulated damage Dj is determined, Dj = D(Fi;tj). The damage 
increment is calculated as follows: 
.D = D(Fi;tj + .t ) - D(Fi;tj) (Eq. S-9) 
Time increment(s) for the simulation must be selected. The criteria for selection are the accuracy 
of the simulation (stress state considered to be constant during the time increment) and 
calculation time. Preliminary investigations showed that initially selected time increments did 
not significantly affect model results. For example, the results in Figure S-36 are obtained for 
the same conditions as the results in Figure S-38, but using the following points in time: 1, 2, 3, 
5, 10, 20, 30, 50, 100, 200, 300, 500, 1000, 2000, 3000, 5000 and 10,000 years. The results are 
not identical. However, the difference is insignificant considering other uncertainties in the 
model, and the use of the selected time increments is justified. 
Damage is calculated and accumulated for joints. The stress state used for calculation of the 
damage is determined by averaging stresses in the blocks separated by a joint. 
S3.4 MODELING RESULTS 
S3.4.1 Time-Dependent Consideration in Lithophysal Units 
The drift degradation results are presented as damage and displacement plots at time increments 
of 1, 5, 100, 1000, 5000 and 10,000 years. A complete set of damage and displacement results 
for the tuff static-fatigue curves at lithophysal categories 1, 2, 3, and 5 are presented in this 
section. Lac du Bonnet granite static-fatigue curves are analyzed for lithophysal categories 1, 2, 
and 5, only, to show the range of results. 
Two sets of static-fatigue curves (for Lac du Bonnet granite and tuff) were selected to bound 
expected time-dependent behavior of the lithophysal tuff, considering that limited data are 
available. The validity of the PFC stress corrosion modeling and the selected model parameters 
can be shown by a comparison with the observed behavior of the existing drifts at Yucca 
Mountain. The construction of the ESF main loop began in November 1992 and was completed 
ANL-EBS-MD-000027 REV 03 S-32 September 2004 

Drift Degradation Analysis 
in April 1997, while the construction of the ECRB Cross-Drift began in December 1997, and 
was completed in October 1998. The ESF and ECRB Cross-Drift have been excavated and open 
for 5 to 12 years. While minor rockfall in the drifts was observed immediately after excavation, 
there is no indication of increased damage as a function of time, and no indication of rockfall as 
a consequence of time-dependent drift degradation. The ground support in the lithophysal rock 
in the ECRB Cross-Drift consists of rock bolts and wire mesh installed in the roof. The walls are 
not supported, and are comparable to the UDEC model results, which do not include ground 
support. 
Figure S-32 shows the model state 500 years after excavation of the drift in category 2 tuff 
material considering the tuff best-fit static fatigue line. The damage occurs in the drift 
walls. Stresses are redistributed away from the drift sidewalls as the drift degrades. The stress 
redistribution causes the local driving-stress ratio to increase at greater distances from the 
excavation boundary. 
block plot 
Principal stresses 
(color code - s1 magnitude) 
-2.788E+ 07 -> 1.185E+ 05 
-2.000E+ 06 0.000E+ 00 
-4.000E+ 06 -2.000E+ 06 
-6.000E+ 06 -4.000E+ 06 
-8.000E+ 06 -6.000E+ 06 
-1.000E+ 07 -8.000E+ 06 
-1.200E+ 07 -1.000E+ 07 
-1.400E+ 07 -1.200E+ 07 
-1.600E+ 07 -1.400E+ 07 
-1.800E+ 07 -1.600E+ 07 
-2.000E+ 07 -1.800E+ 07 
NOTE: The top left figure shows the contours of displacement magnitudes (m) and fractures in the rock mass 
(blue lines); the top right figure shows accumulated damage, where the thickness of the blue lines are 
proportional to the accumulated damage (between 0 and 1); the bottom left figure shows the principal 
stress tensors (Pa) colored by the magnitude of the major principal stress; the bottom right figure shows 
the contours of the scaled driving stress (between 0 and 1). 
Figure S-32. Model State for Tuff, Category 2 After 500 Years 
ANL-EBS-MD-000027 REV 03 S-33 September 2004 

Drift Degradation Analysis 
Evolution of damage due to time-dependent strength degradation in the lithophysal rock mass 
(categories 1, 2, and 5) considering Lac du Bonnet granite static-fatigue, is shown in 
Figures S-33 through S-35. The stress states in the wall in category 2, and particularly in 
category 1, are close to the yield state under in situ stress conditions. There is a relatively large 
region of the rock mass, a couple of meters from the drift wall, loaded with driving stress, F, 
equal to, or larger than 0.7. The static-fatigue curve for the Lac du Bonnet granite implies that 
time-to-failure is 1 year for the driving stress approximately equal to 0.5. Consequently, there is 
a significant rockfall from the drift walls 1 year after drift excavation. Damage and rockfall 
increase with time (for categories 1 and 2), eventually resulting in total drift collapse for 
category 1. In the case of category 5, the driving stress around the opening is on the order of 0.3, 
resulting in relatively minor rockfall from the drift walls over a period of 10,000 years. Clearly, 
the model predictions after 5 and 10 years are in disagreement with observations in the ESF and 
ECRB. The tunnels, which have been open between 5 and 12 years, are stable. There are no 
observations of their degradation with time. It appears that static-fatigue curves for Lac du 
Bonnet granite result in too rapid deterioration of the drift, and do not provide a good 
representation of time-dependent behavior of the lithophysal tuff. 
Evolution of damage due to time-dependent strength degradation in the lithophysal rock mass 
(categories 1, 2, 3 and 5) considering tuff static-fatigue, is shown in Figures S-37 through S-40 
for tuff best-fit static-fatigue curves. Time-dependent strength degradation using the best-fit 
static-fatigue curves for lithophysal tuff has been extended to 20,000 years in Figure S-41 for 
categories 1, 2, 3, and 5. 
It seems that category 1 underestimates the strength of the lithophysal rock mass. The tuff 
best-fit static-fatigue curve results in significant rockfall from the drift walls at 5 and 10 years 
after excavation (Figure S-37). The minor rockfall in Figure S-38 predicted by the model at 5 
and 10 years after excavation, would have been prevented if the ground support was taken into 
account in the model (note that the rockfall comes from above the springline). Based on model 
validation with respect to the conditions in the ESF and ECRB, it seems that category 2 with a 
tuff best-fit static-fatigue curve is a conservative approximation of the mechanical behavior of 
the poorest quality lithophysal rock mass. 
The best-fit tuff static fatigue line implies that a driving-stress ratio of approximately 0.60 results 
in approximately 20,000 years time-to-failure (see the tuff (Pc = 0) best-fit curve in Figure S-27). 
The damage coefficient for this case is D20,000  1 - 0.60 (Equation S-3), or 0.40, indicating there 
will be an approximate 40 percent cohesive strength reduction in 20,000 years. The drift profile 
for a 40 percent cohesive strength reduction case (i.e., 60 percent cohesive strength) was initially 
determined as shown in Figure 6-171c for category 1. Note that Figure 6-171c is similar to the 
category 1 profile in Figure S-41, indicating that at year 20,000, the rock mass is expected to 
have about 60 percent of its original cohesive strength due to time-dependent strength 
degradation. 
ANL-EBS-MD-000027 REV 03 S-34 September 2004 

Drift Degradation Analysis 
Figure S-33. Evolution of Damage Due to Strength Degradation for Category 1 - Lac du Bonnet Granite 
Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-35 September 2004 

Drift Degradation Analysis 
Figure S-34. Evolution of Damage Due to Strength Degradation for Category 2 - Lac du Bonnet Granite 
Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-36 September 2004 

Drift Degradation Analysis 
Figure S-35. Evolution of Damage Due to Strength Degradation for Category 5 - Lac du Bonnet Granite 
Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-37 September 2004 

Drift Degradation Analysis 
1 years 
10 years 
5 years 
100 years 
1000 years 
10000 years 
Figure S-36. Evolution of Damage Due to Strength Degradation for Category 2 - Tuff Best-Fit 
Static-Fatigue Curve (Reduced Time Increment) 
ANL-EBS-MD-000027 REV 03 S-38 September 2004 

Drift Degradation Analysis 
Figure S-37. Evolution of Damage Due to Strength Degradation for Category 1 - Tuff Best-Fit 
Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-39 September 2004 

Drift Degradation Analysis 
Figure S-38. Evolution of Damage Due to Strength Degradation for Category 2 - Tuff Best-Fit 
Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-40 September 2004 

Drift Degradation Analysis 
Figure S-39. Evolution of Damage Due to Strength Degradation for Category 3 - Tuff Best-Fit 
Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-41 September 2004 

Drift Degradation Analysis 
Figure S-40. Evolution of Damage Due to Strength Degradation for Category 5 - Tuff Best-Fit 
Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-42 September 2004 

Drift Degradation Analysis 
Category 2 
Category 3 Category 5 
Category 1 
NOTE: The drift profiles show the effects of time-dependent strength degradation at 20,000 years. Thermal and 
seismic effects are not included with these drift profiles. Based on the comparison of model results to field 
data as described in this section, the category 2 rock mass is considered representative of the poorest 
quality lithophysal rock. 
Figure S-41. Damage Due to Strength Degradation for Categories 1, 2, 3, and 5 - Tuff Best-Fit 
Static-Fatigue Curve at Year 20,000 
S3.4.2 Combined Thermal and Time-Dependent Effect in Lithophysal Units 
Throughout the regulatory period of 10,000 years, the emplacement drifts and surrounding rock 
mass will be subject to a heating cycle. Time-dependent strength degradation will happen 
concurrently with transient, thermally induced stress changes. Increased stresses around the 
excavation will accelerate the process of strength degradation. The results of numerical 
simulation of drift degradation as a result of these two processes are shown in Figures S-42 
through S-44. Time-dependent strength degradation is assessed using the tuff best-fit 
static-fatigue line. From the discussion in the previous section, it appears that the tuff best-fit 
static-fatigue line is consistent with the behavior of the excavated drifts at Yucca Mountain and 
the results of the testing on lithophysal rock mass completed so far. As expected, most rockfall 
occurs in category 2 rock mass, as shown in Figure S-42. Initially most of rockfall comes from 
ANL-EBS-MD-000027 REV 03 S-43 September 2004 

Drift Degradation Analysis 
the walls, which are loaded almost to a yielding state for this rock mass category under in situ 
stress conditions. Strength degradation combined with a temperature increase, which at early 
times increases the hoop stress in the walls (not only in the roof), results in some rockfall from 
the wall at 5 and 10 years after emplacement of the waste. The large increase in the temperature, 
and consequently in the stresses, after the forced ventilation stops causes additional rockfall (at 
80 years). At this stage, stress increase is predominantly in the roof. Therefore, some rockfall 
comes from the roof. It is counterintuitive that more rockfall is predicted in category 5 
(Figure S-44) than in category 3 (Figure S-43). However, a large stiffness of category 5 
lithophysal rock mass causes a large (larger than in category 3) increase in the hoop stress and 
yielding in the roof, even considering the short-term yield strength of the rock mass 
(Figure 6-144). 
It should be noted that static-fatigue curves are temperature dependent. This dependence is not 
explicitly included in the analysis. However, the tuff data are obtained from tests conducted at 
150 C (see Section S2.1), which is larger than the maximum temperature of the rock mass 
anticipated throughout the repository for the base case described in Section 6.2. Consequently, 
the results obtained in this analysis, although for isothermal static-fatigue curves are 
conservative. 
ANL-EBS-MD-000027 REV 03 S-44 September 2004 

Drift Degradation Analysis 
Figure S-42. Evolution of Damage Due to Strength Degradation and Thermal Load for Category 2 - Tuff 
Best-Fit Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-45 September 2004 

Drift Degradation Analysis 
Figure S-43. Evolution of Damage Due to Strength Degradation and Thermal Load for Category 3 - Tuff 
Best-Fit Static-Fatigue Curve 
ANL-EBS-MD-000027 REV 03 S-46 September 2004 

Drift Degradation Analysis 
Figure S-44. Evolution of Damage Due to Strength Degradation and Thermal Load for Category 5 - Tuff 
Best-Fit Static-Fatigue Curve 
S3.4.3 Combined Seismic, Thermal, and Time-Dependent Effect in Lithophysal Units 
The effect of the preclosure seismic loading (110-4 probability of annual occurrence) was 
investigated for categories 2 and 5 of the tuff best-fit curve. An analysis of the combined effects 
of thermal and seismic loading is presented in Section 6.4.2.3. Note that because ground motion 
with 110-6 probability of annual occurrence results in complete drift collapse in lithophysal rock 
ANL-EBS-MD-000027 REV 03 S-47 September 2004 

Drift Degradation Analysis 
(see Section 6.4.2.2), it was not of particular interest to investigate the effect of that level of 
ground motion combined with thermally induced initial stresses and time-dependent strength 
degradation. Instead, a ground motion with 110-4 probability of annual occurrence was 
considered. The state of the rock mass when the effect of seismic ground motion is most adverse 
for drift stability was selected based on an elastic stress path with respect to the short-term yield 
surface. Under such conditions, the critical state was reached 80 years after waste emplacement, 
when the temperatures and the thermal stresses around the drift reach the maximum. When the 
time-dependent strength degradation is considered, the state when the maximum stresses are 
generated around the drift is not necessarily the critical one. The largest stresses occur relatively 
early during the regulatory period. Subsequently, the stresses decay gradually, returning to the 
state that existed prior to heating. At the same time, the strength of the rock mass monotonically 
decreases as a function of time, such that the weakest rock strength occurs at the end of the 
regulatory period (i.e., at year 10,000). In order to investigate the worst-case effects of seismic 
ground motion on drift stability, dynamic analyses were carried out for the model states at 80 and 
10,000 years after waste emplacement. 
The model geometry before and after the dynamic simulation is shown in Figures S-45 and S-46 
for seismic ground motion at 80 years after emplacement, and in Figures S-47 and S-48 for 
seismic ground motion at 10,000 years after emplacement. In each case, an additional rockfall is 
predicted due to the earthquake, which shakes down already damaged rock mass. This increase 
in the rockfall due to seismic loading is not significant in any of the cases, although it seems that 
there is more rockfall in the case of an earthquake at 10,000 years after waste emplacement. 
The effect of multiple seismic events on stability of the emplacement drifts in category 2 
lithophysal rock mass at different stages during the regulatory period was also investigated. 
Figure S-49 shows the model geometry after two identical 110-4 seismic events have shaken the 
emplacement drifts at 80 and 10,000 years of heating. These results should be compared with 
results shown in Figures S-45 and S-47 for a single seismic event in a rock mass of the same 
quality and age (80 and 10,000 respectively) after waste emplacement. The second event, 
although exactly the same ground motion, causes much less additional rockfall. In fact, after 
10,000 years of heating, the second event does not produce any additional rockfall. Some 
relatively small additional rockfall can be observed on the left side of the drip shield for a 
repetitive seismic event taking place 80 years after waste emplacement. The second earthquake 
shakes down a small volume of the loose rock that remained in the drift roof after the first 
earthquake. 
ANL-EBS-MD-000027 REV 03 S-48 September 2004 

Drift Degradation Analysis 
Figure S-45. Effect of 110-4 Ground Motion After 80 Years of Heating in Category 2 Contours of 
Displacement Magnitude (m) 
NOTE: There is a residual, rigid body translation of the model at the end of dynamic simulation because the entire 
seismogram was not simulated. 
Figure S-46. Effect of 110-4 Ground Motion After 80 Years of Heating in Category 5: Contours of 
Displacement Magnitude (m) 
ANL-EBS-MD-000027 REV 03 S-49 September 2004 

Drift Degradation Analysis 
NOTE: There is a residual, rigid body translation of the model at the end of dynamic simulation because the entire 
seismogram was not simulated. 
Figure S-47. Effect of 110-4 Ground Motion After 10,000 Years of Heating in Category 2: Contours of 
Displacement Magnitude (m) 
NOTE: There is a residual, rigid body translation of the model at the end of dynamic simulation because the entire 
seismogram was not simulated. 
Figure S-48. Effect of 110-4 Ground Motion After 10,000 Years of Heating in Category 5: Contours of 
Displacement Magnitude (m) 
ANL-EBS-MD-000027 REV 03 S-50 September 2004 

Drift Degradation Analysis 
NOTE: There is a residual, rigid body translation of the model at the end of dynamic simulation since the entire 
seismogram was not simulated. 
Figure S-49. Effect of Two Successive 110-4 Ground Motions in Category 2: Contours of Displacement 
Magnitude (m) 
S4. CONSIDERATION OF SPATIAL VARIABILTY OF ROCK MASS STRENGTH 
The lithophysal rockfall modeling presented in Section S3 considers a constant rock property 
category throughout the model. In reality, the lithophysal rock mass can contain multiple rock 
property categories within a 5 to 10 meter zone (see Section 7.3.2). The use of a constant rock 
property category throughout the rockfall model bounds the rockfall response since the poorest 
quality category (categories 1 and 2) will likely contain areas of higher quality rock, and 
therefore, the rockfall models for these categories will produce conservative (i.e., higher) 
predictions of drift damage and rockfall. Conversely, the highest quality category (category 5) 
will likely contain areas of poorer quality rock, and therefore, the rockfall model for this 
category may result in less damage and rockfall compared to actual conditions. A more realistic 
model of lithophysal rock mass conditions is described in this section, allowing for varied rock 
mass properties throughout the model. The results presented in this section supplement the 
analyses presented in Section S3 by providing a more realistic case for lithophysal drift 
degradation. 
It is considered that the volume fraction of the lithophysae (referred to as porosity) is the only 
factor that controls mechanical properties of the lithophysal rock mass. The other factors 
certainly have an effect (e.g. jointing), but the volume fraction of the lithophysae is the most 
important. Therefore, the consideration is reasonable, while it considerably simplifies the task of 
establishing a correlation between the actual conditions of the rock mass and the mechanical 
properties used in the model. The correlation between the porosity and lithophysal rock mass 
categories from Table E-10 was used in the analysis. 
The distribution of lithophysal porosity in the ECRB Cross-Drift is shown in Figure S-50. 
Spatial variation of porosity (developed in Appendix T) was simulated inside a 
50 m  50 m  40 m volume. The simulated porosity, shown in Figure S-51, varies between 
5 percent and 30 percent throughout the simulated region. The analysis was conducted using a 
ANL-EBS-MD-000027 REV 03 S-51 September 2004 

Drift Degradation Analysis 
two-dimensional model for three different cross-sections and locations of the drift center within 
the simulated volume. Normal to the cross-section plane is always in the direction of the y-axis. 
The coordinates of the drift center (relative to the coordinate system shown in Figure S-51) are: 
a) Section 1, x = 25 m, y = 5 m, z = 37.5 m; b) Section 2, x = 25 m, y = 10 m, z = 37.5 m; and c) 
Section 3, x = 25 m, y = 5 m, z = 25 m. Sections 1 and 2 are located in a region of the simulated 
volume with a large average porosity, while the third section is located in a region with a 
medium average porosity. The analysis has shown that there is no significant variability of the 
rockfall for different cross-sections throughout the simulated volume. Consequently, the use of a 
two-dimensional model is justified for the assessment of rockfall for a drift located in the 
lithophysal rock mass, accounting for actual variability of porosity and mechanical properties. 
The porosity is interpolated in the centers of zones and joints of the UDEC model. Using the 
relations between porosity and rock mass categories (Table E-10) and between the rock mass 
categories and UDEC micro-properties (Table 6-43), variable properties of the blocks (bulk and 
shear moduli) and the joints (normal and shear stiffness, cohesion and tensile strength) are 
generated. Variability of block bulk modulus for Section 1 is shown in Figure S-52. 
The results of the simulation for the thermal load combined with time-dependent strength 
degradation for Section 1 are shown in Figure S-53. The rockfall is very similar to the rockfall 
predicted for category 3, considering homogeneous rock mass properties, shown in Figure S-43. 
This is an expected result because the average properties for Section 1 are similar to category 3 
rock mass properties. 
0 
10 
20 
30 
40 
50 
60 
70li) 
0% 
liiili 
25-30 
Category 1 
20-25 
Category 2 
15-20 
Category 3 
10-15 
Category 4 
<10 
Category 5 
Lithophysa Porosty (%
Frequency 
10% 
20% 
30% 
40% 
50% 
60% 
70% 
80% 
90% 
100% 
Cumuatve Distrbuton 
Frequency 
Cumuatve % 
NOTE: Lithophysal porosity data are from ECRB Cross-Drift station 14+44 to 23+26 (Appendix O and Section O6.6; 
see Microsoft Excel file, Drift Deg AMR AF T-A-P Fit.xls, worksheet Volume Percent - Stats, which can 
accessed through the TDMS using DTN: MO0408MWDDDMIO.002). 
Figure S-50. Distribution of Lithophysal Porosity in the ECRB Cross-Drift 
ANL-EBS-MD-000027 REV 03 S-52 September 2004 

Drift Degradation Analysis 
45 
40 
35 
z 
30 
25 
20 
15 
10 
5 
5 1015202530354045 
y= 0m plane 
yX 
45 
40 
35 
30 
30 
25
45 
29 
28 
27 
26 20
40 
25 
24 15 
23 
22 
35 
21 10 
20 
19 
30 
25 
18 5 
17 
16 
5 1015202530354045 
20 
15 
14 
13 
15 
y= 20m plane 
12 
11 
10
10 
9 
8 
7
5 
6 45 
5 
0 5 10152025303540 
X= 23.75m p
40 
lane 
35 
30 
25 
20 
15 
10 
5 
5 1015202530354045 
y= 40m plane 
Figure S-51. Porosity Contours in Cross-Sections Through the 3D Simulated Porosity Field 
ANL-EBS-MD-000027 REV 03 S-53 September 2004 

Drift Degradation Analysis 
Figure S-52. Distribution of Block Bulk Modulus for Section 1 
ANL-EBS-MD-000027 REV 03 S-54 September 2004 

Drift Degradation Analysis 
Figure S-53. Evolution of Damage Due to Strength Degradation and Thermal Load for Spatially Variable 
Properties, Section 1 - Tuff Best-Fit Static-Fatigue Curve 
S5. VALIDATION OF THE MODELING APPROACH 
As one means of validating the PFC stress corrosion modeling approach for estimating long-term 
damage formation surrounding the ECRB Cross-Drift, two independent technical reviews were 
conducted using experts in the field of rock mechanics testing (see Section 7.5.2.3). 
ANL-EBS-MD-000027 REV 03 S-55 September 2004 

Drift Degradation Analysis 
The first independent technical review is provided by Dr. Jaak Daemen, Professor of Mining 
Engineering and Department Chair at the University of Nevada, Reno. Dr. Daemen received his 
Ph.D. in Geological Engineering from the University of Minnesota where his research involved 
development of the analytical and numerical solutions for ground support  rock mass 
interaction. He worked for DuPont in development of ground support products prior to joining 
the University of Arizona, Department of Geological Engineering. Dr. Daemen's current 
research involves time-dependent testing of joints and intact tuff from the Yucca Mountain 
nuclear waste disposal site. 
The second independent technical review is provided by Mr. Ronald Price and Dr. Randolph 
Martin. Mr. Price is a Senior Member of Technical Staff at Sandia National Laboratories. He 
has a M.S. in Geology from the Center for Tectonophysics at Texas A&M University, where his 
thesis research was entitled, Effects of Anhydrite and Pressure on the Mechanical Behavior of 
Synthetic Rocksalt. Since his arrival at Sandia in 1980, Mr. Price has planned, carried out and 
published results from laboratory studies on many different rock types and for many 
applications. He has, however, had a central focus on the mechanical properties of tuffs, with 
special emphasis on Yucca Mountain tuffs, for over 22 years. His depth of knowledge of tuff 
rheological properties is particularly valuable for the present application. Dr. Martin is the 
President of and Principal Scientist at New England Research, Inc. in White River Junction, 
Vermont. He has a Ph.D. from MIT, where his thesis research was entitled, Time-Dependent 
Crack Growth in Quartz and Its Application to the Creep of Rocks. Dr. Martin has a wide range 
of experience managing and performing both field and laboratory rock mechanics projects, 
including designing/building high-pressure equipment, testing rocks at elevated pressures and 
temperatures, and analyzing data with various (e.g. empirical, analytical, and numerical) 
techniques. His seminal work in the area of static fatigue makes him particularly valuable in the 
review of this material. 
S5.1 OBJECTIVE AND SCOPE OF THE INDEPENDENT TECHNICAL REVIEW 
The technical review is limited to documentation on the validity of the PFC stress corrosion 
modeling approach applied to the rockfall models (i.e., draft documentation of this appendix). 
While the time of failure presented in the damage curves (Figures S-28 and S-29) is based on 
laboratory measurements, the shape of the curve as a function of time is determined from the 
PFC stress corrosion model, and has not been validated by test data. To assess the validity of the 
PFC stress corrosion model, the technical review addresses the following items: 
 Provide an assessment of the bi-linear shapes of these damage curves to determine if they 
are reasonable and consistent with observations and measurements of static fatigue failure 
of rock specimens. 
 Provide a discussion of the validity of the static-fatigue curves and the damage curves 
used as input to the UDEC analyses (Figures S-27 through S-29). 
 Provide a discussion of the validity of the results (i.e., the predictions of drift degradation 
as a function of time-dependent strength degradation) produced by the UDEC rockfall 
model (Section S3.4.1). 
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Drift Degradation Analysis 
S5.2 REVIEW CRITERIA 
The following criteria are used when reviewing the documentation on the validity of the PFC 
stress corrosion modeling approach: 
 Is this information presented accurately using applicable methods, assumptions, and 
recognized techniques? 
 Does existing model documentation provide adequate confidence required by the models 
relative importance to the potential performance of the repository system to support model 
validation for its intended purpose and stated limitations? 
S5.3 INDEPENDENT TECHNICAL REVIEW #1 
The review from Dr. Jaak Daemen is provided in this section. 
This appendix presents a powerful analysis of potential time-dependent drift 
deterioration. The analysis is based on a convincing fundamental model of rock 
strength deterioration over time. The results provide considerable insight into 
what might be expected with regard to time-dependent drift deterioration. 
While the strategy developed in this appendix is very convincing, the significance 
of specific results is less so, because of the lack of experimental input data, as 
recognized by the authors. 
The shape of the bi-linear damage curves is eminently reasonable. However, the 
presentation of the sensitivity analysis (Section S3.2) and its implementation and 
results (Figure S-31) is exceedingly brief. It would help if this discussion could 
be expanded, could provide a bit more detail. The most convincing support for 
the damage curves is the calibration of the results based on the ESF and ECRB 
observations (Section S3.4.1). 
The results are eminently reasonable, and provide significant insight into the 
likely drift degradation mechanisms and time frame. Although, as the report 
recognizes, there is considerable input data uncertainty, the sensitivity analyses 
performed give considerable confidence that the results are good predictors of 
likely drift degradation. 
The information presented appears accurate, and the analysis uses applicable 
models, assumptions, and recognized techniques. 
The model documentation provides adequate confidence about the potential 
repository system component performance, and will support model validation. 
Limitations associated with the model, in particular with regard to the paucity of 
experimental input data, are clearly identified. 
ANL-EBS-MD-000027 REV 03 S-57 September 2004 

Drift Degradation Analysis 
S5.4 INDEPENDENT TECHNICAL REVIEW #2 
The review from Mr. Ronald Price and Dr. Randolph Martin is provided in this section. 
This manuscript contains two sections. First, analysis of the time-dependent 
behavior of intact rocks on specimens using the PFC and second, a model 
incorporating the time-dependent strength of tuff into long-term strength of the 
roof and rock fall in the repository. 
In general, the paper presents a good representation of the behavior of intact rock 
samples and how that might be used to predict long-term rock properties 
especially strength. The approach used in these models has been developed on 
other projects. Several modifications were made to the models to accommodate 
the strong porosity dependence of rock properties measured at the laboratory 
scale. 
The PFC is used to model the time-dependent strain (creep) and the 
time-dependent strength (static fatigue) observed in laboratory measurements. 
The flexibility of the PFC model allows incorporation of (1) large-scale porosity 
in the sample and (2) time-dependent properties in the matrix bonds to adequately 
represent time-dependent processes in the bulk rock. 
The approach used here has been successfully applied in Canada for granitic 
rocks. The model is calibrated with available rock properties measurements both 
in situ and in the laboratory. By tying the model to existing data, they were able 
to represent the behavior of the material and in particular its time-dependent 
properties reasonably well. 
The PFC is a representation of the gross behavior of rock and does not provide 
insight into the physical processes leading to deformation or failure in the tuffs. 
However, in most codes this is the case and probably should not be considered as 
a serious defect in the model. What is needed to fully validate the model is 
additional in situ and laboratory data to check the predictive capability of the 
PFC. 
The time-dependent deformation and failure results of the particle flow code are 
incorporated into the analysis of roof collapse. The approach that they used is 
clearly presented and is a reasonable for the long-term performance of the roof in 
the repository. 
Again, as with the PFC, as additional measurements on time-dependent behavior 
and in situ strength become available, these data will be incorporated into the 
model to further refine the predictions. 
Another suggestion is that they consider referring to some of the historical data on 
the long-term performance of existing tunnels. There is sufficient experience over 
the years on numerous mines in a variety of rocks that have been subjected to 
elevated temperatures (especially deep mines in South Africa). Sufficient 
ANL-EBS-MD-000027 REV 03 S-58 September 2004 

Drift Degradation Analysis 
measurements have been made in some cases so that time-dependent changes can 
be used to bound the parameters in the model. No reference has been made as yet 
to such historical data in the report. It seems prudent that in order to demonstrate 
the models are valid and that the long-term predictions are defensible, these must 
be considered. 
S6. CONCLUSIONS 
Time-dependent drift stability for unsupported emplacement drifts is predicted. Time-dependent 
strength degradation under an in-situ stress state was combined with thermal or seismic loading 
conditions expected during the regulatory period. Predictions are based on two sets of data: a) 
test results obtained for Lac du Bonnet granite, and b) test results obtained for nonlithophysal 
tuff. 
The effect of lithophysae on time-to-failure is investigated using the PFC stress corrosion model. 
The time-dependent parameters of the model were selected to match a straight-line fit to the 
Lac du Bonnet granite static-fatigue curve. Voids (corresponding to lithophysal porosity) were 
then generated in the synthetic material, which was numerically tested again to generate 
static-fatigue curves for lithophysal rock with different percentages of lithophysal porosity. The 
analysis showed that lithophysal porosity does affect the static-fatigue curves. As a function of 
porosity, the straight-line fits are offset slightly relative to one another, but have the same slope. 
The variability is not significant and for the purposes of this application, considering 
uncertainties in the analysis, it was justified to consider that lithophysal porosity does not affect 
the static-fatigue curve when the driving stress is normalized with the short-term strength of the 
rock mass. Considering the stress in the absolute form, the lithophysal porosity has a significant 
effect on the time-to-failure. 
The evolution of damage due to strength degradation for different levels of driving-stress ratio 
was studied using the PFC stress corrosion model. At different stages during the numerical 
simulation of static-fatigue tests, samples were loaded in compression (at 0.1 MPa confinement) 
to failure. These numerical tests indicate that damage increases gradually, at a very slow rate, 
until a relatively short time before time-to-failure for a given driving stress, when damage 
quickly increases, resulting in the sample failure. 
Analysis of drift stability was carried out using the UDEC model in which the rock mass was 
represented as an assembly of Voronoi blocks. The cohesive strength of the synthetic material 
decays as a function of time according to the input static-fatigue lines and curves of damage 
evolution under the different levels of sustained load as a function of time. Predictions of the 
rockfall are not sensitive to variation of the damage rate (before the time-to-failure) within the 
range of rates predicted by the PFC stress corrosion model. The most important model 
parameter for rockfall predictions is time-to-failure as a function of the driving stress. 
Model prediction for different categories (1 through 5) of rock mass quality, combined with 
different static-fatigue lines were compared with observations from the ESF and ECRB. The 
drifts have been open between 5 and 12 years and no indication of their time-dependent 
deterioration has been observed yet (note that the drifts are supported with bolts and wire mesh 
in the roof only). Comparison of the model predictions of drift behavior after 5 and 10 years 
ANL-EBS-MD-000027 REV 03 S-59 September 2004 

Drift Degradation Analysis 
with underground observation led to the following conclusions: a) rock mass category 1 for tuff 
as a homogeneous medium around the drifts underestimates the strength of the poorest quality 
lithophysal rock mass, b) Lac du Bonnet static-fatigue lines are inconsistent with tunnel 
behavior, leading to some rockfall after 10 years for all rock mass categories, and c) the poorest 
quality rock mass can be represented as rock mass category 2 with the tuff best-fit static-fatigue 
curve. It appears that the tuff best-fit static-fatigue lines are in the best agreement with both 
observations of tunnel performance and the results from short-term tests on the lithophysal rock 
mass. Further analysis was carried out using the tuff best-fit static-fatigue line only. 
The best-fit tuff static fatigue line implies that a driving-stress ratio of approximately 0.60 results 
in approximately 20,000 years time-to-failure (see the tuff [Pc = 0] best-fit curve in Figure S-26), 
indicating there will be an approximate 40 percent cohesive strength reduction in 20,000 years. 
The drift profile for a 40 percent cohesive strength reduction case (i.e., 60 percent cohesive 
strength) was initially determined as shown in Figure 6-171c for category 1. Note 
that Figure 6-171c is similar to the category 1 profile in Figure S-41. Considering only 
time-dependent strength degradation, it is clear that the 60 percent through 100 percent strength 
reduction cases (Figures 6-171d, 6-171e, and 6-171f) do not occur within the first 20,000 years 
of the postclosure period. 
A combination of the thermally induced stresses with time-dependent strength degradation 
results in more rockfall than predicted for each of the loading conditions independently. Most 
rockfall, which is a result of deterioration of the walls, occurs for category 2. However, this poor 
quality rock accounts for only a small percentage (i.e., approximately 10 percent as shown in 
Figure S-50) of the total lithophysal rock mass in the emplacement drifts. Also, the combination 
of thermally induced stresses with time-dependent strength degradation does not increase 
rockfall significantly over a period of 10,000 years, as shown by comparing Figures S-38 and 
S-42. Note that while thermal stresses were not analyzed for the period from 10,000 years to 
20,000 years, it can be inferred that the thermal impacts will be minimal during this period, since 
the temperature during this period has returned to near ambient, as shown in Section 6.2. 
Therefore, for the nominal case (i.e., considering thermal and time-dependent effects, but 
excluding seismic effects), the expected drift profiles after 20,000 years are adequately 
represented by Figures S-41 through S-44. As rock mass quality increases, there is less rockfall 
from the walls and more rockfall from the drift roof (Figure S-44). Better quality rock mass is 
stiffer, resulting in larger thermal stresses in the roof. 
Postclosure seismic ground motion with a 110-6 probability of annual occurrence results in 
complete drift collapse, with the geometry of the collapsed drift unchanged from the previous 
results (see Section 6.4.2.2). To analyze the coupled effects of seismic load, thermal load, and 
time-dependent strength degradation, seismic loading by a preclosure ground motion with a 
110-4 probability of annual occurrence was considered at two stages during the regulatory 
period (accounting for damage and rockfall due to thermal load history and time-dependent 
strength degradation): 80 years after waste emplacement, when thermally-induced stresses are 
maximum and 10,000 years after waste emplacement, which is the worst-case condition (during 
the regulatory period) of time-dependent strength degradation. Preclosure seismic ground 
motion causes an additional, but not significant, rockfall, which comes as a result of shaking 
down already loose, broken ground. 
ANL-EBS-MD-000027 REV 03 S-60 September 2004 

Drift Degradation Analysis 
Damage to the host rock is not significantly accumulating from multiple 110-4 probability of 
annual occurrence ground motions. That is, the 110-4 seismic event is shaking loose rock 
fragments that have already failed by strength degradation and thermal stress; no new fractures 
and failures are caused by this low amplitude ground motion, either at 80 years when thermal 
stress is at its peak or at 10,000 years, when long-term strength degradation has occurred. Lack 
of new damage is also anticipated for more probable seismic events, such as 510-4 or 110-3 
probability of annual occurrence ground motions, because they have smaller amplitudes than the 
110-4 probability of annual occurrence ground motion. 
Most of the analyses were carried out for different rock mass categories, but considering 
homogeneous properties throughout the model. Mechanical properties of the lithophysal rock 
mass are variable as a function of the position within the lithophysal unit. There is concern that 
homogeneous models do not properly represent the mechanical behavior of a heterogeneous rock 
mass. A mechanical model (with variable properties) of drift stability was generated 
corresponding to porosity fields obtained from the cross-sections through a three-dimensional 
model of the lithophysal porosity, which is considered to be the factor controlling the quality of 
the rock mass. There is no significant variability in rockfall predictions from one cross-section 
to another. Also, the rockfall predictions are very similar to those obtained for rock mass 
category 3. 
The presented analysis deals with time-dependent drift degradation explicitly relating the 
rockfall predictions to a specific time. The analysis uses the existing information about the 
time-dependent behavior of tuff (static-fatigue tests), and behavior of the existing drifts (ESF and 
ECRB) over time. However, there is still a significant level of uncertainty in the predictions, 
because they are obtained by extrapolation of the test results and observations on short 
time-scales (maximum 10 years) to very long time-scales (10,000 years). 
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INTENTIONALLY LEFT BLANK 
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APPENDIX T 
SIMULATION OF LITHOPHYSAL POROSITY SPATIAL VARIATION 
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SIMULATION OF LITHOPHYSAL 
POROSITY SPATIAL VARIATION 
T1. INTRODUCTION 
To assist in modeling the spatial variability of mechanical properties in two and three dimensions 
for areas and volumes surrounding tunnels, a simple method of projecting the two-dimensional 
distribution of lithophysal cavity porosity has been developed. The calculation described in this 
appendix is for rock in the lower lithophysal zone of the Topopah Spring Tuff (Tptpll), and it is 
based on the data from the ECRB Cross-Drift (see Appendix O). The ECRB Cross-Drift data 
represents one of the best and detailed distributions of lithophysal cavity porosity available, so 
these data are projected to a vertical simulated cross section that is perpendicular to the ECRB 
Cross-Drift. Once the spatial variation of the lithophysal cavity porosity has been determined for 
areas and volumes surrounding the tunnels, correlation equations for the porosity to unconfined 
compressive strength and Youngs Modulus can be used distribute the elastic properties and 
material strength (see Appendix E, Table E-10). 
Four steps are used for projecting and distributing lithophysal cavity porosity in a tunnel (such as 
the ECRB Cross-Drift) into a two-dimensional cross section that is perpendicular to the tunnel. 
A simplified summary of these four steps is described below and in Figure T-1, with a detailed 
explanation (with specific examples) provided in Section T6. 
 Step 1. Lithophysal cavity porosity values are projected along the apparent dip of the 
lithostratigraphic unit to a vertical line that is perpendicular to the tunnel (Figure T-1a), 
and this vertical line forms the center of the cross section. For simplicity, only the 
values that project to the top and bottom of the vertical line are depicted (Figure T-1a), 
but each point along the tunnel can be projected along the same apparent dip. 
 Step 2. The vertical line is divided into a series of sections or horizons, and these 
sections are projected along the apparent dip to form stratigraphically equivalent 
windows along the tunnel (Figure T-1b). 
 Step 3. The distribution of values and descriptive statistics, for example mean and 
standard deviation, are determined for each window, and these statistics are imparted 
to the correlative section on the vertical line (Figure T-1c). 
 Step 4. Descriptive statistics for each section on the vertical line are propagated along a 
horizon across the cross section (Figure T-1d). 
T2. INPUT DATA 
The data required for the projection of lithophysal cavity porosity in a vertical cross section 
include (1) the distribution of the lithophysal cavity porosity along the ECRB Cross-Drift 
(Appendix O) and (2) the strike and dip of the top of the Tptpll in the ECRB Cross-Drift 
(Mongano et al. 1999 [DIRS 149850], Table 1). 
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Drift Degradation Analysis 
j)(a) 
Percent cavities 
Apparent 
Dip 
Proection along 
Apparent Dip 
Tunnel Profile 
Vertical Line 
(VL
Distance along tunnel 
VL(b) 
Percent cavitiesSection 1 
Section 2 Window1 
Window2 
Distance along tunnel 
VL Sw2(c) 
Percent cavities 
Sw1 
Ss1 
Ss2 
Ss1 = Sw1 
Ss2 = Sw2 
Distance along tunnel 
VLSs1 
Ss2 
(d) 
Distance away from tunnel 
Horizons Tunnel 
Ss1 
Ss2 
Figure T-1. Simplified Steps for Projecting and Distributing Lithophysal Cavity Porosity Values in a 
Tunnel Into a Two-Dimensional Cross Section 
T3. SOFTWARE USED IN THE CALCULATIONS 
The input data, intermediate calculations, and results of the assessment of the distribution of 
lithophysal cavity porosity are stored and implemented in the Microsoft Excel file, Lithophysal 
projection to vertical plane.xls (DTN: MO0408MWDDDMIO.002). The transfers of values, 
calculations, logic functions, and descriptive statistics are done with standard functions in Excel. 
There are three small macros embedded in the Excel file, named Prop_Distribute, 
Contour_Text, and Contour_Fill. These macros are exempt from the qualification 
ANL-EBS-MD-000027 REV 03 T-2 September 2004 

Drift Degradation Analysis 
requirements of LP-SI.11Q-BSC, Software Management, since they are used solely for visual 
display of data: 
A. The Prop_Distribute macro is an automated copy and paste function that takes the 
distributed values in a large (10184 cell) 5 m window table and makes a small 
(1029 cell) compacted table of the values. 
B. The Contour_Text and Contour_Fill macros are basically the same and they 
simply change the format of the values or cells (but not the values themselves) in the 
50200 and 2080 cell tables. The difference between these two macros is that one 
(Contour_Text) colors the text (i.e., values), and the other (Contour_Fill) changes 
the fill color of the cell and the color of the text (i.e., values). 
C. Confirmation that the macros are operating correctly can be made with simple visual 
comparisons of the large and small tables for the Prop_Distribute macro, and the 
input data table with the 50200 and 2080 cell tables for the Contour_Text and 
Contour_Fill macros. 
T4. GEOMETRIC RELATIONS AND CONDITIONS IN THE CALCULATION 
Calculations of the distributed lithophysal cavity porosity in a vertical plane are based on six 
fundamental lithostratigraphic and geometric relations and conditions: 
A. Lithostratigraphic zones and subzones of the Topopah Spring Tuff are stratiform and 
are traceable across the repository area. However, some subzones might not occur 
across the entire repository area. 
B. The ECRB Cross-Drift transects the Tptpll as a shallowly inclined tunnel. Therefore, 
lithophysal cavity data represents vertical (and to some amount horizontal) variations 
in the lithostratigraphic features. 
C. Lateral continuity of variations in lithophysal cavity porosity in the tunnel is projected 
along the apparent dip of the Tptpll (and lithostratigraphic features) to a vertical line 
that is perpendicular to the tunnel. 
D. The vertical line is divided into 5 m tall horizons, and these horizons are projected 
along the apparent dip to the tunnel to form a series of windows along the tunnel. 
E. Each 5 m horizon along the vertical line contains the potential variability in porosity in 
their respective window along the tunnel. 
F. The statistical variation in porosity in each 5 m tall horizon is projected away from the 
tunnel along a vertical cross section that is perpendicular to the tunnel. 
T5. DETERMINATION OF THE APPARENT DIPS FOR INPUT 
The three-dimensional orientation of an inclined plane can be defined by a strike and dip, but an 
apparent dip is formed where the inclined plane intersects vertical planes along a section that is 
ANL-EBS-MD-000027 REV 03 T-3 September 2004 

Drift Degradation Analysis 
not at a right angle to the strike of the vertical plane. The strike is the angle from north of a 
horizontal line in the inclined plane, and the dip is the angle from horizontal measured in a 
vertical plane that is 90 to the strike of the inclined plane. An apparent dip is the angle from the 
horizontal in a vertical plane of a line formed by the intersection of an inclined plane with the 
vertical plane. 
An example of these geometric relations is illustrated in Figure T-2 with three planes. The 
inclined plane is the top contact of the Tptpll in the ECRB Cross-Drift and has a strike of 270 
(Mongano et al. 1999 [DIRS 149850], Table 1). The true dip is measured in a plane 
perpendicular to the strike of the inclined plane, and is illustrated with the 7 dip. The ECRB 
Cross-Drift is contained in a vertical plane that has a strike of 229. This strike is used because it 
is in the direction of the heading of the tunnel and in the area of the lithostratigraphic contact is 
in the direction of the inclination or plunge of the tunnel. A cross section perpendicular to the 
ECRB Cross-Drift forms a second vertical plane with a strike of 319. The apparent dip of the 
lithophysal zone contact is 4.6 to the northeast (NE) in the plane of the cross drift and 5.3 to 
the northwest (NW) in the cross section perpendicular to the ECRB Cross-Drift. If another strike 
and dip were used, then the apparent dips will differ. For example, the top of the Tptpll in the 
ECRB Cross-Drift in the Geologic Framework Model (BSC 2004 [DIRS 170029]) has a strike 
and dip of 345 and 5.8, respectively. The apparent dips are 5.2 NE in the plane of the ECRB 
Cross-Drift and 2.5 NW in the plane perpendicular to the ECRB Cross-Drift. 
AziCross section perpendicular to ECRB Cross-Drift 
Top contact of Tptpll 
muth of ECRB Cross-Drift 
NOTE: The orientation of the Tptpll contact and the ECRB Cross-Drift is based on Mongano et al. (1999 
[DIRS 149850]). The ECRB Cross-Drift is considered to be horizontal. 
Figure T-2. Geometric Relations of Strike and Dip and the Apparent Dips in Cross Sections Parallel and 
Perpendicular to the ECRB Cross-Drift 
T6. DISTRIBUTION OF LITHOPHYSAL CAVITY POROSITY IN THE ECRB 
CROSS-DRIFT AND SIMULATED VERTICAL CROSS SECTION 
The stratiform geometry of the zones in the Topopah Spring Tuff occur throughout the repository 
area (Buesch et al. 1996 [DIRS 100106] and Buesch et al. 1996 [DIRS 101202], BSC 2004 
[DIRS 170029]) as do many of the subzones such as the subzones of the Tptpmn (Buesch et al. 
1996 [DIRS 100106], Buesch and Spengler 1998 [DIRS 101433]), although some subzones 
ANL-EBS-MD-000027 REV 03 T-4 September 2004 

Drift Degradation Analysis 
might not occur across the entire repository area (Buesch and Spengler 1998 [DIRS 101433]). 
Variations in the orientation of lithostratigraphic contacts (Mongano et al. 1999 [DIRS 149850]) 
and the abundance (and percent) of lithostratigraphic features in the lower lithophysal zone, 
including lithophysal cavity porosity (Appendix O), are consistent with the ECRB Cross-Drift 
transecting a dipping lithostratigraphic section (Figure T-2). The lower lithophysal zone has not 
been divided into subzones, but the variations in features including the lithophysal cavity 
porosity are consistent with identification of 5 to 12 subzones (Figure T-3). 
The lateral continuity of lithostratigraphic features, and the projection of these features along the 
apparent dip in the ECRB Cross-Drift, forms the principal component of creating a geologically 
informed calculation of the distribution of lithophysal cavity porosity in a vertical plane. 
Identification of a 50 m tall, vertical line (section) perpendicular to the tunnel is the first step in 
creation of the 50200 m cross section (Figure T-3). Based on the apparent dip, the top and 
bottom of the vertical section can represent rocks from several hundred meters away from the 
centerline of the section. For example, with a 5 apparent dip, the equivalent rocks at the top and 
bottom of the vertical section are 286 m from the section (Figure T-3). With an apparent dip of 
4.6 (Figure T-2), the projection for the top and bottom of vertical section is 311 m. This 
projection distance is consistent with the overall stratiform characteristics of the 
lithostratigraphic section. 
The second step in creation of a cross section is to divide the vertical section into a series of 5 m 
tall sections or horizons. The projection along the apparent dip of the 5 m horizons result in a 
series of windows along the tunnel, and the position and length of each window results from 
the apparent dip. For example, with a 5 apparent dip, the equivalent window for the top 5 m 
horizon is 57 m long (Figure T-3). Each window contains unique variations in the number of 
measurements and the distribution of lithophysal cavity porosity values (Table T-1 and 
Figure T-4). 
NOTE: The simulated cross section is at 1800 m with an apparent dip of 5 for the stratiform features. 
Figure T-3. Variation in Lithophysal Cavity Porosity Along the ECRB Cross-Drift and the Geometric 
Relations of Calculation Components 
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Drift Degradation Analysis 
Table T-1. Windows Containing Unique Variations of Lithophysal Cavity Porosity Values 
Station (m) Cavity fitted 0-5 Window 5-10 Window 10-15 Window 15-20 Window 
1445 2.5 null null null null 
1450 3.8 3.8 null null null 
1455 4.7 4.7 null null null 
1460 5.7 5.7 null null null 
1465 7.6 7.6 null null null 
1470 7.4 7.4 null null null 
1475 8.2 8.2 null null null 
1480 6.0 6.0 null null null 
1485 7.9 7.9 null null null 
1490 10.6 10.6 null null null 
1495 14.4 14.4 null null null 
1500 15.3 15.3 null null null 
1505 19.4 19.4 null null null 
1510 17.7 null 17.7 null null 
1515 17.0 null 17.0 null null 
1520 13.2 null 13.2 null null 
1525 13.6 null 13.6 null null 
1530 12.1 null 12.1 null null 
1535 10.2 null 10.2 null null 
1540 8.8 null 8.8 null null 
1545 11.0 null 11.0 null null 
1550 12.2 null 12.2 null null 
1552.8 12.2 null 12.2 null null 
1555 13.4 null 13.4 null null 
1560 12.0 null 12.0 null null 
1565 11.0 null 11.0 null null 
1570 11.0 null null 11.0 null 
1575 17.2 null null 17.2 null 
1580 21.0 null null 21.0 null 
1585 25.6 null null 25.6 null 
1590 22.1 null null 22.1 null 
1595 26.5 null null 26.5 null 
1600 26.9 null null 26.9 null 
1605 29.2 null null 29.2 null 
1610 24.6 null null 24.6 null 
1615 19.3 null null 19.3 null 
1620 19.0 null null 19.0 null 
1625 17.4 null null 17.4 null 
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Drift Degradation Analysis 
Table T-1. Windows Containing Unique Variations of Lithophysal Cavity Porosity Values (Continued) 
Station (m) Cavity fitted 0-5 Window 5-10 Window 10-15 Window 15-20 Window 
1630 20.1 null null 20.1 null 
1635 17.0 null null null 17.0 
1640 18.8 null null null 18.8 
NOTE: This table shows a portion of the lithophysal cavity porosity input data that are divided into windows 
representing 5 m tall horizons in the simulated cross section. The Cavity (fitted) column provides 
adjusted mapped lithophysal porosity values as described in Appendix O (Section O5). Porosity 
values for each window are depicted in Figure T-4. Data in the Station (m) and Cavity (fitted) 
columns are from Appendix O (Section O6.6; see Microsoft Excel file, Drift Deg AMR AF T-A-P Fit.xls, 
worksheet Volume Percent -Stats, which can accessed through the TDMS using 
DTN: MO0408MWDDDMIO.002). These data are for a calculation with a centerline of the simulated 
cross section at 1756 m and an apparent dip of 4.6. 
lities iili0 
5 
10 
15 
20 
25 
30 
ii33) 
iiiiiiiiiLithophysa Cavn Smuated Secton 
1450 1550 1650 1750 1850 1950 2050 2150 2250 2350 
Staton (m) 
Porosty (cm/cm0-5 w ndow 
5-10 w indow 
10-15 w ndow 
15-20 w ndow 
20-25 w ndow 
25-30 w ndow 
30-35 w ndow 
35-40 w ndow 
40-45 w ndow 
45-50 w ndow 
Simulated section 
NOTE: Apparent Dip of 4.6, and 10 Windows. 
Figure T-4. Lithophysal Cavity Porosity in the Lower Lithophysal Zone of the ECRB Cross-Drift with the 
Centerline of the Simulated Cross Section at 1756 m 
The third step in creation of a simulated cross section is to distribute the descriptive statistics of 
the lithophysal cavity porosity in each window in the associated 5 m tall horizon. The statistical 
variation in porosity in each horizon is represented by sampling the actual porosity values in the 
respective window. Two methods using standard Excel functions have been used for this 
distribution; one function is Choose where the values in each window are randomly selected, 
and the other approach uses the random number generator in the analysis tool. For example, the 
first three 5 m horizons (0-5, 5-10, and 10-15 windows) in Table T-1 are depicted as Horizons 
0, 5, and 10 and Y positions 1 to 15, respectively, in Table T-2 and T-3. Comparison of 
values in Table T-1 and parts of Table T-2 and T-3 indicate the same values occur in the tables. 
ANL-EBS-MD-000027 REV 03 T-7 September 2004 

Drift Degradation Analysis 
Table T-2. Display of Part of the 50200 Cell Table with Descriptive Statistics for Calculation of 
Lithophysal Cavity Porosity in a 50200 m Simulated Cross Section with the Centerline 
Station 17+56 
Table of porosity values (1x1 m grid) 
Horizon Cell Y\X 1 2 3 4 5 6 7 8 9 10 
0 1 7.6 4.7 19.4 7.6 8.2 8.2 10.6 7.6 7.9 3.8 
0 2 6.0 7.4 8.2 19.4 7.9 10.6 14.4 7.9 15.3 7.9 
0 3 6.0 15.3 15.3 7.9 7.4 6.0 4.7 3.8 15.3 7.6 
0 4 10.6 10.6 10.6 7.9 3.8 3.8 19.4 7.9 7.6 7.6 
0 5 8.2 15.3 7.9 10.6 5.7 8.2 7.4 6.0 7.9 7.6 
5 6 13.2 11.0 17.7 11.0 17.7 10.2 12.2 12.1 12.2 12.2 
5 7 11.0 12.1 12.2 10.2 12.2 8.8 12.2 11.0 12.2 12.0 
5 8 12.2 13.6 12.0 12.2 11.0 8.8 12.1 12.2 11.0 12.0 
5 9 17.7 13.6 10.2 17.0 10.2 17.0 8.8 11.0 12.2 10.2 
5 10 12.2 12.2 12.1 11.0 12.2 10.2 13.4 12.2 13.2 17.7 
10 11 26.5 26.9 22.1 25.6 19.0 21.0 17.2 26.9 17.2 26.9 
10 12 11.0 26.5 24.6 26.9 19.0 29.2 19.0 21.0 17.2 19.0 
10 13 24.6 17.4 26.9 19.0 19.0 19.0 19.3 29.2 25.6 17.4 
10 14 17.4 26.5 17.2 17.2 24.6 21.0 26.9 26.5 20.1 26.9 
10 15 22.1 17.2 19.0 17.4 26.9 26.9 21.0 11.0 17.2 21.0 
15 16 18.8 16.5 13.6 20.5 20.5 22.9 21.4 20.6 16.5 20.6 
15 17 16.8 15.5 22.9 20.5 16.5 17.0 13.6 19.1 13.6 17.0 
15 18 20.6 19.3 15.5 17.0 17.0 19.3 20.6 19.1 16.8 17.0 
15 19 20.5 13.6 23.4 16.8 23.4 16.8 20.6 22.9 15.5 20.5 
15 20 23.4 21.4 19.3 15.5 16.8 21.4 20.5 17.0 21.4 17.0 
20 21 10.7 15.5 13.0 15.5 11.0 15.3 15.3 15.3 12.8 15.3 
20 22 13.0 14.5 17.3 11.0 11.7 13.0 17.3 14.5 10.6 10.6 
20 23 15.5 15.3 11.7 15.3 14.2 14.5 10.6 14.5 10.6 11.0 
20 24 15.3 14.5 15.5 13.0 15.5 15.3 11.7 14.5 13.0 10.7 
20 25 10.7 10.6 11.0 15.5 11.0 14.5 15.3 11.0 15.3 14.5 
25 26 16.9 24.5 17.3 20.1 18.1 15.5 20.1 18.1 13.8 13.8 
25 27 18.1 25.6 14.5 17.3 18.1 20.1 21.1 17.3 14.5 14.5 
25 28 17.3 15.5 18.8 18.1 17.3 21.1 17.3 18.8 17.3 18.1 
25 29 20.1 20.1 18.1 24.5 18.8 21.1 18.1 13.8 18.1 21.1 
25 30 18.1 18.1 15.5 18.1 13.8 18.1 14.5 24.5 18.1 21.1 
30 31 12.7 13.5 8.5 12.7 13.5 8.5 8.5 12.7 11.6 10.0 
30 32 8.1 11.8 10.8 13.9 13.9 13.5 13.9 7.8 8.1 8.5 
30 33 9.7 12.7 9.7 9.7 10.8 10.0 11.8 13.9 9.7 11.6 
ANL-EBS-MD-000027 REV 03 T-8 September 2004 

Drift Degradation Analysis 
Table T-2. Display of Part of the 50200 Cell Table with Descriptive Statistics for Calculation of 
Lithophysal Cavity Porosity in a 50200 m Simulated Cross Section with the Centerline 
Station 17+56 (Continued) 
Table of porosity values (1x1 m grid) 
Horizon Cell Y\X 1 2 3 4 5 6 7 8 9 10 
30 34 13.5 10.0 11.8 13.6 13.6 7.8 13.6 13.9 11.6 11.8 
30 35 7.8 10.0 10.8 13.6 10.0 8.5 13.6 7.8 10.8 8.5 
35 36 12.3 19.1 21.3 12.3 17.8 12.3 13.9 15.2 5.7 21.3 
35 37 15.2 5.7 12.3 16.6 13.9 12.3 14.4 5.7 16.6 17.8 
35 38 19.1 5.7 5.7 19.1 11.6 15.2 14.4 18.0 18.0 18.0 
35 39 21.3 13.9 12.3 19.1 12.3 13.9 17.8 16.6 18.0 15.2 
35 40 15.2 13.9 9.8 19.1 15.2 17.8 16.6 9.8 16.6 16.6 
40 41 10.7 10.7 12.9 11.1 13.3 7.7 15.8 9.6 7.7 11.7 
40 42 7.7 13.3 10.7 13.3 10.7 10.7 11.9 15.8 6.0 11.1 
40 43 7.7 11.9 11.7 9.6 6.0 12.9 15.8 11.7 13.3 12.9 
40 44 11.9 6.0 7.7 10.7 11.1 11.9 12.9 12.9 12.9 11.1 
40 45 15.8 9.6 12.9 9.6 6.0 12.9 11.1 11.9 7.7 7.7 
45 46 12.0 16.5 17.3 17.3 16.3 16.3 13.2 15.3 16.3 11.6 
45 47 13.5 12.0 11.6 13.2 16.6 11.6 15.6 15.3 15.3 13.5 
45 48 15.6 12.0 15.3 15.6 16.6 15.2 16.6 13.5 15.3 15.6 
45 49 12.0 15.3 17.3 15.3 16.3 16.3 13.2 17.3 11.6 14.5 
45 50 16.3 16.3 13.5 13.2 17.3 13.2 16.6 15.2 16.6 13.5 
Descriptive Statistics 
Simulated X 
position 1 2 3 4 5 6 7 8 9 10 
Mean 14.4 14.6 14.5 15.2 14.2 14.5 15.2 14.5 13.8 14.3 
Standard Error 0.7 0.7 0.7 0.6 0.7 0.8 0.6 0.8 0.6 0.7 
Median 13.5 13.9 13.2 15.4 13.9 14.2 14.5 14.2 13.7 13.6 
Mode 6.0 15.3 15.5 19.1 11.0 8.2 12.2 14.5 12.2 7.6 
Standard 
Deviation 5.0 5.3 4.8 4.5 4.9 5.3 4.2 5.5 4.1 5.0 
Sample Variance 24.6 28.1 22.6 20.0 23.8 28.6 17.2 30.7 17.1 25.2 
Kurtosis -0.4 0.4 -0.1 0.1 0.2 0.2 0.5 0.4 0.2 0.1 
Skewness 0.4 0.6 0.6 0.5 0.2 0.5 0.2 0.6 0.1 0.5 
Range 20.5 22.2 21.2 19.3 23.1 25.4 22.2 25.4 19.9 23.1 
Minimum 6.0 4.7 5.7 7.6 3.8 3.8 4.7 3.8 5.7 3.8 
Maximum 26.5 26.9 26.9 26.9 26.9 29.2 26.9 29.2 25.6 26.9 
Sum 720.3 731.0 726.9 758.6 711.3 723.6 758.2 727.1 689.7 715.6 
Count 50 50 50 50 50 50 50 50 50 50 
Confidence Level 
(95.0%) 
1.4 1.5 1.3 1.2 1.4 1.5 1.2 1.5 1.1 1.4 
Explanation of symbols (percent lithophysal cavity porosity) 
<=5 <=10 <=15 <=20 <=25 >25 
ANL-EBS-MD-000027 REV 03 T-9 September 2004 

Drift Degradation Analysis 
Table T-3. Display of Part of the 2080 Cell Table with Descriptive Statistics for Calculation of 
Lithophysal Cavity Porosity in a 50200 m Simulated Cross Section with the Centerline at 
Station 17+56 
Table of porosity values (2.5x2.5 m grid) 
Horizon Cell Y\X 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.5 25.0 
0 2.5 15.3 7.4 7.9 5.7 8.2 6.0 5.7 7.4 5.7 15.3 
0 5.0 7.4 8.2 8.2 10.6 8.2 8.2 3.8 6.0 14.4 10.6 
5 7.5 12.0 12.2 11.0 17.0 12.2 10.2 10.2 12.1 8.8 12.2 
5 10.0 13.4 10.2 13.6 12.0 11.0 17.0 10.2 12.2 11.0 17.7 
10 12.5 29.2 21.0 19.0 26.9 17.4 17.2 29.2 19.0 17.4 19.0 
10 15.0 24.6 29.2 25.6 25.6 11.0 19.0 19.0 17.4 21.0 17.4 
15 17.5 18.8 17.0 13.6 18.8 20.5 21.4 19.3 17.0 23.4 15.5 
15 20.0 19.1 20.6 20.5 16.8 15.5 16.8 16.8 15.5 19.1 22.9 
20 22.5 13.0 15.3 13.0 14.5 10.7 14.5 11.0 13.0 11.0 14.5 
20 25.0 15.3 14.5 15.3 17.3 11.7 11.7 10.7 10.6 15.5 17.3 
25 27.5 15.5 13.8 18.1 16.9 25.6 16.9 18.1 25.6 18.8 20.1 
25 30.0 14.5 16.9 25.6 18.1 18.1 21.1 17.3 18.1 25.6 16.9 
30 32.5 7.8 10.8 9.7 7.8 11.8 12.7 11.8 10.8 11.8 11.6 
30 35.0 9.7 11.8 12.7 13.6 8.5 9.7 9.7 10.8 12.7 7.8 
35 37.5 9.8 9.8 11.6 19.1 5.7 21.3 16.6 17.8 17.8 5.7 
35 40.0 21.3 15.2 9.8 19.1 9.8 12.3 14.4 15.2 21.3 17.8 
40 42.5 9.6 12.9 9.6 11.9 9.6 11.9 6.0 12.9 11.7 13.3 
40 45.0 9.6 11.1 11.9 10.7 9.6 9.6 10.7 6.0 11.1 11.9 
45 47.5 14.5 17.3 15.2 17.3 15.3 13.5 16.6 15.6 16.6 15.2 
45 50.0 15.3 16.6 14.5 16.5 12.0 16.5 15.6 13.2 16.5 16.6 
Descriptive Statistics 
Simulated X 
position 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.5 25.0 
Mean 14.8 14.6 14.3 15.8 12.6 14.4 13.6 13.8 15.6 15.0 
Standard Error 1.3 1.1 1.2 1.2 1.1 1.0 1.3 1.1 1.1 0.9 
Median 14.5 14.1 13.3 16.9 11.4 14.0 13.1 13.1 16.0 15.4 
Mode 14.5 #N/A #N/A 19.1 8.2 #N/A 10.2 10.8 #N/A #N/A 
Standard 
Deviation 5.6 5.1 5.2 5.2 4.8 4.5 5.9 4.8 5.1 4.2 
Sample Variance 31.8 25.9 26.6 27.3 23.3 20.5 34.3 22.7 26.4 17.3 
Kurtosis 1.0 2.3 0.5 0.4 1.5 -0.9 1.3 0.7 -0.5 0.3 
Skewness 1.0 1.2 1.0 0.2 1.2 0.0 0.6 0.4 0.1 -0.5 
Range 21.8 21.8 17.8 21.2 19.9 15.4 25.4 19.6 20.0 17.2 
Minimum 7.4 7.4 7.9 5.7 5.7 6.0 3.8 6.0 5.7 5.7 
Maximum 29.2 29.2 25.6 26.9 25.6 21.4 29.2 25.6 25.6 22.9 
Sum 295.8 291.7 286.4 316.3 252.4 287.7 272.6 276.5 311.4 299.5 
Count 20 20 20 20 20 20 20 20 20 20 
Confidence Level 
(95.0%) 
2.5 2.2 2.3 2.3 2.1 2.0 2.6 2.1 2.3 1.8 
Explanation of symbols (percent lithophysal cavity porosity) 
<=5 <=10 <=15 <=20 <=25 >25 
ANL-EBS-MD-000027 REV 03 T-10 September 2004 

Drift Degradation Analysis 
The fourth step in creation of a simulated vertical cross section is to project the 5 m horizons in 
the vertical section away from the vertical section to create the cross section. For a 200 m wide 
cross section, the projection away from the central vertical section is 100 m to either side. In this 
construct, the maximum straight line projection distance for an apparent dip of 4.6 and an 
along-the-tunnel projection of 311 m is only 327 m. This projection distance is consistent with 
the overall stratiform characteristics of the lithostratigraphic section. Figure T-5 displays two 
simulations of a 50200 m cross section using a 4.6 apparent dip, one for a center of the section 
at 1756 m and a second for a center at 2014 m. In these simulations, there is an overlap of 364 m 
along the tunnel and when projected to the vertical plane it represents an overlap of about 30 m 
of section (Figure T-5). Each simulation is depicted with a 50200 cell table representing a 
11 m grid (sections A and C) and a 2080 cell table representing a 2.22.5 m grid (sections B 
and D). The four sections in Figure T-5 display similar stratiform relations. 
Descriptive statistics (from standard Excel functions) for the input data in the various windows 
(Table T-4) with the selected statistics from 5 m tall horizons in the 50200 cell and 2080 cells 
indicate very good correlations. The descriptive statistics (from standard Excel functions) of the 
total Tptpll zone in the ECRB Cross-Drift is provided in Table T-4 (first column of values). 
Descriptive statistics for the total windows in the ECRB Cross-Drift (input) data and the total 
50200 cell and 2080 cell tables indicate very high correlations (Table T-5). These correlations 
reinforce the technical soundness of this approach to project the distribution of lithophysal cavity 
porosity from the cross section data to a vertical plane. 
T7. LIMITATIONS OF THE CALCULATION 
The calculations of the distribution of lithophysal cavity porosity from the ECRB Cross-Drift to 
a vertical plane that is perpendicular to the tunnel is based on sound geologic and geometric 
relations; however, there are a few limitations to the results: 
A. The calculations exemplified in this appendix are based on the consideration that the 
ECRB Cross-Drift is horizontal. The gradient of the tunnel is 1.5 percent (0.86) from 
07+73 to 16+02 and is 0.9 percent (0.52) from 16+02 to 24+67 (Mongano et al. 1999 
[DIRS 149850], pp. 3 to 6). So, although these inclinations are small, they can be 
factored into the apparent dip of the lithostratigraphic units and features to enhance the 
geologic and construction conditions. 
B. Using a constant apparent dip of 4.6 from the strike and dip of 270/07 for the top 
contact of the lower lithophysal zone in the ECRB Cross-Drift (Mongano et al. 1999 
[DIRS 149850], Table 1) and the total intercept of the lower lithophysal zone in the 
ECRB Cross-Drift (from 14+44 to 23+26), the calculated thickness of the lower 
lithophysal zone is only 71 m. This calculated thickness is less than what is calculated 
and depicted by a variety of other methods, so the apparent dip of 4.6 is probably too 
shallow; therefore, the number and the distribution of values in each window along the 
tunnel might be over represented. 
C. The simulated cross section is constructed perpendicular to the tunnel; however, it 
does not include the apparent dip in the plane of the cross section. For example, using 
the features and data depicted in Figure T-2, the apparent dip in the cross section is 
5.3 to the northwest. 
ANL-EBS-MD-000027 REV 03 T-11 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 T-12 September 2004 
IISECTON A or B at STATION 17+ 56 
SECTON C or D at STATION 20+ 14 
NOTE: 
Cross section A is a 50x200 cell table representing a 1x1 m grid, and cross section B is a 20x80 cell table representing a 2.2x2.5 m grid for the 
simulated section at 17+56. Cross Section C is a 50x200 cell table representing a 1x1 m grid, and cross Section D is a 20x80 cell table representing a 
2.2x2.5 m grid for the simulated section at 20+14. 
Figure T-5. Two 50200 m Simulated Cross Sections of Lithophysal Cavity Porosity at Stations 17+56 and 20+14 

Drift Degradation Analysis 
Because the values in each cell in the 50200 and 2080 cell tables are independently and 
randomly allocated, locally there are a few geologically inconsistent results. While this 
allocation technique results in very high correlations of the descriptive statistics between the 
input data and resulting cross-section horizons, it is possible that locally, the minimum and 
maximum values in a window or in adjacent windows can be in adjacent cells. This extreme 
change in lithophysal cavity porosity has not been observed in the ECRB Cross-Drift as shown 
by the gradual increase or decrease in values (although sharp changes can occur across distances 
of 5 to 10 m; Figure T-3). One result of this random allocation of values and the potential 
juxtaposition of large and small (or mostly values of one end of the distribution or another) is the 
variation in descriptive statistics in vertical sections (X positions; Table T-2 and T-3). The affect 
of this juxtaposition of minimum and maximum values is probably greater in the 2080-cell 
table that represents a 2.52.5 m grid than in the 50200 cell table that represents a 11 m grid. 
One way to minimize this affect is to filter the values in the tables and remove (or change) one or 
both of the juxtaposed values. Development of such a filter needs to focus on diminishing the 
anomalies, but maintaining the statistical integrity of the resultant calculated values. 
Table T-4. Comparison of Descriptive Statistics for the Total Tptpll Zone in the ECRB Cross-Drift, 
Individual Windows from the Input Data, and Selective Statistics for 5 m Tall Horizons in a 
50200 m Simulated Cross Section with 11 m and 2.52.5 m Grids 
Descriptive Statistics (for Total Input and Windows) 
StatisticTotal ECRBCross-Drift Data0-5 Window 
0-51x1 Grid0-52.5x2.5 Grid5-10 Window 
5-101x1 Grid5-102.5x2.5 Grid10-15 Window 
10-151x1 Grid10-152.5x2.5 Grid15-20 Window 
15-201x1 Grid15-202.5x2.5 Grid20-25 Window 
20-251x1 Grid20-252.5x2.5 Grid 
Mean 12.9 9.2 9.1 9.3 12.6 12.6 12.3 21.5 21.2 22.4 18.6 18.6 18.3 13.5 13.6 13.6 
Standard 
Error 0.4 1.4 0.1 0.4 0.7 0.1 0.2 1.4 0.1 0.4 0.7 0.1 0.2 0.5 0.1 0.2 
Median 12.7 7.7   12.2   21.0   18.8   13.6   
Mode 17.0 #N/A   12.2   #N/A   17.0   13.0   
Standard 
Deviation 5.4 4.8 4.6 4.7 2.5 2.3 2.4 5.0 4.7 4.6 2.8 2.7 2.6 2.0 2.0 2.0 
Sample 
Variance 29.6 22.7 21.1 21.9 6.2 5.5 5.9 24.8 22.2 20.8 7.7 7.0 7.0 4.2 3.9 3.8 
Kurtosis -0.2 0.3 0.8 0.1 -0.6 -0.8 
Skewness 0.4 1.1 1.0 1.0 0.9 0.8 0.9 -0.4 -0.2 -0.5 0.2 0.2 0.1 0.0 0.0 0.0 
Range 26.7 15.5   8.9   18.2   9.8   6.7   
Minimum 2.5 3.8   8.8   11.0   13.6   10.6   
Maximum 29.2 19.4   17.7   29.2   23.4   17.3   
Sum 2352.1 110.9   164.4   279.9   279.2   189.5   
Count 183 12   13   13   15   14   
Confidence 
Level 
(95.0%) 
0.8 2.7   1.3   2.7   1.4   1.1   
ANL-EBS-MD-000027 REV 03 T-13 September 2004 

Drift Degradation Analysis 
Table T-4. Comparison of Descriptive Statistics for the Total Tptpll Zone in the ECRB Cross-Drift, 
Individual Windows from the Input Data, and Selective Statistics for 5 m Tall Horizons in a 
50200 m Simulated Cross Section with 11 m and 2.52.5 m Grids (Continued) 
Descriptive Statistics (for Total Input and Windows) 
StatisticTotal ECRBCross-Drift Data25-30 Window 
25-301x1 Grid25-302.5x2.5 Grid30-35 Window 
30-351x1 Grid30-352.5x2.5 Grid35-40 Window 
35-401x1 Grid35-402.5x2.5 Grid40-45 Window 
40-451x1 Grid40-452.5x2.5 Grid45-50 Window 
45-501x1 Grid45-402.5x2.5 Grid 
Mean 12.9 18.5 18.6 18.2 11.1 11.0 11.0 14.6 14.6 14.6 11.0 11.0 10.8 14.8 14.9 14.6 
Standard 
Error 0.4 0.9 0.1 0.3 0.6 0.1 0.2 1.3 0.1 0.4 0.7 0.1 0.2 0.5 0.1 0.1 
Median 12.7 18.1   11.6   14.8   11.4   15.3   
Mode 17.0 18.1   11.8   #N/A   #N/A   #N/A   
Standard 
Deviation 5.4 3.4 3.3 3.3 2.1 2.0 2.0 4.4 4.1 4.6 2.6 2.4 2.7 1.8 1.7 1.8 
Sample 
Variance 29.6 11.6 10.8 10.6 4.4 4.1 4.1 19.0 17.2 20.8 6.7 5.9 7.5 3.2 2.9 3.3 
Kurtosis -0.2 0.5   -1.2   0.2   0.6   -0.6   
Skewness 0.4 0.9 0.8 0.8 -0.2 -0.2 -0.1 -0.5 -0.5 -0.6 -0.2 -0.2 -0.3 -0.6 -0.6 -0.3 
Range 26.7 11.9   6.1   15.6   9.8   5.7   
Minimum 2.5 13.8   7.8   5.7   6.0   11.6   
Maximum 29.2 25.6   13.9   21.3   15.8   17.3   
Sum 2352.1 259.4   143.8   175.8   132.3   192.9   
Count 183 14   13   12   12   13   
Confidence 
Level 
(95.0%) 
0.8 1.8   1.1   2.5   1.5   1.0   
Table T-5. Comparison of Descriptive Statistics for the Total Windows from ECRB Cross-Drift (Input) 
Data and the Total 50200 m Simulated Cross Section with 11 m and 2.52.5 m Grids 
Descriptive Statistics for Total Windows 
ECRB ECRB 
Cross-Drift 2.5x2.5 Cross-Drift 2.5x2.5 
Statistic Data 1x1 Grid Grid Statistic Data 1x1 Grid Grid 
Mean 14.7 14.5 14.5 Skewness 0.4 0.4 0.4 
Standard Error 0.4 0.0 0.1 Range 25.4 25.4 25.4 
Median 14.4 13.9 13.9 Minimum 3.8 3.8 3.8 
Mode 17.0 11.6 11.6 Maximum 29.2 29.2 29.2 
Standard 
Deviation 4.9 4.9 5.1 Sum 1928.1 145404.3 23193.6 
Sample 
Variance 24.0 24.0 25.5 Count 131.0 10000 1600 
Kurtosis 0.2 0.2 0.2 Confidence 
Level (95.0%) 0.8 0.10 0.25 
ANL-EBS-MD-000027 REV 03 T-14 September 2004 

Drift Degradation Analysis 
APPENDIX U 
METHODOLOGY OF AND VERIFICATION OF THE INTERCHANGE AND 
APPLICATION OF ROCK MASS PRE- AND POSTCLOSURE TEMPERATURE 
PREDICTIONS FROM THE NUFT THERMAL CALCULATION TO THE UDEC AND 
FLAC MODELS 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
METHODOLOGY OF AND VERIFICATION OF THE INTERCHANGE AND 
APPLICATION OF ROCK MASS PRE- AND POSTCLOSURE TEMPERATURE 
PREDICTIONS FROM THE NUFT THERMAL CALCULATION TO THE UDEC AND 
FLAC MODELS 
Stability of the drift in the lithophysal and nonlithophysal rock mass due to thermal loading was 
analyzed using the UDEC and 3DEC discontinuum models as described in Sections 6.3 and 6.4. 
For consistency with other thermal calculations performed for performance assessment at Yucca 
Mountain, the UDEC and 3DEC programs were not used to determine the rock mass 
temperatures. Instead, the evolution of the temperature field after waste emplacement was 
obtained using the hydro-thermal code NUFT, which is one of the component submodels of the 
LDTH model, described in Multiscale Thermohydrologic Model (BSC 2004 [DIRS 169565]). 
The temperature fields were imported sequentially into UDEC (lithophysal rock) and FLAC 
(nonlithophysal rock) for a number of times after waste emplacement, making sure that the 
temperature change between two stages is relatively small (i.e., it does not result in a large stress 
change). The thermal stresses due to temperature changes were calculated, and the model was 
solved for equilibrium for the selected thermal times. The purpose of this appendix is to describe 
the process of application of the NUFT temperature fields to the UDEC and FLAC models, and 
to verify that this process results in proper NUFT rock mass temperature within the UDEC and 
FLAC models. 
NUFT provides the temperature fields on a rectangular grid, which are stored in a spreadsheet 
(DTN: MO0408MWDDDMIO.002, file LA1450_NUFT_Temp_crss-sctn3.xls; see example 
shown in Figure U-1). The temperature fields, corresponding to different thermal times, are 
extracted and stored in separate ASCII files (see example shown in Figure U-2.), which are read 
by UDEC. The UDEC model is composed of a large number of irregularly-shaped blocks which 
are, in turn, discretized into a number of triangular finite difference elements. The temperatures 
from the NUFT grid must be interpolated at the nearby UDEC grid points. To perform this 
interpolation, the NUFT elements that contain UDEC grid points must be identified. In order to 
speed up the search of the NUFT element that contains a UDEC grid point, the coordinates in the 
ASCII files are sorted by increasing x-and y-coordinates. The UDEC geometry is generated 
using the same coordinate system as the one used in NUFT. The origins of the coordinate 
systems in both models are at the center of the drift. The NUFT model uses the symmetry 
condition with respect to the vertical plane through the drift center. The symmetry was not used 
in the UDEC model for the mechanical simulations, but the temperature field is considered to be 
(, ,
symmetrical, i.e., Tx y ) = T (-x y ). 
ANL-EBS-MD-000027 REV 03 U-1 September 2004 

Drift Degradation Analysis 
NUFT 2D Multi-Scale TH (LDTH) model 
TSPA-LA: 1.45 kW/m, 0 yrs emplacment duration (50 yrs Ventialtion), closure at 50 yrs 
90% integrated heat removal ratio 
Location Temperature (oC) 
Pre-closure 
x z 1 2 3 5 10 20 
(m) (m) (oC) (oC) (oC) (oC) (oC) (oC) 
0.285 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
0.745 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
1.0855 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
1.43085 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
1.80055 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
2.2004 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
2.5801 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
2.9998 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
3.6998 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
4.8998 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
6.8998 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
10.1498 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
15.1498 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
22.6498 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
33.8249 278.293 16.94 16.94 16.94 16.94 16.94 16.94 
0.285 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
0.745 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
1.0855 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
1.43085 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
1.80055 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
2.2004 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
2.5801 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
2.9998 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
3.6998 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
4.8998 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
6.8998 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
10.1498 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
15.1498 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
22.6498 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
33.8249 277.385 16.96 16.96 16.96 16.96 16.96 16.96 
0.285 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
0.745 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
1.0855 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
1.43085 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
1.80055 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
2.2004 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
2.5801 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
2.9998 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
3.6998 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
4.8998 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
6.8998 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
10.1498 272.595 17.07 17.07 17.07 17.07 17.07 17.07 
Source: DTN: MO0408MWDDDMIO.002, file LA1450_NUFT_Temp_crss-sctn3.xls. 
Figure U-1. Portion of the Excel Spreadsheet With the NUFT Output 
ANL-EBS-MD-000027 REV 03 U-2 September 2004 

Drift Degradation Analysis 
0 -330.229 29.20 
0 -282.534 27.67 
0 -227.574 26.06 
0 -205.997 25.52 
0 -162.843 24.49 
0 -144.723 24.06 
. 
. 
. 
0 253.6255 17.47 
0 261.6675 17.29 
29.20 
27.67 
26.06 
25.52 
24.49 
24.06 
23.42 
23.91 
40.22 
. 
. 
. 
0 -317.2945 28.78 
0 -296.7135 28.15 
0 -266.0695 27.10 
0 -247.2465 26.57 
0 -184.42 24.99 
0 -133.9125 23.78 
0 -121.6955 23.46 
0 -105.9045 23.32 
0 237.871 17.84 
0 266.135 17.20 
0 272.595 17.07 
0 277.385 16.96 
0 278.293 16.94 
0.285 -330.229 
0.285 -317.2945 28.78 
0.285 -296.7135 28.15 
0.285 -282.534 
0.285 -266.0695 27.10 
0.285 -247.2465 26.57 
0.285 -227.574 
0.285 -205.997 
0.285 -184.42 24.99 
0.285 -162.843 
0.285 -144.723 
0.285 -133.9125 23.78 
0.285 -121.6955 23.46 
0.285 -105.9045 23.32 
0.285 -84.7085 
0.285 -70.5585 
0.285 -60.544 24.30 
0.285 -43.044 25.77 
0.285 -30.544 27.53 
0.285 -22.544 29.18 
0.285 -17.544 30.76 
0.285 -14.044 32.74 
0.285 -11.294 35.71 
0.285 -9.044
Source: DTN: MO0408MWDDDMIO.002, file temperature_5080.dat. 
Figure U-2. Example of ASCII File With Temperature Field for 50.8 Years After Waste Emplacement 
After the NUFT temperature field is read into UDEC, interpolation of temperatures was 
performed for the UDEC grid points. In UDEC, the temperature is a grid point variable. First, a 
UDEC grid point is located in one of the NUFT rectangular zones (Figure U-3). This operation 
can be done relatively quickly because the NUFT grid is rectangular. It is carried out by 
independent searches along x - and y -coordinate axes. After local coordinates .,. (of the 
UDEC grid point inside the NUFT zone) are determined (Equation U-1), the temperature is 
calculated using bi-linear interpolation based on temperatures at four NUFT grid points, as 
shown in Equation U-2. 
ANL-EBS-MD-000027 REV 03 U-3 September 2004 

Drift Degradation Analysis 
Figure U-3. Interpolation of UDEC Temperatures from the NUFT Grid 
.
UDEC = 2 xUDEC - x1 -1
x3 - x1 
(Eq. U-1) 
UDEC - y1 -1.
UDEC = 2 y
y -y
31 
1
f1 = (1 -.)(1 -.)
4
1
f2 = (1 +.)(1 -.)
4
f3 = 1 (1 +.)(1 +.) (Eq. U-2) 
4
1
f4 = (1 -.)(1 +.)
4
T
UDEC = f T + f T + f T 3 +f1 1223 T44
The temperature field 50.8 years after emplacement of the waste, as provided by NUFT, is 
transferred into UDEC using the method described above. The contour lines of the temperature 
field imported in UDEC are compared with contour lines of the original temperature field in 
Figure U-4. The temperature profiles along the horizontal section through the drift center 
obtained from the NUFT data and after importing them into UDEC are compared in Figure U-5. 
The transfer of temperature field and interpolation are carried out correctly, as the contour lines 
and the profiles in the horizontal section are almost coincident. 
The same algorithm was used for the FLAC model, the verification for UDEC model is therefore 
applicable to FLAC results. 
ANL-EBS-MD-000027 REV 03 U-4 September 2004 

Drift Degradation Analysis 
3.000E+ 01 
4.000E+ 01 
5.000E+ 01 
6.000E+ 01 
7.000E+ 01 
8.000E+ 01 
9.000E+ 01 
1.000E+ 02 
NOTE: Temperature in degrees C; NUFT Results are dashed lines; Data transferred into UDEC solid colored lines. 
Figure U-4. Comparison of Temperature Contours 50.8 Years after Waste Emplacement Obtained from 
the NUFT Results and the Data Transferred into UDEC 
Figure U-5. Comparison of Temperature Profiles Along the Horizontal Section Through the Center of the 
Drift 50.8 Years After Waste Emplacement Obtained from the NUFT Results and the Data 
Transferred into UDEC 
ANL-EBS-MD-000027 REV 03 U-5 September 2004

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 U-6 September 2004 

Drift Degradation Analysis 
APPENDIX V 
CALCULATION OF BULKING AND IMPACT OF 
STRESS ARCHING FROM THE UDEC DISCONTINUUM MODEL 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
CALCULATION OF BULKING AND IMPACT OF 
STRESS ARCHING FROM THE UDEC DISCONTINUUM MODEL 
V1. INTRODUCTION 
It is possible, using the UDEC Voronoi block model, to simulate the entire process of rockfall, 
including accumulation of the broken rock on the invert of the emplacement drift and on the top 
of the drip shield. The final configuration of the blocks and effective bulking are results of a 
simulation. Many approaches for calculating the extent of caving above excavations use bulking 
factor as an input to the analysis. In the UDEC Voronoi block model, the bulking is a model 
result, a function of many factors, including size distribution and shape of the blocks, friction 
angle between the blocks, and sequence of rockfall formation (i.e. if the rockfall first occurs from 
the crown or from the walls of the drift). However, it is useful to calculate the effective bulking 
factor of the caved rock resulting from UDEC simulations as a reference for comparison with 
other methods. 
In order to calculate the bulking factor, the region of the rock mass that caved must be identified 
first. This region is determined based on the displacement magnitudes of the blocks. If the 
average block displacements are larger than a predefined length threshold, the block is classified 
to be a part of the rockfall. Considering that the caved rock completely fills the drift, the bulking 
factor is calculated as the ratio between the area inside the drift (area of the drift in the original 
configuration before the rockfall minus the area of the outline of the drip shield) and the area of 
the caved blocks. A larger value of the predefined threshold will result in a smaller region of 
caved rock and, consequently, a larger bulking factor. The displacement length threshold was 
selected based on inspection of the displacement contours. Figure V-1 illustrates the contours of 
the displacement field for Case 4 from Section 6.4.2.5. Although the legend of Figure V-1 
indicates x -displacements, the figure actually represents contours of total displacement. The 
contour line corresponding to a displacement of 0.12 m appears to be a good choice for the 
outline of the caved rock around the emplacement drift, because there is a large displacement 
gradient inside that contour line. If the caved rock completely fills the drift, the available volume 
predefines the increase in volume of the caved rock. The volume of the rock mass (in its original 
configuration) that caved is calculated by simply adding the areas of the blocks classified to be a 
part of the rockfall. Note that UDECs data structure has information about geometry, including 
area, of every block in a model. The total area, A , of the blocks in the model that displaced
comore than 0.12 m, calculated by summing their areas, is 88.71 m2. The calculated bulking factor 
is: 
2
pR - b h 23.76 - 7.31
B = dd ==0.19 (Eq. V-1) 
A 88.71
co 
The area of the outline of the drip shield in the cross-section normal to the drift axis is 7.31 m2 
(the drip shield is 2.533 m wide and 2.886 m high). 
Summation of block areas was also done manually. The blocks with average displacements 
larger than 0.12 m are printed out (Figure V-2). UDEC prints out, among the other information, 
the block masses, which are summed in Excel. The sum of masses of the caved blocks is 
ANL-EBS-MD-000027 REV 03 V-1 September 2004 

Drift Degradation Analysis 
189,840 kg/m. The corresponding area for a density of 2,140 kg/m3 is 88.71 m2exactly the 
same number as obtained using the FISH function. 
Figure V-1. Contours of Displacement Magnitudes (m): Case 4 of the Drift Degradation Analysis 
The area of the rock mass that has caved and the bulking factor are also calculated manually in 
order to verify the procedure described in the previous paragraph. The outline of the caved rock 
mass is drawn and measured horizontally at every 1 meter increment of the cave height, which is 
approximately 14 m (see Figure V-3). The area of the cross-section of the cave, A, is 
111.03 m2, equal to the sum of the widths indicated in Figure V-3 (multiplied by the 1 m 
increment height). The other approach is to approximate the cave with an ellipse (as indicated in 
red in Figure V-3). With a major axis of 14.0 m and a minor axis of 10.34 m, the area of the 
ellipse is 113.69 m2. The difference between these two estimates of cave area is very small, of 
the order of a couple of percent. The total area of the blocks that have caved is equal to the area 
of the cave minus the increase in volume (i.e. area filled with rubble): 
2
A = A -pR= 111.03 - 23.76 =87.27 m2 (Eq. V-2) 
co c 
The difference between the area of the caved rock mass calculated by adding areas of blocks in 
UDEC and manually integrating the area of the cave is less than 2 percent. The bulking factor, 
based on the manually estimated area of the caved rock mass, is: 
2
pR - bh 23.76 - 7.31
dd == 0.19 . (Eq. V-3) 
B= 2A-pR 111.03 - 23.76
c 
Clearly, the bulking factor numerically calculated using UDEC is in agreement with the 
estimates obtained using simple methods. 
ANL-EBS-MD-000027 REV 03 V-2 September 2004 

Drift Degradation Analysis 
block data 
block 
address 
mat const fixity 
no. no. cond. 
centroid coords. mass pol. mom. 
2147913 10 3 0 1.378E+00 -1.850E+00 4.531E+01 1.898E-01 
(fdef)
2147255 10 3 0 -2.461E+00 -1.149E+00 5.525E+01 3.490E-01 
(fdef)
2146517 10 3 0 -7.434E-01 8.458E-01 7.498E+01 4.518E-01 
(fdef)
2146336 10 3 0 -5.605E-01 7.503E-01 3.725E+01 1.647E-01 
(fdef)
2146104 10 3 0 -1.600E+00 -1.276E+00 1.190E+02 1.193E+00 
(fdef)
2145621 10 3 0 1.790E+00 -1.955E+00 3.791E+01 1.383E-01 
(fdef)
2145226 10 3 0 1.436E+00 -1.870E+00 2.314E+01 1.041E-01 
(fdef) 
. 
. 
. 
764634 10 3 0 -1.831E+00 -2.380E+00 1.380E+02 1.559E+00 
(fdef)
757418 10 3 0 -1.992E+00 -2.182E+00 7.788E+01 5.579E-01 
(fdef)
755122 10 3 0 1.533E-01 8.312E+00 9.266E+01 7.050E-01 
(fdef)
753590 10 3 0 2.248E-01 8.476E+00 8.412E+01 5.655E-01 
(fdef)
745568 10 3 0 -9.186E-02 1.025E+01 8.732E+01 6.199E-01 
(fdef)
745169 10 3 0 -4.920E-01 1.018E+01 9.538E+01 7.205E-01 
(fdef)
744531 10 3 0 -2.940E-01 1.028E+01 1.212E+02 1.138E+00 
(fdef) 
Source: File: loose_blocks.log.
Figure V-2. Printout of Information for the Blocks with Average Displacement Larger than 0.12 m 
Figure V-3. Outline of the Caved Rock Mass and Its Dimensions Used for Manual Integration 
ANL-EBS-MD-000027 REV 03 V-3 September 2004 

Drift Degradation Analysis 
V2. STRESS ARCHING IN THE BROKEN ROCK ABOVE THE DRIP SHIELD 
ARCHING EFFECT FOR A RIGID, RECTANGULAR DRIP SHIELD 
A calculation is presented here to demonstrate the impact of stress arching for the case illustrated 
in Figure V-1. Here, a rigid, rectangular drip shield is considered, which will result in less stress 
arching effect than would be expected for a deformable drip shield. For the approximate height 
(14.0 m) of the cave (measured from the invert of the drift), the dead weight of the broken rock 
on the drip shield is: 
1ph g 
B 
. 
= 
+ 
= (14.0m 2.75m 0.67m)- -  
3 22400kg/m 10m/s 
(1 0.19) 
 
+
= 2213.4 kN/m (Eq. V-4) 
where h is the height of broken rock above the drip shield, which is determined knowing the cave 
height (14.0 m), the drift radius (2.75 m), and the distance from the drift center to the top of the 
drip shield (0.67 m). The average vertical pressure on the drip shield as calculated by using 
UDEC, which integrates the forces acting between the drip shield and the blocks in the rubble, is 
179.2 kN/m2. The arching inside the rubble accounts for only a 16 percent reduction in the load 
on the drip shield. LeFebvre et al. (1976 [DIRS 168919]) measured pressures of the fill on the 
corrugated steel arch, 15.5 m in span. The pressure was measured during backfilling of the arch. 
The fill consisted mainly of fine silty sand, compacted at 90 percent of the modified Proctor. 
The measured vertical stress, 2 ft above the top of the structure, shows that positive arching 
develops when the fill is approximately 3.5 m above the measurement point. At the end of 
construction, when the top of the embankment is approximately 12.5 m above the pressure cell, 
the measured pressure is only 25 percent of the overburden. Similar results are reported by 
Byrne et al. (1990 [DIRS 168921]) for an arch metal culvert, 13.4 m in span. The arch was 
7.3 m high, covered by 9.6 m of natural sand and gravel compacted to between 95 and 
100 percent of standard Proctor. The pressure cell was located 1.2 m above the crown of the 
arch. The stresses were measured as a function of the height of fill. Positive arching is observed 
when the fill was approximately 1.5 m above the pressure cell. At the end of construction, with 
9.6 m of the cover, the measured vertical stress is 40 percent of the overburden. The pressure 
cells placed in the fill at the elevation of the springline show the vertical stress larger than the 
overburden, which is more evidence of the presence of a stress arch. 
Stress arching is much more likely to develop in the caved rock, resulting from rockfall, than in 
sand or gravel, because: a) the average block size in the caved rock is larger than the grain size 
in sand or gravel, and b) the friction angle in the broken rock fill is larger than the friction angle 
in sand or gravel. Relatively large load (84 percent of overburden) of the broken rock for the 
rigid, rectangular drip shield predicted by the UDEC model, compared to measured loads on the 
steel arch culverts, is due to considerations that: a) the drip shield is infinitely stiff, and b) the 
drip shield is rectangular. 
V3. IMPACT OF DEFORMABILITY AND SHAPE OF THE DRIP SHIELD 
The actual finite stiffness of the drip shield will result in deformation and increase load transfer 
through the broken rock (i.e., a positive arching effect). The top of the drip shield is designed to 
have an arched shape, which is more favorable for development of a stress arch in the cover 
(above the drip shield) than the rectangular shape considered in the previous example. The 
ANL-EBS-MD-000027 REV 03 V-4 September 2004 

Drift Degradation Analysis 
arched shape of the top of the drip shield will promote lateral displacements of the blocks above, 
causing more load to be transferred through the broken rock than to the drip shield. In the 
following example, taken from Section 6.4, a random geometry of 20 cm blocks form the rock 
mass. The cohesion and tensile strength of the rock mass is reduced to force complete collapse 
and filling of the excavation until equilibrium is achieved. The approximate bulking factor for 
these simulations is 19 percent. 
A comparison of loads to the drip shield is made for two cases: a) rigid drip shield with proper 
arched geometry, and b) a deformable drip shield with proper arched geometry. The drip shield 
in both cases is developed from finite difference elements within the UDEC model. The 
objective here is not to represent the exact geometry of the drip shield, which is a true 
three-dimensional frame structure, but to provide a two-dimensional model that reproduces the 
overall stiffness of the actual structure. To ensure that the model adequately represents this 
stiffness, it was calibrated against the LS-DYNA finite element model that is used for the 
detailed drip shield vibratory motion and damage assessment modeling (see, for example, Drip 
Shield Structural Response to Rockfall, BSC 2004 [DIRS 168993]). A sample problem was run 
with the LS-DYNA program in which the detailed drip shield model was subjected to a uniform 
vertical pressure over its crown. It was demonstrated that the simplified UDEC model correctly 
represents deformation of the drip shield (See Appendix Y). 
The final collapsed state for the rigid and deformable cases are given in Figures V-4 to V-7. The 
deformable drip shield footings are allowed to slide on or separate from the invert. A friction 
coefficient of 0.5 is considered between the footing and the invert, although this value is not 
important in defining load in the drip shield. The invert, pallet and waste package are rigid and 
placed only to provide a boundary restraint to the drip shield legs. The displacement contours of 
the rubble and intact rock are given to help visualize the ultimate height of broken rock, as 
opposed to yielded or damage rock in the surrounding mass. 
The deformation of the drip shield legs and sliding against the pallet due to side pressure of the 
broken rock on the sides of the drip shield are clearly visible in Figure V-6. The resulting 
average pressure on the top and sides of the drip shield are given in Table V-1 show that the 
average pressure on the top of the drip shield is approximately 25 percent lower, in this case, for 
the deformable drip shield, although the right hand side loading is increased significantly. 
Although a number of realizations are necessary for a complete comparison of the impact of 
rigid versus deformable considerations, this example provides an illustration of the methodology 
employed. The estimates of drip shield loading presented in the main body of the report 
(Section 6.4) consider a deformable drip shield. 
ANL-EBS-MD-000027 REV 03 V-5 September 2004 

Drift Degradation Analysis 
Figure V-4. Quasi-static Drift Degradation, 0.2-m Block Size: Equilibrium State for Rigid Drip Shield with 
Arched Top, Bottom Fixed to the Invert 
Figure V-5. Quasi-static Drift Degradation, 0.2-m Block Size: Contours of Displacement (m) Magnitude 
for Rigid Drip Shield with Arched Top, Bottom Fixed to the Invert 
ANL-EBS-MD-000027 REV 03 V-6 September 2004 

Drift Degradation Analysis 
Figure V-6. Quasi-static Drift Degradation, 0.2 m Block Size: Equilibrium State for Deformable Drip 
Shield with Arched Top, Bottom Rests on the Invert 
Figure V-7. Quasi-static Drift Degradation, 0.2 m Block Size: Contours of Displacement (m) Magnitude for 
Deformable Drip Shield with Arched Top, Bottom Rests on the Invert 
ANL-EBS-MD-000027 REV 03 V-7 September 2004 

Drift Degradation Analysis 
Table V-1. Quasi-static Drift Degradation, 0.2 m Block Size: Average Loads on the Drip Shield for Cases 
with Invert 
Left Top Right 
Drip Shield kN/m2 kN/m2 kN/m2 
Rigid, arched top, bottom fixed to 
invert 66.45 144.15 11.28 
Deformable, arched top, bottom 
rests on invert 41.54 108.92 58.76 
ANL-EBS-MD-000027 REV 03 V-8 September 2004 

Drift Degradation Analysis 
APPENDIX W 
BOUNDARY CONDITIONS IN THE THERMAL-MECHANICAL MODEL 
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Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
BOUNDARY CONDITIONS IN THE THERMAL-MECHANICAL MODEL 
The thermal-mechanical analysis of drift stability in the lithophysal rock was carried out using a 
two-dimensional model. The vertical model boundaries are placed in the plane half-distance 
between two drifts. The symmetry conditions of stresses and deformation considered on that 
plane (i.e., the roller boundary condition) are applied on the vertical model boundaries. There 
are no natural boundaries below the repository. The ground surface is the natural mechanical 
boundary above the repository. The model size in the vertical direction is considered finite. The 
horizontal model boundaries are artificial, truncation boundaries, created to limit the model size 
and calculation time. In the UDEC thermal-mechanical calculations, it was considered that the 
horizontal model boundaries are 17.5 m below and above the drift axis. The vertical model size 
is 35 m. The bottom model boundary was considered to be fixed. The uniform normal stress 
equal to the weight of the truncated overburden was applied on the top model boundary as a 
stress boundary condition. It is necessary to demonstrate that the model size and the selected 
boundary conditions do not affect significantly model results. The stresses around the drift (in 
the roof and the wall) are predicted (with continuum elastic model in FLAC) using three 
different model geometries: 30 m (Figure W-1), 60 m (Figure W-2) and 120 m (Figure W-3) 
vertical model dimensions. The horizontal model size is the same in the three cases. The 
simulations were carried out for two extreme cases of material properties in the lithophysal rock 
mass, Categories 1 and 5. 
Figure W-1. Geometry of the Model: Vertical Model Dimension 30 m 
ANL-EBS-MD-000027 REV 03 W-1 September 2004 

Drift Degradation Analysis 
Figure W-2. Geometry of the Model: Vertical Model Dimension 60 m 
Figure W-3. Geometry of the Model: Vertical Model Dimension 120 m 
The stress paths in the principal stress space at five points in the roof and in the wall are 
generated for the simulated cases. The results for Category 1 are shown in Figures W-4 and 
W-5. The model size (in the range between 30 m and 120 m) has no effect on predicted stress 
paths. If the model were extended to the ground surface, the results would not be different. The 
results for Category 5 are shown in Figures W-6 and W-7. Stresses in the crown are practically 
ANL-EBS-MD-000027 REV 03 W-2 September 2004 

Drift Degradation Analysis 
independent of the model size. The effect of the model size can be observed on stress paths 
recorded at the points in the wall. The maximum value of the major principal stress during the 
thermal cycle at the point 0.14 m from the wall is approximately 20 percent larger in the 60 m 
model than in the 30 m model. The stress difference between the 60 m and 120 m models is 
insignificant. That stress change does not cause yield in the drift wall since it is below the yield 
surface and consequently does not effect model predictions of rockfall. Also, at the points that 
are at 0.5 m from the drift wall or further, the increase in the vertical model size results in 
increase in the both principal stresses resulting in the stress state moving away from the yield 
surface, and more favorable stability conditions. With an exception of the point very close to the 
wall surface , the smaller size model results in more conservative conditions from the perspective 
of rockfall predictions. The different stress path as a function of model size take place over a 
relatively short period of time (compared to the duration of the regulatory period), between 
50 years and 100 years after waste emplacement, just after ventilation shut down. 
The selected vertical model size (35 m) and the boundary conditions on the bottom and the top 
model boundaries are satisfactory for the analysis of drift degradation. 
NOTE: 30 m model size  solid line; 60 m model size  dashed line; 120 m model size  pale line. 
Figure W-4. Stress Paths in the Drift Crown for Category 1 
ANL-EBS-MD-000027 REV 03 W-3 September 2004 

Drift Degradation Analysis 
NOTE: 30 m model size  solid line; 60 m model size  dashed line; 120 m model size  pale line. 
Figure W-5. Stress Paths in the Drift Wall for Category 1 
NOTE: 30 m model size  solid line; 60 m model size  dashed line; 120 m model size  pale line. 
Figure W-6. Stress Paths in the Drift Crown for Category 5 
ANL-EBS-MD-000027 REV 03 W-4 September 2004 

Drift Degradation Analysis 
NOTE: 30 m model size  solid line; 60 m model size  dashed line; 120 m model size  pale line. 
Figure W-7. Stress Paths in the Drift Wall for Category 5 
ANL-EBS-MD-000027 REV 03 W-5 September 2004 

Drift Degradation Analysis 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000027 REV 03 W-6 September 2004 

Drift Degradation Analysis 
APPENDIX X 
LISTING OF SITE-SPECIFIC GROUND MOTION PARAMETERS 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
ANL-EBS-MD-000027 REV 03 September 2004 

Drift Degradation Analysis 
LISTING OF SITE-SPECIFIC GROUND MOTION PARAMETERS 
Site-specific ground motions for five levels of annual probability of exceedance, 510-4, 110-4, 
110-5, 110-6, and 110-7, are included in this study. The 510-4 and 110-4 ground motions 
are for preclosure consideration, while the 110-5, 110-6 and 110-7 ground motions are for 
postclosure. The preclosure level motions are provided for comparison to the postclosure levels. 
A total of 15 sets of Point B ground motions (i.e., ground motions developed at repository 
horizon) were selected for each annual postclosure hazard level. The multiple sets ensure a 
reasonable distribution of spectral shapes and time history durations. For each set of ground 
motions, two horizontal components (H1 and H2) and one vertical component (V) of 
acceleration, velocity, and displacement are supplied. 
Two sets of 110-6 ground motions were used. The difference in these sets is described in 
DTN: MO0403AVDSC106.001, file 10-6 TH memo.doc. The original set (i.e., 
DTN: MO0301TMHIS106.001) is used in Section 6.4.2.2. Since this ground motion results in 
complete drift collapse for lithophysal rock, it was not necessary to repeat the analyses using the 
revised set (i.e., DTN: MO0403AVDSC106.001). 
Only one ground motion was provided for the preclosure hazard levels because of the 
deterministic-based design approach for preclosure consideration. This appendix provides a 
complete listing of the peak ground velocity (Tables X-1 to X-5), Arias Intensity (Tables X-6 to 
X-10), and Power Spectral Density (Tables X-11 to X-15). 
Ground velocity time histories are provided for fixed time intervals in the ASCII files contained 
in the DTNs listed below each table. Files for ground velocity are the ones with extension of vts 
or vth. Peak ground velocity is obtained by opening the vts or vth files in the Excel program and 
using the spreadsheet function abs() (absolute value) and max() (maximum value). The values 
for Arias Intensity can be directly extracted from the ASCII files with file extension dur 
contained in the DTNs. Power Spectral Density is obtained by transforming the velocity time 
history to the frequency domain using the fast Fourier transform function in Mathcad. Next, the 
square of the velocities is integrated along the frequency domain. The Mathcad files used to 
obtain the Power Spectral Density are described in Appendix A (Table A-1, 
files *.powe cal.mcd). 
Table X-1. Peak Ground Velocity (cm/sec) for Preclosure Ground Motions 
Ground Motion Set H1 H2 V 
510-4 19.00 17.72 17.73 
110-4 38.38 43.78 47.51 
Source: DTNs: MO0407TMHIS104.003 [DIRS 170599] and MO0306SDSAVDTH.000 [DIRS 164033]. 
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Drift Degradation Analysis 
Table X-2. Peak Ground Velocity (cm/sec) for 110-5 Ground Motions 
Ground Motion Set H1 H2 V 
1 104.58 83.31 70.88 
2 104.58 125.02 145.25 
3 104.58 262.05 398.11 
4 104.59 100.41 152.27 
5 104.58 166.71 106.52 
6 104.54 45.61 173.88 
7 104.51 89.33 333.16 
8 104.56 152.20 98.16 
9 104.59 357.76 281.76 
10 104.60 31.81 50.16 
11 104.60 126.04 120.31 
12 104.54 70.34 100.60 
13 104.58 103.75 318.01 
14 104.62 40.87 92.78 
16 104.56 67.43 137.53 
Source: DTN: MO0402AVDTM105.001 [DIRS 168890], file vts.zip. 
Table X-3. Peak Ground Velocity (cm/sec) for 110-6 Ground Motions (Revised Set) 
Ground Motion Set H1 H2 V 
1 244.14 195.41 111.29 
2 244.12 268.58 233.12 
3 244.14 642.80 609.45 
4 244.10 259.50 297.45 
5 244.07 257.01 113.84 
6 244.13 132.27 270.94 
7 244.66 242.17 637.11 
8 244.14 401.84 153.58 
9 244.16 817.00 457.09 
10 244.02 78.24 84.58 
11 244.12 255.98 127.82 
12 244.14 271.53 194.53 
13 244.13 303.50 337.21 
14 244.15 125.60 245.79 
16 244.12 158.41 211.80 
Source: DTN: MO0403AVDSC106.001 [DIRS 168891], file Vts.zip. 
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Drift Degradation Analysis 
Table X-4. Peak Ground Velocity (cm/sec) for 110-6 Ground Motions (Original Set) 
Ground Motion Set H1 H2 V 
1 244.00 243.35 229.79 
2 243.79 243.90 229.34 
3 254.63 242.69 228.36 
4 243.61 243.28 228.37 
5 243.35 243.39 229.27 
6 244.11 243.05 229.59 
7 243.86 244.08 229.92 
8 244.21 243.93 229.78 
9 244.01 243.98 229.62 
10 241.90 238.07 230.00 
11 243.76 243.82 229.73 
12 243.27 242.83 229.76 
13 243.95 243.95 229.77 
14 244.13 244.27 230.13 
16 243.99 244.07 229.80 
Source: DTN: MO0301TMHIS106.001 [DIRS 161868], file 10-6THb.zip. 
Table X-5. Peak Ground Velocity (cm/sec) for 110-7 Ground Motions 
Ground Motion Set H1 H2 V 
1 535.26 428.42 298.44 
2 535.32 588.89 625.10 
3 535.27 1409.30 1634.20 
4 535.27 569.05 797.61 
5 535.27 563.65 305.27 
6 535.27 290.00 726.52 
7 536.24 530.78 1708.30 
8 535.14 880.81 411.80 
9 535.22 1791.10 1225.70 
10 535.24 171.62 226.79 
11 535.23 561.25 342.73 
12 535.39 595.47 521.62 
13 535.27 665.45 904.21 
14 535.28 275.36 659.11 
16 535.27 347.33 567.89 
Source: DTN: MO0403AVTMH107.003 [DIRS 168892], file Vts.zip. 
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Drift Degradation Analysis 
Table X-6. Arias Intensity (m/sec) for Preclosure Ground Motions 
Ground Motion Set H1 H2 V Sum 
510-4 0.59 0.67 0.46 1.72 
110-4 4.21 4.51 8.97 17.69 
Source: DTNs: MO0407TMHIS104.003 [DIRS 170599] and MO0306SDSAVDTH.000 [DIRS 164033]. 
Table X-7. Arias Intensity (m/sec) for 110-5 Ground Motions 
Ground Motion Set H1 H2 V Sum 
1 32.90 34.36 36.06 103.32 
2 30.76 38.43 123.30 192.49 
3 16.02 22.53 47.60 86.15 
4 12.09 15.47 19.97 47.53 
5 16.20 11.15 13.48 40.83 
6 6.99 5.30 18.21 30.50 
7 3.99 3.75 49.48 57.22 
8 8.45 12.70 15.53 36.68 
9 21.64 52.24 138.70 212.58 
10 8.60 3.51 14.05 26.16 
11 8.27 6.67 14.64 29.58 
12 3.93 4.05 6.69 14.67 
13 9.41 16.03 25.95 51.39 
14 2.57 2.46 7.28 12.31 
16 2.71 1.57 6.85 11.13 
Source: DTN: MO0402AVDTM105.001 [DIRS 168890], file dur.zip. 
Table X-8. Arias Intensity (m/sec) for 110-6 Ground Motions (Revised Set) 
Ground Motion Set H1 H2 V Sum 
1 234.70 252.80 114.00 601.50 
2 205.60 250.00 413.30 868.90 
3 120.10 152.80 135.00 407.90 
4 177.90 218.70 140.90 537.50 
5 77.53 52.45 28.52 158.50 
6 68.81 56.33 78.73 203.87 
7 62.98 60.60 466.90 590.48 
8 71.44 109.00 60.79 241.23 
9 169.20 351.80 464.50 985.50 
10 58.58 26.02 56.83 141.43 
11 56.60 44.59 44.66 145.85 
12 57.63 59.04 46.19 162.86 
13 97.55 169.50 122.60 389.65 
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Drift Degradation Analysis 
Table X-8. Arias Intensity (m/sec) for 110-6 Ground Motions (Revised Set) (Continued) 
Ground Motion Set H1 H2 V Sum 
14 62.75 73.01 118.80 254.56 
16 23.29 14.90 33.94 72.13 
Source: DTN: MO0403AVDSC106.001 [DIRS 168891], file Dur.zip.
Table X-9. Arias Intensity (m/sec) for 110-6 Ground Motions (Original Set) 
Ground Motion Set H1 H2 V Sum 
1 246.40 303.80 481.70 1031.90 
2 228.60 188.10 471.20 887.90 
3 139.00 22.53 33.45 194.98 
4 179.10 176.30 282.30 637.70 
5 57.90 80.54 149.50 287.94 
6 41.90 159.70 70.89 272.49 
7 64.79 58.10 216.60 339.49 
8 64.55 35.10 212.60 312.25 
9 174.00 38.51 90.62 303.13 
10 93.55 185.50 614.60 893.65 
11 63.25 73.79 146.10 283.14 
12 96.98 40.30 117.10 254.38 
13 81.51 131.00 56.29 268.80 
14 43.49 386.10 206.20 635.79 
16 24.26 41.52 85.64 151.42 
Source: DTN: MO0301TMHIS106.001 [DIRS 161868], file dur.zip. 
Table X-10. Arias Intensity (m/sec) for 110-7 Ground Motions
Ground Motion Set H1 H2 V Sum 
1128.00 1215.00 819.60 3162.60 
988.70 1202.00 2972.00 5162.70 
577.30 734.70 970.60 2282.60 
855.60 1052.00 1013.00 2920.60 
372.90 252.20 205.10 830.20 
330.80 270.80 566.10 1167.70 
302.60 291.10 3357.00 3950.70 
343.30 523.60 437.00 1303.90 
812.90 1691.00 3340.00 5843.90 
281.80 125.20 408.60 815.60 
272.10 214.40 321.10 807.60 
277.20 283.90 332.10 893.20 
469.00 815.00 881.40 2165.40 
301.60 350.90 854.40 1506.90 
16 112.00 71.63 244.00 427.63 
Source: DTN: MO0403AVTMH107.003 [DIRS 168892], file Dur.zip. 
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Drift Degradation Analysis 
Table X-11. Power Spectral Density (m2/sec) for Preclosure Ground Motions 
Ground Motion Set H1 H2 V Sum 
510-4 1287 1427 901 3615 
110-4 8251 7359 9672 25282 
Source: DTNs: MO0407TMHIS104.003 [DIRS 170599] and MO0306SDSAVDTH.000 [DIRS 164033]. 
Table X-12. Power Spectral Density (m2/sec) for 110-5 Ground Motions 
Ground Motion Set H1 H2 V Sum 
1 5594 3024 5896 14514 
2 8826 15622 20070 44518 
3 5708 34876 175806 216390 
4 38760 31748 47600 118108 
5 18787 17025 25098 60910 
6 35838 2702 68988 107528 
7 21865 15657 140657 178179 
8 9688 11694 9819 31201 
9 16553 91014 88415 195982 
10 7799 929 2315 11043 
11 10747 14344 29290 54381 
12 21548 10193 18214 49955 
13 39915 37122 288495 365532 
14 50317 2198 27392 79907 
16 15940 5339 22348 43627 
Source: DTN: MO0402AVDTM105.001 [DIRS 168890]. 
Table X-13. Power Spectral Density (m2/sec) for 110-6 Ground Motions (Revised Set) 
Ground Motion Set H1 H2 V Sum 
1 25137 15521 13552 54210 
2 38218 56878 44828 139924 
3 21097 127952 271411 420460 
4 143472 142743 162474 448689 
5 34247 32007 24550 90804 
6 92128 19052 94674 205854 
7 94514 74336 309918 478768 
8 37159 69337 23214 129710 
9 62740 389694 168328 620762 
10 36474 4801 6386 47661 
11 37799 46690 31106 115595 
12 108978 78619 75170 262767 
13 149590 155633 324138 629361 
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Drift Degradation Analysis 
Table X-13. Power Spectral Density (m2/sec) for 110-6 Ground Motions (Revised Set) (Continued) 
Ground Motion Set H1 H2 V Sum 
14 180951 13466 67867 262284 
16 75416 26879 46547 148842 
Source: DTN: MO0403AVDSC106.001 [DIRS 168891]. 
Table X-14. Power Spectral Density (m2/sec) for 110-6 Ground Motions (Original Set) 
Ground Motion Set H1 H2 V Sum 
1 29936 21251 39224 90411 
2 46225 42946 33651 122822 
3 26398 15208 30807 72413 
4 109976 90561 30803 231340 
5 23474 38142 75680 137296 
6 42567 53873 37483 133923 
7 71944 48153 18740 138837 
8 29360 22606 43412 95378 
9 56045 34205 22540 112790 
10 50542 34874 47166 132582 
11 33239 61177 56971 151387 
12 122679 40647 85307 248633 
13 88844 89105 68762 246711 
14 103244 73012 42195 218451 
16 56962 52193 58160 167315 
Source: DTN: MO0301TMHIS106.001 [DIRS 161868]. 
Table X-15. Power Spectral Density (m2/sec) for 110-7 Ground Motions 
Ground Motion Set H1 H2 V Sum 
1 120827 74606 97450 292883 
2 183772 273453 322334 779559 
3 101411 615062 1951533 2668006 
4 689917 686412 1168272 2544601 
5 164712 153940 176528 495180 
6 442885 91587 680740 1215212 
7 454046 357113 2228184 3039343 
8 178537 333143 166899 678579 
9 301482 1872982 1210336 3384800 
10 175483 23099 45916 244498 
11 181710 224448 223650 629808 
12 524097 378094 540483 1442674 
13 719146 748201 2330664 3798011 
14 869763 64725 488013 1422501 
16 362583 129224 334650 826457 
Source: DTN: MO0403AVTMH107.003 [DIRS 168892]. 
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Drift Degradation Analysis 
APPENDIX Y 
VALIDATION OF THE UDEC DRIP SHIELD MODEL
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Drift Degradation Analysis 
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Drift Degradation Analysis 
VALIDATION OF THE UDEC DRIP SHIELD MODEL 
Y1. INTRODUCTION 
The analysis of the rockfall inside the emplacements drifts at Yucca Mountain under different 
loading conditions (e.g. in situ stress, thermally induced load and seismic load) has been carried 
out using the two-dimensional, distinct element code UDEC. The rock mass is represented as an 
assembly of polygonal (Voronoi) blocks of relatively small size (e.g., 0.2 m or 0.3 m) compared 
to the drift size. It was considered in the initial calculations that the drip shield was rectangular 
(with dimensions approximately corresponding to the actual drip shield geometry), infinitely 
stiff, and slaved to free-field movement of the rock mass (i.e., movement unaffected by 
interaction of the seismic wave with the drift). One of the objectives of the rockfall analysis is to 
estimate the drip shield loads, either due to dynamic impact during the rockfall or quasi-static 
load of the caved rock when it reaches equilibrium. If the drip shield is considered to be 
infinitely rigid, the predicted loads are conservative and sometimes can be excessively large. In 
order to access the level of conservatism in predicting loads, the drip shield also is modeled as 
deformable. 
Representation of the deformable drip shield in the two-dimensional model, calculation of the 
model geometrical and mechanical properties, and model validation are discussed in this 
appendix. 
Y2. CALCULATION OF GEOMETRICAL AND MECHANICAL PROPERTIES 
The complex geometry of the drip shield, as illustrated in Figures Y-1 to Y-4 in different views 
and sections, is three-dimensional and, as such, was considered in the analysis of its performance 
under different loads. However, in the UDEC model for rockfall predictions, the drip shield was 
approximated in two dimensions. A typical longitudinal segment in the middle of the drip shield 
equal to the spacing of 1071.6 mm between the stiffeners (Figure Y-2) was considered to be 
representative of the drip shield geometry. The geometry of the cross-sections in the top and the 
side-wall of the drip shield, as used to calculate the geometrical characteristics, are shown in 
Figures Y-4 and Y-5, respectively. The drip shield dimensions used for the calculation are listed 
in Table Y-1. The height of the sidewall stiffener varies between 86.27 mm at the top to 
27.69 mm at the base. In the UDEC approximation of the drip shield, it is considered that the 
height of the stiffener is constant, equal to 86 mm (Figure Y-5). This consideration is 
conservative, as it results in a stiffer drip shield and, consequently, larger predicted loads. The 
calculated geometrical characteristics of the two cross-sections are listed in Table Y-2. 
The drip shield was represented using a regular grid and triangular, two-dimensional zones. 
Consequently, each cross-section is rectangular with a given height, h , and unit width, b . The 
heights of the cross-sections were calculated from the moment of inertia, using the following 
formula: 
I =1 bh3 (Eq. Y-1) 
12 
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Drift Degradation Analysis 
where b = 1. The calculated heights of the rectangular cross-sections are 6.2 cm and 5.7 cm in 
the top and the sidewall of the drip shield, respectively. With these dimensions, the UDEC 
model of the drip shield matches moments of inertia of different cross-sections of the drip shield, 
but the areas of the cross-sections in the UDEC model are larger. This discrepancy has 
negligible effect on predicted displacements, because axial deformation of beams can be 
neglected in bending dominated deformation (as is the case for the drip shield). 
In order to correctly model bending of the beams, represented by the two-dimensional, 
constant-strain, continuum zones, it is necessary to have at least four or five zones per beam 
thickness. For beam 6.2 cm or 5.7 cm thick, the zone size would be of the order of 1 cm. Such a 
small zone size in the drift stability model would result in a number of numerical problems and 
very long calculation times (particularly for dynamic simulations). The product EI is the 
measure of beam stiffness, where E is the Youngs modulus. To overcome the problem of small 
zone size, the heights of the cross-sections and Youngs modulus were rescaled, maintaining the 
product EI constant, according to the following formula: 
h 3
..
EE .. (Eq. Y-2) 
= 
h
..
where E and h are rescaled values of Youngs modulus and height of the cross-section, 
respectively. Different parts of the drip shield are designed to be constructed from titanium 
grades 7 (Ti-7) and 24. Youngs moduli at 150C for Ti-7 and Ti-24 are E = 101GPa and 
E = 108 GPa, respectively (BSC 2004 [DIRS 168993]). The Poissons ratio is 0.32. It was 
considered conservatively (with small overall error) that the entire drip shield was built from 
Ti-24 (i.e., a Youngs modulus of 108 GPa). After rescaling according to Equation Y-2, a 
Youngs modulus of 3.22 GPa and cross-section heights of 20 cm and 18.3 cm in the top and the 
sidewall, respectively, were used for the drift shield in the UDEC simulations of the 
emplacement drift stability. Geometry of the drip shield, as idealized in the UDEC model, is 
shown in Figure Y-6. Because of the relatively large thickness of the drip shield in the UDEC 
model, compared to its height and span, the neutral axis of the UDEC representation was 
selected to coincide with the outline of the actual drip shield geometry. (The geometry of the 
drip shield is such that neutral axis is very close to the outline.) 
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Drift Degradation Analysis 
Source: BSC 2004 [DIRS 168993], Attachment I, p. I-2. 
NOTE: Dimensions are in inches [millimeters]. 
Figure Y-1. Geometry of the Drip Shield: Cross-Section 
Source: BSC 2004 [DIRS 168993], Attachment I, p. I-2. 
NOTE: Dimensions are in inches [millimeters]. 
Figure Y-2. Geometry of the Drip Shield: Side View 
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Drift Degradation Analysis 
Source: BSC 2004 [DIRS 168993], Attachment I, p. I-2. 
NOTE: Dimensions are in inches [millimeters]. 
Figure Y-3. Geometry of the Drip Shield: Plane View 
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Drift Degradation Analysis 
Source: BSC 2004 [DIRS 168993], Attachment I, p. I-2. 
Figure Y-4. Section A-A through the Roof of the Drip Shield Indicated in Figure Y-1 
Figure Y-5. Horizontal Section Through the Wall of the Drip Shield 
Table Y-1. Drip Shield Dimensions 
Nominal Length Nominal width Nominal Height 
5805 mm 2532.78 mm 2885.62 mm 
228.543 in 99.716 in 113.607 in 
Source: BSC 2004 [DIRS 169220], Table 1.
Table Y-2. Geometrical Characteristic of Cross-Sections 
Top Side-wall 
I [cm4] 2156.4 1617.8 
A [cm2] 214.8 226.0 
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Drift Degradation Analysis 
Figure Y-6. Geometry of the Drip Shield as Idealized in the UDEC Model 
Y3. VALIDATION OF THE DRIP SHIELD MODEL 
In order to demonstrate that the UDEC model of the drip shield correctly represents its 
deformation, two tests were carried out. In the first test, the UDEC results were compared with 
FLAC results obtained using FLAC structural element logic. The actual geometrical properties 
(shown in Table Y-1) and Youngs modulus were used in the FLAC simulations. Because of the 
plane-strain deformation of the drip shield and the plane-stress formulation of the structural 
element logic in FLAC, the Youngs modulus in the FLAC model was modified according to the 
following formula: 
E'= E 
2 (Eq. Y-3) 
1-. 
Two loading cases were considered. The results for loading case 1 (illustrated in Figure Y-7), 
the vertical concentrated force acting in the middle of the drip shield, are shown in Figures Y-8 
to Y-12. The maximum vertical displacement calculated in UDEC is 6.31 mm (Figure Y-10), 
compared to 6.05 mm calculated in FLAC (Figure Y-12). The error is 4 percent. The results for 
loading case 2 (illustrated in Figure Y-13), the horizontal concentrated force acting at the top of 
the drip shield sidewall, are shown in Figures Y-14 to Y-18. The horizontal vertical 
displacement calculated in UDEC is 1.60 cm (Figure Y-16), compared to 1.67 cm calculated in 
FLAC (Figure Y-18). The error is 4 percent in this case as well. In the second test, the UDEC 
results were compared with results obtained using the code LS-DYNA, in which the drip shield 
was modeled as a three-dimensional body. For loading case 3 (illustrated in Figure Y-19), the 
uniformly distributed load on top of the drip shield, LS-DYNA predicts vertical displacement in 
the middle of the top of the drip shield of 2.4 cm. The UDEC results are shown in Figures Y-20 
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Drift Degradation Analysis 
to Y-22. The maximum vertical displacement in the middle of the drip shield is 2.4 cm 
(Figure Y-22). 
Y4. CONCULSIONS 
The deformable drip shield is represented in the two-dimensional UDEC model using 
continuum, constant-strain zones that form beams of constant thickness. To optimize UDEC 
simulations, the thickness and Youngs modulus of beams were rescaled to maintain their 
stiffness. 
It is demonstrated that the simplified UDEC model correctly represents deformation of the drip 
shield. 
Figure Y-7. Loading Case 1 
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Drift Degradation Analysis 
Figure Y-8. Deformation (m) of the Drip Shield for Loading Case 1
NOTE: Deformation magnified 50 times. 
Figure Y-9. Original and Deformed Configuration of the Drip Shield for Loading Case 1 
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Drift Degradation Analysis 
Figure Y-10. History of Vertical Displacement (m) of a Point on the Drip Shield Where Vertical
Concentrated Force is Applied for Loading Case 1 
Figure Y-11. Deformation of FLAC Structure Elements for Loading Case 1 
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Figure Y-12. History of Vertical Displacement (m) of a Point on the Drip Shield Where Vertical 
Concentrated Force is Applied for Loading Case 1 Calculated Using FLAC Structural 
Elements 
Figure Y-13. Loading Case 2 
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Figure Y-14. Deformation (m) of the Drip Shield for Loading Case 2
NOTE: Deformation magnified 20 times. 
Figure Y-15. Original and Deformed Configuration of the Drip Shield for Loading Case 2 
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Drift Degradation Analysis 
Figure Y-16. History of Vertical Displacement (m) of a Point on the Drip Shield Where Vertical
Concentrated Force is Applied for Loading Case 2 
Figure Y-17. Deformation of FLAC Structure Elements for Loading Case 2 
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Drift Degradation Analysis 
Figure Y-18. History of Vertical Displacement (m) of a Point on the Drip Shield Where Vertical 
Concentrated Force is Applied for Loading Case 2 Calculated Using FLAC Structural 
Elements 
Figure Y-19. Loading Case 3 
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Drift Degradation Analysis 
Figure Y-20. Deformation (m) of the Drip Shield for Loading Case 3
NOTE: Deformation magnified 10 times. 
Figure Y-21. Original and Deformed Configuration of the Drip Shield for Loading Case 3 
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Drift Degradation Analysis 
Figure Y-22. History of Vertical Displacement (m) of a Point on the Drip Shield Where Vertical
Concentrated Force is Applied for Loading Case 3 
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INTENTIONALLY LEFT BLANK 
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