Multiscale Thermohydrologic Model Rev 02, ICN 00

ANL-EBS-MD-000049

October 2004 

1. PURPOSE 
The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible 
range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the 
repository emplacement drifts, including the invert, and in the adjoining host rock for the 
repository at Yucca Mountain. Thus, the goal is to predict the range of possible 
thermal-hydrologic conditions across the repository; this is quite different from predicting a 
single expected thermal-hydrologic response. The MSTHM calculates the following 
thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, 
evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and 
gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support Total 
System Performance Assessment (TSPA) Model/Analysis for the License Application (BSC 2004 
[DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position 
along each of the emplacement drifts and as a function of waste package type. These parameters 
are determined at various reference locations within the emplacement drifts, including the waste 
package and drip-shield surfaces and in the invert. The parameters are also determined at 
various defined locations in the adjoining host rock. 
The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. 
The majority of those DTNs were generated from the following analyses and model reports: 
 UZ Flow Model and Submodels (BSC 2004 [DIRS 169861]) 
 Development of Numerical Grids for UZ Flow and Transport Modeling (BSC 2004 
[DIRS 169855]) 
 Calibrated Properties Model (BSC 2004 [DIRS 169857]) 
 Thermal Conductivity of the Potential Repository Horizon (BSC 2004 [DIRS 169854]) 
 Thermal Conductivity of the Non-Repository Lithostratigraphic Layers (BSC 2004 [DIRS 
170033]) 
 Ventilation Model and Analysis Report (BSC 2004 [DIRS 169862]) 
 Heat Capacity Analysis Report (BSC 2004 [DIRS 170003]). 
The MSTHM simulations provide the Total System Performance Assessment for the License 
Application (TSPA-LA) with the thermal-hydrologic parameters (as a function of time) that 
influence the evolution of in-drift coupled flow and transport processes. The TSPA-LA then 
uses those thermal-hydrologic parameters as part of its integrated assessment of the following: 
 General corrosion of the waste package 
 Localized corrosion of the waste package 
 Waste-form degradation 
 Radionuclide solubility. 
 In-drift seepage evolution and thermal seepage 
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 Dust-leachate evolution 
 Radionuclide transport in the Engineered Barrier System 
Analysis and model reports that are directly downstream of this report include: 
 Drift Degradation Analysis 
 Evaluation of Features, Events, and Processes (FEP) for the Biosphere Model 
 Total System Performance Assessment (TSPA) Model/Analysis for the License 
Application. 
The limitations of the MSTHM include: 
 Drift seepage prediction during the post-boiling period is beyond the scope of this report 
 The predicted evaporation rate on the drip shield pertains to the case with no dripping on 
the drip shield. 
The MSTHM accounts for three-dimensional drift-scale and mountain-scale heat flow and 
captures the influence of the key engineering-design parameters and natural system factors 
affecting thermal-hydrologic conditions in the emplacement drifts and adjoining host rock. The 
natural system factors include: 
 Repository-scale spatial variability of percolation flux above the repository 
 Temporal variability of percolation flux (as influenced by climate change) 
 Uncertainty in percolation flux (as addressed by the lower-bound, mean, and 
upper-bound infiltration-flux cases) 
 Stratigraphic variation of thermal conductivity 
 Stratigraphic variation of bulk rock density and specific heat 
 Stratigraphic variation of hydrologic properties of the rock matrix 
 Stratigraphic variation of hydrologic properties of fractures 
 Variability in overburden thickness. 
The engineering-design parameters include: 
 Overall areal heat-generation density of the waste inventory, quantified by the average 
Areal Mass Loading (AML, expressed in metric tons of uranium (MTU) per acre) 
 Line-averaged thermal load along emplacement drifts, quantified by the average Lineal 
Power Density (LPD, expressed in kW/m) 
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 Distance between emplacement drifts (also called drift spacing) 
 Age of spent-nuclear fuel at time of emplacement 
 Repository footprint shape, which influences the evolution of the edge-cooling effect that 
increases with proximity to the repository edges 
 Dimensions of the in-drift design (waste packages, drip shield, and invert) 
 Properties of the in-drift engineered barrier system components 
 Waste package spacing along the drift (line-load versus point-load spacing) 
 Waste package sequencing (particularly with respect to the heat output from the 
respective waste package types) 
 Time- and distance-dependent heat-removal efficiency of preclosure drift ventilation. 
The MSTHM (Figure 1-1, Tables 1-2 and 1-3) couples the Smeared-heat-source Drift-scale 
Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermal-Hydrologic (LDTH), 
Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source 
Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water, water vapor, 
air, and heat through partially saturated fractured porous rock are adequately represented. The 
relationships between the various submodel and model types are diagrammed in Figure 1-1. The 
submodel and model types are defined in Table 1-2. All submodels use the Nonisothermal 
Unsaturated-saturated Flow and Transport (NUFT) simulation code (Nitao 1998 [DIRS 
100474]). In addition to being used within the MSTHM itself, the two-dimensional LDTH 
submodel (Section 6.2.6) is also used as a stand-alone model to conduct sensitivity analyses in 
this report. 
This report provides a description of the MSTHM concept and approach, detailing the software 
and the routines used in the MSTHM. It describes the inputs to the software and details the 
specific parameters of that data. It discusses the specific assumptions made in this modeling 
system and provides the rationale for each assumption. The report includes a description of the 
MSTHM and the specific submodel components, input-data-preparation and model-building 
steps, and the MSTHM calculation sequence. Finally, the report includes a discussion of the 
MSTHM validation in accordance with Technical Work Plan For: Near-Field Environment and 
Transport In-Drift Heat and Mass Transfer Model and Analysis Reports Integration (BSC 2004 
[DIRS 170950]). 
Appendix XIII presents a listing of list of data sources for figures and tables in this report. This 
includes the source DTN, the associated file name, and the software necessary to access the data. 
An example of accessing data temperature and saturation time history data generated from the 
MSTHAC v7.0 (Section 3.1.5), using XTOOL v10.1 (Section 3.1.4) is presented in the flow 
chart in Figure XV-1 in Appendix XV. Note that in accessing the data, it is necessary to 
download from the YMP server using the Windows Operating System, and then to use File 
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Transfer Protocol (FTP) to transfer the files to a Sun Workstation with the Sun OS 5.8 operating 
system with XTOOL v10.1 software installed. 
Table 1-1. List of Thermal-Hydrologic Parameters Predicted with the MSTHM 
Thermal-Hydrologic Parameter Drift-Scale Location 
Temperature Near-field environment host rock (5 m above crown of drift) 
Near-field environment host rock (mid-pillar at repository horizon) 
Maximum lateral extent of boiling 
Drift wall (perimeter average) 
Drip shield (perimeter average) 
Drip shield (upper surface) 
Waste package (surface average) 
Invert (average) 
Relative humidity Drift wall (perimeter average) 
Drip shield (perimeter average) 
Waste package 
Invert (average) 
Liquid-phase saturation (matrix) Drift wall (perimeter average) 
Drip shield (perimeter average) 
Invert (average) 
Liquid-phase flux Near-field environment host rock (5 m above crown of drift) 
Near-field environment host rock (3 m above crown of drift) 
Drift wall (upper surface) 
Drift wall (lower surface below invert) 
Drip shield (crown) 
Drip shield (upper surface average) 
Drip shield (lower side at the base) 
Invert (average) 
Gas-phase air-mass fraction Drip shield (perimeter average) 
Gas-phase pressure Drip shield (perimeter average) 
Capillary pressure Drip shield (perimeter average) 
Invert (average) 
Drift wall (crown, in matrix) 
Drift wall (crown, in fractures) 
Gas-phase (water vapor) flux Drift wall (perimeter average) 
Gas-phase (air) flux Drift wall (perimeter average) 
Evaporation rate Drip shield (crown) 
Drip shield (perimeter total) 
Drift wall (upper surface) 
Drift wall (lower surface below invert) 
Invert (total) 
NOTE: The invert relative humidity is not predicted by the MSTHM. It is calculated, using the MathCad 
spreadsheet described in Appendix XV, based on the MSTHM-predicted temperature and liquid-
phase saturation in the invert. 
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NOTE: SDT-, LDTH-, and DDT-submodel calculations are run with the NUFT code for different AMLs (left side). 
The SMT-submodel calculation is also run with the NUFT code. The SMT, LMTH and DMTH models are the 
series of 3-D mountain-scale models of increasing complexity (right side). The MSTHAC code assembles 
the results of the NUFT submodels in six stages, constructing intermediate parameters (AMLhstrk,eff, .Ti,j,DMTH, 
Ti,LMTH and AMLi,j-specific) and final MSTHM parameters (Ti,j,DMTH, RHi,j,DMTH and Hi,j,DMTH) from NUFT submodel 
output (TSDT, TSMT, Ti,LDTH, Hi,LDTH and .Ti,j,DDT). The submodel and model types are defined in Table 1-2. 
The parameters are defined in Table 1-3. Note that the four submodels of the MSTHM are the SDT, LDTH, 
DDT, and SMT submodels. The LMTH model is an intermediate result of the MSTHM and the DMTH model 
is the final result of the MSTHM. 
Figure 1-1. Six Stage Flow Chart Diagram of the MSTHM 
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Table 1-2. Submodel and Model Types Used in the MSTHM 
Submodel / 
Model Type Description 
MSTHM Multiscale thermohydrologic model 
SMT Smeared-heat-source, mountain-scale, thermal-conduction: three-dimensional NUFT 
submodel 
SDT Smeared-heat-source, drift-scale, thermal-conduction: one-dimensional NUFT submodel 
LDTH Line-averaged-heat-source, drift-scale, thermal-hydrologic: two-dimensional NUFT 
submodel 
DDT Discrete-heat-source, drift-scale, thermal-conduction: three-dimensional NUFT submodel 
LMTH Line-averaged-heat-source, mountain-scale, thermal-hydrologic model: three-dimensional 
MSTHM intermediate result 
DMTH Discrete-heat-source, mountain-scale, thermal-hydrologic model: three-dimensional 
MSTHM final result 
D/LMTH Discrete / line-averaged-heat-source, mountain-scale, thermal-hydrologic model: the 
nested-mesh monolithic three-dimensional NUFT model used in the MSTHM validation 
(Section 7.5) 
NOTE: The four submodels of the MSTHM are the SDT, LDTH, DDT, and SMT submodels. The LMTH 
model is an intermediate result of the MSTHM and the DMTH model is the final result of the MSTHM. 
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Table 1-3. Parameters Used in the MSTHM Methodology 
Parameter 
Name Description 
Stage 
(see Figure 
1-1) 
TSDT Host-rock temperature output from the one-dimensional SDT submodel. Stage 1 (NUFT 
output) 
TSMT Host-rock temperature output from the three-dimensional mountain-scale SMT Stage 1 (NUFT 
submodel. output) 
.Ti,j,DDT Temperature deviation of individual waste package from averaged drift-wall 
temperature for reference location i and waste package j. 
Stage 3a 
(NUFT output) 
.Ti,j,DMTH Temperature deviation of individual waste package from averaged drift-wall 
temperature for reference location i and waste package j, adjusting for three-
Stages 3a, 3b 
dimensional mountain-scale heat loss. 
Ti,LDTH Temperature output from two-dimensional LDTH drift-scale submodel. Stages 2, 4 
(NUFT output) 
Ti,LMTH Temperature for reference location i adjusted for the three-dimensional mountain Stages 2, 3b 
scale heat loss. 
Ti,j,DMTH Temperature for reference location i and waste package j adjusted for the three-Stages 3b, 4 
dimensional mountain-scale heat loss and for waste package variation. 
Hi,LDTH Set of hydrologic parameters for reference location i. This set includes RHi,LDTH Stage 5 (NUFT 
and Si,LDTH. output) 
Hi,j,DMTH Set of hydrologic parameters for reference location i and waste package j 
adjusted for three-dimensional mountain-scale heat loss and for waste package 
variation. This set includes RHi,j,DMTH and Si,j,DMTH. 
Stages 5, 6 
RHi,j,DMTH Relative humidity of the reference location i and waste package j for the DMTH Stage 5, 6 
model. 
Si,j,DMTH Liquid-phase saturation of the reference location i and waste package j for the Stage 5, 6 
DMTH model. 
Tdw,cav Perimeter averages of surfaces adjoining the open cavity outside of the drip Stage 6 
RHdw,cav shield only for the DMTH model. 
AMLhstrk,eff A time-varying parameter that incorporates the influence of three-dimensional Stages 1, 2, 3a 
mountain-scale heat-loss (determined by the combined use of the SMT and SDT 
submodels) onto the LDTH submodel results. 
AMLi,j-specific A time-varying parameter that combines the influences of waste 
package-to-waste package variation (determined by the DDT submodels) and 
three-dimensional mountain-scale heat loss (represented by the LMTH-modeled 
temperatures), resulting in DMTH-model results for reference location i and 
waste package j. 
Stages 4, 5 
Psat Saturated vapor pressure, which is a function of temperature. Stage 6 
NOTE: Subscript i refers to a reference location in the drift (or host rock); i = dw refers to drift wall, i = ds refers 
to drip shield, i = in refers to invert, and i = wp refers to waste package. Subscript j refers to the waste 
package type, such as j = DHLW, 21-PWR CSNF, or 44-BWR CSNF. The MSTHM calculation 
sequence is described in detail in Section 6.2.4. 
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2. QUALITY ASSURANCE 
The Quality Assurance program applies to the development of this document (BSC 2004 [DIRS 
170950], Section 8.1). This document was prepared in accordance with Technical Work Plan 
for: Near-Field Environment and Transport In-Drift Heat and Mass Transfer Model and 
Analysis Reports Integration (BSC 2004 [DIRS 170950]), which directs the work identified in 
work package ARTM02. The technical work plan (TWP) was prepared in accordance with 
AP-2.27Q, Planning for Science Activities. There were no variances from the planned activities. 
The methods used to control the electronic management of data are identified in the TWP (BSC 
2004 [DIRS 170950], Section 8.4) and were implemented without variance. As directed in the 
TWP, this document was prepared in accordance with AP-SIII.10Q, Models; LP-SI.11Q-BSC, 
Software Management; AP-3.15Q, Managing Technical Product Inputs; and reviewed in 
accordance with AP-2.14Q, Document Review. As needed, unqualified project data is qualified 
in this document in accordance with AP-SIII.2Q, Qualification of Unqualified Data. 
The work scope described in this report has been determined to be subject to the U.S. 
Department of Energys (DOEs) Quality Assurance Requirements and Description (DOE 2004 
[DIRS 171539]). The work scope of this report involves conducting investigations or analyses 
of Engineered Barrier System components contained in Q-List (BSC 2004 [DIRS 168361]). 
Safety Categories for the components are provided in Table 2-1. 
Table 2-1. Engineered Barrier System Components Addressed in This Report, Listed with 
Corresponding Safety Category (SC) Level 
Engineered Barrier System Component Safety Category 
Drip Shield SC 
Drift Invert (Steel) SC 
Emplacement Drift Excavated Opening SC 
DOE and Commercial Waste Packages SC 
Source: BSC 2004 [DIRS 168361]. 
Furthermore, this report provides analysis of model results supporting performance assessment 
activities for the Total Systems Performance Assessment for License Application. 
This report documents the determination of in-drift thermal-hydrologic conditions that are 
required by TSPA-LA. It provides in-drift thermal-hydrologic parameters that are important to 
the performance of the engineered barriers classified in 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. The results of this report are important 
to the demonstration of compliance with the postclosure performance objectives prescribed in 
10 CFR 63.113. 
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3. USE OF SOFTWARE 
A complete list of the software and the associated software tracking number is given in Table 3-1. 
Table 3-1. Software Used 
Software Name and Version 
Software 
Tracking 
Number 
Software 
Qualification 
Status 
Computers Used to 
Run Software (DOE 
Property Number) 
Sections Where 
Software Output 
Is Useda 
NUFT v3.0s 10088-3.0s-02 Qualified 6549273, 6549266, 
6700902, 6290847, 
6426406, 6290830, 
6877864, 6481320, 
6290823, 6813251, 
6877857, 6524867, 
6878182, 6575968, 
6274861, 6813244, 
6877840, 6549297 
6.2, 6.3, 6.4, 7.3, 
7.5, 8.3 
NUFT v3.0.1s 10130-3.0.1s-01 Qualified 6700902, 6426406, 
6290830 
7.4, 7.5 
RADPRO v4.0 10204-4.0-00 Qualified 6877840, 6878182 6.2, 6.3, 8.3 
XTOOL v10.1 10208-10.1-00 Qualified 6496843 6.2, 6.3, 6.4, 7.3, 
7.4, 7.5 
MSTHAC v7.0 10419-7.0-00 Qualified 6813251, 6290830, 
6878182 
6.2, 6.3, 7.5, 8.3 
readsUnits v1.0 10602-1.0-00 Qualified 6371317 6.2, 6.3, 7.4, 7.5, 
8.3 
YMESH v1.54 10172-1.54-00 Qualified 6813251, 6813244, 
6877864, 6878182 
6.2, 6.3, 7.4, 7.5, 
8.3 
boundary_conditions v1.0 11042-1.0-00 Qualified 6877840 6.3, 7.4, 8.3 
heatgen_ventTable_emplace v1.0 11039-1.0-00 Qualified 6813251 6.3, 8.3 
rme6 v1.2 10617-1.2-00 Qualified 6813251 6.3, 8.3 
xw v1.0 11035-1.0-00 Qualified 6813251 6.3, 8.3 
colCen v1.0 11043-1.0-00 Qualified 6877840 6.3, 8.3 
repository_percolation_calculator 
v1.0 
11041-1.0-00 Qualified 6813251 6.3, 8.3 
extractBlocks_EXT v1.0 11040-1.0-00 Qualified 6877857 6.3, 8.3 
Chimney_interpolate v1.0 11038-1.0-00 Qualified 6813251, 6290830 6.3, 8.3 
reformat_EXT_to_TSPA v1.0 11061-1.0-00 Qualified 6813251, 6290830, 6.3, 8.3 
6878182 
a 
These are the sections that directly or indirectly utilize the output from the listed software. 
3.1 QUALIFIED SOFTWARE 
The software described in this section is used in the data-flow diagrams (Figures 6-1 and 6-2) of 
Section 6. The computer software was qualified under procedure AP-SI.2Q, Qualification of 
Level A Software, before procedure LP-SI.11Q-BSC became effective and is therefore part of the 
established baseline in accordance with Section 2.0 of LP-SI.11Q-BSC. Because many of these 
items have to process or produce files consistent with NUFT formats and have been validated for 
this use, they are the only software appropriate for their tasks. 
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3.1.1 NUFT v3.0s 
NUFT v3.0s (NUFT V3.0s, STN: 10088-3.0s-02 [DIRS 164541]) is baselined as qualified 
software per LP-SI.11Q-BSC, Software Management, and is used to conduct all of the submodel 
calculations required by the MSTHM. NUFT v3.0s was obtained from software configuration 
management and run on Sun workstations with the Sun OS 5.8 operating system. NUFT v3.0s 
was selected because it solves the governing equations of the mathematical model (Section 6.2), 
is supported by a suite of special-purpose software that completes implementation of the 
MSTHM, and imposes no limitations on outputs. As discussed below, the use of NUFT v3.0s 
for the submodel calculations was within the documented validation range of the software. 
Therefore, the use of this software was consistent with its intended use. 
NUFT v3.0s (and v3.0.1s) is a general-purpose code for simulating mass and heat transport in 
fractured porous media. Because NUFT is based on the conservation of mass and energy, it is 
valid for any such calculation, provided the mass- and heat-transport parameters are used within 
their validation ranges. In other words, what limits the range of validation of NUFT are the 
mass- and heat-transport-phenomena-related parameters (or constitutive properties), such as 
thermal conductivity, which affects heat conduction, and permeability, which affects gas- and 
liquid-phase flow. Thus, if thermal conductivity and permeability are applicable for the range of 
predicted temperatures, the software (NUFT) is valid for this range. The validation range and 
limitation of applicability of NUFT is determined by the validation studies conducted in 
conjunction with the Large Block Test (Section 7.3) and the Drift Scale Test (Section 7.4). 
Comparisons of the NUFT-predicted temperatures with the measured temperatures in those tests 
show that NUFT meets the validation requirement described in Technical Work Plan for: 
Near-Field Environment and Transport In-Drift Heat and Mass Transfer Model and Analysis 
Reports Integration (BSC 2004 [DIRS 170950]). Because measured temperatures in the Drift 
Scale Test are as great as 280C in the rock, the validation range of NUFT is up to 280C in the 
host rock. In Section 6.3.4, which summarizes the range of thermal-hydrologic conditions 
predicted for the TSPA-LA, it is shown that the maximum peak drift-wall and waste package 
temperatures are 175.2 and 203.1C, respectively (Table 6.3-38). Therefore, NUFT was applied 
within its validation limits for the TSPA-LA. 
3.1.2 NUFT v3.0.1s 
NUFT v3.0.1s (NUFT V3.0.1s, STN: 10130-3.0.1s-01 [DIRS 166636]) is baselined as qualified 
software per LP-SI.11Q-BSC, and is used to conduct all of the nested-mesh model calculations 
in the model validation exercises for the MSTHM. NUFT v3.0.1s was obtained from software 
configuration management and run on Sun workstations with the Sun OS 5.8 operating system. 
NUFT v3.0.1s was selected because nested meshes are a feature of this newer version. Because 
its use was within the documented validation range of the software (see Section 3.1.1), it was 
consistent with its intended use. 
3.1.3 RADPRO v4.0 
RADPRO v4.0 (RADPRO V4.0, STN: 10204-4.0-00 [DIRS 164273]) is baselined as qualified 
software per LP-SI.11Q-BSC, and was obtained from software configuration management and 
run on a Sun workstation with a SunOS 5.8 (Solaris 8) operating system. RADPRO v4.0 was 
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selected because it calculates the radiative heat transfer coefficients in the emplacement drift in 
accordance with Equation 10 of Section 6.2.3.3 without limitations on its output. Its use was 
consistent with its intended use and within the documented validation range of the software. 
Because this software is only used to conduct simple arithmetic functions, it is not applicable to 
identify validation ranges or limitations of use. 
3.1.4 XTOOL v10.1 
XTOOL v10.1 (XTOOL V10.1, STN: 10208-10.1-00 [DIRS 148638]) is baselined as a qualified 
software routine per LP-SI.11Q-BSC, and was obtained from software configuration 
management and run on a Sun workstation with a SunOS 5.6.1 operating system. XTOOL v10.1 
is used to generate graphical representations of the results given in the NUFT and MSTHAC 
v7.0 time-history files (which are files with the suffix: *.ext). XTOOL v10.1 is the only 
appropriate software for this task. Because this software is only used to generate graphical 
displays of data, it is not applicable to identify validation ranges or limitations of use. 
3.1.5 MSTHAC v7.0 
MSTHAC v7.0 (MSTHAC V7.0, STN: 10419-7.0-00 [DIRS 164274]) is baselined as qualified 
software per LP-SI.11Q-BSC, and was obtained from software configuration management and 
run on a Sun workstation with a SunOS 5.8 (Solaris 8) operating system. MSTHAC v7.0 
integrates the results of NUFT submodel calculations to predict the multiscale 
thermal-hydrologic conditions in the emplacement drifts and adjoining host rock throughout the 
repository area. MSTHAC v7.0 is the only appropriate software for this task. Because 
MSTHAC integrates the results of NUFT submodel calculations, its validation range is the same 
as that described for NUFT v3.0s (Section 3.1.1). 
3.1.6 readsUnits v1.0 
Software routine readsUnits v1.0 (readsUnits V1.0, STN: 10602-1.0-00 [DIRS 164542]) is 
baselined as qualified software per LP-SI.11Q-BSC, and was obtained from software 
configuration management and run on a Sun workstation with a SunOS 5.5.1 operating system. 
This code reads YMESH-generated data describing a stratigraphic column and generates 
comment lines for NUFT input files that summarize the thicknesses of each of the 
hydrostratigraphic units (also called UZ model layers) in that column. Software routine 
readsUnits v1.0 is the only appropriate software for this task. Because this software is only used 
to generate comment lines in the NUFT input files, it does not influence any model predictions. 
Therefore, it is not applicable to identify validation ranges or limitations of use. 
3.1.7 YMESH v1.54 
YMESH v1.54 (YMESH v1.54, STN: 10172-1.54-00 [DIRS 163894]) is baselined as qualified 
software per LP-SI.11Q-BSC, and was obtained from software configuration management and 
run on a Sun workstation with a SunOS 5.8 (Solaris 8) operating system. YMESH v1.54 is used 
to generate the thicknesses of the hydrostratigraphic units (also called the UZ model layers) in 
the various MSTHM submodels based upon the grids from Development of Numerical Grids for 
UZ Flow and Transport Modeling (BSC 2004 [DIRS 169855]). YMESH v1.54 is the only 
appropriate software for this task. Because this software is only used to generate numerical grids 
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on the basis of geometric relationships, it is not applicable to identify validation ranges or 
limitations of use. 
3.1.8 boundary_conditions v1.0 
The software routine boundary_conditions v1.0 (boundary_conditions V 1.0, STN: 11042-1.0-
00 [DIRS 164275]) is baselined as qualified software per LP-SI.11Q-BSC, and was obtained 
from software configuration management and run on a Sun workstation with a SunOS 5.8 
(Solaris 8) operating system. The purpose of this routine is to generate upper and lower 
boundary conditions for the LDTH, SMT, and SDT submodels of the MSTHM (Section 6.2), as 
well as for other models such as the three-dimensional thermal-hydrologic model for the Drift 
Scale Test (DST) (Section 7.4). The software routine boundary_conditions v1.0 is the only 
appropriate software for this task. Because this software is only used to conduct simple 
interpolations of data, it is not applicable to identify validation ranges or limitations of use. 
3.1.9 heatgen_ventTable_emplace v1.0 
The software routine heatgen_ventTable_emplace v1.0 (heatgen_ventTable_emplace V1.0, 
STN: 11039-1.0-00 [DIRS 164276]) is baselined as qualified software per LP-SI.11Q-BSC, and 
was obtained from software configuration management and run on a Sun workstation with a 
SunOS 5.8 (Solaris 8) operating system. The software routine heatgen_ventTable_emplace v1.0 
modifies a heat-generation-rate-versus-time table in two ways. First, it can age the 
heat-generation table by adding a specified number of years to the time entries. Second, it can 
account for the heat-removal efficiency of ventilation by multiplying the heat-generation-rate 
values by a specified fraction during the specified ventilation period. The software routine 
heatgen_ventTable_emplace v1.0 also can incorporate the dependence of the heat-removal 
efficiency table on distance (along the emplacement drift) from the ventilation inlet. The 
software routine heatgen_ventTable_emplace v1.0 is the only appropriate software for this task. 
Because this software is only used to conduct simple arithmetic functions, it is not applicable to 
identify validation ranges or limitations of use. 
3.1.10 rme6 v1.2 
The software routine rme6 v1.2 (rme6 v1.2, STN: 10617-1.2-00 [DIRS 163892]) is baselined as 
qualified software per LP-SI.11Q-BSC, and was obtained from software configuration 
management and run on a Sun workstation with a SunOS 5.8 (Solaris 8) operating system. This 
code converts the grid from Development of Numerical Grids for UZ Flow and Transport 
Modeling (BSC 2004 [DIRS 169855]) to a format that is readable by YMESH v1.54 (Section 
3.1.7). The software routine rme6 v1.2 is the only appropriate software for this task. Because 
this software is only used to reformat input data for YMESH v1.54, it is not applicable to 
identify validation ranges or limitations of use. 
3.1.11 xw v1.0 
The software routine xw v1.0 (xw V1.0, STN: 11035-1.0-00 [DIRS 164278]) is baselined as 
qualified software per LP-SI.11Q-BSC, and was obtained from software configuration 
management and run on a Sun workstation with a SunOS 5.8 (Solaris 8) operating system. The 
software routine xw v1.0 extends the grid from the three-dimensional unsaturated zone (UZ) 
ANL-EBS-MD-000049 REV 02 3-4 October 2004 

Multiscale Thermohydrologic Model 
flow model in the horizontal direction for the purpose of building mountain-scale submodels that 
extend laterally beyond the grid of the three-dimensional UZ flow model. The software routine 
xw v1.0 is the only appropriate software for this task. Because this software is only used to 
horizontally extend the grid of the three-dimensional UZ flow model, it is not applicable to 
identify validation ranges or limitations of use. 
3.1.12 colCen v1.0 
The software routine colCen v1.0 (colCen V1.0, STN: 11043-1.0-00 [DIRS 164279]) is 
baselined as qualified software per LP-SI.11Q-BSC, and was obtained from software 
configuration management and was run on a Sun workstation with a SunOS 5.8 (Solaris 8) 
operating system. The purpose of colCen v1.0 grid is to determine the gridblock column in the 
three-dimensional UZ flow model in which a given gridblock column in a MSTHM submodel 
resides. The software routine colCen v1.0 is the only appropriate software for this task. Because 
this software is only used to identify the UZ flow-model gridblock column in which a MSTHM 
submodel resides, it is not applicable to identify validation ranges or limitations of use. 
3.1.13 repository_percolation_calculator v1.0 
The software routine repository_percolation_calculator v1.0 (repository_percolation_calculator 
V1.0, STN: 11041-1.0-00 [DIRS 164280]) is baselined as qualified software per LP-SI.11Q-
BSC, and was obtained from software configuration management and run on a Sun workstation 
with a SunOS 5.8 (Solaris 8) operating system. The purpose of 
repository_percolation_calculator v1.0 is to determine the value of percolation flux for each of 
the LDTH submodels based on the percolation flux map from the three-dimensional UZ flow 
model. The software routine repository_percolation_calculator v1.0 is the only appropriate 
software for this task. Because this software is only used to conduct simple arithmetic functions, 
it is not applicable to identify validation ranges or limitations of use. 
3.1.14 extractBlocks_EXT v1.0 
The software routine extractBlocks_EXT v1.0 (extractBlocks_EXT V1.0, STN: 11040-1.0-00 
[DIRS 164281]) is baselined as qualified software per LP-SI.11Q-BSC, and was obtained from 
software configuration management and run on a Sun workstation with a SunOS 5.8 (Solaris 8) 
operating system. The purpose of extractBlocks_EXT is to determine the effective thermal 
conductivity for the gridblocks in the drift cavity of an LDTH submodel based on a correlation 
accounting for the influence of natural convection (Francis et al. 2003 [DIRS 164602], Table 6). 
The software routine extractBlocks_EXT v1.0 is the only appropriate software for this task. 
Because this software is only used to conduct simple arithmetic functions, it is not applicable to 
identify validation ranges or limitations of use. 
3.1.15 Chimney_interpolate v1.0 
The software routine Chimney_interpolate v1.0 (Chimney_interpolate V1.0, STN: 11038-1.0-00 
[DIRS 164271]) is baselined as qualified software per LP-SI.11Q-BSC, and was obtained from 
software configuration management and run on a Sun workstation with a SunOS 5.8 (Solaris 8) 
operating system. The purpose of Chimney_interpolate is to create a set of virtual SDT and 
LDTH chimney submodels from the 108 real chimney submodels (see Appendix VII) for 
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Multiscale Thermohydrologic Model 
more details). The virtual chimney submodels are an input to the MSTHAC v7.0 
micro-abstraction process (see Appendix VII for more details). The software routine 
Chimney_interpolate v1.0 is the only appropriate software for this task. Because this software is 
only used to conduct simple arithmetic functions, it is not applicable to identify validation ranges 
or limitations of use. 
3.1.16 reformat_EXT_to_TSPA v1.0 
The software routine reformat_EXT_to_TSPA v1.0 (reformat_EXT_to_TSPA V1.0, 
STN: 11061-1.0-00 [DIRS 164272]) is baselined as qualified software per LP-SI.11Q-BSC, and 
was obtained from software configuration management and run on a Sun workstation with a 
SunOS 5.8 (Solaris 8) operating system. The purpose of reformat_EXT_to_TSPA v1.0 is to 
post-process the micro-abstraction data produced by MSTHAC V7.0 (see Appendix VII for more 
details). The processing includes finding the typical waste package and location from a set of 
locations forming a bin and writing an output file in a format specified by the TSPA-LA 
organization. The software routine reformat_EXT_to_TSPA v1.0 is the only appropriate 
software for this task. Because this software is only used to reformat MSTHM output data, it is 
not applicable to identify validation ranges or limitations of use. 
3.2 OTHER SOFTWARE 
Commercial off-the-shelf software was used in the creation of tables and figures shown in this 
document as well as some data processing. 
The figures can be divided into the following types: line plots showing time histories, contour 
plots showing the variation in some property at a particular point in time for a cross sectional 
area of interest, plots showing material properties for the repository plan view, and schematic 
drawings showing repository design parameters. 
Contour plots were created using tecplot v9.2-0-3 (09-16-2002). 
Plots showing material properties for the repository plan view were created using Matlab 
v6.1.0.450 release 12.1. 
Mathcad 11.2a Professional was used to perform the calculations in Appendices X, XII and XV 
for developing the hydrologic properties of the invert; for comparing percolation fluxes, and for 
prediction of RH in the invert, respectively. 
Schematic drawings showing repository design information were created using Adobe 
Illustrator v8.0. 
Microsoft Excel 2000 9.0.4402 SR-1 was used to process data for the development of chimney 
percolation data as detailed in Appendix I. 
Numerical results from the use of commercial off-the-shelf software in this report are not 
dependent on the software used. The documentation of each such use includes sufficient detail 
to allow an independent reviewer to reproduce or verify the results by visual inspection or hand 
calculation. 
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Multiscale Thermohydrologic Model 
4. INPUTS 
4.1 DIRECT INPUTS 
Data, parameters, design information, and other model/analyses inputs are compiled and 
presented in Table 4.1-1. There are seven major sections of the table: (1) geometry of the 
engineered system, (2) geometry of the natural system, (3) properties of the engineered system 
inside the emplacement drift, (4) properties of the natural system, (5) boundary conditions of the 
natural system, (6) distribution of percolation flux just below the base of the PTn unit, and 
(7) waste package heat-generation data and ventilation heat-removal efficiency. The seven 
sections are further delineated to distinguish separate data, design information, and parameters. 
The majority of the information compiled in Table 4.1-1, which is direct input, falls into the 
parameter and design information categories. 
In Table 4.1-1, most of the direct inputs to this report are traced to current qualified project data 
or to qualified data that have been superseded with small changes. One exception is the 
emissivity range for rock, which is from Incropera and DeWitts (1996 [DIRS 108184]) 
advanced textbook for heat and mass transfer. Their range of 0.88 to 0.95 is adapted from 
sources for hemispherical emissivity of rock at 300 K and is corroborated by handbook values 
(Knudsen et al. 1984 [DIRS 170057], pp. 10-51 to 10-52, Table 10-17) for normal emissivity of 
rough silica and rough fused quartz, which range from 0.80 to 0.93. Therefore, the information 
is qualified for its use as emissivities of drift wall and crushed tuff in the MSTHM calculations. 
The design of the repository continued to evolve during and after the calculations with the 
MSTHM. The effects of small changes in the design are discussed in Sections 4.1.2.1 through 
4.1.2.8 
4.1.1 Data, Parameters, and Parameter Uncertainty 
The data and parameters required as input for the development of parameter values used in the 
models/analyses documented in this report are summarized in Table 4.1-1. The following 
sections of the table include information about parameters: geometry of natural system, invert 
thermal and hydrologic properties, hydrologic properties of all hydrostratigraphic units (also 
called UZ model layers), bulk thermal properties of the UZ model layers, and percolation flux 
below the base of the PTn unit. All of these data were obtained from studies specific to the 
Yucca Mountain site and are therefore appropriate for use in the MSTHM calculations reported 
in Section 6.3. 
Sections 6.3.2, 6.3.4, and 6.3.0 provide analyses of the impact of uncertainty of key natural 
system parameters. Sections 6.3.11 and 6.3.12 provide analyses of the impact of uncertainty of 
key engineered system parameters. 
4.1.2 Design Information 
Other inputs required for the development of parameter values used in the models/analyses 
documented in this report take the form of design information, often from Interface Exchange 
Drawings (IEDs). The following sections of Table 4.1-1 include design information: geometry 
of the engineered system, waste package thermal properties, drip shield thermal properties, 
ANL-EBS-MD-000049 REV 02 4-1 October 2004 

Multiscale Thermohydrologic Model 
drift-wall emissivity and waste package heat generation and ventilation heat-removal efficiency. 
Information from IEDs is appropriate for use in the MSTHM calculations reported in Section 
6.3. 
Table 4.1-1. Summary of Input Data and Information Required by the MSTHM 
Model Input Value Source 
Geometry of the Engineered System: Design Information 
Repository emplacement-drift layout 
(elevations and end-point coordinates for 
each emplacement drift) 
See IED BSC 2003 [DIRS 161727] 
Drift spacing 81 m BSC 2004 [DIRS 168489], Table 1 
Waste package spacing 0.1 m BSC 2004 [DIRS 168489], Table 1 
Drift diameter 5.5 m BSC 2004 [DIRS 168489], Table 1 
Location of 21-PWR AP WP centerline 
above invert 
1018 mm BSC 2004 [DIRS 167040] 
Invert height from bottom of drift 0.806 m BSC 2003 [DIRS 164101] 
21-PWR AP WP length 5.165 m BSC 2003 [DIRS 165406], Table 1 
21-PWR AP WP diameter 1.644 m BSC 2003 [DIRS 165406], Table 1 
21-PWR CR WP diameter 1.644 m BSC 2003 [DIRS 165406], Table 1 
21-PWR AP WP inner-vessel thickness 0.0508 m BSC 2004 [DIRS 169472], Table 1 
21-PWR AP WP outer-barrier thickness 0.020 m BSC 2004 [DIRS 169472], Table 1 
Nominal quantity of 21-PWR AP waste 
packages in LA-design inventory 
4299 BSC 2004 [DIRS 169472], Table 11 
Nominal quantity of 21-PWR CR waste 
packages in LA-design inventory 
95 BSC 2004 [DIRS 169472], Table 11 
44-BWR WP length 5.165 m BSC 2003 [DIRS 165406], Table 1 
44-BWR WP diameter 1.674 m BSC 2003 [DIRS 165406], Table 1 
44-BWR WP inner-vessel thickness 0.0508 m BSC 2004 [DIRS 169472], Table 1 
44-BWR WP outer-barrier thickness 0.020 m BSC 2004 [DIRS 169472], Table 1 
Nominal quantity of 44-BWR AP waste 
packages in LA-design inventory 
2831 BSC 2004 [DIRS 169472], Table 11 
5 DHLW/DOE SNF-LONG WP length 5.217 m BSC 2003 [DIRS 165406], Table 1 
5 DHLW/DOE SNF-LONG WP diameter 2.110 m BSC 2003 [DIRS 165406], Table 1 
5 DHLW/DOE SNF-LONG WP 
inner-vessel thickness 
0.0508 m BSC 2004 [DIRS 169472], Table 1 
5 DHLW/DOE SNF-LONG WP 
outer-barrier thickness 
0.0254 m BSC 2004 [DIRS 169472], Table 1 
Nominal quantity of 5 DHLW/DOE 
SNF-LONG waste packages in LA-design 
inventory 
1406 BSC 2004 [DIRS 169472] Table 11 
5 DHLW/DOE SNF-SHORT WP length 3.590 m BSC 2003 [DIRS 165406], Table 1 
5 DHLW/DOE SNF-SHORT WP diameter 2.110 m BSC 2003 [DIRS 165406], Table 1 
5 DHLW/DOE SNF-SHORT WP 
inner-vessel thickness 
0.0508 m BSC 2004 [DIRS 169472], Table 1 
5 DHLW/DOE SNF-SHORT WP 
outer-barrier thickness 
0.0254 m BSC 2004 [DIRS 169472], Table 1 
Nominal quantity of 5 DHLW/DOE 
SNF-SHORT waste packages in LA-
design inventory 
1147 BSC 2004 [DIRS 169472], Table 11 
Drip-shield length 6.105 m BSC 2003 [DIRS 171024], Sheet 2 
Drip-shield width 2.512 m BSC 2003 [DIRS 171024], Sheet 2 
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Multiscale Thermohydrologic Model 
Table 4.1-1. Summary of Input Data and Information Required by the MSTHM (Continued) 
Model Input Value Source 
Drip-shield thickness (plate-1 or plate-2) 0.015 m BSC 2004 [DIRS 169220], Table 5 
Intersection of drip-shield plate-1 with 
drip-shield plate-2 from base/top of invert 
1875 mm BSC 2003 [DIRS 171024], Sheet 2 
Total nominal quantity of waste package in 
LA-design inventory 
11,184 BSC 2004 [DIRS 169472], Table 11 
Geometry of Natural System: Parameters 
Grid of three-dimensional 
Unsaturated-Zone Flow and Transport 
Model: element/connection file 
Entire File DTN: LB03023DKMGRID.001 [DIRS 162354], 
File: Grid_LA_3D.mesh 
Grid of three-dimensional 
Unsaturated-Zone Flow and Transport 
Model: vertices file 
Entire File DTN: LB03023DKMGRID.001 [DIRS 162354], 
File: grid2002.grd 
Properties of the Engineered System 
Invert Thermal and Hydrologic Properties: Parameters 
Intragranular permeability (tswM5, tsw35 
matrix continuum for mean infiltration-flux 
property set) 
4.48  10-18 m2 DTN: LB0208UZDSCPMI.002 [DIRS 161243] 
Porosity of crushed-tuff grains (tswM5, 
tsw35 matrix continuum for mean 
infiltration-flux property set) 
0.131 DTN: LB0208UZDSCPMI.002 [DIRS 161243] 
Intragranular van Genuchten a (tswM5, 
tsw35 matrix continuum for mean 
infiltration-flux property set) 
1.08  10-5 1/Pa DTN: LB0208UZDSCPMI.002 [DIRS 161243] 
Intragranular van Genuchten m (tswM5, 
tsw35 matrix continuum for mean 
infiltration-flux property set) 
0.216 DTN: LB0208UZDSCPMI.002 [DIRS 161243] 
Intragranular residual saturation (tswM5, 
tsw35 matrix continuum for mean 
infiltration-flux property set) 
0.12 DTN: LB0208UZDSCPMI.002 [DIRS 161243] 
Invert Thermal and Hydrologic Properties: Data 
Bulk Density of 4-10 crushed tuff Table IV-8 in 
Appendix IV 
DTN: GS020183351030.001 [DIRS 163107] 
Specific heat of 4-10 crushed tuff Table IV-9 in 
Appendix IV 
DTN: GS000483351030.003 [DIRS 152932] 
Thermal conductivity of 4-10 crushed tuff Table IV-9 in 
Appendix IV 
DTN: GS000483351030.003 [DIRS 152932] 
Emissivity (upper invert surface) 0.88 to 0.95 Incropera and DeWitt 1996 [DIRS 108184], 
Table A.11 for Rocks 
Range in maximum void ratio for 
United Soils Classification type SP, 
which are poorly graded sands and 
gravelly sands. 
0.67 to 0.94 Hilf 1975 [DIRS 169699], Table 7.3, p. 257 
Waste Package Thermal Properties: Design Information 
Weight of 21-PWR AP WP 43,000 kg BSC 2003 [DIRS 165406], Table 1 
Weight of 44-BWR WP 43,000 kg BSC 2003 [DIRS 165406], Table 1 
Weight of 5 DHLW/DOE SNF-SHORT WP 39,000 kg BSC 2003 [DIRS 165406], Table 1 
Weight of 5 DHLW/DOE SNF-LONG 57,000 kg BSC 2003 [DIRS 165406], Table 1 
Emissivity of Alloy 22 (at T=650C), which 
is the outer barrier of the following WPs: 
21-PWR AP, 44-BWR, 5 DHLW/DOE 
SNF-SHORT, 5 DHLW/DOE SNF-LONG 
0.87 DTN: MO0003RIB00071.000 [DIRS 148850] 
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Multiscale Thermohydrologic Model 
Table 4.1-1. Summary of Input Data and Information Required by the MSTHM (Continued) 
Model Input Value Source 
Mass density of Alloy 22 (N06022), which 
is the outer barrier of the following WPs: 
21-PWR AP, 44-BWR, 5 DHLW/DOE 
SNF-SHORT, 5 DHLW/DOE SNF-LONG 
8690 kg/m3 DTN: MO0003RIB00071.000 [DIRS 148850] 
Mass density of Stainless Steel Type 316, 
which is the inner vessel of the following 
WPs: 21-PWR AP, 44-BWR, 
5 DHLW/DOE SNF-SHORT, 5 
DHLW/DOE SNF-LONG 
7.98 g/cm3 Table XI of ASTM G 1-90 [DIRS 103515] 
Mass density of the internal cylinder of the 
21-PWR AP WP 
3495 kg/m3 BSC 2004 [DIRS 169990], Table 20 
Mass density of the internal cylinder of the 
44-BWR WP 
3342 kg/m3 BSC 2004 [DIRS 169990], Table 20 
Mass density of the internal cylinder of the 
5 DHLW/DOE SNF-SHORT WP 
2175 kg/m3 BSC 2004 [DIRS 169990], Table 20 
Mass density of the internal cylinder of the 
5 DHLW/DOE SNF-LONG WP 
2302 kg/m3 BSC 2004 [DIRS 169990], Table 20 
Thermal conductivity of Alloy 22 
(at T = 373.15 K), which is the outer 
barrier of the following WPs: 21-PWR AP, 
44-BWR, 5 DHLW/DOE SNF-SHORT, 5 
DHLW/DOE SNF-LONG 
11.1 W/mK DTN: MO0107TC239938.000 [DIRS 169995], 
p. 13 
Thermal conductivity of Stainless Steel 
Type 316, which is the inner vessel of the 
following WPs: 21-PWR AP, 44-BWR, 5 
DHLW/DOE SNF-SHORT, 5 DHLW/DOE 
SNF-LONG 
8.4 BTU/hr-ft-F at 
200F 
8.7 BTU/hr-ft-F at 
250F 
ASME 1995, Section II-D, Table TCD, p. 606 
Thermal diffusivity of Stainless Steel Type 
316, which is the inner vessel of the 
following WPs: 21-PWR AP, 44-BWR, 5 
DHLW/DOE SNF-SHORT, 5 DHLW/DOE 
SNF-LONG 
0.141 ft2/hr at 200F 
0.143 ft2/hr at 250F 
ASME 1995, Section II-D, Table TCD, p. 606 
Thermal conductivity of the internal 
cylinder of the following WPs: 21-PWR 
AP, 44-BWR, 5 DHLW/DOE SNF-SHORT, 
5 DHLW/DOE SNF-LONG 
1.5 W/mK BSC 2004 [DIRS 169990], Table 20 
Specific heat of Alloy 22 (at T = 373.15 K, 
or 212F), which is the outer barrier of the 
following WPs: 21-PWR AP, 44-BWR, 5 
DHLW/DOE SNF-SHORT, 5 DHLW/DOE 
SNF-LONG 
423.0 J/kgK DTN: MO0107TC239938.000 [DIRS 169995], 
p. 13 
Specific heat of the internal cylinder of the 
21-PWR AP WP 
378.0 J/kgK BSC 2004 [DIRS 169990], Table 20 
Specific heat of the internal cylinder of the 
44-BWR WP 
395.0 J/kgK BSC 2004 [DIRS 169990], Table 20 
Specific heat of the internal cylinder of the 
5 DHLW/DOE SNF-SHORT WP 
718.0J/kgK BSC 2004 [DIRS 169990], Table 20 
Specific heat of the internal cylinder of the 
5 DHLW/DOE SNF-LONG WP 
731.0 J/kgK BSC 2004 [DIRS 169990], Table 20 
Drip-Shield Thermal Properties: Design Information 
Nominal weight of drip shield (for a 
nominal length of 5.805 m) 
5000 kg BSC 2004 [DIRS 169220], Table 1 
Mass density of titanium 0.163 lb/in3 ASME 1995, Section II-D, Table NF-2, p. 620 
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Multiscale Thermohydrologic Model 
Table 4.1-1. Summary of Input Data and Information Required by the MSTHM (Continued) 
Model Input Value Source 
Distribution of Percolation Flux Below PTn Unit: Parameters 
Percolation Flux from PTn to TSw unit for 
mean infiltration-flux case (twodimensional 
map of PTn-to-TSw 
percolation flux) 
Entire DTN DTN: LB0302PTNTSW9I.001 [DIRS 162277] 
Percolation Flux from PTn to TSw unit for 
upper-bound infiltration-flux case (twodimensional 
map of PTn-to-TSw 
percolation flux) 
Entire DTN DTN: LB0302PTNTSW9I.001 [DIRS 162277] 
Percolation Flux from PTn to TSw unit for 
lower-bound infiltration-flux case (twodimensional 
map of PTn-to-TSw 
percolation flux) 
Entire DTN DTN: LB0302PTNTSW9I.001 [DIRS 162277] 
Probabilities of the three infiltration-flux 
cases 
See Table 6.3-35 BSC 2003 [DIRS 165991], Table 6.3-2 
Waste Package Heat-Generation and Ventilation Heat-Removal Efficiency: Design Information 
Heat-generation rate history for entire 
repository 
See IED BSC 2004 [DIRS 167369], Table 13 
Average initial heat-generation rate per 
meter 
1.45 kW/m BSC 2004 [DIRS 168489], Table 1 
Ventilation-period duration 50 years after final 
emplacement 
BSC 2004 [DIRS 168489], Table 1 
Duration of waste package emplacement 23 years BSC 2004 [DIRS 168489], Table 1 
Heat-generation rates for each of the 
waste package types 
See IED BSC 2004 [DIRS 167754], Table 12 
Ventilation heat-removal efficiency as a 
function of time and distance from the inlet 
of the emplacement drift 
Entire Worksheet DTN: MO0304MWDALACV.000 [DIRS 
164551], FILE: ANSYS-LA-coarse.xls, 
Efficiency Data Worksheeta 
a 
DTN: MO0304MWDALACV.000 [DIRS 164551], which was superseded by DTN: MO0306MWDASLCV.001 [DIRS 
165695], is justified for its use in this report, as documented in Appendix XIV. 
During the preparation of this report, some of the design information was updated as several 
information exchange drawings (IEDs) were superseded. These revisions resulted in small 
changes to the dimensions of the waste packages and drip shield as summarized in Table 4.1-2. 
For the direct inputs to be justified as they appear in Table 4.1-1, these small changes to the 
dimensions must insignificantly affect the results of the MSTHM described in this report. The 
details of this justification are discussed in Sections 4.1.2.1 through 4.1.2.7. 
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Multiscale Thermohydrologic Model 
Table 4.1-2. Changes to the Waste Package and Drip Shield Design Information 
Model Input 
Superseded IED Current IED Relative 
Change 
in ValueValue Source Value Source 
21-PWR AP WP length 5.165 m BSC 2003 [DIRS 5.024 m BSC 2004 [DIRS -2.7% 
165406], Table 1 169472], Table 1 
21-PWR AP WP diameter 1.644 m BSC 2003 [DIRS 1.718 m BSC 2004 [DIRS +4.5% 
165406], Table 1 169472], Table 1 
21-PWR CR WP diameter 1.644 m BSC 2003 [DIRS 1.718 m BSC 2004 [DIRS +4.5% 
165406], Table 1 169472], Table 1 
Weight of 21-PWR AP 43,000 kg BSC 2003 [DIRS 41,100 kg BSC 2004 [DIRS -4.4% 
165406], Table 1 169472], Table 1 
44-BWR WP length 5.165 m BSC 2003 [DIRS 5.024 m BSC 2004 [DIRS -2.7% 
165406], Table 1 169472], Table 1 
44-BWR WP diameter 1.674 m BSC 2003 [DIRS 1.756 m BSC 2004 [DIRS +4.9% 
165406], Table 1 169472], Table 1 
Weight of 44-BWR WP 43,000 kg BSC 2003 [DIRS 41,700 kg BSC 2004 [DIRS -3.0% 
165406], Table 1 169472], Table 1 
5 DHLW/DOE SNF-LONG WP 5.217 m BSC 2003 [DIRS 5.059 m BSC 2004 [DIRS -3.0% 
length 165406], Table 1 169472], Table 1 
5 DHLW/DOE SNF-LONG WP 2.110 m BSC 2003 [DIRS 2.126 m BSC 2004 [DIRS +0.8% 
diameter 165406], Table 1 169472], Table 1 
Weight of 5 DHLW/DOE 57,000 kg BSC 2003 [DIRS 53,100 kg BSC 2004 [DIRS -6.8% 
SNF-LONG 165406], Table 1 169472], Table 1 
5 DHLW/DOE SNF-SHORT 3.590 m BSC 2003 [DIRS 3.453 m BSC 2004 [DIRS -3.8% 
length 165406], Table 1 169472], Table 1 
5 DHLW/DOE SNF-SHORT 2.110 m BSC 2003 [DIRS 2.126 m BSC 2004 [DIRS +0.8% 
diameter 165406], Table 1 169472], Table 1 
Weight of 5 DHLW/DOE 39,000 kg BSC 2003 [DIRS 36,100 kg BSC 2004 [DIRS -7.4% 
SNF-SHORT 165406], Table 1 169472], Table 1 
Drip-shield length 6.105 m BSC 2003 [DIRS 5.805 m BSC 2004 [DIRS -4.9% 
171024], Sheet 2 169220], Table 1 
Drip-shield width 2.512 m BSC 2003 [DIRS 2.533 m BSC 2004 [DIRS +0.8% 
171024], Sheet 2 169220], Table 1 
Intersection of drip-shield plate-1 1875 mm BSC 2003 [DIRS 1891 mm BSC 2004 [DIRS +0.9% 
with drip-shield plate-2 from 171024], Sheet 2 168067] 
base/top of invert 
Location of 21-PWR AP 1018 mm BSC 2004 [DIRS 1050.9 mm BSC 2004 [DIRS +3.2% 
centerline above invert 167040], Figure 1 168489], Figure 1 
AP = Absorber Plate, CR = Control Rods. 
4.1.2.1 Waste Package Lengths 
As summarized in Table 4.1-2, the differences in waste package lengths between those used in 
this report, which are obtained from the superseded IED (BSC 2003 [DIRS 165406]), and those 
listed in the current IED (BSC 2004 [DIRS 169472]) are small, ranging from 2.7 to 3.8 
percent. Waste package lengths are used only in the DDT submodel. The DDT submodel is 
primarily used for two purposes: (1) calculating the temperature difference between the waste 
package and drip shield and (2) calculating the longitudinal temperature variations along the drift 
axis. If the slightly shorter waste package lengths given in the current IED (BSC 2004 [DIRS 
169472]) were employed in the MSTHM calculations for this report, it would only result in 
ANL-EBS-MD-000049 REV 02 4-7 October 2004 

Multiscale Thermohydrologic Model 
slightly less longitudinal temperature and relative humidity variation along the drift axis. This 
small reduction in longitudinal variability is insignificant compared to the range of temperature 
and relative humidity that results from the influence of parametric variability and uncertainty, 
which is discussed in Section 6.3. Therefore, the waste package lengths from the superseded 
IED are suitable for use in the MSTHM calculations reported in Section 6.3. 
4.1.2.2 Waste Package Diameters 
As summarized in Table 4.1-2, the differences in waste package diameters between those used in 
this report, which are obtained from the superseded IED (BSC 2003 [DIRS 165406]), and those 
listed in the current IED (BSC 2004 [DIRS 169472]) are small, ranging from +0.8 to +4.9 
percent. Waste package diameters are used only in the DDT submodel. The DDT submodel is 
only used for two purposes: (1) calculating the temperature difference between the waste 
package and drip shield and (2) calculating the longitudinal temperature variations along the drift 
axis. If the slightly wider waste package diameters given in the current IED (BSC 2004 [DIRS 
169472]) were employed in the MSTHM calculations for this report, it would only result in 
facilitating slightly better thermal-radiative heat transfer between the ends of the waste packages, 
thereby resulting in slightly less longitudinal temperature and relative humidity variations along 
the drift axis. If the slightly wider waste package diameters were employed in the MSTHM 
calculations for this report, it would also have the effect of slightly decreasing the temperature 
difference between the waste package and drip shield. The very small reductions in longitudinal 
temperature variability and in waste package-to-drip-shield temperature difference are 
insignificant compared to the range of temperature and relative humidity that results from the 
influence of parametric variability and uncertainty, which is discussed in Section 6.3. Therefore, 
the waste package diameters from the superseded IED are suitable for use in the MSTHM 
calculations reported in Section 6.3. 
4.1.2.3 Waste Package Weights 
As summarized in Table 4.1-2, the differences in waste package weights between those used in 
this report, which are obtained from the superseded IED (BSC 2003 [DIRS 165406]), and those 
listed in the current IED (BSC 2004 [DIRS 169472]) are small, ranging from 3.0 to 7.4 
percent. Waste package weights are used only in the LDTH and DDT submodels. The weight of 
the waste package, multiplied by the waste package-specific heat capacity, is the heat capacity of 
the waste package. The only manner in which the waste package heat capacity affects the 
MSTHM results is by influencing the time required for heat transfer from the waste packages to 
the drift wall to reach a quasi-steady-state condition. Because this quasi-steady-state condition is 
established much earlier than when peak waste package, drip-shield, and drift-wall temperatures 
occur, it has an insignificant effect on peak temperatures. If the slightly lower waste package 
weights given in the current IED (BSC 2004 [DIRS 169472]) were employed in the MSTHM 
calculations for this report, they would only result in allowing heat transfer from the waste 
package to the drift wall reaching the quasi-steady-state condition slightly earlier. Furthermore, 
because the weight of the waste package is much less than that of the surrounding host rock, the 
waste package heat capacity per unit length of drift is much less than that of the surrounding host 
rock. As discussed in Section 6.3.2, parametric uncertainty of the host-rock heat capacity has an 
insignificant influence on MSTHM predictions of temperature and relative humidity. Therefore, 
ANL-EBS-MD-000049 REV 02 4-8 October 2004 

Multiscale Thermohydrologic Model 
the waste package weights from the superseded IED are suitable for use in the MSTHM 
calculations reported in Section 6.3. 
4.1.2.4 Drip Shield Length 
As summarized in Table 4.1-2, the difference in drip-shield length between that used in this 
report, which is obtained from the superseded IED (BSC 2003 [DIRS 171024]), and that listed in 
the current IED (BSC 2004 [DIRS 169220]) is small (4.9 percent). The only use of the 
drip-shield length, in conjunction with the drip-shield weight, is to determine the drip-shield 
weight per unit length of drift in the LDTH submodels and to determine the drip-shield mass 
density in the DDT submodels. The weight of the drip shield, multiplied by the specific heat 
capacity, affects the heat capacity of the drip shield. The only manner in which the drip-shield 
heat capacity affects the MSTHM results is by influencing the time required for heat transfer 
from the waste package to the drift wall to reach a quasi-steady-state condition. Because this 
quasi-steady-state condition is established much earlier than when peak waste package, 
drip-shield, and drift-wall temperatures occur, it has an insignificant effect on peak temperatures. 
If the slightly shorter drip-shield lengths given in the current IED (BSC 2004 [DIRS 169220]) 
were employed in the MSTHM calculations for this report, it would result in a slightly larger 
weight per unit length of drift, thereby causing a slight increase in heat capacity for the drip 
shield. The weight of the drip shield per unit length is much less than that of the waste packages. 
Therefore, the time required for heat transfer from the waste package to the drift wall reaching 
the quasi-steady-state condition would be insignificantly affected by this small change in 
drip-shield heat capacity. Furthermore, because the weight of the drip shield is much less than 
that of the surrounding host rock, the drip-shield heat capacity per unit length of drift is very 
much less than that of the surrounding host rock. As discussed in Section 6.3.2, parametric 
uncertainty of the host-rock heat capacity has an insignificant influence on MSTHM predictions 
of temperature and relative humidity. Therefore, the drip shield length from the superseded IED 
is suitable for use in the MSTHM calculations reported in Section 6.3. 
4.1.2.5 Drip Shield Width 
As summarized in Table 4.1-2, the difference in drip-shield width between that used in this 
report, which is obtained from the superseded IED (BSC 2003 [DIRS 171024]), and that listed in 
the current IED (BSC 2004 [DIRS 169220]) is extremely small (+0.8 percent). The only use of 
the drip-shield width is in the LDTH and DDT submodels, where it primarily affects the 
drip-shield surface area. In the LDTH submodels, it influences thermal-radiative heat transfer 
between the drip shield and other surfaces inside the drift cavity. In the DDT submodels (Figure 
6.2-8) it influences thermal-radiative heat transfer between the waste package and underside of 
the drip shield and between the outside of the drip shield and the other surfaces inside the drift 
cavity. Thermal-radiative heat transfer is extremely efficient, driven by the difference of 
temperature to the fourth power of the respective surfaces. A very small (0.8 percent) difference 
in surface area of the drip-shield will have an insignificant effect on the temperature differences 
within the drift. Therefore, the difference in drip-shield width, which influences drip-shield 
surface area, has an insignificant effect on temperature or relative humidity predicted by the 
MSTHM, which is discussed in Section 6.3. Given the manner in which the DDT submodel 
approximates the geometry of the drip shield (Figure 6.2-8), the 0.8 percent change in drip-shield 
width is insignificant. Moreover, because the DDT submodel representation of the drip shield 
ANL-EBS-MD-000049 REV 02 4-9 October 2004 

Multiscale Thermohydrologic Model 
was done to conserve the drip-shield weight per unit length of drift, any change in drip-shield 
width, however large or small, will not affect the heat capacity of the drip shield per unit length 
of drift. Therefore, the drip shield width from the superseded IED is suitable for use in the 
MSTHM calculations reported in Section 6.3. 
4.1.2.6 Intersection of Drip-Shield Plate-1 with Drip-Shield Plate-2 from Base/Top of 
Invert 
As summarized in Table 4.1-2, the difference in the intersection of drip shield plate-1 with drip 
shield plate-2 between that used in this report, which is obtained from the superseded IED (BSC 
2003 [DIRS 171024]), and that listed in the current IED (BSC 2004 [DIRS 168067]) is 
extremely small (+0.9 percent). The only use of this value is in the LDTH submodels, where it 
affects the point at which the sloping portion of the drip shield meets the vertical sides of the drip 
shield (see Figure 6.2-6). Relative to the coarse approximation of the drip-shield shape in the 
LDTH submodel, this small change in where the sloping portion of the drip shield meets the 
vertical sides of the drip shield is insignificant. The primary manner in which the shape of the 
drip shield affects in-drift thermal-hydrologic behavior is by affecting the surface area from 
which thermal-radiative heat transfer occurs from the drip shield to the drift-wall and 
upper-invert surfaces. Changing where the sloping and vertical portions of the drip shield 
intersect does not change the surface area of the drip shield as it is represented in the LDTH 
submodel. Therefore, thermal-radiative heat transfer from the drip shield to the drift-wall and 
upper-invert surfaces is unaffected by this change. Consequently, the intersection location from 
the superseded IED is suitable for use in the MSTHM calculations reported in Section 6.3. 
4.1.2.7 Location of 21-PWR AP Waste Package Centerline Above the Invert 
As summarized in Table 4.1-2, the difference in the location of the 21-PWR AP WP centerline 
above the invert between that used in this report, which is obtained from the superseded IED 
(BSC 2004 [DIRS 167040]), and that given in the current IED (BSC 2004 [DIRS 168489]) is 
small (+3.2 percent). The only use of this dimension is in the DDT submodels, where it 
determines the position of the waste package above the invert (see Figures 6.2.7 through 6.2.10). 
Because the purpose of the MSTHM is to predict postclosure thermal-hydrologic conditions, the 
only manner in which this dimension affects results from the MSTHM is in how it influences 
radiative heat transfer between the waste package and drip shield. This radiative heat transfer is 
the primary factor influencing the temperature difference between the waste package and drip 
shield. Given the geometric approximation of the waste package and drip shield (see Figure 
6.2.8) this small (3.2 percent) difference in the location of the waste package above the invert has 
an insignificant influence on the predicted temperature difference between the waste package and 
drip shield. Consequently, it also has an insignificant influence on the predicted 
thermal-hydrologic conditions within the emplacement drifts. Given the manner in which the 
DDT submodel approximates the geometry of the waste package and drip shield (Figure 6.2-8), 
this small change in vertical positioning of the waste package is insignificant. Therefore, the 
location of the centerline from the superseded IED is suitable for use in the MSTHM calculations 
reported in Section 6.3. 
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Multiscale Thermohydrologic Model 
4.1.2.8 Repository Layout 
During the preparation of this report, the repository layout information was updated as several 
IEDs were superseded (Table 4.1-3), causing small changes to the repository layout (Table 4.1-4 
and Figure 4-1). Specifically, endpoint coordinates of emplacement drifts were updated in the 
current IED, resulting in the following changes: 
1. Elimination of the northernmost drift in Panel P3W, formerly called Panel P2W. 
2. Small reductions in the length of several emplacement drifts, particularly in the southern 
end of Panel 4, formerly called Panel 3 (Figure 4-1). Note that the minor reductions in 
drift length in Panel 1 and in Panel 3E, formerly called Panel 2E, are too small to appear 
in Figure 4-1. 
3. Addition of two emplacement drifts in Panel P2, formerly called Panel P4. 
As evident in Figure 4-1, the changes in the repository layout are small, justifying the use of the 
superseded IED in the MSTHM calculations reported in Section 6.3. 
Table 4.1-3. Summary of Current and Superseded IEDs Providing Repository Layout Information 
Model Input Superseded IED Current IED 
Repository emplacement-drift layout (elevations BSC 2003 [DIRS 161727] BSC 2004 [DIRS 164519] 
and end-point coordinates for each emplacement 
drift) 
Available emplacement drift lengths Not Availablea BSC 2004 [DIRS 170202] 
Invert height above drift 0.806 m 2 10 (0.8636 m) 
(BSC 2003 [DIRS 164101]) (BSC 2004 [DIRS 169503]) 
a 
The footnote labeled ** in BSC 2004 [DIRS 170202] states that this information was not available for the 
superseded repository layout.
Table 4.1-4. Summary of Emplacement Panels and Drifts Represented in the SMT Submodel for the 
Layout in the Superseded IED and the Current IED 
Panel Number of drifts 
Number of gridblocks 
Modeled drift length 
(m) 
Current drift length (m) 
Old New Old New 
1 1 8 8 206 4,120 4092 
2E 3E 19 19 545 10,900 10,728 
2W 3W 23 22 689 13,780 13,272 
3 4 30 30 877 17,540 17,003 
5 2 15a 17a 557 11,140 12,506 
Total 95 96 2874 57,480 57,601 
a 
Panel 5 (2) has a total of 27 drifts; the 15 (17) northernmost drifts are used in the TSPA-LA base case. 
NOTES: The superseded (old) IED is presented in BSC 2003 [DIRS 161727]; the current (new) IED is presented in 
BSC 2004 [DIRS 170202]). Note that the layout for the superseded IED is also described in Table 6.2-1. 
Each of the heated gridblocks represents a 20-m interval along the emplacement drift. 
ANL-EBS-MD-000049 REV 02 4-11 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: The repository layout incorporated in the MSTHM for the TSPA-LA (Figure 6.2-3) is based on the IED 
presented in Repository Design, Repository/PA IED Subsurface Facilities (BSC 2003 [DIRS 161727]). 
This IED has been superceded by the IED presented in D&E / PA/C IED Subsurface Facilities (BSC 2004 
[DIRS 164519]). The LDTHSDT submodel locations shown in blue are those that have been either 
moved or added relative to Figure 6.2-3; those shown in orange are those used in the MSTHM for the 
TSPA-LA, and also correspond to those shown in Figure 6.2-3. Note that the minor reductions in drift 
length in Panel 1 and in Panel 3E, formerly called Panel 2E, are too small to be apparent at the scale of 
this diagram. The outline of the repository perimeter corresponds to the end-point coordinates of the 
heated portions of the emplacement drifts as given in D&E / PA/C IED Subsurface Facilities (BSC 2004 
[DIRS 164519]). 
Figure 4-1. Differences Between the Repository Layout Incorporated in the MSTHM for the TSPA-LA, 
and the Repository Layout Given in the Current IED 
ANL-EBS-MD-000049 REV 02 4-12 October 2004 

Multiscale Thermohydrologic Model 
Figure 4-1 clearly shows that the superseded and current repository layouts are very similar. The 
only areas where the two layouts do not coincide are (1) the northernmost drift of Panel P3W, 
which was formerly called Panel P2W, (2) the southwestern edge and southeastern corner of 
Panel 4, which was formerly called Panel 3, and (3) the two southernmost drifts in Panel 2, 
formerly called Panel P5, of the current repository layout (BSC 2004 [DIRS 164519]). These 
two southernmost drifts, which have a total length of 1400 m, were added to make up for the 
length of emplacement drifts that were removed from the superseded layout (BSC 2003 [DIRS 
161727]). Dividing 1400 m by the total length of emplacement drift in the new repository layout 
(57,600 m) gives the percentage (2.4 percent) of the new repository area that lies outside of the 
superseded repository layout. Therefore, 97.6 percent of the new repository layout coincides 
with that of the superseded repository layout. 
An important natural-system parameter influencing in-drift and near-field thermal-hydrologic 
conditions is the host-rock percolation flux. Figure 4-2 shows that the distribution of host-rock 
percolation flux over the repository area is very similar for the superseded and current repository 
layouts for all three climate states: (1) present-day, (2) monsoonal, and (3) glacial. Therefore, 
the repository layout from the superseded IEDs is suitable for use in the MSTHM calculations 
reported in Section 6.3. 
Source: See Table XIII-1. 
NOTE: CCDF is given for the present-day, monsoonal, and glacial climates. The superceded repository layout is 
presented in Repository Design, Repository/PA IED Subsurface Facilities (BSC 2003 [DIRS 161727]). 
The current repository layout is presented in D&E / PA/C IED Subsurface Facilities (BSC 2004 [DIRS 
164519]). 
Figure 4-2. Complementary Cumulative Distribution Function (CCDF) for Distribution of Host-Rock 
Percolation Flux in the Superseded Repository Layout and the Current Repository Layout 
ANL-EBS-MD-000049 REV 02 4-13 October 2004 

Multiscale Thermohydrologic Model 
4.1.3 Direct Inputs for Development of the Properties of Crushed Tuff in the Invert 
Appendix X presents an analysis that produces retention and flow parameters for the invert. The 
input for that analysis includes the permeability, porosity, and retention data for volcanic sand, 
fine sand, glass beads and Touchet Silt Loam (DTN: MO0307SPAUSFPD.000 [DIRS 164436]). 
Table 4.1-5 presents the permeability data (k) and the porosity data (f) of these unconsolidated 
materials. Table 4.1-6 presents the retention data for the same materials. 
Table 4.1-5. Summary of Permeability and Porosity of Various Unconsolidated Materials 
Material a Porosity 
Value 
(-) 
Intrinsic Permeability 
(m2) 
Value 
(m2) 
Volcanic Sand fvs 0.351 kvs 1.80E-11 
Fine Sand ffs 0.377 kfs 2.50E-12 
Glass Beads fgb 0.37 kgb 6.30E-12 
Touchet Silt Loam fts 0.485 kts 6.00E-13 
DTN: MO0307SPAUSFPD.000 [DIRS 164436]. 
a 
See Section 6.4 for a description of these materials. 
In addition to DTN: MO0307SPAUSFPD.000 [DIRS 164436], the development in Appendix X 
uses the following direct inputs: 
 A value of 2 for the ratio of the capillary rise of water to the capillary rise of the 
hydrocarbon liquid used for the measurements (Brooks and Corey 1964 [DIRS 
156915]). 
 The Kozeny-Carman equation as Equation X.52 (Bear 1972 [DIRS 156269], p. 166). 
 Porosity of poorly graded sands in the loose state (see below). 
 Properties of water (see below). 
These inputs are justified for this use in three ways. First, the data, and curve-fits to the data, for 
various size particles are corroborated by parallel calculations using the Campbell retention 
relation for the same size particles (BSC 2003 [DIRS 170881]). 
The retention relationships developed by the Campbell method show the same characteristics as 
the nondimensionalized van Genuchten method based upon the Leverett Equation (Leverett 1941 
[DIRS 100588]). The results show that as particle size is increased, water retention is reduced. 
Note that the NUFT dual continuum analyses presented in Advection versus Diffusion in the 
Invert (BSC 2003 [DIRS 170881]) were conducted over the range of moisture potentials 
anticipated for the repository using both the nondimensionalized van Genuchten and the 
Campbell retention constitutive relationships. In both instances, it was determined that 
intergranular porosity did not cause water retention. For this reason, the use of 
nondimensionalized van Genuchten parameters as direct input in this report is corroborated. 
ANL-EBS-MD-000049 REV 02 4-14 October 2004 

Multiscale Thermohydrologic Model 
Table 4.1-6. Retention Data for Various Materials 
Volcanic Sand Fine Sand Glass Beads Touchet Silt Loam 
Saturation 
Capillary 
Rise(cm) 
Hydrocarbon 
Capillary 
Rise(cm) 
Water Saturation 
Capillary 
Rise(cm) 
Hydrocarbon 
Capillary 
Rise(cm) 
Water Saturation 
Capillary 
Rise(cm) 
Hydrocarbon 
Capillary 
Rise(cm) 
Water Saturation 
Capillary 
Rise(cm) 
Hydrocarbon 
Capillary 
Rise(cm) 
Water 
0.99 12 24 0.99 12.8 25.6 0.995 5.9 11.8 0.998 32.8 65.6 
0.986 13.5 27 0.98 27.8 55.6 0.989 11.8 23.6 0.995 42.8 85.6 
0.98 14.5 29 0.962 30.8 61.6 0.985 17.8 35.6 0.992 52.8 105.6 
0.974 15.5 31 0.95 31.8 63.6 0.98 23.8 47.6 0.984 62.8 125.6 
0.948 16 32 0.926 34.8 69.6 0.971 26.9 53.8 0.978 67.8 135.6 
0.895 17 34 0.901 36.8 73.6 0.938 28.8 57.6 0.967 72.5 145 
0.875 17.2 34.4 0.855 39.8 79.6 0.912 29.3 58.6 0.946 77.8 155.6 
0.638 21 42 0.788 42.8 85.6 0.764 30.4 60.8 0.892 82.3 164.6 
0.479 24.8 49.6 0.716 45.8 91.6 0.681 31 62 0.821 87.7 175.4 
0.277 36.9 73.8 0.627 48.8 97.6 0.579 32.1 64.2 0.719 97.8 195.6 
0.188 67.7 135.4 0.503 52.8 105.6 0.465 32.7 65.4 0.641 107.6 215.2 
0.158 136.6 273.2 0.393 57.7 115.4 0.337 33.9 67.8 0.562 123 246 
   0.314 64.8 129.6 0.269 35.7 71.4 0.492 142.6 285.2 
   0.273 71.7 143.4 0.19 39 78 0.424 177 354 
   0.262 74.4 148.8 0.13 43.8 87.6 0.383 207.2 414.4 
   0.217 92.1 184.2 0.099 53.5 107    
   0.174 150.1 300.2 0.097 150.4 300.8    
DTN: MO0307SPAUSFPD.000 [DIRS 164436]. 
ANL-EBS-MD-000049 REV 02 4-15 October 2004 

Multiscale Thermohydrologic Model 
Second, the use of nondimensionalized constitutive relationships is corroborated by unsaturated 
flow measurements as reported in Advection versus Diffusion in the Invert (BSC 2003 [DIRS 
170881], Section 6.8.3). The measurement results indicate that the intergranular porosity was 
free of water. 
Finally, the sources of the inputs are individually justified. The value for the ratio of capillary 
rise of water to the capillary rise of the hydrocarbon is an estimate that is included in the original 
report of the qualified data. Van Genuchten (1980 [DIRS 100610]) used the same factor in his 
analysis. All three authors are prominent soil scientists whose work is widely recognized. 
The Kozeny-Carman equation is corroborated by a similar form in a handbook (Winterkorn and 
Fang 1975 [DIRS 169700], p. 106, Eq. 2.19). 
Porosity of Poorly Graded Sands in the Loose State 
In a handbook, Hilf (1975 [DIRS 169699], Table 7.3, p. 257) reports a range in the maximum 
void ratio (e) of 0.67 to 0.94 for the Unified Soils Classification System type SP, which is for 
poorly graded sands and gravelly sands with little to no fines (Hilf 1975 [DIRS 169699], p. 84). 
The corresponding porosity (f) can be calculated using the handbook formula that relates the 
void ratio to porosity (Kaviany 1998 [DIRS 170520], p. 9.76): 
f 
e = 
1 -f 
where 
e = void ratio and 
f= porosity 
Solving for f in terms of e: 
f= e 
1 + e 
For the range of void ratios for SP materials, the corresponding range for intergranular porosity 
is 0.40 to 0.48. A value of 0.45 is selected for the intergranular porosity of the crushed tuff 
gravel in the invert because it is near the middle of this range. 
Properties of Water 
The properties of water at ambient temperature are given by Incropera and DeWitt (1996 [DIRS 
108184]). The water density (.) equals approximately 1000 kg/m3 and the absolute viscosity () 
equals 8.935  10-4 Ns/(m2). The surface tension of water equals 72 dynes/cm. These values 
are corroborated by handbook values from Liley et al. (1984 [DIRS 146851], pp. 3-75 and 
3-238) by interpolation to 25C. Using MathCad 11.2a, the interpolation proceeds as follows: 
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Multiscale Thermohydrologic Model 
Convert the temperature to Kelvin from Celsius: 
25C + 273.15 = 298.15 K 
The density of water given by Liley et al. (1984 [DIRS 146851], Table 3-38) is 997.045 kg/m3. 
Use 1,000 kg/m3 for purposes of illustrating hydraulic conductivity versus moisture potential 
relationships, as in Attachment X. Liley et al. (1984 [DIRS 146851], Table 3-302) list the 
following values of viscosity and surface tension: 
i := 01
.. 
.. 
. 
..
Te 
Vs 
St 
.
.
.
:= 
Temperature 
(K) 
Absolute 
Viscosity 
(N*sec/m2) 
Surface 
Tension 
(N/m) 
295 9.59E-04 0.0727 
300 8.55E-04 0.0717 
Add units for purposes of interpolation: 
Temperaturei := TeiK
..
.
N

.
sec
Viscosityi Vsi
:=

2 
m
.
N 
m 
Perform a linear interpolation on this data for a temperature of 25C or 298.15 K: 
Surface_Tensioni := Sti

N

sec
10
-
4
(,
Viscosity eTemperatur linterp 15.298 , 

K )
=
94. 8

2
m 
dyne
eTemperatur linterp , Tension Surface 
( 
15.298 ,

K
)
=
1.72 
cm 
The properties listed above are used for analysis of moisture retention and hydraulic conductivity 
relationships for the intergranular porosity of the invert in Appendix X. The ambient 
temperature of 25C is consistent with the temperature used in the analysis of the Brooks and 
Corey moisture retention measurements presented in Appendix X. This analysis, which applies 
the ambient temperature value, is used only to illustrate the relationship of unsaturated hydraulic 
conductivity to moisture potential of the intergranular porosity of the invert. The NUFT code 
uses van Genuchten moisture retention and relative permeability relationships that are 
independent of temperature; however, NUFT accounts for the temperature dependence of the 
fluid properties in the thermal-hydrologic simulations. 
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Multiscale Thermohydrologic Model 
Adjustment for Fluid Density for the Height of Capillary Rise 
The Brooks and Corey retention data presented in Appendix X used hydrocarbon as the fluid. 
The data in Appendix X are adjusted to account for the difference between water and the 
hydrocarbon fluid. According to Brooks and Corey (1964 [DIRS 156915], Equation 17, p. 9), 
the capillary rise of water was about twice that of the hydrocarbon used in the measurements. 
This relationship is justified for the intended use in that it is established fact that the capillary rise 
or retention equals the capillary pressure divided by the density of the fluid. 
Qualification of the Use of Information from Fetter 
The referenced source by Fetter (1993 [DIRS 102009]) on the topics of the theory supporting 
analytical equations for steady-state unsaturated flow in porous medium and the use of the van 
Genuchten relation was reviewed by the following individuals: J.M. Bahr at the University of 
Wisconsin  Madison; R.A. Griffin at the University of Alabama; J.I. Hoffman at Eastern 
Washington University; M. Th. van Genuchten at the U.S. Department of Agriculture Salinity 
Laboratory; S. Kornder at the James River Paper Company; G. Sposito at the University of 
California  Berkeley; N. Valkenburg at Geraghty and Miller, Inc.; and P. Wierenga at the 
University of Arizona. Noting that the information of interest from Fetter pertains to unsaturated 
flow and the van Genuchten relation, and the fact that this source was reviewed by Martinus Th. 
van Genuchten, among others, the source is considered reliable for its intended use. The extent 
to which this source of information addresses the supporting analytical equations for steady-state 
unsaturated flow in porous medium and the use of the van Genuchten relation is considered 
adequate because these topics were extensively reviewed, as documented here. 
4.2 CRITERIA 
Project Requirements Document (Canori and Leitner 2003 [DIRS 166275]) contains three 
criteria that are relevant to the work documented in this report. They are: 
1. PRD-002/T-014 Performance Objectives for the Geologic Repository After Permanent 
Closure; see 10 CFR 63.113 [DIRS 156605] for compete requirement text. 
2. PRD-002/T-015 Requirements for Performance Assessment; see 10 CFR 63.114 for 
compete requirement text. 
3. PRD-002/T-016 Requirements for Multiple Barriers; see 10 CFR 63.115 for compete 
requirement text. 
Work described in this document will support these requirements, but more specific criteria exist 
in Yucca Mountain Review Plan, Final Report (Yucca Mountain Review Plan) (NRC 2003 
[DIRS 163274]). Selected Yucca Mountain Review Plan acceptance criteria are presented to 
supplement or clarify the Project Requirements Document citation. 
Technical Work Plan for: Near-Field Environment In-Drift Heat and Mass Transfer Model and 
Analysis Reports Integration (BSC 2004 [DIRS 170950], Section 3.2) identifies the applicable 
acceptance criteria for this model report. Because this model report predicts results that directly 
or indirectly pertain to quantity of water contacting engineered barriers and waste forms, the 
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Multiscale Thermohydrologic Model 
following Yucca Mountain Review Plan acceptance criteria, based on meeting the requirements 
of 10 CFR 63.114(a)(c) and (e)(g) [DIRS 156605]), were identified as applicable to this 
technical product (NRC 2003 [DIRS 163274], Section 2.2.1.3.3.3). As discussed in Section 8.4, 
several parts of the criteria are not included because they are not relevant to this model report. 
Section 8.4 discusses the contents of this report as they relate to the acceptance criteria. 
4.2.1 Acceptance Criterion 1  System Description and Model Integration Are Adequate 
(1) Total system performance assessment adequately incorporates important design 
features, physical phenomena, and couplings, and uses consistent and appropriate 
assumptions throughout the quantity and chemistry of water contacting engineered 
barriers and waste forms abstraction process; 
(2) The abstraction of the quantity and chemistry of water contacting engineered barriers 
and waste forms uses assumptions, technical bases, data, and models, that are 
appropriate and consistent with other related U.S. Department of Energy abstractions. 
For example, the assumptions used for the quantity and chemistry of water contacting 
engineered barriers and waste forms are consistent with the abstractions of 
Degradation of Engineered Barriers (Section 2.2.1.3.1); Mechanical Disruption of 
Engineered Barriers (Section 2.2.1.3.2); Radionuclide Release Rates and Solubility 
Limits (Section 2.2.1.3.4); Climate and Infiltration (Section 2.2.1.3.5); and Flow 
Paths in the Unsaturated Zone (Section 2.2.1.3.6). The descriptions and technical 
bases provide transparent and traceable support for the abstraction of quantity and 
chemistry of water contacting engineered barriers and waste forms; 
(3) Important design features, such as waste package design and material selection, 
backfill, drip shield, ground support, thermal loading strategy, and degradation 
processes, are adequate to determine the initial and boundary conditions for 
calculations of the quantity and chemistry of water contacting engineered barriers and 
waste forms; 
(4) Spatial and temporal abstractions appropriately address physical couplings (thermal-
hydrologic-mechanical-chemical). For example, the U.S. Department of Energy 
evaluates the potential for focusing of water flow into drifts, caused by coupled 
thermal-hydrologic-mechanical-chemical processes; 
(5) Sufficient technical bases and justification are provided for total system performance 
assessment assumptions and approximations for modeling coupled thermal-
hydrologic-mechanical-chemical effects on seepage and flow, the waste package 
chemical environment, and the chemical environment for radionuclide release. The 
effects of distribution of flow on the amount of water contacting the engineered 
barriers and waste forms are consistently addressed, in all relevant abstractions; 
(6) The expected ranges of environmental conditions within the waste package 
emplacement drifts, inside the breached waste packages, and contacting the waste 
forms and their evolution with time are identified. These ranges may be developed to 
include: (i) the effects of the drip shield and backfill on the quantity and chemistry of 
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Multiscale Thermohydrologic Model 
waster (e.g., the potential for condensate formation and dripping from the underside of 
the shield); (ii) conditions that promote corrosion of engineered barriers and 
degradation of waste forms; (iii) irregular wet and dry cycles; (iv) gamma-radiolysis; 
and (v) size and distribution of penetrations of engineered barriers; 
(7) The model abstraction for quantity and chemistry of water contacting engineered 
barriers and waste forms is consistent with the detailed information on engineered 
barrier design and other engineered features. For example, consistency is 
demonstrated for: (i) dimensionality of the abstractions; (ii) various design features 
and site characteristics; and (iii) alternative conceptual approaches. Analyses are 
adequate to demonstrate that no deleterious effects are caused by design or site 
features that the U.S. Department of Energy does not take into account in this 
abstraction; 
(8) Adequate technical bases are provided, including activities such as independent 
modeling, laboratory or field data, or sensitivity studies, for inclusion of any thermal-
hydrologic-mechanical-chemical couplings and features, events, and processes; 
(9) Performance-affecting processes that have been observed in thermal-hydrologic tests 
and experiments are included into the performance assessment. For example, the U.S. 
Department of Energy either demonstrates that liquid water will not reflux into the 
underground facility or incorporates refluxing water into the performance assessment 
calculation, and bounds the potential adverse effects of alteration of the hydraulic 
pathway that result from refluxing water; 
(12) Guidance in NUREG1297 (Altman et al. 1988 [DIRS 103597] and NUREG1298 
(Altman et al. 1988 [DIRS 103750]), or other acceptable approaches, is followed. 
4.2.2 Acceptance Criterion 2  Data Are Sufficient for Model Justification 
(1) Geological, hydrological, and geochemical values used in the license application are 
adequately justified. Adequate description of how the data were used, interpreted, and 
appropriately synthesized into the parameters is provided; 
(2) Sufficient data were collected on the characteristics of the natural system and 
engineered materials to establish initial and boundary conditions for conceptual 
models of thermal-hydrological-mechanical-chemical coupled processes, that affect 
seepage and flow and the engineered barriers chemical environment; 
(3) Thermo-hydrologic tests were designed and conducted with the explicit objectives of 
observing thermal-hydrologic processes for the temperature ranges expected for 
repository conditions and making measurements for mathematical models. Data are 
sufficient to verify that thermal-hydrologic conceptual models address important 
thermal-hydrologic phenomena; 
(4) Sufficient information to formulate the conceptual approach(es) for analyzing water 
contact with the drip shield, engineered barriers, and waste forms is provided. 
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4.2.3 Acceptance Criterion 3  Data Uncertainty Is Characterized and Propagated 
Through the Model Abstraction 
(1) Models use parameter values, assumed ranges, probability distributions, and bounding 
assumptions that are technically defensible, reasonably account for uncertainties and 
variabilities, and do not result in an under-representation of the risk estimate; 
(2) Parameter values, assumed ranges, probability distributions, and bounding 
assumptions used in the total system performance assessment calculations of quantity 
and chemistry of water contacting engineered barriers and waste forms are technically 
defensible and reasonable, based on data from the Yucca Mountain region (e.g., results 
from large block and drift-scale heater and niche tests), and a combination of 
techniques that may include laboratory experiments, field measurements, natural 
analog research, and process-level modeling studies; 
(3) Input values used in the total system performance assessment calculations of quantity 
and chemistry of water contacting engineered barriers (e.g., drip shield and waste 
package) are consistent with the initial and boundary conditions and the assumptions 
of the conceptual models and design concepts for the Yucca Mountain site. 
Correlations between input values are appropriately established in the 
U.S. Department of Energy total system performance assessment. Parameters used to 
define initial conditions, boundary conditions, and computational domain in sensitivity 
analyses involving coupled thermal-hydrologic-mechanical-chemical effects on 
seepage and flow, the waste package chemical environment, and the chemical 
environment for radionuclide release, are consistent with available data. Reasonable 
or conservative ranges of parameters or functional relations are established; 
(4) Adequate representation of uncertainties in the characteristics of the natural system 
and engineered materials is provided in parameter development for conceptual models, 
process-level models, and alternative conceptual models. DOE may constrain these 
uncertainties using sensitivity analyses or conservative limits. For example, DOE 
demonstrates how parameters used to describe flow through the EBS bound the effects 
of backfill and excavation-induced changes; 
4.2.4 Acceptance Criterion 4  Model Uncertainty Is Characterized and Propagated 
Through the Model Abstraction 
(1) Alternative modeling approaches of features, events, and processes are considered and 
are consistent with available data and current scientific understanding, and the results 
and limitations are appropriately considered in the abstraction; 
(2) Alternative modeling approaches are considered and the selected modeling approach is 
consistent with available data and current scientific understanding. A description that 
includes a discussion of alternative modeling approaches not considered in the final 
analysis and the limitations and uncertainties of the chosen model is provided; 
(3) Consideration of conceptual model uncertainty is consistent with available site 
characterization data, laboratory experiments, field measurements, natural analog 
ANL-EBS-MD-000049 REV 02 4-21 October 2004 

Multiscale Thermohydrologic Model 
information and process-level modeling studies; and the treatment of conceptual 
model uncertainty does not result in an under-representation of the risk estimate; 
(4) Adequate consideration is given to effects of thermal-hydrologic-mechanical-chemical 
coupled processes in the assessment of alternative conceptual models. These effects 
may include: (i) thermal-hydrologic effects on gas, water, and mineral chemistry; (ii) 
effects of microbial processes on the engineered barrier chemical environment and the 
chemical environment for radionuclide release; (iii) changes in water chemistry that 
may result from the release of corrosion products from the engineered barriers and 
interactions between engineered materials and ground water; and (iv) changes in 
boundary conditions (e.g., drift shape and size) and hydrologic properties, relating to 
the response of the geomechanical system to thermal loading. 
4.2.5 Acceptance Criterion 5  Model Abstraction Output Is Supported by Objective 
Comparisons 
No subcriteria are applicable to this report. 
4.3 CODES, STANDARDS, AND REGULATIONS 
This report was prepared to comply with 10 CFR Part 63 [DIRS 156605], the U.S. Nuclear 
Regulatory Commission rule on high-level radioactive waste. Subparts of this rule that are 
applicable to data include Subpart E, Section 114 (Requirements for Performance Assessment). 
The subpart applicable to models is also outlined in Subpart E Section 114. The subparts 
applicable to features, events, and processes (FEPs) are 10 CFR 63.114(d), (e), and (f) [DIRS 
156605]. Standard Practice for Preparing, Cleaning, and Evaluating Corrosion Test Specimens 
(ASTM G 1-90 [DIRS 103515]) was also used in preparing this report, as was Section II of 1995 
ASME Boiler and Pressure Vessel Code (ASME 1995 [DIRS 108417]). 
4.4 DATA FROM FIELD MEASUREMENTS IN THE LARGE BLOCK TEST AND 
DRIFT SCALE TEST 
The source DTNs for the field measurements in the Large Block Test (LBT) are listed in Table 
4.4-1. These DTNs are used for model validation purposes only and are not direct input to the 
MSTHM. The source DTNs for the field measurements in the Drift Scale Test (DST) are listed 
in Table 4.4-2. 
Table 4.4-1. Source DTNs for Field Measurements Made in the Large Block Test (LBT) 
Model Input 
Heater power history 
Value 
Heater power input for each of 5 heater boreholes; power 
history read from 7 tables; table name and time range as 
follows: 
 S98461_018 2/27/1997-4/30/1997 
 S98461_019 5/1/1997-7/31/1997 
 S98461_020 8/1/1997-10/31/1997 
 S98461_021 11/1/1997-1/20/1998 
 S98461_011 1/20/1998-3/31/1998 
 S98461_012 4/1/1998-6/30/1998 
 S98461_013 7/1/1998-9/16/1998 
Source 
DTN: LL980918904244.074 
[DIRS 135872] 
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Table 4.4-1. Source DTNs for Field Measurements Made in the Large Block Test (LBT) (Continued) 
Model Input Value Source 
Top surface boundary 
temperature controlled 
by heat exchanger 
Temperature averaged from 4 RTDs, TNE-1, TNW-1,TSE1-
1, and TSW-1; table name and time range as follows: 
 S98461_022 2/27/1997-4/30/1997 
DTN: LL980918904244.074 
[DIRS 135872] 
 S98461_023 5/1/1997-7/31/1997 
 S98461_024 8/1/1997-10/24/1997 
 S98461_025 10/25/1997-12/31/1997 
 S98461_026 1/1/1998-3/31/1998 
 S98461_027 4/1/1998-6/30/1998 
 S98461_028 7/1/1998-9/16/1998 
Snapshots of rock 
temperature profile 
along Borehole TT1 
Temperature profile along Borehole TT1 at five different 
times. Given below are table (or file) name, elapsed time in 
hours (h), and the range of row numbers that contain the 
data for each time. 
DTN: LL980918904244.074 
[DIRS 135872] 
S98461_033 719.8 h 1  41136 
S98461_034 2399.6 h 1  159235 
S98461_ 035 4800.13 h 1  149893 
S98461_029 7200.03 h 1  90950 
S98461_031 9600.22 h 1  98329 
Initial volumetric water 
content from neutron 
Initial water content obtained from average of values 
measured along Borehole TN3 prior to heating; data from 
DTN: LL980919304244.075 
[DIRS 145099] 
measurements file at row numbers 1 -- 159 
Volumetric water Rock water content profile along Borehole TN3 at 103 d, DTN: LL980919304244.075 
content from neutron 361 d, and 501 d; data from file at row numbers 2200  [DIRS 145099] 
measurements 2254 for 103 d, 2365  2419 for 361 d, and 2585  2639 for 
501 d 
Air temperature: 
1/1/1997  
Bureau of Land Management Site 8 temperature data used 
in boundary conditions. Data under table name 
DTN: MO0312SEPQ1997.001 
[DIRS 167116] 
12/31/1997 S04010_001, and parameter name Temperature. Data in 
Microsoft Access folder Met1997t.mdb, in table S008_97t. 
The Julian day number is in Column 3 (1-365), time of day 
in Column 4 (hr, min) and temperature in Column 8 (C). 
Air temperature: 
1/1/1998  3/31/1998 
Bureau of Land Management Site 8 temperature data used 
in boundary conditions. MOL.19990315.0065 Data file: 
1q98b_sr.txt. The site number is in Column 1 (used only 
Site 8 data), Julian day number in Column 3 (1-365), time of 
day in Column 4 (hr) and temperature in Column 7 (K). 
DTN: MO98METDATA114.000 
[DIRS 165702] 
Air temperature: 
4/1/1998  6/30/1998 
Bureau of Land Management Site 8 temperature data used 
in boundary conditions. Data file: 2q98a_sr.txt 
(MOL.19990323.0416). The site number is in Column 1 
(used only Site 8 data), Julian day number in Column 3 (1DTN: 
MO98METDATA117.000 
[DIRS 165705] 
365), time of day in Column 4 (hr) and temperature in 
Column 7 (K). 
Air temperature: 
7/1/1998  9/30/1998 
Bureau of Land Management Site 8 temperature data used 
in boundary conditions. Data file: 3q98_sr.txt 
(MOL.19990105.0204). The site number is in Column 1 
(used only Site 8 data), Julian day number in Column 3 (1DTN: 
MO98METDATA120.000 
[DIRS 165706] 
365), time of day in Column 4 (hr) and temperature in 
Column 7 (K). 
Drift-scale calibrated Entire DTN. DTN: LB990861233129.001 
one-dimensional [DIRS 110226] 
property set, FY99: 
Base-case infiltration 
NOTE: Also listed is one of the data sets used in the thermal-hydrologic model calculations of the LBT. Note that 
these DTNs are used for validation purposes only. 
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Multiscale Thermohydrologic Model 
Table 4.4-2. Source DTNs for Field Measurements Made in the Drift Scale Test (DST) 
Model Input Value Source 
As-built locations of boreholes, Location of temperature sensors in Table DTN: MO0002ABBLSLDS.000 
sensors, and heaters S00085_001; locations of temperature and [DIRS 147304] 
neutron boreholes and heaters in Table 
S00085_002 
Heater power and sensor 
temperatures: November 7, 
1997  May 31, 1998 
Floor heater and wing heater power in Table 
S98349_001; Table names and time intervals 
for temperatures are as follows: 
 S98349_004 11/7/1997  11/30/1997 
 S98349_005 12/1/1997  12/31/1997 
DTN: MO9807DSTSET01.000 
[DIRS 113644] 
 S98349_006 1/1/1998  1/31/1998 
 S98349_007 2/1/1998  2/28/1998 
 S98349_008 3/1/1998  3/31/1998 
 S98349_009 4/1/1998  4/30/1998 
 S98349_010 5/1/1998  5/31/1998 
Heater power and sensor Floor heater and wing heater power in Table DTN: MO9810DSTSET02.000 
temperatures: June 1, 1998  
August 31, 1998 
S99012_001; Table names and time intervals 
for temperatures are as follows: 
 S99012_004 6/1/1998  6/30/1998 
 S99012_005 7/1/1998  7/31/1998 
[DIRS 113662] 
 S99012_006 8/1/1998  8/31/1998 
Heater power and sensor 
temperatures: September 1, 
1998  May 31, 1999 
Floor heater and wing heater power in Table 
S99304_010; Table names and time intervals 
for temperatures are as follows: 
DTN: MO9906DSTSET03.000 
[DIRS 113673] 
 S99304_001 9/1/1998  9/30/1998 
 S99304_002 10/1/1998  10/31/1998 
 S99304_003 11/1/1998  11/30/1998 
 S99304_004 12/1/1998  12/30/1998 
 S99304_005 1/1/1999  1/31/1999 
 S99304_006 2/1/1999  2/28/1999 
 S99304_007 3/1/1999  3/30/1999 
 S99304_008 4/1/1999  4/29/1999 
 S99304_009 5/1/1999  5/31/1999 
Heater power and sensor 
temperatures: June 1, 1999  
Floor heater and wing heater power in Table 
S00044_001; Table names and time intervals 
DTN: MO0001SEPDSTPC.000 
[DIRS 153836] 
October 31, 1999 for temperatures are as follows: 
 S00044_004 6/1/1999  6/30/1999 
 S00044_005 7/1/1999  7/31/1999 
 S00044_006 8/1/1999  8/31/1999 
 S00044_007 9/1/1999  9/30/1999 
 S00044_008 10/1/1999  10/31/1999 
Heater power and sensor 
temperatures: November 1, 
Floor heater and wing heater power in Table 
S00327_009; Table names and time intervals 
DTN: MO0007SEPDSTPC.001 
[DIRS 153707] 
1999  May 31, 2000 for temperatures are as follows: 
 S00327_002 1/1/2000  1/31/2000 
 S00327_003 2/1/2000  2/29/2000 
 S00327_004 3/1/2000  3/31/2000 
 S00327_005 4/1/2000  4/30/2000 
 S00327_006 5/1/2000  5/31/2000 
 S00327_007 11/1/1999  11/30/1999 
 S00327_008 12/1/1999  12/31/1999 
Sensor temperatures: January Data obtained from text files: DTN: MO0208SEPDSTTD.001 
15, 2002  June 30, 2002 TDIF_009_0201_2.txt, TDIF_009_0202.txt, [DIRS 161767] 
TDIF_009_0203.txt, TDIF_009_0204.txt, 
TDIF_009_0205.txt, and TDIF_009_0206.txt 
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Multiscale Thermohydrologic Model 
Table 4.4-2. Source DTNs for Field Measurements Made in the Drift Scale Test (DST) (Continued) 
Model Input Value Source 
Heater power and sensor 
temperatures: June 1, 2000  
November 30, 2000 
Floor heater and wing heater power in Table 
S00468_002; Table names and time intervals 
for temperatures are as follows: 
 S00468_003 10/1/2000  10/31/2000 
 S00468_004 6/1/2000  6/30/2000 
 S00468_005 9/1/2000  9/30/2000 
 S00468_006 8/1/2000  8/31/2000 
 S00468_007 7/1/2000  7/31/2000 
 S00468_008 11/1/2000  11/30/2000 
DTN: MO0012SEPDSTPC.002 
[DIRS 153708] 
Heater power and sensor 
temperatures: December 1, 
2000  May 31, 2001 
Floor heater and wing heater power in Table 
S01100_002; Table names and time intervals 
for temperatures are as follows: 
DTN: MO0107SEPDSTPC.003 
[DIRS 158321] 
 S01100_004 12/1/2000  12/31/2000 
 S01100_005 1/1/2001  1/31/2001 
 S01100_006 2/1/2001  2/28/2001 
 S01100_007 3/1/2001  3/31/2001 
 S01100_008 4/1/2001  4/30/2001 
 S01100_009 5/1/2001  5/31/2001 
Heater power and sensor 
temperatures: June 1, 2001  
January 14, 2002 
Floor heater and wing heater power in Table 
S02060_010; Table names and time intervals 
for temperatures are as follows: 
DTN: MO0202SEPDSTTV.001 
[DIRS 158320] 
 S02060_001 6/1/2001  6/30/2001 
 S02060_002 7/1/2001  7/31/2001 
 S02060_003 8/1/2001  8/31/2001 
 S02060_004 9/1/2001  9/30/2001 
 S02060_005 10/1/2001  10/31/2001 
 S02060_006 11/1/2001  11/30/2001 
 S02060_007 12/1/2001  12/31/2001 
 S02060_008 1/1/2002  1/14/2002 
Sensor temperatures: July 1, Data obtained from text files: DTN: MO0303SEPDSTTM.000 
2002  December 31, 2002 TDIF_010_0207.txt, TDIF_010_0208.txt, [DIRS 165698] 
TDIF_010_0209.txt, TDIF_010_0210.txt, 
TDIF_010_0211.txt, and TDIF_010_0212.txt 
Sensor temperatures: January 1, Data obtained from text files: DTN: MO0307SEPDST31.000 
2003  June 30, 2003 TDIF_011_0306.txt, TDIF_011_0302.txt, [DIRS 165699] 
TDIF_011_0303.txt, TDIF_011_0304.txt, 
TDIF_011_0305.txt, and TDIF_011_0301.txt 
Water content in rock from Following are the neutron boreholes and files DTN: LL020710223142.024 
neutron measurements: August that supply the water content data: [DIRS 159551] 
1997  May 2002  Borehole 68 File N10hv.xls 
 Borehole 79 File N11hxv.xls 
 Borehole 80 File N12hxv.xls 
Water content in rock from Following are the neutron boreholes and files DTN: LL030709023122.032 
neutron measurements: January that supply the water content data: [DIRS 165701] 
2003  May 2003  Borehole 68 File TD100307.xls 
 Borehole 79 File TD110307.xls 
 Borehole 80 File TD120307.xls 
Temperatures and gas-phase Files: INCON_thm_s32.dat and DTN: LB991201233129.001 
pressures at upper boundary MESH_rep.VF [DIRS 146894] 
(ground surface) and lower 
boundary (water table) of the 
three-dimensional Site-Scale UZ 
Flow Model (Table 4.1-1) 
NOTE: These DTNs are used for validation purposes only. 
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INTENTIONALLY LEFT BLANK 
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5. ASSUMPTIONS 
5.1 BOUNDARY CONDITIONS 
5.1.1 Ground-Surface Relative Humidity 
Assumption: The relative humidity at the ground surface above the repository is assumed to be 
100 percent. 
Rationale: The liquid-phase flux distribution applied at the upper boundary of the LDTH 
submodels of the MSTHM is the percolation-flux distribution (from the base of the PTn unit into 
the top of the TSw sequence of units) calculated by UZ Flow Models and Submodels (BSC 2004 
[DIRS 169861]). Note that the three-dimensional UZ flow model accounts for the influence of 
evapotranspiration in the soil zone on net infiltration flux at Yucca Mountain by virtue of the fact 
that it is addressed in the net infiltration-flux distribution applied at the top of the 
three-dimensional UZ flow model. A relative humidity of 100 percent is applied at the 
atmosphere boundary at the top of the MSTHM to ensure that the PTn-to-TSw percolation flux is 
neither significantly diminished nor increased by virtue of gas-phase moisture flux at the top of 
the MSTHM. To verify that the PTn-to-TSw percolation flux is neither significantly diminished 
nor increased, the ambient present-day percolation flux above the repository horizon was 
compared to the PTn-to-TSw percolation flux, which is imposed at the upper boundary in the 
LDTH submodels (Section 6.2.6). It was found that the differences between the imposed 
PTn-to-TSw percolation flux at the upper boundary and the percolation flux above the repository 
horizon never exceed 3.61  10-4 mm/yr for the mean infiltration-flux case. For example, the 
percolation flux above the repository is 3.11  10-5 mm/yr greater than the imposed PTn-to-TSw 
percolation flux for the LDTH submodel location with the lowest present-day PTn-to-TSw 
percolation flux; because this difference is only 0.01 percent of the PTn-to-TSw percolation flux, 
which is 0.23 mm/yr, it is insignificant. The percolation flux above the repository is 
3.61  10-4 mm/yr greater than the imposed PTn-to-TSw percolation flux for the LDTH 
submodel location with the highest present-day PTn-to-TSw percolation flux; because this 
difference is only 0.003 percent of the PTn-to-TSw percolation flux, which is 13.8 mm/yr, it is 
insignificant. Note that these small differences are positive; that is to say that imposing a relative 
humidity of 100 percent at the ground surface slightly increases the moisture flux above the 
repository horizon (by the very small quantities given above) compared to the imposed 
liquid-phase flux at the top of the LDTH submodel. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption affects all LDTH submodels, and is used in Sections 6.2, 6.3, 
6.4, 7.4, and 7.5. 
5.1.2 Ambient Percolation Flux above Repository Horizon 
Assumption: The ambient percolation-flux distribution above the repository horizon is assumed 
to be unaffected by mountain-scale repository-heat-driven thermal-hydrologic effects until it 
reaches the boiling condensation zones surrounding the emplacement drifts. Moreover, between 
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the base of the PTn UZ model layers and the repository horizon, ambient percolation flux is 
assumed to be one-dimensional vertically downward with no lateral diversion caused by layering 
or heterogeneity in the hydrologic-property distributions. Therefore, the percolation-flux 
distribution above the repository horizon is taken to be the percolation-flux distribution from the 
PTn to the upper TSw UZ model layer unit (also called the PTn-to-TSw percolation flux) that is 
predicted by UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]). 
Rationale: The influence of subboiling evaporation has an insignificant effect on the magnitude 
or direction of liquid-phase flux. Moreover, the LDTH submodels already account for the 
influence of subboiling evaporation within the confines of the two-dimensional LDTH-submodel 
geometry. Fracturing within the sequence of UZ model layer units between the PTn and the 
repository horizon is dense and ubiquitous (BSC 2004 [DIRS 169857]), which is not conducive 
to laterally diverting gravity-driven ambient percolation; thus, percolation within this interval is 
vertically downward. The denseness of the fracture spacing is evident in the data on fracture 
frequency (DTN: LB0205REVUZPRP.001 [DIRS 159525]). As is discussed in Section 6.1 of 
Calibrated Properties Model (BSC 2004 [DIRS 169857]), heterogeneity of hydrologic properties 
(including fracture spacing) is treated as a function of geologic layering; thus, any one geologic 
layer has homogeneous properties throughout the grid derived from UZ Flow Models and 
Submodels (BSC 2004 [DIRS 169861]), as well as throughout the MSTHM. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: Section 6.2.6.6 describes the use of the PTn-to-TSw percolation flux in the 
MSTHM LDTH submodels. This assumption is used in Sections 6.2, 6.3, and 7.5. 
5.1.3 Barometric Pressure Fluctuations at the Ground Surface 
Assumption: Barometric (i.e., gas-phase) pressure fluctuations at the ground surface above the 
repository are assumed to be insignificant. Consequently, the gas-phase pressure at the ground 
surface is held constant (i.e., does not fluctuate with time) in all thermal-hydrologic models. 
Rationale: The magnitude of gas-phase pressure fluctuations resulting from barometric pumping 
is small compared to the gas-phase pressure gradients resulting from (1) forced convective 
cooling of emplacement drifts during the preclosure ventilation period and (2) repository-heat-
driven boiling during the postclosure period. Moreover, barometric pumping is not a significant 
contributor to the removal of water vapor from emplacement drifts and the adjoining host rock, 
compared to the effect of drift ventilation during the preclosure period and the effect of boiling 
during the postclosure period. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.3, 6.4, 7.3, 7.4, and 7.5. 
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5.1.4 Timing of Climate Change Influence on Percolation Flux above Repository 
Assumption: For representing percolation flux above the repository, the transition from 
present-day to monsoonal climate is assumed to occur 600 years after emplacement and the 
transition from monsoonal to glacial transition climate is assumed to occur 2,000 years after 
emplacement. 
Rationale: Section 6.6.1 and Table 6-1 of Future Climate Analysis (BSC 2004 [DIRS 170002]) 
give a range of duration for the transition from the present day to the monsoonal climate of 400 
to 600 years, and a range of duration for the transition from the monsoonal to the glacial 
transition climate of 900 to 1,400 years. Thus, the minimum times for the timing of the climate 
transitions are 400 and 1,300 years, respectively. The maximum times for the timing of the 
climate transitions are 600 and 2,000 years, which is what is assumed in this report, as well as in 
all other thermal-hydrologic models supporting TSPA-LA, such as Mountain-Scale Coupled 
Processes (TH/THC/THM) Models (BSC 2004 [DIRS 169866] and Drift-Scale Coupled 
Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). Because peak repository 
temperatures are predicted to occur within 15 to 20 years after closure (Section 6.3.2), the timing 
of the first climate transition (400 to 600 years) has no effect on peak temperatures. Because the 
majority of waste package locations in the repository are predicted to cool down below boiling 
(at the drift wall) prior to 1,300 years (Figure 6.3-52 and Table 6.3-37), the timing of the second 
climate transition (1,300 to 2,000 years) will have an insignificant effect on the majority of the 
waste package locations in the repository. The only locations potentially affected by this 
assumption are those in regions of low percolation flux, close to the center of the repository. 
Even for those situations, the influence of this assumption is not expected to be significant, 
compared to the influences of host-rock thermal conductivity uncertainty and percolation-flux 
uncertainty. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.3 and 7.5. 
5.1.5 Water Table Rise 
Assumption: The influence of water table rise, which results from future (wetter) climates, is 
assumed to have an insignificant effect on thermal-hydrologic conditions in the emplacement 
drifts and adjacent host rock. Thus, the influence of water table rise is assumed to have an 
insignificant effect on temperature and relative humidity in the emplacement drifts. 
Rationale: A rise in the water table of 100 to 120 m for the glacial-transition climate is predicted 
in Section 6.6.3 of UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]). This change in 
water table elevation is small compared to the average distance between the repository horizon 
and the water table, which is on the order of 300 m. With regards to the thermal-hydrologic 
response in the repository, the primary potential influence of this change is to cause a small 
increase in liquid-phase saturation in the lower 100 to 120 m of the unsaturated zone, causing a 
small change in the thermal conductivity in that vertical interval. Heat flow in that vertical 
interval, which is dominated by thermal conduction, will experience an insignificant change as a 
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result of this small increase in liquid-phase saturation, causing an insignificant change in 
predicted repository temperatures. The other potential influence of water table rise is to increase 
the relative humidity in the host rock under ambient conditions. Because ambient relative 
humidity is already close to unity under the present-day climate, any increases resulting from a 
future (wetter) climate will be insignificant. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.3, 6.4, and 7.5. 
5.2 HEAT FLOW PROCESSES 
5.2.1 Mountain-Scale Heat Flow 
Assumption: The following assumption only applies to the SMT submodels (Section 6.2.5). For 
the SMT submodels, differences in temperature that arise as a result of proximity to the 
repository edges are assumed to be governed by thermal conduction in the rock. This 
assumption is equivalent to saying that convective heat transfer mechanisms (notably, buoyant 
gas-phase convection and the heat-pipe effect) have an insignificant influence on lateral 
mountain-scale heat flow at Yucca Mountain. This assumption tends to preserve temperature 
differences that arise as a result of differences in proximity to the repository edges. This 
assumption allows mountain-scale heat flow to be represented using thermal-conduction models. 
This assumption is applied to the SMT submodels. 
Rationale: The bulk permeability kb of much of the unsaturated zone is much less than the 
threshold kb value at which buoyant gas-phase convection begins to significantly influence heat 
flow (Buscheck and Nitao 1994 [DIRS 130561]); therefore, heat flow is dominated by heat 
conduction. Mountain-Scale Coupled Processes (TH/THC/THM) (BSC 2004 [DIRS 169866], 
Section 6.3) documents a three-dimensional mountain-scale thermal-hydrologic model that is 
similar in scale to the SMT submodel in the MSTHM. The vertical temperature profile of the 
mountain-scale thermal-hydrologic model (Figure 6.3.1-6 of BSC 2004 [DIRS 169866]) is 
indicative of conduction-dominated heat flow. Moreover, the primary role of the SMT submodel 
in the MSTHM methodology is to predict the rate at which the edge-cooling effect propagates 
inward from the repository edges toward the repository center. Mountain-scale buoyant 
gas-phase convection has an insignificant effect on controlling the rate at which the edge-cooling 
effect propagates in toward the center of the repository. This assumption is also justified because 
it tends to preserve temperature differences that arise as a result of differences in proximity to the 
repository edges. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in the MSTHM calculations in Sections 6.3, 6.4, 
and 7.5. 
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5.2.2 Drift-Scale Heat Flow 
Assumption: The following assumption only applies to the DDT submodels. For the DDT 
submodels, the influence of repository-scale thermal conductivity variability and drift-scale 
buoyant gas-phase convection within the host rock are assumed to have an insignificant 
influence on waste package-to-waste package temperature deviations along the emplacement 
drifts. This assumption allows the MSTHM methodology to rely upon only one set of DDT 
submodel calculations conducted at a single LDTHSDT submodel location. 
Rationale: During the preclosure period, thermal radiation between the waste package and drift 
wall controls the longitudinal temperature deviations along the emplacement drift in the 
DDT submodels. During the postclosure period, thermal radiation between the waste package 
and drip shield and between the drip shield and drift wall control the temperature deviations 
along the emplacement drift. Heat flow in the longitudinal direction in the host rock (both by 
conduction and convection) plays a much smaller role in attenuating waste package-to-waste 
package temperature variations along the drift wall than does thermal radiation in the drift 
(Hardin 1998 [DIRS 100350], Section 3.7.5.4). 
The DDT submodel is only used for two purposes: (1) calculating the temperature difference 
between the waste package and drip shield, and (2) calculating the longitudinal temperature 
variations along the drift axis. Neither of these quantities is significantly influenced by the 
thermal conductivity in the host rock (or in any of the other UZ model layers). Therefore, it is 
not necessary to run the DDT submodels at multiple locations because the only potential benefit 
would be to capture the influence of the local thermal conductivity values, which is relatively 
unimportant with regards to the two quantities that the DDT submodel is required to predict. 
Convective heat transfer driven by thermal-hydrologic behavior in the host rock has little effect 
on longitudinal temperature variation in the drift. In other words, thermal-hydrologic processes 
in the host rock do not contribute significantly to equalization of axial temperature variations in 
the drift. Therefore, the conduction-only DDT submodel adequately represents longitudinal 
temperature deviations in the drifts or adjoining host rock (relative to line-average-heat-source 
conditions). This assumption is also justified because it tends to preserve temperature variability 
along the drifts. 
Drift-scale latent heat and convective heat transport by seeping water are included in the 
MSTHM methodology because these effects are fully addressed by the LDTH submodels. 
Section 6.2.1 outlines the MSTHM approach and the thermal-hydrologic processes accounted for 
by the model. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in the MSTHM calculations in Sections 6.2.8, 6.3, 
6.4, and 7.5. 
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5.2.3 Waste Package Emplacement 
Assumption: The assumption is made that the entire waste package inventory of the repository is 
emplaced at the same time. 
Rationale: The heat-generation-rate-versus-time tables (BSC 2004 [DIRS 167369]) for the 
entire waste package inventory, as well as for the individual waste package types (BSC 2004 
[DIRS 167754]), were effectively developed for a single time of emplacement and therefore, do 
not represent how the heat-generation-rate tables may vary for the inventory and respective 
waste package types during the 23-year emplacement period. Therefore, this assumption is 
consistent with the heat-generation-rate-versus-time tables. The 50-year ventilation duration is 
the minimum time that any waste package location in the repository will experience ventilation. 
For a sequential emplacement repository analysis with all waste packages assumed to be the 
same years out of reactor at the time of emplacement, packages emplaced at the beginning of the 
23-year period would experience higher peak temperatures relative to those emplaced at the end 
of the emplacement period. The assumption that all waste packages are emplaced 
simultaneously at 50 years results in an analysis that bounds peak temperatures compared to an 
analysis that accounts for sequential emplacement after a minimum 50-year ventilation period. 
Thus, this assumption requires a minimum 50-year ventilation period in order to bound peak 
temperatures. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is applied to all submodels, and is used in the MSTHM 
calculations in Sections 6.3, 6.4, and 7.5. 
5.3 MATERIAL PROPERTIES 
5.3.1 Hydrologic Properties 
5.3.1.1 Permeability of the Drip Shield and Waste Package for the MSTHM 
Assumption: The drip shield and waste packages are assumed to be impermeable to liquid-phase 
flow for the entire duration of the MSTHM simulation. The drip-shield is not impermeable to 
gas-phase flow. 
Rationale: Because it is not the purpose of the MSTHM model to predict the consequences of 
seepage onto (or through) the waste package, the assumption that the drip-shield and waste 
package are impermeable to liquid-phase flow does not affect the intended purpose of the 
MSTHM. The drip shield will have joints where the drip-shield segments meet. The joints 
between the drip-shield segments allow the transport (by advection and binary diffusion) of gas 
(air plus water vapor) between the inside and outside of the drip shield. Note that the assumption 
of the continuity of Pv across the drip shield is also used in In-Drift Natural Convection and 
Condensation (BSC 2004 [DIRS 164327], Section 5.3.6), the calculations from which are used 
as bounding cases only for TSPA-LA. 
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Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Section 6.3. 
5.3.1.2 Hydrologic Properties of the Intragranular Porosity in the Invert Materials 
Assumption: The hydrologic properties of the intragranular porosity of the invert materials are 
assumed to be the same as those of the matrix of the host rock. Because the Tptpll (tsw35) unit 
is the host-rock unit for 75.1 percent of the repository area as modeled in the MSTHM (Table 
6.3-3), it is assumed that matrix properties of the tsw35 unit are applicable to the crushed-tuff 
invert for the entire repository area. The ratio of the surface area of the crushed tuff grains 
divided by the connection length into the grains is assumed to be 1  105 for the intragranular 
porosity. These assumptions are used in all LDTH submodels (Sections 6.2.6 and 6.3). 
Rationale: The invert is composed of crushed-tuff gravel, which is derived from the host rock. 
The dual-permeability model (DKM) is applied to represent flow in crushed-tuff gravel, with 
flow within the tuff grains (called the intragranular porosity) corresponding to flow in the matrix 
continuum of the DKM, and flow around the tuff grains (called the intergranular porosity) 
corresponding to flow in the fracture continuum of the DKM. Therefore, it is reasonable to 
assume that the hydrologic properties of the intragranular porosity are the same as those for the 
matrix of the predominant host-rock unit. Applying the intact host-rock matrix properties to the 
intragranular porosity of the invert implies that there is no reduction in the rewetting rate of the 
invert by virtue of limited rock-to-grain or grain-to-grain contact area. The limited contact area 
will not prevent the crushed-tuff grains from eventually attaining capillary-pressure equilibrium 
with the adjoining host rock. When the drift wall has rewet to ambient liquid-phase saturation, 
relative humidity at the drift wall will be very high (> 99 percent). The crushed-tuff grains in the 
invert cannot remain dry when exposed to a high-relative humidity environment. However, the 
limited rock-to-grain (and grain-to-grain) contact area may impede the rate at which rewetting 
allows the invert to attain capillary-pressure equilibrium with the adjoining host rock. Thus, 
there is some uncertainty about the time required for the invert to rewet to ambient liquid-phase 
saturation conditions. The fact that the crushed-tuff invert could be derived from material from 
the other three host-rock units (Tptpll, Tptpmn, and Tptpln) is also a source of uncertainty with 
respect to the time required for the invert to rewet to ambient liquid-phase saturation conditions. 
The assumption that the ratio of the surface area of crushed-tuff grains divided by the connection 
length into the grains is equal to 1  105 affects the disequilibrium between the intergranular 
porosity and the intergranular porosity. For 3-mm-diameter grains and 45 percent intergranular 
porosity that apply to the invert (Table 4.1-2), this ratio is 7.33  105. Using a value of 1  105, 
which is a ratio smaller than 7.33  105, is appropriate because it is unlikely that all of the grain 
surfaces will be wetted as water drains through the intergranular porosity. 
Section 6.3-11 discusses a sensitivity analysis of thermal-hydrological conditions in the invert to 
hydrologic properties of the intragranular porosity of the crushed-tuff gravel. Figure 6.3-63 plots 
the liquid-phase saturation for the intragranular porosity and the temperature averaged over the 
invert. Four different cases are considered, with each case utilizing the matrix properties from 
each of the respective host-rock units: Tptpul (tsw33), Tptpmn (tsw34), Tptpll (tsw35), and 
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Tptpln (tsw36). Invert temperature is insensitive to the hydrologic properties of the intragranular 
porosity (Figure 6.3-63b). Liquid-phase saturation is also insensitive to hydrologic properties of 
the intragranular porosity (Figure 6.3-63a). Figure 6.3-64 plots temperature and relative 
humidity at different locations in the drift, including the host rock at crown of the drift and below 
the invert, and at the top and bottom of the invert beneath the drip shield for crushed-tuff gravel 
derived from each of the host-rock units, respectively. Both temperature and relative humidity at 
those locations are insensitive to hydrologic properties of the intragranular porosity. This lack of 
sensitivity justifies this assumption. 
Confirmation Status: Because these assumptions are considered to be adequate, they do not 
require further confirmation. 
Use in the Model: This assumption is used in Section 6.3. 
5.3.1.3 Hydrologic Properties for the Concrete Invert in the Drift Scale Test 
Assumption: The hydrologic properties for the Tptpmn (tsw34) host rock in the Drift Scale Test 
(DST) are assumed to be applicable to the concrete invert in the Heated Drift of the DST. 
Rationale: Hydrologic properties for the concrete invert were not measured and are not readily 
available from the literature. Because the invert comprises such a small volume relative to the 
thermally perturbed volume of the host rock in the DST, this assumption is justified. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Section 7.4. 
5.3.1.4 Fracture Permeability of the Host Rock in the Wing-Heater Array of the Drift 
Scale Test 
Assumption: The boreholes that contain the wing heaters in the Drift Scale Test (DST) are not 
explicitly represented in the DST thermal-hydrologic models. The boreholes, which intersect the 
Heated Drift are not sealed and provide preferential conduits for gas flow. It is assumed that 
increasing the fracture permeability by a factor of 1,000, in the lateral (horizontal) direction, for 
the wing-heater array (Figures 7.4-2 and 7.4-16) adequately represents the influence of the 
wing-heater boreholes as preferential conduits to gas flow. Note that the lateral direction is 
parallel to the axis of the wing-heater boreholes. Note also that for the interval between the wing 
heaters and the Heated Drift the fracture permeability is also increased by a factor of 1,000 in the 
lateral (horizontal) direction. 
Rationale: The wing-heater arrays consist of 50 open boreholes (with 25 boreholes located on 
each side of the Heated Drift) that function as preferential conduits (in the lateral direction) to 
gas flow within the boiling and dryout zones of the DST. The effect on thermal-hydrologic 
behavior is to provide a means of relieving gas-phase pressure buildup in the center of the 
boiling zone and to allow some of the water vapor generated in that zone to enter the Heated 
Drift and exit through the leaky bulkhead. A thousand-fold increase in lateral fracture 
permeability effectively eliminates resistance to gas flow from the wing-heater array into the 
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Heated Drift. In Section 7.4, it is found that modeled temperatures and liquid-phase saturations 
are weakly dependent on whether water vapor leaves the DST through the bulkhead. It should 
be noted that much of this water vapor entered in the Heated Drift from the wing-heater array. 
Therefore, the assumption for fracture permeability in the wing-heater array is justified in light 
of its small impact on modeled thermal-hydrologic behavior in the DST. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Section 7.4. 
5.3.1.5 Permeability of the Bulkhead in the Drift Scale Test 
Assumption: The bulkhead in the Drift Scale Test (DST) is assumed to be extremely permeable, 
with a permeability one-tenth that of the open drift. This assumption is made because the 
bulkhead is not sealed and because it contains several openings between the hot and cold side of 
the bulkhead. 
Rationale: Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 
170338], Section 7.4.4) discusses how the bulkhead functions as an open boundary for gas-phase 
flow. In Section 7.4, it is found that modeled temperatures and liquid-phase saturations are 
weakly dependent on whether water vapor leaves the DST through the bulkhead. Therefore, the 
assumption for the permeability of the bulkhead is justified in light of its small impact on 
modeled thermal-hydrologic behavior in the DST. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Section 7.4. 
5.3.1.6 Permeability of the Bulkhead in the Three-Dimensional Monolithic 
Thermal-Hydrologic Model Used in the MSTHM Validation Test Case 
Assumption: The nested-mesh three-dimensional monolithic thermal-hydrologic model, which is 
called the D/LMTH model and used in the MSTHM validation test case (Section 7.5), has a 
leaky bulkhead located just beyond the last waste package at the edge of the drift. It is assumed 
that this bulkhead is leaky, with the same bulk permeability as that of the adjoining fractured 
rock mass. 
Rationale: The influence of an extremely leaky bulkhead on the DST thermal-hydrologic model 
results is investigated in Section 7.4, where it is found that modeled temperatures and 
liquid-phase saturations are weakly dependent on whether water vapor leaves the DST through 
the bulkhead. Therefore, the permeability of the bulkhead in the DST has a small impact on 
modeled thermal-hydrologic behavior in the DST. Because the thermally perturbed (boiling) 
zone of the DST is in closer proximity to the bulkhead than it will be for most of the interval of 
most emplacement drifts in the repository, the impact of the bulkhead on predicted 
thermal-hydrologic conditions along emplacement drifts will be no greater than that 
demonstrated for the DST in Section 7.4. Therefore, the assumed permeability of the bulkhead 
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in the three-dimensional monolithic D/LMTH model does not play a significant role in 
thermal-hydrologic behavior predicted in that model; thus, this assumption is justified. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Section 7.5. 
5.3.1.7 Pseudo Permeability of the Gas-Filled Cavities Inside the Emplacement Drifts in 
the LDTH Submodels 
Assumption: The gas-filled cavity between the drip shield and drift wall is represented as a 
porous media with 100 percent porosity and a very large value of pseudo permeability of 
2
1.0  10-8 m. 
Rationale: The value for permeability (1.0  10-8 m2) for the gas-filled cavity in the 
emplacement drifts is much larger than the bulk permeability (which is nearly the same as the 
fracture permeability in Table IV-4) of the four host-rock units (7.8  10-13, 3.3  10-13, 
2
9.1  10-13, and 1.3  10-12 m for the tsw33, tsw34, tsw35, and tsw36, respectively). The 
effective permeability is large enough so that it does not impede advective gas-phase flow within 
the emplacement drifts. Because the LDTH submodel, in principle, allows natural convection to 
occur within the drift cavity, a possible concern is whether the in-drift convective cooling effect, 
together with the use of the effective thermal conductivity for the drift cavity, will over-account 
for the magnitude of in-drift convective cooling. Section 6.3.10 discusses a sensitivity analysis 
of in-drift pseudo permeability. Figure 6.3-62 plots drip-shield temperature and relative 
humidity for six different values of in-drift pseudo permeability, ranging over six orders of 
magnitude. Over this six order of magnitude range, the value of in-drift pseudo permeability has 
an insignificant influence on in-drift temperature and relative humidity. The range in peak drip-
shield temperature is 150.9oC to 151.1oC for these cases. Clearly, there is no over-accounting of 
convective cooling in the LDTH submodels that support the MSTHM calculations in this report. 
Therefore, the approach of using an effective thermal conductivity for the drift cavity and a value 
of pseudo permeability of 1.0  10-8 m2 is reasonable and appropriate in the LDTH submodels. 
Confirmation Status: Because this assumption is considered to be adequate, it does not require 
further confirmation. 
Use in the Model: This assumption is used in Sections 6.3, 6.4, 7.4, and 7.5. 
5.3.1.8 Permeability of the Intergranular Porosity of the Invert Materials 
Assumption: The permeability of the intergranular porosity of the crushed-tuff invert is 
1.0  10-9 m2, which is between the permeability values for the 0.317-mm particle size 
(1.681  10-10 m2) and for the 3-mm particle size (1.511  10-8 m2) from Table X-7 of Appendix 
X. 
Rationale: The potential range of values for the permeability of the intergranular porosity of the 
crushed-tuff invert (Table X-7 of Appendix X) has little effect on thermal-hydrologic conditions 
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in the invert for two reasons. The first reason relates to liquid-phase flow. An inspection of the 
LDTH submodel output related to the MSTHM base-case calculations for the TSPA-LA shows 
that the intergranular porosity remains dry for all but the initial one-to-two years of the 
postclosure period. During the first year or two following the end of the ventilation period, 
boiling and condensation within the invert results in a very small amount of condensate drainage 
at the base of the invert. After this condensate has drained and the invert has become dry as a 
result of boiling, the intergranular porosity is completely dry (i.e., 100 percent gas-filled). 
Therefore, liquid-phase flow in the intergranular porosity does not occur after the brief period of 
condensate drainage. The second reason relates to gas-phase flow. The value for permeability 
(of 1.0  10-9 m2) for the intergranular porosity of the crushed-tuff invert is much larger than the 
bulk permeability (which is nearly the same as the fracture permeability in Table IV-4) of the 
2
four host-rock units (7.8  10-13, 3.3  10-13, 9.1  10-13, and 1.3  10-12 m for the tsw33, 
tsw34, tsw35, and tsw36, respectively). The effective permeability is large enough that it does 
not impede advective gas-phase flow within the emplacement drifts. 
Section 6.3-11 discusses a sensitivity analysis of thermal-hydrological conditions in the invert to 
hydrologic properties of the intergranular porosity of the crushed-tuff gravel. Figure 6.3-65 plots 
the liquid-phase saturation for the intragranular porosity, temperature, and relative humidity at 
the top of the invert beneath the drip shield for five different sets of hydrologic properties for the 
intergranular porosity. Temperature, liquid-phase saturation, and relative humidity are all 
insensitive to the hydrologic properties of the intergranular porosity. This lack of sensitivity 
justifies this assumption. 
Confirmation Status: Because this assumption is considered to be adequate, it does not require 
further confirmation. 
Use in the Model: This assumption is used in Section 6.3. 
5.3.1.9 Tortuosity Factor for Binary Gas-Phase Diffusion 
Assumption: Appropriate values for the tortuosity factor are selected for the matrix and fracture 
continuum on the basis of the parameter range given by de Marsily (1986 [DIRS 100439], 
p. 233), which ranges from a value of 0.1 for clays to 0.7 for sands. A value of 0.2 is estimated 
for the matrix continuum because the pore sizes for the matrix are closer to that of clays than to 
that of sands. A value of 0.7 is assumed for the fracture continuum because the effective pore 
sizes for fractures are similar to those of sands. 
Rationale: The tortuosity factor is used for determining the binary gas-phase diffusion of air and 
water vapor. Binary gas-phase diffusion is insignificant to the MSTHM results because its 
influence is primarily confined to being an insignificant impact on heat flow, compared to the 
impact of conductive and convective heat flow (Buscheck and Nitao 1994 [DIRS 130561], pp. 
15 to 16). Therefore, exact quantification of the tortuosity factor is not required; instead 
appropriate values are taken from the literature, as discussed above. A value of tortuosity factor 
of 0.2 is selected for the rock matrix because the pore sizes of the matrix are similar to those of 
clay, which has a value for tortuosity factor of 0.1. The tortuosity factor is set to 0.7 for the 
fractures, which corresponds to the highest value reported by de Marsily (1986 [DIRS 100439]), 
which corresponds to the value for sand. Binary gas-phase diffusion is further modified for the 
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fracture-to-fracture connections by multiplication of the tortuosity factor by the fracture porosity 
of the bulk rock (Buscheck and Nitao 1994 [DIRS 130561], Equation 8). This operation yields 
the appropriate value for fracture-to-fracture interconnection area. Similarly, binary gas-phase 
diffusion is modified for the matrix-to-matrix connections by multiplication of the tortuosity 
factor by the matrix porosity of the bulk rock. This operation yields the appropriate value for the 
matrix-to-matrix interconnection area. 
Confirmation Status: Because this assumption is considered to be adequate, it does not require 
further confirmation. 
Use in the Model: This assumption is used in Sections 6.3, 7.3, 7.4, and 7.5. 
5.3.1.10 Permeability of Host Rock at Emplacement Drift Wall 
Assumption: The permeability of the host rock at the drift-wall surface is assumed to be 
unaffected by the presence of Bernold-style surface sheets, which are described by Michel (1999 
[DIRS 163054]), Ground Control for Emplacement Drifts for LA (BSC 2004 [DIRS 170292]), 
and Longevity of Emplacement Drift Ground Support Materials for LA (BSC 2003 
[DIRS 165425]). Thus, it is assumed that the drift wall can be treated as an uncovered surface, 
with unimpeded gas- and liquid-phase flow between the host rock and drift cavity. 
Rationale: Bernold-style surface sheets (Michel 1999 [DIRS 163054]) are bolted tightly to the 
drift wall to provide ground control for emplacement drifts, as described in Ground Control for 
Emplacement Drifts for LA (BSC 2004 [DIRS 170292]) and Longevity of Emplacement Drift 
Ground Support Materials for LA (BSC 2003 [DIRS 165425]). The Bernold-style surface sheets 
are perforated and corrugated to provide air circulation with the drift cavity (BSC 2004 
[DIRS 170292], Section 6.3.1.2; BSC 2003 [DIRS 165425], Section 6.3.2). Therefore, it is 
reasonable to assume that the Bernold surface sheets have an insignificant influence on the 
permeability of the host rock at the emplacement drift-wall surface. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.3, 6.4, and 7.5. 
5.3.2 Thermal Properties 
5.3.2.1 Thermal Conductivity in SDT, DDT, and SMT Submodels 
Assumption: The thermal conductivity data is provided for both dry and wet conditions. The 
conduction-only submodels (SDT, DDT, and SMT submodels in Section 6.2) cannot explicitly 
represent the influence of liquid-phase saturation on thermal conductivity. Since the rock is 
generally much closer to being fully saturated than being completely dry, the wet value of 
thermal conductivity are applied to all conduction-only submodels. This assumption has an 
insignificant effect on the results of the MSTHM. 
Rationale: This assumption must be judged in light of how the MSTHM combines the results of 
four families of submodels: SDT, DDT, SMT, and LDTH. The MSTHM methodology (see 
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Figure 1-1, Table 1-1, Table 1-2, Table 1-3, Section 6.2.4, and Appendix IX) accounts for the 
influence of thermal-hydrologic processes (including liquid-phase saturation changes) on the 
temperature distribution around and inside the emplacement drifts. Thus the MSTHM fully 
accounts for the significant liquid-saturation dependence of thermal conductivity as it is affected 
by rock dryout and condensation buildup (if any). The LDTH submodels also represent the 
influence of the ambient liquid-phase saturation distribution, which is consistent with that of the 
three-dimensional UZ flow model, on drift-scale heat flow. It is also important to note that the 
zone for which the dry thermal conductivity is applicable is confined to a narrow cylindrically 
shaped dryout zone with a radius generally no greater than 10 m for the mean infiltration-flux 
case (Figure 6.3-4b). The primary influence of the narrow zone of decreased thermal 
conductivity is on temperature buildup in the immediate vicinity of the emplacement drifts; this 
influence is fully captured in the finely gridded LDTH submodels of the MSTHM, which 
account for the liquid-phase saturation dependence of thermal conductivity. While significantly 
affecting the drift-scale temperature gradients around the drifts, this narrow region of reduced 
thermal conductivity has a no influence on mountain-scale heat flow. Because the volume of 
reduced thermal conductivity around the drifts is so small, compared to the scale at which 
mountain-scale heat flow occurs, it has an insignificant influence on mountain-scale heat flow. 
For the purposes of the SDT, SMT, and DDT submodels, the approximation is made that 
ambient liquid-phase saturation is 100 percent. The difference in thermal conductivity between a 
liquid-phase saturation of 90 percent (which is prevalent in the host-rock units) and 100 percent 
is small in comparison to parametric uncertainty of thermal conductivity (Section 6.3.2.2). 
Moreover, the LDTH submodel utilizes the ambient liquid-phase saturation values in 
determining thermal conductivity; thus, for drift-scale heat flow the MSTHM fully accounts for 
the ambient liquid-phase saturation conditions. 
As for the validity of this assumption in the DDT submodel, it should be noted that the DDT 
submodel is only used for two purposes: (1) calculating the temperature difference between the 
waste package and drip shield and (2) calculating the longitudinal temperature variations along 
the drift axis. Neither of these quantities is influenced by whether wet or dry thermal 
conductivity is applied in the host rock. 
Section 7.5 describes the comparison between the MSTHM and a corresponding 
three-dimensional monolithic thermal-hydrologic model of the same three-drift system. The 
good agreement between the MSTHM and the corresponding monolithic thermal-hydrologic 
model attests to the validity of this approach, as well as justifying the appropriateness of the 
assumption of the thermal conductivity used in the SDT, SMT, and DDT submodels. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in the MSTHM calculations in Sections 6.3 and 7.5. 
5.3.2.2 SMT Submodel Saturated-Zone Thermal Properties 
Assumption: The SMT submodel (Section 6.2.5) is the only submodel that explicitly represents 
the saturated zone. An assumption is made that the saturated zone is composed of a material 
with average thermal properties, including thermal conductivity, mass density, and specific heat 
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capacity. The averaging is accomplished by determining area-weighting factors for each of the 
model layers from the UZ model that occur at the water table, which is the base of the grid from 
UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]). 
Rationale: The range in thermal properties of the units occurring at the water table is relatively 
narrow, and because the saturated zone is far enough away from the repository horizon (on the 
order of 300 m), the results of the MSTHM are insensitive to the averaging scheme selected for 
the thermal properties of the saturated zone. 
Confirmation Status: Because the output of the MSTHM is not sensitive to this assumption, the 
assumption is justified and does not require further confirmation. 
Use in the Model: This assumption is used in the MSTHM calculations in Sections 6.3 and 7.5. 
5.3.2.3 Thermal Conductivity and Mass Density for the Dual-Permeability Model 
Assumption: The dual-permeability model (DKM) is comprises a fracture and matrix continuum. 
It is necessary to apportion the bulk thermal property values to the fracture and matrix continua. 
The values of thermal conductivity Kth and mass density . are apportioned to the fracture and 
matrix from the values for the bulk rock mass, based on the fracture porosity ffrac by the 
following relationships: 
Kth,frac = Kth,bulk  (ffrac) 
Kth,mat = Kth,bulk  (1 -ffrac) 
.frac = .bulk  (ffrac) 
.mat = .bulk  (1 -ffrac) 
The apportioning of fracture and matrix values of Kth and .is shown in Table IV-3b in Appendix 
IV. This assumption is used in the MSTHM calculations in Sections 6.3 and 7.5. 
Rationale: This approach conserves the total value of thermal conductivity and the total value of 
mass density. Therefore, the total conductive heat flow is the same as a single continuum with 
the same total value of thermal conductivity. Similarly, during the transient (heat-up) period, the 
correct mass density of the rock mass is honored. This method is only used in the LDTH 
submodels. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.2.6, 6.3, and 7.5. 
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5.3.2.4 Thermal Properties of the Lumped Drip-Shield/Waste Package Heat Source in 
the LDTH Submodels 
Assumption: The drip shield and waste package are represented as a lumped monolithic heat 
source in the LDTH submodels with thermal property values that are an average of the respective 
values for the waste package and drip shield. The mass density, specific heat, and thermal 
conductivity of the lumped monolithic heat source are a mass-weighted average of the respective 
waste package and drip-shield values. 
Rationale: The purpose of the LDTH submodel within the context of the MSTHM 
(Section 6.2.4) does not require that the LDTH submodel provide a description of the 
temperature or hydrological effects inside the drip shield; thus, this assumption is justified. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in the MSTHM calculations in Sections 6.2.6, 6.3, 
and 7.5. 
5.3.2.5 Thermal Properties for the Concrete Invert in the Drift Scale Test 
Assumption: The thermal properties for the Tptpmn (tsw34) host rock in the Drift Scale Test 
(DST) are assumed to be applicable to the concrete invert in the Heated Drift of the DST. It is 
noted that the TSPA-LA design does not include a concrete liner. 
Rationale: Because the invert comprises such a small volume relative to the thermally perturbed 
volume of the host rock in the DST (Figures 7.4-2 and 7.4-16) this assumption has an 
insignificant effect on thermal-hydrologic behavior in the DST; therefore, this assumption is 
justified. Moreover, the comparison between observed and simulated behavior in the DST is 
limited to the host rock, wherein the assumption about invert properties have an insignificant 
effect. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Section 7.4. 
5.3.2.6 Thermal Conductivity and Thickness of the Bulkhead in the Drift Scale Test 
Assumption: The bulkhead in the Drift Scale Test is assumed to have a very large value of 
thermal conductivity (5.5 W/mC) and a thickness of 0.12 m; thus, the thermal conductance of 
the bulkhead is assumed to be approximately 46 W/m2C. 
Rationale: As described in Drift-Scale Test As-Built Report (CRWMS M&O 1998 [DIRS 
111115]), the bulkhead in the Drift Scale Test (DST) consists of a complex mix of steel, glass, 
and fiberglass. The thermal conductance of the bulkhead is assumed to be very large because 
portions of the bulkhead (such as the glass window) are not insulated and because the bulkhead 
is penetrated by a large array of metal conduit containing instrument cables and power lines. 
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Moreover, during the DST, the fiberglass insulation became extremely wet as a result of the 
condensation of water vapor that was passing through the bulkhead. The total effect of these 
conditions results in a large value of thermal conductance for the bulkhead that is very difficult 
to quantify. In Section 7.4, it is found that modeled temperatures and liquid-phase saturations 
are weakly dependent on whether water vapor leaves the DST through the bulkhead. In Section 
7.4, it is also found that the heat loss through the bulkhead resulting from the convection of water 
vapor is much larger than the heat loss resulting from thermal conduction. Therefore, the 
assumption for the thermal conductance of the bulkhead is justified in light of its small impact on 
modeled thermal-hydrologic behavior in the DST. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Section 7.4. 
5.3.2.7 Emissivity of Emplacement Drift Wall 
Assumption: The emissivity at the drift-wall surface is assumed to be unaffected by the presence 
of Bernold-style surface sheets, which are described by Michel (1999 [DIRS 163054]), Ground 
Control for Emplacement Drifts for LA (BSC 2004 [DIRS 170292]), and Longevity of 
Emplacement Drift Ground Support Materials for LA (BSC 2003 [DIRS 165425]). Thus, it is 
assumed that the drift wall can be treated as an uncovered surface, with an emissivity value of 
0.9, which is the value for rock given by Incropera and DeWitt (1996 [DIRS 108184], Table 
A.11). 
Rationale: Bernold-style surface sheets (Michel 1999 [DIRS 163054]) are rock bolted tightly to 
the drift wall to provide ground control for emplacement drifts, as described in Ground Control 
for Emplacement Drifts for LA (BSC 2004 [DIRS 170292]) and Longevity of Emplacement Drift 
Ground Support Materials for LA (BSC 2003 [DIRS 165425]). Because the Bernold surface 
sheets are in good mechanical contact with the surrounding rock, they are in reasonable thermal 
contact with the host rock as well. Thus, with respect to heat transfer in the drift, the influence of 
the Bernold surface sheets is to modify the value of emissivity at the drift-wall surface, compared 
to the value for exposed rock, as is described in Appendix VI. The Bernold-style surface sheets 
are a Type 316 stainless steel, which has an emissivity range of 0.52 to 0.66 (McAdams 1954 
[DIRS 161435]). The value of effective emissivity eeff between the drip shield and drift-wall 
surface is affected by this change in emissivity at the drift wall surface. For the emissivity range 
of 0.52 to 0.66 for Type 316 stainless steel, the value of eeff between the drip shield and drift wall 
is reduced by 6.8 to 15.5 percent, compared to value of eeff used in the MSTHM predictions used 
in TSPA-LA (Appendix VI). Because thermal radiation depends on the difference of the 
respective temperatures each raised to the fourth power (Eq. VI-4), the influence of a 6.8 to 15.5 
percent reduction in the value of eeff is small. When peak temperatures occur at the drift wall and 
drip shield (about 20 years after closure), reducing eeff by 6.8 to 15.5 percent results in a 
drip-shield temperature increase of 0.9 to 2.3oC, with an increase of 1.5oC for the average case 
(Appendix VI). The influence of reducing eeff by 6.8 to 15.5 percent on temperature decreases 
during cooldown after temperatures have peaked. These changes in temperature are insignificant 
compared to the influence of host-rock thermal conductivity uncertainty and percolation-flux 
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uncertainty. Therefore, it is reasonable to assume the Bernold surface sheets have an 
insignificant influence on heat transfer within the drift. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.3 and 6.4. 
5.4 WASTE PACKAGE MODELING 
5.4.1 Average Waste Package Diameter 
Assumption: The waste package outer diameter is 1.644 meters, which is the diameter of the 
21-PWR AP waste package (Table 4.1-2). This value is taken as the average diameter for the 
waste packages emplaced over the entire repository. This information is used only in the DDT 
submodels (Section 6.2.8). 
Rationale: This assumption only influences two aspects of the MSTHM: (1) the temperature 
difference between the waste package and drip shield and (2) the waste package-to-waste 
package variation of this temperature difference. Note that this temperature difference depends 
on the waste package heat output. The 21-PWR AP waste packages, 21-PWR CR waste 
packages, and 44-BWR AP waste packages, comprising the majority of waste packages with an 
appreciable heat output, have diameters of 1.644, 1.644, and 1.674 meters, respectively 
(Table 4.1-2) which are very close to the value of 1.644 meters in the DDT submodels. Table 11 
of D&E /PA/C IED Typical Waste Package Components Assembly (2) (BSC 2004 [DIRS 
169472]) gives the nominal quantities of the various waste package types for the TSPA-LA 
design, including 4,299 21-PWR AP waste packages, 95 21-PWR CR waste packages, 
2,831 44-BWR AP waste packages, and 11,184 total waste packages. Thus, these waste 
packages comprise a large portion (64.6 percent) of the waste package inventory in the 
TSPA-LA design. Waste packages that deviate more from a value of 1.644 meters, such as the 
24-BWR 1.318-m-diameter AP waste packages and the 5-DHLW/DOE-SNF 2.110-m-diameter 
co-disposal waste packages (Table 4.1-2), generate much less heat and also comprise a relatively 
small portion of the overall waste package inventory (BSC 2004 [DIRS 169472], Table 11). 
Therefore, 1.644 meters is very close to the actual diameter for the majority of waste packages in 
the overall inventory and is also very close to the diameter of the waste packages generating an 
appreciable temperature difference between the waste package and drip shield. 
Confirmation Status: On the basis of the rationale given above, this assumption is justified and 
does not require further confirmation. 
Use in the Model: This assumption is used in Sections 6.2.8, 6.3, and 7.5. 
5.4.2 Waste Package Sequence along Drifts 
Assumption: The waste package sequence given in Figure 6.2-2 is assumed to be applicable over 
all emplacement drifts. Thus, this sequence is assumed to be representative of waste package-to-
waste package heat output variability throughout the entire repository. The use of this sequence 
is equivalent to assuming that defense high-level waste (DHLW) waste packages, which produce 
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much less heat than commercial spent nuclear fuel (CSNF) waste packages, will not be grouped 
together. In other words, DHLW waste packages will always be placed adjacent to CSNF waste 
packages. 
Rationale: Table 5.4-1 lists the nominal number of waste packages for the repository inventory. 
Table 5.4-1 also lists the waste packages of the assumed sequence in the MSTHM calculations. 
The waste packages in the assumed sequence in the MSTHM cover 86.7 percent of the total 
inventory. Moreover, the percentages of each of the respective waste package types in the 
MSTHM are similar to the corresponding percentages in the repository inventory. Therefore, the 
waste package sequence assumed in all of the MSTHM calculations is representative of the 
inventory of waste packages in the repository. 
Table 5.4-1. Summary of Waste Package Types in the Repository Inventory and in the MSTHM 
Waste Package Type Nominal 
Number in 
Inventorya 
Nominal 
Percentage 
of Inventory 
Number 
Represented 
in MSTHMb 
Percentage of 
Waste Packages 
Represented in 
MSTHM 
21-PWR AP 4299 38.4% 2.5 35.7% 
44-BWR AP 2831 25.4% 2.5 35.7% 
5 DHLW/DOE SNF LONG 1406 12.6% 1 14.3% 
5 DHLW/DOE SNF SHORT 1147 10.3% 1 14.3% 
Total Number of 21-PWR AP, 44-BWR AP, 
5 DHLW/DOE SNF LONG, 5 DHLW/DOE 
SNF-SHORT 
9683 86.7% 7 100% 
Total Inventory 11,184 100% 7 100% 
a 
Source: BSC 2004 [DIRS 169472 ], Table 11. 
b See Figure 6.2-2 and Table 6.3-13. 
Confirmation Status: On the basis of the rationale given above, this assumption is justified and 
does not require further confirmation. 
Use in the Model: This assumption is used in Sections 6.2.8 and 6.3. 
5.5 RELATIVE HUMIDITY IN EMPLACEMENT DRIFTS 
Assumption: For the purposes of calculating relative humidity (RH) on the drip shield and on the 
waste package the assumption is made that the partial pressure of water vapor Pv in the drift is 
uniform and the same as that on the drift-wall surface at a given location. This is the equivalent 
of saying that the absolute humidity in the drift is the same as that on the drift wall. 
Rationale: This assumption recognizes that the gas in the drift (which consists of air and water 
vapor) is well mixed as a result turbulent mixing (driven by buoyant gas-phase convection) and 
binary vapor diffusion of air and water. This mixing causes the absolute humidity to be uniform 
inside the emplacement drift at a given location along the drift. This assumption is validated in 
Section 7.5 by virtue of the good agreement between the MSTHM predictions of relative 
humidity in the drift and those of the corresponding three-dimensional monolithic 
thermal-hydrologic model, which does not make this assumption about relative humidity in 
emplacement drifts. 
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Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.2.4, 6.3, 6.4, and 7.5. 
5.6 CONDENSATE DRAINAGE AROUND EMPLACEMENT DRIFTS 
Assumption: Condensate that drains around the boiling zone surrounding an individual drift is 
assumed not to cross the vertical midplanes, which lie between that drift and the adjoining 
emplacement drifts (note that these vertical midplanes are 40.5 m away (which is half the 81-m 
drift spacing) from the centerline of each drift). This assumption is implied with the use of the 
two-dimensional LDTH submodels (Section 6.2.6), which have adiabatic, no-fluid-flow 
boundaries on either side of the LDTH submodels. 
Rationale: The boiling zones surrounding each emplacement drift are relatively narrow. As 
discussed in Section 6.3.1.1, the maximum lateral extent of boiling relative to the centerline of 
the emplacement drift is always much smaller than the half-drift spacing for the TSPA-LA 
design. Therefore, the majority of the host rock between emplacement drifts always remains 
below the boiling point, thereby enabling condensate and percolation flux to continuously drain 
between emplacement drifts. Fracturing within the sequence of UZ model layer units at the 
repository horizon is dense and ubiquitous (BSC 2004 [DIRS 169857]), which is not conducive 
to laterally diverting condensate drainage; thus, condensate drainage is extremely unlikely to 
cross the vertical midplane separating emplacement drifts. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.2.8, 6.3 and 7.5. 
5.7 GAS- AND LIQUID-PHASE FLOW IN THE LONGITUDINAL DIRECTION 
ALONG EMPLACEMENT DRIFTS (THE COLD-TRAP EFFECT) 
Assumption: Gas- and liquid-phase flow in the longitudinal direction along drifts is assumed to 
have an insignificant effect on all MSTHM predictions. This is equivalent to saying that the 
cold-trap effect does not play a significant role in the evolution of the temperature, relative 
humidity, and liquid-phase saturation histories within the emplacement drifts, as well as in the 
adjoining host rock. At the repository scale, the cold-trap effect involves the flow of water vapor 
from the hotter intervals of emplacement drifts (typically closer to the center of the repository) to 
cooler intervals (typically located closer to the edges of the repository) where this water vapor 
condenses. In principal, the cold-trap effect results in the transport of heat and moisture from 
hotter to cooler intervals of the emplacement drift. For all MSTHM predictions, it is assumed 
that heat and moisture transport in the longitudinal direction along emplacement drifts do not 
significantly affect thermal-hydrologic conditions along (and adjacent to) emplacement drifts. 
Thus, it is assumed that heat flow along the drifts is dominated by thermal radiation and that 
within the invert there is no capillary wicking of moisture in the longitudinal direction. 
Rationale: This assumption is tested in Section 7.5, where the MSTHM is compared against a 
corresponding three-dimensional monolithic thermal-hydrologic model in which gas- and 
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liquid-phase flow (i.e., the cold-trap effect) is allowed to occur along the emplacement drift, 
subject to limitations of porous media models. For the waste packages at the center of the 
repository, the MSTHM calculations are found to agree closely with those of the 
three-dimensional monolithic thermal-hydrologic model, with the differences between the two 
models being much smaller than the range of thermal-hydrologic conditions arising from 
parametric uncertainty. For the waste packages at the outer edge of the repository, the 
differences between the MSTHM predictions and those of the corresponding three-dimensional 
monolithic thermal-hydrologic model are larger than at the center of the repository. These 
differences, however, are still smaller than the range of thermal-hydrologic conditions arising 
from parametric uncertainty. The results of the validation study in Section 7.5 demonstrate that 
the MSTHM methodology (which includes the assumption of insignificant gas- and liquid-phase 
flow in the longitudinal direction along drifts) is validated for its intended purpose of predicting 
thermal-hydrologic conditions in emplacement drifts and in the adjoining host rock. Thus, this 
assumption is also justified. 
Confirmation Status: Because this assumption is justified, it does not require further 
confirmation. 
Use in the Model: This assumption is used in Sections 6.3 and 6.4, and is tested in Section 7.5. 
5.8 PROPERTIES OF HOST-ROCK RUBBLE FOR LOW-PROBABILITY-SEISMIC 
COLLAPSED-DRIFT SCENARIO 
5.8.1 Bulk Density of Host-Rock Rubble 
In setting up the LDTH and DDT submodels (Sections 6.2.10 and 6.2.11) to represent the low-
probability-seismic collapsed-drift scenario, a value of 1850 kg/m3 was used for the rubble bulk 
density in the LDTH submodels (Table 6.2-3), while a rubble bulk density of 1608 kg/m3 was 
used in the DDT submodels (Table 6.2-4). The bulk density of the intact Tptpll (tsw35) host 
rock is 1980 kg/m3 (Tables IV-3b and IV-3c of Appendix IV). Using a bulk factor of 0.231 
(Section 6.2.10.2) and a bulk density of 1980 kg/m3 for the intact host rock, results in a rubble 
bulk density of 1608 kg/m3. To assess whether this small difference in bulk density is 
significant, the LDTH submodel was rerun for the case where the rubble bulk density is 1608 
kg/m3, so that it could be compared to the case where the rubble bulk density is 1850 kg/m3. As 
is evident in Figure 6.3-58, which plots the temperature and relative humidity at the crown of the 
drip shield for the low-Kth rubble, the influence of rubble bulk density is insignificant over the 
range of 1608 to 1850 kg/m3. Therefore the following assumption can be made. 
Assumption: The use of a bulk density value of 1850 kg/m3 for the host-rock rubble in the 
LDTH submodels for the low-probability-seismic collapsed-drift scenario gives the same 
MSTHM results that would have been produced if a bulk density value of 1608 kg/m3 had been 
used in the LDTH submodels for this scenario. 
Rationale: Because steady-state heat flow conditions are quickly established within the rubble, 
temperature and relative humidity in the drift (Figure 6.3-58) are insensitive to the range in bulk 
rubble density (1680 to 1850 kg/m3) considered in Section 6.3.7. Therefore, the MSTHM 
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calculations for the low-probability-seismic collapsed-drift scenario are insensitive to the choice 
of rubble bulk density (1850 kg/m3 versus 1608 kg/m3). 
Confirmation Status: Based on the rationale given above, this assumption is justified and does 
not require further confirmation. 
Use in the Model: This assumption is used in Section 6.3.7. 
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6. MODEL DISCUSSION
This section of the model report describes the multiscale thermohydrologic model (MSTHM), 
including a discussion about its conceptual framework and how the MSTHM methodology 
implements that framework. The MSTHM is implemented in several input-data-processing and 
submodel-building steps (Figures 6-1 and 6-2). The four major steps are (1) submodel input-file 
preparation, (2) execution of the four submodel families with the use of the NUFT v3.0s code 
(Section 3.1.1), (3) execution of MSTHAC v7.0 (Section 3.1.5), and (4) binning and 
postprocessing (i.e., graphics preparation) of the output from MSTHAC v7.0. The overall 
organization of Section 6 is as follows: 
 Section 6.1 presents the scientific framework for Yucca Mountain thermohydrology, 
beginning with an overview of the ambient hydrological system. This is followed by a 
discussion of radioactive-decay-heat-driven thermal-hydrologic behavior within the 
repository emplacement drifts and in the adjoining repository host rock. 
 Section 6.2 describes the MSTHM approach. Before discussing the details of the 
MSTHM approach, this section presents the governing equations that are solved by the 
NUFT v3.0s and v3.0.1s codes to represent the coupled flow of water, water vapor, air, 
and heat at the drift scale and to represent heat flow at the mountain scale. This is 
followed by a detailed description of the four families of MSTHM submodels, which are 
run with the NUFT code, and the manner in which the Multiscale Thermohydrologic 
Model Abstraction Code (MSTHAC v7.0) integrates the results from those four families 
of submodels. 
 Section 6.3 presents the results of the MSTHM for the lower-bound, mean, and 
upper-bound infiltration-flux cases with mean host-rock thermal conductivity; for the 
lower-bound infiltration-flux case with low host-rock thermal conductivity; and for the 
upper-bound infiltration-flux case with high host-rock thermal conductivity. This 
section also covers the sensitivity analysis of parameter uncertainty. 
 Section 6.4 describes a study that compares the results of the MSTHM against those of a 
corresponding alternative conceptual model. 
Before continuing, it is important to distinguish between the MSTHM and the Multiscale 
Thermohydrologic Abstraction Code (MSTHAC v7.0). The MSTHM is the process-level model 
itself, which consists of four families of submodel types (Section 6.2.4) that are run using the 
thermal-hydrologic simulation code NUFT v3.0s (Section 3.1.1) and the software that integrates 
the results of those submodel families. The integrating software used in this report is 
MSTHAC v7.0 (Section 3.1.5). There were no supporting and corroborating data or product 
outputs used in the development of this model. 
The MSTHM predictions supporting the TSPA-LA utilize assumptions described in Sections 
5.1.1, 5.1.2, 5.1.3, 5.1.4, 5.1.5, 5.2.1, 5.2.2, 5.2.3, 5.3.1.1, 5.3.1.2, 5.3.1.7, 5.3.1.8, 5.3.1.9, 
5.3.1.10, 5.3.2.1, 5.3.2.2, 5.3.2.3, 5.3.2.4, 5.3.2.7, 5.4.1, 5.4.2, 5.5, 5.6, 5.7, and 5.8.1. 
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NOTE: BC = boundary conditions; IC = initial conditions. 
Figure 6-1. Overall Data Flow Diagram for the MSTHM 
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Figure 6-2. Relationship Between Input Data and Submodels for Three Infiltration-Flux Cases 
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6.1 YUCCA MOUNTAIN THERMOHYDROLOGY CONCEPTUAL MODEL 
The role of the movement of water and heat within the repository is treated by the study of 
thermohydrology, which combines the more traditional fields of hydrology and heat transfer. 
The physical domain that this model report is primarily concerned with is the unsaturated zone of 
Yucca Mountain that lies above the groundwater table. The geology of Yucca Mountain consists 
of several sequences of welded and nonwelded volcanic rocks, and the main hydrologic concern 
is with the movement of liquid water, originating from rainfall and snowmelt (Section 6.1.1). 
The thermal component of this model is concerned with the movement of liquid water driven by 
radioactive decay heat from emplaced waste and its effect on temperature and relative humidity 
(Section 6.1.2). When examining thermal-hydrologic phenomena, there are two distinct regions 
of concern: (1) the near-field host rock, and (2) within the repository emplacement drifts. The 
thermal-hydrologic phenomena associated with the host rock primarily involve boiling of water 
and re-wetting as heating diminishes with time (Section 6.1.3), while the thermal-hydrologic 
phenomena within the emplacement drift is associated with boiling, evaporation and 
condensation of water on the waste packages, drip shield, and drift wall (Section 6.1.4). Several 
factors can influence thermal-hydrologic phenomena, either through the design of the repository 
(e.g., the average areal-heat-density of the emplaced waste, as discussed in Section 6.1.5), or 
through the description of the natural system (e.g., percolation flux and thermal conductivity, as 
discussed in Section 6.1.5). 
6.1.1 Ambient Hydrology and Geology 
Yucca Mountain is composed of several sequences of volcanic tuffs deposited as ash flow sheets 
about 13 million years ago. Some units are completely devitrified and welded, while others are 
vitric or partially vitric with various degrees of welding. Some are also zeolitized to varying 
degrees. In general, the more welded units are more densely fractured. Hydrogeologic units, 
referred to as UZ-model layers in the grid developed by UZ Flow Models and Submodels (BSC 
2004 [DIRS 169861], Section 6.1.1), are defined primarily based on the degree of welding 
(Montazer and Wilson 1984 [DIRS 100161], p. 8). From the ground surface to the water table, 
these units are generally referred to as Tiva Canyon welded (TCw), Paintbrush nonwelded (PTn), 
Topopah Spring welded (TSw), Calico Hills nonwelded (CHn) and Crater Flat (Cfu). More 
details about the layering in the UZ are found in Table 6-11 of Development of Numerical Grids 
for UZ Flow and Transport Modeling (BSC 2004 [DIRS 169855]). 
Most of the total fluid storage capacity of the welded units at Yucca Mountain is contained in the 
matrix pores of this rock. The permeability in the rock matrix in these units, however, is low, so 
fractures are the primary conduits for large-scale flow of water, air, and water vapor in these 
units. In some of the nonwelded units, fracturing is much less extensive, and the rock matrix is 
more permeable than in the welded units, causing gas and liquid-phase fluid flow to occur 
predominantly through the rock matrix. 
The climate at Yucca Mountain is arid to semiarid, with infiltration from rainfall and snowmelt. 
Field data show that water that infiltrates at the ground surface percolates mostly vertically 
downward to the water table 700 m beneath the surface, with some degree of lateral diversion 
and the occasional occurrence of perched or semiperched aquifers (Flint et al. 2001 
[DIRS 156351]). Note that under ambient conditions, the relative humidity (RH) in the 
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unsaturated zone at the elevation of the repository is very high with relative humidity generally 
above 99 percent (Buscheck et al. 2002 [DIRS 160749]). 
6.1.2 Incorporating Radioactive Decay Heat 
The repository is located in the unsaturated zone in the TSw hydrostratigraphic unit along a very 
gently dipping plane, approximately midway between the ground surface and the water table. 
The repository will accommodate the emplacement of spent nuclear fuel from commercial 
nuclear power plants and solidified high-level waste. The repository-wide thermal load declines 
exponentially with time, continuing for tens of thousands of years because of the very long 
half-life of many of the radionuclides (Figure 6.1-1). 
NOTE: The total repository heat load divided by the total length of emplacement drift in the repository (57.48 km) is 
equal to the line-averaged heat load. At the time of emplacement (0 yr) the total repository heat load is 
83,300 kW, resulting in an initial line-averaged heat load of 1.45 kW/m. It is important to note that this is a 
semilog plot. At the time that this plot begins (1 year), the total repository heat load is 80,400 kW. This is 
the total thermal load represented in the SMT submodel (Section 6.2.5), using the information from BSC 
2004 [DIRS 167369], Table 13. 
Figure 6.1-1. Repository-Wide Thermal Load Plotted as a Function of Time for the TSPA-LA Design. 
After the emplacement of heat-generating nuclear waste, the thermally driven flow of water 
vapor away from the heat source causes a redistribution of the pore fluids in the rock. Water in 
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the matrix pores evaporates, creating zones of rock dryout (with liquid-phase saturation 
substantially less than ambient values) around the emplacement drifts. This water vapor is 
driven (primarily in fractures) away from the heat source in the emplacement drifts to where 
cooler temperatures cause it to condense, forming condensation zones outside of the dryout 
zones. The reduction in liquid-phase saturation causes a reduction in relative humidity in both 
the near-field host rock as well as in the emplacement drifts. Heat pipes can result from the 
countercurrent flow of water vapor and liquid water between the dryout and condensation zones. 
The magnitude of the liquid flux in a heat pipe can greatly exceed the magnitude of ambient 
liquid-phase fluxes. As the heat pulse decays, the system gradually rewets, returning to ambient 
(humid) preheating conditions. 
6.1.3 Thermohydrology in the Repository Host Rock 
In the host rock, local thermal-hydrologic behavior is dominated by whether a location is inside 
or outside of the zone of boiling temperatures, 96C (Buscheck et al. 2002 [DIRS 160749]) at the 
elevation of the repository horizon at Yucca Mountain approximately 1,100 m above mean sea 
level. Although evaporation, vapor flow (away from the heat source), and condensation occur at 
below-boiling temperatures, the thermally driven vaporization rates and vapor fluxes in the 
repository horizon are generally not great enough to result in significant dryout (and relative 
humidity reduction) in the rock unless temperatures are well above the boiling point. 
The boiling zone evolves with time. Because most of the decay heat is removed with the 
ventilation air, temperatures are not high enough to allow boiling to occur during the preclosure 
(ventilation) period. However, because the ventilation air has a much lower relative humidity 
than ambient conditions in the host rock, some dryout will occur during the preclosure 
(ventilation) period. At the onset of the postclosure period when ventilation stops, a dryout zone 
caused by boiling-to-above-boiling temperatures forms in the rock immediately encircling each 
individual emplacement drift. Within this dryout zone, vaporization prevents liquid-phase flow. 
Moreover, capillary diversion will continue to divert liquid flow away from the drift opening, 
even after temperatures have dropped below the boiling point. As thermal output wanes, the 
dryout zones shrink, and the extent of dryout eventually retreats back to the drift wall (Section 
6.2.2.1 of BSC 2004 [DIRS 170338]). Dryout zones around adjacent emplacement drifts never 
coalesce; they always remain distinct and separate. 
Whether or not the boiling zones around adjacent drifts coalesce is important because it affects 
condensate drainage between drifts. If the repository (thermal) design does not result in 
coalescence of boiling zones, condensate drains continuously between the emplacement drifts. 
As discussed in Section 6.3.1.1, the maximum lateral extent of boiling relative to the centerline 
of the emplacement drift is always much smaller than the half-drift spacing for the TSPA-LA 
repository (thermal) design. Therefore, much of the host rock between emplacement drifts 
always remains below the boiling point, enabling condensate and percolation flux to 
continuously drain between emplacement drifts. Accordingly, the cap of accumulated 
condensate above the emplacement drifts is of very limited spatial extent. Variation in the 
spatial extent and duration of the boiling zone along the drift axis may also be important. 
Nonuniformity in boiling conditions along the drift axis (resulting from waste package-to-waste 
package variability in heat output) causes longitudinal variability in the radial extent and 
duration of boiling, and may promote seepage and/or condensation in the vicinity of cooler waste 
packages. The end-to-end waste package spacing (with 10-cm gaps separating waste packages) 
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(Table 4.1-2) used in the TSPA-LA repository design limits this longitudinal variability (Section 
6.3.1.2). 
6.1.4 Thermohydrology in Repository Emplacement Drifts 
The TSPA-LA repository design includes 1.6-to 2.1-m-diameter (on average) waste packages 
constructed of corrosion-resistant materials, which are overlain by upside down, U-shaped, 
corrosion-resistant metallic barriers called drip shields. Both the waste packages and drip shields 
are supported on an invert made of granular material on the floor of the drift. The configuration 
of these engineered components influences thermohydrologic behavior within the emplacement 
drifts. 
Two important factors influence the local thermohydrologic conditions in the emplacement 
drifts. The first is whether temperature at the drift wall is above the boiling point, which controls 
the relative humidity in the near-field host rock and the potential for water seeping into the drift. 
The second is the temperature difference between the waste package and drift wall, which 
determines the relative humidity on the surfaces of the drip shield and waste package (Figure 
6.1-2). Specifically, the temperature difference between the waste package (or drip-shield) 
surface and the drift wall determines how much lower the relative humidity is on the waste 
package (or drip-shield) surface, compared to that on the drift wall. Note that the ratio of relative 
humidity on the waste package to relative humidity on the drift wall for a given temperature 
difference between these two surfaces decreases as the absolute temperature on the waste 
package increases during heating. Because of the edge-cooling effect, waste packages located 
closer to the repository edges cool down more quickly than those located closer to the repository 
center. Consequently, relative humidity reduction for waste packages located closer to the 
repository edges can be greater than for those located closer to the repository center. 
Thermal-hydrologic behavior in and around emplacement drifts is easily described by three 
fundamental processes: 
1. Heat flowOccurs within emplacement drifts primarily by thermal radiation, and in the 
adjoining host rock, primarily by thermal conduction. Host-rock thermal conductivity is 
the key natural-system parameter determining the magnitude of temperature buildup in 
the host rock. 
2. Host-rock dryoutIs driven by temperature buildup, resulting in evaporation (at the 
boiling point), which lowers the liquid-phase saturation in the host rock, thereby lowering 
the relative humidity in the host rock and in the emplacement drifts. The extent of dryout 
depends on the extent and duration of boiling conditions in the host rock, which depend 
on the magnitude of temperature buildup. 
3. Host-rock rewettingPrimarily occurs as a result of gravity-driven percolation in 
fractures, with capillary-driven imbibition into the adjoining matrix. The rate of 
rewetting is controlled by the local percolation flux, except in regions of very low 
percolation flux (less than approximately 0.1 mm/yr), where modeling analyses show it is 
controlled by capillary-driven imbibition of water from the surrounding rock into the 
dryout zone, through the rock matrix. 
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Source: See Table XIII-1. 
NOTE: The ratio of relative humidity (RH) on the waste package surface to relative humidity on the drift-wall 
surface versus the temperature difference between these surfaces is plotted for three different 
temperatures (taken to be the average of the drift wall and waste package temperatures). 
Figure 6.1-2. Ratio of Relative Humidity (RH) on the Waste Package Surface to Relative Humidity on 
the Drift-Wall Surface 
The processes of dryout and rewetting are opposing. Net host-rock dryout, which is the balance 
between dryout and rewetting, is greatest in regions with a combination of low host-rock thermal 
conductivity (which facilitates greater temperature buildup) and low local percolation flux 
(which facilitates slower rewetting). Net host-rock dryout is least in regions with a combination 
of high host-rock thermal conductivity (which facilitates smaller temperature buildup) and high 
local percolation flux (which facilitates faster rewetting). 
The temperature at the drift wall is controlled by the temperature buildup in the host rock, which 
is controlled by the local heating conditions and the host-rock thermal conductivity. The relative 
humidity at the drift wall is controlled by the reduction in liquid-phase saturation that results 
from boiling and rock dryout. The relative humidity at the drift wall controls relative humidity 
conditions within the drift; relative humidity in the drift can be no greater than it is at the drift 
wall. This is true because the absolute humidity within the drift is uniform or nearly so. Heat 
transfer between engineered components (such as the waste package and drip shield) and the 
drift wall determines the temperature difference between the waste package and drift wall. This 
temperature difference controls the reduction in relative humidity on the waste package, relative 
to that on the drift wall. The drip shield, which lies between the waste package and drift wall, 
functions as a thermal-radiation shield, which increases this temperature difference. The 
temperature difference between the waste package and the drift wall is greatest immediately after 
closure, and slowly decreases with time. 
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During the preclosure period (nominally 50 years), waste package heat output starts at the 
maximum, but the emplacement drifts are ventilated to remove most of the heat. Waste package 
temperatures are elevated, and some packages may approach 100C immediately after 
emplacement (subject to control by ventilation). However, the warming of ventilation air 
ensures that preclosure conditions are dry (e.g., less than 20% relative humidity), especially 
where in-drift temperatures are greatest. 
At permanent closure, ventilation ceases and the drift-wall rock temperature is initially below 
boiling, but increases sharply, with temperature peaking within about 20 years. Waste package 
temperatures follow the evolution of the local drift-wall temperature, but are as much as 10 to 
20C warmer at the time when waste package temperatures peak, because of thermal resistance 
across the drip shield and the in-drift air spaces. This temperature difference approaches zero 
with time, as the heat output declines. The maximum postclosure temperature of a waste 
package at any location is determined by the history of heat output, the resistance to dissipation 
of heat in the host rock, heat transfer from the waste package to the drift wall, and the 
relationship to other nearby heat sources. 
6.1.5 Design Factors Influencing Thermohydrology 
There are many thermal design parameters that can affect thermohydrologic behavior in an 
underground nuclear waste repository (Table 6.1-1). These include the average 
areal-heat-generation density of the waste inventory over the heated repository footprint, and the 
average lineal-heat-generation density along the drifts (called the line-averaged thermal load). 
For a given waste inventory, these two parameters constrain the distance between drifts and the 
size of the required repository footprint. 
Other engineering parameters include the placement of the repository horizon relative to the 
ground surface and the local hydrostratigraphy. The depth of the repository below the ground 
surface (overburden thickness) translates into the thickness of insulating rock between the 
repository and the ground surface, which acts like a heat sink. In-drift configuration, including 
most notably the presence or absence of backfill in the emplacement drifts, and the properties of 
any in-drift materials are also important to thermohydrology. 
Waste package spacing affects the degree of nonuniformity of heating conditions along the axis 
of the drift. Individual waste packages are cylindrical in shape and 3.5 to 5.1 m long 
(Table 4.1-2). If waste packages are spaced far apart from each other along the drift 
(point-load waste package spacing), heating conditions along the drift are less uniform. For 
waste packages spaced nearly end-to-end (line-load waste package spacing), and which is the 
TSPA-LA repository design, adjacent waste packages couple and share their heat output more 
effectively, acting more like a uniform line source of heat. Line-load waste package spacing 
results in more uniform, and persistent rock dryout around the drifts and more efficient 
condensate shedding between drifts than does point-load waste package spacing with the same 
overall areal-heat-generation density. Point-load waste package spacing results in less uniform 
rock dryout around the drifts and less uniform thermohydrologic conditions along the drifts 
(Buscheck et al. 1999 [DIRS 145972]; Buscheck et al. (2002) [DIRS 160749]). 
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Table 6.1-1. Key Thermal Design Factors and Natural System Parameters Influencing 
Thermal-Hydrologic Conditions in the Emplacement Drifts and Near-Field Host Rock. 
Engineering Design Factors Natural System Parameters 
 
 
 
Overall areal-heat-generation density of waste 
inventory 
Line-averaged thermal load along drifts 
Distance between emplacement drifts 
 
 
 
 
Percolation flux above the repository horizon 
Thermal conductivity (particularly for host-rock units) 
Bulk rock density and specific heat 
Matrix imbibition 
 
 
Age of spent nuclear fuel at time of emplacement 
Location of repository horizon with respect to 
stratigraphy 
 Capillary wicking in fractures 
 Overburden thickness (depth of repository below 
ground surface) 
 Repository footprint 
 Waste package spacing (line load versus point load) 
 Waste package sequencing 
 Duration and heat-removal efficiency of drift 
ventilation 
 In-drift design and materials 
6.1.6 Natural System Factors Influencing Thermohydrology 
Important natural system factors that affect the thermal-hydrologic environment include thermal 
properties of the repository host rock, hydrologic properties of the host rock, and the magnitude 
and spatial and temporal distribution of the percolation flux above the repository horizon (Table 
6.1-1). Of these factors, the host-rock thermal conductivity and percolation flux above the 
repository horizon are the most important. 
6.2 THE MULTISCALE THERMOHYDROLOGIC MODELING APPROACH 
6.2.1 Overview of the MSTHM 
The multiscale thermohydrologic model simulates nonisothermal, multiphase-flow in fractured 
porous rock of variable liquid-phase saturation and thermal radiation and convection in open 
cavities. The motivation behind the multiscale modeling approach is the need for a modeling 
tool that simultaneously accounts for relevant features, events, and processes (FEPs) that occur at 
a scale of a few tens of centimeters around individual waste packages and emplacement drifts 
and also at the scale of the mountain. A single numerical model is not used because it requires 
too large a computational cost to be a viable simulation tool. Note that performance assessment 
requires the ability to conduct multiple realizations. The multiscale modeling approach was used 
to model more than 20 different realizations for Total System Performance Assessment-Viability 
Assessment (TSPA-VA) Analyses Technical Basis Document (CRWMS M&O 1998 [DIRS 
108000], Chapter 3). The approach was also used to model fourteen alternative repository 
designs during the license application design selection process (Buscheck 1999 [DIRS 130078]) 
and in six different realizations for Total System Performance Assessment for the Site 
Recommendation (CRWMS M&O 2000 [DIRS 153246], Section 3.3.3) and six different 
realizations for FY 01 Supplemental Science and Performance Analyses, Volume 1: Scientific 
Bases and Analyses (BSC 2001 [DIRS 155950], Section 5). The following description is a brief 
overview; a detailed description of the MSTHM is found in Section 6.2.4. 
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The multiscale approach breaks the solution of thermal-hydrologic modeling at Yucca Mountain 
into smaller pieces by varying dimensionality requirements (one-, two-, or three-dimensional) as 
needed for detail. The approach further subdivides the problem into thermal and 
thermal-hydrologic submodels. By subdividing the problem into more tractable pieces, the DOE 
can use efficient thermal-conduction/radiation submodels to address the three-dimensional nature 
of the heated repository footprint and mountain-scale heat flow as well as the three-dimensional 
geometric details of the in-drift engineered components, waste package-to-waste package 
heat-generation variability, and drift-scale heat flow. Two-dimensional thermal-hydrologic 
models, which are more efficient than three-dimensional thermal-hydrologic models, are used to 
model all thermal-hydrologic parameters in detail within the emplacement drifts and in the 
adjoining host rock. 
Thermohydrologic behavior is directly simulated for an average waste package using a 
two-dimensional drift-scale cross section for a variety of areal-heat-generation densities at 
numerous locations throughout the repository footprint. In these simulations, the flow of liquid 
and gas (water vapor and air) through variably saturated fractured porous media is represented 
with a dual-permeability model of flow interaction between the fractures and rock matrix. This 
model accounts for two-phase behavior (i.e., evaporation, boiling, and condensation). Open 
drifts are modeled as porous media with very high permeability and porosity. The influence of 
buoyant gas-phase (natural) convection in the drift on heat flow is approximated with the use of 
an effective thermal conductivity for the gas-filled drift cavity that is based on a correlation 
(Francis et al. 2003 [DIRS 164602], Table 6). The model represents the processes of thermal 
conduction and convection in rock, and thermal conduction, convection, and radiation in the 
open cavities in the emplacement drifts. 
The primary purpose of the multiscale thermohydrologic model is to predict the evolution of 
thermal-hydrologic conditions within emplacement drifts. To accomplish this it is necessary to 
predict thermal-hydrologic conditions in the adjoining host rock. As discussed in Section 6.1.4, 
thermal-hydrologic behavior in and around emplacement drifts can be simply broken down to 
three fundamental processes: (1) heat flow, (2) host-rock dryout, and (3) host-rock rewetting. A 
key principle utilized by the multiscale thermal-hydrologic model approach is that 
mountain-scale heat flow is dominated by thermal conduction. A second key principle is that 
heat flow within the drift is dominated by thermal radiation and that the influence of natural 
convection on heat flow within the drift can be approximated with an effective thermal 
conductivity. To summarize, the multiscale thermal-hydrologic model must represent the 
following processes: 
1. Heat flow within the driftThe range of heat output generated by various waste package 
types and the delivery of that heat to the drift wall. 
2. Mountain-scale heat flowConduction of heat throughout the mountain, from the 
ground surface down to a sufficient depth, which includes the entire unsaturated zone 
plus the upper portion (1000 m) of the saturated zone. 
3. Drift-scale heat flow in the host rockHeat flow (primarily by conduction, but also 
convection) occurring in variably saturated, fractured porous rock. Because thermal 
conductivity depends on liquid-phase saturation, it is necessary to capture the influence 
of host-rock dryout and rewetting. 
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4. Host-rock dryout and rewettingTemperature buildup and cooldown in the host rock, 
as well as the magnitude of liquid-phase flux that enters the dryout zone (primarily 
resulting from gravity-driven percolation flux), influence the spatial and temporal extent 
of dryout. 
The multiscale thermohydrologic model consists of four different submodel types, described in 
detail in Section 6.2.4, which collectively represent all four of these processes. Two of the 
submodel types (SMT and DDT) are three-dimensional in order to represent mountain-scale heat 
flow, which occurs by conduction, and to represent heat flow within the drifts, which occurs by 
conduction, radiation, and convection, and which is approximated with an effective thermal 
conductivity. 
Two-dimensional drift-scale thermal-hydrologic submodels are used to predict drift-scale heat 
flow, dryout, and rewetting in the host rock; these models also predicts heat flow within the drift 
and how that heat flow influences relative humidity within the drift. One-dimensional drift-scale 
thermal-conduction models are used to relate the temperature predicted by the two-dimensional 
drift-scale thermal-hydrologic submodels with the temperatures predicted by the three-
dimensional mountain-scale thermal-conduction submodel. 
It is important to note that drift-scale thermal-hydrologic models are bounded on all four sides by 
insulated impermeable boundaries that prevent any heat or mass (gas- and liquid-phase) flow 
across these boundaries. As in the mountain-scale submodel, drift-scale submodels have an 
upper and lower boundary with specified boundary conditions. Thus, heat and mass flow can 
leave the drift-scale submodels at the upper and lower boundary. Because of the insulated lateral 
and longitudinal boundaries, drift-scale models cannot (directly) represent the influence of 
three-dimensional mountain-scale heat flow. There are several possible options for incorporating 
the influence of three-dimensional mountain-scale heat flow into the results of drift-scale 
submodels, including: (1) specifying time-dependent temperature boundary conditions, which 
are obtained from the three-dimensional mountain-scale submodel, at the sides of the drift-scale 
submodels, and (2) specifying time-dependent heat flux, which is determined from the 
three-dimensional mountain-scale submodel, out of the sides of the drift-scale submodels. 
Because it is computationally feasible, the multiscale thermal-hydrologic model uses the second 
approach, as is conceptually explained below, and which is described in detail in Section 6.2.4. 
The multiscale thermal-hydrologic model implements the time-dependent heat flux at the lateral 
boundaries of the drift-scale thermal-hydrologic submodels in an empirical fashion. For a 
repository of theoretically infinite lateral and longitudinal extent, there would be no 
mountain-scale heat flow in the lateral and longitudinal directions. Consequently, drift-scale 
submodels could take advantage of symmetry by utilizing insulated lateral and longitudinal 
boundaries and closely predict the temperature evolution. These models could utilize an 
insulated boundary along the center axis of the drift and an insulated boundary at the mid-pillar 
location, which is 40.5 m from the drift centerline. Because the repository system is of finite 
lateral and longitudinal extent, three-dimensional mountain-scale heat flow causes heat to cross 
the lateral and longitudinal boundaries in the drift-scale submodels. The multiscale 
thermohydrologic model approximates this heat loss by allowing heat to leave the lateral 
boundary in the drift-scale submodels, which is 40.5 m away from the centerline of the drift, in a 
manner that is consistent with three-dimensional mountain-scale heat flow. This is accomplished 
by comparing temperatures predicted by the three-dimensional mountain-scale submodel with 
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those predicted by equivalent one-dimensional drift-scale submodels to adjust the lateral 
dimension of the drift-scale submodels so that the temperature predicted by the drift-scale 
submodel matches that of the mountain-scale submodel at each timestep. This adjustment 
process results in an effective drift spacing, which gradually increases with time, just as the 
lateral and longitudinal heat loss grows with time. Note that the description in Section 6.2.4 
utilizes an effective areal mass loading, which has a one-to-one equivalence to the effective drift 
spacing. Thus, an effective drift spacing of 81 m corresponds to an effective areal mass loading 
of 55 MTU/acre, while an effective drift spacing of 162 m corresponds to an effective areal mass 
loading of about 27 MTU/acre. The gradually increasing drift spacing allows the appropriate 
quantity of heat to leave the physical lateral boundary (with time). This time-dependent drift 
spacing is then applied to the two-dimensional drift-scale thermal-hydrologic submodels, so that 
the influence of three-dimensional mountain-scale heat flow is appropriately represented in those 
submodels. 
After the effective drift spacing is incorporated into the two-dimensional drift-scale 
thermohydrologic submodels, the intermediate results represent a repository that is uniformly 
heated with a repository-wide average thermal load per unit length. To incorporate the influence 
of nonuniform heating conditions along drifts (resulting from waste package-to-waste package 
variability in heat output), three-dimensional drift-scale submodels are used to determine the 
local temperature deviations relative to those arising from line-averaged heating conditions. 
These temperature deviations are added to the line-averaged results to determine temperature 
conditions that incorporate both the influence of three-dimensional mountain-scale heat flow and 
three-dimensional drift-scale heat flow. Thus, the effective drift spacing (and the corresponding 
equivalent effective areal mass loading) is adjusted to account for local temperature deviations, 
as well as for three-dimensional mountain-scale heat flow. The adjusted effective areal mass 
loading is applied to the two-dimensional drift-scale thermal-hydrologic submodels to determine 
all hydrologic parameters of interest throughout the repository. 
The process of adding the results from three-dimensional thermal submodels to those from 
two-dimensional thermohydrologic submodels relies on the assumption (Section 5.2.1) that 
three-dimensional convective heat and mass transfer in the host rock do not influence 
longitudinal temperature variability along the drift axis. Moreover, the multiscale model 
approach assumes (Sections 5.2.2 and 5.6) that mountain-scale movement of water and water 
vapor along the drift axes or between drifts is insignificant. Thus, fluid flow and convection are 
mostly confined to a two-dimensional vertical cross section orthogonal to the drift axis, with 
insignificant fluid flow across the vertical midplane in the rock pillar between the drifts. These 
assumptions are justified by the model validation study documented in Section 7.5, where it was 
found that the influence of longitudinal vapor transport along the drift has an insignificant 
influence on in-drift thermal-hydrologic conditions compared to the influence of parametric 
uncertainty. The thermal-hydrologic multiscale model also neglects any changes in rock 
properties due to three-way or four-way coupled thermohydrologic-chemical-mechanical 
processes (Manteufel et al. 1993 [DIRS 100776]) and neglects the influence of dissolved solutes 
on the thermohydrologic properties of water. 
The thermal-hydrologic multiscale modeling approach considers the influence of the following 
parameters as a function of geographic location in the repository: local stratigraphy, overburden 
thickness (i.e., distance between the repository and ground surface, which varies by 
approximately 150 m across the repository), thermal boundary conditions, and percolation flux. 
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It also considers the influence of the proximity to the edge of the repository, which is important 
because a waste package close to the repository edge will cool more quickly than one at the 
repository center. As discussed in Section 5.2.1, it is assumed that the differences in temperature 
that arise as a result of proximity to the repository edges are governed by thermal conduction in 
the rock. This assumption is equivalent to saying that convective heat transfer mechanisms have 
an insignificant influence on lateral mountain-scale heat flow at Yucca Mountain. These 
mechanisms (notably, buoyant gas-phase convection and the heat pipe effect) are included in the 
two-dimensional thermal-hydrologic (drift-scale) submodels of the MSTHM. The assumption of 
conduction dominance at the mountain scale bounds temperature differences that arise from 
differences in proximity to the repository edges, which captures the full range of boiling-period 
duration across the repository. 
The MSTHM represents all possible waste packages emplaced in the repository by four major 
types: CSNF from pressurized-water reactors (PWRs), CSNF from boiling-water reactors 
(BWRs), high-level radioactive waste (HLW), and DOE-owned spent nuclear fuel. The relevant 
point here is that the heat-generation-rate-versus-time relationships for these four waste package 
types are different. The model considers a waste package sequence (Figure 6.2-2) that results in 
eight distinct local heating conditions for waste packages. For example, the model distinguishes 
between a BWR placed between a PWR and a HLW and a BWR placed between two PWRs. As 
discussed in Section 5.2.2, it is assumed that the differences in temperature between relatively 
hotter and cooler waste package locations are governed by thermal conduction in the host rock 
and emplacement drift and thermal radiation in the open cavities in the drift. This assumption is 
equivalent to saying that convective heat transfer mechanisms (notably, buoyant gas-phase 
convection) do not significantly contribute to the attenuation of temperature variations along the 
axis of the drift. However, the influence of buoyant gas-phase convection is represented in the 
vertical plane perpendicular to the drift axis. This assumption bounds temperature variability 
along the drifts. 
To implement this multiscale approach, a modeling system has been developed that is called the 
MSTHM, which is described in detail in Section 6.2.4. The following discussion begins with the 
unsaturated zone hydrology model on which the natural system aspects of the MSTHM are 
based, followed by a detailed discussion of the governing equations that are used in all the 
MSTHM simulations. 
6.2.2 Incorporating the Unsaturated-Zone Hydrology Model in the MSTHM 
The MSTHM uses the representation of the unsaturated zone developed in UZ Flow Models and 
Submodels (BSC 2004 [DIRS 169861]). From Development of Numerical Grids for UZ Flow 
and Transport Modeling (BSC 2004 [DIRS 169855]), a three-dimensional definition of 
hydrostratigraphic units (called UZ-model layers) is incorporated in the MSTHM, including 
position of the water table and surface topography; thermohydrologic properties for these units; 
and model boundary conditions. The model includes 36 UZ-model layers, each of which is 
considered to be homogeneous with respect to thermal and hydrologic properties. These 
hydrologic properties are determined through an inverse modeling approach constrained by site 
hydrologic data; the assumption is made that important heterogeneity is captured by the detailed 
stratification (Bandurraga and Bodvarsson 1999 [DIRS 103949]). The thermal properties are 
determined based on laboratory and field measurements (BSC 2004 [DIRS 169854]; BSC 2004 
[DIRS 170033]). 
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Multiscale Thermohydrologic Model 
The MSTHM also incorporates the conceptualization for flow through unsaturated fractured 
porous rock at Yucca Mountain from the Lawrence Berkeley National Laboratory (LBNL) 
unsaturated-zone hydrology model. The current conceptual model is based on a 
dual-permeability representation of overlapping fracture and matrix continua, modified from the 
traditional approach such that only a portion of connected fractures actively conduct liquid water 
(Liu et al. 1998 [DIRS 105729]), a portion which depends on liquid-phase saturation in the 
fractures. 
The next step in building the MSTHM involves the addition of the repository emplacement drifts 
and the engineered components inside those drifts to the unsaturated zone hydrology model 
discussed above. The geometric configuration of the engineered components inside the drifts 
used in the MSTHM calculations in support of the TSPA-LA base case is shown in Figures 6.2-1 
and 6.2-2. 
Source: BSC 2003 [DIRS 164101], Figure 2, for invert depth; BSC 2004 [DIRS 168489], Figure 1, for drift diameter. 
NOTE: Average waste package diameter is obtained from assumption in Section 5.4.1. Drip-shield width is from 
BSC 2003 [DIRS 171024], Sheet 2. Location of waste package centerline above invert is from BSC 2004 
[DIRS 167040]. 
Figure 6.2-1. Geometric Configuration of the Engineered Components Shown for an Average 
Cross-Section Inside the Emplacement Drifts as Represented in MSTHM 
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Multiscale Thermohydrologic Model 
NOTE: Average waste package diameter is obtained from assumption in Section 5.4.1. Waste package lengths are 
obtained from BSC 2003 [DIRS 165406], Table 1. The names of the respective waste packages (21-PWR, 
44-BWR, etc.) used in the DDT submodel are shown above for each waste package. 
Figure 6.2-2. Diagram Showing Drift Spacing, Waste Package Lengths, and Waste Package Spacing in 
Plan View Considered in MSTHM Calculations for the TSPA-LA Base Case 
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6.2.3 Governing Equations for Unsaturated-Zone Thermohydrology 
This section describes the theoretical basis for the NUFT software, which solves the governing 
equations. Section 3 lists versions of NUFT that are qualified software and are used in the 
MSTHM. The theoretical basis is repeated here for background. 
6.2.3.1 Mass-Balance Equation for Thermal-Hydrologic Models 
All thermal-hydrologic models in this report solve the mass-balance equation for air, water, and 
energy components for liquid- and gas-fluid phases and a nondeformable solid. The 
mass-balance equation for the air and water components is: 
 

. .f. S.. = -. . f. S.(.. V.+ J.) (Eq. 1) 
. t ... . 
. 
where t is time, the superscript  denotes a component (e.g., air and water), the subscript . 
denotes fluid phases (e.g., liquid and gas), f is porosity, .. is density of phase ., S. is saturation 

of a . phase, .. denotes mass fraction of  component in phase ., V. is velocity vector for . 

phase advection, and J. is combined diffusive and dispersive flux tensor, which can be further 
given by Ficks law (Cho 1998 [DIRS 160802], p. 1.3, Equation 1-7): 
 

J
.=- D . ... (Eq. 2) 
D
 
. is combined diffusion and dispersion coefficient for  component in . phase. Darcys law 
gives the advective flux vector (Nitao 2000 [DIRS 159883]): 
f V.=- 
k.( S.)(. p +. g . z ) (Eq. 3) 
S
. 
..
 
. 
where k. is the permeability function, . is phase viscosity, p. is phase pressure, g is gravitational 
acceleration, and z denotes distance in the vertical direction. The capillary pressure relationship 
is given by: 
p
a= pg - pc (Eq. 4) 
and pc is the retention pressure function. In addition to the mass balance equation, there are the 
constraints: 
.S.= 1
.
.. = 1 and 
. 
(Eq. 5) 
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Local thermodynamic equilibrium is assumed between all phases. Partitioning of components 
between phases is expressed in terms of partitioning coefficients: 
 

n.=K ..n. (Eq. 6) 
, 

where n. is the mole fraction and K  
.,. is the partitioning coefficient between phase .and 
phase .. For predicting the partitioning of water between the aqueous phases, the model includes 
the vapor pressure lowering effect based on the Kelvin law: 
P . MP . (Eq. 7) 
c .
RH = 
Pv 
(T ) 
=exp.
.
sat ..
RT .
. 
where RH is relative humidity, Pv is partial pressure of water vapor, Psat (T) is the saturated vapor 
pressure from the steam tables, based on the local temperature T, M is the molecular weight of 
water, Pc is capillary pressure, . is the density of water R is the Gas Constant, and T is 
temperature. 
6.2.3.2 Energy Balance Equation for Thermal-Hydrologic Models 
For all thermal-hydrologic models and submodels in this report, the energy balance equation is: 
 
.
...
.f.uS +(1 -f. C (T -Tref ).=....
.f . S (. V +Ja).+. K .T (Eq. 8) 
.. . ) sp 
. 
h.. . 
.. H.t .. ... 
where T denotes temperature, Tref is reference temperature, u.is specific internal energy, .s 
is 
h

solid density, Cp is specific heat of solid, . is partial specific enthalpy, and KH is thermal 
conductivity. Note that thermal conductivity is a function of liquid-phase saturation S, varying 
linearly from a dry value of KH (S = 0.0) to a wet value of KH (S = 1.0). Where thermal 
radiation is included to couple grid blocks within the numerical model, a classical radiation term 
can be added to the right hand side of Equation 8, to represent the conceptual basis for radiative 
heat transfer. 
It is noted that it is possible to use either a specific internal energy accumulation term or a 
specific enthalpy accumulation term for the fluid phases of Equation 8. Transport Phenomena 
(Bird et al. 1960 [DIRS 103524]) discusses the validity of either approach. The justification for 
the use of specific internal energy in the accumulation term of the fluid phases in the NUFT code 
is discussed in detail in Section 6.2.3.6. 
The balance equations (1) and (8) are discretized in space using the integrated finite difference 
method and discretized in time using the fully implicit backward Euler method. The resulting 
nonlinear system of equations is solved at each time step using the Newton-Raphson method. 
6.2.3.3 Radiative Heat Transfer 
Where relevant, models, such as the LDTH and DDT submodels (Sections 6.2.6 and 6.2.8), 
include radiative heat transfer in the energy balance model for the open cavities within the 
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repository drifts in which waste packages are emplaced. In this case, the surfaces of the drift 
wall and waste package are subdivided into surface elements, each of which is mapped to a 
computational volume element. Radiative heat flux is calculated for connections between each 
pair of surface elements using temperatures from the corresponding volume element. The net 
radiative heat transferred between two model nodes is calculated from the Stefan-Boltzmann law 
(Cho 1998 [DIRS 160802]): 
4
Qc T 
= (4 -T ) (Eq. 9) 
12 
where T1 is the absolute temperature of the radiator, T2 is the absolute temperature of the 
receiver, and c is a coefficient defined by: 
c =AFes (Eq. 10) 
where A is the area of the radiating surface element, F is the radiative view factor (Holman 1990 
[DIRS 106052]), e is emissivity, and s is the Stefan-Boltzmann constant. 
6.2.3.4 Energy Balance Equations for Thermal-Conduction-Only Models 
For all thermal-conduction models in this report, the energy balance is written: 
(1 -f.C .T =. KH .T (Eq. 11) 
) sp .t 
where fis porosity, . is solid density, Cp is specific heat of solid, and KH is thermal 
s
conductivity. For thermal-conduction-only models, thermal conductivity is not a function of 
liquid-phase saturation. 
6.2.3.5 Dual-Permeability and Active-Fracture Models 
All thermal-hydrologic models in this report utilize a dual-permeability approach in which the 
fracture and matrix systems are treated as two separate continua with a complete set of balance 
equations and computational grid for each continuum. Each continuum has coupling terms for 
mass and energy fluxes between the two continua. These terms have the general form: 
q
exchange =a..u / L , (Eq. 12) 
where qexchange is flux of mass or energy per unit bulk volume, .u is the difference in pressure or 
temperature between the continua, and . is a transfer coefficient. The coefficient .for 
advective flux is of the form Kkr/, where K is saturated permeability, and kr is relative 
permeability. For diffusive mass flux of a phase, . is equal to the apparent diffusion coefficient 
Dapp = fStD, where tis tortuosity factor, and D is the free diffusion coefficient. For energy flux, 
. is the bulk thermal conductivity KH. In the conventional dual-permeability approach, a is the 
surface area of the fracture walls per unit bulk volume, and L is the average distance between 
centers of the matrix elements, which is proportional to the fracture spacing. Also used is an 
active-fracture model modification to the traditional dual-permeability approach in which a and 
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Multiscale Thermohydrologic Model 
L are modified to account for inactive fractures (or portions of fractures) as suggested by Liu et 
al. (1998 [DIRS 105729]). 
Specifically, a is multiplied by Se, and L is multiplied by Se 
-., where: 
r
=
Se SSf -
- 
SS , (Eq. 13)
max r 
and Sr and Smax are residual and maximum liquid-phase fracture saturations, respectively, while 
Sf is the fracture saturation. 
The relationships between permeability, saturation, and capillary pressure described in 
Equations 14 and 15 are described by the formulations of van Genuchten (1980 [DIRS 100610]) 
and Mualem (1976 [DIRS 100599]), modified to account for the active fracture model by the 
parameter . which has a value between 0 and 1 (0 if all fractures are active). 
The relative permeability for the liquid phase is given by: 
k 
2 
rl = S (1+. )/2 . (1-. )/ m ) m . 
e .. 
1.0 -( 1.0 - Se .. 
(Eq. 14) 
It is assumed that krl + krg = 1; the subscripts l and g refer to the liquid and gas phases, 
respectively. The capillary pressure is given by: 
1 
.- 1 . 
n
1 . 
c
p = 
a.
. 
Sem - 1 
.
. (Eq. 15) 
where a is a curve-fitting parameter (units of inverse pressure), n is a dimensionless curve-fitting 
parameter, and m = 1-1/n. 
The parameters used in this model are functions of pressure p, temperature T, mass fraction . , 
..
and/or saturation S as follows: .a ( p,T, . ), Da ( p,T ), a ( p,T, . ), Ka ( p,T,S), ua ( p,T, . ), 
.
ha (p,T), ka(S), ta(S), and pc (S,T ). 
6.2.3.6 Formulation of Energy Balance Equation for Thermal-Hydrologic Models 
It is possible to formulate the energy balance equation (Equation 8) using either specific internal 
energy (u) or specific enthalpy (h) in the fluid-phase accumulation terms inside the time 
derivative. Numerical models for subsurface flow and transport have formulated the equation of 
energy for multicomponent systems both using enthalpy (e.g., Manteufel et al. 1993 [DIRS 
100776]; Pollock 1986 [DIRS 164747]) and using specific internal energy (e.g., Lichtner and 
Walton 1994 [DIRS 152609]; Nitao 1998 [DIRS 100474]). Bird et al. (1960 [DIRS 103524], 
Table 18.3-1, p. 562) demonstrate that both formulations are valid, as follows: 
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Multiscale Thermohydrologic Model 
D ( 
n 
.h  . - = q)+ Dp - (t : . v) +. (j  g ) (Eq. 16) 
ii
DtDt i = 1 
n 
.Du  . - = q)- (p : . v) +. (j  g ) (Eq. 17) 
(
ii
Dt i = 1 
u
One may note the fact that specific enthalpy of evaporation (hevap) is greater than the specific 
internal energy of evaporation (uevap) because the specific enthalpy includes a compressible work 
term. For example, at standard atmospheric pressure (101.3 kPa), hevap = 2,257 kJ/kg while 
evap = 2088 kJ/kg, a difference of approximately 8 percent (Keenan et al. 1969 [DIRS 134666]). 
Such a difference is crucial when considering a simplified batch system (i.e., zero-dimensional 
reactor). In such simplified cases, one must consider different approaches to the system (i.e., 
approaching the problem as a closed system versus approaching the problem as an open system). 
The partial differential equation formulation as represented by Bird et al. (1960 [DIRS 103524], 
p. 566, Equation 18.4-2) in Equations 16 and 17 incorporates multidimensional transient 
processes, however. Both the enthalpy formulation (Equation 16) and the internal energy 
formulation (Equation 17) result in equivalent solutions. 
The energy-balance equation in NUFT is based on the derivation of Equation 17, which is the 
internal energy formulation of the energy equation for n species. Expanding the total derivative 
on the left-hand side of Equation 17 and incorporating the continuity equation, Equation 17 can 
be rewritten as: 
n
. 
(.u)  . + (. uv)  . - = q)- (p : . v) +. (j  g ) (Eq. 18) 
(
ii
. ti = 1 
The thermal energy flux q is composed of three terms (Bird et al. 1960 [DIRS 103524], 
Equation 18.4-2, p. 566): 
n 
q(x)
k
q . - = T -. h .Di.. + (Eq. 19) 
ii 
i= 1 
representing, respectively, thermal conduction, species diffusion enthalpy transport, and the 
Dufour energy flux. Note that according to Bird et al. (1960 [DIRS 103524]), the Dufour energy 
flux is of minor importance and is therefore typically neglected. Incorporating Equation 19 (less 
the Dufour energy flux) into Equation 18 and noting that gravitational work (the last term in 
Equation 18) is zero (Nitao 2000 [DIRS 159883]), results in the simplified equation: 
n
..
. 
(.u)  . + (. uv) =.  .. k. T +. h . Di ....
...
- (p : . v) (Eq. 20) 
i
.
. t .. i = 1 
i .. 
The stress tensor p is related to the viscous shear tensor and pressure as follows: 
p=t+ pI (Eq. 21) 
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Incorporating Equation 21 into the last term of Equation 20 and noting that 
p . v  . = (pv) - v .  p , Equation 20 can be rewritten as: 
n
..
. 
(. u)  . + (. uv) =.  .. k. T +. h . Di ....
...
(t : . v)  . - (pv) + v .  p
i
.
. t .. i = 1 
i .. 
(Eq. 22) 
As discussed by Nitao (2000 [DIRS 159883]), both the viscous dissipation term (t: . v) and the 
pressure gradient term (v.  p) are typically neglected in Equation 22 because these terms are 
small compared to other terms. Estimates of the approximate potential error incurred by 
neglecting these two terms are discussed below. The third term on the right-hand side of 
Equation 22 can be incorporated into the second term on the left-hand side resulting in a 
convective enthalpy term. This results in the energy equation as it is employed in the NUFT 
code: 
n
..
. 
(. u)  . + (. hv) =.  .. k. T +. h . Di ....
. (Eq. 23) 
.
. t .. i = 1 
ii ..
.
. 
For a more rigorous mathematical development of Equation 23 from Equation 17, see 
Documentation of the Thermal Energy Balance Equation Used in the USNT Module of the NUFT 
Flow and Transport Code (Nitao 2000 [DIRS 159883]). Note that the above equations apply 
only at the pore level and not at the porous medium, or macroscopic, level. Nitao (2000 
[DIRS 159883]) also discusses the method used to derive the porous medium energy balance 
equation by volume averaging the pore level equations. 
It is possible to estimate the error incurred by neglecting the viscous dissipation term (t: . v) in 
Equation 22 by considering the maximum error that could occur for a thermal-hydrologic model 
calculation using the NUFT code. Nitao (2000 [DIRS 159883]) estimates that the maximum 
error caused by neglecting this term would occur during infiltration through the rock fractures. 
The maximum possible error in temperature at the repository for a high infiltration of 100 mm/yr 
would be . T ~ 0.3 C. 
The largest potential source of error lies in neglecting the pressure gradient term in Equation 22. 
Note that this assumption does not mean that a constant pressure is assumedonly that this 
particular term in the energy equation is neglected. In fact, pressure is a variable in all of the 
remaining terms in Equation 22 where it appears. It is possible to estimate the maximum 
potential error incurred by neglecting the heat gradient term (v. p) by comparing it to the 
convective enthalpy term (  . (. hv) ). The greatest pressure would occur in the host rock 
immediately adjacent to the drift wall during a boiling event. As an example, consider a 
maximum drift-wall temperature of 140 C as estimated for the higher-temperature operating 
mode conditions analyzed in FY 01 Supplemental Science and Performance Analyses, Volume 1: 
Scientific Bases and Analyses (BSC 2001 [DIRS 155950], Figure 5.4.1-2). Such a temperature 
would result in a Psat of 361 kPa. The results of the supplemental analyses indicate that such a 
drift-wall temperature incurs a relative humidity of 30 percent; thus, the pressure can be 
estimated as approximately 120 kPa. The extreme downstream temperature and pressure at the 
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Multiscale Thermohydrologic Model 
repository level would be about 96 C and 84.5 kPa. If the ratio of (v . p)/ . (. hv)is 
approximated as .p/.(.sathsat) then the maximum difference is (120 kPa84.5 
kPa)/(1.12 kg/m3  2,706 kJ/kg - 0.353 kg/m3  2,652 kJ/kg) or about 2 percent. Note that this 
is a conservative error estimate for this particular problem; the estimate neglects thermal 
conduction as an energy transport mechanism and thus exaggerates the potential error of this 
scenario where heat flow is dominated by thermal conduction. Hence, is concluded that 
neglecting the pressure gradient in Equation 22 would result in a maximum error of less than 
2 percent for a short time over only the small region of host rock adjacent to drift wall, where 
boiling of pore water occurs. Neglecting the influence of viscous dissipation and the pressure 
gradient in the energy equation is therefore acceptable. 
6.2.4 MSTHM Calculation Sequence 
The MSTHM consists of four submodel types (Figure 1-1, Tables 1-2 and 1-3), all of which are 
run using the NUFT v3.0s code (Nitao 1998 [DIRS 100474], Section 3.1.1). For this report, the 
LDTH and SDT submodels (Sections 6.2.6 and 6.2.7) are run at 108 geographic locations 
distributed uniformly over the repository area (Figure 6.2-3); these submodels use the 
stratigraphy, overburden thickness, thermal-hydrologic boundary conditions, and percolation 
fluxes appropriate for each location. At each of those 108 geographic locations, the LDTH and 
SDT submodel calculations are conducted at different values of thermal loading, which can be 
quantified by the Areal Mass Loading (AML). Note that AML is expressed in terms of metric 
tons of uranium per acre. For the current repository design, the initial Lineal Power Density 
(LPD) is 1.45 kW/m (BSC 2004 [DIRS 168489], Table 1), which for a drift spacing of 81 m 
(BSC 2004 [DIRS 168489], Table 1) corresponds to an areal power density of 17.9 W/m2. The 
repository has 57,480.2 m of emplacement drift (Table 6.2-1), which corresponds to a heated 
repository footprint of 4,655,896 m2 (57,480.2 m of drift multiplied by an 81-m drift spacing, 
which is 1150 acres). From Table 6.2-1 it can be seen that the SMT submodel represents the 
repository as having 57,480 m of emplacement drift. For a 63,000 MTU inventory of 
commercial spent nuclear fuel (CSNF) waste packages, this corresponds to an AML of 54.76 
MTU/acre (63,000 MTU divided by 1150 acres). Therefore, 1 MTU/acre is equivalent to 0.327 
W/m2 at the time of emplacement for the TSPA-LA design. The modeled AML is obtained by 
virtue of the selected drift spacing in the submodel. 
Section 7.5 describes a MSTHM validation test case, also reported by Buscheck et al. (2003 
[DIRS 164638]), in which the MSTHM and a corresponding monolithic thermohydrologic model 
are used to predict the thermohydrologic behavior of a three-drift repository test case, which is a 
scaled-down version of the repository. The following description of the MSTHM calculation 
sequence also pertains specifically to that test case, which utilizes six modeled AMLs: 66, 55, 
37, 27, 14, and 7 MTU/acre. Because of the very small heated footprint of the three-drift 
repository test case, the influence of the edge-cooling effect occurs faster and with greater 
magnitude than is applicable to repository heating conditions, which requires that the 
LDTH-SDT submodel pairs be run at six different AMLs, rather than at just four (as is typically 
done for a full-scale repository example). An AML of 55 MTU/acre corresponds to 81-m drift 
spacing, while 27 MTU/acre corresponds to 162-m drift spacing. The emplaced AML for the 
repository is 55 MTU/acre for a total repository-wide heat load of 70,000 MTU (Canori and 
Leitner 2003 [DIRS 166275], p. 3-95). The modeled AMLs that are less than the emplaced 
AML account for the evolving influence of the edge-cooling effect (i.e., waste package locations 
close to the repository edges cool faster than those at the center). The modeled AML that is 
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Multiscale Thermohydrologic Model 
higher than the emplaced AML accounts for hotter-than-average waste package thermal-loading 
conditions. The LDTH submodel domain is a two-dimensional drift-scale cross-section 
extending down from the ground surface to the water table. The LDTH submodels are the only 
submodels to include coupled thermal-hydrologic processes; these submodels assume a 
heat-generation history that is effectively that of the entire waste package inventory 
line-averaged over the total length of emplacement drifts in the repository. 
Source: See Table XIII-1. 
NOTE: Nevada State Northing and Easting coordinates are given in kilometers. The subhorizontal lines depict the 
rows of gridblocks in the SMT submodel that represent each of the emplacement drifts. The rectangles 
correspond to the locations of LDTHSDT submodel pairs. A total of 108 LDTHSDT submodel locations 
are used in the TSPA-LA base case. The outline of the repository perimeter corresponds to the end-point 
coordinates of the heated portions of the emplacement drifts as given in the IED presented in Repository 
Design, Repository/PA IED Subsurface Facilities (BSC 2003 [DIRS 161727]). The MSTHM representation 
of the heated repository footprint closely matches the end-point coordinates of the repository layout. This 
layout has been slightly revised as shown in Figure 4-1, which is based on the end-point coordinates given 
in the IED presented in D&E / PA/C IED Subsurface Facilities (BSC 2004 [DIRS 164519]). Note that the 
Panel numbers have changed in the revised layout, as shown in Figure 4-1. 
Figure 6.2-3. Repository Layout Considered in MSTHM Calculations for the TSPA-LA Base Case 
ANL-EBS-MD-000049 REV 02 6-24 October 2004 

Multiscale Thermohydrologic Model 
The three-dimensional SMT submodel, which simulates conductive heat flow from a heat source 
smeared over the repository area, represents the heated footprint of the repository and allows for 
consideration of edge-cooling effects and the influence of the varying overburden thickness 
above the repository. For this example, originally by Buscheck et al. (2003 [DIRS 164638]), the 
linear power density is 1.35 kW/m. Note that this linear power density is different from that 
being analyzed for the TSPA-LA (Section 6.3). The SMT submodel assumes a heat-generation 
history that is areally averaged for the entire waste package inventory over the entire heated 
footprint of the repository. The one-dimensional SDT submodels are run at the same 108 
geographic locations as the two-dimensional LDTH submodels such that every LDTH submodel 
is paired to a corresponding SDT submodel. The SDT submodels utilize the same 
heat-generation history as the LDTH submodels except that heat is smeared over the repository 
plane in the SDT submodels. 
The fundamental concept in the MSTHM is that the results from the two-dimensional LDTH 
submodels can be modified to account for the influence of three-dimensional mountain-scale 
heat flow as well as for local deviations arising from waste package-to-waste package variability 
in heat output. Output from the SMT submodel, together with the LDTHSDT submodel pairs, 
is integrated to create the LMTH model (Figure 1-1). The DDT submodel is then used to further 
modify the LMTH model to account for waste package-specific deviations from average waste 
package behavior. For this report, the DDT submodels represent eight different waste packages, 
which fall in two major categories: commercial spent nuclear fuel (CSNF) waste packages, 
which include pressurized water reactor (PWR) and boiling water reactor (BWR) waste 
packages; and defense high-level waste (DHLW) waste packages. Four different waste package 
types are used in the model validation study: PWR1, PWR2, DHLW and BWR (Table 7.3-2). 
DDT submodel temperature variations are superimposed on LMTH model temperatures to 
generate the temperatures of the final discrete-heat-source mountain-scale thermal-hydrologic 
(DMTH) model (Figure 1-1, Tables 1-2 and 1-3). 
For the MSTHM analysis of the repository, after all of the submodels have been run using the 
NUFT code, LDTH and SDT submodel results are spatially interpolated from the geographic 
locations (a total of 108 for the TSPA-LA MSTHM) to all of the repository subdomains in the 
SMT submodel (2,874 for the TSPA-LA MSTHM). This approximates running the LDTHSDT 
submodel pairs at all repository subdomains in the SMT submodel. 
The MSTHM calculation sequence to obtain temperature, relative humidity, and liquid-phase 
saturation is shown in Figures 6.2-4 and 6.2-5 and is divided into the six stages of Figure 1-1. 
While this analysis pertains to the three-drift repository model validation test case (Section 7.5), 
it also illustrates the MSTHM calculation sequence for each of the repository subdomains. The 
six calculation stages conceptually illustrated in Figure 1-1 are discussed in detail below. 
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Multiscale Thermohydrologic Model 
NOTE: (a) Host-rock temperature TSDT vs. time calculated for the six listed AMLs; also plotted is TSMT vs. time 
calculated at the repository center. Because the SDT and SMT submodels use smeared heat sources, the 
SDT and SMT host-rock temperatures are averaged temperatures for the repository horizon (from pillar 
mid-point to pillar mid-point) at a given drift location. (b) Host-rock effective AML (AMLhstrk,eff) vs. time 
calculated at the repository center. (c) Drift-wall temperature vs. time calculated for the six listed AMLs; also 
plotted is Tdw,LMTH vs. time determined at the repository center. (d) Temperature difference .Tdw,j,DMTH 
between the local and the axially averaged Tdw,LMTH calculated using the six DDT submodels and 
interpolated on the basis of AMLhstrk,eff vs. time (Figure 6.2-4b) for the HLW and PWR2 waste packages; also 
plotted are the corresponding temperature deviations .Tds,j,DMTH between the local drip-shield temperature 
and the axially averaged Tds,LMTH. 
Figure 6.2-4. MSTHM Calculation Sequence for a Three-Drift 55-MTU/Acre-Repository Example 
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NOTE: (a) Tdw,j,DMTH vs. time for the HLW and PWR2 waste packages at the repository center; also plotted is 
Tdw,LMTH vs. time at the repository center (Figure 6.2-4c). (b) Tdw,LDTH vs. time calculated for the six listed 
AMLs; also plotted is Tdw,j,DMTH vs. time for the HLW and PWR2 waste packages at the repository center. (c) 
AMLi,j-specific at the drift wall for the HLW and PWR2 waste packages at the repository center. (d) Drift-wall 
relative humidity RHdw,LDTH vs. time calculated for the six listed AMLs; also plotted is RHdw,j,DMTH vs. time for 
the HLW and PWR2 waste packages at the repository center, which is determined on the basis of 
AMLi,j-specific vs. time for the respective waste packages. (e) Tds,j,DMTH vs. time for the HLW and PWR2 waste 
packages at the repository center; also plotted is Tds,LMTH vs. time at the repository center. (f) RHds,j,DMTH vs. 
time for the HLW and PWR2 waste packages. 
Figure 6.2-5. MSTHM-Calculation Sequence (Continued) 
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STAGE 1The first calculation stage generates the host-rock effective AML, referred to as 
AMLhstrk,eff. The AMLhstrk,eff is generated at each repository subdomain in the following manner: 
1. First, the repository subdomains host-rock temperature history simulated by the 
three-dimensional SMT submodel is compared with temperature histories simulated by 
the one-dimensional SDT submodels for a range of heat loading conditions (e.g., for 
55 MTU/acre, for 46 MTU/acre, etc.). Note that because the SDT and SMT 
submodels use smeared heat sources, the SDT and SMT host-rock temperatures are 
averaged temperatures for the repository horizon (from pillar centerline to pillar 
centerline) at a given location. 
2. Second, the value of AMLhstrk,eff at any given time is the AML that a one-dimensional 
SDT submodel would have to use in order to match the three-dimensional SMT 
modeled temperature at that location. By using the AMLhstrk,eff, the influence of 
three-dimensional mountain-scale heat flow is imposed on the two-dimensional LDTH 
submodels discussed in Stage 2. As an example, Figure 6.2-4a-c illustrates how the 
concept of the AMLhstrk,eff is used to account for three-dimensional mountain-scale 
heat flow. The host-rock temperature TSMT calculated by the three-dimensional SMT 
submodel is compared with temperatures TSDT calculated by the family of 
AML-dependent SDT submodels (Figure 6.2-4a). For each timestep, AMLhstrk,eff 
(Figure 6.2-4b) is obtained by interpolating for TSMT among the family of 
AML-dependent TSDT curves. For example, Point A, which is at 20 years, finds the 
TSMT to be virtually the same as TSDT for 55 MTU/acre, thus yielding an AMLhstrk,eff of 
55 MTU/acre at 20 years. Point B, which is at 200 years, finds TSMT lying between 
TSDT for 55 and 37 MTU/acre; linear interpolation between TSMT and the two TSDT 
curves straddling Point B results in an AMLhstrk,eff of 43 MTU/acre at 200 years. 
Initially, TSMT at the center of this three-drift repository test case corresponds exactly to TSDT 
calculated by the 55-MTU/acre SDT submodel because there has been no thermal 
communication between the center and edge of the repository. Thus, AMLhstrk,eff is the emplaced 
AML of 55 MTU/acre for early time (Figure 6.2-4b). Because of the relatively small size of the 
repository in this example (which corresponds to the MSTHM validation test problem described 
in Section 7.5), it takes only 50 years to establish thermal communication between the center and 
edge of the repository. Thus, the edge-cooling effect begins to influence the repository center at 
about 50 years, causing TSMT to begin a steady decline relative to the family of AML-dependent 
TSDT curves. This relative decline in TSMT (Figure 6.2-4a) results in a corresponding steady 
decline in host-rock effective AML (Figure 6.2-4b). 
STAGE 2This stage generates the three-dimensional LMTH-model (Table 1-2) temperatures at 
each of the repository subdomains; it does not address the influence of waste package-to-waste 
package variability in heat output. The LMTH-model drift-wall temperature Tdw,LMTH is 
determined by linearly interpolating to the parameter AMLhstrk,eff among the family of six 
AML-dependent LDTH submodel drift-wall temperature Tdw,LDTH curves. Returning to the 
example discussed in Stage 1 and examining Figure 6.2-4c, the AMLhstrk,eff is 55 MTU/acre at 
Point A (t = 20 years), and thus Tdw,LMTH is equal to Tdw,LDTH for 55 MTU/acre, which is about 
81C. At Point B (t = 200 years), the AMLhstrk,eff is 43 MTU/acre, and thus an interpolated value 
of Tdw,LMTH of 105C is determined, which is between Tdw,LDTH for 55 MTU/acre (115C) and 
Tdw,LDTH for 37 MTU/acre (100C). The process of using AMLhstrk,eff to generate LMTH-model 
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temperatures is repeated for invert temperatures Tin,LMTH, for drip-shield temperatures Tds, 
LMTH, and for temperatures at various reference locations in the host rock. LMTH-model 
temperatures are determined for each of the repository subdomains. It is important to note that 
the LDTH and DDT submodels include the mechanism of thermal-radiative heat transfer 
between the waste package, drip-shield, invert, and drift-wall surfaces. Because 
thermal-radiative heat transfer is proportional to the temperature difference between two surfaces 
raised to the fourth power (i.e., T1 
4  T2 
4), it is dependent on temperature differences within the 
drifts, as well as on the absolute temperature (history) in the drifts. Consequently, a DDT 
submodel, which is run at only one AML, cannot address the manner in which thermal-radiative 
heat transfer is dependent on absolute temperature (history). To address this issue, DDT 
submodels are run at a variety of AMLs so that thermal-radiative heat transfer incorporates the 
influence of the temperature differences, as well as the influence of the absolute temperature in 
the drift, all as a function of time. Because the DDT submodels are run for at least four different 
AMLs that cover a wide range of temperature histories, interpolations between the respective 
DDT submodels are performed over small enough temperature-history ranges that piecewise 
linear interpolation adequately characterizes the underlying nonlinear process of 
thermal-radiative heat transfer. 
STAGE 3After LMTH-model temperatures have been determined at all reference locations 
(except for on the waste package) and for all repository subdomains, the next stage in the 
MSTHM process is to build the DMTH-model (Table 1-2) by incorporating the influence of 
waste package-to-waste package variability in heat output obtained from the family of 
DDT submodels. For each DDT submodel, the local deviation from an axially averaged 
temperature (i.e., averaged along the axis of the drift) is determined for each of the four waste 
package types (PWR1, PWR2, BWR, and HLW) for a variety of reference locations (e.g., drift 
wall, drip shield, invert, etc.). This local deviation is the difference between the local 
temperature of interest (e.g., the drift-wall temperature) and the corresponding axially averaged 
temperature. For example, local temperature deviations are computed for the drift wall 
(.Tdw,j,DDT) and for the drip shield (.Tds,j,DDT). These temperature deviations are then 
interpolated as a function of the AMLhstrk,eff in the same manner as Ti,LDTH is interpolated to 
determine Ti,LMTH, as discussed in Stage 2. This is done to determine a temperature deviation 
accounting for the evolving influence of the edge-cooling effect at that repository subdomain. 
Computed temperature deviations for the drift wall and drip shield (.Tdw,j,DMTH and .Tds,j,DMTH) 
are illustrated in Figure 6.2-4d. The DMTH-model values of drift wall temperature (Tdw,j,DMTH, 
Figure 6.2-5a) are determined by adding .Tdw,j,DMTH (Figure 6.2-4d) to Tdw,LMTH (Figure 6.2-4c). 
Note that the DMTH-model values of drip-shield temperature Tds,j,DMTH are similarly determined 
by adding .Tds,j,DMTH to Tds,LMTH (Figure 6.2-5e). 
STAGE 4The parameter AMLi,j-specific accounts for axial variations due to waste package 
sequencing and waste package-to-waste package variability in heat output and is necessary for 
the calculation of all hydrologic parameters in the DMTH-model. The parameter AMLi,j-specific is 
generated in much the same manner as the parameter AMLhstrk,eff in Stage 1. A number of values 
of AMLi,j-specific are generated at each of the repository subdomains. For example, at the drift 
wall AMLdw,j-specific is calculated in the following manner: (1) the local drift-wall temperature for 
a specific waste package Tdw,j,DMTH is compared to the family of AML-dependent Tdw,LDTH curves 
(Figure 6.2-5b); (2) the value of AMLdw,j-specific at any given time is the AML that an LDTH 
submodel would have to be to match the three-dimensional DMTH-model result. Figure 6.2-5c 
illustrates the AMLdw,PWR2-specific and AMLdw,HLW-specific curves. 
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STAGE 5Once the parameter AMLi,j-specific is determined from the temperature at a particular 
repository subdomain and a reference/waste package-specific location, it is possible to determine 
the corresponding hydrologic parameters, using output from the family of AML-dependent 
LDTH submodels. Note that the hydrologic parameters from the LDTH submodels are 
collectively referred to as Hi,j,LMTH in Figure 1-1 and Table 1-3. For example, RHdw,j,DMTH is 
obtained by linear interpolation for each timestep, using the AMLdw,j-specific and the family of 
AML-dependent RHdw,LDTH curves (Figure 6.2-5d). The value of RHdw,j,DMTH accounts for both 
the reference/waste package-specific deviations in local temperature and for the influence of 
three-dimensional mountain-scale heat flow at that particular repository subdomain. With the 
exception of drip-shield relative humidity RHds,j,DMTH and waste package relative humidity 
RHwp,j,DMTH, all other hydrologic parameters are calculated in a similar manner to RHdw,j,DMTH. 
STAGE 6The relative humidity on the drip shield and waste package (RHds,j,DMTH and 
RHwp,j,DMTH) is determined by relating thermal-hydrologic parameters that were determined by 
the DMTH model. The drip-shield relative humidity, RHds,j,DMTH is obtained by the following 
relation: 
P
sat (Tcav dw )
,
RH 
ds, j ,DMTH =RH cav dw Psat (Tds, j ,DMTH ) (Eq. 24) 
, 
Here RHds,j,DMTH and Tds,j,DMTH are the perimeter-averaged relative humidity and temperature on 
the drip shield, RHdw,cav and Tdw,cav are the perimeter-averaged relative humidity and temperature 
on the drift wall and invert surfaces that adjoin the open drift cavity outside of the drip shield, 
and Psat is the saturated vapor pressure. The waste package relative humidity RHwp,j,DMTH is 
calculated in an analogous manner. The relationship for the RHwp,j,DMTH utilizes the manner in 
which gas-phase mixing at the drip-shield joints allows the continuity of the partial pressure of 
water vapor Pv between the outside and inside of the drip shield. As discussed in Section 5.3.1.1, 
the joints in the drip shield allow the transport (by advection and binary diffusion) of gas (air 
plus water vapor) across the drip shield, which allows the continuity of Pv across the drip shield. 
Note that the assumption of the continuity of Pv across the drip shield is also used as a bounding 
case in In-Drift Natural Convection and Condensation (BSC 2004 [DIRS 164327], Section 
5.3.6). From a heat-transfer perspective, the drip shield functions like a thermal-radiation shield 
(between the waste package and the drift wall) that causes the waste package to be hotter than it 
would have been without the presence of the drip shield. Figure 6.2-5f illustrates RHds,j,DMTH at 
two waste package locations at the center of the repository. 
6.2.5 SMT Submodels 
The three-dimensional SMT submodel is used to determine the repository-scale variations in 
host-rock temperature (T) resulting from the heat output from the entire inventory of 70,000 
MTU of waste, including 63,000 MTU of commercial spent nuclear fuel (CSNF) and 7,000 
MTU of other nuclear waste (Canori and Leitner 2003 [DIRS 166275], p. 3-95). The SMT 
submodel includes the influence of mountain-scale thermal-property stratigraphic variation, the 
edge-cooling effect, which results from lateral heat loss at the repository edges, and the 
overburden-thickness distribution. Overburden thickness is defined to be the depth of the 
repository horizon below the ground surface. The SMT submodel domain extends from the 
ground surface to 1,000 m below the present-day water table and the lateral (adiabatic) 
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boundaries are far enough away from the repository that they do not affect repository 
temperatures. The temperature 1,000 m below the water table is estimated by extrapolation 
using the software routine boundary_conditions v1.0 (Section 3.1.8). 
The SMT submodel is a conduction-only calculation that does not require separate validation in 
this report. The reason they do not require validation is that they are conduction-only 
calculations that utilize standard scientific methods (e.g., Fouriers Law) to perform the 
calculations. Moreover, validation testing of the NUFT v3.0s code included conduction-only test 
problems (bmrk002 and verif02), which are described in the Validation Test Plan for NUFT 3.0s 
(LLNL 2002 [DIRS 170259]; LLNL 2000 [DIRS 170258]). 
6.2.5.1 SMT Submodel Mesh 
The actual and modeled repository footprints (Figure 6.2-3) cover nearly identical areas of 
approximately 4.656 km2, which is based on the modeled length of drifts (Table 6.2-1) 
multiplied by the 81-m drift spacing. The repository footprint corresponds to the area that is 
heated by the smeared-heat-source representation of heat generation from waste packages. The 
areal distribution of gridblocks in the repository area of the SMT submodel is shown in Figure 
6.2-3. The SMT submodel discretely represents each emplacement panel (Panels 1, 2E, 2W, 3, 
and 5) as well as each emplacement drift by using rows of heated gridblocks that are 20 m in the 
longitudinal direction, 81 m perpendicular to the drift axis, and 6-m thick in the vertical 
direction. The 6-m-thickness of the smeared heat source in the SMT submodel is consistent with 
that of the SDT submodel discussed in Section 6.2.7. There are 2,874 20-m intervals along the 
95 emplacement drifts in the SMT submodel. The actual total heated length of emplacement 
drift in the repository is 57,480.2 m; the modeled length of emplacement drifts is 57,480.0 m. 
Table 6.2-1 lists the actual and modeled lengths of heated emplacement drifts in each of the 
panels. The heated length of each emplacement drift is obtained from the end-point coordinates 
(BSC 2003 [DIRS 161727]). 
The SMT submodel mesh is constructed so that boundary effects have an insignificant influence 
on the predicted temperatures near the repository. This is accomplished by extending the lateral 
boundaries at least 1,000 m beyond the repository edges and by extending the lower boundary 
1,000 m below the water table. 
The software routine YMESH v1.54 (Section 3.1.7) is used to generate the SMT submodel mesh 
file so that it is consistent with the three-dimensional distribution of UZ model layers in the 
site-scale UZ flow and transport model (DTN: LB03023DKMGRID.001 [DIRS 162354]) as 
described in Table 11 of Development of Numerical Grids for UZ Flow and Transport Modeling 
(BSC 2004 [DIRS 169855]). The process of building the SMT submodel mesh is described in 
Appendix I. Note that the lower boundary (corresponding to the water table) of the three-
dimensional site-scale UZ flow model is a gently sloping surface. It is also noted that the output 
from the previous version of the site-scale UZ flow model (DTN: LB990701233129.001 [DIRS 
106785]) had a horizontal lower boundary at an elevation of 730 m, which was based on an 
assumption that the water table was horizontal. 
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Table 6.2-1. Summary of Emplacement Panels and Drifts Represented in the SMT Submodel 
Total heated drift Number of Total modeled 
Panel 
length 
(m)a 
emplacement 
driftsa 
Number of heated 
gridblocksb 
length of drifts 
(m)c 
1 4,100.4 8 206 4,120.0 
2E 10,882.0 19 545 10,900.0 
2W 13,845.1 23 689 13,780.0 
3 17,493.6 30 877 17,540.0 
5 11,159.1 15d 557 11,140.0 
Entire 
repository 
57,480.2 95 2874 57,480.0 
a 
Total heated drift lengths for each panel and for the entire repository, as well as the number of emplacement 
b 
drifts, are determined from the endpoint coordinates in BSC 2003 [DIRS 161727]. 
Each of the heated gridblocks represents a 20-m interval along the emplacement drift. 
d 
Total length of drifts as represented in the SMT submodel, as well as in the MSTHM. 
Panel 5 has a total of 27 drifts; the 15 northernmost drifts are emplaced in the TSPA-LA base case. 
The 2,874 gridblocks in the SMT submodel are the 2,874 locations for which the MSTHM 
provides thermal-hydrologic output. Because each of these 2,874 locations is represented by a 
gridblock that is 20-m-long in the axial direction along the drift, they can each contain 
approximately four waste packages. The MSTHM uses the DDT submodel (Section 6.2.8) to 
discretely represent the thermal-hydrologic conditions for a wide range of waste packages, 
ranging from those that have low heat-generation rates (e.g., DHLW waste packages) to those 
that have high heat-generation rates (e.g., 21-PWR CSNF waste packages). The DDT submodel 
discretely represents eight waste packages, including three 21-PWR CSNF waste packages, three 
44-BWR CSNF waste packages, and two DHLW waste packages. The MSTHM is constructed 
to provide thermal-hydrologic parameter histories (e.g., temperature and relative humidity) for 
each one of those eight waste packages at all 2,874 locations in the repository, which results in a 
total of 22,992 sets of thermal-hydrologic parameter histories. This number of sets is greater 
than the number of waste packages that could be emplaced in 57,480 m of emplacement drifts. 
The extra thermal-hydrologic parameter sets are provided to address uncertainty concerning the 
actual emplaced sequencing of waste packages. In other words, it cannot be known a priori what 
the actual emplaced waste package sequencing will be. The 22,992 sets of thermal-hydrologic 
parameter histories are provided for multiple scenarios, such as lower-bound, mean, and 
upper-bound infiltration-flux cases to allow downstream process models to sample from a broad 
set of thermohydrologic conditions that encompasses the influence of various sources of 
uncertainty. 
6.2.5.2 SMT Submodel Boundary Conditions 
The SMT submodel domain extends from the ground surface to 1,000 m below the present-day 
water table. The lateral boundaries, which are adiabatic boundaries, are at least 1,000 m from the 
repository edges, which is far enough away from the repository so that they do not affect thermal 
behavior in the repository. The temperature at the ground surface is based on ground-surface 
temperatures from the three-dimensional UZ flow model (DTN: LB991201233129.001 [DIRS 
146894], File INCON_thm_s32.dat), which is based on a correlation of temperature versus 
elevation. 
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The temperature at the lower boundary of the model domain is extrapolated vertically from the 
temperature gradient at the (sloping) water table of the current site-scale UZ flow model. The 
temperature at the sloping water is interpolated, based on the temperature at an elevation of 
730 m, which was the water table in the previous three-dimensional UZ flow model, and the 
ground-surface temperature. Both the ground-surface temperature distribution and the 
(730-m-elevation) water-table temperature distribution are found in 
DTN: LB991201233129.001 [DIRS 146894], File INCON_thm_s32.dat. Appendix II describes 
the process of generating boundary temperatures for the SMT submodels, as well as for the other 
submodels. 
Note that since the boundary conditions were determined for the SMT submodel, a new source of 
boundary conditions has been made available in Mountain-Scale Coupled Processes 
(TH/THC/THM) Models (BSC 2004 [DIRS 169866]). The temperature boundary conditions can 
be extracted from the INCON block of file: th_v16.dat of DTN: LB0310MTSCLTH3.001 
[DIRS 170270]. As discussed in Appendix I, these updated boundary conditions result in 
insignificant differences in temperatures at both the upper boundary (the ground surface) and the 
lower boundary (the water table), compared to those obtained in this report from file: 
INCON_thm_s32.dat of DTN: LB991201233129.001 [DIRS 146894]. 
6.2.5.3 SMT Submodel Heat-Generation Rates 
The heat-generation rate for the SMT submodel is in the form of a 
heat-generation-rate-versus-time table, which is part of the SMT submodel NUFT-input file. For 
the TSPA-LA base case there is an assumption that all waste packages are simultaneously 
emplaced (Section 5.2.3). Thus, heating starts at the same time for the entire repository 
represented in the SMT submodel. The heat-removal efficiency of drift ventilation is represented 
by the reduction of the net heat-generation rate during the preclosure period. It is important to 
note that the heat-removal efficiency depends on the distance from the ventilation inlet and it 
also varies with time (Table III-1 of Appendix III). Thus, the effective heat-generation rate 
along an emplacement drift depends on the distance from the edge of that drift during the 
preclosure period. The heat-removal effect of drift ventilation is incorporated into the 
heat-generation-rate-versus-time tables for the heated repository blocks, using the software 
routine heatgen_vent_emplace v1.0 (Section 3.1.9). For the postclosure period, the same heat-
generation-rate-versus-time table is applied to the entire repository because drift ventilation has 
ceased and the effective heat-generation rate is the full nominal rate. Appendix III describes the 
process of generating heat-generation-rate-versus-time tables for the SMT submodel, as well as 
for the other submodels. 
6.2.5.4 SMT Submodel Material Properties 
Because the SMT submodel is a thermal-conduction model, it only requires thermal properties, 
which are contained in the SMT submodel NUFT-input files. 
The SMT submodel uses bulk thermal properties consistent with the SDT submodel (Section 
6.2.7). These properties are based on Table IV-3a in Appendix IV and the assumption of using 
the wet thermal conductivity as discussed in Section 5.3.2.1. 
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Where saturated zone thermal properties are required the thermal properties are a weighted 
average of UZ model layers as discussed in Section 5.3.2.2. The averaging is accomplished by 
determining area-weighting factors for each of the UZ model layers that occur at the water table, 
which is the lower boundary of the three-dimensional site-scale UZ flow model. The process of 
building the SMT submodel material property files is described in Appendix IV. 
6.2.5.5 SMT Submodel Simulations 
The initialization of the SMT submodel is accomplished by running the SMT submodel with no 
repository thermal load until a steady-state temperature distribution is achieved. Only one SMT 
submodel simulation is required to represent the preclosure and postclosure period. This 
simulation is run for 20,000 years after closure of the repository. The process of building the 
SMT submodel input files is described in Appendix V. 
6.2.6 LDTH Submodels 
The two-dimensional LDTH submodels use the dual-permeability method, modified with the 
active-fracture concept, to represent two-phase heat and fluid flow in the fractured porous rock. 
The LDTH submodels are run at the 108 drift-scale-submodel locations (Figure 6.2-3) and for 4 
different values of modeled AML (14, 27, 55, and 66 MTU/acre). Representing the influence of 
edge-cooling effects requires that most of the LDTH submodel runs use a modeled AML that is 
less than the actual AML of the repository. 
In addition to their use as a submodel within the MSTHM methodology, the two-dimensional 
LDTH submodels are also used as stand-alone models to conduct sensitivity analyses in this 
report (e.g., Section 6.3.9). Thus, the LDTH submodel is validated against the Drift Scale Test 
in Section 7.4. 
The NUFT code is used to model flow through a fractured porous media in the LDTH 
submodels. The key NUFT options that are required for LDTH simulations include the 
dual-permeability and the active-fracture concept. These NUFT options are required to be 
consistent with the hydrologic property set (DTN: LB0208UZDSCPMI.002 [DIRS 161243]) 
used in the MSTHM calculations supporting the TSPA-LA. 
The DKM conceptualizes the fractured rock as having two interacting materials, one 
representing the matrix and one representing the fractures. The interaction between the fractures 
and the matrix is explicitly calculated from the local temperature and pressure differences, thus 
allowing transient behavior to be predicted. 
The active fracture concept accounts for the contact area between the fracture and the matrix, as 
well as the frequency of fractures. The concept is that fracture flow only occurs through some of 
the fractures. The flux through a fracture increases with liquid-phase saturation; thereby 
focusing flow through a portion of the fractures (i.e., through active fractures), which results in 
faster pathways for liquid-phase flux through the mountain. 
The natural system hydrologic properties in the calibrated drift-scale hydrologic property set 
(DTN: LB0208UZDSCPMI.002 [DIRS 161243]) were calibrated in Calibrated Properties 
Model (BSC 2004 [DIRS 169857]), using an inverse modeling technique that assumes the use of 
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the DKM and the active-fracture concept. Both the DKM and active-fracture concept are 
implemented in NUFT as options. 
6.2.6.1 LDTH Submodel Locations 
The LDTH submodel locations are shown in Figure 6.2-3, and represent repository-scale 
variability of thermal properties, hydrologic properties, percolation flux, and overburden 
thickness. 
6.2.6.2 LDTH Submodel Mesh 
The cross-sectional (lateral) dimensions of the drift for the postclosure period are shown in 
Figure 6.2-1; these dimensions were used to build the numerical meshes of the LDTH submodels 
(Figure 6.2-6). The same mesh is used for the initialization submodel runs, which establish 
steady-state conditions for the time of emplacement and the submodel runs for the preclosure and 
postclosure periods. The process of building the LDTH submodel input files is described in 
Appendix V. 
The numerical mesh for the LDTH submodel (Figure 6.2-6) assumes that the drip shield and 
waste package are lumped as a monolithic heat source. This lumped approximation of the drip 
shield and waste package allows for the representation of thermal-hydrologic behavior down to 
the surface of the drip shield. This lumped heat source is 1 m in the longitudinal direction along 
the drift axis (as it is in the smeared heat source in the SDT submodel discussed in 
Section 6.2.7). This lumped representation for the waste package and drip shield is applied 
during both the preclosure period and the postclosure period. Note that the drip shield is 
emplaced at the very end of the preclosure period. For the preclosure period, this lumped 
approximation of the drip shield and waste package in the LDTH submodel is corrected by the 
manner in which the preclosure DDT submodel (Figure 6.2-7), which accounts for the actual 
dimensions of the waste package (without the presence of the drip shield), is applied in the 
MSTHAC methodology (Section 6.2.4). The postclosure DDT submodel (Figure 6.2-8), which 
accounts for the actual waste package and drip-shield dimensions (including the correct 
dimensions of the gap between the waste package and drip shield), is applied in the MSTHAC 
methodology (Section 6.2.4) to represent thermohydrologic behavior between the drip shield and 
waste package. 
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Source: See Table XIII-1. 
NOTE: This illustrates just a portion of the mesh. The entire model extends laterally 40.5 m (the mid-pillar 
centerline) and extends from the ground surface to the water table. 
Figure 6.2-6. Cross-Sectional (Lateral) View of the Numerical Mesh Used in the Vicinity of the Drift for All 
LDTH Submodels, Including Both the Initialization Runs and the Preclosure and 
Postclosure Runs 
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6.2.6.3 LDTH Submodel Boundary Conditions 
Because the LDTH submodels are for a symmetry cell between the vertical plane down the 
center of the drift and the vertical midplane between drifts, the lateral boundaries are adiabatic 
and no-mass-flow boundaries. The LDTH submodels require temperature, pressure, and 
gas-phase air-mass fraction at the upper boundary, which represents the ground surface, and at 
the lower boundary, which represents the water table. The upper boundary also requires the 
enthalpy associated with the infiltration flux at the top of the model. Note that the enthalpy is 
determined from the temperature of the upper boundary. 
Both the upper and lower boundaries have constant conditions with time. Note that the process 
of calculating air-mass fraction at the ground surface utilizes the assumption that the atmosphere 
is at 100 percent relative humidity (Section 5.1.1). The process of adding the boundary 
conditions to the LDTH submodels is described in Appendix II. 
Note that since the boundary conditions were determined for the LDTH submodels, a new source 
of boundary condition has been made available in Mountain-Scale Coupled Processes 
(TH/THC/THM) Models (BSC 2004 [DIRS 169866]). The temperature and gas-phase-pressure 
boundary conditions can be extracted from the INCON block of file: th_v16.dat of DTN: 
LB0310MTSCLTH3.001 [DIRS 170270]. As discussed in Appendix I, these updated boundary 
conditions result in insignificant differences in temperatures and gas-phase pressures at both the 
upper boundary (the ground surface) and the lower boundary (the water table) compared to those 
obtained in this report from file: INCON_thm_s32.dat of DTN: LB991201233129.001 [DIRS 
146894]. 
6.2.6.4 LDTH Submodel Heat-Generation Rates 
The heat-generation rates for the LDTH submodels are in the form of 
heat-generation-rate-versus-time tables located in NUFT include files. Because any given LDTH 
submodel covers the same model domain (including the same area in plan view) as the 
corresponding SDT submodel, the LDTH and corresponding SDT submodel use the same 
heat-generation-rate-versus-time tables. The drip shield and waste package are lumped as a 
monolithic heat source. The heat-removal efficiency of drift ventilation is represented by the 
reduction of the net heat-generation rate during the preclosure period. The heat-removal 
efficiency depends on the distance from the ventilation inlet and also varies with time. Thus, the 
effective heat-generation rate along an emplacement drift depends on the distance from the edge 
of that drift during the preclosure period. The heat-removal effect of drift ventilation is 
incorporated into the heat-generation-rate-versus-time tables for a given LDTHSDT submodel 
location, using the software routine heatgen_ventTable_emplace v1.0 (Section 3.1.9). For the 
postclosure period, the same heat-generation-rate-versus-time table is applied to all LDTHSDT 
submodel locations because drift ventilation has ceased and the effective heat-generation rate is 
the full nominal rate at all locations. The input files for the LDTH submodels involve 
assumptions described in Sections 5.1.1, 5.1.2, 5.1.3, 5.1.4, 5.1.5, 5.3.1.1, 5.3.1.2, 5.3.1.7, 
5.3.1.8, 5.3.1.9, 5.3.1.10, 5.3.2.3, 5.3.2.4, and 5.3.2.7. Appendix III describes the process of 
generating heat-generation-rate-versus-time tables for the LDTH submodels. 
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6.2.6.5 LDTH Submodel Material Properties 
Material properties are read into the LDTH submodel NUFT-input files as include files for the 
natural system properties and for the engineered barrier system properties inside the 
emplacement drifts. 
One hydrologic property set, called the modified-mean infiltration-flux hydrologic property set 
(dkm-afc-1Dds-mc-mi-04), is used to conduct the LDTH submodel calculations for lower-bound, 
mean, and upper-bound infiltration-flux cases. The modified-mean infiltration-flux property set 
is the same as the mean infiltration-flux property set (DTN: LB0208UZDSCPMI.002 
[DIRS 161243]), with the one modification being that the van Genuchten fracture alpha in the 
Tptpul (tsw33) is set to be the same (1.02  10-4 Pa-1) as that in the Tptpll (tsw35) unit (Table 
IV-4 in Appendix IV). The file dkm-afc-EBS-mi-03 gives the thermal and hydrologic properties 
of the materials inside the emplacement drift. The thermal properties inside the emplacement 
drifts, such as the drip shield composed of titanium and invert composed of crushed tuff, are 
given in Table 4.1-2. The thermal properties inside the drifts also include the emissivity values 
of the surfaces. Note that a value of 0.9 is used for the emissivity of the rock and invert surfaces 
in the drift, which is obtained from Incropera and DeWitts (1996 [DIRS 108184]) advanced 
textbook for heat and mass transfer. The engineered barrier system thermal properties also 
include the use of an effective thermal conductivity for the gas-filled drift cavity that is based on 
a correlation (Francis et al. 2003 [DIRS 164602], Table 6) accounting for the influence of natural 
convection, which is described in Appendix I. It should be noted that the correlations for the 
in-drift effective thermal conductivity, which were obtained from Table 6 of Francis et al. (2003 
[DIRS 164602]), have been updated in In-Drift Natural Convection and Condensation (BSC 
2004 [DIRS 164327], Table 6.4.7-3), resulting in small changes to the coefficients. As evident 
in Figure I-1 of Appendix I, the small changes to the coefficients result in insignificant changes 
to the in-drift effective thermal conductivity. The gas-filled cavity between the drip shield and 
drift wall is represented as a porous medium with 100 percent porosity and a permeability of 
1  10-8 m2 (Section 5.3.1.7). Because the dual-permeability method is used, it is necessary to 
partition the gas-filled cavity into the matrix and fracture continua. This partitioning, which is 
taken to be 50 percent matrix continuum and 50 percent fracture continuum, has an insignificant 
on flow because of conditions in these respective continua are in equilibrium within the 
gas-filled drift. The input files are associated with the assumptions described in Sections 5.1.1, 
5.1.2, 5.2.3, 5.3.1.1, 5.3.1.2, 5.3.1.7, 5.3.1.8, 5.3.2.3, and 5.3.2.4. The process of generating the 
LDTH submodel material properties files is described in Appendix IV. The input files require 
the assumptions described in Sections 5.1.1, 5.1.2, 5.2.3, 5.3.1.1, 5.3.1.2, 5.3.1.7, 5.3.1.8, 5.3.2.3, 
and 5.3.2.4. The process of generating the LDTH submodel material properties files is described 
in Appendix IV. 
6.2.6.6 LDTH Submodel Percolation Flux 
The liquid-phase flux is specified at the upper boundary of the LDTH submodels. For the 
TSPA-LA base case, the upper-boundary liquid-phase flux corresponds to the distribution of 
percolation flux just below the base of the PTn unit (also called the PTn-to-TSw percolation 
flux); these data are generated by the three-dimensional UZ flow model for the three climate 
states: present-day, monsoonal, and glacial-transition. Thus, the MSTHM includes the influence 
of lateral diversion in the PTn as represented in the three-dimensional UZ flow model. 
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The PTn-to-TSw percolation flux is provided for the present-day, monsoonal, and 
glacial-transition climates for lower-bound, mean, and upper-bound infiltration-flux cases 
(DTN: LB0302PTNTSW9I.001 [DIRS 162277]), resulting in nine files. The software routine 
repository_percolation_calculator v1.0 (Section 3.1.13) is used to determine the percolation flux 
at each of the 108 LDTHSDT submodel locations (Figure 6.2-3) in Panels 1, 2E, 2W, 3, and 5. 
The process of generating LDTH submodel percolation-flux boundary conditions is described in 
Appendix I. Appendix XII describes a comparison of the percolation-flux distribution 
implemented in the MSTHM compared to the PTn-to-TSw percolation-flux distribution from 
DTN: LB0302PTNTSW9I.001 [DIRS 162277]. As is evident in Figures XII-3 through XII-11, 
the percolation flux implemented in the MSTHM corresponds closely with that from 
DTN: LB0302PTNTSW9I.001 [DIRS 162277] for all three climate states and for all three 
infiltration-flux cases. 
6.2.6.7 LDTH Submodel Simulations 
The LDTH submodel is the only submodel type that has to be run for each of the three 
infiltration-flux cases (lower-bound, mean, and upper-bound). The simulations for the other 
three submodel types are applicable to all infiltration-flux cases. 
Each LDTH submodel set for a given infiltration-flux case consists of 432 simulations, which 
comes from 108 drift-scale-submodel locations (Section 6.3.1) and 4 AML values run at each 
location (108  4 = 432). The process of building the LDTH submodel input files is described in 
Appendix I. 
6.2.7 SDT Submodels 
The one-dimensional smeared-heat-source drift-scale thermal-conduction (SDT) submodels are 
run in parallel with the LDTH submodels at the same 108 locations and for the same AMLs 
(14, 27, 55, and 66 MTU/acre). These submodels are required to obtain functional relationships 
between line-averaged temperatures predicted by the LDTH submodel and the smeared 
host-rock temperatures predicted by the SDT submodel. 
The SDT submodels are conduction-only calculations that do not require separate validation in 
this report. The reason they do not require validation is that they are conduction-only 
calculations that utilize standard scientific methods (e.g., Fouriers Law) to perform the 
calculations. Moreover, validation testing of the NUFT v3.0s code included conduction-only test 
problems (bmrk002 and verif02), which are described in the Validation Test Plan for NUFT 3.0s 
(LLNL 2002 [DIRS 170259]; LLNL 2000 [DIRS 170258]). 
6.2.7.1 SDT Submodel Locations 
The SDT submodels are run at the same 108 drift-scale-submodel locations (Figure 6.2-3) as the 
LDTH submodel (Section 6.2.6.1). 
6.2.7.2 SDT Submodel Mesh 
The SDT submodels use the same vertical discretization of gridblocks as is used in the SMT 
submodels (Section 6.2.5). The manner in which the LDTHSDT temperature relationships are 
developed and used to modify SMT-predicted host-rock temperatures (Section 6.2.4) requires 
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consistency between how vertical heat flow is modeled in the respective SDT and SMT 
submodels, including consistency in the vertical gridblock discretization in the respective 
submodels. 
6.2.7.3 SDT Submodel Boundary Conditions 
The SDT submodel boundary temperature conditions are the same as the corresponding LDTH 
submodel (Section 6.2.6.3). Consistent upper and lower boundary temperatures ensure 
self-consistency with respect to how the LDTH and SDT submodels are used to generate 
LDTH-temperature versus SDT-temperature relationships and how these relationships are used 
in the MSTHAC v7.0 methodology to correct SMT-predicted temperatures to LMTH conditions 
(Section 6.2.4). 
Because the SDT submodels are for a symmetry cell between the vertical plane down the center 
of the drift and the vertical midplane between drifts, the lateral boundaries are adiabatic and 
no-mass-flow boundaries. The SDT submodels require temperature at the upper boundary, 
which represents the ground surface, and the lower boundary, which represents the water table. 
Both boundaries have constant temperature conditions with time. The process for generating 
SDT submodel boundary conditions is described in Appendix II. 
Note that since the boundary conditions were determined for the SDT submodels, a new source 
of boundary condition has been made available from the Mountain-Scale Coupled Processes 
(TH/THC/THM) Models (BSC 2004 [DIRS 169866). The temperature boundary conditions can 
be extracted from the INCON block of file: th_v16.dat of DTN: LB0310MTSCLTH3.001 
[DIRS 170270]. As discussed in Appendix I, these updated boundary conditions result in 
insignificant differences in temperatures at both the upper boundary (the ground surface) and the 
lower boundary (the water table), compared to those obtained in this report from file: 
INCON_thm_s32.dat of DTN: LB991201233129.001 [DIRS 146894]. 
6.2.7.4 SDT Submodel Heat-Generation Rates 
Because any given SDT submodel represents the same model domain (including the same area in 
plan view) as the corresponding LDTH submodel, the SDT and corresponding LDTH submodel 
use the same heat-generation rate-versus-time table (Section 6.2.6.4). Appendix III describes the 
process of generating heat-generation-rate-versus-time tables for the SDT submodels. The heat 
generation is smeared over a gridblock that is 6-m thick in the vertical direction (as it is in the 
SMT submodel, discussed in Section 6.2.5), 1 m in the longitudinal direction along the drift axis 
(as it is in the LDTH submodels, discussed in Section 6.2.6), and which extends from the drift 
centerline to the midpillar location between drifts. 
6.2.7.5 SDT Submodel Material Properties 
Because the SDT submodel is a conduction-only model, the material properties only involve 
thermal properties. Material properties are read into the SDT submodel NUFT-input files as 
include files for the natural system thermal properties. The SDT submodel uses the same 
thermal properties (for the UZ model layers) that are used in the SMT submodel 
(Section 6.2.5.4). The material properties of the SDT submodels utilize assumptions described 
in Section 5.3.2.1. The process of building the SDT submodel material-property file is described 
in Appendix IV. 
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6.2.7.6 SDT Submodel Simulations 
Each SDT submodel set consists of 432 simulations that come from 108 LDTHSDT submodel 
locations (Figure 6.2-3) and 4 AML values run at each location (108  4 = 432). The process of 
building the SDT submodel input files is described in Appendix V. 
6.2.8 DDT Submodels 
The three-dimensional DDT submodel is used to account for waste package-specific heat output 
and for thermal radiation between all waste package and drift surfaces to determine waste 
package-specific deviations (relative to line-averaged-heat-source conditions) in temperatures in 
the drift and adjoining host rock. For the preclosure and postclosure periods, thermal radiation 
between the waste package and drift surfaces controls the longitudinal temperature deviations 
along the drift. The values of thermal conductivity or convective heat-flow processes in the host 
rock play a minor role on the magnitude of longitudinal temperature deviations along the drift 
(Hardin 1998 [DIRS 100350], Section 3.7.5.4). This allows an MSTHM calculation to only 
require a set of DDT submodel calculations conducted at a single location in the repository. The 
P2WR5C10 LDTHSDT submodel location is located in Panel 2W, which is located in the 
approximate center of the repository (Figures 6.2-3 and 6.3-1). The nomenclature R5C10 refers 
to the row and column of this drift-scale submodel location within the lattice of drift-scale 
submodel locations (Figure 6.2-3). This location was selected because the repository horizon at 
that location is in the middle of the Tptpll (tsw35 UZ model layer), which is the predominant 
host-rock type in the repository, and because the overburden thickness at that location is close to 
the average for the repository. The DDT submodels utilize assumptions described in Sections 
5.2.2, 5.2.3, 5.3.2.1, and 5.4. 
The DDT submodels are conduction-only calculations that do not require separate validation in 
this report. The reason they do not require validation is that they are conduction-only 
calculations that utilize standard scientific methods (e.g., Fouriers Law) to perform the 
calculations. Moreover, validation testing of the NUFT v3.0s code included conduction-only test 
problems (bmrk002 and verif02), which are described in the Validation Test Plan for NUFT 3.0s 
(LLNL 2002 [DIRS 170259]; LLNL 2000 [DIRS 170258]). The DDT submodel represents 
thermal radiation inside the emplacement drifts and also represents the influence of natural 
convective heat flow in the drifts through the use of an equivalent thermal conductivity that is 
based on a correlation given by Francis et al. (2003 [DIRS 164602], Table 6) (Section 6.2.8.5). 
Thus, the DDT does not model natural convection in the drift; it only uses a correlation derived 
elsewhere as indicated. The software qualifications of NUFT v3.0s and NUFT v3.0.1s include 
test problems that demonstrate the validity of NUFT in modeling a one-dimensional thermal 
conduction problem (bmrk 002), a three-dimensional thermal conduction problem (verif02), and 
a three-dimensional thermal radiation problem (verif03) (LLNL 2002 [DIRS 170259]; LLNL 
2000 [DIRS 170258]). 
6.2.8.1 DDT Submodel Locations 
The P2WR5C10 LDTHSDT submodel location, which is in the center of the repository, located 
in Panel 2W (Figures 6.2-3 and 6.3-1), is used for all DDT submodel calculations. 
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6.2.8.2 DDT Submodel Mesh 
The lateral and longitudinal dimensions of the drift for the preclosure and postclosure periods are 
shown in Figures 6.2-1 and 6.2-2, respectively. Note that the drip shield (Figure 6.2-1) is not 
present during the preclosure ventilation period. These dimensions were used to build the 
numerical meshes of the DDT submodels. The cross-section view of the mesh is shown in 
Figures 6.2-7 and 6.2-8 for the preclosure and postclosure periods, respectively. The 
longitudinal view of the mesh is shown in Figures 6.2-9 and 6.2-10 for the preclosure and 
postclosure periods, respectively. The DDT submodel utilizes symmetry in all four directions: 
(1) about the vertical midplane down the center of the drift, (2) the vertical midplane down the 
center of the rock pillar between drifts, (3) the vertical plane that is orthogonal to and intersects 
the one-half 21-PWR waste package, and (4) the vertical plane that is orthogonal to and 
intersects the one-half 44-BWR waste package (Figure 6.2-2). Thermal radiation is 
represented between all surfaces in the drift. From a heat-transfer perspective, the drip shield 
functions like a thermal-radiation shield (between the waste package and the drift wall) that 
causes the waste package to be hotter than it would have been without the presence of the drip 
shield. The increased temperature difference between the waste package and the drift wall 
reduces the relative humidity on the waste package in a fashion that is analogous to that given in 
Equation 24 (Section 6.2.4) for the drip shield itself. 
6.2.8.3 DDT Submodel Boundary Conditions 
The temperature boundary conditions for the DDT submodels are the same as those for the SDT 
submodel at the P2WR5C10 LDTHSDT submodel location (Figures 6.2-3 and 6.3-1), which is 
in the center of the repository, located in Panel 2W. The DDT submodel temperature boundary 
conditions are the same as the corresponding LDTH submodel. 
Because the DDT submodels are for a symmetry cell between the vertical plane down the center 
of the drift and the vertical midplane between drifts, the lateral boundaries are adiabatic and 
no-mass-flow boundaries. The DDT submodels require temperature at the upper boundary, 
which represents the ground surface, and at the lower boundary, which represents the water 
table. Both boundaries have constant temperature conditions with time. The process for 
generating DDT submodel boundary conditions is described in Appendix II. 
6.2.8.4 DDT Submodel Heat-Generation Rates 
Heat-generation-rate-versus-time tables are required for the 8 different waste packages 
represented in the DDT submodels (Figure 6.2-2), which are read into the DDT submodel 
NUFT-input files as include files. The heat-generation-rate-versus-time tables utilize the 
assumption described in Section 5.2.3. During the preclosure period, the DDT submodel has the 
same heat-removal-efficiency-versus-time table that is applicable to the P2WR5C10 LDTH-SDT 
submodel location (Figures 6.2-3 and 6.3-1). Note that the heat-removal-efficiency-versus-time 
tables are derived from DTN: MO0304MWDALACV.000 [DIRS 164551]. Appendix III 
describes the process of generating heat-generation-rate-versus-time tables for the DDT 
submodel, as well as for the other submodels. 
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Source: See Table XIII-1. 
NOTE: This illustrates just a portion of the mesh. The entire model extends laterally 40.5 m (the mid-pillar 
centerline) and extends from the ground surface to the water table. 
Figure 6.2-7. Cross-Sectional (Lateral) View, Perpendicular to Drift Axis, of the Mesh Used in the 
Preclosure DDT Submodels 
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Source: See Table XIII-1. 
NOTE: This illustrates just a portion of the mesh. The entire model extends laterally 40.5 m (the mid-pillar 
centerline) and extends from the ground surface to the water table. 
Figure 6.2-8. Cross-Sectional (Lateral) View, Perpendicular to Drift Axis, of the Mesh Used in the 
Postclosure DDT Submodels 
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Source: See Table XIII-1. 
NOTE: WP = waste package. This illustrates just a portion of the mesh. The entire model extends laterally 40.5 
m (the mid-pillar centerline) and extends from the ground surface to the water table. 
Figure 6.2-9. Cross-Sectional (Longitudinal) View, Parallel to Drift Axis, of the Mesh Used in the 
Preclosure DDT Submodels 
Source: See Table XIII-1. 
NOTE: WP = waste package. This illustrates just a portion of the mesh. The entire model extends laterally 40.5 
m (the mid-pillar centerline) and extends from the ground surface to the water table. 
Figure 6.2-10. Cross-Sectional (Longitudinal) View, Parallel to Drift Axis, of the Mesh used in the 
Postclosure DDT Submodels 
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6.2.8.5 DDT Submodel Material Properties 
Because the DDT submodel is a thermal-conduction/radiation-only model (i.e., does not 
represent hydrologic processes), the material properties only involve thermal properties. 
Material properties are read into the SDT submodel NUFT-input files as include files for the 
natural system thermal properties. The DDT submodel uses the same thermal properties (for the 
UZ model layers) that are used in the SMT and SDT submodels (Sections 6.2.5.4 and 6.2.7.5). 
The DDT submodels also use thermal properties of the engineered barrier system components, 
such as the drip shield, invert, and respective waste packages (Table 4.1-2). The thermal 
properties of the engineered barrier system components include the emissivity values of the 
surfaces within the emplacement drifts. The engineered barrier system thermal properties also 
include the use of an effective thermal conductivity for the air in the drift cavity that is based on 
a correlation (Francis et al. 2003 [DIRS 164602], Table 6) accounting for the influence of natural 
convection, which is described in Appendix I. It should be noted that the correlations for the 
in-drift effective thermal conductivity, which were obtained from Table 6 of Francis et al (2003 
[DIRS 164602]), have been updated in In-Drift Natural Convection and Condensation (BSC 
2004 [DIRS 164327], Table 6.4.7-3), resulting in very small changes to the coefficients. As 
evident in Figure I-1 of Appendix I, the small changes to the coefficients result in insignificant 
changes to the in-drift effective thermal conductivity. The material properties of the DDT 
submodels utilize assumptions described in Section 5.3.2.1. The process of building the DDT 
submodel material-property file is described in Appendix IV. 
6.2.8.6 DDT Submodel Simulations 
A single set of DDT submodel simulations (for modeled AMLs of 14, 27, 55, and 66 MTU/acre) 
was conducted for this report at the P2WR5C10 LDTHSDT submodel location (Figures 6.2-3 
and 6.3-1). This set of DDT submodel simulations is used in all three (lower-bound, mean, and 
upper-bound) infiltration-flux cases. The process of building the DDT submodel NUFT-input 
files is described in Appendix V. 
6.2.9 SMT and SDT Submodels for the Low-Probability-Seismic Collapsed-Drift 
Scenario 
For the low-probability-seismic collapsed-drift scenario, no changes are required for the SMT 
submodel. Therefore, the description of the SMT submodel (Section 6.2.5) is applicable. For 
the collapsed-drift scenario, no changes are required for the SDT submodels. Therefore, the 
description of the SDT submodels (Section 6.2.7) is applicable. The SDT submodel location is 
the P2WR5C10 LDTHSDT submodel location (Figures 6.2-3 and 6.3-1). A single set of SDT 
submodel simulations (for modeled AMLs of 14, 27, 55, and 66 MTU/acre) was utilized. 
6.2.10 LDTH Submodels for the Low-Probability-Seismic Collapsed-Drift Scenario 
For the low-probability-seismic collapsed-drift scenario, two changes need to be implemented in 
the LDTH submodels. First, the geometry of the drift is changed to account for the host-rock 
rubble that fills the drift from the outer surface of the drip shield to the intact host-rock. Second, 
thermal-hydrologic properties are required for the host-rock rubble. The implementation of these 
changes is described in the following sections. The boundary conditions, heat-generation rates, 
and percolation-flux values are the same as those used in the corresponding MSTHM 
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calculations for the intact drift (i.e., nominal) case. Two thermal conductivity Kth cases are 
considered: (1) high-Kth host-rock rubble and (2) low-Kth host-rock rubble. 
6.2.10.1 LDTH Submodel Location 
The LDTH submodel location is the P2WR5C10 LDTHSDT submodel location (Figures 6.2-3 
and 6.3-1). Two sets of LDTH submodel simulations (for modeled AMLs of 14, 27, 55, and 66 
MTU/acre) are conducted for two different host-rock rubble thermal conductivity cases. This 
location was selected because it is representative of a typical location in the predominant 
host-rock unit (Tptpll), close to the center of the repository area, and because the local 
percolation-flux values (Table 6.3-9) are close to the repository-wide averages for the 
present-day, monsoonal, and glacial climates (Table 6.3-4). 
6.2.10.2 LDTH Submodel Mesh 
The low-probability-seismic scenario causes collapse of the drift opening, which is represented 
by a circular profile with a diameter of 11 m. The resulting host-rock rubble completely fills the 
modified drift opening, from the outer surface of the drip shield out to the modified drift wall, 
as shown in Figures 6.2-11 and 6.2-12 of this report, and in Section 6.4.3.4 of Abstraction of 
Drift Seepage (BSC 2004 [DIRS 169131]). A schematic of the collapsed-drift scenario is also 
given in Figure 6.4-22 of Abstraction of Drift Seepage (BSC 2004 [DIRS 169131]). The 
cross-sectional (lateral) geometry of the drift for the collapsed drift is represented in the LDTH 
submodel mesh, which is shown in Figure 6.2-11. Note that the cross-sectional geometries of the 
drip shield and invert remain the same. Note that this mesh is used for both the preclosure and 
postclosure periods. 
The bulking factor is obtained from the LDTH submodel mesh (Figure 6.2-11) as follows. The 
bulking factor is a measure of the additional volume that the host-rock rubble occupies (after it 
collapses into and completely fills the previously open drift cavity) compared to the volume it 
occupied while it was intact host rock. Thus, the bulking factor is a relative measure of how 
much bulkier the host-rock rubble is (when it falls into and fills the drift cavity) than the 
original intact host rock that it was derived from. Note that the host-rock rubble also completely 
fills the volume that the intact host rock originally occupied. The bulking factor is equal to the 
cross-sectional area of the previously open drift cavity, which is the area of the blue region that 
lies inside of the dashed line in Figure 6.2-11 (and which is shown in white in Figure 6.2-6), 
divided by the cross-sectional area of the host-rock rubble zone outside of the original 5.5-m-
diameter drift (which is the area of the blue region that lies outside of the dashed line in Figure 
6.2-11). On the basis of the LDTH submodel mesh (Figure 6.2-11), the bulking factor is equal to 
0.231. Thus, the volume of host-rock rubble zone is 23.1 percent larger than the original volume 
of the intact host rock from which the rubble was derived. 
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Source: See Table XIII-1. 
NOTE: This mesh is used for the preclosure and postclosure periods. The figure illustrates just a portion of the 
mesh. The entire model extends laterally 40.5 m (the mid-pillar centerline) and extends from the ground 
surface to the water table. 
Figure 6.2-11. Cross-sectional (Lateral) View of the LDTH Submodel Mesh Used for the Low-
Probability-Seismic Collapsed-Drift Scenario 
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Source: See Table XIII-1. 
NOTE: This mesh is used for the preclosure and postclosure periods. 
Figure 6.2-12. Cross-Sectional (Lateral) View of the DDT Submodel Mesh Used for the Low-Probability-
Seismic Collapsed-Drift Scenario 
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6.2.10.3 LDTH Submodel Host-Rock Rubble Thermal-Hydrologic Properties 
The thermal-hydrologic properties of the host-rock rubble are derived from those of the Tptpll 
(tsw35) unit, which is the host-rock unit at the P2WR5C10 LDTHSDT submodel location 
(Figures 6.2-3 and 6.3-1). The hydrologic properties of the host-rock rubble are modified from 
those of the intact host rock (Table 6.2-2) in a manner that is analogous to what is done to the 
crushed-tuff invert. The only matrix-continuum hydrologic parameters that are modified from 
the intact host-rock values are the matrix porosity and matrix permeability; these two parameters 
are reduced to account for the decreased density of the host-rock rubble by multiplying the 
intact-host-rock values by 1/(1 + BF), where BF is the bulking factor. The bulk grain density 
and bulk thermal conductivity (Table 6.2-3) are also reduced to account for the decreased density 
of the host-rock rubble by multiplying the intact-host-rock values by 1/(1 + BF). This value of 
bulk thermal conductivity Kth is applied to the high-Kth case because it implicitly incorporates 
parallel thermal conductors (versus series thermal conductors). Thus, the solid portion of the 
host-rock rubble is effectively lined up in parallel with the void portion of the rubble. 
The low-Kth case is intended to account for the thermal-contact resistance between blocks of the 
rubble. Because the thermal conductivity of the solid portion of the rubble is much greater than 
that of the air-filled voids, the vast majority of thermal conduction occurs in the solid portion. 
The geometry of the rubble causes a bottle-necking effect at the point where the rock blocks 
contact each other. The values of Kth for the low-Kth case are half of those of the high-Kth case to 
account for thermal-contact resistance at the bottlenecks. Thermal radiative heat transfer also 
contributes to heat transfer within the air-filled voids. The relative contribution of radiative heat 
transfer depends on the size of the rock blocks and voids, with larger voids facilitating more 
efficient thermal-radiative heat transfer than smaller voids. For large block (and void) sizes, 
thermal-radiative heat transfer will mitigate the influence of the bottlenecking effect, which will 
make the high-Kth case applicable. For small block (and void) sizes, the low-Kth case will be 
applicable. Neither the high-Kth case nor low-Kth case is more or less likely to be the appropriate 
value to be applied for effective thermal conductivity of the host-rock rubble. As a result of this 
argument, each alternative, the high- and low-Kth cases, can be assigned the same probability (of 
50 percent). 
Table 6.2-2. Hydrologic Property Values for the Intact Tptpll (tsw35) Host-Rock Unit and for the 
Host-Rock Rubble Derived from the Tptpll (tsw35) Unit. 
Intact Host-Rock Host-Rock Rubble Property Basis for Rubble Property 
Property Property Value Value Value 
Matrix porosity 0.131 0.1065 Intact Value x 1/(1 + BF) 
Fracture porosity 9.6 x 10-3 0.187 1  1/(1 + BF) 
Matrix permeability 4.48 x 10-18 m2 3.6393 x 10-18 m2 Intact Value x 1/(1 + BF) 
Fracture permeability 9.10 x 10-13 m2 1.0 x 10-10 m2 Assumption 2 of Section 5 of 
BSC 2004 [DIRS 169131] 
Fracture van Genuchten 
alpha 
1.02 x 10-4 Pa-1 0.01Pa-1 Assumption 1 of Section 5 of 
BSC 2004 [DIRS 169131] 
NOTES: Intact host-rock property values for the Tptpll (tsw35) unit are obtained from Table IV-4 and IV-5 in 
Appendix IV. 
The only property values listed are those for which the intact and rubble values differ. All other property 
values for the intact host rock and host-rock rubble are the same. 
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Table 6.2-3. Thermal Property Values for the Intact Tptpll (tsw35) Host-Rock Unit and for the 
Host-Rock Rubble Derived from the Tptpll (tsw35) Unit 
Property 
Intact Host-Rock 
Property Value 
Host-Rock Rubble Property 
Value 
Basis for Rubble Property 
Value 
Bulk density 1980 kg/ma 1850.0 kg/ma Assumption, Section 5.8.1 
Bulk density of matrix Not used or 1831.5 kg/ma 99 percent of bulk rubble value 
continuum determined 
Bulk density of fracture Not used or 18.5 kg/ma 1 percent of bulk rubble value 
continuum determined 
Grain density of matrix 
continuum 
2258.11 kg/ma 2049.8 kg/ma Bulk matrix density/(1  fm), 
where fm = 0.1065 (Table 6.2-2) 
Grain density of fracture 
continuum 
21.89 kg/ma 22.76 kg/ma Bulk fracture density/(1  ff), 
where ff = 0.187 (Table6.2-2) 
Bulk dry thermal 1.28 W/m-K 1.0 W/m-K (High-Kth case)b Intact Value x 1/(1 + BF) 
conductivity 0.5 W/m-K (Low-Kth case) (High-Kth rubble value)/2 
Bulk wet thermal 1.89 W/m-K 1.515 W/m-K (High-Kth case)a Intact Value x 1/(1 + BF) 
conductivity 0.7575 W/m-K (Low-Kth case) (High-Kth rubble value)/2 
Dry thermal conductivity 
of matrix continuum 
1.268 W/m-K 0.99 W/m-K (High-Kth case) 
0.495 W/m-K (Low-Kth case) 
99 percent of bulk rubble value 
Dry thermal conductivity 
of fracture continuum 
1.23 x 10-2 W/m-K 0.01 W/m-K (High-Kth case) 
0.005 W/m-K (Low-Kth case) 
1 percent of bulk rubble value 
Wet thermal conductivity 
of matrix continuum 
1.872 W/m-K 1.5 W/m-K (High-Kth case) 
0.75 W/m-K (Low-Kth case) 
99 percent of bulk rubble value 
Wet thermal conductivity 
of fracture continuum 
1.81 x 10-2 W/m-K 0.015 W/m-K (High-Kth case) 
0.0075 W/m-K (Low-Kth case) 
1 percent of bulk rubble value 
Bulk density 1980.0 kg/ma 1608.0 kg/ma Intact Value x 1/(1 + BF) 
(sensitivity case: Figure 6.3-58) 
Bulk density of matrix 
continuum 
Not used or 
determined 
1591.9 kg/ma 
(sensitivity case: Figure 6.3-58) 
99 percent of bulk rubble value 
Bulk density of fracture 
continuum 
Not used or 
determined 
16.1 kg/ma 
(sensitivity case: Figure 6.3-58) 
1 percent of bulk rubble value 
Grain density of matrix 
continuum 
2258.11 kg/ma 1781.6 kg/ma 
(sensitivity case: Figure 6.3-58) 
Bulk matrix density/(1  fm), 
where fm = 0.1065 (Table 6.2-2) 
Grain density of fracture 
continuum 
21.89 kg/ma 19.8 kg/ma 
(sensitivity case: Figure 6.3-58) 
Bulk fracture density/(1  ff), 
where ff = 0.187 (Table 6.2-2) 
a 
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. 
b This value is rounded down slightly. 
NOTE: Intact host-rock property values are obtained from Table IV-3b in Appendix IV. The only property values 
listed are those for which the intact and rubble values differ. All other property values for the intact host 
rock and host-rock rubble are the same. Note that fm and ff are matrix-continuum and fracture-continuum 
porosity, respectively. 
Appendix XI corroborates estimates of the effective dry bulk thermal conductivity of the 
host-rock rubble in the collapsed drift on the basis of the Kunii and Smith relationship (Kunii and 
Smith 1960 [DIRS 153166], Equation 8). On the basis of that assessment, a mean value of 0.81 
W/mC is determined for the dry bulk thermal conductivity, with a range of 0.57 to 1.05 W/mC. 
The low end of this range (0.57 W/mC) is very close to the dry bulk thermal conductivity value 
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of 0.5 W/moC used in low-Kth case. The high end of this range (1.05 W/moC) is very close to 
the dry bulk thermal conductivity value of 1.0 W/moC used in the high-Kth case. 
The fracture-continuum porosity of the rubble does not include the small contribution of the 
fracture porosity, which is 9.6 x 10-3 for the Tptpll (tsw35) unit (Table IV-4 of Appendix IV), 
that was present in the intact rock (prior to its collapse into the drift). The fracture-continuum 
permeability and van Genuchten alpha parameter are taken from Section 6.4.3.4 of Abstraction 
2
of Drift Seepage (BSC 2004 [DIRS 169131]). The fracture-continuum permeability is 10-10 m(about two orders of magnitude larger than that of the intact Tptpll host rock). The 
fracture-continuum van Genuchten alpha is 0.01 Pa-1. The bulk density and bulk thermal 
conductivity of the host-rock rubble are partitioned between the fracture and matrix continuum in 
the exactly same fashion, and for the same reasons, as is done for the crushed-tuff invert material 
(see Appendix IV). Thus, 99 percent of the bulk density and bulk thermal conductivity are 
partitioned to the matrix continuum and 1 percent is partitioned to the fracture continuum. This 
partitioning is done because the majority of the thermal mass in the rubble resides in the matrix 
continuum. 
6.2.11 DDT Submodels for the Low-Probability-Seismic Collapsed-Drift Scenario 
For the collapsed-drift scenario, two changes need to be implemented in the DDT submodels. 
First, the geometry of the drift is changed to account for the host-rock rubble that fills the drift 
from the outer surface of the drip shield to the intact host-rock. Second, thermal properties are 
required for the host-rock rubble. The implementation of these changes is described in the 
following sections. The boundary conditions and heat-generation rates are the same as those 
used in the corresponding MSTHM calculations for the intact drift (i.e., nominal) case. Two 
thermal conductivity Kth cases are considered: (1) high-Kth host-rock rubble and (2) low-Kth 
host-rock rubble. 
6.2.11.1 DDT Submodel Location 
The DDT submodel location is the P2WR5C10 LDTHSDT submodel location (Figures 6.2-3 
and 6.3-1). Two sets of LDTH submodel simulations (for modeled AMLs of 14, 27, 55, and 66 
MTU/acre) are conducted for two different host-rock rubble thermal conductivity cases. 
6.2.11.2 DDT Submodel Mesh 
The low-probability-seismic scenario causes collapse of the drift opening, which is represented 
by a circular profile with a diameter of 11 m (see Section 6.2.10.2). The resulting host-rock 
rubble completely fills the modified drift opening, from the outer surface of the drip shield out to 
the modified drift wall, which now has a diameter of 11 m. The cross-sectional (lateral) 
geometry of the drift for the collapsed drift is represented in the DDT submodel mesh as is 
shown in Figure 6.2-12. Note that the cross-sectional geometries of the drip shield, waste 
package, and invert remain the same. 
6.2.11.3 DDT Submodel Host-Rock Rubble Thermal Properties 
The thermal properties of the host-rock rubble (Table 6.2-4) are derived from those of the Tptpll 
(tsw35) unit, which is the host-rock unit at the P2WR5C10 LDTHSDT submodel location 
(Figures 6.2-3 and 6.3-1). Just as is done for the LDTH submodels, the bulk grain density and 
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Multiscale Thermohydrologic Model 
bulk thermal conductivity are reduced to account for the decreased density of the host-rock 
rubble by multiplying the intact-host-rock values by 1/(1 + BF). The DDT submodels use the 
same bulk grain density as is used in the LDTH submodels for the high-Kth and low-Kth host-rock 
rubble cases. For thermal conductivity, the DDT submodels use the bulk dry thermal 
conductivity that is used in the LDTH submodels for the high-Kth and low-Kth host-rock rubble 
cases, respectively. The dry value of bulk thermal conductivity is used because the DDT 
submodels are primarily used to predict longitudinal variability in temperature along the axis of 
the drift. The longitudinal variability is greatest when peak temperatures occur, which is when 
the majority of the rubble is dry as a result of boiling. Much of the rubble remains relatively dry 
throughout the majority of the simulation period of 20,050 years; therefore, the dry value of 
thermal conductivity for the rubble is a reasonable choice. 
Table 6.2-4. Thermal Property Values for the Intact Tptpll (tsw35) Host-Rock Unit and for the 
Host-Rock Rubble Derived from the Tptpll (tsw35) Unit. 
Property Intact Host-Rock Host-Rock Rubble Property Basis for Rubble Property 
Property Value Value Value 
Bulk density 1980 kg/m3 1608 kg/m3 Intact Value x 1/(1 + BF) 
Bulk grain density 2280 kg/m3 1850 kg/m3 Bulk density/(1  fm), where 
fm = 0.131a 
Bulk dry thermal 1.28 W/m-K 1.0 W/m-K (High-Kth case) Intact Value x 1/(1 + BF) 
conductivity 0.5 W/m-K (Low-Kth case) (High-Kth rubble value)/2 
a 
A porosity value of 0.131 only affects the relationship between bulk density and bulk grain density applied to the 
DDT submodel. It has no other influence on the DDT submodel. 
NOTE: Intact host-rock property values are obtained from Table IV-3b in Appendix IV. The only property values 
listed are those for which the intact and rubble values differ. All other property values for the intact host rock 
and host-rock rubble are the same. 
6.3 MSTHM RESULTS 
6.3.1 TSPA-LA Base Case 
This section discusses the MSTHM calculations that were conducted for the TSPA-LA base 
case. As was done for the Total System Performance Assessment for the Site Recommendation 
(called the TSPA-SR), the base case consists of three infiltration-flux cases: lower-bound, mean, 
and upper-bound infiltration-flux cases for three climate states: present-day, monsoonal, and 
glacial-transition. Past MSTHM calculations directly used the infiltration maps for these three 
cases with the underlying assumption being that there is no lateral attenuation of infiltration in 
the PTn unit (or in any other unit above the repository); thus, percolation above the repository 
occurs strictly as one-dimensional vertical downward flow. For the TSPA-LA base case, the 
upper-boundary liquid-phase flux in the MSTHM corresponds to the distribution of percolation 
flux just below the base of the PTn unit; these data (Table 4.1-1) are generated for the three 
climate states: present-day, monsoonal, and glacial-transition. Thus, the TSPA-LA base-case 
MSTHM accounts for the influence of lateral diversion in the PTn as represented in the 
three-dimensional UZ flow model. 
Previous MSTHM calculations (such as those in support of the TSPA-SR) used different 
hydrologic property sets for each of the infiltration-flux cases; thus, lower-bound, mean, and 
upper-bound one-dimensional drift-scale hydrologic property sets were applied to their 
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respective infiltration-flux cases. For this study it was found that only one hydrologic property 
set (called the modified-mean infiltration-flux property set) is needed for conducting MSTHM 
calculations for the three infiltration-flux cases. Abstraction of Drift Seepage (BSC 2004 [DIRS 
169131], Section 6.6.3) addresses the van Genuchten fracture alpha and permeability 
distributions for the Tptpul (tsw33) and Tptpln (tsw36) units. It is noted by this reference that 
the Tptpul (tsw33) unit is hydrogeologically similar to the Tptpll (tsw35) unit; furthermore, it is 
stated that the two units with lithophysal cavities in the rock (the Tptpul and Tptpll units) should 
have similar hydrogeological characteristics. The modified-mean infiltration-flux property set is 
the same as the mean infiltration-flux property set (DTN: LB0208UZDSCPMI.002 [DIRS 
161243]) with the one modification being that the van Genuchten fracture alpha in the Tptpul 
(tsw33) is set to be the same (1.021  10-4 Pa-1) as that in the Tptpll (tsw35) unit (see Table 
IV-4, Appendix IV). This is consistent with the observation in Abstraction of Drift Seepage 
(BSC 2004 [DIRS 169131], Section 6.6.3) that the Tptpul and Tptll are hydrologically similar. 
As discussed below, this one modification also produces a consistent contrast in capillary 
pressure between the matrix and fracture continuum for all four host-rock units. 
For this study, it was found that the application of the modified-mean infiltration-flux property 
set to lower-bound, mean, and upper-bound infiltration-flux cases produces uniform calculated 
host-rock liquid-phase saturation for the three infiltration-flux cases. It was also found that 
host-rock liquid-phase saturation consistently increases (slightly) with increasing percolation 
flux. The purpose for conducting lower-bound, mean, and upper-bound infiltration-flux cases 
with the MSTHM is to address the influence of percolation-flux uncertainty on 
thermal-hydrologic conditions within emplacement drifts and in the adjoining host rock. In 
conducting a sensitivity study to a particular parameter (in this case, percolation flux), it is 
preferred to vary only one parameter at a time. Table 6.3-1 lists the initial (ambient) liquid-phase 
saturation in the host rock (immediately above the crown of the emplacement drift) for 
lower-bound, mean, and upper-bound infiltration-flux cases when the modified-mean drift-scale 
hydrologic property set is applied to the MSTHM. Table 6.3-1 shows that the use of the 
modified-mean infiltration-flux property set results in similar initial liquid-phase saturation at a 
given location for lower-bound, mean, and upper-bound infiltration-flux cases. 
Table 6.3-2 lists the initial (ambient) capillary pressure in the fracture and matrix continuum of 
the host rock for the same locations given in Table 6.3-1. The mean infiltration-flux property set 
produces very small values of capillary pressures in the fracture continuum for locations where 
the host rock is the Tptpul (tsw33) unit; these small values of fracture capillary pressure are 
much smaller than they are for regions of the repository where the host rock is not the Tptpul 
(tsw33) unit (i.e., where the local host-rock unit is either Tptpmn (tsw34), Tptpll (tsw35), or 
Tptpln (tsw36)). Moreover, the mean infiltration-flux property set produces a large (order of 
magnitude) contrast in capillary pressure between the matrix and fracture continuum in the 
Tptpul (tsw33) unit, whereas the contrast in capillary pressure is much smaller for the other three 
host-rock units: Tptpmn, Tptpll, and Tptpln. The modified-mean infiltration-flux property set 
produces fracture capillary pressures in the Tptpul unit that are consistent with those in the rest 
of the repository (i.e., in regions where the host rock is either Tptpmn, Tptpll, or Tptpln). 
Moreover, for all four host-rock units, the modified-mean infiltration-flux property set produces 
a consistent contrast in capillary pressure between the matrix and fracture continuum, which is 
generally on the order of a factor of two throughout most of the repository area, with the only 
exception being in the Tptpln unit where the contrast is larger (about a factor of six). 
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Table 6.3-3 and Figure 6.3-1 show the distribution of host-rock units over the repository area. 
The majority of the repository area (81.1 percent) is in the two units (Tptpll and Tptpul) with 
lithophysal cavities. Most of the remainder of the repository area (where waste is to be 
emplaced) is in the nonlithophysal units (Tptpmn and Tptpln) with a small percentage (1.6 
percent) being in fault zones. These areas are based on Development of Numerical Grids for UZ 
Flow and Transport Modeling (BSC 2004 [DIRS 169855]). 
Table 6.3-1. Initial Liquid-Phase Saturation in the Host Rock at Several Locations in the Repository for 
Three Infiltration-Flux Cases 
Nevada State Initial Liquid-Phase Saturation 
LDTHSDT 
submodel 
location Host-Rock unit 
Coordinates in the Host Rock (%) 
Easting 
(m) 
Northing 
(m) 
Lower-Bound 
Infiltration-
Flux Case 
Mean 
Infiltration-
Flux Case 
Upper-Bound 
Infiltration-
Flux Case 
P2ER4C4 Tptpul (tsw33) 172138.9 235625.9 96.4 96.4 96.9 
P2ER5C5 Tptpul (tsw33) 171985.7 235320.6 95.5 95.6 95.8 
P2ER6C6 Tptpul (tsw33) 171623.3 234947.4 95.4 95.5 95.7 
P2ER8C7 Tptpul (tsw33) 171393.1 234361.5 94.0 97.2 97.3 
P2ER8C6 Tptpul (tsw33) 171564.3 234417.2 90.5 95.6 95.7 
P2ER8C5 Tptpul (tsw33) 171735.5 234472.8 93.6 97.4 97.3a 
P2ER7C6 Tptpul (tsw33) 171584.3 234679.2 93.0 96.5 96.3a 
P2ER7C5 Tptpul (tsw33) 171793.5 234747.2 95.1 95.2 95.3 
P2ER6C5 Tptpul (tsw33) 171851.6 235021.5 93.6 95.5 95.6 
P2ER3C4 Tptpmn (tsw34) 172292.1 235931.1 97.5 97.8 98.0 
P2ER2C5 Tptpll (tsw35) 172121.9 236131.4 92.0 92.0 92.1 
P2WR1C8 Tptpll (tsw35) 171647.4 236232.7 94.0 94.0 94.1 
P3R1C11 Tptpll (tsw35) 171038.7 236034.9 94.6 94.6 94.7 
P3R8C13 Tptpln (tsw36) 170080.6 233935.1 98.6 98.7 98.7 
Source: See Table XIII-2. 
a 
The value of percolation flux for the upper-bound infiltration-flux case is less than that for the mean 
infiltration-flux case at this particular location. 
NOTE: The initial (ambient) liquid-phase saturation in the host rock (prior to waste emplacement) is 
obtained by applying the modified-mean infiltration-flux property set to the MSTHM. 
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Table 6.3-2. Initial Capillary Pressure for the Fracture and Matrix Continuum in the Host Rock 
LDTHSDT 
Fracture capillary pressure 
(Pa) 
Matrix capillary pressure 
(Pa) 
Modified-Mean Modified-Mean 
submodel Mean Infiltration-Infiltration-Flux Mean Infiltration-Infiltration-Flux 
location Host-Rock Unit Flux Property Set Property Set Flux Property Set Property set 
P2ER4C4 Tptpul (tsw33) 1.46  103 2.28  104 3.23  104 4.27  104 
P2ER5C5 Tptpul (tsw33) 1.46  103 2.28  104 4.51  104 5.06  104 
P2ER6C6 Tptpul (tsw33) 1.46  103 2.27  104 4.38  104 5.18  104 
P2ER8C7 Tptpul (tsw33) 1.45  103 2.27  104 2.03  104 3.50  104 
P2ER8C6 Tptpul (tsw33) 1.45  103 2.26  104 4.51  104 5.09  104 
P2ER8C5 Tptpul (tsw33) 1.47  103 2.29  104 3.14  104 3.34  104 
P2ER7C6 Tptpul (tsw33) 1.43  103 2.22  104 3.46  104 4.25  104 
P2ER7C5 Tptpul (tsw33) 1.46  103 2.28  104 5.34  104 5.43  104 
P2ER6C5 Tptpul (tsw33) 1.47  103 2.30  104 4.55  104 5.13  104 
P2ER3C4 Tptpmn (tsw34) 2.22  104 2.22  104 2.32  104 2.32  104 
P2ER2C5 Tptpll (tsw35) 2.40  104 2.40  104 5.78  104 5.78  104 
P2WR1C8 Tptpll (tsw35) 2.44  104 2.44  104 4.37  104 4.37  104 
P3R1C11 Tptpll (tsw35) 2.44  104 2.44  104 3.95  104 3.95  104 
P3R8C13 Tptpln (tsw36) 3.32  103 3.32  103 1.94  104 1.94  104 
Source: See Table XIII-2. 
NOTE: The initial (ambient) capillary pressure for the fracture and matrix continuum in the host rock (prior to 
waste emplacement) is obtained by applying the mean and the modified-mean infiltration-flux property
set to the MSTHM. Note that values are listed for the same locations given in Table 6.3-1.
Table 6.3-3. Distribution of the Host-Rock Units as Represented in SMT Submodel for the Emplaced 
Repository Area (Figure 6.3-1) 
GFM2000 
Lithostratigraphic 
Unit 
UZ Model 
Layer Unit 
Length of 
Emplacement 
Drift (m) 
Area 
(km2) 
Percentage of 
Repository Area 
Tptpul tsw33 3,460 0.2803 6.0% 
Tptpmn tsw34 9,260 0.7501 16.1% 
Tptpll tsw35 43,160 3.4960 75.1% 
Tptpln tsw36 660 0.0535 1.2% 
Fault zone tswfl 940 0.0761 1.6% 
Total N/A 57,480 4.6559 100% 
NOTE: The values of emplacement-drift length and area are as they are represented in the SMT 
submodel (Section 6.2.5). In the SMT submodel, the represented lengths of the 
emplacement drifts are based on information from BSC 2003 [DIRS 161727]; the 
distribution of host-rock units (with respect to the UZ model layers) is consistent with the 
grid in DTN: LB03023DKMGRID.001 [DIRS 162354]. 
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Source: See Table XIII-1. 
NOTE: Note that tswfl stands for fault zone. Also shown are the five representative locations that were selected to 
examine thermal-hydrologic conditions in the four primary host-rock units. 
Figure 6.3-1. Distribution of the Four Primary Host-Rock Units Shown for the Repository Layout 
Considered in MSTHM Calculations for the TSPA-LA Base Case 
6.3.1.1 Lower-Bound, Mean, and Upper-Bound Infiltration-Flux Cases 
The repository-wide averaged percolation flux for the three climate states (present-day, 
monsoonal, and glacial-transition) is summarized in Table 6.3-4 for the lower-bound, mean, and 
upper-bound infiltration-flux cases. Table 6.3-5 summarizes the range of percolation flux for the 
present-day climate for the lower-bound, mean, and upper-bound infiltration-flux cases. Figure 
6.3-2 gives the complementary cumulative distribution function for the peak temperature on the 
drift wall and on waste packages; these complementary cumulative distribution functions are for 
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all waste packages over the entire repository area. Table 6.3-6 gives the coolest, median, and 
hottest peak drift-wall and waste package temperatures for the three infiltration-flux cases. The 
spatial extent and duration of dryout of the host rock increase with decreasing percolation flux. 
Because the thermal conductivity of dry rock is less than that of wet rock, peak temperatures 
increase with decreasing percolation flux. The sensitivity of peak temperature to percolation flux 
is strongest at either end of the complementary cumulative distribution function distributions. 
The differences between the mean and lower-bound infiltration-flux cases are greatest for the 
hottest waste package locations. The differences between the mean and upper-bound 
infiltration-flux cases are greatest for the coolest waste package locations. In general, the 
sensitivity of peak temperature to percolation flux is stronger for the hottest waste package 
locations. 
Table 6.3-4. Repository-Wide Averaged Percolation Flux Summarized for Lower-Bound, Mean, and 
Upper-Bound Infiltration-Flux Cases 
Infiltration-Flux Case 
Repository-Wide Averaged Percolation Flux (mm/yr) 
Present-Day 
(0 years < t < 600 years) 
Monsoonal 
(600 years < t < 2,000 years) 
Glacial-Transition 
(2,000 years < t) 
Lower 0.41 4.23 1.95 
Mean 3.77 11.15 17.29 
Upper 10.84 19.48 34.35 
NOTE: These averages are based on averaging the percolation data from DTN: LB0302PTNTSW9I.001 [DIRS 
162277] over the heated repository footprint represented in the SMT submodel, as described in Appendix I. 
Table 6.3-5. Range of Percolation Fluxes for the MSTHM for the Lower-Bound, Mean, and 
Upper-Bound Infiltration-Flux Cases for the Present-Day Climate 
Percolation flux (mm/yr) 
Lower infiltration-flux case Mean infiltration-flux case Upper infiltration-flux case 
Lowest value 2.8  10-5 0.24 1.12 
Mean value 0.41 3.77 10.84 
Highest value 2.20 13.74 36.18 
DTN: LL030808623122.036. 
Table 6.3-6. Peak Drift-Wall and Waste Package Temperatures for Lower-Bound, Mean, and 
Upper-Bound Infiltration-Flux Cases 
Infiltration- 
Peak Drift-Wall Temperature 
(C) 
Peak Waste Package Temperature 
(C) 
Flux Case Coolest Median Hottest Coolest Median Hottest 
Lower 105.7 135.4 154.8 116.3 156.0 182.9 
Mean 105.0 133.0 144.2 115.6 153.3 172.0 
Upper 98.6 131.6 142.5 108.6 152.1 170.8 
NOTE: These values are based on Figure 6.3-2. 
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Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: CCDF is plotted for lower-bound, mean, and upper-bound infiltration-flux cases. 
Figure 6.3-2. Complementary Cumulative Distribution Function (CCDF) for Peak Temperature on the 
Drift Wall and Waste Packages 
Figure 6.3-3, which is the contour map of peak waste package temperature for PWR waste 
packages, illustrates how peak temperatures increase with distance from the repository edges. 
There are two reasons for this relationship. First, the edge-cooling effect, which results from 
lateral heat loss at the repository edges, is strongest for locations close to the edge of the 
repository. Second, the direction of the ventilation-air flow is from the ventilation inlets located 
at the repository edges in towards the ventilation outlets, which are generally located close to the 
center of the repository. Table III-1 of Appendix III, which lists the net available 
heat-generation fraction as a function of time and distance from the ventilation inlet 
(DTN: MO0304MWDALACV.000 [DIRS 164551]), shows that heat-removal efficiency 
(resulting from ventilation of emplacement drifts) decreases with distance from the ventilation 
inlet. Thus, locations closer to the repository edge receive more of the ventilation cooling effect 
than locations closer to the repository center. One slight variation of this trend is in Panel 5 
where the ventilation inlet is on the eastern edge and the ventilation outlet is on the western edge. 
Figure 6.3-3 shows that peak temperatures on the eastern side of Panel 5 (where the heat-removal 
efficiency is greatest) are slightly lower than on the western side (where the heat-removal 
efficiency is least). 
ANL-EBS-MD-000049 REV 02 6-59 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: This contour map is plotted over the repository area for the mean infiltration-flux case. The pwr1-2 
(21-PWR AP CSNF) waste package is the hottest package in the sequence (Table 6.3-13). 
Figure 6.3-3. Contour Map of Peak Waste Package Temperature for the pwr1-2 Waste Package 
ANL-EBS-MD-000049 REV 02 6-60 October 2004 

Multiscale Thermohydrologic Model 
Figure 6.3-4a and Table 6.3-7 give the complementary cumulative distribution function for the 
time when boiling at the drift wall ceases for lower-bound, mean, and upper-bound 
infiltration-flux cases; these complementary cumulative distribution functions are for all waste 
package locations throughout the repository area. Note that at the repository horizon, which 
ranges in elevation ranging from about 1038 to 1092 m, the boiling temperature is approximately 
96oC. The boiling-period duration is a useful thermohydrologic parameter because seepage into 
the drift is predicted not to occur during this period in Section 6.3.2 of Abstraction of Drift 
Seepage (BSC 2004 [DIRS 169131]). As was the case for peak temperatures, the boiling-period 
duration increases with decreasing percolation flux. Figure 6.3-5, which is a contour map of the 
time when boiling at the drift wall ceases for a PWR CSNF waste package for the mean 
infiltration-flux case, clearly shows that the boiling-period duration increases strongly with 
distance from the repository edges. The sensitivity of boiling-period duration to percolation flux 
is greatest for those locations with the longest boiling-period duration, which correspond to 
locations furthest away from the repository edges where differences in the spatial (and temporal) 
extent of rock dryout (resulting from differences in percolation flux) have more time to develop. 
There is a strong relationship between boiling-period duration and the spatial (and temporal) 
extent of rock dryout. Areas with low percolation flux will have a greater spatial extent of 
dryout, increasing the volume of rock in which the dry (low) value of thermal conductivity 
pertains, which enhances the temperature rise around the drifts. The enhanced temperature rise 
around the drift has the effect of extending the duration of boiling. Areas with high percolation 
flux will have a smaller spatial (and temporal) extent of rock dryout, decreasing the volume of 
rock in which the dry (low) value of thermal conductivity pertains, which reduces the 
temperature rise around the drifts. This reduced temperature rise around the drifts has the effect 
of shortening the duration of boiling. 
Figure 6.3-4b and Table 6.3-8 give the complementary cumulative distribution function for the 
maximum lateral extent of the boiling-point isotherm for lower-bound, mean, and upper-bound 
infiltration-flux cases. Note that the lateral extent of the boiling-point isotherm approximately 
corresponds to the lateral extent of the dryout zone. As was the case for the peak temperatures 
and boiling-period duration, the maximum lateral extent of boiling increases with decreasing 
percolation flux. Figure 6.3-6 is a contour map of the maximum lateral extent of boiling (and 
dryout) for a PWR CSNF waste package. It is apparent that the maximum lateral extent of 
boiling increases with distance from the repository edges. Areas with low percolation flux will 
have a greater spatial extent of dryout, increasing the volume of rock in which the dry (low) 
value of thermal conductivity pertains, which enhances the temperature rise around the drifts. 
This enhanced temperature rise has the effect of increasing the volume of rock dryout around the 
drifts. Areas with high percolation flux will have a smaller spatial (and temporal) extent of rock 
dryout, decreasing the volume of rock to which the dry (low) value of thermal conductivity 
pertains, which reduces the temperature rise around the drifts. This reduced temperature rise 
around the drifts has the effect of limiting the volume of rock dryout around the drifts. 
It is important to note that the lateral extent of boiling is always much smaller than the half 
spacing between emplacement drifts. Therefore, the majority of the host rock between 
emplacement drifts always remains below the boiling point, thereby enabling condensate and 
percolation flux to continuously drain between emplacement drifts. 
ANL-EBS-MD-000049 REV 02 6-61 October 2004 

Multiscale Thermohydrologic Model 
Table 6.3-7. Time When Boiling Ceases at the Drift Wall Summarized for Lower-Bound, Mean, and 
Upper-Bound Infiltration-Flux Cases 
Time when boiling at the drift wall ceases 
Infiltration-
(years) 
10th 30th 70th 90th 
flux case Shortest Percentile Percentile Median Percentile Percentile Longest 
Lower 130.2 349.9 630.9 859.6 1,122.5 1,453.3 1,734.6 
Mean 127.2 297.5 535.8 721.0 870.6 1,006.5 1,356.0 
Upper 97.7 267.7 471.6 643.7 768.6 887.2 1,162.9 
NOTE: These values are based on data plotted in Figure 6.3-4a. 
Table 6.3-8. Maximum Lateral Extent of the Boiling-Point Isotherm (96C) Summarized for Lower-
Bound, Mean, and Upper-Bound Infiltration-Flux Cases 
Infiltration-
Maximum Lateral Extent of Boiling (T > 96C) 
(m) 
10th 30th 70th 90th 
flux case Least Percentile Percentile Median Percentile Percentile Greatest 
Lower 5.6 7.1 7.9 8.4 9.4 12.3 17.8 
Mean 5.3 6.7 7.5 7.9 8.2 8.7 9.9 
Upper 5.1 6.5 7.3 7.7 7.9 8.1 9.0 
NOTE: These values are based on data plotted in Figure 6.3-4b. The maximum lateral extent of the 
boiling-point isotherm, which is measured from the center of the emplacement drift, approximately 
corresponds to the maximum lateral extent of dryout. 
ANL-EBS-MD-000049 REV 02 6-62 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: CCDFs are plotted for the lower-bound, mean, and upper-bound infiltration-flux cases. The maximum 
lateral extent of the boiling-point isotherm, which is measured from the center of the emplacement drift, 
approximately corresponds to the maximum lateral extent of the dryout zone. 
Figure 6.3-4. Complementary Cumulative Distribution Functions (CCDFs) for (a) the Time When Boiling 
at the Drift Wall Ceases and (b) the Maximum Lateral Extent of the Boiling-Point Isotherm 
(96C) 
ANL-EBS-MD-000049 REV 02 6-63 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: This contour map is plotted over the repository area for the mean infiltration-flux case. The pwr1-2 
(21-PWR AP CSNF) waste package is the hottest package in the sequence (Figure 6.2-2). 
Figure 6.3-5. Contour Map of the Time When Boiling at the Drift Wall Ceases for the pwr1-2 Waste 
Package 
ANL-EBS-MD-000049 REV 02 6-64 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE This contour map is plotted over the repository area for the mean infiltration-flux case. The pwr1-2 
(21-PWR AP CSNF) waste package is the hottest package in the sequence (Table 6.3-13). The maximum 
lateral extent of the boiling-point isotherm, which is measured from the center of the emplacement drift, 
approximately corresponds to the maximum lateral extent of dryout. 
Figure 6.3-6. Contour Map of the Maximum Lateral Extent of the Boiling-Point Isotherm (96C) from the 
Drift Centerline for the pwr1-2 Waste Package 
ANL-EBS-MD-000049 REV 02 6-65 October 2004 

Multiscale Thermohydrologic Model 
For the purpose of examining the details of thermal-hydrologic behavior in emplacement drifts, 
five locations were chosen that cover all four of the host-rock units (Tables 6.3-9, 6.3-10 and 
Figure 6.3-1). Four of these locations (P2ER8C6, P2WR8C8, P2WR5C10, and P3R8C13) were 
chosen because their respective values of percolation flux are close to the repository-wide 
averages (Table 6.3-4). The fifth location (P3R7C12) was chosen because it has close to the 
longest boiling-period duration over the entire repository area; note that this location is in a 
region of low percolation flux, which is a major contributing factor to its very long 
boiling-period duration. Time histories of drift-wall temperature and liquid-phase saturation, 
waste package temperature and relative humidity, and invert liquid-phase saturation are plotted 
(Figures 6.3-7 through 6.3-11) for these five locations (Figure 6.3-1). Tables 6.3-9 and 6.3-10 
summarize the relationship between percolation flux and infiltration-flux case for the five 
locations and three climate states. Using Tables 6.3-9 and 6.3-10 as a guide, the influence of 
percolation flux on peak temperatures is summarized in Table 6.3-11 for the five locations. The 
influence of percolation flux on the duration of boiling is summarized in Table 6.3-12, which 
gives the time when boiling at the drift wall ceases. 
Table 6.3-9. Percolation Flux for Mean Infiltration-Flux Case for Five Locations Used to Examine 
Thermal-Hydrologic Conditions in the Repository 
Percolation flux for the mean infiltration-
LDTHSDT Nevada State Coordinates flux case (mm/yr) 
submodel Glacial-
location Host-rock unit Easting (m) Northing (m) Present-day Monsoonal transition 
P2ER8C6 Tptpul (tsw33) 171564.3 234417.3 5.41 11.70 23.03 
P2WR8C8 Tptpmn (tsw34) 171240.9 234312.1 4.47 10.45 15.65 
P2WR5C10 Tptpll (tsw35) 170730.3 234912.7 4.71 14.60 22.07 
P3R7C12 Tptpll (tsw35) 170347.9 234277.5 0.86 3.43 6.32 
P3R8C13 Tptpln (tsw36) 170080.6 233935.1 7.07 21.95 31.66 
NOTE: See Figure 6.3-1 for locations. The percolation flux is obtained from DTN: LB0302PTNTSW9I.001 
[DIRS 162277], as discussed in Appendix I of this report. 
Table 6.3-10. Percolation Flux for the Lower and Upper Infiltration-Flux Cases for Five Locations Used 
to Examine Thermal-Hydrologic Conditions in the Repository 
LDTHSDT 
Percolation Flux for the Lower-Bound 
Infiltration-Flux Case (mm/yr) 
Percolation Flux for the Upper-Bound 
Infiltration-Flux Case (mm/yr) 
submodel 
location Present-day Monsoonal 
Glacial-
transition Present-day Monsoonal 
Glacial-
transition 
P2ER8C6 6.331  10-2 3.57 1.79 7.22 14.11 34.53 
P2WR8C8 2.621  10-3 3.44 1.31 7.31 12.51 22.14 
P2WR5C10 2.261  10-3 5.58 2.02 15.22 26.12 43.60 
P3R7C12 1.081  10-4 0.91 0.12 6.76 12.82 24.28 
P3R8C13 0.36 6.66 3.69 16.57 33.64 54.99 
NOTE See Figure 6.3-1 for locations. The percolation flux is obtained from DTN: LB0302PTNTSW9I.001 
[DIRS 162277], as discussed in Appendix I of this report. 
ANL-EBS-MD-000049 REV 02 6-66 October 2004 

Multiscale Thermohydrologic Model 
Table 6.3-11. Range of Peak Temperatures over the Three Infiltration-Flux Cases for the pwr1-2 Waste 
Package for Five Locations in the Repository 
LDTHSDT 
submodel 
location 
Host-rock 
unit 
Peak Drift-Wall Temperature 
(C) 
Peak Waste Package Temperature 
(C) 
Lower Mean Upper Range Lower Mean Upper Range 
P2ER8C6 Tptpul 138.2 135.5 135.2 3.0 165.8 163.2 163.5 2.3 
(tsw33) 
P2WR8C8 Tptpmn 127.4 123.0 122.3 5.1 154.8 150.6 150.8 4.0 
(tsw34) 
P2WR5C10 Tptpll 149.3 141.5 139.6 9.7 177.8 169.4 168.2 9.6 
(tsw35) 
P3R7C12 Tptpll 148.9 140.0 138.7 10.2 176.6 167.3 166.5 10.1 
(tsw35) 
P3R8C13 Tptpln 121.4 120.5 118.8 2.6 149.2 148.2 147.4 1.8 
(tsw36) 
NOTE: See Figure 6.3-1 for locations. These values are based on data plotted in Figures 6.3-7 through 6.3-11. 
Table 6.3-12. Range of Time When Boiling at the Drift Wall Ceases over the Three Infiltration-Flux Cases 
for the pwr1-2 Waste Package for Five Locations in the Repository 
LDTHSDT 
submodel 
Host-rock 
unit 
Time When Boiling at the Drift Wall Ceases for Three Infiltration-flux cases 
(years) 
location Lower Mean Upper Range Rangea 
P2ER8C6 Tptpul 
(tsw33) 
425.3 365.6 359.8 65.5 16.7% 
P2WR8C8 Tptpmn 
(tsw34) 
298.8 221.0 213.1 85.7 33.5% 
P2WR5C10 Tptpll (tsw35) 1,230.7 686.1 540.4 690.3 78.0% 
P3R7C12 Tptpll (tsw35) 1,592.3 1,200.1 1,030.9 561.4 42.8% 
P3R8C13 Tptpln 
(tsw36) 
242.3 218.8 199.2 43.1 19.5% 
a 
The range (%) is the range (years) divided by the average time when drift-wall boiling ceases [(shortest +
longest)/2]. 
NOTE: See Figure 6.3-1 for locations. These values are based on data plotted in Figures 6.3-7 through 6.3-11. 
ANL-EBS-MD-000049 REV 02 6-67 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-7. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Lower-Bound, 
Mean, and Upper-Bound Infiltration-Flux Cases at the P2ER8C6 Location in the Tptpul 
(tsw33) Unit 
ANL-EBS-MD-000049 REV 02 6-68 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-8. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Lower-Bound, 
Mean, and Upper-Bound Infiltration-Flux Cases at the P2WR8C8 Location in the Tptpmn 
(tsw34) Unit 
ANL-EBS-MD-000049 REV 02 6-69 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-9. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Lower-Bound, 
Mean, and Upper-Bound Infiltration-Flux Cases at the P2WR5C10 Location in the Tptpll 
(tsw35) Unit 
ANL-EBS-MD-000049 REV 02 6-70 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-10. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Lower-Bound, 
Mean, and Upper-Bound Infiltration-Flux Cases at the P3R7C12 Location in the Tptpll 
(tsw35) Unit 
ANL-EBS-MD-000049 REV 02 6-71 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-11. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Lower-Bound, 
Mean, and Upper-Bound Infiltration-Flux Cases at the P3R8C13 Location in the Tptpln 
(tsw36) Unit 
ANL-EBS-MD-000049 REV 02 6-72 October 2004 

Multiscale Thermohydrologic Model 
The influence of percolation flux on peak temperature is about the same for the waste package as 
it is for the drift wall (Table 6.3-11). The range of peak temperatures (from lower-bound to 
upper-bound infiltration-flux case) is slightly less for the waste package than it is for the drift 
wall. The reason for this relationship is that the effectiveness of thermal radiation increases 
slightly with temperature; consequently, the difference in peak temperature between the waste 
package and drift wall decreases slightly with increasing peak drift-wall temperature. Because 
the thermal conductivity of the rock is less for the lithophysal units (Tptpul and Tptpll) than it is 
for the nonlithophysal units (Tptpmn and Tptpln), peak temperatures are greater in the 
lithophysal units than in the nonlithophysal units. 
The influence of percolation flux on the duration of boiling at the drift wall is greater for the 
locations (P2WR5C10 and P3R7C12) further from the repository edges than for those closer to 
the repository edges (P2ER8C6, P2WR8C8, and P3R8C13). Because location P2WR8C8 
(located on the eastern edge of Panel 2W) receives some heat from the southern portion of Panel 
2E, its boiling duration is somewhat greater than it is for the other two edge locations 
(P2ER8C6 and P3R8C13). Locations away from the repository edges have longer boiling 
durations that allow more time for the differences in rock dryout between lower and higher 
percolation fluxes to develop. There is a strong relationship between boiling-period duration and 
the spatial (and temporal) extent of rock dryout. Areas with low percolation flux will have a 
greater spatial extent of dryout, increasing the volume of rock in which the dry (low) value of 
thermal conductivity pertains, which enhances the temperature rise around the drifts. The 
enhanced temperature rise around the drift has the effect of extending the duration of boiling. 
Areas with high percolation flux will have a smaller spatial (and temporal) extent of rock dryout, 
decreasing the volume of rock in which the dry (low) value of thermal conductivity pertains, 
which reduces the temperature rise around the drifts. This reduced temperature rise around the 
drifts has the effect of shortening the duration of boiling. 
The influence of percolation flux on dryout/rewetting is illustrated by the drift-wall and invert 
liquid-phase saturation histories (Figures 6.3-7c, 6.3-7e, 6.3-8c, 6.3-8e, 6.3-9c, 6.3-9e, 6.3-10c, 
6.3-10e, 6.3-11c, and 6.3-11e). Locations P2ER8C6 and P2WR8C8 have small differences in 
dryout/rewetting between the upper-bound and mean infiltration-flux cases (Figures 6.3-7c, 
6.3-7e, 6.3-8c, and 6.3-8e), while having larger differences between the lower-bound and mean 
infiltration-flux cases. Location P2WR5C10 has moderate differences in dryout/rewetting 
between the upper-bound and mean infiltration-flux cases (Figures 6.3-9c and 6.3-9e), while 
having larger differences between the lower-bound and mean infiltration-flux cases. Tables 
6.3-9 and 6.3-10 show that location P2WR5C10 has larger differences in percolation flux 
between the lower-bound, mean, and upper-bound infiltration cases than do locations P2ER8C6 
and P2WR8C8; consequently, location P2WR5C10 shows a greater sensitivity to the 
infiltration-flux case. Tables 6.3-9 and 6.3-10 show that location P3R7C12 has larger 
differences in percolation flux between the lower-bound, mean, and upper-bound infiltration-flux 
cases than does location P2WR5C10; thus, location P3R7C12 (Figures 6.3-10c and 6.3-10e) has 
larger differences in dryout/rewetting between the upper-bound and mean infiltration-flux cases 
than does location P2WR5C10 (Figures 6.3-9c and 6.3-9e). Location P3R7C12 has substantial 
differences in dryout/rewetting between the lower-bound and mean infiltration-flux cases, with 
the lower-bound infiltration-flux case remaining at low liquid-phase saturation beyond 20,000 
years (Figures 6.3-10c and 6.3-10e). Location P3R8C13 has larger differences in 
dryout/rewetting between the upper-bound and mean infiltration-flux cases (Figures 6.3-11c and 
6.3-11e) and between the lower-bound and mean infiltration-flux cases. 
ANL-EBS-MD-000049 REV 02 6-73 October 2004 

Multiscale Thermohydrologic Model 
The influence of percolation flux on waste package relative humidity histories is similar to its 
influence on dryout/rewetting (Figures 6.3-7d, 6.3-8d, 6.3-9d, 6.3-10d, and 6.3-11d). Locations 
P2ER8C6 and P2WR8C8 have small differences in waste package relative humidity history 
between the upper-bound and mean infiltration-flux cases (Figures 6.3-7d and 6.3-8d), while 
having larger differences between the lower-bound and mean infiltration-flux cases. Location 
P2WR5C10 has moderate differences in waste package relative humidity history between the 
upper-bound and mean infiltration-flux cases (Figure 6.3-9d), while having larger differences 
between the lower-bound and mean infiltration-flux cases. Location P3R7C12 has moderate 
differences in waste package relative humidity history between the upper-bound and mean 
infiltration-flux cases (Figure 6.3-10d), while having substantial differences between the 
lower-bound and mean infiltration-flux cases. Location P3R8C13 has small differences in waste 
package relative humidity history between the upper-bound and mean infiltration-flux case 
(Figure 6.3-11d); moderate differences between the lower-bound and mean infiltration-flux cases 
persist for about 700 years. With the exception of location P3R7C12, differences in waste 
package relative humidity history among the infiltration-flux cases generally diminish within one 
to several thousand years. 
6.3.1.2 Influence of Waste Package-to-Waste Package Heat-Generation Variability 
This section investigates the influence of waste package-to-waste package heat-generation 
variability on thermal-hydrologic conditions in the emplacement drifts. The eight different waste 
packages considered in all of the MSTHM calculations (Figure 6.2-2) are summarized in Table 
6.3-13. Time histories of drift-wall temperature and liquid-phase saturation, waste package 
temperature and relative humidity, and invert liquid-phase saturation are plotted (Figures 6.3-12 
through 6.3-16) for three of these waste packages (dhlw-l1, bwr1-1, and pwr1-2) for the five 
locations discussed in the previous section (see Figure 6.3-1 for locations). Note that these three 
waste packages include the coolest and hottest in the waste package sequence considered. The 
influence of waste package-to-waste package heat-generation variability on peak temperatures is 
summarized in Table 6.3-14 for the five locations. The influence of waste package-to-waste 
package heat-generation variability on the duration of boiling is summarized in Table 6.3-15, 
which gives the time when boiling at the drift wall ceases. 
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Multiscale Thermohydrologic Model 
Table 6.3-13. Summary of Waste Packages Included in the MSTHM Calculations (Figure 6.2-2) 
Waste 
Package 
Name in 
MSTHM Waste Package type 
Length in 
Model (m) 
Initial Heat-
Generation 
Rate (kW) 
Notes 
(based on MSTHM output temperatures 
and heat output) 
pwr1-1 21-PWR AP CSNF 
 21-PWR AP 
2.5825 5.764a Half waste package in model; coolest 
PWR waste package in sequence, but 
average PWR waste package with 
respect to heat output 
dhlw-l1 5 DHLW/DOE SNF-LONG 
5-HLW LONG 
5.217 0.990 Coolest waste package in sequence with 
the lowest heat output 
pwr2-1 21-PWR AP CSNF 
21-PWR AP (HOT) 
5.165 11.800 Average PWR waste package in 
sequence with respect to temperatures, 
but highest heat output in sequence 
bwr1-1 44-BWR CSNF 
44-BWR AP 
5.165 7.377 Hottest BWR waste package in sequence, 
but average BWR waste package with 
respect to heat output 
bwr2-1 44-BWR CSNF 
44-BWR ADJESTED 
5.165 7.100 Oldest BWR waste package in sequence 
dhlw-s1 5 DHLW/DOE SNF-SHORT 
5-HLW SHORT 
3.59 2.983 Hottest DHLW waste package in 
sequence 
pwr1-2 21-PWR AP CSNF 
21-PWR AP 
5.165 11.528 Hottest waste package in sequence, but 
average PWR waste package with respect 
to heat output 
bwr1-2 44-BWR CSNF 
 44-BWR AP 
2.5825 3.689a Half waste package in model; coolest 
BWR waste package in sequence, but 
average BWR waste package with 
respect to heat output 
a 
These values represent the heat-generation rate for a half waste package. 
NOTES: Waste packages included in Figures 6.3-12 through 6.3-16 are shown in bold. Names of waste package 
types as they appear in BSC 2004 [DIRS 167754] are shown in italics. 
Waste package lengths are based on information from BSC 2003 [DIRS 165406], Table 1. Heat 
generation rates are based on information from BSC 2004 [DIRS 167754], Table 12. The heat generation 
rates used in the MSTHM calculations are based on the first 25,000 years of entries in Table 12 of BSC 
2004 [DIRS 167754]. Heat generation values for 20,050 years, which corresponds to the end of the 
MSTHM simulations, are linearly interpolated between the values for 20,000 years and 25,000 years from 
Table 12 of BSC 2004 [DIRS 167754]. 
Table 6.3-14. Range of Peak Temperatures from Variability in Waste Package-to-Waste Package Heat 
Generation for the Mean Infiltration-Flux Case, Summarized for Five Locations in the 
Repository 
LDTHSDT Peak Waste Package 
Submodel Peak Drift-Wall Temperature (C) Temperature (C) 
Location Host-Rock Unit Lowest Highest Range Lowest Highest Range 
P2ER8C6 Tptpul (tsw33) 122.3 135.5 13.2 132.0 163.2 31.2 
P2WR8C8 Tptpmn (tsw34) 109.7 123.0 13.3 118.9 150.6 31.7 
P2WR5C10 Tptpll (tsw35) 126.8 140.8 14.0 136.7 168.8 32.1 
P3R7C12 Tptpll (tsw35) 126.8 140.0 13.2 136.3 167.3 31.0 
P3R8C13 Tptpln (tsw36) 106.6 120.2 13.6 116.1 148.2 32.1 
NOTE: See Figure 6.3-1 for locations. These values are based on data plotted in Figures 6.3-7 through 6.3-16. 
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Table 6.3-15. Range of Time When Boiling at the Drift Wall Ceases (Resulting from Variability in Waste 
Package-to-Waste Package Heat Generation) for the Mean Infiltration-Flux Case, 
Summarized for Five Locations in the Repository 
LDTHSDT 
Submodel Host-Rock Unit 
Time When Boiling at the Drift Wall Ceases 
(years) 
Location Shortest Longest Range Rangea 
P2ER8C6 Tptpul (tsw33) 284.2 364.8 80.6 24.8% 
P2WR8C8 Tptpmn (tsw34) 166.1 242.8 76.7 37.5% 
P2WR5C10 Tptpll (tsw35) 340.7 623.0 282.3 58.6% 
P3R7C12 Tptpll (tsw35) 1,072.3 1,200.1 127.8 11.3% 
P3R8C13 Tptpln (tsw36) 140.4 195.2 54.8 32.7% 
a 
The range (%) is the range (years) divided by the average time when drift-wall 
boiling ceases [(shortest + longest)/2]. 
NOTE: See Figure 6.3-1 for locations. 
The influence of waste package-to-waste package heat-generation variability on peak drift-wall 
temperatures is virtually the same for all five locations (Table 6.3-14); similarly, the influence of 
heat-generation variability on peak waste package temperatures is virtually the same for all five 
locations. The range of peak drift-wall temperatures is less than the range of peak waste package 
temperatures. Thermal radiation in the drift is an efficient heat-transfer mechanism for limiting 
the extent of temperature variability along the axis of the drift. The influence of heat-generation 
variability on boiling duration varies among the five locations (Table 6.3-15). The greatest 
degree of boiling-duration variability is at location P2WR5C10, while location P3R7C12 has the 
least degree of boiling-duration variability. 
The influence of heat-generation variability on dryout/rewetting is illustrated by the drift-wall 
and invert liquid-phase saturation histories (Figures 6.3-12c, 6.3-12e, 6.3-13c, 6.3-13e, 6.3-14c, 
6.3-14e, 6.3-15c, 6.3-15e, 6.3-16c, and 6.3-16e). Dryout/rewetting at locations P2ER8C6, 
P2WR8C8, and P3R8C13 (Figures 6.3-12c 6.3-12e, 6.3-13c, 6.3-13e, 6.3-16c, and 6.3-16e), 
which are close to the repository edges, exhibit more sensitivity to heat-generation variability 
than at locations P2WR5C10 and P3R7C12 (Figures 6.3-14c, 6.3-14e, 6.3-15c, and 6.3-15e), 
which are farther away from the repository edges. Note that location P3R7C12 has by far the 
least degree of dryout/rewetting variability. For all locations, the invert exhibits less 
dryout/rewetting variability than the drift wall. 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. These waste packages bracket the entire range of temperature at this 
location. 
Figure 6.3-12. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for a Range of 
Waste Packages at the P2ER8C6 Location in the Tptpul (tsw33) Unit 
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Source: See Table XIII-1. 
NOTE: WP = waste package. See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. These waste packages bracket the entire 
range of temperature at this location. 
Figure 6.3-13. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for a Range of 
Waste Packages at the P2WR8C8 Location in the Tptpmn (tsw34) Unit 
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Source: See Table XIII-1. 
NOTE: WP = waste package. See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. These waste packages bracket the entire 
range of temperature at this location. 
Figure 6.3-14. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for a Range of 
Waste Packages at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: WP = waste package. See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. These waste packages bracket the entire 
range of temperature at this location. 
Figure 6.3-15. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for a Range of 
Waste Packages at the P3R7C12 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: WP = waste package. See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. These waste packages bracket the entire 
range of temperature at this location. 
Figure 6.3-16. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for a Range of 
Waste Packages at the P3R8C13 Location in the Tptpln (tsw36) Unit 
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The influence of heat-generation variability on waste package relative humidity variability is 
similar to the influence on dryout/rewetting. Because the relative humidity at the drift wall 
depends on the liquid-phase saturation and temperature, the variability of drift-wall relative 
humidity is similar to that of drift-wall liquid-phase saturation. Relative humidity at a given 
waste package depends on two factors. The first is the adjacent drift-wall relative humidity. The 
second factor is the temperature difference between the waste package and adjoining drift-wall 
surface; relative humidity reduction (relative to the adjacent drift wall) depends on this 
temperature difference (Section 6.1.4). Waste packages with higher heat-generation rates result 
in a greater relative humidity reduction, for longer times, than those with lower heat-generation 
rates. The large difference in heat-generation rate between the coolest and hottest waste 
packages results in a large difference in the respective relative humidity histories. 
From a heat-transfer perspective, the drip shield functions like a thermal-radiation shield 
(between the waste package and the drift wall) that causes the waste package to be hotter than it 
would without the presence of the drip shield. The increased temperature difference between the 
waste package and the drift wall reduces the relative humidity on the waste package. For waste 
packages with higher heat-generation rates (i.e., the pwr1-2 waste package in Figure 6.3-16), the 
influence of the thermal-radiation shield on waste package temperature and relative humidity is 
much greater than it is for waste packages with lower heat-generation rates (i.e., the dhlw-l1 
waste package in Figure 6.3-16). This effect is exhibited by comparing the range in drift-wall 
temperatures (Figure 6.3-16a) with the range in waste package temperatures 
(Figure 6.3-16b). The larger range in waste package temperatures, compared to the 
corresponding range in drift-wall temperatures, results in a wide range in waste package relative 
humidities (Figure 6.3-16d). 
6.3.1.3 Alternative MSTHM with Vertically Extended LDTH/SDT Submodels 
The standard MSTHM utilizes LDTH and SDT submodels that have a constant-temperature 
boundary at the water table. To test an alternative approach, MSTHM calculations were 
conducted with vertically extended LDTH and SDT submodels. In these submodels, the lower 
boundary of the LDTH and SDT submodels is set 1,000 m below the water table (as is done in 
the SMT submodel). A series of initialization runs are conducted with the SDT submodel where 
the lower boundary temperature is iteratively adjusted until the temperature at the water table is 
equal to that of the SDT submodel with the lower boundary at the water table. The vertically 
extended SDT submodel is then run with the appropriate heat-generation-rate-versus-time table 
and the temperature at the water table is saved as output. The water-table temperature history is 
then applied as the lower boundary temperature (at the water table) in the corresponding LDTH 
submodel. Applying the SDT submodel water-table temperature history to the lower 
(water-table) boundary of the LDTH submodel is equivalent to having extended the LDTH 
submodel 1,000 m below the water table. This alternative MSTHM approach, with vertically 
extended LDTH and SDT submodels, was applied to four of the five locations (Figure 6.3-1) 
discussed in previous sections. The alternative MSTHM approach is compared to the standard 
MSTHM approach in Figures 6.3-17 through 6.3-20. Overall, the two approaches predict nearly 
the same thermal-hydrologic conditions at the four locations. The small differences between the 
two approaches occur only at later time (e.g., Figures 6.3-19a, 6.3-19b, 6.3-20a, 6.3-20b, 
6.3-20c, and 6.3-20e). At early time, the two approaches predict virtually identical 
thermal-hydrologic conditions. Peak temperatures (Table 6.3-16) are exactly the same for the 
two approaches and the duration of boiling (Table 6.3-17) is nearly the same for the two 
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approaches. Waste package relative humidity is virtually the same for all time (Figures 6.3-17d, 
6.3-18d, 6.3-19d, and 6.3-20d). The alternative MSTHM approach is applied to the low 
percolation-flux cases described in Sections 6.3.2.1 and 6.3.2.3. 
Table 6.3-16. Peak Temperatures in an Alternative MSTHM with Vertically Extended LDTH and SDT 
Submodels, as Compared with Standard MSTHM Results, for the pwr1-2 at Four 
Locations in the Repository 
Peak Drift-Wall Temperature Peak Waste Package Temperature 
LDTHSDT (C) (C) 
Submodel Host-Rock Standard Alternative Standard Alternative 
Location Unit MSTHM MSTHM Difference MSTHM MSTHM Difference 
P2ER8C6 Tptpul 
(tsw33) 
135.5 135.5 0.0 163.2 163.2 0.0 
P2WR8C8 Tptpmn 123.0 123.0 0.0 150.6 150.6 0.0 
(tsw34) 
P2WR5C10 Tptpll 140.8 140.8 0.0 168.8 168.8 0.0 
(tsw35) 
P3R8C13 Tptpln 120.2 120.2 0.0 148.2 148.2 0.0 
(tsw36) 
NOTE: See Figure 6.3-1 for locations. These values are based on data plotted in Figures 6.3-17 through 6.3-
20. 
Table 6.3-17. Time When Boiling at the Drift Wall Ceases in an Alternative MSTHM with Vertically 
Extended LDTH and SDT Submodels, as Compared to the Standard MSTHM Results, for 
the pwr1-2 at Four Locations in the Repository 
LDTHSDT 
Time When Boiling at the Drift Wall Ceases 
(years) 
Submodel Standard Alternative 
Location Host-Rock Unit MSTHM MSTHM Difference Rangea 
P2ER8C6 Tptpul (tsw33) 364.8 364.9 0.1 0.027% 
P2WR8C8 Tptpmn (tsw34) 242.8 242.6 -0.2 0.082% 
P2WR5C10 Tptpll (tsw35) 623.0 622.0 -1.0 0.161% 
P3R8C13 Tptpln (tsw36) 195.2 195.1 -0.1 0.051% 
a 
The range (%) is the range (years) divided by the average time when drift-wall 
boiling ceases [(shortest + longest)/2]. 
NOTE: See Figure 6.3-1 for locations. These values are based on data plotted in 
Figures 6.3-17 through 6.3-20. 
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Source: See Table XIII-1. 
NOTE: SZ = saturated zone. See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. The standard MSTHM calculation is 
compared with an alternative MSTHM calculation in which the LDTH and SDT submodels are vertically 
extended to include the upper 1 km of the saturated zone. 
Figure 6.3-17. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for the pwr1-2 
Waste Package at the P2ER8C6 Location in the Tptpul (tsw33) Unit 
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Source: See Table XIII-1. 
NOTE: SZ = saturated zone. See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. The standard MSTHM calculation is 
compared with an alternative MSTHM calculation in which the LDTH and SDT submodels are vertically 
extended to include the upper 1 km of the saturated zone. 
Figure 6.3-18. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for the pwr1-2 
Waste Package at the P2WR8C8 Location in the Tptpmn (tsw34) Unit 
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Source: See Table XIII-1. 
NOTE: SZ = saturated zone. See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. The standard MSTHM calculation is 
compared with an alternative MSTHM calculation in which the LDTH and SDT submodels are vertically 
extended to include the upper 1 km of the saturated zone. 
Figure 6.3-19. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for the pwr1-2 
Waste Package at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: SZ = saturated zone. See Figure 6.3-1 for location). The plotted thermal-hydrologic parameters are (a) 
drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste 
package relative humidity, and (e) invert liquid-phase saturation. The standard MSTHM calculation is 
compared with an alternative MSTHM calculation in which the LDTH and SDT submodels are vertically 
extended to include the upper 1 km of the saturated zone. 
Figure 6.3-20. Thermal-Hydrologic Conditions for the Mean Infiltration-Flux Case Plotted for a Range of 
Waste Packages at the P3R8C13 Location in the Tptpln (tsw36) Unit 
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6.3.2 Parameter-Uncertainty-Sensitivity Analyses 
For MSTHM predictions of thermal-hydrologic conditions within the emplacement drifts and in 
the adjoining host rock, the key uncertainty parameters (Table 6.3-18) fall into three categories: 
(1) thermal properties, (2) hydrologic properties, and (3) percolation flux. For thermal and 
hydrologic properties, the primary focus is the properties of the host rock and of the materials 
within the emplacement drifts and the ambient percolation flux at the repository horizon. 
The primary thermal properties are heat capacity and thermal conductivity. From past analyses, 
it is known that host-rock heat capacity has an insignificant effect on the thermal-hydrologic 
response in the drifts and adjacent host rock. This is corroborated by Section 5.3.1.4.10 of FY 01 
Supplemental Science and Performance Analyses, Volume 1: Scientific Bases and Analyses 
(BSC 2001 [DIRS 155950]). Similarly, the insensitivity to invert thermal conductivity, within its 
range of uncertainty, is corroborated by Section 5.3.1.4.10 of that report. Note that the host-rock 
thermal conductivity was found to be a significant parameter (BSC 2001 [DIRS 155950], Section 
5.3.1.4.8); consequently, it is addressed in Sections 6.3.2.2 and 6.3.2.3 of this report. 
The primary hydrologic property of interest is the bulk permeability of the host rock, which is 
primarily affected by the permeability of the fracture network. A sensitivity study of host-rock 
bulk permeability (BSC 2001 [DIRS 155950], Section 5.3.1.4.7) found the influence to be 
primarily confined to temperature. Host-rock bulk permeability was found to modestly influence 
peak temperatures and boiling-period duration. In Section 6.3.9 of this report, temperature and 
relative humidity were found to be insensitive to a range of host-rock bulk permeability. The 
influence of coupled thermal-hydrologic-mechanical coupling on permeability is investigated for 
the Tptpmn (tsw34) and Tptpll (tsw35) host-rock units in Drift Scale THM Model (BSC 2004 
[DIRS 169864]). There it was found that thermal stresses alter the host-rock permeability in the 
vertical and horizontal directions. However, these thermal-stress-induced changes in host-rock 
permeability were concluded to have a small influence on dryout and rewetting (BSC 2004 
[DIRS 169864], Section 8.1). Because the effect of host-rock bulk permeability on temperature 
and relative humidity is insignificant, compared to that of host-rock thermal conductivity 
uncertainty (which is addressed in Sections 6.3.2.2 and 6.3.2.3), it is unnecessary to further 
investigate the influence of bulk-permeability uncertainty in this report. 
Percolation-flux uncertainty at the repository horizon can result from at least two sources. The 
first source is the uncertainty concerning the magnitude of infiltration flux, which is addressed 
by way of lower-bound, mean, and upper-bound infiltration flux cases in Section 6.3.1.1. 
The second source of percolation-flux uncertainty concerns the possibility of flow focusing in 
the UZ model layers between the base of the PTn sequence of units and the repository horizon. 
The liquid-phase flux distribution applied at the upper boundary of the LDTH submodels of the 
MSTHM is the percolation-flux distribution (from the base of the PTn unit into the top of the 
TSw sequence of units) calculated by UZ Flow Models and Submodels (BSC 2004 
[DIRS 169861]). Flow focusing is the term used to denote the potential concentration of 
percolation flux from the large-scale average distribution of percolation flux, as simulated by the 
relatively coarsely gridded three-dimensional UZ flow model, to the drift scale, as simulated by 
the MSTHM and by Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338]). The impact of flow focusing of ambient percolation flux at the repository 
horizon is addressed in Sections 6.3.2.1 and 6.3.2.3. 
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Table 6.3-18. Potentially Important Parameters to Thermal-Hydrologic Conditions in Emplacement Drifts, 
Listed for Consideration in the Parameter-Uncertainty Sensitivity Analysis. 
Previous Parameter-Importance to In-drift Parameter Uncertainty-
Parameter 
Uncertainty-Sensitivity 
Analyses 
Thermal-Hydrologic 
Conditions 
Sensitivity Analyses in 
This Report 
Host-rock heat BSC 2001 [DIRS 155950], Insignificant None 
capacity (which Section 5.3.1.4.10 
includes influence 
of specific heat 
and bulk density) 
Host-rock thermal BSC 2001 [DIRS 155950], Important Sections 6.3.2.2 and 
conductivity Section 5.3.1.4.8 6.3.2.3 
Invert thermal BSC 2001 [DIRS 155950], Insignificant None 
conductivity Section 5.3.1.4.10 
Host-rock bulk BSC 2001 [DIRS 155950], Minor influence on temperature, None 
permeability Section 5.3.1.4.7 small compared to that of host 
rock thermal conductivity 
uncertainty (Sections 6.3.2.2 and 
6.3.2.3) 
Percolation flux BSC 2001 [DIRS 158204], Important Sections 6.3.1.1, 6.3.2.1, 
Sections 6.11 and 6.12 and 6.3.2.3 
6.3.2.1 Percolation-Flux Uncertainty at the Repository Horizon, Including the Influence 
of Flow Focusing 
Between the base of the PTn unit and the repository horizon, ambient percolation flux is assumed 
to be vertically downward with neither lateral diversion nor flow focusing caused by layering or 
heterogeneity in the hydrologic-property distributions. Section 6.2.1.4 of Drift-Scale Coupled 
Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]) discusses the need to 
address the potential for flow focusing of percolation flux in the hydrogeologic units above the 
repository horizon. Flow focusing is the term used to denote the potential concentration of 
percolation flux from the large-scale distribution of percolation flux, as simulated by the 
relatively coarsely gridded three-dimensional UZ flow model, to the drift scale, as simulated by 
the MSTHM and by Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338]). Stochastic modeling analyses discussed in Section 4.3.2 of FY 01 
Supplemental Science and Performance Analyses, Volume 1: Scientific Bases and Analyses 
(BSC 2001 [DIRS 155950]), using a two-dimensional, finely gridded vertical cross section of the 
unsaturated zone, resulted in maximum flow-focusing factors between 5 and 6. In Section 
6.2.2.2.4 of Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338]) flow-focusing factors of 5 and 10 were considered in the sensitivity study to 
percolation flux, resulting in percolation fluxes of 30, 80, and 125 mm/yr for the present-day, 
monsoonal, and glacial-transition climate states, respectively. 
Table 6.3-19 summarizes the percolation fluxes for the low and high percolation-flux cases 
considered in this study. To better discern the influence of the local host-rock unit on 
thermal-hydrologic behavior, it was decided to use the same value of present-day percolation 
flux (25 mm/yr) for the high percolation-flux case at all four locations, thus resulting in an 
effective flow focusing factor of close to 5 at all locations. To obtain the monsoonal and 
glacial-transition high percolation-flux values at a given location (Table 6.3-19), the 
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corresponding percolation flux values in Table 6.3-9 are multiplied by the corresponding factor. 
Note that the present-day, monsoonal, and glacial-transition high percolation-flux values are 
similar to those used in Section 6.2.2.2.4 of Drift-Scale Coupled Processes (DST and TH 
Seepage) Models (BSC 2004 [DIRS 170338]) for the case with a factor of 5 (that case used 
percolation flux values of 30, 80, and 125 mm/yr for the three climate states, respectively). 
The low percolation-flux case in Table 6.3-19 corresponds to the possibility of a region of the 
repository experiencing flow defocusing, which is the opposite of flow focusing. Thus, for 
flow focusing to be able to occur in one region of the repository, it is necessary for adjoining 
regions to receive less percolation flux than would have occurred without flow focusing. To 
discern the influence of the local host-rock unit on thermal-hydrologic behavior, it was decided 
to apply the same value (0.025 mm/yr) to all four locations. Because the low percolation-flux 
cases are meant to correspond to regions that are, in effect, shielded from significant percolation 
flux, regardless of the magnitude of repository-wide percolation flux, it was decided to use the 
same small value of percolation flux for all (three) climate states. Thus, this defocusing effect 
persists during all (three) climate states. It is noted that the low percolation-flux cases 
considered in this section correspond to persistently small flux values, thereby allowing the 
dryout and temperature effects of low percolation flux to develop. Note that values of 
present-day percolation flux vary by a factor of 1,000 between the low and high percolation-flux 
cases. 
Table 6.3-19. Percolation Flux for the Low, Mean, and High Percolation-Flux Cases Summarized for 
Four Locations Used to Examine Thermal-Hydrologic Conditions in the Repository 
LDTHSDT 
Submodel 
Location 
Percolation Flux for the Low 
Percolation-Flux (defocused flow) 
Case (mm/yr) 
Percolation Flux for the High Percolation-Flux 
(focused flow) Case (mm/yr) 
Present-
Day Monsoonal 
Glacial-
Transition 
Present-
Day Monsoonala 
Glacial-
Transitiona 
Effective 
Focus 
Factorb 
P2ER8C6 0.025 0.025 0.025 25.00 54.04 106.3 4.62 
P2WR8C8 0.025 0.025 0.025 25.00 58.41 87.47 5.59 
P2WR5C10 0.025 0.025 0.025 25.00 77.49 117.18 5.31 
P3R8C13 0.025 0.025 0.025 25.00 77.57 111.89 3.54 
a 
The monsoonal and glacial-transition percolation flux values for the high percolation-flux case are obtained by 
multiplying the corresponding percolation flux values in Table 6.3-9 by the effective focus factor for that location. 
b 
The effective focus factor is obtained by dividing 25.00 mm/yr by the present-day percolation flux listed for the 
given location in Table 6.3-9. 
NOTE: See Figure 6.2-2 for locations. Values for the mean percolation-flux case are given in Table 6.3-9. 
The influence of percolation-flux uncertainty on thermohydrologic behavior at four locations 
(P2ER8C6, P2WR8C8, P2WR5C10, and P3R8C13) in the repository (see Figure 6.3-1 for 
locations) is shown in time histories of drift-wall temperature and liquid-phase saturation, waste 
package temperature and relative humidity, and invert liquid-phase saturation (Figures 6.3-21 
through 6.3-24) for a 21-PWR AP CSNF waste package. Percolation-flux uncertainty is seen to 
have a small influence on peak drift-wall temperature (Table 6.3-20) and on peak waste package 
temperature (Table 6.3-21). Peak drift-wall temperatures only vary by 3.7 to 5.2 percent and 
peak waste package temperatures only vary by 2.9 to 4.3 percent for a 1,000-fold range of 
percolation flux. Compared to its influence on peak temperatures, percolation-flux uncertainty 
has a much stronger influence on the duration of boiling (Table 6.3-22). The sensitivity of 
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boiling-period duration to percolation-flux uncertainty is greatest for those locations with the 
longest boiling-period duration, which correspond to locations near the center of the repository 
where the extent of rock dryout has more time to develop. Thus locations P2ER8C6 and 
P3R8C13, which are at the repository edges have the smallest sensitivity to percolation-flux 
uncertainty, while location P2WR5C10, which is close to the center of the repository, has the 
greatest sensitivity. 
Percolation-flux uncertainty has a strong influence on dryout/rewetting behavior, as shown in the 
drift-wall and invert liquid-phase saturation histories (Figures 6.3-21c, 6.3-21e, 6.3.22c, 6.3.22e, 
6.3-23c, 6.3-23e, 6.3-24c, and 6.3-24e). Similarly, it also has a strong influence on the waste 
package relative humidity histories (Figures 6.3-21d, 6.3-22d, 6.3-23d, and 6.3-24d). Because 
the relative humidity at the drift wall depends on the liquid-phase saturation (as well as on 
temperature) at the drift wall, the variability of drift-wall relative humidity is similar to that of 
drift-wall liquid-phase saturation. Relative humidity on a given waste package depends on 
relative humidity at the adjacent drift wall. The large differences in drift-wall liquid-phase 
saturation histories (between the low and high percolation-flux cases) result in large differences 
in waste package relative humidity histories between the flux cases. 
Table 6.3-20. Range of Peak Drift-Wall Temperatures for the pwr1-2 Waste Package (Resulting from 
Percolation-Flux Uncertainty) Summarized for Four Locations in the Repository 
LDTHSDT 
Submodel 
Location 
Host-Rock 
Unit 
Peak Drift-Wall Temperature (C) 
Low 
Percolation 
Flux 
Mean 
Percolation 
Flux 
High 
Percolation 
Flux 
Low to High 
Range 
Low to High 
Rangea 
P2ER8C6 Tptpul (tsw33) 138.9 135.5 131.9 7.0 5.2% 
P2WR8C8 Tptpmn (tsw34) 124.5 123.0 119.4 5.1 4.2% 
P2WR5C10 Tptpll (tsw35) 144.1 140.8 137.2 6.9 4.9% 
P3R8C13 Tptpln (tsw36) 121.9 120.2 117.5 4.4 3.7% 
a 
The range (%) is the range (C) divided by the peak drift-wall temperature [(low + high)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). These values are based on data plotted in Figures 6.3-21 
through 6.3-29. 
Table 6.3-21. Range of Peak Waste Package Temperatures for the pwr1-2 Waste Package (Resulting 
from Percolation-Flux Uncertainty) Summarized for Four Locations in the Repository 
LDTHSDT 
Submodel 
Location 
Host-Rock 
Unit 
Peak Waste Package Temperature (C) 
Low 
Percolation 
Flux 
Mean 
Percolation 
Flux 
High 
Percolation 
Flux 
Low to High 
Range 
Low to High 
Rangea 
P2ER8C6 Tptpul (tsw33) 166.5 163.2 159.5 7.0 4.3% 
P2WR8C8 Tptpmn (tsw34) 151.7 150.6 147.4 4.3 2.9% 
P2WR5C10 Tptpll (tsw35) 172.4 168.8 165.4 7.0 4.1% 
P3R8C13 Tptpln (tsw36) 149.9 148.2 145.9 4.0 2.7% 
a 
The range (%) is the range (C) divided by the peak drift-wall temperature [(low + high)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). These values are based on data plotted in Figures 6.3-21 
through 6.3-29. 
ANL-EBS-MD-000049 REV 02 6-91 October 2004 

Multiscale Thermohydrologic Model 
Table 6.3-22. Range of Time When Boiling at the Drift Wall Ceases for the pwr1-2 Waste Package 
(Resulting from Percolation-Flux Uncertainty) Summarized for Four Locations in the 
Repository 
LDTHSDT 
Submodel 
Location 
Host-Rock 
Unit 
Time When Boiling at the Drift Wall Ceases (years) 
Low 
Percolation 
Flux 
Mean 
Percolation 
Flux 
High 
Percolation 
Flux 
Low to High 
Range 
Low to High 
Rangea 
P2ER8C6 Tptpul (tsw33) 438.1 364.8 313.3 124.8 33.2% 
P2WR8C8 Tptpmn (tsw34) 286.1 242.8 197.7 88.4 36.5% 
P2WR5C10 Tptpll (tsw35) 896.9 623.0 385.4 484.5 75.6% 
P3R8C13 Tptpln (tsw36) 224.2 195.2 175.2 49.0 24.5% 
a 
The range (%) is the range (years) divided by the average time when drift-wall boiling ceases [(shortest +
longest)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). These values are based on data plotted in Figures 6.3-21 
through 6.3-29. 
ANL-EBS-MD-000049 REV 02 6-92 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-21. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Low, Mean, 
and High Percolation-Flux Cases at the P2ER8C6 Location in the Tptpul (tsw33) Unit 
ANL-EBS-MD-000049 REV 02 6-93 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-22. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Low, Mean, 
and High Percolation-Flux Cases at the P2WR8C8 Location in the Tptpmn (tsw34) Unit 
ANL-EBS-MD-000049 REV 02 6-94 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-23. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Low, Mean, 
and High Percolation-Flux Cases at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
ANL-EBS-MD-000049 REV 02 6-95 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) 
waste package temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and 
(e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
Figure 6.3-24. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Low, Mean, 
and High Percolation-Flux Cases at the P3R8C13 Location in the Tptpln (tsw36) Unit 
ANL-EBS-MD-000049 REV 02 6-96 October 2004 

Multiscale Thermohydrologic Model 
6.3.2.2 Host-Rock Thermal Conductivity Uncertainty 
The sensitivity of thermal-hydrologic behavior to host-rock thermal conductivity uncertainty is 
addressed for ranges that extend approximately 1 standard deviation about the mean value 
(Table 6.3-23). The thermal conductivity data from Table 7-10 of DTN: SN0404T0503102.011 
[DIRS 169129] (File: readme.doc) are used to determine the ranges for the wet and dry thermal 
conductivity values for the four host-rock units. Note that the mean values of Kth of the Tptpul 
(tsw33) unit are slightly different from those in Table 7-10 of DTN: SN0404T0503102.011 
[DIRS 169129] (File: readme.doc). To be consistent with the other thermal-hydrologic models, 
such as those in Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338]), Kth for the Tptpul (tsw33) unit is computed as a straight arithmetic average of 
Kth for the Tptpul from Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: 
readme.doc) and the Kth of the Tptrl from DTN: SN0303T0503102.008 [DIRS 162401] (row 
66). This averaging for the Tptpul (tsw33) unit is also applied to the other thermal properties to 
be consistent with Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338]), which computes the thermal properties (including Kth) of the Tptpul (tsw33) 
unit to be the average of the thermal properties of the Tptpul from Table 7-10 of 
DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc) and the thermal properties of 
the Tptrl unit from DTN: SN0303T0503102.008 [DIRS 162401] (row 66). 
For all locations, host-rock thermal conductivity uncertainty has a strong influence on peak 
temperatures (Table 6.3-25) and on boiling duration (Table 6.3-26), with the influence being 
stronger for locations closer to the repository center. Thus, the P2WR5C10 location, which is 
located close to the center of the repository, has the widest range (114.3 percent) of the time 
when boiling at the drift wall ceases. Locations P2ER8C6 and P3R8C13, which are at the edge 
of the repository, have somewhat smaller ranges (65.2 percent and 75.4 percent, respectively) of 
the time when boiling ceases at the drift wall. 
Host-rock thermal conductivity uncertainty has a strong influence on dryout/rewetting behavior 
for the first 1,000 to 2,000 years, as shown in the drift-wall and invert liquid-phase saturation 
histories (Figures 6.3-25c, 6.3-25e, 6.3.26c, 6.3.26e, 6.3-27c, 6.3-27e, 6.3-28c, and 6.3-28e). 
Similarly, host-rock thermal conductivity uncertainty also has a strong influence on the waste 
package relative humidity histories for the first one- to two-thousand years (Figures 6.3-21d, 
6.3-22d, 6.3-23d, and 6.3-24d). 
ANL-EBS-MD-000049 REV 02 6-97 October 2004 

Multiscale Thermohydrologic Model 
Table 6.3-23. Wet and Dry Thermal Conductivity Values Used in the Host-Rock Thermal Conductivity 
Uncertainty Study 
Host-Rock Dry Thermal Conductivity (W/m C) Wet Thermal Conductivity (W/m C) 
Unit Low Mean High Low Mean High 
Tptpul (tsw33) 0.9842 1.24 1.4958 1.5405 1.79 2.0395 
Tptpmn (tsw34) 1.1544 1.42 1.6856 1.8188 2.07 2.3212 
Tptpll (tsw35) 1.0286 1.28 1.5314 1.6415 1.89 2.1385 
Tptpln (tsw36) 1.2056 1.49 1.7744 1.8624 2.13 2.3976 
NOTE: 
Table 6.3-24. 
Low, mean, and high thermal conductivity cases are considered for ranges that extend
approximately 1 standard deviation about the mean value. With the exception of the 
mean values of Kth for the Tptpul (tsw33) unit, these values are taken from Table 7-10 of 
DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc). The mean values of 
Kth for the Tptpul (tsw33) unit are a straight arithmetic averages of the mean Kth values 
for the Tptpul from Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: 
readme.doc) and the mean Kth of the Tptrl from DTN: SN0303T0503102.008 [DIRS 
162401] (row 66). Also note that Table IV-3a in Appendix IV lists Kth for the Tptpul unit 
from Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc) and 
Kth for the Tptrl unit from DTN: SN0303T0503102.008 [DIRS 162401]. The standard 
deviations for the Tptpul (tsw33) in Table 7-10 of DTN: SN0404T0503102.011 [DIRS 
169129] (File: readme.doc) are divided by the corresponding mean Kth values to obtain 
the percentage differences for plus and minus one standard deviation. These 
percentages are then applied to the arithmetic-averaged mean Kth for the Tptpul (tsw33) 
unit to obtain the plus and minus one-standard-deviation values of Kth for the Tptpul 
(tsw33) unit. 
Range of Peak Drift-Wall Temperatures for the pwr1-2 Waste Package (Resulting from 
Thermal Conductivity Uncertainty) Summarized for Four Locations in the Repository 
LDTHSDT Peak Drift-Wall Temperature (C) 
Submodel 
Location Host-Rock Unit 
Low Thermal 
Conductivity 
Mean Thermal 
Conductivity 
High Thermal 
Conductivity 
Low to High 
Range 
Low to High 
Rangea 
P2ER8C6 Tptpul (tsw33) 153.3 135.5 123.2 30.1 21.8% 
P2WR8C8 Tptpmn (tsw34) 136.5 123.0 113.8 22.7 18.1% 
P2WR5C10 Tptpll (tsw35) 158.9 140.8 127.4 31.5 22.0% 
P3R8C13 Tptpln (tsw36) 132.7 120.2 110.8 21.9 18.0% 
a 
The range (%) is the range (C) divided by the peak drift-wall temperature [(low + high)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). Low, mean, and high thermal conductivity cases are considered 
for a range of plus and minus one standard deviation about the mean value. These values are based on 
data plotted in Figures 6.3-25 through 6.3-28. 
ANL-EBS-MD-000049 REV 02 6-98 October 2004 

Multiscale Thermohydrologic Model 
Table 6.3-25. Range of Peak Waste Package Temperatures for the pwr1-2 Waste Package (Resulting 
from Thermal Conductivity Uncertainty) Summarized for Four Locations in the Repository 
LDTHSDT 
Submodel 
Location 
Host-Rock 
Unit 
Peak Waste Package Temperature (C) 
Low Thermal 
Conductivity 
Mean 
Thermal 
Conductivity 
High 
Thermal 
Conductivity 
Low to High 
Range 
Low to High 
Range* 
P2ER8C6 Tptpul 181.2 163.2 151.4 29.8 17.9% 
(tsw33) 
P2WR8C8 Tptpmn 163.8 150.6 141.9 21.9 14.3% 
(tsw34) 
P2WR5C10 Tptpll (tsw35) 187.2 168.8 155.8 31.4 18.3% 
P3R8C13 Tptpln 160.6 148.2 139.2 21.4 14.3% 
(tsw36) 
a 
The range (%) is the range (C) divided by the peak drift-wall temperature [(low + high)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). Low, mean, and high thermal conductivity cases are 
considered for a range of plus and minus one standard deviation about the mean value. These values 
are based on data plotted in Figures 6.3-25 through 6.3-28.
Table 6.3-26. Range of Time When Boiling at the Drift Wall Ceases for the pwr1-2 Waste Package 
(Resulting from Host-Rock Thermal Conductivity Uncertainty) Summarized for Four 
Locations in the Repository 
Time When Boiling at the Drift Wall Ceases 
LDTHSDT 
Submodel 
Location 
Host-Rock 
Unit 
(years) 
Low Thermal 
Conductivity 
Mean 
Thermal 
Conductivity 
High 
Thermal 
Conductivity 
Low to High 
Range 
Low to High 
Rangea 
P2ER8C6 Tptpul 508.9 364.8 258.9 250.0 65.2% 
(tsw33) 
P2WR8C8 Tptpmn 412.8 242.8 163.8 249.0 86.4% 
(tsw34) 
P2WR5C10 Tptpll (tsw35) 963.8 623.0 263.0 700.8 114.3% 
P3R8C13 Tptpln 309.0 195.2 139.8 169.2 75.4% 
(tsw36) 
a 
The range (%) is the range (years) divided by the average time when drift-wall boiling ceases [(shortest +
longest)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). Low, mean, and high thermal conductivity cases are 
considered for a range of plus and minus one standard deviation about the mean value. These values 
are based on data plotted in Figures 6.3-25 through 6.3-28. 
ANL-EBS-MD-000049 REV 02 6-99 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Low, mean, and high thermal conductivity cases are considered for a range 
of plus and minus one standard deviation about the mean value. The plotted thermal-hydrologic 
parameters are (a) drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase 
saturation, (d) waste package relative humidity, and (e) invert liquid-phase saturation. The pwr1-2 
(21-PWR AP CSNF) waste package is the hottest waste package in the sequence (Figure 6.2-2). 
Figure 6.3-25. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Mean 
Infiltration-Flux Case at the P2ER8C6 Location in the Tptpul (tsw33) Unit 
ANL-EBS-MD-000049 REV 02 6-100 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Low, mean, and high thermal conductivity cases are considered range of 
plus and minus one standard deviation about the mean value. The plotted thermal-hydrologic parameters 
are (a) drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase saturation, (d) 
waste package relative humidity, and (e) invert liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) 
waste package is the hottest waste package in the sequence (Figure 6.2-2). 
Figure 6.3-26. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Mean 
Infiltration-Flux Case at the P2WR8C8 Location in the Tptpmn (tsw34) Unit 
ANL-EBS-MD-000049 REV 02 6-101 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Low, mean, and high thermal conductivity cases are considered for a range 
of plus and minus one standard deviation about the mean value. The plotted thermal-hydrologic 
parameters are (a) drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase 
saturation, (d) waste package relative humidity, and (e) invert liquid-phase saturation. The pwr1-2 
(21-PWR AP CSNF) waste package is the hottest waste package in the sequence (Figure 6.2-2). 
Figure 6.3-27. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Mean 
Infiltration-Flux Case at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
ANL-EBS-MD-000049 REV 02 6-102 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Low, mean, and high thermal conductivity cases are considered for a range 
of plus and minus one standard deviation about the mean value. The plotted thermal-hydrologic 
parameters are (a) drift-wall temperature, (b) waste package temperature, (c) drift-wall liquid-phase 
saturation, (d) waste package relative humidity, and (e) invert liquid-phase saturation. The pwr1-2 
(21-PWR AP CSNF) waste package is the hottest waste package in the sequence (Figure 6.2-2). 
Figure 6.3-28. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for the Mean 
Infiltration-Flux Case at the P3R8C13 Location in the Tptpln (tsw36) Unit 
ANL-EBS-MD-000049 REV 02 6-103 October 2004 

Multiscale Thermohydrologic Model 
6.3.2.3 Combined Influence of Percolation Flux and Host-Rock Thermal Conductivity 
Uncertainty, Including the Influence of Flow Focusing 
In this section, the combined influence of percolation-flux uncertainty and host-rock thermal 
conductivity uncertainty on thermal-hydrologic behavior at four locations (P2ER8C6, 
P2WR8C8, P2WR5C10, and P3R8C13) in the repository (Figure 6.3-1) is shown in time 
histories of drift-wall temperature and liquid-phase saturation, waste package temperature and 
relative humidity, and invert liquid-phase saturation (Figures 6.3-29 through 6.3-32) for a 
21-PWR AP CSNF waste package. Three cases are considered: (1) low percolation flux and 
low host-rock thermal conductivity, (2) mean percolation flux and mean host rock thermal 
conductivity, and (3) high percolation flux and high host-rock thermal conductivity. The values 
of present-day, monsoonal, and glacial-transition percolation flux values for the low and high 
percolation-flux cases are summarized in Table 6.3-19; the mean percolation flux values are 
summarized in Table 6.3-9. The values of dry and wet host-rock thermal conductivity for the 
low, mean, and high thermal conductivity cases are summarized in Table 6.3-23. Note that the 
values of percolation flux for these cases are the same as those considered in Section 6.3.2.1 and 
that the values of host-rock thermal conductivity are the same as those considered in 
Section 6.3.2.2. Low percolation flux and low host-rock thermal conductivity both result in 
higher peak temperatures and longer boiling durations. High percolation flux and high host-rock 
thermal conductivity both result in lower peak temperatures and shorter boiling durations. The 
range of peak drift-wall and waste package temperatures that result from the two extreme 
combinations of percolation flux and thermal conductivity are summarized in Tables 6.3-27 and 
6.3-28, respectively; the range of the time when boiling on the drift wall ceases is summarized in 
Table 6.3-29. 
Table 6.3-27. Range of Peak Drift-Wall Temperatures for the pwr1-2 Waste Package (Resulting from a 
Combination of Percolation Flux Qperc and Thermal Conductivity Kth Uncertainty) 
Summarized for Four Locations in the Repository 
LDTHSDT Peak Drift-Wall Temperature (C) 
Submodel 
Location 
Host-Rock 
Unit 
Low Qperc 
Low Kth 
Mean Qperc 
Mean Kth 
High Qperc 
High Kth 
Low to High 
Range 
Low to High 
Rangea 
P2ER8C6 Tptpul (tsw33) 156.9 135.5 120.4 36.5 26.3% 
P2WR8C8 Tptpmn (tsw34) 138.0 123.0 111.4 26.6 21.3% 
P2WR5C10 Tptpll (tsw35) 162.8 140.8 124.5 38.3 26.7% 
P3R8C13 Tptpln (tsw36) 136.1 120.2 108.8 27.3 22.3% 
a 
The range (%) is the range (C) divided by the peak drift-wall temperature [(low + high)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the 
hottest waste package in the sequence (Figure 6.2-2). Low, mean, and high thermal 
conductivity cases are considered for a range of plus and minus one standard deviation 
about the mean. 
ANL-EBS-MD-000049 REV 02 6-104 October 2004 

Multiscale Thermohydrologic Model 
Table 6.3-28. Range of Peak Waste Package Temperatures for the pwr1-2 Waste Package (Resulting 
from a Combination of Percolation Flux Qperc and Thermal Conductivity Kth Uncertainty) 
Summarized for Four Locations in the Repository 
LDTHSDT Peak Waste Package Temperature (C) 
Submodel 
Location 
Host-Rock 
Unit 
Low Qperc 
Low Kth 
Mean Qperc 
Mean Kth 
High Qperc 
High Kth 
Low to High 
Range 
Low to High 
Rangea 
P2ER8C6 Tptpul (tsw33) 185.1 163.2 148.7 36.4 21.8% 
P2WR8C8 Tptpmn (tsw34) 165.4 150.6 139.5 25.9 17.0% 
P2WR5C10 Tptpll (tsw35) 191.0 168.8 152.7 38.3 22.3% 
P3R8C13 Tptpln (tsw36) 163.9 148.2 137.3 26.6 17.7% 
a 
The range (%) is the range (C) divided by the peak drift-wall temperature [(low + high)/2]. 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest 
waste package in the sequence (Figure 6.2-2). Low, mean, and high thermal conductivity 
cases are considered for a range of plus and minus one standard deviation about the mean. 
Table 6.3-29. Range of Time When Boiling at the Drift Wall Ceases for the pwr1-2 Waste Package 
(Resulting from a Combination of Percolation Flux Qperc and Thermal Conductivity Kth 
Uncertainty) Summarized for Four Locations in the Repository 
LDTHSDT Time When Boiling at the Drift Wall Ceases (years) 
Submodel 
Location Host-Rock Unit 
Low Qperc 
Low Kth 
Mean Qperc 
Mean Kth 
High Qperc 
High Kth 
Low to High 
Range 
Low to High 
Range* 
P2ER8C6 Tptpul (tsw33) 615.5 364.8 222.5 393.0 93.8% 
P2WR8C8 Tptpmn (tsw34) 514.1 242.8 144.7 369.4 112.1% 
P2WR5C10 Tptpll (tsw35) 1,415.8 623.0 207.4 1,208.4 148.9% 
P3R8C13 Tptpln (tsw36) 377.2 195.2 129.8 247.4 97.6% 
a 
The range (%) is the range (years) divided by the average time when drift-wall boiling ceases [(shortest 
+ longest)/2]. 
NOTE: See Figure 6.3-1 for location. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest 
waste package in the sequence (Figure 6.2-2). Low, mean, and high thermal conductivity 
cases are considered for a range of plus and minus one standard deviation about the mean. 
ANL-EBS-MD-000049 REV 02 6-105 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. These cases are: (1) low percolation flux and low thermal conductivity, (2) 
mean percolation flux and mean thermal conductivity, and (3) high percolation flux and high thermal 
conductivity, where the thermal conductivity is varied by plus and minus one standard deviation about the 
mean. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) waste package 
temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and (e) invert 
liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste package in 
the sequence (Figure 6.2-2). 
Figure 6.3-29. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Three Cases at 
the P2ER8C6 Location in the Tptpul (tsw33) Unit 
ANL-EBS-MD-000049 REV 02 6-106 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. These cases are: (1) low percolation flux and low thermal conductivity, 
(2) mean percolation flux and mean thermal conductivity, and (3) high percolation flux and high thermal 
conductivity, where the thermal conductivity is varied by plus and minus one standard deviation about the 
mean. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) waste package 
temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and (e) invert 
liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste package in 
the sequence (Figure 6.2-2). 
Figure 6.3-30. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Three Cases at 
the P2WR8C8 Location in the Tptpmn (tsw34) Unit 
ANL-EBS-MD-000049 REV 02 6-107 October 2004 

Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. These cases are: (1) low percolation flux and low thermal conductivity, (2) 
mean percolation flux and mean thermal conductivity, and (3) high percolation flux and high thermal 
conductivity, where the thermal conductivity is varied by plus and minus one standard deviation about the 
mean. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) waste package 
temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and (e) invert 
liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste package in 
the sequence (Figure 6.2-2). 
Figure 6.3-31. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Three Cases at 
the P2WR5C10 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. These cases are: (1) low percolation flux and low thermal conductivity, (2) 
mean percolation flux and mean thermal conductivity, and (3) high percolation flux and high thermal 
conductivity, where the thermal conductivity is varied by plus and minus one standard deviation about the 
mean. The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) waste package 
temperature, (c) drift-wall liquid-phase saturation, (d) waste package relative humidity, and (e) invert 
liquid-phase saturation. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste package in 
the sequence (Figure 6.2-2). 
Figure 6.3-32. Thermal-Hydrologic Conditions for the pwr1-2 Waste Package Plotted for Three Cases at 
the P3R8C13 Location in the Tptpln (tsw36) Unit 
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Multiscale Thermohydrologic Model 
An important question to ask is whether the combined influence of percolation-flux uncertainty 
and host-rock thermal conductivity on peak temperatures is simply the sum of the individual 
contributions to peak-temperature uncertainty. Table 6.3-30 compares the ranges of peak 
temperatures resulting from (1) percolation-flux uncertainty, (2) host-rock thermal conductivity 
uncertainty, and (3) a combination of percolation flux and host-rock thermal conductivity 
uncertainty; Table 6.3-31 makes the same comparison for peak waste package temperatures. 
Adding the range of peak temperatures resulting from percolation-flux uncertainty to those from 
host-rock thermal conductivity uncertainty, the results are nearly identical to the range of peak 
temperatures resulting from the combination of percolation-flux uncertainty and host-rock 
thermal conductivity. Taking location P2WR5C10 in Table 6.3-30 as an example: adding the 
peak-temperature range resulting from percolation-flux uncertainty (6.9C) to that resulting from 
host-rock thermal conductivity uncertainty (31.5C) yields a total of 38.4C, which is close to the 
peak-temperature range (38.3C) that results when the influences of percolation flux and 
host-rock thermal conductivity uncertainty are combined. 
A related question is whether the combined influence of percolation-flux uncertainty and 
host-rock thermal conductivity on boiling duration is simply the sum of the individual 
contributions to boiling-duration uncertainty. Table 6.3-32 compares the ranges of the time 
when boiling at the drift wall ceases resulting from (1) percolation-flux uncertainty, (2) host-rock 
thermal conductivity uncertainty, and (3) the combination of percolation flux and host-rock 
thermal conductivity uncertainty. Adding the range of time when drift-wall boiling ends 
resulting from percolation-flux uncertainty to that from host-rock thermal conductivity 
uncertainty is nearly equal to the range of boiling duration resulting from the combination of 
percolation-flux uncertainty and host-rock thermal conductivity uncertainty. Taking location 
P2WR5C10 in Table 6.3-32 as an example, adding the range of the time when boiling at the drift 
wall ceases resulting from percolation-flux uncertainty (484.5 years) to that resulting from 
host-rock thermal conductivity uncertainty (700.8 years), yields 1,185.3 years, which is similar 
to the range (1,208.4 years) that results when the influences of percolation flux and host-rock 
thermal conductivity uncertainty are combined. In general, the range resulting from the 
combined uncertainties is always slightly greater than the sum of the individual contributions to 
boiling-duration uncertainty. 
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Table 6.3-30. Range of Peak Drift-Wall Temperatures for the pwr1-2 Waste Package Resulting from 
Various Combinations of Percolation Flux Qperc and Thermal Conductivity Kth Uncertainty, 
Summarized for Four Locations in the Repository 
Influence of 
LDTHSDT 
Percolation-
Flux 
Uncertainty on 
Peak Drift-Wall 
Temperature 
Influence of Host-
Rock Thermal 
Conductivity 
Uncertainty on Peak 
Drift-Wall Temperature 
Influence of Combined 
Percolation Flux and Host-
Rock Thermal Conductivity 
Uncertainty on Peak Drift-
Wall Temperature 
Submodel 
Location 
Host-Rock 
Unit 
Range 
(C) 
Range 
(%) 
Range 
(C) 
Range 
(%) 
Range 
(C) 
Range 
(%) 
P2ER8C6 Tptpul (tsw33) 7.0 5.2% 30.1 21.8% 36.5 26.3% 
P2WR8C8 Tptpmn (tsw34) 5.1 4.2% 22.7 18.1% 26.6 21.3% 
P2WR5C10 Tptpll (tsw35) 6.9 4.9% 31.5 22.0% 38.3 26.7% 
P3R8C13 Tptpln (tsw36) 4.4 3.7% 21.9 18.0% 27.3 22.3% 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). These values summarize Tables 6.3-20 through 6.3-29. 
Table 6.3-31. Range of Peak Waste Package Temperatures for the pwr1-2 Waste Package Resulting 
from Various Combinations of Percolation Flux Qperc and Thermal Conductivity Kth 
Uncertainty, Summarized for Four Locations in the Repository 
Influence of Influence of Host-Rock Influence of Combined 
Percolation-Flux 
Uncertainty on Peak 
Thermal Conductivity 
Uncertainty on Peak 
Percolation Flux and Host-
Rock Thermal Conductivity 
LDTHSDT 
Waste Package 
Temperature 
Waste Package 
Temperature 
Uncertainty on Peak Waste 
Package Temperature 
Submodel 
Location Host-Rock Unit 
Range 
(C) 
Range 
(%) 
Range 
(C) 
Range 
(%) 
Range 
(C) 
Range 
(%) 
P2ER8C6 Tptpul (tsw33) 7.0 4.3% 29.8 17.9% 36.4 21.8% 
P2WR8C8 Tptpmn (tsw34) 4.3 2.9% 21.9 14.3% 25.9 17.0% 
P2WR5C10 Tptpll (tsw35) 7.0 4.1% 31.4 18.3% 38.3 22.3% 
P3R8C13 Tptpln (tsw36) 4.0 2.7% 21.4 14.3% 26.6 17.7% 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
The combined influence of percolation-flux uncertainty and host-rock thermal conductivity 
uncertainty on dryout/rewetting is illustrated by the drift-wall and invert liquid-phase saturation 
histories (Figures 6.3-29c, 6.3-29e, 6.3-30c, 6.3-30e, 6.3-31c, 6.3-31e, 6.3-32c, and 6.3-32e). 
The time for liquid-phase saturation to rewet back to ambient values ranges by two orders of 
magnitude for these cases. The combined influence of percolation-flux uncertainty and 
host-rock thermal conductivity uncertainty on waste package relative humidity histories is shown 
in Figures 6.3-29d, 6.3-30d, 6.3-31d, and 6.3-32d. Because of the contribution of the 
temperature difference between the waste package and the drift wall on relative humidity 
reduction on waste packages, the combined influence of percolation flux and host-rock thermal 
conductivity uncertainty on waste package relative humidity, while evident, is not as strong as 
for liquid-phase saturation histories. 
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Table 6.3-32. Range of Time When Boiling at the Drift Wall Ceases for the pwr1-2 Waste Package 
Resulting from Various Combinations of Percolation Flux Qperc and Thermal Conductivity Kth 
Uncertainty, Summarized for Four Locations in the Repository 
LDTHSDT 
Influence of 
Percolation-Flux 
Uncertainty on 
Time When 
Boiling at the 
Drift Wall Ceases 
Influence of 
Host-Rock Thermal 
Conductivity 
Uncertainty on Time 
When Boiling at the 
Drift Wall Ceases 
Influence of Combined 
Percolation Flux and Host-
Rock Thermal 
Conductivity Uncertainty 
on Time When Boiling at 
the Drift Wall Ceases 
Submodel 
Location Host-Rock Unit 
Range 
(years) 
Range 
(%) 
Range 
(years) 
Range 
(%) 
Range 
(years) 
Range 
(%) 
P2ER8C6 Tptpul (tsw33) 124.8 33.2% 250.0 65.2% 393.0 93.8% 
P2WR8C8 Tptpmn (tsw34) 88.4 36.5% 249.0 86.4% 369.4 112.1% 
P2WR5C10 Tptpll (tsw35) 484.5 75.6% 700.8 114.3% 1,208.4 148.9% 
P3R8C13 Tptpln (tsw36) 49.0 24.5% 169.2 75.4% 247.4 97.6% 
NOTE: See Figure 6.3-1 for locations. The pwr1-2 (21-PWR AP CSNF) waste package is the hottest waste 
package in the sequence (Figure 6.2-2). 
6.3.2.4 Influence of Hydrologic-Property Uncertainty on In-Drift Temperature and 
Relative Humidity 
The primary purpose of this section is to help determine whether it is necessary to propagate 
hydrologic-property uncertainty in the MSTHM calculations for TSPA-LA. The primary 
hydrologic property of interest is the bulk permeability of the host rock; this parameter is 
primarily affected by the permeability of the fracture network. As discussed in Section 6.3.2, a 
sensitivity study (BSC 2001 [DIRS 155950], Section 5.3.1.4.7) found that host-rock bulk 
permeability has a minor influence on peak temperatures and boiling-period duration. Therefore, 
host-rock bulk permeability uncertainty does not need to be propagated in the MSTHM 
calculations for TSPA-LA. In this section, the influence of hydrologic-property uncertainty is 
further addressed by investigating the impact of utilizing various hydrologic-property sets that 
have differing values of matrix and fracture properties in the four host-rock units (Tptpul, 
Tptpmn, Tptpll, and Tptpln). 
The influence of hydrologic-property uncertainty on in-drift temperature and relative humidity at 
four locations (P2ER8C6, P2WR8C8, P2WR5C10, and P3R8C13) in the repository 
(Figure 6.3-1) is illustrated in time histories of drip-shield temperature and relative humidity 
(Figures 6.3-33 through 6.3-36). These time histories were generated with the use of the LDTH 
submodel (Section 6.2.6), which is the primary thermal-hydrologic submodel in the MSTHM 
family of submodels. Because the LDTH submodel is the only MSTHM submodel that uses 
hydrologic-property information as input, it is reasonable to use the results of the LDTH 
submodel to investigate the degree of sensitivity of in-drift temperature and relative humidity to 
hydrologic-property uncertainty. The LDTH submodel calculations in this section were 
conducted for an Areal Mass Loading (AML) of 55 MTU/acre. Thus, these results correspond to 
line-average heat-generation conditions for a repository location far enough away from the 
repository edges not to be influenced by the edge-cooling effect. For these four locations in the 
repository, four different cases are investigated: (1) lower-bound infiltration-flux case with 
lower-bound infiltration-flux property set, (DTN: LB0208UZDSCPLI.002 [DIRS 161788]), 
(2) lower-bound infiltration-flux case with modified-mean infiltration-flux property set, 
(3) upper-bound infiltration-flux case with upper-bound infiltration-flux property set 
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(DTN: LB0302UZDSCPUI.002 [DIRS 161787]), and (4) upper-bound infiltration-flux case 
with modified-mean infiltration-flux property set. The modified-mean infiltration-flux property 
set is used in all of the MSTHM calculations discussed in Sections 6.3.2.1 through 6.3.2.3 and in 
Section 6.3.3. These pairs of cases were chosen to be able to discern the influence of hydrologic 
properties on in-drift temperature and relative humidity. Because temperature and relative 
humidity on the drip shield are key measures of in-drift thermal-hydrologic conditions, this 
section focuses on those parameters. 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The four cases are: (1) lower-bound infiltration-flux case with lower-bound 
infiltration-flux property set, (2) lower-bound infiltration-flux case with modified-mean infiltration-flux 
property set, (3) upper-bound infiltration-flux case with upper-bound infiltration-flux property set, and (4) 
upper-bound infiltration-flux case with modified-mean infiltration-flux property set. 
Figure 6.3-33. Drip-Shield Temperature (a,b) and Relative Humidity (c,d) for Line-Averaged Heating 
Conditions Plotted for Four Cases at the P2ER8C6 Location in the Tptpul (tsw33) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The four cases are: (1) lower-bound infiltration-flux case with lower-bound 
infiltration-flux property set, (2) lower-bound infiltration-flux case with modified-mean infiltration-flux 
property set, (3) upper-bound infiltration-flux case with upper-bound infiltration-flux property set, and (4) 
upper-bound infiltration-flux case with modified-mean infiltration-flux property set. 
Figure 6.3-34. Drip-Shield Temperature (a,b) and Relative Humidity (c,d) for Line-Averaged Heating 
Conditions Plotted for Four Cases at the P2WR8C8 Location in the Tptpmn (tsw34) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The four cases are: (1) lower-bound infiltration-flux case with lower-bound 
infiltration-flux property set, (2) lower-bound infiltration-flux case with modified-mean infiltration-flux 
property set, (3) upper-bound infiltration-flux case with upper-bound infiltration-flux property set, and (4) 
upper-bound infiltration-flux case with modified-mean infiltration-flux property set. 
Figure 6.3-35. Drip-Shield Temperature (a,b) and Relative Humidity (c,d) for Line-Averaged Heating 
Conditions Plotted for Four Cases at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. The four cases are: (1) lower-bound infiltration-flux case with lower-bound 
infiltration-flux property set, (2) lower-bound infiltration-flux case with modified-mean infiltration-flux 
property set, (3) upper-bound infiltration-flux case with upper-bound infiltration-flux property set, and (4) 
upper-bound infiltration-flux case with modified mean infiltration-flux property set. 
Figure 6.3-36. Drip-Shield Temperature (a,b) and Relative Humidity (c,d) for Line-Averaged Heating 
Conditions Plotted for Four Cases at the P3R8C13 Location in the Tptpln (tsw36) Unit 
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Figures 6.3-33 through 6.3-36 indicate that in-drift temperature and relative humidity are 
insensitive to hydrologic-property uncertainty. For drifts located in the Tptpul (tsw33) unit 
(Figure 6.3-33) and the Tptpmn (tsw34) unit (Figure 6.3-34), which comprise 6.0 percent and 
16.1 percent of the repository area, respectively (Table 6.3-3), drip-shield temperature and 
relative humidity are weakly sensitive to hydrologic properties. For drifts located in the Tptpll 
(tsw35) unit (Figure 6.3-35), which comprise 75.1 percent of the repository area (Table 6.3-3), 
drip-shield temperature and relative humidity are insensitive to hydrologic properties. For drifts 
located in the Tptpln (tsw36) unit (Figure 6.3-36), which comprise only 1.6 percent of the 
repository area (Table 6.3-3), drip-shield temperature and relative humidity are relatively 
insensitive to hydrologic properties. The results support the conclusion that hydrologic-property 
uncertainty does not need to be propagated in the MSTHM calculations of in-drift temperature 
and relative humidity. 
6.3.3 Mass Flux in the Invert 
The primary purpose of this section is to examine gas- and liquid-phase mass fluxes in the invert, 
including fluxes into and out of the invert, as well as fluxes within the invert. Time histories of 
gas- and liquid-phase flux and of liquid-phase saturation are provided in Figures 6.3-37 through 
6.3-44 for four locations (P2ER8C6, P2WR8C8, P2WR5C10, and P3R8C13) in the repository 
(Figure 6.3-1). Figure 6.3-45 plots the phase change (with positive and negative phase change 
corresponding to evaporation and condensation, respectively) and the liquid-phase flux for the 
lower half of the invert. These four locations were chosen because they cover all four of the 
host-rock units in the repository and because their respective values of percolation flux are 
relatively close to the repository-wide averages (Tables 6.3-4, 6.3-5, and 6.3-9). These time 
histories were generated with the use of the LDTH submodel (Section 6.2.6), which is the 
primary thermal-hydrologic submodel in the MSTHM family of submodels. The LDTH 
submodel calculations in this section were conducted for an Areal Mass Loading (AML) of 55 
MTU/acre. Thus, these results correspond to line-average heat-generation conditions for a 
repository location far enough away from the repository edges not to be influenced by the 
edge-cooling effect. 
Figure 6.3-37 plots liquid-phase and gas-phase fluxes between the invert and the adjoining drift 
and host rock, as well as plotting the liquid-phase saturation in the invert, for the P2ER8C6 
location, which is in the Tptpul (tsw33) unit. Figures 6.3-38 plots liquid- and gas-phase fluxes 
between the upper and lower halves of the invert. Table 6.3-33 provides the peak values of 
liquid-phase and gas-phase fluxes after 50 years, while Table 6.3-34 provides the peak values 
after 100 years. These figures and tables show there are three distinctive time periods with 
respect to mass flux, dryout, and rewetting of the invert, which are: 
1. Initial period of strong dryout, when the strong gas-phase flux of water vapor (in the 
fracture continuum) out of the invert dominates the return capillary-driven liquid-phase 
flux (in the matrix continuum). Thus, refluxing (i.e., the countercurrent flow of water 
vapor and liquid water) is quite pronounced during this period. Gas- and liquid-phase 
fluxes rapidly increase and decrease during this period. At the very beginning of the 
initial dryout period, condensation is strong in the lower half of the invert (Figure 
6.3-45), which lasts until the boiling front passes through the bottom of the invert and 
into the underlying host rock. Liquid-phase flux (in the fracture continuum) drains from 
the bottom of the invert to the underlying host rock. Thus, liquid-phase drainage in the 
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fracture continuum contributes significantly to the initial dryout of the invert. The source 
of this liquid-phase drainage is condensation of water vapor that boiled in the upper 
portion of the invert and was driven downward to the lower portion of the invert. By the 
end of the initial dryout period the liquid-phase saturation in the invert has attained its 
minimum value. 
2. Period of sustained dryout, when the dryout front is in the host rock beyond the drift wall. 
During this period, the liquid-phase saturation remains close to its minimum value and 
mass fluxes within the invert, as well as at its interface with the adjoining drift and with 
the host rock, are essentially zero. 
3. Period of rewetting, when the return capillary-driven liquid-phase flux (in the matrix 
continuum) dominates the outward flux of water vapor (in the fracture continuum). Gas-
and liquid-phase fluxes gradually increase and decrease during this period. Liquid-phase 
flux (in the fracture continuum) drains from the bottom of the invert to the underlying 
host rock. The source of this liquid-phase drainage flux (which is of a much smaller 
magnitude than during the initial dryout period) is the condensation of water vapor that 
boiled in the upper portion of the invert and was driven downward to the lower portion of 
the invert (Figures 6.3-45a and 6.3-45b). Refluxing, both within the invert as well as at 
the interface with the host rock, is strong during this period. 
Figures 6.3-39 and 6.3-40 for the P2WR8C8 location, which is in the Tptpmn (tsw34) host-rock 
unit, are qualitatively similar to Figures 6.3-37 and 6.3-38; however, the magnitudes of the gas-
and liquid-phase fluxes associated with refluxing are much less during the rewetting period 
(Table 6.3-34). Moreover, the P2WR8C8 location experiences no liquid-phase drainage in the 
fracture continuum during the rewetting period (Figure 6.3-45d). 
Figures 6.3-41 and 6.3-42 for the P2WR5C10 location, which is in the Tptpll (tsw35) host-rock 
unit, are also qualitatively similar to Figures 6.3-37 and 6.3-38; however, the magnitude of the 
gas- and liquid-phase fluxes associated with refluxing is somewhat less during the rewetting 
period (Table 6.3-34). Moreover, the P2WR5C10 location experiences a much smaller 
liquid-phase drainage flux in the fracture continuum during the rewetting than the P2ER8C6 
location (compare Figure 6.3-45f with Figure 6.3-45b). 
Figures 6.3-43 and 6.3-44 for the P3R8C13 location, which is in the Tptpln (tsw36) host-rock 
unit, are qualitatively similar to Figures 6.3-37 and 6.3-38; however, the magnitude of the gas- 
and liquid-phase fluxes associated with refluxing is much less during the rewetting period (Table 
6.3-34). Moreover, the P3R8C13 location experiences no liquid-phase drainage in the fracture 
continuum during the rewetting period (Figure 6.3-45h). 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Also plotted is (f) the total (gas-phase + liquid-phase) mass flux for the 
matrix + fracture continua. A positive value of mass flux corresponds to flux out of the invert. Also plotted 
is the liquid-phase saturation for the (b) matrix and (d) fracture continuum. These fluxes are the result of 
line-averaged heating conditions. 
Figure 6.3-37. Liquid-Phase and Gas-Phase Flux Between the Invert and Adjoining Drift and Host Rock 
Plotted for the (a) Matrix, (c) Fracture, and (e) Matrix + Fracture Continuum at the 
P2ER8C6 Location in the Tptpul (tsw33) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. A positive value of mass flux corresponds to vertically downward flow. 
These fluxes are the result of line-averaged heating conditions. 
Figure 6.3-38. Liquid-Phase and Gas-Phase Flux Between the Upper and Lower Half of the Invert 
Plotted for the (a) Matrix, (b) Fracture, and (c) Matrix + Fracture Continuum at the 
P2ER8C6 Location in the Tptpul (tsw33) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Also plotted is (f) the total (gas-phase + liquid-phase) mass flux for the 
matrix + fracture continua. A positive value of mass flux corresponds to flux out of the invert. Also plotted 
is the liquid-phase saturation for the (b) matrix and (d) fracture continuum. These fluxes are the result of 
line-averaged heating conditions. 
Figure 6.3-39. Liquid-Phase and Gas-Phase Flux Between the Invert and Adjoining Drift and Host Rock 
Plotted for the (a) Matrix, (c) Fracture, and (e) Matrix + Fracture Continuum at the 
P2WR8C8 Location in the Tptpmn (tsw34) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. A positive value of mass flux corresponds to vertically downward flow. 
These fluxes are the result of line-averaged heating conditions. 
Figure 6.3-40. Liquid-Phase and Gas-Phase Flux Between the Upper and Lower Half of the Invert 
Plotted for the (a) Matrix, (b) Fracture, and (c) Matrix + Fracture Continuum at the 
P2WR8C8 Location in the Tptpmn (tsw34) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Also plotted is (f) the total (gas-phase + liquid-phase) mass flux for the 
matrix + fracture continua. A positive value of mass flux corresponds to flux out of the invert. Also plotted 
is the liquid-phase saturation for the (b) matrix and (d) fracture continuum. These fluxes are the result of 
line-averaged heating conditions. 
Figure 6.3-41. Liquid-Phase and Gas-Phase Flux Between the Invert and Adjoining Drift and Host Rock 
Plotted for the (a) Matrix, (c) Fracture, and (e) Matrix + Fracture Continuum at the 
P2WR5C10 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. A positive value of mass flux corresponds to vertically downward flow. 
These fluxes are the result of line-averaged heating conditions. 
Figure 6.3-42. Liquid-Phase and Gas-Phase Flux Between the Upper and Lower Half of the Invert 
Plotted for the (a) Matrix, (b) Fracture, and (c) Matrix + Fracture Continuum at the 
P2WR5C10 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Also plotted is (f) the total (gas-phase + liquid-phase) mass flux for the 
matrix + fracture continua. A positive value of mass flux corresponds to flux out of the invert. Liquid-
phase saturation for the (b) matrix and (d) fracture continuum is also plotted. These fluxes are the result of 
line-averaged heating conditions. 
Figure 6.3-43. Liquid-Phase and Gas-Phase Flux Between the Invert and Adjoining Drift and Host Rock 
Plotted for the (a) Matrix, (c) Fracture, and (e) Matrix + Fracture Continuum at the 
P3R8C13 Location in the Tptpln (tsw36) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. A positive value of mass flux corresponds to vertically downward flow. 
These fluxes are the result of line-averaged heating conditions. 
Figure 6.3-44. Liquid-Phase and Gas-Phase Flux Between the Upper and Lower Half of the Invert 
Plotted for the (a) Matrix, (b) Fracture, and (c) Matrix + Fracture Continuum at the 
P3R8C13 Location in the Tptpln (tsw36) Unit 
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Table 6.3-33. Peak Values of Liquid-Phase and Gas-Phase Flux for the Matrix and Fracture Continuum 
Given for t > 50 Years at Two Different Interfaces 
LDTH Mass Flux (kg/yr/m) 
Submodel 
Location 
Matrix Fracture Matrix + Fracture 
(Host-Rock 
Unit) Interface 
Liquid-
Phase 
Gas-
Phase 
Liquid-
Phase 
Gas-
Phase 
Liquid-
Phase 
Gas-
Phase 
P2ER8C6 
Tptpul 
(tsw33) 
Invert to drift 
+ host rock -74.18 5.57 49.92 48.95 -37.15 53.73 
Upper to 
lower invert -40.77 0.33 0.00 47.96 -40.77 48.29 
P2WR8C8 
Tptpmn 
(tsw34) 
Invert to drift 
+ host rock -27.25 3.25 27.29 23.19 -14.11 25.36 
Upper to 
lower invert -35.06 0.40 0.00 35.02 -35.06 35.41 
P2WR5C10 
Tptpll 
(tsw33) 
Invert to drift 
+ host rock -28.07 4.47 3.93 30.57 -28.07 33.09 
Upper to 
lower invert -30.05 0.46 0.00 33.94 -30.05 34.41 
P3R8C13 
Tptpln 
(tsw36) 
Invert to drift 
+ host rock -34.31 3.09 24.78 30.87 -17.77 32.92 
Upper to 
lower invert -34.66 0.42 0.00 34.42 -34.66 34.84 
NOTE: Values are given for t > 50 years at two different interfaces, including (1) between the invert 
and the adjoining drift and host rock and (2) between the upper and lower halves of the invert. 
The mass fluxes are given for four typical locations in the repository. These fluxes, which are 
the result of line-averaged heating conditions, are given in kg/yr per meter of drift. Because 
peak mass fluxes can occur at different times for the matrix and fracture, the sum of the peak 
matrix and fracture fluxes may not be equal to the peak matrix + fracture flux. These values 
are based on data plotted in Figures 6.3-37, 6.3-39, 6.3-41 and 6.3-43. 
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Table 6.3-34. Peak Values of Liquid-Phase and Gas-Phase Flux for the Matrix and Fracture Continuum 
Given for t > 100 Years at Two Different Interfaces 
LDTH Mass Flux (kg/yr/m) 
Submodel 
Location 
Matrix Fracture Matrix + Fracture 
(Host-Rock 
Unit) Interface 
Liquid-
Phase 
Gas-
Phase 
Liquid-
Phase 
Gas-
Phase 
Liquid-
Phase 
Gas-
Phase 
P2ER8C6 
Tptpul 
(tsw33) 
Invert to drift + 
host rock -8.04 0.88 1.39 7.08 -7.97 7.91 
Upper to lower 
invert -8.34 0.04 0.00 8.30 -8.34 8.33 
P2WR8C8 
Tptpmn 
(tsw34) 
Invert to drift + 
host rock -0.18 0.76 0.00 -0.79 -0.18 0.18 
Upper to lower 
invert -1.89 -0.03 0.00 1.89 -1.89 1.89 
P2WR5C10 
Tptpll 
(tsw33) 
Invert to drift + 
host rock -1.87 0.62 0.02 1.42 -1.87 1.84 
Upper to lower 
invert -2.77 0.03 0.00 2.75 -2.77 2.77 
P3R8C13 
Tptpln 
(tsw36) 
Invert to drift + 
host rock -0.31 0.66 0.00 -0.69 -0.31 0.31 
Upper to lower 
invert -0.91 0.02 0.00 0.90 -0.91 0.91 
NOTE: Values are given for t > 100 years at two different interfaces, including (1) between the 
invert and the adjoining drift and host rock and (2) between the upper and lower halves of 
the invert. The mass fluxes are given for four typical locations in the repository. These 
fluxes, which are the result of line-averaged heating conditions, are given in kg/yr per 
meter of drift. Because the peak mass fluxes can occur at different times for the matrix 
and fracture, the sum of the peak matrix and fracture fluxes may not be equal to the peak 
matrix + fracture flux. These values are based on data plotted in Figures 6.3-37, 6.3-39, 
6.3-41 and 6.3-43. 
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Source: See Table XIII-1. 
NOTE: The locations (P2ER8C6, P2WR8C8, P2WR5C10, and P3R8C13) are shown in Figure 6.3-1. Positive 
values of phase change correspond to evaporation, while negative values correspond to condensation. 
Figure 6.3-45. Phase Change (a, c, e, and g) in the Matrix and Fracture Continuum and Liquid-Phase 
Flux (b, d, f, h) in the Fracture Continuum Plotted for the Lower Two Gridblocks in the 
Invert at Four Locations in the Repository 
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As discussed above, during the rewetting period the return capillary-driven liquid-phase flux (in 
the matrix continuum) is greater than the outward gas-phase flux of water vapor (in the matrix 
and fracture continuum) leaving the invert. The total (or net) mass flux of water (liquid-phase 
plus gas-phase) is plotted in Figures 6.3-37f, 6.3-39f, 6.3-41f, and 6.3-43f. During the rewetting 
period, the magnitude of this net mass flux is a small negative value (which is too small to be 
readily apparent in these figures), indicating that mass is returning to the invert. To clearly 
demonstrate that water is returning to the invert during the rewetting period, and that a mass 
balance of water is achieved in the invert, the net accumulated mass flux of water out of the 
invert is plotted in Figures 6.3-46 through 6.3-49; these figures also plot the liquid-phase 
saturation history in the invert. Note that this rewetting process occurs over a very long period, 
while the initial dryout process occurred over a very short period at the beginning of the 
postclosure period (t > 50 yr). Note also that all time histories are plotted with a logarithmic 
time scale. During the initial dryout period, the liquid-phase saturation (very quickly) reaches its 
minimum value just as the net accumulated mass flux out of the invert has reached its maximum 
value. During the sustained dryout period, the liquid-phase saturation in the invert remains 
nearly constant, just as the net accumulated mass flux out of the invert remains nearly constant. 
During the rewetting period, the liquid-phase saturation in the invert gradually rises, just as the 
net accumulated mass flux out of the invert gradually declines. 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Increasing net accumulated mass flux indicates drying, while decreasing net 
accumulated mass flux indicates rewetting. 
Figure 6.3-46. Mass Balance in the Invert Shown by Plotting (a) Liquid-Phase Saturation in the Fracture 
and Matrix Continuum in the Invert and (b) the Net Accumulated Mass Flux out of the 
Invert at the P2ER8C6 Location in the Tptpul (tsw33) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Increasing net accumulated mass flux indicates drying, while decreasing net 
accumulated mass flux indicates rewetting. 
Figure 6.3-47. Mass Balance in the Invert Shown by Plotting (a) Liquid-Phase Saturation in the Fracture 
and Matrix Continuum in the Invert and (b) the Net Accumulated Mass Flux out of the 
Invert at the P2WR8C8 Location in the Tptpmn (tsw34) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Increasing net accumulated mass flux indicates drying, while decreasing net 
accumulated mass flux indicates rewetting. 
Figure 6.3-48. Mass Balance in the Invert Shown by Plotting (a) Liquid-Phase Saturation in the Fracture 
and Matrix Continuum in the Invert and (b) the Net Accumulated Mass Flux out of the 
Invert at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Increasing net accumulated mass flux indicates drying, while decreasing net 
accumulated mass flux indicates rewetting. 
Figure 6.3-49. Mass Balance in the Invert Shown by Plotting (a) Liquid-Phase Saturation in the Fracture 
and Matrix Continuum in the Invert and (b) the Net Accumulated Mass Flux out of the 
Invert at the P3R8C13 Location in the Tptpln (tsw36) Unit 
6.3.4 Combined Influences of Percolation-Flux and Host-Rock Thermal Conductivity 
Uncertainty on the TSPA-LA Base Case 
The purpose of this section is to combine the analyses discussed in Sections 6.3.1.1 and 6.3.2.2. 
Section 6.3.2.2 describes a sensitivity analysis of the influence of host-rock thermal conductivity 
uncertainty on thermal-hydrologic behavior in the repository. The analysis in Section 6.3.2.2 
was conducted at four locations in the repository (Figure 6.3-1), which cover all four of the 
host-rock units (Table 6.3-3). This analysis does not explicitly address thermal-hydrologic 
behavior across the entire repository. These four repository locations (P2ER8C6, P2WR8C8, 
P2WR5C10, and P3R8C13) were selected because their respective values of percolation flux are 
relatively close to the repository-wide averages for the mean infiltration-flux case (Tables 6.3-4, 
6.3-5, and 6.3-9). Section 6.3.1.1 describes the MSTHM TSPA-LA base-case calculations of the 
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entire repository for the three infiltration-flux cases (lower, mean, and upper). Thus, 
Section 6.3.1.1 addresses the influence of percolation-flux uncertainty on the MSTHM 
TSPA-LA base-case calculations for the entire repository. The purpose of this subsection 
(Section 6.3.4) is to address the combined influences of percolation-flux and host-rock thermal 
conductivity uncertainty on the MSTHM TSPA-LA base-case calculations for the entire 
repository. 
As discussed in Section 6.3.2, the two most significant sources of uncertainty for the output of 
the MSTHM are host-rock thermal conductivity and percolation flux. Percolation-flux 
uncertainty is addressed in Section 6.3.1.1 of this report with the use of the three infiltration-flux 
cases, which are called the lower-, mean, and upper-bound infiltration-flux cases (Table 6.3-4). 
The three cases in Section 6.3.1.1 use the mean thermal conductivity values (Table 6.3-23) for 
the four host-rock units (also called repository units), as well as for all of the non-repository 
units. The probabilities of the three infiltration-flux cases are provided in Table 6.3-35, which is 
based on Table 6.3-2 of Section 6.3.2 of Analysis of Infiltration Uncertainty (BSC 2003 
[DIRS 165991]), excluding the contingency area. The sensitivity of thermohydrologic behavior 
to host-rock thermal conductivity uncertainty is addressed for approximately 1 standard 
deviation about the mean values (Table 6.3-23). 
Table 6.3-35. Probabilities of the Three Infiltration-Flux Cases 
Infiltration-Flux Case Probability 
Lower 0.24 
Mean 0.41 
Upper 0.35 
Total 1.00 
Source: Table 6.3-2 of BSC 2003 [DIRS 165991]. 
The three host-rock thermal conductivity cases, which are called the low-, mean, and high-
thermal conductivity cases, are used to address parametric uncertainty. The guidelines for 
TSPA-LA define certain types of uncertainty (BSC 2002 [DIRS 158794], Section 4.1). 
Variability, also referred to as aleatory uncertainty, arises due to natural randomness or 
heterogeneity. This first type of uncertainty cannot be reduced through further testing and data 
collection; it can only be better characterized. Thus, aleatory uncertainty is also referred to as 
irreducible uncertainty. The second type of uncertainty, which is referred to as epistemic 
uncertainty, arises from lack of knowledge about a parameter because the data are limited or 
there are alternative interpretations of the available data. This second type of uncertainty is also 
called reducible uncertainty because the state of knowledge can be improved with further testing 
or data collection. 
Section 6.2.4 describes the manner in which the MSTHM combines the results from the four 
submodel types. The SMT submodel (Section 6.2.5) is used to determine the repository-scale 
variations in host-rock temperature as affected by the mountain-scale thermal-property 
distribution, the overburden-thickness distribution, and the edge-cooling effect, which is strongly 
affected by the overall shape of the repository area. The LDTH submodels (Section 6.2.6) are 
used to determine the influence of local conditions on thermal-hydrologic behavior, including 
percolation flux and the thermal and hydrologic properties of the local host-rock unit. 
Percolation-flux uncertainty is incorporated in only the LDTH submodels. In the same fashion, 
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host-rock thermal conductivity uncertainty is also incorporated in only the LDTH submodels. 
The SMT submodel does not incorporate host-rock thermal conductivity uncertainty because it 
would only potentially influence the rate at which the edge-cooling effect propagates from the 
edges towards the central region of the repository. At the scale at which the edge-cooling effect 
propagates, the natural randomness of host-rock thermal conductivity distribution tends to 
average out, allowing, in effect, the mean thermal conductivity values to control the rate at which 
the edge-cooling effective propagates in those respective units. Note that for the low-thermal 
conductivity case, Kth is equal to the mean minus one standard deviation for all of the host-rock 
units. Similarly, for the high-thermal conductivity case, Kth is equal to the mean plus one 
standard deviation for all of the host-rock units: (1) Tptpul (tsw33), (2) Tptpmn (tsw34), (3) 
Tptpll (tsw35), and (4) Tptpln (tsw36 and tsw37). 
In Thermal Conductivity of the Potential Repository Horizon (BSC 2004 [DIRS 169854]), fifty 
equally likely sets of three-dimensional thermal conductivity fields (or realizations) are 
generated for the four host-rock units. Each field has a mean thermal conductivity, ij, and a 
standard deviation, sij, for local variability in thermal conductivity (e.g., see Figure 6-31 of BSC 
2004 [DIRS 169854]), where i = 1, 2, 3, 4 corresponds to the four host-rock units and j = 1, 2,, 
50 corresponds to the fifty fields (or realizations). Values for 
50
1 

= .ij
50
i 
j=1 
and 
si =
si,15 +si,30 +si,45 
3 
are reported in Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc). 
The quantity si 
is a reasonable estimator of drift-scale variability and uncertainty, and is 
appropriate for use in the LDTH submodels. 
Calculations performed using i 
 si, i, and i 
+ si 
(Table 6.3-20) raise the question concerning 
how much weight (i.e., probability in the epistemic sense) should be applied to these three host-
rock thermal conductivity cases. Probability distributions for ij for the fifty fields are presented 
in Thermal Conductivity of the Potential Repository Horizon (e.g., see lower right plot in Figure 
6-31 of BSC 2004 [DIRS 169854]). These distributions are very narrow, with i si 
tending to 
be close to the extremes of the presented distributions. As presented by Thermal Conductivity of 
the Potential Repository Horizon (BSC 2004 [DIRS 169854]), the distributions for i, probably 
underestimate the uncertainty in i 
(i.e., the value for a single effective thermal conductivity to 
be used over an entire host-rock unit) because they are based only on the fifty fields generated 
without including potential epistemic uncertainties, such as (1) those associated with the quality 
of the observational data underlying the generation of the fields, (2) those associated with the 
model used in determining thermal conductivity values, and (3) the appropriateness of the 
geostatistical model used in the generation of the thermal conductivity fields. 
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Therefore, neither i 
 si 
nor i 
+ si 
represents extreme or unlikely values for the appropriate 
effective (i.e., spatially averaged) thermal conductivity values to be applied to the respective 
host-rock units in the LDTH submodels. Furthermore, neither i 
 si 
nor i 
+ si 
is more or less 
likely than i 
to be the appropriate value to be applied for effective thermal conductivity in the 
host-rock units in the LDTH submodels. As a result of this argument, each alternative (i 
 si, 
i, and i 
+ si) can be assigned the same probability (i.e., one in three), which is shown in Table 
6.3-36. 
Combining the probabilities of the three infiltration-flux cases (Table 6.3-35) and the equal (one 
in three) probabilities of the three host-rock thermal conductivity cases results in a three-by-three 
matrix of nine percolation-flux host-rock thermal conductivity cases provided in Table 6.3-36. 
Repository-wide MSTHM calculations were conducted for five of these nine cases, including the 
three infiltration-flux cases conducted with the mean thermal conductivity values 
(Section 6.3.1.1), as well as the two cases with the extreme combinations of percolation flux and 
host-rock thermal conductivity: (1) the lower-bound infiltration-flux, low host-rock thermal 
conductivity case, and (2) the upper-bound infiltration-flux, high host-rock thermal conductivity 
case. The four cases for which repository-wide calculations were not conducted are shown in 
italics in Table 6.3-36. 
Table 6.3-36. Probabilities of the Combinations of the Three Infiltration-Flux Cases and the Three 
Host-Rock Thermal Conductivity Cases 
Infiltration-Flux Case 
Probability 
Host-Rock Thermal Conductivity Case 
All 
Low 
(Mean  1 SD) Mean 
High 
(Mean + 1 SD) 
All 1.0000 0.33333 0.33333 0.33333 
Lower 0.2400 0.08000 0.08000 0.08000 
Mean 0.4100 0.13667 0.13667 0.13667 
Upper 0.3500 0.11666 0.11666 0.11666 
NOTE: SD stands for standard deviation. Repository-wide MSTHM calculations 
were not conducted for the four cases shown in italics. 
Figure 6.3-50 outlines how the four cases for which repository-wide MSTHM calculations were 
not made (shown in italics in Table 6.3-36) are addressed by the other five cases. First, as was 
shown in Sections 6.3.2.1 and 6.3.2.2, low percolation flux and low host-rock thermal 
conductivity affect thermal-hydrologic behavior in a similar fashion, which is to create hotter 
drier conditions in the adjoining host rock, and high percolation flux and high host-rock thermal 
conductivity affect thermal-hydrologic behavior similarly, by creating cooler, less dry conditions 
in the adjoining host rock. Accordingly, there are two cases for which percolation flux and host-
rock thermal conductivity have opposing effects: (1) the lower-bound infiltration-flux case with 
high host-rock thermal conductivity and (2) the upper-bound infiltration-flux case with low 
host-rock thermal conductivity. For both of these cases, the effects of percolation flux and 
host-rock thermal conductivity tend to be mutually canceling and the net effect is equivalent to 
having the mean infiltration-flux case with mean host-rock thermal conductivity. These two 
cases appear in the upper right and lower left corners of Figure 6.3-50. The arrows from the 
upper right and lower left corners that point to the center of Figure 6.3-50 are depicting how the 
mean infiltration-flux case with mean host-rock thermal conductivity is the surrogate case for 
these two corner cases. Thus, the probabilities (Table 6.3-36) for the lower-bound 
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infiltration-flux case with high host-rock thermal conductivity (0.08000) and for the upper-bound 
infiltration flux with low thermal conductivity (0.11666) are added to that of the mean 
infiltration-flux case with mean host-rock thermal conductivity (0.13667), resulting in a 
combined probability of 0.33333, as shown in Table 6.3-37. 
Thermal-conductivity case 
Low High 
(Mean  1 SD) Mean (Mean +1 SD) 
Lower 
Infiltration-flux case Mean 
Upper 
NOTES: The open circles correspond to the cases for which repository-wide MSTHM calculations were not 
conducted. The filled circles correspond to the cases for which repository-wide MSTHM calculations have 
been conducted. 
Figure 6.3-50. Regrouping of the Three-by-Three Matrix of Infiltration Flux and Host-Rock Thermal 
Conductivity Cases 
Table 6.3-37. Probabilities of the Combinations of the Three Infiltration-Flux Cases and the Three 
Host-Rock Thermal Conductivity Cases after the Regrouping Shown in Figure 6.3-50 
Infiltration-Flux 
Case 
Probability 
Host-Rock Thermal Conductivity Case 
All 
Low 
(Mean  1 SD) Mean 
High 
(Mean + 1 SD) 
All 1.0000 0.33333 0.33333 0.33333 
Lower 0.2400 0.08000 0.21667 
Mean 0.4100 0.33333 
Upper 0.3500 0.25334 0.11666 
NOTE: SD stands for standard deviation. 
As discussed above, low percolation flux and low host-rock thermal conductivity affect 
thermal-hydrologic behavior in a similar fashion, which is to promote hotter drier conditions in 
the adjoining host rock. Accordingly, the lower-bound infiltration-flux case with mean host-rock 
thermal conductivity is the surrogate case for the mean infiltration-flux case with low host-
rock thermal conductivity. This substitution is depicted in Figure 6.3-50 by the arrow pointing 
from the left column in the middle row to the middle column in the upper row. Thus, the 
probability (Table 6.3-36) for the mean infiltration-flux case with low host-rock thermal 
conductivity (0.13667) is added to that of the lower-bound infiltration-flux case with mean host-
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rock thermal conductivity (0.08000), resulting in a combined probability of 0.21667, as shown in 
Table 6.3-37. 
As discussed above, high percolation flux and high host-rock thermal conductivity affect 
thermal-hydrologic behavior in a similar fashion, which is to promote cooler, less dry conditions 
in the adjoining host rock. Accordingly, the upper-bound infiltration-flux case with mean 
host-rock thermal conductivity is the surrogate case for the mean infiltration-flux case with 
high host-rock thermal conductivity. This substitution is depicted in Figure 6.3-50 by the arrow 
pointing from the right column in the middle row to the middle column in the lower row. Thus, 
the probability (Table 6.3-36) for the mean infiltration-flux case with high host-rock thermal 
conductivity (0.13667) is added to that of the upper-bound infiltration-flux case with mean 
host-rock thermal conductivity (0.11666), resulting in a combined probability of 0.25334, as 
shown in Table 6.3-37. 
Figure 6.3-51 gives the complementary cumulative distribution function (CCDF) for the peak 
temperature on the drift wall and on waste packages for the five infiltration-flux/host-rock 
thermal conductivity cases; these CCDFs are for all waste packages over the entire repository 
area. Table 6.3-38 gives the coolest, median, and hottest peak drift-wall and waste package 
temperatures for these five cases. Because there are 2874 locations in the MSTHM (Table 6.2-1) 
and eight different waste packages that are represented at each location, there are a total of 
22,992 waste package histories provided in each of the five cases for which repository-wide 
MSTHM calculations were conducted. For the upper-bound infiltration-flux case with high 
host-rock thermal conductivity, there are 22 waste package histories for which the peak drift-wall 
temperature is less than the boiling point (96C). These 22 histories represent 0.10 percent of the 
22,992 histories in that case. Because that case has a probability of 0.11666 (Table 6.3-37), 
these 22 waste package histories are representative of only 0.01 percent of all waste packages in 
the repository. Thus, for a total of 11,184 waste packages in the repository (Table 4.1-2), there is 
a probability of 1.0 that a single waste package will never experience boiling at the drift wall. 
For the lower-bound infiltration-flux case with low host-rock thermal conductivity, there are 106 
waste package histories for which the peak waste package temperature is greater than 200C. 
Because the probability of this case is 0.08000, these 106 histories are representative of only 0.04 
percent of all waste packages in the repository. Thus, for a total of 11,184 waste packages in the 
repository (Table 4.1-2), only four waste packages are predicted to have a peak temperature in 
excess of 200 C. 
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Source: See Table XIII-1. 
NOTE: These five cases cover the range of percolation-flux and host-rock thermal conductivity uncertainty 
addressed in this report. 
Figure 6.3-51. Complementary Cumulative Distribution Function (CCDF) for Peak Temperature on the 
(a) Drift Wall and on the (b) Waste Packages Plotted for Five Cases 
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Table 6.3-38. Peak Drift-Wall and Waste Package Temperatures Summarized for Five Cases 
Peak Drift-Wall Temperature Peak Waste Package Temperature 
Case 
(C) (C) 
Coolest Median Hottest Coolest Median Hottest 
Lower-bound infiltration-flux, 
low thermal conductivity 
119.1 152.9 175.2 130.1 173.6 203.1 
Lower-bound infiltration-flux, 105.7 135.4 154.8 116.3 156.0 182.9 
mean thermal conductivity 
Mean infiltration-flux, mean 105.0 133.0 144.2 115.6 153.3 172.0 
thermal conductivity 
Upper-bound infiltration-flux, 98.6 131.6 142.5 108.6 152.1 170.8 
mean thermal conductivity 
Upper-bound infiltration-flux, 92.3 119.6 129.3 102.0 139.5 157.2 
high thermal conductivity 
NOTE: These cases cover the range of percolation-flux and host-rock thermal conductivity uncertainty 
addressed in this report. This table is based on Figure 6.3-51. These values are data plotted in Figure 
6.3-51. 
Figure 6.3-52a and Table 6.3-39 give the complementary cumulative distribution function 
(CCDF) for the time when boiling at the drift wall ceases for the five infiltration-flux host-rock 
thermal conductivity cases; these CCDFs are for all waste package locations throughout the 
repository area. As was the case for peak temperatures, the boiling period duration increases 
with decreasing percolation flux and with decreasing host-rock thermal conductivity. The 
median waste package experiences boiling at the drift wall for 721 years, and there is a broad 
range of duration of boiling at the drift wall. There is a probability of less than 1.0 that a single 
waste package will never experience boiling at the drift, while the waste package at the hottest, 
driest location in the repository may experience boiling at the drift wall for up to 2,176 years. 
Figure 6.3-52b and Table 6.3-40 provide the complementary cumulative distribution function 
(CCDF) for the maximum lateral extent of the boiling point isotherm for the five cases. As was 
the case for the peak temperatures and boiling period duration, the maximum lateral extent of 
boiling increases with decreasing percolation flux and with decreasing host-rock thermal 
conductivity. The median waste package has a maximum lateral extent of boiling of 7.9 m, 
which is 5.15 m beyond the springline of the drift. There is a probability of less than 1.0 that a 
single waste package will never experience boiling in the host rock, while the waste package at 
the hottest, driest location in the repository may have a maximum lateral extent of boiling of 27.9 
m, which represents 69 percent of the lateral extent between the emplacement drift centerline and 
the midplane in the center of the rock pillar between drifts. For the lower-bound infiltration-flux, 
low host-rock-thermal conductivity case, 10 percent of the waste package histories have a 
maximum lateral extent of boiling that exceeds 19 m. Because the probability of this case is 
0.08000 (Table 6.3-37), this is representative of 0.8 percent of the waste packages in the 
repository. Thus, for a total of 11,184 waste packages in the repository (Table 4.1-2), 89 waste 
packages are expected to have a maximum lateral extent of boiling that exceeds 19 m. 
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Source: See Table XIII-1. 
NOTE: These five cases cover the range of percolation-flux and host-rock thermal conductivity uncertainty 
addressed in this report. 
Figure 6.3-52. Complementary Cumulative Distribution Functions (CCDF) for (a) the Time When Boiling 
at the Drift Wall Ceases and (b) the Maximum Lateral Extent of the Boiling-Point Isotherm 
(96C) from the Drift Centerline, Plotted for Five Cases 
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Table 6.3-39. Time When Boiling Ceases at the Drift Wall Summarized for Five Cases 
Infiltration-Flux, Host-
Time When Boiling at the Drift Wall Ceases 
(years) 
Rock Thermal 10 30 70 90 
Conductivity Case Shortest Percentile Percentile Median Percentile Percentile Longest 
Lower-bound infiltration-192.6 555.3 861.6 1125.4 1447.4 1862.7 2176.5 
flux, low thermal 
conductivity 
Lower-bound infiltration-130.2 349.9 630.9 859.6 1122.5 1453.3 1734.6 
flux, mean thermal 
conductivity 
Mean infiltration-flux, 127.2 297.5 535.8 721.0 870.6 1006.5 1356.0 
mean thermal conductivity 
Upper-bound infiltration-97.7 267.7 471.6 643.7 768.6 887.2 1162.9 
flux, mean thermal 
conductivity 
Upper-bound infiltration-NAa 175.7 281.6 430.4 568.9 689.5 859.5 
flux, high thermal 
conductivity 
a 
22 out of 22,992 waste package/location combinations (or 0.1 percent of the total) never experience boiling at the 
drift wall. 
NOTE: These cases cover the range of percolation-flux and host-rock thermal conductivity uncertainty addressed in 
this report. This table is based on data plotted in Figure 6.3-52a. 
Table 6.3-40. Maximum Lateral Extent of the Boiling-Point Isotherm (96C) Measured from the Drift 
Centerline, Summarized for Five Cases 
Infiltration-Flux, Host-
Maximum Lateral Extent of Boiling (T > 96C) 
(m) 
Rock Thermal 10 30 70 90 
Conductivity Case Least Percentile Percentile Median Percentile Percentile Greatest 
Lower-bound infiltration-6.9 8.8 10.2 11.1 13.2 19.0 27.9 
flux, low thermal 
conductivity 
Lower-bound infiltration-5.6 7.1 7.9 8.4 9.4 12.3 17.8 
flux, mean thermal 
conductivity 
Mean infiltration-flux, 5.3 6.7 7.5 7.9 8.2 8.7 9.9 
mean thermal conductivity 
Upper-bound infiltration-5.1 6.5 7.3 7.7 7.9 8.1 9.0 
flux, mean thermal 
conductivity 
Upper-bound infiltration-4.1a 5.3 5.9 6.1 6.4 6.7 7.2 
flux, high thermal 
conductivity 
a 
22 out of 22,992 waste package/location combinations (or 0.1 percent of the total) never experience boiling at the 
drift wall; therefore, for those locations, the lateral extent of boiling is inside the emplacement drift. 
NOTE: These cases cover the range of percolation-flux and host-rock thermal conductivity uncertainty addressed in 
this report. This table is based on data plotted in Figure 6.3-52b. 
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6.3.5 Summary of the Range of Thermal-Hydrologic Conditions for the TSPA-LA Base 
Case 
In Section 6.3, the ranges of thermal-hydrologic conditions across the repository are described 
for the five infiltration-flux host-rock thermal conductivity cases addressed in this report (Table 
6.3-37). Figure 6.3-53 gives the corresponding ranges of temperature and relativehumidity 
histories for all waste packages. The plots in Figure 6.3-53, sometimes referred to as horsetail 
plots, also break down the ranges in temperature and relativehumidity histories into CSNF and 
DHLW groupings. The peak temperatures are predicted to be 203.1C and 189.4C for the 
hottest CSNF and DHLW waste packages, respectively. The peak temperatures are predicted to 
be 107.7C and 102.0C for the coolest CSNF and DHLW waste packages, respectively. Table 
6.3-39 shows that the predicted range in the time when boiling at the drift wall ceases ranges 
from no boiling to 2176.5 years. The ranges in thermohydrologic conditions shown in 
Figure 6.3-53 incorporate the influence of percolation-flux uncertainty, as it is represented in the 
lower, mean, and upper infiltration-flux cases. The ranges in thermohydrologic conditions 
shown in Figure 6.3-53 also incorporate the influence of host-rock thermal conductivity 
uncertainty. 
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Source: See Table XIII-1. 
NOTE: The ranges include the five cases listed in Table 6.3-37: (1) lower infiltration-flux, low thermal conductivity 
case, (2) lower infiltration-flux, mean thermal conductivity case, (3) mean infiltration-flux, mean thermal 
conductivity case, (4) upper infiltration-flux, mean thermal conductivity case, and (5) upper infiltration-flux, 
high thermal conductivity case. 
Figure 6.3-53. Range of Waste Package Temperature and Relative Humidity Histories for all Waste 
Packages (a, b), for All CSNF Waste Packages (c, d), and for All DHLW Waste Packages 
(e, f) 
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6.3.6 Relationship Between Relative Humidity on the Waste Package and Drip Shield 
and Temperature on the Drift Wall 
For the purpose of conducting in-drift geochemical analyses, it is useful to extract 
thermal-hydrologic output that quantifies the relationship between when boiling conditions cease 
at the drift wall (and when seepage can potentially commence) and the corresponding relative 
humidity on the drip-shield and waste package surfaces. Note that the boiling temperature at the 
repository horizon is 96oC. Figure 6.3-54 is a plot of the complementary cumulative distribution 
function (CCDF) of the relative humidity on the drip shield and waste package that corresponds 
to when the drift-wall temperature is 96oC. Figure 6.3-54 also plots the CCDF of drip-shield and 
waste package relative humidity that corresponds to when the drift-wall temperature is 100oC. 
Note that in Section 6.5.2.2 of Abstraction of Drift Seepage (BSC 2004 [DIRS 169131]), it is 
recommended that a threshold temperature of 100oC, which is higher than the nominal boiling 
point of 96oC, be used to define the duration of boiling for abstraction of drift seepage for intact 
drifts. Note also that the CCDF plots in Figure 6.3-54 account for the influence of parametric 
uncertainty of host-rock thermal conductivity and percolation flux as is discussed in Section 
6.3.4. The probabilities of the five infiltration-flux/host-rock thermal conductivity cases, 
summarized in Table 6.3-37, were utilized as weighting factors for those respective cases. Table 
6.3-41 summarizes the data given in Figure 6.3-54. 
Source: See Table XIII-1. 
NOTE: The CCDF corresponds to when the drift-wall temperature is 96oC and 100oC. These plots account for the 
five infiltration-flux/host-rock thermal conductivity cases discussed in Section 6.3.4, using the probabilities 
summarized in Table 6.3-37. 
Figure 6.3-54. The Complementary Cumulative Distribution Function (CCDF) for Relative Humidity on 
the Drip Shield and Waste Package 
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Table 6.3-41. Relative Humidity on the Drip Shield and Waste Package Corresponding to When the 
Drift-Wall Temperature is 96oC and 100oC, Summarized for Figure 6.3-54. 
Drift-wall 
temperature 
(oC) 
Drip-shield relative humidity (%) Waste package relative humidity (%) 
Lowest Median Highest Lowest Median Highest 
96 47.76 72.61 89.76 36.19 67.32 88.62 
100 43.08 65.62 76.20 32.92 60.36 74.60 
6.3.7 The Influence of a Low-Probability-Seismic Collapsed-Drift Scenario on In-Drift 
Thermal-Hydrologic Conditions 
The influence of a low-probability-seismic collapsed-drift scenario on in-drift 
thermal-hydrologic conditions is considered for the P2WR5C10 location, which is a typical 
location at the center of the repository. Throughout Section 6.3, the P2WR5C10 location (see 
Figure 6.3-1 for location) is used for examining the sensitivity of thermal-hydrologic conditions 
in emplacement drifts to various sources of uncertainty and variability. This location is 
representative of a typical location in the predominant host-rock unit, which is the Tptpll (tsw35) 
unit, close to the center of the repository area, and because the local percolation-flux values 
(Table 6.3-9) are close to the repository averages for the present-day, monsoonal, and glacial 
climates (Table 6.3-4) for the mean infiltration-flux case. 
Sections 6.2.9, 6.2.10, and 6.2.11 describe the changes to the MSTHM submodels that are 
required to model the influence of drift collapse. Although a full MSTHM calculation involves 
submodels located at 108 locations spread across the entire repository (Figure 6.2-3), it is only 
necessary to conduct a MSTHM calculation at a single repository location for the purpose of 
analyzing the influence of drift collapse on in-drift thermal-hydrologic conditions. The 
reasoning for this is that the purpose of this section (Section 6.3.7) is to generate tables of 
deltas, which are the differences between the thermal-hydrologic results for the case with drift 
collapse and those for the intact (nominal) case with no drift collapse. These differences, such as 
the temperature difference (or delta), are entirely dependent on the modified material properties 
within the emplacement drifts. In other words, the differences are insensitive to the local host-
rock unit or local percolation flux. Because of this lack of sensitivity to conditions outside of the 
drift, these calculated differences (or deltas) can then be applied to the MSTHM results of the 
five nominal cases with no drift collapse, which are summarized in Table 6.3-37. These 
differences (deltas) are determined for the eight different waste packages addressed by the 
MSTHM (Figure 6.2-2 and Table 6.3-13). 
The low-probability-seismic scenario causes severe shaking that fails the host rock (breaking it 
into rubbelized blocks) out to a diameter of 11 m. This scenario is shown in Figure 139f of Drift 
Degradation Analysis (BSC 2004 [DIRS 166107]). The result of this is a host-rock rubble zone 
that extends from the outer surface of the drip shield out to the modified drift wall, which is 
the interface between rubbelized host rock and intact host rock. A schematic of this case is given 
in Figure 6.4-22 of Abstraction of Drift Seepage (BSC 2004 [DIRS 169131]). The key 
uncertainty influencing in-drift thermal-hydrologic conditions is the effective thermal 
conductivity Kth of the host-rock rubble. Two Kth cases are considered to address this 
uncertainty: (1) high-Kth case and (2) low-Kth case. On the basis of the discussion in Section 
6.2.10.3, the high- and low-Kth cases are assigned the same probability (of 50 percent). 
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6.3.7.1 In-Drift Thermal-Hydrologic Conditions for the High and Low Thermal 
Conductivity Rubble Cases with Total Drift Collapse 
Figures 6.3-55, 6.3-56, and 6.3-57 show the influence of drift collapse, out to a diameter of 11 m, 
on in-drift thermal-hydrologic conditions for the coolest, average, and hottest waste packages, 
respectively. These three waste packages are the dhlw-l1, bwr1-1, and pwr1-2 waste packages in 
Table 6.3-13 and in Figure 6.2-2. Table 6.3-42 summarizes the peak waste package temperatures 
for the same three waste packages, while Table 6.3-43 summarizes the time when boiling on the 
waste package ceases for these waste packages. For both the high- and low-Kth cases, the 
host-rock rubble functions as an insulator that increases the temperature rise on the drip shield 
(not shown in the figures) and on the waste packages (Figure 6.3-55a, Figure 6.3-56a, and Figure 
6.3-57a), as well as in the invert (Figure 6.3-55b, Figure 6.3-56b, and Figure 6.3-57b). The 
increase in temperature rise, compared to the intact (nominal) case, resulting from drift collapse 
is about twice as great for the low-Kth case as it is for the high-Kth, which is consistent with Kth 
for the low-Kth case being half of that for the high-Kth case (Table 6.3-23). 
The insulating effect of the host-rock rubble substantially extends the duration of boiling 
conditions on the waste packages (Table 6.3-43). The increase in waste package boiling duration 
is about twice as great for the low-Kth case as it is for the high-Kth case. Higher temperatures and 
extended boiling duration in the drift have the effect of substantially extending the period of 
reduced liquid-phase saturation in the invert (Figure 6.3-55d, Figure 6.3-56d, and Figure 
6.3-57d). The liquid-phase saturation in the matrix continuum of the host-rock rubble also 
remains low for a greatly extended period (Figure 6.3-55e, Figure 6.3-56e, and Figure 6.3-57e). 
Higher temperatures and extended boiling duration in the drift also substantially extend the 
period of reduced relative humidity on the drip-shield humidity (not shown in figure) and on the 
waste package (Figure 6.3-55c, Figure 6.3-56c, and Figure 6.3-57c). 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. 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 parameters 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 6.3-55. Thermal-Hydrologic Parameters for the Coolest Waste Package, the 5 DHLW/DOE SNF-
Long (dhlw-l1), Plotted for the Mean Infiltration Flux at the P2WR5C10 Location in the 
Tptpll (tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. 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 parameters 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 6.3-56. Thermal-Hydrologic Parameters for the Average Waste Package, the 44-BWR CSNF 
(bwr1-1), Plotted for the Mean Infiltration Flux at the P2WR5C10 Location in the Tptpll 
(tsw35) Unit 
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Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. 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 parameters 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 6.3-57. Thermal-Hydrologic Parameters for the Hottest Waste Package, the 21-PWR AP CSNF 
(pwr1-2), Plotted for the Mean Infiltration Flux at the P2WR5C10 Location in the Tptpll 
(tsw35) Unit. 
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Table 6.3-42. Peak Waste Package Temperature for the Coolest, Average, and Hottest Package for 
Three Cases at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
Peak Waste Package Temperature 
Waste Package Type (oC) 
Intact-drift (nominal) Collapsed Drift with Collapsed Drift with 
case High-Kth Rubble Low-Kth Rubble 
Coolest Waste Package 136.7 169.3 225.9 
5 DHLW/DOE SNF-Long (dhlwl1) 
WP 
Average Waste Package 159.5 213.2 270.0 
44-BWR CSNF (bwr1-1) WP 
Hottest Waste Package 168.8 223.4 282.2 
21-PWR AP CSNF (pwr1-2) WP 
NOTES: See Figure 6.3-1 for location of the Tptpll. The location of the waste packages is given in Figure 6.2-2 and 
their characteristics listed in Table 6.3-13. 
Cases are evaluated for the mean infiltration flux. 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 host-rock rubble. 
Table 6.3-43. Time When Boiling on the Waste Package Ceases for the Coolest, Average, and 
Hottest Package for Three Cases at the P2WR5C10 Location in the Tptpll (tsw35) Unit 
Time When Boiling on the Waste Package Ceases 
Waste Package Type (yr) 
Intact Drift (Nominal) Collapsed Drift with Collapsed Drift with 
Case High-Kth Rubble Low-Kth Rubble 
Coolest Waste Package 527.8 912.6 1368.9 
5 DHLW/DOE SNF-Long (dhlwl1) 
WP 
Average Waste Package 888.2 1466.0 1898.7 
44-BWR CSNF (bwr1-1) WP 
Hottest Waste Package 995.0 1527.1 1947.2 
21-PWR AP CSNF (pwr1-2) WP 
NOTES: See Figure 6.3-1 for location of the Tptpll. The location of the waste packages is given in Figure 6.2-2 and 
their characteristics listed in Table 6.3-13. 
Cases are evaluated for the mean infiltration flux. 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. 
6.3.7.2 Influence of Bulk Density of Rubble on Thermal-Hydrologic Conditions for 
Low-Probability-Seismic Collapsed-Drift Scenario 
As is discussed in Section 6.2.10.3, the rubble bulk density value used in the LDTH submodels 
(1850 kg/m3) is greater than the value used in the DDT submodels (1608 kg/m3). Note that a 
rubble bulk density value of 1608 kg/m3 is the value that corresponds to a bulking factor of 0.231 
and a bulk density of 1980 kg/m3 (see Table IV-3b and IV-3c of Appendix IV) for the intact 
Tptpll (tsw35) host-rock unit. To assess whether this difference in bulk density is significant, the 
LDTH submodel was rerun for the case where the rubble bulk density is 1608 kg/m3, so that it 
could be compared to the case where the rubble bulk density is 1850 kg/m3. As is evident in 
Figure 6.3-58, which plots the temperature and relative humidity at the crown of the drip shield 
for the low-Kth rubble, the influence of rubble bulk density over this range of 1608 to 1850 kg/m3 
is insignificant. Because steady-state heat flow conditions are quickly established within the 
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rubble, temperature and relative humidity in the drift are insensitive to the bulk density value of 
the rubble. Therefore, the MSTHM calculations are insensitive to the choice of rubble bulk 
density (1850 kg/m3 versus 1608 kg/m3). 
Source: See Table XIII-1. 
NOTE: See Figure 6.3-1 for location. Two cases for bulk density of the host-rock rubble are considered, including: 
(1) bulk density = 1850 kg/m3 and (2) bulk density = 1608 kg/m3. Because these plots are from an LDTH 
submodel, they are representative of line-averaged heating conditions. 
Figure 6.3-58. Temperature and Relative Humidity at the Drip Shield Crown for the P2WR5C10 Location 
in the Tptpll (tsw35) Unit, Plotted for the Mean Infiltration Flux and the Low-Probability-
Seismic Collapsed Drift with Low-Kth Rubble 
6.3.7.3 Influence of Seepage on the High and Low Thermal Conductivity Rubble Cases 
with Total Drift Collapse 
This section describes a sensitivity study of the potential influence of seepage on the high- and 
low-Kth rubble cases that are discussed in Section 6.3.7.1. Note that the results presented in 
Section 6.3.7.1 are obtained by executing the full MSTHM methodology executed at a specific 
location in the repository (location P2WR5C10 in Figure 6.3-1). The seepage analysis in this 
section (Section 6.3.7.3) is conducted using the LDTH submodel at the P2WR5C10 location 
conducted for an AML of 55 MTU/acre. Thus, the results in this section are not full MSTHM 
results. However, the results of the seepage analysis in this section are representative of 
line-averaged heating conditions at the P2WR5C10 location, which is close to the repository 
center (i.e., relatively distant from the repository edges). 
The seepage analysis is conducted by specifying a seep at the top of the rubble for selected seep 
magnitudes of 100, 300, 1000, and 10,000 liter/yr/WP, which represents a broad range of 
possible conditions. In order not to artificially heat or cool the model by virtue of this specified 
seepage flux, the seep has a specified enthalpy history, which causes the seep temperature history 
to be consistent with the local temperature history that would have occurred in the absence of the 
seep. To account for the residual dryout effects resulting from drift ventilation, the seep is turned 
on at 65 years, which is 15 years after closure. 
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Table 6.3-44 summarizes the time that the seep arrives at the crown of the drip shield for the 
high- and low-Kth rubble cases and for four seep magnitudes. Also summarized is the range in 
waste package temperatures that occur at the time that the seep arrives at the drip-shield crown 
based upon the corresponding MSTHM calculations conducted in Section 6.3.7.1. Note that the 
range of temperatures corresponds to the eight different waste packages that are represented by 
the MSTHM (see Table 6.3-13). Because the temperatures are taken from the MSTHM 
calculations that did not incorporate the seeps, the cooling effect of the seep is not included in the 
waste package temperature ranges in Table 6.3-44. Thus, the listed waste package temperatures 
are somewhat higher than would occur if the cooling effect of the seep had been included. 
Table 6.3-44. Summary of Arrival Time at Drip-Shield Crown for Seeps of Varying Magnitude for Low-
Probability-Seismic Collapsed-Drift Scenario for the High-Kth and Low- Kth Rubble Cases 
Seep Magnitude 
(liter/yr/WP) 
High-Kth Rubble Low-Kth Rubble 
Arrival Time at 
Drip-Shield Crown 
(yr) 
Waste Package 
Temperature Range 
(oC) 
Arrival Time at 
Drip-Shield Crown 
(yr) 
Waste Package 
Temperature Range 
(oC) 
100 10,000 54.1 - 57.2 15,000 46.7 - 49.5 
300 5000 69.3 - 73.4 8000 61.7 - 65.7 
1000 2800 79.1 - 84.0 4000 75.6 - 80.8 
10,000 1400 90.3 - 98.3 1500 93.7 - 102.4 
DTN: LL040404423122.045. 
NOTE: Waste package temperature ranges are obtained from full MSTHM results at the P2WR5C10 location (see 
Figure 6.3-1 for location). 
As discussed in Section 6.3.7.1, because the rubble has a lower thermal conductivity than the 
adjoining host rock, and because the nominal case of no drift collapse involves thermal radiation, 
which is a highly efficient mode of heat transfer, the introduction of rubble has a strong 
insulating effect. The insulating effect of the rubble substantially extends the duration of the 
boiling period on the waste packages (Table 6.3-43). The increase in waste package boiling 
duration is about twice as great for the low-Kth case as it is for the high-Kth case. The liquid-
phase saturation in the matrix continuum of the host-rock rubble remains low for a greatly 
extended period (Figure 6.3-55e, Figure 6.3-56e, and Figure 6.3-57e). The low liquid-phase 
saturation substantially reduces the relative humidity in the rubble. 
The extended boiling duration and extended duration of reduced relative humidity in the rubble 
greatly extend the time that seeps can be completely evaporated in the rubble. Thus, a seep of 
100 liter/yr/WP requires 10,000 and 15,000 years to reach the crown of the drip shield for the 
high- and low-Kth rubble cases, respectively. Waste package temperatures have declined 
substantially by the time that a 100-liter/yr/WP seep reaches the drip shield. A seep of 1000 
liter/yr/WP requires 2800 and 4000 yr to reach the crown of the drip shield for the high- and 
low-Kth rubble cases, respectively. Waste package temperatures have declined to well below the 
boiling point by the time a 1000-liter/yr/WP seep reaches the crown of the drip shield. It 
requires a seep of 10,000 liter/yr/WP to reach the crown of the drip shield while some (but not 
all) of the waste packages are above the boiling point. Had the cooling effect of the seep on the 
waste package temperatures been included, it is likely that all of waste package temperatures for 
the 10,000-liter/yr/WP seep would also have been below the boiling point. 
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6.3.8 Comparison of Results for the TSPA-LA Base Case with Those for the FY01 
Supplemental Science and Performance Analyses (SSPA) 
This section gives a brief comparison between the thermal-hydrologic conditions predicted for 
the TSPA-LA base case with those predicted for the FY 01 Supplemental Science and 
Performance Analyses, Volume 1: Scientific Bases and Analyses (Section 5.4.1 of BSC 2001 
[DIRS 155950]). Figure 6.3-59 plots the thermal-hydrologic parameters for all eight waste 
packages considered in both the TSPA-LA and the SSPA. The LDTH submodel location 
P3R7C12 was chosen because it is very close to the location used to plot the thermal-hydrologic 
parameters in Figure 5.4.1-7 of the FY 01 Supplemental Science and Performance Analyses, 
Volume 1: Scientific Bases and Analyses (Section 5.4.1 of BSC 2001 [DIRS 155950]). This 
location was chosen because it is close to the geographic center of the repository and because it 
is the Tptpll (tsw35), which is the host-rock unit for 75.1 percent of the repository area (Table 
6.3-2). Note that this comparison is for the mean infiltration-flux case. Note also that the 
MSTHM calculations for the SSPA were for a period of 1,000,000 years, while the MSTHM 
calculations for the TSPA-LA are for a period of 20,050 years. The same time axis is used in 
Figure 6.3-59 as in Figure 5.4.1-7 (Section 5.4.1 of BSC 2001 [DIRS 155950]) to provide a more 
consistent basis for comparing the history plots of thermal-hydrologic conditions. The legend in 
Figure 6.3-59 utilizes the same waste package names used in Figure 5.4.1-7 (Section 5.4.1 of 
BSC 2001 [DIRS 155950]), as well as providing the waste package names (e.g., pwr1-1) used in 
the TSPA-LA (see Table 6.3-13). 
Peak waste package temperatures at the repository center in the MSTHM calculations for the 
SSPA, as given in Figure 5.4.1-7 (Section 5.4.1 of BSC 2001 [DIRS 155950]), range from 152.3 
to 180.1oC. Peak waste package temperatures at the repository center in the MSTHM 
calculations for the TSPA-LA base case, as given in Figure 6.3-59, range from 136.3 to 167.3oC. 
Thus, for this location in the repository, and for the mean infiltration-flux case, peak waste 
package temperatures are 12 to 16oC lower for the TSPA-LA than for the SSPA. There are two 
primary causes for the TSPA-LA temperatures being lower than they are in the SSPA. The first 
is differences in the heat-removal efficiency that was applied to the respective models during the 
preclosure ventilation period. The MSTHM calculations for the SSPA used a constant heat-
removal efficiency of 70 percent (Section 5.3.2.4.1 of BSC 2001 [DIRS 155950]). The MSTHM 
calculations for the TSPA-LA use a time-varying heat-removal efficiency 
(DTN: MO0304MWDALACV.000 [DIRS 164551]). Thus, in-drift temperatures are lower at 
the onset of the postclosure period for the TSPA-LA MSTHM calculations than they are for the 
SSPA MSTHM calculations. The second reason for the lower TSPA-LA temperatures is the 
approximation of the influence of natural convection on heat transfer in the drift. The TSPA-LA 
MSTHM calculations use an effective thermal conductivity for the gas-filled drift cavity that is 
based on a correlation (Francis et al. 2003 [DIRS 164602], Table 6) that more realistically 
accounts for the in-drift geometry than the approximation used in the SSPA MSTHM 
calculations (CRWMS M&O 2001 [DIRS 153410]). It should be noted that the correlations for 
the in-drift effective thermal conductivity, which were obtained from Table 6 of Francis et al 
(2003 [DIRS 164602]), have been updated in In-Drift Natural Convection and Condensation 
(BSC 2004 [DIRS 164327], Table 6.4.7-3), resulting in very small changes to the coefficients. 
As evident in Figure I-1 of Appendix I, the small changes to the coefficients result in 
insignificant changes to the in-drift effective thermal conductivity. The in-drift convective heat 
transfer approximation for the TSPA-LA MSTHM results in more efficient heat transfer (by 
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natural convection), which lowers the temperature difference between the waste package and 
drift wall; the lower temperature difference results in lower waste package temperatures. 
Source: See Table XIII-1. 
NOTE: The plotted thermal-hydrologic parameters are (a) drift-wall temperature, (b) drift-wall relative humidity, (c) 
waste package temperature, (d) waste package relative humidity, and (e) drift-wall liquid-phase saturation. 
The waste package names (in parentheses) are given in Figure 6.2-2 and in Table 6.3-13. 
Figure 6.3-59. Thermal-Hydrologic Parameters for the Eight Waste Packages Considered in this Report, 
Plotted for the Mean Infiltration-Flux Cases at the P3R7C12 Location in the Tptpll (tsw35) 
Unit, Close to the Repository Center 
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6.3.9 Influence of Host-Rock Hydrologic-Property Variability and Uncertainty 
The multiscale thermal-hydrologic model addresses repository-scale variability of hydrologic 
properties. A sensitivity study of hydrologic-property variability, described below, for the four 
host-rock types (Tptpul, Tptpmn, Tptpll, and Tptpln) demonstrates that multiscale 
thermohydrologic model-simulated in-drift and near-field thermal-hydrologic conditions are 
insensitive to differences in the hydrologic property values for these respective host-rock units. 
The reason for this lack of sensitivity is provided at the end of this section (6.3.9). 
Figure 6.3-60 gives the drift-wall and drip-shield temperature histories at a typical location at the 
center of the repository for percolation flux values ranging from 0.1 to 10 mm/yr. Figure 6.3-61 
gives the corresponding drift-wall and drip-shield relative humidity histories for this location. 
This location (P2WR5C10 in Figure 6.3-1) happens to be in the Tptpll host-rock unit, which is 
the predominant host-rock type in the repository (Table 6.3-3). For the purpose of showing the 
influence of hydrologic-property variability, model calculations were made using the line-
averaged-heat-source drift-scale thermal-hydrologic (LDTH) submodel (Section 6.2.6) applying 
the hydrologic property values for each of the host-rock types (Tptpul, Tptpmn, Tptpll, and 
Tptpln), respectively. For a percolation flux of 0.1 mm/yr or greater, temperature is insensitive 
to hydrologic properties (Figures 6.3-60a to 6.3-60f). For a percolation flux of 0.01 mm/yr, 
hydrologic properties exert a minor influence on temperature (Figures 6.3-60g and 6.3-60h). For 
a percolation flux of 1 mm/yr or greater, relative humidity is insensitive to hydrologic properties 
(Figures 6.3-61a to 6.3-61d). For a percolation flux of 0.1 mm/yr or less, hydrologic properties 
exert a minor influence on relative humidity (Figures 6.3-61e to 6.3-61h). 
The influence that hydrologic properties exert on temperature and relative humidity is 
insignificant for two reasons. First, it is insignificant compared to the influence of host-rock 
thermal conductivity and percolation flux, as evident in Figures 6.3-51 and 6.3-61. Second, the 
percolation flux range for which hydrologic properties exert some influence (equal to or less than 
0.1 mm/yr) constitutes a small portion of the repository for the three climate states (present-day, 
monsoonal, and glacial), as is evident in Figure 4-2. 
The lack of sensitivity of in-drift and near-field temperature and relative humidity to hydrologic 
properties can be understood by considering the key processes and factors governing 
thermal-hydrologic behavior in and around emplacement drifts. Thermal-hydrologic behavior in 
and around emplacement drifts consists of three fundamental processes: 
1. Heat FlowOccurs in emplacement drifts, primarily by thermal radiation, and in the 
adjoining host rock, primarily by thermal conduction. Consequently, host-rock 
thermal conductivity is the key natural-system parameter determining the magnitude 
of temperature buildup in the host rock. 
2. Host-Rock DryoutIs driven by temperature buildup, resulting in evaporation 
(boiling), which lowers the liquid-phase saturation in the host rock, thereby lowering 
the relative humidity in the host rock and in the emplacement drifts. 
3. Host-Rock RewettingPrimarily occurs as a result of gravity-driven percolation in 
fractures, with capillary-driven imbibition into the adjoining matrix. The rate of 
rewetting is controlled by the local percolation flux except in regions of very low 
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percolation flux (less than approximately 0.1 mm/yr), where it is controlled by 
capillary-driven imbibition in the matrix. The approximate percolation-flux threshold 
of 0.1 mm/yr is obtained by observing the sensitivity of temperature (Figure 6.3-60) 
and relative humidity (Figure 6.3-61) to percolation flux, which is discussed above 
Source: See Table XIII-1. 
NOTE: The temperature histories are calculated by the LDTH submodel of the multiscale thermohydrologic model 
(Section 6.2.6). These temperature histories are calculated for a location close to the center of the 
repository (the P2WR5C10 location shown Figure 6.3-1). All cases use the thermal properties, including 
the mean thermal conductivity, of the Tptpll host-rock unit (Table 6.3-23). 
Figure 6.3-60. Drift-Wall and Drip-Shield Temperature History at the Repository Center for Four Values 
of Percolation Flux and for the Hydrologic Properties of Each of the Host-Rock Types 
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Source: See Table XIII-1. 
NOTE: The relative-humidity histories are calculated by the LDTH submodel of the multiscale thermal-hydrologic 
model (Section 6.2.6). These relative-humidity histories are calculated for a location close to the center of 
the repository (the P2WR5C10 location shown Figure 6.3-1). All cases use the thermal properties, 
including the mean thermal conductivity, of the Tptpll host-rock unit (Table 6.3-23). 
Figure 6.3-61. Drift-Wall and Drip-Shield Relative-Humidity History at the Repository Center for Four 
Values of Percolation Flux and for the Hydrologic Properties of Each of the Host-Rock 
Types 
For the range of host-rock hydrologic properties of the four host-rock units, vapor flow from the 
boiling to the condensation zone essentially occurs in an unthrottled (i.e., unrestricted) fashion. 
Permeability in the fractures and matrix and fracture spacing is always sufficiently large to result 
in a (insignificantly) small gas-phase pressure buildup with respect to boiling. Consequently, the 
gas-phase pressure buildup is small enough to not throttle (i.e., restrict) the rate at which boiling 
occurs and the resulting vapor flux from the boiling zone to the condensation zone. Thus, the 
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range in hydrologic properties for the host rock does not result in differences in the rate at which 
boiling occurs in the host rock. 
For the range of host-rock hydrologic properties of the four host-rock units, the contribution of 
buoyant gas-phase convection to overall heat flow is small compared to that of thermal 
convection. Thus, the range in host-rock thermal-hydrologic properties of the four host-rock 
types does not result in differences in the temperature buildup in the host rock, as is evident in 
Figure 6.3-60. 
For the range of hydrologic properties of the four host-rock units, fracture permeability is 
sufficiently large and fractures are sufficiently well connected to allow gravity-driven drainage 
of percolation 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. One important caveat to this generalization relates to flow 
focusing, which arises due to heterogeneity in fracture permeability. The influence of flow 
focusing is addressed by including areal variability of percolation flux, which results in a broad 
range of percolation flux over the repository footprint (Table 6.3-5), and by including 
uncertainty, as is addressed in the lower, mean, and upper infiltration-flux cases (Table 6.3-4). 
Thus, the manner in which hydrologic properties primarily affect rewetting (and, thus, net 
dryout) behavior is related to the manner in which those properties affect capillary-driven flow, 
which primarily occurs as imbibition in the matrix. 
For the range of host-rock hydrologic properties of the four host-rock units, capillary-driven 
imbibition always results in a rewetting magnitude that is effectively less than approximately 
0.1 mm/yr. Accordingly, only in regions with very low percolation flux (less than 0.1 mm/yr) do 
the hydrologic properties exert a small but insignificant influence on dryout and rewetting 
behavior in the host rock, as is evident in Figure 6.3-61. For areas of the repository with a local 
percolation flux greater than 0.1 mm/yr (which is the vast majority of the repository area for all 
three climate states, as shown in Figure 4-2), differences in host-rock hydrologic properties exert 
an insignificant influence on dryout and rewetting behavior. Even in areas with low percolation 
flux, the influence of hydrologic properties on dryout and rewetting behavior is small compared 
to that of host-rock thermal conductivity and percolation flux, as is evident in Figures 6.3-50 and 
6.3-51. 
6.3.10 Influence of Pseudo Permeability on In-Drift Temperature and Relative Humidity 
Although the emplacement drift is an open cavity rather than a porous media, the vast majority 
of simulations of in-drift and near-field thermal-hydrologic conditions use porous-media flow 
and transport simulators, such as NUFT (Nitao 1998 [DIRS 100474]) and TOUGH2 (Pruess et 
al. 1999 [DIRS 160778]), which necessitates treating the drift cavity as a porous media with a 
large permeability and 100 percent porosity. Because the drift cavity is not a porous medium, 
the permeability of the drift cavity is called pseudo permeability. A value of pseudo 
permeability of 1 x 10-8 m2 is used in all of the LDTH submodels used to support all MSTHM 
calculations in this report. It is important that the value of pseudo permeability is at least as large 
as that of the bulk permeability of the fractured host rock. In that way, the value of pseudo 
permeability will not impede advective gas-phase flow within the drift cavity, particularly as it 
relates to buoyant gas-phase convection (also called natural convection) cells that develop in the 
adjoining host rock. 
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As demonstrated below, the porous medium approach with pseudo permeability does not 
represent the influence of buoyant gas-phase convection (also called natural convection) on heat 
transfer within the emplacement drift. To represent the influence of natural convection on heat 
transfer within the drift, an effective thermal conductivity for the gas-filled drift cavity is used. 
This effective thermal conductivity is based on a correlation (Francis et al. 2003 [DIRS 164602], 
Table 6) accounting for the influence of natural convection, which is described in Appendix I. It 
should be noted that the correlations for the in-drift effective thermal conductivity, which were 
obtained from Table 6 of Francis et al. (2003 [DIRS 164602]), have been updated in In-Drift 
Natural Convection and Condensation (BSC 2004 [DIRS 164327], Table 6.4.7-3), resulting in 
small changes to the coefficients. As evident in Figure I-1 of Appendix I, the small changes to 
the coefficients result in insignificant changes to the in-drift effective thermal conductivity. The 
effective conductivity approach is used both in the DDT submodels (Section 6.2.8) and in the 
LDTH submodels (Section 6.2.6). Because the LDTH submodel allows natural convection to 
occur within the drift cavity, a concern is whether the in-drift convective cooling effect, together 
with the use of the effective thermal conductivity for the drift cavity, will over-account for the 
magnitude of in-drift convective cooling. 
10
Figure 6.3-62 plots drip-shield temperature and relative humidity for six different values of 
in-drift pseudo permeability, ranging over six orders of magnitude. The largest value of in-drift 
pseudo permeability considered is 1 x 10-6 m2, which is two orders of magnitude larger than the 
value used in all MSTHM calculations. The smallest value of in-drift pseudo permeability is 1 x 
-12 m2, which is four orders of magnitude smaller than the value used in all MSTHM 
calculations; it is also of the same order of the fracture permeability of the host rock. Over this 
range, the value of in-drift pseudo permeability has an insignificant effect on in-drift temperature 
and relative humidity. The range in peak drip-shield temperature is 150.9oC to 151.1oC for these 
cases. Clearly, there is no over-accounting of convective cooling in the LDTH submodels that 
support the MSTHM calculations in this report. Therefore, the approach of using an effective 
thermal conductivity for the drift cavity is reasonable and appropriate in the LDTH submodels. 
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Source: See Table XIII-1. 
NOTE: Temperature and relative-humidity histories are calculated by the LDTH submodel (Section 6.2.6) for an 
AML of 55 MTU/acre and for a location close to the center of the repository (the P2WR5C10 location 
shown Figure 6.3-1) for the mean infiltration-flux case with mean host-rock thermal conductivity. 
Figure 6.3-62. Drip-Shield Temperature (a) and Relative Humidity (b) at the Repository Center for 
Different Values of Pseudo Permeability of the Gas-Filled Emplacement Drift Cavity 
6.3.11 Influence of Invert Hydrologic-Property Variability and Uncertainty 
All of the MSTHM calculations in this report utilized a single hydrologic property set for the 
crushed-tuff gravel invert. The dual-permeability model (DKM) is applied to represent flow in 
crushed-tuff gravel, with flow within the tuff grains (called the intragranular porosity) 
corresponding to flow in the matrix continuum of the DKM and flow around the tuff grains 
(called the intergranular porosity) corresponding to flow in the fracture continuum of the DKM. 
As discussed in Section 5.3.1.2, the hydrologic properties of the intragranular porosity are 
assumed to be the same as the intact properties for the Tptpll (tsw35) host-rock unit. As 
discussed in Section 5.3.1.8, the hydrologic properties of the intergranular porosity are taken 
from case 2 (3-mm particle size) from Table X-7 of Appendix X, with the one modification that 
the permeability is taken to be 1.0  10-9 m2, which is between the values for case 1, which has a 
0.317-mm particle size (1.681  10-10 m2) and for case 2, which has a 3-mm particle size 
(1.511  10-8 m2) from Table X-7 of Appendix X. Thus, the base case MSTHM calculations 
used a modified case 2 intergranular-porosity hydrologic property set. The purpose of this 
section (Section 6.3-11) is to demonstrate the sensitivity (or lack thereof) of thermal-hydrologic 
conditions in the invert to intragranular properties (as represented by the matrix properties of the 
four host-rock units) and to intergranular properties (as represented by the cases 1 through 4 in 
Table X-7 of Appendix X, as well as the modified case 2). 
Figure 6.3-63 plots the liquid-phase saturation for the intragranular porosity and the temperature 
averaged over the invert. Four different cases are considered, with each case utilizing the matrix 
properties from each of the respective host-rock units: Tptpul (tsw33), Tptpmn (tsw34), Tptpll 
(tsw35), and Tptpln (tsw36). All four cases utilize the modified case 2 intergranular properties 
discussed above. Invert temperature is insensitive to the hydrologic properties of the 
intragranular porosity (Figure 6.3-63b). Liquid-phase saturation is also insensitive to hydrologic 
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properties of the intragranular porosity (Figure 6.3-63a), and also justifies not propagating invert 
hydrologic-property through the MSTHM calculations supporting TSPA-LA. Rewetting 
proceeds similarly in the two lithophysal units (Tptpul and Tptpll), and also in the two 
nonlithophysal units (Tptpmn and Tptpln). Because the matrix permeability is smaller in the 
nonlithophysal units than in the lithophysal units, rewetting proceeds somewhat more slowly in 
the nonlithophysal units than in the lithophysal units. 
Source: See Table XIII-1. 
NOTE: Invert liquid-phase saturation and temperature histories are calculated by the LDTH submodel (Section 
6.2.6) for an AML of 55 MTU/acre and for a location close to the center of the repository (the P2WR5C10 
location shown Figure 6.3-1) for the mean infiltration-flux case with mean host-rock thermal conductivity. 
Figure 6.3-63. Invert Liquid-Phase Saturation for the Intragranular Porosity (a) and Temperature (b) at 
the Repository Center for Invert Gravel Derived from Each of the Indicated Host-Rock 
Units 
Figure 6.3-64 plots temperature and relative humidity at different locations in the drift, including 
the host rock at the crown of the drift and below the invert, and at the top and bottom of the 
invert beneath the drip shield for crushed-tuff gravel derived from each of the host-rock units, 
respectively. Both temperature and relative humidity at those locations are insensitive to 
hydrologic properties of the intragranular porosity. This lack of sensitivity justifies the 
assumption discussed in Section 5.3.1.2. The small thermal conductivity in the invert results in a 
large vertical temperature gradient in the invert. This large temperature gradient results in a 
large relative-humidity gradient in the invert. Consequently, the top of the invert beneath the 
drip shield always has a much lower relative humidity than any location around the drift wall. 
As seen in Figure 6.3-64, this relationship (that relative humidity is always less at the top of the 
invert than at the drift wall) holds for all four of the crushed-tuff gravels (Tptpul, Tptpmn, Tptpll, 
and Tptpln). 
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Source: See Table XIII-1. 
NOTE: Temperature and relative humidity histories are calculated by the LDTH submodel (Section 6.2.6) for an 
AML of 55 MTU/acre and for a location close to the center of the repository (the P2WR5C10 location 
shown Figure 6.3-1) for the mean infiltration-flux case with mean host-rock thermal conductivity. 
Figure 6.3-64. Temperature (a,c,e,g) and Relative Humidity (b,d,f,h) for Various Locations in the Drift at 
the Repository Center for Invert Gravel Derived from Each of the Indicated Host-Rock 
Units 
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Table 6.3-45 lists the temperatures at the drift crown, drip-shield crown, top and bottom of the 
invert beneath the drip shield, and in the host rock below the invert. It is important to note that 
the temperature difference between the top and bottom of the invert is always greater than the 
temperature difference between the top of the invert and drip-shield crown. This observation has 
important implications for the consequences of the flux of water vapor longitudinally along the 
drift axis from hotter to cooler locations where it will condense. For any given drift cross 
section, the coolest and most humid location is always at the bottom of the invert. Therefore, 
water vapor that is transported longitudinally along the drift axis will have a greater tendency to 
condense at the bottom of the invert, where it is coolest and most humid. Moreover, much of the 
water vapor created by virtue of evaporation at the top of the invert will move downward by 
advection and binary gas-phase diffusion to the bottom of the invert (or into the host rock 
below), where it will condense. 
Table 6.3-45. Summary of Temperature at Various Locations in Drift Cross Section, Including Host Rock 
at Drift Crown, Top and Bottom of Invert Beneath Drip Shield, and Host Rock Below Invert 
Time Temperature (oC) 
(yr) Host Rock at 
Drift Crowna 
Crown of Drip 
Shieldb 
Top of Invert 
Beneath Drip 
Shielda 
Bottom of 
Invert Beneath 
Drip Shielda 
Host Rock 
Below Inverta 
70. 146.6 152.2 158.7 125.5 122.3 
100. 140.1 144.2 149.3 124.4 122.1 
1000. 99.7 100.9 102.1 97.7 97.2 
2000. 87.3 88.0 88.7 86.5 86.2 
5000. 64.5 64.9 65.4 63.9 63.8 
10,000. 49.0 49.3 49.7 48.6 48.5 
20,050. 36.5 36.7 37.0 36.3 36.2 
a 
Temperatures correspond to Figure 6.3-64e. 
b Temperatures obtained by applying the temperature difference between top of invert and crown of invert calculated 
using the DDT submodel. 
Figure 6.3-65 plots the liquid-phase saturation for the intragranular porosity, temperature, and 
relative humidity at the top of the invert beneath the drip shield for five different sets of 
hydrologic properties for the intergranular porosity discussed above. Temperature, liquid-phase 
saturation, and relative humidity are all insensitive to the hydrologic properties of the 
intergranular porosity. This lack of sensitivity justifies the assumption discussed in Section 
5.3.1.8. This lack of sensitivity also justifies not propagating invert hydrologic-property 
uncertainty through the MSTHM calculations supporting TSPA-LA. 
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Source: See Table XIII-1. 
NOTE: Liquid-phase saturation, temperature and relative humidity histories are calculated by the LDTH submodel 
(Section 6.2.6) for an AML of 55 MTU/acre and for a location close to the center of the repository (the 
P2WR5C10 location shown Figure 6.3-1) for the mean infiltration-flux case with mean host-rock thermal 
conductivity. 
Figure 6.3-65. Invert Liquid-Phase Saturation (a) for the Intragranular Porosity, Temperature (b), and 
Relative Humidity (c) at the Top of the Invert Beneath the Drip Shield at the Repository 
Center for Different Sets of Hydrologic Parameters for the Intergranular Porosity 
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6.3.12 Influence of Ventilation Heat-Removal Efficiency Uncertainty 
All MSTHM calculations in this report utilize the distance- and time-dependent ventilation 
heat-removal efficiency tables from DTN: MO0304MWDALACV.000 [DIRS 164551]. This 
section (Section 6.3-12) investigates the potential impact of uncertainty in ventilation 
heat-removal efficiency on in-drift thermal-hydrologic conditions. Five heat-removal efficiency 
cases are considered for a location close to the center of the repository, which is the P2WR5C10 
location (see Figure 6.3-3 for location). These calculations use the LDTH submodel (Section 
6.2.6) for an AML of 55 MTU/acre. The five cases include the base case, which applied a 
time-dependent heat-removal efficiency table from DTN: MO0304MWDALACV.000 
[DIRS 164551]. The other four cases apply a constant heat-removal efficiency (i.e., constant 
during the 50-year ventilation period) for values of 70, 80, 90, and 100 percent efficiency. Note 
that the case with 100 percent efficiency is a hypothetical limiting case, which is equivalent to 
the surface storage of waste packages during the entire 50-year preclosure period. Figure 6.3-66 
plots drip-shield temperature and relative humidity for these five cases. Note that the drip-shield 
temperature and relative-humidity temperatures for the base case lie between those of the 80- and 
90-percent efficiency cases. Based on linear interpolation of peak drip-shield temperature (Table 
6.3-45), the base case has an effective constant heat-removal efficiency of 83 percent. 
Source: See Table XIII-1. 
NOTE: Temperature and relative humidity histories are calculated by the LDTH submodel (Section 6.2.6) for an 
AML of 55 MTU/acre and for a location close to the center of the repository (the P2WR5C10 location 
shown Figure 6.3-1) for the mean infiltration-flux case with mean host-rock thermal conductivity. 
Figure 6.3-66. Drip-Shield Temperature (a) and Relative Humidity (b) at the Repository Center for 
Different Values of Ventilation Heat-Removal Efficiency 
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Table 6.3-46. Peak Drip-Shield Temperature for Different Values of Ventilation Heat-Removal Efficiency 
Ventilation Heat-Removal 
Efficiency 
(%) 
Peak Drip-Shield Temperature 
(Co) 
Peak Drip-Shield Temperature 
Compared to Base Case 
(Co) 
70 160.4 9.4 
80 153.2 2.2 
Base Case 151.0 0.0 
90 146.3 -4.7 
100 139.3 -11.7 
NOTE: Drip-shield temperatures correspond to Figure 6.3-66. 
Over the range of heat-removal efficiency of 70 to 100 percent, the range in the in-drift 
temperature and relative humidity conditions is less than that resulting from parametric 
uncertainty of percolation flux and host-rock thermal conductivity (Tables 6.3-27 through 6.3-29 
and Figure 6.3-31). Moreover, the impact of the differences arising as a result of proximity to 
the repository edge, together with the impact of parametric uncertainty (Figure 6.3-53) is much 
greater than that arising from uncertainty in ventilation heat-removal efficiency. Therefore, 
uncertainty in ventilation heat-removal efficiency does not need to be propagated through the 
MSTHM results supporting the TSPA-LA. 
6.3.13 Relationship Between Temperature and Relative Humidity on Waste Packages 
Figure 6.3-67 plots the range of temperature histories for all waste packages across the 
repository, accounting for the influence of parametric uncertainty of host-rock thermal 
conductivity and percolation flux above the repository. Note that a comprehensive discussion of 
the influence of parametric uncertainty on in-drift and near-field thermal-hydrologic conditions 
is given in Section 6.2.4. Figure 6.3-68 plots the corresponding range of waste package relative 
humidity histories across the repository. Figure 6.3-69 plots the corresponding range of 
temperature versus relative humidity trajectories, during cooldown (i.e., after the waste package 
temperature has peaked). Also plotted on these three figures are histories and trajectories for 
three distinct waste packages, including (1) a cool DHLW waste package close to the edge of the 
repository, (2) an average BWR waste package at the center of the repository, and (3) a hot PWR 
waste package at the edge of the repository. The temperature versus relative humidity 
trajectories are important to the evolution of the chemical environment on waste packages. 
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Source: See Table XIII-1. 
NOTE: Also plotted are the temperature histories of three distinct waste packages, including (1) a cool DHLW 
waste package at the edge of the repository, (2) an average BWR waste package at the center of the 
repository, and (3) a hot PWR waste package at the center of the repository. The upward arrows indicate 
the time when boiling ceases at the drift wall. The range of waste package temperature histories is the 
same as that given in Figure 6.3-53a. 
Figure 6.3-67. Range of Temperature Histories for All Waste Packages, Accounting for Uncertainty of 
Host-Rock Thermal Conductivity and Percolation Flux 
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Source: See Table XIII-1. 
NOTE: Also plotted are the relative-humidity histories of three distinct waste packages, including (1) a cool DHLW 
waste package at the edge of the repository, (2) an average BWR waste package at the center of the 
repository, and (3) a hot PWR waste package at the center of the repository. The upward arrows indicate 
the time when boiling ceases at the drift wall. The range in waste package relative-humidity histories is the 
same as that given in Figure 6.3-53b. 
Figure 6.3-68. Range of Relative Humidity Histories for All Waste Packages, Accounting for Uncertainty 
of Host-Rock Thermal Conductivity and Percolation Flux 
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Source: See Table XIII-1. 
NOTE: Also plotted are the temperature versus relative-humidity trajectories, during cooldown, of three distinct 
waste packages, including (1) a cool DHLW waste package at the edge of the repository, (2) an average 
BWR waste package at the center of the repository, and (3) a hot PWR waste package at the center of the 
repository. The upward arrows indicate the time when boiling ceases at the drift wall. 
Figure 6.3-69. Range of Temperature vs. Relative Humidity Trajectories for All Waste Packages, During 
Cooldown, Accounting for Uncertainty in Host-Rock Thermal Conductivity and 
Percolation Flux 
6.4 COMPARISON AGAINST AN ALTERNATIVE CONCEPTUAL MODEL 
An alternative conceptual model to the MSTHM is a mountain-scale thermal-hydrologic model 
developed by LBNL (Haukwa et al. 1998 [DIRS 117826]). The LBNL model is a monolithic 
thermal-hydrologic model. Note that the three-drift repository MSTHM model validation test 
case (Section 7.5) also used a monolithic thermal-hydrologic model to compare against the 
MSTHM. There is an important distinction between how the monolithic thermal-hydrologic 
model was used in Section 7.5 and how the LBNL monolithic thermal-hydrologic model is being 
used in this section (Section 6.4). In Section 7.5, the MSTHM and monolithic 
thermal-hydrologic model representation of the model validation test problem are essentially 
equivalent in a number of important respects, including (1) gridblock discretization at the drift 
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scale, (2) heat-generation-rate-versus-time tables, (3) representation of in-drift heat-flow 
processes, and (4) hydrologic and thermal properties used in the respective models. In Section 
6.4, the MSTHM and corresponding LBNL thermal-hydrologic model were similar, but not 
identical in any of these aspects. As discussed below, the LBNL thermal-hydrologic model used 
(1) coarser grid discretization at the drift scale than the MSTHM, (2) a line-averaged 
approximation of the heat-generation-rate-versus-time table (whereas the MSTHM represented 
the waste packages as discrete heat sources), and (3) a lumped heat source that filled the entire 
cross section of the emplacement drift. 
Before discussing the comparison study between the MSTHM and an alternative conceptual 
model, it is noted that there are several differences between the version of the MSTHM used at 
the time of this comparison study (Buscheck et al. 1998 [DIRS 148521]) and the version of the 
MSTHM used to support TSPA-LA (as described in this report). These differences fall under the 
following categories. 
1. Repository layout: As seen in comparing Figure 6.2-3 with Figures 5.1, 5.2, and 6.1 of 
BSC 2001 [DIRS 158204], both the repository layout and the MSTHM representation of 
the layout have changed. The current version of the MSTHM utilizes 108 drift-scale 
submodel locations, while the previous version of the MSTHM utilizes 31 locations. The 
current version explicitly represents each emplacement drift, while the previous version 
does not. 
2. Drift ventilation: The current version of the MSTHM represents how heat-removal 
efficiency from drift ventilation varies as a function of time and distance along each of 
the emplacement drifts, given in DTN: MO0304MWDALACV.000 [DIRS 164551], 
while the previous version used a single value of heat-removal efficiency for the entire 
repository, which is held constant during the preclosure ventilation period. 
3. Percolation flux: The current version of the MSTHM represents the influence of lateral 
diversion in the PTn by using the percolation-flux distribution (from the base of the PTn 
unit into the top of the TSw sequence of units) calculated by UZ Flow Models and 
Submodels (BSC 2004 [DIRS 169861]). Because the previous version used the 
infiltration maps at the ground surface from DTN: GS000308311221.005 [DIRS 
147613], it did not represent the influence of lateral diversion in the PTn. 
Because these differences also pertain to the alternative conceptual model, they do not affect the 
usefulness of the comparison between the MSTHM and that model. 
Figure 6.4-1 compares the drift-wall temperature predicted by the MSTHM 
(Buscheck et al. 1998 [DIRS 148521]) with those predicted by an east-west cross-sectional 
mountain-scale thermal-hydrologic model (Haukwa et al. 1998 [DIRS 117826]). Because the 
east-west thermal-hydrologic model does not predict in-drift thermal-hydrologic conditions and 
because relative humidity and liquid-phase saturation was not provided from that model, the 
comparison is restricted to predictions of drift-wall temperatures by the respective modeling 
approaches. 
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NOTE: This comparison of predicted temperatures at (a) center of the repository (l4c3 location in Buscheck et al. 
1998 [DIRS 148521], Table 2-2) and (b) 100 m from the edge of the repository (l4c1 location) is run for the 
12/97 TSPA-VA base-case I1  1 af,mean parameter set, where the symbol I stands for the nominal infiltration 
flux qinf map (average qinf = 7.8 mm/yr) for the present-day climate and the parameter af is the van 
Genuchten alpha parameter for fractures. The MSTHM is used to predict drift-wall temperature adjacent to 
an average 21-PWR medium-heat CSNF waste package. The east-west cross-sectional mountain-scale 
thermal-hydrologic model (Haukwa et al. 1998 [DIRS 117826]) is used to predict the drift temperature, which 
is averaged over the cross section of the drift, arising from a line-averaged heat-source representation of 
waste package decay heat. 
Figure 6.4-1. Comparison of Predicted Temperatures at (a) the Center of the Repository and (b) 100 m 
from the Edge of the Repository 
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Before discussing the differences in the temperatures predicted by the two approaches 
(Figure 6.4-1), it is important to discuss the differences in the models. The temperature predicted 
by the MSTHM is the perimeter-averaged drift-wall temperature adjacent to an average 
21-PWR medium-heat CSNF waste package. MSTHM discretely represents the decay-heat 
source from individual waste packages; therefore, some of the drift-wall locations are hotter than 
that shown in Figure 6.4-1, while some are considerably cooler. The drift-wall gridblocks over 
which the temperature is averaged extend 0.5 m into the host rock surrounding the drift. The 
temperature prediction in the east-west cross-sectional mountain-scale thermal-hydrologic model 
is for a gridblock that occupies the entire cross section of the drift; therefore, it is a lumped 
representation of the drift temperature. Moreover, because the east-west cross-sectional 
mountain-scale model uses a line-averaged heat source, it axially smears out the differences 
between hot and cold waste package locations along the drift. 
Another difference between the modeling approaches concerns the mountain-scale 
dimensionality. The MSTHM represents three-dimensional mountain-scale heat flow for the 
entire extent of the heated repository footprint, while the east-west cross-sectional 
mountain-scale thermal-hydrologic model has a reflected boundary at the east-west midpoint of 
the repository. Thus, the east-west model assumes that the overburden thickness of the entire 
repository area can be approximated with the overburden thickness between the western 
repository boundary and the midpoint of the repository. Because the eastern half of the 
repository has much less overburden thickness than the western half, this east-west symmetry 
approximation effectively over represents the effective overburden thickness for the eastern half 
of the repository. The cross-sectional geometry of the east-west mountain-scale model implicitly 
assumes that mountain-scale heat loss in the north-south dimension is insignificant, which is a 
reasonable assumption given the large north-south dimension of the repository. 
Another difference between the two modeling approaches concerns the areal power density 
applied in the respective models. The initial areal power density in the MSTHM is 92.3 
kW/acre, while it is 99.4 kW/acre in the east-west cross-sectional mountain-scale model. Thus, 
the east-west model has a 7.7 percent larger areal power density than does the MSTHM 
(Buscheck et al. 1998 [DIRS 148521], p. 3-10). 
At the center of the repository (the l4c3 location in Buscheck et al. 1998 [DIRS 148521], Table 
2-2) the respective modeling approaches predict almost an identical duration of boiling (Figure 
6.4-1a). At the edge repository location, which is 100 m from the western edge of the repository 
in the MSTHM (the l4c1 location in Buscheck et al. 1998 [DIRS 148521], Table 2-2), the 
east-west cross-sectional mountain-scale model predicts a longer duration of boiling than does 
the MSTHM (Figure 6.4-1b). One reason for this difference is that the east-west model 
representation of the heated repository footprint extends slightly further to the west than in the 
MSTHM. 
During the postboiling period, the temperatures predicted by the respective modeling approaches 
are in good agreement. During the early time heat-up period, the coarse (lateral and axial) 
grid-block spacing in the east-west cross-sectional mountain-scale model does not capture the 
rapid drift-wall temperature rise that the more finely gridded MSTHM predicts. Because of the 
coarse lateral grid-block spacing in the east-west model, it smears out the lateral temperature 
gradient between the drift and the mid-pillar location. Therefore, it tends to overpredict the 
temperature at the mid-pillar location and thereby prevent condensate from shedding between 
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drifts. The fine lateral grid-block spacing in the MSTHM captures the influence that the lateral 
temperature gradient has on allowing condensate to shed between drifts. The tendency for the 
east-west cross-sectional mountain-scale model to underrepresent condensate shedding results in 
a more substantial condensate buildup above the repository horizon. Also, the line-averaged 
heat-source approximation smears out differences in temperature between otherwise hot and 
cold waste package locations and thereby preventing condensate from breaking through cold 
waste package locations along the drift. Altogether, the underprediction of condensate shedding 
between drifts and condensate breakthrough at cold waste package locations causes the 
east-west cross-sectional mountain-scale model to build up more condensate above the 
repository horizon that leads to episodic heat-pipe behavior. This episodic behavior is exhibited 
by the rapid decline from superheated conditions to heat-pipe conditions (Figure 6.4-1a) and the 
rapid rise once again to superheated conditions at about 400 years. Notice that during the second 
superheated period predicted by the east-west model, the temperature climbs to be almost exactly 
that predicted by the MSTHM. 
Given the differences between the MSTHM and the east-west cross-sectional mountain-scale 
model, the agreement between the two models is adequate. Moreover, the differences in 
predicted temperatures between the MSTHM and the east-west cross-sectional mountain-scale 
model are within the range of temperature differences resulting from parametric uncertainty 
(Tables 6.3-30 and 6.3-31). Therefore, the impact of conceptual-model uncertainty is no larger 
than that of parametric uncertainty. On the basis of this comparison, it is determined that the 
MSTHM is validated for its intended use. 
6.5 FEPS 
The development of a comprehensive list of features, events, and processes (FEPs) potentially 
relevant to postclosure performance of the Yucca Mountain repository is an ongoing, iterative 
process based on site-specific information, design, and regulations. The approach for developing 
an initial list of FEPs in support of TSPA-SR (CRWMS M&O 2000 [DIRS 153246]) was 
documented in The Development of Information Catalogued in REV00 of the YMP FEP 
Database (BSC 2001 [DIRS 154365]). The initial FEP list contained 328 FEPs, of which 176 
were included in the TSPA-SR models (CRWMS M&O 2000 [DIRS 153246], Tables B-9 to 
B-17). To support TSPA-LA, the FEP list was re-evaluated in accordance with The Enhanced 
Plan for Features, Events, and Processes (FEPs) at Yucca Mountain (BSC 2002 [DIRS 158966], 
Section 3.2). Table 6.5-1 provides a listing of FEPs. 
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Table 6.5-1. FEPs Addressed by This Report 
FEP Name Section Where Disposition is Addressed 
2.1.06.06.0A Effects of drip 
shield on flow 
6.3 
2.1.08.03.0A Repository dry-out 
due to waste heat 
6.3 
2.1.08.04.0A Condensation 
forms on roofs of 
drifts (drift-scale 
cold traps) 
7.5 and 6.3 
2.1.08.04.0B Condensation 
forms at repository 
edges (repositoryscale 
cold traps) 
7.5 
2.1.08.05.0A Flow through invert 6.3 
2.1.08.06.0A Capillary effects 
(wicking) in EBS 
6.3 
2.1.08.11.0A Repository 
resaturation due to 
waste cooling 
6.3 
2.1.11.01.0A Heat generation in 
EBS 
6.3 
2.1.11.02.0A Non-uniform heat 
distribution in EBS 
6.3 
2.1.11.09.0A Thermal effects on 
flow in the EBS 
6.3 and 7.5 
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7. MODEL VALIDATION 
AP-SIII.10Q requires that TSPA model components be validated for their intended purpose and 
stated limitations, and to the level of confidence required by a components relative importance 
to the performance of the repository. Section 1 of this report provides the intended use of the 
MSTHM and the model limitations. 
The governing technical work plan (BSC 2004 [DIRS 170950], Section 2.3.2) identifies Level II 
as the appropriate level of validation for the MSTHM. The appropriateness of Level II is based 
on the position that the outputs of this model are judged to be of moderate importance because 
they may impact TSPA dose results and are therefore used for demonstration of regulatory 
compliance. 
7.1 CONFIDENCE BUILDING DURING MODEL DEVELOPMENT TO ESTABLISH 
SCIENTIFIC BASIS AND ACCURACY FOR INTENDED USE 
In accordance with AP-2.27Q, Planning for Science Activities, Level II validation includes a 
discussion of model development. In particular, this report documents decisions implemented 
during model development that build confidence and verify that a reasonable, credible technical 
approach using scientific and engineering principles was taken. The development of the model 
is documented in accordance with the requirements of Section 5.3.2(b) of AP-SIII.10Q and 
Attachment 3 of AP-2.27Q. The development of the multiscale thermohydrologic model has 
been conducted according to these criteria, as follows: 
1. Selection of input parameters and/or input data, and a discussion of how the selection 
process builds confidence in the model. [AP-SIII.10Q 5.3.2(b) (1) and AP-2.27Q 
Attachment 3 Level I (a)] 
The inputs to the multiscale thermohydrologic model have all been obtained from 
controlled sources. All data for the natural system are from studies specific to the site 
(Section 4.1.1). All design information is from IEDs (Section 4.1.2). Section 4.1 
includes a discussion about selection of input and design parameters. The input data and 
information and their sources are summarized in Table 4.1-1. Table 4.1-2 summarizes 
changes to the waste package and drip shield information that occurred during model 
development. The details of the relative impacts of these changes are discussed in 
sections 4.1.2.1 through 4.1.2.7. Additional discussion of material properties used, 
including the rationale for use, are contained in Section 5.3. 
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)]. 
Initial and boundary conditions for the MSTHM calculations of repository performance 
are based on inputs from other project documents (Section 4.1) and the assumptions are 
documented in Section 5. Descriptions of design features are documented in IEDs. 
Predicted efficiency of the ventilation system is documented in Ventilation Model and 
Analysis Report (BSC 2004 [DIRS 169862]). Surface and water table conditions are 
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Multiscale Thermohydrologic Model 
documented in Mountain-Scale Coupled Processes (TH/THC/THM) (BSC 2004 [DIRS 
169866]). Percolation fluxes are documented in UZ Flow Models and Submodels (BSC 
2004 [DIRS 169861]). These inputs were sufficient to define complete initial and 
boundary conditions for the MSTHM submodels which can be found in Sections 6.2.5, 
6.2.6, 6.2.7, and 6.2.8. Additional simulation cases were set up to cover the low 
probability seismic collapsed-drift scenario in Sections 6.2.9, 6.2.10, and 6.2.11. Results 
are presented in Section 6.3. The MSTHM addresses the three-dimensional spatial and 
temporal (e.g., percolation flux and ventilation heat-removal efficiency) distribution of 
natural-system parameters, boundary conditions, and design information that influence 
the thermal-hydrologic response throughout the repository, which assures consistency of 
the MSTHM outputs. The MSTHM predictions have been thoroughly inspected, as 
displayed in plots and tables throughout Section 6.3, and thoroughly tested, by way of 
sensitivity analyses documented in Section 6.3, to assure the reasonableness and 
appropriateness of the MSTHM outputs. 
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.10Q 5.3.2(b)(3) and AP-2.27Q Attachment 3 Level 1 (d) and (f)]. 
Discussion of model uncertainties and their impacts on model results are provided in 
Section 6.3.1 which discusses the TSPA-LA base case, Section 6.3.4 which discusses the 
combined influences of percolation-flux and host-rock thermal conductivity uncertainty, 
and Section 6.3.7 which discusses the influence of a low-probability-seismic 
collapsed-drift scenario on in-drift thermal-hydrologic conditions relative to the 
TSPA-LA base case. 
4. Formulation of defensible assumptions and simplifications. [AP-2.27Q Attachment 3 
Level I (b)]. 
Discussion of assumptions and simplifications are provided in Sections 5, 6.1, and 6.2. 
Additional discussion of simplifications can be found in Appendix IX. 
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 is demonstrated by the conceptual and mathematical 
formulations for the mass and energy balance equations in Section 6.2.3 and the selection 
and use of the NUFT code based on those physical principles. 
The purpose of the MSTHM plays a key role in its validation. The purpose of the MSTHM is to 
predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and 
variability, in the repository emplacement drifts, and in the adjoining host rock for the repository 
at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic 
responses across the repository; this is quite different from predicting a single expected 
thermal-hydrologic response. This range in thermal-hydrologic conditions must capture the 
influence of the key processes and conditions, including the uncertainty and variability 
associated with those processes and conditions. Thus, the influence of conceptual-model 
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uncertainty must be judged relative to the influence of parametric uncertainty on the range of 
predicted thermal-hydrologic responses. 
The propagation of parametric uncertainty in the MSTHM addresses the two key natural system 
parameters: host-rock thermal conductivity and percolation flux. A sensitivity study of the 
influence of hydrologic-property uncertainty supports the conclusion that hydrologic-property 
uncertainty does not need to be propagated in the MSTHM calculations of in-drift temperature 
and relative humidity. The propagation of percolation-flux uncertainty and host-rock thermal 
conductivity uncertainty on repository-wide MSTHM output is captured with five 
infiltration-flux host-rock thermal conductivity cases (Table 6.3-37). For these five data sets, the 
range in peak drift-wall temperature is from 92.3C to 175.2C, with a median drift-wall 
temperature of 133.0C; the range in peak waste package temperature is from 102.0C to 
203.1C, with a median waste package temperature of 153.3C (Table 6.3-38). These five cases 
also result in a wide range of waste package relative-humidity histories as is shown in Figure 
6.3-53. For the five infiltration-flux host-rock thermal conductivity cases, the time when 
drift-wall boiling ceases ranges from no boiling to 2,176.5 years, with a median time of 721.0 
years (Table 6.3-39). The percentage of waste packages that may experience no boiling at the 
drift wall is extremely low (0.01% of all waste packages in the repository). 
The validation of the MSTHM involves the validation of both the MSTHM methodology and the 
submodels, or components, used in the MSTHM. Note that all MSTHM submodels (called the 
SDT, SMT and DDT submodels) are executed with the NUFT v3.0s code (Section 3.1.1). 
Because the SDT, SMT and DDT submodels are conduction-only calculations, which utilize 
standard scientific methods (e.g., Fouriers Law) to perform the calculations, they do not require 
separate validation in this report in the manner that is applied to the LDTH submodel. Moreover, 
the SDT, SMT, and DDT submodels are never applied as stand-alone models for analysis, as is 
the case for the LDTH submodel (e.g., Section 6.3.9). It should be noted that validation testing 
of the NUFT v3.0s code included conduction-only test problems (bmrk002 and verif02), which 
are described in the Validation Test Plan for NUFT 3.0s (LLNL 2002 [DIRS 170259]; LLNL 
2000 [DIRS 170258]). These conduction-only test problems are sufficient to validate the usage 
of the conduction-only submodels in the MSTHM. In Section 7.5, the MSTHM is validated as a 
whole. However, it would be inappropriate to validate the individual components (or 
submodels) of the MSTHM as independent entities in Section 7.5 because they do not function 
as independent entities within the MSTHM methodology. The LDTH submodel is validated in 
Section 7.4 against the Drift Scale Test, because it is sometimes applied in this report as a 
stand-alone model to conduct sensitivity analyses (e.g., see Section 6.3.9). 
The manner in which the MSTHM utilizes the SDT, SMT, and DDT submodels is justified and 
further described in Sections 5.3.2.1 and 6.2.4. The DDT submodel represents thermal radiation 
inside the emplacement drifts and also represents the influence of natural convective heat flow in 
the drifts through the use of an equivalent thermal conductivity that is based on a correlation 
given by Francis et al. (2003 [DIRS 164602], Table 6) (Section 6.2.8.5). Thus, the DDT does 
not model natural convection in the drift; it uses a correlation derived elsewhere as indicated. 
The software qualifications of NUFT v3.0s and NUFT v3.0.1s include test problems that 
demonstrate the validity of NUFT in modeling a one-dimensional thermal-conduction problem 
(bmrk 002), a three-dimensional thermal-conduction problem (verif02), and a three-dimensional 
thermal-radiation problem (verif03) (LLNL 2002 [DIRS 170259]; LLNL 2000 [DIRS 170258]). 
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Multiscale Thermohydrologic Model 
The NUFT code uses an industry-standard finite-difference method that solves the mass balance 
of water and air and an energy balance. 
7.2 CONFIDENCE BUILDING AFTER MODEL DEVELOPMENT TO SUPPORT 
THE SCIENTIFIC BASIS OF THE MODEL 
Level II validation must include at least one postdevelopment method described in Paragraph 
5.3.2c of AP-SIII.10Q. The governing TWP (BSC 2004 [DIRS 170950], Section 2.3.3) 
describes two such activities. One is a corroboration of model results with data acquired from 
the Drift Scale Test (DST). 
The other validation method is a comparison to a validation case, consisting of a porous-medium 
simulation of multiple emplacement drifts and the rock surrounding them. The validation case 
utilizes an alternative model, which is a monolithic three-dimensional thermohydrologic model. 
The results from the alternative model are compared with those from an implementation of the 
MSTHM methodology specifically pertaining to the validation case. The locations for 
comparison include the repository center and the repository edge. 
In addition to the postdevelopment validation activities listed in the TWP, this section reports 
two other confidence-building comparisons. One is a comparison of results against the Large 
Block Test (LBT). The other is a comparison of MSTHM results against alternative numerical 
models. All of these comparisons are summarized in the following list and described in greater 
detail throughout the remainder of this section: 
 Comparison of NUFT LDTH submodel results against the Large Block Test 
Thermal Tests Thermal-Hydrological Analyses/Model Report (CRWMS M&O 2000 
[DIRS 146921], Section 6.2.4) documents the comparison of NUFT thermal-hydrologic 
model calculations against measurements made in the Large Block Test. This 
confidence-building activity supplements the activities required by the TWP and 
therefore has no specific validation criterion. The difference between the modeled and 
field-measured thermal-hydrologic behavior is compared with the impact of parameter 
uncertainty on thermal-hydrologic behavior. A summary of this comparison is given in 
Section 7.3. The NUFT thermal-hydrologic model used in this confidence-building 
study is a three-dimensional equivalent to the two-dimensional LDTH submodels 
(Section 6.2.6) used in the MSTHM. These thermal-hydrologic calculations used NUFT 
v3.0s (Section 3.1.1). The sources of the test data are listed in Table 4.4-1. 
 Comparison of NUFT LDTH submodel results against the Drift Scale Test 
Section 7.4 documents the comparison of NUFT thermal-hydrologic model calculations 
against measurements made in the Drift Scale Test. The adequacy of the agreement 
between the modeled and field-measured thermal-hydrologic behavior is judged in light 
of the impact of parameter uncertainty on thermal-hydrologic behavior. The NUFT 
thermal-hydrologic model used in this validation study is a three-dimensional equivalent 
to the two-dimensional LDTH submodels (Section 6.2.6) used in the MSTHM. These 
thermal-hydrologic calculations used NUFT v3.0.1s (Section 3.1.2), which is essentially 
identical to NUFT v3.0s except that NUFT v3.0.1s is able to address nested-mesh 
problems having a large number of nests, while NUFT v3.0s can handle nested meshes 
with two nests. One validation criterion for this comparison is that temperature changes 
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should agree within 30 percent for the heating phase (BSC 2004 [DIRS 170950], Section 
2.2.5). The 30-percent validation criterion for temperature rise (above ambient) is 
consistent with the magnitude of the influence of the parametric uncertainty of host-rock 
thermal conductivity and percolation flux on temperature. As shown in Table 6.3-30, 
the combined influence of host-rock thermal conductivity uncertainty and 
percolation-flux uncertainty causes the rise in peak drift-wall temperature (above 
ambient) to vary by about 30 percent. Differences greater than 30 percent may be 
accepted if they resulted from short-term or localized transients in the test conditions, or 
from instrument response. Another criterion is that matrix liquid saturation trends 
should be qualitatively the same with respect to location and direction. Table 4-9 lists 
the sources for results of the Drift Scale Test. 
 Comparison of the MSTHM results against a monolithic three-dimensional 
thermal-hydrologic modelUsing a three-drift repository test case (which is a 
scaled-down version of the repository), the validity of the MSTHM approach is 
demonstrated by comparing the results of the MSTHM against a corresponding 
monolithic three-dimensional thermal-hydrologic model that uses a nested mesh. This 
validation test case is similar to that reported by Buscheck et al. (2003 [DIRS 164638]). 
A summary of this comparison is given in Section 7.5. For this comparison, NUFT 
v3.0s is used for the MSTHM calculations, while NUFT v3.0.1s is used in the 
corresponding monolithic three-dimensional thermal-hydrologic model that uses a 
nested mesh. The validation criterion for this comparison is based on the maximum 
model-to-model differences for changes in temperature or relative humidity at either of 
the two representative locations (representing the repository center and edge), at any 
time during the simulation. The criterion is that each maximum difference must be 
smaller than a range of uncertainty in the relevant parameter. The pertinent range of 
uncertainty is the range in the results generated by the MSTHM for ranges of percolation 
flux and host rock thermal conductivity in full-repository simulations (BSC 2004 [DIRS 
170950], Section 2.2.5). These results are propagated to TSPA (BSC 2004 [DIRS 
170950], Section 2.2.4). 
 Comparison of MSTHM results against alternative numerical modelsBuscheck et 
al. (1998 [DIRS 148521]) document a comparison between the results of the MSTHM 
against a three-dimensional east-west cross-sectional mountain-scale thermal-hydrologic 
model developed at Lawrence Berkeley National Laboratory (Haukwa et al. 1998 [DIRS 
117826]). This confidence-building activity is another supplement to the activities 
required by the TWP; there are no specific validation criteria for this comparison. The 
difference between the model results is compared with the impact of parameter 
uncertainty on thermal-hydrologic behavior. A brief summary of this comparison is 
given in Section 6.4. 
7.3 COMPARISON OF NUFT THERMAL-HYDROLOGIC MODEL AGAINST THE 
LARGE BLOCK TEST 
The NUFT thermal-hydrologic model used to model the Large Block Test (LBT) is described in 
Section 6.1.4 of Thermal Tests Thermal-Hydrological Analyses/Model Report (CRWMS M&O 
2000 [DIRS 146921]). The NUFT thermohydrologic model used in this confidence-building 
study is a three-dimensional equivalent to the two-dimensional LDTH submodels (Section 6.2.6) 
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Multiscale Thermohydrologic Model 
used in the MSTHM. As in the case of the Drift-Scale Test (DST), the LBT was located in the 
Tptpmn (tsw34) unit. In the LBT, a block of excavated rock (3 m by 3 m by 4.5 m) was heated 
for one year with five heaters placed in an array of horizontal boreholes 2.75 m from the top of 
the block. Temperatures were constantly monitored during the test, while liquid-phase 
saturations were measured on a regular basis. The source DTN for the heater power history is 
listed in Table 4.4-1. Note that location-specific thermal or hydrologic property data were not 
available for the LBT. As described below, two different data sets were used to model the LBT, 
including that used in the TSPA-SR base-case MSTHM calculations and that used in the 
TSPA-LA base-case MSTHM calculations (which are described in this report). 
7.3.1 Comparison of Simulated and Field-Measured Temperatures 
Figure 7.3-1 shows the NUFT-simulated versus measured temperature profile along Borehole 
TT1 at five times from 30 to 400 days. The source DTNs for all field measurements of 
temperatures are listed in Table 4.4-1. Because the LBT is in the Tptpmn (tsw34) unit, the 
NUFT thermal-hydrologic models apply the thermal and hydrologic properties for that unit. 
Two cases are considered: (1) the mean infiltration-flux hydrologic property set used in the 
TSPA-SR base-case MSTHM calculations (BSC 2001 [DIRS 158204]) and (2) the 
modified-mean infiltration-flux hydrologic property set used in the TSPA-LA base-case 
MSTHM calculations. The source of the mean infiltration-flux hydrologic property set used in 
the TSPA-SR base-case MSTHM calculations is DTN: LB990861233129.001 [DIRS 110226], 
Table 4.4-1. For the Tptpmn (tsw34) unit, the modified-mean infiltration-flux property set used 
in the TSPA-LA base-case MSTHM calculations is the same mean infiltration-flux property set 
(DTN: LB0208UZDSCPMI.002 [DIRS 161243]). Both the TSPA-SR and TSPA-LA cases are 
in good agreement with the field-measured temperature data. However, both cases predict 
slightly higher temperatures than the field-measured values, with the TSPA-LA case resulting in 
the highest temperatures. As is discussed below, the primary cause for the higher simulated 
temperatures for the TSPA-LA case is the large gas-phase pressure buildup in the matrix 
(Figure 7.3-2b, d, and f). 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations include two cases. The TSPA-LA case uses the modified-mean infiltration-flux 
hydrologic property values for the Tptpmn (tsw34) unit that are used in the MSTHM calculations for the 
TSPA-LA base case (Section 6.3). Note that for the Tptpmn (tsw34) unit, the mean and modified-mean 
property sets (discussed in Section 6.3.1) are the same. The TSPA-SR case uses the mean infiltration-
flux property values for the Tptpmn (tsw34) unit that are used in the MSTHM calculations for the TSPA-SR 
base case (BSC 2001 [DIRS 158204]). 
Figure 7.3-1. Comparison of the NUFT-Simulated and Measured Temperatures along Borehole TT1 in 
the Large Block Test, Given at (a) 30 Days, (b) 100 Days, (c) 200 Days, (d) 300 Days, 
and (e) 400 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT-simulated gas-phase pressures in the matrix are also plotted at (b) 100 days, (d) 365 days, and 
(f) 500 days. Note that there are no field measurements of gas-phase pressure in the matrix. The NUFT 
simulations include two cases. The TSPA-LA case uses the modified-mean infiltration-flux hydrologic 
property values for the Tptpmn (tsw34) unit that are used in the MSTHM calculations for the TSPA-LA 
base case (Section 6.3). Note that for the Tptpmn (tsw34) unit, the mean and modified-mean property 
sets (discussed in Section 6.3.1) are the same. The TSPA-SR case uses the mean infiltration-flux 
property values for the Tptpmn (tsw34) unit that are used in the MSTHM calculations for the TSPA-SR 
base case. 
Figure 7.3-2. Comparison of the NUFT-Simulated and Measured Liquid-Phase Saturations in the 
Matrix along Borehole TN3, Given at (a) 100 Days, (c) 365 Days, and (e) 500 Days 
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7.3.2 Comparison of Simulated and Field-Measured Liquid-Phase Saturations in the 
Matrix 
Figure 7.3-2 shows the NUFT-simulated and measured liquid-phase saturation profile along 
TN3, which is a vertical borehole used for neutron probe measurements of water content. Note 
that the liquid-phase saturations discussed in this section apply to the matrix, rather than to the 
fractures. The source DTNs for all liquid-phase saturation measurements are listed in Table 
4.4-1. Figure 7.3-2 also shows the NUFT-simulated gas-phase pressures in the matrix; note that 
there are no field measurements of gas-phase pressure in the matrix. At 100 days, the NUFT 
simulation for the TSPA-SR case shows a well-developed dryout zone, while the TSPA-LA case 
shows almost no dryout. An important distinction between these two cases is that the matrix 
permeability for the TSPA-SR case is 23 times greater than it is for the TSPA-LA case. The 
small matrix permeability in the TSPA-LA case causes more gas-phase pressure buildup, which 
drives the saturation (or boiling) temperature to be higher, thereby throttling the rate of 
vaporization and rock dryout. The difference in gas-phase pressure buildup is pronounced at 365 
days (Figure 7.3-2d), which causes a large difference in the dryout zones for these two cases 
(Figure 7.3-2c). The simulated dryout zone for the TSPA-SR case is in close agreement with the 
measured dryout zone, which in the TSPA-LA case results in little dryout. At 365 days the 
gas-phase pressure nearly reaches 5 atm for the TSPA-LA case, while for the TSPA-SR case it is 
less than 1.5 atm (Figure 7.3-2d). Notice that the TSPA-SR case produces two zones of 
increased gas-phase pressure with each zone corresponding to the boiling zones above and below 
the heater horizon. 
Although the NUFT-simulated dryout lags behind the LBT-observed dryout for the TSPA-LA 
case, this is not adverse to model confidence. The reason this is not adverse to model confidence 
is that rock dryout predicted for repository heating conditions is much slower, occurring over 
much longer time frames than that applicable to the LBT. Consequently, although there may be 
some lag in predicting dryout under repository conditions in regions of the repository where the 
Tptpmn (tsw34) unit is the local host-rock unit, it cannot be nearly as great as that illustrated for 
the LBT conditions, and the long-term MSTHM-predicted saturation histories should closely 
correspond to those applicable to repository heating conditions. 
A comparison of the field-measured liquid-phase saturations at 365 days (when heating ceased) 
and at 500 days (Figure 7.3-2c and e) indicate that rewetting of the dryout zone in the LBT 
progresses at a slow rate. Similarly, a comparison of the NUFT-simulated liquid-phase 
saturations for 365 and 500 days indicates that rewetting progresses at a slow rate. Therefore, 
the NUFT thermal-hydrologic model, for both the TSPA-SR and TSPA-LA hydrologic property 
sets, provides a valid representation of rewetting behavior observed in the LBT. 
7.3.3 Summary of Model Validation Using LBT Data 
The good agreement between the NUFT-simulated and measured temperatures demonstrates that 
the thermal conductivity values in the TSPA-SR and TSPA-LA property sets are appropriate. 
Moreover, this agreement demonstrates that the NUFT thermal-hydrologic model provides a 
valid representation of heat flow in the LBT. The differences between the predicted and 
field-measured temperatures are well within the relative impact of parametric uncertainty (Tables 
6.3-30 and 6.3-31). The agreement between the simulated and measured dryout behavior 
demonstrates that the NUFT thermal-hydrologic model provides a valid representation of dryout 
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behavior for the TSPA-SR hydrologic property set. The NUFT thermal-hydrologic model, using 
both the TSPA-SR and TSPA-LA hydrologic property sets, also provides a valid representation 
of rewetting behavior observed in the LBT. The cause for the differences between the 
NUFT-simulated dryout (using the TSPA-LA hydrologic property set) and the measured dryout 
data is well understood and does not affect the conclusion that the NUFT thermal-hydrologic 
model of the LBT provides a valid representation of dryout behavior. 
7.4 VALIDATION OF THE LDTH SUBMODEL USING THE DRIFT SCALE TEST 
The three-dimensional thermal-hydrologic model of the Drift-Scale Test (DST) is a 
three-dimensional equivalent of the two-dimensional LDTH submodels (Section 6.2.6) used in 
the MSTHM. Both the three-dimensional thermal-hydrologic model of the DST and the 
two-dimensional LDTH submodel use the NUFT code. Both models use the same (lateral) 
cross-sectional approximation of the emplacement (or heater) drift and both use the same grid 
refinement within the drift and in the near-field host rock. Both models use the same 
representation of thermal-radiative heat transfer in the drift. They both use the same effective 
thermal conductivity approach to representing the influence of natural convective heat flow in 
the drifts, which is based on a correlation by Francis et al. (2003 [DIRS 164602], Table 6) 
(Section 6.2.8.5). Both models use the same thermal and hydrologic property set. Both models 
use the same boundary conditions at the ground surface and at the water table. The only 
difference between the three-dimensional thermal-hydrologic model of the DST and the 
two-dimensional LDTH submodel is the dimensionality of the respective models. Therefore, the 
validation of the three-dimensional thermal-hydrologic model of the DST is equivalent to 
validating the two-dimensional LDTH submodels in the MSTHM. 
7.4.1 Design and Geometry of the DST 
The DST is the largest (and longest duration) in situ heater test of its kind (Figure 7.4-1). At the 
center of the DST is the Heated Drift, which is 47.5-m long with a 5.0-m diameter (similar to the 
5.5-m-diameter emplacement drifts in the repository). The thermal load comes from two kinds 
of heat sources. The Heated Drift has nine waste package-sized heat sources. Emanating from 
either side of the Heated Drift are 50 horizontal boreholes (25 on each side), containing wing 
heaters that provide additional heating to simulate (in an accelerated fashion) the influence of 
heating from neighboring emplacement drifts. Each wing heater is composed of two 
4.44-m-long segments separated by a 0.66-m gap. The outside of each wing heater is 14 m from 
the centerline of the heater drift, while the inside of each wing heater is 4.46 m from the 
centerline. The hot side of the Heated Drift is separated from the cold side with a thermally 
insulated bulkhead. The DST heating began on December 3, 1997 and continued for 1,503 days 
(4.1 years) until January 14, 2002. The DST is now in the cooldown phase and continues to be 
monitored. The source DTN for the heater power history is listed in Table 4.4-2. 
The purpose of large-scale thermal testing at Yucca Mountain is discussed in Section II.E of 
Thermal-Hydrological Analysis of Large-Scale Thermal Tests in the Exploratory Studies Facility 
at Yucca Mountain (Buscheck and Nitao 1995 [DIRS 100657]). Sections II.F and II.G of that 
report discuss the rationale and criteria for the design of large-scale thermal tests. A 
thermal-hydrologic modeling study (Buscheck and Nitao 1995 [DIRS 100657], Section IV) 
helped determine the recommended size and duration of the DST. A comprehensive description 
of the design and geometry of the DST is documented in Sections 7.2.1 and 7.2.2 of Drift-Scale 
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Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). Section 7.4 of 
that report gives a detailed and discussion of a thermal-hydrologic model validation study, 
similar to the results presented below. 
Source: BSC 2004 [DIRS 170338], Figure 7.2.1-1. 
NOTE: The bulkhead is shown as the cross-hatched region, adjacent to the Plate-Loading Niche. 
Figure 7.4-1. Plan View of the Drift Scale Test Area 
7.4.2 Description of Three-Dimensional Thermal-Hydrologic Model of the DST 
The model is designed to accurately represent the test domain and the processes governing heat 
and mass transport in the system. The test geometry, including the dimensions of the 
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stratigraphic units from the water table to the ground surface, is adequately represented in this 
full three-dimensional model. Fracture and matrix interaction is handled using the 
dual-permeability model employing the active-fracture concept. The thermal-hydrologic 
simulation code NUFT v3.0.1s (Section 3.1.2) is used because of its ability to handle nested 
meshes containing many levels of nesting. The model handles heat transfer by conduction, 
convection, and radiation. The simulation time is 6 years, which includes the 4.1-year heating 
phase, and 1.9 years of the ongoing cooldown phase. 
The thicknesses of hydrogeologic units in the model were obtained by using the software routine 
YMESH v1.54 (Section 3.1.7) to extract a profile of the units located at the origin of the DST 
field coordinate system, E171432, N234060 (CRWMS M&O 1998 [DIRS 111115]). The model 
extends from the ground surface to the water table 576 m below the surface, 278 m in the 
x-direction, and 478 m in the y-direction. The center of the bulkhead is located at elevation 
1,053 m, 253 m below the ground surface, and 323 m above the water table. The test 
configuration geometry allows use of a half-symmetry model since the test is approximately 
symmetrical about the axis of the Heated Drift. The Connecting Drift, Access Observation Drift, 
and Plate-Loading Niche are not included in the model. Field data show that these structures 
have limited effect on the thermal-hydrologic response of the system within a radius of about 25 
m from the Heated Drift. 
The half-symmetry model has x-coordinate origin at the center of the bulkhead, and x positive in 
the direction away from the access drift (Northward). The y-coordinate axis is parallel to the 
axis of the Heated Drift with origin 215.9 m from the bulkhead, and positive in a general 
westerly direction. The z-direction is positive downward, with origin at the ground surface 
252.9 m above the center of the bulkhead. The root mesh contains four levels of nesting, 
permitting sufficiently fine discretization in the Heated Drift and wing heater areas, while 
limiting memory requirements and computation time for the relatively large model. Element 
dimension varies from 6 cm in the bulkhead to tens of meters away from the heated areas of the 
test. The model has a total of 58,258 active elements, 29,129 elements in each of the two 
continua. 
The origin of field coordinates is located at the center of the cold side of the bulkhead that 
separates the Heated Drift from an unheated and ventilated section of the drift. The y-axis 
extends from the origin through the bulkhead towards the back end of the Heated Drift (positive 
to west). X is positive in a direction away from the access drift (approximately north) and z is 
positive downward. The origin of field coordinates is located at approximately (0, 216, 253) 
with respect to the computational mesh. 
The Heated Drift section in the x-z plane is stair-stepped to approximate the 5-m diameter 
circular drift using a rectangular Cartesian coordinate system. The surface of the invert is 1.3 m 
below the center of the drift. Since no thermal and hydrologic properties are available for the 
invert, material properties of the host rock, Tptpmn (tsw34), are assumed to be applicable to the 
invert for the DST thermal-hydrologic calculation (Sections 5.3.1.3 and 5.3.2.5). 
The nine cylindrical heaters along the Heated Drift are modeled as having a square cross section 
with area equal to that of the 1.7-m diameter of the cylinder. There are no gaps between the 
heaters in the model; however, the thermal influence of the gaps is represented by removing 
conductive heat transfer between the ends of the heaters and by adding thermal-radiative heat 
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transfer between the ends of the heaters. Thermal-radiative heat transfer between heater and 
rock wall elements and across rock wall elements is handled in the model. No fluid flow 
between canisters is permitted. Wing heater arrays are treated as a separate smeared heat 
sources. 
7.4.2.1 Wing-Heater Arrays 
Because the wing-heater boreholes are open to the Heated Drift and because they reside in the 
area of intensive boiling they are preferential conduits for the flow of water vapor into the 
Heated Drift. Once the water vapor enters the Heated Drift it then tends to flow towards and 
through the leaky bulkhead. The NUFT thermal-hydrologic model of the DST does not 
discretely represent the wing-heater boreholes. However, it is important to include the influence 
of the wing-heater boreholes on the preferential flow of water vapor. To include the influence of 
these conduits, the fracture permeability is treated as being anisotropic over the volume of rock 
occupied by the wing-heater boreholes. The fracture permeability in the x-direction (which is 
lateral to the Heated Drift axis) is increased by a factor of 1,000 relative to the value of fracture 
permeability for the Tptpmn (tsw34) unit (Section 5.3.1.4). 
7.4.2.2 Bulkhead 
The bulkhead, which separates the hot and cold sides of the Heated Drift, is treated as being 
highly permeable (Section 5.3.1.5). This was necessary because gas-phase pressure 
measurements across the bulkhead suggest that the structure acts as a partially open boundary 
that allows substantial vapor loss from the Heated Drift. As described in Drift Scale Test 
As-Built Report (CRWMS M&O 1998 [DIRS 111115]), the bulkhead consists of a complex mix 
of steel, glass, and fiberglass insulation. As described in Section 5.3.2.6, the bulkhead in the 
Drift Scale Test is assumed to have a very large value of thermal conductivity (5.5 W/mC) and a 
thickness of 0.12 m; thus, the thermal conductance of the bulkhead is equal to 45.83 W/m2C. 
This assumption is made because portions of the bulkhead (such as the glass window) are not 
insulated and because the bulkhead is penetrated by a large array of metal conduit containing 
instrument cables and power lines. 
7.4.2.3 Initial and Boundary Conditions 
One-dimensional initialization models with the stratigraphic profile developed from the software 
routine YMESH v1.54 (Section 3.1.7) were used to establish initial conditions for the full 
three-dimensional models. Boundary conditions were obtained using the software routine 
boundary_conditions v1.0 (Section 3.1.8), a code developed for calculating boundary conditions 
for multiscale submodels based on location. For the present-day climate of the mean infiltration-
flux case the local percolation flux is 5.922 mm/yr at location of the bulkhead. This percolation 
flux is obtained for the P1-UB26@r#83:43:1 location in the MSTHM. Note that this 
nomenclature is related to the naming convection in the SMT submodel, with P1 standing for 
Panel 1, UB26 pertaining to the 26th drift in the SMT submodel, and r#83:43:1 corresponding to 
the numerical mesh in the SMT submodel. The ground surface and water table boundary 
conditions at this location were obtained from the software routine boundary_conditions v1.0 
(Section 3.1.8). Surface boundary parameters calculated were temperature, pressure, air mass 
fraction, and specific enthalpy of water. Water table parameters were temperature and pressure. 
The simulation time used for one-dimensional initialization run is 1.0  109 years, which is more 
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than enough time for the model to reach steady state. The initialization process is equivalent to 
that of the LDTH submodels. 
7.4.3 Comparison of Simulated and Field-Measured Temperatures 
Temperatures are monitored in the DST area on a continuous basis by resistance temperature 
device (RTD) sensors along 28 boreholes; thus, the boreholes containing the thermocouples are 
called RTD boreholes. The source DTNs for all field measurements of temperatures in the DST 
are listed in Table 4.4-2. The spatial layout of the 28 RTD boreholes is shown in Figure 7.2.2-1 
of Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). 
For the purpose of comparison with the simulated temperatures, a daily temperature value is 
taken at 00:00 Greenwich Mean Time. Table 7.4-1 summarizes the RTD boreholes that were 
used to compare against the NUFT-simulated temperatures. The RTD boreholes fall into four 
categories. The first three categories consist of RTD boreholes that lie within vertical planes that 
are orthogonal to the HD axis, including those oriented (1) vertically, (2) laterally, and (3) at a 
45o angle. The fourth category consists of RTD boreholes oriented in the longitudinal direction, 
which is parallel to the HD axis. The NUFT simulations considered three cases. The base case 
represents the bulkhead as being thermally insulated and permeable, thereby being leaky to gas 
flow. The sealed bulkhead case represents the bulkhead as being thermally insulated and 
impermeable, thereby allowing no gas flow across it. The high thermal conductivity Kth case is 
the same as the base case with Kth being one standard deviation above the mean, based on 
Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: ReadMe Summery.doc). 
Table 7.4-1. Summary of Thermocouple (RTD) Boreholes Used to Compare Field-Measured 
Temperatures with NUFT-Simulated Temperatures. 
Borehole 
Number Figure Orientation 
Collar X 
Coordinate 
Collar Y 
Coordinate 
Collar Z 
Coordinate 
137 7.4-3, 7.4-4 Vertical above HD (+Z) 0.775 11.918 2.510 
141 7.4-3, 7.4-4 Vertical below HD (-Z) 0.764 11.893 -1.637 
168 7.4-5, 7.4-6 Vertical above HD (+Z) -0.071 31.952 2.451 
169 7.4-5, 7.4-6 Vertical below HD (-Z) -0.003 32.007 -1.629 
170 7.4-7, 7.4-8 Vertical above HD (+Z) 0.751 39.306 2.488 
173 7.4-7, 7.4-8 Vertical below HD (-Z) 0.758 39.324 -1.623 
139 7.4-9, 7.4-10 Lateral (-X) -2.569 11.891 -0.017 
143 7.4-9, 7.4-10 Lateral (+X) 2.665 11.890 -0.008 
79 7.4-11, 7.4-12 Longitudinal (+Y) 9.460 -11.022 3.752 
80 7.4-11, 7.4-12 Longitudinal (+Y) -9.486 -11.059 3.228 
NOTE: HD = Heated Drift. The indicated orientation is relative to the Heated Drift. The 
source of the coordinates is given in Tables S00085_001 and S00085_002 of DTN: 
MO0002ABBLSLDS.000 [DIRS 147304]. 
Figure 7.4-2 shows the temperature contours just prior to the end of the heating phase (1,500 
days) in plan view through a plane at the elevation of the wing-heater array and for a vertical 
cross-section midway along the length of the Heated Drift. Note that the heaters are turned off at 
1,503 days. Notice also that the highest temperatures are located close to the wing heaters and 
that the temperature contours are vertically symmetrical about the heater horizon, which 
indicates that heat flow there is dominated by heat conduction. Because the bulk permeability kb 
of the DST area is less than the threshold kb value at which buoyant gas-phase convection begins 
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to significantly influence heat flow (Buscheck and Nitao 1994 [DIRS 130561], pp. 8 to 12), heat 
flow in the subboiling region is dominated by heat conduction. 
Figures 7.4-3 through 7.4-8 compare NUFT-simulated temperatures (for three cases) with 
measured temperatures along vertically oriented RTD boreholes. Figures 7.4-9 and 7.4-10 
compare NUFT-simulated temperatures (for the three cases) with measured temperatures along 
horizontal (lateral) RTD boreholes. Figures 7.4-13 through 7.4-16 compare NUFT-simulated 
temperature histories (for the three cases) with measured temperature histories. Table 7.4-2 
summarizes the information for the thermocouple sensors used to compare NUFT-simulated and 
field-measured temperature histories. 
Table 7.4-2. Coordinates of Thermocouple Sensors Used in Figures 7.4-13, 7.4-14, and 
7.4-15 
Borehole Sensor Figure X Coordinate Y Coordinate Z Coordinate 
133 52 7.4-13 0.85 2.81 17.85 
133 23 7.4-13 0.79 2.77 9.12 
141 20 7.4-13 0.70 11.94 -8.87 
138 23 7.4-13 -6.39 11.77 6.36 
134 8 7.4-14 0.73 2.74 -3.13 
144 21 7.4-14 6.31 11.96 6.27 
162 26 7.4-14 0.79 22.9 -8.85 
163 24 7.4-14 6.39 22.72 -6.49 
138 3 7.4-15 -2.15 11.88 2.12 
139 23 7.4-15 -8.9 11.91 0.04 
144 1 7.4-15 2.07 11.92 2.04 
164 24 7.4-15 9.01 22.77 0.11 
Source: CRWMS M&O 1998 [DIRS 111115]. 
NOTE: The source of the coordinates is given in the top of Table 4.4-2. 
It is noted that these comparisons are made for the NUFT simulations that applied the 
modified-mean infiltration-flux hydrologic-property set (Section 6.3.1). In Section 7.4.4 of 
Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]), 
comparisons are made for thermal-hydrologic simulations for two property sets. The first set is 
the DS/AFM-UZ02-MEAN property set (BSC 2004 [DIRS 170338]), also known as the 
calibrated hydrologic property set, which is equivalent to the modified-mean infiltration-flux 
hydrologic-property set in the Tptpmn (tsw34), Tptpll (tsw35), and Tptpln (tsw36) units, as 
discussed in Section 6.3.1. The second set is the site-specific DKM-TT99 property set that was 
developed specifically for the DST (BSC 2001 [DIRS 157330]). An important difference 
between these two property sets is that the value of matrix permeability of the Tptpmn (tsw34) 
unit in the site-specific property set is 70 times larger than that of the calibrated property set. 
Another difference is that the calibrated property uses the Active Fracture Model (AFM), 
described in Liu et al. (1998 [DIRS 105729]), while the site-specific set does not use the AFM. 
As evident in Section 7.4.4 of Drift-Scale Coupled Processes (DST and TH Seepage) Models 
(BSC 2004 [DIRS 170338]), differences between these respective property sets affect 
above-boiling temperatures and rock dryout, which are discussed below. Several general 
observations are made about the temperature comparisons in the vertical RTD boreholes. 
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 NUFT-simulated temperatures are higher than the measured temperatures in the zone 
where temperatures exceed 96C. In Section 7.4.4.1 of Drift-Scale Coupled Processes 
(DST and TH Seepage) Models (BSC 2004 [DIRS 170338]), it was found that the 
site-specific property set resulted in lower simulated temperatures for the above-boiling 
region than those resulting from the calibrated hydrologic property set (which is the same 
as that used in NUFT DST TH simulations). Figures 7.4.4.1-1 and 7.4.4.1-2 of 
Drift-Scale Coupled Processes (DST and TH Seepage) Models (2004 [DIRS 170338]) 
show differences in simulated temperature of up to 20oC in the above-boiling region 
between these two property sets. Results from Section 7.4.4.1 of Drift-Scale Coupled 
Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]) show that better 
agreement is obtained between simulated and measured temperatures in the above-boiling 
region when the site-specific property set is used. 
 NUFT-simulated temperatures agree fairly well with measured temperatures for the lower 
temperature range (less than 80C) during the heating phase. This is consistent with 
Figures 7.4.4.1-1 and 7.4.4.1-2 of Drift-Scale Coupled Processes (DST and TH Seepage) 
Models (2004 [DIRS 170338]), which show small differences in simulated temperatures 
in the below-boiling region between the calibrated and site-specific property sets, 
together with Figures 7.4.3.1-1, 7.4.3.1-2, and 7.4.3.1-3 of Drift-Scale Coupled Processes 
(DST and TH Seepage) Models (2004 [DIRS 170338]), which show close agreement 
between measured and simulated temperatures, with the use of the site-specific property 
set. 
 The high-Kth case, which results in the lowest NUFT-simulated temperatures, is in best 
agreement with the measured temperatures during both the heating and cooldown phases. 
 The sealed-bulkhead case results in slightly higher NUFT-simulated temperatures than 
the base case (which had a leaky bulkhead). The influence of the leaky bulkhead on 
simulated temperatures is less than that resulting from a one standard-deviation range in 
thermal conductivity (which is evident in the temperature differences between the 
high-Kth case and the base case). 
 For the vertical RTD boreholes (Figures 7.4-3 through 7.4-8), plateau behavior in 
temperature close to 96C develops in virtually all of the measured temperature profiles. 
However, it appears in only a few of the NUFT-simulated temperature profiles, occurring 
at times later than observed in the field. This effect is associated with the use of the 
calibrated hydrologic property set and the low value of matrix permeability, which results 
in a large gas-phase pressure buildup in the matrix that increases the saturation (boiling) 
temperature. This is consistent with Figure 7.4.4.1-2 of Drift-Scale Coupled Processes 
(DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). The impact of the large 
gas-phase pressure buildup is discussed in more detail in Section 7.4.4 of this report. 
 At early time (175, 365, and 730 days) for the lateral RTD boreholes (Figure 7.4-9), the 
NUFT-simulated temperature profiles exhibit more plateau behavior than the measured 
temperature profiles within the zone of likely condensate shedding. 
 At later time (1,096 and 1,500 days) for the lateral RTD boreholes (Figure 7.4-10), the 
plateau behavior in temperature close to 96C appears in measured temperature profiles. 
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The NUFT-temperature profiles exhibit plateau behavior at much higher temperatures. 
This effect is associated with the use of the calibrated hydrologic property set and the low 
value of matrix permeability, which results in a large gas-phase pressure buildup in the 
matrix that increases the saturation (boiling) temperature. High gas-phase pressures in 
the matrix throttle (i.e., restrict) both vaporization and rock dryout rates. This is 
consistent with Section 7.4.4 of Drift-Scale Coupled Processes (DST and TH Seepage) 
Models (BSC 2004 [DIRS 170338]). The impact of the large gas-phase pressure buildup 
is discussed in more detail in Section 7.4.4 in this report. 
 For all boreholes, measured temperatures indicate a more rapid cooldown than 
NUFT-simulated cooldown. This effect is associated with the use of the calibrated 
hydrologic properties and the low value of matrix permeability. 
 For distances greater than 12 m from the borehole collar for the lateral RTD boreholes 
(Figures 7.4-10e and 7.4-10f), there is a pronounced scattering of the measured 
temperature profile during the cooldown phase, which is indicative of either RTD failure 
or of preferential condensate drainage down fractures into the boreholes, resulting in 
local convective cooling. Note that the outer portions of Boreholes 139 and 143 are 
located in the intervals where condensate shedding is most likely to occur. 
 At early time (175 and 365 days) for (longitudinal) Boreholes 79 and 80 (Figures 7.4-11 
and 7.4-12), NUFT-simulated temperatures agree closely with the measured 
temperatures. Good temperature agreement persists in Borehole 79 throughout the 
heating phase. 
 At later time (730, 1,096, and 1,500 days) for (longitudinal) Borehole 80 (Figures 7.4-11 
and 7.4-12), NUFT-simulated temperatures are higher than measured temperatures for the 
interval of 15 to 50 m from the borehole collar. For the interval of 0 to 15 m from the 
borehole collar, measured temperatures are higher than NUFT-simulated temperatures. 
The measured-temperature profile suggests vapor migration towards the borehole collar, 
where it condenses, with associated heat transfer along the borehole. This effect removes 
the latent heat of evaporation from the interval of 15 to 50 m from the borehole collar and 
deposits this latent heat along the interval 0 to 15 m. 
 For (longitudinal) Boreholes 79 and 80 (Figures 7.4-11 and 7.4-12), scattering of the 
measured temperature profile during the cooldown phase is indicative of either RTD 
failures or of preferential condensate drainage down fractures into the boreholes, 
resulting in local convective cooling. Note that Boreholes 79 and 80 are located in a 
region where condensate shedding is more likely to occur. 
It is important to note that the simulated large gas-phase pressure rise in the rock matrix, as 
discussed above, is transient and that temperature rise and dryout in the DST are accelerated, 
compared to those predicted for repository heating conditions. Peak temperatures in the DST 
occurred within 4 years, while peak temperatures require approximately 15 years to occur for 
repository heating conditions (e.g., Figure 6.3-23). In Section 6.3.9, which describes a 
sensitivity analysis of the influence of hydrologic properties on the in-drift thermal-hydrologic 
response, it is found that temperature (peak temperatures and boiling-period duration) and 
relative humidity are insensitive to the differences in the hydrologic properties for the four 
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host-rock units. Although matrix permeability varies by a factor of 37 over the four host-rock 
units, there is an insignificant influence on predicted thermal-hydrologic responses. Differences 
in simulated temperatures for the DST arising from differences in the value of matrix 
permeability are therefore not applicable to temperatures predicted by the MSTHM for 
repository heating conditions. Thus, although matrix permeability is seen to have a noticeable 
affect on temperatures simulated for the DST, it does not significantly affect repository 
temperature evolution predicted by thermal-hydrologic models supporting TSPA-LA. 
Source: See Table XIII-1. 
NOTE: Heaters are turned off at 1,503 days, ending the heating phase. 
Figure 7.4-2. Contours of Temperature (for the Base Case) at the End of the Heating Phase, Plotted in 
(a) Plan View Through a Horizontal Plane at the Elevation of the Wing-Heater Array and (b) 
for a Vertical Cross-Section Midway along the Heated Drift (y = 22.9 m) 
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Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. 
Figure 7.4-3. NUFT-Simulated and Measured Temperatures Compared along Borehole 137 (a, c, e) and 
Borehole 141 (b, d, f) at 175, 365, and 730 Days 
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Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-4. NUFT-Simulated and Measured Temperatures Compared along Borehole 137 (a, c, e) and 
Borehole 141 (b, d, f) at 1,096, 1,500, and 2,005 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. 
Figure 7.4-5. NUFT-Simulated and Measured Temperatures Compared along Borehole 168 (a, c, e) and 
Borehole 169 (b, d, f) at 175, 365, and 730 Days 
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Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three cases. The base case represents gas leakage through the 
bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The high-Kth 
case is the same as the base case except with the host-rock thermal conductivity Kth being one standard 
deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-6. NUFT-Simulated and Measured Temperatures Compared along Borehole 168 (a, c, e) and 
Borehole 169 (b, d, f) at 1,096, 1,500, and 2,005 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. 
Figure 7.4-7. NUFT-Simulated and Measured Temperatures Compared along Borehole 170 (a, c, e) and 
Borehole 173 (b, d, f) at 175, 365, and 730 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-8. NUFT-Simulated and Measured Temperatures Compared along Borehole 170 (a, c, e) and 
Borehole 173 (b, d, f) at 1,096, 1,500, and 2,005 Days 
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Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. 
Figure 7.4-9. NUFT-Simulated and Measured Temperatures Compared along Borehole 139 (a, c, e) and 
Borehole 143 (b, d, f) at 175, 365, and 730 Days 
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Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-10. NUFT-Simulated and Measured Temperatures Compared along Borehole 139 (a, c, e) 
and Borehole 143 (b, d, f) at 1,096, 1,500, and 2,005 Days 
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Multiscale Thermohydrologic Model 
Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. 
Figure 7.4-11. NUFT-Simulated and Measured Temperatures Compared along Borehole 79 (a, c, e) and 
Borehole 80 (b, d, f) at 175, 365, and 730 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-12. NUFT-Simulated and Measured Temperatures Compared along Borehole 79 (a, c, e) and 
Borehole 80 (b, d, f) at 1,096, 1,500, and 2,005 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-13. NUFT-Simulated and Measured Temperature Histories Compared at Borehole 133: 
Sensor 52 (a) and Sensor 23 (b), Borehole 141: Sensor 20 (c), and Borehole 138: 
Sensor 23 (d) 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-14. NUFT-Simulated and Measured Temperature Histories Compared at Borehole 134: 
Sensor 8 (a), Borehole 144: Sensor 21 (b), Borehole 162: Sensor 26 (c), and Borehole 
163: Sensor 24 (d) 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-15. NUFT-Simulated and Measured Temperature Histories Compared at Borehole 138: 
Sensor 3 (a), Borehole 139: Sensor 23 (b), Borehole 144: Sensor 1 (c), and Borehole 
164: Sensor 24 (d) 
7.4.4 Comparison of Simulated and Field-Measured Liquid-Phase Saturations in the 
Matrix 
The source DTNs for all field measurements of liquid-phase saturations in the DST are listed in 
Table 4.4-2. Note that all of the liquid-phase saturations discussed in this section apply to the 
matrix, rather than to the fractures; thus, they are called matrix liquid-phase saturations. Figure 
7.4-16 shows the matrix liquid-phase saturation contours near the end of the heating phase (1,500 
days) in plan view through a plane at the elevation of the wing-heater array and for a vertical 
cross-section midway along the length of the Heated Drift. Note that the heaters are turned off at 
1,503 days. The maximum spatial extent of rock dryout occurs at the end of the heating phase. 
The dryout zones have coalesced between the wing-heater arrays and the Heated Drift. Also, 
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rock dryout is vertically symmetrical about the heater horizon, indicating that condensate 
shedding is occurring efficiently around the edges of the boiling/rock-dryout zone. 
Source: See Table XIII-1. 
NOTE: Heaters are turned off at 1,503 days, ending the heating phase. 
Figure 7.4-16 Contours of Liquid-Phase Saturation (for the Base Case) in the Matrix at the End of the 
Heating Phase, Plotted in (a) Plan View Through a Horizontal Plane at the Elevation of 
the Wing-Heater Array and (b) for a Vertical Cross-Section Midway along the Heated Drift 
(y = 22.9 m) 
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Figures 7.4-17 through 7.4-19 compare NUFT-simulated and measured matrix liquid-phase 
saturation profiles along the Neutron Probe boreholes. Boreholes 79 and 80 are described in 
Table 7.4-1, while Borehole 68 is an inclined borehole passing below the Heated Drift, as is 
shown in Figure 7.2.2-3 of Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 
2004 [DIRS 170338]). All of the comparisons of matrix liquid-phase saturation profiles clearly 
indicate that the NUFT-simulated rock dryout lags far behind the dryout measured in the field. 
Figure 7.4-20 shows the NUFT-simulated time histories of temperature, liquid-phase saturation, 
and gas-phase pressure in the matrix at two locations: 20 and 27 m from the collar in Borehole 
68. An inspection of Table 7.4-3, which summarizes NUFT-simulated temperature, liquid-phase 
saturation, and gas-phase pressure in the matrix at those locations, indicates that high gas-phase 
pressure is throttling vaporization and delaying rock dryout (indicated by the NUFT-simulated 
matrix liquid-phase saturation) compared to the observed dryout rate in the DST (indicated by 
field measurements of matrix liquid-phase saturation). The implication is that the use of a larger 
value of matrix permeability in the NUFT thermal-hydrologic model would result in less of a 
delay in NUFT-simulated rock dryout compared to the observed dryout rate in the DST. This 
conclusion is supported by the comparison of NUFT-simulated and observed rock dryout for the 
Large Block Test (Figure 7.3-2), which showed that the use of a larger value of matrix 
permeability resulted in a larger dryout zone. As discussed earlier, this is also consistent with the 
discussion in Section 7.4.4 of Drift-Scale Coupled Processes (DST and TH Seepage) Models 
(BSC 2004 [DIRS 170338]). 
Table 7.4-3. NUFT-Simulated (Base-Case) Temperature, Liquid-Phase Saturation, and Gas-Phase 
Pressure in the Matrix Summarized at 20 and 27 m from the Collar of Borehole 68. 
Distance (m) 
From Collar of 
Borehole 68 
Time 
(days) 
Temperature 
(C) 
Liquid-Phase 
Saturation 
Gas-Phase 
Pressure in 
Matrix (atm) 
Saturation 
Temperature from 
Steam Tables (C) 
20 877 128.7 0.806 2.600 128.7 
20 1,242 143.9 0.684 4.032 143.9 
20 1,500 150.9 0.560 4.864 150.9 
20 1,917 118.2 0.376 1.946 118.2 
27 877 121.8 0.847 2.100 121.8 
27 1,242 139.7 0.721 3.582 139.7 
27 1,500 147.8 0.632 4.476 147.8 
27 1,917 128.0 0.462 2.562 128.0 
NOTE: These values are based on data plotted in Figure 6.3-20. 
The underlying cause for the NUFT-simulated dryout behavior lagging behind the dryout 
behavior observed in the DST is the low value of matrix permeability in the Tptpmn (tsw34) in 
the modified-mean infiltration-flux hydrologic property set, which results in a large gas-phase 
pressure buildup in the matrix. This gas-phase pressure buildup throttles (i.e., restricts) the rate 
of vaporization and delays dryout of the host rock in the DST. Eventually, the spatial extent of 
the NUFT-simulated dryout zones approaches that of the measured dryout zones. The cause of 
the throttled dryout is consistent with the discussion in Section 7.4.4.2 of Drift-Scale Coupled 
Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). The influence of matrix 
permeability on dryout is evident by comparing Figure 7.4.4.2.1a (which used the calibrated 
hydrologic property set, which is the same as the modified-mean infiltration-flux hydrologic 
property set in the Tptpmn, Tptpll, and Tptpln units) with Figure 7.4.4.2.1b (which used the 
site-specific property set), both of which are from BSC (2004 [DIRS 170338]). The site-specific 
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property set, which has a larger value of matrix permeability, results in a larger simulated rock 
dryout zone than that simulated with a smaller value of matrix permeability (Figures 7.4.4.2.1a 
and 7.4.4.2.1b from BSC 2004 [DIRS 170338]). 
A comparison of the measured matrix liquid-phase saturation profiles at 1,510 days 
(approximately when heating ceased) and 1,917 days shows that the dryout zone continues to 
expand during the cooldown phase. Thus, the DST measurements indicate that no rewetting has 
commenced prior to 1,917 days. Similarly, the NUFT-simulated matrix liquid-phase saturations 
continue to decrease during the cooldown phase. Thus, the NUFT thermal-hydrologic model 
agrees with the field measurements of rewetting behavior in the DST. 
The lag in simulated dryout for the DST is a transient effect. As noted earlier, heating conditions 
for the DST result in an accelerated temperature rise and rock dryout, compared to those 
predicted for repository heating conditions. Although the comparison of NUFT-simulated dryout 
with the DST-observed dryout shows that NUFT-simulated dryout lags behind the 
DST-observed dryout, this is not important to the application of the MSTHM for post-closure 
repository predictions. This is because rock dryout predicted for repository heating conditions is 
much slower, occurring over much longer time frames than occurred during the DST. Within 
four years, the DST-observed rock dryout approaches the NUFT-simulated dryout. Under 
repository heating conditions, predicted rock dryout occurs over a much longer timeframe 
(hundreds to thousands of years as shown in Figure 6.3-22c) than was applicable to the DST. 
This conclusion is consistent with the discussion in Section 7.4.4.2 of Drift-Scale Coupled 
Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). Summarizing, compared 
to the typical duration of rock dryout predicted for repository heating conditions, the duration of 
the DST-observed lag in rock dryout is insignificant. 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-17. NUFT-Simulated and Measured Liquid-Phase Saturations in the Matrix Compared along 
Borehole 68 at (a) 200 Days, (b) 350 Days, (c) 877 Days, (d) 1,242 Days, (e) 1,510 Days, 
and (f) 1,917 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-18. NUFT-Simulated and Measured Liquid-Phase Saturations in the Matrix Compared along 
Borehole 79 at (a) 200 Days, (b) 365 Days, (c) 877 Days, (d) 1,242 Days, (e) 1,510 Days, 
and (f) 1,917 Days 
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Source: See Table XIII-1. 
NOTE: The NUFT simulations are for the three indicated cases. The base case represents gas leakage through 
the bulkhead, while the sealed-bulkhead case does not allow gas leakage through the bulkhead. The 
high-Kth case is the same as the base case except with the host-rock thermal conductivity Kth being one 
standard deviation higher than the mean. Note that the heaters are turned off at 1,503 days. 
Figure 7.4-19. NUFT-Simulated and Measured Liquid-Phase Saturations in the Matrix Compared along 
Borehole 80 at (a) 200 Days, (b) 365 Days, (c) 877 Days, (d) 1,242 Days, (e) 1,510 Days, 
and (f) 1,917 Days 
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Source: See Table XIII-1. 
Figure 7.4-20. NUFT-Simulated Time Histories of (a) Temperature, (b) Liquid-Phase Saturation, and 
(c) Gas-Phase Pressure in the Matrix, Plotted at Distances of 20 m and 27 m from the 
Collar of Borehole 68. 
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7.4.5 Summary of Model Validation Using DST Data 
The underlying cause for the absence of a NUFT-simulated temperature plateau (at 96C) is the 
low value of matrix permeability in the Tptpmn (tsw34) in the modified-mean infiltration-flux 
hydrologic property set, which results in a large gas-phase pressure buildup in the matrix, 
causing an increase in the saturation (boiling) temperature. The absence of a temperature plateau 
at 96C causes the NUFT-simulated temperatures to be generally higher than field-measured 
temperatures for temperatures exceeding 96C. These observations are consistent with the 
discussion in Sections 7.4.3 and 7.4.4 of Drift-Scale Coupled Processes (DST and TH Seepage) 
Models (BSC 2004 [DIRS 170338]). 
Another reason for NUFT-simulated temperatures being higher than measured temperatures is 
the uncertainty in host-rock thermal conductivity Kth in the DST area. For the high-Kth case (one 
standard deviation above the mean), NUFT-simulated temperatures were in better agreement 
with measured temperatures than the cases that used the mean Kth values. Because percolation 
fluxes cannot be directly measured, uncertainty in local percolation flux in the DST area also 
contributes to differences between NUFT-simulated and measured temperatures. Section 6.3.4 
discusses the influence of key parametric uncertainties on predicted thermohydrologic conditions 
in the repository. Table 6.3-30 shows that the combined influence of host-rock percolation-flux 
and thermal conductivity uncertainties results in peak drift-wall temperatures varying by 26.6 to 
38.3oC for the four host-rock units. Note that the 30-percent validation criterion for temperature 
rise (above ambient), which is given in the TWP, is consistent with the magnitude of the 
influence of the parametric uncertainty of host-rock thermal conductivity and percolation flux on 
temperature. As shown in Table 6.3-30, the combined influence of host-rock thermal 
conductivity uncertainty and percolation-flux uncertainty causes the rise in peak drift-wall 
temperature (above ambient) to vary by about 30 percent. 
For temperatures less than about 80C, NUFT-simulated and measured temperatures are in good 
agreement (within 30 percent as required by the TWP) for all three cases: (1) base case, (2) 
sealed bulkhead, and (3) high Kth. Overall, the comparison of NUFT-simulated and measured 
temperatures demonstrate that the NUFT thermohydrologic model provides a valid 
representation of heat flow in the DST. These observations are consistent with the discussion in 
Sections 7.4.3 and 7.4.4 of Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 
2004 [DIRS 170338]). 
The underlying cause for the NUFT-simulated throttled (i.e., restricted) vaporization and delayed 
dryout (compared to dryout observed in the DST) is the large gas-phase pressure buildup in the 
matrix, which is caused by the low matrix permeability in the Tptpmn (tsw34) in the calibrated 
hydrologic property set. Thus, the cause of the difference between the NUFT-simulated and 
observed rock-dryout rate is well understood. Eventually, the spatial extent of the 
NUFT-simulated dryout zone approaches that of the dryout zone observed in the DST. 
Therefore, the ultimate spatial extent of rock dryout simulated by the NUFT thermohydrologic 
model agrees with that measured in the DST. From this it is concluded that the NUFT 
thermohydrologic model provides a valid representation of rock dryout in the DST. This 
conclusion is consistent with the discussion in Sections 7.4.3 and 7.4.4 of Drift-Scale Coupled 
Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). To the extent that the 
observations of cooldown in the DST presently allow, the NUFT thermohydrologic model 
provides a valid representation of rewetting behavior in the DST. 
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With a few exceptions, the differences between the NUFT-simulated and measured temperature 
changes from ambient temperatures are less than 30 percent. The exceptions are related to the 
above-mentioned large gas-phase pressure buildup that temporarily throttles (i.e., restricts) 
vaporization and rock dryout. It is important to note that this effect is transient that dissipates as 
the NUFT-simulated gas-phase pressure buildup declines. With the decline of the 
NUFT-simulated gas-phase pressure buildup, agreement between the NUFT-simulated and 
measured temperatures improves, and the differences between the NUFT-simulated and 
measured temperature changes from ambient temperatures are less than 30 percent. The 
NUFT-simulated rock dryout behavior (as measured by liquid-phase saturation in the matrix 
continuum versus time) agrees qualitatively with the measured dryout behavior. For the ultimate 
spatial extent of rock dryout, there is very good agreement between the NUFT-simulated and 
measured dryout. Overall, the comparisons of NUFT-simulated and measured temperatures and 
matrix liquid-phase saturations demonstrate that the NUFT thermohydrologic model provides a 
valid representation of heat flow, as well as dryout and rewetting of the host rock in the DST. 
These conclusions are consistent with the discussion in Sections 7.4.3 and 7.4.4 of Drift-Scale 
Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]). 
Another conclusion from the DST model validation study is that the sealed-bulkhead case results 
in slightly higher NUFT-simulated temperatures than the base case (which had a leaky 
bulkhead). The influence of the leaky bulkhead on simulated temperatures is much less than that 
resulting from a one standard-deviation range in thermal conductivity. This conclusion is useful 
with respect to the potential significance of whether the ends of the emplacement drifts are 
sealed with bulkheads or simply backfilled with highly permeable crushed tuff. The conclusion 
of the insensitivity of the DST thermohydrologic simulations to the treatment of the bulkhead 
(leaky versus sealed) suggests that the MSTHM representation of thermohydrologic behavior in 
the emplacement drifts will not be significantly affected by whether the ends of the emplacement 
drifts are sealed. 
7.5 COMPARISON OF THE MSTHM RESULTS AGAINST A MONOLITHIC 
THREE-DIMENSIONAL THERMAL-HYDROLOGIC MODEL 
This model validation test case is similar to that conducted by Buscheck et al. (2003 [DIRS 
164638]). Using a scaled-down three-drift repository as a model validation test case, the 
MSTHM is applied along with a corresponding monolithic three-dimensional thermal-hydrologic 
model for calculating drift-scale thermal-hydrologic conditions. The monolithic 
thermal-hydrologic model, which is called a Discrete-/Line-Averaged-Heat-Source 
Mountain-Scale Thermal-Hydrologic (D/LMTH) model (Table 1-2), uses a nested mesh to 
represent detailed thermal-hydrologic behavior in the vicinity of the emplacement drifts as well 
as mountain-scale thermal-hydrologic behavior. Both the MSTHM and the corresponding 
monolithic three-dimensional thermal-hydrologic model discretely represent eight individual 
waste packages down to the surface of the drip shield. Results from these two models are 
compared at the drift wall, drip shield, and invert. This comparison is the basis for the validation 
of the MSTHM methodology. 
7.5.1 Description of the MSTHM Validation Test Case 
The test case used to validate the MSTHM approach represents a scaled-down repository, 
consisting of three 243-m long drifts (Figure 7.5-1 and Table 7.5-1). The total heat output from 
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these three drifts is 986.6 kW, representing approximately 143 average waste packages (Buscheck 
et al. 2003 [DIRS 164638]). This heat output is modeled in the three drifts as a line-averaged heat 
source everywhere except at the center of Drift #2 where 15 discrete waste packages are modeled: 
7 at the center of Drift #2 and 4 at either end of Drift #2. Because the test case is symmetric, the 
15 discrete waste packages can be modeled as the 7.5 discrete waste packages described in Table 
7.5-2. The thermal-operating parameters of the three-drift repository test case are equivalent to 
those being considered for the TSPA-LA except for the total inventory of waste packages. The 
waste packages are spaced end to end along the drift with a gap of 10.6 cm, which is similar to 10 
cm gap that is being considered for the TSPA-LA (Table 4.1-2). Preclosure ventilation of the 
drifts is assumed to remove 70 percent of the heat generated during the 50-year ventilation period. 
Note that at the time this validation test case was developed, a heat-removal efficiency of 70 
percent was being used in the MSTHM calculations in support of FY 01 Supplemental Science 
and Performance Analyses, Volume 1: Scientific Bases and Analyses (BSC 2001 [DIRS 
155950]). The initial heat output is 986.6 kW for the entire three-drift system, which is 
equivalent to about 1.18 percent of the 63,000-MTU thermal load (83,346 kW) for the repository 
(Canori and Leitner 2003 [DIRS 166275], p. 3-95). Note that the total repository thermal load is 
obtained by multiplying the initial linear power density of 1.45 kW/m (Table 4.1-1) by 57,480 m 
of heated emplacement drift (Table 6.2-1). Four different types of waste packages are represented 
in the test case and are described in Table 7.5-2. 
Table 7.5-1. Design and Operating Parameters Used in MSTHM Validation Test Case 
Parameter Parameter Value 
Drift spacing 81 m 
Drift length 243 m 
Drift diameter 5.5 m 
Drip-shield diameter 2.512 m 
Areal Mass Loading (AML) 54.5 MTU/acrea 
Heated repository footprint 59,049 m2 
Lineal Power Density 1.3534 kW/m 
Total heat output 986.6 kW 
Approximate number of waste packages 143 
represented in entire three-drift model 
Heat removal by ventilation 70% for 50 years 
Waste package configuration and spacing Line load with10.6-cm gaps 
Source: Buscheck et al. 2003 [DIRS 164638], Table 4. 
a 
Note that this value is rounded to 55 MTU/acre elsewhere in Section 7.5. 
Table 7.5-2. Waste Package Types Used in the MSTHM Validation Test Case 
Waste 
Package Type 
Waste Package 
Description 
Number of Waste 
Packagesa 
Length 
(m) 
Initial Heat 
Output (kW) 
PWR1 Average 21-PWR CSNF 1.5 5.17 11.53 
DHLW Long DHLW 2 5.22 0.282 
PWR2 Design-Basis 21-PWR CSNF 2 5.17 11.80 
BWR Average 44-BWR CSNF 2 5.17 7.377 
Source: Buscheck et al. 2003 [DIRS 164638]. 
a 
The number of discrete waste packages in the quarter-symmetry element test case (Figure 7.5-1). 
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Multiscale Thermohydrologic Model 
NOTE: To the upper left is the plan view of the three-drift repository test case; highlighted in blue is the zone of 
symmetry. To the upper right is a close-up of the Drift #2 waste package sequencing. To the bottom right is 
the vertical cross-section of the modeled drift with the drip shield and waste package lumped together as a 
heat source. 
Figure 7.5-1. Drift-Scale Conceptual Schematic Shown for the Model Validation Test Case 
The validation test case focuses on two locations: at the center and edge of the repository. At 
the center of the repository, four waste package types are discretely represented (Figure 7.5-1) in 
Drift #2, which is the central drift. At the edge of the repository, the same four waste package 
types are discretely represented; these four waste packages are also in Drift #2. In this test case, 
the waste packages are not represented distinctly from the drip shield. Instead, the waste 
package and drip shield are lumped together and treated as a monolithic heat source. The 
remainder of Drift #2, beyond the discretely represented waste package locations, has a 
line-averaged heat source within the drip-shield/waste package monolith (Figure 7.5-1). For 
Drifts #1 and #3, the heat-source representation is a line-averaged heat source distributed over 
the entire 5.5-m diameter cross section of the drift. Because heat is delivered directly to the host 
rock (with a line-averaged heat source) in Drifts #1 and #3, the contribution of thermal radiation 
and convection inside of those drifts is irrelevant. Within Drift #2, thermal radiation and natural 
convection are approximated with a time-dependent effective thermal conductivity for the drift 
cavity between the drip shield and the drift wall (CRWMS M&O 2001 [DIRS 153410]). Note 
that this approximation is different from that being used in the MSTHM calculations in support 
of the TSPA-LA (Section 6.3). However, for the purpose of the MSTHM validation problem it 
is only necessary that the MSTHM and the corresponding D/LMTH model both use the same 
approximation for thermal radiation and convection in the drift. Permeability in the drift cavity 
ANL-EBS-MD-000049 REV 02 7-42 October 2004 

Multiscale Thermohydrologic Model 
of Drift #2 (which is the central drift in Figure 7.5-1) is 1.0  10-8 m2 in all three principal 
directions. Because advective and diffusive transport of gas can occur in the longitudinal 
direction along the drift axis (also called the axial direction), this model allows the cold-trap 
effect to occur. This D/LMTH model also allows liquid-phase flow in the invert to occur in the 
longitudinal direction along the drift axis. Note that in the MSTHM calculations in support of 
the TSPA-LA (Section 6.3) the permeability in the drift is 1.0  10-8 m2 in the vertical and lateral 
directions. However, the MSTHM calculations in support of the TSPA-LA assume that gas- and 
liquid-phase flow in the axial direction along the drift is insignificant (Section 5.7). This 
assumption is equivalent to assuming that the cold-trap effect is insignificant. A sealed bulkhead 
is placed at the very end of the heated portion of Drift #2 in the D/LMTH model. However, this 
sealed bulkhead is not impermeable, because it is assigned the same bulk permeability as that of 
the adjoining host rock (Section 5.3.1.6). 
A second set of D/LMTH model calculations was conducted in which the permeability in the 
drift cavity and in the invert of Drift #2 is set to zero in the axial direction. Because this 
D/LMTH model prevents the cold-trap effect from occurring, it corresponds to the assumption in 
the MSTHM calculations in support of the TSPA-LA. The differences in thermal-hydrologic 
behavior in the drift between the D/LMTH model, which allows gas-phase and liquid-phase flow 
in the axial direction along the drift, and the D/LMTH model, which does not allow this axial 
flow, quantify the relative influence of the cold-trap effect in this three-drift repository test case. 
The D/LMTH model assumes the stratigraphy and boundary conditions, including infiltration 
flux, that pertain to the center of the repository modeled in supplemental analyses (BSC 2001 
[DIRS 155950]; BSC 2001 [DIRS 158204]) in the MSTHM. The stratigraphic information and 
boundary conditions are derived from DTN: LB991201233129.001 [DIRS 146894], while the 
percolation fluxes for the present-day, monsoonal, and glacial climates are derived from 
GS000308311221.005 [DIRS 147613], according to Section 4.1.12 of Multiscale 
Thermohydrologic Model (BSC 2001 [DIRS 158204]). The assumption in this test case is that 
the conditions at this location apply to the entire model domain, that is, there is no lateral 
variation of stratigraphy in the test model. At this location, the repository is 372.9 m below the 
ground surface and 344.7 m above the water table. The host-rock unit at this location is the 
Tptpll (tsw35) unit. The Tptpll unit, which is the host-rock unit for the majority of the repository 
area, is modeled with a matrix porosity of 0.131, a matrix permeability of 3.04  10-17 m, a 
2
fracture porosity of 0.018 and a fracture permeability of 2.38  10-11 m. Thermal parameters for 
the Tptpll unit are modeled using 900 J/kgC for specific heat capacity, and 1.84 and 1.25 
W/m/C for wet and dry thermal conductivity, respectively. The time-dependent infiltration 
rates at this location, the 14C3 location, are 5.7 mm/yr for the present-day climate (0 to 600 
years), 15.1 mm/yr for the monsoonal climate (600 to 2,000 years), and 23.2 mm/yr for the 
glacial-transition climate (beyond 2,000 years) (Flint et al. 2001 [DIRS 156351]; BSC 2001 
[DIRS 158204]). Parameter values used here are the same as those used for FY 01 Supplemental 
Science and Performance Analyses, Volume 1: Scientific Bases and Analyses (BSC 2001 [DIRS 
155950]). 
The numerical mesh in the D/LMTH model includes four nested regions: (1) the 
very-fine-gridded inner nest surrounding Drift #2 with grid-block dimensions of 
approximately 0.2 m in the horizontal and the vertical directions; (2) the fine-gridded 
intermediate mesh, surrounding the inner nest, with grid-block dimensions of approximately 1 m 
in the horizontal and the vertical directions; (3) the medium-gridded intermediate nest 
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surrounding the fine-gridded intermediate nest, as well as Drifts #1 and #3, with grid-block 
dimensions of approximately 5 m in the horizontal and the vertical directions; and (4) the 
coarse-gridded mountain-scale mesh, surrounding the medium-gridded intermediate nest with 
grid-block dimensions of approximately 50 m in the horizontal direction and approximately 20 m 
in the vertical direction, and which extends 2 km laterally to the model boundaries. Because of 
symmetry, it is only necessary to explicitly model one-quarter of the model domain 
(Figure 7.5-1). 
All of the MSTHM submodels used in the model validation test case used the same stratigraphy 
and boundary conditions as in the D/LMTH model. The SMT submodel has a heated repository 
footprint of 59,049 m2 and the same total initial heat output (986.6 kW or 829 MTU) as in the 
D/LMTH model (Buscheck et al. 2003 [DIRS 164638], p. 434, Table 4). MSTHM calculations 
for TSPA-LA involved running the LDTH and SDT submodels at four different AMLs. Because 
of the smaller heated footprint in this example, the influence of the edge-cooling effect occurs 
faster and with greater magnitude so that the LDTHSDT submodel pairs are run at six different 
AMLs, rather than four. The DDT submodels are also run for the same six AMLs. 
An important distinction between the MSTHM and the D/LMTH model concerns the treatment 
of air and vapor flow along the emplacement drift. The MSTHM effectively sets the axial 
permeability along the emplacement drift to zero, preventing axial air and vapor flow along the 
drift. For the D/LMTH model, the axial permeability is the same as that in the lateral and 
vertical directions (1  10-8 m2, which is about three orders of magnitude greater than the bulk 
permeability of the host rock). Consequently, axial vapor flow (and the resulting moisture 
redistribution or cold-trap effect) occurs in the D/LMTH model, but does not occur in the 
MSTHM. The comparison of the MSTHM-simulated thermal-hydrologic behavior with that of 
the D/LMTH model is useful in determining the relative importance of axial vapor flow on 
thermal-hydrologic behavior in the emplacement drifts. 
7.5.2 Results of the MSTHM Validation Test Case 
The results of the nested-mesh D/LMTH model and the MSTHM are compared at the four waste 
package locations at the center and at the edge of the three-drift repository test case. For the 
center of the repository (Sections 7.5.2.1, 7.5.2.2, and 7.5.2.3), the results from the D/LMTH 
model are shown for two cases: (1) the case with axial gas- and liquid-phase flow along the drift, 
a sealed bulkhead at the edge of the drift, and small gas-phase dispersivity in the drift and (2) the 
case without that axial flow. Note that the small gas-phase dispersion coefficient accounts for 
binary diffusion of water vapor, but does not account for the influence of natural-convective 
mixing. For the repository edge (Sections 7.5.2.4, 7.5.2.5, 7.5.2.6, and 7.5.2.7), D/LMTH-model 
results are given for three cases, including one case without axial gas- and liquid-phase flow 
along the drift and two with axial flow along the drift. The two cases with axial flow include one 
with a sealed bulkhead at the end of the drift and small gas-phase dispersivity in the drift and a 
case with no bulkhead and large gas-phase dispersivity in the drift. The large gas-phase 
dispersion coefficient in the second case is used to account for the influence of turbulent natural-
convection mixing. The second case also accounts for the open unheated section of drift (called 
the turnout area) beyond the last outermost waste package, and it includes the effects of rock 
dryout during the ventilation period. Of the D/LMTH-model cases, the case with no bulkhead 
and a large gas-phase dispersion coefficient in the drift is most realistic. Differences between 
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that case and the D/LMTH case with no axial gas- and liquid-phase flow quantify the influence 
of the cold-trap effect. 
7.5.2.1 Temperature at the Center of the Three-Drift Repository Test Case 
Drift-wall and drip-shield temperatures that are predicted by the D/LMTH model and the 
MSTHM are in good agreement at all four waste package locations at the center of Drift #2 
(Figure 7.5-2). Axial gas- and liquid-phase flows along the drift are seen to have an insignificant 
influence on temperatures at the center of the three-drift repository test case. Table-7.5-3 
summarizes the peak drift-wall and drip-shield temperatures predicted by the MSTHM and the 
D/LMTH model at the center of the three-drift repository test case. Differences in peak 
drift-wall temperature between the MSTHM and the D/LMTH model with axial gas- and 
liquid-phase flow along the drift axis range from 0.5C to 2.3C; differences in peak drip-shield 
temperature range from 1.7C to 2.7C. Table 7.5-4 summarizes the time when boiling at the 
drift wall ceases; differences between the two models are insignificant (generally 3 percent or 
less). 
There is similar good agreement in temperature at other reference locations, such as in the invert. 
The D/LMTH-predicted temperatures tend to be slightly lower than the MSTHM-predicted 
temperatures. This is most likely because the MSTHM does not consider mountain-scale 
buoyant gas-phase convection, nor does it consider vapor (and latent heat) flow along the axis of 
the drift from the center to the edge of the repository and beyond. The D/LMTH model 
considers both of these cooling mechanisms and therefore predicts slightly cooler temperature 
histories than the MSTHM. 
Table 7.5-3. Summary of Peak Temperatures for the Four Waste Package Locations at the Center of 
the Three-Drift Repository Test Case 
Waste Peak Drift-Wall Temperature (C) Peak Drip Shield Temperature (C) 
package MSTHM D/LMTH model Difference MSTHM D/LMTH model Difference 
PWR1 140.4 138.8 (139.3) 1.6 (1.1) 160.0 160.5 (160.9) -0.5 (-0.9) 
DHLW 135.5 133.2 (133.8) 2.3 (1.7) 145.1 142.4 (142.9) 2.7 (2.2) 
PWR2 146.4 145.9 (146.3) 0.5 (0.1) 168.0 169.7 (170.1) -1.7 (-2.1) 
BWR 145.5 144.9 (145.3) 0.6 (0.2) 163.1 163.1 (164.4) 0.0 (-1.3) 
NOTE: The D/LMTH-model results are for the cases with and without axial gas- and liquid-phase 
flow along the drift; the latter case is given in the parentheses. These values are based 
on data plotted in Figure 7.5-2. 
7.5.2.2 Relative Humidity at the Center of the Three-Drift Repository Test Case 
Drift-wall relative humidity predicted by the D/LMTH model and the MSTHM are in good 
agreement at all four center waste package locations. Figure 7.5-3 shows drift-wall relative 
humidity for the four waste packages. The agreement is closest up until the very end of the rock 
dryout period when the MSTHM predicts slightly lower relative humidity at the drift wall. The 
agreement in the predicted drip-shield relative humidity between the two models is best for the 
PWR2 and BWR waste package (Figure 7.5-3f and h). The MSTHM predicts slightly lower 
relative humidity than the D/LMTH model for the relatively cool DHLW waste package (Figure 
7.5-3d). It is noted that the DHLW waste package location has temperature and relative 
humidity gradients within the drip shield in the axial direction (not shown). The DHLW waste 
ANL-EBS-MD-000049 REV 02 7-45 October 2004 

Multiscale Thermohydrologic Model 
package is warmer (and drier) at its end than at its center because it is being heated by its 
neighboring waste packages that generate more heat (Table 7.5-2). Axial gas- and liquid-phase 
flow along the drift are seen to have an insignificant influence on relative humidity at the center 
of the three-drift repository test case. 
Table 7.5-4. Summary of Time When Boiling Ceases at the Drift Wall for the Four Waste Package 
Locations at the Center of the Three-Drift Repository Test Case 
Waste package 
Time When Boiling at Drift Wall Ceases (years) 
MSTHM D/LMTH model Difference Differencea 
PWR1 291.2 283.1 8.1 2.82% 
DHLW 269.7 259.6 10.1 3.82% 
PWR2 312.0 303.3 8.7 2.83% 
BWR 304.0 294.4 9.6 3.21% 
a 
The difference (%) is the difference (years) divided by the average time when drift-wall boiling ceases [(shortest + 
longest)/2]. The D/LMTH-model results are for the case with axial gas- and liquid-phase flow along the drift. 
These values are based on data plotted in Figure 7.5-2. 
7.5.2.3 Liquid-Phase Saturation at the Center of the Three-Drift Repository Test Case 
Drift-wall liquid-phase saturation Sdw,j,DMTH predicted by the D/LMTH model and MSTHM are 
in good agreement at all four center waste package locations (Figure 7.5-4a, c, e, and g). This 
good agreement is obtained regardless of whether axial gas- and liquid-phase flow is allowed to 
occur along the drift in the D/LMTH model. The minimum Sdw,j,DMTH, which occurs during the 
boiling period, is virtually identical for the two models. The MSTHM predicts a slightly longer 
duration of dryout for the PWR1, PWR2, and BWR waste packages; for the DHLW waste 
package, the two models predict virtually the same dryout duration (Figure 7.5-4c). Axial gas- 
and liquid-phase flow along the drift are seen to have an insignificant influence on drift-wall 
liquid-phase saturation. The agreement between the MSTHM and the D/LMTH model for the 
invert liquid-phase saturation, Sinv,j,DMTH, is good for the CSNF waste packages (Figure 7.5-4b, f, 
and h) and it is adequate for the relatively cool DHLW waste package (Figure 7.5-4d). The 
influence of the cold-trap effect is exhibited by the slightly higher values of Sinv,j,DMTH for the 
DHLW waste package in the D/LMTH model with axial gas- and liquid-phase flow along the 
drift, compared to the D/LMTH model that does not allow that axial flow. The cold-trap effect 
causes the advection of water vapor from the relatively hot CNSF waste package locations to the 
relatively cool DHLW waste package location, where it condenses, causing an increase in 
Sin,j,DMTH. The two hot CSNF waste packages next to the DHLW waste package have slightly 
reduced Sin,j,DMTH for the D/LMTH model with axial gas- and liquid-phase flow along the drift 
compared to the D/LMTH model that does not allow that axial flow. 
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Source: See Table XIII-1. 
NOTE: Drift-wall temperature (Tdw,j,DMTH) vs. time (a, c, e, g) and drip-shield temperature (Tds,j,DMTH) vs. time (b, d, 
f, h) are determined by the MSTHM and the D/LMTH model. The D/LMTH-model results are given for the 
cases with and without axial gas- and liquid-phase flow along the drift. 
Figure 7.5-2. Drift-Wall and Drip-Shield Temperature vs. Time for the (a,b) PWR1, (c,d) DHLW, (e, f) 
PWR2, and (g, h) BWR Waste Packages at the Center of the Three-Drift Repository Test 
Case 
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Source: See Table XIII-1. 
NOTE: Drift-wall relative humidity (RHdw,j,DMTH) vs. time (a, c, e, g) and drip-shield relative humidity (RHds,j,DMTH) vs. 
time (b, d, f, h) are determined by the MSTHM and the D/LMTH model. The D/LMTH-model results are 
given for the cases with and without axial gas- and liquid-phase flow along the drift. 
Figure 7.5-3. Drift-Wall and Drip-Shield Relative Humidity vs. Time for the (a,b) PWR1, (c,d) DHLW, (e, 
f) PWR2, and (g, h) BWR Waste Packages at the Center of the Three-Drift Repository 
Test Case 
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Source: See Table XIII-1. 
NOTE: Drift-wall liquid-phase saturation (Sdw,j,DMTH) vs. time (a, c, e, g) and invert liquid-phase saturation 
(Sin,j,DMTH) vs. time (b, d, f, h) are determined by the MSTHM and the D/LMTH model. The D/LMTH-model 
results are given for the cases with and without axial gas- and liquid-phase flow along the drift. 
Figure 7.5-4. Drift-Wall Liquid-Phase and Invert Liquid-Phase Saturation vs. Time for the (a, b) PWR1, 
(c, d) DHLW, (e, f) PWR2, and (g, h) BWR Waste Packages at the Center of the 
Three-Drift Repository Test Case 
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7.5.2.4 Temperature at the Edge of the Three-Drift Repository 
At the edge of the three-drift repository test case, the longitudinal waste package order from the 
end of the drift is the following: PWR1, DHLW, PWR2, BWR. The drift-wall temperatures 
predicted by the D/LMTH model and the MSTHM are in reasonably good agreement at the four 
waste package locations at the edge of Drift #2 (Figure 7.5-5). This agreement is achieved 
regardless of whether axial gas- and liquid-phase flow along the drift is allowed to occur in the 
D/LMTH model. Tables 7.5-5 and 7.5-6 summarize the peak drift-wall and drip-shield 
temperatures predicted by the MSTHM and the D/LMTH model at the edge of the three-drift 
repository test case. A comparison of the D/LMTH-model temperatures (Figure 7.5-5 and 
Tables 7.5-5 and 7.5-6) clearly shows that the effect of axial transport of vapor and condensation 
on temperatures is small. When the MSTHM is compared with the D/LMTH model that allows 
axial gas- and liquid-phase flow along the drift (with no bulkhead and large gas-phase 
dispersivity in the drift), differences in peak drip-shield temperature range from 6.5C for BWR 
package to 17.1C for the PWR1 package (Table 7.5-6). The outermost two waste package 
locations, which have a temperature bias of about 17oC, are representative of waste package 
locations that occupy only 1.6 percent of the repository area. The third and fourth waste package 
locations in from the repository edge, which have a temperature bias of about 7oC (Table 7.5-6), 
are representative of waste packages that occupy only 1.6 percent of the repository area. These 
results indicate that for waste packages located more than 20 m from the repository edge, which 
encompasses about 97 percent of the repository area, the temperature overprediction by the 
MSTHM is less than about 7oC. 
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Source: See Table XIII-1. 
NOTE: Drift-wall temperature (Tdw,j,DMTH) vs. time (a, c, e, g) and drip-shield temperature (Tds,j,DMTH) vs. time (b, d, 
f, h) are determined by the MSTHM and the D/LMTH model. The D/LMTH-model results are given for a 
case without axial gas- and liquid-phase flow along the drift and for two cases with flow along the drift, 
including one with a sealed bulkhead and small gas-phase dispersivity in the drift and one with no 
bulkhead and large gas-phase dispersivity. 
Figure 7.5-5. Drift-Wall and Drip-Shield Temperature vs. Time for the (a, b) PWR1, (c, d) DHLW, (e, f) 
PWR2, and (g, h) BWR Waste Packages at the Edge of the Three-Drift Repository Test 
Case 
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Table 7.5-5. Peak Drift-Wall Temperatures Summarized for the Four Waste Package Locations at the 
Edge of the Three-Drift Repository Test Case 
Waste 
Package 
Peak Drift-Wall Temperature (C) 
MSTHM D/LMTH Model Difference (MSTHM  D/LMTH Model) 
Axial gas- and liquid-phase 
flow in drift 
No axial gas-
& liquid-
phase flow in 
drift 
Axial gas- and liquid-phase 
flow in drift 
No axial gas-
& liquid-
phase flow in 
driftNo bulkhead 
& large 
With 
bulkhead & 
No bulkhead 
& large 
With 
bulkhead & 
dispersivity small dispersivity small 
dispersivity dispersivity 
PWR1 136.3 115.4 117.5 115.8 20.9 18.8 20.5 
DHLW 131.3 113.5 115.8 114.3 17.8 15.5 17.0 
PWR2 142.3 131.6 133.5 132.2 10.7 8.8 10.1 
BWR 141.4 133.0 135.5 134.5 8.4 5.9 6.9 
NOTE: These values are based on data plotted in Figure 7.5-5. 
Table 7.5-6. Peak Drip-Shield Temperatures Summarized for the Four Waste Package Locations at the 
Edge of the Three-Drift Repository Test Case 
Waste 
Package 
Peak Drip-Shield Temperature (C) 
MSTHM D/LMTH Model Difference (MSTHM  D/LMTH Model) 
Axial gas- and liquid-phase 
flow in drift 
No axial gas-
& liquid-
phase flow in 
drift 
Axial gas- and liquid-phase 
flow in drift 
No axial gas-
& liquid-
phase flow in 
driftNo bulkhead 
& large 
With 
bulkhead & 
No bulkhead 
& large 
With 
bulkhead & 
dispersivity small dispersivity small 
dispersivity dispersivity 
PWR1 156.7 140.2 141.0 139.2 16.5 15.7 17.5 
DHLW 141.0 123.9 125.5 124.0 17.1 15.5 17.0 
PWR2 164.7 156.9 158.0 156.6 7.8 6.7 8.1 
BWR 159.9 153.4 154.9 153.9 6.5 5.0 6.0 
NOTE: These values are based on data plotted in Figure 7.5-5. 
As discussed above, the agreement between the two models improves with distance from the 
edge of the repository. There are two reasons for the increasing disagreement in temperature 
with proximity to the edge. The first is related to the gridblock discretization in the SMT 
submodel and the second is related to the dimensionality of the DDT submodel. 
The current implementation of the MSTHM has an SMT submodel that discretizes the 
emplacement drifts into 20-m intervals (Section 6.2.5.1). Thus, the edge of the repository is 
represented by an SMT submodel temperature history that is 10 m from the repository edge. 
Finer gridding in the axial direction would result in finer representation of the rate of cooling for 
the outermost waste packages in the drift. 
As discussed in Section 6.2.1, an underlying principle in the MSTHM concept is that the 
influence of three-dimensional mountain-scale heat flow on drift-scale thermal-hydrologic 
behavior can be approximated with the use of an effective drift spacing that is implemented in 
the LDTH submodels. This effective drift spacing gradually increases with time to approximate 
the increasing influence of the edge-cooling effect, which allows heat to migrate away from the 
heated footprint of the repository area. The principle of the effective drift spacing relies on heat 
flow immediately away from the emplacement drift (and into the adjoining host rock) occurring 
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in a predominantly radial fashion. However, for the outermost two to three waste packages at the 
repository edge, heat flow can also have a substantial axial component. The use of a DDT 
submodel (Section 6.2.8) with an unheated portion in the axial direction (i.e., beyond the 
outermost waste package) would capture the influence of axial heat flow for the outermost two to 
three waste packages. The implementation of such a DDT submodel in the MSTHM 
methodology would likely result in closer agreement in temperatures predicted by the MSTHM 
and the D/LMTH model, and thereby reduce the small disagreement in temperatures for the 
outermost waste packages. 
It is important to point out that even while the MSTHM overpredicts temperatures for packages 
near the end of the drift, these temperature differences between the MSTHM and D/LMTH 
model are well within the range of temperature differences resulting from parametric uncertainty 
(Tables 6.3-30 and 6.3-31). When the D/LMTH model that allows axial flow along the drift is 
compared with the D/LMTH model that does not, the small (insignificant) influence of the 
cold-trap effect on temperatures is evident (Tables 7.5-5 and 7.5-6). 
A useful way of examining the differences between the MSTHM and D/LMTH models is to 
consider the center-to-edge temperature differences predicted by the two models (Table 7.5-7). 
Note that the MSTHM represents all four waste packages as having the same center-to-edge 
distance, whereas the D/LMTH-model representation has a progressively smaller center-to-edge 
distance with increasing distance from the repository edge. The MSTHM utilizes an SMT 
submodel that discretizes the emplacement drifts into 20-m intervals; thus, the outer 20 m of the 
MSTHM is treated in the same fashion insofar as the influence of the edge-cooling effect is 
concerned. Similarly, the four waste packages at the center of the three-drift repository are 
treated in the same fashion insofar as their proximity to the repository edge is concerned. In a 
sense, the MSTHM does not distinguish which of the four waste packages is actually the 
outermost waste package over the outermost 20 m of the emplacement drift. All four waste 
packages are treated as though their respective centers are located 10 m from the edge of the 
heated footprint of the repository. Similarly, all four waste packages at the center of the 
three-drift repository are treated as though their centers are located 111.5 m from the edge of the 
heated repository footprint. Consequently, all four waste packages have virtually the same 
center-to-edge temperature difference. Conversely, the D/LMTH model does distinguish the 
respective distances from the repository edge for each of the four waste packages. 
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Table 7.5-7. Drip-Shield Temperature Difference Between the Center and Edge of the Three-Drift 
Repository Test Case, Compared for the D/LMTH Model and MSTHM 
Waste 
Package 
Center-to-Edge Distance 
(m) 
Center-to-Edge Drip 
Shield Temperature 
Difference (C) 
MSTHM D/LMTH model MSTHM D/LMTH 
model 
PWR1 101.5 118.862 3.3 19.5 
DHLW 101.5 108.260 4.1 16.9 
PWR2 101.5 97.658 3.3 11.7 
BWR 101.5 87.106 3.2 8.2 
NOTE: Temperature differences are based upon Tables 7.5-6 and 
7.5-5. The center-to-edge distances are based upon Figure 
7.5-1. The D/LMTH-model results are for the case with 
longitudinal gas- and liquid-phase flow along the drift axis. 
These values are based on data plotted in Figure 7.5-5. 
Table 7.5-7 indicates that the center-to-edge temperature difference in the D/LMTH model 
approaches that of the MSTHM for increasing distance from the repository edge. The reasons 
for the increasing agreement with increasing distance from the edge are discussed above. Tables 
7.5-5 and 7.5-6 indicate that for waste packages located 20 m or more from the repository edge, 
the differences in temperature predicted by the MSTHM and D/LMTH model are small (less 
than 5C for peak drip-shield temperatures). The MSTHM discretizes thermal-hydrologic 
behavior for 2,874 20-m intervals (Figure 6.2-3); of these intervals, only 92 are potentially 
affected by the axial vapor (and latent heat) loss at the edge of the repository, constituting only 
3.2 percent of the repository area. Consequently, 96.8 percent of the repository should not be 
influenced by this effect at the outermost edge of the repository. For the outermost 3.2 percent 
of the repository, the small overprediction of MSTHM temperatures is well within the range of 
temperature differences resulting from parametric uncertainty (Tables 6.3-30 and 6.3-31). 
Table 7.5-8 summarizes the time when boiling at the drift wall ceases; differences between the 
two models range from 17.3 to 44.9 percent. Again, the agreement between the two models 
improves with distance from the edge of the repository. Because the differences between the two 
models are within the range of differences arising from parametric uncertainty (Table 6.3-32), 
the impact of conceptual-model uncertainty is less than that of parametric uncertainty. 
Table 7.5-8. Summary of Time When Boiling Ceases at the Drift Wall for the Four Waste Package 
Locations at the Edge of the Three-Drift Repository Test Case 
Waste Package 
Time When Boiling at Drift Wall Ceases (years) 
MSTHM D/LMTH Model Difference Differencea 
PWR1 215.0 136.1 78.9 44.9% 
DHLW 195.9 136.0 59.9 36.1% 
PWR2 233.2 184.2 49.0 23.5% 
BWR 226.6 190.6 36.0 17.3% 
a 
The difference (%) is the difference (years) divided by the average time when 
drift-wall boiling ceases [(shortest + longest)/2]. The D/LMTH model results are for 
the case with longitudinal gas- and liquid-phase flow along the drift axis. 
NOTE: These values are based on data plotted in Figure 7.5-5. 
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7.5.2.5 Relative Humidity at the Edge of the Three-Drift Repository Test Case 
Figure 7.5-6 gives the drift-wall relative humidity for the four waste packages at the edge of the 
repository. Drift-wall relative humidity predicted by the D/LMTH model and the MSTHM are 
in reasonable agreement at the four edge waste package locations. This agreement is achieved 
regardless of whether axial gas- and liquid-phase flow along the drift is allowed to occur in the 
D/LMTH model. However, the inclusion of axial vapor transport and the unheated part of the 
drift in the D/LMTH model (with no bulkhead and large gas-phase dispersivity) improves the 
agreement of predicted relative humidity (Figure 7.5-6) between the MSTHM and the D/LMTH 
model. Note also that the agreement between the two models improves with distance from the 
repository edge. The agreement in the predicted drift-wall relative humidity between the two 
models is best for the PWR2 and BWR waste package (Figure 7.5-6e and g). The agreement 
between the two models is better for drip-shield relative humidity (Figure 7.5-6b, d, f, and h) 
than it is for drift-wall relative humidity (Figure 7.5-6a, c, e, and g). The agreement is best 
during the postboiling period when relative humidity reduction resulting from rock dryout no 
longer plays a significant role in relative humidity reduction on the drip shield. During the 
boiling period, the agreement in drip-shield relative humidity improves with distance from the 
edge of the repository. The differences between the two models in drip-shield relative humidity 
are within the range of differences arising from parametric uncertainty (Section 6.3.2). 
The influence of the cold-trap effect can be observed in Figure 7.5-6 by comparing the results 
from the D/LMTH model that allows axial gas- and liquid-phase flow along the drift with those 
from the D/LMTH model that does not allow that axial flow. The influence of the cold-trap 
effect is to reduce the drift-wall relative humidity, with the reduction being stronger for the three 
CSNF waste packages than it is for the DHLW waste package. This reduction results because 
some of the water vapor generated in the host rock flows radially inward into the drift and then 
axially along the drift beyond the outermost waste package, where it condenses and is imbibed 
into the host rock. This process results in a net reduction in moisture in the host rock, 
particularly adjacent to the CSNF waste packages. The drift-wall temperature adjacent to the 
DHLW waste package drops below the boiling point earlier than at the (relatively hotter) CSNF 
waste package locations. The earlier return to sub-boiling temperatures causes preferential 
condensation and imbibition into the host rock adjoining the DHLW waste package. The 
preferential condensation in the host rock adjacent to the DHLW waste package offsets some of 
the ongoing moisture loss from the host rock, decreasing the net reduction in liquid-phase 
saturation in the host rock. This smaller net reduction in liquid-phase saturation at the (relatively 
cooler) DHLW waste package location results in a smaller reduction in relative humidity than 
occurs for the (relatively hotter) CSNF waste packages. 
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Source: See Table XIII-1. 
NOTE: Drift-wall relative humidity (RHdw,j,DMTH) vs. time (a, c, e, g) and drip-shield relative humidity (RHds,j,DMTH) vs. 
time (b, d, f, h) are determined by the MSTHM and the D/LMTH model. The D/LMTH-model results are 
given for a case without axial gas- and liquid-phase flow along the drift and for two cases with flow along 
the drift, including one with a sealed bulkhead and small gas-phase dispersivity in the drift and one with no 
bulkhead and large gas-phase dispersivity. 
Figure 7.5-6. Drift-Wall and Drip-Shield Relative Humidity vs. Time for the (a, b) PWR1, (c, d) DHLW, 
(e, f) PWR2, and (g, h) BWR Waste Packages at the Edge of the Three-Drift Repository 
Test Case 
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7.5.2.6 Liquid-Phase Saturation at the Edge of the Three-Drift Repository Test Case 
Drift-wall liquid-phase saturation Sdw,j,DMTH predicted by the D/LMTH model and MSTHM are 
in reasonable agreement at the four edge center waste package locations (Figure 7.5-7a, c, e, 
and g). This agreement is achieved regardless of whether axial gas- and liquid-phase flow along 
the drift is allowed to occur in the D/LMTH model. However, the inclusion of axial vapor 
transport and the unheated part of the drift in the D/LMTH model (with no bulkhead and large 
gas-phase dispersivity) improves the agreement of predicted liquid-phase saturation (Figure 
7.5-7) between the MSTHM and the D/LMTH model, with one exception, which is the invert 
liquid-phase saturation for the DHLW waste package (Figure 7.5-7d). Preferential condensation 
at the cold (DHLW waste package) location increases the invert liquid-phase saturation beneath 
that waste package. The cold-trap effect also results in a loss of moisture from the host rock 
adjoining all waste package locations (the hot CSNF waste packages in particular), which 
decreases the drift-wall liquid-phase saturation at those locations. The net reduction in 
liquid-phase saturation in the host rock at the cooler DHLW waste package location is reduced 
by virtue of preferential condensation occurring there after boiling ceases. The cold-trap effect 
also removes moisture from the invert liquid-phase saturation beneath the hot CSNF waste 
packages, which reduces the invert liquid-phase saturation at those locations. Preferential 
condensation beneath the (relatively cooler) DHLW waste package results in an increase in 
liquid-phase saturation in the invert (Figure 7.5-7d). 
7.5.2.7 Vapor and Condensate Fluxes at the Edge of the Three-Drift Repository Test 
Case 
Figure 7.5-8 shows the axial mass flux of water vapor in the gas phase along the central drift in 
the model, plotted for the upstream end of each of the four waste packages (the end closer to the 
repository center), and also at the repository edge (the downstream end of the outermost waste 
package, PWR1). Note that Figure 7.5-1 shows the waste package sequence. These results are 
for the most realistic D/LMTH case, which has no bulkhead and large gas-phase dispersivity in 
the drift. The curves are parallel, with the upstream value being less than the downstream value 
at a given waste package location, with the exception of the last two curves labeled PWR1 (the 
outermost waste package) and Repository Edge. The last two curves drop below the value of the 
respective upstream curves at approximately 300 years, signifying that condensation is occurring 
in the vicinity of the cooler DHLW waste package after about 300 years. 
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Source: See Table XIII-1. 
NOTE: Drift-wall liquid-phase saturation (Sdw,j,DMTH) vs. time (a, c, e, g) and invert liquid-phase saturation 
(Sin,j,DMTH) vs. time (b, d, f, h) are determined by the MSTHM and the D/LMTH model. The D/LMTH-model 
results are given for a case without axial gas- and liquid-phase flow along the drift and for two cases with 
flow along the drift, including one with a sealed bulkhead and small gas-phase dispersivity in the drift and 
one with no bulkhead and large gas-phase dispersivity. 
Figure 7.5-7. Drift-Wall Liquid-Phase and Invert Liquid-Phase Saturation vs. Time for the (a, b) PWR1, 
(c, d) DHLW, (e, f) PWR2, and (g, h) BWR Waste Packages at the Edge of the Three-Drift 
Repository Test Case 
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Source: See Table XIII-1. 
NOTE: This figure corresponds to the D/LMTH-model case with no bulkhead and large gas-phase dispersivity. 
This case also includes the influence of host-rock dryout during the ventilation period. The waste package 
sequencing, starting from the edge, is PWR1, DHLW, PWR2, and BWR, as is shown in Figure 7.5-1. The 
upstream side of the waste package is the side closer to the repository center. The curve listed repository 
edge corresponds to the downstream side of the PWR1 waste package. The curve listed PWR1 
corresponds to the upstream side of the PWR 1 waste package, and to the downstream side of the DHLW 
waste package. The curve listed DHLW corresponds to the upstream side of the DHLW waste package 
and to the downstream site of the PWR2 waste package. The curve listed PWR2 corresponds to the 
upstream side of the PWR2 waste package and to the downstream side of the BWR waste package. The 
curve listed BWR corresponds to the upstream side of the BWR waste package. 
Figure 7.5-8. Axial Vapor Flux on the Upstream Side of the Listed Waste Packages at the Edge of the 
Three-Drift Repository Test Case 
Tables 7.5-9 to 7.5-12 show moisture balance results for each of the four outermost waste 
packages at the repository edge, from the D/LMTH model case with no bulkhead and large 
dispersivity (case 3). The phase change columns show where evaporation (positive values) and 
condensation (negative values) are occurring at each waste package location for several discrete 
times distributed over the regulatory period. Note that the delta axial vapor flux, which is the 
difference in axial vapor flux between the upstream and downstream sides of a waste package 
(see Figure 7.5-8), corresponds to the net condensation or evaporation occurring at a waste 
package location. The radial vapor flux corresponds to the phase change that occurs in the host 
rock. Thus, the sum of the radial vapor flux, the invert phase change, and the drift phase change 
is equal to the delta axial vapor flux. Of the four waste packages, the DOE high-level 
radioactive waste package (Table 7.5-10) is the coolest, and condensation occurs mainly there. 
A comparison of the delta axial vapor flux with the radial vapor flux shows that most of the 
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condensation at the cooler waste package results from water vapor migration outward into cooler 
rock, where it condenses. This water is then diverted around the drift opening along with the 
ambient percolation flux. 
Table 7.5-9. Summary of Moisture Balance for PWR1 Waste Package in Multiscale Thermal-Hydrologic 
Model Validation Test Case 
Time 
Vapor Flux (kg/yr) Phase Change (kg/yr) 
Axial Axial 
(years) (upstream) (downstream) Delta Axial Radial Invert Drift 
60 35,137.6 39,680.5 4,542.9 4,300.3 242.8 0.0 
100 25,530.0 28,876.8 3,346.8 3,113.4 233.3 0.0 
500 9,273.2 9,554.1 280.9 51.9 229.5 -0.4 
1,000 2,928.7 2,978.4 49.7 -59.4 109.1 0.0 
2,000 878.3 904.4 26.1 -17.6 51.6 -7.9 
5,000 547.5 603.6 56.1 19.3 36.8 0.0 
10,000 448.7 499.4 50.7 21.5 29.1 0.0 
Source: DTN: LL040703223122.050. 
NOTE: The PWR1 waste package is located at the outer edge of the three-drift validation test case Figure 7.5-1) for 
the D/LMTH model with no bulkhead and a high gas-phase dispersion coefficient along the drift. Positive 
values of radial vapor flux correspond to vapor leaving the host rock and entering the drift (and invert); 
negative values correspond to vapor leaving the drift (and invert) and entering the host rock. Positive values 
of phase change correspond to evaporation; negative values correspond to condensation. The delta axial 
vapor flux, which is the difference in axial vapor flux between the upstream and downstream sides of a 
waste package (see Figure 7.5-8), corresponds to the net condensation or evaporation occurring at a waste 
package location. The radial vapor flux corresponds to the phase change that occurs in the host rock. 
Thus, the sum of the radial vapor flux, the invert phase change, and the drift phase change is equal to the 
delta axial vapor flux. 
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Table 7.5-10. Summary of Moisture Balance for DOE High-Level Radioactive Waste Package in 
Multiscale Thermal-Hydrologic Model Validation Test Case 
Time 
Vapor Flux (kg/yr) Phase Change (kg/yr) 
Axial Axial 
(years) (upstream) (downstream) Delta Axial Radial Invert Drift 
60 34,102.0 35,138.0 1,036.0 1,036.0 0.0 0.0 
100 24,835.0 25,530.0 695.0 695.0 0.0 0.0 
500 11,679.4 9,273.2 -2,406.2 -2,381.4 -12.5 -12.4 
1,000 4,902.1 2,928.7 -1,973.4 -1,920.2 -30.4 -22.8 
2,000 1,851.1 878.3 -972.8 -925.7 -19.1 -28.0 
5,000 1,076.4 547.5 -528.8 -495.0 -10.4 -23.4 
10,000 800.6 448.7 -351.9 -332.2 -6.6 -13.1 
Source: DTN: LL040703223122.050. 
NOTE: The DOE high-level radioactive waste package is the second to the last waste package located at the outer 
edge of the three-drift validation test case (Figure 7.5-1) for the D/LMTH model with no bulkhead and a high 
gas-phase dispersion coefficient along the drift. Positive values of radial vapor flux correspond to vapor 
leaving the host rock and entering the drift (and invert); negative values correspond to vapor leaving the drift 
(and invert) and entering the host rock. Positive values of phase change correspond to evaporation; 
negative values correspond to condensation. The delta axial vapor flux, which is the difference in axial 
vapor flux between the upstream and downstream sides of a waste package (see Figure 7.5-8), 
corresponds to the net condensation or evaporation occurring at a waste package location. The radial 
vapor flux corresponds to the phase change that occurs in the host rock. Thus, the sum of the radial vapor 
flux, the invert phase change, and the drift phase change is equal to the delta axial vapor flux. 
Table 7.5-11. Summary of Moisture Balance for PWR2 Waste Package in Multiscale Thermal-Hydrologic 
Model Validation Test Case 
Time 
Vapor Flux (kg/yr) Phase Change (kg/yr) 
Axial Axial 
(years) (upstream) (downstream) Delta Axial Radial Invert Drift 
60 32,775.4 34,102.0 1,326.6 1,326.9 0.0 0.0 
100 24,014.0 24,835.0 821.0 821.0 0.0 0.0 
500 10,813.1 11,679.4 866.3 711.8 153.7 0.8 
1,000 3,744.8 4,902.1 1,157.3 1,062.5 94.8 0.0 
2,000 1,202.0 1,851.1 649.1 592.5 56.6 0.0 
5,000 678.6 1,076.4 397.8 348.9 48.8 0.0 
10,000 524.7 800.6 275.9 238.2 37.7 0.0 
Source: DTN: LL040703223122.050. 
NOTE: The PWR2 waste package is the third to the last waste package located at the outer edge of the three-drift 
validation test case (Figure 7.5-1) for the D/LMTH model with no bulkhead and a high gas-phase dispersion 
coefficient along the drift. Positive values of radial vapor flux correspond to vapor leaving the host rock and 
entering the drift (and invert); negative values correspond to vapor leaving the drift (and invert) and entering 
the host rock. Positive values of phase change correspond to evaporation; negative values correspond to 
condensation. The delta axial vapor flux, which is the difference in axial vapor flux between the upstream 
and downstream sides of a waste package (see Figure 7.5-8), corresponds to the net condensation or 
evaporation occurring at a waste package location. The radial vapor flux corresponds to the phase change 
that occurs in the host rock. Thus, the sum of the radial vapor flux, the invert phase change, and the drift 
phase change is equal to the delta axial vapor flux. 
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Table 7.5-12. Summary of Moisture Balance for BWR Waste Package in Multiscale Thermal-Hydrologic 
Model Validation Test Case 
Time 
Vapor Flux (kg/yr) Phase Change (kg/yr) 
Axial Axial 
(years) (upstream) (downstream) Delta Axial Radial Invert Drift 
60 31,340.2 32,775.4 1,435.2 1,435.3 0.0 0.0 
100 23,118.2 24,014.0 895.8 895.7 0.0 0.0 
500 10,292.6 10,813.1 520.5 389.3 130.2 1.0 
1,000 3,161.5 3,744.8 583.3 500.9 82.4 0.0 
2,000 889.2 1,202.0 312.8 264.5 48.4 0.0 
5,000 489.6 678.6 189.0 155.7 33.4 -0.1 
10,000 400.8 524.7 123.9 98.7 26.3 -1.1 
Source: DTN: LL040703223122.050. 
NOTE: The BWR waste package is the fourth to the last waste package located at the outer edge of the three-drift 
validation test case (Figure 7.5-1) for the D/LMTH model with no bulkhead and a high gas-phase dispersion 
coefficient along the drift. Positive values of radial vapor flux correspond to vapor leaving the host rock and 
entering the drift (and invert); negative values correspond to vapor leaving the drift (and invert) and entering 
the host rock. Positive values of phase change correspond to evaporation; negative values correspond to 
condensation. The delta axial vapor flux, which is the difference in axial vapor flux between the upstream 
and downstream sides of a waste package (see Figure 7.5-8), corresponds to the net condensation or 
evaporation occurring at a waste package location. The radial vapor flux corresponds to the phase change 
that occurs in the host rock. Thus, the sum of the radial vapor flux, the invert phase change, and the drift 
phase change is equal to the delta axial vapor flux. 
7.5.3 Summary of Three-Drift Repository Validation Test Case 
The MSTHM is also validated against a monolithic three-dimensional porous-medium model 
implemented using the NUFT code (Nitao 1998) for a three-drift test case, representing a 
scaled-down repository. Each simulated drift is 243 m long and uses a combination of 
line-averaged and discrete heat sources to represent the waste packages. The central drift uses a 
combination of a line-averaged heat source for most of the drift and four discrete sources 
(representing individual waste packages) at the center of the drift and four discrete sources at the 
outer end of the drift (Figure 7.5-1). The monolithic three-dimensional thermal-hydrologic 
model is called the discrete/line-averaged mountain-scale thermal-hydrologic (D/LMTH) model. 
The D/LMTH model was run in three ways: 
 Case 1: This case allows no axial vapor (or gas) transport along the drifts, 
corresponding to the MSTHM, which does not include vapor transport along the drift 
axis. 
 Case 2: This case allows axial vapor transport, using a small value for the gas-phase 
dispersion coefficient to account for binary diffusion of water vapor but not for the 
influence of convective mixing. In addition, a bulkhead was located just beyond the 
outermost waste package at the end of each drift. 
 Case 3: This case allows axial vapor transport, using the high value of the gas-phase 
dispersion coefficient to account for the influence of turbulent convective mixing. The 
third case has no bulkhead at the end of the drift, and includes the unheated section of 
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the drift beyond the outermost waste package. The third case includes the effects of 
rock dryout during the ventilation period. 
Of the three cases, the third is most realistic and is emphasized in the discussion below. 
Differences in the predicted thermal-hydrologic conditions for the drift and the adjoining host 
rock between cases 1 and 3 are used as quantitative indicators of the importance of the cold-trap 
effect, and moisture transport to the unheated part of each drift, with respect to MSTHM 
predictions. D/LMTH-model calculations were conducted for cases 1 and 2 for the four waste 
packages at the repository center. D/LMTH-model calculations were conducted for cases 1, 2, 
and 3 for the four waste packages at the repository edge. 
For comparison, the MSTHM was configured for this same three-drift configuration and 
boundary conditions, so that results are directly comparable to the three-dimensional nested-grid 
thermal-hydrologic cases. The locations selected for direct comparisons are at the center and 
edge of the simplified repository. 
Temperature differences between the MSTHM results and cases 1 through 3 are dominated by 
how the MSTHM methodology addresses three-dimensional heat losses. For waste packages 
located more than 20 m from the repository edge, which represents approximately 97% of the 
repository area, overprediction of peak drip shield temperature by the MSTHM is less than 6.5 
C. At the edge, comparison of the MSTHM with case 3 shows relatively small differences (6.5 
to 17.1 C) in peak drip-shield temperature (Figure 7.5-6). These differences are smaller than the 
overall effect of parametric uncertainty of host-rock thermal conductivity and percolation flux 
(Section 6.3.5). Temperature differences are greatest for the last two waste packages at the edge, 
and are caused by the coarse spatial grid resolution of the SMT submodel used in the MSTHM 
framework. 
The small differences in temperatures between cases 1 and 3 show the lack of influence of the 
cold-trap effect on temperatures for waste package locations at the repository edge. This result 
supports use of the MSTHM for predicting thermal-hydrologic conditions in the drifts and in the 
adjoining host rock for waste package locations near the repository edge. 
For case 3, which includes axial vapor transport and the resulting cold-trap effect, the predicted 
in-drift relative humidity and host-rock liquid saturation conditions (Figures 7.5-6 and 7.5-7) 
agree more closely with the MSTHM results than the other cases. Importantly, the cold-trap 
effect causes net reduction in moisture (matrix liquid-phase saturation) in the host rock at all 
waste package locations, because water is evaporated and transported to unheated regions of the 
drift. The greatest moisture losses occur at the hotter spent-fuel waste packages, and smallest 
losses occur at the cooler DHLW waste packages that receive condensation when they cool 
below boiling (96C). Condensation at the drift wall, and within the near-field host rock 
adjacent to the DHLW waste package, offsets some (but not all) of the initial moisture loss. The 
smaller net moisture reduction at the cooler waste package locations results in smaller reduction 
in relative humidity than occurs for at hotter waste packages. Axial vapor transport is also 
predicted to cause net moisture reduction in the invert beneath the hotter waste package locations 
(Figure 7.5-7). Condensation in the invert beneath cooler waste packages increases the 
liquid-phase saturation there (Figure 7.5-7d). 
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Because the MSTHM does not include axial vapor transport along the drift, it does not represent 
the net moisture reduction discussed above. However, the differences in predicted relative 
humidity and host-rock liquid saturation between the MSTHM results and case 3 are smaller than 
the overall effect of parametric uncertainty of host-rock thermal conductivity and percolation 
flux for the MSTHM of the repository (Section 6.3.5). Although the MSTHM does not directly 
account for the influences of the cold-trap effect or of rock dryout during the ventilation period, 
it does compare well with case 3, which includes both of these influences. Therefore, it is 
unnecessary to incorporate axial vapor transport and the resulting cold-trap effect into the 
MSTHM for TSPA-LA. 
7.6 VALIDATION SUMMARY 
The MSTHM has been validated by applying acceptance criteria, which are based on evaluation 
of the models relative importance to the performance of the repository system. All validation 
requirements defined in the governing TWP (BSC 2004 [DIRS 170950], Section 2.2) have been 
fulfilled, including corroboration of model results with experimental data (Section 7.4) and 
corroboration with an alternative mathematical model (Section 7.5). Requirements for 
confidence building during model development have also been satisfied. The model 
development activities and post-development validation activities described in Section 7.1 of this 
report establish the scientific bases for the MSTHM. Based on this, the MSTHM is sufficiently 
accurate and adequate for the intended purpose, consistent with the level of confidence required 
by the models relative importance to the performance of the repository system. 
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8. CONCLUSIONS 
8.1 ANALYSIS AND MODELING CONCLUSIONS 
This model report documents the multiscale thermohydrologic model (MSTHM). An important 
phenomenological consideration for the licensing of the repository at Yucca Mountain is the 
generation of decay heat by the emplaced waste and the thermal-hydrologic consequences of this 
decay heat. A thermal-hydrologic modeling tool is developed and used to support the 
performance assessment of the engineered barrier system of the repository. This modeling tool 
simultaneously accounts for processes occurring at a scale of a few tens of centimeters around 
individual waste packages, for processes occurring around the emplacement drifts themselves, 
and for processes occurring at the mountain scale. Additionally, many other features are 
considered including nonisothermal, multiphase-flow in fractured porous rock of variable 
liquid-phase saturation and thermal radiation and convection in open cavities. 
The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative 
humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, 
capillary pressure, and liquid-and gas-phase fluxes. The thermal-hydrologic parameters are 
determined as functions of position along each of the emplacement drifts in the repository and as 
functions of waste package type. These parameters are determined at various reference locations 
within the emplacement drifts, including the waste package and drip-shield surfaces and in the 
invert. They are also determined at various reference locations in the adjoining host rock; these 
parameters are determined every 20 m for each emplacement drift in the repository. Each 
emplacement drift is represented with its precise coordinate location, as well as each of the 
emplacement panels in the repository area (Figure 4-1). The MSTHM also accounts for 
ventilation during the preclosure period, including how heat-removal efficiency from drift 
ventilation varies as a function of time and distance along each of the emplacement drifts. The 
MSTHM accounts for three-dimensional drift-scale and mountain-scale heat flow. The MSTHM 
captures the influence of the key engineering-design parameters and natural system factors 
affecting thermal-hydrologic conditions in the emplacement drifts and adjoining host rock, 
including: 
 Repository-scale variability of percolation flux above the repository 
 Temporal variability of percolation flux (as influenced by climate change) 
 Uncertainty in percolation flux (as addressed by the lower-bound, mean, and 
upper-bound infiltration-flux cases) 
 Uncertainty in percolation flux (associated with infiltration estimates, flow focusing, and 
flow diversion by the rock layers overlying the repository) 
 Stratigraphic variation of thermal conductivity 
 Uncertainty in host-rock thermal conductivity of the host rock 
 Stratigraphic variation of bulk rock density and specific heat 
 Stratigraphic variation of hydrologic properties of the rock matrix 
 Stratigraphic variation of hydrologic properties of fractures 
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 Variability in overburden thickness 
 Overall areal heat-generation density of the waste inventory, quantified by the Areal 
Mass Loading (AML, expressed in MTU/acre) 
 Line-averaged thermal load along emplacement drifts, quantified by the Lineal Power 
Density (LPD, expressed in kW/m) 
 Distance between emplacement drifts (also called drift spacing) 
 Age of spent-nuclear fuel at time of emplacement 
 Repository footprint shape, which influences the evolution of the edge-cooling effect 
that increases with proximity to the repository edges 
 Dimensions of the in-drift design (waste packages, drip shield, and invert) 
 Properties of the in-drift engineered barrier system components 
 Waste package spacing along the drift (line-load versus point-load spacing) 
 Waste package sequencing (particularly with respect to the heat output from the 
respective waste package types) 
 Time- and distance-dependent heat-removal efficiency of preclosure drift ventilation. 
This report describes MSTHM calculations conducted to support the Total System Performance 
Assessment for the License Application (TSPA-LA). The MSTHM simulations are conducted 
for three infiltration-flux cases (lower-bound, mean, and upper-bound). The impact of 
parametric uncertainty of the key input parameters, percolation flux and host-rock thermal 
conductivity, is also addressed. Percolation flux and host-rock thermal conductivity are the two 
most important natural system parameters influencing peak temperatures and the time that the 
drift wall remains above the boiling point. It is found that the combined influence of 
percolation-flux uncertainty and host-rock thermal conductivity uncertainty on peak 
temperatures is represented by the sum of the individual contributions to peak-temperature 
uncertainty. It is also found that the combined influence of percolation-flux uncertainty and 
host-rock thermal conductivity on the duration of boiling at the drift wall is represented by the 
sum of the individual contributions to drift-wall-boiling-duration uncertainty. These conclusions 
are consistent with the approach used for abstraction of MSTHM results, with uncertainty, for 
TSPA-LA. 
8.2 MODEL VALIDATION, UNCERTAINTIES, AND LIMITATIONS 
This report documents decisions implemented during model development that build confidence 
and verify that a reasonable, credible technical approach using scientific and engineering 
principles was taken in order to: 
 Evaluate and select inputs 
 Formulate defensible assumptions 
 Ensure consistency with physical principles 
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 Represent important uncertainties 
 Ensure that MSTHM predictions represent the range of possible outcomes, consistent 
with important processes, variabilities, and uncertainties. 
For the purpose of confidence building and model validation, results from the MSTHM are 
compared against those from a mountain-scale thermohydrologic model, which is an alternative 
conceptual model (Section 6.4). Validation of the MSTHM is also supported by using results 
from field-scale thermal tests and using a monolithic thermohydrologic model of a three-drift 
repository test case, which is a scaled-down example of the actual repository (Section 7.5). The 
following discussion summarizes results using the Large Block Test (LBT) and Drift Scale Test 
(DST), and the three-drift repository test case. 
Three-dimensional NUFT thermohydrologic-model simulations are compared with temperatures 
and liquid-phase saturations measured in the Large Block Test (LBT). The NUFT 
thermohydrologic model used in this confidence-building study is a three-dimensional equivalent 
to the two-dimensional LDTH submodels (Section 6.2.6) used in the MSTHM. The good 
agreement between the simulated and measured temperatures in the LBT builds confidence that 
the NUFT model provides a valid representation of heat flow in partially saturated fractured 
porous rock. Good agreement between the simulated and measured dryout and rewetting 
behavior in the LBT demonstrates that the NUFT thermohydrologic simulations provide valid 
representation of dryout and rewetting behavior in partially saturated fractured porous rock. 
Three-dimensional NUFT thermohydrologic simulations are also compared with temperatures 
and liquid-phase saturations measured in the Drift Scale Test (DST). Note that the 
thermal-hydrologic model of the DST is a three-dimensional equivalent to the two-dimensional 
LDTH submodels (Section 6.2.6) used in the MSTHM. Overall agreement was achieved 
between simulated and measured temperatures. Simulated temperatures exhibit less of a 
distinctive plateau close to 96oC than the measured temperatures. This effect is associated with 
the use of the calibrated hydrologic property set and the low value of matrix permeability, which 
causes a large gas-phase pressure buildup in the matrix that increases the saturation (boiling) 
temperature and temporarily throttles (i.e., restricts) vaporization and delays rock dryout. 
Higher saturation (boiling) temperatures and lack of a temperature plateau close to 96C cause 
simulated temperatures to be higher than measured temperatures for the above-boiling region. 
Results from Section 7.4.4 of Drift-Scale Coupled Processes (DST and TH Seepage) Models 
(BSC 2004 [DIRS 170338]) show that when the site-specific property set is used, this transient 
throttling effect does not occur and better agreement is obtained between simulated and 
measured temperatures in the above-boiling region. 
Another reason for the NUFT-simulated temperatures being higher than measured temperatures 
is the uncertainty in host-rock thermal conductivity Kth at the DST location. For the high-Kth 
case (one standard deviation above the mean), simulated temperatures are in better agreement 
with the measured temperatures than the cases that used the mean Kth values. Because 
percolation fluxes cannot be directly measured, uncertainty in the local percolation flux in the 
DST area also contributes to differences between simulated and measured temperatures. Section 
6.3.4 discusses the influence of key parametric uncertainties on predicted thermohydrologic 
conditions in the repository. Table 6.3-30 shows that the combined influence of host-rock 
percolation-flux and thermal conductivity uncertainties results in peak drift-wall temperatures 
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varying by 26.6 to 38.3oC for the four host-rock units. The 30-percent validation criterion for 
temperature rise (above ambient), which is given in the TWP, is consistent with the magnitude of 
the influence of the parametric uncertainty of host-rock thermal conductivity and percolation flux 
on temperature. As shown in Table 6.3-30, the combined influence of host-rock thermal 
conductivity uncertainty and percolation-flux uncertainty causes the rise in peak drift-wall 
temperature (above ambient) to vary by about 30 percent. For temperatures less than about 
80C, simulated and measured temperatures are in good agreement for all three cases considered: 
(1) base case, (2) sealed bulkhead, and (3) high Kth. 
With a few exceptions, the differences between the NUFT-simulated and measured temperature 
increases above ambient temperatures are less than 30 percent, thereby satisfying one part of the 
validation criterion for the DST comparison. The few exceptions are associated with the use of 
the calibrated hydrologic property set and the low value of matrix permeability, which results in 
a large gas-phase pressure buildup in the matrix that increases the saturation (boiling) 
temperature. It is important to note that this transient throttling effect dissipates as the 
NUFT-simulated gas-phase pressure buildup declines. Heating conditions for the DST result in 
an accelerated temperature increase, compared to that predicted for repository heating 
conditions. Thus, although matrix permeability is seen to have a noticeable affect on 
temperatures simulated for the DST, it does not significantly affect repository temperature 
evolution predicted by thermal-hydrologic models supporting TSPA-LA. Overall, the 
comparison of NUFT-simulated and measured temperatures demonstrates that the NUFT 
thermohydrologic model provides a valid representation of heat flow in the DST. 
Although the NUFT-simulated dryout behavior (as measured by the liquid-phase saturation in 
the matrix continuum) lagged behind that observed in the DST, this is a transient effect. Heating 
conditions for the DST result in an accelerated temperature rise and dryout, compared to those 
predicted for repository heating conditions. Although the NUFT-simulated dryout lags behind 
the DST-observed dryout, this is not important to the application of the MSTHM for post-closure 
repository predictions. This is because predicted rock dryout for repository heating conditions is 
slower, occurring over much longer time frames than applicable to the DST. Within four years, 
the DST-observed rock dryout approaches the NUFT-simulated dryout, which satisfies the 
validation criterion for the DST comparison. Therefore, it can be concluded that the NUFT 
thermohydrologic model provides a valid representation of rock dryout in the DST and that the 
MSTHM provides valid predictions of post-closure dryout. To the extent that the observations in 
the DST allow, the NUFT thermohydrologic model provides a valid representation of rewetting 
behavior in the DST. 
Another conclusion from the DST model validation study is that the sealed-bulkhead case results 
in slightly higher NUFT-simulated temperatures than the base case (which had a leaky 
bulkhead). The influence of the leaky bulkhead on simulated temperatures is less than that 
resulting from a one standard-deviation estimated range in thermal conductivity. This 
conclusion is useful with respect to the potential significance of whether the ends of the 
emplacement drifts are sealed with bulkheads or simply backfilled with highly permeable 
crushed tuff. The lack of sensitivity of the DST thermohydrologic simulations to the treatment 
of the bulkhead (leaky versus sealed) suggests that the MSTHM predictions of thermohydrologic 
response in the emplacement drifts is not significantly affected by whether the ends of the 
emplacement drifts are sealed. 
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Validation of the MSTHM methodology itself involves a three-drift repository test case. This 
test case represents a scaled-down repository, consisting of three 243-m long drifts. A 
monolithic three-dimensional thermohydrologic model of this three-drift repository test case 
discretely represents 15 waste packages: 7 at the center of the central drift and 4 at either end of 
the central drift. The MSTHM and the monolithic thermohydrologic model predict almost 
identical thermohydrologic conditions at all waste package locations at the center of the 
three-drift repository test case. At the edge of the three-drift repository test case, the MSTHM 
and monolithic thermohydrologic model also predict similar conditions. Differences between the 
two models are largest for the last two waste packages at the edge, where the MSTHM predicts 
peak temperatures that are about 17oC higher than predicted in the monolithic 
thermal-hydrologic model. Note that the outermost two waste packages cover only 1.6 percent 
of the repository area. For the third and fourth waste package in from the repository edge, the 
MSTHM predicts peak temperatures that are about 6 to 8oC higher than predicted in the 
monolithic thermal-hydrologic model. For waste packages located more than 20 m from the 
repository edge, which encompasses 96.8 percent of the repository area, the bias in peak 
temperatures predicted by the MSTHM is less than about 6oC. However, because all of the 
differences are within the range of those caused by parametric uncertainty (totaling about 30 to 
40oC, depending on the host-rock unit, as shown in Table 6.3-28), the MSTHM satisfies the 
validation criterion for this comparison and is suitable for predicting thermal-hydrologic 
conditions for all waste package locations. 
The propagation of parametric uncertainty in the MSTHM addresses the two key natural system 
parameters: host-rock thermal conductivity and percolation flux. A sensitivity study of the 
influence of hydrologic-property uncertainty supports the conclusion that hydrologic-property 
uncertainty does not need to be propagated in the MSTHM calculations of in-drift temperature 
and relative humidity. Propagation of percolation-flux and host-rock thermal conductivity 
uncertainty in repository-wide MSTHM output is addressed with the following five 
(infiltration-flux host-rock thermal conductivity) cases: 
 Lower-bound infiltration-flux case with low (mean minus one standard deviation) 
host-rock thermal conductivity 
 Lower-bound infiltration-flux case with mean host-rock thermal conductivity 
 Mean infiltration-flux case with mean host-rock thermal conductivity 
 Upper-bound infiltration-flux case with mean host-rock thermal conductivity 
 Upper-bound infiltration-flux case with high (mean plus one standard deviation) host-
rock thermal conductivity 
For these five cases, the range in peak drift-wall temperature is from 92C to 175C, with a 
median drift-wall temperature of 133C; the range in peak waste package temperature is from 
102C to 203C, with a median waste package temperature of 153C (Table 6.3-38). These five 
cases also result in a wide range of waste package relative-humidity histories as is shown in 
Figure 6.3-53. 
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Another thermohydrologic parameter is the time when boiling ceases at the drift wall. For the 
five infiltration-flux host-rock thermal conductivity cases, the time when drift-wall boiling 
ceases ranges from no boiling to 2,177 years, with a median time of 721 years (Table 6.3-39). 
The percentage of waste packages that may experience no boiling at the drift wall is low (0.1% 
of all waste packages). 
Another thermohydrologic result of interest is the maximum lateral extent of the boiling zone 
relative to the centerline of the emplacement drifts because this indicates the likelihood of 
condensate and percolation flux drainage around emplacement drifts during the dryout period. 
For the five infiltration-flux host-rock thermal conductivity cases, the maximum lateral extent of 
boiling ranges from 4.1 to 27.9 m, with a median maximum lateral extent of 7.9 m (Table 
6.3-40). The lowest end of this range (4.1 m) pertains to the situation where boiling only occurs 
within the emplacement drift (i.e., not at the drift wall). For the majority of cases the lateral 
extent of boiling is much smaller than the half spacing between emplacement drifts. Therefore, 
the majority of the host rock between emplacement drifts always remains below the boiling 
point, thereby enabling condensate and percolation flux to continuously drain between 
emplacement drifts. Because of the continuous drainage of condensate around a dryout zone of 
limited extent, condensate above the emplacement drifts is limited. 
8.3 MODEL OUTPUTS 
The MSTHM results supplied to TSPA are summarized in Table 1-1. For each SMT submodel 
location (2,874 locations distributed over the repository area, which is shown in Figure 6.2-3), 
bin indices are calculated based on the rank order of the percolation flux associated with the 
location. Bin 1 includes the 5 percent of locations with the smallest percolation flux. Bin 2 
includes locations with percolation fluxes in the 5th to 30th percentile. Bin 3 includes locations 
with percolation fluxes in the 30th to 70th percentile. Bin 4 includes locations with percolation 
fluxes in the 70th to 95th percentile. Bin 5 includes locations with percolation fluxes above the 
95th percentile. Note that the binning is based solely on the percolation fluxes for the 
glacial-transition climate of the mean infiltration-flux case. Moreover, the lower- and 
upper-bound infiltration-flux cases share the same areal binning as that determined for the mean 
infiltration-flux case. 
MSTHAC v7.0 calculations are performed at all 2,874 SMT submodel locations, and the output 
from these calculations are postprocessed and written in a format required to satisfy TSPA 
parameter requirements. Two sets of information are generated for the MSTHM 
output-parameter DTNs. The first set, which is called the WAPDEG binning set, includes 
limited output parameters at every SMT submodel location and for each of the two waste 
package groups, including commercial spent nuclear fuel (CSNF) and defense high-level waste 
(DHLW). The second set, which is called the TSPA binning set, includes complete output 
variable information for only typical bin locations and for typical waste packages (with respect to 
temperature and relative humidity histories) for each of the two waste package groups (CSNF 
and DHLW). Note that the waste package degradation (WAPDEG) model is a process model, 
which is downstream of the MSTHM (with respect to model-to-model parameter flow) and 
which directly uses MSTHM output parameters. 
For seepage modeling and engineered barrier system performance assessment (Seepage and 
WAPDEG models), all SMT submodel locations and each of the eight waste package types 
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(Table 6.3-13) are considered; therefore, there are 2,874 locations multiplied by 8 waste package 
types, which results in 22,992 waste package histories that are reported. For each SMT 
submodel location and waste package type, a single file is produced that reports Twp, RHwp, Tdw, 
Tds, and RHds, where T and RH are temperature and relative humidity and wp, dw, and ds stand 
for waste package, drift wall, and drip shield, respectively. Two waste package groupsDHLW 
and CSNFare also defined, and for each SMT submodel location, the most typical waste 
package in the grouping is selected and the same five parameters reported. The DHLW group 
includes waste packages dhlw-l1 and dhlw-s1. The CSNF group includes waste packages 
pwr1-1, pwr2-1, bwr1-1, bwr2-1, pwr1-2 and bwr1-2. Details of the determination of the typical 
waste package can be found in Appendix VIII. 
Since the WAPDEG binning produces a large number of output files, the first set of files are 
concatenated using a UNIX shell script so that all locations falling within a bin and all waste 
packages of a given type (CSNF or DHLW) are included in a single file. This process creates 
5 (the number of bins) multiplied by 2 (the number of waste package groups), which results in 10 
output files. The second set of typical files is also concatenated so that there is one file for each 
bin and each waste package group. This produces another 5  2 = 10 files. Hence a total of 
20 WAPDEG files are provided for each infiltration-flux case. 
The second process (TSPA binning) involves determining the most typical location given a set of 
locations that define a bin. For TSPA purposes, the focus is the most typical waste package 
(see below) in a group or bin; therefore, there are 5 bins  2 groups = 10 typical waste packages 
reported. TSPA binning uses the same waste package group definitions used in WAPDEG 
binning. For each bin, two output files are created, one for the most typical CSNF package and 
one for the most typical DHLW package. There are 5 (the number of bins) multiplied by 2 (the 
number of waste package groups) files created for this type of processing. The process of 
determining the typical waste packages is described in Appendix VIII. The TSPA files include 
all MSTHM output parameters that are relevant to the modeled repository (43 in all) covering 
temperature, relative humidity, liquid-phase saturation, liquid-phase flux and other 
thermal-hydrologic parameters at reference locations within and adjacent to the emplacement 
drifts. 
Table 8-1 is a list of data tracking numbers (DTNs) associated with the output produced by this 
report. 
8.4 YUCCA MOUNTAIN REVIEW PLAN CRITERIA ASSESSMENT 
This model report predicts results that directly pertain to the abstraction of the quantity and 
chemistry of water contacting engineered barriers and waste forms. This section summarizes the 
contents of this report as they apply to U.S. Nuclear Regulatory Commissions criteria for a 
detailed review of that abstraction. These are the relevant criteria from the Yucca Mountain 
Review Plan, Final Report (NRC 2003, Section 2.2.1.3.3.3 [DIRS 163274] which is from 
10 CFR 63.114(a)(c) and (e)(g) [DIRS 156605]). 
This report provides predictions of the evolution of thermal-hydrologic conditions in the 
repository emplacement drifts and in the adjoining host rock, but not predictions of seepage or 
in-drift condensation. These predictions provide the downstream process models and model 
abstraction with the thermal-hydrologic parameters (as functions of time) that influence the 
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evolution of in-drift coupled flow and transport processes. Some aspects of the acceptance 
criteria (chemistry, seepage) are not addressed by this report. 
8.4.1 Acceptance Criterion 1  System Description and Model Integration are Adequate 
(1) Total system performance assessment adequately incorporates important design 
features, physical phenomena, and couplings, and uses consistent and appropriate 
assumptions throughout the quantity and chemistry of water contacting engineered 
barriers and waste forms abstraction process; 
Table 4.1-1 lists the sources of input for design features and physical features. The design 
features that are inputs to the MSTHM calculations (including drip shield, invert, waste 
packages, drift design, and thermal loading) are in accordance with Interface Exchange Drawings 
(IEDs) (Section 4.1.1). Section 4.1.2 discusses the effects of small changes to the IEDs 
subsequent to the calculations documented in this report. Supplementary properties of the 
planned components are inputs from ASME standards and other justified sources (Section 4.1.1 
and Appendix X). Simplifying assumptions about material properties are stated and justified 
(Section 5.3). The ventilation efficiency as a function of drift location and time is input from 
Ventilation Model and Analysis Report (BSC 2004 [DIRS 169862]). 
Physical features of the unsaturated zone (stratigraphy) and some properties of the materials are 
input from Development of Numerical Grids for UZ Flow and Transport Modeling (BSC 2004 
[DIRS 169855]). Other properties of the natural materials are input from Calibrated Properties 
Model (BSC 2004 [DIRS 169857]), Analysis of Hydrologic Properties Data (BSC 2004 
[DIRS 170038]), Thermal Conductivity of Non-Repository Lithostratigraphic Layers (BSC 2004 
[DIRS 170033]), Thermal Conductivity of the Potential Repository Horizon (BSC 2004 
[DIRS 169854]), and other justified sources (Section 4.1). These sources assure consistency 
throughout the abstractions affecting the representation of the quantity and chemistry of water 
contacting engineered barriers and waste forms. Simplifying assumptions about material 
properties are stated and justified (Section 5.3). 
The MSTHM represents the design features, physical phenomena, and couplings at the 
appropriate spatial scales. It incorporates a conceptual model for flow through unsaturated 
fractured porous rock at Yucca Mountain that is based on a dual-permeability representation of 
overlapping fracture and matrix continua (Section 6.2.2), which is consistent with all other 
hydrologic models, such as UZ Flow Models and Submodels (BSC 2004 [DIRS 169861], 
Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]) and 
Mountain-Scale Coupled Processes (TH/THC/THM) (BSC 2004 [DIRS 169866]). The 
conceptual model for unsaturated-zone thermohydrology is implemented from standard form 
mass- and energy-balance equations (Sections 6.2.3.1, 6.2.3.2, and 6.2.3.6), including treatments 
of radiative heat transfer (Section 6.2.3.3) and thermal conduction (Section 6.2.3.4), with an 
active-fracture modification to the traditional dual-permeability approach (Section 6.2.3.5). The 
model does not address the chemistry of the water, but provides input to process models and 
abstractions that address chemical environments, waste package corrosion, and waste-form 
degradation. 
The coupling of thermal and hydrologic processes is at the heart of the model presented in this 
report. The MSTHM couples the effects of processes at various spatial scales, from a few tens of 
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centimeters around individual waste packages and emplacement drifts to the scale of the 
mountain (Section 6.2.1). The MSTHM accomplishes this with four submodel types of varying 
dimensionality (Section 6.2.4), using simplified assumptions that are stated and justified 
(Sections 5.2, 5.5, 5.6, and 5.7). The MSTHM is validated by comparing predictions from its 
key thermal-hydrological submodel (called the LDTH submodel) against field test data (Sections 
7.3 and 7.4) and by comparing MSTHM predictions with predictions from a monolithic 
three-dimensional thermal-hydrological model (Section 7.5). Coupled processes that are not 
addressed in this report are considered, and their rationale for exclusion presented, in Engineered 
Barrier System Features, Events, And Processes (BSC 2004 [DIRS 169898]). 
(2) The abstraction of the quantity and chemistry of water contacting engineered barriers 
and waste forms uses assumptions, technical bases, data, and models, that are 
appropriate and consistent with other related U.S. Department of Energy abstractions. 
For example, the assumptions used for the quantity and chemistry of water contacting 
engineered barriers and waste forms are consistent with the abstractions of 
Degradation of Engineered Barriers (Section 2.2.1.3.1); Mechanical Disruption of 
Engineered Barriers (Section 2.2.1.3.2); Radionuclide Release Rates and Solubility 
Limits (Section 2.2.1.3.4); Climate and Infiltration (Section 2.2.1.3.5); and Flow 
Paths in the Unsaturated Zone (Section 2.2.1.3.6). The descriptions and technical 
bases provide transparent and traceable support for the abstraction of quantity and 
chemistry of water contacting engineered barriers and waste forms; 
The MSTHM provides the basis for how long boiling conditions in the host rock adjacent to the 
drift wall prevent water from seeping into drifts. The MSTHM also determines temperature and 
relative humidity on the engineered barriers, quantities required for determining in-drift 
chemistry. The MSTHM has been validated for its intended purpose (Sections 7.1 and 7.2), 
using the results of field tests (Sections 7.3 and 7.4), and by comparing the MSTHM against an 
alternative model for the three-drift repository test case (Section 7.5). The magnitude of seepage 
during the post-boiling period and the chemistry of that seepage are not determined by the 
MSTHM nor in this report. 
(3) Important design features, such as waste package design and material selection, 
backfill, drip shield, ground support, thermal loading strategy, and degradation 
processes, are adequate to determine the initial and boundary conditions for 
calculations of the quantity and chemistry of water contacting engineered barriers and 
waste forms; 
Initial and boundary conditions for the MSTHM calculations of repository performance are 
based on inputs from other project documents (Section 4.1). Descriptions of design features are 
documented in IEDs (Section 4.1). Predicted heat-removal efficiency of the ventilation system is 
documented in Ventilation Model and Analysis Report (BSC 2004 [DIRS 169862]). The 
rationale for not directly representing ground support in the MSTHM is documented in Sections 
5.3.1.10 and 5.3.2.7, and in Appendix VI. These inputs were sufficient to completely define the 
initial and boundary conditions for the MSTHM calculations. 
(4) Spatial and temporal abstractions appropriately address physical couplings (thermal-
hydrologic-mechanical-chemical). For example, the U.S. Department of Energy 
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evaluates the potential for focusing of water flow into drifts, caused by coupled 
thermal-hydrologic-mechanical-chemical processes; 
The physics of coupled thermal-hydrological processes (Sections 6.1 and 6.2) are adequately 
incorporated into the MSTHM methodology (Section 6.2.4) and its submodels (Sections 6.2.5 
through 6.2.11). Sensitivity analyses (Sections 6.3.9) on the influence of hydrologic property 
variability and uncertainty, demonstrate that the potential impact of mechanical and chemical 
coupling on the thermal-hydrological response in repository drifts (and in the adjacent host rock) 
are insignificant, compared to the influences of parametric uncertainty (Sections 6.3.2 and 6.3.4), 
which are addressed by the MSTHM and this report. 
(5) Sufficient technical bases and justification are provided for total system performance 
assessment assumptions and approximations for modeling coupled thermal-
hydrologic-mechanical-chemical effects on seepage and flow, the waste package 
chemical environment, and the chemical environment for radionuclide release. The 
effects of distribution of flow on the amount of water contacting the engineered 
barriers and waste forms are consistently addressed, in all relevant abstractions; 
The MSTHM addresses repository-scale variability and uncertainty of percolation flux that is 
based on the output (DTN: LB0302PTNTSW9I.001 [DIRS 162277]) from the UZ Flow Models 
and Submodels (BSC 2004 [DIRS 169861]). The MSTHM provides the basis for how long 
boiling conditions in the host rock adjacent to the drift wall prevent water from seeping into 
drifts. The magnitude of seepage during the post-boiling period and the chemistry of that 
seepage are not determined by the MSTHM nor in this report. However, the MSTHM 
determines temperature and relative humidity on the engineered barriers, quantities required for 
determining in-drift chemistry. The physics of coupled thermal-hydrological processes (Sections 
6.1 and 6.2) are adequately incorporated into the MSTHM methodology (Section 6.2.4) and its 
submodels (Sections 6.2.5 through 6.2.11). Sensitivity analyses (Sections 6.3.9) on the influence 
of hydrologic property variability and uncertainty, demonstrate that the potential impact of 
mechanical and chemical coupling on the thermal-hydrological response in repository drifts (and 
in the adjacent host rock) is insignificant, compared to the influences of parametric uncertainty 
(Sections 6.3.2 and 6.3.4), which are addressed by the MSTHM and this report. 
(6) The expected ranges of environmental conditions within the waste package 
emplacement drifts, inside the breached waste packages, and contacting the waste 
forms and their evolution with time are identified. These ranges may be developed to 
include: (i) the effects of the drip shield and backfill on the quantity and chemistry of 
waster (e.g., the potential for condensate formation and dripping from the underside of 
the shield); (ii) conditions that promote corrosion of engineered barriers and 
degradation of waste forms; (iii) irregular wet and dry cycles; (iv) gamma-radiolysis; 
and (v) size and distribution of penetrations of engineered barriers; 
The MSTHM provides the basis for how long boiling conditions in the host rock adjacent to the 
drift wall prevent water from seeping into drifts. The magnitude of seepage during the 
postboiling period and the chemistry of that seepage are not determined by the MSTHM or in 
this report. However, the MSTHM determines temperature and relative humidity on the 
engineered barriers, quantities required for determining in-drift chemistry. 
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(7) The model abstraction for quantity and chemistry of water contacting engineered 
barriers and waste forms is consistent with the detailed information on engineered 
barrier design and other engineered features. For example, consistency is 
demonstrated for: (i) dimensionality of the abstractions; (ii) various design features 
and site characteristics; and (iii) alternative conceptual approaches. Analyses are 
adequate to demonstrate that no deleterious effects are caused by design or site 
features that the U.S. Department of Energy does not take into account in this 
abstraction; 
The MSTHM accounts for the three-dimensional geometry of the emplacement drift, drip shield, 
and invert (Section 6.2), including a discrete representation of each emplacement drift (Figure 
6.2-3). The MSTHM also addresses the distribution of hydrostratigraphic units (and their 
respective thermal-hydrologic properties), based on Numerical Grids for UZ Flow and Transport 
Modeling (BSC 2004 [DIRS 169855]), Calibrated Properties Model (BSC 2004 
[DIRS 169857]), Thermal Conductivity of the Potential Repository Horizon (BSC 2004 
[DIRS 169854]), Thermal Conductivity of Non-Repository Lithostratigraphic Layers (BSC 2004 
[DIRS 170033]), and Heat Capacity Analysis Report (BSC 2004 [DIRS 170003]). The MSTHM 
also addresses the distribution of percolation flux above the repository, based on UZ Flow 
Models and Submodels (BSC 2004 [DIRS 169861]). 
(8) Adequate technical bases are provided, including activities such as independent 
modeling, laboratory or field data, or sensitivity studies, for inclusion of any thermal-
hydrologic-mechanical-chemical couplings and features, events, and processes; 
This report lists ten features, events and processes (FEPs) that are included in the MSTHM 
model (Section 6.5). Table 6.5-1 provides, for each FEP, a cross-reference to the section that 
describes its disposition. Coupled processes that are not addressed in this report are considered, 
and their rationale for exclusion or inclusion elsewhere, is presented in Engineered Barrier 
System Features, Events, And Processes (BSC 2004 [DIRS 169898]). 
(9) Performance-affecting processes that have been observed in thermal-hydrologic tests 
and experiments are included into the performance assessment. For example, the U.S. 
Department of Energy either demonstrates that liquid water will not reflux into the 
underground facility or incorporates refluxing water into the performance assessment 
calculation, and bounds the potential adverse effects of alteration of the hydraulic 
pathway that result from refluxing water; 
The LDTH submodel of the MSTHM has been validated against the Large Block Test (Section 
7.3) and the Drift Scale Test (Section 7.4). The LDTH submodel includes the influence of 
refluxing water in the host rock on the predicted thermal-hydrologic response in the drift and 
adjacent host rock. However, the LDTH-submodel results have never suggested the possibility 
of that refluxing water entering the emplacement drifts. Neither the results of the 
thermal-hydrological model simulations nor the measurements associated with the DST suggest 
the possibility of refluxing water entering emplacement drifts. Section 8.1 of Drift-Scale 
Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338]) includes the 
following key conclusions: 
ANL-EBS-MD-000049 REV 02 8-11 October 2004 

Multiscale Thermohydrologic Model 
 For cases where thermal seepage takes place, it is predicted to begin several hundred to a 
few thousand years after rock temperature has returned below boiling, the delay caused 
by the slow saturation buildup in fractures; there is no seepage during the time period of 
above-boiling temperatures in the rock. 
 Thermal-seepage percentages are always smaller than the respective ambient reference 
values, indicating that there is no enhanced seepage as a result of reflux of water. 
Based on these conclusions, it is unnecessary to incorporate refluxing water in performance 
assessment calculations. 
(12) Guidance in NUREG1297 (Altman et al. 1988 [DIRS 103597]) and NUREG1298 
(Altman et al. 1988 [DIRS 103750]), or other acceptable approaches, is followed. 
Inputs were selected and documented, and documents were checked and reviewed according to 
applicable BSC procedures, which comply with NUREG-1297 and 1298 (see Section 2). 
8.4.2 Acceptance Criterion 2  Data Are Sufficient for Model Justification 
(1) Geological, hydrological, and geochemical values used in the license application are 
adequately justified. Adequate description of how the data were used, interpreted, and 
appropriately synthesized into the parameters is provided; 
Geological and hydrological parameters and related information are input from Development of 
Numerical Grids for UZ Flow and Transport Modeling (BSC 2004 [DIRS 169855]), Calibrated 
Properties Model (BSC 2004 [DIRS 169857]), Analysis of Hydrologic Properties Data (BSC 
2004 [DIRS 170038]), Thermal Conductivity of Non-Repository Lithostratigraphic Layers (BSC 
2004 [DIRS 170033]), Thermal Conductivity of the Potential Repository Horizon (BSC 2004 
[DIRS 169854], Section 4.1), and other justified sources. Descriptions of how the data were 
used, interpreted, and appropriately synthesized are provided in those documents. 
(2) Sufficient data were collected on the characteristics of the natural system and 
engineered materials to establish initial and boundary conditions for conceptual 
models of thermal-hydrological-mechanical-chemical coupled processes, that affect 
seepage and flow and the engineered barrier chemical environment; 
Initial and boundary conditions for the MSTHM calculations are documented in Mountain-Scale 
Coupled Processes (TH/THC/THM) (BSC 2004 [DIRS 169866]) and UZ Flow Models and 
Submodels (BSC 2004 [DIRS 169861]). Those reports describe the technical basis for 
establishing the initial and boundary conditions. 
(3) Thermo-hydrologic tests were designed and conducted with the explicit objectives of 
observing thermal-hydrologic processes for the temperature ranges expected for 
repository conditions and making measurements for mathematical models. Data are 
sufficient to verify that thermal-hydrologic conceptual models address important 
thermal-hydrologic phenomena; 
ANL-EBS-MD-000049 REV 02 8-12 October 2004 

Multiscale Thermohydrologic Model 
The Large Block Test and the Drift Scale Test provided data for processes in the expected 
temperature range. These tests were used to validate the conceptual model underlying the LDTH 
submodels used in the MSTHM (Sections 7.3 and 7.4). 
(4) Sufficient information to formulate the conceptual approach(es) for analyzing water 
contact with the drip shield, engineered barriers, and waste forms is provided. 
The MSTHM provides the basis for how long boiling conditions in the host rock adjacent to the 
drift wall prevents water from seeping into drifts. The magnitude of seepage during the 
postboiling period and the chemistry of that seepage are not determined by the MSTHM or in 
this report. However, the MSTHM determines temperature and relative humidity on the 
engineered barriers, quantities required for determining in-drift chemistry. The MSTHM is 
validated by comparing predictions from its key thermal-hydrological submodel (called the 
LDTH submodel) against field test data (Sections 7.3 and 7.4) and by comparing MSTHM 
predictions with predictions from a monolithic three-dimensional thermal-hydrological model 
(Section 7.5), which is an alternative model. 
8.4.3 Acceptance Criterion 3  Data Uncertainty Is Characterized and Propagated 
Through the Model Abstraction 
(1) Models use parameter values, assumed ranges, probability distributions, and bounding 
assumptions that are technically defensible, reasonably account for uncertainties and 
variabilities, and do not result in an under-representation of the risk estimate; 
The model parameter values were selected based on the characteristics of the input and are 
considered representative of the natural and engineered systems (Section 4.1). Design 
information is taken from Interface Exchange Drawings and qualified analyses. Boundary 
conditions, stratigraphy, and percolation fluxes are from UZ flow models, including 
uncertainties. Properties of the natural and engineered materials are based on measurements 
taken and documented in accordance with DOE quality requirements (Section 4.1 and 
Appendices IV and X). When modeling decisions were necessary, the choices were made to 
preserve the variability of thermal-hydrologic responses (Sections 5.2.1, 5.2.2, and 6.2.1), 
thereby avoiding an under-representation of the risk estimate. 
(2) Parameter values, assumed ranges, probability distributions, and bounding 
assumptions used in the total system performance assessment calculations of 
quantity and chemistry of water contacting engineered barriers and waste forms are 
technically defensible and reasonable, based on data from the Yucca Mountain 
region (e.g., results from large block and drift-scale heater and niche tests), and a 
combination of techniques that may include laboratory experiments, field 
measurements, natural analog research, and process-level modeling studies; 
Sufficiently wide ranges of the key natural-system parameters are addressed to reasonably 
account for uncertainty (Section 6.3), and therefore do not result in an under-representation of 
the risk estimate. A sensitivity study (Section 6.3.9) justifies the decision not to propagate 
hydrologic-property uncertainty in the MSTHM. Sensitivity studies (Sections 6.3.10, 6.3.11, and 
6.3.12) justify assumptions made in Section 5 concerning engineered-system parameter values. 
ANL-EBS-MD-000049 REV 02 8-13 October 2004 

Multiscale Thermohydrologic Model 
(3) Input values used in the total system performance assessment calculations of quantity 
and chemistry of water contacting engineered barriers (e.g., drip shield and waste 
package) are consistent with the initial and boundary conditions and the assumptions 
of the conceptual models and design concepts for the Yucca Mountain site. 
Correlations between input values are appropriately established in the 
U.S. Department of Energy total system performance assessment. Parameters used to 
define initial conditions, boundary conditions, and computational domain in sensitivity 
analyses involving coupled thermal-hydrologic-mechanical-chemical effects on 
seepage and flow, the waste package chemical environment, and the chemical 
environment for radionuclide release, are consistent with available data. Reasonable 
or conservative ranges of parameters or functional relations are established; 
Parameters used to define initial conditions, boundary conditions, and computational domain of 
the MSTHM are consistent with available data. The MSTHM addresses the distribution of 
hydrostratigraphic units (and their respective thermal-hydrologic properties), based on Numerical 
Grids for UZ Flow and Transport Modeling (BSC 2004 [DIRS 169855]), Calibrated Properties 
Model (BSC 2004 [DIRS 169857]), Thermal Conductivity of the Potential Repository Horizon 
(BSC 2004 [DIRS 169854]), Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
(BSC 2004 [DIRS 170033]), and Heat Capacity Analysis Report (BSC 2004 [DIRS 170003]). 
The MSTHM addresses the distribution of percolation flux above the repository, based on UZ 
Flow Models and Submodels (BSC 2004 [DIRS 169861]). 
(4) Adequate representation of uncertainties in the characteristics of the natural system 
and engineered materials is provided in parameter development for conceptual models, 
process-level models, and alternative conceptual models. The U.S. Department of 
Energy may constrain these uncertainties using sensitivity analyses or conservative 
limits. For example, the U.S. Department of Energy demonstrates how parameters 
used to describe flow through the engineered barrier system bound the effects of 
backfill and excavation-induced changes; 
Previous studies have found that uncertainty in calculated thermohydrologic response is 
dominated by the uncertainty in host-rock thermal conductivity (Section 6.3.2). The sensitivity 
of thermohydrologic response to host-rock thermal conductivity uncertainty is addressed for plus 
and minus one standard deviation about the mean value (Section 6.3.2.2). Measurement 
statistics are used to determine the standard deviation for the wet and dry thermal conductivity 
values for each of the four host-rock units. Section 6.3.9 demonstrates that host-rock hydrologic 
property uncertainty has an insignificant influence on the thermal-hydrologic response. Section 
6.3.11 demonstrates that invert hydrologic-property uncertainty has an insignificant influence on 
the thermal-hydrologic response. Sections 5.3.1.10 and 5.3.2.7 justify the assumption that 
ground support does not need to be incorporated in the MSTHM. 
Previous studies have found that the contribution to uncertainty in calculated thermal-hydrologic 
conditions from the uncertainties in boundary values is dominated by the uncertainty in 
percolation flux (Section 6.3.2). The uncertainty in percolation flux at the repository horizon is 
addressed by way of lower-bound, mean, and upper-bound infiltration-flux cases, generated by 
UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]) for each of three climate states: 
present-day, monsoonal, and glacial-transition (Section 6.3.2.1). The percolation-flux range 
ANL-EBS-MD-000049 REV 02 8-14 October 2004 

Multiscale Thermohydrologic Model 
from lower bound to upper bound for the present-day climate covers five orders of magnitude. 
Similar ranges apply to the monsoonal and glacial-transition climates. 
In summary, the influence of parametric uncertainty of host-rock thermal conductivity and 
percolation flux on the predicted thermal-hydrologic response, which is represented in the 
MSTHM, is greater than differences in the predicted thermal-hydrologic response between the 
MSTHM and alternative conceptual models (Section 7.5). 
8.4.4 Acceptance Criterion 4  Model Uncertainty Is Characterized and Propagated 
Through the Model Abstraction 
(1) Alternative modeling approaches of features, events, and processes are considered and 
are consistent with available data and current scientific understanding, and the results 
and limitations are appropriately considered in the abstraction; 
The validation of the MSTHM involved comparison with the results from a three-dimensional 
monolithic thermal-hydrologic model (Section 7.5), which is an alternative model. The 
differences in predicted thermal-hydrologic responses between the MSTHM and the alternative 
model are smaller than differences resulting from parametric uncertainty. Therefore, model 
uncertainty does not need to be propagated through the model abstraction. 
(2) Alternative modeling approaches are considered and the selected modeling approach is 
consistent with available data and current scientific understanding. A description that 
includes a discussion of alternative modeling approaches not considered in the final 
analysis and the limitations and uncertainties of the chosen model is provided; 
The validation of the MSTHM involved comparison with the results from a three-dimensional 
monolithic thermal-hydrologic model (Section 7.5), which is an alternative model. The 
differences in predicted thermal-hydrologic responses between the MSTHM and the alternative 
model are smaller than differences resulting from parametric uncertainty. Therefore, model 
uncertainty does not need to be propagated through the model abstraction. This report also 
considers a mountain-scale thermal-hydrologic model as an alternative to the MSTHM (Section 
6.4). A calculation with the alternative model used (1) coarser grid discretization at the drift 
scale than the MSTHM, (2) a line-averaged approximation of the heat-generation-rate-versus-
time table (whereas the MSTHM represented the waste packages as discrete heat sources), and 
(3) a lumped heat source that filled the entire cross section of the emplacement drift. Because of 
limitations in the predictions provided from the alternative model, comparison is restricted to 
predictions of drift-wall temperatures. The differences are within the range of temperature 
differences resulting from parametric uncertainty. This report also contains a discussion of the 
limitations of the MSTHM (Section 1) and its uncertainties (Sections 6.3.9 through 6.3.13). 
(3) Consideration of conceptual model uncertainty is consistent with available site 
characterization data, laboratory experiments, field measurements, natural analog 
information and process-level modeling studies; and the treatment of conceptual 
model uncertainty does not result in an under-representation of the risk estimate; 
Comparison of the MSTHM with data from field tests (Sections 7.3 and 7.4) finds that the model 
uncertainty is within the range of parameter uncertainty. Comparison between the MSTHM and 
ANL-EBS-MD-000049 REV 02 8-15 October 2004 

Multiscale Thermohydrologic Model 
the 3-drift monolithic TH model for the three-drift repository test case (Section 7.5), finds that 
the model uncertainty is within the range of parameter uncertainty. 
(4) Adequate consideration is given to effects of thermal-hydrologic-mechanical-chemical 
coupled processes in the assessment of alternative conceptual models. These effects 
may include: (i) thermal-hydrologic effects on gas, water, and mineral chemistry; (ii) 
effects of microbial processes on the engineered barrier chemical environment and the 
chemical environment for radionuclide release; (iii) changes in water chemistry that 
may result from the release of corrosion products from the engineered barriers and 
interactions between engineered materials and ground water; and (iv) changes in 
boundary conditions (e.g., drift shape and size) and hydrologic properties, relating to 
the response of the geomechanical system to thermal loading. 
Sensitivity analyses (Sections 6.3.9) on the influence of hydrologic property variability and 
uncertainty, demonstrate that the potential impact of mechanical and chemical coupling on the 
thermal-hydrological response in repository drifts (and in the adjacent host rock) are 
insignificant, compared to the influences of parametric uncertainty (Sections 6.3.2 and 6.3.4), 
which are addressed by the MSTHM and this report. The influence of drift collapse on 
thermal-hydrologic response is addressed in Section 6.3.7. 
Table 8-1. Data Tracking Numbers Associated with the Output Produced by This Report 
DTN Title 
LL030602723122.027 Multiscale Thermohydrologic Model Output to TSPA and WAGDEG for Upper 
Infiltration Case 
LL030608723122.028 Multiscale Thermohydrologic Model Output to TSPA and WAPDEG for the Lower 
Infiltration Case 
LL030610323122.029 Multiscale Thermohydrologic Model Output to TSPA and WAPDEG for the Mean 
Infiltration Case 
LL030704523122.030 NUFT Input File Data Development to Support LA Multi-Scale Analyses 
LL030704623122.031 NUFT Input File Data Development to Support LA Multi-Scale Analyses 
LL030804023122.034 Sensitivity Studies for Evaluating the Impact of Thermal Conductivity and Percolation 
Rate on LA Multi-Scale Analyses 
LL030808523122.035 Input and Output Files Supporting MSTHM Micro-Abstractions for LA Multi-Scale 
Analyses 
LL030808623122.036 Input and Output Files for NUFT MSTHM Submodels Supporting LA Multi-Scale 
Analyses 
LL030808723122.037 Input and Output Files for the Creation of NUFT MSTHM Submodel Input Files 
Supporting LA Multi-Scale Analyses 
LL030808823122.038 Input and Output Files for Building SMT, SDT, and LDTH Submodel Mesh Files in 
Support of LA Multi-Scale Analyses 
LL030808923122.039 Input and Output Files Associated with the Large-Block and Drift Scale Tests in 
Support of LA Multi-Scale Analyses 
LL030906131032.002 Output from the Multi-Scale AMR for the Lower Percolation Mean Thermal 
Conductivity Case including Drift Wall Temperatures 
LL040102223122.042 Evaluation of the Sensitivity of In-Drift Temperature and Relative Humidity to 
Hydrologic-Property Uncertainty 
LL031206723122.041 WAPDEG Output from the Multi-Scale AMR for the Mean Percolation Mean Thermal 
Conductivity Case including Drift Wall Temperatures 
LL030906531032.005 Output from the Multi-Scale AMR for the Upper Percolation Mean Thermal 
Conductivity Case including Drift Wall Temperatures 
ANL-EBS-MD-000049 REV 02 8-16 October 2004 

Multiscale Thermohydrologic Model 
Table 8-1. Data Tracking Numbers Associated with the Output Produced by This Report (Continued) 
DTN Title 
LL030905931032.001 Sensitivity Studies for Evaluating the Impact of Thermal Conductivity and Percolation 
Rate on LA Multi-Scale Analyses. Lower Percolation Case, Low Thermal 
Conductivity in Host Rock 
LL030906331032.004 Sensitivity Studies for Evaluating the Impact of Thermal Conductivity and Percolation 
Rate on LA Multi-Scale Analyses. Upper Percolation Case, High Thermal 
Conductivity in Host Rock 
LL040310323122.044 Input and Output files of the MSTHM Micro-Abstractions for the Collapsed-Drift cases 
for the TSPA-LA Low-Probability-Seismic Scenario 
LL040404423122.045 Input and Output Files of the LDTH-Model Runs for the Focused-Seepage Sensitivity 
Analysis for the Collapsed-Drift Cases Conducted in ANL-EBS-MD-000049 Rev 1 
ICN1 
LL040501323122.046 Input and Output Files for the Sensitivity Studies for (1) Host-Rock Hydrologic 
Properties, (2) Invert Intragranular Hydrologic Properties, and (3) Rubble Heat 
Capacity for the Low-Probability-Seismic, Collapsed-Drift Cases 
LL040604823122.047 Input and Output Files for the Creation of NUFT MSTHM Submodel Input Files 
Supporting LA Multi-Scale Analyses 
LL040703023122.048 Input and Output Files Associated with the Large-Block and Drift Scale Tests in 
Support of LA Multi-Scale Analyses 
LL040703123122.049 Input and Output Files for the Sensitivity Studies for (1) Invert Intergranular 
Hydrologic Properties, (2) Pseudo Permeability of the Gas-Filled Drift Cavity, and (3) 
Ventilation Heat-Removal Efficiency 
LL040703223122.050 Validation of the Multiscale Thermal-Hydrologic Model Against a Corresponding 
Three-Dimensional Monolithic Thermal-Hydrologic Model 
LL040704323122.051 Input and Output Files for the Comparison Study of Initial Liquid-Phase Saturation 
and Capillary Pressure for the Mean and Modified-Mean Infiltration-Flux Property 
Sets for the Lower-Bound, Mean, and Upper-Bound Infiltration-Flux Cases 
MO0307SPAVGSUM.000 van Genuchten hydrologic parameters 
MO0406CDFINSMT.000 Area Weighted Cumulative Distribution Function (CDF) for PTN/TSW Infiltration 
Rates Within SMT Area 
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Multiscale Thermohydrologic Model 
INTENTIONALLY LEFT BLANK 
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9. INPUTS AND REFERENCES 
9.1 DOCUMENTS CITED 
Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Qualification of Existing 103750
Data for High-Level Nuclear Waste Repositories: Generic Technical Position. 
NUREG-1298. Washington, D.C.: U.S. Nuclear Regulatory Commission. 
TIC: 200652. 
Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Peer Review for High-103597
Level Nuclear Waste Repositories: Generic Technical Position. NUREG-1297. 
Washington, D.C.: U.S. Nuclear Regulatory Commission. TIC: 200651. 
Bandurraga, T.M. and Bodvarsson, G.S. 1999. Calibrating Hydrogeologic 103949
Parameters for the 3-D Site-Scale Unsaturated Zone Model of Yucca Mountain, 
Nevada. Journal of Contaminant Hydrology, 38, (1-3), 25-46. New York, New 
York: Elsevier. TIC: 244160. 
Bear, J. 1972. Dynamics of Fluids in Porous Media. Environmental Science 156269
Series. Biswas, A.K., ed. New York, New York: Elsevier. TIC: 217356. 
Bird, R.B.; Stewart, W.E.; and Lightfoot, E.N. 1960. Transport Phenomena. 103524
New York, New York: John Wiley & Sons. TIC: 208957. 
Brooks, R.H. and Corey, A.T. 1964. Hydraulic Properties of Porous Media. 156915
Hydrology Paper No. 3. Fort Collins, Colorado: Colorado State University. 
TIC: 217453. 
BSC 2001. FY 01 Supplemental Science and Performance Analyses, Volume 1: 155950
Scientific Bases and Analyses. TDR-MGR-MD-000007 REV 00 ICN 01. Las 
Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20010801.0404; 
MOL.20010712.0062; MOL.20010815.0001. 
BSC 2001. Multiscale Thermohydrologic Model. ANL-EBS-MD-000049 REV 158204
00 ICN 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20020123.0279. 
BSC 2001. Thermal Tests Thermal-Hydrological Analyses/Model Report. ANL-157330
NBS-TH-000001 REV 00 ICN 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20011116.0025. 
BSC 2002. The Enhanced Plan for Features, Events, and Processes (FEPs) at 158966
Yucca Mountain. TDR-WIS-PA-000005 REV 00. Las Vegas, Nevada: Bechtel 
SAIC Company. ACC: MOL.20020417.0385. 
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Multiscale Thermohydrologic Model 
BSC 2002. Guidelines for Developing and Documenting Alternative Conceptual 158794 
Models, Model Abstractions, and Parameter Uncertainty in the Total System 
Performance Assessment for the License Application. TDR-WIS-PA-000008 
REV 00, ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20020904.0002. 
BSC 2003. Advection Versus Diffusion in the Invert. ANL-EBS-MD-000063. 170881
Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20040217.0004. 
BSC 2003. Analysis of Infiltration Uncertainty. ANL-NBS-HS-000027 REV 01. 165991
Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20031030.0003. 
BSC 2003. Design and Engineering, D&E/PA/C IED Typical Waste Package 165406
Components Assembly 1 of 9. 800-IED-WIS0-00201-000-00C. Las Vegas, 
Nevada: Bechtel SAIC Company. ACC: ENG.20030917.0002. 
BSC 2003. Interlocking Drip Shield. 000-MW0-TED0-00102-000-00A. Las 171024
Vegas, Nevada: Bechtel SAIC Company. ACC: ENG.20030205.0002. 
BSC 2003. Longevity of Emplacement Drift Ground Support Materials for LA. 165425
800-K0C-TEG0-01200-000-00A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20030922.0004. 
BSC 2003. Repository Design Project, Repository/PA IED Emplacement Drift 164101
Committed Materials (2). 800-IED-WIS0-00302-000-00A. Las Vegas, Nevada: 
Bechtel SAIC Company. ACC: ENG.20030627.0004. 
BSC 2003. Repository Design, Repository/PA IED Subsurface Facilities. 800-161727
IED-EBS0-00402-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20030109.0146. 
BSC 2004. Abstraction of Drift Seepage. MDL-NBS-HS-000019, Rev. 01. Las 169131
Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Analysis of Hydrologic Properties Data. ANL-NBS-HS-000042, 170038
Rev. 00. Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Calibrated Properties Model. MDL-NBS-HS-000003, Rev. 02. Las 169857
Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. D&E / PA/C IED Emplacement Drift Configuration. 800-IED-167040
MGR0-00201-000-00A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040113.0011. 
BSC 2004. D&E / PA/C IED Emplacement Drift Configuration and 168489
Environment. 800-IED-MGR0-00201-000-00B. Las Vegas, Nevada: Bechtel 
SAIC Company. ACC: ENG.20040326.0001. 
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Multiscale Thermohydrologic Model 
BSC 2004. D&E / PA/C IED Interlocking Drip Shield and Emplacement Pallet. 169220
800-IED-WIS0-00401-000-00D. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040503.0018. 
BSC 2004. D&E / PA/C IED Subsurface Facilities. 800-IED-WIS0-00101-000-164519
00A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040309.0026. 
BSC 2004. D&E / PA/C IED Subsurface Facilities. 800-IED-WIS0-00102-000-170202
00A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040309.0027. 
BSC 2004. D&E / PA/C IED Typical Waste Package Components Assembly. 167754
800-IED-WIS0-00203-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040202.0011. 
BSC 2004. D&E / PA/C IED Typical Waste Package Components Assembly. 167369
800-IED-WIS0-00204-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040202.0012. 
BSC 2004. D&E / PA/C IED Typical Waste Package Components Assembly. 169990
800-IED-WIS0-00205-000-00D. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040518.0001. 
BSC 2004. D&E/PA/C IED Typical Waste Package Components Assembly. 800-169472
IED-WIS0-00202-000-00C. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040517.0008. 
BSC 2004. Data Qualification Plan, Qualification of DTN: 170747
MO0304MWDALACV.000 for Use in ANL-EBS-MD-000049 Rev02. Las Vegas, 
Nevada: Bechtel SAIC Company. ACC: MOL.20040722.0266. 
BSC 2004. Design and Engineering, Interlocking Drip Shield Configuration. 168067
000-M00-SSE0-00102-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040305.0021. 
BSC 2004. Development of Numerical Grids for UZ Flow and Transport 169855
Modeling. ANL-NBS-HS-000015 REV 02. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: DOC.20040901.0001. 
BSC 2004. Drift Degradation Analysis. ANL-EBS-MD-000027 REV. 03. Las 166107
Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20040915.0010. 
BSC 2004. Drift-Scale Coupled Processes (DST and TH Seepage) Models. 170338
MDL-NBS-HS-000015, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040930.0003. 
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Multiscale Thermohydrologic Model 
BSC 2004. Drift Scale THM Model. MDL-NBS-HS-000017, Rev. 01. Las 169864 
Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Engineered Barrier System Features, Events, and Processes. ANL-169898 
WIS-PA-000002, Rev. 03. Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Evaluation of Features, Events, and Processes (FEP) for the 
169826 
Biosphere Model. ANL-MGR-MD-000011 Rev. 04. Las Vegas, Nevada: 
Bechtel SAIC Company. 
BSC 2004. Future Climate Analysis. ANL-NBS-GS-000008 REV 01. Las 170002
Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20040908.0005. 
BSC 2004. Ground Control for Emplacement Drifts for LA. 800-K0C-SSE0-170292
00100-000-00A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040712.0019. 
BSC 2004. Heat Capacity Analysis Report. ANL-NBS-GS-000013, Rev. 01. 170003
Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. In-Drift Natural Convection and Condensation. MDL-EBS-MD-164327
000001, Rev. 00. Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Mountain-Scale Coupled Processes (TH/THC/THM). MDL-NBS-169866
HS-000007 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Q-List. 000-30R-MGR0-00500-000-000 REV 00. Las Vegas, 168361
Nevada: Bechtel SAIC Company. ACC: ENG.20040721.0007. 
BSC 2004. Repository Subsurface Emplacement Drifts Steel Invert Structure 169503
Plan & Elevation. 800-SS0-SSE0-00101-000-00B. Las Vegas, Nevada: Bechtel 
SAIC Company. ACC: ENG.20040520.0004. 
BSC 2004. Technical Work Plan For: Near-Field Environment and Transport 170950 
In-Drift Heat and Mass Transfer Model and Analysis Reports Integration. TWP-
MGR-PA-000018 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040729.0006. 
BSC 2004. Thermal Conductivity of Non-Repository Lithostratigraphic Layers. 170033
MDL-NBS-GS-000006, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Thermal Conductivity of the Potential Repository Horizon. MDL-169854
NBS-GS-000005 REV 01. Las Vegas, Nevada: Bechtel SAIC Company.
ACC: DOC.20040928.0006. 
BSC 2004. Total System Performance Assessment (TSPA) Model/Analysis for the 168504
License Application. MDL-WIS-PA-000004, Rev. 00. Las Vegas, Nevada: 
Bechtel SAIC Company. 
ANL-EBS-MD-000049 REV 02 9-4 October 2004 

Multiscale Thermohydrologic Model 
BSC 2004. UZ Flow Models and Submodels. MDL-NBS-HS-000006, Rev. 02. 169861 
Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Ventilation Model and Analysis Report. ANL-EBS-MD-000030, 169862 
Rev. 04. Las Vegas, Nevada: Bechtel SAIC Company. 
Buscheck, T.A. 1999. Thermohydrologic Calculations for the Site 
130078 
Recommendation/License Application Design Selection, Phase 2. UCRL-ID-
133988. BB0000000-01717-0210-00009 REV 00. Livermore, California: 
Lawrence Livermore National Laboratory. ACC: MOL.20000606.0193. 
Buscheck, T.A. and Nitao, J.J. 1994. The Impact of Buoyant, Gas-Phase Flow 130561 
and Heterogeneity on Thermo-Hydrological Behavior at Yucca Mountain. 
UCRL-JC-115351. Livermore, California: Lawrence Livermore National 
Laboratory. ACC: NNA.19940524.0012. 
Buscheck, T.A. and Nitao, J.J. 1995. Thermal-Hydrological Analysis of 100657 
Large-Scale Thermal Tests in the Exploratory Studies Facility at Yucca 
Mountain. UCRL-ID-121791. Livermore, California: Lawrence Livermore 
National Laboratory. ACC: MOL.19960501.0392. 
Buscheck, T.A.; Gansemer, J.; DeLorenzo, T.H.; Nitao, J.J.; and Shaffer, R.J. 148521 
1998. Multiscale Thermohydrologic Model Sensitivity Analysis. UCRL-ID-
131489. Livermore, California: Lawrence Livermore National Laboratory. 
ACC: MOL.19980901.0245. 
Buscheck, T.A.; Gansemer, J.; Nitao, J.J.; and Delorenzo, T.H. 1999. Multi-145972 
Scale Near-Field Thermohydrologic Analysis of Alternative Designs for the 
Potential Repository at Yucca Mountain. Scientific Basis for Nuclear Waste 
Management XXII, Symposium held November 30-December 4, 1998, Boston, 
Massachusetts, U.S.A. Wronkiewicz, D.J. and Lee, J.H., eds. 556, 615-622. 
Warrendale, Pennsylvania: Materials Research Society. TIC: 246426. 
Buscheck, T.A.; Glascoe, L.G.; Lee, K.H.; Gansemer, J.; Sun, Y.; and Mansoor, 164638 
K. 2003. Validation of the Multiscale Thermohydrologic Model Used for 
Analysis of a Proposed Repository at Yucca Mountain. Journal of Contaminant 
Hydrology, 62-63, 421-440. New York, New York: Elsevier. TIC: 254205. 
Buscheck, T.A.; Rosenberg, N.D.; Gansemer, J.; and Sun, Y. 2002. 160749
Thermohydrologic Behavior at an Underground Nuclear Waste Repository. 
Water Resources Research, 38, (3), 10-1 through 10-19. Washington, D.C.: 
American Geophysical Union. TIC: 253566. 
Canori, G.F. and Leitner, M.M. 2003. Project Requirements Document. TER-166275
MGR-MD-000001 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20031222.0006. 
ANL-EBS-MD-000049 REV 02 9-5 October 2004 

Multiscale Thermohydrologic Model 
Cho, Y.I.; Ganic, E.N.; Hartnett, J.P.; and Rohsenow, W.M. 1998. Basic 
160802 
Concepts of Heat Transfer. Chapter 1 of Handbook of Heat Transfer. 3rd 
Edition. Rohsenow, W.M.; Hartnett, J.P.; and Cho, Y.I., eds. New York, New 
York: McGraw-Hill. TIC: 253612. 
Crane, R.A.; Vachon, R.I.; and Khader, M.S. 1977. Thermal Conductivity of 113426
Granular Materials - A Review. Proceedings of the Seventh Symposium on 
Thermophysical Properties, held at National Bureau of Standards, Gaithersburg, 
Maryland, May 10-12, 1977. Cezairliyan, A., ed. Pages 109-123. New York, 
New York: American Society of Mechanical Engineers. TIC: 246057. 
CRWMS (Civilian Radioactive Waste Management System) M&O (Management 111115
and Operating Contractor) 1998. Drift Scale Test As-Built Report. BAB000000-
01717-5700-00003 REV 01. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.19990107.0223. 
CRWMS M&O 1998. Total System Performance Assessment-Viability 108000
Assessment (TSPA-VA) Analyses Technical Basis Document. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.19981008.0001; MOL.19981008.0002; 
MOL.19981008.0003; MOL.19981008.0004; MOL.19981008.0005; 
MOL.19981008.0006; MOL.19981008.0007; MOL.19981008.0008; 
MOL.19981008.0009; MOL.19981008.0010; MOL.19981008.0011. 
CRWMS M&O 2000. Thermal Tests Thermal-Hydrological Analyses/Model 146921
Report. ANL-NBS-TH-000001 REV 00. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20000505.0231. 
CRWMS M&O 2000. Total System Performance Assessment for the Site 153246
Recommendation. TDR-WIS-PA-000001 REV 00 ICN 01. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.20001220.0045. 
CRWMS M&O 2001. Effective Thermal Conductivity for Drift-Scale Models 153410
Used in TSPA-SR. CAL-EBS-HS-000001 REV 00. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.20010301.0252. 
de Marsily, G. 1986. Quantitative Hydrogeology: Groundwater Hydrology for 100439
Engineers. San Diego, California: Academic Press. TIC: 208450. 
DOE (U.S. Department of Energy) 2004. Quality Assurance Requirements and 171539
Description. DOE/RW-0333P, Rev. 16. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040907.0002. 
Fetter, C.W. 1993. Contaminant Hydrogeology. Upper Saddle River, New 102009
Jersey: Prentice Hall. TIC: 240691. 
ANL-EBS-MD-000049 REV 02 9-6 October 2004 

Multiscale Thermohydrologic Model 
Flint, A.L.; Flint, L.E.; Bodvarsson, G.S.; Kwicklis, E.M.; and Fabryka-Martin, J. 156351
2001. Evolution of the Conceptual Model of Unsaturated Zone Hydrology at 
Yucca Mountain, Nevada. Journal of Hydrology, 247, ([1-2]), 1-30. New York, 
New York: Elsevier. TIC: 250932. 
Francis, N.D., Jr.; Webb, S.W.; Itamura, M.T.; and James, D.L. 2003. CFD 164602
Modeling of Natural Convection Heat Transfer and Fluid Flow in Yucca 
Mountain Project (YMP) Enclosures. SAND2002-4179. Albuquerque, New 
Mexico: Sandia National Laboratories. ACC: MOL.20030906.0165. 
Freeze, G.A.; Brodsky, N.S.; and Swift, P.N. 2001. The Development of 154365
Information Catalogued in REV00 of the YMP FEP Database. TDR-WIS-MD-
000003 REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company.
ACC: MOL.20010301.0237. 
Freeze, R.A. and Cherry, J.A. 1979. Groundwater. Englewood Cliffs, New 101173
Jersey: Prentice-Hall. TIC: 217571. 
Hardin, E.L. 1998. Near-Field/Altered-Zone Models Report. UCRL-ID-129179 100350
DR. Livermore, California: Lawrence Livermore National Laboratory. 
ACC: MOL.19980504.0577. 
Haukwa, C.; Wu, Y.S.; Hinds, J.J.; Zhang, W.; Ritcey, A.C.; Pan, L.H.; Simmons, 117826
A.M.; and Bodvarsson, G.S. 1998. Results of Sensitivity Studies of Thermo-
Hydrologic Behavior Conducted on Hydrologic Parameter Sets. Milestone 
SP3CK5M4. Berkeley, California: Lawrence Berkeley National Laboratory. 
ACC: MOL.19980918.0001. 
Hilf, J.W. 1975. Compacted Fill. Chapter 7 of Foundation Engineering 169699
Handbook. Winterkorn, H.F. and Fang, H.-Y., eds. New York, New York: Van 
Nostrand Reinhold. TIC: 248400. 
Hillel, D. 1998. Environmental Soil Physics. San Diego, California: Academic 165404
Press. TIC: 254422. 
Holman, J.P. 1990. Heat Transfer. 7th Edition. New York, New York: 106052
McGraw-Hill. TIC: 242477. 
Incropera, F.P. and DeWitt, D.P. 1996. Fundamentals of Heat and Mass 108184
Transfer. 4th Edition. New York, New York: John Wiley & Sons. 
TIC: 243950. 
Incropera, F.P. and DeWitt, D.P. 2002. Fundamentals of Heat and Mass 163337
Transfer. 5th Edition. New York, New York: John Wiley & Sons. 
TIC: 254280. 
ANL-EBS-MD-000049 REV 02 9-7 October 2004 

Multiscale Thermohydrologic Model 
Irvine, T.F., Jr. 1998. Thermophysical Properties. Chapter 2 of Handbook of 170361
Heat Transfer. 3rd Edition. Rohsenow, W.M.; Hartnett, J.P.; and Cho, Y.I., eds. 
New York, New York: McGraw-Hill. TIC: 253612. 
Jury, W.A.; Gardner, W.R.; and Gardner, W.H. 1991. Soil Physics. 5th Edition. 102010
New York, New York: John Wiley & Sons. TIC: 241000. 
Kaviany, M. 1998. Heat Transfer in Porous Media. Chapter 9 of Handbook of 170520
Heat Transfer. 3rd Edition. Rohsenow, W.M.; Hartnett, J.P.; and Cho, Y.I., eds. 
New York, New York: McGraw-Hill. TIC: 253612. 
Keenan, J.H.; Keyes, F.G.; Hill, P.G.; and Moore, J.G. 1969. Steam Tables, 134666
Thermodynamic Properties of Water Including Vapor, Liquid, and Solid Phases 
(English Units). New York, New York: John Wiley & Sons. TIC: 246766. 
Knudsen, J.G.; Bell, K.J.; Holt, A.D.; Hottel, H.C.; Sarofim, A.F.; Standiford, 170057
F.C.; Stuhlbarg, D.; and Uhl, V.W. 1984. Heat Transmission. Section 10 of 
Perry's Chemical Engineers' Handbook. 6th Edition. Perry, R.H.; Green, D.W.; 
and Maloney, J.O., eds. New York, New York: McGraw-Hill. TIC: 246473. 
Kunii, D. and Smith, J.M. 1960. Heat Transfer Characteristics of Porous 153166
Rocks. American Institute of Chemical Engineers Journal, 6, (1), 71-78. New 
York, New York: American Institute of Chemical Engineers. TIC: 249321. 
Leverett, M.C. 1941. Capillary Behavior in Porous Solids. AIME 100588
Transactions, Petroleum Development and Technology, Tulsa Meeting, October 
1940. 142, 152-169. New York, New York: American Institute of Mining and 
Metallurgical Engineers. TIC: 240680. 
Lichtner, P.C. and Walton, J.C. 1994. Near-Field Liquid-Vapor Transport in a 152609
Partially Saturated High-Level Nuclear Waste Repository. CNWRA 94-022. 
San Antonio, Texas: Center for Nuclear Waste Regulatory Analyses. 
TIC: 216007. 
Lide, D.R., ed. 1995. CRC Handbook of Chemistry and Physics. 76th Edition. 101876
Boca Raton, Florida: CRC Press. TIC: 216194. 
Liley, P.E.; Reid, R.C.; and Buck, E. 1984. Physical and Chemical Data. 146851
Section 3 of Perry's Chemical Engineers' Handbook. 6th Edition. Perry, R.H.; 
Green, D.W.; and Maloney, J.O., eds. New York, New York: McGraw-Hill. 
TIC: 246473. 
Liu, H.H.; Doughty, C.; and Bodvarsson, G.S. 1998. An Active Fracture Model 105729
for Unsaturated Flow and Transport in Fractured Rocks. Water Resources 
Research, 34, (10), 2633-2646. Washington, D.C.: American Geophysical 
Union. TIC: 243012. 
ANL-EBS-MD-000049 REV 02 9-8 October 2004 

Multiscale Thermohydrologic Model 
LLNL (Lawrence Livermore National Laboratory) 2000. Validation Test Plan, 170258
The Prediction of Thermohydrologic BehaviorNUFT 3.0.1s. Document 
Number: 10130-VTP-3.0.1s-00. North Las Vegas, Nevada: U.S. Department of 
Energy, Yucca Mountain Site Characterization Office. 
ACC: MOL.20010905.0180. 
LLNL (Lawrence Livermore National Laboratory) 2002. Validation Test Plan, 170259
The Prediction of Thermohydrologic BehaviorNUFT 3.0s, Rev 02. Software 
Document Number: 10088-VTP-3.0s-02. North Las Vegas, Nevada: U.S. 
Department of Energy, Yucca Mountain Site Characterization Office. 
ACC: MOL.20031024.0397. 
Manteufel, R.D.; Ahola, M.P.; Turner, D.R.; and Chowdhury, A.H. 1993. A 100776 
Literature Review of Coupled Thermal-Hydrologic-Mechanical-Chemical 
Processes Pertinent to the Proposed High-Level Nuclear Waste Repository at 
Yucca Mountain. NUREG/CR-6021. Washington, D.C.: U.S. Nuclear 
Regulatory Commission. TIC: 207771. 
McAdams, W.H. 1954. Heat Transmission. 3rd Edition. New York, New York: 161435
McGraw-Hill. TIC: 242359. 
Michel, H. 1999. Bernold Sheets. Letter from H. Michel (Bernold AG) to M. 163054
Grigore (MK), July 2, 1999, with enclosures. ACC: MOL.20030506.0321. 
Montazer, P. and Wilson, W.E. 1984. Conceptual Hydrologic Model of Flow in 100161
the Unsaturated Zone, Yucca Mountain, Nevada. Water-Resources Investigations 
Report 84-4345. Lakewood, Colorado: U.S. Geological Survey. 
ACC: NNA.19890327.0051. 
Mualem, Y. 1976. A New Model for Predicting the Hydraulic Conductivity of 100599
Unsaturated Porous Media. Water Resources Research, 12, (3), 513-522. 
Washington, D.C.: American Geophysical Union. TIC: 217339. 
Nitao, J.J. 1998. Reference Manual for the NUFT Flow and Transport Code, 100474
Version 2.0. UCRL-MA-130651. Livermore, California: Lawrence Livermore 
National Laboratory. ACC: MOL.19980810.0391. 
Nitao, J.J. 2000. Documentation of the Thermal Energy Balance Equation Used 159883
in the USNT Module of the NUFT Flow and Transport Code. UCRL-ID-139836. 
Livermore, California: Lawrence Livermore National Laboratory. 
ACC: MOL.20020711.0161. 
NRC (U.S. Nuclear Regulatory Commission) 2003. Yucca Mountain Review 163274
Plan, Final Report. NUREG-1804, Rev. 2. Washington, D.C.: U.S. Nuclear 
Regulatory Commission, Office of Nuclear Material Safety and Safeguards. 
TIC: 254568. 
ANL-EBS-MD-000049 REV 02 9-9 October 2004 

Multiscale Thermohydrologic Model 
Perry, R.H.; Green, D.W.; and Maloney, J.O., eds. 1984. Perrys Chemical 125806
Engineers Handbook. 6th Edition. New York, New York: McGraw-Hill. 
TIC: 246473. 
Pollock, D.W. 1986. Simulation of Fluid Flow and Energy Transport Processes 164747
Associated with High-Level Radioactive Waste Disposal in Unsaturated 
Alluvium. Water Resources Research, 22, (5), 765-775. Washington, D.C.: 
American Geophysical Union. TIC: 253791. 
Pruess, K.; Oldenburg, C.; and Moridis, G. 1999. TOUGH2 Users Guide, 160778
Version 2.0. LBNL-43134. Berkeley, California: Lawrence Berkeley National 
Laboratory. TIC: 253038. 
van Genuchten, M.T. 1980. A Closed-Form Equation for Predicting the 100610
Hydraulic Conductivity of Unsaturated Soils. Soil Science Society of America 
Journal, 44, (5), 892-898. Madison, Wisconsin: Soil Science Society of 
America. TIC: 217327. 
Winterkorn, H.F. and Fang, H.-Y. 1975. Soil Technology and Engineering 169700
Properties of Soils. Chapter 2 of Foundation Engineering Handbook.
Winterkorn, H.F. and Fang, H.-Y., eds. New York, New York: Van Nostrand 
Reinhold. TIC: 248400. 
Yagi, S. and Kunii, D. 1957. Studies on Effective Thermal Conductivities in 170330
Packed Beds. AIChE Journal, 3, (3), 373-381. New York, New York: 
American Institute of Chemical Engineers. TIC: 255847. 
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-2.14Q, Rev. 3, ICN 0. Document Review. Washington, D.C.: 
U.S. Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20030827.0018. 
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-2.27Q, Rev. 1, ICN 4. Planning for Science Activities. Washington, D.C.: 
U.S. Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040610.0006. 
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. 
ANL-EBS-MD-000049 REV 02 9-10 October 2004 

Multiscale Thermohydrologic Model 
AP-SI.2Q, Rev. 0. Qualification of Level A Developed or Modified Software. 
Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive 
Waste Management. ACC: MOL.20030113.0150. 
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.10Q, Rev. 2, ICN 7. Models. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040920.0002. 
ASME (American Society of Mechanical Engineers) 1995. Materials. Section 108417
II of 1995 ASME Boiler and Pressure Vessel Code. New York, New York: 
American Society of Mechanical Engineers. TIC: 245287. 
ASTM G 1-90 (Reapproved 1999). 1999. Standard Practice for Preparing, 103515
Cleaning, and Evaluating Corrosion Test Specimens. West Conshohocken, 
Pennsylvania: American Society for Testing and Materials. TIC: 238771. 
LP-SI.11Q-BSC, Rev. 0, ICN 1. Software Management. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20041005.0008. 
9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
GS000308311221.005. Net Infiltration Modeling Results for 3 Climate Scenarios 147613 
for FY99. Submittal date: 03/01/2000. 
GS000483351030.003. Thermal Properties Measured 12/01/99 to 12/02/99 152932 
Using the Thermolink Soil Multimeter and Thermal Properties Sensor on 
Selected Potential Candidate Backfill Materials Used in the Engineered Barrier 
System. Submittal date: 11/09/2000. 
GS020183351030.001. Uncompacted Bulk Density for Analyses Performed 163107 
02/02/00 to 05/23/00 on Potential Backfill Materials Used in the Engineered 
Barrier System. Submittal date: 01/22/2002. 
GS980808312242.015. Water Retention and Unsaturated Hydraulic Conductivity 119916 
Measurements for Various Size Fractions of Crushed, Sieved, Welded Tuff 
Samples Measured Using a Centrifuge. Submittal date: 08/21/1998. 
LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed 159525 
from Field Data. Submittal date: 05/14/2002. 
LB0208UZDSCPLI.002. Drift-Scale Calibrated Property Sets: Lower 161788 
Infiltration Data Summary. Submittal date: 08/26/2002. 
ANL-EBS-MD-000049 REV 02 9-11 October 2004 

Multiscale Thermohydrologic Model 
LB0208UZDSCPMI.002. Drift-Scale Calibrated Property Sets: Mean 
161243 
Infiltration Data Summary. Submittal date: 08/26/2002. 
LB03023DKMGRID.001. UZ 3-D Site Scale Model Grids. Submittal date: 162354 
02/26/2003. 
LB03023DSSCP9I.001. 3-D Site Scale UZ Flow Field Simulations for 9 
163044 
Infiltration Scenarios. Submittal date: 02/28/2003. 
LB0302PTNTSW9I.001. PTN/TSW Interface Percolation Flux Maps for 9 162277
Infiltration Scenarios. Submittal date: 02/28/2003. 
LB0302UZDSCPUI.002. Drift-Scale Calibrated Property Sets: Upper 161787
Infiltration Data Summary. Submittal date: 02/05/2003. 
LB0310MTSCLTH3.001. Mountain Scale 3D TH Predictions: Simulations. 170270
Submittal date: 10/21/2003. 
LB990701233129.001. 3-D UZ Model Grids for Calculation of Flow Fields for 106785
PA for AMR U0000, Development of Numerical Grids for UZ Flow and 
Transport Modeling. Submittal date: 09/24/1999. 
LB990861233129.001. Drift Scale Calibrated 1-D Property Set, FY99. 110226
Submittal date: 08/06/1999. 
LB991201233129.001. The Mountain-Scale Thermal-Hydrologic Model 146894
Simulations for AMR U0105, Mountain-Scale Coupled Processes (TH) 
Models. Submittal date: 03/11/2000. 
LL020710223142.024. Moisture Content of Rock from Neutron Logging 159551
Activities in the Drift Scale Test (DST): August 1997 through May 2002. 
Submittal date: 08/20/2002. 
LL030709023122.032. Moisture Content of Rock from Neutron Logging 165701
Activities in the Drift Scale Test (DST): January 2003 through May 2003. 
Submittal date: 07/24/2003. 
LL980918904244.074. Temperature, Relative Humidity and Gas Pressure 135872
Results During the Large Block Test FY 98. Submittal date: 09/29/1998. 
LL980919304244.075. Neutron Logging Activities at the Large Block Test 145099
(LBT). Submittal date: 09/30/1998. 
MO0001SEPDSTPC.000. Drift Scale Test (DST) Temperature, Power, Current, 153836
and Voltage Data for June 1, 1999 through October 31, 1999. Submittal date: 
01/12/2000. 
ANL-EBS-MD-000049 REV 02 9-12 October 2004 

Multiscale Thermohydrologic Model 
MO0002ABBLSLDS.000. As-Built Borehole Locations and Sensor Locations 147304
for the Drift Scale Test Given in Local (DST) Coordinates. Submittal date: 
02/01/2000. 
MO0003RIB00071.000. Physical and Chemical Characteristics of Alloy 22. 148850
Submittal date: 03/13/2000. 
MO0007SEPDSTPC.001. Drift Scale Test (DST) Temperature, Power, Current, 153707
and Voltage Data for November 1, 1999 through May 31, 2000. Submittal date: 
07/13/2000. 
MO0012SEPDSTPC.002. Drift Scale Test (DST) Temperature, Power, Current, 153708
and Voltage Data for June 1, 2000 through November 30, 2000. Submittal date: 
12/19/2000. 
MO0107SEPDSTPC.003. Drift Scale Test (DST) Temperature, Power, Current, 158321
and Voltage Data for December 1, 2000 through May 31, 2001. Submittal date: 
07/06/2001. 
MO0107TC239938.000. Hastelloy Alloy C-22, the Most Versatile Nickel-169995
Chromium-Molybdenum Alloy Available Today with Improved Resistance to 
Both Uniform and Localized Corrosion as Well as a Variety of Mixed Industrial 
Chemicals. Submittal date: 07/23/2001. 
MO0202SEPDSTTV.001. Drift Scale Test (DST) Temperature, Power, Current, 158320
and Voltage Data for June 1, 2001 through January 14, 2002. Submittal date: 
02/28/2002. 
MO0208SEPDSTTD.001. Drift Scale Test (DST) Temperature Data for January 161767
15, 2002 through June 30, 2002. Submittal date: 08/29/2002. 
MO0303SEPDSTTM.000. Drift Scale Test (DST) Temperature Data for July 1, 165698
2002 through December 31, 2002. Submittal date: 03/17/2003. 
MO0304MWDALACV.000. ANSYS-LA-Coarse Ventilation. Submittal date: 164551
04/09/2003. 
MO0306MWDASLCV.001. ANSYS-LA-Coarse Ventilation. Submittal date: 165695
07/01/2003. 
MO0307SEPDST31.000. Drift Scale Test (DST) Temperature Data for 165699
01/01/2003 through 06/30/2003. Submittal date: 07/07/2003. 
MO0307SPAUSFPD.000. Brooks and Corey Unsaturated Flow Properties Data. 164436
Submittal date: 07/23/2003. 
MO0312SEPQ1997.001. Meteorological Monitoring Data for 1997. Submittal 167116
date: 12/24/2003. 
ANL-EBS-MD-000049 REV 02 9-13 October 2004 

Multiscale Thermohydrologic Model 
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. 
MO9810DSTSET02.000. Drift Scale Test (DST) Temperature, Power, Current, 113662
Voltage Data for June 1 through August 31, 1998. Submittal date: 10/09/1998. 
MO98METDATA114.000. Validated Meteorological Data for Ambient Air 165702
Monitoring Report Period 27, January - March 1998. Submittal date: 
04/30/1998. 
MO98METDATA117.000. Validated Meteorological Data for Ambient Air 165705
Monitoring Report Period 28, April - June 1998. Submittal date: 08/11/1998. 
MO98METDATA120.000. Validated Meteorological Data for Ambient Air 165706
Monitoring Report Period 29, July - September 1998. Submittal date: 
10/30/1998. 
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. 
SN0303T0503102.008. Revised Thermal Conductivity of the Non-Repository 162401
Layers of Yucca Mountain. Submittal date: 03/19/2003. 
SN0307T0510902.003. Updated Heat Capacity of Yucca Mountain Stratigraphic 164196
Units. Submittal date: 07/15/2003. 
SN0404T0503102.011. Thermal Conductivity of the Potential Repository 169129
Horizon Rev 3. Submittal date: 04/27/2004. 
9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
LL030602723122.027. Multiscale Thermohydrologic Model Output to TSPA and WAGDEG 
for Upper Infiltration Case. Submittal date: 06/25/2003. 
LL030608723122.028. Multiscale Thermohydrologic Model Output to TSPA and WAPDEG for 
the Lower Infiltration Case. Submittal date: 06/27/2003. 
LL030610323122.029. Multiscale Thermohydrologic Model Output to TSPA and WAPDEG for 
the Mean Infiltration Case. Submittal date: 06/27/2003. 
LL030704523122.030. NUFT Input File Data Development to Support LA Multi-Scale 
Analyses. Submittal date: 07/17/2003. 
LL030704623122.031. NUFT Input File Data Development to Support LA Multi-Scale 
Analyses. Submittal date: 07/23/2003. 
ANL-EBS-MD-000049 REV 02 9-14 October 2004 

Multiscale Thermohydrologic Model 
LL030804023122.034. Sensitivity Studies for Evaluating the Impact of Thermal Conductivity 
and Percolation Rate on LA Multi-Scale Analyses. Submittal date: 09/11/2003. 
LL030808523122.035. Input and Output Files Supporting MSTHM Micro-Abstractions for LA 
Multi-Scale Analyses. Submittal date: 09/11/2003. 
LL030808623122.036. Input and Output Files for NUFT MSTHM Submodels Supporting LA 
Multi-Scale Analyses. Submittal date: 09/11/2003. 
LL030808723122.037. Input and Output Files for the Creation of NUFT MSTHM Submodel 
Input Files Supporting LA Multi-Scale Analyses. Submittal date: 09/11/03. 
LL030808823122.038. Input and Output Files for Building SMT, SDT, and LDTH Submodel 
Mesh Files in Support of LA Multi-Scale Analyses. Submittal date: 09/11/03. 
LL030808923122.039. Input and Output Files Associated with the Large-Block and Drift Scale 
Tests in Support of LA Multi-Scale Analyses. Submittal date: 09/11/2003. 
LL030906131032.002. Output from the Multi-Scale AMR for the Lower Percolation Mean 
Thermal Conductivity Case including Drift Wall Temperatures. Submittal date: 09/16/2003. 
LL040102223122.042. Evaluation of the Sensitivity of In-Drift Temperature and Relative 
Humidity to Hydrologic-Property Uncertainty. Submittal date: 01/12/2004. 
LL031206723122.041. WAPDEG Output from the Multi-Scale AMR for the Mean Percolation 
Mean Thermal Conductivity Case including Drift Wall Temperatures. Submittal date: 
12/22/2003. 
LL030906531032.005. Output from the Multi-Scale AMR for the Upper Percolation Mean 
Thermal Conductivity Case including Drift Wall Temperatures. Submittal date: 09/16/2003. 
LL030905931032.001. Sensitivity Studies for Evaluating the Impact of Thermal Conductivity 
and Percolation Rate on LA Multi-Scale Analyses. Lower Percolation Case, Low Thermal 
Conductivity in Host Rock. Submittal date: 09/16/2003. 
LL030906331032.004. Sensitivity Studies for Evaluating the Impact of Thermal Conductivity 
and Percolation Rate on LA Multi-Scale Analyses. Upper Percolation Case, High Thermal 
Conductivity in Host Rock. Submittal date: 09/16/2003. 
LL040310323122.044. Input and Output files of the MSTHM Micro-Abstractions for the 
Collapsed-Drift cases for the TSPA-LA Low-Probability Seismic Scenario. Submittal date: 
03/26/2004. 
LL040404423122.045. Input and Output Files of the LDTH-Model Runs for the Focused-
Seepage Sensitivity Analysis for the Collapsed-Drift Cases Conducted in ANL-EBS-MD-000049 
Rev 1 ICN1. Submittal date: 04/21/2004. 
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Multiscale Thermohydrologic Model 
LL040501323122.046. Input and Output Files for the Sensitivity Studies for (1) Host-Rock 
Hydrologic Properties, (2) Invert Intragranular Hydrologic Properties, and (3) Rubble Heat 
Capacity for the Low-Probability-Seismic, Collapsed-Drift Cases. Submittal date: 05/19/2004. 
LL040604823122.047. Input and Output Files for the Creation of NUFT MSTHM Submodel 
Input Files Supporting LA Multi-Scale Analyses. Submittal date: 07/12/2004. 
LL040703023122.048. Input and Output Files Associated with the Large-Block and Drift Scale 
Tests in Support of LA Multi-Scale Analyses. Submittal date: 07/15/2004. 
LL040703123122.049. Input and Output Files for the Sensitivity Studies for (1) Invert 
Intergranular Hydrologic Properties, (2) Pseudo Permeability of the Gas-Filled Drift Cavity, and 
(3) Ventilation Heat-Removal Efficiency. Submittal date: 07/14/2004. 
LL040703223122.050. Validation of the Multiscale Thermal-Hydrologic Model Against a 
Corresponding Three-Dimensional Monolithic Thermal-Hydrologic Model. Submittal date: 
07/14/2004. 
LL040704323122.051. Input and Output Files for the Comparison Study of Initial Liquid-Phase 
Saturation and Capillary Pressure for the Mean and Modified-Mean Infiltration-Flux Property 
Sets for the Lower-Bound, Mean, and Upper-Bound Infiltration-Flux Cases. Submittal date: 
07/16/2004. 
MO0307SPAVGSUM.000. van Genuchten hydrologic parameters. Submittal date: 07/26/2003. 
MO0406CDFINSMT.000. Area Weighted Cumulative Distribution Function (CDF) for 
PTN/TSW Infiltration Rates Within SMT Area. Submittal date: 07/01/2004. 
9.5 SOFTWARE CODES 
boundary_conditions. V1.0. Sun, Sun OS 5.8. 11042-1.0-00. 164275 
Chimney_interpolate. V1.0. Sun, Solaris 8. 11038-1.0-00. 164271 
colCen. V1.0. Sun, Solaris 8. 11043-1.0-00. 164279 
extractBlocks_EXT. V1.0. Sun, SUN O.S. 5.8. 11040-1.0-00. 164281 
heatgen_ventTable_emplace. V1.0. Sun, Solaris 8. 11039-1.0-00. 164276 
MSTHAC. V7.0. Sun, SUN O.S. 5.8. 10419-7.0-00. 164274 
NUFT. V3.0.1s. Sun, SUN O.S. 5.8. 10130-3.0.1s-01. 166636 
NUFT. V3.0s. SUN, Sun O.S. 5.8. 10088-3.0s-02. 164541 
RADPRO. V4.0. Sun, SUN O.S. 5.8. 10204-4.0-00. 164273 
readsUnits. V1.0. Sun, O.S. 5.5.1. 10602-1.0-00. 164542 
ANL-EBS-MD-000049 REV 02 9-16 October 2004 

Multiscale Thermohydrologic Model 
reformat_EXT_to_TSPA. V1.0. Sun, Sun OS 5.8. 11061-1.0-00. 
164272
repository_percolation_calculator. V1.0. Sun, SUN O.S. 5.8. 11041-1.0-00. 164280
rme6. v1.2. SUN, SOLARIS 8. 10617-1.2-00. 
163892
XTOOL V10.1. V10.1. Sun Ultra10. 10208-10.1-00. 
148638
xw. V1.0. Sun, Solaris 8. 11035-1.0-00. 
164278
YMESH. v1.54. SUN, SOLARIS 8. 10172-1.54-00. 163894
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INTENTIONALLY LEFT BLANK 
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Multiscale Thermohydrologic Model 
APPENDIX I 
BUILDING NUFT SUBMODELS
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Multiscale Thermohydrologic Model 
To build the NUFT submodels, the following 14 steps must be completed: 
Step 1 - Reformat the mesh from UZ Flow Models and Submodels (BSC 2004 [DIRS 
169861]) using rme6 v1.2. 
The mesh of the three-dimensional site-scale UZ flow model requires some minor modifications 
in order to be usable as input to YMESH v1.54. Note that the term World Grid, which is used 
in the following description, refers to the three-dimensional mountain-scale mesh that is required 
as input to YMESH v1.54. The software code rme6 v1.2 is used to read the element and vertices 
files in DTN: LB03023DKMGRID.001 [DIRS 162354] and to then create a single output file 
(called the World Grid), which contains the three-dimensional mountain-scale mesh in a format 
that can be read by YMESH v1.54. The software code rme6 v1.2 renames the UZ blocks such 
that the substring Ze in the block name is replaced by z. Likewise, VI is replaced by v, 
and all trailing _ characters are removed. 
The three-dimensional mountain-scale mesh (called the World Grid) is built by taking the 
element/connection and vertices files in DTN: LB03023DKMGRID.001 [DIRS 162354] and 
reformatting them into a YMESH-readable format using software code rme6 v1.2. Rename 
*__ to *, rename *Ze to *z, and rename *VI to *v. 
software code: 
rme6 
inputs: 
1) Element/connection file (from DTN: LB03023DKMGRID.001 [DIRS 162354]) 
Grid_LA_3D.mesh 
2) Vertices file (from DTN: LB03023DKMGRID.001 [DIRS 162354]) 
grid2002.grd 
output: 
1) World Grid 
LBL2003-LA-YMESH (DTN: LL030808823122.038) 
command line: 
rme6 Grid_LA_3D.mesh grid2002.grd LBL2003-LA-YMESH 
Step 2 - Expand the reformatted mountain-scale mesh using xw v1.0. 
The three-dimensional mountain-scale mesh (file LBL2003-LA-YMESH, which is called the 
World Grid) created in the previous step needs to be expanded since it is not large enough to 
encompass the required SMT submodel mesh. The software code xw v1.0 reads the 
three-dimensional mountain-scale mesh (LBL2003-LA-YMESH) and expands it in the easting 
direction such that the grid begins at 166,000 m easting and ends at 177,000 m easting in the 
Nevada Central coordinate system. 
software code: 
xw v1.0 
inputs: 
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Multiscale Thermohydrologic Model 
LBL2003-LA-YMESH (output from rme6 v1.2) 
outputs: 
1) Expanded World Grid 
LBL2003-LA-YMESH-expand (DTN: LL030808823122.038) 
command line: 
xw LBL2003-LA-YMESH LBL2003-LA-YMESH-expand (DTN: LL030808823122.038) 
Step 3 - Create the SDT, LDTH, DDT submodel .dat files. 
The first step in building the NUFT LDTH, SDT, and DDT submodel (also called chimney 
submodels) input files is to create the files containing the vertical grid dimensions and associated 
UZ model layers at each LDTH/SDT submodel location. This process begins with a file that 
gives the easting, northing, and repository elevation in Nevada Central coordinates for each 
LDTH/SDT submodel location. There are two additional reference files (one for LDTH 
submodels and one for SDT submodels) that detail how the UZ model layers should be vertically 
discretized by YMESH v1.54. These files serve as a template for the .dat files, which are 
constructed by taking the relevant template (SDT or LDTH) and inserting the Nevada Central 
coordinates for the specified LDTH/SDT submodel locations. These files are in the format 
specified by the YMESH v1.54 users manual for extracting LDTH/SDT submodel (chimneysubmodel) 
stratigraphies from the expanded World Grid. 
inputs: 
a. SDT and LDTH submodel inputs: 
chimneyLocation.dat (DTN: LL030808823122.038) 
Contains name, easting, northing, and repository elevation for each chimney 
LDTH/SDT submodel location. 
b. SDT submodel inputs: 
SDT_column_template_2003: Template for the SDT submodel .dat files. The template 
gives instructions to YMESH v1.54 about how to discretize the grid vertically by 
defining the vertical gridblock dimensions. This is essentially a complete .dat file, except 
the easting, northing, and repository elevation for each LDTH/SDT submodel (i.e., 
chimney-submodel) location (e.g., P1R10C5) defined in the file chimneyLocation.dat 
have been inserted (by copying and pasting), which creates .dat files for each of the 
respective SDT submodel locations (DTN: LL030808823122.038). 
c. LDTH submodel inputs: 
LDTH_column_template_2003: Template for the LDTH .dat files. The template gives 
instructions to YMESH v1.54 about how to discretize the grid vertically by defining the 
vertical gridblock dimensions. This is essentially a complete .dat file, except the easting, 
northing, and repository elevation for each chimney-submodel location (e.g., P1R10C5) 
defined in the file chimneyLocation.dat have been inserted (by copying and pasting), 
which creates .dat files for each of the respective LDTH submodel locations 
(DTN: LL030808823122.038). 
Step 4 - Create the SDT, LDTH, DDT submodel .col and .nft files (software code 
YMESH v1.54). 
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Multiscale Thermohydrologic Model 
Once the .dat files have been created, YMESH v1.54 is used to create the User Column 
Description files that contain the vertical dimensions of the grid, along with the vertical 
distribution of UZ model layers. This file contains the definition of each gridblock layer 
including its thickness and material type (i.e., UZ model layer). To create these files, YMESH 
v1.54 is started and the expanded World Mesh is read. Next, a .dat file is opened and a .col 
file is saved by selecting the User Column Description save option in the YMESH File/Save 
menu. This process is repeated at each chimney-submodel location and for each of the SDT, 
LDTH, and DDT submodels. 
The output .nft file is a NUFT genmsh table as defined in the NUFT users manual (Nitao 
1998 [DIRS 100474]). To create these files, YMESH v1.54 is started and the expanded World 
Mesh is read as input (using the Open data file command). Next, a .dat file is opened and a 
.nft file is saved by selecting the User NUFT genmsh save option in the YMESH v1.54 
File/Save menu. This process is repeated at each chimney-submodel location and for each of the 
SDT, LDTH, and DDT submodels. 
software code: 
YMESH v1.54 
inputs: 
LBL2003-LA-YMESH-expand (output from xw v1.0) (DTN: LL030808823122.038) 
.dat files for each SDT submodel (chimney-submodel) location 
(DTN: LL030808823122.038) 
.dat files for each LDTH submodel (chimney-submodel) location 
(DTN: LL030808823122.038) 
outputs: 
.col file for each SDT submodel (chimney-submodel) location 
(DTN: LL030808823122.038) 
.nft file for each SDT submodel (chimney-submodel) location 
(DTN: LL030808823122.038) 
.col file for each LDTH submodel (chimney-submodel) location 
(DTN: LL030808823122.038) 
.nft file for each LDTH submodel (chimney-submodel) location 
(DTN: LL030808823122.038) 
methodology: 
1) Start YMESH v1.54 
2) Open data file: World Grid (/LBL2003-LA-YMESH-expand) 
3) Open data file: chimney.dat file (*.dat) 
4) Save data file: User NUFT genmsh file (*.nft) 
5) Save data file: User Column Description file (*.col) 
6) Repeat Substeps 3 to 5 for all chimney-submodel locations and for each of the SDT, 
LDTH, and DDT submodels. 
Step 5 - Create the SDT submodel files. 
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Multiscale Thermohydrologic Model 
Once the .nft files have been created for the SDT submodel chimney-submodel files 
(Step 4), the following substeps are carried out. For each chimney-submodel location, two 
output files are created. The first output file is a .nft.dkm file that adds the atm, wt, and wp 
blocks (for atmosphere, water table boundaries, and waste package, respectively) to the input 
NUFT gensmsh .nft file; this file is used for the SDT submodel runs with repository heating. 
A second file is also created that is a duplicate of the .nft.dkm file except there is no wp block 
present. The second file is called .nft.dkm0; this file is used for the SDT submodel 
initialization runs that have no repository heating. Note that because the file-naming convention 
is parallel with that used for the LDTH submodels (discussed below), the suffix dkm is used 
for the SDT submodels, as well as for the LDTH submodels. This naming convention does not 
mean that the SDT submodels use the DKM. 
inputs (DTN: LL030808823122.038) 
.nft file for each SDT submodel (chimney-submodel) location 
output files: (DTN: LL030808823122.038) 
.nft.dkm file: adds the atm, wt boundary gridblocks and wp gridblocks to the input 
.nft file for each chimney-submodel location 
.nft.dkm0 file: adds the atm and wt blocks to the input .nft file for each chimneysubmodel 
location 
Step 6 - Create the LDTH submodel DKM files. 
Once the .nft files have been created, the DKM version of these files are created for each 
LDTH submodel (chimney-submodel) location. There are five output files created for each 
chimney-submodel location. The input files are modified to include the atmosphere and water 
table boundary gridblocks, to define the gridblocks within the emplacement drifts that represent 
the engineered barrier system components (e.g., invert), and to define the matrix and fracture 
continua. The specific elements added to each of the five types of output files are detailed 
below. Note that the files with the string dkm are used in the LDTH submodel runs with 
repository heating. The files with the string dkm0 are used in the LDTH submodel 
initialization runs that have no repository heating. 
inputs: (DTN: LL030808823122.038) 
.nft file for each LDTH submodel (chimney-submodel) location 
output files (a total of 5: for each chimney-submodel location): (DTN: LL030808823122.038) 
*.nft.msh.dkm0: adds the atm and wt boundary gridblocks to the input .nft file 
*.nft.msh.dkm0.f: adds the atm and wt fracture boundary gridblocks to the input 
.nft file. All blocks are prepended with f- to represent the 
fractures. 
*.nft.msh.dkm.f: adds the atm, wt, drift, wp, invert, and hstrk fracture gridblocks to 
the input .nft file. All blocks are prepended with f- to 
represent the fractures. 
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Multiscale Thermohydrologic Model 
*.nft.msh.dkm0.m: adds the atm and wt matrix boundary gridblocks to the input .nft 
file. All blocks are prepended with m- to represent the matrix. 
*.nft.msh.dkm.m: adds the atm, wt, drift, wp, invert, and hstrk matrix gridblocks to 
the input .nft file. All blocks are prepended with m- to represent 
the matrix. 
Step 7 - Create DDT and LDTH submodel thermal-radiation connections. 
Radiative heat transfer is an important component in the DDT and LDTH heat transfer models. 
To accommodate this mechanism, NUFT requires a list of all thermal-radiation connections 
between surfaces inside the drifts that are separated by air. Typical thermal-radiation 
connections are found between the waste package and the drift wall, the waste package and the 
drip shield, the drip shield and the drift wall, and the drift wall and other drift wall elements. 
These connections are generated by hand and verified visually using RADPRO v4.0. 
Step 8 - Calculate LDTH submodel percolation flux values. 
1. Determine the raw percolation flux value for each LDTH submodel (chimneysubmodel) 
location 
The LDTH submodel .col files created in Step 4 include the name of the grid 
column (e.g., g_9) from the three-dimensional site-scale UZ model grid (DTN: 
LB03023DKMGRID.001 [DIRS 162354]) that a given LDTH submodel resides 
within. For each of the respective LDTH submodel locations, the identity of the three-
dimensional site-scale UZ model grid column is recorded; note that this grid column is 
called the World Column by YMESH v1.54). Note that the identity of the World 
Column is given after the string WORLD COLUMN in the LDTH submodel input 
file. For each LDTH submodel location, the identity of the World Column is used to 
find the corresponding the present-day-, monsoonal- and glacial-transition-climate 
PTn-to-TSw percolation fluxes calculated by the three-dimensional site-scale UZ flow 
model (DTN: LB0302PTNTSW9I.001 [DIRS 162277]). This is repeated for the 
lower-bound, mean, and upper-bound infiltration flux cases. Note that there are nine 
percolation flux maps produced by the three-dimensional site-scale UZ flow model, 
corresponding to the three climate states and three infiltration flux cases. 
i. For each LDTH submodel .col file generated above, grep for the string 
WORLD COLUMN and record the name of the World Column that the LDTH 
submodel resides within. 
ii. From the three-dimensional site-scale UZ flow model 
(DTN: LB0302PTNTSW9I.001 [DIRS 162277]) and on the basis of the World 
Column that a given LDTH submodel resides within, find the PTn-to-TSw 
percolation flux values for the present-day, monsoonal, and glacial-transition 
climates and for the lower-bound, mean, and upper-bound infiltration flux cases. 
2. Determine the average percolation flux value for each repository panel 
The software code repository_percolation_calculator v1.0 is used, along with two 
input files to determine the repository-panel-averaged percolation flux for each 
ANL-EBS-MD-000049 REV 02 I-5 October 2004 

Multiscale Thermohydrologic Model 
repository panel (Panels 1, 2E, 2W, 3, and 5 in Figure 6.3-1). The first input file gives 
the coordinates of the vertices (i.e., corners) of a given repository panel. The second 
file is one of nine PTn-to-TSw percolation flux maps calculated by the three-
dimensional site-scale UZ flow model (DTN: LB0302PTNTSW9I.001 [DIRS 
162277]). The output from repository_percolation_calculator v1.0 is a file that 
contains the percolation flux values for each of the World Columns (i.e., grid columns 
from the three-dimensional site-scale UZ flow model) that fall within the given 
repository panel footprint. The output file also contains the average percolation flux 
for that repository panel. This averaged panel flux is a simple arithmetic average of 
the percolation flux values falling within the repository-panel footprint. Because 
Panel 1 is relatively small, it was decided to group it with Panel 2W and to treat Panels 
1 and 2W as a contiguous repository panel. Panels 2E, 3, and 5 are treated 
individually according to the procedure described above. 
software code: 
repository_percolation_calculator v1.0: given a set of coordinates 
defining the footprint of a repository panel and a PTn-to-TSw percolation 
flux map from the three-dimensional site-scale UZ flow model 
(DTN: LB0302PTNTSW9I.001 [DIRS 162277]), determine which World 
Columns lie within the polygon and do a simple average of the 
corresponding percolation values to determine the average panel 
percolation. 
input files: (DTN: LL030808723122.037) 
frameData1.dat: define the polygon for panel 1 
frameData2e.dat: define the polygon for panel 2E 
frameData2w.dat: define the polygon for panel 2W
frameData3.dat: define the polygon for panel 3 
frameData5.dat: define the polygon for panel 5 
preq_la_ptn.dat: the present-day-climate lower-bound infiltration 
flux case PTn-to-TSw percolation flux map 
(DTN: LB0302PTNTSW9I.001 [DIRS 162277]) 
preq _ma_ptn.dat: the present-day-climate mean infiltration flux case 
PTn-to-TSw percolation flux map (DTN: LB0302PTNTSW9I.001 [DIRS 
162277]) 
preq _ua_ptn.dat: the present-day-climate upper-bound infiltration 
flux case PTn-to-TSW percolation flux map 
(DTN: LB0302PTNTSW9I.001 [DIRS 162277]) 
monq_la_ptn.dat: the monsoonal-climate lower-bound infiltration flux 
case PTn-to-TSw percolation flux map (DTN: LB0302PTNTSW9I.001 
[DIRS 162277]) 
monq _ma_ptn.dat: the monsoonal-climate mean infiltration flux case 
PTn-to-TSw percolation flux map (DTN: LB0302PTNTSW9I.001 [DIRS 
162277]) 
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Multiscale Thermohydrologic Model 
monq _ua_ptn.dat: the monsoonal-climate upper-bound infiltration flux 
case PTn-to-TSw percolation flux map (DTN: LB0302PTNTSW9I.001 
[DIRS 162277]) 
glaq_la_ptn.dat: the glacial-transition-climate lower-bound 
infiltration flux case PTn-to-TSw percolation flux map 
(DTN: LB0302PTNTSW9I.001 [DIRS 162277]) 
glaq _ma_ptn.dat: the glacial-transition-climate mean infiltration flux 
case PTn-to-TSw percolation flux map (DTN: LB0302PTNTSW9I.001) 
glaq _ua_ptn.dat: the glacial-transition-climate upper-bound 
infiltration flux case PTn-to-TSw percolation flux map 
(DTN: LB0302PTNTSW9I.001 [DIRS 162277]) 
command line 
repository_percolation_calculator <percolation map> <panel outline> 
<output file> 
output files: (DTN: LL030808723122.037) 
glacial_la_frameData1.dat 
glacial_la_frameData2e.dat 
glacial_la_frameData2w.dat 
glacial_la_frameData3.dat 
glacial_la_frameData5.dat 
modern_la_frameData1.dat 
modern_la_frameData2e.dat 
modern_la_frameData2w.dat 
modern_la_frameData3.dat 
modern_la_frameData5.dat 
monsoon_la_frameData1.dat 
monsoon_la_frameData2e.dat 
monsoon_la_frameData2w.dat 
monsoon_la_frameData3.dat 
monsoon_la_frameData5.dat 
glacial_ma_frameData1.dat 
glacial_ma_frameData2e.dat 
glacial_ma_frameData2w.dat 
glacial_ma_frameData3.dat 
glacial_ma_frameData5.dat 
modern_ma_frameData1.dat 
modern_ma_frameData2e.dat 
modern_ma_frameData2w.dat 
modern_ma_frameData3.dat 
modern_ma_frameData5.dat 
monsoon_ma_frameData1.dat 
monsoon_ma_frameData2e.dat 
monsoon_ma_frameData2w.dat 
monsoon_ma_frameData3.dat 
monsoon_ma_frameData5.dat 
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glacial_ua_frameData1.dat 
glacial_ua_frameData2e.dat 
glacial_ua_frameData2w.dat 
glacial_ua_frameData3.dat 
glacial_ua_frameData5.dat 
modern_ua_frameData1.dat 
modern_ua_frameData2e.dat 
modern_ua_frameData2w.dat 
modern_ua_frameData3.dat 
modern_ua_frameData5.dat 
monsoon_ua_frameData1.dat 
monsoon_ua_frameData2e.dat 
monsoon_ua_frameData2w.dat 
monsoon_ua_frameData3.dat 
monsoon_ua_frameData5.dat 
Note: These files contain the PTn-to-TSw percolation flux values falling 
within a given repository panel footprint and average value for that 
repository panel. 
3. Calculate panel averages for panels 1 and 2w 
Panels 1 and 2W are grouped for the purpose of computing the LDTH submodel 
percolation fluxes. This is an area-weighted average, using the respective areas of 
Panels 1 and 2W. 
4. Calculate average percolation of all LDTH submodels falling within a repository 
panel 
A weighted average of the percolation flux values (Substep 2) for all LDTH submodel 
locations that fall inside of a particular panel footprint is calculated. The weighting 
factors, found in DTN: LL030808723122.037 (Microsoft Excel spreadsheets: scaled 
chimney percolation (base PTn)_la.xls, scaled chimney percolation (base 
PTn)_ma.xls, and scaled chimney percolation (base PTn)_ua.xls), are determined by 
the following simple process. First, each of the SMT gridblocks in a given Panel is 
assigned to the closest LDTH submodel location. The weighting factors are equal to 
the number of SMT gridblocks assigned to a given LDTH submodel location divided 
by the total number of SMT gridblocks in that panel. 
5. Determine the scaled LDTH submodel percolation flux values from the raw 
LDTH submodel chimney percolation flux values 
The raw LDTH submodel (chimney-submodel) percolation values determined in 
Step 8, Substep 1 above are scaled so that the average scaled percolation flux of all 
LDTH submodels falling within a given repository panel is the same as the average 
percolation flux for that panel determined in Step 8, Substep 2 above. First, a simple 
arithmetic average of the raw LDTH submodel percolation flux values is calculated 
for a given repository panel. Then a scaling factor is computed for that panel, which is 
ANL-EBS-MD-000049 REV 02 I-8 October 2004 

Multiscale Thermohydrologic Model 
equal to the average percolation flux for that panel (determined in Step 8, Substep 2 
above) divided by the average raw percolation flux of all LDTH submodels 
(determined in Step 8, Substep 4) within that panel. Finally, for each of the LDTH 
submodels within a repository panel, the raw percolation flux values are multiplied 
by the scaling factor for that panel to obtain the scaled percolation flux values for each 
of the LDTH submodels. This process is repeated for each repository panel, for each 
of the three climate states and for each of the three infiltration flux cases. These 
calculations are performed using Microsoft Excel spreadsheets in 
DTN: LL030808723122.037: 
scaled chimney percolation (base PTn)_la.xls 
scaled chimney percolation (base PTn)_ma.xls 
scaled chimney percolation (base PTn)_ua.xls 
6. Create scaled SMT submodel repository-gridblock percolation-flux values 
Once the scaled percolation flux values have been calculated for each of the LDTH 
submodel locations, the corresponding percolation flux values for each of the SMT 
submodel gridblock locations can be calculated by interpolating the percolation fluxes 
between each of the LDTH submodel locations. Note that each of the LDTH/SDT 
submodel locations lies at the centers of SMT submodel repository gridblocks (see 
Figure 6.2-3). The LDTH and SDT submodel pairs are more or less equally spaced 
along drifts in the SMT submodel, and are always located at the ends of the 
emplacement drifts, and typically at one or two other locations along the central 
portion of the drift. Also, LDTH and SDT submodel pairs are typically located along 
every fourth drift. It is important to note that the gridblocks representing the 
emplacement drifts in the SMT submodel are regularly spaced, with 20-m gridblock 
spacing along each drift and each drift being represented by a gridblock row that is 81m 
wide (which represents the drift spacing). Thus, intermediate locations along a drift 
(between LDTH/SDT submodel locations) can be linearly interpolated simply on the 
basis of the number of gridblocks separating that particular location from the pair of 
LDTH/SDT submodel locations that straddle it, and upon which the simple linear 
interpolation is based. Once the drifts that contain LDTH and SDT submodel pairs 
have been filled in with interpolated values, the drifts lying between these interpolated 
drifts can also be interpolated as well. The interpolation methodology interpolates 
linearly between drifts (north/south) such that the previously interpolated SMT 
submodel gridblock pairs are the same distance from the ventilation inlet as the target 
SMT submodel gridblock location. Again, because of the uniform gridblock spacing, 
the interpolation process is simply based upon the number of drifts between the drift 
for which the interpolation is being conducted and the previously interpolated 
emplacement drifts (which contain the LDTH-SDT submodel locations) that straddle 
the target drift. 
Step 9 -Determine the identity of the world column (from the three-dimensional site-scale UZ 
flow model) for each LDTH-SDT submodel pair. 
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The .col files created in Step 4 include the name of the world column into which an 
LDTH/SDT submodel pair falls. These world column names are recorded from the .col files 
for the LDTH and SDT submodels. 
Step 10 - Compute SMT, SDT, and LDTH submodel boundary conditions. 
The software code boundary_conditions v1.0 generates upper and lower boundary conditions for 
the LDTH, SMT, and SDT submodels of the MSTHM. The boundary conditions are derived 
from the three-dimensional site-scale UZ flow model. Data are extracted from the 
three-dimensional site-scale UZ flow model grid (DTN: LB03023DKMGRID.001 [DIRS 
162354]) and from a file (DTN: LB991201233129.001 [DIRS 146894]) containing boundary 
conditions at the ground surface and at an elevation of 730 m, which was the location of the 
(horizontal) water table in the three-dimensional site-scale UZ flow model grid used in the 
TSPA-SR (DTN: LB990701233129.001 [DIRS 106785]). Interpolation is used to determine 
the boundary conditions at the sloping water table in the three-dimensional site-scale UZ flow 
model. The software code boundary_conditions v1.0 reads input files containing the following 
information, respectively: (1) the SMT submodel grid, (2) the UZ model grid (File: 
MESH_rep.VF of DTN: LB991201233129.001 [DIRS 146894]) and (3) the initial conditions 
(File: INCON_thm_s32.dat of DTN: LB991201233129.001 [DIRS 146894]) from Mountain-
Scale Coupled Processes (TH/THC/THM) Models (BSC 2004 [DIRS 169866]), (4) the grid 
centers and ground-surface and water-table elevations of the World Columns in the three-
dimensional site-scale UZ flow model, (5) coordinates of the LDTH/SDT submodel locations, 
and (6) the values of wet thermal conductivity of the UZ model layers. Boundary conditions are 
generated at all World Columns (from the three-dimensional site-scale UZ flow model) and at all 
LDTH/SDT submodel locations. For the LDTH submodels, boundary_conditions v1.0 generates 
a table of boundary conditions at the ground surface, including temperature, gas-phase pressure, 
air mass fraction, and specific enthalpy of water at the ground-surface conditions in NUFT-input 
format. Also generated for LDTH submodels are boundary conditions at the water table, 
including temperature and gas-phase pressure in NUFT-input format. For the SMT and SDT 
submodels, boundary_conditions v1.0 generates ground-surface and water table temperatures in 
NUFT-input format. See Appendix II for details on the SMT submodel boundary condition 
construction. 
Note that since the boundary conditions were determined for the SMT, SDT, and LDTH 
submodels, a new source of boundary condition has been made available from the Mountain-
Scale Coupled Processes (TH/THC/THM) Models (BSC 2004 [DIRS 169866]). The temperature 
and gas-phase-pressure boundary conditions can be extracted from the INCON block of file: 
th_v16.dat of DTN: LB0310MTSCLTH3.001 [DIRS 170270]. Compared to the use of file: 
INCON_thm_s32.dat of DTN: LB991201233129.001 [DIRS 146894], these updated boundary 
conditions result in negligible differences in temperatures and gas-phase pressures at both the 
upper boundary (the ground surface) and the lower boundary (the water table). Table I-1 gives 
the repository-wide averaged temperature at the upper and lower boundaries for the mountain-
scale TH model from Mountain-Scale Coupled Processes (TH/THC/THM) Models (BSC 2004 
[DIRS 169866]) and for the MSTHM. Table I-2 gives the corresponding repository-wide 
averaged gas-phase pressure at the upper and lower boundaries for the respective models. 
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Multiscale Thermohydrologic Model 
Table I-1. Repository-Wide Averaged Temperature at the Upper and Lower Boundaries of the Mountain-
Scale TH Model and the MSTHM 
Temperature (C) 
Mountain-Scale TH 
Modela 
MSTHMb Mean Difference Root Mean Squared 
Error 
Upper Boundary 17.098 17.061 -0.037 0.170 
Lower Boundary 30.097 30.117 0.021 0.157 
a 
Mountain Scale TH values based on DTN: LB0310MTSCLTH3.001 [DIRS 170270], INCON block of file: 
th_v16.dat. 
b MSTHM based on DTN: LB991201233129.001 [DIRS 146894], file INCON_thm_s32.dat. 
NOTE: Repository-wide temperature and gas-phase pressures are determined for the heated repository footprint, 
plus the contingency area in the southern portion of Panel 2 (previously called Panel 5 in Figure 6.2.3). 
Table I-2. Repository-Wide Averaged Gas-Phase Pressure at the Upper and Lower Boundaries of the 
Mountain-Scale TH Model and the MSTHM 
Gas-Phase Pressure (Pa) 
Mountain-Scale TH 
Modela 
MSTHMb Mean Difference Root Mean Squared 
Error 
Upper Boundary 85,787 85,782 -5 172 
Lower Boundary 91,810 91,805 -5 18 
a 
Mountain Scale TH values based on DTN: LB0310MTSCLTH3.001 [DIRS 170270], INCON block of file: 
th_v16.dat. 
b MSTHM based on DTN: LB991201233129.001 [DIRS 146894], file INCON_thm_s32.dat. 
NOTE: Repository-wide temperature and gas-phase pressures are determined for the heated repository footprint, 
plus the contingency area in the southern portion of Panel 2 (previously called Panel 5 in Figure 6.2.3). 
Tables I-1 and I-2 also give the root mean square error in temperature and gas-phase pressure 
boundary conditions between the Mountain-Scale TH and the MSTHM. The differences 
between the two models are negligible. Therefore, obtaining the boundary conditions from 
DTN: LB991201233129.001 [DIRS 146894], file INCON_thm_s32.dat is reasonable and 
appropriate. 
Step 11 - Compute SMT, SDT, LDTH and DDT submodel heat-generation curves. 
Using a reference heat-generation-versus-time table, as well as a table of 
ventilation-heat-removal-efficiency as a function of time and distance from the ventilation inlet, 
heatgen_ventTable_emplace v1.0 produces files of heat-generation-versus-time tables in NUFTheatgen 
format. These heat-generation files have the influence of reduced heat-generation rates 
during the 50-year ventilation preclosure period and full-power heating during the 
postventilation postclosure period. See Appendix III for details on building the heat generation 
curves. See Appendix V for the assembly of NUFT input files. 
Step 12 - Compile natural- and engineered-system properties. 
Using several DTNs containing material-property values of the natural system and several 
Information Exchange Drawings containing material-property values of the engineered system, 
material-property files (called NUFT rocktab files) are constructed. These files are in the NUFT 
rocktab format; these files are read in as include file in the SMT, SDT, LDTH and DDT 
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Multiscale Thermohydrologic Model 
submodel NUFT input files. See Appendix IV for details on assembling the rocktab files that 
contain the material property values for the respective submodels. 
Step 13 - Compute effective thermal conductivity. 
Effective Thermal Conductivity 
To account for heat transfer by natural convection in the emplacement drift, correlations have 
been developed (Francis et al. 2003 [DIRS 164602], Table 6) for the relationship between drift 
wall, waste package, and drift air temperatures and an effective thermal conductivity Keff of the 
air in the emplacement drift cavity that represents the influence of heat transfer by natural 
convection. This process is conducted for the cavity between the drip shield and drift wall in the 
LDTH submodels and DDT submodels. This process is also conducted for the cavity between 
the waste package and drip shield in the DDT submodels. 
It should be noted that the correlations for the in-drift effective thermal conductivity, which were 
obtained from Table 6 of Francis et al (2003 [DIRS 164602]), have been updated in In-Drift 
Natural Convection and Condensation (BSC 2004 [DIRS 164327], Table 6.4.7-3), resulting in 
very small changes to the coefficients. The small changes to the coefficients in the correlations 
are negligible, as shown in Figure I-1 for the effective thermal conductivity between the drip 
shield and drift wall at an average fluid temperature of 95C. 
35.0 
30.0 
25.0 
20.0 
15.0 
10.0 
5.0 
0.0 
liFrancis et a. 2003 
In-Drift Convecton and 
Condensation Model 
0.0 5.0 10.0 15.0 20.0 25.0 30.0 
Temperature Difference (oC) 
NOTE: The in-drift effective thermal conductivity between the drip shield and drift wall as a function of the 
temperature difference between those surfaces is plotted from the correlation in Table 6 of Francis et al. 
(2003 [DIRS 164602]) and in Table 6.4.7-3 of In-Drift Natural Convection and Condensation (BSC 2004 
[DIRS 164327]). 
Figure I-1. Plot of In-Drift Effective Thermal Conductivity Between the Drip Shield and Drift Wall as a 
Function of Temperature Difference 
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Multiscale Thermohydrologic Model 
The effective thermal conductivity Keff is determined by running a NUFT submodel (either 
LDTH or DDT) starting with an initial guess for Keff for the gas-filled cavities in the drift. The 
appropriate formula from Table 6 of CFD Modeling of Natural Convection Heat Transfer and 
Fluid Flow in Yucca Mountain Project (YMP) Enclosures (Francis et al. 2003 [DIRS 164602]) 
is used to compute Keff in the gas-filled cavities and the NUFT submodel is rerun with the new 
value of Keff. Each time a new NUFT-submodel run is completed, the value of Keff is computed 
and compared with the previous iteration. After the value of Keff has converged (between 
successive iterations), the iterative process is completed. The effective thermal conductivity Keff 
is a time-varying parameter and the formula in Table 6 of Frances et al. (2003 [DIRS 164602]) 
involves computing temperatures averaged over the gridblocks representing the gas-filled 
cavities in the emplacement drift. To carry out this iterative process, extractBlocks_EXT v1.0 is 
used. This software code takes a list of gridblocks, extracts the required information from the 
NUFT-submodel output, applies the appropriate formula from Table 6 of Frances et al. (2003 
[DIRS 164602]), and produces a time history of calculated Keff. 
software code: 
extractBlocks_EXT v1.0 
inputs: 
The name of an input file that defines how to apply the formula from Table 6 of Frances et 
al. (2003 [DIRS 164602]) (DTN: LL030808723122.037) 
DDT_Keff_postclose_inside_0_wp1
DDT_Keff_postclose_inside_0_wp2
DDT_Keff_postclose_inside_0_wp3
DDT_Keff_postclose_inside_0_wp4
DDT_Keff_postclose_inside_0_wp5
DDT_Keff_postclose_inside_0_wp6
DDT_Keff_postclose_inside_0_wp7
DDT_Keff_postclose_inside_0_wp8
DDT_Keff_preclose_0_wp1
DDT_Keff_preclose_0_wp2
DDT_Keff_preclose_0_wp3
DDT_Keff_preclose_0_wp4
DDT_Keff_preclose_0_wp5
DDT_Keff_preclose_0_wp6
DDT_Keff_preclose_0_wp7
DDT_Keff_preclose_0_wp8 
outputs: 
A file with a time history of Keff calculated from the NUFT input 
(DTN: LL030808723122.037) 
DDT_Keff_postclose_inside_0_wp1.out
DDT_Keff_postclose_inside_0_wp2.out
DDT_Keff_postclose_inside_0_wp3.out
DDT_Keff_postclose_inside_0_wp4.out
DDT_Keff_postclose_inside_0_wp5.out
DDT_Keff_postclose_inside_0_wp6.out
DDT_Keff_postclose_inside_0_wp7.out
DDT_Keff_postclose_inside_0_wp8.out
DDT_Keff_preclose_0_wp1.out
DDT_Keff_preclose_0_wp2.out 
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DDT_Keff_preclose_0_wp3.out
DDT_Keff_preclose_0_wp4.out
DDT_Keff_preclose_0_wp5.out
DDT_Keff_preclose_0_wp6.out
DDT_Keff_preclose_0_wp7.out
DDT_Keff_preclose_0_wp8.out 
Step 14 - Create SMT submodel mesh. 
To create the SMT submodel mesh used for the MSTHM calculations in this report, one must 
carefully perform the following steps. Note that one must be using the qualified version of 
YMESH v1.54 and Solaris OS 5.8 UNIX operating system. 
a. Execute YMESH v1.54 
ymesh 
b. Pull down File tab on YMESH v1.54 to and Open the data file. In the Select Input File 
popup highlight the file LBL2003-LA-YMESH-expand_qualified (from 
NUFT-submodel Building Step 2) and click OK 
c. Pull down Edit tab and highlight Extend World Columns. Make certain the Above tab is 
active. Enter the following: 
Material atm 
Thickness 200. 
click OK button 
d. Remain in the Extended World Columns but now make the Below tab active. Enter the 
following: 
Material sz1 
Thickness 30. 
click OK button 
Material sz2 
Thickness 60. 
click OK button 
Material sz3 
Thickness 70. 
click OK button 
Material sz4 
Thickness 120. 
click OK button 
Material sz5 
Thickness 240. 
click OK button 
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Multiscale Thermohydrologic Model 
Material sz6 
Thickness 480. 
click OK button 
Material bsmnt 
Thickness 0.1 
click OK button 
e. Click CLOSE button on Extend World Columns popup 
f. Open File pulldown from YMESH v1.54 menu and select Open data file 
g. In the Select Input File popup, select file tspa03.grid03-150w and click OK button 
h. Highlight Options pulldown from YMESH v1.54 menu and select Trim Top Boundary 
i. In Ending Conditions popup menu, enter the following: 
Material atm 
Thickness 0.1 
click Apply button 
click Close button 
j. Highlight Edit pulldown from YMESH v1.54 menu and select Element Names 
k. In Rename Elements popup window, follow these steps: 
i. Select Material button and enter 
Prefix atm 
Material atm 
Click Apply button 
Prefix bsm 
Material bsmnt 
Click Apply button 
ii. Select PrefixIndexFile button 
In the PrefixIndexRangeFile space enter 
heatBlockIndicesPanel1_2e_2w_3_5.data 
Click Apply button 
Click Close button 
l. Highlight the File pulldown menu and select Save data file 
In the Save File popup window type the Selection space enter tspa03.mesh03-150w 
Click OK button 
(Note that this saves the mesh) 
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m. Return to a UNIX command prompt and type the following UNIX commands 
rm P1-UB_list P2E-UB_list P2W-UB_list P3-UB_listP5-UB_list
grep P1 tspa03.mesh03-150w > P1-UB_list 
grep P2E tspa03.mesh03-150w > P2E-UB_list 
grep P2W tspa03.mesh03-150w > P2W-UB_list 
grep P3 tspa03.mesh03-150w > P3-UB_list 
grep P5 tspa03.mesh03-150w > P5-UB_list 
n. Using a text editor, open the five files just created: P1-UB_list, P2E-UB_list, P2W-
UB_list, P3-UB_list, and P5-UB_list (DTN: LL030808823122.038) 
o. Edit the five files by removing all gridblock connections information (which is the last 70 
percent of the file), saving only the element information (which is the first 30 percent of 
the file) 
p. Save the five files with the above names 
Note that any mistake made by the user in executing the YMESH v1.54 steps forces the user to 
return to the beginning and redo the YMESH v1.54 steps. 
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APPENDIX II 
BUILDING BOUNDARY CONDITIONS FOR SUBMODELS 
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The software code boundary_conditions v1.0 generates upper and lower boundary conditions for 
the LDTH, SMT, and SDT submodels (see Step 10 of Appendix I). The boundary conditions are 
derived from Mountain-Scale Coupled Processes (TH/THC/THM) Models (BSC 2004 [DIRS 
169866]) (DTN: LB991201233129.001 [DIRS 146894]). Data are extracted from the three-
dimensional site-scale UZ flow model grid being used in the TSPA-LA 
(DTN: LB03023DKMGRID.001 [DIRS 162354]), as well as from Mountain-Scale Coupled 
Processes (TH/THC/THM) Models (BSC 2004 [DIRS 169866]), including the boundary 
conditions (file INCON_thm_s32.dat in DTN: LB991201233129.001 [DIRS 146894]) and the 
corresponding three-dimensional mountain-scale grid (file MESH_rep.VF in 
DTN: LB991201233129.001 [DIRS 146894]). It should be noted that the three-dimensional 
mountain-scale grid used in Mountain-Scale Coupled Processes (TH/THC/THM) Models (BSC 
2004 [DIRS 169866]) has a horizontal water table at an elevation of 730 m, while the three-
dimensional site-scale UZ flow model grid used in the TSPA-LA 
(DTN: LB03023DKMGRID.001 [DIRS 162354]) has a sloping water table. The software code 
boundary_conditions v1.0 uses linear interpolation to determine the water-table boundary 
conditions at the sloping water-table surface in the three-dimensional site-scale UZ flow model 
grid used in the TSPA-LA (DTN: LB03023DKMGRID.001 [DIRS 162354]). The software 
code boundary_conditions v1.0 reads input files containing the following information, 
respectively: (1) the SMT submodel grid, (2) the UZ model grid and (3) initial conditions from 
Mountain-Scale Coupled Processes (TH/THC/THM) Models (BSC 2004 [DIRS 169866]), (4) 
the grid centers and ground-surface and water-table elevations of the World Columns in the 
three-dimensional site-scale UZ flow model, (5) coordinates of the LDTH/SDT submodel 
locations, and (6) the values of wet thermal conductivity of the UZ model layers. 
For item (4) above, colCen v1.0 is used to determine the grid centers for all World Columns in 
the three-dimensional site-scale UZ flow model. 
Boundary conditions are generated by boundary_conditions v1.0 at all World Columns (from the 
three-dimensional site-scale UZ flow model) and at all LDTH/SDT submodel locations. For the 
LDTH submodels, boundary_conditions v1.0 generates a table of boundary conditions at the 
ground surface, including temperature, gas-phase pressure, air mass fraction, and specific 
enthalpy of water at the ground-surface conditions in NUFT-input format. Also generated for 
LDTH submodels are boundary conditions at the water table, including temperature and gas-
phase pressure in NUFT-input format. For the SMT and SDT submodels, boundary_conditions 
generates ground-surface and water-table temperatures in NUFT-input format. 
Prior to determining the boundary conditions, Steps 1 and 2 of Appendix I, which result in an 
expanded three-dimensional mountain-scale mesh (called the expanded World Grid for YMESH 
v1.54), must be executed. This expanded three-dimensional mountain-scale mesh (also called 
the expanded World Grid) is used as an input to boundary_conditions v1.0, which subsequently 
outputs all of the boundary condition files to be used for all of the submodels (see Appendix V 
for the assembly of NUFT input files). 
Create boundary condition files for all submodels. 
The software code boundary_conditions v1.0 was used to create the boundary conditions for all 
submodels. 
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software code: 
boundary_conditions 
input files (DTN: LL030808723122.037) 
smtMesh (SMT submodel mesh file in NUFT meshfile input format) 
MESH_rep.VF of DTN: LB991201233129.001 [DIRS 146894] (Mesh file for 
Mountain-Scale Coupled Processes (TH/THC/THM) Models (BSC 2004 [DIRS 
169866])) 
INCON_thm_s32.dat of DTN: LB991201233129.001 (Initial conditions for 
Mountain-Scale Coupled Processes (TH/THC/THM) Models (BSC 2004 [DIRS 
169866])) 
grid_column_centers (Ground-surface and water-table elevations and coordinates 
of World Columns of the three-dimensional site-scale UZ flow model grid, 
which is the LBL2002-YMESH Expanded World Grid; this information is 
generated as output from colCen v1.0see above) 
chimneyLocation (For each LDTH-SDT submodel pair this file locates the 
corresponding World Column in the LBL2002-YMESH Expanded World Grid) 
tcond.dat (Thermal conductivity of UZ model layers) 
output files (DTN: LL030808723122.037) 
chimSurfBC.out (LDTH submodel surface boundary conditions: temperature, gas 
pressure, air mass fraction in gas phase, and specific enthalpy of water) 
chimLowerBC.out (LDTH submodel water table boundary conditions: 
temperature and gas pressure) 
smtUpperBC.out (Surface boundary temperature for SMT submodel in NUFT 
input format) 
smtLowerBC.out (Lower boundary temperature for SMT submodel in NUFT 
input format) 
worldColBC.out (LDTH/SDT submodel-type boundary conditions for all World 
Columns in the LBL2002-YMESH Expanded World Grid) 
smtWorldBC (Summary of SMT submodel boundary conditions for columns in 
the LBL2002-YMESH Expanded World Grid) 
execution process 
To start, type: 
boundary_conditions 
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Enter output file extension: 
out
Enter thermal cond. of material below water table, SMT submodel: 
1.2 
Enter value of added thickness below water table, SMT submodel: 
1000 
Enter name of SMT submodel mesh file: 
Hit return with no entry to use default file, smtMesh 
SMTMESHTEST 
Enter name of the Mountain-Scale Coupled Process (TH/THC/THM) 
Models (BSC 2004 [DIRS 169866]) mesh file: 
Hit return with no entry to use default file, MESH_rep.VF 
MESH_rep.VF 
Enter name of the Mountain-Scale Coupled Process (TH/THC/THM) 
Models (BSC 2004 [DIRS 169866]) file with init.cond.: 
Hit return with no entry to use default file, INCON_thm_s32.dat 
INCON_thm_s32.dat 
Enter name of file with World Column data from the 3-D site-scale UZ 
flow model: 
Hit return with no entry to use default file, grid_column_centers 
GRID_COLUMN_CENTERS 
Enter name of file with LDTH-/SDT submodel chimney locations: 
Hit return with no entry to use default file, chimneyLocation 
CHIMNEYLOCATION 
Enter name of file with thermal cond. data: 
Hit return with no entry to use default file, tcond.dat 
TCOND.DAT
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INTENTIONALLY LEFT BLANK 
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APPENDIX III 
HEAT GENERATION FOR SUBMODELS 
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To produce the heat generation for the SMT, SDT, DDT, and LDTH submodels (Step 11 in 
Appendix I) the following instructions must be followed. The software code 
heatgen_ventTable_emplace v1.0 is used for this purpose. 
The software code heatgen_ventTable_emplace v1.0 is used to incorporate the influence of 
ventilation heat-removal efficiency on the net heat generation available for heating the host rock. 
This is accomplished using a net-available-heat-generation fraction (Table III-1), which is equal 
to 1 minus the heat-removal-efficiency fraction, and which is given as a function of time and 
distance from the ventilation inlet. This code requires a control file that provides names of the 
locations (within the repository) at which heat generation files should be created along with the 
distance of that location from the ventilation inlet. The output of heatgen_ventTable_emplace 
v1.0 is a series of files of heat-generation-rate-versus-time tables that account for the heat-
removal efficiency of forced-convection ventilation of the emplacement drifts during the 
preclosure period. The output files from heatgen_ventTable_emplace v1.0 are in NUFT heatgen 
format. 
Table III-1. Net Available Heat-Generation Fraction as a Function of Time and Distance from the 
Ventilation Inlet Used in this Report 
Time Distance from Ventilation Inlet (m) 
(yr) 0 1 10 100 200 300 400 500 600 700 800 
0.000001 1 1 1 1 1 1 1 1 1 1 1 
0.00001 0.146308 0.142676 0.142563 0.140993 0.140799 0.140799 0.140799 0.140799 0.140799 0.140799 0.140799 
0.0001 0.217303 0.216986 0.227705 0.228043 0.227014 0.226996 0.226996 0.226996 0.226996 0.226996 0.226996 
0.001 0.476088 0.473018 0.481063 0.53203 0.523485 0.52025 0.520202 0.520168 0.520168 0.520168 0.520168 
0.002 0.292264 0.316736 0.339064 0.639182 0.629461 0.623959 0.623759 0.623744 0.623744 0.623744 0.623744 
0.005 0.280038 0.285626 0.299503 0.623057 0.63828 0.632743 0.625883 0.625394 0.625413 0.625413 0.625413 
0.01 0.193758 0.208711 0.222313 0.342672 0.618228 0.62856 0.609709 0.607226 0.607041 0.607041 0.607041 
0.02 0.13269 0.147196 0.158759 0.269033 0.281053 0.620632 0.614217 0.601249 0.599502 0.599277 0.599301 
0.05 0.098427 0.107858 0.117531 0.207132 0.270728 0.592514 0.600299 0.609218 0.624081 0.640142 0.621325 
0.1 0.081837 0.090038 0.098317 0.179413 0.242904 0.301132 0.38071 0.447719 0.48086 0.561239 0.641619 
0.167 0.071587 0.07973 0.087446 0.161575 0.219363 0.276089 0.328697 0.372876 0.398714 0.457227 0.51574 
0.5 0.054689 0.061099 0.067563 0.12848 0.173734 0.216918 0.259313 0.300316 0.333768 0.364466 0.395163 
1 0.046744 0.051877 0.057946 0.111957 0.152629 0.191916 0.230384 0.269126 0.306335 0.340477 0.372663 
2 0.040779 0.043124 0.048668 0.098252 0.133631 0.168209 0.203015 0.237214 0.27068 0.30221 0.333407 
5 0.034946 0.028339 0.034312 0.07884 0.109622 0.139492 0.170165 0.20001 0.229961 0.257114 0.285117 
7 0.034075 0.032974 0.039111 0.07985 0.107428 0.135075 0.163945 0.191241 0.218936 0.245204 0.271005 
10 0.031507 0.027718 0.034033 0.072152 0.098795 0.124889 0.151777 0.178159 0.204479 0.229816 0.253769 
20 0.027692 0 0.008322 0.04327 0.068591 0.093648 0.117834 0.142747 0.166506 0.191557 0.213319 
30 0.026128 0.001645 0.010748 0.038894 0.060805 0.083288 0.103578 0.125227 0.145393 0.166498 0.186734 
50 0.021768 0 0 0.008813 0.026882 0.044891 0.064152 0.080771 0.099534 0.11707 0.134762 
SOURCE: These values are equal to 1 minus the heat-removal-efficiency fraction, which is given in DTN: 
MO0304MWDALACV.000 [DIRS 164551], FILE: ANSYS-LA-coarse.xls, Efficiency Data Worksheet. 
ANL-EBS-MD-000049 REV 02 III-1 October 2004 

Multiscale Thermohydrologic Model 
It is important to note that the source of the heat-removal efficiency versus time and distance 
table (DTN: MO0304MWDALACV.000 [DIRS 164551], FILE: ANSYS-LA-coarse.xls, 
Efficiency Data Worksheet) was superseded by DTN: MO0306MWDASLCV.001 [DIRS 
165695], FILE: ANSYS-LA-coarse.xls, Efficiency Data Worksheet. Table III-2 gives the net 
available heat-generation fraction as a function of time and distance from the ventilation inlet, 
which is obtained from DTN: MO0306MWDASLCV.001 [DIRS 165695]. Appendix XIV 
documents the qualification of DTN: MO0304MWDALACV.000 for use in the MSTHM 
calculations reported in Section 6.3. 
Table III-2. Net Available Heat-Generation Fraction as a Function of Time and Distance from the 
Ventilation Inlet from Updated Data Source 
Time Distance from Ventilation Inlet (m) 
(yr) 0 1 10 100 200 300 400 500 600 700 800 
0.000001 1 1 1 1 1 1 1 1 1 1 1 
0.00001 0.135066 0.135098 0.134942 0.133348 0.133147 0.133147 0.133147 0.133147 0.133147 0.133147 0.133147 
0.0001 0.214621 0.215113 0.225830 0.219550 0.218889 0.218889 0.218889 0.218889 0.218889 0.218889 0.218889 
0.001 0.478338 0.475022 0.483168 0.524651 0.511303 0.509651 0.509610 0.509610 0.509610 0.509610 0.509610 
0.002 0.357323 0.341228 0.359332 0.637949 0.615778 0.613866 0.613771 0.613771 0.613771 0.613771 0.613771 
0.005 0.295914 0.298644 0.311384 0.626357 0.638665 0.618744 0.617352 0.617309 0.617309 0.617309 0.617309 
0.01 0.211570 0.220611 0.234199 0.344166 0.623465 0.608533 0.600455 0.599997 0.599962 0.599927 0.599927 
0.02 0.148423 0.156541 0.167830 0.277095 0.588253 0.597282 0.616473 0.596000 0.592972 0.592701 0.592664 
0.05 0.111385 0.113755 0.123993 0.213644 0.274106 0.347422 0.619900 0.623108 0.623445 0.612159 0.609106 
0.1 0.093342 0.094252 0.103040 0.184760 0.248296 0.300246 0.305689 0.627862 0.637413 0.647127 0.656842 
0.167 0.082390 0.083169 0.090779 0.165763 0.224567 0.282320 0.334485 0.365615 0.431550 0.553138 0.674726 
0.5 0.064291 0.063075 0.069602 0.130512 0.175606 0.219324 0.262088 0.302489 0.331269 0.309213 0.287158 
1 0.055766 0.053096 0.059301 0.113254 0.153850 0.192711 0.231531 0.269038 0.306778 0.340002 0.371565 
2 0.049463 0.043804 0.050139 0.098439 0.133850 0.167701 0.201723 0.235521 0.269083 0.300283 0.331118 
5 0.043663 0.028618 0.035436 0.078572 0.108016 0.138321 0.167566 0.197426 0.225970 0.252974 0.280183 
7 0.042880 0.033521 0.038796 0.078778 0.105996 0.133101 0.160787 0.188093 0.214863 0.240398 0.265608 
10 0.040675 0.028033 0.034276 0.071455 0.097638 0.123108 0.149386 0.174865 0.199773 0.224872 0.248124 
20 0.038559 -0.001342 0.009525 0.042960 0.067913 0.092815 0.116884 0.140830 0.164491 0.187746 0.209693 
30 0.038599 0.003452 0.011231 0.040311 0.062029 0.083344 0.104132 0.125229 0.145945 0.166299 0.186499 
50 0.037744 -0.022832 -0.011204 0.010284 0.029428 0.048125 0.067176 0.085635 0.103205 0.120745 0.139413 
SOURCE: These values are equal to 1 minus the heat-removal-efficiency fraction, which is given in DTN: 
MO0306MWDASLCV.001 [DIRS 165695], FILE: ANSYS LA- Base Case.xls, Efficiency Data Worksheet. 
ANL-EBS-MD-000049 REV 02 III-2 October 2004 

Multiscale Thermohydrologic Model 
Creating Heat Generation Curves for the SDT and LDTH submodels 
software code 
heatgen_ventTable_emplace v1.0 
inputs: (DTN: LL030808723122.037) 
SDT: string indicating to the software code that this is an SDT/LDTH submodel heatgen 
file 
multi-package_7WP_Segment_Info_SDT_LDTH_TSPA03: default SDT/LDTH 
submodel heat-generation table with nominal loading and no ventilation 
LA_ventilation_table_50yr.rfm: ventilation table with ventilation efficiency as a function 
of time and distance from the ventilation inlet. 
ventilation_time.reform: file giving the name and distance from the ventilation inlet 
for each LDTH-/SDT submodel chimney location. 
outputs: (heatgen file) (DTN: LL030808723122.037) 
P*_LDTH-SDT output heatgen file for each LDTH-/SDT submodel chimney location 
Creating Heat Generation Curves for the DDT submodels 
software code 
heatgen_ventTable_emplace 
inputs: (DTN: LL030808723122.037) 
DDT: string indicating to the software code that this is a DDT heatgen file 
DDT_TSPA03: default DDT heat generation table with nominal loading and no 
ventilation 
LA_ventilation_table_50yr.rfm: ventilation table with ventilation efficiency as a function 
of time and distance from the ventilation inlet. 
ventilation_time.reform: file giving the name and distance from the ventilation inlet 
for each LDTH-/SDTsubmodel chimney location. 
outputs: (heatgen file) (DTN: LL030808723122.037) 
P*_DDT output heatgen file for each LDTH-/SDT-submodel chimney location 
Creating Heat Generation Curves for the SMT submodel 
software code 
heatgen_ventTable_emplace 
inputs: (DTN: LL030808723122.037) 
SMT: string indicating to the software code that this is an SMT submodel heatgen file 
SMT_TSPA03: default SMT submodel heat-generation-versus-time table with 
nominal loading and no ventilation 
LA_ventilation_table_50yr.rfm: ventilation table with ventilation efficiency as a function 
of time and distance from the ventilation inlet. 
ANL-EBS-MD-000049 REV 02 III-3 October 2004 

Multiscale Thermohydrologic Model 
ventilation_time.rfm: file giving the name and distance from the ventilation inlet for 
each LDTH-/SDT submodel chimney location. 
outputs: (heatgen file) (DTN: LL030808723122.037) 
SMT_TSPA03_P* output heatgen file for each SMT submodel location 
The heatgen files are then used as inputs to the NUFT input files; see Appendix V for details on 
the assembly of NUFT input files. 
ANL-EBS-MD-000049 REV 02 III-4 October 2004 

Multiscale Thermohydrologic Model 
APPENDIX IV 
BUILDING SUBMODEL MATERIAL PROPERTY FILES 
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Multiscale Thermohydrologic Model 
LDTH - Submodel DKM Properties 
Hydrologic properties from DTN: LB0208UZDSCPMI.002 [DIRS 161243] are used for all 
three infiltration flux cases (Table IV-4), which are documented in Sections 6.3.1, 6.3.2, 6.3.3. 
Hydrologic properties from DTN: LB0208UZDSCPLI.002 [DIRS 161788] (Table IV-5) and 
from DTN: LB0302UZDSCPUI.002 [DIRS 161787] (Table IV-6) are used for the sensitivity 
study to hydrologic-property uncertainty, which is discussed in Section 6.3.2.4. From each of 
the three Microsoft Excel spreadsheet files contained in the respective DTNs, the following 
parameters are obtained: permeability (matrix and fracture), porosity (matrix and fracture), van 
Genuchten properties (matrix and fracture) and residual saturation (matrix and fracture). 
The thermal properties are taken from files of the following sources: 
DTN: SN0303T0503102.008 [DIRS 162401], DTN: SN0307T0510902.003 [DIRS 164196], 
and Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc). Bulk 
thermal conductivity Kth (for both wet and dry conditions) and bulk density (average and 1 
standard deviation above and below) of the nonrepository GFM2000 layers are contained in 
DTN: SN0303T0503102.008 [DIRS 162401]. The bulk thermal conductivity (for both wet and 
dry conditions) and bulk density .b 
of the repository UZ model layers was obtained from Table 
7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc); these data include 
mean values as well as one standard deviation above and below the mean. The specific heat 
capacity of the mineralogical model layers is taken from DTN: SN0307T0510902.003 [DIRS 
164196]. The source input data for bulk density and bulk thermal-conductivity is summarized in 
Table IV-3a. 
The following parameters were calculated by hand using parameters obtained in the files listed 
above: (1) grain density, (2) matrix density and fracture density, (3) matrix and fracture contact 
length factors, and (4) thermal conductivity relations for matrix and fracture. Table IV-3b shows 
the results of calculating the density and thermal conductivity for the matrix and fracture 
continua. It should be noted that the vitric units have no fractures, but in order for the DKM to 
work, values must be assigned to a pseudo-fracture continuum for vitric units. This is 
accomplished by simply assigning matrix properties to the fracture continuum for the vitric units 
(tsw9v, ch1v, ch2v, ch3v, ch4v, ch5v, and ch6v). The specific details of the hand calculations 
are listed below. 
1. The grain density .g 
is calculated as: 
.= 
.b 
g 
1 -f
m 
where fm is matrix porosity and .b 
is bulk density. 
ANL-EBS-MD-000049 REV 02 IV-1 October 2004 

Multiscale Thermohydrologic Model 
2. The grain density .g 
is partitioned to the matrix and fracture continuum according to the 
fracture porosity, ff. The matrix and fracture densities, .g,m and .g,f, are calculated as: 
. =.(1-f )
,
gmg f 
.
gf =.f f
, g 
Because the vitric units do not have fractures, the grain density for the fracture and matrix 
continuum is calculated slightly differently. The matrix porosity is portioned 50 percent to 
the matrix continuum and 50 percent to the pseudo-fracture continuum. The bulk density 
is portioned 50 percent to the matrix continuum and 50 percent to the pseudo-fracture 
continuum. Thus, the grain densities for the fracture and matrix continuum are calculated 
as: 
.g,m= .g,f = .b 
.fm .
-1 2 . 
. 2 . 
. 
where fm is the total matrix porosity and .b 
is the total bulk density. Table IV-3b shows 
the result of this hand calculation for the vitric units. 
3. The matrix-contact-length factor is calculated as 1/(6N) where N is the fracture frequency 
from DTN: LB0205REVUZPRP.001 [DIRS 159525] (Table IV-7) and 6 accounts for the 
distance between the center of the matrix block and the fractures for Type #1 fractures as 
described in Development of Numerical Grids for UZ Flow and Transport Modeling (BSC 
2004 [DIRS 169855], Equation 6-4). The fracture-contact-length factor is always 0, which 
is obtained from Equation 6-3 of Development of Numerical Grids for UZ Flow and 
Transport Modeling (BSC 2004 [DIRS 169855], Section 6.7). The matrix-contact-length 
factor and the fracture-contact-length factor affect disequilibrium between the matrix and 
fracture continuum in the LDTH submodels. 
4. The thermal conductivity for the matrix Kth,m and fracture Kth,f (both dry and wet) are 
calculated as a function of fracture porosity ff 
for the given wet and dry bulk thermal 
conductivities Kth: 
dry dry 
K
th m = Kth (1 -f )
, f 
dry dry 
K
th f = Kth f 
, f 
wet wet 
K
th m = Kth (1 -f )
, f 
wet wet 
, 
K
th f = Kth ff 
These properties are written into a rocktab file (an example of which is listed at the bottom of 
this Appendix) for the NUFT input file (see Appendix V). All transport and partitioning 
parameters (e.g., Kd and KdFactor) are set to zero because sorption is not considered for any of the 
calculations of this report. 
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Multiscale Thermohydrologic Model 
The uncertainty of the wet and dry thermal conductivity values of the repository UZ model 
layers was addressed with values from DTN: SN0303T0503102.008 [DIRS 162401] and from 
Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc). 
Note that de Marsily (1986 [DIRS 100439], p. 233) gives a range from 0.1 for clays to 0.7 for 
sands. The value of 0.2 for the matrix continuum is used because the pore sizes for matrix are 
closer to that of clays than to that of sands. A value of 0.7 is assumed for the fracture. 
LDTH Submodel In-Drift, DKM Properties 
Invert Properties 
The invert properties for the matrix continuum (i.e., the intragranular porosity) are obtained from 
DTN: LB0208UZDSCPMI.002 [DIRS 161243] and for the fracture continuum (i.e., the 
intergranular porosity) are from Appendix X. Section 5.3.1.8 discusses the assumption about the 
intergranular permeability of the crushed-tuff invert material. The van Genuchten alpha for the 
fracture continuum from Table X-7 of Appendix X is 624 bar-1, which converted to SI units, is 
equal to 6.24  10-3 Pa-1. The input parameters that require hand calculations are: (1) 
intragranular porosity (fm), (2) the thermal conductivity for the fracture and matrix continuum, 
and (3) the grain density of the matrix and of the fracture continuum. The thermal properties of 
the crushed-tuff invert are given in Tables IV-8 and IV-9. 
Invert Porosity 
The matrix porosity or intergranular porosity of the crushed-tuff grains in the invert, fm, is taken 
from DTN: LB0208UZDSCPMI.002 [DIRS 161243] and is equal to 0.131, which is the matrix 
porosity of the Tptpll (tsw35) unit. The intergranular porosity of the crushed-tuff invert material 
is obtained from Table X-7 of Appendix X and is equal to 0.45. The porosity of the fracture 
continuum in the invert, ff, which is called the intergranular porosity, is a bulk quantity. 
Because the porosity of the matrix continuum in the invert, which is called the intragranular 
porosity, fg,m, is also a bulk quantity, the intragranular porosity of the crushed-tuff invert 
material is given by: 
fg,m = fm (1  ff) 
Thus, the intragranular porosity (or matrix-continuum porosity) of the crushed-tuff invert 
material used in the LDTH submodels is equal to 0.0721. 
Invert Thermal Conductivity 
The bulk thermal conductivity of the crushed-tuff invert material is partitioned 99 percent to the 
matrix continuum and 1 percent to the fracture continuum, as follows: 
Kth,f = Kth (0.01) 
Kth,m = Kth (0.99) 
This partitioning is done because the majority of the thermal mass in the invert resides in the 
matrix continuum. 
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Multiscale Thermohydrologic Model 
Invert Grain Density 
The bulk grain density of the crushed-tuff invert material is partitioned 99 percent to the matrix 
continuum and 1 percent to the fracture continuum, as follows: 
.g,m = (0.99).b/(1-fm) 
.g,f = (0.01).b/(1-ff) 
where .g,m is the grain density of the matrix continuum, .g,f is the grain density of the fracture 
continuum, .b 
is the bulk density of the crushed-tuff invert material obtained from 
DTN: GS020183351030.001 [DIRS 163107] (rows 321-370) and given in Table IV-8, fm is the 
matrix-continuum porosity of the crushed-tuff invert material, and ff 
is the fracture-continuum 
porosity of the crushed-tuff invert. This partitioning is done because the majority of the thermal 
mass in the invert resides in the matrix continuum. 
Waste Package and Drip Shield Properties 
Due to grid resolution limitations in the drift, the geometry of the waste package and drip shield 
are lumped into a monolithic heat source in the LDTH submodels (see Figure 6.2-6). Waste 
package density, drip shield density, and thermal conductivity should be averaged into this 
lumped approximation. The half-area (called A1/2) of the waste package and drip shield as 
represented in the LDTH submodel as a group of finite difference blocks with an area calculated 
as: 
A1/2 = 0.2420.58+0.40(0.58+0.37)+(0.759+0.760+0.425)(0.58+0.37+0.3025) = 2.9552 m2 
These dimensions are obtained from the gridblock spacings in the LDTH submodels (see Figure 
6.2-6). Table 4-1 gives the nominal number of waste packages in the repository: (1) 4,299 21PWR 
AP waste packages, (2) 2,831 44-BWR AP waste packages, and (3) 11,184 total waste 
packages. Therefore, the majority of waste packages (64 percent) will be either 21-PWR AP 
waste packages or 44-BWR AP waste packages; both of these waste packages weigh 43,000 kg 
and are 5.165 m in length (Table 4-1). After adding 0.1 m for the waste-package spacing (Table 
4-1) to the length of the waste package, the weight per unit length of the majority of waste 
packages is 43,000 kg divided by 5.265 m (5.165 m + 0.1 m), or 8,200 kg/m. This is taken to be 
representative of the average waste package in the repository. The lineal weight per unit length 
of drip shield is equal to the weight of the drip shield (5,000 kg, given in Table 4-1) divided by 
the drip-shield length (6.105 m, given in Table 4-1), which is equal to 820 kg/m. 
The lineal weight per unit length of the average waste package and drip shield is 8,200 kg/m and 
820 kg/m, respectively, yielding a total lineal weight of 9,020 kg/m. The equivalent density, 
.equiv, of the LDTH waste package and drip shield is calculated as: 
.equiv = (9,020 kg/m)/(2  A1/2) = 1,526.1 kg/m3 
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Multiscale Thermohydrologic Model 
The thermal conductivity of the waste package and drip shield is the sum of the thermal 
conductivity values weighted by the relative weight of the respective materials: 
Kth,equiv = Kth,ds  (820/9,020) + Kth,wp  (8,200/9,020) 
SDT/DDT Submodel Thermal Properties 
The thermal properties are taken from files of the following sources: 
DTN: SN0303T0503102.008 [DIRS 162401], DTN: SN0307T0510902.003 [DIRS 164196], 
and DTN: SN0404T0503102.011 [DIRS 169129] (Table 7-10, File: readme.doc). Bulk thermal 
conductivity and bulk density (average and 1 standard deviation above and below) of the 
GFM2000 nonrepository layers are contained in DTN: SN0303T0503102.008 [DIRS 162401]. 
Bulk thermal conductivity and bulk density variation (mean, and 1 standard deviation above and 
below) of the repository horizon UZ model layers are contained in Table 7-10 of DTN: 
SN0404T0503102.011 [DIRS 169129] (File: readme.doc). The specific heat capacity of the 
mineralogical model units was taken from DTN: SN0307T0510902.003 [DIRS 164196]. The 
input data from these DTNs are summarized in Table IV-3a. As discussed in the footnotes of 
Table IV-3a there are minor differences between the specific heat capacity used for several 
mineralogical model units and those given in the source DTN: SN0307T0510902.003 [DIRS 
164196]. These differences are much smaller than the range of uncertainty for the affected 
layers (see column Z of the excel spreadsheet for DTN: SN0307T0510902.003 [DIRS 164196]). 
The affected mineralogical model units are well removed from the repository horizon; 
consequently, these small differences have no effect on thermal-hydrologic conditions within and 
adjacent to emplacement drifts. The SDT, DDT, and SMT submodels use the bulk density and 
bulk thermal conductivity values and do not require that these values be partitioned into the 
fracture and matrix continuum. Note that because NUFT uses the grain density (also called solid 
density), the matrix porosity, which is obtained from DTN: LB0208UZDSCPMI.002 [DIRS 
161243], is also required as input to the input files for the SDT, DDT, and SMT submodels. 
The only parameter requiring a hand calculation for the SDT and DDT submodel near-field 
properties is the grain density (or solid density) .g, which is calculated as: 
.= 
.b 
g 
1 -f
m 
DDT Submodel In-drift Thermal Properties 
The material properties for the DDT submodel are the same as the corresponding bulk thermal 
properties in the drift for the LDTH submodel. There is a difference with how the waste package 
and drip shield are accounted for in the DDT submodel, however, as the DDT submodel 
represents each waste package separately and discretizes the drip shield. 
Waste Package and Drip Shield Thermal Properties 
For the DDT submodel the weights of each individual waste package are discretely represented, 
not lumped, into an average representation of the drip shield and waste package, as was done for 
ANL-EBS-MD-000049 REV 02 IV-5 October 2004 

Multiscale Thermohydrologic Model 
the LDTH submodel. The mass density of each waste package type (21-PWR, 44-BWR, 
5DHLW-long, and 5DHLW-short) is determined by taking volumetric average of the materials 
(outer barrier, inner vessel, internal cylinder): 
2
.WP = [.outer (d32  d22) + .inner (d22  d12) + .internal (d12)] / d3 
where d3 is the outermost diameter of the waste package, d2 is the inner diameter of the outer 
barrier, and d1 is the diameter of the internal cylinder obtained. The mass densities, .WP, .outer, 
.inner, and .internal are, respectively, the weighted waste package mass density, the outer-barrier 
mass density, the inner-vessel mass density, and the internal cylinder density. These diameters 
were obtained from Design and Engineering, D&E/PA/C IED Typical Waste Package 
Components Assembly 1 of 9 (BSC 2003 [DIRS 165406], Table 1). The density of the outer 
barrier (Alloy 22) was obtained from DTN: MO0003RIB00071.000 [DIRS 148850]; the density 
of the inner vessel (Stainless Steel Type 316) was obtained from Table XI of ASTM G 1-90; the 
density of the internal cylinder was obtained from Table 20 of D&E / PA/C IED Typical Waste 
Package Components Assembly (BSC 2004 [DIRS 169990]). 
The effective waste package specific heat, CpWP, of the DDT submodel are calculated for each 
waste package using a volumetric average of the corresponding materials: 
2
CpWP = [Cpouter (d32  d22) + Cpinner (d22  d12) + Cpinternal (d12)] / d3 
where d3 is the outer diameter of the outer barrier, d2 is the outer diameter of the inner vessel, 
and d1 is the inner diameter of the inner vessel; Cpouter is the specific heat of the outer barrier, 
Cpinner is the specific heat of the inner vessel, and Cpinternal is the specific heat of the internal 
cylinder. 
The effective waste package thermal conductivity, Kth,WP, also uses a volumetric average: 
2
Kth,WP = [Kth,outer (d32  d22) + Kth,inner (d22  d12) + Kth,internal (d12)] / d3 
The waste package thermal conductivity only influences longitudinal heat flow along the axis of 
the drift in the DDT submodel. In other words, radial heat flow (from the center of the waste 
package to the outer surface) is not predicted in the DDT submodel. Therefore, only the axial 
component of Kth,WP is required in the DDT submodel. Because the materials in the waste 
package are concentrically arranged, the volumetric average of Kth,WP of the respective 
components of the waste package is the appropriate manner in which to determine the effective 
waste package thermal conductivity. 
The thermal parameters for the drip shield (Table 4-1) were taken directly from Table TCD of 
1995 ASME Boiler and Pressure Vessel Code (ASME 1995, Section II). The thermal parameters 
required in the NUFT submodels necessitate the calculations described below for titanium. 
Due to limitations of grid resolution in the drift of the DDT submodels, all waste packages are 
modeled as though they have the same diameter even though the actual diameters are not the 
same (Table 4-1). An effective density .eff is calculated for each of the respective waste 
packages so that the mass of each waste package is properly represented in the DDT submodels. 
ANL-EBS-MD-000049 REV 02 IV-6 October 2004 

Multiscale Thermohydrologic Model 
The effective density .eff is equal to the mass of the waste package (Table 4-1) divided by 
volume of the waste package as it is represented in the DDT submodel. 
Thermal Properties for Stainless Steel Type 316 and Titanium 
Several of the direct inputs available for determining waste package and drip shield thermal 
properties require interpolation (to a reference temperature) and/or require simple calculations to 
the input parameters required by the DDT submodel. The thermal conductivity of Stainless Steel 
Type 316, which is used in the inner cylinder of the waste packages, requires interpolation to 
100C. Furthermore, the specific heat for Stainless Steel Type 316 should be calculated on the 
basis of thermal diffusivity and thermal conductivity, which are direct inputs. Similarly, the 
thermal conductivity of titanium, which is used in the drip shield, require interpolation to a 
temperature of 100C. Furthermore, the specific heat for titanium should be calculated on the 
basis of thermal diffusivity and thermal conductivity, which are direct inputs. The following 
steps were used to obtain the required parameter values. 
1. Mass density of Stainless Steel Type 316 
7.98 g/cm3 = 7,980 kg/m3 = 498.175 lb/ft3 
The bold value above is taken from Table XI of ASTM G 1-90. 
2. Thermal conductivity of Stainless Steel Type 316 (T = 100C) 
Table IV-1. Interpolation of Thermal Diffusivity and Thermal Conductivity Outlined for Stainless Steel 
Type 316. 
Thermal Thermal Thermal 
Temperature 
(F) 
Temperature 
(C) 
Diffusivity 
(ft2/hr) 
Conductivity 
(BTU/hr-ft-F) 
Conductivity 
(W/mK) 
200 93.33 0.141 8.4 14.54 
250 121.11 0.143 8.7 15.06 
212 100.00 0.1415 8.472 14.665 
Conversion Factor 1.0 1.730734666 
NOTE: The conversion of these parameters from English units to SI units is also 
shown. The bold values are from Table TCD of 1995 ASME Boiler and 
Pressure Vessel Code (ASME 1995). 
0.1415 = 0.141 +(0.143 - 0.141 ) 212 - 200 
250 - 200 
8.472 = 8.4 +(8.7 - 8.4 ) 212 - 200 
250 - 200 
14.665 = 14.54 +(15.06 -14.54 ) 212 - 200 
250 - 200 
14.663 = 1.730734666  8.472 
ANL-EBS-MD-000049 REV 02 IV-7 October 2004 

Multiscale Thermohydrologic Model 
3. Specific heat of Stainless Steel Type 316 (T = 100C) 
o 
o Thermal Conductivity (BTU/hr-ft-F) 
3 2
Specific Heat (BTU/lb-F) = 
Density (lb/ft ) Thermal Diffusivity(ft /hr) 
8.472 o
= = 0.1202 (BTU/lb-F) 
498.1750.1415 
o
= 503.19 (J/kg-K). 
4. Density of titanium 
0.163 lb/in3 = 4521 kg/m3 = 281.675 lb/ft3 
The bold value above is taken from Section II, Table NF-2 of 1995 ASME Boiler and 
Pressure Vessel Code (ASME 1995). 
5. Thermal conductivity of titanium (T = 100C) 
Table IV-2. Interpolation of Thermal Diffusivity and Thermal Conductivity Outlined for Titanium 
Thermal Thermal Thermal 
Temperature 
(F) 
Temperature 
(C) 
Diffusivity 
(ft2/hr) 
Conductivity 
(BTU/h-ft-F) 
Conductivity 
(W/mK) 
200 93.33 0.331 12.00 20.7688 
250 121.11 0.322 11.85 20.5092 
212 100.00 0.3288 11.964 20.7065 
NOTE: The conversion of these parameters from English units to SI units is 
also shown. The bold values are taken from Section II, Table NF-2 
of 1995 ASME Boiler and Pressure Vessel Code (ASME 1995). 
0.3288 = 0.331 +(0.322 - 0.331 ) 212 - 200 
250 - 200 
11.96 4 = 12.0 +(11.8 5 - 12.0 ) 212 - 200 
250 - 200 
6. Specific heat of titanium (T = 100C) 
o 
o
Specific Heat (BTU/lb-F) = Thermal Conductivity (BTU/h-ft-F) 
3
Density(lb/ft ) Thermal Diffusivity(ft2/h) 
11.964 o
= = 0.1292 (BTU/lb-F)
281.675 0.3288 
= 540.85 (J/kg-K). 
These simple calculations used the following conversion factors: 
1. Heat Capacity: 1.0 Btu/(lb-F) = 4186.8 J/(kgK) 
2. Thermal Conductivity 1.0 Btu/(h-ft-F) = 1.730734666 W/(mK) 
ANL-EBS-MD-000049 REV 02 IV-8 October 2004 

Multiscale Thermohydrologic Model 
3. Density 1.0 g/cm3= 62.427960576 lb/ft3 
4. 1.0 lb/in3 = 27,679.904710203 kg/m3 
Invert Thermal Properties 
For the DDT submodels, the invert has the same bulk thermal properties as the bulk thermal 
properties in the LDTH submodels. That is to say that the thermal conductivity, specific heat, 
and mass density in the DDT submodels are the same as the bulk thermal conductivity, specific 
heat capacity, and bulk mass density of the invert in the LDTH submodels. 
SMTSubmodel thermal properties 
Only fault and saturated zone thermal properties need to be specifically calculated for the SMT 
submodel thermal properties. Otherwise, the SMT submodel uses the same thermal properties as 
the SDT submodels. 
Fault-Zone Thermal Properties 
The density of the fault zone is simply the average of all of the units that make up the fault zone: 
.tcwfl = (.tcwl1 + .tcwl2 + .tcwl3)/3 
.ptnfl = (.ptn21 + .ptn22 + .ptn23 + .ptn24 + .ptn25 + .ptn26)/6 
.tsw = (.tsw31 + .tsw32 + .tsw33 + .tsw34 + .tsw35 + .tsw36 + .tsw37 + .tsw38 + .tsw9v+ .tsw9z)/10 
.ch1fl = (.ch1v + .ch1z)/2 (similar for ch2fl, ch3fl, ch4fl, ch5fl, ch6fl) 
.pp4fl = .pp4 (similar for pp3, pp2, pp1, bf3, bf2, tr3, tr2) 
The same process is used to determine the fault-zone properties for thermal conductivity, specific 
heat and porosity. 
Saturated Zone Thermal Properties 
The saturated zone intersects 14 UZ model layers (ch1z, ch2z, ch3z ch4z, ch5z, ch6z, pp4, pp3, 
pp2, pp1, bf3, bf2, tr3, and tr2). The saturated-zone density, thermal conductivity, specific heat, 
and porosity are simply calculated as the sum of the properties for those units divided by 14. 
Rocktab File Example 
Listed below is a part of an example rocktab file (dkm-afc-1Dds-mc-mi-03) that would be called 
in a NUFT input file (see Appendix V). Of note is that several material properties are listed each 
delineated by the line ;; End of the material. Specific details of the rocktab file properties are 
found in the NUFT users manual (Nitao 1998 [DIRS 100474], p. 41). 
;; dkm-afc-1Dds-mc-mi-03 
;; 4/11/2003 @16:23:21;; 0.50 Shared in matrix & 0.50 shared in fracture 
;; atm(atm
(cont-len-fac 1.00e+00) (cont-area-fac 2.00e+00)
(exfac-adv (liquid 1.00e+00) (gas 1.00e+00))
(solid-density 1.00e+08) (porosity 0.99) 
ANL-EBS-MD-000049 REV 02 IV-9 October 2004 

Multiscale Thermohydrologic Model 
(Kd (water 0.0) (air 0.0))
(KdFactor (water 0.0) (air 0.0))
(Cp 1.00e+08)
(tcond tcondLin (solid 1.00e+02) (liquid 1.00e+02) (gas 1.00e+02))
(K0 1.00e-08) (K1 1.00e-08) (K2 1.00e-08)
(tort (gas 1.00e+00) (liquid 0.00e+00))
(kr (liquid krlLinear (Sr 0.00e+00) (Smax 1.0))
(gas krgLinear (Sr 0.00e+00) (Smax 1.0)))
(pc (liquid 0.0))
(krMC (liquid krMCintrinsic) (gas krMCintrinsic))
) ;;End of the material;;Matrix materials(m-tcw11
(cont-len-fac 1.81e-01) (cont-area-fac 1.56e+00)
(exfac-adv (liquid 1.00e+00) (gas 1.00e+00))
(solid-density 2820.64) (porosity 0.241)
(Kd (water 0.0) (air 0.0))
(KdFactor (water 0.0) (air 0.0))
(Cp 9.30e+02)
(tcond tcondLin (solid 1.26880) (liquid 1.76656) (gas 1.26880))
(K0 3.74e-15) (K1 3.74e-15) (K2 3.74e-15)
(tort (gas 2.00e-01) (liquid 0.00e+00))
(kr (liquid krlVanGen (Sr 2.00e-02) (m 3.88e-01) (Smax 1.0))
(gas krgModCorey (Srl 2.00e-02) (m 3.88e-01) (Slmax 1.0)))
(pc (liquid pcVanGen (Sr 2.00e-02) (m 3.88e-01) (alpha 1.01e-05) (Smax 1.0)))
(krMC (liquid krMCintrinsic) (gas krMCintrinsic))
) ;;End of the material 
[SECTION SKIP] 
(f-ptn24(cont-len-fac 0.00e+00) (cont-area-fac 1.00e+00)
(exfac-adv (liquid 1.00e+00) (gas 1.00e+00))
(solid-density 24.90) (porosity 1.00e-02)
(Kd (water 0.0) (air 0.0))
(KdFactor (water 0.0) (air 0.0))
(Cp 9.60e+02)
(tcond tcondLin (solid 0.00490) (liquid 0.01060) (gas 0.00490))
(K0 3.00e-12) (K1 3.00e-12) (K2 3.00e-12)
(tort (gas 7.00e-01) (liquid 0.00e+00))
(kr (liquid krlVanGen (Sr 1.00e-02) (m 6.33e-01) (Smax 1.0) (gamma 2.32e-01))
(gas krgModCorey (Srl 1.00e-02) (m 6.33e-01) (Slmax 1.0)))
(pc (liquid pcVanGen (Sr 1.00e-02) (m 6.33e-01)(alpha 1.86e-03)
(Smax 1.0) (gamma 2.32e-01)))
(krMC (liquid krMCactiveFrac (gamma 2.32e-01) (Sr 1.00e-02))
(gas krMCactiveFrac (gamma 2.32e-01) (Sr 0.0)))
) ;;End of the material(f-ptn25
(cont-len-fac 0.00e+00) (cont-area-fac 1.00e+00)
(exfac-adv (liquid 1.00e+00) (gas 1.00e+00))
(solid-density 16.00) (porosity 5.50e-03)
(Kd (water 0.0) (air 0.0))
(KdFactor (water 0.0) (air 0.0))
(Cp 9.60e+02)
(tcond tcondLin (solid 0.00269) (liquid 0.00583) (gas 0.00269))
(K0 1.70e-13) (K1 1.70e-13) (K2 1.70e-13)
(tort (gas 7.00e-01) (liquid 0.00e+00))
(kr (liquid krlVanGen (Sr 1.00e-02) (m 6.33e-01) (Smax 1.0) (gamma 2.32e-01))
(gas krgModCorey (Srl 1.00e-02) (m 6.33e-01) (Slmax 1.0)))
(pc (liquid pcVanGen (Sr 1.00e-02) (m 6.33e-01)(alpha 1.33e-03)
(Smax 1.0) (gamma 2.32e-01)))
(krMC (liquid krMCactiveFrac (gamma 2.32e-01) (Sr 1.00e-02)) 
ANL-EBS-MD-000049 REV 02 IV-10 October 2004

Multiscale Thermohydrologic Model 
(gas krMCactiveFrac (gamma 2.32e-01) (Sr 0.0)))
) ;;End of the material 
[SECTION SKIP] 
(f-tr2(cont-len-fac 0.00e+00) (cont-area-fac 1.00e+00)
(exfac-adv (liquid 1.00e+00) (gas 1.00e+00))
(solid-density 0.85) (porosity 3.70e-04)
(Kd (water 0.0) (air 0.0))
(KdFactor (water 0.0) (air 0.0))
(Cp 9.40e+02)
(tcond tcondLin (solid 0.00020) (liquid 0.00041) (gas 0.00020))
(K0 2.50e-14) (K1 2.50e-14) (K2 2.50e-14)
(tort (gas 7.00e-01) (liquid 0.00e+00))
(kr (liquid krlVanGen (Sr 1.00e-02) (m 6.33e-01) (Smax 1.0) (gamma 3.70e-01))
(gas krgModCorey (Srl 1.00e-02) (m 6.33e-01) (Slmax 1.0)))
(pc (liquid pcVanGen (Sr 1.00e-02) (m 6.33e-01)(alpha 8.90e-04)
(Smax 1.0) (gamma 3.70e-01)))
(krMC (liquid krMCactiveFrac (gamma 3.70e-01) (Sr 1.00e-02))
(gas krMCactiveFrac (gamma 3.70e-01) (Sr 0.0)))
) ;;End of the material 
ANL-EBS-MD-000049 REV 02 IV-11 October 2004

Multiscale Thermohydrologic Model 
Table IV-3a. Specific Heat Capacity, Thermal Conductivity (Dry and Wet) and Bulk Density for the 
GFM2000 Units 
Material 
Name Used 
in LDTH 
Submodels 
GFM2000 
Layer 
Mineralogic 
Model Unit 
Bulk 
Density 
kg/m3 
Thermal 
Conductivity 
, Dry 
W/m K 
Thermal 
Conductivity 
, Wet 
W/m K 
Specific 
Heat 
Capacity 
J/gK 
tcw11 Tpcp Tpc_un 2,190 1.30 1.81 0.93 
tcw12 Tpcp 2,190 1.30 1.81 0.93 
TpcLD 2,190 1.30 1.81 0.93 
tcw13 Tpcpv3 Tcppv3 - 2,310 0.688 0.796 0.95 
Tpcpv2 Tpcpv2 1,460 0.490 1.06 0.95 
ptn21 Tpcpv1 PTnf 1,460 0.490 1.06 0.96 
ptn22 Tpbt4 1,460 0.490 1.06 0.96 
Tpy (Yucca) 1,460 0.490 1.06 0.96 
ptn23 Tpbt3 1,460 0.490 1.06 0.96 
ptn24 Tpy 1,460 0.490 1.06 0.96 
Tpbt3 1,460 0.490 1.06 0.96 
ptn25 Tpp (Pah) 1,460 0.490 1.06 0.96 
ptn26 Tpbt2 1,460 0.490 1.06 0.96 
Tptrv3 1,460 0.490 1.06 0.96 
Tptrv2 1,460 0.490 1.06 0.96 
tsw31 Tptrv1 Tptrv1 2,310 0.688 0.796 0.95 
Tptrn Tptrn - 2,190 1.30 1.81 0.93 
tsw32 Tptrn Tptrl - 2,190 1.30 1.81 0.93 
tsw33 Tptrl Tptf 2190 1.30 1.81 0.93 
Tptpul Tptul 1,830 1.1829 1.7749 0.93 
tsw34 Tptpmn Tptpmn 2,150 1.4189 2.0741 0.93 
tsw35 Tptpll Tptpll 1,980 1.2784 1.8895 0.93 
tsw36 Tptpln Tptpln 2,210 1.4900 2.1303 0.93 
tsw37 Tptpln 2,210 1.4900 2.1303 0.93 
tsw38 Tptpv3 Tptpv3 2,310 0.688 0.796 0.98 
tsw9v Tptpv2 Tptpv2 1,460 0.490 1.06 0.98a 
tsw9z Tptpv2 1,460 0.490 1.06 0.98 
ch1v Tptpv1 Tptpv1 - 1,460 0.490 1.06 1.08b 
Tpbt1 Tpbt1 1,460 0.490 1.06 1.08b 
ch1z Tptpv1 1,460 0.490 1.06 1.08 
Tpbt1 1,460 0.490 1.06 1.08 
ch2v Tac (Calico) Tac 1,670 0.595 1.26 1.07c 
ch3v Tac (Calico) (4 layers) 1,670 0.595 1.26 1.07c 
ch4v Tac (Calico) 1,670 0.595 1.26 1.07c 
ch5v Tac (Calico) 1,670 0.595 1.26 1.07c 
ch2z Tac (Calico) 1,670 0.595 1.26 1.07 
ch3z Tac (Calico) 1,670 0.595 1.26 1.07 
ch4z Tac (Calico) 1,670 0.595 1.26 1.07 
ANL-EBS-MD-000049 REV 02 IV-12 October 2004 

Multiscale Thermohydrologic Model 
Table IV-3a. Specific Heat Capacity, Thermal Conductivity (Dry and Wet) and Bulk Density for the 
GFM2000 Units (Continued) 
Material 
Name Used 
in LDTH 
Submodels 
GFM2000 
Layer 
Mineralogic 
Model Unit 
Bulk 
Density 
kg/m3 
Thermal 
Conductivity 
, Dry 
W/m K 
Thermal 
Conductivity 
, Wet 
W/m K 
Specific 
Heat 
Capacity 
J/gK 
ch5z Tac (Calico) Tac (Cont.) 1,670 0.595 1.26 1.07 
ch6v Tacbt (Calicobt) Tacbt 1,670 0.595 1.26 1.02 d 
ch6z Tacbt (Calicobt) 1,670 0.595 1.26 1.02 
pp4 Tcpuv (Prowuv) Tcpuv 1,790 0.569 1.13 1.04 
pp3 Tcpuc (Prowuc) Tcpuc - 1,790 0.569 1.13 0.93 
pp2 Tcpmd (Prowmd) Tcplc 2,070 1.06 1.63 0.93 
Tcplc (Prowlc) 1,790 0.569 1.13 0.93 
pp1 Tcplv (Prowlv) Tcplv - 1,790 0.569 1.13 1.05 e 
Tcpbt (Prowbt) Tcbuv 1,790 0.569 1.13 1.05 e 
Tcbuv (Bullfroguv) 1,880 0.658 1.19 1.05 e 
bf3 Tcbuc (Bullfroguc) Tcbuc - 1,880 0.658 1.19 0.93 
Tcbmd (Bullfrogmd) Tcblc 2,260 1.30 1.81 0.93 
Tcblc (Bullfroglc) 1,880 0.658 1.19 0.93 
bf2 Tcblv (Bullfroglv) Tcblv - 1,880 0.658 1.19 1.05 
Tcbbt (Bullfrogbt) Tctuv 1,880 0.658 1.19 1.05 
Tctuv (Tramuv) 1,760 0.535 1.10 1.05 
tr3 Tctuc (Tramuc) Tctuc - 1,760 0.535 1.10 0.94 
Tctmd (Trammd) Tctlc 2,140 1.06 1.63 0.94 
Tctlc (Tramlc) 1,760 0.535 1.10 0.94 
tr2 Tctlv (Tramlv) Tctlv - 
Tctbt 
1,760 0.535 1.10 0.94 
Tctbt (Trambt) 1,760 0.535 1.10 0.94 
a 
Zeolitic value of specific heat capacity (0.98 J/gK) is used rather than the vitric value (0.96 J/gK).
b 
Zeolitic value of specific heat capacity (1.08 J/gK) is used rather than the vitric value (0.96 J/gK). 
Zeolitic value of specific heat capacity (1.07 J/gK) is used rather than the vitric value (0.96 J/gK).
d 
Zeolitic value of specific heat capacity (1.02 J/gK) is used rather than the vitric value (0.97 J/gK). 
e 
Specific heat capacity value for the Tcblv-Tctuv (1.05 J/gK) is used rather than for the Tcplv-Tcbuv (1.10 
J/gK). 
f 
Ptn = Tpcpv1, Tpbt4, Tpy, Tpbt3, Tpp, Tpbt2, Tptrv3, Tptrv2 
NOTE: The values for the nonrespository layers are from DTN: SN0303T0503102.008 [DIRS 162401]. The 
thermal conductivity and bulk density values for the repository layers (tsw33, tsw34, tsw35, tsw36, 
and tsw37) are from Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc), 
with the density values rounded. The GFM2000 layers shown in italics pertain to data obtained from 
Table 7-10 of DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc). The bulk density 
values from DTN: SN0404T0503102.011 [DIRS 169129] (File: readme.doc) have been slightly 
rounded to be consistent with the bulk density values from DTN: SN0303T0503102.008 [DIRS 
162401]. Mineralogic model units are from Heat Capacity Analysis Report (BSC 2004 [DIRS 
170003], Tables 6.1 and 6.7). The specific heat capacity for all layers is from DTN: 
SN0307T0510902.003 [DIRS 164196] for the temperature range of 25 to 325C. The values of 
specific heat capacity, thermal conductivity, and bulk density for the layers with multiple GFM2000 
layers (e.g., pp1) are the arithmetic average of the corresponding GFM2000-layer values. Table IV3b 
gives the result of this averaging for bulk density and bulk thermal conductivity. 
ANL-EBS-MD-000049 REV 02 IV-13 October 2004 

Multiscale Thermohydrologic Model 
Table IV-3b. Thermal Properties for the UZ Model Layers. 
Porosity Density Thermal Conductivity 
Kth,b Kth,m Kth,f Kth,b Kth,m Kth,f 
Material 
Name fm ff 
.b 
kg/m3 
.G 
kg/m3 
.G,m 
kg/m3 
.G,f 
kg/m3 
wet 
W/mC 
wet 
W/mC 
wet 
W/mC 
dry 
W/mC 
dry 
W/mC 
dry 
W/mC 
tcw11 0.241 2.40E-02 2190 2890 2820.64 69.36 1.81 1.767 4.34E-02 1.30 1.269 3.12E-02 
tcw12 0.088 1.70E-02 2190 2400 2359.20 40.80 1.81 1.779 3.08E-02 1.30 1.278 2.21E-02 
tcw13 0.200 1.30E-02 1890 2360 2329.32 30.68 0.93 0.918 1.21E-02 0.59 0.582 7.67E-03 
ptn21 0.387 9.20E-03 1460 2380 2358.10 21.90 1.06 1.050 9.75E-03 0.49 0.485 4.51E-03 
ptn22 0.428 1.00E-02 1460 2550 2524.50 25.50 1.06 1.049 1.06E-02 0.49 0.485 4.90E-03 
ptn23 0.233 2.10E-03 1460 1900 1896.01 3.99 1.06 1.058 2.23E-03 0.49 0.489 1.03E-03 
ptn24 0.413 1.00E-02 1460 2490 2465.10 24.90 1.06 1.049 1.06E-02 0.49 0.485 4.90E-03 
ptn25 0.498 5.50E-03 1460 2910 2894.00 16.00 1.06 1.054 5.83E-03 0.49 0.487 2.69E-03 
ptn26 0.490 3.10E-03 1460 2860 2851.13 8.87 1.06 1.057 3.29E-03 0.49 0.488 1.52E-03 
tsw31 0.054 5.00E-03 2250 2380 2368.10 11.90 1.30 1.294 6.50E-03 0.99 0.985 4.95E-03 
tsw32 0.157 8.30E-03 2190 2600 2578.42 21.58 1.81 1.795 1.50E-02 1.30 1.289 1.08E-02 
tsw33 0.155 5.80E-03 2010 2380 2366.20 13.80 1.79 1.780 1.04E-02 1.24 1.233 7.19E-03 
tsw34 0.111 8.50E-03 2150 2420 2399.43 20.57 2.07 2.052 1.76E-02 1.42 1.408 1.21E-02 
tsw35 0.131 9.60E-03 1980 2280 2258.11 21.89 1.89 1.872 1.81E-02 1.28 1.268 1.23E-02 
tsw36 0.103 1.30E-02 2210 2460 2428.02 31.98 2.13 2.102 2.77E-02 1.49 1.471 1.94E-02 
tsw37 0.103 1.30E-02 2210 2460 2428.02 31.98 2.13 2.102 2.77E-02 1.49 1.471 1.94E-02 
tsw38 0.043 1.10E-02 2310 2410 2383.49 26.51 0.80 0.791 8.80E-03 0.69 0.682 7.59E-03 
tsw9v 0.115a 0.115a 1460 1890b 824.39c 824.39c 1.06 1.060 N/A 0.49 0.490 N/A 
tsw9z 0.275 4.30E-03 1460 2010 2001.36 8.64 1.06 1.055 4.56E-03 0.49 0.488 2.11E-03 
ch1v 0.166a 0.166a 1460 2180b 874.78c 874.78c 1.06 1.060 N/A 0.49 0.490 N/A 
ch1z 0.285 1.60E-04 1460 2040 2039.67 0.33 1.06 1.060 1.70E-04 0.49 0.490 8.00E-05 
ch2v 0.173a 0.173a 1670 2550b 1009.67c 1009.67c 1.26 1.260 N/A 0.60 0.600 N/A 
ch3v 0.173a 0.173a 1670 2550b 1009.67c 1009.67c 1.26 1.260 N/A 0.60 0.600 N/A 
ch4v 0.173a 0.173a 1670 2550b 1009.67c 1009.67c 1.26 1.260 N/A 0.60 0.600 N/A 
ch5v 0.173a 0.173a 1670 2550b 1009.67c 1009.67c 1.26 1.260 N/A 0.60 0.600 N/A 
ch2z 0.322 3.70E-04 1670 2460 2459.09 0.91 1.26 1.260 4.70E-04 0.60 0.600 2.20E-04 
ch3z 0.322 3.70E-04 1670 2460 2459.09 0.91 1.26 1.260 4.70E-04 0.60 0.600 2.20E-04 
ch4z 0.322 3.70E-04 1670 2460 2459.09 0.91 1.26 1.260 4.70E-04 0.60 0.600 2.20E-04 
ch5z 0.322 3.70E-04 1670 2460 2459.09 0.91 1.26 1.260 4.70E-04 0.60 0.600 2.20E-04 
ch6v 0.166a 0.166a 1670 2550b 1000.60c 1000.60c 1.26 1.260 N/A 0.60 0.600 N/A 
ch6z 0.271 1.60E-04 1670 2290 2289.63 0.37 1.26 1.260 2.00E-04 0.60 0.600 1.00E-04 
pp4 0.321 3.70E-04 1790 2640 2639.02 0.98 1.13 1.130 4.20E-04 0.57 0.570 2.10E-04 
pp3 0.318 9.70E-04 1790 2620 2617.46 2.54 1.13 1.129 1.10E-03 0.57 0.569 5.50E-04 
pp2 0.221 9.70E-04 1930 2480 2477.59 2.41 1.38 1.379 1.34E-03 0.81 0.809 7.90E-04 
pp1 0.297 3.70E-04 1820 2590 2589.04 0.96 1.15 1.150 4.30E-04 0.60 0.600 2.20E-04 
bf3 0.175 9.70E-04 2010 2440 2437.63 2.37 1.40 1.399 1.36E-03 0.87 0.869 8.40E-04 
bf2 0.234 3.70E-04 1840 2400 2399.11 0.89 1.16 1.160 4.30E-04 0.62 0.620 2.30E-04 
tr3 0.175 9.70E-04 1890 2290 2287.78 2.22 1.28 1.279 1.24E-03 0.71 0.709 6.90E-04 
tr2 0.234 3.70E-04 1760 2300 2299.15 0.85 1.10 1.100 4.10E-04 0.54 0.540 2.00E-04 
a 
Vitric units have matrix porosity partitioned 50% to the matrix continuum and 50% to the pseudo-fracture continuum. 
b Value not used in LDTH submodel. 
Vitric units have grain density partitioned 50% to the matrix continuum and 50% to the pseudo-fracture continuum. 
.
NOTES: The subscripts m, f, b, and g stand for matrix, fracture, bulk, and grain, respectively. The bulk density 
 and bulk thermal conductivity Kth,b (wet and dry) are obtained from Table IV-3a, with averaging applied 
to UZ model layers with multiple GFM2000 layers. The density and thermal-conductivity for the matrix and 
fracture continua are calculated by hand on the basis of fracture porosity. 
Porosity values are derived from Table IV-4. 
ANL-EBS-MD-000049 REV 02 IV-14 October 2004 

Multiscale Thermohydrologic Model 
Table IV-4. Matrix and Fracture Properties for the Mean Infiltration Flux One-Dimensional Drift-Scale 
Hydrologic Property Set 
Material Material 
name name used in Residual 
from DTN 
source 
LDTH 
submodels 
Permeability 
[m2] 
Porosity 
[-] 
saturation 
[-] 
a (alpha) 
[1/Pa] 
m 
[-] 
. (gamma) 
[-] 
tcwM1 m-tcw11 3.74E-15 0.241 0.02 1.01E-05 0.388 N/Aa 
tcwM2 m-tcw12 5.52E-20 0.088 0.20 3.11E-06 0.280 N/Aa 
tcwM3 m-tcw13 5.65E-17 0.200 0.31 3.26E-06 0.259 N/Aa 
ptnM1 m-ptn21 4.60E-15 0.387 0.24 1.62E-04 0.245 N/Aa 
ptnM2 m-ptn22 4.43E-12 0.428 0.13 1.46E-04 0.219 N/Aa 
ptnM3 m-ptn23 9.20E-15 0.233 0.07 2.47E-05 0.247 N/Aa 
ptnM4 m-ptn24 2.35E-12 0.413 0.14 7.90E-04 0.182 N/Aa 
ptnM5 m-ptn25 2.15E-13 0.498 0.06 1.04E-04 0.300 N/Aa 
ptnM6 m-ptn26 1.00E-11 0.490 0.05 9.83E-04 0.126 N/Aa 
tswM1 m-tsw31 2.95E-17 0.054 0.21 8.70E-05 0.218 N/Aa 
tswM2 m-tsw32 2.23E-16 0.157 0.07 1.14E-05 0.290 N/Aa 
tswM3 m-tsw33 6.57E-18 0.155 0.12 6.17E-06 0.283 N/Aa 
tswM4 m-tsw34 1.77E-19 0.111 0.19 8.45E-06 0.317 N/Aa 
tswM5 m-tsw35 4.48E-18 0.131 0.12 1.08E-05 0.216 N/Aa 
tswM6 m-tsw36 2.00E-19 0.103 0.20 8.32E-06 0.442 N/Aa 
tswM7 m-tsw37 2.00E-19 0.103 0.20 8.32E-06 0.442 N/Aa 
tswM8 m-tsw38 2.00E-18 0.043 0.42 6.23E-06 0.286 N/Aa 
tswMv m-tsw9v 1.49E-13 0.229 0.13 4.86E-05 0.293 N/Aa 
tswMz m-tsw9z 3.5E-17 0.275 0.36 4.61E-06 0.059 N/Aa 
ch1Mv m-ch1v 6.65E-13 0.331 0.06 8.73E-05 0.240 N/Aa 
ch1Mz m-ch1z 3.5E-17 0.285 0.38 2.12E-07 0.349 N/Aa 
ch2Mv m-ch2v 2.97E-11 0.346 0.06 2.59E-04 0.158 N/Aa 
ch3Mv m-ch3v 2.97E-11 0.346 0.06 2.59E-04 0.158 N/Aa 
ch4Mv m-ch4v 2.97E-11 0.346 0.06 2.59E-04 0.158 N/Aa 
ch5Mv m-ch5v 2.97E-11 0.346 0.06 2.59E-04 0.158 N/Aa 
ch2Mz m-ch2z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch3Mz m-ch3z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch4Mz m-ch4z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch5Mz m-ch5z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch6Mv m-ch6v 2.35E-13 0.331 0.06 1.57E-05 0.147 N/Aa 
ch6Mz m-ch6z 8.2E-19 0.271 0.36 1.56E-07 0.499 N/Aa 
pp4Mz m-pp4 8.77E-17 0.321 0.29 4.49E-07 0.474 N/Aa 
pp3Md m-pp3 7.14E-14 0.318 0.08 8.83E-06 0.407 N/Aa 
pp2Md m-pp2 1.68E-15 0.221 0.10 2.39E-06 0.309 N/Aa 
pp1Mz m-pp1 2.35E-15 0.297 0.30 9.19E-07 0.272 N/Aa 
bf3Md m-bf3 4.34E-13 0.175 0.11 1.26E-05 0.193 N/Aa 
bf2Mz m-bf2 8.1E-17 0.234 0.21 1.18E-07 0.617 N/Aa 
tr3Md m-tr3 1.1E-15 0.175 0.11 1.12E-05 0.193 N/Aa 
tr2Mz m-tr2 8.1E-17 0.234 0.21 1.18E-07 0.617 N/Aa 
tcwF1 f-tcw11 3.0E-11 2.4E-02 0.01 5.27E-03 0.633 0.587 
tcwF2 f-tcw12 5.3E-12 1.7E-02 0.01 1.57E-03 0.633 0.587 
tcwF3 f-tcw13 4.5E-12 1.3E-02 0.01 1.24E-03 0.633 0.587 
ANL-EBS-MD-000049 REV 02 IV-15 October 2004 

Multiscale Thermohydrologic Model 
Table IV-4. Matrix and Fracture Properties for the Mean Infiltration Flux One-Dimensional Drift-Scale 
Hydrologic Property Set (Continued) 
Material Material 
name name used in Residual 
from DTN 
source 
LDTH 
submodels 
Permeability 
[m2] 
Porosity 
[-] 
saturation 
[-] 
a (alpha) 
[1/Pa] 
m 
[-] 
. (gamma) 
[-] 
ptnF1 f-ptn21 3.2E-12 9.2E-03 0.01 8.70E-04 0.633 0.232 
ptnF2 f-ptn22 3.0E-13 1.0E-02 0.01 1.57E-03 0.633 0.232 
ptnF3 f-ptn23 3.0E-13 2.1E-03 0.01 5.18E-03 0.633 0.232 
ptnF4 f-ptn24 3.0E-12 1.0E-02 0.01 1.86E-03 0.633 0.232 
ptnF5 f-ptn25 1.7E-13 5.5E-03 0.01 1.33E-03 0.633 0.232 
ptnF6 f-ptn26 2.2E-13 3.1E-03 0.01 1.34E-03 0.633 0.232 
tswF1 f-tsw31 8.1E-13 5.0E-03 0.01 1.60E-05 0.633 0.129 
tswF2 f-tsw32 7.1E-13 8.3E-03 0.01 1.00E-04 0.633 0.600 
tswF3 f-tsw33 7.8E-13 5.8E-03 0.01 1.59E-03 0.633 0.600 
tswF4 f-tsw34 3.3E-13 8.5E-03 0.01 1.04E-04 0.633 0.569 
tswF5 f-tsw35 9.1E-13 9.6E-03 0.01 1.02E-04 0.633 0.569 
tswF6 f-tsw36 1.3E-12 1.3E-02 0.01 7.44E-04 0.633 0.569 
tswF7 f-tsw37 1.3E-12 1.3E-02 0.01 7.44E-04 0.633 0.569 
tswF8 f-tsw38 8.1E-13 1.1E-02 0.01 2.12E-03 0.633 0.569 
tswFv f-tsw9v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
tswFz f-tsw9z 8.1E-13 4.3E-03 0.01 1.5E-03 0.633 0.370 
ch1Fv f-ch1v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch1Fz f-ch1z 2.5E-14 1.6E-04 0.01 1.4E-03 0.633 0.370 
ch2Fv f-ch2v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch3Fv f-ch3v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch4Fv f-ch4v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch5Fv f-ch5v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch2Fz f-ch2z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.370 
ch3Fz f-ch3z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.370 
ch4Fz f-ch4z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.370 
ch5Fz f-ch5z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.370 
ch6Fv f-ch6v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch6Fz f-ch6z 2.5E-14 1.6E-04 0.01 1.4E-03 0.633 0.370 
pp4Fz f-pp4 2.5E-14 3.7E-04 0.01 1.83E-03 0.633 0.370 
pp3Fd f-pp3 2.2E-13 9.7E-04 0.01 2.47E-03 0.633 0.199 
pp2Fd f-pp2 2.2E-13 9.7E-04 0.01 3.17E-03 0.633 0.199 
pp1Fz f-pp1 2.5E-14 3.7E-04 0.01 1.83E-03 0.633 0.370 
bf3Fd f-bf3 2.2E-13 9.7E-04 0.01 2.93E-03 0.633 0.199 
bf2Fz f-bf2 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.370 
tr3Fd f-tr3 2.2E-13 9.7E-04 0.01 1.6E-03 0.633 0.199 
tr2Fz f-tr2 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.370 
DTN: LB0208UZDSCPMI.002 [DIRS 161243]. 
a 
Gamma value does not apply to matrix continuum. 
b 
Vitric units (those units ending with a v) do not have fractures. The fracture continuum properties are the same as 
those of the matrix continuum for these units. 
NOTE: The prefix m- stands for matrix and f- stands for fracture. 
ANL-EBS-MD-000049 REV 02 IV-16 October 2004 

Multiscale Thermohydrologic Model 
Table IV-5. Matrix and Fracture Properties for the Lower-Bound Infiltration Flux One-Dimensional Drift-
Scale Hydrologic Property Set 
Material 
Material name used Residual 
name from 
DTN source 
in LDTH 
submodels 
Permeability 
[m2] 
Porosity 
[-] 
saturation 
[-] 
a (alpha) 
[1/Pa] 
m 
[-] 
. (gamma) 
[-] 
tcwM1 m-tcw11 3.44E-15 0.241 0.02 1.16E-05 0.388 N/Aa 
tcwM2 m-tcw12 3.00E-20 0.088 0.20 2.67E-06 0.280 N/Aa 
tcwM3 m-tcw13 3.96E-17 0.200 0.31 1.64E-06 0.259 N/Aa 
ptnM1 m-ptn21 5.55E-15 0.387 0.24 6.38E-05 0.245 N/Aa 
ptnM2 m-ptn22 8.40E-12 0.428 0.13 1.67E-04 0.219 N/Aa 
ptnM3 m-ptn23 1.92E-14 0.233 0.07 4.51E-05 0.247 N/Aa 
ptnM4 m-ptn24 6.66E-13 0.413 0.14 2.52E-03 0.182 N/Aa 
ptnM5 m-ptn25 1.96E-14 0.498 0.06 1.24E-04 0.300 N/Aa 
ptnM6 m-ptn26 1.00E-11 0.490 0.05 1.63E-03 0.126 N/Aa 
tswM1 m-tsw31 1.42E-17 0.054 0.21 8.02E-05 0.218 N/Aa 
tswM2 m-tsw32 3.96E-16 0.157 0.07 9.46E-06 0.290 N/Aa 
tswM3 m-tsw33 1.60E-18 0.155 0.12 4.25E-06 0.283 N/Aa 
tswM4 m-tsw34 1.38E-19 0.111 0.19 1.19E-06 0.317 N/Aa 
tswM5 m-tsw35 2.33E-18 0.131 0.12 1.97E-06 0.216 N/Aa 
tswM6 m-tsw36 5.58E-19 0.103 0.20 4.22E-07 0.442 N/Aa 
tswM7 m-tsw37 5.58E-19 0.103 0.20 4.22E-07 0.442 N/Aa 
tswM8 m-tsw38 2.93E-18 0.043 0.42 1.43E-06 0.286 N/Aa 
tswMv m-tsw9v 3.15E-13 0.229 0.13 1.86E-05 0.293 N/Aa 
tswMz m-tsw9z 3.5E-17 0.275 0.36 4.61E-06 0.059 N/Aa 
ch1Mv m-ch1v 3.15E-14 0.331 0.06 4.50E-05 0.240 N/Aa 
ch1Mz m-ch1z 3.5E-17 0.285 0.38 2.12E-07 0.349 N/Aa 
ch2Mv m-ch2v 1.13E-11 0.346 0.06 1.22E-04 0.158 N/Aa 
ch3Mv m-ch3v 1.13E-11 0.346 0.06 1.22E-04 0.158 N/Aa 
ch4Mv m-ch4v 1.13E-11 0.346 0.06 1.22E-04 0.158 N/Aa 
ch5Mv m-ch5v 1.13E-11 0.346 0.06 1.22E-04 0.158 N/Aa 
ch2Mz m-ch2z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch3Mz m-ch3z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch4Mz m-ch4z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch5Mz m-ch5z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch6Mv m-ch6v 2.54E-13 0.331 0.06 9.05E-06 0.147 N/Aa 
ch6Mz m-ch6z 8.2E-19 0.271 0.36 1.56E-07 0.499 N/Aa 
pp4Mz m-pp4 2.98E-16 0.321 0.29 2.88E-07 0.474 N/Aa 
pp3Md m-pp3 5.37E-14 0.318 0.08 7.97E-06 0.407 N/Aa 
pp2Md m-pp2 4.24E-16 0.221 0.10 2.41E-06 0.309 N/Aa 
pp1Mz m-pp1 7.02E-16 0.297 0.30 1.36E-06 0.272 N/Aa 
bf3Md m-bf3 2.97E-14 0.175 0.11 1.32E-05 0.193 N/Aa 
bf2Mz m-bf2 8.1E-17 0.234 0.21 1.18E-07 0.617 N/Aa 
tr3Md m-tr3 1.1E-15 0.175 0.11 1.12E-05 0.193 N/Aa 
tr2Mz m-tr2 8.1E-17 0.234 0.21 1.18E-07 0.617 N/Aa 
tcwF1 f-tcw11 3.0E-11 2.4E-02 0.01 4.68E-03 0.633 0.483 
tcwF2 f-tcw12 5.3E-12 1.7E-02 0.01 3.20E-03 0.633 0.483 
tcwF3 f-tcw13 4.5E-12 1.3E-02 0.01 2.13E-03 0.633 0.483 
ANL-EBS-MD-000049 REV 02 IV-17 October 2004 

Multiscale Thermohydrologic Model 
Table IV-5. Matrix and Fracture Properties for the Lower-Bound Infiltration Flux One-Dimensional Drift-
Scale Hydrologic Property Set (Continued) 
Material 
Material name used Residual 
name from 
DTN source 
in LDTH 
submodels 
Permeability 
[m2] 
Porosity 
[-] 
saturation 
[-] 
a (alpha) 
[1/Pa] 
m 
[-] 
. (gamma) 
[-] 
ptnF1 f-ptn21 3.2E-12 9.2E-03 0.01 2.93E-03 0.633 0.065 
ptnF2 f-ptn22 3.0E-13 1.0E-02 0.01 6.76E-04 0.633 0.065 
ptnF3 f-ptn23 3.0E-13 2.1E-03 0.01 3.96E-03 0.633 0.065 
ptnF4 f-ptn24 3.0E-12 1.0E-02 0.01 2.51E-03 0.633 0.065 
ptnF5 f-ptn25 1.7E-13 5.5E-03 0.01 1.53E-03 0.633 0.065 
ptnF6 f-ptn26 2.2E-13 3.1E-03 0.01 1.52E-03 0.633 0.065 
tswF1 f-tsw31 8.1E-13 5.0E-03 0.01 1.58E-05 0.633 0.037 
tswF2 f-tsw32 7.1E-13 8.3E-03 0.01 1.31E-04 0.633 0.528 
tswF3 f-tsw33 7.8E-13 5.8E-03 0.01 1.94E-03 0.633 0.528 
tswF4 f-tsw34 3.3E-13 8.5E-03 0.01 6.55E-04 0.633 0.476 
tswF5 f-tsw35 9.1E-13 9.6E-03 0.01 1.35E-03 0.633 0.476 
tswF6 f-tsw36 1.3E-12 1.3E-02 0.01 1.31E-03 0.633 0.476 
tswF7 f-tsw37 1.3E-12 1.3E-02 0.01 1.31E-03 0.633 0.476 
tswF8 f-tsw38 8.1E-13 1.1E-02 0.01 1.75E-03 0.633 0.476 
tswFv f-tsw9v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
tswFz f-tsw9z 8.1E-13 4.3E-03 0.01 1.5E-03 0.633 0.276 
ch1Fv f-ch1v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch1Fz f-ch1z 2.5E-14 1.6E-04 0.01 1.4E-03 0.633 0.276 
ch2Fv f-ch2v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch3Fv f-ch3v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch4Fv f-ch4v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch5Fv f-ch5v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch2Fz f-ch2z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.276 
ch3Fz f-ch3z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.276 
ch4Fz f-ch4z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.276 
ch5Fz f-ch5z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.276 
ch6Fv f-ch6v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch6Fz f-ch6z 2.5E-14 1.6E-04 0.01 1.4E-03 0.633 0.276 
pp4Fz f-pp4 2.5E-14 3.7E-04 0.01 1.88E-03 0.633 0.276 
pp3Fd f-pp3 2.2E-13 9.7E-04 0.01 1.32E-03 0.633 0.248 
pp2Fd f-pp2 2.2E-13 9.7E-04 0.01 2.80E-03 0.633 0.248 
pp1Fz f-pp1 2.5E-14 3.7E-04 0.01 6.39E-04 0.633 0.276 
bf3Fd f-bf3 2.2E-13 9.7E-04 0.01 1.91E-03 0.633 0.248 
bf2Fz f-bf2 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.276 
tr3Fd f-tr3 2.2E-13 9.7E-04 0.01 1.6E-03 0.633 0.248 
tr2Fz f-tr2 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 0.276 
DTN: LB0208UZDSCPLI.002 [DIRS 161788]. 
a 
Gamma value does not apply to matrix continuum. 
b 
Vitric units (those units ending with a v) do not have fractures. The fracture continuum properties are the 
same as those of the matrix continuum for these units. 
NOTE: The prefix m- stands for matrix and f- stands for fracture. 
ANL-EBS-MD-000049 REV 02 IV-18 October 2004 

Multiscale Thermohydrologic Model 
Table IV-6. Matrix and Fracture Properties for the Upper-Bound Infiltration Flux One-Dimensional Drift-
Scale Hydrologic Property Set 
Material 
Material name used in Residual 
name from 
DTN source 
LDTH 
submodels 
Permeability 
[m2] 
Porosity 
[-] 
saturation 
[-] 
a (alpha) 
[1/Pa] 
m 
[-] 
. (gamma) 
[-] 
tcwM1 m-tcw11 3.90E-15 0.241 0.02 1.23E-05 0.388 N/Aa 
tcwM2 m-tcw12 1.16E-19 0.088 0.20 3.39E-06 0.280 N/Aa 
tcwM3 m-tcw13 4.41E-16 0.200 0.31 3.25E-06 0.259 N/Aa 
ptnM1 m-ptn21 2.14E-14 0.387 0.24 1.56E-04 0.245 N/Aa 
ptnM2 m-ptn22 1.29E-11 0.428 0.13 1.33E-04 0.219 N/Aa 
ptnM3 m-ptn23 4.07E-14 0.233 0.07 2.39E-05 0.247 N/Aa 
ptnM4 m-ptn24 4.27E-12 0.413 0.14 5.62E-04 0.182 N/Aa 
ptnM5 m-ptn25 1.01E-12 0.498 0.06 9.48E-05 0.300 N/Aa 
ptnM6 m-ptn26 1.00E-11 0.490 0.05 5.23E-04 0.126 N/Aa 
tswM1 m-tsw31 1.77E-17 0.054 0.21 4.85E-05 0.218 N/Aa 
tswM2 m-tsw32 2.13E-16 0.157 0.07 1.96E-05 0.290 N/Aa 
tswM3 m-tsw33 2.39E-17 0.155 0.12 5.22E-06 0.283 N/Aa 
tswM4 m-tsw34 2.96E-19 0.111 0.19 1.65E-06 0.317 N/Aa 
tswM5 m-tsw35 8.55E-18 0.131 0.12 5.03E-06 0.216 N/Aa 
tswM6 m-tsw36 7.41E-19 0.103 0.20 1.08E-06 0.442 N/Aa 
tswM7 m-tsw37 7.41E-19 0.103 0.20 1.08E-06 0.442 N/Aa 
tswM8 m-tsw38 7.40E-18 0.043 0.42 5.58E-06 0.286 N/Aa 
tswMv m-tsw9v 2.24E-13 0.229 0.13 4.86E-05 0.293 N/Aa 
tswMz m-tsw9z 3.5E-17 0.275 0.36 4.61E-06 0.059 N/Aa 
ch1Mv m-ch1v 1.39E-12 0.331 0.06 8.82E-05 0.240 N/Aa 
ch1Mz m-ch1z 3.5E-17 0.285 0.38 2.12E-07 0.349 N/Aa 
ch2Mv m-ch2v 4.90E-11 0.346 0.06 2.73E-04 0.158 N/Aa 
ch3Mv m-ch3v 4.90E-11 0.346 0.06 2.73E-04 0.158 N/Aa 
ch4Mv m-ch4v 4.90E-11 0.346 0.06 2.73E-04 0.158 N/Aa 
ch5Mv m-ch5v 4.90E-11 0.346 0.06 2.73E-04 0.158 N/Aa 
ch2Mz m-ch2z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch3Mz m-ch3z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch4Mz m-ch4z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch5Mz m-ch5z 5.2E-18 0.322 0.26 2.25E-06 0.257 N/Aa 
ch6Mv m-ch6v 2.72E-13 0.331 0.06 1.67E-05 0.147 N/Aa 
ch6Mz m-ch6z 8.2E-19 0.271 0.36 1.56E-07 0.499 N/Aa 
pp4Mz m-pp4 1.02E-15 0.321 0.29 4.57E-07 0.474 N/Aa 
pp3Md m-pp3 1.26E-13 0.318 0.08 9.50E-06 0.407 N/Aa 
pp2Md m-pp2 1.70E-15 0.221 0.10 2.25E-06 0.309 N/Aa 
pp1Mz m-pp1 2.57E-15 0.297 0.30 8.77E-07 0.272 N/Aa 
bf3Md m-bf3 3.55E-14 0.175 0.11 3.48E-05 0.193 N/Aa 
bf2Mz m-bf2 8.1E-17 0.234 0.21 1.18E-07 0.617 N/Aa 
tr3Md m-tr3 1.1E-15 0.175 0.11 1.12E-05 0.193 N/Aa 
tr2Mz m-tr2 8.1E-17 0.234 0.21 1.18E-07 0.617 N/Aa 
tcwF1 f-tcw11 3.0E-11 2.4E-02 0.01 5.01E-03 0.633 5.00E-01 
tcwF2 f-tcw12 5.3E-12 1.7E-02 0.01 2.19E-03 0.633 5.00E-01 
tcwF3 f-tcw13 4.5E-12 1.3E-02 0.01 1.86E-03 0.633 5.00E-01 
ptnF1 f-ptn21 3.2E-12 9.2E-03 0.01 2.69E-03 0.633 1.00E-01 
ANL-EBS-MD-000049 REV 02 IV-19 October 2004 

Multiscale Thermohydrologic Model 
Table IV-6. Matrix and Fracture Properties for the Upper-Bound Infiltration Flux One-Dimensional Drift-
Scale Hydrologic Property Set (Continued) 
Material 
Material name used in Residual 
name from 
DTN source 
LDTH 
submodels 
Permeability 
[m2] 
Porosity 
[-] 
saturation 
[-] 
a (alpha) 
[1/Pa] 
m 
[-] 
. (gamma) 
[-] 
ptnF2 f-ptn22 3.0E-13 1.0E-02 0.01 1.38E-03 0.633 1.00E-01 
ptnF3 f-ptn23 3.0E-13 2.1E-03 0.01 1.23E-03 0.633 1.00E-01 
ptnF4 f-ptn24 3.0E-12 1.0E-02 0.01 2.95E-03 0.633 1.00E-01 
ptnF5 f-ptn25 1.7E-13 5.5E-03 0.01 1.10E-03 0.633 1.00E-01 
ptnF6 f-ptn26 2.2E-13 3.1E-03 0.01 9.55E-04 0.633 1.00E-01 
tswF1 f-tsw31 8.1E-13 5.0E-03 0.01 1.58E-05 0.633 1.00E-01 
tswF2 f-tsw32 7.1E-13 8.3E-03 0.01 1.00E-04 0.633 5.61E-01 
tswF3 f-tsw33 7.8E-13 5.8E-03 0.01 1.58E-03 0.633 5.61E-01 
tswF4 f-tsw34 3.3E-13 8.5E-03 0.01 1.00E-04 0.633 5.70E-01 
tswF5 f-tsw35 9.1E-13 9.6E-03 0.01 5.78E-04 0.633 5.70E-01 
tswF6 f-tsw36 1.3E-12 1.3E-02 0.01 1.10E-03 0.633 5.70E-01 
tswF7 f-tsw37 1.3E-12 1.3E-02 0.01 1.10E-03 0.633 5.70E-01 
tswF8 f-tsw38 8.1E-13 1.1E-02 0.01 8.91E-04 0.633 5.70E-01 
tswFv f-tsw9v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
tswFz f-tsw9z 8.1E-13 4.3E-03 0.01 1.5E-03 0.633 5.00E-01 
ch1Fv f-ch1v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch1Fz f-ch1z 2.5E-14 1.6E-04 0.01 1.4E-03 0.633 5.00E-01 
ch2Fv f-ch2v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch3Fv f-ch3v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch4Fv f-ch4v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch5Fv f-ch5v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch2Fz f-ch2z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 5.00E-01 
ch3Fz f-ch3z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 5.00E-01 
ch4Fz f-ch4z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 5.00E-01 
ch5Fz f-ch5z 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 5.00E-01 
ch6Fv f-ch6v N/Ab N/Ab N/Ab N/Ab N/Ab N/Ab 
ch6Fz f-ch6z 2.5E-14 1.6E-04 0.01 1.4E-03 0.633 5.00E-01 
pp4Fz f-pp4 2.5E-12 3.7E-04 0.01 8.91E-04 0.633 5.00E-01 
pp3Fd f-pp3 2.2E-12 9.7E-04 0.01 1.66E-03 0.633 5.00E-01 
pp2Fd f-pp2 2.2E-13 9.7E-04 0.01 1.66E-03 0.633 5.00E-01 
pp1Fz f-pp1 2.5E-14 3.7E-04 0.01 8.91E-04 0.633 5.00E-01 
bf3Fd f-bf3 2.2E-13 9.7E-04 0.01 1.66E-03 0.633 5.00E-01 
bf2Fz f-bf2 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 5.00E-01 
tr3Fd f-tr3 2.2E-13 9.7E-04 0.01 1.6E-03 0.633 5.00E-01 
tr2Fz f-tr2 2.5E-14 3.7E-04 0.01 8.9E-04 0.633 5.00E-01 
DTN: LB0302UZDSCPUI.002 [DIRS 161787]. 
a 
Gamma value does not apply to matrix continuum. 
b Vitric units (those units ending with a v) do not have fractures. The fracture continuum properties are the same 
as those of the matrix continuum for these units. 
NOTE: The prefix m- stands for matrix and f- stands for fracture. 
ANL-EBS-MD-000049 REV 02 IV-20 October 2004 

Multiscale Thermohydrologic Model 
Table IV-7. Fracture Frequency and Fracture-to-Matrix Interface Area 
Material Name 
Fracture Frequency 
(m-1) 
Interface Area 
[m2/m3] 
tcw11 0.92 1.56 
tcw12 1.91 13.39 
tcw13 2.79 3.77 
ptn21 0.67 1.00 
ptn22 0.46 1.41 
ptn23 0.57 1.75 
ptn24 0.46 0.34 
ptn25 0.52 1.09 
ptn26 0.97 3.56 
tsw31 2.17 3.86 
tsw32 1.12 3.21 
tsw33 0.81 4.44 
tsw34 4.32 13.54 
tsw35 3.16 9.68 
tsw36 4.02 12.31 
tsw37 4.02 12.31 
tsw38 4.36 13.34 
tsw39 (tsw9v) NAa NAa 
tsw39 (tsw9z) 0.96 2.95 
ch1VI (ch1v) NAa NAa 
ch1Ze (ch1z) 0.04 0.11 
ch2VI (ch2v) NAa NAa 
ch3VI (ch3v) NAa NAa 
ch4VI (ch4v) NAa NAa 
ch5VI (ch5v) NAa NAa 
ch2Ze (ch2z) 0.14 0.43 
ch3Ze (ch3z) 0.14 0.43 
ch4Ze (ch4z) 0.14 0.43 
ch5Ze (ch5z) 0.14 0.43 
ch6VI (ch6v) NAa NAa 
ch6 (ch6z) 0.04 0.11 
pp4 0.14 0.43 
pp3 0.20 0.61 
pp2 0.20 0.61 
pp1 0.14 0.43 
bf3 0.20 0.61 
bf2 0.14 0.43 
tr3 0.20 0.61 
tr2 0.14 0.43 
DTN: LB0205REVUZPRP.001 [DIRS 159525] 
a 
Vitric units (those units ending with a VI or a v) do not have 
fractures; therefore, fracture properties do not pertain to those units. 
NOTE: In parentheses are the material names used in the LDTH 
submodels of this report. 
ANL-EBS-MD-000049 REV 02 IV-21 October 2004 

Multiscale Thermohydrologic Model 
Table IV-8. Bulk Density of 4-10 Crushed Tuff 
Row number Mass density (gm/cm3) 
321 1.3 
322 1.2 
323 1.3 
324 1.3 
325 1.3 
326 1.2 
327 1.3 
328 1.2 
329 1.3 
330 1.2 
331 1.2 
332 1.2 
333 1.3 
334 1.3 
335 1.3 
336 1.3 
337 1.3 
338 1.2 
339 1.2 
340 1.2 
341 1.3 
342 1.3 
343 1.3 
344 1.3 
345 1.3 
346 1.3 
347 1.3 
348 1.3 
349 1.3 
350 1.2 
351 1.3 
352 1.3 
353 1.3 
354 1.2 
355 1.3 
356 1.3 
357 1.2 
358 1.2 
359 1.2 
360 1.3 
361 1.3 
362 1.3 
363 1.3 
364 1.2 
365 1.2 
366 1.2 
367 1.3 
368 1.3 
369 1.3 
370 1.3 
DTN: GS020183351030.001 [DIRS 163107], rows 321-370. 
NOTE: The average mass density for the 50 samples is 
1.27 gm/cm3, which is the value used for the 
crushed-tuff invert. 
ANL-EBS-MD-000049 REV 02 IV-22 October 2004 

Multiscale Thermohydrologic Model 
Table IV-9. Specific heat and thermal conductivity of 4-10 crushed tuff 
Row number Specific heat 
(J/cm3-C) 
Thermal conductivity 
(W/m C) 
1 0.82 0.17 
2 0.84 0.14 
3 0.98 0.17 
4 0.98 0.17 
5 0.99 0.17 
6 0.92 0.16 
7 0.96 0.17 
8 0.86 0.15 
9 0.88 0.16 
10 1.06 0.17 
11 0.94 0.17 
DTN: GS000483351030.003 [DIRS 152932], rows 1-11 
NOTE: The average specific heat for the 11 samples is 0.93 
J/cm3-C, which is the value used for the crushed-tuff 
invert. The average thermal conductivity for the 11 
samples is 0.2 W/m-C, which is the averaged valued 
rounded up to the nearest tenths; this rounded averaged 
value is used for the crushed-tuff invert. 
ANL-EBS-MD-000049 REV 02 IV-23 October 2004 

Multiscale Thermohydrologic Model 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000049 REV 02 IV-24 October 2004 

Multiscale Thermohydrologic Model 
APPENDIX V 
BUILDING SUBMODEL INPUT FILES 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
SMT Submodel 
The SMT submodel has the following information in this order: 
1. Time information (starttime, stoptime, timestepsize) 
2. Material properties (in the form of a rocktab file; see Appendix IV) 
3. Output information (for .ext time-history output; this is readable by XTOOL v10.1) 
4. Heat generation information (in the form of a heatgen file; see Appendix III) 
5. Restart file information 
6. Boundary-conditions 
7. Initial conditions 
8. SMT submodel mesh file (in the form of an SMT submodel mesh file; see Appendix I) 
9. Run control parameters 
All parameter values are taken directly from inputs or calculations described in other 
Appendices. An example of an SMT submodel NUFT usnt-option input file follows below. For 
more information, see the NUFT documentation (Nitao 1998 [DIRS 100474]). 
(usnt
(title "* YMP Site-Scale 3D Model, Conduction-Only Post-Emplacement Run")
;; AML = 55 MTU/acre;; ventilation + post-closure run for MSTHM for the License Application;; rotated mesh explicitly representing emplacement drifts;; Western Model representing Panels 1, 2E, 2W, 3, and 5;; conduction only
(modelname usnt)
(include-pkg "thermcon.pkg")
;; single-comp (air), single-phase (gas) pkg for cond-only run
(tstop 20100y)
(time 0)
(stepmax 1000000)
(dtmax 1.0e25)
(dt 1e2)
;; include thermal properties
(rocktab(include "/data34/TSPA03/physical_properties/SDT-1Dds-03") ;; read rocktab data(include "/data34/TSPA03/physical_properties/SMT-1Dds-fl-03") ;; read rocktab data(include "/data34/TSPA03/physical_properties/SMT-1Dds-sz-03") ;; read rocktab data
) ;; end rocktab 
;;
;; ************************************************************************ 
(output
(extool (variables T ) ;; repository node temperatures
(file-ext ".lvl.ext")(range "*#*:*:1")
(outtimes
(include "/data34/TSPA03/outputTimes/outputTimes-SMT-55-01")
)
)
) ;; end output;; ************************************************************************ 
;; include heat curves in srctab 
;; (srctab
(include"/data34/TSPA03/heatgen/SMT_blocks/preliminary_DTN2/SMT_LA_includes01")
;; ) ;; end srctab;; ************************************************************************
;; read restart file 
ANL-EBS-MD-000049 REV 02 V-1 October 2004 

Multiscale Thermohydrologic Model 
(read-restart
(file "/data34/TSPA03/SMT/SMT55/03-150w-i/SMT55-03-150w-i.rst") 
(time 1.0e6y)) 
;; ************************************************************************
(bctab
(top 
(range "at*") 
(clamped))
(bottom 
(range "bs*") 
(clamped))
) ;; end bctab;; ************************************************************************
;; set initial conditions;; (state;; P by-key ("*" 1.0e5))
;; (T by-key;; (include "/data34/TSPA03/BoundaryConditions/preliminary_DTN/smtUpperBC.out")
;; (include "/data34/TSPA03/BoundaryConditions/preliminary_DTN/smtLowerBC.out")
;; )
;; ) ;; end state;; **************************************************************************
(mesh-file "/data34/TSPA03/smt_mesh/preliminary_DTN/tspa03.mesh03-150w")
;; read mesh and connection data;; ************************************************************************** 
(include "/data30/TSPA01/run_control_param/run_control_param_SMT-v01"))
;; end of model 
LDTH submodel 
For the LDTH submodel input files, a calculation (in addition to those described in other 
Appendices) must be made to convert the percolation flux from mm/yr to kg/m2/sec. An 
example of this calculation is: 
3
J=4.1884 mm/yr (1 day/86,400 sec)(1 yr/365.25 days)(m/1,000 mm)(1,000 kg/m) = 1.327410-7 kg/m2/sec 
The LDTH submodel has the following information in this order: 
1. Header information (lines preceded by a semicolon) 
2. Time information (start time, stop time, timestepsize) 
3. Convergence tolerance information 
4. Output file (for .ext time-history output; this is readable by XTOOL v10.1) 
5. Material properties (in the form of rocktab files; see Appendix IV) 
6. Percolation flux information (see the flux conversion mm/yr to kg/m2/sec noted above) 
7. Heat generation information (in the form of a heatgen file; see Appendix III) 
8. Boundary-conditions 
9. Restart conditions (optional) 
10. Initial conditions (optional) 
11. Mesh information for matrix continuum 
12. Radcon information for matrix continuum (in the form of a file for doing thermal-
radiation connections, see Appendix VI) 
13. Mesh information for fracture continuum 
14. Run control parameters 
ANL-EBS-MD-000049 REV 02 V-2 October 2004 

Multiscale Thermohydrologic Model 
All parameter values are taken directly from inputs or calculations described in other appendices. 
An example of an DDT submodel NUFT usnt-option input file (P1R10C8-LDTH14-1Dds_mc-
mi-02.in) follows below. For more information, see the NUFT documentation (Nitao 1998 
[DIRS 100474]). LDTH submodel input files follow the naming convention P(x)R(y)C(z)-
LDTH(aml)-1Dds_mc-(percolation)i-0(property set).in. For the three infiltration flux cases, 
there are 2,592 input files including 1,296 initialization runs and 1,296 postemplacement runs. 
These files are found in DTN: LL030808623122.036. 
;; This Model was produced on 
;; Thu May 22 18:12:31 PDT 2003 
;; Implicit DKM with active fracture concept (AFC) 
;; NBS material properties from 1D drift-scale infiltration flux property set 
;; AML = 13.705 MTU/acre; half drift spacing = 162.0 m 
;; P1R10C8.col.units 
;; COLUMN INFORMATION (x,y = 171232.891, 233883.719) WORLD COLUMN h44 
;; unitthickness (m) 
;; 
;; tcw11 0.059 
;; tcw12 77.988 
;; tcw13 5.771 
;; ptn21 3.867 
;; ptn22 5.303 
;; ptn23 1.670 
;; ptn24 8.643 
;; ptn25 18.486 
;; ptn26 12.832 
;; tsw31 1.904 
;; tsw32 52.070 
;; tsw33 85.734 
;; tsw34 33.656 
;; tsw35 101.756 
;; tsw36 36.992 
;; tsw37 18.486 
;; tsw38 16.699 
;; tsw9v 1.904 
;; tsw9z 0.000 
;; ch1v 0.000 
;; ch1z 16.787 
;; ch2v 0.000 
;; ch3v 0.000 
;; ch4v 0.000 
;; ch5v 0.000 
;; ch2z 21.299 
;; ch3z 21.299 
;; ch4z 21.299 
;; ch5z 21.299 
;; ch6v 0.000 
;; ch6z 17.461 
;; pp4 12.949 
;; pp3 8.320 
;; pp2 0.000 
;; pp1 0.000 
;; bf3 0.000 
;; bf2 0.000 
;; tr3 0.000 
;; tr2 0.000 
;; repository elevation (m): 1069.300 
;; host rock: tsw34 
;; meters of host rock (tsw34) above repository: 12.001 
;; meters of host rock (tsw34) below repository: 21.656 
;; overburden thickness (m): 286.329 
;; distance from repository plane to top of chn (m): 197.494 
ANL-EBS-MD-000049 REV 02 V-3 October 2004 

Multiscale Thermohydrologic Model 
;; distance from repository plane to top of water table (m): 338.206 
(usnt 
(title "4.1883590e+00mm_yr,line-load,AML=14mtu_acre,LDTH14_1Dds_mc-mi") 
(modelname usnt) 
(tstop 20100y) 
(time 0y) 
(stepmax 1000000) 
(dtmax 1.000e+25) 
(dt 1e2) 
(tolerconv (P 5000.)(S 0.005)(X 0.005)(T 0.5)) 
;; absolute NR conv. tolerance 
(reltolerconv (P 0.005)(S 0.0)(X 0.0)(T 1.e-3)) 
(tolerdt (P 2.e4)(S 0.35)(X 0.25)(T 10.)) 
(reltolerdt (P 0.1)(S 0.0)(X 0.0)(T 0.0)) 
;; trying with harmonic mean everywhere which means 
;; turning off the geometric before vtough.pkg gets called. 
(diffusion-geo-mean off) 
;; for imp-DKM do not have this so that it will default to 
;; harmonic for fract-matrix interaction 
;;(mult-cont-diff-harmonic off) 
;; following has to come after tolerances 
(rmstolerconv 1e-4) 
(include-pkg "vtough.pkg") 
(check-mult-con off ) 
;; 
**************************************************************************************
************* 
(output 
(extool (continuum f) 
(variables T S.liquid X.air.gas RH Pc.liquid P.gas qPhChg.water.gas 
QPhChg.water.gas q.liquid q.water.gas q.air.gas) 
(file-ext ".f.EBS.ext")(range "*hstrk*.f*" "dr*.f*" "*in*.f*" 
"*wp*.f*") 
(outtimes 
(include "/data34/TSPA03/outputTimes/outputTimes-LDTH-SDT-DDT-14-01") 
) 
) 
(extool (continuum m) 
(variables T S.liquid X.air.gas RH Pc.liquid P.gas qPhChg.water.gas 
QPhChg.water.gas q.liquid q.water.gas q.air.gas) 
(file-ext ".m.EBS.ext")(range "*hstrk*.m*" "dr*.m*" "*in*.m*" 
"*wp*.m*") 
(outtimes 
(include "/data34/TSPA03/outputTimes/outputTimes-LDTH-SDT-DDT-14-01") 
) 
) 
) ;; end output 
;; ********************************************************************************** 
(rocktab 
(include "/data34/TSPA03/physical_properties/dkm-afc-1Dds-mc-mi-04") 
(include "/data34/TSPA03/physical_properties/dkm-afc-EBS-mi-03") 
) ;; close rocktab 
(include "/data34/TSPA03/physical_properties/modpropTSPA03_01_14") 
;; ********************************************************************************** 
;; This srctab is adjusted to allocate percolation to just the fracture. 
(srctab 
(compflux 
(comp water) 
(name infil) 
(range "*.f*:*:2") 
(mult-by-area z) 
(allocate-by-element ("*" 1.0)) 
(table 0.0 1.3274464e-07 600.00y 1.3274464e-07 ;;4.1883590e+00 mm/yr 
600.001y 2.4720940e-07 2000.00y 2.4720940e-07 ;;7.7999510e+00 mm/yr 
ANL-EBS-MD-000049 REV 02 V-4 October 2004 

Multiscale Thermohydrologic Model 
2000.001y 3.6606447e-07 1.0e30 3.6606447e-07);;1.1550066e+01 mm/yr 
(enthalpy 0.0 7.1314900e+04 1E+30 7.1314900e+04 ) 
) 
(include "/data34/TSPA03/heatgen/SDT_LDTH_blocks/preliminary_DTN/P1R10C8_LDTH-SDT") 
) ;; end srctab 
;; set boundary conditions 
(bctab 
(atmos 
(range "at*") 
(basephase gas) 
(tables 
(T 0.0 1.6984000e+01 1.0e30 1.6984000e+01 ) 
(S.liquid 0.0 0.0 1.0e30 0.0 ) 
(P 0.0 8.5705180e+04 1.0e30 8.5705180e+04 ) 
(X.air 0.0 9.8582710e-01 1.0e30 9.8582710e-01 ) 
) 
) 
(gwater 
(range "wt*") 
(basephase liquid) 
(tables 
(T 0 3.2083000e+01 1.0e30 3.2083000e+01) 
(S.liquid 0 1.0 1.0e30 1.0) 
(P 0 9.1988930e+04 1.0e30 9.1988930e+04) 
(X.air 0 1.0e-6 1.0e30 1.0e-6) 
)
;; SET PHASEFACTOR GAS TO 0, AND LIQUID TO 1 
(phasefactor 
(gas 0 0.0 1.0e30 0.0) 
(liquid 0 1.0 1.0e30 1.0) 
) 
) 
) ;; end bctab 
;; set initial conditions. 
(read-restart (time 3.15576e20) 
(file "/data33/TSPA03/LDTH/LDTH14/1Dds_mc-mi/02i/P1R10C8-LDTH14-1Dds_mc-mi-02i.res")) 
(overwrite-restart 
(X.air by-key ("dr*" 1.0)("*wp*" 1.0)("*in*" 1.0)) 
(S.liquid by-key ("dr*" 0.0)("*wp*" 0.0)("*in.m*" 0.9)("*in.f*" 0.1)) 
) ;; end overwrite 
;;This is for a unit symmetry cell with a half drift and half pillar 
;;between drifts. 
(genmsh 
(anisotropic) 
(down 0. 0. 1.0) 
(coord rect) 
(multi-continua 
(type rocktab) 
(continuum (name m) 
;; 13.705 MTU/acre 
(dx 0.580 0.370 0.3025 0.4222 0.4222 0.350 0.3031 0.35 0.5 0.9 
1.0 1.5 2.5 4.0 7.0 13.0 24.00 42.0 62.5) 
(dy 1.0) 
(dz 
1.0e-30 0.059 17.988 30.000 30.000 ;; 1-5: atm tcw11 tcw12 tcw12 tcw12 
5.771 3.867 5.303 1.670 8.643 ;; 6- 10: tcw13 ptn21 ptn22 ptn23 ptn24 
18.486 12.832 1.904 17.070 15.000 ;; 11- 15: ptn25 ptn26 tsw31 tsw32 tsw32 
10.000 10.000 7.734 6.000 6.000 ;; 16- 20: tsw32 tsw32 tsw33 tsw33 tsw33 
6.000 6.000 6.000 6.000 6.000 ;; 21- 25: tsw33 tsw33 tsw33 tsw33 tsw33 
6.000 6.000 6.000 6.000 3.000 ;; 26- 30: tsw33 tsw33 tsw33 tsw33 tsw33 
3.000 3.000 3.000 1.500 2.000 ;; 31- 35: tsw33 tsw33 tsw33 tsw34 tsw34 
1.000 1.000 0.500 0.300 0.200 ;; 36- 40: tsw34 tsw34 tsw34 tsw34 tsw34 
0.200 0.200 0.200 0.200 0.200 ;; 41- 45: tsw34 tsw34 tsw34 tsw34 tsw34 
0.200 0.200 0.200 0.200 0.200 ;; 46- 50: tsw34 tsw34 tsw34 tsw34 tsw34 
0.108 0.242 0.400 0.759 0.760 ;; 51- 55: tsw34 tsw34 tsw34 tsw34 tsw34 
0.425 0.403 0.403 0.800 1.200 ;; 56- 60: tsw34 tsw34 tsw34 tsw34 tsw34 
1.500 2.500 3.000 3.000 6.000 ;; 61- 65: tsw34 tsw34 tsw34 tsw34 tsw34 
3.656 6.000 6.000 6.000 6.000 ;; 66- 70: tsw34 tsw35 tsw35 tsw35 tsw35 
6.000 6.000 6.000 6.000 6.000 ;; 71- 75: tsw35 tsw35 tsw35 tsw35 tsw35 
6.000 6.000 6.000 10.000 10.000 ;; 76- 80: tsw35 tsw35 tsw35 tsw35 tsw35 
9.756 15.000 20.000 1.992 18.486 ;; 81- 85: tsw35 tsw36 tsw36 tsw36 tsw37 
16.699 1.904 16.787 21.299 21.299 ;; 86- 90: tsw38 tsw9v ch1z ch2z ch3z 
21.299 21.299 17.461 12.949 8.320 ;; 91- 95: ch4z ch5z ch6z pp4 pp3 
ANL-EBS-MD-000049 REV 02 V-5 October 2004 

Multiscale Thermohydrologic Model 
1.0e-30 ;; 96- 96: wt 
) 
(mat 
(atm atm 
(tcw11 m-tcw11 
(tcw12 m-tcw12 
(tcw13 m-tcw13 
(ptn21 m-ptn21 
(ptn22 m-ptn22 
(ptn23 m-ptn23 
(ptn24 m-ptn24 
(ptn25 m-ptn25 
(ptn26 m-ptn26 
(tsw31 m-tsw31 
(tsw32 m-tsw32 
(tsw33 m-tsw33 
(tsw34 m-tsw34 
(tsw35 m-tsw35 
(tsw36 m-tsw36 
(tsw37 m-tsw37 
(tsw38 m-tsw38 
(tsw9v m-tsw9v 
(ch1z m-ch1z 
(ch2z m-ch2z 
(ch3z m-ch3z 
(ch4z m-ch4z 
(ch5z m-ch5z 
(ch6z m-ch6z 
(pp4 m-pp4 
(pp3 m-pp3 
(wt m-pp3 
(hstrk m-tsw34 
(dr m-dr 
(dr m-dr 
(dr m-dr 
(dr m-dr 
(dr m-dr 
(dr m-dr 
(dr m-dr 
(dr m-dr 
(wp lsnf 
(wp lsnf 
(wp lsnf 
;; invert 
(in m-invert1 
(in m-invert2 
) 
1 nx 1 ny 1 1) 
1 nx 1 ny 2 2) 
1 nx 1 ny 3 5) 
1 nx 1 ny 6 6) 
1 nx 1 ny 7 7) 
1 nx 1 ny 8 8) 
1 nx 1 ny 9 9) 
1 nx 1 ny 10 10) 
1 nx 1 ny 11 11) 
1 nx 1 ny 12 12) 
1 nx 1 ny 13 13) 
1 nx 1 ny 14 17) 
1 nx 1 ny 18 33) 
1 nx 1 ny 34 66) 
1 nx 1 ny 67 81) 
1 nx 1 ny 82 84) 
1 nx 1 ny 85 85) 
1 nx 1 ny 86 86) 
1 nx 1 ny 87 87) 
1 nx 1 ny 88 88) 
1 nx 1 ny 89 89) 
1 nx 1 ny 90 90) 
1 nx 1 ny 91 91) 
1 nx 1 ny 92 92) 
1 nx 1 ny 93 93) 
1 nx 1 ny 94 94) 
1 nx 1 ny 95 95) 
1 nx 1 ny 96 96) 
1 nx 1 ny 34 61) 
1 1 1 ny 41 41) 
1 3 1 ny 42 42) 
1 4 1 ny 43 44) 
1 5 1 ny 45 46) 
1 6 1 ny 47 49) 
1 7 1 ny 50 54) 
1 6 1 ny 55 55) 
1 5 1 ny 56 56) 
1 1 1 ny 52 52) 
1 2 1 ny 53 53) 
1 3 1 ny 54 56) 
1 4 1 ny 57 57) 
1 2 1 ny 58 58) ;; bottom of invert 
(radcon 
(surface-offset 0 0 -3) 
(include "/data34/TSPA03/radcon/LDTH/preliminary_DTN/ldth0_300m.radcon") 
) ;; close radcon 
) ;; end continuum 
(continuum (name f) 
(flow-area-density ("*.f*" 1.0)) 
(LenFirst ("*.f*" 1.0)) ;; same as y-direction 
;; half-width of matrix block 
(Len ("*.f*" 1.0)) ;; same as y-direction 
;; half-width of fracture 
;; LenFirst and Len values are doubled here since 50% of cont-
len-fac 
;; is used in rocktab file 
;; 13.705 MTU/acre 
(dx 0.580 0.370 0.3025 0.4222 0.4222 0.350 0.3031 0.35 0.5 0.9 
1.0 1.5 2.5 4.0 7.0 13.0 24.00 42.0 62.5) 
dy 1.0) 
(dz 
1.0e-30 0.059 17.988 30.000 30.000 ;; 1-5: atm tcw11 tcw12 tcw12 tcw12 
5.771 3.867 5.303 1.670 8.643 ;; 6- 10: tcw13 ptn21 ptn22 ptn23 ptn24 
18.486 12.832 1.904 17.070 15.000 ;; 11- 15: ptn25 ptn26 tsw31 tsw32 tsw32 
10.000 10.000 7.734 6.000 6.000 ;; 16- 20: tsw32 tsw32 tsw33 tsw33 tsw33 
6.000 6.000 6.000 6.000 6.000 ;; 21- 25: tsw33 tsw33 tsw33 tsw33 tsw33 
6.000 6.000 6.000 6.000 3.000 ;; 26- 30: tsw33 tsw33 tsw33 tsw33 tsw33 
3.000 3.000 3.000 1.500 2.000 ;; 31- 35: tsw33 tsw33 tsw33 tsw34 tsw34 
1.000 1.000 0.500 0.300 0.200 ;; 36- 40: tsw34 tsw34 tsw34 tsw34 tsw34 
0.200 0.200 0.200 0.200 0.200 ;; 41- 45: tsw34 tsw34 tsw34 tsw34 tsw34 
ANL-EBS-MD-000049 REV 02 V-6 October 2004 

Multiscale Thermohydrologic Model 
0.200 0.200 0.200 0.200 
0.108 0.242 0.400 0.759 
0.425 0.403 0.403 0.800 
1.500 2.500 3.000 3.000 
3.656 6.000 6.000 6.000 
6.000 6.000 6.000 6.000 
6.000 6.000 6.000 10.000 
9.756 15.000 20.000 1.992 
16.699 1.904 16.787 21.299 
21.299 21.299 17.461 12.949 
1.0e-30 
0.200 ;; 46- 50: tsw34 tsw34 tsw34 tsw34 tsw34 
0.760 ;; 51- 55: tsw34 tsw34 tsw34 tsw34 tsw34 
1.200 ;; 56- 60: tsw34 tsw34 tsw34 tsw34 tsw34 
6.000 ;; 61- 65: tsw34 tsw34 tsw34 tsw34 tsw34 
6.000 ;; 66- 70: tsw34 tsw35 tsw35 tsw35 tsw35 
6.000 ;; 71- 75: tsw35 tsw35 tsw35 tsw35 tsw35 
10.000 ;; 76- 80: tsw35 tsw35 tsw35 tsw35 tsw35 
18.486 ;; 81- 85: tsw35 tsw36 tsw36 tsw36 tsw37 
21.299 ;; 86- 90: tsw38 tsw9v ch1z ch2z ch3z 
8.320 ;; 91- 95: ch4z ch5z ch6z pp4 pp3 
;; 96- 96: wt 
) 
(mat 
(atm atm 1 nx 
(tcw11 f-tcw11 
(tcw12 f-tcw12 
(tcw13 f-tcw13 
(ptn21 f-ptn21 
(ptn22 f-ptn22 
(ptn23 f-ptn23 
(ptn24 f-ptn24 
(ptn25 f-ptn25 
(ptn26 f-ptn26 
(tsw31 f-tsw31 
(tsw32 f-tsw32 
(tsw33 f-tsw33 
(tsw34 f-tsw34 
(tsw35 f-tsw35 
(tsw36 f-tsw36 
(tsw37 f-tsw37 
(tsw38 f-tsw38 
(tsw9v f-tsw9v 
(ch1z f-ch1z 
(ch2z f-ch2z 
(ch3z f-ch3z 
(ch4z f-ch4z 
(ch5z f-ch5z 
(ch6z f-ch6z 
(pp4 f-pp4 
(pp3 f-pp3 
(wt f-pp3 
(hstrk f-tsw34 
(dr f-dr 
(dr f-dr 
(dr f-dr 
(dr f-dr 
(dr f-dr 
(dr f-dr 
(dr f-dr 
(dr f-dr 
(wp lsnf 
(wp lsnf 
(wp lsnf 
;; invert 
(in f-invert1 
(in f-invert2 
) 
) ;; end continuum 
) ;; end multi-continua 
) ;; end genmsh 
1 ny 1 1) 
1 nx 1 ny 2 2) 
1 nx 1 ny 3 5) 
1 nx 1 ny 6 6) 
1 nx 1 ny 7 7) 
1 nx 1 ny 8 8) 
1 nx 1 ny 9 9) 
1 nx 1 ny 10 10) 
1 nx 1 ny 11 11) 
1 nx 1 ny 12 12) 
1 nx 1 ny 13 13) 
1 nx 1 ny 14 17) 
1 nx 1 ny 18 33) 
1 nx 1 ny 34 66) 
1 nx 1 ny 67 81) 
1 nx 1 ny 82 84) 
1 nx 1 ny 85 85) 
1 nx 1 ny 86 86) 
1 nx 1 ny 87 87) 
1 nx 1 ny 88 88) 
1 nx 1 ny 89 89) 
1 nx 1 ny 90 90) 
1 nx 1 ny 91 91) 
1 nx 1 ny 92 92) 
1 nx 1 ny 93 93) 
1 nx 1 ny 94 94) 
1 nx 1 ny 95 95) 
1 nx 1 ny 96 96) 
1 nx 1 ny 34 61) 
1 1 1 ny 41 41) 
1 3 1 ny 42 42) 
1 4 1 ny 43 44) 
1 5 1 ny 45 46) 
1 6 1 ny 47 49) 
1 7 1 ny 50 54) 
1 6 1 ny 55 55) 
1 5 1 ny 56 56) 
1 1 1 ny 52 52) 
1 2 1 ny 53 53) 
1 3 1 ny 54 56) 
1 4 1 ny 57 57) 
1 2 1 ny 58 58) ;; bottom of invert 
;; ************************ Solver options **************************** 
(include "/data30/TSPA01/run_control_param/run_control_param_LDTH-v09") 
);; end of model input 
;; ********************* Done ***************************************** 
ANL-EBS-MD-000049 REV 02 V-7 October 2004 

Multiscale Thermohydrologic Model 
SDT submodel 
The SDT submodel has the following information in this order: 
1. Header information (lines preceded by a semicolon) 
2. Time information (start time, stop time, timestepsize) 
3. Output information (for .ext time-history output; this is a readable by XTOOL 
v10.1) 
4. Material properties (in the form of a rocktab file, see Appendix IV) 
5. Heat generation information (in the form of a heatgen file, see Appendix III) 
6. Boundary-conditions 
7. Initial conditions (state command) 
8. SDT submodel mesh file (in the form of an SDT submodel mesh file, see Appendix I) 
All parameter values are taken directly from inputs or calculations described in other appendices. 
An example of an SDT submodel NUFT input file (P5415C8-SDT27-00-01.in) follows. For 
more information, see the NUFT documentation (Nitao 1998 [DIRS 100474]). SDT submodel 
input files follow the naming convention P(x)R(y)C(z)-SDT(aml)-00-01.in. Note that only one 
set of SDT submodels to cover all three infiltration flux cases (lower-bound, mean, and upper-
bound), thus, there are 540 input files, which includes 108 initialization runs and 324 
postemplacement runs. These files are found in DTN: LL030808623122.036. 
;; /data34/TSPA03/chimney_mesh/SDT/preliminary_DTN/P5R16C8-SDT27-00-01.in;; was produced on;; Wed Apr 23 09:48:11 PDT 2003;; Conduction-only for smeared-heat-source cases;; AML = 27 MTU/acre; half drift spacing = 81.00 m;; use tcond_wet for both solid and gas pgases. 
;; P5R16C8.col.units 
;; COLUMN INFORMATION (x,y = 171137.797, 232234.609) WORLD COLUMN q47 
;; unitthickness (m) 
;; _________________ 
;; tcw11 
;; tcw12 
;; tcw13 
;; ptn21;; ptn22;; ptn23;; ptn24;; ptn25;; ptn26;; tsw31 
;; tsw32 
;; tsw33 
;; tsw34 
;; tsw35 
;; tsw36 
;; tsw37 
;; tsw38 
;; tsw9v 
;; tsw9z 
;; ch1v 
;; ch1z 
0.000 
68.320 
5.039 
3.105 
0.000 
0.000 
3.809 
3.867 
10.195 
1.992 
32.041 
69.281 
35.906 
86.696 
43.164 
21.553 
9.082 
9.023 
0.000 
22.529 
0.000 
ANL-EBS-MD-000049 REV 02 V-8 October 2004 

Multiscale Thermohydrologic Model 
;; ch2v 14.326 
;; ch3v 14.326 
;; ch4v 0.000 
;; ch5v 14.326 
;; ch2z 0.000 
;; ch3z 0.000 
;; ch4z 14.355 
;; ch5z 0.000 
;; ch6v 0.000 
;; ch6z 14.971 
;; pp4 8.643 
;; pp3 33.545 
;; pp2 23.760 
;; pp1 25.049 
;; bf3 0.000 
;; bf2 0.000 
;; tr3 0.000 
;; tr2 0.000 
;; repository elevation (m): 1091.500 
;; host rock: tsw34 
;; meters of host rock (tsw34) above repository: 29.906 
;; meters of host rock (tsw34) below repository: 6.000 
;; overburden thickness (m): 227.556 
;; distance from repository plane to top of chn (m): 175.518 
;; distance from repository plane to top of water table (m): 361.347 
(usnt
(title "AML=27mtu_acre,SDT27,00")
(modelname usnt) 
(include-pkg "thermcon.pkg")
;; single-comp (air), single-phase (gas) pkg for cond-only run(tstop 20100y)
(time 0)
(stepmax 1000000)
(dtmax 1.728e+18)
(dt 1e2) 
;; ********************************************************************************** 
(output(extool (variables T)
(file-ext ".ext")(range "*")
(outtimes(include "/data34/TSPA03/outputTimes/outputTimes-LDTH-SDT-DDT-27-01")
)
) 
) 
;;********************* ************************************************************
(rocktab
(include "/data34/TSPA03/physical_properties/SDT-1Dds-03")
) ;; close rocktab;;************************************************ ********************************** 
;; There is no percolation for the conduction-only case(srctab(include "/data34/TSPA03/heatgen/SDT_LDTH_blocks/preliminary_DTN/P5R16C8_LDTH-SDT")
) ;; end srctab;;******************************************** ************************************** 
;; set boundary conditions 
ANL-EBS-MD-000049 REV 02 V-9 October 2004 

Multiscale Thermohydrologic Model 
(bctab
(atmos 
(range "at*") 
(clamped)
)
(gwater 
(range "wt*") 
(clamped)
)
) ;; end bctab 
;;***********************************************************************************
(state(include "/data34/TSPA03/SDT/SDT66/00/00i/P5R16C8-SDT-00i.ztable")
) ;; end state;;***********************************************************************************
(genmsh
(down 0. 0. 1.0)
(coord rect)
(dx 81.00)
(dy 1.0)
(dz
1.0e-30 8.320 30.000 30.000 5.039 ;; 1 - 5: atm tcw12 tcw12 tcw12 tcw13 
3.105 3.809 3.867 10.195 1.992 ;; 6 - 10: ptn21 ptn24 ptn25 ptn26 tsw31 
12.041 10.000 10.000 3.281 6.000 ;; 11 - 15: tsw32 tsw32 tsw32 tsw33 tsw33 
6.000 6.000 6.000 6.000 6.000 ;; 16 - 20: tsw33 tsw33 tsw33 tsw33 tsw33 
6.000 6.000 6.000 6.000 6.000 ;; 21 - 25: tsw33 tsw33 tsw33 tsw33 tsw33 
5.906 6.000 6.000 6.010 5.990 ;; 26 - 30: tsw34 tsw34 tsw34 tsw34 tsw34 
6.000 6.000 6.000 6.000 6.000 ;; 31 - 35: tsw34 tsw35 tsw35 tsw35 tsw35 
6.000 6.000 6.000 6.000 6.000 ;; 36 - 40: tsw35 tsw35 tsw35 tsw35 tsw35 
6.000 6.000 6.000 6.000 4.348 ;; 41 - 45: tsw35 tsw35 tsw35 tsw35 tsw35 
4.348 10.000 10.000 15.000 8.164 ;; 46 - 50: tsw35 tsw36 tsw36 tsw36 tsw36 
20.000 1.553 9.082 9.023 22.529 ;; 51 - 55: tsw37 tsw37 tsw38 tsw9v ch1v 
14.326 14.326 14.355 14.326 14.971 ;; 56 - 60: ch2v ch3v ch4z ch5v ch6z 
8.643 30.000 30.000 30.000 30.000 ;; 61 - 65: pp4 pp3 pp3 pp2 pp1 
1.0e-30 ;; 66 - 66: wt 
)
(mat( atm atm 1 nx 1 ny 1 1)
( tcw12 tcw12 1 nx 1 ny 2 4)
( tcw13 tcw13 1 nx 1 ny 5 5)
( ptn21 ptn21 1 nx 1 ny 6 6)
( ptn24 ptn24 1 nx 1 ny 7 7)
( ptn25 ptn25 1 nx 1 ny 8 8)
( ptn26 ptn26 1 nx 1 ny 9 9)
( tsw31 tsw31 1 nx 1 ny 10 10)
( tsw32 tsw32 1 nx 1 ny 11 13)
( tsw33 tsw33 1 nx 1 ny 14 25)
( tsw34 tsw34 1 nx 1 ny 26 31)
( tsw35 tsw35 1 nx 1 ny 32 46)
( tsw36 tsw36 1 nx 1 ny 47 50)
( tsw37 tsw37 1 nx 1 ny 51 52)
( tsw38 tsw38 1 nx 1 ny 53 53)
( tsw9v tsw9v 1 nx 1 ny 54 54)
( ch1v ch1v 1 nx 1 ny 55 55)
( ch2v ch2v 1 nx 1 ny 56 56)
( ch3v ch3v 1 nx 1 ny 57 57)
( ch4z ch4z 1 nx 1 ny 58 58)
( ch5v ch5v 1 nx 1 ny 59 59)
( ch6z ch6z 1 nx 1 ny 60 60)
( pp4 pp4 1 nx 1 ny 61 61)
( pp3 pp3 1 nx 1 ny 62 63)
( pp2 pp2 1 nx 1 ny 64 64)
( pp1 pp1 1 nx 1 ny 65 65)
( wt pp1 1 nx 1 ny 66 66)
(wp tsw34 1 nx 1 ny 30 30)
)
) ;; end genmsh 
ANL-EBS-MD-000049 REV 02 V-10 October 2004 

Multiscale Thermohydrologic Model 
;; Use this for the 1-D, 2-D cases(linear-solver d4vband) 
);; end of model input 
DDT submodel 
The DDT submodel has the following information in this order: 
1. header information (lines preceded by a semicolon) 
2. time information (start time, stop time, timestepsize) 
3. output information (for .ext time-history output this is a readable by XTOOL v10.1) 
4. material properties (in the form of a rocktab file, see Appendix IV) 
5. heat generation information (in the form of a heatgen file, see Appendix III) 
6. boundary-conditions 
7. restart file information 
8. initial conditions 
9. DDT mesh file 
10. radcon information (in the form of a file for doing thermal-radiation connections, see 
Appendix VI) 
11. run control parameters 
All parameter values are taken directly from inputs or calculations described in other appendices. 
An example of an DDT submodel NUFT input file (P2WR5C10-DDT55-01-1e11.in) follows 
below. The interested reader is referred to the NUFT documentation (Nitao 1998 [DIRS 
100474]) for specific details of this input file. 
DDT submodel input files are found in DTN: LL030808623122.036. The names of these files 
are: 
P2WR5C10-DDT14-01v.in 
P2WR5C10-DDT27-01v.in 
P2WR5C10-DDT55-01v.in 
P2WR5C10-DDT66-01v.in 
P2WR5C10-DDT66-03.in 
P2WR5C10-DDT55-03.in 
P2WR5C10-DDT27-03.in 
P2WR5C10-DDT14-03.in 
;; Implicit DKM with active fracture concept (AFC) 
;; NBS material properties from 1D drift-scale mean infiltration flux property set 
;; AML = 54.82 MTU/acre; half drift spacing = 40.5 m 
;; represents 8 WPs: 6 full WPs and 2 half WPs 
;; P2WR5C10.col.units 
;; COLUMN INFORMATION (x,y = 170730.297, 234912.719) WORLD COLUMN g_9 
;; unitthickness (m) 
;; _________________ 
;; tcw11 0.000 
;; tcw12 20.244 
;; tcw13 4.014 
;; ptn21 7.207 
;; ptn22 5.596 
;; ptn23 2.021 
;; ptn24 12.510 
ANL-EBS-MD-000049 REV 02 V-11 October 2004 

Multiscale Thermohydrologic Model 
;; ptn25 36.504 
;; ptn26 11.279 
;; tsw31 1.992 
;; tsw32 45.586 
;; tsw33 85.252 
;; tsw34 32.954 
;; tsw35 104.719 
;; tsw36 25.828 
;; tsw37 12.914 
;; tsw38 21.904 
;; tsw9v 0.000 
;; tsw9z 6.592 
;; ch1v 0.000 
;; ch1z 15.039 
;; ch2v 0.000 
;; ch3v 0.000 
;; ch4v 0.000 
;; ch5v 0.000 
;; ch2z 20.293 
;; ch3z 20.303 
;; ch4z 20.273 
;; ch5z 20.303 
;; ch6v 0.000 
;; ch6z 17.578 
;; pp4 19.688 
;; pp3 14.326 
;; pp2 4.102 
;; pp1 0.000 
;; bf3 0.000 
;; bf2 0.000 
;; tr3 0.000 
;; tr2 0.000 
;; repository elevation (m): 1052.901 
;; host rock: tsw35 
;; meters of host rock (tsw35) above repository: 45.328 
;; meters of host rock (tsw35) below repository: 59.391 
;; overburden thickness (m): 310.485 
;; distance from repository plane to top of chn (m): 126.629 
;; distance from repository plane to top of water table (m): 278.533 
(usnt 
(title "line-load,AML=55mtu_acre,P2WR5C10-DDT55-01") 
(modelname usnt) 
(include-pkg "thermcon.pkg") 
;; single-comp (air), single-phase (gas) pkg for cond-only run 
(tstop 20100y) 
(time 50y) 
(stepmax 1000000) 
(dtmax 1.000e+25) 
(dt 1e2) 
(check-mult-con off) 
;; ******************************************************************************** 
(output 
(extool (variables T ) 
(file-ext ".EBS.ext")(range "hstrk*" "dr*" "dhlw*" "bwr*" "pwr*" "in*" "ds*") 
(outtimes 
(include "/data34/TSPA03/outputTimes/outputTimes-LDTH-SDT-DDT-55-01") 
) 
) 
) ;; end output 
;; ********************************************************************************* 
(rocktab 
(include "/data34/TSPA03/physical_properties/SDT-1Dds-03") 
(include "/data34/TSPA03/physical_properties/DDT-EBS_Rev500") 
) ;; close rocktab 
ANL-EBS-MD-000049 REV 02 V-12 October 2004 

Multiscale Thermohydrologic Model 
;; ********************************************************************************* 
;; There is no percolation for the conduction-only case 
(srctab 
(include "/data34/TSPA03/heatgen/DDT_blocks/preliminary_DTN/P2WR5C10_DDT") 
) ;; end srctab 
;;********************************************************************************** 
;; set boundary conditions 
(bctab 
(atmos 
(range "at*") 
(clamped) 
) 
(gwater 
(range "wt*") 
(clamped) 
) 
) ;; end bctab 
;;********************************************************************************** 
;; set initial conditions. 
(read-restart (time 50y) 
(file "/data34/TSPA03/DDT/DDTlab/01v/P2WR5C10-DDT55-01v.res")) 
;;********************************************************************************** 
;;This is for a unit symmetry cell with a half drift and half pillar 
;;between drifts. 
(genmsh 
(down 0. 0. 1.0) 
(coord rect) 
;; 54.82 MTU/acre 
(dx 0.7285 0.5125 0.015 0.4187 0.4222 0.350 0.3031 0.35 0.5 0.9 
1.0 1.5 2.5 3.0 5.0 7.0 9.250) 
;; the WP cross-sectional area is the same as 
;; for a 21-PWR AP WP with a diameter of 1.644 m 
;; the drip-shield width is 2.512 m 
;; the drip-shield half-width is 1.256 m 
(dy 1.29125 1.29125 ;; 1/2 21-PWR AP 2.5825 m j = 1-2 
0.1 ;; gap 0.1 m j = 3 
1.30425 2.60850 1.30425 ;; 5-DHLW Long 5.217 m j = 4-6 
0.1 ;; gap 0.1 m j = 7 
1.29125 2.58250 1.29125 ;; 21-PWR AP Hot 5.165 m j = 8-10 
0.1 ;; gap 0.1 m j = 11 
1.29125 2.58250 1.29125 ;; 44-BWR AP 5.165 m j = 12-14 
0.1 ;; gap 0.1 m j = 15 
1.29125 2.58250 1.29125 ;; 44-BWR AP 5.165 m j = 16-18 
0.1 ;; gap 0.1 m j = 19 
0.89750 1.79500 0.89750 ;; 5-DHLW Short 3.59 m j = 20-22 
0.1 ;; gap 0.1 m j = 23 
1.29125 2.58250 1.29125 ;; 21-PWR AP 5.165 m j = 24-26 
0.1 ;; gap 0.1 m j = 27 
1.29125 1.29125 ;; 1/2 44-BWR AP 2.5825 m j = 28-29 
) ;; total length of drift = 35.3320 m 
(dz 
1.0e-30 20.244 4.014 7.207 5.596 ;; 1-5: atm tcw12 tcw13 ptn21 ptn22 
2.021 12.510 6.504 30.000 11.279 ;; 6- 10: ptn23 ptn24 ptn25 ptn25 ptn26 
1.992 15.586 30.000 18.252 20.000 ;; 11- 15: tsw31 tsw32 tsw32 tsw33 tsw33 
15.000 10.000 10.000 6.000 6.000 ;; 16- 20: tsw33 tsw33 tsw33 tsw33 tsw33 
4.477 4.477 6.000 6.000 6.000 ;; 21- 25: tsw34 tsw34 tsw34 tsw34 tsw34 
6.000 3.328 6.000 6.000 6.000 ;; 26- 30: tsw34 tsw35 tsw35 tsw35 tsw35 
3.000 3.000 3.000 3.000 1.500 ;; 31- 35: tsw35 tsw35 tsw35 tsw35 tsw35 
2.000 1.000 1.000 0.500 0.300 ;; 36- 40: tsw35 tsw35 tsw35 tsw35 tsw35 
0.200 0.200 0.200 0.200 0.200 ;; 41- 45: tsw35 tsw35 tsw35 tsw35 tsw35 
0.200 0.200 0.200 0.200 0.200 ;; 46- 50: tsw35 tsw35 tsw35 tsw35 tsw35 
0.200 0.335 0.015 0.5975 0.7285 ;; 51- 55: tsw35 tsw35 tsw35 tsw35 tsw35 
0.7285 0.2895 0.403 0.403 0.800 ;; 56- 60: tsw35 tsw35 tsw35 tsw35 tsw35 
1.200 1.500 2.500 3.000 3.000 ;; 61- 65: tsw35 tsw35 tsw35 tsw35 tsw35 
6.000 6.000 6.000 6.000 6.000 ;; 66- 70: tsw35 tsw35 tsw35 tsw35 tsw35 
6.000 6.000 5.391 6.000 6.000 ;; 71- 75: tsw35 tsw35 tsw35 tsw36 tsw36 
6.000 3.914 3.914 6.000 6.914 ;; 76- 80: tsw36 tsw36 tsw36 tsw37 tsw37 
10.000 10.000 1.904 6.592 15.039 ;; 81- 85: tsw38 tsw38 tsw38 tsw9z ch1z 
20.000 0.293 20.303 20.273 20.303 ;; 86- 90: ch2z ch2z ch3z ch4z ch5z 
17.578 19.688 14.326 4.102 1.0e-30 ;; 91- 95: ch6z pp4 pp3 pp2 wt 
) 
(mat 
(atm atm 1 nx 1 ny 1 1) 
(tcw12 tcw12 1 nx 1 ny 2 2) 
(tcw13 tcw13 1 nx 1 ny 3 3) 
ANL-EBS-MD-000049 REV 02 V-13 October 2004 

Multiscale Thermohydrologic Model 
(ptn21 ptn21 1 nx 1 ny 4 4) 
(ptn22 ptn22 1 nx 1 ny 5 5) 
(ptn23 ptn23 1 nx 1 ny 6 6) 
(ptn24 ptn24 1 nx 1 ny 7 7) 
(ptn25 ptn25 1 nx 1 ny 8 9) 
(ptn26 ptn26 1 nx 1 ny 10 10) 
(tsw31 tsw31 1 nx 1 ny 11 11) 
(tsw32 tsw32 1 nx 1 ny 12 13) 
(tsw33 tsw33 1 nx 1 ny 14 20) 
(tsw34 tsw34 1 nx 1 ny 21 26) 
(tsw35 tsw35 1 nx 1 ny 27 73) 
(tsw36 tsw36 1 nx 1 ny 74 78) 
(tsw37 tsw37 1 nx 1 ny 79 80) 
(tsw38 tsw38 1 nx 1 ny 81 83) 
(tsw9z tsw9z 1 nx 1 ny 84 84) 
( ch1z ch1z 1 nx 1 ny 85 85) 
( ch2z ch2z 1 nx 1 ny 86 87) 
( ch3z ch3z 1 nx 1 ny 88 88) 
( ch4z ch4z 1 nx 1 ny 89 89) 
( ch5z ch5z 1 nx 1 ny 90 90) 
( ch6z ch6z 1 nx 1 ny 91 91) 
( pp4 pp4 1 nx 1 ny 92 92) 
( pp3 pp3 1 nx 1 ny 93 93) 
( pp2 pp2 1 nx 1 ny 94 94) 
(wt pp2 1 nx 1 ny 95 95) 
(hstrk tsw35 1 nx 1 ny 35 62) 
(dr drift 1 1 1 ny 42 42) 
(dr drift 1 3 1 ny 43 43) 
(dr drift 1 4 1 ny 44 45) 
(dr drift 1 5 1 ny 46 47) 
(dr drift 1 6 1 ny 48 50) 
(dr drift 1 7 1 ny 51 55) 
(dr drift 1 6 1 ny 56 56) 
(dr drift 1 5 1 ny 57 57) 
;; WP1 half 21-PWR PWR AP WP 
(dro_wp1 dro_wp1 1 1 1 3 42 42) 
(dro_wp1 dro_wp1 1 3 1 3 43 43) 
(dro_wp1 dro_wp1 1 4 1 3 44 45) 
(dro_wp1 dro_wp1 1 5 1 3 46 47) 
(dro_wp1 dro_wp1 1 6 1 3 48 50) 
(dro_wp1 dro_wp1 1 7 1 3 51 55) 
(dro_wp1 dro_wp1 1 6 1 3 56 56) 
(dro_wp1 dro_wp1 1 5 1 3 57 57) 
(dri_wp1 dri_wp1 1 2 1 3 54 57) 
(ds_pwr1-1 drpshld 1 3 1 2 53 53) 
(ds_pwr1-1 drpshld 3 3 1 2 54 57) 
(pwr1-1 pwr 1 1 1 2 55 56) 
(dr drift 1 1 3 3 55 56) 
;; Gap1 
(dr drift 1 1 3 3 55 56) 
(ds_gap1 drpshld 1 3 3 3 53 53) 
(ds_gap1 drpshld 3 3 3 3 54 57) 
;; WP2 full 5-DHLW Long WP 
(dro_wp2 dro_wp2 1 1 4 7 42 42) 
(dro_wp2 dro_wp2 1 3 4 7 43 43) 
(dro_wp2 dro_wp2 1 4 4 7 44 45) 
(dro_wp2 dro_wp2 1 5 4 7 46 47) 
(dro_wp2 dro_wp2 1 6 4 7 48 50) 
(dro_wp2 dro_wp2 1 7 4 7 51 55) 
(dro_wp2 dro_wp2 1 6 4 7 56 56) 
(dro_wp2 dro_wp2 1 5 4 7 57 57) 
(dri_wp2 dri_wp2 1 2 4 7 54 57) 
(ds_dhlw-l1 drpshld 1 3 4 6 53 53) 
(ds_dhlw-l1 drpshld 3 3 4 6 54 57) 
(dhlw-l1 dhlw-l 1 1 4 6 55 56) 
;; Gap2 
(dr drift 1 1 7 7 55 56) 
(ds_gap2 drpshld 1 3 7 7 53 53) 
(ds_gap2 drpshld 3 3 7 7 54 57) 
;; WP3 full 21-PWR AP Hot WP 
(dro_wp3 dro_wp3 1 1 8 11 42 42) 
(dro_wp3 dro_wp3 1 3 8 11 43 43) 
(dro_wp3 dro_wp3 1 4 8 11 44 45) 
ANL-EBS-MD-000049 REV 02 V-14 October 2004 

Multiscale Thermohydrologic Model 
(dro_wp3 dro_wp3 1 5 8 11 46 47) 
(dro_wp3 dro_wp3 1 6 8 11 48 50) 
(dro_wp3 dro_wp3 1 7 8 11 51 55) 
(dro_wp3 dro_wp3 1 6 8 11 56 56) 
(dro_wp3 dro_wp3 1 5 8 11 57 57) 
(dri_wp3 dri_wp3 1 2 8 11 54 57) 
(ds_pwr2-1 drpshld 1 3 8 10 53 53) 
(ds_pwr2-1 drpshld 3 3 8 10 54 57) 
(pwr2-1 pwr 1 1 8 10 55 56) 
;; Gap3 
(dr drift 1 1 11 11 55 56) 
(ds_gap3 drpshld 1 3 11 11 53 53) 
(ds_gap3 drpshld 3 3 11 11 54 57) 
;; WP4 full 44-BWR AP WP 
(dro_wp4 dro_wp4 1 1 12 15 42 42) 
(dro_wp4 dro_wp4 1 3 12 15 43 43) 
(dro_wp4 dro_wp4 1 4 12 15 44 45) 
(dro_wp4 dro_wp4 1 5 12 15 46 47) 
(dro_wp4 dro_wp4 1 6 12 15 48 50) 
(dro_wp4 dro_wp4 1 7 12 15 51 55) 
(dro_wp4 dro_wp4 1 6 12 15 56 56) 
(dro_wp4 dro_wp4 1 5 12 15 57 57) 
(dri_wp4 dri_wp4 1 2 12 15 54 57) 
(ds_bwr1-1 drpshld 1 3 12 14 53 53) 
(ds_bwr1-1 drpshld 3 3 12 14 54 57) 
(bwr1-1 bwr 1 1 12 14 55 56) 
;; Gap4 
(dr drift 1 1 15 15 55 56) 
(ds_gap4 drpshld 1 3 15 15 53 53) 
(ds_gap4 drpshld 3 3 15 15 54 57) 
;; WP5 full 44-BWR AP Adjusted WP 
(dro_wp5 dro_wp5 1 1 16 19 42 42) 
(dro_wp5 dro_wp5 1 3 16 19 43 43) 
(dro_wp5 dro_wp5 1 4 16 19 44 45) 
(dro_wp5 dro_wp5 1 5 16 19 46 47) 
(dro_wp5 dro_wp5 1 6 16 19 48 50) 
(dro_wp5 dro_wp5 1 7 16 19 51 55) 
(dro_wp5 dro_wp5 1 6 16 19 56 56) 
(dro_wp5 dro_wp5 1 5 16 19 57 57) 
(dri_wp5 dri_wp5 1 2 16 19 54 57) 
(ds_bwr2-1 drpshld 1 3 16 18 53 53) 
(ds_bwr2-1 drpshld 3 3 16 18 54 57) 
(bwr2-1 bwr 1 1 16 18 55 56) 
;; Gap5 
(dr drift 1 1 19 19 55 56) 
(ds_gap5 drpshld 1 3 19 19 53 53) 
(ds_gap5 drpshld 3 3 19 19 54 57) 
;; WP6 full 5-DHLW Short WP 
(dro_wp6 dro_wp6 1 1 20 23 42 42) 
(dro_wp6 dro_wp6 1 3 20 23 43 43) 
(dro_wp6 dro_wp6 1 4 20 23 44 45) 
(dro_wp6 dro_wp6 1 5 20 23 46 47) 
(dro_wp6 dro_wp6 1 6 20 23 48 50) 
(dro_wp6 dro_wp6 1 7 20 23 51 55) 
(dro_wp6 dro_wp6 1 6 20 23 56 56) 
(dro_wp6 dro_wp6 1 5 20 23 57 57) 
(dri_wp6 dri_wp6 1 2 20 23 54 57) 
(ds_dhlw-s1 drpshld 1 3 20 22 53 53) 
(ds_dhlw-s1 drpshld 3 3 20 22 54 57) 
(dhlw-s1 dhlw-s 1 1 20 22 55 56) 
;; Gap6 
(dr drift 1 1 23 23 55 56) 
(ds_gap6 drpshld 1 3 23 23 53 53) 
(ds_gap6 drpshld 3 3 23 23 54 57) 
;; WP7 full 21-PWR AP WP 
(dro_wp7 dro_wp7 1 1 24 27 42 42) 
(dro_wp7 dro_wp7 1 3 24 27 43 43) 
(dro_wp7 dro_wp7 1 4 24 27 44 45) 
(dro_wp7 dro_wp7 1 5 24 27 46 47) 
(dro_wp7 dro_wp7 1 6 24 27 48 50) 
(dro_wp7 dro_wp7 1 7 24 27 51 55) 
(dro_wp7 dro_wp7 1 6 24 27 56 56) 
(dro_wp7 dro_wp7 1 5 24 27 57 57) 
ANL-EBS-MD-000049 REV 02 V-15 October 2004 

Multiscale Thermohydrologic Model 
(dri_wp7 dri_wp7 1 2 24 27 54 57) 
(ds_pwr1-2 drpshld 1 3 24 26 53 53) 
(ds_pwr1-2 drpshld 3 3 24 26 54 57) 
(pwr1-2 pwr 1 1 24 26 55 56) 
;; Gap7 
(dr drift 1 1 27 27 55 56) 
(ds_gap7 drpshld 1 3 27 27 53 53) 
(ds_gap7 drpshld 3 3 27 27 54 57) 
;; WP8 half 44-BWR AP WP 
(dro_wp8 dro_wp8 1 1 28 29 42 42) 
(dro_wp8 dro_wp8 1 3 28 29 43 43) 
(dro_wp8 dro_wp8 1 4 28 29 44 45) 
(dro_wp8 dro_wp8 1 5 28 29 46 47) 
(dro_wp8 dro_wp8 1 6 28 29 48 50) 
(dro_wp8 dro_wp8 1 7 28 29 51 55) 
(dro_wp8 dro_wp8 1 6 28 29 56 56) 
(dro_wp8 dro_wp8 1 5 28 29 57 57) 
(dri_wp8 dri_wp8 1 2 28 29 54 57) 
(ds_bwr1-2 drpshld 1 3 28 29 53 53) 
(ds_bwr1-2 drpshld 3 3 28 29 54 57) 
(bwr1-2 bwr 1 1 28 29 55 56) 
(in invert 1 4 1 ny 58 58) 
(in invert 1 2 1 ny 59 59) 
) ;; end of material assignment 
(radcon 
(surface-offset 0 0 0) 
(include 
"/data34/TSPA03/radcon/DDT/preliminary_DTN/P2WR5C10-DDT55-01_1e-11.radcon") 
) ;; close radcon 
) ;; end genmsh 
;; ************************ Solver options ************************************* 
(include "/data30/TSPA01/run_control_param/run_control_param_SMT-v02") 
);; end of model input 
;; ********************* Done ************************************************** 
ANL-EBS-MD-000049 REV 02 V-16 October 2004 

Multiscale Thermohydrologic Model 
APPENDIX VI 
LDTH AND DDT SUBMODEL THERMAL-RADIATION CONNECTION 
CALCULATION 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
The LDTH and DDT submodels include heat transfer by thermal radiation inside the drift. The 
LDTH and DDT submodels represent thermal-radiative heat transfer between the drip shield, 
drift wall, and invert surfaces. The DDT submodels also represent thermal-radiative heat 
transfer between the waste package, drip shield, and invert surfaces beneath the drip shield. The 
determination of the thermal-radiation coefficients requires one direct input, which is the 
emissivity of the surfaces. The emissivity of the drift wall and invert surfaces is taken to be 0.9, 
which is near the middle of the range given for rocks (0.88 to 0.95) in Table A.11 of 
Fundamentals of Heat and Mass Transfer (Incropera and DeWitt 1996 [DIRS 108184]). The 
process of determining thermal-radiation connections for the LDTH and the DDT submodels is 
done by hand following these steps: 
1. Compile a list of model gridblocks that have at least 1 face contacting air within the 
drift 
2. For each pair of gridblocks in this list 
a. Determine if there is a clear path (line of sight between face centers) between the 
air contacting face of each block 
b. If a clear path exists, calculate the thermal-radiation coefficient for that 
connection and write a radcon entry in NUFT format, which is given in 
Reference Manual for the NUFT Flow and Transport Code, Version 2.0 (Nitao 
1998 [100474]). The coefficient c used in Equations 9 and 10 of Section 6.2.3.3, 
and which is calculated by RADPRO v4.0 (Section 3.1.3), is determined as 
follows: 
c = (se (N1  R)(-N2  R) A1 A2) / p | R |4 (Eq. VI-1) 
where: 
s = Stefans Constant 
p = pi 
e = emissivity 
A1 = area of grid block face 1 (radiating) 
A2 = area of grid block face 2 (connecting) 
N1 = unit vector normal to face 1 
N2 = unit vector normal to face 2 
R = distance from center of face 1 to center of face 2 
ANL-EBS-MD-000049 REV 02 VI-1 October 2004 

Multiscale Thermohydrologic Model 
grid block 1 
N1 
N2 
R 
grid block 2 
Radcon files are located in DTN: LL030808623122.036. The file names are: 
P2WR5C10-DDT55-01_full.radcon 
ldth0_300m.radcon 
P2WR5C10-DDT55-01v.radcon 
Determining Effective Emissivity for RADPRO Radcon Files 
Equations 9 and 10 in Section 6.2.3.3 apply to gray-body-to-black-body thermal radiation, where 
the heat receiving surface (A2) is a perfect black body (i.e., eequal to 1). The software routine 
RADPRO v4.0 (Section 3.1.3), which calculates the coefficient c in Eq. VI-1, also pertains to 
gray-body-to-black-body thermal radiation. However, all surfaces within the emplacement 
drifts are gray bodies, with values of emissivity less than 1. Therefore, the value of emissivity e 
taken as input for RADPRO v4.0 is actually an effective emissivity eeff, for the heat emitting 
surface, which accounts for the fact that the heat receiving surface is a gray body, rather than a 
black body. The value of effective emissivity eeff is determined by applying the solution of Bird 
et al. (1960 [DIRS 103524]) for radiative heat transfer between two long, gray coaxial cylinders 
by considering multiple reflections from the two sources: 
Q12 = s(T14  T24)/[1/ A1e1 
+ (1/ A2)(1/e2 
 1)] (Eq. VI-2) 
Multiplying the numerator and denominator by A1e1 
results in the following expression: 
Q12 = A1e1s(T14  T24)/[1 + (A1e1/ A2)(1/e2 
 1)] (Eq. VI-3) 
Using an effective emissivity eeff results in the following expression: 
4
Q12 = A1 eeff s(T14  T2 ) (Eq. VI-4) 
where eeff is given by: 
eeff = e1/[1 + (A1/ A2) e1 
(1/e2 
 1 )] (Eq. VI-5) 
The effective emissivity eeff is simply e1, multiplied by a coefficient C: 
eeff = Ce1 
(Eq. VI-6) 
ANL-EBS-MD-000049 REV 02 VI-2 October 2004 

Multiscale Thermohydrologic Model 
where the coefficient C is given by 
C = 1/[1 + (A1/ A2) e1 
(1/e2 
 1 )] (Eq. VI-7) 
For the LDTH submodels (Section 6.2.6) and DDT submodels (6.2.9), A1 is taken to be equal to 
A2, resulting in the following expression: 
C = 1/[1 + e1 
(1/e2 
 1 )] (Eq. VI-8) 
Section 5.3.2.7 discusses the assumption concerning the emissivity at the drift-wall surface of 
emplacement drifts. The value of eeff between the drip shield and drift-wall surface is determined 
for the LDTH and DDT submodels, using Equations VI-6 and VI-8 and the following values for 
emissivity on the drip shield (e1) and for emissivity on the drift-wall (rock) surface (e2): 
e1 = 0.63 (titanium from Lide 1995 [DIRS 101876], p. 10-298) 
e2 = 0.9 (rock, in the range of 0.88 to 0.95 from Incropera and DeWitt 1996 [DIRS 108184]) 
This results in a value of 0.935 for the coefficient C. As discussed in Section 5.3.2.7, the drift-
wall surface is covered with Type 316 stainless steel liner, which has an emissivity of 0.52 to 
0.66 (McAdams, Heat Transmission, 1954 [DIRS 161435]). Table VI-1 summarizes the value of 
the coefficent C for different values of emissivity (e2) at the drift wall. 
Table VI-1. The Value of the Coefficient C from Equation VI-7 Calculated for Different Values of 
Emissivity at the Drift Wall 
Emissivity at Drift Wall 
(e2) 
C C/Corig 
b 
0.90 0.935a 1.000 
0.90 0.969 1.037 
0.52 0.790 0.845 
0.59 0.833 0.892 
0.66 0.871 0.932 
NOTE: These values pertain to radiation between the drip shield and drift wall, where emissivity on the drip shield 
(e1) is equal to 0.63. aC is calculated using Eq. VI-8. bCorig is the value of C that was applied to determine 
eeff from the drip shield to the drift wall for the LDTH and DDT submodels, which was calculated using Eq. 
VI-8, and is equal to 0.935. 
For emissivity (e1) on the drip shield equal to 0.63, and emissivity (e2) at the drift wall ranging 
from 0.52 to 0.66, Eq. VI-7 gives values of C ranging from 0.790 to 0.871. As discussed above, 
for the LDTH and DDT submodels, a value of 0.935 was calculated (using Eq. VI-8) for the 
coefficient C (called Corig in Table VI-1), which was used to determine the value eeff from the 
drip shield to drift wall. The ratio C/Corig is listed in Table VI-1 to illustrate the relative change 
in eeff that would occur if this range of e2 
were applied, compared to the value of eeff used in the 
LDTH and DDT submodels. Thus, the value of eeff would be reduced by 6.8 to 15.5 percent for 
the range of emissivities reported for Type 316 stainless steel. 
ANL-EBS-MD-000049 REV 02 VI-3 October 2004 

Multiscale Thermohydrologic Model 
Because thermal radiation depends on the difference of the respective temperatures each raised 
to the fourth power (Eq. VI-4), the influence of a 6.8 to 15.5 percent reduction in the value of eeff 
is small. An example illustrating this point is taken from Figure 6.3-23 in Section 6.3.2.1 of this 
report. At 70 years (20 years after closure), the temperature on the drip shield attains its peak 
value of 155.3oC. (Note that the drip-shield temperature is not plotted in Figure 6.3-23.) At 70 
years, the drift wall attains a peak temperature of 140.8oC. When eeff is reduced by 6.8 percent, 
the peak drip-shield temperature from Eq. VI-6 is calculated to be 156.2oC. When eeff is reduced 
by 10.8 percent (the average case in Table VI-1), the peak drip-shield temperature is calculated 
to be 156.8oC. When eeff is reduced by 15.5 percent, the peak drip-shield temperature is 
calculated to be 157.6oC. Thus, reducing the value of eeff by 6.8 to 15.5 percent results in a drip-
shield temperature increase of 0.9 to 2.3oC, with an increase of 1.5oC for the average case. 
ANL-EBS-MD-000049 REV 02 VI-4 October 2004 

Multiscale Thermohydrologic Model 
APPENDIX VII 
EXTRACTION/MICRO-ABSTRACTION PROCESS FOR MSTHAC (BUILDING 
VIRTUAL LDTH AND SDT CHIMNEY SUBMODELS) 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
Extract MSTHAC v7.0 information from real LDTH and SDT chimney submodel output 
For the first stage of the multiscale thermohydrologic model abstraction process, MSTHAC v7.0 
reads the NUFT output files for the SMT, SDT, LDTH, and DDT submodels, extracts the 
requested time histories, and saves them to a MSTHAC v7.0 extraction file. In order to 
perform the extraction, a MSTHAC v7.0 input file is created using the format defined in the 
MSTHAC 7.0 users manual. A set of input files is created for each LDTH-/SDT submodel 
chimney location, with input files corresponding to each of the AMLs for which the LDTH 
and SDT submodels are run (e.g., AMLs of 66, 55, 27, and 14 MTU/acre). The resulting input 
files are run using MSTHAC 7.0. 
Interpolate extracted real LDTH and SDT chimney submodel output to the SMT 
submodel locations (virtual LDTH and SDT chimney submodel extraction files) 
Note that 108 out of 2874 of the SMT submodel repository-gridblock locations correspond to 
actual LDTH/SDT submodel locations. As discussed in Appendix I, these 108 locations 
generally occur for every fourth emplacement drift (see Figure 6.2-3). LDTH/SDT submodels 
are always placed at the ends of drifts and are usually placed at one or two locations along the 
central portion of those drifts. For the other locations that lie in between the 108 LDTH/SDT 
submodel locations, it is necessary to interpolate LDTH and SDT submodel results. These 
interpolated LDTH and SDT submodels are called virtual LDTH and SDT submodels. 
The process of creating virtual LDTH and SDT chimney submodel extraction files is carried 
out with the use of chimney_interpolate v1.0. The software code chimney_interpolate v1.0 reads 
a control file that defines the following information: (1) name of a real chimney-submodel 
extraction file, (2) fractional weighting for this real chimney-submodel file (note that these 
weighting factors are the same as those used to interpolate percolation flux, as described in 
substep 6 of step 8 in Appendix I), (3) name of a second real chimney-submodel extraction file, 
(4) fractional weighting for this file and (5) the name of the virtual chimney-submodel extraction 
that will be created. Note that the two real chimney submodels straddle the target location 
where the interpolation occurs. The software code chimney_interpolate v1.0 does a simple linear 
interpolation between the two input files using the specified weights for each of the real chimney 
submodels. 
The interpolation process is the same as that carried out for percolation flux (see substep 6 of 
step 8 of Appendix I). The interpolation process is two step: (1) row-wise interpolation along 
the drifts containing real chimney submodels and (2) column-wise interpolation to obtain 
virtual chimney submodels for the drifts lying between the drifts containing the real chimney 
submodels. First, virtual LDTH and SDT submodels are interpolated for all intermediate 
locations along the emplacement drifts that contain real LDTH and SDT submodels. Once 
these drifts have all of the virtual LDTH and SDT submodels created for the entire row of SMT 
submodel repository gridblocks, the column-wise interpolation process is conducted to create 
the virtual chimney submodels for the repository drifts lying between those with the real 
chimney submodels. The specified weighting factors for this linear interpolation process are the 
same as those used in interpolating the percolation flux for the SMT submodel repository 
gridblocks, as is described in Appendix I (see Substep 6 of Step 8). The output is a virtual 
chimney-submodel extraction file at each SMT submodel location and for each AML (e.g., 66, 
55, 27, and 14 MTU/acre). This process is only conducted for the SDT and LDTH submodels. 
ANL-EBS-MD-000049 REV 02 VII-1 October 2004 

Multiscale Thermohydrologic Model 
There are approximately 69,000 such files created. These files are found in DTN: 
LL030808523122.035. File names follow the conventions: 
LDTH submodels: (panel #)(i index):(j index)-LDTH(AML)-1Dds_mc-(percolation 
case)I-0(parameter case).m-f.EBS.ext.extract_LDTH_rev_14 
SDT submodels: (panel #)(i index):(j index)-SDT(AML)-00-01.ext.extract_SDT_rev_0 
Create *.in files for each virtual NUFT LDTH chimney submodel 
For the purposes of micro-abstraction, MSTHAC v7.0 requires the following: (1) the 
coordinates of the LDTH chimney submodels, (2) the real number for the AML (e.g., the real 
number for an AML of 66 MTU/acre is 65.784 MTU/acre), and (3) the present-day-, 
monsoonal-, and glacial-transition-climate percolation fluxes for that LDTH submodel location. 
Note that 108 out of 2874 of the SMT submodel repository-gridblock locations correspond to 
actual LDTH submodel locations. For the other locations, interpolated LDTH and SDT 
submodel results are obtained; these interpolated LDTH and SDT submodels are called virtual 
LDTH and SDT submodels. To obtain this information, MSTHAC v7.0 reads a *.in file 
associated with each LDTH submodel. The format of the *.in file is specified by the NUFT 
users manual (Nitao 1998 [DIRS 100474]) (see Appendix V), and the MSTHAC 7.0 users 
manual specifies the required information for this file. A virtual LDTH submodel *.in file is 
created for each SMT submodel repository-gridblock location. Note that the only purpose for 
the virtual LDTH submodel *.in files is to supply MSTHAC v7.0 with the percolation flux for 
the glacial-transition climate for each of the SMT submodel repository gridblock locations. 
Although it is not required, the virtual LDTH submodel *.in files also contain the percolation-
flux values for the present-day and monsoonal climates as well. The percolation-flux values that 
were interpolated for each of the SMT submodel repository gridblock locations (see substep 6 of 
step 8 in Appendix I), along with the coordinates of that location, are edited into each of the 
virtual LDTH submodel *.in files with the use of scripts containing standard UNIX commands. 
There is a script for each of the three infiltration-flux cases: (1) create_virtual_in_SCRIPT_ma 
for the mean-infiltration-flux case, (2) create_virtual_in_SCRIPT_la for the lower-infiltration-
flux case, and (3) create_virtual_in_SCRIPT_ua for the upper-infiltration-flux case. These three 
scripts, along with the instructions and control files for running these scripts, are found in 
DTN: LL030808523122.035 [DIRS 166419]. The names of these virtual LDTH submodel *.in 
files use the following convention: 
(panel #)(i index):(j index)-LDTH(AML)-1Dds_mc-(infiltration-flux case)i-0(parameter case).in 
Note that the infiltration-flux-case labels are: 
1. mi, which stands for mean infiltration flux 
2. ui, which stands for upper infiltration flux 
3. li, which stands for lower infiltration flux 
Note also that the i and j indices are those from the SMT submodel and that the Panel numbers 
are P1, P2E, P2W, P3, and P5 (see Figure 6.2-3). The parameter case is 2, which is for the 
modified-mean-infiltration-flux property set. 
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Run MSTHAC v7.0 at all SMT submodel locations using virtual SDT and LDTH 
chimney submodel extraction files, in conjunction with DDT and SMT submodel 
extraction files 
Once the virtual SDT and LDTH submodel extraction files have been created and the virtual 
LDTH submodel *.in files have been created, MSTHAC v7.0 is run to generate the 
micro-abstraction output file at each SMT submodel location. This process also requires DDT 
submodel extraction files, as well as the SMT submodel extraction file. This process is carried 
out by first creating an abstraction MSTHAC v7.0 input file, as defined in the MSTHAC 7.0 
users manual. Once the input files are created, MSTHAC 7.0 is run with these files as input and 
the micro-abstraction output files are generated at each SMT submodel location. 
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APPENDIX VIII 
BINNING CALCULATIONS 
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Bin Indexes 
Bin indexes were calculated for each SMT submodel location based on the rank of the 
percolation flux associated with the location. The general calculation procedure is as follows: 
1. Sort SMT submodel locations by ascending values of percolation flux 
2. Calculate quantile values for each sorted point according to the rank of the point in the 
sorted data set 
3. Assign bin indexes according to quantile intervals. 
Binning was performed according to specifications provided by the Performance Assessment 
Department. Glacial-transition climate state (median case) was specified as the percolation flux 
source. Binning quantiles were as follows: 
Bin Index Quantile Range 
Bin 1 less than 5 percent 
Bin 2 greater than or equal to 5 percent 
less than 30 percent 
Bin 3 greater than or equal to 30 percent 
less than 70 percent 
Bin 4 greater than or equal to 70 percent 
less than 95 percent 
Bin 5 greater than or equal to 95 percent 
Bin indexes were calculated for each of the 2,874 SMT submodel locations. 
Bin the MSTHAC v7.0 output and reformat it for TSPA 
After all 2,874 MSTHAC v7.0 microabstractions have been created for a particular percolation 
case, the output is processed to produce the set of information required by TSPA. To facilitate 
their work, TSPA requires the micro-abstraction to be processed two different ways: 
WAPDEG binning and TSPA binning. Note that WAPDEG is a process model that uses 
MSTHM output. Because the WAPDEG model is downstream of the MSTHM (with respect to 
model-to-model parameter flow), WAPDEG does not produce any output required by the 
MSTHM. The total binned files are: 
22,992 (from WAPDEG) + 5,748 (from TSPA) = 28,740 
WAPDEG Binning 
The first processing (WAPDEG binning) involves reporting the T_wp, RH_wp, T_ds and RH_ds 
for each SMT submodel location and each waste package type. There are 8 waste package types 
which form two waste package groups: 
Group1 : DHLW : dhlw-l1, dhlw-s1 
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Group2 : CSNF : pwr1-1, pwr2-1, bwr1-1, bwr2-1, pwr1-2, bwr1-2 
For WAPDEG purposes, we are interested in each repository location and each waste package 
type, therefore, there are 2,874 locations  8 waste package type = 22,992 typical waste packages 
reported. 
Since the WAPDEG binning produces a large number of output files, the files are concatenated 
using a UNIX shell script so that all locations falling within a bin and all waste packages of a 
given type (CSNF or DHLW) are included in a single file. This process creates 5 (# of bins)  2 
(number of waste package groups) = 10 output files for delivery. A second set of 10 files is 
provided in the WAPDEG format that only uses the typical waste package as explained below. 
Hence a total of 20 WAPDEG files are provided for each infiltration flux case. 
TSPA Binning 
The second process (TSPA binning) involves determining the most typical location given a set of 
locations that define a bin. For TSPA purposes, this process is interested in the most typical 
waste package (see below) in a group / bin; therefore, there are 5 bins  2 groups = 10 typical 
waste packages reported. A bin is a set of SMT submodel locations that have similar percolation 
values and is defined by the TSPA organization. For the purposes of processing, the waste 
packages are grouped into two waste package type groups (CSNF and DHLW). For each bin, 
two output files are created, one for the most typical CSNF package and one for the most typical 
DHLW package. There are 5 (# of bins)  2 (waste package groups) files created for this type of 
processing. This results in an additional 2,874 locations  2 waste package groups = 5,748 files. 
The TSPA binning results of typical waste packages are concatenated using a UNIX shell so that 
all locations falling within a bin and all waste packages of a given type (CSNF or DHLW) are 
included in a single file. This process creates 5 (# of bins)  2 (number of waste package groups) 
= 10 output files for delivery. 
Typical Waste Package Determination 
The most typical package is selected by compiling for each waste package type and bin member, 
peak waste package temperature, and duration of boiling at the drift wall. These data are sorted 
from low to high, and a percentile assigned to each. For each waste package type and location in 
the list, the typical package is the one that is most median on the two parameter spaces. 
To do this processing, reformat_EXT_to_TSPA v1.0 is used. The software code 
reformat_EXT_to_TSPA v1.0 takes the name of an input file as its only input. The format of 
this file is defined in the software code reformat_EXT_to_TSPA v1.0 users manual. 
Binning files are delivered as output from reformat_EXT_to_TSPA v1.0. 
Binning Algorithm 
For each location in a bin and waste package in a waste package group: 
1. Calculate peak waste package temperature 
2. Calculate boiling duration at the waste package 
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3. Sort peak waste package temperature from high to low 
4. Sort boiling duration from low to high 
5. Assign percentile rank to each waste package temperature 
6. Assign percentile rank to each boiling duration 
For each included waste package type / location in the bin: 
1. Calculate deviation of percentile rank from median (50 percent) for peak waste 
package temperature 
a. if current loc/waste package type is ranked 47 percent, deviation = 0.50 - 0.47 = 
0.03 
2. Calculate deviation of percentile rank from median (50 percent) for boiling duration 
b. if current loc/waste package type is ranked 54 percent, deviation = 0.50 - 0.54 = 
-0.04 
3. Calculate sum of squared deviations from Step 1 and 2 
c. 0.032 + 0.042 = 0.0025 
For the current bin / waste package group, select the waste package/location with the smallest 
squared deviation (this is the most typical package). 
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APPENDIX IX 
MULTISCALE MODEL APPROACH TO THERMOHYDROLOGY AT YUCCA 
MOUNTAIN 
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MSTHM Concept 
The MSTHM approach breaks the solution of thermal-hydrologic modeling at Yucca Mountain 
into smaller pieces by varying dimensionality requirements (one-, two-, or three-dimensional) as 
needed for detail. The MSTHM approach subdivides the problem into thermal and 
thermal-hydrologic submodels. By subdividing the problem into more tractable pieces, more 
efficient thermal-conduction and thermal-radiation submodels are used to address the 
three-dimensional nature of the heated repository footprint and mountain-scale heat flow and the 
three-dimensional geometric details of the engineered components in the emplacement drifts, 
waste-package-to-waste-package heat-generation variability, and drift-scale heat flow. 
Two-dimensional thermal-hydrologic models, which are much more efficient than 
three-dimensional thermal-hydrologic models, are used to model all thermal-hydrologic variables 
in detail, within the emplacement drifts and in the adjoining host rock. 
MSTHM Spatial Scales 
Two spatial scales are considered for the MSTHM: (1) mountain scale (on the order of hundreds 
to thousands of meters) and (2) drift scale (on the order of fraction of meters). Drift-scale 
modeling includes the coupling of drift-scale processes both within the engineered barrier system 
and within the near field environment. Mountain-scale processes are needed to account for the 
influence of the ground surface, the water table, and most importantly, the influence of 
repository edge cooling effects. In addition to coupling the drift scale and mountain scale, the 
MSTHM also allows for consideration of the effect of different waste package types (e.g., 
different CSNF waste packages, co-disposal of DHLW) on the various performance measures. 
MSTHM Submodels 
The MSTHM simulates processes under a range of heat loading conditions to capture the edge 
effects within the repository and the discrete nature of waste packages. MSTHM simulates the 
TH response at various locations within the domain to account for variations in stratigraphy and 
infiltration. This is accomplished by simultaneously solving four submodels at different 
spatial scales. These four submodels comprising the MSTHM are categorized into four NUFT 
submodel types (SMT, SDT, DDT, and LDTH). The MSTHM also results in two MSTHAC 
v7.0 models (LMDH and DMTH). A consistent naming convention is used for these submodels. 
The first letter applies to the thermal loading where S is the smeared area averaged heat 
loading, L is the line heat loading, and D is the discrete point heat loading. The second letter 
applies to the spatial scaling where M is the mountain scale and D is the drift scale. The last 
letters refer to the variables considered where T indicates that only thermal conduction 
variables are considered and where TH indicates that all thermal-hydrologic variables are 
considered. 
The four different NUFT submodels (listed below) are solved simultaneously at different spatial 
scales: 
 SMT Submodel  The three-dimensional smeared-source mountain-scale thermal-only 
submodel. 
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 LDTH Submodel  The two-dimensional line-source drift-scale thermal-hydrology 
submodel. 
 SDT Submodel  The one-dimensional smeared-source drift-scale thermal-only 
submodel. 
 DDT Submodel  The three-dimensional discrete-source drift-scale thermal-only 
submodel. 
The MSTHM processes the four NUFT submodels using MSTHAC v7.0 to produce the two 
following models: 
 LMTH Model  The intermediary three-dimensional line-source mountain-scale 
thermal-hydrologic model. 
 DMTH Model  The final three-dimensional discrete-source mountain-scale 
thermohydrology model. 
Figure IX-1 illustrates the general conceptual relation between the four NUFT submodels 
(identified by red text) and the two MSTHAC v7.0 submodels (identified by blue text). The 
successive nature of the NUFT submodel execution followed by the MSTHAC v7.0 calculation 
for final output is illustrated in the flowchart of Figure IX-2. 
The fundamental concept behind MSTHM is that two-dimensional representations of drift-scale 
thermal-hydrology (the LDTH submodels) can account for mountain-scale edge cooling 
processes by changing the horizontal distance of the adiabatic boundary in the drift-scale model. 
For locations within an infinite (x and y) expansive repository, the drift-scale model adiabatic 
boundary distance would be the half-way point between drifts. Edge effects within the model are 
accommodated by allowing the adiabatic boundaries to extend in time to mimic the cooling 
process. The distance to the adiabatic boundary is measured using the areal mass loading (AML) 
factor, which reports the heat input per unit area (reported in metric tonnes of uranium/acre, 
MTU/acre). As the distance to the adiabatic boundary increases, the AML decreases. 
The relation between the time-varying AML at any given point in the repository is determined by 
interpolating the necessary width to the adiabatic boundary needed for an SDT submodel at the 
point to match the SMT submodel-predicted temperature. This is merely a superposition process 
justified by the linear nature of the conduction-only energy equation. Once this AML history is 
established, it is applied to the LDTH submodel, which introduces the dimensionality of the heat 
source (a waste package) and the hydrology of the system. The final component of MSTHM is 
the inclusion of thermal-radiative heat transfer with the DDT submodel. Here the temperature 
redistribution due to the variation between hotter waste packages, colder waste packages, and 
gaps between waste packages for one location in the repository is determined. This temperature 
difference is then applied to the two-dimensional thermal-hydrologic results to give complete 
thermal-hydrologic histories for all locations and all waste packages within the repository. 
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MSTHM Model Process 
The MSTHM methodology can be subdivided into the two specific steps illustrated in Figure 
IX-2. Step 1 is the simultaneous execution of the four NUFT submodels. Step 2 is the assembly 
of the NUFT submodel results into final MSTHM results through the use of MSTHAC v7.0. 
These processes are discussed in detail below. 
STEP 1: NUFT Submodel Execution 
A three-dimensional SMT submodel simulation determines the temperature history for a specific 
simulated repository life-cycle event. This three-dimensional conduction-only submodel has the 
total energy of the repository delivered over a smeared heat-source. Taking advantage of the fact 
that the transient conduction equation is linear and therefore super-positional, the temperature 
generated at any given location of the 3D SMT submodel at any given point in time can be 
simulated by a one-dimensional SDT conduction-only submodel of a certain heat input. This 
heat input can be characterized as the emplaced heat input divided by the lateral width of 
drift that the SDT submodel heating occurs, resulting in an areal mass loading AML. By 
superposing SDT submodels to create an SMT submodel temperature, an AML-varying history 
referred to as an AMLhstrk,eff is used to describe the heat-up and cool-down of that particular 
location of the repository. The MSTHM represents thermal-hydrologic processes, which 
includes the influences of hydrologic properties and percolation flux, by incorporating the results 
of two-dimensional LDTH submodels at each of the drift-scale-submodel locations. At each 
location, an AML curve is generated which describes the temperature history due to a specified 
heat input to the LDTH submodel. 
The three-dimensional SMT and the one-dimensional SDT submodels solve for thermal 
conduction only and both share the same smeared-heat-source approximation and 
thermal-conduction representation of heat flow. The one-dimensional SDT submodels are 
executed at the same 108 locations and for the same AMLs as are the LDTH submodels 
providing a linkage between the SMT and the LDTH submodels. The common repository 
location of the SDT submodel and LDTH submodel drift wall temperatures allows for the SMT 
submodel temperature to be corrected for both the influence of thermal-hydrologic processes on 
temperature and for the influence of two-dimensional drift-scale dimensionality (orthogonal to 
the axis of the drift). This is accomplished by interpolating between AML histories. The SMT, 
SDT, and LDTH submodels share a blended heat-generation history of the entire waste package 
repository; hence, the heat-generation history is effectively that of an average waste package. 
The three-dimensional DDT submodel is a drift-scale submodel, which includes individual waste 
packages with distinct heat-generation histories. The DDT submodel solves for thermal 
conduction and accounts for thermal radiation in addition to thermal conduction between the 
waste package and drift surfaces. The drift wall temperatures for an average waste package, 
calculated with the combined use of the LDTH, SMT, and SDT submodels, are then further 
modified to account for waste-package-specific deviations using the DDT submodel. 
One complete MSTHM simulation requires multiple NUFT submodel executions to simulate the 
entire repository. Each MSTHM simulation includes the following NUFT submodel executions: 
 1 SMT submodel execution for the mountain 
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 1 DDT submodel  4 AMLs execution at one location in the repository 
 N SDT submodel locations  4 AMLs 
 N LDTH submodel locations  4 AMLs. 
STEP 2: MSTHM assembly process 
The use of MSTHAC v7.0 to assemble the execution results of the NUFT submodels into final 
output is the second part of MSTHM process (see Figure IX-2). MSTHAC v7.0 assembles the 
execution results from the submodels at the N locations within the repository creating 
time-varying AML curves. 
The MSTHM assembly process can be broken into six calculation stages which center on the 
construction of two time-varying AMLs: an effective AML for the host rock (AMLhstrk,eff) and a 
specific AML (AMLspecific) for specific waste package locations along the drift. The AMLhstrk,eff 
varies spatially and temporally and is the interpolated AML that would be prescribed for an 
insulated heat submodel (SDT) to predict the temperature produced by a mountain-scale 
submodel (SMT). The AMLspecific incorporates the discrete nature of the waste packages using 
the DDT submodel. Both AMLs are used to interpret LDTH submodel results to the LMTH and 
DMTH models. The six-stage process of MSTHM assembly is illustrated as an overview in 
Figure IX-2. Each stage is explained in detail below in conjunction with Figures IX-3 through 
IX-7. 
Assembly Stage 1: Assemble AMLhstrk,eff (Figure IX-3) 
The SDT submodel temperature histories are plotted for each of the N spatial locations for a 
family of four AMLs (66, 55, 27, and 14 MTU/acre for this model report). For each spatial 
location, the plotted family of SDT submodel temperature histories is plotted against the time 
history of the temperature from the SMT submodel. The AMLhstrk,eff is interpolated by 
determining the AML needed for the SDT submodel to generate the SMT temperature at any 
given time. 
Assembly Stage 2: Interpolate LMTH (Figure IX-4) 
The LMTH results are determined by taking the thermal-hydrologic output from the LDTH 
submodels and plotting the time-history of the variables for each of the family of AMLs. First 
for each of the N locations, the thermal-hydrologic output history from the LDTH submodel is 
plotted for each of the four AMLs. Second, the thermal-hydrologic history for the LMTH at any 
given time t* is determined by interpolating the thermal-hydrologic value at AMLhstrk,eff(t*) from 
the LDTH histories (note that the LDTH and DDT submodels include radiative heat transfer 
between the waste package, drip shield, and drift wall surfaces). As radiative heat transfer is 
proportional to the temperature difference between two surfaces raised to the fourth power, i.e., 
.T4, linear interpolation between two bounding AML curves is not sufficient to accurately 
calculate a result. To address this issue, MSTHM submodels are run at a variety of AMLs. 
Hence, interpolations are performed over a small enough range that piecewise linear 
interpolation adequately characterizes the underlying nonlinear process of radiative heat transfer. 
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Assembly Stage 3: Calculate DMTH (Figure IX-5) 
The discrete thermal-hydrologic values are calculated from the LMTH submodel by 
incorporating the DDT submodel temperature results. Here, the temperature variation along the 
average temperature of the LMTH submodel accounts for differences in waste package loading. 
The temperature difference is calculated using the AMLhstrk,eff and the temperature from the DDT 
submodel. This difference is then superimposed on the LMTH submodel to yield DMTH 
submodel results. 
Assembly Stage 4: Assembling AMLspecific (Figure IX-6) 
The procedure for assembling AMLspecific is very similar to that of assembling AMLhstrk,eff. The 
temperature history from the LDTH submodel is plotted for each of the N spatial locations for a 
family of four AMLs (66, 55, 27, and 14 MTU/acre). Along with the family of 
LDTH submodel temperature histories at each spatial location is plotted the time history of the 
temperature from the DMTH model. The AMLspecific is interpolated by determining the AML 
needed for the LDTH submodel to generate the DMTH- model temperature at any given time. 
Assembly Stage 5: Interpolate Thermal-Hydrologic Variables for DMTH (Figure IX-7) 
The DMTH results are determined by taking the thermal-hydrologic output from the LDTH 
submodels and plotting the time-history of the variables for each of the family of AMLs. First 
for each of the N locations, the thermal-hydrologic output history from the LDTH submodel is 
plotted for each of the four AMLs. The thermal-hydrologic history for the DMTH at any given 
time t* is determined by interpolating the thermal-hydrologic value at AMLspecific(t*) from the 
LDTH histories. 
Assembly Stage 6: Determine Relative Humidity for the Waste Package and Drip Shield 
The relative humidity on top of the drip shield and on the waste package is calculated as a 
function of the saturated pressures in the drift. 
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NOTE: SDT, LDTH, and DDT submodels are run a different AMLs (left side). SMT, LMTH, and DMTH models are 
the series of three-dimensional mountain-scale models of increasing complexity (right side). The six 
stages illustrate the process of constructing intermediate variables. 
Figure IX-1. Six-Stage Flow Chart Diagram of the Multiscale Thermohydrologic Model (MSTHM) 
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Figure IX-2. MSTHM Flowchart Shown in Two Steps: (1) NUFT Submodel Execution in Red, and (2) 
MSTHM Processing of Final Output Using MSTHAC v7.0 (Blue) 
NOTE: Stage 1 involves the interpolation of the variable AML,effective from the SMT submodel temperature 
T_SMT and the family of SDT submodel temperatures T_SDT at three different AMLs. 
Figure IX-3. MSTHM Stage 1 
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NOTE: Stage 2 involves the interpolation of the LMTH-model temperature T_LMTH from the variable 
AML,hstrk,effective and the family of LDTH submodel temperatures T_LDTH. 
Figure IX-4. MSTHM Stage 2 
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NOTE: Stage 3 involves the calculation of the DMTH-model temperature T_DMTH from the LMTH-model 
temperature T_LMTH and DDT submodel temperature T_DDT. 
Figure IX-5. MSTHM Stage 3 
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NOTE: Stage 4 involves the interpolation of the variable AMLspecific from the DMTH-model temperature T_DMTH 
and the family of LDTH submodel temperatures T_LDTH. 
Figure IX-6. MSTHM Stage 4 
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NOTE: Stage 5 involves the determination of each hydrologic variable (e.g., RH) using the variable AML,specific 
and the corresponding family of LDTH submodel hydrologic variable values. 
Figure IX-7. MSTHM Stage 5 
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APPENDIX X 
HYDROLOGIC PROPERTIES FOR THE INTERGRANULAR POROSITY OF THE 
INVERT 
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The multiscale thermohydrologic model requires an evaluation of the retention and hydraulic 
properties of the crushed tuff that comprises the invert. In this appendix, retention and hydraulic 
properties are estimated for the coarse pore space of the crushed tuff invert. 
This appendix initially develops a nondimensionalized curve fit to the two-parameter van 
Genuchten retention relation for several materials that cover a wide range of particle sizes. The 
nondimensional curve fit is then applied to crushed tuff to develop moisture potential retention 
relations for various size particles ranging from 0.3 mm to 20 mm. The relationship of 
unsaturated hydraulic conductivity to moisture potential is then developed on the basis of the van 
Genuchten curve-fit parameters. A summary of the hydrologic properties for the intergranular 
porosity of the invert is then presented. 
Sections X.1 and X.2 develop water retention relationships for four unconsolidated materials, 
each representing a particular particle size. First, Section X.1 converts the retention data for a 
hydrocarbon fluid (DTN: MO0307PAUSFPD.000 [DIRS 164436]) into water retention data, 
using an estimate from Brooks and Corey (1964 [DIRS 156915]). Section X.1 also provides 
constants from Incropera and DeWitt (1996 [DIRS 108184]) that are needed to make relations 
nondimensional. 
Next, for each of the four unconsolidated materials, Section X.2 demonstrates the development 
of a best-fit formula for the water retention relation, using the functional form of van Genuchten 
(1980 [DIRS 100610]). These are only examples; for further analysis, the appendix needs a form 
that incorporates information about particle size. To this end, and following a procedure 
suggested by Leverett (1941 [DIRS 100588], p. 159), Section X.2.5 develops a best fit to a 
formula that contains a nondimensional form of the intrinsic permeability (van Genuchten 
alpha), using the capillary rise as a surrogate for the particle size. 
Sections X.3 and X.4 develop estimates of intrinsic permeability for possible crushed tuffs of 
differing particle size. Section X.3 begins by estimating an intergranular porosity applicable to 
all four crushed tuffs, taking the central value from a handbook range. Section X.4 determines 
the intrinsic permeability (as (cm)-1 or (bars)-1) for each of the crushed tuffs, using the Kozeny-
Carman equation (Bear 1972 [DIRS 156269], p. 166). 
Unsaturated hydraulic conductivity is calculated within the qualified NUFT software, based on a 
relationship given by Fetter (1993 [DIRS 102009], p. 182). Section X.5 provides example 
results for each of the crushed tuffs. 
X.1 NON-DIMENSIONALIZED VAN GENUCHTEN RETENTION RELATION 
DTN: MO0307SPAUSFPD.000 [DIRS 164436] contains measured data on retention of a 
hydrocarbon fluid by four different particulate materials. These are measurements reported by 
Brooks and Corey (1964 [DIRS 156915]), as presented in Advection versus Diffusion in the 
Invert (BSC 2003 [DIRS 170881]). Figure X-1 presents the capillary rise of these 
unconsolidated samples. The Brooks and Corey moisture potential measurements include a 
range of particle sizes. A description of these data sets follows: 
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 Volcanic Sand This material originates from a wind-blown deposit along Crab Creek 
in Washington State. It consists of dark-colored aggregates that can be broken down 
into finer particles by applying pressure. It is not known to what degree these 
Capillary Rise (cm) 
aggregates are themselves permeable, but they undoubtedly have some permeability. 
This sand has a degree of structure and has both primary and secondary porosity. 
 Fine Sand This sand was supplied by the Hanford Laboratories of General Electric 
Company at Richland, Washington, and apparently contains some volcanic minerals. 
This material contains a wide range of particle sizes, ranging down to silt size. Most of 
the particles are angular and not as rounded as most river bed sands. 
 Glass Beads  This material is an example of media having a very narrow range of pore 
sizes. It is not much different in this respect, however, from many clean river sands. 
 Touchet Silt Loam  This soil comes from the Columbia River basin and is also 
supplied by the Hanford Laboratory. It is extremely fine textured in that it contains 
practically no coarse sand, but it is somewhat unusual in that it contains a smaller 
amount of clay than would be expected in such a fine-textured soil. It is, in fact, nearly 
pure silt mixed with some extremely fine sand. It contains enough clay, however, to 
create a structure with secondary porosity. 
p y p 
600 
500 
400 
300 
200 
100 
0 
1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 
Volcanic Sand 
. 
Fine Sand 
. 
Glass Beads 
. 
Touchet Silt Loam 
Saturation 
. 
DTN: MO0307SPAUSFPD.000 [DIRS 164436]. 
Figure X-1. Capillary Rise of Unconsolidated Samples 
ANL-EBS-MD-000049 REV 02 X-2 October 2004 

Multiscale Thermohydrologic Model 
The dependence of the capillary pressure curve on particle diameter and porosity is analyzed in 
the same manner as Leverett (1941 [DIRS 100588], p.159). Leverett showed that capillary 
pressure data for various sands could be correlated using a non-dimensional group that included 
the mean particle diameter and the porosity. This approach is applied to the data of DTN: 
MO0307SPAUSFPD.000 [DIRS 164436] to produce a non-dimensional capillary 
pressure/saturation curve. This non-dimensional data is then fitted with the functional form 
posed by van Genuchten (1980 [DIRS 100610], Equation 21). 
The relative permeability is based upon the work of Mualem, as reported by van Genuchten 
(1980 [DIRS 100610]). Mualem developed a semi-empirical relationship between the capillary 
pressure curve and the relative permeability curve. Mualems correlation coefficient is 
combined with the fit of the non-dimensional capillary pressure to produce a liquid relative 
permeability curve appropriate for the invert interparticle porosity. The relative permeability of 
the gas phase is set to unity in anticipation of the very low interparticle saturation anticipated in 
the invert. 
The Brooks and Corey data (DTN: MO0307SPAUSFPD.000 [DIRS 164436]) for 
unconsolidated particulate media are appropriate for the proposed invert configuration. Like the 
invert, all materials are composed of unconsolidated particles. Angularity of the particulate will 
be reflected in the data for sands. This, of course, presumes that the invert rock is roughly 
spherical, as opposed to a plate-like shape. 
Input the properties for the four materials from DTN: MO0307SPAUSFPD.000 [DIRS 164436], 
Table 2: 
Note that only the first few values are printed out in the MathCad format. For a complete listing 
of the properties, the data are presented in DTN MO0307SPAUSFPD.000 [DIRS 164436]. 
ANL-EBS-MD-000049 REV 02 X-3 October 2004 

Multiscale Thermohydrologic Model 
Input the intrinsic permeability and porosity (DTN: MO0307SPAUSFPD.000 [DIRS 164436]). 
kVS
.
.. 
. 
. 
. 
. 
. 
. 
. 
.
. 
:=
.. 
. 
. 
. 
. 
. 
. 
..
18
. 
......
. 
kFS 
kFM 
kGB 
kTSL 
(
.....
. 
2.5
11.3
6.3 
0.6 
10- 6 
m
)
2 
(Eq. X.1)

30
.
kFFH
.
The data have to be adjusted to account for the difference between water and the hydrocarbon 
fluid. According to Brooks and Corey (1964 [DIRS 156915], Equation 17, p. 9), the capillary 
rise of water was about twice that of the hydrocarbon used in the measurements. Van Genuchten 
(1980 [DIRS 100610]) used the same factor in his analysis. 
VS<1> 
VS<1>
2
.
. 
. 
. 
. 
. 
. 
. 
. 
.
.
.
:=
.
. 
. 
. 
. 
. 
. 
. 
. 
.
.
.
<>
FS 1
<>
FM 1
<>
GB 1
<>
TSL 1
<>
FS 1
......
.
......
.
2
<>
FM 1
2 
(Eq. X.2)
<>
GB 1
2
<>
TSL 1
2
<>
FFH 1
<>
FFH 1
2
.
.
Because Brooks and Corey (1964 [DIRS 156915]) do not specify surface tension or 
temperature, they assume an ambient temperature to represent laboratory conditions. The 
surface tension of water equals 72 dynes/cm at 25oC. The water surface tension and density are 
(Incropera and DeWitt 1996 [DIRS 108184], p. 846): 

72 
dyne 
cm 
sw := 

998 
kg 
3
m
.
:= 
In accordance with the Brooks-Corey estimate of capillary rise, 
ANL-EBS-MD-000049 REV 02 X-4 October 2004 

Multiscale Thermohydrologic Model 
sw 
sHC := 
2 
X.2 DATA FITTING 
In the following analysis, curve fits are developed for the four materials separately for 
comparison to the measured retention data. A function representing the van Genuchten function 
is defined. Error functions are defined that for a set of van Genuchten parameters (a, n, Sr) 
provide a summation of the residuals squared between the predicted value for capillary pressure, 
and the measured capillary pressure. After defining the error function, the MathCad Minerr 
function is used to calculate the set of van Genuchten parameters (a, n, Sr) that minimizes the 
sum of the residuals squared. Define a vector of points for plotting purposes in MathCad. Note 
that the following function in MathCad defines a set of saturations that are then used to calculate 
corresponding capillary pressure or moisture potential that can then be used to generate a plot of 
moisture retention. 
fplot := for i 1 .. 9999. (Eq. X.3) 
i 
si 10000. 
s 
The van Genuchtens fitting function (van Genuchten 1980 [DIRS 100610], Equation 21) is: 
. s 
. r
.. r 
(Eq. X.4)
m1 
.
( .a)n 
Van Genuchten includes the residual saturation in the fit. The van Genuchten m parameter is 
defined in terms of n (van Genuchten 1980 [DIRS 100610], Equation 22): 
1 
m1 - (Eq. X.5) 
n 
Rewriting this Equation X.5 to solve for the exponent: 
1n 
(Eq. X.6) 
m n1
-
-1n 
(Eq. X.7) 
m 1n
-
Substituting in the value of m into Equation X.4: 
ANL-EBS-MD-000049 REV 02 X-5 October 2004 

Multiscale Thermohydrologic Model 
. s 
. r
.. r 
(Eq. X.8)
1
1 
n
.
1 
Define the values for saturation 
( .a)n 
. s
Ss 
. s 
1 
By definition, the value of Ss at saturation is one. 
Ss 
.
. 
S . s 
.
. r 
Sr . s 
Substitute these definitions into Equation X.8: 
. 
1
. s 
. 
.
Sr . s 
S r 
(Eq. X.9)
S . s 
.
1 
( .a)n 
Factor out .s from both sides of the equation: 
. 
1 
1 
n
1
1 
SSr 
S r 
(Eq. X.10) 
.
1 
( .a)n 
Restating the equation: 
SSr 
1 
1 
n
1 
1 
(Eq. X.11)
1Sr 
.
1 
( .a)n 
Solve for the value of moisture potential as a function of saturation (S): 
1 
n
.
1 
( .a)n 
1 
(Eq. X.12) 
1S r 
1 
n 
SSr
ANL-EBS-MD-000049 REV 02 X-6 October 2004 

Multiscale Thermohydrologic Model 
n1 
n 
.a
. 
1S 
r
n 
(Eq. X.13)
1 
( 
)
SSr
n 
n1
SSr
n 
(Eq. X.14)
1 
( .a
.
)
1Sr 
n 
n1
SSr
n
( .a
.
)
1 
1Sr 
Solving for the moisture potential in terms of the saturation, and defining a function for the 
moisture potential: 
1 
n
.. 
. 
.
. 
-- 
- 
..
. 
.. 
. 
.
. 
SSr 
1n
- 1
1Sr 
n 
.
)
GS Sr a , , n
,
(
:=
1
a

(Eq. X.15) 
.
X.2.1 Volcanic Sand 
Define a function, in terms of the van Genuchten, parameters that represents the sum of the 
residuals squared between the measured capillary pressure and the predicted capillary pressure 
for the volcanic sand: 
rows VS
()
..
,
)
,
(
GVSi2, n VSi12 
1 (Eq. X.16) 
(
..
)
.
(
error Sr a , , n) 
:=
, Sr 
a ,
-
i
=
Define an initial estimate of the parameters: 
.. 
. 
.
.
.
:=
.. 
. 
.
.
.
Sr 
0.1 
0.02
.
.
(Eq. X.17)
a
6
.
.
n 
Use the Minerr function to obtain the lease squares fit to the volcanic sand data: 
Given 
error Sr a , , n( ) 0 (Eq. X.18) 
ANL-EBS-MD-000049 REV 02 X-7 October 2004 

Multiscale Thermohydrologic Model 
. SrVS . 
. 
.a VS . :=Minerr Sr a , , n) (Eq. X.19)
( 
. 
. nVS . 
. SrVS . 
. 0.156 .
..
.a VS . =. 0.021 . (Eq. X.20)
..
. nVS .. 4.413 . 
Output the sum of the residuals squared: 
error SrVS ,a VS , nVS)=536.779 (Eq. X.21)
( 
Define a function for plotting purposes: 
-
SplotVS :=SrVS +( 1SrVS) fplot (Eq. X.22) 
X.2.2 Fine Sand 
Define a function, in terms of the van Genuchten parameters, that represents the sum of the 
residuals squared between the measured capillary pressure and the predicted capillary pressure 
for the fine sand: 
rows FS
() 
2
.
error Sr a , , n) :=.( GFSi2,, Sr a , , n)- FSi1,)
( ..( . 
i = 1 (Eq. X.23) 
Define an initial estimate of the parameters: 
. Sr .. 0.01 . 
.. 
.a. :=. 0.1 . 
.. 
. n .. 2 . 
Use the Minerr function to obtain the lease squares fit to the fine sand data: 
Given 
error Sr a , , n) 0 (Eq. X.24)
( 
ANL-EBS-MD-000049 REV 02 X-8 October 2004 

Multiscale Thermohydrologic Model 
. SrFS . 
. 
.a FS . :=Minerr Sr a , , n)
( 
. 
. nFS . (Eq. X.25) 
. SrFS . 
. 0.170 .
.. 
.a FS . =. 0.010 . 
.. 
. nFS .. 5.664 . 
(Eq. X.26) 
Output the sum of the residuals squared: 
error SrFS ,a FS , nFS)=675.283 (Eq. X.27)
( 
Define a function for plotting purposes: 
-
SplotFS :=SrFS +( 1SrFS) fplot (Eq. X.28) 
X.2.3 Glass Beads 
Define a function, in terms of the van Genuchten parameters, that represents the sum of the 
residuals squared between the measured capillary pressure and the predicted capillary pressure 
for the glass beads: 
rows GB)
( 
2
error Sr a , , n) :=.( GGBi2,, Sr a , , n)- GBi1, ). (Eq. X.29)
( ..( . 
i = 1 
Define an initial estimate of the parameters: 
. Sr .. 0.01 . 
..
.a. :=. 0.03 . (Eq. X.30)
..
. n .. 7 . 
Use the Minerr function to obtain the lease squares fit to the glass beads data: 
Given 
error Sr a , , n) 0
( 
ANL-EBS-MD-000049 REV 02 X-9 October 2004 

Multiscale Thermohydrologic Model 
. SrGB . 
. 
.a GB . :=Minerr Sr a , , n) (Eq. X.31)
( 
. 
. nGB . 
. SrGB . 
. 0.096991 .
..
.a GB . =. 0.016780 . (Eq. X.32)
..
. nGB .. 8.122966 . 
Output the sum of the residuals squared: 
error SrGB ,a GB , nGB)=2.472  103 (Eq. X.33)
( 
Define a function for plotting purposes: 
-
SplotGB :=SrGB +( 1SrGB) fplot (Eq. X.34) 
X.2.4 Touchet Silt Loam 
Define a function, in terms of the van Genuchten parameters, that represents the sum of the 
residuals squared between the measured capillary pressure and the predicted capillary pressure 
for the Touchet Silt Loam: 
rows TSL)
( 
2
error Sr a , , n) :=.( G TSLi2,, Sr a , , n)- TSLi1, ). (Eq. X.35)
( ..( . 
i = 1 
Define an initial estimate of the parameters: 
. Sr .. 0.001 . 
..
.a. :=. 0.01 . (Eq. X.36) 
..
. n .. 3 . 
Use the Minerr function to obtain the lease squares fit to the Touchet Silt Loam data: 
Given 
error Sr a , , n) 0 (Eq. X.37)
( 
ANL-EBS-MD-000049 REV 02 X-10 October 2004 

Multiscale Thermohydrologic Model 
SrTSL 
a TSL 
(
:=Minerr Sr a , , n) (Eq. X.38) 
.
. 
. 
.
.
nTSL 
.
.
. 
.
. 
. 
.
. 
SrTSL 
a TSL 
nTSL 
.
. 
. 
.
.
.
.
.
.
0.360
4.775

10- 3
.
(Eq. X.39)
=
5.808
.
Output the sum of the residuals squared: 
error SrTSL a TSL nTSL
,
(
)
=

103
1.872 
(Eq. X.40)
,
Define a function for plotting purposes: 
)

fplot
-
(
1SrTSL
SplotTSL SrTSL 
(Eq. X.41)
:=
+
The data sets have now been fitted individually. The residual saturation (Sr) for each set is 
inferred from the data. The results of the analysis are presented in Figure X-1. 
X.2.5 Nondimensional Capillary Pressure Correlation Using Leveretts Non-Dimensional 
Group 
The next analysis applies Leveretts nondimensional group (Leverett 1941 [DIRS 100588], 
p. 159) to the four data sets. It collapses the data reasonably well, with the volcanic sand 
providing the major deviation from the group. It compares favorably with Leveretts drainage 
curve for clean unconsolidated sands (Leverett 1941[DIRS 100588], Figure 4). 
Composite Set 
Define the function using the := notation for assigning a function. 
1 
n
.
n
...
 
1
- 
f 
)
(
G2 Seffa , , n 1n
Define the nondimensional parameter for analysis (Leverett 1941 [DIRS 100588], p. 159). 
Pc k 
Seff 
- 1 
(Eq. X.42)
:=
.
a 
G2 
sw 

(Eq. X.43) 
ANL-EBS-MD-000049 REV 02 X-11 October 2004 

Multiscale Thermohydrologic Model 
Define a function in terms of the dimensionless capillary pressure and the nondimensional van 
Genuchten parameters that represents the sum of the residuals squared between the measured 
dimensionless capillary pressure and the predicted dimensionless capillary pressure for all data 
sets: 
(Eq. X.44) 
(Eq. X.45) 
...
... 
kGB 
kTSL 
kVS 
kFS
cm. g
cm. g
cm. g
sw 
sw 
cm. g
:=
, n 
rows GB)
( 
rows FS
() 
rows VS
() 
Use the Minerr function to obtain the lease squares fit to the volcanic sand data: 
Given 
error(a, n) 0 (Eq. X.46) 
:=Minerr(a, n) (Eq. X.47) 
(Eq. X.48) 
1 
()
i := 1 .. rows VS
Define an initial estimate of the parameters: 
4 
2.3 
2.455 
8.013 
a comp 
ncomp 
a comp 
ncomp 
rows TSL)
( 
error(a, n) 
fTSL 
2.
...
... 
fGB 
2.
...
.. 
.. 
.
. 
fFS 
2.
...
.. 
.. 
.
. 
fVS 
2.
...
.. 
.. 
.
. 
.. 
.. 
.
. 
 
 
 
,
GBi1sw 
.. 
..
-

VSi1
, 
.. 
.. 
- 
,
TSLi1sw 
.. 
..
-
FSi1
, 
.. 
.. 
- 
. 
. 
.
.
..
. 
:=
.
a
.
n 
..
.
.
.
a , , n
1SrTSL
- 
.
.
..
.
.
.
.
.
a , , n
1SrFS
- 
a , , n
1SrGB
- 
=
.
.
a , 
1SrVS
- 
FSi2SrFS
, 
VSi2SrVS
, 
-
TSLi2SrTSL
, 
GBi2SrGB
, 
-
-
.
. 
.. 
.. 
.. 
.. 
-
..
. 
G2 
.. 
.. 
.
. 
..
.
+ 
1
=
i 
..
.
G2 
.. 
.. 
.
. 
..
. 
1
=
i 
..
.
G2 
.. 
.. 
.
. 
..
.
+ 
=
i 
..
.
G2 
.. 
.. 
.
. 
..
.
+ 
1
=
i 
Output the sum of the residuals squared: 
ANL-EBS-MD-000049 REV 02 X-12 October 2004 

Multiscale Thermohydrologic Model 
()
j := 1 .. rows FS
(
k := 1 .. rows GB) 
error (a comp, ncomp)=4.054 (Eq. X.49) 
Define a function for plotting purposes: 
Splotcomp := fplot 
(
l :=1 .. rows TSL) (Eq. X.50) 
The results of the analysis for normalized capillary rise for various materials are presented in 
Figure X-2. 
Advection versus Diffusion in the Invert (BSC 2003 [DIRS 170881], Appendix VII) presents an 
independent verification using the Microsoft EXCEL equation solver. The analysis uses the 
same curve fitting procedure for volcanic sand, fine sand, glass beads, and Touchet Silt Loam 
individually, and then collectively by transforming the capillary rise data to a nondimensional 
capillary rise. Microsoft EXCEL is used to perform curve fitting to the van Genuchten retention 
relationship. The Solver is an add-in function in EXCEL. The Solver can minimize a target cell 
that involves multiple cell variables that might be subject to multiple constraints. The Solver is 
used specifically to solve for several variables under the constraint for a target value. In this 
case, the minimization of the least squares of the capillary rise is the target value for curve 
fitting. 
ANL-EBS-MD-000049 REV 02 X-13 October 2004 

Multiscale Thermohydrologic Model 
Capillary Rise 
N. D. Pc of Unconsolidated Samples
1.6 
1.4 
1.2
1
0.8 
0.6 
0.4 
0.2
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 
Volcanic Sand 
Fine Sand 
Glass Beads 
Touchet Silt Loam 
Saturation 
. 
DTN MO0307SPAVGHYD.000 
Figure X-2. Normalized Capillary Rise for Various Materials 
X.3 ASSESSMENT OF INTERGRANULAR POROSITY 
Hilf evaluated uniformly graded or poorly sorted sands and measured intergranular porosity 
(fmatrix) ranges from 0.40 to about 0.48 when considering the maximum void ratio or porosity 
(Hilf 1975 [DIRS 169699], p. 257). For purposes of analysis, considering that crushed tuff may 
settle over time, a median value of 0.45 is adopted for the intergranular porosity (fintergrain). 
Prior analyses reported in Advection versus Diffusion in the Invert (BSC 2003 [DIRS 170881], 
Section 6.3) have estimated the intragranular porosity (finatrix) of crushed tuff to be 0.112 (BSC 
2003 [DIRS 170881], Table 4-3). However, the total porosity includes both the intergranular 
porosity (fintergrain), related to the voids between the crushed tuff particles, as well as the 
intragranular porosity, related to the voids within the crushed tuff particles (fmatrix). A total 
ANL-EBS-MD-000049 REV 02 X-14 October 2004 

Multiscale Thermohydrologic Model 
porosity of 0.545 has been calculated in Advection versus Diffusion in the Invert (BSC 2003 
[DIRS 170881], Appendix XI) for sieved samples of crushed tuff ranging from 2 to 4.75 mm. 
Previous analysis in Advection versus Diffusion in the Invert (BSC 2003 [DIRS 170881], Section 
6.3) estimated the intergranular porosity (fintergrain) that pertains to this coarse void space is equal 
to 0.49. 
Because the intergranular porosity value of 0.49 exceeds the range 0.40 to 0.48, it suggests that 
the USGS values for measured bulk porosity (DTN GS980808312242.015 [DIRS 119916]) are 
consistent with a poorly graded sand in a loose state. 
X.4 MOISTURE POTENTIAL RETENTION RELATION FOR VARIOUS SIZE 
PARTICLES 
This section presents the calculations and plots of the retention curves for the nondimensionalized 
van Genuchten moisture potential retention relation for various size particles 
ranging from 0.317 mm to 20 mm. The summary of the calculations of the air entry parameters 
is presented in Table X-1. The van Genuchten (n) value is 8.013 as discussed below. 
Equation X.51 defines a nondimensional moisture potential parameter (.ND) for analysis, as 
suggested by Leverett (1941[DIRS 100588], p.159). 
.
ND =.
. gk 
(Eq. X.51) 
 
sW f 
where 
.ND = nondimensionalized moisture potential 
. = moisture potential 
. = mass density of water (kg/m3) 
g = acceleration due to gravity 
k = intrinsic permeability 
sw = interfacial tension between the pore water and mineral surface (dyne/cm) 
f= porosity 
The van Genuchten non-dimensional parameter (n) is calculated, where the van Genuchten 
dimensionless air entry parameter, aND = 2.455, such that n = 8.01 as presented above. For 
specific sized grains, the Kozeny-Carman equation expresses the relationship of the intrinsic 
permeability (k) to the porosity (f) (Bear 1972 [DIRS 156269], p. 166): 
3
d 2 f
m
Intrinsic permeability = k= 
180 
(1 -f) (Eq. X.52) 
2 
where 
dm = mean particle diameter 
f= porosity 
ANL-EBS-MD-000049 REV 02 X-15 October 2004 

Multiscale Thermohydrologic Model 
This equation is rearranged to obtain: 
k = dm
f (Eq. X.53) 
f 180 ( 1 -f) 
The Leverett Equation as presented in Equation X.51 expresses the relationship of the 
nondimensional moisture potential (. ND) to the dimensional moisture potential (. ). Since the 
air-entry parameter a is inversely proportional to the moisture potential (See Equation X.4), the 
relationship of the nondimensional air-entry parameter as determined from the regression 
analysis for Equation X.4 is given by: 
11 . gk 
=  
a
ND as 
f
w 
(Eq. X.54) 
Solving for the air-entry parameter a in terms of the nondimensional air-entry parameter: 
a a ND 
. gk 
= 
sf
w 
(Eq. X.55) 
Substituting in Equation X.53 into Equation X.55 to express the air-entry parameter a in terms of 
the particle diameter (dm); the fluid density (. ); the surface tension (s w); the porosity (f ), the 
gravitational constant (g); and the dimensionless air entry parameter (a ND) as determined from 
the curve-fitting analysis: 
a a ND 
. gd f 
. gd f
mm
= = 455.2   
s 180 (1-f ) s 180 (1-f )
ww 
(Eq. X.56) 
Substituting in the value of 0.317 mm as a particle size with an intergranular porosity (f intergrain) 
of 0.45, the calculated value for the van Genuchten air-entry parameter (a ) in cm- 1 for this size 
material is given in Equation X.55: 
. gk 45.0 
455 . 2 = 
. g 0317 .0  cm ( 1- 45.0 ) 455.2 = 0646 .0  cm- 1 
sf s w 180
w 
(Eq. X.57) 
This analysis uses the following referenced properties for water: mass density, . = 1000 kg/m3, 
s g, geometric standard deviation, an interfacial tension between the pore water and mineral 
ANL-EBS-MD-000049 REV 02 X-16 October 2004 

Multiscale Thermohydrologic Model 
surface, s w = 72 dynes/cm at ambient temperature, and gravity, g = 9.81 m/sec2 (Incropera and 
DeWitt 1996 [DIRS 108184], p. 846). Equation X.58 is used to calculate the value of the air-
-
entry parameter (a ) in terms of (bars)1 for a particle size of 0.3173 mm: 
a= 06466.0  cm- 1 
= 9.65 (bars)- 1 
1000  kg  81.9  m (Eq. X.58) 
32
m sec 
Now consider the particle size of 3 mm. The van Genuchten air-entry parameter (a ) for this 
grain size from Equations X.55, is given as: 
. g 
k  455.2 = 
. cm 3.0 g  45.0  455.2 = cm 612 .0 - 1 (Eq. X.59) 
 
s w fs w 180 ( 1 - 45.0 ) 
The value of the van Genuchten air-entry parameter (a ) for the 3 mm diameter grain size in 
terms of bars- 1 is calculated using Equation X.58 (bars)- 1: 
 
a= cm 611 . 0 - 1 
= bars .624 - 1 (Eq. X.60) 
 
1000  kg  81. 9  m 
32
m sec 
The van Genuchten air entry parameter calculations are presented in Table X-1. The individual 
retention curves with curve fits are presented in Tables X-2 through X-5 and are illustrated in 
Figures X-3 through X-6. 
Table X-1. van Genuchten Air Entry Parameter (a ) Calculations. 
Parameter 
Particle Diameter (dm) 
0.317 mm 3 mm 10 mm 20 mm 
van Genuchten air-entry parameter(a ) (cm) - 1 0.0646a 0.612c 2.05 4.09 
van Genuchten air entry parameter(bars) - 1 65.9b 624d 2080 4160 
a 
b 
See the calculation presented in Equation X.57. 
See the calculation presented in Equation X.58. 
c 
d 
See the calculation presented in Equation X.59. 
See the calculation presented in Equation X.60. 
ANL-EBS-MD-000049 REV 02 X-17 October 2004 

Multiscale Thermohydrologic Model 
Table X-2. Moisture Retention Data for 0.317 mm Crushed Tuff 
Van Genuchten Curve Parameters 
Moisture Content at Saturation (.s) 0.45 
Residual Moisture Content (.r) 0.05 
Alpha (a) 65.9 bars^-1 0.0646 cm^-1 
n 8.01 
m 0.88 
Retention Analysis 
Moisture Potential 
.(bars) 
Predicted 
Moisture 
Content 
(.) 
0.0001 0.450 
0.0002 0.450 
0.0005 0.450 
0.001 0.450 
0.002 0.450 
0.005 0.450 
0.01 0.438 
0.02 0.103 
0.05 0.050 
0.1 0.050 
0.2 0.050 
0.5 0.050 
1 0.050 
2 0.050 
5 0.050 
10 0.050 
20 0.050 
50 0.050 
100 0.050 
200 0.050 
500 0.050 
1000 0.050 
Predicted Moisture content obtained from Equation X.4 
ANL-EBS-MD-000049 REV 02 X-18 October 2004 

Multiscale Thermohydrologic Model 
Table X-3. Moisture Retention Data for 3.0 mm Crushed Tuff 
Van Genuchten Curve Parameters 
Moisture Content at Saturation (.s) 0.45 
Residual Moisture Content (.r) 0.05 
Alpha (a) 624 bars^-1 0.612 cm^-1 
n 8.01 
m 0.88 
Retention Analysis 
Moisture Potential 
.(bars) 
Predicted 
Moisture 
Content 
(.) 
0.0001 0.450 
0.0002 0.450 
0.0005 0.450 
0.001 0.442 
0.002 0.124 
0.005 0.050 
0.01 0.050 
0.02 0.050 
0.05 0.050 
0.1 0.050 
0.2 0.050 
0.5 0.050 
1 0.050 
2 0.050 
5 0.050 
10 0.050 
20 0.050 
50 0.050 
100 0.050 
200 0.050 
500 0.050 
1000 0.050 
Predicted Moisture content obtained from Equation X.4 
ANL-EBS-MD-000049 REV 02 X-19 October 2004 

Multiscale Thermohydrologic Model 
Table X-4. Moisture Retention Data for 10.0 mm Crushed Tuff 
Van Genuchten Curve Parameters 
Moisture Content at Saturation (.s) 0.45 
Residual Moisture Content (.r) 0.05 
Alpha (a) 2080 bars^-1 2.05 cm^-1 
n 8.01 
m 0.88 
Retention Analysis 
Moisture Potential 
.(bars) 
Predicted 
Moisture 
Content 
(.) 
0.0001 0.450 
0.0002 0.450 
0.0005 0.238 
0.001 0.052 
0.002 0.050 
0.005 0.050 
0.01 0.050 
0.02 0.050 
0.05 0.050 
0.1 0.050 
0.2 0.050 
0.5 0.050 
1 0.050 
2 0.050 
5 0.050 
10 0.050 
20 0.050 
50 0.050 
100 0.050 
200 0.050 
500 0.050 
1000 0.050 
Predicted Moisture content obtained from Equation X.4 
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Multiscale Thermohydrologic Model 
Table X-5. Moisture Retention Data for 20.0 mm Crushed Tuff 
van Genuchten Curve Parameters 
Moisture Content at Saturation (.s) 0.45 
Residual Moisture Content (.r) 0.05 
Alpha (a) 4160 bars^-1 4.09 cm^-1 
n 8.01 
m 0.88 
Retention Analysis 
Moisture Potential 
.(bars) 
Predicted 
Moisture 
Content 
(.) 
0.00001 0.450 
0.0002 0.384 
0.0005 0.052 
0.001 0.050 
0.002 0.050 
0.005 0.050 
0.01 0.050 
0.02 0.050 
0.05 0.050 
0.1 0.050 
0.2 0.050 
0.5 0.050 
1 0.050 
2 0.050 
5 0.050 
10 0.050 
20 0.050 
50 0.050 
100 0.050 
200 0.050 
500 0.050 
1000 0.050 
Predicted Moisture content obtained from Equation X.4 
ANL-EBS-MD-000049 REV 02 X-21 October 2004 

Multiscale Thermohydrologic Model 
1 
10 
100 
1000 
0.0001 
0.001 
0.01 
0.1 
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 
Volumetric Water Content 
Water Potential (-bars) 
Figure X-3. Nondimensionalized Relationship for Mean Particle Diameter of 0.317 mm 
1 
10 
100 
1000 
) 
0.0001 
0.001 
0.01 
0.1 
Water Potential (-bars
0.00 0.20 0.40 0.60 
Volum etric Water Content 
Figure X-4. Nondimensionalized Relationship for Mean Particle Diameter of 3.0 mm 
ANL-EBS-MD-000049 REV 02 X-22 October 2004 

Multiscale Thermohydrologic Model 
1 
10 
100 
1000 
) 
0.0001 
0.001 
0.01 
0.1 
Water Potential (-bars
0.00 0.20 0.40 0.60 
Volum etric Water Content 
Figure X-5. Nondimensionalized Relationship for Mean Particle Diameter of 10.0 mm 
1 
10 
100 
1000 
) 
0.00001 
0.0001 
0.001 
0.01 
0.1 
Water Potential (-bars
0.00 0.20 0.40 0.60 
Volum etric Water Content 
Figure X-6. Nondimensionalized Relationship for Mean Particle Diameter of 20.0 mm 
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Multiscale Thermohydrologic Model 
X.5 UNSATURATED HYDRAULIC CONDUCTIVITY AND CAPILLARY PRESSURE 
FOR THE CRUSHED TUFF INVERT 
The following discussion presents the methodology and the analysis for determining the 
relationship between unsaturated hydraulic conductivity (Kus) and capillary pressure from the 
retention curve using the two-parameter nondimensional van Genuchten relationship and the size 
of the crushed tuff. The basis for the nondimensional retention relationship is a least squares 
curve fit for a series of retention measurements made on the materials presented above. The 
nondimensional van Genuchten air-entry parameter (a) is determined from a scaling relationship 
while the nondimensional (n) parameter is constant. The intrinsic permeability (k) is determined 
from the Kozeny-Carman formula shown by Equation X.62 (Bear 1972 [DIRS 156269], p. 166) 
that relates intrinsic permeability (k) to the grain size or pore diameter (dm) and porosity (f). On 
the basis of the selected grain size, the saturated hydraulic conductivity (Ks) and the van 
Genuchten relationship for relative permeability, the relationship of unsaturated hydraulic 
conductivity (Kus) relationship to moisture potential (.) is determined. 
A qualitative assessment is made over the range of moisture potentials (.) of interest (0.01 to 0.1 
bars) as to whether significant intergranular liquid-phase advection in the coarse fraction of the 
crushed tuff would occur for a range of particle diameters. The analysis presented below is 
performed for grain size diameters of 0.317 mm, 3 mm, 10 mm and 20 mm for the intergranular 
porosity (f intergrain) respectively to cover a broad range of particle diameters. 
The wetting-phase relative permeability as a function of moisture potential (.) for van 
Genuchten curve fit is restated from Fetter (1993 [DIRS 102009], p. 182). The unsaturated 
hydraulic conductivity (Kus) (wetting-phase relative permeability times saturated hydraulic 
conductivity) as a function of moisture potential (.) is derived using Equation X.61 (same as Eq. 
4.17 of Fetter 1993 [DIRS 102009], with n=1/(1-m)). 
2
. .
.. 1 .. 
. 
.. 
n .. (Eq. X.61) 
. 1-( . a 
. .
K= K ( a,n, .,K )= K 
. 
).
. n - 1.
. ..
. 
1+( . a ) n ...
..
.
- 1 + .
.
.
. 
us 
ss . .
. 11 ..
. 
. .- ..
. ..
2n...
.
.. ..
.. 1 +( . a ) n ..
. 
.. 2 
... 
. 
.. 
. ..
. 
The intrinsic permeability (k) corresponding to a grain size of 3 mm is calculated from Equation 
X.52 as 1.51 10- 8 m2: 
f3 
k = dm2 
= 10 51.1 - 8  m2 (Eq. X.62) 
 
180 (1 -f )2 
Noting a conversion to saturated hydraulic conductivity from intrinsic permeability, the value for 
saturated conductivity is calculated for each of the particle sizes from 0.3 to 20 mm in diameter. 
ANL-EBS-MD-000049 REV 02 X-24 October 2004 

Multiscale Thermohydrologic Model 
The unsaturated hydraulic conductivity relationships are determined from the van Genuchten 
properties presented in Table X-1, and the saturated hydraulic conductivity. The calculations 
over a range of moisture potentials are presented in Table X-6, and are plotted in Figure X-7. 
Comparison of Conductivity Relationships 
1 
10 
100 
Hydraulic Conductivity (cm/s) 
1E-17 
1E-16 
1E-15 
1E-14 
1E-13 
1E-12 
1E-11 
1E-10 
1E-09 
1E-08 
1E-07 
1E-06 
1E-05 
0.0001 
0.001 
0.01 
0.1 
1000 
0.0001 0.001 0.01 0.1 1 10 100 1000
Moisture Potential (bars) 
Tuff Matrix k Tuff Fracture k 0.317 mm "3 mm" 10 mm 20 mm 
Figure X-7. Unsaturated Hydraulic Conductivity Relationships 
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Multiscale Thermohydrologic Model 
Table X-6. Unsaturated Hydraulic Conductivity (Kus) Calculations for the Non-Dimensionalized 
Moisture Potential (.) Retention Relation 
Moisture 
Potential 
Unsaturated Hydraulic Conductivity (Kus) (cm/sec) 
Particle Size (dm)
(.)(bars) Welded Tuff Matrix 0.317 mm 3 mm 10 mm 20 mm 
0.0001 6.23E-09 1.84E-01 1.65E+01 1.83E+02 7.29E+02 
0.0002 6.21E-09 1.84E-01 1.65E+01 1.82E+02 3.97E+02 
0.001 6.15E-09 1.84E-01 1.52E+01 8.60E-05 4.56E-10 
0.0015 6.13E-09 1.84E-01 4.54E+00 3.15E-08 1.66E-13 
0.002 6.10E-09 1.84E-01 1.16E-01 1.14E-10 6.01E-16 
0.005 5.99E-09 1.84E-01 2.81E-09 1.93E-18 1.01E-23 
0.01 5.86E-09 1.63E-01 3.71E-15 2.54E-24 1.36E-29 
0.02 5.66E-09 5.02E-04 4.89E-21 3.41E-30 2.02E-34 
0.05 5.24E-09 1.08E-11 8.27E-29 1.22E-35 5.45E-36 
0.1 4.74E-09 1.42E-17 1.57E-34 1.36E-36 5.92E-37 
0.2 4.02E-09 1.86E-23 7.34E-37 1.48E-37 6.30E-38 
DTN: MO0307SPAVGSUM.000 
NOTE: The values for the saturated hydraulic conductivity (Ks) (cm/sec) as a function of the moisture potential (.) 
are obtained by calculating the intrinsic permeability (k) for a given set of van Genuchten parameters from 
Equation X.62 and then applying the conversion from intrinsic permeability (k) to saturated hydraulic 
conductivity (Ks) (Freeze and Cherry 1979 [DIRS 101173], p. 27): 
. g
K = k
s 
 
The properties of water at ambient temperature are given by (Incropera and DeWitt 1996 [DIRS 108184], 
p. 846). The water density (.) equals 1000 kg/m3 and the absolute viscosity () equals 8.935 10-4 
Ns/(m2). The values for the unsaturated hydraulic conductivity are then determined by scaling the 
saturated hydraulic conductivity relationship by the relative permeability relationship presented in Eq. IV.11 
for a given moisture potential. 
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Multiscale Thermohydrologic Model 
X.6 SUMMARY OF HYDROLOGIC PROPERTIES BASED ON THE NONDIMENSIONALIZED 
MOISTURE POTENTIAL RETENTION RELATIONS 
The van Genuchten retention parameters as well as other hydrologic properties are summarized 
in Table X-7 over a range of particle sizes. These analyses show that the finer crushed tuff 
would have a greater tendency to retain water over the range of the moisture potentials in the 
repository. 
Table X-7. Summary of Hydrologic Properties Based on the Non-Dimensionalized Moisture Potential 
Retention Relation 
Parameter 
Particle Size (dm) 
0.317 mm 3 mm 10 mm 20 mm 
Saturated Volumetric Moisture Content (.s)a 0.450 0.450 0.450 0.450 
Residual Volumetric Moisture Content (.r) 0.050 0.050 0.050 0.050 
van Genuchten Air-entry Parameter (bars-1) (a)b 65.9 624. 2080. 4160. 
van Genuchten Air-entry Parameter (cm-1) (a) 0.0647 0.612 2.04 4.08 
van Genuchten n Value (n) 8.013 8.013 8.013 8.013 
van Genuchten m Value (m)c 0.875 0.875 0.875 0.875 
Saturated Intrinsic Permeability(m2) (k)d 1.68E-10 1.51E-08 1.67E-07 6.69E-07 
Saturated Hydraulic Conductivity (cm/sec) (Ks)e 0.184 16.48 183.1 732.5 
DTN: MO0307SPAVGSUM.000 
b See text and Table X-1 for the calculation of the van Genuchten Air-Entry Parameter (a) 
a 
The saturated volumetric moisture (.s) content equals the porosity (f) . 
d 
The value of n is given by 1/(1-m) (Fetter 1993 [DIRS 102009], p. 172). 
The intrinsic permeability (k) is calculated from Equation X.62. 
e 
The value of the saturated hydraulic conductivity (Ks) is obtained by the equation that converts an unsaturated 
intrinsic permeability (k) to a saturated hydraulic conductivity (Ks) (Freeze and Cherry 1979 [DIRS 101173], p. 
27): 
. g
K = k
s 
 
The properties of water at ambient temperature are given by (Incropera and DeWitt 1996 [DIRS 108184], p. 846). 
The water density (.) equals 997 kg/m3 and the absolute viscosity () equals 8.935 x10-4 Ns/(m2). Note that 
these values compare well with the values for sands and gravels from Freeze and Cherry (1979 [DIRS 101173], 
p. 29). 
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INTENTIONALLY LEFT BLANK
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Multiscale Thermohydrologic Model 
APPENDIX XI 
THERMAL CONDUCTIVITY OF THE COLLAPSED DRIFT ZONE 
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Multiscale Thermohydrologic Model 
This appendix presents two EXCEL workbooks used to corroborate the thermal conductivity of 
the collapsed drift as a function of the void fraction within this zone. Section XI.1 presents the 
calculation of the void fraction determination from the bulking factor as determined in Drift 
Degradation Analysis (BSC 2004 [DIRS 166107], Section 6.4.2 and Appendix V). Section XI.2 
presents the thermal conductivity calculation based upon the Kunii and Smith relationship (Kunii 
and Smith 1960 [DIRS 153166]). 
XI.1 ASSESSMENT OF THE VOID FRACTION WITHIN THE COLLAPSED DRIFT 
The intergranular porosity of collapsed drift material is a function of the bulking factor and 
lithophysal porosity. The lithophysal porosity is assumed to be added to the void volume after 
collapse. Consider that one cubic meter of drift collapses with a lithophysal porosity of f, and 
the bulking factor (a fraction) is B. Then the total void volume is f + B, and the total volume of 
the one cubic meter is 1 + B as presented in the derivation below. 
Derive the expression for the void fraction. Using the fundamental definition of lithophysal 
porosity: 
VvoidsfL Vsolids + Vvoids 
(Eq. XI-1) 
Where Vvoids is equal to the volume of the voids, and Vsolids is equal to the volume of the solids. 
Note the following relationship: 
VTotal Vsolids + Vvoids 
(Eq. XI-2) 
Where Vtotal is equal to the total volume. 
Now consider the new total volume is VTotal after bulking has occurred. Let Vsolids be equal to 
one, following the soil mechanics convention. Expressing the lithophysal porosity in terms of 
the volume of the voids: 
VvoidsfL 1 + Vvoids 
(Eq. XI-3) 
Now expressing the change in total volume in terms of the bulking factor: 
(1 + B)
V'Total VTotal 
(Eq. XI-4) 
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Multiscale Thermohydrologic Model 
Derive an expression for the volume of the voids before and after bulking. The volume of the 
voids after bulking: 
(1 + B) 
V'voids VTotal - Vsolids 
'= (1+ B) -1
VvoidsVTotal 
(Eq. XI-5) 
Solving for the volume of the voids in terms of the lithophysal porosity: 
fLVvoids 1 -fL 
(Eq. XI-6) 
Expressing the total volume in terms of the lithophysal porosity, with the volume of solids set to 
one: 
VTotal 1 + 
fL 
1 fL- 
(Eq. XI-7) 
The void fraction after bulking is defined as: 
Void_Fraction 
V'voids 
V'Total 
(Eq. XI-8) 
Substituting in the relationships for the void volume and the total volume: 
Void_Fraction 
1 + B( ) VTotal - 1 
1 + B( )VTotal 
(Eq. XI-9) 
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Multiscale Thermohydrologic Model 
.f L . 
(1 + B) . 1 +- 1. 1 -f L .
.
Void_Fraction 
.f L . 
(1 + B) . 1 +. 1 -f L .
. 
(Eq. XI-10) 
B +f LVoid_Fraction 
1 +B 
(Eq. XI-11) 
The calculations of the void fraction as a function of the lithophysal porosity, and of the bulking 
factor as given by Equation XI.11 are presented in the EXCEL workbook in Table XI-1. A 
range of lithophysal porosities are considered, 10% to 30%, and a range of bulking factors, 0.1 to 
0.4. The lithophysal porosity of interest is 35% for a lithophysal rock mass category of 1 (BSC 
2004 [DIRS 166107], Table 6-33). Category 1 and a bulking factor of 0.19 are chosen for 
analysis in Drift Degradation Analysis (BSC 2004 [DIRS 166107], Section 6.4.2.5). 
XI.2 SUMMARY OF THE EFFECTIVE THERMAL CONDUCTIVITY OF DRIFTCOLLAPSE 
MATERIAL 
Kunii and Smith (1960 [DIRS 153166]) describe a method for calculating the thermal 
conductivity of a porous medium with radiant heat transfer. The effective thermal conductivity 
is expressed by Kunii and Smith (1960 [DIRS 153166], Equation 8): 
.. 
.. 
.. 
k = kg 
...
e
..
. 
1 +߷ 
hrvk 
 
gDp .
..
+ 
߷ (1-e ) .
. 
1 k .
e . 
g 
.
+. 
1 D  h
. 
f+ pkg 
rs ks 
..
. 
. 
. 
(Eq. XI- 12) 
where 
Dp Nominal or average diameter of packing (m) 
hrv Heat transfer coefficient for radiation, void to void 
hrs Heat transfer coefficient for radiation, solid to solid 
ks Thermal conductivity of the solids (W/(m K) 
kg Thermal conductivity of the fluid (W/(m K) 
e Void fraction 
ANL-EBS-MD-000049 REV 02 XI-3 October 2004 

Multiscale Thermohydrologic Model 
 lp/Dp which equals 1 as presented by Kunii and Smith (1960 [DIRS 153166], p. 72). 
. ls/Dp which equals 2/3 as presented by Kunii and Smith (1960 [DIRS 153166], p. 72). 
. Ratio of the solids thermal conductivity to the thermal conductivity of air. 
The function f (. = ks/kg) is defined in Kunni and Smith (1960 [DIRS 153166], Equation 13) as: 
. ..- 1. 22 . 
. . sin(. ) . 
f (. ) =f( ks / k )= 1 . ... 
.- 1 
.- 2  1 
g 
. 
 (1- )) cos( 
.
. 
3 .
2 
.
. 
ln(.- (.- 1) )) cos( -
. 
... 
(Eq. XI-13) 
where sin(. 2) = 1/n, and n is associated with the fraction of the total heat transfer associated with 
one contact point (of the solids). Kunii and Smith (1960 [DIRS 153166], p. 74) define n  1.5 
for loose solids. 
The radiant heat transfer coefficients need to be estimated. The radiant heat-transfer coefficients 
(hrs and hrv) are given by Yagi and Kunii (1957 [DIRS 170330], Equations 7 and 8): 
h = 1952.0 { p 2 /( - p)}{ (t + 273)/100} 3 
rs 
(Eq. XI- 14) 
. .e
h =. 1952.0 /. 1 + 
2  (1-e ) 
 1 - p ..
.. (t + 273/100)3 
rv 
p
.. .. 
(Eq. XI-15) 
The lead coefficient of 0.1952 is derived from four times the Stephan Boltzmann constant in 
units of kcal/(m2 h K4) (Perry et al. 1984 [DIRS 125806], p. 10-53). 
The calculations are presented in Table XI-2. The calculations involve inputting the thermal 
parameters; estimating the thermal conductivity of the air as a function of absolute temperature 
using the relationship from Irvine (1998 [DIRS 170361]); estimating the f function using the 
equation presented above; estimating the radiant heat transfer coefficients using the relationships 
presented above; and then substituting these values into the effective thermal conductivity 
relationship presented by Kunii and Smith (1960 [DIRS 153166], Equation 8). 
The effective thermal conductivity of dry drift-collapse material is calculated to be 0.82 
W/(m K),  30%, or ranges from 0.57 to 1.05 W/(m K). The 0.82 W/(m K) value cited here is 
based on the following independent variables: a temperature of 75 C (with radiant heat transfer 
being temperature dependent); a lithophysal porosity of 35% and a bulking factor of 0.19, as 
noted previously; a dry rock thermal conductivity of 1.3998 W/(m K) for stratigraphic unit Tptpll 
(DTN: SN0404T0503102.011 [DIRS 169129], Table 7-11); drift-collapse material (rock size) of 
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Multiscale Thermohydrologic Model 
10 centimeters (BSC 2004 [DIRS 166107], Section 6.4.2.5); and a rock emissivity of 0.92, which 
is the midpoint of the range in Table 4.1-1. 
The uncertainty of 30% is based on a review of the literature by Crane et al. (1977 [DIRS 
113426]). An estimate of a wet effective thermal conductivity is not provided because there has 
been no analysis to show that the flux of water vapor down the thermal gradient is resupplied at 
the energy source by an equal or greater amount of liquid water. If there is no resupply of liquid 
water to the energy source, the collapse material will be dry. 
The effective thermal conductivity that contains a radiation component is a function of 
temperature. Consider that the base case described above at 75C has an effective thermal 
conductivity of 0.76 W/(mK) at 65C, and at 85C this becomes 0.86 W/(mK). 
ANL-EBS-MD-000049 REV 02 XI-5 October 2004 

Multiscale Thermohydrologic Model 
Table XI-1. Workbook for Determining the Void Fraction in the Collapsed Drift 
file: voidbulk.xls; 7/8/2004b 
Purpose: Calculate the void fraction after drift collapse as a 
function of the bulking factor and lithophysal porosity. The 
lithophysal porosity is added to the void volume. Therefore the 
void volume in 1 cubic meter of rock becomes the bulking factor + 
the lithophysal porosity %/100. 
Lithophysal Bulking 
Porosity Factor 
% 0.1 0.19 0.4 0.2 
10 0.18 0.24 0.36 0.25 
15 0.23 0.29 0.39 0.29 
20 0.27 0.33 0.43 0.33 
25 0.32 0.37 0.46 0.38 
27.5 0.34 0.39 0.48 0.40 
30 0.36 0.41 0.50 0.42 
35 0.41 0.45 0.54 0.46 
Intergranular Void 
Fraction
Obtain the lithophysal porosity from the drift degradation analysis, 
use 35% (BSC 2004 [DIRS 166107], Table 6-33) for Category 1, 
(BSC 2004 [DIRS 166107], Sect. 6.4.2.5), and a bulking factor of 
of 19% (BSC 2004 [DIRS 166107], Sec. 6.4.2.5). 
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Multiscale Thermohydrologic Model 
Table XI-2. Workbook for Calculation of the Collapsed Drift Thermal Conductivity 
file: thermalk.xls; 7/8/2004b 
Purpose: Calculate the effective thermal conductivity for loose solids, includes a contribution 
from radiant heat transfer. Refer to line 96 in this xls file for keff. 
Reference: S. Yagi & D. Kunii, AIChE J., 3(3), 373-381, 1957; refer to as Y&K [DIRS 170330]. 
Reference: D. Kunii & J.M. Smith, AIChE J., 6(1), 71-77, 1960; refer to as K&S [DIRS 153166]. 
ENTER THE FOLLOWING: 
Air thermal k = 0.030 W(m*K), calculated from temperature entered below. 
Rock thermal k = 1.3998 W/(m*K), wet = 2.0707, or dry = 1.3998. 
Void fraction = 0.45 from the bulking factor and lithophysal porosity. 
Rock size = 10 cm 
Rock emissivity = 0.92 Ranges from 0.88 to 0.95. 
Temperature = 75 deg C, see note at end of this file. 
Temperature = 348 deg K 
Stephan-Boltzmann= 5.67E-08 W/(m^2 K^4) 
Beta = 1.00 see page 72, right column K&S 
Gamma = 0.67 see page 72, right column K&S 
Uncertainty, % = 30 see notes 
Air thermal k from Irvine (1998 [DIRS 170361], p. 2.4). 
Void fraction from bulking factor & lithophysal porosity, see spreadsheet voidbulk.xls in Table XI-1. 
Rock thermal k from SN0404T0503102.011 ([DIRS 169129], file: Readme.doc). 
Rock size from Drift Degradation Analysis (BSC 2004 [DIRS 166107], Sec. 6.1.4.1). 
Rock emissivity is from Incropera & DeWitt (2002 [DIRS 163337], Table A.11). 
Stephan-Boltzmann constant from Cho, et al. (1998 [DIRS 160802], p.1.3). 
Calculate phi1 and phi2 in K&S, verify Figure 5, see plot on sheet2. 
phi1 is for loose packing, phi2 is for close packing. 
See K&S, page 74, left column for n1 and n2. 
n1 = 1.5 theta1 = 54.73 degrees, 
= 
0.955 radian 
n2 = 6.928 theta2 = 22.3 degrees, 
= 
0.389 radian 
sin^2(t1) = 0.666 cos(t1) = 0.577 
sin^2(t2) = 0.144 cos(t2) = 0.925 
Calculate phi1 & phi2 versus ks/kg using equation 13, K&S, page 73. 
kappa = Denom. Denom. Denom. Numerato 
r 
ks/kg log term cos term term phi1 = 
0.01 -0.542470853 -41.877 41.33453 3263.733 12.29233 
0.02 -0.53522138 -20.727 20.19178 799.533 6.263624 
0.05 -0.513783134 -8.037 7.523217 120.213 2.645603 
0.1 -0.479043714 -3.807 3.327956 26.973 1.438308 
0.2 -0.412989167 -1.692 1.279011 5.328 0.832386 
0.5 -0.237562492 -0.423 0.185438 0.333 0.46242 
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Table XI-2. Workbook for Calculation of the Collapsed Drift Thermal Conductivity (Continued) 
2 0.35267768 0.2115 0.141178 0.08325 0.256349 
5 0.990032778 0.3384 0.651633 0.21312 0.193722 
10 1.569674229 0.3807 1.188974 0.26973 0.160193 
20 2.200767898 0.40185 1.798918 0.300533 0.13373 
50 3.077773458 0.41454 2.663233 0.319813 0.106751 
100 3.757380549 0.41877 3.338611 0.326373 0.091091 
200 4.443602026 0.420885 4.022717 0.329678 0.078621 
500 5.355588201 0.422154 4.933434 0.331669 0.065896 
1000 6.047198316 0.422577 5.624621 0.332334 0.058419 
2000 6.739488203 0.422789 6.3167 0.332667 0.052331 
5000 7.655137182 0.422915 7.232222 0.332867 0.045892 
10000 8.347971888 0.422958 7.925014 0.332933 0.041944 
Calculate phi1 here in the next line for the given entries above. 
47.45 3.026864954 0.414085 2.61278 0.319112 0.108085 
phi2 is not used, it is calculated and plotted for further verification. 
phi2 = 
0.01 -0.077131455 -7.425 7.347869 705.672 29.37098 
0.02 -0.076321835 -3.675 3.598678 172.872 14.7043 
0.05 -0.073896901 -1.425 1.351103 25.992 5.904281 
0.1 -0.069868369 -0.675 0.605132 5.832 2.970906 
0.2 -0.061859681 -0.3 0.23814 1.152 1.504151 
0.5 -0.038211501 -0.075 0.036788 0.072 0.6238 
2 0.072302285 0.0375 0.034802 0.018 0.183874 
5 0.262297597 0.06 0.202298 0.04608 0.09445 
10 0.515682096 0.0675 0.448182 0.05832 0.063459 
20 0.885606432 0.07125 0.814356 0.06498 0.04646 
50 1.541837278 0.0735 1.468337 0.069149 0.03376 
100 2.130661932 0.07425 2.056412 0.070567 0.027649 
200 2.767186873 0.074625 2.692562 0.071282 0.02314 
500 3.647781143 0.07485 3.572931 0.071712 0.018738 
1000 4.328645811 0.074925 4.253721 0.071856 0.016226 
2000 5.015508247 0.074963 4.940546 0.071928 0.014225 
5000 5.927882982 0.074985 5.852898 0.071971 0.012163 
10000 6.619623289 0.074993 6.544631 0.071986 0.010933 
Calculate the radiation heat transfer coefficients from Y&K for solid-to-solid (hrs), 
equation (7), and void-to-void (hrv), equation (8): 
hrs = 8.14 W/(m^2 K) Note: division of temperature by 100 is not included 
hrv = 9.23 W/(m^2 K) because the Stephan-Boltzmann constant is used 
with its 10^-8. 
Calculate the effective conductivity from equation (8) from K&S for the given independent 
variables. 
term1 = 14.53 is the first term in equation (8) from K&S. 
term2 = 13.35 is the second term in equation (8) from K&S. 
ANL-EBS-MD-000049 REV 02 XI-8 October 2004 

Multiscale Thermohydrologic Model 
Table XI-2. Workbook for Calculation of the Collapsed Drift Thermal Conductivity (Continued) 
keff = 0.82 W/(m*K), is the effective thermal conductivity, equation (8), 
K&S. 
keff range based on input uncertainty = 0.58 to 1.07 W/(m*K) 
End of file note: The radiant heat transfer coefficients are temperature dependent. Therefore, the 
use of any heat transfer coefficient with a radiant contribution becomes a trial-and-error heat transfer 
calculation. It is necessary to choose a temperature at which to perform the heat transfer 
calculation and this temperature should be in the range of temperatures subsequently calculated. 
ANL-EBS-MD-000049 REV 02 XI-9 October 2004 

Multiscale Thermohydrologic Model 
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000049 REV 02 XI-10 October 2004 

Multiscale Thermohydrologic Model 
APPENDIX XII 
COMPARISON OF PERCOLATION FLUXES 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
This appendix compares percolation fluxes from UZ Flow Models and Submodels (BSC 2004 
[DIRS 169861]) models with the corresponding fluxes implemented in the discretization used for 
calculations with the multiscale thermohydrologic model (MSTHM). The detailed comparisons 
are for the three climates (present-day, monsoonal and glacial) and for the lower, mean and 
upper-bound infiltration flux cases. The input DTNs are discussed and input to the analysis in 
Section XII.1 through XII.2. The sampling points are presented. Sections XII.3 through XII.7 
develop the cumulative distribution functions. The cumulative distribution functions are 
developed for the respective cases and compared between the input DTN and its implementation 
in the MSTHM grid. 
Figure XII-1 presents a flowchart showing how information for making the comparison is 
obtained from the Technical Data Management System (TDMS). The upper portion of the 
flowchart shows DTN: MO0406CDFINSMT.000 for the UZ flow model. This DTN contains a 
summary EXCEL workbook file T2_perc_data_and CDF.xls. The workbook contains nine 
worksheets that correspond to three climates and three cases. These represent cumulative 
distribution functions that are weighted according to grid areas. Each of these worksheets are 
used to define MathCad Column vectors that represent nine individual cumulative distribution 
functions (CDFs). 
The lower portion of the flow chart shows the three output DTNs for the MSTHM model. These 
are DTNs: LL030608723122.028, LL030610323122.029, LL030602723122.027 for the lower, 
mean, and upper bounds respectively. These DTNs contain the following text files, all of which 
are used to define EXCEL components that are read into MathCad column vectors for purposes 
of plotting the distribution functions: 
 Nevada_SMT_percolation_BIN_la.txt 
 Nevada_SMT_percolation_BIN_ma.txt 
 Nevada_SMT_percolation_BIN_ua.txt 
The calculations presented in this appendix are performed in the MathCad File Cumulative 
Distribution Plots of Percolation.mcd. The data from the DTNs are input as EXCEL components 
in MathCad Professional 11. These DTNs are output from the multiscale thermohydrologic 
model. 
EXCEL components in MathCad represent an efficient method for inputting the data from the 
input DTNs into MathCad. The EXCEL components presented below are input from EXCEL 
files that in turn are compiled from text files as discussed below. The inputs are generally 
column vectors from the EXCEL spreadsheet component as defined by the output property for 
each EXCEL component in MathCad. 
ANL-EBS-MD-000049 REV 02 XII-1 October 2004 

Multiscale Thermohydrologic Model 
Cumulative Distribution Functions for the UZ Flow 
Model 
TDMS EXCEL Workbook EXCEL Worksheets 
DTN 
MO0406CDFINSMT.000 
glac_l 
glac_m 
glas_u 
mon_l 
mon_m 
mon_u 
pre_l 
pre_m 
pre_u 
Indivipre_m,pre_m_CDF 
mon_l,mon_l_CDF 
mon_m,mon_m_CDF 
gla_m,gla_m_CDF 
MathCad 
Cumulative Distribution Functions for the MSTHM 
Model 
DTNs _
_
_
Textfile 
Components from Monsoon 
Glacial 
TDMS 
Workbook 
T2_perc_data_and_CDF.xls 
Worksheets 
MathCad 
EXCELComponents for each 
dual Worksheets 
MathCad Column Vectors 
pre_l,pre_l_CDF 
pre_u,pre_u_CDF 
mon_u,mon_u_CDF 
gla_l,gla_l_CDF 
gla_u,gla_u_CDF 
Comparison Plots 
CDFs for Present Day 
CDFs for Monsson 
CDFs for Glacial 
for the two models. 
LL030608723122.028, 
LL030610323122.027, 
LL030602723122.029 
Nevada_SMT_percolation 
BIN_la.txt, 
Nevada_SMT_percolation 
BIN_ma.txt 
Nevada_SMT_percolation 
BIN_ua.txt 
MathCad EXCEL 
the Text File 
MathCad Column Vectors 
Modern or Present Day 
Figure XII-1. Flow Chart for Comparing Cumulative Distribution Functions 
ANL-EBS-MD-000049 REV 02 XII-2 October 2004 

Multiscale Thermohydrologic Model 
XII.1 INPUT DATA FROM THE 3-D SITE-SCALE UZ FLOW MODEL 
The DTN LB0302PTNTSW9I.001 [DIRS 162277] entitled PTN/TSW Interface Percolation 
Flux Maps for 9 Infiltration Scenarios and DTN LB03023DSSCP9I.001[DIRS 163044] 
entitled 3-D Site Scale UZ Flow Field Simulations for 9 Infiltration Scenarios were used to 
develop the cumulative distribution function for the nine cases in DTN 
MO0406CDFINSMT.000. Input the coordinate data from DTN LB03023DSSCP9I.001[DIRS 
163044] for purposes of developing a plot of sampling points of percolation for the UZ flow 
model. Note that any of the text files can be used since the coordinates are included in each file. 
Use the file monq_ma_ptn.q. 
.. 
..
EPTn
perc 
NPTn
perc 
.
.
:=
168251 229650 
168551 229650 
170181 229720 
170951 229650 
171551 229650 
172451 229650 
172750 229650 
168301 229890 
168551 229950 
170201 230010 
In the above EXCEL MathCad assignment, EPTNperc represents the Easting coordinate (m) 
vector, and NPTNperc represents the Northing coordinate (m) vector. 
Determine the number of points using the row function: 
)
(
rows EPTn
perc 
Rescale the data: 
j := 1 .. 2042 
EPTn
perc 

103
2.042
=
105
j
-
1.701

EPTn':=
percj 
1000 1000 
NPTn
perc 
j
-
2.319

105 
NPTn':=
percj 
1000 1000 
ANL-EBS-MD-000049 REV 02 XII-3 October 2004 

Multiscale Thermohydrologic Model 
Figure XII-2 shows the sampling points for the 3-D Site-Scale UZ Flow Model. 
Repository Layout 
Northing(km) 
4 
3 
2 
1 
0 
012 
Easting(km) 
Figure XII-2. Sampling Points for the Tough2 PTn/TSw Model 
Input the cumulative distribution functions from the EXCEL spreadsheet summarizing the results 
from DTN MO0406CDFINSMT.000. In this DTN, there is an EXCEL workbook entitled 
T2_perc_data_and_CDF.xls. This EXCEL workbook has 10 worksheets. The first worksheet is 
the combined data, and is not used in the analysis presented below. The next nine worksheets 
present cumulative distribution functions for the three climates and the three bounds as listed in 
Table XII-2. These are input to the MathCad program through the use of vectors using the 
properties tab for the EXCEL component. 
ANL-EBS-MD-000049 REV 02 XII-4 October 2004 

Multiscale Thermohydrologic Model 
Table XII-1. Summary of EXCEL Worksheets in T2_perc_data_and_CDF.xls for DTN 
MO0406CDFINSMT.000 
Climate Bound Worksheet Name 
Glacial Lower glac_l 
Glacial Mean glac_m 
Glacial Upper glac_u 
Monsoon Lower mon_l 
Monsoon Mean mon_m 
Monsoon Upper mon_u 
Present-Day Lower pre_l 
Present-Day Mean pre_m 
Present-Day Upper pre_u 
Input the values for the present day climate for the lower case. These values are obtained from 
the worksheet pre_l of T2_perc_data_and_CDF.xls. Note that only the first few rows are shown. 
..
.
pre_l 
pre_l_CDF 
.
.
:=
pre_l pre_l_CDF 
0.00 2.358330E-03 
0.00 4.716688E-03 
0.00 7.139175E-03 
0.00 9.718286E-03 
0.00 1.208377E-02 
0.00 1.416974E-02 
0.00 1.644986E-02 
pre_l represents the percolation flux in mm per year. pre_l_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
Input the values for the present day climate for the mean case. These values are obtained from 
the worksheet pre_m of T2_perc_data_and_CDF.xls 
..
.
pre_m 
pre_m_CDF 
.
.
:= 
pre_m pre_m_CDF 
0.203114 0.00257911 
0.20648 0.00523494 
0.298709 0.0075933 
0.337577 0.00987342 
0.363078 0.01223175 
0.440667 0.01445095 
0.445001 0.01691418 
0.466575 0.01900016 
0.561075 0.02154509 
ANL-EBS-MD-000049 REV 02 XII-5 October 2004 

Multiscale Thermohydrologic Model 
pre_m represents the percolation flux in mm per year. pre_m_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
Input the values for the present day climate for the upper case. These values are obtained from 
the worksheet pre_u of T2_perc_data_and_CDF.xls. 
..
.
pre_u 
pre_u_CDF 
.
.
:=
pre_u pre_u_CDF 
0.872483 0.0022801 
1.014349 0.0049359 
1.275882 0.0063444 
1.460394 0.0084303 
1.486113 0.0110095 
1.573294 0.0114768 
1.634857 0.0126458 
1.69199 0.0138239 
1.827775 0.0144066 
1.9445 0.0153848 
pre_u represents the percolation flux in mm per year. pre_u_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
Input the values for the monsoon climate for the lower case. These values are obtained from the 
worksheet mon_l of T2_perc_data_and_CDF.xls. 
..
.
mon_l 
mon_l_CDF 
.
.
:=
mon_l mon_l_CDF 
0.1104 0.00265583 
0.113641 0.00304332 
0.149631 0.00562243 
0.201519 0.00790255 
0.315411 0.01026091 
0.339742 0.01234688 
0.460166 0.01269943 
0.49525 0.01387761 
0.496857 0.01504657 
mon_l represents the percolation flux in mm per year. mon_l_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
ANL-EBS-MD-000049 REV 02 XII-6 October 2004 

Multiscale Thermohydrologic Model 
Input the values for the monsoon climate for the mean case. These values are obtained from the 
worksheet mon_m of T2_perc_data_and_CDF.xls. 
..
mon_m 
mon_m_CDF 
.
.
:=
mon_m mon_m_CDF 
0.317967 0.00228012 
0.339869 0.00493595 
0.464943 0.00751506 
0.668382 0.00960103 
0.865489 0.01195939 
0.914458 0.01442262 
0.935272 0.01678095 
0.937129 0.01900016 
1.567351 0.02089934 
mon_m represents the percolation flux in mm per year. mon_m_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
Input the values for the monsoon climate for the upper case. These values are obtained from the 
worksheet mon_u of T2_perc_data_and_CDF.xls. 
..
.
mon_u 
mon_u_CDF 
.
.
:=
mon_u mon_u_CDF 
0.615142 0.00228012 
1.213646 0.00493595 
1.302603 0.00702192 
2.1896 0.00960103 
2.466724 0.01100946 
2.505965 0.0114768 
2.721702 0.01205944 
2.949617 0.01273885 
3.309009 0.01391703 
3.37513 0.015086 
mon_u represents the percolation flux in mm per year. mon_u_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
ANL-EBS-MD-000049 REV 02 XII-7 October 2004 

Multiscale Thermohydrologic Model 
Input the values for the glacial climate for the lower case. These values are obtained from the 
worksheet glac_l of T2_perc_data_and_CDF.xls. 
..
glac_l 
glac_l_CDF 
.
.
:=
glac_l glac_l_CDF 
0.002101 0.00236548 
0.007418 0.00502132 
0.007655 0.00710729 
0.010456 0.00938741 
0.017005 0.0097749 
0.017178 0.01235401 
0.021309 0.01270911 
0.0608 0.01306165 
0.067621 0.01552488 
glac_l represents the percolation flux in mm per year. glac_l_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
Input the values for the glacial climate for the mean case. These values are obtained from the 
worksheet glac_m of T2_perc_data_and_CDF.xls. 
..
.
glac_m 
glac_m_CDF 
.
.
:=
glac_m glac_m_CDF 
0.604386 0.00265583 
0.772607 0.00493595 
0.827256 0.00751506 
1.086087 0.00997829 
1.222658 0.01219749 
1.312919 0.01428347 
1.757234 0.0166418 
1.942364 0.01900016 
2.488503 0.02136434 
glac_m represents the percolation flux in mm per year. glac_m_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
ANL-EBS-MD-000049 REV 02 XII-8 October 2004 

Multiscale Thermohydrologic Model 
Input the values for the glacial climate for the upper case. These values are obtained from the 
worksheet glac_u of T2_perc_data_and_CDF.xls. 
..
glac_u 
glac_u_CDF 
.
.
:=
glac_u glac_u_CDF 
1.533968 0.002280115 
2.549426 0.004935948 
2.83767 0.007021922 
4.015425 0.00748926 
4.621348 0.010068371 
4.734478 0.011476797 
5.203607 0.012059437 
5.413422 0.012738851 
5.888617 0.013907817 
glac_u represents the percolation flux in mm per year. glac_u_CDF represents the cumulative 
distribution pertaining to the percolation flux (dimensionless). 
XII.2 INPUT DATA FROM THE MSTHM 
Consider the output DTNs containing the percolation flux boundary conditions for the MSTHM. 
These DTNs are summarized below: 
Table XII-1 Output DTNs for MSTHM model 
Lower Percolation Rate DTN: LL030608723122.028 
Mean Percolation Rate DTN: LL030610323122.029 
Upper Percolation Rate DTN: LL030602723122.027 
Input the properties for the mean case. Note that the data are organized for the three climates for 
the lower, mean, and upper percolation rates presented above. The data are obtained from the 
text file Nevada_SMT_percolation_BIN_ma.txt of DTN: LL030610323122.029. Note that only 
the first few rows of the EXCEL component derived from the textfile are shown below. 
ANL-EBS-MD-000049 REV 02 XII-9 October 2004 

Multiscale Thermohydrologic Model 
E
perc 
N
perc 
.
. 
. 
. 
. 
. 
. 
.
.
Modernmean 
Monsoonmean 
Glacialmean 
. 
....
.
:=
easting northing Modern Monsoon Glacial 
171132.8 236151.3 2.220288 7.246367 10.20758 
171151.8 236157.5 2.265795 7.410341 10.59777 
171170.8 236163.7 2.311301 7.574315 10.98797 
171189.8 236169.9 2.356808 7.738289 11.37816 
171208.8 236176.1 2.402314 7.902264 11.76835 
171227.9 236182.3 2.447821 8.066237 12.15854 
171246.9 236188.5 2.493327 8.230211 12.54874 
171265.9 236194.7 2.538834 8.394186 12.93893 
171284.9 236200.8 2.58434 8.558161 13.32912 
171303.9 236207 2.629847 8.722135 13.71932 
Modernmean represents the percolation flux vector (mm/yr) for the mean bound for the present 
day climate. Monsoonmean represents the percolation flux vector (mm/yr) for the for mean 
bound for the monsoon climate. Glacialmean represents the percolation flux vector (mm/yr) for 
the for mean bound for the glacial climate. Eperc represents the easting coordinate vector (m). 
Nperc represents the northing coordinate vector. 
Input the percolation fluxes for the lower bound case. The data that are read into the EXCEL 
component presented below are obtained from the text file Nevada_SMT_percolation_BIN_la.txt 
of from DTN: LL030608723122.028. 
.
. 
. 
. 
.
Modernlower 
Monsoonlower 
Glaciallower 
.
.
.
:= 
Modern Monsoon Glacial 
0.555732 4.865694 2.496985 
0.576192 4.890319 2.519521 
0.596651 4.914944 2.542056 
0.617111 4.939568 2.564592 
0.637571 4.964193 2.587128 
0.658031 4.988817 2.609663 
0.678491 5.013442 2.632199 
0.698951 5.038067 2.654735 
0.719411 5.062692 2.677271 
0.739871 5.087317 2.699807 
0.76033 5.111941 2.722343 
0.78079 5.136565 2.744878 
ANL-EBS-MD-000049 REV 02 XII-10 October 2004 

Multiscale Thermohydrologic Model 
Modernlower represents the percolation flux vector (mm/yr) for the lower bound for the present 
day climate. Monsoonlower represents the percolation flux vector (mm/yr) for the for lower 
bound for the monsoon climate. Glaciallower represents the percolation flux vector (mm/yr) for 
the for lower bound for the glacial climate. 
Input the percolation fluxes for the upper bound case. The data that are read into the EXCEL 
component presented below are obtained from the text file 
Nevada_SMT_percolation_BIN_ua.txt of from DTN: LL030602723122.027. 
. Modern upper .
.
. Monsoon upper .
:=
.
. Glacial 
upper . 
Modern Monsoon Glacial 
11.33837 20.15363 29.32075 
11.27895 19.90239 29.25167 
11.21954 19.65115 29.18258 
11.16013 19.39991 29.11349 
11.10072 19.14868 29.04441 
11.04131 18.89744 28.97532 
10.9819 18.6462 28.90624 
10.92249 18.39497 28.83715 
10.86308 18.14373 28.76806 
10.80367 17.89249 28.69898 
10.74425 17.64126 28.62989 
10.68484 17.39002 28.5608 
Modernupper represents the percolation flux vector (mm/yr) for the upper bound for the present 
day climate. Monsoonupper represents the percolation flux vector (mm/yr) for the for upper 
bound for the monsoon climate. Glacialupper represents the percolation flux vector (mm/yr) for 
the for upper bound for the glacial climate. 
Rescale the plots to km. 
j := 1 .. rows Eperc)
( 
min Eperc)= 1.701 105
(
E(
percj min Eperc)
E':= -
percj 1000 1000
min Nperc)= 2.319 105
(
Npercj min Nperc)
(
N':= -
percj 1000 1000 
ANL-EBS-MD-000049 REV 02 XII-11 October 2004 

Multiscale Thermohydrologic Model 
ANL-EBS-MD-000049 REV 02 XII-12 October 2004 
Figure XII-2 shows the SMT sampling locations. 
01201234Repository LayoutEasting(km)
Northing(km) 
Figure XII-3. Sampling Points for the MSTHM Model 
XII.3 COMPARISONS FOR THE PRESENT-DAY CLIMATE 
The data for the present-day climate from the MSTHM calculations have equal weightings. In 
order to develop the CDF for the MSTHM model, sort the data in ascending order. Note that 
since the percolation values are for areas that are equal weighting, the CDF is determined 
directly by sorting the data in MathCad, and plotting the sorted data against the rank order 
expressed as a percentile. Output the first 16 values in mm/yr Modernlower for purposes of 
illustration: 

Multiscale Thermohydrologic Model 
Modernlower = 
Determine the number of rows in the column vector: 
rows Modernlower)= 2.874 103
( 
Now use the sort function in MathCad to sort the values in ascending order: 
Modernlower := sort Modernlower)
( 
Output the first values to show that MathCad sorted the values in ascending order: 
Modernlower = 
1 
1 0.556 
2 0.576 
3 0.597 
4 0.617 
5 0.638 
6 0.658 
7 0.678 
8 0.699 
9 0.719 
10 0.74 
11 0.76 
12 0.781 
13 0.801 
14 0.822 
15 0.892 
16 0.961 
1 
2.810-53.810-54.410-54.710-54.910-5510-55.610-55.910-5610-56.110-56.210-56.310-56.410-56.610-56.710-5710-5
Now sort the other cases having demonstrating the results for the lower case: 
ANL-EBS-MD-000049 REV 02 XII-13 October 2004 

Multiscale Thermohydrologic Model 
Modernmean := sort Modernmean)
( 
Modern:= sort Modernupper)
upper ( 
Develop the CDF by plotting the rank order against the sorted values for mean, lower and upper 
Cumulative Probability 
percolation cases. The results are shown in Figure XII-3 for the modern or present case. The 
figure shows the .05, 0.30,0.70, and 0.95 percentiles for the CDF. 
Perform the analysis for the other cases. These are presented in Figures XII-4 through XII-6. 
jj := 1 .. rows Modernlower)
( 
mm := 1 .. rows( pre_l) 
Percolation CDFs Present Lower 
1 
0.8 
0.6 
0.4 
0.2 
0 
01234 
Percolation (mm/yr) 
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-4. Cumulative Distribution Function Comparison for the Present Day Lower Case 
ANL-EBS-MD-000049 REV 02 XII-14 October 2004 

Multiscale Thermohydrologic Model 
jj := 1 .. rows Modernmean)
( 
Percolation CDFs Present Mean 
0 5 10 15 200 
0.2 
0.4 
0.6 
0.8 
1 
SMT Model 
Percolation (mm/yr) 
Cumulative Probability 
jj 1.0
mean()
pre_m_CDFmm 
.05 
0.3 
0.7 
0.95 
Modernmean jj 
pre_mmm,
rows Modern
Tough 2 Model 
0.05 Percentile
0.30 Percentile
0.70 Percentile
0.95 Percentile
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-5. Cumulative Distribution Function Comparison for the Present-Day Mean Infiltration-Flux 
Case 
ANL-EBS-MD-000049 REV 02 XII-15 October 2004 

Multiscale Thermohydrologic Model 
Percolation CDFs PresentUpper 
1 
0.8 
Cumulative Probability
0.6 
0.4 
0.2 
0 
0 10203040 
Percolation (mm/yr) 
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-6. Cumulative Distribution Function Comparison for the Present Day Upper Case 
XII.4 COMPARISONS FOR THE MONSOONAL CLIMATE 
The data for the monsoonal climate from the MSTHM calculations have equal weightings. In 
order to develop the CDF for the MSTHM, sort the data in ascending order. 
Monsoonlower := sort Monsoonlower)
( 
Monsoonmean := sort Monsoonmean)
( 
Monsoon:= sort Monsoonupper)
upper ( 
Develop the CDF by plotting the rank order against the sorted values for lower-, mean, and 
upper-bound infiltration-flux cases. Figures XII-7 through XII-9 show these cases for the 
monsoonal climate. 
ANL-EBS-MD-000049 REV 02 XII-16 October 2004 

Multiscale Thermohydrologic Model 
jj 
:= 1 .. rows Monsoonlower)
( 
Percolation CDFs Monsoon Lower 
0 5 10 15 200 
0.2 
0.4 
0.6 
0.8 
1 
MSTHM Model 
Percolation (mm/yr) 
Cumulative Probability 
3D UZ Model 
0.05 Percentile
0.30 Percentile
0.70 Percentile
0.95 Percentile
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-7. Cumulative Distribution Function Comparison for the Monsoonal-Climate Lower-Bound 
Infiltration-Flux Case 
ANL-EBS-MD-000049 REV 02 XII-17 October 2004 

Multiscale Thermohydrologic Model 
jj 
:= 1 .. rows Monsoonmean)
( 
(
mm := 1 .. rows mon_m ) 
Percolation CDFs Monsoon Mean 
00 
0.2 
0.4 
0.6 
0.8 
1 
MSTHM Model 
Percolation (mm/yr) 
20 40 60 80 
Cumulative Probability 
3D UZ Model 
0.05 Percentile
0.30 Percentile
0.70 Percentile
0.95 Percentile
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-8. Cumulative Distribution Function Comparison for the Monsoonal-Climate Mean Infiltration-
Flux Case 
ANL-EBS-MD-000049 REV 02 XII-18 October 2004 

Multiscale Thermohydrologic Model 
Percolation CDFs Monsoon Upper 
0 100 120 1400 
0.2 
0.4 
0.6 
0.8 
1 
MSTHM Model 
Percolation (mm/yr) 
20 40 60 80 
Cumulative Probability 
3D UZ Model 
0.05 Percentile
0.30 Percentile
0.70 Percentile
0.95 Percentile
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-9. Cumulative Distribution Function Comparison for the Monsoonal-Climate Upper-Bound 
Infiltration-Flux Case 
ANL-EBS-MD-000049 REV 02 XII-19 October 2004 

Multiscale Thermohydrologic Model 
XII.5 COMPARISONS FOR THE GLACIAL CLIMATE 
The data for the glacial climate from the MSTHM calculations have equal weightings. In order 
to develop the CDF for the MSTHM, sort the data in ascending order. 
Glaciallower := sort Glaciallower)
( 
Cumulative Probability 
Glacialmean := sort Glacialmean)
( 
Glacial:= sort Glacialupper)
upper ( 
Develop the CDF by plotting the rank order against the sorted values for lower-, mean, and 
upper-bound infiltration-flux cases. Figures XII-10 through XII-12 show these cases for the 
glacial climate. 
jj := 1 .. rows Glaciallower)
(
Percolation CDFs Glacial Lower 
1 
0.8 
0.6 
0.4 
0.2 
0 
3D UZ Model 
0 5 10 15 
MSTHM Model 
Percolation (mm/yr) 
0.05 Percentile
0.30 Percentile
0.70 Percentile
0.95 Percentile
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-10. Cumulative Distribution Function Comparison for the Glacial-Climate Lower-Bound 
Infiltration-Flux Case 
ANL-EBS-MD-000049 REV 02 XII-20 October 2004 

Multiscale Thermohydrologic Model 
jj := 1 .. rows Glacialmean)
(
(
mm := 1 .. rows glac_m ) 
Percolation CDFs Glacial Mean 
00 
0.2 
0.4 
0.6 
0.8 
1 
MSTHM Model 
Percolation (mm/yr) 
Cumulative Probability 
20 40 60 80 
3D UZ Model 
0.05 Percentile
0.30 Percentile
0.70 Percentile
0.95 Percentile
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-11. Cumulative Distribution Function Comparison for the Glacial-Climate Mean Infiltration-Flux 
Case 
ANL-EBS-MD-000049 REV 02 XII-21 October 2004 

Multiscale Thermohydrologic Model 
0 100 150 2000 
0.2 
0.4 
0.6 
0.8 
1 
MSTHM Model 
Percolation CDFs Glacial Upper 
Percolation (mm/yr) 
Cumulative Probability 
50 
3D UZ Model 
0.05 Percentile
0.30 Percentile
0.70 Percentile
0.95 Percentile
NOTE: Red line = MSTHM model; blue line = UZ flow model. 
Figure XII-12. Cumulative Distribution Function Comparison for the Glacial-Climate Upper-Bound 
Infiltration-Flux Case 
XII.8 SUMMARY OF RESULTS 
Comparisons between the two models have been conducted. The comparisons of the cumulative 
distribution functions (CDF) show good agreement for the nine cases considered in the analysis 
with minor differences attributable to differences in gridding, sampling locations, and the areas 
tributary to sampling locations. 
ANL-EBS-MD-000049 REV 02 XII-22 October 2004 

Multiscale Thermohydrologic Model 
APPENDIX XIII 
LIST OF DATA SOURCES FOR FIGURES AND TABLES 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures 
Figure 
No. Data Source File Name 
Plotting 
Software Notes 
4-1 LL030808623122.036 INPUT/main_runs/SMT/tspa03.mesh03-150w MATLAB 
v6.1.0.450 
(R12.1) 
4-2 LL040703123122.049 percolation_flux_files/ccdf_modern_perc_new-old-layouts.pltsc 
percolation_flux_files/ccdf_monsoonal_perc_new-old-layouts.pltsc 
percolation_flux_files/ccdf_glacial_perc_new-old-layouts.pltsc 
XTOOL v10.1 
6.1-2 Buscheck et al. 2002 XTOOL v10.1 
[DIRS 160749], 
Figure 2 
6.2-3 LL030808623122.036 INPUT/main_runs/SMT/tspa03.mesh03-150w MATLAB 
v6.1.0.450 
(R12.1) 
6.2-6 LL030808623122.036 INPUT/main_runs/LDTH/mi/LDTH55/P2WR5C10-LDTH55-1Dds_mc-mi-01.in RADPRO v4.0 
6.2-7 LL030808623122.036 INPUT/initialization_runs/DDT/DDT55/P2WR5C10-DDT55-01v.in RADPRO v4.0 
6.2-8 LL030808623122.036 INPUT/main_runs/DDT/DDT55/P2WR5C10-DDT55-03.in RADPRO v4.0 
6.2-9 LL030808623122.036 INPUT/initialization_runs/DDT/DDT55/P2WR5C10-DDT55-01v.in RADPRO v4.0 
6.2-10 LL030808623122.036 INPUT/main_runs/DDT/DDT55/P2WR5C10-DDT55-03.in RADPRO v4.0 
6.2-11 LL040310323122.044 Submodel_input_files_listing/P2WR5C10-LDTH55-mi-mkt-14.in RADPRO v4.0 
6.2-12 LL040310323122.044 Submodel_input_files/P2WR5C10-DDT55_nat-bkfl-11.in RADPRO v4.0 
6.3-1 LL030808623122.036 INPUT/main_runs/SMT/tspa03.mesh03-150w MATLAB 
v6.1.0.450 
(R12.1) 
6.3-2 LL030808523122.035 MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz XTOOL v10.1 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
ANL-EBS-MD-000049 REV 02 XIII-1 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. Data Source File Name 
Plotting 
Software Notes 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz 
6.3-3 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
Tecplot v9.2-
0-3 (09-16-
2002) 
6.3-4 LL030808523122.035 MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-2 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. Data Source File Name 
Plotting 
Software Notes 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
6.3-5 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
Tecplot v9.2-
0-3 (09-16-
2002) 
6.3-6 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
Tecplot v9.2-
0-3 (09-16-
2002) 
6.3-7 LL030808523122.035 MSTHAC/li_abstractions/OUTPUT/li_P2e@r#111:46:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#111:46:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#111:46:1.ext.gz 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-3 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-8 LL030808523122.035 MSTHAC/li_abstractions/OUTPUT/li_P2w@r#94:46:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#94:46:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#94:46:1.ext.gz 
XTOOL v10.1 
6.3-9 LL030808523122.035 MSTHAC/li_abstractions/OUTPUT/li_P2w@r#79:55:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#79:55:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#79:55:1.ext.gz 
XTOOL v10.1 
6.3-10 LL030808523122.035 MSTHAC/li_abstractions/OUTPUT/li_P3@r#51:49:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#51:49:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#51:49:1.ext.gz 
XTOOL v10.1 
6.3-11 LL030808523122.035 MSTHAC/li_abstractions/OUTPUT/li_P3@r#33:46:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#33:46:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#33:46:1.ext.gz 
XTOOL v10.1 
6.3-12 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#111:46:1.ext.gz XTOOL v10.1 
6.3-13 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#94:46:1.ext.gz XTOOL v10.1 
6.3-14 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#79:55:1.ext.gz XTOOL v10.1 
6.3-15 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#51:49:1.ext.gz XTOOL v10.1 
6.3-16 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#33:46:1.ext.gz XTOOL v10.1 
6.3-17 LL030804023122.034 mi-mkt/P2ER8C6/mi-mkt-P2ER8C6.ext.gz 
mi-mkt/P2ER8C6_EXT/mi-mkt-P2ER8C6.ext.gz 
XTOOL v10.1 
6.3-18 LL030804023122.034 mi-mkt/P2WR8C8/mi-mkt-P2WR8C8.ext.gz 
mi-mkt/P2WR8C8_EXT/mi-mkt-P2WR8C8.ext.gz 
XTOOL v10.1 
6.3-19 LL030804023122.034 mi-mkt/P2WR5C10/mi-mkt-P2WR5C10.ext.gz 
mi-mkt/P2WR5C10_EXT/mi-mkt-P2WR5C10.ext.gz 
XTOOL v10.1 
6.3-20 LL030804023122.034 mi-mkt/P3R8C13/mi-mkt-P3R8C13.ext.gz 
mi-mkt/P3R8C13_EXT/mi-mkt-P3R8C13.ext.gz 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-4 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-21 LL030804023122.034 dp-mkt/P2ER8C6/dp-mkt-P2ER8C6.ext.gz 
mi-mkt/P2ER8C6/mi-mkt-P2ER8C6.ext.gz 
fp-mkt/ P2ER8C6/fp-mkt-P2ER8C6.ext.gz 
XTOOL v10.1 
6.3-22 LL030804023122.034 dp-mkt/P2WR8C8/dp-mkt-P2WR8C8.ext.gz 
mi-mkt/P2WR8C8/mi-mkt-P2WR8C8.ext.gz 
fp-mkt/ P2WR8C8/fp-mkt-P2WR8C8.ext.gz 
XTOOL v10.1 
6.3-23 LL030804023122.034 dp-mkt/P2WR5C10/dp-mkt-P2WR5C10.ext.gz 
mi-mkt/P2WR5C10/mi-mkt-P2WR5C10.ext.gz 
fp-mkt/ P2WR5C10/fp-mkt-P2WR5C10.ext.gz 
XTOOL v10.1 
6.3-24 LL030804023122.034 dp-mkt/P3R8C13/dp-mkt-P3R8C13.ext.gz 
mi-mkt/P3R8C13/mi-mkt-P3R8C13.ext.gz 
fp-mkt/ P3R8C13/fp-mkt-P3R8C13.ext.gz 
XTOOL v10.1 
6.3-25 LL030804023122.034 mi-1lkt/P2ER8C6/mi-1lkt-P2ER8C6.ext.gz 
mi-mkt/P2ER8C6/mi-mkt-P2ER8C6.ext.gz 
mi-1hkt/P2ER8C6/mi-1hkt-P2ER8C6.ext.gz 
XTOOL v10.1 
6.3-26 LL030804023122.034 mi-1lkt/P2WR8C8/mi-1lkt-P2WR8C8.ext.gz 
mi-mkt/P2WR8C8/mi-mkt-P2WR8C8.ext.gz 
mi-1hkt/P2WR8C8/mi-1hkt-P2WR8C8.ext.gz 
XTOOL v10.1 
6.3-27 LL030804023122.034 mi-1lkt/P2WR5C10/mi-1lkt-P2WR5C10.ext.gz 
mi-mkt/P2WR5C10/mi-mkt-P2WR5C10.ext.gz 
mi-1hkt/P2WR5C10/mi-1hkt-P2WR5C10.ext.gz 
XTOOL v10.1 
6.3-28 LL030804023122.034 mi-1lkt/P3R8C13/mi-1lkt-P3R8C13.ext.gz 
mi-mkt/P3R8C13/mi-mkt-P3R8C13.ext.gz 
mi-1hkt/P3R8C13/mi-1hkt-P3R8C13.ext.gz 
XTOOL v10.1 
6.3-29 LL030804023122.034 dp-1lkt/P2ER8C6/dp-1lkt-P2ER8C6.ext.gz 
mi-mkt/P2ER8C6/mi-mkt-P2ER8C6.ext.gz 
fp-1hkt/ P2ER8C6/fp-1hkt-P2ER8C6.ext.gz 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-5 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-30 LL030804023122.034 dp-1lkt/P2WR8C8/dp-1lkt-P2WR8C8.ext.gz 
mi-mkt/P2WR8C8/mi-mkt-P2WR8C8.ext.gz 
fp-1hkt/ P2WR8C8/fp-1hkt-P2WR8C8.ext.gz 
XTOOL v10.1 
6.3-31 LL030804023122.034 dp-1lkt/P2WR5C10/dp-1lkt-P2WR5C10.ext.gz 
mi-mkt/P2WR5C10/mi-mkt-P2WR5C10.ext.gz 
fp-1hkt/ P2WR5C10/fp-1hkt-P2WR5C10.ext.gz 
XTOOL v10.1 
6.3-32 LL030804023122.034 dp-1lkt/P3R8C13/dp-1lkt-P3R8C13.ext.gz 
mi-mkt/P3R8C13/mi-mkt-P3R8C13.ext.gz 
fp-1hkt/ P3R8C13/fp-1hkt-P3R8C13.ext.gz 
XTOOL v10.1 
6.3-33 LL040102223122.042 01/P2ER8C6-LDTH55-1Dds_mc-li-01.m.EBS.ext (a) 
01/P2ER8C6-LDTH55-1Dds_mc-li-01.f.EBS.ext (c) 
02/P2ER8C6-LDTH55-1Dds_mc-li-02.m.EBS.ext (a) 
02/P2ER8C6-LDTH55-1Dds_mc-li-02.f.EBS.ext (c) 
01/P2ER8C6-LDTH55-1Dds_mc-ui-01.m.EBS.ext (b) 
01/P2ER8C6-LDTH55-1Dds_mc-ui-01.f.EBS.ext (d) 
02/P2ER8C6-LDTH55-1Dds_mc-ui-02.m.EBS.ext (b) 
02/P2ER8C6-LDTH55-1Dds_mc-ui-02.f.EBS.ext (d) 
XTOOL v10.1 T ds at upper drip-
shield gridblock 
RHds at drift block 
above upper drip-
shield block 
6.3-34 LL040102223122.042 01/P2WR8C8-LDTH55-1Dds_mc-li-01.m.EBS.ext (a) 
01/P2WR8C8-LDTH55-1Dds_mc-li-01.f.EBS.ext (c) 
02/P2WR8C8-LDTH55-1Dds_mc-li-02.m.EBS.ext (a) 
02/P2WR8C8-LDTH55-1Dds_mc-li-02.f.EBS.ext (c) 
01/P2WR8C8-LDTH55-1Dds_mc-ui-01.m.EBS.ext (b) 
01/P2WR8C8-LDTH55-1Dds_mc-ui-01.f.EBS.ext (d) 
02/P2WR8C8-LDTH55-1Dds_mc-li-02.m.EBS.ext (b) 
02/P2WR8C8-LDTH55-1Dds_mc-li-02.f.EBS.ext (d) 
XTOOL v10.1 T ds at upper drip-
shield gridblock 
RHds at drift block 
above upper drip-
shield block 
ANL-EBS-MD-000049 REV 02 XIII-6 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-35 LL040102223122.042 01/P2WR5C10-LDTH55-1Dds_mc-li-01.m.EBS.ext (a) 
01/P2WR5C10-LDTH55-1Dds_mc-li-01.f.EBS.ext (c) 
02/P2WR5C10-LDTH55-1Dds_mc-li-02.m.EBS.ext (a) 
02/P2WR5C10-LDTH55-1Dds_mc-li-02.f.EBS.ext (c) 
XTOOL v10.1 T ds at upper drip-
shield gridblock 
RHds at drift block 
above upper drip-
shield block 
01/P2WR5C10-LDTH55-1Dds_mc-ui-01.m.EBS.ext (b) 
01/P2WR5C10-LDTH55-1Dds_mc-ui-01.f.EBS.ext (d) 
02/P2WR5C10-LDTH55-1Dds_mc-ui-02.m.EBS.ext (b) 
02/P2WR5C10-LDTH55-1Dds_mc-ui-02.f.EBS.ext (d) 
6.3-36 LL040102223122.042 01/P3R8C13-LDTH55-1Dds_mc-li-01.m.EBS.ext (a) 
01/P3R8C13-LDTH55-1Dds_mc-li-01.f.EBS.ext (c) 
02/P3R8C13-LDTH55-1Dds_mc-li-02.m.EBS.ext (a) 
02/P3R8C13-LDTH55-1Dds_mc-li-02.f.EBS.ext (c) 
XTOOL v10.1 T ds at upper drip-
shield gridblock 
RHds at drift block 
above upper drip-
shield block 
01/P3R8C13-LDTH55-1Dds_mc-ui-01.m.EBS.ext (b) 
01/P3R8C13-LDTH55-1Dds_mc-ui-01.f.EBS.ext (d) 
02/P3R8C13-LDTH55-1Dds_mc-ui-02.m.EBS.ext (b) 
02/P3R8C13-LDTH55-1Dds_mc-ui-02.f.EBS.ext (d) 
6.3-37 LL040703123122.049 base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.m.EBS.ex.gz (matrix) MATLAB 
base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) v6.1.0.450 
(R12.1) 
6.3-38 LL040703123122.049 base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) MATLAB 
base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) v6.1.0.450 
(R12.1) 
6.3-39 LL040703123122.049 base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) MATLAB 
base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) v6.1.0.450 
(R12.1) 
6.3-40 LL040703123122.049 base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) MATLAB 
base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) v6.1.0.450 
(R12.1) 
ANL-EBS-MD-000049 REV 02 XIII-7 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-41 LL040703123122.049 base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-42 LL040703123122.049 base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-43 LL040703123122.049 base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-44 LL040703123122.049 base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-45 LL040703123122.049 base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-46 LL040703123122.049 base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2ER8C6-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-47 LL040703123122.049 base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2WR8C8-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-48 LL040703123122.049 base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
6.3-49 LL040703123122.049 base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (matrix) 
base-case_output/P3R8C13-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (fracture) 
MATLAB 
v6.1.0.450 
(R12.1) 
ANL-EBS-MD-000049 REV 02 XIII-8 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-51 LL030808523122.035 
LL030905931032.001 
LL030906331032.004 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1.ext.gz 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P1@r#*:*:1.ext.gz 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-9 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P5@r#*:*:1.ext.gz 
6.3-52 LL030808523122.035 
LL030905931032.001 
LL030906331032.004 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz (a) 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz (a) 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz (a) 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz (a) 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2e@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2w@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1.ext.gz (a) 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-10 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P1@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2e@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2w@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P3@r#*:*:1.ext.gz (a) 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P5@r#*:*:1.ext.gz (a) 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF_pillar.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
(b) 
ANL-EBS-MD-000049 REV 02 XIII-11 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
MSTHAC_abstraction/MSTHAC_output/LI-
lkt_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC_abstraction/MSTHAC_output/LI-
lkt_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
(b) 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz 
(b) 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF_pillar.txt 
MSTHAC_abstraction/MSTHAC_output/UI-
hkt_P1@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC_abstraction/MSTHAC_output/UI-
hkt_P2e@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC_abstraction/MSTHAC_output/UI-
hkt_P2w@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC_abstraction/MSTHAC_output/UI-
hkt_P3@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
MSTHAC_abstraction/MSTHAC_output/UI-
hkt_P5@r#*:*:1_T_horizontalPillar_Xdist.ext.gz (b) 
6.3-53 LL030808523122.035 
LL030905931032.001 
LL030906331032.004 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-12 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1.ext.gz 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P5@r#*:*:1.ext.gz 
6.3-54 LL030808523122.035 
LL030905931032.001 
LL030906331032.004 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-13 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1.ext.gz 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P5@r#*:*:1.ext.gz 
6.3-55 LL040310323122.044 
LL030804023122.034 
From LL040310323122.044: 
MSTHAC_output/P2WR5C10-mi-mkt_nat-bkfl-11-15.ext (low Kth) 
MSTHAC_output/P2WR5C10-mi-mkt_nat-bkfl-10-14.ext (high Kth) 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-14 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
From LL030804023122.034 
mi-mkt/P2WR5C10/mi-mkt-P2WR5C10.ext.gz (Intact drift) 
6.3-56 LL040310323122.044 
LL030804023122.034 
From LL040310323122.044: 
MSTHAC_output/P2WR5C10-mi-mkt_nat-bkfl-11-15.ext (low Kth) 
MSTHAC_output/P2WR5C10-mi-mkt_nat-bkfl-10-14.ext (high Kth) 
From LL030804023122.034: 
mi-mkt/P2WR5C10/mi-mkt-P2WR5C10.ext.gz (Intact drift) 
XTOOL v10.1 
6.3-57 LL040310323122.044 
LL030804023122.034 
From LL040310323122.044: 
MSTHAC_output/P2WR5C10-mi-mkt_nat-bkfl-11-15.ext (low Kth) 
MSTHAC_output/P2WR5C10-mi-mkt_nat-bkfl-10-14.ext (high Kth) 
From LL030804023122.034: 
mi-mkt/P2WR5C10/mi-mkt-P2WR5C10.ext.gz (Intact drift) 
XTOOL v10.1 
6.3-58 LL040501323122.046 The following files are found in file: rubble_heat-capacity output files.zip: 
P2WR5C10-LDTH55-mi-mkt-15.m.EBS.ext (a) 
P2WR5C10-LDTH55-mi-mkt-17.m.EBS.ext (a) 
P2WR5C10-LDTH55-mi-mkt-15.f.EBS.ext (b) 
P2WR5C10-LDTH55-mi-mkt-17.f.EBS.ext (b) 
XTOOL v10.1 
6.3-59 LL030808523122.035 MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#51:49:1.ext.gz XTOOL v10.1 
6.3-60 LL040501323122.046 host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e2-09.m.EBS.ext (a,b) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e2-09.m.EBS.ext (a,b) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e2-09.m.EBS.ext (a,b) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e2-09.m.EBS.ext (a,b) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e1-09.m.EBS.ext (c,d) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e1-09.m.EBS.ext (c,d) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e1-09.m.EBS.ext (c,d) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e1-09.m.EBS.ext (c,d) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e-1-09.m.EBS.ext (e,f) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e-1-09.m.EBS.ext (e,f) 
MATLAB 
v6.1.0.450 
(R12.1) 
Tdw is the grid-
block-volume-
weighted average 
for host-rock 
gridblocks around 
drift perimeter 
Tds is the grid-
block-volume-
weighted average 
around drip-shield 
perimeter 
ANL-EBS-MD-000049 REV 02 XIII-15 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e-1-09.m.EBS.ext (e,f) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e-1-09.m.EBS.ext (e,f) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e-2-09.m.EBS.ext (g,h) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e-2-09.m.EBS.ext (g,h) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e-2-09.m.EBS.ext (g,h) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e-2-09.m.EBS.ext (g,h) 
6.3-61 LL040501323122.046 host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e2-09.f.EBS.ext (a,b) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e2-09.f.EBS.ext (a,b) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e2-09.f.EBS.ext (a,b) 
MATLAB 
v6.1.0.450 
(R12.1) 
RHdw is the grid-
block-volume-
weighted average 
for host-rock 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e2-09.f.EBS.ext (a,b) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e1-09.f.EBS.ext (c,d) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e1-09.f.EBS.ext (c,d) 
gridblocks around 
drift perimeter 
RHds is the grid-
block-volume-
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e1-09.f.EBS.ext (c,d) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e1-09.f.EBS.ext (c,d) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e-1-09.f.EBS.ext (e,f) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e-1-09.f.EBS.ext (e,f) 
weighted average 
for drift gridblocks 
around drip-shield 
perimeter 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e-1-09.f.EBS.ext (e,f) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e-1-09.f.EBS.ext (e,f) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw33-e-2-09.f.EBS.ext (g,h) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw34-e-2-09.f.EBS.ext (g,h) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw35-e-2-09.f.EBS.ext (g,h) 
host-rock_study output_files/P2WR5C10-LDTH55-mi-tsw36-e-2-09.f.EBS.ext (g,h) 
6.3-62 LL040703123122.049 base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (a) 
base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (b) 
pseudo-kb_ouput/P2WR5C10-LDTH55-mi-mkt-kbe-12-02.m.EBS.ext.gz (a) 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-12-02.f.EBS.ext.gz (b) 
XTOOL v10.1 T ds at upper drip-
shield gridblock 
RHds at drift block 
above upper drip-
shield block 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-10-02.m.EBS.ext.gz (a) 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-10-02.f.EBS.ext.gz (b) 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-9-02.m.EBS.ext.gz (a) 
ANL-EBS-MD-000049 REV 02 XIII-16 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-9-02.f.EBS.ext.gz (b) 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-7-02.m.EBS.ext.gz (a) 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-7-02.f.EBS.ext.gz (b) 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-6-02.m.EBS.ext.gz (a) 
pseudo-kb_output/P2WR5C10-LDTH55-mi-mkt-kbe-6-02.f.EBS.ext.gz (b) 
6.3-63 LL040501323122.046 invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw33inv-02.f.EBS.ext (a) 
invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw33inv-02.m.EBS.ext (b) 
invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw34inv-02.f.EBS.ext (a) 
invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw34inv-02.m.EBS.ext (b) 
invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw35inv-02.f.EBS.ext (a) 
invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw35inv-02.m.EBS.ext (b) 
invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw36inv-02.f.EBS.ext (a) 
invert_study output_files/P2WR5C10-LDTH55-mi-mkt_tsw36inv-02.m.EBS.ext (b) 
XTOOL v10.1 Sliq,inv is the grid-
block-volume-
weighted average 
for the invert 
gridblocks 
Tinv is the grid-
block-volume-
weighted average 
for the invert 
gridblocks 
6.3-64 LL040703123122.049 invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw33inv-02fninv.m.EBS.ext.gz (a) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw33inv-02fninv.f.EBS.ext.gz (b) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw34inv-02fninv.m.EBS.ext.gz (c) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw34inv-02fninv.f.EBS.ext.gz (d) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw35inv-02fninv.m.EBS.ext.gz (e) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw35inv-02fninv.f.EBS.ext.gz (f) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw36inv-02fninv.m.EBS.ext.gz (g) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw36inv-02fninv.f.EBS.ext.gz (h) 
XTOOL v10.1 T and RH 
obtained for 
center gridblock at 
upper invert layer 
below drip shield 
6.3-65 LL040703123122.049 invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw35inv-02fninv.m.EBS.ext.gz (a,b; 
base case) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case1-02.m.EBS.ext.gz (a,b) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case2-02.m.EBS.ext.gz (a,b) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case3-02.m.EBS.ext.gz (a,b) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case4-02.m.EBS.ext.gz (a,b) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_tsw35inv-02fninv.f.EBS.ext.gz (c; base 
case) 
XTOOL v10.1 T and RH 
obtained for 
center gridblock at 
indicated locations 
ANL-EBS-MD-000049 REV 02 XIII-17 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case1-02.f.EBS.ext.gz (c) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case2-02.f.EBS.ext.gz (c) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case3-02.f.EBS.ext.gz (c) 
invert_study_output/P2WR5C10-LDTH55-mi-mkt_case4-02.f.EBS.ext.gz (c) 
6.3-66 LL040703123122.049 base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.m.EBS.ext.gz (a) 
base-case_output/P2WR5C10-LDTH55-mi-mkt-02Q.f.EBS.ext.gz (b) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-70p.m.EBS.ext.gz (a) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-70p.f.EBS.ext.gz (b) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-80p.m.EBS.ext.gz (a) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-80p.f.EBS.ext.gz (b) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-90p.m.EBS.ext.gz (a) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-90p.f.EBS.ext.gz (b) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-100p.m.EBS.ext.gz (a) 
vent_study_output/P2WR5C10-LDTH55-mi-mkt-02.in-100p.f.EBS.ext.gz (b) 
XTOOL v10.1 T ds at upper drip-
shield gridblock 
RHds at drift block 
above upper drip-
shield block 
6.3-67 LL030808523122.035 
LL030905931032.001 
LL030906331032.004 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz 
MATLAB 
v6.1.0.450 
(R12.1) 
ANL-EBS-MD-000049 REV 02 XIII-18 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1.ext.gz 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P5@r#*:*:1.ext.gz 
6.3-68 LL030808523122.035 
LL030905931032.001 
LL030906331032.004 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz 
MATLAB 
v6.1.0.450 
(R12.1) 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz 
ANL-EBS-MD-000049 REV 02 XIII-19 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1.ext.gz 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P5@r#*:*:1.ext.gz 
6.3-69 LL030808523122.035 
LL030905931032.001 
LL030906331032.004 
From LL030808523122.035: 
MSTHAC/li_abstractions/OUTPUT/li_P1@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P2e@r#*:*:1.ext.gz 
MATLAB 
v6.1.0.450 
(R12.1) 
MSTHAC/li_abstractions/OUTPUT/li_P2w@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P3@r#*:*:1.ext.gz 
MSTHAC/li_abstractions/OUTPUT/li_P5@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P1@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2e@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P2w@r#*:*:1.ext.gz 
ANL-EBS-MD-000049 REV 02 XIII-20 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
MSTHAC/mi_abstractions/OUTPUT/mi_P3@r#*:*:1.ext.gz 
MSTHAC/mi_abstractions/OUTPUT/mi_P5@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P1@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2e@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P2w@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P3@r#*:*:1.ext.gz 
MSTHAC/ui_abstractions/OUTPUT/ui_P5@r#*:*:1.ext.gz 
From LL030905931032.001: 
/post_process/createCCDFS/LI-lkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/LI-lkt_P5@r#*:*:1.ext.gz 
From LL030906331032.004: 
/post_process/createCCDFS/UI-hkt_CCDF.txt 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P1@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2e@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P2w@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P3@r#*:*:1.ext.gz 
MSTHAC_abstraction/MSTHAC_output/UI-hkt_P5@r#*:*:1.ext.gz 
7.3-1 LL040703023122.048 OUTPUTS/ms-valid-LBT-02.ST.m.ext.gz XTOOL v10.1 
7.3-2 LL040703023122.048 OUTPUTS/ms-valid-LBT-02.ST.m.ext.gz 
OUTPUTS/ms-valid-LBT-02.m.P.ext.gz 
XTOOL v10.1 
7.4-2 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.ext (base case) XTOOL v10.1 
7.4-3 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-21 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
7.4-4 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-5 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-6 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-7 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-22 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
7.4-8 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-9 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-10 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-11 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-12 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-23 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
7.4-13 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-14 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-15 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.T (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.T 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.T (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.T 
(high Kth, restart run) 
XTOOL v10.1 
7.4-16 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.ext (base case) XTOOL v10.1 
7.4-17 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.S (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.S 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.S (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.S 
(high Kth, restart run) 
XTOOL v10.1 
ANL-EBS-MD-000049 REV 02 XIII-24 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
7.4-18 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.S (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.S 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.S (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.S 
(high Kth, restart run) 
XTOOL v10.1 
7.4-19 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.xyz.S (base case) 
MSTHM_large_block/DST/BH__SEAL/OUTPUTS/ ms-valid-DST-03-bhSeal.m.xyz.S 
(sealed bulkhead) 
MSTHM_large_block/DST/SENSITIV/OUTPUTS/ ms-valid-DST-sensit-1htk.m.xyz.S (high 
Kth) 
MSTHM_large_block/DST/SENSITIV_R/OUTPUTS/ ms-valid-DST-sensit-1htkr.m.xyz.S 
(high Kth, restart run) 
XTOOL v10.1 
7.4-20 LL030808923122.039 MSTHM_large_block/DST/MAIN_RUN/OUTPUTS/ ms-valid-DST-03.m.ext (base case) XTOOL v10.1 
7.5-2 LL040703223122.050 MSTHAC_center_output: 
center_MSTHAC7_T_ds.ext.gz 
center_MSTHAC7_T_dw.ext.gz 
DLMTH_center_output: 
ms-valid-anisot-cen-01r.m.T.EBS.ext.gz (no gas transport along drift) 
ms-valid-anisot-cen-01rb.m.T.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rc.m.T.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rd.m.T.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01re.m.T.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rf.m.T.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-mixed-cen-01r.m.T.EBS.ext.gz (with sealed bulkhead) 
XTOOL v10.1 D/LMDTH model: 
Tdw is the grid-
block-volume-
weighted average 
for host-rock 
gridblocks around 
drift perimeter 
Tds is the grid-
block-volume-
weighted average 
around drip-shield 
perimeter 
7.5-3 LL040703223122.050 MSTHAC_center_output: 
center_MSTHAC7_RH_ds.ext.gz 
center_MSTHAC7_RH_dw.ext.gz 
XTOOL v10.1 D/LMTH model: 
RHdw is the grid-
block-volume-
weighted average 
ANL-EBS-MD-000049 REV 02 XIII-25 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
DLMTH_center_output: 
ms-valid-anisot-cen-01r.f.RH.EBS.ext.gz (no gas transport along drift) 
ms-valid-anisot-cen-01rb.f.RH.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rc.f.RH.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rd.f.RH.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01re.f.RH.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rf.f.RH.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-mixed-cen-01r.f.RH.EBS.ext.gz (with sealed bulkhead) 
for host-rock 
gridblocks around 
drift perimeter 
RHds is the grid-
block-volume-
weighted average 
for drift gridblocks 
around drip-shield 
perimeter 
7.5-4 LL040703223122.050 MSTHAC_center_output: 
center_MSTHAC7_S.liq_dw.ext.gz 
center_MSTHAC7_S.liq_invert.ext.gz 
DLMTH_center_output: 
ms-valid-anisot-cen-01r.m.S.EBS.ext.gz (no gas transport along drift) 
ms-valid-anisot-cen-01rb.m.S.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rc.m.S.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rd.m.S.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01re.m.S.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-anisot-cen-01rf.m.S.EBS.ext.gz (no gas transport along drift, restart) 
ms-valid-mixed-cen-01r.m.S.EBS.ext.gz (with sealed bulkhead) 
XTOOL v10.1 D/LMTH model: 
Sliq,dw is the grid-
block-volume-
weighted average 
for host-rock 
gridblocks around 
drift perimeter 
Sliq,inv is the grid-
block-volume-
weighted average 
for the invert 
gridblocks 
7.5-5 LL040703223122.050 MSTHAC_edge_output: 
edge_MSTHAC7_T_ds.ext.gz 
edge_MSTHAC7_T_dw.ext.gz 
DLMTH_edge_output: 
ms-valid-anisot-edge-01r.m.T.EBS.ext.gz (no gas transport along drift) 
ms-valid-mixed-edge-01r.m.T.EBS.ext.gz (with sealed bulkhead) 
ms-valid-mixed-edge-01rb.m.EBS.T.ext.gz (with sealed bulkhead, restart) 
ms-valid-mixed-edge-19.m.T.ext.gz (no bulkhead) 
ms-valid-mixed-edge-19b.m.T.ext.gz (no bulkhead, restart) 
XTOOL v10.1 D/LMDTH model: 
Tdw is the grid-
block-volume-
weighted average 
for host-rock 
gridblocks around 
drift perimeter 
Tds is the grid-
block-volume-
weighted average 
around drip-shield 
perimeter 
ANL-EBS-MD-000049 REV 02 XIII-26 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-1. List of Data Sources for Figures (Continued) 
Figure 
No. 
Data Source File Name Plotting 
Software 
Notes 
7.5-6 LL040703223122.050 MSTHAC_edge_output: 
edge_MSTHAC7_RH_ds.ext.gz 
edge_MSTHAC7_RH_dw.ext.gz 
DLMTH_edge_output: 
ms-valid-anisot-edge-01r.f.RH.EBS.ext.gz (no gas transport along drift) 
ms-valid-mixed-edge-01r.f.RH.EBS.ext.gz (with sealed bulkhead) 
ms-valid-mixed-edge-01rb.f.RH.EBS.ext.gz (with sealed bulkhead, restart) 
ms-valid-mixed-edge-19.f.RH.EBS.EBS.ext.gz (no bulkhead) 
ms-valid-mixed-edge-19b.f.RH.EBS.EBS.ext.gz (no bulkhead, restart) 
XTOOL v10.1 D/LMTH model: 
RHdw is the grid-
block-volume-
weighted average 
for host-rock 
gridblocks around 
drift perimeter 
RHds is the grid-
block-volume-
weighted average 
for drift gridblocks 
around drip-shield 
perimeter 
7.5-7 LL040703223122.050 MSTHAC_edge_output: 
edge_MSTHAC7_S.liq_dw.ext.gz 
edge_MSTHAC7_S.liq_invert.ext.gz 
DLMTH_edge_output: 
ms-valid-anisot-edge-01r.m.S.ext.gz (no gas transport along drift) 
ms-valid-mixed-edge-01r.m.S.ext.gz (with sealed bulkhead) 
ms-valid-mixed-edge-01rb.m.S.ext.gz (with sealed bulkhead, restart) 
ms-valid-mixed-edge-19.m.S.ext.gz (no bulkhead) 
ms-valid-mixed-edge-19b.m.S.ext.gz (no bulkhead, restart) 
XTOOL v10.1 D/LMTH model: 
Sliq,dw is the grid-
block-volume-
weighted average 
for host-rock 
gridblocks around 
drift perimeter 
Sliq,inv is the grid-
block-volume-
weighted average 
for the invert 
gridblocks 
ANL-EBS-MD-000049 REV 02 XIII-27 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-2. List of Data Sources for Tables 
Table 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-1 LL040704323122.051 li-02/output: 
P2ER4C4-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER5C5-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER6C6-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER8C7-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER8C6-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER8C5-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER7C6-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER7C5-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER6C5-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER3C4-LDTH66-1Dds_mc-li-02i.m.ext 
P2ER2C5-LDTH66-1Dds_mc-li-02i.m.ext 
P2WR1C8-LDTH66-1Dds_mc-li-02i.m.ext 
P3R1C11-LDTH66-1Dds_mc-li-02i.m.ext 
P3R8C13-LDTH66-1Dds_mc-li-02i.m.ext 
mi-02/output: 
P2ER4C4-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER5C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER6C6-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER8C7-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER8C6-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER8C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER7C6-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER7C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER6C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER3C4-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER2C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2WR1C8-LDTH66-1Dds_mc-mi-02i.m.ext 
P3R1C11-LDTH66-1Dds_mc-mi-02i.m.ext 
P3R8C13-LDTH66-1Dds_mc-mi-02i.m.ext 
ui-02/output: 
P2ER4C4-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER5C5-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER6C6-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER8C7-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER8C6-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER8C5-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER7C6-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER7C5-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER6C5-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER3C4-LDTH66-1Dds_mc-ui-02i.m.ext 
P2ER2C5-LDTH66-1Dds_mc-ui-02i.m.ext 
P2WR1C8-LDTH66-1Dds_mc-ui-02i.m.ext 
P3R1C11-LDTH66-1Dds_mc-ui-02i.m.ext 
P3R8C13-LDTH66-1Dds_mc-ui-02i.m.ext 
XTOOL 
v10.1 
ANL-EBS-MD-000049 REV 02 XIII-28 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-2. List of Data Sources for Tables (Continued) 
Table 
No. 
Data Source File Name Plotting 
Software 
Notes 
6.3-2 LL040704323122.051 mi-02/output: 
P2ER4C4-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER4C4-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER5C5-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER5C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER6C6-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER6C6-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER8C7-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER8C7-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER8C6-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER8C6-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER8C5-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER8C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER7C6-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER7C6-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER7C5-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER7C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER6C5-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER6C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER3C4-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER3C4-LDTH66-1Dds_mc-mi-02i.m.ext 
P2ER2C5-LDTH66-1Dds_mc-mi-02i.f.ext 
P2ER2C5-LDTH66-1Dds_mc-mi-02i.m.ext 
P2WR1C8-LDTH66-1Dds_mc-mi-02i.f.ext 
P2WR1C8-LDTH66-1Dds_mc-mi-02i.m.ext 
P3R1C11-LDTH66-1Dds_mc-mi-02i.f.ext 
P3R1C11-LDTH66-1Dds_mc-mi-02i.m.ext 
P3R8C13-LDTH66-1Dds_mc-mi-02i.f.ext 
P3R8C13-LDTH66-1Dds_mc-mi-02i.m.ext 
mi-01/ouput: 
P2ER4C4-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER4C4-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER5C5-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER5C5-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER6C6-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER6C6-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER8C7-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER8C7-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER8C6-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER8C6-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER8C5-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER8C5-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER7C6-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER7C6-LDTH66-1Dds_mc-mi-01i.m.ext 
XTOOL 
v10.1 
ANL-EBS-MD-000049 REV 02 XIII-29 October 2004 

Multiscale Thermohydrologic Model 
Table XIII-2. List of Data Sources for Tables (Continued) 
Table 
No. 
Data Source File Name Plotting 
Software 
Notes 
P2ER7C5-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER7C5-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER6C5-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER6C5-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER3C4-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER3C4-LDTH66-1Dds_mc-mi-01i.m.ext 
P2ER2C5-LDTH66-1Dds_mc-mi-01i.f.ext 
P2ER2C5-LDTH66-1Dds_mc-mi-01i.m.ext 
P2WR1C8-LDTH66-1Dds_mc-mi-01i.f.ext 
P2WR1C8-LDTH66-1Dds_mc-mi-01i.m.ext 
P3R1C11-LDTH66-1Dds_mc-mi-01i.f.ext 
P3R1C11-LDTH66-1Dds_mc-mi-01i.m.ext 
P3R8C13-LDTH66-1Dds_mc-mi-01i.f.ext 
P3R8C13-LDTH66-1Dds_mc-mi-01i.m.ext 
ANL-EBS-MD-000049 REV 02 XIII-30 October 2004 

Multiscale Thermohydrologic Model 
APPENDIX XIV 
QUALIFICATION OF UNQUALIFIED PROJECT DATA 
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ANL-EBS-MD-000049 REV 02 October 2004 

Multiscale Thermohydrologic Model 
This appendix presents the results of the documentation of a data qualification task. The 
checking, reviewing, and documentation of the results of the data qualification activity are 
performed according to AP-SIII.2Q, Rev. 1 ICN 2, dated June 27, 2004. The following 
discussion addresses point by point the data qualification: 
Data Set for Qualification: 
The data set for qualification is DTN: MO0304MWDALACV.000 [DIRS 164551]. 
Methods of Qualification Selected: 
The method selected for qualification is through the use of corroborating data. The data sets for 
ventilation efficiencies or heat generation fractions from the qualified source are compared to the 
source requiring qualification both spatially and temporally to determine if the comparisons 
satisfy the quantitative evaluation criteria. The rationale for this method is that if the heat mass 
fractions are in agreement to within the range of uncertainty, then the temperatures predicted at 
the drift wall from the average waste package line loading will be in agreement over the 
postclosure period that is analyzed in the multiscale thermohydrologic model. 
Evaluation Criteria: 
Appendix III presents the heat generation fractions derived from ventilation efficiencies for the 
various submodels used in this report. The DTN for ventilation efficiency (DTN: 
MO0304MWDALACV.000 [DIRS 164551]) requires qualification according to the data 
qualification plan (BSC 2004 [DIRS 170747]). This plan requires a comparison of the heat 
generation fraction (ventilation efficiencies) at times of 10, 20, 30, and 50 years at distances of 
100, 200, 300, 400, 500, 600, 700, and 800 meters from the ventilation inlet from DTN: 
MO0304MWDALACV.000 [DIRS 164551] with the qualified source from DTN: 
MO0306MWDASLCV.001 [DIRS 165695]. The criterion for data qualification is that the 
difference in heat generation fraction or ventilation efficiency from these two sources is less than 
0.02, or 2%. This difference represents an estimate in the uncertainty in the data. 
Evaluation of the Technical Correctness of the Data, as Applicable: 
As documented in Ventilation Model and Analysis Report (BSC 2004 [DIRS 169862]), both 
analytical and finite element methods were developed for assessing spatial and temporal 
variations in ventilation efficiencies for use in repository preclosure analysis. These calculations 
show that for the selected repository design parameters, and existing thermal properties of the 
rock mass surrounding the emplacement drift at the repository horizon, a high ventilation 
efficiency is achievable over a range of conditions as predicted by either analytical or finite-
element methods and that the ventilation efficiency is insensitive to variations in rock thermal 
properties. The ventilation model was validated against measured data in Ventilation Model and 
Analysis Report (BSC 2004 [DIRS 169862]). Therefore, since the ventilation model is validated, 
correct ventilation efficiencies or heat mass fractions are calculated from the qualified source. 
ANL-EBS-MD-000049 REV 02 XIV-1 October 2004 

Multiscale Thermohydrologic Model 
Data Generated by the Evaluation 
Table XIV-1 presents the heat generation fraction or ventilation efficiencies (rounded to three 
decimal places) at the times and locations from the source DTNs reproduced from Table III-1 
and III-2, and the absolute value of the differences in these values that constitutes the data 
generated by this evaluation. The difference in heat generation fraction is equal to the difference 
in ventilation efficiency. The table shows that the criterion for data qualification from the plan is 
satisfied, with the maximum difference being 0.006 or 0.6%. 
Table XIV-1 Qualification of Heat Removal Fraction or Ventilation Efficiency 
Time 
(yr) 
Distance from Ventilation Inlet (m) 
100 200 300 400 500 600 700 800 
Net Available Heat Generation Fraction used in this Report from Table III-1. 
10 0.072 0.099 0.125 0.152 0.178 0.204 0.230 0.254 
20 0.043 0.069 0.094 0.118 0.143 0.167 0.192 0.213 
30 0.039 0.061 0.083 0.104 0.125 0.145 0.166 0.187 
50 0.009 0.027 0.045 0.064 0.081 0.100 0.117 0.135 
Net Available Heat Generation Fraction from the Updated Data Source from Table III-2. 
10 0.071 0.098 0.123 0.149 0.175 0.200 0.225 0.248 
20 0.043 0.068 0.093 0.117 0.141 0.164 0.188 0.210 
30 0.040 0.062 0.083 0.104 0.125 0.146 0.166 0.186 
50 0.010 0.029 0.048 0.067 0.086 0.103 0.121 0.139 
Difference between the Sources 
10 0.001 0.001 0.002 0.003 0.003 0.004 0.005 0.006 
20 0.000 0.001 0.001 0.001 0.002 0.003 0.004 0.003 
30 0.001 0.001 0.000 0.000 0.000 0.001 0.000 0.001 
50 0.001 0.002 0.003 0.003 0.005 0.003 0.004 0.004 
NOTE: Values presented in this table from Tables III-1 and III-2 are rounded to the third decimal place. 
EVALUATION RESULTS: 
Based upon the comparisons made above, and based upon the experience of the data 
qualification team, the data are qualified for use in the calculations reported in Section 6.3. 
Rationale for Abandoning any Qualification Methods, if Appropriate: 
Note that a single method was specified in the data qualification plan, and that there were no 
deviations from this plan. Therefore this item does not apply to the data qualification effort. 
Limits or Caveats Considered by Potential Users of the Data: 
The ventilation efficiency or heat mass fraction as presented in DTN: 
MO0304MWDALACV.000 [DIRS 164551] is based upon the current repository design 
involving an emplacement drift diameter of 5.5 m; an emplacement drift spacing of 81 m; an 
emplacement drift length varying from 600 m to 800 m; a ventilation air flow rate of 15 m3/sec; 
and a ventilation preclosure period of 50 years. The heat mass fraction from these DTNs is 
ANL-EBS-MD-000049 REV 02 XIV-2 October 2004 

Multiscale Thermohydrologic Model 
limited to this repository design. Any change in these design parameters would require a new 
analysis of heat mass fraction with the technical method of analysis presented in Ventilation 
Model and Analysis Report (BSC 2004 [DIRS 169862]). 
Identification of Any Supporting Information Used in the Qualification Effort: 
Note that the qualification is a direct comparison, and requires no supporting information other 
than the source DTN, and the method of analysis as presented in Ventilation Model and Analysis 
Report (BSC 2004 [DIRS 169862]). 
Data Qualification Plan: 
The data are qualified according to Data Qualification Plan, Qualification of DTN: 
MO0304MWDALACV.000 for Use in ANL-EBS-MD-000049 Rev02 (BSC 2004 [DIRS 170747]). 
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Multiscale Thermohydrologic Model 
INTENTIONALLY LEFT BLANK
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Multiscale Thermohydrologic Model 
APPENDIX XV 
PREDICTION OF RH IN THE INVERT 
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Multiscale Thermohydrologic Model 
This appendix presents a method for the calculation of the relative humidity in the invert from 
the temperature and saturation time histories obtained from the multiscale thermohydrologic 
analysis. The method is being implemented in the total system performance assessment because 
of a problem in the method that MSTHAC Version 7.0 uses to calculate the invert relative 
humidity. The calculation presented in this appendix can be used to verify the calculation 
method used in the total system performance assessment. The saturation and temperature 
histories are obtained for P2WR5C10 as discussed below. The data for this prediction are 
obtained from DTN: LL040703123122.049, entitled Input and Output Files for the Sensitivity 
Studies for (1) Invert Intergranular Hydrologic Properties, (2) Pseudo Permeability of the Gas-
Filled Drift Cavity, and (3) Ventilation Heat-Removal Efficiency, dated 14 July 2004. 
Section XV.1 presents a partial list of basic thermophysical properties of water in Table XV-1 as 
obtained from Incropera and DeWitt (2002 [DIRS 163337], Table A.6 , pp. 924-925). Section 
XV.2 then defines three column vectors for the time, temperature, and matrix saturation 
histories over the time period from emplacement to 20,000 years after emplacement (from DTN: 
LL040703123122.049, PZWR5C10-LDTH55-mi-mkt-02Q.m.ebs.ext). A partial list of these 
column vectors is presented in Table XV-2. Section XV.3 then presents the governing 
relationships and Van Genuchten retention properties for the lower lithophysal unit. Also, this 
section defines the retention properties for the governing relationships. Section XV.4 then 
presents hand calculations that verify the MathCad 11 capillary pressure functions. Section 
XV.5 presents the governing relationships for the relative humidity calculation in the invert. 
Section XV.6 then presents the hand calculation for verification of the invert relative humidity 
calculation. Section XV.7 presents the MathCad 11 functions and the verification of these 
functions for relative humidity. Section XV.8 presents the comparison of relative humidity 
predictions from the MathCad 11 calculation with the multiscale thermohydrologic model. 
Section XV.9 presents the conclusions to the analysis. 
The analyses presented in this appendix use MathCad 11 and EXCEL 97 for performing 
calculations and illustrating graphical output. The calculations have been performed using 
standard functions for this software, and the results illustrated are not dependent on the use of 
this software as evidenced by the independent verification of MathCad 11 functions by 
independent hand calculation in Section XV.4 and XV.6. The software does not need to follow 
LP-SI.11Q-BSC, Software Management, under Sections 2.1.2, and 2.1.6 of that procedure, 
because this standard industrial software is exempt. 
The translation of information from DTN: LL040703123122.049 is shown in Figure XV-1. 
Note that in this figure an EXCEL workbook refers to the EXCEL file. The EXCEL workbook 
consists of several worksheets that refer to individual spreadsheets. The saturation, temperature, 
capillary pressure, and relative humidity information is downloaded through the following steps: 
1. Access the technical data management system (TDMS) and locate DTN: 
LL040703123122.049 in the trace window. The trace type is Get TDIF. In this 
window, click on the link on the upper right hand of the web page that you use to 
access the Model Warehouse Datatset. 
2. Click button to download files. Note that at this stage, the address is 
ftp://sol.ymp.gov/pub11/LL040703123122.049/LDTH_Sensitivity_Studies/. 
ANL-EBS-MD-000049 REV 02 XV-1 October 2004 

Multiscale Thermohydrologic Model 
3. Open the zip file LL040703123122_049.zip with Winzip and specify a directory for 
receipt of the data. Note that the zip file that is downloaded from the above site is 
large (over 200 megabytes). Now after downloading to the personal computer, Winzip 
can be used to extract (uncompress) the files. The extraction process generates a 
subfolder that contains other subfolders. 
4. Locate directory base-case_output folder. 
5. Locate and extract the file P2WR5C10-LDTH55-mi-mkt-02Q.m.ebs.ext. Note that 
the file is again a compressed file that needs to be extracted. This file represents the 
file datafile that is used by XTOOL Version 10.1. 
6. Note that XTOOL v10.1 works on a Sun workstation. The file then needs to be sent to 
a workstation with the current version of XTOOL v10.1. 
7. Open the .ext file with File/Open. 
8. Press extraction from the data menu. 
9. Input the element name (in#1:1:58) where the history data will be plotted. 
10. Highlight T to save the temperature history into the buffer window. Highlight S to 
save the saturation history into the buffer window. The other variables are placed into 
the buffer window accordingly. Each of these histories is exported as text files entitled 
S_vs_t_P2WRC10_55_58.PLTSC, and T_vs_t_P2WR5C10_55_58.PLTSC to the 
EXCEL Inputs to the Prediction of the Invert.xls workbook; and 
Pcap_vs_t_P2WR5C10_55_58.PLTSC; and RH_vs_t_P2WR5C10_55_58.PLTSC 
to the EXCEL Outputs to the Prediction of the Invert.xls accordingly. 
11. These files are placed in the workbook entitled Inputs to the Prediction of the 
Invert.xls in worksheets with the titles for the files respectively. The saturation, and 
temperature time histories are input to MathCad 11 as column vectors as Time, 
Temperature, and Saturation. The predicted capillary pressure and relative humidity is 
then exported with the Preout.prn textfile to EXCEL for comparison with the 
capillary pressure and relative humidity predicted by NUFT. Note that MathCad 11 
uses a function entitled WRITEPRN(filename):= array to export data (capillary 
pressure and relative humidity time histories) that are then read on the worksheet 
MathCad in the Outputs to the Prediction of the Invert.xls. 
12. The completion of steps 10 and 11 then allow for a comparison of the MathCad 11 
calculation to data in the DTN. 
ANL-EBS-MD-000049 REV 02 XV-2 October 2004 

Multiscale Thermohydrologic Model 
Prediction of Relative Humidity(RH) in the Invert 
TDMS TDMS Subdirectory XTOOL v10.1 
DTN 
LL040703123122.049 
(LL040703123122.049.zip) 
Subdirectory 
base-case_output 
File P2WR5C10-LDTH55-
mi-mkt-02Q.m.EBS.ext.gz 
Extract Files 
S_vs_t_P2WR5C10_55_58.PLTSC 
T_vs_t_P2WR5C10_55_58.PLTSC 
Mathcad 11 File:Prediction 
of RH in the Invert.mcd 
MathCad11 Column Vectors 
Time 
Temperature 
Sw 
Mathcad 11 File:Prediction 
of RH in the Invert.mcd 
MathCad11 Prediction of 
Capillary Pressure versus 
Time and 
RH versus Time 
Workbook:Inputs_to_the 
Prediction_of_the_Invert.xls 
Input Worksheets 
S_vs_t_P2WR5C10_55_58.pltsc 
T_vs_t_P2WR5C10_55_58.pltsc 
These histories are restated on 
Worksheet THistory (time 
vs.temperature vs.saturation) 
EXCEL INPUTS MathCad 11 INPUTS MathCad 11 Calculation 
Workbook:Outputs to the Prediction 
of the Invert.xls: 
Output Worksheets 
Pcap_vs_t_P2WR5C10_55_58.pltsc 
RH_vs_t_P2WR5C10_55_58.pltsc 
Workbook:Inputs_to_the 
Prediction_of_the_Invert.xls 
Input Worksheet 
Properties 
Mathcad 11 File:Prediction 
of RH in the Invert.mcd 
MathCad11 Column Vectors 
Liquid Density and Surface 
Tension as a Function of 
Temperature 
EXCEL OUTPUT 
Workbook:Outputs to the 
Prediction of the Invert.xls: 
Comparison of LDTH and MathCad 
11 Results from file Prediction of 
RH in the Invert..mcd 
Capillary Pressure versus Time and 
RH versus Time 
Export 
textfile 
Preout.prn 
Note: Files shown in Bold. 
Figure XV-1. Flow of Information for Extracting Invert Data 
As shown in the figure, after the input and output histories are downloaded from the TDMS, the 
data are placed on the EXCEL worksheets in the workbook entitled 
Inputs_to_the_Prediction_of_the_Invert.xls. The thermophysical properties of water are also 
placed on the Properties worksheet. MathCad 11 then references these inputs as EXCEL 
ANL-EBS-MD-000049 REV 02 XV-3 October 2004 

Multiscale Thermohydrologic Model 
components. After the calculations are processed in MathCad 11, the calculations are output to 
the EXCEL file Outputs_to_the_Prediction_of_the_Invert.xls on the MathCad 11 worksheet 
for plotting purposes and for comparison to the NUFT calculations. 
XV.1 THERMOPHYSICAL PROPERTIES OF WATER 
Read in the properties of water vapor used to estimate the vapor pressure, the mass density, and 
the surface tension properties of the water as a function of temperature (Incropera and DeWitt, 
2002 [DIRS 163337], pp. 924-925, Table A.6). The properties are used in the capillary pressure 
and relative humidity calculations from invert saturation. Table XV-1 is a partial list of these 
properties used in the calculations in subsequent sections. 
ANL-EBS-MD-000049 REV 02 XV-4 October 2004 

Multiscale Thermohydrologic Model 
Table XV-1. Thermophysical Properties of Water 
B := 
Temperature (K) 
Saturated 
Vapor 
Pressure 
(Bars) 
Specific 
Volume 
(m3/kg)*10^ 
3 
Surface 
Tension 
(N/m) 
*10^3 
273.15 0.00611 1 75.5 
275 0.00697 1 75.3 
280 0.0099 1 74.8 
285 0.01387 1 74.3 
290 0.01917 1.001 73.7 
295 0.02617 1.002 72.7 
300 0.03531 1.003 71.7 
305 0.04712 1.005 70.9 
310 0.06221 1.007 70 
315 0.08132 1.009 69.2 
320 0.1053 1.011 68.3 
325 0.1351 1.013 67.5 
330 0.1719 1.016 66.6 
335 0.2167 1.018 65.8 
340 0.2713 1.021 64.9 
345 0.3372 1.024 64.1 
350 0.4163 1.027 63.2 
355 0.51 1.03 62.3 
360 0.6209 1.034 61.4 
365 0.7514 1.038 60.5 
370 0.904 1.041 59.5 
373.15 1.0133 1.044 58.9 
375 1.0815 1.045 58.6 
380 1.2869 1.049 57.6 
385 1.5233 1.053 56.6 
390 1.794 1.058 55.6 
400 2.455 1.067 53.6 
410 3.302 1.077 51.5 
420 4.37 1.088 49.4 
430 5.699 1.099 47.2 
440 7.333 1.11 45.1 
450 9.319 1.123 42.9 
460 11.71 1.137 40.7 
470 14.55 1.152 38.5 
480 17.9 1.167 36.2 
490 21.83 1.184 33.9 
500 26.4 1.203 31.6 
510 31.66 1.222 29.3 
520 37.7 1.244 26.9 
These properties are read from the workbook Inputs_to_the_Prediction_of_the_Invert.xls 
from worksheet Properties. Note that not all values are shown for the EXCEL component. The 
underlying worksheet does show all the values in the interpolation table. 
Define the unit bar for expressing pressure results. 
ANL-EBS-MD-000049 REV 02 XV-5 October 2004 

Multiscale Thermohydrologic Model 
bar :=105 Pa 
<> <> T .
() :=linterp..
(B 0),B 1,
K..
bar
Psat T. 
Psat(342K) =0.298 bar 
Psat(342K) =0.294 atm 
(Eq. XV-1) 
Define an interpolation function for the surface tension of the liquid water. 
. <> <> T .-3 N
s() :=linterp.(B 0),B 3,
K 
..
10  
m
fT
. 
N
sf (342K) =0.06458 
m (Eq. XV-2) 
Define the specific volume and density functions. 
. .<> <> T ..cm 3 
spev T
() :=.linterp.(B 0),B 2,
K..
..
 
gm
.. 
1
.T
() := 
spev T
() 
.(300K) =997.009 
kg 
3 
m (Eq. XV-3) 
Note that these MathCad linear interpolation functions are verified in Section XV.4. 
XV.2 TEMPERATURE HISTORIES FROM THERMOHYDROLOGIC MODELING 
AND ANALYSIS 
Input the temperature and saturation (Sw) histories for P2WR5C10. The data for this prediction 
are obtained from DTN: LL040703123122.049, entitled Input and Output Files for the 
Sensitivity Studies for (1) Invert Intergranular Hydrologic Properties, (2) Pseudo Permeability 
of the Gas-Filled Drift Cavity, and (3) Ventilation Heat-Removal Efficiency, dated 14 July 2004. 
ANL-EBS-MD-000049 REV 02 XV-6 October 2004 

Multiscale Thermohydrologic Model 
Table XV-2. Invert Temperature and Saturation Time Histories for the P2WR5C10 Column 
Time
.. 
. 
..
Temperature 
Sw 
.
.
.
:=
Time 
(yrs) 
Temperature 
C 
Saturation 
() 
0.01 22.43 0.94 
0.10 63.37 0.96 
1.00 76.23 0.27 
2.00 78.72 0.27 
5.00 77.85 0.28 
10.00 74.32 0.29 
15.00 70.61 0.29 
20.00 65.54 0.30 
25.00 62.21 0.31 
30.00 58.80 0.33 
40.00 53.46 0.35 
50.00 48.86 0.39 
50.10 76.66 0.27 
51.00 107.83 0.24 
52.00 120.89 0.23 
55.00 135.04 0.21 
60.00 145.78 0.21 
65.00 149.81 0.21 
70.00 150.94 0.21 
75.00 150.55 0.21 
80.00 149.40 0.21 
90.00 146.55 0.21 
100.00 143.43 0.21 
120.00 137.94 0.21 
140.00 133.15 0.21 
160.00 129.41 0.22 
180.00 126.61 0.22 
200.00 124.27 0.22 
220.00 122.89 0.22 
240.00 121.47 0.22 
260.00 120.28 0.23 
These time histories are read from the workbook Inputs_to_the_Prediction_of_the_Invert.xls 
from worksheet THistory. Note that not all values are shown for the EXCEL component. Note 
that the Temperature and Saturation Histories are restated from the worksheets 
T_vs_t_P2WR5C10_55_58.pltsc and S_vs_t_P2WR5C10_55_58.pltsc, respectively. Note 
also that not all the data are shown in MathCad 11 for this EXCEL component. These time 
histories are restated on a single worksheet THistory that is derived from data on worksheets 
T_vs_t_P2WR5C10_55_58.pltsc and S_vs_t_P2WR5C10_55_58.pltsc. The data on THistory 
is then read into MathCad as an EXCEL component. 
Figures XV-2 and XV-3 present the temperature and saturation (Sw) relationships as a function 
of time. Note that data plotting in these figures is performed in MathCad 11 and is considered 
qualified for graphical display of information. 
ANL-EBS-MD-000049 REV 02 XV-7 October 2004 

Multiscale Thermohydrologic Model 
0 
50 
100 
150 
200 
Invert Temperature (C)
Temperature 
0.01 0.1 1 10 100 1 .103 1 .104 1 .105 
Time 
Time After Emplacement (Years) 
DTN: LL040703123122.049. 
Figure XV-2. Invert Temperature History as a Function of Time (from Time versus Temperature on the 
Worksheet Thistory) 
0.2 
0.4 
0.6 
0.8 
Invert Saturation (C)
Sw 
0.01 0.1 1 10 100 1 .103 1 .104 1 .105 
Time 
Time After Closure(Years) 
DTN: LL040703123122.049. 
Figure XV-3. Invert Matrix Saturation History as a Function of Time (from Time versus Saturation on the 
Worksheet Thistory) 
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Multiscale Thermohydrologic Model 
XV.3 GOVERNING RELATIONSHIPS AND VAN GENUCHTEN RETENTION 
PROPERTIES FOR THE LOWER LITHOPHYSAL UNIT 
This section presents the governing relationships and then presents the van Genuchten retention 
properties for the lower lithophysal unit used in the analysis. 
The prediction of the moisture potential can be performed through the van Genuchten retention 
relationship for the tuff matrix (Fetter 1993 [DIRS 102009], p. 172): 
sr
.. ) =. + (. -. )
(
mr 
m
n
[ 1 + a. 
m 
] 
(Eq. XV-4) 
where 
. Volumetric moisture content (-) 
. r Residual volumetric moisture content (-) 
. s Saturated volumetric moisture content (-) 
. m Moisture potential (bars or Pa)) 
a Van Genuchten air entry parameter (bar- 1 or Pa- 1) 
n Van Genuchten curve-fit parameter (-), and 
m Van Genuchten curve-fit parameter (-) 
Note that in NUFT, the moisture potential is expressed as a capillary pressure in which it is 
understood that the air entry parameter a is expressed in (Pa)- 1. Also, Fetter (1993 [DIRS 
102009], p. 172) designates the (m) parameter for the van Genuchten relationship as: m = 1- 1/n. 
This value of m can be substituted into Equation XV-4 to derive the volumetric moisture 
content (. ) along with the notation: 
()=. + (. -.)
sr
. P
cr 1
(1- )
n 
n 
c
[ 1+( Pa) ] (Eq. XV-5) 
where 
Pc (Capillary Pressure expressed in bars) = . m (expressed in bars) 
In Equation XV-5, the moisture potential can be solved for in terms of the volumetric moisture 
content: 
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Multiscale Thermohydrologic Model 
1 
n
. 1 . 
m
... . . 
- 
sr 
-
..
. . . r 
.
. 
- 1..
.
..
P (. ) =. 
c
a (Eq. XV-6) 
The van Genuchten capillary pressure relationship for the tuff matrix (Fetter 1993 [DIRS 
102009], p. 172) is for ambient temperature. Note that a correction for surface tension effects is 
necessary since surface tension is a function of temperature. Note that, as discussed by Hillel 
(1998 [DIRS 165404], pp38-44), the height of capillary rise or capillary pressure is a function of 
surface tension that in turn is a function of temperature. Therefore to calculate the correct 
capillary pressure, multiply the ambient capillary pressure by the ratio of the surface tension at 
elevated temperature to that at ambient temperature (set at 25 degrees Centigrade). The 
following calculation is performed in MathCad 11: 
P'c (., T) Pc() s f (T + 273.15 K)
.
s f (25 K+ 273.15 K) 
(Eq. XV-7) 
where 
Pc (. ,T) is the capillary pressure corrected for surface tension effects 
The moisture retention properties for the tuff matrix from the Tptpll unit (TSw35) are taken from 
Table IV-4 under the row heading tswM5 that corresponds to the material name m-tsw35 in the 
LDTH submodel. It should also be noted that the ratio (. -. r)/(. -. r) is equivalent to the ratio (1s 
Sr)/(S-Sr) that is used in NUFT. 
. S : = 0.131 . r : = 0.12 . 
a : = 1.08 - 5  Pa- 1 m' : = 0.216 
S 
1 
n := 
1 - m' 
Input the universal gas constant and the molecular weight of water. 
M := 016.18  gm R := 315.8  J 
mole K mole 
 
. r
= 0.12 . r = 0.01572
. s
(Eq. XV-8) 
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Multiscale Thermohydrologic Model 
a= 1.08  10- 51 
Pa 
Solve for . as a function of Sw. Note that in the following equation, index notation is used to 
define the corresponding volumetric moisture content (T) for the saturation (Sw). The index 
range is established by the statement i:= 0...rows(Sw)-1. 
(
i := 0 .. rows Sw ) - 1 Ti := 
.s Swi 
(Eq. XV-9) 
Output the results of the calculation. The following table shows the relationship of volumetric 
moisture content as a function of time as derived from Equation XV-9. 
Ti = 
Time i = 
0.123 
0.125 
0.036 
0.035 
0.037 
0.038 
0.038 
0.04 
0.041 
0.043 
0.046 
0.051 
0.035 
0.031 
0.03 
0.028 
0.027 
0.027 
0.027 
0.027 
0.027 
0.027 
0.027 
0.028 
0.028 
0.01 
0.1 
1 
2 
5 
10 
15 
20 
25 
30 
40 
50 
50.1 
51 
52 
55 
60 
65 
70 
75 
80 
90 
100 
120 
Note that this is a partial listing of the data. The complete listing of the data are presented on 
Worksheet Thistory of the workbook Input to the Prediction of the Invert.xls. 
Plot the invert volumetric moisture content as a function of time. 
ANL-EBS-MD-000049 REV 02 XV-11 October 2004 

Multiscale Thermohydrologic Model 
XV.4 HAND CALCULATIONS FOR VERIFICATION OF MATHCAD FUNCTIONS 
Develop a hand calculation for verification of the relative humidity function. At 4,000 years the 
temperature of the invert is 70.5 degrees centigrade with a saturation of 0.52163. Calculate the 
moisture potential in bars. From Equation XV-4: 
(Eq. XV-10) 
(Eq. XV-11) 
Sr := 0.12 Ss := 1 
Rewriting Equation XV-10: 
1 
1
1
0.12
Invert Volumetric Moisture Content
0.1 
0.08 
0.06 
0.04 
0.02 
0.01 0.1 1 10 1001 .103 1 .104 1 .105 
Time(years) 
Figure XV-4. Invert Volumetric Moisture Content as a Function of Time 
m
.. 
n
)

(
a.
+
..
r 
.r-
- 
.s 
..
m 
)
)
.r 
 
-.s
(
+
.r
. 
a.
.. 
n
(
+
.. 
or rewriting in terms of saturation: 
ANL-EBS-MD-000049 REV 02 XV-12 October 2004 

Multiscale Thermohydrologic Model 
SSr 
Sr 
-
1 
1
-
m
n
1
+
.
.
(
aPc
)

.
. 
(Eq. XV-12) 
Substituting in the saturation: 
0.5216 - 0.12 1 
1 - 0.12
.
.
m
.
.
1
+
(
aPc 
n
)
 
(Eq. XV-13) 
1
.4563 
m
.
.
1
+
..
(
aPc 
n
)
 
(Eq. XV-14) 
m 1
.
.
..
(
)
aPc 
 
n
1
+
.4563 (Eq. XV-15) 
m 
2.191 
(Eq. XV-16) 
.
.
..
(
)

aPc 
n
1
+
..
.
1
0.216
..
)

(
aPc 
n
1 
2.191
+
(Eq. XV-17) 
n 2.1914.6296
)

(
aPc
1
+
(Eq. XV-18) 
+
(
)

aPc 
n
1 
37.760 
(Eq. XV-19) 
(
)

aPc 
n 
37.760 -1 
(Eq. XV-20) 
n
(
)

aPc 
36.760 
(Eq. XV-21) 
1
1.276

aPc 36.760 
(Eq. XV-22) 

aPc 16.857 
(Eq. XV-23) 
ANL-EBS-MD-000049 REV 02 XV-13 October 2004 

Multiscale Thermohydrologic Model 
16.857
Pc 

1.08 10- 5 1 
Pa (Eq. XV-24) 
Pc 1560833.Pa 
(Eq. XV-25) 
or 15.60 Bars at a temperature of 70.5 degrees C at 4,000 yrs and a saturation of 0.5216. 
Now consider the surface tension effects (sf) and correct the capillary pressure function for 
surface tension effects. From Incropera and DeWitt (2002 [DIRS 163337], p. 924, Table A.6) 
and as reproduced in Table XV-1: 
340 64.9 *10-3 
70.5K+ 273.15K = 343.65 K 
345 64.1 *10-3 
(Eq. XV-26) 
sf ..
343.65 - 340 (64.1 - 64.9) + 64.9..10- 3 N 
. 345 - 340 . m (Eq. XV-27) 

sf 64.3 10 - 3  N 
for a temperature of 70.5 C. 
m 
(Eq. XV-28) 
Now calculate the surface tension at ambient temperature (25 degrees C): 
273.15K+ 25K = 298.15 K 
295 72.7*10-3 
300 71.7 *10-3 (Eq. XV-29) 
.298.15 - 295 .- 3 N
sf .(71.7 - 72.7) + 72.7.10 
. 300 - 295 . m (Eq. XV-30) 
sf 72.07 10 - 3 N 
 
m (Eq. XV-31) 
for a temperature of 25 C. 
ANL-EBS-MD-000049 REV 02 XV-14 October 2004 

Multiscale Thermohydrologic Model 
Provide a capillary pressure correction based upon the ratio of the surface tension (0.07207 N/m) 
at 25 degrees C and 70.5 degrees C: 
P'c 
.
. 
. 
.
.
1560833.Pa
..
.
.
. 
. 
.
. 
(Eq. XV-32) 
64.3 10- 3 N 


.
m 
..
. 
 
.
72.07 10- 3 N 


.
m 
1392556. Pa 
Now calculate the density of water at this temperature. From Incropera and DeWitt (2002 [DIRS 
163337], p. 924, Table A.6) and as reproduced in Table XV-1: 

340 1.021*10-3 
345 1.024*10-3
P'c 
(Eq. XV-33) 
3
(

1.024 10 - 3
-

1.021 10 - 3
..
. 

)
1.021 10 - 3
..
.
343.65 - 340
345 - 340

m 
kg 
+

977.3 
kg 
3 
m 
(Eq. XV-34) 
 
XV.5 GOVERNING RELATIONSHIPS FOR RELATIVE HUMIDITY CALCULATION 
IN THE INVERT 
The relative humidity, RH (Pc), in the invert can be expressed as a function of the moisture 
potential expressed as the capillary pressure through the soil-psychrometer relation (Kelvin 
equation) presented by Jury et al. (1991 [DIRS 102010], p. 60): 
'
M 
Pc 

* 
w
(
P RH c 
Pv P
v
) 
/ 
exp( 
) (Eq. XV-35) 
=
=

.
T R 
w 
where 
P c Capillary Pressure (Pa ) with surface tension correction 
Mw Molecular weight of water (kg/mole), 
.w Mass Density of Water (kg/m3) 
Tw Absolute temperature (K) 
Pv Partial pressure of water (Pa ) 
Pv* Saturated vapor pressure of water (Pa) 
R Universal Gas Constant (8.315 J/(mole*K)) 

w 
ANL-EBS-MD-000049 REV 02 XV-15 October 2004 

Multiscale Thermohydrologic Model 
XV.6 HAND CALCULATIONS FOR VERIFICATION OF THE MATHCAD 
FUNCTION FOR INVERT RELATIVE HUMIDITY 
The hand calculation for the corrected capillary pressure in Equation XV-32 is 1.393*106 Pa. 
Now substitute values into the Kelvin equation (Equation XV-35) to calculate the relative 
humidity. The hand calculation produces: 
kgm 2
..
.
.
1 
0.018016 
kg
exp M.

R
=
8.315
M
=
s 2K mol 
.(343.65K
mol
.
RT
) 
(Eq. XV-36) 
(
106Pa
)
..

exp 
.. 
. 
.
.
K
.. 
. 
.
.
1
-1.395
..
gm
18.016


 
kgm 2
.. 
..
.
mole 
977.3 
kg 
8.315 
343.65

3
.
s 2K mol 
m 
= 0.99104 
(Eq. XV-37) 
Note that before the adjustment for surface tension, the capillary pressure was 1.56 *106 Pa as 
presented above. Therefore the capillary tension correction is about 11 percent. 
XV.7 MATHCAD FUNCTIONS AND VERIFICATION 
Note that in the relative humidity function presented below requires the moisture potential as a 
function of the volumetric moisture content. Define the inverse van Genuchten Moisture 
Retention Function. Note that in MathCad a := is equivalent to an assignment statement. Note 
also that the MathCad calculations in this Appendix are found in file Prediction of the RH in 
the Invert.mcd. 
1 
n 
.. 
.. 
.
. 
. 
.
. 
.
. 
. 
.
. 
)
.r
(
- 1 
1
m'
.. 
.. 
.s
-
(
)
a 
-
..r
.
Pc() 
:= 
(Eq. XV-38) 
.
() 
sf (T
+
273.15K
)
)
P'c T ,.
(
:=Pc 

sf (25K
+
273.15K
) 
(Eq. XV-39) 
ANL-EBS-MD-000049 REV 02 XV-16 October 2004 

Multiscale Thermohydrologic Model 
Define the relative humidity function on the basis of temperature, and volumetric moisture 
content. 
( 1M. 
REL2 T ,.) := exp 
.
. 
-P'c (T ,.)
 . 
(
..(T + 273.15K) RT + 273.15K) . 
(Eq. XV-40) 
The MathCad 11 functions presented above produce the following results that are in agreement 
with the hand calculations presented in Sections XV.4 and XV.6. The functions are therefore 
verified. 
Pc(0.5216.s)= 1.56321  106Pa (Eq. XV-41) 
N
sf (343.65K) = 0.064 (Eq. XV-42) 
m 
.(343.65K) = 977.336 
kg (Eq. XV-43)
3 
m 
-Pc(0.52163.s)
sf (70.5K+ 273.15K) 
=-1.395  106Pa (Eq. XV-44)
sf (25K+ 273.15K) 
REL2( 70.5K, 0.52163.s)= 0.99104 
(Eq. XV-45) 
Now develop the capillary pressure relationship (after surface tension correction) as a function of 
time. The data are output in the following arrays and Figure XV-5 presents a plot of the data. 
ANL-EBS-MD-000049 REV 02 XV-17 October 2004 

Multiscale Thermohydrologic Model 
Timei = Pc(Ti) P'c ( TemperatureiK,Ti) 
= 
bar bar
0.01 
0.1 
1 
2 
5 
10 
15 
20 
25 
30 
40 
50 
50.1 
51 
52 
55 
60 
65 
70 
75 
80 
90 
100 
120 
140 
160 
180 
200 
0.438 
0.329 
0.435 
0.299 
532.092 
467.423 
559.908 
488.379 
450.19 
393.654 
358.257 
316.43 
341.592 
304.757 
269.585 
243.646 
220.765 
201.36 
172.438 
158.604 
111.629 
104.103 
69.987 
66.014 
594.822 
521.903 
1.308103
1.0421032.054103
1.5611033.047103
2.1931032.7421032.9461033.0071032.9931032.9441032.8281032.6821032.4321032.2041032.0191031.8741031.748103
Note that MathCad 11 illustrates a portion of the results. The results are exported to the EXCEL 
workbook entitled Output_to_the_Prediction_of_Invert.xls on the MathCad 11 worksheet. 
ANL-EBS-MD-000049 REV 02 XV-18 October 2004 

Multiscale Thermohydrologic Model 
0.01 0.1 1 100 1 .103 1 .104 1 .105 
0.1 
1 
10 
100 
1 .103 
1 .104 
Corrected Pc 
Uncorrected Pc 
Time After Closure (years) 
Invert Capillary Pressure (bar) 
10 
Figure XV-5. Invert Capillary Pressure and Corrected Capillary Pressure as a Function of Time 
Note that MathCad 11 illustrates a portion of the results. The results are exported to the EXCEL 
workbook entitled Output_to_the_Prediction_of_Invert.xls on the MathCad 11 worksheet. 
ANL-EBS-MD-000049 REV 02 XV-19 October 2004 

Multiscale Thermohydrologic Model 
Timei = REL2 TemperatureiKTi,( ) 
0.01 0.99968 
0.1 0.9998 
1 0.74261 
2 0.73405 
5 0.77903 
10 0.81682 
15 0.82156 
20 0.85298 
25 0.87593 
30 0.90009 
40 0.93237 
50 0.95605 
50.1 0.71752 
51 0.53676 
52 0.40195 
55 0.286 
60 0.21409 
65 0.19263 
70 0.18668 
75 0.18797 
80 0.19268 
90 0.20436 
100 0.22038 
120 0.25106 
140 0.2832 
160 0.31273 
180 0.33837 
200 0.36249 
220 0.37956 
240 0.39727 
Note that MathCad 11 plots presented in Figures XV-6 and XV-7 are exported to the EXCEL 
workbook entitled Output_to_the_Prediction_of_Invert.xls on the MathCad 11 worksheet. A 
complete listing of the data is presented. 
ANL-EBS-MD-000049 REV 02 XV-20 October 2004 

Multiscale Thermohydrologic Model 
0 
0.5 
1 
Invert Relative Humidity 
0.01 0.1 1 10 100 1 .103 1 .104 1 .105 
Time (Years) 
Figure XV-6. Relationship of Invert Relative Humidity to Time 
0.6 
0.8Invert Relative Humidity 
100 1 .103 1 .104 1 .105 
Time (Years) 
Figure XV-7. Relationship of Invert Relative Humidity over the Range from 0.50 to 1.0 After 100 Years 
ANL-EBS-MD-000049 REV 02 XV-21 October 2004 

Multiscale Thermohydrologic Model 
Write the MathCad 11 results to an output file for comparing results to the LDTH model. These 
results are then placed on the worksheet MathCad 11 of the workbook 
Output_to_the_Prediction_of_Invert.xls. The EXCEL worksheet presents a complete listing 
of the output. 
ARHi , 0 := Timei 
(
ARHi , 1 := REL2 TemperatureiK,Ti) 
P'c (TemperatureiK,Ti)
ARHi , 2 :=
bar
WRITEPRN("Preout") := ARH 
XV.8 COMPARISON OF RELATIVE HUMIDITY PREDICTIONS FROM THE 
MATHCAD 11 CALCULATION WITH THE MULTISCALE 
THERMOHYDROLOGIC MODEL 
The tabulated relative humidity and capillary pressure results along with the results generated 
from the MathCad 11 File Prediction of the RH in the Invert Rev01 for P2WR5C10 are 
presented in the EXCEL workbook Output_to_the_Prediction_of_Invert.xls. Figures XV-8 
through XV-9 present the comparisons between the two calculations. The calculations are in 
close agreement. 
ANL-EBS-MD-000049 REV 02 XV-22 October 2004 

Multiscale Thermohydrologic Model 
1 
10 
10 1000 
(
Invert Capillary Pressure (bars)
Prediction of Invert Capillary Pressure Based 
Upon Temperature and Saturation for 
P2WR5C10_55_58 
0.01 
0.1 
100 
1000 
10000 
100000 
100 10000 100000 
Time After Emplacement Years) 
MathCad 
NUFT 
Figure XV-8. Comparison of Invert Capillary Pressure Between the MathCad 11 and Multiscale 
Calculations 
and Saturation for P2WR5C10_55_58 
0 
1 
100 1000 
) 
Invert RH (-)
Prediction of Invert RH Based Upon Temperature 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
10 10000 100000 
Time After Emplacement (YearsMathCad 
Nuft 
NOTE: The data for this plot are presented in the Workbook Outputs to the Prediction of the Invert.xls on 
worksheet RH_vs_t_P2WR5C10_55_58.pltsc and worksheet Math11. A complete listing of the data is 
presented on that worksheet. 
Figure XV-9. Comparison of Invert Relative Humidity Between the MathCad 11 and Multiscale LDTH 
Calculations 
ANL-EBS-MD-000049 REV 02 XV-23 October 2004 

Multiscale Thermohydrologic Model 
Prediction of Invert RH Based Upon 
Temperature and Saturation for 
P2WR5C10_55_58 
Invert RH (-)
1 
0.99 
0.98 
0.97 
0.96 
0.95 
0.94 
0.93 
0.92 
0.91 
0.9 
MathCad 
Nuft 
1000 10000 100000 
Time After Emplacement (Years) 
NOTE: the data for this plot are presented in the Workbook Outputs to the Prediction of the Invert.xls on 
worksheet RH_vs_t_P2WR5C10_55_58.pltsc and worksheet Math11. A complete listing of the data are 
presented on that worksheet. 
Figure XV-10. Comparison of Invert Relative Humidity Between the MathCad 11 and Multiscale 
Calculations Near 100 Percent Relative Humidity 
XV.9 CONCLUSIONS 
The relative humidity is a smooth function based upon the Kelvin equation, the van Genuchten 
equation, and the temperature saturation from the multiscale thermohydrologic model. The 
results of the two calculations are in agreement. 
ANL-EBS-MD-000049 REV 02 XV-24 October 2004