Thermal Conductivity of Non-Repository Lithostratigraphic Layers Rev 01, ICN 00 

MDL-NBS-GS-000006

October 2004
 
1. PURPOSE 
This model report addresses activities described in Technical Work Plan for: Near-Field 
Environment and Transport Thermal Properties and Analysis Reports Integration (BSC 2004 
[DIRS 171708]). The model develops values for thermal conductivity, and its uncertainty, for 
the nonrepository layers of Yucca Mountain; in addition, the model provides estimates for matrix 
porosity and dry bulk density for the nonrepository layers. The studied lithostratigraphic units, 
as identified in the Geologic Framework Model (GFM 2000) (BSC 2004 [DIRS 170029]), are 
the Timber Mountain Group, the Tiva Canyon Tuff, the Yucca Mountain Tuff, the Pah Canyon 
Tuff, the Topopah Spring Tuff (excluding the repository layers), the Calico Hills Formation, the 
Prow Pass Tuff, the Bullfrog Tuff, and the Tram Tuff. The deepest model units of the GFM 
(Tund and Paleozoic) are excluded from this study because no data suitable for model input are 
available. 
The parameter estimates developed in this report are used as input to various models and 
calculations that simulate heat transport through the rock mass. Specifically, analysis model 
reports that use product output from this report are: 
 Drift-scale coupled processes (DST and TH seepage) models 
 Drift degradation analysis 
 Multiscale thermohydrologic model 
 Ventilation model and analysis report. 
In keeping with the methodology of the thermal conductivity model for the repository layers in 
Thermal Conductivity of the Potential Repository Horizon (BSC 2004 [DIRS 169854]), the Hsu 
et al. (1995 [DIRS 158073]) three-dimensional (3-D) cubic model (referred to herein as the Hsu 
model) was used to represent the matrix thermal conductivity as a function of the four 
parameters (matrix porosity, thermal conductivity of the saturating fluid, thermal conductivity of 
the solid, and geometric connectivity of the solid). 
The Hsu model requires input data from each test specimen to meet three specific conditions: 
1) Known value for matrix porosity 
2) Known values for wet and dry thermal conductivity 
3) The location of the measured specimen in relation to the model stratigraphic unit. 
The only matrix thermal conductivity values developed are limited to fully saturated and dry 
conditions. The model does not include the effects of convection and thermal radiation in voids. 
The model does not include temperature dependence of thermal conductivity, porosity, or bulk 
density. 
Of the geologic formations being modeled by this report, only the Tiva Canyon Tuff is observed 
to have lithophysal porosity (Rautman and Engstrom 1996 [DIRS 100693], Appendix B). 
However, the effect of lithophysal porosity on the whole-rock thermal conductivity of the 
formation is not modeled. This is because the formation is exposed and eroded at the surface. 
These near-surface effects will have a significant impact on thermal properties and behavior of 
the Tiva Canyon Tuff. These effects have more significant impact on the layers thermal 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 1-2 October 2004 
behavior than modeling lithophysal porosity. This is documented as a sensitivity analysis, and is 
presented in Appendix S. 
The only deviation from the technical work plan (TWP) (BSC 2004 [DIRS 171708], Section 3.2) 
concerns the Yucca Mountain Review Plan, Final Report (NRC 2003 [DIRS 163274]) 
acceptance criteria. The TWP states that these acceptance criteria are not relevant to this report 
because certain outputs are not specifically covered by any category and, instead, provide inputs 
to downstream numerical models. Contrary to this, the report identifies and discusses the 
relevant acceptance criteria in Sections 4.2 and 8.2. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 2-1 October 2004 
2. QUALITY ASSURANCE 
Activities associated with the development of this model report were determined to be quality 
affecting, and subject to the Office of Civilian Radioactive Waste Management quality assurance 
program (DOE 2004 [DIRS 171539]). Approved quality assurance procedures identified in the 
TWP (BSC 2004 [DIRS 171708], Section 4) have been used to conduct and document the 
activities described in this model report. Electronic management of data was evaluated in 
accordance with procedure AP-SV.1Q, Control of the Electronic Management of Information, 
and the applicable controls are discussed in the TWP (BSC 2004 [DIRS 171708], Section 8.4). 
This model report contributes to the analysis and modeling of the unsaturated zone, which is a 
natural barrier, and is classified on the Q-List (BSC 2004 [DIRS 168361] as safety category 
because it is important to waste isolation, as defined in AP-2.22Q, Classification Analyses and 
Maintenance of the Q-List. The report contributes to the analysis of data used to support 
performance assessment; the conclusions do not directly impact engineered features important to 
safety, as defined in AP-2.22Q. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
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INTENTIONALLY LEFT BLANK

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 3-1 October 2004 
3. USE OF SOFTWARE 
3.1 SOFTWARE TRACKED BY CONFIGURATION MANAGEMENT 
The codes subject to Software Configuration Management are listed in Table 3-1, together with a 
brief description of their functionality. These software packages were obtained from Software 
Configuration Management and were judged appropriate for intended use with this type of 
modeling activity based on similar use with other Yucca Mountain Project model development. 
SPLICE (STN: 10906-1.0-00 [DIRS 162672]) software was created specifically for this model 
report. SPLICE examines input files and matches porosity data with wet and dry conductivity 
data. The matching of data is based on a common sample identification (ID) and common 
sample depth (allows for a delta of 1.3 ft). Appendix B provides documentation of SPLICE 
used to process data for the NRG boreholes; Appendix E documents a similar process for data 
from the SD boreholes. 
REFORMAT (STN 10907-2.0-00 [DIRS 162673]) software was used to extract and to change 
the format of text data from the specific data tables listed in Appendices C, D, F, G, and I to P. 
The range of use of reformat is to change the format and arrangement of the data tables listed in 
those Appendices. 
The parameters documented in this report were constructed, in part, using algorithms that are 
part of the public-domain Geostatistical Software Library subroutine HISTPLT (STN 10802- 
2.01-00 [DIRS 158223]) as implemented by Sandia National Laboratories. The software was 
selected for its ability to display data and statistical functions used to analyze the model results. 
Section 2.5 of the Software Management Report, GSLIB HISTPLTV2.01 (SNL 2002 
[DIRS 171558]) states the limitations on software and range of parameter values as Not 
applicable. 
HSUINV (STN: 10804-1.0-00 [DIRS 158228]) was used to solve the inverse problem for the 
Hsu 3-D cube model of matrix thermal conductivity. Section 2.5 of the Software Management 
Report, HsuInv, Version 1.0 (SNL 2002 [DIRS 171559]) states the limitations on software the 
range of parameter values as Not applicable. 
HSUINV (STN: 10804-1.0-00 [DIRS 158228]) and HISTPLT (STN 10802-2.01-00 
[DIRS 158223]) were selected, in part, to be compatible with the modeling of thermal 
conductivity of potential repository layers, and were used for the same purpose and range of 
validation. 
GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) was used to calculate the mean 
and standard distribution of wet and dry matrix thermal conductivity values as described in 
Section 6.3 of this model report. Section 2.5 of the Software Management Report, 
GENHSUMODELDATA Version 1.00 (SNL 2002 [DIRS 171560]) states: 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 3-2 October 2004 
There are the following restrictions on the range of parameter values: 
For porosity: 0 < ((*phi*)) < 1 
For: 0 < ((*gamma c*)) <= 1 
For: Ks: ks > 0 
The codes listed in Table 3-1 were run on an Intel personal computer under the Microsoft 
Windows Server 2000 operating system. Software codes GSLIB HISTPLT (STN: 10802-2.01- 
00 [DIRS 158223]) and HSUINV (STN: 10804-1.0-00 [DIRS 158228]) were qualified in 
accordance with AP-SI.1Q, Rev 3, ICN 3, Software Management. Software codes 
GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]), REFORMAT 
(STN 10907-2.0-00 [DIRS 162673]), and SPLICE (STN: 10906-1.0-00 [DIRS 162672]) were 
qualified in accordance with AP-SI.1Q Rev 3, ICN 4, Software Management. All software codes 
were used within their range of validation. 
Table 3-1. Software Tracked by Software Configuration Management 
Code Name Version STN Number Platform 
Operating 
System Brief Description 
GSLIB HISTPLT 
[DIRS 158223] 
V. 2.01 10802-2.01-00 PC Microsoft 
Windows 
Server 2000 
Generates univariate statistical 
summaries and histograms that are 
compatible with a PostScript 
display device. 
HSULNV 
[DIRS 158228] 
V. 1.0 10804-1.0-00 PC Microsoft 
Windows 
Server 2000 
The code solves the inverse 
problem for Hsu et al. (1995 
[DIRS 158073]) 3-D cube model of 
matrix thermal conductivity. The 
inverse problem consists of 
simultaneously solving two 
nonlinear equations. 
REFORMAT 
[DIRS 162673] 
V. 2.0 10907-2.0-00 PC Microsoft 
Windows 
Server 2000 
Extracts columns of data from one 
or more input files to an output file 
or from one input file to one or 
more output files. Lithostratigraphy 
can be added to the output file(s) if 
borehole ID and depth are 
available. 
GENHSUMODE 
LDATA 
[DIRS 162671] 
V. 1.0 10905-1.0-00 PC Microsoft 
Windows 
Server 2000 
Takes distributions of matrix 
porosity, solid thermal conductivity, 
and Hsu model geometry 
parameter gamma_c, and 
calculates the mean and standard 
distribution of wet and dry matrix 
thermal conductivities. 
SPLICE 
[DIRS 162672] 
V. 1.0 10906-1.0-00 PC Microsoft 
Windows 
Server 2000 
Combines a file of porosity data 
with a file of wet and dry thermal 
conductivity data, based on a 
common sample ID. 
NOTES: All software was run on a 530 Work Station model CPU barcode R436032 manufactured by Dell. 
CPU = central processing unit; PC = personal computer; STN = Software Tracking Number. 

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MDL-NBS-GS-000006 REV 01 3-3 October 2004 
3.2 EXEMPT SOFTWARE 
In accordance with Section 2.1 of LP-SI.11Q-BSC, Software Management, exempt software 
products include operating systems, utilities, compilers and their associated libraries, 
spreadsheets, database managers, graphical representations of data, computer-aided design 
systems, acquired software that is embedded in the test and measurement equipment, and the 
standard functions of commercial off-the-shelf software. The following exempt software were 
used in the development of the modeling activities discussed in this modeling report or the 
display of modeling results. All exempt software was run on a Microsoft Windows 2000 server. 
 Aladdin Free Public License (AFPL) Ghostscript Version 7.04 is software that provides 
an interpreter for the PostScript language with the ability to convert PostScript language 
files to many raster formats, view them on displays, print them on non-PostScript 
printers, and act as an interpreter for Portable Document Format. Ghostscript also has 
the ability to convert back and forth between PostScript language and Portable 
Document Format files. 
 Digital Visual Fortran Version 5.0 is a Fortran 90 compiler for Windows. Digital Visual 
Fortran is a complete development system that includes Digitals Fortran 90 compiler, a 
visual development environment from Microsoft, and support for numerous 
industry-standard Fortran-language extensions. 
 GSView Version 4.2 is a graphical interface for Ghostscript. GSView allows 
encapsulated postscript plot files to be viewed or printed. GSView requires AFPL 
Ghostscript. 
 Microsoft Excel 2000 is a spreadsheet application used to sort and count data, and to 
perform linear regressions for the model validation. 
 MATHCAD Professional 11.2a is used in Appendix S for graphical representation and 
arithmetic manipulation. 
Attachment 2, Item 3 of AP-SIII.10Q, Models, requests four pieces of information for exempt 
software: 
 The formula or algorithm used 
 A listing of the inputs to the formula or algorithm 
 A listing of the outputs from the formula or algorithm 
 Other information (e.g., operating environment information) that would be required in 
order to independently reproduce the work. 
For AFPL Ghostscript Version 7.04, Digital Visual FORTRAN Version 5.0, and GSView 
Version 4.2, the user provides no formulas or algorithms, and knowledge of the internal 
algorithms in these applications is not necessary to use them. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 3-4 October 2004 
Any formulas used in Microsoft Excel 2000 are provided in this report, where the inputs and 
outputs are identified. 
The inputs to GSView Version 4.2 are encapsulated postscript files prepared from the postscript 
plots produced by the histogram plotter HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 
The postscript plots from HISTPLT (STN 10802-2.01-00 [DIRS 158223]) are modified with an 
editor, to remove the first three lines. This converts the postscript to encapsulated postscript. 
All formulas used by MATHCAD Professional 11.2a are fully documented and described in 
Appendix S. 
To access the encapsulated postscript file, the option Open is selected from the GSView File 
menu. From the Edit menu, the option Add EPS Preview is selected, and TIFF 6 
uncompressed is selected from the resulting submenu. The plot is converted, and GSView 
prompts the user for a name (filename) for the output file. The user should add the suffix .eps to 
the chosen filename. The plot is displayed in the lower-left portion of the window (to view the 
plot, it may be necessary to use the scroll bars to scroll down to that part of the window). 
The actual work is done by AFPL Ghostscript Version 7.04. GSView provides a Windows-style 
interface to Ghostscript. The output files are suitable to be included in a Microsoft Word 
document. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-1 October 2004 
4. INPUTS 
4.1 DIRECT INPUTS 
Direct inputs to the Hsu model (Hsu et al. 1995 [DIRS 158073]) are matrix porosity and thermal 
conductivity. The model also requires a stratigraphic coordinate system that represents the 
relative position of each model unit for which the measured data are used. 
The Site and Engineering Properties (SEP) parameters porosity and thermal conductivity 
were searched for all qualified, verified data tables. Data tables containing data exclusively for 
the repository layers or for materials other than geologic layers (e.g., titanium or grout) were 
excluded from consideration because the scope of the model is the nonrepository geologic layers 
of Yucca Mountain. Only data tables that included lithostratigraphy and depth, and either 
borehole ID or sample ID, were retained for consideration, because one of these items is 
necessary to determine the lithostratigraphic layer. Porosity data other than matrix porosity data 
were excluded from consideration because the Hsu model requires matrix porosity and wet and 
dry thermal conductivity as inputs. Matrix porosity data are obtained from laboratory core 
measurements. It is worth distinguishing between matrix porosity, which is due to interstitial 
porosity between grains, and whole rock porosity, which is structurally controlled by regional 
fracturing. 
Figure 4-1 shows the location of 44 boreholes in the Yucca Mountain region that supplied rock 
specimens used for parameter measurements. Boreholes that were chosen for model input are 
shown as black diamonds; boreholes that supplied core used for model validation are shown as 
open circles. Appendix T lists these boreholes and their casing elevation and Nevada State Plane 
coordinates. 
Qualified, verified matrix porosity and thermal conductivity data are used to generate the Hsu 
model for thermal conductivity for the nonrepository layers of the Yucca Mountain site. 
1. Data tables in the SEP database of the Yucca Mountain Project Technical Data 
Management System (TDMS) provided the material properties (matrix porosity, dry 
and saturated matrix thermal conductivity) used to construct the thermal conductivity 
model. 
2. DTNs: MO0004QGFMPICK.000 [DIRS 152554] and SNF40060298001.001 
[DIRS 107372] are used to correlate the location of matrix porosity and thermal 
conductivity to the stratigraphic units defined in Table U-1 of Appendix U of this 
report. 
3. The range of values for the thermal conductivity of solid glass was taken from the 
Chemical Engineers' Handbook (Perry and Chilton 1973 [DIRS 104946], p. 3-260). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-2 October 2004 
Source: DTNs: MO9906GPS98410.000 [DIRS 109059], MO9905LUSWWT24.000 [DIRS 165921], 
MO9912GSC99492.000 [DIRS 165922]. 
NOTES: Prefixes UE-25 and USW are omitted from borehole names because of spacing constraints. Complete 
names are listed in Appendix T. 
Unqualified data, and data not available as triads, are also used in model validation. 
Figure 4-1. Location of Boreholes Used for the Thermal Conductivity Study 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-3 October 2004 
The thermal conductivity model applies to the nonrepository stratigraphic units of the GFM as 
described in Appendix U, Table U-1. The construction of the thermal conductivity model 
requires matrix porosity and dry and saturated matrix thermal conductivities for the same 
location. These triads of data are obtained from qualified and verified data tracking numbers 
(DTNs) in TDMS. The triads are processed by the inverse code HSUINV (STN 10804-1.0-00 
[DIRS 158228]) to generate solid thermal conductivity and a geometric parameter (gamma_c or 
.c). The development of the thermal conductivity model also uses matrix porosity data for the 
stratigraphic model units listed in Table U-1. Only qualified and verified matrix porosity data 
are used. The data used in model validation require porosity and either dry or saturated thermal 
conductivity, or else porosity and in situ saturation and thermal conductivity. These data are 
obtained from qualified, verified DTNs in TDMS. The probability distributions for solid thermal 
conductivity, .c, and porosity are used by GENHSUMODELDATA (STN 10905-1.0-00 
[DIRS 162671]) to generate the model data. 
4.1.1 Lithostratigraphic Contacts 
Lithostratigraphic contacts can be established from observations based on core specimens, 
petrophysical logs, or borehole video logs. The DTNs which include this type of information are 
shown in Table 4-1. 
Table 4-1. Source of Input for Observed Lithostratigraphic Contacts 
Data Source Description Reference 
Lithostratigraphic Contacts (multiple boreholes) DTN MO0004QGFMPICK.000 [DIRS 152554] 
Lithostratigraphic Contacts (USW SD-6) DTN SNF40060298001.001 [DIRS 107372] 
Definitions of the lithostratigraphic layers are given in the DTNs cited in Table 4-1. The GFM 
units from Table U-1 are identified as divisions of lithostratigraphic subzones whose contact 
depths are available from Table 4-1 DTNs. Because the 31 matrix porosity, wet thermal 
conductivity, and dry thermal conductivity data triads (Table 4-2) do not provide data for all of 
the Table U-1 units shown, it is necessary to group the units into larger categories: welded, nonwelded, 
vitric, and calico. The assignment of Table U-1 model units to one of these categories is 
based on the textural description of the lithostratigraphic subzone in 
DTN MO0004QGFMPICK.000 [DIRS 152554]. Vitric, densely welded subzones are classified 
as vitric. Non-welded and moderately welded vitric subzones are classified as non-welded. 
Welded subzones are classified as welded. Subzones of the Calico Hills Formation are classified 
as calico. The remaining subzones above the Calico Hills Formation are classified as 
non-welded. The lithostratigraphic units below the Calico Hills Formation (i.e., the Tram, 
Bullfrog, and Prow Pass tuffs) are divided into welded and non-welded subzones for the Prow 
Pass, Bullfrog, and Tram Tuff, respectively. The correlation of GFM units to layer 
characterization is shown in Table 4-2. Because more porosity data are available, ten unique 
rock types are characterized for matrix porosity. Conversely, fewer thermal-conductivity input 
data are available; therefore, only four unique rock types are characterized. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-4 October 2004 
Table 4-2. Layer Characterization of the GFM 
GFM Units 
(from Table U-1) 
Layer Characterization for 
Matrix Porosity 
Layer 
Characterization 
for Thermal 
Conductivity 
Triad 
Counta,b 
Crystal-rich Tiva/Post-Tiva, Tpcp, TpcLD welded welded 6 
Tpcpv3 vitric vitric 0 
Tpcpv1, Tpcpv2, Tpbt4, Yucca, Tpbt3_dc, 
Pah, Tpbt2, Tptrv3, Tptrv2 
non-welded non-welded 9 
Tptrv1 vitric vitric 0 
Tptrl, Tptrn, and Tptf welded welded 11 
Tptpv3 vitric vitric 0 
Tptpv1, Tptpv2, Tpbt1 non-welded non-welded 0 
Calico, Calicobt calico calico 5 
Prowuv, Prowuc Prow Pass Hills non-welded non-welded 0 
Prowmd Prow Pass Hills welded welded 0 
Prowlv, Prowlc, Prowbt Prow Pass Hills non-welded non-welded 0 
Bullfroguv, Bullfroguc Bullfrog non-welded non-welded 0 
Bullfrogmd Bullfrog welded welded 0 
Bullfroglc, Bullfroglv, Bullfrogbt Bullfrog non-welded non-welded 0 
Tramuv, Tramuc Tram Tuff non-welded non-welded 0 
Trammd Tram Tuff weldedc welded 0 
Tramlc, Tramlv, Trambt Tram Tuff non-welded non-welded 0 
Source: Geologic Framework Model (GFM2000) (BSC 2004 [DIRS 170029], Table 6-2). 
Column triad count was produced by REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) using the data from 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file DATAQ.zip)), and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
a Zero count indicates lack of wet matrix thermal conductivity, dry matrix thermal conductivity, and porosity data 
acquired from rock samples collected at a single location. 
b A complete triad count and listing of associated data are provided in Table 6-13. 
c Matrix porosity values from the Prow Pass Welded layer are substituted for those of the Tram Tuff welded layer 
because no data are available for the Tram Tuff welded layer. 
4.1.2 Matrix Porosity Data 
Matrix porosity data for Boreholes UE-25 NRG #4, UE-25 NRG #5, USW NRG-6 and USW 
NRG-7/7a, USW SD-7, USW SD-9 and USW SD-12 are the only qualified data available that 
can be paired with qualified dry and saturated matrix thermal conductivity data. The data for 
UE-25 NRG #5 are located in the repository horizons and are not of interest for this model 
report. The sources of matrix porosity are shown in Table 4-3. 

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MDL-NBS-GS-000006 REV 01 4-5 October 2004 
Table 4-3. Sources of Matrix Porosity Data for Thermal Conductivity Model Input 
Data Source Description Reference DTN Data Table 
Matrix porosity data for Boreholes UE-25 NRG #4, 
UE-25 NRG #5, USW NRG-6 and USW NRG-7/7a 
SNL01A05059301.007 
[DIRS 108980] 
S98424_003 
Matrix porosity data for Borehole USW NRG-6 GS000508312231.006 
[DIRS 153237] 
S00415_001 
Matrix porosity data for Boreholes USW SD-7, 
USW SD-9, and USW SD-12 
MO0109HYMXPROP.001 
[DIRS 155989] 
S01144_001 
(file DATAQ.zip) 
Matrix porosity data for Borehole USW NRG-6 SNL02030193001.002 
[DIRS 120575] 
S98484_001 
Matrix porosity data for Borehole USW NRG-6 SNL02030193001.002 
[DIRS 120575] 
S98484_005 
Matrix porosity data for Borehole USW NRG-6 SNL02030193001.022 
[DIRS 109613] 
S99111_001 
4.1.3 Matrix Thermal Conductivity 
Qualified and verified matrix thermal conductivity data that can be paired with matrix porosities 
are used as input to the inverse code HSUINV (STN 10804-1.0-00 [DIRS 158228]) to generate 
solid thermal conductivity distributions and a geometric parameter. These distributions are used 
to build the thermal conductivity model. The thermal conductivity DTNs used to develop the 
thermal conductivity model are shown in Table 4-4. 
Table 4-4. Sources of Qualified, Verified Matrix Thermal Conductivity Data 
Data Source Description Reference DTN Data Table 
Matrix thermal conductivity data for Boreholes UE-25 NRG #4, 
UE-25 NRG #5, USW NRG-6, and USW NRG-7/7a 
SNL01A05059301.005 
[DIRS 109002] 
S96370_001 
Matrix thermal conductivity data for Boreholes USW SD-7, 
USW SD-9, and USW SD-12 
SNL22100196001.006 
[DIRS 158213] 
S98169_002 
4.1.4 Thermal Conductivity of Solid Glass 
There are no DTNs that contain vitric data triads (porosity, wet and dry thermal conductivities), 
so there are no inputs for the inverse code HSUINV (STN 0804-1.0-00 [DIRS 158228]). 
HSUINV (STN 0804-1.0-00 [DIRS 158228]) generates solid thermal conductivity and geometry 
factor values, but the solid thermal conductivity and geometry factor can be estimated from other 
sources. A range of solid thermal conductivity for solid glass (0.35 to 1.26 W/m K) is taken 
from the Chemical Engineers' Handbook (Perry and Chilton 1973 [DIRS 104946], Table 3-260). 
4.1.5 Dry Bulk Density 
Dry bulk density measurements are used to develop product outputs shown in Table 6-13. 
However, the measurements are not direct input to the Hsu model; they were processed using the 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) code to assign model layers in accordance 
with the lithostratigraphic correlation table given in Appendix U. The resulting output is 
included in Table 6-13 and output DTN SN0303T0503102.008; therefore, the dry bulk density 
measurements listed in Table 4-5 are considered direct input for this model report. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-6 October 2004 
In the absence of validation thermal conductivity data for several of the layers, it is necessary to 
calculate validation data by a regression of existing qualified, verified data. Porosity and dry 
bulk density are used as variables in the regression. The data regression is described in 
Section 7.2, and is supported by documentation provided in Appendix Q and Appendix R. Dry 
bulk density data are available from 48 data tables from 37 DTNs. The DTNs are given in 
Table 4-5. 
Supporting documentation for the processing of dry bulk density data is provided in Section 6.7 
and in Appendix L. Appendix V documents the qualification of two "unqualified" dry bulk 
density data sets (GS920408312314.011 [DIRS 129660] and GS930408312132.007 
[DIRS 129625]) intended for use in this model report (see Table 6-13). 
Table 4-5. Sources of Dry Bulk Density 
Data Source Description Reference DTN Data Table 
Dry bulk density data for USW UZ-N11 to USW 
UZ-N64 
GS000408312231.004 [DIRS 149582] S00276_001 
Dry bulk density data for USW NRG-6 GS000508312231.006 [DIRS 153237] S00415_001 
Dry bulk density data for USW SD-12 and radial 
boreholes 
GS950308312231.002 [DIRS 108990] S96015_001 
Dry bulk density data for USW SD-9 GS950408312231.004 [DIRS 108986] S96021_001 
Dry bulk density data for UE-25 UZ #16 GS940508312231.006 [DIRS 107149] S96024_003 
Dry bulk density data for USW UZ-N53 GS930108312231.006 [DIRS 108997] S96025_001 
Dry bulk density data for USW UZ-N54 and USW 
UZ-N55 
GS920508312231.012 [DIRS 109001] S96026_001 
Dry bulk density data for USW UZ-N57, USW 
UZ-N61, USW UZ-N62 
GS940408312231.004 [DIRS 109000] S96027_001 
Dry bulk density data for USW SD-7 GS951108312231.009 [DIRS 108984] S96037_001 
Dry bulk density data for USW NRG-7/7a GS951108312231.010 [DIRS 108983] S96046_001 
Dry bulk density data for USW UZ-7a GS951108312231.011 [DIRS 108992] S96049_001 
Dry bulk density data for USW SD-7 and USW 
SD-12 
GS960808312231.004 [DIRS 108985] S97058_001 
Dry bulk density data for USW H-1 GS920408312314.011 [DIRS 129660] S97135_002 
Dry bulk density data for UE-25 J-13 GS930408312132.007 [DIRS 129625] S97276_001 
Dry bulk density data for USW WT-24 GS980708312242.010 [DIRS 106752] S98248_004 
Dry bulk density data for USW SD-6 GS980808312242.014 [DIRS 106748] S98285_001 
Dry bulk density data for UE-25 NRG #4, UE-25 
NRG #5, USW NRG-6, USW NRG-7/7a 
SNL01A05059301.007 [DIRS 108980] S98424_001 
Dry bulk density data for USW NRG-6 SNL02030193001.002 [DIRS 120575] S98484_001 
Dry bulk density data for USW NRG-6 SNL02030193001.002 [DIRS 120575] S98484_002 
Dry bulk density data for USW NRG-6 SNL02030193001.002 [DIRS 120575] S98484_004 
Dry bulk density data for USW NRG-6 SNL02030193001.002 [DIRS 120575] S98484_005 
Dry bulk density data for USW NRG-6 SNL02030193001.004 [DIRS 108415] S98485_001 
Dry bulk density data for USW NRG-6 SNL02030193001.004 [DIRS 108415] S98485_003 
Dry bulk density data for USW NRG-6 SNL02030193001.008 [DIRS 120597] S98486_001 
Dry bulk density data for UE-25 NRG #2 SNL02030193001.003 [DIRS 120578] S99100_001 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-7 October 2004 
Table 4-5. Sources of Dry Bulk Density (Continued) 
Data Source Description Reference DTN Data Table 
Dry bulk density data for UE-25 NRG #2 SNL02030193001.003 [DIRS 120578] S99100_004 
Dry bulk density data for UE-25 NRG #2a SNL02030193001.006 [DIRS 120579] S99101_001 
Dry bulk density data for UE-25 NRG #2a SNL02030193001.006 [DIRS 120579] S99101_004 
Dry bulk density data for UE-25 NRG #2b SNL02030193001.013 [DIRS 120614] S99104_001 
Dry bulk density data for UE-25 NRG #2b SNL02030193001.013 [DIRS 120614] S99104_004a 
Dry bulk density data for UE-25 NRG #3 SNL02030193001.005 [DIRS 122545] S99105_001 
Dry bulk density data for UE-25 NRG #3 SNL02030193001.005 [DIRS 122545] S99105_004b 
Dry bulk density data for UE-25 NRG #3 SNL02030193001.007 [DIRS 120582] S99106_001 
Dry bulk density data for UE-25 NRG #4 SNL02030193001.014 [DIRS 109609] S99107_001 
Dry bulk density data for UE-25 NRG #4 SNL02030193001.014 [DIRS 109609] S99107_004 
Dry bulk density data for UE-25 NRG #4 SNL02030193001.015 [DIRS 120617] S99108_001 
Dry bulk density data for UE-25 NRG #5 SNL02030193001.009 [DIRS 109614] S99109_001c 
Dry bulk density data for UE-25 NRG #5 SNL02030193001.012 [DIRS 108416] S99110_001 
Dry bulk density data for USW NRG-6 SNL02030193001.022 [DIRS 109613] S99111_002 
Dry bulk density data for USW NRG-7/7a SNL02030193001.016 [DIRS 120619] S99112_001 
Dry bulk density data for USW NRG-7/7a SNL02030193001.017 [DIRS 109610] S99113_001 
Dry bulk density data for USW NRG-7/7a SNL02030193001.018 [DIRS 109611] S99114_001 
Dry bulk density data for USW NRG-7/7a SNL02030193001.019 [DIRS 108431] S99115_001 
Dry bulk density data for USW NRG-7/7a SNL02030193001.019 [DIRS 108431] S99115_002 
Dry bulk density data for USW NRG-7/7a SNL02030193001.020 [DIRS 108432] S99116_001 
Dry bulk density data for USW NRG-7/7a SNL02030193001.020 [DIRS 108432] S99116_004 
Dry bulk density data for USW NRG-7/7a SNL02030193001.021 [DIRS 108433] S99117_001 
Dry bulk density data for USW NRG-6 SNL01A05059301.002 [DIRS 150042] S99435_001 
a Data table S99104_004 was excluded because the data are for an alluvium layer not considered in this report. 
b Data table S99105_004 was excluded because the lithostratigraphy correlation data 
(DTN MO0004QGFMPICK.000 [DIRS 152554]) are not available for UE-25 NRG #3. 
c Data table S99109_001 was excluded because the data are for the repository layers not considered in this 
report. 
4.2 CRITERIA 
The Project Requirements Document (Canori and Leitner 2003 [DIRS 166275]) includes the 
following criterion that is relevant to the work documented in this report: 
 PRD-002/T-015 Requirements for Performance Assessment; see 10 CFR 63.114 
[DIRS 156605] for complete requirement text. 
Work described in this model report supports these requirements, but more-specific criteria exist 
in the Yucca Mountain Review Plan, Final Report (NRC 2003 [DIRS 163274]). The criteria 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-8 October 2004 
established for the quantity and chemistry of water contacting engineered barriers and waste 
forms as presented in Section 2.2.1.3.3.3 of Yucca Mountain Review Plan, Final Report 
(NRC 2003 [DIRS 163274]) and 10 CFR 63.114(a)-(c) and (e)-(g) [DIRS 156605] are applicable 
to this model report. 
4.2.1 Acceptance Criteria 
The acceptance criteria relevant to this model report are presented in Section 4.2.1 of this report, 
and an assessment of how the criteria are addressed is provided in Section 8.2 of this report. 
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. 
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. 
Acceptance Criterion 4  Model Uncertainty is Characterized and 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; 
4.2.2 Completion Criteria 
Section 3.4 of the TWP (BSC 2004 [DIRS 171708]) addresses completion criteria for this report, 
and specifically requires that work be done to address Condition Report #2054. The condition 
report was written because some of the dry bulk density data used as direct input in this report 
were downgraded to unqualified status after this report was first issued. Appendix V documents 
the qualification of two unqualified data sets intended for use in this model report. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-9 October 2004 
Section 1.2.2 of the TWP (BSC 2004 [DIRS 171708]) describes the revision of this report as 
partial rewriting, editing, and reformatting to incorporate Regulatory Integration Team 
evaluation Phase 1 comments. 
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 and models include Subpart E, Section 114 (Requirements for Performance 
Assessment). 
4.4 INDIRECT INPUT DATA USED FOR MODEL VALIDATION 
Indirect input data include those data that are used to validate the Hsu model. It should be noted 
that the same DTN and SEP table may appear in the tables for direct input and also indirect 
input. In these cases, data extracted from SEP for model input were unique and separate from 
data used for model validation (e.g., unique sample numbers differing from core extraction 
depths within the same SEP table). 
4.4.1 Matrix Porosity 
Matrix porosity data used to evaluate the average porosity for the layer categories come from 
boreholes UE-25 NRG #4, UE-25 NRG #5, USW NRG-6, USW NRG-7/7a, USW SD-7, 
USW SD-9, and USW SD-12 from the six DTNs listed in Table 4-3. These data include 
487 welded porosities, 72 vitric porosities, 307 non-welded porosities, 258 Calico porosities, 55 
Prow Pass welded porosities, 421 Prow Pass non-welded porosities, 87 Bullfrog welded 
porosities, 54 Bullfrog non-welded porosities, and 26 Tram Tuff non-welded porosities. These 
porosity data do not have corresponding thermal conductivity data because they are used to 
compute an average porosity; the porosity data are not used by the inverse code HSUINV 
(STN 10804-1.0-00 [DIRS 158228]). 
Porosity data from 40 DTNs (57 data tables) are used to verify that the porosities used in 
building the Hsu model are representative of all the remaining porosities. The DTNs and data 
table numbers are shown in Table 4-6. 
Table 4-6. Sources of Matrix Porosity Data Used to Validate the Representative Data Assumption 
Data Source Description Reference DTN Data Table 
Matrix porosity data for various Boreholes USW 
UZ-N11 to USW UZ-N64 (see Figure 4-1), UE-25 
UZN #63 
GS000408312231.004 [DIRS 149582] S00276_001 
Matrix porosity data for Boreholes UE-25 c#1 and 
UE-25 c#2 MO0012POROCHOL.000 [DIRS 153376] S00452_001 
Matrix porosity data for various Boreholes USW 
UZ-N11 to USW UZ-N64, USW NRG-6, USW 
NRG-7, USW SD-7, USW SD-9, USW SD-12 
MO0109HYMXPROP.001 [DIRS 155989] S01144_001 
(file DATAQ.zip) 
Matrix porosity data for Borehole USW SD-7 MO0109HYMXPROP.001 [DIRS 155989] S01144_032 
(file DATAQ.zip) 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-10 October 2004 
Table 4-6. Sources of Matrix Porosity Data Used to Validate the Representative Data Assumption 
(Continued) 
Data Source Description Reference DTN Data Table 
Matrix porosity data for Borehole USW UZ-14 MO0109HYMXPROP.001 [DIRS 155989] S01144_033 
(file DATAQ.zip) 
Matrix porosity data for Borehole USW UZ-16 MO0109HYMXPROP.001 [DIRS 155989] S01144_034 
(file DATAQ.zip) 
Matrix porosity data for Borehole USW SD-12 and 
radial boreholes GS950308312231.002 [DIRS 108990] S96015_001 
Matrix porosity data for borehole USW SD-12 and 
radial boreholes GS950308312231.002 [DIRS 108990] S96015_002 
Matrix porosity data for borehole USW SD-9 GS950408312231.004 [DIRS 108986] S96021_002 
Matrix porosity data for borehole UE-25 UZ #16 GS940508312231.006 [DIRS 107149] S96024_002 
Matrix porosity data for borehole USW UZ-N53 GS930108312231.006 [DIRS 108997] S96025_002 
Matrix porosity data for borehole USW UZ-N54 
and USW UZ-N55 GS920508312231.012 [DIRS 109001] S96026_002 
Matrix porosity data for borehole USW UZ-N57, 
USW UZ-N61, USW UZ-N62 GS940408312231.004 [DIRS 109000] S96027_002 
Matrix porosity data for borehole USW SD-7 GS951108312231.009 [DIRS 108984] S96037_002 
Matrix porosity data for borehole USW NRG-7/7a GS951108312231.010 [DIRS 108983] S96046_001 
Matrix porosity data for borehole USW UZ-7/7a GS951108312231.011 [DIRS 108992] S96049_001 
Matrix porosity data for borehole USW SD-7 and 
USW SD-12 
GS960808312231.004 [DIRS 108985] S97058_002 
Matrix porosity data for borehole USW H-1 GS920408312314.011 [DIRS 129660] S97135_007 
Matrix porosity data for borehole UE-25 J-13 GS930408312132.007 [DIRS 129625] S97276_003 
Matrix porosity data for borehole USW WT-24 GS980708312242.010 [DIRS 106752] S98248_006 
Matrix porosity data for borehole USW SD-6 GS980808312242.014 [DIRS 106748] S98285_002 
Matrix porosity data for boreholes UE-25 NRG #4, 
UE-25 NRG #5, USW NRG-6, USW NRG-7/7a SNL01A05059301.007 [DIRS 108980] S98424_003 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.001 [DIRS 120572] S98483_001 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.002 [DIRS 120575] S98484_002 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.002 [DIRS 120575] S98484_004 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.004 [DIRS 108415] S98485_001 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.004 [DIRS 108415] S98485_003 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.004 [DIRS 108415] S98485_005 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.008 [DIRS 120597] S98486_001 
Matrix porosity data for borehole UE-25 NRG #2 SNL02030193001.003 [DIRS 120578] S99100_001 
Matrix porosity data for borehole UE-25 NRG #2 SNL02030193001.003 [DIRS 120578] S99100_004 
Matrix porosity data for borehole UE-25 NRG #2a SNL02030193001.006 [DIRS 120579] S99101_001 
Matrix porosity data for borehole UE-25 NRG #2a SNL02030193001.006 [DIRS 120579] S99101_004 
Matrix porosity data for borehole UE-25 NRG #2b SNL02030193001.013 [DIRS 120614] S99104_001 
Matrix porosity data for borehole UE-25 NRG #2b SNL02030193001.013 [DIRS 120614] S99104_004 a 
Matrix porosity data for borehole UE-25 NRG #2b SNL02030193001.013 [DIRS 120614] S99104_005 
Matrix porosity data for borehole UE-25 NRG #3 SNL02030193001.005 [DIRS 122545] S99105_001 
Matrix porosity data for borehole UE-25 NRG #3 SNL02030193001.005 [DIRS 122545] S99105_004 b 
Matrix porosity data for borehole UE-25 NRG #3 SNL02030193001.007 [DIRS 120582] S99106_001 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-11 October 2004 
Table 4-6. Sources of Matrix Porosity Data Used to Validate the Representative Data Assumption 
(Continued) 
Data Source Description Reference DTN Data Table 
Matrix porosity data for borehole UE-25 NRG #4 SNL02030193001.015 [DIRS 120617] S99108_001 
Matrix porosity data for borehole UE-25 NRG #5 SNL02030193001.009 [DIRS 109614] S99109_001 c 
Matrix porosity data for borehole UE-25 NRG #5 SNL02030193001.009 [DIRS 109614] S99109_002 
Matrix porosity data for borehole UE-25 NRG #5 SNL02030193001.012 [DIRS 108416] S99110_001 
Matrix porosity data for borehole USW NRG-6 SNL02030193001.022 [DIRS 109613] S99111_002 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.016 [DIRS 120619] S99112_001 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.017 [DIRS 109610] S99113_001 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.017 [DIRS 109610] S99113_003 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.018 [DIRS 109611] S99114_001 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.019 [DIRS 108431] S99115_001 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.019 [DIRS 108431] S99115_002 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.020 [DIRS 108432] S99116_001 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.020 [DIRS 108432] S99116_004 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.020 [DIRS 108432] S99116_006 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.021 [DIRS 108433] S99117_001 
Matrix porosity data for borehole USW NRG-7/7a SNL02030193001.021 [DIRS 108433] S99117_005 
Matrix porosity data for borehole USW SD-9 SNL02030193001.028 [DIRS 159972] S99121_001 
Matrix porosity data for borehole USW NRG-6 SNL01A05059301.002 [DIRS 150042] S99435_001 
a Data table S99104_004 was excluded because the data are for an alluvium layer not considered in this report. 
b Data table S99105_004 was excluded because the lithostratigraphy correlation data 
(DTN MO0004QGFMPICK.000 [DIRS 152554]) are not available for UE-25 NRG #3. 
c Data table S99109_001 was excluded because the data are for the repository layers not considered in this 
report. 
4.4.2 Thermal Conductivity 
The sources of thermal conductivity data used to validate the thermal conductivity model are 
shown in Table 4-7. 
Table 4-7. Sources of Thermal Conductivity Data 
Data Source Description Reference DTN Data Table 
Matrix thermal conductivity data for Boreholes UE-25 NRG #4, 
UE-25 NRG #5, USW NRG-6, and USW NRG-7/7a 
SNL01A05059301.005 
[DIRS 109002] 
S96370_001 
Matrix thermal conductivity data for Boreholes USW SD-7, 
USW SD-9, and USW SD-12 
SNL22100196001.006 
[DIRS 158213] 
S98169_002 
Matrix thermal conductivity summary data SN0011T0571897.014 
[DIRS 154449] 
S00441_001 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-12 October 2004 
Data tables DTN SNL01A05059301.005 [DIRS 109002] s96370_001 and 
DTN SNL22100196001.006 [DIRS 158213] s98169_002 were used to develop the thermal 
conductivity model. DTN SN0011T0571897.014 [DIRS 154449] data table s00441_001 and the 
data not used for model building in tables SNL01A05059301.005 [DIRS 109002] s96370_001 
and DTN SNL22100196001.006 [DIRS 158213] s98169_002 are used to validate the model. 
All ten qualified validation thermal conductivity values for the Prow Pass Tuff and all eight 
qualified validation thermal conductivity values available for the Bullfrog Tuff come from 
DTN SN0011T0571897.014 [DIRS 154449] data table s00441_001. Eight of the locations for 
these data, designated by Tcp1, Tcp2, Tcp3, Tcp4, Tcb1, Tcb2, Tcb3, and Tcb4, are not standard 
lithostratigraphic units as defined in Table U-1. The designations span one or more standard 
lithostratigraphic units. A correlation between these designations and stratigraphic units listed in 
Table U-1 was established by using borehole identifier and depth information in 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file DATAQ.zip)) and 
examining the relative sizes of the thermal conductivity values in DTN SN0011T0571897.014 
([DIRS 154449] data table s00441_001). 
The DTN MO0109HYMXPROP.001 [DIRS 155989] data table s01144_001 (file DATAQ.zip) 
includes 239 lines of data from Tcp units 1, 2, 3, and 4, each with borehole identifier and depth. 
The borehole identifiers and depths allow the unique determination of the stratigraphic units 
listed in Table U-1. Of the 114 values for Tcp unit 1, 105 were from Prow Pass Tuff non-welded 
units, and nine were from Bullfrog Tuff non-welded units, so Tcp1 is most likely categorized as 
Prow Pass non-welded, with a possibility of being Bullfrog non-welded. The Tcp1 data are 
assigned to the Prow Pass non-welded category, and the impact of the data actually falling in the 
Bullfrog non-welded category will be assessed at the end of this section (Section 4.4.2). 
The 56 values for Tcp unit 2 in DTN MO0109HYMXPROP.001 [DIRS 155989] data 
table s01144_001 (file DATAQ.zip) correspond to stratigraphic unit Tcplv (see Table U-1), 
which is in the Prow Pass non-welded category. The two Tcp unit 4 points correspond to Tcpuv, 
which is Prow Pass non-welded; therefore, both Tcp2 and Tcp4 are Prow Pass non-welded 
layers. 
The 67 values for Tcp unit 3 in DTN MO0109HYMXPROP.001 [DIRS 155989] data 
table s01144_001 (file DATAQ.zip) correspond to both welded and non-welded units. The dry 
thermal conductivity values for Tcp1, Tcp2, Tcp3, and Tcp4 in DTN SN0011T0571897.014 
[DIRS 154449] data table s00441_001 are 0.67, 0.69, 0.63, and 0.60 watts per meter degree 
Kelvin (W/m K), respectively. Because the high and low values are non-welded (Tcp2 and 
Tcp4), it is reasonable that all four values are non-welded values. 
The wet thermal conductivity values for Tcp1, Tcp2, Tcp3, and Tcp4 are 1.28, 1.32, 1.23, and 
1.18 W/m K, respectively. Because the values for Tcp1 and Tcp2 samples fall within the range 
defined by Tcp2and Tcp4, it is reasonable to assign non-welded values to all four samples. 
The Bullfrog designators Tcb1, Tcb2, Tcb3, and Tcb4 are not present in any input DTN other 
than SN0011T0571897.014 [DIRS 154449], so the assignment to welded or non-welded is based 
on the similarity to the Prow Pass data, and on the relative sizes of the thermal conductivity 
values. The dry thermal conductivity values for Tcb1, Tcb2, Tcb3, and Tcb4 are 0.70, 0.70, 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 4-13 October 2004 
1.40, and 1.40 W/m K, respectively. The 95-percent confidence limits on these values in the 
source DTN SN0011T0571897.014 [DIRS 154449] are 0.68 to 0.72 W/m K for Tcb1 and Tcb2 
and 1.37 to 1.44 W/m K for Tcb3 and Tcb4. It is reasonable that the 0.70 W/m K values 
represent non-welded layers because of their closeness to the Prow Pass non-welded range of 
0.60 to 0.69 W/m K. It is reasonable that the significantly higher 1.40 W/m K values represent 
the welded layers. 
The wet thermal conductivity values for Tcb1, Tcb2, Tcb3, and Tcb4 are 1.33, 1.33, 1.85, and 
1.85 W/m K, respectively. The 95-percent confidence limits are 1.20 to 1.46 W/m K for Tcb1 
and Tcb2 and 1.80 to 1.90 W/m K for Tcb3 and Tcb4, so the values are from two distinctly 
different groups. It is reasonable that the 1.33 W/m K values are non-welded and the 1.85 
W/m K values are welded because the welded thermal conductivities tend to be higher than the 
non-welded within a layer. The Tcp non-welded thermal conductivity averages are 0.648 
W/m K for dry samples and 1.25 W/m K for wet samples. The Tcb non-welded averages are 
0.70 W/m K for dry samples and 1.33 W/m K for wet samples. If the Tcp1 values were assigned 
to the Bullfrog unit rather than the Prow Pass unit, the new thermal conductivity averages would 
be 0.640 W/m K for dry Tcp, 1.24 W/m K for wet Tcp, 0.69 W/m K for dry Tcb and 
1.31 W/m K for wet Tcb. The changes are all less than 1.6 percent. These changes would be 
negligible in the model validation because all the model standard deviations will be shown to 
exceed 10 percent of the means. 

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INTENTIONALLY LEFT BLANK

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 5-1 October 2004 
5. ASSUMPTIONS 
Assumption 1: Data from boreholes UE-25 NRG #4, USW NRG-6, USW NRG-7, USW SD-7, 
USW SD-9, and USW SD-12 intersect the repository and are representative of the repository 
layers in terms of matrix porosity, saturated thermal conductivity and dry thermal conductivity. 
These boreholes are also assumed to be representative of the entire Yucca Mountain. 
Basis: The boreholes are well spaced and located in the interior of the repository boundary. 
They sample an appropriate portion of the repository host rock and surrounding lithostratigraphic 
units. 
Confirmation Status: Confirmed. This assumption is verified by showing that the means for the 
model and the means for the remaining data are not statistically different at a confidence level of 
95 or 98 percent. The assumption is validated in Section 7.1. No further confirmation is needed 
because Assumption 1 is fully supported by the statistical analysis in Section 7.1. 
Use: Assumption 1 is used in selecting the data processed as described in Section 6.3 and 
Section 6.4. 
Assumption 2: It is assumed that the vitric solid thermal conductivity distribution can be 
approximated by a uniform distribution over the thermal conductivity range for glass from the 
Chemical Engineers' Handbook (Perry and Chilton 1973 [DIRS 104946], p. 3-260), from 0.35 to 
1.26 W/m K and the .c distribution is constant with value 1.0. (This value is the most probable 
value for the .c distributions above the Calico Hills.) 
Basis: The chemical and mineral composition of vitric lithostratigraphic units associated with 
layers surrounding the repository are sufficiently similar to glass as characterized in the 
engineering handbook to enable this approximation of material properties to be valid for this use. 
Confirmation Status: Confirmed. The assumption is validated in Section 7.3. No further 
confirmation is required because Assumption 2 is fully supported by the statistical analysis in 
Section 7.3. Justification of this assumption is provided by showing that the model mean and the 
mean of the remaining data are not statistically different at a confidence level of 95 or 98 
percent. 
Use: Assumption 2 is used in the data processed as described in Section 6.3 and Section 6.4. 

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Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-1 October 2004 
6. MODEL 
As outlined in Section 1, this report documents the development and results of the thermal 
conductivity model for nonrepository layers of the Yucca Mountain. Section 6 consists of the 
following: 
 Model discussion (Section 6.1) 
 Uncertainties in data measurement (Section 6.2) 
 Creation of matrix porosity, wet thermal conductivity, and dry thermal conductivity 
triads (Section 6.3) 
 Distributions of gamma_c and solid thermal conductivity for welded, non-welded, vitric, 
and Calico rock types (Section 6.4) 
 Distributions of matrix porosity for welded, non-welded, vitric, Calico, Prow, Bullfrog, 
and Tram Tuff units (Section 6.5) 
 Distributions of matrix porosity, gamma_c and solid thermal conductivity used by 
GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) (Section 6.6) 
 Dry bulk density analysis (Section 6.7) 
 Impact of the choice of distribution type on thermal conductivity values (Section 6.8). 
Data used for model development are listed according to the following direct input use: 
Lithostratigraphic contact input data are from DTN MO0004QGFMPICK.000 [DIRS 152554] 
and DTN SNF40060298001.001 [DIRS 107372]. 
Layer characterization of model units is from Table U-1, DTN MO0004QGFMPICK.000 
([DIRS 152554] data table s00214_001), DTN SNF40060298001.001 ([DIRS 107372 
s98430_001), DTN SNL01A05059301.007 ([DIRS 108980] s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] s96370_001), DTN MO0109HYMXPROP.001 
([DIRS 155989] s01144_001 (file DATAQ.zip)), and DTN SNL22100196001.006 
([DIRS 158213] s98169_002). 
Matrix porosity input data are from DTN SNL01A05059301.007 ([DIRS 108980] s98424_003), 
DTN GS000508312231.006 ([DIRS 153237] s00415_001), DTN MO0109HYMXPROP.001 
([DIRS 155989] s01144_001 (FILE DATAQ.ZIP)), DTN SNL02030193001.002 ([DIRS 120575] 
s98484_001), DTN SNL02030193001.002 ([DIRS 120575] s98484_005), and 
DTN SNL02030193001.022 ([DIRS 109613] s99111_001). 
Thermal conductivity input data are from DTN SNL01A05059301.005 ([DIRS 109002] 
s96370_001) and DTN SNL22100196001.006 ([DIRS 158213] s98169_002). 
As discussed in Section 4.1.5, dry bulk density data were not used for model development. They 
were included in the model output (Table 6-13) only to correlate model units with average dry 
bulk density values. Appendix V documents the qualification of two unqualified data sets 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-2 October 2004 
(GS920408312314.011 [DIRS 129660] and GS930408312132.007 [DIRS 129625]) intended for 
use (product output) in this model report. 
No corroborating or supporting data were used for model development. 
6.1 MODEL DISCUSSION 
The thermal conductivity model for nonrepository layers of the Yucca Mountain is a summary of 
wet and dry thermal conductivities for the GFM lithostratigraphic units based on qualified, 
verified thermal conductivity measurements. 
The thermal conductivity of porous materials has been the subject of considerable study for 
several decades. Consequently, many analytical and empirical models have been developed for 
this property. This research is beneficial from the perspective of finding a predictive model that 
may be applied at Yucca Mountain. In order to include the effects of matrix porosity and 
saturation in the model, a mathematical model developed by Hsu et al. (1995 [DIRS 158073]) 
was used to represent the thermal conductivity of the repository horizons (Thermal Conductivity 
of the Potential Repository Horizon (BSC 2004 [DIRS 169854]). The nonrepository thermal 
conductivity model continues to use the Hsu model for the reasons cited in Thermal Conductivity 
of the Potential Repository Horizon (BSC 2004 [DIRS 169854], Section 6.1.7). 
As cited in Thermal Conductivity of the Potential Repository Horizon (BSC 2004 
[DIRS 169854], Section 6.1.7), three candidate models are examined for application at Yucca 
Mountain. The proposed models are Heat Transfer Characteristics of Porous Rocks. 
American Institute of Chemical Engineers Journal, 6 (Kunii and Smith 1960 [DIRS 153166]); 
Thermal Conductivity of Packed Metal Powders. International Journal of Heat and Mass 
Transfer, 29 (Hadley 1986 [DIRS 153165]); and A Lumped-Parameter Model for Stagnant 
Thermal Conductivity of Spatially Periodic Porous Media. Journal of Heat Transfer, 117 (Hsu 
et al. 1995 [DIRS 158073]). All three models address consolidated porous media and in theory 
are good candidates for this work. One of the three was ultimately selected based on the 
following screening criteria: 
1. The theoretical development must be well documented, relatively easy to comprehend, 
and appropriate for consolidated porous media. 
2. The model must be capable of reproducing experimental results within the estimated 
range of experimental error. 
3. The model parameters and their uncertainty must be easily derived through existing 
qualified data. 
Kunii and Smith (1960 [DIRS 153166]) assume that the thermal conductivity of a porous 
medium can be represented by a layer of fluid acting in parallel with a composite layer consisting 
of both fluid and solid phases. Parameters that dictate the geometry of the composite layer are 
derived based on an analytical solution of heat flow between two spheres. The authors 
extrapolate this solution to approximate multiple spheres by considering additional contact points 
and the orientation of these contacts for various packing arrangements. The theory can be 
extended to consolidated porous media by adjusting the shape and relative size of void and solid 
space. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-3 October 2004 
The fundamental premise behind the Kunii and Smith model is that the analytical solution of 
heat flux between two spheres can be stretched and approximated to the point that it is applicable 
to consolidated porous substances. This argument is convincing for unconsolidated granular 
substances, but not as convincing for consolidated media, because the geometric configuration of 
the pore space in the latter is quite different for loosely packed spheres for which the basic 
formulation of the Kunii and Smith model was developed. This model was, therefore, not 
selected based on Criterion 1. 
The Hadley model (1986 [DIRS 153165]) is derived from volume-averaging theory and makes 
use of the pioneering work of Maxwell (1954 [DIRS 158165], pp. 440 and 441). This is a 
versatile model that is applicable over the complete range of potential pore structures. In 
addition, the model is unique in that it is not explicitly tied to a specific geometry or packing 
arrangement. The model was not selected, however, due to the difficulty of quantifying model 
parameter uncertainty from existing data. 
The final model examined and ultimately selected is the 3-D cubic model developed by Hsu 
et al. (1995 [DIRS 158073]). This model is conceptually similar to that proposed by Kunii and 
Smith (1960 [DIRS 153166]) in that a simplified geometrical representation of the porous 
medium is proposed and then the effective thermal conductivity of the simplified problem is 
derived through resistance analogues. In the case of the 3-D cubic model, the porous medium is 
represented by a periodic array of in-line cubes with connecting nodules. The unit cell of the 
3-D periodic array is shown in Figure 6-1. 
Source: Hsu et al. (1995 [DIRS 158073], Figure 8). 
Figure 6-1. 3-D Schematic of the HSU Model 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-4 October 2004 
Hsu et al. (1995 [DIRS 158073], Equation 14) derive the following equation for this geometry: 
( )
. . . + . . - 
. . - . . 
+ 
. . + . - 
. . - . 
+ 
.
. . 
+ . . + . . - . - = 
a c a c 
2
a c a c 
a a 
2
a 
2
c 
2
a 
2
a 
2
c 2
a c a c 
2
a 
f
m 
1
2 
1 
2 2 1 
k
k (Eq. 6-1) 
where: 
.a = a/l; .c = c/a; . = kf / ks; 
and 
ks, kf, and km are the thermal conductivities of the solid, fluid, and composite matrix, 
respectively, 
and where: 
the scales a, c, and l are as shown in Figure 6-1. 
As illustrated in Figure 6-1, l is the length of the unit cell cube shown, a is the length of one side 
of the solid square, and c is the width of the connecting nodule. It should be noted that the 
connecting nodules have square cross-sections, but are not cubes. The connecting nodule 
protrudes from the face of the solid cube a distance defined by (l-a)/2. 
For the 3-D cubic model unit cell illustrated in Figure 6-1, the pore-volume may be computed by 
subtracting the volume of the solid cube, a3, and the 6 connecting nodules, each having a volume 
of c2(l-a)/2, from the unit cell volume, l3. Furthermore, from geometrical considerations it can 
be shown that .a and .c are functionally dependent. This dependency may be written as Hsu 
et al.s Equation 13 (1995 [DIRS 158073]): 
( ) 0 3 1 3a 
2
a 
2
c 
3a
m = . - . . - . - f - . (Eq. 6-2) 
It is apparent from Equation 6-1 and Equation 6-2 that the effective matrix thermal conductivity 
may be expressed as a function of four independent variables: 
( ) c m s f m , , k , k f k . f = . (Eq. 6-3) 
The Hsu model uses parameters matrix porosity (fm), solid thermal conductivity (ks), a 
geometrical factor (.c), and thermal conductivities for air and water to generate the wet and dry 
matrix thermal conductivities (kw and kd) of a material. The geometrical factor is not a 
measurable quantity, and measurements of solid thermal conductivity usually are not available, 
but both can be calculated using the inverse of the Hsu model. The inverse code HSUINV 
(STN 10804-1.0-00 [DIRS 158228]), takes matrix porosity and wet (saturated) and dry thermal 
conductivity measurements and calculates ks and .c. This computational method was chosen 
over other inverse codes because the HSUINV (STN 10804-1.0-00 [DIRS 158228]) software is 
used for a parallel modeling study involving potential repository layers (BSC 2004 
[DIRS 169854]). The model development is done using qualified, verified data for matrix 
porosity and thermal conductivity for boreholes USW SD-7, USW SD-9, USW SD-12, UE-25 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-5 October 2004 
NRG #4, UE-25 NRG #5, USW NRG-6, and USW NRG-7/7a. These inputs are identified in 
Table 4-3 and Table 4-4. 
From the calculated values of ks and .c, distributions of ks and .c are developed with methods 
discussed in Section 6.4 for four categories of geologic layers (defined in Section 4.1.1): 
1. Welded 
2. Non-welded 
3. Vitric 
4. Calico. 
Because there are many more matrix porosity values than thermal conductivity values, matrix 
porosity distributions are developed with methods discussed in Section 6.5 for 10 types of 
geologic layers: 
1. Welded above the Calico Hills 
2. Non-welded above the Calico Hills 
3. Vitric 
4. Calico Hills 
5. Prow Pass welded 
6. Prow Pass non-welded 
7. Bullfrog welded 
8. Bullfrog non-welded 
9. Tram Tuff welded 
10. Tram Tuff non-welded. 
Combining the porosity and thermal conductivity distributions using qualified software package 
GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) gives the thermal conductivity 
model for these ten types. The model is presented as the mean and standard deviation for kd, kw, 
and fm for each of the 41 nonrepository model units (see Table U-1) within the ten types of 
geologic layers. 
The model development is done using most of the qualified, verified data for matrix porosity and 
thermal conductivity for boreholes USW SD-7, USW SD-9, USW SD-12, UE-25 NRG #4, UE-5 
NRG #5, USW NRG-6, and USW NRG-7. These inputs are identified in Table 4-3 and 
Table 4-4. All of the remaining qualified, verified data for matrix porosity and thermal 
conductivity are used for data for model validation. These inputs are identified in Table 4-6 and 
Table 4-7. 
The Product Output information from this model report is available in the TDMS as 
DTN SN0307T0503102.009. The top-level directory contains a file README.TXT that 
describes how to reproduce the calculations and output in this report. There are two first level 
subdirectories: Inputs and Outputs. Subdirectory Inputs contains subdirectories 
Genhsumodeldata, Hsuinv, Lithostr, QVDryBulkDens, QVPorosity, and QVTC. Subdirectory 
Outputs contain subdirectories HsuInv, Lithostr, QVDryBulkDens, QVPorosity, QVTC, 
TCRegression, and Validation. Subdirectories Inputs and Outputs contain the input and output 
data described in Section 6 and Section 7 of this report. No preliminary outputs were developed 
for this study; therefore, comparison between preliminary and final output is not discussed. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-6 October 2004 
The SEP data tables used in this report contain more than 35,000 lines of data, so the contents of 
the tables are not listed in this report. The SEP tables are included in subdirectories 
Inputs\Lithostr, Inputs\QVDryBulkDens, Inputs\QVPorosity and Inputs\QVTC with file names 
given by the data table name (shown in Table 4-3 to Table 4-7) with a .txt suffix appended. 
6.2 UNCERTAINTIES IN DATA MEASUREMENT 
Estimates on the uncertainties in the experimental measurements of porosity, bulk density, and 
wet and dry thermal conductivity are discussed in Appendix A. Although the term errors is 
used in Appendix A, these are actually uncertainties caused by limitations in the measuring 
equipment and technique rather than errors made by the person making the measurement. The 
matrix thermal conductivity measurement uncertainties are approximately 5 percent of the 
measured value for both oven dry and saturated specimens. 
Differences between matrix porosities calculated using dry densities and grain densities, rather 
than dry bulk densities and saturated bulk densities, indicate relative differences as large as 
17 percent; however a 9-percent relative difference is assessed to be a reasonable bound for most 
of the data (34 of 37 data points) (Appendix A, Column O of spreadsheet). Using these data 
(Appendix A, Column O), a reasonable estimate of measurement uncertainty is approximately 
5 percent for porosities less than 0.11. However, the smallest porosity examined in Appendix A, 
Column L, is approximately 0.066. Therefore, the maximum relative uncertainty based on the 
absolute measurement uncertainty (1 percent in Appendix A) is approximately 15 percent 
(0.01/0.066 = 0.15) for values less than 0.11. For porosities greater than 0.11, 9 percent of the 
measured is a good bound on the measurement relative uncertainty, because 34 of 37 data points 
(approximately 92 percent of the data points) have smaller relative uncertainties. 
Dry bulk density is computed from the specimen mass divided by the specimen volume. Mass is 
measured to 0.01g (Appendix A of this report) and masses are typically from 16 g to 60 g 
(DTN SNL01A05059301.002 [DIRS 150042], data table s99435_001), so the relative 
uncertainty in the mass measurement is, at most, 0.0006. Volumes are typically 12 cm3 to 
26 cm3 (DTN SNL01A05059301.002 [DIRS 150042], data table s99435_001). Using the cube 
root of the volume as an estimate of the length measurement, the length measurement would be 
roughly 2.3 cm. Because lengths are usually accurate to 0.001 inch (approximately 0.0025 cm), 
the relative uncertainty in the length is approximately 0.001. Because the volume is 
approximately three times the length, the relative uncertainty in volume is approximately 0.003. 
Combining the measurement relative uncertainties in mass and volume, the relative uncertainty 
in the dry bulk density measurement is approximately 0.004, or approximately 0.4 percent. 
When measurement uncertainties are compared to model uncertainties in Section 6.6, they are 
bounded by the model uncertainties. 
6.3 CREATION OF POROSITY, WET THERMAL CONDUCTIVITY, AND DRY 
THERMAL CONDUCTIVITY TRIADS 
DTN SNL01A05059301.007 ([DIRS 108980] SEP table s98424_003) provides porosities for 
54 samples. DTN SNL01A05059301.005 ([DIRS 109002] SEP table s96370_001) provides wet 
and dry thermal conductivity values at 56 different locations. The program SPLICE 
(STN 10906-1.0-00 [DIRS 162672]), which combines a file of porosity data with a file of wet 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-7 October 2004 
and dry thermal conductivity data based on a common sample ID, uses these input data with the 
input control file shown in Appendix B to produce the 47 fm, kd, kw, data triads shown in 
Table 6-1. Table 6-1 is used as input to the inverse program HSUINV (STN: 10804-1.0-00 
[DIRS 158228]) to obtain values for Hsu-model (Hsu et al. 1995 [DIRS 158073]) parameters ks 
and .c. The output of the inverse program HSUINV (STN 10804-1.0-00 [DIRS 158228]) is 
shown in Table 6-2; units of thermal conductivity (ks) are W/m K, and porosity (phi) and 
gamma_c (a geometrical factor (gc)) are dimensionless. 
Table 6-1. Input Data from NRG Boreholes 
Borehole Sample IDa 
Porosity 
(fm) 
Dry Thermalb 
Conductivity 
(kd) 
(W/m K) 
Wet 
Thermalb 
Conductivity 
(kw) (W/m K) 
Porosity 
Data Table 
Name 
(see 
Table 4-3) 
Porosity 
Data 
Table 
Row 
Thermal 
Conductivity 
Data Table 
Name 
(see Table 4-4) 
NRG4 470.0 SNL B 0.4855043 0.355 0.980 s98424_003 3 s96370_001 
NRG4 529.0 SNL B 0.1650256 1.160 1.670 s98424_003 4 s96370_001 
NRG4 586.2 SNL B 0.1944229 0.945 1.640 s98424_003 6 s96370_001 
NRG4 654.0 SNL B 0.1369164 1.155 1.800 s98424_003 10 s96370_001 
NRG5 781.8 SNL A 0.1571485 1.000 1.920 s98424_003 11 s96370_001 
NRG5 791.6 SNL A 0.2458759 0.820 1.780 s98424_003 12 s96370_001 
NRG5 834.8 SNL B 0.0891167 1.655 1.920 s98424_003 13 s96370_001 
NRG5 843.5 SNL A 0.0876777 1.650 2.200 s98424_003 14 s96370_001 
NRG5 848.0 SNL B 0.1210091 1.500 2.610 s98424_003 15 s96370_001 
NRG5 853.8 SNL Ac 0.0873173 1.705 2.260 s98424_003 16 s96370_001 
NRG5 874.9 SNL Bc 0.0862342 1.675 2.320 s98424_003 17 s96370_001 
NRG5 879.6 SNL A 0.0869565 1.625 3.090 s98424_003 18 s96370_001 
NRG5 886.5 SNL B 0.1235689 1.370 2.530 s98424_003 19 s96370_001 
NRG5 893.3 SNL B 0.1125198 1.460 2.750 s98424_003 20 s96370_001 
NRG5 899.8 SNL B 0.1100516 1.475 2.770 s98424_003 21 s96370_001 
NRG6 28.8 SNL C 0.0400000 1.750 1.910 s98424_003 22 s96370_001 
NRG6 98.1 SNL I 0.0600000 1.590 1.710 s98424_003 23 s96370_001 
NRG6 111.0 SNL I 0.0900000 1.435 2.010 s98424_003 24 s96370_001 
NRG6 152.9 SNL E 0.4300000 0.430 1.040 s98424_003 25 s96370_001 
NRG6 187.0 SNL F 0.4900000 0.315 0.790 s98424_003 26 s96370_001 
NRG6 241.5 SNL E 0.6100000 0.250 0.730 s98424_003 27 s96370_001 
NRG6 277.5 SNL E 0.1000000 1.255 1.680 s98424_003 28 s96370_001 
NRG6 321.1 SNL E 0.1500000 1.165 1.710 s98424_003 29 s96370_001 
NRG6 392.1 SNL D 0.0400000 1.185 1.550 s98424_003 31 s96370_001 
NRG6 416.0 SNL K 0.0900000 1.285 1.550 s98424_003 32 s96370_001 
NRG6 421.8 SNL D 0.1268657 1.190 1.700 s98424_003 33 s96370_001 
NRG6 425.3 SNL B 0.1379992 1.260 1.820 s98424_003 34 s96370_001 
NRG6 451.2 SNL B 0.1852146 1.290 1.700 s98424_003 35 s96370_001 
NRG6 556.1 SNL B 0.2774451 0.910 2.040 s98424_003 36 s96370_001 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-8 October 2004 
Table 6-1. Input Data from NRG Boreholes (Continued) 
Borehole Sample IDa Porosity 
Dry Thermalb 
Conductivity 
(W/m K) 
Wet 
Thermalb 
Conductivity 
(W/m K) 
Porosity 
Data Table 
Name 
(see 
Table 4-3) 
Porosity 
Data 
Table 
Row 
Thermal 
Conductivity 
Data Table 
Name 
(see Table 4-4) 
NRG6 693.1 SNL C 0.1362916 1.385 1.930 s98424_003 37 s96370_001 
NRG6 757.0 SNL B 0.0959556 1.610 2.020 s98424_003 38 s96370_001 
NRG6 778.1 SNL B 0.0840000 1.710 1.850 s98424_003 39 s96370_001 
NRG6 787.5 SNL B 0.1122611 1.600 1.720 s98424_003 40 s96370_001 
NRG6 802.7 SNL D 0.0945353 1.670 1.780 s98424_003 41 s96370_001 
NRG6 809.4 SNL B 0.0919952 1.640 1.660 s98424_003 42 s96370_001 
NRG6 900.4 SNL D 0.1445313 1.500 2.230 s98424_003 43 s96370_001 
NRG6 926.3 SNL E 0.1287437 1.540 2.150 s98424_003 44 s96370_001 
NRG6 987.0 SNL B 0.1175322 1.550 2.040 s98424_003 45 s96370_001 
NRG7 18.6 SNL D 0.0702314 1.550 1.900 s98424_003 46 s96370_001 
NRG7 27.0 SNL B 0.0657578 1.480 1.930 s98424_003 47 s96370_001 
NRG7 56.8 SNL D 0.1713371 1.175 2.040 s98424_003 48 s96370_001 
NRG7 75.0 SNL D 0.3025142 0.745 1.200 s98424_003 49 s96370_001 
NRG7 91.6 SNL D 0.4226626 0.435 1.010 s98424_003 50 s96370_001 
NRG7 104.1 SNL C 0.5843724 0.320 0.950 s98424_003 51 s96370_001 
NRG7 113.1 SNL B 0.4021739 0.435 1.040 s98424_003 52 s96370_001 
NRG7 248.5 SNL D 0.4950367 0.345 0.980 s98424_003 53 s96370_001 
NRG7 312.8 SNL D 0.1061018 1.330 1.630 s98424_003 54 s96370_001 
NOTES: This table was generated by SPLICE (STN: 10906-1.0-00 [DIRS 162672]) using data from 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003) and from 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001). 
The column headings have been modified for clarification and are not the same as in the computer 
output. 
This output is included in Product Output DTN SN0307T0503102.009 file 
Inputs\Hsuinv\nrghsuinv.inp. 
a Numeric values listed in the Sample ID column represent depth from the surface, in feet. The alpha character 
shown in the Sample ID column designates a particular test specimen taken from a single interval of core. When 
possible, wet and dry measurements were conducted on the same specimen. 
b Wet and dry thermal conductivity values corresponding to 70C and 110C, respectively, were selected for input, 
based on abundance of data. 
c Depths listed in the two input files disagree for NRG5 samples extracted from 853.8 feet and 874.9 feet because 
SPLICE (STN: 10906-1.0-00 [DIRS 162672]) allows for a difference of 1.3 feet. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-9 October 2004 
Table 6-2. HSUINV Output for Boreholes UE-25 NRG #4, UE-25 NRG #5, USW NRG-6 and 
USW NRG-7/7a 
Porosity 
phi 
Solid 
Thermal 
Conductivity 
(W/m K) 
ks 
Gamma_c 
gc Borehole Sample ID 
0.486 1.471 0.683 NRG4 470.0 SNL B 
0.165 2.048 0.943 NRG4 529.0 SNL B 
0.194 2.101 0.753 NRG4 586.2 SNL B 
0.137 2.165 0.799 NRG4 654.0 SNL B 
0.157 2.419 0.663 NRG5 781.8 SNL A 
0.246 2.569 0.617 NRG5 791.6 SNL A 
0.089 2.419 1.000 NRG5 834.8 SNL B 
0.088 2.533 0.888 NRG5 843.5 SNL A 
0.122 3.299 0.693 NRG5 848.0 SNL B 
0.088 2.610 0.892 NRG5 853.8 SNL A 
0.087 2.687 0.845 NRG5 874.9 SNL B 
0.087 3.739 0.632 NRG5 879.6 SNL A 
0.124 3.193 0.662 NRG5 886.5 SNL B 
0.113 3.451 0.647 NRG5 893.3 SNL B 
0.110 3.462 0.647 NRG5 899.8 SNL B 
0.040 2.203 1.000 NRG6 28.8 SNL C 
0.060 2.134 1.000 NRG6 98.1 SNL I 
0.090 2.296 0.849 NRG6 111.0 SNL I 
0.430 1.507 0.730 NRG6 152.9 SNL E 
0.490 1.093 1.000 NRG6 187.0 SNL F 
0.610 1.197 1.000 NRG6 241.5 SNL E 
0.100 1.894 0.945 NRG6 277.5 SNL E 
0.150 2.070 0.874 NRG6 321.1 SNL E 
0.040 1.617 0.843 NRG6 392.1 SNL D 
0.090 1.869 1.000 NRG6 416.0 SNL K 
0.127 1.991 0.884 NRG6 421.8 SNL D 
0.138 2.194 0.870 NRG6 425.3 SNL B 
0.185 2.375 1.000 NRG6 451.2 SNL B 
0.277 3.366 0.578 NRG6 556.1 SNL B 
0.136 2.345 0.906 NRG6 693.1 SNL C 
0.096 2.395 1.000 NRG6 757.0 SNL B 
0.084 2.466 1.000 NRG6 778.1 SNL B 
0.112 2.484 1.000 NRG6 787.5 SNL B 
0.095 2.478 1.000 NRG6 802.7 SNL D 
0.092 2.415 1.000 NRG6 809.4 SNL B 
0.145 2.842 0.814 NRG6 900.4 SNL D 
0.129 2.639 0.873 NRG6 926.3 SNL E 
0.118 2.437 1.000 NRG6 987.0 SNL B 
0.0658 2.116 0.897 NRG7 27.0 SNL B 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-10 October 2004 
Table 6-2. HSUINV Output for Boreholes UE-25 NRG #4, UE-25 
NRG #5, USW NRG-6 and USW NRG-7/7a (Continued) 
Porosity 
phi 
Solid 
Thermal 
Conductivity 
(W/m K) 
ks 
Gamma_c 
gc 
Borehole Sample ID 
0.171 2.677 0.720 NRG7 56.8 SNL D 
0.303 1.753 1.000 NRG7 75.0 SNL D 
0.423 1.414 0.789 NRG7 91.6 SNL D 
0.5843 1.648 0.706 NRG7 104.1 SNL C 
0.4023 1.450 0.721 NRG7 113.1 SNL B 
0.4953 1.496 0.665 NRG7 248.5 SNL D 
0.106 2.021 1.000 NRG7 312.8 SNL D 
NOTES: This table was generated by HSUINV (STN: 10804-1.0-00 
[DIRS 158228]) using data from: DTN SNL01A05059301.007 
([DIRS 108980] data table s98424_003) and 
DTN SNL01A05059301.005 ([DIRS 109002] data table 
s96370_001). 
The column headings have been modified for clarification, and are 
not the same as in the computer output. 
This output is included in Product Output DTN 
SN0307T0503102.009 (file Output\Hsuinv\\hsuinv\nrghsuinv.out). 
Data triads for the Calico Hills layer were created in the following manner. SEP data table 
DTN SNL22100196001.006 ([DIRS 158213] S98169_002) contains thermal conductivity and 
saturation values for boreholes USW SD-7, USW SD-9, and USW SD-12. SEP data table 
DTN MO0109HYMXPROP.001 ([DIRS 155989] s01144_001 (file DATAQ.zip)) contains 
porosity data for six samples for these boreholes in the Calico Hills Formation. These two data 
files are not in the format expected by the program SPLICE (STN 10906-1.0-00 
[DIRS 162672]), so it is necessary to reformat the files using the program REFORMAT 
(STN 10907-2.0-00 [DIRS 162673]). The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) 
input control files are shown in Appendix C and Appendix D. The reformatted data tables 
r01144_001.txt (from DTN MO0109HYMXPROP.001 [DIRS 155989] data table s01144_001 
(file DATAQ.zip)) and r98169_002.txt (from DTN SNL22100196001.006 [DIRS 158213] data 
table s98169_002) are used as input to the program SPLICE (STN 10906-1.0-00 
[DIRS 162672]). The input control file for SPLICE (STN 10906-1.0-00 [DIRS 162672]) is 
shown in Appendix E. Table 6-3 shows the five data triads developed for the Calico Hills layer. 
Table 6-3 is used as input to the inverse program HSUINV (STN 10804-1.0-00 [DIRS 158228]) 
to obtain values for Hsu-model parameters ks and .c. The output of the inverse program 
HSUINV (STN 10804-1.0-00 [DIRS 158228]) is shown in Table 6-4. Units of thermal 
conductivity are W/m K. Porosity and .c are dimensionless. Note that though data triads were 
not available for the Calico Hills layer, the process that creates the triads is reasonable because 
(1) the vertical depths at the sampling locations for the two data sets within the three different 
boreholes have comparable high porosities (25 to 35 percent) and (2) the degree of spatial 
correlation of the high porosity zones of the Calico Hills unit is of the order of several meters. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-11 October 2004 
Therefore, it is reasonable to treat the sampling points between the data sets as the same. 
The program REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) is used to append the 
lithostratigraphy to the two inverse-program HSUINV (STN 10804-1.0-00 [DIRS 158228]) 
output-data files. The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input control file is 
shown in Appendix F. The inverse program HSUINV (STN 10804-1.0-00 [DIRS 158228]) 
output data with lithostratigraphy is shown in Table 6-5. The lithostratigraphic units Tptpmn, 
Tptpul, and Tptpll are repository layers and are not used in this model. 
Table 6-3. HSUINV Input for Boreholes USW SD-7, USW SD-9, and USW SD-12 
Porosity (see Table 4-3) 
Borehole 
Sample ID Porosity 
Dry Thermal 
Conductivitya 
(W/m K) 
Wet Thermal 
Conductivityb 
(W/m K) 
Data Table 
Name 
Data Table 
Row 
SD7 1509 0.325 0.535 1.100 s01144_001 2211 
SD9 1635.1 0.356 0.520 1.220 s01144_001 2978 
SD9 1813.2 0.248 0.730 1.580 s01144_001 3035 
SD12 1513.0 0.381 0.530 1.150 s01144_001 3545 
SD12 1644.9 0.260 0.760 1.420 s01144_001 3587 
NOTES: This table was generated by SPLICE (STN 10906-1.0-00 [DIRS 162672]) using data from 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file DATAQ.zip)) and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
The column headings have been modified for clarification and are not the same as in the computer 
output. 
This output is included in Product Output DTN SN0307T0503102.009. 
aAt 110C. 
bAt 70C. 
Table 6-4. HSUINV Output for Boreholes USW SD-7, USW SD-9, and USW SD-12 
Porosity 
phi 
Solid 
Thermal Conductivity 
(W/m K) 
ks 
Gamma_c 
gc 
Borehole Sample ID 
0.325 1.437 0.781 SD7 1509 
0.356 1.766 0.658 SD9 1635.1 
0.248 2.180 0.634 SD9 1813.2 
0.381 1.661 0.750 SD12 1513.0 
0.260 1.909 0.749 SD12 1644.9 
NOTES: This table was generated by HSUINV (STN: 10804-1.0-00 [DIRS 158228]) using data from 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file DATAQ.zip)) and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
The column headings have been modified for clarification and are not the same as in the computer 
output. 
This output is included in Product Output DTN SN0307T0503102.009. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-12 October 2004 
Table 6-5. HSUINV Output File with Lithostratigraphy 
phi 
ks 
(W/m K) gc 
Borehole Sample 
ID 
Lithostratigraphic 
Unit 
0.486 1.471 0.683 NRG4 470.0 SNL B Tpbt2 
0.165 2.048 0.943 NRG4 529.0 SNL B Tptrn 
0.194 2.101 0.753 NRG4 586.2 SNL B Tptrn 
0.137 2.165 0.799 NRG4 654.0 SNL B Tptrn 
0.157 2.419 0.663 NRG5 781.8 SNL A Tptpmn 
0.246 2.569 0.617 NRG5 791.6 SNL A Tptpmn 
0.089 2.419 1.000 NRG5 834.8 SNL B Tptpmn 
0.088 2.533 0.888 NRG5 843.5 SNL A Tptpmn 
0.121 3.299 0.693 NRG5 848.0 SNL B Tptpmn 
0.087 2.610 0.892 NRG5 853.8 SNL A Tptpmn 
0.086 2.687 0.845 NRG5 874.9 SNL B Tptpmn 
0.087 3.739 0.632 NRG5 879.6 SNL A Tptpmn 
0.124 3.193 0.662 NRG5 886.5 SNL B Tptpmn 
0.113 3.450 0.647 NRG5 893.3 SNL B Tptpmn 
0.110 3.462 0.647 NRG5 899.8 SNL B Tptpmn 
0.040 2.203 1.000 NRG6 28.8 SNL C Tpc_un 
0.060 2.136 1.000 NRG6 98.1 SNL I Tpc_un 
0.090 2.296 0.849 NRG6 111.0 SNL I Tpc_un 
0.430 1.508 0.730 NRG6 152.9 SNL E Tpcpv1 
0.490 1.093 1.000 NRG6 187.0 SNL F Tpp 
0.610 1.197 1.000 NRG6 241.5 SNL E Tpbt2 
0.100 1.894 0.945 NRG6 277.5 SNL E Tptrn 
0.150 2.070 0.874 NRG6 321.1 SNL E Tptrn 
0.040 1.617 0.843 NRG6 392.1 SNL D Tptrn 
0.090 1.869 1.000 NRG6 416.0 SNL K Tptrn 
0.127 1.991 0.884 NRG6 421.8 SNL D Tptrn 
0.138 2.194 0.870 NRG6 425.3 SNL B Tptrn 
0.185 2.375 1.000 NRG6 451.2 SNL B Tptrl 
0.277 3.366 0.578 NRG6 556.1 SNL B Tptpul 
0.136 2.345 0.906 NRG6 693.1 SNL C Tptpul 
0.096 2.395 1.000 NRG6 757.0 SNL B Tptpmn 
0.084 2.466 1.000 NRG6 778.1 SNL B Tptpmn 
0.112 2.484 1.000 NRG6 787.5 SNL B Tptpmn 
0.095 2.478 1.000 NRG6 802.7 SNL D Tptpmn 
0.092 2.415 1.000 NRG6 809.4 SNL B Tptpmn 
0.145 2.842 0.814 NRG6 900.4 SNL D Tptpll 
0.129 2.640 0.873 NRG6 926.3 SNL E Tptpll 
0.118 2.437 1.000 NRG6 987.0 SNL B Tptpll 
0.070 2.144 1.000 NRG7 18.6 SNL D Tpc_un 
0.066 2.116 0.897 NRG7 27.0 SNL B Tpc_un 
0.171 2.677 0.720 NRG7 56.8 SNL D Tpc_un 
0.303 1.753 1.000 NRG7 75.0 SNL D Tpcpv2 
0.423 1.414 0.789 NRG7 91.6 SNL D Tpcpv1 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-13 October 2004 
Table 6-5. HSUINV Output File with Lithostratigraphy (Continued) 
phi 
ks 
(W/m K) gc 
Borehole Sample 
ID 
Lithostratigraphic 
Unit 
0.584 1.648 0.706 NRG7 104.1 SNL C Tpbt4 
0.402 1.450 0.721 NRG7 113.1 SNL B Tpy 
0.495 1.496 0.665 NRG7 248.5 SNL D Tpp 
0.106 2.021 1.000 NRG7 312.8 SNL D Tptrn 
0.325 1.437 0.781 SD7 1509 Tac 
0.356 1.766 0.658 SD9 1635.1 Tac 
0.248 2.180 0.634 SD9 1813.2 Tacbt 
0.381 1.661 0.750 SD12 1513.0 Tac 
0.260 1.909 0.749 SD12 1644.9 Tacbt 
NOTES: This table was generated by REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) using data from 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file DATAQ.zip)), and from 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
Lithostratigraphic units are designations of GFM2000 (Appendix U). 
6.4 DISTRIBUTIONS OF GAMMA_C AND SOLID THERMAL CONDUCTIVITY 
FOR WELDED, NON-WELDED, VITRIC, AND CALICO ROCK TYPES 
Just as the thermal conductivity of a material will vary spatially, the ks and .c values generated 
from experimental data tend to differ for each triad. Instead of using a constant or mean value 
for each parameter, the calculated values are used to approximate probability distributions for the 
parameter. The program GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) samples 
these probability distributions for fm, ks, and .c and calculates averages and standard deviations 
for fm, kd, and kw. However, the only distribution types accepted by GENHSUMODELDATA 
(STN 10905-1.0-00 [DIRS 162671]) are normal, uniform, and exponential. 
For some of the available data, the .c distribution appears roughly exponential, with its peak 
probability at .c = 1 (the theoretical range of .c is from 0, exclusive, to 1, inclusive). For some 
geologic layers the distribution is not readily identifiable because there are too few 
measurements available. A uniform distribution is used when the data are not readily 
identifiable as a particular type of probability distribution. The impact of choosing a uniform 
distribution when a normal distribution might be considered more appropriate is assessed in 
Section 6.8. The impact was found to be negligible. In a similar manner, a probability 
distribution can be assigned to the values of ks that are calculated by the inverse program 
HSUINV (STN: 10804-1.0-00 [DIRS 158228]). The same could be done with matrix porosity, 
but because there are more than 1,700 matrix porosity measurements and only 31 data triads of 
matrix porosity and wet and dry thermal conductivity, it is more reasonable to take the larger 
number of data points and determine the matrix porosity distribution from them. 
The program REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) is used to separate the inverse 
program HSUINV (STN 10804-1.0-00 [DIRS 158228]) output file with lithostratigraphy into 
four ks files and four .c files based on the lithostratigraphy. The vitric output files contain 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-14 October 2004 
headers, but no data. The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input control file is 
shown in Appendix G. Data from the separate data tables are shown in Table 6-6 to Table 6-11. 
The first line of these tables shows the geologic layers for the data. The 1 on the second line 
specifies that column one contains input data for HISTPLT (STN 10802-2.01-00 
[DIRS 158223]). The third line is the x-axis label for HISTPLT (STN 10802-2.01-00 
[DIRS 158223]). 
Data triads corresponding to the repository have been removed at this point by REFORMAT 
(STN 10907-2.0-00 [DIRS 162673]) 
Table 6-6. Welded Solid Thermal Conductivity Data 
Welded Layers 
1 
Solid Thermal Conductivity 
(W/m K) 
Lithostratigraphic 
Unit 
Borehole Sample 
ID 
2.048 Tptrn NRG4 529.0 SNL B 
2.101 Tptrn NRG4 586.2 SNL B 
2.165 Tptrn NRG4 654.0 SNL B 
2.203 Tpc_un NRG6 28.8 SNL C 
2.134 Tpc_un NRG6 98.1 SNL I 
2.296 Tpc_un NRG6 111.0 SNL I 
1.894 Tptrn NRG6 277.5 SNL E 
2.070 Tptrn NRG6 321.1 SNL E 
1.617 Tptrn NRG6 392.1 SNL D 
1.869 Tptrn NRG6 416.0 SNL K 
1.991 Tptrn NRG6 421.8 SNL D 
2.194 Tptrn NRG6 425.3 SNL B 
2.375 Tptrl NRG6 451.2 SNL B 
2.144 Tpc_un NRG7 18.6 SNL D 
2.116 Tpc_un NRG7 27.0 SNL B 
2.677 Tpc_un NRG7 56.8 SNL D 
2.021 Tptrn NRG7 312.8 SNL D 
NOTES: This table was generated by REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) 
using data from 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 
(file DATAQ.zip)), and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
The first line of this table shows the geologic layers for the data. 
The 1 on the second line specifies that column one contains input data for 
HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 
The third line is the x-axis label for HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-15 October 2004 
Table 6-7. Welded Gamma_c Data 
Welded Layers 
1 
Gamma_c Lithostratigraphic Unit Borehole Sample ID 
0.943 Tptrn NRG4 529.0 SNL B 
0.753 Tptrn NRG4 586.2 SNL B 
0.799 Tptrn NRG4 654.0 SNL B 
1.000 Tpc_un NRG6 28.8 SNL C 
1.000 Tpc_un NRG6 98.1 SNL I 
0.849 Tpc_un NRG6 111.0 SNL I 
0.945 Tptrn NRG6 277.5 SNL E 
0.874 Tptrn NRG6 321.1 SNL E 
0.843 Tptrn NRG6 392.1 SNL D 
1.000 Tptrn NRG6 416.0 SNL K 
0.884 Tptrn NRG6 421.8 SNL D 
0.870 Tptrn NRG6 425.3 SNL B 
1.000 Tptrl NRG6 451.2 SNL B 
1.000 Tpc_un NRG7 18.6 SNL D 
0.897 Tpc_un NRG7 27.0 SNL B 
0.720 Tpc_un NRG7 56.8 SNL D 
1.000 Tptrn NRG7 312.8 SNL D 
NOTES: This table was generated by REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) 
using data from 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file 
DATAQ.zip)), and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
The first line of this table shows the geologic layers for the data. 
The 1 on the second line specifies that column one contains input data for 
HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 
The third line is the x-axis label for HISTPLT(STN 10802-2.01-00 [DIRS 158223]). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-16 October 2004 
Table 6-8. Non-welded Solid Thermal Conductivity Data 
Non-welded Layers 
1 
Solid thermal conductivity 
(W/m K) Lithostratigraphic Unit Borehole Sample ID 
1.471 Tpbt2 NRG4 470.0 SNL B 
1.507 Tpcpv1 NRG6 152.9 SNL E 
1.093 Tpp NRG6 187.0 SNL F 
1.197 Tpbt2 NRG6 241.5 SNL E 
1.753 Tpcpv2 NRG7 75.0 SNL D 
1.414 Tpcpv1 NRG7 91.6 SNL D 
1.648 Tpbt4 NRG7 104.1 SNL C 
1.450 Tpy NRG7 113.1 SNL B 
1.496 Tpp NRG7 248.5 SNL D 
NOTES: This table was generated by REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) using 
data from DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file 
DATAQ.zip)), and DTN: SNL22100196001.006 ([DIRS 158213] data table 
s98169_002). 
The first line of this table shows the geologic layers for the data. 
The 1 on the second line specifies that column one contains input data for 
HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 
The third line is the x-axis label for HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-17 October 2004 
Table 6-9. Non-welded Gamma_c Data 
Non-welded Layers 
1 
Gamma_c Lithostratigraphic Unit Borehole Sample ID 
0.683 Tpbt2 NRG4 470.0 SNL B 
0.730 Tpcpv1 NRG6 152.9 SNL E 
1.000 Tpp NRG6 187.0 SNL F 
1.000 Tpbt2 NRG6 241.5 SNL E 
1.000 Tpcpv2 NRG7 75.0 SNL D 
0.789 Tpcpv1 NRG7 91.6 SNL D 
0.706 Tpbt4 NRG7 104.1 SNL C 
0.721 Tpy NRG7 113.1 SNL B 
0.665 Tpp NRG7 248.5 SNL D 
NOTES: This table was generated by REFORMAT (STN: 10907-2.0-00 
[DIRS 162673]) using data from 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file 
DATAQ.zip)), and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
The first line of this table shows the geologic layers for the data. 
The 1 on the second line specifies that column one contains input data for 
HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 
The third line is the x-axis label for HISTPLT (STN 10802-2.01-00 
[DIRS 158223]). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-18 October 2004 
Table 6-10. Calico Hills Solid Thermal Conductivity Data 
Calico Hills Layers 
1 
Solid thermal 
conductivity (W/m K) Lithostratigraphic Unit Borehole Sample ID 
1.437 Tac SD7 1509 
1.766 Tac SD9 1635.1 
2.180 Tacbt SD9 1813.2 
1.661 Tac SD12 1513.0 
1.909 Tacbt SD12 1644.9 
NOTES: This table was generated by REFORMAT (STN: 10907-2.0-00 
[DIRS 162673]) using data from 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file 
DATAQ.zip)), and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
The first line of this table shows the geologic layers for the data. 
The 1 on the second line specifies that column one contains input data for 
HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 
The third line is the x-axis label for HISTPLT (STN 10802-2.01-00 
[DIRS 158223]). 
Table 6-11. Calico Hills Gamma_c Data 
Calico Hills Layers 
1 
Gamma_c Lithostratigraphic Unit Borehole Sample ID 
0.781 Tac SD7 1509 
0.658 Tac SD9 1635.1 
0.634 Tacbt SD9 1813.2 
0.750 Tac SD12 1513.0 
0.749 Tacbt SD12 1644.9 
NOTES: This table was generated by REFORMAT (STN: 10907-2.0-00 
[DIRS 162673]) using data from 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file 
DATAQ.zip)), and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002). 
The first line of this table shows the geologic layers for the data. 
The 1 on the second line specifies that column one contains input data for 
HISTPLT (STN 10802-2.01-00 [DIRS 158223]). 
The third line is the x-axis label for HISTPLT (STN 10802-2.01-00 
[DIRS 158223]). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-19 October 2004 
The welded ks values are shown in the histogram produced by HISTPLT (STN 10802-2.01-00 
[DIRS 158223]) in Figure 6-2. By visual inspection, a normal probability density distribution 
appears appropriate for a distribution, partly because the peak probability occurs near the center 
of the distribution, but also because the density of points drops off away from the center. The 
welded .c values are shown in the histogram in Figure 6-3. By visual inspection, an exponential 
distribution increasing between zero and one appears appropriate for the distribution. 
The program GENHSUMODELDATA (STN: 10905-1.0-00 [DIRS 162671]) requires as input 
the growth or decay rate of an exponential distribution. The growth or decay rate . can be found 
by iteration from the equation for the mean : 
) 1 e ( 
/ 1 e ) / 1 1 ( 
- 
+ - 
= . 
. . . 
 (Eq. 6-4) 
For increasing exponentials with  greater than 0.6, a good starting guess for . is: 
. = 1/(1 - ) (Eq. 6-5) 
For decreasing exponentials with  less than 0.3, a good starting guess for . is: 
. = - 1/ (Eq. 6-6) 
This starting guess is likely to be accurate to two or more significant digits. Appendix H 
contains a derivation of Equation 6-4, Equation 6-5, and Equation 6-6, and examples of the use 
of tabulations to improve the approximation of .. 
For the welded .c mean 0.9046, the growth rate . is 10.479. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-20 October 2004 
Solid Thermal Conductivity 
Frequency 
Solid thermal conductivi 
0.00 1.00 2.00 3.00 
0.000 
0.040 
0.080 
0.120 Welded ks Hsu output 
Number of Data 17 
mean 2.1126 
std. dev. 0.2199 
coef. of var 0.1041 
maximum 2.6773 
upper quartile 2.1963 
median 2.1164 
lower quartile 2.0136 
minimum 1.6171 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-2. Welded Solid Thermal Conductivity Histogram 
Frequency 
Gamma_c 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.100 
0.200 
0.300 
Welded gamma_c Hsu output 
Number of Data 17 
mean 0.9046 
std. dev. 0.0893 
coef. of var 0.0987 
maximum 1.0000 
upper quartile 1.0000 
median 0.8974 
lower quartile 0.8473 
minimum 0.7200 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-3. Welded Gamma_c Histogram 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-21 October 2004 
The non-welded ks values are shown in the histogram in Figure 6-4. The standard deviations 
shown in the histograms from the program HISTPLT (STN 10802-2.01-00 [DIRS 158223]) 
compute the standard deviation using a division by sqrt(N), where N is the number of points to 
obtain the appropriate standard deviation. 
Because the mean is computed from the data rather than known from other principles, the 
standard deviation from HISTPLT (STN 10802-2.01-00 [DIRS 158223]) should be multiplied by 
sqrt(N/(N-1)). For the 0.191 standard deviation from the histogram, the standard deviation 
using a division by sqrt(N-1) is 0.203. By visual inspection, no standard distribution appears 
appropriate, so a uniform distribution is chosen. The standard deviation for a uniform 
distribution ranged from A to B is: 
(B-A)/(2 sqrt (3)) (Eq. 6-7) 
where: 
A = start value. 
B = end value. 
sqrt = square root operator. 
The mean for a uniform distribution is (A+B)/2. Based on the known standard deviation and the 
mean, A and B are calculated, as shown in Table 6-12. This puts the endpoints approximately 
0.352 from the mean, and results in a uniform distribution between 1.096 and 1.799. The 
non-welded .c values are shown in the histogram in Figure 6-5. By visual inspection, no 
standard distribution appears appropriate, so a uniform distribution is chosen, resulting in a 
distribution between approximately 0.621 and 1.00. 
Frequency 
Solid thermal conductivi 
0.00 0.50 1.00 1.50 2.00 
0.000 
0.050 
0.100 
0.150 
0.200 
Non-welded ks Hsu output 
Number of Data 9 
mean 1.4476 
std. dev. 0.1914 
coef. of var 0.1322 
maximum 1.7529 
upper quartile 1.5423 
median 1.4715 
lower quartile 1.3598 
minimum 1.0928 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-4. Non-welded Solid Thermal Conductivity Histogram 
Solid Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-22 October 2004 
Frequency 
Gamma_c 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.100 
0.200 
0.300 
Non-welded gamma_c Hsu output 
Number of Data 9 
mean 0.8107 
std. dev. 0.1377 
coef. of var 0.1698 
maximum 1.0000 
upper quartile 1.0000 
median 0.7305 
lower quartile 0.7006 
minimum 0.6655 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-5. Non-welded Gamma_c Histogram 
No distribution can be chosen from the vitric data because there are no data triads. A range of 
solid thermal conductivity for glass from the Chemical Engineers' Handbook (Perry and Chilton 
1973 [DIRS 104946], p. 3-260), is used for the range of ks: 0.35 to 1.26 W/m K. The 
distribution is assumed to be uniform. The vitric .c is assumed to be a constant 1.0. This is the 
most probable value for the welded and non-welded rock types above the Calico Hills Formation 
(see Section 5, Assumptions). Note that for units located away from the repository that are near 
saturation and are isolated from the dry out zone near the repository horizon, the predicted 
thermal conductivity for the saturated case based upon the Hsu model is not sensitive to the 
solids. 
The Calico Hills ks values are shown in the histogram in Figure 6-6. By visual inspection, no 
standard distribution appears appropriate, so a uniform distribution is chosen. The distribution 
1.31 to 2.271 gives approximately the data mean and standard deviation. The Calico Hills .c 
values are shown in the histogram in Figure 6-7. By visual inspection, no standard distribution 
appears appropriate, so a uniform distribution is chosen. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-23 October 2004 
Frequency 
0.00 0.50 1.00 1.50 2.00 2.50 
0.000 
0.050 
0.100 
0.150 
0.200 
Calico Hills ks Hsu output 
Number of Data 5 
mean 1.7905 
std. dev. 0.2482 
coef. of var 0.1386 
maximum 2.1799 
upper quartile 1.9767 
median 1.7659 
lower quartile 1.6050 
minimum 1.4369 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-6. Calico Hills Solid Thermal Conductivity Histogram 
Frequency 
Gamma_c 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.100 
0.200 
0.300 
0.400 
Calico Hills gamma_c Hsu output 
Number of Data 5 
mean 0.7143 
std. dev. 0.0575 
coef. of var 0.0806 
maximum 0.7808 
upper quartile 0.7577 
median 0.7489 
lower quartile 0.6520 
minimum 0.6336 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-7. Calico Hills Gamma_c Histogram 
Solid Thermal Conductivity

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-24 October 2004 
6.5 DISTRIBUTIONS OF MATRIX POROSITY FOR WELDED, NON-WELDED, 
VITRIC, CALICO HILLS, PROW PASS, BULLFROG, AND TRAM TUFF UNITS 
Six data tables containing qualified, verified matrix porosity data for 7 boreholes are given in 
Table 4-3. The wet and dry thermal conductivity values used in model building come from these 
boreholes, so it is appropriate to obtain fm distributions from these same boreholes. The data 
from these six data tables are extracted for these boreholes and put into a data file using the 
REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input control file in Appendix I; a second 
REFORMAT run separates the data into nine files using the REFORMAT input control file in 
Appendix J of this report. 
The porosity data file yields 608 welded values, 73 vitric values, 351 non-welded values, 
258 Calico Hills values, 421 Prow Pass non-welded values, 55 Prow Pass welded values, 
54 Bullfrog non-welded values, 87 Bullfrog welded values, and 26 Tram Tuff non-welded 
values. Histograms of the data are shown in Figure 6-8 to Figure 6-16. No histogram is 
provided for the Tram Tuff welded layer because no porosity data are available. As described in 
Section 6.6, the Prow Pass welded layer was selected as a surrogate for the Tram Tuff welded 
layer. 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.050 
0.100 
0.150 
0.200 
Model welded porosity 
Number of Data 608 
mean 0.1189 
std. dev. 0.0489 
coef. of var 0.4117 
maximum 0.4520 
upper quartile 0.1560 
median 0.1200 
lower quartile 0.0750 
minimum 0.0060 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-8. Model Welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-25 October 2004 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.100 
0.200 
0.300 
0.400 
0.500 
Model vitric porosity 
Number of Data 73 
mean 0.0360 
std. dev. 0.0422 
coef. of var 1.1725 
maximum 0.3400 
upper quartile 0.0392 
median 0.0250 
lower quartile 0.0160 
minimum 0.0110 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-9. Model Vitric Matrix Porosity 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.020 
0.040 
0.060 
0.080 
0.100 
Model non-welded porosity 
Number of Data 351 
mean 0.3847 
std. dev. 0.1320 
coef. of var 0.3430 
maximum 0.6190 
upper quartile 0.4958 
median 0.3950 
lower quartile 0.3002 
minimum 0.0310 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-10. Model Non-welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-26 October 2004 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.050 
0.100 
0.150 
0.200 
0.250 
Model Calico Hills porosity 
Number of Data 258 
mean 0.3327 
std. dev. 0.0467 
coef. of var 0.1404 
maximum 0.4330 
upper quartile 0.3670 
median 0.3415 
lower quartile 0.3120 
minimum 0.1810 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-11. Model Calico Hills Matrix Porosity 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.050 
0.100 
0.150 
0.200 
0.250 
Model Prow Pass non-welded porosity
Number of Data 421 
mean 0.3001 
std. dev. 0.0445 
coef. of var 0.1482 
maximum 0.4400 
upper quartile 0.3290 
median 0.3040 
lower quartile 0.2788 
minimum 0.1510 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-12. Model Prow Pass Non-welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-27 October 2004 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.050 
0.100 
0.150 
0.200 
Model Prow Pass welded porosity - 
Number of Data 55 
mean 0.2093 
std. dev. 0.0556 
coef. of var 0.2654 
maximum 0.3030 
upper quartile 0.2515 
median 0.2160 
lower quartile 0.1655 
minimum 0.1000 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-13. Model Prow Pass Welded Matrix Porosity 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.050 
0.100 
0.150 
0.200 
Model Bullfrog non-welded porosity 
Number of Data 54 
mean 0.2298 
std. dev. 0.0551 
coef. of var 0.2399 
maximum 0.3470 
upper quartile 0.2720 
median 0.2085 
lower quartile 0.1870 
minimum 0.1430 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-14. Model Bullfrog Non-welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-28 October 2004 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.050 
0.100 
0.150 
0.200 
0.250 
Model Bullfrog welded porosity 
Number of Data 87 
mean 0.1212 
std. dev. 0.0519 
coef. of var 0.4280 
maximum 0.3180 
upper quartile 0.1345 
median 0.1050 
lower quartile 0.0900 
minimum 0.0590 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-15. Model Bullfrog Welded Matrix Porosity 
Frequency 
porosity 
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 
0.000 
0.050 
0.100 
0.150 
0.200 
Model Tram Tuff non-welded porosity
Number of Data 26 
mean 0.3318 
std. dev. 0.0593 
coef. of var 0.1786 
maximum 0.4420 
upper quartile 0.3800 
median 0.3415 
lower quartile 0.2940 
minimum 0.2120 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 6-16. Model Tram Tuff Non-welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-29 October 2004 
6.6 DISTRIBUTIONS OF MATRIX POROSITY, GAMMA_C, AND SOLID 
THERMAL CONDUCTIVITY USED BY GENHSUMODELDATA 
There are no kd, kw, fm data triads for the Prow Pass, Bullfrog, and Tram Tuff units. These 
units consist of welded and non-welded layers. There are, however, at least 26 values 
of fm for each of these layers, with the exception of the Tram Tuff non-welded layer. These data 
come from DTN GS000508312231.006 [DIRS 153237] data table s00415_001, 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file DATAQ.zip)), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNL02030193001.002 ([DIRS 120575] data tables s98484_001 and s98484_005), and 
DTN SNL02030193001.022 ([DIRS 109613] data table s99111_001). The thermal conductivity 
model for these layers is built from the inverse program HSUINV (STN 10804-1.0-00 
[DIRS 158228]) .c and ks distributions for the welded and non-welded units above the Calico 
Hills Formation and the fm distributions for the Prow Pass, Bullfrog, and Tram Tuff units. 
Because there are no fm data for the welded Tram Tuff layer (Table U-1, GFM Unit Trammd), 
the results for the Prow Pass welded layer (Prowmd) (Figure 6-13) are used for Trammd because 
of the proximity of the layers and the similarity between the non-welded fm distributions for 
Prow Pass (Figure 6-12) and Tram Tuff (Figure 6-16). 
With probability distributions of .c, ks, and fm available for a geologic layer, 
GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) can be used to generate values 
for the wet and dry matrix thermal conductivities. The distributions for .c, ks, and fm are shown 
in Table 6-12. Cells containing dashes () in Table 6-12 indicate that the data are not needed in 
the description of the distribution. 
The qualified program GENHSUMODELDATA (STN: 10905-1.0-00 [DIRS 162671]) generates 
15,625 values for wet and dry thermal conductivity using 25 values from each of the .c, ks, and 
fm distributions. The 25 values are evenly spaced from 0.02 to 0.98 on the cumulative 
probability distributions. The means and standard deviations of the matrix porosity and the wet 
and dry thermal conductivities are presented as the thermal conductivity model output data for 
each geologic layer. Because the model means come from distributions, it is possible that using 
the mean values of fm, .c, and ks as input to the Hsu model may not produce the model means. 
The three mean values of fm, .c, and ks are connected by the Hsu model. 
Dry bulk density data from boreholes USW SD-7, USW SD-9, USW SD-12, UE-25 NRG #4, 
UE-25 NRG #5, USW NRG-6, and USW NRG-7 were separated into welded, non-welded, 
vitric, Calico Hills, Prow Pass non-welded, Prow Pass welded, Bullfrog non-welded, Bullfrog 
welded, Tram Tuff welded, and Tram Tuff non-welded layers. The means and standard 
deviations of these data were computed. The results are shown in Table 6-13 along with the 
matrix porosity data and the wet and dry thermal conductivity results from the program 
GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-30 October 2004 
Table 6-12. Distributions Used by Program GENHSUMODELDATA 
Layer Type Parameter Distribution Start End Mean 
Standard 
Deviation 
Growth 
Rate 
welded fm normal   0.119 0.049  
welded ks (W/m K) normal   2.113 0.227  
welded .c exponential 0. 1. 0.905 0.092 10.479 
vitric fm exponential 0. 1 0.036 0.043 -27.778 
vitric ks (W/m K) uniform 0.35 1.26 0.805 0.263  
vitric .c constant 1. 1. 1.   
non-welded fm normal   0.385 0.132  
non-welded ks (W/m K) uniform 1.096 1.799 1.448 0.203  
non-welded .c uniform 0.621 1. 0.811 0.146  
Calico Hills fm normal   0.333 0.047  
Calico Hills ks (W/m K) uniform 1.31 2.271 1.791 0.278  
Calico Hills .c uniform 0.603 0.826 0.714 0.064  
Prow Pass 
non-welded 
fm normal   0.300 0.045  
Prow Pass 
non-welded 
ks (W/m K) uniform 1.096 1.799 1.448 0.203  
Prow Pass 
non-welded 
.c uniform 0.621 1. 0.811 0.146  
Prow Pass welded fm normal   0.209 0.056  
Prow Pass welded ks (W/m K) normal   2.113 0.227  
Prow Pass welded .c exponential 0. 1. 0.905 0.092 10.479 
Bullfrog non-welded fm normal   0.230 0.056  
Bullfrog Non-welded ks (W/m K) uniform 1.096 1.799 1.448 0.203 
Bullfrog Non-welded .c uniform 0.621 1. 0.811 0.146  
Bullfrog Welded fm normal   0.121 0.052  
Bullfrog Welded ks (W/m K) normal   2.113 0.227  
Bullfrog Welded .c exponential 0. 1. 0.905 0.092 10.479 
Tram Tuff 
Non-welded 
fm normal   0.332 0.061  
Tram Tuff 
Non-welded 
ks (W/m K) uniform 1.096 1.799 1.448 0.203  
Tram Tuff 
Non-welded 
.c uniform 0.621 1. 0.811 0.146  

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-31 October 2004 
Table 6-12. Distributions Used by Program GENHSUMODELDATA (Continued) 
LayerType Parameter Distribution Start End Mean 
Standard 
Deviation 
Growth 
Rate 
Tram Tuff Welded fm normal   0.209 0.056  
Tram Tuff Welded ks (W/m K) normal   2.113 0.227  
Tram Tuff Welded .c exponential 0. 1. 0.905 0.092 10.479 
NOTES: This table was assembled manually from visual inspection and output from Figure 6-2 to Figure 6-16 
generated by HISTPLT (STN: 10802-2.01-00 [DIRS 158223]). 
The standard deviation for a uniform distribution ranged from A to B is: 
(B-A)/(2 sqrt (3)) 
where: 
A = start value; B = end value; sqrt = square root operator. 
The mean for a uniform distribution is (A+B)/2. 
A and B are based on the known standard deviation and the mean. The standard deviation in the 
table is obtained using a division by sqrt(N-1). 
The input data are from: 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN GS000508312231.006 ([DIRS 153237] data table s00415_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file DATAQ.zip)), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002), 
DTN SNL01A05059301.007 ([DIRS 108980] data table s98424_003), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL02030193001.002 ([DIRS 120575] data tables s98484_001 and s98484_005), and 
Perry and Chilton (1973 [DIRS 104946], Table 3-320). 
Cells containing dashes () indicate that the data are not needed in the description of the 
distribution. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-32 October 2004 
Table 6-13. Thermal Conductivity Model Results 
Thermal Conductivity 
Dry Matrix Thermal 
Conductivity 
(W/m K) 
Wet Matrix Thermal 
Conductivity 
(W/m K) 
Matrix Porosity 
Dry Bulk 
Density 
(kg/m3) 
Geologic 
Framework 
Model 
Unit a 
# points mean std dev mean std dev # points mean std dev # points mean std dev 
Layer 
Characterization 
Crystal-Rich 
Tiva/Post-Tiva 17 1.30E0 2.31E-1 1.81E0 1.95E-1 608 1.19E-1 4.89E-2 1323 2.19E3 1.77E2 welded 
Tpcp 17 1.30E0 2.31E-1 1.81E0 1.95E-1 608 1.19E-1 4.89E-2 1323 2.19E3 1.77E2 welded 
TpcLD 17 1.30E0 2.31E-1 1.81E0 1.95E-1 608 1.19E-1 4.89E-2 1323 2.19E3 1.77E2 welded 
Tpcpv3 2 6.88E-1 2.29E-1 7.96E-1 2.51E-1 73 3.60E-2 4.25E-2 118 2.31E3 8.86E1 vitric 
Tpcpv2 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tpcpv1 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tpbt4 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Yucca 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tpbt3_dc 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Pah 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tpbt2 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tptrv3 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tptrv2 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tptrv1 2 6.88E-1 2.29E-1 7.96E-1 2.51E-1 73 3.60E-2 4.25E-2 118 2.31E3 8.86E1 vitric 
Tptrn 17 1.30E0 2.31E-1 1.81E0 1.95E-1 608 1.19E-1 4.89E-2 1323 2.19E3 1.77E2 welded 
Tptrl 17 1.30E0 2.31E-1 1.81E0 1.95E-1 608 1.19E-1 4.89E-2 1323 2.19E3 1.77E2 welded 
Tptf 17 1.30E0 2.31E-1 1.81E0 1.95E-1 608 1.19E-1 4.89E-2 1323 2.19E3 1.77E2 welded 
Tptpv3 2 6.88E-1 2.29E-1 7.96E-1 2.51E-1 73 3.60E-2 4.25E-2 118 2.31E3 8.86E1 vitric 
Tptpv2 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tptpv1 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Tpbt1 9 4.90E-1 1.58E-1 1.06E0 1.46E-1 351 3.85E-1 1.32E-1 594 1.46E3 3.37E2 non-welded 
Calico 5 5.95E-1 1.12E-1 1.26E0 1.41E-1 258 3.33E-1 4.68E-2 611 1.67E3 1.57E2 calico 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-33 October 2004 
Table 6-13. Thermal Conductivity Model Results (Continued) 
Thermal Conductivity 
Dry Matrix Thermal 
Conductivity 
(W/m K) 
Wet Matrix Thermal 
Conductivity 
(W/m K) 
Matrix Porosity 
Dry Bulk 
Density 
(kg/m3) 
Geologic 
Framework 
Model 
Unit a 
# points mean std dev mean std dev # points mean std dev # points mean std dev 
Layer 
Characterization 
Calicobt 5 5.95E-1 1.12E-1 1.26E0 1.41E-1 258 3.33E-1 4.68E-2 611 1.67E3 1.57E2 calico 
Prowuv 9 5.69E-1 1.04E-1 1.13E0 1.17E-1 421 3.00E-1 4.46E-2 508 1.79E3 1.17E2 non-welded 
Prowuc 9 5.69E-1 1.04E-1 1.13E0 1.17E-1 421 3.00E-1 4.46E-2 508 1.79E3 1.17E2 non-welded 
Prowmd 17 1.06E0 1.83E-1 1.63E0 1.68E-1 55 2.09E-1 5.61E-2 81 2.07E3 1.39E2 welded 
Prowlc 9 5.69E-1 1.04E-1 1.13E0 1.17E-1 421 3.00E-1 4.46E-2 508 1.79E3 1.17E2 non-welded 
Prowlv 9 5.69E-1 1.04E-1 1.13E0 1.17E-1 421 3.00E-1 4.46E-2 508 1.79E3 1.17E2 non-welded 
Prowbt 9 5.69E-1 1.04E-1 1.13E0 1.17E-1 421 3.00E-1 4.46E-2 508 1.79E3 1.17E2 non-welded 
Bullfroguv 9 6.58E-1 1.30E-1 1.19E0 1.38E-1 54 2.30E-1 5.56E-2 68 1.88E3 1.67E2 non-welded 
Bullfroguc 9 6.58E-1 1.30E-1 1.19E0 1.38E-1 54 2.30E-1 5.56E-2 68 1.88E3 1.67E2 non-welded 
Bullfrogmd 17 1.30E0 2.39E-1 1.81E0 1.98E-1 87 1.21E-1 5.22E-2 92 2.26E3 1.38E2 welded 
Bullfroglc 9 6.58E-1 1.30E-1 1.19E0 1.38E-1 54 2.30E-1 5.56E-2 68 1.88E3 1.67E2 non-welded 
Bullfroglv 9 6.58E-1 1.30E-1 1.19E0 1.38E-1 54 2.30E-1 5.56E-2 68 1.88E3 1.67E2 non-welded 
Bullfrogbt 9 6.58E-1 1.30E-1 1.19E0 1.38E-1 54 2.30E-1 5.56E-2 68 1.88E3 1.67E2 non-welded 
Tramuv 9 5.35E-1 1.06E-1 1.10E0 1.16E-1 26 3.32E-1 6.05E-2 37 1.76E3 1.95E2 non-welded 
Tramuc 9 5.35E-1 1.06E-1 1.10E0 1.16E-1 26 3.32E-1 6.05E-2 37 1.76E3 1.95E2 non-welded 
Trammd 17 1.06E0 1.83E-1 1.63E0 1.68E-1 55 2.09E-1 5.61E-2 2 2.14E3 7.78E1 welded 
Tramlc 9 5.35E-1 1.06E-1 1.10E0 1.16E-1 26 3.32E-1 6.05E-2 37 1.76E3 1.95E2 non-welded 
Tramlv 9 5.35E-1 1.06E-1 1.10E0 1.16E-1 26 3.32E-1 6.05E-2 37 1.76E3 1.95E2 non-welded 
Trambt 9 5.35E-1 1.06E-1 1.10E0 1.16E-1 26 3.32E-1 6.05E-2 37 1.76E3 1.95E2 non-welded 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-34 October 2004 
Table 6-13. Thermal Conductivity Model Results (Continued) 
Sources: 
DTN MO0004QGFMPICK.000 ([DIRS 152554] data table s00214_001), 
DTN GS000508312231.006 ([DIRS 153237] data table s00415_001), 
DTN MO0109HYMXPROP.001 ([DIRS 155989] data table s01144_001 (file 
DATAQ.zip)), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002), 
DTN SNL01A05059301.007 ([DIRS 108980] data tables s98424_001 and 
s98424_003), 
DTN SNF40060298001.001 ([DIRS 107372] data table s98430_001), 
DTN SNL02030193001.002 ([DIRS 120575] data tables s98484_001, 
s98484_002, s98484_004, and s98484_005), 
DTN GS000408312231.004 ([DIRS 149582] data table s00276_001), 
DTN GS950308312231.002 ([DIRS 108990] data table s96015_001), 
DTN GS950408312231.004 ([DIRS 108986] data table s96021_001), 
DTN GS940508312231.006 ([DIRS 107149] data table s96024_003), 
DTN GS930108312231.006 ([DIRS 108997] data tables s96025_001 and 
s96025_002), 
DTN GS920508312231.012 ([DIRS 109001] data tables s96026_001, 
DTN GS940408312231.004 ([DIRS 109000] data table s96027_001), 
DTN GS951108312231.009 ([DIRS 108984] data table s96037_001), 
DTN GS951108312231.010 ([DIRS 108983] data table s96046_001), 
DTN GS951108312231.011 ([DIRS 108992] data table s96049_001), 
DTN GS960808312231.004 ([DIRS 108985] data table s97058_001), 
DTN GS920408312314.011 ([DIRS 129660] data table s97135_002), 
DTN GS930408312132.007 ([DIRS 129625] data table s97276_001), 
DTN GS980708312242.010 ([DIRS 106752] data table s98248_004), 
DTN GS980808312242.014 ([DIRS 106748] data table s98285_001), 
DTN SNL02030193001.004 ([DIRS 108415] data tables s98485_001 and 
s98485_003), 
DTN SNL02030193001.008 ([DIRS 120597] data table s98486_001), 
DTN SNL02030193001.003 ([DIRS 120578] data tables s99100_001 and 
s99100_004), 
DTN SNL02030193001.006 ([DIRS 120579] data table s99101_001 and 
s99101_004), 
DTN SNL02030193001.013 ([DIRS 120614] data table s99104_001 and 
S99104_004) b, 
DTN SNL02030193001.005 ([DIRS 122545] data table s99105_001 and 
S99105_004) c, 
DTN SNL02030193001.007 ([DIRS 120582] data table s99106_001), 
DTN SNL02030193001.014 ([DIRS 109609] data tables s99107_001 and 
s99107_004), 
DTN SNL02030193001.015 ([DIRS 120617] data table s99108_001), 
DTN SNL02030193001.009 ([DIRS 109614] data table s99109_001 and 
s99109_002) d, 
DTN SNL02030193001.012 ([DIRS 108416] data table s99110_001), 
DTN SNL02030193001.022 ([DIRS 109613] data tables s99111_001 and 
s99111_002), 
DTN SNL02030193001.016 ([DIRS 120619] data table s99112_001), 
DTN SNL02030193001.017 ([DIRS 109610] data table s99113_001), 
DTN SNL02030193001.018 ([DIRS 109611] data table s99114_001), 
DTN SNL02030193001.019 ([DIRS 108431] data tables s99115_001 and 
s99115_002), 
DTN SNL02030193001.020 ([DIRS 108432] data tables s99116_001 and 
s99116_004), 
DTN SNL02030193001.021 ([DIRS 108433] data table s99117_001), and 
DTN SNL01A05059301.002 ([DIRS 150042] data table s99435_001). 
NOTE: This table is included in output DTN SN0303T0503102.008 (file: TC_CD\Outputs\Genhsumodeldata\finalstats). 
a Model Unit corresponds to the Geologic Framework Model Unit listed in Table U-1. 
b Data table S99104_004 was excluded because the data are for an alluvium layer not considered in this report. 
c Data table S99105_004 was excluded because the lithostratigraphy correlation data (DTN MO0004QGFMPICK.000 [DIRS 152554]) are not available for UE- 
25 NRG #3. 
d Data table S99109_001 was excluded because the data are for the repository layers not considered in this report. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-35 October 2004 
Table 6-13 represents the numerical output for the thermal conductivity model and is available 
with some additional notes as Product Output DTN SN0303T0503102.008. The measurement 
uncertainties described in Section 6.2 are all small compared to the 95 percentile ranges (two or 
more standard deviations, depending on the number of measurements) of the model results in 
Table 6-13. The standard-deviation range for Tram Tuff non-welded wet thermal conductivity is 
approximately 11 percent of the mean, or 0.116. This is the smallest uncertainty for any thermal 
conductivity model value. The 5-percent measurement uncertainty, taken to have 95-percent 
confidence, is 2.5 percent of the mean, or an absolute value of 0.028. The combined standard 
deviation is found by taking the square root of the sum of the variances, giving 0.119. The 
thermal conductivity measurement uncertainty causes a negligible change in the standard 
deviation and, therefore, can be ignored. 
The porosity measurement uncertainty is approximately 5 percent (absolute) for porosities less 
than 0.11. Only the vitric porosity falls in this range. The standard deviation of the vitric mean 
porosity is 0.0425. The 5-percent absolute measurement uncertainty corresponds to a 0.025 
standard deviation. The combined standard deviation is 0.0493 (from sqrt(0.04252+0.0252)), 
which is close enough to the numerical standard deviation to ignore the measurement 
uncertainty. For porosities greater than 0.11, the measurement uncertainty is approximately 
9 percent of the measured value. The smallest standard deviation is 0.0446 for Prow Pass nonwelded. 
The measurement standard deviation would be approximately 0.0135 (absolute), which 
is negligible compared to the standard deviation. 
6.7 DRY BULK DENSITY ANALYSIS 
The program REFORMAT (STN 10907-2.0-00 [DIRS 162673]) uses the control input file in 
Appendix K to convert the 48 dry bulk density data tables into one table of 5,030 values with 
lithostratigraphy appended. In tables that included both 105C oven and relative humidity oven 
measurements, the relative humidity measurements were used. The control input file in 
Appendix L enables REFORMAT (STN 10907-2.0-00 [DIRS 162673]) to rewrite the data into 
tables for welded, non-welded, vitric, Calico Hills, Prow Pass non-welded, Prow Pass welded, 
Bullfrog non-welded, Bullfrog welded, Tram Tuff non-welded, and Tram Tuff welded units. 
This analysis includes all available qualified, verified dry bulk density data available as of 
February 13, 2003. 
Mean and standard deviations for the 10 categories are obtained from the program HISTPLT 
(STN 10802-2.01-00 [DIRS 158223]). The results are converted from centimeter-gram-second 
units to the International System of Units and the standard deviations are converted to 
sample-mean standard deviations. The results are shown in Table 6-13. The Tram Tuff welded 
value is based on two measurements and should be considered less reliable than the other values. 
The remaining units consist of from 37 to 1,323 values. The dry bulk density data are averaged 
from available data, and are not a model; therefore, it does not require a separate validation. 
The standard deviations for dry bulk density (Table 6-13) range from 4 to 23 percent of the 
means. Because the measurement uncertainty (Section 6.2) is approximately 0.4 percent, the 
measurement uncertainty is negligible in comparison, and can be ignored. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 6-36 October 2004 
6.8 IMPACT OF THE CHOICE OF DISTRIBUTION TYPE ON THERMAL 
CONDUCTIVITY VALUES 
GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) computes 15,625 values of wet 
and dry thermal conductivity from 25 values from the matrix porosity (fm) distribution, 
25 values from the solid thermal conductivity (ks) distribution, and 25 values from the 
distribution of the geometric parameter (.c). The averages of the 15,625 wet and dry thermal 
conductivity values are the value used as the model output. The porosity distributions 
(Figure 6-8 to Figure 6-16) are based on 26 to 603 data points, and the choice of distribution is 
much less subject to interpretation than the choice of the non-welded ks (Figure 6-4), non-welded 
.c (Figure 6-5), and Calico Hills .c (Figure 6-7) distributions. The uniform, exponential, and 
normal distributions used by GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) are 
each built from the mean and standard deviation of the experimental data, so each distribution 
type will generate 25 values with the same range and mean, but the spacing of the values will 
differ somewhat. The 25 data points on each of the porosity and .c distributions remain 
unchanged. For this reason it is reasonable that the averages of the 15,625 wet and dry thermal 
conductivity values will not differ significantly. 
Consider the non-welded solid thermal conductivity distribution from Figure 6-4. A uniform 
distribution was used to approximate the distribution, and GENHSUMODELDATA 
(STN 10905-1.0-00 [DIRS 162671]) gave a dry thermal conductivity mean of 0.4902 with a 
standard deviation of 0.1578 and a wet thermal conductivity mean of 1.0587 with a standard 
deviation of 0.1459. If a normal distribution is used for ks, GENHSUMODELDATA 
(STN 10905-1.0-00 [DIRS 162671]) gives a dry thermal conductivity mean of 0.4902 with a 
standard deviation of 0.1572 and a wet thermal conductivity mean of 1.0588 with a standard 
deviation of 0.1445. The changes in the means, 0 and 0.0001, are negligible. The changes in the 
standard deviations, 0.0006 and 0.0014, are less than 1 percent relative error, and also are 
negligible. 
Now consider the non-welded .c distribution from Figure 6-5. If normal distributions are used 
instead of uniform distributions for both ks and .c, GENHSUMODELDATA (STN 10905-1.0-00 
[DIRS 162671]) gives a dry thermal conductivity mean of 0.4837 with a standard deviation of 
0.1597 and a wet thermal conductivity mean of 1.0587 with a standard deviation of 0.1445. The 
changes in the means, 0.0065 and 0.0, and the changes in the standard deviations, 0.0019 and 
0.0014, are all less than 1.5-percent relative error, and are therefore negligible. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-1 October 2004 
7. VALIDATION 
7.1 CONFIDENCE BUILDING DURING MODEL DEVELOPMENT TO ESTABLISH 
SCIENTIFIC BASIS AND ACCURACY FOR INTENDED USE 
Section 2.2.2.2 of TWP-MGR-PA-000019 REV 00 ICN 1 (BSC 2004 [DIRS 171708]) identifies 
this Thermal Conductivity of Non-Repository Lithostratigraphic Layers report as requiring 
Level I model validation per AP-2.27Q. AP-2.27Q specifies the following steps for Confidence 
Building During Model Development: 
The development of the model should be documented in accordance with the 
requirements of Section 5.3.2(b) of AP-SIII.10Q. 
The development of the Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
report has been conducted in accordance with 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 model are obtained from controlled sources as described in Section 4. Qualified 
matrix porosity and thermal conductivity data that were previously verified are used to generate 
the Hsu model for thermal conductivity for the nonrepository layers of the Yucca Mountain site. 
The SEP parameters porosity and thermal conductivity were searched for all qualified data 
tables that have been verified. SEP tables containing data exclusively for the repository layers or 
for materials other than geologic layers (e.g., titanium or grout) are not considered because the 
scope of the model is limited to nonrepository geologic layers of Yucca Mountain. Only data 
tables that included lithostratigraphy and depth, and either borehole ID or sample ID (because 
one of these items is necessary to determine the lithostratigraphic layer), were retained for 
consideration. Porosity data other than matrix porosity data were excluded from consideration 
because the Hsu model requires matrix porosity and wet and dry thermal conductivity as inputs. 
Matrix porosity data are obtained from laboratory core measurements. Data sources are 
described in greater detail in Section 4 tables. The selection of site-specific data provides 
additional confidence that the thermal conductivity model provides results that are appropriate 
for the intended use. Therefore, this criterion is considered to be met. 
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)]. 
The Thermal Conductivity of Non-Repository Lithostratigraphic Layers is a static model, and 
therefore discussion of run convergences or non-convergences is not generally applicable. The 
use of site-specific data for inputs to the model and consistent use of the GFM stratigraphy builds 
confidence in the model. Discussion about initial boundary conditions and non-convergence 
runs is not relevant for this model report. Thus, this requirement is considered satisfied. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-2 October 2004 
3. Discussion of the impacts of uncertainties to the model results including how the 
model results represent the range of possible outcomes consistent with important 
uncertainties [(AP-SIII.10 Q, 5.3.2(b)(3) and AP-2.27Q, Attachment 3, Level 1 (d) and 
(f)]. 
Section 6.2 and Appendix A describe the uncertainties associated with data measurement. 
Section 6.4 describes distributions of gamma_c and solid thermal conductivity for welded, 
non-welded, vitric, and calico rock types. 
Section 6.5 describes distributions of matrix porosity, for welded, non welded, vitric, Calico 
Hills, Prow Pass, Bullfrog, and Tram Tuff units. 
Section 6.8 provides a discusion of the impacts of the choice of distribution type on model 
results. 
Appendix S provides a detailed uncertainty analysis of the Thermal Conductivity on the Non 
Repository Lithostratigraphic Layers, to assess the significance of the nonrepository horizon 
units on the repository temperature over extended periods of time. Regression and error analyses 
presented in Section 7 indicate that model results represent the range of possible outcomes. 
A summary discussion on uncertainties is given in Section 8.2.2 and Section 8.2.3. 
4. Formulation of defensible assumptions and simplifications [AP-2.27Q, Attachment 3, 
Level I (b)]. 
Discussions of assumptions and simplifications are provided in Section 5 and Section 6.1. 
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 evaluation of alternate conceptual 
and mathematical models, and the selection of the Hsu model described in Section 6.1. 
Appendix S provides additional details regarding the mathematical development. 
7.2 CONFIDENCE BUILDING AFTER MODEL DEVELOPMENT TO SUPPORT 
THE SCIENTIFIC BASIS OF THE MODEL 
The model validation involves two steps. First, it is shown that the porosity values used in the 
model development represent all remaining matrix porosity data (Assumption 1 in Section 5). 
The normalized differences in the averages are compared to the 95-percent confidence levels on 
the normal distribution. Note that the TWP specifies the 98-percent confidence level, which is 
less stringent than the 95-percent confidence level. Second, the model wet and dry thermal 
conductivity values are compared to the averages from all remaining qualified thermal 
conductivity data, in accordance with the TWP (BSC 2004 [DIRS 171708], Section 2.2.2). The 
normalized differences in the averages are compared to the 95- or 98-percent confidence levels 
on Students t-distribution because of the low numbers of data points. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-3 October 2004 
For estimating the properties for the Prow Pass welded, Tram Tuff non-welded, and Tram Tuff 
welded layers, the model regression relationships based upon matrix porosity and saturation near 
the repository horizon can be used and is considered a valid model for these units because: 
 These welded and nonwelded units are similar in geologic structure (matrix porosity) 
and mineralogy to the welded and nonwelded units near the repository for which data 
are available. 
 As noted in Appendix S, these units that are remote to the repository do not provide a 
significant contribution to uncertainty in predicting repository driftwall temperatures on 
the basis of thermal properties of the rock mass. 
Estimates of these values are obtained by linear regression in accordance with the TWP (BSC 
2004 [DIRS 171708], Section 2.1.2) from the remaining seven layers using functions of matrix 
porosity and dry bulk density as variables. 
The TWP (BSC 2004 [DIRS 171708], Section 2.2.2.2) classifies this report as Level I in terms of 
model importance and validation. The model does not provide any direct input to the total 
system performance assessment model. 
The model development is done using most of the qualified, verified data for matrix porosity and 
thermal conductivity for Boreholes USW SD-7, USW SD-9, USW SD-12, UE-25 NRG #4, 
UE-25 NRG #5, USW NRG-6, and USW NRG-7. These inputs are identified in Table 4-3 and 
Table 4-4. All of the remaining qualified, verified data for matrix porosity and thermal 
conductivity are used for data for model validation. These inputs are identified in Table 4-6 and 
Table 4-7. There are approximately 150 thermal conductivity values and approximately 
10,000 porosity values. If the model were built using approximately 30 measurements, or more, 
for each of fm, .c, and ks, then the model and validation means could be compared using the 
normalized difference of the means ((1-2)/s) for a normal distribution, where s is the standard 
deviation. However, there are 17 or fewer measurements for model thermal conductivity in each 
geologic group and fewer than 30 measurements for validation of thermal conductivity in most 
of the geologic groups, so it is more appropriate to do a comparison of means using the Students 
t-distribution. To meet the specified validation criteria, the magnitude of the normalized 
difference of the means must be smaller than the Students coefficient for the 0.975 percentile 
point for 95 percent significance or the 0.99 percentile point for 98 percent significance at the 
appropriate number of degrees of freedom to assess the significance of a difference in means. 
When working with a combination of two distributions, the formulas are usually expressed in 
terms of the sum of squared deviations S2, where the sum of squared deviations is related to the 
variance s2 by S 2 = N s2. The normalized difference of the means t is given by Bulmer (1979 
[DIRS 111961], p. 151): 
2 1 combined 
2 1 
N / 1 N / 1 s 
) ( 
t 
+ 
- 
= 
  
(Eq. 7-1) 
The combined variance comes from the sum-of-variances relation (Bulmer 1979 [DIRS 111961], 
p. 150): 
) 2 N N ( 
) S S ( s 
2 1 
2 
2 
2 
1 2
combined - + 
+ 
= (Eq. 7-2) 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-4 October 2004 
where n1 and n2 are the counts and S1 and S2 are the sums of squared deviations of the model and 
validation data. 
Model validation is accomplished by using dry bulk density data listed in Table 4-5, matrix 
porosity data listed in Table 4-6, and thermal conductivity data listed in Table 4-7. 
7.2.1 Porosity Validation 
The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input control file in Appendix M of this 
report collects the porosity data from the 57 SEP data tables listed in Table 4-6, and puts the data 
into a single file. The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input control file in 
Appendix N separates the porosity data from this one file into 10 files, one for each geologic 
group. Figure 7-1 to Figure 7-10 show histograms of the validation porosities generated by 
HISTPLT (STN 10802-2.01-00 [DIRS 158223]). The numbers of points, means, and standard 
deviations shown in Figures 7-1 to 7-10 provide the data for the columns headed N2, 2, and s2 in 
Table 7-1. Because the combined number of model and validation data points is at least 57, the 
comparison of the means can be done using the normal distribution, where the normalized 
difference of the means is (1-2)/s. The critical normalized difference in the means is 
approximately 1.96 at the 95-percent confidence level. Table 7-1 shows that all the normalized 
differences in mean values (column t in Table 7-1) are 0.749 or smaller in magnitude, so the 
model and validation mean porosities are statistically equivalent; therefore, in terms of porosity, 
the model meets the 98-percent confidence criteria (BSC 2004 [DIRS 171708]) which is less 
stringent than the 95-percent interval shown above, and is validated for its intended use. 
Because the means are always within one combined standard deviation (scombined) of each other, 
this result is not unexpected. 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.040 
0.080 
0.120 
0.160 
Welded porosity for validation 
Number of Data 3677 
mean 0.1284 
std. dev. 0.0687 
coef. of var 0.5351 
maximum 0.5280 
upper quartile 0.1650 
median 0.1260 
lower quartile 0.0720 
minimum 0.0100 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-1. Validation Welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-5 October 2004 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.100 
0.200 
0.300 
Vitric porosity for validation 
Number of Data 374 
mean 0.0377 
std. dev. 0.0406 
coef. of var 1.0758 
maximum 0.3400 
upper quartile 0.0460 
median 0.0255 
lower quartile 0.0150 
minimum 0.0040 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-2. Validation Vitric Matrix Porosity 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.0000 
0.0100 
0.0200 
0.0300 
0.0400 
0.0500 
0.0600 
0.0700 
Nonwelded porosity for validation 
Number of Data 1990 
mean 0.3793 
std. dev. 0.1377 
coef. of var 0.3631 
maximum 0.6690 
upper quartile 0.4930 
median 0.4000 
lower quartile 0.2840 
minimum 0.0170 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-3. Validation Non-welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-6 October 2004 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.040 
0.080 
0.120 
Calico porosity for validation 
Number of Data 1723 
mean 0.2822 
std. dev. 0.0700 
coef. of var 0.2481 
maximum 0.4700 
upper quartile 0.3370 
median 0.2870 
lower quartile 0.2360 
minimum 0.0220 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-4. Validation Calico Hills Matrix Porosity 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.040 
0.080 
0.120 
Prownonwelded porosity for validation 
Number of Data 1464 
mean 0.2666 
std. dev. 0.0660 
coef. of var 0.2475 
maximum 0.5380 
upper quartile 0.3140 
median 0.2750 
lower quartile 0.2240 
minimum 0.0590 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-5. Validation Prow Pass Non-welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-7 October 2004 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.040 
0.080 
0.120 
Prowwelded porosity for validation 
Number of Data 274 
mean 0.1942 
std. dev. 0.0658 
coef. of var 0.3385 
maximum 0.3330 
upper quartile 0.2400 
median 0.1980 
lower quartile 0.1430 
minimum 0.0660 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-6. Validation Prow Pass Welded Matrix Porosity 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.040 
0.080 
0.120 
0.160 
Bullfrog nonwelded porosity for validati 
Number of Data 192 
mean 0.2204 
std. dev. 0.0719 
coef. of var 0.3264 
maximum 0.3800 
upper quartile 0.2735 
median 0.2010 
lower quartile 0.1580 
minimum 0.1190 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-7. Validation Bullfrog Non-welded Matrix Porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-8 October 2004 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.100 
0.200 
0.300 Bullfrog welded porosity for validation 
Number of Data 272 
mean 0.1154 
std. dev. 0.0529 
coef. of var 0.4588 
maximum 0.3180 
upper quartile 0.1290 
median 0.0990 
lower quartile 0.0810 
minimum 0.0520 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-8. Validation Bullfrog Welded Matrix Porosity 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.040 
0.080 
0.120 
Tram nonwelded porosity for validation 
Number of Data 98 
mean 0.2883 
std. dev. 0.0642 
coef. of var 0.2229 
maximum 0.4420 
upper quartile 0.3380 
median 0.2860 
lower quartile 0.2400 
minimum 0.1660 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-9. Validation Tram Tuff Non-welded Matrix Porosity 

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MDL-NBS-GS-000006 REV 01 7-9 October 2004 
Frequency 
validation porosity 
0.00 0.20 0.40 0.60 0.80 1.00 
0.000 
0.100 
0.200 
0.300 
0.400 
0.500 
Tram welded porosity for validation 
Number of Data 2 
mean 0.1840 
std. dev. 0.0190 
coef. of var 0.1033 
maximum 0.2030 
upper quartile 0.2030 
median 0.1840 
lower quartile 0.1650 
minimum 0.1650 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-10. Validation Tram Tuff Welded Matrix Porosity 
Table 7-1. Validation of the Representative Borehole Assumption for Porosity 
Model Validation 
Layer N1 1 s1 S1 N2 2 s2 S2 scombined t 
welded 608 0.119 0.049 1.206 3677 0.128 0.069 4.166 0.066 -0.143 
vitric 73 0.036 0.042 0.361 374 0.038 0.041 0.785 0.041 -0.042 
non-welded 351 0.385 0.132 2.473 1990 0.379 0.138 6.143 0.137 0.039 
Calico Hills 258 0.333 0.047 0.750 1723 0.282 0.070 2.906 0.067 0.749 
Prow Pass 
non-welded 
421 0.300 0.045 0.913 1464 0.267 0.066 2.525 0.062 0.541 
Prow Pass 
welded 
55 0.209 0.056 0.412 274 0.194 0.066 1.089 0.064 0.234 
Bullfrog 
non-welded 
54 0.230 0.055 0.405 192 0.220 0.072 0.996 0.069 0.137 
Bullfrog welded 87 0.121 0.052 0.484 272 0.115 0.053 0.872 0.053 0.110 
Tram Tuff 
non-welded 
26 0.332 0.059 0.302 98 0.288 0.064 0.636 0.064 0.683 
Tram Tuff 
welded 
55 0.209 0.056 0.412 2 0.184 0.019 0.027 0.056 0.454 
NOTES: This table was generated by using data from Table 6-13, and Figure 7-1 to Figure 7-10. 
Column scombined and column t were generated through the use of the equation for normal 
distribution t = (1-2)/scombined and Equation 7-2. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-10 October 2004 
7.2.2 Regression Analysis of Validation Thermal Conductivity 
The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input control file in Appendix O collects 
the thermal conductivity data not used for model development from three SEP data tables 
(DTN SN0011T0571897.014 ([DIRS 154449] data table s00441_001), 
DTN SNL01A05059301.005 ([DIRS 109002] data table s96370_001), and 
DTN SNL22100196001.006 ([DIRS 158213] data table s98169_002)), and puts the data into one 
file. The REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input control file in Appendix P 
separates the thermal conductivity data from this one file into 20 files, wet and dry data for each 
of the ten geologic groups. Six of these files have no data in them. Figure 7-11 to Figure 7-24 
show histograms of the validation dry and wet thermal conductivities generated by HISTPLT 
(STN 10802-2.01-00 [DIRS 158223]). 
Figure 7-11 to Figure 7-24 provide means and standard deviations for wet and dry thermal 
conductivity for seven of the ten layers in the model. There are no model validation thermal 
conductivity values for the Prow Pass welded rock unit, the Tram Tuff welded rock unit, or the 
Tram Tuff non-welded rock unit. Because average matrix porosity values and average dry bulk 
density values were available for these rock units, linear regression was used to develop fits to 
the values for model validation dry and wet thermal conductivities as functions of these 
parameters. The Hsu-model equations are not useful in this analysis, because they include a 
geometric factor that is not available for the model validation data. The form of the regression 
equation was arrived at in the following manner. A relationship was found between thermal 
conductivity, porosity, and bulk density using a series of regression analyses. 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-11. Validation Welded Dry Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-11 October 2004 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-12. Validation Vitric Dry Thermal Conductivity 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-13. Validation Non-welded Dry Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-12 October 2004 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-14. Validation Calico Hills Dry Thermal Conductivity 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-15. Validation Prow Pass Non-welded Dry Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-13 October 2004 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-16. Validation Bullfrog Non-welded Dry Thermal Conductivity 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-17. Validation Bullfrog Welded Dry Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-14 October 2004 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-18. Validation Welded Wet Thermal Conductivity 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-19. Validation Vitric Wet Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-15 October 2004 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-20. Validation Non-welded Wet Thermal Conductivity 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-21. Validation Calico Hills Wet Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-16 October 2004 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-22. Validation Prow Non-welded Wet Thermal Conductivity 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-23. Validation Bullfrog Non-welded Wet Thermal Conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-17 October 2004 
NOTE: This figure was generated by HISTPLT (STN 10802-2.01-00 [DIRS 158223]), using data in Product Output 
DTN SN0307T0503102.009. 
Figure 7-24. Validation Bullfrog Welded Wet Thermal Conductivity 
First, a regression was performed to determine the best exponent E for a fit of the form: 
k = A + fm
E (Eq. 7-3) 
where: 
k = thermal conductivity 
fm = matrix porosity. 
The regression gave an exponent E approximately equal to -1. Using E = -1, a second 
regression was done on the form k = A + B/fm + C fm
F. The regression gave a value of 
approximately -2 for the exponent F. Next, using F = -2, two regressions were performed to 
determine whether adding a bulk density or a grain density term would improve the fit. The 
grain density term gave a better fit, but because bulk density data are more readily available than 
grain density data, the grain density term was written as db/(1-fm), where db is the bulk density. 
Because the regression form 
k = A + B/fm + C/fm
2 + D db/(1-fm) (Eq. 7-4) 
gave fits that were good to within 10 percent of most data points, it was selected as the final 
form. Thermal conductivity data were fitted to the form (Equation 7-4) by linear regression on 
columns of data for 1/fm, 1/fm
2, and db/(1-fm). Here, fm is the matrix porosity and db is the dry 
bulk density. The dry thermal conductivity (kd) values give the fit 
kd = -1.651 + 0.1802/fm - 4.726E-3/fm
2 + 6.922E-4 db/(1-fm) (Eq. 7-5) 

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MDL-NBS-GS-000006 REV 01 7-18 October 2004 
and the wet thermal conductivity (kw) values give the fit 
kw = -1.207 + 0.1302/fm - 3.323E-3/fm
2 + 8.264E-4 db/(1-fm), (Eq. 7-6) 
where: 
db is in kg/m3. 
Table 7-2 shows the inputs to and predictions from the dry thermal conductivity regression and 
Table 7-3 shows the inputs to and predictions from the wet thermal conductivity regression. The 
relative errors of the fits are shown in the column labeled relerr (relative error). The regression 
data analysis tool in Excel performs the regression. The Excel spreadsheets for the dry and wet 
regressions are shown in Appendix Q and Appendix R. 
Table 7-2. Regression Fit of Validation Dry Thermal Conductivity 
kd 
(W/m K) 1/f 1/f2 db/(1-f) 
kd fit 
(W/m K) relerr layer 
Inputs: 
1.132 7.812 61.04 2511. 1.207 0.066 welded 
1.480 26.32 692.5 2401. 1.481 0.001 vitric 
0.417 2.639 6.962 2351. 0.419 0.004 non-welded 
0.577 3.546 12.57 2326. 0.538 -0.067 Calico Hills 
0.652 3.745 14.03 2442. 0.648 -0.006 Prow Pass non-welded 
0.700 4.545 20.66 2410. 0.739 0.055 Bullfrog non-welded 
1.400 8.696 75.61 2554. 1.326 -0.053 Bullfrog welded 
Root-Mean-Square Error = 0.046 
Coefficients: A= -1.651 B= 0.1802 C= -0.004726 D= 0.0006922 
Predictions: 
5.155 26.57 2568 0.930  Prow Pass welded 
3.472 12.06 2472. 0.629  Tram Tuff non-welded 
5.435 29.54 2623. 1.004  Tram Tuff welded 
NOTE: This table is from the Excel spreadsheet in Appendix Q. 
relerr=relative error 
Table 7-3. Regression Fit of Validation Wet Thermal Conductivity 
kw 
(W/m K) 1/f 1/f2 db/(1-f) 
kw fit 
(W/m K) relerr layer 
Inputs: 
1.593 7.812 61.04 2511. 1.683 0.056 welded 
1.903 26.32 692.5 2401. 1.903 0.000 vitric 
1.026 2.639 6.962 2351. 1.056 0.029 non-welded 
1.162 3.546 12.57 2326. 1.135 -0.023 Calico Hills 
1.258 3.745 14.03 2442. 1.252 -0.005 Prow Pass non-welded 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-19 October 2004 
Table 7-3. Regression Fit of Validation Wet Thermal Conductivity (Continued) 
kw 
(W/m K) 1/f 1/f2 db/(1-f) 
kw fit 
(W/m K) relerr layer 
Inputs: 
1.330 4.545 20.66 2410. 1.308 -0.017 Bullfrog non-welded 
1.850 8.696 75.61 2554. 1.784 -0.035 Bullfrog welded 
Root-Mean-Square Error = 0.030 
Coefficients: A= -1.207 B= 0.1302 C= -0.003323 D= 0.0008264 
Predictions: 
5.155 26.57 2568. 1.498  Prow Pass welded 
3.472 12.06 2472. 1.248  Tram Tuff non-welded 
5.435 29.54 2623. 1.570  Tram Tuff welded 
NOTE: This table is from the Excel spreadsheet shown in Appendix R. 
relerr=relative error 
The maximum relative error is 0.067 for kd and 0.056 for kw. The root-mean-square errors are 
approximately 0.046 for kd and 0.030 for kw. These fits give the thermal conductivity values 
used in Table 7-5 and Table 7-6 for Prow Pass welded, Tram Tuff non-welded, and Tram Tuff 
welded. Note that in the comparison of the t statistic (Equation 7-1) based upon the normalized 
difference in the means, the combined variance is used to calculate the standard deviations from 
the two distributions. Because the number of data points is limited to seven (one for each layer 
of the original data), the standard deviation was set to zero. This has the effect of increasing the 
t statistic in Equation 7-1 by reducing S in Equation 7-2, and provides a more severe Student t 
test statistic for accepting the test hypothesis (that the means are derived from the same 
distribution) than would be the case if the standard deviation was set to a nonzero value. 
To reproduce the computer calculations, Excel spreadsheets drytcregression.xls and 
wettcregression.xls are prepared in subdirectory Outputs\TCRegression using the inputs parts of 
the data in Table 7-2 and Table 7-3. The Tools menu is selected in Excel, then the Data Analysis 
menu is selected, followed by the Regression option. The input Y range is column B of the 
spreadsheet ($B$2:$B$8), the thermal conductivity values. The input X range is cells E2 
through G8. Excel performs the regression and puts the resulting coefficients in the Coefficients 
column of a worksheet. The Intercept line is the constant A in Equation 7-4. The next three 
rows give the B, C, and D coefficients. 
7.2.3 Validation of the Thermal Conductivity Part of the Model 
All qualified, verified thermal conductivity data not used in the model development are used to 
validate the thermal conductivity model. The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) 
input control file in Appendix O collects the thermal conductivity data from two SEP data tables, 
and puts the data into a single file. The REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input 
control file in Appendix P separates the thermal conductivity data from this one file into 10 files, 
one for each geologic rock type. The Students t coefficients (Beyer 1987 [DIRS 103805]) for 
one-sided 0.975 confidence (0.025 out of confidence on each side, or 95-percent confidence) and 
one-sided 0.99 confidence (0.01 out of confidence on each side, or 98-percent confidence) values 
are shown in Table 7-4 for the number of degrees of freedom v = N1 + N2 - 2. Because there 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-20 October 2004 
are only two endpoint model values for the solid thermal conductivity of the vitric rock types, the 
number of data values for N1 was set at two. 
The numbers of points, means, and standard deviations shown in Figures 7-11 to 7-17 provide 
dry thermal conductivity data for the columns headed N2, 2, and s2 in Table 7-5 for the welded, 
vitric, non-welded, calico, Prow Pass non-welded, Bullfrog non-welded and Bullfrog welded 
layers. The linear regression in Table 7-2 provides dry thermal conductivity values for the Prow 
Pass welded, Tram Tuff non-welded and Tram Tuff welded layers. Standard deviations are not 
available from the regression and are conservatively taken as 10 percent of the mean values. The 
standard deviations of the 7 wet and 7 dry input values average more than 10 percent of the 
means, so the 10-percent choice for the regression standard deviations is somewhat conservative. 
The dry thermal conductivity validation is shown in Table 7-5. Columns S1 and S2 are calculated 
as sqrt (N1) multiplied by s1 and sqrt (N2) multiplied by s2. Column scombined is computed using 
Equation 7-2. Column t is computed from Equation 7-1. All of the normalized differences of 
the means are smaller in magnitude than the corresponding critical values in Table 7-4, so the 
means show no statistically significant difference at the 95- or 98-percent significance levels. 
Table 7-4. Student's t-Distribution Critical Values at Various Confidence Levels 
Critical Value for Significance Level at: 
Type Rock Type 
Degrees of 
Freedom (.) 95% 98% 
dry welded 60 2.000 2.390 
dry vitric 3 3.182 N/A 
dry non-welded 38 2.025 N/A 
dry Calico Hills 11 2.201 N/A 
dry Prow Pass non-welded 12 2.179 N/A 
dry Prow Pass welded 22 2.074 N/A 
dry Bullfrog non-welded 9 2.262 N/A 
dry Bullfrog welded 17 2.110 N/A 
dry Tram Tuff non-welded 14 2.145 N/A 
dry Tram Tuff welded 22 2.074 N/A 
wet welded 18 2.101 N/A 
wet vitric 3 3.182 4.541 
wet non-welded 20 2.086 N/A 
wet Calico Hills 11 2.201 N/A 
wet Prow Pass non-welded 12 2.179 N/A 
wet Prow Pass welded 22 2.074 N/A 
wet Bullfrog non-welded 9 2.262 N/A 
wet Bullfrog welded 17 2.110 N/A 
wet Tram Tuff non-welded 14 2.145 2.624 
wet Tram Tuff welded 22 2.074 N/A 
NOTES: Critical values come from Beyer (1987 [DIRS 103805], p. 571). 
N/A =not applicable. 

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MDL-NBS-GS-000006 REV 01 7-21 October 2004 
Table 7-5. Validation of the Dry Matrix Thermal Conductivity Model 
Model 
Thermal Conductivity 
(W/m K) 
Validation 
Thermal Conductivity 
(W/m K) 
t for significance 
level at: 
Layer N1 mean s1 S1 N2 mean s2 S2 . scombined t 95% 98% 
welded 17 1.300 0.231 0.952 45 1.132 0.268 1.800 60 0.263 2.241 2.000 2.390 
vitric 2 0.688 0.229 0.324 3 1.480 0.327 0.566 3 0.377 -2.304 3.182 N/A 
non-welded 9 0.490 0.158 0.474 31 0.417 0.160 0.889 38 0.163 1.183 2.025 N/A 
Calico Hills 5 0.595 0.112 0.250 8 0.578 0.053 0.150 11 0.088 0.349 2.201 N/A 
Prow Pass 
non-welded 
9 0.569 0.104 0.312 5 0.652 0.033 0.073 12 0.092 -1.609 2.179 N/A 
Prow Pass 
welded 
17 1.060 0.183 0.755 7 0.930 0.093 0.246 22 0.169 1.711 2.074 N/A 
Bullfrog 
non-welded 
9 0.658 0.130 0.390 2 0.700 0.000 0.000 9 0.130 -0.413 2.262 N/A 
Bullfrog 
welded 
17 1.300 0.239 0.985 2 1.400 0.000 0.000 17 0.239 -0.560 2.110 N/A 
Tram Tuff 
non-welded 
9 0.535 0.106 0.318 7 0.629 0.063 0.166 14 0.096 -1.945 2.145 N/A 
Tram Tuff 
welded 
17 1.060 0.183 0.755 7 1.004 0.100 0.266 22 0.171 0.731 2.074 N/A 
NOTES: This table was generated by using data from Table 6-13, Table 7-2, Figure 7-11 to Figure 7-17, and 
Equation 7-1 and Equation 7-2. 
N/A = Not applicable. 
Figure 7-18 to Figure 7-24 provide the numbers of points, means, and standard deviations for the 
wet thermal conductivity data in the welded, vitric, non-welded, calico, Prow Pass non-welded, 
Bullfrog non-welded and Bullfrog welded layers for the columns headed N2, 2, and s2 in 
Table 7-6. The linear regression in Table 7-3 provides the wet thermal conductivity values for 
the Prow Pass welded, Tram Tuff non-welded and Tram Tuff welded layers. Standard deviations 
are not available from the regression and are taken as 10 percent of the mean values. 
The wet thermal conductivity validation is shown in Table 7-6. Columns S1 and S2 are 
calculated as sqrt (N1) multiplied by s1 and sqrt (N2) multiplied by s2. Column scombined is 
computed using Equation 7-2. Column t is computed from Equation 7-1. All of the normalized 
differences of the means are smaller in magnitude than the corresponding critical values in 
Table 7-4, so the means show no statistically significant difference. In terms of thermal 
conductivity, the model meets the 95- or 98-percent confidence criteria (BSC 2004 
[DIRS 171708]), and is validated for its intended use. 

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MDL-NBS-GS-000006 REV 01 7-22 October 2004 
Table 7-6. Validation of the Wet Matrix Thermal Conductivity Model 
Model 
Thermal Conductivity 
(W/m K) 
Validation 
Thermal Conductivity 
(W/m K) 
t for significance 
level: 
Layer N1 mean s1 S1 N2 mean s2 S2 . scombined t 95% 98% 
welded 17 1.810 0.195 0.804 3 1.593 0.079 0.136 18 0.192 1.800 2.101 N/A 
vitric 2 0.796 0.251 0.355 3 1.903 0.237 0.410 3 0.313 -3.871 3.182 4.541 
non-welded 9 1.060 0.146 0.438 13 1.026 0.225 0.809 20 0.206 0.379 2.086 N/A 
Calico Hills 5 1.260 0.141 0.315 8 1.163 0.064 0.180 11 0.110 1.561 2.201 N/A 
Prow Pass 
non-welded 
9 1.130 0.117 0.351 5 1.258 0.048 0.108 12 0.106 -2.165 2.179 N/A 
Prow Pass 
welded 
17 1.630 0.168 0.693 7 1.498 0.150 0.396 22 0.170 1.728 2.074 N/A 
Bullfrog 
non-welded 
9 1.190 0.138 0.414 2 1.330 0.000 0.000 9 0.138 -1.298 2.262 N/A 
Bullfrog 
welded 
17 1.810 0.198 0.816 2 1.850 0.000 0.000 17 0.198 -0.270 2.110 N/A 
Tram Tuff 
non-welded 
9 1.100 0.116 0.348 7 1.248 0.125 0.330 14 0.128 -2.291 2.145 2.624 
Tram Tuff 
welded 
17 1.630 0.168 0.693 7 1.570 0.157 0.415 22 0.172 0.776 2.074 N/A 
NOTES: This table was generated by using data from Table 6-13, Table 7-3, Figure 7-18 to Figure 7-24, and 
Equation 7-1 and Equation 7-2. 
N/A = Not applicable. 
7.2.4 Maximum Relative Errors In the Model Thermal Conductivity Values 
There are two ways to determine the limits of validity of the model. One way to estimate the 
errors in the model thermal conductivity values is to use the standard deviations of the model 
data (Table 6-13) with (two-sided) 95- or 98-percent confidence limits from Students 
t-distribution. The (one-sided) 0.975 or 0.99 values for the numbers of model data points are 
shown in Table 7-7, along with the means and standard deviations from Table 6-13. Because 
Students t-distribution is symmetrical, the one-sided 0.975 and 0.99 values are equivalent to the 
two-sided 95- and 98-percent confidence values, respectively. 
The other way to determine the limits of validity of the model is to estimate the maximum 
possible relative errors in the thermal conductivity that allow validation from the limits on the 
validation restriction on the difference of the means: 
| 1  x | / scombined = tcritical (Eq. 7-7) 
Here, 1 is the model mean and x is the maximum or minimum value at which the normalized 
difference in the means equals the critical value (tcritical) from Students t-distribution. The

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MDL-NBS-GS-000006 REV 01 7-23 October 2004 
minimum and maximum values are the limits that the validation thermal conductivity could have 
had and still show that the model mean is valid. The maximum relative error E is: 
E = | 1  x | / 1 = tcritical scombined/ 1 (Eq. 7-8) 
Table 7-8 gives the maximum relative errors calculated from Equation 7-8 using the values in 
Table 7-4, Table 7-5, and Table 7-6. 
Table 7-7. Percent Relative Errors in Thermal Conductivity Data Based on Standard Deviations 
Dry Matrix Thermal Conductivity 
(W/m K) 
Wet Matrix Thermal Conductivity 
(W/m K) 
Layer N 
Confidence 
Level 
T for . 
= N-1 mean s 
% 
Relative 
Error 
Confidence 
Level 
T for . 
= N-1 mean s 
% 
Relative 
Error 
welded 17 98% 2.583 1.300 0.231 46 95% 2.120 1.810 0.195 23 
vitric 2 95% 12.706 0.688 0.229 423 98% 31.821 0.796 0.251 1003 
non-welded 9 95% 2.306 0.490 0.158 74 95% 2.306 1.060 0.146 32 
Calico Hills 5 95% 2.776 0.595 0.112 52 95% 2.776 1.260 0.141 31 
Prow Pass 
non-welded 
9 95% 2.306 0.569 0.104 42 95% 2.306 1.130 0.117 24 
Prow Pass 
welded 
17 95% 2.120 1.060 0.183 37 95% 2.120 1.630 0.168 22 
Bullfrog 
non-welded 
9 95% 2.306 0.658 0.130 46 95% 2.306 1.190 0.138 27 
Bullfrog 
welded 
17 95% 2.120 1.300 0.239 39 95% 2.120 1.810 0.198 23 
Tram Tuff 
non-welded 
9 95% 2.306 0.535 0.106 46 98% 2.896 1.100 0.116 31 
Tram Tuff 
welded 
17 95% 2.120 1.060 0.183 37 95% 2.120 1.630 0.168 22 
NOTES: Columns N, mean, and s are taken from Table 6-13. 
Column T is taken from Beyer (1987 [DIRS 103805], p. 571). 
Percent Relative Error = 100  s  T/mean. 
Table 7-8. Percent Relative Errors of the Model Thermal Conductivity Values from Validation Limits 
Layer 
Dry Matrix Thermal Conductivity 
(W/m K) 
Wet Matrix Thermal Conductivity 
(W/m K) 
. 
Confidence 
Level Tcritical mean scombined 
% 
Relative 
Error . 
Confidence 
Level Tcritical mean scombined 
% 
Relative 
Error 
welded 60 98% 2.390 1.300 0.263 48 18 95% 2.101 1.810 0.192 22 
vitric 3 95% 3.182 0.688 0.377 174 3 98% 4.541 0.796 0.313 179 
nonwelded 
38 95% 2.025 0.490 0.163 68 20 95% 2.086 1.060 0.206 40 
Calico 
Hills 
11 95% 2.201 0.595 0.088 33 11 95% 2.201 1.260 0.110 19 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-24 October 2004 
Table 7-8. Percent Relative Errors of the Model Thermal Conductivity Values from Validation Limits 
(Continued) 
Layer 
Dry Matrix Thermal Conductivity 
(W/m K) 
Wet Matrix Thermal Conductivity 
(W/m K) 
. 
Confidence 
Level Tcritical mean scombined 
% 
Relative 
Error . 
Confidence 
Level Tcritical mean scombined 
% 
Relative 
Error 
Prow 
Pass 
nonwelded 
12 95% 2.179 0.569 0.092 35 12 95% 2.179 1.130 0.106 20 
Prow 
Pass 
welded 
22 95% 2.074 1.060 0.169 33 22 95% 2.074 1.630 0.170 22 
Bullfrog 
nonwelded 
9 95% 2.262 0.658 0.130 45 9 95% 2.262 1.190 0.138 26 
Bullfrog 
welded 
17 95% 2.110 1.300 0.239 39 17 95% 2.110 1.810 0.198 23 
Tram 
Tuff 
nonwelded 
14 95% 2.145 0.535 0.096 38 14 98% 2.624 1.100 0.128 31 
Tram 
Tuff 
welded 
22 95% 2.074 1.060 0.171 33 22 95% 2.074 1.630 0.172 22 
NOTES: The input data in this table are taken from Table 7-4, Table 7-5, and Table 7-6. 
Percent Relative Error = 100  scombined  Tcritical /mean (see Equation 7-8). 
Because these two methods give different limits, the smaller value must be taken from Table 7-7 
and Table 7-8 to maintain the validity of the model. These values are shown in Table 7-9, which 
represent the actual limits on the model for the model to be valid. 
Table 7-9. Maximum Relative Errors of the Model Thermal Conductivity Values 
Maximum Relative Error (percent) 
Layer 
Dry Matrix Thermal 
Conductivity 
Wet Matrix Thermal 
Conductivity 
welded 46 22 
vitric 174 179 
non-welded 68 32 
Calico Hills 33 19 
Prow Pass non-welded 35 20 
Prow Pass welded 33 22 
Bullfrog non-welded 45 26 
Bullfrog welded 39 23 
Tram Tuff non-welded 38 31 
Tram Tuff welded 33 22 
NOTE: The data in this table are the minimum values from Table 7-7 and Table 7-8. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-25 October 2004 
7.3 VALIDATION SUMMARY 
The Thermal Conductivity of Non-Repository Lithostratigraphic Layers model has been 
validated by applying acceptance criteria based on an evaluation of the relative importance of the 
model to the potential performance of the repository system. All validation requirements defined 
in TWP-MGR-PA-000019 REV 00 ICN 01 (BSC 2004 [DIRS 171708], Section 2.2.2) have been 
fulfilled, including corroboration of model results with qualified thermal conductivity data. 
Requirements for confidence building during model development have also been satisfied. The 
model development activities and post-development validation activities described in this report 
establish the scientific bases for the Thermal Conductivity of Non-Repository Lithostratigraphic 
Layers Model. Based on this, the model and results are considered to be sufficiently accurate and 
adequate for the intended purpose and to the level of confidence required by the relative 
importance of the model to the potential performance of the repository system. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 7-26 October 2004 
INTENTIONALLY LEFT BLANK

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 8-1 October 2004 
8. CONCLUSIONS 
8.1 SUMMARY 
The thermal conductivity model is developed using 31 sets of dry and wet thermal conductivity 
values, and approximately 1,900 porosity measurements. The data triads are processed by the 
inverse program HSUINV (STN 10804-1.0-00 [DIRS 158228]) to produce 31 sets of porosity, 
solid thermal conductivity, and a geometric parameter. Distributions are estimated from these 
data for the welded, non-welded, and calico rock types. In the absence of any vitric rock-type 
data, the distribution for solid thermal conductivity is assumed to be the handbook range for solid 
glass and the geometric parameter is assumed to be one. The distributions are used as input to 
the GENHSUMODELDATA (STN 10905-1.0-00 [DIRS 162671]) to produce average values 
and standard deviations for dry and wet thermal conductivity and for porosity. The dry and wet 
thermal conductivities and porosities presented in Table 6-13 are the final model of values for 
the nonrepository layers of the GFM of Yucca Mountain from Crystal-Rich Tiva/Post Tiva down 
through the Tram Tuff non-welded layer, Trambt (Appendix U). The results in Table 6-13 are 
available as Output DTN SN0303T0503102.008. The input and output data used in this model 
development are available as Product Output DTN SN0307T0503102.009. 
The model is validated using 356 thermal conductivity values and approximately 10,000 porosity 
values. The standard deviations on the model are moderately large, varying from 10 percent to 
33 percent of the mean. Because the number of data points used in model development is small, 
confidence intervals are found using Students t-distribution rather than the normal distribution. 
Measurement uncertainties are small compared to 95- and 98-percent confidence intervals and, 
therefore, are not included in the calculations. The Prow Pass welded, Tram Tuff welded, and 
Tram Tuff non-welded rock types lack dry or wet thermal conductivity data for the validation, so 
the values for the other seven rock types are fitted by linear regression to predict values for these 
three rock types. The form used (Equation 7-4 from Section 7.2 of this report) is: 
k = A + B/fm + C/fm
2 + D db/(1-fm) 
where: 
A, B, C, and D are the regression coefficients 
k = thermal conductivity 
fm = matrix porosity 
db = dry bulk density. 
The fits of the validation thermal conductivities have maximum relative errors of less than seven 
percent. The means of the model and validation dry and wet thermal conductivities are 
compared using Students t-distribution, and the differences in the means are not statistically 
significant at the 95- or 98-percent confidence level. This constitutes validation of the vitric rock 
assumption and the thermal conductivity model at the 95- or 98-percent confidence level. 
The means of the model and model validation porosity data are compared in a similar manner 
and are found to be statistically equivalent. This validates the assumption that the approximately 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 8-2 October 2004 
1,900 model porosity values are representative of the remaining 10,000 model validation 
porosity values. 
8.2 YUCCA MOUNTAIN REVIEW PLAN CRITERIA ASSESSMENT 
The model developed in this report addresses the Yucca Mountain Review Plan, Final Report 
(NRC 2003 [DIRS 163274]) acceptance criteria. 
8.2.1 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. 
Basis: Qualified, site-specific data obtained from core sample measurements are used to develop 
the geostatistical models of porosity and thermal conductivity. The input data and their 
appropriateness in model selection and development are described in Sections 4.1 and 6.1 
respectively. Adequate descriptions of how the data were used, interpreted, and synthesized into 
the developed parameters are included in Section 6 and Appendices B through R. 
8.2.2 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. 
Basis: The input data described in Section 4.1 and used in the model development activities 
described in Section 6 are representative of the nonrepository lithostratigraphic layers. The data 
are technically defensible because they were obtained from Project qualified and controlled 
sources. Measurement errors (see Appendix A), biases, and natural sample variabilities are 
propagated into the models that use these data. Therefore, the approach used to develop the 
output of this report reasonably accounts for uncertainties and variabilities and does 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. 
Basis: The validation of the thermal conductivity and porosity models, as described in Section 7, 
is based on corroboration with data from laboratory and field experiments involving the 
nonrepository units characterized in this report. These validation and confidence building 
exercises provide justification that the models are technically defensible, reasonable and support 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 8-3 October 2004 
the use of these models as input to other process-level models in the Total System Performance 
Assessment (TSPA) for the License Application (LA). 
The justification for the values used is addressed in Section 4.1. The use of natural analogue 
data (solid glass) as an approximation of vitric, densely welded properties is addressed in 
Section 5, Assumption 2, and is justified in Section 7.2.3. The suitability of data for use in the 
Hsu model is discussed in Section 6.3. The estimation of probability distributions for data is 
described in Sections 6.4, 6.5, and 6.6. Estimates of measurement uncertainty in the data are 
discussed in Sections 6.2 and 6.6. The numerical uncertainties in averages of data are addressed 
in Sections 7.2.1, 7.2.3, and 7.2.4. The maximum uncertainties in model results are evaluated in 
Section 7.2.4. 
8.2.3 Acceptance Criterion 4  Model Uncertainty is Characterized and 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. 
Basis: Alternative conceptual models of thermal conductivity are discussed in Section 6.1. The 
rationale used in the model selection process is consistent with the data available for model 
development and the intended use of the models. The limitations of these models are discussed 
in Section 6.1. The appropriateness of the selected models is confirmed through the validation 
and confidence building exercises described in Section 7. 
8.3 ADDITIONAL SENSITIVITY ANALYSIS 
The Multiscale Thermohydrologic Model (BSC 2004 [DIRS 169565]) evaluates repository 
temperatures based upon the uncertainty in thermal conductivity of the main repository units 
based upon the mean and standard deviation of these units as developed in Thermal Conductivity 
of the Potential Repository Horizon (BSC 2004 [DIRS 169854]). This uncertainty is propagated 
to the TSPA-LA. The following discussion addresses the issue of propagating the uncertainty 
for thermal conductivity for the nonrepository horizon units and provides a justification for not 
propagating uncertainty for these units to the TSPA-LA. 
An analysis (Appendix S) was performed to assess the significance of the nonrepository horizon 
units on the uncertainty in repository temperature over extended periods of time (20,000 years). 
The analysis utilized the steady-state heat transfer by heat conduction in the vertical direction. 
Both the thermal conductivity under saturated conditions of the repository and nonrepository 
horizon units are included in this analysis. The analysis predicts an approximate peak 
uncertainty in temperature of 7 degrees C. This uncertainty decreases with time after closure due 
to a decrease in average repository heat loading over this period. An uncertainty analysis 
utilizing Hahn and Shapiro (1967 [DIRS 146529], p. 231) was performed and predicted that the 
Tsw38 layer (Tptpv3) below the repository provides the most significant contribution to 
uncertainty over extended periods. This is because the rock mass thermal conductivity of this 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 8-4 October 2004 
unit is much lower (0.8 W/(m K)) than the repository horizon unit (1.89 W/(m K)) under 
saturated conditions. 
The steady state analysis tends to overestimate the uncertainty of the nonrepository units because 
in reality, heat diffuses more slowly from the repository horizon. The results of calculations in 
the Multiscale Thermohydrologic Model (BSC 2004 [DIRS 169565]) show that, immediately 
after closure, the variations in repository temperature, and therefore waste package temperature, 
are dominated by the uncertainty at the repository horizon, because heat has not diffused very far 
from the repository horizon at the time the peak waste package temperature is reached. At later 
times, the steady state analysis in Appendix S indicates that Tsw38 is more dominant; however, 
at later times, the uncertainty in repository temperatures is low and need not be considered in the 
TSPA-LA. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-1 October 2004 
9. REFERENCES 
The following is a list of the references cited in this document. Column 2 represents the unique 
six digit numerical identifier (the Document Input Reference System number), which is placed in 
the text following the reference callout (e.g., BSC 2004 [DIRS 168489]). The purpose of these 
numbers is to assist in locating a specific reference. Multiple sources by the same author (e.g., 
BSC 2004) are sorted alphabetically by title. 
9.1 DOCUMENTS CITED 
Beyer, W.H., ed. 1987. CRC Standard Mathematical Tables. 28th Edition. 3rd 
Printing 1988. Boca Raton, Florida: CRC Press. TIC: 240507. 
103805 
Brodsky, N.S. 2003. Uncertainty Estimates - Measurement Error Estimates for 
Porosity, Thermal Conductivity, Bulk Density. Fax from N.S. Brodsky (SNL) to N. 
Garcia, July 29, 2003. ACC: MOL.20030729.0082. 
164584 
BSC (Bechtel SAIC Company, LLC) 2004. D&E / PA/C IED Emplacement Drift 
Configuration and Environment. 800-IED-MGR0-00201-000-00B. Las Vegas, 
Nevada: Bechtel SAIC Company. ACC: ENG.20040326.0001. 
168489 
BSC 2004. D&E / PA/C IED Typical Waste Package Components Assembly. 
800-IED-WIS0-00203-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040202.0011. 
167754 
BSC 2004. Data Qualification Plan, Qualification of Unqualified Dry Bulk Density 
Data Contained in DTNs GS920408312314.011, SEP Table S97135_002 and DTN 
GS930408312132.007, SEP Table S97276_001 for Use in MDL-NBS-GS-000006 
Rev 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20041011.0006. 
171956 
BSC 2004. Geologic Framework Model (GFM2000). MDL-NBS-GS-000002 
REV 02. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20040827.0008. 
170029 
BSC 2004. In-Drift Natural Convection and Condensation. MDL-EBS-MD-000001, 
REV 00. Las Vegas, Nevada: Bechtel SAIC Company. 
164327 
BSC 2004. Multiscale Thermohydrologic Model. ANL-EBS-MD-000049 REV 02. 
Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20041014.0008. 
169565 
BSC 2004. Q-List. 000-30R-MGR0-00500-000-000 REV 00. Las Vegas, Nevada: 
Bechtel SAIC Company. ACC: ENG.20040721.0007. 
168361 
BSC 2004. Technical Work Plan for: Near-Field Environment and Transport 
Thermal Properties Model and Analysis Reports Integration. TWP-MGR-PA-000019 
REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040920.0003. 
171708

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-2 October 2004 
BSC 2004. Thermal Conductivity of the Potential Repository Horizon. MDL-NBSGS-
000005 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040928.0006. 
169854 
BSC 2004. Ventilation Model and Analysis Report. ANL-EBS-MD-000030 REV 04. 
Las Vegas, Nevada: Bechtel SAIC Company. 
169862 
Buesch, D.C. and Spengler, R.W. 1999. Correlations of Lithostratigraphic Features 
with Hydrogeologic Properties, a Facies-Based Approach to Model Development in 
Volcanic Rocks at Yucca Mountain, Nevada. Proceedings of Conference on Status 
of Geologic Research and Mapping in Death Valley National Park, Las Vegas, 
Nevada, April 9-11, 1999. Slate, J.L., ed. Open-File Report 99-153. Pages 62-64. 
Denver, Colorado: U.S. Geological Survey. TIC: 245245. 
107905 
Buesch, D.C.; Spengler, R.W.; Moyer, T.C.; and Geslin, J.K. 1996. Proposed 
Stratigraphic Nomenclature and Macroscopic Identification of Lithostratigraphic 
Units of the Paintbrush Group Exposed at Yucca Mountain, Nevada. Open-File 
Report 94-469. Denver, Colorado: U.S. Geological Survey. ACC: 
MOL.19970205.0061. 
100106 
Bulmer, M.G. 1979. Principles of Statistics. 3rd Edition. New York, New York: 
Dover. TIC: 245835. 
111961 
Canori, G.F. and Leitner, M.M. 2003. Project Requirements Document. TERMGR-
MD-000001 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
DOC.20031222.0006. 
166275 
Chapman, A.J. 1974. Heat Transfer. 3rd Edition. New York, New York: Macmillan 
Publishing. TIC: 245061. 
152938 
CRWMS (Civilian Radioactive Waste Management System) M&O (Management 
and Operating Contractor) 1997. Determination of Available Volume for Repository 
Siting. BCA000000-01717-0200-00007 REV 00. Las Vegas, Nevada: CRWMS 
M&O. ACC: MOL.19971009.0699. 
100223 
DOE (U.S. Department of Energy) 2004. Quality Assurance Requirements and 
Description. DOE/RW-0333P, Rev. 16. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: 
DOC.20040907.0002. 
171539 
Freeze, R.A. and Cherry, J.A. 1979. Groundwater. Englewood Cliffs, New Jersey: 
Prentice-Hall. TIC: 217571. 
101173 
Hadley, G.R. 1986. Thermal Conductivity of Packed Metal Powders. International 
Journal of Heat and Mass Transfer, 29, (6), 909-920. New York, New York: 
Pergamon Journals. TIC: 249320. 
153165

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-3 October 2004 
Hahn, G.J. and Shapiro, S.S. 1967. Statistical Models in Engineering. New York, 
New York: John Wiley & Sons. TIC: 247729. 
146529 
Hsu, C.T.; Cheng, P.; and Wong, K.W. 1995. A Lumped-Parameter Model for 
Stagnant Thermal Conductivity of Spatially Periodic Porous Media. Journal of Heat 
Transfer, 117, (2), 264-269. New York, New York: American Society of Mechanical 
Engineers. TIC: 252402. 
158073 
Kunii, D. and Smith, J.M. 1960. Heat Transfer Characteristics of Porous Rocks. 
American Institute of Chemical Engineers Journal, 6, (1), 71-78. New York, New 
York: American Institute of Chemical Engineers. TIC: 249321. 
153166 
Maxwell, J.C. 1954. A Treatise on Electricity and Magnetism. 3rd Edition 
(unabridged). Two volumes. New York, New York: Dover Publications. TIC: 
252475. 
158165 
NRC (U.S. Nuclear Regulatory Commission) 2003. Yucca Mountain Review Plan, 
Final Report. NUREG-1804, Rev. 2. Washington, D.C.: U.S. Nuclear Regulatory 
Commission, Office of Nuclear Material Safety and Safeguards. TIC: 254568. 
163274 
Perry, R.H. and Chilton, C.H., eds. 1973. Chemical Engineers' Handbook. 5th 
Edition. New York, New York: McGraw-Hill. TIC: 242591. 
104946 
Rautman, C.A. and Engstrom, D.A. 1996. Geology of the USW SD-7 Drill Hole, 
Yucca Mountain, Nevada (Final Draft). SAND96-1474. Albuquerque, New Mexico: 
Sandia National Laboratories. ACC: MOL.19971218.0440. 
100693 
SNL (Sandia National Laboratories) 1998. Laboratory Measurements of Thermal 
Conductivity as a Function of Saturation State for Welded and Nonwelded Tuff 
Specimens. Albuquerque, New Mexico: Sandia National Laboratories. 
ACC: MOL.19980901.0177. 
118788 
SNL 2002. Software Management Report, HsuInv, Version 1.0. Software 
Management Report Number: 10804-SMR-1.0-00. Albuquerque, New Mexico: 
Sandia National Laboratories. ACC: MOL.20020717.0285. 
171559 
SNL 2002. Software Management Report, GENHSUMODELDATA Version 1.00. 
Software Management Report Number: 10905-SMR-1.0-00. Albuquerque, New 
Mexico: Sandia National Laboratories. ACC: MOL.20021202.0356. 
171560 
SNL 2002. Software Management Report, GSLIB HISTPLTV2.01. Software 
Management Report Number: 10802-SMR-2.01-00. Albuquerque, New Mexico: 
Sandia National Laboratory. ACC: MOL.20020710.0501. 
171558

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-4 October 2004 
9.2 CODES, STANDARDS, REGULATIONS AND PROCEDURES 
10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada. Readily available. 
156605 
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-SI.1Q, Rev. 3, ICN 3. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20020102.0200. 
AP-SI.1Q, Rev. 3, ICN 4. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20020520.0283. 
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. 
AP-SV.1Q, Rev. 1, ICN 1. Control of the Electronic Management of Information. 
Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste 
Management. ACC: DOC.20040308.0001. 
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 
GS000408312231.004. Data for Core Dried in RH Oven and 105C Oven for USW 
UZ-N31, UZ-N32, UZ-N33, UZ-N34, UZ-N35, UZ-N38, UZ-N58, UZ-N59, UE-25 
UZN#63 and USW UZ-N64; Data for Core Dried in 105C Oven Only for USW UZN11, 
UZ-N15, UZ-N16, UZ-N17, UZ-N27, UZ-N36 and UZ-N37. Submittal date: 
04/28/2000. 
149582 
GS000508312231.006. Physical Properties and Water Content from Borehole USW 
NRG-6, 3/19/94 to 3/27/95. Submittal date: 05/23/2000. 
153237 
GS920408312314.011. Geohydrology of Test Well USW H-1, Yucca Mountain, Nye 
County, Nevada. Submittal date: 08/21/1987. 
129660 
GS920508312231.012. USW UZ-N54 and USW UZ-N55 Core Analysis: Bulk 
Density, Porosity, Particle Density and In Situ Saturation for Core Dried in 105C 
Oven. Submittal date: 05/14/1992. 
109001

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-5 October 2004 
GS930108312231.006. USW UZ-N53 Core Analysis: Bulk Density, Porosity, 
Particle Density, and In-Situ Saturation for Core Dried in 105C Oven. Submittal date: 
10/05/1992. 
108997 
GS930408312132.007. Geohydrologic Data and Test Results from Well J-13, 
Nevada Test Site, Nye County, Nevada. Submittal date: 04/23/1993. 
129625 
GS940408312231.004. Core Analysis of Bulk Density, Porosity, Particle Density, 
and In-Situ Saturation for 3 Neutron Boreholes, USW UZ-N57, UZ-N61, and UZN62. 
Submittal date: 04/01/1994. 
109000 
GS940508312231.006. Core Analysis of Bulk Density, Porosity, Particle Density and 
In Situ Saturation for Borehole UE-25 UZ#16. Submittal date: 05/04/1994. 
107149 
GS950308312231.002. Laboratory Measurements of Core from USW SD-12 and 
Radial Boreholes. Submittal date: 03/02/1995. 
108990 
GS950408312231.004. Physical Properties and Water Potentials of Core from 
Borehole USW SD-9. Submittal date: 03/01/1995. 
108986 
GS951108312231.009. Physical Properties, Water Content, and Water Potential for 
Borehole USW SD-7. Submittal date: 09/26/1995. 
108984 
GS951108312231.010. Physical Properties and Water Content for Borehole USW 
NRG-7/7A. Submittal date: 09/26/1995. 
108983 
GS951108312231.011. Physical Properties, Water Content, and Water Potential for 
Borehole USW UZ-7A. Submittal date: 09/26/1995. 
108992 
GS960808312231.004. Physical Properties, Water Content and Water Potential for 
Samples from Lower Depths in Boreholes USW SD- 7 and USW SD-12. Submittal 
date: 08/30/1996. 
108985 
GS980608314221.002. Revised Bedrock Geologic Map of the Yucca Mountain Area, 
Nye County, Nevada. Submittal date: 06/09/1998. 
107024 
GS980708312242.010. Physical Properties of Borehole Core Samples, and Water 
Potential Measurements Using the Filter Paper Technique, for Borehole Samples 
from USW WT-24. Submittal date: 07/27/1998. 
106752 
GS980808312242.014. Physical Properties of Borehole Core Samples and Water 
Potential Measurements Using the Filter Paper Technique for Borehole Samples from 
USW SD-6. Submittal date: 08/11/1998. 
106748

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-6 October 2004 
MO0004QGFMPICK.000. Lithostratigraphic Contacts from 
MO9811MWDGFM03.000 to be Qualified Under the Data Qualification Plan, TDPNBS-
GS-000001. Submittal date: 04/04/2000. 
152554 
MO0012POROCHOL.000. Porosity Data (Using Deionized Water) from UE-25 C 
#1, UE-25 C #2, and UE-25 C #3. Submittal date: 12/05/2000. 
153376 
MO0109HYMXPROP.001. Matrix Hydrologic Properties Data. Submittal date: 
09/17/2001. 
155989 
MO0406SEPTVDST.000. Temperature and Volume Water Content for Drift Scale 
Test (DST) Heating Phase for Boreholes 79 and 80. Submittal date: 06/29/2004. 
170616 
MO9510RIB00002.004. RIB Item: Stratigraphic Characteristics: Geologic/Lithologic 
Stratigraphy. Submittal date: 06/26/1996. 
103801 
MO9905LUSWWT24.000. Surveyed Location USW WT-24. Submittal date: 
05/07/1999. 
165921 
MO9906GPS98410.000. Yucca Mountain Project (YMP) Borehole Locations. 
Submittal date: 06/23/1999. 
109059 
MO9912GSC99492.000. Surveyed USW SD-6 As-Built Location. Submittal date: 
12/21/1999. 
165922 
SN0011T0571897.014. Revised Thermal Modeling Parameters for Conduction-Only 
Models by Stratigraphic Unit. Submittal date: 11/29/2000. 
154449 
SNF40060298001.001. Unsaturated Zone Lithostratigraphic Contacts in Borehole 
USW SD-6. Submittal date: 10/15/1998. 
107372 
SNL01A05059301.002. Thermal Conductivity Data from USW NRG-6 Drillhole 
Samples from Depth of 28.8 ft. to 987.0 ft. Submittal date: 07/15/1994. 
150042 
SNL01A05059301.005. Laboratory Thermal Conductivity Data for Boreholes UE25 
NRG-4, NRG-5; USW NRG-6 and NRG-7/7A. Submittal date: 02/07/1996. 
109002 
SNL01A05059301.007. Calculated Porosities for Thermal Conductivity Specimens 
from Boreholes UE25 NRG-4, UE25 NRG-5, USW NRG-6, and USW NRG-7/7a. 
Submittal date: 10/14/1998. 
108980 
SNL02030193001.001. Mechanical Properties Data for Drillhole USW NRG-6 
Samples from Depth 22.2 ft. to 328.7 ft. Submittal date: 05/17/1993. 
120572 
SNL02030193001.002. Mechanical Properties Data for Drillhole USW NRG-6 
Samples from Depth 22.2 ft. to 427.0 ft. Submittal date: 06/25/1993. 
120575

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-7 October 2004 
SNL02030193001.003. Mechanical Properties Data for Drillhole UE-25 NRG-2 
Samples from Depth 150.5 ft. to 200.0 ft. Submittal date: 07/07/1993. 
120578 
SNL02030193001.004. Mechanical Properties Data for Drillhole USW NRG-6 
Samples from Depth 462.3 ft. to 1085.0 ft. Submittal date: 08/05/1993. 
108415 
SNL02030193001.005. Mechanical Properties Data for Drillhole UE-25 NRG#3 
Samples from Depth 15.4 ft. to 297.1 ft. Submittal date: 09/23/1993. 
122545 
SNL02030193001.006. Mechanical Properties Data for Drill Hole UE-25 NRG#2A 
Samples from Depth 90.0 ft. to 254.5 ft. Submittal date: 10/13/1993. 
120579 
SNL02030193001.007. Mechanical Properties Data for Drill Hole UE-25 NRG#3 
Samples from Depth 263.3 ft. to 265.7 ft. Submittal date: 10/20/1993. 
120582 
SNL02030193001.008. Mechanical Properties Data for Drill Hole USW NRG-6 
Sample 416.0 ft. Submittal date: 10/20/1993. 
120597 
SNL02030193001.009. Mechanical Properties Data for Drillhole UE25 NRG-5 
Samples from Depth 781.0 ft. to 991.9 ft. Submittal date: 11/18/1993. 
109614 
SNL02030193001.012. Mechanical Properties Data for Drillhole UE25 NRG-5 
Samples from Depth 847.2 ft. to 896.5 ft. Submittal date: 12/02/1993. 
108416 
SNL02030193001.013. Mechanical Properties Data for Drillhole UE25 NRG-2B 
Samples from Depth 2.7 ft. to 87.6 ft. Submittal date: 12/02/1993. 
120614 
SNL02030193001.014. Mechanical Properties Data for Drillhole UE25 NRG-4 
Samples from Depth 378.1 ft. to 695.8 ft. Submittal date: 01/31/1994. 
109609 
SNL02030193001.015. Mechanical Properties Data for Drillhole UE25 NRG-4 
Samples from Depth 527.0 ft. Submittal date: 02/16/1994. 
120617 
SNL02030193001.016. Mechanical Properties Data for Drillhole USW NRG-7/7A 
Samples from Depth 18.0 ft. to 472.9 ft. Submittal date: 03/16/1994. 
120619 
SNL02030193001.017. Mechanical Properties Data for Drillhole USW NRG-7/7A 
Samples from Depth 18.0 ft. to 495.0 ft. Submittal date: 03/21/1994. 
109610 
SNL02030193001.018. Mechanical Properties Data for Drillhole USW NRG-7/7A 
Samples from Depth 344.4 ft. Submittal date: 04/11/1994. 
109611 
SNL02030193001.019. Mechanical Properties Data for Drillhole USW NRG-7/7A 
Samples from Depth 507.4 ft. to 881.0 ft. Submittal date: 06/29/1994. 
108431

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 9-8 October 2004 
SNL02030193001.020. Mechanical Properties Data for Drillhole USW NRG-7/7A 
Samples from Depth 554.7 ft. to 1450.1 ft. Submittal date: 07/25/1994. 
108432 
SNL02030193001.021. Mechanical Properties Data (Ultrasonic Velocities, Static 
Elastic Properties, Triaxial Strength, Dry Bulk Density & Porosity) for Drillhole 
USW NRG-7/7A Samples from Depth 345.0 ft. to 1408.6 ft. Submittal date: 
02/16/1995. 
108433 
SNL02030193001.022. Mechanical Properties Data for Drill Hole USW NRG-6 
Samples from Depth 5.7 ft. to 1092.3 ft. Submittal date: 02/27/1995. 
109613 
SNL02030193001.028. Confined Compression Experiments at 150 Degrees C on 
TSW2 from Borehole USW SD-9. Submittal date: 09/05/1996. 
159972 
SNL03042594001.002. Average Grain Density for Thermal Properties Test Samples 
from Boreholes UE25 NRG-4, UE25 NRG-5, and USW NRG-6. Submittal date: 
06/20/1994. 
109607 
SNL03042594001.003. Average Grain Density for Thermal Properties Test Samples 
from Borehole UE25 NRG-7/7A. Submittal date: 06/20/1994. 
109608 
SNL22100196001.006. Laboratory Measurements of Thermal Conductivity as a 
Function of Saturation State for Welded and Nonwelded Tuff Specimens. Submittal 
date: 06/08/1998. 
158213 
9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
SN0303T0503102.008. Revised Thermal Conductivity of the Non-repository Layers of Yucca 
Mountain. Submittal date: 03/19/2003. 
SN0307T0503102.009. Thermal Conductivity Model for the Non-repository Layers of Yucca 
Mountain. Submittal date: 07/21/2003. 
9.5 SOFTWARE CODES 
SNL 2002. Software Code: GENHSUMODELDATA. V1.0. PC/Windows 2000 
Server. 10905-1.0-00. 
162671 
SNL 2002. Software Code: GSLIB HISTPLT. V2.01. 10802-2.01-00. 158223 
SNL 2002. Software Code: HSUINV. V.1.0. PC/Windows 2000 Server. 
10804-1.0-00. 
158228 
SNL 2002. Software Code: REFORMAT. V2.0. PC/Windows 2000 Server. 
10907-2.0-00. 
162673 
SNL 2002. Software Code: SPLICE. V1.0. PC/Windows 2000 Server. 10906-1.0-00. 162672 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX A 
ESTIMATES OF MEASUREMENT UNCERTAINTIES IN THERMAL 
CONDUCTIVITY, MATRIX POROSITY, AND DRY BULK DENSITY

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 A-1 October 2004 
-----Original Message----- 
From: Brodsky, Nancy 
Sent: Tuesday, July 29, 2003 4:06 PM 
To: Iuzzolino, Harold Joseph 
Cc: Castagna, Iris J 
Subject: Uncertainty Estimates 
Harold: 
The error in matrix thermal conductivity for oven-dried specimens is plus/minus 5 percent of the 
measured value. This is the error associated with the NIST standards used for calibration, and it is 
the minimum error associated with the guarded heat flow method (GHFM). 
For saturated specimens, 5 percent has also always been the error specified by the equipment 
manufacturer. As documented in Laboratory Measurements of Thermal Conductivity as a Function of 
Saturation State for Welded and Nonwelded Tuff Specimens, ACC: MOL.19980901.0177, on page 
21, I have suspected it might be higher for saturated specimens, but there is no solid qualified data at 
this time to provide any alternative error value. 
Matrix porosity - This depends on the method used in the calculation. A lot of laboratory methods 
report about 1 percent error - that's 1 percent porosity, not 1 percent of the measured porosity. A 
realistic assessment might come from comparing porosities calculated using dry bulk densities and 
grain densities, as opposed to calculated using dry and saturated porosities. I did this on the attached 
spreadsheet - see column O. In some cases, the errors are higher than 1 percent. 
Dry bulk density - this is mass divided by specimen volume. Mass is usually measured to 0.01g; 
volume is calculated from diameter and length measurements, usually accurate to 0.001 inches. This 
is then converted to metric, probably using a conversion factor of 3 significant digits. 
- Nancy 
Poros_tc_addcalc.xl 
s 
Nancy S. Brodsky 
Sandia National Laboratories 
P.O. Box 5800 
Albuquerque, NM 87185-0778 
email: nsbrods@sandia.gov 
phone: (505) 844-3408 
fax: (505) 284-4002 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 A-2 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 A-3 October 2004 
Sources: The text and spreadsheet parts of this memo are from the Records Information System under Brodsky 
2003 [DIRS 164584]. 
Source data for the spreadsheet are from DTNs: SNL01A05059301.005 [DIRS 109002], 
SNL03042594001.002 [DIRS 109607], and SNL03042594001.003 [DIRS 109608]. 
The memo references SNL 1998 [DIRS 118788]. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 A-4 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX B 
PROGRAM SPLICE INPUT CONTROL DATA FOR NRG4, 
NRG5, NRG6, AND NRG7 BOREHOLES 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 B-1 October 2004 
Table B-1. Input DTN List 
DTN Renamed Program Input File 
SNL01A05059301.007 [DIRS 108980] s98424_003.txt 
SNL01A05059301.005 [DIRS 109002] s96370_001.txt 
SPLICE (STN: 10906-1.0-00 [DIRS 162672]) input: 
delta 1.3 ft 
title Input data for the Hsu inverse thermal conductivity model 
title Boreholes NRG4, NRG5, NRG6 and NRG7 
title March 13, 2003 
colhead Sample Porosity Dry Wet Por table/row TC 
table 
colhead ------------------+----------+---------+---------+----------+----+---- 
-----+ 
porinputfile s98424_003.txt 
porsample out 1 18 in sample 
porosity out 21 29 in porosity 
portable out 51 60 in $inputfile 
porrow out 62 66 in row 
readpor 
tcinputfile s96370_001.txt 
tctemp out 0 0 in temperature 
tcond out 0 0 in 'thermal ' 
drythermalcond out 30 38 in 'thermal ' 
! for experiment = 'oven dry' 
wetthermalcond out 39 47 in 'thermal ' 
! for experiment = 'vacuum sat' 
tctest out 0 0 in test 
tcsample out 0 0 in sample 
tctable out 67 76 in $inputfile 
readtc 
outputfile nrghsuinv.inp 
Source: STN 10906-1.0-00 [DIRS 162672]. 
NOTES: The colhead command lines exceed the width of this page and do not wrap in the original data file. 
Por is an abbreviation for porosity. 
TC is an abbreviation for thermal conductivity. 
The delta 1.3 ft line allows a difference of 1.3 feet in the porosity and thermal conductivity sample depths. 
This appendix is a copy of data file Inputs\HsuInv\nrgsplice.inp, dated 3/13/03, 1:10PM, 938 bytes. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 B-2 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX C 
REFORMAT INPUT CONTROL FILE FOR POROSITY DATA 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 C-1 October 2004 
Table C-1. Input DTN List 
DTN Renamed Program Input File 
MO0109HYMXPROP.001 [DIRS 155989] s01144_001.txt 
REFORMAT (STN 10907-2.0-00 [DIRS 162673]) input: 
inputfile s01144_001.txt 
outputfile r01144_001.txt 
colhead **************************************** 
colhead row# sample number porosity 
colhead **************************************** 
colhead 
field out 1 4 in row 
field out 9 13 in location 
replace 'USW SD-7' ' SD7-' 
replace 'USW SD-9' ' SD9-' 
replace 'USW SD-12' 'SD12-' 
keep ' SD' 'SD' 
!field "sample" contains depth in feet 
field out 14 20 in sample 
bounds 1400 1900 
field out 28 33 in porosity 
Sources: STN 10907-2.0-00 [DIRS 162673], 
DTN MO0109HYMXPROP.001 [DIRS 155989]. 
NOTE: This appendix is a copy of data file Inputs\HsuInv\ref_01144_001.inp, dated 2/14/03 4:02PM, 493 bytes. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 C-2 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX D 
REFORMAT INPUT CONTROL FILE FOR THERMAL CONDUCTIVITY DATA 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 D-1 October 2004 
Table D-1. Input DTN List 
DTN Renamed Program Input File 
SNL22100196001.006 [DIRS 158213] s98169_002.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
inputfile s98169_002.txt 
outputfile r98169_002.txt 
colhead ************************************************* 
colhead row# sample test condition temperature thermal cond 
colhead ************************************************* 
colhead 
field out 1 4 in row 
field out 12 26 in sample 
field out 28 49 in saturation 
replace '0/' 'oven dry 110.' 
replace '1/' 'oven dry 110.' 
replace '2/' 'oven dry 110.' 
replace '97/' 'vacuum saturated 70.' 
replace '98/' 'vacuum saturated 70.' 
replace '99/' 'vacuum saturated 70.' 
keep oven vacuum 
field out 59 64 in thermal 
Source: STN 10907-2.0-00 [DIRS 162672]. 
NOTES: 1. The second colhead command line exceeds the width of this page and does not wrap in the original 
data file. 
2. This appendix is a copy of data file Inputs\HsuInv\ref_98169_002.inp, dated 2/14/03 3:13AM, 655 bytes. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 D-2 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX E 
PROGRAM SPLICE INPUT CONTROL DATA FOR 
SD7, SD9, AND SD12 BOREHOLES 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 E-1 October 2004 
Table E-1. Input DTN List 
DTN Renamed Program Input File 
MO0109HYMXPROP.001 [DIRS 155989] r01144_001.txt 
SNL22100196001.006 [DIRS 158213] r98169_002.txt 
SPLICE (STN: 10906-1.0-00 [DIRS 162672]) input: 
delta 1.3 ft 
title Input data for the Hsu inverse thermal conductivity model 
title Boreholes SD7, SD9, SD12 
title March 13, 2003 
colhead Sample Porosity Dry Wet Por table/row TC 
table 
colhead ------------------+----------+---------+---------+----------+----+---- 
-----+ 
porinputfile r01144_001.txt 
porsample out 1 18 in sample 
porosity out 21 29 in porosity 
portable out 51 60 in $inputfile 
porrow out 62 66 in row 
readpor 
tcinputfile r98169_002.txt 
tctemp out 0 0 in temperature 
tcond out 0 0 in 'thermal ' 
drythermalcond out 30 38 in 'thermal ' 
! for experiment = 'oven dry' 
wetthermalcond out 39 47 in 'thermal ' 
! for experiment = 'vacuum sat' 
tctest out 0 0 in test 
tcsample out 0 0 in sample 
tctable out 67 76 in $inputfile 
readtc 
outputfile sdhsuinv.inp 
Sources: STN 10907-2.00 [DIRS 162673], DTN SNL22100196001.006 ([DIRS 158213] s98169_002). 
NOTES: 
1. The colhead command lines exceed the width of this page and do not wrap in the original data file. 
2. Por is an abbreviation for porosity. 
3. TC is an abbreviation for thermal conductivity. 
4. This appendix is a copy of data file Inputs\HsuInv\sdsplice.inp, dated 3/13/03, 1:19PM, 926 bytes.

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 E-2 October 2004 
INTENTIONALLY LEFT BLANK

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX F 
REFORMAT INPUT CONTROL FILE TO APPEND 
LITHOSTRATIGRAPHY TO HSUINV OUTPUT

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 F-1 October 2004 
Table F-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] lithostratigraphy.txt 
SNF40060298001.001 [DIRS 107372] lithostratigraphy.txt 
SNL01A05059301.007 [DIRS 108980] nrghsuinvout.txt 
SNL01A05059301.005 [DIRS 109002] nrghsuinvout.txt 
MO0109HYMXPROP.001 [DIRS 155989] sdhsuinvout.txt 
SNL22100196001.006 [DIRS 158213] sdhsuinvout.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
lsfile ..\lithostratigraphy.txt 
outputfile lhsuinv.out 
start template 1 
colhead ************************************************* 
colhead phi ks gc sample lithostratigraphy 
colhead ************************************************* 
colhead 
!copy porosity 
field out 1 10 in phi 
!copy solid thermal conductivity 
field out 12 20 in ks 
!copy gamma_c 
field out 23 32 in gc 
!copy sample 
field out 34 49 in 34 49 
!determine lithostratigrapy from sample number: 
lithostrat 52 58 samplenum 34 49 
end template 1 
inputfile nrghsuinvout.txt 
run template 1 
start template 2 
!copy porosity 
field out 1 10 in phi 
!copy solid thermal conductivity 
field out 12 20 in ks 
!copy gamma_c 
field out 23 32 in gc 
!copy sample 
field out 34 49 in 34 49 
!determine lithostratigrapy from sample number: 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 F-2 October 2004 
lithostrat 52 58 samplenum 34 49 
end template 2 
inputfile sdhsuinvout.txt 
run template 2 
Sources: STN 10907-2.0-00 [DIRS 162673], 
STN 10804-1.0-00 [DIRS 158228]. 
NOTES: 1. The colhead lines exceed the width of this page and do not wrap in the original data file. 
2. This appendix is a copy of data file Inputs\HsuInv\ref_hsu_litho.inp, dated 2/17/03, 4:49PM, 984 
bytes. 
3. Renamed program input files correspond to input files listed for Table 4-2 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX G 
REFORMAT INPUT CONTROL FILE FOR HSUINV OUTPUT 
SEPARATION BY PARAMETER AND LAYER GROUPS

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 G-1 October 2004 
Table G-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] lhsuinv.out 
SNF40060298001.001 [DIRS 107372] lhsuinv.out 
SNL01A05059301.007 [DIRS 108980] lhsuinv.out 
SNL01A05059301.005 [DIRS 109002] lhsuinv.out 
MO0109HYMXPROP.001 [DIRS 155989] lhsuinv.out 
SNL22100196001.006 [DIRS 158213] lhsuinv.out 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
inputfile lhsuinv.out 
start template 1 
title Welded layers 
title 1 
title Solid thermal conductivity 
field out 1 10 in ks 
field out 11 16 in lithos 
KEEP Qa Tmr Tpc_un Tpk Tptrn Tptrl 'Tptp ' Tptf 
KEEP Tcpm Tcbm Tctm RHH 
!append sample number: 
field out 20 35 in 34 49 
end template 1 
outputfile weldedks.dat 
run template 1 
start template 2 
title Welded layers 
title 1 
title Gamma_c 
field out 1 10 in gc 
field out 11 16 in lithos 
KEEP Qa Tmr Tpc_un Tpk Tptrn Tptrl 'Tptp ' Tptf 
KEEP Tcpm Tcbm Tctm RHH 
!append sample number: 
field out 20 35 in 34 49 
end template 2 
outputfile weldedgc.dat 
run template 2 
start template 3 
title Non-welded layers 
title 1 
title Solid thermal conductivity 
field out 1 10 in ks 
field out 11 16 in lithos 
KEEP Tpcrv3 Tpcpv1 Tpbt4 Tpy Tpbt3 Tpp Tpbt2 Tptrv3 Tptpv1 Tpbt1 
KEEP Pah Yucca Tpcpv2 Tptrv2 Tptpv2 
!append sample number: 
field out 20 35 in 34 49 
end template 3 
outputfile nonweldedks.dat 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 G-2 October 2004 
run template 3 
start template 4 
title Non-welded layers 
title 1 
title Gamma_c 
field out 1 10 in gc 
field out 11 16 in lithos 
KEEP Tpcrv3 Tpcpv1 Tpbt4 Tpy Tpbt3 Tpp Tpbt2 Tptrv3 Tptpv1 Tpbt1 
KEEP Pah Yucca Tpcpv2 Tptrv2 Tptpv2 
!append sample number: 
field out 20 35 in 34 49 
end template 4 
outputfile nonweldedgc.dat 
run template 4 
start template 5 
title Vitric layers 
title 1 
title Solid thermal conductivity 
field out 1 10 in ks 
field out 11 16 in lithos 
KEEP Tpcpv3 Tptrv1 Tptpv3 
!append sample number: 
field out 20 35 in 34 49 
end template 5 
outputfile vitricks.dat 
run template 5 
start template 6 
title Vitric layers 
title 1 
title Gamma_c 
field out 1 10 in gc 
field out 11 16 in lithos 
KEEP Tpcpv3 Tptrv1 Tptpv3 
!append sample number: 
field out 20 35 in 34 49 
end template 6 
outputfile vitricgc.dat 
run template 6 
start template 7 
title Calico Hills layers 
title 1 
title Solid thermal conductivity 
field out 1 10 in ks 
field out 11 16 in lithos 
KEEP Tac V-Z 
!append sample number: 
field out 20 35 in 34 49 
end template 7 
outputfile calicoks.dat 
run template 7 
start template 8 
title Calico Hills layers 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 G-3 October 2004 
title 1 
title Gamma_c 
field out 1 10 in gc 
field out 11 16 in lithos 
KEEP Tac V-Z 
!append sample number: 
field out 20 35 in 34 49 
end template 8 
outputfile calicogc.dat 
run template 8 
Source: STN 10907-2.00 [DIRS 162673]. 
NOTES: 
1. This appendix is a copy of data file Inputs\HsuInv\ref_hsu_layers.inp, dated 3/13/03, 2:25PM, 2473 
bytes. 
2. Renamed program input files correspond to input files listed for Table 4-2 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 G-4 October 2004 
INTENTIONALLY LEFT BLANK

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX H 
APPROXIMATIONS TO EXPONENTIAL DISTRIBUTION 
GROWTH AND DECAY RATES 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 H-1 October 2004 
The probability density for the exponential probability distribution (Bulmer 1979 
[DIRS 111961], p. 97) is given by 
( ) x e c x f . = 
When this distribution is used to approximate the .c and fm distributions, x is in the interval 
[0, 1]. The constant c is found by normalizing the integral of f(x) on the interval [0, 1]: 
( ) 
1
0 
1
0 
.. 
. 
.. 
. = . x e c dx x f . 
. 
= 1 
so 
( ) 1 1 = - . 
. 
e c 
Then 
( ) 1 - 
= . 
. 
e 
c 
The mean  is given by 
( ) 
1
0 
1
0 
1
0 
2 
1 . . .. 
. 
.. 
. 
.. 
. 
.. 
. - = = = x e x c dx e x c dx x f x x . 
. . 
 . 
Then 
( ) 
( ) 1 
/ 1 / 1 1 
- 
+ - 
= . 
. . . 
 
e 
e (Eq. H-1) 
When the exponential distribution is used as an approximation to .c, . is positive and  is usually 
greater than 0.7. To achieve this mean on the interval [0, 1], the exponential distribution must 
increase sharply near x=1. This means that . is a relatively large positive number. Dividing the 
numerator and denominator of Equation H-1 by e.: 
( ) 
. 
. . . 
 - 
- 
- 
+ - 
= 
e 
e 
1 
/ / 1 1 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 H-2 October 2004 
Approximating e-. as zero, 
.. 
. 
.. 
. - = 
. 
 1 1 
so 
( )  
. 
- 
= 
1 
1 (Eq. H-2) 
For non-welded gamma_c,  = 0.9046. Using Equation H-2 with this mean, . = 10.482. A more 
precise value of . can be found by using Equation H-1 to make a table of values of  for values 
of . at and around . = 10.482: 
.  
10.478 0.90459 
10.480 0.90461 
10.482 0.90463 
10.484 0.90464 
It is apparent from this table that when  = 0.9046 the appropriate value of . is 10.479. 
When the exponential distribution is used as an approximation to the vitric porosity data,  is 
0.036. To achieve this small a mean on the interval [0, 1], the exponential distribution must 
decrease sharply near x=1. This means that . is a relatively large negative number. In this case, 
e. can be approximated as 0, and Equation H-1 becomes: 
. 
 1 - = 
so 
 
. 1 - = (Eq. H-3) 
For vitric porosity,  = 0.036. Using Equation H-3 with this mean, . = -27.778, a more precise 
value of . can be found by using Equation H-1 to make a table of values of  for values of . at 
and around . = -27.778. 
.  
-27.776 0.03600 
-27.778 0.03600 
-27.780 0.03600 
It is apparent from this table that  is not very sensitive to small changes in ., so the initial 
approximation . = -27.778 is adequate to 5 significant digits. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX I 
REFORMAT INPUT CONTROL FILE TO EXTRACT MATRIX POROSITY FOR 
MODEL FROM SITE AND ENGINEERING PROPERTIES TABLES

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 I-1 October 2004 
Table I-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] lithostratigraphy.txt 
SNF40060298001.001 [DIRS 107372] lithostratigraphy.txt 
SNL01A05059301.007 [DIRS 108980] s98424_003.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_001.txt 
GS000508312231.006 [DIRS 153237] s00415_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_005.txt 
SNL02030193001.022 [DIRS 109613] s99111_001.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
lsfile ..\lithostratigraphy.txt 
outputfile mporosity.txt 
start template 1 
title QUALIFIED POROSITY DATA FOR MODEL CONSTRUCTION 
colhead ****************************************** 
colhead porosity litho- location datasource row# 
colhead strati- (borehole id 
colhead graphy + depth (ft)) 
colhead ****************************************** 
colhead 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location 
field out 21 40 in sample 
!datasource 
field out 46 55 in $inputfile 
!row number 
field out 60 63 in row 
end template 1 
inputfile s98424_003.txt 
run template 1 
start template 2 
!porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 I-2 October 2004 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from borehole id and depth: 
lithostrat 11 18 bid location depth sample 
! well id 
field out 21 33 in location 
keep "USW SD-7" "USW SD-9" "USW SD-12" 
keep "USW NRG-6" "USW NRG-7" 
! depth in ft 
field out 35 40 in sample 
!datasource 
field out 46 55 in $inputfile 
!row number 
field out 60 63 in row 
end template 2 
inputfile s01144_001.txt 
run template 2 
start template 3 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from borehole id and depth: 
lithostrat 11 18 bid location depth depth 
! well id 
field out 21 30 in location 
! depth in ft 
field out 32 40 in depth 
!datasource 
field out 46 55 in $inputfile 
!row number 
field out 60 63 in row 
!test description 
field out 68 74 in experiment 
keep RH 
end template 3 
inputfile s00415_001.txt 
run template 3 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 I-3 October 2004 
start template 4 
!porosity 
field out 1 8 in porosity 
scale 0.01 
numeric 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location 
field out 21 40 in sample 
!datasource 
field out 46 55 in $inputfile 
!row number 
field out 60 63 in row 
end template 4 
inputfile s98484_001.txt 
run template 4 
start template 5 
!porosity 
field out 1 8 in porosity 
scale 0.01 
numeric 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location 
field out 21 40 in sample 
!datasource 
field out 46 55 in $inputfile 
!row number 
field out 60 63 in row 
end template 5 
inputfile s98484_005.txt 
run template 5 
start template 6 
!porosity 
field out 1 8 in porosity 
scale 0.01 
numeric 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 I-4 October 2004 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location 
field out 21 40 in sample 
!datasource 
field out 46 55 in $inputfile 
!row number 
field out 60 63 in row 
end template 6 
inputfile s99111_001.txt 
run template 6 
Sources: STN 10907-2.0-00 [DIRS 162673], DTN GS000508312231.006 [DIRS 153237] S00415_001, 
DTN MO0109HYMXPROP.001 [DIRS 155989] s01144_001 (file DATAQ.zip), 
DTN SNL01A05059301.007 [DIRS 108980] s98424_003, 
DTN SNL02030193001.002 [DIRS 120575] S98484_001 and S98484_005, and 
DTN SNL02030193001.022 [DIRS 109613] S99111_001. 
NOTE: This appendix is a copy of data file Inputs\QVPorosity\mporosity.inp, dated 3/12/03, 5:51PM, 3024 bytes. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX J 
REFORMAT INPUT CONTROL FILE TO SEPARATE 
MODEL MATRIX POROSITY BY GEOLOGIC UNIT

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 J-1 October 2004 
Table J-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] mporosity.txt 
SNF40060298001.001 [DIRS 107372] mporosity.txt 
SNL01A05059301.007 [DIRS 108980] mporosity.txt 
MO0109HYMXPROP.001 [DIRS 155989] mporosity.txt 
GS000508312231.006 [DIRS 153237] mporosity.txt 
SNL02030193001.002 [DIRS 120575] mporosity.txt 
SNL02030193001.022 [DIRS 109613] mporosity.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
inputfile mporosity.txt 
start template 1 
title POROSITY DATA FOR NON-REPOSITORY WELDED LAYERS ABOVE CALICO HILLS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Qa Tmr Tpc_un Tpk Tptrn Tptrl 'Tptp ' Tptf 
! location 
field out 21 40 in location 
end template 1 
OUTPUTFILE mweldedpor.dat 
run template 1 
start template 2 
title POROSITY DATA FOR NONWELDED LAYERS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 J-2 October 2004 
KEEP Tpcrv3 Tpcpv1 Tpbt4 Tpy Tpbt3 Tpp Tpbt2 Tptrv3 Tptpv1 Tpbt1 
KEEP Pah Yucca Tpcpv2 Tptrv2 Tptpv2 
! location 
field out 21 40 in location 
end template 2 
OUTPUTFILE mnonweldedpor.dat 
run template 2 
start template 3 
title POROSITY DATA FOR VITRIC LAYERS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tpcpv3 Tptrv1 Tptpv3 
! location 
field out 21 40 in location 
end template 3 
OUTPUTFILE mvitricpor.dat 
run template 3 
start template 4 
title POROSITY DATA FOR CALICO LAYERS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tac Tacbt V-Z 
! location 
field out 21 40 in location 
end template 4 
OUTPUTFILE mcalicopor.dat 
run template 4 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 J-3 October 2004 
start template 5 
title POROSITY DATA FOR PROW PASS WELDED LAYERS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tcpm Prowmd 
! location 
field out 21 40 in location 
end template 5 
OUTPUTFILE mprowweldedpor.dat 
run template 5 
start template 6 
title POROSITY DATA FOR PROW PASS NONWELDED LAYERS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tcplc Tcplv Tcpuc Tcpuv Tcpbt Prowuv Prowuc Prowlc Prowlv 
KEEP Prowbt Tcp1 Tcp2 Tcp3 Tcp4 Tcpbt 
! location 
field out 21 40 in location 
end template 6 
OUTPUTFILE mprownonweldedpor.dat 
run template 6 
start template 7 
title POROSITY DATA FOR BULLFROG WELDED LAYERS 
colhead 1 
colhead porosity 
!porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 J-4 October 2004 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tcbm Tcb3 Tcb4 Bullfrogmd 
! location 
field out 21 40 in location 
end template 7 
OUTPUTFILE mbullfrogweldedpor.dat 
run template 7 
start template 8 
title POROSITY DATA FOR BULLFROG NONWELDED LAYERS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tcblv Tcb1 Bullfroguv Bullfroguc Bullfroglc Bullfroglv 
Bullfrogbt 
KEEP Tcblc Tcbuv Tcbuc Tcbbt 
! location 
field out 21 40 in location 
end template 8 
OUTPUTFILE mbullfrognonweldedpor.dat 
run template 8 
start template 9 
title POROSITY DATA FOR TRAM TUFF WELDED LAYERS 
colhead 1 
colhead porosity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 J-5 October 2004 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tctm Trammd 
! location 
field out 21 40 in location 
end template 9 
OUTPUTFILE mtramweldedpor.dat 
run template 9 
start template 10 
title POROSITY DATA FOR TRAM TUFF NONWELDED LAYERS 
colhead 1 
colhead porosity 
!porosity 
field out 1 8 in porosity 
!lithostratigraphy 
field out 11 18 in litho 
KEEP 'Tct ' Tctuv Tctuc Tctlc Tctlv Tctbt Tramuv Tramuc Tramlc 
KEEP Tramlv Trambt 
! location 
field out 21 40 in location 
end template 10 
OUTPUTFILE mtramnonweldedpor.dat 
run template 10 
Source: STN 10907-2.0-00 [DIRS 162673]. 
NOTES: 
1. This appendix is a copy of data file Inputs\QVPorosity\mlayers.inp, dated 3/12/03, 6:07PM, 3905 
bytes. 
2. Renamed program input files correspond to input files listed for Table 4-3 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 J-6 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX K 
REFORMAT INPUT CONTROL FILE TO COMBINE DRY BULK 
DENSITY TABLES AND APPEND LITHOSTRATIGRAPHY

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-1 October 2004 
Table K-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] lithostratigraphy.txt 
SNF40060298001.001 [DIRS 107372] lithostratigraphy.txt 
GS000408312231.004 [DIRS 149582] s00276_001.txt 
GS000508312231.006 [DIRS 153237] s00415_001.txt 
GS950308312231.002 [DIRS 108990] s96015_001.txt 
GS950408312231.004 [DIRS 108986] s96021_001.txt 
GS940508312231.006 [DIRS 107149] s96024_003.txt 
GS930108312231.006 [DIRS 108997] s96025_001.txt 
GS920508312231.012 [DIRS 109001] s96026_001.txt 
GS940408312231.004 [DIRS 109000] s96027_001.txt 
GS951108312231.009 [DIRS 108984] s96037_001.txt 
GS951108312231.011 [DIRS 108992] s96049_001.txt 
GS960808312231.004 [DIRS 108985] s97058_001.txt 
GS980708312242.010 [DIRS 106752] s98248_004.txt 
GS980808312242.014 [DIRS 106748] s98285_001.txt 
GS951108312231.010 [DIRS 108983] s96046_001.txt 
GS920408312314.011 [DIRS 129660] s97135_002.txt 
GS930408312132.007 [DIRS 129625] s97276_001.txt 
SNL01A05059301.007 [DIRS 108980] s98424_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_002.txt 
SNL02030193001.002 [DIRS 120575] s98484_004.txt 
SNL02030193001.002 [DIRS 120575] s98484_005.txt 
SNL02030193001.004 [DIRS 108415] s98485_001.txt 
SNL02030193001.004 [DIRS 108415] s98485_003.txt 
SNL02030193001.008 [DIRS 120597] s98486_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_004.txt 
SNL02030193001.006 [DIRS 120579] s99101_001.txt 
SNL02030193001.006 [DIRS 120579] s99101_004.txt 
SNL02030193001.013 [DIRS 120614] s99104_001.txt 
SNL02030193001.013 [DIRS 120614] s99104_004.txt 
SNL02030193001.005 [DIRS 122545] s99105_001.txt 
SNL02030193001.005 [DIRS 122545] s99105_004.txt 
SNL02030193001.007 [DIRS 120582] s99106_001.txt 
SNL02030193001.014 [DIRS 109609] s99107_001.txt 
SNL02030193001.014 [DIRS 109609] s99107_004.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-2 October 2004 
Table K-1. Input DTN List (Continued) 
DTN Renamed Program Input File 
SNL02030193001.015 [DIRS 120617] s99108_001.txt 
SNL02030193001.009 [DIRS 109614] s99109_001.txt 
SNL02030193001.012 [DIRS 108416] s99110_001.txt 
SNL02030193001.022 [DIRS 109613] s99111_002.txt 
SNL02030193001.016 [DIRS 120619] s99112_001.txt 
SNL02030193001.017 [DIRS 109610] s99113_001.txt 
SNL02030193001.018 [DIRS 109611] s99114_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_002.txt 
SNL02030193001.020 [DIRS 108432] s99116_001.txt 
SNL02030193001.020 [DIRS 108432] s99116_004.txt 
SNL02030193001.021 [DIRS 108433] s99117_001.txt 
SNL01A05059301.002 [DIRS 150042] s99435_001.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
lsfile ..\lithostratigraphy.txt 
outputfile dbd.txt 
start template 1 
title Qualified, verified dry bulk density 
colhead ******************************************************************** 
colhead dry litho- borehole datasource row experiment 
colhead bulk straticolhead 
density graphy 
colhead (g/cc) 
colhead ******************************************************************** 
colhead 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 18 samplenum depth 
!borehole 
field out 20 34 in location 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
!test type 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-3 October 2004 
field out 56 62 in experiment 
keep RH 
end template 1 
inputfile s00276_001.txt 
run template 1 
start template 2 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 16 bid location depth depth 
!borehole 
field out 20 34 in location 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
!test type 
field out 56 62 in experiment 
keep RH 
end template 2 
inputfile s00415_001.txt 
run template 2 
start template 3 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 16 samplenum sample 
!borehole 
field out 20 34 in location 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
!test type 
field out 56 62 in experiment 
keep RH 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-4 October 2004 
end template 3 
inputfile s96015_001.txt 
run template 3 
inputfile s96021_001.txt 
run template 3 
inputfile s96024_003.txt 
run template 3 
inputfile s96025_001.txt 
run template 3 
inputfile s96026_001.txt 
run template 3 
inputfile s96027_001.txt 
run template 3 
inputfile s96037_001.txt 
run template 3 
inputfile s96049_001.txt 
run template 3 
inputfile s97058_001.txt 
run template 3 
inputfile s98248_004.txt 
run template 3 
inputfile s98285_001.txt 
run template 3 
start template 4 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 16 bid location depthm depth 
!borehole 
field out 20 34 in location 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
!test type 
field out 56 62 in experiment 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-5 October 2004 
keep RH 
end template 4 
inputfile s96046_001.txt 
run template 4 
start template 5 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 16 bid location depthm depth 
!borehole 
field out 20 34 in location 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
end template 5 
inputfile s97135_002.txt 
run template 5 
inputfile s97276_001.txt 
run template 5 
start template 6 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 16 samplenum sample 
!borehole 
field out 20 34 in location 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
end template 6 
inputfile s98424_001.txt 
run template 6 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-6 October 2004 
inputfile s98484_001.txt 
run template 6 
inputfile s98484_002.txt 
run template 6 
inputfile s98484_004.txt 
run template 6 
inputfile s98484_005.txt 
run template 6 
inputfile s98485_001.txt 
run template 6 
inputfile s98485_003.txt 
run template 6 
inputfile s98486_001.txt 
run template 6 
inputfile s99100_001.txt 
run template 6 
inputfile s99100_004.txt 
run template 6 
inputfile s99101_001.txt 
run template 6 
inputfile s99101_004.txt 
run template 6 
inputfile s99104_001.txt 
run template 6 
inputfile s99104_004.txt 
run template 6 
inputfile s99105_001.txt 
run template 6 
inputfile s99105_004.txt 
run template 6 
inputfile s99106_001.txt 
run template 6 
inputfile s99107_001.txt 
run template 6 
inputfile s99107_004.txt 
run template 6 
inputfile s99108_001.txt 
run template 6 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-7 October 2004 
inputfile s99109_001.txt 
run template 6 
inputfile s99110_001.txt 
run template 6 
inputfile s99111_002.txt 
run template 6 
inputfile s99112_001.txt 
run template 6 
inputfile s99113_001.txt 
run template 6 
inputfile s99114_001.txt 
run template 6 
inputfile s99115_001.txt 
run template 6 
inputfile s99115_002.txt 
run template 6 
start template 7 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 16 bid location depth depth 
!borehole 
field out 20 34 in location 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
end template 7 
inputfile s99116_001.txt 
run template 7 
inputfile s99116_004.txt 
run template 7 
inputfile s99117_001.txt 
run template 7 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 K-8 October 2004 
start template 8 
!dry bulk density 
field out 1 8 in dry 
numeric 
!lithostratigraphy 
lithostrat out 11 16 samplenum sample 
!borehole 
field out 20 24 in sample 
!datasource 
field out 36 45 in $inputfile 
!row 
field out 49 53 in row# 
end template 8 
inputfile s99435_001.txt 
run template 8 
Source: STN 10907-2.0-00 [DIRS 162673]. 
NOTE: This appendix is a copy of data file Inputs\QVDryBulkDens\reformat_dbd.inp, dated 3/12/03, 11:46AM, 5180 
bytes. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX L 
REFORMAT INPUT CONTROL FILE FOR DRY BULK DATA 
SEPARATION BY LAYER GROUPS 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 L-1 October 2004 
Table L-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] dbd.txt 
SNF40060298001.001 [DIRS 107372] dbd.txt 
GS000408312231.004 [DIRS 149582] dbd.txt 
GS000508312231.006 [DIRS 153237] dbd.txt 
GS950308312231.002 [DIRS 108990] dbd.txt 
GS950408312231.004 [DIRS 108986] dbd.txt 
GS940508312231.006 [DIRS 107149] dbd.txt 
GS930108312231.006 [DIRS 108997] dbd.txt 
GS920508312231.012 [DIRS 109001] dbd.txt 
GS940408312231.004 [DIRS 109000] dbd.txt 
GS951108312231.009 [DIRS 108984] dbd.txt 
GS951108312231.011 [DIRS 108992] dbd.txt 
GS960808312231.004 [DIRS 108985] dbd.txt 
GS980708312242.010 [DIRS 106752] dbd.txt 
GS980808312242.014 [DIRS 106748] dbd.txt 
GS951108312231.010 [DIRS 108983] dbd.txt 
GS920408312314.011 [DIRS 129660] dbd.txt 
GS930408312132.007 [DIRS 129625] dbd.txt 
SNL01A05059301.007 [DIRS 108980] dbd.txt 
SNL02030193001.002 [DIRS 120575] dbd.txt 
SNL02030193001.002 [DIRS 120575] dbd.txt 
SNL02030193001.002 [DIRS 120575] dbd.txt 
SNL02030193001.002 [DIRS 120575] dbd.txt 
SNL02030193001.004 [DIRS 108415] dbd.txt 
SNL02030193001.004 [DIRS 108415] dbd.txt 
SNL02030193001.008 [DIRS 120597] dbd.txt 
SNL02030193001.003 [DIRS 120578] dbd.txt 
SNL02030193001.003 [DIRS 120578] dbd.txt 
SNL02030193001.006 [DIRS 120579] dbd.txt 
SNL02030193001.006 [DIRS 120579] dbd.txt 
SNL02030193001.013 [DIRS 120614] dbd.txt 
SNL02030193001.013 [DIRS 120614] dbd.txt 
SNL02030193001.005 [DIRS 122545] dbd.txt 
SNL02030193001.005 [DIRS 122545] dbd.txt 
SNL02030193001.007 [DIRS 120582] dbd.txt 
SNL02030193001.014 [DIRS 109609] dbd.txt 
SNL02030193001.014 [DIRS 109609] dbd.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 L-2 October 2004 
Table L-1. Input DTN List (Continued) 
DTN Renamed Program Input File 
SNL02030193001.015 [DIRS 120617] dbd.txt 
SNL02030193001.009 [DIRS 109614] dbd.txt 
SNL02030193001.012 [DIRS 108416] dbd.txt 
SNL02030193001.022 [DIRS 109613] dbd.txt 
SNL02030193001.016 [DIRS 120619] dbd.txt 
SNL02030193001.017 [DIRS 109610] dbd.txt 
SNL02030193001.018 [DIRS 109611] dbd.txt 
SNL02030193001.019 [DIRS 108431] dbd.txt 
SNL02030193001.019 [DIRS 108431] dbd.txt 
SNL02030193001.020 [DIRS 108432] dbd.txt 
SNL02030193001.020 [DIRS 108432] dbd.txt 
SNL02030193001.021 [DIRS 108433] dbd.txt 
SNL01A05059301.002 [DIRS 150042] dbd.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
! This Reformat input control file generates dry bulk density files by 
! geologic layer group (welded, non-welded, ...) that are suitable as 
! input files for program histplt (histogram plotter). 
inputfile dbd.txt 
start template 1 
title DRY BULK DENSITY DATA FOR NON-REPOSITORY WELDED LAYERS ABOVE CALICO 
HILLS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Qa Tmr Tpc_un Tpk Tptrn Tptrl 'Tptp ' Tptf 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 1 
OUTPUTFILE weldeddbd.dat 
run template 1 
start template 2 
title DRY BULK DENSITY DATA FOR NONWELDED LAYERS 
colhead 1 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 L-3 October 2004 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tpcrv3 Tpcpv1 Tpbt4 Tpy Tpbt3 Tpp Tpbt2 Tptrv3 Tptpv1 Tpbt1 
KEEP Pah Yucca Tpcpv2 Tptrv2 Tptpv2 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 2 
OUTPUTFILE nonweldeddbd.dat 
run template 2 
start template 3 
title DRY BULK DENSITY DATA FOR VITRIC LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tpcpv3 Tptrv1 Tptpv3 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 3 
OUTPUTFILE vitricdbd.dat 
run template 3 
start template 4 
title DRY BULK DENSITY DATA FOR CALICO LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tac Tacbt V-Z 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 L-4 October 2004 
end template 4 
OUTPUTFILE calicodbd.dat 
run template 4 
start template 5 
title DRY BULK DENSITY DATA FOR PROW PASS WELDED LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tcpm Prowmd 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 5 
OUTPUTFILE prowweldeddbd.dat 
run template 5 
start template 6 
title DRY BULK DENSITY DATA FOR PROW PASS NONWELDED LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tcplc Tcplv Tcpuc Tcpuv Tcpbt Prowuv Prowuc Prowlc Prowlv 
KEEP Prowbt Tcpbt 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 6 
OUTPUTFILE prownonweldeddbd.dat 
run template 6 
start template 7 
title DRY BULK DENSITY DATA FOR BULLFROG WELDED LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 L-5 October 2004 
field out 11 18 in litho 
KEEP Tcbm Bullfrogmd 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 7 
OUTPUTFILE bullfrogweldeddbd.dat 
run template 7 
start template 8 
title DRY BULK DENSITY DATA FOR BULLFROG NONWELDED LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tcblv Bullfroguv Bullfroguc Bullfroglc Bullfroglv Bullfrogbt 
KEEP Tcblc Tcbuv Tcbuc Tcbbt 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 8 
OUTPUTFILE bullfrognonweldeddbd.dat 
run template 8 
start template 9 
title DRY BULK DENSITY DATA FOR TRAM TUFF WELDED LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP Tctm Trammd 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 9 
OUTPUTFILE tramweldeddbd.dat 
run template 9 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 L-6 October 2004 
start template 10 
title DRY BULK DENSITY DATA FOR TRAM TUFF NONWELDED LAYERS 
colhead 1 
colhead dry bulk density 
! dry bulk density 
field out 1 8 in dry 
!lithostratigraphy 
field out 11 18 in litho 
KEEP 'Tct ' Tctuv Tctuc Tctlc Tctlv Tctbt Tramuv Tramuc Tramlc 
KEEP Tramlv Trambt 
! location 
field out 21 40 in borehole 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 10 
OUTPUTFILE tramnonweldeddbd.dat 
run template 10 
Source: STN 10907-2.0-00 [DIRS 162673]. 
NOTES: 
1. This appendix is a copy of data file Inputs\QVDryBulkDens\dbdlayers.inp, dated 3/28/03, 3:44 PM, 5063 bytes. 
3. Renamed program input files correspond to input files listed for Table 4-5 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX M 
REFORMAT INPUT CONTROL FILE TO COMBINE POROSITY TABLES AND 
APPEND LITHOSTRATIGRAPHY FOR MODEL VALIDATION

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-1 October 2004 
Table M-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] lithostratigraphy.txt 
SNF40060298001.001 [DIRS 107372] lithostratigraphy.txt 
GS000408312231.004 [DIRS 149582] s00276_001.txt 
MO0012POROCHOL.000 [DIRS 153376] s00452_001.txt 
SNL02030193001.020 [DIRS 108432] s99116_001.txt 
SNL02030193001.020 [DIRS 108432] s99116_004.txt 
SNL02030193001.020 [DIRS 108432] s99116_006.txt 
SNL02030193001.021 [DIRS 108433] s99117_001.txt 
SNL02030193001.021 [DIRS 108433] s99117_005.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_001.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_032.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_033.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_034.txt 
GS950308312231.002 [DIRS 108990] s96015_001.txt 
GS950308312231.002 [DIRS 108990] s96015_002.txt 
GS950408312231.004 [DIRS 108986] s96021_002.txt 
GS940508312231.006 [DIRS 107149] s96024_002.txt 
GS930108312231.006 [DIRS 108997] s96025_002.txt 
GS920508312231.012 [DIRS 109001] s96026_002.txt 
GS940408312231.004 [DIRS 109000] s96027_002.txt 
GS951108312231.009 [DIRS 108984] s96037_002.txt 
GS951108312231.011 [DIRS 108992] s96049_001.txt 
GS960808312231.004 [DIRS 108985] s97058_002.txt 
GS920408312314.011 [DIRS 129660] s97135_007.txt 
GS930408312132.007 [DIRS 129625] s97276_003.txt 
GS980708312242.010 [DIRS 106752] s98248_006.txt 
GS980808312242.014 [DIRS 106748] s98285_002.txt 
GS951108312231.010 [DIRS 108983] s96046_001.txt 
SNL02030193001.001 [DIRS 120572] s98483_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_002.txt 
SNL02030193001.002 [DIRS 120575] s98484_004.txt 
SNL02030193001.004 [DIRS 108415] s98485_001.txt 
SNL02030193001.004 [DIRS 108415] s98485_003.txt 
SNL02030193001.004 [DIRS 108415] s98485_005.txt 
SNL02030193001.008 [DIRS 120597] s98486_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_004.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-2 October 2004 
Table M-1. Input DTN List (Continued) 
DTN Renamed Program Input File 
SNL02030193001.006 [DIRS 120579] s99101_001.txt 
SNL02030193001.006 [DIRS 120579] s99101_004.txt 
SNL02030193001.013 [DIRS 120614] s99104_001.txt 
SNL02030193001.013 [DIRS 120614] s99104_004.txt 
SNL02030193001.013 [DIRS 120614] s99104_005.txt 
SNL02030193001.005 [DIRS 122545] s99105_001.txt 
SNL02030193001.005 [DIRS 122545] s99105_004.txt 
SNL02030193001.007 [DIRS 120582] s99106_001.txt 
SNL02030193001.015 [DIRS 120617] s99108_001.txt 
SNL02030193001.009 [DIRS 109614] s99109_001.txt 
SNL02030193001.009 [DIRS 109614] s99109_002.txt 
SNL02030193001.012 [DIRS 108416] s99110_001.txt 
SNL02030193001.022 [DIRS 109613] s99111_002.txt 
SNL02030193001.016 [DIRS 120619] s99112_001.txt 
SNL02030193001.017 [DIRS 109610] s99113_001.txt 
SNL02030193001.017 [DIRS 109610] s99113_003.txt 
SNL02030193001.018 [DIRS 109611] s99114_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_002.txt 
SNL02030193001.028 [DIRS 159972] s99121_001.txt 
SNL01A05059301.002 [DIRS 150042] s99435_001.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
lsfile ../../lithostratigraphy.txt 
outputfile vporosity.txt 
start template 1 
title QUALIFIED POROSITY DATA FOR MODEL VALIDATION 
colhead ****************************************** 
colhead porosity litho- location datasource row# 
colhead strati- (borehole id 
colhead graphy + depth (ft)) 
colhead ****************************************** 
colhead 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from sample number (in the depth field): 
lithostrat 11 18 samplenum depth 
! location is in the depth field: 
field out 21 40 in depth 
!datasource 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-3 October 2004 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 1 
inputfile s00276_001.txt 
run template 1 
start template 2 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from borehole id and depth: 
lithostrat 11 18 bid location depth depth 
! well id 
field out 21 31 in location 
! depth in ft 
field out 33 40 in depth 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 2 
!inputfile s00415_001.txt 
!run template 2 
start template 3 
!porosity (in %) 
field out 1 8 in porosity 
numeric 
scale 0.01 
!determine lithostratigrapy from borehole id and depth: 
lithostrat 11 18 bid location depth depth 
! well id 
field out 21 31 in location 
! depth in ft 
field out 33 40 in depth 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 3 
inputfile s00452_001.txt 
run template 3 
inputfile s99116_001.txt 
run template 3 
inputfile s99116_004.txt 
run template 3 
inputfile s99116_006.txt 
run template 3 
inputfile s99117_001.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-4 October 2004 
run template 3 
inputfile s99117_005.txt 
run template 3 
start template 4 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from borehole id and depth: 
lithostrat 11 18 bid location depth sample 
! well id 
field out 21 32 in location 
replace "USW NRG-7" "USW NRG-7" 
keep "UE-25 UZ #16" "USW NRG-6" "USW NRG-7" "USW SD-12" "USW UZ-14" 
keep "USW UZ-7a" "USW UZ-N11" "USW UZ-N15" "USW UZ-N16" "USW UZ-N17" 
keep "USW UZ-N27" "USW UZ-N31" "USW UZ-N32" "USW UZ-N33" "USW UZN34" 
keep "USW UZ-N35" "USW UZ-N36" "USW UZ-N37" "USW UZ-N38" "USW UZN53" 
keep "USW UZ-N54" "USW UZ-N55" "USW UZ-N57" "USW UZ-N58" "USW UZN59" 
keep "USW UZ-N61" "USW UZ-N62" "USW UZ-N63" "USW UZ-N64" 
! depth in ft is in the sample designation field 
field out 34 40 in sample 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 4 
inputfile s01144_001.txt 
run template 4 
start template 5 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from borehole id and depth: 
lithostrat 11 18 bid sample depth depth 
! well id is in the sample designation field 
field out 21 28 in sample 
! depth in ft 
field out 30 40 in depth 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 5 
inputfile s01144_032.txt 
run template 5 
inputfile s01144_033.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-5 October 2004 
run template 5 
inputfile s01144_034.txt 
run template 5 
start template 6 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from sample number 
lithostrat 11 18 samplenum sample 
! location is in the depth field: 
field out 21 40 in sample 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 6 
inputfile s96015_001.txt 
run template 6 
inputfile s96015_002.txt 
run template 6 
inputfile s96021_002.txt 
run template 6 
inputfile s96024_002.txt 
run template 6 
inputfile s96025_002.txt 
run template 6 
inputfile s96026_002.txt 
run template 6 
inputfile s96027_002.txt 
run template 6 
inputfile s96037_002.txt 
run template 6 
inputfile s96049_001.txt 
run template 6 
inputfile s97058_002.txt 
run template 6 
inputfile s98248_006.txt 
run template 6 
inputfile s98285_002.txt 
run template 6 
!! inputfile s98424_003.txt was used to build the model 
start template 7 
!porosity 
field out 1 8 in porosity 
numeric 
!determine lithostratigrapy from location + depth 
lithostrat 11 18 bid location depthm depth 
! location is in the depth field: 
field out 21 29 in location 
field out 31 40 in depth 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-6 October 2004 
scale 3.2808 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 7 
inputfile s96046_001.txt 
run template 7 
start template 8 
!porosity in % 
field out 1 8 in porosity 
numeric 
scale 0.01 
!determine lithostratigrapy from sample number 
lithostrat 11 18 samplenum sample 
! location 
field out 21 40 in sample 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 8 
inputfile s98483_001.txt 
run template 8 
!inputfile s98484_001.txt 
!run template 8 
inputfile s98484_002.txt 
run template 8 
inputfile s98484_004.txt 
run template 8 
!inputfile s98484_005.txt 
!run template 8 
inputfile s98485_001.txt 
run template 8 
inputfile s98485_003.txt 
run template 8 
inputfile s98485_005.txt 
run template 8 
inputfile s98486_001.txt 
run template 8 
inputfile s99100_001.txt 
run template 8 
inputfile s99100_004.txt 
run template 8 
inputfile s99101_001.txt 
run template 8 
inputfile s99101_004.txt 
run template 8 
inputfile s99104_001.txt 
run template 8 
inputfile s99104_004.txt 
run template 8 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-7 October 2004 
inputfile s99104_005.txt 
run template 8 
inputfile s99105_001.txt 
run template 8 
inputfile s99105_004.txt 
run template 8 
inputfile s99106_001.txt 
run template 8 
inputfile s99108_001.txt 
run template 8 
inputfile s99109_001.txt 
run template 8 
inputfile s99109_002.txt 
run template 8 
inputfile s99110_001.txt 
run template 8 
!inputfile s99111_001.txt 
!run template 8 
inputfile s99111_002.txt 
run template 8 
inputfile s99112_001.txt 
run template 8 
inputfile s99113_001.txt 
run template 8 
inputfile s99113_003.txt 
run template 8 
inputfile s99114_001.txt 
run template 8 
inputfile s99115_001.txt 
run template 8 
inputfile s99115_002.txt 
run template 8 
inputfile s99121_001.txt 
run template 8 
inputfile s99435_001.txt 
run template 8 
start template 9 
!porosity in % 
field out 1 8 in porosity 
numeric 
scale 0.01 
!determine lithostratigrapy from sample number 
lithostrat 11 18 bid location depthm depth 
! location is in the depth field: 
field out 21 29 in location 
field out 31 40 in depth 
scale 3.2808 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 9 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 M-8 October 2004 
inputfile s97135_007.txt 
run template 9 
inputfile r97276_003.txt 
run template 9 
Source: STN 10907-2.0-00 [DIRS 162673]. 
NOTE: This appendix is a copy of data file Inputs\QVPorosity\vporosity.inp dated 4/7/03, 12:11 PM, 7093 bytes.

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX N 
REFORMAT INPUT CONTROL FILE TO SEPARATE 
POROSITY DATA BY GEOLOGIC LAYER

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 N-1 October 2004 
Table N-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] vporosity.txt 
SNF40060298001.001 [DIRS 107372] vporosity.txt 
GS000408312231.004 [DIRS 149582] vporosity.txt 
MO0012POROCHOL.000 [DIRS 153376] vporosity.txt 
SNL02030193001.020 [DIRS 108432] vporosity.txt 
SNL02030193001.020 [DIRS 108432] vporosity.txt 
SNL02030193001.020 [DIRS 108432] vporosity.txt 
SNL02030193001.021 [DIRS 108433] vporosity.txt 
SNL02030193001.021 [DIRS 108433] vporosity.txt 
MO0109HYMXPROP.001 [DIRS 155989] vporosity.txt 
MO0109HYMXPROP.001 [DIRS 155989] vporosity.txt 
MO0109HYMXPROP.001 [DIRS 155989] vporosity.txt 
MO0109HYMXPROP.001 [DIRS 155989] vporosity.txt 
GS950308312231.002 [DIRS 108990] vporosity.txt 
GS950308312231.002 [DIRS 108990] vporosity.txt 
GS950408312231.004 [DIRS 108986] vporosity.txt 
GS940508312231.006 [DIRS 107149] vporosity.txt 
GS930108312231.006 [DIRS 108997] vporosity.txt 
GS920508312231.012 [DIRS 109001] vporosity.txt 
GS940408312231.004 [DIRS 109000] vporosity.txt 
GS951108312231.009 [DIRS 108984] vporosity.txt 
GS951108312231.011 [DIRS 108992] vporosity.txt 
GS960808312231.004 [DIRS 108985] vporosity.txt 
GS920408312314.011 [DIRS 129660] vporosity.txt 
GS930408312132.007 [DIRS 129625] vporosity.txt 
GS980708312242.010 [DIRS 106752] vporosity.txt 
GS980808312242.014 [DIRS 106748] vporosity.txt 
GS951108312231.010 [DIRS 108983] vporosity.txt 
SNL02030193001.001 [DIRS 120572] vporosity.txt 
SNL02030193001.002 [DIRS 120575] vporosity.txt 
SNL02030193001.002 [DIRS 120575] vporosity.txt 
SNL02030193001.004 [DIRS 108415] vporosity.txt 
SNL02030193001.004 [DIRS 108415] vporosity.txt 
SNL02030193001.004 [DIRS 108415] vporosity.txt 
SNL02030193001.008 [DIRS 120597] vporosity.txt 
SNL02030193001.003 [DIRS 120578] vporosity.txt 
SNL02030193001.003 [DIRS 120578] vporosity.txt 
SNL02030193001.006 [DIRS 120579] vporosity.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 N-2 October 2004 
Table N-1. Input DTN List (Continued) 
DTN Renamed Program Input File 
SNL02030193001.006 [DIRS 120579] vporosity.txt 
SNL02030193001.013 [DIRS 120614] vporosity.txt 
SNL02030193001.013 [DIRS 120614] vporosity.txt 
SNL02030193001.013 [DIRS 120614] vporosity.txt 
SNL02030193001.005 [DIRS 122545] vporosity.txt 
SNL02030193001.005 [DIRS 122545] vporosity.txt 
SNL02030193001.007 [DIRS 120582] vporosity.txt 
SNL02030193001.015 [DIRS 120617] vporosity.txt 
SNL02030193001.009 [DIRS 109614] vporosity.txt 
SNL02030193001.009 [DIRS 109614] vporosity.txt 
SNL02030193001.012 [DIRS 108416] vporosity.txt 
SNL02030193001.022 [DIRS 109613] vporosity.txt 
SNL02030193001.016 [DIRS 120619] vporosity.txt 
SNL02030193001.017 [DIRS 109610] vporosity.txt 
SNL02030193001.017 [DIRS 109610] vporosity.txt 
SNL02030193001.018 [DIRS 109611] vporosity.txt 
SNL02030193001.019 [DIRS 108431] vporosity.txt 
SNL02030193001.019 [DIRS 108431] vporosity.txt 
SNL02030193001.028 [DIRS 159972] vporosity.txt 
SNL01A05059301.002 [DIRS 150042] vporosity.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
! This Reformat input control file generates porosity files by 
! geologic layer group (welded, non-welded, ...) that are suitable as 
! input files for program histplt (histogram plotter). 
inputfile vporosity.txt 
start template 1 
title VALIDATION POROSITY DATA FOR WELDED LAYERS ABOVE CALICO HILLS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Qa Tmr Tpc_un Tpk Tptrn Tptrl 'Tptp ' Tptf 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 1 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 N-3 October 2004 
OUTPUTFILE vweldedpor.dat 
run template 1 
start template 2 
title VALIDATION POROSITY DATA FOR NONWELDED LAYERS ABOVE CALICO HILLS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tpcrv3 Tpcpv1 Tpbt4 Tpy Tpbt3 Tpp Tpbt2 Tptrv3 Tptpv1 Tpbt1 
KEEP Pah Yucca Tpcpv2 Tptrv2 Tptpv2 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 2 
OUTPUTFILE vnonweldedpor.dat 
run template 2 
start template 3 
title VALIDATION POROSITY DATA FOR VITRIC LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tpcpv3 Tptrv1 Tptpv3 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 3 
OUTPUTFILE vvitricpor.dat 
run template 3 
start template 4 
title VALIDATION POROSITY DATA FOR CALICO LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 N-4 October 2004 
KEEP Tac Tacbt V-Z 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 4 
OUTPUTFILE vcalicopor.dat 
run template 4 
start template 5 
title VALIDATION POROSITY DATA FOR PROW PASS WELDED LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcpm Prowmd 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 5 
OUTPUTFILE vprowweldedpor.dat 
run template 5 
start template 6 
title VALIDATION POROSITY DATA FOR PROW PASS NONWELDED LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcplc Tcplv Tcpuc Tcpuv Tcpbt Prowuv Prowuc Prowlc Prowlv 
KEEP Prowbt Tcpbt Tcp1 Tcp2 Tcp3 Tcp4 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 6 
OUTPUTFILE vprownonweldedpor.dat 
run template 6 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 N-5 October 2004 
start template 7 
title VALIDATION POROSITY DATA FOR BULLFROG WELDED LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcbm Bullfrogmd Tcb3 Tcb4 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 7 
OUTPUTFILE vbullfrogweldedpor.dat 
run template 7 
start template 8 
title VALIDATION POROSITY DATA FOR BULLFROG NONWELDED LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcblv Bullfroguv Bullfroguc Bullfroglc Bullfroglv Bullfrogbt 
KEEP Tcblc Tcbuv Tcbuc Tcbbt Tcb1 Tcb2 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 8 
OUTPUTFILE vbullfrognonweldedpor.dat 
run template 8 
start template 9 
title VALIDATION POROSITY DATA FOR TRAM TUFF WELDED LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tctm Trammd 
! location 
field out 21 40 in 21 40 
!data source 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 N-6 October 2004 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 9 
OUTPUTFILE vtramweldedpor.dat 
run template 9 
start template 10 
title VALIDATION POROSITY DATA FOR TRAM TUFF NONWELDED LAYERS 
colhead 1 
colhead validation porosity 
! validation porosity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP 'Tct ' Tctuv Tctuc Tctlc Tctlv Tctbt Tramuv Tramuc Tramlc 
KEEP Tramlv Trambt 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
end template 10 
OUTPUTFILE vtramnonweldedpor.dat 
run template 10 
Source: STN 10907-2.0-00 [DIRS 162673]. 
NOTES: 
1. This appendix is a copy of data file Inputs\QVPorosity\vporlayers.inp, dated 3/28/03, 4:42PM, 5200 bytes. 
2. Renamed program input files correspond to input files listed for Table 4-6 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX O 
REFORMAT INPUT CONTROL FILE TO COMBINE VALIDATION THERMAL 
CONDUCTIVITY TABLES AND APPEND LITHOSTRATIGRAPHY 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 O-1 October 2004 
Table O-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] lithostratigraphy.txt 
SNF40060298001.001 [DIRS 107372] lithostratigraphy.txt 
SN0011T0571897.014 [DIRS 154449] s00441_001.txt 
SNL01A05059301.005 [DIRS 109002] s96370_001.txt 
SNL22100196001.006 [DIRS 158213] s98169_002.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
lsfile ..\lithostratigraphy.txt 
outputfile vtc.txt 
start template 1 
title Validation Thermal Conductivity Data 
colhead ****************************************** 
colhead TC DATA litho- location datasource row# temp 
type 
colhead strati- (borehole id 
colhead graphy + depth(ft)) 
colhead ****************************************** 
colhead 
! thermal conductivity 
field out 1 8 in "thermal cond" 
rlist out 63 72 separator / rval "70. wet"/"110. dry" 
!copy lithostratigrapy 
field out 11 18 in lithostratigrap 
! sample id -- none 
field out 21 40 in sample 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
end template 1 
inputfile s00441_001.txt 
run template 1 
start template 2 
! thermal conductivity 
field out 1 8 in "thermal cond" 
numeric 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location = sample number 
field out 21 40 in sample 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 O-2 October 2004 
! temperature 
field out 63 66 in temperature 
bounds 65. 75. 
! type (wet or dry): 
field out 69 72 in test 
replace oven dry 
replace air dry 
keep dry 
end template 2 
inputfile s96370_001.txt 
run template 2 
start template 3 
! thermal conductivity 
field out 1 8 in "thermal cond" 
numeric 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location = sample number 
field out 21 40 in sample 
! these samples were not used to build the model: 
keep NRG-4-431.3-SNL-B NRG-4-450.6-SNL-B NRG-4-545.0-SNL-G 
keep NRG-4-590.5-SNL-B NRG-4-610.5-SNL-B NRG-4-619.9-SNL-B 
keep NRG-6-354.9-SNL NRG-7-293.3-SNL-C 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
! temperature 
field out 63 66 in temperature 
bounds 105. 115. 
! type (wet or dry): 
field out 69 72 in test 
replace oven dry 
replace air dry 
keep dry 
end template 3 
inputfile s96370_001.txt 
run template 3 
start template 4 
! thermal conductivity 
field out 1 8 in "thermal cond" 
numeric 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location = sample number 
field out 21 40 in sample 
keep NRG-4-431.3-SNL-B NRG-4-450.6-SNL-B NRG-4-545.0-SNL-G 
keep NRG-4-590.5-SNL-B NRG-4-610.5-SNL-B NRG-4-619.9-SNL-B 
keep NRG-6-354.9-SNL NRG-7-293.3-SNL-C 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 O-3 October 2004 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
! temperature 
field out 63 66 in temperature 
bounds 65. 75. 
! type (wet or dry): 
field out 69 72 in test 
replace vacuum wet 
keep wet 
end template 4 
inputfile s96370_001.txt 
run template 4 
start template 5 
! thermal conductivity 
field out 1 8 in "thermal cond" 
numeric 
!determine lithostratigrapy from sample number: 
lithostrat 11 18 samplenum sample 
! location = sample number 
field out 21 40 in sample 
! this sample was not used to build the model 
keep SD12-1442.8-A 
!datasource 
field out 42 51 in $inputfile 
!row number 
field out 57 60 in row 
! type (wet or dry): 
field out 69 72 in saturation 
replace 98/ wet 
replace 97/ wet 
replace 0/ dry 
replace 1/ dry 
keep wet dry 
end template 5 
inputfile s98169_002.txt 
run template 5 
Source: STN 10907-2.0-00 [DIRS 162673]. 
NOTES: 1. The second colhead command line is wider than this page and does not wrap in the original file. 
2. This appendix is a copy of data file Inputs\QVTC\vtc.inp, dated 3/28/03, 4:57PM, 3565 bytes.

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 O-4 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX P 
REFORMAT INPUT CONTROL FILE TO SEPARATE VALIDATION THERMAL 
CONDUCTIVITY DATA BY SATURATION AND GEOLOGIC LAYER 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-1 October 2004 
Table P-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] vtc.txt 
SNF40060298001.001 [DIRS 107372] vtc.txt 
SN0011T0571897.014 [DIRS 154449] vtc.txt 
SNL01A05059301.005 [DIRS 109002] vtc.txt 
SNL22100196001.006 [DIRS 158213] vtc.txt 
REFORMAT (STN: 10907-2.0-00 [DIRS 162673]) input: 
! This Reformat input control file generates wet and dry thermal conductivity 
! files by geologic layer group (welded, non-welded, ...) that are suitable 
! as input files for program histplt (histogram plotter). 
inputfile vtc.txt 
start template 1 
title DRY THERMAL CONDUCTIVITY DATA FOR WELDED LAYERS ABOVE CALICO HILLS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Qa Tmr Tpc_un Tpk Tptrn Tptrl 'Tptp ' Tptf 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 1 
OUTPUTFILE vweldeddtc.dat 
run template 1 
start template 2 
title DRY THERMAL CONDUCTIVITY DATA FOR NON-WELDED LAYERS ABOVE CALICO HILLS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tpcrv3 Tpcpv1 Tpbt4 Tpy Tpbt3 Tpp Tpbt2 Tptrv3 Tptpv1 Tpbt1 
KEEP Pah Yucca Tpcpv2 Tptrv2 Tptpv2 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-2 October 2004 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 2 
OUTPUTFILE vnonweldeddtc.dat 
run template 2 
start template 3 
title DRY THERMAL CONDUCTIVITY DATA FOR VITRIC LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tpcpv3 Tptrv1 Tptpv3 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 3 
OUTPUTFILE vvitricdtc.dat 
run template 3 
start template 4 
title DRY THERMAL CONDUCTIVITY DATA FOR CALICO LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tac Tacbt V-Z 
! location 
field out 21 40 in 21 40 
!data source 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-3 October 2004 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 4 
OUTPUTFILE vcalicodtc.dat 
run template 4 
start template 5 
title DRY THERMAL CONDUCTIVITY DATA FOR PROW PASS WELDED LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcpm Prowmd 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 5 
OUTPUTFILE vprowweldeddtc.dat 
run template 5 
start template 6 
title DRY THERMAL CONDUCTIVITY DATA FOR PROW PASS NONWELDED LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcplc Tcplv Tcpuc Tcpuv Tcpbt Prowuv Prowuc Prowlc Prowlv 
KEEP Prowbt Tcpbt Tcp1 Tcp2 Tcp3 Tcp4 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-4 October 2004 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 6 
OUTPUTFILE vprownonweldeddtc.dat 
run template 6 
start template 7 
title DRY THERMAL CONDUCTIVITY DATA FOR BULLFROG WELDED LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcbm Bullfrogmd Tcb3 Tcb4 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 7 
OUTPUTFILE vbullfrogweldeddtc.dat 
run template 7 
start template 8 
title DRY THERMAL CONDUCTIVITY DATA FOR BULLFROG NONWELDED LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcblv Bullfroguv Bullfroguc Bullfroglc Bullfroglv Bullfrogbt 
KEEP Tcblc Tcbuv Tcbuc Tcbbt Tcb1 Tcb2 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-5 October 2004 
field out 69 72 in type 
keep dry 
end template 8 
OUTPUTFILE vbullfrognonweldeddtc.dat 
run template 8 
start template 9 
title DRY THERMAL CONDUCTIVITY DATA FOR TRAM TUFF WELDED LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tctm Trammd 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 
end template 9 
OUTPUTFILE vtramweldeddtc.dat 
run template 9 
start template 10 
title DRY THERMAL CONDUCTIVITY DATA FOR TRAM TUFF NONWELDED LAYERS 
colhead 1 
colhead dry thermal conductivity 
! dry thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP 'Tct ' Tctuv Tctuc Tctlc Tctlv Tctbt Tramuv Tramuc Tramlc 
KEEP Tramlv Trambt 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep dry 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-6 October 2004 
end template 10 
OUTPUTFILE vtramnonweldeddtc.dat 
run template 10 
start template 11 
title WET THERMAL CONDUCTIVITY DATA FOR WELDED LAYERS ABOVE CALICO HILLS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Qa Tmr Tpc_un Tpk Tptrn Tptrl 'Tptp ' Tptf 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 11 
OUTPUTFILE vweldedwtc.dat 
run template 11 
start template 12 
title WET THERMAL CONDUCTIVITY DATA FOR NON-WELDED LAYERS ABOVE CALICO HILLS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tpcrv3 Tpcpv1 Tpbt4 Tpy Tpbt3 Tpp Tpbt2 Tptrv3 Tptpv1 Tpbt1 
KEEP Pah Yucca Tpcpv2 Tptrv2 Tptpv2 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 12 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-7 October 2004 
OUTPUTFILE vnonweldedwtc.dat 
run template 12 
start template 13 
title WET THERMAL CONDUCTIVITY DATA FOR VITRIC LAYERS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tpcpv3 Tptrv1 Tptpv3 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 13 
OUTPUTFILE vvitricwtc.dat 
run template 13 
start template 14 
title WET THERMAL CONDUCTIVITY DATA FOR CALICO LAYERS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tac Tacbt V-Z 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 14 
OUTPUTFILE vcalicowtc.dat 
run template 14 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-8 October 2004 
start template 15 
title WET THERMAL CONDUCTIVITY DATA FOR PROW PASS WELDED LAYERS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcpm Prowmd 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 15 
OUTPUTFILE vprowweldedwtc.dat 
run template 15 
start template 16 
title WET THERMAL CONDUCTIVITY DATA FOR PROW PASS NONWELDED LAYERS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcplc Tcplv Tcpuc Tcpuv Tcpbt Prowuv Prowuc Prowlc Prowlv 
KEEP Prowbt Tcpbt Tcp1 Tcp2 Tcp3 Tcp4 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 16 
OUTPUTFILE vprownonweldedwtc.dat 
run template 16 
start template 17 
title WET THERMAL CONDUCTIVITY DATA FOR BULLFROG WELDED LAYERS 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-9 October 2004 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcbm Bullfrogmd Tcb3 Tcb4 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 17 
OUTPUTFILE vbullfrogweldedwtc.dat 
run template 17 
start template 18 
title WET THERMAL CONDUCTIVITY DATA FOR BULLFROG NONWELDED LAYERS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tcblv Bullfroguv Bullfroguc Bullfroglc Bullfroglv Bullfrogbt 
KEEP Tcblc Tcbuv Tcbuc Tcbbt Tcb1 Tcb2 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 18 
OUTPUTFILE vbullfrognonweldedwtc.dat 
run template 18 
start template 19 
title WET THERMAL CONDUCTIVITY DATA FOR TRAM TUFF WELDED LAYERS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 P-10 October 2004 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP Tctm Trammd 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 19 
OUTPUTFILE vtramweldedwtc.dat 
run template 19 
start template 20 
title WET THERMAL CONDUCTIVITY DATA FOR TRAM TUFF NONWELDED LAYERS 
colhead 1 
colhead wet thermal conductivity 
! wet thermal conductivity 
field out 1 8 in 1 8 
!lithostratigraphy 
field out 11 18 in 11 18 
KEEP 'Tct ' Tctuv Tctuc Tctlc Tctlv Tctbt Tramuv Tramuc Tramlc 
KEEP Tramlv Trambt 
! location 
field out 21 40 in 21 40 
!data source 
field out 45 54 in datasource 
!data row number 
field out 57 60 in row 
!temperature 
field out 63 66 in temp 
!type (wet/dry): 
field out 69 72 in type 
keep wet 
end template 20 
OUTPUTFILE vtramnonweldedwtc.dat 
run template 20 
Source: STN 10907-2.0-00 [DIRS 162673]. 
NOTES: 1. This appendix is a copy of data file Inputs\QVTC\vtclayers.inp, dated 3/26/03, 4:22PM, 12519 bytes. 
2. Renamed program input files correspond to input files listed for Table 4-7 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX Q 
EXCEL SPREADSHEET OF VALIDATION DRY THERMAL 
CONDUCTIVITY REGRESSION 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 Q-1 October 2004 
Table Q-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] S00214_001.txt 
SNF40060298001.001 [DIRS 107372] S98430_001.txt 
SN0011T0571897.014 [DIRS 154449] s00441_001.txt 
SNL01A05059301.005 [DIRS 109002] s96370_001.txt 
SNL22100196001.006 [DIRS 158213] s98169_002.txt 
GS000408312231.004 [DIRS 149582] s00276_001.txt 
GS000508312231.006 [DIRS 153237] s00415_001.txt 
GS950308312231.002 [DIRS 108990] s96015_001.txt 
GS950408312231.004 [DIRS 108986] s96021_001.txt 
GS940508312231.006 [DIRS 107149] s96024_003.txt 
GS930108312231.006 [DIRS 108997] s96025_001.txt 
GS920508312231.012 [DIRS 109001] s96026_001.txt 
GS940408312231.004 [DIRS 109000] s96027_001.txt 
GS951108312231.009 [DIRS 108984] s96037_001.txt 
GS951108312231.011 [DIRS 108992] s96049_001.txt 
GS960808312231.004 [DIRS 108985] s97058_001.txt 
GS980708312242.010 [DIRS 106752] s98248_004.txt 
GS980808312242.014 [DIRS 106748] s98285_001.txt 
GS951108312231.010 [DIRS 108983] s96046_001.txt 
GS920408312314.011 [DIRS 129660] s97135_002.txt 
GS930408312132.007 [DIRS 129625] s97276_001.txt 
SNL01A05059301.007 [DIRS 108980] s98424_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_002.txt 
SNL02030193001.002 [DIRS 120575] s98484_004.txt 
SNL02030193001.002 [DIRS 120575] s98484_005.txt 
SNL02030193001.004 [DIRS 108415] s98485_001.txt 
SNL02030193001.004 [DIRS 108415] s98485_003.txt 
SNL02030193001.008 [DIRS 120597] s98486_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_004.txt 
SNL02030193001.006 [DIRS 120579] s99101_001.txt 
SNL02030193001.006 [DIRS 120579] s99101_004.txt 
SNL02030193001.013 [DIRS 120614] s99104_001.txt 
SNL02030193001.013 [DIRS 120614] s99104_004.txt 
SNL02030193001.005 [DIRS 122545] s99105_001.txt 
SNL02030193001.005 [DIRS 122545] s99105_004.txt 
SNL02030193001.007 [DIRS 120582] s99106_001.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 Q-2 October 2004 
Table Q-1. Input DTN List (Continued) 
DTN Renamed Program Input File 
SNL02030193001.014 [DIRS 109609] s99107_001.txt 
SNL02030193001.014 [DIRS 109609] s99107_004.txt 
SNL02030193001.015 [DIRS 120617] s99108_001.txt 
SNL02030193001.009 [DIRS 109614] s99109_001.txt 
SNL02030193001.012 [DIRS 108416] s99110_001.txt 
SNL02030193001.022 [DIRS 109613] s99111_002.txt 
SNL02030193001.016 [DIRS 120619] s99112_001.txt 
SNL02030193001.017 [DIRS 109610] s99113_001.txt 
SNL02030193001.018 [DIRS 109611] s99114_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_002.txt 
SNL02030193001.020 [DIRS 108432] s99116_001.txt 
SNL02030193001.020 [DIRS 108432] s99116_004.txt 
SNL02030193001.021 [DIRS 108433] s99117_001.txt 
SNL01A05059301.002 [DIRS 150042] s99435_001.txt 
MO0012POROCHOL.000 [DIRS 153376] s00452_001.txt 
SNL02030193001.020 [DIRS 108432] s99116_006.txt 
SNL02030193001.021 [DIRS 108433] s99117_005.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_001.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_032.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_033.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_034.txt 
GS950308312231.002 [DIRS 108990] s96015_002.txt 
GS950408312231.004 [DIRS 108986] s96021_002.txt 
GS940508312231.006 [DIRS 107149] s96024_002.txt 
GS930108312231.006 [DIRS 108997] s96025_002.txt 
GS920508312231.012 [DIRS 109001] s96026_002.txt 
GS940408312231.004 [DIRS 109000] s96027_002.txt 
GS951108312231.009 [DIRS 108984] s96037_002.txt 
GS960808312231.004 [DIRS 108985] s97058_002.txt 
GS920408312314.011 [DIRS 129660] s97135_007.txt 
GS930408312132.007 [DIRS 129625] s97276_003.txt 
GS980708312242.010 [DIRS 106752] s98248_006.txt 
GS980808312242.014 [DIRS 106748] s98285_002.txt 
SNL02030193001.001 [DIRS 120572] s98483_001.txt 
SNL02030193001.004 [DIRS 108415] s98485_005.txt 
SNL02030193001.013 [DIRS 120614] s99104_005.txt 
SNL02030193001.009 [DIRS 109614] s99109_002.txt 
SNL02030193001.017 [DIRS 109610] s99113_003.txt 
SNL02030193001.028 [DIRS 159972] s99121_001.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 Q-3 October 2004 
Table Q-2. Excel Spreadsheet of Regression Analysis 
layer kd phi drybd 1/phi 1/phi^2 dbd/(1-phi) kd fit relerr 
welded 1.132 0.128 2190 7.8125 61.03516 2511.468 1.206793 0.066072 SUMMARY OUTPUT 
vitric 1.48 0.038 2310 26.3158 692.5208 2401.247 1.481068 0.000721 
nonwelded 0.417 0.379 1460 2.63852 6.961801 2351.047 0.418815 0.004351 Regression Statistics 
calico 0.577 0.282 1670 3.5461 12.57482 2325.905 0.538451 -0.06681 Multiple R 0.99347322 
prow nw 0.652 0.267 1790 3.74532 14.02741 2442.019 0.647866 -0.00634 R Square 0.98698905 
bull nw 0.7 0.22 1880 4.54545 20.66116 2410.256 0.738732 0.055332 Adjusted R S 0.9739781 
bull weld 1.4 0.115 2260 8.69565 75.61437 2553.672 1.326276 -0.05266 Standard Err 0.06840338 
RMSERR= 0.045862 Observations 7 
Coefficients: A= -1.65125 B= 0.18022 C= -0.004726 D= 0.000692 
ANOVA 
Predictions: df SS MS F 
prow weld 0.194 2070 5.15464 26.57031 2568.238 0.929954 Regression 3 1.0648284 0.3549428 75.8583247 
tram nw 0.288 1760 3.47222 12.05633 2471.91 0.628654 Residual 3 0.0140371 0.004679 
tram wel 0.184 2140 5.43478 29.53686 2622.549 1.004018 Total 6 1.0788654 
Coefficients Standard Ert Stat P-value 
Intercept -1.6512471 1.9223781 -0.8589606 0.45351945 
X Variable 1 0.18022044 0.0499715 3.6064615 0.03659487 
X Variable 2 -0.0047255 0.0016455 -2.871852 0.06395337 
X Variable 3 0.00069222 0.0008673 0.7981024 0.48314726 
NOTE: This appendix is a copy of data file Outputs\TCRegression\drytcregression.xls, dated 4/10/03, 2:57PM, 
18432 bytes. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 Q-4 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX R 
EXCEL SPREADSHEET OF VALIDATION WET 
THERMAL CONDUCTIVITY REGRESSION 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 R-1 October 2004 
Table R-1. Input DTN List 
DTN Renamed Program Input File 
MO0004QGFMPICK.000 [DIRS 152554] S00214_001.txt 
SNF40060298001.001 [DIRS 107372] S98430_001.txt 
SN0011T0571897.014 [DIRS 154449] s00441_001.txt 
SNL01A05059301.005 [DIRS 109002] s96370_001.txt 
SNL22100196001.006 [DIRS 158213] s98169_002.txt 
GS000408312231.004 [DIRS 149582] s00276_001.txt 
GS000508312231.006 [DIRS 153237] s00415_001.txt 
GS950308312231.002 [DIRS 108990] s96015_001.txt 
GS950408312231.004 [DIRS 108986] s96021_001.txt 
GS940508312231.006 [DIRS 107149] s96024_003.txt 
GS930108312231.006 [DIRS 108997] s96025_001.txt 
GS920508312231.012 [DIRS 109001] s96026_001.txt 
GS940408312231.004 [DIRS 109000] s96027_001.txt 
GS951108312231.009 [DIRS 108984] s96037_001.txt 
GS951108312231.011 [DIRS 108992] s96049_001.txt 
GS960808312231.004 [DIRS 108985] s97058_001.txt 
GS980708312242.010 [DIRS 106752] s98248_004.txt 
GS980808312242.014 [DIRS 106748] s98285_001.txt 
GS951108312231.010 [DIRS 108983] s96046_001.txt 
GS920408312314.011 [DIRS 129660] s97135_002.txt 
GS930408312132.007 [DIRS 129625] s97276_001.txt 
SNL01A05059301.007 [DIRS 108980] s98424_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_001.txt 
SNL02030193001.002 [DIRS 120575] s98484_002.txt 
SNL02030193001.002 [DIRS 120575] s98484_004.txt 
SNL02030193001.002 [DIRS 120575] s98484_005.txt 
SNL02030193001.004 [DIRS 108415] s98485_001.txt 
SNL02030193001.004 [DIRS 108415] s98485_003.txt 
SNL02030193001.008 [DIRS 120597] s98486_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_001.txt 
SNL02030193001.003 [DIRS 120578] s99100_004.txt 
SNL02030193001.006 [DIRS 120579] s99101_001.txt 
SNL02030193001.006 [DIRS 120579] s99101_004.txt 
SNL02030193001.013 [DIRS 120614] s99104_001.txt 
SNL02030193001.013 [DIRS 120614] s99104_004.txt 
SNL02030193001.005 [DIRS 122545] s99105_001.txt 
SNL02030193001.005 [DIRS 122545] s99105_004.txt 
SNL02030193001.007 [DIRS 120582] s99106_001.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 R-2 September 2004 
Table R-1. Input DTN List (Continued) 
DTN Renamed Program Input File 
SNL02030193001.014 [DIRS 109609] s99107_001.txt 
SNL02030193001.014 [DIRS 109609] s99107_004.txt 
SNL02030193001.015 [DIRS 120617] s99108_001.txt 
SNL02030193001.009 [DIRS 109614] s99109_001.txt 
SNL02030193001.012 [DIRS 108416] s99110_001.txt 
SNL02030193001.022 [DIRS 109613] s99111_002.txt 
SNL02030193001.016 [DIRS 120619] s99112_001.txt 
SNL02030193001.017 [DIRS 109610] s99113_001.txt 
SNL02030193001.018 [DIRS 109611] s99114_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_001.txt 
SNL02030193001.019 [DIRS 108431] s99115_002.txt 
SNL02030193001.020 [DIRS 108432] s99116_001.txt 
SNL02030193001.020 [DIRS 108432] s99116_004.txt 
SNL02030193001.021 [DIRS 108433] s99117_001.txt 
SNL01A05059301.002 [DIRS 150042] s99435_001.txt 
MO0012POROCHOL.000 [DIRS 153376] s00452_001.txt 
SNL02030193001.020 [DIRS 108432] s99116_006.txt 
SNL02030193001.021 [DIRS 108433] s99117_005.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_001.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_032.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_033.txt 
MO0109HYMXPROP.001 [DIRS 155989] s01144_034.txt 
GS950308312231.002 [DIRS 108990] s96015_002.txt 
GS950408312231.004 [DIRS 108986] s96021_002.txt 
GS940508312231.006 [DIRS 107149] s96024_002.txt 
GS930108312231.006 [DIRS 108997] s96025_002.txt 
GS920508312231.012 [DIRS 109001] s96026_002.txt 
GS940408312231.004 [DIRS 109000] s96027_002.txt 
GS951108312231.009 [DIRS 108984] s96037_002.txt 
GS960808312231.004 [DIRS 108985] s97058_002.txt 
GS920408312314.011 [DIRS 129660] s97135_007.txt 
GS930408312132.007 [DIRS 129625] s97276_003.txt 
GS980708312242.010 [DIRS 106752] s98248_006.txt 
GS980808312242.014 [DIRS 106748] s98285_002.txt 
SNL02030193001.001 [DIRS 120572] s98483_001.txt 
SNL02030193001.004 [DIRS 108415] s98485_005.txt 
SNL02030193001.013 [DIRS 120614] s99104_005.txt 
SNL02030193001.009 [DIRS 109614] s99109_002.txt 
SNL02030193001.017 [DIRS 109610] s99113_003.txt 
SNL02030193001.028 [DIRS 159972] s99121_001.txt 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 R-3 September 2004 
Table R-2. Excel Spreadsheet of Regression Analysis 
layer kw phi drybd 1/phi 1/phi^2 dbd/(1-phi) kd fit relerr 
welded 1.593 0.128 2190 7.8125 61.03516 2511.468 1.682987 0.056489 SUMMARY OUTPUT 
vitric 1.903 0.038 2310 26.3158 692.5208 2401.247 1.903189 9.92E-05 
nonwelded 1.026 0.379 1460 2.63852 6.961801 2351.047 1.056249 0.029483 Regression Statistics 
calico 1.162 0.282 1670 3.5461 12.57482 2325.905 1.135025 -0.023214 Multiple R 0.98954035 
prow nw 1.258 0.267 1790 3.74532 14.02741 2442.019 1.252097 -0.004692 R Square 0.9791901 
bull nw 1.33 0.22 1880 4.54545 20.66116 2410.256 1.308016 -0.01653 Adjusted R S 0.9583802 
bull weld 1.85 0.115 2260 8.69565 75.61437 2553.672 1.784436 -0.03544 Standard Err 0.06965905 
RMSERR= 0.029642 Observations 7 
Coefficients: A= -1.20708 B= 0.13024 C= -0.00332 D= 0.000826 
ANOVA 
Predictions: df SS MS F 
prow weld 0.194 2070 5.15464 26.57031 2568.238 1.49827 Regression 3 0.6849729 0.2283243 47.054053 
tram nw 0.288 1760 3.47222 12.05633 2471.91 1.247779 Residual 3 0.0145571 0.0048524 
tram wel 0.184 2140 5.43478 29.53686 2622.549 1.569778 Total 6 0.69953 
CoefficientsStandard Erro t Stat P-value 
Intercept -1.2070813 1.9576669 -0.6165918 0.58113587 
X Variable 1 0.13024348 0.0508889 2.5593711 0.08325973 
X Variable 2 -0.0033234 0.0016757 -1.9833011 0.1416023 
X Variable 3 0.00082636 0.0008833 0.9355875 0.4185031 
NOTE: This appendix is a copy of data file Outputs\TCRegression\wettcregression.xls, dated 4/10/03, 3:56PM, 
18432 bytes.

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 R-4 October 2004 
INTENTIONALLY LEFT BLANK 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX S 
UNCERTAINTY ANALYSIS OF THERMAL CONDUCTIVITY 
OF NONREPOSITORY LITHOSTRATIGRAPHIC LAYERS 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-1 October 2004 
S1. UNCERTAINTY ANALYSIS OF THERMAL CONDUCTIVITY OF 
NONREPOSITORY LITHOSTRATIGRAPHIC LAYERS 
S1.1 INTRODUCTION AND PURPOSE 
This section develops a one-dimensional (1-D) steady-state calculation for heat flow through 
various layers above and below the repository, and then develops an uncertainty analysis of 
thermal conductivity of the nonrepository lithostratigraphic layers. 
The calculation is then used to estimate the contribution to the variance of the temperature from 
the thermal conductivity for the nonrepository layers. The calculation compares these 
contributions to the variance of temperature from the thermal conductivity with the main 
repository layers for the prediction of the repository driftwall temperature. 
The calculation then examines the effect of an increased porosity in the Tiva Canyon unit above 
the repository. 
S2. CONCEPTUAL AND MATHEMATICAL MODEL DEVELOPMENT 
This section develops the method for predicting temperature in the repository as a function of 
lithostratigraphic unit thermal conductivity, strata thickness, and repository heating (i.e., f (Kth, 
thickness, and q)). Noting the analogy between solving the 1-D heat conduction problem in 
accordance with Fourier's Law, and the fluid flow problem in accordance with Darcy's Law, an 
expression for the effective thermal conductivity for heat flow in series in the vertical direction 
(Freeze and Cherry 1979 [DIRS 101173], p. 34) is: 
Kz 
d 
1 
n 
i 
di 
Ki 
.= 
(Eq. S-1) 
where: 
Kz = Composite thermal conductivity (W/(m K)), 
d = Overall thickness of a series of units, 
di = Unit thickness of the ith unit, and 
Ki = Thermal conductivity of the ith unit. 
n = Number of Layers 
Consider the simple node network in Figure S-1; the three nodes of this network correspond to 
the ground surface, the repository horizon, and the base of the 1-D model. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-2 October 2004 
1
2
3 
Repository Horizon Node 
Surface Temperature Node 
Base of the Model Node 
Figure S-1. Simple Lumped Parameter Model 
Note that the effective thermal conductivity (Kth) above and below the repository can be 
provided. For above and below the repository horizon we have: 
K12 
d12 
1 
n1 
i 
di 
Ki 
.= 
K32 
d32 
1 
n2 
i 
d'i 
K'i 
.= 
(Eq. S-2) 
where: 
K12 = Effective thermal conductivity from the repository horizon to the ground surface 
K32 = Effective thermal conductivity from the repository horizon to the base of the 
model 
d12 = Depth to the repository horizon from the ground surface, and 
d32 = Depth from the repository horizon to the base of the 1-D model. 
n1 = Number of layers above the repository horizon 
n2 = Number of layers below the repository horizon 
Let qR equal the vertical heat flux at the repository horizon. The temperature response can be 
solved for by writing the general heat flow equation (Chapman 1974 [DIRS 152938], p. 173): 
j 
tj ti - ( ) 
Rij . qR + 
(Eq. S-3) 
0

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-3 October 2004 
Expanding this relationship at the repository horizon: 
t2 t1 - 
R12 
t2 t3 - 
R32 
+ qR + 
(Eq. S-4) 
where: 
t1 = Fixed temperature at the ground surface, 
t2 = Variable temperature at the repository horizon, 
t3 = Fixed temperature at the base of the model, 
R12 = Resistance to heat flow from the repository horizon to the ground surface, and 
R32 = Resistance to heat flow from the repository horizon to the base of the model. 
Note that the resistances are given (Chapman 1974 [DIRS 152938], p. 173) as: 
R12 
d12 
K12 Ak  
R32 
d32 
K32 Ak  
(Eq. S-5) 
The solution to the steady-state heat conduction pertains to vertical flow from the repository. 
The resistances presented in Equation S-5 are for a unit area (the area for vertical heat flow (Ak) 
equals 1 m2 for the SI system of units). Substituting in the formulas for the thermal 
conductivities: 
R12 
d12 
d12 
1 
n1 
i 
di 
Ki 
.= 
1  
R32 
d32 
d32 
1 
n2 
i 
d'i 
K'i 
.= 
1  
Simplifying: 
R12 
1 
n1 
i 
di 
Ki 
.= 
R32 
1 
n2 
i 
d'i 
K'i 
.= 
(Eq. S-6) 
t2 t1 - 
1 
n1 
i 
di 
Ki 
.= 
t2 t3 - 
1 
n2 
i 
d'i 
K'i 
.= 
+ qR + 
(Eq. S-7) 
0 
0

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-4 October 2004 
The analysis considers the change in temperature induced in the rock due to repository heating. 
The In-Drift Natural Convection and Condensation (BSC 2004 [DIRS 164327]) sets the 
temperature at the ground surface equal to ambient temperature, and shows that this temperature 
boundary condition is reasonable. For purposes of analysis, the temperature at the ground 
surface and at the greatest depth is set equal to zero. This is adequate for this analysis, because 
changes in temperature are of interest in this report. 
t2 
1 
n1 
i 
di 
Ki 
.= 
t2 
1 
n2 
i 
d'i 
K'i 
.= 
+ qR + 
(Eq. S-8) 
t2 
1 
1 
n1 
i 
di 
Ki 
.= 
1 
1 
n2 
i 
d'i 
K'i 
.= 
+ ..... 
.
.
. 
 q - 
(Eq. S-9) 
Factoring out the repository temperature: 
t2 
qR - 
1 
1 
n1 
i 
di 
Ki 
.= 
1 
1 
n2 
i 
d'i 
K'i 
.= 
+ ..... 
.
.
. (Eq. S-10) 
t2 qR - 1 
1 
n1 
i 
di 
Ki 
.= 
1 
1 
n2 
i 
d'i 
K'i 
.= + ..... 
.
.
. 
1 - 
 
(Eq. S-11) 
S3. MATHEMATICAL UNCERTAINTY ANALYSIS 
Hahn and Shapiro (1967 [DIRS 146529], p. 231) present the following relationship for the 
variance: 
.= 
 . .. 
. 
. .. 
. 
.
. 
= 
n 
i 
i 
i 
x Var 
x
h z Var 
1 
2 
) ( ) ( 
(Eq. S-12) 
Note that the measure for uncertainty in repository temperature is the standard deviation (or the 
square root of the variance). Note also that in the application of this equation to the prediction of 
temperature, h equals temperature at the repository horizon t2, and xi corresponds to thermal 
conductivity of each of the repository and nonrepository horizon units. 
0
R

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-5 October 2004 
Equation S-12 provides information pertaining to the source of uncertainty from the individual 
variables. In Equation S-12, the variance of each individual variable (xi) is multiplied by the 
square of the derivative of the system function for that parameter. The square of the derivative 
represents the sensitivity of the system variance to the individual parameter. If the sensitivity, 
and the variance, to an individual parameter, are large, then the system variance is dominated by 
this contribution. Conversely, if the sensitivity, and the variance, to an individual parameter are 
small, then the system variance is not influenced by this individual contribution. 
Equation S-12 is applied to the calculation of the repository temperature as given by Equation 
S-10. The derivative of the temperature with respect to rock-mass thermal conductivity is 
determined for each of the layers. 
In some applications, it may be necessary to have a measure of uncertainty that encompasses a 
larger fraction of the values than could reasonably be attributed to the measurement. If 
necessary, the user may multiply the standard uncertainty by a coverage factor to obtain an 
expanded uncertainty. 
To factor the uncertainty, use a value of 1.96 from the table of percentage points for the 
Students t distribution for a large number of measurements (Beyer 1987 [DIRS 103805], 
p. 571). 
The 95-percent confidence interval is an appropriate range for this sensitivity study for two 
reasons: 
1) Most of the model predictions fall within the 95-percent confidence interval, and 
2) This study biases all of the thermal conductivities high, then low, to make bounding 
estimates of the effects to repository temperatures, although it would be a more 
realistic approach would be to let random variation occur across the thermal 
conductivity estimates. 
Now consider the derivative with respect to thermal conductivity above the repository horizon. 
Consider the use of three layers, and then expand this expression for all layers. 
Expanding Equation S-10 for three layers above and below the repository: 
t2 qR - 1 
d1 
K1 
d2 
K2 
+ 
d3 
K3 
+ 
1 
d'1 
K'1 
d'2 
K'2 
+ 
d'3 
K'3 
+ 
+ ..... 
.
.
. 
1 - 
 
(Eq. S-13) 
where d1, d2, d3, K1, K2, and K3 refer to the layer thickness and thermal conductivity above the 
repository, respectively, and d'1, d'2, d'3, K'1, K'2, and K'3 are the comparable parameters below 
the repository. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-6 October 2004 
Differentiation of Equation S-13 yields: 
K1
t2 
. 
. 
qR 
1 
d1 
K1 
d2 
K2 
+ 
d3 
K3 
+ 
1 
d'1 
K'1 
d'2 
K'2 
+ 
d'3 
K'3 
+ 
+ ..... 
.
.
.
2 d1 
K1 
d2 
K2 
+ 
d3 
K3 
+ 
... 
.
.
2 
 
d1 
K1
2 
 
(Eq. S-14) 
or, writing for the general case for the influence of the effective thermal conductivity of the ith 
layer above the repository on the temperature of the repository: 
Ki
t2 
. 
. 
qR 
1 
1 
n1 
i 
di 
Ki .= 
1 
1 
n2 
i 
d'i 
K'i .= 
+ ..... 
.
.
.
2 
1 
n1 
i 
di 
Ki .= 
.... 
.
.
2 
 
di 
Ki
2 
 
(Eq. S-15) 
q d' R 
1 
1 
n1 
i 
di 
Ki 
. 
= 
1 
1 
n2 
i 
d'i 
K'i 
. 
= 
+ . 
. 
. 
. 
. 
. 
.
2 
1 
n2 
i 
d'i 
K'i 
. 
= 
. . 
. 
. 
. . 
2 
 
i 
K'i
2  
(Eq. S-16) 
S3.1 REPOSITORY PROPERTY VALUES ABOVE AND BELOW THE DISPOSAL 
HORIZON 
In this section, thermal conductivity and thickness for lithostratigraphic layers above and below 
the repository are defined. The planned thermal load for the repository is also defined. These 
values will be used to calculate the repository temperatures and variances. The properties for 
thermal conductivity are obtained from Table 6-13 of this report, and presented in Table S-1. 
The saturated thermal conductivities are used for this analysis because the matrix pore volume is 
generally close to saturation after 1,000 years, when heat has diffused into the nonrepository 
horizon units. The results of the Multiscale Thermohydrologic Model (BSC 2004 
[DIRS 169565]) show a high matrix saturation during this period for the repository horizon units. 
For example, matrix saturation is high at the repository horizon at locations P2ER8C6, 
P2WR8C8, P2WR5C10, and P3R7C12 (BSC 2004 [DIRS 169565], Figures 6.3-7 to 6.3-10) 
after 1,000 years for the mean and high infiltration cases. These results would provide a lower 
bound for matrix saturation for the nonrepository horizon units because the maximum extent of 
the dryout zone is only about 10 meters from the repository horizon (BSC 2004 [DIRS 169565]. 
In addition, the volumetric moisture content versus temperature relationship, as measured from 
K1
t2 
. 
.

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-7 October 2004 
neutron logging of Borehole 79 and Borehole 80 during the Drift Scale Test heating phase, 
shows little reduction in volumetric moisture content below the boiling point of water 
(DTN MO0406SEPTVDST.000 [DIRS 170616], file both.xls). 
The thickness of the layers is obtained from Multiscale Thermohydrologic Model (BSC 2004 
[DIRS 169565]) (for column P2WR5C10 as contained in Attachment V; this column is located at 
coordinates E170730.297 and N234912.719). The thermal conductivity at the repository horizon 
is obtained from Thermal Conductivity of the Potential Repository Horizon (BSC 2004 
[DIRS 169854], Table 6-6). Note that the data are input from Table S-1. 
Table S-1. Summary of Lithostratigraphic Units and Relevant Thermal Properties 
A B C D E F G H I J K 
Matrix Thermal Conductivity 
(W/(m K))1,3 
Dry Wet 
GFM Unit1 Strat. Unit2 
No. of 
Points1 mean std dev mean std dev 
Strat. Unit 
Thickness 
(m)4 
Layer 
Type 
Max. 
Relative 
Error9 
Uncertainty 
(W/(m K)) 
3 Crystal-Rich 
Tiva/Post 
Tiva 
tcw11 17 1.30 0.23 1.81 0.20 0.00 welded 1.96 0.38 
4 Tpcp (2) tcw12 17 1.30 0.23 1.81 0.20 0.00 welded 1.96 0.38 
5 TpcLD (3) tcw12 17 1.30 0.23 1.81 0.20 20.24 welded 1.96 0.38 
6 Tpcpv3 (4) tcw135 2 0.59 0.19 0.93 0.20 4.01 vitric 1.96 0.39 
7 Tpcpv2 (5) tcw135 2 0.59 0.19 0.93 0.20 0.00 nonwelded 
1.96 0.39 
8 Tpcpv1(6) ptn21 9 0.49 0.16 1.06 0.15 7.21 nonwelded 
1.96 0.29 
9 Tpbt4 (7) ptn22 9 0.49 0.16 1.06 0.15 5.60 nonwelded 
1.96 0.29 
10 Yucca (8) ptn23 9 0.49 0.16 1.06 0.15 2.02 nonwelded 
1.96 0.29 
11 Tpbt3_dc (9) ptn24 9 0.49 0.16 1.06 0.15 12.51 nonwelded 
1.96 0.29 
12 Pah (10) ptn25 9 0.49 0.16 1.06 0.15 36.50 nonwelded 
1.96 0.29 
13 Tpbt2 (11) ptn26 9 0.49 0.16 1.06 0.15 3.76 nonwelded 
1.96 0.29 
14 Tptrv3 (12) ptn26 9 0.49 0.16 1.06 0.15 3.76 nonwelded 
1.96 0.29 
15 Tptrv2 (13) ptn26 9 0.49 0.16 1.06 0.15 3.76 nonwelded 
1.96 0.29 
16 Tptrv1 (14) tsw316 2 0.99 0.23 1.30 0.22 1.99 vitric 1.96 0.44 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-8 October 2004 
Table S-1. Summary of Lithostratigraphic Units and Relevant Thermal Properties (Continued) 
A B C D E F G H I J K 
Matrix Thermal Conductivity 
(W/(m K))1,3 
Uncertainty 
(W/(m K)) 
Dry Wet 
GFM Unit1 Strat. Unit2 
No. of 
Points1 mean std dev mean std dev 
Strat. Unit 
Thickness 
(m)4 
Layer 
Type 
Max. 
Relative 
Error9 
17 Tptrn (15) tsw32 17 1.30 0.23 1.81 0.20 45.59 welded 1.96 0.38 
18 Tptrl (16) tsw33 17 1.30 0.23 1.81 0.20 0.00 welded 1.96 0.38 
19 Tptpul tsw33 - 1.18 0.24 1.77 0.25 85.25 welded 1.96 0.48 
20 Tptpmn tsw34 - 1.42 0.27 2.07 0.25 32.95 welded 1.96 0.49 
21 Tptpll 
above 
tsw35 above - 1.2784 0.2511 1.89 0.25 45.33 welded 1.96 0.49 
22 Tptpll 
below 
tsw35 below - 1.28 0.25 1.89 0.25 59.39 welded 1.96 0.49 
23 Tptpln tsw36 - 1.49 0.28 2.13 0.27 25.83 welded 1.96 0.52 
24 Tptpln tsw377 - 1.49 0.28 2.13 0.27 12.91 welded 1.96 0.52 
25 Tptpv3 (18) tsw38 2 0.69 0.23 0.80 0.25 21.90 vitric 1.96 0.49 
26 Tptpv2(19) tsw9z 
(tsw39)8 
9 0.49 0.16 1.06 0.15 3.30 nonwelded 
1.96 0.29 
27 Tptpv1(20) ch1z 9 0.49 0.16 1.06 0.15 3.30 nonwelded 
1.96 0.29 
28 Tpbt1 ch1z 9 0.49 0.16 1.06 0.15 15.04 nonwelded 
1.96 0.29 
29 Calico ch2z 5 0.60 0.11 1.26 0.14 20.29 calico 1.96 0.28 
30 Calico ch3z 5 0.60 0.11 1.26 0.14 20.30 calico 1.96 0.28 
31 Calico ch4z 5 0.60 0.11 1.26 0.14 20.27 calico 1.96 0.28 
32 Calico ch5z 5 0.60 0.11 1.26 0.14 20.30 calico 1.96 0.28 
33 Calicobt ch6z 5 0.60 0.11 1.26 0.14 17.58 calico 1.96 0.28 
34 Prowuv pp4 9 0.57 0.10 1.13 0.12 19.69 Prow 
Pass 
nonwelded 
1.96 0.24 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-9 October 2004 
Table S-1. Summary of Lithostratigraphic Units and Relevant Thermal Properties (Continued) 
A B C D E F G H I J K 
Matrix Thermal Conductivity 
(W/(m K))1,3 
Uncertainty 
(W/(m K)) 
Dry Wet 
GFM Unit1 Strat. Unit2 
No. of 
Points1 mean std dev mean std dev 
Strat. Unit 
Thickness 
(m)4 
Layer 
Type 
Max. 
Relative 
Error9 
35 Prowuc pp3 9 0.57 0.10 1.13 0.12 14.33 Prow 
Pass 
nonwelded 
1.96 0.24 
36 Prowmd pp2 17 1.06 0.18 1.63 0.17 4.10 welded 1.96 0.33 
1 Thermal conductivities are obtained from Table 6-13 of this report. 
2 Lithostratigraphic units are obtained from Table IV-3a of the Multiscale Thermohydrologic Model (BSC 2004) 
[DIRS 169565]. 
3 Thermal conductivities for the repository units are obtained from Table 6-6 of the Thermal Conductivity of the 
Potential Horizon (BSC 2004 [DIRS 169854]). 
4 See Table IV-3a of the Multiscale Thermohydrologic Model (BSC 2004) [DIRS 169565]. 
5 The thermal properties for tsw13 are obtained from the average for GFM units Tpcpv3(4) and Tpcpv2(5) from 
Table 6-13 based upon the correlation presented in Table 4-10 of the Ventilation Model and Analysis Report 
(BSC 2004 [DIRS 169862]). 
6 The thermal properties for tsw31 are obtained from the average for GFM units Tptrv1(14) and Tptrn(15) from 
Table 6-13 based upon the correlation presented in Table 4-10 of the Ventilation Model and Analysis Report 
(BSC 2004 [DIRS 169862]). 
7 Tsw37 has the same thermal properties as the Tptpln unit. 
8 Tsw9v is identified as tsw39 in Table 4-10 of the Ventilation Model and Analysis Report (BSC 2004 [DIRS 169862]). 
9 To factor the uncertainty, use a value of 1.96 from the table of percentage points for the Student's t distribution for a 
large number of measurements (Beyer, W.H., ed. 1987. CRC Standard Mathematical Tables, p. 571) 
[DIRS 103805]. 
Extract the depths above the repository horizon. Referring to Table S-1, the submatrix function 
is used for the extraction. The submatrix function will extract a submatrix from a beginning row 
(Table S-1) to an ending row, and a beginning column to an ending column. 
The data for the depths above the repository horizon begin at row 3, and end at row 21. The 
stratigraphic unit thickness data are in column H. Thus, the submatrix is a vector, and the 
function is evaluated submatrix (Strat, beginning row, ending row, beginning column, ending 
column): 
d submatrix Strat 3 , 21 , 8 , 8 , ( ) := m 
Now, as shown in Table S-2, extract the data from below the repository horizon. Again, the 
submatrix function is used with the beginning row at 22 to 36. The thickness data are again in 
Table S-1, column H. 
d' submatrix Strat 22 , 36 , 8 , 8 , ( ) := m 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-10 October 2004 
Table S-2. Unit Thicknesses Above and Below the Repository Horizon 
Above the Repository Horizon Below the Repository Horizon 
d 
1 
1
2
3
4
5
6
7
8
9 
10 
11 
12 
13 
14 
15 
16 
17 
18 
19 
0
0 
20.24 
4.01
0 
7.21 
5.6 
2.02 
12.51 
36.5 
3.76 
3.76 
3.76 
1.99 
45.59
0 
85.25 
32.95 
45.33 
m = 
d' 
1 
1
2
3
4
5
6
7
8
9 
10 
11 
12 
13 
14 
15 
59.39 
25.83 
12.91 
21.9 
3.3 
3.3 
15.04 
20.29 
20.3 
20.27 
20.3 
17.58 
19.69 
14.33 
4.1 
m = 
Assign the number of units above and below the repository. 
n1 rows d ( ) := n2 rows d' ( ) := 
n1 19 = n2 15 = 
Calculate the thickness d12 and d32 above and below the repository. 
d12 
1 
n1 
i 
di .= 
:= d12 310.49m = 
d32 
1 
n2 
i 
d'i .= 
:= d32 278.53m = 
NOTE: In MathCad 11 a := symbol is an assignment statement 
for a function or a variable. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-11 October 2004 
An extraction of the thermal conductivity for the wet case above and below the repository is 
shown in Table S-3. In this case, the submatrix command from the same rows as above is made, 
but with column F of Table S-1 (saturated thermal conductivity data): 
. submatrix Strat 3 , 21 , 6 , 6 , ( )
W 
mK  
 := .' submatrix Strat 22 , 36 , 6 , 6 , ( )
W 
mK  
 := 
NOTE: In MathCad 11 a := symbol is an assignment statement for a function or a 
variable. 
Table S-3. Saturated Thermal Conductivities Above and Below the Repository Horizon 
Above the Repository Horizon Below the Repository Horizon 
. 
1 
1
2
3
4
5
6
7
8
9 
10 
11 
12 
13 
14 
15 
16 
17 
18 
19 
1.81 
1.81 
1.81 
0.93 
0.93 
1.06 
1.06 
1.06 
1.06 
1.06 
1.06 
1.06 
1.06 
1.3 
1.81 
1.81 
1.77 
2.07 
1.89 
W 
mK  
= 
.' 
1 
1
2
3
4
5
6
7
8
9 
10 
11 
12 
13 
14 
15 
1.89 
2.13 
2.13 
0.8 
1.06 
1.06 
1.06 
1.26 
1.26 
1.26 
1.26 
1.26 
1.13 
1.13 
1.63 
W 
mK  
= 
S3.2 AVERAGE WASTE PACKAGE HEAT LOADING 
To input the average line loading at the repository horizon, the line averaged powers are obtained 
from D&E/PA/C IED Typical Waste Package Components Assembly (BSC 2004 
[DIRS 167754]). This line load includes the net influence of ventilation on the waste package 
load thermal output. The complete dataset is presented in Table S-4. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-12 October 2004 
Table S-4. Average Line Load 
Time (yr) 
Line Load 
Power (W/m) 
Line Load 
Power (W/m) 
with 
Ventilation 
0.001 1.450E+03 2.030E+02 
1 1.399E+03 1.958E+02 
2 1.357E+03 1.899E+02 
3 1.321E+03 1.849E+02 
4 1.289E+03 1.804E+02 
5 1.259E+03 1.763E+02 
6 1.232E+03 1.724E+02 
7 1.206E+03 1.688E+02 
8 1.181E+03 1.653E+02 
9 1.157E+03 1.620E+02 
10 1.135E+03 1.589E+02 
11 1.110E+03 1.554E+02 
12 1.088E+03 1.523E+02 
13 1.068E+03 1.495E+02 
14 1.049E+03 1.469E+02 
15 1.033E+03 1.446E+02 
16 1.012E+03 1.417E+02 
17 9.934E+02 1.391E+02 
18 9.759E+02 1.366E+02 
19 9.595E+02 1.343E+02 
20 9.443E+02 1.322E+02 
21 9.267E+02 1.297E+02 
22 9.103E+02 1.274E+02 
23 8.950E+02 1.253E+02 
24 8.805E+02 1.233E+02 
25 8.666E+02 1.213E+02 
26 8.525E+02 1.194E+02 
27 8.382E+02 1.173E+02 
28 8.245E+02 1.154E+02 
29 8.114E+02 1.136E+02 
30 7.992E+02 1.119E+02 
31 7.858E+02 1.100E+02 
32 7.730E+02 1.082E+02 
33 7.610E+02 1.065E+02 
34 7.493E+02 1.049E+02 
35 7.381E+02 1.033E+02 
36 7.262E+02 1.017E+02 
37 7.150E+02 1.001E+02 
Time (yr) 
Line Load 
Power (W/m) 
Line Load 
Power (W/m) 
with 
Ventilation 
38 7.042E+02 9.859E+01 
39 6.938E+02 9.713E+01 
40 6.838E+02 9.573E+01 
41 6.733E+02 9.426E+01 
42 6.632E+02 9.284E+01 
43 6.535E+02 9.148E+01 
44 6.441E+02 9.018E+01 
45 6.351E+02 8.892E+01 
46 6.258E+02 8.762E+01 
47 6.169E+02 8.637E+01 
48 6.083E+02 8.517E+01 
49 6.000E+02 8.400E+01 
50 5.920E+02 8.287E+01 
50.5 5.920E+02 3.400E+01 
51 5.837E+02 5.837E+02 
52 5.757E+02 5.757E+02 
53 5.679E+02 5.679E+02 
54 5.603E+02 5.603E+02 
55 5.531E+02 5.531E+02 
56 5.457E+02 5.457E+02 
57 5.384E+02 5.384E+02 
58 5.315E+02 5.315E+02 
59 5.247E+02 5.247E+02 
60 5.182E+02 5.182E+02 
61 5.115E+02 5.115E+02 
62 5.050E+02 5.050E+02 
63 4.988E+02 4.988E+02 
64 4.926E+02 4.926E+02 
65 4.868E+02 4.868E+02 
66 4.808E+02 4.808E+02 
67 4.750E+02 4.750E+02 
68 4.694E+02 4.694E+02 
69 4.639E+02 4.639E+02 
70 4.586E+02 4.586E+02 
71 4.533E+02 4.533E+02 
72 4.481E+02 4.481E+02 
73 4.430E+02 4.430E+02 
74 4.381E+02 4.381E+02 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
Table S-4. Average Line Load (Continued) 
MDL-NBS-GS-000006 REV 01 S-13 October 2004 
Time (yr) 
Line Load 
Power (W/m) 
Line Load 
Power (W/m) 
with 
Ventilation 
75 4.333E+02 4.333E+02 
76 4.285E+02 4.285E+02 
77 4.238E+02 4.238E+02 
78 4.192E+02 4.192E+02 
79 4.148E+02 4.148E+02 
80 4.104E+02 4.104E+02 
81 4.061E+02 4.061E+02 
82 4.019E+02 4.019E+02 
83 3.978E+02 3.978E+02 
84 3.938E+02 3.938E+02 
85 3.898E+02 3.898E+02 
86 3.859E+02 3.859E+02 
87 3.822E+02 3.822E+02 
88 3.784E+02 3.784E+02 
89 3.748E+02 3.748E+02 
90 3.713E+02 3.713E+02 
91 3.678E+02 3.678E+02 
92 3.644E+02 3.644E+02 
93 3.611E+02 3.611E+02 
94 3.578E+02 3.578E+02 
95 3.546E+02 3.546E+02 
96 3.515E+02 3.515E+02 
97 3.484E+02 3.484E+02 
98 3.454E+02 3.454E+02 
99 3.425E+02 3.425E+02 
100 3.396E+02 3.396E+02 
110 3.142E+02 3.142E+02 
120 2.927E+02 2.927E+02 
130 2.742E+02 2.742E+02 
140 2.583E+02 2.583E+02 
150 2.443E+02 2.443E+02 
160 2.335E+02 2.335E+02 
170 2.239E+02 2.239E+02 
180 2.152E+02 2.152E+02 
190 2.074E+02 2.074E+02 
200 2.002E+02 2.002E+02 
250 1.752E+02 1.752E+02 
300 1.578E+02 1.578E+02 
350 1.444E+02 1.444E+02 
Time (yr) 
Line Load 
Power (W/m) 
Line Load 
Power (W/m) 
with 
Ventilation 
400 1.334E+02 1.334E+02 
450 1.240E+02 1.240E+02 
500 1.159E+02 1.159E+02 
550 1.087E+02 1.087E+02 
600 1.022E+02 1.022E+02 
650 9.647E+01 9.647E+01 
700 9.122E+01 9.122E+01 
750 8.643E+01 8.643E+01 
800 8.202E+01 8.202E+01 
850 7.800E+01 7.800E+01 
900 7.428E+01 7.428E+01 
950 7.088E+01 7.088E+01 
1000 6.767E+01 6.767E+01 
1500 4.666E+01 4.666E+01 
2000 3.660E+01 3.660E+01 
2500 3.154E+01 3.154E+01 
3000 2.874E+01 2.874E+01 
3500 2.695E+01 2.695E+01 
4000 2.569E+01 2.569E+01 
4500 2.466E+01 2.466E+01 
5000 2.375E+01 2.375E+01 
5500 2.292E+01 2.292E+01 
6000 2.212E+01 2.212E+01 
6500 2.139E+01 2.139E+01 
7000 2.070E+01 2.070E+01 
7500 2.002E+01 2.002E+01 
8000 1.938E+01 1.938E+01 
8500 1.877E+01 1.877E+01 
9000 1.820E+01 1.820E+01 
9500 1.763E+01 1.763E+01 
10000 1.708E+01 1.708E+01 
15000 1.284E+01 1.284E+01 
20000 9.955E+00 9.955E+00 
25000 7.984E+00 7.984E+00 
30000 6.578E+00 6.578E+00 
35000 5.518E+00 5.518E+00 
40000 4.721E+00 4.721E+00 
45000 4.075E+00 4.075E+00 
50000 3.582E+00 3.582E+00 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
Table S-4. Average Line Load (Continued) 
MDL-NBS-GS-000006 REV 01 S-14 October 2004 
Time (yr) 
Line Load 
Power (W/m) 
Line Load 
Power (W/m) 
with 
Ventilation 
55000 3.166E+00 3.166E+00 
60000 2.808E+00 2.808E+00 
65000 2.526E+00 2.526E+00 
70000 2.279E+00 2.279E+00 
75000 2.068E+00 2.068E+00 
80000 1.880E+00 1.880E+00 
85000 1.728E+00 1.728E+00 
90000 1.616E+00 1.616E+00 
95000 1.504E+00 1.504E+00 
100000 1.387E+00 1.387E+00 
150000 9.522E-01 9.522E-01 
200000 8.589E-01 8.589E-01 
250000 8.389E-01 8.389E-01 
300000 8.203E-01 8.203E-01 
350000 7.945E-01 7.945E-01 
400000 7.746E-01 7.746E-01 
450000 7.555E-01 7.555E-01 
500000 6.960E-01 6.960E-01 
550000 6.772E-01 6.772E-01 
600000 6.574E-01 6.574E-01 
650000 6.389E-01 6.389E-01 
700000 6.139E-01 6.139E-01 
750000 5.957E-01 5.957E-01 
800000 5.769E-01 5.769E-01 
850000 5.589E-01 5.589E-01 
900000 5.350E-01 5.350E-01 
950000 5.172E-01 5.172E-01 
1000000 4.992E-01 4.992E-01 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-15 October 2004 
The ventilation efficiency used in the analysis is 86 percent for a 50-year period for an 800-m 
drift as presented in Ventilation Model and Analysis Report (BSC 2004 [DIRS 169862], 
Table 8-3). 
To assign the function for the calculation of the average planar heat flux, note that line load must 
be divided by the waste package spacing of 81 m (BSC 2004 [DIRS 168489], Table 1) to express 
the heat flux in the vertical direction. Note that in MathCad 11 a := symbol is an assignment 
statement for a function or a variable. The heat loading function (see Figure S-2) that is defined 
using the MathCad linear interpolation function has the form q(t)=linterp(QLoad<1> =x 
,QLoad<3> =y,t) where x is the interpolation vector in time, y is the heat loading interpolation 
vector, and t is the time at which the interpolation function is evaluated. 
qR t ( ) linterp QLoad 1 < > 
QLoad 3 < > 
, t , ( ) 
W
m 
81 m  
 := 
Plot the planar heat loading as a function of time in years. 
t 1 2 , 20000 .. := 
1 10 100 1 .103 1 .104 1 .105 
0.1
1 
10 
Time(Years) 
Planar Heat Loading (W/m) 
Sources: D&E / PA/C IED Typical Waste Package Components Assembly (BSC 2004 [DIRS 167754]); 
D&E / PA/C IED Emplacement Drift Configuration and Environment (BSC 2004 [DIRS 168489], Table 1). 
Note: Average waste package line load is reduced by 86% from 0 to 50 years to account for the effect of 
ventilation. 
Figure S-2. Average Waste Package Line Loading 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-16 October 2004 
Because the analysis examines the change in temperature, the initial temperatures can be set to 
zero, and the change in temperature can then be calculated. The change in temperature can then 
be added to the initial temperature. 
S4. PREDICTION OF TEMPERATURE AT THE REPOSITORY HORIZON UNDER 
STEADY-STATE CONDITIONS 
The prediction of repository temperatures for postclosure analysis considers time-dependent heat 
diffusion through the media. With the analysis presented below, the steady-state solution should 
tend to overpredict the influence of the nonrepository horizon units. This approach is adequate 
for the purpose of this analysis. 
Calculating the effective thermal conductivities shown in Equation S-18 for the saturated case 
gives the values (see Equation S-2): 
d12 
1 
n1 
i 
di 
.i .= 
.... 
.
. 
1.54 
W 
mK  
= 
d32 
1 
n2 
i 
d'i 
.'i .= 
1.34 
W 
mK  
= 
(Eq. S-17) 
The function to predict repository driftwall temperature is based upon Equation S-10 is presented 
in Equation S-19. 
t2 t ( ) 
qR t ( ) 
1 
1 
n1 
i 
di 
.i .= 
.... 
.
. 
1 
1 
n2 
i 
d'i 
.'i .= 
+ 
:= 
(Eq. S-18) 
Plotting the base-case temperature as a function of time from 500 years to 2,000 years, 
Figure S-3 is generated. Note that after about 500 years, heat has diffused away from the 
repository horizon units into the nonrepository horizon units. 
t 500 501 , 20000 .. := 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-17 October 2004 
100 1 .103 1 .104 1 .105 
0 
50 
100 
150 
200 
Time(Years) 
Temperature (C) 
Figure S-3. Prediction of Temperature with Time for the QuasiSteady-State Model 
S5. UNCERTAINTY ANALYSIS TEMPERATURE RESULTS FROM THE 
STEADY-STATE SOLUTION 
In Section S4, the repository temperature, as a function of time, was shown. The following 
analysis evaluates the impact of uncertainty in the thermal conductivity (Kth) for each of the 
units on this temperature distribution. The analysis will be done using Equation S-13 as 
presented by Hahn and Shapiro (1967 [DIRS 146529], p. 231). As discussed above, the 
uncertainty of the thermal conductivity for each of the lithostratigraphic units that is related to 
the square root of the variance will be represented by the standard deviation associated with the 
thermal conductivity predictions multiplied by a factor of 1.96. 
The calculation reflects the exponential decay of heat. Extracting the standard deviation from 
the summary data in Table 6-13 yields the data arrays shown in Table S-5. The submatrix 
function is used with the same beginning and ending rows in column K of Table S-1. 
s submatrix Strat 3 , 21 , 11 , 11 , ( )
W 
mK  
 := s' submatrix Strat 22 , 36 , 11 , 11 , ( )
W 
mK  
 := 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-18 October 2004 
Table S-5. Uncertainty in Saturated Thermal Conductivity Above and Below the Repository Horizon 
Above the Repository Horizon Below the Repository Horizon 
s 
1 
1
2
3
4
5
6
7
8
9 
10 
11 
12 
13 
14 
15 
16 
17 
18 
19 
0.38 
0.38 
0.38 
0.39 
0.39 
0.29 
0.29 
0.29 
0.29 
0.29 
0.29 
0.29 
0.29 
0.44 
0.38 
0.38 
0.48 
0.49 
0.49 
W 
mK  
= 
s' 
1 
1
2
3
4
5
6
7
8
9 
10 
11 
12 
13 
14 
15 
16 
17 
18 
0.49 
0.52 
0.52 
0.49 
0.29 
0.29 
0.29 
0.28 
0.28 
0.28 
0.28 
0.28 
0.24 
0.24 
0.33 
W 
mK  
= 
Note that the solution to the sensitivity (or the partial derivatives) as represented by 
Equations S-15 and S-16 contains several summations that are constant for the analysis. In order 
to simplify the solution, the following constant terms (Term1, Term2, and Term12) are defined: 
Term1 
1 
n1 
i 
di 
.i .= 
.... 
.
.
2 
:= Term1 4.04 104  s6K2 
kg2 
= 
(Eq. S-19) 
Term2 
1 
n2 
i 
d'i 
.'i .= 
.... .
.
2 
:= Term2 4.34 104  s6K2 
kg2 
= 
(Eq. S-20) 
Term12 
1 
1 
n1 
i 
di 
.i .= 
1 
1 
n2 
i 
d'i 
.'i .= 
+ ..... 
.
.
.
2 
:= 
Term12 9.55 10 5 -  kg2 
s6K2 
= 
(Eq. S-21) 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-19 October 2004 
Now substitute the constant terms into expressions into the partial derivatives in Equations S-15 
and S-16: 
Ki
t2 
. 
. 
qR 
Term12 Term1  
di 
Ki ( )2 
 
(Eq. S-22) 
K'i
t2 
. 
. 
qR 
Term12 Term2  
d'i 
K'i ( )2 
 
(Eq. S-23) 
Now form the sum for the variances that are consistent with Equation S-12. 
Var 
1 
n1 
i 
qR 
Term12 Term1  
di 
Ki ( )2 
 
.... 
.
... 
2 
si ( )2 
 
..... 
..... 
.=
1 
n2 
i 
qR 
Term12 Term2  
d'i 
K'i ( )2 
 
.... 
.... 
2 
s'i ( )2 
 
..... 
..... 
.= 
+ 
(Eq. S-24) 
Now define a function that expresses the uncertainty in the waste package heat loading. 
Vart t ( ) 
1 
n1 
i 
qR t ( ) 
Term12 Term1  
di 
.i ( )2 
 
.... 
.
... 
2 
si ( )2 
 
.... 
.
... 
.=
1 
n2 
i 
qR t ( ) 
Term12 Term2  
d'i 
.'i ( )2 
 
.... 
.... 
2 
s'i ( )2 
 
.... 
.... 
.= 
+ := 
(Eq. S-25) 
The range of uncertainty as a function of time is plotted in Figure S-4. The solid line represents 
the mean temperature prediction. The dotted line represents the mean temperature plus or minus 
one standard deviation (square root of the variance from Equation S-25). Figure S-5 displays 
results of the analysis and indicates that the temperature uncertainty is small. The uncertainty is 
7 degrees Celsius after 800 years. The uncertainty is an overestimate because the more remote 
lithostratigraphic units will not influence repository temperature until sometime after waste 
emplacement, because of the time required for the heat to propagate to the remote nonrepository 
horizon units. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-20 October 2004 
100 1 .103 1 .104 1 .105 
0 
50 
100 
150 
200 
Mean plus Uncertainty Estimate 
Mean 
Mean minus Uncertainty Estimate 
Time(Years) 
Temperature Increase (degrees C) 
Figure S-4. Prediction of Temperature Range with Time for the Steady State Analysis 
100 1 .103 1 .104 1 .105 
0
2
4
6
8 
10 
12 
Time(Years) 
Temperature Increase (degrees C) 
Figure S-5. Uncertainty as a Function of Time 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-21 October 2004 
Calculating the contribution to variance for the various layers at 500 years (a representative 
time), the percentage contribution to variance for each of the thermal conductivities is: 
Above the repository horizon. Below the repository horizon. 
i 1 n1 .. := j 1 n2 .. := 
VectorAi 
qR 500 ( ) 
Term12 Term1  
di 
.i ( )2 
 
.... 
.
... 
2 
si ( )2 
 
.... 
.
... 
:= VectorBj 
qR 500 ( ) 
Term12 Term2  
d'j 
.' j ( )2 
 
.... 
.... 
2 
s' j ( )2 
 
.... 
.... 
:= 
(Eq. S-26) 
Use the MathCad function stack to form a single vector from the ground surface to the base of 
the model. Vector =: stack means to form a single vector with Vector A above and Vector B 
below columnwise. 
Vector stack VectorA VectorB , ( ) := (Eq. S-27) 
The results of the analysis are output in Table S-6. 
Table S-6. Contribution of Variance of Temperature from the Thermal Conductivity of Each 
Lithostratigraphic Unit 
Lithostratigraphic 
Unit 
Change in 
Temperature 
(C) 
Percent 
Contribution 
Crystal-Rich 
Tiva/Post Tiva 
0.00 0.00% 
Tpcp (2) 0.00 0.00% 
TpcLD (3) 0.77 0.73% 
Tpcpv3 (4) 0.45 0.43% 
Tpcpv2 (5) 0.00 0.00% 
Tpcpv1(6) 0.46 0.44% 
Tpbt4 (7) 0.28 0.27% 
Yucca (8) 0.04 0.03% 
Tpbt3_dc (9) 1.39 1.33% 
Pah (10) 11.88 11.36% 
Tpbt2 (11) 0.13 0.12% 
Tptrv3 (12) 0.13 0.12% 
Tptrv2 (13) 0.13 0.12% 
Tptrv1 (14) 0.04 0.03% 
Tptrn (15) 3.89 3.72% 
Tptrl (16) 0.00 0.00% 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-22 October 2004 
Table S-6. Contribution of Variance of Temperature from the Thermal Conductivity of Each 
Lithostratigraphic Unit (Continued) 
Lithostratigraphic 
Unit 
Change in 
Temperature 
(C) 
Percent 
Contribution 
Tptpul 23.66 22.64% 
Tptpmn 1.96 1.88% 
Tptpll above 5.25 5.02% 
Tptpll below 7.80 7.46% 
Tptpln 1.06 1.01% 
Tptpln 0.26 0.25% 
Tptpv3 (18) 33.44 32.00% 
Tptpv2(19) 0.09 0.08% 
Tptpv1(20) 0.09 0.08% 
Tpbt1 1.84 1.76% 
Calico 1.48 1.42% 
Calico 1.49 1.42% 
Calico 1.48 1.42% 
Calico 1.49 1.42% 
Calicobt 1.11 1.07% 
Prowuv 1.56 1.50% 
Prowuc 0.83 0.79% 
Prowmd 0.03 0.03% 
Total 104.50 100.00% 
These results show that the primary contributions to temperature prediction variances originate 
with uncertainties in the Tptpv3 unit. 
S6. INFLUENCE OF HIGH POROSITY ZONES IN THE TIVA CANYON 
Thermal conductivity in the welded tuffs of the Tiva Canyon are influenced by zones of 
lithophysal porosity. The quasisteady-state can be used to assess the influence of including a 
lithophysal porosity on thermal conductivity (1.81 W/(m K) (see Table 6-13)). 
Strat5 6 , 1.81 = 
Now, consider that this value would be lower due to the air porosity effects. Assume a porosity 
of 20 percent, and calculate the reduction in rock-mass thermal conductivity. Thermal 
Conductivity of the Potential Repository Horizon (BSC 2004 [DIRS 169854], Section 6.1.8), 
states that it was found that the parallel or the volumetric averaging model applied to the 
calculation of bulk or rock-mass thermal conductivity. The reported value for the thermal 
conductivity of air is 0.01615*BTU/(hr*ft*R), which equals 0.028 W/(m K) at 50C or 120F 
(Chapman 1974 [DIRS 152938], p. 593). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-23 October 2004 
Strat 5 6 , 1 0.2 - ( ) 1.81  0.2 0.028  + := Strat5 6 , 1.45 = 
Now extract the thermal conductivity for the wet case above and below the repository. 
. submatrix Strat 3 , 21 , 6 , 6 , ( )
W 
mK  
 := .' submatrix Strat 22 , 36 , 6 , 6 , ( )
W 
mK  
 := 
The function for repository driftwall temperature based upon Equation S-10 is shown below in 
Equation S-19. 
t3 t ( ) 
qR t ( ) 
1 
1 
n1 
i 
di 
.i .= 
.... 
.
. 
1 
1 
n2 
i 
d'i 
.'i .= 
+ 
:= 
(Eq. S-28) 
A plot of the base-case temperature as a function of time is shown in Figure S-6, and compared 
to the base-case prediction shown in Figure S-3. 
t2 800 ( ) 103.61K = 
t 500 501 , 20000 .. := * 
100 1 .103 1 .104 1 .105 
0 
50 
100 
150 
200 
Base Case 
TC High Porosity Zone
Time(Years) Temperature (C) 
Figure S-6. QuasiSteady-State Analysis for Variations in the Tiva Canyon Thermal Conductivity 
Over 20,000 Years 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-24 October 2004 
Take 500 years and calculate the contribution to variance for the various layers. 
i 1 n1 .. := j 1 n2 .. := n2 15 = 
VectorAi 
qR 500 ( ) 
Term12 Term1  
di 
.i ( )2 
 
.... 
.
... 
2 
si ( )2 
 
.... 
.
... 
:= 
VectorBj 
qR 500 ( ) 
Term12 Term2  
d'j 
.' j ( )2 
 
.... 
.... 
2 
s' j ( )2 
 
.... 
.... 
:= 
Vector stack VectorA VectorB , ( ) := 
(Eq. S-29) 
Output of the analyses are listed in Table S-7. 
Table S-7. Percent Contribution to Temperature Variance Considering a High Porosity Zone in the Tiva 
Canyon 
Lithostratigraphic 
Unit 
Change in 
Temperature 
(C) 
Percent 
Contribution 
Crystal-Rich 
Tiva/Post Tiva 
0.00 0.00% 
Tpcp (2) 0.00 0.00% 
TpcLD (3) 1.84 1.75% 
Tpcpv3 (4) 0.45 0.43% 
Tpcpv2 (5) 0.00 0.00% 
Tpcpv1(6) 0.46 0.44% 
Tpbt4 (7) 0.28 0.26% 
Yucca (8) 0.04 0.03% 
Tpbt3_dc (9) 1.39 1.32% 
Pah (10) 11.88 11.25% 
Tpbt2 (11) 0.13 0.12% 
Tptrv3 (12) 0.13 0.12% 
Tptrv2 (13) 0.13 0.12% 
Tptrv1 (14) 0.04 0.03% 
Tptrn (15) 3.89 3.68% 
Tptrl (16) 0.00 0.00% 
Tptpul 23.66 22.41% 
Tptpmn 1.96 1.86% 
Tptpll above 5.25 4.97% 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-25 October 2004 
Table S-7. Percent Contribution to Temperature Variance Considering a High Porosity Zone in the Tiva 
Canyon (Continued) 
Lithostratigraphic 
Unit 
Change in 
Temperature 
(C) 
Percent 
Contribution 
Tptpll below 7.80 7.39% 
Tptpln 1.06 1.00% 
Tptpln 0.26 0.25% 
Tptpv3 (18) 33.44 31.68% 
Tptpv2(19) 0.09 0.08% 
Tptpv1(20) 0.09 0.08% 
Tpbt1 1.84 1.74% 
Calico 1.48 1.41% 
Calico 1.49 1.41% 
Calico 1.48 1.40% 
Calico 1.49 1.41% 
Calicobt 1.11 1.05% 
Prowuv 1.56 1.48% 
Prowuc 0.83 0.78% 
Prowmd 0.031 0.03% 
105.58 100.00% 
S7. CONCLUSIONS 
An analysis was performed to assess the significance of the nonrepository horizon units on the 
uncertainty in repository temperature over extended periods (20,000 years). The analysis used 
the steady-state heat transfer by heat conduction in the vertical direction. The thermal 
conductivity under saturation conditions of both the repository and the nonrepository horizon 
units are included in this analysis. The analysis predicts an approximate increase in temperature 
(between 0C and 6C) after 1,000 years due to an average repository heat loading when 
maximum uncertainties are added to the nominal thermal conductivity values. This represents an 
extreme case, because the thermal conductivity uncertainties are multiplied by a factor of 1.96. 
An uncertainty analysis utilizing Hahn and Shapiro (1967 [DIRS 146529], p. 231) was 
performed, and predicted that the Tsw38 layer (Tptpv3) below the repository provides the most 
significant contribution to uncertainty over extended periods of time. This is because the rockmass 
thermal conductivity of this unit is much lower (0.8 W/(m K)) than the rock-mass thermal 
conductivity of the repository horizon unit (1.89 W/(m K) under saturated conditions. 
The steady-state analysis tends to overestimate the uncertainty of the nonrepository units 
because, in reality, heat diffuses more slowly from the repository horizon. The results show that 
immediately after closure, the variations in repository temperature (and, therefore, waste package 
temperature) are dominated by the uncertainty at the repository horizon. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 S-26 October 2004 
The steady-state heat conduction analysis was repeated using an increased lithophysal porosity in 
the Tiva Canyon unit. This unit has lithophysal porosity with a rock fabric that is similar to the 
Topopah Spring unit. The analysis shows that uncertainty in thermal properties of the Tiva 
Canyon is not significant. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX T 
NOMENCLATURE AND COORDINATES 
FOR THERMAL CONDUCTIVITY BOREHOLES

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 T-1 October 2004 
Table T-1. Nomenclature and Coordinates for Thermal Conductivity Boreholes 
Borehole ID 
Casing 
Elevation 
(ft. MSL) 
X_COORD 
(NV Stateplane 
Central ft.) 
Y_COORD 
(NV Stateplane 
Central ft.) Source DTN 
UE-25 c #1 3709.11 569680.562 757096.750 MO9906GPS98410.000 
UE-25 c #2 3715.29 569633.938 756849.625 MO9906GPS98410.000 
UE-25 J-13 3319.44 579647.938 749202.000 MO9906GPS98410.000 
UE-25 NRG #2 3803.02 569162.438 765763.750 MO9906GPS98410.000 
UE-25 NRG #2a 3782.90 569001.062 765699.938 MO9906GPS98410.000 
UE-25 NRG #2b 3803.08 569214.562 765765.250 MO9906GPS98410.000 
UE-25 NRG #3 3826.33 568316.125 766250.625 MO9906GPS98410.000 
UE-25 NRG #4 4101.64 566820.000 767080.188 MO9906GPS98410.000 
UE-25 NRG #5 4108.66 564769.875 767889.625 MO9906GPS98410.000 
UE-25 UZ #16 4001.58 564857.500 760535.125 MO9906GPS98410.000 
UE-25 UZN #63 3944.06 566169.625 768837.250 MO9906GPS98410.000 
USW H-1 4275.75 562388.438 770254.812 MO9906GPS98410.000 
USW NRG-6 4093.02 564187.000 766726.500 MO9906GPS98410.000 
USW NRG-7a 4208.52 562984.000 768880.125 MO9906GPS98410.000 
USW SD-12 4343.17 561605.625 761956.562 MO9906GPS98410.000 
USW SD-6 4906.42 558607.680 762421.390 MO9912GSC99492.000 
USW SD-7 4474.99 561240.250 758949.875 MO9906GPS98410.000 
USW SD-9 4274.97 561818.000 767998.500 MO9906GPS98410.000 
USW UZ-14 4427.20 560141.562 771309.812 MO9906GPS98410.000 
USW UZ-7 4170.96 562911.625 760837.000 MO9906GPS98410.000 
USW UZ-7a 4230.23 562269.812 760692.750 MO9906GPS98410.000 
USW WT-24 4902.36 562329.905 776703.061 MO9905LUSWWT24.000 
USW UZ-N11 5223.72 559020.938 780573.938 MO9906GPS98410.000 
USW UZ-N15 5109.43 559551.750 778090.562 MO9906GPS98410.000 
USW UZ-N16 5116.65 559626.000 778150.812 MO9906GPS98410.000 
USW UZ-N17 5127.55 559995.125 778224.125 MO9906GPS98410.000 
USW UZ-N27 4859.42 558871.750 771569.375 MO9906GPS98410.000 
USW UZ-N31 4153.84 562751.938 764245.625 MO9906GPS98410.000 
USW UZ-N32 4158.10 562799.625 764302.625 MO9906GPS98410.000 
USW UZ-N33 4331.26 561192.188 770070.125 MO9906GPS98410.000 
USW UZ-N34 4323.76 561251.375 770158.750 MO9906GPS98410.000 
USW UZ-N35 4247.41 562309.938 762264.000 MO9906GPS98410.000 
USW UZ-N36 4642.23 563582.688 773899.500 MO9906GPS98410.000 
USW UZ-N37 4123.59 563713.500 767499.125 MO9906GPS98410.000 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 T-2 October 2004 
Table T-1. Nomenclature and Coordinates for Thermal Conductivity Boreholes (Continued) 
Borehole ID 
Casing 
Elevation 
(ft. MSL) 
X_COORD 
(NV Stateplane 
Central ft.) 
Y_COORD 
(NV Stateplane 
Central ft.) Source DTN 
USW UZ-N38 4148.92 563343.875 767466.312 MO9906GPS98410.000 
USW UZ-N53 4055.66 564237.250 760096.250 MO9906GPS98410.000 
USW UZ-N54 4045.93 564262.188 760271.938 MO9906GPS98410.000 
USW UZ-N55 4072.58 564248.250 760502.875 MO9906GPS98410.000 
USW UZ-N57 4185.70 560829.812 755164.500 MO9906GPS98410.000 
USW UZ-N58 4181.25 560862.188 755240.375 MO9906GPS98410.000 
USW UZ-N59 4179.81 560888.375 755321.250 MO9906GPS98410.000 
USW UZ-N61 4184.22 560893.938 755375.938 MO9906GPS98410.000 
USW UZ-N62 4884.02 558302.688 757125.188 MO9906GPS98410.000 
USW UZ-N64 4791.28 559435.500 765728.125 MO9906GPS98410.000 
MSL = mean sea level 
NOTE: The date of survey for each borehole is available in the source DTNs.

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX U 
CORRELATION CHART FOR MODEL STRATIGRAPHY

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 U-1 October 2004 
Table U-1. Correlation Chart for Model Stratigraphy 
Stratigraphic Unita Abbreviationa 
PTna 
and 
RHHb 
Geologic 
Framework 
Model Unit 
Group 
Formation 
Member 
Zone 
Subzone 
Alluvium and Colluvium Qal, Qc Alluvium 
Timber Mountain Group Tm 
Rainier Mesa Tuff Tmr 
Paintbrush Group Tp 
Post-tuff unit x bedded tuff Tpbt6 
Tuff unit xc Tpki (informal) Crystal-Rich 
Pre-tuff unit x bedded tuff Tpbt5 Tiva and 
Tiva Canyon Tuff Tpc Post-Tiva 
Crystal-Rich Member Tpcr 
Vitric zone Tpcrv 
Nonwelded subzone Tpcrv3 
Moderately welded subzone Tpcrv2 
Densely welded subzone Tpcrv1 
Nonlithophysal subzone Tpcrn 
Subvitrophyre transition subzone Tpcrn4 
Pumice-poor subzone Tpcrn3 
Mixed pumice subzone Tpcrn2 
Crystal transition subzone Tpcrn1 
Lithophysal zone Tpcrl 
Crystal transition subzone Tpcrl1 
Crystal-Poor Member Tpcp 
Upper lithophysal zone Tpcpul 
Spherulite-rich subzone Tpcpul1 
Middle nonlithophysal zone Tpcpmn 
Upper subzone Tpcpmn3 
Lithophysal subzone Tpcpmn2 
Lower subzone Tpcpmn1 Tpcp 
Lower lithophysal zone Tpcpll 
Hackly fractured subzone Tpcpllh 
Lower nonlithophysal zone Tpcpln 
Hackly subzone Tpcplnh 
Columnar subzone Tpcplnc TpcLD 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 U-2 October 2004 
Table U-1. Correlation Chart for Model Stratigraphy (Continued) 
Stratigraphic Unita Abbreviationa 
PTna 
and 
RHHb 
Geologic 
Framework 
Model Unit 
Group 
Formation 
Member 
Zone 
Subzone 
Vitric zone Tpcpv 
Densely welded subzone Tpcpv3 Tpcpv3 
Moderately welded 
subzone Tpcpv2 Tpcpv2 
Nonwelded subzone Tpcpv1 Tpcpv1 
Pre-Tiva Canyon bedded tuff Tpbt4 Tpbt4 
Yucca Mountain Tuff Tpy Yucca 
Pre-Yucca Mountain bedded tuff Tpbt3 Tpbt3_dcd 
Pah Canyon Tuff Tpp PTn Pah 
Pre-Pah Canyon bedded tuff Tpbt2 Tpbt2 
Topopah Spring Tuff Tpt 
Crystal-Rich Member Tptr 
Vitric zone Tptrv 
Nonwelded subzone Tptrv3 Tptrv3 
Moderately welded subzone Tptrv2 Tptrv2 
Densely welded subzone Tptrv1 Tptrv1 
Nonlithophysal zone Tptrn 
Dense subzone Tptrn3 
Vapor-phase corroded subzone Tptrn2 
Crystal transition subzone Tptrn1 Tptrn 
Lithophysal zone Tptrl 
Crystal transition subzone Tptrl1 Tptrl 
Crystal-Poor Member Tptp 
Lithic-rich zone Tptpf or Tptrf Tptf 
Tptpul 
Upper lithophysal zone Tptpul RHH RHHtop 
Middle nonlithophysal zone Tptpmn 
Nonlithophysal subzone Tptpmn3 
Lithophysal bearing subzone Tptpmn2 
Nonlithophysal subzone Tptpmn1 Tptpmn 
Lower lithophysal zone Tptpll Tptpll 
Lower nonlithophysal zone Tptpln Tptpln 
Vitric zone Tptpv 
Densely welded subzone Tptpv3 Tptpv3 
Moderately welded subzone Tptpv2 Tptpv2 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 U-3 October 2004 
Table U-1. Correlation Chart for Model Stratigraphy (Continued) 
Stratigraphic Unita Abbreviationa 
PTna 
and 
RHHb 
Geologic 
Framework 
Model Unit 
Group 
Formation 
Member 
Zone 
Subzone 
Nonwelded subzone Tptpv1 Tptpv1 
Pre-Topopah Spring bedded tuff Tpbt1 Tpbt1 
Calico Hills Formation Ta Calico 
Bedded tuff Tacbt Calicobt 
Crater Flat Group Tc 
Prow Pass Tuff Tcp 
Prow Pass Tuff upper vitric 
nonwelded zone (Tcpuv)e Prowuv 
Prow Pass Tuff upper crystalline 
nonwelded zone (Tcpuc)e Prowuc 
Prow Pass Tuff moderately densely 
welded zone (Tcpmd)e Prowmd 
Prow Pass Tuff lower crystalline 
nonwelded zone (Tcplc)e Prowlc 
Prow Pass Tuff lower vitric 
nonwelded zone (Tcplv)e Prowlv 
Pre-Prow Pass Tuff bedded tuff (Tcpbt) e Prowbt 
Bullfrog Tuff Tcb 
Bullfrog Tuff upper vitric nonwelded 
zone (Tcbuv)e Bullfroguv 
Bullfrog Tuff upper crystalline 
nonwelded zone (Tcbuc)e Bullfroguc 
Bullfrog Tuff welded zone (Tcbmd)e Bullfrogmd 
Bullfrog Tuff lower crystalline 
nonwelded zone (Tcblc)e Bullfroglc 
Bullfrog Tuff lower vitric nonwelded 
zone (Tcblv)e Bullfroglv 
Pre-Bullfrog Tuff bedded tuff (Tcbbt)e Bullfrogbt 
Tram Tuff Tct 
T
ram Tuff upper vitric nonwelded 
zone (Tctuv)e Tramuv 
T
ram Tuff upper crystalline 
nonwelded zone (Tctuc)e Tramuc 
T
ram Tuff moderately densely 
welded zone (Tctmd)e Trammd 
T
ram Tuff lower crystalline 
nonwelded zone (Tctlc)e Tramlc 
T
ram Tuff lower vitric nonwelded 
zone (Tctlv)e Tramlv 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 U-4 October 2004 
Table U-1. Correlation Chart for Model Stratigraphy (Continued) 
Stratigraphic Unita Abbreviationa 
PTna 
and 
RHHb 
Geologic 
Framework 
Model Unit 
Group 
Formation 
Member 
Zone 
Subzone 
Pre-Tram Tuff bedded tuff (Tctbt)e Trambt 
Lava and flow breccia (informal) Tll 
Bedded tuff Tllbt 
Lithic Ridge Tuff Tr 
Bedded tuff Tlrbt 
Lava and flow breccia (informal) Tll2 
Bedded tuff Tllbt 
Lava and flow breccia (informal) Tll3 
Bedded tuff Tll3bt Tund 
Older tuffs (informal) Tt 
Unit a (informal) Tta 
Unit b (informal) Ttb 
Unit c (informal) Ttc 
Sedimentary rocks and calcified tuff 
(informal) Tca 
Tuff of Yucca Flat (informal) Tyf 
Pre-Tertiary sedimentary rock 
Lone Mountain Dolomite Slm 
Roberts Mountain Formation Srm Paleozoic 
Source: Geologic Framework Model (GFM2000) (BSC 2004 [DIRS 170029], Table 6-2). 
NOTE: Shaded rows indicate header lines for subdivided units. 
a DTN MO9510RIB00002.004 [DIRS 103801]. 
b CRWMS M&O 1997 [DIRS 100223], pp. 43 to 50. 
c Correlated with the rhyolite of Comb Peak (Buesch et al. 1996 [DIRS 100106], Table 2). 
d Includes rhyolite of Delirium Canyon north of Yucca Wash (DTN GS980608314221.002 
[DIRS 107024]). 
e For the purposes of GFM2000, each formation in the Crater Flat Group was subdivided into six 
zones based on the requirements of the users of the geologic framework model. The 
subdivisions are upper vitric (uv), upper crystalline (uc), moderately to densely welded (md), 
lower crystalline (lc), lower vitric (lv), and bedded tuff (bt) (Buesch and Spengler 1999 
[DIRS 107905], pp. 62 to 64). 
PTN = Paintbrush nonwelded hydrologic unit; RHH = Repository Host Horizon 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 
APPENDIX V 
QUALIFICATION OF UNQUALIFIED DRY BULK DENSITY DATA 
CONTAINED IN 
DTN: GS920408312314.011, SEP TABLE S97135_0002 
AND 
DTN: GS930408312132.007, SEP TABLE S97276_001 
FOR USE IN 
MDL-NBS-GS-000006, REV 01 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 October 2004 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 V-1 October 2004 
This appendix presents the documentation for the data qualification of unqualified project data 
used as direct input only to this report. This data qualification has been performed in accordance 
with AP-SIII.2Q, Rev. 1 ICN 2, Qualification of Unqualified Data. 
Data for Qualification 
Product Output DTN SN0303T0503102.008 contains the average and standard deviation for 
saturated thermal conductivity, dry thermal conductivity, matrix porosity, and dry bulk density 
for the nonrepository GFM (BSC 2004 [DIRS 170029]) units. Two data tracking numbers 
(DTNs) that provide dry bulk density values to develop DTN SN0303T0503102.008 are 
unqualified. The applicable data to be qualified for intended use in this report are: 
1. GS920408312314.011 [DIRS 129660], Geohydrology of Test Well USW H-1, Yucca 
Mountain, Nye County, Nevada. 
The dry bulk density data for this DTN are contained in SEP table S97135_002. 
2. GS930408312132.007 [DIRS 129625], Geohydrologic Data and Test Results from 
Well J-13, Nevada Test Site, Nye County, Nevada. 
The dry bulk density data for this DTN are contained in SEP table S97276_001. 
Methods of Qualification Selected 
The method selected for qualification is corroborating data. The unqualified dry bulk density 
data sets from test wells USW H-1 and J-13 are compared to the qualified dry bulk density data 
from DTNs listed at the bottom of Table V-1. The rationale for this method is that if the 
unqualified dry bulk density data sets are in agreement to within the range of uncertainty 
established for model validation, the unqualified data can be considered qualified for intended 
use within this report. 
Evaluation Criteria 
The dry bulk density values in the two unqualified DTNs will be considered qualified for 
intended use if the difference in mean values of qualified versus unqualified data is within the 
95-percent confidence level. Specifically, if the normalized difference in mean values (column 
t in Table V-2) has an absolute value less than 1.96, then the data are considered qualified. 
Evaluation of the Technical Correctness of the Data 
Table V-1 contains the unqualified dry bulk density values from DTN GS920408312314.011 
([DIRS 129660], SEP table S97135_002) and DTN GS930408312132.007 ([DIRS 129625], SEP 
table S97276_001), and organizes the data according to layer characterization as presented in 
Table 6-13 of this report. Table V-1 also contains averaged qualified data; note that the data in 
Table V-1 are the same data presented in Table 6-13, but are split into sets, a small set of 
unqualified data from two wells (USW H-1 and J-13), and a large set of qualified data from the 
twenty-two remaining wells listed in Table 4-5. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 V-2 October 2004 
Table V-1. Qualified and Unqualified Dry Bulk Density Data 
Unqualified 
Dry Bulk Density Data 
Qualified 
Dry Bulk Density Data 
Well 
Name GFM Unit Layer Type 
Meas. 
Value 
(g/cm3) 
Mean 
(g/cm3) 
# 
points 
Std 
Dev 
Mean 
(g/cm3) Std Dev 
# 
points 
H-1 Tptrn Welded 2.0 2.19 0.177 1314 
H-1 Tptrn Welded 2.0 2.19 0.177 1314 
H-1 Tptrn Welded 2.0 2.19 0.177 1314 
H-1 Tptrn Welded 2.1 2.19 0.177 1314 
H-1 Tptrn Welded 2.2 2.19 0.177 1314 
H-1 Tptrn Welded 2.2 2.19 0.177 1314 
H-1 Tptrn Welded 2.2 2.19 0.177 1314 
H-1 Tptrn Welded 2.2 2.19 0.177 1314 
J-13 Tptrl Welded 2.08 2.11 9 0.093 2.19 0.177 1314 
J-13 Tptpv3 Vitric 2.31 2.31 0.087 116 
J-13 Tptpv3 Vitric 2.12 2.22 2 0.134 2.31 0.087 116 
H-1 Pah Non-welded 1.3 1.46 0.338 588 
H-1 Yucca Non-welded 1.3 1.46 0.338 588 
H-1 Yucca Non-welded 1.4 1.46 0.338 588 
J-13 Tpbt2 Non-welded 1.05 1.46 0.338 588 
J-13 Tpbt2 Non-welded 1.76 1.46 0.338 588 
J-13 Tptpv2 Non-welded 1.60 1.40 6 0.250 1.46 0.338 588 
H-1 Calicobt Calico 1.3 1.68 0.157 608 
H-1 Calicobt Calico 1.4 1.68 0.157 608 
J-13 Calicobt Calico 1.73 1.48 3 0.225 1.68 0.157 608 
H-1 Prowlv Non-welded (prow) 1.7 1.79 0.118 504 
H-1 Prowlv Non-welded (prow) 1.7 1.79 0.118 504 
H-1 Prowlv Non-welded (prow) 1.7 1.79 0.118 504 
J-13 Prowbt Non-welded (prow) 1.74 1.71 4 0.020 1.79 0.118 504 
H-1 Bullfrogbt Non-welded (bull) 1.8 1.89 0.162 61 
H-1 Bullfroguc Non-welded (bull) 2.1 1.89 0.162 61 
H-1 Bullfroguc Non-welded (bull) 1.9 1.89 0.162 61 
H-1 Bullfroguv Non-welded (bull) 1.6 1.89 0.162 61 
H-1 Bullfroguv Non-welded (bull) 1.6 1.89 0.162 61 
H-1 Bullfroguv Non-welded (bull) 1.6 1.89 0.162 61 
J-13 Bullfroguc Non-welded (bull) 1.92 1.79 7 0.197 1.89 0.162 61 
H-1 Bullfrogmd Welded (bull) 2.0 2.27 0.130 87 
H-1 Bullfrogmd Welded (bull) 2.1 2.27 0.130 87 
H-1 Bullfrogmd Welded (bull) 2.1 2.27 0.130 87 
H-1 Bullfrogmd Welded (bull) 2.1 2.27 0.130 87 
J-13 Bullfrogmd Welded (bull) 1.89 2.27 0.130 87 
J-13 Bullfrogmd Welded (bull) 2.07 2.04 6 0.085 2.27 0.130 87 
H-1 Tramlv Non-welded (tram) 2.0 1.67 0.130 26 
H-1 Tramlv Non-welded (tram) 2.0 1.67 0.130 26 
H-1 Tramlv Non-welded (tram) 2.0 1.67 0.130 26 
H-1 Tramlv Non-welded (tram) 2.2 1.67 0.130 26 
H-1 Tramlv Non-welded (tram) 2.1 1.67 0.130 26 
H-1 Tramlv Non-welded (tram) 2.1 1.67 0.130 26 
H-1 Tramuv Non-welded (tram) 1.8 1.67 0.130 26 
H-1 Tramuv Non-welded (tram) 1.8 1.67 0.130 26 
H-1 Tramuv Non-welded (tram) 2.0 1.67 0.130 26 
J-13 Tramlc Non-welded (tram) 1.93 1.67 0.130 26 
J-13 Tramuv Non-welded (tram) 1.95 1.99 11 0.121 1.67 0.130 26 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 V-3 October 2004 
Table V-1. Qualified and Unqualified Dry Bulk Density Data (Continued) 
Unqualified 
Dry Bulk Density Data 
Qualified 
Dry Bulk Density Data 
Well 
Name GFM Unit Layer Type 
Meas. 
Value 
(g/cm3) 
Mean 
(g/cm3) 
# 
points 
Std 
Dev 
Mean 
(g/cm3) Std Dev 
# 
points 
J-13 Trammd Welded (tram) 2.09 N/A N/A 0 
J-13 Trammd Welded (tram) 2.20 2.15 2 0.078 N/A N/A 0 
NOTES: 
Sources of unqualified data: 
DTN GS930408312132.007 [DIRS 129625] 
DTN GS920408312314.011 [DIRS 129660] 
Sources of qualified data: 
DTN MO0004QGFMPICK.000 [DIRS 152554] DTN GS000508312231.006 [DIRS 153237] 
DTN SNL01A05059301.007 [DIRS 108980] DTN SNL02030193001.002 [DIRS 120575] 
DTN GS000408312231.004 [DIRS 149582] DTN GS950308312231.002 [DIRS 108990] 
DTN GS950408312231.004 [DIRS 108986] DTN GS940508312231.006 [DIRS 107149] 
DTN GS930108312231.006 [DIRS 108997] DTN GS920508312231.012 [DIRS 109001] 
DTN GS940408312231.004 [DIRS 109000] DTN GS951108312231.009 [DIRS 108984] 
DTN GS951108312231.010 [DIRS 108983] DTN GS951108312231.011 [DIRS 108992] 
DTN GS960808312231.004 [DIRS 108985] DTN GS980708312242.010 [DIRS 106752] 
DTN GS980808312242.014 [DIRS 106748] DTN SNL02030193001.004 [DIRS 108415] 
DTN SNL02030193001.008 [DIRS 120597] DTN SNL02030193001.003 [DIRS 120578] 
DTN SNL02030193001.006 [DIRS 120579] DTN SNL02030193001.013 [DIRS 120614] 
DTN SNL02030193001.005 [DIRS 122545] DTN SNL02030193001.007 [DIRS 120582] 
DTN SNL02030193001.014 [DIRS 109609] DTN SNL02030193001.015 [DIRS 120617] 
DTN SNL02030193001.009 [DIRS 109614] DTN SNL02030193001.012 [DIRS 108416] 
DTN SNL02030193001.022 [DIRS 109613] DTN SNL02030193001.016 [DIRS 120619] 
DTN SNL02030193001.017 [DIRS 109610] DTN SNL02030193001.018 [DIRS 109611] 
DTN SNL02030193001.019 [DIRS 108431] DTN SNL02030193001.020 [DIRS 108432] 
DTN SNL02030193001.021 [DIRS 108433] DTN SNL01A05059301.002 [DIRS 150042] 
Qualified data are extracted from Output DTN: SN0307T0503102.009, files Input\QVDry Bulk-Dens\*.dat 
N/A = Not available. 
As can be seen in Table V-1, when the number of data points are summed for qualified and 
unqualified data, the total equals the number of data points listed in Table 6-13. The same 
correlation method (DTN MO0004QGFMPICK.000 [DIRS 152554]) used to assign dry bulk 
density values to rock layer types (i.e., welded, calico) in Table 6-13 is used to classify dry bulk 
density values for Table V-1. The Microsoft program Excel was used to calculate statistical 
values such as the mean, standard deviation, and variance for each rock layer. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 V-4 October 2004 
It should be noted that the two dry bulk density values for GFM unit Trammd came solely from 
unqualified DTN GS930408312132.007 [DIRS 129625] because no corroborating data from 
other data sources could be identified for this GFM unit. 
Data Generated by the Evaluation 
Table V-2 was generated by using Equation 7-1 and Equation 7-2, and data from Table V-1. All 
values listed in column t are less than 1.96; therefore, DTN GS930408312132.007 
[DIRS 129625] and DTN GS920408312314.011 [DIRS 129660] are qualified based on the 
evaluation criteria. 
Table V-2. Comparison of Means for Qualified and Unqualified Data 
Qualified Data Unqualified Data 
Layer Type N1  1 s1 S1 N2  2 s2 S2 . scombined t 
Welded 1314 2.19 0.177 232.898 9 2.11 0.093 0.840 1321 6.408 0.04 
Vitric 116 2.31 0.087 10.149 2 2.22 0.134 0.269 116 0.943 0.15 
Non-welded 588 1.46 0.338 198.724 6 1.40 0.250 1.499 592 8.168 0.02 
Calico 608 1.68 0.157 95.284 3 1.48 0.225 0.675 609 3.861 0.09 
Prow Pass 
nonwelded 
504 1.79 0.118 59.267 4 1.71 0.020 0.080 506 2.635 0.06 
Prow Pass 
welded 
81 2.07 0.139 11.259 N/A N/A N/A N/A N/A N/A N/A 
Bullfrog 
nonwelded 
61 1.89 0.162 9.897 7 1.79 0.197 1.381 66 1.230 0.21 
Bullfrog 
welded 
87 2.27 0.130 11.347 6 2.04 0.085 0.507 91 1.191 0.46 
Tram Tuff 
nonwelded 
26 1.67 0.130 3.385 11 1.99 0.121 1.330 35 0.615 -1.45 
Tram Tuff 
welded a 
81 2.07 0.139 11.259 2 2.15 0.078 0.156 81 1.251 -0.08 
a The Prow Pass welded layer is selected as a surrogate for the Tram Tuff welded layer because no 
qualified data are available. The same layer substitution was done for matrix porosity in Section 6.5 and 
is reasonable because of the proximity of layers. 
N/A = Not available. 
Because no Prow Pass welded data were acquired from test wells USW H-1 and J-13, no 
statistics are shown in Table V-2 for unqualified data pertaining to the Prow pass welded layer. 
Because there are no dry bulk density data for the welded Tram Tuff layer, the results for the 
Prow Pass welded layer are used for Trammd, because of the proximity of the layers and the 
similarity between the rock types of the two layers.) 
Only standard spreadsheet functions were used in the generation of data contained in Table V-1; 
such software usage is exempt from software qualification per Section 2.1.6 of LP-SI.11Q-BSC, 
Software Management. 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 V-5 October 2004 
Evaluation Results 
Based upon the comparisons made above, and based upon the experience of the data 
qualification team, the data from DTN GS920408312314.011 ([DIRS 129660], SEP table 
S97135_002) and from DTN GS930408312132.007 ([DIRS 129625], SEP table S97276_001) 
are qualified for use in this report. 
Rationale for Abandoning Any Qualification Methods, if Appropriate 
No qualification methods were abandoned. 
Limits or Caveats To Be Considered by Potential Users of the Data 
No limits or caveats have been identified which would apply to the use of these data within this 
report. 
Identification of Any Supporting Information Used in the Qualification Effort 
No supporting information, other than data and reports previously mentioned in the report, were 
used in the qualification effort. 
Data Qualification Plan 
The data in this appendix are qualified in accordance with the Data Qualification Plan, 
Qualification of Unqualified Dry Bulk Density Data Contained in DTNs GS920408312314.011, 
SEP Table S97135_002 and DTN GS930408312132.007, SEP Table S97276_001 for Use in 
MDL-NBS-GS-000006 Rev 01 (BSC 2004 [DIRS 171956]). 

Thermal Conductivity of Non-Repository Lithostratigraphic Layers 
MDL-NBS-GS-000006 REV 01 V-6 October 2004 
INTENTIONALLY LEFT BLANK