(text) NOTICE OF OPEN CHANGE DOCUMENTS - THIS DOCUMENT IS IMPACTED BY THE LISTED CHANGE DOCUMENT AND CANNOT BE USED WITHOUT IT.
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1) ACN-001, DATED 08/01/2005 

DISCLAIMER 

This report was prepared as an account of work sponsored by an agency of the United States Government. Neither 
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subcontractors or their employees, makes any warranty, express or implied, or assumes any legal liability or 
responsibility for the accuracy, completeness, or any third partys use or the results of such use of any information, 
apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. 
Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, 
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expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. 

MDL-NBS-HS-000001 REV 04 February 2005 


QA: QA 


Drift-Scale THC Seepage Model 
MDL-NBS-HS-000001 REV 04 
February 2005 


MDL-NBS-HS-000001 REV 04 February 2005 


MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

REV 01 ICN 02 
Removed incorrect reference DTN: MO0008THRMODYN.000 [DIRS 153742], inserted 
correct reference DTN: MO0009THRMODYN.001 [DIRS 152576] (this impacted sections 4, 
8.3 and attachments V and VI). 
Made editorial correction in section 5.A.7. 
Added assumption 20 to section 5.A, to identify DTN: LA0008SC12213N.001 [DIRS 153386] 
as data that augments DTN: MO0009THRMODYN.001 [DIRS 152576]. 
Revised three assumptions to indicate no further confirmation is required as the assumptions 
were adequately justified (C-1, C-4, and C-6). Revision of assumptions resulted in the removal 
of TBVs 5028, 5029, and 5030 in the Document Input Reference System (DIRS). 
Updated section 8.3 to remove URNs where appropriate. 
Changes to the data status made in DIRS. 
The following sections were revised in REV 01 ICN 02: 
Section 1 (p. 23), 2 (p. 27), 3 (p. 30), 4 (pp. 33, 37-38, 42), 5 (pp. 50, 53, 55), 6 (p. 107), 7 (p. 
225), 8 (pp. 228-229, 235-240), Att V (p. V-3), and VI (p. VI-3). 
REV 02 Entire model documentation was revised. Side bars are not used because the changes were too 
extensive to use Step 5.9d)1) per AP-SIII.10Q/REV.1/ICN 2. 
REV 03 
Entire model documentation was revised. Side bars are not used because the changes were too 
extensive to use Step 5.8f)1), AP-SIII.10Q/REV 02/ICN 5. All Revision 01 THC Seepage 
Model simulations (Sections 6.5, 6.6, 6.7 of REV 02) and Revision 01 DST THC model 
simulations (in Section 7.1 of REV 02) and associated inputs that are not used by the current 
revision were removed. In Section 4.1, superseded or historical inputs to the current model 
were justified for intended use. Section 5 was expanded to include more assumptions. Several 
subsections of Section 6 were removed, and a new section, documenting a sensitivity analysis 
relating to host rock thermal properties has been added. Section 7.1 was rewritten to more 
explicitly address procedural requirements. Sections 7.2 and 7.3 were reduced to short 
descriptions. The errata associated with the previous revision were fixed. Regulatory 
Integration Team review items were addressed through more thorough descriptions of the 
process model, justification of assumptions, evaluation of the model validation, and discussion 
of propagation of model uncertainty to downstream models. The report also addresses 
Condition Reports CR79, CR168, CR821, CR938, CR1805, CR1821, CR2049, CR2050, and 
CR2104. 
REV 04 
Revisions to the validation section (Section 7) of the document, to address CR99 and CR4888. 
Specifically, changes were made to Sections 1.1, 1.3, 4.2, 7.1.7, 7.1.7.2, and 7.1.11.3. Side 
bars are not used because the changes were too extensive to use Step 5.7.2c)1) per 
LP-SIII.10Q-BSC REV. 0/ICN 0. 

MDL-NBS-HS-000001 REV 04 iv February 2005 


Drift-Scale THC Seepage Model 

CONTENTS 

Page 

ACRONYMS AND ABBREVIATIONS.................................................................................... xix 


1. PURPOSE.............................................................................................................................1-1 


1.1 BACKGROUND .......................................................................................................... 1-1 


1.2 OVERVIEW OF MODELS.......................................................................................... 1-2 


1.3 MODEL LIMITATIONS.............................................................................................. 1-3 


2. QUALITY ASSURANCE.....................................................................................................2-1 


3. USE OF SOFTWARE ........................................................................................................... 3-1 


3.1 QUALIFIED SOFTWARE........................................................................................... 3-1 


3.2 EXEMPT SOFTWARE................................................................................................3-1 


4. INPUTS................................................................................................................................. 4-1 


4.1 DIRECT INPUT ........................................................................................................... 4-1 


4.1.1 Hydrologic and Thermal Properties.................................................................. 4-1 


4.1.1.1 Fracture Tortuosity.............................................................................4-3 


4.1.1.2 Mean Infiltration Rates......................................................................4-3 


4.1.1.3 Thermal Properties............................................................................. 4-5 


4.1.1.4 Effective Thermal Conductivities for In-Drift Open Spaces ............. 4-5 


4.1.2 Mineralogical Data............................................................................................ 4-6 


4.1.3 Kinetic Data ...................................................................................................... 4-6 


4.1.4 Thermodynamic Data........................................................................................ 4-8 


4.1.5 Water and Gas Chemistry ............................................................................... 4-10 


4.1.6 Tptpll THC Model Grid..................................................................................4-12 


4.1.7 Design Information ......................................................................................... 4-14 


4.2 CRITERIA .................................................................................................................. 4-20 


4.3 CODES, STANDARDS, AND REGULATIONS...................................................... 4-26 


5. ASSUMPTIONS.................................................................................................................... 5-1 


6. MODEL DISCUSSION......................................................................................................... 6-1


6.1 RELEVANT FEATURES, EVENTS, AND PROCESSES.........................................6-3 


6.2 CONCEPTUAL MODEL.............................................................................................6-5 


6.2.1 Conceptualization of Coupled THC Processes.................................................6-5 


6.2.1.1 TH Processes...................................................................................... 6-6 


6.2.1.2 THC Processes...................................................................................6-7 


6.2.1.3 Effects of Infiltration and Climate Changes on THC Processes......6-10 

6.2.1.4 Hydrologic Property Changes in Fractures and Matrix ................... 6-10 


6.2.1.5 Dual-Permeability Model for THC Processes .................................6-10 


6.2.2 Conceptualization of the Geochemical System .............................................. 6-11 


6.2.2.1 Initial Pore-Water and Pore-Gas Chemistry....................................6-11 


6.2.2.2 Geochemical Systems ...................................................................... 6-18 


MDL-NBS-HS-000001 REV 04 v February 2005 


Drift-Scale THC Seepage Model 

CONTENTS (Continued) 

Page 

6.2.3 Conceptualization of the Model Domain........................................................6-19 


6.3 ALTERNATIVE CONCEPTUAL MODELS............................................................6-20 


6.4 MATHEMATICAL MODEL.....................................................................................6-22 


6.4.1 General Numerical Model for Coupled THC Processes................................. 6-23 


6.4.2 Kinetic Rate Laws........................................................................................... 6-25 


6.4.3 Fracture and Matrix Mineral Reactive Surface Areas .................................... 6-27 


6.4.3.1 Fracture Mineral Reactive Surface Areas........................................6-27 


6.4.3.2 Matrix Mineral Reactive Surface Areas ..........................................6-29 


6.4.4 Effects of Mineral Precipitation/Dissolution on Hydrologic Properties......... 6-29 


6.4.4.1 Porosity Changes .............................................................................6-29 


6.4.4.2 Fracture Permeability Changes........................................................6-29 


6.4.4.3 Matrix Permeability Changes .......................................................... 6-31 


6.4.4.4 Effects of Permeability and Porosity Changes on Capillary 
Pressures ..........................................................................................6-31 

6.4.5 Mineral Precipitation in Dry Grid Blocks....................................................... 6-31 


6.4.6 Principal Model Approximations and Approaches......................................... 6-32 


6.4.7 Summary of Hydrologic and Thermal Properties...........................................6-36 


6.4.8 Thermodynamic Data Sensitivity ................................................................... 6-37 


6.5 THC SEEPAGE MODEL...........................................................................................6-39 


6.5.1 Numerical Mesh (Tptpll) ................................................................................ 6-40 


6.5.2 Boundary Conditions ...................................................................................... 6-44 


6.5.3 Input Data and Modeling Procedure...............................................................6-45 


6.5.4 Model Runs.....................................................................................................6-46 


6.5.5 Simulation Results (THC Seepage Model; Tptpll Unit)................................. 6-47 


6.5.5.1 TH Results (No Chemical Reactions)..............................................6-48 


6.5.5.2 Water Chemistry Trends..................................................................6-55 


6.5.5.2.1 Drift Wall Results ....................................................... 6-55 


6.5.5.2.2 High-Liquid Saturation Zone above Drift Crown.......6-70 


6.5.5.3 Mineral Alteration and Porosity/Permeability Changes (Tptpll)..... 6-93 

6.5.5.4 Simulations of Ambient Conditions (Thermodynamic Data 
Sensitivity) .....................................................................................6-103 

6.5.5.5 Sensitivity to Revised Matrix Porosity and Thermal Values.........6-107 


6.6 MODEL UNCERTAINTY.......................................................................................6-123 


6.6.1 Potential Sources of Uncertainty .................................................................. 6-123 


6.6.2 Evaluation of Model Result Uncertainty ...................................................... 6-129 


7. VALIDATION...................................................................................................................... 7-1 


7.1 THE DRIFT SCALE TEST THC SUBMODEL..........................................................7-4 


7.1.1 Modeling Approach .......................................................................................... 7-5 


7.1.2 Drift Scale Test Two-Dimensional Numerical Grid.........................................7-5 


7.1.3 Heater Power..................................................................................................... 7-6 


7.1.4 Hydrologic and Geochemical Input Data ....................................................... 7-10 


7.1.5 Initial and Boundary Conditions: Hydrologic and Thermal .......................... 7-10 


7.1.6 Initial and Boundary Conditions: Geochemical............................................. 7-11 


MDL-NBS-HS-000001 REV 04 vi February 2005 


Drift-Scale THC Seepage Model 

CONTENTS (Continued) 

Page 

7.1.7 Model Validation Methods, Criteria, and Limitations.................................... 7-11 


7.1.7.1 Validation Method 1Corroboration with Experimental Data ...... 7-11 

7.1.7.2 Publication in a Refereed Technical Journal ...................................7-14 


7.1.8 THC Simulations ............................................................................................ 7-15 


7.1.9 Simulation Results: Thermal and Hydrologic Evolution............................... 7-16 


7.1.10 Gas-Phase CO2 Evolution: Measured Compositions and Simulation 
Results............................................................................................................. 7-20 

7.1.10.1 Gas Sampling and CO2 Measurements............................................7-20 


7.1.10.2 Modeled Spatial Distribution of CO2...............................................7-21 


7.1.10.3 Modeled and Measured CO2 Concentrations over Time ................. 7-23 


7.1.11 Aqueous Species Evolution ............................................................................ 7-25 


7.1.11.1 Chemistry of Waters Sampled During the Drift Scale Test.............7-25 


7.1.11.2 Evolution in the pH of Waters from the DST..................................7-34 


7.1.11.3 Evolution of Anion and Cation Concentrations...............................7-38 


7.1.12 Mineralogical Changes ................................................................................... 7-50 


7.1.13 Porosity and Permeability Changes ................................................................ 7-57 


7.1.14 Isotopic Compositions of Gases and Water: Model Corroboration Using 
14C in CO2 ....................................................................................................... 7-59 

7.1.15 Summary of Model-Data Comparisons Using the Drift Scale Test ............... 7-62 


7.2 SIMULATION OF THE PLUG-FLOW REACTOR EXPERIMENT....................... 7-63 


7.3 SIMULATION OF THE FRACTURE SEALING EXPERIMENT ..........................7-64 


7.4 VALIDATION SUMMARY......................................................................................7-65 


8. CONCLUSIONS.................................................................................................................... 8-1 


8.1 MODELED COUPLED PROCESSES AND UNCERTAINTY .................................8-1 


8.2 THC SEEPAGE MODEL RESULTS ..........................................................................8-3 


8.3 DST THC SUBMODEL RESULTS (VALIDATION)................................................8-6 


8.4 UNCERTAINTIES AND RESTRICTIONS FOR DOWNSTREAM USE.................8-7 


8.5 DATA TRACKING NUMBERS FOR DATA GENERATED IN THIS REPORT....8-7 

9. INPUTS AND REFERENCES..............................................................................................9-1 


9.1 DOCUMENTS CITED.................................................................................................9-1 


9.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES.......................... 9-13 


9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER ..............................9-13 


9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER ..............................9-18 


9.5 SOFTWARE CODES.................................................................................................9-18 


APPENDIX A: MINERAL INITIAL VOLUME FRACTIONS ............................................. A-1 


APPENDIX B: MINERAL REACTIVE SURFACE AREAS .................................................B-1 


APPENDIX C: THERMODYNAMIC DATABASE ...............................................................C-1 


APPENDIX D: WASTE PACKAGE AVERAGE HEAT TRANSFER.................................. D-1 


MDL-NBS-HS-000001 REV 04 vii February 2005 


Drift-Scale THC Seepage Model 

CONTENTS (Continued) 

Page 

APPENDIX E: EFFECTIVE THERMAL CONDUCTIVITY FOR IN-DRIFT OPEN 
SPACES...........................................................................................................E-1 
APPENDIX F: PARAMETERS FOR FRACTURE PERMEABILITY MODIFICATION....F-1 
APPENDIX G: LIST OF MODEL INPUT AND OUTPUT FILES........................................ G-1 
APPENDIX H: QUALIFICATION OF MINERAL DISSOLUTION/PRECIPITATION 
KINETICS DATA FOR USE IN THC COUPLED PROCESS 
MODELING ................................................................................................... H-1 
APPENDIX I: QUALIFICATION OF IN-DRIFT CONFIGURATION, DIMENSIONS, 
AND COMPONENT PROPERTIES ...............................................................I-1 

MDL-NBS-HS-000001 REV 04 viii February 2005 


Drift-Scale THC Seepage Model 

FIGURES 


Page 

4.1-1. Sketch Showing Modeled In-Drift Dimensions.......................................................... 4-19 
6.2-1. Schematic Diagram of THC Processes around a Heated Drift.....................................6-7 
6.2-2. Schematic Diagram of Fracture-Matrix Interface Showing the Relation Between 

TH Processes and Geochemical Processes ................................................................... 6-8 
6.2-3. Conceptual Model (Schematic) for ReactionTransport Processes in 

Dual-Permeability Media............................................................................................ 6-11 
6.2-4. Piper Plot of Water Compositions (meq/L) from Repository Units ........................... 6-16 
6.5-1. THC Model Mesh with Hydrogeologic Units Shown in the Vicinity of the Drift: 

Topopah Spring Tuff Middle Nonlithophysal (tsw34triangles), Lower 

Lithophysal (tsw35dots), and Lower Nonlithophysal (tsw36diamonds) 

Units........................................................................................................................... 6-41 
6.5-2. Discretization of the Repository Drift in the THC Model .......................................... 6-43 
6.5-3. TH Simulation (Tptpll): Time Profiles of Modeled Temperatures in Fractures 

(Similar in Matrix) at Three Drift-Wall Locations and in the Waste Package ........... 6-49 
6.5-4. TH Simulation (Tptpll): Time Profiles of Modeled Temperatures in Fractures at 

Three Drift-Wall Locations......................................................................................... 6-50 
6.5-5. TH Simulation (Tptpll): Contour Plot of Modeled Temperatures (C) and 

Liquid Saturations in the Matrix and Fractures at 600 Years (Near the Time of 

Maximum Dryout in Fractures) .................................................................................. 6-51 
6.5-6. TH Simulation (Tptpll): Time Profiles of Modeled Liquid Saturations in 

Fractures at Three Drift-Wall Locations..................................................................... 6-52 
6.5-7. TH Simulation (Tptpll): Time Profiles of Modeled Liquid Saturations in Matrix 

at Three Drift-Wall Locations..................................................................................... 6-53 
6.5-8. TH Simulation (Tptpll): Time Profiles of Modeled Air Mass Fractions in the 

Gas Phase in Fractures at Three Drift-Wall Locations ............................................... 6-54 
6.5-9. TH Simulation (Tptpll): Time Profiles of Modeled Water Flux at the Drift 

Crown.......................................................................................................................... 6-55 
6.5-10. THC Seepage Model (Tptpll): Time Profiles of Modeled Temperatures at Three 

Drift-Wall Locations with and without Water-Vapor-Pressure Lowering (eos4 

and eos3, Respectively) .............................................................................................. 6-59 
6.5-11. THC Seepage Model (Tptpll): Time Profiles of Modeled CO2 Concentrations in 

the Gas Phase in Fractures at Three Drift-Wall Locations under Heating (Heat) 

and Non-Heating (Ambient) Conditions, Including (eos4) and Excluding (eos3) 

Water-Vapor-Pressure Lowering................................................................................6-60 
6.5-12. THC Seepage Model (Tptpll): Time Profiles of the Modeled pH of Fracture 

Water at Three Drift-Wall Locations under Heating (Heat) and Non-Heating 

(Ambient) Conditions, Including (eos4) and Excluding (eos3) Water-Vapor-

Pressure Lowering ...................................................................................................... 6-61 
6.5-13. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Carbonate Concentrations (as HCO3) in Fracture Water at Three Drift-Wall 

Locations, under Heating (Heat) and Non-Heating (Ambient) Conditions, 

Including (eos4) and Excluding (eos3) Water-Vapor-Pressure Lowering ................. 6-62 


MDL-NBS-HS-000001 REV 04 ix February 2005 


Drift-Scale THC Seepage Model 

FIGURES (Continued) 

Page 

6.5-14. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 
Calcium Concentrations in Fracture Water at Three Drift-Wall Locations, under 
Heating (Heat) and Non-Heating (Ambient) Conditions, Including (eos4) and 
Excluding (eos3) Water-Vapor-Pressure Lowering.................................................... 6-63 

6.5-15. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 
Sodium Concentrations in Fracture Water at Three Drift-Wall Locations, under 
Heating (Heat) and Non-Heating (Ambient) Conditions, Including (eos4) and 
Excluding (eos3) Water-Vapor-Pressure Lowering.................................................... 6-64 

6.5-16. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Silica 
Concentrations in Fracture Water at Three Drift-Wall Locations, under Heating 
(Heat) and Non-Heating (Ambient) Conditions, Including (eos4) and Excluding 
(eos3) Water-Vapor-Pressure Lowering.....................................................................6-65 

6.5-17. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 
Chloride Concentrations in Fracture Water at Three Drift-Wall Locations, under 
Heating (Heat) and Non-Heating (Ambient) Conditions, Including (eos4) and 
Excluding (eos3) Water-Vapor-Pressure Lowering.................................................... 6-66 

6.5-18. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Fluoride 
Concentrations in Fracture Water at Three Drift-Wall Locations, under Heating 
(Heat) and Non-Heating (Ambient) Conditions, Including (eos4) and Excluding 
(eos3) Water-Vapor-Pressure Lowering.....................................................................6-67 

6.5-19. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Nitrate 
Concentrations in Fracture Water at Three Drift-Wall Locations, under Heating 
(Heat) and Non-Heating (Ambient) Conditions, Including (eos4) and Excluding 
(eos3) Water-Vapor-Pressure Lowering.....................................................................6-68 

6.5-20. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Nitrate to 
Chloride Ratio at Three Drift-Wall Locations, under Heating (Heat) and 
Non-Heating (Ambient) Conditions, Including (eos4) and Excluding (eos3) 
Water-Vapor-Pressure Lowering................................................................................6-69 

6.5-21. THC Seepage Model (Tptpll): Location of Model Grid Blocks for Data Shown 
on Figures 6.5-22 through 6.5-37, for Each Time When Model Output Is 
Produced ..................................................................................................................... 6-76 

6.5-22. THC Seepage Model (Tptpll): Time Profiles of Modeled Temperatures in 
Fracture Water in Areas of Highest Liquid Saturation above the Drift Crown..........6-77 
6.5-23. THC Seepage Model (Tptpll): Time Profiles of Modeled Liquid Saturations in 
Fracture Water in Areas of Highest Liquid Saturation above the Drift Crown..........6-78 

6.5-24. THC Seepage Model (Tptpll): Time Profiles of Modeled CO2 Gas 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above 
the Drift Crown...........................................................................................................6-79 

6.5-25. THC Seepage Model (Tptpll): Time Profiles of Modeled pH in Fracture Water 
in Areas of Highest Liquid Saturation above the Drift Crown ................................... 6-80 

6.5-26. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 
Carbonate Concentrations (as HCO3) in Fracture Water in Areas of Highest 
Liquid Saturation above the Drift Crown ................................................................... 6-81 

MDL-NBS-HS-000001 REV 04 x February 2005 


Drift-Scale THC Seepage Model 

FIGURES (Continued) 

Page 

6.5-27. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Chloride Concentrations in Fracture Water in Areas of Highest Liquid 

Saturation above the Drift Crown...............................................................................6-82 
6.5-28. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Nitrate 

Concentrations in Fracture Water in Areas of Highest Liquid Saturation above 

the Drift Crown...........................................................................................................6-83 
6.5-29. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Calcium Concentrations in Fracture Water in Areas of Highest Liquid 

Saturation above the Drift Crown...............................................................................6-84 
6.5-30. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Calcium to Chloride Ratios in Fracture Water in Areas of Highest Liquid 

Saturation above the Drift Crown...............................................................................6-85 
6.5-31. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Sodium Concentrations in Fracture Water in Areas of Highest Liquid Saturation 

above the Drift Crown ................................................................................................ 6-86 
6.5-32. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Sodium to Chloride Ratios in Fracture Water in Areas of Highest Liquid 

Saturation above the Drift Crown...............................................................................6-87 
6.5-33. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Calcium to Carbonate Ratios in Fracture Water in Areas of Highest Liquid 

Saturation above the Drift Crown...............................................................................6-88 
6.5-34. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Nitrate 

to Chloride Ratios in Fracture Water in Areas of Highest Liquid Saturation 

above the Drift Crown ................................................................................................ 6-89 
6.5-35. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Magnesium Concentrations in Fracture Water in Areas of Highest Liquid 

Saturation above the Drift Crown...............................................................................6-90 
6.5-36. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Silica 

Concentrations in Fracture Water in Areas of Highest Liquid Saturation above 

the Drift Crown...........................................................................................................6-91 
6.5-37. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous 

Fluoride Concentrations in Fracture Water in Areas of Highest Liquid 

Saturation above the Drift Crown...............................................................................6-92 
6.5-38. TH Simulation (Tptpll): Contour Plot of Modeled Liquid Saturation and 

Temperature Contours (C) in Fractures at 2,400 Years (No Chemical 

Reactions) ................................................................................................................... 6-95 
6.5-39. THC Simulation (Tptpll  Water W0): Contour Plot of Modeled (a) Liquid 

Saturation and Temperature Contours (C) and (b) Permeability Change in 

Fractures at 2,400 Years ............................................................................................. 6-96 
6.5-40. THC Simulation (Tptpll  Water W5): Contour Plot of Modeled (a) Liquid 

Saturation and Temperature Contours (C) and (b) Permeability Change in 

Fractures at 2,400 Years ............................................................................................. 6-97 
6.5-41. TH Simulations and THC Seepage Model (Tptpll): Comparison of Modeled 

Liquid Flux at the Drift Crown in Fractures at 2,400 Years.......................................6-98 


MDL-NBS-HS-000001 REV 04 xi February 2005 


Drift-Scale THC Seepage Model 

FIGURES (Continued) 

Page 

6.5-42. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral 
Abundances above the Drift Crown............................................................................ 6-99 
6.5-43. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral 
Abundances above the Drift Crown.......................................................................... 6-100 
6.5-44. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral 
Abundances above the Drift Crown.......................................................................... 6-101 
6.5-45. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral 
Abundances above the Drift Crown.......................................................................... 6-102 

6.5-46. Predicted Water Compositions without Thermal Loading (in the Tptpll 
Lithostratigraphic Unit at the Repository Location) Using the Thermodynamic 
Data Adopted for this Study (Data Set 1  Appendix C).......................................... 6-104 

6.5-47. Predicted Water Compositions without Thermal Loading (in the Tptpll 
Lithostratigraphic Unit at the Repository Location) Using Thermodynamic Data 
from Data Set 2 (Section 6.4.8) ................................................................................ 6-105 

6.5-48. Predicted Water Compositions without Thermal Loading (in the Tptpll 
Lithostratigraphic Unit at the Repository Location) Using Thermodynamic Data 
from Data Set 3 (Section 6.4.8) ................................................................................ 6-106 

6.5-49. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled 
Temperatures in Fractures at Three Drift-Wall Locations........................................ 6-110 
6.5-50. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled 
Liquid Saturations in Fractures at Three Drift-Wall Locations................................6-111 
6.5-51. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled 
Liquid Saturations in Matrix at Three Drift-Wall Locations....................................6-112 
6.5-52. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled Air 
Mass Fractions in the Gas Phase in Fractures at Three Drift-Wall Locations.......... 6-113 
6.5-53. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled 
Downward Water Flux at the Drift Crown ............................................................... 6-114 

6.5-54. THC Simulations (Revised vs. Original Properties): Location of Model Grid 
Blocks for Data Shown on Figures A-7 through A-22, for Each Time When 
Model Output Is Produced........................................................................................6-114 

6.5-55. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 
Temperatures in Fractures in Areas of Highest Liquid Saturation above the Drift 
Crown........................................................................................................................ 6-115 

6.5-56. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 
Liquid Saturations in Fractures in Areas of Highest Liquid Saturation above the 
Drift Crown...............................................................................................................6-115 

6.5-57. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 
CO2 Gas Concentrations in Fractures in Areas of Highest Liquid Saturation 
above the Drift Crown .............................................................................................. 6-116 

6.5-58. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 
pH in Fracture Water in Areas of Highest Liquid Saturation above the Drift 
Crown........................................................................................................................ 6-116 

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Drift-Scale THC Seepage Model 

FIGURES (Continued) 

Page 

6.5-59. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Carbonate Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-117 
6.5-60. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Chloride Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-117 
6.5-61. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Nitrate Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-118 
6.5-62. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Sulfate Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-118 
6.5-63. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Fluoride Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-119 
6.5-64. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Calcium Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-119 
6.5-65. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Calcium to Carbonate Concentration Ratios in Fracture Water in 

Areas of Highest Liquid Saturation above the Drift Crown ..................................... 6-120 
6.5-66. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Magnesium Concentrations in Fracture Water in Areas of 

Highest Liquid Saturation above the Drift Crown....................................................6-120 
6.5-67. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Sodium Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-121 
6.5-68. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Sodium to Chloride Concentration Ratios in Fracture Water, in 

Areas of Highest Liquid Saturation above the Drift Crown ..................................... 6-121 
6.5-69. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Potassium Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-122 
6.5-70. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 

Total Aqueous Silica Concentrations in Fracture Water in Areas of Highest 

Liquid Saturation above the Drift Crown ................................................................. 6-122 
7.1-1. Three-Dimensional Schematic Diagram of the DST Showing Perspective View 

of Numerical Mesh for DST THC Submodel Simulations...........................................7-7 
7.1-2. Numerical Mesh for DST THC Submodel Simulations ............................................... 7-7 
7.1-3. Enlarged View of the Numerical Grid Showing the Locations of Grid Blocks 

Representing the Heated Drift, Wing Heaters, and Concrete Invert............................. 7-8 
7.1-4. Locations of Hydrology Boreholes, Sampling Intervals (Numbered) and 

Temperature Sensors................................................................................................... 7-13 


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Drift-Scale THC Seepage Model 

FIGURES (Continued) 

Page 

7.1-5. Drift Center and Drift Crown Modeled Temperatures over the First Six Years of 

the DST ....................................................................................................................... 7-18 
7.1-6. Comparison of Modeled and Measured Temperatures over Time for the Sensor 

Located at Hydrology Borehole Packer 60-4.............................................................. 7-18 
7.1-7. Liquid Saturation (Colors) and Temperature (Contour Lines) in the DST (Base 

Case) at One Year (Matrix  a, Fracture  b) and at Four Years (Matrix  c, 

Fracture  d)................................................................................................................7-19 
7.1-8. Measured Concentrations of CO2 (log vol. fraction) in Gas Phase around the 

DST at 1 Year and at 15 Months ................................................................................ 7-21 
7.1-9. Modeled Gas Phase CO2 Concentrations (Log ppmv) in Fractures during the 

Heating Phase of the DST at 1, 2, 3, and 4 Years....................................................... 7-22 
7.1-10. Modeled Gas Phase CO2 Concentrations (Log ppmv) in Fractures during the 

Cooling Phase of the DST at 5, 6, 7, and 8 Years....................................................... 7-23 
7.1-11. Close-Up of DST Grid, Showing Nodes Used to Extract Model Data for 

Comparison to Concentrations Measured in Gas Samples.........................................7-24 
7.1-12. Comparison of Modeled CO2 Concentrations in Fractures to Measured 

(Corrected) Concentrations in Boreholes: (a) Borehole Interval 74-3 (Average 

of Bounding Grid Blocks); (b) Borehole Interval 75-3; (c) Borehole Interval 

76-3 ............................................................................................................................. 7-26 
7.1-13. Comparison of Measured and Corrected Concentrations for Borehole Interval 

75-3 and the Model Simulation Results...................................................................... 7-27 
7.1-14 Zones Where Water Was Collected from Hydrology Boreholes Superimposed 

(Thick Shading in Blue) on the Model Grid ............................................................... 7-33 
7.1-15. Modeled Distribution of pH in Fractures at Various Times When Water Was 

Sampled from Hydrology Borehole Intervals: (a) 6 Months, (b) 11 Months, and 

(c) 14 Months..............................................................................................................7-36 
7.1-16. Comparison of Measured pH in Water Samples Collected from Borehole 
Intervals (a) 60-3, (b) 59-2, and (c) 76-3 to the Modeled Fracture Water pH at 
Representative Model Grid Blocks.............................................................................7-37 
7.1-17. Modeled Distribution of Cl in Fractures and Matrix at One and Four Years 
during the Heating Phase of the DST: (a) Fracture1 Year, (b) Matrix1 
Year, (c) Fracture4 Years, and (d) Matrix4 Years.............................................7-39 
7.1-18. Cl Concentrations (mg/L) in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water Cl ......... 7-40 
7.1-19. SO42 Concentrations (mg/L) in Water Samples Collected from Borehole 
Intervals (a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture 
Water SO42................................................................................................................. 7-41 
7.1-20. Na+ Concentrations (mg/L) in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 the Modeled Na+ Concentrations in Fractures.......... 7-42 
7.1-21. Ca2+ Concentrations (mg/L) in Water Samples Collected from Borehole 
Intervals (a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Ca2+ in 
Fracture Water ............................................................................................................ 7-43 

MDL-NBS-HS-000001 REV 04 xiv February 2005 


Drift-Scale THC Seepage Model 

FIGURES (Continued) 

Page 

7.1-22. SiO2(aq) Concentrations (mg/L) in Water Samples Collected from Borehole 
Intervals (a) 60-3, (b) 59-2, and (c) 76-3 Compared to Modeled Fracture Water 
SiO2(aq) Concentrations ............................................................................................... 7-45 
7.1-23. K+ Concentrations (mg/L) in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 Compared to Modeled Fracture Water K+ 
Concentrations ............................................................................................................ 7-46 
7.1-24. HCO3 Concentrations (mg/L) in Water Samples Collected from Borehole 
Intervals (a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture 
Water HCO3 Concentrations ..................................................................................... 7-47 
7.1-25. Mg2+ Concentrations (mg/L) in Water Samples Collected from Borehole 
Intervals (a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture 
Water Mg2+ Concentrations ........................................................................................ 7-52 
7.1-26. NO3 Concentrations (mg/L) in Water Samples Collected from Borehole 
Intervals (a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture 
Water NO3 Concentrations ........................................................................................ 7-53 
7.1-27. F Concentrations (mg/L) in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water F 
Concentrations ............................................................................................................ 7-54 
7.1-28. Modeled Volume Percent Change in Calcite in Fractures as of November 2000 
(35 Months of Heating)............................................................................................... 7-56 
7.1-29. Modeled Volume Percent Amorphous Silica in Fractures as of November 2000 
(35 Months of Heating)............................................................................................... 7-56 
7.1-30. Modeled Volume Percent Gypsum in Fractures as of November 2000 
(35 Months of Heating)............................................................................................... 7-57 
7.1-31. Change in Fracture Porosity after Four Years of Heating .......................................... 7-58 
7.1-32. Change in Matrix Porosity after Four Years of Heating............................................. 7-59 
7.1-33. Measured Activities of 14C (Expressed as a Fraction of Modern Carbon) in CO2 
from Gas Collected in Several Hydrology Boreholes over Most of the Heating 
Phase of the DST ........................................................................................................ 7-61 
7.1-34. Measured Activities of 14C (Expressed as a Fraction of Modern Carbon) 
Compared to Measured CO2 (Corrected for Water Vapor Removal) from Gas 
Collected in Some Hydrology Boreholes over Most of the Heating Phase of the 
DST............................................................................................................................ 7-62 
8-1. Key Findings of the THC Seepage Model....................................................................8-4 

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MDL-NBS-HS-000001 REV 04 xvi February 2005 


Drift-Scale THC Seepage Model 

TABLES 


Page 

3-1. Qualified Software Used............................................................................................... 3-2 
4.1-1. Sources of Hydrologic and Thermal Properties Used as Direct Input Data for the 

Drift-Scale Coupled-Processes Models That Feed TSPA-LA Activities ..................... 4-2 
4.1-2. Average Infiltration Values (mm/yr) for Different Climate Periods ............................ 4-4 
4.1-3. THC Model Kinetic Data.............................................................................................. 4-7 
4.1-4. Input Pore-Water Compositions ................................................................................. 4-11 
4.1-5. Comparison of Adopted and Revised Values of Elevation and Thickness of 


Stratigraphic Layers for the THC Seepage Model (Tptpll Unit) ................................ 4-13 
4.1-6. Drift and Committed Materials Model Parameters..................................................... 4-16 
4.2-1. Applicable Project Requirements and YMRP Acceptance Criteria ........................... 4-21 
6-1. Summary of the Development of the THC Seepage Model ......................................... 6-1 
6.1-1. Relevant Features, Events, and Processes Included in TSPA-LA................................6-3 
6.1-2. Relevant Features, Events, and Processes Excluded from TSPA-LA .......................... 6-5 
6.2-1. Input Pore-Water Compositions for the THC Seepage Model ................................... 6-14 
6.2-2. Mineral, Aqueous, and Gaseous Species Used in the THC Seepage Model .............. 6-19 
6.4-1. Summary of Hydrologic and Thermal Properties of Repository Units ...................... 6-38 
6.5-1. Vertical Mesh Dimensions and Geologic Contacts in the THC Seepage Model 


(Tptpll Unit)................................................................................................................6-42 
6.5-2. Tptpll THC Seepage Model (Tptpll Unit) Boundary Conditions ............................... 6-44 
6.5-3. THC Seepage Model Infiltration Rates....................................................................... 6-45 
6.5-4. Selected Input Waters (Section 6.2.2.1) for the Tptpll THC Seepage Model 

(Tptpll Unit)................................................................................................................6-45 
6.5-5. THC Seepage Model Runs Using the Mean Infiltration Rock-Property Set for 

All Simulations ........................................................................................................... 6-47 
6.5-6. Tptpll THC Model Sensitivity Runs Using Revised Matrix Properties from 

Table 6.5-7 ................................................................................................................ 6-107 
6.5-7. Summary of Revised and Original Rock Matrix Properties ..................................... 6-108 
6.6-1. Summary of Uncertainties Affecting Chemical Processes in the THC Seepage 

Model ........................................................................................................................ 6-125 
6.6-2. Standard Deviations in Water and Gas Compositions Predicted Using Five 

Different Input Water Compositions (W0, W4, W5, W6, and W7) ......................... 6-130 
7-1. Sources of Data Used for Model Validation or Corroboration..................................... 7-4 
7.1-1. Input DTNs Used for Estimating Times/Dates of Power Reductions and 

Outages for DST THC Submodel Simulations.............................................................7-8 
7.1-2. Step-Wise Averaged Power Data for the DST THC Simulations ................................ 7-9 
7.1-3. Measured Concentrations in Tptpmn Pore Water from Alcove 5 and Chemistry 

of Water Samples from Hydrology Boreholes............................................................ 7-29 
8.5-1. Drift-Scale THC Seepage Model Output DTNs ........................................................... 8-8 


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Drift-Scale THC Seepage Model 

ACRONYMS AND ABBREVIATIONS 

BET Brunauer, Emmet, Teller (static volume method) 

DST Drift Scale Test 
DTN data tracking number 

ECRB Enhanced Characterization of Repository Block 
EOS Equation of State 
ESF Exploratory Studies Facility 

FEP feature, event, or process 

Kthmax maximum thermal conductivity 

LA license application 
LBNL Lawrence Berkeley National Laboratory 

MSTHM multiscale thermohydrologic model 

NBS National Bureau of Standards 
NRC U.S. Nuclear Regulatory Commission 

QA Quality Assurance 

TDMS Technical Data Management System 
TH thermal-hydrologic 
THC thermal-hydrologic-chemical 
TSPA total system performance assessment 
TWP technical work plan 

UZ unsaturated zone 

YMP Yucca Mountain Project 
YMRP Yucca Mountain Review Plan 

Major Hydrogeologic Units 

PTn Paintbrush Tuff nonwelded hydrogeologic unit 

TSw Topopah Spring welded hydrogeologic unit 
TCw Tiva Canyon welded hydrogeologic unit 
Tptpul Topopah Spring Tuff upper lithophysal zone 
Tptpmn Topopah Spring Tuff middle nonlithophysal zone 
Tptpll Topopah Spring Tuff lower lithophysal zone 
Tptpln Topopah Spring Tuff lower nonlithophysal zone 

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Drift-Scale THC Seepage Model 

Geologic and Model Layer Abbreviations 

Stratigraphic Unita Abbreviationa UZ Model Layerb 
GroupFormation 
MemberZoneSubzoneAlluvium and Colluvium Qal, Qc 
Timber Mountain Group Tm 
Rainier Mesa Tuff Tmr 
Paintbrush Group Tp 
Post-tuff unit x bedded tuff Tpbt6 
Tuff unit x Tpki (informal) 
Pre-tuff unit x bedded tuff Tpbt5 
Tiva Canyon Tuff Tpc 
tcw11 
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 
tcw12 
Upper lithophysal zone Tpcpul 
Spherulite-rich subzone Tpcpul1 
Middle nonlithophysal zone Tpcpmn 
Upper subzone Tpcpmn3 
Lithophysal subzone Tpcpmn2 
Lower subzone Tpcpmn1 
Lower lithophysal zone Tpcpll 
Hackly-fractured subzone Tpcpllh 
Lower nonlithophysal zone Tpcpln 

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Drift-Scale THC Seepage Model 

Geologic and Model Layer Abbreviations (Continued) 

Stratigraphic Unita Abbreviationa UZ Model Layerb 
GroupFormation 
MemberZoneSubzone 
Hackly subzone Tpcplnh 
tcw12 (continued) 
Columnar subzone Tpcplnc 
Vitric zone Tpcpv 
tcw13 Densely welded subzone Tpcpv3 
Moderately welded subzone Tpcpv2 
Nonwelded subzone Tpcpv1 ptn21 
Pre-Tiva Canyon bedded tuff Tpbt4 ptn22 
Yucca Mountain Tuff Tpy ptn23 
ptn24 Pre-Yucca Mountain bedded tuff Tpbt3 
Pah Canyon Tuff Tpp ptn 25 
Pre-Pah Canyon bedded tuff Tpbt2 
ptn26Topopah Spring Tuff Tpt 
Crystal-Rich Member Tptr 
Vitric zone Tptrv 
Nonwelded subzone Tptrv3 
Moderately welded subzone Tptrv2 
Densely welded subzone Tptrv1 tsw31 
Nonlithophysal zone Tptrn 
tsw32 Dense subzone Tptrn3 
Vapor-phase corroded subzone Tptrn2 
Crystal transition subzone Tptrn1 
Lithophysal zone Tptrl 
tsw33 
Crystal transition subzone Tptrl1 
Crystal-Poor Member Tptp 
Lithic-rich zone Tptpf or Tptrf 
Upper lithophysal zone Tptpul 
Middle nonlithophysal zone Tptpmn 
tsw34 Nonlithophysal subzone Tptpmn3 
Lithophysal bearing subzone Tptpmn2 
Nonlithophysal subzone Tptpmn1 
Lower lithophysal zone Tptpll tsw35 
Lower nonlithophysal zone Tptpln tsw36, tsw37 

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Drift-Scale THC Seepage Model 

Geologic and Model Layer Abbreviations (Continued) 

Stratigraphic Unita Abbreviationa UZ Model Layerb 
GroupFormation 
MemberZoneSubzoneVitric zone Tptpv 
tsw38 
Densely welded subzone Tptpv3 
Moderately welded subzone Tptpv2 tsw39 
Nonwelded subzone Tptpv1 ch1 
Pre-Topopah Spring bedded tuff Tpbt1 
Calico Hills Formation Ta ch2, ch3, ch4, ch5 
Bedded tuff Tacbt ch6 
Crater Flat Group Tc 
pp4Prow Pass Tuff Tcp 
Prow Pass Tuff upper vitric 
nonwelded zone Tcpuv 
Prow Pass Tuff upper crystalline 
nonwelded zone Tcpuc pp3 
Prow Pass Tuff moderately-densely 
welded zone Tcpmd 
pp2Prow Pass Tuff lower crystalline 
nonwelded zone Tcplc 
Prow Pass Tuff lower vitric 
nonwelded zone Tcplv 
pp1Pre-Prow Pass Tuff bedded tuff Tcpbt 
Bullfrog Tuff Tcb 
Bullfrog Tuff upper vitric nonwelded 
zone Tcbuv 
Bullfrog Tuff upper crystalline 
nonwelded zone Tcbuc 
bf3Bullfrog Tuff welded zone Tcbmd 
Bullfrog Tuff lower crystalline 
nonwelded zone Tcblc 
Bullfrog Tuff lower vitric nonwelded 
zone Tcblv 
bf2Pre-Bullfrog Tuff bedded tuff Tcbbt 
Tram Tuff Tct 
Tram Tuff upper vitric nonwelded 
zone Tctuv 

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Drift-Scale THC Seepage Model 

Geologic and Model Layer Abbreviations (Continued) 

Stratigraphic Unita Abbreviationa UZ Model Layerb 
GroupFormation 
MemberZoneSubzoneTram Tuff upper crystalline 
nonwelded zone Tctuc 
tr3Tram Tuff moderately-densely welded 
zone Tctmd 
Tram Tuff lower crystalline nonwelded 
zone Tctlc 
Tram Tuff lower vitric nonwelded zone Tctlv 
tr2 
Pre-Tram Tuff bedded tuff Tctbt 
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 
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 

Sources: a BSC 2004 [DIRS 170029], Table 6-2 
b BSC 2004 [DIRS 169855], Table 6-5 

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Drift-Scale THC Seepage Model 

CHEMICAL ABBREVIATIONS 
Elements 

Al Aluminum 
Carbon 

Ca Calcium 
Cl Chlorine 
F Fluorine 

Fe Iron 
H Hydrogen 
K Potassium 
Mg Magnesium 
N Nitrogen 

Na Sodium 
O Oxygen 
S Sulfur 

Si Silicon 

Chemical Compounds, Aqueous Species, and Gases 

AlO2 Aluminum primary aqueous species (essentially same as Al(OH)4); here used to 
describe total aqueous aluminum concentrations as AlO2 

CO2 Carbon dioxide gas 

H2O Water 
HCO3 Bicarbonate aqueous species; used here to describe total aqueous carbon 
concentration 
HFeO20 Iron primary aqueous species (essentially same as Fe(OH)30; used here to describe 
total aqueous iron concentrations as HFeO20 

K2SO4 Potassium sulfate (solid; mineral name: arcanite) 

MgSO4 Magnesium sulfate (solid) 

Na2SO4 Sodium sulfate (solid; mineral name: thenardite) 
NaCl Sodium chloride (solid; mineral name: halite) 
NaNO3 Sodium nitrate (solid) 
NO3 Nitrate aqueous species 


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Drift-Scale THC Seepage Model 

CHEMICAL ABBREVIATIONS (Continued) 

O2 Oxygen gas 

PCO2 Carbon dioxide partial pressure (in bars) 
pH Negative logarithm of the hydrogen ion activity 

SiO2 Silica 
SO42 Sulfate aqueous species 

Chemical Units 

meq milliequivalent (mol  103  ionic charge) 
meq/L milliequivalent per liter of solution 
mg/L milligram per liter of solution 
mol moles 
mol/kg moles per kilogram water (molality) 

ppm parts per million 
ppmv parts per million volume 

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1. PURPOSE 
1.1 BACKGROUND 
The purpose of this report (REV04) is to document the thermal-hydrologic-chemical (THC) 
seepage model, which simulates the composition of waters that could potentially seep into 
emplacement drifts, and the composition of the gas phase. The THC seepage model is processed 
and abstracted for use in the total system performance assessment (TSPA) for the license 
application (LA). 

This report has been developed in accordance with Technical Work Plan for: Near-Field 
Environment and Transport: Coupled Processes (Mountain-Scale TH/THC/THM, Drift-Scale 
THC Seepage, and Post-Processing Analysis for THC Seepage) Report Integration (BSC 2005 
[DIRS 172761]). The technical work plan (TWP) describes planning information pertaining to 
the technical scope, content, and management of this report. The plan for validation of the 
models documented in this report is given in Section 2.2.2, Model Validation for the DS THC 
Seepage Model, of the TWP. The TWP (Section 3.2.2) identifies Acceptance Criteria 1 to 4 for 
Quantity and Chemistry of Water Contacting Engineered Barriers and Waste Forms (NRC 2003 
[DIRS 163274]) as being applicable to this report; however, in variance to the TWP, Acceptance 
Criterion 5 has also been determined to be applicable, and is addressed, along with the other 
Acceptance Criteria, in Section 4.2 of this report. Also, three FEPS not listed in the TWP 
(2.2.10.01.0A, 2.2.10.06.0A, and 2.2.11.02.0A) are partially addressed in this report, and have 
been added to the list of excluded FEPS in Table 6.1-2. 

This report has been developed in accordance with LP-SIII.10Q-BSC, Models. 

This report documents the THC seepage model and a derivative used for validation, the Drift 
Scale Test (DST) THC submodel. The THC seepage model is a drift-scale process model for 
predicting the composition of gas and water that could enter waste emplacement drifts and the 
effects of mineral alteration on flow in rocks surrounding drifts. The DST THC submodel uses a 
drift-scale process model relying on the same conceptual model and many of the same input data 
(i.e., physical, hydrologic, thermodynamic, and kinetic) as the THC seepage model. The DST 
THC submodel is the primary means for validating the THC seepage model. The DST THC 
submodel compares predicted water and gas compositions, and mineral alteration patterns, with 
observed data from the DST. These models provide the framework to evaluate THC coupled 
processes at the drift scale, predict flow and transport behavior for specified thermal-loading 
conditions, and predict the evolution of mineral alteration and fluid chemistry around potential 
waste emplacement drifts. The DST THC submodel is used solely for the validation of the THC 
seepage model and is not used for calibration to measured data. 

Data developed with the THC seepage model are analyzed in Post-Processing Analysis for THC 
Seepage (BSC 2004 [DIRS 169858]), for downstream use in modeling the in-drift chemical 
environment in Engineered Barrier System: Physical and Chemical Environment Model (BSC 
2004 [DIRS 169860], Section 4.1), which directly feeds the TSPA-LA. 

The work scope for this report is summarized as follows: further develop the THC seepage 
model; use sensitivity analyses and model-data comparisons to evaluate model, data, and 

MDL-NBS-HS-000001 REV 04 1-1 February 2005 


Drift-Scale THC Seepage Model 

parameter uncertainties; validate the model by comparison of derivative cases with field and 
experimental data; perform simulations to predict the composition of fracture water that could 
potentially seep into repository emplacement drifts; submit modeling results to the Technical 
Data Management System (TDMS) and document the models; and evaluate model uncertainty 
and the propagation of uncertainty to other models. 

This report (REV04) is a minor revision of the previous version, and addresses shortcomings in 
model validation, as described in Condition Report CR99. It differs only slightly from Revision 
03 with respect to technical content. Relative to previous revisions of this model, the simulations 
presented in this document make use of improved treatment of various modeled processes, 
together with updated rock properties and some new kinetic and thermodynamic input data. In 
addition, the uncertainties associated with the THC seepage model are represented using five 
different input water compositions, with consideration of sensitivity studies on the effects of 
variations in key parameters including infiltration rates, CO2 effective diffusivity, and 
vapor-pressure lowering by capillarity. Previous revisions of this model investigated model 
sensitivity to other parameters. Those results are discussed, as applicable, in this document, but 
not presented in detail. Those developmental model simulations are discussed for comparative 
purposes to evaluate model uncertainty and sensitivity to model parameters and are not direct 
inputs to TSPA-LA. 

1.2 OVERVIEW OF MODELS 
The THC seepage model provides an analysis of the effects of THC processes on percolation 
water chemistry and gas-phase composition in the near-field host rock around the emplacement 
drifts. This analysis includes a complete description of the relevant mineralwater interactions in 
the host rock. Sensitivity studies document the effect of varying rock properties, including 
fracture-permeability heterogeneity, reaction rates, repository emplacement-horizon lithology, 
geochemical systems, infiltration rates, and input water compositions. 

The DST THC submodel, constructed for the DST, is used to investigate THC processes during 
the DST and validate the THC modeling approach. The spatial scale and temperatures for the 
DST are similar to those for current designs of the repository. This similarity, combined with the 
extended period of operation (four years of heating, ending in January 2002, and continued 
monitoring during cooling), makes the DST the best available experiment for validating 
drift-scale THC coupled process models (such as the THC seepage model). Measured data from 
the DST are used to evaluate and validate the conceptual and numerical models presented here. 

The following designations are assigned for description of the work presented in this report: 

 THC seepage model: Developed for use by downstream models that feed TSPA (Section 
6.5). In this model, the repository is located in the Tptpll lithostratigraphic unit. Five 
simulations, using five different starting pore waters, provide feeds to downstream 
models. Several sensitivity analyses using the current model are also documented here. 
 DST THC submodel: DST THC submodel simulations developed for the current revision 
of this report (Section 7.1). This model is derived from the THC seepage model, and 
used for validation of the THC seepage model. The DST is located in the middle 
MDL-NBS-HS-000001 REV 04 1-2 February 2005 


Drift-Scale THC Seepage Model 

nonlithophysal unit (Tptpmn) but the results are applicable to all the host rock 
lithostratigraphic units as discussed below. 

Results of earlier developmental (REV01) versions of the THC model are discussed in this report 
as alternative conceptualizations and sensitivity analyses. Previous model revisions provide 
alternative conceptualizations of the THC seepage model and are used to evaluate the effects of 
mineral dissolution and precipitation; the effects of CO2 exsolution and transport in the region 
surrounding emplacement drifts; the potential for forming calcite, silica, or other mineral 
assemblage precipitation caps (low-permeability zones of precipitated minerals above the 
drifts); and the resulting changes to porosity, permeability, and percolation. The effects of 
various model refinements and improvements implemented through successive revisions of this 
report are also documented. These include, for example, the effects of improved treatment of 
porosity-permeability coupling, improved treatment of mineral precipitation at the boiling front, 
and consideration of lowering vapor pressure caused by capillary pressure. 

As discussed later in this report, the THC seepage model is located in the Tptpll 
lithostratigraphic unit, but is run using a range of input water compositions from various host 
rock lithostratigraphic units (including the Tptpmn, Tptpll, and Tptpul units) and representing the 
natural variability in pore water compositions. The range of model results from the use of these 
different water compositions is representative of that associated with other factors such as host 
rock unit, drift location, infiltration rate, and other model conceptualizations discussed in Section 

6.3. Also, the host rock lithostratigraphic units are mineralogically similar (Peterson and Cloke 
2002 [DIRS 162576]). Therefore, it is assumed (Section 5) that the THC model results 
calculated for the Tptpll unit (taking into account the variability introduced by the different input 
water compositions) are applicable to the other repository host rock units. 
1.3 MODEL LIMITATIONS 
The THC seepage model has stated limitations associated with its mathematical formulation, 
certain assumptions (Section 5), and approximations in model development (Section 6.4.6). The 
THC seepage model is designed for simulation of speciation and mineral precipitation for 
evaporatively concentrated waters with ionic strength < 4 molal. At ionic strengths > 4 molal, 
the model uses specific approximations to represent the behavior of soluble salts. While the 
method is consistent with the activity model implemented here and ensures numerical stability, it 
introduces uncertainty with respect to the relative concentrations of soluble species (e.g. NO3 
and Cl) when the salts are first redissolved. However, during this initial rewetting stage, the 
liquid saturation is low and the associated volume of water is small, immobile, and unlikely to 
contribute to seepage. This limitation and others affecting the uncertainty of model results, such 
as the use of average properties to describe thermal, hydrologic, and chemical characteristics of 
the host rock, are discussed in Section 6.6. Another limitation of the THC seepage model is that 
it is computationally intensive (run times up to ten days per simulation case); hence, the number 
of sensitivity analyses is limited. These limitations are addressed by evaluating the model 
sensitivity to key input parameters (Section 6.5), and by comparing model results against data 
from the DST and laboratory experiments (Section 7). Also, the model conceptualization and 
mathematical formulation (Sections 6.2 through 6.4) have been improved, through the successive 
revisions of this report, to achieve reasonably good agreement (generally to within an order of 
magnitude) between calculated and measured data. 

MDL-NBS-HS-000001 REV 04 1-3 February 2005 


Drift-Scale THC Seepage Model 

Although the THC seepage model provides aqueous Fe concentrations as output, these values are 
not used by downstream models. Because of the paucity of measured Fe values in DST waters, 
and the large uncertainty in these values due to the low solubility of Fe3+ (Section 7.1.11.3), Fe 
model predictions are not validated, and are presented in THC seepage model results for 
information only. 

The THC seepage model represents a two-dimensional slice across a repository drift, at a 
representative repository-center location. This approach closely represents conditions 
throughout much of the repository, and gives a representation of THC effects near the repository 
edge, which tends to over-state the aggressiveness of the waters with respect to waste package 
corrosion. Water and gas compositions predicted at the edge of the repository (BSC 2001 
[DIRS 155950], Section 3.3.6) are within the range of compositions simulated in this report. For 
these reasons, results presented here can be used to represent potential effects of THC processes 
on the composition of seepage at all waste package locations (BSC 2004 [DIRS 169858], 
Section 6.3.2). 

MDL-NBS-HS-000001 REV 04 1-4 February 2005 


Drift-Scale THC Seepage Model 

2. QUALITY ASSURANCE 
Development of this report and supporting modeling activities has been determined to be subject 
to the Yucca Mountain Projects quality assurance (QA) program as indicated in Technical Work 
Plan for: Near-Field Environment and Transport: Coupled Processes (Mountain-Scale 
TH/THC/THM, Drift-Scale THC Seepage, and Post-Processing Analysis for THC Seepage) 
Report Integration (BSC 2005 [DIRS 172761]; Work Package ARTM02). Approved QA 
implementing procedures identified in the TWP (BSC 2005 [DIRS 172761], Section 4) have 
been used to conduct and document the activities described in this report. Electronic 
management of information has been evaluated in accordance with AP-SV.1Q, Control of the 
Electronic Management of Information, and controlled under YMP-LBNL-QIP-SV.0, 
Management of YMP-LBNL Electronic Data. 

This report investigates the effect of drift-scale THC processes on the following safety category 
barriers that are important to the demonstration of compliance with the postclosure performance 
objective prescribed in 10 CFR 63.113 [DIRS 156605]: 

 Unsaturated zone above the repository 
 Unsaturated zone below the repository. 
Therefore, the barriers are classified as Safety Category (SC) with regard to importance to waste 
isolation as defined in AP-2.22Q, Classification Analyses and Maintenance of the Q-List. The 
report contributes to the analyses and modeling data used to support performance assessment; the 
conclusions do not directly impact the engineered features important to safety as defined in 
AP-2.22Q. 

MDL-NBS-HS-000001 REV 04 2-1 February 2005 


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INTENTIONALLY LEFT BLANK 


MDL-NBS-HS-000001 REV 04 2-2 February 2005 


Drift-Scale THC Seepage Model 

3. USE OF SOFTWARE 
The following software is used in the preparation of this report: 

3.1 QUALIFIED SOFTWARE 
The qualified software used in this study is listed in Table 3-1. The software has been baselined 
in accordance with LP-SI.11Q-BSC, Software Management, or previous approved procedures, is 
adequate and appropriate for the intended use, is used strictly within the range of validation, and 
has been obtained from the software configuration management department. The software 
performs the functions described in Table 3-1 in the qualified environment described. Input 
limitations are discussed in table column Range of Use. Unless specifically listed in 
Table 3-1, there are no limitations on the software output, provided that the appropriate input 
limitations are observed. 

TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]) is the primary code used for the DST THC 
submodel and THC seepage model. SOLVEQ/CHILLER V1.0 (LBNL 1999 [DIRS 153217]) is 
utilized to prepare water-chemistry data for input to the model simulations, SUPCRT92 V1.0 
(LBNL 1999 [DIRS 153218]) is used to generate thermodynamic data for use by 
SOLVEQ/CHILLER V1.0 (LBNL 1999 [DIRS 153217]) and various TOUGHREACT versions, 
TOUGH2 V1.4 (LBNL 2000 [DIRS 146496]) is used to generate boundary conditions, AMESH 
V1.0 (LBNL 1999 [DIRS 147561]) is used to generate grids for the models. Other routines 
listed in Table 3-1 are used for various data pre- and post-processing tasks. 

This report documents the DST THC submodel and the THC seepage model as described in 
Section 1. The input and output files for the model runs presented in this report are listed in 
Appendix G. 

3.2 EXEMPT SOFTWARE 
The commercial, off-the-shelf software code Microsoft Excel has been used in the preparation of 
this report in an exempt manner to do basic calculations and statistical operations based on the 
internal functions of the code. TOUGHREACT model output is also exported to Excel for 
graphing and data presentation, and the primary output DTNs for this model, 
LB0302DSCPTHCS.002 and LB0307DSTTHCR2.002, contain data summarized in Excel 
spreadsheets. The individual spreadsheets are called out in the DTNs where they are used, and 
are summarized in Appendix G. As discussed in Appendix G, readme.doc files in each DTN 
contain a general description of the spreadsheets contained therein, and worksheets in the Excel 
spreadsheets document in detail the calculations that are performed in each spreadsheet. 

MDL-NBS-HS-000001 REV 04 3-1 February 2005 


Drift-Scale THC Seepage Model 

Table 3-1. Qualified Software Used 

Software Name 
and Version 
Software 
Tracking 
Number Platform OS Range of Use Brief Description 
TOUGHREACT 
V3.0 
[DIRS 161256] 
10396-3.0-00 Alpha 
System 
OSF1 V5.1 Porous and fractured media in a pressure-
temperature-composition (P-T-X) range 
defined by the P-T-X range of the 
thermodynamic database. Ionic strength limit 
of ~4 molal (NaCl-dominant solutions). 
TOUGHREACT V3.0 is used to calculate 
coupled thermal-hydrologic and chemical 
processes for kinetic and/or equilibrium 
mineral-water reactions and equilibrium 
gas-water reactions. 
SOLVEQ/CHILLER 
V1.0 
[DIRS 153217] 
10057-1.0-00 PC Windows NT Pressure-temperature-composition (P-T-X) 
range defined by the P-T-X range of the 
thermodynamic database. Ionic strength limit 
of ~4 molal (NaCl-dominant solutions) 
Used to compute multicomponent 
heterogeneous chemical equilibria among 
solids, gases, and an aqueous phase. 
SUPCRT92 V1.0 
[DIRS 153218] 
10058-1.0-00 PC Windows 98/NT Pressure-temperature-composition (P-T-X) 
range defined by the P-T-X range of the input 
reference thermodynamic data and equation 
of state parameters (1 to 5000bar and 0 to 
1000C). 
Used to calculate the standard molal 
thermodynamic properties of minerals, 
gases, aqueous species and reactions from 1 
to 5000 bars and 0 to 1000 degrees Celsius. 
TOUGH2 V1.4 
[DIRS 146496] 
10007-1.4-01 Sun 
UltraSparc 
SUNOS 5.5.1 Porous and fractured media, unsaturated to 
fully saturated conditions. 
Used as an integral finite difference 
numerical simulator for non-isothermal flows 
of multicomponent, multiphase fluids in 
porous and fracture media. 
AMESH V1.0 
[DIRS 147561] 
10045-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 1-, 2-, or 3-dimensional grids of any size. Generates discrete 1-D, 2-D or 3-D grids for 
numerical modeling of flow and transport 
problems in which the formulation is based 
on the integral finite difference method. 
switch V1.0 
[DIRS 152899] 
10322-1.0-00 PC Windows NT Input database must be in 
SOLVEQ/CHILLER V1.0 database format. 
Pressure-temperature-composition (P-T-X) 
range defined by the P-T-X range of the 
thermodynamic database. 
Used to switch component species in 
SOLVEQ/CHILLER V1.0. 
regress V1.0 
[DIRS 152900] 
10321-1.0-00 PC Windows NT Input database must be in 
SOLVEQ/CHILLER V1.0 database format. 
Pressure-temperature-composition (P-T-X) 
range defined by the P-T-X range of the 
thermodynamic database. 
Used to calculate regression coefficients of 
log K data as a function of temperature for 
SOLVEQ/CHILLER V1.0. 
mk_incon V1.0 
[DIRS 152901] 
10350-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 Limited to 1-D column for input, and 2-D 
mesh for output. 
Used to create INCON files for input into 
TOUGH2 codes. 

MDL-NBS-HS-000001 REV 04 3-2 February 2005 


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Table 3-1. Qualified Software Used (Continued) 

Software Name 
and Version 
Software 
Tracking 
Number Platform OS Range of Use Brief Description 
KREG V1.1 
[DIRS 161258] 
10318-1.1-00 PC Windows NT Input database must be in TOUGHREACT 
V2.4 (and above) database format. 
Pressure-temperature-composition (P-T-X) 
range defined by the P-T-X range of the 
thermodynamic database. 
Used to calculate regression coefficients of 
log K data as a function of temperature for 
the thermodynamic database of 
TOUGHREACT V2.4 and above. 
KSWITCH V1.1 
[DIRS 161259] 
10319-1.1-00 PC Windows NT Input database must be in TOUGHREACT 
V2.4 (and above) database format. 
Pressure-temperature-composition (P-T-X) 
range defined by the P-T-X range of the 
thermodynamic database. 
Used to switch component species in the 
thermodynamic database of TOUGHREACT 
V2.4 and above. 
THERMOCHK V1.1 
[DIRS 161262] 
10895-1.1-00 PC Windows NT Input database must be in TOUGHREACT 
V2.4 (and above) database format, and 
include molecular weights must be provided 
for all species listed (aqueous, solid, and 
gas). 
Used to check the consistency (mass 
balance and charge balance) of reactions in 
the thermodynamic database of the reactive 
transport code TOUGHREACT V2.4 and 
above 
DBCONV V1.0 
[DIRS 161263] 
10893-1.0-00 PC Windows NT Input database must be in EQ3/6 database 
format, with pressure-temperaturecomposition 
(P-T-X) range defined by the 
P-T-X range of the thermodynamic database. 
Used to convert the YMP EQ3/6 
thermodynamic database to a format suitable 
for input into the reactive transport model 
TOUGHREACT V3.0 
CUTCHEM V1.0 
[DIRS 161127] 
10898-1.00.0 
PC Windows NT Only for use with TOUGHREACT output files 
TEC_nnn.dat. Limit of 30 extracted points 
per general location per point in time. 
Used to extract automatically data from large 
output data files created by the reactive 
transport model TOUGHREACT V2.1 and 
above 
exclude.f V1.0 
[DIRS 153089] 
10316-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 Only for use with output files from mk_circ2 
V1.0 and mk_rect2 V1.0 
Used to exclude points outside a specified 
radius so that points will not overlap when 
output is merged using merggrid.f V1.0 for 
2-D THC seepage model. 
assign.f V1.0 
[DIRS 153090] 
10315-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 2-D grids in TOUGH2 MESH format. Used to assign a geologic name to all 
TOUGH2 elements according to their 
location in the Z-direction for 2-D THC 
seepage model. 
merggrid2.f V1.0 
[DIRS 153091] 
10314-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 Only for use with output files from mk_circ2 
V1.0, mk_rect2 V1.0, and exclude V1.0 
Used to merge input files into one file for 
input into AMESH V1.0 for 2-D THC 
seepage model. 

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Drift-Scale THC Seepage Model 

Table 3-1. Qualified Software Used (Continued) 

Software Name 
and Version 
Software 
Tracking 
Number Platform OS Range of Use Brief Description 
mk_circ2 V1.0 
[DIRS 153092] 
10312-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 1-D or 2-D grids only. Used to create a radial grid for 2-D THC 
seepage model. 
mk_rect2 V1.0 
[DIRS 153093] 
10313-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 1-D or 2-D grids only. Used to create orthogonal grid for 2-D THC 
seepage model. 
2kgridv1a.for V1.0 
[DIRS 153067] 
10382-1.0-00 PC DOS Emul-ation Only for use with 2-D grids in TOUGH2 
format. 
Generates dual-permeability grids for the 
TOUGH2 family of codes. 
mk_grav2.f V1.0 
[DIRS 153068] 
10379-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 Only for use with 2-D grids generated by 
AMESH. 
Reads AMESH V1.0 output files and creates 
TOUGH2 V1.4 mesh input file data, namely 
the gravity vector data and grid block labeling 
data 
sav1d_dst2d.f V1.0 
[DIRS 153083] 
10381-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 Limited to 1-D column for input, and 2-D 
mesh for output. 
Creates an INCON file for TOUGH2 input for 
a 2-D mesh from existing INCON and MESH 
data for a 1-D column 
Mrgdrift.f V1.0 
[DIRS 153082] 
10380-1.0-00 Sun 
UltraSparc 
SUNOS 5.5.1 Limited for use only with a TOUGH2 and 
TOUGHREACT numerical mesh. The 
connecting boundaries of the drift and 
geologic meshes must exactly overlap. 
Merges the geologic mesh with the drift mesh 
for TOUGH2 and TOUGHREACT 
simulations. 

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4. INPUTS 
4.1 DIRECT INPUT 
This section presents all input data used for the THC seepage model (i.e., for the simulations 
presented in Section 6.5), which provides output for use by downstream models that feed 
TSPA-LA (see Section 1.1). The qualified status of all direct inputs is shown in the DIRS 
database. Because this report documents models of coupled phenomena, a wide variety of input 
data is required. The appropriateness of technical product outputs directly used by this model is 
discussed in the following sections, and they are justified for intended use in this model. Input 
data and parameter uncertainties are further addressed in Sections 6 and 7. Section 7 documents 
model input-related model validation. 

4.1.1 Hydrologic and Thermal Properties 
Source DTNs for hydrologic and thermal properties are listed in Table 4.1-1. All sources of 
direct inputs for these parameters are listed in Table 4.1-1; other DTNs and data sources 
discussed in this section are presented for corroborative or informational purposes only. Specific 
values of hydrologic and thermal properties for the repository hydrogeologic model units tsw33, 
tsw34, and tsw35 (Topopah Spring Tuff upper-lithophysal, middle-nonlithophysal, and 
lower-lithophysal units, respectively) are summarized later in Section 6 (Table 6.4-1). 

Modeling analyses utilized data from the mean-calibrated hydrologic property sets for the 
present-day climate. The data sets include properties that are calibrated, such as fracture and 
matrix permeabilities and van Genuchten parameters, and properties such as porosity, heat 
capacity, and thermal conductivity that are obtained from field measurements. DTNs for 
model-boundary temperatures are also included in Table 4.1-1. 

Transport parameters considered in the model are diffusion coefficients for aqueous and gaseous 
species and tortuosities of the fracture, matrix, and engineered system components. Diffusion 
coefficients for all aqueous species are direct inputs to the model and entered as the tracer 
diffusion coefficient of the chloride anion (Cl) at infinite dilution. The aqueous diffusion 
coefficient of Cl at infinite dilution is 2.03  109 m2/s at 25C (Lide 1993 [DIRS 123032], 

p. 5-111), which in the model input is rounded to 2.0  109 m2/s. This handbook source is 
Established Fact, and requires no further justification for use. 
These same sources provide inputs for approximating the CO2 diffusion coefficient from ideal 
gas behavior as described in Section 6.4.6 (item 5), using direct inputs for molecular diameter 
(dm) and molecular weight (M) as follows (unless specified otherwise in Section 6): 

dm = 2.5  1010 m (Lasaga 1998 [DIRS 117091], p. 322) 

M = .04401 kg/mol (Lide 1993 [DIRS 123032], p. 4-50). 

Once again, input from Lide (1993 [DIRS 123032]) is Established Fact. The data from Lasaga 
(1998 [DIRS 117091], p. 322) are widely accepted and referenced throughout the scientific 
community and, hence, are justified for their intended use in this model. 

MDL-NBS-HS-000001 REV 04 4-1 February 2005 


Drift-Scale THC Seepage Model 

The diffusion coefficient for CO2 is calculated using Equation 6.4-24 (Lasaga 1998 
[DIRS 117091], p. 322). This is a standard method of calculating the diffusion coefficient (see, 
for instance, Bird et al. 1960 [DIRS 103524], Equations 16.4 to 16.9), is quite common, and is 
justified for use in this document. 

Table 4.1-1. Sources of Hydrologic and Thermal Properties Used as Direct Input Data for the Drift-Scale 
Coupled-Processes Models That Feed TSPA-LA Activities 

Source Data/Parameter Descriptiona 
Hydrologic and Thermal Rock Properties 
Penman 1940 [DIRS 109941], pp. 441, 
461, Eq. 5 
Fracture tortuosity applied to thermal parameters of lithologic units (see 
text) 
LB0205REVUZPRP.001 [DIRS 159525] Fracture parameters: permeability, porosity, van Genuchten m, 
residual saturation, satiated saturation, fracture frequency, fracture to 
matrix area 
LB0208UZDSCPMI.002 [DIRS 161243] Fracture and matrix van Genuchten alpha, matrix permeability, active 
fracture parameter (gamma) 
LB0207REVUZPRP.002 [DIRS 159672] 
(file: matrix_props.xls) 
Matrix parameters: van Genuchten m, residual saturation, satiated 
saturation 
LB0210THRMLPRP.001 [DIRS 160799] Matrix porosity and thermal properties: dry- and wet-rock grain 
conductivity, grain specific heat, and grain density 
LL000114004242.090 [DIRS 142884] Infiltration ratesaverage infiltration rate (mean, lower bound, and upper 
bound for present-day, monsoonal, and glacial transition climates) from 
the TH drift-scale models 
SN0002T0872799.009 [DIRS 153364] Effective thermal conductivities for in-drift open spaces (see Appendix 
E) 
Mineralogical Data 
LB0101DSTTHCR1.002 [DIRS 161277] 
(file: ecrb_cdtt_mindata.xls) 
Mineral volume fractions 
LB0101DSTTHCR1.004 [DIRS 161279] 
(file: ecrb_cdtt_mindata.xls) 
Mineral surface areas 
Kinetic Data 
LB0307KNTDBRTM.001 [DIRS 164433] Rate constants and activation energies 
Thermodynamic Data 
LB0307THMDBRTM.001 [DIRS 164434] Thermodynamic data for aqueous species and minerals: equilibrium 
constants, molecular weights, molar volumes, Debye-Hckel 
parameters, CO2 molecular diameter 
Analytical Water and Gas Chemistry Data 
MO0005PORWATER.000 [DIRS 
150930] 
Analyses of pore waters from Alcove 5 core samples in the ESF 
(HD-PERM-2 and HD-PERM-3 samples) 
GS020408312272.003 [DIRS 160899] Pore water analyses from ECRB Cross-Drift and USW SD-9 borehole 
core samples (Table 4.1-3) 
Tptpmn and Tptpll THC Model Grid Data 
LB990501233129.004 [DIRS 111475] 
LB0011DSTTHCR1.002 [DIRS 161282] 
Stratigraphy (Z coordinates of hydrogeologic units) for central location 
(column j34) Tptpll THC model. 
THC model mesh with hydrogeologic units in the vicinity of the drift 

MDL-NBS-HS-000001 REV 04 4-2 February 2005 


Drift-Scale THC Seepage Model 

Table 4.1-1. Sources of Hydrologic and Thermal Properties Used as Direct Input Data for the 
Drift-Scale Coupled-Processes Models That Feed TSPA-LA Activities (Continued) 

LB990701233129.002 [DIRS 125604] Top and bottom boundary temperatures, pressure, liquid/gas 
saturations, and boundary elevations 
LB990601233124.001 [DIRS 105888] Permeability Measurements in Tptpmn 
a Values of thermal and hydrologic properties used in the THC models are summarized in Table 6.4-1 

4.1.1.1 Fracture Tortuosity 
Tortuosities are set to 0.7 for fractures, based upon theoretical calculations and experimental 
measurements given by Penman (1940 [DIRS 109941], p. 441, Eq. 5), who estimated that an 
isotropic porous medium has a tortuosity of 2 -1 or ~0.707. Penman (1940 [DIRS 109941], 

p. 461) also obtained an experimentally measured tortuosity value 0.66 based on steady-state 
vapor diffusion through soil material having porosities of up to 0.7, thus corroborating his own 
theoretical value. Additional corroborative data are available from de Marsily (1986 
[DIRS 100439], p. 233), who states that a tortuosity value of 0.7 is within the upper range for 
porous media. Its use in this model is based on the assumption that the ensemble of fractures in 
an unsaturated media behaves as an isotropic porous medium. 
Given the similarity of Penmans two estimated values, and the corroborative data provided by 
de Marsily, and assuming that the actual percolation paths expected in granular materials 
approximate those present in a complex fractured medium, a fracture tortuosity value of 0.7 is 
justified for the intended use in this model. A matrix tortuosity of 0.2 is assumed, with rationale 
provided, in Section 6.4.6. 

An additional justification for the fracture and matrix tortuosity values used here is consistency 
with other unsaturated zone reports. The same matrix and fracture tortuosity values are used in 
Multiscale Thermohydrologic Model (BSC (2004 [DIRS 169565], Section 5.3.1.9), 
Mountain-Scale Coupled Processes (TH/THC/THM) (BSC 2004 [DIRS 169866]), and 
Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338], 
Section 4.1.1.1). 

4.1.1.2 Mean Infiltration Rates 
The infiltration values used in this model are provided in DTN: LL000114004242.090 
([DIRS 142884], file chimney_infiltration_fluxes). The infiltration rates applied at the top of 
the THC seepage model are adopted from the mean infiltration scenario that includes present-day 
(0 to 600 years), monsoonal (600 to 2,000 years), and glacial transition climates (more than 
2,000 years), as described in Simulation of Net Infiltration for Modern and Potential Future 
Climates (BSC 2004 [DIRS 170007], Sections 6.9 and 6.11) and, for the time interval defining 
each climate state, Multiscale Thermohydrologic Model (BSC 2004 [DIRS 169565], Section 5). 
The specific infiltration values (6, 16, and 25 mm/yr for the present-day, monsoonal, and glacial 
transition periods, respectively) represent repository-wide averages based upon historical data. 
These values are calculated as arithmetic averages of 31 repository locations considered in 
Multiscale Thermohydrologic Model (BSC 2001 [DIRS 158204], Section 6.3.1). The infiltration 
values used at these 31 repository locations are provided in DTN: LL000114004242.090 

MDL-NBS-HS-000001 REV 04 4-3 February 2005 


Drift-Scale THC Seepage Model 

([DIRS 142884], file chimney_infiltration_fluxes, median infiltration cases) and summarized 
in Table 4.1-2. The calculated averages have been rounded to 6 mm/yr, 16 mm/yr, and 25 
mm/yr, respectively, for use in this report. 

More recent estimates of the average infiltration rates under the three different climatic 
conditions are now available, and provide corroboration for these historic values. Table 6.1-2 in 
UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]) provides the mean infiltration 
values at the top of the entire UZ model domain (not the same as the 31 locations previously 
averaged) as 4.4, 11.8, and 17.0 mm/yr under present-day, monsoonal, and glacial transition 
climatic conditions. These numbers are obtained by averaging infiltration data in 
DTN: GS000308311221.005 [DIRS 147613]. Average infiltration rates at the PTn-TSw 
interface have also been developed based on the average surface infiltration rates given in Table 
6.1-2 of UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]). These average rates are 
summarized in Table 6.6-11 of Abstraction of Drift Seepage (BSC 2004 [DIRS 169131]). Over 
the entire UZ model domain, the average infiltration fluxes at the PTn-TSw interface under mean 
infiltration conditions are 4.8, 13.2, and 18.8 mm/yr for the three climatic conditions. However, 
over the repository footprint, the average infiltration fluxes at the same location (PTn-TSw 
interface) are 3.8, 11.7, and 17.9 mm/yr, respectively, for the three climatic states. 

Table 4.1-2. Average Infiltration Values (mm/yr) for Different Climate Periods 

Column Present-Day Monsoonal Glacial Transition 
l7c4 1.493 3.252 5.211 
l7c3 4.677 10.710 18.418 
l7c2 5.554 13.726 22.420 
l7c1 1.700 4.588 7.013 
l6c5 9.410 17.746 30.732 
l6c4 11.302 32.651 47.872 
l6c3 4.180 10.303 16.574 
l6c2 3.147 7.163 10.986 
l6c1 3.879 9.432 15.079 
l5c5 8.428 17.265 29.872 
l5c4 14.412 40.972 60.237 
l5c3 5.680 13.120 19.949 
l5c2 7.395 17.707 27.097 
l5c1 0.663 0.436 0.816 
l4c5 5.449 14.472 20.214 
l4c4 10.132 28.876 41.998 
l4c3 10.144 24.091 38.660 
l4c2 6.909 16.900 27.923 
l4c1 4.794 12.093 18.881 
l3c4 15.877 43.993 65.028 
l3c3 1.304 2.637 4.194 
l3c2 0.485 0.492 1.271 
l3c1 6.335 18.869 27.005 
l2c4 15.998 42.285 58.627 
l2c3 12.011 40.749 63.168 
l2c2 1.416 9.154 23.399 

MDL-NBS-HS-000001 REV 04 4-4 February 2005 


Drift-Scale THC Seepage Model 

Table 4.1-2. Average Infiltration Values (mm/yr) for Different Climate 
Periods (Continued) 

Column Present-Day Monsoonal Glacial Transition 
l2c1 0.406 0.250 0.733 
l1c4 3.015 11.575 19.057 
l1c3 7.809 21.854 32.439 
l1c2 0.877 0.940 2.130 
l1c1 0.574 10.004 13.523 
Average 5.942 16.074 24.856 

Source: DTN: LL000114004242.090 [DIRS 142884]. 

It is evident that the average percolation fluxes (6, 16, and 25 mm/yr for the present-day, 
monsoonal, and glacial transition climatic conditions, respectively) used in the THC model 
simulations in this report are larger than the most recent estimates for the entire UZ domain of 
4.4, 11.8, and 17.0 mm/yr. However, the UZ model domain covers a much larger area than the 
repository footprint, and includes more area at low elevation that, in general, has lower 
percolation fluxes. Also, because infiltration rates and transport through the rock matrix are so 
slow, processes in the high thermal gradient of the near field (evaporation, condensation, 
degassing) have a much greater effect on the chemical evolution of potential seepage waters than 
the small differences between currently accepted infiltration rates and those used in the THC 
seepage model. Furthermore, the present range in infiltration rates over the repository block is 
much greater than the small differences in the averages (BSC 2004 [DIRS 169565], Table 6.3-4), 
which are also a function of the actual area over which the averages are computed. This justifies 
the use of 6, 16, and 25 mm/yr as the infiltration fluxes for the three climatic conditions. 

4.1.1.3 Thermal Properties 
The source for the thermal properties data listed in Table 4.1-1 of this report is 
DTN: LB0210THRMLPRP.001 [DIRS 160799]. Thermal properties for the UZ model layers 
have since been updated and a more recent source (DTN: LB0402THRMLPRP.001 
[DIRS 168481]) is currently available. These new values provide corroboration for the older 
data set used here, because in most cases, especially for repository-level units, the new values are 
the same or very similar to the older ones. In addition, sensitivity analyses have been 
carried out to determine the impact of using the older thermal properties from 
DTN: LB0210THRMLPRP.001 [DIRS 160799] instead of the more recent values. The results 
of these analyses are presented in Section 6.5.5.5, and show that the choice of a thermal property 
data set has no significant effect on model predictions. Thus, the older data set 
(DTN: LB0210THRMLPRP.001 [DIRS 160799]) is justified for intended use within this model. 

4.1.1.4 Effective Thermal Conductivities for In-Drift Open Spaces 
The effective thermal conductivities for in-drift open spaces that are used in the THC seepage 
model are listed in Appendix E. The source for these numbers is an historic DTN, 
SN0002T0872799.009 [DIRS 153364]. These values are generated based on in-drift 
temperature predictions calculated for FY 01 Supplemental Science and Performance Analyses, 
Volume 1: Scientific Bases and Analyses (BSC 2001 [DIRS 155950], Section 5.4.1) (SSPA). 

MDL-NBS-HS-000001 REV 04 4-5 February 2005 


Drift-Scale THC Seepage Model 

The in-drift temperature predictions used by the SSPA are compared to those of the current 
multiscale thermohydrologic model (MSTHM), as given in Section 6.3.8 of the accompanying 
report (BSC 2004 [DIRS 169565]). The differences are slight, indicating that the effective 
thermal conductivities, if recalculated, would be very similar to those used here. Because the 
effective thermal conductivity of the rock is much lower than that of the in-drift atmosphere, the 
rock properties dominate in terms of thermal-hydrologic effects, and the slight differences in the 
thermal conductivity of the in-drift air would have no effect on THC seepage model results. 
Thus, the historic values from DTN: SN0002T0872799.009 [DIRS 153364] are justified and 
sufficient for intended use in this model. 

4.1.2 Mineralogical Data 
These input data consist of mineral volume fractions per total solid volume and their reactive 
surface areas. Reactive surface areas are used to characterize minerals either in the matrix of the 
rock (cm2/g mineral) or those on the surface of fractures (m2/m3 of fracture medium, including 
pore space), respectively (see Section 6.4.3.1). 

These data are taken from DTN: LB0101DSTTHCR1.002 [DIRS 161277] and 
DTN: LB0101DSTTHCR1.004 [DIRS 161279]. For convenience, these data are shown in 
Appendix A (volume fractions) and Appendix B (reactive surface areas), respectively. 

The mineral abundances and surface areas used in the model simulations are calculated from 
core sample measurements, as explained in Section 6.2.2.2 (these data are presented and 
discussed here for reference onlythey are not direct inputs). The rock matrix mineralogical 
data are for a stratigraphic column near the center of the repository, based on a surface borehole 
core (DTN: LA9908JC831321.001 [DIRS 113495]). The fracture mineralogical data are based 
on fracture mineral abundances in core from underground boreholes in the Exploratory Studies 
Facility (ESF), in the regions of the Single Heater Test (DTN: LA0009SL831151.001 
[DIRS 153485]) and the Drift Scale Test (DTNs: LA9912SL831151.001 [DIRS 146447] and 
LA9912SL831151.002 [DIRS 146449]). Section 6.4.3 details the sources and methods for 
obtaining these data. 

These two direct input DTNs are product output of a previous revision (REV01) of this report 
(BSC 2001 [DIRS 154426], Section 6.1.5 and Attachments II and IV). They were developed as 
input for model simulations. The previous report was revised because of changes in other input 
parameter sets and in model implementation. These changes had no effect on the mineralogical 
data in these DTNs, which are based upon the best available project information. Therefore, 
although these DTNs are product output from a superseded document, they are justified as 
sources for the mineralogical data used in the current report. 

4.1.3 Kinetic Data 
Kinetic data refer to the reaction rate constants (ko), activation energies (Ea), and related data 
required to describe the rates of dissolution and precipitation of minerals as a function of 
temperatures and fluid chemistry. 

MDL-NBS-HS-000001 REV 04 4-6 February 2005 


Drift-Scale THC Seepage Model 

Reaction rate laws can take numerous forms, of which a restricted number are used for the model 
analyses. The form of these rate laws and their significance are described in Section 6.4.2. 
Listed kinetic parameters are defined and used in Equations 6.4-5 through 6.4-8. 

Model simulations are conducted using the kinetic data from DTN: LB0307KNTDBRTM.001 
[DIRS 164433]. These data are qualified for use in Appendix H of this document. For 
convenience, these data are shown in Table 4.1-3. Not listed in this table are salt phases that are 
quantitatively precipitated, using a normative approach, when grid cells dry out (Section 6.4.5). 
Upon rewetting, dissolution of these salt minerals (i.e., NaNO3, K2SO4, Na2SO4, MgSO4, halite, 
sylvite) is kinetically limited (to ensure that solute concentrations do not exceed the ionic 
strength limit of the model), with a relatively fast rate constant (106 mol/m2/s). 

Table 4.1-3. THC Model Kinetic Data 

MINERAL 
k+/- (mol m2 s1)a 
at 298.15 K Ea (kJ/mol)b mc nc Commentd 
a-Cristobalite 
SiO2 
3.45  1013 68.9 1 1 dissolution only 
Quartz 
SiO2 
4.52  1014 90.1 1 1 dissolution only 
Tridymite 
SiO2 
3.45  1013 68.9 1 1 dissolution only 
Amorphous silica 7.32  1013 60.9 1 1 dissolution 
SiO2 1.0  1010 50 4.4 1 precipitation 
Opal-proxy 
SiO2 
7.32  1013 60.9 1 1 dissolution only 
Microcline = K-spar 
KAlSi3O8 
1.78  1013 36 1 1 reversible 
Albite-low 
NaAlSi3O8 
7.08  1013 67.7 1 1 reversible 
Anorthite 
CaAl2Si2O8 
3.16  1012 67.7 1 1 dissolution only 
Illite 
K0.5(Mg0.22Al1.78) 
(Si3.72Al0.28)O10(OH)2 
2.0  1014 58.6 1 1 reversible 
Smectite-Ca 
Ca0.145(Mg0.26Al1.74) 
(Si3.97Al0.03)O10(OH)2 
2.0  1014 58.6 1 1 reversible 
Smectite-Mg 
(Mg0.405Al1.74)(Si3.97Al0.03) 
O10(OH)2 
2.0  1014 58.6 1 1 reversible 
Smectite-Na 
Na0.29(Mg0.26Al1.74) 
(Si3.97Al0.03)O10(OH)2 
2.0  1014 58.6 1 1 reversible 
Sepiolite 
Mg2Si3O7.5OH3H2O 
2.67  1014 58.6 1 1 reversible 
Kaolinite 
Al2Si2O5(OH)4 
1.0  1013 7.1 ( 2.5) 1 1 reversible 

MDL-NBS-HS-000001 REV 04 4-7 February 2005 


Drift-Scale THC Seepage Model 

Table 4.1-3. THC Model Kinetic Data (Continued) 

MINERAL 
k+/- (mol m2 s1)a 
at 298.15 K Ea (kJ/mol)b mc nc Commentd 
Heulandite 
Ca0.33K0.04Na0.1 
(Al0.8Si2.8O7.2)  2.6H2O 
5.66  1013 58.0 1 1 dissolution 
Clinoptilolite 
Ca0.28K0.08Na0.04 
(Al0.68Si2.92O7.2)  2.6H2O 
2.37  1013 58.0 1 1 reversible 
Stellerite 
Ca0.39Na0.01(Al0.79Si2.81O7.2) 
2.8H2O 
5.66  1013 58.0 1 1 reversible 
Mordenite 
Ca0.15Na0.21K0.09(Al0.6Si3O7.2) 
2.2H2O 
5.66  1013 58.0 1 1 reversible 
Calcitee 1.60  106 48.1 1 1 reversible 
CaCO3 equilibrium NA NA NA local equilibrium 
Gypsum 
CaSO42H2O 
equilibrium NA NA NA local equilibrium 
Fluorite 
CaF2 
1.22  107 0.0 1 2 reversible 
Hematite 
Fe2O3 
equilibrium NA NA NA local equilibrium 
Glass 7.72  1015 91.0 1 1 dissolution only 

Source: DTN: LB0307KNTDBRTM.001 [DIRS 164433]. 

a

 k+/-: Dissolution/precipitation rate constants at 298.15 K. 
b Ea: Activation energy. 


c 

Exponents m and n in Equations 6.4-5, 6.4-7, and 6.4-8. 
d The comment dissolution only means precipitation of this mineral is not allowed; reversible 
indicates the same precipitation and dissolution rates apply. 

e 

Calcite is fixed at local equilibrium in the THC seepage model, and kinetically limited in the DST THC 
submodel. 

4.1.4 Thermodynamic Data 
The source of the thermodynamic data is DTN: LB0307THMDBRTM.001 [DIRS 164434]. 
These data consist mostly of chemical equilibrium constants in logarithmic form, log(K), as a 
function of temperature (not to be confused with thermal conductivity, often described also using 
the letter K), for reactions describing the dissociation of secondary aqueous species, minerals, 
and gases involved in the model (Section 6.4.1). Molecular weight and diameter, molar volume, 
and ion size data for the calculation of aqueous activity coefficients are also included in the 
thermodynamic data sets. Kinetic rate constants, k (always in lower case), are provided in a 
separate database discussed in Section 4.1.3 (also Sections 6.4.2 and 6.4.8) and are not to be 
confused with equilibrium constants, K. 

For convenience, the thermodynamic data set is shown in Appendix C (zeolite phases used are 
those identified in Appendix C with names heul/10-r02, stell/10-r02, mord/10-r02, and 

MDL-NBS-HS-000001 REV 04 4-8 February 2005 


Drift-Scale THC Seepage Model 

clpt/10-r02, except for alternative data sets as discussed in Section 6.4.8). The mineralogical 
database represents a compendium of data from several sources, as described below. Only 
DTN: LB0307THMDBRTM.001 [DIRS164434] is direct input; the discussion below is 
provided so the reader can evaluate the appropriateness of the thermodynamic data in that DTN. 

Most of the data in the direct input DTN (LB0307THMDBRTM.001 [DIRS164434]), are 
originally from the Yucca Mountain Project (YMP) thermodynamic database data0.ymp.R2 
(DTN: MO0302SPATHDYN.000 [DIRS 161756]). Documentation of changes from the 
data0.ymp.R2 database is provided in DTN: LB0307THMDBDRTM.001 [DIRS 164434]. The 
most important changes from data0.ymp.R2 include: 

 Aluminum aqueous species data consistent with thermodynamic data used in earlier 
revisions of this report. These aluminum data are derived from Pokrovskii and Helgeson 
(1995 [DIRS 101699]). In the weakly-acid-to-alkaline pH values covered in this study, 
and at temperatures below 150C, the Pokrovskii and Helgeson (1995 [DIRS 101699]) 
data yield essentially the same gibbsite solubility as the data currently in data0.ymp.R2 
(DTN: MO0302SPATHDYN.000 [DIRS 161756]), and essentially the same pK values 
for the protonation of the AlO2 (or Al(OH)4) to HAlO2 (or Al(OH)3). 
 Revised aqueous silica thermodynamic properties yielding solubility constants (log(K)) 
very similar to those reported by Rimstidt (1997 [DIRS 101709]) for quartz and 
Gunnarsson and Arnrsson (2000 [DIRS 160465]) for amorphous silica. These data are 
also consistent with thermodynamic data used in earlier revisions of this report, and 
provide more accurate amorphous silica solubilities than the data0.ymp.R2 data. 
 Solubility constants for albite and anorthite from Arnrsson and Stefnsson (1999 
[DIRS 153329], p. 173). These data are consistent with those used in earlier versions of 
this report and with the aqueous silica data used here. 
 Solubility constants for K-feldspar adjusted to yield equilibration of the HD-PERM pore 
water (Table 6.2-1) with illite (below) and K-feldspar. This adjustment results in a Gibbs 
free energy value for this phase at 25C within the range of literature data reported by 
Arnrsson and Stefnsson (1999 [DIRS 153329], Table 1) and within 700 calories of the 
value reported by Robie et al. (1979 [DIRS 107109]). Without this adjustment, 
calculated potassium concentrations in pore waters are too small. 
 Revised clay (smectite and illite) data consistent with those used in earlier versions of this 
report. The revisions include log(K) values for illite derived from accurate solubility 
measurements by Kulik and Aja (1997 [DIRS 128132]), and log(K) values for smectites 
adjusted to yield equilibration as an ideal solid solution at 25C with the HD-PERM pore 
water (Table 6.2-1). Without this revision, the calculated pH of pore waters through 
time, under ambient conditions (no thermal load), becomes unrealistically elevated 
(Section 6.5.5.2.1). 
 Revised zeolite (stellerite, heulandite, mordenite, and clinoptilolite) data for consistency 
with new stellerite data reported by Fridriksson et al. (2001 [DIRS 160460]). Without 
this revision, an unrealistic calcium depletion is predicted to occur in pore waters under 
MDL-NBS-HS-000001 REV 04 4-9 February 2005 


Drift-Scale THC Seepage Model 

ambient conditions (no thermal load), due to the precipitation of large amounts of 
calcium zeolites (Section 6.5.5.2.1) 

Of these changes, the last two have the most significant effect on simulation results compared to 
results obtained using the project database data0.ymp.R2 (DTN: MO0302SPATHDYN.000 
[DIRS 161756]) (Section 6.5.5.1). The stellerite thermodynamic data in data0.ymp.R2 reflect a 
significantly higher stability for this mineral than what the new data from Fridriksson et al. (2001 
[DIRS 160460]) suggest. The clay data in data0.ymp.R2 also reflect a greater stability than 
the revised data used here. More details on all changes from the data0.ymp.R2 
database are provided in the documentation accompanying the data filed under 
DTN: LB0307THMBDRTM.001 [DIRS 164434]. 

Ambient simulations (Section 6.5.5.4) have been conducted using alternative data sets including 
the data0.ymp.R2 database. These ambient simulations have been run to provide a justification 
for the use of data from DTN: LB0307THMDBRTM.001 [DIRS 164434] (which include the 
changes described above). Sources of data for the alternative data sets are presented in Section 

6.4.8. 
4.1.5 Water and Gas Chemistry 
Sources of water- and gas-chemistry data are provided in Table 4.1-1. The pore-water 
compositions used as inputs to the model simulations are shown in Table 4.1-4. 

The only nearly complete pore-water analyses available at the start of these investigations, for 
samples collected from a repository unit near the repository footprint, were obtained in 1998 
from the Tptpmn geologic unit in Alcove 5 near the DST. At the time, three pore-water samples 
were ultracentrifuged from Alcove 5 core. These analyses are reported in 
DTN: MO0005PORWATER.000 [DIRS 150930]. Two of these analyses with the closest 
compositions (HD-PERM-2 and HD-PERM-3, Table 4.1-4) have been averaged and the 
resulting composition, referenced hereafter as Alcove 5 or HD-PERM water (Section 6.2.2.1), is 
used as input to the THC model. 

Although the HD-PERM waters are used as input into the THC seepage model and the DST 
THC submodel, storage and analysis conditions for these samples were not optimal, and may 
have affected sample chemistry. These samples were stored for several months prior to analysis, 
exceeding recommended EPA holding times for water analysis (BSC 2004 [DIRS 169900], 
Section 6.3.4.1.3). Such long hold times may affect the concentration of some ionsin 
particular, nitrate concentrations may be lowered by microbial reduction in the stored waters. 
Despite these issues, HD-PERM waters have been retained as model inputs because they have 
been used historically, and continued use allows more direct comparison with previous versions 
of the model. 

MDL-NBS-HS-000001 REV 04 4-10 February 2005 


Table 4.1-4. Input Pore-Water Compositions 

Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 4-11 
February 2005 

Sample ID . 
ESF-HD-PERM-2 
(30.1-30.5)a 
(ESF Alcove 5) 
ESF-HDPERM-3 
(34.8-35.1)a 
(ESF Alcove 5) 
ECRB-SYS-
CS1000/7.3-7.7/UCb 
ECRB-SYS-
CS2000/16.521.1/UCb SD-9/990.4-991.7/UCb 
ECRB-SYS-
CS500/12.0-16.7/UCb 
Lithostratigraphic Unit . Tptpmn Tptpmn Tptpul (base) Tptpll Tptpll Tptpul 
Units 
pH (measured) pH 8.32 8.31 7.6 7.4 7.9 8.0 
Na+ mg/L 61 62 39 130 84 57 
K+ mg/L 7 9 7.6 10.6 7.9 10.3 
Ca+2 mg/L 106 97 94 82 56 120 
Mg+2 mg/L 16.6 17.4 18.1 5.3 0.9 19.3 
SiO2 mg/L 31 (as Si) 35 (as Si) 42 48 50 49 
Cl mg/L 110 123 21 26 23 54 
SO4 
2 mg/L 111 120 36 39 10 78 
HCO3 
 (measured) mg/L   333 382 313 286 
NO3 
 mg/L 3 10 2.6 4.2 17 6.1 
F mg/L 0.96 0.76 3.4 11 2.5 4.8 

a 

Pore water analyses from Alcove 5 (Tptpmn)are reported in DTN: MO0005PORWATER.000 [DIRS 150930]. The sample ID corresponds to the ESF borehole 
ID and is followed by the sampling depth in feet from collar. 

b Pore water analyses from the ECRB cross-drift and borehole SD-9 are reported in DTN: GS020408312272.003 [DIRS 160899]. Note that, for ECRB samples, 
the sample ID contains the cross-drift station in meters (e.g., CS1000) and the sampled interval in feet from collar (e.g., 7.3-7.7). The ID of the SD-9 sample 
contains the sampled depth interval in feet from the ground surface. 


Drift-Scale THC Seepage Model 

For the current THC model, five different input pore water compositions are used. In addition to 
HD-PERM, four additional waters have been chosen from a series of pore-water samples that 
were ultracentrifuged from core collected in the Enhanced Characterization of Repository Block 
(ECRB) Cross-Drift and from core obtained from the drilling of borehole SD-9. These samples 
were analyzed and the compositions are reported in DTN: GS020408312272.003 
[DIRS 160899]. Four of these samples (ECRB-SYS-CS7.3-7.7/UC, ECRB-SYS-CS2000/16.521.1/
UC, SD-9/990.4-991.7/UC, and ECRB-SYS-CS500/12.0-16.7/UC) and HD-PERM water 
have been selected as input water compositions for the THC seepage model (Table 4.1-4). The 
rationale for selecting these samples and determination of concentrations for constituents that 
were not measured is discussed in Section 6.2.2.1. 

4.1.6 Tptpll THC Model Grid 
Direct input sources of the THC model grid data are provided in Table 4.1-1. Stratigraphy is 
provided by DTN: LB99051233129.004 [DIRS 111475]; the THC model mesh, by 
DTN: LB0011DSTTHCR1.002 [DIRS 161282]; and model boundary conditions, by 
DTN: LB990701233129.002 [DIRS 125604]. These are historical data sets, slightly different 
than the current values. Justification for using older data sets for stratigraphy, THC model mesh, 
and boundary conditions is provided below. A more recent source of this data 
(DTN: LB03023DKMGRID.001 [DIRS 162354]) is referenced here for corroborative purposes 
only. 

The geologic data for the Tptpll THC model is derived from the UZ model grid in 
DTN: LB99051233129.004 [DIRS 111475]. This DTN represents the UZ model grid that was 
current at the time the THC seepage modeling was performed; however, a more recent numerical 
grid for the UZ is now available (DTN: LB03023DKMGRID.001 [DIRS 162354]). 

The stratigraphy of the Tptpll THC model is extracted at a location near the center of the 
repository (at approximately Nevada State Plane coordinates E170572, N233194). Geologic 
data from column j34 of the UZ model grid (DTN: LB990501233129.004 [DIRS 111475]) are 
used to map geologic contacts into the two-dimensional mesh. The elevations of the contacts 
between various geological layers as implemented in the Tptpll model are shown in Table 4.1-5. 
Table 4.1-5 also gives the thickness of each geological layer in Column j34. These thickness 
values have been adopted for the Tptpll THC model. The column closest to the location 
of Column j34 in the revised UZ numerical grid (DTN: LB03023DKMGRID.001 
[DIRS 162354]) is Column h74. The elevations and thicknesses of each geological layer in 
Column h74 in DTN: LB03023DKMGRID.001 [DIRS 162354] are also shown in Table 4.1-5 
(fourth and fifth columns). The top elevations and thicknesses of the geological layers in 
Column h74 (revised) are comparable with those of Column j34 (adopted), particularly for 
the repository units. For example, for the tsw33, tsw34, tsw35, and tsw36 layers, the 
(adopted) thicknesses in Column j34 are 80.1 m, 37.2 m, 101.4 m, and 33.2 m, respectively. 
The respective (revised) values in Column h74 are 80.3, 34.5, 102.5, and 32.7 m. In the Tptpll 
THC model, the waste emplacement drift (and the source of heat) is located in the tsw35 
geological layer. For this layer, the difference in adopted and revised thickness is only 1.1 m (or 
the difference is about one percent). The thickness of the tsw34 layer differs by about 2.7 m 
(or less than eight percent). However, the tsw34 layer is situated more than 50 m away from 
the source of heat in the Tptpll THC model and the impact of heating in the Tptpll THC model is 

MDL-NBS-HS-000001 REV 04 4-12 February 2005 


Drift-Scale THC Seepage Model 

not realizable that far away. Thus, the difference in thickness in the Tsw34 layer between the 
adopted and revised values is unlikely to have any impact on the thermal seepage simulations in 
the Tptpll model. The differences in thickness between adopted and revised values far away 
(both top and bottom) from the source of heat in the Tptpll THC model are similarly not 
expected to have any significant impact on the thermal seepage simulations. It is thus justified to 
use geological data from the older DTN (LB990501233129.004 [DIRS 111475]). No sensitivity 
analysis is considered necessary for this adaptation. 

The model mesh is from DTN: LB0011DSTTHCR1.002 [DIRS 161282], which contains input 
and output files from an earlier revision of this document. This file has been superseded by more 
recent THC seepage model outputs. However, the supersession was due to changes in other 
input parameters (e.g., thermodynamic data) and updates in the model code to TOUGHREACT 
V3.0. The model mesh was not affected by these changes. In addition, the mesh is based on the 
stratigraphic column described in DTN: LB990501233129.004 [DIRS 111475], with node 
coordinates based on stratigraphic contacts between lithologic units. Thus, the stratigraphic data 
and model mesh are linked, and use of the stratigraphic data from DTN: LB990501233129.004 
[DIRS 111475] requires use of the model mesh described in DTN: LB0011DSTTHCR1.002 
[DIRS 161282]. The model boundary conditions (depth, pressure, etc.) described in 
DTN: LB990701233129.002 [DIRS 125604] are also, in part, linked to the assumed geologic 
column and dimensions of the model grid. Although the boundary conditions used in the THC 
model may vary slightly from currently accepted values, predicted water compositions within the 
near field (a few tens of meters from the drift) are not sensitive to these parameters. Therefore, 
stratigraphy in DTN: LB990501233129.004 [DIRS 111475], the model mesh from 
DTN: LB0011DSTTHCR1.002 [DIRS 161282], and the boundary conditions from 
DTN: LB990701233129.002 [DIRS 125604] are justified for intended use. 

Table 4.1-5. Comparison of Adopted and Revised Values of Elevation and Thickness of Stratigraphic 
Layers for the THC Seepage Model (Tptpll Unit) 

Model 
Layer 
Direct Inputs Corroborative Data 
Adopted Elevation, 
Column j34 in 
LB990501233129.004 
(m) 
Adopted Thickness, 
Column j34 in 
LB990501233129.004 
(m) 
Revised Elevation, 
Column h74 in 
LB03023DKMGRID.001 
(m) 
Revised Thickness, 
Column h74 in 
LB03023DKMGRID.001 
(m) 
Top 1446.6  1424.4  
tcw11 1446.6 27.4 1424.4 3.6 
tcw12 1419.2 77.1 1420.8 96.7 
tcw13 1342.1 15.6 1324.1 5.3 
ptn21 1326.5 3.4 1318.8 2.3 
ptn22 1323.1 2.1 1316.5 5.1 
ptn23 1321.0 2.8   
ptn24 1318.2 5.5 1311.4 4.3 
ptn25 1312.7 9.1 1307.1 7.9 
ptn26 1303.6 9.5 1299.2 13.6 
tsw31 1294.1 14.4 1285.6 2.0 
tsw32 1279.7 30.4 1283.6 39.1 
tsw33 1249.3 80.1 1244.5 80.3 
tsw34 1169.2 37.2 1164.2 34.5 
tsw35 1132.0 101.4 1129.7 102.5 

MDL-NBS-HS-000001 REV 04 4-13 February 2005 


Drift-Scale THC Seepage Model 

Table 4.1-5. Comparison of Adopted and Revised Values of Elevation and Thickness of Stratigraphic 
Layers for the THC Seepage Model (Tptpll Unit) (Continued) 

Model 
Layer 
Direct Inputs Corroborative Data 
Adopted Elevation, 
Column j34 in 
LB990501233129.004 
(m) 
Adopted Thickness, 
Column j34 in 
LB990501233129.004 
(m) 
Revised Elevation, 
Column h74 in 
LB03023DKMGRID.001 
(m) 
Revised Thickness, 
Column h74 in 
LB03023DKMGRID.001 
(m) 
tsw36 1030.6 33.2 1026.2 32.7 
tsw37 997.4 16.6 993.5 23.1 
tsw38 980.8 13.8 970.4 9.2 
tsw39 967.0 10.1 961.2 4.1 
ch1v 956.9 21.7 957.1 14.4 
ch2v 945.2 13.3 942.7 12.9 
ch3v 931.9 12.7 929.8 12.8 
ch4z 919.2 12.8 917.0 10.3 
ch5z 906.4 14.0 906.7 20.3 
ch6 892.4 13.9 886.4 7.8 
pp4 878.5 12.6 878.6 13.3 
pp3 865.9 32.7 865.3 50.3 
pp2 833.2 15.0   
pp1 818.2 61.5 815.0 64.1 
bf3 756.7 33.7   
Bottom 730.0  751.9  

Source: DTNs: LB990501233129.004 [DIRS 111475], LB03023DKMGRID.001 [DIRS 162354]. 

NOTE: The elevations in the second column above have been calculated by taking an average of the elevations 
at nodes of respective elements in the vertical column j34. Note also that in Column h74 of DTN: 
LB03023DKMGRID.001 [DIRS 162354] there is no ptn23 geologic layer. Also, geologic layers pp2 and 
bf3 are absent in this column. The water table is located at 751.9 m at this column. 
4.1.7 Design Information 

Design information is specified in contrast to data resulting from measurements. Design 
information has evolved continuously as the THC seepage model has been developed, and 
current design-related parameters may vary slightly from the values used to generate the THC 
model output used by TSPA. Differences between the values used and currently accepted values 
are not expected to significantly affect model results because these results are primarily 
dependent on the initial water compositions, mineralogy, and applied heat load, and not on the 
specifics of in-drift engineered features. All direct input design parameters used in the THC 
model are summarized in Table 4.1-6, under the column Model Direct Inputs. Current values 
are also presented in the table, for corroborative or informational purposes only. The parameters 
used in the model vary little from the currently accepted values, and these inputs are adequate 
and justified for the intended use in this model. Some design parameters are from 
DTN: SN9908T0872799.004 [DIRS 108437]; because the calculations summarized in that DTN 
were not verified, this data, specifically, has been qualified for project use in Appendix I of this 
document. 

MDL-NBS-HS-000001 REV 04 4-14 February 2005 


Drift-Scale THC Seepage Model 

Two time periods are considered in the THC seepage model: 

 A 50-year preclosure period during which a large amount of the heat released by the 
waste packages is removed by ventilation (see below) 
 A postclosure period immediately following the initial 50-year preclosure period and 
extending to 100,000 years (the total simulation time), during which a drip shield is 
located above the waste packages and no heat is removed by ventilation. 
Accordingly, some of the drift-specific model-input design information is not the same for the 
preclosure and postclosure time periods. The model drift geometry and thermophysical 
properties of design elements are shown in Table 4.1-6 and Figure 4.1-1. This drift design 
information is the same as that used for Site Recommendation. However, an important 
difference from previous model revisions is that the drift is modeled here as open to both 
advective and diffusive fluxes of liquid and gas. As a result, hydrologic properties had to be 
assigned to open in-drift areas. These properties are included in Table 4.1-6. The discretization 
of the drift is consistent with the dimensions shown in Figure 4.1-1, within the limits imposed by 
the resolution of the model mesh. 

The drip shield is not explicitly modeled as a barrier to gas transport, but its thickness and 
thermal conductivity have been considered in the width and thermal properties, respectively, of 
the open zone between the waste package and drip shield during the postclosure period. This has 
no effect on predicted THC seepage model water compositions because the thermal conductivity 
of the in-drift open spaces is much greater than that of the host rock. Thus, heat loss and 
predicted temperatures are controlled by the host rock thermal properties, and in-drift 
components have no significant effect. In addition, because of the high permeability of the 
invert, and the relative ease with which gas-phase diffusion and equilibration occur, a pathway 
for equilibration of in-drift atmosphere above and below the drip shield exists through the invert, 
and little difference in gas-phase composition would be expected. 

The total (unventilated) heat load (Appendix D) in the model simulations was obtained from a 
historical repository design document (BSC 2002 [DIRS 159527]). The initial heat transfer from 
the waste package is 1.45 kW/m(drift), which decays to 0.593 kW/m after 50 years and to 0.0684 
W/m after 1,000 years. This is essentially the same heat load as the currently accepted values, as 
shown in D&E / PA/C IED Typical Waste Package Components Assembly (BSC 2004 
[DIRS 167369]). Currently, the initial heat transfer is 1.45 kW/m(drift), which decays to 

0.592 kW/m after 50 years and to 0.0677 W/m after 1,000 years. The effect of such minor 
differences in heat load (1 percent or less at all times) is not expected to be significant relative to 
that of the choice of initial water composition. Because the heat loads used vary little from the 
currently accepted values, these inputs are adequate and justified for the intended use in this 
model. 
MDL-NBS-HS-000001 REV 04 4-15 February 2005 


Drift-Scale THC Seepage Model 

Table 4.1-6. Drift and Committed Materials Model Parameters 

Parameter 
Model Direct Inputs(a) Current value(b) 
Source Value Value Source 
Drift spacing 800-IED-MGR0-00201-000-00B 
(BSC 2004 [DIRS 168489]) 
81 m 81 m 800-IED-MGR0-00201-000-00B 
(BSC 2004 [DIRS 168489]) 
Drift diameter 800-IED-MGR0-00201-000-00B 
(BSC 2004 [DIRS 168489]) 
5.5 m 5.5 m 800-IED-MGR0-00201-000-00B 
(BSC 2004 [DIRS 168489]) 
Waste package outer 
diameter 
800-IED-WIS0-00201-000-00E 
(BSC 2004 [DIRS 169480]) (for 
44-BWR waste package) 
1.67 m 
(rounded off from 
1.674 m) 
1.318 to 2.110 m 
(1.674 m for 
44-BWR WP) 
800-IED-WIS0-00201-000-00E 
(BSC 2004 [DIRS 169480]) 
Top of invert as measured 
from bottom of drift (invert 
thickness) 
800-IED-EBS0-00301-000-00A 
(BSC 2003 [DIRS 162444]) 
0.8 m 
(rounded off from 
0.806 m) 
0.864 m 800-SS0-SSE0-00102-000-00B 
(BSC 2004 [DIRS 169776]) 
Location of waste package 
center above bottom of drift 
DTN: SN9908T0872799.004 
[DIRS 108437](c) 
1.945 m 1.75 to 2.15 m 800-IED-MGR0-00201-000-00B (BSC 
2004 [DIRS 168489]) (center line of 
waste package height above invert) and 
800-SS0-SSE0-00102-000-00B (BSC 
2004 [DIRS 169776]) (invert thickness) 
Location of waste package 
center below the drift 
springline 
DTN: SN9908T0872799.004 
[DIRS 108437](c) 
0.805 m 0.6 to 1.0 m BSC 2004 [DIRS 168489] (drift 
diameter; center line of waste package 
height above invert) and BSC 2004 
[DIRS 169776] (invert thickness) 
Drip shield thickness DTN: SN9908T0872799.004 
[DIRS 108437](g) 
0.02 m 0.015 m BSC 2004 [DIRS 169220], Table 5 
Air gap between waste 
package surface and the 
inside of drip shield 
DTN: SN9908T0872799.004 
[DIRS 108437](c) 
0.396 m 0.367 to 1.132 m BSC 2004 [DIRS 168489], Figure 1 
Inside radius of drip shield DTN: SN9908T0872799.004 
[DIRS 108437](c) 
1.231 m 1.285 m BSC 2004 [DIRS 168283] 
Waste package thermal 
conductivity 
DTN: SN9908T0872799.004 
[DIRS 108437](c) 
14.42 W/m K 10.1 to 15.5 W/m* K 
for Alloy 22; 13.33 
to 17.83 W/m*K for 
316 stainless steel 
BSC 2001 [DIRS 156276], Table 5-11 
(Alloy 22, for temperature range of 48 to 
300C), Table 5-13 (316 stainless steel, 
temperature range of 22.11 to 
287.78C) 
Waste package density DTN: SN9908T0872799.004 
[DIRS 108437](c) 
8189.2 kg/m3 8690 kg/m3 DTN: MO0003RIB00071.000 
[DIRS 148850] 
Mass density of Alloy 22 

MDL-NBS-HS-000001 REV 04 4-16 February 2005 


Drift-Scale THC Seepage Model 

Table 4.1-6. Drift and Committed Materials Model Parameters (Continued) 

Parameter 
Model Direct Inputs(a) Current value(b) 
Source Value Value Source 
Waste package specific heat DTN: SN9908T0872799.004 
[DIRS 108437](c) 
488.86 J/kg K 378- 731 J/kg/K BSC 2004 [DIRS 169990] 
(homogeneous thermal properties for 
waste package internal cylinder) 
Invert intrinsic permeability DTN: SN9908T0872799.004 
[DIRS 108437](c) 
6.152  1010 m2 6.0  1010 m2 (3 
mm particle) (d) 
BSC 2003 [DIRS 170881], Section 6.4 
and Attachment XI 
Invert porosity DTN: SN9908T0872799.004 
[DIRS 108437](c) 
0.545 0.55 (d) BSC 2003 [DIRS 170881], Attachment 
XI 
Invert grain density DTN: SN9908T0872799.004 
[DIRS 108437](c) 
2,530 kg/m3 2530 kg/m3 (e) BSC 2003 [DIRS 170881], Attachment 
XI 
Invert specific heat DTN: SN9908T0872799.004 
[DIRS 108437](c) 
948 J/kg K 810 J/kg/K (f) DTN: GS000483351030.003 
[DIRS 152932] 
Invert thermal conductivity 
(upper invert) 
BSC 2002 [DIRS 159906], Table 6-48 
(100C data, average between ballast 
K = 0.1 and 0.2 W/m-K) 
1.52 W/m K Not in an IED Not Applicable 
Invert thermal conductivity 
(lower invert) 
DTN: GS000483351030.003 
[DIRS 152932] 
0.15 W/m K 
(value chosen based 
on 11 samples 
ranging from 0.14 to 
0.17) 
Not in an IED Not Applicable 
Open areas (linear capillary 
pressure and relative 
permeability functions) 
Permeability 
Residual saturation (drift 
wall/all other areas) 
Porosity 
Capillary pressure 
Model setup (Section 6.4.6, comment 
14) 
1  109 m2 
0.01 / 0.0 
1.0 
0.0 Pa 
Not in an IED Not Applicable 

MDL-NBS-HS-000001 REV 04 4-17 February 2005 


Table 4.1-6. Drift and Committed Materials Model Parameters (Continued) 

Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 4-18 
February 2005 

Parameter 
Model Direct Inputs(a) Current value(b) 
Source Value Value Source 
Heat load BSC 2002 [DIRS 159527] (Sheet 5) 1.45 kW/m (see text) 1.45 kW/m 800-IED-EBS0-00403-000-00B 
(BSC 2003 [DIRS 167369]) 
Heat removal by ventilation BSC 2002 [DIRS 160975], Table 6-6 86.3% 88% BSC 2004 [DIRS 169862], Table 8-2 
Invert capillarity (linear 
capillary pressure function) 
Set equal to 1/(Van Genuchten 
alpha), with alpha = 1.2  103 Pa1 
(rounded off from value in 
DTN: SN9908T0872799.004 
[DIRS 108437]) 
833 Pa 24 to 1517 Pa BSC 2003 [DIRS 170881] 
Invert residual saturation DTN: SN9908T0872799.004 
[DIRS 108437](c) 
0.1 0.19 (g) DTN: LB0208UZDSCPMI.002 
[DIRS 161243] 

(a) If a parameter value has not changed, the current source is given as direct input, rather than the original source. 
(b) If current values and direct input values differ (most cases), the current values are presented as corroborative data (indirect inputs). 
(c) Data from DTN: SN9908T0872799.004 [DIRS 108437] are qualified in Appendix I. 
(d) The porosity of the invert is calculated using measured data (from the sources cited) for grain density (2530 kg/m3) and bulk density (1150 kg/m3) of crushed 
tuff sieved between 2.00 to 4.75 mm. 
(e) The grain density of invert material is the measured (from the source cited) grain density of crushed tuff sieved between 2.00 and 4.75 mm. 
(f) The average specific heat (volumetric) of invert material for 11 samples (4-10 crushed tuff) listed in DTN: GS000483351030.003 [DIRS 152932] is 0.93 
J/cm3/C. Specific heat capacity (gravimetric) = volumetric heat capacity / bulk density. Bulk density = invert grain density * (1-porosity) = (2530 kg/m3) 
(1-0.545) = 1151 kg/m3 = 1.15 g/cm3. Thus specific heat capacity = (0.93 J/cm3/C) / 1.15 g/cm3 = 0.810 J/g/C = 810 J/Kg/C. 
(g) Residual saturation measured from rock core for the TSwM4 layer (Topopah Spring Tuff middle non-lithophysal unit). 

Drift-Scale THC Seepage Model 

Ventilation efficiency denotes the fraction of heat removed from the repository as a result of 
ventilation during the 50-year preclosure period. The ventilation efficiency value adopted in this 
report is 86.3 percent. This value was reported in an earlier version of Ventilation Analysis and 
Model Report (BSC 2002 [DIRS 160975], Table 6-6), which has subsequently been revised to 
address repository design changes and to replace calculations that utilized unqualified software. 
The ventilation efficiency of 86.3 percent, which was the best estimate available at the time that 
the majority of the analyses in this report were conducted, is qualified for use in this report by 
corroboration with the more recent, qualified data presented above (the data qualification plan is 
included in Appendix H of BSC 2004 [DIRS 170338]). The integrated ventilation efficiency 
provided by current YMP reports is 88 percent (BSC 2004 [DIRS 169862], Table 8-2) when the 
emplacement drift is 600 m in length. The standard deviation of the calculated ventilation 
efficiency is 3 percent (BSC 2004 [DIRS 169862], Table 8-2). Thus, the 1s range is 85 percent 
to 91 percent for a 600-m-long drift. The ventilation efficiency value used in this report falls 
within the 1s range of current values described above, and actually is similar to the mean 
ventilation efficiency of 86 percent for an 800-m-long emplacement drift (BSC 2004 
[DIRS 169862], Table 8-2). Also, the impact of the minor difference between adopted and 
best-estimate values of ventilation efficiencies on water compositions in the drift vicinity is 
expected to be much smaller than the range of variability due to use of differing starting water 
compositions. Thus, the choice of ventilation efficiency value is justified for its intended use in 
this report. 


Source: Table 4.1-6. 

Figure 4.1-1. Sketch Showing Modeled In-Drift Dimensions 

MDL-NBS-HS-000001 REV 04 4-19 February 2005 


Drift-Scale THC Seepage Model 

Heat transfer from the waste package to the drift wall is implemented in the model by using 
time-varying effective thermal conductivities (for open spaces within the drift) that have been 
calculated to account for radiative and convective heat transport. These time-varying variables 
are input into the model as coefficients (values between 0 and 1) for each open zone within the 
drift. Each zone is also assigned a constant maximum thermal conductivity (Kthmax), which is 
then multiplied by the corresponding time-varying coefficients to obtain effective conductivities 
as a function of time (DTN: SN0002T0872799.009 [DIRS 153364]; Appendix E). 

The effective thermal conductivities (Section 4.1.1.4) and corresponding open zones of the drift 
prior to closure are not the same as those following closure. Only one open space between the 
waste package and the drift wall is considered for the preclosure period. For postclosure, two 
zones are considered: (1) the open space between the waste package and the drip shield (Inner 
Zone, drip shield included) and (2) the open space between the drip shield and the drift wall 
(Outer Zone) (Figure 4.1-1). Kthmax values are listed in DTN: SN0002T0872799.009 
[DIRS 153364]. For preclosure, Kthmax = 10.568 W/m-K for the zone between the waste 
package and the drift wall. For postclosure, Kthmax = 2.298 W/m-K for the Inner Zone (between 
the waste package and the drip shield), and Kthmax = 14.407 W/m-K for the Outer Zone (between 
the drip shield and the drift wall). Accordingly, model runs are started with the preclosure 
thermal conductivities, then stopped after 50 years and restarted with the corresponding 
postclosure data. 

The invert is divided into two zones with different thermal conductivities: 1.52 W/m-K for the 
upper half and 0.15 W/m-K for the lower half (Table 4.1-6). When the model was implemented, 
the design value for the invert thickness was 0.806 m (BSC 2003 [DIRS 162444]). The current 
value is 0.864 m (2 feet-10 inches) (BSC 2004 [DIRS 169776]). This change is minor and 
would not be expected to generate any difference in model output. 

The implementation of the drift design in the model is further documented by Spycher (2001 
[DIRS 160898], LBNL Scientific Notebook SN-LBNL-SCI-141-V1, pp. 11 to 14, 116 to 129). 
A summary of the hydrologic and thermal properties of repository units used in the current 
model is given in Table 6.4-1. 

4.2 CRITERIA 
Technical requirements to be satisfied by performance assessment are based on 10 CFR 63.114 
[DIRS 156605]. These technical requirements are also identified in Project Requirements 
Document (Canori and Leitner 2003 [DIRS 166275], Section 3). The acceptance criteria that 
will be used by the U.S. Nuclear Regulatory Commission (NRC) to determine whether the 
technical requirements have been met are identified in Yucca Mountain Review Plan, Final 
Report (YMRP) (NRC 2003 [DIRS 163274]). The pertinent requirements and acceptance 
criteria for this report are summarized in Table 4.2-1. 

MDL-NBS-HS-000001 REV 04 4-20 February 2005 


Drift-Scale THC Seepage Model 

Table 4.2-1. Applicable Project Requirements and YMRP Acceptance Criteria 

Requirement 
Numbera Requirement Titlea 10 CFR 63 Link YMRP Acceptance Criteria 
PRD-002/T-015 Requirements for 
Performance Assessment 
10 CFR 
63.114(a)-(c) and 
(e)-(g) 
[DIRS 156605] 
Criteria 1 to 5 for Quantity and Chemistry of 
Water Contacting Engineered Barriers and 
Waste Forms 

a 

Canori and Leitner 2003 [DIRS 166275], Section 3. 

The acceptance criteria identified in Section 2.2.1.3.3.3 of the YMRP (NRC 2003 
[DIRS 163274]) are given below, followed by a short description of their applicability to this 
report: 

 Acceptance Criterion 1, System Description and Model Integration Are Adequate: 
The applicable subcriteria are: 

Subcriterion 1. This subcriterion requires that the total system performance assessment 
adequately incorporates important design features, physical phenomena, and couplings, 
and uses consistent and appropriate assumptions throughout the quantity and chemistry of 
water contacting waste packages and waste forms abstraction process. This subcriterion 
is addressed in Sections 6.2, 6.3, and 6.4. 

Subcriterion 2. This subcriterion requires that the abstraction of the quantity and 
chemistry of water contacting waste packages and waste forms uses assumptions, 
technical bases, data, and models that are appropriate and consistent with other related 

U.S. Department of Energy abstractions. Sections 5, 6, and 7 address this subcriterion 
regarding water chemistry. 
Subcriterion 3. This subcriterion requires that important design features, including waste 
package design and thermal loading strategy, are adequately defined to determine initial 
and boundary conditions for calculations of the quantity and chemistry of water 
contacting engineered barriers and waste forms. Design criteria used as model inputs are 
addressed in Section 4.1.7. 

Subcriterion 4. This subcriterion requires that spatial and temporal abstractions 
appropriately address physical couplings (thermal-hydrologic-mechanical-chemical). 
Sections 6.5.5.3 and 6.5.5.4 address this subcriterion. 

Subcriterion 5. This subcriterion requires that sufficient technical bases and justifications 
be provided for total system performance assessment assumptions and approximations for 
modeling coupled thermal-hydrologic-mechanical-chemical effects on seepage and flow, 
the waste package chemical environment, and the chemical environment for radionuclide 
release. This subcriterion also requires that the effects of distribution of flow on the 
amount of water contacting the waste packages and waste forms be consistently 
addressed in all relevant abstractions. This report addresses coupled THC effects on 

MDL-NBS-HS-000001 REV 04 4-21 February 2005 


Drift-Scale THC Seepage Model 

water chemistry and flow in the UZ up to the drift wall (Section 6). It therefore addresses 
parts of this subcriterion. 

Subcriterion 8. This subcriterion requires that adequate technical bases are provided, 
including activities such as independent modeling, laboratory or field data, or sensitivity 
studies, for inclusion of any thermal-hydrologic-mechanical-chemical couplings and 
features, events, and processes (FEPs). FEPs are addressed in Section 6.1, technical 
bases in Sections 6.2 to 6.4, modeling and sensitivity studies in Section 6.5 and in Section 
6.3, and modeling of field and laboratory experiments in Section 7.0, thus addressing this 
subcriterion. 

Subcriterion 9. This subcriterion requires that performance-affecting processes that have 
been observed in thermal-hydrologic tests and experiments are included in the 
performance assessment. Simulations presented in this report reproduce coupled THC 
effects observed in thermal test (Section 7.1) and laboratory experiments (Sections 7.2 
and 7.3) and, therefore, address this subcriterion. 

Subcriterion 10. This subcriterion requires that likely modes for container corrosion are 
identified and considered in determining the quantity and chemistry of water entering the 
engineered barriers and contacting waste forms. The geochemical system used in the 
THC seepage model includes chemical components needed as inputs for modeling the 
corrosion environment. This subcriterion is addressed in Section 6.2.2.2, where the 
geochemical system is described. 

Subcriterion 12. This subcriterion requires that peer review or data qualification be 
carried out following rigorous outlines. Peer review was not required for the analyses 
presented in this report. However, data collected prior to establishment of the current 
quality assurance program has been qualified (Section 4.0), as per LP-SIII.10Q-BSC, 
Models, and LP-SIII.2Q-BSC, Qualification of Unqualified Data, so this subcriterion has 
been addressed. 

Subcriteria 6 and 7 are not applicable because they deal with the chemistry of water that 
could exist in the emplacement drifts in contact with engineered materials (ground 
support or invert materials) and with the waste package. This model considers only 
chemistry of water as it may exist in the volume of rock in the near-field around the 
repository drifts. 

Subcriterion 11 is not applicable because the analyses presented in this report do not 
affect the evaluations of potential criticality. 

 Acceptance Criterion 2, Data Are Sufficient for Model Justification: 
The applicable subcriteria are: 

Subcriterion 1. This subcriterion requires that geological, hydrologic, and geochemical 
values used in the safety case are adequately justified, and that adequate descriptions of 
how data are used, interpreted, and appropriately synthesized into the parameters are 

MDL-NBS-HS-000001 REV 04 4-22 February 2005 


Drift-Scale THC Seepage Model 

provided. This subcriterion is addressed in Sections 4.1, 6.2 (and in particular 6.2.2), 6.3, 
and 6.4. 

Subcriterion 2. This subcriterion requires that sufficient data have been collected on the 
characteristics of the natural system and engineered materials to establish initial and 
boundary conditions for conceptual models of thermal-hydrologic-chemical coupled 
processes that affect seepage and flow and the waste package chemical environment. 
This report addresses parts of this subcriterion by considering variations in pore-water 
compositions (Sections 6.2.2 and 6.5.5) and rock properties (Sections 6.3 and 6.5) 
representative of the natural system. 

Subcriterion 3. This subcriterion requires that thermal-hydrologic tests have been 
designed and conducted with the explicit objectives of observing thermal-hydrologic 
processes for the temperature ranges expected for repository conditions and making 
measurements for mathematical models. This subcriteria also requires that data are 
sufficient to verify that thermal-hydrologic conceptual models address important 
thermal-hydrologic phenomena. Section 7.1, which presents details on results of the 
Drift Scale Test and simulations reproducing results of this test, addresses this 
subcriterion. 

Subcriterion 4. This subcriterion requires that sufficient information to formulate the 
conceptual approach(es) for analyzing water contact with the drip shield, engineered 
barriers, and waste forms be provided. Because this report determines water 
compositions in the host rock surrounding the drifts, which are passed to Engineered 
Barrier System: Physical and Chemical Environment Model (BSC 2004 DIRS 169860]) 
as potential seepage entering the drifts (Section 6.5.5), this subcriterion is addressed. 

Subcriterion 5 is not applicable because it deals with the effects of microbial activity on 
the chemistry of water that could exist in the repository emplacement drifts. This model 
considers only chemistry of water as it may exist in the volume of rock in the near-field 
around the repository drifts. 

 Acceptance Criterion 3, Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction: 
Subcriterion 1. This subcriterion requires that models use parameter values, assumed 
ranges, probability distributions, and/or bounding assumptions that are technically 
defensible and that reasonably account for uncertainties and variabilities. This 
subcriterion is addressed by using ranges of input data (Section 6.2.2, pore-water 
composition) and alternative conceptualizations of the modeled systems (Section 6.3) to 
model uncertainty, also discussed in Section 6.6. 

Subcriterion 2. This subcriterion requires that parameter values, assumed ranges, 
probability distributions, and bounding assumptions used in the calculations of quantity 
and chemistry of water contacting waste packages and waste forms are technically 
defensible and reasonable, based on data from the Yucca Mountain region (i.e., DST), 
and a combination of techniques that include laboratory experiments and field 

MDL-NBS-HS-000001 REV 04 4-23 February 2005 


Drift-Scale THC Seepage Model 

measurements and process-level modeling studies. This report addresses the parts of this 
subcriterion that relate to the uncertainty of the chemistry of water that could potentially 
enter drifts, with inputs and results discussed in Sections 6.2.2, 6.5.5, and 6.6 and 
validation, including the results of the DST and laboratory experiments, presented in 
Section 7. 

Subcriterion 3. This subcriterion requires that input values used in the TSPA calculations 
of quantity and chemistry of water contacting engineered barriers (e.g., drip shield and 
waste package) are consistent with the initial and boundary conditions and the 
assumptions of the conceptual models and design concepts for the Yucca Mountain site. 
This criterion also requires that correlations between input values are appropriately 
established in the U.S. Department of Energy TSPA; that parameters used to define initial 
conditions, boundary conditions, and computational domain in sensitivity analyses 
involving coupled thermal-hydrologic-mechanical-chemical effects on seepage and flow, 
the waste package chemical environment, and the chemical environment for radionuclide 
release, are consistent with available data; and that reasonable or conservative ranges of 
parameters or function relations are established. This subcriterion is addressed with 
respect to the chemistry of water that could potentially enter drifts, with the conceptual 
models described in Sections 6.3 to 6.4, initial and boundary conditions discussed in 
Sections 6.5.2 and 6.3, and ranges of input parameters presented in Sections 6.5.3 and 

6.3. 

Subcriterion 4. This subcriterion requires that adequate representation of uncertainties in 
the characteristics of the natural system and engineered materials be provided in 
parameter development for conceptual models, process-level models, and alternative 
conceptual models. This subcriterion also states that the U.S. Department of Energy 
may constrain these uncertainties using sensitivity analyses or conservative limits. This 
subcriterion is addressed by considering ranges of input parameters and alternative 
conceptualizations (Table 6-1 and Sections 6.2.2 and 6.3), as well as evaluations of the 
spread of model results (Section 6.6). 

Subcriterion 5 is not applicable because the analyses presented in this report do not affect 
the evaluations of potential criticality. 

Subcriterion 6 is not applicable because sufficient data were available in project sources 
such that expert elicitation was not required. 

 Acceptance Criterion 4, Model Uncertainty Is Characterized and Propagated Through the 
Model Abstraction: 
Subcriterion 1. This subcriterion requires that alternative modeling approaches of FEPs, 
consistent with available data and current scientific understanding, are investigated. This 
subcriterion also requires that the results and limitations are appropriately considered in 
the abstraction. This subcriterion is addressed by reviewing FEPs (Section 6.1), by using 
alternative conceptual models (Section 6.3), and evaluating model limitation and 
uncertainty (Sections 1.3, 6.6, and 8.4). 

MDL-NBS-HS-000001 REV 04 4-24 February 2005 


Drift-Scale THC Seepage Model 

Subcriterion 2. This subcriterion requires that alternative modeling approaches are 
considered and the selected modeling approach is consistent with available data and 
current scientific understanding, and the results and limitations and uncertainties of the 
chosen model are provided. This subcriterion is addressed by considering various model 
conceptualizations (Section 6.3), evaluating spread in model results (Section 6.5.5), and 
reporting on limitations and uncertainties (Section 1.3, 6.6, and 8.4). 

Subcriterion 3. This subcriterion requires that consideration of conceptual model 
uncertainty is consistent with available site characterization data, laboratory experiments, 
field measurements, natural analogue information and process-level modeling studies; 
and that the treatment of conceptual model uncertainty does not result in an 
under-representation of the risk estimate. This subcriterion is addressed by using 
site-specific data (Section 4.1), as well as data from field and laboratory experiments 
(Section 7), and considering ranges of key input parameters (e.g. Section 6.2.2), 
alternative conceptualizations (Section 6.3), and spread in model results (Section 6.6). 

Subcriterion 4. This subcriterion requires that adequate consideration is given to effects 
of thermal-hydrologic-mechanical-chemical coupled processes in the assessment of 
alternative conceptual models. These effects may include: (a) thermal-hydrologic effects 
on gas, water, and mineral chemistry; (b) effects of microbial processes on the waste 
package chemical environment for radionuclide release; (c) changes in water chemistry 
that may result from the release of corrosion products from the waste package and 
interactions between engineered materials and groundwater; and (d) changes in boundary 
conditions (e.g., drift shape and size) and hydrologic properties, relating to the response 
of the geomechanical system to thermal loading. This report addresses part (a) of this 
subcriterion through conceptual and mathematical models described in Sections 6.2 and 
6.4, and model results presented in Section 6.5.5 and Section 6.3. 

Subcriterion 5 is not applicable for this model because it does not contain a model for the 
total system performance assessment, nor does it make estimates that assess calculated 
compliance. 

 Acceptance Criterion 5, Model Abstraction Output is Supported by Objective Comparisons: 
Subcriterion 3. This subcriterion requires that accepted and well-documented procedures 
are used to construct and test the numerical models that simulate coupled thermal-
hydrologic-mechanical-chemical effects on seepage and flow, engineered barrier 
chemical environment, and the chemical environment for radionuclide release. It also 
requires that analytical and numerical models are appropriately supported, and that 
abstracted results are compared with different mathematical models, to judge robustness 
of results. This report addresses this subcriterion through conceptual and mathematical 
models described in Sections 6.2 and 6.4, and through evaluation of alternative 
conceptual models in Section 6.3. 

Subcriteria 1 and 2 pertain to model abstraction results, and are not applicable to this 
model because the THC seepage model abstraction is done in the downstream report 
Post-Processing Analysis for THC Seepage (BSC 2004 [DIRS 169858]). 

MDL-NBS-HS-000001 REV 04 4-25 February 2005 


Drift-Scale THC Seepage Model 

Additional criteria are identified in the TWP (BSC 2005 [DIRS 172761]). Representativeness of 
model outputs is discussed in Section 6.2.2.1 of the report. The selection of input water 
compositions from various repository-level lithostratigraphic units has been made to encompass 
the natural variability in extant pore water compositions. In this way, the model results are 
sufficiently representative for locations throughout the repository footprint. Uncertainties in 
output parameters passed to down-stream users of the THC seepage model are discussed in 
Section 6.6. Boundary conditions used in the THC seepage model are established in other 
process model documents and in IEDs, and are presented and justified for intended use in 
Section 4.1. The report also addresses the following Condition Reports: 

 CR79Recategorization of Technical Information citations in DIRS. 
 CR99Model validation. 
 CR168Qualification status of the data0.ymp.R2 database. 
 CR821Ensure that adequate justification is given for use of any data formerly 
classified as Technical Information. 
 CR938Ensure that assumptions have sufficient basis, and do not require additional 
confirmation or future work. 
 CR1805Verify that software is adequate for its intended use and used within its range 
of validation. 
 CR1821Ensure that material included on model report Errata Sheets undergoes the 
same reviews as the rest of the model report. 
 CR2049The criteria used to establish the adequacy of the scientific basis for the model 
and to demonstrate that the model is sufficiently accurate for its intended use must be 
consistent with parameter uncertainties and justified in the documentation. 
 CR2050Validate the model to the required level of confidence. 
 CR2104Incorporate errata into the model report. 
4.3 CODES, STANDARDS, AND REGULATIONS 
No specific, formally established codes, standards, or regulations, other than those discussed in 
Section 4.2, have been identified as applying to this modeling activity. 

MDL-NBS-HS-000001 REV 04 4-26 February 2005 


Drift-Scale THC Seepage Model 

5. ASSUMPTIONS 
Development of methodology for the numerical modeling of heat and fluid flow in unsaturated 
fractured porous media, calculation of mineralwater reactions, and transport of aqueous and 
gaseous species are discussed in Section 6. Many simplifications and approximations underlie 
this methodology, yet other simplifications and approximations are inherent in data that describe 
repository designs and associated parameters on which model simulations rely. In this section, 
only cases in which an assumption is made where there is an absence of data or information for 
the parameter or concept are described. These are listed below. Approximations and 
simplifications related to the development and implementation of the mathematical model 
applied for this study are presented as part of the model documentation in Section 6.4.6. 

1. The THC model results, calculated for a repository in the Tptpll lithologic unit, are 
applicable to all lithologies intersected by the repository driftsAnalysis and results of 
this model are assumed to apply across the lithology of the entire repository drift, although 
the current THC seepage model results only provide output from the Tptpll lithologic unit. 
This assumption has several bases: 
 Model simulations carried out in a previous revision of this report (Section 6.3) were run 
in both the Tptpmn and Tptpll lithologic units, and showed that the lithology had little 
effect on predicted water chemistries. Although the Tptpmn simulations have not been 
repeated with the current THC model, which uses different input parameters and differs 
conceptually in some ways from the earlier model, these developmental simulations 
provide confidence that the current model results are applicable over the stratigraphic 
section intersected by the repository. 
 The repository horizon within the Topopah Spring Tuff (including the Tptpln, Tptpll, 
Tptpmn, and Tptpul units) is relatively uniform in composition. Peterman and Cloke 
(2002 [DIRS 162576]) analyzed twenty core samples, in duplicate, from the cross-drift 
within the four lithologic units constituting the repository level. All samples were 
compositionally similar with respect to major oxides and trace elements (Peterman and 
Cloke 2002 [DIRS 162576], Table 4), and normative mineral compositions (Peterman 
and Cloke 2002 [DIRS 162576], Figure 4, Table 5, p. 692). Samples vary by only 2 
percent in SiO2 concentration, and plot as a tight cluster in the rhyolite field on the 
chemical rock classification diagram for igneous rocks (SiO2 plotted against 
Na2O + K2O) (Peterman and Cloke 2002 [DIRS 162576], Figure 3, Table 4, p. 687). The 
tight clustering also indicates that the effect of localized mineral heterogeneity on 
large-scale rock compositions, due to the presence of minerals that precipitated from the 
vapor phase during cooling of the tuff, and low-temperature minerals, such as calcite and 
amorphous SiO2 (opal), is likely very small (Peterman and Cloke 2002 [DIRS 162576], 
pp. 695 to 696). 
 The five starting waters used in the current THC seepage model simulations have been 
chosen to represent the entire range of available pore water compositions, and include 
pore waters from three of the four repository-level lithologic units (Tptpll, Tptpmn, and 
Tptpul) (Section 6.2.2.1). 
MDL-NBS-HS-000001 REV 04 5-1 February 2005 


Drift-Scale THC Seepage Model 

2. THC model runs using the five starting waters adequately represent all possible seepage 
watersThe five starting waters (Section 6.2.2.1) have been chosen from available 
measured pore water compositions for repository-level lithologic units. These waters are 
plotted on Figure 6.2-4, and cover the spread of measured compositions. However, pore 
water samples are not available from all possible locations in the repository, and available 
data are assumed to be representative of all water chemistries actually present in the 
repository units. This assumption is supported in part by the chemical similarity of the four 
TSw lithostratigraphic units that will host the repository, as described in the previous 
assumption. Reaction with these rocks should homogenize many reactive mineral species 
and make large variations in the concentrations of nonconservative aqueous species (i.e., 
those that are unreactive and nonvolatile) from any single unit unlikely. This assumption is 
borne out by the available data (Figure 6.2-4); when the five starting waters were originally 
chosen, only about half the data were available (BSC 2004 [DIRS 168848], Figure 6.2-4). 
Pore water samples collected more recently fall within the range of the previous data and 
cluster in a similar fashion. 
Additional support that these five waters adequately represent the range of pore water 
compositions is presented in Engineered Barrier System: Physical and Chemical 
Environment (BSC 2004 [DIRS 169860], Section 7.2.3). There, an evaluation of 38 different 
pore waters shows that, upon evaporation, they cluster similarly with respect to composition, 
and nearly in the same proportion, as the five pore waters used as THC simulation starting 
waters. 

3. Water compositions in the fractures and matrix are identical, and the same water is 
present in all hydrogeologic unitsThe infiltrating water and initial fracture water 
chemical compositions are set to be the same as the initial matrix pore-water compositions, 
with minor adjustments for temperature and Pco2 at the upper boundary of the model. The 
basis for this assumption is that the pore waters must, at any given point in time, constitute 
the vast majority of the water in the rock column, because the total matrix porosity is much 
greater than the fracture porosity. Also, it is clear from model results that water-rock 
interactions blend out the effect of varying starting water compositions to a significant degree 
by controlling the concentrations of reactive species (Section 6.6). 
Also, the same initial water compositions are used in all hydrogeologic units. This model 
simplification is justified because the THC model provides, as output, near-field water 
compositions, derived from grid blocks within 10 m of the drift center (water compositions 
from greater distances are of no interest). Also, since some thermodynamic and kinetic 
data, and initial concentrations, were adjusted so that ambient near-field pore water 
compositions are stable over time (e.g., are stable over ambient steady-state flow 
conditions), the effects of far-field water-rock interactions and changes in pore water 
compositions have been effectively eliminated. 

4. Aqueous species are unreactive at solution concentrations greater than 4 molalUpon 
boiling or evaporation, the aqueous phase is treated as unreactive and is not concentrated 
further, once its ionic strength reaches an input upper limit of 4 or if the liquid saturation 
drops below an input lower limit of 104 to 105. This ensures that the calculated ionic 
strength does not exceed the range of applicability of the activity coefficient model used 
MDL-NBS-HS-000001 REV 04 5-2 February 2005 


Drift-Scale THC Seepage Model 

(Section 6.4.1). Thus, reaction of aqueous components in concentrated (ionic strength 
greater than 4 molal) solutions does not occur. Transport is neglected if the liquid saturation 
drops below an input lower limit of 105, which is also below the residual saturation, but 
takes place at all values of the ionic strength. At liquid saturations this low, the total amount 
of dissolved mass present in any given model grid block is exceedingly small. Thus, 
ignoring chemical reaction for such small mass amounts (and over a limited time period) 
does not significantly affect the general computed trends of aqueous phase concentrations 
and precipitated mineral amounts over long periods of time and a wide range of liquid 
saturations. The salt phases that are formed during dryout are described in Section 6.4.5. 
These phases are available for dissolution upon rewetting (using a relatively fast dissolution 
rate of 106 mol s1 kgH2O1). 

5. Axial transport effects would not significantly impact THC Seepage Model resultsThe 
THC seepage model is a two-dimensional slice through an emplacement drift at the center of 
the repository. Transport of heat and mass (liquid/vapor) in the third dimension, paralleling 
the drift, are not incorporated into the model. The effect of such transport on water chemistry 
is assumed to be negligible. Confidence in this assumption is gained by comparing the 
two-dimensional THC model results (with water-rock interactions turned off) and the 
three-dimensional MSTHM results (BSC 2004 [DIRS 169565], Section 6.3) for a 
repository-center location. The two models predict similar drift-wall temperatures for given 
waste package temperatures. The maximum waste package and drift wall temperatures from 
the THC seepage model are around 164C and 141C, respectively (Figure 6.5-4). The 
MSTHM, for a similar mean infiltration case, predicts a drift-wall temperature around 139C 
for the same waste package temperature (around 164C) (BSC 2004 [DIRS 169565], 
Figure 6.3-2). 
6. In the event of complete drift collapse, the composition of potential seepage is assumed 
to be the same as seepage for uncollapsed driftsIn the low-probability-seismic 
collapsed-drift scenario, the drift opening collapses, and the resulting host-rock rubble 
completely fills the modified drift opening, from the outer surface of the drip shield out to the 
modified drift wall. It is assumed that drift collapse will have no effect on potential 
seepage water compositions. Thermal-hydrologic simulation results for a complete 
drift-collapse scenario are presented in Multiscale Thermohydrologic Model (BSC 2004 
[DIRS 169565], Section 6.3.7), and show that the main effect of the rubble is to thermally 
insulate the waste package, resulting in higher temperatures and extended boiling duration in 
the drift (relative to the no-collapse scenario). The effect of drift collapse on potential 
seepage compositions was evaluated in the now-historic Abstraction of Drift-Scale Coupled 
Processes (BSC 2004 [DIRS 169617], Section 6.3). Simulation results confirmed that the 
maximum waste package temperature increased, but also showed that water is diverted 
around the rubble zone, which extends to a radius of 11 m from drift center, due to capillary 
effects, such that the wetting front and high-saturation zones in the rock actually occur 
further from drift-center, and at lower temperatures (BSC 2004 [DIRS 169617], Section 
6.3.5.2). Because it is waters at these locations that are sampled by the THC seepage model 
and passed to downstream models (see Section 6.5.5.2), and because lower temperature 
seepage waters are less corrosive than higher temperature waters (BSC 2004 [DIRS 169860], 
Section 6.13), this assumption is justified because it is conservative with respect to corrosion 
and radionuclide release. 
MDL-NBS-HS-000001 REV 04 5-3 February 2005 


Drift-Scale THC Seepage Model 

INTENTIONALLY LEFT BLANK 


MDL-NBS-HS-000001 REV 04 5-4 February 2005 


Drift-Scale THC Seepage Model 

6. MODEL DISCUSSION 
This section presents the conceptual and mathematical models implemented for the development 
of the drift-scale THC seepage model. Relevant FEPs are also briefly discussed in Section 6.1. 
Details on the conceptualization and mathematical treatment of the various coupled processes 
considered in the THC seepage model follow in Sections 6.2 through 6.4. The results of the 
THC seepage model are presented in Section 6.5, where coupled THC processes are evaluated 
for 100,000 years under boundary conditions that are varied to represent the effects of potential 
climatic change, two repository host units, various input water compositions, and other 
alternative model conceptualizations. Simulations are carried to 100,000 years to capture the 
entire duration of the thermal pulse and the return to ambient conditions. Model uncertainty, and 
the propagation of that uncertainty to downstream models, is discussed in Section 6.6. The 
validation of the THC seepage model is presented in Section 7. The model validation consists of 
simulating the water, gas, and mineral evolution in the Drift Scale Test using the DST THC 
submodel (Section 7.1) and laboratory water-rock interaction experiments (Sections 7.2 and 7.3). 
The laboratory experiments are used to compare simulated and measured water compositions 
evolved during interaction with crushed tuff and mineral precipitation patterns in a fracture 
where boiling and reflux are taking place. These validation simulations were run using a 
previous revision of the model with different model inputs, but they rely on the same 
conceptualizations and mathematical formulations presented in the current model, and provide 
additional confidence in the model. 

The development of the THC seepage model is summarized in Table 6-1, which includes 
changes between model revisions and a summary of the various conceptualizations and 
sensitivities that have been considered over the course of model development. 

Table 6-1. Summary of the Development of the THC Seepage Model 

Tptpmn THC Model 
(REV01) 
Tptpmn THC 
Heterogeneous 
Model (REV01) 
Tptpll THC Model 
(REV01) 
THC Seepage Model 
(Current Report 
Revision; Tptpll 
Unit) 
Chronological order of 
model development 1 2 3 4 
Information provided by 
this model 
Compare with the 
Tptpll model 
(REV01) to evaluate 
the effect of host 
hydrogeologic unit 
and stratigraphic 
location 
Compare with the 
homogenous 
Tptpmn model 
(REV01) to evaluate 
the effect of fracture 
permeability 
heterogeneity 
Compare with the 
Tptpmn model 
(REV01) to evaluate 
the effect of host 
hydrogeologic unit 
and stratigraphic 
location 
Provides feeds to 
downstream models 
(and indirectly to 
TSPA) and evaluates 
sensitivities to 
various model 
parameters and 
conceptualizations 
TOUGHREACT version 2.3 2.3 2.3 3.0 
Model dimensions: 
Thermal loading 
Ambient conditions 
(baseline) 
Two-dimensional 
Two-dimensional 
(with drift) 
Two-dimensional 
Two-dimensional 
(with drift) 
Two-dimensional 
Two-dimensional 
(with drift) 
Two-dimensional 
One-dimensional (no 
drift) 
Stratigraphic column 
location SD-9 SD-9 Center of repository Center of repository 
Host lithostratigraphic 
unit Tptpmn Tptpmn Tptpll Tptpll 

MDL-NBS-HS-000001 REV 04 6-1 February 2005 


Drift-Scale THC Seepage Model 

Table 6-1. Summary of the Development of the THC Seepage Model (Continued) 

Tptpmn THC Model 
(REV01) 
Tptpmn THC 
Heterogeneous 
Model (REV01) 
Tptpll THC Model 
(REV01) 
THC Seepage Model 
(Current Report 
Revision; Tptpll 
Unit) 
Heterogeneous 
permeability No Yes No No 
Geochemical system 
(Table 6.2-2 for the current 
Extended geochemical 
system) 
Basea 
Extendedb 
Basea 
Extendedb 
Basea 
Extendedb Extended 
Input pore water 
composition (Table 6.2-1) ESF Alcove 5 ESF Alcove 5 ESF Alcove 5 
ESF Alcove 5 
ECRB, 500 m 
ECRB, 1000 m 
ECRB, 2000 m 
SD-9, 990 ft 
Infiltration rates (mm/yr) Stepped up 6, 16, 25 Stepped up 6, 16, 25 Stepped up 6, 16, 25 
Stepped up 6, 16, 25 
Constant 6 (sensitivity) 
Constant 25 
(sensitivity) 
Heat Load (kW/m) 1.45 1.45 1.45 1.45 
Ventilation Period (yr) 50 50 50 50 
Ventilation efficiency 
(% heat removal) 70 70 70 86.3 
Drift wall conceptualization Closed 
to advective fluid flow 
Closed 
to advective fluid flow 
Closed 
to advective fluid flow Open 
Invert thickness 0.6 0.6 0.8 0.8 
Vapor-pressure lowering 
due to capillary pressure No No No Yes 
No (sensitivity) 
CO2 diffusion coefficient 
change None None None Six-fold increase 
No change (sensitivity) 
Improved treatment of 
mineral precipitation at 
boiling front 
No No No Yes 
Chronological changes in 
Mineralogy (Table 6.2-2 
and Appendix A for current 
values) 
Initial dataa No change 
Added fluorite and opal 
as primary minerals in 
host rock 
Added sepiolite and 
removed goethite as 
possible secondary 
minerals 
Main chronological 
changes in thermal 
properties (Table 6.4-1 for 
current values) 
Initial dataa No change 
In Tptpll versus 
Tptpmn: 23% and 
13% decrease in 
effective Kdry and Kwet, 
respectively 
For Tptpll, 6% increase 
in Kdry and 6% 
decrease in Kwet 
(effective values) 
Main chronological 
changes in hydrologic 
properties (Table 6.4-1for 
current values) 
Initial dataa 
In Tptpmn fractures: 
heterogeneous, 4order-
of-magnitude 
spread in fracture 
permeabilities in 
Tptpmn (3 different 
realizations) 
In Tptpll versus 
Tptpmn fractures: six 
times higher 
permeability, 80% 
increase in porosity, 
and six times higher 
capillarity (1/alpha) 
In Tptpll fractures: 
62% decrease in 
permeability, 47% 
decrease in porosity 
and 20% decrease in 
capillarity (1/alpha) 

a 

See BSC 2004 [DIRS 168848], Table 6.2-2, for a summary of these values. 

b The REV01 Extended geochemical system varies slightly from the current (BSC 2004 [DIRS 168848], 
Table 6.2-2). 

NOTE: Sources of model input data and technical information shown here are discussed in Section 4. 

MDL-NBS-HS-000001 REV 04 6-2 February 2005 


Drift-Scale THC Seepage Model 

The results of developmental (REV01) models will be discussed in context throughout Section 6 
as alternative model conceptualizations (Section 6.3) and sources of information on model 
sensitivities and uncertainties (Section 6.6). The current THC model implements many 
improvements relative to these early models, including updated model input parameters, a 
change in the drift wall conceptualization (open versus closed), and a more accurate treatment of 
mineral precipitation at the boiling front (Section 6.4.5). Results of the current simulations are 
presented in Section 6.5, including model results for various input water compositions, 
infiltration rates, and two boiling/evaporation conceptual models, (including/excluding 
vapor-pressure lowering caused by capillary pressure). Simulations of ambient conditions using 
various sources of thermodynamic data are also presented in Section 6.5.5.5 as a means of 
justifying the thermodynamic data (Section 4) used in the model. 

Product output from the THC seepage model is analyzed in Post-Processing Analysis for THC 
Seepage (BSC 2004 [DIRS 169858]), for use in downstream models in the in-drift chemical 
environment (BSC 2004 [DIRS 169860], Section 4.1), which directly feed the TSPA-LA. 

6.1 RELEVANT FEATURES, EVENTS, AND PROCESSES 
The results of this model abstraction are part of the basis for the treatment of features, events, 
and processes (FEPs) as discussed in Technical Work Plan for: Near-Field Environment and 
Transport: Coupled Processes (Mountain-Scale TH/THC/THM, Drift-Scale THC Seepage, and 
Post-Processing Analysis for THC Seepage) Report Integration (BSC 2005 [DIRS 172761], 
Section 2.1.5). FEPs that are relevant to the subject matter of this report and that are included in 
TSPA-LA are summarized in Table 6.1-1. Relevant FEPS that are excluded from TSPA-LA are 
listed in Table 6.1-2. In variance to the TWP, three FEPS (2.2.10.01.0A, 2.2.10.06.0A, and 
2.2.11.02.0A) have been added to the list of excluded FEPS in Table 6.1-2. 

These FEPS have been taken from the LA FEP list (DTN: MO0407SEPFEPLA.000 
[DIRS 170760]). Each FEP is cross-referenced to the relevant section (or sections) in this report 
in Table 6.1-1. The discussions provided in this and other model and abstraction reports form 
the technical basis for evaluating these FEPs for TSPA-LA. 

Table 6.1-1. Relevant Features, Events, and Processes Included in TSPA-LA 

LA FEP Number FEP Name 
Sections Discussing 
FEPs-Related Items 
1.1.02.02.0A Preclosure ventilation 4.1.7 
1.2.02.01.0A Fractures 4.1.1 
6.2.1 
6.4.3 
6.4.4 
Tables 4.1-4, 6.4-1 
1.3.01.00.0A Climate change 4.1.1.2 
6.2.1.3 
6.5.2 
Table 4.1-2 
1.4.01.01.0A Climate modification increases recharge 4.1.1.2 
6.2.1.3 
6.5.2 

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Drift-Scale THC Seepage Model 

Table 6.1-1. Relevant Features, Events, and Processes Included in TSPA-LA (Continued) 

LA FEP Number FEP Name 
Sections Discussing 
FEPs-Related Items 
2.1.08.01.0A Water influx at the repository 6.5.2 (climate) 
6.5.5.1 (climate) 
6.5.5.2 (reflux) 
8.2 
2.2.03.01.0A Stratigraphy 4.1.1 
4.1.6 
6.5.1 
Table 4.1-5 
2.2.03.02.0A Rock properties of host rock and other units 4.1.1 
4.1.2 
6.2.1 
6.3 
6.4.4 
6.4.6 
6.5.5.5 
Tables 6.4-1, 6.5-7 
2.2.07.02.0A Unsaturated groundwater flow in the geosphere 6.2.1 
6.5.5.3 
2.2.07.04.0A Focusing of unsaturated flow (fingers, weeps) 6.2.1 
6.3 
8.2 
2.2.07.08.0A Fracture flow in the UZ 6.2.1 
6.4.3 
6.4.4 
8.2 
2.2.07.09.0A Matrix imbibition in the UZ 6.2.1 
2.2.07.10.0A Condensation zone forms around drifts 6.2.1 
6.5.5.3 
2.2.07.11.0A Resaturation of geosphere dryout zone 6.2.1 
6.5.5.1 
6.5.5.2 
6.5.5.3 
8.2 
2.2.07.20.0A Flow diversion around repository drifts 6.2.1 
6.5.5.1 
6.5.5.3 
8.2 
2.2.08.01.0B Chemical characteristics of groundwater in the UZ 4.1.5 
6.2.2 
6.5.5.2 
Table 4.1-4 
2.2.08.04.0A Redissolution of precipitates directs more corrosive 
fluids to containers 
6.4.5 
6.5.5.2 
8.2 
2.2.08.12.0A Chemistry of water flowing into the drift 4.1.5 
6.2.1.2 
6.2.2 
6.5.5.2 
8.2 
Table 4.1-4 
2.2.10.03.0B Natural geothermal effects on flow in the UZ 6.5.2 
2.2.10.10.0A Two-phase buoyant flow/heat pipes 6.2.1 

Source: DTN: MO0407SEPFEPLA.000 [DIRS 170760]. 

MDL-NBS-HS-000001 REV 04 6-4 February 2005 


Drift-Scale THC Seepage Model 

Table 6.1-2. Relevant Features, Events, and Processes Excluded from TSPA-LA 

LA FEP Number FEP Name 
Sections Discussing 
FEPs-Related Items 
2.2.10.12.0A Geosphere dry-out due to waste heat 6.2.1 
6.5.5.1 
8.2 
2.1.09.12.0A Rind (chemically altered zone) forms in the near-field 6.2.1 
6.4.4 
6.4.5 
6.5.5.3 
2.2.08.03.0B Geochemical interactions and evolution in the UZ 4.1.3 
4.1.4 
6.2.2 
6.4.4 
6.4.5 
6.5.5.2 
6.5.5.3 
Table 4.1-3 
2.2.10.01.0A Repository induced thermal effects on flow in the UZ 6.5.5.3 
2.2.10.06.0A Thermo-chemical alteration in the UZ (solubility, 
speciation, phase changes, precipitation/dissolution) 
6.2.2.1 
6.5.5.2 
6.5.5.3 
2.2.11.02.0A Gas effects in the UZ 6.5.5.2 
6.5.5.3 

Source: DTN: MO0407SEPFEPLA.000 [DIRS 170760]. 

6.2 CONCEPTUAL MODEL 
This section describes the conceptual model underlying the drift-scale THC seepage model. The 
THC seepage model conceptualization is presented below in several parts. The first part deals 
with the conceptualization of the coupled processes that need to be taken into account to model 
watergasrock interactions in a heated unsaturated and fractured rock environment. In the 
second part, the conceptualization of the chemical system is presented and a rationale is laid out 
for selecting input water compositions, mineral phases, and chemical constituents included 
within the model. Finally, the conceptualization of the physical domain being modeled is 
discussed. 

6.2.1 Conceptualization of Coupled THC Processes 
The THC conceptual model underlies the numerical simulations of THC processes in the DST 
THC submodel and THC seepage model. The TH conceptual model must be able to describe 
processes involving liquid and vapor flow, heat transport, and thermal effects resulting from 
boiling and condensation. The THC conceptual model must treat the transport of aqueous and 
gaseous species, mineralogical characteristics and changes, and aqueous and gaseous chemistry. 
A conceptual model of reaction-transport processes in the fractured welded tuffs of the 
repository host rock must also account for different rates of transport in highly permeable 
fractures compared to the much less permeable rock matrix (Steefel and Lichtner 1998 
[DIRS 144878], pp. 186 and 187). 

MDL-NBS-HS-000001 REV 04 6-5 February 2005 


Drift-Scale THC Seepage Model 

In addition to the unsaturated hydrologic properties required to simulate THC processes in the 
UZ, the data necessary for the evaluation of THC processes include the initial and boundary 
water and gas chemistry, initial mineralogy, mineral volume fractions, reactive surface areas, 
equilibrium thermodynamic data for minerals, aqueous and gaseous species, kinetic data for 
mineralwater reactions, and diffusion coefficients for aqueous and gaseous species. The 
following subsections describe the conceptual model for thermal-hydrologic (TH), geochemical, 
and coupled THC processes in the fractured tuffs. 

6.2.1.1 TH Processes 
TH processes in the fractured welded tuffs at Yucca Mountain have been examined theoretically 
and experimentally since the early 1980s (Pruess et al. 1984 [DIRS 144801]; Pruess et al. 1990 
[DIRS 100818]; Buscheck and Nitao 1993 [DIRS 100617]; Pruess 1997 [DIRS 144794]; Tsang 
and Birkholzer 1999 [DIRS 137577]; Kneafsey and Pruess 1998 [DIRS 145636]). A conceptual 
model showing the important TH processes occurring around a drift (as derived through these 
studies and through observations of the single heater test and the DST) is shown in Figure 6.2-1. 
This diagram also indicates (in boxes) the important parameters and issues addressed in the THC 
seepage model simulations. To summarize the processes as depicted in the figure, heat 
conduction from the drift wall into the rock matrix results in vaporization and boiling, with vapor 
migration out of matrix blocks into fractures. The vapor moves away from the drift through the 
permeable fracture network by buoyancy, by the increased vapor pressure caused by heating and 
boiling, and through local convection. In cooler regions, the vapor condenses on fracture walls, 
where it drains through the fracture network either down toward the heat source from above or 
away from the drift into the zone underlying the heat source. Slow imbibition of water from 
fractures into the matrix gradually leads to increases in the liquid saturation in the rock matrix. 
Under conditions of continuous heat loading, a dryout zone may develop closest to the heat 
source separated from the condensation zone by a nearly isothermal zone maintained at about the 
boiling temperature. Where this nearly isothermal zone is characterized by a continuous process 
of boiling, vapor transport, condensation, and migration of water back to the heat source (either 
by capillary forces or gravity drainage), this zone may be termed a heat pipe (Pruess et al. 1990 
[DIRS 100818], p. 1235). 

MDL-NBS-HS-000001 REV 04 6-6 February 2005 


Drift-Scale THC Seepage Model 


Figure 6.2-1. Schematic Diagram of THC Processes around a Heated Drift 

6.2.1.2 THC Processes 
The chemical evolution of waters, gases, and minerals is intimately coupled to the TH processes 
(boiling, condensation, and drainage) discussed in the previous section. The distribution of 
condensate in the fracture system determines where mineral dissolution and precipitation can 
occur in the fractures and where there can be direct interaction (via diffusion) between matrix 
pore waters and fracture waters. Figure 6.2-2 shows schematically the relationships between TH 
and geochemical processes in the zones of boiling, condensation, and drainage in the rock mass 
at the fracture-matrix interface outside of the drift and above the heat source. 

MDL-NBS-HS-000001 REV 04 6-7 February 2005 


Drift-Scale THC Seepage Model 


Figure 6.2-2. Schematic Diagram of Fracture-Matrix Interface Showing the Relation Between TH 
Processes and Geochemical Processes 

One important aspect of the system is the exsolution of CO2 from the liquid phase as the 
temperature increases. The exsolution of CO2 in the boiling zone results in a local increase in 
pH, and a decrease in pH in the condensation zone into which the vapor enriched in CO2 is 
transported and condensed. The extent to which the pH is shifted depends strongly on the rates 
of mineralwater reactions, which can buffer the change in pH. Because the diffusivities of 
gaseous species are several orders of magnitude greater than those of aqueous species, and 
because the advective transport of gases can be more rapid than that of liquids, the region where 
CO2 degassing affects water and gas chemistry could be much larger than the region affected by 
the transport of aqueous species. 

The effects of TH processes on water chemistry are varied and depend on the behavior of the 
dissolved species and their relation to mineralwater reactions. Conservative species (i.e., those 
that are unreactive and nonvolatile), such as chloride (Cl) and nitrate (NO3), become 
concentrated in waters undergoing vaporization or boiling, but are essentially absent from the 
vapor condensing in the fractures. Therefore, the concentration of conservative species in the 
draining condensate waters is determined by mixing with fracture waters and diffusive mixing 
with matrix pore waters. 

More reactive aqueous species are affected by mineral precipitation-dissolution and ion 
exchange reactions, in addition to dilution and evaporative concentration as descirbed above. 
Calcium concentrations are affected by calcite dissolution or precipitation, by feldspar 
dissolution, and by ion exchange reactions involving Ca-bearing zeolites and clays. Ion 

MDL-NBS-HS-000001 REV 04 6-8 February 2005 


Drift-Scale THC Seepage Model 

exchange is not explicitly included in the THC seepage model, but is represented by 
dissolution/precipitation of solid solutions for smectites, and of pure end-member compositions 
for other clays and zeolites. Similarly, magnesium concentrations are affected by ion exchange 
(the THC seepage model does not contain a magnesium zeolite, but magnesiun-bearing clay 
phases are included), and by precipitation-dissolution of sepiolite. 

Sodium (Na+) and potassium (K+) are more conservative than the divalent ions, and 
concentrations are mainly controlled by evaporation (and salt precipitation at dryout conditions) 
and dilution, and, to a lesser degree, by feldspar dissolution reactions and ion exchange with 
clays and zeolites. 

Aqueous silica (SiO2(aq)) concentrations are controlled by precipitation of amorphous silica, as 
well as by dissolution and precipitation of other silicates. 

Zonation in the distribution of mineral phases can occur as a result of differences in mineral 
solubility as a function of temperature. The inverse relation between temperature and calcite 
solubility (as opposed to the silica phases, which are more soluble at higher temperatures) can 
cause zonation in the distribution of calcite and silica phases in both the condensation and 
boiling zones (Figure 6.2-2). Precipitation of amorphous silica or another silica phase is likely to 
be confined to a narrower zone where evaporative concentration from boiling exceeds its 
solubility. In contrast, calcite could precipitate in fractures over a broad zone of elevated 
temperature and where CO2 has exsolved because of temperature increases or boiling. Alteration 
of feldspars to clays and zeolites is likely to be most rapid in the boiling zone because of their 
increased solubility (as well as having higher dissolution and precipitation rates) at higher 
temperatures (Lasaga 1998 [DIRS 117091], p. 66). In drainage zones, mineral alteration could 
be zoned within the rock matrix adjacent to a fracture, in a similar manner to that observed as a 
function of distance along the transport path (Steefel and Lichtner 1998 [DIRS 144878], p. 186). 

In the THC seepage model, most precipitation and dissolution reactions are modeled as being 
kinetically limited (Section 6.4.2), with dissolutionprecipitation rates that are a function of both 
temperature and the degree of saturationundersaturation (the saturation index). Hence, species 
concentrations in solution at any given time and location are not controlled by the equilibrium 
thermodynamic condition, but rather by the influx rate, the rate of evaporation, and the rate of 
mineral dissolution in the grid cell of interest as countered by the rates of precipitation and 
outflow. For this reason, predicted solution compositions at any given location can be 
supersaturated with respect to a given mineral and remain so for extended periods of time. 

When chemical species are transported in fracture waters at rates greater than the rate of 
equilibration with the rock matrix, disequilibrium will exist between waters in fractures and 
matrix, potentially leading to different precipitating mineral assemblages and differences in 
reaction rates. Because the system is unsaturated and undergoes boiling, the transport of gaseous 
species between matrix and fractures is also important. The separate yet interacting geochemical, 
hydrologic, and thermal processes in the fractures and the rock matrix are incorporated into a 
dual-permeability modeling approach. In this approach, each location in the model is represented 
by both matrix and fracture gridblocks, each with its own pressure and temperature, liquid 
saturation, water and gas chemistry, and mineralogy. Communication between the coinciding 

MDL-NBS-HS-000001 REV 04 6-9 February 2005 


Drift-Scale THC Seepage Model 

matrix and fracture gridblocks is implemented by advective and diffusive transport of aqueous 
and gaseous species (Section 6.2.1.5). 

6.2.1.3 Effects of Infiltration and Climate Changes on THC Processes 
Early in the thermal period of the repository, much of the chemistry of the UZ around drifts will 
be constrained by the chemistry of ambient fracture and matrix pore water, which could change 
as a result of boiling, dilution with condensate water, or mineralwatergas reactions. Once the 
peak thermal period has subsided, percolating water will mix with the condensate above the 
repository and eventually rewet the dryout zone. The composition of the percolating waters 
(before mixing) could be similar to that presently found above the repository as matrix pore 
water, or it could be more dilute, reflecting wetter climate conditions. Changes in the percolation 
flux also affect the extent of mineral deposition and dissolution, because of the changes in the 
flux of dissolved species to the region around drifts. For example, the greater the flux of 
calcium, the more calcite would precipitate for a given initial calcium concentration in 
percolating water. Higher percolation fluxes could increase the dissolution rates of minerals that 
are undersaturated in the fluid because it could increase the degree to which the mineral is 
undersaturated. 

6.2.1.4 Hydrologic Property Changes in Fractures and Matrix 
Mineral precipitation and dissolution in fractures and matrix have the potential for modifying the 
porosity, permeability, and unsaturated hydrologic properties of the system. Because the molar 
volumes of minerals created by hydrolysis reactions (i.e., anhydrous phases, such as feldspars, 
reacting with aqueous fluids to form hydrous minerals, such as zeolites or clays) are commonly 
larger than the molar volumes of the primary reactant minerals, dissolutionprecipitation 
reactions commonly lead to porosity reductions. The extent of mineralwater reaction is 
controlled by the surface areas of the mineral phases in contact with the aqueous fluid, and 
heterogeneity in the distribution of minerals in the fractures. Therefore, changes in porosity and 
permeability caused by these processes may also be heterogeneously distributed. Other factors 
that could lead to heterogeneity in property changes are the distribution of liquid saturation in 
fractures, proportion of fractures having actively flowing water, and rates of evaporative 
concentration due to boiling, which could change the dominant mechanisms of crystal growth 
and nucleation. 

6.2.1.5 Dual-Permeability Model for THC Processes 
Transport rates by fluid flow in fractures greater than the rate of equilibration via diffusion 
necessarily leads to disequilibrium between waters in fractures and matrix. This disequilibrium 
can lead to differences in the prevailing mineral assemblage and to differences in reaction rates. 
Because the system is unsaturated and undergoes boiling, the transport of gaseous species is an 
important consideration. The model must also capture the differences between the initial 
mineralogy in fractures and matrix and their evolution. These separate yet interacting processes 
in fractures and matrix have been treated by adapting the dual-permeability model to include 
geochemical as well as hydrologic and thermal processes. In the dual-permeability model, each 
grid-block is partitioned into matrix and fracture continua, each characterized by its own 
pressure, temperature, liquid saturation, water and gas chemistry, and mineralogy. Figure 6.2-3 

MDL-NBS-HS-000001 REV 04 6-10 February 2005 


Drift-Scale THC Seepage Model 

illustrates the dual-permeability conceptual model used for THC processes in the drift-scale THC 
seepage model and the DST THC submodel. 


NOTE: Arrows refer to aqueous and gaseous species transport pathways. Angular objects in the fracture are 
minerals coating the fracture surface. 

Figure 6.2-3. Conceptual Model (Schematic) for ReactionTransport Processes in Dual-Permeability 
Media 

As summarized in the preceding subsection, the conceptual model for THC processes 
incorporates a wide range of coupled physical and chemical processes. The following subsection 
describes the implementation of this conceptual framework into a numerical model. 

6.2.2 Conceptualization of the Geochemical System 
The rationale used for defining the types and concentrations of chemical constituents (solid and 
gaseous) included in the THC seepage model is presented below. This discussion includes the 
selection of initial pore-water and pore-gas compositions and description of the geochemical 
system. The geochemical system includes the aqueous components used in the model, the types 
and initial abundances of primary minerals (those already present in the rock), and 
secondary minerals that may precipitate as the result of watergasrock interactions. 

6.2.2.1 Initial Pore-Water and Pore-Gas Chemistry 
The initial water composition input into the model could be chosen from either the pore-water 
chemistry in the UZ at or above the repository horizon, or from the perched water or saturated 
zone. The perched waters are generally much more dilute than UZ pore waters. Isotopic 
compositions (36Cl/Cl, 18O/16O, D/H, 14C) and chloride concentrations suggest that the perched 
waters have a large proportion of late Pleistocene/early Holocene water (Levy et al. 1997 
[DIRS 126599], p. 906; Sonnenthal and Bodvarsson 1999 [DIRS 117127], pp. 107 and 108). 
The saturated zone water is also more dilute than pore waters, and neither saturated nor perched 

MDL-NBS-HS-000001 REV 04 6-11 February 2005 


Drift-Scale THC Seepage Model 

water reflect calculated CO2 partial pressures consistent with CO2 concentrations in gas 
measured in the unsaturated zone in repository units. The saturated zone and perched-water 
compositions are, therefore, deemed poor candidates as initial input water compositions for the 
THC seepage model. Preference is given instead to actual pore waters from unsaturated regions 
within or above the repository units. 

A conceptual model that explains the aqueous chemistry and background 36Cl/Cl isotopic ratios 
in the Exploratory Studies Facility (ESF) holds that percolating water must pass mostly through 
the Paintbrush nonwelded hydrogeologic unit (PTn) matrix (because of its high permeability and 
low fracture density) before reverting to predominantly fracture flow in the Topopah Spring 
welded hydrogeologic unit (TSw). As discussed by Levy et al. (1997 [DIRS 126599], pp. 907 
and 908), this seems to be true everywhere except near large structural discontinuities in the PTn 
(i.e., faults). Hence, percolating water in the TSw ultimately had come predominantly through 
the PTn matrix. Analyses of PTn pore waters (and some at the top of the TSw) and many 
chloride analyses of TSw pore waters are consistent with this interpretation (Sonnenthal and 
Bodvarsson 1999 [DIRS 117127], pp. 140 and 141). The relatively higher concentrations of 
anions and cations in pore waters (compared to perched water) from the TSw, similar to PTn 
waters, are consistent with the premise that the waters had flowed through the PTn matrix. 

The initial composition of water in fractures is taken to be the same as in the rock matrix 
throughout the model domain, using the same initial composition in all hydrogeologic units. The 
composition of water infiltrating the top of the model domain (in the Tiva Canyon welded 
hydrogeologic unitTCw) is also set to be the same as the initial fracture and matrix pore-water 
composition, with the exception of minor changes related to a pH adjustment, reflecting a higher 
CO2 partial pressure and a lower temperature at the top model boundary than deeper into the 
model domain (see below). Setting nearly identical compositions for infiltration at the top model 
boundary and initial fracture-matrix waters is a simplification of the natural system to avoid 
having to consider complex near-surface geochemical and transport processes, such as 
evapotranspiration and biologically mediated reactions. 

In the early stages of development of the THC seepage model, only a few nearly complete 
pore-water analyses from a repository unit were available. These were water ultracentrifuged 
from core samples collected from the Tptpmn geologic unit in Alcove 5 near the DST. Three 
water samples were analyzed (HD-PERM-1, HD-PERM-2, and HD-PERM-3) from the same 
suite of core and yielded very similar compositions. Two of these analyses with nearly identical 
compositions were averaged for use as an input water composition for the developmental THC 
seepage models (Table 6.2-1). This water has been retained as one of the input waters in the 
current model. Since then, a series of pore-water samples from repository host units has been 
analyzed. These samples were ultracentrifuged from core collected in the ECRB Cross-Drift and 
in boreholes SD-9 and NRG-7/7A. The compositions of these waters are shown on a Piper 
diagram in Figure 6.2-4 with the composition of HD-PERM samples and groundwater from well 
J-13. This figure also shows the hydrogeologic units from which the water samples were 
extracted. It is evident from Figure 6.2-4 that the span of potential initial water compositions for 
use in the THC seepage model is large. This figure also shows a tendency for samples from 
deeper hydrogeologic units to exhibit higher sodium (plus potassium) concentrations relative to 
calcium (plus magnesium) concentrations, and a higher proportion of aqueous carbonate (relative 
to chloride and sulfate) compared to shallower waters. The sodium increase relative to calcium 

MDL-NBS-HS-000001 REV 04 6-12 February 2005 


Drift-Scale THC Seepage Model 

with depth has been noted previously in pore waters from hydrogeologic units above and below 
the repository units (Yang et al. 1996 [DIRS 100194], p. 13). It is likely caused by the 
hydrolysis of volcanic glass and feldspars and, mostly below the repository units, exchange 
reactions with zeolites (BSC 2002 [DIRS 160247]; Vaniman et al. 2001 [DIRS 157427]). The 
precipitation of calcite in fractures under the ambient geothermal gradient would also exacerbate 
the decrease in calcium relative to sodium concentrations with depth. Trends in carbonate 
concentrations relative to chloride and sulfate concentrations are subject to large uncertainties as 
a result of the determination of total aqueous carbonate concentrations. An increase in aqueous 
carbonate concentration with depth could be attributed to the pH increase expected to accompany 
glass and feldspar hydrolysis reactions. 

The differences in the proportions (not absolute values) of cations and anions in analyzed waters 
have an important bearing on the types of residual brines that could develop upon evaporation 
and boiling due to thermal loading (BSC 2004 [DIRS 169863], Section 6.3.2). Should these 
waters seep onto the surface of a hot waste package, knowledge of their end-brine composition is 
important to assess the likelihood and intensity of waste package corrosion (BSC 2004 
[DIRS 169860], Section 6.1). Therefore, the span of selected input water compositions should 
take into account factors that influence the end-brine composition of these waters. One 
important factor is whether calcium (or magnesium) chloride brines could develop instead of 
sodium chloride brines. Calcium chloride brines persist to higher temperatures (i.e., exist at a 
lower relative humidity, more hygroscopic) than sodium chloride brines, and are potentially 
deleterious with respect to corrosion. No simple a priori criteria have been developed to 
determine with certainty the end-brine composition of a given water, but calcium chloride brines 
are more likely to form if the total calcium concentration (in meq/L) exceeds the total aqueous 
carbonate concentration (in meq/L) in the initial water (calcite precipitation chemical divide, 
Drever 1997 [DIRS 140067]). Waters with such compositions would have a tendency to plot in 
the upper half of the diamond-shaped area in Figure 6.2-4, although other waters may also plot in 
this area if their magnesium concentrations are high relative to calcium. Other chemical divides 
after calcite precipitation (Drever 1997 [DIRS 140067], p. 331; Rosenberg et al. 2001 
[DIRS 154862], p. 1,238) could result in the development of brines that are potentially less 
deleterious than calcium or magnesium chloride, even though the calcium content of the original 
waters (in equivalents) exceeds the total carbonate content. 

MDL-NBS-HS-000001 REV 04 6-13 February 2005 


Table 6.2-1. Input Pore-Water Compositions for the THC Seepage Model 

-

Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 6-14 
February 2005 

Sample ID: 
HD-PERMa 
(Alcove 5) 
ECRB-SYS-
CS1000/7.3-7.7/UCb ECRB-SYS-
CS2000/16.5-21.1/UC2 SD-9/990.4-991.7/UCb 
ECRB-SYS-
CS500/12.0-16.7/UCb 
Lithostratigraphic Unit: Tptpmn Tptpul (base) Tptpll Tptpll Tptpul 
Simulation Water ID: W0 W5 W4 W6 W7 
Water Input Type: Fract/Matrix Boundary Fract/Matrix Boundary Fract/Matrix Boundary Fract/Matrix Boundary Fract/Matrix Boundary 
Units 
Temperature C 25 17 25 17 25 17 25 17 25 17 
pH (measured) 
pH (calc)c 
Na+ 
K+ 
Ca+2 
Mg+2 
SiO2 
Cl 
SO4 
2 
HCO3 
 (measured) 
HCO3 
 (calc)d 
NO3 
 
F 
pH 
pH 
mg/L 
mg/L 
mg/L 
mg/L 
mg/L 
mg/L 
mg/L 
mg/L 
mg/L 
mg/L 
mg/L 
8.31 
-
61.5 
8 
101 
17 
70.5 
117 
116 
-
200 
6.5 
0.86 
-
7.750 
61.5 
8 
101 
17 
70.5 
117 
116 
-
216 
6.5 
0.86 
7.6 
8.062 
39 
7.6 
94 
18.1 
42.0 
21 
36 
333 
395 
2.6 
3.4 
-
8.026 
39 
7.6 
94 
18.1 
42.0 
21 
36 
-
400 
2.6 
3.4 
7.4 
8.175 
130 
10.6 
82 
5.3 
48 
26 
39 
382 
515 
4.2 
6.01e (11) 
-
8.140 
130 
10.6 
82 
5.3 
48 
26 
39 
382 
515 
4.2 
5.52 
7.9 
8.001 
84 
7.9 
56 
0.9 
50 
23 
10 
313 
335 
17 
2.5 
-
7.964 
84 
7.9 
56 
0.9 
50 
23 
10 
-
338 
17 
2.5 
8.0 
8.073 
57 
10.3 
120 
19.3 
49 
54 
78 
286 
412 
6.1 
4.8 
-
8.038 
57 
10.3 
120 
19.3 
49 
54 
78 
-
417 
6.1 
4.8 
Al+3 (calc)f molal 6.173  1010 9.775  1011 1.112  109 3.415  1010 1.082  109 3.305  1010 1.00  109 3.08  1010 8.061  1010 2.477  1010 
Fe+3 (calc)g molal 1.155  1012 5.162  1013 1.138  1012 5.000  1013 1.143  1012 4.984  1013 1.14  1012 5.02  1013 1.138  1012 5.006  1013 
log(PCO2)h 
CO2 (approx)i 
bar 
ppmv 
-3.1 
900 
-2.5 
3100 
-2.5 
3100 
-2.5 
3100 
-2.5 
3100 
-2.5 
3100 
-2.5 
3100 
-2.5 
3100 
-2.5 
3100 
-2.5 
3100 

a 

Average of Tptpmn pore-water analyses ESF-HD-PERM-2 (30.1'-30.5') and ESF HD-PERM-3 (34.8'-35.1'), DTN: MO0005PORWATER.000 [DIRS 150930]. 

b 

Pore water analyses from the ECRB Cross-Drift and borehole SD-9 reported with DTN: GS020408312272.003 [DIRS 160899]. 

c 

pH calculated by speciation at the temperature and log(PCO2) shown (using SOLVEQ/CHILLER V1.0, LBNL 1999 [DIRS 153217]). 

d 

Total aqueous carbonate as HCO3, calculated from charge balance computed by speciation at the temperature and pH shown (at measured pH for 
HD-PERM sample; at calculated pH for other samples) (using SOLVEQ/CHILLER V1.0). Note: these are slightly different values than values calculated from 
charge balance reported in DTN: GS020408312272.003 [DIRS 160899] because the latter do not include the effect of speciation. 

e 

Value shown is calculated at equilibrium with fluorite at 25C. Value in parentheses is measured value. 

f 

Calculated by equilibrating with illite at the temperature and calculated pH shown (using SOLVEQ/CHILLER V1.0) (Section 6.2.2.1). 

g 

Calculated by equilibrating with hematite at the temperature and calculated pH shown (using SOLVEQ/CHILLER V1.0) (Section 6.2.2.1). 

h 

Set at values shown except for HD-PERM sample at 25C (calculated in this case) (Section 6.2.2.1). 

i 

Approximate conversion assuming 1 bar total pressure. 

NOTE: Compositions shown are those used for initial fracture and matrix water (column labeled Fract/Matrix) and infiltration water at the model top 
boundary (column labeled Boundary) 


Drift-Scale THC Seepage Model 

The choice of input water composition must also consider the natural variability of pore-water 
compositions in the repository units. This natural variability is illustrated in Figure 6.2-4. The 
number of samples collected from a range of lithologies and infiltration regimes is too small to 
associate a probability of occurrence for any of these pore-water compositions. From the 
considerations discussed above, one could expect deeper waters to exhibit lower calcium and 
higher total carbonate concentrations and, therefore, be less conducive to the formation of 
calcium chloride brines. However, other factors could affect the spatial distribution of 
pore-water compositions in the repository units. These factors include variations in infiltration 
rates in various parts of the repository footprint (Sonnenthal and Bodvarsson 1999 
[DIRS 117127], pp. 122 and 123) and possibly the presence or absence of ion-exchanging 
zeolites in areas above the repository. Furthermore, as noted above, the evolution of brine 
composition upon evaporation and boiling follows several other chemical divides besides the 
first calcite divide mentioned earlier. 

Given these considerations, several initial water compositions have been selected for use in the 
current THC seepage model based on the following criteria: 

(1) Capture the spread of pore-water compositions shown on Figure 6.2-4 and 
include, to the extent practicable, waters that may yield different end-brine 
compositions. 
(2) Include at least one pore water from the most important repository host unit 
(Tptpll). 
(3) Use analyses that show the best charge balance if more than one sample meets the 
other criteria. 
(4) Limit the number of waters to limit overall computational effort. 
On these bases, five water compositions have been selected and listed here with an arbitrary 
identification (W0, W5, etc.) assigned for this report: 

W0: HD-PERM water, from the Tptpmn unit in Alcove 5. This is an average 
composition (from Samples HD-PERM-2 and HD-PERM-3) used for all REV01 
work. The HD-PERM samples plot higher than other pore waters on the 
diamond-shaped area in Figure 6.2-4, bounding the range of compositions in the 
calcium-sulfate-chloride field. 

W5: Sample CS-1000/7.3-7.7/UC, from the base of the Tptpul lithostratigraphic unit in 
the ECRB Cross-Drift. This sample was selected because it exhibits one of the 
highest (Ca+Mg)/(Na+K) ratios of the ECRB Cross-Drift samples and exhibits 
better charge balance than other samples with high (Ca+Mg)/(Na+K) ratios. 

W4: Sample CS-2000/16.5-21.1/UC, from the Tptpll lithostratigraphic unit in the 
ECRB Cross-Drift. This sample exhibits the lowest (Ca+Mg)/(Na+K) ratio of the 
ECRB Cross-Drift samples and exhibits better charge balance than other samples 
of similar composition. Also, this sample is from the main repository host unit 
and contains a higher fluoride concentration than the other samples. 

MDL-NBS-HS-000001 REV 04 6-15 February 2005 


Drift-Scale THC Seepage Model 


DTNs: GS030408312272.002 [DIRS 165226], GS020408312272.003 [DIRS 160899], GS020808312272.004 
[DIRS 166569], GS031008312272.008 [DIRS 166570], MO0005PORWATER.000 [DIRS 150930]. 

NOTE: Samples labeled HD-PERM are pore waters from the Tptpmn unit in Alcove 5 of the ESF. Sample IDs 
starting with SYS-CS represent pore waters from the ECRB Cross-Drift and are listed in order of 
increasing distance (m) into the drift (down stratigraphy). Additional borehole interval information after 
each SYS-CS sample labeling is sample interval distances from borehole collar given in feet. CS is the 
abbreviation for Construction Station, indicating distance along the ECRB Cross-Drift in meters. 
THERMALK pore waters are from near the south bend of the ESF drift. SAD-GTB pore water samples are 
from the Alcove 7 area of the ESF. Sample IDs starting with SD-9, UZ-14, and UZ-16 represent pore 
waters from surface boreholes with the same names. The 5 starting waters are indicated (see text). 
DTN: GS020808312272.004 [DIRS 166569] is unqualified due to missing closing calibrations for 
electronic balances and NIST traceable weights. These data are included here to show the full spread of 
measured waters. 

Figure 6.2-4. Piper Plot of Water Compositions (meq/L) from Repository Units 

Upon further evaluation and a request from downstream project personnel, two additional 
samples have been considered: 

W6: Sample SD-9/990.4-991.7, from the Tptpll lithostratigraphic unit in borehole 
SD-9. This sample exhibits a low (Ca+Mg)/(Na+K) ratio nearly identical to that 
of W4, but exhibits a better charge balance than W4 and a higher nitrate 
concentration compared to most other samples. This water is very similar in 
composition to Water W4. 

W7: Sample CS500/12.0-16.7, from the Tptpul lithostratigraphic unit in the ECRB 
Cross-Drift. This sample plots between the HD-PERM waters and Water W5 on 

MDL-NBS-HS-000001 REV 04 6-16 February 2005 


Drift-Scale THC Seepage Model 

Figure 6.2-4, further capturing the variability of water compositions in the upper 
part of Figure 6.2-4. 

The compositions of these waters are given in Table 6.2-1. This table also includes calculated 
concentrations used for input into the THC seepage model, and distinguishes between the 
compositions used for initial fracture and matrix waters and slightly adjusted compositions used 
for infiltration water at the top model boundary, as discussed further below. 

It is shown in Figure 6.2-4 that the water compositions chosen for input into the THC seepage 
model capture the spread of currently available pore-water compositions in repository units. 
Water compositions W4, W5, and W6 plot in the lower half of the diamond-shaped area on 
Figure 6.2-4. The HD-PERM waters and W7 plot in the upper half of this area, and for this 
reason may be more likely to evolve toward a calcium chloride brine than the other waters upon 
evaporation. 

As discussed in Section 5 (Assumption 2), binning analysis in Engineered Barrier System: 
Physical and Chemical Environment Model (BSC 2004 [DIRS 169860], Section 7.2.3) also 
indicates that the five chosen starting waters adequately encompass the variability in repository 
host rock pore water compositions. 

The set of analyzed species for these samples does not include iron and aluminum. Because 
these components are needed to include aluminum silicates in simulations, their concentrations 
have been calculated assuming equilibrium with hematite and illite, respectively. Illite was 
chosen to set the initial aluminum concentration because waters from Yucca Mountain typically 
plot on, or near, the illite-K-feldspar equilibrium boundary (Wang 2003 [DIRS 161665], 
Notebook SN-LBNL-SCI-141-V2, pp. 176 and 184). Hematite is the most abundant iron oxide 
mineral found in the tuffs at Yucca Mountain and is a reasonable candidate to use for setting the 
initial iron concentration in solution. 

The total aqueous carbonate concentration (reported here as HCO3) was not measured in 
HD-PERM samples and has been calculated from charge balance, after full speciation 
calculations (using SOLVEQ/CHILLER V1.0 (LBNL 1999 [DIRS 153217])). Doing so yields a 
partial pressure of CO2 (at equilibrium with the HD-PERM water) near 103 bar, consistent with 
CO2 concentrations near 1,000 ppmv measured in repository units in the ESF 
(DTN: LB0208ISODSTHP.001 [DIRS 161638]) and in borehole UZ-1 (Yang et al. 1996 
[DIRS 100194], p. 43). 

Total aqueous carbonate concentrations were reported for the other samples. However, the 
analyses of these samples reflect a fairly significant charge imbalance (2 to 11 percent). Also, it 
is known that aqueous carbonate analyses can be easily impacted by interference with 
atmospheric carbon dioxide during sample preparation. For these reasons, the carbonate 
concentrations have been recalculated from charge balance after full speciation calculations. 

Other adjustments have been made to some of the reported analytical data before input into the 
model as follows. The pH reported for the ECRB and SD-9 samples yield equilibrium carbon 
dioxide partial pressures significantly higher (up to 14,000 ppmv) than what is observed in the 
repository units (typically around 1,000 ppmv). For this reason, the pH of these waters has been 

MDL-NBS-HS-000001 REV 04 6-17 February 2005 


Drift-Scale THC Seepage Model 

recalculated to yield lower CO2 partial pressure values more in line with concentrations 
measured in repository units. Bringing the CO2 partial pressure down to near 1,000 ppmv 
requires raising the water pH to values of 8.5 and higher. Such pH values seem too high in 
comparison to values of 7.79, 8.31, and 8.32 reported for the HD-PERM samples 
(DTN: MO0005PORWATER.000 [DIRS 150930]). Therefore, an intermediate but still 
reasonable CO2 partial pressure around 3,100 ppmv (log(Pco2) ~ -2.5) has been used, yielding 
pH values between 8 to 8.2 (Table 6.2-1). In this respect, these water compositions are likely to 
represent high-end CO2 concentrations, whereas the HD-PERM samples represent a somewhat 
lower bound. 

Another adjustment to input water concentrations involves fluoride in sample ECRB-SYSCS2000/
16.5-21.1/UC. The fluoride concentration in this sample (11 mg/L) reflects a significant 
supersaturation with respect to fluorite (CaF2 solid) at 25C. The precipitation of fluorite is 
typically quite rapid (Section 4.1.3) and, for this reason, the fluoride concentration of this sample 
has been lowered to a concentration reflecting saturation with fluorite (near 6 mg/L for this 
water). 

As mentioned earlier, infiltration water at the top model boundary is taken to have the same 
composition as the initial pore water, but with adjusted total aqueous carbonate, aluminum, and 
iron concentrations to reflect a lower temperature (17C) and higher CO2 partial pressure near 
the ground surface. Using this boundary water yields chemically steadier ambient water 
compositions at the location of the modeled drift (Section 6.5.5.4). 

The initial CO2 partial pressure in fractures and matrix has been calculated as the partial pressure 
of CO2 in chemical equilibrium with the input water composition at 25C, assuming ideal gas 
behavior (i.e., partial pressure is equal to fugacity). The 25C temperature is close to the initial 
temperature at the location of the drift. 

6.2.2.2 Geochemical Systems 
Minerals and chemical-aqueous components considered in this study are shown in Table 6.2-2. 
Primary mineral types and abundances are derived from X-ray diffraction (XRD) measurements 
on cores reported in the Yucca Mountain mineralogical model (DTN: LA9908JC831321.001 
[DIRS 113495]) and analyses of fracture surfaces (Carlos et al. 1993 [DIRS 105210], p. 47; 
DTNs: LA9912SL831151.001 [DIRS 146447]; LA9912SL831151.002 [DIRS 146449]). 
Amounts of minerals observed, but present in quantities below the detection limit (typically 
around a percent for XRD), have been estimated. Potential secondary minerals (i.e., those 
allowed to precipitate but which may not necessarily form) have been determined from field 
observation of thermal alteration (Vaniman et al. 2001 [DIRS 157427], p. 3,409) and 
corroborated by running multicomponent heterogeneous equilibrium simulations of water-rock 
interaction (Wang 2003 [DIRS 161665], Notebook SN-LBNL-SCI-141-V2, pp. 94 and 95) using 
SOLVEQ/CHILLER V1.0 (LBNL 1999 [DIRS 153217]) and the current thermodynamic 
database (DTN: LB0307THMDBRTM.001 [DIRS 164434]). From these simulations, the stable 
mineral assemblage at each reaction step is calculated from a large list of possible minerals (after 
suppressing phases known not to form under ambient pressures and low temperatures). 
Anorthite is not observed as a secondary phase, so calcium enters other minerals such as zeolites 
and calcite. 

MDL-NBS-HS-000001 REV 04 6-18 February 2005 


Drift-Scale THC Seepage Model 

The bases for selection of aqueous species included in this study are: (1) use the major 
components of pore water, (2) use all components in major rock-forming minerals considered in 
the model, and (3) use additional components specifically requested by downstream users 
(nitrate, iron, and fluoride). Thus, the geochemical system used includes the major solid phases 
(minerals and glass) encountered in geologic units at Yucca Mountain, together with a range of 
possible reaction product minerals, CO2 gas, and aqueous species necessary to include these 
solid phases and the pore-water composition within the THC seepage model (Table 6.2-2 and 
Section 4.1). 

Table 6.2-2. Mineral, Aqueous, and Gaseous Species Used in the THC Seepage Model 

Aqueous Basis Species Minerals Mineral Typea 
H2O Calcite P,S 
H+ Tridymite P 
Na+ a-Cristobalite P 
K+ Quartz P 
Ca+2 Amorphous Silica S 
Mg+2 Hematite P,S 
SiO2 Fluorite P,S 
AlO2 
 Gypsum S 
HFeO2 
2 Goethite S 
HCO3 
 Albite P,S 
Cl K-Feldspar P,S 
SO4 
2 Anorthite P 
F Ca-Smectite P,S 
NO3 
 Mg-Smectite P,S 
Na-Smectite P,S 
Gases Opal_proxy P 
CO2 Illite P,S 
H2O Kaolinite S 
Air Glass P 
Stellerite P,S 
Heulandite P,S 
Mordenite P,S 
Clinoptilolite P,S 
Sepiolite S 

Source: DTN: LB0307THMDBRTM.001 [DIRS 164434]. 

a 

Primary (P) and secondary (S) minerals. 

6.2.3 Conceptualization of the Model Domain 
The current repository design includes a planar series of parallel, equidistant, and horizontal 
waste emplacement drifts that are laid out over a large surface area. As such, encompassing all 
areas of the repository would require a large and detailed three-dimensional model. However, 
the scope of this report covers THC processes at the drift-scale. Therefore, the model has been 
reduced and simplified to focus on areas surrounding a typical waste emplacement drift. 
Because the number of grid-blocks directly affects the simulation time, the model domain is 
reduced as much as possible without losing important information. Based on the geologic 

MDL-NBS-HS-000001 REV 04 6-19 February 2005 


Drift-Scale THC Seepage Model 

framework model (BSC 2002 [DIRS 170029]), the dip of repository host units is subhorizontal. 
Assuming that the rock properties are laterally homogeneous between drifts (Section 6.4.6, item 
12), a planar and parallel drift layout can be conceptualized, in two dimensions, as a series of 
symmetrical, identical half-drift X-Z models (X representing the horizontal distance in a 
direction perpendicular to the length of the drifts, and Z the vertical distance) with no-flux (heat, 
fluid, chemical) vertical boundaries between them. Note that this half-drift simplification based 
on symmetry is theoretically applicable only for homogeneous properties, but is also a good 
approximation for heterogeneous fracture permeability fields if they display only weak spatial 
correlation. 

Accordingly, the THC seepage model has been reduced to a half-drift model with a width 
corresponding to the midpoint between drifts. The model is refined in the vicinity of the drift 
and extends in a progressively coarser fashion to the TCw (near the ground surface) above the 
drift and to the water table below the drift. This symmetrical chimney model represents 
coupled THC processes at the drift scale in areas that are not affected by repository-edge effects 
(i.e., effects resulting from the cooler temperatures at the repository edge). Water and gas 
compositions at the edge of the repository (BSC 2004 [DIRS 169866], Section 6.4) are less 
concentrated and, therefore, within the range of compositions simulated in this report. However, 
the temperature history of the edge location is different from an interior, and therefore the 
compositions would not follow the same time history as the repository-center simulations for the 
THC seepage model. Also, drifts that do not reach boiling are likely to show a narrower range of 
compositions than the case simulated in this report. Even with large-scale gas transport at the 
repository-scale, the range of gas composition (e.g., CO2 concentration) over time is less than for 
the repository-center locations (BSC 2004 [DIRS 169866], Figure 6.4-16). Apart from the 
thermal loading and temperature history, the major contributor to variations in potential seepage 
chemistry is the initial water chemistry. Rock mineralogy is relatively uniform throughout the 
repository block (Peterman and Cloke 2002 [DIRS 162576], p. 683; see Assumption 1 for a more 
complete description), and pore water compositions are represented by the available data from 
different host rock units. Water compositions selected from the available data include samples 
collected from near the repository edge (W0) as well as from the repository center in the Tptpll 
unit (W4). Based on this information the THC seepage model results can be used to represent 
potential effects of THC processes on seepage water compositions at all waste package locations 
with consideration of the temperature history at each specific location. 

In the THC seepage model, perched-water effects are ignored. Perched-water conditions are 
confined mainly to the lower units of the Topopah Spring welded (TSw) hydrogeological unit 
and on top of the Calico Hills nonwelded unit (CHn). Over the repository domain, perched water 
locations are typically 100 to 150 m below the repository horizon (Wu et al. 1999 
[DIRS 117167]). Because the dominant heat-transfer mechanism at these locations is heat 
conduction and boiling conditions are not attained, the effect of repository thermal load on 
perched-water bodies is ignored (BSC 2004 [DIRS 169866], Section 6.1.2). 

6.3 ALTERNATIVE CONCEPTUAL MODELS 
Developmental versions of the THC seepage model used alternate conceptualizations of drift 
location, drift representation, modeled stratigraphic column, geochemical systems, and 
boiling/evaporation mathematical models. These conceptualizations were implemented in 

MDL-NBS-HS-000001 REV 04 6-20 February 2005 


Drift-Scale THC Seepage Model 

various model variations and are discussed in detail in the previous revision of this report 
(BSC 2004 [DIRS 168848], Sections 6.5 to 6.7). Although the model has been significantly 
revised between the early Revision 1 (REV01) simulations and the current ones (Table 6-1), the 
early results are adequate and sufficient for their intended use in this report, which is to evaluate 
model sensitivity and uncertainty, and they do not provide feeds to TSPA. They are summarized 
below with the current model for reference: 

 THC model (Section 6.5)This model provides feeds to downstream reports and to 
TSPA. In this scenario, the repository drift is in the Tptpll lithostratigraphic unit, the drift 
wall open to gas and liquid flow, stepwise increases in infiltration rate are used (two 
fixed-rate simulations are run as sensitivity analyses), and the effect of vapor-pressure 
lowering due to capillary pressure is considered. A sensitivity analysis has also been run 
without this effect. (Although the current revision of this report is REV04, model inputs 
and outputs have not been modified from the previous model. Hence, the current model 
results are the same as those presented as REV02 in the previous version of this report.) 
 Developmental model simulationsThese were run with thermodynamic and kinetic 
parameter databases that differ from those used in the current model, and differing 
geochemical systems. Drift walls were closed to fluid flow, and vapor pressure lowering 
due to capillary pressure was not implemented. 
1. Tptpmn THC model REV01 (BSC 2004 [DIRS 168848], Section 6.5). This model 
represents a stratigraphic column on the edge of the repository (borehole SD-9) and 
considers a drift in the Tptpmn lithostratigraphic unit. Two alternative geochemical 
systems are used with this model: a base-case system and an extended-case system. 
2. Tptpmn THC heterogeneous model REV01 (BSC 2004 [DIRS 168848], Section 6.6). 
This model includes the same conceptualizations as the above model except that it 
considers heterogeneous fracture permeability variations. 
3. Tptpll THC model REV01 (BSC 2004 [DIRS 168848], Section 6.7). This model 
represents a stratigraphic column at the center of the repository with a drift in the 
Tptpll lithostratigraphic unit. Both base-case and extended-case geochemical systems 
(Section 6.2.2.2) are considered. 
These historical simulations are discussed in this report where relevant. They primarily provide 
an assessment of the sensitivity of model results to the drift geologic host unit (Tptpmn versus 
Tptpll) and fracture permeability heterogeneity. The Tptpll and Tptpmn THC models do not 
show significantly different water chemistry in either space or time, indicating that the THC 
seepage model is insensitive to the choice of repository host rock, and provide the basis for 
extrapolation of the results of the current THC seepage model (in the Tptpll unit) to other 
lithostratigraphic units (Section 5). The Tptpmn Heterogeneous THC model includes the 
observed natural heterogeneity in fracture permeability (4 orders of magnitude) and does not 
show significantly different water chemistry when compared to the homogeneous REV01 
Tptpmn THC model, justifying the use of homogenous properties in the current model 
(Section 6.4.6). However, the magnitude of the revisions between the historic and current 
models hampers pinpointing direct cause-effect relationships between a given specific change in 

MDL-NBS-HS-000001 REV 04 6-21 February 2005 


Drift-Scale THC Seepage Model 

the model and its effect on simulation results. For these reasons, the REV01 results are best 
regarded as a qualitative assessment of model sensitivity to drift location and fracture 
permeability heterogeneity. Because the historical model results indicate that the effect of these 
parameters on predicted water chemistry and mineral alteration may not be as significant as the 
effect of uncertainties in input water composition, thermodynamic data, and infiltration rates, 
evaluating the latter uncertainties is given priority in this report. For predictive evaluations, the 
most recent results are used, keeping in mind that the model uncertainty encompasses the results 
of both earlier and recent work. 

Alternative conceptualizations not treated here could yield differences in model results. 
Examples of such alternative models include the use of more than two porous media continua (to 
better represent lithophysae or better capture gradients between fractures and matrix, or both), 
heterogeneous fracture porosity (in addition to heterogeneous permeability), or other sets of 
potential secondary minerals. These alternatives have not been considered because they are 
expected to result in smaller differences in model results than the alternatives considered here. 
This is primarily because the range of input water compositions considered in the model 
(Section 6.2.2.1), by itself, already introduces a significant spread in model results 
(Section 6.5.5). 

6.4 MATHEMATICAL MODEL 
This section describes the mathematical formulations that underlie the THC seepage model (and 
the DST THC submodel presented in Section 7). The model is implemented using the 
TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]) reactive transport code. Other reactive 
transport simulators, using various formulations, were considered by the project, including 
OS3D/GIMRT (Steefel and Yabusaki 1996 [DIRS 100827]) and MULTIFLO (Lichtner and Seth 
1996 [DIRS 151989]). However, these simulators either have limitations that make them 
unsuitable for use in this study or have drawbacks in terms of availability, technical support, and 
qualification status. For instance, OS3D/GIMRT (Steefel and Yabusaki 1996 [DIRS 100827]) 
deals only with fully liquid-saturated conditions. When development of the THC seepage model 
was initiated in 1997, TOUGHREACT was the only code that could perform coupled 
thermal-hydrologic-chemical calculations in unsaturated rock, with phase changes (boiling), 
gaseous species transport (e.g. water vapor, CO2, air), multicomponent transport, and kinetic and 
equilibrium reactions, in multicontinuum and multidimensional domains with unstructured grids. 
TOUGHREACT is the only software of its type qualified for Yucca Mountain work. Also, the 
developers of the THC seepage model have contributed to the development of this software and, 
most particularly, to its development for applications to the repository at Yucca Mountain. They 
are also familiar with other thermal hydrology and transport codes used by the Yucca Mountain 
Project, and have repeatedly updated and re-qualified TOUGHREACT with new features to 
maintain consistency with the other hydrologic codes used by the project. For these reasons, 
TOUGHREACT and its formulation have been selected for this study. As stated in Section 3, 
the software is adequate and appropriate for the intended use in this model, and is used strictly 
within the range of validation. 

For brevity, unless a formulation is used that is specific to a particular version of 
TOUGHREACT, hereafter the code version and reference are not cited. 

MDL-NBS-HS-000001 REV 04 6-22 February 2005 


Drift-Scale THC Seepage Model 

6.4.1 General Numerical Model for Coupled THC Processes 
Thermal and hydrologic processes modeled using TOUGHREACT (all versions) are equivalent 
to those using TOUGH2 V1.6 (LBNL 2003 [DIRS 161491]), which are described in detail in 
Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338], 
Section 6.2.1.1) and in the TOUGHREACT V3.0 Users Manual (BSC 2002 [DIRS 164454]; 
LBNL 2002 [DIRS 161256]). 

The geochemical module incorporated in TOUGHREACT V2.2 (LBNL 1999 [DIRS 153219]); 
V2.3 (LBNL 2001 [DIRS 153101]); V2.4 (LBNL 2001 [DIRS 160880]); and V3.0 (LBNL 2002 
[DIRS 161256]) simultaneously solves a set of chemical mass-action, kinetic-rate expressions for 
mineral dissolution/precipitation and mass-balance equations. This provides the extent of 
reaction and mass transfer between a set of given aqueous species, minerals, and gases at each 
grid block of the flow model. Equations for heat, liquid and gas flow, aqueous and gaseous 
species transport, and chemical reactions are summarized by Xu and Pruess (1998 
[DIRS 117170]; 2001 [DIRS 156280], p. 30, Tables A and B) and Xu et al. (1998 
[DIRS 101751]; 2001 [DIRS 161864]). Flow and reactiontransport equations are solved 
sequentially (Steefel and Lasaga 1994 [DIRS 101480], p. 550). Equations for mineralchemical 
equilibrium, kinetic rates, and permeabilityporosity changes are given further below. 

The setup of mass-action and mass-balance equations in TOUGHREACT is similar to the 
formulation implemented by Reed (1982 [DIRS 117901], pp. 514 to 516). Additional provisions 
are made for mineral dissolution and precipitation under kinetic constraints and a 
volume-dependent formulation for gas equilibrium, as described below. The chemical system is 
described in terms of primary aqueous species (the independent variables). Minerals, gases, and 
secondary aqueous species are defined in terms of reactions involving only the primary species. 
It has been shown that if the diffusivities of all aqueous species are equal, only the transport of 
primary species (in terms of total dissolved concentrations) needs to be considered to solve the 
entire reactive flow/transport problem (Steefel and Lasaga 1994 [DIRS 101480], p. 546). 

The system of nonlinear equations describing chemical mass-balance, mass-action, and 
kinetic-rate expressions is solved by a Newton-Raphson iterative procedure. In TOUGHREACT 
V2.2 (LBNL 1999 [DIRS 153219]), activity coefficients of aqueous species are computed by an 
extended Debye-Hckel equation (Drever 1997 [DIRS 140067], p. 28, Equation 2-12). In 
TOUGHREACT V2.2 (LBNL 1999 [DIRS 153219]), activity coefficients of neutral species are 
assumed equal to one, and the activity of water is computed using a method described by Garrels 
and Christ (1990 [DIRS 144877], pp. 64 to 66), which essentially equates the water activity to its 
mole fraction. These methods are generally reliable for ionic strengths up to 2 molal. In 
TOUGHREACT V2.3 (LBNL 2001 [DIRS 153101]), V2.4 (LBNL 2001 [DIRS 160880]), and 
V3.0 (LBNL 2002 [DIRS 161256]), activity coefficients of charged species and the activity of 
water are calculated with the method of Helgeson et al. (1981 [DIRS 106024], Equations 298, 
190, 106, and Tables 1, 3, 29, and 30), as further described by Wang (2003 [DIRS 161665], 
Notebook SN-LBNL-SCI-112-V2, pp. 21 to 27). Using this method, activities of water and 
activity coefficients of electrolytes typical of natural systems (NaCl, CaCl2, Mg2SO4, Ca2SO4) 
are fairly well reproduced up to ionic strengths of 6 molal (Wang 2003 [DIRS 161665], 
Notebook SN-LBNL-SCI-112-V2, pp. 28 to 30 and 32). In TOUGHREACT V2.3 (LBNL 2001 
[DIRS 153101]), V2.4 (LBNL 2001 [DIRS 160880]), and V3.0 (LBNL 2002 [DIRS 161256]), 

MDL-NBS-HS-000001 REV 04 6-23 February 2005 


Drift-Scale THC Seepage Model 

activity coefficients of selected neutral species are calculated using salting-out coefficients as 
described by Langmuir (1997 [DIRS 100051], Equation 4.62 and Table 4.1-4). 

Equilibration with mineral phases is computed by adding a mass-action equation, for each 
saturated mineral, into the system of nonlinear equations as follows: 

log(Ki ) =log(Qi ) (Eq. 6.4-1) 

where Ki denotes the equilibrium constant and Qi the product of the ion activities in the reaction 
that expresses mineral i in terms of the primary aqueous species. A term representing the 
amount of primary aqueous species consumed or produced by equilibration of minerals is added 
to the mass-balance equation for each primary species involved in mineral reactions, and this 
term is solved simultaneously with the concentrations of all primary species. Minerals thus 
dissolve if log (Qi/Ki) < 0 and precipitate if log (Qi/Ki) > 0. For some minerals (Section 6.4.3, 
calcite), a supersaturation gap can be specified by which the mineral is not allowed to 
precipitate if log (Qi/Ki) is greater than zero but less than a specified gap value (positive). This 
gap can be set to decrease exponentially with temperature, as described by Wang (2003 
[DIRS 161665], Notebook SN-LBNL-SCI-112-V2, p. 33). 

Gas species, such as CO2, are treated as ideal mixtures of gases in equilibrium with the aqueous 
solution. A mass-action equation is added to the system of simultaneous equations for each 
saturated gas present, except for H2O vapor and air, which are handled separately through the 
flow module in TOUGHREACT. The gas mass-action equation takes the form: 

log(Ki ) =log(Qi ) - log(Pi ) (Eq. 6.4-2) 

where Pi is the partial pressure of gaseous species i. Pi is first calculated from the 
advective-diffusive gas transport equation in TOUGHREACT. Then Pi is replaced with the ideal 
gas law, 

Pi =ni RT 
(Eq. 6.4-3) 

V

g 

where ni denotes the number of moles of gas species i, R is the gas constant, T is the absolute 
temperature, and Vg is the gas total volume. By expressing Vg in terms of the gas saturation Sg, 
the porosity of the medium f, and the volume of each grid block in the flow model Vblock, 
Equation 6.4-3 is rewritten as: 

Pi =ni RT 
(Eq. 6.4-4) 
VblockfSg 

The gas saturation is computed in the flow module of TOUGHREACT (reflecting H2O and air 
partial pressures computed in this module). The amount of trace gas species (ni/Vblock) is then 

MDL-NBS-HS-000001 REV 04 6-24 February 2005 


Drift-Scale THC Seepage Model 

obtained by substitution of Equation 6.4-4 into Equation 6.4-2 and solving together with the 
concentrations of all primary species. 

The partial pressures of trace gas species are not fed back to the multiphase flow module of 
TOUGHREACT V2.2 (LBNL 1999 [DIRS 153219]) and V2.3 (LBNL 2001 [DIRS 153101]) for 
solving the water and gas flow equations. Therefore, this method should only be applied to gases 
(excluding H2O and air) with partial pressures significantly lower than the total gas pressure. No 
absolute cutoff exists at which this approximation breaks down, and therefore it is validated by 
comparison to DST-measured CO2 concentrations. For cases where the partial pressures of a 
trace gas become closer to the total pressure, chemical equilibrium with the aqueous phase is 
computed correctly, but the gas pressure will be underestimated in the mass-balance equation 
solved for gas flow. Because CO2 concentrations encountered in the DST and model simulations 
are generally less than a few percent, and rarely over 10 percent, this model for the gas species is 
a reasonable approximation for this particular system (Section 6.4.6). 

6.4.2 Kinetic Rate Laws 
Rates of mineral dissolution and precipitation close to equilibrium can be described via a 
relationship of the rate to the saturation index (Q/K) as follows (Steefel and Lasaga 1994 

[DIRS 101480], p. 540): 

-1-1 ..Q .. p

Rate(mol s kgwater ) = sgn..
log..
K ..
.. 
kA. 
i 
ai 

n

..Q .m . 

 (Eq. 6.4-5) 

..

.. K ..-1 
..

where ai is the activity of each inhibiting or catalyzing species, and p is an empirically 
determined exponent, and the variable A is the reactive surface area expressed in units of 

2

mmineral / kgwater . The rate constant k (in mol m2 s1) is given as (Steefel and Lasaga 1994 

[DIRS 101480], p. 541): 

.-E. 11 .. 

a

k = k0 exp. . - .. (Eq. 6.4-6) 

. R . T 298.15..

where the temperature dependence of reaction rate is related to the activation energy (Ea) in units 
of kJ/mol, and T is the temperature in Kelvin units. Following Steefel and Lasaga (1994 
[DIRS 101480], p. 568), by neglecting the effect of pH or other aqueous species activities on 
reaction rates, p=0 is set for each species so that the product . aip = 1 has been eliminated from 

i 

Equation 6.4-5. The ratio of the species activity product (Q) and the equilibrium constant (K) 
describes the extent to which a mineral is in disequilibrium with a given solution composition. 
For Q/K equal to one, the mineral is at equilibrium, and thus the net rate of reaction becomes 
zero. For Q/K greater than one, the mineral is oversaturated and thus the rate becomes negative. 
The expression sgn [log(Q/K)] ensures that the correct sign is enforced when the exponents m 
and n are not equal to one. The variable A is the reactive surface area expressed in units of 

2

mmineral / kgwater . In the case of ideal solutions, the saturation index of the solid solution is 

MDL-NBS-HS-000001 REV 04 6-25 February 2005 


Drift-Scale THC Seepage Model 

calculated as the sum of the saturation indices of the individual end members, and the reaction 
rate of the solid solution is calculated as described by Wang (2003 [DIRS 161665], Notebook 
SN-LBNL-SCI-112-V2, pp. 37 to 40). 

Carroll et al. (1998 [DIRS 124275], p. 1,379) noted that the calculated rates of amorphous silica 
precipitation, based on research by Rimstidt and Barnes (1980 [DIRS 101708], p. 1,683), are 
about three orders of magnitude lower than those observed in geothermal systems. Carroll et al. 
(1998 [DIRS 124275], p. 1,379) presented experimental data on amorphous silica precipitation 
for more complex geothermal fluids at higher degrees of supersaturation, and also for a near-
saturation simple fluid chemistry. Under far from equilibrium conditions, the rate law for 
amorphous silica precipitation has been expressed as (Carroll et al. 1998 [DIRS 124275], 

p. 1,382): 
m

QkA...
..
.


1

-
Q/KThis rate does not tend to zero as goes to one; therefore, a modification has been made to 
Q/Kthis law so that it tends to zero as approaches one (Wang 2003 ([DIRS 161665], Notebook 

SN-LBNL-SCI-109-V1, p. 45) as follows: 

-

11 

1 

water 

-

Rate(mol s

kg 

)


 (Eq. 6.4-7) 

=


K


.

. 

..
. 

.....

....
.


.
. 

m 

1

.-

Q
- 

water

Rate(mol s 

kg 

kA

)


 (Eq. 6.4-8) 

=


K


2m 

KQ
...


..
.


This rate law applies only to silica precipitation. For silica dissolution, the rate law expressed in 
Equation 6.4-8 is used. Rate constants for the two cases are different (Table 4.1-3). 

Over a finite time step (.t), the change in the concentration of each primary species j on account 
of mineral precipitation or dissolution under kinetic constraints is computed from the sum of the 
rates, ri, of all j-containing minerals i as follows: 

.Cj =-Sri.ij .t (Eq. 6.4-9) 

where .ij is the stoichiometric coefficient of component j in mineral i. These concentration 
changes are incorporated into the mass-balance equation of each primary species involved in 
mineral reactions, using Equations 6.4-5 through 6.4-7, and solved simultaneously with the 
concentrations of all primary species. 

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6.4.3 Fracture and Matrix Mineral Reactive Surface Areas 
6.4.3.1 Fracture Mineral Reactive Surface Areas 
Reactive surface areas of minerals on fracture walls have been calculated from the 
fracture-matrix interface area/volume ratio, the fracture porosity, and the derived mineral volume 
fractions. The fracture-matrix interface areas and fracture porosities for each unit have been 
taken from appropriate calibrated properties sets (Table 4.1-1). These areas are based on the 
fracture densities, fracture porosities, and mean fracture diameter. The wall of the fracture is 
treated as a surface covered by mineral grains having the form of uniform hemispheres. The 
grain diameter and spatial density are not included in this calculation, so that the area is actually 
only marginally greater than the fracture geometric surface area. An alternative method to 
approximating the surface area in excess of the geometric area would be to include a roughness 
factor. The geometric surface area of the fracture wall can be approximated by: 

pAf-m

Ar = (Eq. 6.4-10) 
2ff -m

where Ar is the reactive surface area ( m2/m3fracturemedium), Af-m is the fracture-matrix interface 

23

area/volume ratio ( mfracture / mfracture+matrix volume), and ff-m is the fracture porosity of the rock. Af-m 

is the surface area used as input to the model simulations as an approximation of the reactive 
surface area. This model for the fracture surface area considers that the areal coverage is 
approximately equivalent to the mineral volume fraction. A further modification, which was 
implemented in TOUGHREACT V2.3 (LBNL 2001 [DIRS 153101]), relates the 
three-dimensional cross-sectional area to the two-dimensional surface area in the fracture, which 
yields a factor of 3/2, i.e., an increase of 50 percent in the reactive surface area. This relation 
was used for all previous DST THC model REV01 sensitivity studies, Tptpmn, and Tptpll THC 
simulations. 

The reactive surface area of each mineral (in units of m2/ kg ) used in Equations 6.4-5

mineral water 

and 6.4-8 is then given by: 

Ai (m2/ kgwater) = Ar fi (Eq. 6.4-11) 
.wff 

where fi is the volume fraction of the mineral in the mineral assemblage, .w is the density of 
water (taken as a constant 1,000 kg/m3), and ff 
is the porosity of the fracture medium, as opposed 
to the fracture porosity of the rock. This is the surface area/water mass ratio for a mineral in a 
liquid-saturated system. Calculated volume fractions of minerals for the current model are 
tabulated in Appendix A. 

To provide the correct rock/water ratio in an unsaturated system, the form of this surface area 
can be written as: 

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Drift-Scale THC Seepage Model 

Ai (m2/ kgwater) = Ar fi (Eq. 6.4-12) 
.wf f Sw 

where Sw is the water saturation. However, as Sw goes to zero, the reactive surface area would 
tend to infinity. Clearly, at a very low liquid saturation, the surface area of the rock contacted by 
water is likely much smaller than the total area. 

Two methods have been implemented to address this phenomenon. The first method considers 
that the surface area contacted by water diminishes proportionately to the saturation. This yields 
the saturated surface area given by Equation 6.4-10. The second method employs the 
active-fracture-model concept (Liu et al. 1998 [DIRS 105729], pp. 2,636 to 2,638) modified to 
consider water-rock reactions taking place below the residual saturation. The form of the active 
fracture parameter for reaction is then given by the following set of equations: 

Sar = (Sw - Sm )/(1-Sm ) (Eq. 6.4-13) 

afmr = Sar 
(1+. ) (Eq. 6.4-14) 

where Sm is the minimum liquid saturation for which water-rock reactions are considered and Sar 
is the effective saturation available for reaction. The active fracture parameter, ., is obtained 
from the calibrated hydrologic property set (DTN: LB0208UZDSCPMI.002 [DIRS 161243]). 
The factor that reduces the surface area contacted by the water phase is given by afmr. In all 
simulations Sm is set to the very small saturation of 1  105 to ensure that reactions take place 
until virtually no water is left (e.g., during dryout via ventilation or heating). Finally, the 
reactive surface area, using this modified form of the active fracture model, is given by: 

Ai (m2/kg water) = 
fiAra fmr (Eq. 6.4-15) 
.wf fSw 

The surface area calculated in this way is applicable only to reactions taking place in the fracture 
medium and is used directly in Equations 6.4-5 and 6.4-8. Note that this area is not comparable 
to the input surface areas that are listed in Appendix B. 

In the dual permeability method, the porosity of the fracture medium can be taken as 1.0; 
however, for modeling of mineral dissolution and precipitation, there would then be no rock to 
dissolve. Because the dissolution rates of many minerals are quite slow at temperatures below 
100C, only a small volume of rock adjoining the open space of the fracture needs to be 
considered as the starting rock fraction. In the REV01 Tptpmn THC model, the porosity of the 
fracture medium was set to 0.99, thus making available 1 percent of the total fracture volume for 
reaction. In the REV01 Tptpll THC model, and in all current THC seepage model simulations, 
the fracture medium porosity is set to 0.5 (Section 6.4.6). 

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6.4.3.2 Matrix Mineral Reactive Surface Areas 
Mineral surface areas in the rock matrix (Appendix B) are taken from DTNs shown in 
Table 4.1-1. These values have been estimated using the geometric area of a cubic array of 
truncated spheres that make up the framework of the rock. Clay minerals are considered as 
coatings of plate-like grains. The mineral surface areas of framework grains (truncated spheres) 
in contact with the open pore space are calculated using an initial grain diameter, followed by 
successive truncation of the grains in the vertical direction until the porosity of this system is 
close to the measured porosity of the rock. In the welded tuff, crystals are often tightly 
intergrown with little or no pore space within the aggregate. Thus, a check is made so that the 
resultant mean pore throat size and spacing yields a permeability (from a modified 
Hagen-Poiseuille relation) (Ehrlich et al. 1991 [DIRS 117799], p. 1,582, Equation 11) that is 
relatively close to the measured saturated permeability. 

The grains forming the framework of this rock are considered to be the primary high-temperature 
phases of the tuff (i.e., quartz, cristobalite, tridymite, and feldspars). The abundance of 
secondary phases (i.e., those that formed as alteration products or low-temperature coatings on 
the primary assemblage), such as clay minerals, are used to reduce the free surface area of the 
framework grains. The surface areas of the secondary phases are approximated using a tabular 
morphology. 

6.4.4 Effects of Mineral Precipitation/Dissolution on Hydrologic Properties 
6.4.4.1 Porosity Changes 
Changes in porosity and permeability resulting from mineral dissolution and precipitation have 
the potential to modify percolation fluxes and seepage fluxes at the drift wall. In this analysis, 
porosity changes in matrix and fractures are directly tied to the volume changes that result from 
mineral precipitation and dissolution. The molar volumes of hydrous minerals, such as zeolites 
and clays, created by hydrolysis reactions with anhydrous phases, such as feldspars, are 
commonly larger than those of the primary reactant minerals. Therefore, constant molar 
dissolution-precipitation reactions can lead to porosity reductions. These changes are taken into 
account in this analysis. The porosity of the medium (fracture or matrix) is given by 

nm 

f=1-. frm - fru (Eq. 6.4-16) 

m=1 

where nm is the number of minerals, frm is the volume fraction of mineral m in the rock 
(Vmineral/Vmedium, including porosity), and fru is the volume fraction of nonreactive rock. As the 
frm of each mineral changes, the porosity is recalculated at each time step. The porosity is not 
allowed to go below zero. 

6.4.4.2 Fracture Permeability Changes 
Fracture permeability changes can be approximated using the porosity change and considering 
plane parallel fractures of uniform aperture (cubic law) (Steefel and Lasaga 1994 

MDL-NBS-HS-000001 REV 04 6-29 February 2005 


Drift-Scale THC Seepage Model 

[DIRS 101480], p. 556). If the fracture spacing and density remain constant, the updated 
permeability, k, is given by 

.f.3k =ki. . (Eq. 6.4-17) 
.fi . 

where ki and fi 
are the initial permeability and porosity, respectively. This law yields zero 
permeability only under the condition of zero fracture porosity. 

In most experimental and natural systems, permeability reductions to values near zero occur at 
porosities significantly greater than zero. This generally is the result of mineral precipitation 
preferentially closing the narrower interconnecting apertures. The hydraulic aperture, as 
calculated from the fracture spacing and permeability (as determined through air-permeability 
measurements) using a cubic law relation, is a closer measure of the smaller apertures in the flow 
system. Using the hydraulic aperture, a much stronger relationship between permeability and 
porosity can be developed. This relationship can be approximated as follows: 

The initial hydraulic aperture b0,h (m) is calculated using the following cubic law relation: 

3

b0,h =[12k0s]1 (Eq. 6.4-18) 

where k0 is the initial fracture permeability (m2) and s is the fracture spacing (m) for a single 
fracture set. The permeability (k ) resulting from a change in the hydraulic aperture is given by 

(b0,h +.b)3 

k'= (Eq. 6.4-19) 

12s

where .b is the aperture change resulting from mineral precipitation/dissolution. The aperture 
change resulting from a calculated volume change can be approximated by assuming 
precipitation of a uniform layer over the entire geometric surface area of the fracture, assuming 
also that this area (as well as the fracture spacing) remains constant. In geologic systems, the 
actual distribution of mineral alteration is much more heterogeneous and depends on many 
factors that are active at scales much smaller than the resolution of the model. The combined 
effect of the initial heterogeneities and localized precipitation processes can only be treated 
through model sensitivity studies and experiments. The initial aperture available for 
precipitation (bg, the geometric, rather than the hydraulic, aperture) can be calculated (Appendix 
F) from the ratio of the initial fracture porosity (ff,0) to the fracture surface area (Af), as follows: 

bg =
ff ,0 
Af 
(Eq. 6.4-20) 

For a dual-permeability model, changes in the fracture porosity are calculated based on the 
porosity of the fracture medium so that .b can be approximated by: 

MDL-NBS-HS-000001 REV 04 6-30 February 2005 


Drift-Scale THC Seepage Model 

(f' fm -f fm,0 )

.b = bg (Eq. 6.4-21) 
f fm,0 

Equations 6.4-18, 6.4-19, and 6.4-21 were implemented in TOUGHREACT V2.3 (LBNL 2001 
[DIRS 153101]) and successive versions, with input parameters of bg and s. This relation was 
used for sensitivity studies in the REV01 Tptpmn THC model simulations discussed in Section 

6.3 (heterogeneous and homogeneous permeability fields), REV01 and current Tptpll THC 
model simulations, and REV01 and current DST THC model simulations. 
6.4.4.3 Matrix Permeability Changes 
Matrix permeability changes are calculated from changes in porosity using ratios of 
permeabilities calculated from the Carman-Kozeny relation (Bear 1988 [DIRS 101379], p. 166, 
Equation 5.10.18, symbolically replacing n by f), and neglecting changes in grain size, 
tortuosity, and specific surface area as follows: 

(1-fi )2 . f.3

k = ki . . (Eq. 6.4-22) 

(1-f)2 .fi . 

6.4.4.4 Effects of Permeability and Porosity Changes on Capillary Pressures 
Changing permeability and porosity also results in changes in the unsaturated flow properties of 
the rock. These effects are treated by modifying the calculated capillary pressure (Pc) using the 
Leverett scaling relation (Slider 1976 [DIRS 128146], p. 280) to obtain a scaled Pc as follows: 

Pc'= Pc 
kk 
f 
if 
i 
(Eq. 6.4-23) 

Simulations performed with TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]) have the 
maximum value of Pc (Equation 6.4-23) limited by the cutoff prescribed in the input file. All 
developmental simulations, done using earlier TOUGHREACT versions, have the cutoff apply 
to Pc (not Pc) in Equation 6.4-23 unless an extrapolation in the Pc-saturation curve was 
performed, in which case no cutoff was applied. Capillary pressure cutoff values used in various 
model revisions are discussed in Section 6.4.6 (Approximation 15). 

6.4.5 Mineral Precipitation in Dry Grid Blocks 
In certain cases of evaporation or boiling, a grid block may experience an influx of water that 
evaporates completely during the solution of the flow equations. After the flow equations are 
solved, TOUGHREACT solves the transport equations followed by the speciation and reaction 
equations. The speciation and reaction equations require that the grid block is wet; that is, the 
liquid saturation is greater than zero (or a small value). Because of the lack of water in the grid 
block, a method has been developed for storing all residual aqueous species in a solid salt 
assemblage. 

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Drift-Scale THC Seepage Model 

The amount of solute stored is simply the product of the concentration in the upstream grid 
block and the flux of water into the grid block that dries out. Also, any water that is initially 
present in the grid block, and dries out, gives rise to some solute mass that is transformed into 
solid phases. For these cases, the mass of each primary solute species is saved and may be 
assigned to minerals in a prescribed order in the chemical input file. This approximation is 
performed so that solute mass loss is minimized and most of the solute mass can be accounted 
for in a solid mineral phase. Simulations performed with TOUGHREACT V2.4 (LBNL 2001 
[DIRS 160880]) and V3.0 (LBNL 2002 [DIRS 161256]) have this option, whereas V2.2 (LBNL 
1999 [DIRS 153219]) and V2.3 (LBNL 2001 [DIRS 153101]) do not. 

In the simulations presented in this report, for the specific cases when water flows into grid 
blocks that dry out in the flow calculation (by boiling or evaporation), the following solid phases 
are formed, stoichiometrically and in the following order: silica, calcite, gypsum, hematite, 
fluorite, NaNO3, K2SO4, Na2SO4, MgSO4, halite, and sylvite. The order is predetermined (i.e., 
nitrates are formed before chlorides) to ensure nitrate mass is not lost in cases where insufficient 
sodium remains to form NaNO3 (in the absence of other nitrate salts that could have formed). 
The goal, here, is not to model evaporation accurately, but to save as much mass of the dissolved 
constituents as possible for grid blocks that completely dry out. 

Upon rewetting, the salt minerals (i.e., NaNO3, K2SO4, Na2SO4, MgSO4, halite, sylvite) are 
assumed to dissolve kinetically with a relatively fast rate constant (set here at 106 mol/m2/s) and 
a dissolution rate limited by their solubility (Section 6.4.2). The salt solubilities are from the 
data0.ymp.R2 database (DTN: MO0302SPATHDYN.000 [DIRS 161756]), except that NaNO3 
(not in that database) is given the solubility of KNO3 in that database. Therefore, this model 
captures the general behavior of salt dissolution as the boiling front recedes. However, the 
predicted major ion concentrations during the short time when these salts dissolve are 
approximate because the identity of the salt phases is not based on a thermodynamic 
speciation/precipitation model, and their dissolution rates are only approximate. 

6.4.6 Principal Model Approximations and Approaches 
The following modeling approximations and simplifications are used in the THC seepage model. 

1. The rock is described by a dual-permeability model (Section 6.2.1.5), which considers 
separate but interacting fracture and matrix continua, each with specified permeabilities. In 
the dual-permeability model, the fracture continuum is considered as co-located but 
interacting with the matrix continuum, in terms of the flow of heat, water, and vapor through 
advection, diffusion, and conduction (for heat). The aqueous and gaseous species are 
transported via advection and molecular diffusion between the fractures and matrix. Each 
continuum has its own well-defined initial physical and chemical properties. The 
dual-permeability approach for modeling physical processes in fractured porous media is 
discussed in detail by Doughty (1999 [DIRS 135997], pp. 76 and 77). This approach is 
validated by comparing geochemical data obtained from the DST to the results of simulations 
of the DST (Section 7.1), and further validated in Drift-Scale Coupled Processes (DST and 
TH Seepage) Models (BSC 2004 [DIRS 170338], Section 7.4). 
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Drift-Scale THC Seepage Model 

2. 
3. 
4. 
5. 
The mass of minerals precipitated is small and its thermal properties are similar to those of 
the host rock. Therefore, the thermal properties are not modified to account for precipitated 
minerals. However, the bulk heat capacity is modified to account for changes in porosity. 

Effects of changes in the partial pressure of CO2 (resulting from heating, water reaction with 
calcite, and gas-phase transport) on the density of the gas phase are neglected. This is 
justified because, in this study, CO2 generally accounts for less than 5 percent and always 
less than 10 percent of the gas phase volume (air, water, and CO2). Although the molecular 
weight of CO2 is greater than that of air (approximately 44 g/mol versus 29 g/mol), the 
density is only increased proportionally to the volume fraction of CO2 and the ratio of the 
molecular weights. This would result in a density increase of about 5 percent for a gas with a 
CO2 volume fraction of 10 percent. These conditions make the effect of evolved CO2 on the 
physical properties of the gas phase negligibly small and justify the use of this 
approximation. The effect of CO2 on the density of steam (molecular weight approximately 
18 g/mol) would be somewhat greater; however, increases in the steam fraction 
accompanying boiling would tend to dilute the CO2 fraction. 

The effects of changes in water chemistry on the water density and viscosity are neglected. 
This approximation is justified because aqueous-species concentrations are low in waters at 
most values of the liquid saturation (in the rock matrix or fractures). In cases where 
concentrations are significantly higher, the liquid saturation is generally much less than 1 
percent. Therefore, the liquid is nearly immobile because of the very small relative 
permeability for the liquid phase under such conditions. 

Diffusion coefficients of all aqueous species are set to the same value (the value for the 
chloride anion; Section 4.1.1). This is justified because the tracer diffusion coefficients of 
aqueous species differ by, at most, about one order of magnitude, with many differing by less 
than a factor of 2 (Lasaga 1998 [DIRS 117091], p. 315). The strong effects of water-rock 
interaction, boiling condensation, and rapid fracture drainage overwhelm effects of aqueous 
species diffusion. 

Diffusion coefficients for gases are calculated. In the gas phase, CO2 is the only transported 
reactive species (other than H2O vapor). For an ideal gas, the tracer diffusion coefficient of a 
gaseous species can be expressed as a function of temperature and pressure in the following 
form (Lasaga 1998 [DIRS 117091], p. 322): 

RT 8RT

D =

 (Eq. 6.4-24) 
32pPNAdm 
2 pM 

where 

D = diffusion coefficient (m2/s) 
R = gas constant (8.31451 m2 kg s2 mol1 K1) 
T = temperature in Kelvin units 
P = pressure (kg m1 s2) 
NA = Avogadros number (6.0221367  1023 mol1) 


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Drift-Scale THC Seepage Model 

dm = molecular diameter (m) 
M = molecular weight (kg/mol) 


The CO2 diffusion coefficient is calculated using input values of dm and M (Section 4.1.1). 

6. Mineral precipitation or dissolution is modeled to occur uniformly over the smooth 
plane-parallel fracture walls (Section 6.4.4.2). However, mineral precipitation could be 
non-uniform, leading to a different relationship between changes in permeability and 
porosity. This approximation can be justified by the use of bulk permeabilities and porosities 
that initially account for the net effect of variability in fracture aperture at a macroscopic 
scale. Furthermore, effective (hydraulic) apertures are used instead of true apertures, the 
latter being much larger (Section 6.4.4.2). As a result, the permeability change is quite 
sensitive to porosity changes (in this study, a 10 to 14 percent drop in fracture porosity leads 
to zero permeability in fractures in the modeled repository units). 
7. CO2 gas is treated as an ideal gas (i.e., obeys the ideal gas law and its partial pressure equals 
its fugacity). This approximation is valid for the low ambient pressures (near atmospheric) 
considered in this study (Langmuir 1997 [DIRS 100051], p. 15). 
8. Except for smectites, the chemical and physical properties of minerals that form solid 
solutions are approximated by their individual end-member compositions and properties. 
Because smectite end-members are (individually) near equilibrium with pore waters, some of 
the smectite end members could be calculated to precipitate while others dissolve. For this 
reason, an ideal solid-solution model is implemented for smectite (Na, Ca, and Mg 
end-members), with each end-members activity equaling its mole fraction. Treating the 
smectite as a solid solution results in individual smectite end-members either all dissolving or 
all precipitating, providing a better physical representation of dissolution/precipitation 
processes. Feldspar solid solutions are not considered because albite (Na-feldspar) and 
anorthite (Ca-feldspar) are generally strongly undersaturated in the simulations and, thus, 
their dissolution rates are governed primarily by the kinetic-rate constant rather than the 
saturation index (Equation 6.4-5). In addition, nearly pure secondary K-feldspar 
compositions are observed in geothermal systems (Stefnsson and Arnrsson 2000 
[DIRS 153578], p. 2,578). Therefore, the precipitation of secondary K-feldspar can be 
approximated fairly well with a pure end-member. These approximations are further 
validated by comparison of model results to measured water chemistry in the DST (Section 
7.1). 
9. The fracture continuum is modeled with grid blocks having an initial fraction of void space 
less than one (0.5 in the current THC seepage model for the Tptpll unit). This value is 
chosen such that the fracture medium always contains solids that can react with fluids in 
fractures. It is verified that there is always enough solid initially present in the fracture 
continuum to avoid the possibility that some of the primary rock forming minerals become 
exhausted (through dissolution). Note that the volume of each grid block assigned to the 
fracture continuum is then calculated in such a way that the true fracture porosity (i.e., the 
fraction of the bulk rock occupied by fracture void space) is always reproduced. 
MDL-NBS-HS-000001 REV 04 6-34 February 2005 


Drift-Scale THC Seepage Model 

10. The thermal conductivities of fracture and matrix grid blocks are calculated assuming a linear 
interpolation between dry and wet conductivities as a function of liquid saturation. These are 
the thermal conductivities for the solid + fluid system. For fractures, thermal conductivities 
are multiplied by the fracture porosity to account for the correct fracture-to-fracture 
connection area in calculations of heat conduction (i.e., this is needed because full grid block 
areas are input into the model). Fracture thermal conductivities are also multiplied by 0.1 (an 
arbitrary value less than 1) to account for the limited spatial continuity and connectivity 
between fracture grid blocks. The volume of the fracture continuum is, however, only a 
small fraction of the matrix continuum. Therefore, heat conduction occurs primarily through 
the matrix continuum and, as a result, the model is not sensitive to the amount of heat 
conduction in fractures. This linear interpolation approach to determine bulk thermal 
conductivities is discussed and validated in Thermal Conductivity of the Potential Repository 
Horizon (BSC 2004 [DIRS 169854], Sections 7.4.1 and 7.4.2). 
11. Vapor-pressure lowering due to capillary pressure (the Kelvin effect) is implemented in 
simulations carried out for this current model revision (Sections 6.5 and 7.1). The impact of 
including or neglecting this effect is evaluated in Section 6.5.5.3. 
12. Hydrogeologic rock properties in each hydrogeologic unit of the model are approximated as 
being laterally homogeneous. In the Tptpmn Heterogeneous THC model, an earlier, alternate 
conceptualization (Section 6.3), the natural heterogeneity in fracture permeability (4 orders 
of magnitude) was assumed. Results of the Tptpmn Heterogeneous THC model did not show 
significantly different water chemistry in either space or time when compared to the 
homogeneous model. Furthermore, good comparisons are obtained between modeled and 
measured water and gas chemistry for the DST, assuming homogeneous properties (Section 
7.1). 
13. The capillary pressure in both fractures and matrix must reach some maximum, finite value 
upon complete dryout (zero liquid saturation). The default limit in the THC seepage model 
and the DST THC submodel is set to 108 Pa. For fractures and matrix in the Tptpmn, Tptpll, 
and Tptpln lithostratigraphic units (model units tsw34, tsw35, and tsw36, respectively), the 
limit is set, as previously, by the calculated slope of the Pcap versus liquid saturation curve at 
a liquid saturation value equal to Sr + e. For these units, e values for the matrix yield 
maximum Pcap values of 108 Pa (Table 6.4-1); for fractures, e is set to 0.01 as done for 
REV01 simulations (maximum Pcap values around 103 to 104 Pa). 
14. Open spaces in the drift are approximated as a porous medium with a large permeability 
(109 m2) greater than in surrounding rocks, but not so large as to create numerical difficulties 
when computing flow. In addition, these open spaces are modeled with no capillarity, unit 
porosity, and no residual saturation except directly against the drift wall (arbitrary small 
value of 0.01 to account for some water condensation, if any, against the drift wall). These 
approximations are made because the mathematical model is not formulated to accurately 
treat fluid flow in non-porous media. The sensitivity to the chosen permeability value for the 
porous medium has been evaluated for in-drift RH and temperature in Multiscale 
Thermohydrologic Model (BSC 2004 [DIRS 169565], Section 6.3.10) and found to be 
insignificant. 
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Drift-Scale THC Seepage Model 

15. The fracture tortuosity value of 0.7 (Section 4.1.1.1) has been adopted for use with thermal 
and diffusive transport parameters of lithologic units. This value is based on experimental 
determinations of tortuosity in soils having various porosities (Penman 1940 [DIRS 109941], 
pp. 441 to 461), and also corresponds to the highest tortuosity value given by de Marsily 
(1986 [DIRS 100439], p. 233). The rationale for this value is that fracture tortuosity should 
be high compared to matrix tortuosity (i.e., less tortuous path in fractures than in the matrix). 
This fracture tortuosity is modified for fracture-fracture connections by multiplication of the 
tortuosity by the fracture porosity of the bulk rock. This operation yields a better 
approximation for the fracture-to-fracture interconnection area (only for calculation of 
diffusive fluxes; the entire grid block connection area is used for calculating advective fluxes, 
because the bulk fracture permeability of the entire grid block is entered into the model). 
16. An estimated matrix tortuosity of 0.2 is assumed to be applicable to the tuff matrix at Yucca 
Mountain. This is in the lower part of the parameter range given by de Marsily (1986 
[DIRS 100439], p. 233), consistent with the much finer pore size in the matrix. The 
tortuosity is a factor applied along with the porosity and the saturation to the diffusion 
coefficient. Common matrix tortuosity values only cover a span of about one order of 
magnitude, so this value has a very limited effect on reaction-transport processes. A 
tortuosity of 0.7 is assumed for the invert for similar reasons as described for the matrix 
fracture permeability above. The invert is coarse granular material and its tortuosity would 
be expected to be between 0.7 and 1.0. The tortuosity of sand is about 0.7 (de Marsily 1986 
[DIRS 100439], p. 233). These values only slightly affect diffusive transport of CO2 in the 
drift. Because reactions involving CO2 are minimal in the drift, the diffusivity of CO2 within 
in-drift components has a negligible effect on THC processes outside of the drift. 
17. The satiated saturation is the maximum liquid saturation before saturated flow conditions are 
reached (i.e., at which the capillary pressure reaches zero). It is typically given the value of 1 
(fully saturated conditions), and is the same as Smax. 
18. The drift wall is open to all fluid fluxes. No specific boundary conditions of pressure, 
relative humidity, or gas compositions are applied inside the drift (i.e., as if the repository is 
sealed off, and neglecting sources or sinks of CO2 due to microbial activity or atmospheric 
CO2). Computing fluid flow through open spaces of the drift using a model designed to 
calculate flow through porous media is by itself a very coarse approximation. Thus, 
modeling the drift wall as either open or closed to advective fluid flow yields equally coarse 
approximations. However, the scope of this report is to model THC processes in the 
near-field outside the drift and not in the drift itself. Comparisons between these alternatives 
are presented in Section 6.5. Note that for the open drift case used in the current THC 
seepage model, the invert is allowed to react with any water present in it (pore water or 
condensation). 
6.4.7 Summary of Hydrologic and Thermal Properties 
The hydrologic and thermal properties of repository units used in simulations presented in the 
following sections of this report are summarized in Table 6.4-1. Sources of properties used for 
all modeled hydrogeological units and other input data are listed in Sections 4.1 and 6.4.8. 

MDL-NBS-HS-000001 REV 04 6-36 February 2005 


Drift-Scale THC Seepage Model 

6.4.8 Thermodynamic Data Sensitivity 
Simulations of ambient conditions (i.e., without thermal loading, under natural geothermal 
gradient, and without drift opening) have been run using alternative thermodynamic data sets to 
evaluate the model sensitivity to these data (Section 6.5.5.1) and to justify the thermodynamic 
data (Set 1, below) selected for THC seepage model simulations that provide feeds to 
downstream models. The following three sets of data are used for these ambient simulations: 

Set 1 

This is the thermodynamic data set adopted for all current THC seepage model simulations 
(DTN: LB0307THMDBRTM.001 [DIRS 164434]) (Appendix C) and is discussed in 
Section 4.1.4. 

Set 2 

This thermodynamic data set contains all data from the YMP thermodynamic database 
data0.ymp.R2 (DTN: MO0302SPATHDYN.000 [DIRS 161756]), except for necessary changes 
to data for a few minerals (not prevalent in the vicinity of the drift) as described below (Wang 
2003 [DIRS 161665], SN-LBNL-SCI-141-V2, pp. 158 to 160). 

Heulandite in database data0.ymp.R2 contains significant amounts of barium and strontium. 
These chemical components are not considered in this study. For this reason, the data from 
database data0.ymp.R2 for heulandite could not be used. Instead, log(K) values used in Set 2 for 
heulandite are taken as the uncorrected log(K) values given in DTN: LB0307THMDBRTM.001 
[DIRS 164434] (heuland/10 in Appendix C). The source of these data and the calculation 
methods are the same as those used for the stellerite log(K) values in the data0.ymp.R2 database 
(DTN: MO0302SPATHDYN.000 [DIRS 161756]). 

For clinoptilolite, log(K) values are taken for the mineral identified as clinoptilolite-Ca in 
database data0.ymp.R2 because this phase has a similar composition to the phase used in Set 1. 
However, this phase contains a very small amount of iron, which is not included in the 
clinoptilolite in Set 1. By using this phase, the already very small amount of iron in the aqueous 
phase is completely depleted, causing chemical convergence problems in simulations. For this 
reason, iron has been removed from this phase. It was not deemed necessary to recompute 
log(K) values because the amount of iron in this phase is very small (approximately 0.1 percent 
stoichiometric proportion of Fe relative to Si). 

No other changes have been made to the data0.ymp.R2 database for Set 2. For calcium, 
magnesium, and sodium smectites, the phases identified as montmorillonite-Ca, 
montmorillonite-Mg, and montmorillonite-Na in the data0.ymp.R2 database are used. For 
potassium feldspar, the phase identified as maximum_microcline is used. Glass data from Set 1 
are included in Set 2 because no glass data are included in the data0.ymp.R2 database. Note that 
if a mineral is specified with different unit cell stoichiometries in Set 1 and Set 2 (i.e., some clays 
and zeolites), the kinetic rate of that mineral (Section 4.1.3) has been corrected to account for the 
same stoichiometric Si release (or consumption) per unit time for consistency between data sets. 

MDL-NBS-HS-000001 REV 04 6-37 February 2005 


Drift-Scale THC Seepage Model 

Set 3 

This set is identical to Set 2 (data0.ymp.R2 database), except that all zeolite thermodynamic data 
are taken from Set 1 (minerals identified as mord/10-r02, heul/10-r02, stell/10-r02, and 
clpt/10-r02 in Appendix C). 

Table 6.4-1. Summary of Hydrologic and Thermal Properties of Repository Units 

Model Layer > 
Lithostratigraphic Unit > 
tsw33 
Tptpul 
tsw34 
Tptpmn 
tsw35 
Tptpll 
MATRIX DATA DTN: 
permeability km (m2) 6.57E-18 1.77E-19 4.48E-18 LB0208UZDSCPMI.002 [DIRS 161243] 
porosity fm 0.1425 0.1287 0.1486 LB0210THRMLPRP.001[DIRS 160799] 
van Genuchten a a m (1/Pa) 6.17E-6 8.45E-6 1.08E-5 LB0208UZDSCPMI.002 [DIRS 161243] 
van Genuchten m (or .) mm 0.283 0.317 0.216 LB0207REVUZPRP.002 [DIRS 159672] 
(file matrix_props.xls) 
residual saturation Slrm 0.12 0.19 0.12 LB0207REVUZPRP.002 [DIRS 159672] 
(file matrix_props.xls) 
satiated saturation Slsm 1.00 1.00 1.00 LB0207REVUZPRP.002 [DIRS 159672] 
(file matrix_props.xls) 
epsilon (for max Pcap) e 0.138 0.091 0.216 Yield maximum Pcap = 108 Pa 
(Section 6.4.6) 
rock grain density .g (kg/m3) 2358 2466 2325 LB0210THRMLPRP.001[DIRS 160799] 
rock grain specific heat Cp (J/kg-K) 985 985 985 LB0210THRMLPRP.001[DIRS 160799] 
dry conductivity .dry (W/m-K) 1.164a 1.419a 1.278a LB0210THRMLPRP.001[DIRS 160799] 
wet conductivity .wet (W/m-K) 1.675a 2.074a 1.890a LB0210THRMLPRP.001[DIRS 160799] 
tortuosity t 0.2 0.2 0.2 Assumed (Section 6.4.6) from range of 
accepted values (de Marsily 1986 
[DIRS 100439]) 
FRACTURE DATA 
b 
permeability kf (m2) 7.80E-13 3.30E-13 9.10E-13 LB0205REVUZPRP.001[DIRS 159525] 
porosity (Tptpll Model) ff 5.8E-3 8.5E-3 9.6E-3 LB0205REVUZPRP.001[DIRS 159525] 
van Genuchten a a f (1/Pa) 1.59E-3 1.04E-4 1.02E-4 LB0208UZDSCPMI.002 [DIRS 161243] 
van Genuchten m (or .) mf 0.633 0.633 0.633 LB0205REVUZPRP.001[DIRS 159525] 
residual saturation Slrf 0.01 0.01 0.01 LB0205REVUZPRP.001[DIRS 159525] 
satiated saturation Slsf 1.00 1.00 1.00 LB0205REVUZPRP.001[DIRS 159525] 
active fracture parameter gamma 0.60 0.57 0.57 LB0208UZDSCPMI.002 [DIRS 161243] 
frequency f (1/m) 0.81 4.32 3.16 LB0205REVUZPRP.001[DIRS 159525] 
fracture to matrix area A (m2/m3) 4.44 13.54 9.68 LB0205REVUZPRP.001[DIRS 159525] 

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Drift-Scale THC Seepage Model 

Table 6.4-1. Summary of Hydrologic and Thermal Properties of Repository Units (Continued) 

Model Layer > 
Lithostratigraphic Unit > 
tsw33 
Tptpul 
tsw34 
Tptpmn 
tsw35 
Tptpll 
FRACTURE DATA 
b 
(Cont.) 
tortuosity t 0.7 0.7 0.7 (Penman 1940 [DIRS 109941], pp. 441 
and 461) 
epsilon (for max Pcap) e 0.01 0.01 0.01 Model Setup (Section 6.4.6) 

a 

Bulk conductivities converted from grain conductivity values and lithophysal porosities listed in the DTN are shown 
using Kbulk = Kgrain (1-flith) + flith Kair, with Kair = 0.028 (W/m-K) (extrapolated at 50C from Lide 1993 
[DIRS 123032], p. 6-172). 

b Fracture thermal properties are derived using matrix properties as discussed in Section 6.4.6. 

NOTE: Also see Section 4.1.1. 

6.5 THC SEEPAGE MODEL 
Key elements of the THC seepage model include: 

 Initial heat load 1.45 kW/m (Appendix D, Section 4.1.7 and Table 4.1-6) 
 50-year preclosure period with 86.3 percent ventilation efficiency (Section 4.1.7 and 
Table 4.1-6) 
 Drift in the Tptpll unit (Section 4.1.6) 
 Model stratigraphy at a location near the center of the repository, at approximately 
Nevada State Plane coordinates E170572, N233195 (Section 4.1.6.1) 
 Use of an extended-case geochemical system that is more complex than that used in 
earlier revisions (Section 6.2.2.2) 
 Drift wall open to fluid and gas advective and diffusive fluxes (Section 6.4.6) 
 Vapor pressure lowering due to capillary pressure (Section 6.4.6 and Table 4.1-6) 
 Experimentally measured rock thermal and hydrologic properties (Section 4.1.1) 
 Thermodynamic data (Section 4.1.4 and Table 4.1-1, Appendix C) 
 Kinetic data (Section 4.1.3 and Table 4.1-3) 
 Use of TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]). This version takes into 
account the precipitation of solids in dry grid blocks where water influx occurs and, 
therefore, models more precisely the mineral deposition at the boiling front (Section 3). 
MDL-NBS-HS-000001 REV 04 6-39 February 2005 


Drift-Scale THC Seepage Model 

In addition, this revised model is used to conduct a broad range of evaluations, including 
simulations using: 

 Different input thermodynamic data (ambient conditions) (Section 6.5.5.4) 
 Five different input water compositions (Section 4.1.5, Table 4.1-4, Section 6.2.2.1, 
Table 6.2-1) 
 Fixed and variable infiltration rates (Section 4.1.1.2, Tables 4.1-1 and 4.1-2, 
Section 6.5.2, Table 6.5-3) 
 Different water-vapor-pressure models (with and without vapor-pressure lowering) 
 Two values of CO2 gas molecular diameter (resulting in a six-fold difference in the 
diffusion coefficient) (Section 6.5.3). 
For all direct input sources, see Section 4.1. 

6.5.1 Numerical Mesh (Tptpll) 
Simulations are performed on a vertical two-dimensional mesh, using a drift spacing of 81 m 
(center to center) (BSC 2004 [DIRS 168489]) and a drift diameter of 5.5 m (BSC 2004 
[DIRS 168489]). With rock properties laterally homogeneous between drifts (Section 6.4.6), this 
setup can be viewed as a series of symmetrical, identical half-drift models with vertical no-flow 
boundaries between them. Accordingly, the numerical mesh is reduced to a two-dimensional 
half-drift model with a width of 40.5 m, corresponding to the midpoint between drifts (Figure 
6.5-1). Geologic data from column j34 of the UZ99_2_3D calibration model 
(DTN: LB990501233129.004 [DIRS 111475]) have been used to map geologic contacts into the 
two-dimensional mesh, and the mesh coordinate system is set with reference to the center of the 
drift (Table 6.5-1). 

To limit grid orientation effects, the mesh design is mostly orthogonal, with a small radially 
gridded area in the immediate vicinity of the drift (Figures 6.5-1 and 6.5-2). The area extending 
approximately 40 m above the drift is more finely gridded than other areas to capture THC 
effects potentially affecting seepage into the drift. Outside the drift, the smallest grid spacing is 
specified at the drift wall (20 cm) and increased outward. A constant square cell size of 50 cm is 
used from approximately 5 m to 7 m above drift center, increased to a 1-m size until 15 m above 
drift center, then a 2-m size from 15 to 30 m above drift center. All geologic layers down to the 
water table below the modeled drift are incorporated into the numerical mesh (Table 6.5-1). 
Grid block sizes increase significantly 100 m above and below the drift to increase computing 
efficiency. The mesh consists of 3,202 grid blocks, including those representing matrix, fracture, 
and in-drift design elements. 

The drift discretization is shown in Figure 6.5-2. The drift is discretized to include the design 
elements and dimensions shown on Figure 4.1-1 (338 grid blocks total). The invert, 0.8 m thick, 
is divided into an upper invert and lower invert for assignment of different thermal 
conductivities in these zones (Section 4.1.7). The drip shield is not explicitly modeled 

MDL-NBS-HS-000001 REV 04 6-40 February 2005 


Drift-Scale THC Seepage Model 

(Section 4.1.7). The grid block size inside the drift is chosen to be small enough to provide a 
realistic drift model (compare Figure 6.5-2 to Figure 4.1-1). Two in-drift configurations are 
considered in this model: 

 Preclosure configuration (during the first 50 years): waste package, upper invert, lower 
invert, and open space between the waste package and drift wall 
 Postclosure configuration (after 50 years): waste package, upper invert, lower invert, drip 
shield, and two open zones (inner zone, between the waste package and drip shield; and 
outer zone, between the drip shield and drift wall). 
Source: DTN: LB0011DSTTHCR1.002 [DIRS 161282]. 

NOTE: Grid detail around (0, 0) is shown in Figure 6.5-2. 

Figure 6.5-1. THC Model Mesh with Hydrogeologic Units Shown in the Vicinity of the Drift: Topopah 
Spring Tuff Middle Nonlithophysal (tsw34triangles), Lower Lithophysal (tsw35dots), 
and Lower Nonlithophysal (tsw36diamonds) Units 

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Drift-Scale THC Seepage Model 

Table 6.5-1. Vertical Mesh Dimensions and Geologic Contacts in the THC Seepage Model (Tptpll Unit) 

Model Layer 
Top of Layer 
Elevation (m) 
Mesh Top of Layer 
Z Coordinate (m) 
Top 1446.6 363.8 
tcw11 1446.6 363.8 
tcw12 1419.2 336.4 
tcw13 1342.1 259.3 
ptn21 1326.5 243.7 
ptn22 1323.1 240.3 
ptn23 1321.0 238.2 
ptn24 1318.2 235.4 
ptn25 1312.7 229.9 
ptn26 1303.6 220.8 
tsw31 1294.1 211.3 
tsw32 1279.7 196.9 
tsw33 1249.3 166.5 
tsw34 1169.2 86.4 
tsw35 1132.0 49.2 
Drift center 1082.8 0.0 
tsw36 1030.6 52.2 
tsw37 997.4 85.4 
tsw38 980.8 102.0 
tsw39 967.0 115.8 
ch1v 956.9 125.9 
ch2v 945.2 137.6 
ch3v 931.9 150.9 
ch4z 919.2 163.6 
ch5z 906.4 176.4 
ch6 892.4 190.4 
pp4 878.5 204.3 
pp3 865.9 216.9 
pp2 833.2 249.5 
pp1 818.2 264.6 
bf3 756.7 326.1 
Bottom 730.0 352.8 

Source: DTNs: LB0011DSTTHCR1.002 [DIRS 161282] (model), 
LB990501233129.004 [DIRS 111475] (geologic column). 

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Drift-Scale THC Seepage Model 


Source: DTN: LB0011DSTTHCR1.002 [DIRS 161282]. 

NOTE: Shaded grid blocks are those with top, side, base designations in other figures. 

Figure 6.5-2. Discretization of the Repository Drift in the THC Model 

The discretization of the drift is kept the same for the two configurations. As such, the 
preclosure period is simulated by assigning identical open-space properties to grid blocks 
representing the inner zone and outer zone. 

Simulations of ambient conditions (no thermal load) are run with a one-dimensional (vertical 
column) grid having the same stratigraphy and vertical discretization as the Tptpll 
two-dimensional mesh. This one-dimensional model does not have a drift opening and uses 
uniform vertical gridding through the area cutting across the drift on Figure 6.5-2. 
One-dimensional columns are used to speed up the computational effort. Because of the no-flow 
boundary conditions existing on each side of the model mesh, the horizontal geologic contacts 
and laterally continuous rock properties, two-dimensional simulations under ambient conditions 
are essentially the same as one-dimensional simulations (vertical flow only). Close to the drift, 
however, flow is diverted around the drift opening because of the capillary barrier created by this 
opening. Therefore, the only differences between one- and two-dimensional ambient simulations 
result from the effect of the drift opening. 

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Drift-Scale THC Seepage Model 

6.5.2 Boundary Conditions 
The boundary conditions are set according to those appropriate for the column location near the 
repository center (DTN: LB990701233129.002 [DIRS 125604]) (Table 6.5-2), with temperatures 
at the top and bottom boundary reflecting the natural geothermal gradient. The pressures and 
temperatures are constant at the top and bottom boundaries. The use of a constant temperature 
boundary at the water table is not expected to have much effect on the predicted thermal history 
or water chemistry in the repository drifts because the boundary is so far (more than 350 m) from 
the repository horizon (BSC 2004 [DIRS 169866], Section 6.1.3). The initial CO2 partial 
pressure in the drift is set to the ambient CO2 partial pressure in the adjacent wall rock. 

Three cases of infiltration are considered as shown in Table 6.5-3. The infiltration values (6, 16, 
and 25 mm/yr for the present-day, monsoonal, and glacial transition periods, respectively) 
represent repository-wide averages of percolation; the values are calculated as the arithmetic 
average of the 31 repository locations considered in Multiscale Thermohydrologic Model 
(BSC 2001 [DIRS 158204], Section 6.3.1). The calculated averages have been rounded to 
6 mm/yr, 16 mm/yr, and 25 mm/yr, respectively, for use in this report. These values vary 
slightly from current estimates; their use in this model is justified in Section 4.1.1.2. 

One-dimensional simulations of ambient conditions are run with the same boundary conditions 
as the two-dimensional runs, except that these simulations do not include a drift opening. A 
constant infiltration rate of 6 mm/yr is used in one-dimensional simulations to evaluate the model 
sensitivity to thermodynamic data (Section 6.5.5.4). The mean infiltration case in Table 6.5-3 
(step-wise infiltration increase) is used for all other ambient simulations (Section 6.5.5.4). 

Table 6.5-2. Tptpll THC Seepage Model (Tptpll Unit) Boundary Conditions 

Boundary Boundary Condition Reference 
Top T = 16.13C 
Sg = 0.99 
P = 84725 Pa 
Time-varying infiltration rate (mean infiltration 
regime only) 
Constant composition of infiltration and Pco2 
Table 4.1-1 
Table 4.1-1 
Table 4.1-1 
Table 6.5-3 
Table 6.2-1 
Bottom T = 32.62C 
SL = 0.99999 
P = 92000 Pa 
Constant water composition and Pco2 
Table 4.1-1 
Table 4.1-1 
Table 4.1-1 
Table 6.2-1 
Sides No flux for water, gas, heat, and chemical species Not Applicable 
Drift Wall Open to gas and liquid fluxes (advective and 
diffusive); conduction only for heat 
Not Applicable 
Waste Package Initial full heat load of 1.45 kW/m decreasing with 
time (due to radioactive decay), and reduced by 
86.3% during the first 50 years (due to heat removal 
by ventilation) 
Appendix D and 
Table 4.1-6 

NOTES: T = Temperature 
Sg = Gas saturation 
SL = Liquid saturation
P = Pressure 


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Drift-Scale THC Seepage Model 

Table 6.5-3. THC Seepage Model Infiltration Rates 

Case 
Infiltration Rate 
(mm/yr) 
Time Period 
(years) Reference DTN 
Mean infiltration 
(increasing 
stepwise) 
6 
16 
25 
0 to 600 (present-day) 
600 to 2000 (monsoonal) 
2,000 to 100,000 (glacial 
transition) 
Infiltration rates used in this model 
taken from DTN: LL000114004242.090 
[DIRS 142884] and Table 4.1.1 
Mean present day 
(fixed) 
6 0 to 100,000 
Mean glacial 
transition (fixed) 
25 0 to 100,000 

NOTE: All simulations are carried out with the present-day mean calibrated rock properties set. See 
Table 6.5-5. 


6.5.3 Input Data and Modeling Procedure 
The Tptpll THC model is run using TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]). 
Simulations are carried out using the rock properties data shown in Table 6.4-1; the geochemical 
system described in Table 6.2-2; thermodynamic data shown in Appendix C (Section 4.1.5); 
kinetic data from Table 4.1-3; and mineral abundance and surface area data tabulated in 
Appendices A and B, respectively. Simulations are run using the five water compositions (Table 
6.2-1) discussed in Section 6.2.2.1 and summarized below in Table 6.5-4. 

Table 6.5-4. Selected Input Waters (Section 6.2.2.1) for the Tptpll THC Seepage Model (Tptpll Unit) 

Name of Alternative 
Sample or Water 
Name Location 
Lithostratigraphic 
Unit 
W0 HD-PERMa ESF Alcove 5 Tptpmn 
W5 CS-1000/7.3-7.7/UC ECRB Cross-Drift base of Tptpul 
W4 CS-2000/16.5-21.1/UC ECRB Cross-Drift Tptpll 
W6 SD-9/990.4-991.7 Borehole SD-9 Tptpll 
W7 CS-500/12.0-16.7/UC ECRB Cross-Drift Tptpul 

a 

Average of two samples as discussed in Section 6.2.2.1. 
NOTE: See Table 6.2-1 for compositions. 


For model output runs, the diffusion coefficient of CO2 in gas was unintentionally set to a default 
molecular diameter of 1  1010 m. The CO2-specific value is 2.5  1010 m (Section 4.1.6). This 
change in molecular diameter, through the use of Equation 6.4-24, causes approximately a 
six-fold increase in the CO2 diffusion coefficient. Although this change is within the range of 
uncertainty affecting the calculation of gas diffusivity in the model, a sensitivity simulation has 
been run using the correct CO2 molecular diameter value (2.5  1010 m) with results compared 
in Section 6.5.5.2. 

In this model, calcite is not treated kinetically, but is rather set to remain locally at equilibrium, 
(although a certain degree of supersaturation is allowed for, as discussed below). Assuming 
equilibrium is reasonable because calcite reaction rates reported in the literature (Table 4.1-3) are 
quite rapid. Very similar results in simulations of the DST are obtained when using local 
equilibrium for calcite and assuming a kinetically controlled reaction rate (Section 7.1). Using 

MDL-NBS-HS-000001 REV 04 6-45 February 2005 


Drift-Scale THC Seepage Model 

equilibrium has the advantage of allowing simulations with larger time steps than would be 
required with a kinetically controlled fast calcite reaction rate. 

Using pH and calcium concentrations measured in pore-water samples (Table 6.2-1), together 
with independently measured CO2 partial pressures in ambient pore-gas samples (Table 7-1), 
calcite is calculated to supersaturate in pore waters by approximately 1 log(Q/K) unit at 25C. 
The reason for this supersaturation has not been determined and could be the result of various 
factors, including (but not limited to) analytical errors, kinetic inhibition caused by organic or 
other compounds in solution, or effects caused by high capillary pressure or pressures developed 
during the ultra-centrifuge water-extraction process. To reconcile measured pH, calcium, and 
CO2 concentrations, calcite is allowed to remain supersaturated by approximately 1 log(Q/K) 
unit at 25C. This precipitation gap is set to decrease exponentially with temperature and 
become negligible (one hundredth of the gap value at 25C) at an arbitrarily selected temperature 
of 200C. This approach (using a precipitation gap) can be viewed as a crude approximation of 
precipitation with a nucleation threshold. Note that dissolution still occurs only if log(Q/K) < 0. 
The stability of water and gas concentrations calculated for ambient conditions over long periods 
of time is improved by implementing the calcite supersaturation gap. 

Simulations of ambient conditions (i.e., without thermal loading, under natural geothermal 
gradient, and without drift opening) are run using the same input data as described above. 
However, to evaluate the models sensitivity to thermodynamic data (Section 6.5.5.4), three 
different sets of thermodynamic data are used and are described further in Section 6.4.8: Set 1, 
the database used for model output runs for TSPA, and alternative data sets Set 2 and Set 3. 

As discussed in Section 4.1.7, THC simulations are run for an initial period of 50 years, using the 
preclosure drift configuration and thermal properties. The simulations are then restarted using 
the postclosure drift configuration and properties from 50 years to a total simulation time of 
100,000 years. At times corresponding to changes in infiltration rates (at 600 and 2,000 years, 
Table 6.5-3), the simulations are stopped and then restarted with the new infiltration rate, 
resulting in a stepwise change in infiltration. 

Maximum time steps of 15 days, 1 month, 2 months, 1 year, and 5 years are used for the time 
periods spanning 0 to 50, 50 to 600, 600 to 2,400, 2,400 to 20,000, and 20,000 to 100,000 years, 
respectively. To change infiltration rates and the maximum time step length, each run is stopped 
and then restarted at 50, 600, 2,000, 2,400, and 20,000 years after changing these input data. 

6.5.4 Model Runs 
Sixteen simulations have been performed, and are summarized in Table 6.5-5. 

MDL-NBS-HS-000001 REV 04 6-46 February 2005 


Drift-Scale THC Seepage Model 

Table 6.5-5. THC Seepage Model Runs Using the Mean Infiltration Rock-Property Set for All Simulations 

Input Water 
(Table 6.5-3) 
Thermo. Data 
Set 
(Section 6.4.8) 
Infiltration Case 
(Table 6.5-2) 
Equation of State 
(EOS) Modulea Simulation Type Run ID 
None None Mean Infiltration EOS4 TH (two-dimensional) th6_1.45kw 
W0 Set 1 Mean Infiltration EOS4 THC (two-dimensional) thc6_w0 
W4 Set 1 Mean Infiltration EOS4 THC (two-dimensional) thc6-w4 
W5 Set 1 Mean Infiltration EOS4 THC (two-dimensional) thc6_w5 
W6 Set 1 Mean Infiltration EOS4 THC (two-dimensional) thc6_w6 
W7 Set 1 Mean Infiltration EOS4 THC (two-dimensional) thc6_w7 
W0 Set 1 Mean Present day 
(fixed) 
EOS4 THC (two-dimensional) thc6_w0a 
W0 Set 1 Mean Glacial 
transition (fixed) 
EOS4 THC (two-dimensional) thc25_w0 
W0 Set 1b Mean Infiltration EOS4 THC (two-dimensional) thc6_w0b 
W0 Set 1 Mean Infiltration EOS3 THC (two-dimensional) thc6_w0e3 
W0 Set 1 Mean Infiltration EOS3 (isothermal) THC (one-dimensional, 
ambient) 
thc6_w0amb1 
W4 Set 1 Mean Infiltration EOS3 (isothermal) THC (one-dimensional, 
ambient) 
thc6_w4amb1 
W5 Set 1 Mean Infiltration EOS3 (isothermal) THC (one-dimensional, 
ambient) 
thc6_w5amb1 
W6 Set 1 Mean Infiltration EOS3 (isothermal) THC (one-dimensional, 
ambient) 
thc6_w6amb1 
W0 Set 1 Mean Present day 
(fixed) 
EOS3 (isothermal) THC (one-dimensional, 
ambient) 
thc6_w0amb 
W0 Set 2 Mean Present day 
(fixed) 
EOS3 (isothermal) THC (one-dimensional, 
ambient) 
thc6_w0_q 
W0 Set 3 Mean Present day 
(fixed) 
EOS3 (isothermal) THC (one-dimensional, 
ambient) 
thc6_w6_w0_q1 

a 

TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]) flow modules: EOS3 neglects vapor pressure lowering due to 
capillary pressure; EOS4 takes this effect into account. 
b A CO2 molecular diameter of 2.5  1010 m (Section 4.1.6) is used for this run instead of the value of 1  1010 m input 
in other simulations listed here (Section 6.5.3). 

NOTE: Run IDs are used in Output DTNs: LB0307DSTTHCR2.001, LB0307DSTTHCR2.002, 
LB0302DSCPTHCS.001, and LB0302DSCPTHCS.002; also see Appendix G. 
6.5.5 Simulation Results (THC Seepage Model; Tptpll Unit) 

The model results are presented below in several subsections. First, the results of a simulation of 
thermal loading (TH) with no chemical reactions are presented (6.5.5.1). Then, THC results are 
presented in two parts. Predicted water chemistry trends around the drift are presented first 
(Section 6.5.5.2), then the effect of watergasrock reaction on fracture permeability and flow 
patterns around the drift is assessed (Section 6.5.5.3). The results are presented in a way that 
allows an assessment of model sensitivity to input water compositions, infiltration rates, 
water-vapor pressure models, and CO2 effective diffusivity. Then, THC simulations of ambient 
conditions (non-heating) using different input thermodynamic data sets are discussed 
(Section 6.5.5.4). These simulations serve as the basis for justifying the use of revised 
thermodynamic data selected for this study. Finally, simulations using current, revised matrix 

MDL-NBS-HS-000001 REV 04 6-47 February 2005 


Drift-Scale THC Seepage Model 

porosity and thermal values are presented (Section 6.5.5.5). These simulations serve as the basis 
for justifying the use of the older data set used in the THC seepage model simulations that feed 
TSPA. All model results have been submitted to the technical database under DTNs as listed in 
Section 8.5. 

6.5.5.1 TH Results (No Chemical Reactions) 
For comparison to the THC simulations, a model run is performed considering only thermal and 
hydrologic (TH) processes. This simulation is run using the mean infiltration case (Table 6.5-3) 
and serves as a baseline for interpreting the effects of watergasrock chemical interaction on the 
thermal and hydrologic behavior of the system. 

Calculated temperatures, liquid saturation, and air mass fractions around the drift are shown in 
Figures 6.5-3 through 6.5-9. Postclosure temperatures quickly climb above the boiling point 
(near 96C at Yucca Mountain), with temperatures at the drift crown peaking at around 140C at 
a time of about 75 years. The highest modeled temperature in the waste package is attained 
during this time interval as well (the highest output value is near 160C). Temperatures are 
lower at the base of the drift (approximately 10C less than at the crown) because of the 
insulating effect of the invert (Figures 6.5-3 through 6.5-5). The return to ambient temperatures 
after heating takes 50,000 to 100,000 years. 

Around the drift, the fractures are predicted to rewet at times between 1,000 and 2,000 years 
(Figure 6.5-6). Rewetting of the matrix occurs between 200 and 300 years (Figure 6.5-7). A 
contour plot of temperatures and matrix saturations in the vicinity of the drift at a simulated time 
of 600 years (near the time of maximum dryout in the fractures) shows the fracture dryout zone 
extending approximately 4 m above the drift, 5 m to the side of it, and 8 m below it 
(Figure 6.5-5). In fractures, liquid saturations show strong diversion of water around the dryout 
zone. Air mass fractions in the gas phase at the drift wall (the complement of the steam mass 
fraction; Figure 6.5-8) drop to near-zero values in the fractures during dryout (i.e., the gas phase 
is almost entirely water vapor). 

The calculated rate of vertical water influx in fractures at the drift crown (Figure 6.5-9) shows a 
small short-lived influx peak at the time of rewetting. The intensity of this peak may only reflect 
the time intervals at which data are output from the model (i.e., peaks of flux in this figure may 
not be fully resolved because such peaks are narrow relative to the time intervals specified for 
data output from the simulations). The predicted ambient water flux in the model is for a 
one-dimensional column without a drift opening. It does not take into account the diverting 
effect of a drift opening (i.e., the diversion of percolating water around the drift capillary 
barrier). Stepped increases in the ambient flux rates reflect infiltration rate increases at 600 and 
2,000 years, corresponding to changes in climate state (Table 6.5-3). At most times (except for 
short-lived peaks around 50 and 1,200 years), the ambient water flux without a drift opening is 
larger than the predicted flux above the drift under thermal loading conditions (Figure 6.5-9). 
Calculated temperatures, liquid saturations, and fluxes shown here are consistent with results of 
TH simulations presented in Drift-Scale Coupled Process (DST and TH Seepage) Models 
(BSC 2004 [DIRS 170338], Section 6.2.3). Predicted temperatures are also directly comparable 
with the results of the multiscale thermohydrologic models LDTH (Line-averaged-heat-source, 

MDL-NBS-HS-000001 REV 04 6-48 February 2005 


Drift-Scale THC Seepage Model 

Drift-scale, Thermal-Hydrologic) submodel simulations (BSC 2004 [DIRS 169565] Section 6.3). 
The vertical flux is further discussed in Section 6.5.5.3. 

Note that in all models presented in this report, the drying of the rock caused by drift ventilation 
(i.e., the physical removal of moisture from wall rock by ventilation) is not considered. This 
drying could reduce the amount of water available for mobilization by boiling during 
postclosure. However, sensitivity studies (BSC 2001 [DIRS 155950], Section 5.3.2.4.4) indicate 
that inclusion of preclosure dryout due to ventilation has little effect on TH conditions around the 
drift during the postclosure period, compared to a model that does not account for the influence 
of preclosure dryout. Therefore, inclusion of preclosure dryout is not expected to have a large 
effect on thermal seepage. The effect of evaporative concentration on pore water compositions 
would be more pronounced during preclosure than predicted here. However, the small effect of 
preclosure dryout on postclosure TH conditions is not expected to significantly affect water 
compositions during postclosure. 


Output DTN: LB0307DSTTHCR2.002. 

Figure 6.5-3. TH Simulation (Tptpll): Time Profiles of Modeled Temperatures in Fractures (Similar in 
Matrix) at Three Drift-Wall Locations and in the Waste Package 

MDL-NBS-HS-000001 REV 04 6-49 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.002. 

Figure 6.5-4. TH Simulation (Tptpll): Time Profiles of Modeled Temperatures in Fractures at Three 
Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-50 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Rewetting of the matrix at the drift wall has already occurred (Figure 6.5-7). 

Figure 6.5-5. TH Simulation (Tptpll): Contour Plot of Modeled Temperatures (C) and Liquid Saturations 
in the Matrix and Fractures at 600 Years (Near the Time of Maximum Dryout in Fractures) 

MDL-NBS-HS-000001 REV 04 6-51 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.002. 

Figure 6.5-6. TH Simulation (Tptpll): Time Profiles of Modeled Liquid Saturations in Fractures at Three 
Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-52 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.002. 

Figure 6.5-7. TH Simulation (Tptpll): Time Profiles of Modeled Liquid Saturations in Matrix at Three 
Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-53 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.002. 

Figure 6.5-8. TH Simulation (Tptpll): Time Profiles of Modeled Air Mass Fractions in the Gas Phase in 
Fractures at Three Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-54 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.002. 

Figure 6.5-9. TH Simulation (Tptpll): Time Profiles of Modeled Water Flux at the Drift Crown 

6.5.5.2 Water Chemistry Trends 
The THC seepage model does not simulate actual seepage of water into drifts because the range 
of simulated infiltration rates produces liquid saturation rates below the theoretical seepage 
threshold for rocks around the emplacement drift. Instead, the model computes the compositions 
of pore water and gas throughout the host rock around an emplacement drift (i.e., in the matrix 
and fractures). The THC seepage model provides, for each gridblock at each time step, 
parameter values for thermal-hydrologic variables such as temperature, pressure, and gas and 
liquid saturation; concentrations of aqueous species; mineral volume fractions; and the CO2 
volume fraction in matrix and fractures. Results from three fixed locations adjacent to the drift 
wallthe crown, the side, and the baseare used to calculate the in-drift gas composition 
(Section 6.5.5.2.1). Water compositions are extracted from dynamic zones that follow the 
boiling and condensation fronts that expand and then contract around the drift, to represent the 
composition of potential seepage (Section 6.5.5.2.2). 

6.5.5.2.1 Drift Wall Results 
Time profiles of the evolving water chemistry have been extracted from model output at three 
drift wall locations: crown (model grid blocks F 121 and M 121), side (grid blocks F 44 
and M 44), and base (grid blocks F 128 and M 128) (Figure 6.5-2). These are calculated 
using the HD-PERM water (W0) as input water composition. The results are shown for the 
ambient case and for cases with and without water vapor pressure lowering caused by capillary 
pressure (runs referred to as eos4 and eos3, respectively). The simulations providing feed to 
downstream models are run using a generic value for the molecular diameter of CO2 that is 
smaller than the actual diameter, so the CO2 diffusion coefficient is too high by a factor of six 

MDL-NBS-HS-000001 REV 04 6-55 February 2005 


Drift-Scale THC Seepage Model 

(Section 6.5.3). Therefore, model results are also presented for another eos4 THC simulation, 
which uses the correct CO2 diffusion coefficient. 

Predicted time profiles of temperature, CO2 gas concentrations, and aqueous species total 
concentrations (fracture medium) are shown in Figures 6.5-10 through 6.5-19. The results of the 
ambient condition simulation are presented to provide a baseline by which comparisons can be 
made with simulations of thermal loading. Obtaining an initial steady-state hydrochemical 
system yielding aqueous species concentrations consistent with measured concentrations in pore 
water is difficult. This is because the stability of the system depends on reaction rates and 
relative mineral thermodynamic stability, as well as infiltration rates and rock properties. The 
difficulty in reaching a chemical steady state increases with the number of reactive minerals 
included in the system, because each additional mineral adds its own uncertainty in reaction rate 
to the total model uncertainty. A reasonably steady ambient hydrochemical state is achieved 
here by reducing the stability of smectites and zeolites (Section 4.1.4), and allowing some degree 
of calcite supersaturation (Section 6.5.3) in pore waters. In simulations with unrevised 
thermodynamic data (Section 6.5.5), smectites and zeolites are too stable and form in 
unreasonable amounts. Thus, predicted water compositions are inconsistent with observed pore 
waters (e.g., pH values and sodium concentrations increase with time, while calcium 
concentrations decrease). These trends are governed by feldspar and glass alteration reactions 
such as those discussed below. 

Model simulations are quite sensitive to the effective reaction rates of aluminum silicates, 
particularly clays and calcium zeolites. For example, the dissolution of albite (a sodium 
feldspar) to form sodium smectite (a clay) results in an increase in pH (decrease in H+ activity), 
as follows: 

2.33NaAlSi3O8 (albite) + 2H+ ==> 

Na0.33Al2.33Si3.67O10(OH)2 (smectite) + 3.32SiO2 + 2Na+ (Eq. 6.5-1) 

The alteration of albite to stellerite (a calcium zeolite) can also drive pH to higher values if the 
calcium necessary to form stellerite originates from calcite dissolution, as in the following 
reaction: 

2NaAlSi3O8 (albite) + SiO2 + CaCO3 (calcite) + H+ + 7H2O ==> 



CaAl2Si7O18  7H2O (stellerite) + 2Na+ + HCO3 (Eq. 6.5-2) 

In addition, the consumption of calcium to form calcium-bearing zeolites or clays inhibits calcite 
precipitation as a means of controlling the increase of pH and total aqueous carbonate 
concentrations. 

In the model simulations, ambient trends are fairly steady, with some fluctuations resulting 
mostly from changes in infiltration rates, and indicate that the ambient geochemical system for 
the THC seepage model for the Tptpll unit is fairly well constrained by the minerals included and 
the thermodynamic and kinetic data incorporated into the model. 

MDL-NBS-HS-000001 REV 04 6-56 February 2005 


Drift-Scale THC Seepage Model 

Postclosure temperature profiles from THC simulations (Figure 6.5-10) are similar for model 
runs with and without vapor-pressure lowering, but with slightly higher peak temperatures 
predicted with the latter. 

The predicted trend of CO2 concentrations with time in fracture gas (Figure 6.5-11) generally 
shows a large decline during dryout, followed by a steep increase during the initial cooling and 
rewetting stage. CO2 concentrations drop quickly at the onset of dryout, shortly after 50 years, 
because of displacement by steam. Fluctuations during the dryout period (Figure 6.5-11) appear 
to result from the competing effect of CO2 displacement by steam (from the drift outwards), and 
increased diffusion of CO2 towards the drift resulting from rising temperatures after all water 
boils out. During the cooling stage, CO2 concentrations rise above ambient values at around 600 
years, and remain there for 20,000 to 50,000 years. In all simulations, the predicted CO2 
concentrations at the drift wall remain below 10,000 ppmv for the entire simulated time period. 

The simulation utilizing the specific molecular diameter and corresponding diffusion coefficient 
for CO2 predicts similar trends in the CO2 concentrations with time. The higher CO2 diffusion 
coefficient in the TSPA model runs (six fold here) causes somewhat higher predicted CO2 
concentrations in the gas phase, although the effect is most noticeable during early stages of the 
dryout period (Figure 6.5-11). 

The predicted pH of fracture water around the drift is mostly in the range of 7.6 to 8.4, but dips 
to as low as 7.0 for a short time interval after rewetting (Figure 6.5-12). The predicted pH values 
in fracture water (Figure 6.5-12) are consistent with modeled trends of CO2 concentrations. The 
choice of the water-vapor pressure model and the difference in the CO2 diffusion coefficient 
have only a small effect on predicted pH values (differences mostly within less than 0.2 pH 
units; Figure 6.5-12). The predicted pH range of water in fractures at the drift wall for all cases 
is neutral to slightly alkaline (pH 7 to 8.6), with the lowest values occurring a short period after 
rewetting. The pH remains essentially below predicted ambient values (8.2 to 8.6) for the entire 
simulated time period. The total carbonate concentrations (shown as HCO3 on Figure 6.5-13) 
are depressed, relative to ambient values, because of the exsolution of CO2 gas driven by 
elevated temperatures. 

Calcium concentrations (Figure 6.5-14) drop as temperatures rise during the preclosure, due to 
the inverse solubility of calcite with temperature. Predicted ambient sodium concentrations 
(Figure 6.5-15) approximately double over the 100,000-year simulated time period, which could 
reflect somewhat higher feldspar and/or glass dissolution rates relative to the precipitation rate of 
clay minerals. Relatively elevated calcium and sodium concentrations during rewetting at the 
drift wall at the base of the drift are the result of re-dissolution of salts previously concentrated 
by evaporation at the time of dryout (Section 6.4.5). 

Upon heating, aqueous silica concentrations (Figure 6.5-16) rise significantly above ambient 
values because of the dissolution of silica and aluminosilicate phases at higher temperatures. 
Upon boiling to dryness, aqueous silica concentrations may significantly exceed the solubility of 
amorphous silica (near 370 mg/L at 100C) because the precipitation rate of this mineral, though 
quite fast, does not keep up with boiling rates. During the initial cooling stage, primarily the 
600- to 2,000-year time interval, aqueous silica around the drift precipitates as amorphous silica 

MDL-NBS-HS-000001 REV 04 6-57 February 2005 


Drift-Scale THC Seepage Model 

and, as will be discussed later, accounts for most of the reduction in porosity around the drift 
during this time. Modeled ambient aqueous silica concentrations are nearly stable. 

Chloride concentrations (Figure 6.5-17) increase slightly during the preclosure time because of 
evaporative concentration. The profiles also show, at the time of rewetting, the effect of 
remobilization of concentrated solutions that was mentioned earlier. After rewetting, chloride 
concentrations drop relatively quickly towards ambient values near 110 mg/L. 

Predicted fluoride concentrations in the Tptpll model under ambient and thermal loading 
conditions are relatively high because of fluorite (CaF2) dissolution (Figure 6.5-18). This 
mineral is included as one of the mineral constituents of the Tptpll. Ambient fluoride 
concentrations tend toward equilibrium with fluorite (5 to 6 mg/L for the modeled ambient 
geochemical conditions) because of the fast reaction rate of this mineral. Concentrations 
increase during the preclosure period as the temperature rises and calcium concentrations drop. 
During the cooling period, fluoride concentrations remain above ambient for 10,000 to 20,000 
years, while calcium values remain depressed. 

Nitrate shows very similar behavior to chloride, as both are acting as conservative species at 
concentrations below saturation (Figure 6.5-19). At dryout, its mass inventory is accounted for 
by forming sodium nitrate, using all in solution (without equilibrium calculations; see Section 
6.4.5). Upon rewetting, it dissolves faster than chloride salts because of its greater solubility, 
causing a temporary increase in the NO3/Cl ratio of rewetting waters. However, this effect is 
barely noticeable in fracture waters (Figure 6.5-20). Because the model is limited to moderately 
low ionic strengths, salt dissolution is performed using a kinetic rate, which allows dissolution to 
proceed somewhat more slowly than under an equilibrium approach. However, because of the 
nature of the dilute water rewetting the dryout zone, and its relatively high flux compared to the 
small quantities of salts precipitated in the rock, the lag time in dissolution is short. The increase 
in the nitrate to chloride ratio is consistent with the solubilities of the salt phases, yet the time 
period over which this spike occurs may be less than the model actually predicts, and the 
magnitude of the spike may be different from that predicted. 

The predicted time profiles for constituents other than carbonate and pH (Figures 6.5-14 through 
6.5-20) do not show much sensitivity to the choice of water-vapor pressure model or the CO2 
diffusion coefficient. In most cases, elevated concentrations are predicted at the time the drift 
rewets, followed by a steep fall towards ambient values (e.g., sodium and chloride in 
Figures 6.5-15 and 6.5-17). As noted earlier, these transient-elevated concentrations are caused 
by the rewetting of areas where evaporative concentration took place during dryout. The 
precipitation of salts upon complete dryout is accounted for in this model, and the dissolution of 
these salts upon rewetting causes the concentrations of dissolved constituents to peak. 
Nevertheless, these relatively elevated concentrations are predicted only at small liquid 
saturations at which no significant fluid flow is taking place. 

MDL-NBS-HS-000001 REV 04 6-58 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

Figure 6.5-10. THC Seepage Model (Tptpll): Time Profiles of Modeled Temperatures at Three Drift-Wall 
Locations with and without Water-Vapor-Pressure Lowering (eos4 and eos3, 
Respectively) 

MDL-NBS-HS-000001 REV 04 6-59 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-11. THC Seepage Model (Tptpll): Time Profiles of Modeled CO2 Concentrations in the Gas 
Phase in Fractures at Three Drift-Wall Locations under Heating (Heat) and Non-Heating 
(Ambient) Conditions, Including (eos4) and Excluding (eos3) Water-Vapor-Pressure 
Lowering 

MDL-NBS-HS-000001 REV 04 6-60 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-12. THC Seepage Model (Tptpll): Time Profiles of the Modeled pH of Fracture Water at 
Three Drift-Wall Locations under Heating (Heat) and Non-Heating (Ambient) Conditions, 
Including (eos4) and Excluding (eos3) Water-Vapor-Pressure Lowering 

MDL-NBS-HS-000001 REV 04 6-61 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-13. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Carbonate 
Concentrations (as HCO3) in Fracture Water at Three Drift-Wall Locations, under 
Heating (Heat) and Non-Heating (Ambient) Conditions, Including (eos4) and Excluding 
(eos3) Water-Vapor-Pressure Lowering 

MDL-NBS-HS-000001 REV 04 6-62 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-14. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Calcium 
Concentrations in Fracture Water at Three Drift-Wall Locations, under Heating (Heat) and 
Non-Heating (Ambient) Conditions, Including (eos4) and Excluding (eos3) Water-Vapor-
Pressure Lowering 

MDL-NBS-HS-000001 REV 04 6-63 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-15. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Sodium 
Concentrations in Fracture Water at Three Drift-Wall Locations, under Heating (Heat) and 
Non-Heating (Ambient) Conditions, Including (eos4) and Excluding (eos3) Water-Vapor-
Pressure Lowering 

MDL-NBS-HS-000001 REV 04 6-64 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs (REV02): LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-16. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Silica 
Concentrations in Fracture Water at Three Drift-Wall Locations, under Heating (Heat) and 
Non-Heating (Ambient) Conditions, Including (eos4) and Excluding (eos3) 
Water-Vapor-Pressure Lowering 

MDL-NBS-HS-000001 REV 04 6-65 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-17. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Chloride 
Concentrations in Fracture Water at Three Drift-Wall Locations, under Heating (Heat) and 
Non-Heating (Ambient) Conditions, Including (eos4) and Excluding (eos3) 
Water-Vapor-Pressure Lowering 

MDL-NBS-HS-000001 REV 04 6-66 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-18. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Fluoride Concentrations in 
Fracture Water at Three Drift-Wall Locations, under Heating (Heat) and Non-Heating 
(Ambient) Conditions, Including (eos4) and Excluding (eos3) Water-Vapor-Pressure 
Lowering 

MDL-NBS-HS-000001 REV 04 6-67 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-19. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Nitrate Concentrations in 
Fracture Water at Three Drift-Wall Locations, under Heating (Heat) and Non-Heating 
(Ambient) Conditions, Including (eos4) and Excluding (eos3) Water-Vapor-Pressure 
Lowering 

MDL-NBS-HS-000001 REV 04 6-68 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs (REV01): LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Simulation labeled Heat-a is run with the CO2 diffusion coefficient six times smaller than other 
simulations (see text). 

Figure 6.5-20. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Nitrate to Chloride Ratio at 
Three Drift-Wall Locations, under Heating (Heat) and Non-Heating (Ambient) Conditions, 
Including (eos4) and Excluding (eos3) Water-Vapor-Pressure Lowering 

MDL-NBS-HS-000001 REV 04 6-69 February 2005 


Drift-Scale THC Seepage Model 

6.5.5.2.2 High-Liquid Saturation Zone above Drift Crown 
Predicted concentration profiles at fixed model grid blocks at the crown, side, and base of the 
drift provide limited information on the chemistry of waters that could seep into drifts. Such 
profiles do not fully capture the spatial variability of model results around the drift and, more 
importantly, cannot show water compositions as long as the selected model grid blocks remain 
dry. To complement results shown in previous sections and to better capture spatial variability, 
as well as predicted water compositions during the dryout period, concentration time-profiles are 
also generated for dynamic zones following the expanding, then receding, boiling and 
condensation fronts around the drift. This selection methodology is presented in 
Post-Processing Analysis for THC Seepage (BSC 2004 [DIRS 169858]), and examines 
gridblocks in the host rock that are likely to yield fluids that could seep into the drift, 
emphasizing water compositions that form when the dryout zone rewets. The selection process 
down-selects from the full model output, which contains a water composition for every grid 
block at each time step, to a subset of results corresponding to the water compositions at the 
boiling zone and the zone of saturation in the host rock. These two locations rarely coincide with 
the drift wall. 

Some of these results are presented here for grid blocks with highest liquid saturation above the 
drift in fractures. More specifically, data are extracted for model grid blocks located within a 
45-degree arc of a line bisecting the drift crown, and for the first six of such grid blocks having 
the highest liquid saturation in fractures, within radial distance of 25 m from drift centerline. 

Various time profiles are shown below for data extracted in this manner; thus, data for six grid 
blocks are plotted per point in time for each run. To assess the model sensitivity to initial water 
compositions and other alternative conceptualizations, time profiles are generated for simulations 
considering the following: 

 The five different input initial water compositions described in Section 6.2.2.1: W0, the 
composition used so far (HD-PERM), and alternative compositions W4 through W7. 
These simulations provide results that are used by downstream models. 
 Three different infiltration scenarios (using the HD-PERM input water composition): 
stepwise increase from 6 to 25 mm/yr, fixed 6 mm/yr, and fixed 25 mm/yr (Table 6.5-3). 
 The two different water vapor-pressure models implemented in TOUGHREACT V3.0 
(LBNL 2002 [DIRS 161256]) modules EOS4 and EOS3 (using the HD-PERM input 
water composition), corresponding to with and without vapor-pressure lowering due to 
capillary pressure. 
Time profiles generated in this way capture a spread of concentrations related to (1) the natural 
variability of input water compositions, (2) alternative model conceptualizations, and (3) for each 
model run at any given time, the spatial variability of model results for grid blocks of highest 
liquid saturation above the drift crown. In addition to this spread, fluctuations of computed 
concentrations with time arising from THC effects (as discussed below) are also captured. 

MDL-NBS-HS-000001 REV 04 6-70 February 2005 


Drift-Scale THC Seepage Model 

The distance from drift center, temperature, and liquid saturation in model grid blocks having the 
highest liquid saturation (above the drift) picked up by the extraction procedure (using 
CUTCHEM V1.0 (LBNL 2002 [DIRS 161127])) are shown in Figures 6.5-21, 6.5-22, and 
6.5-23, respectively (these figures exclude a few points extracted at times around 50 years and 
located approximately 24 m away from the drift center). These data provide a context for the 
chemistry profiles discussed below. For simulated times up to 50 years, all data are from zones 
directly above, and adjacent to, the drift crown (i.e., at a distance approximately 2.8 m from drift 
center) (Figure 6.5.21). From the onset of boiling at approximately 50 years, high-liquidsaturation 
grid blocks are all from the condensation (reflux) zone above the drift. Later, after the 
collapse of the boiling front, grid blocks with the highest liquid saturation are located either 
directly adjacent to the drift crown (e.g., some of the W0 data on Figure 6.5-21) or further away, 
adjacent to zones of reduced permeability formed by prior mineral deposition at the boiling front. 
These zones are discussed in Section 6.5.5.3. 

After the onset of boiling, starting at approximately 50 years, the temperature in the most highly 
liquid-saturated grid blocks remains nearly constant (near 96C, the boiling point for the 
modeled elevation), as would be expected in the zone of condensation and reflux (Figure 6.5-22). 
For most runs, the boiling temperature in these grid blocks is maintained until around 1,000 
years. The boiling front is predicted to collapse a few hundred years earlier for the case with the 
higher constant infiltration rate of 25 mm/yr (Figure 6.5-22). This period of time, during which 
temperatures are maintained at the boiling point of water, is hereafter referred to as the boiling 
period. Temperature profiles predicted with the various runs are quite similar, except for the 
shorter boiling period at higher infiltration. The greatest predicted temperature difference 
between simulations (around 5C) is also caused by differences in infiltration rate. 

For a given run, and at a given time, predicted liquid saturations in the first six grid blocks with 
highest liquid saturation (above the drift) are fairly uniform (Figure 6.5-23) because these data 
represent areas of highest liquid saturation in a laterally homogenous model. Consequently, 
corresponding concentration time-profiles (Figures 6.5-24 through 6.5-37), for each run at any 
given time, also show less spatial variability than would evaporated waters from grid blocks with 
much smaller and variable liquid saturations (such as at the boiling front). Therefore, examining 
the variability of predicted water compositions in zones of highest liquid saturation provides a 
better means of evaluating the model sensitivity to various input data or model 
conceptualizations than would examination of predicted water compositions directly at the 
boiling front. This is the main reason for focusing on zones of highest liquid saturation. 
However, when evaluating the compositional variability of waters that could seep into a drift 
during the boiling period (by somehow penetrating the dryout zone), the predicted water 
composition at the boiling front should also be considered. This variability is assessed in 
Post-Processing Analysis for THC Seepage (BSC 2004 [DIRS 169858]). 

MDL-NBS-HS-000001 REV 04 6-71 February 2005 


Drift-Scale THC Seepage Model 

Predicted profiles of concentration versus time for CO2 gas and aqueous species of interest are 
shown in Figures 6.5-24 through 6.5-37. Three observations are particularly significant: 

(1) In general, these figures indicate that the different input water compositions (i.e., natural 
variability) produce a larger relative spread in predicted water and gas compositions than the 
range of infiltration rates considered or the selected water-vapor pressure module. 
(2) At any point, the relative spread of predicted concentrations for the various modeled 
alternatives (at those grid blocks with highest liquid saturation above the drift crown) 
generally does not exceed an order of magnitude and is often much less (BSC 2004 
[DIRS 169858], Section 6.2.4). 
(3) Finally, for all simulations shown, the predicted general concentration trends are quite 
similar. 
The modeled CO2 concentrations in zones of condensation and reflux (Figure 6.5-24) are initially 
higher than at drift wall locations shown previously because heat mobilizes CO2 outward from 
the drift wall (Section 7.1). However, CO2 concentrations eventually also decrease in the 
reflux/condensation zone because of continued depletion of aqueous carbonate (Figure 6.5-26) 
from CO2 exsolution and calcite precipitation (see below). The subsequent trend of rising CO2 
concentration (from approximately 600 to 2,000 years) (Figure 6.5-24) was also noted earlier for 
locations at the drift wall (Figure 6.5-11). Note that during this time period, when the CO2 
concentrations are rising (from approximately 600 to 2,000 years), the spread of these 
concentrations is sharply reduced compared to the spread during other simulated time intervals 
(Figure 6.5-24a). This appears to be caused by the arrival of percolating water with a 
significantly higher dissolved CO2 content than the locally decarbonated water. This temporarily 
higher dissolved CO2 content in percolation water results from prior mobilization of CO2 gas 
from matrix water into fractures, further up the stratigraphic column. The case with a decrease in 
CO2 diffusion coefficient (Figure 6.5-24b) shows a similar rise but occurring at a somewhat 
delayed time, due to the decreased diffusive mobility. The decreasing pH values from 
approximately 600 to 2,000 years (Figure 6.5-25) is also consistent with the arrival of more 
carbonated water from prior CO2 gas mobilization. After approximately 2,000 years, the spread 
in concentrations increases again as these concentrations become less driven by the mobilization 
of CO2 and more by water-rock interactions that are more sensitive to the composition of 
infiltration water (even though all waters are set with the same CO2 partial pressure at the top 
model boundary). Also, the increase in infiltration rate at 2,000 years exacerbates this effect. 
The profiles of total aqueous carbonate concentrations (Figure 6.5-26) are consistent with this 
trend, showing a significant decrease in relative spread when concentrations increase after 
approximately 600 years until about 2,000 years, then spreading wider again after that time. 

After the rise in CO2 concentrations, the simulation using a constant 6 mm/yr infiltration rate 
predicts an earlier decrease in these concentrations than other simulations (all using 25 mm/yr in 
this time period) (Figure 6.5-24b). In the 25-mm/yr cases, CO2 concentrations diminish at later 
times because more CO2 is mobilized (exsolved from incoming water) prior to the collapse of the 
boiling front. Note that in the 6-mm/yr case, CO2 concentrations rise again somewhat after 
15,000 years because of a second small pulse of slightly more carbonated water percolating 
downwards (related to the various degrees of water-rock interaction in the different stratigraphic 

MDL-NBS-HS-000001 REV 04 6-72 February 2005 


Drift-Scale THC Seepage Model 

units further above the drift). In all cases, above-ambient CO2 values are maintained for over 
10,000 years, driven by the mobilized CO2 exsolved from the incoming water prior to collapse of 
the boiling front. 

The predicted range of pH values covered by all simulations (Figure 6.5-25) is from 
approximately 7.2 to 8.4. This range is fairly small and is similar to the range predicted 
previously for locations directly adjacent to the drift wall. After long periods of time 
(> 10,000 years), predicted pH values for runs using the different input water compositions tend 
to converge towards similar ambient values (in the 8.2 to 8.4 range after 100,000 years). Values 
of pH rise toward these ambient values after a decrease (from approximately 600 to 2,000 years) 
caused by the percolation of more carbonated and, thus, slightly more acidic waters as discussed 
above. For some of the waters considered, these long-term ambient values are slightly higher 
than initial values (in the approximate 8 to 8.3 range, Table 6.2-1) because the long-term 
alteration of rock-forming minerals (Equations 6.5-1 and 6.5-2) tends to drive the pH up. 

The concentration profiles of conservative species, such as chloride (Figure 6.5-27) (and also 
nitrate in simulations presented here; Figure 6.5-28), are useful in evaluating the degree of 
dilution and evaporative concentration in the areas for which predicted water compositions are 
shown. Dilution from condensation initially occurs (within a factor of around 10) after the onset 
of boiling. However, later in the boiling period, evaporative concentration takes over (also 
within a factor of around 10, compared to initial values). Comparing the chloride concentration 
profiles (Figure 6.5-27) with profiles showing the distance from drift center at which these 
concentrations occur (Figure 6.5-21) helps in distinguishing the following successive stages in 
the evolution of water composition in the condensation zone: 

1. A dilution stage occurs when the dryout zone is expanding, roughly from 50 to around 100 to 
150 years. It is caused by steam originating from water boiling in the rock matrix then 
migrating and condensing into fractures (Section 6.2.1.1). 
2. An evaporative concentration stage takes place while the high liquid saturation zone remains 
essentially stationary. The water in fractures is concentrated by boiling the percolating 
water, with no or little additional influx of condensation water derived from boiling matrix 
water. This stage lasts approximately from 150 years to 600 years, but is shorter by several 
hundred years under the higher infiltration rate (Figure 6.5-27). 
3. At 600 years (earlier under higher infiltration rates), a change in the climate state (from 
ambient to monsoon) causes infiltration rates to increase, resulting in dilution. 
Concentrations drop slowly until about 2,000 years, when decreasing rates of heat 
generation, coupled with another climate change (monsoonal to glacial-transition) and a 
corresponding increase in infiltration, result in the collapse of the boiling zone and rewetting 
to the drift wall. Concentrations spike slightly during this rewetting phase, as soluble salts 
redissolve, and the pH drops. Following the rewetting period, dilution by percolating waters 
overcomes the effect of evaporative concentration and brings concentrations back to their 
ambient values over tens of thousands of years. 
The effects of these three distinct stages are visible on the predicted concentration trends of most 
constituents. In the case of chloride, looking at the results of all simulations, concentrations drop 

MDL-NBS-HS-000001 REV 04 6-73 February 2005 


Drift-Scale THC Seepage Model 

to as low as around 1 ppm (with Water W6) during the dilution stage and rise to as high as 
approximately 1,500 ppm (with Water W0) during the evaporative concentration stage 
(Figure 6.5-27). 

The trends of most other aqueous species can be evaluated in terms of the degree of dilution, 
concentration, and mineral reaction taking place. By dividing aqueous species concentrations by 
chloride concentrations, the relative degree of mineral dissolution or precipitation can be 
evaluated. However, the variations of these ratios do not necessarily indicate that reactions are 
taking place in the grid blocks where the ratios are evaluated. Reactions in the rock matrix could 
also affect these ratios in fracture water if significant diffusion occurs between fractures and 
matrix. Reactions above areas being investigated could also affect these ratios. In the present 
simulations, in zones of highest liquid saturation above the drift crown, predicted increases in 
Ca/Cl in fractures during the dilution stage (after the onset of boiling and steam condensation) 
(Figure 6.5-30) result from calcite dissolution in fractures. This dissolution is enhanced by the 
somewhat lower pH of condensation waters caused by CO2 dissolution (Section 7.1). After this 
time, when evaporative concentration takes over, Ca/Cl ratios decrease through precipitation of 
calcite and, to a lesser extent, of stellerite. The trends of Ca/Cl ratios in logarithmic form (Figure 
6.5-30) are similar and somewhat parallel for all simulations, suggesting that the degree of 
reaction involving calcium minerals is similar in all cases considered. 

The Na/Cl ratios in fracture water also increase initially during the dilution stage (Figure 6.5-32), 
but much less than Ca/Cl ratios. The increase in this case results from albite dissolution 
(accompanied by stellerite precipitation, Equations 6.5-1 and 6.5-2), which occurs at a much 
slower rate than calcite dissolution. After the dilution stage, the Na/Cl ratios decrease 
significantly, even though albite is still dissolving in fractures. The Na/Cl decrease in this case 
appears to result from sodium diffusion into the rock matrix where albite precipitation is taking 
place (not shown here). This trend is eventually reversed by the continued alteration of albite to 
stellerite in fractures, which becomes even more pronounced as the evaporative stage ends. Like 
the Ca/Cl ratios, the similar and somewhat parallel trends of Na/Cl ratios (in logarithmic form) 
would suggest that all waters react to a similar degree with sodium phases. 

As discussed in Section 6.2.2.1, the ratio of calcium to total aqueous carbonate concentration 
(expressed here as Ca/HCO3) gives some indication of the likelihood for a water to evolve 
towards a potentially deleterious calcium chloride brine upon continued evaporation. These 
brines are more likely to form in initial waters with a Ca/HCO3 molal ratio greater than 1. These 
values are exceeded during the evaporative concentration stage for all considered initial water 
compositions (Figure 6.5-33). However, Waters W0 and W7 display Ca/HCO3 ratios 
significantly higher than the other waters. Water W4 shows the lowest ratios. 

Ratios of nitrate to chloride (Figure 6.5-34) remain essentially constant. This is expected 
because redox processes are not considered in these simulations, and solid nitrate and chloride 
phases are formed only upon complete dryout (Section 6.4.5). The re-dissolution of nitrate and 
chloride salts formed during dryout has a short-lived, hardly noticeable effect in zones with the 
highest liquid saturations. 

The predicted magnesium concentrations (Figure 6.5-35) reflect the effects of the dilution and 
evaporative concentration stages discussed earlier, but remain significantly depressed below 

MDL-NBS-HS-000001 REV 04 6-74 February 2005 


Drift-Scale THC Seepage Model 

ambient values after the boiling period. The magnesium depletion is caused by the precipitation 
of sepiolite early in the simulations. This depletion is also observed in the simulations of 
ambient conditions (Section 6.5.5.1) and is not consistent with observed water compositions at 
Yucca Mountain. One reason may be that sepiolite is either too stable or that it does not belong 
in the set of selected potential secondary minerals. REV01 simulations (ambient and thermal 
pulse) without sepiolite in the geochemical system did not predict such magnesium depletion. 
Another reason for underestimating magnesium concentrations could be the lack of primary 
magnesium-bearing minerals in simulations (e.g., biotite). These minerals, however, occur in 
small amounts in the repository host units. Younger calcite at Yucca Mountain has been 
reported to contain up to around 1 percent (by weight) magnesium (Wilson et al. 2000 
[DIRS 154279]). Therefore, taking this into account in simulations would also have an effect on 
predicted magnesium concentrations. This would contribute more magnesium in solution during 
calcite dissolution, but could also result in magnesium depletion upon calcite precipitation (under 
both thermal loading and ambient conditions). 

Predicted dissolved silica concentration profiles (Figure 6.5-38) show the same effects of 
dilution and evaporative concentration as most other species. Profiles of SiO2/Cl ratios (not 
shown here) have the same general shape as the Ca/Cl profiles (Figure 6.5-30) and indicate 
significant silica dissolution during the dilution stage, as would be expected. Later, continued 
reflux and boiling lead to an increase in concentrations. Predicted concentrations eventually 
reached values greater than the solubility of amorphous silica (around 350 ppm at 95C). This is 
because at this point, the calculated precipitation rate of amorphous silica, although quite fast, 
cannot keep up with the boiling rate. 

Predicted fluoride concentrations (Figure 6.5-37) follow a trend similar to the trend of silica and 
other aqueous species. The host rock is modeled with a small, ubiquitous amount of primary 
fluorite. As noted earlier, because the reaction rate of fluorite is fast, waters generally reach 
saturation with respect to this mineral. During the boiling and refluxing stage, concentrations up 
to around 40 ppm are predicted, which are much larger than the concentration (approximately 

1.4 ppm) calculated by equilibrating fluorite with the solution, using the maximum calcium 
concentrations (around 0.02 molal, see Figure 6.5-29) predicted during that time period. In this 
case also, the precipitation rate of fluorite cannot keep up with the boiling rate. Eventually, 
concentrations come back to values dictated by equilibrium of ambient waters with fluorite 
(typically in the 4 to 8 ppm range). 
MDL-NBS-HS-000001 REV 04 6-75 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-21. THC Seepage Model (Tptpll): Location of Model Grid Blocks for Data Shown on Figures 
6.5-22 through 6.5-37, for Each Time When Model Output Is Produced 

MDL-NBS-HS-000001 REV 04 6-76 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-22. THC Seepage Model (Tptpll): Time Profiles of Modeled Temperatures in Fracture Water 
in Areas of Highest Liquid Saturation above the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-77 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-23. THC Seepage Model (Tptpll): Time Profiles of Modeled Liquid Saturations in Fracture 
Water in Areas of Highest Liquid Saturation above the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-78 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-24. THC Seepage Model (Tptpll): Time Profiles of Modeled CO2 Gas Concentrations in 
Fracture Water in Areas of Highest Liquid Saturation above the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-79 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-25. THC Seepage Model (Tptpll): Time Profiles of Modeled pH in Fracture Water in Areas of 
Highest Liquid Saturation above the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-80 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-26. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Carbonate 
Concentrations (as HCO3) in Fracture Water in Areas of Highest Liquid Saturation above 
the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-81 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-27. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Chloride 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above the Drift 
Crown 

MDL-NBS-HS-000001 REV 04 6-82 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-28. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Nitrate 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above the Drift 
Crown 

MDL-NBS-HS-000001 REV 04 6-83 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-29. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Calcium 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-84 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-30. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Calcium to 
Chloride Ratios in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-85 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-31. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Sodium 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-86 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-32. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Sodium to 
Chloride Ratios in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-87 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-33. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Calcium to 
Carbonate Ratios in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-88 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-34. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Nitrate to 
Chloride Ratios in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-89 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-35. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Magnesium 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-90 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-36. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Silica 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Grid blocks are those with highest liquid saturation in fractures within a 25-m radius from drift center and a 
45 arc from the drift crown. Data are shown in the top graph for simulations using different initial water 
compositions (W0  W7). Except as noted below, all simulations are run using a stepwise-increasing 
infiltration rate (6, 16, and 25 mm/yr) and with vapor pressure lowering. Alternatives using Water W0 are 
shown in the bottom graph, including simulations without vapor pressure lowering (W0  eos3), with the 
smaller CO2 diffusion coefficient (Section 6.5.3), and with fixed 25 and 6 mm/yr infiltration rates 
(W0  6 mm/yr and W0  25 mm/yr, respectively). 

Figure 6.5-37. THC Seepage Model (Tptpll): Time Profiles of Modeled Total Aqueous Fluoride 
Concentrations in Fracture Water in Areas of Highest Liquid Saturation above the 
Drift Crown 

MDL-NBS-HS-000001 REV 04 6-92 February 2005 


Drift-Scale THC Seepage Model 

6.5.5.3 Mineral Alteration and Porosity/Permeability Changes (Tptpll) 
The predicted effect of water-rock-gas interactions on flow patterns around the drift is much 
more noticeable in the current model revision than in previous revisions. This is because 
simulations, using TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]), make use of a better 
treatment of mineral precipitation at the boiling front than previously. Also, the fracture porosity 
used in the current model is approximately half the value that was used in the REV01 
simulations. 

To provide a baseline for evaluating the effect of mineral precipitation and dissolution on flow, 
results of a TH simulation are evaluated first. A contour plot of predicted liquid saturations for 
the simulation (Figure 6.5-38) shows that at 2,400 years, well after the end of the boiling phase, 
the predicted liquid saturations in the vicinity of the drift reflect the capillary barrier effect of the 
drift. Ambient water percolation is deflected around the drift (even at much higher infiltration 
rates than considered here). As a result, liquid saturations in fractures are somewhat increased 
above the drift crown, relative to ambient values, and significantly decreased below the drift 
(shadow zone). 

In contrast, a similar contour map of liquid saturations predicted with Water W0 using a THC 
simulation (Figure 6.5-39a) shows that after the same simulated time period, a zone of higher 
liquid saturation has formed 7 to 8 m above the drift, reflecting partial deflection of flow at this 
location. This kind of umbrella effect results from a thin region of significantly lower 
permeability (Figure 6.5-39b) created by prior mineral deposition at the boiling front. In this 
case, the permeability has decreased by a factor of about 10 in this area. As a result, the shadow 
zone extends somewhat deeper below the drift, and liquid saturations at the drift crown are 
somewhat reduced, compared to the TH prediction. Similar figures for results using Water W5 
as input initial composition show a more pronounced umbrella effect (Figure 6.5-40a), with 
the permeability decreasing by two to three orders of magnitude (Figure 6.5-40b) in the thin 
region of mineral precipitation. The results using the other waters are very similar. 
Consequently, the shadow zone below the drift is extended significantly. The time of fracture 
rewetting around the drift is delayed, and the vertical flux at the drift crown is reduced by up to a 
factor of 10 compared to the ambient flux without drift opening (Figure 6.5-41a). 

Other THC simulations using Water W0 and the two fixed infiltration rates (6 and 25 mm/yr), as 
well as the simulation neglecting water-vapor-pressure lowering, also predict to various degrees 
an umbrella effect above the drift (Figure 6.5-41b). The effect is most noticeable with the 
simulation without vapor-pressure lowering, which predicts that the rewetting of fractures at the 
drift crown is delayed until approximately 20,000 years and around 12,000 years in the matrix. 
However, in this case, this stronger effect could be unrealistic because some amount of 
water-vapor-pressure lowering is expected to occur in the natural system. By retaining more 
water in the matrix, fracture rewetting would be facilitated, because less imbibition of fracture 
water would occur into the matrix. 

The vertical flux predicted at the drift crown at 2,000 years (Figure 6.5-41a or b), without 
considering THC processes, can be compared with the vertical flux value shown in Drift-Scale 
Coupled Processes (DST and TH Seepage) Models (BSC 2004 [DIRS 170338], Figure 6.2.3.1-3) 
for the same time period. Both values are consistent (2.9  107 kg m2 s1, which yields 

MDL-NBS-HS-000001 REV 04 6-93 February 2005 


Drift-Scale THC Seepage Model 

approximately 9.5 mm/yr using the water density at the corresponding temperature [960 kg 
m-3]). The flux peak on Figure 6.5-41 (a or b) at 1,400 years (1.07  106 kg m2 s1) 
corresponds to approximately 35 mm/yr, consistent with values predicted a few meters above the 
drift at 1,000 years in Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338], Figure 6.2.3.1-3). As already mentioned in Sections 6.5.5.1 and 6.5.5.2, these 
peaks may not be fully resolved. However, these are much smaller than the percolation rate 
required for seepage to occur (250 mm/yr in Drift-Scale Coupled Processes (DST and TH 
Seepage) Models [BSC 2004 DIRS 170338], Section 6.2.3.2.3). When THC processes are taken 
into account, as discussed earlier, percolation rates at the drift crown are even smaller because 
percolating water is partly diverted by the zone of lower permeability created by mineral 
precipitation above the drift. However, the model considers homogeneous fracture permeability 
and, therefore, cannot capture potential flow focusing through this zone of lower permeability. 
Because this zone is very thin and located several meters above the drift crown (Figure 6.5-40b), 
the focusing of flow locally through this zone is not anticipated to increase vertical fluxes at the 
drift crown much beyond what is predicted without considering THC processes. 

In all simulations, the permeability decrease results primarily from the precipitation of 
amorphous silica and, to a lesser extent, calcite (Figures 6.5-42 through 6.5-45). The fracture 
porosity is predicted to decrease by approximately 4 to 7 percent, depending on the simulation. 
The maximum porosity decrease is predicted to occur in a thin zone during refluxing at the edge 
of the dryout zone, before the collapse of this zone around the drift. During that time, salt and 
gypsum precipitation account for up to around 15 percent of the volume of precipitated minerals 
(Figure 6.5-44). Gypsum precipitation is noticeable only with Waters W0 and W7, as expected, 
because these waters initially contain a higher proportion of calcium. Both salts and gypsum 
quickly redissolve when the fractures rewet. By 2,400 years, with all simulations except that 
without vapor-pressure lowering, fractures have rewetted, and the amount of precipitated solids 
(Figure 6.5-45) is predicted to remain essentially unchanged for the remainder of the entire 
simulated time period. For a long period of time in the simulation without vapor-pressure 
lowering, any water entering fractures immediately evaporates. This causes further salt 
deposition until well after 2,400 years, most notably directly above the drift crown 
(Figure 6.5-42), even though temperatures are well below boiling by this time. Increasing the 
infiltration rate from a fixed rate of 6 to 25 mm/yr does not significantly alter the amount of 
precipitated solids, but shifts the region of mineral deposition towards the drift by approximately 
1 m (Figure 6.5-43). 

Other minerals besides amorphous silica, calcite, gypsum, and salts form or dissolve in small 
amounts. Some albite dissolution accompanied by stellerite precipitation is predicted to occur in 
fractures (typically 0.1 percent of the porosity or less). Illite and stellerite are predicted to be the 
most significant minerals precipitating in the rock matrix, with maximum amounts around 
1 percent of the matrix porosity. 

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Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

Figure 6.5-38. TH Simulation (Tptpll): Contour Plot of Modeled Liquid Saturation and Temperature 
Contours (C) in Fractures at 2,400 Years (No Chemical Reactions) 

MDL-NBS-HS-000001 REV 04 6-95 February 2005 


Drift-Scale THC Seepage Model 

(a) 
(b) 
Output DTN: LB0302DSCPTHCS.001. 

Figure 6.5-39. THC Simulation (Tptpll  Water W0): Contour Plot of Modeled (a) Liquid Saturation and 
Temperature Contours (C) and (b) Permeability Change in Fractures at 2,400 Years 

MDL-NBS-HS-000001 REV 04 6-96 February 2005 


Drift-Scale THC Seepage Model 

(a) 
(b) 
Output DTN: LB0302DSCPTHCS.001. 

Figure 6.5-40. THC Simulation (Tptpll  Water W5): Contour Plot of Modeled (a) Liquid Saturation and 
Temperature Contours (C) and (b) Permeability Change in Fractures at 2,400 Years 

MDL-NBS-HS-000001 REV 04 6-97 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.002, LB0307DSTTHCR2.002. 

NOTE: Except as noted below, simulations consider vapor-pressure lowering and a stepwise-increasing infiltration 
rate (Table 6.5-2). Results are shown for various thermal loading simulations including: no chemical 
reactions (TH), five different input water compositions (W0, W4 to W7), no vapor pressure lowering 
(W0  eos3), and two fixed infiltration rates (W0  6 mm/yr and W0  25 mm/yr). Predicted fluxes are also 
shown for ambient conditions (Ambient) without thermal load or a drift opening. 

Figure 6.5-41. TH Simulations and THC Seepage Model (Tptpll): Comparison of Modeled Liquid Flux at 
the Drift Crown in Fractures at 2,400 Years 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.001, LB0307DSTTHCR2.001. 

NOTE: Profiles are shown for simulated times of 600 and 2,400 years for simulations using Water W0 with 
vapor-pressure lowering (eos4) and without this effect (eos3). Infiltration rates are increasing from 6 to 
16 to 25 mm/yr in a stepwise manner (Table 6.5-3). 

Figure 6.5-42. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral Abundances above 
the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-99 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.001, LB0307DSTTHCR2.001. 

NOTE: Profiles are shown for simulated times of 600 and 2,400 years for simulations using Water W0 with 
vapor-pressure lowering and two different fixed infiltration rates (6 and 25 mm/yr). 

Figure 6.5-43. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral Abundances above 
the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-100 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.001, LB0307DSTTHCR2.001. 

NOTE: Profiles are shown for a simulated time of 600 years, for simulations using vapor-pressure lowering and 
four different input water compositions (W4 to W7). 

Figure 6.5-44. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral Abundances above 
the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-101 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0302DSCPTHCS.001, LB0307DSTTHCR2.001. 

NOTE: Profiles are shown for a simulated time of 2,400 years for simulations using vapor-pressure lowering and 
four different input water compositions (W4 to W7). These profiles remain essentially unchanged for the 
rest of the simulated time period (100,000 years). 

Figure 6.5-45. THC Seepage Model (Tptpll): Vertical Profile of Predicted Mineral Abundances above 
the Drift Crown 

MDL-NBS-HS-000001 REV 04 6-102 February 2005 


Drift-Scale THC Seepage Model 

6.5.5.4 Simulations of Ambient Conditions (Thermodynamic Data Sensitivity) 
Results of simulations of ambient conditions are presented below to illustrate the model 
sensitivity to thermodynamic data and to justify the selection of the thermodynamic data used in 
this study (Appendix C and Section 4.1.4). These simulations are run with the three 
thermodynamic data sets discussed in Section 6.4.8: Set 1 representing the data adopted for this 
study, and Set 2 and Set 3 representing alternatives (mostly data from the YMP database 
data0.com.R2) that were considered, but not chosen for reasons given below. These simulations 
are run with the HD-PERM input water composition (Table 6.2-1). For consistency between all 
runs, the total aluminum concentration of the initial water in runs using all data sets has been 
recomputed for equilibrium with the illite phase from these alternative thermodynamic data sets. 

Predicted ambient water composition trends with the three sets of thermodynamic data are shown 
in Figures 6.5-46 through 6.5-48. Set 2 leads to the least stable predicted compositions, 
including unrealistic pH fluctuations to near 10, very large depletion of calcium and magnesium, 
and an increase in sodium concentrations to around 500 mg/L after 100,000 years. On the other 
hand, the simulation with Set 1 predicts the most stable trends. Using Set 3 (i.e., by 
incorporating revised zeolite thermodynamic data into Set 2), trend stability improves 
considerably, but the magnitude of concentration changes over the 100,000-year simulated time 
period is still quite large for most species. With all three thermodynamic data sets, unrealistic 
magnesium depletion in water is predicted to occur, primarily on account of sepiolite 
precipitation. However, the least predicted magnesium depletion occurs when using Set 1. Note 
also that simulations using Set 2 and Set 3 predict the total dissolution of calcite initially present 
in the model (with precipitation of zeolites and clays having calcium). Using Set 1, calcite 
dissolution is not predicted. For these reasons, Set 1 is deemed a better alternative than either 
Set 2 or Set 3, because it yields long-term water compositions more consistent with observed 
data than the other two sets. For these reasons, Set 1 has been adopted for the rest of this study. 
It should be recalled here that most of these thermodynamic data are from the 
YMP database data0.com.R2, with changes from this database documented under 
DTN: LB0307THMBDRTM.001 [DIRS 164434] (and summarized in Section 4.1.4 for major 
changes). 

These simulations illustrate that for any fixed water composition close to equilibrium with a 
mineral assemblage, a small change in thermodynamic data can reverse the calculated degree of 
saturation (i.e., from supersaturation to undersaturation and vice versa) of minerals in that water 
and, thus, reverse the calculated direction of reactions between these phases. In such instances, 
different water-composition trends can be predicted regardless of the magnitude of reaction rates 
assumed in the model. In such cases, the reliability of model results can be more affected by 
thermodynamic data than by kinetic data. 

Free energies for minerals such as clays and zeolites may never be known so accurately that 
adjustments within the (sometimes already small) uncertainty in these values will not be 
necessary for ambient simulations lasting thousands of years. Whether these adjustments 
provide values that are better, or not, than the data0.ymp.R2 data depends on the data themselves 
and their intended use. For clay minerals, because the adjustments have been made to better 
match measured water compositions at Yucca Mountain, these adjustments may in part 
compensate for other effects not directly modeled such as more complex solid solutions or ion 

MDL-NBS-HS-000001 REV 04 6-103 February 2005 


Drift-Scale THC Seepage Model 

exchange processes. Therefore, the thermodynamic data for clays and zeolites that are used in 
this model may not be better than those in the data0.ymp.R2 database, but are better suited for 
long-term reactive transport simulations at Yucca Mountain. 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Infiltration is constant at 6 mm/yr. 

Figure 6.5-46. Predicted Water Compositions without Thermal Loading (in the Tptpll Lithostratigraphic 
Unit at the Repository Location) Using the Thermodynamic Data Adopted for this Study 
(Data Set 1  Appendix C) 

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Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Infiltration is constant at 6 mm/yr. 

Figure 6.5-47. Predicted Water Compositions without Thermal Loading (in the Tptpll Lithostratigraphic 
Unit at the Repository Location) Using Thermodynamic Data from Data Set 2 
(Section 6.4.8) 

MDL-NBS-HS-000001 REV 04 6-105 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Infiltration is constant at 6 mm/yr. 

Figure 6.5-48. Predicted Water Compositions without Thermal Loading (in the Tptpll Lithostratigraphic 
Unit at the Repository Location) Using Thermodynamic Data from Data Set 3 
(Section 6.4.8) 

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Drift-Scale THC Seepage Model 

6.5.5.5 Sensitivity to Revised Matrix Porosity and Thermal Values 
After the simulations presented earlier in this section were run, revised porosity and thermal 
property data for the various stratigraphic layers in the UZ at Yucca Mountain became available. 
The potential impact of the new parameter values (DTN: LB0402THRMLPRP.001 
[DIRS 168481]) has been evaluated through sensitivity analyses. Simulations th6_1.45kw, 
thc6_w0, and thc6_w0b (Table 6.5-5) have been rerun using the revised properties but kept all 
other input data (Section 6.5.3) unchanged. These additional model runs are summarized in 
Table 6.5-6. 

Table 6.5-6. Tptpll THC Model Sensitivity Runs Using Revised Matrix Properties from Table 6.5-7 

Input Water 
Composition 
(Table 6.2.1) 
Thermo. Data 
Set 
(Section 6.4.8) 
Infiltration Case 
(Table 6.5-2) 
Equation of State 
(EOS) Modulea Simulation Type Run ID 
None None Mean Infiltration EOS4 TH (two-dimensional) th6_1.45kw_i1 
W0 Set 1 Mean Infiltration EOS4 THC (two-dimensional) thc6_w0_i1 
W0 Set 1b Mean Infiltration EOS4 THC (two-dimensional) thc6_w0b 

a 

TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]) flow modules: EOS3 neglects vapor pressure lowering due to 

capillary pressure; EOS4 takes this effect into account. 
b A CO2 molecular diameter of 2.5  1010 m (Section 4.1.6) is used for this run instead of the value of 1  1010 m input 

in the other THC simulation listed here (Section 6.5.3). 
NOTE: Run IDs are used in Output DTNs: LB0404DSTTHCR2.001 and LB0404DSTTHCR2.002; see Appendix G. 

The revisions to matrix porosity and thermal properties affected primarily hydrogeologic units 
other than the repository units (Table 6.5-7). The properties of the repository units are 
essentially unchanged (shaded data on Table 6.5-7). 

The modeling procedure is unchanged from that described in Section 6.5.3. Prior to running the 
TH and THC simulations, because of the matrix properties revision, a simulation without heat 
load, drift, or reactive transport is run until steady-state thermal and hydrologic conditions are 
achieved. These conditions are then used as the initial thermal and hydrologic state for heat load 
simulations. 

Comparisons of TH simulations results obtained using revised and original rock matrix 
properties are shown in Figures 6.5-49 through 6.5-53 (original and new simulations th6_1.45kw 
and th6_1.45kw_i1, respectively). 

MDL-NBS-HS-000001 REV 04 6-107 February 2005 


Table 6.5-7. Summary of Revised and Original Rock Matrix Properties 

Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 6-108 February 2005 

UZ Model 
Matrix Porosity Grain Density Heat Capacity Bulk Dry Conductivity Bulk Wet Conductivity 
(kg/m3) (J/Kg-K) (W/m-K) (W/m-K) 
Layer Revised Original Revised Original Revised Original Revised Original Revised Original 
tcw11 0.119 0.118 2486 2514 985.0 985.0 1.30 1.30 1.81 1.80 
tcw12 0.119 0.118 2486 2514 985.0 985.0 1.30 1.30 1.81 1.80 
tcw13 0.211 0.0457 2385 2274 1040 1040 0.572 0.670 0.909 0.794 
ptn21 0.385 0.354 2374 2288 1040 1040 0.490 0.489 1.06 1.07 
ptn22 0.385 0.354 2374 2288 1040 1040 0.490 0.489 1.06 1.07 
ptn23 0.385 0.354 2374 2288 1040 1040 0.490 0.489 1.06 1.07 
ptn24 0.385 0.354 2374 2288 1040 1040 0.490 0.489 1.06 1.07 
ptn25 0.385 0.354 2374 2288 1040 1040 0.490 0.489 1.06 1.07 
ptn26 0.385 0.251 2374 2283 1040 1040 0.490 0.537 1.06 0.957 
tsw31 0.0775 0.0457 2441 2274 1012 1040 0.900 0.670 1.11 0.794 
tsw32 0.119 0.118 2486 2514 985.0 985.0 1.30 1.30 1.81 1.80 
tsw33 0.143 0.143 2344 2358 985.0 985.0 1.16 1.16 1.68 1.68 
tsw34 0.129 0.129 2466 2466 985.0 985.0 1.42 1.42 2.07 2.07 
tsw35 0.149 0.149 2325 2325 985.0 985.0 1.28 1.28 1.89 1.89 
tsw36 0.106 0.106 2473 2473 985.0 985.0 1.49 1.49 2.13 2.13 
tsw37 0.106 0.106 2473 2473 985.0 985.0 1.54 1.49 2.20 2.13 
tsw38 0.0360 0.046 2396 2274 1040 1040 0.688 0.670 0.796 0.794 
tsw39 0.385 0.046 2374 2274 1040 1040 0.490 0.670 1.06 0.794 
ch1(v,z) 0.385 0.354 2374 2288 1040 1040 0.490 0.489 1.06 1.07 
ch2(v,z) 0.333 0.328 2504 2256 1038 1038 0.595 0.600 1.26 1.27 
ch3(v,z) 0.333 0.328 2504 2256 1038 1038 0.595 0.600 1.26 1.27 
ch4(v,z) 0.333 0.328 2504 2256 1038 1038 0.595 0.600 1.26 1.27 
ch5(v,z) 0.333 0.328 2504 2256 1038 1038 0.595 0.600 1.26 1.27 
ch6(v,z) 0.333 0.328 2504 2256 1038 1038 0.595 0.600 1.26 1.27 
pp4 0.300 0.297 2557 2103 1040 1040 0.569 0.538 1.13 1.11 
pp3 0.300 0.297 2557 2103 1040 1040 0.569 0.538 1.13 1.11 
pp2 0.255 0.233 2587 2385 1012 1009 0.741 0.733 1.33 1.34 
pp1 0.277 0.273 2519 2038 1040 1040 0.596 0.564 1.15 1.13 
bf3 0.194 0.188 2485 2106 1021 1018 0.788 0.757 1.34 1.33 
bf2 0.264 0.262 2506 2012 1040 1040 0.611 0.576 1.16 1.14 

NOTES: Revised data are from DTN: LB0402THRMLPRP.001 [DIRS 168481] (rounded to the number of significant digit shown). 

Original data are from DTN: LB0210THRMLPRP.001[DIRS 160799] (rounded to the number of significant digit shown). 

Fracture thermal properties are derived using matrix properties as discussed in Section 6.4.6. Other rock properties data are identical to 

those listed in Table 6.4-1 for REV02 simulations. The data for repository units are shaded. 


Drift-Scale THC Seepage Model 

THC model results are compared in Figures 6.5-54 through 6.5-70 (simulations thc6_w0 and 
thc6_w0_i1 using original and revised properties, respectively). These figures are directly 
comparable to Figures 6.5-4 through 6.5-9, and 6.5-21 through 6.5-37. The latter are generated 
for areas of maximum liquid saturation above the drift as described in Section 6.5.5.3.2. 

Temperatures differ by less than one degree between the original and revised simulation results 
(Figures 6.5-49 and 6.5-55), the revised simulation results showing a slight temperature decrease. 
Both TH simulations predict the rewetting of fractures at the drift crown at around the same time 
(~1400 years) (Figure 6.5-50). At the drift side and base, rewetting of fractures is predicted to 
occur up to 200 years earlier for the case using the revised properties (Figure 6.5-50). This small 
difference is not observed with the THC simulations, which predict rewetting to occur around 
2000 years at all three drift wall locations in both cases. However, although the maximum time 
step used in the THC seepage model is 5 years (Section 6.5.3), the time of rewetting is not well 
resolved in Figure 6.5-50, because the model-result printout interval is 200 years. 

In the most liquid saturated regions above the drift, differences in predicted water chemistries 
and CO2 gas concentrations between the original and revised cases are quite small 
(Figures 6.5-57 through 6.5-70). These small differences are negligible compared to the spread 
in model results obtained when using different input water chemistries, infiltration rates, and 
model conceptualizations (Figures 6.5-21 through 6.5-37). Differences in predicted water 
compositions at other locations around the drift are presented in Post-Processing Analysis for 
THC Seepage (BSC 2004 DIRS 169858]) and are also negligible. Therefore, it can be concluded 
that the matrix porosity and thermal properties revisions discussed here have essentially no effect 
on predicted water and gas chemistries in the vicinity of the drift. This would be expected given 
the fact that the thermal properties of the repository units are essentially unchanged between 
these two cases, yielding nearly identical temperatures around the drift. 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

Figure 6.5-49. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled Temperatures 
in Fractures at Three Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-110 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

Figure 6.5-50. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled Liquid 
Saturations in Fractures at Three Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-111 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs : LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

Figure 6.5-51. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled Liquid 
Saturations in Matrix at Three Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-112 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

Figure 6.5-52. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled Air Mass 
Fractions in the Gas Phase in Fractures at Three Drift-Wall Locations 

MDL-NBS-HS-000001 REV 04 6-113 February 2005 


Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: The peaks at the start and end of the boiling period (at ~50 and ~1,400 years, respectively) may not be 
fully resolved. 

Figure 6.5-53. TH Simulation (Revised vs. Original Properties): Time Profiles of Modeled Downward 
Water Flux at the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-54. THC Simulations (Revised vs. Original Properties): Location of Model Grid Blocks for 
Data Shown on Figures A-7 through A-22, for Each Time When Model Output 
Is Produced 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-55. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled 
Temperatures in Fractures in Areas of Highest Liquid Saturation above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-56. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Liquid 
Saturations in Fractures in Areas of Highest Liquid Saturation above the Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-57. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled CO2 Gas 
Concentrations in Fractures in Areas of Highest Liquid Saturation above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-58. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled pH in 
Fracture Water in Areas of Highest Liquid Saturation above the Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-59. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Carbonate Concentrations in Fracture Water in Areas of Highest Liquid 
Saturation above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-60. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Chloride Concentrations in Fracture Water in Areas of Highest Liquid Saturation 
above the Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-61. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Nitrate Concentrations in Fracture Water in Areas of Highest Liquid Saturation 
above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-62. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Sulfate Concentrations in Fracture Water in Areas of Highest Liquid Saturation 
above the Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-63. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Fluoride Concentrations in Fracture Water in Areas of Highest Liquid Saturation 
above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-64. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Calcium Concentrations in Fracture Water in Areas of Highest Liquid Saturation 
above the Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-65. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Calcium to Carbonate Concentration Ratios in Fracture Water in Areas of 
Highest Liquid Saturation above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-66. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Magnesium Concentrations in Fracture Water in Areas of Highest Liquid 
Saturation above the Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-67. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Sodium Concentrations in Fracture Water in Areas of Highest Liquid Saturation 
above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-68. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Sodium to Chloride Concentration Ratios in Fracture Water, in Areas of Highest 
Liquid Saturation above the Drift Crown 

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Drift-Scale THC Seepage Model 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-69. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Potassium Concentrations in Fracture Water in Areas of Highest Liquid 
Saturation above the Drift Crown 


Output DTNs: LB0307DSTTHCR2.002, LB0404DSTTHCR2.002. 

NOTE: Grid blocks are those with the highest liquid saturation in fractures within a 25-m radius from drift center 
and a 45 arc from the drift crown. Data are shown for simulations using the same initial water 
composition (W0). Both simulations are run using a stepwise-increasing infiltration rate (6, 16, and 
25 mm/yr) and with vapor pressure lowering. 

Figure 6.5-70. THC Simulations (Revised vs. Original Properties): Time Profiles of Modeled Total 
Aqueous Silica Concentrations in Fracture Water in Areas of Highest Liquid Saturation 
above the Drift Crown 

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Drift-Scale THC Seepage Model 

6.6 MODEL UNCERTAINTY 
6.6.1 Potential Sources of Uncertainty 
The simulations of THC processes include coupling between heat, water, and vapor flow; 
aqueous and gaseous species transport; kinetic and equilibrium mineralwater reactions; and 
feedback of mineral precipitationdissolution on porosity, permeability, and capillary pressure 
(hydrologic properties) for a dual-permeability (fracture-matrix) system. As such, the THC 
seepage model takes into account the effects of mineral dissolution and precipitation, carbon 
dioxide exsolution and transport in the region surrounding emplacement drifts, and resulting 
changes to porosity, permeability, seepage, and chemical composition of percolating waters. The 
large number of input parameters, numerical methods implemented in simulating these complex 
coupled processes, and simplification and approximations pertaining to the physical setup of the 
model all contribute to uncertainties in the predictions from these models. Uncertainties in 
model input data that could affect calculated water and gas compositions include: 

 Thermodynamic data (equilibrium constants for mineralwater reactions and aqueous 
species dissociation) 
 Kinetic data (rate constants, reactive surface areas, and activation energies) 
 Initial compositions of pore water and pore gas 
 Initial composition of infiltrating water and gas 
 Infiltration rates 
 Transport parameters (diffusion coefficients of aqueous species and gases, tortuosity) 
 Initial rock mineralogy (model location and stratigraphy) 
 Number of geochemical constituents (including the simulations) 
 Number and types of potential secondary mineral phases 
 Rock thermal, physical, and hydrologic properties (including input data for both water-
saturated and unsaturated rock). 
Process model uncertainties also may affect the calculated water and gas compositions. These 
include: 

 Formulation of models to simulate fluid flow in dual permeability media (e.g., 
fracture-matrix interactions; and relative permeability and saturation-capillary pressure 
models) 
 Activity coefficient models 
 Kinetic mineral precipitation and dissolution models 
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Drift-Scale THC Seepage Model 

 Inclusion or exclusion of certain specific thermal, hydrologic, or chemical processes (e.g., 
active fracture model, vapor pressure lowering, mineral solid solutions, redox reactions). 
Uncertainties in the setup of the model could also affect the results of the THC seepage model. 
These include: 

 Physical model representation (stratigraphic and geologic extrapolations) 
 Representation of the fracture and matrix continua in the model mesh 
 Model discretization (in space and time) 
 Boundary conditions (e.g., drift open versus closed to fluid flow). 
Of these uncertainties, those directly affecting chemical processes would be most likely to have 
the most effect on predicted water and gas compositions. Such uncertainties, their treatment in 
the model, and their effect on model results are summarized in Table 6.6-1. 

Note that temperature is also a critical parameter affecting modeling results, although it cannot 
be considered an uncertainty by itself (temperature can generally be predicted to within a few 
degrees; therefore, it is not included in Table 6.6-1). Temperature directly affects equilibrium 
constants and reaction rates, the degree of water evaporation and boiling, and the amount of 
carbon dioxide volatilization from pore water, with direct implications for computed water and 
gas chemistries. Parameters affecting predicted temperatures could significantly affect computed 
aqueous and gas species concentrations. However, important changes in design heat load are 
likely to affect model results more than uncertainties associated with input parameters used to 
calculate temperatures (e.g., rock thermal conductivity and heat capacity). In this report, only 
the heat load from the current repository design is considered. This heat load leads to 
temperatures in the vicinity of emplacement drifts that exceed the boiling point of water for 
several hundred years if ventilation is not maintained after the 50-year preclosure period. The 
increased water-rock-gas interactions resulting from higher temperatures are expected to affect 
water chemistry and flow to a greater extent than if a lower heat load were considered. 
However, some of the effects of elevated temperatures, such as dryout and reduced 
permeabilities caused by mineral precipitation, could have positive aspects with respect to 
repository performance. 

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Drift-Scale THC Seepage Model 

Table 6.6-1. Summary of Uncertainties Affecting Chemical Processes in the THC Seepage Model 

Category Issue Treatment Consequences 
Conceptual 
uncertainties 
Geochemical system 
considered (minerals, 
gases, and aqueous 
species) 
Treated by including major rock-forming minerals, major 
aqueous species, and major gases of interest (CO2, air, 
water vapor) in the system, and also minor minerals such 
as clays. 
Effects of secondary mineral phase precipitation is most 
uncertain at higher temperatures. 
Uncertainty is limited under ambient conditions if ambient 
water concentrations can be reproduced. 
Trace minerals and aqueous species are not considered 
(not within the current scope for the THC seepage model). 
However, results of model validation (Section 7) against 
the Drift Scale Test and other experiments suggest that the 
geochemical system, as modeled, is constrained enough 
to reproduce the experimental data within validation 
criteria. Also, the range of incoming waters considered in 
the model capture, at least in some part, the range of 
uncertainties related to the geochemical system. 
Precipitation of secondary phases not currently included in 
simulations could affect the predicted composition of 
waters around the drift at high temperature. Reactions 
involving trace minerals (e.g., other clay minerals or Mg, 
Fe, Mn minerals) could affect pH, which in turn could affect 
the precipitation/dissolution of other mineral phases and 
indirectly affect the concentrations of major species. 
The type of mineral precipitating could also affect the 
calculated porosity change (i.e., effect of different molar 
volume), although this effect would be minimal because 
the bulk of the precipitation consists of amorphous silica. 
Uncertainties affecting the precipitation of secondary 
phases would increase at near dryout conditions; however, 
such conditions (i.e., small liquid saturations) are not 
conducive to seepage. 
Drift wall 
conceptualization: 
closed vs. open to 
advective fluid flow; 
also, hydrologic effect 
of ventilation is 
neglected 
Both cases of open and closed drift wall are addressed. 
Infiltration rates (even at high rates indicative of future wet 
climates) are below seepage thresholds, so there is little 
effect of closing the drift wall on water percolation fluxes 
around the drift. 
Evaporative concentration effects (due to ventilation) are 
indirectly taken into account by downstream in-drift 
evaporation models. 
Boundary conditions of pressure and relative humidity in 
the drift could affect evaporative concentration effects at 
the drift wall, mostly during the preclosure ventilation 
period. 
In-drift interactions are not considered (this is not a goal of 
the THC seepage model). 
Precipitation/nucleation 
kinetics 
Not treated. 
This affects minerals such as silica and calcite, which have 
fast reaction rates. Implementation of a supersaturation 
gap for calcite (as done here) may approximate the 
nucleation processes. 
Silica precipitation is modeled with a very fast reaction 
rate. 
In areas where rapid boiling occurs, predicted aqueous 
silica concentrations may be overestimated, and silica 
precipitation underestimated. However, the water 
saturation in these areas is very small, and therefore the 
actual amounts of silica are minute. 

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Table 6.6-1. Summary of Uncertainties Affecting Chemical Processes in the THC Seepage Model (Continued) 

Category Issue Treatment Consequences 
Conceptual 
uncertainties 
(cont.) 
Water chemistry is not 
computed below a set 
water saturation limit 
(105) or above a set 
ionic strength limit (4) 
(activity coefficient 
model limitations) 
Salt precipitation in the last remaining water when boiling 
or evaporating is taken into account using a simple 
approach (Section 6.4.5). These salts are then available 
for dissolution upon rewetting, providing a conceptually 
correct (although simplified) representation of actual 
processes accompanying dryout and rewetting. 
The type and sequence of salts assumed to precipitate 
upon dryout affects computed water compositions at the 
very early stages of rewetting only. Changes in nitrate-
chloride ratios during rewetting may be an artifact of this 
approach. However, during this initial rewetting stage, the 
liquid saturation is low and the associated volume of water 
is small, immobile, and unlikely to contribute to seepage. 
Vapor pressure 
lowering due to 
capillary pressure 
Treated by running simulations with and without vapor 
pressure lowering. 
No large effect on computed gas and water chemistries. 
However, a large effect on the predicted time of rewetting 
of fractures and matrix at the drift wall is observed. 
Neglecting vapor pressure lowering could increase the 
effect of evaporative concentration around the drift, 
resulting in higher water salinities, although this is not 
observed. 
Oxidation-reduction 
processes are 
neglected 
Not treated (considers only oxidized conditions). 
Oxidizing conditions prevail in the unsaturated zone at 
Yucca Mountain such that the redox species considered in 
the THC seepage model (iron and sulfate) occur only in 
their oxidized state. 
Limited anticipated effect because of the prevailing 
oxidized conditions. Likely no effect for iron and sulfate in 
the current models. Redox reactions involving microbial 
processes and species not presently modeled (nitrates, 
phosphates) could have a limited effect on pH. 
Mineral solid-solutions Ideal solid-solution treatment for clays; no treatment for 
other minerals. 
Compositions of primary solid solution phases, when 
known, are directly taken into account by the relative 
amounts of individual end-members input into the model. 
Individual mineral phases with fixed solid-solution 
compositions (determined by analysis) are included in the 
simulations (e.g., zeolites). 
Limited anticipated effect because solid solutions are 
partially treated as described in the adjacent table column. 
This primarily affects the composition of precipitating alkali 
feldspars (thus affecting predicted Na and K 
concentrations). However, these minerals form nearly 
pure secondary phases in nature (i.e., as modeled). 
Zeolites in the repository host units (mostly stellerite) are 
not abundant and not particularly variable in composition. 
Ion-exchange and 
surface complexation 
Not explicitly treated. However, precipitation/ dissolution of 
mineral solid solutions and pure end-member phases (for 
clays and zeolites, respectively), accounts for this to some 
degree. 
Dominant primary rock minerals in the repository host units 
are not strong ion exchangers (for major ions). 
THC seepage simulations do not include trace elements 
that could be strongly affected by surface complexation. 
Limited effect for the current application range of the THC 
seepage model. However, a limited shift in the predicted 
concentrations of Na, K, Ca, and Mg could still affect 
significantly the composition of end-brines upon complete 
evaporation. 

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Table 6.6-1. Summary of Uncertainties Affecting Chemical Processes in the THC Seepage Model (Continued) 

Category Issue Treatment Consequences 
Conceptual 
uncertainties 
(cont.) 
Capillary pressure 
effect on chemical 
potentials of reacting 
species 
Not treated. 
It is taken indirectly into account through adjustments of 
thermodynamic data such that ambient water compositions 
can be reproduced. 
Could potentially shift predicted concentrations of some 
species. 
Data 
uncertainties 
Infiltration water and 
initial pore-water 
composition 
Five alternate water analyses are used in REV02 
simulations, covering fairly well the compositional 
variability of pore waters in repository host units. 
Uncertainty can be assessed by comparing predictions of 
ambient water compositions with measured ambient 
pore-water compositions and pore-gas CO2 
concentrations. 
Input water compositions affect predicted water 
compositions around the drift, and likely more so through 
infiltration/transport than through reaction. 
Carbon dioxide partial 
pressures 
Composition of infiltrating water input into the model 
essentially dictates the boundary CO2 pressure; therefore, 
the uncertainty in infiltrating water composition overcomes 
this uncertainty. However, various infiltrating waters are 
assumed to equilibrate at the same boundary CO2 
pressure (around 3200 ppmv). 
A large effect is not expected within the possible range of 
observed natural concentrations because the range of 
thermally induced CO2 partial pressures is much larger 
than (and thus overwhelms) background concentrations. 
Thermodynamic and 
kinetic data 
Treated partly through sensitivity studies on long-term 
behavior of ambient system chemistry, assuming a fixed 
infiltration rate and different thermodynamic data for clays 
and zeolites (the model is very sensitive to the 
thermodynamic data for these minerals). 
When possible within the uncertainty of the original data, 
treated by revising the data to reproduce observed water 
compositions and mineralogical data. 
Other uncertainties treated through model validation (Drift 
Scale Test and laboratory experiments). 
Currently one of the main uncertainties affecting predicted 
water compositions around the drift. However, it can be 
constrained by adjustments and model validation against 
observed data, such that ambient simulations predict 
concentrations consistent with observed values. 
Host rock mineralogy Treated by considering alternative drift locations (Tptpmn 
versus Tptpll host rock unit). 
Bulk chemical composition of the repository host units do 
not differ significantly. 
No significant effect on the predicted compositions of major 
aqueous species. Small amounts of fast reacting minerals 
containing elements present in minor quantities in pore 
water (e.g., fluorite) can have a large effect on the 
predicted concentrations of these minor species (e.g., F) 

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Table 6.6-1. Summary of Uncertainties Affecting Chemical Processes in the THC Seepage Model (Continued) 

Category Issue Treatment Consequences 
Data 
uncertainties 
(cont.) 
Infiltration rates Alternative infiltration rate scenarios are used. Between 6 and 25 mm/yr, there is a small effect on 
predicted concentrations at the drift wall. The effect would 
be greater under lower rates of infiltration (when reaction 
effects start to dominate transport), but such conditions 
would be less likely to cause in-drift seepage. 
At high-infiltration rates, most conducive to in-drift 
seepage, water compositions are more a function of 
transport than of reaction with host rock minerals, such that 
the uncertainty regarding the composition of the infiltration 
water, rather than the rate of mineral dissolution/ 
precipitation, becomes more important. 
Parameter 
uncertainties 
Heterogeneity Heterogeneous fracture permeability was used in an earlier 
(REV01) model, but the current model assumes 
homogeneous fracture permeability. 
Heterogeneity in matrix properties not treated. 
Local heterogeneity in mineralogy not treated; however, 
the bulk composition of host rocks is fairly uniform. 
Heterogeneity in initial water geochemistry not treated 
directly; treated indirectly through testing with alternate 
water compositions. 
Possible local changes in predicted water compositions 
around the drift. However, the bulk composition of waters 
around the drift is not expected to be significantly affected, 
because the rock chemical composition and mineralogy in 
the repository units is fairly homogeneous. Comparison of 
REV01 results showed that heterogeneous fracture 
permeability had little effect (Section 6.6). 
Transport parameters 
(effective diffusivity) 
The CO2 diffusion coefficient was changed by a factor of 6 
between REV01 and REV02 analyses (and a factor of 30 
since earlier simulations). 
Sensitivity to diffusion coefficient for aqueous species was 
not investigated. However, tortuosity was changed from 
0.2 to 0.7 between earlier report revisions (REV00 and 
REV01) without noticeable effect. 
CO2 diffusion coefficient mainly affects in-drift predicted 
CO2 concentrations during dryout. At other times, 
predicted CO2 concentrations are mainly dictated by water 
compositions. 

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6.6.2 Evaluation of Model Result Uncertainty 
Model sensitivities to key input parameters are evaluated through use of additional simulations 
with modified parameter sets/model conditions, and use of developmental model runs with 
differing input parameters (Section 6.5). Furthermore, confidence in model results is obtained by 
comparing model results against data from the DST and laboratory experiments (Section 7), and 
improving the model conceptualization and mathematical formulation (e.g., incorporating vapor 
pressure lowering due to capillary effects, making the drift wall open to advective and diffusive 
flow; adding minerals and aqueous species to the geochemical system; Sections 6.2 to 6.4), as 
necessary, to yield a reasonably good agreement between calculated and measured data (i.e., per 
LP-SIII.10Q-BSC, 5.3.2(c)(1)). 

In this study, the spread in predicted concentrations of aqueous species and CO2 gas 
(Figures 6.5-11 to 6.5-20 and 6.5-24 to 6.5-37) is related to: 

 The natural variability of input water compositions (Sections 6.2.2.1) 
 The various investigated model conceptualizations (vapor-pressure model, drift location, 
stratigraphic columns, open versus closed drift wall) (Table 6-1) 
 Ranges of input parameters other than water composition (in this case, infiltration rates 
and CO2 diffusion coefficients) (Section 6.5.4). 
The relative spread caused by the variability of input water compositions (computed as standard 
deviation) is shown as a function of time in Table 6.6-2. This spread is up to one order of 
magnitude and in many cases much less. The spread overlaps with, and in most cases is larger 
than, the spread introduced by use of the different model conceptualizations and ranges of other 
input data considered (compare Figures 6.5-24a through 6.5-37a to Figures 6.5-24b through 
6.5-37b). This is quantitatively demonstrated in Post-Processing Analysis for THC Seepage 
(BSC 2004 [DIRS 169858]). 

One model validation criterion for use with the DST THC submodel is that gas and aqueous 
species concentrations are predicted to within an order of magnitude, resulting in an acceptable 
range for DST comparisons, of two orders of magnitude. The scatter in model results for the five 
starting waters, is always much less than this (Table 6.2.2). Nevertheless, the scatter in the 
starting waters is a more relevant estimate of uncertainty, for several reasons. The model 
validation criterion used with the DST THC submodel accounts for error in the measured values 
(due to sampling issues; Section 7.1.7.1), as well as uncertainty in the modeled values, and 
recognizes that the relatively small scale of the DST makes it sensitive to local heterogeneities in 
the host rock. 

Also, the uncertainties in many of the parameters passed downstream from the THC seepage 
model are constrained to a relatively narrow range of values by the coupled processes that are 
validated by the DST THC submodel. For instance, nitrate and chloride behave conservatively 
in the model, so their concentration in solution is mostly a function of the degree of evaporation 
and condensation. These are controlled by heat and vapor transfer, processes that are well 
predicted by the DST THC submodel (Section 7.1.9). The conservative behavior means that the 

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spread in the nitrate/chloride ratio closely matches that of the initial solutions (BSC 2004 
[DIRS 169858], Figure 6.2-9). Changes in this ratio in any given run occur only during 
rewetting, when previously precipitated salts redissolve (Figure 6.3-4), and may be a function of 
the model implementation of salt dissolution/reprecipitation (Section 6.4.5). 

Most of the other parameters of importance to downstream models are also constrained to 
relatively narrow ranges due to the processes validated by the DST THC submodel. Interactions 
with calcite and aluminosilicates serve to buffer the pH to a narrow range of values. CO2 
diffuses readily and is not strongly affected by local heterogeneities. Its concentration is mostly 
a function of the temperature, displacement by water vapor due to boiling, and dissolution of 
calcite in zones of condensate formation and drainage. All of these processes buffer the response 
of the chemical system to thermal perturbation, tending to reduce the spread in predicted water 
chemistries, especially over longer time intervals (BSC 2004 [DIRS 169858], Figures 6.2-4 to 
6.2-20). The concentrations of reactive aqueous species are buffered to a narrow range of values, 
while conservative species concentrations are a function of the starting water composition and 
the degree of evaporation/condensation. Concentration ratios for conservative species are largely 
those of the starting waters. Thus, the uncertainty in the THC seepage model is adequately 
captured by the variability in the initial pore water compositions input into the model. 

Uncertainties in kinetic and thermodynamic data could affect the standard deviations shown in 
Table 6.6-2, although the results of model validation against the DST and other laboratory 
experiments (Section 7), as well as the results of simulations of ambient conditions (Section 
6.5.5.4), suggest these data are constrained to the extent that the model results are generally 
consistent with measured data. The model validation results (Section 7) also provide confidence 
that some of the other uncertainties listed in Table 6.6-1 do not significantly affect the spread in 
model results. This could be because model validation results are either not very sensitive to 
these uncertainties (at least over the period of time covered by the validation simulations) or that 
the effects of some of these uncertainties cancel out. 

Table 6.6-2. Standard Deviations in Water and Gas Compositions Predicted Using Five Different Input 
Water Compositions (W0, W4, W5, W6, and W7) 

Time (yr) pH Ca Mg Na Cl SiO2(aq) HCO3 SO4 
0 0.11 0.11 0.52 0.18 0.29 0.08 0.14 0.37 
1 0.10 0.17 0.90 0.13 0.29 0.05 0.16 0.37 
53 0.14 0.15 0.82 0.25 0.37 0.20 0.22 0.44 
100 0.13 0.04 0.23 0.11 0.31 0.06 0.16 0.39 
200 0.09 0.23 0.38 0.16 0.40 0.14 0.23 0.46 
300 0.10 0.40 0.35 0.26 0.46 0.19 0.30 0.51 
400 0.11 0.35 0.38 0.24 0.40 0.16 0.22 0.44 
500 0.15 0.41 0.49 0.29 0.44 0.17 0.13 0.51 
600 0.17 0.42 0.47 0.26 0.40 0.16 0.13 0.45 
700 0.10 0.24 0.34 0.15 0.31 0.06 0.10 0.38 
801 0.10 0.20 0.28 0.12 0.30 0.04 0.07 0.37 
1,000 0.09 0.16 0.23 0.10 0.29 0.02 0.06 0.37 
1,200 0.09 0.15 0.22 0.09 0.29 0.02 0.08 0.37 
2,000 0.08 0.18 0.19 0.08 0.32 0.01 0.07 0.38 
2,200 0.06 0.18 0.17 0.06 0.29 0.02 0.08 0.37 
2,400 0.06 0.18 0.17 0.06 0.29 0.02 0.07 0.37 

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Table 6.6-2. Standard Deviations in Water and Gas Compositions Predicted Using Five Different 
Input Water Compositions (W0, W4, W5, W6, and W7) (Continued) 

Time (yr) K F NO3 CO2(gas) Ca/HCO3 NO3/Cl Na/Cl Ca/Cl 
5,000 0.05 0.14 0.14 0.06 0.29 0.01 0.07 0.37 
10,000 0.03 0.14 0.10 0.06 0.29 0.01 0.08 0.37 
20,000 0.04 0.14 0.11 0.06 0.29 0.01 0.09 0.37 
100,000 0.03 0.13 0.08 0.05 0.29 0.02 0.10 0.37 
Time (yr) K F NO3 CO2(gas) Ca/HCO3 NO3/Cl Na/Cl Ca/Cl 
0 0.06 0.30 0.27 0.23 0.19 0.38 0.36 0.24 
1 0.12 0.06 0.27 0.21 0.30 0.38 0.34 0.17 
53 0.24 0.25 0.35 0.32 0.33 0.38 0.27 0.31 
100 0.11 0.08 0.30 0.29 0.19 0.38 0.29 0.27 
200 0.16 0.12 0.33 0.32 0.45 0.38 0.32 0.21 
300 0.27 0.18 0.42 0.34 0.68 0.37 0.28 0.19 
400 0.24 0.13 0.40 0.25 0.53 0.37 0.19 0.12 
500 0.29 0.12 0.39 0.13 0.51 0.37 0.17 0.11 
600 0.27 0.13 0.41 0.08 0.54 0.38 0.16 0.17 
700 0.16 0.08 0.29 0.07 0.33 0.38 0.17 0.16 
801 0.12 0.07 0.28 0.07 0.27 0.38 0.18 0.14 
1,000 0.10 0.05 0.27 0.03 0.22 0.38 0.20 0.15 
1,200 0.09 0.04 0.27 0.01 0.23 0.38 0.21 0.15 
2,000 0.08 0.07 0.28 0.01 0.25 0.38 0.23 0.15 
2,200 0.07 0.07 0.27 0.03 0.26 0.38 0.23 0.12 
2,400 0.07 0.07 0.27 0.02 0.25 0.38 0.23 0.12 
5,000 0.07 0.06 0.27 0.04 0.21 0.38 0.23 0.15 
10,000 0.06 0.05 0.27 0.08 0.17 0.38 0.25 0.20 
20,000 0.06 0.06 0.27 0.12 0.15 0.38 0.26 0.22 
100,000 0.05 0.05 0.27 0.11 0.15 0.38 0.26 0.24 

Output DTN: LB0307DSTTHCR2.002. 

NOTE: Standard deviations are computed using data depicted in Figures 6.5-25 (top) through 6.5-37 (top) 
(zones of highest liquid saturation above the drift) and represent: 

 For pH, standard deviation of pH values in (+) pH units. 
 For other data, standard deviation of logarithmic values: i.e., (+) change in log10 values of 
concentrations and concentration ratios around the mean of log10 values (thus, a value of 0.5 
corresponds to a total spread of one order of magnitude). 
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INTENTIONALLY LEFT BLANK 


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7. VALIDATION 
This section describes models and data used to validate the THC seepage model and input for the 
THC seepage model. Validation of the model is accomplished through comparison of simulation 
results to data collected from the Drift Scale Test (DST) and to laboratory experiments that 
explore various specific aspects of the model. The DST THC submodel is derived from the THC 
seepage model, relying on the same conceptual model, modeling the same coupled processes in 
the same manner, and using many of the same input data (i.e., intrinsic physical, hydrologic, 
thermodynamic, and kinetic parameters). Because the DST THC submodel is a special case of 
the THC seepage model, evaluation of the DST THC submodel serves to validate the THC 
seepage model. 

The DST THC submodel and comparison of model simulation results to measured data are 
presented in Section 7.1. The validation of the THC models by comparison of DST THC 
submodel results with chemical data for water and gas samples is subject to a variety of 
uncertainties. These uncertainties are discussed in detail throughout Section 7, but can be 
summarized as follows. First, TH processes can lead to spatial differences in the chemistry of 
water and gases by a few orders of magnitude (Section 7.1.10.2) over very small increments in 
temperature as a result of boiling and mineralwater reactions. In contrast, temperature exhibits 
much less spatial variation because it is controlled mainly by conduction in the rock matrix. 
Second, strong differences in aqueous species concentrations that develop in fractures and the 
adjacent matrix can be maintained owing to the slow rates of diffusion of aqueous species 
between them (Section 7.1.11.3). Third, changes that the samples undergo during their 
extraction from the rock (e.g., cooling, degassing, condensation) have the potential for shifting 
the aqueous species compositions. Some measured quantities, such as pH, are sensitive to 
liquid-gas interactions such that shifts in water composition can be orders of magnitude. Sources 
of data used for model validation are shown in Table 7-1. The approach to model validation 
acknowledges these uncertainties in the evaluation of model-data comparisons, in establishing 
and applying the validation criteria, and in the description of uncertainty that is provided for 
downstream use of THC seepage model results. 

Methods and criteria for validating the THC seepage model through the DST THC submodel are 
described in Section 7.1.7; the validation results are described in the rest of Section 7.1. For 
Level II validation, Section 2.2.2.2 of Technical Work Plan for: Near-Field Environment and 
Transport: Coupled Processes (Mountain-Scale TH/THC/THM, Drift-Scale THC Seepage, and 
Post-Processing Analysis for THC Seepage) Report Integration (BSC 2005 [DIRS 172761]) 
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 LP-SIII.10Q-BSC. The development of the THC seepage model has been conducted 
according to these criteria in order to establish the scientific basis for the model, as follows: 

1. Selection of input parameters and/or input data, and a discussion of how the selection 
process builds confidence in the model [LP-SIII.10Q-BSC, 5.3.2(b) (1) and 
LP-2.29Q-BSC, Attachment 3 Level I (a)]. 
The inputs to the THC seepage model have been obtained from controlled sources (see 
Table 4.1-1, Section 4.1), or, if older data, have been evaluated and justified for 

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Drift-Scale THC Seepage Model 

intended use (Section 4.1) in this report. Selection and development of input and 
design parameters is described in detail in Sections 4.1, 6.2, 6.4.8, 6.5, and Appendix C. 
Model assumptions have been described in Section 5. Detailed discussion about model 
concepts can be found in Section 6.2. 

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 
[(LP-SIII.10Q-BSC, 5.3.2(b)(2) and LP-2.29Q-BSC, Attachment 3 Level I (e)]. 
Detailed discussion of initial and boundary conditions for the THC seepage model can 
be found in Section 4.1 (initial model inputs); Section 6.2.2.1 (pore water 
compositions); Section 6.4.3 (mineral reactive surface areas); and Section 6.5.2 and 
Section 6.5.3 (boundary conditions and initial inputs). Calibration of the model to 
ambient pore water compositions is described in Sections 6.4.8 and 6.5.5.4. Section 6.5 
provides detailed discussion of various model results (i.e., those of convergence runs). 
Discussion about issues with non-convergence runs can be found in Section 6.4.8. 
Additional information regarding convergence issues can be found in the file 
chdump.dat described in Appendix G. 

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 
[( LP-SIII.10Q-BSC, 5.3.2(b)(3) and LP-2.29Q-BSC, Attachment 3 Level 1 (d) and (f)]. 
Discussion of model uncertainties and sensitivity analyses are provided in Section 6.6. 
A summary discussion on uncertainties and their impact is given in Section 8.4. 

4. Formulation of defensible assumptions and simplifications [LP-2.29Q-BSC, 
Attachment 3 Level I (b)]. 
Comprehensive discussions of assumptions and simplifications are provided in Section 
5 and Section 6.4.6, respectively. 

5. Consistency with physical principles, such as conservation of mass, energy, and 
momentum [LP-2.29Q-BSC, Attachment 3 Level I (c)]. 
Consistency with physical principles is demonstrated by the conceptual and 
mathematical formulation in Sections 6.2 and 6.4, and the selection and use of the 
TOUGHREACT V.3.0 code (LBNL 2002 [DIRS 161256]) in Section 3. 

For confidence building after model development, Section 2.2.2.2, Confidence Building After 
Model Development of the technical work plan (BSC 2005 [DIRS 172761]) imposes the 
following requirements for model validation to support the scientific basis: 

1. LP-SIII.10Q-BSC, Section 5.3.2(c)(1), Method 1: Corroboration of results from a 
derivative simulation, closely similar to the THC Seepage Model but adapted to the DST, 
with data acquired from the DST. 
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Drift-Scale THC Seepage Model 

Comparison of model results with experimental data is the main method of validation for 
the THC seepage model. Section 7.1 explains the respective validation and modeling 
activities in great detail, and discusses explicitly how the criteria for this validation 
method, as defined in Section 2.2.2.2 of the TWP (BSC 2005 [DIRS 172761]), have been 
met. 

2. LP-SIII.10Q-BSC, Section 5.3.2(d), Technical review through publication in a refereed 
professional journal. 
Additional confidence is obtained through technical review by publication in a refereed 
professional journal (BSC 2005 [DIRS 172761]). Since the following articles on the 
subject have already been published, additional confidence has been obtained: 

 Fluid Flow and Reactive Transport Around Potential Nuclear Waste Emplacement 
Tunnels at Yucca Mountain, Nevada. Journal of Contaminant Hydrology (Spycher et 
al. 2003 [DIRS 162121]). 
 Experimental and Numerical Simulation of Dissolution and Precipitation: 
Implications for Fracture Sealing at Yucca Mountain, Nevada. Journal of 
Contaminant Hydrology (Dobson et al. 2003 [DIRS 165949]). 
In addition to use of the DST THC submodel, confidence in the THC seepage model is provided 
by model-data comparisons from laboratory-scale experiments. Two such experiments have 
been modeled: a plug-flow reactor to evaluate tuff dissolution (Section 7.2) and a fracture sealing 
experiment (Section 7.3). Comparisons between the experimentally measured and simulated 
results using TOUGHREACT are used to test conceptual models that were developed for the 
THC seepage model and the DST THC submodels. These simulations were performed using 
previous revisions of TOUGHREACT software and using previous versions of the 
thermodynamic database. Thus, they do not directly validate the current THC model, but 
provide added confidence in the conceptual model and modeling approach that are implemented 
by TOUGHREACT, the basis of the THC seepage model. A brief summary of each of these 
model-data comparison studies is provided here. The simulations are discussed in detail in a 
previous revision of this report (BSC 2004 [DIRS 168848], Sections 7.2 and 7.3). 

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Drift-Scale THC Seepage Model 

Table 7-1. Sources of Data Used for Model Validation or Corroboration 

DTNs Description 
Mineralogical Data (DST) 
LA0201SL831225.001 [DIRS 158426] Sidewall core sample mineralogical analyses 
Analytical Water and Gas Chemistry Data 
LB0102CO2DST98.001 [DIRS 159306] CO2 gas analyses (1st, 2nd, 3rd, and 7th Qtr.) 
LB990630123142.003 [DIRS 111476] 4th, 5th, and 6th Qtr. DST CO2 data 
LB000121123142.003 [DIRS 146451] DST CO2 data (8/99 to 11/99) 
LB0011CO2DST08.001 [DIRS 153460] DST CO2 data (11/99 to 8/2000) 
CRWMS M&O 2001 [DIRS 153814] DST CO2 data (7/98) 
LB0208ISODSTHP.001 [DIRS 161638] DST CO2 and isotopic data (combined) 
MO0005PORWATER.000 [DIRS 150930] Analyses of pore waters from Alcove 5 core samples in the ESF (HDPERM-
2 and HD-PERM-3 samples) 
LL990702804244.100 [DIRS 144922] Aqueous chemistry of water sampled from the DST (6/4/98 to 3/30/99) 
LL001100931031.008 [DIRS 153288] Aqueous chemistry of water sampled from the DST (collected 10/27/99 
to 1/25/00) 
MO0207AL5WATER.001 [DIRS 159300] DST Field measurements 
SN0203F3903102.001 [DIRS 159133] DST Field measurements 
LL020405123142.019 [DIRS 159307] DST Aqueous chemistry 
LL020302223142.015 [DIRS 159134] DST Aqueous chemistry 
LL001200231031.009 [DIRS 153616] Aqueous chemistry of water sampled from the DST (8/9/99 and 
8/10/99) 
MO0101SEPFDDST.000 [DIRS 153711] Field pH of water sampled from DST on 5/23/00 and 6/29/00 

7.1 THE DRIFT SCALE TEST THC SUBMODEL 
The DST is the second underground thermal test to be carried out in the Exploratory Studies 
Facility (ESF) at Yucca Mountain, Nevada. The purpose of the test is to evaluate the coupled 
thermal, hydrologic, chemical, and mechanical processes that take place in unsaturated fractured 
tuff over a range of temperatures (approximately 25C to 200C). Details regarding the DST 
layout, borehole orientations, operation of the test, and measurements performed (as well as their 
uncertainties) are discussed in Section 6.3 of Thermal Testing Measurements Report (BSC 2004 
[DIRS 169900]) and in Drift-Scale Test As-Built Report (CRWMS M&O 1998 [DIRS 111115]). 
Information on these aspects of the DST is not repeated in this report unless directly related to 
the geochemical data collected and used for model validation. 

In brief, the DST consists of an approximately 50-m-long drift that is 5 m in diameter. Nine 
electrical floor canister heaters were placed in this drift (the Heated Drift) to simulate nuclear-
waste-bearing containers. Electrical heaters were also placed in a series of horizontal boreholes 
(wing heaters) drilled perpendicular outward from the central axis of the Heated Drift. These 
heaters were emplaced to simulate the effect of adjacent emplacement drifts. The DST heaters 
were activated on December 3, 1997, with a planned period of four years of heating, followed by 
four years of cooling. After just over four years, the heaters were switched off on January 14, 
2002, and since that time the test area has been slowly cooling. 

This section describes the DST THC submodel, discusses simulations of THC processes during 
the DST, and presents comparisons to geochemical measurements performed on gas, water, and 
mineral samples collected from the DST. The DST THC submodel is a forward numerical 
model used to gain insight into THC processes taking place during heating of the unsaturated 

MDL-NBS-HS-000001 REV 04 7-4 February 2005 


Drift-Scale THC Seepage Model 

devitrified tuffs. The DST THC submodel provides important support for application of the 
drift-scale THC seepage model to repository simulations. The drift-scale THC conceptual 
models are described in Sections 6.1 to 6.4. The DST THC submodel is compared with, but not 
calibrated to, geochemical data collected from the DST. This is important because calibration, if 
relied upon heavily in model development, could limit the use of the model for representing THC 
processes over repository time scales. The drift-scale hydrologic and thermal properties used in 
the DST THC submodel are based on systematic evaluation of hydrologic data from the overall 
unsaturated zone at Yucca Mountain (BSC 2004 [DIRS 169857]); the property values are not 
calibrated directly to DST results, but are best estimates for application to the site scale. 
Accordingly, more differences are observed in model-data comparisons, but use of the DST THC 
submodel in model validation better represents the other host rock units. Some modifications 
have been made to the thermodynamic database for the THC seepage model and the DST THC 
submodel, to capture aspects of the ambient-system pore-water chemistry (discussed in Section 
4.1.4). The only other adjustments specific to the DST have been made to the connectivity of the 
Heated Drift to the Access Drift, to better represent heat losses through the intervening bulkhead. 

Processes and data collected primarily during the heating phase of the DST are discussed in this 
report. The simulation results are compared to data from the full four-year heating phase (for 
data that are available) as a part of the model validation. 

7.1.1 Modeling Approach 
The modeling approach involves the creation of a numerical grid and the selection or 
development of thermal, hydrologic, mineralogical, aqueous, and gaseous species geochemical 
input data. It also involves the selection of appropriate thermal and hydrologic models, as well 
as chemical, thermodynamic, and kinetic data and models. The approach and input data are 
described as follows in Sections 7.1.2 to 7.1.5. 

7.1.2 Drift Scale Test Two-Dimensional Numerical Grid 
The two-dimensional dual-permeability numerical grid for the DST represents a vertical cross 
section through the Heated Drift at a distance approximately 30 m from the bulkhead, separating 
the Heated Drift from the Access Drift (Figure 7.1-1). 

The mesh used in the current simulations (Figures 7.1-2 and 7.1-3) has been modified slightly 
from that used in earlier revisions of the DST THC submodel. The earlier mesh consisted 
of 4,485 grid blocks, including fracture and matrix (DTN: LB0101DSTTHGRD.001 
[DIRS 153687]). The top boundary is approximately 99 m above the drift center, with the 
bottom boundary at approximately 157 m below the center. Connections between the interior of 
the Heated Drift and the Heater Test Alcove included grid blocks designed to act as a bulkhead 
and as insulating material. Within the drift, heat is applied directly to the drift wall instead of 
explicitly representing the electric heaters and calculating the heat transfer across the air mass 
inside the drift. The DST includes a plane of linear wing heaters on each side of the drift that 
have been given small grid blocks in the model. Small grid blocks are also employed adjacent to 
the wing heaters and drift wall to capture the strong gradients in temperature and liquid 
saturation in these regions. Radial mesh blocks in the drift interior are replaced near the drift 
base by Cartesian grid blocks to represent the concrete invert. Incorporation of the concrete 
invert is unique to the DST THC submodel; it is not part of the model grid for the THC seepage 

MDL-NBS-HS-000001 REV 04 7-5 February 2005 


Drift-Scale THC Seepage Model 

model. Also, in the DST THC submodel, the concrete is only incorporated with respect to 
thermal and hydrologic propertiesno cement phases are present in the geochemical system 
used. 

For the current simulations (Figures 7.1-2 and 7.1-3), grid blocks representing the insulation and 
bulkhead have been removed, and the Heated Drift grid block is connected directly to the Heater 
Test Alcove grid block. The connection area and distance have been adjusted so that heat loss 
from the drift resulted in roughly similar crown temperatures to the maximum observed values. 
This is done to simulate heat and mass losses through the bulkhead, instead of reducing power by 
a set factor, as was done in earlier revisions of this model. In the approximate location of the 
observation drift, the grid block volumes are increased to a large value to represent connection to 
the atmosphere (Figure 7.1-2). Grid blocks that were removed previously (to represent a no-flux 
boundary for the observation drift) have been added and connected to adjacent grid blocks. The 
distances from the drift center grid block and the connecting elements have been modified to 
represent the true distance, so that heat could be applied to the drift center and not to the 
elements at the drift walls. 

7.1.3 Heater Power 
The DST THC submodel employs a nine-month initial period at ambient temperature, 
corresponding approximately to the time that was required to set up the test. The wing heaters 
are split into inner and outer zones, with more power applied to the outer zone to approximate 
the presence of an adjacent parallel drift. In the drift, heat is applied solely to the drift-center 
grid block, which is connected to all surrounding grid blocks. The positions of grid blocks 
representing heaters are shown in Figure 7.1-3. 

The heating schedule is based on step-wise averages of the 10-day incremented power data 
(DTN: MO0208RESTRDST.002 [DIRS 161129]). The sources for this 10-day incremented 
power data are given in Table 7.1-1. Intentional power reductions are directly accounted for in 
the power data, using accurate time information gathered from the DTNs listed in Table 7.1-1. 

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Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Mesh extends in all directions from area shown. 

Figure 7.1-1. Three-Dimensional Schematic Diagram of the DST Showing Perspective View of Numerical 
Mesh for DST THC Submodel Simulations 


Output DTN: LB0307DSTTHCR2.001. 
NOTE: The Observation Drift is shown as black squares. Mesh extends outside the area shown (see text). The 
Heated Drift is a circular region at the center. 
Figure 7.1-2. Numerical Mesh for DST THC Submodel Simulations 

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Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Inner (violet diamonds closer to drift) and outer wing heater (large red squares) grid block coordinates. 
Heat is applied to grid block marked at drift center. Small red squares in the drift represent locations 
where heat was applied in the REV01 model. Green squares indicate grid block locations for the concrete 
invert. 

Figure 7.1-3. Enlarged View of the Numerical Grid Showing the Locations of Grid Blocks Representing 
the Heated Drift, Wing Heaters, and Concrete Invert 

Table 7.1-1. Input DTNs Used for Estimating Times/Dates of Power Reductions and Outages for DST 
THC Submodel Simulations 

Power Data Sources (DTNs) Dates 
MO0208RESTRDST.002 [DIRS 161129] Heating Phase (10-day increments) 
MO9807DSTSET01.000 [DIRS 113644] 11/7/97 to 5/3/98 
MO9810DSTSET02.000 [DIRS 113662] 6/1/98 to 8/31/98 
MO9906DSTSET03.000 [DIRS 113673] 9/1/98 to 5/31/99 
MO0001SEPDSTPC.000 [DIRS 153836] 6/1/99 to 10/31/99 
MO0007SEPDSTPC.001 [DIRS 153707] 11/1/99 to 5/31/00 
MO0012SEPDSTPC.002 [DIRS 153708] 6/1/00 to 11/30/00 
MO0107SEPDSTPC.003 [DIRS 158321] 12/1/00 to 5/31/01 
MO0202SEPDSTTV.001 [DIRS 158320] 6/1/01 to 1/14/02 

The DTNs in Table 7.1-1 are also used to estimate the length of the longer (approximately 
greater than 1/2 day) temporary power outages. Table 7.1-2 gives the step-wise averaged power 
data implemented in the DST THC submodel simulations. Each time in Table 7.1-2 represents 
the initiation of a specific period of heating or power loss that continues until the succeeding 
time. The simulations are run for the full period of heating plus a four-year period of cooling 
(shown by hypothetical end time at the base of Table 7.1-2). 

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Table 7.1-2. Step-Wise Averaged Power Data for the DST THC Simulations 

Date Time (s) 
Time 
(days) 
Canister 
Power (watts) 
WH (inner) 
Power (watts) 
WH (outer) 
Power (watts) Comments 
3/5/97 0.00000E+00 0.00 0.0000 0.0000 0.0000 pre-test 
12/3/97 2.35872E+07 273.00 1091.3740 1232.4007 1626.7690 heaters turned on 
3/15/98 3.24000E+07 375.00 1091.3740 0.0000 0.0000 outage  right rib 
3/16/98 3.25080E+07 376.25 1091.3740 1232.4007 1626.7690 
4/12/98 3.48192E+07 403.00 1077.9972 1198.5773 1582.1220 
8/10/98 4.51872E+07 523.00 1119.6842 1201.8035 1586.3807 
1/27/99 5.98752E+07 693.00 0.0000 0.0000 0.0000 power outage 
1/27/99 5.99400E+07 693.75 1123.5789 1204.4465 1589.8693 
2/16/99 6.16032E+07 713.00 1102.5965 1189.0805 1569.5862 
5/27/99 7.02432E+07 813.00 0.0000 0.0000 0.0000 power outage 
5/27/99 7.03080E+07 813.75 1102.5965 1189.0805 1569.5862 
5/29/99 7.04160E+07 815.00 0.0000 0.0000 0.0000 power outage 
5/30/99 7.04808E+07 815.75 1087.8653 1155.5245 1525.2923 
6/18/99 7.21440E+07 835.00 0.0000 0.0000 0.0000 power outage 
6/19/99 7.22088E+07 835.75 1087.8653 1155.5245 1525.2923 
7/9/99 7.39584E+07 856.00 0.0000 0.0000 0.0000 power outage 
7/15/99 7.44768E+07 862.00 1087.8653 1155.5245 1525.2923 
8/27/99 7.81920E+07 905.00 0.0000 0.0000 0.0000 power outage 
8/29/99 7.83216E+07 906.50 1087.8653 1155.5245 1525.2923 
11/22/99 8.57088E+07 992.00 1087.8653 0.0000 0.0000 outage  right rib 
11/24/99 8.58816E+07 994.00 1087.8653 1155.5245 1525.2923 
2/11/00 9.27072E+07 1073.00 0.0000 0.0000 0.0000 power outage 
2/11/00 9.27720E+07 1073.75 1078.8421 1184.6642 1563.7568 
3/2/00 9.44352E+07 1093.00 1029.1930 1115.3660 1472.2831 power reduction 
3/12/00 9.52992E+07 1103.00 0.0000 0.0000 0.0000 power loss 
3/13/00 9.54072E+07 1104.25 1029.1930 1115.3660 1472.2831 
5/2/00 9.97056E+07 1154.00 964.5263 1040.2813 1373.1713 power reduction 
8/15/00 1.08778E+08 1259.00 917.3463 978.7397 1291.9364 power reduction 
1/20/01 1.22429E+08 1417.00 0.0000 0.0000 0.0000 power outage 
1/21/01 1.22515E+08 1418.00 917.3463 978.7397 1291.9364 
5/1/01 1.31155E+08 1518.00 875.5711 925.4672 1221.6168 power reduction 
7/1/01 1.36426E+08 1579.00 0.0000 0.0000 0.0000 power outage 
7/1/01 1.36490E+08 1579.75 875.5711 925.4672 1221.6168 
8/22/01 1.40918E+08 1631.00 826.8171 875.8317 1156.0979 power reduction 
1/14/02 1.53446E+08 1776.00 0.0000 0.0000 0.0000 heaters turned off 
1/14/06 2.79677E+08 3237.00 0.0000 0.0000 0.0000 cooling period end 

NOTE: Input DTNs for power data are listed in Table 7.1-1. Each time represents the initiation of a particular period 
of heating (or power loss) that continues until the next time in the table. Data are for a two-dimensional 
vertical slice. 

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7.1.4 Hydrologic and Geochemical Input Data 
Sources of hydrologic and geochemical input data are listed in Table 4.1-1. Other details 
regarding the use or modifications to these data are given in Sections 7.1.5 and 7.1.6. 

Thermodynamic data are described in Section 4.1.4 and presented in Appendix C. Kinetic data 
are given in Table 4.1-3. The mineral volume fractions reflect the mineralogical assemblage 
used in the current Tptpll THC seepage model (Appendix A). Mineral reactive surface areas are 
given in Appendix B. 

7.1.5 Initial and Boundary Conditions: Hydrologic and Thermal 
Hydrologic and thermal initial and boundary conditions are derived from the UZ flow model 
(BSC 2004 [DIRS 169861], Table 6.1-2). Hydrologic and thermal properties are from the output 
of separate studies (BSC 2004 [DIRS 169854]; BSC 2004 [DIRS 169857]; BSC 2004 
[DIRS 170033]) that are consistent with the UZ flow model. Models and data for the ambient 
geochemistry of the UZ at Yucca Mountain (i.e., Cl, Sr, calcite) support the infiltration rates used 
as boundary conditions for the UZ flow and transport model (Sonnenthal and Bodvarsson 1999 
[DIRS 117127], p. 107; Liu et al. 2003 [DIRS 162470]; and Xu et al. 2003 [DIRS 162124]). The 
nature and extent of this foundation work is substantially the same for the DST THC submodel 
and the THC seepage model used for repository prediction, and supports confidence that the 
THC seepage model uses representative values for hydrologic and thermal properties, initial 
conditions, and boundary conditions. Further details of the initial and boundary conditions are 
described below. 

Steady-state liquid saturations, temperatures, and pressures are obtained for these simulations 
using the updated drift-scale thermal-hydrologic property set (DTN: LB0208UZDSCPMI.002 
[DIRS 161243]). These hydrologic properties are listed in Table 6.4-1. Modifications have been 
made to the fracture medium void fraction (usually set to 0.99 or 1.0) to be consistent with the 
fracture porosities (DTN: LB0210THRMLPRP.001 [DIRS 160799]). This modification has 
approximately the same effect as changing the relative volumes of the fracture and matrix grid 
blocks (the usual procedure for implementing fracture porosity). 

The top and bottom boundaries are set to constant temperature, pressure, and liquid saturation, 
based on steady-state values obtained from simulations of a one-dimensional column extending 
from the land surface to the water table. The top boundary of the two-dimensional model 
extends 150 m above and below the drift center, but does not reach either the land surface or the 
water table. Under these conditions, the percolation flux at the top boundary is approximately 

0.5 mm/yr. This value is consistent with predicted net infiltration rates for the region of the 
DST, which generally range from 0 to 1 mm/yr (DTN: GS000308311221.005 [DIRS 147613]; 
BSC 2004 [DIRS 170007], Figure 6-26). The bottom boundary condition is open to gas and to 
liquid flow. The side boundaries of the domain are located 81.5 m away from the drift center on 
each side (outside of the test influence area) and are no-flux for mass and heat. The air pressure 
and temperature in the observation drift are set to constant values and, therefore, do not reflect 
temporal fluctuations in barometric pressure or tunnel air temperatures. The heated drift wall is 
open to advection and conduction of heat and mass (e.g., air, water vapor, and CO2). 
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Drift-Scale THC Seepage Model 

7.1.6 Initial and Boundary Conditions: Geochemical 
Initial and boundary geochemical conditions are set using qualified data, based on pore water 
and mineralogical analyses and taken from the TDMS. Pore water data have been selected, over 
successive revisions of the model, from a relatively large set of measured data (Section 6.2.2.1), 
which provides confidence that the selected compositions represent the range of host rock 
conditions. Additional discussion of the available pore water data is provided in Section 4.1.5. 
The approach used to set the initial and boundary conditions is described in the following 
paragraphs. 

Initial geochemical data used in the simulations are given in Appendices A through C (sources in 
Tables 4.1-1). All aqueous and gaseous species concentrations in the rock are initially set to a 
uniform value (Section 6.2.2.1). The Heater Alcove and Observation Drift CO2 concentrations 
are fixed to approximately that of the atmosphere. The Heated Drift CO2 concentration is 
initially set to the same value as that in the Observation Drift, but is allowed to exchange CO2 
with the Heater Test Alcove and with the surrounding rock. The simulations are performed with 
the geochemical system presented in Table 6.2-2. 

Both the top and bottom boundary conditions are open to gas and aqueous species transport. The 
top and bottom boundaries are also set so that no mineral reactions take place (and, therefore, no 
changes in aqueous species concentrations occur as a result of mineralwater reactions). Their 
volumes are set to extremely large values so they act, essentially, as constant concentration 
boundaries. The side boundaries are no-flux for gas and aqueous-species transport. 

7.1.7 Model Validation Methods, Criteria, and Limitations 
In the following sections, data and predictions are reviewed to demonstrate that the criteria 
specified in the TWP (BCS 2005 [DIRS 172761]) have been met for the DST THC submodel. 
Because the THC seepage model uses the same conceptualization and mathematical treatment of 
THC coupled processes as the DST THC submodel, including the same thermodynamic and 
kinetic data, DST model validation effectively validates the THC seepage model. Additional 
validation of the THC modeling approach is presented in Sections 7.2 and 7.3 where results of 
laboratory plug-flow and fracture boiling experiments are compared to simulations. 

The THC seepage model is validated and the necessary confidence is achieved by Method 1 
listed in LP-SIII.10Q-BSC, Section 5.3.2(c)(1), Corroboration with Experimental Data. 
Additional confidence in the model is provided by Technical Review through Publication in a 
Refereed Technical Journal, as per LP-SIII.10Q-BSC, 5.3.2(d). These validation methods 
provide the most confidence in the conceptual and numerical models and their outputs. 

7.1.7.1 Validation Method 1Corroboration with Experimental Data 
Data from the DST used for comparison consist of analyses of water and gas samples from 
borehole intervals between packers and observations of mineral precipitation in boreholes. 
Intervals have been selected for comparison based upon the availability of a long, continuous 
sample record and the absence of confounding factors, such as the sampling interval being too 
long to compare with a particular grid block or pair of grid blocks, or boreholes being near either 

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Drift-Scale THC Seepage Model 

end of the DST and affected by three-dimensional transport (see below). The locations of the 
hydrology boreholes, sampling intervals, and temperature sensors are shown in Figure 7.1-4. 

Differences between the DST THC submodel predictions and DST measurements are important. 
There are several reasons (listed below) why individual measured data may lie outside the 
predictions, and yet support use of the DST THC submodel for validation. It is important that 
these considerations are kept in mind when reviewing the model comparisons to measured data 
(in the following discussion, the term model refers to the DST THC submodel). 

1. The continuum model does not simulate individual fractures, which may intersect 
boreholes near sampling points, their aperture and frequency resulting in different flow 
rates and temperatures; thus, affecting the chemistry of the gas and water samples in 
that interval. 
2. All samples were taken from long borehole intervals (approximately 8 to 10 m long), 
which cross regions of large gradients in gas species concentrations (up to a few orders 
of magnitude) and exhibit temperature variations of tens of degrees Celsius. The 
sampling boreholes may alter composition of the incoming gas and liquid phase 
compositions from fractures. 
3. The model does not consider all deviations from planned operation of the DST. These 
deviations include the exact time periods of power losses, variations in heat loss 
through the bulkhead, changes in pressure from forced ventilation, the effect of the 
many DST boreholes, and barometric pressure fluctuation. Changes predicted to occur 
at a particular time in the model may be shifted in the DST data by several months or 
more. 
4. Gas and water samples are affected by condensation of water vapor as the sample cools 
in the collection tubes from the borehole interval to the sample containers. This results 
in dilution by distillation of water vapor, and changes to CO2 concentrations. The pH 
of the water may drop as distillate formed in the sampling apparatus is mixed with 
water from the sampled borehole. 
The greatest effects from these mechanisms on the magnitude of differences in model-data 
comparisons may be expressed when the boiling front in the rock is proximal to the measurement 
location. The magnitude of such differences may be compared to the difference between 
relatively dilute condensate in fractures, and evaporatively concentrated waters closer to the 
boiling front. 

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Drift-Scale THC Seepage Model 


Coordinates from DTN: MO0002ABBLSLDS.000 [DIRS 147304]. 

NOTE: Borehole intervals are designated as 1, 2, 3, and 4 moving away from the Observation Drift (open circle 
designated OD). Temperature sensors (not labeled) are shown as the small closed circles, and are 
designated similarly to the intervals (i.e., sensor 60-4 is the 4th sensor from the Observation Drift). 
OD = Observation Drift; HD = Heated Drift. 

Figure 7.1-4. Locations of Hydrology Boreholes, Sampling Intervals (Numbered) and Temperature 
Sensors 

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Drift-Scale THC Seepage Model 

Given these considerations, the following criteria are adopted for validation using model-data 
comparisons for the DST: 

 Predicted temporal trends in the concentrations of aqueous and gaseous chemical species, 
and spatial distribution of precipitated mineral phases, should be similar to field 
measurements. Significant differences are explained qualitatively in terms of the 
physical and chemical processes. The THC modeling approach uses average properties 
and simulates average response; local or short-term variability in the measured data is 
associated with effects that are not included in the model. 
 Observed concentrations of gas and aqueous species, once adjusted for sample degassing 
and water vapor loss, match predicted concentrations to within an order of magnitude (up 
or down). This range is justified for several reasons. First, natural variability within the 
repository horizon pore waters is as much as five-fold for any given chemical species. 
Second, TH (boiling and condensation) and THC processes (mineralwatergas 
reactions) can lead to changes in the chemistry of water and gases by one or more orders 
of magnitude (Section 7.1.10.2) in response to small changes in temperature (e.g., around 
the boiling temperature of water). Third, differences in aqueous species concentrations in 
the rock may develop over distances of tens of centimeters or less, because diffusion rates 
of aqueous species in the rock matrix are limited (Section 7.1.11.3). Fourth, changes that 
the samples undergo during their extraction from the rock (e.g., cooling, degassing, 
condensation) have the potential for shifting aqueous species concentrations. 
Consistent with these potential contributions to uncertainty, the validation criterion of one 
order-of-magnitude in concentration (or a pH unit, up or down) is smaller than the potential 
range, and is appropriate for predicted compositions for fracture and matrix waters over the time 
period of the DST. 

As stated above, the THC seepage model approach uses average properties and simulates 
averaged responses, and does not predict small-scale or short-term events such as the spike in 
CO2 after 48 months in borehole 75 of the DST (Section 7.1.10). Furthermore, experimental 
measurements of CO2 and pH are directly impacted by sampling methodology, including 
changes in temperature and pressure, and sample degassing. Accordingly, validation of a given 
parameter may be done indirectly through examination of correlated parameters (e.g., pH, which 
is associated with significant data uncertainty, can be validated by comparing CO2 gas 
concentrations). 

7.1.7.2 Publication in a Refereed Technical Journal 
As described by LP-SIII.10Q-BSC, Section 5.3.2(d), technical review through publication in a 
refereed technical journal provides additional confidence in the THC seepage model. Essentially 
the same THC seepage model has been published in Journal of Contaminant Hydrology 
(Spycher et al. 2003 [DIRS 162121]). A second article in Journal of Contaminant Hydrology 
(Dobson et al. 2003 [DIRS 165949]) does not directly address the THC seepage model, but 
evaluates fracture sealing due to mineral precipitation for a Yucca Mountain tuff, and provides 
added confidence in the conceptual model implemented by TOUGHREACT. 

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Drift-Scale THC Seepage Model 

7.1.8 THC Simulations 
In the following sections, DST THC submodel simulations are described. Only the current 
simulation results are shown, sometimes with a brief discussion of any differences observed from 
previous revisions of this report. 

Key elements of the DST THC submodel include: 

1. A revised numerical mesh, to account for heat input at the drift center and heat and 
mass transfer across the Heated Drift and Observation Drift walls (Section 7.1.2) 
2. More accurate estimates of heater power over time (Section 7.1.3) 
3. Use of the same updated inputs as the current THC seepage model, including: 
 Calibrated thermal-hydrologic properties data set (Table 6.4-1) 
 Thermodynamic data (Appendix C) 
 Kinetic data (Section 4.1.3 and Table 4.1-3) 
 Geochemical system (Section 6.2.2.2 and Table 6.2-2), including aqueous species 
and primary and secondary mineral phases 
4. Consistent with the current THC seepage model, use of an improved method for 
mineral precipitation at the boiling front that is implemented in TOUGHREACT V3.0 
(LBNL 2002 [DIRS 161256]). This includes the addition of various salt minerals as 
potential precipitating phases (or as phases formed during flow into dry blocks; see 
Section 6.4.5). 
Three THC simulations and two TH simulations have been performed for this report using 
TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]): 

1. Extended Case Geochemical System (Table 6.2-2), EOS3 (no vapor pressure lowering 
due to capillary effects), higher CO2 diffusion coefficient (value used in most THC 
seepage model simulations) [simulation dstrev2_thc7] 
2. Extended Case, EOS4 (vapor pressure lowering due to capillary effects implemented), 
lower CO2 diffusion coefficient (used in THC seepage model sensitivity analysis) 
[simulation dstrev2_thc8] 
3. Extended Case, EOS3, lower CO2 diffusion coefficient [simulation dstrev2_thc9] 
4. EOS3 TH simulation [simulation dstrev2_th12] 
5. EOS4 TH simulation [simulation dstrev2_th13]. 
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Drift-Scale THC Seepage Model 

In all DST THC submodel simulations, HD-PERM water (W0, Table 6.2-1) was used as the 
starting water, as this water was recovered from borehole core from Alcove 5, near the DST. 
The extended-case geochemical system is used for all DST THC simulations because the THC 
seepage model considers only this geochemical system. Results from the high diffusion 
coefficient Simulation 1 are not shown because validation should be based on parameter values 
within the range expected. All input and output data files for the DST THC simulations are 
given in Appendix G. 

The following Sections 7.1.9 through 7.1.14 present the model results, representative data from 
the DST, and the model-data comparisons that support validation of the THC seepage model. 
Section 7.1.9 describes the prediction of thermal-hydrologic conditions, which is covered in 
more detail by Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338], Section 7.4). Section 7.1.10 presents the model-data comparisons for gas-phase 
CO2, an important variable that controls carbonate chemistry and directly affects the chemical 
environment in the emplacement drifts. Section 7.1.11 describes model-data comparisons for 
aqueous species, which were analyzed in samples of fracture water collected in DST boreholes. 
Section 7.1.12 describes mineralogical changes predicted by the DST THC submodel, with 
comparison to the available analysis of minerals formed during the test. Section 7.1.13 describes 
the predicted changes in fracture and matrix porosity, and the implication for bulk permeability, 
with discussion of the observed indications of permeability change in the DST. Finally, Section 

7.1.14 presents representative 14C isotopic analysis of gas samples, and interprets the evolution 
of 14CO2 during the heating phase in terms of the operant chemical processes in the DST THC 
submodel. 
7.1.9 Simulation Results: Thermal and Hydrologic Evolution 
The main driving force for changes in the hydrologic and chemical behavior of the system is the 
thermal load applied to the system. The resulting changes in temperature, liquid saturation, and 
gas-phase composition lead to changes in the chemistry of water and gas, as well as mineral 
dissolution and precipitation. A more complete discussion of thermal-hydrologic processes is 
presented in Drift-Scale Coupled Processes (DST and TH Seepage) Models (BSC 2004 
[DIRS 170338]). Key aspects of the thermal-hydrologic behavior of the DST that drive the 
chemical evolution of the system are discussed briefly in this section. 

The simulation results for the TH evolution of the DST, as well as all other simulation results 
shown in this section, are based on Simulation 2 above, performed using the EOS4 module in 
TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]). TH (and chemical) results are nearly 
identical to those not using the vapor-pressure-lowering (EOS3) in Simulation 3, and the latter 
are therefore not shown. Outputs from all simulations are, however, included in the data 
submittal to the TDMS. The relatively minor difference in the results is largely related to the 
implementation of revised capillary pressure curves in the hydrologic parameter set. The 
property set has a maximum capillary pressure of 108 Pa, which results in a relatively small 
change in the saturation-temperature history in the rock as it is heated. Low matrix 
permeabilities in the model parameter set lead to higher matrix pore pressure, thus delaying 
boiling more substantially than the capillarypressurelowering effect. In addition, coupled 
effects of mineral precipitation/dissolution on flow did not significantly affect the TH evolution 
of the DST. 

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Drift-Scale THC Seepage Model 

The modeled temperatures in the drift reflect the heat input at the drift center (at the approximate 
location of the electrical canister heater) and subsequent heat transfer to the drift wall 
(Figure 7.1-5). Differences in temperature between the drift center and drift wall (Figure 7.1-5) 
near the top (drift crown) are approximately 20C, similar to the differences observed between 
electrical canister temperatures and drift-crown temperature measurements 
(DTN: MO0007SEPDSTPC.001 [DIRS 153707]). Sharp temperature drops are the result of 
power losses, heater failures, and/or intentional power reductions. 

Drift-wall temperatures predicted by the two-dimensional model eventually exceed the 
maximum measured values by about 20C. However, predicted temperatures in the rock are 
typically closer to measured values (Figure 7.1-6). There are several reasons for the elevated 
temperature in the drift. First, the two-dimensional cross section can only approximate the 
exchange of heat through the rock along the axis of the DST. Second, heat lost through the 
bulkhead by a combination of advection and diffusion is uncertain and is approximated using a 
bulkhead correction that is essentially one-dimensional. Therefore, this model is most applicable 
to areas near the center of the testaway from both the bulkhead and away from the distal end 
of the Heated Drift. For application to repository simulation, the THC seepage model is used 
similarly, to predict the composition of waters in the host rock that could potentially seep into 
drifts. 

Other factors that control the temperature response of the drift wall include thermal properties 
(conductivity, heat capacity) of the rock and the representation of heat transfer processes in the 
drift (i.e., the approximate treatment of thermal radiation and convection). However, comparison 
of temperatures measured in the rock, with simulated temperatures, provides an effective test of 
validity for treatment of heat transfer to the rock. Confidence in the approach used is supported 
by the close agreement with measured temperatures (Figure 7.1-6). 

The modeled distributions of fracture and matrix liquid saturation (with temperature contours 
overlain) are shown in Figures 7.1-7a to d. The plots correspond to one and four years from the 
initiation of the heating phase. The extent of the dryout zone increases over the heating period 
and is larger in the fractures than in the matrix. A wider spatial interval between the 90C and 
100C isotherms indicates the presence of an isothermal boiling/condensation (heat pipe) zone, 
which is especially well developed above the wing heaters. An extensive drainage zone 
extending several tens of meters in the fractures below the heaters contrasts with a very narrow 
high-saturation zone above the heaters, where water is continuously diverted around the heated 
zone. The narrow band of increased fracture saturation above the heaters is characterized by 
temperatures of about 90C to 95C. Typically, water was collected from hydrology boreholes 
when this heat-pipe zone intersected the borehole intervals (Figure 7.1-4) (BSC 2004 
[DIRS 170338], Section 7.4.3). During the DST, saturation changes in the rock were monitored 
using ground-penetrating radar (GPR) and electrical resistance tomography (ERT) (BSC 2004 
[DIRS 170338], Section 7.4.1). The spatial distribution of the observed changes in matrix 
saturation are similar to model results as discussed further in Drift-Scale Coupled Processes 
(DST and TH Seepage) Models (BSC 2004 [DIRS 170338], Section 7.4.3.2). 

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Output DTN: LB0307DSTTHCR2.001. 
Figure 7.1-5. Drift Center and Drift Crown Modeled Temperatures over the First Six Years of the DST 



Output DTN: LB0307DSTTHCR2.001 (modeled values). 

NOTE: Modeled temperatures are for a nearby grid node. Location of temperature sensor is indicated on Figure 
7.1-4. See Table 7.1-1 for DTNs for measured temperatures. 

Figure 7.1-6. Comparison of Modeled and Measured Temperatures over Time for the Sensor Located at 
Hydrology Borehole Packer 60-4 

MDL-NBS-HS-000001 REV 04 7-18 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Borehole intervals where water samples were collected are shown in Figure 7.1-7. 

Figure 7.1-7. Liquid Saturation (Colors) and Temperature (Contour Lines) in the DST (Base Case) at 
One Year (Matrix  a, Fracture  b) and at Four Years (Matrix  c, Fracture  d) 

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Drift-Scale THC Seepage Model 

7.1.10 Gas-Phase CO2 Evolution: Measured Compositions and Simulation Results 
The evolution of CO2 concentrations in the gas phase is discussed in this section. Simulation 
results are compared to concentrations measured in gas samples taken from boreholes during the 
entire heating phase of the DST. The concentration of CO2 in the gas phase is a function of 
temperature, pressure, aqueous-phase chemistry, mineralwater reactions, and advective and 
diffusive transport. From a model validation standpoint, the strong effect of CO2 partial pressure 
on water pH and the final brine composition formed upon evaporation make the analysis of CO2 
distributions in the DST important. Numerous measurements of CO2 concentrations in gas 
collected from the DST have been made as a function of space and time, and therefore a more 
complete comparison of the model results to CO2 data can be made than to the relatively fewer 
number of water-chemistry measurements. CO2 concentrations in gases collected from the DST 
also provide a qualitative measure of the influence of atmospheric gas on the system, because of 
the relatively low and constant value in the atmosphere ( 400 ppmv). Isotopic compositions of 
CO2 (discussed in Section 7.1.14) yield insight into the sources of CO2. 

7.1.10.1 Gas Sampling and CO2 Measurements 
Gas sampling, analytical methods, and compositional data are discussed in Thermal Testing 
Measurements Report (BSC 2004 [DIRS 169900], Section 6.3.4.2). Gas samples were taken 
from several meter-long borehole intervals that spanned a wide range of temperatures as a result 
of their orientation relative to the heaters. As part of the sampling procedure, the gas samples 
had much of their water vapor removed before analyses were performed, and therefore measured 
CO2 concentrations are for the noncondensable gas fraction. The noncondensable gas fraction is 
very high (>95 percent) at the ambient temperature of about 25C, but may drop to extremely 
low values (<1 percent) under boiling conditions. Hence, reported CO2 concentrations at 
temperatures close to boiling are much higher than if the measurements were made on a 
complete gas composition (air + CO2 + H2O). This effect must be considered when comparing 
model results to measured values. 

An example of the distributions of measured CO2 concentrations (DTNs listed in Table 7-1) after 
one year and after 15 months of heating is shown in Figure 7.1-8. Comparison of the 15-month 
to the one-year data shows that in nearly all of the boreholes, the CO2 concentrations are higher 
at 15 months, owing to heating of pore water and exsolution of CO2 into the gas phase. Areas 
that have maintained CO2 concentrations close to the ambient value in the rock of around 
1,000 ppmv (log volume fraction = 3) can be seen near the observation drift. However, very 
close to the Observation Drift, some of the values are lower, suggesting that mixing with 
atmospheric gas may have taken place. 

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Drift-Scale THC Seepage Model 


Source: DTN: LB990630123142.003 [DIRS 111476]. 

NOTE: Concentrations refer to intervals between pairs of points. 

Figure 7.1-8. Measured Concentrations of CO2 (log vol. fraction) in Gas Phase around the DST at 1 Year 
and at 15 Months 

7.1.10.2 Modeled Spatial Distribution of CO2 
Model results are presented for the extended system (described in Table 6.2-2). Modeled 
distributions of CO2 concentrations (log ppmv) in fractures are shown at yearly intervals during 
the heating phase (Figure 7.1-9) and during the cooling phase (Figure 7.1-10). Over the heating 
phase of four years, a region of highly elevated CO2 concentrations, centered approximately at 
the 60C isotherm, is seen to move gradually outward from the heaters. Outside this region, CO2 
concentrations gradually decrease to the ambient value in equilibrium with pore water 
(approximately 1,000 ppmv). Maximum CO2 concentrations of around 50,000 ppmv are located 
above and below the wing heaters and Heated Drift. Towards the heaters, CO2 concentrations 
drop off more sharply with increasing temperature, decreasing to values below 10 ppmv. This 
sharp decline takes place as a result of the CO2 degassed during heating of the pore water, its 
transport outward, and displacement of air and CO2 by steam generated during boiling. 

MDL-NBS-HS-000001 REV 04 7-21 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Compare to calculated values in Figure 7.1-8. 

Figure 7.1-9. Modeled Gas Phase CO2 Concentrations (Log ppmv) in Fractures during the Heating 
Phase of the DST at 1, 2, 3, and 4 Years 

The zone of maximum CO2 concentrations also transects the hydrology borehole intervals as it 
migrates outwards, with some intervals registering a two order-of-magnitude variation between 
them. 

The effect of the atmospheric CO2 concentration of the gas in the Observation Drift on its 
surroundings is evident up to about 10 m from the drift wall. However, effects on the fracture 
gas composition are relatively minor beyond about 5 m from the drift wall. Carbon dioxide 
concentrations in the Heated Drift stay close to the atmospheric value, owing to transport 
(advection and diffusion) between the Heater Test Alcove (set to atmospheric CO2) and the 
Heated Drift. 

The modeled cooling phase of the DST (Figure 7.1-10) is characterized by a gradual 
re-equilibration of CO2 concentrations throughout the DST area, via cooling, gas-phase 
diffusion, and flow of gas and water. Exchange of atmospheric gas among the Heated Drift, 
Heater Test Alcove, and rock around the Heated Drift is clearly evident. 

MDL-NBS-HS-000001 REV 04 7-22 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001. 

Figure 7.1-10. Modeled Gas Phase CO2 Concentrations (Log ppmv) in Fractures during the Cooling 
Phase of the DST at 5, 6, 7, and 8 Years 

7.1.10.3 Modeled and Measured CO2 Concentrations over Time 
Validation of the DST THC submodel for the prediction of the temporal evolution of CO2 
concentrations is performed by comparison of measured values from intervals repeatedly 
sampled from February 1998 through January 2002 (DTNs listed in Table 7-1) to model results. 
The locations of the grid block central coordinates relative to the gas collected in borehole 
intervals from which the gas samples were taken are illustrated in Figure 7.1-11. Because the 
measured concentrations come from borehole intervals that are several meters long, and not from 
a specific location, model data are chosen from the grid block closest to the center of the interval. 
If a grid block is not centered on the borehole, a grid block closest to the center is chosen on the 
outer (cooler) side of the borehole. Grid blocks on the cooler side should compare more closely 
to the measured data because the two-dimensional model, having no heat loss in the rock 
perpendicular to the drift, produces temperatures that are somewhat higher than the measured 
temperatures after approximately the first year of heating. However, measured temperatures may 
be higher prior to that time (refer back to the temperature comparison in Figure 7.1-6). 

MDL-NBS-HS-000001 REV 04 7-23 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LB991200DSTTHC.002 [DIRS 142162]. 

NOTE: Borehole intervals from which gas samples were taken are shown in the hachured regions. 

Figure 7.1-11. Close-Up of DST Grid, Showing Nodes Used to Extract Model Data for Comparison to 
Concentrations Measured in Gas Samples 

Figure 7.1-12 shows measured CO2 concentrations that have been corrected for the effect of 
water-vapor condensation during sample collection. More details regarding the effect and the 
process involved in the correction procedure are given following the discussion of results in this 
section. Measured and modeled data are presented up to the end of the heating phase of the DST 
(including a few measurements performed about 1 month into the cooling phase). In the hottest 
interval (76-3), the concentrations remained low from 2 years after heating was initiated until 
after the cooling phase had begun. Except for one sample that may have been predominantly 
water vapor, similar but delayed behavior took place in 75-3. Modeled compositions shown for 
74-3 are given as an average of the values from the upper and lower grid blocks shown in 
Figure 7.1-11. 

The measured values in Figure 7.1-12 have been corrected for water extraction from the gas 
during collection. CO2 concentrations have been corrected for the approximate amount of water 
removed during chilling of the gas sample from the temperature of the sampling interval to 25C. 
The method assumes that the gas is vapor-saturated, removes the appropriate amount of water 
vapor to the amount at saturation at 25C, and adds some of the CO2 into solution (the 
condensate) as HCO3, based on the equilibrium partitioning of CO2 into H2O. The actual 
temperature of the chiller was 4C; however, the efficiency of the unit was such that not all water 
was taken out when the gas was at boiling temperatures (BSC 2004 [DIRS 169900], Section 
6.3.4.2.5). Therefore, for consistency, the chill temperature was set to 25C for all samples. 
Because the difference in water vapor content between 25C and 4C is small, this 

MDL-NBS-HS-000001 REV 04 7-24 February 2005 


Drift-Scale THC Seepage Model 

approximation is valid. For samples with temperatures below approximately 60C, the 
correction is very small; however, at temperatures near boiling, the correction may be close to an 
order of magnitude (Section 7.1.10.1). The corrections are documented by Wang (2003 
[DIRS 161665], Notebook SN-LBNL-SCI-112-V2, pp. 60 to 63). 

The effect of the correction on the measured CO2 concentrations is a gradual (but increasing) 
reduction up to the boiling temperature, where the sharp second spike in the uncorrected data 
largely disappears. It is clear that the correction to the measured concentrations substantially 
improves the comparison to the modeled data at higher temperatures. Figure 7.1-13 shows an 
example of the effect of the correction on the CO2 concentrations for borehole interval 75-3. 

Trends in modeled CO2 concentrations are clearly followed for all borehole intervals evaluated. 
Deviations in concentrations for certain samples can be attributed to the factors discussed in 
Section 7.1.7.1. The comparison of simulated and measured (corrected) CO2 concentrations are 
generally within a factor of 2, and in most cases within an order of magnitude, except for low 
concentration, high-temperature samples, where the correction due to condensation of water 
vapor is large. The second peak in the data at 48 months is not consistent with any process 
predicted to occur in the rock and is associated with near-boiling sampling conditions when only 
a tiny fraction of the gas is noncondensable and the potential error in the correction for water 
vapor extraction is relatively large. Accordingly, the validation criteria discussed in Section 

7.1.7 are met. 
7.1.11 Aqueous Species Evolution 
7.1.11.1 Chemistry of Waters Sampled During the Drift Scale Test 
Water samples were collected from several hydrology boreholes during the heating phase of the 
DST. Collection dates, volumes, and field measurements (e.g., pH) for all water samples are 
presented in Thermal Testing Measurements Report (BSC 2004 [DIRS 169900], Table 
6.3.4.1-1). Cation and anion analyses of the water samples are given in Table 6.3.4.1-2 
(DTN: LL020709923142.023 [DIRS 161677]) of the same report. The latter table lists all 
samples that were analyzed, regardless of their origin. In particular, many samples were 
collected from borehole intervals above boiling temperatures and were clearly derived from 
water vapor that condensed in the tubing leading out of the interval. In most cases, such samples 
are clearly recognizable from the water samples pumped directly out of boreholes (and in contact 
with rock), based on (1) their significantly lower pH (most below pH 5) relative to water samples 
that accumulated inside the boreholes (nearly all above pH 6), (2) their extremely low anion and 
cation content (total dissolved solids around 10 ppm or less), and (3) very low total Si 
concentrations (most much less than 10 mg/L) compared to water samples having total Si 
concentrations mostly greater than 40 mg/L. 

MDL-NBS-HS-000001 REV 04 7-25 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LB0208ISODSTHP.001 [DIRS 161638] (measured CO2 uncorrected). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-12. Comparison of Modeled CO2 Concentrations in Fractures to Measured (Corrected) 
Concentrations in Boreholes: (a) Borehole Interval 74-3 (Average of Bounding Grid 
Blocks); (b) Borehole Interval 75-3; (c) Borehole Interval 76-3 

MDL-NBS-HS-000001 REV 04 7-26 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LB0208ISODSTHP.001 [DIRS 161638] (measured CO2 uncorrected). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

NOTE: See text for discussion of the outliers at 48 months. 

Figure 7.1-13. Comparison of Measured and Corrected Concentrations for Borehole Interval 75-3 and 
the Model Simulation Results 

Specific exceptions to these criteria are those samples collected from intervals at high 
temperatures (>140C) that have relatively low pH values (< pH 4), elevated F concentrations 
(>10 mg/L), and relatively high total Si values, but contain few other measurable constituents. 
Experimental studies confirmed the hypothesis that the breakdown of fluoroelastomer packer 
materials at elevated temperatures was responsible for the unusual water compositions that 
formed as high-temperature vapor condensed in tubing and was collected as water (BSC 2004 
[DIRS 169900], Table 6.3.4.1-1). In addition, some waters may have been affected by 
degradation of neoprene packers in sub-boiling zones, such as the high Cl water collected from 
borehole 59, interval 4 (Williams 2003 [DIRS 163765]). 

Chemical analyses of water samples that, based upon the compositional criteria discussed above, 
were wholly or mostly derived from water that had resided in a borehole (rather than formed 
during condensation of water vapor in the collection tube) are given in Table 7.1-3. The 
intervals where these waters were collected are shown as the blue shaded zones in Figure 7.1-14. 
The water samples collected during the test were obtained from zones that were hotter than the 
temperatures given for the samples because the samples cooled substantially as they were 
pumped out of the rock through the sample collection tubing and into the sample containers. 
Also listed in Table 7.1-3 are the compositions of pore waters that had been ultracentrifuged out 
of the rock matrix from a dry-drilled borehole near the DST (HD-PERM designations). 

MDL-NBS-HS-000001 REV 04 7-27 February 2005 


Drift-Scale THC Seepage Model 

INTENTIONALLY LEFT BLANK 


MDL-NBS-HS-000001 REV 04 7-28 February 2005 


Drift-Scale THC Seepage Model 

Table 7.1-3. Measured Concentrations in Tptpmn Pore Water from Alcove 5 and Chemistry of Water Samples from Hydrology Boreholes 

SMF No. (SPC0) 1002488 1002586 1002525 05279699 05279689 0527915a 0527977a 0527916a 0541804a 1541804a,b 05043968 0529637-#1a 0529637-#2a 
Collection Date Pre-Heating Pre-Heating Pre-Heating 06/04/98 06/04/98 08/12/98 06/04/98 08/12/98 11/12/98 11/12/98 01/26/99 03/30/99 03/30/99 
Collection Time 9:50 AM 9:55 AM 
Sample ID PERM-1c PERM-2c PERM-3c BH 60-2 BH 60-2 BH 60-2 BH 60-3 BH 60-3 BH 60-3 BH 60-3 BH 60-3 BH 60-3 BH 60-3 
Field pHd 7.79 8.32 8.31 7.5 na 6.9 7.7 6.8 6.92 6.92 7.4 8.0 na 
Metals / Cations 
Na (mg/L) 60.5 61.0 61.5 20.0 na 20.4 24.0 17.2 10.1 20.3 19.1 11.2 11.0 
Si (mg/L) 37 31 35 56 na 51.8 41 43.5 60.0 53.8 65.0 62.8 59.8 
Ca (mg/L) 98.17 106.17 96.67 20 na 19.9 25 18.7 15.3 13.9 5.93 2.06 2.27 
K (mg/L) 6.0 7.0 9.0 6.0 na 5.4 4.5 4.5 8.7 7.8 4.1 2.4 2.4 
Mg (mg/L) 25.65 16.55 17.35 2.9 na 1.21 5.7 4.0 3.35 3.00 1.17 0.27 0.26 
Al (mg/L) < 0.06 < 0.06 < 0.06 0.12 na < 0.06 0.017e 0.003e 0.033e 0.033e < 0.06 0.36, 0.27e 0.36, 0.27e 
B (mg/L) 3.05 2.75 2.75 1.2 na 1.84 0.92 1.14 1.58 1.41 1.75 2.10 2.11 
S (mg/L) 42.25 38.6 38.65 5.5 na 4.5 9.2 5.2 11.6 10.5 6.4 1.83 1.82 
Fe (mg/L) < 0.02 < 0.02 < 0.02 0.04 na 0.02 < 0.02 0.12 0.02 < 0.02 < 0.02 < 0.02 < 0.02 
Li (mg/L) 0.1 0.45 0.05 0.07 na 0.03 0.07 0.040 0.040 0.040 0.02 0.02 < 0.01 
Sr (mg/L) 1.4 1 1.05 0.18 na 0.11 0.34 2.21 0.22 0.20 0.09 0.02 0.02 
Anions 
HCO3 (mg/L)f na na na na na na na 41 25.0 na 
F (mg/L) 0.36 0.96 0.76 na 1.00 0.71 0.82 0.43 0.49 0.50 1.27 1.02 0.97 
Cl (mg/L) 122.73 109.93 123.13 na 10 6.14 16 5.52 19.5 19.6 10.3 4.15 3.92 
Br (mg/L) 0.6 0.76 1.2 na 0.84 0.05 0.73 0.21 0.6 0.51 0.15 < 0.04 < 0.04 
SO4 (mg/L) 124.18 111.38 119.78 na 17 4.88 30 8.81 30.6 30.8 13.5 3.83 3.75 
PO4 (mg/L) < 0.07 < 0.07 < 0.07 na < 0.07 0.25 < 0.07 0.16 < 0.2 < 0.2 < 0.05 < 0.05 < 0.05 
NO2 (mg/L) < 0.04 < 0.04 < 0.04 na < 0.01 < 0.04 < 0.01 < 0.04 < .10 < .10 < .03 < 0.03 < 0.03 
NO3 (mg/L) 21.72 2.52 10.40 na 3.00 0.46 3.6 0.60 3.38 3.17 2.56 0.92 0.84 

MDL-NBS-HS-000001 REV 04 7-29 February 2005 


Drift-Scale THC Seepage Model 

Table 7.1-3. Measured Concentrations in Tptpmn Pore Water from Alcove 5 and Chemistry of Water Samples from Hydrology Boreholes (Continued) 

SMF No. (SPC0) 0551159a 0551160a 0557029a 0557032 0557033a 0557080 0557081 0557083 0557022 0550671 0550673 0550681 0550682 
Collection Date 08/09/99 08/09/99 10/27/99 10/27/99 10/27/99 11/30/99 11/30/99 11/30/99 01/25/00 01/25/00 01/25/00 05/23/00 05/23/00 
Collection Time 
Sample ID BH 59-2(AC) BH 59-2(BC) BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 
Field pHd na na na 5.93 6.08 6.86 7.24 na 7.07 6.68 na 6.96 6.96 
Metals / Cations 
Na (mg/L) 30 24 na 9.2 9.2 6.6 7.7 na 8.1 6.6 na 17 18 
Si (mg/L) 78 81 na 44.5 44.9 38.0 39.9 na 42.8 41.7 na 59.4 59.2 
Ca (mg/L) 47 39 na 7.53 7.47 4.33 5.63 na 7.54 2.89 na 4.7 4.4 
K (mg/L) 8 6 na 3.4 3.6 2.6 3.0 na 3.6 2.8 na 4.3 4.4 
Mg (mg/L) 13 11 na 1.81 1.72 1.02 1.38 na 1.78 0.72 na 1.1 1.1 
Al (mg/L) < 0.2 < 0.2 na 0.033g 0.033g 0.030 0.030 na < 0.05 0.043 na < 0.053 < 0.053 
B (mg/L) 0.8 0.6 na 0.27 0.21 0.14 0.17 na 0.29 0.21 na na na 
S (mg/L) 22 17 na 2.52 2.50 0.76 1.33 na 6.44 0.65 na na na 
Fe (mg/L) 0.41 0.32 na 0.20 0.19 0.09 0.14 na 0.07 < 0.02 na < 0.038 < 0.038 
Li (mg/L) < 4 < 4 na 0.16 0.01 0.01 0.01 na < 0.01 < 0.01 na 0.021 0.022 
Sr (mg/L) 0.54 0.45 na 0.11 0.08 0.06 0.08 na 0.091 0.036 na < 0.013 < 0.013 
Anions 
HCO3 (mg/L)f na na 23.5 na 23.5 na na 22.3 na na 22.8 31.4 31.4 
F (mg/L) 0.725 0.575 0.27 na 0.27 na na 0.35 na na 0.73 0.58 0.55 
Cl (mg/L) 88.3 71.0 9.5 na 9.1 na na 5.0 na na 3.8 10.15 10.6 
Br (mg/L) 0.515 0.46 0.61 na 0.58 na na < 0.03 na na < 0.1 < 0.1 0.38 
SO4 (mg/L) 64.2 53.5 6.2 na 6.3 na na 2.8 na na 1.8 2.9 3.18 
PO4 (mg/L) < 0.02 < 0.02 < 0.02 na < 0.02 na na < 0.02 na na 0.62 < 0.2 < 0.2 
NO2 (mg/L) < 0.007 < 0.007 < 0.007 na < 0.007 na na < 0.007 na na < 0.05 < 0.06 < 0.06 
NO3 (mg/L) 3.79 2.83 1.32 na 1.40 na na < 0.02 na na 0.77 0.56 0.54 

MDL-NBS-HS-000001 REV 04 7-30 February 2005 


Drift-Scale THC Seepage Model 

Table 7.1-3. Measured Concentrations in Tptpmn Pore Water from Alcove 5 and Chemistry of Water Samples from Hydrology Boreholes (Continued) 

SMF No. (SPC0) 0550684 0550693 0550694 0550691 0550689 0550690 0530398 0557036a 0557038a 0552575 0557043 0541803a 0541803a,b 
Collection Date 05/23/00 06/29/00 06/29/00 06/29/00 06/29/00 06/29/00 01/23/01 10/27/99 10/27/99 11/30/99 11/30/99 11/12/98 11/12/98 
Collection Time 
Sample ID BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-2 BH 59-3 BH 59-3 BH 59-3 BH 59-3 BH 59-4 BH 59-4 
Field pHd 6.95 6.99 to 7.08 6.99 to 7.08 7.00 na na na na 6.64 7.47 na 6.63 6.63 
Metals / Cations 
Na (mg/L) 17 16 15 < 4.8 na na 29 na 19.3 15.6 na 22.6 135 
Si (mg/L) 59.3 62.7 57.5 36.3 na na 84.5 na 84.2 92.5 na 33.5 44.2 
Ca (mg/L) 4.5 4.3 3.8 2.0 na na 7.8 na 13.2 2.86 na 476 450 
K (mg/L) 4.4 4.7 4.2 2.5 na na 5.8 na 5.6 3.9 na 29.5 37.8 
Mg (mg/L) 1.1 1.1 1.0 0.54 na na 1.8 na 1.49 0.29 na 64.1 83.9 
Al (mg/L) < 0.053 < 0.053 < 0.053 < 0.11 na na < 0.053 na 0.040 0.071 na 0.01e < 0.06 
B (mg/L) na na na na na na na na 0.86 1.06 na 4.47 4.13 
S (mg/L) na na na na na na na na 14.48 3.25 na 50.7 64.8 
Fe (mg/L) < 0.038 < 0.038 < 0.038 < 0.076 na na < 0.038 na < 0.02 < 0.02 na < 0.02 < 0.02 
Li (mg/L) 0.021 0.019 0.018 0.010 na na 0.033 na 0.02 0.02 na 0.21 0.20 
Sr (mg/L) < 0.013 < 0.013 < 0.013 < 0.026 na na < 0.013 na 0.13 0.03 na 4.02 3.71 
Anions 
HCO3 (mg/L)f 31.4 na na na 29.4 29.4 na 12.4 12.4 na 20.7 na na 
F (mg/L) 0.49 na na na 0.18 0.15 0.78 0.64 0.73 na 1.3 0.8 4.3 
Cl (mg/L) 10.15 na na na 0.90 0.32 25.20 12.9 12.9 na 8.8 1,130 1,250 
Br (mg/L) < 0.1 na na na 0.62 0.48 < 0.1 0.89 0.51 na < 0.03 1.13 < 0.07 
SO4 (mg/L) 3.1 na na na 0.5 0.42 9.5 40.7 40.3 na 8.2 226 213 
PO4 (mg/L) < 0.2 na na na < 0.2 < 0.2 < 0.2 < 0.04 < 0.04 na < 0.02 < 5 < 0.2 
NO2 (mg/L) < 0.06 na na na < 0.06 < 0.06 < 0.06 < 0.01 < 0.01 na < 0.007 < 3 < 10 
NO3 (mg/L) 0.71 na na na 0.65 0.48 0.99 3.06 3.05 na 2.4 3.12 7.81 

MDL-NBS-HS-000001 REV 04 7-31 February 2005 


Drift-Scale THC Seepage Model 

Table 7.1-3. Measured Concentrations in Tptpmn Pore Water from Alcove 5 and Chemistry of Water Samples from Hydrology Boreholes (Continued) 

SMF No. (SPC0) 
Collection Date 
Collection Time 
Sample ID 
0504397a01/26/99 
BH 59-4 
0551169a 
08/10/99BH 61-3 
0559464 
04/17/01BH 76-2 
0559458 
04/17/01 
BH 76-2 
0559456 
04/17/01BH 76-2 
1016082 
01/07/02BH 76-2 
0557040a 
10/27/99BH 76-3 
0552578 
11/30/99BH 76-3 
0552579 
11/30/99BH 76-3 
0550697 
05/23/00BH 76-3 
0541805a 
11/12/98 
BH 186-3 
0541805a,b11/12/98 
BH 186-3 
0527961a 
01/26/99 
BH 186-3 
Field pHd 
Metals / Cations 
Na (mg/L) 
Si (mg/L) 
Ca (mg/L) 
K (mg/L) 
Mg (mg/L) 
Al (mg/L) 
B (mg/L) 
S (mg/L) 
Fe (mg/L) 
Li (mg/L) 
Sr (mg/L) 
na 
219 
12.0 
429 
29.7 
164 
0.086e 
6.68 
109 
< 0.02 
0.33 
5.84 
na 
19 
67 
14 
5 
3.2 
< 0.2 
1.5 
3.1 
1.2 
< 4 
0.14 
7.68 
9 
42.6 
1.3 
1.6 
0.27 
0.42 
na 
na 
0.40 
0.0098 
< 0.013 
8.22 
9 
44.1 
1.1 
1.6 
0.22 
0.43 
na 
na 
0.40 
0.010 
< 0.013 
8.29 
9 
45.6 
1.3 
1.9 
0.23 
0.45 
na 
na 
0.39 
0.0076 
< 0.013 
7.8 
na 
na 
na 
na 
na 
na 
na 
na 
na 
na 
na 
6.14 to 6.46 
64.5 
133.4 
59.5 
13.4 
13.8 
0.010 
2.38 
34.55 
< 0.02 
0.13 
0.78 
6.94 
28.2 
92.8 
22.3 
7.4 
4.71 
0.031 
0.81 
9.46 
0.10 
0.04 
0.26 
na 
na 
na 
na 
na 
na 
na 
na 
na 
na 
na 
na 
6.92 to 6.96 
29 
96.0 
7.1 
6.5 
1.4 
< 0.053 
na 
na 
< 0.038 
0.045 
< 0.013 
6.83 
105 
16.0 
11.5 
3.5 
5.1 
< 0.003e0.51 
8.47 
0.02 
0.05 
0.30 
6.83 
17.0 
27.2 
20.2 
3.9 
5.68 
< 0.003e0.58 
9.42 
< 0.02 
0.05 
0.34 
7.2 
25.9 
49.3 
2.92 
5.9 
6.32 
< 0.06 
0.84 
7.9 
0.09 
0.05 
0.37 
Anions 
HCO3 (mg/L)f 
F (mg/L) 
Cl (mg/L) 
Br (mg/L) 
SO4 (mg/L) 
PO4 (mg/L) 
NO2 (mg/L) 
NO3 (mg/L) 
na 
0.51 
1,160 
1.51 
240 
< 0.5 
< .3 
11.6 
na 
0.835 
24.1 
0.35 
9.13 
< 0.02 
< 0.007 
0.825 
na 
na 
na 
na 
na 
na 
na 
na 
na 
0.38 
1.9 
< 0.1 
0.89 
< 0.2 
< 0.06 
< 0.09 
na 
0.47 
1.71 
< 0.1 
0.85 
< 0.2 
< 0.06 
< 0.09 
< 5 
0.4 
2.75 
< 0.2 
1.02 
< 0.3 
< 0.2 
< 0.2 
na 
1.11 
81.9 
0.97 
94.6 
< 0.02 
< 0.007 
6.42 
na 
na 
na 
na 
na 
na 
na 
na 
82.3 
1.3 
19 
< 0.03 
26.0 
< 0.02 
< 0.007 
2.5 
na 
0.76 
14.5 
< 0.1 
4.98 
< 0.2 
< 0.06 
1.47 
na 
0.56 
18.7 
0.67 
26.3 
< 0.2 
< .1 
7.47 
na 
0.62 
18.6 
0.60 
26.2 
< 0.2 
< .1 
7.27 
116 
1.20 
23.3 
0.32 
21 
< 0.1 
< 0.05 
6.73 

a 

Analytical results are corroborating data (as defined in Section 3.6 of AP-SIII.3Q) and non-qualified. See Table 7-1 for Source DTNs. 
b Sample filtered in the field and laboratory (LLNL) prior to analyses. 

c 

Pore water samples (baseline): sample ultracentrifuged from borehole core. 
d See entry in BSC 2004 [DIRS 169900], Table 6.3.4.1-1, for temperature of pH measurements. 

e 

Low detection limit analysis  sample filtered to 0.10 mm and acidified. 

f

HCO3  field measurement. 
g Sample ID SPC0057028 submitted for low detection for AI analysis. 

NOTE: na = not available; < = not detected (less than practical reporting limit). Field chemistry of samples for high fluoride study (11/8/01 to 12/5/01) are reported in BSC 2004 [DIRS 169900], Table 6.3.4.5-1. 

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Drift-Scale THC Seepage Model 


DTNs: LB0307DSTTHCR2.001 (meshOutput-DTN), MO0002ABBLSLDS.000 [DIRS 147304] (sensors and 
boreholes). 

Source: BSC 2004 [DIRS 169900], Table 6.3.4.1-1 - water collection locations. 

NOTE: Only those waters having the distinct criteria discussed in this section are considered to have been liquid 
in the borehole. Locations where comparisons are made to measured compositions are shown as green 
circles. The Heater Drift is shown in red. 

Figure 7.1-14 Zones Where Water Was Collected from Hydrology Boreholes Superimposed (Thick 
Shading in Blue) on the Model Grid 

MDL-NBS-HS-000001 REV 04 7-33 February 2005 


Drift-Scale THC Seepage Model 

Some of the processes that could explain the water chemistry of samples collected in the 
hydrology boreholes include mixing of pure condensate water with fracture pore waters, 
equilibration of condensate waters with matrix pore waters via molecular diffusion, reaction of 
condensate waters with fracture-lining minerals, and mineral precipitation. Waters that were 
collected from the hydrology boreholes at elevated temperatures are generally more dilute (lower 
Cl and SO42) and lower in pH than the initial pore water. Aqueous silica concentrations are 
similar to or much higher than in the pore water, indicating that these waters are not simple 
mixtures of pore water and pure condensate water. Some clear trends in water chemistry of the 
condensate waters over time are increases in pH and SiO2 (aq) concentration and a drop in Ca2+. 
The higher silica concentration in the waters collected at later times in several boreholes (and at 
higher temperatures), relative to chloride and the initial pore-water silica concentration, is 
consistent with dissolution of a silicate phase, rather than with increased concentration via 
boiling. Concentrations of K+, Mg2+, and Na+ are also higher than what would be expected by 
dilution of original pore water (as evidenced by the low chloride concentrations). Therefore, the 
silicate phases that dissolved must have been some combination of silica polymorphs (i.e., opal, 
cristobalite, tridymite, and quartz) and feldspar, clays, or zeolites, rather than just a pure silica 
phase. Many of the waters show a drop in Ca2+ over time, consistent with calcite precipitation as 
the water was heated further and underwent CO2 degassing. 

These water samples are considered to be representative of fracture waters produced by THC 
processes in the region around the DST. However, the borehole intervals from which the waters 
were collected are approximately 8 to 10 m in length and at times have temperatures several tens 
of degrees different at each end (Section 7.1.7). Therefore, vapor flow from the hot end to the 
cool end of an interval, accompanied by condensation and reaction with the rock lining the 
borehole, could account for some of the water found in the boreholes. Because the borehole 
surface mineralogy is not identical to the fracture surface mineralogy, the water chemistry in the 
borehole may have some differences from the chemistry of water in the fractures. Yet, because 
the rock surface in the borehole was freshly drilled, it may be more reactive with respect to 
silicate mineral reactions; hence, potentially producing higher concentrations of species making 
up the silicate mineral phases. The fresh mineral surfaces in the borehole could, therefore, result 
in dissolution rates greater than that in the fractures even though the surface area of the smooth 
borehole is likely to be less than that of the irregular fracture surface. 

Further discussion of water chemistry in the DST and comparisons to simulation results is given 
in Section 7.1.11.2. Model results are compared to a more complete data set from these intervals 
and also to borehole interval 76-3, which is above the heaters in an array closer to the area where 
the maximum drift crown temperature is reached (30 m from the bulkhead). Waters were 
collected from other borehole intervals, but on only one or two occasions, and are therefore of 
limited value for validation. However, they do provide additional information on the range of 
potential water compositions. 

7.1.11.2 Evolution in the pH of Waters from the DST 
In this section, simulations of the evolution of pH in space and time are shown, followed by 
comparisons of pH measurements of waters collected from boreholes and model results at 
specific locations. The pH of waters in the rock is a function of the coupled thermal, chemical, 
and transport processes taking place in the fractures and matrix as the system undergoes heating. 

MDL-NBS-HS-000001 REV 04 7-34 February 2005 


Drift-Scale THC Seepage Model 

The water chemistry can also be affected near rock interfaces, such as at the drift wall. Here, 
exchange of atmospheric air with gas in the rock takes place via advective transport and 
diffusion, or by simple degassing of water owing to barometric pressure changes. 

The modeled spatial distribution of pH in fracture water at various times during the heating 
phase is shown in Figure 7.1-15. The times correspond approximately to the dates when water 
was sampled from hydrology borehole intervals, which are also highlighted. Based on the 
compositions of ambient pore water ultracentrifuged from the rock in the DST block, the pH of 
waters in the region of the DST likely started out between approximately 7.8 and 8.3 
(Table 7.1-3). The initial pH of the water used in the DST THC submodel simulation is 
approximately 8.3. The most obvious effect of heating is a reduction in pH to about 7.2 in the 
condensate region, corresponding approximately to the increases in CO2 concentrations shown in 
Figure 7.1-12. As with the CO2 concentrations, the low pH zone increases in size and moves 
outward with time. Close to the dryout zone, the pH of the water increases, owing to boiling, 
degassing, and outward transport of the CO2. Another important factor affecting the pH is the 
reaction rates of certain minerals, such as feldspars, that upon dissolution consume H+, resulting 
in a rise in pH. 

There is greater uncertainty in measured pH values than in other compositional parameters. The 
pH is temperature-sensitive, and the measured values are for partially cooled samples. For 
example, over the temperature range from 60C to ambient (25C) the dissociation constant for 
water changes by approximately one order of magnitude (lowering the pH at higher temperature; 
Garrels and Christ 1965 [DIRS 144877], Table 2.8). In addition, some CO2 degassing and 
exchange with the ambient drift atmosphere occurred during sampling. Finally, as discussed in 
Section 7.1.11.1, some samples were contaminated by acid vapor released from degradation of 
the fluoroelastomer and chloroelastomer packer materials. Because of these factors, model-data 
comparisons for pH are presented here but as supporting information only and not as part of the 
planned validation strategy. Confidence in the predicted pH values is based on superior fits 
between the predicted and measured HCO3, temperature, and Pco2 data, as these parameters are 
among the dominant controls on pH. 

Model-data comparisons for fracture water pH are shown for borehole intervals 60-3, 59-2, and 
76-3 in Figure 7.1-16. The measured and simulated pH values generally fall within 
circumneutral pH range of approximately 6 to 8. At all three sampling locations, an initial 
decrease in pH was followed by an increase and the model results show similar trends at 
comparable times. Note the changes in the time-axis between Figures 7.1-16a, b, and c. 

MDL-NBS-HS-000001 REV 04 7-35 February 2005 


Drift-Scale THC Seepage Model 


Output DTN: LB0307DSTTHCR2.001 (modeled). 
Source: BSC 2004 [DIRS 169900], Table 6.3.4.1-1, water collection locations. 
NOTE: The intervals where water was sampled are more thickly shaded (in blue). Areas of zero liquid saturation


are blanked out in white. 

Figure 7.1-15. Modeled Distribution of pH in Fractures at Various Times When Water Was Sampled 
from Hydrology Borehole Intervals: (a) 6 Months, (b) 11 Months, and (c) 14 Months 

MDL-NBS-HS-000001 REV 04 7-36 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

NOTE: The ambient pore-water pH is approximately 8.3. The measured pH values are selected from Table 7.1-3, 
as representative for model-data comparison. 

Figure 7.1-16. Comparison of Measured pH in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 to the Modeled Fracture Water pH at Representative 
Model Grid Blocks 
MDL-NBS-HS-000001 REV 04 7-37 February 2005 


Drift-Scale THC Seepage Model 

7.1.11.3 Evolution of Anion and Cation Concentrations 
The effects of dilution through condensation of pure water vapor, increases in concentration 
caused by boiling, and fracture-matrix interaction can be assessed by examining the variation in 
conservative species such as chloride (Cl) and sulfate (SO42). These species are conservative 
because chloride and sulfate-bearing minerals, such as halite and gypsum (or anhydrite), are not 
present in the rock initially and precipitate under more saline conditions, expected only at the 
final drying stages of the dilute waters observed in the rock at Yucca Mountain. 

The modeled spatial variations in Cl concentrations in fracture and matrix are plotted in 
Figure 7.1-17, at times of 1 year and 4 years during the heating phase. The main effect is a 
marked decrease in Cl concentrations within fractures in the condensation and drainage zones. 
In the matrix, there is significant dilution in the condensation zones and significant increases in 
concentration near the edge of the dryout zone. 

The predicted trends in fracture-water Cl and SO42 concentrations from the simulation 
(Figures 7.1-18 and 7.1-19) are generally corroborated by the measurements, in particular the 
strong dilution trend from the initial pore water concentration. Model-data agreement could 
have been improved by changes in hydrologic properties to enhance water vapor transport out of 
the matrix and formation of dilute condensate in the fractures. However, site-average properties 
are judged to be more representative for application of the THC seepage model for the reasons 
discussed in Section 7.1.7.1. The reduction in vapor transport out of the matrix led to lower 
liquid saturations in the fractures and a weaker dilution effect on the ambient fracture pore water. 
Despite these differences, the trends are to more dilute compositions compared to the pore water, 
and most measured concentrations are within an order of magnitude of the modeled values. 
Therefore, the DST THC submodel meets the model validation requirements for chloride and 
sulfate concentrations. 

Na+ concentrations in the simulation (Figure 7.1-20) are elevated with respect to the measured 
concentrations in the 60-3 and 59-2 boreholes, but are closer to the measured values in borehole 
interval 76-3. The shape of the modeled Na+ curve shows an increase with temperature prior to 
the main condensation pulse. This increase clearly results from the higher reactivity of albite, 
which also leads to increases in pH and a reduction in the partial pressure of CO2. In the actual 
rock, it is likely that albite had undergone preferential weathering over several million years of 
infiltration and is coated by later-formed clays, silica polymorphs, and Ca-rich zeolites. 

Calcium is more sensitive to water-rock interaction than most other species because of the fast 
reaction rate of calcite, its lower solubility with increasing temperature, and the common 
occurrence of calcite in fractures. Other potential sources of Ca2+ in the rock include Ca-rich 
zeolites, such as stellerite, that are abundant in fractures. 

Ca2+ concentrations in the simulation (Figures 7.1-21a, b, and c) are slightly elevated with 
respect to measured concentrations in the 60-3 and 59-2 boreholes, but are close to the measured 
values in all the boreholes. The shape of the simulated Ca2+ history curve for 60-3 does not 
exhibit as early an initial dilution-induced drop in concentration. Instead, the reduction occurs 
later, when the strong condensation pulse is encountered and increasing temperature results in 
calcite precipitation. The Ca2+ concentration increases as boiling proceeds and the remaining 

MDL-NBS-HS-000001 REV 04 7-38 February 2005 


Drift-Scale THC Seepage Model 

water is evaporated. The model results capture the trend in the Ca2+ concentrations and are, in 
most cases, within one order of magnitude of the measured values. Therefore, the validation 
criteria for Ca2+ in the DST THC submodel have been met. 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Areas of zero liquid saturation are blanked out in white. 

Figure 7.1-17. Modeled Distribution of Cl in Fractures and Matrix at One and Four Years during the 
Heating Phase of the DST: (a) Fracture1 Year, (b) Matrix1 Year, (c) 
Fracture4 Years, and (d) Matrix4 Years 

MDL-NBS-HS-000001 REV 04 7-39 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-18. Cl Concentrations (mg/L) in Water Samples Collected from Borehole Intervals (a) 60-3, 

(b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water Cl 
MDL-NBS-HS-000001 REV 04 7-40 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-19. SO42 Concentrations (mg/L) in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water SO42 
MDL-NBS-HS-000001 REV 04 7-41 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-20. Na+ Concentrations (mg/L) in Water Samples Collected from Borehole Intervals (a) 60-3, 

(b) 59-2, and (c) 76-3 the Modeled Na+ Concentrations in Fractures 
MDL-NBS-HS-000001 REV 04 7-42 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-21. Ca2+ Concentrations (mg/L) in Water Samples Collected from Borehole Intervals (a) 60-3, 

(b) 59-2, and (c) 76-3 Compared to the Modeled Ca2+ in Fracture Water 
MDL-NBS-HS-000001 REV 04 7-43 February 2005 


Drift-Scale THC Seepage Model 

The modeled silica concentrations in fracture waters (Figures 7.1-22a, b, and c) capture the 
strong increases observed in the measured compositions, especially those seen in the borehole 
intervals overlying the heaters (59-2 and 76-3). In 76-3, the first water sample collected had a 
silica concentration of over 280 mg/L, compared to about 180 mg/L in the model simulation. 
The two waters collected later had silica concentration around 200 mg/L, which is closer to the 
model results. Except for two samples in 60-3, for which the model predicts an earlier rise in 
concentration, simulated SiO2 values are within an order of magnitude of the observed ones, and 
therefore the model results meet the validation requirements. 

The modeled concentrations of K+ (Figures 7.1-23a, b, and c), like those of Na+, increase to 
values somewhat higher than the measured concentrations. However, trends between modeled 
and measured data are similar, suggesting that a reduction in the K-feldspar reactivity and an 
increase in the dilution effect would result in a closer match to the measured concentrations. The 
modifications to hydrologic and thermodynamic (and/or kinetic) data required for such reduction 
in reactivity would be consistent with the shifts needed for both the conservative species, such as 
Cl and SO42, as well as for Na+. The lower matrix permeability used in the model induces 
slower transfer of pore water to enter into the fractures, and results in lower dilution of the 
conservative species. 

The fact that Na+ and K+ show similar trends over time is consistent with their predominance in 
either an alkali feldspar solid-solution phase, such as sanidine, and/or as closely intergrown 
exsolved phases from a precursor solid-solution alkali feldspar mineral. All model results meet 
the validation requirements (trend to higher concentrations than in the initial pore water and 
within an order-of magnitude). 

Fewer bicarbonate (HCO3) concentrations were measured in the borehole waters because of 
difficulties making the measurements in the field. Available data are plotted in Figure 7.1-24, 
along with the-modeled concentrations. Although the few measured values do not allow trends 
to be defined, model HCO3 concentrations compare well to the measured concentrations. 
Therefore, the model results for HCO3 meet the model validation criteria. 

MDL-NBS-HS-000001 REV 04 7-44 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-22. SiO2(aq) Concentrations (mg/L) in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 Compared to Modeled Fracture Water SiO2(aq) 
Concentrations 
MDL-NBS-HS-000001 REV 04 7-45 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-23. K+ Concentrations (mg/L) in Water Samples Collected from Borehole Intervals (a) 60-3, 

(b) 59-2, and (c) 76-3 Compared to Modeled Fracture Water K+ Concentrations 
MDL-NBS-HS-000001 REV 04 7-46 February 2005 


Drift-Scale THC Seepage Model 


Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-24. HCO3 Concentrations (mg/L) in Water Samples Collected from Borehole Intervals 

(a) 60-3, (b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water HCO3 
Concentrations 
MDL-NBS-HS-000001 REV 04 7-47 February 2005 


Drift-Scale THC Seepage Model 

Modeled concentrations of some additional aqueous species (Mg2+, NO3, and F) in the 
simulation are compared to measured compositions from 59-2, 60-3, and 76-3 in Figures 7.1-25 
through 7.1-27. Measured Mg2+ concentrations (Figure 7.1-25) show initial concentrations 
closer to the pore-water value of about 17 mg/L, and then a considerable drop in all the borehole 
intervals. Modeled Mg2+ concentrations show a similar pattern and are close to the measured 
concentrations. The sharp drop in the modeled concentrations is related to a combination of 
dilution from condensate and the precipitation of sepiolite (a Mg-rich sheet silicate). It is not 
clear whether precipitation of a Mg-rich phase takes place in the boiling zone in the rock, 
because the extent of dilution of Mg2+ is roughly similar to that observed for the conservative 
species, such as Cl. Some Mg2+ is likely incorporated into calcite that is precipitated as the 
condensate water above the heaters drains down and boils, although this may have a minimal 
effect on Mg2+ concentrations. The thermodynamic model for calcite does not include Mg2+, and 
therefore another Mg-bearing phase (i.e., sepiolite) must take up some of the Mg2+. Most 
samples fall within an order of magnitude of the model results, thus meeting the validation 
requirements. 

Nitrate (NO3) is included in the list of modeled species for the simulations, owing to its 
importance for the evolution of final salt compositions in potential seepage waters. Nitrate is 
highly soluble, and there are no nitrate minerals initially present in the tuff. The pore water has 
somewhat more variable nitrate concentrations compared to Cl and SO42. The greater 
variability in pore-water concentrations may be a result of biologically mediated nitrogen 
reduction, possibly after sample collection. Measured and modeled nitrate concentrations are 
shown in Figure 7.1-26. Concentrations measured in waters collected from the hydrology 
boreholes are almost all lower than those from the pore water, showing a similar pattern as Cl 
and SO42. This finding suggests that over the time scale of the experiment, nitrate acts as a 
conservative species and may not have been affected significantly by biological activity in the 
rock. The modeled concentrations capture the measured pattern of nitrate concentrations quite 
well, although the dilution effect is not as strong. This effect is similar to that seen for most 
other weakly reactive or nonreactive species. Model validation requirements for NO3 have been 
met, both in terms of the trend and range of values. 

Fluorite has been added to the initial mineral assemblage for the simulations. Fluorite is 
observed sporadically in the Yucca Mountain tuffs, and observed fluoride concentrations in pore 
water samples reflect the presence of this mineral. Most pore waters from the repository level 
are near saturation with respect to fluorite (around 4 to 5 mg/L; see Table 6.2-1). Therefore, in 
the THC seepage model, fluorite is assumed to be present in the rock mass, and fluoride 
concentration is limited by fluoride precipitation/dissolution. Fluoride is included in the THC 
seepage model because it may contribute to uniform corrosion of the titanium drip shield 
(BSC 2004 [DIRS 169845], Section 6.5.7). 

However, fluoride concentrations were lower in the water samples recovered from the DST. 
Concentrations in the initial pore waters from the DST block (HD-PERM, Table 7.1-3) were 
found to be less than 1 mg/L, much lower than the equilibrium solubility of fluorite (around 4 to 
5 mg/L at ambient temperatures). In addition, almost all waters from the hydrology boreholes in 
the DST have measured fluoride concentrations of around 1 mg/L or less, with only one sample 
at about 4 mg/L. The measured values are shown in Figure 7.1-27 for borehole intervals 59-2, 
60-3, and 76-3, compared to the model results. The modeled fluoride concentrations quickly 

MDL-NBS-HS-000001 REV 04 7-48 February 2005 


Drift-Scale THC Seepage Model 

increase from the initial concentration of less than 1 mg/L (HD-PERM, shown as PERM-1, 
PERM-2, and PERM-3 in Table 7.1-3) to several mg/L, eventually attaining much higher values 
as increasing temperatures result in much higher fluorite solubility (the rapid initial increase is 
not shown in Figure 7.1-27). The increase is also related to the fast dissolution rate of fluorite. 

The model results do not capture the trend in the fluoride concentrations because the assumption 
that fluorite is present in the rock and controls fluoride concentrations in solution through 
dissolution/precipitation (made to be consistent with the THC seepage model), while generally 
true for repository-level units, is not true for pore waters in the region of the DST. However, as 
stated in the TWP (BSC 2005 [DIRS 172761], Section 2.2.2.4.2), because this deviation can be 
readily explained in terms of simple physical and chemical processes, these data do not 
invalidate the DST THC submodel. 

Model results for aqueous Fe and Al concentrations are not compared to DST measured values in 
this report. There are several reasons for this. First, measured concentrations for these elements 
are sparse. Data for Fe and Al were either not measured or below the detection limit for more 
than half of the water samples listed in Table 7.1-3. Also, the water samples were only filtered 
through 0.45 micron filters. These are not sufficient to exclude colloidal particles, which could 
significantly contribute to the reported concentrations of a few tens of nanograms per milliliter. 
For these reasons, the potential errors in the measured Fe and Al values are large. 

For iron, most of the reported values exceed by several orders of magnitude the calculated 
solubility of crystalline Fe(III) mineral phases, and even amorphous Fe(OH)3, at the measured 
pH values (Langmuir 1997 [DIRS 100051], Figures 7.10 and 7.11). Because iron oxides 
precipitate rapidly and readily, this also suggests that the iron analyses are not reliable. 

THC DST seepage submodel predictions for Fe are also several orders of magnitude lower than 
the measured values. Iron was added to the THC seepage model to provide initial Fe 
concentrations for downstream users, and only one iron-bearing mineral, hematite, is included in 
the model. Because of the large amounts of ferrous materials in the drift, downstream models 
perform their own calculations of Fe concentrations, and make no use of the Fe values from the 
THC seepage model (BSC 2004 [169860], Section 6.6.3). Since Fe values from this report are 
not used by downstream models, and measured concentrations from the DST are sparse and 
probably unreliable, THC Fe concentrations have not been validated and are presented for 
information only. 

The values for dissolved Al that were measured in DST waters are much higher than expected 
from the model. As stated earlier, this is probably an artifact of not filtering the solutions 
appropriately to remove colloidal Al and thus miscounting colloidal aluminum mass as 
"dissolved". Large overestimates in Al concentrations due of inclusion of colloidal material are 
extensively documented throughout the literature. Although the Al concentrations reported in 
THC seepage model output files have little direct affect on downstream models, as 
concentrations are very low and do not affect the predicted major element concentrations of 
evolving brines presented in Engineered Barrier System: Physical and Chemical Environment 
(BSC 2004 [DIRS 169860]), the predicted Al values have a significant impact within the THC 
model, which may propagate indirectly to downstream models. Although Al concentrations are 
very small, they contribute to the predicted ion activity product (Q) for aluminosilicate minerals, 

MDL-NBS-HS-000001 REV 04 7-49 February 2005 


Drift-Scale THC Seepage Model 

which affects mineral dissolution/precipitation rates through the Q/K relationship described in 
Section 6.4.2. If modeled Al concentrations were too low, this would lead to lower Q values for 
aluminosilicate mineral dissolution reactions (corresponding to farther-from-equilibrium 
conditions), which would translate into higher mineral dissolution rates (and lower 
aluminosilicate precipitation rates in the converse). This would affect other dissolved 
components released from the aluminosilicates such as Ca+2, K+, Na+, and silica, and could lead 
to higher than expected dissolved concentrations of these components. This effect would in fact 
be magnified for the cation components because the Al has a larger stoichiometric coefficient 
that multiplies its effect on the rates. For this reason, it is important to validate the Al 
concentrations predicted by the THC seepage model. 

Because Al concentrations measured in the DST are likely to be in error, it is not possible to 
directly validate the Al concentrations predicted by the THC model. Predicted major element 
concentrations (Na, K, Ca, SiO2) are corroborated by DST results, providing supporting evidence 
that aluminosilicate mineral dissolution and precipitation, and hence aluminum concentrations, 
are being accurately modeled. However, pH is already assessed as a dependent variable, and 
because it is involved in all mineral dissolution/precipitation reactions, it is not possible to argue 
that Al concentrations must be accurate simply because the cation concentrations are matched 
adequately. 

The plug flow reactor experiment, described in Section 7.2 and in greater detail in Revision 2 of 
the THC model (BSC 2004 [DIRS 168848], Section 7.2), provides similar supporting data. The 
effect of water-rock interactions was greater in the plug-flow reactor experiment relative to the 
DST, and good matches between the measured and predicted values for the major components in 
the water, including Na, K, Ca, and SiO2 (Al concentrations were below detection limits) also 
support the general approach used by the THC Seepage model. However, it must be noted that 
the plug-flow reactor modeling was performed with earlier versions of the model and the 
thermodynamic database. 

The THC DST seepage submodel results do not capture the measured aluminum concentrations 
because the measured values are very small and have large uncertainties. However, matches in 
major element concentrations for the DST and plug flow reactor provide support that mineral 
dissolution and precipitation are being handled in a reasonable manner, and,, as stated in the 
TWP (BSC 2005 [DIRS 172761], Section 2.2.2.4.2), because the deviation in measured and 
predicted Al concentrations can be readily explained in terms of simple physical and chemical 
processes, these data do not invalidate the DST THC submodel. 

7.1.12 Mineralogical Changes 
As the last few sections have documented, marked changes have taken place in the water and gas 
chemistry in the DST, owing to thermal-hydrologic processes as well as mineralwatergas 
reactions. The total amount of minerals precipitated or dissolved, though, may be exceedingly 
small, even though the effect on the water composition is quite strong. The strong effect on the 
water composition is related to the waterrock ratio, which is very low in the unsaturated 
low-porosity fractured tuff. The system is also characterized by an exceedingly low percolation 
flux of only a few millimeters per year or less and, therefore, the ambient water has a long 
residence time. This section documents the predicted changes in mineralogy over the heating 

MDL-NBS-HS-000001 REV 04 7-50 February 2005 


Drift-Scale THC Seepage Model 

phase of the DST and compares the results to a few measurements made from in situ sidewall 
core samples obtained from above-boiling zones. Since the last revision of this report, a series of 
small core samples was analyzed for evidence of mineral alteration during the heating phase of 
the DST. The first set of samples was obtained in November 2000 by sidewall coring of 
fractures in chemistry boreholes 53 and 54, which were originally designed for water 
sampling. However, the SEAMIST pad system employed in those boreholes failed to provide 
uncontaminated water samples owing to the engineering materials in the boreholes and the 
unknown compositions of the pads. The collection and analyses of the rock samples are 
documented in Thermal Testing Measurements Report (BSC 2004 [DIRS 169900], Section 
6.3.4.3). Chemical analyses, identification, and description of mineral alteration products for a 
few of the samples are given in DTN: LA0201SL831225.001 [DIRS 158426]. These data 
represent observations and analyses from two locations taken about 1 m apart in an 
above-boiling region above the heaters. 

Calcite, amorphous silica, and a calcium sulfate phase (tentatively identified as gypsum) are the 
only phases in these samples identified so far as products of the processes taking place during the 
DST (DTN: LA0201SL831225.001 [DIRS 158426]). Amorphous silica was common in both 
samples, whereas calcite and gypsum were only described from the sample further into the 
above-boiling zone (the other sample was from the outer edge). Although anhydrite 
is thermodynamically more stable than gypsum under the conditions of the DST, 
gypsum was observed in analyses of borehole surfaces from the Single Heater Test 
(DTN: LA0009SL831151.001 [DIRS 153485]). On the basis of this identification, the calcium 
sulfate phase observed in the DST sidewall core samples was considered to be gypsum 
(BSC 2004 [DIRS 169900], Section 6.3.4.3). 

From these descriptions, amorphous silica was the dominant phase precipitated during boiling, 
with much lesser amounts of calcite and gypsum. Amorphous silica appears as glassy coatings 
covering larger areas of the surface, commonly in the form of thin curled sheets and fine tubules. 
Calcite typically is found as scattered, small late-stage mounds, with gypsum as very late-formed 
scattered crystals on top of other phases. Although calcite is not a major phase in the tuffs at 
Yucca Mountain, its rapid reaction rate, strong effect on pH, and ubiquitous presence in fracture 
coatings make it an important mineral phase. The actual percentage of mineral precipitates in the 
fracture system could not be determined from this type of localized analysis. Some of the silica 
coatings were approximately 10 to 20 m thick, with discrete gypsum crystals up to 80 m long. 
Given a uniform 10-m-thick layer of mineral precipitates on one side of all fractures, with a 
hypothetical range in fracture aperture of 100 to 1,000 m, the proportion of fracture volume 
filled would range from 1 to 10 percent. Because many of the coatings are much less than 10 m 
thick and do not cover all areas of every fracture, the volume filled is likely to be less than 1 
percent. 

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Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-25. Mg2+ Concentrations (mg/L) in Water Samples Collected from Borehole Intervals (a) 60-3, 

(b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water Mg2+ Concentrations 
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Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-26. NO3 Concentrations (mg/L) in Water Samples Collected from Borehole Intervals (a) 60-3, 

(b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water NO3 Concentrations 
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Source: DTN: LL020709923142.023 [DIRS 161677] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

Figure 7.1-27. F Concentrations (mg/L) in Water Samples Collected from Borehole Intervals (a) 60-3, 

(b) 59-2, and (c) 76-3 Compared to the Modeled Fracture Water F Concentrations 
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Figures 7.1-28 through 7.1-30 show the modeled distributions of calcite, amorphous silica, and 
gypsum in the DST at the time the samples were collected. The location of borehole 54 is 
plotted, as well as the sites where the mineral was observed in a sidewall core sample. The 
modeled distributions of other, much more minor phases are not shown, because it is not possible 
yet to validate their abundances. 

The modeled distribution of calcite in the simulation (Figure 7.1-28) shows a precipitation zone 
for this mineral above the heaters. The overall calcite abundance in this precipitation zone is 
larger than that observed in previous revisions of the DST THC submodel (Section 6.3) and is 
primarily a result of an improved mass-conservation formulation for mineral precipitation at the 
boiling front that is implemented in TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]). 
Another less important factor is the somewhat lower fracture porosity in the hydrologic property 
set. The location of modeled calcite precipitation matches the location of observed calcite in the 
sidewall core sample. 

Like calcite, the modeled distribution of amorphous silica in the current DST simulation 
(Figure 7.1-29) shows the presence of a precipitation zone above the heaters. This amorphous 
silica precipitation is mainly due to the combined effect of the higher aqueous silica 
concentrations in the simulated water compositions for the current DST THC submodel, which 
are much closer to measured values (Figure 7.1-22), and the improved mass conservation 
formulation in TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]). The maximum amount of 
amorphous silica precipitated is about 0.4 percent after three years and less than about 1 percent 
for the entire duration of the DST. There is also an excellent correspondence in the region of 
modeled amorphous silica precipitation and the observed amorphous silica in the sidewall core 
samples from borehole 54. Although the observations of mineral coatings on a few samples 
cannot be used to judge the total amount of mineral precipitated, the small volumes precipitated 
in the model are consistent with the generally thin coatings observed. 

Precipitation of gypsum is localized to the zones where modeled sulfate concentrations become 
very high as a result of boiling (Figure 7.1-30). The observed location of gypsum in the sidewall 
core sample is consistent with the model results that show this sample to be just within the edge 
of the modeled zone of precipitation. 

The sidewall core sample observations of significantly greater amorphous silica precipitation 
compared to calcite and gypsum, with the latter phases occurring in roughly equivalent amounts, 
are also consistent with the DST THC submodel results. Although the maximum amount of 
amorphous silica precipitated is about an order of magnitude greater than calcite, there are not 
enough samples to determine the spatial distribution of these phases and whether areas exist 
where the relative proportions differ. Given that the three observed mineral phases are in the 
locations predicted by the model simulations, the validation criteria have been met. 

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Source: DTN: LA0201SL831225.001 [DIRS 158426] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

NOTE: Chemistry borehole 54 is shown with location of observed calcite (filled circle) formed during DST. 

Figure 7.1-28. Modeled Volume Percent Change in Calcite in Fractures as of November 2000 
(35 Months of Heating) 


Source: DTN: LA0201SL831225.001 [DIRS 158426] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

NOTE: Chemistry borehole 54 is shown with location of observed amorphous silica (filled circle) formed during DST. 

Figure 7.1-29. Modeled Volume Percent Amorphous Silica in Fractures as of November 2000 
(35 Months of Heating) 

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Source: DTN: LA0201SL831225.001 [DIRS 158426] (measured). 
Output DTN: LB0307DSTTHCR2.001 (modeled). 

NOTE: Chemistry borehole 54 is shown with location of observed gypsum (filled circle) formed during DST. 

Figure 7.1-30. Modeled Volume Percent Gypsum in Fractures as of November 2000 (35 Months of 
Heating) 

7.1.13 Porosity and Permeability Changes 
The predicted amorphous silica abundances are about an order of magnitude greater in the 
current DST THC simulations than in the earlier simulations (Section 6.3). Consequently, 
fracture porosity changes are expected to be about one order of magnitude higher. Figure 7.1-31 
shows the change in fracture porosity after four years of heating in the DST. The areas above the 
Heated Drift and near the edges of the wing heaters show the greatest reduction in fracture 
porosity, reaching somewhat less than -0.8 percent. Areas of slight fracture porosity increases in 
the model results can be found in the outer condensation zones, but are not evident in the contour 
plot. 

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Output DTN: LB0307DSTTHCR2.001. 

NOTE: Negative values indicate a net porosity reduction resulting from mineral precipitation, and positive values 
indicate a net porosity increase resulting from mineral dissolution. 

Figure 7.1-31. Change in Fracture Porosity after Four Years of Heating 

As discussed in the preceding section, several factors are responsible for the modeled increased 
mineral volume changes in fractures. The increase in aqueous silica concentrations from the 
addition of opal as a starting mineral phase, changes in the thermodynamic data, a reduction of 
the initial fracture porosity to 0.0085 from 0.01, and the improved-mass balance formulation at 
the boiling front in TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]) are all contributing 
factors. 

Changes in matrix porosity after four years of heating are shown in Figure 7.1-32. Reductions in 
matrix porosity are limited solely to the dryout zone where mineral precipitation accompanied 
boiling of the in situ pore water. Increases in matrix porosity are actually greater than the 
reductions and are evident throughout the condensation zones, where imbibition of dilute water 
led to mineral dissolution. Areas of strong fracture drainage around the outer edges of the heated 
zone apparently led to the highest level of matrix imbibition and mineral dissolution in the 
matrix. The porosity increase in the matrix is, however, approximately two orders of magnitude 
less than the porosity decrease in the fractures. 

Fracture permeability changes resulting from mineral precipitation and dissolution are tied to 
changes in porosity and more directly to fracture aperture changes. Changes in fracture porosity 
of less than 1 percent of the original value would have a correspondingly small effect on fracture 
permeability. These results are consistent with the observations of minimal changes in air 
permeability during the DST, which have been attributed predominantly to water saturation 
changes (mostly in the condensation zones, where mineral precipitation is negligible) (BSC 2004 
[DIRS 169900], p. 6.3-15). 

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Thermal-hydrologic-mechanical (THM) coupled processes have also been evaluated using data 
from the DST, and are also predicted to cause changes in the repository host rock permeability 
(BSC 2004 [DIRS 169864], Section 6.9). Thermal stress tends to close fractures oriented 
radially to the opening, and open fractures oriented tangentially. For the same simulation 
conditions (equivalent thermal-hydrology), the effects from the THM simulations are centered 
closer to the drift openings than the THC effects. 


Output DTN: LB0307DSTTHCR2.001. 

NOTE: Negative values indicate a net porosity reduction resulting from mineral precipitation, and positive values 
indicate a net porosity increase resulting from mineral dissolution. 

Figure 7.1-32. Change in Matrix Porosity after Four Years of Heating 

7.1.14 Isotopic Compositions of Gases and Water: Model Corroboration Using 14C in CO2 
Gas-phase CO2 concentrations and stable isotopic ratios (d13C, d18O, dD, and 14C) were 
measured from gases pumped from hydrology boreholes (BSC 2004 [DIRS 169900], 
Table 6.3.4.2-1). For the gas-phase compositions, direct comparisons of model results have been 
made only to CO2 concentrations. Isotopic ratios of carbon (d13C), oxygen (d18O), and hydrogen 
(dD) are sensitive to fractionation effects between the liquid and gas phases as well as to 
diffusive fractionation, owing to the differing masses of the isotopes. Thus, they are useful in 
interrogating thermal-hydrologic transport processes. These fractionation effects are pronounced 
at lower temperatures, such that the relatively minor extent of water-rock interaction is strongly 
masked; thus, they are less useful for directly investigating mineral alteration during the DST. 

Relative to the stable carbon isotopes (12C and 13C), carbon-14 (14C) abundances are minimally 
affected by fractionation because their activities vary over a large range, owing to the 
geologically short time for the radioactive decay of this species (t1/2  5,000 years). The virtual 
lack of 14C in carbonate minerals at Yucca Mountain (because these materials are predominantly 

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tens of thousands to millions of years old) allows for a sensitive indicator of the dissolution of 
calcite. Fortuitously, 14C activities in the gas phase in the rock, at approximately the level of the 
Tptpmn unit, are close to 0.5 (fraction modern carbon) for several measurements done in 
different areas (BSC 2002 [DIRS 160247], Table 20 [p. I-39], Figure 44 [p. II-46]). The 
convention fraction modern carbon refers to the activity of 14C prior to atmospheric testing of 
nuclear weapons. Thus, the present-day activity of atmospheric 14C is somewhat greater than 
one, because of the addition of 14C through weapons testing. In the subsurface at Yucca 
Mountain, therefore, any addition of atmospheric CO2 to the rock gas will drive its 14C activity 
from about 0.5 towards 1.0, whereas dissolution of calcite will drive the activity to close to zero. 

Measured 14C activities in CO2 from several hydrology borehole intervals (BH74-3, BH75-3, 
BH76-3, and BH78-3) are shown in Figure 7.1-33 over much of the heating phase of the DST. 
Unfortunately, an initial, unperturbed gas sample was not analyzed; however, the earliest 
samples collected had ratios around 0.4. All of the zones show a significant drop-off over time 
to values below 0.2 and several to around 0.1 or less. By projecting the trajectories of these early 
slopes back to time zero, the zones appear to converge to an initial activity close to 0.5. Note 
that all of the samples analyzed from rock gas (over 40 measurements) had activities below 0.5. 
Two measurements of gas from the Heated Drift (taken after about 12 and 44 months) were also 
analyzed and show nearly identical values of about 0.98, which is almost entirely atmospheric in 
composition. Thus, it is clear that the gas in the Heated Drift is exchanging freely with the 
atmosphere, even though the pore water in the rock is generating abundant CO2 with low 14C 
activities. 

It can be concluded from these data that little atmospheric CO2 has affected the CO2 in the rock 
gas. Although atmospheric gas has undoubtedly been introduced into the system through 
gas-permeability testing and drilling, the relatively low CO2 concentration in atmospheric air 
( 400 ppmv) compared to the ambient rock gas ( 1,000 ppmv) and to the large concentrations 
generated during heating (> 10,000 ppmv) make contamination by atmospheric CO2 difficult. 

The strong drop-off of 14C in the gas over time is caused primarily by the dissolution of calcite 
having little or no 14C. The pore water could also be heterogeneous with respect to 14C, the 
interior of the matrix blocks having older water than the exterior. The latter explanation, 
though, is implausible, owing to the rapid diffusivity of CO2 in the gas phase in the unsaturated 
matrix and the rapid equilibration of CO2 with bicarbonate in the aqueous phase. Furthermore, 
this possibility is not supported by the gradual return in all of the measured borehole intervals to 
higher 14C activities. Finally, 14C activities as low as 0.08 have not been observed in the gas 
phase in the UZ at Yucca Mountain and would imply isolated water with ages over 15,000 years. 

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Source: BSC 2004 [DIRS 169900], Table 6.3.4.2-1. 

NOTE: Two samples collected from the Heater Drift were also analyzed. 

Figure 7.1-33. Measured Activities of 14C (Expressed as a Fraction of Modern Carbon) in CO2 from Gas 
Collected in Several Hydrology Boreholes over Most of the Heating Phase of the DST 

Another aspect to the trend in 14C activities can be found by examining their relation to the CO2 
in the gas phase. The abundance of 14C in the gas is governed by the equilibrium between 
HCO3 in the water and CO2 in the gas phase. Under closed conditions, the gas should be in 
equilibrium with the water. This is assumed in modeling the CO2 concentrations in the DST, 
where there is excellent correspondence between modeled and measured values. The overall 
trend in 14C activities seen in Figure 7.1-33 is inversely related to the changes in CO2 
concentrations observed in these intervals. The timing of the peak in CO2 concentration and the 
low in 14C activity is also very close (Figure 7.1-12). A comparison of measured CO2 (corrected 
for water-vapor removal) and 14C is shown for three borehole intervals in Figure 7.1-34. It is 
apparent that at the highest CO2 concentrations reached in each zone, the 14C activities are also 
among the lowest. 

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Source: BSC 2004 [DIRS 169900], Table 6.3.4.2-1. 

Figure 7.1-34. Measured Activities of 14C (Expressed as a Fraction of Modern Carbon) Compared to 

Measured CO2 (Corrected for Water Vapor Removal) from Gas Collected in Some 

Hydrology Boreholes over Most of the Heating Phase of the DST 

The peak in CO2 concentrations observed in the model results, and in the measured values, takes 
place at temperatures of close to 60C, well below boiling and prior to the dilution of the gas 
phase by significant quantities of water vapor. This temperature region is characterized by some 
vapor condensation (Figure 7.1-7), a lowering of pH (Figure 7.1-15), and calcite dissolution 
(Figure 7.1-28) in the model simulations. Therefore, the trend to low 14C activities in the areas 
where calcite is predicted to dissolve is consistent with the model results and with the aqueous-
and gas-phase chemical data that have been used to validate the model. 

7.1.15 Summary of Model-Data Comparisons Using the Drift Scale Test 
The foregoing discussion in Sections 7.1.9 through 7.1.14 has described the corroboration of the 
THC seepage model, through the DST THC submodel, using experimental data. The validation 
approach described in Section 7.1.7.1 is completed through comparison with thermal-hydrologic 
data (Section 7.1.9), gas-phase CO2 concentration data (Section 7.1.10), measured aqueous 
composition of sampled fracture waters (Section 7.1.11), and sampled mineralogical data 
(Section 7.1.12). Consideration is also given to fracture and matrix porosity changes, and 
changes in bulk permeability, and the corroborative indications from the DST (Section 7.1.13). 
Also, data for the 14C isotopic composition of the gas phase are interpreted to corroborate the 
simulation of reactions involving CO2. The DST is the largest, most comprehensive test of its 
kind ever performed, and the results provide extensive corroboration of the THC seepage model 
approach and predictive capability. Where model-data comparisons exhibit differences, the 
magnitude is incorporated in a general assessment of uncertainty that is propagated to TSPA-LA 
(Section 6.6). 

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7.2 SIMULATION OF THE PLUG-FLOW REACTOR EXPERIMENT 
Comparisons between a laboratory-scale tuff dissolution experiment and simulated results using 
TOUGHREACT have been used to test geochemical models that were developed for the THC 
seepage model and the DST THC submodel. These simulations were performed with previous 
revisions of TOUGHREACT, using older thermodynamic databases, and do not directly address 
validation of the current THC model. However, a brief summary is provided here because these 
simulations do provide added confidence in the conceptual model that is the basis of the THC 
seepage model. The simulations are discussed in detail in a previous revision of this report 
(BSC 2004 [DIRS 168848], Section 7.2). 

The experiment was a plug-flow reactor experiment using crushed tuff from the Tptpmn 
lithostratigraphic unit, and was performed under isothermal elevated temperature conditions 
(94C) with well-constrained initial water and rock compositions. Measured water compositions 
of samples obtained during the duration of the experiment allowed the evaluation of kinetically 
controlled reactions (e.g., mineral dissolution and precipitation) with time. A series of 
isothermal one-dimensional TOUGHREACT V2.2 (LBNL 1999 [DIRS 153219]) and V2.3 
(LBNL 2001 [DIRS 153101]) simulations were performed to model this dissolution. Measured 
and predicted effluent concentrations were compared to evaluate the conceptual models 
developed for the THC seepage model. 

Although some simulations exhibited closer matches than others, depending on the estimated 
mineral surface areas and the thermodynamic database used, predicted concentrations for the 
major aqueous species in the effluent generally matched the measured values well, usually within 
a factor of 3, and always within an order of magnitude. Measured pH values were not modeled 
well. The discrepancy in pH can be attributed to the exposure of the plug-flow effluent to air and 
the subsequent cooling and degassing of the outflow solution before analysis. The outflow pH 
values matched the simulated results closely after they had been corrected for these processes. 

Two important conclusions can be derived from the tuff dissolution experiment and simulations, 
even though they do not serve to directly validate the current THC seepage model: 

 A good match was obtained between the water compositions for the observed and 
simulated plug-flow experiment, providing additional confidence in the THC seepage 
model conceptualization. 
 Differences between the modeled and measured values in pH result from cooling and 
degassing of the experimental samples after exiting the tuff dissolution column. This 
illustrates the potential for fluid-chemistry changes during sample collection for the DST 
experiment, and supports the conclusion (Section 7.1.11.2) that the poor fits between the 
measured DST pH values and those predicted by the DST THC submodel are due to 
cooling, condensation, and degassing during sample collection. 
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7.3 SIMULATION OF THE FRACTURE SEALING EXPERIMENT 
A laboratory-scale fracture-sealing experiment has also been simulated using TOUGHREACT. 
As with the plug-reactor experiment, these simulations were performed with previous versions of 
TOUGHREACT, using older thermodynamic databases. Thus, they do not directly address 
validation of the current THC model, but provide added confidence in the conceptual model 
basis and parameterization. The simulations are discussed in detail in the previous revision of 
this report (BSC 2004 [DIRS 168848], Section 7.3) and are summarized here. 

The fracture sealing experiment was designed to emulate and evaluate the effects of condensate 
reflux through a fracture network and into a boiling environment. Two saw-cut blocks of welded 
rhyolite ash-flow tuff (from unit Tptpmn in Alcove 6 of the ESF), were separated by gold shims 
to create a vertical planar fracture. The outer surfaces of the blocks were sealed and the 
temperature gradient of 80C at the top and 130C at the bottom was established with heaters. 
Effluent from the plug-flow reactor (Section 7.2) was directed into the top of the fracture and 
vapor was removed from the bottom. Fracture sealing occurred after five days. After cooling, 
the fracture was opened and examined to determine the location and nature of secondary mineral 
formation. The precipitate (identified as mainly amorphous silica from SEM X-ray analyses and 
visual and petrographic examination) was deposited almost exclusively in zones where the 
temperature had exceeded 100C. 

TOUGHREACT V2.4 (LBNL 2001 [DIRS 160880]) simulations were performed to model 
fracture sealing, using a mesh configuration with dimensions (in one dimension) identical to 
those of the tuff fracture experiment. The initial rock mineralogy was considered to be the same 
as that used in the plug-flow experiment. Different simulations were run for a period of 5.8 days, 
with amorphous silica controlled by either equilibrium or kinetic conditions. 

The simulation results indicated the formation of a nearly isothermal two-phase region with an 
overlying water column below and a vapor zone below. The precipitation of amorphous silica at 
the base of the two-phase zone accounted for all of the porosity and permeability reduction in the 
fracture system. The base of the boiling zone (and region of silica precipitation) shifted 
downward over time due to a gradual pressure buildup, caused by the reduction of the fracture 
aperture at the top of the fracture system. The thickness and location of the silica precipitation 
zone were different in the kinetic and equilibrium simulations. The simulations conducted using 
equilibrium precipitation and dissolution for amorphous silica showed the effects of both 
precipitation and dissolution, as the trailing (upper) edge of the silica front underwent dissolution 
with time. In the kinetic simulations, almost no dissolution of precipitated amorphous silica 
occurred, resulting in a thicker band of silica that occluded less of the fracture aperture. 
Significant permeability reductions occurred within five days after initiation of fluid flow for 
both the experiment and simulations. The presence of silica precipitate throughout the boiling 
zone in the experimental fracture system suggests that the kinetic simulation, which retains 
early-formed precipitate, is a more appropriate match to the experimental results. 

These simulations provide confidence in the geochemical model developed for the THC seepage 
model and the DST THC submodel presented in this report. Both of the simulations accurately 
predicted the distribution and type of secondary mineral precipitation. Amorphous silica was the 
dominant secondary mineral phase and simulated amorphous silica precipitation was restricted to 

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the lower portion of the two-phase zone at temperatures of around 105C to 109C, consistent 
with the observed pattern of mineralization along the fracture surface in the experiment. The 
predicted total fracture-porosity-reduction values resulting from silica precipitation in the 
equilibrium and kinetic simulations were 2.2 and 3.9 percent, respectively, comparable to the 
estimated values of 0.9 to 3.6 percent for the experiment. The experimentally determined 
distribution of silica precipitation was predicted more accurately by the simulation assuming 
kinetic control of silica precipitation, providing support for the use of this approach in the THC 
seepage model and the DST THC submodel. 

7.4 VALIDATION SUMMARY 
The THC seepage model has been validated by applying acceptance criteria based on an 
evaluation of the models relative importance to the potential performance of the repository 
system. All validation requirements defined in the TWP (BSC 2005 [DIRS 172761], Section 
2.2.2) have been fulfilled, including corroboration of model results with experimental data and 
additional confidence building by publication in a refereed professional journal (Section 7). 
Activities requirements for confidence building during model development have also been 
satisfied. The model development activities and post-development validation activities described 
establish the scientific bases for the drift-scale THC seepage model. Based on this, the 
drift-scale THC seepage model is considered to be sufficiently accurate and adequate for the 
intended purpose and to the level of confidence required by the models relative importance to 
the potential performance of the repository system. No future validation activities are required 
for the drift-scale THC seepage model. 

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INTENTIONALLY LEFT BLANK 


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8. CONCLUSIONS 
This report documents the THC seepage model (Sections 4 and 6), the Drift Scale Test (DST) 
THC submodel (Section 7.1), and experimental studies to validate various aspects of the models 
(Sections 7.2 and 7.3). The models describe coupled THC processes at the drift scale to assess 

(1) the chemistry of water and gas potentially entering drifts and (2) changes in permeability and 
flow around drifts. The THC seepage model is used primarily to predict the composition of 
waters and gases around and potentially seeping into waste emplacement drifts and the effect of 
waterrock interaction on flow. Key findings of this model are summarized in Figure 8-1. The 
DST THC submodel is used primarily to validate the THC seepage model. 
The underlying conceptual and mathematical models (Sections 6.1 to 6.4) provide the basis for 
modeling the thermal and hydrologic effects of the relevant mineralwatergas reactions and 
transport processes in the host rock for 100,000 years, a time period sufficient to capture the 
entire duration of the thermal pulse and the return to ambient conditions. Confirmatory actions 
include evaluating the sensitivity of the models to different input parameters and 
conceptualizations. Validation (Section 7) is accomplished through comparison of simulation 
results to data collected from the DST and to laboratory experiments that explore various specific 
aspects of the modeling approach. Additional confidence building is also accomplished through 
publication in refereed journals (Spycher et al. 2003 [DIRS 162121]; Dobson et al. 2003 
[DIRS 165949]). Model results have been submitted to the Technical Data Management System 
(TDMS) as output under DTNs listed in Sections 9.4 and 8.5, and Appendix G of this report. 
Applicable acceptance criteria from the YMRP addressed by this report are discussed in Section 

4.2 with pointers referring to sections of this report where these criteria are addressed. The 
barrier capabilities of the natural system, including host rocks and the capillary barrier effects of 
drift openings, are considered throughout this report (Sections 6.5.2 and 6.5.5.1). Potential 
barrier effects from mineral precipitation during the thermal period are also considered 
(Section 6.5.5.3). 
8.1 MODELED COUPLED PROCESSES AND UNCERTAINTY 
Simulations of THC processes include coupling among heat, water, and vapor flow; aqueous and 
gaseous species transport; kinetic and equilibrium mineralwater reactions; and feedback of 
mineral precipitationdissolution on porosity, permeability, and capillary pressure for a 
dual-permeability (fracture-matrix) system. Treatment of CO2 included gaswater equilibration, 
gas species diffusion, and advection. Data are incorporated from the calibrated 
thermal-hydrologic property sets, the three-dimensional mineralogical model, the unsaturated 
zone flow and transport model, thermal test geochemical data (fracture and matrix mineralogy, 
aqueous geochemistry, and gas chemistry), thermodynamic data (minerals, gases, and aqueous 
species), kinetic data for mineralwater reactions, and transport (diffusion coefficient) data 
(Section 4.1). The THC seepage model and the DST THC submodel include a wide range of 
major and minor aqueous species and minerals (primary and potential secondary phases). The 



following primary aqueous species are considered: H+, Ca2+, Mg2+, Na+, K+, SiO2(aq), AlO2 , 
HFeO2(aq), SO42, HCO3, Cl, NO3, and F. Minerals include several silica phases 
(a-cristobalite, quartz, tridymite, amorphous silica, and opal-CT), calcite, feldspars, smectites, 
illite, kaolinite, sepiolite, zeolites, fluorite, hematite, goethite, gypsum, and volcanic (rhyolitic) 
glass. In addition to the calibration of the hydrologic properties, some thermodynamic and 

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kinetic data have been revised (within their ranges of uncertainty) to yield model results for the 
ambient system that are consistent with measured pore water compositions over long simulation 
times. 

Many sources of uncertainty exist in modeling coupled THC processes (Section 6.6), because of 
the number of parameters needed to describe the natural system as described in Sections 4, 6, 
and 7. Model validation provides a better test of whether the system can be described 
sufficiently well for the intended purposes of the model. Validation is accomplished through 
analyses of the DST, supplemented by analyses of laboratory plug-flow reactor experiments, and 
fracture sealing experiments performed under temperatures, pressures, and chemical 
compositions corresponding to the range expected for the repository thermal loading conditions 
and drift design. As summarized further in this section, results of DST THC simulations 
captured the important changes in pH, aqueous species concentrations, gas-phase CO2 
concentrations, and mineral deposition at specific locations over time. This provides confidence 
in the modeling capability to predict trends of spatial and temporal variations in water and gas 
chemistry around emplacement drifts. Although the duration of the DST heating phase is 
approximately four years, the DST results exhibit the same processes known to control water 
chemistry, gas compositions, and permeability over longer time periods. 

Several sensitivity analyses have been performed in the development of the present version, and 
previous versions, of this report. The results of these analyses contribute significantly to 
confidence that the important uncertainties have been addressed in the THC seepage model 
implementation for TSPA-LA. These sensitivity analyses address the following major issues: 

1. Different repository host-rock geologic units (Tptpmn and Tptpll) 
2. Alternative geochemical systems (base case and extended case, additional minerals 
and chemical components) 
3. Alternative thermodynamic data sets (different equilibrium constants for key minerals) 
4. Different treatments of mineralwater reactions (different kinetic rate constants and 
reactive surface areas; equilibrium vs. kinetic reactions) 
5. Spatial heterogeneity in fracture permeability 
6. Different infiltration rates and effects of climate change 
7. Alternative water vapor pressure models 
8. Alternative initial water compositions 
9. Different effective CO2 diffusivities 
10. Alternative drift-wall conceptualizations (open vs. closed to liquid flow). 
These THC seepage model simulations covered a wide range of the most important uncertainties, 
and the range of results obtained is represented by the principal source of uncertainty, which is 
the natural variability in input water composition. In the spread of simulation results 
corresponding to the range of input water composition, the uncertainties in predicted 

MDL-NBS-HS-000001 REV 04 8-2 February 2005 


Drift-Scale THC Seepage Model 

concentrations of aqueous species and of CO2 gas are estimated to approximately one order of 
magnitude, or less (Section 6.6.2). 

8.2 THC SEEPAGE MODEL RESULTS 
The THC seepage model is designed to represent waste package heating over time, changes in 
heat load caused by ventilation, the effective heat transfer within the drift, and THC processes in 
the unsaturated zone around waste emplacement drifts. Simulations considered an initial heat 
load of 1.45 kW/m, including a preclosure period of 50 years using a ventilation efficiency of 

86.3 percent. Model results predict the chemistry of matrix and fracture water at various 
locations around a drift, the times of rewetting around the drifts, and the net fluxes of water and 
gas near and across the drift wall for a period of 100,000 years. 
The scope of this report includes essentially one design heat load, resulting in temperatures near 
emplacement drifts that exceed the boiling point of water for approximately 1,500 years after 
repository closure. Temperature is an important parameter because it affects the extent of 
water-rock-gas interaction taking place around proposed emplacement drifts. 

The predicted extent of the dryout zone and the time of rewetting vary with different infiltration 
rates and water-vapor pressure models considered in this report. Depending on the modeled 
scenario, the maximum extent of the dryout zone in fractures is predicted to be between 6 m and 
10 m above drift center, and the predicted time of fracture rewetting at the drift crown varied 
between 1,200 and 2,000 years in most cases. In one case neglecting the effect of vapor-pressure 
lowering caused by capillary suction, rewetting is predicted to occur much later (i.e., between 
12,000 and 20,000 years). 

MDL-NBS-HS-000001 REV 04 8-3 February 2005 


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Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 8-4 February 2005 

General Findings : Potential seepage waters (i.e., water in fractures having higher liquid saturation) are relatively dilute and in the near-neutral to 
moderately alkaline pH range of 7 to 9. Elevated concentrations of aqueous species in the 1,000-10,000 ppm range are predicted for a short period at 
the onset of rewetting, in regions exhibiting very low liquid fluxes. General trends of gas phase CO2 and aqueous species concentrations do not 
differ significantly for any of the scenarios considered, with maximum gas phase CO2 concentrations < 12,000 ppmv. Gas phase CO2 
concentrations around the drift are higher than ambient values during the period when the boiling front is receding. The uncertainty in predicted 
major cation and anion concentrations and gas phase CO2 concentration is estimated to be about an order of magnitude or less. 
compositions: Trends in composition 
through time are similar for all waters. 
Some waters lead to more mineral Sensitivity to infiltration rates : In the 6Other 
sensitivities : Vapor pressure lowering precipitation 
than others (5 to 7% 25 mm/yr range, the effect of infiltration minimal effect on long-term water compositions, 
reduction in fracture porosity). The rate on water composition is less than but results in a much shorter dryout period. Open 
relative spread in model results is that of differing input water chemistry. drift wall - CO2 concentrations in the drift rise 
generally smaller than the relative spread The zone of reduced porosity migrates above ambient levels at an earlier time. Higher 
of input water compositions, and larger closer to the drift at higher infiltration CO2 effective diffusivity - increased CO 2 
than the spread related to infiltration rate. rates, but the maximum porosity concentrations in drift during the dryout period. 
reduction remains similar. 

1 The heterogeneous case was run using REV01 hydrological properties and with TOUGHREACT V2.3 [DIRS 153101]. The use of REV02 properties and 
TOUGHREACT V3.0 [DIRS 161256] resulted in greater reductions in porosity and permeability for the homogeneous permeability case, which would 
also be expected for the heterogeneous case. 

Effect of host rock and stratigraphic 
column: Minor effect on predicted trends in 
major cations and anions. The initial 
relative spread in concentrations between 
models is maintained though time. Higher 
T in Tptpll (~15% higher Tmax) leads to THC Seepage Model slightly greater evaporative concentration. 
Addition of fluorite to host rock results in 

Rev04 

elevated F concentrations (~20-40 ppm). 
Minerals precipitated in the Tptpmn and 
Tptpll models are similar. Greater fracture 
porosity reduction in the Tptpll by several 
% and increased water diversion are not 
related to differences in the host rock. 
(REV01) 

Sensitivity to input pore water 

Effect of fracture permeability heterogeneity: 
Insignificant effect on predicted fracture water 
compositions at a large scale (> 10 m). At a 
small scale (~ 1m), flow focusing and 
heterogeneous liquid saturations yield 
differences in concentrations resulting from 
changes in dilution/evaporation and effective 
mineral surface areas. Reductions in porosity 
(~5 %) and permeability (25 %) are greater than 
for the homogeneous permeability case 1 (REV01) 
Effect of model revisions from REV01 to 
REV02: Enhanced mineral precipitation at the 
boiling front results in a reduction in fracture 
permeability of 1 to 2 orders-of-magnitude. 
Region of reduced permeability above the drift 
results in increased water diversion. 
Figure 8-1. Key Findings of the THC Seepage Model 


Drift-Scale THC Seepage Model 

In all of the model cases, including the five THC runs developed for TSPA-LA using 
representative input water compositions, relatively dilute and near-neutral to moderately alkaline 
water compositions are predicted in fractures around drifts, with circumneutral pH values and 
gas-phase CO2 concentrations less than 12,000 ppmv. General trends of CO2 gas and aqueous 
species concentrations around the drifts do not differ significantly for any of the cases. The 
simulations also exhibit increased CO2 gas concentration around the drifts during rewetting, 
relative to ambient values. Elevated concentrations of aqueous species relative to background 
values are predicted to occur temporarily at the time of rewetting in fractures, though at low 
liquid saturations. 

Similar trends in water and gas compositions are predicted for modeled cases with heat loading 
in the Tptpmn and in the Tptpll geologic units. At any point in time, the spread in predicted 
water compositions above the drift, including alternative model cases and the five THC runs 
developed for TSPA-LA using representative input water compositions, is generally one order of 
magnitude or less (Section 6.6.2). This spread is potentially significant for chemical species for 
which small variations in initial concentration could shift the brine type that forms on 
evaporative concentration. Recognizing this possibility, simulations prepared to support 
TSPA-LA use a range of input water compositions to yield predicted seepage waters that evolve 
toward a representative range of possible end-brine types (Section 6.2.2.1). 

In general, when modeling a geochemical system without aluminum silicate minerals and glass, 
development of the THC seepage model through multiple revisions of this report has shown that 
predicted pH values are somewhat lower and CO2 concentrations higher than in simulations that 
include these phases. Therefore, the incorporation of mineralwater reactions involving clays 
and zeolite minerals is potentially important. Aqueous sodium concentrations are predicted to 
increase by a factor of approximately four in 100,000 years (from the dissolution of mostly albite 
and glass), which is greater than the typical concentrations in the natural system. In this respect, 
simulations including aluminosilicate minerals could provide an upper limit on effects of 
water-rock-gas interactions around waste emplacement drifts. 

The predicted magnitude of fracture porosity change caused by waterrock interaction around 
waste emplacement drifts depends on the initial fracture porosity (with the largest relative 
change for the smallest porosity), and results in large part from mineral precipitation directly at 
the boiling front above the drift opening. Simulations carried out for the THC seepage model 
(Section 6.5) use a more representative treatment of mineral precipitation at the boiling front 
than earlier versions. Accordingly, the THC seepage model simulations predict a significant 
effect of watergasrock interactions on flow patterns around the drift. This zone has a fracture 
permeability that is one to two orders of magnitude lower than in the surrounding rock fractures, 
deflecting some of the percolating water around the drift and significantly extending the shadow 
zone below the drift. Because the silica solubility decreases with declining temperature, the 
amorphous silica precipitated in fractures does not dissolve significantly into percolating water 
over 100,000 years. 

Sensitivity studies documented previously are discussed in this report. Steady-state (ambient 
temperature), TH, and THC simulations have been performed using three heterogeneous fracture 
permeability field realizations. Heterogeneity in fracture permeability can have various effects 
on thermohydrology, including flow focusing and irregularities in the isotherms and liquid 

MDL-NBS-HS-000001 REV 04 8-5 February 2005 


Drift-Scale THC Seepage Model 

saturations. Areas of highest initial liquid saturation, also having lower permeability and 
generally residing above the drift, tend to show the greatest reduction in fracture permeability as 
a result of mineral precipitation. The effect of this localized permeability reduction tends to 
cause some additional flow focusing, but the permeability changes (up to 25 percent) are much 
less than the initial range in permeability. Spatial differences in water chemistry are not affected 
significantly by permeability heterogeneities, and because of the strong control of the mineral 
assemblage on water chemistry (and not the mineral proportions), this would also be expected to 
be the case if the properties used in the current THC seepage model are used. 

8.3 DST THC SUBMODEL RESULTS (VALIDATION) 
Validation of the modeling approach and parameters used in the THC seepage model is 
accomplished using a derivative submodel adapted for direct comparison to observations of gas 
composition, water chemistry, and mineral deposition in the Drift Scale Test (DST). The DST 
THC submodel has been developed for this purpose, and is used for sensitivity studies in 
addition to direct comparisons of model output to measured data. 

Comparisons between observed and modeled aqueous pH and CO2 concentrations in the gas 
phase indicate that a limited set of aqueous species, minerals (calcite, silica phases, fluorite, and 
gypsum), and gases (H2O, air, and CO2) (base case) could describe the general evolution of DST 
waters with respect to pH, CO2, and conservative anions. A more complete geochemical system 
(extended case), including a wide range of aluminosilicates (such as feldspars, clays and 
zeolites), yielded modeled aqueous silica concentrations closer to those observed, plus 
information on additional species (i.e., Mg2+, Al3+, and Fe3+). However, predicted pH values for 
the extended system are slightly higher than those observed, and gas-phase CO2 concentrations 
are slightly lower than the measured values. 

In particular, simulation results compared to measured gas-phase CO2 concentrations and the 
chemistry of waters collected from hydrology boreholes indicate that the model captures the 
general trend in concentrations in the borehole intervals where comparisons have been made. 
Predicted locations and relative abundances of secondary minerals are consistent with in situ 
sidewall core samples retrieved from zones that had undergone boiling. The most important 
mineral phase is amorphous silica followed by significantly lesser amounts of calcite and 
gypsum. Analyses of 14C concentrations in CO2 also corroborate the model results because of 
their sensitivity to calcite dissolution and drift air contamination. 

The evidence based on field and laboratory measurements demonstrates that model validation 
criteria have been met for CO2 concentrations in gas, for several aqueous species concentrations, 
and for mineral precipitation in fractures. Although some disagreements between modeled and 
measured values exist, they could be attributed to sampling interferences or to the selection of a 
phase (e.g., fluorite) in the mineral assemblage (because minor amounts of fluorite are known to 
exist in the Tptpll unit). These differences serve to quantify the sensitivity of the model to the 
associated input parameters. Some heterogeneities in the measured data could not be matched by 
the model results, which is not unexpected for simulation of such an extensive field test. The 
results achieved provide confidence in the modeling approach and the use of average properties 
for the purpose of the THC seepage model, which is to represent the chemical composition of 

MDL-NBS-HS-000001 REV 04 8-6 February 2005 


Drift-Scale THC Seepage Model 

water that could potentially seep into emplacement drifts, and the composition of the gas phase 
in the drifts. 

Confidence in various aspects of the modeling approach and input data used in the THC seepage 
model is also based on a comparison of modeled and measured water compositions from a 
laboratory plug-flow dissolution experiment using volcanic tuff from the Tptpmn unit at Yucca 
Mountain. The model simulations captured the magnitude and change in aqueous species 
concentrations measured during this experiment at elevated temperatures, and thus the validation 
criteria were met. A fracture sealing laboratory experiment has also been simulated, with the 
location and amounts of amorphous silica precipitated closely comparable to that observed, also 
supporting validation. 

Although not required for the planned validation strategy, the THC responses of the Yucca 
Mountain Drift Scale Test have been independently analyzed by the participants of the 
DECOVALEX III project, an international research project to develop coupled models and their 
validation against experiments. The outcome of the analyses by the DECOVALEX participants, 
generally corroborative of the contents of this report, has been presented in the GeoProc2003 
conference held in Stockholm, Sweden, and will be published in a special issue of the 
International Journal of Rock Mechanics. 

Based on the results presented in Section 7 and summarized here, the drift scale THC seepage 
model is considered to be sufficiently accurate and adequate for the intended purpose and to the 
level of confidence required by the models relative importance to the performance of the 
repository system. 

8.4 UNCERTAINTIES AND RESTRICTIONS FOR DOWNSTREAM USE 
Section 1.3 states the general model limitations. Potential uncertainties affecting model results 
are discussed in a qualitative manner in Section 6.6.1, and addressed more quantitatively in 
Section 6.6.2. Various alternative conceptualizations and ranges of input data are considered 
(summarized in Section 8.1; see also Table 6-1). In addition, confidence in the model results is 
obtained by comparing model results to experimental data from the DST (Section 7.1; 
summarized in Section 8.3) and other laboratory experiments (Sections 7.2 and 7.3). Much of 
the spread in the output compositions from the THC seepage model simulations is caused by the 
natural variability of input water compositions. This spread is up to approximately one order of 
magnitude and in many cases less (Section 6.6.2). The input data and model conceptualizations 
considered in this study all yield similar trends in modeled aqueous species and gas-phase CO2 
concentrations over time. 

8.5 DATA TRACKING NUMBERS FOR DATA GENERATED IN THIS REPORT 
Table 8.5-1 lists the DTNs for data generated in this report, which included the following: 

 DTNs containing THC seepage model simulations that provide feeds to downstream 
models and indirectly to TSPA-LA 
 DTNs documenting model validation test cases discussed in Section 7 of this document. 
MDL-NBS-HS-000001 REV 04 8-7 February 2005 


Drift-Scale THC Seepage Model 
The files contained in each DTN are described in detail in Appendix G. 


Table 8.5-1. Drift-Scale THC Seepage Model Output DTNs 

Data Tracking Number Location In Text Description of TSPA Parameters 
THC Seepage Model Output DTNs 
LB0302DSCPTHCS.001 Section 6.4 THC Seepage Model Simulations. 
LB0302DSCPTHCS.002 Section 6.4 THC Seepage Model Data Summary. This DTN 
provides direct feeds to downstream models that 
eventually feed TSPA-LA calculations. These feeds 
are in the form of spatially and temporally abstracted 
water and gas chemical compositions. 
LB0404DSTTHCR2.001 Section 6.5.5.5 THC Seepage Model Simulations. Rerun of 
simulations using revised porosity and thermal property 
data. 
LB0404DSTTHCR2.002 Section 6.5.5.5 THC Seepage Model Simulations. Rerun of 
simulations using revised porosity and thermal property 
data. 
Output DTNs for Model Validation Simulations 
LB0307DSTTHCR2.001 Section 7.1 DST THC Submodel: Simulations. 
LB0307DSTTHCR2.002 Section 7.1 DST THC Submodel: Data Summary. 

MDL-NBS-HS-000001 REV 04 8-8 February 2005 


Drift-Scale THC Seepage Model 

9. INPUTS AND REFERENCES 
The following is a list of the references cited in this document. Column 2 represents the unique 
six digit numerical identifier (DIRS number), which is placed in the text following the reference 
callout (e.g., BSC 2005 [DIRS 172761]). The purpose of these numbers is to assist the reader in 
locating a specific reference. In the reference list below, sources are sorted alphabetically by 
author. Multiple sources by the same author are sorted by date and, if the date is the same, 
alphabetically by title. 

9.1 DOCUMENTS CITED 
Arnrsson, S. and Stefnsson, A. 1999. Assessment of Feldspar Solubility 153329
Constants in Water in the Range 0 to 350C at Vapor Saturation Pressures. 
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University, Kline Geology Laboratory. TIC: 249258. 


Barnes, H.L. 1971. Investigations in Hydrothermal Sulfide Systems. Chapter 160181
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Bear, J. 1988. Dynamics of Fluids in Porous Media. New York, New York: 101379
Dover Publications. TIC: 217568. 


Bird, R.B.; Stewart, W.E.; and Lightfoot, E.N. 1960. Transport Phenomena. 103524
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Blum, A.E. and Stillings, L.L. 1995. Feldspar Dissolution Kinetics. Chapter 7 126590
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S.L., eds. Reviews in Mineralogy Volume 31. Washington, D.C.: Mineralogical 
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Brady, P.V. and Walther, J.V. 1989. Controls on Silicate Dissolution Rates in 110748
Neutral and Basic pH Solutions at 25C. Geochimica et Cosmochimica Acta, 53, 
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Bruno, J.; Stumm, W.; Wersin, P.; and Brandberg, F. 1992. On the Influence of 160189
Carbonate in Mineral Dissolution: I. The Thermodynamics and Kinetics of 
Hematite Dissolution in Bicarbonate Solutions at T = 25C. Geochimica et 
Cosmochimica Acta, 56, (3), 1139-1147. New York, New York: Pergamon Press. 
TIC: 253396. 


BSC (Bechtel SAIC Company) 2001. FY 01 Supplemental Science and 
Performance Analyses, Volume 1: Scientific Bases and Analyses. 
TDR-MGR-MD-000007 REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: MOL.20010801.0404; MOL.20010712.0062; 
MOL.20010815.0001. 


MDL-NBS-HS-000001 REV 04 9-1 February 2005 


Drift-Scale THC Seepage Model 

BSC 2001. Multiscale Thermohydrologic Model. ANL-EBS-MD-000049 158204 
REV 00 ICN 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20020123.0279. 


BSC 2001. Repository Multiple Waste Package Thermal Calculation. 

156276 
CAL-WIS-TH-000010 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20010814.0330. 

BSC 2002. Analysis of Geochemical Data for the Unsaturated Zone. 

160247 
ANL-NBS-HS-000017 REV 00 ICN 02. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: MOL.20020314.0051. 

BSC 2002. Invert Effective Thermal Conductivity Calculation. 159906 
000-00C-WIS0-00100-000-00A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20020828.0178. 

BSC 2002. Repository Design, Repository/PA IED Subsurface Facilities 159527
Plan Sht. 1 of 5, Sht. 2 of 5, Sht. 3 of 5, Sht. 4 of 5, and Sht. 5 of 5. 
DWG-MGR-MD-000003 REV A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20020601.0194. 


BSC 2002. Users Manual (UM) for TOUGHREACT V3.0. 10396-UM-3.0-00. 164454
Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20030411.0090. 


BSC 2002. Ventilation Model. ANL-EBS-MD-000030 REV 01 ICN 01. Las 160975
Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20021106.0055. 


BSC 2003. Advection Versus Diffusion in the Invert. ANL-EBS-MD-000063 170881
REV 00. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040217.0004. 


BSC 2003. Repository Design Project, Repository/PA IED Emplacement Drift 162444
Committed Materials. 800-IED-EBS0-00301-000-00A. Las Vegas, Nevada: 
Bechtel SAIC Company. ACC: ENG.20030311.0022. 


BSC 2004. Abstraction of Drift-Scale Coupled Processes. MDL-NBS-HS-000018 169617
REV 00 Errata 002. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20031223.0004; DOC.20040223.0003; DOC.20040512.0001. 


BSC 2004. Abstraction of Drift Seepage. MDL-NBS-HS-000019 REV 01. Las 169131
Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20041103.0003. 


BSC 2004. Calibrated Properties Model. MDL-NBS-HS-000003 REV 02. Las 169857
Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20041006.0004. 


MDL-NBS-HS-000001 REV 04 9-2 February 2005 


Drift-Scale THC Seepage Model 

BSC 2004. D&E / PA/C IED Emplacement Drift Configuration and Environment. 168489
800-IED-MGR0-00201-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040326.0001. 


BSC 2004. D&E / PA/C IED Interlocking Drip Shield and Emplacement Pallet. 169220
800-IED-WIS0-00401-000-00D. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040503.0018. 


BSC 2004. D&E / PA/C IED Typical Waste Package Components Assembly. 169480
800-IED-WIS0-00201-000-00E. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040517.0007. 


BSC 2004. D&E / PA/C IED Typical Waste Package Components Assembly. 167369
800-IED-WIS0-00204-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040202.0012. 


BSC 2004. D&E / PA/C IED Typical Waste Package Components Assembly. 169990
800-IED-WIS0-00205-000-00D. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040518.0001. 


BSC 2004. Design and Engineering, Drip Shield Plate - 1. 168283
000-M00-SSE0-00601-000-00A. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: ENG.20040310.0027. 


BSC 2004. Development of Numerical Grids for UZ Flow and Transport 169855
Modeling. ANL-NBS-HS-000015 REV 02. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: DOC.20040901.0001. 


BSC 2004. Drift Scale THM Model. MDL-NBS-HS-000017 REV 01. Las 169864
Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20041012.0001. 


BSC 2004. Drift-Scale Coupled Processes (DST and TH Seepage) Models. 170338
MDL-NBS-HS-000015 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040930.0003. 


BSC 2004. Drift-Scale Coupled Processes (DST and THC Seepage) Models. 168848 
MDL-NBS-HS-000001 REV 02 Errata 002. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: DOC.20030804.0004; DOC.20040219.0002; 
DOC.20040405.0005. 


BSC 2004. Engineered Barrier System: Physical and Chemical Environment. 169860
ANL-EBS-MD-000033 REV 03. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20041201.0001. 


BSC 2004. General Corrosion and Localized Corrosion of the Drip Shield. 169845
ANL-EBS-MD-000004 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040921.0002. 


MDL-NBS-HS-000001 REV 04 9-3 February 2005 


Drift-Scale THC Seepage Model 

BSC 2004. Geologic Framework Model (GFM2000). MDL-NBS-GS-000002 170029
REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040827.0008. 


BSC 2004. In-Drift Precipitates/Salts Model. ANL-EBS-MD-000045 REV 02. 169863
Las Vegas, Nevada: Bechtel SAIC Company. ACC: 20041111.0002. 


BSC 2004. Mountain-Scale Coupled Processes (TH/THC/THM) Models. 

169866 
MDL-NBS-HS-000007 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20041108.0001. 

BSC 2004. Multiscale Thermohydrologic Model. ANL-EBS-MD-000049 169565
REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20041014.0008. 


BSC 2004. Post-Processing Analysis for THC Seepage. ANL-NBS-HS-000045 169858
REV 00. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040929.0002. 


BSC 2004. Repository Subsurface Emplacement Drifts Steel Invert Structure Sect. 169776
& Committed Materials. 800-SS0-SSE0-00102-000-00B. Las Vegas, Nevada: 
Bechtel SAIC Company. ACC: ENG.20040520.0005. 


BSC 2004. Simulation of Net Infiltration for Present-Day and Potential Future 170007
Climates. MDL-NBS-HS-000023 REV 00. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: DOC.20041109.0004. 


BSC 2004. Thermal Conductivity of Non-Repository Lithostratigraphic Layers. 170033
MDL-NBS-GS-000006 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20041022.0004. 


BSC 2004. Thermal Conductivity of the Potential Repository Horizon. 169854
MDL-NBS-GS-000005 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040928.0006. 


BSC 2004. Thermal Testing Measurements Report. TDR-MGR-HS-000002 169900
REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
DOC.20040928.0005. 


BSC 2004. UZ Flow Models and Submodels. MDL-NBS-HS-000006, REV 02. 169861
Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20041101.0004. 


BSC 2004. Ventilation Model and Analysis Report. ANL-EBS-MD-000030 169862
REV 04. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20041025.0002. 


MDL-NBS-HS-000001 REV 04 9-4 February 2005 


Drift-Scale THC Seepage Model 

BSC 2005. Technical Work Plan for: Near-Field Environment and Transport: 172761 
Coupled Processes (Mountain-Scale TH/THC/THM, Drift-Scale THC Seepage, 
and Post-Processing Analysis for THC Seepage) Report Integration. 
TWP-MGR-PA-000017 REV 01 ICN 02. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: DOC.20050211.0001 

Buscheck, T.A. and Nitao, J.J. 1993. Repository-Heat-Driven Hydrothermal 100617
Flow at Yucca Mountain, Part I: Modeling and Analysis. Nuclear Technology, 
104, (3), 418-448. La Grange Park, Illinois: American Nuclear Society. 
TIC: 224039. 


Canori, G.F. and Leitner, M.M. 2003. Project Requirements Document. 166275
TER-MGR-MD-000001 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20031222.0006. 


Carlos, B.A.; Chipera, S.J.; Bish, D.L.; and Craven, S.J. 1993. Fracture-Lining 105210
Manganese Oxide Minerals in Silicic Tuff, Yucca Mountain, Nevada, U.S.A. 
Chemical Geology, 107, 47-69. Amsterdam, The Netherlands: Elsevier. 
TIC: 208629. 


Carroll, S.; Mroczek, E.; Alai, M.; and Ebert, M. 1998. Amorphous Silica 124275
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CRWMS M&O 2001. Updated CO2 Analysis of Gas Samples Collected from the 153814
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Drift-Scale THC Seepage Model 

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Drift-Scale THC Seepage Model 

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160190 
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Drift-Scale THC Seepage Model 

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NRC (U.S. Nuclear Regulatory Commission) 2003. Yucca Mountain Review 163274
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MDL-NBS-HS-000001 REV 04 9-8 February 2005 


Drift-Scale THC Seepage Model 

Pokrovskii, V.A. and Helgeson, H.C. 1995. Thermodynamic Properties of 101699 
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Pruess, K. 1997. On Vaporizing Water Flow in Hot Sub-Vertical Rock 

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Pruess, K.; Wang, J.S.Y.; and Tsang, Y.W. 1990. On Thermohydrologic 100818
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of Minerals and Related Substances at 298.15 K and 1 Bar (105 Pascals) Pressure 
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Drift-Scale THC Seepage Model 

Rosenberg, N.D.; Gdowski, G.E.; and Knauss, K.G. 2001. Evaporative Chemical 154862
Evolution of Natural Waters at Yucca Mountain, Nevada. Applied Geochemistry, 
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Savage, D.; Cave, M.R.; Haigh, D.; Milodowski, A.E.; and Young, M.E. 1993. 160198
The Reaction Kinetics of Laumontite Under Hydrothermal Conditions.
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Hudson, M.R. 1994. Episodic Caldera Volcanism in the Miocene Southwestern 
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Slider, H.C. 1976. Practical Petroleum Reservoir Engineering Methods, An 128146
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Sonnenthal, E.L. and Bodvarsson, G.S. 1999. Constraints on the Hydrology of 117127
the Unsaturated Zone at Yucca Mountain, NV from Three-Dimensional Models of 
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Spycher, N. 2001. Drift Scale Modeling (YMP-LBNL-DSM-NS-1). Scientific 160898
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Spycher, N.F.; Sonnenthal, E.L.; and Apps, J.A. 2003. Fluid Flow and Reactive 162121
Transport Around Potential Nuclear Waste Emplacement Tunnels at Yucca 
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York, New York: Elsevier. TIC: 254205. 


Steefel, C.I. and Lasaga, A.C. 1994. A Coupled Model for Transport of Multiple 101480
Chemical Species and Kinetic Precipitation/Dissolution Reactions with 
Application to Reactive Flow in Single Phase Hydrothermal Systems. American 
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Kline Geology Laboratory. TIC: 235372. 


Steefel, C.I. and Lichtner, P.C. 1998. Multicomponent Reactive Transport in 144878
Discrete Fractures: I. Controls on Reaction Front Geometry. Journal of 
Hydrology, 209, 186-199. New York, New York: Elsevier. TIC: 247524. 


MDL-NBS-HS-000001 REV 04 9-10 February 2005 


Drift-Scale THC Seepage Model 

Steefel, C.I. and Yabusaki, S.B. 1996. OS3D/GIMRT Software for Modeling 100827
Multicomponent-Multidimensional Reactive Transport User Manual & 
Programmers Guide. PNL-11166. Richland, Washington: Pacific Northwest 
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Stefnsson, A. and Arnrsson, S. 2000. Feldspar Saturation State in Natural 153578
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Svensson, U. and Dreybrodt, W. 1992. Dissolution Kinetics of Natural Calcite 127978
Minerals in CO2-Water Systems Approaching Calcite Equilibrium. Chemical 
Geology, 100, 129-145. Amsterdam, The Netherlands: Elsevier. TIC: 246497. 


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Correlating Quartz Dissolution Kinetics in Pure Water from 25 to 625C. 
Geochimica et Cosmochimica Acta, 58, (11), 2407-2420. New York, New York: 
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Tsang, Y.W. and Birkholzer, J.T. 1999. Predictions and Observations of the 137577
Thermal-Hydrologic Conditions in the Single Heater Test. Journal of 
Contaminant Hydrology, 38, (1-3), 385-425. New York, New York: Elsevier. 
TIC: 244160. 


Vaniman, D.T.; Chipera, S.J.; Bish, D.L.; Carey, J.W.; and Levy, S.S. 2001. 157427
Quantification of Unsaturated-Zone Alteration and Cation Exchange in Zeolitized 
Tuffs at Yucca Mountain, Nevada, USA. Geochimica et Cosmochimica Acta, 65, 
(20), 3409-3433. New York, New York: Elsevier. TIC: 251574. 


Wang, J.S. 2003. Scientific Notebooks Referenced in Model Report 161665
N0120/U0110, Drift-Scale Coupled Processes (DST and THC Seepage) Models 
MDL-NBS-HS-000001 REV 02. Interoffice correspondence from J.S. Wang 
(BSC) to File, June 6, 2003, with attachments. ACC: MOL.20030611.0079. 


White, A.F. and Brantley, S.L., eds. 1995. Chemical Weathering Rates of Silicate 154492
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Williams, N.H. 2003. Contract No. DE-AC28-01RW1210  Transmittal of 163765
White Paper, Effects of Neoprene on Water in the Drift Scale Test. Letter from


N.H. Williams (BSC) to J.D. Ziegler (DOE/ORD), February 4, 2003, 0129035843, 
with enclosure. ACC: MOL.20030206.0211. 
Wilson, N.S.F.; Cline, J.S.; and Lundberg, S.A.W. 2000. Paragenesis and 154279
Chemical Composition of Secondary Mineralization at Yucca Mountain, Nevada. 
Abstracts with Programs - Geological Society of America, 32, (7), A-260. 
Boulder, Colorado: Geological Society of America. TIC: 249113. 


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Drift-Scale THC Seepage Model 

Wu, Y.S.; Ritcey, A.C.; and Bodvarsson, G.S. 1999. A Modeling Study of 117167 
Perched Water Phenomena in the Unsaturated Zone at Yucca Mountain. Journal 
of Contaminant Hydrology, 38, (1-3), 157-184. New York, New York: Elsevier. 
TIC: 244160. 
Xu, T. and Pruess, K. 1998. Coupled Modeling of Non-Isothermal Multi-Phase 117170 
Flow, Solute Transport and Reactive Chemistry in Porous and Fractured Media: 
1. Model Development and Validation. LBNL-42050. Berkeley, California: 
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Xu, T. and Pruess, K. 2001. Modeling Multiphase Non-Isothermal Fluid Flow 156280 
and Reactive Geochemical Transport in Variably Saturated Fractured Rocks: 1. 
Methodology. American Journal of Science, 301, 16-33. New Haven, 
Connecticut: Yale University, Kline Geology Laboratory. TIC: 251482. 
Xu, T.; Pruess, K.; and Brimhall, G. 1998. An Improved Equilibrium-Kinetics 101751 
Speciation Algorithm for Redox Reactions in Variably Saturated Subsurface Flow 
Systems. LBNL-41789. Berkeley, California: Lawrence Berkeley National 
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Xu, T.; Sonnenthal, E.; and Bodvarsson, G. 2003. A Reaction-Transport Model 162124 
for Calcite Precipitation and Evaluation of Infiltration Fluxes in Unsaturated 
Fractured Rock. Journal of Contaminant Hydrology, 64, (1-2), 113-127. New 
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Modeling Multiphase Non-Isothermal Fluid Flow and Reactive Geochemical 
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Yokoyama, T. and Banfield, J. F. 2002. Direct Determination of the Rates of 171364 
Rhyolite Dissolution and Clay Formation Over 52,000 Years and Comparison 
with Laboratory Measurements. Geochimica et Cosmochimica Acta, 66, (15), 
2665-2681. New York, New York: Pergamon. TIC: 256435. 

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Drift-Scale THC Seepage Model 

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. 


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-SIII.3Q, Rev. 2, ICN 1. Submittal and Incorporation of Data to the Technical 
Data Management System. Washington, D.C.: U.S. Department of Energy, 
Office of Civilian Radioactive Waste Management. ACC: MOL.20040226.0001. 


AP-SV.1Q, Rev. 1, ICN 2. Control of the Electronic Management of Information. 
Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive 
Waste Management. ACC: DOC.20050119.0004. 


LP-2.29Q-BSC, Rev 0, ICN 0. Planning for Science Activities. Washington, 
D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste 
Management. ACC: DOC.20050114.0001. 


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. 


LP-SIII.2Q-BSC, Rev. 0, ICN 0. Qualification of Unqualified Data. Washington, 
D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste 
Management. ACC: DOC.20050119.0002. 


LP-SIII.10Q-BSC, Rev. 0, ICN 0. Models. Washington, D.C.: U.S. Department 
of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20050203.0009. 


YMP-LBNL-QIP-SV.0, Rev. 2, Mod. 1. Management of YMP-LBNL Electronic 
Data. Berkeley, California: Lawrence Berkeley National Laboratory. 
ACC: MOL.20020717.0319. 


9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
GS000308311221.005. Net Infiltration Modeling Results for 3 Climate Scenarios 
for FY99. Submittal date: 03/01/2000. 

GS000483351030.003. Thermal Properties Measured 12/01/99 to 12/02/99 Using 
the Thermolink Soil Multimeter and Thermal Properties Sensor on Selected 
Potential Candidate Backfill Materials Used in the Engineered Barrier System. 
Submittal date: 11/09/2000. 

156605


147613
152932


MDL-NBS-HS-000001 REV 04 9-13 February 2005 


Drift-Scale THC Seepage Model 

GS020408312272.003. Collection and Analysis of Pore Water Samples for the 160899
Period from April 2001 to February 2002. Submittal date: 04/24/2002. 


GS020808312272.004. Analysis of Water-Quality Samples for the Period from 166569
July 1999 to July 2002. Submittal date: 09/18/2002. 


GS030408312272.002. Analysis of Water-Quality Samples for the Period from 165226
July 2002 to November 2002. Submittal date: 05/07/2003. 


GS031008312272.008. Analysis of Pore Water and Miscellaneous Water Samples 166570
for the Period from December 2002 to July 2003. Submittal date: 11/13/2003. 


LA0009SL831151.001. Fracture Mineralogy of the ESF Single Heater Test 153485
Block, Alcove 5. Submittal date: 09/28/2000. 


LA0201SL831225.001. Chemical, Textural, and Mineralogical Characteristics of 158426 
Sidewall Samples from the Drift Scale Test. Submittal date: 01/10/2002. 


LA9908JC831321.001. Mineralogic Model MM3.0 Version 3.0. Submittal 113495
date: 08/16/1999. 


LA9912SL831151.001. Fracture Mineralogy of Drill Core ESF-HD-TEMP-2. 146447
Submittal date: 01/05/2000. 


LA9912SL831151.002. Percent Coverage by Fracture-Coating Minerals in Core 146449
ESF-HD-TEMP-2. Submittal date: 01/05/2000.


LB000121123142.003. Isotope Data for CO2 Gas Samples Collected From the 146451
Hydrology Holes of the ESF Drift Scale Test for the Period August 9, 1999 
through November 30, 1999. Submittal date: 01/21/2000. 


LB0011CO2DST08.001. Isotope Data for CO2 from Gas Samples Collected from 153460
Hydrology Holes in Drift-Scale Test. Submittal date: 12/09/2000. 


LB0011DSTTHCR1.002. Model Input and Output Files, Excel Spreadsheets and 161282
Resultant Figures which are Presented in AMR U0110/N0120, Drift-Scale 
Coupled Processes (DST and THC Seepage) Models REV 01. Submittal date: 
12/19/2000. 


LB0101DSTTHCR1.002. Attachment II - Mineral Initial Volume Fractions for 161277
TPTPLL THC Model for AMR N0120/U0110 REV01, Drift-Scale Coupled 
Processes (Drift-Scale Test and THC Seepage) Models. Submittal date: 
01/26/2001. 


MDL-NBS-HS-000001 REV 04 9-14 February 2005 


Drift-Scale THC Seepage Model 

LB0101DSTTHCR1.004. Attachment IV - Mineral Reactive Surface Areas: 161279
TPTPLL THC Model for AMR N0120/U0110 REV01, Drift-Scale Coupled 
Processes (Drift-Scale Test and THC Seepage) Models. Submittal date: 
01/26/2001. 


LB0101DSTTHGRD.001. 2D Finite Element Mesh Used for DST THC Model 153687
Simulations (Input to AMR N0120/U0110 REV. 01). Submittal date: 01/05/2001. 


LB0102CO2DST98.001. Concentration Data for CO2 from Gas Samples 159306
Collected from Hydrology Holes in Drift-scale Test. Submittal date: 02/28/2001. 


LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed 159525
from Field Data. Submittal date: 05/14/2002. 


LB0207REVUZPRP.002. Matrix Properties for UZ Model Layers Developed 159672
from Field and Laboratory Data. Submittal date: 07/15/2002. 


LB0208ISODSTHP.001. Isotope Data and CO2 Analysis for the Heating Phase of 161638
the DST. Submittal date: 08/09/2002. 


LB0208UZDSCPMI.002. Drift-Scale Calibrated Property Sets: Mean Infiltration 161243
Data Summary. Submittal date: 08/26/2002. 


LB0210THRMLPRP.001. Thermal Properties of UZ Model Layers: Data 160799
Summary. Submittal date: 10/25/2002. 


LB03023DKMGRID.001. UZ 3-D Site Scale Model Grids. Submittal date: 162354
02/26/2003. 


LB0307KNTDBRTM.001. Kinetic Database for Reactive Transport Modeling. 164433
Submittal date: 07/22/2003. 


LB0307THMDBRTM.001. Thermodynamic Database for Reactive Transport 164434
Modeling. Submittal date: 07/22/2003. 


LB0402THRMLPRP.001. Thermal Properties of UZ Model Layers: Data 168481
Summary. Submittal date: 02/20/2004. 


LB990501233129.004. 3-D UZ Model Calibration Grids for AMR U0000, 111475
Development of Numerical Grids of UZ Flow and Transport Modeling. 
Submittal date: 09/24/1999. 


LB990601233124.001. Seepage Data Feed to UZ Drift-Scale Flow Model for 105888
TSPA-SR. Submittal date: 06/18/1999. 


LB990630123142.003. Fourth, Fifth, and Sixth Quarters TDIF Submission for the 111476
Drift Scale Test, September 1998 to May 1999. Submittal date: 06/30/1999. 


MDL-NBS-HS-000001 REV 04 9-15 February 2005 


Drift-Scale THC Seepage Model 

LB990701233129.002. 3-D Model Calibration Grid for Calculation of Flow 125604
Fields Using #3 Perched Water Conceptual Model (Non-Perched Water Model) 
for AMR U0050, UZ Flow Models and Submodels. Submittal date: 
03/11/2000. 


LB991200DSTTHC.002. Model Input and Output Files, Excel Spreadsheets and 142162
Resultant Figures Which are Presented in AMR N0120/U0110, Drift-Scale 
Coupled Processes (Drift-Scale Test and THC Seepage) Models. Submittal date: 
03/11/2000. 


LL000114004242.090. TSPA-SR Mean Calculations. Submittal date: 142884
01/28/2000. 


LL001100931031.008. Aqueous Chemistry of Water Sampled from Boreholes of 153288
the Drift Scale Test (DST). Submittal date: 11/10/2000. 


LL001200231031.009. Aqueous Chemistry of Water Sampled from Boreholes of 153616
the Drift Scale Test (DST). Submittal date: 12/04/2000. 


LL020302223142.015. Aqueous Geochemistry of DST Samples Collected from 159134
HYD Boreholes. Submittal date: 03/07/2002. 


LL020405123142.019. Aqueous Geochemistry of Condensed Fluids Collected 159307
During Studies of Introduced Materials. Submittal date: 05/22/2002. 


LL020709923142.023. Aqueous Geochemistry of Borehole Waters Collected in 161677
the Heating Phase of the DST. Submittal date: 07/26/2002.


LL990702804244.100. Borehole and Pore Water Data. Submittal date: 144922
07/13/1999. 


MO0001SEPDSTPC.000. Drift Scale Test (DST) Temperature, Power, Current, 153836
and Voltage Data for June 1, 1999 through October 31, 1999. Submittal date: 
01/12/2000. 


MO0002ABBLSLDS.000. As-Built Borehole Locations and Sensor Locations for 147304
the Drift Scale Test Given in Local (DST) Coordinates. Submittal date: 
02/01/2000. 


MO0003RIB00071.000. Physical and Chemical Characteristics of Alloy 22. 148850
Submittal date: 03/13/2000. 


MO0005PORWATER.000. Perm-Sample Pore Water Data. Submittal date: 150930
05/04/2000. 


MDL-NBS-HS-000001 REV 04 9-16 February 2005 


Drift-Scale THC Seepage Model 

MO0007SEPDSTPC.001. Drift Scale Test (DST) Temperature, Power, Current, 153707
and Voltage Data for November 1, 1999 through May 31, 2000. Submittal date: 
07/13/2000. 


MO0012SEPDSTPC.002. Drift Scale Test (DST) Temperature, Power, Current, 153708
and Voltage Data for June 1, 2000 through November 30, 2000. Submittal date: 
12/19/2000. 


MO0101SEPFDDST.000. Field Measured Data of Water Samples from the Drift 153711
Scale Test. Submittal date: 01/03/2001. 


MO0107SEPDSTPC.003. Drift Scale Test (DST) Temperature, Power, Current, 158321
and Voltage Data for December 1, 2000 through May 31, 2001. Submittal date: 
07/06/2001. 


MO0202SEPDSTTV.001. Drift Scale Test (DST) Temperature, Power, Current, 158320
and Voltage Data for June 1, 2001 through January 14, 2002. Submittal date: 
02/28/2002. 


MO0207AL5WATER.001. Water Sampling in Alcove 5 (Results from 2/4/1997 159300
through 4/20/1999). Submittal date: 07/11/2002. 


MO0208RESTRDST.002. Restructured Drift Scale Test (DST) Heating Phase 161129
Power and Temperature Data. Submittal date: 08/06/2002. 


MO0302SPATHDYN.000. Thermodynamic Data Input Files - Data0.YMP.R2. 161756
Submittal date: 02/05/2003. 


MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 170760


MO9807DSTSET01.000. Drift Scale Test (DST) Temperature, Power, Current, 113644
Voltage Data for November 7, 1997 through May 31, 1998. Submittal date: 
07/09/1998. 


MO9810DSTSET02.000. Drift Scale Test (DST) Temperature, Power, Current, 113662
Voltage Data for June 1 through August 31, 1998. Submittal date: 10/09/1998. 


MO9906DSTSET03.000. Drift Scale Test (DST) Temperature, Power, Current, 113673
and Voltage Data for September 1, 1998 through May 31, 1999. Submittal date: 
06/08/1999. 


SN0002T0872799.009. Effective Thermal Conductivity Parameter for the No 153364
Backfill Case Implemented in the Drift-Scale Models used in TSPA-SR. Submittal 
date: 02/10/2000. 


SN0203F3903102.001. Drift Scale Test Water Sampling (with Results from 159133
4/17/2001 through 1/14/2002). Submittal date: 03/29/2002.


MDL-NBS-HS-000001 REV 04 9-17 February 2005 


Drift-Scale THC Seepage Model 

SN9908T0872799.004. Tabulated In-Drift Geometric and Thermal Properties 108437 
Used in Drift-Scale Models for TSPA-SR (Total System Performance 
Assessment-Site Recommendation). Submittal date: 08/30/1999 

9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
LB0302DSCPTHCS.001. Drift-Scale Coupled Processes (THC Seepage) Model: Simulations. 
Submittal date: 02/11/2003. 

LB0302DSCPTHCS.002. Drift-Scale Coupled Processes (THC Seepage) Model: Data 
Summary. Submittal date: 02/11/2003. 

LB0307DSTTHCR2.001. Drift-Scale Coupled Processes (DST Seepage) Model: Simulations. 
Submittal date: 07/24/2003. 

LB0307DSTTHCR2.002. Drift-Scale Coupled Processes (DST Seepage) Model: Data 
Summary. Submittal date: 07/24/2003. 

LB0404DSTTHCR2.001. Tptpll THC Model - Simulation Input and Output Files. Submittal 
date: 04/02/2004. 

LB0404DSTTHCR2.002. Tptpll THC Model - Summary Spreadsheets of THC Seepage Models 
Output Data. Submittal date: 04/02/2004. 

9.5 SOFTWARE CODES 
LBNL (Lawrence Berkeley National Laboratory) 09/22/2000. Software Routine 153091 
Report: merggrid2.f. V1.0. SUN w/Unix OS. 10314-1.0-00. 

LBNL 2000. Software Routine Report: mk_circ2. V1.0. SUN w/Unix OS. 153092 
10312-1.0-00. 

LBNL 2000. Software Routine: mk_incon. V1.0. SUN w/Unix OS. 152901 
10350-1.0-00. 

LBNL 2000. Software Routine: regress. V1.0. PC w/Windows OS. 152900 
10321-1.0-00. 

LBNL 2000. Software Routine: switch. V1.0. PC w/Windows OS. 152899 
10322-1.0-00. 

LBNL 2000. Software Routine Report: sav1d_dst2d.f. V1.0. SUN w/Unix OS. 153083 
10381-1.0-00. 

LBNL 1999. Software Code: AMESH. V1.0. Sun, DEC O.S. 5.5.1, V4.0. 147561 
10045-1.0-00. 

MDL-NBS-HS-000001 REV 04 9-18 February 2005 


Drift-Scale THC Seepage Model 

LBNL 1999. Software Code: SOLVEQ/CHILLER. V1.0. PC w/Windows OS. 153217 
10057-1.0-00. 

LBNL 1999. Software Code: SUPCRT92. V1.0. PC w/Windows OS and MAC 153218 
w/MAC OS. 10058-1.0-00. 

LBNL 1999. Software Code: TOUGHREACT. V2.2. DEC and SUN w/Unix 153219 
OS. 10154-2.2-00. 

LBNL 2000. Software Code: TOUGH2. V.1.4. Sun Ultra Sparc, SUN O.S. 146496 
5.5.1, and DEC/ALPHA, OSF 2 V4.0, OSF1 V5.1. 10007-1.4-01. 

LBNL 2000. Software Routine Report: 2kgridv1a.for. V1.0. PC, DOS 153067 
Emulation. 10382-1.0-00. 

LBNL 2000. Software Routine Report: assign.f. V1.0. SUN, SUN O.S. 5.5.1. 153090 
10315-1.0-00. 

LBNL 2000. Software Routine Report: exclude.f. V1.0. SUN, SUN O.S. 5.5.1. 153089 
10316-1.0-00. 

LBNL 2000. Software Routine Report: mk_grav2.f. V1.0. SUN, SUN O.S. 153068 

5.5.1. 10379-1.0-00. 
LBNL 2000. Software Routine: mk_rect2. V1.0. SUN w/Unix OS. 153093 
10313-1.0-00. 
LBNL 2000. Software Routine Report: mrgdrift.f. V1.0. SUN, SUN O.S. 5.5.1. 153082 

10380-1.0-00. 

LBNL 2001. Software Code: TOUGHREACT. V2.3. SUN and DEC w/Unix 153101 
OS. 10396-2.3-00. 
LBNL 2001. Software Code: TOUGHREACT. V2.4. SunOS 5.5.1, Dec Alpha 160880 

TRU64 Unix & OS1 V4.0. 10396-2.4-00. 

LBNL 2002. Software Code: CUTCHEM. V1.0. DEC ALPHA/OSF1 V5.1, PC 161127
/WINDOWS 2000/NT 4.0/98. 10898-1.0-00. 
LBNL 2002. Software Code: DBCONV. V1.0. PC/Windows 98/NT; 


161263 
DEC-Alpha/OSF1 V5.1; SunOS 5.5.1. 10893-1.0-00. 

LBNL 2002. Software Code: KREG. V1.1. SUN UltraSparc with Unix SunOS 161258 
5.5.1, WINDOWS 2000/NT/98, Dec Alpha with OSF1 V5.1. 10318-1.1-00. 

LBNL 2002. Software Code: KSWITCH. V1.1. PC with WINDOWS 

161259 
2000/NT/98, Dec Alpha with OSF1 V5.1, SUN OS 5.5.1. 10319-1.1-00. 

MDL-NBS-HS-000001 REV 04 9-19 February 2005 


Drift-Scale THC Seepage Model 

LBNL 2002. Software Code: THERMOCHK. V1.1. PC/Windows 98/NT 4.0; 161262
DEC-Alpha/OSF1 V5.1; SunOS 5.5.1. 10895-1.1-00. 


LBNL 2002. Software Code: TOUGHREACT. V3.0. DEC ALPHA/OSF1 V5.1, 161256
DEC ALPHA/OSF1 V5.0, Sun UltraSparc/SUN OS 5.5.1, PC/Linux Redhat 7.2. 
10396-3.0-00. 


LBNL 2003. Software Code: TOUGH2. V1.6. PC/MS-DOS Windows 98, Sun 161491
UltraSparc/Sun OS 5.5.1, DEC-Alpha OSF1 V4.0. 10007-1.6-01. 


MDL-NBS-HS-000001 REV 04 9-20 February 2005 


Drift-Scale THC Seepage Model 

APPENDIX A 
MINERAL INITIAL VOLUME FRACTIONS 


MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

Table A-1. Mineral Initial Volume Fractions (1) 

Rock Zone K-Feldspar Albite Anorthite Ca-Smectite Na-Smectite Mg-Smectite Illite Tridymite Cristobalite Quartz 

tcwm1 0.36911 0.27257 0.00917 0.00198 0.00085 0.00198 0.00148 0.10285 0.21294 0.00942 
tcwf1 0.36911 0.27257 0.00917 0.00198 0.00085 0.00198 0.00148 0.10285 0.21294 0.00942 
tcwm2 0.36911 0.27257 0.00917 0.00198 0.00085 0.00198 0.00148 0.10285 0.21294 0.00942 
tcwf2 0.36911 0.27257 0.00917 0.00198 0.00085 0.00198 0.00148 0.10285 0.21294 0.00942 
tcwm3 0.16239 0.11992 0.00403 0.04403 0.01887 0.04403 0.03284 0.00000 0.12577 0.00744 
tcwf3 0.16239 0.11992 0.00403 0.04403 0.01887 0.04403 0.03284 0.00000 0.12577 0.00744 
ptnm1 0.05149 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnf1 0.05149 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnm2 0.05148 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnf2 0.05148 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnm3 0.05149 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnf3 0.05149 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnm4 0.05149 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnf4 0.05149 0.03802 0.00128 0.02441 0.01046 0.02441 0.01821 0.00015 0.01460 0.00702 
ptnm5 0.05136 0.03793 0.00128 0.02435 0.01044 0.02435 0.01817 0.00015 0.01460 0.00702 
ptnf5 0.05136 0.03793 0.00128 0.02435 0.01044 0.02435 0.01817 0.00015 0.01460 0.00702 
ptnm6 0.05137 0.03794 0.00128 0.02436 0.01044 0.02436 0.01817 0.00015 0.01457 0.00701 
ptnf6 0.05137 0.03794 0.00128 0.02436 0.01044 0.02436 0.01817 0.00015 0.01457 0.00701 
tswm1 0.10362 0.07652 0.00257 0.00213 0.00091 0.00213 0.00159 0.00112 0.01999 0.00118 
tswf1 0.10362 0.07652 0.00257 0.00213 0.00091 0.00213 0.00159 0.00112 0.01999 0.00118 
tswm2 0.38312 0.28291 0.00952 0.00343 0.00147 0.00343 0.00256 0.15942 0.13313 0.00473 
tswf2 0.23179 0.17116 0.00576 0.01767 0.00757 0.01767 0.01318 0.09645 0.08054 0.00286 
tswm3 0.36306 0.26810 0.00902 0.00777 0.00333 0.00777 0.00580 0.05630 0.23767 0.02695 
tswf3 0.21965 0.16220 0.00546 0.02029 0.00870 0.02029 0.01514 0.03406 0.14379 0.01630 
tswm4 0.32265 0.23826 0.00802 0.00517 0.00221 0.00517 0.00385 0.02310 0.35588 0.02526 
tswf4 0.19520 0.14415 0.00485 0.01872 0.00802 0.01872 0.01396 0.01397 0.21530 0.01529 
tswm5 0.34968 0.25822 0.00869 0.00686 0.00294 0.00686 0.00512 0.02321 0.18589 0.14046 
tswf5 0.21155 0.15622 0.00526 0.01974 0.00846 0.01974 0.01473 0.01404 0.11247 0.08498 
tswm6 0.36268 0.26782 0.00901 0.00327 0.00140 0.00327 0.00244 0.00195 0.16651 0.16845 
tswf6 0.21942 0.16203 0.00545 0.01757 0.00753 0.01757 0.01311 0.00118 0.10074 0.10191 
tswm7 0.36322 0.26822 0.00902 0.00328 0.00140 0.00328 0.00244 0.00195 0.16676 0.16870 
tswf7 0.21975 0.16227 0.00546 0.01758 0.00753 0.01758 0.01311 0.00118 0.10089 0.10206 
tswm8 0.11030 0.08145 0.00274 0.04279 0.01834 0.04279 0.03192 0.00000 0.09981 0.00790 
tswf8 0.11030 0.08145 0.00274 0.04279 0.01834 0.04279 0.03192 0.00000 0.09981 0.00790 
tswm9 0.06105 0.04508 0.00152 0.02739 0.01174 0.02739 0.02044 0.00000 0.06216 0.01481 
tswf9 0.06105 0.04508 0.00152 0.02739 0.01174 0.02739 0.02044 0.00000 0.06216 0.01481 
ch1mv 0.07829 0.05781 0.00195 0.00747 0.00320 0.00747 0.00557 0.00586 0.06920 0.03831 
ch1fv 0.07829 0.05781 0.00195 0.00747 0.00320 0.00747 0.00557 0.00586 0.06920 0.03831 

MDL-NBS-HS-000001 REV 04 A-1 February 2005 


Drift-Scale THC Seepage Model 

Table A-1. Mineral Initial Volume Fractions (1) (Continued) 

Rock Zone K-Feldspar Albite Anorthite Ca-Smectite Na-Smectite Mg-Smectite Illite Tridymite Cristobalite Quartz 

ch2mv 39 0.09836 0.07263 0.00244 0.00691 0.00296 0.00691 0.00515 0.00079 0.05704 0.04824 
ch2fv 40 0.09836 0.07263 0.00244 0.00691 0.00296 0.00691 0.00515 0.00079 0.05704 0.04824 
ch3mv 41 0.04708 0.03477 0.00117 0.00216 0.00093 0.00216 0.00161 0.00001 0.04663 0.02747 
ch3fv 42 0.04708 0.03477 0.00117 0.00216 0.00093 0.00216 0.00161 0.00001 0.04663 0.02747 
ch4mz 43 0.04820 0.03559 0.00120 0.00058 0.00025 0.00058 0.00043 0.00000 0.03726 0.02878 
ch4fz 44 0.04820 0.03559 0.00120 0.00058 0.00025 0.00058 0.00043 0.00000 0.03726 0.02878 
ch5mz 45 0.04551 0.03361 0.00113 0.00046 0.00020 0.00046 0.00035 0.00000 0.02171 0.02707 
ch5fz 46 0.04551 0.03361 0.00113 0.00046 0.00020 0.00046 0.00035 0.00000 0.02171 0.02707 
ch6mv 47 0.09931 0.07334 0.00247 0.00620 0.00266 0.00620 0.00463 0.00000 0.05861 0.09735 
ch6fv 48 0.09931 0.07334 0.00247 0.00620 0.00266 0.00620 0.00463 0.00000 0.05861 0.09735 
pp4m 49 0.08283 0.06116 0.00206 0.00829 0.00355 0.00829 0.00619 0.00003 0.06691 0.01512 
pp4f 50 0.08283 0.06116 0.00206 0.00829 0.00355 0.00829 0.00619 0.00003 0.06691 0.01512 
pp3m 51 0.36843 0.27207 0.00915 0.00332 0.00142 0.00332 0.00248 0.00590 0.07075 0.24829 
pp3f 52 0.36843 0.27207 0.00915 0.00332 0.00142 0.00332 0.00248 0.00590 0.07075 0.24829 
pp2m 53 0.36843 0.27207 0.00915 0.00332 0.00142 0.00332 0.00248 0.00590 0.07075 0.24829 
pp2f 54 0.36843 0.27207 0.00915 0.00332 0.00142 0.00332 0.00248 0.00590 0.07075 0.24829 
pp1m 55 0.09931 0.07334 0.00247 0.00620 0.00266 0.00620 0.00463 0.00000 0.05861 0.09735 
pp1f 56 0.09931 0.07334 0.00247 0.00620 0.00266 0.00620 0.00463 0.00000 0.05861 0.09735 
bf3m4 57 0.36843 0.27207 0.00915 0.00332 0.00142 0.00332 0.00248 0.00590 0.07075 0.24829 
bf3f4 58 0.36843 0.27207 0.00915 0.00332 0.00142 0.00332 0.00248 0.00590 0.07075 0.24829 

Source: DTN: LB0101DSTTHCR1.002 [DIRS 161277]. 

MDL-NBS-HS-000001 REV 04 A-2 February 2005 


Drift-Scale THC Seepage Model 

Table A-2. Mineral Initial Volume Fractions (2) 

Rock Zone Glass Hematite Calcite Stellerite Heulandite Mordenite Clinoptilolite Kaolinite Am. Silica Opal Fluorite 

tcwm1 0.00139 0.00000 0.00358 0.00000 0.00083 0.00028 0.00167 0.00000 0.00000 0.00990 0.00000 
tcwf1 0.00139 0.00000 0.00358 0.00000 0.00083 0.00028 0.00167 0.00000 0.00000 0.00990 0.00000 
tcwm2 0.00139 0.00000 0.00358 0.00000 0.00083 0.00028 0.00167 0.00000 0.00000 0.00990 0.00000 
tcwf2 0.00139 0.00000 0.00358 0.00000 0.00083 0.00028 0.00167 0.00000 0.00000 0.00990 0.00000 
tcwm3 0.43046 0.00000 0.00032 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00990 0.00000 
tcwf3 0.43046 0.00000 0.00032 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00990 0.00000 
ptnm1 0.78888 0.00000 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnf1 0.78888 0.00000 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnm2 0.78876 0.00015 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnf2 0.78876 0.00015 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnm3 0.78888 0.00000 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnf3 0.78888 0.00000 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnm4 0.78888 0.00000 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnf4 0.78888 0.00000 0.01086 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnm5 0.78694 0.00239 0.01083 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnf5 0.78694 0.00239 0.01083 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnm6 0.78707 0.00228 0.01084 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
ptnf6 0.78707 0.00228 0.01084 0.00000 0.00008 0.00003 0.00017 0.00000 0.00000 0.00990 0.00000 
tswm1 0.75630 0.00485 0.01693 0.00000 0.00005 0.00002 0.00009 0.00000 0.00000 0.00990 0.00010 
tswf1 0.75630 0.00485 0.01693 0.00000 0.00005 0.00002 0.00009 0.00000 0.00000 0.00990 0.00010 
tswm2 0.00070 0.00439 0.00110 0.00010 0.00000 0.00001 0.00000 0.00000 0.00000 0.00990 0.00010 
tswf2 0.00042 0.00265 0.02046 0.32181 0.00000 0.00001 0.00000 0.00000 0.00000 0.00990 0.00010 
tswm3 0.00000 0.00353 0.00067 0.00000 0.00001 0.00000 0.00003 0.00000 0.00000 0.00990 0.00010 
tswf3 0.00000 0.00214 0.02020 0.32175 0.00001 0.00000 0.00002 0.00000 0.00000 0.00990 0.00010 
tswm4 0.00000 0.00036 0.00007 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00990 0.00010 
tswf4 0.00000 0.00022 0.01984 0.32175 0.00000 0.00000 0.00000 0.00000 0.00000 0.00990 0.00010 
tswm5 0.00000 0.00162 0.00038 0.00000 0.00002 0.00001 0.00005 0.00000 0.00000 0.00990 0.00010 
tswf5 0.00000 0.00098 0.02003 0.32175 0.00001 0.00000 0.00003 0.00000 0.00000 0.00990 0.00010 
tswm6 0.00000 0.00194 0.00007 0.00000 0.00035 0.00012 0.00071 0.00000 0.00000 0.00990 0.00010 
tswf6 0.00000 0.00118 0.01984 0.32175 0.00021 0.00007 0.00043 0.00000 0.00000 0.00990 0.00010 
tswm7 0.00000 0.00049 0.00007 0.00000 0.00035 0.00012 0.00071 0.00000 0.00000 0.00990 0.00010 
tswf7 0.00000 0.00029 0.01984 0.32175 0.00021 0.00007 0.00043 0.00000 0.00000 0.00990 0.00010 
tswm8 0.49522 0.00000 0.00039 0.00000 0.01691 0.00564 0.03381 0.00000 0.00000 0.00990 0.00010 
tswf8 0.49522 0.00000 0.00039 0.00000 0.01691 0.00564 0.03381 0.00000 0.00000 0.00990 0.00010 
tswm9 0.69427 0.00000 0.00005 0.00000 0.00723 0.00241 0.01446 0.00000 0.00000 0.00990 0.00010 
tswf9 0.69427 0.00000 0.00005 0.00000 0.00723 0.00241 0.01446 0.00000 0.00000 0.00990 0.00010 
ch1mv 0.50592 0.00000 0.00024 0.00000 0.06265 0.02088 0.12529 0.00000 0.00000 0.00990 0.00000 
ch1fv 0.50592 0.00000 0.00024 0.00000 0.06265 0.02088 0.12529 0.00000 0.00000 0.00990 0.00000 

MDL-NBS-HS-000001 REV 04 A-3 February 2005 


Drift-Scale THC Seepage Model 

Table A-2. Mineral Initial Volume Fractions (2) (Continued) 

Rock Zone Glass Hematite Calcite Stellerite Heulandite Mordenite Clinoptilolite Kaolinite Am. Silica Opal Fluorite 

ch2mv 39 0.60921 0.00000 0.00000 0.00000 0.02384 0.00795 0.04768 0.00000 0.00000 0.00990 0.00000 
ch2fv 40 0.60921 0.00000 0.00000 0.00000 0.02384 0.00795 0.04768 0.00000 0.00000 0.00990 0.00000 
ch3mv 41 0.73775 0.00000 0.00000 0.00000 0.02651 0.00884 0.05302 0.00000 0.00000 0.00990 0.00000 
ch3fv 42 0.73775 0.00000 0.00000 0.00000 0.02651 0.00884 0.05302 0.00000 0.00000 0.00990 0.00000 
ch4mz 43 0.73310 0.00000 0.00003 0.00000 0.03123 0.01041 0.06246 0.00000 0.00000 0.00990 0.00000 
ch4fz 44 0.73310 0.00000 0.00003 0.00000 0.03123 0.01041 0.06246 0.00000 0.00000 0.00990 0.00000 
ch5mz 45 0.77556 0.00000 0.00004 0.00000 0.02520 0.00840 0.05040 0.00000 0.00000 0.00990 0.00000 
ch5fz 46 0.77556 0.00000 0.00004 0.00000 0.02520 0.00840 0.05040 0.00000 0.00000 0.00990 0.00000 
ch6mv 47 0.32953 0.00000 0.00150 0.00000 0.09249 0.03083 0.18497 0.00000 0.00000 0.00990 0.00000 
ch6fv 48 0.32953 0.00000 0.00150 0.00000 0.09249 0.03083 0.18497 0.00000 0.00000 0.00990 0.00000 
pp4m 49 0.49175 0.00000 0.00163 0.00000 0.07269 0.02423 0.14538 0.00000 0.00000 0.00990 0.00000 
pp4f 50 0.49175 0.00000 0.00163 0.00000 0.07269 0.02423 0.14538 0.00000 0.00000 0.00990 0.00000 
pp3m 51 0.00003 0.00474 0.00000 0.00000 0.00005 0.00002 0.00010 0.00000 0.00000 0.00990 0.00000 
pp3f 52 0.00003 0.00474 0.00000 0.00000 0.00005 0.00002 0.00010 0.00000 0.00000 0.00990 0.00000 
pp2m 53 0.00003 0.00474 0.00000 0.00000 0.00005 0.00002 0.00010 0.00000 0.00000 0.00990 0.00000 
pp2f 54 0.00003 0.00474 0.00000 0.00000 0.00005 0.00002 0.00010 0.00000 0.00000 0.00990 0.00000 
pp1m 55 0.32953 0.00000 0.00150 0.00000 0.09249 0.03083 0.18497 0.00000 0.00000 0.00990 0.00000 
pp1f 56 0.32953 0.00000 0.00150 0.00000 0.09249 0.03083 0.18497 0.00000 0.00000 0.00990 0.00000 
bf3m4 57 0.00003 0.00474 0.00000 0.00000 0.00005 0.00002 0.00010 0.00000 0.00000 0.00990 0.00000 
bf3f4 58 0.00003 0.00474 0.00000 0.00000 0.00005 0.00002 0.00010 0.00000 0.00000 0.00990 0.00000 

Source: DTN: LB0101DSTTHCR1.002 [DIRS 161277]. 

MDL-NBS-HS-000001 REV 04 A-4 February 2005 


Drift-Scale THC Seepage Model 

APPENDIX B 
MINERAL REACTIVE SURFACE AREAS 


MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

Table B-1. Mineral Reactive Surface Areas (1) 

Rock Zone K-Feldspar Albite Anorthite Ca-Smectite Na-Smectite Mg-Smectite Illite Tridymite Cristobalite Quartz 

tcwm1 110.5 110.5 110.5 1516.3 1516.3 1516.3 1516.3 110.5 110.5 110.5 
tcwf1 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 
tcwm2 110.5 110.5 110.5 1516.3 1516.3 1516.3 1516.3 110.5 110.5 110.5 
tcwf2 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 
tcwm3 110.5 110.5 110.5 1516.3 1516.3 1516.3 1516.3 110.5 110.5 110.5 
tcwf3 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 
ptnm1 8.7 8.7 8.7 2253.3 2253.3 2253.3 2253.3 8.7 8.7 8.7 
ptnf1 142.8 142.8 142.8 142.8 142.8 142.8 142.8 142.8 142.8 142.8 
ptnm2 9.6 9.6 9.6 2484.8 2484.8 2484.8 2484.8 9.6 9.6 9.6 
ptnf2 184.6 184.6 184.6 184.6 184.6 184.6 184.6 184.6 184.6 184.6 
ptnm3 6.7 6.7 6.7 1721.5 1721.5 1721.5 1721.5 6.7 6.7 6.7 
ptnf3 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 
ptnm4 9.1 9.1 9.1 2356.2 2356.2 2356.2 2356.2 9.1 9.1 9.1 
ptnf4 44.5 44.5 44.5 44.5 44.5 44.5 44.5 44.5 44.5 44.5 
ptnm5 10.3 10.3 10.3 2666.7 2666.7 2666.7 2666.7 10.3 10.3 10.3 
ptnf5 276.2 276.2 276.2 276.2 276.2 276.2 276.2 276.2 276.2 276.2 
ptnm6 10.3 10.3 10.3 2666.7 2666.7 2666.7 2666.7 10.3 10.3 10.3 
ptnf6 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 
tswm1 57.2 57.2 57.2 694.3 694.3 694.3 694.3 57.2 57.2 57.2 
tswf1 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 
tswm2 110.0 110.0 110.0 1317.4 1317.4 1317.4 1317.4 110.0 110.0 110.0 
tswf2 530.8 530.8 530.8 530.8 530.8 530.8 530.8 530.8 530.8 530.8 
tswm3 107.4 107.4 107.4 1303.3 1303.3 1303.3 1303.3 107.4 107.4 107.4 
tswf3 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 
tswm4 90.7 90.7 90.7 1086.6 1086.6 1086.6 1086.6 90.7 90.7 90.7 
tswf4 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 
tswm5 99.0 99.0 99.0 1195.3 1195.3 1195.3 1195.3 99.0 99.0 99.0 
tswf5 844.7 844.7 844.7 844.7 844.7 844.7 844.7 844.7 844.7 844.7 
tswm6 92.0 92.0 92.0 1098.1 1098.1 1098.1 1098.1 92.0 92.0 92.0 
tswf6 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 
tswm7 83.6 83.6 83.6 996.5 996.5 996.5 996.5 83.6 83.6 83.6 
tswf7 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 
tswm8 36.0 36.0 36.0 526.7 526.7 526.7 526.7 36.0 36.0 36.0 
tswf8 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 
tswm9 36.0 36.0 36.0 526.7 526.7 526.7 526.7 36.0 36.0 36.0 
tswf9 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 
ch1mv 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
ch1fv 683.0 683.0 683.0 683.0 683.0 683.0 683.0 683.0 683.0 683.0 

MDL-NBS-HS-000001 REV 04 B-1 February 2005 


Drift-Scale THC Seepage Model 

Table B-1. Mineral Reactive Surface Areas (1) (Continued) 

Rock Zone K-Feldspar Albite Anorthite Ca-Smectite Na-Smectite Mg-Smectite Illite Tridymite Cristobalite Quartz 

ch2mv 39 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
ch2fv 40 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 
ch3mv 41 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
ch3fv 42 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 
ch4mz 43 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
ch4fz 44 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
ch5mz 45 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
ch5fz 46 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
ch6mv 47 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
ch6fv 48 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 
pp4m 49 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
pp4f 50 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
pp3m 51 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
pp3f 52 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 
pp2m 53 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
pp2f 54 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 
pp1m 55 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
pp1f 56 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
bf3m4 57 152.6 152.6 152.6 2024.7 2024.7 2024.7 2024.7 152.6 152.6 152.6 
bf3f4 58 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 

Source: DTN: LB0101DSTTHCR1.004 [DIRS 161279]. 

NOTE: Each unit is listed twice, the second-to-last letter being m for matrix, and f for fracture. Units for mineral 

reactive surface areas in the matrix are cm2/g; units for the reactive surface areas of fracture minerals are 

m2/m3. 

MDL-NBS-HS-000001 REV 04 B-2 February 2005 


Drift-Scale THC Seepage Model 

Table B-2. Mineral Reactive Surface Areas (2) 

Rock Zone Glass Hematite Calcite Stellerite Heulandite Mordenite Clinoptilolite Kaolinite Am. Silica Opal Fluorite 

tcwm1 110.5 128.7 128.7 128.7 128.7 128.7 128.7 1516.3 1516.3 1516.3 128.7 
tcwf1 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 
tcwm2 110.5 128.7 128.7 128.7 128.7 128.7 128.7 1516.3 1516.3 1516.3 128.7 
tcwf2 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 
tcwm3 110.5 128.7 128.7 128.7 128.7 128.7 128.7 1516.3 1516.3 1516.3 128.7 
tcwf3 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 394.8 
ptnm1 8.7 9.6 9.6 9.6 9.6 9.6 9.6 2253.3 2253.3 2253.3 9.6 
ptnf1 142.8 142.8 142.8 142.8 142.8 142.8 142.8 142.8 142.8 142.8 142.8 
ptnm2 9.6 10.5 10.5 10.5 10.5 10.5 10.5 2484.8 2484.8 2484.8 10.5 
ptnf2 184.6 184.6 184.6 184.6 184.6 184.6 184.6 184.6 184.6 184.6 184.6 
ptnm3 6.7 7.3 7.3 7.3 7.3 7.3 7.3 1721.5 1721.5 1721.5 7.3 
ptnf3 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 1099.6 
ptnm4 9.1 10.0 10.0 10.0 10.0 10.0 10.0 2356.2 2356.2 2356.2 10.0 
ptnf4 44.5 44.5 44.5 44.5 44.5 44.5 44.5 44.5 44.5 44.5 44.5 
ptnm5 10.3 11.3 11.3 11.3 11.3 11.3 11.3 2666.7 2666.7 2666.7 11.3 
ptnf5 276.2 276.2 276.2 276.2 276.2 276.2 276.2 276.2 276.2 276.2 276.2 
ptnm6 10.3 11.3 11.3 11.3 11.3 11.3 11.3 2666.7 2666.7 2666.7 11.3 
ptnf6 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 1553.3 
tswm1 57.2 59.0 59.0 59.0 59.0 59.0 59.0 694.3 694.3 694.3 59.0 
tswf1 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 1102.4 
tswm2 110.0 111.9 111.9 111.9 111.9 111.9 111.9 1317.4 1317.4 1317.4 111.9 
tswf2 530.8 530.8 530.8 530.8 530.8 530.8 530.8 530.8 530.8 530.8 530.8 
tswm3 107.4 110.7 110.7 110.7 110.7 110.7 110.7 1303.3 1303.3 1303.3 110.7 
tswf3 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 1056.7 
tswm4 90.7 92.3 92.3 92.3 92.3 92.3 92.3 1086.6 1086.6 1086.6 92.3 
tswf4 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 2126.9 
tswm5 99.0 101.5 101.5 101.5 101.5 101.5 101.5 1195.3 1195.3 1195.3 101.5 
tswf5 844.7 844.7 844.7 844.7 844.7 844.7 844.7 844.7 844.7 844.7 844.7 
tswm6 92.0 93.2 93.2 93.2 93.2 93.2 93.2 1098.1 1098.1 1098.1 93.2 
tswf6 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 
tswm7 83.6 84.6 84.6 84.6 84.6 84.6 84.6 996.5 996.5 996.5 84.6 
tswf7 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 1289.1 
tswm8 36.0 44.7 44.7 44.7 44.7 44.7 44.7 526.7 526.7 526.7 44.7 
tswf8 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 1746.2 
tswm9 36.0 44.7 44.7 44.7 44.7 44.7 44.7 526.7 526.7 526.7 44.7 
tswf9 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 1007.4 
ch1mv 152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
ch1fv 683.0 683.0 683.0 683.0 683.0 683.0 683.0 683.0 683.0 683.0 683.0 

MDL-NBS-HS-000001 REV 04 B-3 February 2005 


Drift-Scale THC Seepage Model 

Table B-2. Mineral Reactive Surface Areas (2) (Continued) 

Rock Zone Glass Hematite Calcite Stellerite Heulandite Mordenite Clinoptilolite Kaolinite Am. Silica Opal Fluorite 

ch2mv 39 152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
ch2fv 40 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 
ch3mv 41 152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
ch3fv 42 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 758.9 
ch4mz 43 152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
ch4fz 44 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
ch5mz 45 152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
ch5fz 46 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
ch6mv 47 152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
ch6fv 48 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 1016.4 
pp4m 49 
152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
pp4f 50 
1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
pp3m 51 
152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
pp3f 52 
871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 
pp2m 53 
152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
pp2f 54 
871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 871.1 
pp1m 55 
152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
pp1f 56 
1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 1570.8 
bf3m4 57 
152.6 171.9 171.9 171.9 171.9 171.9 171.9 2024.7 2024.7 2024.7 171.9 
bf3f4 58 
2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 2228.3 

Source: DTN: LB0101DSTTHCR1.004 [DIRS 161279]. 

NOTE: Each unit is listed twice, the second-to-last letter being m for matrix, and f for fracture. Units for mineral 

reactive surface areas in the matrix are cm2/g; units for the reactive surface areas of fracture minerals are 

m2/m3. 

MDL-NBS-HS-000001 REV 04 B-4 February 2005 


Drift-Scale THC Seepage Model 

APPENDIX C 
THERMODYNAMIC DATABASE 


MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

Table C-1. Thermodynamic Database: Minerals (DTN: LB0307THMDBRTM.001 [DIRS 164434]) 

Mineral 
Molecular 
Weight 
(g/mol) 
Molar 
Volume 
(cm3/mol) Reaction Stoichiometryalog (K) 
0 (C) 25 (C) 60 (C) 100 (C) 150 (C) 200 (C) 250 (C) 300 (C) 
albite-low 262.223 100.070 (1)alo2-, (1)na+, (3)sio2(aq) -21.697 -20.179 -18.365 -16.686 -15.096 -13.987 -13.293 -12.963 
anorthite 278.207 100.790 (2)alo2-, (1)ca+2, (2)sio2(aq) -21.229 -20.484 -19.640 -18.960 -18.514 -18.485 -18.839 -19.547 
calcite 100.087 36.934 (1)ca+2, (-1)h+, (1)hco3- 2.226 1.849 1.333 0.774 0.100 -0.584 -1.326 -2.215 
clinopt/10 277.660 126.410 (2.6)h2o, (0.68)alo2-, (0.28)ca+2, 
(0.08)k+, (0.04)na+,(2.92)sio2(aq) 
-20.216 -18.475 -16.703 -15.136 -13.577 -12.339 -11.395 -10.816 
clpt/10-r02 277.660 126.410 (2.6)h2o, (0.68)alo2-, (0.28)ca+2, 
(0.08)k+, (0.04)na+,(2.92)sio2(aq) 
-17.760 -16.020 -14.250 -12.680 -11.120 -9.880 -8.940 -8.360 
cristoba-a 60.084 25.740 (1)sio2(aq) -3.542 -3.192 -2.867 -2.589 -2.306 -2.071 -1.877 -1.742 
fluorite 78.075 24.542 (1)ca+2, (2)f- -10.310 -10.037 -9.907 -9.967 -10.265 -10.784 -11.555 -12.703 
gypsum 172.172 74.690 (2)h2o, (1)ca+2, (1)so4-2 -4.533 -4.482 -4.609 -4.904 -5.410 -6.058 -6.874 -7.971 
halite 58.442 27.015 (1)na+, (1)cl- 1.492 1.586 1.618 1.578 1.450 1.242 0.936 0.468 
hematite 159.688 30.274 (-1)h2o, (2)hfeo2(aq) -26.438 -23.927 -21.486 -19.661 -18.293 -17.573 -17.272 -17.248 
heuland/10 279.347 126.640 (2.6)h2o, (0.8)alo2-, (0.33)ca+2, 
(0.04)k+, (0.1)na+, (2.8)sio2(aq) 
-21.097 -19.348 -17.565 -15.992 -14.437 -13.217 -12.306 -11.779 
heul/10-r02 279.347 126.640 (2.6)h2o, (0.8)alo2-, (0.33)ca+2, 
(0.04)k+, (0.1)na+, (2.8)sio2(aq) 
-18.620 -16.870 -15.090 -13.510 -11.960 -10.740 -9.830 -9.300 
illite 378.963 135.080 (0.44)h2o, (2.06)alo2-, 
(1.12)h+,(0.5)k+, (0.22)mg+2, 
(3.72)sio2(aq) 
-45.566 -42.016 -38.333 -35.129 -32.064 -29.760 -28.120 -27.254 
kaolinite 258.160 99.520 (1)h2o, (2)alo2-, (2)h+, (2)sio2(aq) -43.234 -39.917 -36.348 -33.216 -30.252 -28.074 -26.558 -25.754 
microcline-b 278.332 108.741 (1)alo2-, (1)k+, (3)sio2(aq) -23.770 -21.820 -19.530 -17.440 -15.470 -14.080 -13.170 -12.670 
morden/10 269.631 127.350 (2.2)h2o, (0.6)alo2-, (0.15)ca+2, 
(0.09)k+, (0.21)na+, (3)sio2(aq) 
-19.244 -17.542 -15.820 -14.298 -12.776 -11.558 -10.617 -10.021 
mord/10-r02 269.631 127.350 (2.2)h2o, (0.6)alo2-, (0.15)ca+2, 
(0.09)k+, (0.21)na+, (3)sio2(aq) 
-16.950 -15.250 -13.530 -12.010 -10.480 -9.270 -8.330 -7.730 
opal-proxy 60.084 29.000 (1)sio2(aq) -3.501 -3.005 -2.627 -2.358 -2.118 -1.926 -1.765 -1.632 
quartz 60.084 22.688 (1)sio2(aq) -4.153 -3.743 -3.348 -3.006 -2.661 -2.376 -2.142 -1.976 
sepiolite 323.913 142.830 (-4)h+, (5.5)h2o, (2)mg+2, (3)sio2(aq) 17.631 15.992 13.961 12.164 10.536 9.352 8.397 7.457 
sio2(amor.) 60.084 29.000 (1)sio2(aq) -2.954 -2.670 -2.422 -2.213 -1.998 -1.815 -1.663 -1.562 

MDL-NBS-HS-000001 REV 04 C-1 February 2005 


Table C-1. Thermodynamic Database: Minerals (DTN: LB0307THMDBRTM.001 [DIRS 164434]) (Continued) 

Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 C-2 February 2005 

Mineral 
Molecular 
Weight 
(g/mol) 
Molar 
Volume 
(cm3/mol) Reaction Stoichiometryalog (K) 
0 (C) 25 (C) 60 (C) 100 (C) 150 (C) 200 (C) 250 (C) 300 (C) 
smect-ca-cal 365.394 132.510 (0.52)h2o, (1.77)alo2-, (0.145)ca+2, 
(0.96)h+, (0.26)mg+2, (3.97)sio2(aq) 
-40.190 -36.970 -33.660 -30.790 -28.010 -25.900 -24.370 -23.550 
smect-na-cal 366.250 132.510 (0.52)h2o, (1.77)alo2-, (0.96)h+, 
(0.26)mg+2, (0.29)na+, (3.97)sio2(aq) 
-40.290 -36.980 -33.560 -30.560 -27.660 -25.440 -23.820 -22.900 
smect-mg-cal 363.107 132.510 (0.52)h2o, (1.77)alo2-, (0.96)h+, 
(0.405)mg+2, (3.97)sio2(aq) 
-40.240 -37.060 -33.790 -30.950 -28.200 -26.110 -24.600 -23.790 
steller/10 281.733 133.1 (2.8)h2o, (0.79)alo2-, 
(0.39)ca+2,(0.01)na+, (2.81)sio2(aq) 
-21.144 -19.432 -17.691 -16.156 -14.636 -13.444 -12.553 -12.041 
stell/10-r02 281.733 133.1 (2.8)h2o, (0.79)alo2-, 
(0.39)ca+2,(0.01)na+, (2.81)sio2(aq) 
-18.37 -16.88 -15.4 -14.12 -12.86 -11.89 -11.2 -10.87 
sylvite 74.551 37.524 (1)k+, (1)cl- 0.525 0.846 1.122 1.285 1.330 1.238 1.013 0.604 
tridymite 60.084 26.586 (1)sio2(aq) -3.946 -3.572 -3.193 -2.834 -2.413 -1.995 -1.587 -1.203 
hydglassfe3 48.466 20.536 (-0.0006)h+, (0.5981)sio2(aq), 
(0.1180)alo2-, (0.0556)na+, 
(0.0594)k+, (0.016)ca+2, 
(0.0002)mg+2, (0.0055)hfeo2(aq), 
(0.0783)h2o 
1.646 1.462 1.209 0.978 0.759 0.584 0.415 0.211 
mgso4 120.369 45.250 (1)mg+2, (1)so4-2 6.237 4.882 3.1 1.263 -0.811 -2.748 -4.677 -6.787 
nano3 84.995 50.000 (1)na+, (1)no3- -0.811 -0.206 0.403 0.88 1.275 1.518 1.651 1.665 
k2so4 
(arcanite) 
174.260 65.500 (2)k, (1)so4-2 -2.273 -1.801 -1.469 -1.365 -1.488 -1.826 -2.365 -3.19 
na2so4 
(thenardite) 
142.043 53.330 (2)na+, (1)so4-2 -0.35 -0.309 -0.438 -0.705 -1.15 -1.716 -2.473 -3.548 
co2(g) 44.01 2.50E-10 (-1)h2o, (1)h+, (1)hco3- -7.677 -7.814 -8.053 -8.357 -8.769 -9.217 -9.720 -10.339 

a 

Negative numbers in parentheses indicate the species is on the left side of equation. 
NOTES: Mineral names or abbreviations above are those used in the database and may not exactly match names used in the text of the report. Names ending 
by /10 indicate the stoichiometry, molecular weight, molar volume, and log(K) values for those minerals were divided by 10 compared to original data. 
Glass phases glass1 and glass were used with the extended-case and base-case geochemical systems, respectively. 

Data in this Appendix are associated with input file thermok1.01.dat. 


Drift-Scale THC Seepage Model 

Table C-2. Thermodynamic Database: Aqueous Species 

Aqueous 
Species 
Molecular 
Weight 
(g/mol) rej Charge Reaction Stoichiometry 0 (C) 25 (C) 60 (C) 100 (C) 150 (C) 200 (C) 250 (C) 300 (C) 
Al+3 26.982 3.33 3 (-2)h2o, (1)alo2-, (4)h+ -25.795 -22.883 -19.571 -16.582 -13.676 -11.409 -9.598 -8.167 
Al(OH)2+ 60.996 2.31 1 (1)alo2-, (2)h+ -13.655 -12.289 -10.825 -9.600 -8.530 -7.823 -7.396 -7.238 
AlOH+2 43.989 2.8 2 (-1)h2o, (1)alo2-, (3)h+ -20.068 -17.926 -15.567 -13.519 -11.625 -10.242 -9.232 -8.547 
CO2(aq) 44.010 0 0 (-1)h2o, (1)h+, (1)hco3- -6.580 -6.345 -6.268 -6.388 -6.724 -7.197 -7.787 -8.528 
CO3-2 60.009 2.81 -2 (-1)h+, (1)hco3- 10.624 10.329 10.130 10.084 10.200 10.465 10.871 11.464 
CaCO3(aq) 100.087 0 0 (1)ca+2, (-1)h+, (1)hco3- 7.505 7.002 6.455 5.975 5.492 5.057 4.589 3.978 
CaCl+ 75.531 2.31 1 (1)ca+2, (1)cl- 0.356 0.293 0.094 -0.215 -0.682 -1.227 -1.870 -2.677 
CaCl2(aq) 110.983 0 0 (1)ca+2, (2)cl- 0.456 0.644 0.634 0.400 -0.118 -0.844 -1.802 -3.116 
CaF+ 59.076 2.31 1 (1)ca+2, (1)f- -0.655 -0.682 -0.862 -1.171 -1.650 -2.217 -2.888 -3.728 
CaHCO3+ 101.095 2.31 1 (1)ca+2, (1)hco3-
1.094 -1.047 -1.158 -1.413 -1.848 -2.383 -3.027 -3.840 
CaHSiO3+ 117.170 2.31 1 (-1)h+, (1)ca+2, (1)h2o, (1)sio2(aq) 8.778 8.575 8.115 7.596 7.043 6.588 6.200 5.837 
CaOH+ 57.085 2.31 1 (-1)h+, (1)ca+2, (1)h2o 14.085 12.833 11.416 10.142 8.903 7.928 7.126 6.434 
CaSO4(aq) 136.142 0 0 (1)ca+2, (1)so4-2 -2.071 -2.111 -2.265 -2.511 -2.910 -3.433 -4.144 -5.188 
Fe+3 55.845 3.46 3 (3)h+, (1)hfeo2(aq), (-2)h2o -14.305 -12.018 -9.602 -7.594 -5.807 -4.521 -3.530 -2.696 
FeCl+2 91.298 2.8 2 (1)cl-, (3)h+, (-2)h2o, (1)hfeo2 -15.770 -13.498 -11.217 -9.449 -8.047 -7.230 -6.813 -6.721 
FeF+2 74.843 2.8 2 (1)f-, (3)h+, (-2)h2o, (1)hfeo2(aq) -20.032 -18.018 -16.038 -14.546 -13.418 -12.827 -12.608 -12.697 
FeF2+ 93.842 2.31 1 (2)f-, (3)h+, (-2)h2o, (1)hfeo2(aq) -22.323 -20.368 -18.459 -17.037 -16.011 -15.569 -15.590 -16.086 
FeO+ 71.844 2.31 1 (1)h+, (-1)h2o, (1)hfeo2(aq) -7.324 -6.368 -5.372 -4.561 -3.865 -3.393 -3.060 -2.807 
FeO2- 87.844 1.81 -1 (-1)h+, (1)hfeo2(aq) 10.231 9.602 8.839 8.111 7.381 6.822 6.430 6.249 
FeOH+2 72.852 2.8 2 (2)h+, (-1)h2o, (1)hfeo2(aq) -11.409 -9.813 -8.174 -6.853 -5.727 -4.964 -4.415 -3.979 
FeSO4+ 151.909 2.31 1 (1)so4-2, (3)h+, (-2)h2o, (1)hfeo2(aq) -15.846 -13.946 -12.089 -10.700 -9.681 -9.213 -9.179 -9.602 
HAlO2 59.988 0 0 (1)alo2-, (1)h+ -7.080 -6.450 -5.846 -5.409 -5.119 -5.035 -5.120 -5.384 
HF 20.006 0 0 (1)f-, (1)h+ -2.985 -3.168 -3.474 -3.848 -4.338 -4.859 -5.437 -6.135 
HF2-39.005 1.81 -1 (1)h+, (2)f- -2.238 -2.551 -2.960 -3.385 -3.880 -4.374 -4.915 -5.578 
HNO3(aq) 63.013 0 0 (1)h+, (1)no3- 1.540 1.303 0.952 0.556 0.074 -0.412 -0.936 -1.579 
HSiO3-77.092 1.81 -1 (-1)h+, (1)h2o, (1)sio2(aq) 9.811 9.585 9.241 8.960 8.802 8.833 9.035 9.433 
KCl(aq) 74.551 0 0 (1)cl-, (1)k+ 2.840 2.536 2.141 1.731 1.255 0.785 0.278 -0.344 
KHSO4(aq) 136.170 0 0 (1)h+, (1)k+, (1)so4-2 2.039 1.495 0.595 -0.476 -1.817 -3.172 -4.601 -6.242 
KOH(aq) 56.106 0 0 (-1)h+, (1)h2o, (1)k+ 15.498 14.439 13.314 12.378 11.552 10.978 10.570 10.267 
KSO4-135.162 1.81 -1 (1)k+, (1)so4-2 -0.886 -0.880 -0.991 -1.195 -1.521 -1.921 -2.419 -3.090 
MgCO3(aq) 84.314 0 0 (-1)h+, (1)hco3-, (1)mg+2 7.742 7.350 6.929 6.574 6.228 5.911 5.543 5.019 
MgCl+ 59.758 2.31 1 (1)cl-, (1)mg+2 0.097 0.135 0.041 -0.173 -0.537 -0.992 -1.550 -2.276 
MgF+ 43.303 2.31 1 (1)f-, (1)mg+2 -1.387 -1.352 -1.478 -1.739 -2.169 -2.691 -3.321 -4.125 
MgHCO3+ 85.322 2.31 1 (1)hco3-, (1)mg+2 -1.077 -1.036 -1.160 -1.423 -1.852 -2.369 -2.984 -3.758 
MgHSiO3+ 101.397 2.31 1 (-1)h+, (1)h2o, (1)mg+2, (1)sio2(aq) 8.454 8.325 7.943 7.501 7.036 6.666 6.358 6.072 

MDL-NBS-HS-000001 REV 04 C-3 February 2005 


Table C-2. Thermodynamic Database: Aqueous Species (Continued) 

Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 C-4 February 2005 

Aqueous 
Species 
Molecular 
Weight 
(g/mol) rej Charge Reaction Stoichiometry 0 (C) 25 (C) 60 (C) 100 (C) 150 (C) 200 (C) 250 (C) 300 (C) 
MgOH+ 41.312 2.31 1 (-1)h+, (1)h2o, (1)mg+2 12.674 11.683 10.502 9.399 8.291 7.392 6.634 5.967 
MgSO4(aq) 120.369 0 0 (1)mg+2, (1)so4-2 -2.184 -2.230 -2.393 -2.641 -3.031 -3.539 -4.236 -5.271 
NaCO3-82.999 1.81 -1 (-1)h+, (1)hco3-, (1)na+ 9.725 9.815 9.917 10.012 10.104 10.177 10.236 10.285 
NaCl(aq) 58.442 0 0 (1)cl-, (1)na+ 0.829 0.777 0.651 0.473 0.214 -0.093 -0.478 -1.013 
NaF(aq) 41.988 0 0 (1)f-, (1)na+ 1.082 0.998 0.833 0.623 0.338 0.010 -0.397 -0.957 
NaHCO3(aq) 84.007 0 0 (1)hco3-, (1)na+ -0.398 -0.154 0.075 0.244 0.358 0.374 0.277 0.004 
NaHSiO3(aq) 100.081 0 0 (-1)h+, (1)h2o, (1)na+, (1)sio2(aq) 7.603 7.754 7.780 7.795 7.873 8.014 8.190 8.365 
NaOH(aq) 39.997 0 0 (-1)h+, (1)h2o, (1)na+ 15.132 14.205 13.210 12.377 11.642 11.130 10.762 10.480 
NaSO4-119.053 1.81 -1 (1)na+, (1)so4-2 -0.677 -0.700 -0.842 -1.063 -1.389 -1.772 -2.242 -2.873 
OH-17.007 1.4 -1 (-1)h+, (1)h2o 14.940 13.995 13.027 12.255 11.631 11.284 11.168 11.300 
SiF6-2 142.076 3 -2 (-2)h2o, (1)sio2(aq), (4)h+, (6)f--27.654 -26.275 -25.220 -24.654 -24.534 -24.919 -25.819 -27.436 

Source: DTN: LB0307THMDBRTM.001 [DIRS 164434]. 
Table C-3. Primary Aqueous Basis Species 


Primary 
Aqueous 
Species 
Molecular 
Weight 
(g/mol) rej Charge 
H2O 18.015 0.00 0 
AlO2-58.980 1.81 -1 
Ca+2 40.078 2.87 2 
Cl-35.453 1.81 -1 
F18.998 
1.33 -1 
H+ 1.008 3.08 1 
HCO3-61.017 2.10 -1 
HFeO2(aq) 88.852 0.00 0 
K+ 39.098 2.27 1 
Mg+2 24.305 2.54 2 
Na+ 22.990 1.91 1 
NO3-62.005 2.81 -1 
SiO2(aq) 60.084 0.00 0 
SO4-2 96.064 3.15 -2 

Source: DTN: LB0307THMDBRTM.001 [DIRS 164434]. 


Drift-Scale THC Seepage Model 

APPENDIX D 
WASTE PACKAGE AVERAGE HEAT TRANSFER 


MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

Table D-1. Waste Package Average Heat Transfer 

Time 
(years) 
Total Heat 
(no ventilation) 
(W/meter) 
Model Heat Load 
(W/meter) 
0 1450.000 198.650 
1 1400.000 191.800 
2 1360.000 186.320 
3 1320.000 180.840 
4 1290.000 176.730 
5 1260.000 172.620 
6 1230.000 168.510 
7 1210.000 165.770 
8 1180.000 161.660 
9 1160.000 158.920 
10 1140.000 156.180 
11 1110.000 152.070 
12 1090.000 149.330 
13 1070.000 146.590 
14 1050.000 143.850 
15 1030.000 141.110 
16 1010.000 138.370 
17 995.000 136.315 
18 978.000 133.986 
19 961.000 131.657 
20 946.000 129.602 
21 929.000 127.273 
22 912.000 124.944 
23 897.000 122.889 
24 882.000 120.834 
25 868.000 118.916 
26 854.000 116.998 
27 840.000 115.080 
28 826.000 113.162 
29 813.000 111.381 
30 801.000 109.737 
31 787.000 107.819 
32 775.000 106.175 
33 762.000 104.394 
34 751.000 102.887 
35 740.000 101.380 
36 728.000 99.736 
37 716.000 98.092 
38 706.000 96.722 
39 695.000 95.215 
40 685.000 93.845 
41 675.000 92.475 

MDL-NBS-HS-000001 REV 04 D-1 February 2005 


Drift-Scale THC Seepage Model 

Table D-1. Waste Package Average Heat Transfer (Continued) 

Time 
(years) 
Total Heat 
(no ventilation) 
(W/meter) 
Model Heat Load 
(W/meter) 
42 665.000 91.105 
43 655.000 89.735 
44 646.000 88.502 
45 636.000 87.132 
46 627.000 85.899 
47 618.000 84.666 
48 609.000 83.433 
49 601.000 82.337 
50 593.000 81.241 
50.001 593.000 593.000 
51 585.000 585.000 
52 577.000 577.000 
53 569.000 569.000 
54 561.000 561.000 
55 554.000 554.000 
56 547.000 547.000 
57 539.000 539.000 
58 532.000 532.000 
59 526.000 526.000 
60 519.000 519.000 
61 512.000 512.000 
62 506.000 506.000 
63 500.000 500.000 
64 494.000 494.000 
65 488.000 488.000 
66 482.000 482.000 
67 476.000 476.000 
68 470.000 470.000 
69 465.000 465.000 
70 460.000 460.000 
71 454.000 454.000 
72 449.000 449.000 
73 444.000 444.000 
74 439.000 439.000 
75 434.000 434.000 
76 430.000 430.000 
77 425.000 425.000 
78 420.000 420.000 
79 416.000 416.000 
80 412.000 412.000 
81 407.000 407.000 

MDL-NBS-HS-000001 REV 04 D-2 February 2005 


Drift-Scale THC Seepage Model 

Table D-1. Waste Package Average Heat Transfer (Continued) 

Time 
(years) 
Total Heat 
(no ventilation) 
(W/meter) 
Model Heat Load 
(W/meter) 
82 403.000 403.000 
83 399.000 399.000 
84 395.000 395.000 
85 391.000 391.000 
86 387.000 387.000 
87 383.000 383.000 
88 379.000 379.000 
89 376.000 376.000 
90 372.000 372.000 
91 369.000 369.000 
92 365.000 365.000 
93 362.000 362.000 
94 359.000 359.000 
95 355.000 355.000 
96 352.000 352.000 
97 349.000 349.000 
98 346.000 346.000 
99 343.000 343.000 
100 340.000 340.000 
110 315.000 315.000 
120 294.000 294.000 
140 259.000 259.000 
150 245.000 245.000 
160 235.000 235.000 
170 225.000 225.000 
180 216.000 216.000 
190 208.000 208.000 
200 201.000 201.000 
250 176.000 176.000 
300 159.000 159.000 
350 145.000 145.000 
400 134.000 134.000 
450 125.000 125.000 
500 117.000 117.000 
550 110.000 110.000 
600 103.000 103.000 
650 97.300 97.300 
700 92.100 92.100 
750 87.200 87.200 
800 82.800 82.800 
850 78.800 78.800 
900 75.000 75.000 

MDL-NBS-HS-000001 REV 04 D-3 February 2005 


Drift-Scale THC Seepage Model 

Table D-1. Waste Package Average Heat Transfer (Continued) 

Time 
(years) 
Total Heat 
(no ventilation) 
(W/meter) 
Model Heat Load 
(W/meter) 
950 71.600 71.600 
1000 68.400 68.400 
1500 47.300 47.300 
2000 37.200 37.200 
2500 32.100 32.100 
3000 29.300 29.300 
3500 27.500 27.500 
4000 26.200 26.200 
4500 25.200 25.200 
5000 24.200 24.200 
5500 23.400 23.400 
6000 22.600 22.600 
6500 21.800 21.800 
7000 21.100 21.100 
7500 20.500 20.500 
8000 19.800 19.800 
8500 19.200 19.200 
9000 18.600 18.600 
9500 18.000 18.000 
10000 17.500 17.500 
15000 13.200 13.200 
20000 10.200 10.200 
25000 8.210 8.210 
30000 6.760 6.760 
35000 5.680 5.680 
40000 4.850 4.850 
45000 4.190 4.190 
50000 3.680 3.680 
55000 3.250 3.250 
60000 2.880 2.880 
65000 2.580 2.580 
70000 2.330 2.330 
75000 2.110 2.110 
80000 1.910 1.910 
85000 1.750 1.750 
90000 1.640 1.640 
95000 1.520 1.520 
100000 1.400 1.400 

Source: BSC 2002 [DIRS 159527], Sheet 5 of 5 (Section 4.1.7). 

NOTE: Point at 50.001 years was interpolated between original data points at 
50 and 55 years. From 0 to 50 years: Model Heat Load = Total Heat  
(1-0.863) [86.3% heat removal]. 

MDL-NBS-HS-000001 REV 04 D-4 February 2005 


Drift-Scale THC Seepage Model 

APPENDIX E 
EFFECTIVE THERMAL CONDUCTIVITY FOR IN-DRIFT OPEN SPACES


MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 February 2005 


Drift-Scale THC Seepage Model 

Table E-1. Effective Thermal Conductivity for In-Drift Open Spaces during 
Preclosure 

Time(sec) (year) 
Factor 
3.15360E+03 0.0 0.395 
3.15360E+07 1.0 0.777 
4.73040E+07 1.5 0.825 
6.30720E+07 2 0.856 
9.46080E+07 3 0.898 
1.26144E+08 4 0.921 
1.57680E+08 5 0.939 
1.89216E+08 6 0.955 
2.20752E+08 7 0.966 
2.52288E+08 8 0.975 
2.83824E+08 9 0.982 
3.15360E+08 10 0.988 
3.46896E+08 11 0.993 
3.78432E+08 12 0.997 
4.73040E+08 15 1 
6.30720E+08 20 0.993 
7.88400E+08 25 0.977 
8.19936E+08 26 0.974 
8.51472E+08 27 0.97 
9.46080E+08 30 0.958 
1.10376E+09 35 0.936 
1.26144E+09 40 0.915 
1.57680E+09 50 0.879 

Source: DTN: SN0002T0872799.009 [DIRS 153364], file tough2-input_noBF.txt in zip 
file effKth_noBF.zip. 
NOTES: Kthermal is calculated as Max. Kthermal  Factor. 
Maximum Kthermal (W/m-K) = 10.568. 

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Table E-2. Effective Thermal Conductivity for In-Drift Open Spaces during 
Postclosure (No Backfill) 

Time(sec) (year) 
Factor 
Inner Outer 
1.57680E+09 50 0.879 0.879 
1.608336E+09 51 0.844 0.829 
1.639872E+09 52 0.892 0.878 
1.734480E+09 55 0.951 0.944 
1.892160E+09 60 0.988 0.986 
2.049840E+09 65 1 1 
2.207520E+09 70 0.995 0.998 
2.365200E+09 75 0.985 0.99 
2.396736E+09 76 0.983 0.988 
2.428272E+09 77 0.981 0.986 
2.522880E+09 80 0.973 0.98 
2.838240E+09 90 0.954 0.963 
3.153600E+09 100 0.932 0.943 
3.185136E+09 101 0.929 0.941 
3.311280E+09 105 0.918 0.929 
3.468960E+09 110 0.905 0.917 
3.784320E+09 120 0.882 0.896 
4.099680E+09 130 0.872 0.886 
4.415040E+09 140 0.864 0.879 
5.045760E+09 160 0.852 0.869 
5.676480E+09 180 0.839 0.857 
6.307200E+09 200 0.83 0.849 
6.937920E+09 220 0.818 0.838 
7.884000E+09 250 0.798 0.818 
9.460800E+09 300 0.763 0.784 
1.103760E+10 350 0.736 0.758 
1.261440E+10 400 0.707 0.729 
1.419120E+10 450 0.689 0.711 
1.576800E+10 500 0.677 0.7 
1.734480E+10 550 0.672 0.694 
1.892160E+10 600 0.667 0.69 
2.207520E+10 700 0.656 0.68 
2.522880E+10 800 0.646 0.67 
2.838240E+10 900 0.637 0.661 
3.153600E+10 1000 0.627 0.651 
3.468960E+10 1100 0.619 0.643 
3.784320E+10 1200 0.611 0.635 

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Table E-2. Effective Thermal Conductivity for In-Drift Open Spaces during 
Postclosure (No Backfill) (Continued) 

Time(sec) (year) 
Factor 
Inner Outer 
4.099680E+10 1300 0.602 0.626 
4.415040E+10 1400 0.592 0.616 
4.730400E+10 1500 0.582 0.605 
5.045760E+10 1600 0.574 0.597 
5.676480E+10 1800 0.559 0.583 
6.307200E+10 2000 0.543 0.566 
6.937920E+10 2200 0.533 0.555 
7.884000E+10 2500 0.519 0.541 
9.460800E+10 3000 0.503 0.523 
1.103760E+11 3500 0.491 0.51 
1.261440E+11 4000 0.48 0.499 
1.419120E+11 4500 0.472 0.491 
1.576800E+11 5000 0.465 0.484 
1.892160E+11 6000 0.453 0.471 
2.207520E+11 7000 0.444 0.461 
2.522880E+11 8000 0.436 0.452 
3.153600E+11 10000 0.422 0.438 
4.730400E+11 15000 0.395 0.411 
6.307200E+11 20000 0.378 0.393 
9.460800E+11 30000 0.354 0.367 
1.261440E+12 40000 0.341 0.354 
1.576800E+12 50000 0.333 0.346 
1.892160E+12 60000 0.326 0.339 
2.522880E+12 80000 0.318 0.33 
3.153600E+12 100000 0.314 0.325 

Source: DTN: SN0002T0872799.009 [DIRS 153364], file tough2-input_noBF.txt in 
zip file effKth_noBF.zip. 
NOTES: Kthermal is calculated as Max. Kthermal  Factor. 
Maximum Kthermal (W/m-K) Inner=2.298, Outer=14.407. 

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INTENTIONALLY LEFT BLANK 


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APPENDIX F 
PARAMETERS FOR FRACTURE PERMEABILITY MODIFICATION 


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Table F-1. Parameters for Fracture Permeability Modification 

Rock Unit a-parameter b-parameter 
tcw11 1.5385E-02 1.0870 
tcw12 1.2696E-03 0.5236 
tcw13 3.4483E-03 0.3584 
ptn21 9.2000E-03 1.4925 
ptn22 7.0922E-03 2.1739 
ptn23 1.2000E-03 1.7544 
ptn24 2.9412E-02 2.1739 
ptn25 5.0459E-03 1.9231 
ptn26 8.7079E-04 1.0309 
tsw31 1.2953E-03 0.4608 
tsw32 2.5857E-03 0.8929 
tsw33 1.3063E-03 1.2346 
tsw34 6.2777E-04 0.2315 
tsw35 9.9174E-04 0.3165 
tsw3[67] 1.0561E-03 0.2488 
tsw38 8.2459E-04 0.2294 
tsw39 1.4576E-03 1.0417 
ch1Ze 1.4545E-03 25.0000 
ch1VI 2.0333E-03 10.0000 
ch[23456]VI 1.7907E-03 7.1429 
ch[2345]Ze 8.6047E-04 7.1429 
ch6 1.4545E-03 25.0000 
pp4 8.6047E-04 7.1429 
pp3 1.5902E-03 5.0000 
pp2 1.5902E-03 5.0000 
pp1 8.6047E-04 7.1429 
bf3 1.5902E-03 5.0000 
bf2 8.6047E-04 7.1429 
tr3 1.5902E-03 5.0000 
tr2 8.6047E-04 7.1429 

NOTE: The calculation and use of the a and b parameters are presented in Section 6.4.4.2. 
Parameter a (bg) is calculated using Equation 6.4-20. Parameter b is the inverse of the 
fracture frequency (derived from DTN: LB0205REVUZPRP.001 [DIRS 159525]). 

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INTENTIONALLY LEFT BLANK


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APPENDIX G 
LIST OF MODEL INPUT AND OUTPUT FILES 


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G.1 INPUT AND OUTPUT FILES 
The following types of files were submitted for REV02 of this report to the TDMS under 
DTN: LB0307DSTTHCR2.001 and LB0302DSCPTHCS.001. They represent the current 
output THC seepage model; this revision of the report (REV04), does not produce new outputs. 

1. Input and output files of simulations with the reactive transport code TOUGHREACT V3.0 
(LBNL 2002 [DIRS 161256]). For each simulation, these files were concatenated into one 
file using the Unix tar utility, then compressed using the Unix gzip utility. Resulting 
concatenated/compressed files have the extension .tar.gz. 
2. Summary Excel spreadsheets of seepage model output data at locations adjacent to the drift 
wall (crown, side, and base). 
3. Spreadsheets containing calculations have been included as part of several DTNs in order to 
document the embedded calculations and supplement the Scientific Notebooks. Readme.doc 
files in each output DTN contain a general description of the spreadsheets contained therein. 
Spreadsheets are annotated with descriptions of the calculations performed, commonly on a 
separate notes worksheet. The calculations can be observed by clicking on the spreadsheet 
cells or selecting the Tools\Options\View\Formulas option in Excel. In addition, the cell 
references in the equations show all cells used as input to the calculation executed in the 
spreadsheet. The formulae in the submitted spreadsheets use the standard functions of MS 
Excel 97. 
DST THC Submodel Input and Output File Folders (Simulations in Section 7.1.8.2) 
(DTN: LB0307DSTTHCR2.001) 
dstrev2_th12 
dstrev2_th13 
dstrev2_thc7 
dstrev2_thc8 
dstrev2_thc9 

More complete descriptions can be found in Section 7.1. 

Tptpll THC Seepage Model Input and Output File Folders (Simulations listed in Table 6.5-4) 

(DTN: LB0307DSTTHCR2.001) 
th6_1.45kw ( _, _a, _b, _c) 
thc6_w0e3 ( _, _a, _b2, _b, bb, _c, _d) 
thc6_w0a (_b, _c, _d) 
thc6_w0b ( _, _a, _b, _bb, _c, _d) 
thc25_w0 ( _, _a, _b, _c, _d) 
thc6_w0_q 
thc6_w0_q1 
thc6_w0amb 
thc6_w0amb1 
thc6_w4amb1 
thc6_w5amb1 

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thc6_w6amb1 

(DTN: LB0404DSTTHCR2.001) 
th6_1.45kw_i1 ( _, _a, _b, _c) 
thc6_w0_i1 ( _, _a, _b, _bb, _c, _d) 
thc6_w0b_i1 ( _, _a, _b, _bb, _c, _d) 

(DTN: LB0302DSCPTHCS.001) 
thc6_w0 ( _, _a, _b, _bb, _c, _d) 
thc6_w4 ( _, _a, _b, _bb, _c, _d) 
thc6_w5 ( _, _a, _b, _bb, _c, _d) 
thc6_w6 ( _, _a, _b, _bb, _c, _d) 
thc6_w7 ( _, _a, _b, _bb, _c, _d) 

G.2 CONTENTS OF .tar.gz FILES 
Note: Some file names are lowercase in TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256]) 
and uppercase in earlier versions. 

flow.inp Rock thermal and hydrologic properties, run flags, and other specifications 
(input) 
flow.out Thermal and hydrologic results (gas/liquid saturation, T, P, air mass 

fraction, etc.) (output) 
GENER Infiltration rates, heat load, and effective thermal conductivity (input) 
INCON Initial thermal and hydrologic conditions (T, P, liquid saturation, etc.) 

(input) 
MESH Input numerical mesh (input) 
SAVE Thermal and hydrologic conditions (T, P, liquid saturation, etc.) to use for 

restarting a run (output, same format as INCON file) 
TABLE Miscellaneous output data 
VERS Miscellaneous output data 
LINEQ Miscellaneous output data 
CHEMICAL.INP Water chemistry, mineralogy, and CO2 partial pressure data (input) 
CHEMICAL.OUT Echo of data read in CHEMICAL.INP 
SOLUTE.INP Run flags and other data relating to reactive transport (input) 
SOLUTE.OUT Echo of data read in SOLUTE.INP 
thermk1.01.dat Thermodynamic database for REV02 (input). Note: The solid KNO3 in 

this file is actually NaNO3. 

TEC_CONC.DAT Calculated concentrations of aqueous species (moles/liter) at each grid 
node (two records for each node  first record for fractures and second 
record for matrix) (output) 

TEC_MIN.DAT Calculated volume fraction change for minerals at each grid node (two 
records for each node  first record for fractures and second record for 
matrix) (output) 

TEC_GAS.DAT Calculated CO2 volume fraction at each grid node (two records for each 
node  first record for fractures and second record for matrix) (output) 
TIME.DAT Chemical data at selected grid nodes (output) 

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chdump.dat Chemical speciation of initial water (output) and nodes with convergence 

problems 
inchem Chemistry data at all grid nodes to use for restarting a run (input) 
savechem Chemistry data at all grid nodes to use for restarting a run (output, same 

format as INCHEM file) 
ITER.DAT Iteration information (output) 
runlog.dat (run_log.dat) Miscellaneous run-time information. Note: mass balances may not be 

printed out correctly in this file for runs that have been restarted (i.e., 
starting at times different than zero). 

mbalance.out Mass balance information for chemical species Note: mass balances may 
not be accurate for runs that have been restarted (i.e., starting at times 
different than zero). Also, mass balances do not reflect mass loss by 
transport into large boundary grid blocks. 

GASOBS.DAT optional tabular flow output for individual grid blocks 

G.3 SUMMARY SPREADSHEETS OF THC SEEPAGE MODELS OUTPUT DATA 
(ALSO USED FOR PLOTTING TIME PROFILES AND TABULATING 
STANDARD DEVIATION) 
The data in these files were extracted from output files FLOW.OUT, TEC_CONC.DAT, 
TEC_MIN.DAT, and TEC_GAS.DAT for each simulation and submitted to the TDMS under 
DTNs: LB0302DSCPTHCS.002 and LB0307DSTTHCR2.002. 

Tptpll THC Model (TOUGHREACT V3.0 (LBNL 2002 [DIRS 161256])) 
(extended-case only, simulations details listed in Table 6.5-4) 

(DTN: LB0302DSCPTHCS.002) 
thc6_w0_r.xls THC, Water W0, 6/16/25 mm/yr (track wet nodes) 
thc6_w0_drift_r.xls THC, Water W0, 6/16/25 mm/yr (drift wall only) 
thc6_w4_r.xls THC, Water W4, 6/16/25 mm/yr (track wet nodes) 
thc6_w4_drift_r.xls THC, Water W4, 6/16/25 mm/yr (drift wall only) 
thc6_w5_r.xls THC, Water W5, 6/16/25 mm/yr (track wet nodes) 
thc6_w5_drift_r.xls THC, Water W5, 6/16/25 mm/yr (drift wall only) 
thc6_w6_r.xls THC, Water W6, 6/16/25 mm/yr (track wet nodes) 
thc6_w6_drift_r.xls THC, Water W6, 6/16/25 mm/yr (drift wall only) 
thc6_w7_r.xls THC, Water W7, 6/16/25 mm/yr (track wet nodes) 
thc6_w7_drift_r.xls THC, Water W7, 6/16/25 mm/yr (drift wall only) 


(DTN: LB0307DSTTHCR2.002) 
th6_1.45kw.xls TH, 6/16/25 mm/yr 
thc25_w0.xls THC, Water W0, 25 mm/yr (track wet nodes) 
thc25_w0_drift.xls THC, Water W0, 25 mm/yr (drift wall only) 
thc6_w0e3.xls THC, Water W0, 6/16/25 mm/yr, EOS3 (track wet nodes) 
thc6_w0e3_drift.xls THC, Water W0, 6/16/25 mm/yr, EOS3 (drift wall only) 
thc6_w0b.xls THC, Water W0, 6/16/25 mm/yr, DCO2 change (track wet nodes) 
thc6_w0b_drift.xls THC, Water W0, 6/16/25 mm/yr, DCO2 change (drift wall only) 
thc6_w0a.xls THC, Water W0, 6 mm/yr (track wet nodes) 


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thc6_w0a_drift.xls THC, Water W0, 6 mm/yr (drift wall only) 
thc6_w0_amb1.xls THC, Water W0, no heat load, 6/16/25 mm/yr (drift wall only) 
wo_4_5_6_7.xls THC, Water W0, W4, W5, W6, and W7, 6/15/25 mm/yr, track wet 


nodes (concentrations of data from files listed above under DTN: 
LB0302DSCPTHCS.002) 
hisat_top-w04567.xls Filtered data from w0-4-5-6-7.xls, used to tabulate standard deviations 
in Table 6.9-2 

(DTN: LB0404DSTTHCR2.002) 
th6_1.45kw_i1.xls TH, 6/16/25 mm/yr (drift wall only) 
thc6_w0_i1.xls THC, Water W0, 6/16/25 mm/yr (track wet nodes) 
thc6_w0_drift_i1.xls THC, Water W0, 6/16/25 mm/yr (drift wall only) 
thc6_w0b_i1.xls THC, Water W0, 6/16/25 mm/yr, DCO2 change (track wet nodes) 
thc6_w0b_drift_i1.xls THC, Water W0, 6/16/25 mm/yr, DCO2 change (drift wall only)


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APPENDIX H 

QUALIFICATION OF MINERAL DISSOLUTION/PRECIPITATION KINETICS DATA 
(MINERAL DISSOLUTION RATE CONSTANTS AND ACTIVATION ENERGIES) IN 
DTN: LB0307KNTDBRTM.001 [DIRS 164433] FOR USE IN THC COUPLED PROCESS 
MODELING 

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This appendix documents the qualification of mineral dissolution rate constants (k+) and 
activation energies (Ea) in DTN: LB0307KNTDBRTM.001 [DIRS 164433], and serves as the 
data qualification report for that DTN. This data qualification effort has been carried out as 
described in the Data Qualification Plan that is included in the records package for this report. A 
facsimile of the Data Qualification Plan is included in Section H.17 of this appendix. 

H.1 EVALUATION CRITERIA 
The data being qualified are the mineral dissolution rate constants (k+) and activation energies 
(Ea) given in DTN: LB0307KNTDBRTM.001 [DIRS 164433], which is provided in Table H.3-1 
for convenience. A subset of these values is used in this report, as listed in Table 4.1-3 of this 
document. All of these values are unqualified data. The qualification of unqualified data must 
be done in accordance with LP-SIII.2Q-BSC, Qualification of Unqualified Data. This procedure 
lists five methods for qualification, summarized (and in some cases abridged) as follows: 

Criterion 1Equivalent QA Program. The Equivalent QA Program approach 
may be used for the qualification of unqualified data when the acquisition, 
development, or processing of data can be demonstrated to be functionally 
equivalent (i.e., similar in scope and implementation) to the general process 
requirements of the QARD. The employed practices or procedures must 
demonstrate industry acceptable scientific, engineering, or administrative 
practices or processes with appropriate documentation as defined in this 
procedure. 

Criterion 2Corroborating Data. The Corroborating Data approach may be 
used when data comparisons can be shown to substantiate or confirm parameter 
values. The corroborating data qualification process may include comparisons of 
unqualified data to unqualified data, as well as unqualified data to qualified data 
with appropriate compliance documentation as defined in this procedure. 

Criterion 3Confirmatory Testing. The Confirmatory Testing approach may be 
used when previous test results are non-verifiable as a result of questionable 
testing methodology or a lack of applicable documentation. Consideration must 
be given to confirmatory testing resource and schedule requirements, to ensure 
confirmatory testing is a viable qualification option within the projects funding 
and time constraints. Confirmatory test results must demonstrate direct 
correlation to previous test results; however, data extrapolation is acceptable 
within the limits defined in the compliance documentation defined in this 
procedure. 

Criterion 4Peer Review. Peer reviews may be initiated per AP-2.12Q. The 
Qualification Team will evaluate the data acquisition and development approach. 
The team will also summarize and evaluate the assumptions, calculations, 
extrapolations, alternative interpretations, methodology, acceptance criteria, and 
conclusions in data being qualified, as applicable. The team will compile 
supporting records and present the teams evaluation and supporting records 
package to a Peer Review Panel convened in accordance with AP-2.12Q. The 

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Peer Review Panel will review the evaluation and supporting documentation, 
assess the adequacy of the data being qualified, and document their conclusions in 
a report in accordance with AP-2.12Q. Under this method, the Qualification 
Teams evaluation and the peer review Panel Report will be the documentation of 
the qualification process. 

Criterion 5Technical Assessment. The Technical Assessment approach may 
be used when it is determined that an independent evaluation of the data by a 
subject matter expert is needed to raise the confidence of the data to a proper level 
for the intended use. Either of the following conditions could require use of the 
Technical Assessment approach: 

a) The confidence in the data is in question because data collection procedures 
are unavailable for review, or the procedures are not adequate. 

b) Documentation or proof of proper data acquisition is unavailable for review. 

The mineral dissolution rate constants (k+) and activation energies (Ea) presented in Table H.1-3 
are a composite of experimental-based values for some minerals, along with estimated values for 
other minerals. Different criteria will apply to experimental and estimated values. 

Mineral dissolution rate measurements are made at relatively few laboratories, and require 
experienced personnel to make reliable measurements. The following criterion is given in 
LP-SIII.2Q-BSC: 

Consideration must be given to confirmatory testing resources and schedule 
requirements to ensure confirmatory testing is a viable qualification option within 
the projects funding and time constraints. 

Given the projects resources and schedule requirements, the use of Criterion 3, Confirmatory 
Testing, is not a viable option for qualification of the mineral dissolution rate constants and 
activation energies database, and it will not be used as a data qualification method in this report. 

The experimental mineral dissolution rate constants and activation energies in this report are 
taken from papers published in peer-reviewed journals, and therefore they have already 
undergone a peer review by several experts in this field of study. However, peer review 
comments for journal papers are not available to the general public, nor are the names of the 
reviewers. Likewise, the responses of the authors and the changes that were made to resolve 
issues raised in the peer reviews are not available. Therefore, the level of documentation for the 
journal peer reviews is not adequate for the present needs, although such reviews do guarantee 
that most of the obvious quality-affecting issues will have been resolved prior to publication of 
these journal papers. Given the projects resources and schedule requirements, the use of 
Criterion 4, Peer Review, within the guidelines of LP-SIII.2Q-BSC, is not a viable option for 
qualification of the mineral dissolution rate constants and activation energies database, and it will 
not be used here. 

Four of the referenced studies were done with YMP support, and one was done with NRC 
support; these studies are those reported by Carroll et al. (1998 [DIRS 124275]), Murphy et al. 

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(1996 [DIRS 142167]), Ragnarsdttir (1993 [DIRS 126601]), and Renders et al. (1995 
[DIRS 107088]). Although these studies were performed using well-documented experimental 
methods, and the resulting information is presented in these reports with sufficient detail to 
assess their reliability, neither these nor the other published experimental studies yielding 
mineral dissolution rate constants and activation energies were performed under a formal YMP 
QA program. Thus, Criterion 1, Equivalent QA Program, will not be used here. 

The Data Qualification for the mineral dissolution rate constants (k+) and activation energies (Ea) 
will be done by use of Criterion 5, Technical Assessment, and/or by Criterion 2, Corroborating 
Data, when corroborating studies are available to allow for comparison of independently 
measured rate constants and activation energies. However, the assessed table of mineral 
dissolution rate constants and activation energies is a composite of experimental-based values 
along with estimated values for systems either lacking such data or with incomplete data. 

H.2 SOME GENERAL CONSIDERATIONS 
The selected experimental mineral dissolution rate constants and activation energies are based on 
measurements using well-characterized mineral samples with adequately described experimental 
methods. However, the tabulated dissolution rate constants depend inversely on the estimated 
surface area of the mineral grains used for the experiments. The usual method of determining 
mineral surface areas is by using gas absorption measured with the BET (Brunauer, Emmet, 
Teller) static volume method. This type of surface-area measurement is made using a non-
reacting gas, generally nitrogen, krypton, or argon. BET measurements using different gases do 
not yield the same estimated surface areas. For example, Ragnarsdttir (1993 [DIRS 126601], 

p. 2441]) determined the surface area of a crushed sample of heulandite as being 
1715  11 cm2 g1 using krypton BET measurements, and 4176  2435 cm2 g1 using nitrogen 
BET measurements. Surface-area measurements using the inert gases are generally considered 
to be more reliable than those using nitrogen gas. However, because three different gases were 
used among the various mineral dissolution studies cited above, any comparison of numerical 
mineral dissolution and precipitation rate constants needs to consider the uncertainties resulting 
from the surface-area measurements. 
With the exception of a few simple minerals such as quartz and hematite, most natural minerals 
show significant variations in the composition of samples collected at different locations and 
even of different samples taken from the same deposit. For example, Murphy et al. (1996 
[DIRS 142167, pp. 133, 139, and 129]) cited the chemical composition of a clinoptilolite from 
Lake Tecopa, Inyo County, California, as being 

(Na0.56K0.98Ca1.50Mg1.23)(Al6.7Fe0.3)Si29O7222H2O 

and another one from Malheur County, Oregon as being 

(Na0.954K0.543)(Ca0.761Mg0.124Ba0.062Sr0.036Mn0.0.002)(Al3.450Fe0.017 Si14.553)O3610.922H2O. 

They also reported analysis results for a Na-clinoptilolite from Death Valley Junction, California, 
yielding a composition of 

(Na1.804K0.123Ca0.003Mg0.035)(Al1.947Fe0.044)(Si10.002Ti0.004)O247.43H2O. 

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They gave the formula of the idealized (pure) Na-clinoptilolite as being 

Na2Al2Si10O248H2O. 

These different formulae are based on use of different-sized structural formula units, and can be 
compared on an equivalent basis by normalizing them to the same number of (nonwater) 
oxygens. However, even without this normalization, it is apparent from these few sample 
compositions that clinoptilolite and most other natural minerals show significant variations in 
chemical composition for samples collected at different locations. 

H.3 SUMMARY OF EXPERIMENTAL MINERAL DISSOLUTION RATE 
CONSTANTS AND ACTIVATION ENERGIES 
The information in DTN: LB0307KNTDBRTM.001 [DIRS 164433] is repeated in Table H.3-1, 
along with the qualification method(s) used for each quantity. The listed values of the mineral 
dissolution rate constants are for the temperature 298.15 K and neutral to near-neutral pHs. The 
corresponding data for muscovite have also been added to this table because they are the source 
for estimated values of the dissolution rate constants and activation energies for several other 
clay minerals. 

The tabulated experimental rate constants at 298.15 K (25C) are given to the same number of 
significant figures as reported in the source documents (i.e., generally to two or three significant 
figures). However, because of the uncertainties introduced by the surface-area determinations, 
and because of the natural variation in chemical composition of most minerals, the listed values 
of the experimental rate constants at 298.15 K should be considered uncertain by approximately 
a factor of 10 when applied to mineral samples from different locations having significantly 
different chemical compositions. 

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Drift Scale THC Seepage Model 

Table H.3-1. Mineral Dissolution/Precipitation Reaction Rate Constants (k+/) and Activation Energies (Ea) to Be Qualified 

MINERAL 
k+/-(mol m2 
s1)(a) 
at 298.15 K 
Ea 
(kJ/mol)(b) m(c) 
n(c) 
Formula Used to 
Calculate Rate 
Constant(d) Comment (e) Reference 
Qualification 
Method(s)(f) 
a-Cristobalite 
SiO2 
3.45  1013 68.9 ( 11) 1 1 lnk+ = (-0.9)  Ea / 
(R  T(K)) 
Dissolution, no 
precipitation 
Renders et al. 1995 [DIRS 
107088], pp. 77, 81 
C 
Quartz 
SiO2 
4.52  1014 90.1 ( 2.5) 1 1 kf, geom. = (276  
193) exp[-Ea / R  
T(K)](g) 
Dissolution, no 
precipitation 
Tester et al. 1994 [DIRS 
101732], p. 2415 
C 
Tridymite 
SiO2 
3.45  1013 68.9 ( 11) 1 1 Dissolution rate 
constant set to acristobalite, 
no 
precipitation 
NA 
E 
Amorphous silica 
SiO2 
7.32  1013 60.9  64.9 1 1 logk+ = - 0.369 + 
(-7.890  104  
T(K)) + (-3438 / 
T(K)) 
Dissolution Rimstidt and Barnes 1980 
[DIRS 101708], pp. 1683, 
1690 
C 
1.0  1010 ( 0.06) 50 ( 3) 4.4(h) 
( 0.3) 
1 Precipitation Carroll et al. 1998 [DIRS 
124275], pp. 1379, 1389 
C 
Opal-proxy 
SiO2 
7.32  1013 60.9  64.9 1 1 Dissolution rate 
constant and Ea 
set to amorphous 
silica, no 
precipitation 
NA 
C 
Microcline = K-spar 
KAlSi3O8 
1.78  1013 
pH ~5  8 
36 
(35  37) 
1 1 Reversible k+/: Blum and Stillings 1995 
[DIRS 126590] in: White and 
Brantley 1995 [DIRS 154492], 
estimated from p. 301, Fig. 5 
Ea: Blum and Stillings 1995 
[DIRS 126590] in: White and 
Brantley 1995 [DIRS 154492], 
p. 313, Tab. 2 
C 
Albite-low 
NaAlSi3O8 
7.08  1013 
pH 5  8 
67.7 1 1 Reversible k+/: Blum and Stillings 1995 
[DIRS 126590] in: White 
and Brantley 1995 [DIRS 
154492], p. 315, Tab. 3 
Ea: Blum and Stillings 1995 
[DIRS 126590] in: White 
and Brantley 1995 [DIRS 
154492], p. 313, Tab. 2 
and p. 317, Fig. 10 
C 

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Drift Scale THC Seepage Model 

Table H.3-1. Mineral Dissolution/Precipitation Reaction Rate Constants (k+/) and Activation Energies (Ea) to Be Qualified (Continued) 

MINERAL 
k+/-(mol m2 
s1)(a) 
at 298.15 K 
Ea 
(kJ/mol)(b) m(c) 
n(c) 
Formula Used to 
Calculate Rate 
Constant(d) Comment (e) Reference 
Qualification 
Method(s)(f) 
Anorthite 
CaAl2Si2O8 
3.16  1012 
pH ~ 5  8 
67.7 
(set to 
albite) 
1 1 Dissolution, no 
precipitation 
Brady and Walther 1989 
[DIRS 110748], 
estimated from p. 2825, 
Fig. 4 
C,E 
Muscovite formula 
K1.84Na0.16(Al3.75Fe0.22Mg0.12 
Ti0.02)[Si6.06Al1.92O20](OH)4 
1.0  1014 Knauss and Wolery 1989 
[DIRS 124300], p. 1500 
E 
Illite 
K0.5(Mg0.22Al1.78) 
(Si3.72Al0.28)O10(OH)2 
2.0  1014 58.6 1 1 
Reversible, rate 
constant 
assumed to be 
equal to 
muscovite 
(corrected for 
stoichiometry) 
NA 
T, E 
Smectite-Ca 
Ca0.145(Mg0.26Al1.74) 
(Si3.97Al0.03)O10(OH)2 
2.0  1014 58.6 
(set to illite) 
1 1 Reversible, rate 
constant set to 
illite 
NA 
E 
Smectite-Mg 
(Mg0.405Al1.74)(Si3.97Al0.03) 
O10(OH)2 
2.0  1014 58.6 
(set to illite) 
1 1 Reversible, rate 
constant set to 
illite 
NA 
E 
Smectite-Na 
Na0.29(Mg0.26Al1.74) 
(Si3.97Al0.03)O10(OH)2 
2.0  1014 58.6 
(set to illite) 
1 1 Reversible, rate 
constant set to 
illite 
NA 
E 
Sepiolite 
Mg2Si3O7.5OH3H2O 
2.67  1014 58.6 
(set to illite) 
1 1 Reversible, rate 
constant based on 
muscovite rate 
constant 
NA 
E 
Kaolinite 
Al2Si2O5(OH)4 
~ 1.0  1013 
pH 5 - 8 
7.1 ( 2.5) 
pH = 7 
1 1 Reversible k+/: Brady and Walther 1989 
[DIRS 110748], p. 2826, 
Fig. 6 
Ea: Carroll and Walther 1990 
[DIRS 160681], p. 806, 
Tab. 2 
C 
Heulandite 
Ca0.33K0.04Na0.1 
(Al0.8Si2.8O7.2)  2.6H2O 
5.66  1013 
pH = 7.2 
58.0 
(set to 
laumontite) 
1 1 Reversible (rate 
based on silica 
release) 
k+/: Ragnarsdttir (1993 
[DIRS 126601], p. 2439) 
Ea: Savage et al. (1993 
[DIRS 160198], p. 533) 
T, E 

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Table H.3-1. Mineral Dissolution/Precipitation Reaction Rate Constants (k+/) and Activation Energies (Ea) to Be Qualified (Continued) 

Drift Scale THC Seepage Model 

MDL-NBS-HS-000001 REV 04 H-
7 
February 2005 

MINERAL 
k+/-(mol m2 
s1)(a) 
at 298.15 K 
Ea 
(kJ/mol)(b) m(c) 
n(c) 
Formula Used to 
Calculate Rate 
Constant(d) Comment (e) Reference 
Qualification 
Method(s)(f) 
Clinoptilolite 
Ca0.28K0.08Na0.04 
(Al0.68Si2.92O7.2)  2.6H2O 
2.37  1013 
pH = 9 
58.0 
(set to 
laumontite) 
1 1 Reversible k+/: Murphy et al. 1996 [DIRS 
142167], p. 160 
T, E 
Stellerite 
Ca0.39Na0.01(Al0.79Si2.81O7.2) 
2.8H2O 
5.66  1013 58.0 
(set to 
laumontite) 
1 1 Reversible, rate 
constant set to 
heulandite 
NA 
E 
Mordenite 
Ca0.15Na0.21K0.09(Al0.6Si3O7.2) 
2.2H2O 
5.66  1013 58.0 
(set to 
laumontite) 
1 1 Reversible, rate 
constant set to 
heulandite 
NA 
E 
Calcite 
CaCO3 
1.60  106 (i) 48.1 ( 3.8) 1 1 Reversible 
(synthetic calcite) 
k+/: Svensson and Dreybrodt 
1992 [DIRS 127978], 
p. 129 
Ea: Inskeep and Bloom 1985 
[DIRS 128129], p. 2165 
T 
Gypsum equilibrium NA NA NA NA N.A. 
CaSO42H2O 
Fluorite 
CaF2 
1.22  107 (j) 0.0 1 2 Reversible k+/: Knowles-Van Cappellan 
et al. 1997 [DIRS 
124306], p. 1873 
N.Q. 
Hematite 
Fe2O3 
7.32  1013 60.9 - 64.9 
(set to 
amorphous 
silica) 
Reversible, rate 
constant set to 
amorphous silica 
NA 
? 
Glass (vitrophyre; 
hydglassfe3) 
7.72  1015 (k) 91.0 1 1 Dissolution, no 
precipitation 
k+/: Mazer et al. 1992 [DIRS 
124354], p. 574 
T 

(a) 
k+/-: dissolution/precipitation rate constants at 298.15 K; some values may slightly differ from source values due to unit conversions. 
(b) 
Ea: Activation energy; some values may differ slightly from source values due to unit conversions. 
(c) Exponents m and n in Equation 6 (Section 6.4-8). 
(d) Formulas are given only for instances where rates were calculated from data in cited references. No formulas are given if the rate was taken directly 
from the cited references. 
(e) no precipitation means precipitation of this mineral is not allowed; reversible indicates that the absolute values of the precipitation rate constant 
are equal to the dissolution rate constant. 
(f) For the qualification methods, C denotes data qualified by Criterion 2 (Corroborating Data), T denotes data qualified by Criterion 5 (Technical 
Assessment), NA denotes not applicable (which is used when the dissolution reaction is rapid enough the equilibrium may be assumed), E 
denotes an estimated value that is usually based on using qualified data for a chemically related mineral, and NQ means not qualified. If different 
methods are used to qualify and k+/ and Ea, then the first entry refers to k+/ and the second to Ea. 

Drift Scale THC Seepage Model 

(g) The  error limits represent fits to a 95% confidence level; the overall logk error using a geometric area basis was estimated by the authors to be 
 0.63. 
(h) The rate law proposed by Carroll et al. (1998 [DIRS 124275]) corresponds to: Rateppt ([Si] m2 s1) = 1.0  1010  0.06 (exp .Gr / R  T(K))4.4  0.3 , 
temperature dependence is accounted for in the rate law. 
(i) 
REMP = a (1  C / Cs); a denotes the rate constant, C the Ca2+ conc. in solution and Cs the equil. conc. of Ca2+ with respect to calcite. 
(j) 
k0 calculated from linear growth rate of Knowles-Van Cappellan et al. (1997 [DIRS 124306], p. 1873); for details of calculations, see Scientific 
Notebook YMP-LBNL-YWT-ELS-1 (Sonnenthal 2000 [DIRS 154870], p. 44). 
(k) Recalculated rate constant based on diffusion-limited model of Mazer et al. (1992 [DIRS 124354], p. 574); for details of calculations, read text and/or 
see Scientific Notebook YMP-LBNL-YWT-ELS-1 (Sonnenthal 2000 [DIRS 154870], p. 43). 
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February 2005 


Drift-Scale THC Seepage Model 

H.4 SILICA PHASES a-CRISTOBALITE, QUARTZ, AMORPHOUS SILICA, 
TRIDYMITE, AND OPAL-PROXY 
To derive reaction rates for quartz and amorphous silica, Rimstidt and Barnes (1980 
[DIRS 101708]) performed closed-system dissolution and precipitation experiments at 
temperatures between 18C and 305C, using distilled water and Barnes-type rocking autoclaves 
(Barnes 1971 [DIRS 160181]), as well as a system for circulating hydrothermal fluids, and they 
compiled their results along with data reported by other investigators. Measurements by 
Rimstidt and Barnes, and the other studies cited by them, were made with a variety of different 
silica samples: quartz sand, fused silica powder, silica gel, porous leached glass, and quartz 
powder with disturbed surfaces. According to the assessed results of Rimstidt and Barnes (1980 
[DIRS 101708], Table 4), which includes not only their data, but also data from numerous other 
studies, the activation energies for dissolution of the silica polymorphs are: for quartz, Ea = 67.4 
to 76.6 kJ mol1; for a-cristobalite, Ea = 68.7 kJ mol1; for -cristobalite, Ea = 65.0 kJ mol1; and 
for amorphous silica, Ea = 60.9 to 64.9 kJ mol1. These values are nearly the same, indicating 
that the rate-limiting step for these reactions is the breaking of strong Si-O bonds. Figure 4 of 
Rimstidt and Barnes is an Arrhenius plot for precipitation of silica polymorphs (log k as a 
function of the inverse of the temperature). This plot indicates that values of k for precipitation 
of the various silica polymorphs coincide within experimental error, which is expected because 
the same activated complex in solution should control the precipitation rates, with the 
least-squares value being Ea = 49.8 kJ mol1. The dissolution rate constant of amorphous silica, 

7.32  1013 mol m2 s1, was taken from these authors and that of opal-proxy set to the same 
value. More recently, Carroll et al. (1998 [DIRS 124275], p. 1386 and Table 3) report Ea = 61  
1 kJ mol1 for precipitation from slightly acidic solutions (pH = 3 to 7), and Ea = 50 kJ mol1 for 
precipitation from near-neutral solutions (pH = 7 to 8). 
More recent data on quartz dissolution kinetics have been provided by Tester et al. (1994 
[DIRS 101732], p. 2410). The dissolution experiments of these authors spanned temperatures 
from 23C to 255C, and were conducted using five different apparatuses. The results of these 
experiments, combined with data from 10 previous investigations ranging up to 625C, including 
those of Rimstidt and Barnes (1980 [DIRS 101708, p. 2407]), revealed a dissolution-rate 
variation of eleven orders of magnitude over the studied temperature range (e.g., from 4  1014 
to 1  103 mol m2 s1). The selected values in Table H.3-1 for the dissolution rate constant of 
quartz at 25C on a geometric surface area basis (k+ = 4.52  1014 mol m2 s1 and 
Ea = 90.1  2.5 kJ mol1) were calculated from Tester et al.s Equation 17a (1994 
[DIRS 101732], p. 2415), and are based on an analysis of a combined set of consistent data from 
numerous independent studies. 

In the course of reviewing the selected values in Table H.3-1, it was discovered that the accepted 
value of k+ = 4.52  1014 mol m2 s1 for quartz was based on use of the surface area determined 
by the geometric area basis by Tester et al. (1994 [DIRS 101732], p. 2415). The geometric 
area basis calculation is based on the approximation that the mineral particles have the same 
surface area as perfectly smooth spheres of similar size. Because mineral grains have irregular 
surfaces, the geometric area basis calculation significantly underestimates the true surface 
area. The authors also reported the surface area for one sample determined by BET 

MDL-NBS-HS-000001 REV 04 H-9 February 2005 


Drift-Scale THC Seepage Model 

measurements, and the value is about a factor of seven larger than the geometric area basis 
value. The more appropriate choices based on the BET surface area measurements are: 

k+ = 1.04  1014 mol m2 s1 

and 

Ea = 87.7  4.7 kJ mol1 

calculated using Tester et al.s Equation 17b (1994 [DIRS 101732], p. 2415). The two values of Ea 
agree to well within their experimental uncertainties, but the values of k+ differ by a factor of 4. 

Experimentally based dissolution and precipitation rates for a-cristobalite were determined by 
Renders et al. (1995 [DIRS 107088]). These closed-system experiments were conducted at high 
temperatures (145C to 301C), and at water-saturation pressures. The determined activation 
energy for the precipitation of cristobalite, Ea = 52.9  10 kJ mol1, was found to be, within the 
uncertainties, equal to those for quartz and amorphous silica determined by Rimstidt and Barnes 
(1980 [DIRS 101708], Table 4), Ea = 49.8 kJ mol1. They also determined Ea = 68.9  11 kJ mol1 
for dissolution of synthetic a-cristobalite. The dissolution rate constant of a-cristobalite and 
tridymite (set to a-cristobalite) at 25C, k+ = 3.45  1013 mol m2 s1, was calculated from Renders 
et al. (1995 [DIRS 107088], p. 77), using an equation given in their abstract (assuming the value 
R = 8.314 J K1 mol1), and it is an extrapolated value obtained from higher-temperature data. 

To investigate the effect of pH, temperature, and aqueous silica concentration on the 
precipitation rates of amorphous silica, Carroll et al. (1998 [DIRS 124275], p. 1380 and 
Figure 3) performed laboratory and field experiments in the temperature range between 80C and 
150C, and the pH values between 3.0 and 8.7. Fluidized bed reactors (FBRs) and quartz sand 
were used in the field experiments, whereas laboratory rates were derived from experiments on 
silica gel. The starting materials were either dissolved in buffer solutions or geothermal waters 
until amorphous silica saturation was achieved. Results of the experiments reveal that, in the 
absence of impurities and in solutions supersaturated with respect to amorphous silica by a factor 
< 1.3, precipitation rates have a first-order dependence, whereas in chemically complex field 
solutions, the precipitation mechanism changes from elementary reaction control to surface 
defect/surface nucleation control reflected by a nonlinear rate law. The overall activation energy 
was determined to be Ea = 50  3 kJ mol1 (Carroll et al. 1998 [DIRS 124275], p. 1389). Carroll 
et al. (1998 [DIRS 124275], p. 1387 and Table 3) also reported Ea = 50 kJ mol1 for precipitation 
from near-neutral solutions (pH = 7 to 8), which is in good agreement with the value of 
Ea = 49.8 kJ mol1 reported by Rimstidt and Barnes (1980 [DIRS 101708], Table 4). 

There are several determinations of the activation energy for precipitation of various silica 
polymorphs at near-neutral pHs that are in very good agreement: 

Ea = 49.8 kJ mol1 from Rimstidt and Barnes (1980 [DIRS 101708], Table 4), 

Ea = 52.9  10 kJ mol1 from Renders et al. (1995 [DIRS 107088], pp. 77, 81), and 

Ea = 50 kJ mol1 from Carroll et al. (1998 [DIRS 124275], Table 3). 

MDL-NBS-HS-000001 REV 04 H-10 February 2005 


Drift-Scale THC Seepage Model 

Because of the three independent studies yielding results that corroborate each other, the selected 
value of Ea = 50 kJ mol1 can be accepted with confidence. The selected values of Ea for 
dissolution of the various polymorphs of silica (excluding quartz), in Table H.3-1, fall in a 
narrow range of Ea = 60.9 to 68.7 kJ mol1, and are based mainly on the measurements of 
Rimstidt and Barnes (1980 [DIRS 101708], Table 4), along with assessed results from numerous 
literature studies, and are supplemented for a-cristobalite by results from the more recent study 
of Renders et al. (1995 [DIRS 107088], pp. 77, 81). Assessed values of k+ and k for the phases 
are taken from the same studies of Rimstidt and Barnes (1980 [DIRS 101708], Table 4 and Table 
3) and Renders et al. (1995 [DIRS 107088], pp. 77, 81). These values are based on many 
independent studies yielding results that corroborate each other, and the assessed results can be 
accepted with confidence. 

The selected values in Table H.3-1 for the dissolution rate constant of quartz at 25C are 
k+ = 4.52  1014 mol m2 s1 and Ea = 90.1  2.5 kJ mol1, which were calculated from Tester et 
al.s Equation 17a (1994 [DIRS 101732], p. 2415) and are based on consistent data from 
numerous studies. However, as noted earlier in this section, these values are also based on use of 
the surface area determined by the geometric area basis by Tester et al. (1994 [DIRS 101732], 

p. 2415), which significantly underestimates the surface area of mineral grains. The 
more appropriate choices based on the BET surface area measurements are 
k+ = 1.04  1014 mol m2 s1 and Ea = 87.7  4.7 kJ mol1, and were calculated from Tester et 
al.s Equation 17b (1994 [DIRS 101732], p. 2415). The two values of Ea agree to well within 
their experimental uncertainties, with some of the difference being due to using dissolution rate 
constants for a wider temperature range for evaluation of the geometric area basis value. 
Given the uncertainties of these two Ea values, the differences are not experimentally 
meaningful. Although the values of k+ differ by about a factor of 4 at 25C, both values agree 
within the scatter of the literature values used by Tester et al. (1994 [DIRS 101732]) in their 
evaluation, as indicated by Figures 8 and 9 of that study. 
H.5 ALBITE 
Various experimental determinations of the dissolution rate constant for low-albite NaAlSi3O8 
have been compiled and summarized by Blum and Stillings (1995 [DIRS 126590], Table 3), and 
these studies cover the pH range from around 1 to over 12 and a temperature range of 5 to 
300C. Figure 4 of that report shows the variation of logk+ with pH at 25C. Experimental data 
from nine separate studies are plotted, and the data from eight of these studies are consistent 
within about 0.5 log unit of a smooth curve through these data. The values of logk+ are 
essentially independent of pH for the range pH = 5 to 8, yielding k+  1016.15 mol cm2 s1 = 7.08 
 1013 mol m2 s1 for this region. Precipitation of albite is assumed to occur at the same rate. 
The activation energies for albite dissolution under neutral pH conditions have been determined 
by various authors, e.g., Knauss and Wolery (1986 [DIRS 160184], pp. 2481 to 2497); Hellmann 
(1994 [DIRS 160183], Table 6). Based on these compiled data, Blum and Stillings (1995 
[DIRS 126590], Table 2) calculated an apparent activation energy of 67.7 kJ mol-1, which was 
accepted and used in the THC simulations. It should be noted that the activation energy, 
Ea = 68.8  4.5 kJ mol1, determined by Hellmann (1994 [DIRS 160183], Table 6) is very close 
to this value, whereas those values determined by two of the other authors are lower, ranging 

MDL-NBS-HS-000001 REV 04 H-11 February 2005 


Drift-Scale THC Seepage Model 

between 51 and 54 kJ mol1. Because of the numerous independent studies yielding results that 
corroborate each other, the assessed results in Table H.3-1 can be accepted with confidence. 

H.6 K-FELDSPARS 
Various experimental determinations of the dissolution rate constant for various K-feldspars 
have been compiled and summarized by Blum and Stillings (1995 [DIRS 126590], Table 4), and 
these studies cover the pH range from around 1 to over 12 and temperature range of 5 to 200C. 
Figure 5 of that report shows the variation of logk+ with pH at 25C. Experimental data from six 
separate studies are plotted, involving data measured for feldspars from different locations, and 
they are consistent within about 0.5 log unit of a smooth curve through these data. The values 
of logk+ are essentially independent of pH for the range pH = 5 to 11, yielding k+  1016.75 mol 
cm2 s1, which is equivalent to k+ = 1.78  1013 mol m2 s1 for this pH region. The activation 
energy for K-feldspar dissolution in neutral pH environments is given by Blum and Stillings 
(1995 [DIRS 126590], Table 2) as ranging between 35 and 38 kJ mol1 for neutral pH. In the 
THC simulations an average activation energy value of Ea = 36 kJ mol1 was used. The 
dissolution rate constant is assumed to be the same as that for precipitation. Because of the six 
independent studies yielding results that corroborate each other, the assessed results in Table 
H.3-1 can be accepted with confidence. Results for the feldspars microcline and sanidine 
essentially coincide on Figure 5 of Blum and Stillings (1995 [DIRS 126590]) and therefore the 
dissolution rate constants of microcline KAlSi3O8 and all other K-feldspar phases were assumed 
to be the same. 

H.7 ANORTHITE 
The dissolution rate constants for anorthite, CaAl2Si2O8, are discussed by Brady and Walther 
(1989 [DIRS 110748], pp. 2823 to 2830) and Blum and Stillings (1995 [DIRS 126590], pp. 292 
to 342). The rate constant in the neutral pH region was estimated from Brady and Walthers 
Figure 4, which is a plot of logk+ against pH. The values of logk+ are essentially independent of 
pH for the range pH = 5 to 7, yielding k+  1015.5 mol cm2 s1, which is equivalent to k+ = 3.16 
 1012 mol m2 s1 at 25C for this pH region. This value is based on data from three concordant 
studies. Because the three independent studies yield results that corroborate each other, the 
assessed results in Table H.3-1 can be accepted with confidence. The only value of the 
activation energy for anorthite dissolution in the neutral pH range that was located is listed by 
Blum and Stillings (1995 [DIRS 126590], Table 2) as Ea = 107 kJ mol-1. Blum and Stillings 
(1995 [DIRS 126590], Table 2) also list values from dissolution measurements at acidic pHs, and 
these values range from Ea = 18.4 to 80.7 kJ mol-1. This value of Ea = 107 kJ mol-1 for neutral 
solutions is much larger than those reported for chemically related minerals albite and 
K-feldspars, which is unlikely, and its value was estimated as being the same as for the 
chemically similar low albite, Ea = 67.7 kJ mol-1 (Blum and Stillings 1995 [DIRS 126590], 
Table 2). 

H.8 MUSCOVITE, ILLITE, SMECTITE, SEPIOLITE (CLAY MINERALS) 
Knauss and Wolery (1989 [DIRS 124300], pp. 1493 to 1501) measured the dissolution rates of 
electronic grade ruby mica muscovite as a function of pH and at 70C. They performed 11 
experiments spanning the pH range of 1.4 to 11.8 at roughly equal intervals of pH. The 

MDL-NBS-HS-000001 REV 04 H-12 February 2005 


Drift-Scale THC Seepage Model 

50-day dissolution experiments were conducted in a single-pass, flow-through apparatus 
(open-system) using muscovite grains of 100 m size and dilute buffer solutions. The mica 
grains were ultrasonically cleaned to remove finer particles. The composition of 
their mica, as determined from 20 analyses using an electron microprobe, was 
K1.84Na0.16(Al3.75Fe0.22Mg0.12Ti0.02)(Si6.06Al1.92O20)(OH)4. To determine dissolution rates under 
far from equilibrium conditions, the ionic strengths of the reacting solutions were very low 

(3.0  104 to 0.13 mol kg1) and solutions were undersaturated with respect to muscovite or any 
other possible secondary phase. The concentrations of silicon and aluminum released during 
dissolution were determined using inductively coupled plasma emission spectroscopy, and those 
of potassium by atomic absorption spectroscopy. The specific surface area of the muscovite was 
determined by BET surface area analysis using argon gas and was found to be 1.10 m2 g1. 
Based on their experimental results, Knauss and Wolery (1989 [DIRS 124300], p. 1500) derived 
a generalized rate expression describing the dissolution behavior of muscovite under far from 
equilibrium conditions and at any pH: 

-0.37 +0.22 
r= 10-14.7 ..
. 
aH + 
..
. 
+10-16.6 +10-18.1 ..
. 
aH + 
..
. 
(Eq. H-1) 

The rate constant for near-neutral pH conditions at 25C was calculated by assuming 
surface-controlled dissolution with an activation energy of Ea = (14 kcal mol1)(4.184 kJ kcal1) 
= 58.6 kJ mol1, which yields k+ = 1.0  1014 mol m2 s1 (Knauss and Wolery 1989 
[DIRS 124300], p. 1500). 

The dissolution rate constant for illite was assumed to be the same as the dissolution rate 
constant given by Knauss and Wolery (1989 [DIRS 124300]) for muscovite. The rate constant 
was adjusted with respect to the number of oxygens per formula unit (k+ multiplied by 2) to 
account for differences in chemical formula between their muscovite and the illite stoichiometry, 
K0.5(Mg0.22Al1.78)(Si3.72Al0.28O10)(OH)2, assumed here. The rate constants of the Ca, Mg, and Na 
smectites were assumed to be the same as that for illite (determined from muscovite), with a 
correction for the difference in the number of the oxygens per formula unit between muscovite 
and smectite (in this case, the original muscovite rate was multiplied by a 
factor of 2). The assumed smectite compositions are Ca0.145(Mg0.26Al1.74)(Si3.97Al0.03O10)(OH)2, 
(Mg0.405Al1.74)(Si3.97Al0.03O10)(OH)2, and Na0.29(Mg0.26Al1.74)(Si3.97Al0.03O10)(OH)2, respectively. 

No measurements were located for the rates of precipitation and dissolution of sepiolite in the 
aqueous phase. Because sepiolite belongs to the same class (phyllosilicates) as the clay minerals 
and mica, its estimated dissolution/precipitation rate constant was based on the rate constant of 
muscovite. The sepiolite formula of the TOUGHREACT V3.0 database (thermk1.01.dat, 
derived in DTN: LB0307THMDBRTM.001 [DIRS 164434]) contains 7.5 oxygens per formula 
unit, Mg2Si3O7.5OH3H2O, compared to 20 oxygens in the muscovite formula of Knauss and 
Wolery (1989 [DIRS 124300], p. 1495); therefore, the rate constant of Knauss and Wolery was 
consequently adjusted by a factor of (20/7.5) = 2.67 to account for the difference in size between 
these structural units. 

MDL-NBS-HS-000001 REV 04 H-13 February 2005 


Drift-Scale THC Seepage Model 

The assessed value of k+/ for ruby muscovite determined by Knauss and Wolery (1989 
[DIRS 124300], p. 1500) at 70C can be accepted with confidence. This technical assessment is 
based on the authors detailed description of their use of a variety of experimental techniques to 
characterize the chemical and mineralogical composition of their muscovite sample and analyses 
of solution concentrations, along with the very detailed presentation of their experimental results. 
However, the value of k+ at 25C is also based on an assumed value of the activation energy. 
The assessed dissolution rate constants in this report (Table H.3-1) for dissolution of most 
silicate minerals fall in the range of k+ = 1  1014 mol m2 s1 to 3  1012 mol m2 s1. The 
estimated values of k+/ for clay minerals in Table H.3-1 fall in this range and are likely to be 
correct within an order of magnitude. 

H.9 KAOLINITE 
The dissolution rate constant of kaolinite, Al2Si2O5(OH)4, was estimated from a graph in Brady 
and Walther (1989 [DIRS 110748], Figure 6), based on measurements from their laboratory. 
According to this figure, the dissolution rate constant in the pH region between 5 and 8 is equal 
to 1017.3 mol cm2 s1, which is equivalent to k+ = 5  1014 mol m2 s1. This value is supported 
by subsequent measurements of Carroll and Walther (1990 [DIRS 160681], Figure 2), which 
yield a value of k+  1012.9 mol m2 s1 = 1.3  1013 mol m2 s1 at pH = 7. Carroll and Walther 
reported careful dissolution measurements for kaolinite at 25, 60, and 80C in buffered solutions 
with a wide range of solution pHs (pH ~ 1 to 12). The average value from these two studies is 

(0.9  0.4)  1013 mol m2 s1, which was rounded off to k+ = 1  1013 mol m2 s1 for the 
accepted value. The values derived by Carroll and Walther (1990 [DIRS 160681], p. 797) 
for the activation energy vary strongly with pH, and at pH = 7 the value is 
Ea = (1.7 kcal mol1)(4.184 kJ kcal1) = 7.1 kJ mol1. Because the results of the two studies yield 
results that corroborate each other, and because the measurements were made in Walthers 
laboratory (Walther is one of the leading researchers in mineral dissolution studies), the assessed 
results in Table H.3-1 can be accepted with confidence. 

H.10 ZEOLITES 
Ragnarsdttir (1993 [DIRS 126601], pp. 2442 to 2447) determined the dissolution rates for 
heulandite in the pH range 2.0 to 12.2 and at (25  2)C, at conditions maintained far from 
equilibrium, by measuring the concentrations of silica, aluminum, calcium, sodium, and 
potassium that were released into solution upon dissolution. The dissolution experiments were 
performed in fluidized-bed reactors using various solutions and buffers. The sieved grain size 
fraction used in the experiments ranged between 75 and 125 m with a surface area determined 
by krypton BET analysis being 1715  11 cm2 g1. The structural formula of heulandite, 
Na2.2K1.4Ca2.2Al14.2Si23.3O7224H2O, was determined by electron microprobe analysis. The 
stability of various zeolites was described in terms of their dependence on pH and sodium 
concentration. Alumina and silica release at intermediate and high pH were approximately 
stoichiometric, whereas at low pH Al was released preferentially compared to Si, resulting in the 
formation of a residual Si-rich surface layer. Steady-state dissolution rates plotted as function of 
pH (see Ragnarsdttir 1993 [DIRS 126601], Figure 9) show a characteristic U-shaped pattern, 
typical of most silicates, with decreasing rates from pH 2 to about 5.5, a pH-independent 
dissolution rate in the near-neutral and neutral pH region, and increasing rates in the high pH 

MDL-NBS-HS-000001 REV 04 H-14 February 2005 


Drift-Scale THC Seepage Model 

region (pH = 7 to 12). The dissolution rate constant at pH = 7.2 is k+ = 1011.8 mol m2 s1, or 

1.585  1012 mol m2 s1. Because the steady-state dissolution rates for heulandite given by 
Ragnarsdttir (1993 [DIRS 126601], pp. 2442 to 2447) were based on the rate of silica release 
into solution, the value of the rate constant was divided by a factor of 2.8 to give k+ = 5.66  
1013 mol m2 s1, corresponding to the number of silica formula units contained in the heulandite 
formula used here, Ca0.33K0.04Na0.1Al0.8Si2.8O7.22.6H2O. The rate constants of stellerite and 
mordenite were taken as having the same value. Ragnarsdttir assumed an activation energy of 
Ea = 58 kJ mol1 for the dissolution of heulandite based on the value obtained by Savage et al. 
(1993 [DIRS 160198], p. 533) for laumontite, and this value was accepted for the other zeolites. 
Murphy et al. (1996 [DIRS 142167], pp. 128 to 186) conducted long-term batch-type 
experiments to study the dissolution and growth kinetics of a Na-clinoptilolite that is 
isostructural with Ragnarsdttirs (1993 [DIRS 126601]) heulandite. The measurements of 
Murphy et al. were made at 25C and pH  9. The authors chose the 100 to 200 mesh size 
fraction (75150 m) for their experiments, and the surface area of the Na-clinoptilolite was 
determined by N2 gas BET analysis to be 10.1  0.3 m2 g1. The experimental system was open 
to atmospheric CO2, and the initial solutions (NaCl-NaHCO3 mixtures) were pre-equilibrated for 
several days before the solid was added. The authors reported very detailed analysis results for 
the solution concentrations of sodium, silica, and aluminum as a function of time. The Na 
concentrations were determined using a Na-ion selective electrode, and the SiO2 and Al were 
determined with their colored complexes using UV-visible spectrophotometry. The dissolution 
rate constant of Na-clinoptilolite given by these authors corresponds to 7.1  1014 mol m2 s1 
and was determined for a chemical formula based on 24 structural oxygens per formula unit, 
Na2Al2Si10O248H2O. Because the clinoptilolite formula used here is based on 7.2 oxygens per 
formula unit, Ca0.28K0.08Na0.04Al0.68Si2.92O7.22.6H2O, the rate constant was multiplied by a factor 
(24/7.2) = 3.33 to account for the difference between these chemical formulas. An activation 
energy of Ea = 58 kJ mol1 for the dissolution of Na-clinoptilolite is based on the value obtained 
by Savage et al. (1993 [DIRS 160198], p. 533) for laumontite. 

The assessed results given in Table H.3-1 for k+/ of heulandite and Na-clinoptilolite at 25C can 
be accepted with confidence. This technical assessment is based on the authors detailed 
description of their use of a variety of experimental techniques to characterize the chemical and 
mineralogical composition of their mineral, and the determination of the solution concentrations 
as a function of time. However, the values of Ea are estimated from an experimental value for a 
chemically related mineral, as are k+/ values for other zeolites. 

H.11 CALCITE 
Svensson and Dreybrodt (1992 [DIRS 127978], pp. 129 to 145) investigated the dissolution 
kinetics of various natural carbonate samples (e.g., marbles, limestones, calcareous marine 
pelagic sediments) and National Bureau of Standards (NBS) synthetic calcite. The batch 
experiments (free drift technique) were conducted on the 100 m sieved fractions, at 20C in 
aqueous CO2 solutions (CO2 pressure of 5  103 atm) under close to equilibrium conditions with 
respect to calcite. Calcium and magnesium solution concentrations were analyzed using 
inductively coupled plasma mass spectrometry. The dissolution rates of the natural carbonate 
samples were fitted by the authors to an empirical rate law of the form: 

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Drift-Scale THC Seepage Model 

REMP = a1 (1  C/Cs)n (Eq. H-2) 

with values for n being different when C = (0.60.8)Cs and when C > 0.8Cs, where C denotes the 
Ca2+ concentration in the solution and Cs the equilibrium concentration of Ca2+ with respect to a 
saturated solution of calcite. The a denotes a rate constant. Literature data at 5, 15, and 25C 
were analyzed with the same rate law. In contrast, NBS synthetic calcite was found to exhibit a 
linear-rate law of the form: 

 R = a (1 - C/Cs) (Eq. H-3) 

Furthermore, the results revealed lower rates for the natural samples than those of pure calcite. 
The different dissolution behavior of the natural samples and pure calcite is attributed to 
adsorbed impurities on the surface of the natural samples, as well as other unknown dissolution 
inhibitors that may have been present during the formation of these natural phases. 

In the THC seepage model, because of the quite rapid calcite reaction rates, this mineral is set to 
precipitate under equilibrium conditions. In other THC simulations, the dissolution rate constant 
determined for the synthetic NBS calcite is used. 

Svensson and Dreybrodt did not determine any activation energies for the dissolution reactions. 
Thus, an activation energy value of Ea = 48.1 kJ mol1 determined by Inskeep and Bloom (1985 
[DIRS 128129], p. 2165), from seeded calcite growth measurements, is used in those simulations 
where kinetics dissolution/precipitation are considered. 

The assessed results given in Table H.3-1 for Ea can be accepted with confidence. In the 
course of reviewing this document, however, it was discovered that that the accepted value of 
k+/ = 1.60  106 mol m2 s1 was appropriate for the experimental temperature of 20C rather 
than the assumed 25C. Svensson and Dreybrodt (1992 [DIRS 127978], Table 2) also analyzed 
literature data and their results imply that k+/ = 1.9  106 mol m2 s1 is a more appropriate 
choice for 25C, which is 19 % larger. This value was taken from Svensson and Dreybrodt 
(1992 [DIRS 127978], Table 2) for measurements made with a CO2 pressure of 3  103 atm. 
Given the experimental uncertainty in the dissolution rate constant of Svensson and Dreybrodt 
and other studies cited by them, the 19 % difference between the two values is negligible 
compared to the experimental error. 

H.12 GYPSUM 
The dissolution/precipitation rate constant for gypsum, CaSO42H2O, is quite high: k+/ ~103 
mol m2 s1 (see Jeschke et al. 2001 [DIRS 161694], p. 27, and references cited by them). This 
rate constant is many orders of magnitude larger than the rate constants for other minerals in this 
report (which is expected behavior because of its larger solubility), and consequentially it may be 
assumed to be at equilibrium with its solutions for modeling purposes. Thus, no values of k+/ 
and Ea need to be assigned for gypsum. 

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H.13 FLUORITE 
Knowles-Van Cappellen et al. (1997 [DIRS 124306], pp. 1871 to 1877) conducted seeded 
fluorite (CaF2) growth experiments at T = 25  0.1C and pH values ranging between 5.1 and 

5.6. (Experiments at lower pH values are not desirable because the dissolution rate and 
solubility are increased by formation of neutral HF in solution.) After pre-equilibration of the 
seeded solutions and initial saturation of solutions with respect to fluorite, the titrants 0.200 mol 
L1 NaF and 0.100 mol L1 Ca(NO3)2 were added at a constant rate and samples periodically 
taken for grain size analysis. The experiments were performed at three different initial ionic 
strengths of 0.01, 0.085 and 0.1 mol L1, with NaNO3 being added to control the ionic strength. 
Two different seed crystal concentrations were used in order to study both aggregating and 
non-aggregating conditions. Dynamic light scattering was use to determine the size and size 
distribution of the crystals in solution, and the initial surface area of the particles was determined 
to be 11.3 m2 g1 by BET N2 gas absorption measurements. The experimental results indicate 
that at low relative degrees of supersaturation, the precipitation of fluorite is a surface-controlled 
process that can be described by a second-order rate law of the form: 
v = kl (S  1)2 (Eq. H-4) 

where v is the linear growth rate (of cubic grains), kl is the linear-growth rate constant, which 
was determined to range between kl = 1.4  103 and 3.8  103 nm s1, and (S  1) corresponds 
to the relative degree of supersaturation (Knowles-Van Cappellen et al. 1997 [DIRS 124306], 
Equation 2, p. 1873). 

The rate constant for fluorite dissolution/precipitation was recalculated as follows from the linear 
growth rate constants of Sonnenthal (2000 [DIRS 154870], Scientific Notebook YMP-LBNLYWT-
ELS-1, p. 44): 

rate constant = (linear growth rate)/ molar volume (Eq. H-5) 

Assuming an intermediate linear growth rate of 3.0  103 nm s1 (Knowles-Van Cappellen et al. 
1997 [DIRS 124306], p. 1873) and a molar fluorite volume of 24.542 cm3 mol1, the rate 
constant was calculated as follows: 

k0 = ..
. 310-3 nm 
..
. 
 ...
10-9 m 
..
. 
/..
..
. 24.542cm3 
..
. 
...
10-6 m 
33 
...
.
. 
= 1.2224 10-7 mol m-2s-1 (Eq. H-6) 
. s .. nm . .. mol .. cm .. 

The same rate constant was assumed to apply to dissolution of fluorite. Because the study by 
Knowles-Van Cappellen et al. (1997 [DIRS 124306], pp. 1871 to 1877) was restricted to 25C, 
the value of Ea was set equal to zero. However the dissolution/precipitation rate constants for 
most minerals have a strong dependence on temperature, and the use of Ea = 0 is likely to 
significantly underestimate the value of k+/ at high temperatures. 

The experiments of Knowles-Van Cappellen et al. (1997 [DIRS 124306], pp. 1871 to 1877) were 
described in detail and appear to have been performed with care. Unfortunately, their 
experimental rate constants were not reported (i.e., the information was only presented 

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graphically and as values of kl). Yucca Mountain pore waters are generally saturated with 
respect to fluorite, and it is present in trace amounts in the rock. Therefore, fluoride 
concentrations are controlled by fluorite solubility (Section 6.2.2.2), and the assumption that 
Ea = 0 is expected to have negligible effect on predicted fluoride concentrations. 

H.14 HEMATITE AND GEOTHITE 
Very little dissolution of minerals containing Fe(III), such as hematite Fe2O3 and goethite 
FeOOH, occur under oxic conditions at near-neutral pH values because of the extremely low 
solubility of Fe(III). However, in the presence of high acidity and certain bidentate ligands, the 
dissolution of Fe(III) becomes much larger (e.g., Hersman et al. 1995 [DIRS 160190], pp. 3327, 
3329 to 3330). The dissolution mechanisms and the solubility of iron oxide minerals have been 
extensively studied in the last decades. A consensus seems to exist that proton- and 
ligand-promoted dissolution of iron oxide minerals can be described by surface complexation 
models. Very little data, however, exist on the dissolution and precipitation kinetics of these 
minerals, and especially for hematite. Hersman et al. (1995 [DIRS 160190], pp. 3327 to 3330) 
studied the effect of siderophores (highly specific, bidentate, iron chelating ligands produced by 
microorganisms), 3  103 mol L1 oxalate, and 2  103 mol L1 ascorbate ligands on dissolution 
of hematite at pH = 3 and temperature 21 0.5C. They determined a dissolution rate constant of 
k+ = 1.4  1011 mol m2 s1 in the presence of oxalate and ascorbate, and k+ = 3  1012 mol m2 
s1 in the presence of siderophores at concentrations comparable to those in natural systems. 

The thermodynamics and kinetics of hematite dissolution in bicarbonate solutions under constant 
CO2 pressure (0.3 atm and 0.97 atm) were studied at 25C by Bruno et al. (1992 [DIRS 160189], 
pp. 1139 to 1147). Results of their investigation reveal that the dissolution of hematite under the 
above-mentioned conditions and total bicarbonate concentrations higher than 3.2  103 mol L1 
is surface controlled and enhanced by the presence of bicarbonate ions. The rate expression 
given in their paper for the dissolution of hematite in the presence of bicarbonate is: 

 Rate = k+ [HCO3]0.23 (Eq. H-7) 

with k+ = 3.9  1011 mol m2 s1 (Bruno et al. 1992 [DIRS 160189], p. 1139). The authors also 
stated that in the absence of CO2 they were unable to detect dissolution of hematite below the 
iron detection limit of  108 mol L1. In neither the study by Hersman et al. (1995 
[DIRS 160190], pp. 3327 to 3330) nor the study by Bruno et al. (1992 [DIRS 160189]) were 
measurements made at higher temperatures. 

Because the rate law incorporated in the TOUGHREACT code so far does not take into account 
the inhibiting and/or catalyzing effects of aqueous ligands on the dissolution/precipitation rates, 
the above-mentioned literature data cannot be used. Because hematite and goethite are minor 
minerals in the tuffs, and Fe solubility is very low under the chemical conditions of the pore 
waters (e.g., near-neutral pH), the assumption that aqueous concentrations are controlled by local 
equilibrium with one of these phases is appropriate. Thus, no rate constants were used for either 
of these phases. For the THC seepage model simulations discussed in this document, hematite 
was assumed to be the controlling phase. 

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H.15 GLASS (VITROPHYRE) 
To get insight into the alteration mechanisms of clay based, silica-rich glass, Mazer et al. (1992 
[DIRS 124354], pp. 573 to 576) examined naturally occurring tektites (Indochinite) by optical 
microscopy, transmission electron microscopy, selected-area electron microdiffraction, and 
energy-dispersive X-ray spectroscopy to determine mineral phases present. The overall chemical 
composition of the tektites was determined by dissolving a sample in acid solution followed by 
chemical analysis using an inductively coupled plasma analysis. They performed dissolution 
experiments with polished monoliths of tektite under selected laboratory conditions. The 
alteration experiments were performed in the temperature range between 150 and 225C at 25C 
intervals and for periods between 3 and 400 days. Results of these experiments reveal that the 
degree of corrosion of the tektites strongly depends on the glass surface-to-water volume ratio 
(S/V). Under high-dilution conditions (low S/V ratio), etching of the outer glass surface is the 
dominant reaction process. Under conditions of restricted water contact (high S/V ratios), such 
as would be expected to occur at Yucca Mountain, the alteration process is initiated by water 
diffusion into the glass, followed by in situ hydrolysis of the silica network and formation of a 
poorly crystalline surface layer, which restructures with time to form a complete clay layer. The 
rate at which the thickness of the altered layer grows was measured using optical microscopy and 
with dark-field imaging using transmission electron microscopy. In this case, the dissolution rate 
of silica-rich glass follows the dependence of water diffusion through a reaction-product layer. 

Because the volcanic glass in the rocks at Yucca Mountain is 12.5 to 13 million years old 
(Sawyer et al. 1994 [DIRS 100075], p. 1305), and has undergone varying degrees of alteration, a 
constant-thickness product layer on the glass surface was assumed for recalculation of the 
dissolution rate constant at 25C. The layer cannot be thicker than a typical grain diameter 
(100 m). However, if it were too thin, a typical grain would be completely dissolved in less 
than 10 million years. A thickness of 10 m results in an inferred grain thickness dissolved of 
about 30 m, thus satisfying both the above requirements. 

The water diffusion rate (hydration rate) at 25C was extrapolated from the data obtained for the 
studied temperature region yielding 1.6  107 m2 d1 or 1.85  1024 m2 s1 (Mazer et al. 1992 
[DIRS 124354], pp. 574). The selected dissolution rate constant for the glass, k+ = 7.72  1015 
mol m2 s1, was calculated by applying Ficks law, assuming a uniform alteration layer of 10 
m thickness and spherical grain geometry (Sonnenthal 2000 [DIRS 154870], Scientific 
Notebook SN-LBNL-SCI-109-V1, p. 43). The selected value Ea = 91 kJ mol1 was the 
experimental activation energy for water diffusion determined by Mazer et al. (1992 
[DIRS 124354], p. 574). 

These dissolution rate values are corroborated by data from Yokoyama and Banfield (2002 
[DIRS 171364], Section 5), who measured rhyolite glass dissolution rates in field studies and 
laboratory experiments. Their field value (~6  1019 mol cm2 s1, or ~6  1015 mol m2 s1) 
corresponds closely to the dissolution rate used here. Their experimentally determined rates 
were one-to-two orders of magnitude higher, which they attribute to changes in the surface 
properties of the rhyolite glass during crushing, and to differences between the natural and 
laboratory weathering conditions. Based upon the laboratory experiments, Yokoyama and 
Banfield (2002 [DIRS 171364], Section 4.6.1) determined an activation energy of 63 kJ mol1. 

MDL-NBS-HS-000001 REV 04 H-19 February 2005 


Drift-Scale THC Seepage Model 

This value is lower than the value used here, but the differences in the field and laboratory 
dissolution rates suggest that it may not be applicable to dissolution under natural conditions. 

A technical assessment of the methods used by Mazer et al. (1992 [DIRS 124354], p. 573-576) 
also suggests that these data are high quality, based on the authors detailed description of their 
use of a variety of experimental techniques to characterize the chemical and mineralogical 
composition of their tektite sample, and the rate at which the surface was altered by water. 

Based upon corroborative data and technical assessment, the results given in Table H.3-1 can be 
accepted with confidence. However, because of the natural chemical variability of tektites and 
volcanic glasses, the listed value of the experimental rate constant k+ = 7.72  1015 mol m2 s1 
at 25C should be considered uncertain by about a factor of 10 when applied to natural glasses 
from different locations having significantly different chemical compositions. 

H.16 FINDINGS OF DATA QUALIFICATION EFFORT 
As described in the sections above, all data in DTN: LB0307KNTDBRTM.001 [DIRS 164433] 
have been evaluated by comparisons with corroborative data and by use of technical assessment. 
In all cases, the qualification criteria have been met, such that the data can be accepted with 
confidence. Based upon the above evaluation, DTN: LB0307KNTDBRTM.001 [DIRS 164433] 
is qualified for use by the Yucca Mountain Project. 

H.17 DATA QUALIFICATION PLAN 
See Figure H-1. 

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Drift-Scale THC Seepage Model 


Figure H-1. Data Qualification Plan 

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Drift-Scale THC Seepage Model 

INTENTIONALLY LEFT BLANK 


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Drift-Scale THC Seepage Model 

APPENDIX I 
QUALIFICATION OF IN-DRIFT CONFIGURATION, DIMENSIONS, AND 
COMPONENT PROPERTIES 


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MDL-NBS-HS-000001 REV 04 February 2005 


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This appendix documents the qualification of in-drift configuration, dimensions, and component 
properties listed in DTN: SN9908T0872799.004 [DIRS 108437], and serves as the data 
qualification report for that DTN. This data qualification effort has been carried out as described 
in the Data Qualification Plan that is included in the records package for this report. A facsimile 
of the Data Qualification Plan is included in Section I.8 of this appendix. 

I.1 PURPOSE OF DATA QUALIFICATION 
DTN: SN9908T0872799.004 [DIRS 108437] is the technical output of the calculation presented 
in Tabulated In-Drift Geometric and Thermal Properties Used in Drift-Scale Models for 
TSPA-SR (CRWMS M&O 2000 [DIRS 171790], Table 2). Unqualifed inputs were used in the 
development of those results, which were thus identified by that report as requiring further 
verification. The purpose of this data qualification effort is to qualify the values derived from 
DTN: SN9908T0872799.004 [DIRS 108437], for the parameters shown in Table I-1, as 
adequate for their intended use in the modeling of THC seepage in this report. Some of the data 
from DTN: SN9908T0872799.004 [DIRS 108437], which have been used to develop the 
predictions in this report, have since been superseded. Even though these data have been 
superseded, the data are shown below to be qualified as adequate for their intended use in this 
report. This qualification is done following LP-SIII.2Q-BSC, Qualification of Unqualified Data. 

Table I-1. Parameters and Values from DTN: SN9908T0872799.004 [DIRS 108437] to Be Qualified 

Parameter Value 
Waste Package and Drip Shield Dimensions and Attributes 
Location of waste package center above bottom of drift 1.945 m 
Location of waste package center below the drift springline 0.805 m 
Drip shield thickness 0.02 m 
Air gap between waste package surface and the inside of drip shield (only 
used for collapsed drift scenarios in Section 6.2.5) 
0.396 m 
Inside radius of drip shield 1.231 m 
Waste package thermal conductivity 14.42 W/m/K 
Waste package density 8189.2 kg/m3 
Waste package specific heat 488.86 J/kg/K 
Invert Properties 
Invert intrinsic permeability 6.152  1010 m2 
Invert porosity 0.545 
Invert grain density 2530 kg/m3 
Invert specific heat 948 J/kg/K 
Invert capillarity 833 Pa 
Invert residual saturation 0.1 

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I.2 PURPOSE OF DATA BEING QUALIFIED 
The data being qualified in this appendix relate to dimensions, configuration, and properties of 
the in-drift materials for a typical emplacement drift. These data are needed to enable the 
development of the THC seepage model. The primary purpose (see Section 1) of the THC 
seepage model is to estimate the chemistry of seepage that could enter a repository drift. Hence, 
the configuration and properties that are assigned to the in-drift components (such as the waste 
packages and the invert) have little impact on the predictions of seepage chemistry by the model. 
Consequently, the data evaluation criteria presented below are based on reasonableness of the 
input data, both in terms of design changes as well as in the scientific sense, rather than actual 
input requirements of the model. 

I.3 QUALIFICATION METHODS 
Consistent with LP-SIII.2Q-BSC, the method selected to qualify the data in Table I-2 is adopted 
from Method 2 in Attachment 3 of the qualification procedure: 

 Corroborating Data - The data to be qualified are compared with either more recent project 
data, or with similar data developed by duplicate or independent calculations since 
DTN: SN9908T0872799.004 [DIRS 108437] was developed. A comparison is made with 
current controlled YMP documentation or data in the TDMS for corroboration. 
I.4 QUALIFICATION PROCESS ATTRIBUTES 
Consistent with LP-SIII.2Q-BSC from Attachment 4, the attributes associated with this data 
qualification include: 

3. The extent to which the data demonstrate the properties of interest (e.g., physical, 
chemical, geologic, mechanical). 
This attribute is justified for application here because the data being qualified 
were developed specifically for the repository waste emplacement drifts. 

10. Extent and quality of corroborating data or confirmatory testing results. 
This attribute is appropriate because the availability of the newer project data that 
supersedes the data used in this report directly corroborate the values in 
DTN: SN9908T0872799.004 [DIRS 108437]. 

I.5 DATA EVALUATION CRITERIA 
Consistent with LP-SIII.2Q-BSC, criteria have been established to evaluate the adequacy of the 
data being qualified. In general terms, the data selected to represent the in-drift environment 
must be reasonably consistent with either (1) the dimensions, geometry, and configuration of the 
current repository layout , or (2) the results of comparable calculations. 

(1) The dimensions and properties associated with the waste package and drip shield 
associated with locations of components should be within a factor of 25 percent of 
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Drift-Scale THC Seepage Model 

the most recent values (if a single value is available) or within the suggested range 
from the most recent source; 

(2) Because the properties of the invert have little impact on the model, the values 
that are used should be scientifically reasonable, and thus values of porosity, 
specific heat, capillarity, and density should be within 25 percent of the most 
recent values, if a single value is available for them. Or they should be located 
within the range of values obtained from the most recent source. The value of 
permeability should be within an order of magnitude of the most recent value, and 
the invert residual saturation should be within 0.20 of the current value. 
I.6 EVALUATION OF DATA TO BE QUALIFIED 
Table I-2 contains the input model data that is to be qualified. The model input value can be 
compared to values given in the corroborative information. 

Table I-2. In-Drift Geometry and Property Choices for THC Seepage Model 

Parameter 
Model Input(a) Corroborative Information 
Value Value Source 
Waste Package and Drip Shield Dimensions and Attributes 
Location of waste package 
center above bottom of drift 
1.945 m 
1.75  2.15 m 
BSC 2004 [DIRS 168489] (center line of 
waste package height above invert) and 
BSC 2004 [DIRS 169776] (invert thickness) 
Location of waste package 
center below the drift 
springline 
0.805 m 0.6  1.0 m BSC 2004 [DIRS 168489] (drift diameter; 
center line of waste package height above 
invert) and BSC 2004 [DIRS 169776] (invert 
thickness) 
Drip shield thickness 0.02 m 0.015 BSC 2004 [DIRS 169220], Table 5 
Air gap between waste 
package surface and the 
inside of drip shield (only 
used for collapsed drift 
scenarios in Section 6.2.5) 
0.396 m 0.367  1.132 m BSC 2004 [DIRS 168489], Figure 1 
Inside radius of drip shield 1.231 m 1.285 m BSC 2004 [DIRS 168283] 
Waste package thermal 
conductivity 
14.42 W/m K 10.115.5 W/m* 
K for Alloy 22; 
13.33-17.83 
W/m*K for 316 
stainless steel 
BSC 2001 [DIRS 156276], Table 5-11 (Alloy 
22, for temperature range of 48 to 300C), 
Table 5-13 (316 stainless steel, temperature 
range of 22.11 to 287.78C) 
Waste package density 
(see also Section 4.1.1.6) 
8189.2 kg/m3 8690 kg/m3 DTN: MO0003RIB00071.000 [DIRS 148850] 
Mass density of Alloy 22 
Waste package specific 
heat 
488.86 J/kg/K 378- 731 J/kg/K BSC 2004 [DIRS 169990] (homogeneous 
thermal properties for waste package 
internal cylinder) 

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Table I-2. In-Drift Geometry and Property Choices for THC Seepage Model (Continued) 

Parameter 
Model Input(a) Corroborative Information 
Value Value Source 
Invert Properties 
Invert intrinsic permeability 6.152  1010 m2 
(2 to 4.75 mm 
particles) 
6.0  1010 m2 
(3 mm particle) 
BSC 2003 [DIRS 170881], Section 6.4 and 
Attachment XI 
Invert porosity 0.545 0.55 (b) BSC 2003 [DIRS 170881], Attachment XI 
Invert grain density 2530 kg/m3 2530 kg/m3 (c) BSC 2003 [DIRS 170881], Attachment XI 
Invert specific heat 948 J/kg/K 809 J/kg/K (d) DTN: GS000483351030.003 [DIRS 152932] 
Invert capillarity 833 Pa 24 to 1517 Pa(e) BSC 2003 [DIRS 170881] 
Invert residual saturation 0.09 0.19 (f) DTN: LB0208UZDSCPMI.002 [DIRS 
161243] 

(a) The source for model input is DTN: SN9908T0872799.004 [DIRS 108437], which is being qualified in this 
appendix. 
(b) The porosity of the invert is calculated using measured data (from the sources cited) for grain density (2530 
kg/m3) and bulk density (1150 kg/m3) of crushed tuff sieved between 2.00 to 4.75 mm. 
(c) The grain density of invert material is the measured (from the source cited) grain density of crushed tuff sieved 
between 2.00 and 4.75 mm. 
(d) The average specific heat (volumetric) of invert material for 11 samples (4-10 crushed tuff) listed in 
DTN: GS000483351030.003 [DIRS 152932] is 0.93 J/cm3/C. Specific heat capacity (gravimetric) = volumetric 
heat capacity / bulk density. Bulk density = invert grain density * (1-porosity) = (2530 kg/m3) (1-0.545) = 1150 
kg/m3 = 1.15 g/cm3. Thus, specific heat capacity = (0.93 J/cm3/C) / 1.15 g/cm3 = 0.810 J/g/C = 810 J/Kg/C. 
(e) The van Genuchten Air Entry parameters for the intergranular void space of the invert are presented in Table 
6.2 of Advection Versus Diffusion in the Invert (BSC 2003 [DIRS 170881]). The results are presented for a 
range of particle diameters from 0.317 mm to 20 mm and the parameters range between 65.9 (bars)1 to 
4160 (bars)1, respectively. The air entry capillary pressure (referred to as capillarity in this report) equals the 
reciprocal of the air entry parameter and varies between 1517 Pa and 24 Pa, respectively. 
(f) Residual saturation measured from rock core for the TSwM4 layer (Topopah Spring Tuff middle non-lithophysal 
unit). 
I.7 FINDINGS OF DATA QUALIFICATION EFFORT 
The parameters grouped under Waste Package and Drip Shield Dimensions and Attributes in 
Table I-2 are repository design information that has evolved since the current THC seepage 
model was developed. The comparison of the model input data with the more recent values 
shows that all of the model input values are within 25 percent of the current values or that they 
reside within the range of values, and thus meet the criteria of acceptability for use in this report. 
The model input data are therefore demonstrated to be qualified for their application. 

The input values for the parameters grouped under Invert Properties in Table I-2 can be 
corroborated by either the duplication of the calculations used in Tabulated In-Drift Geometric 
and Thermal Properties Used in Drift-Scale Models for TSPA-SR (CRWMS M&O 2000 
[DIRS 171790]) to generate the values used in the THC seepage model, or by comparable 
derivations of values. For the parameters of permeability, porosity, grain density, heat capacity, 
and capillarity of the invert, Advection Versus Diffusion in the Invert (BSC 2003 [DIRS 170881]) 
reproduced the same or similar calculations as those that were used as input to 
DTN: SN9908T0872799.004 [DIRS 108437]. This report has been developed, checked and 
approved under the current post-PVAR YMP QA procedures (BSC 2003 [DIRS 170881] was 
developed under AP-SIII.9Q). The comparison of the model input data for invert properties with 

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Drift-Scale THC Seepage Model 

the more recent values shows that all of the model input values meet the criteria of acceptability 
for use in the THC seepage model. 

Based on the above assessment, the data shown on Table I-1 have been demonstrated to be 
qualified for their application as input to the THC seepage model. 

I.8 DATA QUALIFICATION PLAN 
See Figure I-1. 

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Drift-Scale THC Seepage Model 


Figure I-1. Data Qualification Plan 

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