Defense HLW Glass Degradation Model REV 02, ICN 00

ANL-EBS-MD-000016

October 2004 


1. PURPOSE 
The purpose of this report is to document the development of a model for calculating the release 
rate for radionuclides and other key elements from high-level radioactive waste (HLW) glasses 
under exposure conditions relevant to the performance of the repository. Several glass 
compositions are planned for the repository, some of which have yet to be identified (i.e., glasses 
from Hanford and Idaho National Engineering and Environmental Laboratory). The mechanism 
for glass dissolution is the same for these glasses and the glasses yet to be developed for the 
disposal of DOE wastes. All of these glasses will be of a quality consistent with the glasses used 
to develop this report. 
1.1 OVERVIEW 
One of the waste forms to be placed in the repository is HLW glass. For the most part, this 
consists of a borosilicate glass containing approximately 25 mass % high-level waste oxides 
from the DOE inventory of waste from the processing of nuclear weapons. The dissolution 
mechanism for these glasses has been studied since the 1950s, but more intensely since 
about 1980. While the details of the kinetic mechanism are well known, only a few of the 
parameters are of interest for the model that will be used in the performance assessment of the 
Yucca Mountain repository. These parameters are the temperature and the pH of the solution 
that will contact the glass. Since the release of elements from the glass depends only on the 
temperature and the composition of the contacting solution, the same model can be used for glass 
dissolution in packages containing only HLW glass and those containing HLW glass codisposed 
with spent fuel (CSNF or DSNF). 
This report was developed in accordance with Technical Work Plan for: Regulatory Integration 
Modeling and Analysis of the Waste Form and Waste Package (BSC 2004 [DIRS 171583]). It 
specifically addresses the item Defense High-Level Waste Glass Degradation of the product 
development plan, and is in compliance with AP-SIII.10Q, Models. 
1.2 BACKGROUND 
In this section, a concise overview of the mechanism by which glasses interact with water is 
provided so that the reader has a basic understanding of the important aspects of the kinetic 
mechanism. From this, the reader is in a better position to understand how the dissolution of 
glass affects the overall performance of the repository. 
How glasses interact with water has been the subject of many studies dating back to the 1950s 
and 1960s (Doremus 1975 [DIRS 170920]; Goldman et al. 1957 [DIRS 171003]; Durham 1957 
[DIRS 171004]; Schneider 1971 [DIRS 170919]; Thomas and Christenson 1957 
[DIRS 171005]). 
Mostly industrial needs drove these studies, such as the leaching of container and window 
glasses. These uses required a predictive capability on the order of tens of years. In the 1970s, 
the use of glass, in particular borosilicate glass, for nuclear waste applications was investigated. 
By the late 1970s, it was obvious that the existing state of knowledge about the glasswater 
interaction was insufficient to qualitatively calculate how a glass might behave over a period of 
tens of years, much less the 10,000 years needed for the nuclear waste repositories. In the early 

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1980s, Grambow developed what was to become the best mechanism for the glasswater 
interaction. This mechanism is used today as the basis for the assessment of the performance of 
nuclear waste glass to be disposed in Europe, Japan, and the U.S. 
A glass containing 40 components has a chemical mechanism that has up to 39 chemical 
reactions that are needed to accurately describe its dissolution. In alkaline solutions, the 
mechanism is dominated by one reaction that is rate limiting. This one reaction so dominates the 
overall kinetics that it alone need be considered to explain the dissolution rate. It is important at 
this point to make the clear distinction between kinetics and thermodynamics. Kinetics is 
path dependent. Thermodynamics is a state function; the properties depend only on the 
beginning and end states, not which steps were taken to get from the beginning to the end. The 
two can only be combined when the thermodynamics of each step are known and each of the 
chemical reactions in the kinetic mechanism is known. It is fortuitous that the thermodynamics 
of the dominating reaction are simple and known. This has allowed thermodynamics to be 
applied to an otherwise incomplete kinetic mechanism. For borosilicate glasses, the dominant 
reaction in the chemical mechanism is the reaction involving orthosilicic acid, H4SiO4. Although 
thermodynamics is applied to this process, there is an implicit understanding that the system of 
glass plus water can never come to equilibrium. It is impossible to mix the components of glass 
together in an aqueous solution and expect glass to precipitate; there are too many other phases 
that are thermodynamically stable or metastable with respect to glass for glass to form from 
solution. Because only a single reaction must be considered in the overall kinetic mechanism, 
there are some shortcomings that result. For example, although reference may be made to the 
glass being in equilibrium with solution, what is really meant is an apparent equilibrium for the 
rate-limiting step in the reaction. Because glass dissolution depends on only one step in the 
kinetic mechanism, the mechanism can be simplified to that single step so that the kinetic rate 
can be calculated while relegating the remaining reactions to thermodynamic equilibrium. 
Thus, from a simplified mechanistic point of view, glass dissolves congruently (i.e., dissolves 
completely into solution). When the concentration of dissolved glass is very small, say 10-8 g/L, 
all the constituents stay in solution. However, it does not require a much higher concentration of 
glass before the solution becomes saturated with respect to some mineral phases, usually those 
containing elements like Fe or Zr. These elements then precipitate as minerals that achieve 
thermodynamic equilibrium with the contacting solution. While these minerals (some of which 
may contain silica) continue to form and precipitate, H4SiO4 continues to build in solution as 
long as the mass of Si in the mineral phases is less than that supplied by the dissolving glass. As 
the H4SiO4 concentration increases in solution, the dissolution rate of the glass decreases. 
Because many elements from the glass are involved in the formulation of mineral phases, it is 
not easy experimentally to follow the reaction of glass with water. Fortunately, for borosilicate 
glasses, B-bearing minerals are very soluble. Also, B usually forms anionic species in aqueous 
solution and they, for the most part, do not sorb on most surfaces. Therefore, experimentally the 
progress of the reaction (i.e., the amount of glass reacted with solution) is followed by 
determining the concentration of B in solution and knowing the B concentration in the glass. 
The model presented in this report is based on this fundamental knowledge of the glass 
dissolution mechanism. This mechanism is the basis for other performance assessments in 
Sweden (SKB 1999 [DIRS 171283]) and the United States (McGrail et al. 1998 [DIRS 153974). 

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However, because of the required input parameters to TSPA-LA, the kinetic rate equation for the 
HLW glass is modified to give the model developed in this report. 
This model is valid over the relative humidity range of 0% to 100%, the temperature range of 
20C to 300C, the pH range 1 to 14 and for glasses with compositions similar to those shown in 
Table 6-5. For example, the glass degradation model developed in this report is intended to be 
representative of all HLW glasses that meet the chemical durability requirement in the current 
versions of Waste Acceptance System Requirements Document (DOE 2002 [DIRS 158873]) and 
Waste Acceptance Product Specifications for Vitrified High-Level Waste Forms (DOE 1996 
[DIRS 102589]). Application of the glass model to HLW forms other than compliant 
borosilicate glasses must be determined separately. 
This model receives input from in-package chemistry and provides output directly to TSPA-LA. 
1.3 DOCUMENT OUTLINE 
The document outline is contained in Table 1-1. 
Table 1-1. Document Outline 
Section Description 
1. Purpose A description of the purpose of the report with a brief overview, background, and roadmap. 
2. Quality Assurance A brief discussion of the QA applicability. 
3. Use of Software Covers the use of any software other than commercial software. 
4. Inputs Necessary information or data from other parts of the project. 
5. Assumptions Assumptions used in the model discussed in this report. 
6. Model Discussion A discussion in which the technical basis for the model is given, including the in-depth 
discussion of the mathematical model and scientific aspects. 
7. Validation This section contains the discussion of model validation. 
8. Conclusions A conclusion concerning the model presented in this report. 
9. Inputs and 
References 
A bibliography and listing of any model inputs and outputs, including those that support the 
graphs shown in this report. 
Appendix A The pH and temperature dependence of the forward dissolution rate is described. 
Appendix B Measured and calculated HLW glass dissolution rates are used to extract values for the 
effective rate constant. 
Appendix C Results from vapor hydration tests are used to determine the alteration rate of the HLW 
glass in water vapor. 
Appendix D The gel layer that develops on a glass during alteration contains some condensed water. 
The porosity of this layer is calculated in this appendix and used to determine the amount 
of water in this layer. 
Appendix E Knauss and coworkers at Lawrence Livermore National Laboratory performed single-pass 
flow-through tests over a wide pH range. These data are evaluated in this appendix. 

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2. QUALITY ASSURANCE 
This document was developed in accordance with Technical Work Plan for: Regulatory 
Integration Modeling and Analysis of the Waste Form and Waste Package (BSC 2004 
[DIRS 171583]). From Section 8 in this plan, it was determined that this report is subject to 
Quality Assurance Requirements and Description (DOE 2004 [DIRS 171539]) because it will be 
used to support performance assessments. No item or barrier on the Q-List (BSC 2004 
[DIRS 168361]) is investigated as part of the output from this model or the development of this 
model. The primary procedure followed in developing this document was AP-SIII.10Q, Models. 
Technical Work Plan for: Regulatory Integration Modeling and Analysis of the Waste Form and 
Waste Package (BSC 2004 [DIRS 171583]) contains the process control evaluation used to 
evaluate the control of electronic management of data during the modeling and documentation 
activities. The evaluation determined that the methods in the implementing procedures are 
adequate. No deviations from these methods were used. 

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3. USE OF SOFTWARE 
Microsoft Excel:mac 2001 was used to compile test data and perform simple arithmetic 
calculations, such as calculating the mean and standard deviation values that are used in this 
report. No developed applications such as macros were used with the software; only 
user-defined formulas, mathematical functions and statistical routines provided with the 
commercially available version were used. No external models were used in the development of 
this report. 
Microsoft KaleidaGraph Version 3.0.5 was used to plot the data within this report. No 
developed applications, software routines, or macros were used with the software; only plotting 
functions provided with the commercially available version were used. The originator and 
checker have verified the plots against the original data. 
The Microsoft Excel:mac 2001 and Microsoft KaleidaGraph Version 3.0.5 software applications 
are both commercial off-the-shelf software and are not required to be qualified, per Section 2.1.6 
of LP-SI.11Q-BSC, Software Management. 

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4. INPUTS 
This section discusses the inputs used in this report. 
4.1 DIRECT INPUT 
All of the data directly used to develop the glass degradation model in this report were acquired 
as quality data at ANL. Some of the data used to corroborate parameter values used in the model 
were measured in tasks conducted at ANL under other quality assurance plans compliant with 
Quality Assurance Requirements and Description (DOE 2004 [DIRS 171539]) and Integrated 
Safety Management Quality Assurance Program (DOE 2001 [DIRS 155622]). Other 
corroborative data used in the analyses were taken from the open literature; those references are 
listed in Section 9. Information used to develop the model for calculating the exposed glass 
surface area was obtained from controlled sources. Per AP-3.15Q, Managing Technical Product 
Inputs, the input status of these references is reflected in the Document Input Reference System 
entries associated with this report. These data are appropriate for use in this report because they 
provide quantified measures of the dissolution behavior of relevant borosilicate glasses under 
documented test conditions. The data used in this report are the best available data for 
determining a rate expression and parameter values for waste glass degradation. The results 
taken from some literature sources were further analyzed to extract information from the data 
that was not directly provided by the authors or to convert the measured values to different units. 
Data used to model the surface area of glass available for reaction was taken from DOE 
documents providing specifications for canisters and potential waste glasses. Information 
regarding the HLW glasses to be produced at DOE facilities and the nominal dimensions of the 
standard (short) canister used at DWPF and WVDP is obtained from Integrated Interface 
Control Document (DOE 2002 [DIRS 158398], Figure C-20).1 The nominal dimensions of the 
long canister from Hanford are based on the maximum dimensions specified for the long canister 
(DOE 2002 [DIRS 158398], Figure C-21). The nominal dimensions were used because other 
uncertainties, such as fill height (Appendix D, Section D.3) and weighted average glass specific 
surface area (Section 6.5.4), compensate for the small difference if the maximum dimensions 
were used. This information is used to calculate the mass and specific surface area of the glass 
in a canister that is a weighted average based on the projected amount and characteristics of glass 
from different production sites. The impact of the uncertainty in each value, that is, how 
representative the value is for waste forms made at that facility, is captured by the range of 
possible surface areas of the representative glass product that may be contacted by water as 
quantified by the exposure factor (fexposure). 
Other input parameters include handbook values of the gas constant and specific volume of 
saturated steam at 200C (Weast 1977 [DIRS 106266]). Data from three literature sources are 
used in calculations. The best available data for the extent of cracking in DOE HLW glass from 
the thermal stress during cooling was measured by Smith and Baxter (1981 [DIRS 102089]) and 
from impact was measured by Smith and Ross (1975 [DIRS 102088]). These are used to 
1 For a further discussion on the size of the glass waste form, see Appendix D, Section D.3. 

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calculate the maximum value for the available surface area for use in the degradation model. 
These results are suitable for the intended use in the glass surface area model because they are 
the result of a well-planned and executed testing method, and the measurements were carried out 
in a systematic and controlled manner by qualified personnel working for U.S. national 
laboratories. The amount of water measured by Aines et al. (1987 [DIRS 104318]) in a vaporhydrated 
reference waste glass is used to calculate the porosity of alteration rind. This is the best 
available measurement of the water content of a degraded waste glass and was published in a 
peer-reviewed publication. The infrared spectroscopy method used by Aines et al. (1987 [DIRS 
104318]) is based on direct measurement of distinct O-H vibrations in molecular water and 
silanol groups. This method has been used by others to determine the amount of water in glasses 
that have been altered (Zoitos et al. 1989 [DIRS 163351]). The work was conducted as part of 
the glass waste form-testing program for the Nevada Nuclear Waste Storage Investigations 
project under DOE-accepted quality assurance controls. The results are suitable for the intended 
use in the glass surface area model because measurements were carried out in a well thought out, 
systematic, and quality-controlled manner. 
Characteristics of Potential Repository Wastes (DOE 1992 [DIRS 102812]) is used as a direct 
input to this report. This document was produced in 1992 by the Office of Civilian Radioactive 
Waste Management, and contains information on the waste forms expected to be contained in the 
Yucca Mountain Repository. A limited number of technical errors have been found in the 
radionuclide inventories contained in Characteristics of Potential Repository Wastes (DOE 1992 
[DIRS 102812]), which as a result is no longer considered qualified data. However, the 
radionuclide inventory data are not used in this report. Instead, this report uses the dimensions of 
the glass waste canister and the characteristics of the HLW glass. As a result, per 
Section 5.2.1(k) of AP-SIII.10Q, this data may be considered qualified for its intended use 
because the reliability of the data source is not in question for the relevant data. This data source 
demonstrates the properties of interest (i.e., the canister dimensions and waste form 
characteristics) because it is the best available source of the relevant data. Furthermore, the 
dimension data are corroborated in a more recent document (DOE 2002 [DIRS 158398]). 
The input data used in the development of the glass degradation model and the determination of 
model parameter values are summarized in Table 4-1 and described below. Table 4-2 lists the 
input parameters used to develop the model. The uncertainties in the input data are discussed in 
Section 6.8. 
Table 4-1. Input Data 
Data Name Data Source 
Glass immersion test results: concentrations and pH MO0306ANLGIM01.525 [DIRS 164329] 
Glass immersion test results: normalized mass losses MO0306ANLGIM02.525 [DIRS 164330] 
Glass vapor hydration test results: layer thickness MO0306ANLGVH01.526 [DIRS 164331] 
Glass unsaturated (drip) test results: boron mass and pH MO0408ANLGNN01.527 [DIRS 171574] 
Glass compositions and MCC-1 and PCT results MO0308ANLGPC01.528 [DIRS 164790] 
Characteristics of HLW glasses for canister dimensions 
DOE 1992 [DIRS 102812], Tables 3.1.1, 3.2.1, and 
3.3.1 and Sections 3.1.1, 3.2.3, and 3.4.3 
DOE 2002 [DIRS 158398] (Figures C-20 and C-21) 

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Table 4-2. Input Parameters 
Parameter Name Parameter Source Parameter 
Value(s) Units Distribution 
Gas Constant, R Weast 1977 
[DIRS 106266], p. F-241 8.314 J/molK constant 
Specific volume of Saturated Steam at 
200C 
Weast 1977 
[DIRS 106266], p. E-20 0.12716 m3/kg constant 
Thermal Cracking of HLW Glass Smith and Baxter 1981 
[DIRS 102089] 12 (no units) constant 
Impact Cracking of HLW Glass Smith and Ross 1975 
[DIRS 102088] 40 (no units) constant 
Pore Water Content of Glass Alteration 
Rind Layer 
Aines et al. 1987 
[DIRS 104318], Abstract 7 mass % constant 
 DTN: MO0306ANLGIM01.525 [DIRS 164329] (Tables 1, 2, 3, and 4) 
This DTN includes qualified data from the ANL Task Q-Data Immersion Tests that 
was completed as a part of Test Plan for Long-Term Studies of the Degradation and 
Radionuclide Release from Defense High-Level Waste (DHLW) Glass (BSC 2002 
[DIRS 164401]). The data in Tables 1-4 of the DTN are the measured solution 
concentrations and solution pH values (measured on solution aliquots at room 
temperature) for tests conducted at 70C, 90C, and 90C with added iron compounds 
(used in Appendix A). These data are appropriate for use in this report because they 
were collected specifically to provide a measure of the effect of pH and the presence of 
iron oxides, which represent thermodynamically stable iron corrosion products, and 
dissolved iron on the glass corrosion rate under controlled laboratory conditions for 
development of the glass degradation model and determination of parameter values in 
this report. The data provide a measure of the corrosion rates of a glass in solutions 
preset to specific pH values. The solution concentrations are used in Appendix A of this 
report. 
 DTN: MO0306ANLGIM02.525 [DIRS 164330] (Tables 1, 2, 3, 4, and 5) 
This DTN includes qualified data from the ANL Task Q-Data Immersion Tests that 
was completed as a part of Test Plan for Long-Term Studies of the Degradation and 
Radionuclide Release from Defense High-Level Waste (DHLW) Glass (BSC 2002 
[DIRS 164401]). The data in Table 1 of the DTN give the measured compositions of the 
SRL 202G glass (used in Appendix A and Section 6.5.2.2). These data are appropriate 
for use in this report because they were collected specifically to provide the composition 
of the glass used in the tests to calculate the glass degradation rate based on the 
measured concentrations of particular elements. The data in Tables 2-4 of the DTN are 
normalized mass loss values of boron and other major glass components for tests 
conducted at 70C, 90C, and 90C with added iron compounds (used in Appendix A of 
the DTN). Table 5 gives the results for Product Consistency Tests conducted at 90C in 
demineralized water. These data are appropriate for use in this report because they were 
collected specifically to provide a measure of the effect of pH and the presence of iron 
oxides (i.e., iron corrosion products) and dissolved iron on the corrosion rate of glass 

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under controlled laboratory conditions for development of the glass degradation model 
and determination of parameter values in this report. The data provide a measure of the 
corrosion rates of a glass in solutions preset to specific pH values. 
 DTN: MO0306ANLGVH01.526 [DIRS 164331] (Tables 1, 2, and 3) 
This DTN identifies qualified data from the ANL Task Vapor Hydration Testing of 
Glass that was completed as a part of Test Plan for Long-Term Studies of the 
Degradation and Radionuclide Release from Defense High-Level Waste (DHLW) Glass 
(BSC 2002 [DIRS 164401]). Table 1 of the DTN summarizes the test conditions and 
results in terms of measured layer thickness. Table 2 of the DTN provides the measured 
densities of the SRL 51S, SRL 131, and SRL 165S glasses used in the tests. Table 3 of 
the DTN provides the measured glass compositions. These data are appropriate for use 
in this report because they were collected on glasses with compositions similar to those 
that will be made under controlled laboratory conditions for development of the glass 
degradation model and determination of parameter values in this report. The data 
provide a measure of the overall corrosion rate of glass when exposed to humid air, 
which includes the rate of water sorption and condensation onto the glass and glass 
corrosion. The data provide a measure of the effect of the relative humidity and 
temperature on the glass corrosion rate that can be used to extract model parameter 
values for exposure of waste glass to humid air. These data will be used to determine 
the range and distribution of dissolution rates to be used for performance assessment 
calculations. These results are used in Section 6.5.3.3 of this report. 
 DTN: MO0408ANLGNN01.527 [DIRS 171574] (Tables 1, 2, 3, 4, 5, and 6) 
This DTN identifies qualified data from the ANL Task Unsaturated (Drip) Tests with 
Glass that was completed as a part of Test Plan for Long-Term Studies of the 
Degradation and Radionuclide Release from Defense High-Level Waste (DHLW) Glass 
(BSC 2002 [DIRS 164401]). Table 1 of the DTN gives the measured boron 
concentration and normalized mass loss for each sampling and Table 2 of the DTN gives 
the cumulative boron concentration and normalized mass loss for the N2 test series 
(conducted with SRL 165 glass). Table 3 of the DTN gives the measured boron 
concentration and normalized mass loss for each sampling and Table 4 of the DTN gives 
the cumulative boron concentration and normalized mass loss for the N3 test series 
(conducted with ATM-10 glass). Tables 5 and 6 of the DTN give the measured solution 
pH values for the N2 and N3 test series, respectively. These data are appropriate for use 
in this report because they were collected specifically to provide a measure of the 
corrosion rates of two relevant glass compositions under controlled laboratory 
conditions for development of the glass degradation model and determination of 
parameter values in this report. The data are used in this report to determine the 
corrosion rates of two glasses that are periodically contacted by small amounts of a tuff 
groundwater solution. The data provide a measure of the combined effects of water 
dripping onto the glass, glass corrosion, and water dripping off the glass on the glass 
degradation rates. The overall corrosion rate is used to determine the range and 
distribution of glass dissolution rates. These results are used in Section 6.5.3.5 of this 
report. 

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 DTN: MO0308ANLGPC01.528 [DIRS 164790] (Tables 1, 2, and 3) 
This DTN provides MCC-1 and PCT-A results from the ANL Task Evaluating the 
Relationship Between PCT-A and Long-Term Behavior. Table 1 of the DTN gives the 
compositions of nine glasses used to determine the effect of glass composition on the 
dissolution rate. Table 2 of the DTN gives the results for MCC-1 leach tests with the 
nine glasses. These data are used in Section 6.5.2.1 of this report to determine the effect 
of glass composition when solution feedback effects are negligible. Table 3 of the DTN 
gives the results of 7-day PCT conducted with the nine glasses. These data are used in 
Section 6.5.2.2 to determine the effect of glass composition on the dissolution rate when 
solution feedback effects dominate the test response. These data are appropriate for use 
in this report because they were collected specifically to provide measured dissolution 
rates for relevant glass compositions under controlled laboratory conditions for 
development of the glass degradation model and determination of parameter values in 
this report. 
4.2 CRITERIA 
Projects Requirements Document (Canori and Leitner 2003 [DIRS 166275]) identifies the 
high-level requirements for the Project and the U.S. Nuclear Regulatory Commission (NRC) 
acceptance criteria for these requirements are listed in Yucca Mountain Review Plan, Final 
Report (NRC 2003 [DIRS 163274]). The NRC acceptance criterion that is applicable to this 
report and the links to 10 CFR Part 63 [DIRS 156605] are listed in Table 4-3. 
Table 4-3. YMRP Acceptance Criteria Applicable to This Report 
Title 10 CFR Part 63 
Reference 
YMRP Acceptance 
Criteria 
Degradation of Engineered Barriers 
10 CFR 63.114 
[DIRS 156605] 
[(a)-(c) and (e)-(g)] 
NRC 2004 [DIRS 163274], 
Section 2.2.1.3.1.3 
Radionuclide Release Rates [and Solubility Limits] 
10 CFR 63.114 
[DIRS 156605] 
[(a)-(c) and (e)-(g)] 
NRC 2004 [DIRS 163274], 
Section 2.2.1.3.4.3 
The NRC YMRP acceptance criteria are based on meeting the requirements in 10 CFR 63.114 
[DIRS 156605] as they relate to the degradation of engineered barriers and radionuclide release 
rates. Pertinent criteria (BSC 2004 [DIRS 171583], Table 3-1) in Sections 2.2.1.3.1.3 and 
2.2.1.3.4.3 of Yucca Mountain Review Plan, Final Report (NRC 2004 [DIRS 163274]) include 
Acceptance Criterion 1 (System Description and Model Integration are Adequate), Acceptance 
Criterion 2 (Data are Sufficient for Model Justification), Acceptance Criterion 3 (Data 
Uncertainty is Characterized and Propagated Through the Model Abstraction), Acceptance 
Criterion 4 (Model Uncertainty is Characterized and Propagated Through the Model 
Abstraction), and Acceptance Criterion 5 (Model Abstraction Output is Supported by Objective 
Comparisons). These criteria and how they are addressed in the model developed in this report 
are discussed in Section 8.4. The technical work plan (BSC 2004 [DIRS 171583], Section 3) 
includes validation criteria. These are discussed in Section 7. 

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Waste Acceptance System Requirements Document (DOE 2002 [DIRS 158873]) and Waste 
Acceptance Product Specifications for Vitrified High-Level Waste Forms (DOE 1996 
[DIRS 102589]) provide acceptance criteria for standard borosilicate waste glasses and glass 
canisters. The models developed in this report are intended to represent the full range of 
borosilicate waste glass that meet the specifications in these documents and are acceptable for 
disposal. 
4.3 CODES, STANDARDS, AND REGULATIONS 
The work associated with this report was performed in accordance with the following 
regulations, codes, and standards: 
 10 CFR Part 63 [DIRS 156605]. Energy: Disposal of High-Level Radioactive Wastes 
in a Geologic Repository at Yucca Mountain, Nevada. Readily available. 
 ASTM C 1174-97 [DIRS 105725], Standard Practice for Prediction of the Long-Term 
Behavior of Materials, Including Waste Forms, Used in Engineered Barrier Systems 
(EBS) for Geological Disposal of High-Level Radioactive Waste. 
 ASTM C1285-02 [DIRS 163205], Standard Test Methods for Determining Chemical 
Durability of Nuclear, Hazardous, and Mixed Waste Glasses and Multiphase Glass 
Ceramics: The Product Consistency Test (PCT). 
 ASTM C1220-98 [DIRS 119321], Standard Test Method for Static Leaching of 
Monolithic Waste Forms for Disposal of Radioactive Waste. 

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5. ASSUMPTIONS 
Several assumptions were made in the development of this model. 
5.1 WATER HAS ACCESS TO SOME OF THE CRACK SURFACES 
Assumption: It is assumed that water has free access to some of the crack surfaces of the glass 
and that the reaction rate in the cracks is less than for a free glass surface. 
Rationale: As a glass cools in the canister, the combination of thermal and hoop stresses causes 
the glass to crack. The assumption is made in this model that not all the crack surfaces are 
accessible by water. While the data with artificial cracks suggest that the water access is limited 
(Perez and Westsik 1981 [DIRS 111044]), data from basaltic glasses at the ocean trenches 
suggests that the surfaces of bubbles in the glass, including the cracks that connect them to the 
surface, are accessed by water. Reaction rates within the cracks were lower than those at a free 
surface. Sen et al. (1999 [DIRS 163283]) established that the expected surface area contacted 
by water is less than the calculated surface area including the contribution from cracks. The 
reaction rate between water in the cracks and glass is reduced relative to the free surface because 
[H4SiO4] is higher in the crack due to the low transport of dissolved material from the crack. 
Thus, in the model, the high exposed surface area factor assumes free access of water to all 
cracks and the low value assumes 50% of the crack surfaces are contacted with a reaction rate 
that is 50% of the rate at the free surface of the glass. 
5.2 A pH VALUE FOR CONDENSED WATER ON GLASS OF 10 IS USED ABOVE 
100C 
Assumption: It is assumed that condensed water on the surface of glass will have a pH of 10 for 
temperatures above 100C. 
Rationale: When the temperature rises above 100C, most of the liquid phase is converted to 
water vapor and the limit for pH from In-Package Chemistry Abstraction (BSC 2004 
[DIRS 167621] is reached. At these temperatures and humidities, the glass reacts with the water 
vapor to form a thin layer of water on the surface of the glass. Because the ratio of surface area 
to volume is very high (about 4,000 m-1), the pH can be very high. As the temperature increases 
in the repository at constant pressure, the relative humidity decreases. The functional 
dependence on the relative humidity is not known, but alteration rate is known to decrease to 
zero at 44%. Both the effect of CO2 and the relative humidity cannot be accurately calculated as 
a function of temperature. However, conservatively assuming that only Na+ is released from the 
glass, the condensed water would become a NaOH solution. Reacting this solution with CO2 gas 
from a reservoir of unlimited volume at constant pCO2 = 10-1.5 kPa (10-3.5 atm) converts the 
solution to one containing NaCO3, which, under these conditions, has a pH of about 10.2 to 10.3 
(pKa for HCO3
- + H2O = CO3
2- + H3O+ (Stumm and Morgan 1981 [DIRS 100829], pp. 204 
to 206). Therefore, the rate of glass alteration increases as the temperature increases as 
calculated from the activation energy and the pH is fixed at the high value of 10 for the purposes 
of calculating an alteration rate. Using a fixed pH is conservative because the calculated rate 
increases with temperature (activation energy), the actual pH of the solution on the glass is lower 
than 10 because of CO2 availability, and the equilibrium constant for water shifts to lower values 

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with increasing temperature. Implicit in this model is that, other than increases in the rate from 
the temperature contribution, the rate remains constant until 44% relative humidity at which 
point it falls to zero. For pure water at a total pressure of 0.101 MPa, this occurs at 125C. For 
cases where saline solutions from In-Package Chemistry Abstraction (BSC 2004 
[DIRS 167621]) dictate the vapor pressure of water is less than that of pure water. 

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6. MODEL DISCUSSION 
6.1 MODELING OBJECTIVES 
The models described in this report were developed to calculate corrosion rates of waste glasses 
that are immersed in water or contacted by humid air or dripping water in the event that the 
waste package and glass canister are breached. Degradation of defense HLW glass is not 
identified as a principal factor in the calculated dose. Therefore, only the lowest acceptable level 
of confidence (Level 1) in the results from this model is required (BSC 2004 [DIRS 171583], 
Section 2.2), the validations of which are discussed in Sections 6.8, 6.9, and 7. The glass 
dissolution rate is used as an upper limit to the release rates of radionuclides from the glass as it 
corrodes. That is, the solubility of phases containing radionuclides is not taken into account in 
this model. The radionuclide release rate (Curies/time) is calculated as the product of three 
terms: the alteration rate of the glass, the exposed surface area of glass, and the inventory of 
radionuclides in the glass. Contained in this report are models for (1) calculating the glass 
alteration rate at a given solution pH and temperature when contacted by humid air or water 
(dripping or static) and (2) calculating the glass surface area available for corrosion. The release 
rate of a particular radionuclide can be calculated by multiplying the glass dissolution rate by the 
total surface area of glass that can be contacted by water and by the inventory of that 
radionuclide in the glass (e.g., Curies per g glass). The radionuclide inventory must be obtained 
from Initial Radionuclide Inventories (BSC 2004 [DIRS 170022]). 
The terms alteration and dissolution require some definition within the context of this report. 
Alteration refers to the process by which glass is converted to more stable minerals in the 
presence of water or water vapor. Dissolution refers to alteration of the glass but also the 
release of constituents to solution. In the case of dripping or bulk water, both alteration and 
dissolution may be used without confusion. In the case of water vapor, the glass is altered to 
more stable mineral phases, but the components can only migrate away if there is some transport 
mechanism such as dripping water or diffusion. At some time after alteration in water vapor, 
contact with dripping or bulk water would result in release of the soluble components in the 
alteration products on the surface of the glass. Overall, the glass is degraded by these processes 
from its as-produced state, hence, the word degradation appears in the title of this report. 
The glass alteration model is intended to represent the full range of disposed glasses based on the 
current waste form acceptance requirements in Waste Acceptance System Requirements 
Document (DOE 2002 [DIRS 158873]) and because within the range of HLW glasses, the 
dissolution of borosilicate glasses is the same. The effects of pH and temperature are explicitly 
calculated with the model. The effects of glass composition, solution composition, and water 
contact mode are taken into account with a parameter whose range of values provides modeled 
rates that span the range measured in laboratory experiments with various glass compositions 
under a range of water contact conditions. Although the modeled rate is not an explicit function 
of time, the rate that is used for each time step in TSPA-LA calculations is calculated as a 
function of the solution pH and temperature, both of which are expected to change over time. 

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6.2 FEATURES, EVENTS, AND PROCESSES 
This model includes consideration of features of the HLW glass, its disposal environment, and 
the events and processes that are expected to influence the rate of readionuclide release 
(DTN: MO0407SEPFEPLA.000 [DIRS 170760]). These FEPs, along with their disposition into 
the TSPA-LA model, are summarized in Table 6-1. Other screened out HLW glass FEPs and the 
bases for their screening decisions are described in Waste-Form Features, Events, and Processes 
(BSC 2004 [DIRS 170020]). 
Table 6-1. Features, Events, and Processes (FEPs) Included in this Report 
FEP 
Number FEP Name Section(s) Where Disposition is Described 
2.1.01.02.0B Interactions between codisposed waste 6.7 
2.1.01.03.0A Heterogeneity of waste inventory 6.5.2 and 6.5.2.2 
2.1.02.03.0A HLW glass degradation (alteration, 
dissolution, and radionuclide release) 6.5 
2.1.02.05.0A HLW glass cracking 6.5.4 
2.1.09.02.0A Chemical interaction with corrosion products 6.5.2.1, 6.5.2.3, and Appendix A 
6.3 BASE-CASE CONCEPTUAL MODEL 
The model for DHLW glass degradation developed in this report provides the source term for 
radionuclides released as glass degrades in a breached waste package after being contacted by 
humid air or dripping water, or when glass becomes immersed in water. The model is applicable 
to the full range of disposed glasses with compositions that meet the DOE acceptance criteria. 
Model parameter values were developed from the results of tests conducted on glasses with 
compositions that span the range of Al, Na, and Si contents that have the greatest effect on 
chemical durability. The model is also applicable to the possible water-contact scenarios, 
including contact by humid air, contact by dripping water, and immersion. The upper limit value 
of the glass degradation rate coefficient is determined for degradation of immersed glass and the 
lower limit value is determined for degradation under dripping water and humid air conditions. 
The FEPs that are included in the model for DHLW glass degradation and how they are 
addressed are summarized in Table 6-1. 
6.3.1 Mechanism for Glass Dissolution 
The dissolution of glass into water has been studied extensively for many years, resulting in an 
extensive database of test results. Several models have been developed to interpret various 
subsets of these data. Competing models based on diffusion-control and on dissolution control 
have been proposed, usually to describe the results under specific test conditions and for specific 
glass compositions (Doremus 1975 [DIRS 170920]; Wallace and Wicks 1983 [DIRS 171276]). 
The processes that contribute to the degradation of nuclear waste glasses include water diffusion 
in the glass and through alteration layers, ion exchange between the alkali in the glass and 
hydronium (H+) ion in water, alkali metal diffusion through alteration layers, wateralkali metal 
interdiffusion, hydrolysis reactions to release boron, silicon, and other components, diffusion of 

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hydrolyzed species through alteration layers, reformation of hydrolyzed bonds, in situ 
crystallization of hydrolyzed glass (gel), and the formation of alteration phases (Grambow 1984 
[DIRS 118987]; and McGrail et al. 2002 [DIRS 163272]). Different processes may predominate 
under different test conditions. However, most researchers now agree that, after or at the same 
time as ion exchange occurs, the dissolution rate of a borosilicate glass in alkaline solutions is 
controlled by the solution concentration of orthosilicic acid (Advocat et al. 1999 [DIRS 163199]; 
Bourcier 1994 [DIRS 101563]; Grambow et al. 1986 [DIRS 163258]; Knauss et al. 1990 
[DIRS 101701]; McGrail et al. 1998 [DIRS 153974]). As glass reacts with water, the Si-O-Si 
network is hydrolyzed. The rate-limiting step involves the hydrolysis of the last Si-O-Si bond to 
release a unit of orthosilicic acid, H4SiO4, to the bulk solution. 
The dissolution reaction can be written as in Equation 1a, and the reverse (condensation) reaction 
as Equation 1b: 
glass = SiOSi(OH)3 + H2O . glass = SiOH + H4SiO4 (aq) (Eq. 1a) 
glass = SiOH + H4SiO4 (aq) . glass = SiOSi(OH)3 + H2O (Eq. 1b) 
The atomic processes that occur during the hydrolysis of SiOSi groups by water have been 
investigated in ab-initio quantum mechanical studies (Lasaga and Gibbs 1990 [DIRS 163265]). 
The net dissolution rate is the difference between the rates expressed in Equations 1a and 1b. 
Clearly, the net rate will depend on the activity of orthosilicic acid (the activity of SiOSi bonds 
on the glass surface is defined to be 1). The net rate can be expressed in terms of the H4SiO4 
activity in solution and in a saturated solution (Lasaga 1983 [DIRS 141616]; Aagaard and 
Helgeson 1982 [DIRS 101530]). Glass cannot reach true equilibrium with solution because it is 
thermodynamically unstable with respect to more stable minerals made up from the constituents 
of the glass. To put it differently, it is not possible to dissolve all the constituents of a glass in 
solution and have a glass precipitate. Thus, in reality, the rate for the dissolution reaction 
(Equation 1a) will always be higher than the reverse or condensation reaction (Equation 1b). In 
the context of the model for glass dissolution, the solution is considered to attain an apparent 
saturation limit when the net dissolution rate becomes immeasurably low (Grambow 1985 
[DIRS 163257]). This means that there is a hypothetical equilibrium constant for the reaction 
sequence expressed in Equations 1a and 1b. It must be emphasized that the reactions shown in 
Equations 1a and 1b are for the one reaction that determines the overall glass dissolution rate in 
alkaline solutions. The dissolution mechanism contains many such reactions involving other 
components of the glass that do not affect the overall dissolution rate. In acid solutions, the 
reactions that determine the overall glass dissolution rate have not been fully identified, but 
appear to be associated with reactions to release glass network formers other than Si 
(Abraitis et al. 2000 [DIRS 163195]). 
The model for glass dissolution developed by Grambow is described succinctly by Werme et al. 
(1990 [DIRS 163346]), and that description is reproduced here. 

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The rate expression for surface reaction-controlled dissolution can be written as: 
1 Si 
m 
sat 
a r k 
a +
. . 
= - . . 
. . 
(Eq. 2) 
where k+ is the forward rate, aSi is the activity of orthosilicic acid in the bulk solution, and asat is 
the activity of H4SiO4 at saturation. In the Grambow model, diffusion of H4SiO4 through a 
chemically and physically altered layer of glass (alteration layer or rind) may affect or control 
the release under certain conditions. In the alteration layer, there are many sorption sites for 
H4SiO4. Thus, as the alteration layer thickens, transport of H4SiO4 through the layer results in 
the bulk solution having one concentration of H4SiO4 and a higher concentration in the aqueous 
phase near the glass-layer interface. The transport-limited rate is expressed as a diffusion 
equation: 
( ) , t Si s Si lt 
D r a a r 
L 
. . = - + . . 
. . 
(Eq. 3) 
where D is the diffusion constant for silica, L is the alteration layer thickness, aSi,s and aSi are the 
orthosilicic acid activities at the glass surface and bulk solution, respectively. The term rlt is an 
ad hoc term included in the rate expression to account for the residual dissolution rate that is the 
result of a constant driving force to convert glass to alteration products in the presence of water. 
The term rlt is often assigned an empirical value determined from laboratory tests. The term 
(aSi,s-aSi) gives the gradient of the silica activity across the layer. The Grambow model provides 
an expression for the dissolution rate that includes the effects of both dissolution and diffusion 
by combining Equations 2 and 3: 
+ + 
+ 
+ = 
k (D/L) sat a 
lt r ) Si - a sat (a (D/L) 
k m r (Eq. 4) 
The minimum concentration gradient occurs across the layer when aSi is equal to the saturation 
concentration asat and the diffusion rate is rlt. The term asat(D/L) gives the maximum transport 
rate through a layer with thickness L. The measured dissolution rate will be transport-limited 
when asat(D/L) << k+, and Equation 4 reduces to Equation 3. Under conditions where 
asat(D/L) >> k+, Equation 4 reduces to Equation 2 and dissolution is reaction-limited. 
The degradation of borosilicate glasses contacted by water is usually modeled to be the result of 
three main processes: water diffusion into the glass, ion exchange between water and the glass, 
and hydrolysis reactions (Bourcier 1994 [DIRS 101563]; McGrail et al. 2001 [DIRS 171165]; 
Grambow and Muller 2001 [DIRS 171412]). The effects of water diffusion and ion exchange 
discussed above are important early in the reaction. Ion exchange reactions occur to replace 
alkali metal and alkaline earth ions in the glass with protons from solution giving rise to the 
hydroxyl groups in the reactant glass = SiOSi(OH)3 shown in Equation 1a. The alkali metal 
and alkaline earth ions are released from the glass as ions (e.g., Na+ and Ca2+). Hydrolysis 
reactions occur to break the covalent bonds that form the glass network. Many elements are 
released from the glass as polyatomic species, such as B(OH)4
- and Si(OH)4. While ion 

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exchange and hydrolysis reactions can occur at sites on the surface of the glass, water also 
diffuses into the glass and reacts at interior sites (Grambow and Muller 2001 [DIRS 171412]). 
Alkali metals, alkaline earth metals, and boron are initially released from the glass preferentially 
to silicon and aluminum in acidic and neutral solutions (Abraitis et al. 2000 [DIRS 163195]). 
Ion exchange appears to take place independent of matrix dissolution in alkaline solutions 
(McGrail et al. 2001 [DIRS 171165]). The rates of ion exchange and water diffusion decrease 
with time and the dissolution becomes controlled by matrix dissolution. Solubility limits with 
respect to several minerals are quickly reached and they precipitate. The ion exchange and the 
precipitation of minerals leads to a solution that is incongruent with respect to the glass 
composition. Because the precipitating minerals remove less alkali, the solution in contact with 
most nuclear waste glasses becomes alkaline. Although experimentally the glass dominates the 
solution in contact with glass, the corrosion of the package components will dictate the 
composition of the solutions that will come in contact with the glass. Thus, implementation of 
the glass degradation model will utilize the solution pH that is calculated in In-Package 
Chemistry Abstraction (BSC 2004 [DIRS 167621]).2 
Because boron is not incorporated into alteration phases, whereas most of the other elements are, 
the extent of glass dissolution in most laboratory tests is provided by the boron solution 
concentration. The boron concentration is used to determine the parameter values in the glass 
degradation model, which is then used to calculate the release rates of radionuclides from the 
glass. An exception is the use of the vapor hydration test results, which are discussed in 
Section 6.5.3.3. In these tests, a thin film of water, the thickness of which has only been 
estimated, contacts glass. The small volume of water promotes the formation of alteration 
phases. These alteration products are the same as those that are formed in tests in which bulk 
water is in contact with the test specimen and are formed in the long-term on natural materials 
(Bates and Steindler 1983 [DIRS 104261]). The extent of glass corrosion is measured using the 
thickness of an alteration layer (Ebert 2003 [DIRS 164518]) or the thickness of the unreacted 
glass (Jiricka et al. 2001 [DIRS 163262]). With either of these methods, the extent of reaction is 
determined from the amount of glass converted to alteration phases. 
As a result of the mechanistic studies, the glass dissolution rate can generally be expressed with 
the formula given by Aagaard and Helgeson (1982 [DIRS 101530]): 
.. 
. 
.. 
. 
.. 
. 
.. 
. -  .. 
. 
.. 
. 
 = . - 
RT 
A a k r r 
i 
v 
i r glass 
i 
s 
exp 1 (Eq. 5) 
where 
rglass = glass dissolution rate 
kr = rate constant that carries the units of rate 
ai = the chemical activity of the species i 
.i 
= the stoichiometric coefficient for species i in the mechanistic step 
2 Although the pH is passed from In-Package Chemistry Abstraction (BSC 2004 [DIRS 167621]), there is no 
continuous water when the temperature is above 100C. In this case, Assumption 5.2, in which the pH is assumed 
to be 10, is used. 

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s = related to the stoichiometry of the rate limiting step relative to the dissolving 
solid 
Ar = reaction affinity; a measure of the driving force for the reaction to occur 
R = the gas constant 
T = absolute temperature. 
For glass, Equation 5 can be simplified to: 
.. 
. 
.. 
. -  .. 
. 
.. 
. 
.. 
. 
.. 
. -   =  
. 
K
Q 
RT
E k r a pH 
glass 1 exp 10 0 
. (Eq. 6) 
where the parameters have the same meaning as in Equation 5 and where the rate limiting step 
involves only silica (Equations 1a,b): 
.
0 k = intrinsic rate constant that depends only on glass composition and carries units 
of rate 
. = order of the rate limiting step with respect to the activity of hydronium ion, + H a 
Ea = activation energy for the rate limiting step 
Q = ion activity product; in this case, the activity of H4SiO4 
K = equilibrium constant for the rate limiting step, in this case the activity of H4SiO4 
at saturation. 
Since all waste glasses have the reactions shown in Equation 1a,b, then the values for Ea, ., and 
K are the same for these glasses. The only composition dependence is in the intrinsic rate 
constant. This simplifies the discussion of glass dissolution and, in the model presented here, 
allows Equation 6 to be simplified further. 
The final term in Equation 6 is known as the affinity term. This term is responsible for rate 
decreasing as the reaction proceeds or as the H4SiO4 concentration increases either from internal 
(glass) or external sources. Recent work indicates that the final rate of dissolution (that dictated 
by the approach of Q/K to 1) is on the order of 104 lower than the initial dissolution rate at 90C 
and a pH value of 10 (Gin and Mestre 2001 [DIRS 171170]). This means that final dissolution 
rates under static conditions are on the order of 10-4 g/(m2d). In an open system, the actual 
dissolution rate depends on the flow rate through the value of Q (Equation 6). 
Whereas laboratory tests have contributed the most insight to determining the glass corrosion 
mechanism, the results of field tests and the study of natural analogs have provided confidence in 
that understanding. In most cases, the study of glass corrosion in the field is restricted to 
examination of the reacted glass itself. Solution data are rarely available and the reaction 
conditions are often poorly constrained, especially in the case of natural analogs. Changes in the 
chemical compositions of reacted surface layers can provide evidence of leaching soluble glass 
components or the ingression of solutes from water in contact with the glass (Wicks 1992 
[DIRS 163349], Chapter 7). Field and laboratory studies comparisons generally show that 
higher corrosion rates are measured in laboratory studies than occur in the field 
(Zoitos et al. 1989 [DIRS 163351]). 

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6.3.2 Simplifications Used in the Glass Degradation Model 
The glass degradation model is simplified for implementation in TSPA-LA calculations. The 
key simplifications and their impact are discussed below. 
6.3.2.1 Constant Value Used for the Activity of Orthosilicic Acid 
As mentioned in the discussion with respect to Equation 6, the dissolution rate decreases as the 
concentration of H4SiO4 increases at constant pH and T, whether the increase is from glass 
dissolution or external sources. For ease of implementation, the model developed in this report 
includes explicit terms for the temperature and pH and an implicit term containing a constant 
value for the activity of H4SiO4 for each TSPA-LA time step. The value of (1-Q/K) (Equation 6) 
can vary from 1 (Q = 0 or no H4SiO4) to less than 10-4 (Q  K or the saturation value for 
H4SiO4); neither of which represent open repository conditions. To account for the low drip rate 
that is expected in the repository and for the very slow dissolution rate if the aqueous phase was 
static, a maximum value of (1-Q/K) was selected for both acid and alkaline solutions. To bound 
the minimum, a value based on the vapor hydration test results was used for alkaline solutions 
and a value based on unsaturated (drip) test results was used for acidic solutions. This is 
discussed in Section 6.5.3.3.4. 
6.3.2.2 Glass Dissolution Dependence on pH 
Results from tests on several waste glasses have shown the dissolution rate to pass through a 
minimum at a pH value of approximately 7 as the test solutions change from acid to alkaline. 
Although it is likely that the differences in the behaviors of different glasses in acidic solutions is 
due to their composition, and particularly the relative amounts of aluminum and silicon, the rate 
limiting step appears to be different (Abraitis et al. 2000 [DIRS 163195]). In this report, 
degradation rates of all waste glasses are modeled to increase as pH decreases from neutral to 
lower pH values and as pH increases from neutral to higher pH values. This is discussed in 
Sections 6.5.2 and 7.4. In this report, equations are developed to calculate the rates for both the 
acidic and alkaline solutions over the entire pH range (0 to 14). 
6.3.2.3 The Same Dependence on pH and Temperature is Used for All Waste Glass 
Compositions 
Since the rate-limiting step in the dissolution mechanism is the same for all waste glasses, the pH 
and temperature dependence is the same for all waste glasses (Section 7.4.6). 
6.3.2.4 The Glass is Unaltered in Water Vapor Below 100C 
The alteration of glasses in water vapor as a function of the water vapor pressure is not 
completely understood. Water vapor enters the glass matrix in many natural and manmade 
glasses. Obsidian artifacts are often dated by determining the extent to which water has diffused 
into the glass artifact (Friedman and Long 1976 [DIRS 163253]). However, at low temperatures, 
these artifacts are not altered even though water has diffused into the glass. Manmade artifacts 
with much less durability than nuclear waste glasses have existed for up to 3,500 years without 
significant alteration (Cunnane et al. 1994 [DIRS 101589]). 

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6.3.3 Uncertainties in the Subsystem and Environment 
Except in the case where the relative humidity is less than 44%, the amount of water contacting 
the exposed glass is not specified directly in the model. Rather, it is treated as an uncertainty that 
is taken into account through the range and distribution of the effective rate constant. The lower 
end of the range of values of the effective rate constant is selected to yield a calculated value that 
matches the rate measured in tests with glass contacted by dripping water (when the solution is 
acidic) or by humid air (when the solution is alkaline) at the pH and temperatures of those tests. 
The pH of the solution accumulated in a breached waste package is provided by In-Package 
Chemistry Abstraction (BSC 2004 [DIRS 167621]). The upper end of the range of values of the 
effective rate constant is selected to yield a calculated rate that matches the rate measured for 
immersed glass. The most likely value of the effective rate constant is selected to be the lower 
limit. This is because the environment within a breached waste package is anticipated to be 
hydrologically unsaturated for most of the service life. 
The composition of the waste glass in a breached container is also treated as an uncertainty. The 
radionuclide inventory is averaged over all HLW glass packages. However, an average glass 
composition is not used in this report. Instead, the results of tests conducted with glasses having 
a range of compositions are used to provide a corresponding range of degradation rates, and the 
upper range for immersion conditions and lower range for dripping water conditions is used to 
determine model parameter values. 
6.4 CONSIDERATION OF ALTERNATIVE CONCEPTUAL MODELS 
A summary of the alternative conceptual models considered is provided in Table 6-2. 
Table 6-2. Alternative Conceptual Models Considered 
Alternative Conceptual Models Key Concepts Screening Assessment and Basis 
Diffusion-controlled release 
Release rate of radionuclides 
determined by solid-state diffusion 
rates. 
Not incorporated into TSPA-LA model 
Not supported by data for waste glasses 
Composition independent 
effective rate constant 
Intrinsic rate constants vary over 
a small interval for different 
compositions and the very low 
flow rates in the repository 
compared to those used in the 
laboratory mean that the affinity 
term will be low. 
Not incorporated into TSPA-LA model 
Current approach provides a much more 
robust range of values for use in the 
TSPA-LA 
6.4.1 Diffusion-Controlled Release 
An alternative conceptual model that is considered for the process controlling glass degradation 
was developed for HLW glass in France. Researchers at the Commissariat  lnergie Atomique 
(CEA) in France attribute the residual dissolution rate to diffusion-controlled release of silica 
(Jgou et al. 2000 [DIRS 163260]; Vernaz et al. 2001 [DIRS 163328]; Gin, Jollivet et al. 2001 
[DIRS 163256]; Gin, Ribet, and Couillard 2001 [DIRS 163255]). They have concluded that the 
reaction-control model in Equation 5 is inconsistent with the results of various tests they have 
conducted with the reference glass R7T7 and simple analog glasses, and that the results are better 
described with a diffusion-based model. They point to the fact that a range of saturation 

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concentration values are measured under different test conditions (primarily in tests at different 
S/V ratios) and that asat is not an intrinsic value of a glass. Rather, it is simply a fitting parameter 
that is sensitive to the test conditions. Vernaz et al. (2001 [DIRS 163328], pp. 31 and 32) state: 
For most glasses, the dissolution rate is not controlled primarily by the chemical 
affinity of the hydrolysis reaction, but rather by the transport properties of the 
reacting species through the gel layer, which evolve significantly during glass 
leaching 
A current shortcoming of the French approach is the inability to identify the diffusion layer. It 
may be composed of the entire alteration layer or only a very thin layer at the layerglass 
interface. The effects of the diffusion layer are simply regressed from test data. Careful 
examinations of reacted glass surfaces with transmission electron microscopy have not detected 
the presence of such a layer. The CEA researchers admit to the present uncertainty of whether 
the entire gel layer or only a small fraction of the gel layer near the alteration front serves as the 
diffusion layer that controls the glass dissolution rate in concentrated solutions. 
The rate expression used at CEA (Vernaz et al. 2001 [DIRS 163328], p. 34) is given in 
Equation 7 with the following correspondences: rm = Rdissolution; D = Dgel; L = x; as = Cslb; abs = 
CSi; asat = C*; kf = r0. 
0 
0 
r C* 
x
gel D 
residual r ) Si C slb (C 
x
gel D 
r 
n dissolutio R 
+  
. . . 
.
. 
. . . 
.
. 
. . 
.
. 
. . 
.
. 
+ -  
. . . 
.
. 
. . . 
.
. 
= (Eq. 7) 
The silicon concentration at the glass/gel interface (Cslb) is expressed as a function of the 
Si concentration in solution (CSi) and the degree of dissociation ( a) as: 
( ) [ ] { } Si glass slb C C C a - - - = exp 1 1 (Eq. 8) 
Values of the parameters Dgel, C* (or asat), and a are obtained from a fit to the experimental data 
collected under specific test conditions (temperature, pH, S/V) to match anticipated disposal 
environments. The ability of the CEA model to predict glass degradation behavior depends on 
how well the tests conducted to determine these parameter values represent conditions in a 
breached waste package. The dependence of the forward rate, r0, by Vernaz et al. (2001 
[DIRS 163328]) on the temperature and pH must also be determined to implement Equation 7. 
The dependence of the dissolution rate on pH and temperature are not stated explicitly by 
Vernaz et al. (2001 [DIRS 163328]), except for determination of the parameters Dgel, C*, and a. 
Many of the tests conducted at CEA that led them to use a diffusion-controlled model have been 
summarized by Jgou et al. (2000 [DIRS 163260]) and by Vernaz et al. (2001 [DIRS 163328]). 
As part of the screening exercise, the evaluation of those test data was reviewed to confirm that 
they support rejection of the dissolution-control model in Equation 6. The tests described by 
Jgou et al. (2000 [DIRS 163260]) were conducted with the simple, three component glass 

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14.21Na2O20.23B2O365.56SiO2 at 90C at an S/V of 400 m-1 for up to only 14 days. The data 
in Figure 4 of the report by Jgou et al. (2000 [DIRS 163260]) do not indicate that a constant 
silica concentration has been attained within 14 days, even though the Si saturation concentration 
is exceeded. Results from these tests showed that B and Na continued to release even after the 
saturation concentration of H4SiO4 had been reached. 
Diffusion is an important process in the glass dissolution mechanism. Diffusion of water into the 
glass and alkali metals out of the glass are initial steps in glass degradation and in the long-term, 
although the latter is still under discussion. In the long-term, ion exchange and the small but 
constant precipitation of alteration products may also control the rate in silica-saturated solutions 
(McGrail et al. 2001 [DIRS 171165]). In the case of nuclear waste glasses at the beginning of 
the glass-water reaction, ion exchange quickly attains steady-state rates and can be included in 
the rate constant value. 
Accounting for diffusion-control of glass dissolution under near-saturation conditions is not 
addressed in the TSPA-LA model developed in this report for several reasons, including 
unconvincing arguments regarding the importance of diffusion-control in the gel layer during 
glass dissolution, the inability to identify the diffusion barrier, the need for additional fitting 
parameters in the model, the negligible impact on the calculated rates, and the literature that 
shows the same results are consistent with Equation 6. 
6.4.2 Composition-Independent Effective Rate Constant 
In the model developed herein, the affinity term, the (1-Q/K) term from Equation 6, and the 
intrinsic rate constant, 
.
0 k (Equation 6), are combined into an effective rate constant that has 
variability based on the results from many experiments. This approach is taken because the 
concentration of H4SiO4 is not tracked in the TSPA-LA. Thus, the variability in the intrinsic rate 
constant from the different glass compositions is combined with the natural variation in the 
affinity term because of the changes in solution concentration. 
A composition independent intrinsic rate constant is a fairly close approximation to the 
experimental results from experiments in which this quantity has been measured. The value for 
the 
.
0 k in alkaline solutions that can be extracted from the data (pH = 9.9, T = 18C, 
rB = 0.0122 g/(m2d) reported by Abraitis et al. (2000 [DIRS 163195]) on a glass with 
significantly different composition is 4.5  105 g/(m2d). When compared to the 
maximum kE_alkaline value of 3.47  104 g/(m2d) (Table 6-14) for the range of glasses that are 
expected at Yucca Mountain, the agreement is good considering that the tests that were used to 
obtain the dissolution rates were different; both tests yield a rate that is biased low because 
neither is a single-pass flow-through test. Thus, the case can be made that the variation in the 
intrinsic rate constant is small and the use of a constant value would result in an insignificant 
bias when calculating the rates. 
The range of values for the affinity term, (1-Q/K), is from 1 to 104, with the latter value coming 
from the work of Gin and Mestre (2001 [DIRS 171170]). The long-term dissolution rate is 
expected to be quite low and has been measured at values of less than 104 that of the forward 

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rate (Grambow et al. 1992 [DIRS 119131]; Gin and Frugier 2003 [DIRS 171328]; Ebert and 
Mazer 1994 [DIRS 171327]; and Lemens et al. 2003 [DIRS 171169]). The flow rates at Yucca 
Mountain are very low (BSC 2004 [DIRS 169860]). The high flow rate (15 L/y, BSC 2004 
[DIRS 167621]) at the repository divided by the surface area of the glass in a waste package 
(Equation 48 with fexposure = 4) is 4.1  105 m3/d/7.3 m2 = 1.4  106 m/d, or 1.8  1011 m/s. 
This value is several orders of magnitude lower than the fast flow rates used to determine 
forward dissolution rates with single-pass flow-through experiments (McGrail et al. 1997 
[DIRS 111039]). At these flow rates, the dissolution rate of the glass is not expected to be at 
either the forward or the final rate. At the lower flow rate of 0.15 L/y expected at the repository 
(BSC 2004 [DIRS 167621]), the dissolution rate of the glass would be much lower. These 
considerations suggest that the affinity term can be combined with the intrinsic rate constant to 
give an effective rate constant, kE. 
6.5 BASE-CASE GLASS DISSOLUTION MODEL 
As HLW glass dissolves, congruent release of radionuclides is assumed. This is calculated as the 
product of three terms: 
RRN = rateG  S  IRN (Eq. 9) 
where 
RRN = the release rate of radionuclide, RN (g/day) 
rateG = the dissolution rate of the glass (g/(m2d)) 
S = the surface area of glass contacted by water (m2) 
IRN = the inventory of radionuclide RN in the glass (g RN/g glass). 
Mathematical expressions are developed in this report for the degradation rate of the glass and 
the glass surface area contacted by water. The input data and the information used to develop 
each model are described in Section 4.1 and the sources of corroborating/supporting information 
are summarized in Table 6-3. The development of these models is described below. The 
inventory is obtained from Initial Radionuclide Inventories (BSC 2004 [DIRS 170022]). 

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Table 6-3. Corroborative/Supporting Information Used to Develop Models 
Issue Information Sources 
Mechanistic model for dissolution 
of aluminosilicate minerals and 
application to borosilicate waste 
glass 
CRWMS M&O 1998 [DIRS 100362] 
Ebert 2000 [DIRS 145944] 
Lasaga and Gibbs 1990 [DIRS 163265] 
Lasaga 1983 [DIRS 141616] 
Aagaard and Helgeson 1982 [DIRS 101530] 
Grambow 1985 [DIRS 163257] 
Jgou et al. 2000 [DIRS 163260] 
Vernaz et al. 2001 [DIRS 163328] 
Gin, Jollivet et al. 2001 [DIRS 163256] 
Gin, Ribet, and Couillard 2001 [DIRS 163255] 
Effect of glass composition on 
forward rate 
Ellison et al. 1994 [DIRS 111030] 
Van Iseghem and Grambow 1988 [DIRS 111048] 
Strachan and Croak 2000 [DIRS 163327] 
Effect of affinity term and 
alteration phases on glass 
degradation rate 
Bourcier 1991 [DIRS 119110] 
Advocat et al. 1990 [DIRS 110996] 
Patyn et al. 1990 [DIRS 111042] 
Van Iseghem and Grambow 1988 [DIRS 111048] 
Fortner and Bates 1996 [DIRS 111033] 
Ebert et al. 1993 [DIRS 111052] 
Feng et al. 1993 [DIRS 111031] 
Bates and Steindler 1983 [DIRS 104261] 
Abrajano et al. 1986 [DIRS 110990] 
Ebert, Bakel, and Brown 1996 [DIRS 111023] 
Ebert and Tam 1997 [DIRS 111029] 
Ebert and Bates 1993 [DIRS 113264] 
Range of parameter values kE Ebert et al. 1998 [DIRS 111027] 
Ebert et al. 1987 [DIRS 163248] 
Wronkiewicz et al. 1997 [DIRS 163350] 
Brady and Walther 1989 [DIRS 110748] 
Carroll et al. 1994 [DIRS 111011] 
Form of glass dissolution rate 
expression 
Glass degradation in humid air 
and dripping water 
Ebert, Hoburg, and Bates 1991 [DIRS 111028] 
Hagymassy et al. 1969 [DIRS 111034] 
Bates et al. 1990 [DIRS 111002] 
Friedman and Long 1976 [DIRS 163253] 
Bates and Steindler 1983 [DIRS 104261] 
Byers et al. 1985 [DIRS 163209] 
Luo et al. 1997 [DIRS 163271] 
Greenspan 1977 [DIRS 104945] 
Exposed glass surface area Model parameter values 
Bickford and Pellarin 1987 [DIRS 163207] 
Perez and Westsik 1981 [DIRS 111044] 
Pederson et al. 1983 [DIRS 118927] 
Jiricka et al. 2001 [DIRS 163262] 
6.5.1 Mechanistic Rate Expression for Aqueous Dissolution 
The same rate expression is used to calculate the degradation rate of glass exposed to humid air, 
dripping water, or immersed in water. This is because the same processes are operative under 
those conditions. The primary difference is how much glass must dissolve before solubility 
limits affect the degradation rate. The rate expression used in this report was developed 
originally for the dissolution of aluminosilicate minerals and later adapted for dissolution of 
borosilicate glass in aqueous solutions (Bourcier 1994 [DIRS 101563], pp. 17 to 22). The same 
rate expression that was documented in Chapter 6 of Total System Performance Assessment

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Viability Assessment (TSPA-VA) Analyses Technical Basis Document (CRWMS M&O 1998 
[DIRS 100362], p. 6-77, Equation 6-37) is used in the analyses described in this report. These 
models for aluminosilicate minerals and glass were developed for reaction conditions in which 
the amount of water was not restrictive to dissolution. Extension of the rate expression to the 
degradation of glass contacted by small volumes of water is part of this report. The rate 
expression includes parameters for the effects of glass composition, pH, temperature, and 
dissolved silica on the dissolution rate. The simplification of that rate expression for use in 
TSPA-LA calculations and the determination of parameter values that represent the degradation 
of a range of waste glass compositions in different water contact scenarios are described in this 
report. The analysis of the rate expression is summarized below. The rate expression for the 
dissolution of glass in an aqueous solution is: 
1 G f long 
Q rate k k 
K 
. . = - + . . 
. . 
(Eq. 10) 
where 
rateG = the dissolution rate of the glass, mass/(areatime) 
kf = the forward glass dissolution rate, which is a function of the glass composition, 
temperature, and solution pH, mass/(areatime) 
Q = the H4SiO4 concentration in the solution, mass/volume 
K = the apparent H4SiO4 saturation concentration for the glass, mass/volume 
klong = long-term dissolution rate, mass/(areatime). 
Equation 10 is used to simplify application to experimental data, where concentrations rather 
than activities are provided and the degradation (or dissolution) rates are given on a per area 
basis. The rate expression contains two main parts: the forward rate, kf, which represents the 
dissolution rate in the absence of feedback effects of dissolved silica, and the reaction affinity 
term, (1-Q/K) (Eq. 6). The value of the affinity term is determined based on how far the silica 
concentration (Q) is from the apparent saturation concentration (K). The value of K depends on 
the reaction conditions (experiment or repository). Because the value of Q can range between 
zero and K, the value of the affinity term is mathematically constrained to values between one 
and zero. A glass will dissolve at the highest rate possible at a given temperature and pH value 
when the value of the affinity term is one (i.e., when Q = 0). The dissolution rate will decrease 
as the value of the affinity term decreases (i.e., as the value of Q approaches K) until a minimum 
is reached. The constant term klong was included in the rate expression to prevent the calculated 
rate from becoming zero if the value of Q became equal to (or greater than) K in simulations 
over long durations (Grambow 1985 [DIRS 163257]). The kf and, perhaps, klong are 
characteristics of the glass while Q depends on the contact conditions. 
The forward glass dissolution rate depends on the glass composition, solution pH, and 
temperature (first three terms in Equation 6). 

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These dependencies can be expressed explicitly as (Ebert 2000 [DIRS 145944]): 
.. 
. 
.. 
. -   =  
. 
RT
E k k a pH 
f exp 10 0 
. (Eq. 11) 
where 
kf = forward glass dissolution rate, mass/(areatime) 
.
0 k = intrinsic rate constant, which depends only on glass composition, in units of 
mass/(areatime) 
. = order of the reaction with respect to H+, dimensionless 
Ea = activation energy for the rate limiting step Equation 1a,b, kJ/mol 
R = gas constant, 8.314  10-3 kJ/(molK) 
T = temperature, Kelvin. 
This expression is applied to all borosilicate waste glass compositions. The full rate expression 
is obtained by combining Equations 10 and 11, which yields Equation 12: 
long 
a pH 
G k 
K
Q 
RT
E k rate + .. 
. 
.. 
. -  .. 
. 
.. 
. 
.. 
. 
.. 
. -   =  
. 
1 exp 10 0 
. (Eq. 12) 
The rate expression in Equation 12 can be used for different water contact modes because the 
dissolution rate does not depend directly on the volume of water that is in contact with the glass 
or whether the contact is static or dynamic. Instead, the rate depends on the chemistry of the 
water through the pH and the concentration of dissolved silica (the latter dependence is 
expressed through the affinity term). The rate does not have an explicit time dependence 
because the rate of dissolution is a function of the solution concentrations and the temperature. 
The effect of the exposure mode (i.e., whether glass is contacted by humid air, dripping water, or 
is immersed) will be accounted for by the range of model parameter values. 
The rate expression can be further simplified to a rate expression that can be used in TSPA-LA. 
Because the dissolution rate under repository conditions will never become zero and for ease of 
implementation, the variation in the klong and the affinity term can be combined into an effective 
rate constant. This effective rate constant, then, also carries with it the variability from the 
different glass compositions that will be disposed in the repository. Equation 12 becomes: 
.. 
. 
.. 
. -   =  
RT
E k rate a pH 
E glass exp 10 . (Eq. 13) 
The value of kE takes into account the effects of the glass composition, including the 
heterogeneity of the waste inventory, as well as the effects of the solution composition. The 
model for glass degradation requires specification of three parameter values: kE, ., and Ea, and 
two variables: T and pH. Values of the parameters for use in the glass degradation model are 
determined in this report. The approach taken is to use the same values of . and Ea for all glass 
compositions and define the range and distribution of kE values so that the range of calculated 

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degradation rates spans the range of rates measured in laboratory tests. There are different 
values for both of these parameters for acid and alkaline solutions. 
6.5.2 Determination of Model Parameter Values for TSPA-LA 
6.5.2.1 Dependence on pH and Temperature 
Tests were conducted specifically to measure the effect of pH and temperature on the forward 
dissolution rate of a glass (SRL 202G) having a composition representative of DWPF glasses. 
The tests are described in detail in Appendix A. Briefly, tests were conducted following the 
MCC-1 static leach test procedure (ASTM C 1220-98 [DIRS 119321]). Monolithic glass 
specimens were immersed in test solutions having various buffered pH values for various 
durations at either 70C or 90C. At the end of the test duration, the solution was analyzed for 
boron to determine the extent of dissolution. In some tests, FeCl3, FeOOH, Fe2O3, or Fe3O4 was 
added to measure the effect of dissolved iron and the presence of iron corrosion products on the 
glass dissolution rate. Negligible amounts of iron dissolved except in the pH 1.2 and 3.7 
solutions. The normalized boron mass loss, NL(B), was calculated from the measured 
concentrations with Equation 14: 
.. 
. 
.. 
.  
 - = 
V
S B f 
B C B C B NL 
) ( 
) ( ) ( ) ( (Eq. 14) 
where C(B) is the boron concentration measured in the test solution, C(B) is the boron 
concentration measured in a blank test solution at the same temperature, S/V is the glass surface 
area/solution volume ratio, and f(B) is the mass fraction of boron in the glass. This normalizes 
the mass of boron released from the glass in the test to the surface area of the sample and the 
mass fraction of boron in the glass. The units for NL(B) are mass glass per unit area. The values 
of NL(B) were plotted against the test duration and lines fit to short-term results to estimate the 
forward dissolution rate at each pH for tests at 70C and 90C and at 90C with added iron. For 
each set of pH and temperature, the slope of the fit line gives the forward dissolution rate, which 
is expressed as the normalized boron release rate, NR(B). The data and analyses are given in 
Appendix A. The rates determined from the plots are summarized in Appendix A, Table A-8 
and reproduced in Table 6-4. The dissolution rate at 70C and pH 11.9 was determined both 
with and without the result of the test run for the shortest duration (GB6-70-1). The pH 
dependence was determined from the rate with that point included and the temperature 
dependence was determined from the rate with that point excluded. The impact of the point on 
the parameter values is negligible relative to experimental and modeling uncertainties. 

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Table 6-4. Results of Tests with SRL 202G Glass: NR(B), g/(m2d) 
Nominal pHa Tests at 70C Tests at 90C 
Tests at 90C 
(With Added Iron) 
1.0   133 
1.3 55.5 79.1  
3.7 2.26 6.47 7.17 
5.0 1.03 1.27  
8.5 0.139 0.410 0.543 
9.3 0.197 0.522 0.816 
9.8  3.38  
10.2 0.646  5.17 
11.9 8.33b 15.4 15.6 
NOTE: a pH measured at room temperature. 
b Rate determined by including result of test GB6-70-1. 
The rates measured at each temperature are used to determine the pH dependence for acidic and 
alkaline solutions. These values are plotted against the nominal solution pH in Figure 6-1 for 
acidic and alkaline solutions, respectively. The rates in acidic solution decrease as the pH 
increases, whereas the rates in alkaline solutions increase as the pH increases. 
The results of the 70C tests were fit with regression (KaleidaGraph) lines having the equations: 
log10(rateG) = 0.482  pH + 2.31 (Eq. 15) 
for acidic solutions and 
log10(rateG) = 0.543  pH  5.63 (Eq. 16) 
for alkaline solutions. These fits are shown in Figure 6-1 by dashed lines. The results of tests 
conducted at 90C with and without added iron are experimentally indistinguishable at all pH 
values, and the combined results of tests at 90C with and without added iron were fit with 
regression lines. This result is significant because an abundance of iron corrosion products are 
expected to be present in a breached waste package due to corrosion of iron-containing structural 
components, including the waste package itself. These results show significant concentrations of 
dissolved iron will only occur when the solution pH is very low (near 3.7), and that the chemical 
effects of dissolved iron will not impact the glass degradation rate at any pH value. Iron 
corrosion products may affect the glass degradation rate indirectly through sorption of dissolved 
silica. 
Data for tests at 90C in acidic and alkaline solutions were fit separately with lines having the 
equations: 
log10(rateG) = 0.485  pH + 2.59 (Eq. 17) 
in acidic solutions and: 
log10(rateG) = 0.471  pH  4.35 (Eq. 18) 

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in alkaline solutions. These fits are shown as dotted lines in Figure 6-1. Because results are only 
available for two temperatures, the results in acidic solution at both temperatures and the results 
in alkaline solutions at both temperatures were combined to determine the average slopes. 
Regressions to results at both temperatures are shown as solid lines in Figure 6-1 for acidic and 
alkaline solutions. The equations of the regressed lines are: 
log10(rateG) = 0.494  pH + 2.51 (Eq. 19) 
for acidic solutions and: 
log10(rateG) = 0.491  pH 4.73 (Eq. 20) 
for alkaline solutions. The average slopes are 0.49 for acidic solutions and 0.49 for alkaline 
solutions. These values are used as the values for the pH dependence in the TSPA-LA glass 
model. Only the slope of these lines is used. Separate lines having this slope are fit to the 70C 
and the 90C rates in the next step. 
The pH dependencies determined for dissolution in acidic and alkaline solutions were regressed 
to the measured rates to determine the temperature dependence. Lines having slope 0.49 were 
regressed to the data for tests at 70C and 90C in acidic solutions, and lines having slope 0.49 
were regressed to the data for tests at 70C and 90C in alkaline solutions. Terms for the effects 
of temperature and kE were expressed as Aacid for tests in acidic solutions and Aalkaline for tests in 
alkaline solutions so that the test results could be regressed. The effects of temperature are 
distinguished in a subsequent step. The sum of the residuals between the measured rates 
(Table 6-4) and the rates calculated with Equation 21: 
log10(rateG) = Aacid  0.49  pH (Eq. 21) 
were minimized to determine the value of Aacid for acidic solutions, and the residuals between the 
measured rates (from Table 6-4) and the rates calculated with Equation 22: 
log10(rateG) = Aalkaline + 0.49  pH (Eq. 22) 
were minimized to determine the value of Aalkaline for alkaline solutions. Calculation of the rates 
and minimization of the residuals was done using a Microsoft Excel spreadsheet (Appendix A, 
Table A-9). The resulting equations for the regressed fit lines are: 
log10(rateG) = 2.34  0.49  pH for acidic solutions at 70C (Eq. 23) 
log10(rateG) = 2.60  0.49  pH for acidic solutions at 90C (Eq. 24) 
log10(rateG) = -5.12 + 0.49  pH for alkaline solutions at 70C (Eq. 25) 
log10(rateG) = -4.54 + 0.49  pH for alkaline solutions at 90C (Eq. 26) 
These best fit lines are plotted along with the measured rates in Figure 6-2. 
The Arrhenius relationship was used to calculate the activation energy from the rates at 70C 
and 90C at the same solution pH. This approach is valid even with only two temperatures, since 

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many previous studies have shown that the rate has Arrhenius temperature dependence as seen in 
Equation 5. The rate is expressed as a function of temperature as: 
rateG = B  exp(Ea/RT) (Eq. 27) 
where B is a constant and R is the ideal gas constant (8.314  10-3 kJ/(molK)). The ratio of the 
rates at 90C and 70C is: 
. . . 
. . .
.. 
. 
.. 
. 
- = 
2 1 1
2 1 1 exp 
) ( 
) ( 
T T R 
E 
T rate 
T rate a 
G
G (Eq. 28) 
Inserting T1 = 70C (= 343 K) and T2 = 90C (= 363 K) and R = 0.008314 kJ/(mol K) gives 
{ }a 
G
G E 
C rate 
C rate 
  = 

 -2 10 932 . 1 exp 
) 70 ( 
) 90 ( 
(Eq. 29) 
Source: Table 6-4. 
Figure 6-1. Linear Regression of Test Results at 70C and Combined Results for Tests With and Without 
Added Iron at 90C in (a) Acidic Solutions and (b) Alkaline Solutions 
Equations 23 and 24 were used to calculate the activation energy in acidic solutions, and 
Equations 25 and 26 were used to calculate the activation energy in alkaline solutions. For 
acidic solutions, the rates calculated at a pH value of 0 are 219 g/(m2d) and 398 g/(m2d) at 70C 
and 90C, respectively. The ratio rate (90C)/rate(70C) is 398/219 = 1.820. Solving 
Equation 29 with this ratio gives a value for the acid side activation energy of 
Ea = ln(1.820)/0.01932 = 31.0 kJ/mol. 
Similarly, the alkaline side activation energy used in the model is Ea = 69 kJ/mol. 

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Source: Appendix A, Table A-9. 
Figure 6-2. Plot of Measured Rates and Regressed Lines Against pH Measured at Room Temperature 
Different steps in the reaction mechanism for the dissolution of borosilicate glasses dominate in 
acidic and alkaline solutions. These reactions have different pH dependencies, as shown in 
Figure 6-1 for SRL 202G glass, and intersection of the lines in near-neutral solutions gives rise 
to the overall V-shaped pH dependence seen in Figure 6-2. 
6.5.2.2 Dependence on Glass Composition 
The glass degradation model developed in this report is representative of the range of acceptable 
waste glass compositions for disposal. The effect of the glass composition on the glass 
dissolution rate is represented in Equation 6 by the intrinsic dissolution rate constant ( 
.
0 k ). The 
value of 
.
0 k is determined by separating the contributions of the pH and temperature terms from 
the measured forward rate. The value of 
.
0 k that is extracted from the measured forward rate will 
depend on the values used for the pH (.) and temperature (Ea) dependencies. Tests were 
conducted to estimate the forward dissolution rates of 9 glasses having compositions spanning 
the likely composition ranges of waste forms for DWPF, WVDP, and Hanford wastes 
(DTN: MO0308ANLGPC01.528 [DIRS 164790], Table 1). Glasses having concentrations of 
glass-forming components (e.g., Al, B, Fe, and Si) that are representative of concentrations 
expected in HLW glasses are referred to as reference high-level glasses in this report to 
distinguish them from other glass compositions that were tested to provide extreme 
compositions, for example, a glass without aluminum. Glass durability will not be significantly 
affected by the different radionuclide contents of different wastes because of the relatively low 
concentrations in the glass. However, differences in the amounts of other components in 
different wastes, such as aluminum and iron, will influence the glass composition and may affect 
glass durability. 

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The suite of glasses used in the study was selected to study the sensitivity of 
.
0 k and the 
dissolution rate with respect to major components. Glasses were selected specifically to span the 
range of possible aluminum contents because the aluminum content is known to affect the 
durability of waste glasses in short-term tests (Ellison et al. 1994 [DIRS 111030], pp. 35, 39, 42, 
and 47). The aluminum content is also suspected to affect the propensity for the formation of 
zeolite-alteration phases (Van Iseghem and Grambow 1988 [DIRS 111048], pp. 631 and 639; 
Ellison et al. 1994 [DIRS 111030], p. 46; Strachan and Croak 2000 [DIRS 163327]). The 
compositions of the glasses that were tested are listed in Table 6-5. The PNL 76-68 glass was 
included in the study as a glass with no aluminum. The LD6-5412 and Hanford L compositions 
were developed for low-activity wastes and have higher sodium contents than are anticipated for 
HLW glasses. While these glass compositions may be outside the range of likely HLW glasses, 
they provide useful measures of the sensitivity of 
.
0 k at or near the lower bound of aluminum 
content and upper bound of sodium content of waste glasses. This set of glasses also provides a 
wide composition range: B (5.34 to 12.9 mass % B2O3), Fe (0.12 to 22.9 mass % Fe2O3), Na 
(8.00 to 20.2 mass % Na2O), and Si (30.2 to 58.9 mass % SiO2) contents. 
Test specimens were subjected to MCC-1 tests at 90C for durations between 1 and 15 days to 
measure the forward dissolution rates. These tests were conducted with demineralized water and 
the solution pH was allowed to drift as the glasses dissolved. The pH values attained in the tests 
were all greater than 9, so the results were analyzed with the parameters for alkaline solutions. 
The pH values were measured at room temperature. The glass dissolution rate concentration was 
determined from the boron concentrations. Test results are given in 
DTN: MO0308ANLGPC01.528 [DIRS 164790], Table 2. Values of log10( 
.
0 k ) were extracted 
from the measured rates by separating the effects of the pH and temperature using Equation 13 
with parameter values . = 0.49 and Ea = 69 kJ/mol (Section 6.5.2.1 and Appendix B, Table B-1). 
The mean  one standard deviation of the values of log10( 
.
0 k ) calculated for the nine glasses is 
log10( 
.
0 k ) [g/(m2d)] = 5.14  0.17 (Appendix B, Table B-1). The mean and standard deviation 
for the subset of reference HLW glasses (Hanford-D, WV ref 6, SRL 51S, SRL 165U, SRL 
202U, and SRL 131U) is log10( 
.
0 k ) [g/(m2d)] = 5.07  0.13. The percent relative standard 
deviation is small in both cases (100  0.17/5.14 = 3.31% and 100  0.13/5.07 = 2.56%, 
respectively for the log10 values; 100(2.042  1.380)105/1.380  105 = +48%, 100(0.9333  
1.380)105/1.380  105 = 32%, 100(1.585  1.175)105/1.175  105 = +35%, 100(0.8710  
1.175)105/1.175  105 = 26%, for the values of 
.
0 k ). This indicates that the glass composition 
has only a small effect on the value of log10( 
.
0 k ) or 
.
0 k . A single value of 
.
0 k can be used to 
represent the range of HLW glass compositions. 

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Table 6-5. Compositions and Dissolution Rates of Glasses Used in MCC-1 Tests 
Elemental Mass % 
Glass 
Al B Fe Na Si 
NR(B)a, 
g/(m2d) pH log10(k0) 
[g/(m2d)] 
LD6-5412 6.82 1.66 0.09 15.0 27.5 0.47 9.3 5.04 
Hanford-L 6.33 2.75 4.03 14.8 17.9 0.97 9.5 5.26 
Hanford-D*,b 5.36 2.17 16.1 11.7 14.1 1.8 10.5 5.04 
WV ref 6* 3.17 4.00 8.41 5.93 19.2 0.69 9.5 5.11 
SRL 51S* 2.79 2.30 8.53 7.11 26.3 0.66 9.9 4.90 
SRL 165U* 2.16 2.10 8.21 8.04 24.7 1.0 9.6 5.23 
SRL 202U* 2.03 2.48 7.97 6.61 22.9 0.69 9.8 4.97 
SRL 131U* 1.73 3.00 8.85 8.95 20.4 1.2 9.8 5.21 
PNL 76-68 0 2.79 6.41 10.5 19.8 1.1 9.2 5.46 
Source: DTN: MO0308ANLGPC01.528 [DIRS 164790]. 
NOTES: aRate measured at 90C. 
bGlasses with asterisks are reference HLW glasses. 
6.5.2.3 Effects of the Affinity Term on the Glass Degradation Rate 
The affinity term (1-Q/K), in Equations 6 and 12, provides a measure of the feedback effects of 
solutes that are reactants in the reverse of the rate-determining step for glass dissolution 
(Bourcier 1991 [DIRS 119110], p. 13). The rate when the value of the affinity term is one 
provides the most conservative upper bound for the dissolution rate. This is the forward glass 
dissolution rate. This is an overly conservative bound to use in TSPA-LA calculations, because 
the value of the affinity term cannot remain at a value of one after water contacts the glass and 
the glass begins to dissolve. The amount of dissolved silica present in tuff groundwater is itself 
high enough to give a value of the affinity term that is significantly less than one when it contacts 
waste glass. If a thin film of water forms on the glass, for example, by condensation of water 
vapor, the value of the affinity term will decrease significantly after a small amount of glass has 
dissolved because the release of even a little silica into solution will generate high silica 
concentrations in the small volume of water. The analyses in this section were done to identify a 
defensible upper bound to the dissolution rate that is less conservative than the forward rate. 
It is useful to remember that the affinity term is a thermodynamic term even though it is used in a 
kinetic equation and it is an approximation for the complete dissolution mechanism. From a 
calculation point of view, Q takes on values that depend on the amount of glass dissolved and the 
silica-bearing phases that precipitate. However, in the long term, Q takes on a steady state value 
that depends on the rates of precipitation of phases containing SiO2 and the dissolution of the 
glass. At high amounts of glass dissolved in a static solution, the dissolution rate of some glasses 
has been observed to increase after a long period of nearly constant dissolution rate. 
van Iseghem and Grambow (1988 [DIRS 111048]) first noticed this effect and determined that it 
was the result of the precipitation of analcime (a zeolite). Since 1988, several authors have 
noticed the same phenomenon under a variety of different test conditions (Ebert et al. 1993 
[DIRS 111052], pp. 573 and 575; Patyn et al. 1990 [DIRS 111042], p. 301, Figure 1; 
Feng et al. 1993 [DIRS 111031], pp. 195 and 200, Figure 3; Bates and Steindler 1983 
[DIRS 104261], p. 85; Abrajano et al. 1986 [DIRS 110990], pp. 254 and 255, Figure 1; 
Bourcier 1991 [DIRS 119110], p. 211, Figure 2; Ebert, Bakel, and Brown 1996 [DIRS 111023], 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 6-22 October 2004 
p. 573; McGrail, Martin, and Lindenmeier 1997 [DIRS 111040], p. 257). Other processes that 
remove dissolved silica from solution can impact the glass degradation rate in the same way. 
This has been observed in tests conducted in the presence of various clays (Gin, 
Jollivet et al. 2001 [DIRS 163256]). Tests in the presence of ductile iron and various iron oxides 
have shown a similar effect (McVay and Buckwalter 1983 [DIRS 101728]; Werme et al. 1990 
[DIRS 163346]). The removal of silica from solution due to sequestration in glass alteration 
phases or sorption to other phases has the same effect on the glass degradation rate. The 
long-term impact of these processes in the repository will depend on the precipitation rates of the 
alteration phases and sorption capacities of iron corrosion products. The possibility that the 
precipitation rate or sorption capacity will limit the glass degradation rate is not included in the 
model, thereby making the model conservative. 
Phases like analcime that can cause enhanced dissolution through consumption of silica are 
unlikely to form under most repository conditions. One exception is the case where the relative 
humidity is greater than 44% and the temperature of the glass is greater than 99C. Under these 
conditions, similar to those of a vapor hydration test, a thin layer of water can form on the 
surface of the glass because the reaction kinetics are high enough and the initial solution that 
forms has a water vapor pressure less than the surrounding atmosphere. Unlike the vapor 
hydration test, however, the repository provides essentially an infinite amount of CO2 gas at 
constant pCO2 = 101.5 kPa (10-3.5 atm). It will react with the solution as it forms initially and 
limit the rise in pH. Because these conditions have not been investigated (i.e., VHTs with 
constant partial pressure of CO2), a limit based on other information is used in this model. 
A measure of the pH of the solution that forms on the test specimen in a vapor hydration test is 
given by Vienna et al. (2001 [DIRS 163331]), Jiricka et al. (2001 [DIRS 163262]) and 
Ebert et al. (1991 [DIRS 111026]), where the pH(25C) either measured on the test specimen or 
in the solution that dripped from the test specimen can be as high as 12. The high pH(25C) of 
the solution that is calculated in In-Package Chemistry Abstraction (BSC 2004 
[DIRS 167621]) is 8.5. The pH at elevated temperature is lower than at 25C because of the 
shift of the water dissociation constant to lower values with increasing temperature. The pH shift 
is about 0.8 at 90C and 0.6 at 70C. Therefore, above 99C, it is assumed that the pH in this 
model is fixed at 10 and the increase in the rate is calculated with Equation 13. In practical 
terms, alteration of the glass in humid air is limited to the temperature range 100C to 125C 
because for pure water, the relative humidity at 1 atmosphere total pressure falls below 44% at 
125C. If salt solutions from the evaporation of groundwater elsewhere in the drift or waste 
package control the relative humidity, then the upper temperature at which vapor phase alteration 
would occur is less than 125C. Both 125C and a pH value of 10 represent conservative values. 
6.5.2.4 Maximum Value of kE for Glass Degradation in Alkaline Solutions 
Triplicate 7-day PCTs were conducted with the nine glasses used to evaluate the effect of glass 
composition on the value of 
.
0 k (Section 6.5.2.2) (DTN: MO0308ANLGPC01.528 
[DIRS 164790]). The 7-day PCTs were conducted at 90C. The averages of tests with each 
glass were used to extract values of kPCT using Equation 13 with parameter values . = 0.49 and 
Ea = 69 kJ/mol (Appendix B, Table B-3). The averages of the measured 7-day PCT rates (based 
on the release of boron), the measured final pH, and the extracted value of log10(kPCT) are 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 6-23 October 2004 
summarized in Table 6-6. The mean and standard deviation for glasses in Table 6-6, except for 
EA glass, is log10(kPCT) [g/(m2d)] = 3.574  0.485 (the average of the two sets of analyses of 
SRL 51S glass was used to calculate the mean and standard deviation). The value of the mean 
plus two standard deviations (rounded to three significant figures) is 
log10(kPCT) [g/(m2d)] = 4.54. This value is used as the maximum value for the parameter 
log10(kE) in the base model. This value bounds the values for the other glasses in Table B-2 
(Appendix B) that were excluded from the determination of kE. The fact that the maximum 
value of kE is greater than the value of kE calculated from the 7-day PCT response of the EA 
glass implies that the upper limit rate used in the TSPA-LA calculations will bound the 
dissolution rates of all waste glasses that meet the DOE acceptance criterion that the response 
(i.e., the average dissolution rate) of a waste glass must be lower than the response of the EA 
glass in PCT-A (DOE 2002 [DIRS 158873], Section 4.8.1). The maximum value of log10(kE) in 
alkaline solutions is 4.54, and the maximum value of kE_alkaline is 3.47  104 g/(m2d). Use of this 
value in Equation 13 gives the maximum dissolution rate for all HLW glasses. This value is 
used to calculate the maximum dissolution rate for alkaline solutions. The expression in terms of 
log10(rateG) is: 
log10(rateG) = 4.54 + 0.49  pH + log10 .. 
. 
.. 
. 
.. 
. 
.. 
. - 
RT 
kJ/mol 69 exp (Eq. 30) 
Table 6-6. Values of kPCT Extracted from 7-day PCTs 
Glass NR(B) (g/(m2d)) pH 
log10(kPCT) 
[g/(m2d)] Reference 
SRL 51S 0.0381 10.66 3.29 
MO0308ANLGPC01.528 
[DIRS 164790] 
SRL 51S 0.0353 10.33 3.42 
MO0308ANLGPC01.528 
[DIRS 164790] 
SRL 165U 0.0440 10.31 3.52 
MO0308ANLGPC01.528 
[DIRS 164790] 
SRL 202U 0.0426 10.42 3.45 
MO0308ANLGPC01.528 
[DIRS 164790] 
SRL 131U 0.687 11.63 4.07 
MO0308ANLGPC01.528 
[DIRS 164790] 
WV ref 6 0.0386 9.98 3.63 
MO0308ANLGPC01.528 
[DIRS 164790] 
Hanford-D 0.0516 10.67 3.41 
MO0308ANLGPC01.528 
[DIRS 164790] 
SRL202G 0.0869 11.11 3.42 
MO0306ANLGIM02.525 
[DIRS 164330] 
Hanford-L 0.0679 10.96 3.39 
MO0308ANLGPC01.528 
[DIRS 164790] 
PNL 76-68 0.171 9.43 4.54 
MO0308ANLGPC01.528 
[DIRS 164790] 
LD6-5412 0.0117 11.20 2.51 
MO0308ANLGPC01.528 
[DIRS 164790] 
EA 1.17 11.87 4.18 
Ebert et al. 1998 
[DIRS 111027] 

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ANL-EBS-MD-000016 REV 02 6-24 October 2004 
6.5.2.5 Maximum Value of kE for Glass Degradation in Acidic Solutions 
The dissolution of borosilicate waste glasses causes the solution to become alkaline because of 
the ion exchange reactions that occur and because mineral precipitation leaves alkali ions in 
solution. Acidic solutions arise from other sources such as by radiolysis of the solution in 
contact with the glass or the corrosion of steel in the waste package. Fairly high radiation fields 
are needed to generate enough acid to overcome the hydroxide generated by glass dissolution 
under test conditions relevant to disposal conditions. For example, in tests conducted at an S/V 
of about 30 m-1, gamma radiation exposures of about 10 Gy/h (1  103 R/h) were required to 
maintain pH values below 7 during the dissolution of a DWPF glass (Ebert et al. 1987 
[DIRS 163248]). At the much higher S/V relevant to the disposal system, glass dissolution will 
have a much stronger impact on the solution pH than radiolysis. For example, dissolution of an 
actinide-doped DWPF glass at 90C and an S/V of 340 m-1 in a 35 Gy/h (3.5  103 R/h) gamma 
radiation field resulted in alkaline pH values for tests conducted up to two years 
(Wronkiewicz et al. 1997 [DIRS 163350], p. 48). 
While there have been experiments with glasses under acidic conditions, the rate controlling 
steps in the reaction have not been fully investigated. The approach taken in this report is to use 
the same form as the rate expression for degradation in alkaline solutions and extract model 
parameters from test data for dissolution in acidic solutions. Degradation in acidic solutions is 
probably dominated by the hydrolysis of AlO bonds rather than SiO bonds (Abraitis et al. 
2000 [DIRS 163195]; Brady and Walther 1989 [DIRS 110748], p. 2,828; Carroll et al. 1994 
[DIRS 111011], p. 535) that results in a V-shaped pH dependence observed for many 
borosilicate glasses. Some evidence for the lack of significant feedback in acidic solutions is 
given by the results of the MCC-1 tests discussed in Appendix A, where less negative deviation 
from the linear rate observed in the short-term tests (roll over) is seen at pH 3.7 and pH 5.0 than 
in tests in alkaline solutions. The roll over seen in tests at pH 1.3 occurs because the glass is 
almost completely dissolved at longer durations. That is, the roll over is due to the decrease in 
the amount of glass (the source of boron) available to react rather than to feedback effects of 
dissolved silica. 
No credit is taken in the TSPA-LA glass degradation model for feedback effects slowing glass 
dissolution in acidic solutions. The upper limit for the dissolution rate in acidic solutions is 
determined directly from the results of the pH buffer tests discussed in Section 6.5.2.1. The 
value of kE for acidic solutions is calculated by combining Equation 24 and the log10 of 
Equation 13 (with . = 0.49, Ea = 31 kJ/mol, and R = 0.008314 kJ/mol K) for dissolution at 90C 
(363 K): 
( ) .. 
. 
.. 
. 
.. 
. 
.. 
. 
 
- +  - =  - 
363 R 
31 exp log 49 . 0 log 49 . 0 60 . 2 10 10 pH k pH E (Eq. 31) 

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ANL-EBS-MD-000016 REV 02 6-25 October 2004 
Canceling the pH terms and solving for log10(kE) gives: 
( ) .. 
. 
.. 
. 
. .. 
. 
. .. 
. 
  
- - 
 
= 
K) 363 ( K)) kJ/(mol (0.008314 
kJ/mol 31 exp log 
) d (m
g 60 . 2 k log 10 2 E 10 (Eq. 32) 
from which the value of log10(kE_acid) = 7.06 g/(m2d) and kE_acid = 1.15  107 g/(m2d). This is 
the maximum value of kE in acidic solutions. 
The upper bound glass degradation rate for the acidic pH values expressed in terms of 
log10(rateG) is: 
( ) .. 
. 
.. 
. 
.. 
. 
.. 
. 
 
- +  - = 
363 R 
31 exp 49 . 0 06 . 7 log10 pH rateG (Eq. 33) 
This is checked by comparing the rate calculated at pH 5.0 and 90C with the rate that was 
measured experimentally: 
( ) .. 
. 
.. 
. 
. .. 
. 
. .. 
. 
  
- + - = 
K) (363 K)) kJ/(mol (0.008314 
kJ/mol 31 exp log 0.49(5.0) 7.06 rate log 10 G 10 (Eq. 34) 
log10(rateG) = 0.149 g/(m2d) (Eq. 35) 
rateG = 1.41 g/(m2d) (Eq. 36) 
The measured rate at pH 5.0 and 90C is 1.27 g/(m2d) (Table 6-4). The two values are in good 
agreement. 
6.5.2.6 Support for the Selection of kE 
In this section, the methodology for the selection of kE is discussed by selecting a base case and 
several other options to obtain values for kE. The maximum value for log10(kE) used in the 
model for TSPA-LA for dissolution in the high pH solutions is based on the values determined 
from 7-day PCT results for glasses in Table 6-6 except EA glass. The upper bound to the value 
of log10(kE) for the alkaline pH values is taken as the mean value for log10(kPCT,ref) [g/(m2d)] plus 
two standard deviations (which is 4.54). Several alternatives to the base case were considered 
for selecting the maximum value of kE to bound the range of potential waste glasses in alkaline 
solutions (values summarized here were calculated in Appendix B, Table B-3). These are 
summarized below in the order of increasing level of conservatism. 
Base CaseUse the average 7-day PCT rate for glasses in Table 6-6 except EA: kmax, alkaline = 
kPCT. 
The selected approach uses the average value of the dissolution rates of glasses determined from 
7-day PCT results (at 90C) to determine the value of the effective rate constant. The glass 
compositions that were tested span the expected composition range for waste glasses with regard 

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ANL-EBS-MD-000016 REV 02 6-26 October 2004 
to the Al, Na, and Si contents. The mean log10(kPCT, ref) [g/(m2d)] for all glasses in Table 6-6, 
except EA glass, is 3.57  0.48. 
Option 1aUse the average 7-day PCT rate for all glasses in Table 6-6: kmax, alkaline = kPCT. 
The mean value of log(kE) for the all the glasses is log10(kPCT, ref) [g/(m2d)] = 3.58  0.47. 
Option 1bUse the average 7-day PCT rate for only the HLW glasses in Table 6-6: kmax, alkaline = 
kPCT. 
The mean log10(kPCT, ref) [g/(m2d)] for the seven reference HLW glasses in Table 6-6, namely, 
SRL 51S (average), SRL 165U, SRL 202U, SRL 131U, WV ref 6, Hanford-D, and SRL 202G, is 
3.57 and the standard deviation is 0.23 g/(m2d). 
Option 2Use the average dissolution rate of EA glass in 7-day PCT conducted in tuff 
groundwater: kmax, alkaline = kPCT-B, EA. 
The dissolution rate in tuff groundwater is more repository-relevant than the rate measured in 
demineralized water with 7-day PCT because the composition of the leachant is similar to that of 
groundwater likely to first contact the waste glass. The average dissolution rate of EA glass in a 
tuff groundwater under these conditions (at 90C) is 0.64 g/(m2d) with a pH of 11.61 at the end 
of 7 days. The value of log10(kPCT-B, EA) [g/(m2d)] extracted from these results with Equation 51 
is 4.05. The dissolution rate in tests with tuff groundwater based on the release of boron is about 
one-half of the rate measured with 7-day PCT in demineralized water (Option 3). This is 
because the dissolved silicon already present in the groundwater solution used in the tests 
(approximately 46 mg/L; Ebert et al. 1998 [DIRS 111027], p. 29, Table 2) has a significant effect 
on the dissolution rate as measured by the release of boron. The uncertainty in log10(kE) for tests 
with EA glass in demineralized water (Option 3) is also used as the uncertainty for tests with EA 
glass in tuff groundwater, namely,  0.23. 
Option 3Use the average dissolution rate of EA glass in 7-day PCT: kmax, alkaline = kPCT, EA. 
The average dissolution rate in a 7-day PCT is calculated by dividing the normalized mass loss 
by the test duration, which is 7 days. The 7-day PCT rate includes the effect of the buildup of 
dissolved glass components during the test. The average boron concentration for a 7-day PCT 
conducted with the EA glass at three different laboratories is 553  30 mg/L and the average pH 
is 11.87 (Ebert 2000 [DIRS 145950]). The average normalized dissolution rate is calculated by 
dividing the concentration by the mass fraction of boron in the EA glass, which is 0.0347, by the 
S/V of the test, which is 2,000 m-1, and by the test duration, which is 7 days. The average 
dissolution rate in 7-day PCT (at 90C) is calculated to be about 1.17 g/(m2d) at pH 11.87. The 
value of log10(kE) calculated with Equation 51 is 4.18 g/(m2d). The standard deviation of the 
measured boron concentration is 5.4%. This is used as the relative uncertainty in the value of 
log10(kE), so that the value of log10(kE) [g/(m2d)] is 4.18  0.23. 
This option empirically relates the bounding dissolution rate to the product acceptance 
requirement for vitrified waste forms (DOE 2002 [DIRS 158873], Section 4.8.1) requires 
vitrified waste forms to have lower releases of B, Li, and Na than the EA glass in the PCT-A 

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ANL-EBS-MD-000016 REV 02 6-27 October 2004 
(DOE 1996 [DIRS 102589], Section 3.1). This is tantamount to requiring the PCT-A rates of 
accepted waste glasses to be less than the PCT-A rate of the EA glass. However, because 
different pH values will likely be attained in tests with different glasses, the values of kE for all 
waste glasses accepted for disposal will not necessarily be less than kE for the EA glass. Since 
the values of kE for future waste glass compositions can be calculated and compared with kE for 
the EA glass, this option provides a useful upper bound. 
Option 4Use the intrinsic dissolution rate measured for reference glasses: kmax, alkaline = k0, ref. 
This option uses the intrinsic dissolution rates that have been measured for reference waste 
glasses to determine the effective rate constant. Forward dissolution rates measured with shortterm 
MCC-1 tests (at 90C) for the six reference glasses likely to bound the compositions of 
waste forms for DWPF, WVDP, and Hanford were presented earlier in this report (glasses SRL 
51S, SRL 165U, SRL 202U, SRL 131U, WV6, and Hanford-D in Table 6-5). The mean and 
standard deviation for the intrinsic dissolution rates of those 6 HLW glasses is log10(k0, ref) 
[g/(m2d)] = 5.07  0.13 (Appendix B, Table B-1). 
The values of kE extracted from these tests are summarized in Table 6-7 for values calculated 
based on the releases of boron. Bounding values are calculated as the mean plus two standard 
deviations in order to directly compare the values of log10(kE). The highest bounding value of 
log10(kE) is that calculated from the forward rates of the tests with reference glasses (Option 4, 
kE = k0 ref); these provide the most conservative estimates that have been measured. However, 
this bound is overly conservative because it neglects the slowing effect of the affinity term on the 
dissolution rate. The lowest bounding value of log10(kE) is that calculated from the 7-day PCT 
rates for tests with HLW reference glasses (kPCT, ref). Use of an upper bound value of log10(kE) 
that is higher than the value for EA glass takes into account the possibility that a waste glass 
could be less reactive than the EA glass in PCT-A, but still have a higher long-term dissolution 
rate than the EA glass. 
Based upon this discussion, it is concluded that the kE determined for the model use is 
appropriate. 
Table 6-7. Values of kmax, alkaline Calculated Using Different Options 
log10(kE) [g/(m2d) ]a 
Option Measured Value Mean  sb Bounding Valuec 
Base Case (all glasses except EA) kE = kPCT, ref 3.57  0.48 4.54 
1a (all glasses) kE = kPCT, ref 3.58  0.47 4.52 
1b (HLW reference glasses) kE = kPCT, ref 3.57  0.23 4.05 
2 (EA in tuff groundwater) kE = kPCT-B, EA 4.05  0.23 4.51 
3 (EA in demineralized water) kE = kPCT, EA 4.18  0.23 4.64 
4 (forward rates) kE = k0, ref 5.07  0.13 5.33 
NOTES: a Effective rate constant based on release of boron. 
b Mean  one standard deviation. 
c Upper bound to value of log10(kE) (kmax, alkaline) is calculated as the mean plus two standard 
deviations. 

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6.5.3 Dissolution of Glass Exposed to Humid Air or Dripping Water 
6.5.3.1 Interaction of Humid Air with Waste Glass 
In the unsaturated environment of the Yucca Mountain site, it is likely that waste glass will be 
contacted initially by humid air after failure of the waste package and canister. When glass is 
exposed to humid air, water molecules will sorb onto specific sites on the glass surface, primarily 
silanol and alkali metal sites. The amount of water that sorbs on the glass will depend on the 
relative humidity of the air, the temperature of the glass surface, and how fast the water reacts 
with the glass. The sorption isotherm for water on a reference waste glass made with SRL 165 
frit has been measured at room temperature (Ebert, Hoburg, and Bates 1991 [DIRS 111028], 
p. 134, Figure 1b) (Figure 6-3). The measured isotherm was fit using the following equation: 
. = [-b / ln(RH/100)]1/r (Eq. 37) 
where . is the number of statistical monolayers of sorbed water, RH is the relative humidity, b 
and r are constants with values of b = 3.2 and r = 1.5 for SRL 165U glass. 
Source: Ebert, Hoburg, and Bates 1991 [DIRS 111028], p. 134, Figure 1b. 
Figure 6-3. Sorption Isotherm for Water on SRL 165 Glass at Room Temperature 
The shape of the isotherm is similar to isotherms for water on silica and quartz (Hagymassy et al. 
1969 [DIRS 111034], p. 489). The first layer forms at a relative humidity of about 4%. This 
corresponds to sorption at the primary silanol sites (chemisorption). Subsequent layers form as 
water vapor bonds with chemisorbed water to form beads of water on the glass surface. The 
amount of sorbed water increases to about 3 layers when the relative humidity is 54% and six 
layers when the relative humidity is 80%. At relative humidities above about 80%, a sufficient 
amount of water has condensed to coalesce into a film of water approximately 20-nm to 

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30-nm thick covering the entire surface. Isotherms have not been measured for the sorption of 
water on waste glass at higher temperatures. A similar relationship between the amount of water 
that forms on the glass and the relative humidity is expected at higher temperatures. 
No hysteresis was observed in the isotherm collected for the waste glass, which indicates that the 
sorbed water did not react with the glass at this temperature and did not condense in tight pores 
during the several days required to measure the isotherm. The absence of hysteresis indicates 
that dealkalization reactions did not occur to a significant extent under these conditions. 
However, sorbed and condensed water will react with the glass at higher temperatures 
(discussion of vapor hydration tests in Section 6.5.3.3). The interaction between glass and water 
vapor at temperatures below 100C has not been adequately investigated. However, as the 
temperature decreases from 125C in the repository, the relative humidity increases and the 
reaction rates decrease. Rates as a function of temperature have been investigated and are 
discussed later in this section. However, these rates were obtained at 100% relative humidity 
and limited amounts of CO2 at temperatures greater than 125C. At temperatures above 125C 
in the repository (1 atmosphere total pressure), the relative humidity will be below 44% where 
experimental evidence shows that there is no alteration of the glass. This is consistent with the 
observations by Vernon (1933 [DIRS 100942]) who found no water on iron below 65% relative 
humidity. 
In the various configurations in which fractured glass may be contacted by humid air or dripping 
water, water may drip or flow away from the glass or may accumulate over time while 
contacting the glass. As glass dissolves in the adsorbed water, the ionic strength increases 
causing the water vapor pressure to drop. While the vapor pressure changes little at the 
beginning, the ionic strength of the solution can be quite high at long contact times. Hence, the 
water vapor pressure of any solution on the surface of the glass at long time would be expected 
to be lower than the water in the repository. To be conservative, the case could be made that 
continuous exposure to water-saturated air will result in a process of vapor condensation, flow 
across the glass, and dripping wherein dissolved species can be transported away from the glass 
and fresh water vapor continually condenses. The corrosion rate of the glass under these 
conditions will be affected by the rates at which water vapor condenses in the film of water on 
the surface and solution drips from the glass. These processes will affect the glass dissolution 
rate through their effects on the solution chemistry of the film. How this process starts has not 
been adequately investigated, however, the rate at which the glass reacts with the water, either 
vapor or condensed film, depends on the temperature  faster at higher temperatures. Slowing 
the process is the fact that at a fixed total pressure of 0.1 MPa (1 atmosphere), the relative 
humidity of pure water drops below 44% at 125C, meaning at temperatures above that no 
reaction occurs. The effects of the condensation, flow, and drip rates on the glass dissolution 
rate are taken into account in the TSPA-LA glass degradation model empirically with 
experimentally measured rates to determine model parameter values. That is, even though water 
condensation and transport processes are not modeled explicitly, the fact that rates measured in 
tests in which these processes are operative are used to determine parameter values means the 
effects of that process on the rate are accounted for in the model. 
Two modes of corrosion in humid air are thought to occur in the repository depending on the 
availability of water vapor. If the relative humidity is greater than 44% and the temperature is 
greater than 100C, a film of water will form on the glass. Corrosion products will form as the 

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glass is altered, but these alteration products will remain on the glass surface until contacted and 
transported by liquid water. If the relative humidity approaches 100% from readily available 
water vapor and the temperature approaches 100C, enough water can condense on the glass to 
flow or drip from the glass thereby making dissolved glass components available for transport. 
Extremes for both of these cases have been examined experimentally and are analyzed in this 
report to model glass degradation by humid air or dripping water. In tests representing the first 
case, the amount of water available to form the film on the glass was limited so that the film 
remained static for long times and water did not drip from the glass during the test. Vapor 
hydration tests have been used to promote the formation of alteration phases to identify the 
phases that form, determine if they contain radionuclides, and determine if their formation 
increases the glass alteration rate. Tests have shown that radionuclides become incorporated into 
alteration phases that form on the specimen surface (Ebert et al. 1991 [DIRS 111026], p. 212). 
Subsequent exposure of vapor-hydrated glass to liquid water results in a rapid release of soluble 
components, including some radionuclides, from the alteration layer into solution as dissolved 
and colloidal species (Bates et al. 1990 [DIRS 111002], p. 1,100, Table 5). Radionuclides that 
are retained in soluble phases during vapor hydration (e.g., Tc, Np, U, etc.) will be released 
quickly when those phases are contacted by water. Radionuclides that are retained in sparingly 
soluble phases during vapor hydration will have concentrations controlled by the solubility of the 
alteration phase in which they are sequestered or can be released as radiocolloids if the alteration 
layer spalls from the glass surface. This could occur if there are mechanical strains that exceed 
the strength of the layer, such as those induced by wetdry cycling. 
Two test methods were used to study corrosion in dripping water conditions. One method was 
modified vapor hydration tests conducted with enough water in the vessels that dripping 
occurred in a condensation-dripping reflux cycle. The solution at the bottom of the vessel and 
the reacted samples were analyzed. The other method was unsaturated (drip) tests conducted by 
periodically injecting groundwater into the test vessel so that water collected on and then dripped 
off the sample. The solution that accumulated in the bottom of the vessel was periodically 
recovered and analyzed. The results of these tests are used to model corrosion in dripping water. 
The glass degradation rates measured under humid air and dripping groundwater conditions are 
used to establish the lower bound to the effective rate constant, kE. The following analysis 
describes how the rate expression in Equation 13 is applied to corrosion in humid air and in 
dripping water. 
6.5.3.2 Modeling Glass Degradation by a Thin Film of Water 
The corrosion behavior of glass contacted by a thin film of static water is treated as a special case 
of aqueous corrosion that is described using the same rate expression used for aqueous 
dissolution. Glass degradation in humid air cannot occur until a film of water forms on the glass. 
The sorption of one or two monolayers of water is not sufficient to corrode the glass. Enough 
water must be available to hydrolyze species released from the glass. Tests show that, even at 
elevated temperatures, a relative humidity greater than 44% is required to corrode waste glass 
(Abrajano et al. 1986 [DIRS 110990]). Water consumed by glass reaction or diffusion into the 
glass must be replaced for corrosion to continue. Ion exchange is the first process to take place 
when water contacts glass. Thus, the first reaction between water vapor or condensed water and 
glass would result in a solution with lower water vapor pressure than the surroundings that 

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provides the chemical potential for the sorption of additional water. If water vapor is not 
available, then glass degradation would cease. If water vapor is available, water would absorb 
into the film for as long as the vapor pressure of the film on the glass remains lower than that of 
the water source. The initial dealkalization of glass will result in high concentrations of alkali 
metals and hydroxide (i.e., high pH values) that will provide a large potential for continuous 
condensation of water vapor. 
Several processes take place when glass and water vapor interact at high temperature. The net 
result of these interactions depends on which of these dominates the kinetics. Water diffuses into 
the glass. Water condenses on the surface of the glass or in the alteration layer. Mediated by 
water, the glass is altered to thermodynamically stable alteration minerals. Clearly at 
temperatures in excess of 150C, the alteration process dominates because little if any diffusion 
zone is found at the gel-glass interface. The rate of this process decreases with temperature 
much more rapidly than does diffusion. The dependence of alteration on the relative humidity is 
not well understood; very few tests have been done. In addition, the tests that have been done to 
date were not performed at constant CO2 fugacity. At constant CO2 fugacity, the pH values are 
expected to be limited to values of about 10. Because the pH increase is limited, the increase in 
the reaction rate is limited (Equation 13). 
Since the relative humidity for pure water at 0.1 MPa total pressure falls below 44% at 125C, no 
glass alteration occurs above 125C. Between 100C and 125C, a film of water forms on the 
surface of the glasses based on the analyses shown below. However, because the CO2 fugacity is 
constant and there is an unlimited amount of CO2, the pH of this water is limited to 10. 
6.5.3.3 Using Vapor Hydration Tests to Model Degradation in Humid Air 
This section describes how the results of vapor hydration tests (VHTs) are used to model the 
corrosion of waste glasses exposed to humid air. The vapor hydration test method was initially 
developed to reproduce the hydration of obsidian artifacts in the laboratory. The hydration rinds 
(a layer of different refractive index from the parent glass caused by the presence of water) 
formed on obsidian artifacts are used by archaeologists as a dating method (Friedman and 
Long 1976 [DIRS 163253]). The weathering of obsidian results in water diffusing through the 
surface with little chemical interaction. The hydration rind can be measured with a polarizing 
light microscope. Friedman and Long (1976 [DIRS 163253]) used vapor hydration tests on 
obsidians with different compositions to develop a model for dating obsidian artifacts. Water 
was determined to diffuse into the glass with a rate that depended on the square root of time. 
The VHT was initially applied to nuclear waste glasses by Bates and Steindler 
(1983 [DIRS 104261]), who found complex kinetics and the formation of a complex set of 
alteration phases. It was found that weathering of basaltic glass and nuclear waste glasses 
resulted in the formation of altered material rather than the simple physically strained layer seen 
on obsidians. Thus, alteration of the glass happened much more quickly than or simultaneous to 
the diffusion of the water into the glass. In bulk water, however, the dissolution of obsidian is 
the same as that for nuclear waste glasses (McGrail et al. 1988 [DIRS 171174]). Vapor 
hydration tests have also been used to demonstrate the usefulness of natural analog glasses, such 
as obsidian and basaltic glass, for predicting the long-term corrosion behavior of waste glasses 
weathered under terrestrial conditions (Byers et al. 1985 [DIRS 163209]). Tests have shown the 
same phase assemblages that form during natural weathering of basaltic glass over thousands to 

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millions of years at ambient temperatures also form in short-term VHTs conducted at elevated 
temperatures (Luo et al. 1997 [DIRS 163271]). 
The VHT has also been used to measure the degradation rates of natural glasses and nuclear 
waste glasses at elevated temperatures for extrapolation to lower temperatures of interest. As in 
the case of obsidian, the extent of waste glass degradation in VHTs is measured using the 
thickness of an alteration layer that formed on the surface. Figure 6-4 shows a cross-section 
image of a typical VHT sample. The alteration layer overlays the remaining unreacted glass and 
is itself overlain by discrete precipitated phases (secondary phases). Precipitated phases are 
usually observed on the outer surface of the alteration layer, which indicates nucleation occurs 
preferentially at the outer surface of the alteration layer. The reaction between the glass and 
water proceeds as water diffuses into the glass and alteration and diffusion is mediated by the 
presence of water. The actual process by which the glass is altered in the presence of water 
vapor or a thin layer of water is largely uncertain. However, because the structure is similar to 
that seen in glasses altered in the presence of liquid water, similar mechanisms are likely 
operating. 
The alteration layer does not inhibit glass dissolution at the alteration layerglass interface. This 
is because water can rapidly diffuse through the porous layer to attack the glass and soluble 
elements released from the glass can diffuse through the layer into the water film where they 
may become incorporated into existing or newly precipitated phases. Release of a specific 
element into solution at the surface will depend on its solubility and diffusion through the 
alteration layer. Sparingly soluble components, which are not incorporated into the clay, 
precipitate where the local chemistry allows precipitation to occur. The role of the alteration 
layer as a diffusion barrier is discussed in Appendix D. 
There are two methods for measuring the extent of reaction from the samples from the VHT. 
One is based on the remaining glass in the specimen (Jiricka et al. 2001 [DIRS 163262]). In the 
second, the thickness of the clay alteration layer is used to measure the extent of glass 
degradation. The layer thickness is proportional to the volume of glass that has reacted, since the 
layer is fairly uniform across the glass surface. The precipitated phases at the outer surface are 
excluded from the measurement because most of the material in the precipitated phases was 
leached from the underlying layer. The precipitate phases are excluded to avoid double counting 
the volume of glass that has been altered. The degradation rate is determined as the slope of a 
plot of the layer thickness versus the test duration. The rate as thickness/time is converted to the 
mass of glass dissolved per unit area per unit time by multiplying that rate by the density of the 
glass. In this way, the entire volume of the alteration layer is modeled as being freed from the 
glass. Release of a specific element into solution must be determined based on its solubility and 
diffusion through the alteration layer (rind) using other models. 

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Source: Ebert 2003 [DIRS 164518]. 
Figure 6-4. Typical Cross Section of Vapor-Hydrated Glass 
6.5.3.3.1 ANL Vapor Hydration Tests 
Several series of VHTs were conducted specifically to measure the corrosion rates of three 
glasses at various temperatures and with various amounts of added water: SRL 51S, 
SRL 131-TDS, and SRL 165S. These test results are used to determine parameter values for the 
TSPA-LA glass degradation model that are applicable to glass degradation in humid air. The test 
results and analysis are described in Appendix C. 
6.5.3.3.2 Effect of Relative Humidity 
The VHT results used in the following analyses are taken from Tables C-2, C-3, and C-4 in 
Appendix C (DTN: MO0306ANLGVH01.526 [DIRS 164331]) for tests with SRL 51S, 
SRL 131-TDS, and SRL 165S glass, respectively. The effect of relative humidity was studied by 
varying the amount of water added to the test vessel. The relative humidity was not measured 
directly. Instead, the initial relative humidity was estimated from the volume of the test vessel, 
the mass of water in saturated steam at the test temperature, and the mass of water used in the 
test. The specific volume of steam is 2.0369 ft3/lb, which is used to calculate the density as: 
(1 lb/2.0369 ft3)  (453.6 g/lb)  (1 ft/30.48 cm)3 = 0.00786 g/cm3 
At 200C, about 0.165 g of water is needed to provide 100% RH in the approximately 21 mL 
free volume of the test vessel. 

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Figure 6-5 shows the thicknesses of layers generated in tests conducted with SRL 131-TDS glass 
at 200C with various amounts of demineralized water (the plotted data are tabulated in 
Appendix C, Table C-5). The two samples in each 22 mL vessel are referred to as Sample A 
and Sample B. Most of the results shown in Figure 6-5 are from tests conducted for 21 days. 
Measurable layers were not formed after 21 days in tests with less than 0.1 g of water, but were 
formed after longer test durations. The results for three tests conducted for 31 days and tests 
conducted for 87 and 90 days are included in the plot to better show the low extent of reaction in 
tests with small amounts of water. 
The thickest alteration layers were formed in tests with about 0.20 to 0.25 g of added water. This 
was a sufficient amount of water to provide 100% RH at 200C plus form a film of condensed 
water on the glass that did not drip off. The samples in tests with 0.22 and 0.24 g of water were 
completely corroded within 21 days. Water in excess of that needed to saturate the void space 
was available to condense on and react with the two samples. The brine formed on the sample 
will have a significantly lower vapor pressure than pure water, so less than 0.18 g of water vapor 
will be present as the glass corrodes. The vapor pressure of a film of brine solution on a 
borosilicate waste glass due to dealkalization reactions can be approximated as a solution of 
NaOH. The vapor pressure of a saturated NaOH solution is about 2% RH at 75C and about 
9% RH at 20C (Greenspan 1977 [DIRS 104945]). Even dilute brines will provide an 
appreciable potential for condensation of water vapor in the disposal system. 
Figure 6-5 shows that thinner alteration layers were formed when more than 0.25 g of water were 
added. The layer thickness was independent of the amount of excess water added to the vessel, 
but did increase with the test duration, as shown by the results of tests with 7.5 g of water reacted 
for 21, 31, and 87 days. Slightly thicker layers formed in tests with 0.12 g of water (67% RH) 
than in tests with excess water after 31 days. The lower reactivity is attributed to the lower pH 
values that are attained due to the reflux cycling that occurs with excess water. 
Given these results, it is modeled that the same processes occur when humid air contacts waste 
glass in the disposal system as in VHTs, although the conditions in the VHTs are more 
aggressive because of the higher temperatures and water vapor pressures. In the VHTs, humid 
air contacts a suspended glass monolith in a closed vessel, whereas in the disposal system, humid 
air will contact glass within a steel canister in an open system with unlimited amounts of water 
vapor and CO2 gas (pCO2 = 10-1.5 kPa). High water vapor pressures are attained in the VHTs 
(about 1.4 MPa at 200C), whereas the maximum total pressure in the disposal system will be 
about 0.1 MPa (1 atm). Although the water vapor pressures differ significantly, condensation of 
water on glass is expected to be controlled primarily by the vapor pressures of films formed on 
the glass. The availability of water vapor is an important difference between VHTs and the 
disposal system as is the thermal gradient that will exist between the waste glass and the source 
of water vapor. The water source in the VHTs is contained within the vessel and is near the 
reacting glass. In the disposal system, the condensation of water onto glass in the disposal 
system will probably be limited by transport of humid air to the glass. The VHT results provide 
no insight regarding transport limitations. 

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Source: Appendix C, Table C-5. 
Figure 6-5. Layer Thicknesses in VHTs with SRL 131-TDS Glass at 200C with Various Amounts of 
Demineralized Water 
The observed effects of the amount of water added to the VHT vessel provide insight into the 
likely effects of relative humidity in the disposal system. Tests conducted at 200C with less 
than about 0.18 g of water will result in less than 100% RH in the test vessel, whereas tests with 
more than about 0.2 g of water will maintain 100% RH after water condenses on the glass. 
About 0.05 g of water can condense on the VHT glass sample without dripping off (this is the 
mass of a typical drop of water), so that the addition of 0.25 g of water is enough to maintain a 
saturated vapor phase plus produce thin films on both samples that do not drip off. As the glass 
dissolves in the thin film of condensed water, the equilibrium water vapor pressure of the film of 
water on the sample will be lowered and cause additional water to condense until the film and 
water vapor equilibrate. The film may become heavy enough that some of the solution drips off 
the sample and into the bottom of the vessel. Fresh water vapor will continue to condense on the 
sample, and water at the bottom of the vessel will continue to evaporate in response to its vapor 
pressure, which will always be higher than the vapor pressure of the film on the samples. 
Therefore, water will continuously be transported from the source (i.e., the water at the vessel 
bottom) to the films on the samples and, when enough water condenses on the glass, solution 
will continue to drip from the samples. The importance of this dripping process is that dissolved 
glass components are transported away from the sample with every drop and the film is diluted 
by freshly condensed water vapor. Dilution of the film will lower the pH and consequently 
reduce the glass dissolution rate. 
Figure 6-5 shows that the extent of reaction is much less in tests with less than about 0.2 g of 
water. From the density of steam calculated at 200C, tests with about 0.0764 and 0.0742 g of 
added water provide, at most, initial relative humidities of 0.0764/0.165 = 0.463 (46.3% RH) and 
0.0742/0.165 = 0.449 (44.9% RH). Measurable layers formed in tests with SRL 131-TDS and 

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SRL 51S glass reacted for 90 days in tests with 0.0764 and 0.0742 g of added water (tests 
131-48RH-2 and 51S-48RH-2, see Appendix C, Tables C-2 and C-3). Because the relative 
humidity will decrease during the test when water condenses on the sample, and also as water is 
consumed during glass hydration, a relative humidity of 44% is taken as the minimum relative 
humidity required for corrosion to occur. The glass degradation rate expression is only applied 
when the relative humidity is above 44% RH. Both the effect of the relative humidity on the 
glass degradation rate at relative humidities above 44% and the effect of excess water are taken 
into account by the range of values used for kE. 
6.5.3.3.3 Effect of Temperature in VHTs 
Standard VHTs were conducted at 70C, 90C, 125C, 150C, 175C, and 200C to measure the 
effect of temperature on the degradation rate in humid air. The largest number of tests was 
conducted with SRL 51S glass; the results are summarized in Appendix C, Table C-2 
(DTN: MO0306ANLGVH01.526 [DIRS 164331]). Figure 6-6a shows the results of tests 
conducted with SRL 51S glass at 125C, 150C, 175C, and 200C, and Figure 6-6b shows the 
results of tests with SRL 131 glass at 150C and 200C and the results of tests with SRL 165 
glass at 125C and 200C against the test duration (the plotted data are tabulated in Appendix C, 
Tables C-6 and C-7). The thicker of the layers formed on the two samples in each test are 
plotted to determine the upper bound to the corrosion rates; the plotted layer thicknesses are 
tabulated in Table C-5. The results of tests VHT(150)-8, -9, and -10 were excluded from 
Figure 6-6a because samples in those tests were significantly less reacted than samples in tests 
run for shorter durations under the same conditions. Measurable layers were not formed in tests 
with SRL 51S at 70C or 90C through the longest durations tested (1,361 days). As expected, 
the layer growth rate increases with temperature. The rates determined from the regressions are 
included in the plots. 
For comparison to rates to be calculated by using the TSPA-LA model, the rates were converted 
into units of g glass/(m2d) by multiplying the rate in m/day by the density of the glass. The 
densities of the SRL 51S, SRL 131-TDS, and SRL 165S glasses were measured to be 2.67, 2.78, 
and 2.56 g/cm3, respectively (DTN: MO0306ANLGVH01.526 [DIRS 164331], Table 2). The 
degradation rates measured in standard VHTs with the three glasses are summarized in Table 6-8 
and shown in an Arrhenius plot in Figure 6-7. Linear regression to the standard VHT results for 
the three glasses gives a fit line with the equation ln(rate) = 33.1  118/RT, from which the 
effective activation energy is 118 kJ/mol. 

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Source: Appendix C, Tables C-6 and C-7. 
Figure 6-6. Measured Layer Thickness and Corrosion Rates in Standard VHTs with (a) SRL 51S Glass 
and (b) SRL 131-TDS and SRL 165 Glasses 

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The effective activation energy extracted from the Arrhenius plot in Figure 6-7 represents the 
glass dissolution rates convoluted with the effects of other processes that occur in the test, such 
as water condensation. Differences in the pH and solution chemistries generated at different 
temperatures will affect the measured rates in addition to the differences in the temperature itself. 
A single effective activation energy is determined from results of VHTs with three different 
glasses so the effect of glass composition is also convoluted into the value of 118 kJ/mol 
determined from regression. 
Table 6-8. Corrosion Rates Measured in Standard VHTs 
125C 150C 175C 200C 
Rate, m/d 
SRL 51S 0.024 0.13 1.1 7.1 
SRL 165 0.083 not measured not measured 7.3 
SRL 131-TDS not measured 0.16 not measured 23 
ln(Rate) [g/(m2d)] 
SRL 51S 2.75 1.06 1.08 2.94 
SRL 165 1.55 not measured not measured 2.93 
SRL 131-TDS not measured 0.81 not measured 4.16 
Source: Table 6-8. 
Figure 6-7. Arrhenius Plot for Measured Rates for Glasses in Standard VHTs 
6.5.3.3.4 Extraction of Lower Bounding Rate Parameters 
The same rate equation (Equation 13) is used to calculate degradation rates for glass exposed to 
humid air, dripping water, and immersion environments. The range and distribution of 
parameter values are used to reflect the effects of the environment and glass composition on the 
dissolution rate. The effective activation energy determined from the standard VHTs is 

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significantly different than the activation energies determined from immersion tests for alkaline 
solutions (69 kJ/mol). This is because the activation energy determined from the VHTs includes 
the effects of other processes on the measured rates, including the effects of pH and chemical 
affinity. Both the pH and the chemical affinity may differ in the films formed in VHTs 
conducted at different temperatures. The pH of the film in which the glass degrades in the VHTs 
is not known and the effect of the pH cannot be separated from the effect of temperature in the 
activation energy determined in Figure 6-7. Therefore, the effective activation energy 
determined from the VHTs is only used to extrapolate the corrosion rate in humid air at 90C. 
This extrapolation accounts for the effects of temperature on the pH and chemical affinity as well 
as the reaction rate. The effective activation energy determined from the VHTs is not 
appropriate for use in the glass degradation rate expression (Equation 13). Instead, the activation 
energy measured from immersion tests is used in the glass degradation rate expression because it 
is independent of pH and chemical affinity affects. The rate for corrosion in humid air at 90C is 
used with the pH and temperature parameters determined from the MCC-1 tests to extract the 
value of kE that can be used in Equation 13 to calculate dissolution rates for glass exposed to 
humid air. 
Extrapolation of the solid line in Figure 6-7 gives a rate of 2.5  10-3 g/(m2d) at 90C. This rate 
is used as the minimum dissolution rate to be calculated with the degradation model at 90C. 
The extent of reaction predicted by a rate of 2.5  10-3 g/(m2d) after 1,362 days is 3.4 g/m2, 
which corresponds to a layer thickness of 3.4 g/m2/(2.67 g/cm3) = 1.3 m. A layer this thick 
would be readily detectable with an SEM. The fact that no alteration was detected in the 
standard VHTs conducted at 90C for as long as 1,362 days indicates that the extrapolated rate 
of 2.5  10-3 g/(m2d) at 90C provides a conservative estimate of the lower bound for the range 
of degradation rates calculated by the model. 
The lower limit value of kE is extracted from that rate by using the measured rate and the values 
of . and Ea that were determined using immersion tests (Section 6.5.3.5). This requires that the 
pH of the solution film on the VHT samples be specified. Because the solution is evaporated 
from the sample and recondensed in the bottom of the vessel when the standard VHT is 
terminated (i.e., for VHTs conducted without excess water), the pH of the sample film is not 
measured directly. Three sets of test data provide useful estimates of the pH of the water film: 
1. The pH values of water that was recondensed on the vessel bottom at the end of the 
test were measured as a part of the test procedure. This was done to determine if 
solution dripped from the samples either during the test or during test termination. 
The results are in included in DTN: MO0306ANLGVH01.526 [DIRS 164331]. The 
pH of the condensates in most tests were measured to be 6 or 7, which is interpreted in 
the test method as indicating solution did not drip from the samples. However, the 
condensates in some tests had pH values of 10 or 11. This indicates that the pH values 
of the films on the samples were at least this high. 
2. Small amounts of solution did remain on the samples in some of the standard VHTs. 
These solutions were sufficiently concentrated that they did not completely evaporate 
when the test was terminated. The pH values of these drops of solution were 
measured with pH paper, and the solutions were highly alkaline (e.g., pH 12) in all 
cases. Neither the pH values of solution remaining on the sample nor that of the 

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recondensate is considered quantitative, but both indicate that the film of water on the 
glass had a highly alkaline pH. 
3. The results of VHTs conducted with excess water provide a quantitative measure of 
the pH of the solution in the bottom of the test vessel at the end of the test. The results 
are included in DTN: MO0306ANLGVH01.526 [DIRS 164331]. The pH values of 
those solutions were measured with a combination electrode and pH meter. The pH 
values ranged from about 7 in short-term tests up to 12. Because the pH rises due to 
glass dissolution (primarily due to dealkalization reactions), the pH of the solution 
contacting the glass must have been equal to or higher than that of the solution in the 
bottom of the vessel. The initial pH of the demineralized water was not measured, but 
is conservatively taken to be that of air-saturated water and near pH 5.7. The films on 
the samples in VHTs are modeled to have a value of pH 12 due to glass degradation. 
The value of kE is extracted from the VHT rate at 90C using Equation 13 with the following 
values: rateG = 2.5  103 g/(m2d) (log(rate) = 2.60); . = 0.49; pH = 12; Ea = 69 kJ/mol; and 
T = 363 K. 
.. 
. 
.. 
. 
.. 
. 
.. 
. 
  
  = 
K 363 K kJ/mol 0.008314 
kJ/mol 69 - exp log - 12 0.49 - d) g/(m -2.60 k log 10 
2 
E 10 (Eq. 38) 
The extracted value of log10(kE) is 1.45 g/(m2d); kE = 28.2 g/(m2d). 
The expression to calculate the minimum rate for alkaline solutions is: 
.. 
. 
.. 
. 
.. 
. 
.. 
. +  + = 
RT 
kJ/mol 69 - exp log pH 0.49 1.45 ) (rate log 10 G 10 (Eq. 39) 
6.5.3.4 Using Unsaturated Tests to Model Degradation in Dripping Water 
6.5.3.4.1 ANL Unsaturated Tests 
The dissolution rates of reference HLW glasses SRL 165 and ATM-10 were measured in drip 
tests conducted at 90C. In these tests, 0.075 mL of tuff groundwater solution was injected into 
the test vessel and onto a monolithic glass sample every 3.5 days. The samples (N2-9, N2-10, 
and N2-12), which were accurately measured, were in the form of cylinders with average 
dimensions (1.561  0.039)  102 m in diameter and (2.028  0.026)  102 m in height; the total 
surface area of each sample, rounded to two significant figures was 1.4  103 m2 
(DTN: MO0408ANLGNN01.527 [DIRS 171574]). The samples were suspended in the test 
vessel on a perforated Stainless Steel Type 304L holder. Water collected on and corroded the 
sample. Excess water dripped from the specimen at each injection. At approximately 6-month 
intervals, the tests were interrupted and the solution that collected at the bottom of the vessel was 
removed for analysis. The sides and bottom of the test vessel were rinsed with demineralized 
water that was subsequently analyzed. The sides and bottom of the test vessel were then rinsed 
with a nitric acid solution to dissolve any material that had been released from the glass and 
fixed to the steel during the test interval. This acid strip solution was analyzed separately. The 

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amount of boron released is used as a measure of the extent of glass dissolution. The amount of 
boron in the acid strip solution was generally only a few percent of the total boron. It was 
determined that including the fraction in the acid strip solution would add more uncertainty to 
the analysis, and because the release rate rather than the absolute mass of boron is desired, it was 
neglected. The amounts of actinides in the acid strip were included in the analyses to be 
discussed in Section 6.9.1.2. 
Two blank tests were conducted identically to the other tests, but without a test specimen, one in 
parallel to the triplicate tests on each glass. The tuff groundwater solution contains a small 
amount of boron. The accumulation rate of boron in the blank drip tests were subtracted from 
the rates measured in the tests with glass, as mass B per day, to calculate the degradation rate. 
Triplicate tests identified as N2-9, N2-10, and N2-12 were conducted with samples of SRL 165 
glass and blank test N2-11 was run in parallel. Triplicate tests identified as N3-9, N3-10, and 
N3-12 were conducted with samples of ATM-10 glass and blank test, N3-11, was run in parallel. 
The test results are given in DTN: MO0408ANLGNN01.527 [DIRS 171574] as mass released 
over each test interval in Table 1 for the N2 series of tests and in Table 3 for the N3 series of 
tests. The cumulative masses at each sample date are given in Tables 2 and 4 for the N2 and N3 
series, respectively. These data are shown in Figure 6-8. Solutions were not sampled from the 
N2 series between May 3, 1990 (day 1,550) and December 21, 1993 (day 2,878) and in the N3 
series between September 10, 1990 (day 245) and January 12, 1994 (day 1,220), although the 
groundwater solution continued to be injected every 3.5 days over this period. Two data points 
were excluded from the plot: the boron concentrations measured in tests N3-10 and N3-11 
(blank) were unusually high for the June 8, 2000 samplings. The B concentration in the N3-10 
sample was about 30 times higher the expected value and in the N3-11 sample about 3 times 
higher. The B concentrations in the N3-9 and N3-12 solutions, which were analyzed at the same 
time as the N3-10 and N3-11, were within the expected range for the 686-day test interval and 
are included in Figure 6-8. 
Source: DTN: MO0408ANLGNN01.527 [DIRS 171574], Tables 2 and 4. 
Figure 6-8. Cumulative Boron Release in Tests with (a) SRL 165 Glass and (b) ATM-10 Glass 

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The releases of boron from the test specimens in tests N2-9, -10, and -12 for SRL 165 glass and 
N3-9, -10, and -12 for ATM-10 glass overlap initially, but differ measurably beyond about 2,000 
days. The heavy lines are drawn (empirically) in the figures to bound the boron release rates for 
each glass. The bounding rates from the solid lines are 0.066 and 0.20 g B/d for the N2 and N3 
tests, respectively. The dashed lines give the average release rates from the three replicate tests, 
that is, by regression of the combined results for tests N2-9, N2-10, and N2-12 for SRL 165 glass 
and for tests N3-9, N3-10, and N3-12 for ATM-10 glass. The slopes of the dashed lines are 
0.045 g B/d for the N2 tests 0.12 g B/d for the N3 tests. The thin lines are drawn through the 
results of the blank tests for each test series (N2-11 and N3-11). The boron release rates in the 
blank tests are 0.011 g B/d. The mass fraction of boron in SRL 165 glass is about 0.021 and in 
ATM-10 glass is about 0.028 (DTN: MO0408ANLGNN01.527 [DIRS 171574]). The 
normalized glass dissolution rates are calculated using Equation 40 with both the bounding and 
the average release rates for rateG: 
(rateG g B/d - Blank g B/d)  (1/mass fraction B in glass)  (1/surface area glass) (Eq. 40) 
The upper bounding rate for SRL 165 glass in the N2 series is: 
d m
g 
m B g 
glass g 
g 
g 
d 
B g 
2 
3 
2 3 
6 10 87 . 1 
10 4 . 1 
1 
021 . 0
1 10 1 011 . 0 066 . 0 - 
- 
-  = .. 
. 
.. 
. 
 
 . .. 
. 
. .. 
. 
 . .. 
. 
. .. 
. 
  . .. 
. 
. .. 
. 
- 
 
 
The average rate for SRL 165 glass in the N2 series is: 
d m
g 
m B g 
glass g 
g 
g 
d 
B g 
2 
3 
2 3 
6 10 16 . 1 
10 4 . 1 
1 
021 . 0
1 10 1 011 . 0 045 . 0 - 
- 
-  = .. 
. 
.. 
. 
 
 . .. 
. 
. .. 
. 
 . .. 
. 
. .. 
. 
  . .. 
. 
. .. 
. 
- 
 
 
The upper bounding rate for ATM-10 glass in the N3 series is: 
d m
g 
m B g 
glass g 
g 
g 
d 
B g 
2 
3 
2 3 
6 10 82 . 4 
10 4 . 1 
1 
028 . 0
1 10 1 011 . 0 20 . 0 - 
- 
-  = .. 
. 
.. 
. 
 
 . .. 
. 
. .. 
. 
 . .. 
. 
. .. 
. 
  . .. 
. 
. .. 
. 
- 
 
 
The average rate for ATM-10 glass in the N3 series is: 
d m
g 
m B g 
glass g 
g 
g 
d 
B g 
2 
3 
2 3 
6 10 78 . 2 
10 4 . 1 
1 
028 . 0
1 10 1 011 . 0 12 . 0 - 
- 
-  = .. 
. 
.. 
. 
 
 . .. 
. 
. .. 
. 
 . .. 
. 
. .. 
. 
  . .. 
. 
. .. 
. 
- 
 
 
As was the case in the VHTs, the solution remaining in contact with the glass was not analyzed 
as a part of the unsaturated (drip) test procedure. In a few instances, the pH of a small drop of 
water that remained on the sample was measured with pH paper and found to have values 
of 4 to 5. The pH values of the solutions collected in the bottom of the vessels of the later 
samplings were measured with a combination electrode and pH meter. These were also 
determined to be acidic: the average pH values for the N2 and N3 test series are 4.9 and 5.4, 
respectively (DTN: MO0408ANLGNN01.527 [DIRS 171574], Tables 5 and 6). The pH values 
of the solutions in the blank tests are also acidic. The solution pH values are affected by several 
competing factors. The tuff groundwater solution injected into the tests has a pH of about 8. 

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The solution pH increases as glass dissolves. It will decrease from radiolysis of the water by the 
radiation from the radionuclides in the glass and, potentially, from any corrosion of the stainless 
steel test vessel and sample support. However, corrosion of steels usually causes the solution to 
become more alkaline. The behavior of CO2 in this test is unclear. As the vessel is heated, the 
partial pressure of CO2 decreases as the water vapor pressure increases and the total pressure 
increases. At water injection, the pressure is relieved, but additional CO2 is introduced as 
dissolved carbonate in the water. Depending on the total pressure after each injection, some CO2 
will exsolve from the solution or dissolve into solution. When the vessel is cooled to retrieve the 
accumulated solution from the bottom, CO2 will either dissolve or exsolve depending on the 
solution pH and the total and CO2 pressures. Any chemical effects that make the solution acidic 
must do so sufficiently to overcome the alkalinity imposed by the dissolution of the glass. Thus, 
the reason for the acidic pH values in these tests is not understood nor was it investigated. 
6.5.3.5 Extraction of Lower Bounding Rate Parameters 
The results of the ANL unsaturated tests are used to extract the lower bounding value of kE for 
degradation in acidic solutions. The value of kE was extracted from these results by using the 
same activation energy that is used for aqueous dissolution, namely, 31 kJ/mol. The same 
activation energy is used for the different exposure modes because hydrolysis of silicon-oxygen 
bonds is the rate-limiting step for glass dissolution under both conditions (Section 6.3.1). The 
value of kE is extracted from the rates measured in the unsaturated (drip) tests at 90C using 
Equation 13 with the following values: 
For SRL 165 glass in the N2 series: rateG = 1.16  103 g/(m2d) [log10(rate) = 2.94]; . = 0.49; 
pH = 4.9; Ea = 31 kJ/mol; R = 0.008314 kJ/mol K; and T = 363 K. 
( ) .. 
. 
.. 
. 
.. 
. 
.. 
. 
  
 = 
K 363 K kJ/mol 0.008314 
kJ/mol 31 - exp log - 4.9 0.49 - - 
m
g -2.937 k log 10 2 E 10 d (Eq. 41) 
The extracted value of log10(kE) from the N2 series is 3.92 g/(m2d) and kE = 8.41  103 g/(m2d). 
For ATM-10 glass in the N3 series: rateG = 2.78  103 g/(m2d) [log10(rate) = 2.56]; . = 0.49; 
pH = 5.4; Ea = 31 kJ/mol; and T = 363 K. 
( ) .. 
. 
.. 
. 
. .. 
. 
. .. 
. 
  
 = 
K) (363 K)) kJ/(mol (0.008314 
kJ/mol 31 - exp log - 5.4 0.49 - - 
m
g -2.556 ) (k log 10 2 E 10 d 
(Eq. 42) 
The extracted value of log10(kE) from the N3 series is 4.55 g/(m2d) and kE = 3.56  104 g/(m2d). 
The lower value of kE = 8.41  103 g/(m2d); log10(kE) = 3.92 is used as the lower bound of the 
degradation rates of waste glasses exposed to acidic waters. The expression for calculating the 
minimum degradation rate for acidic pH values (in terms of log10(rateG)) is: 
( ) .. 
. 
.. 
. 
.. 
. 
.. 
. +  + = 
RT 
kJ/mol 31 - exp log pH 0.49 - 3.92 ) (rate log 10 G 10 (Eq. 43) 

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6.5.4 Calculation of the Exposed Surface Area of Waste Glass 
To calculate the release rate of radionuclides, the glass degradation rate is multiplied by the 
surface area that is contacted by water and the radionuclide inventory to calculate fraction release 
(Equation 9). The waste glass will crack in the pour canister from the thermal and mechanical 
stresses generated as the glass cools and as the waste form is handled (including accidental drops 
or other impact events). Cracking of the glass will result in surfaces deep within the glass that 
may be accessible to water or humid air. An important component of the TSPA-LA glass model 
is determination of the surface area that is contacted by water. 
The surface area of glass that is exposed in a laboratory test is usually determined geometrically, 
if the specimens are large enough, or based on the sieve fraction when crushed samples are used. 
Some researchers have multiplied the geometric surface area by a roughness factor to take into 
account the fact that prepared surfaces are not smooth on a microscopic scale (Oversby 1982 
[DIRS 163276]). A similar approach is taken to estimate the surface area of the waste glass, 
wherein the geometric surface area of the glass determined by the dimensions of the pour 
canister and the fill height are multiplied by a water exposure factor: 
S0 = fexposure  (2pro
2 + 2pro  Lo) (Eq. 44) 
where 
S0 is the initial exposed surface area of a glass including that due to fracturing 
ro is the initial radius of a glass 
Lo is the initial length of a glass 
fexposure is the exposure factor. 
The exposure factor is used to account for several uncertainties regarding the glass surface area 
that is used to calculate the glass degradation rate and, ultimately, the radionuclide release rate. 
These are: 
 Thermal cracking 
 Impact cracking 
 Lower accessibility of water to tight cracks than at free surfaces 
 Lower reactivity of glass in tight cracks than at free surfaces 
 Lower transportability in tight cracks than at free surfaces. 
The reactivity of surfaces in the tight fracture cracks that result from thermal and mechanical 
stresses depends on the glass composition, temperature, and the chemistry of the water that fills 
the crack in the same way these factors affect the dissolution rate at free surfaces. The key 
difference between the dissolution rates of the glass within cracks and at the outer surface is the 
transport rates of water and dissolved gases into the crack and reaction products out of the crack. 
Short-term dissolution tests showed that, while more glass dissolved in tests with samples that 
were fractured than not fractured, the difference was less than a factor of 3 (Bickford and 
Pellarin 1987 [DIRS 163207]). It had been concluded previously, from the results of tests in 
which various crack widths were simulated with platinum wire spacers, the assumption that 
crack surfaces leach as readily as the external surface is unduly conservative (Perez and 
Westsik 1981 [DIRS 111044], p. 168). The amounts of glass components released to solution 

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from cracks and from free surfaces cannot be distinguished based on solution results alone. 
Analysis of test specimens reacted under test conditions similar to those used by Perez and 
Westsik (1981 [DIRS 111044]) indicated that the amount of altered glass in cracks near the 
surface (which were probably formed during preparation of specimens for use in the tests) was 
similar to the amount of altered glass that remained at free surfaces (Pederson et al. 1983 
[DIRS 118927], p. 156, Figure 6). The cracks containing altered glass were observed only near 
the surface; it could not be determined if the cracks penetrated into the glass beyond what was 
altered. 
Recent vapor hydration tests have shown that pressurized water can penetrate deep into cracked 
test samples (Jiricka et al. 2001 [DIRS 163262]). The small volumes of water that can 
accumulate within cracks will quickly become saturated as glass dissolves and a low dissolution 
rate will ensue. Observations of altered glass in cracks reveal that the glass on either side of the 
crack becomes either hydrated or transformed into clay (Jiricka et al. 2001 [DIRS 163262]; 
Crovisier et al. 1986 [DIRS 163211]). Cracks in waste glasses are not observed to open 
significantly because very little glass dissolves. Therefore, although water may penetrate 
through cracks well into the interior of glass, the amounts of radionuclides that can be released 
from cracks will be much smaller than from free surfaces. 
Insufficient information is available to quantify either the fraction of cracks that are accessible to 
water or the difference between the corrosion rates in cracks and at a free surface. The approach 
taken in this report is to use a range of exposure factors to account for the uncertainty in the 
accessibility and reactivity of glass in cracks. The upper limit of the exposure factor is assigned 
to be 17. This value is based on reported values for the factors of 12 from thermal cracking 
when the canister is cooled in air (Smith and Baxter 1981 [DIRS 102089]), 40 from impacts 
during handling (Smith and Ross 1975 [DIRS 102088]), and on the accessibility of surfaces in 
cracks to water, and the same reactivity of glass within the crack as at a free surface. The lower 
limit of the exposure factor is assigned to be 4. This accounts for thermal cracking (12) of glass 
in an air-cooled canister, impact cracking (40) applied to 1% of the glass, accessibility of water 
to half of the available surface within cracks, and the reactivity of glass within the crack being 
half the reactivity at a free surface. A maximum value of fexposure = 17 is obtained when all glass 
surfaces formed by fractures are freely accessible to water and glass within cracks has the same 
reactivity as glass at free surfaces: 
fexposure = [40 (impact cracking)  12 (thermal cracking)  0.01] + [12 (thermal cracking)  0.99] 
= 16.68, which is rounded up to 17. 
A minimum value of fexposure = 4 is obtained when one-half of the glass surfaces formed by 
fractures are freely accessible to water and glass within cracks has the one-half the reactivity of 
glass at free surfaces: 
fexposure = [17  0.5 (accessibility)  0.5 (reactivity)] = 4.25, which is rounded down to 4. 
The most probable value for the exposure factor is selected empirically at 4 because less than 
half of the crack surface area will be accessible to water. Data available in the literature indicate 
that the increase in release due to cracking is 3 times that based on the surface area of the for 
full-size samples; this is discussed in Section 7.2. 

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The nominal dimensions of the standard (short) HLW canister that will be used for HLW glass 
produced at the DWPF and WVDP are: overall height = 3.0 m; outside diameter = 0.61 m 
(DOE 1992 [DIRS 102812], Tables 3.1.1 and 3.3.1 and Sections 3.1.1 and 3.3.3; corroborated in 
DOE 2002 [DIRS 158398]). The nominal mass of an average glass produced at the DWPF 
is 1,682 kg and the nominal 85% fill volume is 0.626 m3 (DOE 1992 [DIRS 102812]; 
Tables 3.1.1 and 3.3.1 and Sections 3.1.1 and 3.3.3). The density (.) of a DWPF glass is 
calculated from these values for the average mass and volume is 2.69 g/cm3 (corresponding to 
2,690 kg/m3). Although the density is given as 2,730 kg/m3 in Table 3.3.1 of Characteristics of 
Potential Repository Wastes (DOE 1992 [DIRS 102812]), a density of 2,690 kg/m3 is used for 
DWPF glass in the calculations that follow. To be consistent with the calculation of the Hanford 
glass density, the value of 2,690 kg/m3 was obtained from the average mass of glass per DWPF 
canister, the canister dimensions, and the fill height. 
The nominal mass of an average WVDP glass is 1,900 kg and the density is about 2,700 kg/m3 
(DOE 1992 [DIRS 102812], Tables 3.1.1 and 3.2.1 and Sections 3.1.1 and 3.2.3). The volume of 
the glass calculated by dividing the mass by the density is 0.704 m3. 
The geometric surface area is calculated from the volume of glass and dimensions of the canister. 
The initial radius of the glass, ro, is simply one-half of the value of the outside diameter, which 
is 0.61 m, minus the wall thickness, which is 9.5 mm for DWPF glass. The initial radius of the 
glass, ro, is (0.61 m  2  0.0095 m)/2 = 0.30 m (rounded to two significant figures). The length 
of the glass(Lo) is calculated by treating the canister as a right cylinder of radius 0.30 m, equating 
the expression for the volume of a right cylinder (volume = p  ro
2  Lo) with the volume 
calculated from the total weight of the glass and the glass density (volume = weight/.), and 
solving the resulting expression for the length. The initial length of DWPF glass is estimated to 
be Lo = 2.2 m (expressed to the same accuracy as the radius). This value is based on the overall 
height of the canister subtracting the neck and the concave bottom, a fill height of 85%, and the 
wall thickness. The geometric surface area of the glass is calculated using the formula for the 
surface area of a right cylinder (2pro
2 + 2pro  Lo); the geometric surface area is 4.74 m2. The 
corresponding values for WVDP glass waste forms are: ro = 0.30 m, Lo = 2.49 m, and the 
geometric surface area is 5.26 m2. 
Hanford waste glass will be disposed in a long canister (about 4.5 m overall) (DOE 2002 
[DIRS 158398], Figure C-21) instead of the short canisters used for DWPF and WVDP 
glasses. The diameter of the long canisters will be the same as the short canister. An 
estimated fill height for a Hanford canister is 4.2 m based on a fill neck that is about 0.2 m the 
bottom thickness, and the concave bottom. This fill height gives an estimated geometric surface 
area of 8.5 m2 to two significant figures. The density of the Hanford glass is estimated from the 
available data. In Table 3.4.2 of Characteristics of Potential Repository Wastes (DOE 1992 
[DIRS 102812]), the mass of glass to be contained in a canister is 1,650 kg that would occupy a 
volume of 0.626 m3 at 825C. These data give a value for the density of the Hanford glass 
as 2,636 kg/m3 at 825C. The density would increase with decreasing temperature. The density 
of the Hanford glass at 825C is sufficiently close to the densities of the DWPF and WVDP 
glasses that a value of 2,700 kg/m3 for the cooled Hanford glass is appropriate. The effect of 
uncertainty in the glass density on the surface area calculated for use in the TSPA-LA glass 
model is negligible compared with the uncertainties in the exposure factor. 

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The specific surface area of a glass, Ssp, is calculated by dividing its geometric surface area by its 
mass. For the DWPF glass in a short canister, the specific surface area is (4.7 m2)  (1,680 kg) = 
2.8  103 m2/kg. The specific surface area is 2.8  10-3 m2/kg for a WVDP glass in a short 
canister. The specific surface area for a Hanford glass in a long canister is (8.5 m2)  (3,210 kg) 
= 2.6  103 m2/kg. 
The surface area that remains as the glass degrades is calculated as the product of the specific 
surface area, the exposure factor, and the mass of glass that remains. The expression used to 
calculate the glass surface area as glass dissolves in a time step is: 
S = fexposure  Ssp m2/kg  (M0 kg  SM kg) (Eq. 45) 
where S is the surface area available for reaction in the current time step, M0 is the initial mass of 
glass, and SM is the total mass of glass degraded in all previous time steps. The mass of glass 
degraded in a time step is calculated as the product of the glass degradation rate for that 
realization (see below) and the duration of the time step. 
As listed in Waste Acceptance System Requirements Document (DOE 2002 [DIRS 158873], 
Table 7-1), it is currently expected that there will be about twice as many long canisters of HLW 
glass (14,500 canisters for Hanford) as short canisters (5,978 for the Savannah River Site, 1,190 
for Idaho, 100 for ANL, and 300 for WVDP). The probability that a breached waste package 
contains long canisters is about two times the probability that it contains short canisters, and the 
ratio of short glass canisters from DWPF and WVDP is about 30:1. Therefore, weighted 
averages of 67% Hanford, 32% DWPF, and 1% WVDP are used to calculate both the specific 
surface area and the mass of exposed glass: 
2 2 2 
-3 -3 -3 
sp 
m m m S = 0.67 2.63 10 0.32 2.82 10 0.01 2.77 10 
kg kg kg 
. . . . . . 
  +   +   . . . . . . 
. . . . . . 
(Eq. 46) 
M0 = ( ) ( ) ( ) 0 M = 0.67 3210kg 0.32 1682 kg 0.01 1900 kg  +  +  (Eq. 47) 
The specific surface area from Equation 46 is 2.7  103 m2/kg, and the initial mass from 
Equation 47 is 2,710 kg. Substituting the values calculated in Equations 46 and 47 into 
Equation 45 gives the expression used to calculate the surface area for the next time step using 
Equation 48: 
S = fexposure  2.70  10-3 m2/kg  (2,710 kg  SMt kg) (Eq. 48) 
Calculation of the surface area for each realization requires selection of the cracking factor. The 
initial time step is conducted with SM = 0. The value of SMt is revised after each time step to 
reduce the remaining surface area. The value of SMt is calculated from the glass degradation 
rate and the duration of the time step. Inputs used to calculate the glass degradation rate are 
summarized in Table 4-2. 

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6.5.5 Application of Base Case Model to Heterogeneous Glasses and Glass-Crystalline 
Composites 
The applicability of the glass degradation model to devitrified glasses and glass-crystalline 
composites is evaluated for three reasons. First, almost all HLW glass will have small amounts 
(about 1 vol %) of crystalline inclusion phases. Second, the CWF developed to immobilize salt 
waste from electrometallurgical treatment of spent sodium-bonded fuel is included in the 
government-managed nuclear waste to be accepted at the repository according to Waste 
Acceptance System Requirements Document (DOE 2002 [DIRS 158873], Table 7-1). Third, 
evaluation of the effects of devitrification phases is needed to address the effects of igneous 
intrusion events on HLW glass performance in the disposal system. Literature data are evaluated 
in this section to validate application of the TSPA-LA glass degradation model to devitrified and 
multiphase waste forms. 
Borosilicate HLW glasses are currently formulated to minimize the formation of precipitates 
while it is molten in the melter (either when the melter is at the processing temperature, at lower 
temperatures when idling, or during a malfunction) and as it solidifies in the steel canister. The 
formation of precipitates in the glass melt is minimized because (1) they may form sludge at the 
bottom of the melter that obstructs glass flow and pouring, (2) electrically conductive phases can 
provide a short circuit in Joule-heated melters, and (3) the formation of some phases may lower 
the durability of the glass. The waste loading of most HLW streams processed with a 
Joule-heated melter are limited by formation of phases in the glass-melt such as spinel 
(Ni,Fe,Mn)(Cr,Fe)2O4 and acmite NaFe(Si2O6), particularly for Fe-rich waste streams. The 
formation of these phases does not have a significant impact on the glass durability because the 
silicate network is not significantly affected by the formation of these phases. The limitation on 
the formation of these phases is solely due to melter operation. 
The formation of some phases reduces the chemical durability of the glass. Glasses are 
formulated to avoid formation of phases such as nepheline (NaAlSiO4) because precipitation of 
these phases lead to a composition change in the glass (Li et al. 2003 [DIRS 171167]). 
Precipitation of crystalline phases that result in a higher proportion of alkali in the remaining 
glass usually reduce the glass durability. As these phases form, a higher proportion of 
components that form the silicate structure of the glass, such as Al and Si, are removed from the 
glass melt than components that interrupt the glass structure, such as alkali metals. Likewise, 
glass additives are controlled to avoid both the formation of soluble inclusion phases, such as 
lithium metasilicate (Li2SiO3), and glassglass phase separation. The formation of less durable 
phases could impact the performance of waste glasses if those phases contain radionuclides, and 
may have an indirect effect if they do not contain radionuclides. For example, dissolution of 
soluble phases will increase the exposed surface area of glass, may provide percolation channels 
into the interior of glass that facilitate the release of soluble radionuclides such as technetium, 
and may affect the solution chemistry, such as increasing the pH and the solubility of 
radionuclides. 
6.5.5.1 Tests with Devitrified Glasses 
Bickford and Jantzen (Bickford and Jantzen 1984 [DIRS 163206]; Jantzen and Bickford 1985 
[DIRS 163259]) studied the leach behaviors of DWPF reference glasses made with SRL 131 and 

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SRL 165 frits under conditions to promote devitrification. In addition to nominal compositions, 
glasses having high Al or high Fe contents were tested to better understand the effects of 
devitrification phases on glass durability. The primary precipitated phases were spinel and 
acmite. These were also seen to be the primary devitrification phases in reference glasses for 
Hanford tank wastes (Vienna et al. 1997 [DIRS 163330]; Reynolds and Hrma 1997 
[DIRS 163280]). The chemical durabilities of glasses made under oxidizing and reducing 
conditions, and glasses with different extents of devitrification were measured with the MCC-1 
static leach test. Tests showed that the formation of acmite resulted in a slight decrease in the 
glass durability, whereas the formation of spinel had no effect. Glasses made with high Fe 
contents were more susceptible to devitrification and glasses made with high Al contents were 
less susceptible to devitrification than the composite glasses. The results of 28-day MCC-1 tests 
with composite SRL 165 glasses made using different cooling schedules to promote different 
extents of devitrification are summarized in Table 6-9. 
Table 6-9. Effects of Devitrification on Glass Durability 
Conditions 
vol % 
Crystalline NR(Si), g/(m2d) NR(B), g/(m2d) 
Quenched 0 0.45 0.48 
Simulated Centerline Cooling 5% spinel 
20% acmite 0.63 0.75 
Heat treated 24 hours at 700C 20% acmite 0.79 1.25 
Source: Jantzen and Bickford 1985 [DIRS 163259], Table IV. 
The heat-treated glass showed an increase of less than a factor of 3 in the degradation rate 
relative to the quenched glass based on 28-day MCC-1 tests. Jantzen and Bickford (1985 
[DIRS 163259]) concluded that the nonuniform distribution of precipitates in devitrified glasses 
limited the precision that can be attained in tests with monolithic samples. They conducted a 
more extensive series of tests with crushed glass to expose a greater surface area and better 
represent the bulk glass. These test results corroborated the finding from the MCC-1 tests that 
devitrification resulted in a less than a factor of 3 increase in the dissolution rate. Those results 
also indicated that the release of boron was correlated with the extent of devitrification. 
Li et al. (1997 [DIRS 163269]) and Li et al. (2003 [DIRS 171167]) studied the effects of 
nepheline formation on the chemical durability of a reference glass for the wastes in Hanford 
tanks. They found the amount of nepheline that formed increased with alumina and soda 
contents of the glass, but decreased with increasing silica content. Glasses of several 
compositions were cooled according to different canister centerline cooling (CCC) schedules, 
with CCC-I being cooled from the lowest peak temperature and CCC-VI being cooled from the 
highest peak temperature. The different cooling rates resulted in the formation of different 
amounts of nepheline. The relationship between glass composition, abundance of nepheline, and 
NL(B) and NL(Si) from 7-day PCTs (at 90C) are summarized in Table 6-10. In most cases, 
higher releases of both boron and silicon occur in glasses with nepheline. Since boron is present 
in the glass but not in nepheline, these results show a clear and significant impact of nepheline 
formation on the durability of all glasses except NP-Li-2. The negligible impact on glass 
NP-Li-2 indicates the impact of nepheline formation depends on the glass composition. 

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Table 6-10. Effect of Nepheline on Glass Durability 
Glass Treatment Mass % 
Nepheline NL(B), g/m2 NL(Si), g/m2 
Quenched 0.0 0.54 0.32 
CCC-V 29.4 43.24 2.91 NP-BL 
(baseline) 
CCC-III 30.2 42.38 3.10 
CCC-V 0.0 0.66 0.48 NP-Al-2 
(low Al) CCC-I 5.0 9.10 2.00 
Quenched 0.0 0.38 0.27 
CCC-V 37.9 44.73 0.59 NP-AL-3 
(high Al) 
CCC-IV 38.8 46.90 1.30 
Quenched 0.0 0.37 0.26 NP-Al-4 
(high Al) CCC-V 40.2 44.94 0.93 
Quenched 0.0 0.29 0.19 NP-Li-1 
(low Li) CCC-VI 1.0 0.76 0.20 
Quenched 0.0 1.13 0.51 NP-Li-2 
(high Li) CCC-I 29.1 1.78 0.11 
Quenched 0.0 Not Analyzed 0.47 NP-B-1 
(low B) CCC-V 32.8 Not Analyzed 1.04 
Quenched 0.0 4.27 0.19 NP-B-2 
(high B) CCC-I 0.0 4.35 0.23 
Quenched 0.0 1.06 0.45 NP-K-1 
(high K) CCC-III 29.3 48.19 3.56 
Quenched 0.0 1.76 0.48 NP-K-2 
(high K) CCC-III 28.4 45.22 3.44 
Quenched 0.0 0.81 0.39 NP-Ca-1 
(low Ca) CCC-III 30.5 46.68 3.02 
Quenched 0.0 0.70 0.27 NP-Ca-2 
(high Ca) CCC-II 4.8 1.31 0.32 
Source: Li et al. 1997 [DIRS 163269], Table 2. 
6.5.5.2 Tests with Phase-Separated Glasses 
Nuclear waste glasses are formulated such that glass-in-glass phase separation does not occur. 
Glass-in-glass phase separation usually results in the formation of durable and not so durable 
phases. The compositions in the M2OSiO2Al2O3B2O3 (M represents an alkali metal) system 
that are prone to forming separate borate phases are well known to glass scientists and avoided 
during the formulation of waste glasses. The addition of alkali metals is required to stabilize the 
negative charge of 4-coordinated BO4 groups that fit in the silicate structure. Otherwise, an 
immiscible trigonally coordinated borate glass may form within the silicate glass. Glass-in-glass 
phase separation is sensitive to the thermal treatment of the glass. Vitrification can also result in 
the formation of sulfate and phosphate phases in borosilicate glasses that are less durable than 
the host phase. Consumption of alkali from the formation of these phases may affect the 
composition of the remaining glass (Li et al. 1996 [DIRS 163268]). Although glass-in-glass 
phase separation may add uncertainty to predictions of glass properties based on composition, 
including chemical durability, it does not necessarily impact the modeling of its performance or 
acceptability for disposal. That is, the response in tests such as the PCT will be dominated by the 
low durable phase(s), which ensures the glass durability will not be underestimated. 

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6.5.5.3 Tests With the Ceramic Waste Form 
The CWF was developed to immobilize high-level radioactive salts generated during treatment 
of spent sodium-bonded nuclear fuel (Ebert et al. 2002 [DIRS 163250]; Jeong et al. 2002 
[DIRS 163261]; Lewis et al. 2002 [DIRS 163267]). Both the salt waste and the metallic wastes 
generated during the electrorefining treatment will be submitted for disposal as nonstandard 
HLW forms. Because of the low solubility of chloride in borosilicate glass, the salt waste is first 
occluded in zeolite 5A, then the salt-loaded zeolite is mixed with a borosilicate glass binder at a 
3:1 zeolite-to-glass mass ratio and vitrified at 915C. During the melting operation, the saltloaded 
zeolite converts to the mineral sodalite (Na8Al6Si6O24Cl2). Small amounts of halite 
(NaCl) form as inclusions in the glass phase (1 to 4 vol %). Some of the radionuclides from the 
waste are partitioned between the sodalite, halite, and glass binder phases (e.g., iodine, alkali 
metals, and alkaline earth elements). Insoluble radionuclides form crystalline inclusion phases 
(primarily mixed lanthanide and actinide oxides and silicates) in the glass phase (typically 
<1 vol %). The CWF has been tested and characterized to support qualification for disposal, 
including tests with the separate binder glass and sodalite phases. 
The CWF provides an extreme example of waste glass with crystalline inclusion phases, 
including highly soluble halite inclusions, sodalite inclusions with similar solubility as the glass, 
and insoluble actinide oxide phases. Key test results are discussed below to evaluate the use of 
the TSPA-LA glass degradation model to glass-crystalline composite waste forms. 
Degradation of the CWF is due to the simultaneous dissolution of the binder glass and sodalite 
phases. Inclusion phases within the glass will be exposed to water only as fast as the glass 
dissolves. The behaviors of the different inclusion phases when exposed to water will differ 
significantly. Halite inclusions will dissolve immediately whereas crystalline oxide phases will 
be mostly insoluble. The dissolution rates of both the binder glass and sodalite phases of the 
CWF are modeled with the same rate expression that is used for HLW glass (Equation 5) 
(Fanning et al. 2003 [DIRS 163252]). Tests have been conducted to measure separate parameter 
values for the dissolution of the binder glass, sodalite, and CWF (Fanning et al. 2003 
[DIRS 163252]). The release of silicon was used to measure and compare the dissolution rates 
of the separate phases and the composite because B is not present in the sodalite phase. The 
forward dissolution rates of the sodalite, binder glass, and composite CWF measured in 
short-term MCC-1 tests at 90C at several pH values are given in Table 6-11 and plotted (as 
NR(Si) versus pH) in Figure 6-9. The dissolution rates of the three materials are the same in 
alkaline solutions, but the dissolution rate of sodalite is about a factor of 10 higher than that of 
the binder glass in acidic solutions. Dissolution of the CWF composite is dominated by 
dissolution of the sodalite phase in acidic solutions. Lines are drawn to show the pH dependence 
at 90C, which is based on the combined results of tests at 40C, 70C, and 90C. The pH 
dependencies for CWF dissolution are . = -0.40 and . = 0.19 for acidic and alkaline 
solutions, respectively (Fanning et al. 2003 [DIRS 163252], Table 6). These are bound by the 
values . = 0.49 and . = 0.49 used in the glass degradation model. 

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Table 6-11. Forward Dissolution Rates for Sodalite, Binder Glass, and CWF at 90C 
NR(Si) (g/(m2d)) 
pH Sodalite Binder Glass CWF 
5.1 2.6 0.088 1.8 
6 0.64 0.056 0.67 
7 0.39 0.056 0.69 
8.1 0.99 0.93 1.3 
9.2 1.2 1.5 1.5 
10.2 2.5 5.3 3.3 
Source: Fanning et al. 2003 [DIRS 163252], Table 4. 
Source: Table 6-11. 
NOTE: Lines show pH dependencies for acidic and alkaline solutions that were regressed from test results 
with CWF. 
Figure 6-9. Forward Dissolution Rate [NR(Si)] versus pH for Sodalite, Binder Glass, and CWF at 90C 
The activation energy measured for CWF composite is 65 kJ/mol for acidic solutions 
and 84 kJ/mol for alkaline solutions (Fanning et al. 2003 [DIRS 163252], Table 6). Both values 
are significantly higher than those used in the TSPA-LA glass degradation model (31 kJ/mol for 
acidic solutions and 69 kJ/mol for alkaline solutions; see Section 6.7), but similar to the upper 
range measured for the binder glass and for other borosilicate glasses (Table 7-3). 
The value of kE used in the TSPA-LA model is a function of the apparent solubility limit for the 
rate-limiting step in the kinetic mechanism (K in Equations 10 and 12). The solubility of each 
phase in a multiphase waste form will be different; some crystalline phases may equilibrate with 
solution. The value of kE should represent the solubility of the phases containing radionuclides. 
The apparent solubility limit for the CWF composite at 90C is about 174 mg H4SiO4/L 
(Fanning et al. 2003 [DIRS 163252], Figure 6). The apparent solubility limit is expressed by the 
parameter K in the mechanistic rate expression (Equations 10 and 12). The solubility limit of 
sodalite is about 55 mg H4SiO4/L and the apparent solubility limit of the binder glass is about 

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369 mg H4SiO4/L (Fanning et al. 2003 [DIRS 163252], Figure 6). The apparent solubility limit 
of the CWF is nearly proportional to the 3:1 mass ratio of the sodalite and binder glass. The 
impact of the differences in the solubility limits of the binder glass alone and a CWF composite 
are illustrated in the results of long-term PCT conducted at 90C. The average values of 
replicate tests with pressureless consolidated CWF and binder glass (Lewis et al. 2002 
[DIRS 163267], Tables 25 and 28) are given in Table 6-12 and plotted in Figure 6-10. Tests 
were conducted with binder glass received from the vendor and with glass that was heated at 
915C for 16 hours, which is the condition used to make the pressureless consolidated CWF 
(referred to as PC glass). Both glasses were crushed and sieved to isolate the 100 + 200 mesh 
size fraction for testing. Tests were conducted at solid-to-water mass ratios of 1:10 (S/V ratio of 
about 2,300 m1) and 1:1 (S/V ratio of about 23,000 m1). There is a small difference in the 
reactivities of the as-received and PC-processed binder glass, but there is about a factor of 50 
between the reactivities of the binder glass and the PC-processed CWF composite at all time 
periods. This is attributed to the difference in the solubility limits of the binder glass (either asreceived 
or PC-processed) and the CWF composite. 
The value of K does not appear explicitly in the glass dissolution model. Instead, it is contained 
in the value of kE. A bounding value of 102.26 molal (528 mg H4SiO4/L) at 90C for K was 
recommended by Stout and Leider (1998 [DIRS 111047], Table 3.5.1-2). The value measured 
for the binder glass is lower than that value, and the value measured for the CWF composite is 
lower still. Lower values of K in Equations 6, 10, and 12 mean the glass dissolution rate will 
slow more quickly as the amount of silica in solution increases. 
Table 6-12. Data for PCTs with CWF and Binder Glass 
NL(B) (g/m2) Test Duration 
(days) PC CWF Binder Glass PC Glass 
Tests at S/V = 2,300 m1 
7 0.050 1.69 3.50 
28 0.096 2.79 5.70 
91 0.125 5.73 9.19 
182 0.187 6.90 9.82 
364 0.190 9.66 9.93 
Tests at S/V = 23,000 m1 
7  a 1.09 1.87 
28 0.0390 1.93 3.00 
91 0.0501 4.55 4.85 
182 0.0879  5.44 
364 0.0925  5.53 
Source: Lewis et al. 2002 [DIRS 163267]. 
NOTE: a Not measured. 

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Source: Lewis et al. 2002 [DIRS 163267], Tables 25 and 28. 
Figure 6-10. Results of PCT Conducted with As-Received Binder Glass, PC Binder Glass, and PC CWF 
Composite at (a) S/V = 2,300 m-1 and (b) S/V = 23,000 m-1 
Many 7-day PCTs have been conducted with various CWF materials. An interlaboratory study 
was conducted to measure the precision with which the PCT could be conducted with CWF 
composite (Ebert et al. 2002 [DIRS 163250]). It was found that the precision of tests with CWF 
composite was as good as the precision for tests with borosilicate glasses (e.g., Smith and 
Marschman 1994 [DIRS 163284]). The results of the study are summarized in Table 6-13. Also 
included in Table 6-13 are the normalized mass losses calculated using the mean concentrations, 
an S/V ratio of 2,300 m1, and mass fractions of B = 0.0145, Na = 0.0145, and Si = 0.201. From 
the results pH = 9.01 and NL(B) = 0.0675 g/m2, and the values of . = 0.49 and Ea = 69 kJ/mol 
from the glass dissolution model, the value of log10(kE) is calculated to be 3.50, 
kE = 3.15  103 g/(m2d) (CWF entry in Appendix B, Table B-3). This is well within the range of 
values used in the glass degradation model (Section 6.7). 
Table 6-13. Results of 7-day PCT with CWF Composite 
pH B Na Si 
mean concentration, mg/L 9.01 2.25 30.2 32.6 
pooled interlaboratory 
standard deviation, mg/L 
0.124 0.347 3.40 2.97 
pooled intralaboratory 
standard deviation, mg/L 
0.050 0.113 3.15 0.949 
NL(i), g/m2  0.0675 0.906 0.0705 
NR(i), g/(m2d)  0.00964 0.129 0.0101 
Source: Ebert et al. 2002 [DIRS 163250], Table 4. 
The release of boron is used to track the dissolution of HLW glasses because it has been shown 
to be representative of the glass matrix. Boron is only present in the binder glass phase of the 
CWF composite. Silicon is present in the binder glass and sodalite phases, and sodium is present 
in the binder glass, sodalite, and halite phases. The halite crystals exposed at the surface of 
crushed CWF are dissolved in the water wash step and are taken into account separately in the 
PCT conducted with CWF. Only halite that is exposed as glass dissolves during the test will 

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contribute Na to the test solution. The amount of halite that dissolves during the PCT is tracked 
with the chloride concentration, since a negligible amount of chloride is released as the sodalite 
dissolves. The low solubility of sodalite means that the solution will quickly become saturated 
with respect to sodalite. Unlike the binder glass, sodalite can equilibrate with the test solution. 
Equilibration occurs quickly in the PCT, so that the PCT solution reflects primarily the 
dissolution of the glass binder phase. Silicon is released when either the glass or sodalite 
dissolve, but B is released only when the glass dissolves because only the glass contains boron. 
Dissolution of similar amounts of sodalite and binder glass would result in NL(Si) values being 
higher than NL(B). The similarity between the values of NL(B) and NL(Si) in Table 6-13 
indicates that dissolution of binder glass dominates the PCT response. In contrast, NL(Si) values 
are significantly higher than NL(B) values for CWF reacted in MCC-1 tests. For example, 
NL(B) = 1.5 g/m2 and NL(Si) = 4.4 g/m2 for PC CWF composite reacted in a 3-day MCC-1 test 
at 90C and NL(B) = 10.2 g/m2 and NL(Si) = 21.0 g/m2 for 28-day MCC-1 test at 125C 
(Lewis et al. 2002 [DIRS 163267], Table 9). The solutions from the MCC-1 tests were not 
saturated with respect to sodalite, but the solutions in PCTs were. Degradation of CWF 
composites under disposal conditions will be dominated by dissolution of the binder glass, not 
sodalite. Therefore, it is appropriate to compare the release of boron and dissolution of the 
binder glass phase in laboratory tests with the TSPA-LA glass degradation model to determine if 
that model is representative of CWF performance. 
6.6 BASE-CASE MODEL INPUTS 
Inputs to the HLW glass degradation model developed in this report are summarized in 
Table 6-14. The sources for the input data and parameters for the glass degradation and exposed 
surface area models are summarized in Tables 4-1 and 4-2. Implementation of the glass 
degradation model in performance assessment calculations requires that values for the relative 
humidity, pH, temperature, and average radionuclide inventory be obtained from other sources. 
The relative humidity, pH, temperature, and average radionuclide inventory are variables in the 
model developed here. The values and ranges of the exposure factor (fexposure), the pH 
dependence ( .), temperature dependence (Ea), and rate coefficients (kE_acid and kE_alkaline) are 
selected from the ranges and distributions provided in this report. The glass degradation model 
is valid over the relative humidity range 0% to 100%, the temperature range 20C to 300C, and 
the pH range 1 to 13 and for glasses with compositions similar to those in Table 6-5. Although 
the maximum temperature at which the experiments have been performed with the glasses 
discussed in this report is 200C, the relative humidity at 1 atmosphere total pressure falls below 
44% at 125C. Hence, glass does not react at temperatures exceeding 125C at 1 atmosphere 
total pressure and the maximum range of applicability can be extended to 300C without impact. 
This temperature is well below the glass transition temperature, which is in the range of 600C to 
700C for proposed HLW glasses. At temperatures approaching or exceeding the glass 
transition temperature, glasses could crystallize with a possible impact on the degradation rate in 
water. 

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Table 6-14. Model Inputs Used in HLW Glass Degradation Model 
Input Name Input Description Input Source Value Type of 
Uncertainty 
fexposure glass surface 
exposure factor Section 6.5.4 4 to 17 (no units) Aleatory 
Ssp glass geometric 
specific surface area Section 6.5.4 2.7  103 m2/kg Epistemic 
M0 Average glass mass Section 6.5.4 2,710 kg Epistemic 
.acid 
pH dependence for 
dissolution in acidic 
solutions 
Section 6.5.2.5 0.49 (no units) Epistemic 
.alkaline 
pH dependence for 
dissolution in 
alkaline solutions 
Section 6.5.2.4 0.49 (no units) Epistemic 
Ea_acidic 
Temperature 
dependence for 
dissolution in acidic 
solutions 
Section 6.5.2.5 31 kJ/mol Epistemic 
Ea_alkaline 
Temperature 
dependence for 
dissolution in 
alkaline solutions 
Section 6.5.2.4 69 kJ/mol Epistemic 
kE_acidic 
Glass dissolution 
coefficient for 
dissolution in acidic 
solutions 
Sections 6.5.2.5 
and 6.5.3.5 
8.41  103  1.15  107 
g/(m2d) Epistemic 
kE_alkaline 
Glass dissolution 
coefficient for 
dissolution in 
alkaline solutions 
Sections 6.5.2.4 
and 6.5.3.3.4 28.2  3.47  104 g/(m2d) Epistemic 
6.7 BASE-CASE MODEL RESULTS 
The expression used to calculate the glass surface area as glass dissolves in each time step is: 
S = fexposure  2.70  10-3 m2/kg  (2,710 kg  SMt kg) (Eq. 49) 
where fexposure is the glass exposure factor and SMt is the total mass of glass degraded in all 
previous time steps. A single value of fexposure is selected for all time steps in a realization. The 
total mass of glass degraded in all previous time steps SM is calculated after each time step in a 
realization. 
 The maximum value of the glass exposure factor is fexposure, maximum = 17 
 The minimum value of the glass exposure factor is fexposure, minimum = 4 
 The range is assigned a triangular distribution with a most probable value of 4. 
No glass degradation occurs if the relative humidity is less than 44% and there is no dripping 
water. The rate = 0 and M(t) = M0. 

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The rate expression developed for glass degradation is given by Equation 13 from Section 6.5.2: 
rateG = kE  10.pH  exp(Ea/RT) 
Separate sets of parameter values are used for degradation in acidic and alkaline solutions. 
Constant values of . = -0.49 and Ea = 31 kJ/mol are used for acidic solutions, and constant 
values of . = 0.49 and Ea = 69 kJ/mol are used for alkaline solutions. Substituting these constant 
values into Equation 13, glass dissolution rates are calculated using Equations 50 and 51: 
rateG = kE_acidic  100.49pH  exp(31/RT) (Eq. 50) 
rateG = kE_alkaline  100.49pH  exp(69/RT) (Eq. 51) 
Values for kE_acidic and kE_alkaline to be used in the current realization are selected from the 
following distributions: 
 The maximum value of kE_acidic is 1.15  107 g/(m2d) (Section 6.5.2.5) 
 The minimum and most likely value of kE_acidic is 8.41  103 g/(m2d) (Section 6.5.3.5) 
 The maximum value of kE_alkaline is 3.47  104 g/(m2d) (Section 6.5.2.4) 
 The minimum and most likely value of kE_alkaline is 28.2 g/(m2d) (Section 6.5.3.3.4). 
The sum of the rates from Equations 50 and 51 is used as the degradation rate the current model. 
Only pH and temperature appear in Equations 50 and 51. Therefore, no direct effect on the 
dissolution rate of the HLW glass from codisposed spent fuel occurs. The mass of glass 
degraded at the end of the current time step is calculated using Equation 52: 
M(t) = rateG  t  S (Eq. 52) 
where M(t) and S are the mass degraded and surface area available in the current time step, and t 
is the duration of the time step in the same time units as the rate. 
The mass of glass remaining at the end of the current time step SMt is calculated using 
Equation 53: 
SMt = SMt-1  M(t) (Eq. 53) 
where SMt-1 is the mass of glass remaining prior to the current time step. The surface area 
available for the next time step is then calculated by using the value of SMt calculated in 
Equation 53 in Equation 49. 
The release rate of radionuclides can be calculated from the values of rateG and S calculated in 
Equations 49, 50, and 51 in Equation 9 and the mass or Curie fraction of the radionuclide of 
interest (IRN): 
RRN = rateG  S  IRN (Eq. 9) 

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In this equation, RRN gives the release rate from each canister of HLW glass. An average waste 
package containing HLW glass or HLW glass codisposed with spent fuel will contain 4.87 
canisters of HLW glass, on the average. Therefore, the total release rate from a breached waste 
package will be 4.87 times the value calculated from Equation 9. 
The porosity, water content, volume, and thickness of the alteration layer that will form on the 
HLW glass are calculated in Appendix D. These values can be used to calculate the diffusion of 
elements through the layer. The volume of the alteration layer at the time of interest, VR, is 
calculated from the mass of glass that has degraded up to that time (from Equation 53) and a 
typical density of HLW glass .G, = 2,700 kg/m3 as (Appendix D, Equation D-3c): 
VR (in m3) = 3.7  104  SMt (in kg) (Eq. 54) 
The volume of pore water in the alteration rind is also calculated using the mass of glass that has 
degraded (from Equation 53) and a constant that represents the porosity of the rind (Appendix D, 
Equation D-9): 
Vw (in m3) = 6.3  105  SMt (in kg) (Eq. 55) 
The thickness of the rind layer, TR, is calculated from the initial diameter of the glass and the 
amount of glass that has degraded (from Equation 53) (Appendix D, Equation D-17): 
TR (in meters) = 0.30 - [0.090  (3.0  105)  SMt]1/2 (Eq. 56) 
6.8 UNCERTAINTY AND VARIABILITY 
The outputs of this report are expressions to calculate (1) the glass surface area that can be 
contacted by water in a breached waste package and (2) the glass dissolution rate as a function of 
temperature, pH, and relative humidity. The glass degradation rate is first calculated in units of 
mass glass degraded per unit surface area per unit time then multiplied by the calculated glass 
surface area to calculate the glass degradation rate in units of mass per unit time. That product 
can be combined with the inventories of radionuclides of interest to calculate the release rate of 
those radionuclides (e.g., as curies/time). The uncertainties in the glass surface area and glass 
degradation rate are discussed separately in the following sections. 
6.8.1 Uncertainty in Surface Area of Glass Contacted by Water 
The area of glass that is accessible to water and the area that is contacted by water in a breached 
waste package are the most difficult model parameter values to measure and model. Uncertainty 
exists in the extent of fracturing in each glass, in the fraction of fractures that can be accessed by 
water, and in the fraction of the accessible surface area that is contacted by water vapor, dripping 
water, or bulk water. The uncertainty in the surface area available for reaction is addressed by 
multiplying the geometric surface area by an exposure factor fexposure. The range in values for the 
exposure factor represents uncertainty in the extent of cracking, the water diffusion into the 
cracks, radionuclide diffusion out, and the reactivity of the glass within a crack compared with 
the reactivity of glass at a free surface. It also accounts for variation in the glass densities and fill 
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The extent of fracturing is modeled to be proportional to the geometric surface area of the glass. 
Waste glasses will fracture as they cool because of the thermal stresses in the glass and the hoop 
stresses from the difference in expansion between the glass and the pour canister. Additional 
fracturing may occur during handling. Although fractures at the surface can be measured and 
quantified, fractures in the bulk glass cannot. In addition, not all of the fractures that are formed 
may be accessible to water. The modeled surface area for a glass used in this report is an 
average value that accounts for the thermal cracking of all glass and cracking of a small 
percentage of the glass from handling. Data quantifying the effect of thermal cracking and 
impact cracking are combined with estimates of accessibility and reactivity of glass in tight 
cracks. A factor of 12 is used to account for thermal cracking in all canisters (Smith and 
Baxter 1981 [DIRS 102089]) and a factor of 40 is used to account for impact cracking of 1% of 
the canisters (Smith and Ross 1975 [DIRS 102088]). A maximum value of fexposure = 17 is 
obtained by assuming that all glass surfaces formed by fractures are freely accessible to water 
and that glass within cracks has the same reactivity as glass at free surfaces (Section 6.5.4). A 
minimum value of fexposure = 4 is obtained by assuming that one-half of the glass surfaces formed 
by fractures are freely accessible to water and that glass within cracks has the one-half the 
reactivity of glass at free surfaces (Section 6.5.4). 
The relative humidity and the range of values for the effective dissolution rate constant, kE, are 
used to represent the uncertainty in the glass surface area in contact with water vapor, dripping 
water, and bulk water. If the relative humidity is less than or equal to 44%, no glass degradation 
occurs. If the relative humidity is greater than 44%, glass alteration occurs at a rate determined 
from the rate expression given in this report. The dependence of the rate on relative humidities 
above 44% and the presence of water (under either dripping or immersion conditions) is 
contained implicitly in kE. Between 100C and 125C, the pH of the water on the surface of the 
glass is assigned a value of 10. This value is higher than the mildly acid values noted for the 
case where the layer drips from the surface of the glass and equal to the high value calculated in 
In-Package Chemistry Abstraction (BSC 2004 [DIRS 167621]). Practically, the lower limit to 
the relative humidity limits the temperature range over which glass is altered and, hence, the 
model applied. From the ambient temperatures prior to waste acceptance to the boiling point of 
water, the alteration rate is given by Equation 13. From 100C to 125C, the glass alteration rate 
is given by Equation 57. 
( ) ( ) .. 
. 
.. . 
. .. 
. 
. .. 
. 
  
- + = 
T K mol kJ 
mol kJ rate 
/ 008314 . 0 
/ 69 exp log 35 . 6 log 10 10 (Eq. 57) 
If salt solutions from the evaporation of groundwater elsewhere in the drift or waste package 
control the relative humidity, then the upper temperature at which vapor phase alteration would 
occur is less than 125C. 
Another uncertainty related to the exposed glass surface area is the size of the breached canister. 
Both short canisters (about 3-m long) and long canisters (about 4.5-m long) will be used. 
The glasses in long and short canisters will provide different initial surface areas and initial 
masses. The initial surface area of glass in a long canister is about 1.5 times that in a short 
canister. It is anticipated that about two-thirds of the waste glass will be in long canisters and 
one-third in short canisters (DOE 2002 [DIRS 158873]). This is taken into account by assigning 

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glass to have an initial mass of two-thirds of the mass of glass in a long canister plus one-third of 
the mass in a short canister. 
The total surface area that is available to react in each time step is modeled to decrease in 
proportion to the mass of glass that has degraded in all previous time steps. The specific surface 
area remains constant to represent the balance between the increase in specific surface area as 
large pieces of glass shrink and the decrease as small pieces of glass completely dissolve. 
6.8.2 Uncertainty in the Glass Degradation Model 
How accurately the dissolution rates calculated with the base model represent the actual 
dissolution of glasses in the repository depends on the uncertainties with respect to: 1) the 
environmental conditions to which the glass is exposed, including temperature and water contact 
conditions (condensation of water vapor and the relative humidity, dripping water and the drip 
rate, immersion volume, pCO2, and pH), 2) the degree to which the model represents the glass 
alteration behavior, and (3) the degree to which model parameter values represent the range of 
waste glass compositions. These three sources of uncertainty are addressed in the TSPA-LA 
model through the range and distributions assigned to the model parameter values, primarily 
through the effective rate constant, kE. Another important source of uncertainty is the 
relationship between the radionuclide release and boron release. These are discussed below. 
6.8.2.1 Uncertainty in the Form of the Model 
The uncertainty in how accurately the form of the model represents the glass alteration behavior 
is minimized by use of the same analytical expression to represent alteration rates measured for 
contact by humid air, dripping water, and immersion. This is because the model is directly tied 
to the degradation rates measured in laboratory tests under these conditions. The uncertainty in 
how well the model fits the degradation behavior under those conditions is captured by the value 
of the parameter(s) regressed from those test results. 
The model is timeframe independent. That is, the calculated rate is not an explicit function of 
time. The model can be used to calculate the rate at different pH values and temperatures, both 
of which change over time. The rate reflects disposal time only through changes in those 
variables. This means that the rates, measured in laboratory tests under controlled conditions, 
are the same alteration rates for glass at the same conditions in the repository. 
6.8.2.2 Uncertainty in Parameter Values 
The uncertainty in how well the values for . and Ea represent the measured dissolution rates of 
SRL 202G glass at different pH values and temperature can be calculated from the uncertainties 
in the regression of results from the tests at different durations (Appendix A), from the values 
of . (Figure 6-1), and from the values of Ea extracted from the rates at two different temperatures 
(Equations 23 through 26, and Section 6.5.2.1). 
The more important measure of uncertainty is how well these parameter values represent the 
range of glasses to be disposed. The range of parameter values is obtained by comparing the 
values for SRL 202G glass with those for other glass compositions. In the glass degradation 
model developed here, the uncertainties in the dependencies on the solution pH, temperature, 

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glass composition, solution composition, and water contact conditions are combined in the 
ranges of the effective rate constant, kE, for dissolution in acidic and alkaline solutions. The 
bounding values are determined from experimentally measured dissolution rates under relevant 
conditions. The maximum values are determined from immersion tests in acidic or alkaline 
solutions and the minimum values are determined from tests in dripping water that resulted in 
acidic conditions and tests in humid air that resulted in alkaline conditions. Since the values of 
kE were extracted from the measured reaction rates with constant pH and temperature 
parameters, the effects of glass and solution composition and processes are not modeled 
explicitly. The uncertainties in these processes are captured in the range of values of kE. 
6.8.3 Uncertainty in Stoichiometric Releases of Radionuclides 
In the model, glass dissolution is treated as a constant rate at a given temperature and pH. The 
chemistry associated with the dissolution process and the variation with time even at fixed 
temperature and pH is not calculated. Hence, all radionuclides whether they are controlled by 
the solubility of a solid phase, such as Np or Pu, or not controlled by solubility, such as Cs or Tc 
are released congruently with the glass matrix. This approach is taken because the rate a 
radionuclide is released from the glass matrix cannot be distinguished from the effects of 
solubility control in most test results. The effects of solubility control are imposed in the 
TSPA-LA with a different model. 
6.8.4 Impact of Input Variable Uncertainty 
The uncertainty in the exposure conditions is provided through the input variables pH, 
temperature, and relative humidity. Therefore, the sensitivity of the glass alteration rate is 
obtained through the variability in the individual input parameter. The assignment of constant 
values to the model parameters for the pH and temperature dependence provides a link between 
the uncertainty in the pH and temperature and the uncertainty in the rate that can be readily 
calculated. For example, the degradation rate calculated by the model increases by about a factor 
of 3.1 for every unit increase in pH in acidic or alkaline solutions. When the temperature 
increases, for example, from 35C to 45C in alkaline solutions, the alteration rate increases by a 
factor of 2.7 or decreases by a factor of 2.9 when the temperature decreases from 35C to 25C 
(Equations 50 and 51). Smaller temperature effects occur for acidic solutions. Uncertainty in 
the relative humidity impacts this model only with regard to whether the relative humidity is 
greater than or less than 44%. 
6.8.5 Impacts of Uncertainty on Scientific Analysis Output 
Uncertainty in the individual effects of glass composition, solution composition, temperature, 
and pH on the glass degradation rate is not propagated into other models, such as In-Package 
Chemistry Abstraction (BSC 2004 [DIRS 167621]). This is because the glass dissolution model 
provides only the calculated glass degradation rate, not individual parameter values. The 
assignment of single values, rather than ranges of values, for the pH and temperature parameters 
and assigning the uncertainties in the parameter values to the ranges of kE for degradation in 
acidic and alkaline solutions reduce the uncertainty in the calculated glass dissolution rate. This 
approach avoids the possible calculation of unrealistically high or extremely low rates that would 
be calculated if unrealistic combinations of parameter values were selected. The range of rates 

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calculated by the TSPA-LA model will accurately reflect the range of rates determined from 
experiments in which relevant glass compositions were exposed to repository-relevant 
conditions. 
The glass surface area available for degradation cannot be validated, as well as the glass 
degradation rate. Both the limited data base available on the extent of fracturing of glass in the 
pour canister, the unknown accessibility of water to those fractures, and the difficulties in 
estimating the separate surface areas exposed to humid air, dripping water, and immersion during 
simulations lead to high uncertainty in the surface area parameter, fexposure. The use of the 
maximum value fexposure of 17 (Section 6.5.4) provides a highly conservative estimate. The use 
of the minimum value fexposure = 4 (Section 6.5.4) provides a realistic and lower bound estimate. 
6.9 DESCRIPTION OF BARRIER CAPABILITY 
The DHLW glass waste forms provide a barrier to the release of radionuclides because the glass 
must degrade before radionuclides are made available for transport. The glass dissolution model 
developed here is used to calculate the rate at which radionuclides are made available for 
transport as either dissolved or colloidal species. The measured B release from glasses immersed 
in water or contacted by dripping water, and the alteration of glass specimens in contact with 
humid air were used to develop the glass dissolution model. The primary focus of this model is 
the development of a mathematical model to calculate the glass degradation rate for waste glass 
exposed to humid air, dripping water, or immersion conditions under the constraints of 
TSPA-LA. This section provides an analysis of how well the glass matrix degradation rate 
represents the resulting radionuclide release rate. 
6.9.1 Analysis of DHLW Glass Barrier Capability 
In the glass dissolution model, the release rate of radionuclides is bounded by the glass 
dissolution rate. Dissolution of glass in water results in the formation of a layer of physically 
and chemically altered glass on the surface and the release of some elements to solution. The 
amounts of glass dissolved and the thickness of the alteration layer depend on the water contact 
conditions. Contact with large amounts of water will result in more dissolved glass and thinner 
alteration layers than contact with smaller amounts of water. In the TSPA-LA model, 
radionuclides in both the glass that dissolves and the glass that is altered are considered to be 
available for transport. That is, no credit is taken for the capacity of the altered glass to retain 
radionuclides. This is because the layer on the surface of the altered glass may contain very 
soluble phases or the layer itself can spall from the surface thereby providing material that can be 
transported as colloids. Some experiments in which the release of radionuclides is compared to 
the release of boron under a range of test conditions are discussed below. 
6.9.1.1 Results from Immersion Tests 
The release of radionuclides from several doped glasses has been measured in tests in which the 
glass is immersed in demineralized water or groundwater. These tests have consistently shown 
the release rate of boron is nearly stoichiometric with the release of soluble radionuclides, 
including Tc. Thus, the B release provides a conservative upper bound to the release of less 
soluble radionuclides, such as Np and Pu. Some examples are shown in Figure 6-11 for tests 

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with different glasses at several S/V. These test results show the releases of B and Tc are nearly 
stoichiometric. Although the values of NL(B) do not always exceed the values of NL(Tc), they 
are within experimental error of being the same. 
Figure 6-11a shows the releases of B and Tc in tests with ATM-8 conducted at 90C and an S/V 
of about 39 m1 in tuff groundwater in the presence of tuff and stainless steel (Bazan et al. 1987 
[DIRS 104269]). The results of duplicate tests are shown. Although the results of the duplicate 
tests differ, the values of NL(B) and NL(Tc) are the same for individual tests, within 
experimental uncertainty, and both are significantly higher than the values of NL(Np), NL(Pu), 
and NL(Am) from all tests. 
Figure 6-11b shows the results of tests with a glass made with SRP 165 black frit and added 
NH4TcO4. Tests were conducted at 90C in a simulated tuff groundwater at an S/V of 100 m1 
(Bibler and Jurgensen 1988 [DIRS 128081]). The releases of B, Na, and Tc are nearly congruent 
in all tests. 
Figure 6-11c and Figure 6-11d show the results of SRL 131A and SRL 202A glasses that were 
made with SRL 131 and SRL 202 frits, respectively, and added Tc, Np, Pu, and Am. Tests were 
conducted at 90C in a simulated tuff groundwater at an S/V of 2,000 m-1 (Ebert, Wolf, and 
Bates 1996 [DIRS 163249]). The averages of duplicate tests are plotted. The releases of B, Na, 
and Tc are seen to be significantly higher than the releases of Np, Pu, and Am in all tests. 
Tests with a uranium and plutonium-bearing glass-ceramic waste form have shown the release of 
B bounds the release of U and Pu, which were found to exist primarily as (U, Pu)O2 crystallite 
colloids (Morss et al. 2002 [DIRS 163273]). Figure 6-12 shows the values of NL(B), NL(Si), 
NL(U), and NL(Pu) for long-term PCTs conducted at 90C and 1:10 ceramic waste form 
(CWF)-to-water mass ratio with four CWF materials made with different amounts of U and Pu 
(Morss et al. 2002 [DIRS 163273], Table 9). Even though the amounts of U and Pu in solution 
are not limited by solubility in these tests, their releases are bounded by the release of B. 

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Sources: (a) Bazan et al. 1987 [DIRS 104269]. 
(b) Bibler and Jurgensen 1988 [DIRS 128081]. 
(c) Ebert et al. 1996 [DIRS 163249]. 
(d) Ebert et al. 1996 [DIRS 163249]. 
Figure 6-11. Comparison of Releases of () B, (.) Na, (..) Tc, (.) Np, (.) Pu, and (.) Am in Immersion 
Tests with (a) ATM-8 Glass, (b) an SRP Glass, (c) SRL 131A Glass, and (d) SRL 202A 
Glass 
6.9.1.2 Results from Unsaturated Tests 
The results of N2 tests with an actinide-doped reference glass for DWPF waste glasses that were 
discussed in Section 6.5.3.4.1 provide a measure of how well the release of boron represents the 
releases of Tc, Np, Pu, and Am from the glass. Both the amounts released in each sampling 
interval and the cumulative amounts released over the entire test duration can be compared. The 
normalized mass losses of B, Tc, Np, Pu, and Am at each test interval are given in Table 1 of 
DTN: MO0407ANLGNN02.608 [DIRS 171277]. Figure 6-12 compares the normalized mass 
losses calculated for Tc, Np, Pu, and Am with the normalized mass loss of boron for each 
sampling. Uncertainty bars are drawn at 40% of the NL(Tc) and NL(Pu) values, 50% of the 
NL(Np) values, 30% of the NL(Am) values, and at 15% of the NL(B) values in Figure 6-12a to 
represent the propagated uncertainties in measurements of solution volumes and concentrations, 
sample surface areas, and glass composition. The diagonal lines drawn in Figures 6-10a 

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and 6-10b represent stoichiometric release of B, Tc, Np, Pu, and Am to show how well the 
release of boron represents the release of radionuclides. The values of NL(B) provide an upper 
bound to NL(Tc) and NL(Am) for all samplings and to NL(Np) and NL(Pu) for all but a few 
samplings. 
In the configuration of the unsaturated test, elements released from the glass drip from the 
sample to the bottom of the test vessel. Soluble elements such as B and Tc will accumulate in 
the vessel bottom as solution periodically drips from the sample. Sparingly soluble elements that 
are transported by association with colloids or spalled alteration phases may drop to the vessel 
bottom sporatically. It is possible that elements released from the glass within the same test 
interval may not have been collected in the same sampling. The cumulative releases of the 
different elements can be compared as a better measure of the overall release. The cumulative 
amounts of B, Np, Pu, and Am released in tests N2-9, N2-10, and N2-12 at each sampling are 
given in Table 2 of DTN: MO0407ANLGNN02.608 [DIRS 171277]. The values through the 
longest durations for which data are available for all elements are summarized in Table 6-15. 
The cumulative releases of Tc and B are compared separately for the later samplings that were 
analyzed for Tc. The cumulative amounts of Np released in are about 39% and 29% greater than 
the cumulative amounts of B released tests N2-10 and N2-12, respectively, and 16% lower than 
the cumulative amounts of B released test N2-9. These differences are well within the testing 
uncertainties of 50% for NL(Np) and 15% for NL(B). The release rate of B in the unsaturated 
tests is representative of the release rates of Np and bounds the release rates of Tc, Pu, and Am 
under these test conditions. Since the release rate of boron was used to determine the minimum 
value of kE used in the glass degradation rate for acidic solutions, the modeled rates will bound 
the release rates of these radionuclides. 
Source: DTN: MO0407ANLGNN02.608 [DIRS 171277], Table 1. 
Figure 6-12. Normalized Mass Losses for (a) Tc and Np and (b) Pu and Am versus Normalized Mass 
Loss of Boron for Each Sample in Tests N2-9, N2-10, and N2-12 with SRL 165 Glass 

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Table 6-15. Cumulative Releases of B, Np, Pu, and Am in N2 Tests 
N2-9 N2-10 N2-12 
Release through 12/17/98 
Total Duration, days 4,700 4,700 4,608 
NL(B), g/m2 5.32 9.45 6.08 
NL(Np), g/m2 4.46 13.1 7.85 
NL(Pu), g/m2 0.0641 1.93 0.127 
NL(Am), g/m2 0.0615 0.226 0.0654 
Release 05/03/90 through 12/17/98 
Total Duration, days 3,150 3,150 3,150 
NL(B), g/m2 2.50 6.55 3.40 
NL(Tc), g/m2 0.929 3.01 1.88 
Source: DTN: MO0407ANLGNN02.608 [DIRS 171277], Tables 2 and 3. 
6.9.2 Summary of Barrier Capability of DHLW Glass 
Waste glass will completely immobilize radionuclides until the glass is contacted by water and 
degrades. The degradation rate of waste glass limits the release rates of radionuclides. Even 
soluble radionuclides such as technetium cannot be transported away from the waste form until 
the glass degrades. Tests show the release of technetium is similar to the releases of alkali 
metals (e.g., Li and Na) and boron as glass degrades when contacted by dripping water or 
immersed in water. Technetium is probably physically encapsulated within the glass structure 
rather than being chemically bonded, but cannot diffuse out of the solidified glass. The diffusion 
of water into the glass and alkali metal ions out of the glass opens percolation channels through 
which technetium can escape the glass. The release rate of technetium is similar to the release 
rates of alkali metals and boron. Alkali metals are readily exchanged with protons provided by 
water. The release of boron requires hydrolysis of a boronoxygen bond and is usually observed 
to be slower than the release of alkali metals. Likewise, the release of most radionuclides (e.g., 
Np, Pu, and Am) requires chemical bonds to be broken. The relative bond strengths of different 
elements in the glass will affect their release rates as glass degrades. Because radionuclides are 
present in the glass in relatively low concentrations, a significant amount of glass must degrade 
before radionuclides are exposed to water. Therefore, the durability of the glass matrix and the 
strength of the bonds between radionuclides and the glass matrix contribute to the barrier 
capability of DHLW glass. 

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7. VALIDATION 
The model developed in this report is designed to provide a realistic estimate of the radionuclide 
release from the dissolution of waste glasses that are immersed in groundwater, exposed to 
humid air, or contacted by dripping water in the repository. Validation of the model involves 
presenting technical evidence that the model adequately represents waste glass dissolution and 
radionuclide release in the repository. This is done by showing that the mathematical form and 
resultant range of degradation rates calculated with the model are consistent with data for 
borosilicate glasses and natural analogs in the peer-reviewed technical literature. A comparison 
of key parameters is made to literature data to provide additional confidence. 
The technical work plan (BSC 2004 [DIRS 171583], Section 2.2) under which this model was 
developed states that the model developed herein shall be validated to the lowest acceptable level 
of confidence (Level 1); this is consistent with the criteria specified in AP-SIII.10Q. The models 
developed in this report must meet the criterion listed in the technical work plan, which states, 
the corroborating data must match qualitatively and must be bounded by model predictions. 
Confidence-Building During Model Development to Establish Scientific Basis and 
Accuracy for Intended UseSection 2.2.1 of Technical Work Plan for: Regulatory Integration 
Modeling and Analyses of the Waste Form and Waste Package (BSC 2004 [DIRS 171583]) 
specifies the following steps for confidence building during model development: 
 The model will contain documentation of decisions and activities implemented during 
the model development process to build confidence and verify a reasonable and credible 
technical approach using scientific and engineering principles. 
 The development of the model should be documented in accordance with AP-SIII.10Q, 
Section 5.3.2(b) requirements. 
The development of the HLW glass degradation model was conducted according to the 
following criteria: 
(1) Selection of input parameters and/or input data, and a discussion of how the 
selection process builds confidence in the model. (AP-SIII.10Q 5.3.2(b)(1); 
AP-2.27Q, Attachment 3, Level I (a)) 
The bases for selecting the input data used to determine and develop the HLW glass degradation 
model are documented Section 4.1. Model assumptions have been described in Section 5. 
Detailed discussion about model concepts can be found in Sections 6.3 and 6.5. Thus, this 
requirement can be considered satisfied. 
(2) Description of calibration activities, and/or initial boundary condition runs, 
and/or run convergences, simulation conditions set up to span the range of 
intended use and avoid inconsistent outputs, and a discussion of how the activity 
or activities build confidence in the model. Inclusion of a discussion of impacts of 
any non-convergence runs. ((AP-SIII.10Q 5.3.2(b)(2); AP-2.27Q, Attachment 3, 
Level I (e)). 

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Model formulations for HLW glass degradation and radionuclide release rates under alkaline and 
acidic conditions are discussed in Section 6.5.2.1, and under glass compositions in 
Section 6.5.2.2. The HLW glass degradation and radionuclide release modes span the range of 
intended use conditions for temperature and pH that influence the rate of HLW glass degradation 
and radionuclide release process. Thus, this requirement can also be considered satisfied. 
(3) Discussion of the impacts of uncertainties to the model results including how 
the model results represent the range of possible outcomes consistent with 
important uncertainties. ((AP-SIII.10Q 5.3.2(b)(3); AP-2.27Q, Attachment 3, 
Level 1 (d) and (f)). 
Uncertainties associated with the data used to determine the model parameter values are 
discussed in Section 6.8. A summary discussion on uncertainties and their impact is provided in 
Section 8.2. 
(4) Formulation of defensible assumptions and simplifications. (AP-2.27Q, 
Attachment 3, Level I (b)). 
Discussion of assumptions and simplifications and their rationale are provided in Sections 5 and 
6.3.2. 
(5) Consistency with physical principles, such as conservation of mass, energy, 
and momentum. (AP-2.27Q, Attachment 3, Level I (c)). 
Section 6.3.1 provides a summary of the pertinent physical phenomena and chemical reactions 
associated with the dissolution process that occurs when HLW glass is exposed to water, 
dripping water, and humid air. These sections specifically address pertinent observations as to 
how HLW glass degrades under humid air and infiltrating groundwater conditions relevant to the 
repository and the factors that influence the rate. 
Confidence-Building After Model Development to Establish Scientific Basis and Accuracy 
for Intended Use 
According to Table 2-1 of Technical Work Plan for: Regulatory Integration Modeling and 
Analysis of the Waste Form and Waste Package (BSC 2004 [DIRS 171583]), this report is to be 
validated by answering one of two questions: Is the glass degradation rate consistent with 
experimental data (VA 1) and literature data (VA 3)? However, since this is a Level 1 model, 
only one validation activity is required. The model validation deviates from the technical work 
plan and only uses validation activity 3 (AP-SIII.10Q, Section 5.3.2(c)(3)). 
 Validation Activity 3 is used to show that the required level of confidence has been 
satisfied per Section 5.3.2(C)(3) of AP-SIII.10Q: Corroboration with information 
published in refereed journals or literature. 
The mathematical form and the resultant degradation rates calculated with the glass 
dissolution model reported here are consistent with other models and borosilicate glass 
release rates reported in the literature and discussed in Sections 7.1 and 7.2. 

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Validation of the glass dissolution rate model developed in this report is accomplished by 
comparison with laboratory test results and relevant observations in studies with simulated HLW 
and natural analog glasses that were not used to develop the model, determine model parameter 
values, or calibrate the model. Information used to validate the model or provide confidence in 
the parameter values is listed in Table 7-1. 
Table 7-1. Information Used to Validate the Model and Provide Confidence in the Parameters 
Issue Information Source 
General form of glass 
degradation rate expression 
(Section 7.1) 
Rate expression commonly used 
Advocat et al. 1999 [DIRS 163199] 
CRWMS M&O 1998 [DIRS 100362] 
Grambow et al. 1986 [DIRS 163258] 
Knauss et al. 1990 [DIRS 101701] 
McGrail et al. 1998 [DIRS 153974] 
Final form of glass degradation 
rate expression (Section 7.2) 
Degradation rates calculated with 
model bound degradation rates of 
borosilicate glasses and naturally 
occurring glasses not used for 
model development. 
Grambow et al. 1986 [DIRS 163258] 
Crovisier et al. 1986 [DIRS 163211] 
Model parameter values 
(Section 7.3) 
Parameter values selected for 
model are representative of range 
of borosilicate waste glasses to be 
disposed in Yucca Mountain 
Knauss et al. 1990 [DIRS 101701] 
McGrail, Ebert, et al. 1997 [DIRS 111039] 
(reference was used in Section 6, but no data 
were used) 
Delage and Dussossoy 1991 [DIRS 111014] 
Advocat et al. 1991 [DIRS 111000] 
Gin et al. 1994 [DIRS 163254] 
Abraitis et al. 2000 [DIRS 163195] 
Fanning et al. 2003 [DIRS 163252] 
White 1986 [DIRS 111049] 
Exposed glass surface area 
model (Section 7.4) 
Parameter bounds measured 
increases of surface area due to 
fracturing 
Bickford and Pellarin 1987 [DIRS 163207] 
Sen et al. 1999 [DIRS 163283] 
7.1 VALIDATION OF THE FORM OF THE GENERAL GLASS DEGRADATION 
RATE EXPRESSION 
Literature data are evaluated in this section to validate the form of the rate expression for glass 
dissolution used in the TSPA-LA. First, the common use of the mechanistic rate expression on 
which the model developed here is used as validation of its mathematical form. The range of 
rates from the model is then compared with rates measured in long-term tests in which secondary 
alteration products formed that increased the glass dissolution rate. 
The rate expression for glass dissolution (e.g., as expressed in Equation 5) was developed based 
primarily on the results of tests conducted with minerals and glass immersed in water (Bourcier 
1994 [DIRS 101563], pp. 4 to 12). The general algebraic form of the model (Equation 6) is 
widely accepted and used in the literature of waste glass corrosion (Advocat et al. 1999 
[DIRS 163199]; CRWMS M&O 1998 [DIRS 100362]; Grambow et al. 1986 [DIRS 163258]; 
Knauss et al. 1990 [DIRS 101701]; McGrail et al. 1998 [DIRS 153974]) and is derived from the 
same model used at Hanford (Mann et al. 1998 [DIRS 171176]). In addition to waste glasses, 
the rate expression has been used to describe the alteration of basaltic glass on the seabed 
(Grambow et al. 1986 [DIRS 163258], p. 2,710); basaltic glass is used as a natural analog for 
waste glass. This wide acceptance substantially validates the basic algebraic form of the model, 

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namely, an intrinsic rate constant that depends only on the glass composition, dependence on the 
solution pH, Arrhenius temperature dependence, and dependence on the H4SiO4 concentration as 
representative of the rate-limiting step in the dissolution kinetic mechanism. Therefore, based 
upon the use of the glass degradation rate model form by other researchers and projects in 
refereed journals and literature, the model is validated per validation activity 3. 
7.2 VALIDATION OF THE FINAL DEGRADATION RATE EXPRESSION 
The mathematical form of the model is found in Equation 13. Equation 13 is a simplification of 
Equation 6 obtained by combining the terms  
.
0 k  [1-Q/K] in Equation 6 into one parameter 
kE in Equation 13. This section demonstrates that this simplification and the resultant 
mathematical form is valid based upon comparison of the model results with literature data 
(validation activity 3). The current understanding of waste glass degradation indicates that the 
predominant uncertainties in the long-term term dissolution rate are associated with the value of 
the effective rate constant, kE, in the model. The value of kE is mathematically constrained to the 
range k0 > kE > 0. The appropriate value to use for kE to represent glass degradation over long 
durations and changing environmental conditions is uncertain. The available data show that the 
dissolution rate decreases monotonically over time in static or nearly static systems from values 
on the order of 1 g/(m2d) to values on the order of 1  104 g/(m2d). However, for some 
compositions, after initially decreasing, the dissolution rate has been observed to increase to a 
value nearly equal to the forward rate at the temperature and pH of the test solution. Because the 
conditions in the repository are open, both unlimited amounts of CO2 gas at ambient pCO2 and 
slowly flowing water, the secondary phases that could cause the acceleration will not form. 
Also, the fact that the value of kE selected for the model is close to the estimated values of 
.
0 k 
(i.e., the intrinsic dissolution rate in the absence of solution feed-back effects) for a range of 
reference waste glass compositions (Table 6-5), and the conservative values selected for the 
other model parameters (. and Ea) in Section 6.5.2.1, support the contention that the upper 
bound of the model provides a conservative estimate of the long-term dissolution rate of waste 
glasses in the repository. 
To show that the model provides a conservative representation of the long-term rate in alkaline 
solutions, the rates measured with long-term PCT that are shown in Table 7-2 are compared with 
the range of rates calculated with Equation 51 at the minimum, mean, and maximum values of kE 
and the same pH measured in the tests. The calculation is shown in Appendix B, Table B-3. The 
calculated rates are summarized in Table 7-2. The calculated mean rates for all pH values lie 
above the measured rates. This provides confidence that the base case model conservatively 
bounds the degradation rate of disposed waste glass. This validates the model per validation 
activity 3. 
Table 7-2. Comparison of Measured and Calculated Corrosion Rates of Various Glasses 
Calculated Rate, g/(m2d) 
Glass 
Measured Rate 
g/(m2d) 
Measured pH 
(at room temp.) Mean Maximum Minimum 
EA 0.070 12.3 1.46 4.35 0.00353 
SRL 131A 0.037 12.1 1.16 3.47 0.00282 
SRL 202A 0.032 12.0 1.04 3.10 0.00252 

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SRL 200S 0.87 12.2 1.30 3.88 0.00316 
SAN60 0.074 9.8 0.09 0.259 0.00021 
LD6-5412 0.40 12.0 1.04 3.10 0.00252 
Source: Appendix B, Section B-3, Table B-3. 
The model is further validated by comparison with literature data on basaltic glasses, which are 
used as natural analogs for waste glasses. The calculated dissolution rates (Equation 51) with the 
minimum and maximum value of kE can be compared directly with the dissolution rates of 
basaltic glasses recovered from the seabed. The dissolution rates of several basaltic glass 
samples were calculated based on the thickness of the layer of palagonite (alteration product(s) 
from glass reaction) that forms as an alteration phase and the age of the basaltic glass 
(Grambow et al. 1986 [DIRS 163258], pp. 268 and 269, Table 2, Figure 3). The dissolution rates 
for basaltic glasses covered in sediment and exposed to Si-saturated seawater at about 3C are 
about 0.1 m/1,000 yr, which is equivalent to 6  10-7 g/(m2d). The typical pH range for 
seawater is 7 to 9. The respective minimum and maximum dissolution rates calculated 
with Equation 51 at 3C are 6.62  10-9 and 1.16  10-5 g/(m2d) at pH 7, and 6.33  10-8 
and 1.11  10-4 g/(m2d) at pH 9 (Appendix B, Table B-4). Thus, the rate expression in this 
report bounds the long-term dissolution rate of basaltic glasses. 
The forward dissolution rate of a synthetic basaltic glass in synthetic seawater (pH at 25C 
was 8.8) was measured by Crovisier et al. (1986 [DIRS 163211]) at several temperatures. 
Crovisier et al. (1987 [DIRS 163212]) reported the dissolution rate to be 1  10-3 g/(m2d) at 3C. 
This is more than a factor of 1000 greater than the rate determined by Grambow et al. (1986 
[DIRS 163258) for a natural basaltic glass and shows the important effect of the affinity term on 
the degradation rate. Crovisier et al. (1987 [DIRS 163212]) conducted their tests under 
conditions where the affinity term retained a value near one, whereas Grambow et al. (1986 
DIRS 163258]) conducted their tests under conditions where the value of the affinity term was 
much less than one. The activation energy was determined to be 65 kJ/mol (Crovisier et al. 1986 
[DIRS 163211], p. 275). This is in excellent agreement with the activation energy for alkaline 
solutions used in the base case model (69 kJ/mol, Section 6.5.2.1). Crovisier et al. (1987 
[DIRS 163212]) noted that the dissolution rate of the glass is probably lower in the natural 
environment than it is in laboratory experiments; this favors a kinetic control of the reaction by 
glass network dissolution (surface reaction) rather than by diffusion in the palagonite layer 
(p. 2,987)there is no natural evidence for growth rate control of palagonite layers by 
diffusional transport and, hence, the empirical formula S = (C  t)1/2 must not be used 
(p. 2,988)it appears that the kinetics is mainly controlled by the affinity of the dissolution 
reaction (i.e., the pH and the saturation of the solution with respect to the glass itself) (p. 2,989). 
These results show the degradation rate calculated by the TSPA-LA glass degradation model 
provides confidence that the model gives a realistic estimate of basaltic glass dissolution over 
long reaction times. They also show the activation energy used in the model for dissolution in 
alkaline solutions is applicable to basaltic glasses. This further validates the form of the model 
and the range of calculated rates per validation activity 3. 

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7.3 COMPARISON OF PARAMETER VALUES FOR DEGRADATION MODEL 
WITH VALUES FOR OTHER GLASSES 
Literature data are evaluated in this section to provide confidence in the model parameter values 
of pH (.) and temperature (Ea) in the glass degradation model. This is done by comparing the 
coefficients for the pH and temperature dependencies that were determined in Section 6.5.2 from 
tests with SRL 202G glass with the pH and temperature dependencies that were either 
determined previously for the dissolution rates of other alkali borosilicate glasses or determined 
from published test results. The forward dissolution rates of other borosilicate glasses have been 
measured to determine values of . and Ea. The comparison of the results to the model is 
provided in Section 7.3.1 and the details regarding each particular glass are described thereafter. 
7.3.1 Dependence on pH and Temperature 
The values of . and Ea determined from tests with several glasses are compared with the values 
measured in tests with other glasses and with the values used in the base model. The values of . 
and Ea determined for various borosilicate glasses are summarized in Table 7-3. The pH 
dependence in acidic solutions varies significantly for the different glasses, ranging from -0.36 to 
-0.70. The value of . = -0.49 that is used in the base model (Section 6.5.2.1) is in the middle of 
that range. The range of pH dependencies in alkaline solutions is from 0.40 to 0.64. The value 
of . = 0.49 that is used in the base model (Section 6.5.2.1) is near the middle of that range and is 
therfore appropriate. 
It has been reported that the activation energies for a very large number of [borosilicate glass] 
compositions cluster between 60 and 90 kJ/mol (White 1986 [DIRS 111049], p. 439). The 
values given in Table 7-3 for dissolution in alkaline solutions are consistent with this range. The 
activation energy of 69 kJ/mol that is used in the base case model (Section 6.5.3.1) for alkaline 
solutions is near the middle of the range and is therefore appropriate. 
The activation energy of 31 kJ/mol that is used for acidic solutions in the base case model 
(Section 6.5.3.1) is at the lower end of the range of values measured for other glasses. Higher 
values were determined for the CSG and binder glasses. Because the values of kE were 
determined from tests conducted at 90C, the use of an activation energy at the lower end of the 
range for different glass compositions ensures that the rates calculated at temperatures less 
than 90C will not underestimate the dissolution rates. In the model, a pH of 10 is assigned to 
the solution in contact with glass when the temperature rises above 100C, meaning that the 
value of Ea for alkaline solutions is used in most situations for temperatures above 90C. 
These data show the pH and temperature dependence parameter values used in the TSPA-LA 
glass degradation model are either representative of a wide range of borosilicate waste glass 
compositions or provide a conservative upper bound. 

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Table 7-3. Values of . and Ea Extracted from Literature Data 
Glass Element 
Temperature 
(C) . 
Ea 
(kJ/mol) Literature Reference 
Acidic Solutions 
CSG Si 25, 50, 70 -0.70 60 Knauss et al. 1990 [DIRS 101701]a 
MW Si 30, 50, 70, 90 -0.39 32 Abraitis et al. 2000 [DIRS 163195] 
Binder Glass Si 40, 70, 90 -0.36 72 Fanning et al. 2003 [DIRS 163252] 
Alkaline Solutions 
CSG Si 40, 70, 90 0.49 85 Knauss et al. 1990 [DIRS 101701]a 
MW Si 30, 50, 70, 90 0.43 56 Abraitis et al. 2000 [DIRS 163195] 
LD6-5412 Si 20, 40, 70, 90 0.40 75 McGrail et al. 1997 [DIRS 111040] 
R7T7 B 90  59 Delage and Dussossoy 1991 
[DIRS 111014], p. 47 
R7T7 B 90 0.41  Advocat et al. 1991 [DIRS 111000] 
Binder Glass Si 40, 70, 90 0.64 83 Fanning et al. 2003 [DIRS 163252] 
NOTE: a See Appendix V. 
7.3.2 Tests with CSG Glass 
A simple 5-component glass referred to as Celias Simple Glass (CSG; Knauss et al. 1990 
[DIRS 101701]) was formulated as surrogate for DWPF waste glasses to measure glass 
dissolution parameter values. The glass contains Al2O3, B2O3, CaO, Na2O, and SiO2. Redox 
sensitive elements were excluded to facilitate subsequent analyses of the reacted solids. 
Single-pass flow-through (SPFT) tests were conducted with CSG glass to measure the 
dissolution rate as a function of temperature and pH (Knauss et al. 1990 [DIRS 101701], p. 372). 
Tests were conducted at 25C, 50C, and 70C in pH buffer solutions spanning the range from 
pH 1 to pH 13. Knauss et al. (1990 [DIRS 101701]) quantified the glass dissolution rate based 
on the release of silicon. Knauss et al. (1990 [DIRS 101701]) presented the rate constants 
without separating the intrinsic and temperature-dependent components. They reported rates as 
log10(.), where log10(.) = log10(k0) + log10{exp(Ea/RT)}. Separate values of . were reported 
for each temperature. 
The results reported by Knauss et al. (1990 [DIRS 101701], Figure 1) were reanalyzed here to 
provide single values for the pH dependence in acidic and alkaline solutions at all temperatures. 
The reanalysis was done as follows (Appendix V): the results of tests at 50C and 70C were 
regressed together to determine values for acidic and alkaline solutions. Those values 
are .acid = 0.698 and .alkaline = 0.486. Lines with these slopes were then regressed manually 
with Microsoft Excel to the results of tests at 25C, 50C, and 70C. The equations of these lines 
had the form log10(rate) = log10(.) + .  pH and were used to determine the values of log10(.) at 
each temperature for acidic and alkaline solutions. The resulting lines are shown in Figure 7-1a 
with the test results determined from Figure 1 the report by Knauss et al. (1990 [DIRS 101701]). 
The equations were then used to calculate the rates at pH 0 and at pH 14. These rates were used 
to determine the activation energies for the acidic and alkaline solutions, as shown in the 
Arrhenius plot in Figure 7-1. The activation energies are 60 kJ/mol for acids and 85 kJ/mol for 
bases. 

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NOTES: (a) Acidic solutions fitted with . = -0.698 and alkaline solutions fitted with . = 0.486; data points from 
Knauss et al. (1990 [DIRS 101701]), lines from reanalysis done for this report (Appendix V) (b) Arrhenius 
plot for calculated rates at pH 0 and pH 14. 
Figure 7-1. Measured NR(Si) from Single-Pass Flow-Through Tests with CSG Glass 
7.3.3 Tests with LD6-5412 Glass 
The LD6-5412 glass was developed as a reference test glass for Hanford low-activity waste 
glasses. An extensive series of SPFT tests have been conducted with LD6-5412 glass at 20C, 
40C, 70C, and 90C and at pH values as low as 6 (McGrail et al. 1997 [DIRS 111039], p. 186, 
Figure 12; reproduced here as Figure 7-2). The regressed parameter values based on the release 
of Si are reported to be .alkaline = 0.40  0.03, Ea = 74.8  1.0 kJ/mol, and log10(k0) [g/(m2s)] = 
2.05  0.16 {log10(k0) [g/(m2d)] = 6.99}. The value of log10(k0) given by McGrail et al. (1997 
[DIRS 111039]) for LD6-5412 glass differs from the value of log10(k0) = 5.14 reported in 
Table 6-8, because different values of . and Ea were used to extract the value of log10(k0). 
The intrinsic rate constant of LD6-5412 glass that was measured with MCC-1 tests can be 
compared with the value measured with SPFT tests by McGrail et al. (1997 [DIRS 111039]) if 
the same activation energy and value of . are used to separate the temperature and pH effects 
from the measured rates. The value of log10(k0) extracted from the MCC-1 test results 
[NR(B) = 0.47 g/(m2d) from Table 6-5], with Equation 13 and the values . = 0.40 and 
Ea = 75 kJ/mol, is log10(k0) [g/(m2d)] = 7.00. This is in excellent agreement with the value of 
log10(k0) [g/(m2s)] = 2.05 reported by McGrail et al. (1997 [DIRS 111039]), which is equivalent 
to log10(k0) [g/(m2d)] = 6.99  0.55. This comparison shows that the MCC-1 test method and 
single-pass flow-through tests provide the same estimate the value of log10(k0). 

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Source: McGrail et al. 1997 [DIRS 111039]. 
Figure 7-2. Results of Single-Pass Flow-Through Tests with LD6-5412 Glass 
7.3.4 Tests with R7T7 Glass 
The R7T7 glass is a nonradioactive reference glass for the French R7 vitrification facility at La 
Hague that has been tested extensively. Soxhlet tests were used to measure the temperature 
dependence of R7T7 dissolution rate (Delage and Dussossoy (1991 [DIRS 111014], p. 41). 
Results reported by Delage and Dussossoy (1991 [DIRS 111014], Table IV) are shown in 
Figure 7-3. The slope of the regression line is the negative of the activation energy, which 
is 59.7 kJ/mol. A value of 59  2 kJ/mol was reported by Delage and Dussossoy (1991 
[DIRS 111014]). 

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Source: Delage and Dussossoy 1991 [DIRS 111014]. 
Figure 7-3. Arrhenius Plot for Dissolution of R7T7 Glass 
Short-term MCC-1 tests in solutions with various imposed pH values were used to measure the 
pH dependence of the R7T7 dissolution rate (Advocat et al. 1991 [DIRS 111000], p. 57). 
Results are shown in Figure 7-4. Neither a minimum rate nor an increase in the rate with 
decreasing pH was observed in tests conducted at 90C and at pH values as low 
as 4.5 (Advocat et al. 1991 [DIRS 111000], p. 63, Figure 4). The relative releases of B, Na, and 
Si in mildly acidic solutions mimics that seen by Knauss et al. (1990 [DIRS 101701]) in tests at 
70C over the range pH 3 to pH 7. The slope of the line drawn between pH 7 and pH 10 in 
Figure 7-4 is reported as 0.41. 
The dissolution rate of R7T7 glass (based on the release of B) was measured to be 5.41 g/(m2d) 
at 90C in a pH 2.5 solution (Gin et al. 1994 [DIRS 163254], p. 258). For comparison with the 
data in Figure 7-3, this is equivalent to 9.04  10-11 mol/(cm2s) (log10(rate) = 10.0) when the 
molecular weight of 69.39 g glass/mol is used (Advocat et al. 1990 [DIRS 110996]). This 
indicates that the dissolution rate of R7T7 glass does increase at low pH values and may indeed 
have a V-shaped pH dependence. A bounding value of the degradation rate can be determined 
from the values log10(rate) = 10.0 at pH 2.5 and log10(rate) = 11.2 at pH 4.5 (Figure 7-3). If 
the rate begins to increase at pH values less than 4.5, the value of . will be -0.6. 

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Source: Advocat et al. 1990 [DIRS 110996]. 
Figure 7-4. Results of MCC-1 Tests with R7T7 Glass for (.) B, (.) Na, and (.) Si 
7.3.5 Tests with Magnox Glass 
A borosilicate glass is used to immobilize solutions from Magnox reprocessing operations in 
Britain (referred to as MW glass). Tests have been conducted to study the dissolution 
mechanism and kinetics to support modeling. Figure 7-5 shows the dissolution rates measured 
for MW glass in short-term static leach tests (up to 28 days) conducted in various pH-buffered 
solutions at 60C and 90C (Abraitis et al. 2000 [DIRS 163195], Figure 1). Because of the 
limited data, the rates measured in acidic solutions are fit to the four data points for NR(B) at 
90C and the rates in alkaline solutions are fit to the four data points for NR(B) at 60C. The 
values are .acid = 0.37 and .alkaline = 0.37. The other data are consistent with these pH 
dependencies. Abraitis et al. (2000 [DIRS 163195]) report values of .acid = 0.39 and 
.alkaline = 0.43 based on boron release rates in tests conducted at 18C. The activation energies 
are reported by Abraitis et al. (2000 [DIRS 163195]) to be 32 kJ/mol for acidic and 56 kJ/mol 
alkaline solutions based on the release of Si at pH 2.3 and pH 12.1. 

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Source: Abraitis et al. 2000 [DIRS 163195]. 
Figure 7-5. Results of Tests with MW Glass at 60C and 90C 
7.3.6 Tests with Binder Glass 
A borosilicate binder glass is used to immobilize salt wastes from electrochemically treated spent 
sodium bonded nuclear fuel. Because of the low solubility of Cl in borosilicate glasses, the salt 
is first occluded in zeolite 5A, and then the salt-loaded zeolite is encapsulated in the binder glass. 
Series of MCC-1 tests were conducted to measure the temperature and pH dependence of the 
binder glass dissolution rate. The release of silicon was used to monitor the dissolution rate. 
The results are shown in Figure 7-6. The temperature and pH dependencies were determined 
based on the results of tests at 40C, 70C, and 90C (Fanning et al. 2003 [DIRS 163252]). 
The regression gives values of .acid = 0.36 and Ea = 72 kJ/mol and .alkaline = 0.64 and 
Ea = 83 kJ/mol. Also shown in Figure 7-6 is a comparison of the results of tests conducted 
at 20C and the predicted rates (dashed lines) (Jeong et al. 2002 [DIRS 163261]). Although the 
absolute differences between the measured and predicted rates are only on the order 
of 0.001 g/(m2d), the measured rates are almost all greater than the predicted rates. 

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Source: Jeong et al. 2002 [DIRS 163261]. 
Figure 7-6. Results of MCC-1 Tests with Binder Glass 
7.4 COMPARISON OF THE EXPOSED SURFACE AREA PARAMETER RANGE TO 
LITERATURE DATA 
Literature data are evaluated in this section to provide confidence in the appropriateness for the 
calculation of the exposed glass surface area in the TSPA-LA glass dissolution model. Tests 
with approximately 0.3-m-long and 0.6-m-diameter sections cut from a nonradioactive glass 
(SRL 165 glass) were conducted as scaled-up MCC-1 static leach tests (Bickford and 
Pellarin 1987 [DIRS 163207]). The authors estimated a 25- to 35-fold increase in the surface 
area from cracking. The results of the scaled-up tests were within a factor of 3 of the typical 
laboratory tests results with 1-cm-diameter and 2-mm-thick samples when normalized to the 
surface area. The authors attributed much of the difference to the greater roughness (surface 
finish) of the large samples. The factor of 3 is slightly less than the lower end of the range of 
exposure used in the base model (i.e., 4 to 17). 
A study of the fracturing of full-scale samples of nonradioactive R7T7 glass was conducted 
under the auspices of the European Commission on Nuclear Science and Technology 
(Sen et al. 1999 [DIRS 163283]). Two full-size glass samples had a mass of about 400 kg each, 
compared to the masses of U.S. HLW glasses, which are about 3,200 kg for long canisters 
and 1,700 kg for short canisters. While the size of the canister will affect the cooling rate of the 
glass, the primary cause of fracturing is from the hoop stresses incurred by the difference in 
thermal expansion of the glass and the steel canister. The degree of fracturing measured with the 
smaller R7T7 glass provides validation of the degree of fracturing calculated for U.S. glasses in 
this report. Analyses were conducted with two samples and two different methods: the extent of 
fracturing was measured with tomography and the accessible surface area was evaluated by 
conducting large-scale Soxhlet tests (Sen et al. 1999 [DIRS 163283]). The accessible surface 
area was assessed from Soxhlet results by comparing the measured release rates of glass 
components from full-sized glass with the rates measured with small samples that were not 

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fractured. The difference is attributed to a different surface area. To minimize the amount of 
fracturing incurred by removing the sample from the pour canister, Sample 1 was made in a 
perforated inner container and Sample 2 was made in a four-sided container. The perforated 
inner container was retained for the Soxhlet tests; the four-sided container was removed, which 
resulted in additional fracturing and fragmenting of Sample 2. It was expected that results from 
Sample 1 would underestimate the degree of fracturing because of the perforated container and 
results from Sample 2 would overestimate the degree of fracturing. Both sets of results are 
summarized in Table 7-4 (Sen et al. 1999 [DIRS 163283], Table 13). The fracture ratio was 
calculated as the measured surface area divided by the geometric surface area. The high 
uncertainty in the value from the Soxhlet test with Sample 2 gives a range of 13 to 61. This was 
due to Sample 2 breaking into loose fragments and a more complete exposure of all the 
fractured glass surfaces to the leaching solution (Sen et al. 1999 [DIRS 163283], Section 
5.5.2). Small pieces of glass that were not detected with tomography were probably exposed in 
the Soxhlet test. The Soxhlet results for Sample 2 are not representative of a canistered waste 
glass. The fracture ratios for the other analyses are within the range of 4 to 17 that is used in the 
base model. 
Table 7-4. Measured Surface Areas for Full-Scale Glass of R7T7 Glass 
Sample 1 Sample 2 
Volume, m3 0.140 0.147 
Geometric Surface Area, m2 1.88 1.88 
Results Using Tomography Method 
Total Surface Area, m2 13  3 26  6 
Fracture Ratio 7  2 15  4 
Results Using Soxhlet Method 
Total Surface Area, m2 7  3 64  42 
Fracture Ratio 3  2 37  24 
Source: Sen et al. 1999 [DIRS 163283]. 
This comparison provides confidence that the range of surface areas calculated in the TSPA-LA 
glass degradation model provides a conservative but realistic representation of the reactive 
surface area of a fractured waste glass, compared to available literature information. 
7.5 SUMMARY OF MODEL VALIDATION 
The glass degradation model is validated in the preceding Sections 7.1 through 7.4 by 
comparison with literature data that were not used to develop or calibrate the model (Criterion 
for validation per BSC 2004 [DIRS 171583]). The form of the rate expression is validated by 
comparison with rate expressions used in other waste disposal programs. The range of 
calculated rates for dissolution in alkaline solutions is validated by comparison with increased 
rates after zeolite formation and rates measured for basalt glass. While not validated per se, 
model parameter values for the temperature and pH dependence are compared with parameters 
measured for other glasses to provide additional confidence. These comparisons demonstrate 
that an appropriate level of confidence in the glass degradation model exists and the 
requirements of the technical work plan (BSC 2004 [DIRS 171583], Table 2-1) are satisfied. 
The level of confidence for the results from the model is consistent with the level of importance 

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and the criteria listed in the technical work plan under which the model was developed 
(BSC 2004 [DIRS 171583], Table 2-1). 
No further activities are needed to complete this model validation for its intended use. The basecase 
model developed in this report is adequately validated for HLW borosilicate glass waste 
forms that meet current acceptance requirements (DOE 2002 [DIRS 158873]; DOE 1996 
[DIRS 102589]), the most important of which is the requirement that HLW glasses be more 
durable than the EA glass as measured using PCT-A. 

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8. CONCLUSIONS 
The models developed in this report provide a rate expression to calculate the release of 
radionuclides as the HLW glass dissolves when contacted by water. The radionuclide release 
rate is calculated as the product of three terms: the surface area of glass contacted by water; the 
glass dissolution rate; and the mass fraction of the radionuclide in the glass. Mathematical 
expressions and parameter values for the first two terms are developed output of this report and 
are summarized in the following subsections. The mass fractions of radionuclides in the glass 
are obtained from the inventory abstraction. 
The modeling activities documented in this report include: 
 Simplifying a well-accepted mechanistic model for the dissolution of borosilicate waste 
glasses 
 Determining model parameter values that represent the behavior of the range of glass 
compositions expected to be disposed, based on current DOE waste form acceptance 
criteria (DOE 2002 [DIRS 158873]) 
 Determining model parameter values for the anticipated range of environmental 
conditions in the repository 
 Developing an expression for the glass surface area exposed to water in a breached 
waste package 
 Validating the model for its intended use in TSPA calculations for License Application. 
Constant parameter values were determined from the results of tests conducted specifically to 
provide data to determine the dependence of the glass dissolution rate on pH, temperature, and 
composition. The results of other tests were used to determine ranges of parameter values to 
take into account variability in glass composition and water exposure conditions. The output 
developed in this report are mathematical expressions for calculating the glass dissolution rate 
and surface area of glass available for corrosion and model parameter values. These are 
summarized in the following sections and in output DTN: MO0409ANLGAMR1.016. The 
Microsoft Excel spreadsheets used to perform the calculations are also provided in output 
DTN: MO0307ANLGAMR3.016. 
8.1 DEVELOPED OUTPUT 
The output developed in this report includes the exposed surface area of glass, the rate 
expression for glass degradation, and model parameter values. The computational parameter 
values are summarized in Table 8-1. 

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The expression developed to model the surface area of glass that reacts is: 
S = fexposure  2.70  10-3 m2/kg  (2,710 kg  SMt kg) (Eq. 48) 
where: 
S is the surface area (m2) available during the current time step 
fexposure is an empirical factor that accounts for the effects of cracking, the extent to which 
water can penetrate cracks, and the lower reactivity of glass in cracks relative to 
free surfaces 
SMt is the total mass of glass that has been dissolved through time t (the value of SMt 
is incremented after each time step). 
The surface area available at each time step is calculated from the mass of glass that has not been 
dissolved or altered in all previous time steps. The mass dissolved in each time step is tracked in 
the simulation. A constant value is used for the specific surface area based on the geometric 
surface area and mass of glass in a canister. The nominal dimensions and mass of the glass form 
represent a weighted average of anticipated waste glasses in short and long canisters. The 
exposure factor accounts of the thermal cracking anticipated for all glass and impact cracking 
anticipated for about 1% of the glass. A range of values is used for the exposure factor. The 
upper limit of the range (fexposure = 17) represents the case where glass in cracks has the same 
reactivity as glass at free surfaces. The lower limit of the range (fexposure = 4) accounts for the 
limited access of water to glass in interior cracks and the lower reactivity of glass in the cracks. 
The most probable value of fexposure = 4. 
The mass of glass degraded at the end of the current time step is calculated with Equation 52: 
M(t) = rateG  t  S (Eq. 52) 
where M(t) and S are the mass dissolved or altered and surface area available in the current time 
step, and t is the duration of the time step in the same time units as the rate. The mass of glass 
that remains at the end of the current time step SMt is calculated using Equation 53: 
SMt = SMt-1 - M(t) (Eq. 53) 
where SMt-1 is the mass of glass remaining prior to the current time step. The surface area 
available for the next time step is calculated by substituting the value of SMt into Equation 49. 

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Table 8-1. Computational Model Parameter Values Developed in This Reporta 
Output 
Name 
Output 
Description Value Distribution 
Type of 
Uncertainty 
fexposure glass exposure 
factor 
minimum: 4 (no units) 
maximum: 17 (no units) 
most probable: 4 (no units) 
Triangular Aleatory 
Ssp glass specific 
surface area 2.70  10-3 m2/kg Single Value Epistemic 
M0 initial mass of 
glass 2,710 kg Single Value Epistemic 
.acidic pH coefficient for 
acidic solutions -0.49 (no units) Single Value Epistemic 
.alkaline pH coefficient for 
alkaline solutions 0.49 (no units) Single Value Epistemic 
Ea_ acidic 
temperature 
coefficient for 
acidic solutions 
31 kJ/mol Single Value Epistemic 
Ea_alkaline 
temperature 
coefficient for 
alkaline solutions 
69 kJ/mol Single Value Epistemic 
kE_acidic 
glass degradation 
rate coefficient for 
acidic solutions 
minimum: 8.41  103 g/(m2d) 
maximum: 1.15  107 g/(m2d) 
most probable: 8.41  103 g/(m2d) 
Triangular Epistemic 
kE_ alkaline 
glass degradation 
rate coefficient for 
alkaline solutions 
minimum: 2.82  101 g/(m2d) 
maximum: 3.47  104 g/(m2d) 
most probable: 2.82  101 g/(m2d) 
Triangular Epistemic 
.G 
representative 
density of HLW 
glass and dry rind 
2,700 kg/m3 Single Value Epistemic 
f porosity of rind 
(alteration layer) 17% Single Value Epistemic 
ro initial radius of 
glass log 0.30 m Single Value Epistemic 
Lo initial length of 
average glass log 3.9 m Single Value Epistemic 
NOTE: a Some of the numbers in this table are reported as logarithms or other derived numbers. During 
calculation, additional significant figures were used that were later rounded to a lower number of 
significant figures. Therefore, variations in the last digit should be expected when trying to reproduce 
these calculations. 
Glass degradation does not occur if the relative humidity is less than 44%. If the relative 
humidity is greater than or equal to 44%, the same rate expression is used to calculate the 
degradation rate when HLW glass is exposed to humid air, dripping water, or immersed. At 
temperatures between 100C (100% relative humidity for water at 0.1 MPa total pressure) 
and 125C (44% relative humidity), Equation 13 is used with a pH fixed at 10. The relative 
humidity is obtained from the appropriate model. 

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The rate expression developed for glass alteration is given by Equation 13 from Section 6.5.1: 
.. 
. 
.. 
. -   =  
RT
E k rate a pH 
E glass exp 10 . (Eq. 13) 
Separate sets of parameter values are used for degradation in acidic and alkaline solutions. 
Constant values of . = 0.49 and Ea = 31 kJ/mol are used for acidic solutions, and constant 
values of . = 0.49 and Ea = 69 kJ/mol are used for alkaline solutions. Substituting these constant 
values into Equation 13 yields: 
rateG = kE_acidic  100.49pH  exp(31/RT) (Eq. 50) 
rateG = kE_alkaline  100.49pH  exp(69/RT) (Eq. 51) 
Different bounding values are used for kE in acidic and alkaline solutions. Values for kE_acidic and 
kE_alkaline to be used for any time step in a realization are selected from the following: 
 The maximum value of kE_acidic is 1.15  107 g/(m2d) 
 The minimum and most probable value of kE_acidic is 8.41  103 g/(m2d) 
 The maximum value of kE_alkaline is 3.47  104 g/(m2d) 
 The minimum and most probable value of kE_alkaline is 2.82  101 g/(m2d). 
The greater of the two calculated rates calculated with Equations 50 and 51 is used as the 
degradation rate for all time steps in a calculation. The pH and temperature are variables in the 
glass dissolution model. Values of the pH and temperature must be obtained from another 
model. The glass dissolution model is valid over the pH range 1 to 14, over the temperature 
range 20C to 300C, and over the relative humidity range 0 to 100% RH. 
The release rate of radionuclides from HLW glass dissolution can be calculated from Equation 9 
from Section 6.5: 
RRN = S  rateG  IRN (Eq. 9) 
where RRN is the rate at which a radionuclide RN is released from the glass matrix (in units of 
curies/time), S is the surface area of glass available for reaction (in units of area) calculated with 
Equation 48, rateG is the specific degradation rate of the glass (in units mass glass/(areatime)), 
which is the sum of the rates calculated with Equations 50 and 51, and IRN is the mass fraction of 
a radionuclide RN in the glass (in units curies/mass glass) that must be obtained from another 
model. Expressions to calculate S and rateG are given in this report. The value calculated with 
Equation 9 represents release from a single canister. 
A description of the alteration layer is given in Appendix D, including equations to calculate the 
volume, thickness, and water content of the layer, in terms of the mass of HLW glass that 
dissolves in a canister. The volume of the alteration layer is calculated as: 
VR (in m3) = 3.7  104  SMt (in kg) (Eq. 54) 

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The volume of pore water in the alteration layer is calculated as: 
Vw (in m3) = 6.3  105  SMt (in kg) (Eq. 55) 
The thickness of the layer, TR, is calculated as: 
TR (in meters) = 0.30  [0.090  (3.0  105)  SMt]1/2 (Eq. 56) 
8.2 OUTPUT UNCERTAINTY AND DISTRIBUTIONS 
Uncertainties are associated with both the mathematical expressions for surface area and glass 
dissolution rate and the model parameter values. The glass dissolution rate and the radionuclide 
release rate are also affected by uncertainty in the input variables relative humidity, pH, and 
temperature. These uncertainties are described below. 
8.2.1 Exposed Surface Area 
Uncertainty in the surface area is represented by the range of values assigned to the exposure 
factor, fexposure. The maximum value represents a conservative estimate of the increase in surface 
area based on measurements of the extents of thermal and impact cracking combined with a 
conservative estimate of the fraction of glass that will be affected. The minimum value 
represents a subjective estimate of the accessibility of water to tight cracks within the glass and 
the reduced reactivity of glass within cracks due to transport limits both for water entering cracks 
and radionuclides exiting cracks. Estimates of water accessibility and glass reactivity are based 
on qualitative experimental evidence. The range of values is based on experimental evidence 
that the dissolution of large samples with cracking representative of full-sized glass samples 
increased by less than a factor of 4 compared to laboratory-sized samples without cracks. 
The constant values, used for the specific surface area of a glass and the initial mass, are based 
on the expected number of long and short canisters and the estimated geometric surface area and 
mass of the glass in the canisters. These values are intended to reflect the probability of whether 
a long or short waste package is breached in the simulation. 
8.2.2 Glass Degradation Rate 
The uncertainty in the glass degradation rate is represented by the range of values and 
distributions assigned to the dissolution rate coefficients, kE, for contact by acidic and alkaline 
solutions. The ranges represent the combined uncertainties of the water contact mode (humid 
air, dripping water, and immersion), the glass composition, and the chemical affinity term. The 
ranges of values for degradation in acidic and alkaline solutions are based on the rates measured 
in laboratory tests with a range of water contact modes, glass compositions, and chemical 
affinities. The effects of glass composition on the degradation rate are small compared with the 
effect of the affinity term. The impact of the water contact mode is primarily through its effect 
on the affinity term. The maximum value of kE for acidic solutions represents dissolution under 
immersion conditions with a chemical affinity near 1. The minimum value of kE for acidic 
solutions represents dissolution under dripping water conditions under which the chemical 
affinity is significantly less than 1, perhaps as low as 104. The maximum value of kE for 
alkaline solutions represents dissolution under immersion conditions with a chemical affinity 

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established by secondary alteration phases (e.g., zeolites). The minimum value of kE for alkaline 
solutions represents degradation upon exposure to humid air with a chemical affinity 
significantly less than 1. 
Because the values of kE were extracted from measured degradation rates with the same values 
for the pH and temperature dependence used in the mathematical rate expressions, the 
uncertainty in how well those parameter values represent that glass is also contained in the value 
of kE. That is, the sets of parameter values kE, ., and Ea are not independent. By using the rates 
measured in laboratory tests that simulated likely environmental and water contact conditions, 
the effects of processes not explicitly taken into account in the mathematical rate expression are 
captured in the rates calculated with the model. 
8.2.3 Radionuclide Release Rates 
Another source of uncertainty is the relative release rates of radionuclides and B. The 
dissolution rates of glasses reacted in dripping water and immersed in water are determined from 
the release of B in dissolution tests. The thickness of alteration layer was used to determine the 
alteration rates of glasses exposed to humid air. Boron is taken to be the most rapidly released 
structural element of a borosilicate waste glass and provides a conservative upper limit to the 
release of radionuclides in the glass. The release of B is used to represent the glass dissolution or 
alteration rate, and thereby represents the maximum release rates of all radionuclides. This is, in 
part, a simplification of the model in that a factor could be included in Equation 9 to scale the 
release of individual radionuclides to the release of B. Experiments show B and Tc are released 
nearly congruently; boron is released faster than Tc in some tests and slower in others. This 
probably reflects uncertainty in measuring the release of Tc, which is present in waste glasses at 
much lower concentrations than B and is often not homogeneously distributed in the glass. The 
use of a scaling factor for the release of individual radionuclides was not implemented in the 
model because (1) data are not available to reliably quantify the relative releases of all 
radionuclides, and (2) the relative impacts of reactions to break bonds between the radionuclides 
and the glass cannot be distinguished from the effects of the solubility limits of the radionuclide 
species in the tests. Solubility limitations are imposed on key radionuclides by other models in 
TSPA-LA. 
8.2.4 Impact of Input Uncertainties on Output 
Implementation of the glass dissolution model for performance assessment calculations requires 
specification of values for three variables: relative humidity, in-package solution pH, and 
in-package temperature. Relative humidity, temperature, pH, and radionuclide inventories do 
not affect the models developed in this report. No degradation can occur if the relative humidity 
is less than 44%. Degradation is calculated with Equations 50 and 51 if the relative humidity is 
greater than or equal to 44%. The solution pH and the glass temperature are variables in 
Equations 50 and 51. The uncertainty in those variables can be used to determine their impact on 
the glass dissolution rate with standard propagation of errors methods. 

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8.3 CONFIDENCE IN THE MODEL 
The rate expressions developed in this report provide a mathematically simplified model of a 
generally accepted mechanistic model for borosilicate waste glass dissolution. The 
computational model parameters were selected to represent the effects of environmental 
variables tracked in TSPA-LA on glass dissolution and radionuclide release, and the range of 
those variables over the service life of the disposal system modeled in TSPA-LA calculations. 
The form of the model and the values of model parameters have been validated by comparison 
with the best available data for current waste glass compositions. This model is valid over the 
relative humidity range of 0% to 100%, the temperature range of 20C to 300C, the 
pH range 1 to 14, and for glasses with compositions similar to those shown in Table 6-5. 
Although the maximum temperature at which the experiments have been performed with the 
glasses discussed in this report is 200C, the relative humidity at 1 atmosphere total pressure 
falls below 44% at 125C. Hence, glass does not react at temperatures exceeding 125C 
at 1 atmosphere total pressure and the maximum range of applicability can be extended to 300C 
without impact. This temperature is well below the glass transition temperature, which is in the 
range of 600C to 700C for proposed HLW glasses. At temperatures approaching or exceeding 
the glass transition temperature, glasses could crystallize with a possible impact on the 
degradation rate in water. 
8.4 NRC ACCEPTANCE CRITERIA 
The following acceptance criteria, provided by the NRC in Section 2.2.1.3.4.3 of Yucca 
Mountain Review Plan, Final Report (NRC 2003 [DIRS 163274]), are relevant to the glass 
degradation model developed in this report (BSC 2004 [DIRS 171583, Table 3-1). These 
acceptance criteria are listed with statements summarizing how each criterion is addressed. 
Acceptance Criterion 1System Description and Model Integration are Adequate 
(1) Total system performance assessment adequately incorporates important 
design features, physical phenomena, and couplings, and uses consistent and 
appropriate assumptions throughout the radionuclide release rates and solubility 
abstraction processes. 
The glass degradation model developed in this report is consistent with the design features 
relevant to models from which input is taken and models to which output is provided. The 
values (or ranges of values) of parameters used in the glass degradation model are either 
developed within the model (Section 6.5) or obtained from project sources of technical 
information (e.g., information regarding the dimensions and number of glass canisters and 
nominal masses of canistered glass). Implementation of the glass degradation model requires 
definition of variables for relative humidity, solution pH, and temperature that will be obtained 
from other TSPA-LA or in-package chemistry. 
(2) The abstraction of radionuclide release rates uses assumptions, technical 
bases, data, and models that are appropriate and consistent with other related 
U.S. Department of Energy abstractions. The descriptions and technical bases 

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provide transparent and traceable support for the abstraction of radionuclide 
release rates and solubility limits. 
The glass degradation model is valid for the range of temperatures, pH values, and relative 
humidities (Section 6.5) that are consistent with other models implemented with the glass 
degradation model. 
(3) The abstraction of radionuclide release rates and solubility limits provides 
sufficient, consistent design information on waste packages and engineered 
barrier systems. 
The glass degradation model provides values for the surface area of glass contacted by water 
(Section 6.5.4), the glass degradation rate (Section 6.5.2), and an expression to calculate the 
radionuclide release rates (Section 6.7). The rate expression accounts for the anticipated range of 
glass compositions and water contact scenarios in the disposal system. The surface area 
calculation accounts for the relative amounts of short and long canisters of HLW glass. 
(4) The U.S. Department of Energy reasonably accounts for the range of 
environmental conditions expected inside breached waste packages and in the 
engineered barrier environment surrounding the waste package. 
The glass degradation model is applicable over the range of anticipated environmental conditions 
in a breached waste package, including the relative humidity, pH, temperature, and the amount of 
water. Conditions within the waste package and external to the waste package, as developed in 
other reports, are used as input to the model developed herein. 
(5) The description of process-level conceptual and mathematical models is 
sufficiently complete with respect to thermal-hydrologic processes affecting 
radionuclide release from the emplacement drifts. 
The release rates of radionuclides are sensitive to changes in the temperature and solution pH. 
Hydrologic effects are accounted for in the range of values used for the exposure factor and the 
dissolution rate coefficient. Minimum values for these parameters represent contact by humid air 
(Section 6.5.3) and maximum values represent immersion (Section 6.5.2). 
(6) Technical bases for inclusion of any thermal-hydrologic-mechanical-chemical 
couplings and features, events, and processes in the radionuclide release rates 
and solubility limits model abstraction are adequate. 
Bounding parameter values were selected to provide calculated radionuclide release rates equal 
to rates measured in experiments under humid air, dripping water, and immersion conditions. 
Acceptance Criterion 2Data are Sufficient for Model Justification 
(1) Geological, hydrological, and geochemical values used in the safety case are 
adequately justified. Adequate description of how the data were used, 
interpreted, and appropriately synthesized into the parameters is provided. 

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Justification for the values used in the developed model and descriptions of how the data are 
used, interpreted, and appropriately synthesized into the parameters is provided in Section 6. 
(2) Sufficient data have been collected on the characteristics of the natural system 
and engineered materials to establish initial and boundary conditions for 
conceptual models and simulations of thermal-hydrologic-chemical coupled 
processes. 
The characteristics of the natural system and engineered materials are not addressed in this 
report. 
(4) The corrosion and radionuclide release testing program for high-level 
radioactive waste forms intended for disposal provides consistent, sufficient, and 
suitable data for the in-package and in-drift chemistry used in the abstraction of 
radionuclide release rates and solubility limits. For expected environmental 
conditions, U.S. Department of Energy provides sufficient justification for the use 
of test results, not specifically collected from the YM site, for engineered barrier 
components such as high-level radioactive waste forms, drip shield, and backfill. 
Corrosion tests with borosilicate HLW glasses conducted over the past 30 years show the 
dissolution rate depends on the temperature, pH, and orthosilicic acid activity in solution 
(Section 6.3). Test results from a number of laboratories on glasses with different compositions 
provide consistent information on the dissolution and alteration (corrosion) of HLW glasses and 
the radionuclides they release. 
Acceptance Criterion 3Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction 
(1) Models use parameter values, assumed ranges, probability distributions, and 
bounding assumptions that are technically defensible and reasonably account for 
uncertainties and variabilities, and do not result in an under-representation of the 
risk estimate. 
The uncertainty in specific parameter values is accounted for in the range of the rate coefficients 
for the modeled glass degradation rate and in the range of exposure factors for the modeled 
surface area (Section 6.8). 
(2) Parameter values, assumed ranges, probability distributions, and bounding 
assumptions used in the abstractions of radionuclide release rates in the total 
system performance assessment are technically defensible and reasonable based 
on data from the YM region, laboratory tests, and natural analogs. 
Parameter values, assumed ranges, probability distributions, and bounding assumptions 
adequately reflect the range of environmental conditions expected inside breached waste 
packages (Section 8.1, Table 8-1). The lower bounding values of the ranges of the dissolution 
rate and exposed surface area are based on measured values that are expected to be the most 
representative of the disposal system. The upper bounding values provide conservative estimates 

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of the highest practical rates and surface areas. Sufficient bases exist for selection of maximum 
and minimum model parameter values and distributions for calculation of both the exposed 
surface area and the glass degradation rate. Parameter values were determined based on the 
dissolution rates for several reference waste glasses measured under extreme exposure conditions 
of humid air, dripping water, and immersion. The experimental conditions were representative 
of bounding conditions in a breached waste package. The parameter values used in the model 
were validated by comparison to parameter values determined from dissolution rates for a range 
of glass compositions reported in the technical literature. 
(4) Uncertainty is adequately represented in parameter development for 
conceptual models, process models, and alternative conceptual models 
considered in developing the abstraction of radionuclide release rates and 
solubility limits either through sensitivity analysis or use of bounding analyses. 
Parameter development for the conceptual model is developed in Section 6.5; alternative 
conceptual models have been adequately considered in Section 6.4. 
(8) U.S. Department of Energy adequately considers the uncertainties in the 
characteristics of the natural system and engineered materials, such as the type, 
quantity, and reactivity of material, in establishing initial and boundary 
conditions for conceptual models and simulations of thermal-hydrologic-chemical 
coupled processes that affect radionuclide release. 
The key variables affecting the glass degradation rate that are tracked in TSPA-LA calculations 
are pH, temperature, and relative humidity. The effects of pH and temperature are modeled 
explicitly and the glass degradation rate is directly responsive to the uncertainty in those 
variables (Section 8.1). A minimum relative humidity is required for glass degradation to occur 
(Section 8.1). Since the range of effects of pH, temperature, and relative humidity span the range 
of these characteristics of the natural system and engineered materials, these effects have been 
considered. 
(9) Where sufficient data do not exist, the definition of parameter values and 
conceptual models is based on a appropriate other sources. 
The lack of sufficient data for effects of some conditions on glass dissolution and radionuclide 
release is referred to as bounding in this report. For example, data are not available to evaluate 
glass degradation rates in acidic solutions containing dissolved glass components (Section 6.5). 
The potential slowing effects of dissolved aluminum or silicon in acidic solutions are neglected 
in the model. 
Acceptance Criterion 4Model Uncertainty in Characterized and Propagated Through 
the Model Abstraction 
(1) Alternative modeling approaches of features, events, and processes are 
considered and are consistent with available data and current scientific 
understanding, and the results and limitations appropriately considered in the 
abstraction. 

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The full range of glass compositions (Section 6.5.2), exposed glass surface areas (Section 6.5.4), 
and possible water contact scenarios that can occur in a breached waste package cannot be 
modeled directly. Instead, the impact of these variables is represented by the range and 
distribution of parameter values. 
(2) In considering alternative conceptual models for radionuclide release rates 
and solubility limits, the U.S. Department of Energy uses appropriate models, 
tests, and analyses that are sensitive to the processes modeled for both natural 
and engineering systems. Conceptual model uncertainties are adequately defined 
and documented, and effects on conclusions regarding performance are properly 
assessed. 
The mechanistic model for borosilicate glass dissolution is well established (Section 6.3.1). 
Uncertainty remains only with regard to the process controlling glass dissolution rate in highly 
concentrated solutions, which is usually too slow to measure. Selection of the minimum rate is 
affected by this uncertainty, but this has no significant impact on the dose calculation. 
(4) The effects of thermal-hydrologic-chemical coupled processes that may occur 
in the natural setting due to interactions with engineered materials or their 
alteration products on radionuclide release are appropriately considered. 
The effect of steel corrosion on the glass degradation rate was measured experimentally 
(Section 6.5.2). It was determined that the effects of dissolved iron (III) are negligible relative to 
the pH dependence and the effects of sorption to colloidal and solid iron corrosion products are 
bounded by the upper limit parameter values. 
Acceptance Criterion 5Model Abstraction Output is Supported by Objective 
Comparisons 
(1) The models implemented in this total system performance assessment 
abstraction provide results consistent with output from detailed process level 
models and/or empirical observations (laboratory tests and filed testing and/or 
natural analogs). 
Validation of the glass degradation model was done by comparison to dissolution rates measured 
for waste glasses in laboratory tests and for basaltic glass reacted at the sea floor (Sections 7.1 
through 7.6). 

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9. INPUTS AND REFERENCES 
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ACC: MOL.20040804.0190. 
164412 Tomozawa, H. and Tomozawa, M. 1989. Diffusion of Water into a Borosilicate 
Glass. Journal of Non-Crystalline Solids, 109, (2-3), 311-317. New York, New 
York: North-Holland. TIC: 254577. 
111048 Van Iseghem, P. and Grambow, B. 1988. The Long-Term Corrosion and Modeling 
of Two Simulated Belgian Reference High-Level Waste Glasses. Scientific Basis for 
Nuclear Waste Management XI, Symposium held November 30-December 3, 1987, 
Boston, Massachusetts. Apted, M.J. and Westerman, R.E., eds. 112, 631-639. 
Pittsburgh, Pennsylvania: Materials Research Society. TIC: 203662. 
163328 Vernaz, E.; Gin, S.; Jgou, C.; and Ribet, I. 2001. Present Understanding of R7T7 
Glass Alteration Kinetics and Their Impact on Long-Term Behavior Modeling. 
Journal of Nuclear Materials, 298, (1-2), 27-36. New York, New York: North- 
Holland. TIC: 254328. 
100942 Vernon, W.H.J. 1933. The Role of the Corrosion Product in the Atmospheric 
Corrosion of Iron. Transactions of the Electrochemical Society. Volume LXIV. 
Pages 31-41. New York, New York: Electrochemical Society. TIC: 237703. 
163330 Vienna, J.D.; Hrma, P.; and Smith, D.E. 1997. Isothermal Crystallization Kinetics in 
Simulated High-Level Nuclear Waste Glass. Scientific Basis for Nuclear Waste 
Management XX, Symposium held December 2-6, 1996, Boston, Massachusetts. 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 9-14 October 2004 
Gray, W.J. and Triay, I.R., eds. 465, 17-24. Pittsburgh, Pennsylvania: Materials 
Research Society. TIC: 238884. 
163331 Vienna, J.D.; Hrma, P.; Crum, J.V.; and Mika, M. 2001. Liquidus Temperature 
Composition Model for Multi-Component Glasses in the Fe, Cr, Ni, and Mn Spinel 
Primary Phase Field. Journal of Non-Crystalline Solids, 292, (1-3), 1-24. New York, 
New York: North-Holland. TIC: 254329. 
171276 Wallace, R.M. and Wicks, G.G. 1983. Leaching Chemistry of Defense Borosilicate 
Glass. Scientific Basis for Nuclear Waste Management VI, Symposium held 
November 1-4, 1982, Boston, Massachusetts. Brookins, D.G., ed. 15, 23-28. New 
York, New York: Elsevier. TIC: 204396. 
106266 Weast, R.C., ed. 1977. CRC Handbook of Chemistry and Physics. 58th Edition. 
Cleveland, Ohio: CRC Press. TIC: 242376. 
163346 Werme, L.; Bjrner, I.K.; Bart, G.; Zwicky, H.U.; Grambow, B.; Lutze, W.; Ewing, 
R.C.; and Magrabi, C. 1990. Chemical Corrosion of Highly Radioactive Borosilicate 
Nuclear Waste Glass Under Simulated Repository Conditions. Journal of Material 
Research, 5, (5), 1130-1146. Warrendale, Pennsylvania: Materials Research Society. 
TIC: 254313. 
111049 White, W.B. 1986. Dissolution Mechanisms of Nuclear Waste Glasses: A Critical 
Review. Volume 20 of Nuclear Waste Management II. Westerville, Ohio: American 
Ceramic Society. TIC: 246079. 
163349 Wicks, G.G. 1992. Nuclear Waste Glasses: Corrosion Behavior and Field Tests. 
Chapter 7 of Corrosion of Glass, Ceramics and Ceramic Superconductors, 
Principles, Testing, Characterization and Applications. Clark, D.E. and Zoitos, B.K., 
eds. Park Ridge, New Jersey: Noyes Publications. TIC: 229453. 
163350 Wronkiewicz, D.J.; Bates, J.K.; Buck, E.C.; Hoh, J.C.; Emery, J.W.; and Wang, L.M. 
1997. Radiation Effects in Moist-Air Systems and the Influence of Radiolytic Product 
Formation on Nuclear Waste Glass Corrosion. ANL-97/15. Argonne, Illinois: 
Argonne National Laboratory. TIC: 234821. 
163351 Zoitos, B.K.; Clark, D.E.; Lodding, A.R.; and Wicks, G.G. 1989. Correlation of 
Laboratory and Stripa Field Leaching Studies. Scientific Basis for Nuclear Waste 
Management XII, Symposium held October 10-13, 1988, Berlin, Germany. Lutze, W. 
and Ewing, R.C., eds. 127, 145-151. Pittsburgh, Pennsylvania: Materials Research 
Society. TIC: 203660. 
9.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
103540 10 CFR 60. Energy: Disposal of High-Level Radioactive Wastes in Geologic 
Repositories. Readily available. 

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156605 10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada. Readily available. 
AP-2.27Q, Rev. 1, ICN 4. Planning for Science Activities. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. ACC: 
DOC.20040610.0006. 
AP-3.15Q, Rev. 4, ICN 5. Managing Technical Product Inputs. Washington, D.C.: 
U.S. Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040812.0004. 
AP-SIII.2Q, Rev. 1, ICN 2. Qualification of Unqualified Data. Washington, D.C.: 
U.S. Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040127.0008. 
AP-SIII.10Q, Rev. 2, ICN 7. Models. Washington, D.C.: U.S. Department of Energy, 
Office of Civilian Radioactive Waste Management. ACC: DOC.20040920.0002. 
105725 ASTM C 1174-97. 1998. Standard Practice for Prediction of the Long-Term 
Behavior of Materials, Including Waste Forms, Used in Engineered Barrier Systems 
(EBS) for Geological Disposal of High-Level Radioactive Waste. West 
Conshohocken, Pennsylvania: American Society for Testing and Materials. 
TIC: 246015. 
119321 ASTM C 1220-98. 1998. Standard Test Method for Static Leaching of Monolithic 
Waste Forms for Disposal of Radioactive Waste. West Conshohocken, Pennsylvania: 
American Society for Testing and Materials. TIC: 247005. 
163205 ASTM C 1285-02. 2002. Standard Test Methods for Determining Chemical 
Durability of Nuclear, Hazardous, and Mixed Waste Glasses and Multiphase Glass 
Ceramics: The Product Consistency Test (PCT). West Conshohocken, Pennsylvania: 
American Society for Testing and Materials. TIC: 254461. 
LP-SI.11Q-BSC, Rev. 00, ICN 01. Software Management. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20041005.0008. 
9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
164329 MO0306ANLGIM01.525. Glass Immersion Test Results (BSC Test Plan: SITP-02- 
WF-002); Concentrations and pH. Submittal date: 06/12/2003. 
164330 MO0306ANLGIM02.525. Glass Immersion Test Results (BSC Test Plan: SITP-02- 
WF-002); Normalized Mass Losses. Submittal date: 06/12/2003. 
164331 MO0306ANLGVH01.526. Glass Vapor Hydration Test Results (BSC Test Plan: 
SITP-02-WF-002). Submittal date: 06/12/2003. 

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164790 MO0308ANLGPC01.528. Immersion Tests for Glass Composition Dependence. 
Submittal date: 08/15/2003. 
171277 MO0407ANLGNN02.608. Normalized Mass Losses of Radionuclides In N2 Tests. 
Submittal date: 07/27/2004. 
170760 MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 
171574 MO0408ANLGNN01.527. Glass Unsaturated (Drip) Test Results (BSC Test Plan: 
SITP-02-WF-002): Boron Release. Submittal date: 08/26/2004. 
9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
MO0409ANLGAMR1.016. HLW Glass Degradation Model. Submittal date: 
09/10/2004. 
MO0307ANLGAMR3.016. Excel Spreadsheets for Calculations in HLW Glass 
Degradation Model. Submittal date: 07/25/2003. 

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APPENDIX A 
pH AND TEMPERATURE DEPENDENCE OF THE FORWARD DISSOLUTION RATE 
OF SRL 202G GLASS 

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INTENTIONALLY LEFT BLANK 

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A. pH AND TEMPERATURE DEPENDENCE OF THE FORWARD DISSOLUTION 
RATE OF SRL 202G GLASS 
Tests were conducted specifically to measure the effect of pH and temperature on the forward 
dissolution rate of a glass having a composition within the composition envelope for DWPF 
glasses. The glass is referred to as SRL 202G and the composition is given in Table A-1 
(DTN: MO0306ANLGIM02.525 [DIRS 164330], Table 1). The glass contains depleted 
uranium, but no other radionuclides. The tests are described in detail in (Ebert 2003 
[DIRS 164517]). A modified static leach test method standardized by the American Society for 
Testing and Materials (ASTM) as standard test method C1220-98 was used to conduct the tests. 
In this method, a monolithic glass sample of known geometric surface area is immersed in a test 
solution in a sealed vessel for a predetermined duration. At the end of the test duration, the 
solution is analyzed for dissolved glass components, which are used as a measure of the extent of 
dissolution. Tests were conducted at 70C and 90C. The modification to the ASTM method 
C1220-98 was that tests were conducted in leachant solutions having pH values imposed by 
added salts (Table A-2). Some leachant solutions were made with added FeCl3, FeOOH, Fe2O3, 
or Fe3O4 to measure the effect of dissolved iron and the presence of iron corrosion products on 
the forward dissolution rate. The mass of each iron compound needed to make a 0.1 molal 
solution was added to the leachant, although only the FeCl3 completely dissolved. Undissolved 
FeOOH, Fe2O3, or Fe3O4 particles were included in the tests to ensure the solutions remained 
saturated with respect to these oxides. 
Monolithic samples were in shape of disks nominally 1 cm in diameter and 1.5-mm thick. The 
faces of the disks were polished with silicon carbide paper and water lubrication to a 600-grit 
final finish. All tests were conducted in Teflon vessels with sample-support stands made of 
Teflon mesh. Because it was expected that glass dissolution would be faster at very low and 
very high pH values, tests at pH 1 and pH 11.9 were conducted at a surface area-to-solution 
volume ratio (S/V) of 2.0 m1 in 120 mL Teflon vessels. Tests at other pH values were 
conducted at an S/V of 10 m1 in 22 mL vessels. Blank tests were conducted in 22-mL Teflon 
vessels for 10 and 21 days at 90C and for 7 days at 70C. Short test durations and low glass 
S/V were used to maintain low concentrations of dissolved silica in the tests. At the end of the 
scheduled test duration, an aliquot of the test solution was taken for pH measurement. The pH of 
this aliquot was measured at room temperature with a combination electrode. The remaining test 
solution was passed through a 0.45 m pore-size filter and then acidified with ultrapure nitric 
acid. Solutions were analyzed for concentrations of Al, B, Fe, Na, Si, and U with inductively 
coupled plasma-mass spectrometry (ICP-MS). 
Table A-3 gives the concentrations measured in blank tests in units of parts per billion (ppb), 
which is equivalent to micrograms/liter solution (DTN: MO0306ANLGIM01.525 
[DIRS 164329], Table 4). These results show that, except for tests B1Fe-10, B1Fe-21, and 
B7Fe-10 (nominal pH 1.0 and pH 3.7 solutions), only a small amount of the added iron actually 
dissolved. For tests in which pH was greater than 3.7, the primary effect was the inclusion of 
iron precipitates in the test. 
The test results are summarized in Tables A-4, A-5, and A-6 (DTN: MO0306ANLGIM01.525 
[DIRS 164329], Tables 1-3). The results are grouped by the nominal solution pH. As mentioned 
above, an amount of the iron compound needed to make a 0.1 molal solution was added to the 

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leachant solution. Whereas the FeCl3 almost completely dissolved, very little of the oxides 
dissolved. When leachant solutions were added to the test vessels, small amounts of the finely 
divided iron compound solids were added to the test vessels. This was done to provide a source 
to maintain saturated iron concentrations during the tests. The test solutions were filtered when 
the tests were terminated to exclude this iron from the aliquot submitted for analyses. 
The 1-day tests at 70C were conducted at S/V of about 8 m1 for durations that would allow 
direct comparison with tests conducted at 10 m-1. The 1-day tests at 70C and pH values 
of 1.3 and 11.9 were conducted for about 6 hours (0.25 days). Solutions generated in these tests 
are equivalent to 1-day tests at 2 m1, since the product of S/V and reaction time is 2 d/m for both 
conditions. Likewise, the tests at other pH values were conducted for 30 hours (1.25 days) at 
S/V of about 8 m1, so the product of S/V and reaction time is about 10 d/m. The results of tests 
at all pH values are treated as 1-day tests at 10 m1 and directly compared with longer duration 
tests at 10 m1 for data analysis. 
The normalized boron mass loss, NL(B), was calculated from the measured concentrations from 
the following equation: 
NL(B) = [C(B)  C(B)]  1,000 / (S/V)  f(B) (Eq. A-1) 
Where C(B) is the B concentration (g/L [ppb]) in the leachate, C(B) is the boron concentration 
(g/L) in the blank at the same temperature and for the same or longer duration, and f(B) is the 
mass fraction of B in the glass (see Table A-1). The factor of 1,000 is the conversion 
factor 1  103 (g/m3)/(g/L). The values of NL(B) for tests at 70C, 90C, and 90C with added 
iron are summarized in Table A-7 (DTN: MO0306ANLGIM02.525 [DIRS 164329], Tables 2 
to 4). The values of NL(B) are plotted against the test duration in Figures A-1, A-2, and A-3 for 
tests at 70C, 90C, and 90C with added iron, respectively. Results from the short-term tests 
were fit to a line to estimate the dissolution rate before the buildup of dissolved silica became 
significant. The origin was not included in the regression. This is because rapid dissolution of 
high-energy sites on the as-prepared surfaces results in a nonrepresentative rate early in the test. 
Longer-term results that deviated negatively from the line were excluded from the regression; 
those results were affected by the buildup of silica in the test solutions. The rate-limiting step in 
the mechanism for the dissolution of silicate glasses involves the neutral species H4SiO4 
(see discussion in Section 6.3). Because the mono- and then double-negatively charged silicic 
acid species become dominant at pH values above about pH 9.7 (at 90C), a higher total silica 
concentration must be present to have the same H4SiO4 concentration as at lower pH values. 
This is seen in the results of tests conducted at 70C and 90C with and without added FeOOH 
(Figures A-2f and A-3f). The slope of the fit line gives the normalized B-release rate, NR(B), 
which is defined as: 
NR(B) = . NL(B) / . t (Eq. A-2) 
where t is the test duration in days. 
The values of NR(B) were used as the forward glass dissolution rate (kf in Equation 11) at each 
temperature and pH. The rates determined from the plots are summarized in Table A-8. The 
glass dissolution rate at 70C and pH 11.9 was also determined with the result of test GB6-70-1 

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included in the regression. The equation of the regression line including the result for test 
GB6-70-1 is y = 1.47 + 8.33x, with R2 = 0.980. 
The rates in Table A-8 are used to determine the pH and temperature dependence for acidic and 
alkaline solutions (Section 6.5.2). One step in determining the temperature dependence is a 
manual regression of lines with set pH dependence to the test results to determine 
the temperature dependence. Results from acidic solutions were regressed to lines with slopes 
of 0.49 and results from alkaline solutions were regressed to lines with slopes 0.49. This was 
done by minimizing the difference between the logarithm of the measured rates and the values of 
log10(rate) calculated from Equations A-3 and A-4 with various values of Aacid and Aalkaline: 
log10(rate) = Aacid  0.49  pH (Eq. A-3) 
log10(rate) = Aalkaline + 0.49  pH. (Eq. A-4) 
A Microsoft Excel spreadsheet, A-9, in the workbook, EXCELglasscalc 
(DTN: MO0307ANLGAMR3.016) was used. Trial values of Aacid and Aalkaline and values 
Aacid  0.01 and Aalkaline  0.01 were used to calculate values of log10(rate) for each pH and 
temperature at which the rate was measured. The differences between the calculated and 
measured rates at each pH were summed for both temperatures. The values of Aacid and Aalkaline 
were increased or decreased to minimize the sum of the residuals at both temperatures. 
Table A-9 shows the spreadsheet results for the best fits for acidic and alkaline solutions in tests 
at 70C and 90C (to the nearest 0.01). The best-fit equations for acidic solutions at 70C and 
90C and for alkaline solutions at 70C and 90C are: 
log10(rateG) = 2.34  0.49  pH for acidic solutions at 70C (Eq. A-5) 
log10(rateG) = 2.60  0.49  pH for acidic solutions at 90C (Eq. A-6) 
log10(rateG) = 5.12 + 0.49  pH for alkaline solutions at 70C (Eq. A-7) 
log10(rateG) = 4.54 + 0.49  pH for alkaline solutions at 90C (Eq. A-8) 
These equations are used in Section 6.5.2.1 as Equations 23 through 26, respectively, to 
determine the temperature dependence for the dissolution of SRL 202G glass. 

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Table A-1. Composition of SRL 202G Glass 
Element 
Element 
Mass % Mass Fraction Element 
Element 
Mass % Mass Fraction 
Al 3.07 0.0307 Mo 0.0072 0.000072 
B 3.21 0.0321 Na 11.36 0.1136 
Ba 0.03 0.0003 Nd 0.0107 0.000107 
Ca 0.768 0.00768 Ni 0.75 0.0075 
Cr 0.28 0.0028 P 0.14 0.0014 
Cu 0.096 0.00096 Pb 0.037 0.00037 
Fe 6.48 0.0648 Si 20.77 0.2077 
K 2.74 0.0274 Sr 0.014 0.00014 
La 0.014 0.00014 Ti 0.076 0.00076 
Li 1.60 0.0160 U 1.34 0.0134 
Mg 1.02 0.0102 Zn 0.011 0.00011 
Mn 0.977 0.00977 
Zr 0.060 0.00060 
Source: DTN: MO0306ANLGIM02.525 [DIRS 164329], Table 1. 
Table A-2. Composition of Leachant Solutions 
Composition 
Solution 
Identifier 
pH at 
25C Fe (g/L) 
0.025 m KCl + 0.205 m HCl B1 1.29 76.4 
0.025 m KCl + 0.025 m HCl + 16.3 g FeCl3 / kg solutiona B1Fe 1.21 3.61  106 
0.05 m KHphb + 0.005 m HCl B7 3.68 80.0 
0.05 m KHph + 0.005 m HCl + 0.406 g FeCl3 / kg solutiona B7Fe 3.66 1.89  104 
0.0095 m KHph + 0.00266 m LiOHH2O B2 4.86 50.1 
0.008 m HNO3 + 0.025 m TRISc B3 8.49 76.6 
0.008 m HNO3 + 0.025 m TRIS + 16.0 g Fe2O3 / kg solutiona B3Fe 8.48 65.3 
0.0038 m HNO3 + 0.05 m TRIS B4 9.24 71.5 
0.0038 m HNO3 + 0.05 m TRIS + 23.2 g Fe3O4 / kg solutiona B4Fe 9.24 83.3 
0.00117 m HNO3 + 0.00144 m LiOHH2O B5 9.80 68.6 
0.00117 m HNO3 + 0.00144 m LiOHH2O + 0.889 g FeOOH/ kg solutiona B5Fe 9.92 52.0 
0.00505 m LiCl + 0.0107 m LiOH B6 11.97 30.7 
0.00505 m LiCl + 0.0107 m LiOH + 0.889 g FeOOH/ kg solutiona B6Fe 11.93 75.4 
Source: Ebert 2003 [DIRS 164517]. 
NOTE: a Amount needed to make a 0.1 m solution, although not all of added Fe compound may be dissolved. 
b KHph: Potassium hydrogen phthalate. 
c TRIS: Tris(hydroxymethyl)aminomethane. 

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Table A-3. Results of Blank Tests with SRL 202G Glass 
Concentration (g/L) 
Test Number 
Duration 
(days) pHa B Fe Si U 
Blank Tests at 70C 
B1-70-7-blank 7 1.34 59 100 35.6 0.061 
B7-70-7-blank 7 3.67 62.9 72.2 535 <0.06 
B2-70-7-blank 7 4.95 51.7 61.8 177 <0.06 
B3-70-7-blank 7 8.42 49.6 72.2 193 <0.06 
B4-70-7-blank 7 9.21 49.8 74.3 375 <0.06 
B5-70-7-blank 7 10.18 44.0 67.4 <7.82 <0.06 
B6-70-7-blank 7 11.90 48.8 74.8 53 <0.06 
Blank Tests at 90C 
B1-10 10 1.31 175 76.4 65.5 0.186 
B1-21 21 1.31 123 77.8 67.6 0.276 
B7-10 10 3.78 143 80.0 479 1.89 
B2-10 10 4.81 69.8 50.1 126 0.216 
B2-21 21 5.12 39.6 71.1 <28.6 0.196 
B3-10 10 8.53 108 76.6 125 0.25 
B3-21 21 8.51 73.2 71.4 140 0.231 
B4-10 10 9.29 74.4 71.5 286 <0.142 
B4-21 21 9.23 66.4 78.4 260 <0.142 
B5-10 10 9.34 116 68.6 <18.16 <0.142 
B5-21 21 9.38 89.9 101 29.5 <0.142 
B6-10 10 12.00 123 30.7 51.5 0.124 
B6-21 21 11.96 98.7 51.3 49.0 0.122 
Blank Tests at 90C with Added Iron 
B1Fe-10 10 0.86 629 3,610,000 776 34.7 
B1Fe-21 21 0.81 515 3,350,000 390 1.11 
B7Fe-10 10 3.70 71 18,900 492 <0.08 
B3Fe-10 10 8.45 103 65.3 358 0.199 
B3Fe-21 21 8.39 74.6 75.4 330 0.205 
B4Fe-10 10 9.26 100 83.3 1740 <0.14 
B4Fe-21 21 9.26 84.2 84.3 1900 <0.14 
B5Fe-10 10 10.22 296 52.0 48.9 0.127 
B5Fe-21 21 10.24 273 56.5 69.8 0.098 
B6Fe-10 10 11.99 124 75.4 85.2 <0.2 
Source: DTN: MO0306ANLGIM01.525 [DIRS 164329], Table 4. 
NOTE: apH measured at room temperature. 

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Table A-4. Solution Compositions for Tests with SRL 202G Glass at 70C 
Concentration (g/L) 
Test No. 
Time 
(days) pHa B Fe Si U 
pH 1.3 
GB1-70-1 0.25 not analyzed 27,900 62,800 182,000 14,100 
GB1-70-2 2 1.31 11,200 25,500 63,400 5,610 
GB1-70-3 3 1.30 13,600 29,900 73,900 6,090 
GB1-70-5 5 1.29 16,000 35,200 78,900 7,250 
GB1-70-7 7 1.34 16,400 35,800 79,700 7,370 
pH 3.7 
GB7-70-1 1.25 not analyzed 946 2,300 3,260 545 
GB7-70-2 2 3.66 2,400 5,000 8,190 875 
GB7-70-3 3 3.68 2,670 5,550 10,300 969 
GB7-70-5 5 3.72 3,930 7,880 20,200 1,530 
GB7-70-7 7 3.73 4,280 8,470 23,400 1,630 
pH 5.0 
GB2-70-1 1.25 not analyzed 341 128 1,190 170 
GB2-70-2 2 4.96 972 181 2,580 264 
GB2-70-3 3 4.94 1,100 177 3,140 292 
GB2-70-5 5 4.98 1,500 136 5,340 447 
GB2-70-7 7 5.01 1,840 137 6,350 581 
pH 8.5 
GB3-70-1 1.25 not analyzed 99.0 <40.8 431 6.76 
GB3-70-2 2 8.39 247 101 623 19.5 
GB3-70-3 3 8.45 245 101 901 22.9 
GB3-70-5 5 8.46 322 101 1,100 33.9 
GB3-70-7 7 8.48 389 233 1,610 75.8 
pH 9.3 
GB4-70-1 1.25 not analyzed 96.6 <40.8 1,030 18.1 
GB4-70-2 2 9.23 239 101 2,020 57.0 
GB4-70-3 3 9.26 268 101 2,370 71.9 
GB4-70-5 5 9.27 345 101 3,100 95.1 
GB4-70-7 7 9.27 387 109 3,650 123 
pH 10.2 
GB5-70-1 1.25 not analyzed 55.5 <40.8 942 45.2 
GB5-70-2 2 10.13 455 106 4,220 150 
GB5-70-3 3 10.19 750 101 5,460 191 
GB5-70-5 5 10.20 942 127 6,920 230 
GB5-70-7 7 10.21 1,180 194 8,950 304 
pH 11.9 
GB6-70-1 0.25 not analyzed 361 <40.8 4,160 230 
GB6-70-2 2 11.89 1,380 288 10,500 695 
GB6-70-3 3 11.93 1,810 242 13,200 800 
GB6-70-5 5 11.90 2,690 235 19,200 1,130 
GB6-70-7 7 11.89 3,030 209 22,600 1,260 
Source: DTN: MO0306ANLGIM01.525 [DIRS 164329], Table 1. 
NOTE: a pH measured at room temperature. 

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Table A-5. Solution Compositions for Tests with SRL 202G Glass at 90C 
Concentration (g/L) 
Test No. 
Time 
(days) pHa B Fe Si U 
pH 1.3 
GB1-1 1 1.32 9,540 23,200 47,500 4,810 
GB1-1.3 1.3 1.31 12,000 27,700 58,900 5,980 
GB1-2 2 1.36 15,600 34,300 68,500 6,600 
GB1-3 3 1.34 19,800 41,800 97,300 8,140 
GB1-5 5 1.40 21,300 44,300 98,100 8,730 
GB1-7 7 1.42 26,200 57,500 121,000 11,200 
GB1-10 10 1.44 33,200 71,000 139,000 14,200 
GB1-21 21 1.53 41,900 92,300 142,000 18,100 
pH 3.7 
GB7-1 1 3.74 603 987 2,970 252 
GB7-2 2 3.74 968 1,540 5,970 426 
GB7-3 3 3.74 1,160 1,840 8,190 514 
GB7-5 5 3.75 2,010 2,520 12,400 765 
GB7-7 7 3.77 3,110 3,890 19,300 1,210 
GB7-10 10 3.78 3,460 4,220 22,100 1,390 
pH 5.0 
GB2-2 2 4.97 1,990 79.0 5,630 407 
GB2-3 3 4.95 2,570 82.3 8,340 560 
GB2-5 5 5.03 3,250 91.6 10,900 751 
GB2-7 7 5.07 4,060 74.2 14,300 929 
GB2-10 10 5.06 4,830 64.0 16,100 976 
GB2-21 21 5.20 7,150 66.8 26,500 1,390 
pH 8.5 
GB3-2 2 8.50 518 73.7 1490 25.1 
GB3-3 3 8.50 609 68.7 1760 39.3 
GB3-5 5 8.53 984 101 2480 29.8 
GB3-7 7 8.53 1130 81.5 3160 34.5 
GB3-10 10 8.52 1440 114 3730 39.3 
GB3-21 21 8.52 1920 58.3 5440 51.3 
pH 9.3 
GB4-2 2 9.24 403 83.0 3,210 62.6 
GB4-3 3 9.22 578 81.1 4,700 130 
GB4-5 5 9.29 950 89.8 6,160 90.8 
GB4-7 7 9.27 1,220 86.2 7,900 113 
GB4-10 10 9.27 1,360 91.3 8,910 124 
GB4-21 21 8.93 1,970 427 12,200 363 
pH 9.8 
GB5-2 2 9.72 456 98.2 3,750 91 
GB5-3 3 9.76 609 98.4 5,040 110 
GB5-5 5 9.89 1,090 248 7,220 119 
GB5-7 7 9.87 1,350 85.5 8,880 120 
GB5-10 10 9.96 2,050 87.6 12,300 135 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-10 October 2004 
Table A-5. Solution Compositions for Tests with SRL 202G Glass at 90C (Continued) 
Concentration (g/L) 
Test No. 
Time 
(days) pHa B Fe Si U 
GB5-21 21 9.94 2,450 279 15,500 157 
pH 11.9 
GB6-2 2 11.94 2,450 244 16,500 817 
GB6-3 3 11.91 3,440 239 22,900 1,080 
GB6-5 5 12.00 4,390 216 28,200 1,160 
GB6-7 7 12.00 4,870 247 29,200 1,260 
GB6-10 10 11.91 5,910 220 36,000 1,240 
GB6-21 21 11.90 8,950 <179 51,400 2,130 
Source: DTN: MO0306ANLGIM01.525 [DIRS 164329], Table 2. 
NOTE: a pH measured at room temperature. 
Table A-6. Solution Compositions for Tests with SRL 202G Glass at 90C with Added Iron Compounds 
Concentration (g/L) 
Test No. 
Time 
(days) pHa B Fe Si U 
pH 1.0 + 0.1 m FeCl3 b 
GB1Fe-1 1 1.02 12,700 4980000 68900 6180 
GB1Fe-1.3 1.3 0.98 16,600 4,630,000 86,100 8,150 
GB1Fe-2 2 0.99 19,300 3,940,000 92,100 8,010 
GB1Fe-3 3 0.97 30,400 4,090,000 122,000 13,100 
GB1Fe-5 5 1.00 34,200 4,060,000 127,000 14,700 
GB1Fe-7 7 0.97 45,400 4,070,000 132,000 19,700 
GB1Fe-10 10 0.96 53,800 4,130,000 146,000 24,000 
GB1Fe-21 21 0.90 60,000 3,600,000 143,000 26,900 
pH 3.7 + 0.1 m FeCl3 b 
GB7Fe-1 1 3.72 496 20,800 2,970 188 
GB7Fe-2 2 3.73 917 19,500 6,360 382 
GB7Fe-3 3 3.73 1,410 18,300 9,050 507 
GB7Fe-5 5 3.74 1,980 18,600 13,800 803 
GB7Fe-7 7 3.75 2,700 18,600 19,400 1,040 
GB7Fe-10 10 3.75 3,690 17,300 26,400 1,230 
pH 8.5 + 0.1 m Fe2O3 c 
GB3Fe-2 2 8.46 477 50.8 1820 9.10 
GB3Fe-3 3 8.46 655 59.4 2450 12.6 
GB3Fe-5 5 8.50 1180 53.3 4090 12.6 
GB3Fe-7 7 8.46 1290 44.5 5910 14.5 
GB3Fe-10 10 8.48 1420 44.2 6080 15.9 
GB3Fe-21 21 8.46 2530 57.4 11500 31.0 
pH 9.3 + 0.1 m Fe3O4 d 
GB4Fe-2 2 9.26 789 87.0 4,920 30.2 
GB4Fe-3 3 9.24 988 84.1 6,140 54.0 
GB4Fe-5 5 9.31 1,530 146 8,650 46.9 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-11 October 2004 
Table A-6. Solution Compositions for Tests with SRL 202G Glass at 90C with Added Iron Compounds 
(Continued) 
Concentration (g/L) 
Test No. 
Time 
(days) pHa B Fe Si U 
GB4Fe-7 7 9.31 1,680 78.0 10,300 66.2 
GB4Fe-10 10 9.30 1,950 93.3 10,900 69.7 
GB4Fe-21 21 8.86 2,720 738 14,200 336 
pH 10.2 + 0.1 m FeOOH e 
GB5Fe-2 2 9.91 900 77.2 905 24.6 
GB5Fe-3 3 9.81 1,410 41.0 992 26.1 
GB5Fe-5 5 10.23 2,080 32.2 1,330 28.7 
GB5Fe-7 7 10.25 2,570 39.0 1,510 41.2 
GB5Fe-10 10 10.22 3,340 46.1 2,170 29.3 
GB5Fe-21 21 10.36 6,200 105 8,050 27.0 
pH 11.9 + 0.1 m FeOOH e 
GB6Fe-1 1 12.00 1,770 102 8,860 402 
GB6Fe-2 2 11.98 2,870 109 14,900 568 
GB6Fe-3 3 11.99 3,760 120 18,100 619 
GB6Fe-5 5 11.98 4,590 113 23,500 724 
GB6Fe-7 7 11.98 6,100 146 29,800 813 
GB6Fe-10 10 11.99 7,010 112 34,100 846 
Source: DTN: MO0306ANLGIM01.525 [DIRS 164329], Table 3. 
NOTES: a pH measured at room temperature. 
b FeCl3 added to leachant make 0.1 m FeCl3 solution. 
c Fe2O3 added to leachant make 0.1 m Fe2O3 solution. 
d Fe3O4 added to leachant make 0.1 m Fe3O4 solution. 
e FeOOH added to leachant make 0.1 m FeOOH solution. 
Table A-7. Results of Tests with SRL 202G Glass: NL(B), g/m2 
Tests at 70C Tests at 90C Tests at 90C with added Iron 
Test No. NL(B) Test No. NL(B) Test No. NL(B) 
pH 1.3 a pH 1.3 a pH 1.0 a + 0.1 m FeCl3 
GB1-70-1 102 GB1-1 147 GBFe1-1 189 
GB1-70-2 174 GB1-1.3 185 GBFe1-1.3 250 
GB1-70-3 213 GB1-2 243 GB1Fe-2 294 
GB1-70-5 250 GB1-3 309 GB1Fe-3 468 
GB1-70-7 258 GB1-5 332 GB1Fe-5 535 
GB1-7 410 GB1Fe-7 704 
GB1-10 519 GB1Fe-10 836 
GB1-21 659 GB1Fe-21 940 
pH 3.7 a pH 3.7 a pH 3.7 a + 0.1 m FeCl3 
GB7-70-1 3.70 GB7-1 7.21 GB7Fe-1 6.67 
GB7-70-2 7.36 GB7-2 12.9 GB7Fe-2 13.3 
GB7-70-3 8.22 GB7-3 16.0 GB7Fe-3 21.0 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-12 October 2004 
Table A-7. Results of Tests with SRL 202G Glass: NL(B), g/m2 (Continued) 
Tests at 70C Tests at 90C Tests at 90C with added Iron 
Test No. NL(B) Test No. NL(B) Test No. NL(B) 
pH 1.3 a pH 1.3 a pH 1.0 a + 0.1 m FeCl3 
GB7-70-5 12.2 GB7-5 29.3 GB7Fe-5 29.6 
GB7-70-7 13.3 GB7-7 46.5 GB7Fe-7 41.2 
GB7-10 52.0 GB7Fe-10 56.8 
pH 5.0 a pH 5.0 a 
GB2-70-1 1.25 GB2-2 6.07 
GB2-70-2 2.90 GB2-3 7.85 
GB2-70-3 3.31 GB2-5 10.0 
GB2-70-5 4.56 GB2-7 12.6 
GB2-70-7 5.62 GB2-10 15.0 
GB2-21 22.5 
pH 8.5 a pH 8.5 a pH 8.5 a + 0.1 m Fe2O3 
GB3-70-1 0.337 GB3-2 1.30 GB3Fe-2 1.19 
GB3-70-2 0.621 GB3-3 1.58 GB3Fe-3 1.74 
GB3-70-3 0.615 GB3-5 2.76 GB3Fe-5 3.40 
GB3-70-5 0.857 GB3-7 3.23 GB3Fe-7 3.75 
GB3-70-7 1.07 GB3-10 4.20 GB3Fe-10 4.16 
GB3-21 5.86 GB3Fe-21 7.78 
pH 9.3 a pH 9.3 a pH 9.3 a + 0.1 m Fe3O4 
GB4-70-1 0.295 GB4-2 1.04 GB4Fe-2 2.18 
GB4-70-2 0.595 GB4-3 1.59 GB4Fe-3 2.80 
GB4-70-3 0.688 GB4-5 2.76 GB4Fe-5 4.59 
GB4-70-5 0.929 GB4-7 3.62 GB4Fe-7 5.02 
GB4-70-7 1.06 GB4-10 4.06 GB4Fe-10 5.84 
GB4-21 6.03 GB4Fe-21 8.37 
pH 10.2 a pH 9.8 a pH 10.2 a + 0.1 m FeOOH 
GB5-70-1 0.175 GB5-2 5.36 GB5Fe-2 9.52 
GB5-70-2 1.29 GB5-3 7.75 GB5Fe-3 17.5 
GB5-70-3 2.22 GB5-5 15.3 GB5Fe-5 28.1 
GB5-70-5 2.83 GB5-7 19.4 GB5Fe-7 35.8 
GB5-70-7 3.58 GB5-10 30.4 GB5Fe-10 47.9 
GB5-21 37.2 GB5Fe-21 93.5 
Tests at 70C Tests at 90C Tests at 90C with added Iron 
Test No. NL(B) Test No. NL(B) Test No. NL(B) 
pH 11.9a pH 11.9 a pH 11.9 a + 0.1 m FeOOH 
GB6-70-1 1.34 GB6-2 36.7 GB6Fe-1 25.8 
GB6-70-2 20.8 GB6-3 52.1 GB6Fe-2 43.1 
GB6-70-3 27.7 GB6-5 67.1 GB6Fe-3 57.0 
GB6-70-5 41.4 GB6-7 74.4 GB6Fe-5 70.0 
GB6-70-7 46.8 GB6-10 91.0 GB6Fe-7 93.8 
GB6-21 140 GB6Fe-10 108 
Source: DTN: MO0306ANLGIM02.525 [DIRS 164329], Tables 2, 3, and 4. 
NOTE: a pH measured at room temperature. 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-13 October 2004 
NOTE: Results shown by open symbols were excluded from the regression line (see text following Equation A-1). 
Figure A-1. NL(B) vs. Test Duration for MCC-1 Tests at 70C at (a) pH 1.3, (b) pH 3.7, (c) pH 5.0, 
(d) pH 8.5 and pH 9.3, (e) pH 10.2, and (f) pH 11.9 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-14 October 2004 
NOTE: Results shown by open symbols were excluded from the regression line (see text following Equation A-1). 
Figure A-2. NL(B) vs. Test Duration for MCC-1 Tests at 90C at (a) pH 1.3, (b) pH 3.7, (c) pH 5.0, 
(d) pH 8.5 and pH 9.3, (e) pH 9.8, and (f) pH 11.9 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-15 October 2004 
NOTE: Results shown by open symbols were excluded from the regression line (see text following Equation A-1). 
Figure A-3. NL(B) vs. Test Duration for MCC-1 Tests at 90C with Added Iron at (a) pH 1.0 with FeCl3, (b) 
pH 3.7 with FeOOH, (c) pH 8.5 with Fe2O3, (d) pH 9.3 with Fe3O4, (e) pH 10.2 with FeOOH, 
and (f) pH 11.9 with FeOOH 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-16 October 2004 
Table A-8. Results of Tests with SRL 202G glass: NR(B), g/(m2d) 
Nominal pHa 
NR(B) 
g/(m2d) R2, b 
Tests at 70C 
1.3 55.5 0.971 
3.7 2.26 0.887 
5.0 1.03 0.892 
8.5 0.139 0.734 
9.3 0.197 0.915 
10.2 0.646 0.907 
11.9 6.86c 1.000c 
11.9 8.33d 0.980d 
Tests at 90C 
1.3 79.1 0.987 
3.7 6.47 0.981 
5.0 1.27 0.994 
8.5 0.410 0.967 
9.3 0.522 0.995 
9.8 3.38 0.990 
11.9 15.4 1.000 
Tests at 90C with Iron 
1.0 133 0.968 
3.7 7.17 0.998 
8.5 0.543 0.933 
9.3 0.816 0.993 
10.2 5.17 0.981 
11.9 15.6 0.996 
NOTES: a pH measured at room temperature. 
b Linear correlation coefficient squared. 
c Excluding result of test GB6-70-1. 
d Including result of test GB6-70-1. 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-17 October 2004 
Table A-9. Results of Manual Regression of pH Dependence to Measured Rates 
Tests at 90C in Acidic Solutions 
log10(rate) = 0.49 pH + 2.60 + e Residuals Nominal 
pH 
Measured 
Rate, 
g/(m2d) 
log(rate) 
e = 0 e = 0.01 e = -0.01 e = -0.00107 e = 0 e = 0.01 e = -0.01 e = -0.00107 
1.3 79.1 1.90 1.963 1.973 1.953 1.962 -0.065 -0.075 -0.055 -0.0638 
3.7 6.47 0.811 0.787 0.797 0.777 0.786 0.024 0.014 0.034 0.0250 
5 1.27 0.104 0.150 0.160 0.140 0.149 -0.046 -0.056 -0.036 -0.0451 
1.0 w/ Fe 133 2.12 2.110 2.120 2.100 2.109 0.014 0.004 0.024 0.0149 
3.7 w/ Fe 7.17 0.856 0.787 0.797 0.777 0.786 0.069 0.059 0.079 0.0696 
Sum of Residuals: -0.005 -0.055 0.045 0.0006 
Tests at 90C in Alkaline Solutions 
log10(rate) = 0.49 pH 4.54 + e Residuals Nominal 
pH 
Measured 
Rate, 
g/(m2d) 
log10(rate) 
e = 0 e = 0.01 e = -0.01 e = 0.00175 e = 0 e = 0.01 e = -0.01 e = 0.00175 
8.5 0.41 -0.387 -0.375 -0.365 -0.385 -0.373 -0.012 -0.022 -0.002 -0.0140 
9.3 0.522 -0.282 0.017 0.027 0.007 0.019 -0.299 -0.309 -0.289 -0.3011 
9.8 3.38 0.529 0.262 0.272 0.252 0.264 0.267 0.257 0.277 0.2652 
11.9 15.4 1.19 1.291 1.301 1.281 1.293 -0.103 -0.113 -0.093 -0.1052 
8.5 w/ Fe 0.543 -0.265 -0.375 -0.365 -0.385 -0.373 0.110 0.100 0.120 0.1080 
9.3 w/ Fe 0.816 -0.0883 0.017 0.027 0.007 0.019 -0.105 -0.115 -0.095 -0.1071 
10.2 w/ Fe 5.17 0.713 0.458 0.468 0.448 0.460 0.255 0.245 0.265 0.2537 
11.9 w/ Fe 15.6 1.19 1.291 1.301 1.281 1.293 -0.098 -0.108 -0.088 -0.0996 
Sum of Residuals: 0.014 -0.066 0.094 0.0000 

Defense HLW Glass Degradation Model 
ANL-EBS-MD-000016 REV 02 A-18 October 2004 
Table A-9. Results of Manual Regression of pH Dependence to Measured Rates (Continued) 
Tests at 70C in Acidic Solutions 
log10(rate) = 0.49 pH + 2.34 + e Residuals 
Nominal 
pH 
Measured 
Rate, 
g/(m2d) log10(rate) e = 0 e = 0.01 e = -0.01 e = -0.00293 e = 0 e = 0.01 e = -0.01 e = -0.00293 
1.3 55.5 1.74 1.703 1.713 1.693 1.700 0.041 0.031 0.051 0.0442 
3.7 2.26 0.354 0.527 0.537 0.517 0.524 -0.173 -0.183 -0.163 -0.1700 
5 1.03 0.0128 -0.110 -0.100 -0.120 -0.113 0.123 0.113 0.133 0.1258 
Sum of Residuals: -0.009 -0.039 0.021 0.0000 
Tests at 70C in Alkaline Solutions 
log10(rate) = 0.49 pH  5.12 +e Residuals 
Nominal 
pH 
Measured 
Rate, 
g/(m2d) log10(rate) e = 0 e = 0.01 e = -0.01 e = 0.00325 e = 0 e = 0.01 e = -0.01 e = 0.00325 
8.5 0.139 -0.86 -0.955 -0.945 -0.965 -0.952 0.098 0.088 0.108 0.0948 
9.3 0.197 -0.71 -0.563 -0.553 -0.573 -0.560 -0.143 -0.153 -0.133 -0.1458 
10.2 0.646 -0.19 -0.122 -0.112 -0.132 -0.119 -0.068 -0.078 -0.058 -0.0710 
11.9 6.86 a 0.84 0.711 0.721 0.701 0.714 0.125 0.115 0.135 0.1221 
Sum of Residuals: 0.013 -0.027 0.053 0.0000 
Source: DTN: MO0307ANLGAMR3.016. 
NOTE: a Rate when result of test GB6-70-1 is excluded. 

ANL-EBS-MD-000016 REV 02 B-1 October 2004 
APPENDIX B 
EXTRACTION OF log10(kE) FROM MEASURED DISSOLUTION RATES AND 
CALCULATION OF RATES 

ANL-EBS-MD-000016 REV 02 B-2 October 2004 
INTENTIONALLY LEFT BLANK 

ANL-EBS-MD-000016 REV 02 B-3 October 2004 
B. EXTRACTION OF log10(kE) FROM MEASURED DISSOLUTION RATES AND 
CALCULATION OF RATES 
The rate expression is: 
rate = kE  10.  pH  exp(Ea/RT) (Eq. B-1) 
The logarithm form of the rate expression is: 
log10(rate) = log10(kE) + .  pH + log10(exp(Ea/RT)) (Eq. B-2) 
log10(rate) = log10(kE) + .  pH  Ea/(2.303RT) (Eq. B-3) 
The rate expression is rearranged to solve for the value of log10(kE) as: 
log10(kE) = log10(rate)  .  pH + Ea/(2.303RT) (Eq. B-4) 
The dissolution rate determined from the boron release rate is: 
log10(kE) = log10(NR(B))  .  pH + Ea/(2.303RT) (Eq. B-5) 
If results are available for several durations, the normalized boron release rate can be determined 
as the slope of a plot of NL(B) versus duration and calculated as: 
NR(B) = . NL(B) / .t (Eq. B-6) 
where NL(B) is the normalized boron mass loss and t is the test duration. If tests are conducted 
for a single duration, the average normalized boron release rate can be calculated as: 
NR(B) = NL(B) / t (Eq. B-7) 
B.1 CALCULATION OF kE FROM THE FORWARD DISSOLUTION RATES 
For tests in which NR(B) gives the forward dissolution rate, the value of kE is expressed as k0. 
Equation B-5 was solved by substituting parameters determined from the dissolution in alkaline 
solutions. Table B-1 shows the determination of log10(k0) from the values of NR(B) from 
MCC-1 tests (see Table 6-5 for references to measured rates and pH values) for . = 0.49, 
Ea = 69 kJ/mol, R = 0.008314 kJ/molK, and T = 363 K (90C). The value of the term giving the 
temperature dependence is Ea/(2.303RT) is 9.93 for all calculations. These results are shown in 
Table 6-5. 

ANL-EBS-MD-000016 REV 02 B-4 October 2004 
Table B-1. Extraction of log10(k0) from Forward Dissolution Rates 
Glass 
NR(B), 
g/(m2d) log10(NR(B)), pH 0.49pH log10(k0,) 
HLW Glasses 
SRL 51S 0.66 -0.1805 9.9 4.85 4.90 
SRL 202U 0.69 -0.1612 9.8 4.80 4.97 
SRL 165U 1.0 0.0000 9.6 4.70 5.23 
SRL 131U 1.2 0.0792 9.8 4.80 5.21 
WV6 0.69 -0.1612 9.5 4.66 5.11 
Hanford-D 1.80 0.2553 10.5 5.15 5.04 
Other Glasses 
Hanford-L 0.97 -0.0132 9.5 4.66 5.26 
LD6-5412 0.47 -0.3279 9.3 4.56 5.04 
PNL 7668 1.1 0.0414 9.2 4.51 5.46 
Average: 5.14 
Standard Deviation: 0.17 Average for All Glasses 
Percent Relative Standard Deviation: 3.31 
Average: 5.07 
Standard Deviation: 0.13 Average for 6 HLW 
Glasses 
Percent Relative Standard Deviation: 2.56 
B.2 EXTRACTION OF kE FROM PCT RATES 
For tests in which NR(B) gives the average dissolution rate in a 7-day PCT, the value of kE is 
expressed as kPCT. Equation B-5 was solved by substituting parameters for dissolution in 
alkaline solutions in a Microsoft Excel spreadsheet. Table B-2 shows the determination of 
log10(kPCT) from the values of NR(B) from long-term PCT (see Table 6-6 for measured rates and 
pH values) for . = 0.49, Ea = 69 kJ/mol, R = 0.008314 kJ/(mol K), and T = 363 K (90C). The 
value of the term giving the temperature dependence is Ea/(2.303RT) is 9.93 (unitless) for all 
calculations. These results are included in Table 6-6. 

ANL-EBS-MD-000016 REV 02 B-5 October 2004 
Table B-2. Extraction of log10(kPCT) from 7-day PCT Rates 
Glass 
NL(B) 
(g/m2) 
NR(B) 
(g/(m2d)) log10(NR(B)) pH 0.49pH 
log10(kPCT) 
(g/(m2d)) 
HLW Glasses 
SRL 51Sa 0.267 0.0381 -1.419 10.66 5.223 3.29 
SRL 51Sb 0.247 0.0353 -1.452 10.33 5.062 3.42 
SRL 51S avg 3.35 
SRL 165U 0.308 0.0440 -1.357 10.31 5.052 3.52 
SRL 202U 0.298 0.0426 -1.371 10.42 5.106 3.45 
SRL 131U 4.81 0.6871 -0.163 11.63 5.699 4.07 
WV ref 6 0.270 0.0386 -1.414 9.98 4.890 3.63 
Hanford-D 0.361 0.0516 -1.288 10.67 5.228 3.41 
Glass 
NL(B) 
(g/m2) 
NR(B) 
(g/(m2d)) log10(NR(B)) pH 0.49pH 
log10(kPCT) 
(g/(m2d)) 
HLW Glasses 
SRL202G 0.608 0.0869 -1.061 11.11 5.444 3.42 
SRL 200S 0.700 0.100 -1.000 10.65 5.219 3.71 
Other Glasses 
Hanford-L 0.475 0.0679 -1.168 10.96 5.370 3.39 
PNL 76-68 1.23 0.176 -0.755 9.43 4.621 4.55 
LD6-5412 0.082 0.0117 -1.931 11.20 5.488 2.51 
SAN 60 0.385 0.0550 -1.260 9.80 4.802 3.87 
EA 8.21 1.17 0.0682 11.87 5.816 4.18 
Average: 3.58 
Standard deviation: 0.47 For All Glasses: 
Percent relative standard deviation: 13.13 
Average: 3.57 
Standard deviation: 0.48 For All Glasses Except EA: 
Percent relative standard deviation: 13.45 
Average: 3.57 
Standard deviation: 0.23 For 8 HLW Glasses 
Percent relative standard deviation: 6.44 
Other Tests 
Glass NL(B) 
(g/m2) 
NR(B) 
(g/(m2d)) 
log10(NR(B)) 
(g/(m2d)) pH 0.49pH log10(kPCT) 
(g/(m2d)) 
EA in Tuff 
Groundwater 4.48 0.64 0.6513 11.61 5.689 4.05 
CWF 0.0675 0.00964 -1.171 9.01 4.416 3.50 

ANL-EBS-MD-000016 REV 02 B-6 October 2004 
B.3 CALCULATION OF MODEL RATES FOR COMPARISON WITH MEASURED 
RATES AFTER SECONDARY ALTERATION PHASES FORM 
Equation B-3 was solved using the maximum and minimum values of kE for dissolution in 
alkaline solutions at 90C and at the pH values attained by various glasses when zeolites 
precipitate and cause the dissolution rate to increase. The parameter values are: 
kE_alkaline maximum = 3.47  104 g/(m2d); kE_alkaline minimum = 28.2 g/(m2d); 
. = 0.49;  69/(2.303RT) at 90C =  9.927 
The rate expressions are: 
log10(maximum rate) = log(3.47  104) + 0.49  pH  9.927 (Eq. B-8a) 
log10(minimum rate) = log(28.2) + 0.49  pH  9.927 (Eq. B-8b) 
log10(mean rate) = log(1.16  104) + 0.49  pH  9.927 (Eq. B-8c) 
The mean rate is calculated from the maximum, minimum, and mode of the kE distribution 
(Evans et al. 1993 [DIRS 112115]). These expressions were solved in a Microsoft Excel 
spreadsheet. The results are summarized in Table B-3. The results are included in Table 7-2. 
Table B-3. Calculation of Maximum and Minimum Rates from Tests in which Secondary Alteration 
Products formed on the Sample Surface 
Mean Rate g/(m2d) Maximum Rate g/(m2d) Minimum Rate g/(m2d) 
Glass pH 
log10(Rate) Rate log10(Rate) Rate log10(Rate) Rate 
EA 12.3 0.164 1.46 0.638 4.35 -2.45 0.00353 
SRL 131A 12.1 0.066 1.16 0.540 3.47 -2.55 0.00282 
SRL 202A 12.0 0.017 1.04 0.491 3.10 -2.60 0.00252 
SRL 200S 12.2 0.115 1.30 0.589 3.88 -2.50 0.00316 
SAN60 9.8 -1.061 0.09 -0.587 0.259 -3.68 0.000210 
LD6-5412 12.0 0.017 1.04 0.491 3.10 -2.60 0.00252 
B.4 CALCULATION OF MODEL RATES FOR COMPARISON WITH MEASURED 
RATES FOR BASALTIC GLASS 
Equation B-3 was solved by substituting the maximum and minimum values of kE for dissolution 
in alkaline solutions at 3C. The parameter values are: 
kE_alkaline maximum = 3.47  104 g/(m2d); kE_alkaline minimum = 28.2 g/(m2d); 
. = 0.49;  69/(2.303RT) at 90C =  13.057 
kE_alkaline maximum = 2.47  104 g/(m2d); kE_alkaline minimum = 28.2 g/(m2d); 
. = 0.49;  69/(2.303RT) at 3C =  13.057 
log10(maximum rate) = log(3.47  104) + 0.49  pH  13.057 (Eq. B-9a) 
log10(minimum rate) = log(28.2) + 0.49  pH  13.057 (Eq. B-9b) 

ANL-EBS-MD-000016 REV 02 B-7 October 2004 
These expressions were solved using a Microsoft Excel spreadsheet. The results are given in 
Table B-4 and cited in Section 7.3. 
Table B-4. Calculation of Maximum and Minimum Rates at 3C 
Maximum Rate g/(m2d) Minimum Rate g/(m2d) 
Glass pH log10(Rate) Rate log10(Rate) Rate 
Basalt 7 -4.93513 1.16E-05 -8.17888 6.62E-09 
Basalt 8 -4.44513 3.59E-05 -7.68888 2.05E-08 
Basalt 9 -3.95513 1.11E-04 -7.19888 6.33E-08 

ANL-EBS-MD-000016 REV 02 B-8 October 2004 
INTENTIONALLY LEFT BLANK 

ANL-EBS-MD-000016 REV 02 C-1 October 2004 
APPENDIX C 
VAPOR HYDRATION TESTS 

ANL-EBS-MD-000016 REV 02 C-2 October 2004 
INTENTIONALLY LEFT BLANK 

ANL-EBS-MD-000016 REV 02 C-3 October 2004 
C. VAPOR HYDRATION TESTS 
A series of vapor hydration tests (VHTs) was conducted at ANL specifically to measure the 
degradation rates of three glasses at 70C, 90C, 125C, 150C, 175C, and 200C (Ebert 2003 
[DIRS 164518]). These test results are used to determine parameter values for the TSPA-LA 
glass degradation model that are applicable to glass degradation in humid air. The test results 
and analysis are described in this section. 
The VHTs were conducted by suspending two monolithic glass samples in a sealed stainless 
steel vessel with a small amount of demineralized water, then heating at an elevated temperature 
for durations between a few hours and a few years. The extent of corrosion was quantified by 
measuring the thickness of a surface alteration layer. Tests were conducted at several relative 
humidities by varying the amount of water that was added, to the test vessel; the relative 
humidity was calculated from the vessel volume, the volume of water, the temperature, and the 
published vapor pressure of water at that temperature. Tests at relative humidities less 
than 100% were conducted by adding less water than the amount required to saturate the vapor 
phase, which was calculated steam table data. What will be referred to as standard VHTs were 
conducted by adding enough water to the 22 mL vessel to attain 100% relative humidity and 
provide enough water to condense on the samples and form a thin film in which corrosion 
occurs, but not enough water to cause the solution to drip from the sample during the test. 
Standard VHTs at 70C, 90C, 125C, 150C, 175C, and 200C were conducted with about 
0.10, 0.11, 0.13, 0.15, 0.20, 0.25 g of water, respectively. Some tests were conducted with 
seeded samples.  Small crystals of various minerals were fixed to the surface of one of the 
samples (Sample B) used in a test; the other sample in the test vessel (Sample A) was not seeded. 
This was done to see if the presence of the seed crystal caused the alteration of that test sample to 
increase relative to the other, nonseeded sample. Tests were also conducted with excess water 
(e.g., with 7.5 g) to cause a continuous reflux of water condensing on and dripping off the 
sample. A few tests were interrupted after a few hours to replace the water. This was done to 
determine if tests could be sampled periodically without affecting the reaction progress. Some 
tests were conducted with less than the standard amount of water. This was done to achieve 
less than 100% relative humidity. 
Tests were conducted with three glasses representative of DWPF waste glasses: SRL 51S glass 
was made with SRL 202 frit and added chemicals, SRL 131 was made with SRL 131 frit and 
added chemicals (this glass is referred to as SRL 131-TDS in DTN: MO0306ANLGVH01.526 
[DIRS 164331] and in some of the data source documents), and SRL 165S was made with SRL 
black frit II and added chemicals. The glass compositions are given in Table C-1 
(DTN: MO0306ANLGIM01.525 [DIRS 164329], Table 4). Analytical results that show a mass 
balance of 95% to 105% are considered to be quantitative. Standard VHTs were conducted with 
SRL 51S glass at 70C, 90C, 125C, 150C, 175C, and 200C, with SRL 131 glass at 150C 
and 200C, and with SRL 165S glass at 90C, 125C, and 200C. Tests at <100% relative 
humidity and tests with excess water were conducted with the SRL 51S and SRL 131 glasses. 
At the end of the test duration, vessels were removed from the oven and placed in a shallow 
water bath so that water vapor would rapidly condense to the bottom of the vessel. This also 
resulted in the evaporation of most of the water from the test samples, which remained hotter 
than the vessel bottom for about an hour (depending on the test temperature). The vessel was 
then opened and the pH of the condensed water was measured with pH paper and the pH 

ANL-EBS-MD-000016 REV 02 C-4 October 2004 
recorded. If the water was alkaline (i.e., pH > 8), it was assumed that water had dripped from the 
sample either during the test or when the test vessel was removed from the oven and opened. 
The layers in tests in which water had dripped from the sample during the test are expected to be 
thinner than in tests in which water had not dripped. This is not used as a quantitative measure 
of the solution pH contacting the sample, and samples in tests with alkaline solutions were not 
rejected, but the layer thickness may be less than expected from other tests. 
One or both of the reacted samples from a test were split in half in the direction they hung in the 
vessels then fixed in epoxy so that the range of layer thicknesses formed from top to bottom of 
the sample was analyzed. Jigs were used in the epoxy mounts to hold the samples perpendicular 
in the epoxy mounts to get an accurate measure of the layer thickness. Polishing of the sample 
cross sections was performed with carbide abrasive paper and water lubrication. The thickness 
of the alteration layer was measured with a Topcon AB60 scanning electron microscope. The 
average of 10 to 15 measurements for each sample was typically used as a measure of the extent 
of reaction. 
The results are summarized in Tables C-2 through C-7 (DTN: MO0306ANLGVH01.526 
[DIRS 164331]). Fewer significant figures are reported for the test duration and layer 
thicknesses in these tables than in DTN: MO0306ANLGVH01.526 [DIRS 164331] for some 
tests. Test durations less than 20 days are reported to the nearest tenth of a day. Layer 
thicknesses less than 99 m are reported to two significant figures. 
Table C-1. Compositions of SRL 51S, SRL 165, and SRL 131 Glasses 
Oxide mass % Oxide mass % 
Oxide SRL 51S SRL 131 SRL 165S Oxide SRL 51S SRL 131 SRL 165S 
Al2O3 5.18 3.91 4.08 Na2O 9.19 13.4 10.9 
B2O3 6.41 10.8 6.76 NiO 0.36 1.68 0.85 
BaO   0.06 P2O5 0.573  0.02 
CaO 1.3 1.2 1.62 SiO2 48.5 41.4 52.9 
Cr2O3 0.53 0.1  SrO   0.1 
Fe2O3 14.4 15.4 11.7 TiO2 0.033 0.82 0.14 
K2O 1.64 0.048  ThO2 0.034   
La2O3 0.49 0.30  UO2 0.644 0 0.92 
Li2O 4.69 4.19 4.18 ZnO 0.012 0.31 0.04 
MgO 1.97 1.5 0.70 ZrO2 0.014 0.34 0.66 
MnO2 1.6 3.90 2.79 Total 97.589 99.382 98.383 
Source: DTN: MO0306ANLGVH01.526 [DIRS 164331], Table 3. 
NOTE:  = Not measured or not detected. 
Table C-2. Test Matrix and Layer Thickness on the Test Specimen for VHTs with SRL 51S Glass 
Layer Thickness (m) 
Test No. 
Temperature 
(C) 
Time 
(days) Water (g) pHa Sample A Sample B 
Standard VHTs 
VHT(70)-1 70 182 0.1017 6 not measured not measured 
VHT(70)-2 70 471 0.1014 7 0 not measured 
VHT(70)-3 70 838 0.1044 6 to 7 0 0 
VHT(70)-4 70 1,084 0.1008 7 0 not measured 

ANL-EBS-MD-000016 REV 02 C-5 October 2004 
Table C-2. Test Matrix and Layer Thickness on the Test Specimen for VHTs with SRL 51S Glass 
(Continued) 
Layer Thickness (m) 
Test No. 
Temperature 
(C) 
Time 
(days) Water (g) pHa Sample A Sample B 
VHT(70)-5 70 1,361 0.1010 7 0 0 
VHT(70)-6 70 1,361 0.1017 6 0 0 
VHT(70)-7 70 1,361 0.1017 7 0 0 
VHT(70)-8 70 1,045 0.1018 6 0 not measured 
VHT(70)-9 70 1,322 0.0973 6 0 not measured 
VHT(70)-10 70 1,322 0.0990 7 0 not measured 
VHT(90)-1 90 91 0.1083 8 0.64  0.15 0.75  0.13 
VHT(90)-2 90 182 0.1084 6 not measured not measured 
VHT(90)-3 90 418 0.1086 8 0 0 
VHT(90)-4 90 836 0.1081 6 to 7 0 0 
VHT(90)-5 90 1,360 0.1099 6 0 0 
VHT(90)-6 90 1,360 0.1064 7 0 0 
VHT(90)-7 90 279 0.1073 7 0 0 
VHT(90)-8 90 1,037 0.1091 6 0 0 
VHT(90)-9 90 1,285 0.1096 7 0 0 
VHT(90)-10 90 1,285 0.1090 6 0 0 
VHT(125)-1 125 56 0.1280 8 1.7  0.3 3.2  0.9 
VHT(125)-2 125 91 0.1289 9 5.9  0.9 8.8  1.5 
VHT(125)-3 125 182 0.1307 9 7.8  0.9 15  2 
VHT(125)-4 125 414 0.1285 9 14  2 19  1 
VHT(125)-5 125 832 0.1277 10 to 11 38  2 41  14 
VHT(125)-6 125 245 0.1288 12 14 2.0 
VHT(125)-7 125 1,326 0.1291 9 32  7 33  2 
VHT(125)-8 125 591 0.1306 8 43  2 not measured 
VHT(125)-9 125 591 0.1324 9 18  3 15  3 
VHT(125)-10 125 1,039 0.1311 10 24  3 29  9 
VHT(150)-1 150 28 0.1480 8 0 not measured 
VHT(150)-2 150 56 0.1503 7 0.93  0.15 0.86  0.28 
VHT(150)-3 150 91 0.1510 9 13  2.6 21  2.9 
VHT(150)-4 150 182 0.1503 9 41  1.7 36  2.6 
VHT(150)-5 150 420 0.1516 10 not measured not measured 
VHT(150)-6 150 281 0.1470 12 50 43 
VHT(150)-7 150 443 0.1508 9 51  3 51  9 
VHT(150)-8 150 597 0.1515 9 18  4 17  2 
VHT(150)-9 150 351 0.1498 7 to 8 25  5 28  5 
VHT(150)-10 150 351 0.1502 9 27  1 35  2 
VHT(175)-1 175 17.8 0.1992 10 6.0  0.5 5.6  0.9 
VHT(175)-2 175 28 0.2016 7 1.5  0.2 1.9  0.2 
VHT(175)-3 175 41 0.1997 9 7.3  1.1 11  2 
VHT(175)-4 175 61 0.1983 10 18  3 22  4 
VHT(175)-5 175 102 0.2013 11 30  2 59  4 
VHT(175)-6 175 151 0.1980 9 84  4 79  3 
VHT(175)-7 175 196 0.2001 9 188  7 223  17 
VHT(200)-1 200 2.8 0.2489 9 2.7  0.4 4.4  0.3 

ANL-EBS-MD-000016 REV 02 C-6 October 2004 
Table C-2. Test Matrix and Layer Thickness on the Test Specimen for VHTs with SRL 51S Glass 
(Continued) 
Layer Thickness (m) 
Test No. 
Temperature 
(C) 
Time 
(days) Water (g) pHa Sample A Sample B 
VHT(200)-2 200 6.8 0.2467 9 4.7  0.3 4.3  0.4 
VHT(200)-3 200 9.8 0.2512 8 12  3 8.9  0.9 
VHT(200)-4 200 13.9 0.2508 10 33  1 37  2 
VHT(200)-5 200 16.9 0.2501 9 27  1 not measured 
VHT(200)-6 200 21 0.2485 8 66  3 not measured 
VHT(200)-7 200 35 0.2508 9 79  5 77  4 
VHT(200)-8 200 28 0.2492 9 80  2 89  2 
VHT(200)-9 200 45 0.2492 9 204  7 167  17 
VHT(200)-10 200 57 0.2517 8 345  13 357  41 
VHT(200)-11 200 70 0.2501 8 514  27 510  48 
VHT(200)-12 200 87 0.2496 10 420  31 528  13 
VHT(200)-13 200 49 0.2513 10 55  2 61  7 
Standard VHT with and without Seeded Samplesb 
51S1-1 200 2.8 0.2525 1.7  0.2 1.7  0.3 
51S1-1A 200 13.8 0.2502 12  1 17  5 
51S1-1S 200 13.8 0.2495 136  8 not measured 
51S1-2 200 21 0.2529 24  1 24  1 
51S1-2A 200 6.8 0.2509 3.6  0.6 11  3 
51S1-2S 200 2.6 0.2518 15  1 17  1 
51S1-3 200 9.7 0.2501 14  1 13  1 
51S1-3T 200 9.9 0.2511 7.7  0.3 9.4  0.7 
51S1-4 200 0.9 0.2522 1.5  0.1 not measured 
51S1-4T 200 2.9 0.2516 1.3  0.2 1.6  0.2 
51S1-5 200 35 0.2501 68  3 69  4 
51S1-5A 200 21 0.2514 19  1 24  2 
51S1-6 200 60 0.2509 409  28 649  79 
51S1-6A 200 9.9 0.2505 8.5  0.4 8.6  1.6 
51S1-7 200 6.8 0.2585 2.8  0.3 7.9  1.4 
51S1-7A 200 2.6 0.2491 2.8  0.5 2.5  0.4 
51S1-8 200 13.8 0.2500 15  1 15  1 
51S1-8A 200 16.8 0.2516 32  1 32  2 
51S1-9 200 49 0.2512 180  12 145  22 
51S1-10 200 16.8 0.2507 18  1 15 1 
51S2-11 200 4.9 0.2543 2.6  0.2 not measured 
51S2-12 200 35 0.2530 69  2 67  2 
51S2-13 200 28 0.2498 not measured not measured 
51S2-14 200 49 0.2475 225  10 277  17 
51S2-15 200 28 0.2492 44  2 43  4 
51S-1.5mL-1 200 21 1.4900 10 36  2 38  6 
51S-1.5mL-2 200 6.7 1.4977 10 6.8  0.6 not measured 
51S-1.5mL-3 200 35 1.5113 11 38  1 44  4 
51S-7.5-901 90 61 7.5089 8.60 0.41  0.16 0.75  0.53 
51S-7.5-902 90 458 7.5292 7 0 0 
51S-7.5-1251 125 61 7.5034 8.21 0.97  0.26 not measured 
51S-7.5-1252 125 458 7.4990 8 3.8  0.2 7.7  3.0 

ANL-EBS-MD-000016 REV 02 C-7 October 2004 
Table C-2. Test Matrix and Layer Thickness on the Test Specimen for VHTs with SRL 51S Glass 
(Continued) 
Layer Thickness (m) 
Test No. 
Temperature 
(C) 
Time 
(days) Water (g) pHa Sample A Sample B 
Excess Water VHTc 
51S-7.5-1501 150 61 7.5090 7.22 0.98  0.07 0 
51S-7.5-1502 150 458 7.5059 7 0 2.7  0.7 
51S-7.5-1751 175 49 7.4984 10.16 0 22  2 
51S-7.5-1752 175 458 7.5035 10.50 not measured not measured 
51S-7.5-2001 200 13.8 7.5091 9 7.6  6.3 2.7  3.2 
51S-7.5-2002 200 28 7.5008 9 54  6 60  9 
51S-7.5-2003 200 56 7.5085 10.28 not measured 77  5.4 
51S-7.5-2004 200 73 7.5012 10.34 not measured not measured 
51S-7.5-2005 200 215 7.5083 10 not measured not measured 
51S-7.5-2006 200 458 7.5065 dry not measured 133  49 
51S-7.5-2007 200 6.8 7.5050 8 8.3  1.9 0.91  0.26 
Interrupted Standard VHT 
51S-OP1 200 0.3 0.2497 
51S-OP1R 200 13.5 0.2502 7 23  2 20  1 
51S-OP2 200 0.3 0.2514 
51S-OP2R 200 28 0.2514 9 79  3 76  3 
51S-OP3 200 0.3 0.2498 
51S-OP3R 200 35 0.2509 9 105  4 102  3 
Undersaturated VHTd 
51S-20RH-1 200 182 0.0340 7 not measured not measured 
51S-20RH-2 200 312 0.0301 dry not measured not measured 
51S-20RH-3 200 312 0.0340 dry not measured not measured 
51S-45RH-1 200 182 0.0725 7 not measured not measured 
51S-45RH-2 200 90 0.0742 7 1.4  0.2 not measured 
51S-45RH-3 200 93 0.0757 dry not measured not measured 
51S-64RH-1 200 12.9 0.0997 dry not measured not measured 
51S-64RH-2 200 91 0.1019 dry not measured not measured 
51S-80RH-1 200 35 0.1218 dry not measured not measured 
51S-80RH-2 200 35 0.1215 dry not measured not measured 
51S-80RH-3 200 31 0.1214 dry not measured not measured 
51S-80RH-4 200 14.5 0.1243 dry not measured not measured 
51S-80RH-5 200 90 0.1292 7 5.7  0.5 5.1  0.8 
51S-80RH-6 200 182 0.1229 7 3.9  0.8 3.1  0.5 
51S-80RH-7 200 49 0.1243 7 4.6  0.8 4.6  1.5 
51S-90RH-1 200 49 0.1397 7 33  10 not measured 
51S-90RH-2 200 49 0.1425 7 33  5 41  7 
Source: DTN: MO0306ANLGVH01.526 [DIRS 164331], Table 1. 
NOTES: a pH of solution in bottom of test vessel at end of test; pH measured at room temperature. Integer 
values measured with pH paper (values reported as X-Y reported by experimentalist as between 
integer values X and Y). Values given to hundredth of pH unit measured quantitatively with pH 
electrode. "Dry" indicates not enough solution to measure pH. 
b Appended letters denote test contained one sample seeded with: A = analcime; N = sodium 
silicate; T = tobermorite. Thickness of alteration layer on seeded Sample B is given in bold font. 
c The second group of numbers in the Test No. is the approximate mass of water added, in g. 
d The second group of numbers in the Test No. is the approximate % relative humidity at 200C. 

ANL-EBS-MD-000016 REV 02 C-8 October 2004 
Table C-3. Test Matrix and Layer Thickness on the Test Specimen for VHTs with SRL 131 Glass 
Layer thickness (m) 
Test No. 
Temperature 
(C) 
Time 
(days) 
Water 
(g) pHa Sample A Sample B 
Standard VHT 
131-VHT(150)-1 150 28 0.1495 8 11  1 10  1 
131-VHT(150)-2 150 56 0.1490 10 17  1 18  1 
131-VHT(150)-3 150 91 0.1540 10 20  1 23  1 
131-VHT(150)-4 150 182 0.1501 9 29  1 30  1 
131-VHT(150)-5 150 241 0.1475 9 43 50 
Undersaturated VHTd 
131-48RH-1 200 182 0.0765 7 4.5  0.3 0 
131-48RH-2d 200 90 0.0764 7 0.82  0.16 not measured 
131-48RH-3d 200 21 0.0770 8 0 0 
131-80RH-1d 200 12.7 0.1224 7 15  3 15  1 
131-80RH-2d 200 20.7 0.1224 dry not measured not measured 
131-80RH-3 200 31 0.1218 7 56  5 55  5 
131-80RH-4d 200 21 0.1270 7 98  6 91  2 
131-90RH-1d 200 21 0.1404 7 190  8 186  14 
Excess Water VHTc 
131-0.5mL-1d 200 21 0.4999 10.20 32  1 30  5 
131-1mL-1d 200 21 1.0032 9.65 26  3 26  2 
131-1.5mL-1d 200 21 1.5028 12 28  3 21  8 
131-1.5mL-2 200 5.7 1.4984 12 10  2 27  1 
131-1.5mL-3 200 2.7 1.4982 12 5.6  1 5.7  0.5 
131-1.5mL-4d 200 31 1.5000 10.14 35  2 35  3 
131-4mL-1d 200 21 3.9950 10.23 20  1 26  2 
131-7.5mL-1d 200 21 7.5245 10 45  5 41  2 
131-7.5mL-2 200 2.7 7.4912 9 8.2  0.8 8.7  0.5 
131-7.5mL-3 200 31 7.5143 9.94 28  6 48  5 
131-7.5mL-4d 200 21 7.5015 9 17  1 18  1 
131-7.5mL-5 200 48 7.5284 10 56  13 66  4 
131-7.5mL-6 200 87 7.5229 10.11 130  10 126  5 
131-7.5-901 90 116 7.4992 9 7.7  1.8 18  12 
131-7.5-902 90 399 7.4990 9 8.0  0.7 14  2 
131-7.5-1251 125 116 7.4817 10 29 1 34  2 
131-7.5-1252 125 399 7.5451 10-11 34  19 46  12 
131-7.5-1501 150 116 7.5321 9-10 36  10 29  12 
131-7.5-1502 150 399 7.4609 10-11 27  7 33  3 
Standard VHTs With and Without Seeded Samplesb 
131-1 200 12.0 0.2533 12 41  1 not measured 
131-1K 200 2.7 0.2546 10 11  1 9.5  0.3 
131-1A 200 0.9 0.2502 10 4.4  0.5 5.4  0.9 
131-1N 200 2.7 0.2546 11 not measured 30  5 
131-1T 200 1.0 0.2510 9 18  1 31  2 
131-1A 200 2.7 0.2530 9 15  1 11  1 
131-2 200 3.0 0.2522 dry not measured not measured 

ANL-EBS-MD-000016 REV 02 C-9 October 2004 
Table C-3. Test Matrix and Layer Thickness on the Test Specimen for VHTs with SRL 131 Glass 
(Continued) 
Layer thickness (m) 
Test No. 
Temperature 
(C) 
Time 
(days) 
Water 
(g) pHa Sample A Sample B 
131-2A 200 5.8 0.2535 10 28  1 26  2 
131-2N 200 5.7 0.2518 10 32  3 26  1 
131-2T 200 2.8 0.2518 10 13  1 14  1 
131-3 200 5.9 0.2516 10 24  1 22  1 
131-3N 200 0.7 0.2500 11 not measured 12  2 
131-4 200 3.0 0.2516 10 13  1 14  1 
1312-4N 200 13.8 0.2495 10 69  5 60  6 
1312-5 200 1.0 0.2484 dry not measured not measured 
1312-5N 200 31 0.2499 dry not measured not measured 
131-6 200 1.0 0.2500 10 5.5  0.3 4.4  0.3 
131-7 200 12.8 0.2500 10 46  4 not measured 
131-8 200 0.3 0.2527 dry not measured not measured 
131-9 200 28 0.2567 7 not measured not measured 
131-10 200 1.9 0.2529 10 5.2  0.6 6.1  0.3 
131-11 200 28 0.2529 12 not measured not measured 
131-12 200 0.2 0.2492 7 1.4  0.2 not measured 
131-13 200 0.3 0.2504 10 3.5  0.3 2.3  0.2 
1312-14 200 31 0.2502 12 273  14 310  13 
131-14-1 200 21 0.1414 dry not measured not measured 
131-14-2 200 21 0.1405 9 182  15 172  8 
131-14-3 200 21 0.1390 8 138  9 149  8 
1312-15 200 31 0.2494 12 422  10 428  8 
1312-16 200 21 0.2488 10 110  16 137  14 
131-16-1 200 21 0.1599 12 351  27 341  28 
131-17 200 40 0.2489 12 990  39 1050  20 
131-18 200 42 0.2490 12 584  13 711  225 
131-18-1 200 21 0.1804 8 not measured 349  13 
131-20-1 200 21 0.2005 7 446  22 378  11 
131-22-1 200 21 0.2200 8 completely reacted completely reacted 
131-24-1 200 210.8 0.2414 8 completely reacted completely reacted 
Source: DTN: MO0306ANLGVH01.526 [DIRS 164331], Table 1. 
NOTE: a pH of solution in bottom of test vessel at end of test; pH measured at room temperature. Integer values 
measured with pH paper (values reported as X-Y reported by experimentalist as between integer values 
X and Y). "Dry" indicates not enough solution to measure pH. 
b Appended letters denote test contained one sample seeded with: A = analcime; K = kaolin clay; 
N = sodium silicate; T = tobermorite; Thickness of alteration layer on seeded Sample B is shown in bold. 
c The second group of numbers in the Test No. is the approximate mass of water added, in g. 
d The second group of numbers in the Test No. is the approximate % relative humidity at 200C. 

ANL-EBS-MD-000016 REV 02 C-10 October 2004 
Table C-4. Test Matrix and Layer Thickness on the Test Specimen for VHTs with SRL 165S Glass 
Layer thickness (m) 
Test No. 
Temperature 
(C) 
Time 
(days) Water (g) pHa Sample A Sample B 
165S-VHT(90)-2 90 265 0.1079 7 0 0 
165S-VHT(90)-3 90 511 0.1135 7 not measured not measured 
165S-VHT(90)-4 90 959 0.1120 10 8.0  1.4 not measured 
165S-VHT(90)-5 90 1,237 0.1103 6 0 0 
165S-VHT(90)-6 90 1,237 0.1118 6 0 0 
165S-VHT(90)-7 90 1,237 0.1079 7 0 0 
165S-VHT(125)-2 125 91 0.1292 7 2.2  0.3 5.1  0.7 
165S-VHT(125)-3 125 265 0.1305 8 3.8  1.6 7.4  0.8 
165S-VHT(125)-4 125 511 0.1312 9 9.0  1.4 23  2 
165S-VHT(125)-5 125 959 0.1305 10 78  8 20 
165S-VHT(125)-6 125 1,237 0.1305 7 71  19 45  11 
165S-VHT(125)-7 125 1,237 0.1314 9 111  10 85  23 
165S-VHT(200)-2 200 6.8 0.2507 11 21  2 23  0.9 
165S-VHT(200)-4 200 13.0 0.2530 dry not measured not measured 
165S-VHT(200)-5 200 16.8 0.2537 12 69  4 95  27 
165S-VHT(200)-6 200 21 0.2508 12 125  15 148  8 
165S-VHT(200)-7 200 35 0.2505 10 46  7 57  4 
165S-VHT(200)-8 200 5.0 0.2486 11 20  1 23  3 
165S-VHT(200)-9 200 26 0.2499 12 not measured not measured 
165S-VHT(200)-10 200 1.9 0.2494 8 3.0  1.0 1.7  0.4 
Source: DTN: MO0306ANLGVH01.526 [DIRS 164331], Table 1. 
NOTE: a pH of solution in bottom of test vessel at end of test; pH measured at room temperature. Integer 
values measured with pH paper. "Dry" indicates not enough solution to measure pH. 

ANL-EBS-MD-000016 REV 02 C-11 October 2004 
Table C-5. Test Results Plotted in Figure 6-5 
Thickness (m) 
Test Number 
Duration 
(days) 
Mass Water 
(g) Sample A Sample B 
131-48RH-2 90 0.0764 0.82 
131-80RH-3 31 0.1218 56 55 
131-80RH-4 21 0.1270 98 91 
131-90RH-1 21 0.1404 190 186 
131-0.5mL-1 21 0.4999 32 30 
131-1mL-1 21 1.0032 26 26 
131-1.5mL-1 21 1.5028 28 21 
131-1.5mL-4 31 1.5000 35 35 
131-4mL-1 21 3.9950 20 26 
131-7.5mL-1 21 7.5245 45 41 
131-7.5mL-3 31 7.5143 28 47 
131-7.5mL4 21 7.5015 17 18 
131-7.5mL-6 21 7.5229 130 126 
131-14-2 21 0.1405 182 172 
131-14-3 21 0.1390 138 149 
131-15 31 0.2494 422 428 
1312-16 21 0.2488 110 137 
131-16-1 21 0.1599 351 341 
131-18-1 21 0.1804 349 
131-20-1 21 0.2005 446 378 
131-22-1 21 0.2200 750a 750a 
131-24-1 21 0.2414 750a 750a 
131-7.5mL-4 21 7.5015 17 18 
131-7.5mL-6 87 7.5229 130 126 
Source: DTN: MO0306ANLGVH01.526 [DIRS 164331]. 
NOTE: a Sample was completely reacted. 

ANL-EBS-MD-000016 REV 02 C-12 October 2004 
Table C-6. Test Results Plotted in Figure 6-6a 
Test Number 
Duration 
(days) 
Thickness 
(m) Test Number 
Duration 
(days) 
Thickness 
(m) 
Tests with SRL 51S Glass at 125C 
VHT(125)-1b 55.8 3.2 VHT(125)-6b 245 14 
VHT(125)-2b 90.8 8.8 VHT(125)-7b 1,326 33 
VHT(125)-3b 182 15 VHT(125)-8a 591 43 
VHT(125)-4b 414 19 VHT(125)-9a 591 18 
VHT(125)-5b 832 41 VHT(125)-10b 1,039 29 
Tests with SRL 51S Glass at 150C 
VHT(150)-1a 28 0 VHT(150)-4a 182 41 
VHT(150)-2a 56 0.93 VHT(150)-6a 281 50 
VHT(150)-3b 91 21 VHT(150)-7b 433 51 
Tests with SRL 51S Glass at 175C 
VHT(175)-1a 17.8 6.0 VHT(175)-5b 102 59 
VHT(175)-2b 28 1.9 VHT(175)-6a 151 84 
VHT(175)-3b 41 11 VHT(175)-7b 196 223 
VHT(175)-4b 61 22 
Tests with SRL 51S Glass at 200C 
VHT(200)-1b 2.8 4.4 VHT(200)-7a 35 79 
VHT(200)-2a 6.8 4.7 VHT(200)-8b 28 89 
VHT(200)-3a 9.8 12 VHT(200)-9a 45 204 
VHT(200)-4b 13.9 37 VHT(200)-10b 57 357 
VHT(200)-5a 16.9 27 VHT(200)-11b 70 514 
VHT(200)-6a 21 66 VHT(200)-12b 87 528 
Source: DTN: MO0306ANLGVH01.526 [DIRS 164331]. 
NOTE: a Thickness for Sample A plotted. 
b Thickness for Sample B plotted. 

ANL-EBS-MD-000016 REV 02 C-13 October 2004 
Table C-7. Test Results Plotted in Figure 6-6b 
Test Number 
Duration 
(days) 
Thickness 
(m) Test Number 
Duration 
(days) 
Thickness 
(m) 
Tests with SRL 165 Glass at 125C 
165S-VHT(125)-2 91 5.1 165S-VHT(125)-5 959 78 
165S-VHT(125)-3 265 7.4 165S-VHT(125)-6 1,237 71 
165S-VHT(125)-4 511 23 165S-VHT(125)-7 1,237 111 
Tests with SRL 131 Glass at 150C 
131-VHT(150)-1 28 11 131-VHT(150)-4 182 30 
131-VHT(150)-2 56 18 131-VHT(150)-5 241 50 
131-VHT(150)-3 91 23 
Tests with SRL 165 Glass at 200C 
165S-VHT(200)-2 6.8 23 165S-VHT(200)-8 5.0 23 
165S-VHT(200)-5 16.8 95 165S-VHT(200)-10 1.9 3.0 
165S-VHT(200)-6 21 148 
Tests with SRL 131 Glass at 200C 
131-1 12.0 41 1312-15 31 428 
131-3 5.9 24 1312-16 21 137 
131-4 3.0 14 131-17 40 1,050 
131-7 12.8 46 131-18 42 711 
1312-14 31 310 
Source: DTN: MO0306ANLGVH01.526 [DIRS 164331]. 

ANL-EBS-MD-000016 REV 02 C-14 October 2004 
INTENTIONALLY LEFT BLANK 

ANL-EBS-MD-000016 REV 02 D-1 October 2004 
APPENDIX D 
HIGH-LEVEL RADIOACTIVE WASTE GLASS ALTERATION LAYER MODEL 

ANL-EBS-MD-000016 REV 02 D-2 October 2004 
INTENTIONALLY LEFT BLANK 

ANL-EBS-MD-000016 REV 02 D-3 October 2004 
D. HIGH-LEVEL RADIOACTIVE WASTE GLASS ALTERATION LAYER MODEL 
The degradation of glass contacted by water (by immersion or exposure to dripping water or 
humid air at relative humidities = 44%) will result in transformation of glass into an alteration 
layer consisting of fine-grained clays (Biwer et al. 1990 [DIRS 164408]; Bates et al. 1991 
[DIRS 164407]; Ebert and Bates 1995 [DIRS 164411]; Gong et al. 1998 [DIRS 158976]) and 
other alteration products such as ferrihydrite (Grambow 1984 [DIRS 118987]. Under VHT 
conditions, the small volume of solution condensed on the glass surface is saturated with respect 
to many mineral phases after only a little glass has reacted. Continued glass alteration results in 
a nearly isovolumetric replacement of glass with clay, as illustrated by the vapor-hydrated glass 
shown in Figure 6-4. The alteration layer overlays the remaining unreacted glass and is overlain 
by discrete precipitated phases (secondary phases). Precipitated phases are usually observed on 
the outer surface of the alteration layer, which indicates nucleation occurs preferentially at the 
outer surface of the alteration layer. The reaction between the glass and water proceeds as water 
diffuses into the glass and alteration and diffusion are mediated by the presence of water. The 
actual processes by which the glass is altered in the presence of water vapor or a thin layer of 
water are largely uncertain. However, because the structure is similar to that seen in glasses 
altered in the presence of liquid water, similar mechanisms are likely operating. 
In borosilicate glasses, it appears that, at least at the elevated temperatures of the VHT, alteration 
and diffusion happen at the same time or alteration much more rapidly than water can diffuse. 
An expression to calculate the diffusion coefficient, D, for the diffusion of water into a 
commercial borosilicate glass as a function of temperature was determined by Tomozawa and 
Tomozawa (1989 [DIRS 164412]) from experiments conducted between 200C and 500C to be: 
D = 2.8  107 exp[52 (kJ/mol)/RT] (cm2/s) (Eq. D-1) 
Extrapolating Equation D-1 to 20C and 100C (293 and 373 K), the diffusion coefficients are 
calculated to be 1.5  1016 and 1.5  1014 cm2/s, respectively. These low values indicate glass 
is a nonporous material. Molecular water has not been detected in analyses of reacted glasses 
(Aines et al. 1987 [DIRS 104318]). 
Diffusion of water into glass is complicated by the fact that water is consumed in reactions with 
alkali metal (M), boron, and silica bonds as: 
glass=Si-OM + H2O . glass=Si-OH + M+OH (Eq. D-2a) 
glass=Si-OB(OH)2 + H2O . glass=Si-OH + B(OH)3 (Eq. D-2b) 
glass=Si-O-Si=glass + H2O . glass=Si-OH + HO-Si=glass (Eq. D-2c) 
All three reactions are reversible, and reaction in Equation D-2c provides a means for water to 
penetrate into the glass. Alteration of the glass continues at the layer-glass interface while the 
phase assemblage in the layer changes in response to the changes in the solution chemistry. 
Gel layers have not been detected at the glass surface beneath the alteration layer (Ebert and 
Bates 1995 [DIRS 164411]). Instead, elements that are released from the glass enter solution or 

ANL-EBS-MD-000016 REV 02 D-4 October 2004 
are sequestered into the clay to form the alteration layer, depending on the controlling solubility 
limits. Secondary alteration phases often form on the surface of the original alteration layer, as 
shown in Figure 6-4. In an open system, particularly in flowing or dripping water, solutes are 
carried away from the glass, thereby changing the chemistry and, ultimately, the phase 
assemblage that forms on the glass surface. In the model presented here, the alteration layer is 
modeled to remain in the canister and replace the degraded glass isovolumetrically. 
Equations are derived to calculate the volume of pore water in the alteration layer and to 
calculate the average diffusion length for radionuclides leaving the glass. Both are calculated 
from the mass of glass that has altered at the time of interest. 
D.1 ALTERATION LAYER VOLUME 
If S Mt is the total mass of glass that has degraded up to time, t, (Equation 53) and .G is the 
density of the glass, then the volume of glass that has degraded, VG, is calculated as: 
VG = S Mt / .G (Eq. D-3a) 
Degradation of this volume of glass generates an equal volume of clay as the alteration layer, VR, 
which can be expressed as: 
VR = S Mt / .G (Eq. D-3b) 
A typical HLW glass density of 2,700 kg/m3 gives: 
VR (in m3) = 3.7  104  S Mt (in kg) (Eq. D-3c) 
D.2 ALTERATION LAYER POROSITY AND PORE WATER VOLUME 
The alteration layer is composed of a dense matrix of coarse-grained and fine-grained clay 
crystals, usually smectite clays (Biwer et al. 1990 [DIRS 164408]; Ebert and Bates 1995 
[DIRS 164411]; Gong et al. 1998 [DIRS 158976]). What is referred to as pore water here 
includes both the interlayer water in the clay sheet structures and the water between crystals 
(nonstructural water). Both the structural and nonstructural water will affect the diffusion of 
cations released from the glass, which can be absorbed in the clay sheet structure to form 
interlayer complexes or sorbed on the edges of the clay crystals. All of the pore water in the 
alteration layer is included in the alteration layer volume model. 
The amount of water in the alteration layers formed on vapor-hydrated SRL 131 glass samples 
was measured to be up to 7 mass % (Aines et al. 1987 [DIRS 104318]). A value of 7 mass % is 
used to represent the pore water contents of alteration layers formed on all HLW glasses exposed 
to water or humid air (at RH = 44%). The total volume of water in the alteration layer is simply 
the product of the alteration layer volume and pore water content. 

ANL-EBS-MD-000016 REV 02 D-5 October 2004 
The porosity of the alteration layer is: 
f = XW  .R / .W (Eq. D-4) 
where 
f = porosity of the alteration layer 
XW = mass fraction of water in the alteration layer 
.R = density of the alteration layer 
.W = density of the pore water. 
The bulk density of the alteration layer is not known specifically, but can be expressed in terms 
of the densities of the clay minerals and the amount of pore water. Typical values of dehydrated 
clay minerals are 2,630 kg/m3 for kaolinite, 2,550 kg/m3 for halloysites, and 2,600 kg/m3 for 
dickite and nacrite (Deer et al. 1966 [DIRS 102773], p. 258). Curti and Smith 
(1991 [DIRS 164410]) used a value of 2,760 kg/m3 for the density of bentonite clay. These are 
sufficiently similar to the densities of HLW glasses (2,600 to 2,800 kg/m3; Section 6.5.4) that the 
grain densities of the clay crystals and the glass density are considered equal. A density 
of 2,700 kg/m3 is used for both the unreacted glass and the clay crystals. The bulk density of the 
alteration layer differs from that of the glass due to the presence of pore water. The bulk density 
of the alteration layer, .R, can be expressed in terms of the densities of the clay crystals, .C, and 
pore water, .W, at 100% saturation of pore water as given in Equation D-5: 
.R = .W  f + (1-f)  .C (Eq. D-5) 
which is combined with Equation D-4 and expressed in terms of the porosity as: 
f = {1 + ( .W / .C)  [(1/XW) 1]}1 (Eq. D-6) 
Solving Equation D-6 with the values .W = 1,000 kg/m3, .C = 2,700 kg/m3, and XW = 0.07 gives 
f = 0.17. The porosity of the alteration layer is 17%. A porosity of 17% is consistent with the 
mass %-soluble elements that are not incorporated into the clay alteration layer when glass 
degrades. For example, Table D-1 gives the elemental mass % of soluble elements in 10 glasses 
used to determine model parameter values. The average total mass % of these soluble elements 
for the 10 glasses is 15.78%. 

ANL-EBS-MD-000016 REV 02 D-6 October 2004 
Table D-1. Soluble Elements in Glasses, in Elemental Mass % 
Glass B K Li Na Total 
SRL 202Ga 3.21 2.74 1.60 11.36 18.91 
SRL 51Sb 2.30 1.16 2.11 7.11 12.68 
SRL 202Ub 2.48 3.09 1.97 6.61 14.47 
SRL 165Ub 2.10 0 1.94 8.04 12.08 
SRL 131Ub 3.00 3.22 1.40 8.95 16.57 
WV ref 6b 4.00 4.17 1.73 5.93 15.83 
Hanford-Db 2.17 0.72 1.40 11.7 15.99 
Hanford-Lb 2.75 2.58 0 14.8 20.13 
LD6-5412b 1.66 1.14 0 15.0 17.80 
PNL 76-68b 2.79 0 0 10.5 13.29 
Average 2.65 1.88 1.22 10.00 15.78 
Sources: a DTN: MO0306ANLGIM01.525 [DIRS 164329], Table 1. 
b DTN: MO0308ANLGPC01.528 [DIRS 164790], Table 1. 
The volume of pore water in the alteration layer VW can be calculated as the product of the 
porosity (f) and the volume of the alteration layer VR as: 
Vw = VR  f (Eq. D-7) 
Substituting Equation D-3b into Equation D-7 for VR gives: 
Vw = (S Mt / .G)  f (Eq. D-8) 
Substituting .G = 2,700 kg/m3 and f = 17% into Equation D-8 gives the relationship: 
Vw (in m3) = 6.3  10-5  S Mt (in kg) (Eq. D-9) 
Equation D-9 can be used to calculate the volume of water in the alteration layer as a function of 
the total mass of glass that has degraded. 
D.3 ALTERATION LAYER THICKNESS 
Radionuclides that are freed from the glass matrix as the glass degrades must diffuse through the 
alteration layer to become available for transport away from a breached canister. An average 
alteration layer thickness can be determined by the geometry of the canistered glass waste form. 
The geometry shown in Figure D-1 is used to calculate the volume of alteration layer. In this 
geometry, the inner diameter of the glass pour canister is the same as the original outer surface of 
the glass. As glass is replaced by the alteration layer; the outer surface of the alteration layer 
remains the same as the inner diameter of the pour canister. The inner diameter of the alteration 
layer is determined from the calculated volume of the alteration layer. The pour canister does 
not, in this model, present a diffusion barrier to the movement of water or dissolved constituents 
As discussed in Section 6.5.4, it is expected that about two-thirds of the HLW glass will be in 
canisters that are 4.5-m long, and about one-third in canisters 3.0-m long. The weighted average 
of the overall canister heights is 4.0 m [(4.5  2 + 3)/3]. Typically, the producer will attempt to 
put as much glass in the canister as possible. Over filling the canister must also be avoided. The 

ANL-EBS-MD-000016 REV 02 D-7 October 2004 
typical canister has a neck that is about 0.2 m high (DOE 1992 [DIRS 102812]), 
which means that the average canister could only be filled to just over 3.8 m [((4.5  0.2)  2 + 
(3.0  0.2))/3]. This does not account for the bottom thickness and stress relief bow. To 
accommodate these remaining uncertainties, the average between the two maximum fill 
heights (3.9 m) is used hereinafter to give conservative estimates of the volume and, hence, the 
thickness of the rind and water contained therein. The thickness of the alteration layer is 
determined from the initial glass volume and the volume of glass that has not reacted. These are 
represented by concentric cylinders with radii, ro and ri (see Figure D-1). The initial radius of the 
glass is 0.30 m (Section 6.5.4) and the initial glass volume is: 
Vinitial = p  ro
2  Lo (Eq. D-10) 
where 
Vinitial = initial volume of glass (m3) 
ro = initial radius of glass (0.30 m) 
Lo = length of glass (3.9 m) 
The volume of unreacted glass is: 
Vinner = p  ri
2  Lo (Eq. D-11) 
where 
Vinner = volume of the inner cylinder (m3) 
ri = outer radius of the inner cylinder 
Lo = length of the glass (3.9 m) 
The bulk volume of the alteration layer, VR, is equal to Vinitial  Vinner and can be expressed as: 
VR = p  Lo  (ro
2  ri
2) (Eq. D-12) 
The ends of the glass provide only about 7% of the initial surface area and their contribution 
decreases as the glass is altered. Equation D-9 can be solved for ri: 
ri = [ro
2  VR/(p  Lo)]1/2 (Eq. D-13) 
The thickness of the alteration layer is TR = ro  ri. Substituting Equation D-13 for ri gives: 
TR = ro  ri = ro  [ro
2  VR/(p  Lo)]1/2 (Eq. D-14) 
Substituting the values ro = 0.30 m and Lo = 3.9 m into Equation D-14 gives: 
TR (in meters) = 0.30  [0.090  (8.2  102  VR)]1/2 (Eq. D-15) 
Substituting Equation D-3b in Equation D-15 gives: 
TR = (in meters) = 0.30  [0.090  (8.2  102  (S Mt / .G)]1/2 (Eq. D-16) 

ANL-EBS-MD-000016 REV 02 D-8 October 2004 
Equation D-16 is the average alteration layer thickness in terms of the mass of glass (in kg) 
altered. Substituting .G = 2700 kg/m3 for the density of a typical HLW glass gives the alteration 
layer thickness: 
TR (in meters) = ro  ri = 0.30  [0.090  (3.0  105)  S Mt]1/2 (Eq. D-17) 
Equation D-17 gives the relationship between the average alteration layer thickness (in meters) 
and the mass of altered glass (in kg) that is calculated with the glass alteration rate equation 
developed in this report. 
pour canister 
alteration rind 
glass 
average layer 
thickness = ro  ri 
ri 
ro 
Figure D-1. Schematic Drawing of Canister Cross Section Used to Calculate Alteration Layer Thickness 

ANL-EBS-MD-000016 REV 02 E-1 October 2004 
APPENDIX E 
EVALUATION OF DATA IN KNAUSS ET AL. 1990 [DIRS 101701] 

ANL-EBS-MD-000016 REV 02 E-2 October 2004 
INTENTIONALLY LEFT BLANK 

ANL-EBS-MD-000016 REV 02 E-3 October 2004 
E. EVALUATION OF DATA IN KNAUSS ET AL. 1990 [DIRS 101701] 
The analysis in this appendix was conducted to extract model parameter values from the results 
of single-pass flow-through tests conducted at various temperatures and solution pH values 
presented in: 
Knauss, K.G.; Bourcier, W.L.; McKeegan, K.D.; Merzbacher, C.I.; Nguyen, S.N.; 
Ryerson, F.J.; Smith, D.K.; Weed, H.C.; and Newton, L. 1990. "Dissolution Kinetics 
of a Simple Analogue Nuclear Waste Glass as a Function of pH, Time and 
Temperature." Scientific Basis for Nuclear Waste Management XIII, Symposium held 
November 27-30, 1989, Boston, Massachusetts. Oversby, V.M. and Brown, P.W., 
eds. 176, 371-381. Pittsburgh, Pennsylvania: Materials Research Society. 
TIC: 203658. 
In the cited publication, the authors extracted parameter values based on the release of Si. 
Separate parameter values for the pH dependence were extracted for each temperature. In the 
following analysis, a single set of model parameter values are extracted for acidic and alkaline 
solutions. 
The rate expression for the forward rate is given in Equation 13. The logarithm of Equation 13 is 
used to determine parameters from test results: 
log10(rate) = log10(k0) + .  pH + log10(exp(Ea/RT)) (Eq. E-1) 
where log10(rate) is the measured rate. Values of . were determined through regression of 
log10(rate) and pH data obtained from experiments performed at 40C and 70C. Lines having 
the slopes for acidic and alkaline solutions determined from those plots were then fit to the 
results at 25C, 50C, and 70C to determine the values of the sum of the terms log10(k0) + 
log10(exp(-Ea/RT)) at each temperature. The rates were then calculated at pH 0 and at pH 14 at 
each temperature. These rates were used in a plot of ln(rate) vs. 1/RT for acidic and alkaline 
solutions. From Equation E-1, the slopes of those plots give the values of -Ea. 
E.1 EXTRACTION OF DATA FROM KNAUSS ET AL. (1990 [DIRS 101701]) 
FIGURE 2 
Figure 2 from the report by Knauss et al. (1990 [DIRS 101701]) is reproduced in Figure E-1. 
The values of pH and log(rate) for Si data at the three temperatures were read from enlarged 
photocopies of the graphs in this figure. An architects scale (with 50 divisions per inch) was 
used measure the distance of each data point on the pH and log(rate)scales. The relationship 
between distance and scale was determined by measuring distances between tick marks on the 
plots. The extracted data are shown in Table E-1. 

ANL-EBS-MD-000016 REV 02 E-4 October 2004 
NOTE: The x-axis gives the solution pH and the y-axis gives the dissolution rate, g/(m2d). 
Figure E-1. Reproduction of Figure 2 from Knauss et al. (1990 DIRS 101701]) 

ANL-EBS-MD-000016 REV 02 E-5 October 2004 
Table E-1. Values of pH and log10(Rate) 
Acidic Solutions Alkaline Solutions 
pH 70C 50C 25C pH 70C 50C 25C 
2.1   -1.54 6.8 -2.65   
2.3 -0.51   7.5   -4.25 
2.4  -1.17  7.9 -1.93   
3.3  -1.56 -2.36 8.0  -2.85  
3.4 -1.11   8.7   -3.71 
4.1   -3.22 8.8 -1.64 -2.42  
4.5  -2.38  9.6 -1.35   
4.7 -2.01   9.7   -3.18 
5.3  -3.08  9.8  -1.95  
5.6 -2.67   10.8 -0.78   
6.4  -3.79  11.2  -1.19  
6.8 -2.65   11.7 -0.37   
12.1   -1.74 
12.2  -0.7  
12.9   -1.62 
NOTE: Based on NR(Si). Extracted from Knauss et al. 1990 [DIRS 101701], 
Figure 2 (Figure E-1 in this document). 
E.2 DETERMINATION OF PH DEPENDENCE (.) 
The data for tests at 50C and 70C were regressed to determine the pH dependence. Results of 
tests in acidic and alkaline solutions were regressed separately. These are shown in Figure E-2. 
Results for tests at 50C are included in the plot to show they follow the same pH dependence, 
but they were not used in the regression. The pH dependence for acid is .= 0.698 and the pH 
dependence for bases is .= 0.486. 
Figure E-2. Regression of Data (Table V-1) at 50C and 70C 

ANL-EBS-MD-000016 REV 02 E-6 October 2004 
The rates measured by Knauss et al. (1990 [DIRS 101701]) at each temperature were fit with 
lines having slopes of 0.698 for acids and slopes 0.486 for bases. The general equation of the 
line was: 
log10(rate) = A + .  pH. (Eq. E-2) 
The best value of A was determined by minimizing the residuals between the calculated and 
measured values of log(rate) at each temperature for both acids and bases. This was done in a 
Microsoft Excel spreadsheet. The results are shown in Table E-2. The equations of the fit lines 
are as follows: 
Acidic Solutions 
70C: log(rate) = 1.217  0.698  pH 
50C: log(rate) = 0.6613  0.698  pH 
25C: log(rate) = 0.1630  0.698  pH 
Alkaline Solutions 
70C: log(rate) = 5.9014 + 0.486  pH 
50C: log(rate) = 6.682 + 0.486  pH 
25C: log(rate) = 7.8475 + 0.486  pH 
The fitted lines are shown with the measured rates in Figure E-3a. The pH dependencies 
determined by Knauss et al. (1990 [DIRS 101701) for each temperature are shown in 
Figure E-3b for comparison (visual comparison of Figures E-3a and b confirms the rate and pH 
values extracted from the report by Knauss et al. (1990 [DIRS 101701]) Figure 2 and shown in 
Table E-1.) The pH dependencies are . = 0.698 for the acidic leg and . = 0.486 for the alkaline 
leg. These are used in Section 7.4.1. 
Figure E-3. Regression of Data provided by Knauss et al. (1990 [DIRS 101701]) (a) This Analysis and (b) 
as Presented in Figure 3 in a Report by Knauss et al. (1990 [DIRS 101701]) 

ANL-EBS-MD-000016 REV 02 E-7 October 2004 
Table E-2. Regression of Lines with Constant Slopes to Data 
Calculated log10(Rate) Residual 
e e 
pH 
Measured 
log(Rate) 0 0.01 0.01 0 0.01 0.01 
Acids at 70C log10(Rate) = 1.217  0.698  pH + e 
2.3 0.51 0.3884 0.3784 0.3984 0.1216 0.1316 0.1116 
3.4 1.11 1.1562 1.1462 1.1662 0.0462 0.0362 0.0562 
4.7 2.01 2.0636 2.0536 2.0736 0.0536 0.0436 0.0636 
5.6 2.67 2.6918 2.6818 2.7018 0.0218 0.0118 0.0318 
Sum of Residuals: 1.5543E15 0.04 0.04 
Acids at 50C log10(Rate) = 0.6613  0.698  pH + e 
2.4 1.17 1.0139 1.0039 1.0239 0.1561 0.1661 0.1461 
3.3 1.56 1.6421 1.6321 1.6521 0.0821 0.0721 0.0921 
4.5 2.38 2.4797 2.4697 2.4897 0.0997 0.0897 0.1097 
5.3 3.08 3.0381 3.0281 3.0481 0.0419 0.0519 0.0319 
6.4 3.79 3.8059 3.7959 3.8159 0.0159 0.0059 0.0259 
Sum of Residuals: 0.0003 0.0503 0.0497 
Acids at 25C log10(Rate) = 0.163  0.698  pH + e 
2.1 1.54 1.6288 1.6188 1.6388 0.0888 0.0788 0.0988 
3.3 2.36 2.4664 2.4564 2.4764 0.1064 0.0964 0.1164 
4.1 3.22 3.0248 3.0148 v3.0348 0.1952 0.2052 0.1852 
Sum of Residuals: 8.8818E16 0.03 0.03 
Bases at 70C log10(Rate) = 5.9014 + 0.486  pH + e 
6.8 2.65 2.5966 2.5866 2.6066 0.0534 0.0634 0.0434 
7.9 1.93 2.062 2.052 2.072 0.132 0.122 0.142 
8.8 1.64 1.6246 1.6146 1.6346 0.0154 0.0254 0.0054 
9.6 1.35 1.2358 1.2258 1.2458 0.1142 0.1242 0.1042 
10.8 0.78 0.6526 0.6426 0.6626 0.1274 0.1374 0.1174 
11.7 0.037 0.2152 0.2052 0.2252 0.1782 0.1682 0.1882 
Sum of Residuals: 0.0002 0.0602 0.0598 
Bases at 50C log10(Rate) = 6.682 + 0.486  pH + e 
8 2.85 2.794 2.784 2.804 0.056 0.066 0.046 
8.8 2.42 2.4052 2.3952 2.4152 0.0148 0.0248 0.0048 
9.8 1.95 1.9192 1.9092 1.9292 0.0308 0.0408 0.0208 
11.2 1.19 1.2388 1.2288 1.2488 0.0488 0.0388 0.0588 
12.2 0.7 0.7528 0.7428 0.7628 0.0528 0.0428 0.0628 
Sum of Residuals: 2.22E15 0.05 0.05 
Bases at 25C log10(Rate) = 7.8475 + 0.486  pH + e 
7.5 4.25 4.2025 4.1925 4.2125 0.0475 0.0575 0.0375 
8.7 3.71 3.6193 3.6093 3.6293 0.0907 0.1007 0.0807 
9.7 3.18 3.1333 3.1233 3.1433 0.0467 0.0567 0.0367 
12.1 1.74 1.9669 1.9569 1.9769 0.2269 0.2169 0.2369 
12.9 1.62 1.5781 1.5681 1.5881 0.0419 0.0519 0.0319 
Sum of Residuals: 0.0001 0.0499 0.0501 
Source: DTN: MO0307ANLGAMR3.016. 

ANL-EBS-MD-000016 REV 02 E-8 October 2004 
E.3 DETERMINATION OF TEMPERATURE DEPENDENCE (Ea) 
From Table V-2, the equations for log10(rate) were used to calculate the values of log10(rate) 
were calculated at pH 0 and at pH 14. These were then converted to ln(rate) and plotted against 
1/RT to determine the activation energy (R = 0.008314 kJ/mol  K). The data are tabulated in 
Table E-3 and plotted in Figure E-4. The equations from linear regression of the acidic and 
alkaline data are: 
Acid: ln(rate) = 23.9  60.1/(RT) 
Base: ln(rate) = 31.8  84.7/(RT) 
The activation energies are Ea = 60.1 kJ/mol for acids and Ea = 84.7 kJ/mol for bases. The 
values of . and Ea rounded to two significant figures are reported in Table 7-3. 
Table E-3. Data for Arrhenius plots 
ln(Rate) [g/(m2d)] Temperature 
(C) 1/RT (mol/kJ) Acids Bases 
70 0.35067 2.8022 2.0783 
50 0.37238 1.5226 0.28092 
25 0.40362 0.37532 2.4027 
Figure E-4. Arrhenius Plot of Rates Calculated at pH 0 and pH 14 (Table V-3) 

ANL-EBS-MD-000016 REV 02 F-1 October 2004 
APPENDIX F 
DATA QUALIFICATION REPORT FOR DTN: MO0408ANLGNN01.527 

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ANL-EBS-MD-000016 REV 02 F-3 October 2004 
F. DATA QUALIFICATION REPORT FOR DTN: MO0408ANLGNN01.527 
F.1. PURPOSE 
The purpose of this Data Qualification Report is to qualify the data from 
DTN: MO0408ANLGNN01.527 [DIRS 171574], for use as direct input to Defense HLW Glass 
Degradation Model, ANL-EBS-MD-000016, Rev. 2. The data in the DTN are unqualified 
because some of the data were acquired prior to May 1989, when DOE established the Quality 
Assurance Requirements and Description (QARD) to meet 10 CFR Part 60 [DIRS 103540], 
Subpart G, and are required to be qualified in accordance with AP-SIII.2Q. 
F.2 QUALIFICATION METHOD 
The data from DTN: MO0408ANLGNN01.527 [DIRS 171574] are qualified in accordance with 
AP-SIII.2Q, Qualification of Unqualified Data. The qualification process used for these data 
involves the method of Corroborating Data (AP-SIII.2Q, Attachment 3). This qualification 
process is designed to provide the desired level of confidence for the data in their intended use 
for this model report. 
This report documents the data qualification task conducted in accordance with the approved 
Data Qualification Plan (Appendix G). For the Corroborating Data qualification method, 
qualification process attributes 1 through 6 and 10 (AP-SIII.2Q, Attachment 4) were used as 
appropriate. The rationale for selecting the corroborating data method was to provide confidence 
that the test results are consistent with the test results acquired under the QARD. The 
qualification criterion is that the data collected before May 1989 must be consistent with the data 
collected after May 1989. 
F.3 CORROBORATING DATA 
The data for this DTN were acquired over the period from 02/18/86 to 05/30/01. The DOE 
adopted the QARD in May of 1989 and by the definition of qualified data, data acquired or 
developed under a Quality Assurance program which meets the requirements of the QARD, the 
data acquired prior to May of 1989 are unqualified and require qualification under AP-SIII.2Q. 
The data are the results of unsaturated (drip) tests conducted to measure the degradation rates of 
SRL 165 (N2 series) and ATM-10 (N3 series) glasses contacted by dripping tuff groundwater 
(J-13 well water that had been pre-reacted with tuff at 90C) at 90C. The extent of degradation 
was monitored by release of boron into solution. This data was acquired by Argonne National 
Laboratory (ANL) under the technical direction of Lawrence Livermore National Laboratory 
(LLNL). All of this work has been done under contract to DOE (Yucca Mountain Project), 
which established the Quality Assurance program requirements. 
F.3.1 Data Acquired After May 1989 
ANL has maintained a quality assurance program throughout the period of this data acquisition. 
After May 1989, the data collection was completed under a QA program required by contract to 
DOE to meet the requirements of the QARD. All of the data were acquired using The NNWSI 
Unsaturated Test Procedure, procedure number DP-05-174, for the ANL Unsaturated Glass 

ANL-EBS-MD-000016 REV 02 F-4 October 2004 
Testing Program. This procedure, which defines the test method, was initially issued 01/15/86 
and has been revised throughout the data acquisition period. It has been produced and revised 
under ANLs QA program. Additional procedures for the operation and calibration of measuring 
and test equipment, sample preparation and other activities necessary to support the testing were 
produced and maintained under ANLs QA program. Scientific notebooks, maintained under 
ANLs QA program, were used to document the data and its acquisition. Both LLNL and DOE 
(Yucca Mountain Project) have audited ANLs QA program on a scheduled basis. The audits 
determined that ANL was satisfactorily implementing the QA requirements established by the 
DOE contract. 
The data acquired since May 1989 have been acquired under a QA program meeting the 
requirements of DOE (Yucca Mountain Project) QARD. These data are therefore qualified. 
F.3.2 Data Acquired Before May 1989 
From February 1986 to May 1989, ANLs QA program was maintained to meet contractual 
requirements set by DOE (Yucca Mountain Project) through the technical direction of LLNL. 
ANLs activities during this time period were audited by LLNL to confirm satisfactory 
implementation of the QA requirements. The data acquired during this period were acquired 
using an earlier revision of the same procedure (DP-05-174) for the ANL Unsaturated Glass 
Testing Program that was used for data acquisition after May 1989. This procedure identified 
the measuring and test equipment, and their calibration requirements, required to support the data 
acquisition under this procedure. The procedure also identified procedures for use in the 
calibration of the measuring and test equipment. This procedure and the others used to conduct 
the testing were produced and maintained under ANLs QA program at that time. The 
measuring and test equipment used in this testing was the same or equivalent to that used in data 
acquisition after May 1989. The procedure, DP-05-174, through its revision process maintained 
the same methodology and testing requirements throughout the testing period, 02/18/89 to 
05/30/01. 
F.3.3 Data Comparison 
Two data sets are qualified in this appendix. The first set, N2-9 through N2-12, was collected 
between 03/20/86 and 05/01/89. The second set, N3-9 through N3-12, was collected from 
08/24/87 to 04/03/89. These sets are qualified by comparison with later (qualified) test results 
from the same test series. The later data collection periods used the same test methods, 
procedures, equipment, and samples. 
Two data sets are used as corroboration in this appendix. The first set, The first set, N2-9 
through N2-12, was collected between 10/30/89 and 05/30/01. The second set, N3-9 through 
N3-12, was collected from 07/06/89 and 06/08/00. Results were compared for cumulative boron 
release into solution. 
When the results are plotted for the entire period of testing for each test (e.g., Figure F-1) it is 
clear that the unqualified results are consistent with the qualified results and supportive of the 
overall test objective. The qualification criterion (the data collected before May 1989 must be 
consistent with the data collected after May 1989) is met. 

ANL-EBS-MD-000016 REV 02 F-5 October 2004 
Source: Figure 6-8. 
Figure F-1. Cumulative Boron Release in Tests with (a) SRL 165 Glass and (b) ATM-10 Glass 
F.4 CONCLUSION 
Based upon the evaluation of the attributes used in the qualification process and the comparison 
of the corroborating data meeting the qualification criteria, it is concluded that the desired level 
of confidence needed for this model has been obtained and that the data is qualified for its 
intended use in this model. 
There was no data generated by this qualification report, and there are no limitations or caveats 
associated with the use of this data in the model. 

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ANL-EBS-MD-000016 REV 02 G-1 October 2004 
APPENDIX G 
DATA QUALIFICATION PLAN 

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G. DATA QUALIFICATION PLAN 

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