Waste Form Degradation Process Model Report Rev 00, ICN 01

TDR-WIS-MD-000001

July 2000

EXECUTIVE SUMMARY 
The Waste Form Degradation Process Model Report (Waste Form Degradation PMR) is one of 
nine PMRs that have the shared objective of describing the technical information that was used 
in the total system performance assessment (TSPA) conducted to evaluate the postclosure 
performance of a potential monitored geologic repository at Yucca Mountain. The TSPA-SR 
(site recommendation) will be used in the preparation of a document for a Secretarial decision on 
whether to recommend the Yucca Mountain site for development as a repository. The Waste 
Form Degradation PMR summarizes the results of investigations on the degradation of the 
radioactive spent nuclear fuel (SNF), high-level waste (HLW), dissolved radionuclides, and 
colloidal radionuclides. 
The culmination of these investigations was the construction of the Waste Form Degradation 
Model to predict the dissolved or colloidal radionuclides available for transport in the TSPA for 
SR (TSPA-SR). The Waste Form Degradation Model consists of eight major modeling/analysis 
components: (1) Radioisotope Inventory, (2) In-Package Chemistry, (3) Commercial Spent 
Nuclear Fuel (CSNF) Degradation, (4) CSNF Cladding Degradation (5) U.S. Department of 
Energy (DOE) Spent Nuclear Fuel (DSNF) Degradation, (6) HLW Degradation, (7) 
Radioisotope Dissolved Concentration (solubility), and (8) Radioisotope Colloidal 
Concentration. These eight components are generally connected sequentially starting with the 
radioisotope inventory as input and ending with projected radioisotope dissolved and colloidal 
concentration. 
As a result of further investigations and in response to extensive comments by, for example, 
internal reviews and the U.S. Nuclear Regulatory Commission (NRC) through its Issue 
Resolution Status Reports (IRSRs), these eight components of the Waste Form Degradation 
Model have evolved substantially from those used in previous analyses as described below. 
1. The Radioisotope Inventory Component developed for the TSPA-SR uses updated 
values for the inventory. The sources of information are based on internal documents 
for CSNF, reports from the National Spent Nuclear Fuel Program (NSNFP) for DSNF, 
and the Environmental Impact Statement (EIS) for HLW. An updated screening was 
conducted and resulted in 27 radionuclides identified as important (24 based on human 
dose and 3 mandated by the Groundwater Protection Requirements of the proposed 
U.S. Environmental Protection Agency [EPA] standard 40 CFR 197 [64 FR 46976]). 
2. The In-Package Chemistry Component developed for the TSPA-SR couples the 
seepage rate of water into the package and degradation of the steel, aluminum, DSNF, 
CSNF, and HLW inside the package to evaluate water chemistry parameters such as 
hydronium ion concentration, total carbonate concentration, dissolved partial pressures 
of carbon dioxide and oxygen, ionic strength, and fluoride and chloride ion 
concentrations (i.e., pH, p[CO3]T , PCO2, PO2, [I], [F], [Cl]). The analysis is performed 
using the EQ3/6 geochemical code. The sources of information for the EQ3/6 
geochemical simulations include a chemical thermodynamics database and 
information on the in-package environment. These results influence degradation of 
the CSNF cladding and matrix, HLW degradation, radionuclide solubility, and colloid

TDR-WIS-MD-000001 REV 00 ICN 01 x July 2000 
availability and stability. The degradation of the CSNF matrix and HLW, in turn, 
influence the In-Package Chemistry Component. 
3. The CSNF Matrix Degradation Component uses two linear regression equations based 
on pH, p[CO3]T, PO2, and temperature (T) to evaluate matrix degradation over time; 
one equation is applicable for pH less than or equal to 7 and the other is applicable for 
pH greater than 7. The regression variables used, pH, p[CO3]T and PO2, are coupled to 
in-package chemistry to account for uncertainty. The sources of information include 
flow through, static, batch reactor, and drip tests involving the dissolution of fresh and 
spent reactor fuels under both saturated and unsaturated conditions. 
4. The CSNF Cladding Degradation Component evaluates degradation of the cladding 
and is coupled to the CSNF Matrix Degradation and In-Package Chemistry 
components developed for the TSPA-SR. The sources of information include failure 
data from reactor operation, pool and dry storage, and transportation. To better 
evaluate the performance of the cladding, two steps of degradation are included: 
perforation and matrix exposure. Perforation mechanisms include cladding damage 
during reactor use, creep failures at high temperatures during dry storage, 
transportation, or initial disposal, mechanical failure from earthquakes, and localized 
corrosion after disposal. The process of exposing the matrix and releasing 
radionuclides is through potential unzipping of the cladding caused by expansion of 
the fuel matrix as the uranium dioxide (UO2) forms secondary minerals. 
5. The DSNF Degradation Component developed for TSPA-SR uses a constant, 
bounding degradation rate based upon experimental data for N-Reactor SNF for all the 
DSNF waste types with the exception of naval SNF. However, the radioisotope 
inventory is the weighted mass average of DSNF waste types. Naval SNF degradation 
behavior is bounded by that of the CSNF. 
6. The HLW Degradation Component developed for TSPA-SR uses bounds on 
parameters of a phenomenological model to develop a simplified (Arrhenius-type) rate 
equation of degradation that is dependent only upon pH and temperature. 
Conservative estimates of the model parameters are based upon experimental data for 
the degradation of borosilicate glass. 
7. In the Dissolved Radioisotope Concentration Component, the solubilities of important 
radionuclides (as determined by updated screening) were reevaluated. The sources of 
information include EQ3/6 simulations of in-package chemistry for three categories of 
radionuclides. Three radioisotope solubilities were abstracted as a direct function of 
in-package chemistry (Np, U, Am) and three radionuclides solubilities (Ac, Cm, Sm) 
set equal to that of Am. Four additional radioisotope solubilities were defined by 
probability distributions (Pu, Pb, Pa, Ni). All other radioisotope solubilities were set at 
bounding values. The distributions and bounding values were based on results of the 
process modeling of the in-package chemistry.

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8. For the Colloidal Radioisotope Concentration Component, the conceptualization 
directly used YMP-relevant experimental results from YMP-specific work and from 
the published literature. The conceptualization identified the availability and the 
stability of three categories of colloids: (1) existing colloids in the groundwater, (2) 
colloids generated during degradation of the waste, and (3) colloids generated during 
degradation of the disposal container. 
Based on previous sensitivity analysis, the solubility of Np in the Dissolved Radioisotope 
Concentration Component has a strong influence on human dose and thus is a principal factor of 
the repository safety strategy. 
Concurrent with model development, numerous (FEPs) have been formally developed to ensure 
that no important and/or influential FEP has been omitted in Waste Form Degradation Model. 
This formal process assigned 87 FEPs to the Waste Form Degradation PMR for consideration, 
and the vast majority are included in the Waste Form Degradation Model. This formal process 
has influenced the CSNF Cladding Degradation Component more than other components since it 
is a rather new component in comparison to others that have been under study over the past 
20 years.

1. INTRODUCTION 
To evaluate the postclosure performance of a potential monitored geologic repository at Yucca 
Mountain, a total system performance assessment (TSPA) will be conducted. A set of nine 
process model reports (PMRs), of which this document is one, is being developed to summarize 
the technical basis for each of the process models supporting the TSPA model. These reports 
cover the following areas: 
 Integrated Site Model 
 Unsaturated Zone Flow and Transport 
 Near Field Environment 
 Engineered Barrier System Degradation, Flow, and Transport 
 Waste Package Degradation 
 Waste Form Degradation 
 Saturated Zone Flow and Transport 
 Biosphere 
 Disruptive Events. 
These PMRs are supported by analysis model reports (AMRs) that contain the more detailed 
technical information to be input into each PMR and the TSPA. This technical information 
consist of data, analyses, models, software, and supporting documentation that will be used to 
defend the applicability of each process model for its intended purpose of evaluating the 
postclosure performance of the potential Yucca Mountain repository system. The methodology 
used to develop AMRs and PMRs is designed to ensure traceability of information. Its final use 
in the TSPA is intended to ensure that the data are the best available when the TSPA is 
performed. 
1.1 OBJECTIVE 
The degradation and potential release of the radioactive waste placed into the potential Yucca 
Mountain repository are dependent on numerous features1, events2, and processes3 (FEPs) of the 
disposal system. Because of the different spatial and time scales and the large number of FEPs, 
they have been grouped into several modeling systems and components for modeling and 
discussion in reports. The overall objective of the Waste Form Degradation Process Modeling 
Report (Waste Form Degradation PMR) is to summarize the technical basis of the Waste Form 
Degradation model. The degradation of the waste eventually leads to mobilization of 
radionuclides and release into other components of the engineered barrier system (EBS) in the 
TSPA. Because a small fraction of the radioisotope in the waste can be transported through the 
EBS and the natural rock barrier, the source concentrations of radionuclides evaluated by the 
Waste Form Degradation Model can influence results of the TSPA analysis when the waste 
1 An object, structure, or condition that has a potential to affect performance of the disposal system. 
2 A natural or anthropogenic phenomenon that has a potential to affect performance of the disposal system and that 
occurs during an interval that is short compared to the period of performance. 
3 A natural or anthropogenic phenomenon that has a potential to affect performance of the disposal system and that 
occurs during all or a significant part of the period of performance.

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package (WP) is breached. This TSPA analysis, in turn, is an important basis of the Site 
Recommendation Consideration Report (SRCR) and, thus, designated as TSPA-SR in this report. 
1.2 PURPOSE AND SCOPE 
Nineteen AMRs were written to document (1) various experimental results, (2) conceptual 
models and detailed numerical models, and (3) further abstraction of the experiments or 
numerical models and to define consistent model parameters pertinent to degradation of the 
waste form. The purpose and scope of the Waste Form Degradation PMR is to summarize the 
most important aspects of these 19 AMRs to provide a coherent view of the components of the 
Waste Form Degradation Model. More specifically, in order to satisfy several important 
requirements for the analysis for the TSPA-SR according to the DOE interim guidance 
(Dyer 1999) to the proposed U.S. Nuclear Regulatory Commission (NRC) regulation (proposed 
DOE 10 CFR 63.114 Interim Guidance [Dyer 1999]), Waste Form Degradation PMR purpose 
and scope are to briefly summarize: 
1. The technical basis for either including or excluding FEPs influencing the degradation, 
deterioration, and alteration of the waste form 
2. The technical basis for the models (usually the experimental foundation but 
occasionally comparison with more detailed modeling or natural analogs) used to 
evaluate FEPs thought to significantly influence the degradation of the waste form 
3. The technical basis for bounding values or probability distributions of parameters of 
the corresponding components 
4. The relationship of the FEPs to particular key technical issues (KTIs) that have been 
raised by the NRC in their IRSRs-particularly the Container Life and Source Term 
(CLST) IRSR. 
The numerical results of the Waste Form Degradation Model as implemented in the analysis for 
the TSPA-SR are not discussed here. These results will be found in documentation of the 
analysis for the TSPA-SR. Hence, the features of the waste form that are definitely considered 
barriers important to waste isolation are not identified here. Rather these identified features will 
be found in the TSPA-SR, the SRCR, and future versions of the Repository Safety Strategy 
(RSS) (CRWMS M&O 2000a). 
1.3 QUALITY ASSURANCE 
The Quality Assurance (QA) program applies to this PMR and the AMRs that support it. The 
development of this analysis is conducted under activity evaluation Waste Form Analysis & 
Models (CRWMS M&O 2000b), which was prepared per AP-2.16Q, Activity Evaluation. The 
results of that evaluation were that the activity is subject to the Quality Assurance Requirements 
and Description (DOE 2000) requirements. 
This report has a formal planning document (CRWMS M&O 2000c). Development of this report 
did not involve the electronic management of data. The purpose of this ICN is to address DOE 
comments.

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This report was prepared in accordance with AP-3.11Q, Technical Reports and reviewed in 
accordance with AP-2.14Q, Review of Technical Products. The Waste Form Degradation PMR 
does not serve as a primary source for data, models, and codes described in the AMRs related to 
waste form degradation; this function is provided by the AMRs themselves. The AMRs 
supporting the Waste Form Degradation PMR were prepared in accordance with AP-3.10Q, 
Analyses and Models, including AP-3.15Q, Managing Technical Product Inputs, for data 
verification, AP-SIII.2Q, Qualification of Unqualified Data and the Documentation of Rationale 
for Accepted Data, for data qualification and AP-SI.1Q, Software Management, for management 
of software. The quality assurance documentation of the models, codes, and data is deferred to 
the AMRs cited in this document. The current quality status of data and software can be found 
in the Document Input Reference System (DIRS). 
This PMR includes the results from software codes and routines used in the supporting AMRs. 
However no software codes were used in the development of this PMR. The following 
statements are presented for information only. The only software code used in the AMRs was the 
EQ3/6 package, Version 7.2b, which was approved for QA work by LLNL and is identified as 
Computer Software Configuration Item (CSCI): UCRL-MA-110662 V 7.2b (CRWMS 
M&O 1998a) and its addendum (CRWMS M&O 1999c). The package was used both for 
chemical equilibrium calculations, and reaction path calculations (see Sections 3.2 and 3.7). 
1.4 RELATIONSHIP TO OTHER PROJECT REPORTS 
The Waste Form Degradation PMR describes how information is used in the TSPA-SR analysis 
by summarizing the modeling components of the Waste Form Degradation Model. Although not 
directly coupled, the Waste Form Degradation Model, in turn, is related to the Waste Package 
Degradation Model and Engineered Barrier System Model and their corresponding PMRs: 
Waste Package Degradation PMR (CRWMS M&O 2000d) and Engineered Barrier System PMR 
(CRWMS M&O 2000y). The Waste Form Degradation PMR is also related to the Disruptive 
Events PMR (CRWMS M&O 2000an) since it requires waste inventory information. 
Eight summary/abstraction AMRs specifically support the Waste Form Degradation PMR 
(Figure 1.4-1). Other documents underlying these primary areas are mentioned within Chapter 3. 
Abstraction Level AMRs: 
 Inventory Abstraction, ANL-WIS-MD-000006 (CRWMS M&O 2000f) 
 In-Package Chemistry Abstraction, ANL-EBS-MD-000037 (CRWMS M&O 2000g) 
 CSNF Waste Form Degradation: Summary Abstraction, ANL-EBS-MD-000015 
(CRWMS M&O 2000h) 
 Clad Degradation-Summary and Abstraction, ANL-WIS-MD-000007 (CRWMS 
M&O 2000i) 
 DSNF and Other Waste Form Degradation Abstraction, ANL-WIS-MD-000004 
(CRWMS M&O 2000j)

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 Defense High Level Waste Glass Degradation, ANL-EBS-MD-000016 (CRWMS M&O 
2000k) 
 Summary of Dissolved Concentration Limits, ANL-WIS-MD-000010 (CRWMS M&O 
2000l) 
 Waste Form Colloid-Associated Concentrations Limits: Abstraction and Summary, 
ANL-WIS-MD-000012 (CRWMS M&O 2000m). 
Process Level AMRs: 
 Miscellaneous Waste-Form FEPs, ANL-WIS-MD-000009 (CRWMS M&O 2000n) 
 Summary of In-Package Chemistry for Waste Forms, ANL-EBS-MD-000050 (CRWMS 
M&O 2000o) 
 Initial Cladding Condition, ANL-EBS-MD-000048 (CRWMS M&O 2000p) 
 Clad Degradation-Local Corrosion of Zirconium and Its Alloys under Repository 
Conditions, ANL-EBS-MD-000012 (CRWMS M&O 2000ag) 
 Hydride-Related Degradation of SNF Cladding Under Repository Conditions, 
ANL-EBS-MD-000011 (CRWMS M&O 2000r) 
 Clad Degradation-FEPs Screening Arguments, ANL-WIS-MD-000008 (CRWMS 
M&O 2000s) 
 Clad Degradation-Wet Unzipping, ANL-EBS-MD-000014 (CRWMS M&O 2000t) 
 Clad Degradation-Dry Unzipping, ANL-EBS-MD-000013 (CRWMS M&O 2000u) 
 Pure Phase Solubility Limits-LANL, ANL-EBS-MD-000017 (CRWMS M&O 2000v) 
 Secondary Uranium-Phase Paragenesis and Incorporation of Radionuclides into 
Secondary Phases, ANL-EBS-MD-000019 (CRWMS M&O 2000w) 
 Colloid-Associated Radionuclide Concentration Limits: ANL, ANL-EBS-MD-000020 
(CRWMS M&O 2000x). 
1.5 OVERVIEW OF WASTE FORM DEGRADATION MODEL 
The analysis for the TSPA-SR requires numerous models and analyses. Many of these models 
are components of larger models that, in turn, are models to system-level models. Rather than 
call all the parts models, this report uses terms that identify the hierarchy of the models to help 
orient the reader. The system-level model, which uses total system simulation software, is 
referred to as the TSPA-SR system-level model or TSPA-SR. The major parts of TSPA-SR 
are referred to as models. The Waste Form Degradation Model is one such model. The 
models and analyses that are parts of the Waste Form Degradation Model are referred to as

 1-5
components. (A possible alternative term is submodel. However, not all the parts are 
models in the sense used by YMP but rather are analyses, so the term components was 
selected.) Although the Waste Form Degradation PMR has several broad purposes already 
listed, one important purpose is to describe the Waste Form Degradation Model in the TSPA-SR 
and its underlying components. 
1.5.1 Function of Waste Form Degradation Model 
Within the analysis for the TSPA-SR analysis, the function of the Waste Form Degradation 
Model is to determine three outputs over time: (1) dissolved concentration, (2) reversible 
colloidal concentration, and (3) irreversible colloidal concentration of radionuclides 
(Figure 1.5-1). 
Numerous inputs are required for the Waste Form Degradation Model. Several inputs are 
intimately tied with the waste form degradation models such as initial cladding condition and 
thermodynamic data for radionuclides. They are summarized in this report. Other inputs are 
summarized in other PMRs. For example, the time dependent seepage flow into the WP and WP 
surface temperatures are summarized in the EBS PMR (CRWMS M&O 2000y). Corrosion rates 
of the inner stainless steel container and supports for waste inside the waste package are 
summarized in the Waste Package Degradation PMR (CRWMS M&O 2000d). 
1.5.2 Components of Waste Form Degradation Model 
To determine the three output radioisotope concentrations, the Waste Form Degradation Model 
uses eight major modeling/analysis components to evaluate the degradation, deterioration, or 
alteration of the waste: (1) Radioisotope Inventory (described in CRWMS M&O 2000f), (2) In- 
Package Chemistry (described in CRWMS M&O 2000g), (3) Commercial Spent Nuclear Fuel 
(CSNF) Matrix Degradation (described in CRWMS M&O 2000h), (4) CSNF Cladding 
Degradation (described in CRWMS M&O 2000i), (5) DOE Spent Nuclear Fuel (DSNF) 
Degradation (described in CRWMS M&O 2000j), (6) High-Level Waste (HLW) Degradation 
(described in CRWMS M&O 2000k), (7) Radioisotope Dissolved Concentration (described in 
CRWMS M&O 2000l), and (8) Radioisotope Colloidal Concentration (described in CRWMS 
M&O 2000m) (Figure 1.4-1). 
The mathematical description of these eight components is one specific purpose of the Waste 
Form Degradation PMR. Another important purpose is to summarize the technical bases of the 
eight components. Generally, the primary technical bases or foundations of the eight 
components of the waste form degradation models are the CSNF, DSNF, and HLW degradation 
experiments described throughout the report. 
1.5.3 Major Models Communicating with Waste Form Degradation Models within 
TSPA-SR Analysis 
For TSPA-SR analysis, the major model communication with the Waste Form Degradation 
Model is from the EBS abstraction models and the TSPA (Figure 1.5-2). The EBS abstraction 
models determine the water seepage quantity onto the waste form that is used by both the 
In-Package Chemistry Component and the Dissolved Radioisotope Concentration Components. 
In turn, the Waste Form Degradation Model determines dissolved and colloidal concentrations of

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radionuclides for the EBS. The Waste Form Degradation Model is also uncoupled from the 
Waste Package Degradation Model. Although conceptually, the Waste Package Degradation 
Model could calculate the rate iron oxides or other corrosion products are produced by the 
degradation of the WP and pass this information onto the Waste Form Degradation Model. 
Instead of this communication, the underlying in-package process model evaluated the resulting 
chemistry from a variety of corrosion rates and expressed this as uncertainty in the final inpackage 
Chemistry Component. 
1.5.4 Linkage of Components in Waste Form Degradation Model 
The components of the Waste Form Degradation Model are generally connected sequentially 
starting with the Radioisotope Inventory Component and ending with the Radioisotope Colloidal 
Concentration Component; however, some complications occur. First, the rates of degradation 
of the three general categories of waste forms modeled (CSNF, DSNF, and HLW) are not 
coupled, and so three different paths through the Waste Form Degradation Model are possible 
(Figure 1.5-3). Furthermore, because the in-package chemistry (primarily pH) is dependent upon 
the amount of CSNF exposed and the rate of alteration of the borosilicate glass of the HLW, 
some minor feedback does occur. Because the feedback is minor (i.e., secondary effect), the 
feedback lags by one timestep (i.e., the Waste Form Degradation Model does not iterate during 
the timestep). 
1.6 PRINCIPAL AND OTHER FACTORS CONSIDERED 
The magnitude of the YMP and the complexities associated with both the natural and EBSs 
dictate that the YMP prioritize its activities and focus on the factors most important to 
performance, hereafter named the principal factors. The Repository Safety Strategy (RSS) 
(CRWMS M&O 2000a, Table 3-1) has identified seven principal factors and 18 other factors of 
lesser importance. The selection of the principal factors has been based on preliminary TSPA 
analyses and expert judgment, which identified these factors as likely to provide sufficient 
confidence for the safety case. The other factors were deemed to be less important to the safety 
case, nevertheless requiring representation in the current methodology (CRWMS M&O 2000a, 
Section 3.1). Table 1.6-1 lists the seven principal factors, the 18 other factors, and the PMRs that 
address each. The Waste Form Degradation PMR addresses the principal factor Solubility 
Limits of Dissolved Radionuclides. 
Solubility Limits of Dissolved Radionuclides is a principal factor because it describes the 
limitation to the mobilization of the relatively immobile radionuclides because of their limited 
solubilities in the water at Yucca Mountain. Some of these radionuclides present significant risk 
potential because of the long half-life and large dose conversion factor. In many cases, the 
solubilities of these radionuclides are so low they present no significant issue for the potential 
repository system. However, there are a few cases, notably neptunium, plutonium, and uranium 
isotopes, for which solubility limits could be very important to the postclosure safety case 
(CRWMS M&O 2000a, Section 3.2.4).

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Table 1.6-1. Principal Factors, Other Factors, and the Process Model Reports Where Addressed 
Factor Process Model Report 
Seepage into drifts Unsaturated Zone Flow and Transport 
Performance of the drip shield Waste Package Degradation 
Performance of the waste package barriers Waste Package Degradation 
Solubility limits of dissolved radionuclides Waste Form Degradation 
Retardation of radionuclide migration in the 
unsaturated zone 
Unsaturated Zone Flow and Transport 
Retardation of radionuclide migration in the saturated 
zone 
Saturated Zone Flow and Transport 
Principal 
Factors 
(Nominal 
Scenario) 
Dilution of radionuclide concentrations during 
migration 
Saturated Zone Flow and Transport 
Climate, net infiltration into the mountain, and 
unsaturated zone flow above the repository 
Unsaturated Zone Flow and Transport 
Coupled processes  effects on unsaturated zone flow Unsaturated Zone Flow and Transport 
Coupled processes  effects on seepage Near-Field Environment 
Environments on the drip shield Engineered Barrier System Degradation, 
Flow, and Transport 
Environments on the waste package Engineered Barrier System Degradation, 
Flow, and Transport 
Environments within the waste package Waste Form Degradation 
CSNF waste form performance Waste Form Degradation 
HLW glass waste form performance Waste Form Degradation 
DSNF, naval SNF, Pu-disposition waste form 
performance 
Waste Form Degradation 
Colloid-associated radionuclide concentrations Waste Form Degradation 
In-package radionuclide transport Waste Form Degradation 
Transport through the drift invert Engineered Barrier System Degradation, 
Flow, and Transport 
Advective pathways in the unsaturated zone Unsaturated Zone Flow and Transport 
Colloid-facilitated transport in the unsaturated zone Unsaturated Zone Flow and Transport 
Coupled processes  effects on unsaturated zone 
transport 
Unsaturated Zone Flow and Transport 
Advective pathways in the saturated zone Saturated Zone Flow and Transport 
Colloid-facilitated transport in the saturated zone Saturated Zone Flow and Transport 
Other 
Factors 
(Nominal 
Scenario) 
Biosphere transport and uptake Biosphere 
Factors for 
Disruptive 
Event 
Scenarios 
To be determined. See CRWMS M&O (2000a, 
Section 3.5) for preliminary considerations 
Disruptive Events 
Source: Derived from CRWMS M&O 2000a, Table 3-3

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In addition, the following six other factors are within the scope of the Waste Form Degradation 
PMR.
1. Environment within the WP (Section 3.2) 
2. CSNF waste form performance (Section 3.3 and 3.4) 
3. HLW glass waste form performance (Section 3.5) 
4. DSNF, naval SNF, Pu-disposition waste form performance (Section 3.6) 
5. Colloid-associated radionuclide concentrations (Section 3.8) 
6. In-package radionuclide transport (Section 3.2.1.2). 
The general guidelines for addressing these other factors were to use conservative bounding 
analysis, when possible. Principal factors are studied and evaluated more thoroughly, using both 
rigorous, realistic numerical evaluations and also conservative bounding analyses if warranted by 
the overall site performance. 
1.7 ORGANIZATION OF REPORT 
Chapter 2 discusses the evolution of the Waste Form Degradation Model from past TSPA 
analysis and the formal screening of FEPs to include in the current model. The major portion of 
this report, Chapter 3, discusses the inner workings and technical basis of the eight main 
components of the Waste Form Degradation Model used in the TSPA-SR analysis. The order of 
discussion for the eight components reflects the direction of data flow between components 
(Figure 1.5-3). Each section of Chapter 3 begins with an introduction to the component. This 
introduction includes a listing of the AMRs and calculations that provide the detailed technical 
basis for that component, and an overview of the conceptual model as appropriate. The 
description sub-section, which follows, includes summaries of (1) the descriptions of the 
analysis, models, and/or abstractions, (2) relevant data and uncertainties, (3) assumptions and 
basis, and (4) model results. The amount of detail provided varies with each component. For 
many components, the results are simply the models and parameters provided to the TSPA-SR 
and are, thus, included in the model/analysis abstraction description. In addition, many times, 
the relevant data and uncertainties are only briefly summarized, and the reader is referred to the 
supporting AMRs for detailed discussion. The Confidence/Limitations/Validation sub-section 
includes a discussion of model limitations, the justification and confidence, and validation that 
the component is appropriate for the intended use (i.e., appropriate as support for making a 
recommendation on the suitability of the Yucca Mountain site for a repository). Each 
component section ends with a sub-section, which summarizes alternative models and/or 
addresses known issues posed by groups that have project oversight, regulatory oversight, or 
stakeholder interfaces with the YMP. The last section of Chapter 3, Section 3.9, tabulates these 
issues for all eight components, and provides cross-references to the component sections. 
Chapter 4 of the report summarizes the relationship of the topics of this report with the NRC 
IRSRs, primarily the CLST KTIs. Chapter 5 is a brief summary of the report.

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2. EVOLUTION OF WASTE FORM DEGRADATION MODEL 
The waste form degradation models have generally evolved over the years along with the overall 
TSPA model of the disposal system. Thus, this section first presents a short summary of the 
evolution of the TSPAs of the Yucca Mountain disposal system by the Yucca Mountain Project 
(YMP), followed by a summary of the evolution of various components in the Waste Form 
Degradation Model. More detail is presented along with each major section of the various 
components. 
2.1 GENERAL HISTORY OF ASSESSMENTS OF YUCCA MOUNTAIN 
PERFORMANCE 
As summarized by Rechard (1999), simple analytic calculations to determine the relative 
importance of various phenomena postulated to occur at Yucca Mountain were conducted in 
1984 (which identified 99Tc, 129I, and 237Np as important radionuclides for evaluating 
compliance) (Sinnock et al. 1984) and 1988 (performed in conjunction with the Site 
Characterization Plan (SCP) (DOE 1988, Section 8.3.5.13). The first large-scale analysis of 
water movement through the unsaturated zone occurred in 1990 (Prindle and Hopkins 1990). 
Shortly thereafter, a series of deterministic calculations using best estimates for model 
parameters were run by several organizationsSandia National Laboratories, Pacific Northwest 
National Laboratory, and Los Alamos National Laboratoryto simulate the radioisotope 
transport in the unsaturated zone (Barnard and Dockery 1991). 
In 1992, the YMP completed the first probabilistic TSPA of the potential Yucca Mountain 
disposal system to evaluate releases to a 5-km boundary. Two different organizations conducted 
total system performance analysis: Sandia National Laboratories (TSPA-91-SNL) (Barnard et al. 
1992) and Pacific Northwest National Laboratory (TSPA-91-PNNL) (Eslinger et al. 1993). For 
the first time, gaseous flow of 14C was included. In this first probabilistic assessment, the YMP 
was at a relatively early stage in conceptual model development; thus, parameter values and 
distributions were determined primarily by individual PA analysts. 
In 1993, a second iteration of the SNL TSPA (TSPA-93-SNL) (Wilson et al. 1994) was started 
that included an improved Waste Form Degradation Model (called source-term model) and a 
saturated zone model. The analysis also greatly expanded the data used for defining 
geochemical parameters. The formality increased as well in that distributions for many more 
parameters were developed and more often based on the consensus of several PA analysts, 
accompanied by input from site characterization scientists. 
In 1993, the newly assigned CRWMS M&O also conducted a TSPA (TSPA-93-Duke) (CRWMS 
M&O 1994) using the Repository Integration Program (RIP) modeling system intended to 
rapidly simulate the behavior of the disposal system to evaluate design systems. The system 
used a variety of techniques such as curve fits to previous results and selection of distributions 
for particular data to incorporate previous results. This simplified modeling style, called 
abstraction, had been originally proposed in the 1988 SCP (DOE 1988, Chapter 8, 
Section 8.3.5.13) as the culmination of sensitivity analysis on process models. The analyses 
using RIP were the only TSPAs performed by CRWMS M&O after 1993. The basic information 
on parameter distributions reported in TSPA-93-SNL (Wilson et al. 1994) was used for

 2-2
TSPA-93-Duke (CRWMS M&O 1994) and subsequent TSPAs in 1995, 1996, and 1997 
(CRWMS M&O 1995; CRWMS M&O 1996a; CRWMS M&O 1996b; CRWMS M&O 1997a); 
although some differences did occur for radionuclide inventory, and other parameter values were 
sometimes changed for parametric sensitivity analysis. 
Besides TSPAs conducted specifically by CRWMS M&O for the Yucca Mountain Site 
Characterization Office of DOE (DOE/RW/YMSCO), TSPAs conducted specifically for the 
National Spent Nuclear Fuel Program (NSNFP) of the Office of Environmental Management of 
DOE (DOE/EM) by SNL in 1993, 1995, and 1998 examined the behavior of DSNF to test the 
viability of direct disposal of the waste in salt, granite, and tuff (DSNF-TSPA-93-SNL) 
(Rechard 1993), DSNF-TSPA-94-SNL (Rechard 1995), DSNF-TSPA-98-SNL) (DOE 1998a; 
Rechard 1993, 1995). The analysis included the effects of cladding since this was an important 
feature that distinguished ~250 types of DSNF and CSNF. The NSNFP also contracted with 
CRWMS M&O to conduct similar analysis in 1997 for DSNF, DSNF-TSPA-97-Duke (CRWMS 
M&O 1997a). The CRWMS M&O had done a similar sensitivity study the year before on the 
disposal of excess weapons and plutonium (CRWMS M&O 1996b). In 1998, NSNFP supported 
CRWMS M&O such that DSNF was included as a sensitivity study in the TSPA-VA 
(DOE 1998b) (viability assessment) technical basis document discussed below (CRWMS 
M&O 1998b). 
In 1997, Congress mandated in its energy appropriation bill that the YMP provide a viability 
assessment that (along with a preliminary design and costs estimates for constructing and 
operating that design) would include a TSPA describing the probable behavior of the potential 
Yucca Mountain disposal system (Energy and Water Development Appropriations Act 1997). 
A TSPA-VA was thus initiated and completed in November 1998 (DOE 1998b). For TSPA-VA, 
numerous changes and additions were made to the TSPA-95 (CRWMS M&O 1995) models, 
including the addition of more phenomena. Some of these changes included the influence of the 
Zircaloy cladding on CSNF, evaluation and inclusion of geochemistry changes near the waste 
package, colloid formation and transport, and a factor of 100 reduction in solubility of Np 
(DOE 1998b; CRWMS M&O 1997b; CRWMS M&O 1998b). 
2.2 EVOLUTION OF EACH MODEL COMPONENT 
A brief history of the evolution of the waste form models and components is discussed. 
1. Radioisotope Inventory Component (Section 3.1) 
 Many of the early assessments in the 1990s used the inventory for CSNF 
developed around the time of the 1988 SCP: the DOE Characteristics Data Base of 
1987. 
 TSPA-93-Duke (CRWMS M&O 1994) used the DOE Characteristics Data Base of 
1987 to evaluate the inventory of CSNF and HLW and screen radionuclides. 
 TSPA-95 (CRWMS M&O 1995) used the DOE Characteristics Data Base of 1992; 
the weighted average burnup (BU) was slightly lower than TSPA-93-Duke 
(CRWMS M&O 1994) (36,666 versus 39,075 megawatt days [MWd]/metric tons

 2-3
of heavy metal [MTHM]); nine radionuclides were tracked in TSPA-95. The 
screening criteria for the radioisotope selection were based on the maximum 
release rates allowed in 10 CFR 60. 
 TSPA-VA (DOE 1998b) used the same inventory information as TSPA-95 
(CRWMS M&O 1995). Inventories for sixteen DSNF groups (supplied by 
NSNFP), naval fuel (supplied by the Naval Nuclear Propulsion Program), and 
immobilized plutonium from the disposition of excess weapons were not included 
in the base case analysis but were considered in separate sensitivity analysis 
(CRWMS M&O 1998b, Section 6.2.1). Releases from naval SNF were found to be 
insignificant. 
 TSPA-SR analysis uses updated values (CRWMS M&O 2000f) for the CSNF 
inventory based on internal documents, DSNF inventory based on a report of 
eleven groups supplied by NSNFP (DOE 1999b), HLW inventory based on the 
draft EIS (DOE 1999a, Section A.2.1), and immobilized plutonium based on the 
draft EIS (DOE 1999a, Section A.2.3). This evaluation includes the trend toward 
higher burnup fuels in utility operation. 
2. In-Package Chemistry Component (Section 3.2) 
 Through 1997, the effects of in-package chemistry on degradation of the waste 
form and solubility of radionuclides were incorporated through judgement when 
assigning a parameter value or distribution, or through use of conservatively 
bounded models. This resulted in wide distribution ranges for many parameters. 
Sensitivity analyses suggested that application of chemically dependent models 
could reduce uncertainty and conservatism. 
 TSPA-VA (DOE 1998b) evaluated chemistry of the water potentially entering a 
waste package based on the water flux and presence of a degraded concrete liner 
for several input conditions. The results were then collapsed into two time periods 
and used to guide the selection of solubility for a few radionuclides (CRWMS 
M&O 1998b). This two group chemistry was dominated by the concrete liner, 
but allowed further sensitivity assessment for the effect of chemical conditions 
within the EBS. 
 For TSPA-SR analysis, the Waste Form Degradation Model has an In-Package 
Chemistry Component that was coupled with the seepage rate of water into the 
package and degradation of the steel, aluminum, SNF, and HLW inside the 
package. The TSPA-SR analysis design does not have a concrete liner that 
dominates the chemistry, therefore processes at the surface of waste package 
materials and waste forms control the range of chemistry. The estimated minimum 
pH after breach of the container was lower than was considered in previous 
TSPAs. Results from the In-Package Chemistry influenced degradation of the 
CSNF cladding and matrix, solubility, and colloid availability and stability. The 
degradation of HLW and exposed amount of CSNF, in turn, influenced the In- 
Package Chemistry (Figure 1.5-3).

 2-4
3. CSNF Matrix Degradation Component (Section 3.3) 
 Early performance assessments bound CSNF oxidation and dissolution rates by 
experimental observations. Testing of UO2 and spent fuel has included elevated 
temperature air oxidation, aqueous dissolution at high water flow rates, and in 
aqueous dissolution batch reactors. Because of the possibility for early waste 
package failure, high temperatures, and no modeling of cladding performance, dry 
oxidation of the fuel matrix to more soluble forms was an important consideration 
in early assessments. Aqueous dissolution is observed to be temperature and pH 
dependent. Carbonate ions can influence the surface reaction rate, and at high 
rates and limited oxygen availability the rate may be bounded by PO2. Burnup 
dependence includes a combination of effects from radiation, fission products and 
thermal alteration of the matrix. 
 Since TSPA-93-Duke (CRWMS M&O 1994), empirical dissolution rates have 
been based on experimental data. 
 For TSPA-95, a simplified regression equation based on T, pH, PO2, [CO3]T was 
used, based on high flow rate experiments to provide a upper bound on dissolution 
rate. 
 After TSPA-95, the fuel test program was expanded to include aqueous dissolution 
at very low drip rates to represent the slow seepage conditions indicated as most 
likely to occur in an unsaturated repository. 
 For TSPA-VA, an eleven term regression equation dependent on temperature (T), 
pH, total carbonate concentration [CO3]T , oxygen partial pressure (as percent of 
atmosphere) (PO2), burnup of the fuel, and several cross-product terms was used. 
This equation was based on high flow rate dissolution experiments, and thus 
represents an upper bound. The longevity of the VA waste package and inclusion 
of cladding performance resulted in protection of the fuel matrix until temperatures 
were low enough that dry oxidation was no longer an important process. A more 
detailed chemistry dependence was included to allow sensitivity analyses to 
evaluate the value of tracking chemical condition within the EBS. The collection 
of radionuclides in secondary phases, as seen in the drip tests was considered in a 
sensitivity study. 
 For TSPA-SR analysis, a simplified regression equation based only on T, pH, PO2, 
[CO3]T was used and these controlling variables were coupled to in-package 
chemistry to account for uncertainty. The model is based on data from the high 
flow rate experiments and represents an upper bound for the dissolution rate. 
4. CSNF Cladding Degradation Component (Section 3.4) 
 While fuel cladding is very corrosion resistant, it is thin and used in a harsh reactor 
environment. Because of these concerns, cladding was not considered in early 
assessments. Cladding degradation testing and modeling has evolved and is used

 2-5
as a basis for extending the period of wet and dry storage and for licensing 
shipping casks for spent fuel. This information has accumulated in the literature. 
Development of long lived waste packages that protect the fuel during the early 
thermal transient, along with the accumulated literature, has allowed consideration 
of cladding in repository performance. 
 Cladding degradation was first considered in DSNF-TSPA-93-SNL (Rechard 
1993) and DSNF-TSPA-94-SNL (Rechard 1995) to distinguish performance of 
various SNF (Rechard 1993, 1995; DOE 1998a); the cladding was divided into two 
classes, failed and intact cladding; the degradation of intact cladding was based on 
Arrhenius type rate equation and a reduction factor to account for localized 
corrosion. 
 For TSPA-95, cladding degradation from creep rupture was discussed but not used 
in the analysis, and the fuel was considered to be bare. 
 For TSPA-VA, several cladding degradation modes (initial reactor failures, creep 
rupture, failures from rockfall, and localized corrosion as estimated by a zirconium 
model within the waste package degradation model, WAPDEG) were combined 
into a time-varying function of failed cladding. Other cladding modes such as 
cladding unzipping, stress corrosion cracking, and hydride failures (hydride 
embrittlement, delayed hydride cracking [DHC] and hydride reorientation) were 
not considered likely to occur and were omitted from consideration. 
 For TSPA-SR analysis, cladding degradation was coupled to CSNF Matrix 
Degradation and In-Package Chemistry; furthermore, two steps of degradation 
were included: perforation and unzipping. The modes of cladding degradation 
were formally evaluated during FEP screening; hydride failures were still omitted 
from consideration. 
5. DSNF Degradation Component (Section 3.5) 
 DSNF was first considered in DSNF-TSPA-93-SNL (Rechard 1993) and 
DSNF-TSPA-94-SNL (Rechard 1995). An Arrhenius-type rate equation was used 
for degradation except that each of the various types of DSNF used different model 
parameters. 
 CRWMS M&O studied the sensitivity of DSNF in 1997. 
 TSPA-VA (DOE 1998b) studied the sensitivity of DSNF in 1998; the degradation 
rate of N-Reactor SNF was used to bound the response of all other waste types; the 
rate equation was that developed for DSNF-TSPA-94-SNL (Rechard 1995).

 2-6
 In an analysis to support TSPA-SR, DSNF (with the exception of naval SNF) was 
included using N-Reactor SNF to represent the physical degradation rate; however, 
the inventory was the weighted sum of all waste types included in the DSNF 
allocation category. The degradation rate of N-Reactor SNF was a bound on the 
maximum degradation rate observed to date in on-going experiments (Gray and 
Einziger 1998). 
6. HLW Degradation Component (Section 3.6) 
 Early assessments were based on bounds of observed glass dissolution rates. 
Initially short-term, aqueous batch testing was done for developing glass mixtures 
and evaluating product consistency. Later, long term batch and high flow rate 
testing was done to obtain long term reaction rate. 
 A separate degradation rate for HLW was first included in TSPA-93-SNL and 
TSPA-93-Duke (CRWMS M&O 1994) and afterwards. 
 For TSPA-VA, a phenomenological model of degradation was used where several 
parameters were based on experimental data; a few variables were set at fixed 
values (e.g., silica concentration). Development of long lived waste packages 
reduced the importance of higher temperature processes. 
 For TSPA-SR analysis, bounds on parameters of a phenomenological model were 
used to develop a simplified (Arrhenius-type) rate equation of degradation. The 
parameter values in this model are based on laboratory test results for a range of 
reference glass compositions and are designed to conservatively bound the rate of 
glass corrosion under the range of conditions (immersion, humid air and dripping 
groundwater) to which it may be exposed in the repository. Specifically, the 
model is now designed to bound the higher corrosion rates observed after extensive 
reaction progress in some laboratory tests and also bounds the corrosion rates 
observed under vapor hydration and dripping groundwater conditions. 
7. Dissolved Radioisotope Concentration Component (Section 3.7) 
 Early assessments assumed conservative upper bounds on aqueous solubility. 
 For TSPA-93-SNL, an elicitation of project experts was used in 1993 to determine 
solubility of important radionuclides. 
 TSPA-95 (CRWMS M&O 1995) generally used the values of TSPA-93-SNL; 
however, some values were modified based on experimental observations and 
controlling processes and phase assumptions. 
 TSPA-VA (DOE 1998b) used the values of TSPA-95 (CRWMS M&O 1995) 
except Np solubility was reduced by factor of 100 after reevaluating previous 
experiments.

 2-7
 In TSPA-SR analysis, solubility of important radionuclides (as determined by 
updated screening) was reevaluated. Three radioisotope solubilities were 
abstracted as a direct function of in-package chemistry (Np, U, Am) to better 
account for the uncertainty. Four radioisotope solubilities were defined by a 
probability distribution, and all others were set at bounding values. 
8. Colloidal Radioisotope Concentration Component (Section 3.8) 
 Early assessments used wide ranges on solubility that bounded the potential effect 
of colloidal transport of specific radionuclides since experimental data and colloid 
formation, stability and transport models were limited. 
 Colloids first incorporated as a radioisotope transport mechanism in TSPA-VA. 
Colloid formation, stability, and transport properties were inferred from glass and 
fuel dissolution tests, field observations, and laboratory experiments. 
 Colloid model incorporates new details for TSPA-SR. 
2.3 SCREENING OF FEATURES, EVENTS, AND PROCESSES 
2.3.1 Screening Criteria 
Throughout the 20 years of analysis of the potential Yucca Mountain disposal system, various 
FEPs have been identified and their influence on the disposal system evaluated. The FEPs have 
been identified by a variety of methods, such as hypothesis by scientists and engineers working 
on the project or through review of their work. The variety of project participants and reviewers 
have helped ensure that a wide variety of FEPs has been considered. These hypotheses and 
reviews have been the impetus for the changes and evolution of the models discussed above. An 
initial set of FEPs was created for TSPA-SR analysis by combining three general lists of FEPs: 
82 from various YMP workshops in 1998 and 1999, 292 FEPs gathered from YMP literature and 
site studies, and 1,412 FEPs from a draft report of the Nuclear Energy Agency (NEA) of the 
Organization for Economic Cooperation and Development (OECD) for a total of 1,786 FEPs. 
The latter list is a compilation of FEPs from seven geologic repository programs in other 
countries and, thus, the most complete attempt internationally to develop a comprehensive list of 
FEPs relevant to radioactive waste disposal. 
To ensure the list was comprehensive, all potentially relevant FEPs identified have been 
included; however, this list has led to considerable redundancy. Consequently, late in 1998, the 
FEPs were classified as either primary or secondary. The 310 primary FEPs are those FEPs for 
which detailed screening arguments are developed. The remaining 1,476 secondary FEPs are 
either completely redundant or can be reasonably aggregated and mapped into a single primary 
FEP through modification of the description the primary FEP. 
To develop screening arguments, the primary FEPs have been assigned to applicable PMRs. 
However, since a FEP can effect many facets of the disposal system, a FEP may be assigned to 
several PMRs. For example, some FEPs that affect the degradation of waste form also influence

 2-8
the waste package degradation and the evolution of the Engineered Barrier System and, thus, 
have been assigned to all three corresponding PMRs. 
The 87 primary waste form FEPs assigned to the Waste Form Degradation PMR have been 
evaluated by subject-matter experts and discussed in three different AMRs: 57 primary waste 
form FEPs are discussed in Miscellaneous Waste-Form FEPs (CRWMS M&O 2000n, Table 1), 
15 are discussed in Waste Form Colloid-Associated Concentrations Limits: Abstraction and 
Summary (CRWMS M&O 2000m, Attachments I through XV), and 16 are discussed in Clad 
DegradationFEPs Screening Arguments (CRWMS M&O 2000s). One FEP (Mutation) appears 
in two AMRs (CRWMS M&O 2000n, CRWMS M&O 2000m). 
The decision to include or exclude a FEP related to the waste form was based on two criteria in 
the NRCs proposed rule 10 CFR 63.114 (Dyer 1999) .4 
 Consider only events that have at least one chance in 10,000 of occurring over 10,000 
years (Section 63.114(d)). 
 Provide the technical basis for either inclusion or exclusion of degradation, 
deterioration, or alteration processes of engineered barriers in the performance 
assessment, including those processes that would adversely affect the performance of 
natural barriers. Degradation, deterioration, or alteration processes of engineered 
barriers must be evaluated in detail if the magnitude and time of the resulting expected 
annual dose would be significantly changed by their omission (Section 63.114(f)). 
In accordance with its proposed rule (Dyer 1999), the NRC provides additional guidance in the 
TSPAI IRSR (NRC 2000a) on the screening process to follow to exclude FEPs. The guidance 
states four criteria that will be used (NRC 2000a, Section 4.2.3), with the first three criteria 
dealing with evaluating the probability of the FEP: 
 Criterion T1: Categories of processes and events that are not credible for the YM 
repository because of waste characteristics ... are identified and sufficient justification is 
provided for DOEs conclusions. 
 Criterion T2: The probability assigned to each category of processes and events not 
screened based on criterion T1 or criterion T2 is consistent with site information, well 
documented, and appropriately considers uncertainty. 
 Criterion T3: DOE has demonstrated that processes and events screened from the PA 
on the basis of their probability of occurrence, have a probability of less that one chance 
in 10,000 of occurring over 10,000 years. 
4 The proposed EPA Standard 40 CFR 197 (Dyer 1999; 64 FR 46976) has a similar approach in Section 197.40.

 2-9
 Criterion T4: DOE has demonstrated that categories of processes and events omitted 
from the PA on the basis that their omission would not significantly change the 
calculated expected annual dose, do not significantly change the calculated expected 
annual dose. 
In summary, the first criterion permits an exclusion argument for FEPs that are not credible 
because of waste characteristics, repository design, or site characteristics. The second and third 
criteria deal with the assignment of probabilities to FEPs and demonstrating that the probabilities 
of excluded FEPs are below the quantitative probability limit of 10-4 over 104 yr. The fourth 
criterion permits exclusion of FEPs that do not significantly change the calculated expected 
annual dose. These exclusions must be adequately justified in accompanying discussions or 
calculations, including the use of either bounding or representative estimates. In applying the 
fourth criterion, calculations of intermediate results are often used instead of dose calculations. 
For example, if a FEP does not affect release from the waste packages, it will not affect dose, so 
it is sufficient to consider release alone. 
Based on the four criteria stated above, a statement on whether to Include or Exclude the FEP is 
provided. If the screening decision is Include, the FEP is considered either in the nominal 
scenario (i.e., the scenario that contains all expected FEPs and no disruptive5 FEPs), in a 
disruptive scenario (i.e., any scenario that contains all expected FEPs and one or more disruptive 
FEPs), or in the human intrusion scenario. 
Because the primary FEPs are the coarsest aggregate suitable for analysis, situations may result 
in which a given primary FEP contains some secondary FEPs that are Include and some that are 
Exclude. In these situations, the screening decision specifies which elements are Include and 
which are Exclude. 
2.3.2 Screening Decisions 
Most of the waste form FEPs that have been excluded from further consideration were excluded 
based on low consequence. Several waste form FEPs have been excluded based on the FEP not 
being credible for the waste characteristics and repository design at Yucca Mountain. 
For the discussion herein, the 87 FEPs have been grouped and tabulated according to the eight 
major modeling components of the waste degradation model (Figure 2.3-1). Each of the eight 
tables provides the YMP FEP number, the short title, the decision as to whether to include or 
exclude the FEP, the PMRs where the FEP was discussed, the AMR that provides the full 
argument for the screening decision related to the waste form, and a brief synopsis of the 
screening argument. The synopsis only pertains to the Waste Form Degradation PMR. The 
reasoning to include or exclude a FEP in relation to other PMRs is not given but can be found in 
those other PMRs or the underlying AMR. 
Several waste form FEPs have been excluded because the FEP is not credible for the 
characteristics of the waste proposed for disposal at Yucca Mountain (i.e., first criterion, T1). 
5 A disruption FEP is a retained FEP that has a probability of occurrence less than 1.0 during the period of 
performance but greater than the cutoff of 10-4/104 yr defined by the NRC as proposed 10 CFR 63.114(e) (Dyer 
1999).

 2-10
The succinct description for this reasoning is Excluded based on low probability (credibility). 
For example, cellulosic material is not present in CSNF, DSNF, or HLW that would be disposed 
of at Yucca Mountain; furthermore, organic material will be excluded based on current waste 
acceptance criteria. Therefore, FEP 2.1.02.10.00 in Table 2.3-2 that discusses this feature of the 
waste is excluded based on a low probability (credibility) argument. 
No FEPs were excluded based on quantitatively evaluating the probability of a FEP (i.e., criteria 
T2 and T3). Rather, most of the excluded FEPs related to the waste form were excluded based 
on the fourth criterion (T4), no significant change in the expected annual dose. FEPs excluded 
based on this criterion are succinctly described as Excluded based on low consequence. For 
example, generation of H2 is credible in an anoxic environment when steel corrodes; yet, it is 
unlikely that much will be produced since the drifts at Yucca Mountain will be mostly oxic. 
Only in small pores and crevices would an anoxic environment be found in the waste. Because 
evaluating a probability for this phenomenon is very difficult, the low consequences of this 
phenomenon were used to exclude this FEP. H2, if produced, is very mobile and kinetically 
unreactive at low temperatures, so it is expected to leave the drift before it reacts with any of the 
emplaced materials. In addition, oxidation of hydronium ion to H2 instead of sulfur to sulfate 
results in less pH suppression. 
The latter reason is a minor aspect of the argument to exclude the process, but in other FEPs it 
can be a major aspect of the argument because bounding estimates are often used in the 
TSPA-SR. That is, the argument for exclusion is often that the exclusion of the FEP provides a 
bound on the expected annual dose (i.e., inclusion of the FEP would only decrease the expected 
annual dose). For this case, the succinct description of the FEP reasoning used in the summary 
tables is Excluded based on low consequence (conservative bound). For example, a few 
radioisotopes, such as Np, may be incorporated into the structure of phases of other minerals 
(primarily uranium minerals) that form during degradation of the waste. For chemically similar 
elements such as Np and U, the effective solubility of Np as a minor constituent of a uranium 
mineral is less than the solubility of the analogues pure Np mineral. However, this FEP, 
secondary phase effects on dissolved radionuclide concentrations at the waste form in Table 
2.3-7, was conservatively excluded in TSPA-SR. The degree of conservatism is not quantified 
since the collection of data to justify the model would require either too much time or too many 
resources for the surmised potential benefit. The exclusion of FEPs that have a potential 
beneficial consequence is a conservatism of the FEPs screening process. This conservatism is in 
addition to the many conservative approaches used to include FEPs as more fully discussed in 
Chapter 3.

 2-11
2.3.2.1 FEPs Related to the Radioisotope Inventory Component 
Five FEPs relate to the Radioisotope Inventory Component (Table 2.3-1). The waste inventory 
was reconsidered and 27 important radionuclides identified. The radioisotopic gas inventory was 
omitted because the screening analysis showed that gases were not significant contributors to 
dose. However, one radioisotopic gas, 14C, is included as a dissolved species. Not all isotopes of 
uranium and plutonium are included in the 27 important radionuclides, and so the proper 
proportion (dilution) of the included uranium and plutonium isotopes is evaluated for the 
Waste Form Degradation Model when evaluating solubility. For the TSPA-SR analysis, 
radioactive decay (and ingrowth6) is modeled, and the heterogeneity of the inventory in the waste 
form is included using three waste forms (CSNF, DSNF, and HLW). 
Table 2.3-1. FEPs Related to the Radioisotope Inventory Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.01.01.00 Waste 
inventory 
Include WF ANL-WISMD-
000009 
ANL-WISMD-
000006 
Included: Average and bounding inventories for 27 
radioisotopes for 3 waste allocation categories 
(CSNF, DSNF, and HLW) have been developed; 24 
isotopes from screening arguments based on 
human dose, two isotopes mandated by the 
Groundwater Protection Requirement of the 
proposed 40 CFR 197 and one isotope (235U) to 
properly perform radioactive decay; different 
subsets of the isotopes are used for the various 
scenarios: volcanic release (16), nominal 
groundwater release (21), and human intrusion (23). 
This FEP is the topic of AMR, Inventory Abstraction. 
2.1.01.03.00 Heterogeneity 
of waste forms 
Include WF ANL-WISMD-
000009 
Heterogeneity of waste forms, is included by 
handling CSNF, DSNF, and HLW separately. 
Heterogeneity is included within these three 
categories only to the extent that it is used to 
determine the average or bounding inventory. 
6 Ingrowth is the further production of a radioisotope as its parent decays, e.g., initial inventory of 237Np increases as 
the parent 241Am decays.

 2-12
Table 2.3-1. FEPs Related to the Radioisotope Inventory Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.12.07.00 Radioactive 
gases in waste 
and EBS 
Exclude WF, EBS ANL-WISMD-
000009 
Excluded based on low consequence: The potential 
human dose from inhalation of radioactive gases 
was low relative to other doses and, thus they were 
screened out except for dissolved 14C. 
Other influences of gases (radioactive or not) are 
also excluded as discussed in other FEPs: 
Biological activity in the waste is screened out 
(colloid FEP 2.1.10.01.00) and so generation of 
microbial gases such as CO2, CH4, H2S are also 
screened out (in-package chemistry FEP 
2.1.12.04.00). The chemical influence of H2 is 
conservatively neglected (in-package chemistry 
FEP 2.1.12.03.00). Generally, the physical aspects 
of gas generation such as displacement of oxygen 
and pressurization of the disposal drifts by He and 
H2 (in-package chemistry FEPs 2.1.12.02.00 and 
2.1.12.03.00, respectively) have been excluded 
since gas would readily dissipate from the 
repository over geologic time (i.e., because 
fractures and fault zones are unsaturated, the 
relative permeability to gas is large). (Note: the 
relative permeability of the fractures and fault zones 
to water is lower than for air and is included in the 
unsaturated flow modelsee FEPs related to 
unsaturated flow model.) 
Included: See cladding FEP 2.1.02.20.00 where the 
pressurization of CSNF cladding is included. 
3.1.01.01.00 Radioactive 
decay and 
ingrowth 
Include WF, UZ, 
SZ 
ANL-WISMD-
000009 
Included: Radioactive decay and ingrowth (i.e., 
further production of a radioisotope as its parent 
decays) is either incorporated in the computer 
codes used for the TSPA-SR total system model, or 
the inventory of a daughter is conservatively 
increased when generating the inventory in cases 
where decay and ingrowth are not explicitly 
modeled. 
3.2.07.01.00 Isotopic dilution Include/ 
Exclude 
WF, SZ ANL-WISMD-
000009 
Included: Mixing or dilution of specific radionuclides 
of the same element within the WP is accomplished 
by assuming that the dissolved isotopic mass at a 
given elemental concentration is proportional to the 
isotopic inventory at that time. 
Exclude outside waste package based on low 
consequence (conservative bound). 
Isotopic dilution during transport away from the WP 
due to stable and/or naturally occurring isotopes of 
the same element; dilution only decreases adverse 
radiological effects.

 2-13
2.3.2.2 FEPs Related to the In-Package Chemistry Component 
Twenty-five FEPs relate to the In-Package Chemistry Component (Table 2.3-2). Prior to 
TSPA-SR analysis, uncertainty in the in-package chemistry was evaluated through scientific 
judgment; but objectively demonstrating that the uncertainty from these 25 FEPs was included 
was difficult; an in-package chemistry component was developed for TSPA-SR analysis to 
explicitly include many of these FEPs. Furthermore, a few FEPs dealt with the coupling of the 
in-package chemistry with other model components; these FEPs can now be included in the 
current TSPA-SR analysis. 
Table 2.3-2. FEPs Related to the In-Package Chemistry Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.01.02.00 Codisposal/ 
colocation of 
waste 
Include/ 
Exclude 
WF ANL-WISMD-
000009 
Included: The chemical interaction between DSNF 
and HLW in one codisposal package is explicitly 
included in the In-Package Chemistry Component. 
Codisposal/colocation of DSNF and HLW is also 
included in the TSPA-SR by separately modeling 
waste form degradation of both categories within a 
codisposal waste package (see DSNF FEP 
2.1.02.01.00 and HLW FEP 2.1.02.03.00). 
Colocation: outside WF scope.

 2-14
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.01.04.00 Spatial 
heterogeneity of 
emplaced waste 
Exclude/ 
Include 
WF ANL-WISMD-
000009 
Excluded based on low consequence: The time 
scale of convective transport and diffusion of 
aqueous species in the fully flooded waste 
package is rapid in relation to alteration of the 
contents (waste form, cladding, and support 
material); consequently, the contents are assumed 
to be uniformly mixed and spatial heterogeneity in 
the waste to evaluate in-package chemistry is 
excluded. Spatial heterogeneity of the two types of 
waste packages modeled is also excluded based 
on low consequence. WPs of CSNF and 
codisposed DSNF and HLW are to be closely 
packed together so that variations in temperature 
(which can influence aspects of waste form 
degradation and in-package chemistry) of 
individual WPs will not vary significantly. 
Included: Spatial heterogeneity of temperatures in 
a waste package are evaluated to determine 
perforation through creep rupture (cladding FEP 
2.1.02.19.00) and stress corrosion cracking 
(cladding FEP 2.1.02.21.00). 
2.1.02.09.00 Void space 
(in waste 
package) 
Include/ 
Exclude 
WF ANL-WISMD-
000009 
Included: For determining the radioisotope 
concentration, the Dissolved Radioisotope 
Concentration Component uses a time varying void 
volume of the altered waste form (see Solubility 
FEP 2.1.09.12.00). In addition, in the process 
model for evaluating the In-Package Chemistry 
Component, the mixing cell volume is equal to the 
fixed void volume in the waste package; hence, 
void space is indirectly included in the In-Package 
Chemistry Component. 
Excluded based on low consequence. The 
potentially time varying void space available and its 
influence on determining the in-package chemistry 
was excluded based on low consequence. Rather, 
the uncertainty in the in-package chemistry that 
might be caused by different void volumes would 
be swamped by the use of various water inflow 
rates into the waste package that were used to 
define the various simulations and, thereby, the 
uncertainty used in the In-Package Chemistry 
Component. 
2.1.02.10.00 Cellulosic 
degradation 
Exclude WF ANL-WISMD-
000009 
Excluded because of low probability (credibility). 
According to preliminary waste acceptance criteria 
(DOE 1999c, Section 4.2.3.A.3), no cellulosic 
materials will be included as part of the waste in 
the potential Yucca Mountain repository.

 2-15
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.03.06.00 Internal 
corrosion of 
waste container 
Include/ 
Exclude 
WF, WP ANL-WISMD-
000009 
Included: After breach of the WP, the corrosion of 
the inner structural stainless steel is important to 
determining the in-package chemistry (provided a 
high sulfur steel is used) and is, thus, included in 
the process model and as part of the uncertainty of 
the In-Package Chemistry Component (see also inpackage 
chemistry FEP 2.1.09.02.00). 
Excluded based on low consequence: Prior to WP 
breach, internal corrosion will not be significant. 
The current design specifies placement of inert 
gases in the package and limited water allowed in 
the CSNF (see cladding FEP 2.1.02.11.00) and 
HLW glass packages. Some canisters containing 
DSNF such as those containing N-Reactor fuel, 
may have more water, but this water would be 
scavenged by the waste form itself. 
2.1.08.07.00 Pathways for 
unsaturated 
flow and 
transport in the 
waste and EBS 
Include/ 
Exclude 
WF, EBS ANL-WISMD-
000009 
Include through the use of a series of linked onedimensional 
flow paths and mixing cells through 
the EBS, drip shield, waste package, and into the 
invert. 
Exclude based on low consequence (conservative 
bound): transport pathways inside container 
excluded; rather, container assumed to be a mixing 
cell for In-Package Chemistry Component. 
Inclusion of the pathways would delay release of 
radionuclides and thus they are conservatively 
neglected. 
2.1.08.08.00 Induced 
hydrological 
changes in the 
waste and EBS 
Include/ 
Exclude 
WF, EBS ANL-WISMD-
000009 
Included: Changes in flow volume into the WP as 
it degrades are included. Changes in the exposed 
fuel area as CSNF cladding fails are also included 
(see cladding unzipping FEP 2.1.02.23.00). 
Excluded based on low consequence: Changes to 
hydrologic properties of the waste form and invert 
are excluded since the slight changes in hydrologic 
properties are small in relation to the overall 
uncertainty of the in-package chemistry 
predictions. 
2.1.08.10.00 Desaturation/ 
dewatering of 
the repository 
Include WF, NFE ANL-WISMD-
000009 
Included through unsaturated flow modeling in the 
TSPA thermal hydrologic models which, in turn, 
affects the volume of water entering the disposal 
WPs.

 2-16
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.01.00 Properties of 
the potential 
carrier plume in 
the waste and 
EBS 
Include/ 
Exclude 
WF ANL-WISMD-
000009 
Included: Water entering the package is assumed 
to have chemical properties of J-13 well water in 
the process models of the in-package chemistry. 
Water chemistry was then altered based on waste 
type, cladding failure, seepage flux, and waste 
degradation rate. Furthermore, corrosion of steel 
is directly used to establish an uncertainty range 
for the water chemistry. 
Excluded based on low consequence: the 
changing properties of incoming water, as 
evaluated by EBS. Although the changing 
properties of the incoming water as evaluated by 
EBS are not coupled to these process calculations, 
slight changes in the incoming water over time are 
swamped by the dramatic changes that are 
predicted in the in-package chemistry because of 
the waste and internal parts of the waste package. 
That is, the range of uncertainty used for the In- 
Package Chemistry Component is not changed by 
the minor changes of the initial chemistry of the 
water entering the package. This fact is especially 
true now that a concrete tunnel liner is not used. 
2.1.09.02.00 Interaction with 
corrosion 
products 
Exclude/ 
Include 
WF, EBS ANL-WISMD-
000009 
Included: The chemical effects of the corrosion of 
steel (e.g., release of sulfur) on the in-package 
water chemistry have been included (see also inpackage 
chemistry FEP 2.1.03.06.00). Several 
other interactions are also included and discussed 
in other FEPs: the presence of corrosion product 
is included in determining the availability of water 
for radioisotope dissolution (solubility FEP 
2.1.09.12.00); the volume increase of the corrosion 
products and the unzipping of the cladding is 
included (cladding FEP 2.1.09.03.00); and the 
sorption on mobile colloids is included (colloid FEP 
2.1.09.05.00). Coupling of related processes was 
also included (see in-package chemistry coupled 
processes FEP 2.1.11.04.00). 
Excluded based on low consequence (conservative 
bound): The potential beneficial effects from 
corrosion productswhich include sorption on 
immobile corrosion products (colloid FEP 
2.1.09.05.00), and the decreased ability for 
advective and diffusive transport of radioisotopes 
have been conservatively excluded.

 2-17
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.06.00 Reductionoxidation 
potential in 
waste and EBS 
Include WF, EBS ANL-WISMD-
000009 
In developing the regression equation of pH for the 
In-Package Chemistry Component, which is based 
on the EQ3/6 equilibrium process model, the fluid 
is assumed equilibrated with the atmosphere to 
ensure maximum plausible O2 and CO2 conditions. 
Furthermore, to match these assumptions, the In- 
Package Chemistry Component sets the O2 and 
CO2 conditions at atmospheric conditions. These 
conditions are then used by the CSNF Matrix 
Degradation Component (see CSNF FEP 
2.1.02.02.00) and Dissolved Radioisotope 
Concentration Component (see Solubility FEP 
2.1.09.04.00). 
2.1.09.07.00 Reaction 
kinetics in 
waste and EBS 
Include/ 
Exclude 
WF, EBS ANL-WISMD-
000009 
Included reaction kinetics through quasi-equilibrium 
analysis. The equilibrium model evaluates the pH 
over time as a function of several rates of 
degradation of the cladding, SNF matrix, HLW 
glass, and internal components of the disposal 
package (stainless steel and aluminum); the 
resulting variance in the pH is then used to set 
bounds on the uncertainty of the in-package water 
chemistry. 
Excluded based on low consequence of the 
reaction transients between time steps: The inpackage 
chemistry process model, EQ3/6, 
assumes instantaneous equilibrium between 
changes in amounts of corrosion products 
available. Small enough time steps are taken to 
avoid errors exceeding uncertainty in 
thermodynamic parameters. 
2.1.09.08.00 Chemical 
gradients / 
enhanced 
diffusion in 
waste and EBS 
Exclude WF, EBS ANL-WISMD-
000009 
Excluded based on low consequence. The WP is 
assumed to be a mixing cell without chemical 
gradients in the In-Package Chemistry Component. 
Provided the WP is fully saturated, the rate of the 
flow of water into and out of the package is slow 
enough that no long-term gradient would be 
present and equilibrium would occur. Furthermore, 
rather than include diffusive release of 
radionuclides out of the CSNF perforated cladding, 
DSNF perforated cladding, or cracked HLW glass, 
a more conservative conceptual model is 
developed that subsumes enhanced release from 
diffusion caused by chemical gradients, cladding 
unzipping for CSNF (cladding unzipping FEP 
2.1.02.23.00), 100% failed cladding for DSNF 
except naval SNF (DSNF cladding FEP 
2.1.02.25.00), and very high reactive surface area 
for HLW glass (HLW surface area FEP 
2.1.02.05.00). Performance analysis of naval SNF 
will account for the performance of the cladding.

 2-18
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.09.00 Electrochemical 
effects 
(electrophoresis, 
galvanic 
coupling) in 
waste and EBS 
Exclude WF ANL-WISMD-
000009 
Excluded based on low consequence. The 
influence of fluid flow through a failed container on 
the in-package chemistry is much greater than any 
effect on the degradation of the SNF or HLW 
matrix that can be created by electrophoresis or 
electro-osmosis. 
2.1.09.11.00 Waste-rock 
contact 
Include/ 
Exclude 
WF, EBS ANL-WISMD-
000009 
Included: The indirect influence of waste-rock 
contact on in-package chemistry is included 
through the use of the J-13 well water (in-package 
chemistry FEP 2.2.08.12.00). The perforation of 
cladding from shaking in a severe earthquake is 
included as a disruptive event (cladding FEP 
2.1.02.24.00). 
Excluded based on low consequence: Because of 
the drip shield and the long-lived waste package, 
rock is not expected to come in contact with the 
waste in the first 10,000 yr. Furthermore, even if 
some contact were to occur, the overall result 
would be little or no involvement of the rock 
minerals in chemical reaction due to their 
dissolution kinetics. The perforation of CSNF 
cladding from rock fall is also excluded in the first 
10,000 yr (cladding FEP 2.1.07.01.00). 
2.1.11.04.00 Temperature 
effects / 
coupled 
processes in 
waste and EBS 
Include/ 
Exclude 
WF, EBS ANL-WISMD-
000009 
Included: Many of the processes of the Waste 
Form Degradation model are coupled. CSNF 
matrix degradation (CSNF FEP 2.1.02.02.00), 
HLW degradation (HLW FEP 2.1.02.03.00), and 
Dissolved Radioisotope Concentration (solubility 
FEP 2.1.09.04.00) are coupled to the chemical 
conditions calculated by the In-Package Chemistry 
Component (this FEP). Cladding unzipping 
(Cladding FEP 2.1.02.23.00) is coupled to CSNF 
matrix degradation (see also in-package chemistry 
FEP 2.1.09.02.00). In turn, weak feedback to the 
In-Package Chemistry Component occurs from 
HLW degradation and cladding degradation. 
Temperature is also coupled to CSNF matrix 
degradation (CSNF FEP 2.1.11.05.00), CSNF 
cladding degradation (cladding FEP 2.1.11.07.00), 
and HLW degradation (HLW FEP 2.1.11.01.00), 
and solubility of uranium (solubility FEP 
2.1.09.04.00). 
Excluded based on low consequence: because the 
primary effects of temperature on waste form 
degradation are included directly, the secondary 
effects of temperature on in-package chemistry 
such as pH are of low additional consequence 
(also see in-package chemistry FEP 2.1.11.08.00).

 2-19
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.11.08.00 Thermal effects: 
chemical and 
microbiological 
changes in the 
waste and EBS 
Include/ 
Exclude 
WF, NFE, 
EBS 
ANL-WISMD-
000009 
Included: temperature effects are included directly 
in various components (e.g., cladding degradation 
rate [cladding FEP 2.1.11.07.00], CSNF matrix 
degradation rate [CSNF FEP 2.1.02.02.00], HLW 
degradation rate [HLW FEP 2.1.02.03.00], and 
solubility of uranium [solubility FEP 2.1.09.04.00]). 
Excluded based on low consequence: Because the 
primary effects of temperature on waste form 
degradation are included directly, the secondary 
effects of temperature on in-package chemistry 
such as pH are of low additional consequence. 
Furthermore, the use of a cooler repository design, 
drip shield, and long-lived WP implies WP breach 
occurs when temperatures are near ambient 
temperature where thermodynamic data has been 
collected. Thus, the collection of thermodynamic 
data as a function of temperature is not necessary. 
Thermal effects on microbiological activity are 
excluded since microbiological FEP was screened 
out as a process that effects waste form 
degradation (colloid FEP 2.1.10.01.00). 
2.1.11.09.00 Thermal effects 
on liquid or twophase 
fluid flow 
in the waste 
and EBS 
Include/ 
Exclude 
WF, EBS, 
NFE 
ANL-WISMD-
000009 
Included: thermal effects on fluid flow are included 
indirectly to the extent that they influence the 
seepage flux into the drift. 
Excluded based on low consequence. Thermal 
effects on flow within the waste form are excluded 
because temperature within and outside the 
package will be fairly uniform by the time WPs fail, 
and thus thermal gradients will not significantly 
influence flow. Furthermore, temperature will be 
too low to promote two-phase flow (see in-package 
chemistry FEPs 2.1.11.10.00 and 2.1.09.08.00 on 
thermal and chemical diffusion processes, which 
are also excluded). 
2.1.11.10.00 Thermal effects 
on diffusion 
(Soret effect) in 
waste and EBS 
Exclude WF, EBS, 
NFE 
ANL-WISMD-
000009 
Excluded based on low consequence. Bounding 
analyses indicate diffusion due to temperature 
gradients within the waste form is insignificant (see 
cladding gap release FEP 2.1.02.07.00).

 2-20
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.12.01.00 Gas generation Exclude WF, EBS, 
UZ 
ANL-WISMD-
000009 
Excluded based on low consequence: Prior to 
breach of a WP, gas generation will be insignificant 
(see in-package chemistry FEP 2.1.03.06.00 on 
internal corrosion of waste container). After breach 
of a WP, the chemical influence of gas generation 
of H2 has been conservatively excluded since it 
moderates the low pH values encountered from 
sulfur release from steel (see in-package FEP 
2.1.12.03.00). 
Generation of radioactive gases in waste is also 
excluded since the inhalation dose is low relative to 
ingestion doses (inventory FEP 2.1.12.07.00). In 
addition, most physical aspects of gas generation 
such as displacement of oxygen and pressurization 
of the disposal drifts by He and H2 (in-package 
chemistry FEPs 2.1.12.02.00 and 2.1.12.03.00, 
respectively) have been excluded since gas would 
readily dissipate from the repository over geologic 
time (i.e., because fractures and fault zones are 
unsaturated, the relative permeability to gas is 
large). (Note: The relative permeability of the 
fractures and fault zones to water is lower than air 
and included in the unsaturated flow modelsee 
FEPs related to unsaturated flow model.) Only the 
physical aspect of pressurization of CSNF cladding 
is indirectly included (cladding FEP 2.1.02.20.00). 
2.1.12.02.00 Gas generation 
(He) from fuel 
decay 
Exclude WF, EBS ANL-WISMD-
000009 
Excluded based on low consequence. Radioactive 
alpha decay of actinides such as Pu, U, Th, etc., 
could result in the creation of additional He gas 
within the waste form; however, studies done for 
TSPA-VA shows increases in internal pressures 
from He to be small relative to fission gas 
pressures. Internal gas pressure inside of CSNF 
cladding is a driving force for cladding creep and 
stress corrosion cracking and is included in 
2.1.01.20.00. 
2.1.12.03.00 Gas generation 
(H2) from metal 
corrosion 
Exclude WF, EBS, 
WP 
ANL-WISMD-
000009 
Excluded based on low consequence. The amount 
of hydrogen that could be produced from metal 
corrosion will be small since the repository is likely 
to be primarily oxic since it is well connected to the 
surface. Also, because the repository is connected 
to the surface, any gas produced is expected to 
escape. The influence of H2 gas on in-package 
chemistry is negligible. It is conservative to 
exclude H2 evolution from steel corrosion as this 
limits pH depression. See cladding FEP 
2.1.02.22.00 for effect of H2 on cladding 
degradation.

 2-21
Table 2.3-2. FEPs Related to the In-Package Chemistry Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.12.04.00 Gas generation 
(CO2, CH4, H2S) 
from microbial 
degradation 
Exclude WF, EBS ANL-WISMD-
000009 
Excluded based on low probability (credibility) and 
consequence. Biological activity inside the WP is 
excluded (colloid FEP 2.1.10.01.00) since no 
organic material will be allowed inside the WP 
based on preliminary waste acceptance criteria 
(DOE 1999c, Section 4.2.3.A.3). Therefore, the 
effects of biological gases on the in-package 
chemistry are also expected to be negligible. 
2.1.12.06.00 Gas transport in 
waste and EBS 
Exclude WF, EBS ANL-WISMD-
000009 
ANL-WISMD-
000006 
Excluded based on low consequence: Screening 
studies conclude that if most gaseous 
radioisotopes, except 14C, were to be released 
through an atmospheric pathway, the potential 
dose relative to the ingestion dose would be low 
thus most gaseous radioisotopes were screened 
out (waste inventory FEP 2.1.01.01.00). However, 
in TSPA-SR, rather than transport 14C as a gas 
(which would normally be incorporated in CO2), 14C 
was transported to a receptor entirely in the 
aqueous phase (i.e., gas transport of 14C is 
included indirectly). This approach is conservative 
since less dilution occurs in aqueous transport). 
2.2.08.12.00 Use of J-13 well 
water as a 
surrogate for 
water flowing 
into the EBS 
and waste 
Include WF ANL-WISMD-
000009 
J-13 well water is used to set initial water chemistry 
inside the WP. On-going work will verify or 
improve this assumption. 
2.3.2.3 FEPs Related to the CSNF Matrix Degradation Component 
Seven FEPs relate to the CSNF Matrix Degradation Component (Table 2.3-3). The process of 
CSNF dissolution and radioisotope release has been included in TSPA analysis for a number of 
years through an regression equation of experimental results on both irradiated and unirradiated 
fuel. The use of samples of irradiated fuel implies that the potential enhanced dissolution from 
radiolysis, radiation damage, and alpha recoil has indirectly been included in the dissolution 
rates. The small differences in results and theoretical arguments, however, show that these latter 
effects are actually insignificant and can be excluded from consideration. While an unimportant 
distinction for the CSNF since experimental results are available that include these effects, 
enhanced dissolution from radiolysis, radiation damage, and alpha recoil are excluded from 
DSNF and HLW degradation as discussed below. The process of magma interacting with the 
waste has formally been included this year in the analysis for the TSPA-SR and is described in 
the Disruptive Events PMR.

 2-22
Table 2.3-3. FEPs Related to the CSNF Matrix Degradation Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
1.2.04.04.00 Magma 
interacts with 
waste 
Include WF, Tec, 
WP 
ANL-WISMD-
000009 
Included: Direct volcanic disruption of the 
repository is included as a process in TSPA-SR. 
Hence, magmatic interaction with the waste is 
plausible and included also. This FEP sets 
plausible particle sizes for the fragmented waste. 
Direct volcanic effects (i.e., radioisotopes carried 
by ash plumes from volcanic eruptions) are 
modeled as described in the Disruptive Events 
Report. 
2.1.02.02.00 CSNF 
alteration, 
dissolution, and 
radionuclide 
release 
Include WF ANL-WISMD-
000009 
CSNF degradation is included in the TSPA-SR 
analysis as a source term for the mobilization of 
contaminants. A kinetic rate equation, assuming 
saturated conditions, is used where terms of the 
coefficients have been evaluated through 
regression analysis on experimental data obtained 
over a range of temperatures and water chemistry. 
2.1.02.04.00 Alpha recoil 
enhances 
dissolution 
Exclude WF ANL-WISMD-
000009 
Excluded based on low consequence. The 
radioactive decay processes that directly increase 
waste matrix corrosion are bounded by alpharecoil 
rates. Even when assuming that all 
radioactive decays result in alpha-recoils, analysis 
shows that it will not cause significant increases to 
the degradation rate of the different waste forms 
(CSNF, DSNF, or HLW). 
2.1.08.07.05 Waste-form and 
backfill 
consolidation 
Exclude WF ANL-WISMD-
000009 
Excluded based on consequence (low 
conservative bound) since backfill and waste form 
consolidation would tend to decrease the available 
reactive surface area. The potential deleterious 
effect of maintaining water contact with the waste 
form is already conservatively bounded (with or 
without backfill) by assuming the waste package is 
fully flooded with water. 
2.1.11.05.00 Differing 
thermal 
expansion of 
repository 
component 
Include WF ANL-WISMD-
00009 
ANL-EBSMD-
000015 
Degradation of CSNF is a function of temperature 
in the CSNF Matrix Degradation Component. This 
FEP is the topic of CSNF Waste Form 
Degradation: Summary and Abstraction; influence 
of temperature is also discussed in FEPs 
2.1.11.07.00 on cladding and 2.1.11.01.00 on 
HLW.

 2-23
Table 2.3-3. FEPs Related to the CSNF Matrix Degradation Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.13.01.00 Radiolysis Exclude WF, EBS, 
WP 
ANL-WISMD-
000009 
Excluded based on low consequence. Fluid is not 
expected to contact the waste (CSNF, DSNF, or 
HLW) until gamma radiolysis has become 
negligible. Specifically for CSNF and HLW, alpha 
radiolysis is included since irradiated fuel and 
active HLW was used for some of the experiments 
from which regression equations were developed. 
It is, therefore, not necessary to include radiolysis 
explicitly in the models. 
2.1.13.02.00 Radiation 
damage in 
waste and EBS 
Exclude WF, WP, 
EBS 
ANL-WISMD-
000009 
ANL-EBSMD-
000015 
ANL-WISMD-
000010 
Excluded based on low consequence. 
Experimental data show little influence of burnup 
on degradation rate of CSNF as described in AMR, 
CSNF Waste Form Degradation Summary 
Abstraction. However, radiation damage was 
conservatively assumed for evaluating the 
solubility of Pu, Pa, and Cm when the controlling 
solid was unknown; that is, an amorphous 
controlling solid was used, thereby indirectly 
assuming radiation damage to the crystal lattice of 
the unknown controlling solid. 
2.3.2.4 FEPs Related to the CSNF Cladding Degradation Component 
Twenty FEPs relate to the CSNF Cladding Degradation Component (Table 2.3-4). These 
20 FEPs were developed based on comments received on early TSPAs (e.g., 
DSNF-TSPA-93-SNL [Rechard 1993] and DSNF-TSPA-94-SNL [Rechard 1995] and the 
TSPA-VA [DOE 1998b]). 
Several perforation mechanisms have been included in the CSNF Cladding Degradation 
Component: initial perforation in reactor before receipt of the waste, creep perforation, stress 
corrosion cracking, mechanical failure due to severe earthquakes, and localized corrosion. The 
influence of temperature on creep and stress corrosion cracking are also included. Localized 
crevice corrosion, and diffusion-controlled cavity growth, have been excluded based on FEP 
arguments. Based on arguments in an AMR dealing solely with this topic, hydride perforation 
mechanisms such as hydride embrittlement and DHC have also been excluded. 
Complete failure of the cladding after perforation is modeled through unzipping of the cladding 
in an aqueous environment7. Unzipping in a very hot, dry environment where the UO2 is rapidly 
oxidized to U3O8 is excluded based on low consequence since the required high temperature 
conditions do not exist when WP failure typically occurs. 
7 The unzipping in a wet environment is hypothetical since it has not been observed experimentally or in storage 
pools at reactors. The unzipping process conservatively bounds the slow release of radionuclides through pinhole 
perforations. This is important for release of radionuclides, such as 99Tc, which are not controlled by solubility.

 2-24
Table 2.3-4. FEPs Related to the CSNF Cladding Degradation Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.02.07.00 Gap and grain 
release of 
radionuclides 
after cladding 
perforation 
Include/ 
Exclude 
WF ANL-WISMD-
000009 
ANL-WISMD-
000007 
Included: The inventory of radionuclides located at 
gap and grain boundaries is included. This 
inventory is released either when the WP fails (for 
cladding that is already perforated) or when the 
cladding is first perforated. 
Excluded based on low consequence: Generation 
of additional gap and grain-boundary inventory 
after emplacement in the repository since 
temperatures are not high enough to promote 
sufficient diffusion. 
Interaction with impurities in the waste matrix 
which mitigate the release of the gap and grain 
boundary inventory is also excluded both because 
the reactions are thought to be limited and 
because it is conservative to do so. 
2.1.02.11.00 Waterlogged 
rods 
Exclude WF ANL-WISMD-
000008 
Excluded based on low consequence. The 
moisture in a dried fuel rod using standard drying 
processes is insufficient to cause further 
degradation of spent fuel cladding or structural 
stainless steel of container. 
2.1.02.12.00 Cladding 
degradation 
before YMP 
receives it 
Include WF ANL-WISMD-
000008 
ANL-EBSMD-
000048 
The CSNF Cladding Degradation Component 
includes a distribution with a median of 0.1% of 
fuel rods perforated during reactor operations. The 
minor additional failures during less harsh storage 
and transportation conditions are also included but 
do not substantially change the distribution of 
perforations. This FEP is the topic of AMR Initial 
Cladding Condition. 
2.1.02.13.00 General 
corrosion of 
cladding 
Exclude WF ANL-WISMD-
000008 
Excluded based on low consequence. General 
corrosion of Zircaloy cladding is very slow and will 
not be important in the first 10,000 yrs or even 
100,000 yr. 
2.1.02.14.00 Microbially 
influenced 
corrosion (MIC) 
of cladding 
Exclude/ 
Include 
WF ANL-WISMD-
000008 
While microbial activity has been screened out as 
a significant bulk process at YMP (colloid FEP 
2.1.10.01.00), it has not been excluded for 
localized effects. There is no experimental 
evidence of enhanced MIC of zirconium metal or 
alloys, however, the possibility of local depression 
of pH by microbes is included in the conservative 
local corrosion model. 
2.1.02.15.00 Acid corrosion 
of cladding from 
radiolysis 
Exclude/ 
Include 
WF ANL-WISMD-
000008 
Excluded based on low consequence. Zirconium is 
used for fuel cladding because of its resistance to 
corrosion in highly acidic environments including 
those local environments in high radiation fields 
and studies show that zirconium has excellent 
corrosion resistance to nitric acids and 
concentrated hydrogen peroxide. However, this 
process is has not been ruled out as one of the 
possible contributors to local suppression of pH 
resulting in local corrosion of cladding and is thus 
included in the local corrosion model.

 2-25
Table 2.3-4. FEPs Related to the CSNF Cladding Degradation Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.02.16.00 Localized 
corrosion of 
cladding 
through pitting 
Exclude/ 
Include 
WF ANL-WISMD-
000008 
ANL-EBSMD-
000012 
Include: While the conditions for pitting corrosion 
of the cladding (very low pH and high anion 
concentration) are not predicted for the bulk 
solution within the WP, they have not yet been 
ruled out for localized regions. Thus, a 
conservative localized corrosion model has been 
included in the TSPA-SR as discussed in cladding 
FEP 2.1.02.27.00. This FEP is the topic of AMR, 
Clad Degradation-Local Corrosion of Zirconium 
and its Alloys Under Repository Conditions 
2.1.02.17.00 Localized 
corrosion 
(crevice 
corrosion) of 
cladding 
Exclude WF ANL-WISMD-
000008 
ANL-EBSMD-
000012 
Excluded based on low probability (credibility). 
The CSNF Cladding Degradation Component 
excludes a component that accounts for localized 
corrosion of the cladding through crevice corrosion 
because zirconium does not corrode in this 
manner. This FEP is the topic of AMR, Clad 
Degradation-Local Corrosion of Zirconium and its 
Alloys Under Repository Conditions. 
2.1.02.18.00 High dissolved 
silica content of 
waters 
enhances 
corrosion of 
cladding 
Exclude WF ANL-WISMD-
000008 
Excluded based on low consequence. Silica is 
stable and is not corrosive to most materials, 
including Zircaloy. 
2.1.02.19.00 Creep rupture 
of cladding 
Include WF ANL-WISMD-
000008 
ANL-WISMD-
000007 
Perforation of Zircaloy cladding from creep rupture 
at high temperature is included in the CSNF 
Cladding Degradation Component as described in 
detail in AMR, Clad Degradation  Summary and 
Abstraction. The creep model conservatively 
bounds recent experiments on irradiated cladding. 
2.1.02.20.00 Pressurization 
from He 
production 
causes 
cladding failure 
Include WF ANL-WISMD-
000008 
Both DHC and creep perforation are driven by the 
cladding stress caused by the internal gas 
(including initial fill gas, fission product gases, and 
helium gas from alpha decay) and, thus indirectly, 
pressurization is included in the CSNF Cladding 
Degradation Component. 
2.1.02.21.00 Stress 
corrosion 
cracking (SCC) 
of cladding 
Include WF ANL-WISMD-
000008 
ANL-WISMD-
000007 
Stress corrosion cracking is modeled as a 
perforation mechanism for rods with high stresses. 
SCC is primarily relevant to iodine since SCC from 
other halogens such as chlorides is generally not 
observed. However, fluoride is considered 
independently as a localized corrosion mechanism 
(cladding FEP 2.1.02.16.00). 
2.1.02.22.00 Hydride 
embrittlement 
of cladding 
Exclude WF ANL-WISMD-
000008 
ANL-EBSMD-
000011 
Excluded based on low consequence. 
Experimental data indicate that the in-package 
environment and cladding stresses are not 
conducive to hydride cracking and embrittlement. 
This FEP is the subject of AMR, Hydride-Related 
Degradation of SNF Cladding under Repository 
Conditions.

 2-26
Table 2.3-4. FEPs Related to the CSNF Cladding Degradation Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.02.23.00 Cladding 
unzipping 
Include/ 
Exclude 
WF ANL-WISMD-
000008 
ANL-EBSMD-
000013 
ANL-EBSMD-
000014 
Included: Unzipping of cladding in an aqueous 
environment is included as the key element in 
exposing and dissolving fuel after perforation of the 
cladding. This mechanism conservatively bounds 
the slow diffusive release of radionuclides through 
pinholes of the fuel cladding. "Wet unzipping" is 
the topic of AMR, Clad Degradation - Wet 
Unzipping. 
Excluded: Unzipping of cladding in a dry 
environment is excluded based on low 
consequence. In the environment of the repository 
only a very small fraction of the fuel would undergo 
dry unzipping, and then only if the disposal 
container was breached in the first few hundred 
years, and the cladding was already perforated 
such that the UO2 would be rapidly oxidized to 
U3O8. Dry unzipping is the topic of AMR, Clad 
Degradation - Dry Unzipping. 
2.1.02.24.00 Mechanical 
failure of 
cladding 
Include WF ANL-WISMD-
000008 
The CSNF Cladding Degradation Component 
includes perforation of cladding from severe 
earthquakes (once per million years). 
2.1.02.27.00 Localized 
corrosion 
perforation of 
cladding by 
fluoride 
Include WF ANL-WISMD-
000008 
ANL-EBSMD-
000012 
The CSNF Cladding Degradation Component 
includes a component that accounts for localized 
corrosion of the cladding through corrosion by 
fluorides flowing into the WP. This FEP is the topic 
of AMR, Clad Degradation Local Corrosion of 
Zirconium and its Alloys Under Repository 
Conditions. 
2.1.02.28.00 Diffusioncontrolled 
cavity growth 
(DCCG) 
concerns 
Exclude WF ANL-WISMD-
000008 
ANL-WISMD-
000007 
Excluded based on low probability. Diffusioncontrolled 
cavity growth as a mechanism to fail 
Zircaloy cladding has not been observed 
experimentally. 
Excluded based on low probability (credibility): 
NRC once required license applicants for dry 
storage of CSNF to assume DCCG to evaluate dry 
storage designs. Recent literature does not 
support the use of this specific creep mechanism 
for zirconium materials since it has not been 
observed experimentally (voids and cavities are 
rarely seen in irradiated Zircaloy). Current NRC 
Interim Staff Guidance permits license applicants 
to use other creep models. Although DCCG is 
excluded as a specific type of creep rupture 
mechanism, creep rupture, as a general cladding 
perforation process, is included (see cladding FEP 
2.1.02.19.00).

 2-27
Table 2.3-4. FEPs Related to the CSNF Cladding Degradation Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.07.01.00 Rockfall 
(Large Block) 
Exclude WF ANL-WISMD-
000009 
ANL-WISMD-
000008 
Excluded based on low consequence. Cladding 
perforation from the collapse of the WP with a 
large block rockfall is not considered since 
cladding perforation from other modes occurs 
before the WP can collapse (see also FEP 
2.1.02.24.00). 
2.1.09.03.00 Volume 
increase of 
corrosion 
products 
Include/ 
Exclude 
WF, WP ANL-WISMD-
000009 
Included: The underlying driving mechanism 
assumed for wet unzipping is the volume increase 
as the UO2 forms secondary minerals, and thus 
this FEP is included in the CSNF Cladding 
Degradation Component. 
Excluded based on low consequence. Dry 
oxidation of CSNF is not expected to be a 
significant contributor to the results since it can 
only occur when both the WP and cladding fail in 
the first 300 years (see cladding FEP 
2.1.02.23.00). 
2.1.11.07.00 Thermallyinduced 
stress 
changes in 
waste and EBS 
Include EBS, WF ANL-WISMD-
000009 
ANL-WISMD-
000007 
Included: Thermally induced stress changes in the 
CSNF cladding influences creep rupture and SCC 
perforations in the CSNF Cladding Degradation 
Component. Furthermore, temperature differences 
on different fuel assemblies in the cross-section of 
the WP are considered in the first 1000 yr. 
Degradation of the waste matrix of CSNF and 
HLW is also a function of temperature (CSNF 
matrix FEP 2.1.11.05.00 and HLW FEP 
2.1.11.01.00). 
2.3.2.5 FEPs Related to the DSNF Degradation Component 
Three of the FEPs related to CSNF Degradation Component (Section 2.3.2.3) also apply here 
(radiolysis, alpha recoil, and radiation damage). These three radiation effects are included by 
conservatively bounding the degradation of rate of experiments on irradiated N-Reactor fuel. Six 
additional FEPs specifically related to the DSNF Degradation Component are listed here 
(Table 2.3-5). Four of these FEPs relate to the potentially increased reactivity of some types of 
the DSNF. However, the additional reactivity is of low consequence and so these four FEPs are 
screened out. One FEP relates to the degradation of cladding for DSNF, but is conservatively 
excluded by not including cladding performance for DSNF except for the naval SNF, whose 
analysis will account for the performance of the cladding.

 2-28
Table 2.3-5. FEPs Related to the DSNF Degradation Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.02.01.00 DSNF 
degradation, 
alteration, and 
dissolution 
Include/ 
Exclude 
WF ANL-WISMD-
000009 
ANL-WISMD-
000004 
Included: DSNF and its degradation are included 
in TSPA-SR. The largest component of the DSNF 
is the metallic N-Reactor fuel. A constant rate that 
conservatively bounds the temperature varying 
rate of metallic uranium is used since the corrosion 
characteristics of uranium metal, in turn, 
conservatively bound the degradation of all other 
DSNF. (The inventory, however, is the weighted 
mass average of all the ~250 types of DSNF 
[waste inventory FEP 2.1.01.01.00].) 
Excluded based on low consequence: Time 
dependence of available surface area for 
degradation or release of radioisotopes (see DSNF 
cladding FEP 2.1.02.25.00). 
2.1.02.08.00 Pyrophoricity Exclude WF ANL-WISMD-
000009 
Excluded based on low consequence. The 
performance on the DSNF waste form itself is not 
affected since (except for naval SNF) no credit for 
cladding is assumed and the degradation rate of 
the matrix is already conservatively bounded. 
2.1.02.08.04 Flammable gas 
generation from 
DSNF 
Exclude WF ANL-WISMD-
000009 
Excluded based on low consequence. The 
chemical reaction of U/Th carbide with water could 
produce CO2 and hydrocarbon gases. The major 
constituent of the gas is methane; minor 
constituents are ethane, ethylene, and acetylene. 
Only DSNF from the Peach-Bottom Core 1 has 
uncoated U/Th carbide pellets and thus the 
potential to generate flammable gases over a short 
period of time. However, the Peach Bottom core 1 
is in only ~100 WPs out of ~3900 DSNF WPs and 
of ~11,800 WPs. Also, relatively good connection 
with the surface through fractures and fault zones 
would eventually disperse any flammable gas in 
the repository before explosive concentrations 
could be obtained (see in-package chemistry gas 
generation FEP 2.1.12.01.00). 
2.1.02.25.00 DSNF cladding 
degradation 
Exclude WF ANL-WISMD-
000009 
Excluded based on low consequence 
(conservative bound): No credit is taken for DSNF 
cladding (with the exception of naval SNF 
cladding). More than 80% of the DSNF is from the 
N-Reactor and is in poor condition; up to 50% may 
already be perforated; hence, all the cladding is 
conservatively assumed to be perforated. The 
cladding is conservatively neglected since the 
bounding alteration rate of the DSNF fuel matrix is 
so high and the radioisotope inventory is so small. 
The rapid degradation of DSNF fuel influences the 
in-package chemistry pH in the first 1000 yr (inpackage 
chemistry codisposal FEP 2.1.01.02.00).

 2-29
Table 2.3-5. FEPs Related to the DSNF Degradation Component (Continued) 
FEP Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.11.03.00 Exothermic 
reactions and 
other thermal 
effects in waste 
and EBS 
Exclude EBS, WF ANL-WISMD-
000009 
Excluded based on low consequence. The 
possible temperature rise in a disposal container 
from exothermic degradation of DSNF is 
inconsequential in comparison to heat generated 
by radioactive decay. The fixed, conservative rate 
bounds by at least an order of magnitude the 
maximum degradation rate observed and thus also 
bounds any thermal effects on waste degradation. 
2.1.12.08.00 Gas explosions Exclude EBS, WF ANL-WISMD-
000009 
Excluded based on low probability. Because of the 
absence of O2 and water, there is a very low 
probability of explosion within the canister until the 
WP and DSNF canister is breached. After the 
canister is breached, generation of flammable 
gases has been excluded (see DSNF FEP 
2.1.02.08.04). Furthermore, any gas produced will 
disperse into the drift. The permeability of Yucca 
Mountain provides adequate connection to the 
surfaces such that flammable/explosive gases 
would be diluted and/or dispersed before they 
could reach explosive concentrations (see inpackage 
chemistry gas generation FEP 
2.1.12.01.00) 
2.3.2.6 FEPs Related to the HLW Degradation Component 
Four FEPs specifically relate to the HLW Degradation Component (Table 2.3-6). One primary 
FEP and its underlying secondary FEPs deal with the enhanced degradation that may occur if 
extensive phase separation or glass recrystallization occur in the encapsulating glass; however, 
production controls will prevent significant initial phase separation. Furthermore, temperatures 
in the repository are low relative to the melting point of the glass such that extensive 
recrystallization will not occur in the glass. The HLW Degradation Component explicitly 
includes the effect of temperature on HLW glass degradation. Another FEP deals with the 
proper reactive surface area to use when evaluating the degradation rate of the glass. The HLW 
Degradation Component bound the reactive surface area by multiplying the geometric surface 
area by a very conservative, but constant cracking factor of 20.

 2-30
Table 2.3-6. FEPs Related to the HLW Degradation Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) 
Reason for 
Include/Exclude Decision 
2.1.02.03.00 Glass 
degradation, 
alteration, and 
dissolution 
Include/ 
Exclude 
WF ANL-WISMD-
000009 
Included: HLW degradation is included in the 
TSPA-SR analysis as a source term for the 
congruent mobilization of contaminants. 
Degradation rate is dependent on pH of inpackage 
water chemistry. The effects of minor 
phase separation are subsumed in the degradation 
model since parameters for the model 
conservatively bound dissolution experiments on 
samples where minor phase separation might have 
occurred. 
Excluded based on low probability (credibility): 
Extensive phase separation 
(precipitation/coprecipitates/solid solution phase) is 
excluded because phase separation is controlled 
during production. 
Excluded based on low consequence: Extensive 
selective leaching is excluded since the rate of 
degradation used for the glass matrix is an upper 
bound on the actual rate of release and, therefore, 
bounds any additional consequence due to 
selective leaching. 
2.1.02.05.00 Glass cracking 
and surface 
area 
Include WF ANL-WISMD-
000009 
ANL-EBSMD-
000016 
The thermal stress during cooling increases the 
surface area accessible to water through cracking 
beyond the geometric surface area; a robust 
container and cool temperatures, relative to the 
transition temperature of glass, prevent extensive 
increases in this initial surface area during 
disposal. Nonetheless, a very conservative 
cracking surface area-enhancement factor of 20 is 
used to set the surface area accessible to water for 
degradation. 
2.1.02.06.00 Glass 
recrystallization 
Exclude WF ANL-WISMD-
000009 
Extensive recrystallization excluded based on low 
probability (credibility). Controls are to be 
implemented as part of the waste production to 
ensure that extensive glass recrystallization and 
phase separation will not occur. 
2.1.11.01.00 Heat output / 
temperature in 
waste and EBS 
Include WF, EBS, 
NFE 
ANL-WISMD-
000009 
Included: Decay heat is a major issue in repository 
design, where high loading densities and high 
temperatures (~96C) are intended to be part of 
the waste isolation scheme. Degradation of HLW 
is a function of temperature. See also CSNF FEP 
2.1.11.05.00 and Cladding FEP 2.1.11.07.00.

 2-31
2.3.2.7 FEPs Related to the Dissolved Radioisotope Concentration Component 
Many processes influence the dissolved concentration of radionuclides in the Dissolved 
Radioisotope Concentration Component. However, most of those processes have been discussed 
separately in the In-Package Chemistry Component since these processes also affect other model 
components. Here four FEPs are listed that have a more direct connection with the dissolved 
radionuclide concentration (Table 2.3-7). First, solubility control based on pure phases has been 
and continues to be included in the TSPA-SR analysis. Although a few radionuclides such as 
Np may be incorporated into the structure of phases of other minerals (primarily uranium) 
that form during degradation of the waste such that the solubility of these other minerals control 
the concentration of the radioisotope, these effects have been conservatively excluded. 
Complexation of radionuclides by organic ligands has been excluded because organic material is 
generally prohibited from the repository and the incidental amounts of organic material that may 
inadvertently occur cannot alter the solubility of significant amounts of radionuclides. 
Table 2.3-7. FEPs Related to the Dissolved Radioisotope Concentration Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.04.00 Radionuclide 
solubility, 
solubility limits, 
and speciation 
in the waste 
form and EBS 
Include WF ANL-WISMD-
000009 
A controlling phase is used to develop a dissolved 
concentration limit for each of the transported 
radioactive elements. These limits are expressed 
as an empirical equation, distribution, or bounding 
constant, depending on the element and available 
data. The concentration limit is used to bound the 
amount of a radionuclide that can be mobilized by 
the Dissolved Radioisotope Concentration 
Component. 
2.1.09.10.00 Secondary 
phase effects 
on dissolved 
radionuclide 
concentrations 
at the waste 
form 
Exclude WF ANL-WISMD-
000009 
ANL-EBSMD-
000019 
Excluded based on beneficial consequences 
(conservative bound). The solubility of many 
radionuclides depends only on pure phases; 
however, a few radionuclides such as Np may be 
incorporated into other minerals (primarily uranium 
minerals) that form during degradation of the 
waste. These other minerals control the 
concentration of the radioisotope. These effects 
have been conservatively excluded; hence 
solubility of Np is somewhat greater than in TSPAVA. 
2.1.09.12.00 Rind (altered 
zone) formation 
in waste, EBS, 
and adjacent 
rock 
Include/ 
Exclude 
EBS, NFE 
WF 
ANL-WISMD-
000009 
Included: For determining the radioisotope 
concentration, the Dissolved Radioisotope 
Concentration Component assumes that the 
volume of water available for dissolution in the 
waste form cell is equal to the pore space of the 
rind of alteration products that forms as the UO2 is 
converted into secondary minerals. 
Excluded (conservative bound) based on beneficial 
consequences: Rind or altered zone may tend to 
prevent advective flow past the waste and thus 
reduce release of radionuclides. This effect has 
been conservatively excluded.

 2-32
Table 2.3-7. FEPs Related to the Dissolved Radioisotope Concentration Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.13.00 Complexation 
by organics in 
waste and EBS 
Exclude EBS 
WF 
ANL-WISMD-
000009 
Excluded based on low probability (credibility). 
Based on the preliminary waste acceptance criteria 
(DOE 1999c, Section 4.2.3.A.3), organic material 
will be excluded from the radioactive waste. 
Hence, sources of organic material will not be 
present in waste; only small amounts could occur 
and even then it will be isolated incidents. For 
example, organic complexes have not been 
associated with Yucca Mountain waters, now or in 
the past. Furthermore, drift temperatures are 
sufficient to drive off many volatile organics, should 
they occur. 
2.3.2.8 FEPs Related to the Colloidal Radioisotope Concentration Component 
Sixteen FEPs relate to the Colloidal Radioisotope Concentration Component (Table 2.3-8). 
Three types of colloids were included: those already present in the groundwater, those formed 
during corrosion of the WP, and those formed during degradation of the waste. Condensed Pu 
polymer colloids were excluded since they have not been observed in fuel or glass dissolution 
tests. Biological activity was screened out, and so microbial colloids were also excluded. 
Transport and filtration of colloids inside the WP were conservatively excluded. 
Table 2.3-8. FEPs Related to the Colloidal Radioisotope Concentration Component 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.05.00 In Package 
Sorption 
Include/ 
Exclude 
WF ANL-WISMD-
000009 
ANL-WISMD-
000012 
Included: Sorption on mobile colloidal material is 
included. 
Excluded based on low consequence 
(conservative bound): Sorption on stationary 
material inside the waste package is excluded. 
This is a conservative exclusion since sorption 
decreases the release rate of radioisotopes. 
2.1.09.14.00 Colloid 
formation in 
waste and EBS 
Include WF, EBS ANL-WISMD-
000012 
A colloid source term has been developed for the 
Waste Form Degradation Model of the TSPA-SR 
analysis using experimental data produced from 
YMP investigations. 
2.1.09.15.00 Formation of 
true (real) 
colloids in 
waste and EBS 
Exclude WF, EBS ANL-WISMD-
000012 
Excluded based on low consequence: true colloids 
would be expected to dissolve when the solution is 
diluted. 
2.1.09.16.00 Formation of 
pseudo-colloids 
(natural) in 
waste and EBS 
Include WF, EBS ANL-WISMD-
000012 
The Colloidal Radioisotope Concentration 
Component assumes pseudo-colloids may form 
from groundwater colloids and can reversibly sorb 
Am, Pu, and other radionuclides.

 2-33
Table 2.3-8.FEPs Related to the Colloidal Radioisotope Concentration Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.16.01 Colloidal 
phases 
produced by 
coprecipitation 
in the waste 
package or 
EBS. 
Include WF ANL-WISMD-
000012 
The Colloidal Radioisotope Concentration 
Component assumes colloids produced from 
degradation of HLW glass incorporate Am and Pu 
radioisotopes irreversibly. The assumption of 
irreversibility is a bounding approximation. 
2.1.09.17.00 Formation of 
pseudo-colloids 
(corrosion 
products) in 
waste and EBS 
Include WF, EBS ANL-WISMD-
000012 
The Colloidal Radioisotope Concentration 
Component assumes colloids are produced from 
corrosion of the disposal container and other 
material inside the container and reversibly sorb 
Am and Pu and other radionuclides. These colloids 
are conservatively assumed to be similar to natural 
colloids (see colloid FEP 2.1.09.16.00). 
2.1.09.18.00 Microbial colloid 
formation in the 
waste and 
transport in 
EBS. 
Exclude WF, EBS ANL-WISMD-
000012 
Excluded based on low consequence 
(conservative bound). Microbial activity has been 
screened out as a FEP as concerns the waste 
form (colloid FEP 2.1.10.01.00). However, even if 
microbial activity were present, it would tend to 
increase colloid size over time, which would result 
in increased gravitational settling and filtration. 
2.1.09.19.00 Colloid sorption 
and transport in 
the waste and 
EBS 
Exclude WF, EBS ANL-WISMD-
000012 
Exclude based on low consequence (conservative 
bound). The Colloidal Radioisotope Concentration 
Component assumes colloids reversibly sorb or 
irreversibly incorporate radionuclides. However, 
the modeling component only acts as a sourceterm 
and conservatively neglects the transport of 
these colloids inside the WP. Filtration is also 
excluded (see colloid FEP 2.1.09.20.00). 
2.1.09.20.00 Colloid filtration Exclude WF, EBS ANL-WISMD-
000012 
Exclude based on low consequence (conservative 
bound). The conservative assumption is made 
that all colloids produced within the WP (the 
calculated colloid source term) exit the WP and 
enter the drift/EBS. Colloid transport time is also 
excluded (see colloid FEP 2.1.09.19.00). 
2.1.09.21.00 Suspensions of 
particles larger 
than colloids 
Exclude EBS, SZ ANL-WISMD-
000012 
Excluded based on low consequence. It is unlikely 
that larger-than-colloid particles will have access to 
a sufficient number of vertical or subvertical 
fractures whose apertures permit their passage in 
significant quantities. The relatively small quantity 
of particles that may make it through the UZ would 
encounter low groundwater velocities in the SZ, 
which would likely result in the particles settling 
and becoming immobile. 
2.1.09.22.00 Colloidal 
sorption at the 
groundwater 
interface 
Exclude WF ANL-WISMD-
000012 
Excluded based on low consequence 
(conservative bound). Although colloids may be 
retained at the air-water interface in unsaturated 
conditions, neglecting this phenomena is 
conservative; thus, the conceptual model of waste 
package uses a fully saturated mixing cell.

 2-34
Table 2.3-8.FEPs Related to the Colloidal Radioisotope Concentration Component (Continued) 
FEP 
Number FEP Title 
Include/ 
Exclude 
Process 
Model 
Report 
(PMR) 
AMR 
Document 
Identifier 
(DI) Reason for Include/Exclude Decision 
2.1.09.23.00 Colloidal 
Stability and 
concentration 
dependence on 
aqueous 
chemistry 
Include WF ANL-WISMD-
000012 
The Colloidal Radioisotope Concentration 
Component develops (based on experimental 
data) stability curves as a function of pH and ionic 
strength. 
2.1.09.24.00 Colloidal 
diffusion 
Include WF ANL-WISMD-
000012 
The Colloidal Radioisotope Concentration 
Component uses a diffusion coefficient of 10-2 i.e., 
the diffusion coefficient of colloids is a factor of 100 
less than the diffusion coefficient of dissolved 
radionuclides. 
2.1.09.25.00 Colloidal 
gravitational 
settling 
Exclude WF ANL-WISMD-
000012 
Excluded based on low consequence 
(conservative bound). The conservative 
assumption is made that gravitational settling of 
radionuclide-bearing colloids does not occur, but 
instead all of the colloids (if stable) leave a 
breached waste package and can reach the 
accessible environment. Most likely, some percent 
of the colloids will settle out during the transport 
process and reduce the amount of radionuclides 
reaching the accessible environment. 
2.1.10.01.00 Biological 
activity in waste 
and EBS 
Exclude WF, EBS, 
WP 
ANL-WISMD-
000012 
Excluded based on low probability (credibility) and 
low consequence. Since organic matter is 
excluded from the waste based on the preliminary 
waste acceptance criteria (DOE 1999c, Section 
4.2.3.A.3), preliminary analysis shows that 
sufficient quantities of microbes will not be 
available to promote colloid mobility or adversely 
accelerate corrosion rates significantly. 
2.1.13.03.00 Mutation Exclude EBS ANL-WISMD-
000009 
Excluded based on low consequence. General 
principles of population genetics indicate that most 
mutations are either neutral or deleterious to the 
fitness of an organism and, in the absence of 
strong natural selection, are unlikely to produce 
any definite change in the phenotypes of the 
organisms.

 2-35
2.3.3 Relationship of Model Components, FEPs, and Factors 
The model components listed in Section 2.2 are closely aligned with the principal and other 
factors that affect repository performance. Table 2.3-9 shows the correspondence. Note that 
FEPs 2.1.02.09.00 and 2.1.09.02.00 are related to two different factors. 
Table 2.3-9. Relationship of Model Components to Factors 
Model Component Factor 
Radioisotope Inventory (all FEPs) (none) 
In-Package Chemistry (FEPs 2.1.01.02.00, 2.1.02.09.00, 
2.1.02.10.00, 2.1.03.06.00, 2.1.08.10.00, 2.1.09.01.00, 
2.1.09.02.00, 2.1.09.06.00, 2.1.09.07.00, 2.1.09.11.00, 
2.1.11.04.00, 2.1.11.08.00, 2.1.12.01.00, 2.1.12.02.00, 
2.1.12.03.00, 2.1.12.04.00, 2.2.08.12.00) 
Environments within the waste package 
In-Package Chemistry (FEPs 2.1.01.04.00, 2.1.02.09.00, 
2.1.08.07.00, 2.1.08.08.00, 2.1.09.02.00, 2.1.09.08.00, 
2.1.09.09.00, 2.1.11.09.00, 2.1.11.10.00, 2.1.12.06.00) 
In-package radionuclide transport 
CSNF Matrix Degradation (all FEPs) CSNF waste form performance 
CSNF Cladding Degradation (all FEPs) CSNF waste form performance 
DSNF Degradation (all FEPs) DSNF, naval SNFa, Pu-disposition waste form 
performance 
HLW Degradation (all FEPs) HLW glass waste form performance 
Dissolved Radioisotope (all FEPs) Solubility limits of dissolved radionuclides 
Colloidal Radioisotope Concentration (all FEPs) Colloid-associated radionuclide concentrations 
NOTE: aFor purposes of performance assessment, Naval SNF will be represented by CSNF. 
2.4 INFLUENCE OF DESIGN CHANGES ON WASTE FORM DEGRADATION 
MODEL 
The design of the repository continues to evolve in preparation for the future license application. 
In general, these design changes can directly influence the screening arguments for FEPs and 
their inclusion in or exclusion from the waste form degradation model. The elimination of 
backfill is an important design change that has been made after the development of the current 
Waste Form Degradation Model. The primary effect of the elimination of backfill is the 
decrease of peak temperatures inside the WP, which is beneficial. For example, the temperature 
decrease (1) reduces the chance for creep rupture and stress corrosion cracking of CSNF 
cladding; (2) reduces the degradation rates of the CSNF and HLW matrices; (3) improves the 
applicability of the current data for in-package chemistry; and (4) decreases the solubility of 
uranium. However, design change to eliminate backfill does not affect the Waste Form 
Degradation Model because temperature is explicitly included as a model variable. That is, the 
model is an explicit function of the surface temperature of the waste package (Figure 1.5-1), so 
any changes in the surface temperature of the waste package because of the design change are 
automatically included.

 2-36
INTENTIONALLY LEFT BLANK

 3-1
3. MODELS AND ABSTRACTIONS 
3.1 RADIONUCLIDE INVENTORY COMPONENT 
The function of the radioisotope inventory abstraction component is to estimate the inventory of 
those radionuclides most important to human dose. The inventory abstraction component is 
input for the waste form degradation models and is developed from a series of steps that starts 
with radioisotope inventories of various spent nuclear fuel assemblies and HLW then estimates 
the radioisotope inventory when packaged in disposal containers. Three important aspects of the 
radionuclide inventory are (1) selecting the most important radionuclides for human dose out of 
the few hundred found within the waste, (2) obtaining the radioisotope inventories of various 
wastes, and (3) grouping the fuels into the waste packages selected for modeling in the TSPA-SR 
analysis. 
Using radionuclide activities for CSNF assemblies, DSNF canisters, and HLW canisters, the 
radionuclide inventory component provides an estimate for activities in containers destined for 
disposal in the potential Yucca Mountain repository as shown in Figure 3.1-1. 
The inventory abstraction is described in the Inventory Abstraction AMR (CRWMS 
M&O 2000f) and the eleven supporting calculations (Figure 3.1-2). Three sources were used for 
inventory data: the commercial utilities for CSNF (CRWMS M&O 1999d), the DOE NSNFP for 
DSNF (DOE 1999b), and the Yucca Mountain EIS program for the HLW, mixed oxide 
fuel (MOX), and plutonium ceramic (DOE 1999a). From this radioisotope inventory, the most 
important radionuclides for human dose were evaluated. Arrival scenarios were developed for 
CSNF, and the inventory was assigned to WP configurations. Average and bounding inventories 
were developed for each package configuration recommended for the repository. Then, the 
package-specific radionuclide activities were combined using the number of WPs in each group 
as a weighting factor to get the radionuclide activities in each allocation category. 
3.1.1 Description 
3.1.1.1 Radionuclides Important for Total System Performance Assessment 
The relative importance of individual radionuclides for human inhalation and ingestion doses 
was evaluated for several waste types, time frames, and release scenarios. In this evaluation, the 
effects of inventory abundance, radionuclide longevity, element solubility, and element transport 
affinity were considered. To address inventory abundance, eight waste types were examined.9 
To address radionuclide longevity, the fuels were evaluated between 100 and 1 million years 
after repository closure. The elements were evaluated in two solubility groups, the relatively 
soluble and the relatively insoluble (Am, Cm, Zr, Th, Nb, Pa, and Sn) and three transport affinity 
groups: (1) highly sorbing, (2) moderately sorbing, and (3) slightly to non-sorbing. The isotopes 
within each group were compared to one another for relative importance. Three release 
scenarios were considered: nominal case, human intrusion, and direct volcanic release. Two 
time frames were considered: 100 to 10,000 years and 100 to 1 million years. 
9 Average and bounding types for each of PWR, BWR, DSNF, and HLW

 3-2
The set of important isotopes was different for each scenario and time frame. For the first 
10,000 years, 99Tc and 129I are normally the primary contributors to dose (DOE 1998c, Figure 
4-29). For a direct release from a disruptive event scenario out to 10,000 years, 90Sr, 137Cs, 
227Ac, 229Th, 231Pa, 232U, 233U, 234U, 238Pu, 239Pu, 240Pu, 241Am, 243Am were screened in. These 
are the isotopes that contribute most to the dose when release is not mitigated by either solubility 
or transport. For a nominal release and human intrusion scenario out to 10,000 years 14C, 99Tc, 
129I, 227Ac, 229Th, 232U, 233U, 234U, 236U, 238U, 237Np, 238Pu, 239Pu, 240Pu, 241Am, 243Am were 
screened in. By modeling the plutonium isotopes (238Pu, 239Pu, 240Pu), the americium isotopes 
(241Am, 243Am), 229Th, and 227Ac, doses that could result from colloidal transport of radioactive 
material to the biosphere will be adequately represented. By modeling 14C, 99Tc, 129I, the 
uranium isotopes (232U, 233U, 234U, 236U, 238U), and 237Np, doses that could result from transport 
of solutes, either by fracture flow or matrix diffusion, will be adequately represented. In 
addition, 63Ni, 90Sr and 137Cs are screened in for a human intrusion scenario because the event 
could occur as early as 100 years after repository closure. For the time period from 10,000 to 1 
million years, 210Pb, 226Ra, 230Th, and 242Pu are screened in for all of the scenarios, and 231Pa is 
screened in for the human intrusion and nominal release scenarios. The result is 24 isotopes 
recommended for modeling in the TSPA-SR analysis and TSPA-FEIS. The 24 isotopes are 
shown in Table 3.1-1, along with the isotope selection from previous performance assessments. 
For TSPA 1993 (Wilson et al. 1994) and 1995 (CRWMS M&O 1995), all radionuclides 
contributing to 99.99 percent of the potential dose at any time from 1,000 to 1 million years were 
retained for the inventories. For TSPA-SR analysis, all radionuclides contributing to 95 percent 
of the potential dose at any time from 100 to 1 million years were retained for the inventories. 
Thus, radionuclides that contribute to the last five percent of the dose estimate were eliminated 
from consideration in the TSPA-SR analysis. 
For the TSPA-VA (CRWMS M&O 1998b), a smaller number of representative radionuclides 
were chosen. A radionuclide was included in the TSPA-VA (DOE 1998b) if it had: (1) a high 
solubility, (2) a low sorption affinity, (3) a significant inventory,10 (4) a high dose conversion 
factor, and (5) a long half-life. In addition, some radionuclides were included based on previous 
experience (1993 TSPA calculations [Wilson et al. 1994], 1995 TSPA calculations [CRWMS 
M&O 1995], and scoping calculations) and the experience of other organizations (NRC 
performance assessments [Wescott et al. 1995]). 
10 Including the inventory generated by decay of a parent radionuclide

 3-3
Table 3.1-1. Isotope Selection 
Isotope 
TSPA-SRa & 
Final EIS 2000 
TSPA 
1993b 
TSPA 
1995c 
TSPA-VA 
1998d 
NRC Iterative 
Performance 
Assessment 1995e 
227Ac X X X 
108mAg X 
241Am X X X X 
242mAm X X 
243Am X X X X 
14C X X X X X 
36Cl X X 
243Cm X 
244Cm X X 
245Cm X X X 
246Cm X X X 
135Cs X X X 
137Cs X X X 
129 I X X X X X 
93Mo X 
93mNb X 
94Nb X X X 
59Ni X X X 
63Ni X X X 
237Np X X X X X 
231Pa X X X X 
210Pb X X X X 
107Pd X X 
238Pu X X X 
239Pu X X X X X 
240Pu X X X X 
241Pu X X 
242Pu X X X X 
226Ra X X X X 
228Ra X 
79Se X X X X 
151Sm X X 
121mSn X 
126Sn X X 
90Sr X X 
99Tc X X X X X 
229Th X X X 
230Th X X X X 
232Th X 
232U X X 
233U X X X 
234U X X X X X 
235U X X 
236U X X X 
238U X X X X 
93Zr X X 
Sources: a CRWMS M&O 2000f, Section 7.1 
b Wilson et al. 1994 
c CRWMS M&O 1995 
d DOE 1998b 
e Wescott et al. 1995

 3-4
For the Iterative Performance Assessment (IPA) (Wescott et al. 1995), the NRC screened 
radionuclides to include only the major contributors to cumulative release and dose. A 
radionuclide was retained in the inventory if, in preliminary calculations, it contributed more 
than one percent of the EPA cumulative release limit for that radionuclide.11 The screening 
analysis also checked the maximum dose to a farm family to see if any of the radionuclides that 
might have been screened out on the basis of cumulative release should have been kept on the 
basis of dose. 
The differences between the isotope selection in these PAs are primarily due to: (1) the changing 
regulations (dose - cumulative release - groundwater protection; 10,000 years - 1 million years, 
groundwater - human intrusion - volcanic releases), (2) inventory data relied upon, and (3) the 
screening techniques. 
3.1.1.2 Commercial Spent Nuclear Fuel Inventory 
Commercial nuclear power plants use a variety of fuels and fuel configurations in their reactor 
cores to generate power. The predominant fuel is enriched uranium dioxide, but a 
plutonium/uranium mix is also planned for use in commercial reactors to dispose of excess 
plutonium from the government inventory. Fuel pellets are packed into fuel rods (which vary in 
size depending on the application), and fuel rods (clad in Zircaloy or stainless steel) are bundled 
into assemblies. The number of fuel rods per assembly and the number of assemblies in a reactor 
core vary depending on the reactor design. 
Once a reactor fuel has been irradiated to the extent that it can no longer effectively sustain a 
chain reaction, it is removed from the reactor and becomes spent nuclear fuel. Its isotopic 
composition at that point depends on the initial enrichment of the fuel, the reactor configuration 
(pellet size, fuel rod size, assembly layout, and other parameters), and the extent of irradiation 
(called burnup). Once removed from the core, the fuel is placed in storage and it ages. 
Almost 230,000 CSNF assemblies will need to be disposed, and each assembly, depending on 
the reactor configuration, initial fuel enrichment, burnup, and the age of the waste (time in 
storage), will have a unique isotopic composition. The radionuclide inventory abstraction 
collects this information and synthesizes it into a form that can be modeled in TSPA-SR analysis. 
A 1995 data submittal from the commercial utilities provided the basic information from which 
the TSPA-SR analysis inventory for CSNF was developed. In 1995, the utilities supplied 
historical information about reactor assembly discharges up through December 1995, and they 
provided five-cycle forecasts for assembly discharges from their reactors. With this information, 
a design basis waste stream was developed (CRWMS M&O 1999d), and forecasts for assembly 
discharges over the lifetime of each commercial power reactor were developed. 
For the base case repository design of 70,000 MTHM, three alternative schedules were 
developed for moving the CSNF assemblies out of storage and shipping the assemblies to Yucca 
Mountain. The schedules, called arrival scenarios, include the year of receipt for each shipment, 
the number of assemblies in each shipment, the type of fuel in each shipment (pressurized water 
11 From 40 CFR 191 (now obsolete)

 3-5
reactor (PWR) versus boiling water reactor (BWR), and the enrichment/burnup characteristics of 
the fuel. 
Radionuclide activities for each assembly in the waste stream were estimated, and the WP 
configuration that could accommodate the assembly based on its potential criticality level was 
determined. The result was a grouping of the 230,000 CSNF assemblies into five proposed WP 
configurations. For each group, average and bounding assembly radionuclide activities were 
calculated. 
3.1.1.3 U.S. Department of Energy Spent Nuclear Fuel and High-Level Waste 
For the most part, DSNF (with the exception of the naval SNF) and HLW are planned to be 
disposed together in codisposal waste packages. Therefore, they are discussed together here. 
The DSNF consists of more than 250 distinct types of spent fuel, and much like CSNF, 
radionuclide inventories for defense fuels will vary widely depending on the history of the fuel. 
The NSNFP grouped the fuels into 11 groups (DOE 1999b). DOE fuels will be packaged in three 
types of canisters before they are shipped to Yucca Mountain; short, long, and multi-container 
overpack (MCO). Similarly, the naval fuels will be packaged in two types of canisters: naval 
long and naval short (Dirkmaat 1997, Appendix F, Attachment, p. 1). For analysis, the fuels are 
grouped by canister type and average and bounding per canister radionuclide inventories were 
calculated. 
The HLW in storage at DOE sites is the result of reprocessing SNFs (some CSNF and some 
DSNF). The proposed technology for immobilization of HLW is vitrification in a borosilicate 
glass. The vitrified waste will be placed in one of two canister types (long and short). A small 
amount of HLW glass has been produced at the West Valley Demonstration Project (WVDP) in 
New York. Production of HLW has started at the Savannah River Site (SRS) and HLW will 
eventually be produced and stored at two other sitesthe Hanford Reservation (HR) and the 
Idaho National Engineering and Environmental Laboratory (INEEL). Because the fuels 
reprocessed at each of these sites differ, the radionuclide inventory of the HLW and resultant 
glass product will vary slightly among the sites. 
The data source for the HLW source terms, which include radionuclide inventory, decay heat, 
and radiation sources due to gamma rays and neutrons, is the response to the EIS data call as 
described in DOE (1999a). The sites included in the data call are the HR, SRS, INEEL, and 
WVDP. HLW fuels will be packaged in three types of canisters before they are shipped to Yucca 
Mountain: short, long, and Pu disposition. The information from the data call was used to 
calculate average and bounding per canister inventories. 
The average radionuclide activity from DSNF for one of these WPs is the number of canisters 
times the average per canister radionuclide activity calculated. The average radionuclide activity 
from HLW for one of these WPs is the number of canisters times the average per canister 
radionuclide activity calculated. The radionuclide activity for the DSNF allocation group is an 
average, weighted by the number of packages in each group, over the six WP configurations. 
Similarly, the radionuclide activity for the HLW allocation category is an average, weighted by 
the number of packages in each group.

 3-6
The naval SNF, by agreement, is conservatively treated separately using average CSNF 
inventory and degradation characteristics. 
3.1.1.4 Radionuclide Masses in Allocation Categories for Total System Performance 
Assessment for Site Recommendation 
The waste types, allocations, and waste packages for commercial spent nuclear fuel, DOE spent 
nuclear fuel, high-level radioactive waste, and plutonium disposition waste are shown in 
Figure 3.1-1. In the TSPA model, over 250 types of DOE spent nuclear fuels and HLWs are 
represented as being packaged in the ten types of canisters listed in Table 3.1-2. These canisters 
and the CSNF assemblies are, in turn, represented as being emplaced in ten types of waste 
packages, which are also listed in Table 3.1-3. The waste packages and canisters combine to 
give a total of thirteen waste package configurations. The waste package configurations and the 
number of packages with each configuration for TSPA modeling purposes are listed in 
Table 3.1-3. 
Table 3.1-2. Waste Package and Canister Designs 
WP Design 
WP Design 
Code Canister Design 
Canister Design 
Code 
21 PWR absorber plate W1 Naval short C1 
21 PWR control rod W2 Naval long C2 
12 PWR W3 DSNF short C3 
44 BWR W4 DSNF long C4 
24 BWR W5 DSNF short, wide C5 
Codisposal short W6 DSNF long, wide C6 
Codisposal long W7 HLW short C7 
2-MCO/2-HLW W8 HLW long C8 
Naval short W9 HLW short with Pu-ceramic C9 
Naval long W10 MCO C10 
Source: CRWMS M&O 2000ao, Section 4 
Table 3.1-3a. Waste Configurations Used in the Inventory Abstraction 
Configuration 
WP Design 
Code Number 
DSNF Canisters per 
Waste Package 
HLW Canisters per 
Waste Package 
21 PWR absorber plate W1 4500a --- --- 
21 PWR control rod W2 100a --- --- 
12 PWR W3 170a --- --- 
44 BWR W4 3000a --- --- 
24 BWR W5 90a --- --- 
Total CSNF 7860

 3-7
Table 3.1-3a. Waste Configurations Used in the Inventory Abstraction (Continued) 
Configuration 
WP Design 
Code Number 
DSNF Canisters per 
Waste Package 
HLW Canisters per 
Waste Package 
Pu-ceramic in HLW W6 100a --- Five C9 (short) 
Codisposal short W6 1100a One C3 or C5 (short) Five C7 (short) 
Codisposal long W7 1500a One C4 or C6 (long) Five C8 (long) 
Codisposal mixed W7 130a One C3 or C5 (short) Five C8 (long) 
HLW-only W7 600a --- Five C8 (long) 
2-MCO/2-HLW W8 160a Two C10 Two C8 (long) 
Total Codisposal 3590 
Naval short W9 200b One C1 (short) --- 
Naval long W10 100b One C2 (long) --- 
Total Naval 300 
Sources: aStroupe 2000, Att. 1 
bDirkmaat 1997, Appendix F, Attachment, p. 6 
These waste package numbers were specified by management edict (Stroupe 2000), and are 
somewhat different from the Proposed Action numbers used in the DEIS (DOE 1999a) or the 
truncated case in recent input transmittals (CRWMS M&O 2000aj and 2000ae). The 
management specified numbers are not to exceed numbers and are rounded up from the 
truncated case, in order to convey flexibility in the design. The truncated case has more HLW 
canisters than the DEIS, in order to use the ideal waste emplacement scenario for codisposal. 
Neither the management case nor the truncated case may be emplaced without a redefinition of 
HLW MTHM equivalency or the elimination of the 70,000 MTHM limit specified in the 
Nuclear Waste Policy Act of 1982. Using the historical definition of 0.5 MTHM per HLW 
canister, these cases contain more than 4,667 MTHM HLW equivalent. Table 3.1-3b compares 
some of the canister and assembly numbers for the various scenarios. 
Table 3.1-3b Canister and Assembly Numbers for the Various Scenarios 
Total 
Management 
Casea 
Truncated 
Caseb 
Full Inventory 
Caseb 
DEIS Proposed 
Actionc 
DEIS 
Module 1c 
HLW canisters 
(including Pu) 
17,470 16,613 22,153 8,315d 22,300d 
DSNF canisters 
(excluding naval SNF) 
3,050 2,882 3,842 3,470e 3,721f 
CSNF assemblies 232,800 220,810 291,792 218,700g 359,963h 
NOTES: aAttachment 1 of Stroupe 2000 as used in TSPA-SR 
bfrom waste package counts in CRWMS M&O 2000aj and 2000ae 
cDOE 1999a 
dTable J-8 of DOE 1999a 
eTable J-7 of DOE 1999a 
fTable A-21 of DOE 1999a 
gTable A-6 of DOE 1999a 
hTable A-7 of DOE 1999a

 3-8
There will be 7860 CSNF packages and 3590 codisposal packages in the TSPA-SR analysis 
model. The 300 naval packages were grouped with the codisposal packages in the first version 
of CRWMS M&O 2000f, but were regrouped with CSNF packages in the subsequent input 
transmittal (CRWMS M&O 2000ak). Naval spent fuel is expected to perform very well within 
the repository, and it is better represented by commercial packages than by codisposal packages 
in the TSPA. Accordingly, the naval fuel inventory was removed from the high level waste and 
DOE spent nuclear fuel averages, and the averages were recalculated for the input transmittal 
(CRWMS M&O 2000ak). The impact analysis of this change is expected to show that the old 
values were conservative, and the total TSPA values are not significantly affected. The 
radionuclide inventories in grams for the selected isotopes are shown in Table 3.1-4. 
Three radionuclides appear in Table 3.1-4 that were not listed in Table 3.1-1. 228Ra, 232Th, and 
235U were not identified as important contributors to dose for the direct release scenario, the 
human intrusion scenario, or the nominal release scenario. However, 228Ra and 232Th will be 
modeled in TSPA for the groundwater protection scenario and therefore were included in the 
inventory abstraction. 235U will be modeled in the TSPA because it is a parent to 231Pa. To get 
accurate estimates of the dose from 231Pa, TSPA must track the transport of 235U. 
Table 3.1-4. Abstracted Inventory 
Grams in TSPA-SR 
Codisposal Packages 
Isotope 
Specific 
Activity (Ci/g) 
Grams in TSPA-SR 
CSNF Packages From Spent Fuel From HLW glass 
227Ac 7.24E+01 3.09E-06 1.13E-04 4.67E-04 
241Ama 3.44E+00 1.09E+04 1.18E+02 6.51E+01 
243Am 2.00E-01 1.29E+03 1.49E+00 5.09E-01 
14C 4.46E+00 1.37E+00 4.96E-02 6.43E-03 
137Cs 8.65E+01 5.34E+03 1.12E+02 4.50E+02 
129I 1.73E-04 1.80E+03 2.51E+01 4.80E+01 
63Ni 5.68E+01 5.53E+01 4.44E-01 3.39E-01 
237Np 7.05E-04 4.74E+03 4.79E+01 8.28E+01 
231Pa 4.72E-02 9.87E-03 3.25E-01 7.96E-01 
210Pb 7.64E+01 0.00E+00 1.40E-08 1.44E-07 
238Pu 1.71E+01 1.51E+03 6.33E+00 9.04E+01 
239Pu 6.21E-02 4.38E+04 2.30E+03 3.89E+03 
240Pu 2.27E-01 2.09E+04 4.89E+02 3.80E+02 
242Pu 3.93E-03 5.41E+03 1.11E+01 7.66E+00 
226Ra 9.89E-01 0.00E+00 1.87E-06 1.67E-05 
228Ra 2.72E+02 0.00E+00 6.98E-06 3.37E-06 
90Sr 1.37E+02 2.24E+03 5.54E+01 2.88E+02 
99Tc 1.70E-02 7.68E+03 1.15E+02 7.31E+02 
229Th 2.14E-01 0.00E+00 2.66E-02 4.08E-03 
230Th 2.06E-02 1.84E-01 1.06E-02 7.79E-03

 3-9
Table 3.1-4. Abstracted Inventory (Continued) 
Grams in TSPA-SR 
Codisposal Packages 
Isotope 
Specific 
Activity (Ci/g) 
Grams in TSPA-SR 
CSNF Packages From Spent Fuel From HLW glass 
232Th 1.10E-07 0.00E+00 1.49E+04 7.77E+03 
232U 2.20E+01 1.01E-02 1.47E-01 8.23E-04 
233U 9.66E-03 7.00E-02 2.14E+02 1.11E+01 
234U 6.24E-03 1.83E+03 5.72E+01 4.63E+01 
235U 2.16E-06 6.28E+04 8.31E+03 1.70E+03 
236U 6.47E-05 3.92E+04 8.53E+02 3.96E+01 
238U 3.36E-07 7.92E+06 5.09E+05 2.66E+05 
Source: From Chapter 7 and Table I-5 of the Inventory Abstraction AMR (CRWMS M&O 2000f) 
and a subsequent input transmittal (CRWMS M&O 2000ak). 
NOTE: aPart of the 241Am inventory is due to decay of 241Pu and 245Cm. 
3.1.2 Uncertainties, Limitations, and Conservatisms 
The screening analysis is conservative because all fuel types, bounding and average, all time 
periods, and all transport groups were examined. Any changes that might be expected in the 
wastes that may be disposed at Yucca Mountain will not change the radionuclides that were 
screened in for modeling in TSPA. 
The representative inventories were derived from unqualified projections of future waste 
streams. The actual waste streams will be known only at the time of actual repository loading. 
The projected waste streams could differ from the actual waste streams in their fuel burnups, fuel 
ages, fuel enrichments, and utility efficiencies. However, changes that might be expected in the 
waste stream will produce only minimal (less than 20 percent) changes in the radionuclide 
activities in the fuels. Given this understanding, the values chosen for initial inventories in 
CSNF and codisposal waste packages are reasonable representations of the inventory that may be 
disposed at Yucca Mountain (CRWMS M&O 2000f). 
3.1.3 Other Views 
Alternative approaches for developing the radionuclide inventory have been explored in previous 
TSPAs (Wilson et al. 1994; CRWMS M&O 1995; CRWMS M&O 1998b) and in the DEIS 
(DOE 1999a). In previous TSPAs, (Wilson et al. 1994; CRWMS M&O 1995; CRWMS 
M&O 1998b), radionuclide activities for CSNF were developed by assuming an average set of 
fuel characteristics (enrichment, burnup, and age of the waste) and using the DOEs 
Characteristics Database to determine radionuclide activities for a fuel having the specified 
characteristics. Radionuclide activities for DSNF were developed by assuming that the defense 
fuels can be grouped into a few representative groups (based on their chemical characteristics) 
and calculating inventories for a representative fuel from each group. Radionuclide inventories 
for HLW were developed by assuming that an average of glass waste from the Savannah River 
Vitrification Plant and processed waste from Hanford, INEEL, and the West Valley Facility can 
represent HLW.

 3-10
The TSPA-SR analysis screening method used a qualified process to ensure traceability. It 
looked at both bounding and average fuels, DSNF and HLW as well as CSNF, time periods from 
100 to 1 million years, and both inhalation and ingestion doses. By using two solubility groups 
and three different transport groups and comparing the radionuclides within the groups, better 
discrimination was achieved. For example, if all isotopes were lumped together, plutonium 
would dominate the dose. But this is true only if Pu is readily transported to the accessible 
environment. The full TSPA-SR analysis and its colloid models will predict the likelihood of 
significant Pu transport. The screening could not rely on TSPA output and, thus, did not rely on 
any assumptions about solubility or transport affinity. 
The TSPA-SR inventory analysis is more detailed and flexible than previous analyses and is tied 
to the waste stream. Changes in WP configuration or waste stream are more easily reflected in 
the per package inventory of representative WPs. An example of such a change is seen in the 
recent regrouping of naval spent nuclear fuel. 
3.2 IN-PACKAGE CHEMISTRY COMPONENT 
The function of the in-package chemistry model component is to estimate the fluid chemistry 
inside the WP over time after the initial breach of the disposal container. This chemistry is then 
used by the several other model components (see Figure 1.5-3) since the rate of degradation of 
the matrix of waste, the resulting dissolved concentration of radionuclides, the stability of any 
colloids, and degradation of cladding are all dependent on the chemistry of fluids within the WP. 
The rate of degradation of the waste matrix and inner stainless steel container, in turn, influences 
the fluid chemistry and so there is a coupling between all the chemically interacting components 
of the system. 
The In-Package Chemistry Abstraction AMR (CRWMS M&O 2000g) is the primary document 
describing the regression equations used for evaluating the in-package chemistry. This 
document, in effect, abstracts the process models that are developed in Summary of In-Package 
Chemistry for Waste Forms (CRWMS M&O 2000o). The In-Package Chemistry Abstraction 
(CRWMS M&O 2000g) also relies on a few of the FEP screening arguments in Miscellaneous 
Waste-Form FEPs (CRWMS M&O 2000n). While abstraction of process models is numerically 
convenient, it is technically defensible only if the abstracted model conservatively bounds the 
predictions of process-level models. In this case, dissolved radionuclide levels predicted with the 
abstracted model must be equal to, or greater than, those predicted by the underlying processlevel 
models. The most reliable way to assure technical reliability of the abstraction is to force it 
to be mechanistically identical to the process-level model. This was done for the solubilities of 
the majority of the primary radionuclides by building abstractions of in-package chemistry and 
solubility expressions on equilibrium speciation output of EQ3NR. 
3.2.1 Description 
The fluid chemistry inside the package (in-package chemistry) is dependent upon the initial 
chemistry of the water entering the breached package, the volume of water flowing through the 
package, the amount of water remaining within the package, and the amount of time that inflows 
into the waste package occur. The inflows were assumed to have the composition of J-13 
groundwater. Early breach of a WP would almost certainly entail chemical interaction under

 3-11
substantially higher temperatures. Under such a scenario, evaporative concentration of reacting 
fluids would be expected to result in in-package fluids that diverge substantially from the 
compositions calculated under the 25C, zero-evaporation limiting case considered here (see 
below). Various breach scenarios can be envisioned for the container, but as explained later, the 
current model assumes a fully flooded container (bathtub scenario) for the volume of water 
present in the container at all times. In addition, the in-package chemistry is dependent upon the 
degradation rates of the contents of the package. Two representative WPs were modeled, a 
CSNF package and a DSNF/HLW codisposal package (Figure 3.2-1). In both cases, there is an 
inner stainless steel disposal container, but the basket materials and waste forms are different and 
influence the fluid chemistry at least for short time periods. 
Direct use of a complex equilibrium code within the TSPA-SR analysis calculation was not 
practical; rather, a limited number of simulations were run with the complex equilibrium code, 
for a variety of input conditions and degradation rates of the contents. Regression equations 
were then developed for use directly in the TSPA-SR analysis calculations as explained below 
(Figure 3.2-2). 
3.2.1.1 In-Drift Fluids 
The calculations for revision 00 of the Summary of In-Package Chemistry for Waste Forms AMR 
(CRWMS M&O 2000o) were performed in parallel with the testing and analysis of the effects of 
the near-field environment (NFE) on the water that may contact and enter the waste package. 
This parallel work is summarized in the NFE (CRWMS M&O 2000z), EBS (CRWMS M&O 
2000y), and waste package degradation (CRWMS M&O 2000d) process model reports. 
However, for these first calculations, the J-13 well water composition was used for water 
entering the waste package (Harrar et al. 1990, Section 11). J-13 well water is quite dilute and 
its composition is not expected to significantly affect the in-package chemistry. On-going work 
will verify this assumption, or provide better information. 
J-13 well water is used as a surrogate for the groundwaters passing through the repository and 
possibly into breached WPs several thousand years after the repository has closed. The most 
abundant dissolved constituents in J-13 well water include Na and C, along with Si, Ca, K, F, Cl, 
N, and Mg. Dissolved Na, K, and Ca came from dissolution of feldspars into down-flowing 
meteoric water. Si was contributed by dissolution of feldspars and Si polymorphs. C and N 
came from equilibrium with soil and atmospheric gases encountered in transit. J-13 well water 
has undergone cation exchange with zeolitic rocks (causing increased Na/Ca) compared to UZ 
pore waters at the repository horizon. This is important for understanding the overall chemical 
budget of repository waters. Because Na and Ca play non-specific roles in the overall 
degradation process, ion exchange is less important to predicting what occurs once J-13 comes 
into contact with WPs. J-13 well water has a pH of ~8 and is thought to be close to equilibrium 
with carbon dioxide at levels slightly higher than that present in the atmosphere. The slightly 
higher than neutral pH of the solution is a direct result of alkalinity production that occurs when 
primary phase silicates are weathered. Waste package alteration scenarios are less sensitive to 
the exact composition of the water entering the package than they are to dissolution rates of a 
number of waste package components because: (1) The rates of WP component dissolution are 
not overly sensitive to minor variations in these parameters and (2) WP components rapidly 
come to dominate the dissolved phase after onset of reaction. Calculations have been started for

 3-12
a new version of the Summary of In-Package Chemistry for Waste Forms analyses and models 
report to test the sensitivity of the in-package chemistry to incoming water composition. It is 
expected that the incoming water will consist of the water found in the unsaturated zone 
subsequently modified by evaporation and/or condensation and fluid-rock interaction. 
Accordingly, sensitivity calculations are being done using a range of waters including the 
compositions in Table 3.2-1 as well as 100-fold evaporated J-13 water. 
Table 3.2-1 provides the major element composition of J-13 well water, Drift-Scale Test (DST) 
water, and the output of THC modeling. DST compositions represent an average of waters 
collected from Alcove 5 near the DST and were used as input compositions for modeling of 
thermal-hydrologic-chemical coupling in the NFE. DST water is thought to have moved 
appreciably through fractures and interacted with the rock matrix. The modeling output for 
waters expected to seep into the drifts is shown for two time periods, the transitional cool-down 
period (1,000-2,000 years) and the extended cool-down period of 2,000-100,000 years. By using 
these water compositions as well as 100-fold evaporated J-13 well water, the sensitivity 
calculations are covering a broad range of chemistries and should give a good indication of the 
sensitivity of the resulting in-package chemistry on the input water composition. 
Table 3.2-1. Major Element Composition of Input Waters Considered in Sensitivity Studies 
Component 
J-13 
Well Watera DSTb 
Modelingc 
1000-2000 years 
Modelingc 
2000-100,000 years 
pH 7.41 8.32 7.8 7.3 
Na (ppm) 45.8 61.3 60 60 
SiO2(aq) (ppm) 61 70.5 126 72 
Ca (ppm) 13.0 101 40 72 
K (ppm) 5.04 8.0 12 3.9 
Mg (ppm) 2.01 17 0.04 0.19 
F (ppm) 2.18 0.86 0.85 0.85 
Cl (ppm) 7.14 117 113 117 
SO4(ppm) 18.4 116 115 115 
HCO3 (ppm) 128.9 200 18.3 128 
Sources: aFrom Harrar et al. 1990 Table 4.1 with ppm of Si converted to ppm of SiO2. 
bUnits converted from Table 3 of CRWMS M&O 2000af. 
cUnits converted from Table 3 of CRWMS M&O 2000ai. 
The in-package chemical reaction calculations used input fluid flows of 1.5 to 150 L/yr. The 
temperature of the simulations was set at 25C to represent the conditions that will occur several 
thousand years after WP emplacement, when the original thermal pulse has passed and 
temperatures have returned to near ambient levels. Waste form degradation may occur at 
temperatures up to 100C. It is assumed that the process can be modeled adequately with the 
25C thermodynamic database. The calculations represent what occurs at times > 10,000 years, 
after the thermal pulse has passed and package temperatures are at, or below, 100C. The 
justification for using 25C thermodynamic data to model processes that might occur at 
somewhat higher temperatures is that many of the input thermodynamic parameters are not 
strongly sensitive to temperature over the range of 25 to 100C, hence the broad scale features of

 3-13
the output fluid compositions are deemed independent of temperature. Dissolution rates of WP 
internal components would be greater at temperatures greater than 25C. Typically, dissolution 
rates of minerals roughly double with every 10C increase in temperature. In the absence of high 
temperature dissolution rates, this is probably a reasonable approximation for the behavior of 
metallic and oxide WP internal components as well. The net effect of temperatures greater than 
25C would therefore be a more rapid release of WP components into solution than what is 
reported here. Note that the existing calculations tend to err in this direction already because 
they use very high rates as input. 
Higher temperatures would also affect the boundary conditions of the calculation by decreasing 
the solubilities of oxygen and carbon dioxide in the fluids reacting with the WP. A more 
important impact of temperature on in-package chemistry would almost certainly be the 
evaporative concentration of inflowing and reacting solutions, which could conceivably change 
the concentrations of a number of important chemical species by orders of magnitude. 
Evaporation of J-13 water before interaction with WP components would result in a high ionic 
strength, alkaline solution. For example, 200-fold open-system concentration of J-13 water 
produces a pH 10, 1 mol/L ionic strength solution, which has 200 times as much chloride and 
total carbonate as J-13. Evaporation of J-13 type water is expected to lead to the formation of 
calcite, chalcedony, fluorite, and possibly sepiolite and other less abundant minerals. The 
important consequences of evaporation for fluid influx chemistry are increases in chloride, pH, 
and bicarbonate. Increased chloride impacts WP internal component corrosion. Glass and 
mineral dissolution rates tend to double for every unit increase in pH above 8. Many 
radionuclides are more soluble in the presence of bicarbonate. The sensitivity calculations will 
provide an indication of how important evaporation may be on in-package chemistry. 
The partial pressure of carbon dioxide and oxygen were set to, respectively, 10-3.0 and 10-0.7 bar 
(DOE 1998c, Figure 3-36). The latter represents equilibrium with oxygen at atmospheric levels. 
Reaction with rock bolts (and steel supports) was neglected because the interaction of the fluid 
with waste package components would greatly outweigh any transient contact of the fluid with 
the rock bolts and the steel ground support. The total surface area of rock bolts likely to be 
encountered by seepage before contact with waste package components is small. It is likewise 
difficult to envision substantial interaction with the support material before seepage into the 
waste package. 
3.2.1.2 Water Contact Scenarios 
As described in the Summary of In-Package Chemistry for Waste Forms Process Model 
CRWMS M&O (2000o), a simple degradation scenario for the WP entails breaching the WP 
(presumably through stress corrosion cracking and/or mechanical failure); filling of the WP void 
volume with seepage fluids from the drift; reaction within the WP; and releasing contaminated 
fluids at the same rate at which fresh fluids entered. This simple breach scenario was adopted 
and each breached WP was modeled as a continually stirred, fixed volume vessel. Specifically, 
the calculations used the solid-centered, flow-through mode of EQ3/6; in this mode, an 
increment of fresh fluid solution is added to the WP system and a like amount of solution is 
removed at each time step. The void volumes considered were a constant 4,507 L for the CSNF 
WP and a constant 5,811 L for the DSNF WP.

 3-14
The assumption of a continually stirred vessel is a simple and common approach to estimating 
the nature and extent of chemical reaction. The basis of the assumption is that either the fluid is 
continually stirred, or equivalently, the residence time of the fluids in the vessel is sufficient for 
diffusion to eliminate chemical gradients. In general, the latter basis is valid because of the 
geologic time scale of seepage and chemical reaction involved. 
Further justification is reasoned as follows. If wetting of WP components were complete, but 
void filling was not, the reduced fluid/solid ratio would tend to maximize the amount of 
dissolved solids in the effluent. On the other hand, the overall chemical reaction would be less 
for fluids that found themselves in dead-end channels, or if portions of the WP were physically 
inaccessible to fresh fluids. Furthermore, fluids that found fast paths that short-circuited 
interaction with WP solids would bear a much fainter signature of chemical reaction. 
Evaporation of fluids by residual heat could increase the salt content (i.e., ionic strength), and, 
thereby, increase some radioisotope solubilities, and possibly increase the rate of WF or WP 
degradation. The increased salt content, however, is not expected to significantly alter the overall 
reaction path (CRWMS M&O 2000o, Section 7) and was examined in a FEP on the use of J-13 
well water (Section 2.3.2.2). 
This breach scenario provides an upper bound for in-package radionuclide transport and release. 
It does not include any time delay for water that enters the package; it does not include any 
retardation of radionuclides into immobile secondary phases by coprecipitation or sorption; it 
does not allow for radionuclides to be held-up in stagnant areas of the WP, and it maximizes 
contact between oxidizing fluids and WF and WP materials. 
The analyses using the in-package chemistry results also used bounding assumptions or large 
uncertainty (see Section 3.3, CSNF Matrix Degradation; Section 3.4, CSNF Cladding 
Degradation, Section 3.6, HLW Degradation, and Section 3.7, Dissolved Radioisotope 
Concentration). In particular, the possible effects of localized chemistry are included in the 
CSNF cladding degradation model. 
3.2.1.3 Waste Package Contents 
In-drift solutions seeping into a breached WP would encounter a number of kinetically reactive 
solids whose reaction rates are only known within orders of magnitude (Table 3.2-2). Fluids 
intruding into WPs containing CSNF would encounter UO2 fuel wrapped in Zircaloy cladding, 
Al alloy, 316 stainless steel (with and without neutron absorbers, such as boron or GdPO4), and 
A516 low carbon steel. A range of degradation rates was used for each. Dissolution of the fuel, 
and release of radionuclides, occurs only after degradation of some of the cladding. General 
corrosion of cladding is likely to be insignificant under the geochemical conditions expected 
inside reacting WPs. Uncertainty in the initial failures, localized corrosion, mechanical damage, 
and other degradation mechanisms are addressed in the cladding degradation AMRs and were 
not available when the in-package calculations were started, so a range of clad damage and 
CSNF fuel exposure was investigated (100 percent, 20 percent, and 1 percent). The WP 
configuration used for the codisposal package calculations was that of the Fast Flux Test Facility 
(FFTF) DSNF with five HLW glass logs.

 3-15
Table 3.2-2. Chemical Characteristics of CSNF and Codisposal Waste Package Components 
Material 
Amount 
(mol/L) 
Degradation Rate 
(mol/cm2s) (25C) 
Surface Area 
(cm2/L) 
CSNF WP Parameters 
Al alloy 2.36 2.28  10-13 96.424 
A516 11.948 2.487  10-11 (high) 
8.706  10-12 (low) 
504.160 
316 SS 23.75 2.528  10-13 (high) 
2.528  10-14 (low) 
52.500 
316 SS/B 7.856 1.169  10-13 (high) 
1.169  10-14 (low) 
156.010 
CSNF 27.21 4.420  10-14 + 10-10.59 - 0.5  pH 96200 
Codisposal WP Parameters 
304L 6.384 
0.065 
2.516  10-13 (high) 
2.516  10-14 (low) 
150.804 
6.661 
A516 10.140 129.615 
HLW glass 24.821 1.983  10-19[H+]-0.4721 + 6.144  10-12[H+]0.6381 (low) 
1.983  10-18[H+]-0.4721 + 6.144  10-11[H+]0.6381 (high) 
1915.142 
316 SS 
(various parts) 
0.946 
20.573 
0.423 
26.35 
24.134 
27.267 
257.913 
56.5 
316 SS/ GdPO4 0.653 2.528  10-14 16.732 
U oxide 0.018 4.420  10-14 + 10-10.59 - 0.5  pH 72.072 
MOX 0.393 4.420  10-14 + 10-10.59 - 0.5  pH 1559.382 
NOTE: Table 1 of Summary of In-Package Chemistry for Waste Forms ANL-EBS-MD-000050 (CRWMS 
M&O 2000o). Values for 304L have been corrected; each had an extraneous "2" added to the 
beginning. 
3.2.1.4 EQ3/6 Reaction Path Modeling 
As described in the Summary of In-Package Chemistry for Waste Forms AMR (CRWMS M&O 
2000o) simulations of WP alteration by ambient groundwater were done using the qualified 
reaction path code EQ3/6 (CRWMS M&O 1998a; CRWMS M&O 1999c), which titrates masses 
of WP components at a rate determined by input reaction rates and fluid influxes into the 
breached WP. The software package, EQ3/6, Version 7.2b, was approved for QA work by 
LLNL and is identified as Computer Software Configuration Item (CSCI): UCRL-MA-110662 V 
7.2b. EQ3/6 periodically assesses the chemical equilibrium state of the solution and removes 
newly saturated, secondary mineral or gas phases from the fluid. In addition to kinetic inputs 
(e.g., rates, compositions, and masses of reactants) EQ3/6 relies on a thermodynamic database 
describing the chemical stability of minerals, aqueous species, and gases. When the reacting 
solution becomes saturated with respect to solids or gasses, EQ3/6 converts dissolved 
components into the respective phase and then allows the latter to act as a reservoir of the 
respective components for use at subsequent times. In this way, EQ3/6 tracks the elemental 
composition of the reacting fluid for the duration of the reaction path calculation while at the 
same time providing estimates of the nature and masses of secondary phases that are predicted to

 3-16
form. The code, however, does not provide for the kinetic inhibition for phase formation, which 
is, therefore, the responsibility of the analyst. Generally, the assessment of kinetic inhibition 
must be made on the basis of there being an absence of the particular phase in low-temperature 
(~25C) environments. For example, dolomite (CaMg(CO3)2) is predicted to form in a number 
of runs due to the accumulation of Ca, Mg, and alkalinity upon reaction with WP components. 
Dolomite, though thermodynamically favored to grow in a number of low temperature natural 
solutions such as seawater, apparently must overcome severe kinetic obstacles to actually form 
and is actually observed growing only in highly evaporated brines. These kinetic considerations 
are then the basis for suppressing formation of dolomite in the reaction path calculations. 
Similar arguments are used to suppress the formation of a number of oxide and silicate minerals 
that are typically observed to form only under high temperature conditions. 
3.2.1.5 Results of Waste Package and Waste Form Alteration Modeling 
Table 3.2-3 summarizes the range of in-package fluid compositions predicted to occur for both 
the CSNF and codisposal packages (see Section 3.2.1.6 for further discussion of this chemistry 
and Section 3.2.2 for limitations). 
Table 3.2-3. Range of In-Package Fluid Compositions (mol/L for all 
except pH and Eh [volts]) 
Variable CSNF Codisposal 
pH 3.6 - 8.1 4.8 - 10.0 
Eh (V) 0.7 - 1.0 0.6 - 0.9 
Ionic Strength 0.003 - 1.7 0.003 - 5.8 
Ca 3.9  10-6 - 0.00032 3.0  10-7 - 0.02 
C 2.8  10-5 - 0.002 3.5  10-5 - 0.5 
Si 3.7  10-10 - 1.9  10-4 5.3  10-10 - 1.9  10-4 
Source: Table 3 of Summary of In-Package Chemistry for Waste Forms 
ANL-EBS-MD-000050 (CRWMS M&O 2000o) 
CSNF WPs-The majority of WPs in the repository will contain spent fuel rods from commercial 
reactors. The primary reactions that occur upon breach of CSNF WPs and subsequent alteration 
by intruding fluids are: (1) a rapid decrease in pH caused by dissolution of low-carbon steel and 
(2) a subsequent rise in pH caused by CSNF dissolution and oxidation of Al alloy (Figure 3.2-3). 
The latter rise is more pronounced under conditions of high clad failure. By the same token, the 
lowest predicted pHs are those calculated for the least amount of clad failure. Feedback between 
the pH and clad corrosion rate was not included within the calculations, as the pH is not expected 
to go low enough to cause significant increases in clad failure rates (see Section 3.4.2.4). Under 
the assumed fixed CO2 conditions of the simulations, carbonate levels are relatively high at high 
pH and low at low pH. Because both U and Pu form soluble complexes with carbonate, the 
dissolved levels of each tend to increase at high pH and decrease at low pH. However, the 
lowest pHs occur in the early stages of the reaction paths before appreciable U or Pu has been 
dissolved from the CSNF matrix.

 3-17
Minerals predicted to form during alteration of CSNF WPs include: copper minerals, silicates 
(clays, uranium silicates), oxides (metal oxides, actinide oxides), carbonates, phosphates, 
sulfates, and fluorides. Although the inputs to the calculation are normalized to a liter of fluid, 
and a liter volume is assumed to persist, the large volumes of lower density corrosion products 
(mainly hematite and UO32H2O) suggest that alteration products might actually fill the void 
space and seal off portions of the WPs to further fluid influx. This is further discussed in 
Section 3.4. 
Codisposal WPs-In all codisposal runs (Figure 3.2-4), the input pH of ~8.1 prevails initially. 
Then the system pH progresses towards a minimum, primarily due to the oxidation of the A516 
carbon steel. The high specific rate and relatively high surface area of the latter mean that its 
dissolution tends to dominate the whole reaction path, at least as long as it remains. Oxidation of 
sulfur in the steel to sulfate is the primary proton-producing reaction. After the steel is 
exhausted, dissolution of base cation-containing HLW glass leads to increased pHs. pHs as high 
as 10 and ionic strengths as high as ~5.8 mol/L were predicted for codisposal WPs under 
conditions of high glass dissolution and low flow rates. 
Minerals predicted to form during alteration of codisposal WPs typically include the same 
minerals formed during CSNF alteration, though borates are also predicted to form, and the 
uranium silicates are more important. 
3.2.1.6 Abstraction of In-Package Chemistry 
The predicted compositions of in-package fluids are of particular importance for estimating 
releases of radionuclides to the biosphere. The Summary of In-Package Chemistry for Waste 
Forms (CRWMS M&O 2000o, Section 6) provides reaction-path modeling assuming 
steady-state CO2 and O2 concentrations in the drift and breached WPs. The analysis indicates the 
broad range of effluent compositions that might be expected from a breached WP and provides a 
basis from which to establish abstractions describing radioisotope solubilities. 
The analysis of calculated in-package fluid compositions possesses four broad features. 
Carbonate alkalinity increases with pH due to the assumed fixed partial pressure of CO2. System 
Eh decreases with pH due to the assumed constant partial pressure of O2. Low early pHs are 
only seen with low cladding failures, and alkalinities typically correlate with high ionic strengths 
associated with high glass dissolution and low flow rates. 
The EQ3/6 simulations calculate the fluid chemistries that are operative over long periods of 
time (> 1,000 years). The simulations over this time period are typically different than those that 
prevail over shorter periods of time. Recognition of this change in process is important for 
estimating long-term behavior. Typically reaction times of less than 1,000 years result in 
relatively minor degradation of WP components; hence, the concentrations of many 
radionuclides are often well below their respective solubility limits. In effect their 
concentrations depend directly on the dissolution rates of WP components. At much greater time 
spans, many, but not all, radionuclides have reached saturation with at least one mineral phase. 
Once this has occurred, dissolved levels of the particular radionuclides will depend on the 
thermodynamics of secondary phase stability and much less directly upon the dissolution rates of 
the WP components.

 3-18
The abstraction of in-package processes is based upon a series of multiple linear regression 
analyses of the output from the EQ3/6 simulations as presented in the In-Package Chemistry 
Abstraction (CRWMS M&O 2000g, Attachment I). The multiple linear regression analyses take 
explicit account of the change in process control with time and treats results for times less than 
1,000 years after waste package breach separately from those for later times. The specific 
relationships between pH, Eh, clad failure, and component degradation are illustrated in 
Figure 3.2-2. The predictions from the multiple regression analyses, and the output from the 
EQ3/6 simulations are presented in the abstraction AMR (CRWMS M&O 2000g) and 
summarized here. 
Because it is difficult to track the failures of individual packages in TSPA, the in-package 
chemistry abstraction was implemented in an approximate way for a group of packages. Let t be 
the current time and let tfail be the average time of failure for all the breached waste packages. 
The short-time abstraction would apply for t - tfail < 1000 years, and the long-time abstraction 
would apply for t - tfail > 1000 years. 
The pH abstraction follows two lines of reasoning based on the WP type (CSNF or codisposal ), 
and the difference in kinetic rate laws between the two. The rate law for CSNF is proportional to 
the hydrogen ion activity, i.e., proportional to pH, such that at low pH the dissolution rate 
increases (CRWMS M&O 2000o, Section 6.1.1). For HLW the rate law is U shaped with the 
minimum at pH 7 and the rate increasing above and below pH 7 (CRWMS M&O 2000o, Section 
6.1.1). Therefore, conservative assumptions for one waste form may not be conservative for the 
other. In the case of the CSNF (and naval SNF), for example, assuming the lowest observed pH 
for the first 1000 years after breach, and the averaged pH thereafter would be the most 
conservative, while still honoring the pHtime history. However, for the codisposal package 
using the lowest observed pH would be conservative for the first 1000 years after breach but not 
for later times, when use of the maximum pH is conservative. The difference in the rate laws 
between HLW and CSNF and the difference in their pHtime profiles for the two waste forms 
predicates the use of different assumptions in the abstractions. 
For the CSNF, at times less than 1,000 years after waste package breach, minimum pH values for 
each flow/cladding/corrosion scenario were regressed to produce two abstractions of pH; one for 
low WP corrosion rates and the other for high WP corrosion rates, where the axes were 
x = cladding coverage, y = water flow (Q), and z = pH. This process was repeated for times 
greater than 1,000 years after breach, where the average pH for the entire modeled duration (0 to 
10,000 years after breach) was used to calculate the average pH. The average pH for the entire 
duration is conservative because it includes the low pH values at early times, which tends to 
lower the average value compared to averaging over the late time information (1,000 to 10,000 
years after breach). 
The resulting four data matrices were used to generate four response surfaces describing pH at 
less than and greater than 1,000 years after breach. These response surfaces were provided for 
TSPA to use in pH calculations. Table 3.2-4 provides the equations of the planes that bound the 
pH parameter space for CSNF, and Figures 3.2-5 and 3.2-6 show these planes. Each plane 
represents either the low or high corrosion rate data for the WP materials, 316 stainless steel, 
aluminum alloy, A516 carbon steel, and borated stainless steel. An uncertainty range of 1 pH 
unit was recommended for TSPA.

 3-19
Table 3.2-4. Response Surface Parameters for CSNF pH 
z = yo + ax + by 
Time After 
Breach 
(Years) 
Corrosion 
Rate z yo a b Adj. R2 
Sigma 
(pH) 
< 1,000 Low Min. pH in 0 - 1,000 years 3.4916 -1.0918 0.4571 0.993 0.066 
< 1,000 High Min. pH in 0 - 1,000 years 3.3977 -0.7468 0.3515 0.998 0.027 
> 1,000 Low Ave. pH in 0  10,000 years 6.0668 -0.5395 4.0479 0.774 0.257 
> 1,000 High Ave. pH in 0  10,000 years 6.0913 -0.3057 1.2913 0.77 0.13 
Source: In-Package Chemistry Abstraction. ANL-EBS-MD-000037. (CRWMS M&O 2000g, Table 6 
and Attachment I) 
NOTE: z = pH a range of  1 pH unit was applied to all calculated pH values. x = log10 (cladding coverage), y 
= water flow (m3/yr) (Q) 
Table 3.2-5 and Figures 3.2-7 and 3.2-8 show the equations describing minimum and maximum 
pH parameter space for codisposal WPs. The balance of the acid production from the Alloy 
516 carbon steel and base production from the glass determine the pH. At early times (< 1,000 
years after breach), acid production dominates, but as the steel is consumed, base production 
overcomes the acid production. In most cases, this is not calculated to occur until considerably 
after 10,000 years after breach. To obtain conservative glass degradation rates, the maximum pH 
in the 100,000 year simulations was used. 
Table 3.2-5. Response Surface Parameters for Codisposal pH 
z = yo + ax + by 
Time After 
Breach 
(Years) 
Corrosion 
Rate z yo a b Adj. R2 
Sigma 
(pH) 
< 1,000 Low Min. pH in 0 - 1,000 years 5.1257 2.6692 0.0764 0.94 0.11 
< 1,000 High Min. pH in 0 - 1,000 years 4.7324 0.7307 0.0837 0.99 0.04 
> 1,000 Low Max. pH in 100,000 years 8.4247 -3.4173 0.1403 0.78 0.37 
> 1,000 High Max. pH in 100,000 years 9.2554 -3.1280 -0.0418 -0.31 0.76 
Source: In-Package Chemistry Abstraction. ANL-EBS-MD-00037. (CRWMS M&O 2000g, Table 12 
and Attachment I) 
NOTE: z = pH, a range of  1 pH unit was applied to all calculated pH values. x = water flow (m3/yr) (Q), 
y = relative glass dissolution rate 
Due to the simplicity of the mathematical expressions used to calculate pH, it is possible, by 
increasing the water flow Q, to calculate unrealistic pH values. Therefore, it was necessary to set 
limits for the maximum allowable Q. Since the calculated pH from all of the expressions in 
Tables 3.2-4 and 3.2-5 are directly proportional to water flow through the WP and as the water 
flow increases the potential for reaction of the through-flowing water with the WP/waste form 
materials decreases, the pH of the water exiting the WP should approach that of J-13 well water. 
Therefore, above some maximum Q-value, the water exiting the WP should have the same pH as 
the water entering the WP. This critical value of Q was calculated by solving the expressions in 
Tables 3.2-4 and 3.2-5 for Q and using the input, J-13 well water value for pH and assuming 
linear behavior.

 3-20
For CSNF at time less than 1,000 years after breach, the pH expressions (Table 3.2-4) are valid 
within the range of 0 < Q < 5.3 (m3/yr). Likewise, when Q = 5.3 m3/yr, then the pH is constant 
at 8.1 (1). For time greater than 1,000 years after breach, the pH expression (Table 3.2-4) is 
valid for 0 < Q < 0.24 (m3/yr), and when Q = 0.24 m3/yr the pH is constant at 8.1 (1). Similarly 
for codisposal waste packages, the pH expressions (Table 3.2-5) are valid within the range of 0 < 
Q < 1.1 (m3/yr) at time less than 1,000 years after breach and 0 < Q < 0.36 (m3/yr) for time 
greater than 1,000 years after breach. Above these values, the pH is constant at 8.1 (1). 
Total dissolved carbonate affects the solubilities of a number of actinide phases as well as the 
degradation rate of CSNF. The total dissolved carbonate is abstracted as a function of pH by 
assuming a partial pressure of atmospheric CO2 = 10-3 atm and equilibrium between the 
carbonate, bicarbonate, and carbonic acid in solution: 
Total C (mol/L) = 10-4.47 + (10-10.82)/10-pH + (10-21.15)/10-2pH (Eq. 3.2-1) 
The system Eh is important in particular for determining the solubilities of many of the actinides. 
In aqueous systems in equilibrium with the atmosphere, the Eh may be abstracted directly from 
the pH and the assumed partial pressure of oxygen (0.20 atm): 
Eh = 1.217  0.059  pH (Eq. 3.2-2) 
where Eh is in volts. The ionic strength was used in determining the colloid content of the water 
exiting the NFE. For the period before 1,000 years after breach, the minimum ionic strength was 
calculated for each flow/cladding scenario (beta distribution from 2.757  10-3 to 2.922  10-3 
mol/L) and glass rate/corrosion rate scenario (beta distribution from 2.537  10-3 to 3.479  10-3 
mol/L). At times greater than 1,000 years after breach, the average value of ionic strength was 
used from each scenario to get the ionic strength range used in the abstraction (beta distributions 
from 2.827  10-3 to 3.943  10-1 mol/L for CSNF and from 7.86  10-3 to 1.353 mol/L for 
codisposal). This is a conservative approach compared to using the maximum value because low 
ionic strength is conducive to colloid formation, and using the minimum value would also create 
the worst case, which is not reflective of the actual in-package conditions. 
Fluoride was considered in the cladding degradation model. Fluoride was only pertinent for the 
CSNF and naval SNF because there was no cladding protection included in the codisposal 
package modeling. The CSNF calculations indicate that the fluoride concentration is controlled 
by fluorapatite. The abstracted distribution was normal between 1.148  10-4 and 9.114  10-4 
mol/kg with a standard deviation of 2.2  10-4 mol/ kg. Chloride levels remain constant at 
2.0  10-4 mol/kg and therefore are too low to influence the models that rely on bulk chemistry.

 3-21
3.2.2 Confidence/Limitations/Validation 
This work represents the first attempt by the DOE to model the chemical interactions that occur 
within the WP for use within the TSPA calculations. Only limited sensitivity runs have been 
completed to study the importance of issues such as: 
 Codisposal fuel configurations (type and amount of DSNF, type and amount of basket 
materials) (Sections 6 of CRWMS M&O 2000aa, CRWMS M&O 2000ab, CRWMS 
M&O 2000ac). 
 Feedback between chemistry and corrosion rates (built-in or iterations)The 
substantial accumulation of alteration products might choke off subsequent corrosion. 
At the same time, sharp shifts in fluid chemistry associated with WP alteration might 
also accelerate corrosion. At present, there is little feedback, either negative or positive, 
within the modeling. Iterations or more involved rate laws describing chemical 
corrosion would allow the more important feedbacks to be assessed. For example, for a 
flooded WP, the development of an alteration rind, even 1 cm thick, could prevent 
widespread oxidizing conditions at the sites of waste form degradation, which could 
substantially lower actinide solubilities (Section 6.3 of CRWMS M&O 2000ad). The 
uncertainties associated with predictions of fluid flow and solid exposure in the WP are 
formidable. By assuming full exposure of WP components, the calculation is 
conservative since it maximizes the potential for chemical degradation of the WP and for 
release of radionuclides. 
 Water contact scenarioPredictions of specific degradation geometries and reduction 
in the uncertainty due to water contact scenario are difficult. The water contact scenario 
in the TSPA-SR analysis used to calculate in-package chemistries is merely the simplest 
of approaches. Only scoping calculations to determine the sensitivity of the system are 
justified at this time. 
 Assumptions of fixed O2, CO2Assuming oxidized, carbonated conditions in the WP 
tends to maximize the solubilities of many of the most important radionuclides. 
Reaction paths calculated under less oxidized, and/or less carbonated conditions would 
tend to predict lower dissolved levels of Pu and U (Section 6.3 of CRWMS 
M&O 2000ad). 
 Hydrogen evolutionThe assumption was made that H2 gas was not evolved in 
modeling carbon steel corrosion. This is conservative in allowing for the maximum pH 
reduction. 
 Radiolysis-Radiolysis was neglected in the present analysis. The probability of WP 
breach is quite low before about 1,000 years, and the likelihood of significant radiolysis 
is much lower at later times. In theory the formation of NO2 by radiolysis might 
conceivably cause in-package pHs to decrease by forming nitric acid. Two features that 
would tend to work against such a scenario are the inherent buffer capacity of the 
assemblage and outgassing of NO2 from the breached WP and into the drift. Radiolysis 
of water and off-gassing of H2 may also increase the local effective Eh; however, at late

 3-22
times this is also not expected to be significant (CRWMS M&O 2000s, Section 6.2; 
2000h, Section 6.1; 2000n, Section 6.2.52). Highly localized energy deposition from 
alpha-decay might have some effect on dissolution rates, but these effects are also not 
expected to be significant (CRWMS M&O 2000h). 
 Database 
 TemperatureAlthough the thermodynamic database used in the EQ3/6 calculations 
extends to 300C, for many species, the data are most accurate at 25C, the 
temperature where the data were originally measured. 
 Ionic strengthNote that calculations for solutions with ionic strengths exceeding 
~0.7 mol/L are less accurate than dilute systems, but the uncertainties are small 
relative to the other uncertainties within the system. 
The above limitations and uncertainties were considered as the modeling was performed (see 
CRWMS M&O 2000ad, Section 5.1 for discussion of ionic strength effects on actinide carbonate 
complexes and some uncertainties in the databases [Pu stability constants, U-silicate stability 
constants]). The range of predicted chemistry is quite large and conservative, and further work is 
expected to only fine-tune the scenario and time dependent in-package chemistry. The 
calculated range of in-package chemistries is believed to represent the widest possible range of 
conditions that can confidently be expected. Indeed, a number of natural processes would tend 
to prevent more extreme chemistries than predicted here. Substantial reservoirs of freely 
exchangeable carbon dioxide would tend to prevent excursions to hyperalkaline conditions. 
Dissolution of solid components in the WP can buffer pH as well. The fact that free oxygen is 
likely to prevail in the drifts sets limits on how reduced WP fluids can become. Moreover, the 
accumulation of reactive corrosion products formed during WP degradation will also tend to 
buffer in-package solution chemistries. 
Based on the considerations discussed above, this model is appropriate for its intended use. 
In summary, the in-package geochemistry model was based on a large number of reaction path 
calculations covering a range of fluid fluxes, WP component degradation rates, and clad 
exposure scenarios. The calculated range of solution compositions is believed to encompass the 
most reasonable range of compositions of fluids that ultimately exit the WP. Nevertheless, the 
model outputs are valid only under the conditions stated above, and by necessity require a 
number of assumptions about the amount of WP components contacted by fluids, feedback 
between chemical compositions and corrosion, radiolysis, in-package evaporation, and the 
validity of the thermodynamic database. Wherever possible, these inputs have been used in a 
conservative fashion. Nevertheless, because there exist no complete long-term measurements of 
WP degradation, and because natural analogs for such a process are not known to exist, it is not 
possible to fully validate the model at this time, or to assign absolute confidence limits to inpackage 
chemistry outputs. Model outputs would be expected to be less valid if temperatures 
greatly exceed 25C, if in-package evaporation causes ionic strengths to exceed 1 mol/L, or if 
input solutions contact only certain parts of the WP rather than the entire WP.

 3-23
3.2.3 Other Views 
Chemistry inside of the WP affects the degradation of the waste form and the ability to support 
cladding credit. The TSPA Peer Review report (Budnitz et al. 1999, Section II.E) cited the 
TSPA-VA (DOE 1998b, p. 3-102) in noting that the chemistry within the WP, hence the long 
term performance of Zircaloy cladding, is not well understood and has considerable uncertainty. 
It also noted (Budnitz et al. 1999, Section II.G) that hydrogen production internal to the WP was 
not addressed adequately in the TSPA-VA (DOE 1998b). The peer review report (Budnitz et al. 
1999, Section IV.E) also cites an Nuclear Waste Technical Review Board (NWTRB) report to 
Congress (NWTRB 1998, p. 34) calling for theoretical and experimental work to predict the 
ranges of local environmental conditions that could exist inside a WP and identifies the need for 
more explicit definition of the geochemical environment during potential corrosion events, 
particularly within the WP (Budnitz et al. 1999, Section II.E). 
For the TSPA-SR analysis, the Waste Form Degradation Model now explicitly contains an In- 
Package Chemistry Component (a regression model based on process modeling) to predict 
ranges of chemical conditions inside the WP to better characterize the uncertainty in the 
degradation of the cladding and waste form. Ongoing sensitivity studies will provide more 
information. For the TSPA-SR analysis, the production of hydrogen was examined; however, 
the process was screened out in a FEP argument. 
3.3 CSNF DEGRADATION COMPONENT 
Under oxidizing conditions in the presence of liquid or vapor water, the UO2 in CSNF is not 
stable and alters. Alteration of the UO2 matrix can liberate radionuclides important to human 
dose. 
The main function of the CSNF degradation model component is to determine the rate of 
degradation of the CSNF fuel as a function of temperature and water chemistry (specifically, pH, 
and partial pressures of O2 and CO2) as shown in Figure 3.3-1. This degradation rate function is 
combined with the in-package chemistry to determine a rate, which is then directly used by the 
Cladding Degradation Model Component (Section 3.4) to determine the rate that the CSNF 
cladding splits open and exposes more of the fuel matrix. In addition, the CSNF degradation 
model examined the distribution of radionuclides within the fuel and established a gap fraction 
for the more volatile radionuclides. 
One AMR is the primary document supporting the CSNF Matrix Degradation Model 
Component, CSNF Waste Form Degradation: Summary Abstraction (CRWMS M&O 2000h) 
(see Figure 3.3-2). This, in turn, depends on the data reports of the major sets of experiments 
conducted on CSNF. A minor document supporting this AMR is Miscellaneous Waste-Form 
FEPs (CRWMS M&O 2000n). 
3.3.1 Model Description 
To determine the rate and consequences of CSNF degradation, dissolution of a number of fresh 
and spent fuels was examined under both saturated and unsaturated conditions using 
flow-through reactors as well as static, batch reactors and drip tests. Flow-through experiments 
involve passing fluids past a chamber containing CSNF fragments and allow rapid measurement

 3-24
of the dependency of CSNF forward dissolution rates on variables such as solution pH and pCO3. 
Batch tests involve placing a few grams of spent fuel in various configurations in less than a liter 
of synthetic J-13 groundwater, periodically sampling the solution, and analyzing for the 
appropriate radionuclides. These data provide information on the spent fuel dissolution rates for 
saturated conditions such as may occur if water pools within the WP. Unsaturated drip tests, in 
which the fuel is exposed to 100 percent relative humidity and various amounts of injected 
simulated groundwater, provide information on the degradation of the fuel in WPs that do not 
have pooling of water. The batch and unsaturated tests also give empirical information on 
secondary phase production, colloids, and effective solubility limits for the more insoluble 
radionuclides. 
From the many experiments performed, an understanding of the mechanisms of spent fuel 
dissolution has emerged. Commercial nuclear fuel is composed primarily of uranium dioxide 
which, when exposed to mildly oxidizing solutions, is oxidatively dissolved to uranyl ion, UO2
+2. 
The rate of UO2 oxidation depends on the interaction of specific surface species that control the 
rate-determining dissolution step. The increase in CSNF degradation rates with decreasing pH 
(at low pH), and with increasing carbonate levels (at high pH), suggests that adsorbed protons 
and/or carbonate ions control the dissolution reaction under flow-through conditions. Indeed, 
Grandstaff (1976) showed that the uraninite dissolution rate dependence on aqueous carbonate 
concentrations could be explained by using a Langmuir adsorption isotherm relating coverage of 
the surface by carbonate ions to carbonate solution concentrations. 
Important aqueous species that might also affect dissolution rates are calcium and silicon ions, 
which can form stable corrosion products possessing low solubilities. Electrochemical studies 
have shown fast reduction in dissolution currents when thin layers of corrosion products form, 
but an increase of UO2 reactivity as the applied potential is increased (Shoesmith 1999, 
Section 3.1.1). At very low applied potentials (< -400 mV vs. saturated calomel) very slow 
oxidation begins (possibly concentrating at grain boundaries); up to -100 mV, dissolution 
becomes discernible. As the applied potential increases to +300 mV oxidation, dissolution and 
corrosion product formation are significant; above +300 mV dissolution is rapid because 
corrosion products are not formed on the solid surface. The likely electrochemical reaction 
sequence is: 
surface oxidation bulk oxidation dissolution 
UO2 . UO2+x . UO2.33 . {UO2
2+}surface . [UO2
2+]bulk . [UO2
2+]soln . Secondary Phases 
The intrinsic dissolution rates of UO2+x and a number of spent fuels were determined by using a 
single-pass flow-through reactor that allows UO2 dissolution to be measured far from solution 
saturation (no precipitation of dissolved products). Note that the forward dissolution rate bounds 
the release rate, the latter being the material loss rate from the fuel + alteration products. 
Tables 3.3-1 and 3.3-2 show the tests and results from which the dissolution model for alkaline 
conditions (pH > 7) were regressed (CRWMS M&O 2000h, Equation 16): 
Log Rate = 4.69 + [-1085/T] - 0.12  p[CO3]T 
- 0.32  pO2 (Eq. 3.3-1) 
Rate has units of mg/m2day. T is temperature (kelvin); p denotes the negative logarithm of either 
the carbonate concentration (mol/L) or the oxygen partial pressure (atm).

 3-25
Table 3.3-1. Test Parameters and Dissolution Measurement Results for YMP Spent-Fuel Studies 
Run BUa LBU T (C) T (K) 1/T (K) 
Total 
CO3 p[CO3]T O2 pO2 
[H+] 
(mol/L)) pH DR LDR 
1 30 1.48 50 323 3.09E-03 0.002 2.70 0.2 0.7 1E-09 9 6.34 0.802 
2 30 1.48 50 323 3.09E-03 0.002 2.70 0.2 0.7 1E-09 9 7.05 0.848 
3 30 1.48 50 323 3.09E-03 0.002 2.70 0.2 0.7 1E-09 9 5.07 0.705 
4 30 1.48 22 295 3.39E-03 0.020 1.70 0.2 0.7 1E-08 8 3.45 0.538 
5 30 1.48 74 347 2.88E-03 0.020 1.70 0.2 0.7 1E-10 10 14.20 1.152 
6 30 1.48 74 347 2.88E-03 0.0002 3.70 0.2 0.7 1E-08 8 8.60 0.934 
7 30 1.48 21 294 3.40E-03 0.0002 3.70 0.2 0.7 1E-10 10 0.63 0.201 
8 30 1.48 22 295 3.39E-03 0.02 1.70 0.2 0.7 1E-09 9 2.83 0.452 
9 30 1.48 22 295 3.39E-03 0.002 2.70 0.2 0.7 1E-10 10 2.04 0.310 
10 30 1.48 27 300 3.33E-03 0.0002 3.70 0.02 1.7 1E-08 8 1.79 0.253 
11 30 1.48 78 351 2.85E-03 0.0002 3.70 0.02 1.7 1E-10 10 1.49 0.173 
12 30 1.48 25 298 3.35E-03 0.02 1.70 0.02 1.7 1E-10 10 2.05 0.312 
13 30 1.48 77 350 2.86E-03 0.02 1.70 0.02 1.7 1E-08 8 2.89 0.461 
14 30 1.48 23 296 3.38E-03 0.02 1.70 0.003 2.5 1E-08 8 2.83 0.452 
15 30 1.48 74 347 2.88E-03 0.02 1.70 0.003 2.5 1E-10 10 0.69 -0.16 
16 30 1.48 78 351 2.85E-03 0.0002 3.70 0.003 2.5 1E-08 8 1.98 0.297 
17 30 1.48 19 292 3.42E-03 0.0002 3.70 0.003 2.5 1E-10 10 0.51 -0.29 
18 30 1.48 50 323 3.09E-03 0.02 1.70 0.003 2.5 1E-10 10 1.04 0.017 
19 30 1.48 21 294 3.40E-03 0.002 2.70 0.003 2.5 1E-09 9 1.87 0.272 
20 30 1.48 75 347 2.88E-03 0.02 1.70 0.02 1.7 1E-10 10 4.75 0.677 
21 31 1.49 50 323 3.10E-03 0.002 2.70 0.2 0.7 1E-09 9 6.60 0.82 
22 50 1.70 25 298 3.39E-03 0.02 1.70 0.2 0.7 1E-08 8 1.50 0.18 
23 31 1.49 25 298 3.36E-03 0.02 1.70 0.2 0.7 1E-08 8 4.00 0.60 
24 31 1.49 75 348 2.87E-03 0.02 1.70 0.2 0.7 1E-08 8 9.10 0.96 
25 31 1.49 25 298 3.36E-03 0.0002 3.70 0.2 0.7 1E-08 8 2.60 0.41 
26 31 1.49 75 348 2.87E-03 0.0002 3.70 0.2 0.7 1E-08 8 11.00 1.04 
27 44 1.64 25 298 3.36E-03 0.02 1.70 0.2 0.7 1E-08 8 3.50 0.54 
28 50 1.70 25 298 3.36E-03 0.02 1.70 0.2 0.7 1E-08 8 3.80 0.58 
29 50 1.70 75 348 2.87E-03 0.02 1.70 0.2 0.7 1E-08 8 6.90 0.84 
30 50 1.70 25 298 3.36E-03 0.0002 3.70 0.2 0.7 1E-08 8 2.90 0.46 
31 50 1.70 75 348 2.87E-03 0.0002 3.70 0.2 0.7 1E-08 8 9.50 0.98 
32 50 1.70 25 298 3.36E-03 0.02 1.70 0.002 2.7 1E-08 8 4.1 0.61 
33 50 1.70 75 348 2.87E-03 0.02 1.70 0.002 2.7 1E-08 8 1.4 0.15 
34 50 1.70 25 298 3.36E-03 0.0002 3.70 0.002 2.7 1E-08 8 1.9 0.28 
35 50 1.70 75 348 2.87E-03 0.0002 3.70 0.002 2.7 1E-08 8 3.5 0.54 
36 15 1.18 25 298 3.36E-03 0.02 1.70 0.20 0.7 1E-08 8 3.2 0.51

 3-26
Table 3.3-1. Test Parameters and Dissolution Measurement Results for YMP Spent-Fuel 
Studies (Continued) 
37 15 1.18 75 348 2.87E-03 0.02 1.70 0.20 0.7 1E-08 8 11.9 1.08 
38 15 1.18 25 298 3.36E-03 0.0002 3.70 0.20 0.7 1E-08 8 3.7 0.57 
Source: CSNF Waste Form Degradation: Summary Abstraction. ANL-EBS-MD-00005 (CRWMS 
M&O 2000h, Table 1). The source document lists four additional runs; since they were not used 
for model development, they are not included here. 
NOTES: aBU = burnup MWd/kgU, LBU = log10 (BU), T = temperature, 
Total CO3 = [HCO3-] + [CO3
-2] in molar, p[CO3]T = -log10 (Total CO3) 
O2 = oxygen pressure in atmospheres, pO2 = -log10 (O2) 
DR = dissolution rate in mg/(m2day), LDR = log10 (DR) 
Table 3.3-2. Test Parameters and Dissolution Measurement Results for YMP UO2 Studies 
Run BUa LBU T (C) T (K) 1/T (K) 
Total 
CO3 p[CO3]T O2 pO2 
[H+] 
(mol/L) pH DR LDR 
39 0 b 50 323 3.09E-03 0.002 2.70 0.02 1.7 1E-09 9 12.30 1.090 
40 0 b 50 323 3.09E-03 0.002 2.70 0.02 1.7 1E-09 9 7.96 0.901 
41 0 b 50 323 3.09E-03 0.002 2.70 0.02 1.7 1E-09 9 10.4 1.015 
42 0 b 25 298 3.35E-03 0.02 1.70 0.2 0.7 1E-08 8 2.42 0.384 
43 0 b 75 348 2.87E-03 0.02 1.70 0.2 0.7 1E-10 10 77.38 1.889 
44 0 b 75 348 2.87E-03 0.0002 3.70 0.2 0.7 1E-08 8 10.9 1.036 
45 0 b 25 298 3.35E-03 0.0002 3.70 0.2 0.7 1E-10 10 2.55 0.407 
46 0 b 25 298 3.35E-03 0.02 1.70 0.002 2.7 1E-08 8 0.22 -0.666 
47 0 b 75 348 2.87E-03 0.02 1.70 0.002 2.7 1E-10 10 5.61 0.749 
48 0 b 75 348 2.87E-03 0.0002 3.70 0.002 2.7 1E-08 8 0.51 -0.292 
49 0 b 26 299 3.34E-03 0.0002 3.70 0.002 2.7 1E-10 10 0.23 -0.633 
50 0 b 26 299 3.34E-03 0.0002 3.70 0.02 1.7 1E-08 8 0.12 -0.922 
51 0 b 75 348 2.87E-03 0.0002 3.70 0.02 1.7 1E-10 10 9.21 0.964 
52 0 b 26 299 3.34E-03 0.02 1.70 0.02 1.7 1E-10 10 1.87 0.272 
53 0 b 75 348 2.87E-03 0.02 1.70 0.02 1.7 1E-08 8 5.11 0.709 
54 0 b 50 323 3.09E-03 0.02 1.70 0.002 2.7 1E-10 10 4.60 0.663 
55 0 b 25 298 3.35E-03 0.02 1.70 0.2 0.7 1E-09 9 6.72 0.827 
56 0 b 25 298 3.35E-03 0.002 2.70 0.2 0.7 1E-10 10 9.34 0.970 
57 0 b 26 299 3.34E-03 0.002 2.70 0.002 2.7 1E-09 9 1.52 0.180 
58 0 b 75 348 2.87E-03 0.0002 3.70 0.2 0.7 1E-10 10 6.48 0.812 
59 0 b 75 348 2.87E-03 0.002 2.70 0.2 0.7 1E-09 9 23.3 1.367 
60 0 b 75 348 2.87E-03 0.02 1.70 0.2 0.7 1E-08 8 54.0 1.700 
Source: CSNF Waste Form Degradation: Summary Abstraction. ANL-EBS-MD-000015. (CRWMS 
M&O 2000h, Table 1) 
NOTES: aBU = burnup MWd/kgU. LBU = log10 (BU), 
b log10 (0) is undefined, a LBU of 0 is used for modeling UO2. 
T = temperature, Total CO3 = [HCO3-] + [CO3=] in molar, p[CO3]T = -log10 (Total CO3) 
O2 = oxygen pressure in atmospheres, pO2 = -log10 (O2) 
DR = dissolution rate in mg/(m2day), LDR = log10 (DR)

 3-27
To construct the abstracted acid dissolution model, the temperature and oxygen rate 
dependencies derived under alkaline conditions were assumed to hold for acid conditions. The 
pH 7 alkaline rate was then assumed to be common to the alkaline and acid pH rate laws (within 
the uncertainty of both rate laws). A qualified data point (pH = 3) was used to define the low pH 
end of the acid pH rate law. The latter, which describes rates at pH = 7, is given below 
(CRWMS M&O 2000h, Equation 18): 
Log Rate = 7.13 + [-1085/T] - 0.32  pO2 - 0.41  pH (Eq. 3.3-2) 
The combined abstracted model is shown in Figure 3.3-3. 
As discussed in the AMR (CRWMS M&O 2000h, Section 6.2.2.2), pH dependence is weak 
under alkaline conditions and rate and pH are controlled by carbonate and oxygen. Under acidic 
conditions pH is a more significant factor, while p[CO3]T is less significant as (H+) protons 
dominate the surface reaction sites. 
3.3.1.1 Gap and Grain Boundary Inventory 
As summarized in CRWMS M&O (2000h, Section 6.5) some fission-produced radionuclides, 
14C, 135Cs, 137Cs, 129I, 99Tc, and 79Se, migrate from the UO2 matrix of light water reactor (LWR) 
spent fuels at the high fuel temperatures of reactor operation and deposit onto the cooler grain 
boundaries and fuel/cladding gap surfaces. At waste package and cladding breach, these 
radionuclides may be released faster than those within the fuel matrix. Volatile cesium and 
iodine, in addition to the fission gases, are the most conspicuous elements in this category. 
Recent performance assessments (CRWMS M&O 1998b, Section 6.3.1.3.1) of the potential 
repository at Yucca Mountain used gap and grain-boundary fractions of 2 percent of the total 
inventories of 135Cs, 137Cs, 129I, and 99Tc. The gap fraction was modeled to dissolve rapidly if the 
spent fuel were to be contacted by groundwater (CRWMS M&O 1998b, Section 6.3.1.3.2). 
Laboratory measurements of a few LWR spent fuels show that both the gap and grain boundary 
inventories of 99Tc and 90Sr were near the detection limits of the methods used, less than 0.2 
percent of the total inventories of these elements. However, some of the 99Tc may reside at the 
grain boundaries in the form of relatively insoluble metallic particles and not be detected by 
these tests. Measured combined gap and grain-boundary inventories of 129I approximately equal 
the fission gas release fractions. For 137Cs, the combined gap and grain-boundary inventories 
were approximately one third of the fission gas release fractions. For the TSPA-SR analysis, the 
fast release fraction consists of an immediate release of 4.2 percent of the total iodine inventory, 
and 1.4 percent of the cesium inventory. In addition, 0.2 percent (range 0 to 0.4 percent, 
uniformly distributed) of all the radionuclides including additional cesium and iodine is 
immediately released from the grain boundaries and fuel and gap surfaces. 
3.3.2 Confidence/Limitations/Validation 
The abstracted CSNF dissolution model was based on a large set of qualified flow-through 
experiments. It is valid from pH 3 to 10, oxygen pressure from 0.002 to 0.2 atmospheres, and 
total carbon concentrations from 2  10-4 to 2  10-2 molar. At pHs less than or equal to 7, this 
model is valid at CO2 pressures of 10-3 atmospheres. From an analysis of the fit of the model to 
the data, and from further consideration of the uncertainty of application of data from young

 3-28
spent fuel (< 30 years out of reactor) and unburned UO2 toward the prediction of long term 
(> 1,000 year) performance of spent fuel, the model was estimated to be valid to within 
1.5 orders of magnitude. This model was compared to unsaturated drip tests, batch tests, and a 
range of literature results. The model and uncertainty range adequately accounted for, or 
overestimated, all dissolution rate data. In addition, a comparison of the phases produced in the 
unsaturated drip tests compare well with that of natural analogs. 
Based on the considerations discussed below, this model is appropriate for its intended use. 
3.3.2.1 Comparison to Unsaturated Drip Tests 
Long-term drip testing of CSNF under hydrologically unsaturated conditions, i.e., limited water 
and an oxidizing atmosphere, has been done over the past six years to determine the relationship 
between the rate of CSNF alteration, i.e., dissolution and secondary phase formation, and the 
release rate of radionuclides. Small samples of two commercial PWR spent nuclear fuels, 
Approved Testing Material-103 and Approved Testing Material-106, are subjected to three 
experimental conditions: vapor injection, low-drip-rate injection, and high-drip-rate injection, all 
at 90C (CRWMS M&O 2000h, Section 6.3). All drip samples were completely wetted. The 
nominal drip rate is 0.75 mL every 3.5 days in the high-drip-rate tests and 0.075 mL every 3.5 
days in the low-drip-rate-tests. In the vapor tests, minimum water is available for transport, and 
the absence of added cations and anions limits the type of alteration products (secondary phases) 
that may form. A CSNF intrinsic dissolution/corrosion rate is estimated from the release of 
highly soluble 99Tc and 90Sr which are assumed to be homogeneously distributed in the spent 
fuel matrix (129I and 137Cs are concentrated at the fuel grain boundaries and fuel-clad gap). 
In the high-drip-rate tests iodine release rates decreased about an order of magnitude after 
1.3 years of reaction. Tc release remained relatively constant over time and appears to depend 
on the initial burnup of the fuel. Less than 1 percent of the reacted uranium was released into 
solution after 1.6 years. Most of the neptunium and plutonium release occurred in the first year. 
Thereafter, nearly all of the 237Np (96.5 - 99 percent) and 239Pu (99.5 - 99.6 percent) was 
retained. Transmission-electron microscope examination (Finn et. al. 1998) indicates that the Pu 
is retained as a residue at the fuel surface. Of the 0.01 percent of the Pu that is released into the 
leachate, greater than 50 percent is sorbed on the walls of the stainless steel vessel (the remainder 
is colloidal). After 4.8 years of reaction, 129I and 99Tc release rates are similar. 
In the low-drip-rate tests, 99Tc release rates increased by 2.5 orders of magnitude when the fuel 
was immersed in leachate at 3.1 years, suggesting that the 99Tc that was originally dissolved had 
become loosely bound to the corrosion products before immersion. Apparently pertechnetate, 
TcO4
, precipitates as a soluble salt as the liquid in the low-drip-rate test becomes concentrated. 
When excess water is introduced as in an immersion test, the salts dissolve and Tc, Cs, and Sr 
are released. 
In the vapor hydration tests, material transport may occur by one of two pathways: thin-film flow 
or spallation of unwashed fuel fines. Radioisotope release rates were observed to vary 
substantially between the different fuel types that were considered. The cause of this remains 
unclear.

 3-29
If a roughness factor (the ratio of the measured surface area to the geometrically estimated 
surface area) of three is assumed, the high-drip-rate dissolution rates are estimated to be 17 and 
38 mg/(m2d), compared against a predicted value of 22 mg/(m2d) at pH 8, 0.001 mol/L 
carbonate, and 90C for a fuel with a burnup of 30 MWd/kgU. Therefore, the agreement 
between the rate model above and 99Tc release rates is good. The calculations for the other 
isotopes show reduced release rates because the isotopes are retained in corrosion products. 
3.3.2.2 Comparison to Batch Tests and Literature 
The rate models can be compared against batch tests, published data cited in reviews by 
Grambow (1989) and McKenzie (1992) of pre-1992 literature, as well as more recent, 
flow-through measurements of de Pablo et al. (1997), Torrero et al. (1997), and Tait and Luht 
(1997). Batch dissolution rates are lower than predicted rates but within a factor of 6. The rate 
model above does not have as strong a carbonate dependency as that seen by de Pablo et al.s 
(1997) study. The alkaline pH model predicts 0.0002 mol/L total carbonate rates that are 
consistently higher than Torrero et al.s (1997) carbonate-free rates. The difference in carbonate 
levels though makes direct comparison impossible. Torreros acidic data can be as low as 1/20th 
of the predicted value, yet Torreros acidic data overall seem low compared to other work (see 
Grambow 1989). In general, the present model predicts Tait and Luhts (1997) results well at the 
various sample, temperature, oxygen, and water-chemistry conditions. Moreover, the trends in 
the model and data with temperature, carbonate, and oxygen are the same. The models 
underpredict Tait and Luhts (1997) data at bounding conditions, such as 75C, and 0.1 mol/L 
bicarbonate by at most 0.88 orders of magnitude, which is within the uncertainty range of the 
model. 
3.3.2.3 Natural Analogs 
To establish confidence that experimental CSNF alteration pathways effectively represent likely 
natural processes, it is useful to compare the alteration mineralogy observed in experiments with 
natural occurrences of altered uranium oxides. Uranium dioxide occurs in nature as the mineral 
uraninite which is structurally similar to CSNF. Nopal I, a uranium mining site at 
Pea Blanca, Mexico, contains substantial quantities of uraninite and is arguably one of the best 
natural analogs for CSNF degradation in Yucca Mountain as it possesses geologic, geochemical, 
and hydrogeologic characteristics most similar to those at Yucca Mountain (Murphy 1995). The 
volcanic (tuffaceous) host rock at Nopal I, the youngest of the studied sites, has been relatively 
oxidizing for tens of thousands of year, though uraninite, containing U4+, was originally formed 
several million years ago. 
In general, uraninite has been oxidized and hydrated at Nopal I. In the presence of silicate and 
alkali ions, such as calcium and sodium, various alkaline uranyl silicate hydrates such as 
Na-boltwoodite and -uranophane dominates alteration mineralogy at long times. 
In the vapor tests a relatively simple combination of uranyl oxy-hydroxide alteration phases is 
observeddehydrated schoepite (UO2)O0.25-x(OH)1.5+2x (0 = x = 0.15) and metaschoepite 
(CRWMS M&O 2000h, Section 6.6.2. (A minor phase is Cs-Ba-Mo-uranate, which incorporates 
two fission products, cesium and molybdenum.) Sodium and silicon are among the most 
abundant elements in J-13 well water, and, not surprisingly, the most abundant alteration product

 3-30
in the high-drip rate tests is the Na- and Si-bearing U6+ compound Na-boltwoodite; the Ca- and 
Si-bearing U6+ compound -uranophane has also been identified in solid samples from these 
tests. The higher-drip-rate tests exhibit two uranophane-group silicates, -uranophane 
[Ca(UO2)2(SiO3OH)2(H2O)5] and Na-boltwoodite (Na,K)(UO2)(SiO3OH)(H2O). Samples from 
low-drip-rate tests include metaschoepite, a Na-uranyl oxy-hydroxide tentatively identified as 
Na-compreignacite, and soddyite. Again, Cs-Ba-Mo-uranate is a minor constituent. In one 
sample, soddyite appears to replace Na-compreignacite. Also, a few isolated crystals of 
Na-boltwoodite were first detected in one low-drip-rate test. The groundwater at Nopal I is richer 
in calcium than J-13 (Pearcy et al. 1994) but poorer in sodium and potassium. This could 
explain the dominance of -uranophane at the natural site as well as the limited soddyite and 
weeksite occurrence. There is substantial calcite at Yucca Mountain. In time this may make 
repository alteration products conform more to the Nopal I sequence than that seen in the 
laboratory, which produces -uranophane at long times. Overall, the phase assemblage observed 
at Nopal I is similar to that derived experimentally in the CSNF alteration drip tests. 
The general agreement between the observed alteration products in the various tests, the natural 
analogs, and the geochemical modeling provide confidence that the mechanisms of spent fuel 
corrosion are well understood, and that the forward dissolution model is bounding for long term 
prediction of CSNF degradation rates. 
3.3.3 Other Views 
The TSPA Peer Review Panel Report (Budnitz et al. 1999, Executive Summary, Section E, Data 
and Research Needs) stressed the importance of advancing the spent fuel corrosion model 
beyond its VA representation, stating that a considerable knowledge of spent fuel corrosion is 
needed. It noted that the databases used in the VA for the corrosion of spent fuel were not 
adequate (Budnitz et al. 1999, Section II.A). It also noted that the processes that ensue among 
the WP internals following penetration of the package were not addressed in any depth within 
the TSPA-VA (Budnitz et al. 1999, Section II.F). The panel also questions the conservatism of 
the related base case conditions. It suggested that steps be taken to develop better methods for 
analyzing the movement of radionuclides from the WPs. Substantial discussion was dedicated to 
discussion of weaknesses in the VA spent fuel corrosion model (Budnitz et al. 1999, 
Section IV.F). 
Weaknesses in the VA spent fuel corrosion model and documentation were identified by the peer 
review panel. These were addressed in the development of the SR model and documentation as 
discussed in Section 3.3 and CRWMS M&O 2000h. In particular, the mechanistic basis was 
discussed, a simplified model was developed, and model validation using an expanded database 
was performed. Removing the conservatism of modeling of water-waste contact and 
radionuclide transport within the package was not given priority for SR, because in-package 
radionuclide transport was not determined to be a principal factor for the safety case. However, 
the cladding degradation and the waste matrix degradation have been coupled as explained in 
Section 3.4 and the degradation of the waste matrix was also coupled to the in-package chemistry 
to better characterize uncertainty as explained in Sections 3.2 and 3.3.

 3-31
3.4 CSNF CLADDING DEGRADATION COMPONENT 
3.4.1 Introduction 
Since the 1950s, most CSNF has been clad with less than 1 mm (usually between 600 through 
900 m) of Zircaloy, an alloy that is about 98 percent zirconium with small amounts of tin, iron, 
nickel, and chromium. The Zircaloy cladding is not a designed engineered barrier of the Yucca 
Mountain disposal system, but rather is an existing characteristic of the CSNF that is important 
to determining the rate of release of radionuclides once engineered barriers such as the waste 
packaged have breached. Zircaloy is very resistant to corrosion, and cladding failure is expected 
to be minimal in the first 10,000 years. However, while Zircaloy provides excellent protective 
properties, characterization of the uncertainty in its performance is important. This 
characterization is possible since data have been collected on its performance over the past 
40 years by the nuclear industry and by others in several different harsh environments. 
3.4.1.1 Function of Cladding Degradation Component 
The cladding degradation component of the Waste Form Degradation Model predicts the rate 
that the CSNF matrix is exposed and altered based on the number of rods with perforated 
cladding at any one time. 
3.4.1.2 Summary of Conceptual Model of CSNF Cladding Degradation 
The degradation of CSNF cladding is assumed to proceed through two distinct steps: (1) rod 
failure (perforation of the cladding) and (2) progressive exposure of UO2 spent fuel matrix (see 
Figure 3.4-1). The number of failed rods is based on the observed rod failures while in the 
reactor and during storage, potential creep failures because of high disposal temperatures, stress 
corrosion cracking from high stresses and the presence of halide ions, hypothetical physical 
failures from seismic loads, and hypothetical localized corrosion inside the WP. In all cases, the 
perforation is assumed to occur at the center of the rod because this ensures the fastest exposure 
of the waste matrix. After the initial perforation, further cracking and splitting of the cladding is 
assumed to occur, which exposes the CSNF matrix as it progresses. The splitting of the cladding 
(unzipping) is calculated as a function of the CSNF matrix alteration rate, which was described 
in the previous section, Section 3.3. 
3.4.1.3 Modes for Initiating Cladding Perforations 
Cladding perforation is the formation of small cracks or holes in the cladding. Perforation of the 
cladding may occur because (1) the cladding initially fails within the reactor or during storage, 
(2) the cladding fails from creep or stress corrosion cracking, (3) an earthquake severely shakes 
and severs the rods, or (4) the cladding fails from localized corrosion (Figure 3.4-2). While 
other mechanisms of initiating cladding perforations such as diffusion controlled cavity growth 
(DCCG) or DHC were explored, they were screened out based on low consequence as described 
later.

 3-32
3.4.1.4 Cladding Failure after Perforation 
After the cladding has been perforated, the fuel matrix can react with moisture or air. The 
reaction is assumed to unzip the fuel rod because the fuel volume increases during oxidation of 
the UO2, (i.e., the oxidation of the UO2 to secondary phases of uranium is assumed to cause 
enough pressure by volume expansion to burst the cladding from within) (Figure 3.4-2). This 
mechanism for increasing the exposed surface area of the matrix is sensitive to environmental 
conditions such as temperature. Based on observed behavior within storage pools at reactors, 
unzipping in a wet environment does not occur in observed time periods of 40 years, once the 
Zircaloy cladding has been perforated. However, because unzipping in a wet environment could 
not be entirely ruled out and because complete exposure of the matrix bounds diffusive releases 
of radionuclides through the pinhole perforations, the project included the possibility of the clad 
unzipping in a wet environment (Figure 3.4-2). A small percentage of the inventory of iodine, 
cesium, and a few other radionuclides resides in the gap between the cladding and waste matrix. 
The release of the gap inventory is assumed to be instantaneous when the cladding is perforated 
and, thus, independent of the cladding unzipping. Cladding that was initially perforated is 
predicted to release its gap inventory when the WP is breached. 
3.4.1.5 Documents Supporting Model Development 
To carefully examine and describe the uncertainty about the expected protective capability of the 
cladding, eight AMRs and two calculations were prepared. One AMR dealt strictly with FEPs 
related to cladding to more carefully focus attention on hypothetical failure modes. Three AMRs 
dealt with specific modes of potentially perforating the cladding, an AMR and calculation dealt 
with evaluating temperatures of the cladding for creep calculations, and two AMRs dealt with 
further exposure of the cladding through unzipping (Figure 3.4-3). 
3.4.2 Description 
3.4.2.1 Initial Cladding Condition 
3.4.2.1.1 Initial Cladding Perforations 
Two aspects of initial cladding condition are important (Figure 3.4-2). The first aspect is the 
number of rods of CSNF that arrive for disposal with cladding perforations and is discussed in 
this subsection. The second aspect is the condition and characteristics of the unperforated 
cladding (e.g., the internal pressure and strain history of the cladding) and is discussed in the 
next subsection. Because of the propensity of stainless steel to stress corrosion crack (SCC), all 
of the stainless steel cladding (~1.1 percent of the CSNF) is considered as a separate category of 
CSNF and is assumed to be initially perforated. In the Zircaloy cladding category, the percent of 
rods arriving at the repository with perforations is dependent on the number of rods that perforate 
while (a) in the reactor (including fuel handling), (b) in pool storage or dry storage (including 
fuel handling), and (c) in transportation from storage. Data exist for all three aspects. Based on 
the data, the largest percentage of rods perforate when first placed in the harsh reactor 
environment (CRWMS M&O 2000p, Section 7, Table 13) (Table 3.4-1). Few perforations occur 
in the second and third cycles of the reactor operation or during storage and transportation. 
Some data for reactor perforations extend over the operating history of the commercial nuclear

 3-33
industry. The data for perforations used for TSPA-SR span the period 1969 through 1995. As 
described in CRWMS M&O 2000p, between 1969 and 1985, a contractor report for NRC is 
used; between 1985 and 1995 updates as reported in the literature are used. The data on 
perforations are based on ~65,000 BWR assemblies with ~4 million rods and ~47,000 PWR 
assemblies with ~10 million rods (CRWMS M&O 2000p, Attachment I). 
Currently most fuel is stored in pools at reactors but in the future much may be placed in dry 
storage. Of these two methods of storage, dry storage has higher temperatures and thus greater 
propensity to cause perforations. While not extensive, data have been collected and estimates 
made on future cladding perforations while in dry storage in studies done by the DOE at the 
INEEL and Pacific Northwest National Laboratory. Cladding failures during transportation have 
also been estimated in order to license transportation casks for the NRC (CRWMS M&O 2000p, 
Section 6.11). 
Table 3.4-1. Percent and Cause of Rods Failed in a Waste Package 
Rod Perforation Mode Percent of Rods Perforated/WP 
Reactor Operation including handling perforations (mean) 0.109; Range: 0.0 to 5.23 
Pool Storage 0.0 
Dry Storage (including handling) 0.045 
Dry Storage & Transportation from DHC 0.0 
Transportation (vibration, impact) 0.01 
Total 0.164; Range: 0.055 to 5.28 
Source: Initial Cladding Condition. ANL-EBS-MD-000048. (CRWMS M&O 2000p, Table 13). 
To include uncertainty in TSPA-SR, a distribution of initial rod perforations in a WP, expressed 
as a complementary cumulative distribution function (CCDF), was developed from the available 
data on cladding perforations. When developing the distribution of the perforations per WP, 
however, the type of blending assumed in the WP can be important since the performance of 
cladding has greatly improved over the years; in the mid-1970s, Zircaloy cladding perforations 
were much greater (still less than 5 percent) than observed today (less than 0.1 percent). The 
SNF of the 1970s has lower initial burnup and has also cooled longer and so this CSNF fuel will 
likely be blended with newer, hotter CSNF of today to keep the waste packages at a more 
uniform temperature. 
Conservatively assuming, however, that no blending occurs, a CCDF can be developed that is 
the sum of the CCDF of Zircaloy cladding perforations during reactor operations and the 
perforations during storage and transportation. The small number of perforations that occur 
during storage and transportation (Table 3.4-1) does not have the ability to significantly affect 
the shape of the distribution for initial perforations; consequently, no ranges or distributions were 
assigned to the data on storage and transportation. A reasonable upper bound to this CCDF can 
be developed by assuming that whenever a rod was damaged (say from handling), all four rods 
in a square cluster were damaged. The distribution was assumed to be symmetric and so the 
lower bound was developed by dividing by 4 (Figure 3.4-4). 
Potential perforation from creep rupture or stress corrosion cracking is not included as part of the 
initial perforation in Table 3.4-1. Rather this was treated as incipient perforation information and

 3-34
became part of the initial condition of unperforated cladding discussed in the next subsection. 
The creep rupture analysis was integrated because the rod damage from one period must be 
carried forward to the next temperature period to calculate the total strain and thus potential for 
creep rupture. Stress corrosion cracking is also addressed in the same manner because the same 
highly stressed rods are susceptible to failure from either mechanism. 
3.4.2.1.2 Initial Condition (Pressure and Strain) of Unperforated Cladding 
The fact that few cladding perforations occur after the first cycle in a reactor suggests that there 
are few rods almost ready to perforate (i.e., incipient perforations). Nonetheless, in order to 
analyze the potential perforation of the Zircaloy cladding from creep rupture or stress corrosion 
cracking after disposal, the initial condition of the cladding (e.g., internal pressure and strain 
history) was also estimated and uncertainty included (Figure 3.4-2) (CRWMS M&O 2000p, 
Section 6.7). Table 3.4-2 summarizes the distributions of the various properties developed for 
TSPA-SR. The CCDFs for the various properties are not independent; consequently, they were 
generated using a single burnup distribution based on PWR cladding to maintain consistency. 
PWR cladding was modeled rather than BWR cladding because BWR cladding is thicker, BWR 
fuel is enclosed in flow channels which offer additional protection to the cladding, and BWR fuel 
is discharged with lower burnup and thus lower cladding stress. 
Table 3.4-2. CCDFs Describing Expected Fuel Stream into YMP 
Property Mean Value 5 Percent CCDF Value 
Burnup 44.1 MWd/kgU 63.3 MWd/kgU 
Helium fill Pressure 3.71 MPa 4.99 MPa 
Fission Gas Release 4.2% 10.8% 
Free Volume 17.7 cm3 14.1 cm3 
Internal Pressure 4.8 MPa 7.34 MPa 
Oxide Thickness 54.2 m 112 m 
Hydride Content 358 ppm 738 ppm 
Crack Size 19 m 57.1 m 
Cladding Thickness 522 m 475 m 
Stress 38.4 MPa 61.8 MPa 
Stress Intensity Factor (KI) 0.47 MPam0.5 1.08 MPam0.5 
Source: Initial Cladding Condition (CRWMS M&O 2000p, Table 12) 
3.4.2.2 Temperature History of Cladding and Fuel Matrix 
In order to calculate the strain for creep rupture and hoop stress for stress corrosion cracking, the 
temperature history during storage and transportation is needed. The analysis assumed all 
Zircaloy cladding was placed in dry storage at the design temperature of the Castor Mark V WP. 
Dry storage and the Castor Mark V package with 55 MWd/kgU burnup fuel was selected to be 
conservative. For transportation, the cladding was conservatively assumed to be placed in a 
shipping cask for 3 weeks at a temperature of 350C. This is conservative since most rods will 
actually be exposed to lower temperatures for a shorter time frame.

 3-35
In addition to the temperature history of the unperforated cladding prior to disposal, the 
temperature of the cladding during disposal is needed (Figure 3.4-2). (Only hoop stress is 
considered since thermal stresses from differences in temperature are negligible because of the 
uniform temperatures in the WPs.) For TSPA-SR, a functional relationship between average 
surface temperature of the waste package and the temperature of the cladding was developed 
(Figure 3.4-5); the functional relationship was based on a heat conduction model. Because the 
temperature decreases from the center to the outside of the waste package, the waste package 
was discretized into six zones and a separate temperature profile is developed for each zone. 
Evaluation of cladding and matrix temperatures from the waste package surface temperature 
(Figure 3.4-6) gives the cladding temperature for the average center rod in a WP. In the 
repository, the average center rod cladding temperature peaks at 308C; there is a 13 percent 
uncertainty distribution included. The uncertainty addresses both the uncertainty in WP internal 
temperature distribution and the uncertainty in predicting the WP surface temperature. In the 
statistical analysis of 12,000 fuel rods, the full range of temperature uncertainties is sampled. 
After 1,000 years the WP surface temperature and internal temperatures are practically identical 
and so the WP surface temperature is used. The calculation of internal temperatures is fairly 
independent of the design of the engineered barrier since the WP surface temperature is treated 
as an independent variable in this approach. Only the WP surface temperature is needed to 
correctly account for the engineered barrier design. 
3.4.2.3 Creep Strain and Stress Corrosion Cracking Perforation 
From the statistical expression of the initial internal pressures, temperature history during 
transportation and storage, and the temperatures during disposal, the perforations from creep and 
stress corrosion cracking are calculated in the CSNF Cladding Degradation Component 
(Figure 3.4-2). 
This approach is recommended in both the Pescatore and Cowgill (1994, p. 85) review of creep 
analysis and a recent NRC Interim Staff Guidance for analysis of creep damage during dry 
storage (NRC 2000b, p. 85). It is the methodology used in Germany (Peehs 1998, 
Figures 11 to 13) for licensing dry storage designs. Uncertainties are established based on both 
experimental observations and analysis. This analysis is appropriate for the TSPA since it uses 
both accepted methodology, and sufficient uncertainties. 
Murtys creep strain correlation (Henningson 1998, p. 57), with appropriate uncertainties, was 
used for creep rupture for TSPA-SR. 
Table 3.4-3 compares six different creep rupture correlations to 503 data points reported in five 
different sets of experiments. It should be noted that the stresses and temperatures are 
appropriate for higher stressed rods in a hot repository. While the Matsuo correlation (Matsuo 
1987, p. 23) has a slightly smaller relative error, Murtys correlation was selected because it 
explicitly models Coble creep, a type of creep that could be important at lower stresses and 
temperatures. The uncertainty in the creep correlation was set at 0.80, which was the maximum 
relative error range for Murtys correlation. The uncertainty was assumed to be uniformly 
distributed. Both the data and correlations are for unirradiated cladding. Irradiated cladding has 
a creep rate of about 1/3 that of unirradiated material (Peehs 1998, Figure 10). Most of the data, 
correlations, and earlier creep analyses were for unirradiated cladding. The use of an

 3-36
unirradiated creep correlation introduces a conservatism that could be removed with additional 
creep modeling. 
Table 3.4-3. Comparison of Relative Error of Creep Correlations for All Data Points 
Creep Correlations 
Referenceb 
Total Data 
Pointsa Matsuo Murty Mayuzumi Limback Spilker Peehs 
Spilker, T2 192 0.758 0.727 0.648 0.560 0.344 0.726 
Spilker, T3 240 0.340 0.482 0.901 1.779 2.256 0.546 
Matsuo 21 0.135 0.392 0.640 0.557 1.994 0.521 
Mayuzumi 31 0.282 0.283 0.121 0.477 1.291 0.579 
Limback 19 0.334 0.417 0.142 0.145 1.354 0.596 
Average 0.487 0.557 0.717 1.121 1.431 0.606 
Source: Clad Degradation-Summary and Abstraction. (CRWMS M&O 2000i, Table 3) 
NOTE: Values are: Absolute Value ([Calculated-Measured]/Measured) 
aTotal number of points : 503 
bTests: unirradiated material, over the range 250 = T (C) = 385 and 55 = Stress (MPa) = 120 
A CCDF of the strain required for creep failure was constructed from a series of tests by Chung 
et al. (1987, pp. 780, 781). Chung et al. did a series of 20 slow burst and mandrel tests with 
irradiated BWR and PWR cladding. Half the tests were for over 200 hours. They measured an 
average strain at failure. The average failure strain was 3.3 percent with a range of 0.4 percent to 
11.7 percent (18 data points reported). The lower values of this range are for BWR rods, which 
burst at lower strains. The creep-failure analysis covers the full range of observed failures. 
CRWMS M&O (2000p, Section 6.10.1), compares this failure criterion to four (4) different 
failure criteria developed by four different sources and shows that this criterion is conservative. 
Figure 3.4-7 gives the CCDF for the hoop stress (at room temperature) in the rods expected to be 
received at YMP. A sampling of 2,000 rods with stresses that define this distribution is used for 
the stress variation. One rod (total of 12,000 rods analyzed, 2,000 rods located in each of 6 
regions) with each of these stresses is assumed to be in each of the six regions across the WP. 
This rod represents a specific fraction of the total WP inventory. Each rod is exposed to a 
temperature profile represented by Figure 3.4-6 (including dry storage and shipping) and a 
repository temperature history normalized by a WP radial-shaping factor. A uniform 
temperature uncertainty of 13.5 percent is included. The creep strain is then calculated for the 
rod using the equations given in the AMR for Clad Degradation-Summary and Abstraction 
(CRWMS M&O 2000i, Section 6.2.4) (including a uniform uncertainty of 80 percent). This 
strain is compared to a random sampling of the strain limit CCDF. If the rod creep strain 
exceeds the strain limit, it is assumed that the fraction of rods represented by that radial zone in 
the WP has become perforated and is available for cladding unzipping. This procedure is 
repeated for 12,000 rods in an Excel spreadsheet and the fraction of the WP inventory perforated 
is calculated. In TSPA-SR, for a typical WP, the fraction of rods failed by creep ranges from 
1.1 percent to 19 percent. The best estimate is 2.4 percent. A triangular distribution is sampled 
between these limits. These failures are predicted for dry storage and transportation.

 3-37
The above analysis has not been directly incorporated into the TSPA, but an abstraction has been 
included. For this abstraction, the independent variable is the peak WP surface temperature. The 
above analysis is performed for peak WP surface temperatures that vary from 177C to 412C. 
The cladding temperature history while in the WP (right side of Figure 3.4-6) is linearly shifted 
upward or downward by the difference between the base case and new peak WP surface 
temperature. The change in temperature across the WP is then calculated. 
Figure 3.4-8 is a graphical representation of the abstraction used in TSPA. The plateau at the 
lower WP surface temperatures represents the rods that are failed in dry storage and shipping. 
These rods can only fail once and, therefore, these rods cannot fail again in the repository. Rods 
that have not failed have undergone some creep during dry storage and shipping and start the 
additional creeping from that point. Figure 3.4-8 shows that at a peak WP surface temperature 
above about 300C, the best estimate fraction of rods perforated from creep increases 
dramatically. The upper limit represents the fraction of rods failed if the failure criterion is 
0.4 percent creep, the minimum value in the failure criteria CCDF. The minimum values 
represent the fraction of rods that would fail if the maximum failure criterion of 11.7 percent 
were applied. The best estimate value represents a random sampling of the failure criteria 
CCDF. In the TSPA, a triangular distribution is used between the upper limit, best estimate and 
lower limit in each realization to incorporate uncertainties in the WP peak surface temperature. 
Stress corrosion cracking (SCC) is considered along with creep rupture as a perforation 
mechanism since both require evaluating cladding stresses (Figure 3.4-2) (CRWMS M&O 2000i, 
Section 6.2.4). SCC requires a susceptible material, an aggressive chemical environment, and a 
high stress level (CRWMS M&O 2000ag, Section 6.1.11). Zircaloy is not susceptible to SCC in 
NaCl, HCl, MgCl2, and H2S solutions (Yau 1992, p. 299-311). The environments known to 
cause SCC in zirconium include FeCl3, CuCl2, halogen or halide-containing methanol, 
concentrated HNO3, liquid mercury or cesium (Yau 1992, p. 303), and 64 to 69% H2SO4 
(Fitzgerald and Yau 1993). The extremely oxidizing acidic conditions are not predicted for the 
bulk in-package chemistry but the possibility of such conditions occurring locally and 
transiently, are included in the local corrosion model. However, iodine has been identified by 
several investigators as a cause of SCC in Zircaloy. Iodine stress corrosion cracking (I-SCC) 
requires an iodine concentration in the fuel-cladding gap greater than 5  10-6 g/cm2. Below this 
threshold of free iodine concentration, Zircaloy cracking due to I-SCC has not been observed. 
Free iodine concentrations are expected to be negligible in SNF. For the TSPA-SR it was 
conservatively assumed that a sufficient amount of iodine was present on the cladding, the stress 
was high, and that the duration of elevated temperatures was sufficiently long that once cracking 
started, there was sufficient time to propagate through the cladding. The gas pressure inside the 
cladding and the resulting stress were evaluated (CRWMS M&O 2000p, Section 6.7). It was 
assumed that any fuel rod with a stress above 180 MPa perforated by SCC. This threshold was 
reported by Tasooji et al. (1984, Figure 3, p. 600). Few rods have such high stresses and the 
same rods that fail from SCC are also prone to perforation from creep rupture. The calculations 
were combined, to avoid double counting perforated rods. The inclusion of SCC increases the 
failure from creep alone from 0.49 percent to 1.1 percent for dry storage and transportation (left 
side of Figure 3.4-6). At higher repository temperatures, the difference disappears.

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3.4.2.4 Localized Corrosion Perforation 
Local corrosion is also considered as a perforation mechanism in the CSNF Cladding 
Degradation Component (Figure 3.4-2). Corrosion of zirconium has been observed in 
concentrated fluoride or chloride solutions at very low pHs or very high oxidation potential 
(CRWMS M&O 2000ag, Section 4.1). These conditions are not predicted to occur in the bulk 
solution (see Section 3.2), but have not yet been ruled out for localized and/or non-equilibrium 
effects such as MIC, galvanic coupling, radiolysis in a humid environment, and extreme 
concentration by evaporation. Each of these mechanisms may locally depress the pH or increase 
the concentration of corrosive species such as fluoride or chloride, at least temporarily. None of 
these conditions are expected to impact cladding performance under repository conditions. 
However, until they can be ruled out, or shown to be too transitory to have negative 
consequences on cladding, a conservative model has been adopted to bound the uncertainty. 
This conservative model uses two severe assumptions. The first assumption is that there is no 
filling or flushing of waste package by water. This is the worst case for concentration of 
aggressive species and breach of cladding. It is assumed that ground water entry occurs while 
there is still significant heat and/or radiation. The water flow rate must nearly match the 
evaporation rate within the package. If the flow is too high, the package will fill and overflow. 
The scenario of a filled, well-mixed, overflowing package is covered by the in-package 
chemistry model, which shows only moderate pH reduction (CRWMS M&O 2000g, 
Section 6.1). The scenario with flushing is the worst for transport of species out of the package, 
but is not the worst for cladding performance. Filling the package with water displaces the 
nitrogen that otherwise might be radiolytically converted to nitric acid. Overflow will flush out 
aggressive species, and prevent ground water from concentrating to the point of promoting 
galvanic corrosion of the carbon steel basket materials. Oxygen influx is also greatly reduced in 
a flooded waste package, so the corrosion potential and corrosion rates are reduced, as are many 
radionuclide solubilities. 
The second assumption is that aggressive species concentrate in the worst possible way. 
Because fluoride and chloride are consumed by reaction with Zircaloy (CRWMS M&O 2000ag, 
Section 6.2.2.3.2) and carbon steel (McCright 1998, Section 2.1.8), respectively, it is assumed 
that aggressive species from incoming water will concentrate where they can do the most 
damage. For fluoride, this would be nearly total evaporation of incoming drops on a drop-width 
section of a single fuel rod. For chloride, this would be in a crevice between Zircaloy and carbon 
steel basket materials. It is assumed that the incoming water species are directed to a single rod, 
until they have breached that rod. Then it is assumed that new aggressive species are directed to 
another single rod until it is breached, and so on. In this approach, the fraction of cladding 
perforated is linearly dependent on the water inflow, which generally increases with time as the 
waste package degrades. Inflow, however, is also a function of other factors such as climate, 
location within the repository, etc. The likelihood of significant concentration of aggressive 
species decreases with time, as decay heat and radioactivity decrease, likelihood of good 
galvanic connection to the Zircaloy decreases, and amount of reduced iron as an energy source 
for microbes decreases. The trend toward less aggressive conditions is ignored, however, as it is 
assumed that the aggressive species concentrate in the worst possible way for all time.

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Figure 3.4-9 shows an example: with 50 liters/year of water entering the WP, 20 percent of the 
rods would fail by this mechanism in 10,000 years of water flow. 
3.4.2.5 Physical Perforation 
The CSNF Cladding Degradation Component also considers physical perforation of the Zircaloy 
cladding from mechanical and seismic loads (Figure 3.4-2). Rubble (from the drift wall) falling 
onto the cladding when the WP collapses can perforate the cladding but was not modeled since 
WP collapse takes hundreds of thousands of years to occur. During this time, other modes of 
perforating the cladding (e.g., localized corrosion) are predicted to occur. 
Studies of rock fall (CRWMS M&O 2000ah, Section 6) have concluded that credible rock falls 
will not be sufficient to make the drip shield contact the waste package. Therefore, rock falls 
will not cause cladding perforation. Even an earthquake so strong that it occurs only once in 
100,000 years would not perforate the CSNF cladding. Only severe seismic events with a 
frequency of 1.1  10-6/year can perforate the cladding and were used in CSNF Cladding 
Degradation Component. This event perforates all the cladding and makes it available for 
unzipping. 
3.4.2.6 Other Perforation Mechanisms Evaluated (Features, Events, and Processes) 
Other cladding degradation mechanisms were reviewed using FEPs screening arguments 
(CRWMS M&O 2000s) (see Section 2.3). The results are summarized below. 
Hydride Failures-A review of the various hydride degradation mechanisms was performed for 
TSPA-SR (CRWMS M&O 2000p, Section 6.10.2). DHC of existing cracks was analyzed using 
the distribution of stresses and crack sizes summarized in Table 3.4-2. Stress intensity factors 
were calculated and have a mean of 0.44 MPam0.5 (range 0.002 to 2.7 MPam0.5); this intensity 
factor is below the usual threshold, which ranges from 5 to 12 MPam0.5. Therefore, crack 
propagation by DHC was not expected and was screened out based on low consequence. The 
calculated stress intensities are also below those needed to produce embrittlement failures (KI < 
KIC) and so embrittlement was screened out based on low consequence. Perforation of the 
cladding by hydride reorientation is also unlikely and has not been included in the abstraction for 
TSPA-SR because of the its inability to cause significant consequences. Stresses and 
temperatures are too low for reorientation to occur, and the material will maintain sufficient 
strength even if reorientation did occur, so failure would not be expected (CRWMS M&O 2000r, 
Section 6.4). 
Hydride Embrittlement of Cladding is UnlikelyHydrogen will be generated in the WP as the 
WP internals corrode. This hydrogen is not absorbed because the H2 molecules do not migrate 
through the high-density zirconium oxide layer. Available data on zirconium hydriding indicate 
that corrosion of WP internals will not result in hydriding of fuel cladding. 
Although hydriding as a result of galvanic corrosion has been observed, cladding alloys resist 
such corrosion on contact with carbon steel, and, if such an effect should occur, corrosion of the 
carbon steel would quickly break the electrical contact between the materials. Hydriding from

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Inconel contact requires smearing the Inconel into the zirconium metal matrix and then occurs 
only for a short time. 
Waterlogged Rods-The fraction of fuel rods with breached cladding is small (~0.16 percent). 
Most moisture can be removed from defective rods by standard drying processes. When drying 
the handling can be minimized. The impact of any residual amount of moisture is insufficient to 
cause significant corrosion of the internal structural portion of the WP and further degradation of 
the cladding. Furthermore, any moisture available would likely be consumed first by any CSNF 
exposed by the initially perforated cladding; therefore, the issue is excluded based on low 
consequence. 
General Corrosion of Cladding-General corrosion is synonymous with zirconium oxidation. 
The outer surface of the cladding becomes coated with oxide (ZrO2). Because this ZrO2 is of high 
density and adheres to the surface, it slows down further oxidation. The oxidation can be from 
O2 consumption (dry oxidation) or H2O consumption (wet oxidation). Once the fuel assemblies 
are placed in the waste package, further oxidation cannot occur until the WP is penetrated. Wet 
oxidation has been studied for over forty years because of the importance of cladding 
performance in reactor operation. Furthermore, the metallurgical condition of cladding while in 
storage has been investigated. There was no significant degradation of the Zircaloy cladding. 
Various analyses have concluded that cladding oxidation under repository conditions would not 
lead to perforation within 10,000 or even 100,000 years. The conclusion from this analysis is that 
general corrosion will not perforate the cladding during the regulatory period (CRWMS 
M&O 2000s, Section 6.2.3). 
Microbially Influenced Corrosion of Cladding-There is no experimental evidence that 
microbially influenced corrosion (MIC) occurs on zirconium metal or alloys. The two major 
forms of MIC for materials being considered for containment vessels in mined geologic 
repositories are (1) sulfide attack through the action of sulfate reducing bacteria and (2) corrosion 
induced by organic acids secreted from certain bacteria. With respect to these forms of MIC, 
(1) sulfate reducing bacteria do not affect zirconium, and (2) corrosion induced by organic acids 
is most unlikely because of zirconiums tolerance to organic acids and a wide range of pHs. 
However, MIC was not excluded as a mechanism for producing locally very acid conditions and 
is thus included in the conservative localized corrosion model. 
Acid Corrosion from Radiolysis -Zirconium is used for fuel cladding because of its high 
resistance to corrosion in highly acidic environments including those local environments in high 
radiation fields. Studies show that zirconium has excellent corrosion resistance to nitric acids 
and concentrated hydrogen peroxide. However, this process was not excluded as a mechanism 
for producing locally very acid conditions and is thus included in the conservative localized 
corrosion model. 
High Dissolved Silica Content of Waters Enhances Corrosion of Cladding-Silica is stable 
and is not corrosive to most materials, including Zircaloy. Therefore, this mechanism is 
excluded. The corrosion of Zircaloy in the presence of fluoride in silica saturated water (i.e., the 
formation of fluosilicic acid) is not considered to be a plausible failure mechanism because of the 
predicted concentration of fluorides is low and the pH is above 3.6.

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3.4.2.7 Matrix Exposure Model 
The preceding subsections of Section 3.4 discuss the process of perforating the cladding. This 
subsection addresses the tearing open (unzipping) of the cladding and the release of 
radionuclides. The release of radionuclides does not occur until after the WP fails and steam or 
water can enter the WP. The release is predicted to occur in two stages, (1) fast release and (2) 
wet unzipping (tearing of the cladding). 
Fast ReleaseThe fast release refers to the inventory of radionuclides that are in the gap between 
the fuel pellets and the cladding (gap inventory) as summarized in Section 3.3.1.1 and the 
radionuclides at the grain boundaries of the spent fuel matrix. The gap inventory of iodine and 
cesium is predicted to be released in proportion to the fission gas release fractions (CRWMS 
M&O 2000h, p. 82). That is, the release of iodine is 4.2 percent. The cesium gap inventory is 
1/3 of the fission gas release fraction or 1.4 percent. 
The inventory of the radionuclides in the grain boundaries is also released quickly. The amount 
released is determined as follows. As discussed in CRWMS M&O (2000i, Section 6.5.2), 
Wilson (1990, Section 3) reports releases of various radionuclides from fuel rod samples. The 
samples included intact and defected fuel rod sections and bare fuel. Wilson exposed the 
samples to water and measured the amounts of various radionuclides that were released during 
that period. After the first measurement in about 200 days, the samples were again exposed, and 
the measurements were repeated after an additional period of comparable length. The fast 
release from the uranium pellet through slits and holes in the cladding is estimated by calculating 
the release rate from Wilsons eight experiments and extrapolating this release rate until the 
larger gaps are closed by secondary phases (approximately 5 years). Figure 3.4-10 gives the 
cumulative distribution function (CDF) for the fast release of radionuclides from the fuel matrix 
generated from Wilsons eight experiments. Also shown is a uniform distribution of release 
fraction between 0 and 0.004 (mean and median value = 0.002). This linear fit is conservative, 
overpredicting the release values for the lower CDF samplings. The cesium and iodine gap 
inventories discussed above are added to obtain the total fuel matrix fast release fraction. In the 
TSPA abstraction, the fast release grain boundary fraction is uniformly distributed between 0 and 
0.4 percent for all radionuclides. 
Wet and Dry UnzippingFuel rods with perforated cladding are expected to remain intact until 
the WP fails and permits air and moisture to enter. While the humidity is low, dry unzipping 
could occur. In this mechanism, the UO2 of the CSNF rapidly oxidizes to U3O8. However, the 
WP is expected to last for the regulatory period for the nominal scenario, thus the fuel 
temperatures will be too low for dry unzipping to occur. Wet unzipping is modeled to start at 
WP failure for rods already perforated at WP failure or start when rod perforation occurs, if after 
WP failure. The fuel matrix is modeled to dissolve at the intrinsic dissolution rate that is 
evaluated at the temperature and in-package chemistry. The dissolved UO2 precipitates locally 
as metaschoepite. This secondary phase isolates most of the fuel from the moisture and increases 
volume compared to UO2. In time, the cladding in the reaction region may be torn as the 
reaction continues. This reaction region is modeled to be cone shaped based on experimental 
observations of dry unzipping. The unzipping propagates along the rod at a rate approximately 
40 times (range 1 to 240 times) as fast as the intrinsic dissolution rate of the CSNF evaluated in 
the CSNF Matrix Degradation Component. It is assumed that the cladding perforation is in the

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center of the rod. This maximizes the release rate. Figure 3.4-11 gives the time to unzip a rod as 
a function of temperature for a fixed in-package chemistry. In the TSPA-SR, the intrinsic 
dissolution velocity is calculated for each time step as a function of local chemistry, pH, and 
temperature. The unzipping velocity is then calculated using a triangular distribution with the 
minimum, best estimate, and maximum unzipping velocity being 1, 40, 240 times the intrinsic 
dissolution velocity, respectively. The fraction of fuel dissolved and exposed is then calculated 
for each time step. 
The bases for matrix exposure analysis are measurements of gap inventories, experimental 
measurements of the release of radionuclides from damaged cladding and intrinsic dissolution 
measurements. Although unzipping has not been observed for rods in storage pools for the past 
40 years, the unzipping analysis is consistent with dry unzipping experiments. Uncertainties have 
been defined that are based on both experiments and extremes in the analysis. Therefore this 
analysis is appropriate for TSPA-SR. Although it is conservative, it is not as conservative as the 
assumption of instantaneous unzipping to expose the CSNF that was used in previous TSPAs. 
3.4.3 Confidence/Limitations/Validation 
There is good reason to have confidence in the cladding degradation analysis. The cladding 
degradation analysis is based on over 40 years of experiments and observations of cladding 
behavior. The analysis of initial cladding conditions is based on reactor fuel performance reports 
that have been published since the start of the industry. Creep, SCC and DHC analysis is 
supported by an extensive experimental base. Zirconium alloys were originally developed for 
use in the chemical industry to handle very corrosive fluids such as hydrochloric acid. In water 
environments, continuous corrosion experiments have been performed for 27.5 years. Fuel has 
been exposed in spent fuel pools for over 25 years and in dry storage research programs. The 
models, including ranges and uncertainties, that have been developed for TSPA are based 
primarily on experimental observations. 
There are constraints, caveats, and limitations to this analysis. This cladding degradation 
analysis is only applicable to commercial PWR fuel with Zircaloy cladding. Fuel reliability from 
reactor operation is for both PWR and BWRs. It is also limited to fuel exposed to normal 
operation and anticipated operational events (events which are anticipated to occur within a 
reactor lifetime), and not fuel that has been exposed to severe accidents. (For example, fuel from 
the Three Mile Island reactor accident is included in the DSNF fuel category, which, with the 
exception of naval SNF, does not account for the performance of the cladding.) Fuel burnup 
projections have been limited to the current licensing environment with restrictions on fuel 
enrichment, oxide coating thickness, and rod plenum pressures. Cladding degradation from 
YMP surface facility handling and operation was not considered. Ranges of uncertainties have 
been established and conservatism was used in developing this analysis. 
Based on the considerations discussed above, this analysis is appropriate for its intended use.

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3.4.4 Other Views 
3.4.4.1 Past Modeling of Cladding Degradation 
Before TSPA-VA (DOE 1998b), YMP performance assessments did not consider protection of 
the fuel by cladding and all the fuel in a drip zone was available to dissolve. This rapid 
dissolution was then limited by the solubility of the various radionuclides. 
In TSPA-VA, the failure of PWR cladding was assumed to bound the failure of BWR cladding 
because the PWR cladding is typically thinner than BWR cladding. For PWR cladding, the 
initial cladding failure percentage was set at 1.25 percent; the major portion of this failure 
(1.15 percent) was stainless steel cladding, which was uniformly distributed in all WPs 
throughout the repository. PWR cladding failure from rockfall rubble was assumed to begin 
after the WP was sufficiently weakened (which was set in all cases at 105 years after initial 
breach of the WP). The cladding failure caused by rubble then increased as a power function 
(linearly on a log scale) thereafter from 0.2 percent at 105 years after breach to a sampled value 
at 106 years after breach; the sample range varied between 0.2 percent and 11 percent. PWR 
cladding failure from localized corrosion was evaluated using WAPDEG; the localized corrosion 
rate was assumed to be 10 to 1,000 times smaller than the corrosion rate of Alloy 22. Based on 
these assumptions, the amount of fuel exposed at 106 years varied between 0.3 and 40 percent 
(mean of 7.8 percent). 
In TSPA-VA, the fuel in rods that were failed before emplacement were assumed to be 
completely exposed for dissolution. The fuel in an area below the rock or corrosion patch was 
available for dissolution but the remaining ends of the rods were not. This model was not 
necessarily conservative. 
The method of estimating the performance of the Zircaloy cladding on the CSNF has changed 
substantially from TSPA-VA. Two specific phases of cladding degradation are modeled: (1) 
perforation (such as existing perforations from use in the reactor and creep failures from 
overheating the cladding during storage, etc.) and (2) exposure of the SNF matrix over time (here 
evaluated by assuming the Zircaloy cladding unzips). Many mechanisms of perforation were 
studied and many dismissed in FEPs. Yet, in response to comments discussed in the following 
sections, an extremely conservative estimate of the number of cladding perforations over time is 
used to acknowledge uncertainty. Also in response to comments, the exposure of the SNF is 
evaluated through a hypothetical but bounding rate of unzipping of the cladding such that the 
entire inventory of radionuclides can eventually be exposed over sufficient time. 
3.4.4.2 Comments About Including the CSNF Cladding in Waste Form Degradation 
Model 
Concerns have been expressed in meetings of the Advisory Committee on Nuclear Waste 
(ACNW) and NWTRB as well as in documented reports of the TSPA Peer Review Panel and in 
the IRSR on CLST related to DOEs taking credit for cladding of SNF and the performance of 
the cladding if included in the TSPA. One issue is whether taking credit for cladding is practical 
and the other issue is whether sufficient information has been considered related to clad 
degradation.

 3-44
Comments 
During the 106th meeting of the ACNW, the NRC challenged DOEs heavy reliance on cladding 
credit, considering that the cladding has to remain intact for very long periods of time under 
conditions that it was not designed for and questioning DOEs ability to gather data to support 
related assumptions. During the 110th meeting of the ACNW, the NRC contended that the model 
that the NRC uses for spent nuclear fuel dissolution is better than the DOE models because it 
relied upon slower CSNF dissolution rates and not cladding credit. The TSPA Peer Review 
Report (Budnitz et al. 1999, Section II.E) questioned the extent of credit taken for cladding in the 
TSPA-VA, noting that the credit taken for spent nuclear fuel cladding may be optimistic. 
Response 
NRC purposefully adopted a TSPA approach such that realistic estimates could be made on the 
performance of a disposal system in order to make wise policy decisions (60 FR 42622, 
Section IV; Rechard 1999, p. 777). The Zircaloy cladding is an important characteristic of the 
CSNF. The Zircaloy cladding on the CSNF is in good condition and has been handled carefully 
at the nuclear reactors. Furthermore, Zircaloy cladding readily resists corrosion, and the modes 
of failure in various environments have been studied for 30 years. Therefore, it is believed that 
sufficient data exist for the inclusion of Zircaloy degradation. The Waste Form Degradation 
Model includes the existence of the Zircaloy cladding on the CSNF and naval SNF to provide for 
a realistic estimate of the behavior of these fuels in the TSPA. The NRC fuel dissolution model 
takes credit for the combination of calcium and silicon to suppress the dissolution of the UO2. 
This effect is not observed in drip tests on fuel and, therefore, not used in the TSPA-SR. The 
cladding degradation model used in TSPA-VA was criticized as possibly being optimistic. The 
model used in TSPA-SR is more conservative. 
3.4.4.3 Comments on Modeling Cladding Performance 
Comments 
Questions have been raised related to DOEs ability to sufficiently establish the performance of 
cladding. NRC noted during the 110th meeting of the ACNW that the initial damage and 
condition of cladding are important to determining the effect of cladding. The TSPA Peer 
Review Panel (Budnitz et al. 1999, Executive Summary Sections B and E, Section II.E) noted 
that studies needed to take credit for cladding are not available and identified the quality of data 
from the industry regarding cladding initial state as a vulnerability to taking cladding credit. The 
TSPA Peer Review Panel also stated that the estimates of performance in the TSPA-VA (DOE 
1998b) rest in large part on potentially optimistic, or at least undemonstrated, assumptions of the 
behavior or performance of cladding including understatement of related uncertainties (Budnitz 
et al. 1999, Executive Summary Sections B and E, Section II.E). Insufficient analysis in the 
TSPA-VA (DOE 1998b) was cited related to hydrogen embrittlement of zirconium cladding, and 
suggestions were made related to further investigations to identify additional potential failure 
mechanisms (e.g., pitting and crevice corrosion, unzipping due to secondary phase formation, 
stress corrosion cracking, long-term localized corrosion in a radiolysis-induced acidic condition) 
(Budnitz et al. 1999, Section II.G, IV.E). It also suggested that data needs related to cladding 
performance had not been met (Budnitz et al. 1999, Executive Summary, Section E). The

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NWTRB (NWTRB 1998, Chapter 3, Section V.B.2) expressed concern that combined 
interactions of corrosion products from the WP liner and outer walls, radiolysis, water, and 
elevated temperatures could produce a corrosive environment inside WPs that could affect 
Zircaloy cladding and had not yet been fully investigated. In the IRSR on CLST (NRC 1999a, 
Section 5.3.5), NRC noted a lack of direct comparison of DCCG model prediction against 
experimental data and lack of experimental evidence of DCCG in Zircaloy cladding. It also 
noted disagreements on some constraints in the models and on the validity of extrapolating 
certain creep model results to lower stresses and temperatures. 
Response 
To evaluate all possible behavior of a potential disposal system at Yucca Mountain, DOE 
undertook a formal approach to develop pertinent features, events, and processes (FEPs) for the 
disposal system. This approach also included evaluating FEPs related to perforating the 
cladding. The DOE has proposed 20 FEPs including localized corrosion (general pitting 
corrosion, crevice corrosion, ferric chloride pitting), creep rupture, hydride failures (e.g., DHC 
and embrittlement), mechanical failure due to rock fall, stress corrosion cracking (SCC), 
cladding degradation before YMP receives it, MIC, acid corrosion from radiolysis, DCCG, 
future pressurization of the rods during disposal, and general cladding oxidation (as already 
mentioned and tabulated in Section 2.3.2.4). 
In summary, the DOE has reviewed all potential perforation mechanisms and has taken a 
conservative view for those mechanisms retained. Specifically, the project has included a 
conservative model for localized corrosion due to some unspecified mechanism. This action was 
taken after a review of corrosion mechanisms (CRWMS M&O 2000ag, Section 7) identified no 
plausible mechanism for accelerated corrosion under repository conditions. This conservative 
approach should address the NWTRB concerns. For localized corrosion, the NRC also postulates 
that chloride attack in pits is possible given the presence of ferric ions. However, when the 
waste packages fail late in life, the potential for achieving aggressive ferric chloride chemistries 
is very low. Hence, this mechanism is not included. The NRC is currently re-evaluating its 
approach to estimating creep failures for reactor service. However, in regard to creep in the 
repository, the NRC states that "there is general consensus that cladding failure by creep rupture 
is unlikely under repository conditions." Thus, creep is not an issue. Again, there is consensus 
regarding delayed hydride attack in that the NRC that believes that this mechanism is not 
important under repository conditions. The project has used a realistic treatment for mechanical 
failure due to rock fall and the NRC agrees with this approach. The NRC notes that Zircaloy is 
susceptible to SCC in the presence of tensile stresses lower than the yield stress. The DOE 
agrees that SCC is possible and has provided a conservative model for SCC failure. General 
cladding oxidation is not likely to be of concern due to the long life of the waste packages and 
the resultant low temperatures when the waste packages do breach. Because of the long life of 
the waste packages, the likelihood of aggressive conditions from radiolytic acids inside the waste 
package are small. Although it was not noted in the NRC's IRSR on CLST, there has been 
concern, noted above by the ACNW, that the initial condition of the cladding is uncertain. This 
has been thoroughly reviewed in the AMR on initial cladding condition and been found to be 
only a minor contributor to failure of the cladding.

 3-46
To evaluate the slow release of radionuclides from perforated cladding, the DOE has assumed an 
unzipping mechanism that conservatively bounds the possible diffusive release out of pinholes in 
the cladding. 
3.5 DEPARTMENT OF ENERGY SPENT NUCLEAR FUEL DEGRADATION 
COMPONENT 
The DSNF Degradation Model Component predicts the rate of degradation of the DSNF waste 
category and of the immobilized plutonium ceramic waste. The component was developed using 
the logic shown in Figure 3 of Standard Practice for Prediction of the Long-Term Behavior of 
Materials, Including Waste Forms, Used in Engineered Barrier Systems (EBS) for Geologic 
Disposal of High-Level Radioactive Waste (ASTM C1174-97). 
The primary document supporting the DSNF Degradation Model Component was the DSNF and 
Other Waste Form Degradation Abstraction AMR (CRWMS M&O 2000j), which in turn was 
supported to a limited extent by Miscellaneous Waste-Form FEPs (CRWMS M&O 2000n). 
3.5.1 Model Description 
The degradation rates of all waste forms other than commercial spent nuclear fuel and high level 
waste were analyzed in DSNF and Other Waste Form Degradation Abstraction (CRWMS M&O 
2000j). Over 250 distinct types of DOE spent nuclear fuel may be disposed of in the potential 
repository at Yucca Mountain. The Office of Civilian Radioactive Waste Management and the 
National Spent Nuclear Fuel Program have collaborated in the identification of spent nuclear fuel 
groups to simplify the analysis of their effects on repository preclosure safety analyses or for 
postclosure TSPA. 
The DOE spent nuclear fuel groups are: 
 Group 1Naval spent nuclear fuel 
 Group 2Plutonium/uranium alloy 
 Group 3Plutonium/uranium carbide 
 Group 4Mixed oxide and plutonium oxide fuels 
 Group 5Thorium/uranium carbide 
 Group 6Thorium/uranium oxide 
 Group 7Uranium metal 
 Group 8Uranium oxide 
 Group 9Aluminum-based spent nuclear fuel 
 Group 10Unknown 
 Group 11Uranium-zirconium-hydride. 
In addition, the immobilized ceramic plutonium waste form was also evaluated. This waste form 
will consist of disks of a plutonium-containing, titanium dioxide-based ceramic that will be 
enclosed in stainless steel cans, which in turn will be encased in a borosilicate glass matrix 
within the high level waste canisters.

 3-47
DSNF and Other Waste Form Degradation Abstraction (CRWMS M&O 2000j) provided three 
types of degradation models for the DOE spent nuclear fuel and plutonium-ceramic waste forms: 
upper-limit, conservative, and best-estimate, to provide the user of the models appropriate 
flexibility in their application to any particular postclosure performance scenario. A summary of 
the upper-limit, conservative, and best-estimate dissolution models for each DSNF group is 
shown in Table 3.5-1. This table shows the three types of models for each DSNF group and the 
immobilized ceramic Pu-disposition form, the surrogate material for which the model was 
developed, the literature/document source reference for the model, and the ASTM C1174-97 
classification of the model. An upper-limit model predicts release rates always well in excess of 
actual dissolution rate data. The conservative degradation model provides an estimate of 
dissolution rate that reflects the higher rate end of available dissolution data or the SNF groups or 
similar materials. A best-estimate model is appropriate only when sufficient dissolution data 
exists and the characteristics of the waste form can be shown to correspond to the characteristics 
of the materials that provided the dissolution database. For the conservative and best-estimate 
models, various surrogate spent nuclear fuels were evaluated for degradation behavior. 
A discussion of the individual models for each fuel group is provided in CRWMS M&O (2000j). 
The uranium fuel accounts for the biggest portion of the MTHM of DSNF. In general, the 
degradation rates of the metallic uranium or carbide fuels are much higher than the oxide fuels. 
Because the metallic uranium and carbide fuels degrade very rapidly in TSPA time scales, the 
TSPA results have been very insensitive to these rates. In addition, TSPA analyses have shown 
that the overall performance of the potential repository is driven primarily by the commercial 
spent nuclear fuel and high-level radioactive waste inventories. For these reasons, the 
conservative Hanford N Reactor fuel model (Equation 3.5-1) was recommended as the surrogate 
to bound all the DOE spent nuclear fuel groups 2 through 11. Figure 3.5-1 provides a schematic 
description of how the degradation model is implemented for these groups. 
Rate = 1.75  105 (.matrix/.U-metal) mg/m2day (Eq. 3.5-1) 
where .matrix is the density of the spent fuel matrix, and .U-metal is the density of uranium metal. 
The Navy will provide a best-estimate model for the group 1 naval fuel, but pending this, the 
naval SNF will be represented by commercial spent nuclear fuel in TSPA. 
The best-estimate for the degradation of the immobilized ceramic plutonium is given by a 
titanate ceramic model, with an exposed surface area corresponding to the geometric surface area 
of the plutonium-containing ceramic disks. For TSPA, however, the immobilized plutonium 
inventory was averaged into the high level waste inventory, and the higher rates for high level 
waste degradation (Section 3.6) were used. 

 3-48
Table 3.5-1. DSNF, Naval SNF, Pu-Disposition Release/Degradation Models 
Upper-limit Model Conservative Model Best-estimate Model Waste 
Type 
DSNF 
Group Surrogate Model Surrogate Model Surrogate Model 
DSNF 1. Naval 
SNF 
CSNF Commercial LWR 
SNF dissolution 
modela 
CSNF Commercial LWR SNF 
dissolution modela 
CSNF Commercial LWR SNF 
dissolution modela 
DSNF 2. Pu /U 
Alloy 
Fermi Full release over 
TSPA time step 
U - 6% Mo (bounding) 
10  Unirradiated U-metal 
best-estimate: 
Wet oxic conditions: 
R (kg/m2s) = 1.88  104 exp 
(-7970/TK) 
Humid oxic conditions: 
R (kg/m2s) = 0.27  103 exp 
(-7240/TK) 
U - 8% Mo (semi-empirical) 
Unirradiated U-metal 
best-estimate: 
Wet oxic conditions: 
R (kg/m2s) = 1.88  103 
exp (-7970/TK) 
Humid oxic conditions: 
R (kg/m2s) = 0.27  102 
exp (-7240/TK) 
DSNF 3. Pu/U 
Carbide 
FFTF Full release over 
TSPA time step 
UC2 (bounding) 
100  Unirradiated U-metal 
best-estimate: 
R (kg/m2s) = 100  [1.88 x 
103 exp (-7970/TK)] 
UC2 (bounding) 
100  Unirradiated Umetal 
best-estimate: 
R (kg/m2s) = 100  
[1.88  103 exp 
(-7970/TK)] 
DSNF 4. MOX 
and Pu 
Oxide 
LWR SNF Full release over 
TSPA time step 
LWR SNF (bounding) 
100  Intact U Oxide bestestimate 
UO2 (semi-empirical) 
U Oxide best-estimate 
model 
DSNF 5. Th/U 
Carbide 
UC2 Full release over 
TSPA time step 
UC2 (bounding) 
10  Unirradiated U-metal 
best-estimate 
SiC (semi-empirical) 
R (kg/m2s) = 0.6  10-12 
DSNF 6. Th/U 
Oxide 
Fort St. Vrain Full release over 
TSPA time step 
ThO2 - 2 wt% 
UO2 
(bounding) 
1000  Best-estimate 
Synroc (semi-empirical) 
R (mg/m2d) = 
82.0  10 (-1000/T
K
) 
DSNF 7. UMetal- 
Based 
N-Reactor Full release over 
TSPA time step 
N-Reactor (semi-empirical) 
1.75  106 mg/m2d 
N-Reactor (semi-empirical) 
1.75  105 mg/m2d

 3-49
Table 3.5-1. DSNF, Naval SNF, Pu Disposition Release/Degradation Models (Continued) 
Upper-limit Model Conservative Model Best-estimate Model Waste 
Type 
DSNF 
Group Surrogate Model Surrogate Model Surrogate Model 
DSNF 8a. Intact 
U Oxide 
LWR SNF Full release over 
TSPA time step 
LWR SNF (bounding) 
100  Intact U Oxide bestestimate 
LWR SNF (semi-empirical) 
Commercial LWR SNF 
dissolution modela 
DSNF 8b. 
Damaged 
U Oxide 
Three Mile 
Island 
Full release over 
TSPA time step 
Three Mile 
Island 
(bounding) 
100  Intact U Oxide bestestimate 
Three Mile 
Island 
(bounding) 
100  Intact U Oxide 
best-estimate 
DSNF 9. Albased 
Foreign 
Research 
Reactors, 
Advanced 
Test Reactor 
Full release over 
TSPA time step 
U-Al alloy in 
bicarbonate 
solution 
(bounding) 
36 mgU/m2d @ 25C 
360 mgU/m2d @ 90C 
SRS U-Al 
SNF in J-13 
well water 
(empirical) 
0.22 mgU/m2d @ 25C 
2.20 mgU/m2d @ 90C 
DSNF 10. 
Unknown 
N-Reactor Full release over 
TSPA time step 
N-Reactor (bounding) 
10  Unirradiated U-metal 
best-estimate 
N-Reactor (empirical) 
Unirradiated U-metal 
best-estimate 
DSNF 11. U-Zr- 
Hx 
TRIGA Full release over 
TSPA time step 
U-Zr-Hx (bounding) 
0.1  U-oxide best-estimate 
U-Zr-Hx (empirical)b 
0.1  U-oxide bestestimate 
Pu N/A N/A Full release over 
TSPA time step 
HLW Glass HLW glass dissolution 
modelc with effective surface 
area taken as 20  the 
geometric surface area of 
the exposed glass matrix 
Multi-phase 
titanate 
ceramic 
(semi-empirical) 
pH-dependent titanate 
ceramic dissolution 
equationsd 
Source: DSNF and Other Waste Form Degradation Abstraction. ANL-WIS-MD-000004. (CRWMS M&O 2000j, Table 1) 
NOTES: (bounding)indicates a bounding model per the materials behavior modeling logic of ASTM C 1174-97 
(empirical)indicates an empirical model per the materials behavior modeling logic of ASTM C 1174-97 
(semi-empirical)indicates a semi-empirical model per the materials behavior modeling logic of ASTM C 1174-97 
(mechanistic)indicates a mechanistic model per the materials behavior logic of ASTM C 1174-97 
aCommercial LWR SNF Dissolution Model, see Equations 3.3-3 and 3.3-4 
b See CRWMS M&O 2000j, Section 6.3.11 for reference to empirical data and recommended model 
cHLW Glass Dissolution Model, see Equations 3.6-4, 3.6-5 and 3.6-6 
dSee CRWMS M&O 2000j, Section 6.3.12 for equations

 3-50
3.5.2 Confidence/Limitations/Validation 
The application of the DSNF and immobilized ceramic Pu degradation models involves the 
extrapolation of the models over long periods of time, which are orders of magnitude greater 
than the experimental test periods used to generate the data used to derive the models. 
ASTM C1174-97 (Section 24), recommends that uncertainties in the extrapolation of such 
models be minimized through the use of models whose mathematical forms are as mechanistic as 
possible. However, it can be seen from the abstractions above that the lack of any directly 
relevant experimental dissolution/degradation data for many of the DSNF waste forms, and the 
small amount of data for those which have been tested, precludes the development of a 
mechanistic model at this time. Additionally, uncertainties in the data used to generate the 
models-such as in the surface area measurements used to calculate normalized dissolution rates 
produce significant uncertainties even in the short-term application of the models. For this 
reason and because preliminary TSPA analyses have shown that the overall performance of the 
repository is very insensitive to the degradation rate of the DSNF, upper-limit or bounding 
degradation models will be used. 
The initial results of TSPA sensitivity analyses for DSNF (CRWMS M&O 1999e, Section 7) 
indicate that the performance of the repository is very insensitive to the DSNF degradation 
kinetics. That is, the use of the upper-limit model for the DSNF in the TSPA performed in that 
study still resulted in a calculated boundary dose well within requirements. Use of a less 
conservative model for the DSNF in the TSPA boundary dose calculation would not significantly 
lower the calculated boundary dose, because even with the upper limit, model releases due to 
DSNF are significantly lower than those due to HLW and CSNF. 
If because of this insensitivity the upper-limit model is the only one used for TSPA analyses, 
then validation of the other models would be unnecessary. Since the upper limit release model is 
that of instantaneous release of all radionuclides, i.e., the maximum rate conceivable, it does not 
require validation. It depends only on the total inventory of radionuclides in the DSNF. The 
upper limit model proposed for the DSNF and Pu disposal waste forms are, thus, impacted 
primarily by the total inventory of radionuclides that are present. The conservative and best 
estimate models for the DSNF waste forms are primarily impacted by the validity of the uranium 
metal-based SNF dissolution models. 
Based on the considerations discussed above, this model is appropriate for its intended use. 
3.5.3 Other Views 
For TSPA-VA, the model for the degradation of metallic uranium was a classic Arrhenius kinetic 
rate equation using parameters from assessments of SNF and HLW (Rechard 1995, p. 11-22; 
DOE 1998a, p. 7-32; see also CRWMS M&O 1998b, p. 6-69). The overall degradation rate was 
the Arrhenius rate times the effective surface area. In TSPA-VA, the effective surface area was 
five times the geometric surface area. Because the degradation rate estimated by the Arrhenius 
equation was so rapid, the sensitivity of the results to varying the multiplier for the geometric 
surface area between 0.1 and 100 (thus, the overall degradation rate) was small.

 3-51
3.6 HIGH-LEVEL WASTE DEGRADATION COMPONENT 
The function of the HLW Degradation Component is to provide a conservative model for 
calculating the rate of degradation of borosilicate glass for the range of conditions (immersion, 
humid air, and dripping water) to which it may be exposed after the WPs fail. 
The HLW model will be implemented in the TSPA-SR analysis to calculate the rate of glass 
degradation. The rate of radionuclide release from the HLW matrix will be calculated by 
multiplying the glass degradation rate by the mass fraction of the radionuclide in the glass. This 
approach for calculating the radionuclide release rate is based on the conservative assumption 
that the release of radionuclides is congruent with the degradation of borosilicate glass. 
The model is implemented in the form of an analytical expression containing four parameters 
(., Ea, S, and keff; see Figure 3.6-1 and Equation 3.6-2) and two variables (i.e., temperature and 
pH). The model parameters account for the pH, temperature, surface area, and the combined 
effects of glass composition and solution composition on the rate of glass corrosion. 
Conservative estimates of the values for the model parameters are provided based on 
experimental data. Implementation of the model for the TSPA-SR analysis requires input of 
temperature and pH data. 
Consistent with the conceptual model for in-package chemistry, degradation of borosilicate glass 
is assumed to occur as if the glass were fully immersed although it is expected that much of the 
glass will be exposed to humid air or dripping water conditions. This assumption is based on a 
comparison of the model that was developed for immersion (see Equations 3.6-4 and 3.6-5) to 
the model developed for glass degradation in humid air or dripping groundwater conditions (see 
Equation 3.6-7) CRWMS M&O (2000k, Section 6.3.2). This comparison showed that the rate of 
glass corrosion under humid air and dripping water conditions was conservatively bounded by 
the dissolution rate under immersion conditions. 
The primary document supporting the HLW Degradation Model Component was the Defense 
High Level Waste Glass Degradation (CRWMS M&O 2000k), which in turn was supported to a 
limited extent by Miscellaneous Waste-Form FEPs (CRWMS M&O 2000n, Section 6.2.8). 
3.6.1 Model Description 
Available experimental data concerning the degradation behavior of borosilicate-based glasses 
were analyzed to develop models for the dissolution and consequent radioisotope release from 
HLW glass under aqueous immersion conditions in the repository environment. The mechanism 
and rate expression for aqueous dissolution are sufficiently well understood to designate the 
HLW model as a semi-empirical model as described in ASTM Standard C1174-97 (1997, 
Section 19.3.4). 
The basic form of rate expression that describes dissolution of waste glass immersed in water is 
(CRWMS M&O 2000k, Section 6.1.1): 
Rate = S { ko  10 .  pH  exp(-Ea/RT)  [1 - (Q/K)] } (Eq. 3.6-1) 
where

 3-52
Rate = the dissolution rate of the glass, in units of mass/time 
S = the surface area of glass immersed in water, in units of area 
ko = the intrinsic dissolution rate, which depends only on glass composition, in units of 
mass/(area  time) 
. = the pH dependence coefficient, which is dimensionless 
Ea = the effective activation energy, in units of kJ/mol 
R = the gas constant, which is 8.314 kJ/(mol  K) (accepted value) 
T = the temperature in kelvins 
Q = the concentration of dissolved silica in the solution, in units of mass/volume 
K = a quasi-thermodynamic fitting parameter equal to the apparent silica 
saturation concentration for the glass, in units of mass/volume 
This rate expression contains two main parts: the forward rate, ko  10 .  pH  exp(-Ea/RT), which 
represents the dissolution rate in the absence of feedback effects of dissolved silica (and other 
aqueous species), and the reaction affinity term (1Q/K), which quantifies the feedback effects. 
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, therefore, 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 rate is reached. 
Use of the form of the rate expression shown above would require knowledge of several 
parameter values that depend on the glass (k0, ., Ea, S, K) and of several variables related to the 
exposure conditions (pH, T, and Q). Evaluation of Q would be complex and subject to 
considerable uncertainty. A simpler bounding approach was, therefore, adopted. In this approach 
the affinity term (1 - Q/K) was combined with the intrinsic dissolution rate constant ko to 
generate the following abstraction for aqueous degradation of HLW for the TSPA-SR analysis: 
Rate/S = keff  10 .  pH  exp(-Ea/RT) (Eq. 3.6-2) 
where, 
keff = k0  (1 - Q/K) 
Although keff is a complex function of glass composition and solution variables, the approach 
adopted in the abstraction is to provide a constant value for keff that conservatively bounds the 
anticipated range of the function k0  (1 - Q/K). This approach reduces the abstracted model to 
an equation involving four parameters (., Ea, S, and keff) and two variables (pH and T). 
Available experimental data were used to obtain conservative estimates of each of these 
parameters (CRWMS M&O 2000k, Section 6). 
3.6.1.1 Estimation of the Model Parameters 
The approach used to estimate the model parameters can be broken into three steps. 
The first step was to analyze the dependence of the forward rate on the glass composition, pH, 
and temperature. These dependencies were measured under flow-through test conditions in

 3-53
which the value of the affinity term is maintained near one. In these tests, the dependence of the 
forward rate on glass composition, pH, and temperature was measured under test conditions in 
which two of the variables (e.g., glass composition and pH) were held constant and the other 
(e.g., temperature) varied. On the basis of the experimental results, the pH and temperature 
dependence of rates were found to be independent of the glass composition, within the 
composition range of the glasses tested, so the same values for the ., and Ea parameters are used 
for all waste glasses. The values of these parameters do however depend on pH. Analysis of the 
available data (CRWMS M&O 2000k, Section 6.2) resulted in the empirical estimates for values 
of the . and Ea parameters for acidic and basic conditions (see Equations 3.6-4 and 3.6-5). 
In the second step, a bounding value for the keff parameter was determined based on 
experimental observations of the behavior of the affinity term for test conditions that spanned a 
broad range of reaction progress. Experimental data show that the behavior of the corrosion rate 
with reaction progress can be characterized as proceeding through three stages. Stage I occurs 
when the value of the affinity term is one and glass dissolves at the forward rate for the specific 
temperature and pH conditions involved. Stage I will not occur when glass is contacted by 
groundwater containing high-levels of dissolved silica (from dissolution of minerals present in 
tuff and from the dissolution of the glass itself). Stage II occurs as the value of the affinity term 
decreases significantly due to the accumulation of glass components particularly dissolved silica, 
in solution. The value of the affinity term (and thus the dissolution rate) cannot become zero 
because glass is thermodynamically unstable and cannot equilibrate with the solution. Stage III 
occurs when the dissolution rate increases due to the formation of alteration phases, effectively 
removing dissolved silica from the solution. The formation of alteration phases is believed to 
cause a decrease in the value of Q due to the consumption of dissolved silica as these silicabearing 
phases form (CRWMS M&O 2000k, Section 6.2.2). This Stage III behavior has not 
been observed for all glasses or all experimental conditions and the mechanisms involved remain 
unclear. It is not possible, therefore, to predict when Stage III occurs or to unambiguously 
predict the value of k0  (1 - Q/K) i.e., keff for use in performance assessment calculations. For 
these reasons a conservative bounding approach was adopted in evaluating keff. After evaluating 
several options, an approach based on using the ASTM Product Consistency Test, Type A, 
(PCT-A) (ASTM C1285-97, Standard Test Methods for Determining Chemical Durability of 
Nuclear, Hazardous, and Mixed Waste Glasses: The Product Consistency Test (PCT)) test 
results was selected (CRWMS M&O 2000k, Section 6.2.3). This approach involved using the 
relatively short-term PCT-A dissolution rate test results to obtain bounding values for keff that 
would conservatively encompass all three potential stages of dissolution behavior. The bounding 
values estimated for keff are shown in the leading coefficients of Equations 3.6-4 and 3.6-5. 
The third step involves estimating the surface area parameter S. The glass surface area that is 
available for corrosion in the disposal environment is a difficult parameter to estimate precisely. 
The logs of waste glass will crack within the pour canister due to thermal and mechanical 
stresses generated as the glass cools and as the waste form is handled. Cracking of the glass log 
will result in surfaces that may be contacted by water. The reactivity of surfaces in the tight 
fracture cracks that result from thermal or mechanical stresses will be determined by the glass 
composition, temperature, and the chemistry of the water that fills the crack in the same way that 
these factors affect the dissolution rate of free surfaces. The key difference between the 
dissolution rates of the glass within cracks and at the outer surface is the transport rates of 
reactant into the crack and reaction products out of the crack. Short-term dissolution tests have

 3-54
shown that, while more glass dissolved in tests with samples of fractured glass than in tests with 
samples of a glass that was not fractured, the difference was less than the estimated increase in 
the surface area. It had been concluded from the results of tests in which various crack widths 
were simulated with platinum wire spacers that the assumption that crack surfaces leach as 
readily as the external surface is unduly conservative (Perez and Westsik 1981, page 168). 
However, since sufficient information is not available to quantify either the fraction of cracks 
that are accessible to water or the difference between the corrosion rates in cracks and at an outer 
surface, the conservative assumption that all surfaces corrode at the same rate when exposed to 
water was adopted. The value of the parameter S is, therefore, based on an estimate of the total 
surface area of the glass (i.e., the geometric surface area together with the fracture surface area). 
This area has been estimated to be approximately 20 times the geometric surface area 
(CRWMS M&O 1998b, pp. 6-79, 6-80). An expression to calculate the initial surface area of a 
fractured cylindrical glass log is: 
So = 20  (2pro
2 + 2pro Lo) (Eq. 3.6-3) 
where, 
So = the initial exposed surface area of a glass log due to fracturing 
ro = the initial radius of a glass log 
Lo = the initial length of a glass log 
It is conservatively assumed that the surface area parameter (S) remains constant as the glass 
corrodes. This approach is similar to that used in the TSPA-VA (CRWMS M&O 1998b, 
p. 6-79).

 3-55
3.6.1.2 The Abstracted Model 
The bounding rate expressions are obtained when the estimated value for the four model 
parameters are substituted into Equation 3.6-2. The result is as follows (CRWMS M&O 2000k, 
Section 6.2.3.3): 
For the low pH leg (pH < pHm), 
Rate/S (g/(m2  day) = 10(91)  10 (-0.60.1)  pH  exp((-5815)/RT) (Eq. 3.6-4) 
For the high pH leg (pH = pHm), 
Rate/S (g/(m2  day) = 10(6.90.5)  10 (0.40.1)  pH  exp((-8010)/RT) (Eq. 3.6-5) 
where,
R = the gas constant, which is 8.314  10-3 kJ/(molK) (accepted value) 
T = the temperature, in kelvins 
pH = the negative base-10 logarithm of the hydrogen ion concentration in the water 
pHm = the pH at which the minimum dissolution rate occurs = 2.1 + 1149/T 
pHm = 2.1 + 1149/T (Eq. 3.6-6) 
as shown in Figure 3.6-2. 
3.6.2 Confidence/Limitations/Validation 
The abstracted model is designed to provide a conservative estimate of the rate (i.e., an upper 
bound or overestimate of the likely rate) at which waste glass will corrode when immersed in 
groundwater or exposed to humid air and/or dripping water in the repository. The general 
algebraic form of the proposed model is widely accepted and used in the literature of waste glass 
corrosion (e.g., Strachan et al. 1994, House et al. 2000). Because each of the model parameter 
values were evaluated using a conservative bounding approach (CRWMS M&O 2000k, 
Section 6.4), there is confidence that the abstracted model is likely to bound the long-term HLW 
degradation under neutral to basic conditions. The dissolution rates calculated using 
Equation 3.6-5 can be compared directly with the dissolution rate of basalt glass recovered from 
the sea bed. The dissolution rates of several basalt glass samples were calculated based on the 
thickness of the layer of palagonite that forms as an alteration phase and the age of the basalt 
(Grambow et al. 1986, Table 2, Figure 3, pp. 268 to 269). The dissolution rates for basalts 
covered in sediment and exposed to Si-saturated seawater are about 0.1 m/1000 yr, which is 
equivalent to 6  10-7 g/(m2day). The dissolution rates calculated using Equations 3.6-5 at 3C 
are 3.6  10-6, 9.1  10-6 and 2.3  10-5 g/(m2day) at pH values of 7, 8, and 9, respectively, 
which is the typical pH range for seawater. Thus, the rate expression to be used for basic 
conditions (i.e., Equation 3.6-5) is conservative with regard to the long-term dissolution rate of 
basalt glass.

 3-56
If further model refinement is required in the future, this will be accomplished by confirmation 
testing as described in Section 17 of ASTM C1174-97 and/or by analysis of other appropriate 
experimental data that become available. 
Based on the consideration discussed above, this model is appropriate for its intended use. 
3.6.3 Other Views and Alternative Models 
When a disposal container breaches, the glass logs may be exposed to humid air or dripping 
groundwater. A model was developed for the rate of corrosion of waste glass under humid air 
and dripping water conditions, and it is summarized below. The TSPA-SR analysis will not 
include a separate alteration model for these conditions because use of the immersion model is 
conservative. 
In the unsaturated environment of the Yucca Mountain site, it is likely that waste glass will be 
contacted initially by humid air. When glass is exposed to humid air, molecular water will sorb 
onto specific sites on the glass surface, primarily silanol sites, and alkali metal sites. The amount 
of liquid water that sorbs on the glass will depend on the relative humidity of the air, temperature 
of the glass surface, and hygroscopicity of the glass surface. The first monolayer forms at a 
relative humidity of only a few percent. Subsequent monolayers form as water vapor bonds with 
sorbed water to form beads of water on the glass surface. At relative humidities above about 
80 percent, a sufficient amount of water has condensed to coalesce into a thin film covering the 
entire surface. The glass will react with these sorbed water layers just as it does when immersed 
in water. Initial reactions will likely result in the dissolution of alkali metals into the film of 
water. This will decrease the equilibrium vapor pressure of the film of water and cause more 
water to condense in the film. After the initial film of water is sorbed, the amount of water on 
the glass will likely be determined by the salinity of the water. 
In an open system such as the disposal system, water vapor will continually condense in the film 
of saline water on the exposed waste glass as the glass corrodes. For 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. Once alkali 
metals are released into the film of water, the hygroscopicity of the film will result in continuous 
condensation of water vapor. Continuous exposure to water-saturated air will result in a process 
of vapor condensation, flow across the sample, and dripping, wherein dissolved species can be 
transported away from the glass as solution drips from the glass, and fresh water vapor 
condenses. The corrosion rate of the glass under these conditions will be affected by the rates at 
which water vapor condenses in the film, and solution drips from the sample. These processes 
will affect the glass dissolution rate through their effects on the solution chemistry of the film. 
The effects of the condensation, flow, and drip rates on the glass dissolution rate are taken into 
account in the model by the use of experimental data measured under test conditions designed to 
replicate the phenomena discussed above. 
The corrosion behavior of glass contacted by a thin film of water is modeled as a special case of 
aqueous corrosion that is described with the rate expression given below (Equation 3.6-7). 
Analysis of the available information (CRWMS M&O 2000k, Section 6.3.2) indicates that the 
same mechanistic rate expression used for the case of water immersion can be used for glass

 3-57
contacted by humid air and dripping water. The abstracted rate expression for exposure to 
dripping water or to humid air at a relative humidity of 80 percent or higher: 
Rate = Stf  ktf exp(-Etf/RT) (Eq. 3.6-7) 
where Stf is the surface area contacted by humid air or dripping water. In this abstraction, the 
intrinsic dissolution rate (k0), the pH dependence, and the affinity term (1 - Q/K) are combined 
into a single term called the thin film rate, ktf. The use of this rate expression requires 
knowledge of the surface area that is contacted by a thin film of water due to exposure to humid 
air or dripping water and the temperature. The parameter values for the bounding rate are: 
For relative humidity > 80 percent or exposure to dripping water, 
log ktf = 9.2  0.2 g/(m2day) 
Etf = 80  10 kJ/mol 
Comparison of the model for the corrosion rate under immersion conditions with that 
summarized above for exposure to humid air and dripping water showed that for pH values 
greater than 5.75, use of the rate expression for immersion for all contact modes provides a 
conservative estimate for the glass dissolution rate. At pH values lower than 5.75, the rate 
expression for the acid leg for immersion should also be used for contact by humid air and 
dripping water. However, it is important to note that since laboratory tests results for contact by 
humid air and dripping water are in near neutral or alkaline solutions, no database exists to 
evaluate dissolution in acidic solutions under humid air or dripping conditions. 
In the IRSR on CLST (NRC 1999a, Section 5.4.5), the NRC identified that DOE has not 
properly considered data on naturally occurring glasses, combined with experimental data and 
models on dissolution of HLW glasses, to demonstrate that long-term dissolution behavior under 
repository conditions can be represented by extrapolation of results from short-term laboratory 
tests. As stated more fully in Chapter 4, the bounding formulation of the HLW Degradation 
Component, discussed in Section 3.6, included the consideration of experimental data developed 
by the CRWMS M&O and other relevant data including information from natural analogs. 
Natural analog information is used for corroboration (see Section 3.6.2 and Cunnane et al. 1994). 
3.7 DISSOLVED RADIOISOTOPE CONCENTRATION COMPONENT 
The dissolved concentration component evaluates the dissolved concentration of radionuclides 
(or parents of radionuclides) that are important to human dose as determined by the radioisotope 
screening described in the inventory Section (3.1) (Figure 3.7-1). 
Doses calculated for groundwater pathways from the repository to the environment depend 
critically on the concentrations of radionuclides in fluids issuing from breached WPs. While 
dissolution of radioisotope-containing SNF rods and/or HLW glass solids into incoming fluids 
provides the primary source term, the formation of secondary phases often limits the amounts of 
radionuclides available for subsequent groundwater transport.

 3-58
The primary document supporting the radioisotope concentration model component is Summary 
of Dissolved Concentration Limits AMR (CRWMS M&O 2000l) (Figure 3.7-2). An important 
component of this AMR was the analysis with EQ3NR (a component of the qualified EQ3/6 
Version 7.2b package, CSCI: UCRL-MA-110662; CRWMS M&O 1998a). Ultimately though, 
the values described in the radioisotope concentration model reflect a newly revised 
thermodynamic database developed in CRWMS M&O (2000v). New measurements of 
radionuclide solubilities (Efurd et al. 1998; Kaszuba and Runde 1999) were combined with a 
critical review of recent thermodynamic parameterizations of Np, U, Pu, and Am phase 
stabilities that are being used by the international waste disposal community (NEA OECD) at 
large. 
Important components of this effort included the following. 
 Measurement and critical analysis of Np solubility in J-13 groundwater (see Table 3.7.1 
below). This led to revision of the formation free energy of Np2O5xH2O, an important 
Np-limiting phase, and Np speciation data (see Table 3.7.2 below). 
 Measurement and critical analysis of Pu solubility in J-13 groundwater. 
 Critical analysis of technetium and uranium silicate thermodynamic data 
3.7.1 Models Description 
The dissolved concentration limits calculation builds upon three primary feeds: (1) estimates of 
in-package fluid major element composition (pH, Eh, ionic strength, carbonate levels), 
(2) measured (and estimated) thermodynamic parameters describing the stabilities of aqueous 
species and solid radioisotope phases, and (3) a determination of the likely solubility-controlling 
phases for the specific radionuclides of concern. The in-package chemistry is described in 
Section 3.2 of this PMR. The thermodynamic databases that were used are described in the 
supporting AMRs (CRWMS M&O 2000l, 2000v). 
The chosen solubility-controlling phase can affect the calculated radionuclide concentrations by 
orders of magnitude and is one of the sources for uncertainty in the predicted concentration. In 
nature, the controlling phase may either be a pure radionuclide solid phase with the radioisotope 
as the dominant element or a solid phase with trace amounts of the radionuclide as can occur 
with coprecipitation. For TSPA-SR analysis the pure phases were chosen because in general 
they yield higher dissolved concentrations. See CRWMS M&O (2000w) for discussion of the 
potential effects of secondary phases on radionuclide concentration. The phases were chosen 
based upon geologic and/or experimental observations or crystallochemical arguments. For 
example, uranium solids observed at ore bodies and mine tailings are used to provide some clues 
as to the phases likely to form when fuel elements dissolve. For non-naturally occurring 
radioelements such as Pu and Np, experimental observations must be relied upon. Where no 
information can be gleaned from field observations or experimental results, it is conservative to 
simply assume that the most amorphous and hydrated (hence, most soluble) oxide of the 
particular radioelement forms. Typically, the secondary phases that form first in low 
temperature (T ~25C), natural systems are poorly-crystalline oxides and hydroxides whose 
solubility tends to be relatively high. Over time, secondary alteration minerals tend to become

 3-59
more crystalline and less hydrous. Consequently, the dissolved limits decrease. Some 
exceptions to this trend exist. Crystalline plutonium oxides can lose their crystallinity and 
become amorphous due to structural damage to the crystal caused by the ejection of alpha 
particles. These issues are discussed in CRWMS M&O (2000l) for U, Np, Pu, and Am 
radioisotopes. 
The amount of thermodynamic data available for the radionuclides, the sensitivity of the 
radionuclides solubilities on in-package chemistry, and the importance of the radionuclides to 
total system performance are quite uneven. For example, there is a large database for U, Np, and 
Am as a function of many chemical environments but very little for Pa. For these reasons, the 
implementation of solubility within the TSPA-SR analysis ranged from: (1) multi-termed 
functions of chemistry for U, Np, and Am, (2) distributions for Pu, Pa, Pb, and Ni, and 
(3) constant bounding values for Tc, I, Th, Cs, Sr, Cl, C, Nb, Zr, Ra, and Sn. For the multitermed 
functions, the solubility of the radionuclide was calculated as a function of time for each 
simulation. For the distribution type, a value for the simulation was sampled from the 
distribution and used for the entire simulation. For the last type, the same bounding value was 
used for all times in all simulations (see Table 3.7-5). 
The multi-termed functions describing U, Np, and Am solubilities, while developed from a 
statistical fit to predicted solubilities, possess some deterministic meaning as well. Specifically, 
the reactions affecting the solubilities of U, Np, and Amcarbonate complexation and 
hydrolysiswere identified beforehand. Hence, the solubilities can be resolved into, respectively, 
a PCO2 and pH dependence. For many of the other radionuclides, where little data are available, 
use of a high value bounding solubilities does not result in high doses because of the low 
inventory or other factor. Detailed discussions for each radionuclide are provided in CRWMS 
M&O (2000l). Some highlights are provided here. 
3.7.1.1 Uranium 
Uranyl (UO2
2+) minerals are expected to precipitate under the oxidizing conditions likely to 
prevail when breached WPs are initially altered by incoming fluids. Laboratory experiments and 
field observations show that the most common secondary uranyl minerals likely to form in the 
repository are schoepite, soddyite, uranophane, and/or Na-boltwoodite. For TSPA-SR analysis, 
schoepite was assumed to be the solubility-controlling mineral because: (1) schoepite is the first 
mineral to be formed during spent fuel corrosion; (2) field observations and modeling study 
indicate that schoepite can persist for more than 10,000 years; (3) schoepite is the most soluble 
of the common secondary phases; and (4) the temperature dependence of schoepite solubility is 
known. 
EQ3NR calculations were performed with pHs in half units from 5 to 9, temperatures 30, 50, 70, 
and 90 Celsius, and log( fCO2[bar]) of -2.5, -3.0, -3.5, and -4.0. The calculated U solubility 
ranges from 5  10-7 to 4  10-4 mol/L, with an average of 2  10-5 mol/L. The following 
regression equation provides the best fit (R2 = 0.924) to the 128 calculated points: 
T f T pH f pH 
T f pH pH U 
CO CO 
CO 
 -  -  
+ + - + - = 
2 2 
2 
2 
log 0022 . 0 0051 . 0 log 0.4161 
0.0095 log 1.6286 0.4292 6963 . 2 7.9946 ] log[ 
(Eq. 3.7-1)

 3-60
where [U] is the total concentration of uranium in mg/L, fCO2 is the fugacity of CO2 (bar), T is the 
temperature in kelvins (CRWMS M&O 2000l, Sections 6.3.5 and 6.3.7). 
3.7.1.2 Neptunium 
NpO2 is expected to be the most stable Np-bearing phase under in-package conditions. 
However, NpO2 has only rarely been observed to precipitate in laboratory experiments, 
presumably because kinetic obstacles prevent its nucleation and/or growth over short periods of 
time. Instead, the more soluble Np2O5 (or Np[OH]4[am] under reducing conditions) are assumed 
to be the solubility-controlling minerals. 
Table 3.7-1 shows measured Np solubilities in J-13 groundwater from which the new free energy 
of Np2O5xH2O was derived. Data are measured as a function of pH and temperature from 
oversaturation (after 450 days equilibration) and undersaturation (after 151 days equilibration) 
(Efurd et al. 1998, p. 3896) and compared with literature data (Nitsche et al. 1993, p. 2). 
Uncertainties are given as one standard deviation. 
Table 3.7-1. Averaged 237Np Concentrations in mol/L in J-13 Groundwater 
pH 6 pH 7 pH 8.5 
25C Oversaturation (6.51.1)  10-4 (3.10.2)  10-5 (1.50.6)  10-5 
Undersaturation (6.51.0)  10-4 (2.90.7)  10-5 (1.50.3)  10-5 
[Lit.] (5.30.3)  10-3 (1.30.2)  10-4 (4.40.7)  10-5 
60C Oversaturation (9.41.2)  10-4 (1.60.6)  10-5 (1.70.9)  10-5 
Undersaturation    
[Lit.] (6.40.4)  10-3 (9.81.0)  10-4 (1.00.1)  10-4 
90C Oversaturation (9.11.8)  10-4 (8.62.3)  10-6 (5.82.5)  10-6 
Undersaturation (8.70.9)  10-4 (9.31.9)  10-6 (5.92.1)  10-6 
[Lit.] (1.20.1)  10-3 (1.50.4)  10-4 (8.90.4)  10-5 
Source: Pure Phase Solubility Limits-LANL ANL-EBS-MD-000017. (CRWMS M&O 2000v, Table 5)

 3-61
Table 3.7-2 describes the output, updated thermodynamic parameters that were subsequently 
used in Summary of Dissolved Concentration Limits AMR (CRWMS M&O 2000l). 
Table 3.7-2. Updated Thermodynamic Data for Np(IV,V) Species 
Reaction or Species .fG298 (kJ mol-1) 
NpO2
+ -907.90  5.77 
Np4+ -491.10  9.49 
NpO2
+ + OH- = NpO2OH(aq) -1080.61  5.88 
NpO2
+ + 2 OH- = NpO2(OH) 2
- -1247.33  5.84 
NpO2
+ + 2 OH- + CO3
2- = NpO2(OH)2(CO3)3- -1791.01  7.36 
NpO2
+ + OH- + 2 CO3
2- = NpO2(OH)(CO3)2
4- -2155.41  6.71 
NpO2
+ + CO3
2- = NpO2CO3
- -1463.34  5.84 
NpO2
+ + 2 CO3
2- = NpO2(CO3)2
3- -2001.25  5.92 
NpO2
+ + 3 CO3
2- = NpO2(CO3)3
5- -2523.46  5.80 
NpO2
+ + F- = NpO2F(aq) -1197.07  8.55 
NaNpO2CO33.5H2O(s) = Na+ + NpO2
+ + CO3
2- + 3.5H2O -2591.02  5.86 
Na3NpO2(CO3)2(s) = 3 Na+ + NpO2
+ + 2 CO3
2- -2831.01  5.94 
KNpO2CO3(s) = K+ + NpO2
+ + CO3
2- -1795.97  5.80 
K3NpO2(CO3)2(s) = 3 K+ + NpO2
+ + 2 CO3
2- -2902.00  5.81 
NpO2(OH) (am) = NpO2
+ + OH- -1115.26  5.79 
NpO2(OH) (cr) = NpO2
+ + OH- -1119.31  5.84 
Np2O5 (s) + 2 H+ = 2 NpO2
+ + H2O -2023.30  12.41 
Np4+ + H2O = NpOH3+ + H+ -726.00  10.30 
Np4+ + 4 H2O = Np(OH)4(aq) + 4 H+ -1382.74  11.08 
Np(OH)4(am) + 4 H+ = Np4+ + 4 H2O -1431.26  9.65 
NpO2(s) + 4 H+ = Np4+ + 2 H2O -1021.80  2.5 
Np4+ + 5 CO3
2- = Np(CO3)5
6- -3324.64  11.26 
Np4+ + 4 CO3
2- = Np(CO3)4
4- -2803.14  11.36 
Np4+ + F- = NpF3+ -823.94  9.55 
Np4+ + 2 F- = NpF2
2+ -1144.10  9.74 
Source: Pure Phase Solubility Limits-LANL ANL-EBS-MD-000017. 
(CRWMS M&O 2000v, Table 2) 
NOTE: Bolded species are those for which .fG298 is given.

 3-62
Scoping calculations (CRWMS M&O 2000l, Section 6.4.3) indicated that the only important 
independent variables were pH and fCO2. Calculations were performed with pHs in half units 
from 4.5 to 8.5, and log (fCO2[bar]) of -2.5, -3.0, -3.5, and -4.0. The 32 calculated solubilities 
ranged from 2  10-6 to 1.5  10-2 mol/L, with an average of 2.3  10-3 mol/L. The best fit 
expression for Np solubility is: 
pH Np - -  +  = 8 8 10 086 . 1 10 538 . 7 ][ , R2 = 0.9997 (Eq. 3.7-2) 
where [Np] is the total concentration of neptunium in mg/L. Since fCO2 was significant only 
when pH was above the range of interest for in-package chemistry, it was not included in 
Equation 3.7-2. Figure 3.7-3 shows a comparison of the abstraction (Equation 3.7-2) and the 
under saturation data for 25C as listed in Table 3.7-1. 
3.7.1.3 Plutonium 
The primary candidates for solubility-controlling Pu phases are PuO2 and Pu(OH)4(am) (or 
PuO2xH2O, with x varying from 2 to zero). Since the crystalline phase forms within laboratory 
time scale, it is reasonable to assume that over geological time, plutonium hydroxides will 
convert to PuO2, and it should be used as the solubility-controlling mineral for Pu for the 
repository. However, a-decay of Pu isotopes has been observed to decrease the crystallinity of 
PuO2, while at the same time Pu hydroxide can gradually convert to anhydrous, though poorly 
crystalline, material. In order to be conservative, Pu(OH)4(am) was chosen as the controlling 
phase. The recommended thermodynamic data for Pu are shown in Table 3.7-3.

 3-63
Table 3.7-3. Recommended Thermodynamic Data for Pu(III,IV,V,VI) Species 
Reaction or Species .fGo
298 (kJ mol-1) 
PuO2
2+ -767.0  6.6 
PuO2
+ -857.5  6.7 
Pu4+ -477.8  3.4 
Pu3+ -578.6  3.3 
PuO2
2+ + OH- = PuO2OH+ -970.5  6.6 
PuO2
2+ + 2 OH- = PuO2(OH)2(aq) -1162  6.6 
PuO2
2+ + CO3
2- = PuO2CO3 (aq) -1348.6  6.8 
PuO2
2+ + 2 CO3
2- = PuO2(CO3)2
2- -1906.9  6.8 
PuO2
2+ + 3 CO3
2- = PuO2(CO3)3
4- -2449.1  6.8 
PuO2
2+ + F- = PuO2F+ -1075.1  6.8 
PuO2
2+ + 2 F- = PuO2F2(aq) -1371.6  7.3 
PuO2
+ + H2O = PuO2OH(aq) + H+ -1039.1  6.7 
PuO2
+ + CO3
2- = PuO2CO3
- -1414.7  6.7 
PuO2
+ + 2 CO3
2- = PuO2(CO3)2
3- -1951.2  8.8 
PuO2
+ + 3 CO3
2- = PuO2(CO3)3
5- -2469.4  7.8 
Pu4+ + H2O = PuOH3+ + H+ -712.2  4.1 
Pu4+ + 4 H2O = Pu(OH)4 + 4 H+ -1375  7 
Pu4+ + 5 CO3
2- = Pu(CO3)5
6- -3109.7  3.5 
Pu4+ + F- = PuF3+ -809.9  6.5 
Pu4+ + 2 F- = PuF2
2+ -1131.2  6.7 
Pu3+ + H2O = PuOH2+ + H+ -775.8  4.4 
Pu(OH)3(s) = Pu3+ + 3 OH- -1200.1  5.7 
PuO22H2O = Pu4+ + 4 OH- 
or Pu(OH)4(am) = Pu4+ + 4 OH- 
-1432  17 
PuO2(cr) + 2 H2O = Pu4+ + 4 OH- -976.2  3.6 
PuO2(OH)2(s) = PuO2
2+ + 2 OH- -1211.2  9.1 
PuO2(OH)(am) = PuO2
+ + OH- -1065.6  7.5 
PuO2CO3(s) = PuO2
2+ + CO3
2- 1376.1  6.8 
Source: Pure Phase Solubility Limits-LANL ANL-EBS-MD-000017 (CRWMS 
M&O 2000v, Table 3) 
NOTE: Bolded species are those for which .fG298 is given. Bolding was absent 
from the source document but was added in consultation with the author.

 3-64
EQ3NR calculations were performed with pHs in half units from 4 to 8, Eh (V) of 0.34, 0.55, 
and 0.76, and log (fCO2[bar]) of -3.0, and -3.5. The calculated Pu solubility ranged from 
10-10 mol/L at pH 8 and Eh 0.34 V to 2  10-4 mol/L at pH 8 and Eh 0.76 V. Because the data 
points were more uniformly distributed on a log than a linear scale, a log-uniform distribution 
was assigned (Table 3.7-5). 
A recent study (Haschke et al. 2000) on the reaction of PuO2 with water has found that in the 
presence of water and oxygen, PuO2 may be metastable and can be converted into PuO2+x. In 
other words, Pu may exist as Pu(VI) in the solid, and consequently in the solution. This new 
finding has raised the concern that Pu may be more soluble than previously believed, just as the 
conversion of U(IV) into U(VI) increases U solubility. This concern, however, is mitigated by 
the use of the much more soluble Pu(OH)2(am) instead of PuO2(c ) as the solubility controlling 
solid. While PuO2+x may be more soluble than PuO2(c ), it is not clear that PuO2+x is more 
soluble than Pu(OH)2(am). Also, the recent identification of PuO2+x does not preclude its 
presence in previous PuO2 solubility experiments, some of which were conducted for several 
hundred days. Only further study of PuO2+x and other possible solubility controlling solids will 
provide definitive answers to these questions. Because Pu(OH)2(am) solubility is quite high 
relative to dissolved Pu concentrations observed in spent fuel tests, this model is believed to be 
conservative. 
3.7.1.4 Americium, Actinium, Curium, and Samarium 
AmOHCO3 was chosen as the conservative solubility controlling phase (CRWMS M&O 2000l, 
Section 6.6 for discussion) for Am. Am solubility for 46 calculations ranged from about 2  10-8 
to 0.19 mol/kg as a function of pH and fCO2: 
log[Am] = 58.0335 - 18.9422  pH + 1.4744  pH2 - 6.0032  log(fCO2) 
- 0.7005  (log fCO2)2 + 0.1162  pH2  log(fCO2) + 0.1146  pH  (log fCO2)2 (Eq. 3.7-3) 
where [Am] is the concentration of americium in units of mg/L (Figure 3.7-4). 
Because of chemical similarities, the response functions for Ac, Cm, and Sm were set identical to 
that of Am (with adjustments for atomic weight). 
3.7.1.5 Technetium, Carbon, Chlorine, Iodine, Cesium, and Strontium 
Under the conservative assumption of oxidizing repository conditions, no solids are predicted to 
form to limit the solubility of Tc, C, Cl, I, and Cs. Therefore, the solubility of each is set to 
1.0 mol/L, which will let the waste inventory control their respective release. The recommended 
thermodynamic data for Tc are shown in Table 3.7-4. 
Strontium compounds are potentially quite soluble. Under repository conditions, strontium may 
coprecipitate with uranyl solids, or it may precipitate as carbonate or sulfate. In lieu of a more 
involved treatment, the Sr solubility is set to 1.0 mol/L, which will let the waste inventory 
control Sr release.

 3-65
Table 3.7-4. Recommended Thermodynamic Data for Tc Species 
Reaction or Species .fG298 (kJ mol-1) 
TcO4
- -637.2  7.6 
Tc(s) + 1.75 O2(aq) + 0.5 H2O = TcO4
- + H+ 0 
Tc3+ + O2(aq) + 2 H2O = TcO4
- + 4 H+ 92.4  10.5 
TcO2+ + 0.75 O2(aq) + 1.5 H2O = TcO4
- + 3 H+ -114.0  10.5 
TcO4
2- + H+ + 0.25 O2(aq) = 0.5 H2O + TcO4
- -578.3  10.0 
TcO4
3- + 2 H+ + 0.5 O2(aq) = 1.0 H2O + TcO4
- -521.4  11.2 
HTcO4(aq) = TcO4
- + H+ -637.1 
(TcO(OH)2)2(aq) + 4 H+ = 2 TcO2+ + 4 H2O -1172.2  14.2 
H2TcO4(aq) = TcO4
2- + 2 H+ -629.7  12.1 
HTcO4
- = TcO4
2- + H+ -628.0  10.5 
TcO(OH)2(aq) + 2 H+ = TcO2+ + 2 H2O -567.5  7.1 
TcO(OH)+ + H+ = TcO2+ + H2O -344.7  10.5 
TcO(OH)3
- + H+ = TcO(OH)2(aq) + H2O -742.52  7.10 
Tc(OH)2CO3(aq) = TcO(OH)2(aq) + CO2(g) -667.91  7.20 
Tc(OH)3CO3
- + H+ = TcO(OH)2(aq) + CO2(g) + H2O -857.95  7.20 
HTcO4(s) = TcO4
- + H+ -603.2  10.5 
KTcO4(s) = TcO4
- + K+ -932.7  7.6 
NaTcO4(s) = TcO4
- + Na+ -890.4  10.1 
CsTcO4(s) = TcO4
- + Cs+ -949.8  9.8 
Tc(OH)2(s) + 3 H+ + 0.25 O2(aq) = Tc3+ + 2.5 H2O -460.3  3.8 
Tc(OH)3(s) + 3 H+ = Tc3+ + 3 H2O -656.6  3.8 
Tc2O7(s) + H2O = 2 TcO4
- + 2 H+ -943.2  15.0 
Tc3O4(s) + 9 H+ + 0.25 O2(aq) = 3 Tc3+ + 4.5 H2O -861.4  3.8 
Tc4O7(s) + 10 H+ = 2 Tc3+ + 2 TcO2+ + 5 H2O -1278.4  21.0 
TcO22H2O(am) + 2 H+ = TcO2+ + 3 H2O -849.7  7.0 
TcOH(s) + 3 H+ + 0.5 O2(aq) = Tc3+ + 2 H2O -233.4  3.8 
TcS2(s) + H2O = TcO2+ + 2 HS- -229 
TcS3(s) + 4 H2O = TcO4
2- + 3 HS- + 5 H+ -276 
Tc2S7(s) + 8 H2O = 2 TcO4
- + 7 HS- + 9 H+ -594 
TcO2(cr) -4048 
Source: Pure Phase Solubility Limits-LANL ANL-EBS-MD-000017 (CRWMS M&O 2000v, 
Table 4) 
NOTE: Bolded species are those for which .fG298 is given. Bolding was absent from the 
source document but was added in consultation with the author.

 3-66
3.7.1.6 Nickel, Protactinium, and Lead 
A brief EQ3NR calculation carried out in the AMR titled Pure Phase Solubility LimitsLANL 
(CRWMS M&O 2000v, Section 6.3.6) gives the range of Ni solubility for Yucca Mountain 
waters as 1.4  10-6 to 3.1 mol/L, provided that bunsenite (NiO) is the solubility controlling 
mineral. No effort has been made to generate the distribution type for Ni solubility. A 
log-uniform distribution is proposed for Ni solubility for TSPA-SR, with a minimum of 
1.4  10-6 and a maximum of 3.1 mol/L. 
Due to the lack of thermodynamic data for Pa, no data compilation has been carried out in the 
Pure Phase Solubility Limits-LANL (CRWMS M&O 2000v). Thus, it is not possible to conduct 
EQ3NR calculations for Pa solubility. The process AMR suggests a solubility range of 
1.0  10-5 to 1.0  10-10 mol/L. This range is the same as Pa solubility values used in TSPA-93, 
which was obtained by the Project experts elicitation process (Wilson et al. 1994, Table 9-2b). 
The project experts further suggested a log-uniform distribution over that range. Therefore, for 
TSPA-SR, a log-uniform distribution for Pa solubility is recommended, with a minimum of 
1.0  10-10, a maximum of 1.0  10-5 (CRWMS M&O 2000l, Table 19), and a mean of 
3.2  10-8 mol/L. 
In carbonate containing waters, Pb3(CO3)2(OH)2 is believed to be a major important solid phase 
for constraining Pb solubility (CRWMS M&O 2000v, Section 6.3.11). Unfortunately, EQ3/6 
databases do not contain thermodynamic data for this solid. The process AMR (CRWMS 
M&O 2000v, Section 6.3.11) claims that, without thermodynamic data for that solid, calculated 
Pb(II) solubility is suspect. Based on reported Pb(II) solubility range in carbonate containing 
waters, the process AMR suggests a solubility range of 1.0  10-10 to 1.0  10-5 mol/L in Yucca 
Mountain waters. 
The above range is very close to the solubility range of Pb (1.0  10-8 to 1.0  10-5 mol/L, 
log-beta distribution) used in the TSPA-93 (Wilson et al. 1994, Table 9-2b), which is suggested 
by the Project experts. 
It is recommended that TSPA-SR use a log-uniform distribution, with a minimum of 1.0  10-10, 
and a maximum of 1.0  10-5 mol/L (CRWMS M&O 2000l, Table 19), to constrain Pb 
solubility. 
3.7.1.7 Niobium, Radium, Tin, Thorium, and Zirconium 
A study of Nb solubility has been conducted and documented in Pure Phase Solubility 
Limits-LANL (CRWMS M&O 2000v, Section 6.3.5) using EQ3NR. It suggests that Nb 
solubility ranges from 1.0  10-15 to 1.0  10-7 mol/L. It is recommended that TSPA-SR use a 
constant solubility of 1.0  10-7 mol/L for Nb. This abstraction is conservative and thus, 
adequate for use in TSPA-SR. 
Radium solubility has also been studied briefly in Pure Phase Solubility LimitsLANL (CRWMS 
M&O 2000v, Section 6.3.7). For Yucca Mountain waters, Ra solubility ranges from 1.1  10-6 
to 2.3  10-6 mol/L. A constant solubility of 2.3  10-6 mol/L is recommended for Ra.

 3-67
The calculated solubility range of tin reported in Pure Phase Solubility Limits-LANL (CRWMS 
M&O 2000v, Section 6.3.9) for Yucca Mountain waters is very narrow, from 4.8  10-8 to 
4.9  10-8 mol/L. Thus, a constant solubility of 5.0  10-8 mol/L for Sn is suggested for 
TSPA-SR. 
The AMR titled Pure Phase Solubility LimitsLANL (CRWMS M&O 2000v) does not provide a 
Th solubility range. The major reason for this omission is that the EQ3/6 current databases do 
not include thorium-carbonate species. As experiments have demonstrated that Th solubility 
may increase dramatically if the concentration of carbonate is high enough (Rai et al. 1995), 
model calculations without thorium-carbonate species are not meaningful. 
As a work around solution, a constant solubility of 1.0  10-5 mol/L is proposed for Th 
(CRWMS M&O 2000l, Table 19). A small amount of corroborating data support this proposed 
value: 1) the 1993 Expert Elicitation of the Project gives the Th solubility range of 10-10 to 10-7 
mol/L; 2) NRCs total-system performance assessment code version 3.2 (Center for Nuclear 
Waste Regulatory Analyses 1998, p. A-38) uses 2.3  10-4 kg/m3 = 10-6 mol/L as the solubility 
limit for Th, with consideration of thorium-carbonate species. In fact, this proposed value is one 
to two orders of magnitude higher than these corroborating data, and thus, is conservative and 
adequate for use in TSPA-SR. 
The Th thermodynamic data are being updated. Th carbonate complex data have been entered 
into a new input file (data0.ymp.R0). A qualification plan for this input file using the technical 
assessment method has been prepared. Once the data file is qualified by the Project, modeling 
calculations for Th solubility will be conducted and new values of Th solubility limits will be 
generated. 
Another brief EQ3NR calculation documented in the AMR titled Pure Phase Solubility 
Limits-LANL (CRWMS M&O 2000v, Section 6.3.10) generates a Zr solubility for Yucca 
Mountain waters of 6.8  10-10 mol/L (6.20  10-5 mg/L). This value is recommended for 
TSPA-SR. 
Table 3.7-5. Dissolved Concentration Limits for TSPA-SR 
Element Distribution Type Min (mol/L) Max (mol/L) 
Am Function ~10-7.7 ~0.19 
Ac Function ~10-7.7 ~0.19 
Sm Function ~10-7.7 ~0.19 
Cm Function ~10-7.7 ~0.19 
C Constant 1 1 
Cl Constant 1 1 
Cs Constant 1 1 
I Constant 1 1 
Nb Constant 10-7 10-7 
Ni Log-Uniform 10 -5.9 100.5 
Np Function ~10-5.7 ~10-1.8

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Table 3.7-5. Dissolved Concentration Limits for TSPA-SR 
(Continued) 
Element Distribution Type Min (mol/L) Max (mol/L) 
Pa Log-Uniform 10-10 10-5 
Pb Log-Uniform 10-10 10-5 
Pu Log-Uniform 10-10 10-3.7 
Ra Constant 10-5.6 10-5.6 
Sn Constant 10-7.3 10-7.3 
Sr Constant 1 1 
Tc Constant 1 1 
Th Constant 10-5 10-5 
U Function ~10-6.3 ~10-3.4 
Zr Constant 10-9.2 10-9.2 
Source: Excerpted from AMR: Summary of Dissolved Concentration 
Limits (CRWMS M&O 2000l, Table 19) plus Sections 3.7.1.1 
and 3.7.1.4 of this report 
3.7.2 Confidence/Limitations/Validation 
A systematic review of thermodynamic data and controlling phases has been performed for a 
large range of chemical conditions. When uncertainties were encountered, choices were made 
that would result in higher predicted solubilities. Inherent limitations within the databases can 
lead to an uncertainty up to a factor of 2 when the ionic strength exceeds about 0.7 mol/L. 
However, this uncertainty is small relative to other uncertainties within the system. The net 
result of these efforts is that predicted radionuclide levels closely approximate values measured 
in the laboratory. Equations for Pu solubility predict 25C pH 6 to 8.5 levels between 1  10-10 
and 2  10-4 (CRWMS M&O 2000l, Section 6.5.4) compared to measured values of 9.4  10-9 to 
1.1  10-6 (CRWMS M&O 2000v, Table 6). Parameterizations for Np solubility at pH < 8.1 
(see CRWMS M&O 2000l, Section 6.4) predict 25C pH 6 and 7 values of respectively 
4.6  10-4 and 4.6  10-5 mol/L of Np. For comparison, measured Np values (CRWMS 
M&O 2000v, Table 5) are respectively 6.5  10-4 and 3.1  10-5. 
Based on the considerations discussed above, this model is appropriate for its intended use. 
3.7.3 Other Views 
The TSPA peer review panel (Budnitz et al. 1999, Executive Summary, Section E, Data 
Research Needs) identified that there were several areas for which the need for data had not been 
met including identifying that solubility limit distributions for several key radionuclides come 
from a limited experimental database and suggesting further experimental study. It also 
identified difficulty in applying the conceptual model used to define solubility-limited 
concentrations (Budnitz et al. 1999, Section IV.G). In the VA (DOE 1998b, Section 6.5.2.7) 
DOE acknowledged the need for additional research in the areas of neptunium solubility and 
technetium sorption on degraded WP materials. It noted comments from the peer review panel 
that identified the need for experimental data to confirm the processes that control neptunium

 3-69
solubility (DOE 1998b, Section 6.5.2.2). DOE also acknowledged (DOE 1998b, Section 6.5.3.9) 
the need to support the basis for neptunium solubility with applicable measurements under 
suitable conditions. 
Several substantial changes were made in the Dissolved Radioisotope Concentration Component 
to address these concerns. Thermodynamic data were thoroughly reviewed for Np, and a 
regression model was built such that the solubility limit could be coupled to the estimated in 
package chemical environment as discussed in Section 3.2. Because experiments of the 
incorporation of Np into secondary phase minerals of U were not conclusive, the mechanism to 
potentially reduce solubility was not incorporated into the Dissolved Radioisotope Concentration 
Component (CRWMS M&O 2000w). The detailed process modeling to develop a regression 
model was also applied to U and Am. 
The distributions of three other key radionuclides (Pu, Th, and Ni) were carefully reevaluated in 
conjunction with some process modeling and knowledge of expected in-package chemical 
conditions. Finally, values for other key radionuclides (Tc, I, C, Nb, Zr, Pa, Pb, Ra, Sn, Cs, and 
Cl) were reevaluated through literature review process model calculations and were fixed at 
bounding values. The solubility values for radionuclides determined by the informal expert 
elicitation conducted in 1993 (Wilson et al. 1994) were used only to corroborate the newly 
evaluated distributions and fixed values. 
3.8 COLLOIDAL RADIONUCLIDE CONCENTRATION COMPONENT 
3.8.1 Introduction 
3.8.1.1 Function of Colloidal Concentration Component 
The function of the colloidal radioisotope concentration component is to calculate the 
concentration of colloid-associated radionuclides that may be transported from the waste 
package. The approach described herein is consistent with the approach used in the EBS PMR 
(CRWMS M&O 2000y). 
3.8.1.2 Radionuclides Susceptible to Colloidal Transport 
Colloid transport is potentially important for radionuclide elements that have low solubility and 
can be entrained in, or sorbed onto, waste form, engineered barrier, or geologic barrier materials 
that form colloidal particle substrates. Of these radionuclides, only those that are a major part of 
the waste inventory and have potentially large dose conversion factors are of potential 
importance to the performance of the disposal system. Considering these screening criteria, 
plutonium is the dominant radionuclide and was treated in TSPA-VA (CRWMS M&O 1998b, 
p. 6-97). Americium is also considered for the TSPA-SR analysis. 
3.8.1.3 Colloid Types 
The radionuclide-bearing colloids are formed by radionuclide entrainment as discrete phases in, 
or by radionuclide sorption onto, colloidal substrates. They are, therefore, classified into types 
based on the source of the substrate material and can be further classified based on how the 
radionuclides are attached to the substrates. Three major types of colloids are recognized to be

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important for the colloidal radionuclide concentration component based on the source of the 
colloid substrate material: 
1. Waste-form colloids formed during degradation of HLW glass (Note: these colloids 
are further classified into reversibly attached and irreversibly attached 
radionuclide types) 
2. Corrosion-product colloids formed during corrosion of iron-containing waste 
packages. 
3. Groundwater colloids present in the waste-form area. 
Based on laboratory evidence, waste-form colloids are produced from degradation of borosilicate 
HLW glasses. Fewer colloids have been observed in laboratory testing of CSNF, and 
experimental data are not yet available for defense spent-nuclear fuel DSNF and other waste 
forms, although testing is underway at NSNFP. The waste-form colloids that have been 
observed consist principally of smectite-type clay minerals. The laboratory evidence suggests 
that as HLW glass degrades, colloids are generated and often contain entrained plutonium. 
The engulfed solid inclusions of plutonium may be isolated from the aqueous system by the 
colloid itself and so may not be in equilibrium with the surrounding aqueous environment. 
Therefore, the engulfed plutonium in the waste-form colloids is conservatively assumed to be 
irreversibly associated with the waste form colloids. 
Corrosion-product colloids consist of ferric iron-(hydr)oxide minerals, primarily goethite 
(FeOOH) and hematite (Fe2O3) that are assumed to form as a result of corrosion of the WP 
materials (CRWMS M&O 2000m, Section 6.1.1). 
Groundwater colloids potentially present in the repository include those already present in the 
geosphere such as microbes, organic macromolecules (humic substances, including humic and 
fulvic acids), and mineral colloids (primarily clay minerals, silica, and iron-[hydr]oxide 
minerals). Microbe-facilitated radionuclide transport is disregarded because the relatively large 
size of microbes makes them susceptible to filtration. An assessment of the concentration of 
humic substances in groundwaters collected near the Yucca Mountain was conducted by Minai 
et al. (1992). In that study, humic substances were extracted from J-13 well water and 
experiments were conducted to characterize site binding densities and complexation with Am. 
Considering the presence of calcium in J-13 well water, the authors estimated that the effective 
complexation capacity of humic substances is about 2.3  10-10 eq/L (equivalents per liter) at 
pH 6.9 and 2.7  10-11 eq/L at pH 8.2. Based on this very low complexation capacity of humic 
substances in this system, they are not considered to be important groundwater colloids. Clays, 
silica, hematite, and goethite colloids occur in groundwater in the vicinity of Yucca Mountain, 
and it is assumed that small quantities of these colloids will enter a failed WP and be available to 
interact with released radionuclides. Consequently, mineral colloids are considered and will, 
henceforth, be referred to generically as groundwater colloids. These groundwater colloids are 
assumed to consist of smectite clays, which are fairly strongly sorbing minerals, and have been 
recognized at Yucca Mountain (Kingston and Whitbeck 1991). This assumption is based on the 
fact that smectite colloids are the dominant colloid in groundwaters at the Nevada Test Site and

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the fact that it is a conservative choice because clay minerals are more sorptive than silica and 
are comparable to iron-(hydr)oxide minerals. 
Radionuclides are attached to colloids as a result of two types of processes. For waste form 
colloids, radionuclides can be incorporated into the substrate material before it is suspended as 
colloids. All three colloid types may sorb radionuclides to form pseudocolloids, depending on 
the affinity of the colloid mineral substrate for a dissolved radionuclide. These two types of 
attachment processes are referred to as irreversible and reversible attachment, respectively. 
As illustrated in Figure 3.8-1, the colloid source term includes contributions from the various 
types of colloids, discussed above (i.e., waste-form, corrosion-product, and groundwater colloids 
with reversibly and irreversibly attached radionuclides). The contributions of each colloid type 
are summed to produce the mobile colloid source term for each important radionuclide. 
3.8.1.4 Colloid Stability in the Waste-Form Environment 
Like other mineral colloids, the stability of waste form, corrosion-product, and groundwater 
colloids are controlled by their surface charge and the associated electrostatic forces that 
influence colloid/colloid particle interactions. These surface charges and electrostatic forces are 
affected by the solution ionic strength and pH conditions. 
Surface charge on metal-(hydr)oxide and phyllosilicate minerals develops as hydroxyl functional 
groups protonate and deprotonate. At relatively low pH values, (pH's lower than the zero point 
of charge of the respective mineral) these minerals acquire a positive surface charge, due to 
protonation. Conversely, at high pH values, (pH's greater than the pH of zero surface charge), 
these minerals acquire a negative surface charge, due to deprotonation. Other minerals may 
develop a charge due to reactions of carbonate, phosphate, and silinol surface functional groups. 
Each mineral has a particular pH where the mineral surface is neutral, called the pH at zero-point 
of charge (pHZPC). At the pHZPC, dispersions of colloidal particles composed of a particular 
mineral tend to be destabilized. 
Colloidal particles are maintained in suspension by Brownian forces when electrostatic forces 
inhibit colloidal particles from achieving sufficiently close proximity that the particles can stick 
and agglomerate due to Van Der Waals interactions. However, as the ionic strength of the 
system is increased to a threshold value (the critical coagulation concentration or c.c.c.), the 
thickness and effectiveness of the protective electrostatic shell surrounding the particles 
diminishes, and the particles no longer repel one another during collisions. As a result, the 
colloidal particles agglomerate and eventually become large enough so that they settle out of 
suspension due to gravitational forces. 
3.8.1.5 Implementation of Colloidal Concentration Component 
The colloid concentration component is implemented by summing the contributions of the three 
colloid types to the colloid radioisotope concentration for each radionuclide. 
A model was developed to calculate the colloid radioisotope concentration for each of the three 
colloid types. The model for the waste form colloids includes the contributions of the engulfed 
(irreversible attached) plutonium observed in waste glass tests. The models for all three colloid

 3-72
types include reversibly attached radionuclides. These models are based on the population of 
each colloid type (expressed in terms of mass of colloids per volume of fluid) and experimental 
data for the sorption of radionuclides onto the colloid substrate materials involved. The effects 
of pH and ionic strength on the stability of dispersions of each colloid type are considered. The 
location of the boundaries between pH and ionic strength regimes in which each type of colloid 
substrate is stable or unstable are defined together with the colloid mass concentration in each 
regime. 
The model is shown schematically in Figure 3.8-2. 
3.8.1.6 Documents Supporting Colloidal Concentration Component 
This section is based on the model abstraction AMR Waste Form Colloid-Associated 
Concentrations Limits: Abstraction and Summary (CRWMS M&O 2000m), the model 
abstraction AMR draws on Yucca Mountain research conducted at Argonne National Laboratory 
(ANL) (CRWMS M&O 2000x, Section 6) and Los Alamos National Laboratory (LANL). 
3.8.2 Model Description 
In this section, the technical basis for the model subcomponents, the abstraction, and logic 
diagrams illustrating the implementation in TSPA are described. In reading the section, 
Table 3.8-1 should be consulted for parameter definitions and values discussed in the section. 
The section starts with a description of how radionuclides are attached to colloidal substrates. 
This is followed by a description of how the colloid radioisotope concentrations are modeled for 
each colloid type. 
3.8.2.1 Radionuclide Uptake Mechanisms 
This section addresses the modeling of radionuclide attachment/detachment for colloidal 
substrates. It is based on the experimental evidence that the attachment/detachment processes 
can be divided into two categories. The first involves incorporation of the radionuclides into 
waste form alteration material that subsequently becomes suspended as colloidal material. The 
second involves attachment of dissolved radionuclides to preexisting colloids. Because 
attachment of radionuclides by sorption onto the colloid substrate material is important for all 
three types of colloids, it is discussed first.

 3-73
Table 3.8-1. Parameter Names, Definitions, and Values 
Parameter Name Parameter Description Unitsa 
Basis for 
Value/Source Value and Distribution 
Waste-form 
colloids 
Figure 3.8-6 
Mcoll,wf,both Total mass of both types of waste-form colloids per unit 
volume or mass of water (assumes that the mass contributed 
by reversibly attached radionuclides is negligible) 
mg/L d d 
CRNcoll,wf,irrev,max Highest observed or expected concentration of radionuclide 
element RN associated with both types of waste-form colloids 
mol/L CRWMS M&O 2000m, 
Section 6.2.2 
6  10-8 mol/Lb 
CRNcoll,wf,irrev,min Lowest observed or expected concentration of radionuclide 
element RN associated with both types of waste-form colloids 
mol/L CRWMS M&O 2000m, 
Section 6.2.2 
1  10-11 mol/Lb 
Mcoll,wf,both,max Highest observed or expected mass of both types of wasteform 
colloids per unit volume or mass of water 
mg/L e 5 mg/Lc 
CRNcoll,wf,irrev Concentration of irreversibly attached (or engulfed as a solid 
inclusion) radionuclide element RN associated with wasteform 
colloids 
mol/L d d 
CRNcoll,wf,rev Concentration of reversibly attached radionuclide element RN 
associated with waste-form colloids 
mol/L d d 
Mcoll,wf,both Mass of waste-form colloids with reversibly sorbed or 
irreversibly attached (or engulfed) radionuclide element RN 
per unit volume or mass of water 
mol/L d d 
Ilo-thresh,coll,wf Ionic strength below which waste-form colloids are stable mol/L Figure 3.8-4 (Pu); 
Figure 3.8-5 
0.01 mol/L 
Ihi-thresh,coll,wf Ionic strength above which waste-form colloids are unstable; 
also used for groundwater colloids 
mol/L Figure 3.8-4 (Pu); 
Figure 3.8-5 
0.05 mol/L 
Kd,RNcoll,wf,rev Distribution coefficient for reversible sorption of radionuclide 
element RN onto waste-form colloids 
mL/g 
colloid 
Various sources  
refer to Section 
3.8.2.2.1 
Geometric mean values: 
Pu = 10,000 
Am = 100,000 
log-normal distributions; geometric 
std. dev. = 1 order-of-magnitude 
STcoll,wf,is Function relating stability of waste-form colloids to ionic 
strength, based on results of HLW glass degradation 
experiments (based on Pu concentration) 
mol/L CRWMS M&O 2000m, 
Section 6.2.2 
[Pu colloid] = -1.25  10-6  I +7.25 
 10-8 
STcoll,wf,pH Function relating stability of waste-form colloids to ionic 
strength and pH, over limited pH range, based on results of 
Montmorillonite stability experiments; also used for 
groundwater colloids 
mol/L Figure 3.8-5 I = pH/200

 3-74
Table 3.8-1.Parameter Names, Definitions, and Values (Continued) 
Parameter Name Parameter Description Unitsa 
Basis for 
Value/Source Value and Distribution 
iron-(hydr)oxide 
colloids 
Figure 3.8-8 
CRNcoll,FeOx Concentration of reversibly attached radionuclide element RN 
associated with iron-(hydr)oxide colloids 
mol/L d d 
Mcoll,FeOx Mass of iron-(hydr)oxide colloids per unit volume or mass of 
water 
mg/L d d 
Mcoll,FeOx,max Highest observed or expected mass of iron-(hydr)oxide 
colloids per unit volume or mass of water 
mg/L (CRWMS M&O 
2000m, Table 1) 
1 mg/L 
Mcoll,FeOx,min Lowest observed or expected mass of iron-(hydr)oxide 
colloids per unit volume or mass of water 
mg/L (CRWMS M&O 
2000m, Table 1) 
1  10-3 mg/L 
Ilo-thresh,coll,FeOx Ionic strength below which iron-(hydr)oxide colloids are stable mol/L Figure 3.8-7 0.01 mol/L 
Ihi-thresh,coll,FeOx Ionic strength above which iron-(hydr)oxide colloids are 
unstable 
mol/L Figure 3.8-7 0.05 mol/L 
Kd,RNcoll,FeOx Distribution coefficient for reversible sorption of radionuclide 
element RN onto iron-(hydr)oxide colloids 
mL/g 
colloid 
various sources  refer 
to Section 3.8.2.1 
geometric mean values: 
Pu, Am = 10,000 
log-normal distributions; geometric 
std. dev. = 1 order-of-magnitude 
STcoll,FeOx,pHlo Function relating stability of iron-(hydr)oxide colloids to pH 
and ionic strength at relatively low pH values 
mol/L Figure 3.8-7 I = -0.02  pH +0.17 
STcoll,FeOx,pHhi Function relating stability of iron-(hydr)oxide colloids to pH 
and ionic strength at relatively low pH values 
mol/L Figure 3.8-7 I = +0.02  pH  0.17 
STcoll,FeOx,pHint Function relating stability of iron-(hydr)oxide colloids to pH 
and ionic strength at intermediate pH values 
boolean Figure 3.8-7 boolean 
(pH = 8 AND pH = 9) 
groundwater 
colloids 
Figure 3.8-10 
CRNcoll,gw Concentration of reversibly attached radionuclide element RN 
associated with groundwater colloids 
mol/L d d 
Mcoll,gw Mass of groundwater colloids per unit volume or mass of 
water 
mg/L d d

 3-75
Table 3.8-1.Parameter Names, Definitions, and Values (Continued) 
Parameter Name Parameter Description Unitsa 
Basis for 
Value/Source Value and Distribution 
Mcoll,gw,max Highest observed or expected mass of groundwater colloids 
per unit volume or mass of water 
mg/L Figure 3.8-9 3  10-2 mg/L 
Mcoll,gw,min Lowest observed or expected mass of groundwater colloids 
per unit volume or mass of water 
mg/L Figure 3.8-9 3  10-6 mg/L 
Kd,RN,coll,gw Distribution coefficient for reversible sorption of radionuclide 
element RN onto groundwater colloids 
mL/g 
colloid 
various sources  refer 
to Section 3.8.2.1 
geometric mean values: 
Pu = 10,000 
Am = 100,000 
log-normal distributions; geometric 
std. dev. = 1 order-of-magnitude 
Ilo-thresh,coll,gw Ionic strength below which groundwater colloids are stable mol/L Figure 3.8-9 0.01 mol/L 
Ihi-thresh,coll,gw Ionic strength above which groundwater colloids are unstable mol/L Figure 3.8-9 0.05 mol/L 
STcoll,gw Function relating stability of groundwater colloids to ionic 
strength at intermediate ionic strengths 
mg/L Figure 3.8-9 CRWMS M&O (2000m, p. 53, 
equations 4 and 5) for equation 
colloid source 
term 
Figure 3.8-11 
CRNcoll Concentration of mobile colloidal radionuclide element RN per 
unit volume or mass of water 
mol/L d d 
Mcoll Total mass of all mobile colloids per unit volume or mass of 
water 
mg/L d d 
input parameters Figures 3.8-6, 3.8-8, 
3.8-10, and 3.8-11 
I Ionic strength mol/L f f 
pH pH pH units f f 
CRNdiss Concentration of dissolved radionuclide element RN per unit 
volume or mass of water 
mol/L f f 
Source: Waste Form Colloid-Associated Concentrations Limits: Abstraction and Summary (CRWMS M&O 2000m, Table 1). 
NOTES: a mol/L is actually moles per liter of dispersion and is not molarity in the strict sense; L may be replaced with kg, if PA prefers molality 
buncertainty is linked to uncertainty for ionic strength, which is an input parameter; no additional uncertainty is added 
cmass is correlated with irreversible radionuclide concentration 
dmodel output 
e(CRWMS M&O 2000m, Figure 10) 
finput parameters

 3-76
The processes (referred to as sorption processes) controlling the attachment and detachment of 
soluble materials to colloidal substrates are complex. They are, however, similar to the 
processes that control attachment and detachment of dissolved materials to rock surfaces in the 
subsurface. The approach adopted to describe interactions between colloid substrate materials 
and dissolved radionuclides is, therefore, similar to that used for contaminant-rock interactions in 
the subsurface. The most common approach used in assessing these interactions is the linear 
isotherm, or Kd, approach based on results of batch sorption experiments. The linear isotherm 
model relationship is defined as follows: 
S = Kd  C (Eq. 3.8-1) 
where Kd is the distribution coefficient (mass or surface-area based), S is the mass of a solute 
sorbed on a unit mass (or surface area) of solid, and C is the concentration of the sorbing solute. 
The basis for the Kd values used is described in CRWMS M&O (2000m, Section 6.1.3, 
Attachment XVI). Table 3.8-1 summarizes recommended values, which have been extracted 
from the LANL data. For Pu and Am, values were developed from the colloid experiments. The 
maximum Kd values from the ranges for devitrified tuff and iron oxide were used as an analog 
for colloids consisting of smectite and corrosion-product colloids, respectively. Given the nonexact 
nature of developing these Kd values, a plus-or-minus one-order-of-magnitude uncertainty 
band was assigned to each value. 
As described in CRWMS M&O (2000m, Section 6.1.3 and Attachment XVI) a large amount of 
data exists in published literature for sorption. The ranges of Kd values developed from the YMP 
data are generally consistent with those in the literature. 
It is recognized that, because of the complexity of the processes involved, the assumptions 
implicit in the use of the linear isotherm model may not be satisfied for attachment of actinides 
to colloid substrates. For example, experimental evidence from plutonium sorption experiments 
(CRWMS M&O 2000m, Section 6.1.3, Attachment XVI) with colloidal hematite and goethite 
show that the rate of desorption (backward rate) of Pu is significantly slower than the rate of 
sorption (forward rate). More importantly, over a significant time period (up to 150 days in 
some experiments), the extents of desorption is somewhat less than the extent of sorption. To 
accommodate this non-ideal sorption behavior of plutonium, a larger Kd was selected based on 
the desorption experiments, pending further results from LANL. 
The second type of radionuclide attachment to colloidal substrates involves incorporation of the 
radionuclide into the colloidal material substrate before it becomes suspended as colloids. 
Experimental results from HLW glass degradation experiments show that plutonium can be 
incorporated as discrete phases in smectite colloids generated during the experiments (CRWMS 
M&O 2000x, Section 6.2). Because the plutonium in these colloids appears to be formed by 
coprecipitation, along with the substrate materials, it can be envisioned to be engulfed in the 
colloid matrix. The extent to which these engulfed radionuclides are available for interaction 
with the solution is uncertain. To accommodate this uncertainty, the model and abstraction 
accounts for smectite colloids with engulfed plutonium and other radionuclides by treating 
them as a separate colloid subtype and by conservatively assuming that the engulfed 
radionuclides are an intrinsic part of, and irreversibly attached to, the colloid substrate.

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3.8.2.2 Waste-Form Colloids 
Three broad categories of waste form are to be placed in the repository. The most abundant 
waste type is CSNF from commercially owned and operated electric power reactors. DSNF is a 
diverse collection of waste from reactors at DOE nuclear-complex sites. HLW is a borosilicate 
glass-based waste form. In the following descriptions, CSNF and DSNF are treated together. 
3.8.2.2.1 HLW Glass 
In long-term tests (CRWMS M&O 2000x, Section 6.2 and Ebert 1995, Section 9.2.3) 
experimental evidence indicated that colloids were produced through spallation of altered glass 
at the glass-water interface. The colloids were primarily smectite clay containing discrete 
radionuclide-bearing phases incorporated (entrained) into the clay (CRWMS M&O 2000x, 
Sections 6.2, 6.2.1, Figure 1). Some iron silicate colloids were also observed. Several entrained 
phases were identified including brockite (thorium calcium orthophosphate) and an amorphous 
thorium-titanium-iron silicate, similar to thorutite. The phases contained actinides and rare-earth 
elements. Uranium was detected within the clays and iron silicates in some samples. 
Because the experimental evidence indicates that the entrained phases are often engulfed in a 
smectite clay substrate the colloidal properties of the entrained radionuclide-bearing phases are 
assumed to be governed by the properties of the smectite. The stability (and therefore mobility) 
of smectite colloids will control the stability of the colloids. Also, because the extent to which 
the smectite clay substrate isolates the entrained radionuclide phases from interacting with the 
solution is uncertain, it is conservatively assumed that the radionuclides are irreversibly attached 
to the smectite colloid substrate. 
It was observed in the static tests that colloids developed and increased in concentration with 
time, up to a point where the colloids concentration reached a maximum and then became 
unstable. This was attributed to increase in the ionic strength to a threshold above which the 
colloids precipitated and flocculated (CRWMS M&O 2000x, Section 6.2.1, Figure 8). These 
data provide the experimental basis for evaluating the ionic strength regimes in which the waste 
form colloids are stable or unstable. 
3.8.2.2.2 Spent Nuclear Fuel 
Very little radionuclide-bearing colloidal material was detected in tests on corrosion of the 
uranium dioxide-based commercial LWR SNF (CRWMS M&O 2000x, Sections 6.3.2 and 6.4.3, 
Figures 25 and 30). The available leachate analyses showed that the total Pu concentration 
(dissolved, colloidal, and sorbed onto the test vessel) was in the range 10-8 to 10-10 mol/L. 
However, no colloids with embedded radionuclide phases similar to those observed HLW glass 
tests were observed in the much fewer number of CSNF tests. Although the data show that some 
of this plutonium was colloidal, the types of colloids involved are not known. Little information 
is currently available concerning the quantity or types of colloids formed from DSNF, but 
preliminary tests indicate that colloid formation from metallic uranium-based DSNF may be 
significant. DSNF colloid formation and characterization testing has been initiated. For 
modeling purposes, it is assumed that only colloids with reversibly attached radionuclides are 
formed in the corrosion of commercial and defense spent nuclear fuels. This assumption is

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potentially non-conservative, and will be verified as pertinent results of ongoing confirmatory 
test become available (CRWMS M&O 2000m, Section 6.4.1). Note, however, that corrosionproduct 
colloids, generated from the degradation of the waste packages, are formed in proximity 
of all waste types. As metal-(hydr)oxides, corrosion-product colloids will behave similarly to 
metal-(hydr)oxide colloids generated during SNF degradation, in terms of radionuclides sorption 
and stability characteristics. The mass concentrations of corrosion-product colloids are 
reasonable, based on the ranges of colloid concentrations observed in natural waters spanning a 
wide range of hydrogeochemical conditions. 
3.8.2.2.3 Waste-Form-Colloid Concentration Model and Abstraction 
The waste form concentration model includes contributions from colloids with reversibly and 
irreversibly-attached radionuclides. 
The model for the concentration of irreversibly attached radionuclide is based on the 
experimental data for HLW glasses. It was observed experimentally that, as the ionic strength 
increased, colloid concentration generally decreased and ultimately a threshold value was 
reached above which the colloids were not observed or were observed in very low quantities 
(Figure 3.8-3) (CRWMS M&O 2000x, Figure 8). As this threshold was approached, it was also 
observed for one glass that the colloid size increased significantly due to aggregation of the 
colloids. The threshold at which flocculation occurred was approximately 0.05 mol/kg. 
Colloids formed from HLW glasses in the ANL tests consist predominantly of a smectite clay 
substrate often containing discrete radionuclide-bearing phases entrained within the clay. For 
modeling purposes it is assumed that colloids derived from HLW are all radionuclide-bearing 
smectite. The radionuclides are conservatively assumed to be irreversibly attached to the 
smectite colloid substrate, pending forthcoming data from LANL on radionuclide attachment and 
detachment to/from waste form colloids. Figure 3.8-4 represents the abstraction of the ANL 
experimental results. Based on ionic strength conditions near the waste form, the concentration 
of irreversibly attached colloidal plutonium is calculated. A flow chart illustrating how these 
calculations are performed is shown in Figure 3.8-6a. At ionic strengths less than 0.01 mol/kg, 
colloidal Pu concentration is set to equal the maximum value observed in the experiments 
(6  10-8 mol/L). At ionic strengths greater than or equal to 0.05 mol/kg, colloidal Pu 
concentration is defined as a minimum observed value (1  10-11 mol/L). At intermediate ionic 
strengths, colloidal Pu concentration is an intermediate value calculated as illustrated in 
Figure 3.8-6b. The details of these calculations are described more fully in CRWMS M&O 
(2000m, Section 6.2.2 and Figure 13). Because of changes in methods of analysis, slightly larger 
Pu concentrations are given in CRWMS M&O (2000x, Figure 8). However, the differences are 
small enough that they can have, at the most, a minor effect on total system performance. 
The pHZPC of smectite occurs at a pH value of approximately 2. Since a pH this low is not 
anticipated in the repository, it is a reasonable assumption that smectite colloids will remain in a 
stable pH range much of the time under anticipated repository conditions (unless ionic strength 
exceeds a certain threshold). Tombacz et al. (1990) investigated the stability of montmorillonite 
suspensions as a function of pH and ionic strength in NaCl solutions. They found that 
suspensions became unstable and flocculated at pH 2, 4, and 8 in 0.01 mol/L, 0.025 mol/L, and 
0.04 mol/L NaCl solutions, respectively (Figure 3.8-5a). This relationship suggests that the

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stability of smectite colloids becomes increasingly sensitive to ionic strength as pH drops below 
about 8. This concept is represented by the abstraction shown in Figure 3.8-5b. At combinations 
of ionic strength and pH falling below the sloped line, waste-form colloids are stable, and the 
maximum concentration defined in the previous paragraph (i.e., 6  10-8 mol/L) is maintained. 
At combinations of pH and ionic strength falling above the sloped line, waste-form colloids are 
unstable, and the concentration is adjusted to the minimum value (1  10-11 mol/L). This 
approach assumes that the concentration of irreversibly attached colloidal Pu is directly 
proportional to the mass of colloids. That assumption is valid based on observations from ANL 
experiments and descriptions in the AMR (CRWMS M&O 2000x, Figure 24, Section 6.3). The 
abstraction of the effect of ionic strength on waste-form colloid concentration (Figure 3.8-4) and 
the effect of the combination of ionic strength and pH (Figure 3.8-5) on colloid stability is 
illustrated as a flow chart in Figure 3.8-6a and 6b, respectively. 
To determine the amount of a radionuclide that can reversibly sorb onto the surface of 
waste-form colloids, a mobile mass is required. Since the concentration of irreversibly attached 
colloidal Pu is directly proportional to the mass of colloids, the mobile mass is determined by 
scaling on the basis of predicted plutonium concentration (determined from Figures 3.8-4 and 
3.8-5b). The scaling is based on the ratio of the maximum plutonium concentration 
(6  10-8 mol/L) and the maximum colloid mass concentration (5 mg/L). This approach is 
illustrated in flow chart format in Figure 3.8-6c. Based on a comparison of colloid mass and 
plutonium associated with colloids, it was found that a concentration of approximately 1 mg 
colloids correlated to about 1.2  10-8 moles of colloidal plutonium (CRWMS M&O 2000x, 
Figure 24; CRWMS M&O 2000m, Figure 10). The maximum stable colloid mass concentration 
was about 5 mg/L (corresponding to 6  10-8 mol/L colloidal Pu). These observations are 
specific to the ANL experiments, but they provide a means for scaling irreversible 
colloid-associated Pu concentration to ionic strength. 
The concentration of reversibly sorbed radionuclide is determined using appropriate Kd values 
and Equation 3.8-1 (Figure 3.8-6d). 
3.8.2.3 Corrosion Product Colloids 
Corrosion product colloids are assumed to be generated as a result of the corrosion of ironbearing 
components of the WP. In this section, radionuclide uptake of mobile corrosion product 
colloids, assumed to be iron-(hydr)oxides such as hematite and goethite, is described. 
3.8.2.3.1 Corrosion-Product-Colloid Concentration Model and Abstraction 
Data are not available on the concentration of corrosion product colloids that may be generated 
as a result of corrosion of the WP materials. Limited data do exist, however, for concentrations 
of iron-colloids in natural systems. At the Morro de Ferro natural analog site (Poos de Caldas, 
Brazil) concentrations of iron-hydroxide [Fe(OH)3] colloids were measured in deep 
groundwaters adjacent to an iron-rich rock body. The measured concentration, 0.25 mg/L, is 
similar to concentrations of other inorganic colloids found in natural waters at other deep sites 
(McCarthy and Degueldre, 1993, Table 6). Consequently, it is conservatively assumed that the 
concentration of these colloids is comparable to that of the groundwater colloids (all 
mineralogies) that are observed in natural groundwaters (CRWMS M&O 2000m,

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Section 6.1.1.3). Colloid concentrations observed in natural waters represent concentrations 
developed over a wide range of hydrogeochemical conditions, which provides some assurance 
that the approach used is reasonable. A maximum value of 1 mg/L (Table 3.8-1) was used in the 
TSPA calculations, which imparts a four-fold conservatism relative to concentrations observed at 
the analog site. 
The stability behavior of iron-(hydr)oxide colloids with respect to ionic strength and pH is 
predictable. As shown in Figure 3.8-7a, iron-(hydr)oxide has a pHZPC of about 8.5. At much 
lower and higher pH values, iron-(hydr)oxide colloids are affected by ionic strength much like 
other minerals, in that ionic strengths greater than about 0.05 mol/kg result in destabilization 
(Figure 3.8-7a). These concepts are represented in the abstraction shown in Figure 3.8-7b. At 
pH values close to the pHZPC, the dispersion is determined to be unstable regardless of ionic 
strength, and a minimum mass concentration is established. The same situation applies if an 
input pH value is several pH units away from the pHZPC and ionic strengths are greater than 
0.05 mol/kg. At intermediate pH values the combined effect of ionic strength and pH are 
described by two lines; above the lines, the colloidal dispersion is unstable, and a minimum mass 
concentration is established. These concepts are illustrated in a flow-chart format in 
Figure 3.8-8a in which the approach for calculating the mobile mass of iron-(hydr)oxide colloids 
is defined. 
Given the mass concentration of the corrosion product colloids, the concentration of reversibly 
sorbed radionuclide is determined using appropriate Kd values and Equation 3.8-1 (see 
Figure 3.8-8). 
3.8.2.4 Groundwater Colloids 
As described in Section 3.8.1.3 smectite colloids are expected to be in the groundwater that 
enters the degraded WPs. The basis for modeling the mass concentration and the radioisotope 
concentration associated with these colloids as they exit the WP is described below. 
3.8.2.4.1 Groundwater-Colloid Model and Abstraction 
Several workers (for example, McCarthy and Zachara 1989; McCarthy and Degueldre 1993) 
have studied and compiled the characteristics of colloids in groundwaters from crystalline and 
sedimentary rocks in saturated and unsaturated hydrologic regimes throughout the world. Data 
on colloid concentration and ionic strength for these groundwaters (Figure 3.8-9a) show a 
general inverse correlation above an ionic strength of about 0.01 mol/kg and provide a predictive 
tool for estimating groundwater colloid mass concentration. This relationship is not precise 
because there are other factors, such as pH, that can significantly affect concentration. 
To be useful for TSPA-SR analysis calculations, these data were converted to mass or surface 
area per unit volume. For naturally occurring colloids, it has been observed that the number 
population and colloid size correlate using a power function (CRWMS M&O 2000m, 
Section 6.2.3). In general, the number of colloids increases by a factor of 1000 as colloid 
diameter decreases by a factor of 10 (assuming spherical colloids). Expressed mathematically, 
the colloid population is proportional to the inverse of the colloid diameter cubed. By taking the 
first derivative of the cumulative distribution, combining with masses of individual colloids

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assuming spherical geometry and then integrating the function between a lower and upper size 
limit, the total colloidal mass is obtained. Colloid masses were calculated using the number 
populations in Figure 3.8-9a and extrapolated to include colloid sizes between 10 nm and 
1 micrometer. A colloid mineral density of 2.5 g/cm3 was assumed. Details of this abstraction 
are described in CRWMS M&O (2000m, Section 6.2.3). 
Figure 3.8-9 illustrates the abstraction. The upper and lower bounding lines capture the highest 
and lowest concentrations of colloids shown in Figure 3.8-9a. Between ionic strengths of 
0.01 and 0.05 mol/kg, the number and mass concentrations decrease as groundwater colloids are 
destabilized. The decrease is assumed to be linear in log-log space. The flow chart in 
Figure 3.8-10 illustrates how the groundwater colloid mass concentration is calculated as a 
function of ionic strength. 
Given the assumption that Yucca Mountain groundwater colloids are clays, the relationship 
developed above for the effect of ionic strength and pH on montmorillonite can also be used 
here. The approach for calculating the effect of pH on the groundwater colloid mass 
concentration is illustrated in the flow chart in Figure 3.8-10b. It is similar to the approach 
illustrated in Figure 3.8-5a and 5b. 
It is assumed that sorption for groundwater colloids is similar to clay minerals (CRWMS 
M&O 2000m, Section 6.2.3), and the same Kd values used for waste-form colloids are used for 
groundwater colloids. The concentration of a reversibly-sorbed radionuclide is determined using 
appropriate Kd values (see Figure 3.8-10c). 
3.8.2.5 Mobile Colloidal Radionuclide Source Term 
Also illustrated in Figure 3.8-11, the mobile colloidal radionuclide source term is the sum of the 
radionuclide contribution from waste-form colloids (reversibly and irreversibly attached), 
corrosion-product colloids, and groundwater colloids. The total colloid mass concentration is 
also provided for recalculating reversibly attached radionuclide concentrations as dissolved 
concentrations change during transport. 
3.8.3 Confidence/Limitations/Validation 
The abstractions are based on laboratory results from waste form corrosion testing and testing of 
adsorption and desorption properties of Pu and Am on clay and iron-(hydr)oxide colloids. To the 
extent that the laboratory tests and test conditions represent anticipated repository conditions, the 
abstraction is valid for calculating the colloid-associated radionuclide concentrations and colloid 
mass concentrations. The approach for the colloidal-radionuclide source term is based on 
YM-specific field and laboratory studies and results from YM-relevant studies. The 
development of the conceptual model and implementation requires consideration of colloid 
generation, colloid-radionuclide interaction, colloid stability behavior, and to some extent, 
colloid transport/ retardation behavior. Information used for groundwater colloids, waste-form 
colloids, and corrosion-product colloids was obtained primarily from YM-specific studies. 
Consequently, the colloid-concentration model is expected to be representative of YM behavior. 
Field evidence of small concentrations of radionuclides associated with colloids migrating 
considerable distances provides insight into possible colloid behavior at YM. At the Benham

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nuclear test site at the Nevada Test Site, rapid transport of colloid-associated Pu appears to have 
occurred (Kersting et al. 1999). At a point approximately 1.3 km from the blast site, 1  10-14 
mol/L colloid-associated plutonium was detected 30 years after the detonation. It is difficult to 
determine what fraction of the transport was due to transport on colloids, injection through 
fractures by the blast, or transport as dissolved Pu. However, in the cases of other detonations, 
fracture injections have not been observed to extend beyond a few hundred meters, and dissolved 
Pu would be expected to sorb strongly to the fracture surfaces. It is plausible that the Pu was 
transported as Pu irreversibly attached to colloids. This example underscores the potential 
significance of the irreversibility of radionuclide attachment to smectite colloids observed in the 
ANL waste form corrosion experiments. Irreversibly attached colloids are included in the 
abstracted model as a contribution to the colloid-associated radionuclide concentration. As 
pointed out in 3.8.2.2 the colloids formed from CSNF and DSNF are assumed to have reversibly 
attached radionuclides; this assumption is potentially non-conservative and remains to be 
verified when results from ongoing tests become available. 
Based on the considerations discussed above, this model is appropriate for its intended use. 
3.8.4 Alternative Approaches and Other Views 
The approach described herein for the colloidal radionuclide source term is consistent with what 
was done in the TSPA-VA (DOE 1998b) but is more sophisticated in several ways. The 
treatment for TSPA-SR analysis includes direct consideration of groundwater chemical 
conditions (pH and ionic strength) on stability of waste-form and corrosion-product colloids. 
The effect of ionic strength was considered in the TSPA-VA (DOE 1998b) for groundwater 
colloids, as it is in the TSPA-SR analysis. In TSPA-VA (DOE 1998b), the concentration of 
colloids (Cc) was evaluated from a linear empirical relation with ionic strength of the liquid 
solution. Here, the mass concentration of colloids is not assumed to be constant but varies 
according to groundwater chemical conditions. This approach provides more realism in the 
TSPA-SR analysis calculations. 
In terms of radionuclide uptake, the treatment herein utilizes laboratory results that describe the 
irreversible uptake, or engulfing, of plutonium phases in smectitic waste-form colloids created 
during glass corrosion. In contrast, in the TSPA-VA, the parameter distribution for the fraction 
of radionuclides irreversibly sorbed on colloids was estimated using preliminary information 
from the Benham nuclear test area at the Nevada Test Site. The Benham data showed rapid 
transport of colloid associated plutonium occurred (CRWMS M&O 1998b, p. 6-103). For 
reversible uptake, a similar approach to what was used in the TSPA-VA (DOE 1998b) is used; 
experimental results for Pu and Am sorption by colloidal iron-(hydr)oxides, montmorillonite, 
and silica were used to develop Kd values (CRWMS M&O 1998b, p. 6-101; Lu et al. 1998). 
3.8.4.1 Alternative Models 
An alternative model for waste-form colloid generation was proposed in CRWMS M&O (2000x) 
in which the rate of colloid formation was based on the amount of altered waste form as 
indicated by release of boron for glass and technetium for spent fuel. This model was not used 
because it is based on limited laboratory data. It may, however, be useful in the future.

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To a large extent, the effectiveness of colloids in facilitating contaminant transport is due to their 
very large surface area available for sorption. Depending on the size distribution of colloids in 
the groundwater, the impact of choosing a mass-based Kd, or a surface-area-based Ka, may be 
significant. The greatest variability exists in situations in which an inordinately large number of 
very small colloids exist, which have a high surface-area-to-mass ratio. Based on experimental 
measurements and observations of colloid characteristics in Yucca Mountain groundwater, this 
situation does not exist at Yucca Mountain, and the use of a mass-based Kd is appropriate 
(CRWMS M&O 2000m, Attachment XVI, Section 1.1). 
In the TSPA-VA, a slightly different approach was taken by assuming a constant steady-state 
mass concentration of colloids in groundwater. The steady-state mass concentration was 
embedded in a sorption term referred to as Kc. The approach described herein is more 
comprehensive in that the effect of ionic strength and pH on mass concentration are included. In 
the waste-form area, the Kd approach adopted here will provide more realism by accounting for 
the destabilizing effect of high ionic strength conditions and some pH conditions. The Kc 
approach, however, is well suited for far-field transport, where transients in aqueous chemical 
conditions are not expected. 
3.8.4.2 Issues 
The VA (DOE 1998b, Section 6.5.3.13) acknowledged the need to better define the mechanistic 
basis for plutonium sorption onto colloids, as well as other characteristics associated with these 
colloids. As described in Section 3.8.2.1, an improved mechanistic understanding has been 
accomplished, and has been utilized herein. In particular, research was conducted to evaluate the 
reversibility of plutonium sorption on hematite, goethite, silica, and montmorillonite colloids, 
rates of sorption/desorption, and applicability of the linear isotherm model. The approach taken 
for plutonium sorption was to utilize the relatively large and, therefore, conservative desorption 
Kd in the TSPA model. 
The TSPA peer review panel noted that one of the aspects of repository performance with large 
uncertainties includes actinide transport by colloids and the panel stated that there is no 
convincing way to estimate the type, amounts, or stability of colloids (Budnitz et al. 1999, 
Section II.A and II.G). The approach used is a systematic treatment of the colloid source term 
based on consideration of: (1) the possible types of colloids that could be present or generated, 
(2) modes of radionuclide uptake, and (3) the stability of those colloid types. Screening 
considerations were also made based on near-field colloid transport/retardation behavior, which 
is partly controlled by colloid size, engineered barrier or rock characteristics, colloid surface 
characteristics (including hydrophobicity). 
Because some results from experiments conducted since TSPA-VA (DOE 1998b) on colloidal 
generation on HLW glass were available, a more defensible component of colloidal generation 
and transport has been constructed for TSPA-SR analysis (Section 3.8). A mass-balance model 
for the waste-form colloid component, is used indirectly. Because data for waste-form colloid 
generation rates are based on a few waste types for a relatively short time period (several years), 
it is difficult to develop rate data that are applicable to many thousands of years. However, the 
approach described herein allows tracking of waste-form colloid generation rates, and 
comparison to laboratory observations outside of the TSPA calculation.

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3.9 ISSUES RELATED TO WASTE FORM DEGRADATION 
Technical issues have been raised concerning degradation of the waste form and related topics in 
a number of forums by groups that have project oversight, regulatory oversight, or stakeholder 
interfaces with the YMP. These groups include the NRC, the ACNW, the NWTRB, and peer 
review panels. Raising these issues by the review bodies has resulted in further consideration of 
the issues and, frequently, modifications to project testing and modeling. This section identifies 
issues related to waste form degradation raised by these groups and presents the PMRs approach 
to the issues (Table 3.9-1). 
Table 3.9-1. Key External Issues for the Waste Form Degradation Process Model Report 
Issue Source PMR Approach 
Cladding Credit. Practicality of taking 
performance credit for cladding. 
Comments include: (i) excessive optimism 
in the credit taken in the VA, 
(ii) substantial related uncertainties, 
(iii) quality of data on cladding initial state, 
(iv) lack of industry studies to support 
cladding credit, (v) ability of the cladding to 
remain intact for long periods of time 
under conditions that it was not designed 
for, and (vi) ability of DOE to gather data 
to support related assumptions. 
ACNWa, 
NWTRBb, 
PARPc 
Cladding models have been heavily revised since VA, so 
criticisms of the VA models do not apply to SR models. 
SR models are based on information from various 
sources, including peer-reviewed technical literature, and 
the models account for uncertainty in cladding condition. 
Although the nuclear power industry has not studied 
cladding credit for disposal, that fact is irrelevant because 
the nuclear power industry has no responsibility for 
disposal. Zircaloy has exceptional resistance to a wide 
variety of corrosive environments, so a long lifetime is to 
be expected in the relatively benign environment of a 
repository. DOE has collected a large amount of 
information on as-irradiated cladding and cladding 
degradation mechanisms. See Section 3.4.4 for further 
discussion of this issue. 
Performance of Cladding. Ability to 
sufficiently establish the performance of 
cladding. Questions raised relate to: 
(i) the initial damage and condition of 
cladding, (ii) potentially optimistic or 
undemonstrated assumptions of the 
behavior or performance of cladding, 
(iii) understatement of related 
uncertainties, (iv) insufficient analysis 
related to hydrogen embrittlement of 
Zirconium cladding, and (v) need for 
investigations to identify additional 
potential failure mechanisms. 
NRCd, 
ACNWa, 
PARPc 
The first three items are treated in the discussion of 
cladding credit above. Hydrogen effects have been 
treated in detail (CRWMS M&O 2000r). Literature from the 
nuclear power and chemical industries has been heavily 
reviewed to assure that all potential mechanisms have 
been considered. See Section 3.4.4 for further discussion 
of this issue. 
In-Package Chemistry. The level of 
understanding of and the uncertainty 
related to the chemistry inside of the WP. 
Chemistry affects the degradation of the 
waste form and the ability to support 
cladding credit. 
NWTRBb, 
PARPc 
For TSPA-SR analysis, the Waste Form Degradation 
Model now explicitly contains an In-Package Chemistry 
Component (Section 3.2) to better characterize the 
uncertainty in the degradation of the cladding and waste 
form. See Section 3.2.3 for further discussion of this 
issue.

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Table 3.9-1. Key External Issues for the Waste Form Degradation Process Model Report (Continued) 
Issue Source PMR Approach 
Waste Form Corrosion. Weaknesses 
were noted in the VA spent fuel corrosion 
model related to the adequacy of existing 
data and to the depth of addressing the 
processes that ensue among the WP 
internals following penetration. 
PARPc These VA model and documentation weaknesses were 
addressed in the development of the SR model and 
documentation as discussed in Section 3.3. In particular, 
the mechanistic basis was discussed, a simplified model 
was developed, and model validation was performed. 
The degradation of the cladding and waste matrix is now 
coupled as explained in Section 3.4 and the degradation 
of the waste matrix was also coupled to the in-package 
chemistry to better characterize uncertainty as explained 
in Sections 3.2 and 3.3. 
Formation of Colloids. The need to 
better define the mechanistic basis for 
plutonium sorption onto colloids, as well 
as other characteristics associated with 
these colloids, has been identified. Large 
uncertainties were identified associated 
with actinide transport by colloids. 
NRC,d 
PARPc 
Results from experiments have resulted in an improved 
component of colloidal generation and transport. See 
Section 3.8.4.2 for additional information on this issue. 
Radionuclide Solubility. The need for 
data and additional studies related to 
solubility limit distributions for several key 
radionuclides, including neptunium and 
technetium were identified. 
NRC,d 
PARPc 
Several substantial changes were made in the Dissolved 
Radioisotope Concentration Component to address these 
concerns. See Section 3.7.3 for additional information 
related to this issue. 
Screening of Radionuclides. Thorough 
documentation of the approach used to 
eliminate unimportant radionuclides from 
consideration and to demonstrate the 
potential impacts of not considering the full 
suite of possible radionuclides present. 
NRCd For TSPA-SR analysis a reevaluation of radioisotope 
screening was conducted. See Section 3.1.3 for further 
discussion of this issue. 
Radionuclide Retardation. Failure to 
take credit for radionuclide retardation 
through coprecipitation or sorption by 
secondary alteration phases. 
PARPc TSPA-SR analysis conservatively neglects radioisotope 
retardation through coprecipitation or sorption inside the 
WP. This topic is a FEP and mentioned in Table 2.3-8, 
FEPs Related to the Colloidal Radionuclides 
Concentration Component. 
Natural Analog Studies of High-Level 
Waste Glasses. Proper consideration of 
data on naturally occurring glasses, 
combined with experimental data and 
models on dissolution of high-level waste 
glasses, to demonstrate that long-term 
dissolution behavior under repository 
conditions can be represented by 
extrapolation of results from short-term 
laboratory tests. 
NRCd As stated more fully in discussion of related criteria in 
Chapter 4, the bounding formulation of the HLW 
Degradation Component, discussed in Section 3.6, 
included the consideration of experimental and other 
relevant data, including information from natural analogs. 
Natural analog information is used for corroboration (see 
Section 3.6.2 and Cunnane et al. 1994). 
Consistency of Modeling Assumptions. 
Modeling assumptions should be 
consistent across different process 
models, unless there is a defensible 
technical rationale. 
NRCd The AMRs that document assumptions have been 
subjected to thorough interdisciplinary reviews to help 
ensure consistency among assumptions made in more 
than one document about a given parameter. In addition, 
the PMRs that summarize and integrate the results of the 
AMRs have been subjected to a review by a single review 
team, one of whose main objectives is to identify 
inconsistencies among the PMRs.

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Table 3.9-1. Key External Issues for the Waste Form Degradation Process Model Report (Continued) 
Issue Source PMR Approach 
Importance of Detailed Documentation 
of Assumptions. The need for detailed 
documentation of assumptions used in 
performance assessments to provide 
transparency and credibility of TSPAs. 
NRCd Procedures have been developed that control 
development and documentation of analyses and models 
that are subject to the requirements of the quality 
assurance program (DOE 2000). The QA program 
requires identification and detailed documentation of 
assumptions for both analyses and models (DOE 2000, 
Section 3.2.2, Section 3.2.3, and Supplement III.2.6). 
Implementation of the governing procedures 
fundamentally ensures that analyses and models used for 
performance assessments are transparent and credible. 
Excessive Use of Expert Elicitations. 
Concern that a substantial part of the 
knowledge base rests in expert 
elicitations, e.g., for data on waste form 
degradation. 
PARPc Additional experimental programs in waste form 
degradation have been conducted. The concern has 
been alleviated by additional work in the area and by 
discontinuing the direct use of the expert elicitations. 
NOTES: a ACNW: Advisory Committee on Nuclear Waste 
b NWTRB: Nuclear Waste Technical Review Board 
c PARP: Total System Performance Assessment Peer Review Panel 
d NRC: Nuclear Regulatory Commission

 4-1
4. RELATIONSHIP TO NUCLEAR REGULATORY COMMISSION ISSUE 
RESOLUTION STATUS REPORTS 
4.1 SUMMARY OF THE KEY TECHNICAL ISSUES 
As part of the review of site characterization activities, the Nuclear Regulatory Commission 
(NRC) has undertaken an ongoing review of information on Yucca Mountain Site 
characterization activities to allow early identification and resolution of potential licensing 
issues. The principal means of achieving this goal is through pre-licensing consultation with 
DOE. This approach attempts to reduce the number of, and to better define, issues that may be 
in dispute during the NRC licensing review, by obtaining input and striving for consensus from 
the technical community, interested parties, and other groups on such issues. 
The NRC has focused pre-licensing issue resolution on those topics most critical to the 
post-closure performance of the potential geologic repository. These topics are called Key 
Technical Issues (KTIs). Each KTI is subdivided into a number of subissues. The KTIs are: 
 Activities Related to Development of the EPA Standard 
 Container Lifetime and Source Term 
 Evolution of the Near-Field Environment (ENFE) 
 Igneous Activity 
 Radionuclide Transport 
 Repository Design and Thermal-Mechanical Effects 
 Structural Deformation and Seismicity 
 Thermal Effects on Flow 
 Total System Performance Assessment (TSPA) and Integration 
 Unsaturated Zone and Saturated Zone Flow Under Isothermal Conditions. 
Identifying KTIs, integrating their activities into a risk-informed approach, and evaluating their 
significance for post-closure performance helps ensure that NRCs attention is focused on 
technical uncertainties that will have the greatest affect on the assessment of repository safety. 
Early feedback among all parties is essential to define what is known, what is not known, and 
where additional information is likely to make a significant difference in the understanding of 
future repository safety. The Issue Resolution Status Reports (IRSRs) are the primary 
mechanism that the NRC staff uses to provide feedback to the DOE on the status of the KTI 
subissues. IRSRs focus on NRC acceptance criteria for issue resolution and the status of issue 
resolution, including areas of agreement or when the staff has comment or questions. Open 
meetings and technical exchanges between NRC and DOE provide additional opportunities to 
discuss issue resolution, identify areas of agreement and disagreement and plans to resolve any 
disagreements. 
Each KTI is subdivided into a number of subissues. For most subissues, the NRC staff has 
identified technical acceptance criteria that the NRC may use to evaluate the adequacy of 
information related to the KTIs. The NRC has also identified two cross-cutting programmatic 
criteria that apply to all IRSRs related to the implementation of the Quality Assurance Program 
and the use of expert elicitation.

 4-2
Chapter 4 documents DOEs approach to addressing the acceptance criteria and work performed 
that is related to the criteria. The following sections provide a summary level discussion of the 
related KTIs by subissues and specific NRC acceptance criteria. Table 4.1-1 identifies the 
IRSRs/KTIs related to the WF PMR and tabulates the subissues identified in those IRSRs that 
are addressed in this chapter. 
Table 4.1-1. Issue Resolution Status Report/Key Technical Issues Related to the Waste Form 
Degradation Process Model Report 
NRC KTIs/ IRSRs Subissues 
Container Life and Source Term General Acceptance Criteria 
SUBISSUE 3  The Rate at Which Radionuclides in 
Spent Nuclear Fuel Are Released from the 
Engineered Barrier Subsystem through the 
Oxidation and Dissolution of Spent Fuel 
SUBISSUE 4  The Rate at Which Radionuclides in 
High-Level Waste Glass Are Released from the 
Engineered Barrier Subsystem 
SUBISSUE 5  The Effects of In-Package Criticality 
on Waste Package and Engineered Barrier 
Subsystem Performance 
Evolution of the Near-Field Environment SUBISSUE 3  Effects of Coupled Thermal- 
Hydrologic-Chemical Processes on the Chemical 
Environment for Radionuclide Release 
Data and Model Justification 
Data Uncertainty and Verification 
Model Uncertainty 
Model Verification 
Integration 
Programmatic Criteria 
Total System Performance Assessment and 
Integration 
Programmatic Acceptance Criteria 
SUBISSUE 1  System Description and 
Demonstration of Multiple Barriers 
Transparency and Traceability of the Analysis 
Total System Performance Assessment 
Documentation Style, Structure, and Organization 
Features, Events, and Processes Identification 
and Screening 
Abstraction Methodology 
Data Use and Validity 
Assessment Results 
Code Design and data Flow 
SUBISSUE 2  Scenario Analysis 
Identification of an Initial Set of Processes 
and Events 
Classification of Processes and Events 
Screening of Processes and Events 
Formation of Scenarios 
Screening of Scenario Classes 
SUBISSUE 3  Model Abstraction 
Quantity and Chemistry of Water Contacting 
Waste Packages and Waste Forms 
Radionuclide Release Rates and 
Solubility Limits

 4-3
4.2 RELATION OF THE WASTE FORM DEGRADATION PROCESS MODEL 
REPORT TO THE KEY TECHNICAL ISSUES 
The PMRs address issues and processes that frequently correspond to or overlap those identified 
in the KTIs and IRSRs. Because of their importance, this chapter identifies the KTIs and the 
associated IRSRs and subissues that are related to this PMR and its associated AMRs. 
Table 4.2-1 identifies the specific acceptance criteria that relate to this PMR, describes the 
approach to addressing the criteria, and cross-references sections of the PMR or AMRs for 
additional detail, as appropriate. 
4.2.1 Key Technical Issue: Container Life and Source Term 
The primary issue of the KTI on Container Life and Source Term (CLST) is adequacy of the 
EBS design to provide reasonable assurance that containers will be adequately long-lived and 
that radionuclide releases from the EBS will be sufficiently controlled such that container design 
and packaging of SNF and HLW glass will make a significant contribution to the overall 
repository performance. The related IRSR is focused on the containers and waste forms as the 
primary engineered barriers (NRC 1999a, p. 3). 
The IRSR on CLST (NRC 1999a, p. 4) identifies six subissues important to resolution of the 
KTI. This PMR addresses applicable acceptance criteria of Subissues 3 and 4 as well as the 
general acceptance criteria that the NRC considers applicable to all of the subissues of the IRSR. 
4.2.1.1 General Acceptance Criteria 
The IRSR that addresses CLST identifies nine general acceptance criteria that are applicable to 
all of the CLST subissues (NRC 1999a, pp. 19 to 20) (Table 4.2-1). These criteria deal with 
aspects of data collection, qualification, and verification; documentation of uncertainties; and 
limitations in both data and process models. The Waste Form Degradation PMR and supporting 
AMRs were developed in accordance with project procedures for documenting data, analyses, 
models, and/or computer codes and preparing and reviewing technical reports. The general 
acceptance criteria were implemented as part of the overall quality assurance program and 
implementing procedures and are addressed in Table 4.2-1. 
4.2.1.2 Acceptance Criteria for Subissue 3 
Subissue 3 of the IRSR on CLST deals with the rate at which radionuclides in SNF are released 
from the EBS. Each of the nine acceptance criteria identified in the IRSR on CLST for 
Subissue 3 is related to this PMR (NRC 1999a, pp. 24 to 25). This PMR deals with 
identification of the radionuclides of concern to performance of the repository and identification 
of the source term for release from SNF waste packages. These issues are covered in 
Sections 3.1 through 3.5, 3.7, 3.8 and the AMRs that support them. Acceptance criteria related 
to this subissue and the PMR approach that addresses the acceptance criteria are provided in 
Table 4.2-1.

 4-4
4.2.1.3 Acceptance Criteria for Subissue 4 
Subissue 4 of the IRSR on CLST deals with the rate at which radionuclides in HLW glass are 
released from the EBS. Each of the nine acceptance criteria identified in the IRSR on CLST for 
Subissue 4 is related to this PMR (NRC 1999a, pp. 26 to 27). This PMR deals with 
identification of the radionuclides of concern to performance of the repository and identification 
of the source term for release from HLW glass waste packages and co-disposal waste packages. 
These issues are covered in Sections 3.1, 3.2, 3.6 through 3.8, and the AMRs that support them. 
Acceptance criteria related to this subissue and the PMR approach that addresses the acceptance 
criteria are provided in Table 4.2-1. 
4.2.1.4 Acceptance Criteria for Subissue 5 
Subissue 5 of the IRSR on CLST addresses the effects of in-package criticality on waste package 
and engineered barrier subsystem performance. In-package criticality is not addressed in this 
PMR. However, the related acceptance criteria are addressed in DOEs Disposal Criticality 
Analysis Methodology Topical Report (YMP 1998) and its supporting references. Criticality is 
also mentioned in the Disruptive Events Process Model Report (CRWMS M&O 2000an, p. v). 
4.2.2 Key Technical Issue: Evolution of the Near-Field Environment 
The primary objective of the KTI on the evolution of the ENFE is to assess all aspects of the 
evolution of the near-field geochemical environment that have the potential to affect the 
performance of the potential repository. 
The IRSR on ENFE (NRC 1999b, Section 2.0) identifies five subissues important to resolution 
of the KTI. This PMR addresses applicable acceptance criteria of Subissue 3. 
Acceptance Criteria for Subissue 3Subissue 3 of the IRSR on ENFE deals with the effect of 
coupled thermal-hydrologic-chemical (THC) processes on the chemical environment for 
radionuclide release. The WP corrosion, the quantity and chemistry of fluids contacting waste 
forms, and radionuclide release rates and solubility limits will be affected as a result of the 
evolution of the near-field geochemical environment (NRC 1999b, Section 3.2.3). Subissue 3 of 
the IRSR on ENFE further divides its acceptance criteria into subsections (NRC 1999a, 
Section 4.3.1) as shown in Table 4.2-1. The Waste Form Degradation PMR addresses 
in-package chemistry, solubility limits, formation of colloids, and the various forms of 
degradation of the waste as a result of infiltration of fluids after failure of the waste package. 
These issues are mainly discussed in Section 3.2 and supporting AMRs, but also have less direct 
effect on the other components of the WF degradation model. Acceptance criteria related to this 
subissue and the PMR approach that addresses the acceptance criteria are provided in 
Table 4.2-1. 
4.2.3 Key Technical Issue: Total System Performance Assessment and Integration 
The primary objective of the KTI on Total System Performance Assessment and Integration 
(TSPAI) is to describe an acceptable methodology for conducting assessments of repository 
performance and for using these assessments to demonstrate compliance with the overall 
performance objective and requirements for multiple barriers. The associated IRSR identifies

 4-5
four subissues important to resolution of the KTI (NRC 2000a, p. 4). This PMR addresses 
selected acceptance criteria related to Subissues 2 and 3, as well as the programmatic acceptance 
criteria identified as relevant to all subissues. 
4.2.3.1 Programmatic Acceptance Criteria 
The IRSR identifies two programmatic acceptance criteria as directly applicable to Subissues 2 
and 3 (NRC 2000a, p. 8). As addressed in the table below, the programmatic criteria are integral 
requirements of the quality assurance program and are applied to all quality-affecting activities, 
including development of the PMRs, AMRs, and supporting documents. The approaches to these 
criteria are addressed in Table 4.2-1. 
4.2.3.2 Acceptance Criteria for Subissue 1 
Subissue 1, System Description and Demonstration of Multiple Barriers, addresses the 
demonstration and efficacy of multiple barriers. This includes the identification of natural and 
engineered barriers important to isolation, the capability of these barriers to isolate waste, and the 
identification of processes that may degrade the engineered barriers and thus adversely affect 
performance of the natural barriers (NRC 2000a, p. 4). DOEs TSPA, including scenario 
analysis (Section 4.2.3.3), model abstractions (Section 4.2.3.4) and transparency and traceability 
(this section) will support the demonstration of multiple barriers (NRC 2000a, p. 17). Specific 
technical acceptance criteria have not yet been developed for the demonstration of multiple 
barriers. 
This subissue also addresses the NRCs staff expectation on the contents of DOEs TSPA and 
supporting documents (NRC 2000a, p. 4). It provides criteria to evaluate the transparency and 
traceability of the DOEs TSPA, of the identification and classification of features, events, and 
processes (FEPs), and of the abstractions for TSPA. Finally, this subissue focuses on the 
transparency, traceability and validity of data used to support TSPA and of code design and the 
flow of data in the TSPA (NRC 2000a, pp. 10-17). 
With respect to transparency and traceability, the YMP is committed to improving the 
documentation of the technical analyses that support the TSPA. The development of this PMR, 
and the associated AMRs, focused on improving the transparency and traceability from initial 
data collection through the analysis and incorporation of data and analyses into the process 
model for Waste Form Degradation, and to the abstraction of the process models for use in the 
TSPA. Section 1.3 summarizes the quality assurance status of data and software used in the 
development of this PMR. 
4.2.3.3 Acceptance Criteria for Subissue 2 
Subissue 2, Scenario Analysis, involves the identification of processes and events that could 
affect repository performance and then binning these events and processes into categories. 
A probability of occurrence is assigned to each of these categories of processes and events that 
could result in some processes and events being excluded from the performance assessment. 
Subissue 2 divides its acceptance criteria into five subsections (NRC 2000a, Section 4.2). This

 4-6
PMR addresses the acceptance criteria in each of those subsections (NRC 2000a, Sections 4.2.1 
through 4.2.5) as shown in Table 4.2-1. A systematic method was applied to identify and screen 
FEPs for waste form degradation. Specific information on FEP screening as related to the 
87 primary FEPs related to the Waste Form Degradation PMR is addressed in three AMRs: 57 in 
Miscellaneous Waste-Form FEPs (CRWMS M&O 2000n), 15 in Waste Form Colloid- 
Associated Concentrations Limits: Abstraction and Summary (CRWMS M&O 2000m), and 
16 in Clad Degradation-FEPs Screening Arguments (CRWMS M&O 2000s). One FEP 
(Mutation) appears in two AMRs (CRWMS M&O 2000n, CRWMS M&O 2000m). Acceptance 
criteria related to this subissue and the PMR approach that addresses the acceptance criteria are 
provided in Table 4.2-1. 
Regarding the grouping that addresses formation of scenarios, FEPs related to waste form 
degradation have not been grouped into scenario classes for further screening. Rather, all 
included FEPs have been incorporated in the Waste Form Degradation Model, which is used in 
the nominal scenario that is simulated in the TSPA-SR analysis. 
4.2.3.4 Acceptance Criteria for Subissue 3 
Subissue 3, Model Abstraction, focuses on the information and technical needs related to the 
development of abstracted models for TSPA. This PMR addresses the acceptance criteria of this 
subissue that deal with chemistry of water contacting waste forms (NRC 2000a, 
Section 4.3.1.1.3) and radionuclide release rates and solubility limits (NRC 2000a, 
Section 4.3.1.1.4). It includes documentation of data used to develop conceptual or process 
models for model abstractions, verification of the consistency of the abstractions, and 
explanation of their integration (such as coupling and dependencies) into the TSPA. These 
issues are addressed in the EBS PMR (CRWMS M&O 2000y), Sections 2 and 3 of this report, 
and the AMRs that support them. Acceptance criteria related to this subissue and the PMR 
approach that addresses the acceptance criteria are provided in Table 4.2-1.

 4-7
Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) 
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
IRSR: CONTAINER LIFE AND SOURCE TERM 
GENERAL ACCEPTANCE CRITERIA 
1. The collection and documentation of data, as well as development and 
documentation of analyses, methods, models, and codes, were accomplished 
under approved quality assurance and control procedures and standards. 
Activities associated with the development of this PMR and its related AMRs 
were determined to be subject to the QA program as described in the Quality 
Assurance Requirements and Description (DOE 2000). As such, collection of 
related data, development of analyses and models, and use and validation of 
software are subject to the requirements of procedures developed to 
implement QA program requirements. 
2. Expert elicitations, when used, were conducted and documented in 
accordance with the guidance provided in NUREG-1563 (Kotra et al. 1996) or 
other acceptable approaches. 
Appendix C of the Quality Assurance Requirements and Description 
(DOE 2000) and implementing procedures for expert elicitation were 
developed using the guidance provided in NUREG-1563 (Kotra et al. 1996). 
No expert elicitations are directly associated with the development of the 
Waste Form Degradation PMR and its related AMRs. Only two expert 
elicitations have indirect bearing on the Waste Form Degradation PMR. An 
expert elicitation on waste form degradation (CRWMS M&O 1998c) was 
conducted related to the TSPA-VA (DOE 1998c) and met the requirements of 
the QA program. An informal elicitation to evaluate solubility limits for 
important radionuclides (Wilson et al. 1994) was conducted before the 
provisions of NUREG-1563 were implemented. The results of this elicitation 
were used only to corroborate more recent solubility estimates for the Waste 
Form Degradation PMR. 
3. Sufficient data (field, laboratory, and natural analog) are available to 
adequately define relevant parameters for the models used to evaluate 
performance aspects of the subissues. 
The purpose of the Waste Form Degradation PMR is to summarize the 
technical bases of the parameters of the models. As summarized in Chapter 
3, sufficient degradation data were collected by the project or available in the 
literature to develop defensible bounding components of the Waste Form 
Degradation Model and corresponding parameters of the components. While 
continuing testing and model refinement may narrow the ranges of parameters 
and allow less conservative bounds, the validity of the recommended 
representations described in this PMR is supported by the data and models 
described in the AMRs supporting this document.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-8
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
4. Sensitivity and uncertainty analyses (including consideration of alternative 
conceptual models) were used to determine whether additional data would be 
needed to better define ranges of input parameters. 
For most modeling components within the Waste Form Degradation PMR, a 
detailed process component model of the phenomena was not developed. 
Instead, a simplified (abstraction) component was directly developed from the 
experimental data and information. Hence, sensitivity and uncertainty 
analyses on a detailed process component model were not appropriate and 
are not discussed in the Waste Form Degradation PMR. However, the 
discussion of each waste form degradation model component in Chapter 3 has 
a section titled Confidence/Limitations/Validation" where the current 
confidence of the components is discussed and its suitability for the site 
recommendation justified. Furthermore, sensitivity and uncertainty analyses 
on the components of the Waste Form Degradation Model to determine 
whether additional data are needed are part of the general sensitivity and 
uncertainty analyses of the TSPA associated with the site recommendation. 
5. Parameter values, assumed ranges, test data, probability distributions, and 
bounding assumptions used in the models are technically defensible and can 
reasonably account for known uncertainties. 
An important purpose of the Waste Form Degradation PMR is to summarize 
the technical bases of models addressed in this criterion. The level of 
validation and methods of validation vary from model to model. Sections 3.1 
through 3.8 provide the information suggested by this criterion. Further detail 
is provided within the AMRs. 
6. Mathematical model limitations and uncertainties in modeling were defined 
and documented. 
This criterion is reflected as requirements of the QA program (DOE 2000, 
Section 3.2.2, Section 3.2.3, Supplement III.2.6D); implementing procedures 
specify adequate documentation of assumptions. An important purpose of the 
Waste Form Degradation PMR is to summarize the assumptions, limitations, 
and uncertainties contained in the corresponding AMRs. A subsection in each 
component section in Chapter 3 of this document summarizes model 
limitations. Further discussion can be found in the AMRs cited in this report. 
7. Primary and alternative modeling approaches consistent with available data 
and current scientific understanding were investigated and their results and 
limitations considered in evaluating the subissue. 
Each of the sections of this PMR that describes the components of the Waste 
Form Degradation Model also describes alternative modeling approaches that 
have been considered or suggested. 
8. Model outputs were validated through comparisons with outputs of detailed 
process models, empirical observations, or both. 
Model validation requirements are established in the QA program (DOE 2000, 
Supplement III.2.6). The Waste Form Degradation PMR summarizes the 
current technical basis of model validation. Detailed documentation of model 
validation is included in the appropriate AMRs. 
9. The structure and organization of process and abstracted models were 
found to adequately incorporate important design features, physical 
phenomena, and coupled processes. 
In general, an important purpose of Waste Form Degradation PMR is to 
summarize the technical basis of models including important design features, 
physical phenomena, and coupled processes. Specifically, included/excluded 
FEPs are discussed in three AMRs (CRWMS M&O 2000m, 2000n, and 2000s) 
that support the Waste Form Degradation PMR. Section 2.3 summarizes the 
FEP analysis relevant to this PMR.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-9
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
SUBISSUE 3  THE RATE AT WHICH RADIONUCLIDES IN SPENT NUCLEAR FUEL ARE RELEASED FROM THE 
ENGINEERED BARRIER SUBSYSTEM THROUGH THE OXIDATION AND DISSOLUTION OF SPENT FUEL 
1. DOE has considered all categories of SNF planned for disposal at the 
proposed repository. 
The types of SNF that have been considered for disposal in the potential 
repository are discussed in Section 3.1 of the Waste Form Degradation PMR. 
As discussed in Sections 3.1, 3.3 and 3.5, the majority of radionuclides are 
represented in CSNF while the wide variety of DSNF is considered in the 
inventory and (with the exception of naval SNF) conservatively represented in 
performance by the most rapid release rate component (N-Reactor fuel). 
2. DOE has adequately justified the selection of radionuclides tracked in the 
release models from SNF and their related release parameters. 
With the issuance of draft regulations proposed DOE 10 CFR 63 Interim 
Guidance (Dyer 1999) and 40 CFR 197 (64 FR 46976), the selection of 
radionuclides was reevaluated and is discussed in Section 3.1 of this PMR. As 
discussed further in the supporting Inventory Abstraction AMR (CRWMS 
M&O 2000f) the selection of radionuclides is based on considerations of 
inventory, half-life, mobility, and dose contribution. 
3. DOE has identified the range of environmental conditions to be expected 
inside breached WPs. 
The In-Package Chemistry Component discussed in Section 3.2 was 
specifically added to the Waste Form Degradation Model to capture the range 
of environmental conditions expected inside the WPs. Examples of 
environment ranges considered include fully immersed versus flow through 
models and local chemistries dominated by different WP and WF components. 
This range of potential conditions is based on experimental observations and 
process modeling. EBS testing is currently underway to confirm these 
processes and environmental conditions. 
4. DOE has identified and considered likely processes for SNF degradation 
and the release of radionuclides from the EBS, as follows: dissolution of the 
irradiated UO2 matrix, with the consequent formation of secondary minerals and 
colloids; prompt release of radionuclides; degradation in the dry air 
environment; degradation and failure of fuel cladding; preferential dissolution of 
intermetallics in DOE SNF; and release of radionuclides from the WP 
emplacement drifts. 
Section 3.3 of this PMR is devoted to dissolution of the irradiated UO2 matrix. 
Another entire section, Section 3.4, is devoted to the improved modeling of the 
degradation and failure of fuel cladding. Section 3.4 includes the topics of 
prompt release of radionuclides and degradation of UO2 and cladding in the 
dry air environment (this topic is also a FEP). Another entire section, 
Section 3.5, is devoted to dissolution of DOE SNF. Finally, Section 3.8 
discusses the formation of colloids. The part of this criterion that deals with 
release of radionuclides from the WP emplacement drifts is not discussed in 
the Waste Form Degradation PMR. That criterion is discussed in the EBS 
PMR (CRWMS M&O 2000y).

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-10
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
5. DOE has demonstrated that the numerical models used for SNF degradation 
and radionuclide release from the EBS are adequate representations, including 
consideration of uncertainties, of the expected SNF performance. They are not 
likely to overestimate the actual performance in the repository environment. 
Models in the Waste Form Degradation PMR are regression analyses of 
experimental data at repository conditions (Section 3.3), bounding 
representations of experimental data (Sections 3.5 and 3.8), or assume very 
aggressive degradation to bound uncertainty (Section 3.4). Bounding 
representations of numerical simulations (Section 3.2) explicitly include a 
function to represent uncertainty, define an uncertain distribution, or use 
bounding values for radioisotope solubility (Section 3.7). The models were 
designed to avoid over estimation of performance. 
6. DOE has considered the compatibility of SNF and the internal components 
of the WP, such as the basket materials, in the evaluation of radionuclide 
releases. Specifically, the SNF should not compromise the performance of the 
WP. 
Compatibility of internal components, the SNF, and the WP has been 
considered in selection of materials for the WP and internals (CRWMS 
M&O 2000al, Section 3.3.2). The corrosion of the internal components was 
taken into consideration in the In-Package Chemistry Component model 
summarized in Section 3.2 of the Waste Form Degradation PMR and justified 
in the corresponding AMRs, In-Package Chemistry Abstraction (CRWMS 
M&O 2000g) and Summary of In-Package Chemistry for Waste Forms 
(CRWMS M&O 2000o). 
7. DOE has justified the use of SNF test results not specifically collected for the 
Yucca Mountain site for the environmental conditions expected to prevail after 
breaching of the containers at the Yucca Mountain site. 
In several cases, the Waste Form Degradation PMR uses test results of the 
degradation of SNF not specifically collected for the Yucca Mountain site to 
corroborate the YMP data (e.g., CSNF Matrix Degradation Component, 
Section 3.3). In the case of the CSNF Cladding Degradation Component, 
Section 3.4, YMP uses the extensive data collected over the past 30 years on 
cladding failure mechanisms. This use, however, is evaluated under specific 
QA procedures that address qualification of unqualified data and 
appropriateness of data for their intended use.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-11
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
8. DOE has conducted a consistent, sufficient, and suitable SNF corrosion and 
radionuclide release testing program at the time of the license application 
submittal. In addition, DOE has identified specific plans for further testing to 
reduce any significant area (or areas) of uncertainty as part of the performance 
confirmation program. 
As explained in Sections 3.3 and 3.5, respectively, the foundation of the CSNF 
and DSNF degradation rates for the TSPA-SR analysis is the testing program 
conducted by YMP and NSNFP. A Performance Confirmation Plan (CRWMS 
M&O 2000am) has been developed that establishes the test and analysis 
requirements to confirm, with reasonable assurance, that the performance 
objective for the period after permanent repository closure is met. Postclosure 
performance has been shown to be insensitive to SNF corrosion and 
dissolution for credible ranges in applicable parameters. However, laboratory 
waste form testing has been included in the performance confirmation 
program in compliance with specific regulatory requirements regarding the 
waste forms and the in-package environments. These include tests to confirm 
dissolution rates of waste forms under bounding in-package and repository 
environments. Additionally, SNF cladding has been identified as a potential 
additional enhancement to the defense-in-depth strategy, and therefore, 
cladding degradation tests have also been identified for the pre-emplacement 
period. See Section 5.3.1.8.2 and Appendix G of the Performance 
Confirmation Plan (CRWMS M&O 2000am). 
9. DOE has established an adequate program of monitoring radionuclide 
release from the WP during the performance confirmation period, to assure that 
assumptions and calculations of SNF dissolution and radionuclide release from 
the WP are appropriately substantiated. 
A Performance Confirmation Plan (CRWMS M&O 2000am) has been 
developed that establishes the test and analysis requirements to confirm, with 
reasonable assurance, that the performance objective for the period after 
permanent repository closure is met. Because of the expected long life of the 
waste package, it is not possible to establish a meaningful program for 
monitoring radionuclide release from waste packages. In-drift environments 
will be monitored during the performance confirmation period to ensure no 
waste package breaches occur during the preclosure period. Postclosure 
performance has been shown to be insensitive to SNF corrosion and 
dissolution for credible ranges in applicable parameters. However, laboratory 
waste form testing has been included in the performance confirmation 
program in compliance with specific regulatory requirements regarding the 
waste forms and the in-package environments. These include tests to confirm 
dissolution rates of waste forms under bounding in-package and repository 
environments. Additionally, SNF cladding has been identified as a potential 
additional enhancement to the defense-in-depth strategy, and therefore, 
cladding degradation tests have also been identified for the pre-emplacement 
period. See Sections 5.3.1.8.2 and Appendix G of the Performance 
Confirmation Plan (CRWMS M&O 2000am).

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-12
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
SUBISSUE 4  THE RATE AT WHICH RADIONUCLIDES IN HIGH-LEVEL WASTE GLASS ARE 
RELEASED FROM THE ENGINEERED BARRIER SUBSYSTEM 
1. DOE has taken into account all types of HLW glass planned for disposal at 
the repository. 
Consideration of the several types of HLW to be placed into the potential 
Yucca Mountain is discussed in Section 3.6 of the Waste Form Degradation 
PMR. The model is based on testing of the most representative glass to be 
disposed. Variations in source term from the range of HLW are expected to be 
within the conservative bounds of the recommended representative model. 
2. DOE has adequately justified the selection of radionuclides tracked in the 
release models from HLW glass and their related release parameters. 
After issuance of draft regulations proposed in DOE 10 CFR 63 Interim 
Guidance (Dyer 1999) and 40 CFR 197 (64 FR 46976), the selection of 
radionuclides was reevaluated, as discussed in Section 3.1, formally providing 
justification for the radionuclides and parameters to be tracked in release 
models. Further details are provided in the Inventory Abstraction AMR 
(CRWMS M&O 2000f). 
3. DOE has identified the range of environmental conditions to be expected 
inside breached WPs containing HLW glass and, eventually, certain types of 
SNF as in the codisposal WPs. 
The In-Package Chemistry Component discussed in Section 3.2 was 
specifically added to the Waste Form Degradation Model to capture the range 
of environmental conditions expected inside the WPs. 
4. DOE has identified and considered likely processes for the degradation of 
HLW glass and the release of radionuclides from the EBS (i.e., dissolution of 
the primary phase; formation of secondary minerals and colloids; microbial 
action; and radionuclide releases and transport from the WP emplacement 
drifts). 
Section 3.6 of this PMR is devoted to dissolution of the HLW glass. 
Section 3.8 directly uses experimented data on the formation of colloids from 
HLW. Microbial action is the topic of a FEP (Section 2.3.2.8 FEP 
2.1.10.01.00) that applies both to SNF and HLW degradation. Only release 
and transport of radionuclides from the WP emplacement drifts is not 
discussed in this PMR, since the topic is discussed in the EBS PMR (CRWMS 
M&O 2000y).

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-13
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
5. DOE has demonstrated that the numerical models used for determining the 
rate of dissolution of HLW glass and the rate of radionuclide release from the 
EBS are adequate representations, taking into consideration the associated 
uncertainties of the expected HLW glass performance, and are not likely to 
underestimate the actual rate of degradation of the HLW glass and the 
subsequent rate of release in the repository environment. 
As summarized in Section 3.6 and the associated Defense High Level Waste 
Glass Degradation AMR (CRWMS M&O 2000k), the degradation model is a 
bounding representation of experimental results at different pH values. 
Furthermore, representations of numerical simulations (Section 3.2) explicitly 
include a function to represent uncertainty of the pH. The HLW model was 
designed to avoid under estimation of rate of degradation and release. 
In the discussion of this criterion in Section 5.4.5 of the IRSR (NRC 1999a), 
NRC expressed a concern that, DOE has not considered field data on 
naturally occurring glasses, combined with experimental data and models on 
dissolution of HLW glasses, to demonstrate that long-term dissolution behavior 
under repository conditions can be represented by extrapolation of results 
from short-term laboratory tests. The DOE has considered data on naturally 
occurring glasses and successfully compared the paragenetic sequence 
observed to that found for HLW glass. As summarized in Section 3.6, DOE 
has used a bounding value for a variety of experimental data on dissolution of 
HLW glass to bolster confidence in the prediction of long-term behavior. 
Finally, DOE has been conservative in its use of short-term data for modeling 
of long-term HLW glass dissolution (see Section 3.2 and supporting AMR 
[CRWMS M&O 2000k]). 
6. DOE has assessed the compatibility of HLW glass with internal components 
of the WP in the evaluation of radionuclide release, taking into consideration 
codisposal with DSNF in the same WP. Specifically, HLW glass should not 
compromise the performance of the WP. 
The compatibility of internal components, the HLW, and the WP was 
considered in selection of materials for the WP and internal parts of the WP 
(CRWMS M&O 2000al, Section 3.3.2). Corrosion of the internal components 
was taken into consideration in the In-Package Chemistry Component model 
summarized in Section 3.2 and justified in the corresponding AMRs: 
Bounding chemistries include those dominated by waste forms such as HLW 
glass. 
7. DOE has justified the use of test results for HLW glass that are not 
specifically collected for the Yucca Mountain site for environmental conditions 
expected to prevail after breaching of the containers at the site. 
In several cases, the AMRs supporting the Waste Form Degradation PMR use 
test results of the degradation of HLW not specifically collected for the Yucca 
Mountain site. This use is evaluated under specific QA procedures that 
address tracking of information to be verified, qualification of unqualified data, 
and appropriateness of data for their intended use.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-14
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
8. DOE has conducted a consistent, sufficient, and suitable HLW glass and 
radionuclide release corrosion testing program at the time of the LA submittal. 
In addition, DOE has identified specific plans for further testing to reduce any 
significant area (or areas) of uncertainty as part of the performance confirmation 
program. 
As explained in Section 3.6, the foundation of the HLW degradation rates for 
the TSPA related to the site recommendation is the testing program conducted 
by YMP. A Performance Confirmation Plan (CRWMS M&O 2000am) has 
been developed that establishes the test and analysis requirements to confirm, 
with reasonable assurance, that the performance objective for the period after 
permanent repository closure is met. Postclosure performance has been 
shown to be insensitive to HLW corrosion and dissolution for credible ranges 
in applicable parameters. However, laboratory waste form testing has been 
included in the performance confirmation program in compliance with specific 
regulatory requirements regarding the waste forms and the in-package 
environments. These include tests to confirm dissolution rates of waste forms 
under bounding in-package and repository environments. See Section 
5.3.1.8.2 and Appendix G of the Performance Confirmation Plan (CRWMS 
M&O 2000am). 
9. DOE has established an adequate program of monitoring radionuclide 
release from the WP during the performance confirmation period to assure that 
assumptions and calculations regarding HLW glass dissolution and radionuclide 
release are appropriately substantiated. 
A Performance Confirmation Plan (CRWMS M&O 2000am) has been 
developed that establishes the test and analysis requirements to confirm, with 
reasonable assurance, that the performance objective for the period after 
permanent repository closure is met. Because of the expected long life of the 
waste package, it is not possible to establish a meaningful program for 
monitoring radionuclide release from waste packages. In-drift environments 
will be monitored during the performance confirmation period to ensure no 
waste package breaches occur during the preclosure period. Postclosure 
performance has been shown to be insensitive to HLW corrosion and 
dissolution for credible ranges in applicable parameters. However, laboratory 
waste form testing has been included in the performance confirmation 
program in compliance with specific regulatory requirements regarding the 
waste forms and the in-package environments. These include tests to confirm 
dissolution rates of waste forms under bounding in-package and repository 
environments. See Sections 5.3.1.8.2 and Appendix G of the Performance 
Confirmation Plan (CRWMS M&O 2000am).

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-15
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
SUBISSUE 5  THE EFFECT OF IN-PACKAGE CRITICALITY ON WASTE PACKAGE AND EBS PERFORMANCE 
Subissue 5 addresses the effects of in-package criticality on waste package and engineered barrier subsystem performance. In-package criticality discussions 
are not included in this PMR. However, the related acceptance criteria are addressed in DOEs Disposal Criticality Analysis Methodology Topical Report 
(YMP 1998) and its supporting references. 
IRSR: EVOLUTION OF THE NEAR-FIELD ENVIRONMENT 
SUBISSUE 3  EFFECTS OF COUPLED THERMAL-HYDROLOGIC-CHEMICAL PROCESSES ON THE 
CHEMICAL ENVIRONMENT FOR RADIONUCLIDE RELEASE 
Data and Model Justification 
1. Available data relevant to both temporal and spatial variations in conditions 
affecting coupled THC effects on the chemical environment for radionuclide 
release were considered. 
An important purpose of the Waste Form Degradation PMR is to summarize 
the technical bases of models. This includes consideration of the coupled 
effects on the chemical environment. A conservative range of bounding 
chemistries have been considered as discussed in Section 3.2 and the 
supporting AMRs In-Package Chemistry Abstraction (CRWMS M&O 2000g) 
and Summary of In-Package Chemistry for Waste Forms (CRWMS 
M&O 2000o). Where adequate THC coupled data and models are not 
available, conservative representations are used, such as using the minimum 
pH for CSNF dissolution and the maximum pH for HLW dissolution, each of 
which is the more conservative bound. 
2. DOEs evaluation of coupled THC processes properly considered site 
characteristics in establishing initial and boundary conditions for conceptual 
models and simulations of coupled processes that may affect the chemical 
environment for radionuclide release. 
In general, an important purpose of the Waste Form Degradation PMR is to 
summarize the technical bases of models, which includes the evaluation of 
coupled processes. As more specifically explained in Section 3.2, the In- 
Package Chemistry Component justified use of several initial conditions (e.g., 
use of J-13 water chemistry in a FEP argument) in modeling in-package 
chemistry. However, the Waste Form Degradation PMR is not the sole source 
for initial and boundary conditions. Initial and boundary conditions for 
hydrologic effects and temperature effects are found in the PMR that 
addresses the EBS (CRWMS M&O 2000y). 
3. Sufficient data were collected on 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 THC-coupled processes that affect the chemical environment for 
radionuclide release. 
An important purpose of the Waste Form Degradation PMR is to summarize 
the technical bases of models. As explained throughout this Waste Form 
Degradation PMR, sufficient data were collected by the project or were 
available in the literature to develop defensible bounding models of the 
chemical environment. Section 3.2 of this PMR and its supporting AMRs 
summarize the basis of EBS chemistry, although ongoing EBS testing may 
allow further refinement of these bounded representations.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-16
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
4. A nutrient and energy inventory calculation should be used to determine the 
potential for microbial activity that could impact radionuclide release. 
A nutrient and energy balance was estimated for the repository. However, 
based on arguments for FEPs related to microbial activity (see Section 2.3), 
the influence of microbial activity on radionuclide release was screened out 
and, thus, not considered further as a process within the repository. 
5. Should microbial activity be sufficient to potentially affect the chemical 
environment for radionuclide release, then the time-history of temperature, 
humidity, and dripping should be used to constrain the probability for microbial 
effects, such as production of organic by-products that act as complexing 
ligands for actinides and microbial-enhanced dissolution of the HLW glass form. 
Based on arguments for FEPs related to microbial activity, microbial activity 
was screened out and, thus, not further considered as a process within the 
repository. The screening (see Sections 2.3.2.7 and 2.3.2.8), as summarized 
in FEPs 2.1.10.01.00 and 2.1.09.18.00 and 2.1.09.13.00 is based on limited 
nutrient availability limiting biological activity and the offsetting beneficial effect 
of microbial activity increasing colloid size and increasing filtration. 
6. Sensitivity and uncertainty analyses (including consideration of alternative 
conceptual models) were used to determine whether additional new data are 
needed to better define ranges of input parameters. 
In the case of the In-Package Chemistry Component and the solubility of 
neptunium, americium and uranium, a detailed process model was developed 
and parameter values were varied across a wide range. The numerical results 
were then used directly through a regression analysis to develop a simple 
empirical relationship. These models are summarized in Sections 3.2 and 
3.7 of the Waste Form Degradation PMR and justified in the corresponding 
AMRs, In-Package Chemistry Abstraction (CRWMS M&O 2000g), Summary of 
In-Package Chemistry for Waste Forms (CRWMS M&O 2000o), and Summary 
of Dissolved Concentration Limits (CRWMS M&O 2000l). As explained in 
Chapter 1, for most other modeling components within the Waste Form 
Degradation PMR, a detailed process component model of the phenomena 
was not developed. Rather, a simplified component (abstraction) was directly 
developed from the experimental data and information. Hence, sensitivity and 
uncertainty analyses on a detailed process component model were not 
appropriate and are not discussed in the Waste Form Degradation PMR. 
Instead, sensitivity and uncertainty analyses on the simplified components of 
the Waste Form Degradation Model to determine whether additional data are 
needed as part of the general sensitivity and uncertainty analyses of the TSPA 
related to the site recommendation and discussed in its accompanying 
documentation.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-17
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
7. If the testing program for coupled THC processes on the chemical 
environment for radionuclide release from the EBS is not complete at the time 
of license application, or if sensitivity and uncertainty analyses indicate 
additional data are needed, DOE has identified specific plans to acquire the 
necessary information as part of the performance confirmation program. 
Testing and model refinement for coupled THC processes is ongoing and will 
be complete or sufficiently bounded to support licensing arguments at the time 
of the license application. 
A Performance Confirmation Plan (CRWMS M&O 2000am) has been 
developed that establishes the test and analysis requirements to confirm, with 
reasonable assurance, that the performance objective for the period after 
permanent repository closure is met. Coupled processes and their implications 
for radionuclide release will be measured at several emplacement drift 
locations across the repository horizon from nearby observation drifts, in 
addition to specific tests under simulated postclosure conditions. Waste form 
testing during the pre-emplacement and monitoring periods is also identified 
under reasonably bounding chemical environments to confirm alteration and 
dissolution characteristics of HLW glass and SNF waste forms. See sections 
5.3.1.5, 5.3.1.6, 5.3.1.8, and 5.3.2, as well as Appendix G of the Performance 
Confirmation Plan (CRWMS M&O 2000am). 
Data Uncertainty and Verification 
1. Reasonable or conservative ranges of parameters or functional relations 
were used to determine effects of coupled THC processes on the chemical 
environment for radionuclide release. Parameter values, assumed ranges, 
probability distributions, and bounding assumptions are technically defensible 
and reasonably account for uncertainties. 
Models in the Waste Form Degradation PMR are regression analyses of 
experimental data at repository conditions (Section 3.3), bounding 
representations of experimental data (Sections 3.5 and 3.8), or very 
aggressive assumptions of degradation to bound uncertainty (Section 3.4). 
Bounding representations of numerical simulations (Section 3.2) explicitly 
include a function to represent uncertainty, define an uncertain distribution, or 
use bounding values for radioisotope solubility (Section 3.7). The bounded, or 
most aggressive conditions are determined from coupled THC calculations. 
2. Uncertainty in data due to both temporal and spatial variations in conditions 
affecting coupled THC effects on the chemical environment for radionuclide 
release was considered. 
The In-Package Chemistry Component discussed in Section 3.2 uses the 
available data to couple temporal thermal effects (waste temperature), 
temporal hydrologic effects (seepage into the package), and temporal 
chemical effects (degradation rates of steel, aluminum, HLW, SNF) to evaluate 
the chemical environment inside the WP. Although the conceptual model of a 
fully saturated WP did not assume spatial variations within one package, 
spatial variations in temperature were considered. Spatial discretization 
across the repository and temporal discretization of the simulation is not the 
topic of the Waste Form Degradation PMR; rather, justification of the temporal 
and spatial discretization is discussed in the TSPA-SR analysis report (under 
development).

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-18
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
3. DOEs evaluation of coupled THC processes properly considered 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 THC 
coupled processes that affect the chemical environment for radionuclide 
release. 
The In-Package Chemistry Component (Section 3.2) justified use of several 
initial conditions (e.g., use of J-13 water chemistry in a FEP argument) in 
modeling in-package chemistry. However, the Waste Form Degradation PMR 
is not the sole source for initial and boundary conditions. Initial and boundary 
conditions for hydrologic effects and temperature effects are found in the PMR 
related to the EBS (CRWMS M&O 2000y). 
4. The initial conditions, boundary conditions, and computational domain used 
in sensitivity analyses involving coupled THC effects on the chemical 
environment for radionuclide release were consistent with available data. 
The In-Package Chemistry Component (Section 3.2) justified use of several 
initial conditions (e.g., use of J-13 water chemistry in a FEP argument) in 
modeling in-package chemistry. However, the Waste Form Degradation PMR 
is not the sole source for initial and boundary conditions. Initial and boundary 
conditions for hydrologic effects and temperature effects are found in the PMR 
related to the EBS (CRWMS M&O 2000y). 
5. DOEs performance confirmation program should assess whether the natural 
system and engineered materials are functioning as intended and anticipated 
with regard to coupled THC effects on the chemical environment for 
radionuclide release from the EBS. 
A Performance Confirmation Plan (CRWMS M&O 2000am) has been 
developed that establishes the test and analysis requirements to confirm, with 
reasonable assurance, that the performance objective for the period after 
permanent repository closure is met. Coupled processes and their implications 
for radionuclide release will be measured at several emplacement drift 
locations across the repository horizon from nearby observation drifts, in 
addition to specific tests under simulated postclosure conditions. Waste form 
testing during the pre-emplacement and monitoring periods is also identified 
under reasonably bounding chemical environments to confirm alteration and 
dissolution characteristics of HLW glass and SNF waste forms. See sections 
5.3.1.5, 5.3.1.6, 5.3.1.8, and 5.3.2, as well as Appendix G of the Performance 
Confirmation Plan (CRWMS M&O 2000am). 
Model Uncertainty 
1. Appropriate models, tests, and analyses were used that are sensitive to the 
THC couplings under consideration for both natural and engineering systems as 
described in the following examples. The effects of THC coupled processes 
that may occur in the natural setting or due to interactions with engineered 
materials or their alteration products include: (i) thermal-hydrologic effects on 
gas and water chemistry; (ii) hydrothermally driven geochemical reactions, such 
as zeolitization of volcanic glass; (iii) dehydration of hydrous phases liberating 
moisture; (iv) effects of microbial processes; and (v) changes in water chemistry 
that may result from interactions between cementitious, or WP, materials and 
groundwater, which, in turn, may affect the chemical environment for 
radionuclide release. 
The In-Package Chemistry Component (Section 3.2) uses the available data 
to couple temporal thermal effects (waste temperature), temporal hydrologic 
effects (seepage into the package), and temporal chemical effects 
(degradation rates of steel, aluminum, HLW, SNF) to evaluate the chemical 
environment inside the WP. Hydrothermally driven geochemical processes 
and zeolitization of volcanic glass (item ii) and dehydration of tuff (item iii) 
occur in the near-field environment; they are outside the scope of this PMR. 
Based on arguments found in the FEPs discussion, microbial activity (item iv) 
was screened out (see Section 2.3). Interactions of waters exiting the WP with 
invert and structural material (item v) are found in the EBS PMR (CRWMS 
M&O 2000y).

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-19
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
2. Alternative modeling approaches consistent with available data and current 
scientific understanding were investigated, and their results and limitations were 
appropriately considered. 
Each of the sections describing the components of the Waste Form 
Degradation Model (Sections 3.3, 3.5, 3.6) of this PMR describes alternative 
modeling approaches that were considered. 
3. DOE provided a reasonable description of the mathematical models included 
in its analyses of coupled THC effects on the chemical environment for 
radionuclide release. The description should include a discussion of alternative 
modeling approaches not considered in its final analysis and the limitations and 
uncertainties of the chosen model. 
Thorough descriptions of models are included in the Waste Form Degradation 
PMR and related AMRs. Additionally, the quality assurance program and 
implementing procedures require that analyses, models, and calculations 
provide adequate documentation of assumptions (DOE 2000, Section 3.2.2, 
Section 3.2.3, and Supplement III.2.6). Procedure AP-3.10Q (Attachment I, 
item 6) addresses discussion, as applicable, of any alternate methods or 
models that were not used and the rationale for not selecting them. 
Model Verification 
1. The mathematical models for coupled THC effects on the chemical 
environment for radionuclide release are consistent with conceptual models 
based on inferences about the near-field environment, field data and natural 
alteration observed at the site, and expected engineered materials. 
Model validation requirements are established in the quality assurance 
program (DOE 2000, Supplement III.2.6). The Waste Form Degradation PMR 
summarizes the current technical basis of the CSNF Matrix Degradation 
Component (Section 3.3), the CSNF Cladding Degradation Component, 
(Section 3.4), the HLW Degradation Component (Section 3.6), and the 
Dissolved Radioisotope Concentration Component (Section 3.7), which are all 
functions of temperature and the chemical effects evaluated in the In-Package 
Chemistry Component discussed in Section 3.2. Furthermore, the In-Package 
Chemistry Component is a function of the influx of water (hydrology) into the 
WP. The justification of and confidence in the components are discussed in 
sections titled Confidence/Limitations/ Validation. 
2. DOE appropriately adopted accepted and well-documented procedures to 
construct and test the numerical models used to simulate coupled THC effects 
on the chemical environment for radionuclide release. 
An important purpose of the Waste Form Degradation PMR is to summarize 
the assumptions, limitations, and uncertainties of the waste form degradation 
model. More importantly, the QA procedures for the analyses, models, and 
calculations require adequate documentation of methods used to construct 
models. The Waste Form Degradation PMR summarizes the current technical 
basis of the CSNF Matrix Degradation Component (Section 3.3), the CSNF 
Cladding Degradation Component, (Section 3.4), the HLW Degradation 
Component (Section 3.6), and the Dissolved Radioisotope Concentration 
Component (Section 3.7), which all are a function of temperature and the 
chemical effects evaluated in the In-Package Chemistry Component discussed 
in Section 3.2. The validation of the components are discussed in sections 
titled Confidence/Limitations/Validation.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-20
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
3. Abstracted models for coupled THC effects on the chemical environment for 
radionuclide release were based on the same assumptions and approximations 
shown to be appropriate for closely analogous natural or experimental systems. 
Abstracted model results were verified through comparison to outputs of 
detailed process models and empirical observations. Abstracted model results 
are compared with different mathematical models to judge robustness of 
results. 
For most modeling components within the Waste Form Degradation PMR, a 
detailed process component model of the phenomena was not developed. 
Rather a simplified (abstraction) component was directly developed from the 
experimental observations and information. For the In-Package Chemistry 
Component (Section 3.2), a detailed process model was developed and then 
the numerical results used directly through regression to develop a simple 
empirical relationship, as summarized in Chapter 3 and justified in the 
corresponding AMRs, In-Package Chemistry Abstraction (CRWMS 
M&O 2000g) and Summary of In-Package Chemistry for Waste Forms 
(CRWMS M&O 2000o). Other views and alternative models are discussed in 
each section of Chapter 3 as appropriate. 
Integration 
1. DOE has considered the relevant features, events, and processes. The 
abstracted models adequately incorporated important design features; physical 
phenomena and couplings; and used consistent and appropriate assumptions 
throughout. 
Specifically included/excluded FEPs are discussed in three AMRs that support 
the Waste Form Degradation PMR, and many of these are discussed in the 
Waste Form Degradation PMR itself. Section 2.3 summarizes the FEP 
screening relevant to this PMR. 
2. Models reasonably accounted for known temporal and spatial variations in 
conditions affecting coupled THC effects on the chemical environment for 
radionuclide release. 
The In-Package Chemistry Component (Section 3.2) uses the available data 
to couple temporal thermal effects (waste temperature), temporal hydrologic 
effects (seepage into the package), and temporal chemical effects 
(degradation rates of steel, aluminum, HLW, SNF) to evaluate the chemical 
environment inside the WP. 
3. Not all THC couplings may be determined to be important to performance, 
and DOE may adopt assumptions to simplify performance assessment 
analyses. If potentially important couplings are neglected, DOE should provide 
a technical basis for doing so. The technical basis can include activities, such 
as independent modeling, laboratory or field data, or sensitivity studies. 
Specifically included/excluded FEPs are discussed in AMRs that support the 
Waste Form Degradation PMR, and many of these are discussed in the Waste 
Form Degradation PMR itself. Section 2.3 summarizes the FEP screening 
relevant to this PMR. Section 3.2 summarizes the coupled process analysis 
describing chemical conditions in the waste package, and how this is 
abstracted into conservative bounds for waste form modeling. 
4. Where simplifications for modeling coupled THC effects on the chemical 
environment for radionuclide release were used for performance assessment 
analyses instead of detailed process models, the bases used for modeling 
assumptions and approximations were documented and justified. 
The QA procedures for analyses, models, and calculations require adequate 
documentation of modeling assumptions and approximations used to construct 
models. Bases used for modeling assumptions and approximations are welldocumented 
in supporting AMRs.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-21
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
Programmatic 
1. Data and models were collected, developed, and documented under 
acceptable QA procedures. 
Activities associated with development of this PMR and its related AMRs were 
determined to be subject to the QA program as described in the Quality 
Assurance Requirements and Description (DOE 2000). As such, collection of 
related data, development of analyses, calculations, and models, and use and 
validation of software are subject to the requirements of procedures developed 
to implement quality assurance program requirements. 
2. Deficiency reports concerning data quality on issues related to coupled THC 
effects on the chemical environment for radionuclide release were closed. 
Activities associated with deficiencies and associated corrective action are 
subject to the QA program as described in the Quality Assurance 
Requirements and Description (DOE 2000). Deficiencies are identified, 
tracked, resolved, and closed based on implementing procedures. While data 
quality issues have been well documented in deficiency documents, the 
corrective action process assures effective resolution. 
3. If used, expert elicitations were conducted and documented in accordance 
with the guidance in NUREG-1563 (Kotra et al. 1996) or other acceptable 
approaches. 
Appendix C of the Quality Assurance Requirements and Description 
(DOE 2000) and implementing procedures for expert elicitation were 
developed using the guidance provided in NUREG-1563 (Kotra et al 1996). No 
expert elicitations are directly associated with the development of the Waste 
Form Degradation PMR and its related AMRs. Only two expert elicitations 
have indirect bearing on the Waste Form Degradation PMR. An expert 
elicitation on waste form degradation (CRWMS M&O 1998c) was conducted 
related to the TSPA-VA and met the requirements of the QA program. An 
informal elicitation to evaluate solubility limits for important radionuclides 
(Wilson et al. 1994) was conducted before the provisions of NUREG-1563 
(Kotra et al. 1996) were implemented. The results of this elicitation were used 
only to corroborate more recent solubility estimates for the Waste Form 
Degradation PMR.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-22
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
IRSR: TOTAL SYSTEM PERFORMANCE ASSESSMENT AND INTEGRATION 
Programmatic 
1. The collection, documentation, and development of data, models, and/or 
computer codes have been performed under acceptable quality assurance (QA) 
procedures, or if the data, models and/or computer codes were not subject to 
an acceptable QA procedure, they have been appropriately qualified. 
Activities associated with development of this PMR and its related AMRs were 
determined to be subject to the quality assurance program as described in the 
Quality Assurance Requirements and Description (DOE 2000). As such, 
collection of related data, development of analyses and models, and use and 
validation of software are subject to the requirements of procedures developed 
to implement quality assurance program requirements. The QA program 
(DOE 2000) addresses use of data, models, and/or codes not subject to 
development under a QA program, and these provisions were applied in 
accordance with related implementing procedures. Detailed documentation of 
data, models and/or computer codes is in the AMRs, which this PMR 
summarizes. 
2. Formal expert elicitations can be used to support data synthesis and model 
development for DOEs TSPA, provided that the elicitations are conducted and 
documented under acceptable procedures. 
Appendix C of the Quality Assurance Requirements and Description 
(DOE 2000) and implementing procedures for expert elicitation were 
developed using the guidance provided in NUREG-1563 (Kotra et al. 1996). 
No expert elicitations are directly associated with the development of the 
Waste Form Degradation PMR and its related AMRs. Only two expert 
elicitations have indirect bearing on the Waste Form Degradation PMR. An 
expert elicitation on waste form degradation (CRWMS M&O 1998c) was 
conducted related to the TSPA-VA and met the requirements of the QA 
program. An informal elicitation to evaluate solubility limits for important 
radionuclides (Wilson et al. 1994) was conducted before the provisions of 
NUREG-1563 (Kotra et al. 1996) were implemented. The results of this 
elicitation were used only to corroborate more recent solubility estimates for 
the Waste Form Degradation PMR. 
SUBISSUE 1  System Description and Demonstration of Multiple Barriers 
Transparency and Traceability of the Analysis 
Total System Performance Assessment Documentation Style, Structure, and Organization 
1. Documents and reports are complete, clear, and consistent. The Waste Form Degradation PMR was carefully structured to be complete, 
clear, and consistent. Reviews of the draft document included checks for 
completeness, clarity and consistency. 
2. Information is amply cross-referenced. The Waste Form Degradation PMR contains ample references to data 
sources, codes, assumptions, and conclusions.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-23
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
Features, Events, and Processes Identification and Screening 
1. The screening process by which FEPs were included or excluded from the 
TSPA is fully described. 
Section 2.3 of this PMR summarizes included or excluded FEPs including the 
rationale for the decisions. 
2. Relationships between relevant FEPs are fully described. Section 2.3 of this PMR describes the relationship between FEPs. The 
miscellaneous waste form FEPs AMR (CRWMS M&O 2000n), cladding FEPs 
AMR (CRWMS M&O 2000s), and colloid summary AMR (CRWMS M&O 
2000m) provide additional documentation including the TSPA disposition of 
FEPs, IRSR issues relevant to specific FEPs, and analysis and discussion on 
specific FEPs. 
Abstraction Methodology 
1. The levels and method(s) of abstraction are described starting from 
assumptions defining the scope of the assessment down to assumptions 
concerning specific processes and the validity of given data. 
For each model in the Waste Form Degradation PMR, descriptions are 
provided of process models and, if the models are abstracted, descriptions of 
the abstractions of the models are provided. The description includes a 
summary of data and assumptions used to construct models. The supporting 
AMRs describing the models and the abstracted models provide additional 
details regarding data and assumptions. 
2. A mapping (e.g., a road map diagram, a traceability matrix, a crossreference 
matrix) is provided to show what conceptual features (e.g., patterns of 
volcanic events) and processes are represented in the abstracted models, and 
by what algorithms. 
The Waste Form Degradation PMR and supporting AMRs provide descriptions 
of the basis for the decisions and assumptions that were made during the 
abstraction process. Each major section of Chapter 3 contains figures showing 
the abstracted models. In addition, most major sections of Chapter 3 contain 
figures showing features of the conceptual models. 
3. An explicit discussion of uncertainty is provided to identify which issues and 
factors are of most concern or are key sources of disagreement among experts. 
The Waste Form Degradation PMR provides a discussion of uncertainties and 
limitations for the major process models included in the report. The supporting 
AMRs describing the abstracted models provide additional details regarding 
uncertainties and limitations. 
Data Use and Validity 
1. The pedigree of data from laboratory tests, natural analogs, and the site is 
clearly identified. 
Section 1.3 and Chapter 3 of this PMR summarize the quality assurance 
status of the data and software used in the component models. 
2. Input parameter development and basis for their selection is described. The Waste Form Degradation PMR discusses input parameter development 
and the basis for using the parameters. The supporting AMRs describing the 
models provide additional details regarding input parameter development and 
the basis for input selection.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-24
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
3. A thorough description of the method used to identify performance 
confirmation program parameters [has been developed]. 
The Performance Confirmation Plan (CRWMS M&O 2000am) specifically 
addresses the methodology for identifying and selecting parameters that are 
important to performance based upon TSPA sensitivity analyses and the 
repository safety strategy. Methods used to collect information for each 
parameter will be described by the performance confirmation plan or relevant 
supporting documents to support the license application. Performance 
confirmation test selection and rationale is also described in the plan based 
upon the significance of the parameter being measured, and the ability of the 
test to distinguish construction, emplacement, or time dependent changes in 
the parameter significant to performance. 
Assessment Results 
1. PA results (i.e., the peak expected annual dose within the compliance 
period) can be traced back to applicable analyses that identify the FEPs, 
assumptions, input parameters, and models in the PA. 
The TSPA-SR summarizes features, processes, conceptual models, and their 
implementation into the TSPA. This discussion will be based in part on 
information provided by the Waste Form Degradation PMR. 
2. The PA results include a presentation of intermediate results that provide 
insight into the assessment (e.g., results of intermediate calculations of the 
behavior of individual barriers) 
TSPA-SR provides performance analysis results for the total system and will 
include intermediate results for the components of the system. 
Code Design and Data Flow 
1. The flow of information (input and output) between the various modules is 
clearly described. 
TSPA-SR provides a description of information flow between component 
models including couplings between information and data, conceptual and 
process-level models, and abstracted models. 
2. Supporting documentation (e.g., user's manuals, design documents) clearly 
describes code structure and relationships between modules. 
TSPA-SR describes the TSPA code and provides a reference to supporting 
documentation such as the users guide. 
SUBISSUE 2 - SCENARIO ANALYSIS 
Identification of an Initial Set of Processes and Events 
1. DOE has identified a comprehensive list of processes and events that: 
(i) are present or might occur in the Yucca Mountain region, and (ii) includes 
those processes and events that have the potential to influence repository 
performance. 
Section 2.3 provides a list of the processes and events applicable to this PMR. 
It summarizes the screening arguments and dispositions for the FEPs. The 
process for developing and screening FEPs was formalized for TSPA-SR 
analysis. An overview of the process adopted by DOE is described in Total 
System Performance Assessment-Site Recommendation Methods and 
Assumptions (CRWMS M&O 1999f). Over 1,786 FEPs were identified that are 
applicable to the Yucca Mountain region. One hundred fourteen are related in 
some way to waste form degradation (e.g., criticality), of these, 86 were 
specifically assigned to the Waste Form Degradation PMR.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-25
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
Classification of Processes and Events 
1. DOE has provided adequate documentation identifying how its initial list of 
processes and events has been grouped into categories. 
Section 2.3 of this PMR describes the manner that included FEPs were 
incorporated into the Waste Form Degradation Model. Section 2.3 also 
summarizes justification for screening arguments and TSPA dispositions. For 
comprehensiveness, traceability is maintained in the FEPs database from the 
secondary to the related primary FEPs. 
2. Categorization of processes and events is compatible with the use of 
categories during the screening of processes and events. 
The NRC staff will review the categorization of processes and events as 
described in the various PMRs. Section 2.3 of this PMR describe the features, 
events, and processes applicable to this PMR. The AMRs supporting this 
section, Miscellaneous Waste-Form FEPs (CRWMS M&O 2000n) Waste Form 
Colloid-Associated Concentrations Limits: Abstraction and Summary 
(CRWMS M&O 2000m), and Clad Degradation-FEPs Screening Arguments 
AMR (CRWMS M&O 2000s), provide documentation and justification for 
screening arguments and TSPA dispositions. Documentation is maintained of 
all mapping of FEPs into primary and secondary categories. The PMRs and 
AMRs describe the categorization of processes and events in sufficient detail 
to determine that events are not narrowly defined and that the categorization 
of processes and events is compatible with the use of categories during the 
screening of processes and events. 
Screening of Processes and Events 
1. Categories of processes and events that are not credible for the Yucca 
Mountain repository because of waste characteristics, repository design, or site 
characteristics are identified and sufficient justification is provided for DOEs 
conclusions. 
The arguments in the AMRs containing FEPs include a statement of the 
screening decision for each FEP. Justification is provided for each excluded 
FEP, including the criterion on which it was excluded and the technical basis 
for the screening argument. 
2. The probability assigned to each category of processes and events not 
screened based on criterion 1 or 2 is consistent with the site information, well 
documented, and appropriately considers uncertainty. 
Any probability estimates for FEPs related to waste form degradation are 
generally based on rational arguments as to feasibility of the FEP consistent 
with site information that considers uncertainty. 
3. DOE has demonstrated that processes and events screened from the 
performance assessment on the basis of their probability of occurrence, have a 
probability of less than one chance in 10,000 of occurring over 10,000 years. 
In the three AMRs that address waste form FEPs (CRWMS M&O 2000m, 
2000n, and 2000s), justification is provided for each excluded FEP, including 
the criterion on which it was excluded and the technical basis for the screening 
argument. The probability assigned to a FEP may be one of the screening 
criteria but were only excluded solely based on this criterion if it could be 
argued to have a probability of occurrence of less than 10-8/year. 
4. DOE has demonstrated that categories of processes and events omitted from 
the performance assessment on the basis that their omission would not 
significantly change the calculated expected annual dose, do not significantly 
change the calculated expected annual dose. 
All of the three AMRs that address waste form FEPs provide documentation 
and justification for screening arguments and TSPA disposition. For omitted 
categories, documentation includes the criteria on which it was excluded and 
the technical basis for the screening argument.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-26
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
Formation of Scenarios 
1. DOE has provided adequate documentation identifying: (i) whether 
processes and events have been addressed through consequence model 
abstraction or scenario analysis and (ii) how the remaining categories of 
processes and events have been combined into scenario classes. 
FEPs that have not been excluded are identified as either expected FEPs or 
disruptive FEPs. Expected FEPs have been included in the TSPA-SR 
analysis nominal scenario simulated in the TSPA-SR analysis. 
2. The set of scenario classes is mutually exclusive and complete. Section 2.3 of this PMR describe the features, events, and processes in this 
PMR. The AMRs supporting this section, Miscellaneous Waste-Form FEPs, 
(CRWMS M&O 2000n) Waste Form Colloid-Associated Concentrations Limits: 
Abstraction and Summary (CRWMS M&O 2000m), and Clad Degradation- 
FEPs Screening Arguments (CRWMS M&O 2000s), provide documentation 
and justification for screening arguments and TSPA dispositions. No specific 
scenarios were constructed for the Waste Form Degradation PMR; however, 
taken together, the entire set of PMRs will provide NRC staff with sufficient 
documentation to evaluate whether the set of scenario classes developed is 
mutually exclusive and complete and whether expected FEPs are addressed 
through model abstraction or through incorporation into scenarios. 
Screening of Scenario Classes 
1. Scenario classes that are not credible for the Yucca Mountain repository 
because of waste characteristics, repository design, or site characteristics 
individually or in combinationare identified, and sufficient justification is 
provided for DOEs conclusions. 
In general, scenarios have been screened using the same regulatory, 
probability, and consequence criteria used for screening individual FEPs. 
Documentation of this process includes identification of any scenarios that 
have been screened from the analysis and the technical basis for that 
screening decision. FEPs related to waste form degradation have not been 
grouped into scenario classes for further screening. Rather, the FEPs have 
been included in the nominal scenario simulated in the TSPA-SR analysis. 
2. The probability assigned to each scenario class is consistent with site 
information, well documented, and appropriately considers uncertainty. 
FEPs related to waste form degradation have not been grouped into scenario 
classes for further screening. Rather, the FEPs have been included in the 
nominal scenario simulated in the TSPA-SR analysis, and have appropriately 
considered uncertainty. 
3. Scenario classes that combine categories of processes and events may be 
screened from the performance assessment on the basis of their probability of 
occurrence, provided: (i) the probability used for screening the scenario class is 
defined from combinations of initiating processes and events, and (ii) DOE has 
demonstrated that they have a probability of less than one chance in 10,000 of 
occurring over 10,000 years. 
FEPs related to waste form degradation have not been grouped into scenario 
classes for further screening. Rather, the FEPs have been included in the 
nominal scenario simulated in the TSPA-SR analysis. Thus, scenario 
screening based on probability of occurrence is not applicable to FEPs related 
to this PMR. Inclusion in the nominal TSPA-SR simulation provides an 
alternative approach that achieves the same objective.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-27
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
4. Scenario classes may be omitted from the performance assessment on the 
basis that their omission would not significantly change the calculated expected 
annual dose, provided DOE has demonstrated that excluded categories of 
processes and events would not significantly change the calculated expected 
annual dose. 
FEPs related to waste form degradation have not been grouped into scenario 
classes for further screening. Rather, the FEPs have been included in the 
nominal scenario simulated in the TSPA-SR analysis. Thus omission of 
scenario classes from the TSPA based on significance to the calculated 
expected dose is not applicable to FEPs related to this PMR. 
SUBISSUE 3  MODEL ABSTRACTION 
Quantity and Chemistry of Water Contacting Waste Packages and Waste Forms 
1. Sufficient data (field, laboratory, and/or natural analog data) are available to 
adequately define relevant parameters and conceptual models necessary for 
developing the quantity and chemistry of water contacting WPs and waste 
forms abstracted in TSPA. Where adequate data do not exist, other information 
sources such as expert elicitation have been appropriately incorporated into the 
TSPA. 
An important purpose of Waste Form Degradation PMR is to summarize the 
technical bases of models and corresponding parameters. As explained 
throughout this Waste Form Degradation PMR, sufficient data were collected 
by the project or were available in the literature to develop defensible 
bounding models of the chemical environment. The specific aspects of the 
water chemistry are discussed in Section 3.2 and corresponding AMRs, In- 
Package Chemistry Abstraction (CRWMS M&O 2000g) and Summary of In- 
Package Chemistry for Waste Forms (CRWMS M&O 2000o). 
2. Parameter values, assumed ranges, probability distributions, and bounding 
assumptions used in the quantity and chemistry of water contacting WPs and 
waste forms abstraction, such as the pH, carbonate concentration, chloride 
concentration, and amount of water flowing in and out of the breached WP, are 
technically defensible and reasonably account for uncertainties and variability. 
Variations in water chemistry and three effects on in-package chemistry are 
discussed in Section 3.2. In addition, as described in Section 3.4, a specific 
model component was added to the total system performance assessment for 
site recommendation to reasonably account for uncertainties and variabilities 
in chemistry of water contacting the waste forms. The quantity of water 
entering the WP was evaluated in the PMR on the EBS (CRWMS M&O 
2000y). 
3. Alternative modeling approaches consistent with available data and current 
scientific understanding are investigated and results and limitations 
appropriately factored into the quantity and chemistry of water contacting WPs 
and waste forms abstraction. 
Each of the sections describing the components of the Waste Form 
Degradation Model of the Waste Form Degradation PMR describes alternative 
modeling approaches that could have been used.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-28
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
4. Output of quantity and chemistry of water contacting WPs and waste forms 
abstraction are verified through comparison to output of detailed process 
models and/or empirical observations (laboratory testings or natural analogs, or 
both). 
The Waste Form Degradation PMR summarizes the current technical basis of 
models. For most modeling components within the Waste Form Degradation 
PMR, a detailed process component model of the phenomena was not 
developed. Rather, a simplified (abstraction) component was directly 
developed from the experimental observations and information. For the In- 
Package Chemistry Component, a detailed process model was developed, 
and then the numerical results used directly through regression to develop a 
simple empirical relationship, as summarized in Section 3.2 and justified in the 
corresponding AMRs, In-Package Chemistry Abstraction (CRWMS 
M&O 2000g) and Summary of In-Package Chemistry for Waste Forms 
(CRWMS M&O 2000o). 
5. Important design features, physical phenomena and couplings, and 
consistent and appropriate assumptions are incorporated into the quantity and 
chemistry of water contacting WPs and waste forms abstraction. 
Specifically included/excluded FEPs relevant to the quantity and chemistry of 
water are discussed in AMRs that support the Waste Form Degradation PMR, 
and many of these are discussed in the Waste Form Degradation PMR. 
Section 2.3 summarizes the FEP screening relevant to this PMR. Section 3.2 
summarizes the coupled process analysis describing chemical conditions in 
the waste package and how it is abstracted into conservative bounds for waste 
form modeling. 
Radionuclide Release Rates and Solubility Limits 
1. Sufficient data (field, laboratory, and/or natural analog data) are available to 
adequately define relevant parameters and conceptual models necessary for 
developing radionuclide release rates and solubility limits abstracted in TSPA. 
Where adequate data do not exist, other information sources such as expert 
elicitation have been appropriately incorporated into the TSPA. 
As explained throughout this Waste Form Degradation PMR, sufficient data 
were collected by the project or available in the literature to develop defensible 
bounding models of the chemical environment. Specific aspects of the 
radioisotope release rates are discussed in Sections 3.3, 3.4, 3.5, and 3.6 and 
corresponding AMRs. Specific aspects of the solubility limits are discussed in 
Section 3.7 and the corresponding AMRs, Summary of Dissolved 
Concentration Limits (CRWMS M&O 2000l) and Pure Phase Solubility 
Limits-LANL (CRWMS M&O 2000v). 
2. Parameter values, assumed ranges, probability distributions, and bounding 
assumptions used in the radionuclide release rates and solubility limits 
abstraction, such as the pH, temperature, and amount of liquid contacting the 
waste forms, are technically defensible and reasonably account for 
uncertainties and variabilities. 
An important purpose of Waste Form Degradation PMR is to summarize the 
technical bases of model parameters. Specific aspects of the radioisotope 
release rates are discussed in Sections 3.3, 3.4., 3.5, and 3.6 and the 
corresponding AMRs. Specific aspects of the solubility limits are discussed in 
Section 3.7 and the corresponding AMRs. To better characterize the 
uncertainty in the radionuclide release rates and solubility limits, the 
corresponding modeling components were directly coupled with In-Package 
Chemistry Component (Section 3.2). In turn, the In-Package Chemistry 
Component uses the available data to couple temporal thermal effects (waste 
temperature), temporal hydrologic effects (seepage into the package), and 
temporal chemical effects (degradation rates of steel, aluminum, HLW, SNF) 
to evaluate the chemical environment inside the WP.

Table 4.2-1. Issue Resolution Status Reports, Subissues, Acceptance Criteria, and Process Model Report Approach 
(NRC 1999a, 1999b, 2000a) (Continued) 
 4-29
NRC Technical Acceptance Criteria PMR Approach and Section Reference 
3. Alternative waste form dissolution and radionuclide release modeling 
approaches consistent with available data and current scientific understanding 
are investigated and results and limitations appropriately factored into the 
radionuclide release rates and solubility limits abstraction. 
Each of the sections describing the components of the Waste Form 
Degradation Model of the Waste Form Degradation PMR describes alternative 
modeling approaches that were considered. The alternative modeling 
approaches for the radioisotope release rates and solubility limits are 
discussed in Sections 3.3, 3.4, 3.5, 3.6, and 3.7. 
4. Radionuclide release rates and solubility limits abstraction outputs is 
supported by comparison to outputs of detailed process models or empirical 
observations (field, laboratory, and natural analog data). 
The Waste Form Degradation PMR summarizes the current technical basis of 
models. For most modeling components within the Waste Form Degradation 
PMR, a detailed process component model of the phenomena was not 
developed. Rather, a simplified (abstraction) component was directly 
developed from the experimental observations and information. For 
radionuclides of neptunium, americium, and uranium and the directly related 
In-Package Chemistry Component (Section 3.2), a detailed process model 
was developed and then the numerical results used directly through 
regression to develop a simple empirical relationship, as summarized in 
Sections 3.2 and 3.7. Although material analog data were not used directly, 
the paragenetic sequence observed in experiments mirrors natural analogues. 
5. Important design features, physical phenomena and couplings, and 
consistent and appropriate assumptions are incorporated into the radionuclide 
release rates and solubility limits abstraction. 
Specifically included/excluded FEPs are discussed in AMRs that support the 
Waste Form Degradation PMR and many of these are discussed in the Waste 
Form Degradation PMR. Section 2.3 summarizes the FEP screening relevant 
to this PMR. Section 3.2 summarizes the coupled process analysis describing 
chemical conditions in the waste package, and how this is abstracted into 
conservative bounds for waste form modeling.

 4-30
INTENTIONALLY LEFT BLANK

 5-1
5. SUMMARY AND CONCLUSIONS 
The Waste Form Degradation Process Model Report (Waste Form Degradation PMR) is one of 
nine PMRs that have the shared objective of describing the technical information used in the 
TSPA-SR that was conducted to evaluate the postclosure performance of a potential monitored 
geologic repository at Yucca Mountain. The TSPA-SR will be used in the preparation of a 
document for a Secretarial decision on whether to recommend the Yucca Mountain site for 
development as a repository. The Waste Form Degradation PMR summarizes the results of 
investigations on the degradation of radioactive spent nuclear fuel and high-level waste. 
The performance of the potential Yucca Mountain repository will depend on the rate of 
radionuclide release from the waste packages after the containers are eventually breached. After 
breach, water, or water vapor may enter the packages and contact exposed waste forms. The 
waste forms will degrade slowly and release radionuclides, as solutes and colloids, into the 
contacting groundwater as a result of a broad range of processes and events. This Waste Form 
Degradation PMR, together with the supporting AMRs, describes the approach and scientific 
basis for modeling. In order to ensure that all relevant processes were included, a detailed 
analysis of FEPs believed to be important in controlling the rate of radionuclide release was 
conducted. 
The decision to include or exclude each of the waste form FEPs was based on criteria in 
Section 114(e) of the proposed DOE 10 CFR Part 63 Interim Guidance (Dyer 1999). If the 
screening decision is "Include", the FEP is considered either in the nominal scenario (i.e., the 
scenario that contains all expected FEPs and no disruptive FEPs); in the disruptive scenario 
(i.e., any scenario that contains all expected FEPs and one or more disruptive FEPs); or in the 
human intrusion scenario. If the screening decision is "Exclude", the basis for the exclusion, 
such as low probability or low consequence, is detailed. 
The 87 waste form FEPs assigned to the Waste Form Degradation PMR have been evaluated by 
subject-matter experts and discussed in three different AMRs. Fifty-seven of the waste form 
FEPs are discussed in Miscellaneous Waste-Form FEPs (CRWMS M&O 2000n). Fifteen are 
discussed in Waste Form Colloid-Associated Concentrations Limits: Abstraction and Summary 
(CRWMS M&O 2000m). Sixteen are discussed in Clad DegradationFEPs Screening 
Arguments AMR (CRWMS M&O 2000s). One FEP (Mutation) appears in two AMRs 
(CRWMS M&O 2000n, CRWMS M&O 2000m). 
The culmination of these investigations on degradation of the waste forms was the construction 
of the Waste Form Degradation Model to predict the dissolved or colloidal radionuclides 
available for transport in the TSPA analysis for SR (TSPA-SR). The Waste Form Degradation 
Model consists of eight major modeling/analysis components: (1) Radioisotope Inventory, 
(2) In-Package Chemistry, (3) Commercial Spent Nuclear Fuel (CSNF) Degradation, (4) CSNF 
Cladding Degradation, (5) DOE Spent Nuclear Fuel (DSNF) Degradation, (6) High-Level 
Waste (HLW) Degradation, (7) Radioisotope Dissolved Concentration (solubility), and 
(8) Radioisotope Colloidal Concentration. These eight components are generally connected 
sequentially, starting with the radioisotope inventory as input and ending with projected 
radioisotope dissolved and colloidal concentrations. The summary and conclusions reached in 
each of the eight components are given below.

 5-2
Radioisotope Inventory ComponentThe function of the Radioisotope Inventory Component is 
to estimate the inventory of those radionuclides most important to human dose. This component 
uses updated values for the inventory based on internal documents for CSNF, reports from the 
National Spent Nuclear Fuel Program (NSNFP) for DSNF, and the Environmental Impact 
Statement (EIS) for HLW. An updated screening was conducted, which resulted in 
27 radionuclides being identified as important (24 based on human dose and 3 mandated by the 
groundwater protection requirements of the EPAs proposed standard 40 CFR 197 
(64 FR 46976). The relative importance of individual radionuclides for human inhalation and 
ingestion doses was evaluated for several waste types, time frames, and release scenarios. In this 
evaluation, the effects of inventory abundance, radionuclide longevity, element solubility, and 
element transport affinity were considered. 
In-Package Chemistry ComponentThe function of the In-package Chemistry Model 
Component is to estimate the fluid chemistry inside the waste package over time after the initial 
breach of the waste package. The water chemistry parameters in the model include hydronium 
ion concentration, dissolved partial pressures of carbon dioxide and oxygen, ionic strength, and 
fluoride and chloride ion concentrations. This chemistry is used by the several other model 
components (see Figure 1.5-3) because the rate of degradation of the matrix of waste, the 
resulting dissolved concentration of radionuclides, the stability of any colloids, and degradation 
of cladding are all dependent on the chemistry of fluids within the WP. The in-package 
chemistry component in the TSPA-SR couples the seepage rate of water into the package with 
the degradation of the steel, aluminum, SNF, and HLW inside the package to evaluate the key 
water chemistry parameters. These results influence degradation of the CSNF cladding and 
matrix, HLW degradation, radionuclide solubility, and colloid availability and stability. The 
degradation of the CSNF cladding and matrix, and HLW, in turn, influence the in-package 
chemistry component. 
CSNF Degradation ComponentThe main function of the CSNF Degradation Model 
Component is to determine the rate of degradation of the CSNF matrix as a function of 
temperature and water chemistry (specifically, pH and partial pressures of O2 and CO2). This 
degradation rate is then directly used by the Cladding Degradation Model Component 
(Section 3.4) to determine the rate at which the CSNF cladding splits open and exposes more of 
the fuel matrix. In addition, the CSNF degradation model examines the distribution of 
radionuclides within the fuel and establishes a gap fraction for the more volatile radionuclides. 
Under oxidizing conditions, in the presence of water or water vapor, UO2 in CSNF is not stable 
and alters. Alteration of the UO2 matrix can liberate radionuclides important to human dose. The 
CSNF matrix degradation component uses two linear regression equations, based on pH, the 
partial pressures of O2 and CO2, and temperature (T), to evaluate matrix degradation over time; 
one equation is applicable for pH less than or equal to 7 and the other is applicable for pH greater 
than 7. The regression variables used (pH, PCO2, and PO2) are coupled to in-package chemistry to 
account for uncertainty. 
The CSNF matrix degradation component is based on experimental measurement of the 
dissolution rate of a number of fresh and spent fuels. These materials were examined under both 
saturated and unsaturated conditions using flow-through reactors as well as static, batch, and drip 
reactors. These tests also give empirical information on secondary phase production, colloids,

 5-3
and effective solubility limits for the more insoluble radionuclides. The secondary phases are 
similar to those observed in the corrosion of natural uraninite deposits, indicating that the 
experimental results are indeed relevant to the long-term behavior. 
CSNF Cladding Degradation ComponentThis component evaluates degradation of the 
cladding and is coupled to the CSNF Matrix Degradation and In-Package Chemistry components 
in the TSPA-SR. The degradation of CSNF cladding is assumed to proceed through two distinct 
steps: cladding failure (usually by small perforations), and progressive exposure of the fuel 
matrix. 
Initial breach of the cladding may occur because (1) the cladding fails within the reactor or 
during storage or transportation, (2) an earthquake severely shakes and severs the rods, (3) the 
cladding fails from localized corrosion (Figure 3.4-2), or (4) the cladding fails from creep or 
stress corrosion cracking. While other mechanisms of initiating cladding perforations, such as 
rock fall or DHC, were explored, they were screened out based on low probability. 
After the cladding has initially been breached, it is assumed to unzip because the fuel volume 
increases during alteration of the UO2, (i.e., the alteration of the UO2 to secondary phases of 
uranium is assumed to cause enough pressure due to volume expansion to burst the cladding 
from within) (Figure 3.4-2). This mechanism for increasing the exposed surface area of the 
matrix is sensitive to environmental conditions such as temperature. The anticipated temperature 
of the fuel matrix is not high enough, nor does it occur for a long enough period, to cause 
unzipping in a dry environment, so the dry unzipping is not included. Once the Zircaloy 
cladding has been perforated, unzipping in a wet environment does not occur in time periods of 
40 years, based on observed behavior within storage pools at reactors. However, because 
unzipping in a wet environment could not be entirely ruled out, and because complete exposure 
of the matrix bounds diffusive releases of radionuclides through the perforation, it is 
conservatively assumed that clad unzipping in a wet environment can occur. The rate of wet 
unzipping was conservatively estimated by relating it to the movement of the alteration front. 
DSNF Degradation Model ComponentThis component determines the rate of degradation of 
the DSNF waste category and of the immobilized plutonium ceramic waste. The degradation 
behavior of DSNF (excluding the naval SNF) will be represented by the metallic uranium SNF 
from N-Reactor. The naval SNF degradation behavior will be represented by that of the CSNF. 
TSPA-SR will use a degradation rate and a corresponding effective surface area that bounds the 
experimental data on N-Reactor fuel collected over a range of conditions in the last few years. In 
the TSPA-SR, the DSNF degradation component uses a constant, bounding degradation rate of 
N-Reactor SNF to bound all the DSNF waste types except naval SNF. However, the 
radioisotope inventory of the DSNF components is the weighted mass average of all waste types. 
HLW Degradation ComponentThis component provides a conservative model for calculating 
the rate of degradation of borosilicate glass for the range of conditions (immersion, humid air, 
and dripping water) to which it may be exposed after the waste packages fail. For TSPA-SR, 
this component uses bounds on parameters of a phenomenological model to develop a simplified 
(Arrhenius-type) rate equation of degradation that is dependent only upon pH and temperature.

 5-4
The model parameters account for the pH, temperature, surface area, and the combined effects of 
glass composition and solution composition on the rate of glass corrosion. Conservative 
estimates of the values for the model parameters are provided based on experimental data. 
Consistent with the conceptual model for in-package chemistry, degradation of borosilicate glass 
is conservatively assumed to occur as if the glass were fully immersed, although it is expected 
that much of the glass will be exposed to humid air or dripping water conditions. 
Dissolved Radioisotope Concentration ComponentThis component evaluates the dissolved 
concentration of radionuclides (or parents of radionuclides) that are important to human dose, as 
determined by the radioisotope screening described in the inventory section (Section 3.1). In the 
dissolved radioisotope concentration component, the solubilities of important radionuclides were 
reevaluated: three radioisotope solubilities were abstracted as a direct function of in-package 
chemistry (and three more radionuclides equated to one of these); four radioisotope solubilities 
were defined by a probability distribution; and all others were set at bounding values based on 
results of the process modeling of the in-package chemistry. 
The dissolved concentration limits calculation builds upon three primary feeds: (1) estimates of 
in-package fluid major element composition (pH, Eh, ionic strength, carbonate levels), 
(2) measured (and estimated) thermodynamic parameters describing the stabilities of aqueous 
species and solid radioisotope phases, and (3) a determination of the likely solubility-controlling 
phases for the specific radionuclides of concern. In nature, the controlling phase may either be a 
pure radionuclide solid phase with the radioisotope as the dominant element, or a solid phase 
with trace amounts of the radionuclide as can occur with coprecipitation. For TSPA-SR, the 
pure phases were chosen because, in general, they yield higher dissolved concentrations. Where 
insufficient information can be gleaned from field observations or experimental results, it is 
conservatively assumed that the most amorphous and hydrated (hence, most soluble) oxide of the 
particular radioelement forms. 
A systematic review of thermodynamic data and controlling phases has been performed for a 
large range of chemical conditions. When uncertainties were encountered, choices were made 
that would result in higher predicted solubilities. Inherent limitations within the databases can 
lead to an uncertainty, up to a factor of 2, when the ionic strength exceeds about 0.7 mol/L. 
However, this uncertainty is small relative to other uncertainties within the system. 
Colloidal Radioisotope Concentration ComponentThe function of this component is to 
calculate the concentration of colloid-associated radionuclides that may be transported from the 
waste package. A conceptualization was developed that directly used experimental results. The 
conceptualization identified the availability and the stability of three categories of colloids: 
(1) existing colloids in the groundwater, (2) colloids generated during degradation of the waste, 
and (3) colloids generated during degradation of the disposal container. 
Colloid transport is potentially important for radionuclide elements that have low solubility and 
can be entrained in, or sorbed onto, waste form, engineered barrier, or geologic barrier materials 
that form colloidal particle substrates. Of these radionuclides, only those that are a major part of 
the waste inventory and have potentially large dose conversion factors are of potential 
importance to the performance of the disposal system. Considering these screening criteria, 
plutonium is the dominant radionuclide. Americium is also considered for the TSPA-SR.

 5-5
Radionuclides are attached to colloids as a result of two types of processes: irreversible and 
reversible attachment. For waste form colloids, radionuclides can be incorporated into the 
substrate material before it is suspended as colloids. All colloid types may sorb radionuclides to 
form pseudocolloids, depending on the affinity of the colloid mineral substrate for a dissolved 
radionuclide. The contributions of each colloid type are summed to produce the mobile colloid 
source term for each important radionuclide. 
The abstractions are based on laboratory results from waste form corrosion testing and testing of 
adsorption and desorption properties of Pu and Am on clay and iron-(hydr)oxide colloids. To the 
extent that the laboratory tests and test conditions represent anticipated repository conditions, the 
abstraction is valid for calculating the colloid-associated radionuclide concentrations and colloid 
mass concentrations. 
Input Confirmation-This document may be affected by technical product input information that 
requires confirmation. Any changes to the document that may occur as a result of completing 
the confirmation activities will be reflected in subsequent revisions. The status of the input 
information quality may be confirmed by review of the Document Input Reference System 
database.

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 6-1
6. REFERENCES 
6.1 DOCUMENTS CITED 
Barnard, R.W. and Dockery, H.A., eds. 1991. Nominal Configuration Hydrogeologic 
Parameters and Calculational Results. Volume 1 of Technical Summary of the Performance 
Assessment Calculational Exercises for 1990 (PACE-90). SAND90-2726. Albuquerque, New 
Mexico: Sandia National Laboratories. ACC: NNA.19910523.0001. 
Barnard, R.W.; Wilson, M.L.; Dockery, H.A.; Gauthier, J.H.; Kaplan, P.G.; Eaton, R.R.; 
Bingham, F.W.; and Robey, T.H. 1992. TSPA 1991: An Initial Total-System Performance 
Assessment for Yucca Mountain. SAND91-2795. Albuquerque, New Mexico: Sandia National 
Laboratories. ACC: NNA.19920630.0033. 
Budnitz, B.; Ewing, R.C.; Moeller, D.W.; Payer, J.; Whipple, C.; and Witherspoon, P.A. 1999. 
Peer Review of the Total System Performance Assessment-Viability Assessment Final Report. 
Las Vegas, Nevada: Total System Performance Assessment Peer Review Panel. ACC: 
MOL.19990317.0328. 
Center for Nuclear Waste Regulatory Analyses 1998. Total-System Performance Assessment 
(TPA) Version 3.2 Code: Module Descriptions and User's Guide. Draft. San Antonio, Texas: 
Center for Nuclear Waste Regulatory Analyses. TIC: 248267. 
Chung, H.M.; Yaggee, F.L.; and Kassner, T.F. 1987. "Fracture Behavior and Microstructural 
Characteristics of Irradiated Zircaloy Cladding." Zirconium in the Nuclear Industry, Seventh 
International Symposium Sponsored by ASTM Committee B-10 on Reactive and Refractory 
Metals, Strasbourg, France, 24-27 June 1985. Adamson, R.B. and Van Swam, L.F.P., eds. Pages 
775-801. Philadelphia, Pennsylvania: American Society for Testing and Materials. TIC: 238255. 
CRWMS M&O 1994. Total System Performance Assessment - 1993: An Evaluation of the 
Potential Yucca Mountain Repository. B00000000-01717-2200-00099 REV 01. Las Vegas, 
Nevada: CRWMS M&O. ACC: NNA.19940406.0158. 
CRWMS M&O 1995. Total System Performance Assessment - 1995: An Evaluation of the 
Potential Yucca Mountain Repository. B00000000-01717-2200-00136 REV 01. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.19960724.0188. 
CRWMS M&O 1996a. Description of Performance Allocation. B00000000-01717-2200-00177 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19970116.0052. 
CRWMS M&O 1996b. Total System Performance Assessment of a Geologic Repository 
Containing Plutonium Waste Forms. A00000000-01717-5705-00011 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.19970109.0229. 
CRWMS M&O 1997a. Total System Performance Assessment Sensitivity Studies of U.S. 
Department of Energy Spent Nuclear Fuel. A00000000-01717-5705-00017 REV 01. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.19980618.0474.

 6-2
CRWMS M&O 1997b. Constraints on Solubility-Limited Neptunium Concentrations for Use in 
Performance Assessment Analyses. B00000000-01717-2200-00191 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.19980213.0484. 
CRWMS M&O 1998a. Software Qualification Report (SQR) Addendum to Existing LLNL 
Document UCRL-MA-110662 PT IV: Implementation of a Solid-Centered Flow-Through Mode 
for EQ6 Version 7.2B. CSCI: UCRL-MA-110662 V 7.2b. SCR: LSCR198. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.19990920.0169. 
CRWMS M&O 1998b. "Waste Form Degradation, Radionuclide Mobilization, and Transport 
Through the Engineered Barrier System." Chapter 6 of Total System Performance Assessment- 
Viability Assessment (TSPA-VA) Analyses Technical Basis Document. B00000000-01717-4301- 
00006 REV 01. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19981008.0006. 
CRWMS M&O 1998c. Waste Form Degradation and Radionuclide Mobilization Expert 
Elicitation Project. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19980804.0099. 
CRWMS M&O 1999a. Not used. 
CRWMS M&O 1999b. Not used. 
CRWMS M&O 1999c. Addendum to: EQ6 Computer Program for Theoretical Manual, Users 
Guide, & Related Documentation. Software Change Request (SCR) LSCR198. UCRL-MA- 
110662 PT IV. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19990305.0112. 
CRWMS M&O 1999d. 1999 Design Basis Waste Input Report for Commercial Spent Nuclear 
Fuel. B00000000-01717-5700-00041 REV 00. Washington, D.C.: CRWMS M&O. ACC: 
MOV.19991006.0003. 
CRWMS M&O 1999e. Draft Analysis/Modeling Report - Department of Energy Spent Fuel 
Performance Assessment. Input Transmittal WP-WP-99408.T. Las Vegas, Nevada: CRWMS 
M&O. ACC: MOL.19991209.0105. 
CRWMS M&O 1999f. Total System Performance Assessment-Site Recommendation Methods 
and Assumptions. TDR-MGR-MD-000001 REV 01 ICN 01. Las Vegas, Nevada: CRWMS 
M&O. ACC: MOL.19991104.0570. 
CRWMS M&O 2000a. Repository Safety Strategy: Plan to Prepare the Postclosure Safety Case 
to Support Yucca Mountain Site Recommendation and Licensing Considerations. TDR-WIS-RL- 
000001 REV 03. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000119.0189. 
CRWMS M&O 2000b. Waste Form Analysis & Models. Activity Evaluation, June 13, 2000. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000615.0387. 
CRWMS M&O 2000c. Waste Form Degradation Process Model Report. Development Plan 
TDP-WIS-MD-000031 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000202.0180.

 6-3
CRWMS M&O 2000d. Waste Package Degradation Process Model Report. TDR-WIS-MD- 
000002 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000328.0322. 
CRWMS M&O 2000e. Not used. 
CRWMS M&O 2000f. Inventory Abstraction. ANL-WIS-MD-000006 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.20000414.0643. 
CRWMS M&O 2000g. In-Package Chemistry Abstraction. ANL-EBS-MD-000037 REV 00. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000418.0818. 
CRWMS M&O 2000h. CSNF Waste Form Degradation: Summary Abstraction. ANL-EBS-MD- 
000015 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000121.0161. 
CRWMS M&O 2000i. Clad Degradation - Summary and Abstraction. ANL-WIS-MD-000007 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000602.0055. 
CRWMS M&O 2000j. DSNF and Other Waste Form Degradation Abstraction. ANL-WIS-MD- 
000004 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000223.0502. 
CRWMS M&O 2000k. Defense High Level Waste Glass Degradation. ANL-EBS-MD-000016 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000329.1183. 
CRWMS M&O 2000l. Summary of Dissolved Concentration Limits. ANL-WIS-MD-000010 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000525.0372. 
CRWMS M&O 2000m. Waste Form Colloid-Associated Concentrations Limits: Abstraction and 
Summary. ANL-WIS-MD-000012 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000525.0397. 
CRWMS M&O 2000n. Miscellaneous Waste-Form FEPs. ANL-WIS-MD-000009 REV 00. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000526.0339. 
CRWMS M&O 2000o. Summary of In-Package Chemistry for Waste Forms. ANL-EBS-MD- 
000050 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000217.0217. 
CRWMS M&O 2000p. Initial Cladding Condition. ANL-EBS-MD-000048 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.20000523.0150. 
CRWMS M&O 2000q. Not used. 
CRWMS M&O 2000r. Hydride-Related Degradation of SNF Cladding Under Repository 
Conditions. ANL-EBS-MD-000011 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000319.0048. 
CRWMS M&O 2000s. Clad Degradation - FEPs Screening Arguments. ANL-WIS-MD-000008 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000525.0378.

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CRWMS M&O 2000t. Clad Degradation-Wet Unzipping. ANL-EBS-MD-000014 REV 00. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000502.0398. 
CRWMS M&O 2000u. Clad Degradation - Dry Unzipping. ANL-EBS-MD-000013 REV 00. 
Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000503.0200. 
CRWMS M&O 2000v. Pure Phase Solubility Limits - LANL. ANL-EBS-MD-000017 REV 00. 
Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000504.0311. 
CRWMS M&O 2000w. Secondary Uranium-Phase Paragenesis and Incorporation of 
Radionuclides into Secondary Phases. ANL-EBS-MD-000019 REV 00. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.20000414.0644. 
CRWMS M&O 2000x. Colloid-Associated Radionuclide Concentration Limits: ANL. ANLEBS-
MD-000020 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000329.1187. 
CRWMS M&O 2000y. Engineered Barrier System Degradation, Flow, and Transport Process 
Model Report. TDR-EBS-MD-000006 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000324.0558. 
CRWMS M&O 2000z. Near-Field Environment Process Model Report. TDR-NBS-MD-000001 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000421.0034. 
CRWMS M&O 2000aa. Evaluation of Codisposal Viability for UZrH (TRIGA) DOE-Owned 
Fuel. TDR-EDC-NU-000001 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000207.0689. 
CRWMS M&O 2000ab. Evaluation of Codisposal Viability for HEU Oxide (Shippingport PWR) 
DOE-Owned Fuel. TDR-EDC-NU-000003 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000227.0240. 
CRWMS M&O 2000ac. Waste Package Related Impacts of Plutonium Disposition Waste Forms 
in a Geologic Repository. TDR-EBS-MD-000003 REV 01. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20000202.0170. 
CRWMS M&O 2000ad. Near-Field Accumulation of Fissile Material from Waste Packages 
Containing Plutonium Disposition Waste Forms. Input Transmittal WP-WP-00025.T. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000125.0608. 
CRWMS M&O 2000ae. DOE and Commercial Waste Package Inventory: Various Input 
Scenarios for Design. Input Transmittal WP-RSO-00023.Ta. Las Vegas, Nevada: CRWMS 
M&O. ACC: MOL.20000403.0095. 
CRWMS M&O 2000af. Drift-Scale Coupled Processes (DST and THC Seepage) Models. MDLNBS-
HS-000001 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19990721.0523.

 6-5
CRWMS M&O 2000ag. Clad Degradation - Local Corrosion of Zirconium and Its Alloys Under 
Repository Conditions. ANL-EBS-MD-000012 REV 00. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20000405.0479. 
CRWMS M&O 2000ah. Rock Fall on Drip Shield. CAL-EDS-ME-000001 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.20000509.0276. 
CRWMS M&O 2000ai. Abstraction of Drift-Scale Coupled Processes. ANL-NBS-HS-000029 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000525.0371. 
CRWMS M&O 2000aj. Waste Package and DOE Canister Inventory. Input Transmittal RSOSSR-
99360.T. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000202.0002. 
CRWMS M&O 2000ak. Revised Grams Per Package for Use in TSPA-SR. Input Transmittal 
00306.T. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000628.0043. 
CRWMS M&O 2000al. Waste Package Internal Materials Selection Report. B00000000-01717- 
2200-00226 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000209.0299. 
CRWMS M&O 2000am. Performance Confirmation Plan. TDR-PCS-SE-000001 REV 01 ICN 
01. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000601.0196. 
CRWMS M&O 2000an. Disruptive Events Process Model Report. TDR-NBS-MD-000002 REV 
00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000504.0295. 
CRWMS M&O 2000ao. Waste Package Design Sensitivity Report. TDR-EBS-MD-000008 REV 
00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000518.0179. 
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236934.

 6-10
Peehs, M. 1998. Assessment of Dry Storage Performance of Spent LWR Fuel Assemblies with 
Increasing Burn-Up. Erlangen, Germany: Bereich Energieerzeugung. TIC: 245171. 
Perez, J.M., Jr. and Westsik, J.H., Jr. 1981. "Effects of Cracks on Glass Leaching." Nuclear and 
Chemical Waste Management, 2, 165-168. New York, New York: Pergamon Press. TIC: 
246072. 
Pescatore, C. and Cowgill, M. 1994. Temperature Limit Determination for the Inert Dry Storage 
of Spent Nuclear Fuel. EPRI TR-103949. Palo Alto, California: Electric Power Research 
Institute. TIC: 102933. 
Prindle, R.W. and Hopkins, P.L. 1990. On Conditions and Parameters Important to Model 
Sensitivity for Unsaturated Flow Through Layered, Fractured Tuff: Results of Analyses for 
HYDROCOIN Level 3 Case 2. SAND89-0652. Albuquerque, New Mexico: Sandia National 
Laboratories. ACC: NNA.19900523.0211. 
Rai, D.; Felmy, A.R.; Moore, D.A.; and Mason, M.J. 1995. "The Solubility of Th(IV) and U(IV) 
Hydrous Oxides in Concentrated NaHCO3 and Na2CO3 Solutions." Scientific Basis for Nuclear 
Waste Management XVIII, Symposium held October 23-27, 1994, Kyoto, Japan. Murakami, T. 
and Ewing, R.C., eds. 353, 1143-1150. Pittsburgh, Pennsylvania: Materials Research Society. 
TIC: 216341. 
Rechard, R.P. 1999. "Historical Relationship Between Performance Assessment for Radioactive 
Waste Disposal and Other Types of Risk Assessment." Risk Analysis, 19, (5), 763-807. New 
York, New York: Plenum Press. TIC: 246972. 
Rechard, R.P., ed. 1993. Initial Performance Assessment of the Disposal of Spent Nuclear Fuel 
and High Level Waste Stored at Idaho National Engineering Laboratory. SAND93-2330. 
Volumes 1 and 2. Albuquerque, New Mexico: Sandia National Laboratories. TIC: 247212. 
Rechard, R.P., ed. 1995. Executive Summary. Volume 1 of Performance Assessment of the 
Direct Disposal in Unsaturated Tuff of Spent Nuclear Fuel and High-Level Waste Owned by U.S. 
Department of Energy. SAND94-2563/1. Albuquerque, New Mexico: Sandia National 
Laboratories. TIC: 237101. 
Shoesmith, D.W. 1999. Fuel Corrosion Processes Under Waste Disposal Conditions. AECL- 
12034. Pinawa, Manitoba, Canada: Whiteshell Laboratories. TIC: 246006. 
Sinnock, S.; Lin, Y.T.; and Brannen, J.P. 1984. Preliminary Bounds on the Expected Postclosure 
Performance of the Yucca Mountain Repository Site, Southern Nevada. SAND84-1492. 
Albuquerque, New Mexico: Sandia National Laboratories. ACC: NNA.19870519.0076. 
Strachan, D.M.; Bourcier, W.L.; and McGrail, B.P. 1994. "Toward a Consistent Model for Glass 
Dissolution." Radioactive Waste Management and Environmental Restoration, 19, (1-3), 129- 
145. Chur, Switzerland: Harwood. TIC: 247530.

 6-11
Stroupe, E.P. 2000. "Approach to Implementing the Site Recommendation Design Baseline." 
Interoffice correspondence from E.P. Stroupe (CRWMS M&O) to D.R. Wilkins, January 26, 
2000, LV.RSO.EPS.1/00-004, with attachment. ACC: MOL.20000214.0480. 
Tait, J.C. and Luht, J.L. 1997. Dissolution Rates of Uranium from Unirradiated UO2 and 
Uranium and Radionuclides from Used CANDU Fuel Using the Single-Pass Flow-Through 
Apparatus. 06819-REP-01200-0006 R00. Toronto, Ontario, Canada: Ontario Hydro. TIC: 
243164. 
Tasooji, A.; Einziger, R.E.; and Miller, A.K. 1984. "Modeling of Zircaloy Stress-Corrosion 
Cracking: Texture Effects and Dry Storage Spent Fuel Behavior." Zirconium in the Nuclear 
Industry, Sixth International Symposium, Vancouver, British Columbia, June 28- July 1, 1982. 
Franklin, D.G. and Adamson, R.B., eds. ASTM STP 824, 595-626. Philadelphia, Pennsylvania: 
American Society for Testing and Materials. TIC: 241417. 
Tombacz, E.; Abraham, I.; Gilde, M.; and Szanto, F. 1990. "The pH-Dependent Colloidal 
Stability of Aqueous Montmorillonite Suspensions." Colloids and Surfaces, 49, 71-80. 
Amsterdam, The Netherlands: Elsevier Science. TIC: 246046. 
Torrero, M.E.; Baraj, E.; De Pablo, J.; Gimenez, J.; and Casas, I. 1997. "Kinetics of Corrosion 
and Dissolution of Uranium Dioxide as a Function of pH." International Journal of Chemical 
Kinetics, 29, (4), 261-267. New York, New York: John Wiley & Sons. TIC: 246160. 
Wescott, R.G.; Lee, M.P.; Eisenberg, N.A.; McCartin, T.J.; and Baca, R.G., eds. 1995. NRC 
Iterative Performance Assessment Phase 2: Development of Capabilities for Review of a 
Performance Assessment for a High-Level Waste Repository. NUREG-1464. Washington, D.C.: 
U.S. Nuclear Regulatory Commission. TIC: 221527. 
Wilson, C.N. 1990. Results from NNWSI Series 3 Spent Fuel Dissolution Tests. PNL-7170. 
Richland, Washington: Pacific Northwest Laboratory. ACC: NNA.19900329.0142. 
Wilson, M.L.; Gauthier, J.H.; Barnard, R.W.; Barr, G.E.; Dockery, H.A.; Dunn, E.; Eaton, R.R.; 
Guerin, D.C.; Lu, N.; Martinez, M.J.; Nilson, R.; Rautman, C.A.; Robey, T.H.; Ross, B.; Ryder, 
E.E.; Schenker, A.R.; Shannon, S.A.; Skinner, L.H.; Halsey, W.G.; Gansemer, J.D.; Lewis, L.C.; 
Lamont, A.D.; Triay, I.R.; Meijer, A.; and Morris, D.E. 1994. Total-System Performance 
Assessment for Yucca Mountain  SNL Second Iteration (TSPA-1993). SAND93-2675. Executive 
Summary and two volumes. Albuquerque, New Mexico: Sandia National Laboratories. ACC: 
NNA.19940112.0123. 
Yau, T-L. 1992. "Stress-Corrosion Cracking of Zirconium Alloys." Chapter 11 of Stress- 
Corrosion Cracking. Jones, R.H., ed. Materials Park, Ohio: ASM International. TIC: 246059. 
YMP (Yucca Mountain Site Characterization Project) 1998. Disposal Criticality Analysis 
Methodology Topical Report. YMP/TR-004Q, Rev. 0. Las Vegas, Nevada: Yucca Mountain Site 
Characterization Office. ACC: MOL.19990210.0236.

 6-12
6.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
10 CFR 60. Energy: Disposal of High-Level Radioactive Wastes in Geologic Repositories. 
Readily Available 
40 CFR 191. Protection of Environment: Environmental Radiation Protection Standards for 
Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive 
Wastes. Readily Available 
60 FR 42622. Use of Probabilistic Risk Assessment Methods in Nuclear Regulatory Activities: 
Final Policy Statement. Readily Available 
64 FR 46976. 40 CFR 197: Environmental Radiation Protection Standards for Yucca Mountain, 
Nevada; Proposed Rule. Readily Available 
AP-2.14Q, Rev.0, ICN 1. Review of Technical Products. Washington, D.C.: U.S. Department 
of Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20000405.0477. 
AP-2.16Q, Rev. 0, ICN 0. Activity Evaluation. Washington, D.C.: U.S. Department of Energy, 
Office of Civilian Radioactive Waste Management. ACC: MOL.20000207.0716. 
AP-3.10Q, Rev. 2, ICN 2. Analyses and Models. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20000619.0576. 
AP-3.11Q, Rev. 1, ICN 0. Technical Reports. Washington, D.C.: U.S. Department of Energy, 
Office of Civilian Radioactive Waste Management. ACC: MOL.20000516.0008. 
AP-3.15Q, Rev. 1, ICN 1. Managing Technical Product Inputs. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. ACC: 
MOL.20000218.0069. 
AP-SI.1Q, Rev. 2, ICN 4. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20000223.0508. 
AP-SIII.2Q, Rev. 0, ICN 2. Qualification of Unqualified Data and the Documentation of 
Rationale for Accepted Data. Washington, D.C.: U.S. Department of Energy, Office of Civilian 
Radioactive Waste Management. ACC: MOL.19991214.0625. 
ASTM C 1174-97. 1997. 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. 
ASTM C1285-97. 1999. Standard Test Methods for Determining Chemical Durability of 
Nuclear, Hazardous, and Mixed Waste Glasses: The Product Consistency Test (PCT). West 
Conshohocken, Pennsylvania: American Society for Testing and Materials. TIC: 247001.

 F1-1
NOTE: See CRWMS M&O 2000f through 2000m for AMR references for 
Sections 3.1 through 3.8 respectively. 
Figure 1.4-1. Documents Specifically Supporting the Waste Form 
Degradation PMR

 F1-2
Figure 1.5-1. Summary of Inputs, Outputs, Components, and Assumptions of Waste Form 
Degradation Model

 F1-3
Figure 1.5-2. Major Models within TSPA-SR

 F1-4
Figure 1.5-3. Linkage of Components in Waste Form Degradation Model

 F2-1
Figure 2.3-1. Waste Form FEPs

 F2-2
INTENTIONALLY LEFT BLANK

 F3-1
NOTE: The figure depicts the types and quantities of waste forms to be disposed of in the first repository and their 
representative waste package designs. Until a second repository is in operation, the Nuclear Waste Policy 
Act limits inventory in the first repository to 70,000 MTHM. Dispositioning excess plutonium from weapons 
programs into mixed oxide fuel for burnup in reactors and disposal in a repository aids in the fight against 
nuclear proliferation. 
Figure 3.1-1. Waste Types Grouped into Three Representative Waste Packages for Modeling in 
TSPA-SR

 F3-2
Figure 3.1-2. Flow of Information Supporting the Radionuclide Inventory Component

 F3-3
Figure 3.2-1. Conceptual Model of In-Package Chemistry

 F3-4
Source: In-Package Chemistry Abstraction for TSPA-LA. ANL-EBS-MD-00037. (CRWMS M&O 2000g) 
Figure 3.2-2. Abstraction Equations and Linkage of Subcomponents of In-Package Chemistry Component

 F3-5
Source: In-Package Chemistry Abstraction for TSPA-LA. ANL-EBS-MD-000037. (CRWMS 
M&O 2000g, Figure 1) 
NOTE: CSNF numbers are code numbers for the CSNF calculations. 
Figure 3.2-3. pH History for CSNF Process Model Calculations 
3.0 
4.0 
5.0 
6.0 
7.0 
8.0 
9.0 
0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 
Time(years) 
pH 
CSNF 000 CSNF 001 CSNF 002 
CSNF 100 CSNF 101 CSNF 102 
CSNF 010 CSNF 011 CSNF 012 
CSNF 110 CSNF 111 CSNF 112 
CSNF 200 CSNF 201 CSNF 202 
CSNF 210 CSNF 211 CSNF 212 
00020DC-WFD-PMR-46-M&O Graphics/LV.doc

 F3-6
Source: In-Package Chemistry Abstraction for TSPA-LA. ANL-EBS-MD-000037. (CRWMS 
M&O 2000g, Figure 2) 
NOTE: CDSP numbers are code numbers for the codisposal waste package calculations. 
Figure 3.2-4. pH History for Codisposal Process Model Calculations 
4.0 
5.0 
6.0 
7.0 
8.0 
9.0 
10.0 
11.0 
0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 
Time(years) 
pH 
CDSP 000 CDSP 001 CDSP 002 
CDSP 100 CDSP 101 CDSP 102 
CDSP 010 CDSP 011 CDSP 012 
00020DC-WFD-PMR-47-M&O Graphics/LV.doc

 F3-7
Source: In-Package Chemistry Abstraction for TSPA-LA. ANL-EBS-MD-000037. (CRWMS 
M&O 2000g, Figure 3) 
Figure 3.2-5. pH Abstraction for < 1,000 Years, CSNF 
3.0 
3.5 
4.0 
4.5 
5.0 
5.5 
6.0 
-2.0 
-1.5 
-1.0 
-0.5 
0.0 
0.5 
0.02
0.06 
0.10 
0.14 
pH 
Log Cladding Coverage (cc) 
Q (m3/yr) 
Low WP corrosion rates 
High WP corrosion rates 
pH = 3.4916  1.0918 log(cc) + 0.4571 Q 
pH = 3.3977  0.7468 log(cc) + 0.3515 Q 
00020DC-WFD-PMR-48-M&O Graphics/LV.doc

 F3-8
Source: In-Package Chemistry Abstraction for TSPA-LA. ANL-EBS-MD-000037. (CRWMS 
M&O 2000g, Figure 4) 
Figure 3.2-6. pH Abstraction for 1,000 to 10,000 Years, CSNF 
5.0 
5.5 
6.0 
6.5 
7.0 
7.5 
8.0 
-2.0 
-1.5 
-1.0 
-0.5 
0.0 
0.5 
0.04 
0.08 
0.12 
0.16 
pH 
Log Cladding Coverage (cc) 
Q (m3/yr) 
Low WP Corrosion Rates 
High WP Corrosion Rates 
pH = 6.0668  0.5395 log(cc) + 4.0479Q 
ph = 6.0913  0.3057 log(cc) + 1.2913 Q 
00020DC-WFD-PMR-49-M&O Graphics/LV.doc

 F3-9
Source: In-Package Chemistry Abstraction for TSPA-LA. ANL-EBS-MD-000037. (CRWMS 
M&O 2000g, Figure 5) 
Figure 3.2-7. pH Abstraction for < 1,000 Years, Codisposal Waste Packages 
4.5 
5.0 
5.5 
6.0 
6.5 
7.0 
0.00 
0.04 
0.08 
0.12 
0.16 
0 
2 
4 
6 
8 
10 
pH 
Q (m3 
/yr) 
Relative Glass Rate (GR) 
Low WP Corrosion Rate 
High WP Corrosion Rate 
pH = 5.1257 + 2.6692 Q + 0.0764(GR) 
pH = 4.7324 + 0.7307 Q + 0.0837(GR) 
00020DC-WFD-PMR-50-M&O Graphics/LV.doc

 F3-10
Source: In-Package Chemistry Abstraction for TSPA-LA. ANL-EBS-MD-000037. (CRWMS 
M&O 2000g, Figure 6) 
Figure 3.2-8. pH Abstraction for 1,000 to 100,000 Years, Codisposal Waste Packages 
7 
8 
9 
10 
11 
0.00 
0.04 
0.08 
0.12 
0.16 
2 4 6 8 10 12 
pH 
Q (m3/yr) 
Relative Glass Rate (GR) 
Low WP Corrosion Rate 
High WP Corrosion Rate 
pH = 8.4247  3.1473 Q  0.1403(GR) 
pH = 9.2554  3.1280 Q + 0.0418(GR) 
00020DC-WFD-PMR-51-M&O Graphics/LV.doc

 F3-11
Figure 3.3-1. CSNF Degradation Model

 F3-12
NOTE: Tracking information in CRWMS M&O 2000h. 
Figure 3.3-2. Analysis/Model Reports Supporting the Development 
of the CSNF Degradation Component

 F3-13
Source: CSNF Waste Form Degradation: Summary Abstraction. 
ANL-EBS-MD-000015. (CRWMS M&O 2000h, Figure 2) 
Figure 3.3-3. Abstracted Dissolution Model 
00020DC-WFD-PMR-45-M&O Graphics/LV.doc

 F3-14
Figure 3.4-1. Conceptual Model of CSNF Cladding Degradation

 F3-15
Figure 3.4-2. Implementation of CSNF Cladding Degradation in TSPA-SR

 F3-16
NOTE: Tracking information in CRWMS M&O 2000i 
Figure 3.4-3. Calculations and Analysis and Model Reports Supporting the Development of the CSNF 
Cladding Degradation Component

 F3-17
Source: Initial Cladding Condition. ANL-EBS-MD-000048. (CRWMS M&O 2000p, 
Table 14) 
Figure 3.4-4. CCDF for Existing Perforated CSNF 
% of Rods Initially Perforated in a WP 
0.01 0.1 1 10 
CCDF of WPs with More than 
X% of the Rods Perforated 
0.0001 
0.001 
0.01 
0.1
1 
Lower Limit 
Best Estimate 
Upper Limit 
Rel-PB3.spw 
00020DC-WFD-PMR-52-M&O Graphics/LV.doc

 F3-18
Figure 3.4-5. CSNF Matrix Temperature

 F3-19
Source: Clad DegradationSummary and Abstraction. ANL-WIS-MD-000007. (CRWMS 
M&O 2000i, Figure 5) 
Figure 3.4-6. Temperature History for Average Center Rod in WP 
Time, Years 
0.1 1 10 100 
Center Rod Temperature, oC 
0 
50 
100 
150 
200 
250 
300 
350 
400 
temp12b13.spw 
Dry Storage Shipping 
Preclosure 
Postclosure 
00020DC-WFD-PMR-53-M&O Graphics/LV.doc

 F3-20
Source: Clad DegradationSummary and Abstraction. ANL-WIS-MD-000007. 
(CRWMS M&O 2000i, Figure 1) 
Figure 3.4-7. CCDF for Rod Stress As Received (room temperature) 
Temperature = 27oC 
Time = 100 years
stress2.spw 
Hoop Stress, MPa 
20 40 60 80 100 120 140 160 
Percent of Rods with Stress Exceeding X Stress 
0.1
1 
10 
100 
00020DC-WFD-PMR-54-M&O Graphics/LV.doc

 F3-21
Source: Clad DegradationSummary and Abstraction. ANL-WIS-MD-000007. 
(CRWMS M&O 2000i, Figure 8) 
Figure 3.4-8. Creep and SCC Perforated as a Function of WP Surface Temperature 
CREEP-Mu.spw Creep-Mu.spw 
Peak WP Surface Temperature,oC 
260 280 300 320 340 360 380 400 
Fraction of Rods with Creep Failure 
0.0 
0.2 
0.4 
0.6 
0.8 
1.0 
Upper Limit 
Best Estimate 
Lower Limit 
Creep-Mu.spw 
00020DC-WFD-PMR-55-M&O Graphics/LV.doc

 F3-22
Source: Clad DegradationSummary and Abstraction. ANL-WIS-MD-000007. 
(CRWMS M&O 2000i, Figure 9) 
Figure 3.4-9. Example of Localized Corrosion with Constant Water Flow into WP 
fluor6a 
Minimum 
Maximum 
Best Estimate 
Linear 
Model LNT Calculation 
fluor6a.spw fluor6a.spw 
Time from WP Failure, Years 
0 10000 20000 30000 40000 50000 
Fraction of Rods Failed in WP 
0.0 
0.2 
0.4 
0.6 
0.8 
1.0 
Maximum 
Minimum 
Best Estimate 
fluor9.spw 
Water Ingress into WP = 50 liters/yr 
00020DC-WFD-PMR-56-M&O Graphics/LV.doc

 F3-23
Source: Clad DegradationSummary and Abstraction. ANL-WIS-MD-000007. 
(CRWMS M&O 2000i, Figure 11) 
Figure 3.4-10. CDF for Fast Release Fraction from Fuel Matrix 
0.000 0.001 0.002 0.003 0.004 0.005 
Fast Release Fraction 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0 
CDF 
From Measurement 
Recommended 
00020DC-WFD-PMR-57-M&O Graphics/LV.doc

 F3-24
Source: Clad DegradationSummary and Abstraction. ANL-WIS-MD-000007. 
(CRWMS M&O 2000i, Figure 13) 
Figure 3.4-11. Time to Unzip Rod versus WP Temperature 
WP Temperature, oC 
20 30 40 50 60 70 80 90 100 110 
Time to Unzip Rod, Years 
10000 
20000 
30000 
40000 
50000 
60000 
70000 
unzip4.spw 
O2 = 0.2 atm. 
CO3 = 0.001 M 
pH = 8 
00020DC-WFD-PMR-58-M&O Graphics/LV.doc

 F3-25
Figure 3.5-1. Implementation of DSNF (exclusive of naval SNF) Degradation in TSPA-SR

 F3-26
Figure 3.6-1. Bounding Rates in HLW Degradation Component 
Figure 3.6-2. Abstracted Glass Dissolution Rate Model

 F3-27
Figure 3.7-1. Linkage of Subcomponents of Solubility Component

 F3-28
NOTE: Tracking information in CRWMS M&O 2000l 
Figure 3.7-2. Calculations and Analysis/Model Reports Supporting the 
Development of the Solubility Component

 F3-29
Figure 3.7-3. Comparison of Neptunium Solubility Abstraction to the Data of Efurd et al. (1998) 
Source: Summary of Dissolved Concentration Limits. ANL-WIS-MD-000010. (CRWMS 
M&O 2000l, Figure 2) 
Figure 3.7-4. Comparison of Fitted Response Surface (solid curves) with Calculated 
Americium Solubilities 
-3 
-5 
-7 
log fCO2 
-8 
-7 
-6 
-5 
-4 
-3 
-2 
-1 
log Am (molality) 
5 6 7 8 9 10 11 12 13 
pH 
00020DC-WFD-PMR-59-M&O Graphics/LV.doc

 F3-30
Figure 3.8-1. Conceptual Model of Formation of Reversibly and Irreversibly Attached Radionuclides 
on Colloids

 F3-31
Figure 3.8-2. Linkage of Subcomponents of Colloidal Radionuclide Component

 F3-32
NOTE: Plutonium-bearing colloids as a function of ionic strength for corrosion tests on glass 
samples SRL 202A and SRL 131A at surface area to volume ratios of 2,000 and 20,000/m 
(at 90C). Figure and modified caption from CRWMS M&O (2000m, Figure 7). 
Figure 3.8-3. Generation of Waste-Form Colloids; Data 
00022DC-WFD-PMR-60-M&O Graphics/LV.doc 
0E+0 
2E-8 
4E-8 
6E-8 
0.000 0.020 0.040 0.060 0.080 0.100 
Relative Ionic Strength (mol/kg) 
202A_2K 
202A_20K 
131A_2K 
131A_20K 
[Pucolloids] (M)

 F3-33
NOTE: Schematic relationship between radionuclide-bearing colloid concentration and 
ionic strength. The function represents the bound of the HLW degradation 
experimental data; the maximum value, 6 x 10-8 M, is the maximum 
concentration of colloids observed in the HLW experiments. (Refer to 
Table 3.8-1 for a description of notation and parameter names and values.) 
Source: Waste Form Colloid-Associated Concentration Limits: Abstraction and Summary. 
ANL-WIS-MD-000012. (CRWMS M&O 2000m, Figure 13) 
Figure 3.8-4. Generation of Waste-Form Colloids; Abstraction 
00022DC-WFD-PMR-41-M&O Graphics/LV.doc

 F3-34
(a) Experimental determination of montmorillonite stability as a function of pH and ionic strength. Data points 
represent combinations of ionic strength and pH at which montmorillonite stability is significantly decreased. Data 
from Tombacz et al. (1990). 
(b) Schematic representation of smectite colloid stability as a function of pH and ionic strength. (Refer to Table 3.8-1 
for a description of notation and parameter names and values.) 
Source: Waste Form Colloid-Associated Concentration Limits: Abstraction and Summary. ANL-WISMD-
000012. (CRWMS M&O 2000m, Figures 5 and 12) 
Figure 3.8-5. Stability of Smectite Colloids; Data and Abstraction 
Ionic Strength (NaCl) 
2 6 8 10 
zpc 
pH 
0.01 
0.02 
4 
0.03 
0.04 
0.05 
MONTMORILLONITE 
UNSTABLE 
MONTMORILLONITE 
STABLE 
00022DC-WFD-PMR-61-M&O Graphics/LV.doc 
00022DC-WFD-PMR-42-M&O

 F3-35
(a) Effect of ionic strength on steady-state concentration of waste-form colloids, based on colloidal plutonium 
concentrations as shown in Figure 3.8-5. 
(b) Effect of ionic strength and pH on stability of waste-form colloids, based on behavior of smectite colloids as shown 
in Figure 3.8-5. 
(c) Determination of mass concentration of waste-form colloids, scaled on the basis of maximum and calculated 
plutonium concentrations. 
(d) Calculation of reversibly sorbed radionuclide concentration. (Refer to Table 3.8-1 for a description of notation and 
parameter names and values.) 
Figure 3.8-6. Flow Chart Diagram Depicting Model Implementation for Waste-Form Colloids 
TRI-6243-6272-0 
00020DC-WFD-PMR-35-M&O Graphics/LV.ai 
TRI-6243-6272-0 
00020DC-WFD-PMR-65-M&O Graphics/LV.ai 
TRI-6243-6272-0 
00020DC-WFD-PMR-66-M&O Graphics/LV.ai 
TRI-6243-6272-0 
00020DC-WFD-PMR-67-M&O Graphics/LV.ai

 F3-36
(a) Experimentally derived stability ratio, Wexp, of a hematite suspension plotted as a function of pH for differing ionic strengths. 
The pH of zero proton condition is indicated. Dashed lines are drawn through the experimental points as a guide. Figure and 
caption from Liang and Morgan (1990, Figure 1). Note that Wexp represents the stability of the dispersion, in terms of the rate at 
which colloidal particles in the dispersion agglomerate. A high value indicates rapid agglomeration; a value of zero represents a 
stable dispersion. At ionic strengths of about 0.5 m or more, the stability ratio is very low between pH values of about 6 and 11. A 
relatively low log Wexp of approximately 0.2 was selected for abstraction of pH and ionic strength. 
(b) Schematic representation of iron-(hydr)oxide colloid stability as a function of ionic strength and pH. At and near the zero-pointof-
charge, colloids are unstable, even at low ionic strengths. At higher ionic strengths the pH range at which colloids are unstable 
is greater. Above an ionic strength of 0.05 m, colloids are assumed to be unstable at all pH values. (Refer to Table 3.8-1 for a 
description of notation and parameter names and values.) 
Source: Waste Form Colloid-Associated Concentration Limits: Abstraction and Summary. ANL-WISMD-
000012. (CRWMS M&O 2000m, Figures 6 and 11) 
Figure 3.8-7. Stability of Corrosion-Product Colloids; Data and Abstraction 
00022DC-WFD-PMR-43-M&O Graphics/LV.doc 
6 8 9 11 
zpc 
pH 
0.01 
0.05 
Ionic Strength 
iron oxyhydroxide colloid 
zone of instability 
I = -0.02 pH + 0.17 
I = 0.02 pH - 0.17 
00022DC-WFD-PMR-62-M&O Graphics/LV.doc

 F3-37
(a) Effect of ionic strength and pH on stability of corrosion-product colloids, based on behavior of iron-(hydr)oxide 
colloids as shown in Figure 3.8-7. 
(b) Calculation of reversibly sorbed radionuclide concentration. (Refer to Table 3.8-1 for description of notation 
and parameter names and values.) 
Figure 3.8-8. Flow Chart Diagram Depicting Model Implementation for Corrosion-Product Colloids

 F3-38
(a) Colloid concentration plotted as a function of ionic strength. Error bars denote uncertainty in 
concentration values. 
(b) Schematic representation of groundwater colloid mass concentration as a function of ionic strength. 
(Refer to Table 3.8-1 for a description of notation and parameter names and values.) 
Source: Waste Form Colloid-Associated Concentration Limits: Abstraction and Summary. ANL-WISMD-
000012. (CRWMS M&O 2000m, Figure 9 for (a) and Figure 14 for (b)) 
Figure 3.8-9. Concentration of Groundwater Colloids; Data and Abstraction

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(a) Effect of ionic strength on the mass of mobile naturally occurring groundwater colloids as shown in Figure 3.8-4. 
(b) Effect of ionic strength and pH on stability of waste-form colloids, based on behavior of smectite colloids as 
shown in Figure 3.8-5. 
(c) Calculation of reversibly sorbed radionuclide concentration. (Refer to Table 3.8-1 for description of notation 
and parameter names and values.) 
Figure 3.8-10. Flow Chart Diagram Depicting Model Implementation for Groundwater Colloids

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NOTE: Summation of the concentration of radionuclides associated with waste-form colloids (both 
reversibly and irreversibly attached), corrosion-product colloids, and groundwater colloids. Also, 
summation of the mass of the three types of colloids. (Refer to Table 3.8-1 for description of 
notation and parameter names and values.) 
Figure 3.8-11. Flow Chart Diagram Depicting Model Implementation for all Colloids