Waste Package Degradation Process Model Report Rev 00, ICN 01

TDR-WIS-MD-000002


June 2000

EXECUTIVE SUMMARY 
A crucial element of the long-term postclosure safety strategy for the potential monitored 
geologic repository at Yucca Mountain is to contain high-level radioactive waste (HLW), and to 
keep that waste and its container as dry as possible. This report is one of nine Process Model 
Reports (PMRs) developed to address the technical basis supporting the Total System 
Performance Assessment (TSPA) model. These PMRs are supported by Analysis and Model 
Reports (AMRs) that contain more detailed technical information. 
The waste package (WP) is a major component of the engineered barrier system (EBS) and 
contributes to isolation of HLW during the preclosure and postclosure periods. It also reduces 
the uncertainties associated with performance of the repository. As a result, the integrity of the 
WP and the drip shield (DS) have been designated as Principal Factors important to the 
repository safety strategy. The WP, protected by a DS, will be subjected to degradation 
processes in the repository that will eventually impact postclosure performance. Some of the 
important conditions contributing to WP degradation include: humidity and temperature in the 
emplacement drift; chemistry of the dripping water; and the corrosion susceptibility of the WP 
materials. Eight process-level models or analyses, four abstraction models, and two engineering 
calculations were developed and documented in individual AMRs or Calculations. This PMR 
provides a summary of process-level and abstraction models, as well as a summary of their 
utilization in the integrated WP degradation model contained in the WAPDEG code. 
This report also includes discussions on the features, events, and processes (FEPs) relevant to the 
performance of the WP materials. These FEPs that are deemed important to repository 
performance are evaluated, either as components for the TSPA, or as separate analyses in the 
AMRs. 
In addition to describing the process-level and abstraction models, this PMR addresses two of the 
Key Technical Issues (KTIs) in the Issue Resolution Status Report (IRSR) prepared by the U.S. 
Nuclear Regulatory Commission (NRC). These issues are the Container Life and Source Term 
(CLST) and the TSPA and Integration (TSPAI). Several subissues that relate directly to the WP 
are discussed in this PMR, along with the approach used by the Yucca Mountain Site 
Characterization Project (YMP) to meet the acceptance criteria for each of the KTIs. 
This PMR also addresses relevant issues identified by other agencies and organizations, 
including the Nuclear Waste Technical Review Board (NWTRB). 
The integrated WP model incorporated into the WAPDEG code was used to develop the results 
documented here. The analyses have shown that both the DS and WPs do not experience 
significant failures within the regulatory time period (10,000 years). 
The materials selected for the DS and WP outer barrier, Titanium Grade 7 and Alloy 22, 
respectively are highly corrosion resistant under the repository exposure conditions. Both the DS 
and WP degrade by general corrosion (GC) at very low rates. However, degradation modes such 
as localized corrosion (LC) (pitting and crevice corrosion), stress corrosion cracking (SCC), and 
hydrogen-induced cracking (HIC) could lead to premature failure of the WP or DS, if any 
degradation is initiated. Fortunately, the selected materials appear to be immune to LC under
repository-relevant conditions. With appropriate processing, the initiation of SCC and HIC (in 
the case of Titanium Grade 7) are delayed to a point where acceptable repository performance is 
achieved. To preclude SCC, post-weld stress mitigation processes will be implemented on the 
closure welds of the dual-closure-lid WP. The compressive layer that is needed to preclude SCC 
is produced by either one of two post-weld stress mitigation processes, laser peening or localized 
induction annealing. The life of the WP is determined by the time required to remove the 
mitigated layer of material at each weld by GC.



1. INTRODUCTION 
A crucial element of the long-term postclosure safety strategy for the potential monitored 
geologic repository at Yucca Mountain is to contain high-level radioactive waste (HLW), and to 
keep that waste and its container as dry as possible. There are several degradation processes that 
could impact the performance of the engineered barrier system (EBS). The role of this PMR is 
to describe one of the process-level models (Waste Package Degradation) utilized to evaluate 
these degradation processes. To evaluate the postclosure performance of the monitored geologic 
repository proposed for construction 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 process-level 
models supporting the TSPA model. These reports cover the following areas: 
 Integrated Site Model 
 Unsaturated Zone Flow and Transport 
 Near-Field Environment (NFE) 
 EBS Degradation, Flow, and Transport 
 Waste Package Degradation 
 Waste Form Degradation 
 Saturated Zone Flow and Transport 
 Biosphere 
 Disruptive Events. 
These PMRs are supported by several Analysis and Model Reports (AMRs) that contain more 
detailed technical information. This technical information consists of data, analyses, models, 
software, and other documentation necessary to defend the applicability of each model for its 
intended purpose. The PMR is intended to ensure the traceability of waste package degradation 
information from its various sources through the AMRs, PMRs, and eventually in TSPA. 
As described in the Monitored Geologic Repository Project Description Document, the 
recommended waste package design is Enhanced Design Alternative II (CRWMS M&O 1999a, 
Section 1.1.2). 
The Enhanced Design Alternative II (EDA II) waste package design is the reverse of the 
Viability Assessment (VA) design. In EDA II, the corrosion-resistant material protects the 
underlying structural material from corrosion, while the structural material supports the thinner, 
more expensive corrosion-resistant material. As shown in Figure 1-1, this design includes a 
double-wall waste package (WP) made from Alloy 22 and 316 nuclear grade (NG) stainless 
steel. The WP is placed underneath a protective drip shield (DS) made of a titanium-based alloy, 
as shown in Figure 1.2.

 1-2  
Figure 1-1. Waste Package EDA II uses thermal management features (line loading, ventilation, and blending) to limit peak 
temperatures of cladding, the waste package shell, and the drift wall. This produces more 
uniform temperature along the drifts, and margin in meeting requirements for cladding integrity, 
drift stability, and avoidance of phase instability in the waste package materials. Figure 1-2 
shows a typical layout of an in-drift placement of three types of waste packages. Note that DSs 
will be placed over the waste packages just before repository closure to provide protection from 
dripping water and rock fall. 
Figure 1-2. A View of a Typical In-Drift Placement of Waste Packages 
The purpose of this PMR is to account for the degradation of WP materials under conditions 
expected at the Yucca Mountain site, which is being evaluated as a possible geologic repository 
for the disposal of HLW waste. Data pertaining to WP material degradation are presented in 
supporting AMRs. Functional summaries of the component models and their respective output 
are provided in Section 1.4. This report was developed in accordance with the technical product 
development plan Development Plan for Waste Package Degradation Process Model Report 
(CRWMS M&O 1999b). 
Each of the process-level models described in the Waste Package Degradation PMR accounts for 
a different degradation process, all of which are integrated in the waste package degradation 
code (WAPDEG) (CRWMS M&O 2000g). Each model was developed using unique 
methodologies and inputs, with the determination of that model dependent on the functional 
requirements of the waste package component being represented. 
In January 2000, the Project modified the repository design. The changes instituted involve 
removing backfill from the reference design and reorienting the drifts to minimize the impacts of 
the rockfall. Preparation of this PMR and the supporting AMRs preceded this design change and
do not, therefore, include the impact of that change. However, a qualitative assessment has been 
made to evaluate the effect of no backfill on the results presented in this PMR and the supporting 
AMRs. AMRs impacted by the removal of the backfill include those that describe: 
 Stress corrosion cracking (SCC) of the drip shield (DS), the waste package outer barrier 
(WPOB) and the Stainless Steel Structural Material. 
 Abstraction of Models for the SCC of DS and WPOB and hydrogen-induced cracking 
(HIC) of DS. 
 WAPDEG Analysis of WP and DS Degradation. 
At this time, the AMR on the SCC assumes that the DS is protected by backfill from rockfallinduced 
stress and therefore, no SCC. Removal of the backfill may subject the DS to localized 
stress due to rockfall, thereby increasing the susceptibility to SCC. The abstraction AMR on 
SCC and the WAPDEG analysis AMR are similarly affected. While a more detailed analysis is 
required to quantify the impact of the design change, preliminary analyses indicate that any 
stress corrosion cracks in the DS will not result in the direct dripping of water on the waste 
package since it is believed that the cracks will become plugged with corrosion products. While 
this cracking constitutes failure of the DS, it is expected to continue to maintain its function of 
keeping the water away from the WP. These issues are planned to be addressed in the next 
revisions of the specific AMRs. 
In addition to the increased susceptibility to SCC, the DS may also be subjected to increased 
corrosion due to rockfall-induced cold-worked regions. Preliminary review of the literature 
indicates that this is not a significant issue. 
It is planned to address these issues in the next versions of the AMRs. 
1.1 OBJECTIVES 
1.1.1 Objectives of this Report 
The objectives of this report are to document degradation models for the waste package and DS 
material with specific regard to the data input methodologies used to construct the model, 
uncertainties and limitations of the modeling results, and validation of the model. This report 
summarizes the following: 
 Sources of data input 
 Methodologies used to construct the model components 
 Modeling results, uncertainties, and limitations. 
Assumptions that are specific to the individual models are listed in Chapter 3. Additional details 
of model assumptions can be found in Chapter 5 of the individual AMRs.

 1-5  
1.1.2 Purpose of the Analysis and Model Reports 
The primary purpose of the supporting AMRs is to provide detailed documentation of the 
process-level models necessary for predicting the performance of the WP and DS materials in 
environments relevant to Yucca Mountain. These models enable engineers and scientists to 
predict the release of radionuclides from the WP, and their transport in the saturated and 
unsaturated zones. Figure 1-3 shows the model inputs, outputs and the laboratory test 
information that forms the bases for the confidence in the model results. 
At the base of the model confidence foundation are the data generated from various testing 
programs; then, data along with other input parameters related to the repository design and 
expected environment are used in the development of degradation process models. The output 
from these models are calculated lifetimes for the waste package and drip shields. 
Figure 1-3. Model Confidence Foundation

 1-6  
1.2 SCOPE 
The Waste Package Degradation PMR describes processes that will lead to degradation of the 
waste package components within the near-field environment (NFE). Specific technical 
information contained in the Waste Package Degradation PMR consists of data, analyses, 
models, software, and supporting documents. This report also provides a technical basis for the 
applicability of the overall integrated model for its intended purpose of evaluating postclosure 
performance of the Yucca Mountain repository system. 
The Waste Package Degradation PMR provides information about important factors that affect 
WP and DS lifetimes. This PMR uses inputs from companion documents, including the license 
application design selection (LADS) report, which describes the EDA II design and expected 
temperature history for the waste package in the repository. 
Chapter 2 of this PMR describes the evolution of the waste package degradation model. Details 
of the individual models and analyses are provided in Chapter 3. Chapter 4 describes the 
NRC IRSR, which serves as a driver for much of the work that is discussed. Acceptance criteria 
and responses to these criteria are addressed in this chapter. Summary and conclusions are 
provided in Chapter 5. 
1.3 PRINCIPAL FACTORS AND OTHER FACTORS CONSIDERED 
The magnitude of the Yucca Mountain Site Characterization Project (YMP) and the complexities 
associated with both the natural and engineered barrier systems 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: U.S. Department of Energy's Strategy to Protect 
Public Health and Safety After Closure of a Yucca Mountain Repository (CRWMS M&O 
2000w) has identified seven Principal Factors and twenty Other Factors of second-order 
importance. The selection of the Principal Factors was based on preliminary TSPA analyses and 
expert judgment, which showed that these factors significantly affect the performance of the 
potential repository. The Other Factors were deemed to have minimal impact on the repository 
performance in terms of dose to the accessible environment. Table 1-1 lists the seven Principal 
Factors, the twenty Other Factors, and the PMRs that address each factor. Specific Principal 
Factors discussed in this report are: 
 Performance of the DS 
 Performance of the WP barriers. 
Performance of the DS is a principal factor since it represents the diversion of seepage away 
from the WP. This factor defines the timing and amount of water transmitted through the DS. 
Performance of the WP barriers is a principal factor for the postclosure safety case because it 
defines the timing and amount of water transmitted into the WP, and thereby controls the rate of 
release of radionuclides.

 1-7  
Table 1-1. Principal Factors, Other Factors, and the PMRs Where Addressed 
Principal Factor 
(Nominal Scenario) 
Process Model Report 
Seepage into drifts Unsaturated Zone Flow and Transport 
Performance of the DS Waste Package Degradation 
Performance of the WP barriers Waste Package Degradation 
Solubility limits of dissolved radionuclides Waste Form (WF) 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 
Dilution of radionuclide concentrations during migration Saturated Zone Flow and Transport 
Other Factors 
(Nominal Scenario) 
Climate Unsaturated Zone Flow and Transport 
Net Infiltration into the mountain Unsaturated Zone Flow and Transport 
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 NFE 
Environments on the DS EBS Degradation, Flow, and Transport 
Environments on the waste package EBS Degradation, Flow, and Transport 
Environments within the waste package WF Degradation 
CSNF WF performance WF Degradation 
DHLW glass WF performance WF Degradation 
DSNF, Navy fuel, Pu disposition WF performance WF Degradation 
Colloid-associated radionuclide concentrations WF Degradation 
In-package radionuclide transport WF Degradation 
Transport through the drift invert EBS 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 
Biosphere transport and uptake Biosphere 
Factors For Disruptive Event Scenarios 
To be determined; see Section 3.5 for preliminary 
considerations (CRWMS M&O 2000w) 
Disruptive Events

 1-8  
General guidelines dictate that the YMP bound the effects of the Other Factors, when possible, 
and perform analyses that are conservative. Principal Factors are to be studied and evaluated 
more thoroughly, using both realistic evaluations and bounding analyses. 
1.4 QUALITY ASSURANCE 
The Quality Assurance (QA) program applies to this analysis. All types of WP designs were 
classified as per Classification of Permanent Item, QAP-2-3 as Quality Level 1. This report 
applies to all of the WP designs included in the Monitored Geologic Repository Classification 
Analyses. Classification of the MGR Uncanistered Spent Nuclear Fuel Disposal Container 
System (CRWMS M&O 1999c) is cited as an example of a waste package type. The 
development of this report is conducted under the activity evaluation 1101213PM7 Waste 
Package Analyses & Models - PMR (CRWMS M&O 1999d), which was prepared per QAP-2-0, 
Conduct of Activities. The results of this evaluation indicate that the activity is subject to the 
Quality Assurance Requirements and Description (DOE 2000) requirements. 
The Waste Package Degradation PMR was prepared in accordance with AP-3.11Q, Technical 
Reports, and reviewed in accordance with AP-2.14Q, Review of Technical Products. The AMRs 
that support this PMR were prepared in accordance with AP-3.10Q, Analyses and Models. 
The status of the data supporting this PMR is included in the supporting AMRs and in the 
Document Input Reference System (DIRS) database. The data are incorporated in the Technical 
Data Management System (TDMS). Data verification and qualification were carried out in 
accordance with procedures AP-3.15Q, Managing Technical Product Inputs and AP-SIII.2Q, 
Qualification of Unqualified Data and the Documentation of Rationale for Accepted Data, 
respectively. 
No software codes were used directly in the development of this PMR. However, this report 
does include the results from software codes used in the supporting AMRs. 
ANSYS, Version 5.3, which is a finite element analysis code used for thermal and stress 
analyses, was used to develop data cited in SCC AMR (CRWMS M&O 2000f). 
pcCRACK, Version 3.1, is a fracture mechanics code used for stress intensity and crack growth 
simulation analyses. This code was also used to develop data cited in the SCC AMR (CRWMS 
M&O 2000f). 
WAPDEG, Version 4.0, is used to determine waste package and DS failure fractions as a 
function of time. Details of the use of this code are provided in the AMR on WAPDEG Analysis 
(CRWMS M&O 2000g). 
1.5 WASTE PACKAGE DEGRADATION PROCESS AND ABSTRACTION MODELS 
The integrated model for WP and DS degradation consists of several individual process-level 
and abstraction models, as well as some numerical analyses.

 1-9  
In all, eight (8) process-level models, six (6) abstraction models, and two (2) engineering 
calculations were developed and documented in individual AMRs or Calculations. These are 
listed below. 
Process-Level Model Analyses: 
 Analysis of Mechanisms for Early Waste Package Failure, Document Identifier 
DI # ANL-EBS-MD-000023 (CRWMS M&O 2000m) 
 Environment on the Surface of the Drip Shield and Waste Package Outer Barrier, 
DI # ANL-EBS-MD-000001 (CRWMS M&O 2000a) 
 Aging and Phase Stability of Waste Package Outer Barrier, DI # 
ANL-EBS-MD-000002 (CRWMS M&O 2000b) 
 General Corrosion and Localized Corrosion of Waste Package Outer Barrier, 
DI # ANL-EBS-MD-000003 (CRWMS M&O 2000c) 
 General Corrosion and Localized Corrosion of Drip Shield, DI # 
ANL-EBS-MD-000004 (CRWMS M&O 2000d) 
 Stress Corrosion Cracking of the Drip Shield, the Waste Package Outer Barrier and the 
Stainless Steel Structural Material, DI # ANL-EBS-MD-000005 (CRWMS 
M&O 2000f) 
 Hydrogen Induced Cracking of Drip Shield, DI # ANL-EBS-MD-000006 (CRWMS 
M&O 2000h) 
 Degradation of Stainless Steel Structural Material, DI # ANL-EBS-MD-000007 
(CRWMS M&O 2000e) 
Abstraction Models and Calculations: 
 WAPDEG Analysis of Waste Package and Drip Shield Degradation, 
DI # ANL-EBS-PA-000001 (CRWMS M&O 2000g) 
 Abstraction of Models of Stress Corrosion Cracking of Drip Shield and Waste Package 
Outer Barrier and Hydrogen Induced Corrosion of Drip Shield, DI # 
ANL-EBS-PA-000004 (CRWMS M&O 2000j) 
 FEPs Screening of Processes and Issues in Drip Shield and Waste Package 
Degradation, DI # ANL-EBS-PA-000002 (CRWMS M&O 2000s) 
 Abstraction of Models for Pitting and Crevice Corrosion of Drip Shield and Waste 
Package Outer Barrier, DI # ANL-EBS-PA-000003 (CRWMS M&O 2000n) 
 Calculation of Probability and Size of Defect Flaws in Waste Package Closure Welds to 
Support WAPDEG Analysis, DI # CAL-EBS-PA-000003 (CRWMS M&O 2000k)

 1-10  
 Calculation of General Corrosion Rate of Drip Shield and Waste Package Outer Barrier 
to Support WAPDEG Analysis, DI # CAL-EBS-PA-000002 (CRWMS M&O 2000i) 
 Abstraction of Models for Stainless Steel Structural Material Degradation, 
DI # ANL-EBS-PA-000005 (CRWMS M&O 2000o) 
 Incorporation of Uncertainty and Variability of Drip Shield and Waste Package 
Degradation in WAPDEG Analysis, DI # ANL-EBS-MD-000036 (CRWMS 
M&O 2000p) 
Results from the last two AMRs (CRWMS M&O 2000o and CRWMS M&O 2000p) are not 
being used as input to the Waste Package Degradation Nominal Case Analysis. These two 
reports are omitted as input since the stainless steel inner shell is not considered to be a corrosion 
barrier. Thus, it is not assigned any performance credit. The AMR on uncertainty and 
variability requires additional data to further develop the model, and will be included in the next 
major revision of the PMR. For this PMR, uncertainty and variability are included in the 
bounding approach used for process-level and abstraction models. 
Figure 1-4 shows the elements of the integrated model, and interrelationships among the various 
process-level models and the AMRs that comprise it. Related phenomena are logically grouped 
in the process-level models. For example, the process-level model for general corrosion (GC) 
and localized corrosion (LC) of the waste package outer barrier (WPOB) includes dry oxidation 
(DOX), humid air corrosion (HAC), and expected environment on the surface. A brief overview 
of each of these models is presented below. Details of the process-level and abstraction models 
are presented in the AMRs and in Chapter 3. 
1.5.1 Environment on the Surface of Drip Shield and Waste Package Outer Barrier 
Information on the surface environment provided below is based on the parent AMR (CRWMS 
M&O 2000a, Section 1.2) and is discussed in greater detail in Section 3.1.3. This process-level 
model addresses the evolution of the chemistry of the water film on the DS and WPOB as a 
function of temperature and relative humidity (RH). The concentrations of aqueous salt 
solutions that can form on the hot waste package surface are being determined experimentally 
and theoretically (based upon chemical thermodynamics). These concentrations define the 
medium for testing WP materials under a worst-case scenario. An example is the development 
of a simulated saturated J-13 water (SSW) with an elevated boiling point (120-127C). 
Hygroscopic salts may be deposited on surfaces by seepage water and episodic water flow, as 
well as by dust and aerosols entrained in ventilation air. The deliquescence point of these salts 
determines the RH at which humid-air and aqueous-phase corrosion commences. 
Abstracted models are developed for the evolution of environments on the exposed surfaces of 
the DS and WPOB as a function of time and location within the repository. These abstracted 
models are in forms that are suitable as inputs to the WAPDEG analysis and include the 
uncertainty and variability of exposure conditions. Additional information on the WAPDEG 
code is presented in Section 2.2.

 1-11  
Figure 1-4. Schematic Representation of the Elements of Process Models Interrelationships Among the Process Models and the AMRs 
Containing These Models 
Drift Environment 
Waste Package and 
Drip Shield Surface Environment 
(Section 3.1.4) 
Aging and Phase Stability of 
Waste Package Outer Barrier 
(Section 3.1.4) 
Manufacturing Data 
Flaw Size Distribution 
(Section 3.1.4) 
Stress Corrosion Cracking 
(Section 3.1.4) 
Weld Stress Mitigation 
(Section 3.1.7) 
Calculation of Weld Defect 
Flaw Probability 
(Section 3.2) 
Abstraction of Stress Corrosion 
Cracking Model 
(Section 3.2.3) 
General and Localized 
Corrosion of Waste Packages (WP) 
and Drip Shield (DS) and SSSM 
(Sections 3.1.5 & 3.1.6) 
Abstraction of General and Localized 
Corrosion Models (Section 3.2) 
Integrated Model for WP and DS 
Degradation WAPDEG Analysis 
(Section 3.2) 
FEPs Screening 
(Section 1.5) 
Hydrogen Induced 
Cracking of DS 
(Section 3.1.8) 
Microbiological Effects 
!
! 
Temperature 
Relative Humidity(RH) 
!
! 
Threshold RH 
Chemistry of the Aqueous Film 
!
! 
Precipitation Kinetics 
Long Range Ordering 
! Mechanisms for Early Failures 
!
! 
Threshold Stress Intensity Factor 
Model 
Film Rupture Model 
!
! 
Laser Peening 
Induction Annealing 
!
! 
Dry Oxidation 
Humid Air Corrosion 
!
! 
General Corrosion 
Localized Corrosion 
No Dripping 
ANL-EBS-PA-000003 
CAL-EBS-PA-000002 
ANL-EBS-PA-000001 
WP-PMR-FLOWCHARTTEMP.CDR 
ANL-EBS-PA-000002 
ANL-EBS-PA-000002 
CAL-EBS-PA-000003 ANL-EBS-PA-000004 
Localized Corrosion 
ANL-EBS-MD-000001 
Localized Corrosion 
ANL-EBS-MD-000002 
ANL-EBS-MD-000023 
ANL-EBS-MD-00005 
ANL-EBS-MD-000003 
ANL-EBS-MD-000004 
ANL-EBS-MD-000007 
Dripping 
ANL-EBS-MD-000005

 1-12  
1.5.2 Mechanisms for Early Failures and Manufacturing Defects 
Information on early failures provided below is based on the parent AMR (CRWMS 
M&O 2000m, Section 6) and is described in greater detail in Section 3.1.2. This analysis 
addresses the potential for early failures of the waste package due to material defects, as well as 
defects from waste package fabrication processes. These fabrication processes include welding. 
The probability of waste package fabrication defects, their uncertainty and variability, and the 
consequences of the defects on waste package failure times (e.g., number of potential failure 
sites and flaw size distribution) are discussed. 
Abstracted calculations are developed for the occurrence and size distribution of defect flaws 
from material and manufacturing defects in the waste package. Abstracted calculations include 
uncertainty and variability of the above properties. 
1.5.3 Aging and Phase Stability of Waste Package Outer Barrier 
Information on aging and phase stability provided below is based on the parent AMR (CRWMS 
M&O 2000b, Section 6) and is described in greater detail in Section 3.1.4. This process-level 
model addresses degradation of the WPOB resulting from exposure to elevated temperatures. In 
the case of Alloy 22 and related materials, such thermal histories can result in the formation of 
precipitates (m, P, s) and other undesirable phases. The precipitates can form within the 
individual grains or at grain boundaries. Precipitation can cause embrittlement, thereby 
increasing susceptibility to damage by rockfall and impact. Since these precipitates may be rich 
in molybdenum and chromium, two of the alloying elements responsible for the high degree of 
passivity of Alloy 22, aging can also result in increased susceptibility to general and LC, as well 
as to SCC. The time-temperature-transformation (TTT) curve and an expression for estimating 
the volume fraction of precipitates in the grain boundary (GB) have been developed for Alloy 22. 
Estimates of uncertainty are made. The effect of aging on corrosion has been addressed, and has 
been determined to be a corrosion enhancement factor of approximately 2.5 for the fully aged 
material. 
1.5.4 General Corrosion and Localized Corrosion 
Information on corrosion provided below is based on three separate AMRs (CRWMS 
M&O 2000c Section 6, 2000d Section 6, and 2000e Section 6) and is described in greater detail 
in Sections 3.1.5 and 3.1.6. Three separate process-level models were developed to address 
general corrosion and localized corrosion of the DS, WPOB, and stainless steel structural support 
respectively. The current design uses Titanium Grade 7 as the DS, Alloy 22 as the WPOB, and 
316NG stainless steel as the inner structural material. Each of these models includes sub-models 
for DOX, HAC, GC in the aqueous phase, and LC in the aqueous phase. Note that dry 
oxidation and dry air oxidation are synonymous terms. While the stainless steel structural 
material is not specifically intended to be a corrosion barrier, it may affect the chemistry of water 
entering the waste package and retard the rate of radionuclide release from the breached waste 
package. Given the limited availability of data for 316NG stainless steel, data for 316L stainless 
steel are used as representative. This is appropriate since the compositions of these two materials 
are very similar, and since their susceptibilities to corrosion are known to be similar. Microbial 
corrosion is addressed in the section devoted to LC (Section 3.1.6.8).

 1-13  
1.5.4.1 Dry Oxidation 
The process-level model for corrosion of the DS and WP materials includes a sub-model for 
DOX. It is assumed that DOX can be treated as a type of GC, with uniform attack. The rates of 
DOX are estimated as a function of temperature, to the extent possible. 
1.5.4.2 Humid Air Corrosion & Vapor Phase Corrosion 
The process-level model for corrosion of the DS and waste package materials accounts for humid 
air and vapor phase corrosion. These modes of corrosion are also treated as a type of GC. To 
the extent possible, rates of humid air and vapor phase corrosion (VPC) are estimated as a 
function of temperature. 
1.5.4.3 Aqueous Phase Corrosion 
The process-level model for aqueous phase corrosion (APC) of the DS and WP accounts for both 
general and localized attack. Two models for the initiation of LC are considered (Methods A 
and B). In Method A, the threshold potential for localized attack of the material is determined 
from experimentally determined cyclic polarization (CP) data obtained with relevant test 
environments. These environments include simulated dilute water (SDW), simulated 
concentrated water (SCW) and simulated acidic concentrated water (SAW) at 30, 60, and 90C, 
as well as SSW at 100 and 120C. The compositions of SDW and SAW are 10X and 1,000X 
concentrations of J-13 well water, respectively. More recently, basic saturated water (BSW) has 
been included in the set of standard test media. Published rates for LC are invoked when the 
expected open circuit corrosion potential exceeds the threshold potential. Since pitting has not 
been observed in laboratory experiments at LLNL, the primary mode of LC is expected to be 
crevice corrosion. If the threshold for LC is not exceeded, it is assumed that the mode of attack 
is GC. GC rates are estimated from various sources of available test data, including weight loss 
measurements from the Long Term Corrosion Test Facility (LTCTF). In Method B, a threshold 
temperature for localized attack at the open circuit corrosion potential is determined from 
published literature data or from tests at elevated temperature and pressure. The same rates of 
LC are used in Method B as used in Method A. This APC model will be applied to each unit 
area of the WP exterior surface. 
Abstracted models have been developed to account for GC of the DS and WP materials. These 
abstractions are very similar to the process-level models. The abstracted models include 
thresholds for initiation of various modes of corrosion, as well as the corresponding rates of 
penetration. The abstracted models are in forms that are suitable for input to the WAPDEG 
analysis. The RH threshold for initiation of HAC and APC are included, as well as the 
electrochemical potential for initiation of localized attack during APC. In the case of the DS and 
WPOB, distributions of GC rates are based upon data from the LTCTF, while published data are 
used as the basis of estimating LC rates. Both general and localized corrosion rates of 316NG 
stainless steel are based upon published data. Estimates of the uncertainty and variability of each 
quantity are provided. When LC occurs, it is assumed to occur over an entire WAPDEG patch 
(element).

 1-14  
1.5.5 Stress Corrosion Cracking 
The process-level model for the SCC is documented in the corresponding AMR (CRWMS 
M&O 2000f, Section 6) and is described more fully in Section 3.1.7. SCC of materials may 
occur when an appropriate combination of material susceptibility, tensile stress and environment 
are present. This process-level model accounts for the possibility of SCC of the DS, the WPOB, 
and the stainless steel structural material. This model also evaluates two alternative methods: 
Method A which is based on threshold stress intensity factor criterion for initiation of SCC (KI > 
KISCC); and Method B which is based upon a threshold stress and a finite rate of SCC 
propagation. The rate of SCC propagation is dependent upon the local environment and the 
stress intensity factor at the crack tip. The stresses for initiation and propagation of SCC are due 
to unannealed closure welds, deformation caused by rock fall, and the weight of the WP. This 
particular analysis requires appropriate stress analysis models and measurements for calculation 
of the through-wall stress distribution for representative cross sections of the WP, including 
unwelded base metal and unannealed welds. This stress distribution is used to calculate a 
corresponding stress intensity factor distribution for flaws that range in size from zero to the 
entire thickness of the wall including the welded region. This stress intensity factor distribution 
is used as input for both Methods A and B. In Method A, SCC initiates at pre-existing flaws that 
develop during fabrication of the waste package, or at flaws that develop during LC. Values of 
KISCC are based upon data published in the technical and scientific literature, or measurements 
made with the double cantilever and compact tensions beam techniques. In Method B, SCC is 
initiated if the threshold stress is exceeded on a smooth surface. Then, the SCC propagation rate 
is calculated as a function of local environment and stress intensity factor. The time-to-failure is 
determined by integrating the calculated propagation rate. As previously discussed, relevant test 
environments include SDW, SCW, and SAW at 30, 60, and 90C, SSW at 100 and 120C, and 
BSW at 110C. 
Abstracted models have been developed for SCC of the WPOB (Alloy 22). These abstracted 
models include: (1) a threshold stress for initiation; (2) a crack growth rate as a function of stress 
and local exposure conditions, including temperature; (3) crack density; and (4) crack 
morphology. Crack morphology includes a description of the size of openings. The abstracted 
models are in a form that is suitable for input to the WAPDEG analysis, and include the 
uncertainty and variability of the above processes. 
Post-weld stress mitigation techniques are being employed to delay the initiation of SCC. The 
techniques under consideration include laser peening and localized induction annealing. These 
processes are accounted for in the model presented here. 
1.5.6 Hydrogen-Induced Cracking of Drip Shield 
This process-level model establishes the conditions under which the DS (Titanium Grade 7) will 
experience hydrogen uptake, thereby leading to the threat of hydrogen embrittlement and 
hydrogen-induced cracking (HIC). This mode of failure is not believed to be a credible threat to 
Alloy 22 and has been, excluded as shown in Section 1.6 below. This is based on the design, 
which includes backfill, and the rate of hydrogen pick up is very low. HIC may be a greater 
threat without backfill, since the titanium DS can be galvanically coupled to carbon steel rock

 1-15  
bolts and mesh. Analysis of the galvanic effects and hydrogen pick up is planned to be included 
in the next version of the AMR. 
1.6 SCREENING OF FEATURES, EVENTS, AND PROCESSES 
The initial set of features, events and processes (FEPs) has been developed for the YMP TSPA 
by combining lists of FEPs identified as relevant to the YMP. This combined list consists of 
1,261 FEP entries from the Nuclear Energy Agency working group, 292 FEPs from YMP 
literature and site studies, and 82 FEPs identified during YMP project staff workshops. The 
FEPs have been identified by a variety of methods including expert judgement, informal 
elicitation, event tree analysis, stakeholder review, and regulatory stipulation. All potentially 
relevant FEPs have been included, regardless of origin. The compilation included FEP entries 
mentioned above and 151 layers, categories and headings. It resulted in a FEP list of 1786 
entries. This approach has led to considerable redundancy in the FEP list, because the same 
FEPs are frequently identified by multiple sources, but it also ensures that a comprehensive 
review of narrowly defined FEPs will be performed. 
Each FEP has been classified as either a Primary or Secondary FEP. The classification resulted 
in the identification of 310 Primary FEPs. Primary FEPs are those for which detailed screening 
arguments are developed. The classification and description of Primary FEPs strives to capture 
the essence of all the Secondary FEPs that map to the primary. Secondary FEPs are either FEPs 
that are completely redundant or that can be aggregated into a single Primary FEP. The Primary 
FEPs have been assigned to associated PMRs. The assignments were based on the nature of the 
FEPs so that the analysis and resolution for screening decisions reside with the subject-matter 
experts in the relevant disciplines. The resolution of other system-level FEPs are documented in 
AMRs prepared by the responsible PMR groups. This section summarizes the screening 
decisions associated with the FEPs for the waste package and DS PMR group. Details of the 
screening processes are documented in the associated AMR. 
The scope of the FEPs screening is to identify the treatment of the Primary FEPs affecting waste 
package and DS degradation. The FEPs that are deemed potentially important to repository 
performance are evaluated, either as components for the TSPA or as separate analyses in the 
AMR. The scope for this activity involves the following two tasks: 
Task 1: Identify FEPs that are considered explicitly in the TSPA (called included FEPs) and the 
AMRs in which these FEPs are addressed 
Task 2: Identify FEPs not included in TSPA (called excluded FEPs) and provide justification 
for why these FEPs do not need to be a part of the TSPA model. 
Of the original list of FEPs, twenty-eight have been identified as Primary FEPs in relationship to 
waste package and DS degradation. The approach used for this analysis is a combination of 
qualitative and quantitative screening. The analyses are based on the criteria provided by the 
NRC in the proposed 10 CFR Part 63 (Dyer 1999) and by the U.S. Environmental Protection 
Agency in the proposed 40 CFR Part 197 (64 FR 46976) to determine whether or not each FEP 
should be included in the TSPA. For FEPs that are excluded from the TSPA based on NRC or 
U.S. Environmental Protection Agency criteria, the screening argument includes a summary of

 1-16  
the basis and results that indicate either low probability or low consequence. As appropriate, 
screening arguments cite work performed outside this activity, such as in other AMRs. For FEPs 
that are included in the TSPA, the TSPA disposition includes a reference to the AMR that 
describes how the FEP has been incorporated in the process models or the TSPA abstraction 
models. 
The FEPs screening analysis results for the twenty-eight Primary FEPs relevant to waste package 
and DS degradation processes are summarized in Table 1-2. This table shows the FEP number, 
FEP name, screening decision (include/exclude), and a synopsis of the screening argument. 
Details of the screening processes and arguments are planned to be included in the next revision 
of the FEPs AMR. 
1.7 RELATIONSHIP TO OTHER PROCESS MODEL REPORTS AND DOCUMENTS 
This PMR provides information about important factors affecting waste package lifetime such as 
the thermal, hydrologic, and geochemical processes acting on the waste package surface. The 
PMR uses inputs from other documents such as LADS report (EDA II design) and thermal 
analyses. The emphasis of the discussion of model inputs and outputs is on information needed 
for the assessment of postclosure performance. The waste package degradation PMR supports 
the TSPA and other major Project milestones, such as the Site Recommendation (SR) and the 
License Application (LA). 
While the scope of this PMR is to address degradation of the WP and the DS, other PMRs (such 
as the EBS PMR) address other aspects of DS and EBS component performance.

 1-17  
Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation 
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
1.1.03.01.00 
Error in waste or 
backfill 
emplacement 
Exclude 
Exclude based on low probability constrained by the design 
requirements. The design requirements assume that the repository 
will be constructed, operated, and closed according to the regulatory 
requirements applicable to the construction, operation, and closure 
period and that deviations from design will be detected and 
corrected. Details of the basis will be documented in the next 
revision of FEPs AMR. 
1.2.02.03.00 
Fault movement 
shears waste 
container 
Exclude 
Exclude based on Low probability. Detailed description of the basis 
for the screening decision is given in the Disruptive Events FEPs 
AMR (CRWMS M&O 2000v). 
1.2.03.02.00 
Seismic vibration 
causes container 
failure 
Exclude 
Exclude based on low consequence constrained by the design 
requirements of WP and DS. This FEP was originally directed at 
vertical emplacement of containers in boreholes. The current design 
is to place large containers horizontally in the drifts with drip shield 
and backfill over the drip shield. This design removes the possibility 
of container-rock wall contact due to seismic activity. In addition, 
preliminary analyses indicate that even under most severe seismic 
vibration, the WP will not undergo failure. Details of the basis will be 
documented in the next revision of FEPs AMR. For the DS, the 
design criteria require that the DS be designed to withstand a 
Category 2 design basis earthquake without rupturing or parting 
between individual DS units and without contacting waste packages 
(CRWMS M&O 2000t, System Design Criteria 1.2.1.16 and 1.2.1.17). 
This FEP is also addressed in the Disruptive Events FEPs AMR 
(CRWMS M&O 2000v). 
This FEP addresses CLST KTI IRSR Subissues 2 and 6 (see 
Table 4-1). 
1.2.04.04.00 
Magma interacts 
with waste Include 
Magma interactions with the waste are included in the TSPA as part 
of disruptive events analyses. This FEP is addressed in the 
Disruptive Events FEPs AMR (CRWMS M&O 2000v). 
This FEP addresses CLST KTI IRSR Subissues 2 (see Table 4-1). 
2.1.03.01.00 
Corrosion of waste 
containers 
Include 
Corrosion is the most likely process leading to degradation and 
failure of WPs and DSs in the repository. All significant corrosion 
modes are included in WP/DS corrosion modeling. These include 
dry-air oxidation, humid-air corrosion, and aqueous corrosion 
processes such as general corrosion, localized (pitting and crevice) 
corrosion, stress corrosion cracking, hydrogen-induced corrosion, 
and microbiologically influenced corrosion. WP/DS corrosion is 
modeled with the Waste Package Degradation computer code 
(WAPDEG) (CRWMS M&O 1999e). WAPDEG produces waste 
package/drip shield degradation profiles consisting of the fraction of 
waste packages/drip shields failed versus time and the average (per 
failed waste package/drip shield) number of penetration openings 
versus time. The degradation profiles are used as input into the 
TSPA model. 
This FEP is the subject of this PMR and addressed in Sections 3.1 
and 3.2. This FEP addresses CLST KTI IRSR Subissues 1, 2 and 6 
(see Table 4-1).

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-18  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.03.02.00 
Stress corrosion 
cracking of waste 
containers 
Include for WP; 
Exclude for DS 
Include for waste package. Because, among other exposure 
condition parameters, tensile stress is required to initiate stress 
corrosion cracking (SCC), and the WP closure welds are the only 
places with such tensile stresses, only the WP closure welds are 
considered for SCC (CRWMS M&O 2000f). The other fabrication 
welds of the WP will be fully annealed before waste is loaded into the 
disposal containers, and thus are not subject to SCC. WP SCC is 
modeled with the WP Degradation (WAPDEG) computer code 
(CRWMS M&O 1999e). The degradation profiles are used as input 
into the TSPA model (see FEP 2.1.03.01.00). 
Exclude for drip shield based on low consequence. All fabrication 
welds of the drip shield will be fully annealed before placed in the 
emplacement drift, and thus are not subject to SCC. Also, the major 
sources of stresses in the drip shield induced by backfill and 
earthquakes are not significant for SCC (CRWMS M&O 2000f, 
Section 5, Assumption 1). Additionally, even if it occurs, the SCC 
cracks in the drip shield, which are likely tight openings and filled 
with corrosion products and/or other precipitates, is not expected to 
compromise significantly the intended function of the drip shield (i.e., 
preventing the dripping water from contacting the waste package). 
This FEP is addressed in Section 3.1.7. This FEP addresses CLST 
KTI IRSR Subissues 1 and 2 (see Table 4-1). 
2.1.03.03.00 Pitting of waste 
containers 
Include 
Localized (pitting and crevice) corrosion is one of a number of 
potential corrosion mechanisms that could lead to eventual 
compromise of WPs and/or DSs in the repository. As discussed in 
detail in the companion abstraction AMR, localized corrosion of WP 
outer barrier (Alloy 22) and DS is not likely to occur under repositoryrelevant 
exposure conditions (CRWMS M&O 2000n). Localized 
corrosion initiation and propagation models are included in TSPA as 
part of WP degradation analysis. Waste container localized 
corrosion is modeled with the Waste Package Degradation 
(WAPDEG) computer code (CRWMS M&O 1999e). The degradation 
profiles are used as input into the TSPA model (see FEP 
2.1.03.01.00). 
This FEP is addressed in Section 3.1.7. This FEP addresses CLST 
KTI IRSR Subissues 1 and 2 (see Table 4-1). 
2.1.03.04.00 Hydride cracking of 
waste containers 
Exclude for DS; 
Exclude for WP 
Exclude for drip shield based on low consequence. Hydrogeninduced 
cracking (HIC) of drip shield is a potential degradation 
mechanism that could cause catastrophic failure of drip shield if the 
hydrogen uptake in the titanium drip shield is greater than the critical 
hydrogen concentration (CRWMS M&O 2000h). In the repository 
design of backfill placed over the drip shield, crevice corrosion and 
passive general corrosion of the drip shield are two feasible 
processes in the repository that could lead HIC failure of the drip 
shield. Because the drip shield will not be subject to crevice 
corrosion under the exposure conditions anticipated in the repository 
(CRWMS M&O 2000n), general corrosion is the only mechanism that 
could cause HIC in the drip shield. Bounding analyses have shown 
that the time that the hydrogen uptake concentration reaches the 
critical hydrogen concentration under the exposure conditions 
anticipated in the repository (CRWMS M&O 2000h) is greater than 
the time required to initiate the drip shield breach by general 
corrosion (about 20,000 years) (see Section 3.2.5). Therefore, HIC 
is not a limiting degradation process that could affect the drip shield 
performance in the repository, and is excluded based on low 
consequence.

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-19  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.03.04.00 
(Contd) 
Hydride cracking of 
waste containers 
Exclude for DS; 
Exclude for WP 
Exclude for waste package based on low probability. HIC of the 
waste container outer barrier (Alloy 22) is not considered a possible 
degradation mechanism under repository-relevant exposure 
conditions. Handbook data (ASM International 1987, pp. 650-651) 
indicate that fully annealed nickel-base alloys such as Alloy 22 may 
be immune to hydrogen-induced embrittlement (hydride cracking). 
The susceptibility to hydride cracking may be enhanced only when 
the strength level of this alloy is increased either by cold working or 
by aging at a temperature of 540C at which ordering and/or grainboundary 
segregation can occur. The susceptibility to cracking will be 
reduced with decreasing strength level and correspondingly with 
increasing aging temperature. However, since the waste package 
temperature will be sufficiently less than 540C, the possibility of HIC 
in Alloy 22 will be very remote. Details of the basis will be 
documented in the next revision of FEPs AMR. Therefore, this FEP 
for the waste package outer barrier is excluded on the basis of low 
probability. 
This FEP is addressed in Section 3.1.8. This FEP addresses CLST 
KTI IRSR Subissue 1 (see Table 4-1). 
2.1.03.05.00 
Microbiallymediated 
corrosion 
of waste container 
Include for WP; 
Exclude for DS 
Include for waste package. Microbiologically influenced corrosion 
(MIC) is included in TSPA as part of waste package degradation 
analysis. The potential effect of MIC on waste container corrosion is 
analyzed with an enhancement factor approach, assuming MIC 
increases corrosion penetration rate. In this approach, the abiotic 
corrosion rate is multiplied by the enhancement factor when the 
exposure conditions in the emplacement drift warrant significant 
microbial activity (CRWMS M&O 2000c). Waste container 
microbiologically influenced corrosion is modeled with the Waste 
Package Degradation (WAPDEG) computer code (CRWMS M&O 
1999e). The degradation profiles are used as input into the TSPA 
model (see FEP 2.1.03.01.00). 
Exclude for drip shield based on low consequence. Quantitative data 
on MIC of drip shield materials such as titanium (Ti) Grades 7 and 16 
are not available from the literature. It is considered that the 
candidate titanium alloy is immune to MIC (CRWMS M&O 2000s). 
The MIC is excluded for the drip shield (Ti- Grade 7) corrosion 
modeling in the process model analysis (CRWMS M&O 2000d). 
This FEP is addressed in Sections 3.1.5 and 3.1.6. This FEP 
addresses CLST KTI IRSR Subissue 1 (see Table 4-1). 
2.1.03.06.00 Internal corrosion 
of waste container 
Exclude 
Exclude based on low consequence. The waste container could be 
corrosively attacked from inside if corrosive condition exists in the 
inside. After being loaded with waste, the waste containers are to be 
filled with the inert gas (helium) prior to the closure, displacing water 
and oxygen inside the container. The helium gas-filled condition will 
provide an inert environment inside the container, and will maintain 
the environment for insignificantly low corrosion rates. Prior to the 
breach of the containers, there should be no or minimum corrosion 
because of the inert environment inside the container. The most 
likely cause of any possible internal corrosion is the residual moisture 
remaining in the waste package at the time of emplacement. The 
potential source of this moisture is believed to be primarily 
waterlogged failed fuel rods. Analyses have indicated that the 
amount of moisture available to cause internal corrosion is very 
limited and even with very conservative assumptions, the potential 
for degradation of the container materials is very remote (CRWMS 
M&O 2000s).

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-20  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.03.07.00 
Mechanical impact 
of waste container Exclude 
Excluded based on low consequence constrained by the design 
requirements. Mechanical damage of the waste container and drip 
shield by rockfall is discussed in greater detail under FEP 
2.1.07.01.00  Rockfall (large block). Additionally, the Emplacement 
Drift System design criteria require that the drip shield be designed to 
withstand a 13 metric tons rock falling onto the top of the backfill 
without rupturing the drip shield or parting between individual drip 
shield units and without contacting waste packages (CRWMS M&O 
2000t, System Design Criteria 1.2.1.14 and 1.2.1.15). In view of the 
above rationale, this FEP is excluded based on low consequence. 
Mechanical damage of the waste container and drip shield by ground 
motion during seismic events is discussed in greater detail under 
FEP 1.2.03.02.00  Seismic Vibration Causes Waste Container and 
Drip Shield Failure. In addition, the Emplacement Drift System 
design criteria require that the drip shield be designed to withstand a 
Category 2 design basis earthquake without rupturing or parting 
between individual drip shield units and without contacting waste 
packages (CRWMS M&O 2000t, System Design Criteria 1.2.1.16 
and 1.2.1.17). In view of the above rationale, this FEP is excluded 
based on low consequence. 
A calculation of the maximum stresses developed in the waste 
package due to internal pressurization as a result of fuel rod rupture 
at 400C is less than the ASME code (ASME 1995, Section II); 
requirements for the allowable tensile strength (CRWMS M&O 
2000x, Table 6-3). Therefore, with the current robust waste 
container design, the pressurization of the internal gas under the 
expected repository condition would not cause mechanical damage 
to the waste container. In general, corrosion products have greater 
volume than the bare metal. When the corrosion products form in a 
tightly confined space, the volume increase by the corrosion products 
generates swelling pressure to the surrounding and thus could cause 
mechanical damage to the surrounding. In the current design of 
waste package and engineered barrier system in the emplacement 
drift, there is no possibility of forming such a tightly confined space 
such that the swelling corrosion products could cause mechanical 
damage to the Alloy 22 outer barrier. Therefore, mechanical 
damages by internal gas pressure and swelling corrosion products 
are excluded based on low consequence. 
This FEP addresses CLST KTI IRSR Subissue 2 (see Table 4-1). 
2.1.03.08.00 
Juvenile and early 
failure of waste 
containers 
Include/exclude 
for WP; Exclude 
for DS 
Include manufacturing and welding defects in waste container 
degradation analysis. The major effect of pre-existing manufacturing 
defects is to provide sites for crack growth by stress corrosion 
cracking (SCC), potentially leading to an early failure. Among other 
exposure condition parameters, tensile stress is required to initiate 
SCC (CRWMS M&O 2000f). Effect of manufacturing and welding 
defects on waste container failure is addressed by including the 
defect flaws in SCC analysis (CRWMS M&O 2000g). As discussed 
in FEP 2.1.03.02.00, only the closure welds are considered for SCC. 
Accordingly, the defects in the closure welds will be considered in 
TSPA analysis through the SCC analysis. 
Exclude manufacturing and welding defects in drip shield 
degradation based on low consequence. Because all the fabrication 
welds in drip shields will be fully annealed before placement in the 
emplacement drift, drip shields are not subject to SCC (CRWMS 
M&O 2000f). Also, other sources of stresses in the drip shield 
induced by backfill and earthquakes are insignificant to SCC 
(CRWMS M&O 2000f, Section 5, Assumption 1). Thus 
manufacturing defects in drip shield are excluded from TSPA 
analysis based on low consequence.

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-21  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.03.08.00 
(Contd) 
Juvenile and early 
failure of waste 
containers 
Include/exclude 
for WP; Exclude 
for DS 
Exclude potential early failure of waste container and drip shield from 
improper quality control during the emplacement based on low 
probability. After emplacement the waste containers and drip shields 
will be inspected. If there is any damage, they would be retrieved 
(CRWMS M&O 1998b). Thus, the probability of having potential early 
failure of waste container and drip shield from improper quality 
control during the emplacement will be extremely small and is 
excluded from the TSPA analysis based on low probability. 
This FEP is addressed in Sections 3.1.2, 3.1.7, 3.2.3, and 3.2.4. 
This FEP addresses CLST KTI IRSR Subissues 1 and 2 (see 
Table 4-1). 
2.1.03.09.00 Copper corrosion Exclude 
Exclude based on low probability. Copper is not considered for use 
as an engineered barrier at Yucca Mountain, and thus this FEP is not 
considered relevant for the Yucca Mountain TSPA. There will be 
zero probability to have a copper waste container in the repository. 
2.1.03.10.00 Container healing Exclude 
Exclude based on low consequence. Plugging (or healing) of 
corrosion holes or pits in waste container by corrosion products and 
mineral precipitates is a potentially possible process in the repository. 
However, there are large uncertainties associated with the 
quantification of the effect of the process on water flow and 
radionuclide transport through the openings. Because of this, 
potential performance credit from the plugging (or healing) of the 
corrosion penetration openings are not taken into account in TSPA 
analysis. This FEP is not applicable to waste container corrosion. 
2.1.03.11.00 Container form Exclude 
Exclude based on low consequence. The waste package/drip 
shield/repository design has been standardized for the Yucca 
Mountain Project (CRWMS M&O 1999a). While there is more than 
one waste package design expected to be used in the proposed 
repository, they are all similar in their design, the fabrication 
methodology used, and their dimensions (CRWMS M&O 2000u, 
p. 1). Therefore, there will be little variation in strength, dimensions, 
and shape of the waste packages used in the proposed repository. 
Effects of different waste forms (CSNF, DSNF, and DHLW) on heat 
dissipation and physical and chemical conditions in the vicinity the 
waste packages are indirectly included in the TSPA analysis through 
different thermal-hydrologic-geochemical responses and their 
impacts on corrosion processes. Waste package and drip shield 
degradation modes are modeled with the Waste Package 
Degradation computer code (WAPDEG) (CRWMS M&O 1999e, 
2000g). The WAPDEG code makes use of thermal-hydrologicgeochemical 
time histories for a given simulation, which encompass 
the variability in exposure conditions that are due in part to different 
container forms. 
2.1.03.12.00 
Container failure 
(long term) 
Include 
Long-term corrosion degradation and failure of waste containers and 
drip shields in the repository are included in TSPA as part of waste 
package degradation analysis. The analysis accounts for the major 
degradation mechanisms and processes that are likely in the 
repository. The waste container and drip shield corrosion are 
modeled with the Waste Package Degradation computer code 
(WAPDEG) (CRWMS M&O 1999e, 2000g). WAPDEG produces 
waste package degradation profiles consisting of the fraction of 
waste packages/drip shields failed versus time and the average (per 
failed waste package/drip shield) number of penetration openings 
versus time. The degradation profiles are used as input into the 
TSPA model. 
This FEP is the subject of this PMR and addressed in Sections 3.1 
and 3.2. This FEP addresses CLST KTI IRSR Subissues 1, 2 and 6 
(see Table 4-1).

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-22  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.06.06.00 Effects and 
degradation of DS 
Include/exclude 
Include physical and chemical degradation processes in drip shield 
degradation. Physical and chemical degradation processes for the 
drip shield are included in TSPA as part of waste package and drip 
shield degradation analyses. The analyses accounts for the major 
degradation mechanisms and processes that are likely in the 
repository (CRWMS M&O 2000g; also see Section 3.2.5). This 
includes corrosion-induced and other degradation and failure 
processes. The waste container and drip shield degradation are 
modeled with the Waste Package Degradation computer code 
(WAPDEG) (CRWMS M&O 1999e, 2000g). The degradation profiles 
are used as input into the TSPA model (see FEP 2.1.03.01.00). In 
addition, the model is designed to account for the effect on the drip 
shield of non-corrosion degradation processes such as rockfall or 
seismic motion. These effects are considered for both the intact and 
degraded states of the drip shield. 
Exclude rockfall in drip shield degradation based on low 
consequence. Mechanical damage of the drip shield by rockfall is 
discussed in greater detail under FEP 2.1.07.01.00  Rockfall (large 
block). In addition, the Emplacement Drift System design criteria 
require that the drip shield be designed to withstand a 13 metric tons 
rock falling onto the top of the backfill without rupturing the drip shield 
or parting between individual drip shield units and without contacting 
waste packages (CRWMS M&O 2000t, System Design Criteria 
1.2.1.14 and 1.2.1.15). In view of the above rationale, this FEP is 
excluded based on low consequence. 
Exclude ground motion in drip shield degradation based on low 
consequence. Mechanical damage of the drip shield by ground 
motion during seismic events is discussed in greater detail under 
FEP 1.2.03.02.00  Seismic Vibration Causes Waste Container and 
Drip Shield Failure. In addition, the Emplacement Drift System 
design criteria require that the drip shield be designed to withstand a 
Category 2 design basis earthquake without rupturing the drip shield 
or parting between individual drip shield units and without contacting 
waste packages (CRWMS M&O 2000t, System Design Criteria 
1.2.1.16 and 1.2.1.17). In view of the above rationale, this FEP is 
excluded based on low consequence. 
This FEP is addressed in Sections 3.1.3, 3.1.5, 3.1.6, 3.1.8, and 
3.2.5. This FEP addresses CLST KTI IRSR Subissues 1 and 2 (see 
Table 4-1). 
2.1.06.07.00 
Effects of material 
interfaces 
Include 
Waste container and drip shield corrosion degradation analysis 
includes the effects of material interfaces in the repository. The 
thermal-hydrologic-geochemical condition analyses in the repository 
include effects of materials present in the emplacement drift, 
including waste package, drip shield and backfill. The corrosion 
degradation analysis includes effect on corrosion processes of 
backfill gravel contacting the drip shield and waste container 
(CRWMS M&O 2000g). 
This FEP is addressed in Sections 3.1.3, 3.1.5, 3.1.6, and 3.2.5. 
This FEP addresses CLST KTI IRSR Subissue 1 (see Table 4-1). 
2.1.07.01.00 
Rockfall (large 
block) Exclude 
Exclude based on low consequence. This FEP is also addressed in 
the Disruptive Events FEPs AMR (CRWMS M&O 2000v) and 
excluded based on low consequence. The Emplacement Drift 
System design criteria require that the drip shield be designed to 
withstand a 13 metric tons rock falling onto the top of the backfill 
without rupturing the drip shield or parting between individual drip 
shield units and without contacting waste packages (CRWMS M&O 
2000t, System Design Criteria 1.2.1.14 and 1.2.1.15). In view of the 
above rationale, this FEP is excluded based on low consequence. 
This FEP addresses CLST KTI IRSR Subissue 2 (see Table 4-1).

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-23  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.07.05.00 
Creeping of 
metallic materials 
in the EBS 
Exclude 
Exclude based on low consequence. Creep data were not found for 
Alloy 22 (ASTM B 575 N06022) or Titanium Grade 7. Screening 
argument is developed using the creep data for Alloy 625 (ASTM B 
443  93e1.1995) whose composition is very similar to Alloy 22. 
Creep data for Alloy 625 are reported for temperatures of 1200F 
(650C) and higher (Haynes International 1993, p. 5). This 
temperature is well above the expected temperatures for repository 
operations. At the repository temperatures, the rate of creep is 
expected to be very low, because the stresses required to cause 
creep are not present (CRWMS M&O 2000s). 
This FEP addresses CLST KTI IRSR Subissue 2 (see Table 4-1). 
2.1.09.03.00 Volume increase of 
corrosion products 
Exclude 
Exclude based on low consequence. For the waste package and 
EBS emplacement design considered for the repository, the volume 
increase by corrosion products from the corroding materials in the 
emplacement drift is not expected to affect the stress state of drip 
shields or waste containers, or other EBS materials in the drift. 
Therefore, this FEP is excluded based on low consequence. In 
addition, FEP 2.1.03.07.00  Mechanical Impact on the Waste 
Container and Drip Shield also deals with corrosion products, 
namely, the internal and external forces caused by swelling. This 
portion of the FEP is also excluded. 
This FEP addresses CLST KTI IRSR Subissue 2 (see Table 4-1). 
2.1.09.09.00 
Electrochemical 
effects in waste 
and EBS 
Exclude 
Exclude based on low consequence. Electrochemical reactions 
between the materials in the emplacement drift could establish an 
electrical field within the drift. Both the Titanium Grade 7 used for the 
drip shield and Alloy 22 for the waste-container outer barrier are 
highly corrosion resistant. Thus significant perturbations to the 
electrochemical system in the drift are required to increase corrosion 
potential of the materials and to affect their corrosion behaviors 
(CRWMS M&O 2000c, 2000d). In the current design of the 
engineered barrier system in the emplacement drift, the potential 
electrical fields that could be set up in the drift is not expected to be 
large enough to induce unexpected corrosion behaviors of the drip 
shield or the waste-container outer barrier. Therefore, this FEP is 
excluded on the basis of low consequence. 
2.1.10.01.00 Biological activity in 
waste and EBS 
Include for WP; 
Exclude for DS 
Include for waste package. Microbes can influence the initiation and 
rate of waste container corrosion. Alloy 22 (waste container outer 
barrier material) could be subject to microbiologically influenced 
corrosion (MIC) depending on the microbial activity in the repository. 
MIC is included in TSPA as part of waste package degradation 
analysis. The potential effect of MIC on waste container corrosion is 
analyzed with an enhancement factor approach, assuming MIC 
increases corrosion penetration rate. In this approach, the abiotic 
corrosion rate is multiplied by the enhancement factor when the 
exposure conditions in the emplacement drift warrant significant 
microbial activity (CRWMS M&O 2000c). Waste container MIC is 
modeled with the Waste Package Degradation (WAPDEG) computer 
code (CRWMS M&O 1999e, 2000g). The degradation profiles are 
used as input into the TSPA model (see FEP 2.1.03.01.00). 
Exclude for drip shield based on low consequence. Quantitative data 
on MIC of drip shield materials such as titanium (Ti) Grades 7 and 16 
are not available from the literature. It is considered that the 
candidate titanium alloy is immune to MIC (CRWMS M&O 2000s). 
The MIC is excluded for the drip shield (Ti- Grade 7) corrosion 
modeling in the process model analysis (CRWMS M&O 2000d). 
Therefore, this FEP is excluded for drip shield based on low 
consequence. 
This FEP is addressed in Sections 3.1.5 and 3.1.6. This FEP 
addresses CLST KTI IRSR Subissue 1 (see Table 4-1).

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-24  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.11.05.00 
Differing thermal 
expansion of 
repository 
components 
Exclude 
Exclude based on low consequence. The current drift design 
minimizes the thermal gradient and temperatures where differential 
expansion occurs (due to differences in component/rock properties) 
will not be reached. To mitigate any possibility of thermal stresses as 
a result of differing thermal expansion coefficients of the waste 
package materials, the waste package barriers will be constructed 
with a gap up to 4 mm between the outer barrier (Alloy 22) and inner 
barrier (316 NG stainless steel) (CRWMS M&O 2000s). Therefore, 
this FEP is excluded based on low consequence. 
This FEP addresses CLST KTI IRSR Subissue 2 (see Table 4-1). 
2.1.11.06.00 
Thermal 
sensitization of 
waste containers 
increases fragility 
Include 
Alloy 22 is known to be subject to aging and phase instability when 
exposed to elevated temperatures. The processes involve 
precipitation of different secondary phases and restructuring of the 
microstructure. The affected material exhibits increased brittleness 
and decreased resistance to corrosion, especially to localized 
corrosion and stress corrosion cracking (SCC) (CRWMS M&O 
2000b). Preliminary testing results have shown that the waste 
container outer barrier (Alloy 22) could be subject to aging and phase 
instability under repository thermal conditions (CRWMS M&O 
2000b). Effects of potential thermal sensitization of the waste 
package outer barrier are included in TSPA as part of waste package 
degradation analysis. The effects are accounted for with a corrosion 
enhancement factor that is applied to the corrosion rate for the nonaffected 
condition (CRWMS M&O 2000c). The waste container 
thermally induced corrosion mechanisms are modeled with the 
Waste Package Degradation (WAPDEG) computer code (CRWMS 
M&O 1999e, 2000g). The degradation profiles are used as input into 
the TSPA model (see FEP 2.1.03.01.00). 
This FEP is addressed in Sections 3.1.4, 3.1.5 and 3.1.6. This FEP 
addresses CLST KTI IRSR Subissues 1 and 2 (see Table 4-1). 
2.1.12.13.00 
Gas generation 
(H2) from metal 
corrosion 
Exclude 
Exclude based on low consequence. The Yucca Mountain repository 
is in the unsaturated zone and expected to be connected to the 
atmosphere and to be operating under oxidizing conditions. 
Therefore any gases generated by metal corrosion would escape 
from the drifts. Hydrogen (H2) gas could be generated from the 
reduction of water as a result of corrosion reactions underway (more 
likely under reducing conditions). This hydrogen gas generation 
would be less likely under oxidizing conditions that are assumed for 
the repository. Furthermore, the hydrogen gas generation rate, if 
occur, would be very low for the current repository design because of 
very low corrosion rates of Alloy 22 (waste container outer barrier) 
and titanium Grade 7 (drip shield). Alloy 22 and titanium Grade 7 
were selected because of their excellent resistance to pitting and 
crevice corrosion and stress corrosion cracking. Additionally, the iron 
content in Alloy 22 is very low, therefore the issue of iron corrosion is 
not relevant to the current design. With the waste package materials, 
the hydrogen that may be produced from their corrosion in the 
repository is expected to be small. Therefore, this FEP is excluded 
based on low consequence.

Table 1-2. Primary FEP Summary for Waste Package and Drip Shield Degradation (Continued) 
 1-25  
FEP Number FEP Title 
Screening 
Decision Reason for Include/Exclude Decision 
2.1.13.01.00 Radiolysis Exclude 
Exclude based on low consequence. When significant radiation 
fields and stable liquid water exist on the surface of waste container 
and drip shield, radiolysis of water and some dissolved species in the 
water could produce highly oxidizing and corrosive fluids. Radiolysis 
due to gamma and neutron radiation is possible while the container is 
intact. Alpha and beta radiolysis will be of importance after canister 
failure, when water gets in close contact with the waste form matrix. 
Electrochemical testing results simulating the radiation exposure 
conditions that are expected in the repository have shown that the 
amount of the corrosion potential increase of Alloy 22 (waste 
container outer barrier) and Titanium Grade 7 (drip shield) from the 
radiolysis should not affect their localized corrosion behavior 
(CRWMS M&O 2000c, 2000d). Therefore, the radiolysis effect on 
waste-container outer barrier and drip shield is excluded in TSPA 
analysis based on low consequence. 
This FEP is addressed in Sections 3.1.5 and 3.1.6. This FEP 
addresses CLST KTI IRSR Subissue 1 (see Table 4-1). 
2.1.13.02.00 Radiation damage 
in waste and EBS 
Exclude 
Exclude based on low consequence. The dose rate of gamma 
radiation at the surface of the waste package and drip shield is 
determined by the concentration of the various radioactive isotopes 
within the waste package (as functions of age, type, and length of 
time the fuel was in the reactor, etc.) and the attenuation provided by 
the engineered barriers (ASM International 1987, pp. 971-974; 
CRWMS M&O 2000s). However, the type and dose rates of 
radiation emitted from decaying wastes are not sufficient to degrade 
the metallurgical and mechanical properties of the waste package 
and drip shield materials, and their protective/passive layers 
(CRWMS M&O 2000s). The only significant effect of radiation will be 
the change in external environment due to groundwater radiolysis 
(ASM International 1987, pp. 971-974) (see FEP 2.1.13.01.00). 
Therefore, this FEP is excluded based on low consequence.

 1-26  
INTENTIONALLY LEFT BLANK

 2-1  
2. EVOLUTION OF THE PROCESS MODEL 
2.1 BACKGROUND 
The overall performance of the WP and DS materials has been identified as a principal factor in 
the performance of the repository. It is expected that the lifetime goals for the DS and WP may 
be increased in the future. Therefore, materials and designs that prolong service life are sought 
continuously. 
The reference design used in the viability assessment (VA) has been estimated to experience first 
through-wall failure by pit penetration in about 2,700 years, with about 1% of the packages 
failing in approximately 10,000 years. This estimate is based upon the waste package 
degradation model (WAPDEG) used as input to Total System Performance Assessment-Viability 
Assessment (TSPA-VA) Analyses Technical Basis Document (CRWMS M&O 1998a, TSPA-VA, 
Chapter 5). However, the goals of the YMP have been continuously pushed towards longer WP 
lifetimes, thereby requiring that the repository exceed performance requirements of the VA 
design by a significant margin. Accordingly, a selection process for alternative materials and 
designs intended to provide higher levels of confidence for an extended WP lifetime was 
undertaken. As mentioned in the LADS report, this process resulted in the selection of a doublewalled 
WP placed under a protective DS made of Titanium Grade 7 (CRWMS M&O 1999a). 
The outer wall of the WP is corrosion-resistant Alloy 22, with an inner wall of stainless steel 
(316NG) that serves as a structural support. This new design is known as EDA II 
(CRWMS M&O 1999a). The selection of this new design configuration, coupled with the 
selection of new materials, has necessitated the development of new models to predict 
penetration rates. Individual component models (sub-models) are documented in the individual 
Analysis and Model Reports (AMRs) (see Section 1.5 for the topics in each AMR). Each AMR 
is provided as an input to the WP Degradation PMR, as well as to the TSPA for Site 
Recommendation. 
2.2 PREVIOUS TREATMENT OF WASTE PACKAGE DEGRADATION MODELING 
Modeling of WP degradation has evolved over the past decade along with changes in materials 
selected for its containment barriers. Early WP designs consisted of thin-walled stainless steel 
canisters with heavy-walled carbon steel overpacks, and were designed for emplacement in salt, 
basalt or tuff repositories. The design thickness of the overpack component was the sum of the 
required structural thickness, plus the corrosion allowance necessary to assure that the required 
structural thickness will survive the required containment period. The corrosion allowance was 
established on the basis of the calculated temperature profile of the WP surface during the 
containment period, the unexpected presence of an unlimited quantity of anoxic brine, and the 
resulting corrosion rate. 
In late 1987, the U.S. Congress passed The Nuclear Waste Policy Amendments Act, As 
Ammended. With Appropriations Acts Appended (DOE 1995), which reduced the number of 
potential repository sites to be characterized to one: Yucca Mountain. Prior to this event, work 
on the WP design for Yucca Mountain had followed the same rationale as that for salt and basalt 
repositories. In fact, the initial conceptual design of the WP developed in early 1983 was the 
same as that for the other two repositories. However, it was recognized that the expected 
conditions in Yucca Mountain were quite different from the other two in that the repository was

 2-2  
located in the unsaturated zone. The environment in this zone, although not firmly established, 
was expected to be oxidizing, but dry with low humidity most of the time. The design 
temperature for the WP surfaces was not expected to exceed 250C. Liquid water was expected 
to be present only under transient conditions, and its composition was not expected to be very 
aggressive from a corrosion standpoint. 
The limitations of 304L stainless steel, from the standpoint of SCC and LC had been recognized 
from early on. Consequently, alternative materials were being sought. In 1993 
(CRWMS M&O 1994), the design was changed from thin-walled containers emplaced in bore 
holes to drift-emplaced robust multibarrier WP. The proposed materials were Alloy 825 as the 
inner barrier and a corrosion allowance material (CAM) such as weathering steel as an outer 
barrier. Degradation modeling of this WP design included only APC. It was assumed that no 
corrosion would occur above the temperature at which liquid-phase water could not exist on the 
WP surface. 
Model enhancements were incorporated in 1995 (CRWMS M&O 1995) and were based upon the 
same double-wall WP design that was used in 1993. This model was an initial attempt to 
account for HAC and APC. The APC model had components that simulated pitting corrosion 
and galvanic coupling of the CAM and corrosion resistant materials (CRM). This model 
included estimates of the variability in WP corrosion, including package-to-package and patchto-
patch variability. Estimates of the uncertainty in the threshold RH for initiation of HAC and 
APC were also made. An empirical model for GC and LC of the CAMs was developed based 
upon published literature data. Rates of GC and LC of the CRM were based upon the collective 
opinion of a panel of experts (expert elicitation) (CRWMS M&O 1995). The model assumed 
that galvanic protection would delay LC (pitting) of the CRM until a specified percentage of the 
CAM thickness had been consumed by GC. 
Exposure conditions included temperature, RH, presence of liquid-phase water (dripping), water 
chemistry, backfill, and rock fall (CRWMS M&O 1995). 
Along with the improvements in the degradation modeling, the evaluation of materials selection 
for the WP barriers continued during the following several years. The corrosion resistant 
material, Alloy 825, was replaced with a more corrosion resistant nickel-based Alloy 625 during 
this period (CRWMS M&O 1996). The lifetime goals for the WP was increased further and 
resulted in the selection of Alloy 22 as the corrosion resistant barrier for the Viability 
Assessment design. The superiority of Alloy 22 is well known and generally accepted. 
Additional improvements in the WP corrosion model were made for the Viability Assessment 
(VA) design (CRWMS M&O 1998a, Chapter 5). This model accounted for humid-air GC and 
LC of the CAM; aqueous-phase GC and LC of the CAM; and aqueous-phase GC and LC of the 
CRM. Degradation of the WP was modeled by dividing the surface into patches and populating 
the corrosion rates stochastically over the patches. The concept of a localization factor was used. 
Pitting of the CAM was assumed to occur under alkaline conditions (pH  10). 
Microbiologically influenced corrosion (MIC) and SCC were not accounted for in the TSPA 
models used for VA. The effects of salt deposition and evaporative concentration of dripping 
water on the WP surface were also neglected. These models were not based upon qualified

 2-3  
experimental data from materials testing in repository-relevant environments, but relied heavily 
on the opinion of experts and other published data. For this PMR, a broad range of laboratory 
data and associated process models have been developed to more realistically approximate the 
degradation processes of potential significance to repository performance. Changes to the 
degradation models have been necessitated by the changes in WP design and inclusion of the DS 
for Site Recommendation (SR). 
2.3 TOTAL SYSTEM PERFORMANCE ASSESSMENT-SITE RECOMMENDATION 
APPROACH 
The approach in the TSPA-SR WP degradation analysis is greatly enhanced version of that used 
in TSPA-VA. (For convenience of discussion in this section, the DS is modeled as an integral 
part of WP, and no separate discussion is given for DS.) The WAPDEG model, which is based 
on a stochastic approach, has been upgraded to include SCC and is used for the SR WP 
degradation analysis. The motivations for the stochastic approach used in the WAPDEG model 
are three-fold: 
 To provide realistic representation of WP degradation processes in the repository. 
 To capture the effects of variation and uncertainty both in exposure conditions and 
degradation processes over a geologic time scale. 
 To perform analysis within a reasonable time and within computational resources. 
Abstractions of the process-level models were developed for WAPDEG in a manner that allows 
important features of the process-level models to be captured as explicitly as possible, and in a 
manner that allows the degradation processes and their characteristics to be properly represented 
in the WP degradation analysis. More details of the TSPA-SR approach to WP and DS 
degradation analysis are given in the supporting AMR entitled WAPDEG Analysis of Waste 
Package and Drip Shield Degradation (CRWMS M&O 2000g). 
As in the TSPA-VA analysis, effects of spatial and temporal variations in the exposure 
conditions over the repository were modeled by explicitly incorporating relevant histories of 
exposure condition into the WP degradation analysis. The parameters that represent exposure 
conditions were considered to be varying over the repository. These include RH and temperature 
at the WP surface, seepage into the emplacement drift, chemistry of seepage water, and rockfall. 
In addition, potentially variable corrosion processes within a single WP were represented by 
dividing the WP surface into unit areas called patches and stochastically populating the 
corrosion model parameter values and/or corrosion rates over each patch. The model parameter 
values and corrosion rates were sampled from their distribution over the range of the expected 
local exposure conditions. 
In the nominal case analysis, the WPOB and DS were included in the WP degradation analysis. 
The stainless steel inner container, which is to provide structural support to WP, is not included 
in the degradation analysis. Although, this inner container would actually provide some 
performance for waste containment after the outer barrier breach, and would also provide a 
barrier to radionuclide transport after the WP is breached, the potential performance credit was

 2-4  
ignored in the nominal TSPA-SR analysis. This is a conservative approach. However, 
performance credit for the stainless steel is being evaluated for future consideration. 
In summary, the TSPA-SR WP degradation analysis includes the following potentially important 
degradation processes: 
 General corrosion (GC) 
 Localized (pitting and crevice) corrosion (LC) 
 Stress corrosion cracking (SCC) waste package outer barrier (WPOB only) 
 Microbiologically influenced corrosion (MIC) (WPOB only) 
 Long-term aging and phase instability of WPOB and their effect on corrosion, and 
 Pre-existing manufacturing defects in the WP closure welds and its effect on SCC. 
As previously discussed, significant improvements have been made to the GC and LC models, 
making them superior to those used in TSPA-VA. In the analysis, the DS was considered to be 
immune to SCC because it will be fully annealed before it is placed in the emplacement drift. 
Likewise, all the fabrication welds in the WP, except the welds for the closure lids, will be fully 
annealed and therefore not subject to SCC. Only the WP closure weld is considered in the SCC 
analysis. Two alternative SCC models were considered, the slip dissolution model and the 
threshold stress intensity factor model. The effect of radiolysis on corrosion is expected to be 
insignificant under the conditions expected in the repository (see Section 3.1.6.6), and was 
therefore not included in the nominal case analysis. The DS was assumed to be immune to the 
MIC. Since the bounding analyses have shown that the hydrogen uptake by the DS is much less 
than the threshold hydrogen concentration for HIC (CRWMS M&O 2000h, Sections 6.1.3 and 
6.2.4), this mode of failure was not included in the DS degradation model. 
WP failure requires through-wall penetration. The WAPDEG analysis tracks degradation of WP 
for three penetration modes: SCC (crack penetration), LC (rapid crevice penetration), and GC 
(slower uniform penetration). Here, localized attack is assumed to be crevice corrosion over an 
entire patch, which is conservative. The analysis provides, as output, the cumulative probability 
of WP failure by one of the three penetration modes as a function of time and also provides the 
number of penetrations for each of the penetration modes as a function of time. The WP failure 
time and number profiles for penetration are used as input to other TSPA analyses, such as the 
WF degradation and the radionuclide release rate from WPs. 
The TSPA-SR analysis yields a more explicit representation (than previous TSPA analyses) of 
the uncertainty and variability in WP degradation (i.e., WP failure and penetration number 
profiles). For the corrosion models and parameters for which data and analyses are available, 
their uncertainty and variability were quantified and incorporated into the WAPDEG analysis. 
For other models and parameters for which the uncertainty and variability are not quantifiable, 
the variance in their value was assumed and used as uncertainty. In the TSPA-SR analysis, WP 
degradation was analyzed with multiple realizations of WAPDEG for the uncertainty analysis of 
the uncertain corrosion parameterseach WAPDEG realization corresponding to a complete 
WAPDEG run to account for the WP degradation variability for a given number of WPs. 
Accordingly, each of the WAPDEG analysis outputs (i.e., WP failure time, crack penetration 
number, pit penetration number, and patch penetration number) is reported as a group of curves 
that represents the potential range of the output values.

 2-5  
2.4 ISSUES RELATED TO WASTE PACKAGE DEGRADATION 
This PMR also addresses related issues identified based on a review of the past two years 
Advisory Committee on Nuclear Waste (ACNW) and Nuclear Waste Technical Review Board 
(NWTRB) meeting summaries and correspondences, Viability Assessment (VA) Volume 3, 
Sections 6.5.2 and 6.5.3 and Volume 4 Section 4.3, TSPA peer review documentation, NRC 
comments on TSPA-VA, expert elicitation recommendations, and licensing correspondence files 
for the NRC, the State of Nevada, and the Nevada counties. Table 2-1 provides a summary of all 
identified issues and describes how each issue is addressed in this PMR. In addition, acceptance 
criteria from the Issue Resolution Status Reports Key Technical Issue: Container Life and 
Source Term (NRC 1999a), the Issue Resolution Status Report Key Technical Issue: Total 
System Performance Assessment and Integration (NRC 2000), and the Repository Design and 
Thermal-Mechanical Effects Report (NRC 1999b) are separately addressed in Table 4-1 in 
Chapter 4 of this document.

 2-6  
Table 2-1. Key External Issues for the Waste Package Degradation Process Model Report 
Source Issue PMR Approach 
TSPA-VA, Volume 3, Sec. 6.5.2 
(DOE 1998) 
Physical events and processes such as degradation of 
drift with time due to chemical and mechanical effects 
that have a potential for affecting the WP performance 
were not considered, or not sufficiently covered, within 
the TSPA-VA. 
Degradation of the drift with time could result in rock fall, which can 
impact the DS and WP and increase potential for SCC. The 
incorporation of SCC as a failure mode initiated by rockfall (Section 
3.1.7) may be useful in addressing early failures due to rockfall. 
This will have to be done in future analyses. 
TSPA-VA, Volume 3, Sec. 6.5.2 
(DOE 1998) 
The panel believes that there is insufficient data to 
support the selection of the material for use in the final 
WP design. 
Selection process for WP package materials has considered and 
evaluated all degradation processes. Several materials have been 
electrochemically tested, with a clear indication that Alloy 22 and 
Titanium Grade 7 are more corrosion resistant than other candidate 
materials. Section 3.1.1 provides an overview of the WP materials 
selected. 
TSPA-VA, Volume 3, Sec. 6.5.2 
(DOE 1998) 
Uncertainties and limitations in WP degradation 
models (SCC, crevice corrosion, and WP surface 
chemistry) need to be verified. 
In regard to crevice corrosion, experimental studies have been 
performed to define the crevice chemistry (pH, etc.). In regard to 
SCC, alternative models are employed. Stress mitigation 
techniques are being used as a means of eliminating SCC through 
elimination of the driving force (see Section 3.1.7). Details of these 
degradation modes are provided in the respective AMRs and PMR 
sections (Section 3.1.3, 3.1.6, and 3.1.7). 
TSPA-VA, Volume 3, Sec. 6.5.2 
(DOE 1998) 
The issue states the need for additional research on 
water contact with the WP, critical crevice 
temperatures, Np solubility and technetium sorption on 
degraded WP. 
Evaporative concentration experiments have been used to 
determine the concentrations of saturated electrolytes that may form 
on the surface of the hot WP (see Section 3.1.3). Critical crevice 
potentials and temperatures for the WP barrier materials have been 
determined and documented in the various AMRs and PMR Section 
3.1.6. Np solubility and technetium sorption are not part of the 
scope of this PMR but are addressed in WF degradation PMR. 
TSPA-VA, Volume 3, Sec. 
6.5.3.2 (DOE 1998) 
The rationale for including or excluding any potentially 
significant feature, event or process needs to be 
technically justified and clearly articulated. 
Identification of FEP is discussed in Section 1.6.

 2-7  
Table 2-1. Key External Issues for the Waste Package Degradation Process Model Report (Continued) 
Source Issue PMR Approach 
TSPA-VA, Volume 3, Sec. 
6.5.3.3 (DOE 1998) 
Modeling assumptions should be consistent across 
different process models, unless there is a defensible 
technical rationale. 
The AMRs that document assumptions for WP degradation are 
subject to thorough interdisciplinary reviews to help ensure 
consistency among assumptions made in more than one document 
about a given parameter. In addition, the PMR that summarize and 
integrate the results of the AMRs has been subjected to a review by 
a single review team, one of whose main objectives is to identify 
inconsistencies among the PMRs. Finally, assumptions used in the 
AMRs that feed WP degradation are documented in the WP PMR 
document. These measures provide confidence that consistent 
assumptions are used as appropriate among the various models 
that support the WP PMR. 
TSPA-VA, Volume 3, Sec. 
6.5.3.7 (DOE 1998) 
Rockfall effects need to be considered in the design 
and performance of the Yucca Mountain repository 
system. 
Analyses of seismically induced rockfall damage have been 
explicitly addressed in TSPA-SR. 
NWTRB Letter to DOE (11-10- 
99) (Cohon 1999a) 
The presentation on WP degradation indicated that 
valuable information is being collected on Alloy 22 at a 
rapid pace. However, concern still exists about the 
effects on corrosion of radiolytic species, including 
species formed in the vapor phase. Resolving that 
concern may necessitate additional experimental and 
theoretical work. 
Experiments have been performed to determine the maximum 
increase in corrosion potential that can be caused by hydrogen 
peroxide, the primary product formed during gamma radiolysis of 
water. The maximum increase is approximately 200 mV, which is 
insufficient to cause initiation of LC with materials such as Alloy 22 
(Section 3.1.6).

 2-8  
Table 2-1. Key External Issues for the Waste Package Degradation Process Model Report (Continued) 
Source Issue PMR Approach 
NWTRB Letter to DOE (8-3-99) 
(Cohon 1999b) 
Regarding the engineered repository system, NWTRB 
highlights four areas: the need to vigorously pursue 
ongoing studies of degradation associated with stresscorrosion 
cracking and phase instability of proposed 
WP materials; the need to determine whether 
presently unrecognized corrosion mechanisms exist 
that would be important over the very long term; the 
need to complete experiments on the formation of 
radiolysis products in the near-field and to model the 
effects of such radiolysis products on near-field 
component degradation; and the need to intensify 
investigations into the performance of a titanium DS 
and the effect this DS and associated backfill would 
have on other elements of the engineered system. 
Ongoing SCC studies are underway at the Corporate Research and 
Development Center of General Electric Corporation and at 
Lawrence Livermore National Laboratory (LLNL). All credible 
modes of corrosion such as phase stability and SCC are considered 
in the testing program and the WAPDEG code, so that the 
unexpected can be accounted for. Experiments have been 
performed to determine the maximum increase in corrosion potential 
that can be caused by hydrogen peroxide, the primary product 
formed during gamma radiolysis of water. The maximum increase is 
approximately 200 mV, which is insufficient to cause initiation of LC 
with materials such as Alloy 22. For example, a series of CP of 
Titanium Grade 7 have been performed in test solutions that are 
relevant to the repository (Sections 3.1.5 and 3.1.6). 
NWTRB Letter to DOE (8-3-99) 
(Cohon 1999b) 
Additional research is needed to determine the 
likelihood of new mechanisms (beyond typical LC 
processes) of deterioration that could affect the verylong-
term stability of the passive layer for critical WP 
and other engineered barrier materials, such as Alloy 
22 and titanium. This work could include, for example, 
examination of fundamental models of passive-regime 
stability and the factors that may cause deviation from 
passive-layer dissolution behavior assumed from 
short-term experiments, prediction of the behavior of 
the alloy surface under a thick layer of previous 
passive dissolution products, and a search for relevant 
natural and archeological analogs. 
A variety of cutting edge techniques are now employed to study the 
long-term degradation of WP materials. For example, TEM is used 
to quantify the thermal aging of Alloy 22. Such quantification is in 
the form of TTT diagrams found in this PMR. Thermal aging is 
important in that it may result in the precipitation of undesirable 
intermetallic phases. These precipitates can lead to embrittlement 
and enhanced susceptibility to LC and SCC. Atomic force 
microscope (AFM) and X-ray photo electron spectroscopy are being 
employed to study passive film stability. SIMS is used to quantify 
the amount of hydrogen in the titanium-based materials that will be 
used for construction of the DS. All these modes of degradation are 
addressed in the PMR Sections 3.1.3 through 3.1.9. 
No appropriate natural or archeological analogs are available for 
Alloy 22 or titanium

 2-9  
Table 2-1. Key External Issues for the Waste Package Degradation Process Model Report (Continued) 
Source Issue PMR Approach 
NWTRB Letter to DOE (8-3-99) 
(Cohon 1999b) 
The effects of the DS and backfill on the thermal and 
moisture regime between the DS and the WP and 
evaluating the corrosion behavior of titanium when it is 
in contact with backfill or rock fall. The vulnerability of 
the drip-shield connections to vibratory earthquake 
motion also needs to be addressed. 
The testing of material samples have assumed same bounding 
chemistry for both the DS and the WP outer barrier (Section 3.1.3). 
The DS is designed to withstand expected earthquake motion and 
not separate. 
TSPA Peer Review, Section II.C 
(Budnitz et al. 1999) 
Experimental data are lacking throughout the 
treatment of the WP and EBS. In particular, the effect 
of realistic and extreme environments to come in 
contact with Alloy 22 and critical temperature for 
crevice corrosion of Alloy 22. 
Electrochemical testing has been done in a wide variety of 
repository-relevant test solutions, including SDW, SCW, SAW, 
SCMW, SSW, and BSW. CP tests have been conducted in these 
media with artificial crevices. Long term exposure testing has been 
done in SDW, SCW, SAW, and SCMW at temperatures up to 90C. 
To determine critical crevice temperatures, SCC testing is underway 
in similar solutions. Experiments have been performed to quantify 
the extent that pH can be lowered inside crevices, formed between 
the Alloy 22 WPOB and the 316NG SSSM (see Sections 3.1.6 and 
3.1.7). 
TSPA Peer Review, Section IV.D 
(Budnitz et al. 1999) 
The TSPA-VA treatment of crevice corrosion was 
based on the adaptation of a pitting model. While 
similar chemical and electrochemical processes occur 
as part of both modes of corrosion, the TSPA peer 
review panel has concluded that a direct crevice 
corrosion model would be more realistic. 
In the case of Alloy 22, pitting is not expected. If LC does occur, it is 
expected to be some form of crevice corrosion. Crevice chemistry 
determination has been conducted and documented in the 
supporting AMR and PMR Section 3.1.6. 
TSPA Peer Review, Section IV.D 
(Budnitz et al. 1999) 
There is a need both to improve the models and 
methods for analyzing water chemistries at the metal 
surfaces of the WPs under realistic conditions, and to 
collect experimental data to validate and verify these 
models and the associated analytical methods 
From the evaporative concentration experiments, the saturated 
electrolytes that may form on the WP surface have been defined 
(Section 3.1.3). 
TSPA Peer Review, Section IV.D 
(Budnitz et al. 1999) 
As in the case of analyses of crevice corrosion, 
additional work will be necessary for SCC prior to the 
possible LA stage, especially in light of the tentative 
nature of the SCC model and the fact that failure mode 
is closely coupled to WP fabrication procedures. 
The WAPDEG code now incorporates a wide variety of plausible 
failure modes, including SCC. The effects of residual weld stress in 
the final closure weld are now accounted for. The code has 
developed to a level of sophistication now able to account for stress 
mitigation techniques such as laser peening and induction annealing 
(Section 3.1.7).

 2-10  
Table 2-1. Key External Issues for the Waste Package Degradation Process Model Report (Continued) 
Source Issue PMR Approach 
TSPA Peer Review, Section IV.D 
(Budnitz et al. 1999) 
At the present time, the corrosion behavior of WP with 
backfill or rock debris covering the WP is not well 
defined 
Electrochemical testing has been done in a wide variety of 
repository-relevant test solutions, including SDW, SCW, SAW, 
SCMW, SSW, and BSW. BSW and SSW are determined to be 
bounding environments and cover the effects of backfill. CP tests 
are now being conducted in these media with artificial crevices. 
Experiments have been performed to quantify the extent that pH can 
be lowered inside crevices, formed between the Alloy 22 WPOB and 
the 316NG SSSM (Sections 3.1.3 and 3.1.6). 
TSPA Peer Review, Section IV.D 
(Budnitz et al. 1999) 
The treatment of Alloy 22 corrosion rates and the 
allocation of total variance to their variability and 
uncertainty need to be improved prior to the 
anticipated LA phase. 
The large number of samples involved in testing in the LTCTF 
provide estimates of uncertainty for GC rates (for both HAC and 
APC). By performing large numbers of CP tests with at least three 
replicates at each condition, similar estimates of the uncertainty in 
electrochemical potential measurements are obtained. Separation 
of uncertainty and variability is difficult with these very corrosion 
resistant materials. In many cases, the corrosion rates are so low 
that the measurement limits are exceeded. The treatment of 
uncertainties and variability in the data is addressed in Section 3.1.9 
of the PMR. 
TSPA Peer Review, p. 8 
(Budnitz et al. 1999) 
The analyses (WAPDEG), however, were developed 
to a level of complexity that extended well beyond the 
data that were available. This complexity may be 
useful for the anticipated LA phase of sufficient data 
on key parameters become available. If not the panel 
believes that attempts to apply the WAPDEG model 
may compromise the transparency of the treatment. 
Necessary changes include an updating and/or 
revision of the model, including better integration of the 
multitude of process models used for analyzing 
various degradation modes or engineering 
enhancements and the development of a stronger 
case to confirm the linkage between the process 
models and their abstractions. 
This comment is not longer applicable to the current WAPDEG 
model which is based on new data and new process models. As 
discussed in Section 3.2 of this PMR, several new models and 
correlations have been added replacing old models. The 
complexities of current models (general and localized corrosion, 
stress corrosion cracking etc.) are consistent with the available data.

 2-11  
Table 2-1. Key External Issues for the Waste Package Degradation Process Model Report (Continued) 
Source Issue PMR Approach 
AMR Analysis and Model Report 
APC aqueous phase corrosion 
BSW basic saturated water 
CP cyclic polarization 
DS drip shield 
EBS engineered barrier system 
GC general corrosion 
HAC humid air corrosion 
LA License Application 
LC localized corrosion 
LTCTF Long Term Corrosion Test Facility 
Np Neptunium 
PMR Process Model Report 
SAW simulated acidic concentrated water 
SCC stress corrosion cracking 
SCW simulated concentrated water 
SCMW simulated cement-modified water 
SDW simulated dilute water 
SIMS secondary ion mass spectrometry 
SSSM stainless steel structural material 
SSW simulated saturated water 
TEM transmission electron microscope 
TSPA-VA Total System Performance Assessment Viability Assessment 
TTT time-temperature-transformation 
WPOB waste package outer barrier 
WP waste package

 2-12  
INTENTIONALLY LEFT BLANK

 3-1  
3. MODELS AND ABSTRACTED MODELS 
The WP degradation process model consists of several different models: dry oxidation, humid 
air corrosion, aqueous phase corrosion, general corrosion, localized corrosion, microbiologically 
induced corrosion, stress corrosion cracking, and hydrogen-induced cracking. A generic 
integrated model containing the above component models is illustrated by Figure 1-4. This 
model can be applied to the DS and WP materials of interest. 
3.1 MODEL DESCRIPTIONS 
As stated above, the WP degradation process model includes a number of component models. 
These component models are discussed in the following sections. Model parameters and 
definitions for the individual models are provided in the respective AMRs. 
3.1.1 Overview of Waste Package and Drip Shield Design 
As described in the LADS report, the recommended WP design is EDA II (CRWMS 
M&O 1999a, Section 1.1.2). This design includes a double-wall WP underneath a protective 
DS. The DS is to be fabricated from Titanium Grade 7. The EDA II corrosion resistant WPOB 
is to be fabricated from nickel-based Alloy 22. Stainless steel 316NG is to be used for 
construction of the structural support container within the WPOB. The 316NG inner cylinder 
will increase the overall strength of the WP. 
3.1.1.1 Titanium Drip Shield 
Titanium alloys (1.5-cm thick) have been considered for construction of the DS. The current 
recommendation is to use Titanium Grade 7 [Unified Numbering System for Metals and Alloys 
(UNS) R52400]. The composition of this alloy is 0.03% N (max), 0.10% C (max), 
0.015% H (max), 0.25% O (max), 0.30% iron (max), 0.12-0.25% Pd (max), and 0.4% Residuals 
(total), with the balance being Ti (approximately 98.7 to 98.8%). The nominal thickness of the 
DS is 15 mm. Properties and performance of these materials are reviewed elsewhere and cited in 
the respective AMRs. The unusual corrosion resistance of titanium alloys is due to the formation 
of a passive film of TiO2, which is stable over a relatively wide range of electrochemical 
potential and pH. A similar material, Titanium Grade 16 with 0.04 to 0.08% Pd, is used as an 
analog for Titanium Grade 7 in some parts of the testing program. The rates of general corrosion 
and dry oxidation (or dry air oxidation) of this material have been shown to be very low. 
Corrosion testing of Titanium Grade 16 has been conducted in the Long Term Corrosion Test 
Facility (LTCTF) of the YMP (CRWMS M&O 2000d, Section 6.5). 
3.1.1.2 Nickel-Based Waste Package Outer Barrier 
Alloy 22 [UNS N06022] (2.0 cm thick) is now being considered for construction of the WPOB. 
This alloy consists of 20.0-22.5% chromium, 12.5-14.5% molybdenum, 2.0-6.0% iron, 
2.5-3.5% W, and 2.5% Co (max), with the balance being nickel (approximately 50-60%). Other 
impurity elements include P, Si, S, Mn, Nb, and V. Alloy 22 is less susceptible to LC in 
environments that contain Cl- than Alloys 825 and 625, materials of choice in earlier WP 
designs. Corrosion testing of Alloy 22 has been and continues to be conducted in the LTCTF of

 3-2  
the YMP (CRWMS M&O 2000c, Section 6). Nominal thickness of the Alloy 22 shell is 20 mm 
for the commercial spent fuel packages and 25 mm for the packages containing navy waste. 
3.1.1.3 Stainless Steel Structural Material 
316NG stainless steel (5-cm thick) is to be used for construction of the structural support inside 
the WPOB. This inner cylinder of 316NG stainless steel will increase the overall strength of the 
WP. 316L stainless steel is considered to be a good analog for 316NG stainless steel because the 
chemical composition of the two alloys is essentially the same, except that 316NG stainless steel 
has better mechanical properties than 316L. 316 stainless steel [UNS S31603] has a composition 
of 16-18% chromium, 10-14% nickel, 2-3% molybdenum, 2% Mn (max), 1% Si (max), 0.03% C 
(max), 0.045% P (max), 0.03% S (max), 0.10% N (max) and the balance being iron (65-69%). 
316L stainless steel is less susceptible to LC in environments that contain Cl- than stainless 
steel 304, but more susceptible than other corrosion resistant materials such as Alloys 22, 625 
and 825 that have been considered in various WP designs. The superior LC resistance of 316L 
stainless steel in comparison to 304 stainless steel is apparently due to the addition of 
molybdenum, which helps to stabilize the passive film at low pH values. Molybdenum oxide is 
very insoluble at low pH. Consequently, 316L stainless steel exhibits relatively high thresholds 
for localized attack (CRWMS M&O 2000e, Section 1.2). 
3.1.2 Manufacturing Defects (Early Failure AMR) 
Manufacturing defects and failure modes that might lead to early failure of a WP are accounted 
for in an AMR (CRWMS M&O 2000m, Section 6) that supports this PMR. The AMR on early 
failure includes a literature review directed towards obtaining information on the rate of 
manufacturing defect-related failures in various types of welded metallic containers, the types of 
defects that produce these failures, and the mechanisms that cause defects to propagate to failure. 
Types of defects applicable to the current WP design are identified. For each applicable type of 
defect, the probability of its occurrence on a WP is estimated. Potential consequences to the 
long-term performance of the WP if the defect is present are discussed. Specific details on how 
the defect will affect WP materials are provided in separate AMR on SCC (CRWMS 
M&O 2000f, Section 6). Defects or flaws may serve as initiation sites for SCC. 
3.1.2.1 Analysis Assumptions in AMR 
The following assumptions support the development of probabilities for various size flaws in the 
welds of the WP shell and lids. Based on the similarity of the processes used for welding 
Alloy 22 and stainless steel, they are predicted to have the same frequency and size distributions 
for flaws. Information on the reliability of radiographic, ultrasonic, and dye-penetrant testing is 
assumed to be applicable to the materials and inspection methods that will be used for the WP. 
This information is based on older reliability studies of these non-destructive examination 
methods, and the assumption that future improvements in the inspection technology will result in 
increases in the probability of flaw detection. It was assumed that flaws detected by post-weld 
inspections will be repaired, whenever the flaw size is larger than the flaw size of concern for 
postclosure performance. Embedded weld flaws are not considered to be a concern for 
postclosure performance in the supporting AMR (CRWMS M&O 2000m, Section 6), since the 
WP is not a pressure vessel and will not be subjected to cyclic fatigue (the primary mechanism

 3-3  
for causing such flaws to grow through-wall in pressure vessels). However, as the weld 
undergoes GC, subsurface flaws may eventually be exposed. 
The probabilities of human error have not been quantified for the specific actions associated with 
the fabrication of the WP, but the information used represents human error probabilities for 
similar types of actions. 
In developing the probability of the use of improper material in the WP shell or lid welds, it is 
assumed that a field verification of the chemical composition of weld wire will be performed 
prior to its use in fabricating any weld and that material controls required in nuclear quality 
programs will be used. It is further assumed that such field verification will use state-of-the-art 
instrumentation. This assumption is based on the expected administrative requirements on the 
process qualification program. 
Assumptions are used to support the development of the probability of having 
corrosion-enhancing surface contamination on the WP or improper heat treatment of the WP. 
These assumptions are based on the general descriptions of these activities. The assumptions 
support the development of event sequence trees for quantifying the probabilities of improper 
heat treatment or a failure in the cleaning process. The assumptions involve the number of 
operators involved in each process, the QA procedures and inspections governing the processes, 
and the reliability of the equipment used. 
It is assumed that the probability of damaging a WP during transport or handling at the 
repository is equivalent to the probability of damaging spent nuclear fuel (SNF) assemblies 
during transport or handling. The basis for this assumption is that a WP will be subjected to 
about the same number of handling steps as a SNF assembly. It is assumed that both are handled 
with about the same amount of care. It is expected that the WP will be inspected for handling 
damage upon arrival at the repository and before final emplacement in the drift. It is further 
expected that the WP will be completely repaired or scrapped if such handling damage occurs. 
3.1.2.2 Analysis Description in AMR 
The AMR presents the results of a literature review performed to determine the rate of 
manufacturing defect-related failure for various types of welded metallic containers. In addition 
to providing examples of the rate at which defective containers occur, this information provides 
insight into the various types of defects that can occur and the mechanisms that cause defects to 
propagate to failure. In summary, eleven generic types of defects were identified. These are: 
1. Weld flaws 
2. Base metal flaws 
3. Improper weld material 
4. Improper heat treatment 
5. Improper weld flux material 
6. Poor weld joint design 
7. Contaminants 
8. Mislocated welds 
9. Missing welds

 3-4  
10. Handling and installation damage 
11. Administrative and operational error. 
For dry storage casks, all of the defects were identified by post-weld inspection prior to 
commencement of the storage phase, and thus do not represent true instances of early failure as it 
is defined in the AMR. The eleven types of defects were reviewed for their applicability to the 
WP. From this review, the following generic defect types are considered not applicable to the 
WP: improper weld flux material, poor weld joint design, missing welds, and mislocated welds. 
This determination is based on the fact that the welding process for WP fabrication does not use 
flux as noted in the AMR. Poor joint design is unlikely because of extensive development and 
testing. Missing welds and mislocated welds are easily detected and controlled by process 
qualification. The probability of occurrence and the effect on postclosure performance of the 
WP are assessed for the remaining defects. 
Using information on linear flaw density, flaw size distribution, inspection reliability, and 
information on various weld lengths, frequencies of weld flaws of various size that break the 
outer surface have been estimated in the supporting AMR (CRWMS M&O 2000m). The 
procedure is essentially the same for all cases. First, the total flaws per type of WP weld were 
calculated by multiplying the weld length by the linear flaw density and by an adjustment factor 
for the weld thickness. The base linear flaw density with credit for radiographic and dyepenetrant 
test inspections was used for the shell and bottom lid welds, and the uninspected flaw 
density was conservatively used for the top lid closure weld. Next, the flaw size distribution for 
that weld thickness was used to determine the probability that a flaw would have a size within a 
given range. A range size of 0.5% of the weld thickness was used. This was the largest size 
range that could be used without introducing any significant (within two significant figures) 
amount of numerical error associated with discretizing a continuous size distribution. The 
probability for each size range was then multiplied by the total number of flaws per weld to 
determine the expected number of flaws within that size range. For welds subjected to an 
ultrasonic (UT) inspection, the expected number of flaws within each size range was then 
reduced by multiplying by the probability of nondetection (PND) for the lower end of the size 
range. This is conservative because the PND is higher for smaller flaws and ultrasonic 
inspection identifies small flaws. Since the UT PND is based on a single angle UT examination 
and a multi-angle examination is planned for the lid welds (possibly four angles), the square of 
the PND was used for the lid welds. This effectively treats a multi-angle exam as two 
independent examinations. For all cases, each range was then multiplied by 0.34% to yield the 
expected number of outer surface breaking flaws within that range. Finally, the expected number 
of outer surface breaking flaws in each size range were summed to determine a new value for 
total flaws per weld which accounts for the UT inspections. A complementary cumulative 
distribution of outer surface breaking flaw size was also determined. These results are 
summarized in Figure 3-1 for the Alloy 22 barrier shell welds, and in Figure 3-2 for the Alloy 22 
barrier lid welds.

 3-5  
Source: CRWMS M&O 2000m 
Figure 3-1. Size Distribution for Indicated Frequency of Occurrence for Outer 
Surface Breaking Flaws in Waste Package Alloy 22 Shell Welds 
Source: CRWMS M&O 2000m 
Figure 3-2. Size Distribution for Indicated Frequency of Occurrence of Outer 
Surface Breaking Flaws in Waste Package Alloy 22 Lid Welds 
24 
1.E-11 
1.E-10 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
1.E-02 
1.E-01 
1.E+00 
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 25 
No Inspections 
(0.140 Flaws/Lid) 
Bottom Lid - (0.007 Flaws/Lid) and 
Top Lid - (0.055 Flaws/Lid) 
Flaw Depth (mm) 
Probability of a Larger Surface Flaw 
No inspections 
(0.140 Flaws/Lid) 
Bottom Lid  (0.007 Flaws/Lid) and 
Top Lid  (0.055 Flaws/Lid) 
Probability of a Larger Surface Flaw

 3-6  
3.1.2.3 Uncertainties in AMR 
The inputs used to estimate the probability of various defects that can potentially lead to early 
failure are open to interpretation and uncertainty. An uncertainty analysis was performed to 
develop an upper bound for an event sequence probability based on the uncertainty of modeled 
human actions. The analysis applies to those defects for which probabilities are estimated using 
event sequence trees, namely: DS emplacement error, WP handling error, WP surface 
contamination, thermal misload, and improper heat treatment. The method used to establish an 
upper bound value for event sequences combines the human error rates probabilistically. 
Uncertainties are considered only for human error probabilities related to failures. Probability 
components for success are treated at their nominal level (i.e., without uncertainty), which 
produces conservative results. No upper bounds were estimated for other failure probabilities 
related to mechanical failure or based on historical data. Accordingly, the upper bound for an 
event sequence probability is adjusted for human error probability uncertainties only (CRWMS 
M&O 2000m). 
3.1.2.4 Analysis Conclusions in AMR 
The AMR on early failure of the WP reviewed available literature on defect-related early failures 
of welded metallic components. Types of components examined include boilers and pressure 
vessels, nuclear fuel rods, underground storage tanks, radioactive cesium capsules, dry-storage 
casks for SNF, and tin-plate cans. The fraction of the total population that failed due to defectrelated 
causes during the intended lifetime of the component is generally in the range of 10-3 to 
10-6 per container. In most cases, defects that lead to failure of the component require an 
additional stimulus to cause failure (i.e., the component was not failed when it was placed into 
service). There were several examples that indicate that even commercial standards of quality 
control could reduce the rate of initially failed components well below 10-4 per container. The 
literature review identified eleven generic types of defects that could cause early failures in the 
components examined: weld flaws; base metal flaws; improper weld material; improper heat 
treatment; improper weld flux material; poor weld joint design; contaminants; mislocated welds; 
missing welds; handling and installation damage; and administrative error resulting in an 
unanticipated environment. The following defect types are considered not applicable to the 
WP: improper weld flux material, poor joint design, missing welds, and mislocated welds. The 
analysis estimates the probability that specific defect types will occur on a given WP, despite a 
set of quality controls designed to prevent their occurrence. Results of the analysis for the 
remaining seven types of defects are shown in Table 3-1.

 3-7  
Table 3-1. Summary of Estimated Probabilities and Performance Consequences for Various Types of Waste Package Defects 
Probability per WP Possible Consequences for Postclosure Performance 
WP Defect Type 
Alloy 22 Barrier 
SS 
Structural 
Barrier 
Minimal 
Effect 
Degraded 
Mechanical 
Properties 
Pitting or 
Crevice 
Corrosion 
SCC 
Early 
Water 
Contact 
Weld Flaws 
(Outer Surface Breaking Only) 
< 10-4 for flaws 
> 4 mm deep 
< 10-4 for flaws 
> 10 mm deep 
X X 
Base Metal Flaws 
Factor of 10-4 lower than uninspected 
weld flaw rate 
X X 
Improper Weld Material 1.5x10-5 3.0x10-5 X X 
Improper Heat Treatment 2.2x10-5 X X X 
Surface Contamination 7.3x10-5 4.0x10-5 X 
Handling Damage 5.1x10-6 5.1x10-7 X 
Thermal Misload of 
WP 
1.0x10-3 to 1.0x10-6 X Administrative Error 
Leading to 
Unanticipated 
Environment 
DS Emplacement 
Error 
1.8x10-4 X 
NOTE: SS = stainless steel; WP = waste package

 3-8  
3.1.2.5 Accounting for Embedded Flaws 
While the AMR based the determination of flaw density on surface-breaking flaws, a more 
conservative approach is to base such determinations on embedded flaws. The recent work by 
Khaleel et al. (1999) is cited. The TSPA analysis that will be discussed in subsequent sections 
uses estimates of flaw density based upon data given in Table V of this reference. Specifically, 
the values for embedded flaws at depths equivalent to the outer quarter of the wall thickness are 
used. In the dual-lid WP design, cumulative distribution functions are needed for the closure 
welds of both the inner and outer lids. The flaw density for the outer lid weld is 18 defects per 
WP at the 50th percentile, and 40 defects per WP at the 100th percentile. The flaw density for the 
inner lid weld is 15 defects per WP at the 50th percentile, and 40 defects per WP at the 100th 
percentile (same as outer lid at 100th percentile). Note that each closure weld is represented by 
thirty two (32) WAPDEG patches. 
3.1.2.6 Accounting for Flaw Orientation 
In considering the potential effects of weld defects on SCC, the presence of planar defects in the 
region of the weld and heat-affected zone (HAZ), where weld-induced residual tensile stress 
exists, can lead to SCC initiation and growth. The two principal attributes of such weld defects 
that foster SCC are the stress concentration effect at the base of the defects, which can generate a 
stress intensity, and the occluded nature of such defects that may lead to the development of 
more aggressive crevice chemistry within the defect volume. However, as described in the 
SCC AMR, only defects oriented normal to the direction of the weld centerline (radially oriented 
defects) have sufficient calculated stress intensity to drive a stress corrosion crack through wall. 
Weld defect types and expected defect orientation for the closure weld case are described briefly 
below. 
The fabrication welds will be performed at the contractors facilities. Currently, only two weld 
methods are being considered for the fabrication process, gas metal arc and tungsten inert gas 
methods. This automatically eliminates slag inclusions, the most commonly found defect when 
the autosubmerged arc welding process is used. The most common defects for gas metal arc and 
tungsten inert gas are lack of fusion. This occurs because of missed sidewall or lack of 
penetration in the sidewall. This generally produces large defects that are readily found by 
ultrasonic and radiographic inspection. The other defect types are tungsten inclusion, silicon, 
and porosity. Because both ultrasonic and radiographic methods will be used for post-weld 
inspections, there should be no undiscovered defects for these welds. Additionally, dye 
penetrant inspection will be performed on the surface of the weld to detect and repair any 
surface-breaking defects. The lack of fusion defect is, by definition, oriented in the direction of 
the weld bead. The silicon, porosity, and tungsten are rounded defects that have no direction. 
The closure weld will be made in the hot cell facility using the narrow groove tungsten arc 
welding process. This, by definition, eliminates the lack of fusion defects between beads since 
this is a single-pass process. The other defects such as tungsten inclusion, caused by the flaking 
of the tungsten electrode, and porosity, caused by the loss of gas coverage, are easily detectable 
by monitoring systems that will be built into the welding system. This leaves only nonfusion

 3-9  
defects, which are detectable by ultrasonic testing (UT). All of the above defects are either 
rounded or in the direction of the weld seam; none is oriented in the radial direction. 
The defect description discussed above is consistent with the brief comment on flaw orientation 
in the Early Failure AMR, No information was found in the literature regarding angle of the 
flaw from a line parallel to the direction of the weld. However, most planar defects, such as lack 
of fusion and slag inclusions, would logically be expected to be oriented within a few degrees of 
the same direction in which the weld head is moving. 
This flaw description is also consistent with the relevant literature paper (Shcherbinskii and 
Myakishev 1970) that describes a statistical treatment of weld-flaw orientations based on 
analysis of a significant data set of ultrasonic flaw orientation measurements. This paper 
concludes that planar-type weld defects detected ultrasonically tend to be predominately oriented 
in the direction of the weld centerline. It appears that more than 98% of the defects fall within 
..16 degrees of the weld centerline in the case of steam-pipe welds. A similar conclusion is 
drawn from the data for sheet-structure welds. Statistical distribution of the defects with respect 
to the orientation angle yields a probability of 99% that the defects are located within about ..13 
degrees. This suggests that much less than 1% of these flaws have a potential to undergo SCC. 
Above discussions indicate that a correction factor for weld-flaw orientation for the embedded 
flaw density in the outer quarter of the thickness should be applied and used in waste package 
lifetime calculations. Based on the welding process and the inspection techniques to be 
employed for the closure welds, and the narrowness of the flaw orientation distributions 
presented in the subject paper, it is recommended that a conservative multiplication factor of 
0.01 (1%) be used on total number of flaws of any given size for the subsurface flaws. 
Ultrasonic examinations have now been performed on three actual WP welds on two mock-ups. 
These were unannealed closure welds, one on Alloy 625 and two on Alloy 22. The total length 
of weld was approximately 45 feet, and no defects were detected. Therefore, the probability of 
defects with actual welds is not inconsistent with low-defect densities that will result from this 
recommendation. 
3.1.3 Environment on the Surface of the Waste Package and Drip Shield 
The WP will experience a wide range of environments during its service life. Initially, it will be 
hot and dry due to the heat generated by radioactive decay. However, the temperature will 
eventually drop to levels where both HAC and APC will be possible. A companion AMR 
Environment on the Surface of the Drip Shield and Waste Package Outer Barrier (CRWMS 
M&O 2000a, Section 6) defines the detailed evolution of the environment on the WP surface. 
Input for this AMR includes bounding conditions for the local environment on the WP surface, 
which include temperature, RH, presence of liquid-phase water, liquid-phase electrolyte 
concentration (chloride, buffer, and pH), and oxidant level. This AMR has been used to define 
the threshold RH for HAC and APC, as well as a medium for testing WP materials under what is 
now believed to be a worst-case scenario. These test media are the neutral-pH SSW and the 
high-pH BSW, with nominal boiling points of 112 and 120C, respectively.

 3-10  
Crevices will be formed between the WP and supports, beneath mineral precipitates, corrosion 
products, dust, rocks, cement, and biofilms. After the WP fails, the gap between the WPOB and 
the stainless steel structural support can form crevices where the environment may be more 
severe than the NFE. The hydrolysis of dissolved metal can lead to the accumulation of H+ and a 
corresponding decrease in pH. Electromigration of Cl- (and other anions) into the crevice must 
occur to balance cationic charge associated with H+ ions. These conditions can exacerbate 
subsequent attack of the WPOB and stainless steel structural material by general and LC, SCC, 
and other mechanisms. Crevices might also form with the DS. These are addressed in the 
general and LC discussions in Sections 3.1.5 and 3.1.6. 
3.1.3.1 Threshold Relative Humidity 
As represented by Equation 3-1, HAC can occur at any RH above the threshold (CRWMS 
M&O 2000c, 2000d, 2000e): 
critical RH RH = (Eq. 3-1) 
Rates of HAC and APC are represented by the same cumulative distribution function. HAC is 
assumed to occur uniformly over each patch used in the WAPDEG code. Each patch is 
comparable in size to that of a LTCTF test sample. 
As discussed in the AMR Environment on the Surface of the Drip Shield and Waste Package 
Outer Barrier (CRWMS M&O 2000a, Section 6.4.2), hygroscopic salts may be deposited on the 
EBS components by aerosols and dust entrained in ventilation air, backfill, seepage water that 
enters the drifts, and the episodic water that flows through the drifts. Hygroscopic salts enable 
aqueous solutions to exist at relative humidities below 100%. The threshold RH (RHcritical) at 
which an aqueous solution will form for a particular salt is defined as the deliquescence point. 
This threshold RH defines the condition necessary for aqueous electrochemical corrosion of the 
metal to occur. The deliquescence point of NaCl is relatively constant with temperature, and is 
in the range 74-76% RH. In contrast, the deliquescence point of NaNO3 has a strong dependence 
on temperature, ranging from an RH of 75.36% at 20C to 65% at 90C. The equilibrium RH is 
50.1% at 120.6C, which is the boiling point of the saturated solution at 101.32 kPa. The 
evaporative concentration of well J-13 water, which is assumed to be typical of waters contacting 
the EBS components, results in a solution of Cl-, + - - Na CO , NO 2
3, 3 , and K+ ions. Other ions that 
could form salts with lower deliquescence points, such as Ca2+ and Mg2+, are precipitated. It is 
therefore conservatively assumed that the deliquescence point of NaNO3 determines the 
threshold RH. The equilibrium RH for a saturated solution of NaNO3 as a function of 
temperature is shown in Figure 3-3. The experimental data fit the following polynomial in 
temperature: 
701 . 81 ) ( 45377 . 0 ) ( 10 9649 . 5 ) ( 10 5932 . 3 2 3 3 5 +   -    +    - = - - C T C T C T RHcritical (Eq. 3-2) 
The goodness of fit is characterized by 
R2 = 0.9854

 3-11  
where R2 is the coefficient of determination and where R is the coefficient of correlation. This 
correlation is shown in Figure 3-3 below. The uncertainty in RHcritical is discussed in the AMRs 
on surface environment. 
Source: CRWMS, M&O 2000a, Section 6.4.2 
Figure 3-3. Deliquescence Point for Sodium Nitrate Solutions 
The evaporation of J-13 water results in high concentrations of Na+, K+, Cl-, NO3
-, and CO3
2-. 
The concentrations of F- and SO4
2- initially increase, but eventually fall due to precipitation. The 
SSW used for testing is an abstract embodiment of this observation (Section 1.5.4.3). This 
formulation is based upon the assumption that evaporation of J-13 water will eventually lead to a 
sodium-potassium-chloride-nitrate solution. The elimination of carbonate in this test medium is 
believed to be conservative, in that carbonate would help buffer pH in any occluded geometry 
such as a crevice. 
3.1.3.2 Aqueous Phase Environments 
At a given surface temperature, the existence of liquid-phase water on the WP depends upon the 
nature of the hygroscopic salt either present on the surface or contained in water dripping on the 
surface. Two conditions must exist for APC: dripping water, and RH above the deliquescence 
point of the hygroscopic salts in the dripping water. While dripping can occur without the latter 
condition being met, both conditions are necessary for APC. Without this level of RH, no 
aqueous phase could be sustained on the surface. However, this requires that the evaporation 
rate of water from the surface exceeds the rate of dripping so that equilibrium conditions exist 
(CRWMS M&O 2000a). 
y = -3.5932E-05x3 + 5.9649E-03x2 - 4.5377E-01x + 8.1701E+01 
R2 = 9.8540E-01 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
0 20 40 60 80 100 120 140 
x = T(C) 
y = Critical RH (%)

 3-12  
This model uses Equation 3-2 to conservatively estimate the threshold RH for APC (RHcritical). 
The composition of the electrolyte formed on the WP surface is assumed to be that of SCW 
below temperatures of 100C, and that of SSW above temperatures of 100C. These media are 
defined in Section 1.5.4.3. Their compositions are shown in Table 3-2 (CRWMS M&O 2000a, 
Section 6.12). General APC is assumed to occur uniformly over each WAPDEG patch, which is 
the same size as a standard LTCTF weight-loss sample. Effects of backfill are not considered on 
the APC threshold and rate. 
Table 3-2. Composition of Standard Test Media Based upon J-13 Well Water 
Ion J-13 SDW SCW SAW SSW 
(mg liter-1) (mg liter-1) (mg liter-1) (mg liter-1) (mg liter-1) 
K+1 5.04 3.40E+01 3.40E+03 3.40E+03 1.416E+05 
Na+1 45.8 4.09E+02 4.09E+04 4.09E+04 4.870E+05 
Mg+2 2.01 1.00E+00 1.00E+00 1.00E+03 0.000E+00 
Ca+2 13.0 5.00E-01 1.00E+00 1.00E+03 0.000E+00 
F-1 2.18 1.40E+01 1.40E+03 0.00E+00 0.000E+00 
Cl-1 7.14 6.70E+01 6.70E+03 2.450+04 1.284E+05 
NO3
-1 8.78 6.40E+01 6.40E+03 2.300+04 1.310E+06 
SO4
-2 18.4 1.67E+02 1.67E+04 3.860+04 0.000E+00 
HCO3
-1 128.9 9.47E+02 7.00E+04 0.00E+00 0.000E+00 
Si 28.5 27 (60C), 49 (90C) 27 (60C), 49 (90C) 27 (60C), 49 (90C) 0.000E+00 
pH 7.41 8.1 8.1 2.7 7.0 
3.1.3.3 Condensation Underneath Drip Shield 
Moist air and liquid water flow into and within the drift over time. Although the RH underneath 
the DS increases with time, conditions for condensation on the DS can only occur if the DS is 
cooler than the top of the invert and the invert moisture content produces nearly 100% RH. This 
is unlikely since the surfaces of the WP and DS are at a higher temperature than the invert. 
3.1.3.4 Composition of Water on Exposed Surfaces of Drip Shield and Waste Package 
The YMP has used test media relevant to the environment expected in the repository. Relevant 
test solutions are assumed to include SDW, SCW, and SAW at 30, 60, and 90C, as well as SSW 
at 100 and 120C (Section 1.5.4.2). The compositions of all of the environments are given in 
Table 3-2. While most of the solutions have been used for several years, the SSW has been 
recently developed. In general, anions such as chloride promote LC, whereas other anions such 
as nitrate tend to act as corrosion inhibitors. Thus, there is a very complex synergism of 
corrosion effects in the test media.

 3-13  
BSW represents another plausible extreme in water chemistry. The BSW composition was 
established on the basis of results from a distillation experiment. Tables 3-3 and 3-4, show the 
corresponding water chemistry. The total concentration of dissolved salts in the starting liquid 
was approximately five-times (5) more concentrated than that in the standard SCW solution. It 
was prepared by using five-times the amount of each chemical that is specified for the 
preparation of SCW. After evaporation of approximately ninety percent (~90%) of the water 
from the starting solution, the residual solution reaches a maximum chloride concentration and 
has a boiling point of ~112C. The resultant BSW solution contains (sampled at 112C) 9% 
chloride, 9% nitrate, 0.6% sulfate, 0.1% fluoride, 0.1% silicate, 1% (total inorganic carbon from 
carbonate and bicarbonate), 5% potassium, ion, and 11% sodium ion. 
In order to add some soluble silica to the solution, the initial BSW solution recipe was later 
revised to contain ~1% metasilicate by adding sodium metasilicate (Na2SiO39H2O). This 
solution is designated as BSW-SC where SC indicates the presence of silicate and carbonate in 
the solution. 
The pH of aqueous solutions is affected by the partial pressure of CO2 in the gas phase. The 
implication of this is that unless an effort is made to control the pH of the BSW solution, the pH 
may vary with test conditions and time. In order to conduct long-term testing (months to years), 
the test environments should be stable. Stable test solutions require that carbonate and silicate 
not be added. Both of these species can affect pH. Furthermore, gaseous CO2 must be removed 
from the air passing above the solution. With no gaseous CO2 in contact with the solution, and 
with no carbonate-bicarbonate or silicates in solution, the test environments will be stable. 
Sodium hydroxide is used to maintain the higher pH of the solution. 
Table 3-3. Initial Basic Saturated Water Solution Recipe 
Chemical Quantity (g) 
Na2CO3 (anhydrous) 10.6 
KCl 9.7 
NaCl 8.8 
NaF 0.2 
NaNO3 13.6 
Na2SO4 (anhydrous) 1.4 
H2O 55.7 
Source: CRWMS M&O 2000a, Section 6.12

 3-14  
Table 3-4. Modified Basic Saturated Water Solution Recipes 
BSW-13 BSW-12 BSW-11 
Chemical Quantity Quantity (g) Quantity (g) 
KCl 8.7 g 8.7 g 8.7 g 
NaCl 7.9 g 7.9 g 7.9 g 
NaF 0.2 g 0.2 g 0.2 g 
NaNO3 13.0 g 13.0 g 13.0 g 
Na2SO4 (anhydrous) 1.4 g 1.4 g 1.4 g 
H2O (deionized) 66 ml 66 ml 66 ml 
10N NaOH 2 ml 
1N NaOH 2 ml 
0.1N NaOH 2 ml 
CO2 partial pressure 0 0 0 
pH (measured at room temperature) 13.13 12.25 11. 11 
Source: CRWMS M&O 2000a, Section 6.12 
NOTE: The CO2 partial pressure can be minimized by either scrubbing laboratory air or purchasing CO2 free air. 
In order to maintain constant pH conditions, the BSW solution was modified for corrosion tests, 
yielding BSW-11, BSW-12, and BSW-13. The three solutions have pH values of 
approximately 11, 12, and 13, respectively. The recipes of these solutions are given in 
Table 3-4. 
3.1.4 Phase Stability and Aging 
Exposure of materials like Alloy 22 to elevated temperatures can result in the formation of 
undesirable phases. The phases which form in Alloy 22 are often rich in molybdenum and 
chromium, the two elements that are responsible for the high degree of corrosion resistance of 
this material. The formation of precipitates depletes these alloying elements from the 
surrounding areas, therefore increasing susceptibility to general and LC, as well as SCC. 
Formation of brittle molybdenum- or chromium-rich intermetallics can also lead to 
embrittlement of the material and degradation of its mechanical properties. LRO in alloys 
similar to Alloy 22 has been linked to an increased susceptibility to SCC and hydrogen 
embrittlement. 
The aging of Alloy 22 is dependent on both time and temperature. While the effects of aging 
have been observed for exposures to elevated temperatures (>600C) for short time periods, it is 
important to know the kinetics of this process to enable prediction of aging effects for lower 
temperatures (200-300C) and much longer times (10,000 years).

 3-15  
This section discusses the process-level model developed to account for aging and phase stability 
in Alloy 22. The development of this model is presented in detail in the corresponding AMR 
(CRWMS M&O 2000b). Only the highlights will be presented here. 
3.1.4.1 Phase Identification in Alloy 22 
The long-term aging of Alloy 22 at elevated temperature can cause the precipitation of 
undesirable intermetallic phases, if the temperature is sufficiently high. In order to provide a 
technical basis for the development of a model for aging effects in Alloy 22, samples were aged 
for a variety of times at different temperatures: for 40,000 hours at 260, 343, and 427C; for 
30,000 hours at 427C; for 1000 hours at 482, 538, and 593C; and for 16,000 hours at 593, 649, 
704, and 760C. Samples were then examined with transmission electron microscopy (TEM). A 
weld sample aged at 427C for 40,000 hours was also examined in the weld metal, in the HAZ, 
and in the base metal removed from the weld. Several phases were observed to form in 
Alloy 22: P, , s, carbide, and Ni2 (Cr, Mo) LRO. At 593C, P phase was observed only on the 
GB. At the higher aging temperatures (649, 704, and 760C), both  and P phases precipitated 
on grain boundaries. As the aging temperature increased, more  and P phase precipitation 
occurred within the grains. GB carbide precipitation was observed in samples aged at 593 and 
704C. Because of the small amount of carbide present in these samples and the small volume 
examined in TEM, it is likely that carbides also form at 649C. A s phase was observed in the 
samples aged at 704 and 760C. The amount of s phase observed in these samples was small 
compared to the amount of  and P phases. Long range order (LRO) was observed in the 
samples aged at 593C for 16,000 hours and for 1,000 hours, in the sample aged at 538C for 
1,000 hours, and in the samples aged at 427C for 40,000 hours and for 30,000 hours. These 
observations are summarized in Table 3-5. 
3.1.4.2 Kinetics of Intermetallic Precipitation in Alloy 22 Base Metal 
Table 3-6 shows the aging times for the various stages of intermetallic precipitation in Alloy 22 
base metal as a function of temperature. These times were approximated from the examination 
of aged samples after approximately 1, 10, 100, 1000, and in some cases 16,000 hours. The 
errors noted are due to the uncertainty associated with the coarse time intervals of examination, 
and are not due to any measurement and test equipment uncertainties, which are much smaller. 
For example, if precipitation was observed on twin boundaries at 100 hours, it could have begun 
at any time between 10 and 100 hours. In that case, the time noted for the start of precipitation 
on the twin boundaries would be 55 hours (halfway between 10 and 100), with upper and lower 
error bars of 45 hours. Because of the coarse examination intervals, there is some judgment 
involved in choosing the times noted in Table 3-6. These measurements are only intended as an 
initial estimate of the precipitation kinetics. These measurements were also used to generate the 
isothermal time-temperature-transformation (TTT) diagram for Alloy 22 base metal shown in 
Figure 3-4. Some of the data presented in Table 3-5 are also shown in Figure 3-4. The curve 
associated with LRO came from TEM observations. Only a limited number of samples were 
examined in TEM; therefore, it is likely that ordering occurs at shorter times than indicated in 
Figure 3-4. The precipitation of intermetallic phases at grain boundaries in Alloy 22 is shown in 
Figure 3-5 as the white phase surrounding the grains.

 3-16  
Table 3-5. Intermetallic Phases Observed in Alloy 22 with Transmission Electron Microscopy 
Aging Condition Phases Observed to Form in Alloy 22 
260C for 40,000 hr No LRO - No signs of GB precipitation in base metal 
343C for 40,000 hr No LRO - No signs of GB precipitation in base metal 
427C for 30,000 hr LRO - No signs of GB precipitation in base metal 
427C for 40,000 hr LRO - No signs of GB precipitation in base metal 
482C for 1000 hr No LRO - No signs of GB precipitation in base metal 
538C for 1000 hr LRO - No signs of GB precipitation in base metal 
593C for 1000 hr LRO - GB films of P phase 
593C for 16,000 hr 
LRO - GB films of P phase  
Carbide precipitates at GB 
649C for 16,000 hr 
No LRO 
Precipitation of P and  phase mainly at GB 
704C for 16,000 hr 
No LRO  
Precipitation of P and  phase at GB and within the grains - Carbide and s precipitation 
at GB 
760C for 16,000 hr 
No LRO 
Precipitation of P and  phase at GB and within the grains - s precipitation at GB 
Source: CRWMS M&O 2000b, Section 6.1 
Table 3-6. Time Required for Precipitation of Intermetallic and Carbide Particles on the Grain 
Boundaries of Alloy 22 Base Metal 
Temp Time to Start on Grain Boundaries Time to Cover Grain Boundaries 
(C) Lower Error Time (hr) Upper Error Lower Error Time (hr) Upper Error 
593 0 10 90 7500 8500 7500 
649 1 1 9 450 550 450 
704 0.5 0.5 0.5 90 100 900 
760 0.5 0.5 0.5 9 10 109 
800 0.5 0.5 0.5 9 10 90 
Temp Time to Start on Twin Boundaries Time to Start Within Grains 
(C) Lower Errora Time (hr) Upper Errora Lower Error Time (hr) Upper Error 
593 N/A 
None 
observedb N/A N/A 
None 
observedb N/A 
649 450 550 450 7500 8500 7500 
704 90 100 900 450 550 450 
760 54.5 64.5 54.5 54.5 64.5 54.5 
800 45 55 45 45 55 45 
Source: CRWMS M&O 2000b, Section 6.2 
a Lower and upper errors represent the lower and upper limits for the data 
b None observed after 16,000 hrs.

 3-17  
Source: CRWMS M&O 2000b, Section 6.2 
Figure 3-4. Isothermal Time-Temperature-Transformation Diagram for 
Alloy 22 Base Metal 
Nucleation and growth kinetics can be represented by an equation of the form: 
) exp( 1 n kt f - - = (Eq. 3-3) 
where f is the volume fraction of the precipitating phase, t is time and k and n are constants. The 
value of k depends on nucleation and growth rates, and, therefore, depends very strongly on 
temperature. This dependence is shown in Equation 3-4: 
) / exp( 2 1 T C C k - = (Eq. 3-4) 
where C1 and C2 are constants, and T is the absolute temperature in Kelvins. Combining 
Equation 3-3 and Equation 3-4 at constant volume fraction yields: 
( ) f f C 
T n 
C 
t +  = 1 
ln 2 (Eq. 3-5) 
where tf is the time to reach a given volume fraction of GB precipitation. Plots of logarithm of 
time versus reciprocal temperature for the various stages of precipitation in Alloy 22 base metal 
are shown in Figure 3-6. At the higher temperatures, GB precipitation is predicted to start after 
1 hour, which is the shortest aging time investigated thus far. 
300 
400 
500 
600 
700 
800 
900 
1 10 100 1000 10000 100000 Time (hr) 
Temperaure (C) 
Partial GB Coverage Complete GB Coverage No GB Precipitation 
LRO Not Examined 
No precipitates on GBs 
Complete coverage of GBs with precipitates 
LRO 
Partial 
coverage of 
GBs

 3-18  
Source: CRWMS M&O 2000b, Section 4.1.2 
NOTE: Increased precipitation in the GB after 1,000 hr of aging compared to 100 hr. 
Figure 3-5. Effect of Thermal Aging at 649C on the Precipitation of Intermetallic Phases at Grain Boundaries on Alloy 22 
Mill Annealed 100 hr 1000 hr

 3-19  
Source: CRWMS M&O 2000b Section 6.2 
Figure 3-6. Time to Reach Various Stages of Precipitation in Aged Alloy 22 Base 
Metal Plotted on a Log Scale as a Function of Reciprocal Temperature 
(see Equation 3-5) 
If it can be assumed that the precipitation mechanism does not change, the lines in Figure 3-6 can 
be extrapolated to give the times required for the various stages of precipitation at lower 
temperatures. The measured times are based on examination of micrographs of samples with 
widely spaced aging times. Extrapolation to lower temperature is difficult since the precipitation 
rate is very sensitive to temperature. A small change in slope can make a very large change in 
the time obtained from extrapolation to low temperature. In order to make a bounding argument, 
however, the curves associated with GB coverage and bulk precipitation in Figure 3-6 are 
graphically extrapolated to 10,000 years in Figure 3-7. The start of GB precipitation is not 
plotted because of the limited amount of available data. It must be noted that all data is regarded 
as preliminary at the present time. Additional work is needed. 
1 
10 
100 
1000 
10000 
100000 
0.00095 0.00100 0.00105 0.00110 0.00115 0.00120 
1/T (K-1) 
Time (hr) 
S tart of Grain B oundary Precipitation Grain Boundaries Fully Covered 
S tart of Bulk Precipitation Expon. (S tart of Grain Boundary Precipitation) 
Expon. (Grain Boundaries Fully Covered) Expon. (S tart of B ulk Precipitation) 
593C 
760C

 3-20  
Source: CRWMS M&O 2000b, Section 6.2 
Figure 3-7. Graphical Extrapolation of the Curves to Repository-Relevant Temperatures

 3-21  
The horizontal axes in Figure 3-7 are reciprocal temperature; temperature increases to the left. If 
an extrapolation of the data intersects the horizontal line corresponding to 10,000 years to the left 
of the vertical line corresponding to 300C, then the temperature must be held higher than 300C 
to get bulk precipitation in 10,000 years. In both cases, the data indicate that intermetallic 
precipitation will not occur in less than 10,000 years, even if the temperature is held at 300C. 
Also plotted in Figure 3-7 are lines with the minimum possible slope allowed by the error bars 
on the data. Even accounting for the rather large uncertainty, bulk precipitation does not appear 
likely in 10,000 years at 300C. However, GB precipitation might occur if the Alloy 22 stayed 
at 300C for 10,000 years. Therefore, a good bounding argument would be to assume that 
precipitation covers the grain boundaries. As can be seen in the TTT diagram of Figure 3-4, 
samples aged in the laboratory for more than 100 hours at 700C would produce a microstructure 
with precipitation covering the grain boundaries. Complete GB coverage is taken to represent a 
fully aged material (worst case). Corrosion data obtained from Alloy 22 base metal aged in such 
a way should represent a worst case condition in regard to phase stability. Corrosion data 
obtained with aged samples are presented in Section 3.1.4.5 and are presented in greater detail in 
the AMR on the WPOB (CRWMS M&O 2000c, Section 6.7). 
Figure 3-7a shows calculated WP surface temperature as a function of repository storage time 
(CRWMS M&O 2000r). The curves shown are for the hottest (design basis) WP with and 
without backfill option. It can be seen that, for the case of no backfill, WP temperatures are 
sufficiently low that phase stability of Alloy 22 should not be an issue. 
Source: CRWMS M&O 2000r 
Figure 3-7a. Temperature of the WPOB Surface as a Function of Time 
for the Hottest Waste Package 
0 
50 
100 
150 
200 
250 
300 
350 
400 
450
0.0 0.1 1.0 10.0 100.0 1000.0 10000.0 
Time (Years) 
Temperature (Degrees C) 
21-PWR Design Basis WP 
with 25-Year Ventilation 
and Backfill 
21-PWR Design Basis WP 
with 25-year Ventilation 
and without Backfill

 3-22  
As a measure of the reasonableness of the data plotted in Figure 3-7, the activation energy can be 
calculated. The slopes of the lines in Figure 3-7 (after accounting for the log(e) factor) are equal 
to C2/n in Equation 3-5. If these slopes are averaged and n is assumed to be equal to one, then 
the activation energy is 280 kJ mol-1 (68 kcal mol-1 using a gas constant R=1.987 cal mol-1 K-1). 
This is close to the value of 62 kcal mol-1 obtained for precipitation in Alloy C-276. This value 
is also typical for diffusion of relevant elements in nickel. For example, the activation energy for 
diffusion of chromium in nickel is 272.6 kJ mol-1, that of iron is 253-270 kJ mol-1, and that of 
tungsten in nickel is 300-308 kJ mol-1. 
3.1.4.3 Kinetics of Intermetallic Precipitation in Alloy 22 Welds 
The HAZ of a weld is the region of the base metal near the weld that is subjected to a significant 
thermal pulse during the welding process. Intermetallic precipitation processes in the HAZ are 
expected to be similar to that in the base metal, but actual rates of precipitation (kinetics) may be 
different. The high temperatures, approaching the melting point, seen in the HAZ of welds 
might trigger nucleation of intermetallic carbide precipitates. If nuclei are already present, 
precipitation will proceed much faster than in the base metal where they are not present. 
Very few precipitates have been observed in the HAZ of weld samples thus far, but only two 
weld samples have been examined: one in the as-welded condition and one after aging at 427C 
for 40,000 hours. These precipitates may simply be carbides that were present in the millannealed 
(as-received) condition. Carbides are known to be present in nickel-based alloys 
similar to Alloy 22, but they are usually within the grains. These are generally called primary 
carbides to distinguish them from other secondary phases that often form, on the GB after an 
aging treatment. 
Welding causes melting of the alloy and the development of an as-cast structure upon cooling. 
As an Alloy 22 weld solidifies, molybdenum and chromium are rejected from the solid phase 
causing their concentration to increase in the liquid. Therefore, the interdendritic regions, which 
are the last solid to form in a weld, tend to have high concentrations of these elements relative to 
typical values for Alloy 22. Because formation of the intermetallic phases, which are also 
enriched in molybdenum and/or chromium, are favored by higher molybdenum and chromium 
concentrations, these phases are present in the interdendritic regions of Alloy 22 welds. 
Because precipitates are present in Alloy 22 welds from the beginning, kinetics of precipitation 
in welds is not an issue. Corrosion data available from the LTCTF shows no measurable 
difference between welded and base metal samples.

 3-23  
3.1.4.4 Kinetics of Reactions in Alloy 22 
The LRO is treated in a manner similar to that discussed for intermetallic and carbide 
precipitation. However, very little kinetic data exists for LRO in Alloy 22. Thus far, LRO has 
been observed in five samples. A very fine dispersion of ordered domains was seen in Alloy 22 
base metal after aging for 30,000 and 40,000 hours at 427C, and was also seen in a weld 
similarly aged. The ordering in these cases was so fine that it would have been very difficult to 
measure the volume fraction of the ordered domains. LRO was also observed in Alloy 22 base 
metal aged at 593C for 16,000 hours, and at 538 and 593C for 1,000 hours. The volume 
fraction of ordered domains has not been measured in these samples. No LRO was observed 
with TEM in Alloy 22 base-metal samples aged for 40,000 hours at 260 and 343C, or for 
1,000 hours at 482C. 
A bounding argument may be made by using two facts: LRO is just beginning after aging for 
30,000 hours at 427C together; LRO domains are small after aging for 1,000 hours at 538C. 
The corresponding points are graphed as an Arhenius plot in Figure 3-8. Samples aged for 
shorter times at 427 and 538C have not yet been examined in TEM. The curve in Figure 3-8 
may shift to shorter times (down) after more data are collected. Because the LRO domains are 
very small after aging at 427C for 30,000 hours, the point corresponding to this aging condition 
is not likely to change much (Figure 3-8). In other words, LRO is not likely to occur in Alloy 22 
base metal at 427C in times significantly less than 30,000 hours. After more data are collected, 
the data point corresponding to aging at 538C for 1,000 hours will most likely shift down more 
than that corresponding to aging at 427C for 30,000 hours. Since this shift will cause the slope 
to increase, the curve in Figure 3-8 represents a bounding case. This graph indicates that LRO 
may occur in less than 10,000 years at 300C. Equation 3-6 was obtained by curve fitting and is 
shown in Figure 3-8: 
( ) ( ) T 
x t 
17395 
10 5 ln ln 7 + = - (Eq. 3-6) 
Solving Equation 3-6 for temperature T yields: 
) 10 5 ln( ) ln( 
17395 
7 - - 
= 
x t 
T (Eq. 3-7) 
Based upon this analysis, it is concluded that no LRO will occur after 10,000 years 
(8.8107 hours), provided that the temperature remains below approximately 260C (530 K). 
More samples are being tested to confirm this conclusion.

 3-24  
Figure 3-8. Graphical Extrapolation of the Limited Kinetic Data for Long 
Range Order in Alloy 22 Base Metal 
3.1.4.5 Effects of Thermal Aging on Corrosion Potential and Rate 
The long-term aging of Alloy 22 at elevated temperature can cause the precipitation of 
undesirable intermetallic phases. Based upon the analyses discussed in the preceding section, it 
is recommended that the WP surface temperature be limited to levels below 300C. An 
extrapolation of the data shown in Figure 3-6 indicates that the phase stability of Alloy 22 base 
metal will not be a problem below this limit. The significance of the uncertainties in this data is 
discussed in Section 3.1.9. At temperatures above 350C, there is unacceptable degradation of 
cladding on the SNF. With these two constraints, the impact of aging and phase instability on 
the corrosion of Alloy 22 should be minimal. 
Samples of Alloy 22 were aged at 700C for either 10 or 173 hours. The corrosion resistance of 
these aged samples is compared to that of base metal in several standardized test media. 
Figure 3-9 shows a comparison of CP curves for base metal and thermally aged material in SAW 
at 90C. Both curves exhibit generic Type 1 behavior (see Section 3.1.6.3). Type 1 behavior is 
indicative of passive film stability between the corrosion potential and the thermodynamic limit 
of the electrolyte (oxygen evolution). In this case, aging shifts the corrosion potential to less 
noble values, from -176 to -239 mV (versus a standard Ag/AgCl reference electrode). The 
passive current density is increased slightly, which is interpreted as a slight increase in corrosion 
rate. The highest non-equilibrium passive current density observed for the base metal is 
approximately 4 A cm-2, compared to approximately 10 A cm-2 for fully aged material.

 3-25  
Source: CRWMS M&O 2000c, Section 6.7.1 
Figure 3-9. Effect of Thermal Aging for 173 Hours at 700C on the 
Corrosion Resistance of Alloy 22 in Simulated Acidic 
Concentrated Water at 90C (DEA002 and DEA201) 
Figure 3-10 shows a comparison of CP curves for base metal and thermally aged material in 
SCW at 90C. In this case, aging also appears to shift the corrosion potential to less noble 
values, from -237 to somewhere between -328 and -346 mV versus a standard Ag/AgCl 
reference electrode. In all three cases, the anodic oxidation peak that is characteristic of generic 
Type 2 behavior is observed. See Section 3.1.6.3 for more detailed discussion. In tests with 
BSW-13, aging also appears to shift the corrosion potential to less noble values. 
1.0E-08 
1.0E-07 
1.0E-06 
1.0E-05 
1.0E-04 
1.0E-03 
1.0E-02 
1.0E-01 
1.0E+00
-400 -200 0 200 400 600 800 1000 1200 1400 
Potential (mV vs. Ag/AgCl) 
Current Density (A/cm2) 
DEA002 base metal 
DEA201 aged for 173 hours at 700 C 
Ecorr = -239 mV 
Ecorr = -176 mV 
Effect of Aging on Corrosion of Alloy 22 in SAW at 90 C 
Scan Direction

 3-26  
Source: CRWMS M&O 2000c, Section 6.7.1 
Figure 3-10. Effect of Thermal Aging for 173 Hours at 700C on the 
Corrosion Resistance of Alloy 22 in Simulated 
Concentrated Water at 90C (DEA016, DEA202, and 
DEA203) 
In summary, a fully aged sample of Alloy 22 appears to exhibit a less noble corrosion potential. 
Typically, the corrosion potential of such a sample is shifted approximately -63 mV in SAW at 
90C; -109 mV in SCW at 90C; and more than -100 mV in BSW at 100C. Based on this data, 
it appears that Ecorr can be corrected to account for fully aged material by subtracting 
approximately 100 mV from values calculated for the base metal. The shift in Ecritical (Threshold 
Potential 1) also appears to be approximately 100 mV in most cases. Thus, the difference 
Ecritical-Ecorr is virtually unchanged. This implies that even though the corrosion potential is 
shifted, the susceptibility to LC remains unchanged. 
The effect of thermal aging on the corrosion rate is accounted for in an enhancement factor, 
Gaged, and is based upon a ratio of the non-equilibrium passive current densities for base metal 
and aged material. 
original effective 
aged 
corrected effective dt 
dp 
G 
dt 
dp 
. .
.
. 
. .
.
. 
 = . .
.
. 
. ..
. 
(Eq. 3-8) 
1.0E-09 
1.0E-08 
1.0E-07 
1.0E-06 
1.0E-05 
1.0E-04 
1.0E-03 
1.0E-02 
1.0E-01 
1.0E+00
-600 -400 -200 0 200 400 600 800 1000 1200 1400 
Potential (mV vs. Ag/AgCl) 
Current Density (A/cm2) 
DEA016 base metal 
DEA202 aged 173 hours at 700 C 
DEA203 aged 173 hours at 700 C 
Ecorr = -237 mV 
Ecorr = -346 mV 
Ecorr = -328 mV 
Effect of Aging on Corrosion of Alloy 22 in SCW at 90 C 
Scan Direction

 3-27  
where dp/dt is the penetration rate for LC. The value of Gaged for Alloy 22 base metal is 
approximately one (Gaged ~ 1), whereas the value of Gaged for fully aged material is larger (Gaged 
~ 2.5) (CRWMS M&O 2000c). Material with less precipitation than the fully aged material 
would have an intermediate value of Gaged (1 = Gaged = 2.5). Therefore, a value of 2.5 for Gaged is 
conservatively used to bound the potential aging effect. Corrosion is discussed in greater detail 
in the sections that follow. 
3.1.5 General Corrosion 
The integrated model for general corrosion of the materials of interest includes sub-models for 
dry oxidation, humid air and aqueous phase corrosion. Details of these sub-models are provided 
in supporting AMRs (CRWMS M&O 2000c, 2000d, and 2000e). A schematic representation of 
the integrated model for WP and DS materials, as well as an augmentation of this model, are 
shown in Figures 3-11 and 3-12. Only a brief summary of the integrated model and component 
sub-models is provided here. 
3.1.5.1 Dry Oxidation 
Dry oxidation (DOX) occurs at any RH below the threshold for HAC: 
critical RH RH < (Eq. 3-9) 
This process results in the formation of an adherent, protective oxide film of uniform thickness. 
The rate of DOX may be limited by the rate of mass transport through the growing metal oxide 
film. In such cases, the oxide thickness is expected to obey a parabolic growth law (film 
thickness proportional to the square root of time). This scenario has been adopted for Alloy 22 
and 316NG due to the availability of data at elevated temperature to support such a model. 
Reasonable values of the parabolic rate constant are discussed below. It must be noted that a 
logarithmic law may be more applicable at lower temperatures. However, there is insufficient 
data to support such a model for Alloy 22 and 316NG. There is sufficient data to support the 
application of a logarithmic law to the DOX of titanium. It is assumed that DOX occurs 
uniformly over each WAPDEG patch, which is comparable in size to that of a LTCTF sample 
with generic weight-loss geometry. Backfill effects are not included in the model for DOX 
threshold and rate.

 3-28  
Source: CRWMS M&O 2000c, Section 6.10 
Figure 3-11. Schematic Representation of Model for General Corrosion 
and Localized Corrosion of Drip Shield and Waste Package 
Materials 
critical RH RH = 
? Dripping 
DOX dt 
dp 
HAC dt 
dp 
GC dt 
dp 
LC dt 
dp 
critical corr E E = 
C T  = 100 
) ( 
) (
) ( 
3 
2 
1 
T f i 
T f E 
T f E
SCW 
pass 
critical 
corr
= 
= 
= 
) ( 
) (
) ( 
6 
5 
4
T f i 
T f E 
T f E
SSW 
pass 
critical 
corr
= 
= 
= 
Dripping RH T , , 
Effective dt 
dp 
yes 
yes 
yes 
yes no 
no 
no 
no 
To Figure 3-12

 3-29  
Source: CRWMS M&O 2000c, Section 6.10 
NOTE: A similar strategy is used to account for aging. 
Figure 3-12. Schematic Representation Showing Augmentation of 
Model for General Corrosion and Localized Corrosion to 
Account for Microbiologically Influenced Corrosion of Drip 
Shield and Waste Package Materials 
3.1.5.1.1 Dry Oxidation of Alloy 22 and 316NG 
DOX of Alloy 22 and 316NG stainless steel is expected to occur at any RH < RHcritical, thereby 
forming an adherent, protective oxide film of uniform thickness. It is assumed that the protective 
oxide film is primarily Cr2O3. The oxidation reaction is given as 
3 2 2 3 2 3 4 O Cr O Cr .. . + (Eq. 3-10) 
% 90 = RH 
1 = MIC G 
yes no 
1 = MIC G 
original effective 
MIC 
corrected effective dt 
dp 
G 
dt 
dp 
. ..
. 
. .
.
. 
 = . .
.
. 
. .
.
. 
Effective dt 
dp 
From Figure 30-11

 3-30  
The rate of DOX is limited by mass transport through this growing metal oxide film with the 
film thickness being proportional to the square root of time. This is represented by 
Equation 3-11: 
x = x0
2 + k  t (Eq. 3-11) 
where x 0 is the initial oxide thickness, x is the oxide thickness at time t, and k is a temperaturedependent 
parabolic rate constant. 
To facilitate an approximate calculation, published values of k can be used (CRWMS 
M&O 2000c, Sections 1.6 and 6.10). The highest WP temperature in the repository is expected 
to be approximately 350C (623 K), which corresponds to the limit for the SNF cladding. Note 
that the cladding will be hotter than the WPOB. The value of k corresponding to this upper 
temperature limit is 2.7310-24 m2 s-1 (8.6110-5 square m per year). After one year, this 
corresponds to a growth of about 0.0093 m. The estimated rate (9.3 nm y-1) is comparable to 
that expected for APC at lower temperatures, based upon data presented in this PMR. The 
parabolic law is used to represent the DOX Alloy 22 and 316NG, and is relatively conservative. 
3.1.5.1.2 Dry Oxidation of Titanium Grade 7 
As discussed in the AMRs for general and LC of the DS (CRWMS M&O 2000d, Section 6.1), 
the logarithmic growth law may be more appropriate at low temperature than the parabolic law. 
However, such a logarithmic expression predicts that the oxide thickness (penetration) 
asymptotically approaches a small maximum value. In contrast, the parabolic law predicts 
continuous growth of the oxide, which is much more conservative. Figure 3-13 shows a 
regression analysis of DOX rate data for titanium, where X is the oxide thickness at time t and 
Xmax is the maximum oxide thickness.

 3-31  
Source: CRWMS M&O 2000d, Section 6.1 
Figure 3-13. Regression Analysis of Dry Oxidation Rate Data for Titanium 
3.1.5.2 Humid Air Corrosion 
HAC is assumed to occur above a threshold RH, provided that there are no impinging drips: 
critical RH RH = (Eq. 3-12) 
The threshold RH for HAC (RHcritical) is assumed to obey Equation 3-2. Note that threshold 
RH and critical RH are synonymous terms. The existence of this threshold is due to the 
relationship between water adsorption and RH. 
It can be conservatively assumed that the rate of HAC can be represented by the same corrosion 
rate distribution used for APC during the period where HAC is operable. It is further assumed 
that the corrosion rate is constant and does not decrease with time (at times greater than two 
years). Less conservative corrosion models assume that the rate decays with time. The rates for 
APC of stainless steel 316NG, Alloy 22, and Titanium Grade 16 (analog of Titanium Grade 7) 
are described in detail elsewhere in this section. 
3.1.5.3 Aqueous Phase Corrosion 
At a given temperature, the existence of liquid-phase water on the surface of the WP depends 
upon the presence of a salt deposit. In the presence of such a deposit, a thin-film liquid phase 
can be established at a higher temperature than otherwise possible. In the model discussed here, 
it is assumed that two conditions must be met for APC: RH above the deliquescence point of the 
y = -0.0345x - 0.2549 
R2 = 0.9455 
y = -0.0538x + 0.011 
R2 = 0.9997 
y = -0.0210x - 0.1095 
R2 = 0.9841 
-7 
-6 
-5 
-4 
-3 
-2 
-1
0
1 
0 20 40 60 80 100 120 140 
x = t (min) 
y = ln(1-X/Xmax) 
400 C 
500 C 
600 C

 3-32  
deposit at the temperature of the WP surface and drips impinging on the WP surface. The 
threshold RH for APC is identical to that for HAC: 
critical RH RH = (Eq. 3-13) 
This threshold RH for APC (RHcritical) is also assumed to obey Equation 3-2, which is based upon 
the AMR entitled Environment on the Surface of Drip Shield and Waste Package Outer Barrier 
(CRWMS M&O 2000a, Section 6.4.2). For the time being, the composition of the electrolyte 
formed on the WP surface is assumed to be that of SCW below 100C, and that of SSW above 
100C. The distributions of GC rates for APC of stainless steel 316NG, Alloy 22, and Titanium 
Grade 16 (analog of Titanium Grade 7) are described in detail in this PMR. It is conservatively 
assumed that the corrosion rate is constant and that it does not decrease with time (at times 
greater than two years). 
3.1.5.4 Rates of General and Localized Corrosion 
Penetration rates based upon GC are used in the model if the threshold potential (Ecritical) is not 
exceeded. GC rates have been estimated based on the weight-loss data from the LTCTF. LC 
rates and failure mode characteristics (e.g., number of failure sites and opening size) must be 
estimated from other published data. Since pitting of Alloy 22 or Titanium Grade 16 has not 
been observed in the LTCTF, it is assumed that crevice corrosion is the primary mode of LC (if 
localized attack occurs at all). This accelerated mode of attack is assumed to occur uniformly 
over the entire affected WAPDEG patch. Uncertainty is accounted for in the WAPDEG 
stochastic simulation. 
3.1.5.4.1 Rates for 316L Stainless Steel  Published Data 
The samples involved in the YMP corrosion testing program do not include stainless steel 
specimens. Therefore, data published in the literature must be used to determine corrosion rates. 
Rates of LC are used if the threshold potential is exceeded. Otherwise, GC rates are used. The 
distribution of general and LC rates were estimated from the published data for Types 304 and 
316 stainless steels presented in the AMR on degradation of the stainless steel structural material 
(CRWMS M&O 2000e, Section 6.5). These data are shown in Figures 3-14 through 3-17. 
Curves are shown for GC in atmospheric and aqueous-phase environments, as well as for LC in 
aqueous-phase environments. The corresponding distributions can be represented by the 
following general correlation: 
x b b y 1 0 + = (Eq. 3-14) 
where y is the cumulative probability or percentile, and x is the logarithm of the corrosion rate, 
which is expressed in microns per year. Parameters are given in Figure 3-15. These cumulative 
distribution functions are truncated for any nonsensical calculated values above one-hundred 
percent (100%). These distributions do not reflect any environmental dependence, since such a 
correlation could not be established based upon published data. It is assumed that these 
distributions are primarily due to variability. In lieu of rigorous estimates of uncertainty, the 
uncertainty is assumed to be comparable to the variability.

 3-33  
Source: CRWMS M&O 2000e, Section 6.5 
Figure 3-14. Range of Observed Penetration Rates for Stainless Steels 304 
and 316 Shown as Cumulative Probability Distributions 
Source: CRWMS M&O 2000e, Section 6.5 
Figure 3-15. Range of Observed Logarithms of Penetration Rates for 
Stainless Steels 304 and 316 Shown as Cumulative 
Probability Distributions 
y = 57.657x - 38.597 
R2 = 0.8545 
y = 63.509x + 132.57 R 2 = 0.9649 
y = 63.818x - 170.31 R 2 = 0.9128 
y = 108.29x + 259.11 
R2 = 0.8948 
y = 36.85x + 38.91 
R2 = 0.9618 
y = 71.564x - 184.2 
R2 = 0.9737 
0.000 
20.000 
40.000 
60.000 
80.000 
100.000 
120.000 
140.000
-3.000 -2.000 -1.000 0.000 1.000 2.000 3.000 4.000 5.000 
Log Rate (microns/year) 
Percentile 
304 - Atmospheric 304 - Aqueous 304 - Localized Attack 
316 - Atmospheric 316 - Aqueous 316 - Localized Attack 
Linear (304 - Aqueous) Linear (304 - Atmospheric) Linear (304 - Localized Attack) 
Linear (316 - Atmospheric) Linear (316 - Aqueous) Linear (316 - Localized Attack) 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 
Rate (microns/year) 
Percentile 
304 Atmpospheric 
316 - Atmospheric 
304 - Aqueous 
316 - Aqueous 
304 - Localized Attack 
316 - Localized Attack

 3-34  
Source: CRWMS M&O 2000e, Section 6.5 
Figure 3-16. Range of Localized Penetration Rates for Stainless Steels 
304 and 316 
Source: CRWMS M&O 2000e, Section 6.5 
Figure 3-17. Comparison of Observed Penetration Rates for Stainless 
Steels 304 and 316 
0.001 
0.010 
0.100 
1.000 
10.000 
100.000 
1,000.000 
10,000.000 
100,000.000 
0 10 20 30 40 50 60 70 80 90 100 
Percentile 
Penetration Rate (microns/year) 
304 - Atmospheric 
316 - Atmospheric 
304 - Aqueous 
316 - Aqueous 
304 & 316 - Localized Attack 
y = 9E-05e0.1227x 
R2 = 0.9565 
0.001 
0.010 
0.100 
1.000 
10.000 
100.000 
0 10 20 30 40 50 60 70 80 90 100 
Percentile 
Penetration Rate (mm/y)

 3-35  
From a comparison of the data for Types 304 and 316 stainless steels, the advantages of 
molybdenum additions are evident. Since Type 316 stainless steel contains more molybdenum 
than Type 304 stainless steel, the corrosion rates of Type 304 stainless steel are higher than 
comparable rates of Type 316 stainless steel. From Figure 3-14, the localized corrosion rates of 
Type 316 stainless steel appear to lie between 103 and 104 m y-1. The general corrosion rates 
for APC of Type 316 appear to lie between 10-1 and 102 m y-1. The general corrosion rates for 
HAC (atmospheric corrosion) of Type 316 stainless steel appear to lie between 10-3 and 10- 
1 m y-1. It is assumed that the published rates for Type 316 stainless steel are representative of 
those for Type 316NG stainless steel. The regression line shown in Figure 3-15 is assumed to 
represent the combined uncertainty and variability. Figures 3-16 and 3-17 show the probability 
distribution of the corrosion rates and comparison of the observed penetration rates for 
Types 304 and 316 stainless steels, respectively. 
3.1.5.4.2 Rates for Nickel-Based Alloy 22  Weight-Loss Measurements from Long 
Term Corrosion Test Facility 
The Long-Term Corrosion Test Facility (LTCTF) provides a relatively complete source of 
corrosion data for Alloy 22 in environments relevant to the potential high-level radioactive waste 
(HLW) repository at Yucca Mountain. The results from that facility are described in detail in the 
AMR on GC of Alloy 22 (CRWMS M&O 2000c, Section 6.5.2). Testing is done in a wide range 
of plausible media, including SDW, SCW, SAW, and SCMW. SDW has ten times (10) the 
ionic content of J-13 well water, while SCW has 1000 the ionic content. The measured pH 
levels of the 10 and 1000 J-13 waters are 9.5 to 10. SAW is acidified water that has 4000 the 
ionic content of J-13 water and a pH of approximately 2.7. These concentrated test solutions are 
intended to mimic the evaporative concentration of electrolytes on the hot WP surface. Due to 
solubility limitations, not all salts in the water concentrate to the same nominal levels. However, 
the more soluble anions such as chloride, sulfate, and nitrate (which have the biggest effects on 
corrosion) do reach nominal levels. 
Specimens are tested at two temperatures (60 and 90C) in each water chemistry. Half of the 
specimens are fully immersed, while the remaining half are exposed to the wet vapor above the 
water line. A few specimens are placed right at the water line. Half of the specimens contain 
welds, while the remaining half are unwelded. 
Crevice specimens are mounted to support racks with Teflon-coated fasteners and washers. 
Teflon crevice-forming washers are spring loaded to ensure that contact is maintained between 
the washers and specimens (crevice effects are more severe in tight crevices). 
At least 144 test specimens are measured during each exposure period (6-, 12-, and 24-month, 
thus far). The general corrosion rates are determined from weight-loss measurements made at 
the end of predetermined exposure periods. These measurements are based upon ASTM G 1-81 
Standard Practice for Preparing, Cleaning, and Evaluating Corrosion Test Specimens or the 
more recent ASTM G 1-90, Standard Practice for Preparing, Cleaning, and Evaluating 
Corrosion Test Specimens. All specimens are cleaned in accordance with applicable American 
Society for Testing and Materials (ASTM) procedures prior to making weight and dimensional 
measurements. Uncertainty in the measured rates decreases with increasing exposure time. 
Details of the facility, sample configurations, and the procedure used for handling the samples

 3-36  
are provided in the AMR on general and localized corrosion of Alloy 22 (CRWMS M&O 2000c 
Section 6.5.2). 
The general corrosion (penetration) rate of an alloy can be calculated from weight-loss data 
with the following general formula: 
( ) 
( )D T A 
W K 
Rate Corrosion 
  
 = (Eq. 3-15) 
where K is a constant, T is the time of exposure in hours, A is the exposed area of the sample in 
square centimeters, W is the mass loss in grams, and D is the density of Alloy 22 in grams per 
cubic centimeter. The value of K used for the LTCTF data was 8.76107 m y-1h cm-1. A 
sample calculation for Alloy 22 is shown below: 
( )( ) 
( )( )( ) 1 
3 2 
1 1 7 
3 
2 
1 1 7 
23 . 0 
69 . 8 4320 0 . 1 
0001 . 0 10 76 . 8 
69 . 8
4320 
0 . 1 
0001 . 0 
10 76 . 8 
- 
- 
- - 
- 
- - 
=  = 
= 
=
=
= 
 = 
y m 
cm g h cm 
g cm h y m 
Rate Corrosion
cm g D 
h T 
cm A 
g W 
cm h y m K 
 
 
 
General corrosion rates based on generic weight-loss samples are independent of temperature 
between 60 and 90C. Furthermore, the composition of the test medium (SDW, SCW, or SAW) 
appears to have little effect. When all of the measured rates are ranked together, regardless of 
the test medium or temperature, the data appear to be normally distributed around a median 
value. 
In regard to generic crevice samples, general corrosion rates are based on areas outside the 
crevice. In this case, the measurements are also independent of temperature and test medium. 
When all of the corrosion rates based on these samples are ranked together, most of the data 
points appear to be normally distributed around a median value. There are four samples 
(outliers) that have abnormally high weight losses, which yield rates up to 731 nanometers per 
year. No crevice attack of these four samples is evident with microscopic examination. The 
high weight-loss values for these samples may be due to the accidental removal of material 
during mechanical assembly of the crevice. These outlier rates will not lead to failure of the 
WPOB by general corrosion during the first 10,000 years of service. 
The average corrosion rate based upon all weight-loss samples with 6- and 12-month exposure is 
20 nm y-1, with a standard deviation of 40 nm y-1. The average corrosion rate based upon all 
crevice samples with comparable exposure is 71 nm y-1, with a standard deviation of 89 nm y-1. 
If the four abnormally high rates are omitted, the average rate is then calculated to be 57 nm y-1, 
with a standard deviation of 40 nm y-1. At temperatures less than 90C, it does not appear that 
the life of the WPOB will be determined by GC.

 3-37  
It should be noted that the measured corrosion rates include some negative values. These 
negative rates correspond to cases where the samples actually appear to have gained weight 
during exposure, due to oxide growth or the formation of silicate deposits. To substantiate these 
interpretations, atomic force microscopy (AFM) and X-ray diffraction (XRD) have been used to 
inspect a number of samples removed from the LTCTF. Results of this study are discussed in 
detail in Attachment I of the AMR on the general and LC of Alloy 22 (CRWMS M&O 2000c, 
Section 6.5.5) and summarized later in this subsection. 
Based upon these data and the associated error analysis, one conservative and defensible overall 
representation of the observed corrosion rates with 6- and 12-month exposure has been proposed. 
This approach involves combining the distributions of rates calculated from weight loss and 
crevice samples. These data are for samples having the generic weight-loss and crevice 
geometry, respectively. It is conservatively assumed that no scale formation occurs, so all 
negative rates are eliminated and the entire distribution is assumed to be due to uncertainty. The 
rate at the 50th percentile is approximately 50 nm y-1, the rate at the 90th percentile is 
approximately 100 nm y-1, and the maximum rate is 731 nm y-1. Approximately 10% of the 
values fall between 100 and 731 nm y-1. 
Data representing 24 months of exposure has recently become available. Various cumulative 
distribution functions (CDFs) generated with 24-month data alone are shown in Figures 3-18 
through 3-21. The mean corrosion rate in Figure 3-21 is 10 nm y-1. The rates of GC do not 
appear to depend strongly on temperature and chemical composition of the water. Negative 
corrosion rates may indicate a weight gain by the specimen, even after thorough cleaning to 
remove corrosion products and oxides from the surface. 
CDFs generated with a combined data set representing 6-, 12-, and 24-month data are shown in 
Figures 3-22 and 3-23. The curve shown in Figure 3-22 includes apparent negative rates, while 
those negative values have been eliminated from the curve shown in Figure 3-23. The curve 
shown in Figure 3-23 is summarized in Table 3-7. The distributions based upon the 24-month 
data are more narrow than comparable distributions based upon 6- and 12-month data. Since 
rates are calculated by dividing exposure time into the weight loss, a doubling of exposure time 
reduces the estimated error by a factor of two (2X). While outliers were observed in the 6-month 
data, as previously discussed, none were observed in the 12- and 24-month (one- and two-year) 
data.

 3-38  
Source: CRWMS M&O 2000c, Section 6.9 
Figure 3-18. Two-Year General Corrosion Rate Data from Long Term 
Corrosion Test Facility Based Upon Generic Weight-Loss 
Samples 
Source: CRWMS M&O 2000c, Section 6.9 
Figure 3-19. Two-Year General Corrosion Rate Data from Long Term 
Corrosion Test Facility Based Upon Generic Crevice Samples 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100
-40 -30 -20 -10 0 10 20 30 40 
Penetration Rate (nm/y) 
Percentile 
Two-Year LTCTF Data for Alloy 22 - Generic 
Weight Loss Samples 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100
-20 -10 0 10 20 30 40 50 60 70 80 
Penetration Rate (nm/y) 
Percentile 
Two-Year LTCTF Data for Alloy 22 - Generic 
Crevice Samples

 3-39  
Source: CRWMS M&O 2000c, Section 6.9 
Figure 3-20. Two-Year General Corrosion Rate Data From Long Term 
Corrosion Test Facility Based Upon Both Generic Weight-Loss 
and Crevice Samples, Including Those with Apparent Negative 
Rates 
Source: CRWMS M&O 2000c, Section 6.9 
Figure 3-21. Two-Year General Corrosion Rate Data From Long Term 
Corrosion Test Facility Based Upon Both Generic Weight-Loss 
and Crevice Samples, Excluding Those with Apparent Negative 
Rates 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100
-80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90 
Penetration Rate (nm/y) 
Percentile 
Two-Year LTCTF Data for Alloy 22 - Generic 
Weight Loss and Crevice Samples Combined 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
0 10 20 30 40 50 60 70 80 
Penetration Rate (nm/y) 
Percentile 
Two-Year LTCTF Data for Alloy 22 - Generic Weight Loss and Crevice 
Samples - No Negative Rates

 3-40  
Source: CRWMS M&O 2000c, Section 6.9 
Figure 3-22. Combination of All General Corrosion Rate Data for Alloy 22 from 
Long Term Corrosion Test Facility, Including 6-, 12-, and 24-Month 
Exposures 
Source: CRWMS M&O 2000c, Section 6.9 
Figure 3-23. Combination of All General Corrosion Rate Data for Alloy 22 from 
Long Term Corrosion Test Facility, Including 6-, 12-, and 24-Month 
Exposures with Negative Rates Excluded 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
0 100 200 300 400 500 600 700 800 
Penetration Rate (nm/y) 
Percentile 
Combination of All LTCTF GC Rate Data for Alloy 22 
(6, 12 & 24 Month Exposures) - No Negative Rates 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100
-100 0 100 200 300 400 500 600 700 800 
Penetration Rate (nm/y) 
Percentile 
Combination of All LTCTF GC Rate Data for Alloy 22 (6, 12 & 24 
Month Exposures)

 3-41  
In summary, the ranges of general corrosion rates measured at three time intervals (6, 12, and 
24 months of exposure) are: 
6-month exposure: range -0.06 to +0.73 m y-1; mean 0.05 m y-1 
12-month exposure: range -0.04 to +0.10 m y-1; mean 0.03 m y-1 
24-month exposure: range -0.03 to +0.07 m y-1; mean 0.01 m y-1 
The AFM has been used to characterize the surface topographies of five weight-loss coupons of 
Alloy 22, which had been exposed to various environments in the LTCTF for one year (CRWMS 
M&O 2000c, Section 6.5.5). Having sub-nanometer vertical resolution, the AFM is an ideal tool for 
detecting extremely small penetrations in corrosion-resistant materials such as Alloy 22. These 
samples include an unexposed control sample, a sample exposed to aqueous-phase SAW, a sample 
exposed to vapor-phase SAW, a sample exposed to aqueous-phase SCW, and a sample exposed to 
vapor-phase SCW. After the samples were removed from the LTCTF, they were ultrasonically 
agitated in deionized water, acetone, and methanol for ten minutes each. The Digital Instruments 
DM3100 AFM was then used for imaging. Each set of data consists of a large-area scan (25 m  
25 m), followed by smaller-area details of the region displayed in the large-area scan. 
The gross surface topography is dominated by the machining grooves, with typical heights of several 
hundred nanometers and typical lateral periodicities of several microns, features plainly visible on 
images of the control sample. Samples removed from the LTCTF exhibit varying degrees of 
coverage by a deposit on top of this gross topography. The AFM images show that the most 
extensive deposit formation occurred on the sample exposed to aqueous-phase SAW (CRWMS 
M&O 2000c, Attachment 1). The next most extensive deposit formation occurred on the sample 
exposed to vapor-phase SAW. X-ray diffraction (XRD) of all five coupons show that the deposit is 
predominantly a silicate (SiO2), with some NaCl appearing on the two samples which were in the 
SAW tank (CRWMS M&O 2000c, Attachment 1). Based upon both AFM and XRD data, the two 
samples exposed to SCW showed lesser degrees of coverage by the silicate deposit. In some cases, 
depressions can be seen in the silicate deposit. However, it is not believed that any of these penetrate 
to the underlying metal. 
At the present time, there is insufficient data to determine the amount of silicate removed from 
exposed Alloy 22 samples by the standard cleaning method (CRWMS M&O 2000c). Accordingly, a 
worst-case estimate of the impact of SiO2 on measured GC rates can be used. 
The formation of SiO2 deposits on the surface of the Alloy 22 could bias the distributions of GC rate 
shown in earlier sections of this PMR. From various AFM images of Alloy 22 samples removed 
from the LTCTF, it appears that a typical deposit can have a thickness as great as 0.25 microns after 
12 months of exposure. It is assumed that the deposit has the density of lechatelierite (amorphous 
SiO2), which is approximately 2.19 g cm-3. It is further assumed that the surface is completely and 
uniformly covered by this deposit. The estimated surface areas of the weight-loss and crevice 
samples are 30.65 and 57.08 cm2, respectively (4.75 and 8.85 in2, respectively). Consequently, the 
deposit thickness (0.25 microns) translates into a mass change of 1.678 and 3.125 mg for weight-loss 
and crevice samples, respectively, after 12 months of exposure. The formula used to calculate the 
corrosion rate from weight-loss and dimensional change is then applied to determine the impact of 
such a positive mass change on the calculated rate. The estimated maximum bias is 0.063 m per 
year (63 nm y-1) for all weight-loss samples.

 3-42  
The distributions of GC rate shown in previous sections can be corrected for the maximum bias due 
to SiO2 deposit formation by adding a constant value of 63 nm y-1 to each estimated value of the GC 
rate. This is equivalent to shifting the curves shown in figures to the right by 63 nm y-1. Similar 
corrections could be applied to the Titanium Grade 7 data. Since the entire surface may not be 
covered by SiO2, it may be preferable to distribute the correction between 0 and 63 nm y-1. 
The AFM has been used to examine areas inside and outside of Alloy 22 crevices exposed to SCW at 
90C for 12 months. Though the images were obtained with a welded sample, the unwelded area 
was imaged with the AFM. There appears to be no significant difference between the roughness of 
the four areas that were examined. Since it has been observed that corrosion tends to roughen the 
surface, it is concluded that there is no more attack inside the crevice than outside. 
The observed decrease in the mean corrosion rate and in the range of data scatter with increasing 
exposure time from 6 months to 24 months is fully consistent with the expected corrosion 
behavior of passive alloys such as Alloy 22 under repository type aqueous conditions. For 
example, examination of very long term monitored corrosion results on passive type alloys are 
shown plotted in the Metals Handbook, (ASM International 1987, Vol 13, p. 911, Figure 42). As 
can be seen in this figure for aluminum alloys exposed to various marine environments for times 
up to 30 years, there is an initial higher corrosion rate at short times (< ~ 1 year), and the rate 
drops off in a parabolic manner with increasing time. This is expected behavior for alloys where 
the passive film grows by a parabolic or logarithmic diffusion controlled process. For this type 
behavior, the expected scatter at very short times where the rate is varying rapidly will be greater 
that at longer times where the rate is much lower. This type of behavior can also be seen for 
Alloy 22 where the extensive general corrosion test results now available from the LTCTF show 
a significantly larger 6-month mean rate of 0.05 m y-1 as compared to a mean value of 
0.01 m y-1 at 24 months. Further, the observed 6-month data scatter is much greater (-.06 to 
+0.73 m y-1) than at 24 months (-0.03 to +0.07 m y-1) as expected and indicates that it is 
conservative to use the 24 month results to represent the much longer term general corrosion 
behavior of Alloy 22 under expected repository conditions

 3-43  
The maximum observed rate, which is much less than 1 micron per year, clearly indicates that 
the life of the WPOB will not be limited by general corrosion. No evidence of localized 
corrosion has been observed, even after two years of exposure. Examination of plastically 
strained U-bend specimens, again for all three time periods, indicates no initiation of SCC in 
both the base material and in the welded material. Half the number of these U-bend specimens 
contained welds. 
Table 3-7. Summary of the Distribution of Rates for General Corrosion 
of Alloy 22 Samples 
Percentile Penetration Rate (nm y-1) 
0.00 0 
5.20 2.07 
10.00 4.21 
50.40 26.64 
90.00 97.99 
95.20 112.54 
97.60 143.08 
99.20 250.56 
99.60 467.28 
100.00 730.77 
Source: CRWMS M&O 2000c, Section 6.9 
3.1.5.4.3 Rates for Titanium Grade 16  Weight-Loss Measurements from Long Term 
Corrosion Test Facility 
All GC rates for Titanium Grade 16 are based on LTCTF weight-loss samples and are shown in 
Figure 3-24. It appears that these measurements are independent of temperature between 60 and 
90C. Furthermore, the composition of the test medium (SDW, SCW, or SAW) appears to have 
little impact on the measurements. With the exception of four outliers with negative values, 
most of the rates plotted in Figure 3-24 are between -200 and +200 nanometers per year. The 
median is at approximately zero. The outliers with large negative rates are believed to represent 
samples where there was significant oxide growth or scale formation (CRWMS M&O 2000c).

 3-44  
Source: CRWMS M&O 2000d, Section 6.5.2 
Figure 3-24. General Corrosion of Titanium Grade 16: 12-Month Weight-Loss Samples 
from Long Term Corrosion Test Facility 
This analysis only includes Titanium Grade 16 samples exposed for 12 months in the LTCTF. 
As discussed in the supporting AMR (CRWMS M&O 2000d, Section 6.5.2), the cleaning 
method employed with the 6-month titanium samples caused significant metal loss, thereby 
yielding unusually high corrosion rates that proved to be artifacts. Very little cleaning was used 
for the 12-month samples, which may account for the large negative values in Figure 3-24 (scale 
formation). 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100
-1800 -1600 -1400 -1200 -1000 -800 -600 -400 -200 0 200 
Penetration Rate (nm/y) 
Percentile

 3-45  
All GC rates for Titanium Grade 16 based on LTCTF crevice samples are shown in Figure 3-25 
(rates based on areas outside of crevice). In this case, it also appears that the measurements are 
independent of temperature and test medium. Most of the rates plotted in Figure 3-25 are 
between -350 and +350 nanometers per year. The median is at approximately zero. The largest 
measured rate shown in Figure 3-25, which is less than +350 microns per year, will not lead to 
failure of the DS during the first 10,000 years of its service life. Based upon these data, it does 
not appear that the life of the DS will be limited by the general corrosion of Titanium Grade 16 
(analog of Titanium Grade 7) at temperatures less than those involved in the test (90C). 
The crevice samples were configured in such a way as to reveal crevice corrosion if it occurred. 
Since no obvious crevice attack was observed with the samples represented by these figures, it is 
assumed that all weight loss in the crevice samples was due to GC outside of the crevice region 
(area underneath washer). However, higher scatter may indicate more variability of corrosion 
inside the crevice. Corrosion inside may be influenced by differential aeration, and pH changes. 
Source: CRWMS M&O 2000d, Section 6.5.2 
Figure 3-25. General Corrosion of Titanium Grade 16: 12-Month Crevice Samples 
From Long Term Corrosion Test Facility 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100
-400 -300 -200 -100 0 100 200 300 400 
Penetration Rate (nm/y) 
Percentile

 3-46  
One simple and defensible representation of these GC rates has been proposed. The distribution 
of GC rates determined from weight-loss samples (Figure 3-24) and the distribution of GC rates 
determined from crevice samples (Figure 3-25) are combined into a single distribution. All 
negative rates are eliminated and the entire distribution is assumed to be due to uncertainty. 
From Figure 3-26, it can be seen that the rate at the 50th percentile is approximately 
25 nanometers per year, the rate at the 90th percentile is approximately 100 nanometers per year, 
and the maximum rate is less than 350 nanometers per year. About 10% percent of the values 
fall between 100 and 350 nanometers per year. Figure 3-27 shows that the cumulative 
probability is a linear function of the logarithm of the observed GC rates (log-uniform 
distribution). 
Source: CRWMS M&O 2000d, Section 6.5.4 
Figure 3-26. Distribution of Positive General Corrosion Rates Based Upon 
Weight-Loss and Crevice Samples 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
0 50 100 150 200 250 300 350 
Rate (nm/yr) 
Percentile (%)

 3-47  
Source: CRWMS M&O 2000d, Section 6.5.4 
Figure 3-27. Distribution of Positive General Corrosion Rates with Variability 
Based Upon Weight-Loss and Crevice Samples 
3.1.5.5 Error Analysis for Corrosion Rates  Weight-Loss Measurements from Long 
Term Corrosion Test Facility 
The general method used in the formal error analysis is presented in the AMR on general and LC 
of the WPOB (CRWMS M&O 2000c, Section 6.5.3). The methodology is important since it 
enables correct interpretation of the data. Only the results of that analysis are presented here. In 
the case of Alloy 22, the estimated error is shown in Table 3-8. The corresponding error for 
Titanium Grade 16 (Titanium Grade 7 analog) is shown in Table 3-9. 
Table 3-8. Summary of Error Analysis for Corrosion Rates Based Upon Weight Loss of Alloy 22 
Assumed Weight Loss 0.0001 g 0.0010 g 0.0100 g 
Case Sample Configuration Exposure Time .y nm y-1 .y nm y-1 .y nm y-1 
1 Crevice 6 month 12 13 20 
2 Weight Loss 6 month 23 25 38 
3 Crevice 12 month 6 6 9 
4 Weight Loss 12 month 11 12 18 
Source: CRWMS M&O 2000c, Section 6.5.3 
NOTE: .y = error in GC rate 
y = 27.6844Ln(x) - 
R2 = 0.9571 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
1 10 100 1000 
Rate (nm/yr) 
Percentile (%) 
Variability

 3-48  
Table 3-9. Summary of Error Analysis for Corrosion Rates Based Upon Weight Loss of Titanium 
Grade 16 
Assumed Wt. Loss 0.0001 g 0.0010 g 0.0100 g 
Case Sample Configuration Exposure Time .y nm y-1 .y nm y-1 .y nm y-1 
1 Crevice 6 month 24 26 47 
2 Weight Loss 6 month 45 49 89 
3 Crevice 12 month 12 13 22 
4 Weight Loss 12 month 22 24 42 
Source: CRWMS M&O 2000d, Section 6.5.3 
NOTE: .y = error in GC rate 
It is concluded that the typical uncertainty observed in weight-loss and dimensional 
measurements prevents determination of corrosion rates for Alloy 22 that are less than 
approximately 38 nm y-1. The maximum uncertainty is estimated to be between 6 and 20 nm y-1 
in the case of crevice samples, and between 11 and 38 nm y-1 in the case of weight-loss samples. 
These estimates of probable error are believed to correspond to about one standard 
deviation (1 s). Any measured corrosion rate greater than 160 nm y-1 (4 s) should be easily 
distinguishable from measurement error. Any rate less than 160 nm y-1 will be difficult to 
distinguish from measurement error. The maximum error in the corrosion rate for Titanium 
Grade 16 is estimated to be approximately 89 nm y-1, significantly larger than a comparable 
estimate for Alloy 22. The difference between estimated errors for Alloy 22 and Titanium 
Grade 16 is attributable to the differences in density. 
3.1.6 Localized Corrosion 
The difference between Ecorr and Ecritical is used to determine whether or not LC will occur. If 
Ecritical is less than or equal to Ecorr, LC is likely. These potentials are measured experimentally in 
electrolyte compositions believed to representative of the repository environment 
(Section 1.5.4.3) (Tables 3-2, 3-3, and 3-4). Such electrolytes are described in a supporting 
AMR (CRWMS M&O 2000c, Section 6.4). 
Junction potentials for the reference electrode in all test solutions of interest have been calculated 
and are discussed in the supporting AMR on GC and LC of the WPOB (CRWMS M&O 2000c, 
Section 6.4). Since these calculated junction potentials are not very large, it is concluded that no 
significant error in any measurement of potential results by neglecting to correct for the junction 
potential. 
3.1.6.1 Threshold Potentials 
The generic LC model for WP materials assumes that localized attack occurs if the open circuit 
corrosion potential (Ecorr) exceeds the threshold potential for breakdown of the passive film 
(Ecritical): 
critical corr E E = (Eq. 3-16)

 3-49  
This model of LC initiation is referred to as Method A. In some cases, the threshold potential is 
assumed to be the repassivation potential. The repassivation potential is the level at which a 
failed passive film repassivates, or heals, thereby protecting the surface. In other cases, the 
threshold potential is assumed to be the pit or crevice initiation potential. 
3.1.6.2 Published Threshold Potentials for Alloy 22 
Compared to materials proposed for use in earlier WP designs, Alloy 22 has superior resistance 
to LC. The AMR on general and LC of the WPOB includes published repassivation potentials 
found in the literature (CRWMS M&O 2000c, Section 6.4). These data show that the threshold 
potential for LC of Alloy 22 is far greater than that of Alloy 625, thereby substantiating the claim 
that Alloy 22 is superior to the corrosion resistant materials used in earlier WP designs. 
3.1.6.3 Cyclic Polarization in Synthetic Concentrated J-13 Waters 
Pitting and crevice corrosion are usually associated with the breakdown of passivity. Tests for 
evaluating the susceptibility of a material to pitting and crevice corrosion include CP. These 
tests can be used to detect pit and crevice initiation potentials (where they exist), and 
repassivation potentials if losses in passivity are observed. Most recently, the procedure 
described in ASTM G 61-86, Standard Test Method for Conducting Cyclic Potentiodynamic 
Polarization Measurements for Localized Corrosion Susceptibility of Iron-, Nickel-, or Cobalt 
Based Alloys has been developed for conducting CP measurements of iron- or nickel-base alloys 
in chloride environments. 
Cyclic polarization measurements are based on a procedure similar to ASTM G 5-94, Standard 
Reference Test Method for Making Potentiostatic and Potentiodynamic Anodic Polarization 
Measurements with appropriate and necessary deviations. For example, ASTM G 5-94 calls for 
an electrolyte of 1N H2SO4, whereas SDW, SCW, SAW, and SSW are used here. Furthermore, 
aerated solutions are used, unlike the procedure that calls for de-aerated solutions. A baseline 
curve with Pt in SCW is shown in Figure 3-28. Representative CP curves are shown in 
Figures 3-29 through 3-37. The shapes of these CP curves are categorized as Type 1, 2, 3, or 4, 
as explained in the following paragraphs. 
A generic Type 1 curve exhibits complete passivity (no passive film breakdown) between the 
corrosion potential and the point defined as Threshold Potential 1. This interpretation was 
verified by visual inspection of samples after potential scans. Photographic documentation is 
maintained for some of the samples (all samples are held in the archives at LLNL). Threshold 
Potential 1 is in the range where the onset of oxygen evolution is expected and is defined by a 
large excursion in anodic current. This particular definition of Threshold Potential 1 is specific 
to Type 1 curves. Type 1 behavior has only been observed with Alloy 22 and is illustrated by 
Figure 3-29. The interpretation of Type 1 curves as exhibiting no passive film breakdown is 
consistent with Chapter 7 of ASTM G 61-86.

 3-50  
Source: CRWMS M&O 2000c, Section 6.4 
Figure 3-28. Baseline  Platinum in Simulated Concentrated Water at 
90C (PT001) 
Source: CRWMS M&O 2000c, Section 6.4 
Figure 3-29. Type 1Alloy 22 in Simulated Acidic Concentrated Water at 
90C (DEA002) 
-400 
-200
0 
200 
400 
600 
800 
1,000 
1,200 
1.0E-09 1.0E-08 1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01 1.0E+00 
Current (A) 
Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Maximum Passive Current 
Negative hysteresis loop during reverse scan - 
no localized breakdown of passive film at reversal potential - 
no repassivation potential observed 
Lower Bound for Corrosion Current 
Threshold Potential 1 
0 
100 
200 
300 
400 
500 
600 
700 
800 
900 
1,000 
1,100 
1,200 
1.00E-09 1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 
Current (A) 
Potential (mV vs. Ag/AgCl) 
Open Circuit Potential

 3-51  
Source: CRWMS M&O 2000c, Section 6.4 
Figure 3-30. Type 2Alloy 22 in Simulated Concentrated Water at 90C 
(DEA016) 
Source: CRWMS M&O 2000c, Section 6.4 
Figure 3-31. Type 3316L in Simulated Saturated Water at 100C (PEA016) 
-600 
-400 
-200
0 
200 
400 
600 
800 
1,000 
1,200 
1.0E-09 1.0E-08 1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01 1.0E+00 
Current (A) 
Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Lower Bound for Corrosion Current 
Threshold Potential 1 
Positive hysteresis loop during reverse scan - 
localized breakdown of passive film at reversal potential - 
repassivation during reverse scan 
Threshold Potential 2 
Repassivation Potential 3 
Anodic Oxidation Peak 
-600 
-400 
-200
0 
200 
400 
600 
800 
1,000 
1,200 
1.0E-09 1.0E-08 1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01 1.0E+00 
Current (A) Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Breakdown of the passive film with 
active pitting 
Threshold Potential 1 
Critical Pitting Potential 
Repassivation 
after pit initiation 
Lower Bound for Corrosion Current

 3-52  
Source: CRWMS M&O 2000c, Section 6.4.2 
Figure 3-32. Alloy 22 in Various Repository Media  Comparison 
of Cyclic Polarization Data 
Source: CRWMS M&O 2000c, Section 6.4.2 
Figure 3-33. Potentiostatic Polarization of Alloy 22 in Simulated 
Concentrated Water at 90C and 200 mV Versus 
Ag/AgCl 
1.0E-13 
1.0E-12 
1.0E-11 
1.0E-10 
1.0E-09 
1.0E-08 
1.0E-07 
1.0E-06 
1.0E-05 
1.0E-04 
1.0E-03
-300 -200 -100 0 100 200 300 400 500 
Potential (mV vs. Ag/AgCl) 
Current (A) ~ Current Density (A/cm 2) 
Current SDW 30 DEA025 
Current SDW 60 DEA026 
Current SDW 90 DEA027 
Current SCW 30 DEA009 
Current SCW 60 DEA011 
Current SCW 90 DEA010s 
Current SAW 30 DEA007 
Current SAW 60 DEA004 
Current SAW 90 DEA002 
Current SSW 100 DEA032s 
Current SSW 120 DEA033s 
Apparent corrosion current density corresponding 
to average rates observed in the Long Term 
Corrosion Test Facility 
Apparent corrosion rate of 
2 microns per year 
0
5 
10 
15 
20 
25 
30 
0 10 20 30 40 50 60 70 80 
Time (103 seconds) 
Current (microamps)

 3-53  
Figure 3-34. Cyclic Polarization Curve for Alloy 22 in 110C Basic 
Saturated Water  Thermally Aged at 700C for 10 Hours 
(DEA159) 
Source: CRWMS M&O 2000c, Section 6.9.2 
Figure 3-35. Cyclic Polarization Curve for Alloy 22 in 110C Basic 
Saturated Water  Thermally Aged at 700C for 173 Hours 
(DEA208) 
-600 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200 
1.E-09 1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 
Current (A) 
Potential (mV vs Ag/AgCl) 
(DEA159) 
-600 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200 
1.E-09 1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 
Current (A) 
Potential (mV vs Ag/AgCl) 
(DEA208)

 3-54  
Figure 3-36. Titanium Grade 7 in Simulated Saturated Water at 120C 
(NEA031s) 
Source: CRWMS M&O 2000d, Section 6.4.3 
Figure 3-37. Titanium Grade 7 in Simulated Concentrated Water at 90C 
(NEA003) 
-1,000 
-500
0 
500 
1,000 
1,500 
2,000 
2,500 
1.0E-10 1.0E-09 1.0E-08 1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 
Current (A) 
Potential (mV vs. Ag/AgCl) 
Threshold Potential 1 
Maximum Passive Current 
Corrosion Potential 
Negative hysteresis loop during reverse scan - 
no localized breakdown of passive film at reversal 
potential - 
no repassivation potential observed 
-1,000 
-500
0 
500 
1,000 
1,500 
2,000 
2,500 
1.0E-10 1.0E-09 1.0E-08 1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 
Current (A) 
Potential (mV vs. Ag/AgCl) 
Corrosion 
Potential 
Threshold Potential 1 

 3-55  
A generic Type 2 curve exhibits a well defined oxidation peak at the point defined as Threshold 
Potential 1. Threshold Potential 2 is in the range where the onset of oxygen evolution is 
expected, and is defined by a large increase in anodic current. These particular definitions of the 
threshold potentials are specific to Type 2. Repassivation Potentials 1 and 2 are defined as the 
points where the hysteresis loop passes through a current levels of 4.27x10-6 and 10-5 amps, 
respectively (not shown). Repassivation Potential 3 is determined from the first intersection of 
the hysteresis loop (reverse scan) with the forward scan. Type 2 is observed with both Alloy 22 
and Type 316L stainless steel. In the case of Alloy 22, this behavior is illustrated by 
Figure 3-30. Definitions of the threshold and repassivation potentials are somewhat subjective, 
and may vary from investigator to investigator. The threshold potential for initiation of crevice 
corrosion on Alloy 22 is defined as the point during the potential scan in the forward direction 
where the current density increases to a level of 10-6 to 10-5 A cm-2. The repassivation potential 
is defined as the point during the potential scan in the backward direction where the current 
density drops to 10-6 to 10-7 A cm-2. This definition is comparable to that of Repassivation 
Potential 3. The basis for these current densities is discussed in detail in the AMR on general 
and LC of the WPOB (CRWMS M&O 2000c, Section 6.4). 
As previously discussed, a representative curve for platinum in SCW at 90C is shown in 
Figure 3-28. The CP measurements of Pt were made to serve as a basis of comparison for 
similar measurements with Alloy 22 and other materials of interest. From such comparisons, it 
is concluded that the anodic oxidation peak observed in Type 2 curves (between 200 and 
600 mV) for Alloy 22 is due to an anodic reaction of the passive film. No anodic oxidation peak 
is observed in the curve for platinum. X-ray photoelectron spectroscopy measurements of the 
passive film polarized at potentials above and below the anodic oxidation peak have shown that 
the anodic reaction increases the oxidation state of metal cations in the film, which remains 
intact. 
A generic Type 3 curve exhibits a complete breakdown of the passive film and active pitting at 
potentials relatively close to the corrosion potential (Ecorr). In this case, Threshold Potential 1 
corresponds to the critical pitting potential. Type 3 behavior has only been observed with 
stainless steel 316L in SSW and is illustrated by Figure 3-31. SSW is a saturated sodiumpotassium-
chloride-nitrate electrolyte, formulated to represent the type of concentrated 
electrolyte that might evolve on a hot WP surface. This formulation has a boiling point of 
approximately 120C at ambient pressure. In contrast to the Type 3 behavior exhibited by 
stainless steel 316L in SSW, Alloy 22 maintains passivity at potentials up to the reversal 
potential (1,200 mV versus Ag/AgCl). 
A composite of the CP data for Alloy 22 is shown in Figure 3-32. It should be noted that the 
axes of this figure are changed in comparison to previous figures. The initial portions of these 
curves show that passivity is maintained at potentials at least as high as 400 mV versus Ag/AgCl 
in all cases. The lowest potential at which any electrochemical reactivity of the passive film is 
observed is approximately 200 mV versus Ag/AgCl. Based upon data presented here, it is 
concluded that pitting attack of Alloy 22 should not occur under conditions expected in the 
repository. To further substantiate this conclusion, it is noted that no pitting of Alloy 22 has yet 
been observed in samples removed from the LTCTF after two years of exposure to SDW, SCW, 
and SAW at 60 and 90C.

 3-56  
In regard to Type 2 polarization curves for Alloy 22 in SCW, the electrochemical process leading 
to the anodic oxidation peak (leading edge at approximately 200 mV versus Ag/AgCl) cannot be 
determined from the CP data alone. As previously discussed, this peak is due to some change in 
oxidation state of the passive film and probably has very little to do with any loss of passivity. 
To augment these potentiodynamic measurements, potentiostatic polarization tests have been 
performed. Figure 3-33 shows the observed transient current when an Alloy 22 sample is 
polarized at 200 mV versus Ag/AgCl in SCW at 90C, close to the potential where the leading 
edge of the anodic oxidation peak is located. The current density initially increases to a 
maximum of approximately 25 A cm-2 (the sample size is approximately 0.96 cm2) at 9 hours. 
This corresponds to a typical non-equilibrium passive current density measured for Alloy 22 at 
this potential and in the absence of the anodic oxidation peak. For example, see a Type 1 
polarization curve for Alloy 22 in SAW. It is therefore concluded that the anodic oxidation peak 
observed in Type 2 polarization curves does not define any LC or loss in passivity. Threshold 
Potential 1 (leading edge of the anodic oxidation peak at approximately 200 mV versus 
Ag/AgCl) should not be used as the basis for switching on LC of Alloy 22. In such cases, it 
should be assumed that Threshold Potential 2 (oxygen evolution) represents the lower bound for 
breakdown of the passive film. 
Several CP measurements have now been made with BSW electrolytes and are summarized in 
Table 3-10 and Figures 3-34 and 3-35. As previously discussed in Section 3.1.4.5, extreme 
aging of Alloy 22 can shift the corrosion potential in a less noble (cathodic) direction by 
approximately 100 mV. This is accompanied by a slight increase in non-equilibrium passive 
current density. There is some evidence of an anodic oxidation peak, characteristic of Type 2 
curves. For the present time, we will classify these CP curves as intermediate Type 1-2. 
Examples of CP data for Titanium Grade 7 in SSW and SCW are shown in Figures 3-36 and 
3-37, respectively. Both CP curves are Type 4, showing little evidence of passive film 
breakdown over a very wide range of potential. 
Table 3-10. Electrochemical Potentials Determined from Cyclic Polarization of Alloy 22 in Basic 
Saturated Water 
Sample ID 
Aging 
Time 
Aging 
Temp. Medium Temp. 
Reversal 
Potential 
Corrosion 
Potential 
Threshold 
Potential 1 
CP Curve 
Type 
hours oC oC mV mV mV 
DEA158 10 700 BSW 110oC 1200 -233 418 Type 1-2 
DEA159 10 700 BSW 110oC 1200 -257 419 Type 1-2 
DEA208 173 700 BSW 110oC 1200 -345 394 Type 1-2 
DEA209 173 700 BSW 110oC 1200 -372 361 Type 1-2 
Source: CRWMS M&O 2000c, Section 6.9.2 
The University of Virginia (Uva) has recently generated some CP data with very tight crevices 
and concentrated electrolytes consisting of 5 M LiCl, 0.24 to 0.024 M NaNO3, 0.026 to 
0.26 M Na2SO4, and HCl. Testing was conducted at two temperature levels, 80 and 95C. The 
crevices were formed with a multiple crevice former, and an applied torque of 70 inch pounds. 
Under these circumstances, some electrochemical activity indicative of crevice corrosion was

 3-57  
observed at potentials ranging from 71 to 397 mV versus Ag/AgCl, depending upon the 
composition of the electrolyte. Using a current density criterion for repassivation of 10-5 A cm-2, 
repassivation potentials were determined to be slightly above, but relatively close to the opencircuit 
corrosion potential. 
The concentrated lithium-chloride based electrolytes used in the UVa tests are not relevant to 
those conditions anticipated in the repository. Unlike compositions based upon J-13 well water, 
these electrolytes have no buffer ions per se. Continued testing is underway with samples 
configured like those used by UVa and test media relevant to the repository (BSW). In these 
tests, it has been found that simulated repository waters with buffer inhibit the type of crevice 
corrosion observed in tests with electrolytes based upon lithium chloride, even at the boiling 
point of saturated solutions. As more data become available, correlation equations for the 
corrosion and threshold potentials should be updated, expressing these quantities in terms of 
temperature, pH, and the concentrations of various ions. The UVa approach appears ideally 
suited for determining repassivation potentials when they exist. 
Conclusions from tests with UVa-type samples and BSW are corroborated by other 
measurements. Relatively wide crevices (110 to 540 microns) formed from passive Alloy 22 and 
filled with SCW do not appear to undergo significant increases in hydrogen ion concentration 
(pH suppression) at reasonable electrochemical potentials. These potentials are generally below 
the thresholds determined by CP. Finally, Alloy 22 and Titanium Grade 16 crevices exposed in 
the LTCTF do not indicate significant crevice corrosion. Recall that Titanium Grade 16 is 
considered to be an analog of Titanium Grade 7. 
In the case of 316 stainless steel data shown in Figure 3-31 and Figures 3-14 and 3-15 suggest 
that localized corrosion may be likely under certain conditions. However, even if the material 
fails by localized corrosion (pitting) the structural shell will retard the ingress of water into the 
waste package as the pits are narrow and deep. Nevertheless, the stainless steel structural 
material is not used as a containment barrier at this time to provide for a conservative approach. 
3.1.6.4 Correlation of Potential Versus Temperature Data for Various Test Media 
Values of corrosion and threshold potentials for the three WP materials of interest have been 
correlated as a function of temperature for repository-relevant test media. In general, it has been 
found that these potential versus temperature data can be represented by the following simple 
regression equation: 
2 
2 1 0 x b x b b y + + = (Eq. 3-17) 
where y is either the corrosion or threshold potential (mV vs. Ag/AgCl) and x is the temperature 
(C). Parameters for Equation 3-21 are found in Figures 3-38 through 3-48. These parameters 
were used to calculate values of Ecorr and Ecritical for WP materials in SDW, SCW, SAW, and 
SSW at 10C intervals. These calculations and tabulations of the parameters are found in the 
supporting AMR documents (CRWMS M&O 2000c, Section 6.4.3, 2000d, Section 6.4.3, 2000e 
Section 6.4.3,).

 3-58  
Source: CRWMS M&O 2000e, Section 6.4.3 
Figure 3-38. Potentials versus Temperature  Stainless Steel 316L in 
Simulated Acidic Concentrated Water 
Source: CRWMS M&O 2000e, Section 6.4.3 
Figure 3-39. Potentials versus Temperature  Stainless Steel 316L in 
Simulated Concentrated Water 
y = -0.5333x2 + 44.833x + 285 
R2 = 0.9899 
y = -0.3094x2 + 25.817x + 264 
R2 = 0.9951 
y = -0.3589x2 + 29.133x + 589 
R2 = 0.9917 
y = -2.1x - 172.33 R2 = 0.5919 
y = -0.6347x2 + 54.25x + 33.75 
R2 = 0.9991 
y = -0.6147x2 + 53.617x - 62.25 R2 = 0.9981 
-600 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200 
1400 
30 40 50 60 70 80 90 100 
Temperature (C) 
Measured Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Threshold Potential 2 
Repassivation Potential 1 
Repassivation Potential 2 
Repassivation Potential 3 
Poly. (Threshold Potential 2) 
Poly. (Threshold Potential 1) 
Poly. (Repassivation Potential 3) 
Linear (Corrosion Potential) 
Poly. (Repassivation Potential 2) 
Poly. (Repassivation Potential 1) 
y = -2.206x + 962.26 R2 = 0.7344 
y = -4.1744x + 540.62 R2 = 0.9637 
y = -3.659x + 1008.4 R2 = 0.9759 
y = -2.1974x - 77.538 R2 = 0.6371 
y = -7.4607x + 1169.7 R2 = 0.4976 
y = -6.965x + 1072.6 R2 = 0.4045 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200
30 40 50 60 70 80 90 100 
Temperature (C) 
Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Threshold Potential 2 
Repassivation Potential 1 
Repassivation Potential 2 
Repassivation Potential 3 
Linear (Threshold Potential 2) 
Linear (Threshold Potential 1) 
Linear (Repassivation Potential 3) 
Linear (Corrosion Potential) 
Linear (Repassivation Potential 2) 
Linear (Repassivation Potential 1)

 3-59  
Source: CRWMS M&O 2000e, Section 6.4.3 
Figure 3-40. Potentials versus Temperature  Stainless Steel 316L in 
Simulated Saturated Water 
Source: CRWMS M&O 2000c, Section 6.4.3 
Figure 3-41. Potentials versus Temperature  Alloy 22 in Simulated Dilute Water 
y = 3.625x - 626.5 R2 = 0.7358 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200 
95 100 105 110 115 120 125 
Temperature (C) 
Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Threshold Potential 2 
Repassivation Potential 1 
Repassivation Potential 2 
Repassivation Potential 3 
Linear (Corrosion Potential) 
Boundary of potential and 
temperature where pitting 
is possible 
y = -4.3111x + 565 R2 = 0.9758 
y = -1.6556x - 33.556 R2 = 0.7544 
y = -1.4889x + 888.33 R2 = 0.2421 
y = -3.0231x + 680.92 R2 = 0.943 
y = -3.9278x + 698.22 
R2 = 0.9259 
y = -4.0556x + 656.56 
R2 = 0.9334 
-400 
-200
0 
200 
400 
600 
800 
1000 
20 30 40 50 60 70 80 90 100 
x = Temperature (Centigrade) 
y = Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Threshold Potential 2 
Repassivation Potential 1 
Repassivation Potential 2 
Repassivation Potential 3 
Linear (Threshold Potential 1) 
Linear (Corrosion Potential) 
Linear (Threshold Potential 2) 
Linear (Repassivation Potential 3) 
Linear (Repassivation Potential 2) 
Linear (Repassivation Potential 1)

 3-60  
Source: CRWMS M&O 2000c, Section 6.4.3 
Figure 3-42. Potentials versus Temperature  Alloy 22 in Simulated 
Concentrated Water 
Source: CRWMS M&O 2000c, Section 6.4.3 
Figure 3-43. Potentials versus Temperature  Alloy 22 in Simulated Acidic 
Concentrated Water 
y = -0.875x + 282.93 
R2 = 0.156 
y = -1.0667x - 123.86 R2 = 0.1449 
y = 0.7917x + 679.36 R2 = 0.0167 
y = -1.2078x + 724.18 R2 = 0.1926 
y = -3.4216x + 596.24 
R2 = 0.1447 
y = -3.0882x + 550.24 
R2 = 0.111 
-400 
-200
0 
200 
400 
600 
800 
1000 
20 30 40 50 60 70 80 90 100 
x = Temperature (Centigrade) 
y = Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Threshold Potential 2 
Repassivation Potential 1 
Repassivation Potential 2 
Repassivation Potential 3 
Linear (Threshold Potential 1) 
Linear (Corrosion Potential) 
Linear (Threshold Potential 2) 
Linear (Repassivation Potential 3) 
Linear (Repassivation Potential 2) 
Linear (Repassivation Potential 1) 
y = -1.1153x + 677.33 R2 = 0.5617 
y = -1.9958x + 12 R2 = 0.9522 
y = -2.1667x + 857 R2 = 0.641 
-400 
-200
0 
200 
400 
600 
800 
1000
20 30 40 50 60 70 80 90 100 
x = Temperature (C) 
y = Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Threshold Potential 2 
Repassivation Potential 1 
Repassivation Potential 2 
Repassivation Potential 3 
Linear (Threshold Potential 1) 
Linear (Corrosion Potential) 
Linear (Threshold Potential 2)

 3-61  
Source: CRWMS M&O 2000c, Section 6.4.3 
Figure 3-44. Potentials versus Temperature  Alloy 22 in Simulated 
Saturated Water 
Source: CRWMS M&O 2000d, Section 6.4.3 
Figure 3-45. Corrosion and Threshold Potentials of Titanium Grade 7 in 
Simulated Saturated Water (NEA031s) 
y = 9.175x - 683.5 R2 = 0.1559 
y = -8.75x + 1643 R2 = 0.4068 
y = -2.625x + 28.5 R2 = 0.4501 
-400 
-200
0 
200 
400 
600 
800 
1000
95 100 105 110 115 120 125 
x = Temperature (C) 
y = Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Threshold Potential 2 
Linear (Threshold Potential 1) 
Linear (Threshold Potential 2) 
Linear (Corrosion Potential) 
y = -6.25x + 414 
y = -5.4x + 1461 
-400 
-200
0 
200 
400 
600 
800 
1000
100 102 104 106 108 110 112 114 116 118 120 
Temperature (C) 
Potential (mV) 
Threshold Potential 1 
Corrosion Potential 
Linear (Corrosion Potential) 
Linear (Threshold Potential 1)

 3-62  
Source: CRWMS M&O 2000d, Section 6.4.3 
Figure 3-46. Corrosion and Threshold Potentials for Titanium Grade 7 in 
Simulated Acidic Concentrated Water 
Source: CRWMS M&O 2000d, Section 6.4.3 
Figure 3-47. Corrosion and Threshold Potentials for Titanium Grade 7 in 
Simulated Concentrated Water 
y = -0.0824x2 + 9.9833x - 414.33 
R2 = 0.4127 
y = -0.0515x2 + 5x + 1290.3 
R2 = 0.2468 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200 
1400 
1600 
20 30 40 50 60 70 80 90 100 
Temperature (C) 
Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Poly. (Corrosion Potential) 
Poly. (Threshold Potential 1) 
y = -3.7278x + 1084.3 
R2 = 0.7373 
y = -5.8056x + 14.444 
R2 = 0.8868 
-600 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200
20 30 40 50 60 70 80 90 100 
Temperature (C) Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Repassivation Potential 1 
Repassivation Potential 2 
Linear (Threshold Potential 1) 
Linear (Corrosion Potential)

 3-63  
Source: CRWMS M&O 2000d, Section 6.4.3 
Figure 3-48. Corrosion and Threshold Potentials for Titanium Grade 7 in 
Simulated Dilute Water 
All correlation equations for stainless steel 316NG are found in Figures 3-38 through 3-40. The 
correlation for Ecorr and the most conservative correlation for the threshold potential, Ecritical, are 
labeled. In the case of Type 2 CP curves, the selected threshold potential is determined by the 
position of the observed anodic oxidation peak, and may not result in any actual loss of passivity. 
In the case of Type 3 CP curves, the measured threshold potentials are scattered. The transparent 
square in Figure 3-40 therefore represents the range of potential and temperature where pitting 
attack is believed to be possible. The lower boundary of the square appears to be very close to 
the line representing the corrosion potential. Note that these very low threshold potentials are 
entirely consistent with the published temperature-dependent pitting potentials. These data are 
represented by Equation 3-17 where b0 = 547.76, b1 = -6.617 and b2 = 0. As this correlation is 
extrapolated to 100C, the pitting potential approaches the lower boundary of the transparent box 
used to bound the threshold potentials. 
y = -4.2111x + 1161 
R2 = 0.9203 
y = -2.9462x - 24.154 
R2 = 0.7964 
-400 
-200
0 
200 
400 
600 
800 
1000 
1200
20 30 40 50 60 70 80 90 100 
Temperature (C) 
Potential (mV vs. Ag/AgCl) 
Corrosion Potential 
Threshold Potential 1 
Linear (Threshold Potential 1) 
Linear (Corrosion Potential)

 3-64  
All correlation equations for Alloy 22 are found in Figures 3-41 through 3-44. The correlation 
for the corrosion potential (Ecorr) and the conservative correlation for the threshold potential 
(Ecritical) are labeled. While calculated values of y are believed to have only three significant 
figures, coefficients in that regression equation are given with more figures. The correlation 
equations for Titanium Grade 7 are found in Figures 3-45 through 3-48. The data presented in 
these figures clearly show that the threshold potentials for localized corrosion of Titanium 
Grade 7 and Alloy 22 are not exceeded under conservatively assumed media. 
In an ideal case, the crevice corrosion temperature can be estimated from the intersection of the 
lines representing the corrosion and threshold potentials at elevated temperature. Such 
intersection is evident in Figure 3-38. Better correlations of Ecorr and Ecritical with material 
history, water chemistry, and temperature may ultimately allow precise prediction of the crevice 
corrosion temperature. Improved correlations would provide rigorous statistical estimates of 
uncertainty and variability in Ecorr and Ecritical. The precise determination of uncertainty and 
variability in Ecorr and Ecritical would enable designers to determine the impact of accepting 100% 
of the supplied WP material on repository performance. In the meantime, crevice corrosion can 
be forced to occur in the model by equating Ecorr and Ecritical over temperature ranges of 
uncertainty (90-120C). This assumption would provide a conservative estimate of the crevice 
corrosion temperature. Improved LC models with accurate temperature dependence will allow a 
precise sensitivity study, assessing the impact of various WP design changes on the radiological 
dose at the site boundary. 
There are precedents for using electrochemical measurements as the basis of water chemistry and 
materials specifications in the nuclear industry. For example, measurements of corrosion 
potential are indicative of dissolved oxygen and can be used to assure adequate deaeration in 
various regions of the steam cycle. The role of electrochemical potential on SCC has been well 
documented (CRWMS M&O 2000c). 
3.1.6.5 Prediction of Critical Temperatures for Pitting and Crevice Corrosion 
As previously discussed, a threshold temperature (critical temperature) can be used as an 
alternative to a threshold potential for the initiation of LC. This initiation model for LC is 
referred to as Method B. In an ideal case, the critical temperatures for pitting and crevice 
corrosion can be estimated from the intersection of the lines representing the corrosion and 
threshold potentials as functions of temperature. This intersection occurs at elevated 
temperature, as illustrated by Figure 3-38. The critical temperature for pitting of stainless 
steel 316L is illustrated by Figures 3-49 and 3-50. To force crevice corrosion to occur in the 
model, Ecorr and Ecritical can simply be equated above the critical temperature.

 3-65  
Source: CRWMS M&O 2000e, Section 6.4.5 
Figure 3-49. Effect of Molybdenum on the Critical Pitting Temperature of 
Stainless Steels in Ferric Chloride Solution 
Source: CRWMS M&O 2000e, Section 6.4.5 
Figure 3-50. Effect of Pit Resistance Equivalence Number on the Critical Pitting and 
Crevice Corrosion Temperature of Stainless Steels in Ferric Chloride 
Solution 
y = 34x - 28.667 
R2 = 0.9988 
y = 9x - 6.6667 
R2 = 0.9838 
0 
10 
20 
30 
40 
50 
60 
70 
80 
1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3 
x = Mo (wt. %) 
y = Critical Pitting Temperature (C) 
Unwelded 
Welded 
Pitting 
No Pitting 
y = 3.12x - 73.6 
y = 1.72x - 44.6 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
30 35 40 45 50 55 
x = PREN = Cr + 3.3 Mo + 30 N (wt. %) 
y = Critical Temperature (C) 
Critical Pitting Temperature 
Critical Crevice Temperature 
Linear (Critical Pitting Temperature) 
Linear (Critical Crevice Temperature)

 3-66  
3.1.6.6 Effect of Gamma Radiolysis on Corrosion Potential 
Anodic shifts in the open circuit corrosion potential of stainless steel in irradiated aqueous 
environments have been experimentally observed (CRWMS M&O 2000c, Section 6.4.4). It is 
now accepted as fact by much of the engineering community that this observation is due to the 
generation of hydrogen peroxide by the radiation. The CP experiments performed at ambient 
temperature with 316L samples in 0.018-M NaCl solution during exposure to 3.5-Mrad hr-1 
gamma radiation have shown that the corrosion potential shifts in the anodic direction by 
approximately 200 mV. It was concluded that there is very little increase in the corresponding 
corrosion current density. However, the separation between the corrosion potential and the 
threshold for localized attack decreased slightly. This shift in corrosion potential was shown to 
be due to the formation of hydrogen peroxide. This finding was subsequently confirmed by 
another independent CP experiment with 316 stainless steel at ambient temperature in acidic 
1.5-M NaCl solution (pH~2) during exposure to 0.15-Mrad hr-1 gamma radiation. A 100-mV 
anodic shift in the corrosion potential was observed in this case, with very little effect on the 
corrosion current density. Note that these experiments were performed on stainless steels, not 
Alloy 22. 
To determine the maximum impact that gamma radiolysis could have on the corrosion potential 
of Alloy 22, hydrogen peroxide was added to electrolytes used for testing WP materials. 
Experiments at 25C are illustrated by Figures 3-51 and 3-52. As the concentration of hydrogen 
peroxide in SCW approaches 72 ppm (calculated from number of added drops of H2O2), the 
corrosion potential asymptotically approaches 150 mV versus Ag/AgCl, well below any 
threshold where localized attack would be expected in SAW. Similarly, as the concentration of 
hydrogen peroxide in SCW approaches 72 ppm, the corrosion potential asymptotically 
approaches 25 mV versus Ag/AgCl, well below any threshold where localized attach would be 
expected in SCW. This change in corrosion potential is also below any level where a change in 
oxidation state of metal cations in the passive film would be expected (anodic oxidation peak in 
Type 2 polarization curves). Gamma radiolysis is not expected to exacerbate the LC of Alloy 22 
since the maximum shift in corrosion potential induced by hydrogen peroxide additions is less 
than that required for breakdown of the passive film.

 3-67  
Source: CRWMS M&O 2000c, Section 6.4.4 
NOTE: The numbers above the curve correspond to parts per million (ppm) H2O2 
Figure 3-51. Effect of Hydrogen Peroxide on Corrosion Potential of 
Alloy 22 in Simulated Acidic Concentrated Water at 25C 
Source: CRWMS M&O 2000c, Section 6.4.4 
NOTE: The numbers above the curve correspond to ppm H2O2 
Figure 3-52. Effect of Hydrogen Peroxide on Corrosion Potential of 
Alloy 22 in Simulated Concentrated Water at 25C 
-250 
-200 
-150 
-100 
-50
0
0 1 2 3 4 5 6 
Time (103 seconds) 
Potential (mV vs. Ag/AgCl) 
Addition of 25 microliters of 30% 
H2O2 (~ 8 ppm) 
No H2O2 (~ 0 ppm) 
0 
8 
16 
24 
32 
40 
48 
56 
64 
72 
-100 
-50
0 
50 
100 
150 
200
0 1 2 3 4 5 6 
Time (103 Seconds) 
Potential (mV vs. Ag/AgCl) 
Addition of 25 microliters of 30% 
H2O2 (~ 8 ppm) 
No H2O2 (~ 0 ppm) 
0 
8 
16 
24 
32 
40 
48 
56 
64 
72

 3-68  
3.1.6.7 Crevice Corrosion 
3.1.6.7.1 Deterministic Models of Crevice Chemistry 
Crevices can form at points of contact between the WP and other solid objects. These occluded 
geometries can lead to differential aeration of the crevice solution (electrolyte). Dissolved 
oxygen can become depleted deep within the crevice, while the concentration near the crevice 
mouth remains relatively high. Cathodic reduction of dissolved oxygen at the crevice mouth 
may create a sufficiently high electrochemical potential to drive anodic processes inside the 
crevice, thereby causing an anodic current to flow along the crevice towards the crevice mouth. 
Anodic processes inside the crevice are therefore expected to occur at a rate that corresponds to 
the local passive current density. Given this scenario, two primary electrochemical processes 
can lead to acidification of the solution in a crevice: (1) the preferential transport of anions into 
the crevice from the mouth, driven by the electric field that accompanies the crevice current, and 
(2) hydrolysis reactions of dissolved metal cations. 
Chloride anion will be driven into the crevice by the potential gradient, as discussed in the 
literature and summarized in the AMR. The concentration in the crevice is governed by 
Equation 3-18: 
Cl- [ ]= Cl - [ ]0 exp - 
F 
RT 
F x ( ) . 
. 
. 
. (Eq. 3-18) 
where [Cl-]0 is the concentration at the crevice mouth, F(x) is the potential in the crevice relative 
to that at the mouth, and (x) is the distance from the crevice mouth. Field-driven 
electromigration of Cl- (and other anions) into the crevice must occur to balance cationic charge 
associated with H+ ions, as well as the charge associated with Fe2+, Ni2+, Cr3+, and other cations. 
If such conditions do develop inside Alloy 22 crevices, accelerated attack of this material by LC 
or SCC may be possible. 
A detailed deterministic model has been developed to calculate the spatial distributions of 
electrochemical potential and current density in WP crevices, as well as transient concentration 
profiles of dissolved metals and ions (CRWMS M&O 2000c, Section 6.6.4). These quantities 
are calculated with the transport equations, which govern electromigration, diffusion, and 
convective transport. First, the axial current density along the length of the crevice is calculated 
by integrating the wall current density. The electrode potential along the length of the crevice 
can then be calculated from the axial current density. The partial differential equations that 
define transient concentrations in the crevice require determination of the potential gradient, as 
well as the local generation rates for dissolved species. The concentrations of dissolved metals at 
the crevice mouth are assumed to be zero. Computations are facilitated by assuming that the 
crevices are symmetric about a mirror plane where the flux is zero. This model has been used to 
estimate the extent of pH depression in WP crevices due to the simultaneous hydrolysis and 
transport of dissolved iron, nickel, chromium, molybdenum, and tungsten. The experimental 
measurements discussed below were used for validation.

 3-69  
3.1.6.7.2 Experimental Determinations of Crevice pH and Current 
In crevices made of steels containing more than 20 weight percent chromium, very acidic pH 
levels have been observed (pH < 2). The effect of chromium content on the ultimate crevice pH 
in a number of commercial and binary iron-chromium alloys is illustrated by Figure 3-53, while 
the increase in concentration of dissolved metals in such crevices is illustrated by Figure 3-54 
(CRWMS M&O 2000e, Section 6.7). Based upon experimental work with passive crevices 
without buffer, it is believed that the applied potentials required for significant acidification 
(pH < 5) are not plausible (CRWMS M&O 2000c). Therefore, a minimum crevice pH of about 5 
should be assumed in the absence of buffer and inhibitor ions. 
Source: CRWMS M&O 2000e, Section 6.7.1 
Figure 3-53. Effect of Chromium Content in Nickel-Chromium Alloys on Ultimate 
Crevice pH 
0.0 
0.5 
1.0 
1.5 
2.0 
2.5 
3.0 
3.5 
4.0 
4.5 
5.0 
0 10 20 30 40 50 60 70 80 90 100 
Chromium Content (%) 
Crevice pH 
Stainless Steel 304 
Reference: F. D. Bogar, C. T. Fujii, NRL Report 7690, NRL, Washington, DC, 1974.

 3-70  
Source: CRWMS M&O 2000e, Section 6.7.1 
Figure 3-54. Concentrations of Dissolved Metals in Stainless Steel 304 Crevice 
Exposed to 0.1 N NaCl 
The local crevice environments for Alloy 22 and other relevant materials have been determined 
experimentally (CRWMS M&O 2000c, Section 6.6.5). Crevices were constructed from square 
metallic samples, 2 inches on each side and 1/8 inch thick (same size as crevice samples used in 
the LTCTF). The samples were masked with plastic tape, thereby forming an exposed square 
area, 1.7 inches on each side. The exposed area was placed underneath a clear plastic window 
with an access port for a pH sensor in the center. In this case, the sensor was a miniature 
reference electrode separated from the crevice solution with a thin glass membrane. A second 
pH sensor was located at the mouth of the crevice, in close proximity to a Saturated Calomel 
Electrode (SCE). In parallel experiments, paper strips with a pH-sensitive dye (pH paper) were 
sandwiched between the clear plastic window and photographed with a digital electronic camera 
in a time-lapse mode to add confidence to the measurements made with pH sensors. 
Spectroscopic-grade graphite counter electrodes were also placed in the electrolyte lying outside 
the mouth of the crevice. A potentiostat was then used to control the electrochemical potential at 
the mouth of the crevice. Temperature, potential, current, and pH were then recorded 
electronically during the course of the experiment. 
An example of the pH measurements inside a crevice formed from Type 316L stainless steel is 
shown in Figure 3-55. The electrolyte was 4M NaCl and was maintained at ambient 
temperature. Since this electrolyte contained no buffer ions, it was considered to be a far more 
severe medium than media representative of various concentrations of J-13 well water. The 
electrochemical potential at the mouth was maintained at 200 mV vs. Ag/AgCl. Crevice 
corrosion could be seen initiating near the crevice mouth and propagating towards the pH sensor, 
which was located about 0.5 cm inside the crevice mouth. When the corrosion front reached the 
8 
16 
24 
32 
40 
48 
Ni 
Cr 
Fe 
0.0E+00 
2.0E-05 
4.0E-05 
6.0E-05 
8.0E-05 
1.0E-04 
1.2E-04 
1.4E-04 
1.6E-04 
1.8E-04 
Time (h) 
Dissolved Metal 
(moles/cm3) 
Ni Cr Fe

 3-71  
pH sensor, the pH dropped from the initial value (pH~7) to a very low value (pH~1). The fixed 
one-liter volume of electrolyte outside of the crevice became slightly alkaline. In similar 
experiments with 316L exposed to SCW, no significant lowering of the pH was observed. In 
crevices formed between the WPOB and the stainless steel structural material, a low pH is 
expected only if buffer and inhibitor ions are removed from the electrolyte. 
Measurements of pH inside crevices formed with Alloy 22 surfaces are shown in Figure 3-56 for 
a 4M NaCl electrolyte. The data illustrate the effect of incrementally increasing the applied 
potential, eventually exceeding the threshold required for localized breakdown of the passive 
film. The corresponding measurements of crevice current can be found in the supporting AMR 
(CRWMS M&O 2000c, Section 6.6.5). At an applied potential of 400 mV, the steady-state 
crevice pH remained close to neutrality (pH~6.1). As the potential was stepped to 1000 mV, the 
crevice current increased dramatically and the pH dropped below one. At an applied potential of 
1100 mV, extreme localized attack of the Alloy 22 was observed at the crevice mouth, with a 
crevice pH measurement near zero. In similar experiments with Alloy 22 in SCW, no crevice 
attack and no significant lowering of the pH was observed. Elevations of the eletrochemical 
potential due to gamma radiolysis (~700 mV) are insufficient to drive the crevice pH to low 
levels, even in the absence of buffer and inhibitor. 
0
1
2
3
4
5
6
7
8
9 
10 
0 120 240 360 480 600 720 840 960 1,080 1,200 
Time (minutes) 
Crevice pH 
-400 
-200 
0
200 
400 
600 
800 
1,000 
1,200 
Potential at Mouth 
(mV vs. Ag/AgCl) 
Inside of Crevice (pH) 
Mouth of Crevice (pH) 
Potential at Mouth (mV vs. Ag/AgCl) 
Source: CRWMS M&O 2000e, Section 6.7.5 
Figure 3-55. Stainless Steel 316L, 4M NaCl, 200 mV and 23C  Crevice pH 
versus Time

 3-72  
Source: CRWMS M&O 2000c, Section 6.6.5 
Figure 3-56. Alloy 22, 4M NaCl at 23C  Crevice pH versus Time 
Figure 3-57 is a summary of several experiments where crevice pH was determined in situ as a 
function of applied potential. These data are represented by the following polynomial: 
2 
2 1 0 x b x b b y + + = (Eq. 3-19) 
where x is the potential applied at the crevice mouth (mV versus Ag/AgCl) and y is the steadystate 
pH inside the crevice. Coefficients for the above equation are shown in the figure for both 
Alloy 22 and 316L, under a broad range of conditions. The correlations for 4M NaCl and SCW 
could be used to bound the crevice pH, using interpolation based upon the concentration of 
buffer ion between the two limits. Similar behavior is expected in titanium alloys. Additional 
testing with titanium-based materials is planned to confirm this. 
-2 
-1
0
1
2
3
4
5
6
7
8
9 
0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 
Time (minutes) 
Crevice pH 
-400 
-200 
0
200 
400 
600 
800 
1,000 
1,200 
Potential at Mouth 
(mV vs. Ag/AgCl) 
Inside of Crevice (pH) 
Mouth of Crevice (pH) 
Potential at Mouth (mV vs. Ag/AgCl) 
Sensors return to 
original values at 
end of experiment

 3-73  
Source: CRWMS M&O 2000c, Section 6.6.5 
Figure 3-57. Determination of Crevice pH for Waste Package Materials 
In conclusion, there was no visible evidence of localized corrosion inside crevices at applied 
potentials less than the threshold. However, even though crevices remained passive at potentials 
below the threshold, the passive current density and imposed electric field within the crevice 
were sufficient to cause significant acidification of 4M NaCl at higher applied potential. The 
buffer and inhibitor ions found in simulated concentrated J-13 waters prevent acidification of 
crevices, even at high applied potential. In many of the experiments described here, both the 
applied potential and the test medium are more severe than those expected in the repository. It is 
concluded from these results, that the conditions required for initiation of localized corrosion will 
be present in the repository and, therefore, degradation of these materials by localized corrosion 
is not a credible machanism. 
pH = - 5x10-6 E2 - 0.0012 E + 7.2716 R2 = 0.9782 
pH = 6x10-5 E + 8.1175 R2 = 1 
pH = 3.0586e-0.0012 E 
R2 = 0.9608 
pH = 0.0003 E + 8.276 R2 = 0.9646 
pH = - 4x10-6 E2 - 0.0015 E 
+ 7.0227 R2 = 1 
pH = - 1x10-5 E + 1.035 R2 = 0.0005 
-1
0
1
2
3
4
5
6
7
8
9 
10 
0 200 400 600 800 1000 1200 
Potential at Crevice Mouth (mV vs. Ag/AgCl) 
Crevice pH 
316L 0.54 mm Satd. KCl 20 C 
316L 0.54 mm 4M NaCl 20 C 
316L 0.54 mm SCW 20 C 
316L 0.54 mm 4M NaCl & SCW 20 C 
C22 0.54 mm 4M NaCl 20 C 
C22 0.54 mm SCW 20 C 
C22 0.54 mm 4M NaCl & SCW 20 C 
C22 0.11 mm 4M NaCl 20 C 
C22 0.11 mm 4M NaCl 20 C 
Poly. (C22 0.11 mm 4M NaCl 20 C) 
Poly. (316L 0.54 mm SCW 20 C) 
Expon. (316L 0.54 mm Satd. KCl 20 C) 
Linear (C22 0.54 mm SCW 20 C) 
Poly. (C22 0.54 mm 4M NaCl 20 C) 
Linear (316L 0.54 mm 4M NaCl 20 C)

 3-74  
3.1.6.7.3 Estimated Localized Corrosion Rate of Alloy 22 and Titanium Grade 7 
If the threshold potential or temperature for localized attack is exceeded, a corrosion rate 
representative of LC must be assumed. Due to the outstanding corrosion resistance of Alloy 22, very 
little data exists for such LC under plausible conditions. Work summarized in the AMR indicates 
that the corrosion rate of Alloy 22 in 10 wt. % FeCl3 at 75C might be as high as 12.7 m per year. 
This rate is significantly higher than those measured in the LTCTF, and may be representative of the 
rates expected for LC in the absence of inhibitor and buffer ions, including crevice corrosion. In a 
solution composed of 7 vol. % H2SO4, 3 vol. % HCl, 1 wt. % FeCl3, and 1 wt. % CuCl2, a penetration 
rate of 610 m per year was observed at 102C. Alloy C-276 has a composition similar to that of 
Alloy 22, and is therefore considered to be an appropriate analog. In other work, the corrosion rate 
of Alloy C-276 in dilute HCl at the boiling point is somewhere between 5 and 50 mils per year 
(127 and 1270 m per year). Comparable rates would be expected for Alloy 22. The highest passive 
current density found for Alloy 22 is approximately 10 A cm-2, which corresponds to a corrosion 
rate of approximately 100 m per year. It is expected that the logarithm of the LC rate of Alloy 22 
can be based on the aforementioned data and is normally distributed, as shown in Table 3-11. This 
distribution reasonably bounds those extreme penetration rates found in the literature, and is centered 
about the rate corresponding to the passive current density. 
Like Alloy 22, Titanium Grade 7 has outstanding corrosion resistance. Therefore, relatively little 
data exists for LC under plausible conditions. The published literature cited in the AMR (CRWMS 
M&O 2000d, Section 6.7) discusses a crevice corrosion depth of 250 microns, which was observed 
in a crevice formed from Ti-0.2%Pd and Teflon after a 582-day exposure in deaerated brine at 90C 
(157 m per year). In a metal-metal crevice, a crevice corrosion depth of 70 m was observed in a 
crevice formed from Ti-0.2%Pd after 489 days (52 m per year). Other more severe values are 
shown in Table 3-12 below. A rectangular distribution based on this table is assumed for the LC of 
Titanium Grade 7. 
Table 3-11. Distribution of Localized Corrosion Rates for Alloy 22 
Percentile LC Rate (m per year) 
0th 12.7 
50th 127 
100th 1270 
Source: CRWMS M&O 2000c, Section 6.6.6 
Table 3-12. Distribution of Localized Corrosion Rates for Titanium Grade 7 
Percentile LC Rate (m per year) Conditions 
0th 490 19% HCl + 4% FeCl3 + 4% MgCl2 at 82C 
100th 1120 Boiling 3:1 Aqua Regia 
Source: CRWMS M&O 2000d, Section 6.7

 3-75  
3.1.6.8 Microbial Corrosion 
It has been observed that nickel-based materials such as Alloy 22 are relatively resistant to MIC 
(CRWMS M&O 2000c, Section 6.8). Furthermore, it is believed that microbial growth in the 
repository will be limited by the availability of nutrients. For example, H+ is known to be generated 
by bacterial isolates from Yucca Mountain. Furthermore, thiobacillus ferrooxidans oxidize Fe2+, 
while geobacter metallireducens reduce Fe3+. Other microbes can reduce SO4
2- and produce S2-. 
Ultimately, the impact of MIC should be accounted for by adjusting Ecorr, Ecritical, pH and the sulfide 
concentration. The possible acceleration of abiotic corrosion processes by microbial growth is 
accounted for here. Horn et al. (CRWMS M&O 2000c) have shown that MIC can enhance corrosion 
rates of Alloy 22 by a factor of two (2). Figure 3-11 is a schematic representation of the corrosion 
model for the Alloy 22 outer barrier. The augmentation of corrosion rates due to MIC is accounted 
for in the model as shown in Figure 3-12. The enhancement factor, GMIC, is defined by 
Equation 3-20. 
original effective 
MIC 
corrected effective dt 
dp 
G 
dt 
dp 
. .
.
. 
. .
.
. 
 = . .
.
. 
. .
.
. 
(Eq. 3-20) 
This factor is calculated as the ratio of corrosion rates (microbes to sterile). Horn et al. (CRWMS 
M&O 2000e, Section 6.9) have shown that MIC can enhance corrosion rates of 304 stainless steel by 
a factor of about ten (10). The value of GMIC for 304 stainless steel in sterile media is about one 
(GMIC ~ 1), whereas the value of GMIC for 304 stainless steel in inoculated media is larger (GMIC ~ 10). 
It is assumed that MIC will have the same effect on 316NG stainless steel. The value of GMIC for 
Alloy 22 in sterile media is about one (GMIC ~ 1), whereas the value of GMIC for Alloy 22 in 
inoculated media is larger (GMIC ~ 2). 
The principal nutrient-limiting factor to microbial growth in situ at Yucca Mountain, has been 
determined to be low levels of phosphate. There is virtually no phosphate contained in J-13 
groundwater. Yucca Mountain bacteria grown in the presence of Yucca Mountain tuff are apparently 
able to dissolve phosphate contained in the tuff to support growth to levels of 106 cells ml-1 of 
groundwater. When exogenous phosphate is added (10 mM), the levels of bacterial growth increase 
to 107 to 108 cells ml-1. The difference of one to two orders-of-magnitude in bacterial growth with 
and without the presence of exogenous phosphate is not considered to be significant with respect to 
effects on corrosion rates. Therefore, nutrient limitation was not factored into the overall MIC 
model. It may be noted, however, that the 2-fold correction for MIC (GMIC ~ 2) included in the 
model was in the presence of sufficient phosphate to sustain higher levels of bacterial growth (in an 
effort to achieve accelerated Alloy 22 attack). 
Other environmental factors that could effect levels of bacterial growth include temperature and 
radiation. However, these factors are closely coupled to RH. As temperature and radiation decrease 
in the repository, RH is predicted to increase. There are some types of micro-organisms that can 
survive elevated temperatures (= 120oC) and high radiation doses. However, if there is no available 
water, bacterial activity is completely prevented. Thus, water availability is the primary limiting 
factor for MIC. Water availability is as expressed by RH and is used as the primary gauge of 
microbial activity. This factor is coupled to other less critical limiting factors.

 3-76  
A conservative approach is to assume that a critical mass of bacteria exists for MIC. Bacterial 
densities in Yucca Mountain rock have been determined to be on the order of 104 to 105 cells g-1 of 
rock. In absolute terms, this is almost certainly above the threshold required to cause MIC. Further, 
bacterial densities have been shown to increase one to two (1 to 2) orders-of-magnitude when water 
is available. More germane concerns are the types of bacteria present, their abundance, and how 
their relative numbers are affected when water is available for growth. Corrosion rates will be 
affected on some WP materials if organic acid producers compete more aggressively than sulfate 
reducers or inorganic acid producers for available nutrients, provided that water is sufficient to 
support growth. No data is currently available regarding the composition of the bacterial community 
over the changing environmental conditions anticipated during repository evolution. Instead, this 
issue has been addressed in the current model by determining overall corrosion rates under a 
standardized set of conditions, in the presence and absence of a defined set of characterized Yucca 
Mountain bacteria. 
3.1.7 Stress Corrosion Cracking 
3.1.7.1 Background 
One of the potential failure modes of the drip shield (DS), the waste package outer barrier (WPOB), 
and the stainless steel structural material is the initiation and propagation of SCC. Such 
environmental cracking may be induced by appropriate combination of metallurgical susceptibility, 
corrosive environment, and sustained tensile stress. The DS and the stainless steel structural material 
are excluded from this SCC evaluation. The DS is excluded because the stress that is relevant to 
SCC is considered to be insignificant. The major sources of stresses in the DS are loadings due to 
backfill and earthquakes. These stresses will not induce SCC because the stress caused by backfill is 
generally compressive stress and the stress caused by earthquakes is temporary in nature. The 
stainless steel structural support is excluded from this SCC evaluation since no corrosion 
performance is claimed for the 316NG. The purpose of this section of the PMR is to provide a 
detailed description of the process-level models that can be used to predict the performance of the 
WPOB in repository-relevant environments that may be capable of causing SCC. 
The three driving forces for SCC are metallurgical susceptibility, a corrosive environment, and static 
(or sustained) tensile stresses. Environments that cause SCC are usually aqueous and can be either 
condensed layers of moisture or bulk solutions. The SCC of a particular alloy is usually caused by 
the presence of a specific chemical species in the environment. For example, the SCC of copper 
alloys is almost always due to the presence of ammonia in the environment. Chloride ions cause 
SCC in stainless steels and aluminum-based alloys. Sulfides are known to cause SCC in nickelbased 
alloys such as Alloy 22. Changes in the environmental conditions, which include temperature, 
dissolved oxygen, and ionic concentrations, will normally influence the SCC process. 
The effects of stress on the propagation of SCC can be characterized by the stress intensity factor 
(KI). The definition and detailed calculations of the stress intensity factor are described in the AMR 
on SCC (CRWMS M&O 2000f, Section 6.2).

 3-77  
The SCC evaluation is focused on the WPOB closure weld because this weld cannot be stress 
relieved at the same time as other container welds. This region of the WP is potentially susceptible 
to SCC since welding will produce high-tensile residual stress in close proximity to the weld and 
since pre-existing flaws due to fabrication and welding have much higher distribution in the weld 
than in the base metal. An effective approach to eliminate the threat of SCC and resultant throughwall 
cracking in the closure weld is to implement a post-weld stress mitigation process to either 
remove residual tensile stresses in the weld region, or reduce them below threshold values for SCC 
initiation and growth. The initial process selected to mitigate SCC in the WPOB closure weld was 
single-pass laser peening. The laser peening process utilizes a rapidly pulsed, high energy density 
laser beam rastered across the surface region of the closure weld to induce a compressive surface 
layer with a thickness (depth) of 2-3 mm, thus removing the potential for SCC. However, the rate of 
removal of this beneficial layer by GC indicated that it would be eliminated in an unacceptably short 
time leading to possible SCC initiation and through-wall growth. The closure design was therefore 
modified to include two lids (inner and outer lid) with two separate post-weld stress mitigation 
processes; laser peening of the inner lid and induction annealing stress relief of the outer lid weld. 
During the induction annealing process, the weld region is very rapidly heated to the solution 
annealing temperature to remove weld residual stresses and rapidly cooled to avoid precipitation of 
potentially deleterious intermetallic phases (CRWMS M&O 2000f, Section 6.2). 
Two alternative process-level models that deal with SCC and the effect of stress on cracking 
propensity are described and evaluated in the supporting AMR. The first model, Method A, is based 
on the theory that there exists a threshold value of the stress intensity factor (KISCC) such that no 
growth occurs in a crack having a stress intensity factor (KI) less than the threshold value. This 
model is described in a subsequent section. 
The second model, Method B, relates crack advance to the metal oxidation that occurs when the 
protective film at the crack tip is ruptured. This slip dissolution or film rupture model is described in 
a subsequent section. In this case, the existence of a nominal threshold stress for SCC initiation on a 
smooth surface (s threshold) is assumed. 
Leakage can occur if SCC propagates to the point where a crack penetrates the container wall. Since 
the model predictions indicate that SCC can lead to WPOB breach, it is necessary to mitigate stress 
as described to lower the probability of cracking. 
3.1.7.2 Overview of Two Alternative Models for Stress Corrosion Cracking 
3.1.7.2.1 Model A  Stress Corrosion Cracking Threshold Model 
The concept of a threshold stress intensity factor (KISCC) has been commonly used to assess the 
susceptibility of material to SCC, as described in the SCC AMR (CRWMS M&O 2000f, 
Section 6.3). The applicability of this model to Alloy 22 (the material to be used for the WPOB) has 
been studied experimentally at Lawrence Livermore National Laboratory (LLNL). 
3.1.7.2.2 Model B  Stress Corrosion Cracking Slip Dissolution or Film Rupture Model 
The theory of slip dissolution or film rupture has been successfully applied to assess the SCC crack 
propagation for light water reactors at high temperature (approximately 288C). The detailed 
description of the SCC model based on the theory of slip dissolution or film rupture can be found in 
the AMR devoted to SCC (CRWMS M&O 2000f, Section 6.4). This model has been adopted to

 3-78  
assess the SCC capability of the material to be used for the WPOB. In this case, the existence of a 
nominal threshold stress for SCC initiation on a smooth surface is assumed. 
3.1.7.3 Stress Analysis 
No software codes were used directly in the development of this PMR. However, this report 
does include the results from software codes used in the supporting AMRs. 
ANSYS, Version 5.3, which is a finite element analysis code used for thermal and stress 
analyses, was used to develop data cited in SCC AMR (CRWMS M&O 2000f). 
pcCRACK, Version 3.1, is a fracture mechanics code used for stress intensity and crack growth 
simulation analyses. This code was also used to develop data cited in the SCC AMR (CRWMS 
M&O 2000f). 
3.1.7.4 Parameters and Inputs for Stress Corrosion Cracking Models 
3.1.7.4.1 Material Properties 
The specific properties of the WP materials are important in the determination of the residual stress 
in the closure weld. The properties used in this evaluation are documented in the AMR supporting 
the SCC model (CRWMS M&O 2000f, Section 4.1.1). 
3.1.7.4.2 Welding Parameters 
In evaluating weld-induced stress, the effect of each weld pass was determined by simulating the heat 
being deposited by the welding process over a prescribed time interval. Key parameters needed for 
this evaluation include the rate of electrical energy input, weld speed, and heat transfer. This 
information presented in the AMR supporting the SCC process-level model was used to determine 
the heat generation rate for the elements that represent each weld pass (bead). 
3.1.7.4.3 Threshold Stress Intensity Factor 
KISCC values for Alloy 22 were evaluated by using precracked wedge-loaded double cantilever beam 
(DCB) specimens in deaerated acidic brine (pH 2.7) at 90C. Duplicate samples of each material 
were loaded at four initial levels of the stress intensity factor (KI) with values ranging from 20 to 
39 ksi in1/2 (or 22 to 43 MPa m1/2). Both metallography and compliance methods were used to 
determine the final crack length. The final stress intensity factor for SCC (Kf) was computed from 
the measured final wedge load on the DCB specimens and the average crack length. The final stress 
intensity factor Kf was taken to be the SCC threshold value, KISCC. Studies are now underway to 
determine KISCC using reversing direct current potential drop (DCPD) technique, by which the value 
of KI is determined at zero crack velocity. 
3.1.7.4.4 Input for Slip Dissolution Model 
As discussed in Section 3.1.7.8.2, the slip dissolution model has four parameters: .., n , KI, and 
s threshold. The stress intensity factor KI has already been discussed. The parameter n in the crack 
growth equation for the slip dissolution model was obtained from reverse DCPD tests of Alloy 22 at 
110C, and at a stress intensity factor of 30 MPa m1/2 (CRWMS M&O 2000f, Section 4.1.4). These 
measurements indicate that the value of n is 0.84, which is considered an upper bound value. A

 3-79  
lower bound value of 0.75 was derived from engineering judgement based on comparison of 
available data for Alloy 22 and more SCC resistant stainless steels (CRWMS M&O 2000f, 
Section 3.2.2). 
3.1.7.4.5 Stress Mitigation 
Residual stress in WPOB can be mitigated by the multiple-pass laser peening technique. Preliminary 
measurements indicate that single-pass laser peening of an Alloy 22 plate (1-inch thick) is capable of 
producing a compressive surface layer that is about 1.5-mm deep, with compressive stress in the 
range of 20 to 60 ksi. Compression can be achieved at greater depths with multiple-pass laser 
peening, or localized induction annealing. If this stress mitigation approach is used, the life of the 
WP will be limited by the time required to remove the compressive layer by GC. 
3.1.7.5 Assumptions in Stress Corrosion Cracking Models 
In regard to SCC of the WPOB, the only stress that is significant is the residual stress in the closure 
weld. Dead-load stress is insignificant. Seismic stress is temporary in nature. 
Only the WPOB will be subjected to SCC susceptibility. The DS and the stainless steel structural 
support will be excluded from the evaluation for reasons discussed in Section 3.1.7.1. For the 
WPOB, only the closure welds will be considered for performance assessment. Unlike seam welds, 
the closure weld will not be stress-relieved at the time of fabrication. Welding procedures can 
produce ery high tensile stress in the weld region, and pre-existing flaws due to fabrication and 
welding may have much higher distribution in the weld. Without post-weld stress mitigation, this 
region of the WP will be susceptible to SCC. 
The SCC models have been applied to the single-lid WPOB design with and without laser peening. 
This initial application demonstrated the methodology. The model has more recently been applied to 
the dual-lid WPOB design. To remove deleterious residual tensile stresses, the closure weld in the 
outer lid will be treated by localized induction annealing, while the closure weld in the inner lid will 
be treated by multiple-pass laser peening. The dual-lid concept has been adopted for the WPOB to 
prolong the design life based on experience learned from previous unmitigated closure-weld designs, 
where both calculated and measured residual weld stress were found to be high. 
For the WP closure welds, the flaw orientation most likely susceptible to crack propagation is 
assumed to be that of either a circumferential flaw (parallel to weld) or a radially oriented flaw 
(perpendicular to weld). A radially oriented flaw would be driven by hoop stress, whereas a 
circumferentially oriented flaw would be driven by the radial stress. The distribution of flaw 
orientation is discussed in Section 3.1.2.6. 
In the Performance Assessment (PA), only radial cracks will be considered because the driving force 
(stress intensity factor) for a radial crack is much higher than the driving force for a circumferential 
crack. About one radial crack per closure weld patch was considered (CRWMS M&O 2000f, 
Section 5)). The patch size used in the WAPDEG analysis will be twice the lid thickness 
(~ 2 inches) (CRWMS M&O 2000f, Section 5). More careful review of published data has shown 
that this estimate is too conservative. See Sections 3.1.2.5 and 3.1.2.6. 
The slip dissolution mechanism (Section 3.1.7.8.2, Equation 3-28) relies on the crack-tip strain rate 
(which encompasses the effects of mechanics parameters), as well as the repassivation rate, (which

 3-80  
encompasses the effects of material characteristics and water chemistry). Because of the expected 
similarity in SCC behavior and mechanical response of face centered cubic alloys, the same crack-tip 
strain rate formulations that were employed for quantitative prediction of SCC in austenitic 304 or 
316 stainless steels in 288C high-purity boiling water reactor (BWR) water can be used for this 
analysis. 
The rate of repassivation is captured by the parameter n, the repassivation slope. A characteristic of 
the slip dissolution or film rupture model is that SCC susceptibility decreases with increasing values 
of n (CRWMS M&O 2000f, Section 5). For stainless steels more susceptible to SCC than Alloy 22, 
test data indicates that n = 0.54. Recent test results for SCC crack growth in Alloy 22 indicate that n 
= 0.84 (CRWMS M&O 2000f, Section 5). Conservatively the upper bound for n is set at a value of 
0.84 (CRWMS M&O 2000f, Section 5). Based on published literature values for SCC-resistant 
stainless steels, the lower bound for n is set at a value of 0.75. For highly SCC-resistant Alloy 22, 
this is judged to be appropriate (Section 3.1.7.4.4) (CRWMS M&O 2000f, Section 5). 
Although the slip dissolution model assumes crack growth can initiate at any surface defect that can 
generate a stress intensity (KI), regardless of defect size and tensile stress, examination of the relevant 
SCC literature indicates that there is a threshold stress ( 
.. threshold) below which SCC will not initiate 
on a smooth surface. In the case of the WP closure weld, a smooth surface is defined as an asmachined 
surface with a maximum roughness of 250 rms. This threshold stress is conservatively 
estimated to be between 10 and 40% of the yield stress (YS), based on published SCC initiation data 
for susceptible stainless steels. This range of threshold values is supported by data for drop 
evaporation tests at 200C found in Uhligs Corrosion Handbook (Erbing Falkland 2000). Types 304 
and 316 stainless steels have thresholds of 10% of the YS, whereas the other more SCC-resistant 
materials have thresholds ranging from 40 to 90% of the YS. While the highly SCC-resistant Alloy 
22 would be expected to have a threshold in the 40 to 90% YS range, a very conservative distribution 
of 10 to 40% YS is assumed for the TSPA expected case. If the stress is less than 10% YS, SCC 
does not initiate and the crack velocity (Vt) is set to zero. Below the threshold stress, the film rupture 
model is not invoked. 
The supporting AMR on SCC (CRWMS M&O 2000f, Section 6.3) discusses published threshold 
stress values for susceptible stainless steels in boiling solutions of magnesium chloride (~155C). 
These values tend to indicate a less conservative range of 20 to 30% YS. This range has also been 
used in some TSPA cases. 
3.1.7.6 Stress Analysis and Stress Intensity Factor Calculations 
During the evaluation of the process-level model for SCC, two WP closure designs were considered: 
a single-lid design for WPOB, and a double-lid design for WPOB. Due to the relative simplicity of 
the single-lid design, it is used in the initial discussion to illustrate the approach used to model SCC. 
Insight gained from evaluations of the single-lid WPOB lead to a more robust double-lid design, 
which is addressed in PA calculations shown in Section 3.2.4.

 3-81  
3.1.7.6.1 Calculation of Stress Intensity from Weld Residual Stress 
Determining the residual stress in the closure weld is a problem that can best be solved using finite 
element methods. The ANSYS Version 5.3 finite element model was used for developing data in 
support of the SCC model. As mentioned previously, the methodology and approach used to 
calculate the weld residual stresses and stress intensities will be demonstrated initially for the 
unmitigated and mitigated (laser peened) single-lid design. Then, calculated values specific to the 
dual-lid longer life design are reviewed. The mesh used to represent the unmitigated single-lid 
WPOB closure weld is shown in Figure 3-58. Results of the analysis are shown in Figures 3-59 and 
3-60 for the radial and hoop stresses, respectively (CRWMS M&O 2000f, Section 6.2.2.2). 
Source: CRWMS M&O 2000f, Section 6.2.2.2 
Figure 3-58. Finite Element Model for the Initial WPOB Design and Selected 
Cross Sections for Stress Plots (single-lid design) 
As previously discussed, the flaw orientations in the closure welds of the WPOB most susceptible to 
crack propagation are circumferential (parallel to weld) and radial (perpendicular to weld). 
Figure 3-61 shows these flaw orientations in relationship to the closure weld. A radially oriented 
flaw is driven by the hoop stress, whereas a circumferentially oriented flaw is driven by the radial 
stress.

 3-82  
Source: CRWMS M&O 2000f, Section 6.2.2.2 
Figure 3-59. Radial Stress - Initial WPOB Outer Lid at 125C Plots 
(single-lid design) 
Source: CRWMS M&O 2000f, Section 6.2.2.2 
Figure 3-60. Hoop Stress - Initial WPOB Outer Lid at 125C Plots 
(single-lid design) 
Initial WP, Outer Lid, 125C 
-30 
-20 
-10
0 
10 
20 
30 
0 0.5 1 1.5 2 2.5 3 
Distance from Inside Surface (in) 
Radial Stress, Sx (ksi) 
1-1 
2-2 
3-3 
4-4 
Initial WP, Outer Lid, 125C 
-10
0 
10 
20 
30 
40 
50 
60 
0 0.5 1 1.5 2 2.5 3 
Distance From Inside Surface (in) 
Hoop Stress, Sz (ksi) 
1-1 
2-2 
3-3 
4-4

 3-83  
Source: CRWMS M&O 2000f, Section 6.2.2.2 
Figure 3-61. Flaw Orientations for Lid Welds 
3.1.7.6.2 Impact of Corrosion on Stress and Stress Intensity Factor 
The initial results presented in the AMR on SCC of the WPOB (CRWMS M&O 2000f, Section 6) 
are for the as-built condition. This analysis assumes the full thickness for all WP components. In 
order to simulate the effect of wall thinning caused by GC, a layer of elements from the outside 
surface of the outer lid is removed. The thickness of this layer is 0.125 inches, which is equivalent to 
12.7% of the thickness of the outer lid. The maximum corrosion rate of Alloy 22 is very small, and 
is approximately 0.07 m per year after two years of exposure. At this rate, more than 4,500 years 
would be required to remove the outer layer of mesh elements. 
Figure 3-62 shows the stress intensity factor distributions for the circumferential crack. This 
figure shows the stress intensity factor as a function of absolute distance from the outside 
surface. This figure demonstrates that the overall effect of GC is small, but can make the stress 
intensity factor slightly higher. 
3.1.7.6.3 Mitigation of Weld Residual Stress 
Examination of the predicted stress distribution at the closure weld of the initial WPOB design 
(Figures 3-59 to 3-60) reveals, as expected, that tensile stresses may exceed 20% of the yield 
stress (~ 10 ksi) in both the radial and circumferential directions. This indicates that SCC 
initiation in unacceptably short times cannot be precluded with the as-welded design. 
Furthermore, examination of Figure 3-62 indicates that, at least for radially-oriented cracks, 
through-wall propagation is possible once a crack initiates. Since high residual tensile stresses 
are generated in the as-welded closure, it is necessary, as discussed previously, to implement a 
post-weld process to mitigate these potentially deliterious driving forces. This process can be 
implemented after the closure weld is made, thereby extending WP lifetime. 
Top View 
of Lid 
Circumferential 
Flaw (Parallel to Weld) 
Radial Stress is Driving 
Force. 
Radial Flaw (Perpendicular to 
Weld) Hoop Stress is Driving 
Force. 
Weld

 3-84  
Source: CRWMS M&O 2000f, Section 6.2.2.4 
Figure 3-62. Stress Intensity Factor for Radial Crack in Initial WPOB Outer 
Lid (single-lid design) 
To reduce residual weld stresses below the SCC initiation threshold, Waste Package Department 
has been evaluating improved designs of the WPOB (such as the dual-lid concept shown in 
Figure 3-63), welding techniques that generate low residual stress, and post-weld stress 
mitigation techniques such as localized induction annealing and laser peening. The specific 
selections of laser peening and localized induction annealing are based upon preliminary tests, 
published data, and the analyses presented here. Experimental measurements were made to 
quantify the stress-reduction benefit derived from laser peening. Figure 3-64 shows the effect of 
laser peening on the hoop stress profile in the single-lid closure weld. The corresponding stress 
intensity factor profile is shown in Figure 3-65. Evaluation of the time required to initiate SCC 
with a single-lid design led to the conclusion that a dual-lid design was needed, with both laser 
peening and localized induction annealing. This new design promises adequate performance 
(first breach beyond 10,000 years), with enough margin to allow for the unexpected. The 
thermal cycle used for localized induction annealing involves increasing the temperature of the 
weld region to 1120C in 35 seconds, while maintaining a gradual temperature gradient between 
the induction heated weld region and the remainder of the WPOB. The imposed temperature 
distribution is held constant for 10 seconds. The surface temperature is then lowered to room 
temperature in 30 seconds, thereby simulating the effect of quenching. The heat is dissipated by 
conduction within the WP. Simulation indicates that steady state is approached after five 
minutes. 
As can be seen by examination of the predicted stress distributions, both processes are capable of 
reducing the residual stress to below 10% of the yield stress (SCC initiation threshold) at depths 
down to 2 to 3 mm for laser peening, and at least 6.5 mm for post-weld induction annealing. 
Figure 3-64 illustrates the effect of laser peening. However, as discussed previously, since GC of the 
WPOB may eventually corrode away the beneficial surface layer with mitigated weld stress, it was 
deemed prudent to further modify the closure-weld design, incorporating two separate Alloy 22 lids 
with the weld in the outer lid being induction annealed, and the weld in the inner lid laser peened 
(Figure 3-63). 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 
Crack Depth (in) 
K (ksi-in^0.5) 
Ell. Crack (a/l=0.5) w/o Corr, 257F 
Ell. Crack (a/l=0.5), w/Corr, 257F

 3-85  
Source: CRWMS M&O 2000f, Section 6.2.2 
Figure 3-63. Schematic and Dimensions for Dual-Lid WPOB Design

 3-86  
Source: CRWMS M&O 2000f, Section 6.2.2.4 
NOTE: Figure modified from that in the AMR (Single-Lid Design) 
Figure 3-64. Measured Hoop Stress with and without Single-Pass Laser 
Peening Compared to Threshold Stress for SCC 
Source: CRWMS M&O 2000f, Section 6.2.2.4 
NOTE: Figure modified from that in the AMR (Single-Lid Design). 
Threshold stress intensity factor for SCC is also shown. 
Figure 3-65. Calculated Stress Intensity Factor for Hoop Stress with and 
without Laser Peening 
-60 
-40 
-20
0 
20 
40 
60 
80 
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 
Distance From Outside Surface (in) 
Stress (ksi) 
W/o peening 
W/ peening 
Threshold Stress 
-10
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 
Crack Size (in) 
K (ksi-in^0.5in) 
w/o Laser Peening 
w/ Laser Peening 
K - Threshold

 3-87  
3.1.7.7 SCC Method A  The Threshold Stress Intensity Factor Model 
For SCC to occur three factors have to exist: tensile stress; a susceptible microstructure; and a 
material-specific corrosive environment. Flaws can exacerbate SCC by concentrating the tensile 
stress. Such flaws (surface defects) can be formed during manufacture, localized corrosion, or other 
in situ processes. Once a crack is initiated, the crack will grow by SCC when the applied stress 
intensity factor, KI, is equal to or larger than SCC resistance parameter, KISCC. 
ISCC I K K = (Eq. 3-21) 
KISCC is a material- and environment-dependent property which can be obtained through fracture 
mechanics testing of the material in the specified environment. 
The stress intensity factor KI is usually defined as a function of stress ( s) and crack depth (a): 
a a KI p s  s = ) , ( (Eq. 3-22) 
where  is a geometry factor dependent on the shape of the crack and the configuration of the 
structural component, and s is the stress in a given direction. 
According to the current design, the material to be used for the WPOB is Alloy 22. Currently, the 
only existing source of KISCC values for Alloy 22 and Titanium Grade 7 is the experimental work 
performed at LLNL as described in the AMR on SCC (CRWMS M&O 2000f, Section 6.3). 
The final stress intensity factor (Kf,) obtained by examining DCB samples at the end of the test period 
is interpreted as KISCC, although it may represent only an upper bound of this threshold and may 
therefore not be conservative. The Kf values for the eight Alloy 22 specimens are 27.96, 28.73, 
28.78, 29.58, 29.66, 30.94, 31.98, and 32.39 ksi in1/2 (CRWMS M&O 2000f, Section 6.3.2). If a 
normal distribution is assumed, the mean value (KISCC.MEAN) and the standard deviation can be 
calculated: 
(KISCC.MEAN) = 30  1.6 ksi in1/2 or 33  1.8 MPa m1/2 (Eq. 3-23) 
The KISCC value can vary in accordance with different environmental conditions. In the absence of 
more data needed for the assessment of the variability of KISCC, the values given here are used. These 
values are considered conservative in regard to test environment since acidic NaCl solutions were 
used. 
The mean value of KISCC is 33 MPa m1/2 for an Alloy 22 lid. The maximum values of KI calculated 
for circumferential flaws in the closure welds are 22 MPa m1/2 for the outer lid and 13 MPa m1/2 for 
the inner lid. Since the mean value of KISCC is less than the values of KI associated with 
circumferential flaws, SCC initiation at these flaws is not a significant concern. However, the 
maximum value of KI for the hoop stress in either lid may exceed the threshold value. This is 
illustrated for the outer lid in Figure 3-62 where KI for the hoop stress can exceed 80 MPa m1/2.

 3-88  
3.1.7.8 SCC Method BThe Slip Dissolution or Film Rupture Model 
3.1.7.8.1 Background on Slip Dissolution or Film Rupture Model 
As stated previously, environmental cracking has historically been separated into initiation and 
propagation phases. This distinction is almost always arbitrary, for initiation is invariably defined 
as the time at which a crack is detected, or when the load has relaxed a specific amount (in a straincontrolled 
test): Initiation, therefore, corresponds to a crack depth of significant metallurgical 
dimensions (> 2 mm). 
A lifetime prediction model should be based on a fundamental understanding of the cracking 
mechanism. The formulation of such a crack propagation model requires a working hypothesis for 
the cracking mechanism and the evaluation of the parameters of importance in the mechanism. For 
the systems of interest, the slip dissolution or film rupture mechanism has been chosen. This 
cracking mechanism has been successfully applied to model the SCC for stainless steel, low-alloy 
steel, and nickel-based alloys in light water reactor environments as described in the SCC AMR 
(CRWMS M&O 2000f). The model is described in detail in the AMR on SCC. 
3.1.7.8.2 Application to Stainless Steel in Boiling Water Reactor 
The slip dissolution mechanism is represented by Equation 3-28, which shows the dependence of 
crack propagation rate (Vt) on the crack tip strain rate ( 

ct e ) (CRWMS M&O 2000f, Section 6.4.2): 
n 
ct t A V .. 
. .. 
. = 
 
e (Eq. 3-24) 
The parameters A and n depend upon the material and environment at the crack tip. These two 
parameters can be determined from the measured rate of repassivation. Such measurements are made 
by rapidly straining wires that are fabricated from the material of interest. 
The initial application of the slip dissolution model was the quantitative prediction of crack extension 
in Type 304 or 316 stainless steel in 288C high-purity water, representative of that used in a BWR. 
These extensive investigations led to a quantification of the model parameters: 
( ) 6 . 3 3 10 8 . 7 n A -  = (Eq. 3-25) 
Equations 3-28 and 3-29 have been combined to yield Equation 3-26: 
( ) 
n 
ct t n V .. 
. .. 
.  = 
 
- e 6 . 3 3 10 8 . 7 (Eq. 3-26)

 3-89  
where Vt has the unit of cm s-1 and 

ct e has the units of s-1. The crack tip strain rate in Equation 3-26 
is related to the engineering stress (or stress intensity) parameters via the formulations in the given in 
the SCC AMR (CRWMS M&O 2000f, Section 6.4.2). The relationship for constant load is: 
4 14 10 1 . 4 I ct K - 
 
 = e (Eq. 3-27) 
where KI is the stress intensity factor in the units of MPa m1/2. Since the stress in the WP closure 
weld (load) is essentially constant with time, substitution of Equation 3-27 for constant load into 
Equation 3-26 yields the following alternative expression: 
( )n 
I t K A V = (Eq. 3-28) 
where 
( )n A A 14 10 1 . 4 -  = (Eq. 3-29) 
and 
n n 4 = (Eq. 3-30) 
3.1.7.8.3 Application To Waste Package Outer Barrier Material 
There is ample reason to hypothesize that SCC of nickel-based Alloy 22 occurs by the same 
fundamental mechanism characterized by the slip dissolution model described in Section 3.1.7.8.2, 
(i.e., Equations 3-24 through 3-30). The only question that remains is that associated with the 
quantification of the repassivation rate, which is represented by the parameter n (repassivation slope). 
A characteristic of the slip dissolution model is that SCC susceptibility decreases as the repassivation 
slope increases. For stainless steels, test data indicate that n = 0.54 (CRWMS M&O 2000f, 
Section 6.4.3). Recent SCC tests of Alloy 22 indicate that n = 0.84 for the WPOB (CRWMS 
M&O 2000f, Section 6.4.4). To be conservative, n = 0.84 is considered to be the upper bound for n. 
A lower bound of n = 0.75 is judged to be appropriate for a highly SCC-resistant material such as 
Alloy 22 (CRWMS M&O 2000f, Section 6.4.4). 
In the smooth metal components dealt with in this PMR, the size of an incipient crack is expected to 
be exponentially distributed with a maximum possible size of 50 m and a median size of 20 m . 
The orientation of this crack will be either circumferential or radial, as shown in Figure 3-61. Only 
one crack per weld patch (WAPDEG element) will be considered. Based on the relatively high stress 
intensity factors for radial cracking in the outer lid of the initial WP design, it is evident that the slip 
dissolution model predicts eventual through-wall radial cracking. A modified WP design with duallids 
and stress mitigation in the closure welds has been developed to provide greatly enhanced 
service life. 
It is generally assumed that crack initiation will not occur if the stress is below a threshold value. 
Available data suggested that the threshold stress lies between 10 and 40% of the yield stress.

 3-90  
3.1.7.9 Estimate of Crack Opening 
Leaking through cracks can occur if the cracks grow into through-thickness cracks. A 
comprehensive, finite-element analysis may be used in the future to estimate the crack opening. 
However, a simplified approach is described here. The following assumptions are made for this 
simplified approach: 
1. A given crack in the WPOB closure weld is either circumferential (perpendicular to the 
radial stress) or radial (perpendicular to the hoop stress). A circumferential crack has a 
semi elliptical shape with depth a and length 2c. A radial crack has a semi-circular shape 
(a = c). 
2. The crack length 2c of a circumferential crack remains unchanged, but the final length of a 
through-wall crack is at least twice the wall thickness. Under this assumption, most 
cracks will grow in both directions of the minor (depth a) and major (length 2c) axes and 
assume the semi-circular shape (i.e., a = c) when they become through-wall cracks. 
According to fracture mechanics, a tends to grow faster than c because the stress intensity 
factor tends to have a maximum value at the end of the minor axis and a minimum value at 
the end of the major axis. Eventually, a semi-elliptical crack will become a semi-circular 
crack. The crack length 2c will remain unchanged only for very long cracks, with initial 
crack length greater than twice the wall thickness. For such long cracks, the occurrence 
rate is usually very low. The length of a semi-circular crack will always be equal to twice 
the crack depth. 
3. The crack opening has an elliptical shape with length 2c and a gap d. 
The AMR on SCC (CRWMS M&O 2000f, Section 6.5.4) shows that the opening of a crack in an 
infinite sheet is given for plane stress condition as: 
( ) 
E
c s d 4 = (Eq. 3-31) 
where d is the crack opening, 2c is the crack length, s is the stress and E is Youngs modulus. The 
opening area for an elliptical crack, Acr, can then be estimated with Equation 3-36: 
( ) ( ) 
E
c 
c Acr 
s p d p 
2 
4 
2 
2 = = (Eq. 3-32) 
When Equations 3-35 and 3-36 are used to estimate the crack opening(d) and opening area (Acr), the 
stress (s) is either the radial stress (for a circumferential crack) or the hoop stress (for a radial crack). 
3.1.7.10 Summary of Stress Corrosion Cracking Model 
Two alternative models that deal with SCC have been developed for the PA of the materials to be 
used for the WPOB. The first model (Method A) is based upon the concept of a threshold stress 
intensity factor at a pre-existing surface flaw, whereas the second model (Method B) is based upon 
the concept of a threshold stress at a smooth surface. Method B assumes crack propagation via the 
slip dissolution model, provided that the threshold stress is exceeded.

 3-91  
The first model (threshold stress intensity factor concept) is based on the theory that there exists a 
threshold value (KISCC) for the stress intensity factor such that there is no growth of a crack having a 
stress intensity factor less than the threshold value (CRWMS M&O 2000f). The concept of threshold 
stress intensity factor (KISCC) has been commonly used to assess the susceptibility of materials to 
SCC. The applicability of this model to Alloy 22 (the material to be used for the outer shell of the 
WP) has been studied experimentally. 
Preliminary results based on Method A show that the initial WP design is able to arrest 
circumferential SCC, but not radial SCC. For circumferential flaws in the closure welds, the 
maximum values of KI are less than the mean values of KISCC. Therefore, SCC should not initiate 
(CRWMS M&O 2000f, Section 6.3.2). The mean values of KISCC are 33.00 MPa m1/2 for the outer lid 
and 20.54 MPa m1/2 for the inner lid. The maximum values of KI estimated for a circumferential flaw 
initiated at the outer surface are 22 MPa m1/2 for the outer lid. However, based on the threshold 
value, through-wall, radial cracking can occur. 
Method B (slip dissolution or film rupture concept) relates crack advance to the metal oxidation that 
occurs when the protective film at the crack tip is ruptured. In this case, the theory of slip dissolution 
was successfully applied to predict the SCC propagation rate in light water reactors at high 
temperature. This model was adopted to assess the SCC susceptibility of the materials to be used for 
the WPOB (Alloy 22). Method B also predicts eventual through-wall radial cracking, based on the 
high radial KI value calculated for the outer weld in the initial design. 
3.1.7.11 Mitigation or Elimination of Stress Corrosion Cracking 
Since the crack growth analyses produced by either SCC model indicate that through-wall radial 
cracking is a potential threat to the WP, it is necessary to implement post-weld stress mitigation 
processes to eliminate the driving force for SCC. 
As mentioned previously, two methods have been identified for localized treatment of the closure 
weld region. One of these involves use of induction heating coils to affect a localized annealing of 
the weld region. This process has been used successfully in the annealing of weld stresses in large 
components such as girth welds in large-diameter casings of solid-fuel rockets. This process is 
expected to neutralize the residual tensile stress initially present in the closure weld at substantial 
depths. This post-weld process may be able to mitigate stress to greater depths than laser peening. 
However, there are several concerns associated with this approach. Calculations indicate that 
temperature gradients experienced during cool down tend to shift the location of the tensile stresses 
to another adjacent region of the WP, making that region potentially vulnerable to SCC. A second 
concern is that the process may heat the waste to unacceptably high temperatures. As discussed 
earlier, both possibilities were analyzed using the finite element code ANSYS. The results of this 
analysis show that localized annealing by induction heating is a viable approach for producing low 
tensile stresses (less than 20% YS at depths greater that 7 mm). 
The second method involves the use of laser peening, where a high-powered laser beam is used to 
cause shock waves in the surface of the material. These pulses produce compressive stresses in the 
surface. Multiple-pass laser peening can be used to increase the depth of the compressive stress 
layer. This process has been successfully demonstrated at LLNL on sample weldments 
(Figure 3-64). It has been shown that compressive stress can be produced at depths of 2 to 3 mm 
with multiple-pass laser peening. Additional depth may be possible, but has not been demonstrated. 
As discussed, a shortcoming of this approach is that this process only delays the potential initiation of

 3-92  
SCC. Below the layer of compressive stress, the weld region is still under tensile stresses. When the 
compressive layer of material is lost due to corrosion, the remaining material is still vulnerable to 
SCC. This applies to both mitigation techniques laser peening and induction annealing. 
An optimized closure weld design was developed based on ANSYS stress analysis. Through-wall 
residual stresses have been calculated for two post-weld stress mitigation processes with the ANSYS 
computer program (CRWMS M&O 2000f, Section 6). Based on these analyses, a dual-lid WP 
design employing both stress mitigation processes was developed to maximize the expected WP 
lifetime, which appears to be limited by SCC at the closure welds. 
3.1.7.12 Uncertainty in Stress Distributions for Closure Welds 
In this PMR, weld stress uncertainty limits of  10% of yield are recommended for use in the 
calculations to estimate time to first SCC through-wall cracking. This uncertainty range is based on 
the close degree of control anticipated for the Alloy 22 material, the welding process for the closure, 
and the post-weld stress mitigation processes. In contrast, weld stress uncertainty limits for axially 
oriented stresses as high as  35% of yield around the mean yield value are described in the literature 
(Mohr 1996). This high degree of uncertainty was empirically developed by bounding the measured 
scatter in residual stress developed for a large number of welded carbon-steel pipes covering a range 
of thicknesses, welding processes, weld joint configurations, weld heat inputs, yield strengths, etc. In 
the case of the final closure weld, the various parameters contributing to residual stress variation will 
be closely controlled. This includes close, automated control of the welding process parameters, the 
allowable material and the weld wire yield strength range, the weld joint configuration and spacing, 
etc. 
In contrast to the high degree of scatter noted in the carbon-steel paper (Mohr 1996), data available 
for shot-peened Incoloy 908, a high-performance nickel-based alloy, indicate a relatively narrow 
scatter (Pasupathi 2000). Data are for as-welded and as-welded plus shot-peened material with 1- 
sigma values of  3% of the measured stress value. This corresponds to an uncertainty range of 
about  9% at the 3-sigma level. In comparison, the residual stresses measured in a peened surface 
with X-ray diffraction (XRD) showed a measurement uncertainty of about  15 MPa, which is about 
5% of the Alloy 22 yield strength (Lu 1996). The data given by (Pasupathi 2000) are for both 
welded and non-welded samples (peened and unpeened), many of which also contain some cold 
work due to tube reduction drawing. Thus, they represent a good sampling of the entire range of 
material conditions that may be encountered. Since shot peening is analogous to laser peening in its 
effect on metals, the peened data are also relevant to the peened case for the inner lid. A stress 
variation similar to the peened case would be expected for material processed by localized induction 
annealing. During the induction annealing process cycle, all the residual weld stress in the heated 
weld region is fully relieved at ~1120C, and the remaining post-process stresses are produced during 
the cool-down portion of the thermal cycle. Since it is planned to control this cool-down process in a 
reproducible manner, we expect to see residual stress variations similar to those for laser and shot 
peening. 
In the case of the WP closure weld, XRD measurements of residual stress will be made of the final 
Alloy 22 material with post-weld stress mitigation. These measurements will be made in the 
near-surface region of the weld and HAZ. If stresses are found to deviate from the specified range, 
the weld will either be reprocessed, repaired, or scrapped. Thus, a defensible range of uncertainty in 
the stress distribution of  10% of the yield stress is more conservative than the observed 3-sigma 
scatter band. This range of uncertainty is believed to be appropriate for WAPDEG SCC calculations.

 3-93  
3.1.8 Hydrogen-Induced Cracking 
As discussed in Sections 3.1.5 and 3.1.6, the DS is to be fabricated from a titanium-based alloy and is 
highly resistant to general and LC. Other degradation mechanisms do not appear to be life-limiting. 
The material has been shown to be susceptible to SCC under certain conditions. As discussed in 
Section 3.1.7, mitigation of residual weld stress makes this an unlikely mechanism when backfill is 
present to preclude rockfall-generated stresses. Another possible failure mechanism for titanium and 
its alloys under waste disposal conditions is via hydrogen absorption, which can lead to HIC. HIC is 
also called hydrogen embrittlement and, can cause a decrease of the fracture toughness or ductility of 
a metal due to the presence of atomic hydrogen. The usual failure mode for a ductile material is the 
ductile tearing observed during slow crack growth. The decrease of fracture toughness can also 
cause fast crack growth (brittle fracture) of a normally ductile material under sustained load. During 
slow crack growth, material will fail as the stress intensity factor KI reaches a value KS. During fast 
crack growth, the same material will fail as the stress intensity factor KI reach a value KH, which is 
less than KS. 
It has been observed that the passive oxide film on titanium acts as an excellent barrier to the 
absorption of hydrogen under open-circuit conditions. However, hydrogen absorption may be too 
slow to observe analytically during practical tests (up to tens of years). This absorption could lead to 
a significant accumulation of hydrogen and the danger of HIC during exposures of 103 to 105 years. 
Under Canadian waste repository conditions, a very simple approach was adopted to predict when 
HIC might become a potential failure process in a waste container. In essence, this model is a 
susceptibility model or the equivalent of an initiation model for LC processes such as pitting and 
crevice corrosion. The basic premise of the model is that failure will occur when the concentration 
of hydrogen in the titanium exceeds a critical value (Hc). Combinations of stress intensity factor and 
hydrogen concentration that lead to brittle fracture or ductile rupture are discussed in AMR on HIC 
(CRWMS M&O 2000h, Section 6.1.3). The stress intensity factors for brittle fracture and ductile 
rupture are KH and KS, respectively. 
This model is presented in the AMR and is very conservative because it assumes that, when the 
environmental and material conditions can support cathodic hydrogen-charging processes, failure 
will be effectively instantaneous. 
Clearly, the propagation of a corrosion pit, a crevice, a stress corrosion crack, or a hydrogen-induced 
crack does not proceed instantaneously to failure. However, if the rate of propagation is fast on the 
geologic time scales being considered, then the process can be thought of as instantaneous. Another 
factor ignored in this analysis is the impact of propagation-limiting processes. For example, 
repassivation may occur with a pit or crevice; or crack blunting could occur with a stress corrosion 
crack. In the HIC model described below, no crack initiation or crack blunting processes are 
considered. 
3.1.8.1 Model Description 
The model can best be summarized as follows: 
1. The passive oxide is assumed to be permeable to atomic hydrogen.

 3-94  
2. Atomic hydrogen is generated at the surface of the Ti alloy. This is described by a 
hydrogen generation rate, which is taken to be proportional to the general corrosion rate of 
the passive material. 
3. A fraction of the hydrogen is absorbed into the oxide and assumed to directly enter the 
alloy. The remainder combines to yield hydrogen gas, which is lost to the surroundings. 
The rate of absorption is taken to be directly proportional to the hydrogen generation rate 
multiplied by an absorption efficiency coefficient. 
4. Once in the alloy, the hydrogen is transported throughout the entire thickness of the 
material to yield a uniform distribution of hydrogen. In other words, transport processes 
within the alloy are rapid compared to the rate of absorption. 
5. The hydrogen content of the alloy is allowed to increase until a critical level is reached. 
The material then fails immediately. The model allows for the calculation of hydrogen 
content and for comparison with the critical concentration. 
3.1.8.2 Elements of the Model Assumptions 
3.1.8.2.1 The Oxide is Assumed to be Permeable to Hydrogen 
The potential repository at Yucca Mountain will not achieve anoxic conditions. During the early 
stages of repository operation, the temperature will be high, but the oxygen and water content will be 
low. Since water is the only significant source of hydrogen (due to reaction with the titanium), 
hydrogen absorption rates should be lower during the initial stage of repository operation than during 
subsequent periods. Oxidizing conditions and an open-circuit corrosion potential too positive to 
allow the redox transformations in the oxide will eventually be established. Under oxidizing 
conditions, any exposed intermetallic or noble-metal particles (Ti2Ni in Titanium Grade 12; Ti and 
Pd in Titanium Grades 16 and 7) will be passivated by a surface oxide film. Consequently, their 
catalytic properties for hydrogen production and absorption may be lost. 
The oxide film remains impermeable to hydrogen until the electrical potential becomes sufficiently 
negative that the oxide becomes chemically unstable. When this occurs, Ti (IV) within the TiO2 
oxide is reduced to Ti (III) and hydrogen can be incorporated as a doping defect. When this process 
becomes possible, it is conservatively assumed that the oxide becomes permeable to hydrogen. 
Absorbed hydrogen then has free access to the alloy; in other words, any hydrogen entering the oxide 
can be rapidly transported to the metal (CRWMS M&O 2000h, Section 6.1.5). 
Several mitigating factors indicate that this is a very conservative scenario. First, experimental 
evidence suggests that total permeability is not established as soon as this oxide transformation 
begins. Second, in the absence of specific unexpected reducing reagents, it is unlikely that such 
redox transformations could be induced in the passive film. 
Assuming that the maximum temperature at which an aqueous condition can be sustained on the 
titanium is 125oC, a pH > 13 would be required for significant hydrogen absorption (CRWMS 
M&O 2000g). Therefore, it would be judicious to assume that hydrogen absorption is possible 
within the temperature range of approximately 100 to 125oC. This range effectively defines a 
window of susceptibility for hydrogen absorption.

 3-95  
The probability of hydrogen absorption by titanium alloys at Yucca Mountain is low but cannot be 
ruled out entirely. 
3.1.8.2.2 Hydrogen is Generated at the Surface of the Titanium Alloy 
The only feasible source of absorbable hydrogen appears to be the reaction of Ti with water. The 
direct absorption of radiolytically produced hydrogen requires a combination of high dose rate (> 104 
R h-1) and high temperature (> 200oC) and a steam or aqueous environment. This combination of 
conditions seems extremely unlikely at Yucca Mountain. Under open-circuit conditions, the rate of 
hydrogen production will be directly related to the GC rate. In the presence of dissolved oxygen, this 
rate has been shown to be extremely low and effectively immeasurable by standard procedures such 
as weight change measurements. Consequently, the rate of hydrogen production (the essential model 
boundary condition) will also be extremely low. 
Further, oxidizing conditions expected in the repository will not lead to a significant enhancement of 
GC; the process will be blocked by the excellent protective properties of the passive TiO2 film. 
Under these oxidizing conditions, the intermetallic precipitates should be covered by a passive oxide 
film and their catalytic properties severely degraded. 
Thus under Yucca Mountain repository conditions, the corrosion rate of titanium alloys (with the 
possible exception of Titanium Grade 12), and, hence, the rate of hydrogen production, will most 
likely be slow and transitory. Evidence suggests that even when corrosion, in the form of film 
growth, is initially accelerated under oxidizing conditions, the accumulation of mineral precipitates 
leads to the eventual blocking of corrosion processes. 
3.1.8.2.3 A Fraction of the Hydrogen is Absorbed into the Metal 
Even if the oxide film present on the titanium surface provides just a semi-impermeable barrier to 
hydrogen absorption into the metal, only a fraction of the hydrogen produced will actually be 
absorbed into the metal, and hence, contribute to the eventual embrittlement of the alloy. This 
critical fraction must be known. A consistent single value may not represent the real absorption 
efficiency of the alloy because this efficiency would be expected to change as the condition of the 
surface changed. The initial surface could be relatively free of absorbed hydrogen, and the initial 
absorption efficiency could be high. Subsequently, it would be expected to decrease as the number 
of available surface sites for absorption become saturated. These absorption sites could be the usual 
defects and dislocations known to trap hydrogen and, in addition, noble metal intermetallic particles, 
which would have a high solubility for hydrogen. Alternatively, the formation of surface hydrides 
could lead to a change in the mechanism of proton reduction and a decrease in the rate of hydrogen 
absorption into the alloy. 
The concern remains that in the temperature range extending from 100oC to 125oC and in the 
presence of an aggressive saline solution, the passive oxide film may be degraded and the hydrogen 
absorption efficiency increased. The rate of passive film growth (rate of hydrogen production), as 
well as the hydrogen absorption rate for Titanium Grade 12 in extremely saline solutions at 25 and 
100oC, are discussed in the AMR on HIC (CRWMS M&O 2000h, Section 6). These values for 
passive film growth rate and hydrogen absorption efficiency of 0.03 my-1 and 10%, respectively, 
would be conservatively appropriate for Titanium Grade 7 in a degraded passive condition.

 3-96  
3.1.8.2.4 Hydrogen is Uniformly Distributed in Titanium Alloy 
Once hydrogen is in the metal, its fate becomes dependent on the diffusion rate. The diffusivity is 
affected by the microstructure of the material, as well as the strength and distribution of stresses 
within the material. 
It was assumed that, because the rate of absorption of hydrogen into the metal would be very slow, 
its transport throughout the bulk would be comparatively rapid. Hence, absorbed hydrogen would be 
uniformly distributed throughout the alloy. At the high absorption rates experienced during 
electrochemical experiments, absorbed hydrogen can lead to the formation of a surface hydride layer. 
Since the presence of such a layer appears to impede the further absorption of hydrogen, its presence 
may actually reduce the absorption efficiency of the material (CRWMS M&O 2000h). 
However, hydrogen accumulates at the titanium surface. A conservative assumption is that it 
remains available for transport into the alloy. When the temperature is low enough so that the 
transport rate can be assumed to exceed the absorption rate (below 100oC), the thickness of the 
hydride layer will decrease as the hydride is redissolved in the alloy. The layer of hydride on the 
surface serves as a source of hydrogen for infusion into the bulk material. The hydride continues to 
redissolve until the surface layer is depleted. 
3.1.8.2.5 Hydrogen Concentration Increases to Critical Level where Failure Occurs 
The slow strain rate tests (CRWMS M&O 2000h, Section 6.2.3) show that titanium can tolerate 
substantial amounts of hydrogen before it becomes susceptible to cracking. This critical hydrogen 
concentration is not related to the solubility of hydrogen in the alpha matrix of the alloy but to the 
number density of precipitates, which must be capable of supporting a crack propagation process 
through the material. Values for critical hydrogen concentration (Hc) were obtained from published 
literature for Titanium Grades 2, 12 and 16 (CRWMS M&O 2000h, Section 6). The high value for 
Titanium Grade 16 (greater than 1,000 g per gram) appears to be due to the ability of the 
intermetallics to soak up hydrogen, thereby preventing them from forming hydride precipitates in the 
alloy. 
Whichever process is assumed for the dispersion of hydrogen throughout the titanium alloy, failure is 
assumed to occur once this critical value is achieved. However, this remains a very conservative 
approach because slow strain rate tests have determined the point at which the necessary stress level 
will inevitably be achieved. Also, the critical value is a threshold value, representing the lowest 
concentration at which influence of hydrogen is observed. It is feasible that much higher 
concentrations of hydrogen could be tolerated before failure actually occurs. 
3.1.8.3 Determination of the Critical Hydrogen Concentration 
Using the slow strain rate technique on precracked compact tension specimens precharged with 
known amounts of hydrogen, it has been shown that fracture toughness of Titanium Grade 2 and that 
of Titanium Grade 12 is not significantly affected until their hydrogen content exceeds a critical 
value, Hc. The as-received materials, containing 20 to 50 g per gram of hydrogen, are very tough 
and fail by ductile overload under high stress. This ductile tearing is also observed during slow-crack 
growth for both materials. The hydrogen concentration above which slow-crack growth is no longer 
observed and only fast-crack growth occurs is defined as Hc.

 3-97  
Critical hydrogen concentrations (Hc) of 400 to 2,000 g per gram were reported for Titanium 
Grade 2, 400 to 1,000 g per gram for Titanium Grade 12, and 1,000 to 2,000 g per gram for 
Titanium Grade 16 (CRWMS M&O 2000h, Section 6.2.2). Critical hydrogen concentrations are not 
available for Titanium Grade 7. The value of Hc for Titanium Grade 7 is conservatively assumed to 
be at least 400 g per gram, which is the lower bound value observed for Titanium Grades 2, 12, and 
16, as indicated previously. 
3.1.8.4 Determination of Hydrogen Concentration 
Analytical formulas can be derived to represent the hydrogen concentration in the metal as a function 
of time of emplacement of the container. There are two processes by which hydrogen could be 
produced, and possibly absorbed, under passive conditions: (1) direct absorption of hydrogen 
produced by water radiolysis and (2) absorption of atomic hydrogen produced by the corrosion 
process to produce oxide. The direct absorption of radiolytically produced hydrogen does not appear 
to be significant except at high dose rate (>102 Gy/h) and high temperature (>150C). This 
condition is clearly unattainable under Yucca Mountain conditions, and will not be considered, 
leaving the corrosion process as the only feasible source of hydrogen for absorption. 
The rate of hydrogen absorption will be controlled by the rate of the corrosion reaction, which 
dictates the rate of production of absorbable hydrogen. Since titanium oxide, TiO2, is extremely 
stable and protective in the repository environment, the corrosion reaction will be effectively limited 
to an oxide film growth reaction. 
While the rate of hydrogen production and absorption is directly proportional to the rate of film 
growth, the fraction of hydrogen absorption needs to be determined. Available test data suggest 0.1 
and 0.02 for fractional efficiency for absorption values, fh to represent high and low hydrogen 
absorption efficiencies for titanium alloys. The low value would appear most appropriate for 
Titanium Grade 2 since the passive film is a good transport barrier to hydrogen absorption. For 
Titanium Grades 7 and 16 in which intermetallic formation is very limited or avoided, the lower 
value is appropriate. 
Based on a constant film growth rate, and hence the corrosion rate, the concentration of hydrogen in 
the metal, HA, can be calculated as a function of time of emplacement (t in years) from the 
expression, 
HA = 4(.Ti/103) fh Ruct [MTi (do-Ruct)]-1 (Eq. 3-33) 
where HA = hydrogen content (g mm-3) 
.Ti = density of Ti (g cm-3) 
fh = fractional efficiency for absorption 
Ruc = rate of general passive corrosion (mm y-1) 
t = time of emplacement in years (y) 
MTi = atomic mass of Ti = 47.9 
do = original corrosion allowance (mm) = container wall thickness (mm) 
The units of atomic mass are grams per gram-atom, which for hydrogen is 1.0 grams per gram-atom 
and for titanium is 47.9 grams per gram-atom. Since there is 1 gram of hydrogen per gram-atom, the 
values of HA in (g mm-3) and in (g-atoms mm-3) are equal (to within less than 1 percent).

 3-98  
Considering a Titanium Grade 7 plate with 1 mm2 surface area, it is noted in Equation 3-33 that 
hydrogen in grams produced by the GC after t years of emplacement is based on the reaction: 
Ti + 2H2O . TiO2 + 2H2 
The derivation of Equation 3-37 is based on a constant GC rate. It was noted that the assumption of 
constant corrosion rate is conservative and less conservative corrosion models assume that the rate 
decays with time. (CRWMS M&O 2000d, Section 6.5.4) 
The rate of general passive corrosion, Ruc, can be calculated from the rate of oxide film thickness, 
Rox, by the following formula:
Ruc = Rox (.ox/Mox)(.Ti/Mti)-1 (Eq. 3-34) 
where .ox = density of the oxide in g cm-3 
Mox = molecular mass of the oxide 
Since the value of ( .ox/Mox)( .Ti/MTi)-1 is always greater than unity, it is conservative to assume that 
Ruc = Rox. 
The GC rates reported for Titanium Grade 7, at the 50th percentile is approximately 25 mm y-1, the 
rate at the 90th percentile is approximately 100 mm y-1, and the maximum rate is less than 350 mm y-1 
(CRWMS M&O 2000d, Section 6.5.4). 
3.1.8.5 Critical Hydrogen Concentration 
The HC value for Titanium Grade 7 is assumed to be at least 400 g/g, which is the lower bound 
value observed for Titanium Grades 2 and 12 as indicated previously (CRWMS M&O 2000h, 
Section 6.2). This assumption appears to be extremely conservative based on data reported for 
Titanium Grade 16. As noted, Titanium Grades 7 and 16 are similar alloys because of their similar 
chemical compositions. 
The fractional efficiency for absorption, based on previous discussion, is fh = 0.02 for Titanium 
Grade 7. The rate of general passive corrosion is Ruc = 100x10-6 mm y-1 (90th percentile value) or 
25x10-6 mm y-1 (50th percentile value). The time of employment is t = 10,000 years. A minimum 
wall thickness of 15 mm is assumed for do. 
Case 1: Conservative Estimate Rox=100x10-6 mm y-1 (90th percentile value) 
fh=0.02 
do=15 mm 
t=10000 y 
HA=119 g g-1 < Hc = 400 g g-1 
Case 2: Best Estimate Rox=25x10-6 mm y-1 (50th percentile value) 
fh=0.02 
do=15 mm 
t=10000 y 
HA=28 g g-1 < Hc = 400 g g-1

 3-99  
The hydrogen concentration in the DS at 10,000 years after emplacement is 119 g g-1 resulting from 
a conservative estimate and 28 g g-1 from a best estimate. The estimated hydrogen concentration in 
either case is significantly less than the conservatively selected critical hydrogen concentration of 
400 g g-1 for Titanium Grade 7. These results indicate that there exists a big margin of safety for the 
DS against the effects of HIC and this degradation mechanism is not credible under repository 
conditions. 
3.1.8.6 Results for HIC Model 
In the description of the HIC model presented in the corresponding AMR (CRWMS M&O 2000h, 
Section 6), extensive evidence has been provided to support a qualitative assessment of Titanium 
Grade 7 as an excellent choice of material for the DS with regard to degradation caused by hydrogeninduced 
cracking. Quantitative evaluation based on this model indicates that the DS material 
(Titanium Grade 7) is able to sustain the effects of hydrogen-induced cracking. Available corrosion 
test data show that the hydrogen concentration is below 120 g per gram, which is less than the 
critical hydrogen concentration of 400 g per gram for Titanium Grade 7. 
The current model is based on the use of backfill, which protects the DS from coming into contact 
with ground support materials such as carbon steel, rock bolts, wire mesh, etc. However, in the 
absence of backfill, the DS will likely come in contact with these materials and, therefore, may be 
subject to hydrogen pickup and embrittlement. This issue is being addressed in the revision of the 
AMR and is beyond the scope of this PMR. 
3.1.9 Model Uncertainties 
Uncertainties in each of the process models were identified in the discussion of the models in the 
previous sections and in the individual AMRs. The approach used in dealing with these uncertainties 
is to be conservative and bound the uncertainties. A review of the uncertainties in the various models 
is presented below. 
3.1.9.1 Thermal Aging 
A graphical approach to bounding the uncertainty in the aging model is illustrated in Figure 3-7. The 
line representing a best fit to the data for complete GB coverage predicts that more than 
10,000 years at 300C will be required to completely cover the grain boundaries of Alloy 22 with 
intermetallic precipitates. However, the line with the minimum slope possible within the error bars 
shows that complete GB coverage might occur in as little as 100 years (very unlikely bounding case). 
The best fit line is the most likely scenario. In the case of bulk precipitation, none is predicted with 
the line representing the minimum possible slope. Thus, we conclude with reasonable certainty that 
no bulk precipitation will occur after 10,000 years at 300C. 
From Figures 3-9 and 3-10, it appears that a fully aged sample of Alloy 22 could change the observed 
corrosion potential. For example, corrosion potential was shifted in a less noble (negative) direction 
by 63 mV in SAW at 90C. This potential was shifted in a less noble (negative) direction by 99 mV 
in SCW at 90C. Full aging of Alloy 22 (complete coverage of the grain boundaries) does not appear 
to significantly alter passive film stability.

 3-100  
Thermal aging of Titanium Grade 7 at 300C is expected to have little impact on the corrosion 
resistance of this material. Since no credit is claimed for the corrosion resistance of 316NG, the 
TSPA calculation is insensitive to the uncertainty associated with the corrosion of 316NG. 
3.1.9.2 Dry Oxidation 
In the case of Alloy 22, the rates of DOX are very small (CRWMS M&O 2000c, Section 6.1). 
Therefore, uncertainty in the DOX rate is not expected to have any significant impact on the 
performance of these materials. The current model is based upon published data, and does not 
include estimates of uncertainty (CRWMS M&O 2000c, Section 6.1). 
3.1.9.3 Humid Air and Aqueous Phase Corrosion 
The threshold RH is represented by Equation 3-2. This correlation represents the deliquescence point 
of NaNO3 and has an excellent fit of the data (correlation coefficient of 0.9854). Uncertainty in this 
threshold is primarily due to the composition of the salt film. The WP and DS would always 
experience some combination of HAC and APC. The uncertainty in this parameter is discussed in 
more detail in the associated AMRs. The correlation used for the threshold RH in a consecutive 
bonding case as the deliquescence point for Na NO3 is assumed to determine the threshold RH for the 
formation of aqueous film. As the temperature is increased, the lowest RH under which an aqueous 
film can be sustained is represented by the data for Na NO3. 
The distribution of GC rates for either HAC or APC represented by the curves given in 
Section 3.1.5.4. Distributions for 316NG are represented by Figure 3-15, which shows distributions 
formed from published data. Figure 3-23 shows the distribution of rates for Alloy 22, based upon 
data taken from the LTCTF. Figures 3-26 and 3-27 shows the distribution for Titanium Grade 7 
rates, also based upon data from the LTCTF. The dispersion in these curves is assumed to be entirely 
due to uncertainty. 
The variability is assumed to be comparable in magnitude and is represented by a triangular 
distribution. 
A detailed analysis of the error in GC rate is given in each supporting AMR, with the results 
summarized in Tables 3-8 and 3-9. 
Determinations of corrosion and threshold potential are based upon three replicate CP measurements 
at each combination of environment and temperature. The results are tabulated in the supporting 
AMR, as summarized in Figures 3-38 through 3-48. The uncertainty in the corrosion potential due to 
gamma radiolysis is addressed by Figures 3-51 and 3-52 (maximum positive shift in error of about 
250 mV). Some uncertainty in the selection of corrosion and threshold potential is shown in the 
figures as Threshold Potential 1 through 3. The bounds of the threshold potential are shown 
graphically in the figures. Numerical representations of this uncertainty have been made and are 
embedded in WAPDEG. 
The rates of LC have been bounded with the range of values found in the published literature, and 
are summarized in Tables 3-11 and 3-12.

 3-101  
3.1.9.4 Stress Corrosion Cracking 
For the first time, SCC has been included in the performance assessment calculation done with 
WAPDEG. Two alternative SCC models have been considered, one based upon a threshold stress 
intensity factor (Method A), and another based upon a threshold stress for a smooth surface 
(Method B). In the second approach, cracks are assumed to propagate by the slip-dissolution 
mechanism after initiation. Method B is used as the basis of the PA. The slip-dissolution model 
(Method B) predicts that crack propagation is a function of the local stress intensity at the crack tip. 
Thus, the uncertainty in this driving force must be estimated. 
The local stress intensity is calculated from the local stress and the crack penetration. The 
uncertainties in the stress distribution (stress vs. depth) are based upon analyses of measured residual 
stresses in welds, before and after mitigation, as well as finite element modeling with the ANSYS 
code. These uncertainties are abstracted for WAPDEG and shown quantitatively for the initial PA in 
Figures 3-73 through 3-80. 
Aside from the stress intensity, KI, the parameters in the slip-dissolution model for SCC propagation 
are based upon measurements for stainless steel from the BWR industry. Since stainless steels are 
much more prone to SCC than Alloy 22, these parameter estimates are projected to be conservative. 
The threshold stress for initiation of SCC on a smooth surface is conservatively estimated to be 
approximately 10 to 40% of the yield stress, based upon the determination of such thresholds for 
related but more susceptible alloy systems exposed to very aggressive environments. The 
uncertainty is assumed to be within .. 10% of the median value. 
3.1.10 Model Validation 
According to ASTM C1174-97 Standard Practice for Prediction of the Long-Term Behavior of 
Materials, Including Waste Forms, Used in Engineering Barrier Systems (EBS) for Geological 
Disposal of High-Level Radioactive Waste, model validation is the process through which 
independent measurements are used to ensure that a model accurately predicts an alteration behavior 
of WP materials under a given set of environmental conditions (e.g., under repository environment 
over the time periods required). Obviously, no model can be validated over the 10,000-year service 
life (time period) of the repository. The only means of validating models must involve accelerated 
testing. According to the same ASTM procedure, an accelerated test is a test that results in an 
increase in the rate of an alteration mode, when compared with the rates for service condition. 
Changes in alteration mechanism, if any, must be accounted for in the use of the accelerated test data. 
Model validation of specific process models is addressed in each of the AMRs as required by the 
procedures used to develop these models. Key elements are presented here. 
The thermal aging model is represented by equations 3-5 and 3-6, both of which assume Arheniustype 
kinetics. Precipitation and LRO can be accelerated by increasing the temperature above those 
levels expected in the repository. If the model can accurately predict the kinetics of these phenomena 
at combinations of time and elevated temperature, it will be considered valid for making predictions 
at lower temperature and longer time.

 3-102  
Since all available data has been used to establish these correlations the correlations are considered 
valid for their intended use. Additional data that are being collected will help to reduce uncertainties 
and improve the level of confidence in the model. 
The effects of precipitation and LRO on corrosion are determined by electrochemical techniques. 
Through application of electrochemical potentials more anodic than the open circuit corrosion 
potential, corrosion phenomena can be accelerated. Variations in corrosion and threshold potential 
can be correlated with the extent of thermal aging. Similarly, variations in rates of dissolution 
through the stable passive film can also be correlated with the extent of thermal aging. These rates of 
dissolution are accelerated by application of a potential between the corrosion and threshold 
potentials, and are proportional to the passive current density. The corrosion rate enhancement factor 
is determined by calculating the ratio of measured passive current densities for aged and unaged 
samples. Since all available electrochemical data have been used to establish the corrosion model for 
thermally-aged samples, this model is considered valid for its intended use. 
The models for DOX of Alloy 22, Titanium Grade 7, and 316NG stainless steel are based upon 
published data found in the scientific literature. More specifically the model for DOX of Alloy 22 is 
based upon the parabolic growth of the oxide film at elevated temperature. However, in the absence 
of any such low-temperature data, the parabolic rate constant for high temperature is applied at low 
temperature. Given the extremely small magnitudes of these rates, DOX is expected to have no 
significant impact on WP performance. 
The threshold RH for HAC is based on the deliquescence point of sodium nitrate. The threshold for 
salt films deposited in the repository may be slightly different. However, salt deposits produced by 
evaporating simulated J-13 water to dryness, support this basis. 
Rates of HAC are expected to follow distributions of GC rates based upon weight-loss data from the 
LTCTF. The distributions for Alloy 22 data for 6, 12, and 24 months of exposure to a variety of test 
media. Corroborative measurements made with the atomic force microscope (AFM) and other 
surface analytical techniques have also been used as further means of model validation. The test 
program will continue; ultimately providing data for 60-months of exposure. Future data will be 
considered independent and corroborative, and will be used to reduce uncertainties and conservatism 
in the model. 
The threshold RH for APC is the same as that used for HAC. The same approach has been used for 
validation. Rates of GC in the aqueous phase also obey the general distributions based upon weightloss 
data from the LTCTF. The same approach described for validation of the rate model for HAC 
has been employed for validation of the rate model for GC in the aqueous phase. 
Comparisons of corrosion and threshold potentials are used to determine whether rates for GC or LC 
are applicable. The initial correlations given in this PMR are based upon standard CP measurements 
in SDW, SCW, SAW, and SSW, covering a broad range of temperature. 
The SCC model is primarily based on published data. Very limited data have been obtained under 
repository relevant conditions. The data obtained under the YMP include pre-cracked specimens 
tested under very aggressive environments. Thus the model uses a very conservative approach. 
Future data obtained by the Project will serve to reduce the level of conservatism and improve the 
confidence in the model.

 3-103  
3.1.11 Alternative Approaches or Models 
Alternative models have been considered for rates of DOX, LC thresholds, stress corrosion 
thresholds, stress corrosion cracking, stress mitigation, & HIC. These alternatives are summarized 
below. 
3.1.11.1 Dry Oxidation 
Method A  Parabolic Growth Law 
Method B  Logarithmic Growth Law 
In the case of DOX, Method A is used for Alloy 22 (CRWMS M&O 2000c), while Method B is used 
for Titanium Grade 7 (CRWMS M&O 2000d). These model selections were based upon the 
availability of published data to support the corresponding models. 
3.1.11.2 Localized Corrosion Threshold 
Method A  Threshold Electrochemical Potential 
Method B  Threshold Temperature 
In the case of LC, Method A is used because the threshold potential model is more solidly rooted in 
the theoretical concepts underlying passive film stability (CRWMS M&O 2000c, 2000d). 
Furthermore, it is expected that good correlations of threshold and corrosion potential can be used to 
deduce a threshold temperature. The threshold temperature would be the temperature at which the 
corrosion and threshold potentials are equivalent. 
3.1.11.3 Stress Corrosion Cracking 
Method A  Threshold Stress Intensity Factor at Pre-Existing Flaw 
Method B  Initiation at Threshold Stress on Smooth Surface/Propagation by Slip-Dissolution 
Mechanism 
Method B is preferred for SCC since it is believed to be the more conservative model, and since it 
has been used for predicting the performance of BWRs, and since a wealth of data exists for stainless 
steel, a material more prone to SCC than Alloy 22. In prediction based upon a correlation for 
stainless steel would yield a conservative prediction for Alloy 22 (CRWMS M&O 2000f, 
Section 6.4.4). 
Weld Stress Mitigation 
Method A  Induction Annealing 
Method B  Laser Peening 
In regard to stress mitigation, Method A is preferred for any external lid on the Alloy 22 WPOB. 
This selection is based upon the ability of the induction annealing process to place compressive stress 
deeper into the weld. Method B, laser peening will be used on any internal lid weld, due to the 
occluded nature of such a weld.

 3-104  
3.1.11.4 Hydrogen-Induced Cracking  Titanium 
Method A  Threshold Electrochemical Potential 
Method B  Threshold Hydrogen Concentration 
HIC evaluation is based upon a threshold hydrogen concentration. Since such concentrations are 
possible to measure with secondary ion mass spectrometry (SIMS), Method B is therefore preferred. 
The DS design avoids any galvanic couple that would lead to the possibility of HIC via Method A, 
the threshold electrochemical potential method. 
A simple and conservative model has been developed to evaluate the effects HIC on the DS. The 
basic premise of the model is that failure will occur once the hydrogen content exceeds a certain limit 
or critical value (Hc). This model is very conservative because it assumes that, once the 
environmental and material conditions can support that particular corrosion process, failure will be 
effectively instantaneous. Extensive evidence has been provided to support a qualitative assessment 
of Titanium Grade 7 as an excellent choice of material for the DS with regard to degradation caused 
by HIC (CRWMS M&O 2000h, Section 6.1.3). 
Quantitative evaluation based on the HIC model described in the corresponding AMR indicates that 
the DS material (Titanium Grade 7) is able to sustain the effects of HIC. Available test data show, 
that the hydrogen concentration is below 180 g per gram, which is less than the critical hydrogen 
concentration of 400 g per gram for Titanium Grade 7. 
3.2 INTEGRATED MODEL 
The WAPDEG software was used to develop and implement an integrated model for WP and DS 
degradation analysis, and to perform the degradation simulations. WAPDEG (Version 4.0) is an 
appropriate tool for this application, because it was specifically designed to analyze DS and WP 
degradation profiles in a manner consistent with the information requirements for implementation in 
the TSPA model. WAPDEG (Version 4.0) was used within the range of values for which it is being 
validated (CRWMS M&O 2000g). 
3.2.1 Concept for the Integrated Model 
This section discusses the concept for the integrated model for WP and DS degradation analysis in 
TSPA-SR. More detailed descriptions of the conceptual model are given in the companion AMR, 
WAPDEG Analysis of Waste Package and Drip Shield Degradation (CRWMS M&O 2000g). In the 
TSPA-SR analysis, WAPDEG models various types of corrosion mechanisms that may occur on a 
WP and DS as a function of the exposure time and conditions. (For convenience of discussion in this 
section, DS is considered as an integral part of WP. Except where it is necessary, no separate 
discussion is given for DS.) In the nominal case analysis of TSPA-SR, the WPOB and DS were 
included in the WP degradation analysis. Because the stainless steel inner container, which is to 
provide structural support to the WP, is not expected to provide any substantial time-period for the 
waste-containment performance after an initial breach of the WPOB. Once exposed to corrosive 
condition, the stainless steel inner container is expected to fail by localized corrosion and SCC in 
a relatively short time period (see CRWMS M&O 2000e for the details of the inner container 
degradation). Because of this, performance credit of the inner container is not taken in the waste 
degradation analyses discussed in Section 3.2.7. This is based on the penetration rates shown in 
Figures 3-14 and 3-15 which suggest that the material may fail by localized corrosion under certain

 3-105  
conditions. However, in reality it would provide some performance for waste containment after 
breach of the WPOB, and would also serve as a barrier to radionuclide transport after the WP failure. 
Such potential performance credit of the inner container is ignored in the nominal TSPA-SR analysis. 
This is a conservative approach. 
As discussed in detail in Section 3.1.7, a dual closure-lid design has been proposed for the 
closure-end of waste package outer barrierone Alloy 22 lid on one end of the outer barrier and 
two Alloy 22 lids on the closure end of the outer barrier. This dual-lid design is to mitigate 
potential premature failure of waste packages by stress corrosion cracking (SCC). A schematic 
shown in Figure 3-66 illustrates the dual closure-lid design. The dual closure-lids are referred to 
as the outer-lid and inner-lid, respectively, in this section. The outer lid is 25-mm thick and the 
inner lid is 10-mm thick. There is a physical gap between the two lids. Thus, any SCC cracks 
penetrating the outer closure-lid stop at the gap between the closure lids. Then the inner closurelid 
welds are subject to the SCC crack initiation and growth. This design feature is captured in 
the waste package degradation analysis as described below in this section. 
Abstracted models of the process models for implementation in the WAPDEG model were 
developed in such a manner that important features of the process models are captured as 
explicitly as possible and that the degradation processes and their characteristics are properly 
represented in the waste package degradation analysis. More details of the TSPA-SR approach 
to waste package and drip shield degradation analysis are given in the supporting AMR 
(CRWMS M&O 2000g  WAPDEG Analysis of Waste Package and Drip Shield Degradation). 
As was done in the TSPA-VA analysis, effects of spatial and temporal variations in the exposure 
conditions over the repository were modeled by incorporating explicitly relevant exposure 
condition histories into the waste package degradation analysis. The exposure condition 
parameters that were considered to be varying over the repository are relative humidity and 
temperature at the waste package surface, seepage into the emplacement drift, chemistry of 
seepage water, and rockfall. In the waste package degradation analysis the humid-air corrosion 
condition is defined as an exposure condition that there is no dripping water and that the RH at 
the waste package surface is equal to or greater than the no-drip threshold RH (i.e., threshold RH 
in the absence of drips). The aqueous corrosion condition requires the presence of drips and the 
RH at the waste package surface equal to or greater than the drip threshold RH (i.e., threshold 
RH in the presence of drips). 
In the WAPDEG analysis the waste package (or drip shield) surface is discretized into many 
subareas referred to as patches, and relevant corrosion model parameter values and/or 
corrosion rates are populated over the patches. A schematic showing the conceptual model 
approach is shown in Figure 3-67. This approach is to represent potentially variable corrosion 
processes and other degradation processes on a single waste package. For example, patches 
wetted by dripping water (those marked with s) could be subject to localized corrosion 
depending on the exposure conditions (especially chemistry of contacting water) that those 
patches experience. Patches with closure welds (those marked with y) could be subject to SCC 
depending on the stress state and exposure conditions. In addition, general corrosion rate may 
vary over the waste package surface, and the potential variability is represented by populating 
the general corrosion rate over the patches.

 3-106  
25 mm 
Symmetric 
Symmetric 
Closure Weld 
25 mm 
Outer Lid 
10 mm 
Weld 
30 mm, Gap 
Inner Lid 
Figure 3-66. Schematic of the Dual-Closure-Lid Design for Waste 
Package Outer Barrier 
~ 1,000 Patches 
per WP 
x - Patches with 
fabrication welds 
s - Patches with drips; 
Potential salt deposits; 
Potential localized corrosion 
Single Patch 
Dripping 
Water 
Fabrication 
Welds 
x x x x x x x x
s 
s s s
s s s 
s s s 
s s 
s 
s s s 
s s s 
s s s 
s s s 
s s s 
* T, RH, in-drift water dripping from 
multi-scale T-H and UZ model abstraction 
* pH, [Cl-] of water contacting WP & DS 
from EBS chemical environment 
model abstraction 
x x x x x 
x 
x
x
x
x
x 
x 
x 
x 
y
y 
y 
y 
y 
y 
y 
y 
y 
y 
y - Patches with 
closure welds; 
potential SCC 
Closure 
Welds 
Figure 3-67. Schematic of the Conceptual Model of Stochastic Waste Package Degradation 
Model (WAPDEG) for TSPA-SR

 3-107  
Figure 3-68 shows a logic flow in the WAPDEG model for waste package (or drip shield) 
degradation analysis for TSPA-SR. In the figure each of the yellow boxes represents a model 
abstraction or model abstractions. The logic flow repeats for a drip shield, if included in the 
analysis, and each container layer of waste package. Exposure conditions that are included in the 
TSPA-SR waste-package degradation analyses are temperature and relative humidity at the 
waste package (and drip shield) surface, in-drift water dripping, and pH of the water contacting 
waste package (and drip shield). The temperature and relative humidity histories at the waste 
package and drip shield surface are provided from the multi-scale thermal-hydrologic model 
abstraction. The evolution of pH of solution contacting waste package is provided from the EBS 
chemical environment abstraction. 
In the analysis, the waste package surface RH is tested against the threshold RH (RHth) for 
corrosion initiation of the waste package. The RHth is based on the deliquescence point of 
NaNO3 salt as discussed in Section 3.1.3. If the surface RH becomes greater than or equal to the 
threshold RH, the waste package (or drip shield) undergoes corrosion. Depending on whether it 
is dripped on or not, it could undergo different corrosion degradation modes. In the current 
analysis, the same threshold RH is used for both the dripping and no-drip conditions. Both the 
upper and under sides of drip shield are assumed subject to corrosion if the initiation threshold is 
met, that is, the RH on the drip shield being equal to or greater than the threshold RH. This is 
because the both sides are exposed to the exposure conditions in the emplacement drift. 
For waste packages that are not dripped on, they undergo humid-air corrosion all the time during 
the simulation. Under humid-air conditions, the waste packages undergo general corrosion all 
the time and fail eventually by gradual thinning of the container wall. No localized corrosion 
occurs in the absence of drips. The general corrosion rates of the waste package outer barrier 
(and drip shield) are very low (see Section 3.2.2). For the waste package outer barrier and drip 
shield, the current model assumes the same general corrosion rate distribution for both humid-air 
general corrosion and aqueous general corrosion (i.e., regardless of whether it is dripped on or 
not). The WAPDEG model assumes that microbiologically influenced corrosion (MIC) is 
possible if RH at the surface is greater than or equal to the MIC threshold RH (90% RH) (Section 
3.1.5). The MIC effect is modeled with a corrosion enhancement factor, which is applied to the 
general corrosion rate of the barrier. The enhancement factor has uniform distribution between 1 
and 2 (Section 3.1.5). The MIC enhancement factor is applied to the entire surface as long as the 
RH is above the MIC threshold RH. The drip shield is assumed not subject to microbiologically 
influenced corrosion (MIC) under the repository exposure condition (CRWMS M&O 2000d; 
also see Section 3.1.5). 
The current model assumes that the Alloy 22 outer barrier is subject to aging and phase 
instability under the expected repository condition. The effect is modeled with a corrosion 
enhancement factor that is applied to the general corrosion rate (Section 3.1.4). The aging 
enhancement factor has uniform distribution between 1 and 2.5 (Section 3.1.4), and is applied to 
the entire surface of the outer barrier. The drip shield is assumed not subject to aging and phase 
instability (see Section 3.1.4).

 3-108  
Multi-scale T/H Model: 
WP/DS T & RH, In-Drift Drips 
EBS Chem. Env. Model: 
pH, Cl of contacting water 
Drips 
yes no 
Aqueous 
General Corrosion 
(include MIC & Aging) 
WP/DS 
Exposure Conditions 
RH = RHth(AQ) RH = RHth(HA) 
Ecorr = Ecrit Humid Air 
General Corrosion 
(include MIC & Aging) 
no 
Aqueous 
Localized Corrosion 
(include MIC & Aging) 
yes 
Stress Corrosion 
Cracking (SCC) 
- SCC-affected area 
- Stress profile 
- KI profile 
- Threshold stress 
- SCC model 
KISCC model 
Slip dissolution model 
- Manufacturing defects 
Stress Corrosion 
Cracking (SCC) 
- SCC-affected area 
- Stress profile 
- KI profile 
- Threshold stress 
- SCC model 
KISCC model 
Slip dissolution model 
- Manufacturing defects 
Time-history of 
patch penetrations 
Time-history of 
pit/crevice penetrations 
Time-history of 
crack penetrations 
Ecorr = corrosion potential 
Ecrit = critical corrosion potential 
KI = stress intensity factor 
KISCC = threshold stress intensity factor 
RHth = threshold relative humidity 
AQ = aqueous 
HA = humid air 
MIC = microbiologically influenced corrosion 
Figure 3-68. Logic Flow for Nominal-Case Model for Waste Package and Drip Shield Degradation Model for TSPA-SR

 3-109  
In the current model SCC is possible if the RH at the waste package surface is greater than or 
equal to the threshold RH for corrosion initiation (RHth) (i.e., no dripping or highly corrosive 
water chemistry is not required). As indicated in the logic flow, the input components to the 
SCC analysis are: (1) the area subject to SCC such as closure-lid welds in the current analysis; 
(2) stress and stress intensity factor (KI) versus depth of the affected area; (3) SCC crack 
propagation model (slip dissolution model or threshold stress intensity factor (KISCC) model); (4) 
threshold stress for crack propagation; and (5) manufacturing defect occurrence and size in the 
affected area. 
Both the slip dissolution model and the threshold stress intensity factor model have been 
incorporated in the WAPDEG model, and a selection between the two models is made with a 
flag for the model selection. For the SCC analysis with the slip dissolution model, the following 
should be met before initiating a SCC crack propagation in a patch: (1) the stress intensity factor 
(KI) should be positive, and (2) the stress state must be greater than or equal to the threshold 
stress. In the WAPDEG analysis, for those patches with a compressive stress zone (or layer) in 
the outer surface, the compressive stress zone is removed by general corrosion, and this delays 
the application of the slip dissolution model for the crack propagation rate. The delay time 
depends on the compressive zone thickness and the general corrosion rate sampled for the patch. 
The drip shield is assumed not subject to SCC because it will be fully annealed before it is placed 
in the emplacement drift. Likewise, all the fabrication welds in the waste container, except the 
welds for the closure lids, are assumed fully annealed and thus not subject to SCC. Therefore, 
only the closure-lid welds were considered in the SCC analysis. 
In addition, pre-existing manufacturing defects in a patch are assumed all surface-breaking, and 
the defects grow at the general corrosion rate sampled for the patch. This is based on the 
modeling assumption that the same exposure condition that a patch experiences during a given 
time step is also applicable to the interior of the defects in the patch. Growth of the defects at the 
general corrosion rate of the patch is a conservative assumption. Patches with pre-exisiting 
defects would be subject to SCC earlier than other patches without defect. 
For waste package (or drip shield) that is dripped on, the wetted area (or patches) of the waste 
package by dripping water is assumed to undergo aqueous corrosion if the RH at the surface is 
greater than the threshold RH. As indicated above, the same threshold RH is used for both the 
dripping and no-drip conditions. It is assumed that the entire surface of waste package (or drip 
shield) is wetted by the drips if it is dripped on. While the drip shield is operative (i.e., not 
failed), the waste package underneath the drip shield is assumed to undergo humid-air corrosion 
as described above. General corrosion occurs all the time under aqueous corrosion condition. As 
indicated above, for the waste package outer barrier and drip shield, the current model assumes 
the same general corrosion rate distribution for both humid-air general corrosion and aqueous 
general corrosion (i.e., regardless of whether it is dripped on or not). The same MIC and aging 
and phase instability enhancement factors as under humid-air condition are also applied to 
general corrosion under aqueous corrosion condition. Also, the same SCC model and inputs are 
applied for both humid-air and aqueous conditions. 
Initiation of localized (pitting and crevice corrosion) corrosion is dependent on the local 
exposure environment on the wetted patches. In the current analysis, it is assumed that localized

 3-110  
corrosion of the drip shield and waste package outer barrier can initiate only under dripping 
conditions. This is because of the necessary presence of aggressive ions (such as chloride) in 
order to initiate and sustain pit and crevice growth and because the only mechanism for these 
species to gain ingress to the drift is through drips. Localized corrosion of a patch is assumed to 
initiate if the corrosion potential (Ecorr) of the patch is greater than or equal to the threshold 
critical corrosion potential (Ecrit) sampled for the patch. After initiated, localized corrosion 
continues while Ecorr = Ecrit. If Ecorr becomes less than Ecrit,, or dripping ceases, localized 
corrosion stops. Potential for MIC and aging and phase instability effects on localized corrosion 
is represented with the same corrosion rate enhancement factors as used for general corrosion, 
that is, the MIC enhancement factor with uniform distribution between 1 and 2, and the aging 
and phase instability enhancement factor with uniform distribution between 1 and 2.5. These 
enhancement factors are applied to the localized corrosion rate. 
After failure of the drip shield, it is assumed that the dripping water finds the opening(s) in the 
drip shield regardless of the opening location in the drip shield (i.e., top or side of the drip 
shield), and the waste package underneath the failed drip shield is assumed to be subject to 
dripping. Although, in realty, the area of the waste package surface wetted by drips underneath 
the failed drip shield would depend on the drip rate, and the penetration opening location, size 
and number in the drip shield, the current model assumes that the entire surface of the waste 
package is wetted by the dripping water through the drip shield opening (or openings). The 
waste package is subject to the aqueous corrosion degradation processes (general corrosion, 
localized corrosion, and SCC) described above. 
When waste package fails, the WAPDEG model also considers corrosion degradation of the 
waste package from the inside-out corrosion. The inside-out corrosion analysis includes general 
corrosion and localized corrosion of the waste package outer barrier. The inside-out corrosion 
would cause penetrations by general and localized corrosion in addition to those by the outsidein 
corrosion only. The inside-out general corrosion is assumed to initiate at the time of the waste 
package failure. Like the outside-in localized corrosion, initiation of the inside-out localized 
corrosion is based on the corrosion potential and critical corrosion potential, which are a function 
of the pH of water inside the failed waste package. The in-package water chemistry results from 
degradation of the waste form and other internal structural materials (such as basket materials). 
The current model does not include the radiolysis enhanced corrosion of waste package outer 
barrier and drip shield because the materials are not subject to radiolysis enhanced corrosion 
under the repository conditions (Section 3.1.6). Also the curret model does not consider the 
rockfall induced mechanical damage to drip shield and its effect on the corrosion because the 
rockfall effect is assumed insignificant because of the presence of backfill over the drip shield. 
The bounding analyses have shown that the hydrogen uptake by the drip shield is much less than 
the threshold hydrogen concentration to cause hydrogen induced cracking (HIC) under the 
repository exposure condition (CRWMS M&O 2000h), and thus the HIC is not included in the 
drip shield degradation analysis. 
The WAPDEG analysis tracks down corrosion degradation of waste packages for three types of 
penetration modes: crack penetration by SCC, pit and crevice penetration by localized corrosion, 
and patch penetration by general corrosion. The analysis provides, as output, the cumulative 
probability of waste package failure by one of the three penetration modes as a function of time,

 3-111  
and the number of penetrations for each of the penetration modes as a function of time. The 
waste package failure time and penetration number profiles are used as input to other TSPA 
analyses such as waste form degradation and radionuclide release rate from waste packages. 
In the analysis the HAC condition is defined as an exposure condition for which the RH at the WP 
surface is equal to or greater than the threshold RH in the absence of drips. APC requires the 
presence of drips. 
3.2.2 Abstraction of General Corrosion Models for Waste Package Outer Barrier and Drip 
Shield 
This section discusses the approaches and assumptions used in the abstraction of GC models for 
WPOB and DS, and the abstraction results. Details of the abstraction approaches are described in 
CRWMS M&O (2000i). 
3.2.2.1 Approaches and Assumptions 
The model abstractions are to develop two cumulative distribution functions (CDFs) each one 
representing the GC rate distribution for the WPOB (Alloy 22) (CRWMS M&O 2000c, Sections 5.3 
and 6.5) and the other for the DS (Titanium Grade 7) (CRWMS M&O 2000d, Sections 5.3 and 6.3). 
For each alloy, the weight loss and crevice sample penetration rate data were combined to yield one 
GC rate data set for each alloy. For the WPOB the general corrosion rate data with 6-month, 
1-year and 2-year exposure were considered. As shown in Figure 3-69, the variance in the 
corrosion rate data is reduced with the exposure time, and the median rate decreases also with the 
exposure time (see Section 3.1.5.4.2). It was concluded that the 2 year data are sufficiently 
conservative to represent long-term general corrosion rate of the WPOB. Therefore only the 
2-year data were used in the model abstraction (i.e., the 6-month and 12-month data were not 
included). For the drip shield the 12-month data were used in the model abstraction. The 
cleaning method employed with the 6-month titanium samples caused significant metal loss, 
thereby yielding unusually high corrosion rates that proved to be artifacts (CRWMS M&O 
2000d, Section 6.5.2). Therefore the 6-month data were not included in the abstraction 
development. 
The GC rate data were then sorted in ascending order. Any negative GC rates were then deleted 
from the data set as suggested in Section 3.1.5. Cumulative probabilities were assigned to each GC 
data point based on its rank (position) in the sorted data set yielding a CDF. The units of the GC 
rates were converted from nm per year (reported in Section 3.1.5) to mm per year. An upper bound 
(corresponding to the 100th percentile cumulative probability) was also applied to the resulting GC 
rate CDFs. The upper bound was 7.30E-5 mm/year for Alloy 22 (see the assumption below) and 
3.25E-4 mm/year for Titanium Grade 7 (see the assumption below). Details of the abstraction 
approaches are described in CRWMS M&O (2000i).

 3-112  
General Corrosion Rate (m/year) 
-0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 
Cumulative Probabaility 
0.00 
0.25 
0.50 
0.75 
1.00 
6 Month 
1 Year 
2 Year 
Alloy 22 General Corrosion Rate Data CDFs from 
Different Exposure Times 
Figure 3-69. Cumulative Distribution Functions for the General 
Corrosion Rate of Alloy 22 Derived from 6-month, 
One-Year, and Two-Year Exposure Data 
A set of assumptions were employed in the model abstraction. Key assumptions are described 
below.
 For both alloys considered (Alloy 22 and Titanium Grade 7), corrosion penetration rate data 
from the weight loss of both plain and creviced geometry test coupons were considered to 
represent GC penetration rate. 
 The maximum GC rate for Alloy 22 was set to 7.30E-5 mm/year. This assumed upper 
bound is greater than the maximum penetration rate of 7.25E-5 mm/year observed in the 
LTCTF (Section 3.1.5). 
 The maximum GC rate of Titanium Grade 7 was set to 3.25E-4 mm/year. This assumed 
upper bound is greater than the maximum penetration rate of 3.19E-4 mm/year observed in 
the LTCTF (Section 3.1.5). 
 The Gaussian Variance Partitioning (CRWMS M&O 1998b, Section 5.7.2.2) is an adequate 
method to separate uncertainty and variability from a distribution that represents the 
combination of the both. Details of the Gaussian Variance Partitioning technique is 
described in Section 3.2.2.2 below. 
Detailed discussion of the assumptions employed in the model abstraction is given in CRWMS 
M&O (2000i).

 3-113  
3.2.2.2 Gaussian Variance Partitioning Technique for Uncertainty and Variability 
Representation 
The Gaussian Variance Partitioning is a technique that decomposes a Cumulative Distribution 
Function (CDF) containing both uncertainty and variability into two distributions that 
characterize each element separately. This provides a better conceptual understanding of TSPA 
model sensitivity to the elements of uncertainty and variability. Gaussian variance partitioning 
starts with a distribution that involves both uncertainty and variability and then works backward 
to obtain two separate distributions, one that characterizes variability and another that 
characterizes uncertainty. This is accomplished by assuming that uncertainty and variability are 
independent. If the mixed distribution is normally distributed, i.e. ) , ( 2 2 
v N s s   + , then it can be 
represented as a random variable . having the form
v m + = . (Eq. 3-35) 
where m is a normal random variable with mean  and variance 2
 s , and v is a normal random 
variable with mean zero and variance 2 
v s . Thus, . is a random variable distributed around the 
mean  with a total variance given by the sum of the variances due to uncertainty and 
variability. If uncertainty is defined as the uncertainty in the mean value and variability as the 
variance about that mean, then . can be alternatively parameterized as 
), , m ( N ~ 2 
v s . where ) , ( ~ 2
 s  N m (Eq. 3-36) 
The uncertain mean is represented by the random variable, m , which is normally distributed 
with mean,  and variance, 2
 s . The random variable, . , is then the convolution of the 
distributions of the random variable given by m and a random variable, v , which can be 
represented by the addition of two normal random variables as given above where 
) , ( ~ 2
 s  N m and ) , 0 ( ~ 2 
v N v s (Eq. 3-37) 
Thus, given the distributions for m and v , a variability distribution is realized by sampling a 
value from the parameter uncertainty distribution and adding it to the mean zero variability 
distribution. 
This partitioning method can be extended to non-normal distributions by means of a score 
transform (Deutsch and Journel 1992, p.138) mapping the percentiles of the non-normal CDF to 
those of the standard normal by a lookup table. The normal score transforms works best if the 
non-normal CDF is as symmetric as possible. This may sometimes be accomplished by using the 
natural logarithms of CDF values. The natural logarithms of the CDF values are used to perform 
the normal score transformation and the transformed distribution is used to partition the total 
variance of the transformed distribution between uncertainty and variability. Finally the normal 
score transformation is applied in reverse to the resultant distributions to obtain a final 
distribution for variability.

 3-114  
3.2.2.3 General Corrosion Model for Waste Package Outer Barrier 
The original cumulative distribution function (CDF) for the GC rate for the Alloy 22 WPOB is 
shown in Figure 3-70. The CDF is considered a mix of uncertainty and variability of the GC rate. 
However, quantification of uncertainty and variability in the corrosion rate measurements is limited 
because the corrosion rates are extremely low and considered to be within the measurement noise. 
Because of this, it is difficult to separate what the fraction of the total variance in the parent CDF 
represents the uncertainty and what fraction represents the variability. In the WP degradation 
(WAPDEG) analysis the fraction for the split of the uncertainty and variability from the parent CDF 
is treated as an uncertain parameter (CRWMS M&O 2000g). Figure 3-70 also shows, along with the 
original CDF, the resulting variability CDFs for GC rates using 25%-75%, 50%-50%, and 75%-25% 
uncertainty and variability partitioning ratios, and 50th uncertainty percentile. Figures 3-71 and 372 
show the resulting variability CDFs using 25th and 75th uncertainty percentile, respectively. 
3.2.2.4 General Corrosion Model for Drip Shield 
The resulting original CDF for the GC rate for the Ti-7 DS is shown in Figure 3-73. As with the 
CDF for the WPOB GC rate, the DS general corrosion CDF is considered a mix of uncertainty and 
variability of the GC rate. However, quantification of uncertainty and variability in the corrosion rate 
measurements is also limited because the corrosion rates are extremely low and considered within the 
measurement noise. Because of those it is difficult to separate what the fraction of the total variance 
in the parent CDF represents the uncertainty and what fraction represents the variability. In the WP 
degradation analysis the fraction for the split of the uncertainty and variability from the parent CDF 
is treated as an uncertain parameter (CRWMS M&O 2000g). Figure 3-73 also shows, along with the 
original CDF, the resulting variability CDFs for GC rate using 25%-75%, 50%-50%, and 75%-25% 
uncertainty and variability partitioning ratios, and the 50th uncertainty percentile. Figures 3-74 and 
3-75 show the resulting variability CDFs using 25th and 75th uncertainty percentile respectively. 
3.2.2.5 Alternative Conservative Model for Waste Package and Drip Shield General 
Corrosion 
As discussed in Section 6.5.5 of CRWMS M&O (2000c), the formation of silica scale deposit on 
the surface of the Alloy 22 sample coupons could bias the distributions of the original estimated 
general corrosion rate (shown as Original Distribution in Figures 3-70 to 3-72). The potential 
measurement bias for the weight loss sample coupons was estimated to be 0.063 m/year 
(CRWMS M&O 2000c, Section 6.5.5). It was recommended that the distributions of Alloy 22 
general corrosion rate be corrected for the maximum bias due to silica scale deposit formation by 
adding a constant value of 0.063 m/year to each estimated value of the general corrosion rate 
(CRWMS M&O 2000c, Section 6.5.5). 
In the model abstraction it was assumed that the range of the corrosion rate increase from the 
scale deposit is represented with uniform distribution between zero (i.e., no scale deposit) and 
the maximum bias (0.063 m/year). Then the corrosion rate increment was sampled from the 
assumed distribution and added to each original estimated value of the general corrosion rate (the 
CDF shown as Original Distribution in Figures 3-70 to 3-72). The resulting general corrosion 
rate data were sorted in ascending order. Cumulative probabilities were assigned to each GC 
data point based on its rank (position) in the sorted data set yielding a new CDF. The same data 
treatment was conducted for the correction of the Ti-7 drip shield general corrosion rate data.

 3-115  
The resulting general corrosion rate CDF for the Alloy 22 WPOB and Ti-7 drip shield is shown 
in Figures 3-76 and 3-77 respectively, along with their respective original CDF. As shown from 
comparing the CDFs, the corrosion rate correction causes the median rate (50th percentile value) 
increased by about 50 percent. Effect of this rate increase on waste package and drip shield 
degradation is discussed in the WAPDEG analysis results in Section 3.2.7. 
Figure 3-78 also shows, along with the original CDF, the resulting variability CDFs for the GC 
rate abstraction results of the Alloy 22 WPOB using 25%-75%, 50%-50% and 75%-25% 
uncertainty and variability partitioning ratios, and 50th uncertainty percentile. Figures 3-79 and 
380 show the resulting variability CDFs using 25th and 75th uncertainty percentile, respectively. 
The uncertainty and variability partitioning was accomplished using the Gaussian Variance 
Partitioning technique described in Section 3.2.2.2. A set of new CDFs for the Ti-7 DS general 
corrosion rate abstraction using 25%-75%, 50%-50% and 75%-25% uncertainty and variability 
partitioning ratios at 50th, 25th and 75th uncertainty percentile are shown in Figures 3-81 to 3-83 
respectively. 
Alloy 22 General Corrosion Rate CDFs 
25, 50, and 75% Variability - 50th Uncertainty Percentile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability 
Figure 3-70. The Variability Cumulative Distribution Functions for the 
General Corrosion Rate of the Alloy 22 Waste Package 
Outer Barrier Using 25%-75%, 50%-50%, and 
75%-25% Uncertainty and Variability Partitioning Ratios 
and 50th Uncertainty Percentile

 3-116  
Figure 3-71. The Variability Cumulative Distribution Functions for the General 
Corrosion Rate of the Alloy 22 Waste Package Outer Barrier 
Using 25%-75%, 50%-50%, and 75%-25% Uncertainty and 
Variability Partitioning Ratios and 25th Uncertainty Percentile 
Alloy 22 General Corrosion Rate CDFs 
25, 50, and 75% Variability - 25th Uncertainty Percentile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability

 3-117  
Figure 3-72. The Variability Cumulative Distribution Functions for the General 
Corrosion Rate of the Alloy 22 Waste Package Outer Barrier 
Using 25%-75%, 50%-50%, and 75%-25% Uncertainty and 
Variability Partitioning Ratios and 75th Uncertainty Percentile 
Alloy 22 General Corrosion Rate CDFs 
25, 50, and 75% Variability - 75th Uncertainty Percentile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability

 3-118  
Figure 3-73. The Variability Cumulative Distribution Functions for the General 
Corrosion Rate of the Ti-7 Drip Shield Using 25%-75%, 50%-50%, 
and 75%-25% Uncertainty and Variability Partitioning Ratios and 
50th Uncertainty Percentile 
Ti-7 General Corrosion Rate CDFs 
25, 50, and 75% Variability - 50th Uncertainty Percentile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability

 3-119  
Figure 3-74. The Variability Cumulative Distribution Functions for the General 
Corrosion Rate of the Ti-7 Drip Shield Using 25%-75%, 50%-50%, 
and 75%-25% Uncertainty and Variability Partitioning Ratios and 
25th Uncertainty Percentile 
Ti-7 General Corrosion Rate CDFs 
25, 50, and 75% Variability - 25th Uncertainty Quantile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability

 3-120  
Figure 3-75. The Variability Cumulative Probability Distribution Functions for 
the General Corrosion Rate of the Ti-7 Drip Shield Using 25%- 
75%, 50%-50%, and 75%-25% Uncertainty and Variability 
Partitioning Ratios and 75th Uncertainty Percentile 
Ti-7 General Corrosion Rate CDFs 
25, 50, and 75% Variability - 75th Uncertainty Percentile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability

 3-121  
2-yr Alloy 22 General Corrosion Rate CDFs 
(Original vs. Corrected for silica scale deposit) 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Alloy 22 Data 
Corrected Alloy 22 Data 
Figure 3-76. Cumulative Probability Distribution Functions for 
the General Corrosion Rate of Alloy 22 Waste 
Package Outer Barrier Before (Original) and 
After (Corrected) Accounting for Bias Due to 
Possible Silica Scale Deposits

 3-122  
Titanium Drip Shield General Corrosion Rate CDFs 
(Original vs. Corrected for silica scale deposit) 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Ti Data 
Corrected Ti Data 
Figure 3-77. Cumulative Probability Distribution Functions 
for the General Corrosion Rate of the Ti-7 Drip 
Shield Before (Original) and After (Corrected) 
Accounting for Bias Due to Possible Silica 
Scale Deposits

 3-123  
Alloy 22 General Corrosion Rate CDFs w/ Silica Scale Deposit Correction 
2-yr data only; 25, 50, and 75% Variability - 50th 
Uncertainty Quantile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability 
Figure 3-78. The Variability Cumulative Distribution Functions for the 
General Corrosion Rate of the Alloy 22 Waste Package Outer 
Barrier with the Silica-Scale Deposit Correction Using 25%- 
75%, 50%-50%, and 75%-25% Uncertainty and Variability 
Partitioning Ratios and 50th Uncertainty Percentile 
Alloy 22 General Corrosion Rate CDFs w/ SiO2 Scale Deposit Correction 
2-yr data only; 25, 50, and 75% Variability - 25th 
Uncertainty Quantile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability 
Figure 3-79. The Variability Cumulative Distribution Functions 
for the General Corrosion Rate of the Alloy 22 
Waste Package Outer Barrier with the Silica- 
Scale Deposit Correction Using 25%-75%, 50%- 
50%, and 75%-25% Uncertainty and Variability 
Partitioning Ratios and 25th Uncertainty 
Percentile

 3-124  
Alloy 22 General Corrosion Rate CDFs w/ SiO2 Scale Deposit Correction 
2-yr data only; 25, 50, and 75% Variability - 75th 
Uncertainty Quantile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability 
Figure 3-80. The Variability Cumulative Distribution Functions 
for the General Corrosion Rate of the Alloy 22 
Waste Package Outer Barrier with the Silica- 
Scale Deposit Correction Using 25%-75%, 50%- 
50%, and 75%-25% Uncertainty and Variability 
Partitioning Ratios and 75th Uncertainty 
Percentile 
Ti-7 General Corrosion Rate CDFs w/ Silica Scale Deposit Correction 
25, 50, and 75% Variability - 50th 
Uncertainty Quantile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability 
Figure 3-81. The Variability Cumulative Distribution Functions 
for the General Corrosion Rate of the Ti-7 Drip 
Shield with the Silica-Scale Deposit Correction 
Using 25%-75%, 50%-50%, and 75%-25% 
Uncertainty and Variability Partitioning Ratios and 
50th Uncertainty Percentile

 3-125  
Ti-7 General Corrosion Rate CDFs w/ SiO2 Scale Deposit Correction 
25, 50, and 75% Variability - 25th 
Uncertainty Quantile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability 
Figure 3-82. The Variability Cumulative Distribution Functions 
for the General Corrosion Rate of the Ti-7 Drip 
Shield with the Silica-Scale Deposit Correction 
Using 25%-75%, 50%-50%, and 75%-25% 
Uncertainty and Variability Partitioning Ratios and 
25th Uncertainty Percentile 
Ti-7 General Corrosion Rate CDFs w/ SiO2 Scale Deposit Correction 
25, 50, and 75% Variability - 75th 
Uncertainty Quantile 
General Corrosion Rate (mm/yr) 
10-6 10-5 10-4 10-3 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Original Distribution 
75% Variability 
50% Variability 
25% Variability 
Figure 3-83. The Variability Cumulative Distribution Functions 
for the General Corrosion Rate of the Ti-7 Drip 
Shield with the Silica-Scale Deposit Correction 
Using 25%-75%, 50%-50%, and 75%-25% 
Uncertainty and Variability Partitioning Ratios and 
75th Uncertainty Percentile

 3-126  
3.2.3 Abstraction of Localized Corrosion Models for Waste Package Outer Barrier and 
Drip Shield 
This section discusses the approaches and assumptions used in the abstraction of localized 
corrosion (LC) models for waste package outer barrier (WPOB) and drip shield (DS), and the 
abstraction results. 
3.2.3.1 Approaches and Assumptions 
The model abstractions are to develop two localized corrosion initiation criteria; one representing 
the LC initiation criterion for the WPOB (Alloy 22) and the other for the LC initiation criterion 
for the DS (Titanium Grade 7). As discussed in Section 3.1.6.3, cyclic polarization (CP) 
measurements were made in several synthetic concentrated J-13 waters. For each CP curve 
obtained, the critical potential for localized corrosion initiation, Ecrit, and the corrosion potential, 
Ecorr, were determined. The potential difference between Ecrit and Ecorr (i.e., .E = Ecrit  Ecorr) 
was then fit to a function of relevant exposure parameters. Consistent with the discussion in 
Section 3.6.1.3, localized corrosion should initiate if .E < 0 (i.e., Ecrit < Ecorr). Details of the 
abstraction approaches are described in CRWMS M&O (2000n). 
A set of assumptions were employed in the model abstraction. Key assumptions are described 
below. 
 Threshold Potential 1 (see Figures 3-40 through 3-48) was used as the critical potential 
above which localized corrosion can initiate. This is the lowest (most conservative) of 
the various critical thresholds discussed in Section 3.1.6.3. 
 For both the WPOB (Alloy 22) and the DS (Titanium Grade 7), it was assumed that .E 
varied linearly with relevant exposure parameters. 
Detailed discussion of the assumptions employed in the model abstraction is given in CRWMS 
M&O (2000n). 
3.2.3.2 Localized Corrosion Model for Waste Package Outer Barrier 
The CP data for the WPOB (Alloy 22) was first used to fit .E to a function of absolute 
temperature, T, the base 10 logarithm of the chloride ion concentration (mol/L), solution pH, and 
solution pH2, i.e., 
. . +  +  +  +  + = - 2 
4 3 2 1 0 pH b pH b ) Cl log( b T b b E (Eq. 3-38) 
however, it was found that .E exhibited little dependence on absolute temperature or the base 10 
logarithm of the chloride ion concentration. Therefore, the CP data for the WPOB (Alloy 22) 
was used to fit .E to a function of solution pH and pH2 only i.e.,
e . +  +  + = 2 
2 1 0 pH c pH c c E (Eq. 3-39)

 3-127  
Linear regression gave the following estimates for the parameters in Equation (3-39): co = 1160, 
c1 = -193 and c2 = 12.0. The covariance matrix (s) and correlation matrix (C) resulting from the 
fitting procedure were determined to be: 
. . . 
.
. 
. . . 
.
. 
- 
- - 
- 
= 
. . . 
.
. 
. . . 
.
. 
- 
- - 
- 
= 
1 982 . 0 835 . 0 
982 . 0 1 915 . 0 
835 . 0 915 . 0 1 
C 
69 . 1 4 . 24 4 . 64 
4 . 24 364 1040 
4 . 64 1040 3530 
s (Eq. 3-40) 
and the variance of e determined from the linear regression fitting procedure is 4670. 
Figure 3-84 shows a plot of how the median potential difference .E given by Equation (3-39) 
varies with pH. Also shown are the 3s and 4s confidence intervals. 
pH 
2 4 6 8 10 12 14 
.E 
mV 
0 
200 
400 
600 
800 
1000 
1200 
1400 
.E 
.E 3s 
.E 4s 
Experimental Data 
Source: CRWMS, M&O 2000n, Section 6.3.1 
Figure 3-84. Plot of .E vs. pH for Alloy 22 from Equation (3-39) 
Showing the 3s and 4s Confidence Intervals and the 
CP Experimental Data 
The abstraction results in Figure 3-84 shows that localized corrosion of Alloy 22 can not initiate 
at any pH based on the 4s confidence interval and based on extrapolation of the repositoryrelevant 
experimental data used in the analysis. 
3.2.3.3 Localized Corrosion Model for Drip Shield 
The CP data for the DS (Titanium Grade 7) was first used to fit .E to a function of absolute 
temperature, T, the base 10 logarithm of the chloride ion concentration (mol/L), and solution pH, 
i.e., 
. . +  +  +  + = - pH d ) Cl log( d T d d E 3 2 1 0 (Eq. 3-41)

 3-128  
however, it was found that .E exhibited little dependence on absolute temperature or the base 10 
logarithm of the chloride ion concentration. Therefore, the CP data for the DS (Titanium 
Grade 7) .E to a function of solution pH only i.e., 
e . +  + = pH f f E 1 0 (Eq. 3-42) 
Linear regression gave the following estimates for the parameters in Equation (3-46): fo = 1670 
and f1 = -52.2. The covariance matrix (s) and correlation matrix (C) resulting from the fitting 
procedure was determined to be: 
.. 
. 
.. 
.
- 
- 
= .. 
. 
.. 
.
- 
- 
= 
1 904 . 0 
904 . 0 1 
C 
9 . 31 230 
230 2040 
s (Eq. 3-43) 
and the variance of e determined from the linear regression fitting procedure is 1080. 
Figure 3-85 shows a plot of how the median potential difference .E given by Equation (3-42) 
varies with pH. Also shown are the 3s and 4s confidence intervals. 
pH 
2 4 6 8 10 12 14 
.E 
mV 
400 
600 
800 
1000 
1200 
1400 
1600 
1800 
2000 
2200 
.E 
.E 3s 
.E 4s 
Experimental Data 
Source: CRWMS, M&O 2000n, Section 6.4.1 
Figure 3-85. Plot of .E vs. pH for Titanium Grade 7 from 
Equation (3-42) Showing the 3s and 4s 
Confidence Intervals and the CP Experimental Data 
The abstraction results shown in Figure 3-85 indicate that localized corrosion of Titanium 
Grade 7 can not initiate even at a pH of 14 based on the 3s and 4s confidence intervals based on 
extrapolation of the repository-relevant experimental data used in this analysis. 
3.2.4 Abstraction of Slip Dissolution Stress Corrosion Cracking Model 
In the current waste package degradation analysis, two alternative stress corrosion cracking 
(SCC) models, the slip dissolution (or film rupture) model and the threshold stress intensity

 3-129  
factor (KISCC) model, are considered (CRWMS M&O 2000f, Section 3.2). In the threshold stress 
intensity factor model, the threshold stress intensity factor (KISCC) is used to determine when 
SCC will occur. Provided that an initial flaw and corrosive environment is present, a SCC 
failure will occur when the applied stress intensity factor KI is greater than or equal to the 
threshold stress intensity factor KISCC (i.e., KI = KISCC). The slip dissolution model assumes that 
incipient cracks or defects grow continuously when the oxidation reaction that occurs at the 
crack tip ruptures the protective film via an applied strain in the underlying matrix. The rate at 
which the crack grows is a function of the crack tip strain rate and environmental and material 
chemistries. The theory and fundamentals of the SCC models are described in detail in the 
process model analysis (CRWMS M&O 2000f, Sections 6.3 and 6.4). As recommended in the 
process model analysis (CRWMS M&O 2000f, Section 6.4), the slip dissolution model was used 
to access the SCC degradation of the waste package outer barrier (WPOB) (also see 
Section 3.1.7.2). This section discusses the approach and methodology used in the abstraction 
development for the slip dissolution model and the associated parameters. 
3.2.4.1 Abstraction Approach and Methodology 
The purpose of this analysis is to develop abstractions for the parameters that are associated with 
the slip dissolution model. In the waste package degradation (WAPDEG) analysis this model is 
employed to calculate the growth rate of cracks initiated by stress corrosion cracking (SCC). 
The theory and fundamentals of the model are discussed in detail in the process model analysis 
(CRWMS M&O 2000f, Section 6). The waste package degradation analysis employs a 
stochastic approach to model the initiation and propagation of SCC cracks. The major efforts in 
the abstraction discussed in this section are to develop an approach to represent the uncertainty 
and variability associated with the SCC initiation and crack propagation processes, and to 
implement them in the waste package degradation analysis. As discussed in the following 
section, the associated parameters in the model include two model parameters (A and n), stress 
intensity factor (KI), threshold stress, and incipient crack density and size. The nominal-case 
SCC analysis also includes pre-existing manufacturing defects in the closure-lid welds. 
Abstractions for the manufacturing defects and the residual stress and stress intensity factor in 
the closure-lid welds are discussed in Sections 3.2.5 and 3.2.6, respectively. The current 
abstractions for the model parameters (A and n), threshold stress, and incipient cracks expand the 
process model analysis results to represent and quantify the uncertainty and variability associated 
with the parameters (CRWMS M&O 2000f). The abstraction assumes that statistical sampling 
of the associated model parameter values within their probable range capture the effects of the 
complex processes affecting the SCC crack initiation and growth rate. 
3.2.4.2 Crack Growth Rate Model 
The crack growth rate in the slip dissolution model is determined by the following expression in 
Section 3.1.7.8.2 (CRWMS M&O 2000f, Section 6.4.4). 
( )n 
I t K A V = (Eq. 3-44) 
where V is the crack growth rate in mm/s, and KI is the stress intensity factor in MPa(m)1/2. 
Parameters, n and A , in the above equation are expressed as follows (CRWMS M&O 2000f, 
Section 6.4.4; also see Section 3.1.7.8.2).

 3-130  
( )n 14 6 . 3 2 10 x 1 . 4 n 10 x 8 . 7 A - - = (Eq. 3-45) 
n n 4 = (Eq. 3-46) 
Parameter n (referred to also as the repassivation potential slope) is a function of 
environmental and materials parameters such as solution conductivity, corrosion potential, and 
alloy composition (i.e., chromium depletion in the grain boundary) (CRWMS M&O 2000f, 
Section 6.4.2). The variability in the crack growth rate may be represented with potentially 
varying exposure conditions (n) and stress intensity factor (KI) among waste packages and also 
on different locations over a single waste package. However, due to a lack of data, n is 
considered independent of exposure conditions and alloy composition. In the waste package 
degradation analysis described in the following section (Section 3.2.5), the value of the 
parameter is sampled from a range (i.e., from 0.75 to 0.84 as discussed in the next paragraph). 
Impact of this approach needs to be assessed as additional data and analysis is developed. 
However, the effect of n on the failure time by SCC is less than the stress intensity factor (KI) 
(see Section 3.2.4.5 below). As discussed in Section 3.2.5, the stress intensity factor profile (as a 
function of depth in the closure-lid weld) varies along the circumference of the closure-lid welds, 
but the variability is not significant. It is assumed that there is no variability in the profile among 
waste packages. 
The uncertainty associated with the crack growth rate is represented with the uncertainties in the 
model parameters, i.e., n and KI. As discussed in Section 3.2.5, the uncertainties associated with 
the KI profiles are represented with normal distribution bounded at three standard deviations 
from the mean profile. Because of a lack of data, the uncertainty associated with n is coarsely 
defined: uniform distribution between the lower bound 0.75 and the upper bound 0.84 (CRWMS 
M&O 2000f, Section 6.4.4). The lower bound value for n will be verified from the on-going 
work (CRWMS M&O 2000f, Section 3.2). 
3.2.4.3 Threshold Stress for Crack Growth Initiation 
The threshold stress is defined as the minimum stress at which cracks start growing at a rate 
determined by Equation (3-47). The threshold stress may be represented as a fraction of the 
yield strength of the material, which varies with temperature (CRWMS M&O 1999f, p. 33). 
Because the upper limit of the temperature at which corrosion initiates (or stable liquid water can 
form) is 120.59 C (CRWMS M&O 2000a, Section 4.1.8, Table 7), the yield strength of Alloy 
22 at 125 C is used. The yield strength was calculated by linearly interpolating the yield 
strengths at 93 C (338 MPa) and 204 C (283 MPa) (CRWMS M&O 1999f, p. 33). The 
resulting yield strength used for the threshold stress is 322.3 MPa (46.72 ksi). Although the 
yield strength increases as temperature decreases, the value at 125 C is used for all the waste 
package temperatures after corrosion initiates in the repository. This is because there is only a 
small change in the yield strength of Alloy 22 from 125 C to the ambient temperature. 
Potentially marginal variability in the yield strength and thus the threshold stress are ignored in 
the current analysis. 
As suggested in the process model analysis (CRWMS M&O 2000f, Section 6.5.2), the 
uncertainty in the threshold stress is conservatively represented as 20 to 30 percent of the yield

 3-131  
strength, and uniform distribution is assumed for the uncertainty range. Thus, the resulting 
uncertainty range for the threshold stress is 64.46 to 96.60 MPa with the assumed uniform 
distribution between the two values. In the SCC analysis of waste package closure-lid weld with 
WAPDEG, for each realization (or each run), the threshold stress is sampled from the range with 
the assumed uniform distribution, and the sampled threshold stress is used for all the closure-lid 
weld patches of the waste packages under consideration (CRWMS M&O 2000g, Section 6.3.13). 
3.2.4.4 Incipient Cracks and Manufacturing Defects 
In the SCC process the crack initiation is associated with microscopic crack formation at 
localized corrosion or mechanical defect sites that are associated with pitting, intergranular 
attack, scratches, weld defects, planar dislocations, secondary phase precipitates, or design 
notches (CRWMS M&O 2000f, Section 6.4.2). The crack growth rate increases as the 
microscopic cracks coalesce, and approaches a steady-state value when a crack can be detected 
(CRWMS M&O 2000f, Section 6.4.1). The current analysis assumes that a crack depth range of 
about 20 m to 50 m represents the minimum crack depth for which the Slip Dissolution model 
can be applied. Those cracks are referred to as incipient cracks. Exponential distribution with 
a maximum size of 50 m and a medium size of 20 m was suggested for the incipient crack 
size distribution (CRWMS M&O 2000f, Section 6.5.2). Because the effect of differing incipient 
crack sizes within the suggested range on crack growth rate is much less than the model 
parameters (n and KI), the maximum crack size (50 m) is used for all the incipient cracks 
considered in the SCC analysis. 
The SCC analysis using the slip dissolution model also considers manufacturing defects in the 
closure-lid welds. As discussed in Section 3.2.6, in the WAPDEG analysis, the size of the 
manufacturing defects are sampled for the closure-lid weld patches, and the sampled defect flaws 
are included in the analysis with the slip dissolution model. Because manufacturing defects are 
much larger than the incipient cracks, the closure-lid weld patches with manufacturing defects 
are likely to fail initially by SCC (CRWMS M&O 2000g, Section 6.4). 
3.2.4.5 Slip Dissolution Model Analysis 
Bounding analyses were performed to examine the model responses for the SCC failure time of 
the outer lid (25-mm thick) and inner lid (10-mm thick) as a function of the model parameters (n 
and KI). The analyses considered two bounding values (0.75 and 0.84) for n (CRWMS M&O 
2000f, Sections 3.2 and 6.4.4) and a range of values for the stress intensity factor that is expected 
in the closure-lid welds (CRWMS M&O 2000f, Attachment I). The threshold stress for crack 
growth initiation and pre-existing manufacturing defect were not considered in this bounding 
analysis. The results are shown in Figure 3-86. As shown in the figure, the stress intensity 
factor is the dominant parameter in the model, and the time to failure by SCC increases 
exponentially as the stress intensity factor decreases. The failure time by SCC is less than 100 
years for the stress intensity factors greater than 20 MPa(m). The failure time increases to well 
above 1,000 years if the stress intensity factor is kept below 6 MPa(m). The analysis 
demonstrates that, once a SCC crack initiates, it penetrates the closure-lid thickness fast. It also 
demonstrates importance of stress mitigation in the closure-lid welds to avoid premature failures 
of waste packages by SCC.

 3-132  
Bounding Calculations for Time to Failure by Slip Dissolution Model 
(v = A * KI
4n ; A = 7.8E-2*n3.6(4.1E-14)n) 
KI (MPa*m) 
0 10 20 30 40 50 
Time to Failure (years) 
100 
101 
102 
103 
104 
105 n = 0.84, 25 mm 
n = 0.75, 25 mm 
n = 0.84, 10 mm 
n = 0.75, 10 mm 
Source: CRWMS, M&O 2000j, Section 6.5 
Figure 3-86. Bounding Calculations for the Model Responses for the Time to 
Failure of the Outer and Inner Closure Lids by SCC Calculated 
with the Slip Dissolution Model Using the Bounding Values for 
Parameter n for a Range of the Stress Intensity Factor Values 
3.2.5 Abstraction of Stress and Stress Intensity Factor Profile in Waste Package Closure 
Welds 
This section discusses the approaches and assumptions used to develop abstracted models for stress 
and stress intensity factor profiles as a function of depth in the closure-lid welds of WPOB. Two 
alternative model abstractions are discussed. These are referred to as the realistic-case 
abstraction and the alternative conservative abstraction, respectively. The resulting abstracted 
models represent uncertainty and variability of the profiles and used as input to the SCC analysis in 
the closure lid welds using the integrated WAPDEG (CRWMS M&O 2000g). 
3.2.5.1 Approaches and Assumptions used in Realistic-Case Abstraction 
The WPOB has dual closure lids (referred to as the outer (25-mm thick) and inner lid (10-mm thick), 
respectively) (see Figure 1-1). The process model analyses calculated the stress and stress intensity 
factor profiles along the circumference of the welds for each of the closure lids (CRWMS M&O 
2000f). The results were analyzed to develop abstracted models to represent uncertainty and 
variability of the profiles in the closure-lid welds. In addition, the abstraction was to present the 
profiles in a format that is suitable for implementation in the integrated WP degradation model 
(WAPDEG). Details of the abstraction approaches are discussed elsewhere (CRWMS M&O 2000j).

 3-133  
Major assumptions employed in the realistic-case abstraction are described below. 
 The hoop stress (and the corresponding stress intensity factor for radial cracks) is the 
prevailing stress in the closure-lid welds that could lead to SCC through-wall cracks in the 
closure-lid weld of WPs. Thus, the current abstraction is limited to the profiles for the hoop 
stress and corresponding stress intensity factor for radial crack. 
 The hoop stress (and corresponding stress intensity factor profiles for radial cracks) in the 
inner lid welds are for a plane that is inclined at about 53 degrees from a plane normal to the 
outer surface of the inner lid. Because the SCC analysis in the integrated WAPDEG model 
assumes that cracks propagate normal to the lid surface, the profiles were projected to a 
plane normal to the outer surface of the lid. The crack orientation used in the abstraction is 
in the radial direction, which is normal to the hoop stress. As discussed above, the radial 
crack is considered in the abstraction because the hoop stress was found to be the dominant 
stress in the closure-lid welds. The hoop stress is likely to be close to the first principal (or 
maximum) stress. It is assumed the SCC analysis with the projected profiles properly 
represents the hoop stress and stress intensity factor profiles for the inclined plane. 
 The hoop stress and corresponding stress intensity factor profiles as a function of depth in 
the closure lid welds from the process model analyses (CRWMS M&O 2000f) represent the 
mean profiles. 
 The hoop stress and stress intensity factor profiles vary along the circumference of the 
closure lid welds, and those represent the variability in the profiles on a given waste 
package. The angular variation in the hoop stress, .t(x), where x is the thickness, is 
given by, 
( ) ( ) ( ) ( )) cos 1 ( 17.236892 x , x s t . s . s -  - = (Eq. 3-47) 
 where . is angle around the circumference of the waste package closure-lid welds (. = 
0 point arbitrarily chosen). .t(x) is the mean hoop stress defined in Section 6.3.1 of 
CRWMS M&O 2000j. 
 It is assumed that the same degree of the profile variability is applied equally to all the 
waste packages in the repository, and there is no variability in the profiles among waste 
packages. 
 The uncertainty range in the hoop stress (and corresponding stress intensity factor 
profiles based on the hoop stress) is bounded between  5% of the yield strength and 
centered around the mean hoop stress profile. This uncertainty range is sampled through 
the use of a random variable, z, sampled from standard normal distribution bounded 
within three standard deviations ( 3 s.d.s). The hoop stress is multiplied by an 
uncertain scaling factor, rscale(.,z) of the form, 
( )
( ). s 
. s 
. 
, Thck 
3 
F YS 
z , Thck 
) z , ( rscale 
t 
t .. 
. .. 
.   + 
= (Eq. 3-48)

 3-134  
where Thck is the lid thickness, and F is the uncertainty range bound (0.05 or 5%). 
 As a crack propagates in the closure lid welds or the weld is thinned by GC, the residual 
stresses in the welds may re-distribute in such a way that the SCC initiation and crack 
growth are mitigated (CRWMS M&O 2000f). Such stress re-distribution or relaxation is 
not considered in the current abstraction. This is a conservative approach. 
3.2.5.2 Realistic-Case Abstraction Results for Stress and Stress Intensity Factor Profiles 
The abstraction results for the uncertainty range of the hoop stress as a function of depth in the outer 
closure lid welds (25-mm thick) are given in Figure 3-87. The stress profiles are at a reference 
location (0 angle) on the circumference of the lid welds. As will be shown later in Figure 3-89, the 
reference location on the lid weld circumference was selected in such a way that it has the highest 
hoop stress. The figure shows that the hoop stress in the outer lid weld is compressive at the surface 
and becomes tensile at a depth of about 8 mm. The uncertainty becomes larger with the weld depth. 
This is because the stress uncertainty is obtained by multiplying the mean stress by the 
uncertainty scaling factor in Equation (3-49) and the mean stress increases with the depth. The 
corresponding stress intensity factor profiles as a function of radial crack depth are shown in 
Figure 3-88. The stress intensity factor is negative at the surface and becomes positive at a depth of 
about 12 mm, thus no SCC crack will initiate until the 12-mm thick layer is removed. As with the 
hoop stress, the uncertainty of the stress intensity factor increases with the weld depth. Figures 3-89 
and 3-90 show respectively the hoop stress as a function of depth and the corresponding stress 
intensity factor as a function of radial crack depth, both at 0, 90, and 180 angle along the 
circumference of the outer-lid welds for a given WP. The reference location designated at 0 angle 
has the largest hoop stress, and the location at 180 angle has the least hoop stress. As shown in the 
figures, the variability of the both profiles along the weld circumference in a WP is minor. 
The abstraction results for the uncertainty range of the hoop stress as a function of the projected 
depth in the inner closure lid welds (10-mm thick) are given in Figure 3-91. The stress profiles are at 
a reference location (0 angle) on the circumference of the lid welds. The hoop stress in the inner lid 
welds is compressive at the surface, transits to tensile state at a projected depth of about 2-mm, and 
then back to compressive state at a projected depth of about 8.5-mm. The uncertainty in the profiles 
is larger for the tensile region in the weld depth. The corresponding stress intensity factor profiles as 
a function of the projected radial crack depth are shown in Figure 3-92. The stress intensity factor is 
negative at the surface and becomes positive at a projected depth of about 5 mm, thus no SCC crack 
will initiate until the (projected) 5-mm thick layer is removed. The uncertainty of the stress intensity 
factor increases slightly with the weld depth beyond the depth it becomes positive. Figures 3-93 and 
3-94 show respectively the hoop stress as a function of the projected depth and the corresponding 
stress intensity factor as a function of the projected radial crack depth, both at 0, 90, and 180 angle 
along the circumference of the inner-lid welds for a given WP. As shown in the figures, the 
variability of the both profiles along the weld circumference in a WP is minor. 
3.2.5.3 Alternative Conservative Abstraction for Stress and Stress Intensity Factor 
Profiles 
The alternative conservative abstraction uses the same assumptions as the realistic-case 
abstraction with the exception that:

 3-135  
 The uncertainty range in the hoop stress (and corresponding stress intensity factor 
profiles based on the hoop stress) is bounded between  30% of the yield strength (YS) 
and centered around the mean hoop stress profile. This uncertainty range is sampled 
through the use of a random variable, z, sampled from a triangular distribution with a 
minimum of 3, a maximum of 3 and a most likely value of zero. An uncertain factor 
( .S) is added to the hoop stress of the form, 
.. 
. .. 
.   = 
3 
F YS 
z S . (Eq. 3-49) 
where F is the uncertainty range bound (0.30 or 30%). 
The abstraction results for the uncertainty range of the hoop stress as a function of depth in the 
outer closure lid welds (25-mm thick) are given in Figure 3-95. The stress profiles are at a 
reference location (0 angle) on the circumference of the lid welds. The figure shows that the 
hoop stress in the outer lid welds is compressive at the surface and becomes tensile at a depth 
between 6 and 10 mm depending on the level of uncertainty used. The corresponding stress 
intensity factor profiles as a function of radial crack depth are shown in Figure 3-96. The stress 
intensity factor is negative at the surface and becomes positive at a depth between 3 and about 20 
mm depending on the level of uncertainty used. No SCC crack growth will initiate until this 
layer is removed. 
The abstraction results for the uncertainty range of the hoop stress as a function of the projected 
depth in the inner closure lid welds (10-mm thick) are given in Figure 3-97. The stress profiles 
are at a reference location (0 angle) on the circumference of the lid welds. The hoop stress in 
the inner lid welds is compressive at the surface, transitions to tensile state at a projected depth 
between 1 and 2 mm, and then back to compressive state at a projected depth between 6.8 and 
9.8 mm. The corresponding stress intensity factor profiles as a function of the projected radial 
crack depth are shown in Figure 3-98. The stress intensity factor is negative at the surface and 
becomes positive at a projected depth of about 1.3 mm to 3mm, thus no SCC crack will initiate 
until this layer is removed. The uncertainty of the stress intensity factor increases slightly with 
the weld depth beyond the depth it becomes positive. Overall, the increased range of uncertainty 
of the input parameters to the stress corrosion cracking model should result in an increase in the 
range of SCC crack failure times. 
3.2.6 Abstraction for Manufacturing Defects in Waste Package Closure Welds 
This section describes the approaches and assumptions employed in developing abstracted 
models for the probability and size of manufacturing defects in the waste package closure-lid 
welds. The abstraction results and their implementation in the waste package degradation 
(WAPDEG) model for stress corrosion cracking (SCC) analysis are discussed in this section. 
3.2.6.1 Approaches and Assumptions 
The analyses are to develop abstracted models representing the frequency of occurrence and size 
of defects potentially found in waste package closure-lid welds. Flaw density and flaw size 
distributions are obtained from other analyses (see Section 3.1.2; CRWMS M&O 2000m). The

 3-136  
flaw density is used as the parameter for a Poisson distribution used to represent the frequency of 
occurrence of flaws in a given length of closure weld. The flaw sizes are given as a probability 
density function on each closure-lid weld. 
Major assumptions employed in the abstraction are described below. Further details of the 
assumptions used in the abstraction analyses are discussed in CRWMS M&O (2000k). 
 Only surface-breaking flaws are considered. 
 Flaws occur randomly and its occurrence is represented by a Poisson distribution as 
suggested by the process model analysis (CRWMS M&O 2000m). 
 The mean flaw density (Poisson distribution parameter) of the closure weld is from 
CRWMS M&O (2000m) (0.6839 flaws/meter of one-inch thick weld). 
 The fraction of surface breaking flaws is uniformly distributed between the minimum 
(0.0013) and maximum (0.0049) fractions used to determine the average fraction quoted 
in CRWMS M&O (2000m). The use of the uniform distribution is a reasonable 
representation of the uncertainty in expressing this value. 
 Pre-inspection flaw sizes are log-normally distributed, with distribution parameters 
(dependent on the weld thickness) as given in CRWMS M&O (2000m). 
 The probability of non-detection is given as a function of flaw size as provided in 
CRWMS M&O (2000m). The model is dependent on the detection threshold (p), the 
location parameter (b), and the scale parameter ( .). The location parameter (b) and the 
scale parameter ( .) are taken to be uncertain with a uniform distribution. The ranges for 
these distributions are determined from the values identified in the literature as quoted in 
CRWMS M&O (2000m). This is reasonable, as the manufacturing and detection 
processes for welds on the waste container are not specified to date. The best that may 
be modeled at this time are values based on similar industrial manufacturing practices as 
reported in CRWMS M&O (2000m). 
 Results of the residual stress analyses for the closure-lid welds have indicated that the 
hoop stress (and the radial crack driven by the hoop stress) is the dominant stress that 
could lead to SCC through-wall cracks in the closure-lid weld (CRWMS M&O 2000f). 
As a conservative approach, all the surface-breaking manufacturing defects are 
considered radial cracks and assumed to have a semi-circular shape. 
3.2.6.2 Abstraction Results for the Probability and Size of Defect Flaws 
Initial (pre-inspection) mean flaw densities and flaw sizes used in the analyses for this 
calculation were from CRWMS M&O (2000m). Calculation of the outer surface-breaking mean 
flaw density begins with the base mean flaw density of 0.6839 flaws/meter of weld for a one inch 
thick stainless steel Tungsten Inert Gas weld (this density was measured from an actual weld 
performed under shop conditions) subject to radiographic (RT) and dye-penetrant (PT) tests 
(CRWMS M&O 2000m). To convert this value to a flaw density for an uninspected weld, the

 3-137  
base flaw density is increased by the sum of the flaw reduction factors provided for the RT and 
PT tests. The adjustment for the RT exam increases the total flaw density by a factor of 12.8 
while the PT exam, which detects only surface-breaking flaws, increases the density of only the 
surface-breaking flaws by a factor of 31.4 (CRWMS M&O 2000m). Next the effect of weld 
thickness on flaw density is used to adjust for the actual weld thickness on the closure weld. For 
the 25-mm thick closure weld, the flaw reduction factor (R) is 97.3% (865 divided by 889) 
(CRWMS M&O 2000m). Multiplying this result by this circumference of the closure-lid weld 
results in the flaw density per closure weld (or per waste package). A final multiplication by the 
fraction of surface breaking flaws results in the final mean flaw density of surface breaking flaws 
per waste-package closure weld. 
The resulting cumulative probability for defect flaws for the outer (25-mm thick) and inner 
(10-mm thick) closure-lid welds are shown in Figure 3-99. Each of the cumulative probabilities 
in the figure is from 100 realizations with random sampling of the location parameter (b) and the 
scale parameter ( .) and represent the actual defect probability used in the waste package SCC 
analysis (CRWMS M&O 2000g). The abstraction results show that at 100th percentile about 
18% of waste packages have at least one defect for both the outer and inner closure-lids. At 50th 
percentile, about 8% of waste packages have at least one defect in the outer closure-lid, and 
about 7% of waste packages have at least one defect in the inner closure-lid. Figure 3-100 shows 
several probability density functions for defect sizes in the closure lid welds for various 
combinations of values for the defect location parameter (b) and the scale parameter ( .). The 
same probability density functions are used for both the outer and inner lid welds. As shown in 
Figure 3-100, the size of most defects is between 1 mm and 3 mm. A few defects could have the 
size up to 4 mm. 
3.2.6.3 Implementation of Closure Weld Flaw Abstraction Results in Waste Package 
Degradation Analysis 
The number of flaws that appear on a patch is sampled stochastically as a Poisson random 
variable. For each flaw that occurs, a flaw size is randomly assigned to it by sampling from the 
calculated flaw size cumulative distribution function. This flaws location and size are then used 
in the SCC analysis. The abstracted results are then input to the waste package degradation 
model (WAPDEG) to analyze its effect on waste package performance (CRWMS M&O 2000g). 
The approach used in this abstraction is that, as these distributions accommodate the variability 
observed in the occurrence, frequency and size of flaws, some of the parameters that determine 
these distributions need to be treated as uncertain. The instances of where uncertainty is 
included are for: (1) the flaw detection distributions (parameters b and .) and (2) the fraction of 
surface breaking flaws. The parameters are treated as follows. The b and . parameters of the 
detection distribution are allowed to uniformly range between 1.6 to 5 mm and 1 to 3, 
respectively. The fraction of surface breaking flaws in CRWMS M&O (2000m) is the average 
of three observations (0.13%, 0.40%, and 0.49%) and is 0.34%. Instead of using the average 
value of 0.34%, the fraction of surface breaking flaws should be allowed to uniformly range 
from 0.13 to 0.49%. For a given realization of WAPDEG analysis, the model parameters 
(defect location parameter (b), defect scale parameter ( .), and fraction of surface-breaking defect 
fraction) are sampled independently to estimate the probability of a defect occurrence. Then, as 
discussed above, the number of defects that appear on a patch is sampled stochastically as a

 3-138  
Poisson random variable. Sensitivity analyses with the proposed distributions of the model 
parameters are needed to analyze the affect of not knowing the correct (deterministic) value of 
the parameters. 
3.2.6.4 Alternative Conservative Abstraction for Defect Probability and Size 
Because, as general corrosion proceeds, embedded defects can become surface breaking defects, 
consideration of pre-existing surface breaking defects only may not be conservative. As an 
alternative conservative abstraction, both surface breaking defects and embedded defects within 
the outer  region of the weld surface are considered. Three observations (34.81%, 36.17%, and 
36.32%) for the sum of the fraction of surface breaking flaws and the fraction of flaws embedded 
within the outer  region of the surface (DTN: MO9910SPAFWPWF.001) are used in the 
alternative conservative abstraction. It is assumed that the flaw fraction is uniformly distributed 
between the minimum (0.3481) and maximum (0.3632) fractions (DTN: 
MO9910SPAFWPWF.001). The use of the uniform distribution is a reasonable representation of 
the uncertainty in expressing this value. The same process as for the case with the surface 
breaking defect only (Sections 3.2.6.2 and 3.2.6.3) was performed to develop the alternative 
abstraction, except for the increased flaw fraction range. 
The cumulative probability for the average number of defects per waste package in the welds of 
the outer (25-mm thick) and inner (10-mm thick) lids of waste package outer barrier, considering 
both surface breaking and flaws embedded within the outer  of the surface, is presented in 
Figure 3-101. As shown in the figure, with the alternative abstraction, almost 100% of waste 
packages have at least one defect. At the 50th percentile the outer-lid weld has an average of 18 
defects per waste package, and the value for the inner-lid weld is about 15 defects per waste 
package. An upper bound value for the outer-lid and inner-lid weld is about 40 defects per waste 
package. The same conditional probability density functions of defect sizes in Figure 3-100 are 
used with the current alternative abstraction. Because the number of defects per waste package 
is increased by a factor of about 40, there would be a fairly good probability to sample large 
defects. A few defects could have the size as large as 5 mm or larger. 
Use of the current alternative abstraction in the SCC analysis described in Section 3.2.5 is highly 
conservative because most embedded defects would be oriented that would not lead to radial 
cracks. The SCC analysis considers the hoop stress is the dominant stress in the close-lid welds 
and drives radial crack propagation. 
3.2.7 Drip Shield and Waste Package Degradation Analyses 
This section reports WAPDEG analysis results for the waste package (WP) and drip shield (DS) 
degradation. The conceptual model and model logic flow employed in the WAPDEG model are 
described in Section 3.2.1. The section includes the results for two cases that are likely to 
represent the end-members of potential range of major corrosion model parameter values that 
could affect long-term performance of waste package and drip shield in the repository. These 
cases are referred to as (1) realistic case and (2) alternative conservative case. 
The WAPDEG model, an integrated model used for WP and DS degradation analysis, is based 
on a stochastic simulation approach and provides a description of waste package degradation,

 3-139  
which occurs as a function of time and repository location for specific design and thermalhydrologic 
modeling assumptions. The corrosion modes that were included in the analyses are: 
 Humid-air phase general corrosion of drip shield 
 Aqueous phase general corrosion of drip shield 
 Localized (pitting and crevice) corrosion of drip shield 
 Humid-air phase general corrosion of waste package outer barrier 
 Aqueous phase general corrosion of waste package outer barrier 
 Localized (pitting and crevice) corrosion of waste package outer barrier 
 Stress corrosion cracking (SCC) of closure-lid welds of waste package outer barrier. 
In addition, the following corrosion parameters were abstracted and included in the analyses: 
 Relative humidity threshold for corrosion initiation of drip shield and waste package 
outer barrier 
 Corrosion potential-based threshold for localized corrosion initiation of drip shield and 
waste package outer barrier 
 Probability of the occurrence and size of manufacturing defects in closure-lid welds of 
waste package outer barrier 
 Stress and stress intensity factor profiles in the closure-lid welds of waste package outer 
barrier incorporating stress mitigation techniques 
 Threshold stress intensity factor (KISCC) for waste package outer barrier used with the 
threshold stress intensity factor model 
 Threshold stress for the initiation of SCC crack growth for waste package outer barrier 
used with the slip dissolution model 
 Corrosion enhancement factor for aging and phase instability of waste package outer 
barrier 
 Corrosion enhancement factor for MIC of waste package outer barrier. 
For the SCC analysis of the waste package closure-lid welds in the WAPDEG analysis, the slip 
dissolution model has been adopted over the threshold stress intensity factor model (see 
Section 3.2.4). The threshold stress intensity factor model has also been incorporated in the 
WAPDEG model, and a switch from the slip dissolution model to the threshold stress intensity 
factor model and vice versa can be made with a flag for the model selection. For the SCC 
analysis with the slip dissolution model, the following should be met before initiating a SCC 
crack propagation in a patch: (1) the stress intensity factor (KI) should be positive, and (2) the 
stress state must be greater than or equal to the threshold stress. In the WAPDEG analysis, for 
those patches with a compressive stress zone (or layer) in the outer surface, the compressive 
stress zone is removed by general corrosion, and this delays the application of the slip dissolution

 3-140  
model for the crack propagation rate. The delay time depends on the compressive zone thickness 
and the general corrosion rate sampled for the patch. 
In addition, pre-existing manufacturing defects in a patch are assumed all surface-breaking, and 
grow at the general corrosion rate sampled for the patch. This is based on the modeling 
assumption that the same exposure condition that a patch experiences during a given time step is 
also applicable to the interior of defects in the patch. Growth of the defects at the general 
corrosion rate of the patch is a conservative assumption. Therefore, patches with pre-exisiting 
defects would be subject to SCC earlier than other patches without defect. 
The corrosion enhancement factors for the MIC and aging and phase instability are applied to the 
general corrosion rate of the waste package outer barrier. No MIC and aging and phase 
instability factor is applied to localized corrosion rate because no localized corrosion occurs. 
For the corrosion models and parameters for which data and analyses are available to quantify 
their uncertainty and variability, they were represented explicitly in the WAPDEG analysis. 
Variability in the degradation of the waste packages to be modeled is represented by allocating 
the total variability variance of the individual corrosion models and their parameters to waste 
package-to-waste package variability and to patch-to-patch variability within a single waste 
package. For other corrosion models and parameters that their uncertainty and variability are not 
quantifiable and that the variance in their value is considered representing a mix of the 
uncertainty and variability, the fraction of the total variance to separate each other was treated as 
an uncertain parameter and sampled randomly for each realization. The Gaussian variance 
partitioning techniques was used to separate the uncertainty and variability from the total 
variance (see Section 3.2.2.2 for detailed discussions). 
Because, except the RH threshold for corrosion initiation, temperature and RH do not affect 
significantly waste package and DS degradation, a representative set of T and RH histories were 
used in the current analysis. Also, no separate analysis was conducted for different waste-type 
waste packages (i.e., commercial spent nuclear fuel waste packages, high-level waste wastepackages, 
etc.), which could give rise to varying thermo-hydrologic conditions to the DS and 
waste packages. In addition, the threshold for localized corrosion initiation of DS and waste 
package outer barrier that requires the presence of drips is much higher than the conditions 
expected in the repository. Other corrosion models are not dependent on dripping conditions 
(i.e., drip vs. no-drip). Therefore, no separate analyses were conducted for different dripping 
conditions. The stainless steel inner layer of waste package was not considered in the analysis. 
Details of the approaches and assumptions associated with the analyses are described in the 
supporting report (CRWMS M&O 2000g). 
In the Total System Performance Assessment-Site Recommendation analysis, waste package 
degradation was analyzed with multiple realizations of WAPDEG for the uncertainty analysis of 
the uncertain corrosion parameterseach WAPDEG realization corresponding to a complete 
WAPDEG run to represent the degradation variability for a given number of waste package and 
drip shield pairs. Accordingly, the WAPDEG analysis outputs are reported as a group of 
curves that represent the potential range of the output parameters. The nominal case analysis 
for waste package and DS degradation constitutes 100 realizations of WAPDEG simulation (or 
100 WAPDEG runs) that uses 100 input vectors for uncertain corrosion model parameters and

 3-141  
the simulation parameters that were sampled from their respective range. The major simulation 
parameters used in the analysis are summarized below: 
 Temperature, relative humidity, and contacting solution pH histories in the presence of 
backfill 
 400 waste package and drip shield pairs 
 20-mm thick waste package outer barrier (Alloy 22) (Note: defense waste co-disposal 
waste package and naval fuel waste package have a 25-mm thick outer barrier.) 
 15-mm thick drip shield (Titanium) 
 1000 patches per waste package 
 500 patches per drip shield. 
The WAPDEG analysis results (i.e., waste package and drip shield failure time and number of 
crack, pit and patch penetrations) are reported as a group of degradation profile curves that 
represent the potential range of the output parameters. The analysis results will be presented for 
the upper bound (100th percentile), lower bound (0th percentile), median, mean, and 95th, 75th, 
25th and 5th percentiles as a function of time for the following output parameters: 
 Waste package first breach (or failure) 
 Drip shield first breach (or failure) 
 Waste package first crack penetration 
 Waste package first patch penetration. 
Confidence bounds (or intervals) are produced based on a statistical analysis of the Monte Carlo 
results. These bounds reflect the uncertainty in the actual percentile value due to the finite 
number of Monte Carlo realizations. As the actual percentile value is not known, the value is 
estimated with this estimate itself being a random variable with a distribution (based on the 
binomial distribution). For the CDF curve the bounds represent a confidence limit (from the 
estimator distribution) at each percentile level based on the number of realizations, the percentile 
level, and the values realized. The larger the number of realizations the narrower the confidence 
interval. The median percentile values are constructed such that, in repeated sampling, the 
percentile will be above (or below) this median value 50 percent of the time. The 90 percentile 
confidence interval (given by the 5th and 95th percentile values) will, in repeated sampling, 
contain the percentile of interest 90 percent of the time. 
Note that localized corrosion does not initiate for both the waste package (Alloy 22 outer barrier) 
and drip shield because the exposure conditions on the drip shield and waste package surface are 
not severe enough to initiate localized corrosion (i.e., the corrosion potential is less than the 
critical corrosion potential) (see Section 3.1.6). Therefore no pit or crevice penetration is 
reported. Also note that the drip shield is assumed not subject to stress corrosion cracking, thus 
there is no crack penetration failure of drip shield. Thus, for drip shield, the first patch breach 
time profile is the same as the failure time profile.

 3-142  
3.2.7.1 Realistic Case Analysis Results 
Figure 3-102 shows the upper bound (100th percentile), lower bound (0th percentile), median, 
mean, and 95th, 75th, 25th and 5th percentile confidence intervals of the failure profile of waste 
packages with time. The upper bound profile, which is the upper extreme of the probable range 
of the failure time, indicates that the earliest possible failure time of waste package is about 
51,000 years. Note that an extremely low probability is associated with the estimated earliest 
possible failure time. It can be shown by comparing with the upper bound profile in 
Figure 3-104 (showing the first crack penetration profiles of waste packages with time) that the 
initial failure is by a SCC crack penetration. The median estimate of the failure time of the upper 
bound profile is about 120,000 years. The failure time of the median profile is about 80,000 
years. The second waste package failure time of the upper bound and median profiles is about 
59,000 and 86,000 years respectively. The time to fail 10 percent of waste packages for the two 
profiles is about 80,000 and 97,000 years respectively. 
Figure 3-103 shows the failure profiles of drip shields with time. Because the drip shields are 
not subject to stress corrosion cracking and localized corrosion, the failure profiles shown in the 
figure are all by general corrosion only. Both the upper and under sides of drip shield are 
exposed to the exposure conditions in the emplacement drift and are subject to corrosion. In 
addition, the both sides experience the same exposure conditions regardless of whether the drip 
shields are dripped on or not. Thus, in the analysis, the general corrosion rate for the drip shields 
is sampled twice independently, one for the patches on the upper side and the other for the 
patches on the under side. This results in reduced variability in the degradation profiles and thus 
fast failure rate (i.e., many drip shields failing over a short time period). This is shown in the 
upper bound profile, in which the drip shield failure starts at about 24,000 years and 50 percent 
of the drip shields fail within a couple of thousand years after the initial failure. Similar trends 
are also seen with the 95th, 75th and median profiles. In terms of the number of patch penetration 
openings per failed drip shield with time (not shown here; see CRWMS M&O 2000g, 
Figure 19), the upper bound profile shows that as the drip shields fail, a large number of patches 
are perforated over a relatively short time period (a few thousand years). A similar trend is seen 
for the 95th percentile profile. However, a lot more spread of the failure profile is shown for the 
other profiles. There is no correlation for the uncertainty and variability split of general 
corrosion rate between the drip shield and waste package outer barrier. 
Figures 3-104 and 3-105 show respectively the first crack penetration and patch penetration 
profiles of waste packages with time. The first crack penetration time of the upper and 95th 
percentile profiles is about 51,000 and 61,000 years respectively (Figure 3-104), and the first 
patch penetration time of the upper and 95th percentile profiles is about 62,000 and 64,000 years 
respectively (Figure 3-105). Comparison of the first crack and patch penetration profiles with 
the failure profiles indicates that the initial failure of the waste packages is likely by a SCC crack 
penetration in the waste package closure lid welds. For the 75th percentile profiles in the figures, 
the first crack and patch penetration times are about the same (about 72,000 years). For the 
remaining profiles, the first crack and patch penetration times are reversed.

 3-143  
3.2.7.2 Alternative Conservative Case Analysis Results 
The alternative conservative case analysis was to evaluate the effects of alternative conservative 
model abstractions of several key corrosion model parameters. Those parameters are SCCrelated 
parameters and general corrosion parameters and documented in Sections 3.2.2, 3.2.4, 
3.2.5, and 3.2.6. Table 3-13 lists those parameters and their values used in the realistic case and 
alternative conservative case analyses. As can be seen from the parameter value or its range in 
the table, this alternative conservative case is likely to represent the wrost case combination of 
those parameters from the perspective of initial waste package failure time. 
Figure 3-106 shows the upper and lower bounds, median, mean, and 95th, 75th, 25th and 5th 
percentile confidence intervals of the failure profile of waste packages with time. The upper 
bound profile shows that the earliest possible failure time of waste package is about 12,000 
years, much earlier than the realistic case (about 50,000 years, Figure 3-102). Note that the 
estimated earliest possible failure time has a very low probability. Comparing with the upper 
bound profile in Figure 3-108 (first crack penetration profiles of waste packages) and Figure 3- 
109 (first patch penetration profiles of waste packages), it shows that the initial failure is by a 
SCC crack penetration. The initial failure time of the 95th percentile profile is about 25,000 
years. The median estimate of the failure time of the upper bound profile is about 30,000 years, 
compared to about 120,000 years with the realistic case. The failure time of the median profile is 
about 50,000 years. The time to fail 10 percent of waste packages for the upper bound and 95th 
percentile profiles is about 22,000 and 35,000 years respectively. 
Figure 3-107 shows the failure profiles of drip shields with time. As with the realistic case 
analysis (Figure 3-103), the failure profiles shown in the figure are all by general corrosion only. 
Both the upper and under sides of drip shield are exposed to the exposure conditions in the 
emplacement drift and are subject to corrosion. In addition, the both sides experience the same 
exposure conditions regardless of whether the drip shields are dripped on or not. Thus, in the 
analysis, the general corrosion rate for the drip shields is sampled twice independently, one for 
the patches on the upper side and the other for the patches on the under side. This results in 
reduced variability in the degradation profiles and thus fast failure rate (i.e., many drip shields 
failing over a short time period). As shown in the figure, for the upper bound profile, the drip 
shield failure starts at about 20,000 years, and 50 percent of the drip shields fail within a 
thousand years after the initial failure. Similar trends are also seen with the 95th, 75th, mean and 
median profiles. A little earlier failure times and a tighter overall spread of failures of the drip 
shields are due to the increased general corrosion rate to account for the effect of silica scale 
deposit on the sample coupons (see Section 3.2.2.5). 
Figures 3-108 and 3-109 show respectively the first crack penetration and patch penetration 
profiles of waste packages with time with the alternative conservative case. The first crack 
penetration time of the upper and 95th percentile profiles is about 12,000 and 20,000 years 
respectively (Figure 3-108), and the first patch penetration time of the upper and 95th percentile 
profiles is about 32,000 and 40,000 years respectively (Figure 3-109). Comparison of the first 
crack and patch penetration profiles with the failure profiles (Figure 3-106) shows that the initial 
failures of the waste packages are by a SCC crack penetration in the waste package closure lid 
welds.

 3-144  
3.2.7.3 Analysis Summary 
The waste package and drip shield degradation analyses for the two end-member cases (i.e., 
realistic case and alternative conservative case) have shown that, based on the current corrosion 
model abstractions and assumptions, both the drip shields and waste packages do not fail within 
the regulatory time period (10,000 years). From the perspective of initial waste package failure 
time, the analysis results are encouraging because the alternative conservative case is likely to 
represent the wrost case combination of key corrosion model parameters that significantly affect 
long-term performance of waste packages in the repository. In particular, with the realistic case, 
the waste package service lifetime is predicted to extend far beyond the regulatory time period 
(failure beginning at about 50,000 years). 
The candidate materials for the drip shield (Titanium Grade 7) and the waste package outer 
barrier (Alloy 22) are highly corrosion resistant. Under the expected repository exposure 
conditions, these materials are not expected to be subject to the degradation processes that, if 
initiated, could lead to failure in a short time period. Those degradation modes are localized 
corrosion (pitting and crevice corrosion), stress corrosion cracking (SCC), and hydrogen induced 
cracking (HIC) (applicable to drip shield only). Both the drip shield and waste package degrade 
by general corrosion at very low passive dissolution rate. The current experimental data and 
detailed process-level analyses, upon which the model abstractions that have been incorporated 
in the WAPDEG analysis are based, have also indicated that, except the closure-lid welds of 
waste package, the candidate materials would not be subject to those rapidly penetrating 
corrosion modes under the expected repository conditions. Complete stress mitigation may not 
be possible for the closure-lid welds. Because of the potential residual stresses, the closure-lid 
welds may be subject to SCC. Once a SCC crack initiates, it penetrates the closure-lid thickness 
in a very short time (see Section 3.2.4.5). Thus stress mitigation in the closure-lid welds is a key 
design element to avoid premature failures of waste packages by SCC. 
The estimated long life-time of the waste packages in the current analysis is attributed mostly to 
the following two factors: (1) the stress mitigation to the substantial depths in the dual closure-lid 
welds, which delays the onset of SCC crack propagation until the compressive zone layer is 
corroded; and (2) the very low general-corrosion rate applied to the closure-lid welds to corrode 
the compressive stress zones, which renders a long delay time before initiating SCC crack 
propagation. Substantial uncertainties are associated with the SCC current analyses, especially 
stress mitigation on the closure-lid welds. The uncertainties associated with the uncertainty 
range in hoop stress and associated stress intensity factor used in the current SCC analyses will 
be re-evaluated to further quantify and reduce uncertainties as additional data and analyses are 
developed. In addition, the alternative conservative abstraction including embedded 
manufacturing defects in the WPOB closure-lid welds is highly conservative because most 
embedded defects would be oriented that would not lead to radial cracks. Another major 
uncertainty in the current analysis is the general corrosion rate applied to the closure-lid welds. 
The general corrosion model will be refined as additional data and analyses are developed.

 3-145  
Table 3-13. Corrosion Model Parameters Evaluated in the Waste Package and Drip Shield Degradation 
Analysis for Realistic and Alternative Conservative Cases 
Model Parameter Realistic Case Analysis Alternative Conservative Case Analysis 
WPOB General 
Corrosion 
- 2-year data from the Long-Term 
Corrosion Testing Facility (LTCTF). 
- 2-year data from the LTCTF. 
- Corrected for potential measurement bias 
from silica scale deposit on the sample 
coupons. 
DS General Corrosion 
- 1-year data from the LTCTF. - 1-year data from the LTCTF 
- Corrected for potential measurement bias 
from silica scale deposit on the sample 
coupons. 
Stress and Stress 
Intensity Factor (KI) 
Uncertainty Range in 
WPOB Closure-Lid 
Welds 
-  5% of yield strength. 
- Assume nornal distribution bounded at 
3 standard deviations around the 
mean. 
- Calculate using Eqn. (3-49) 
-  30% of yield strength. 
- Assume triangular distribution bounded at 
the min. and max. and with the mode at the 
mean. 
- Calculate using Eqn. (3-50) 
Threshold Stress for 
Crack Propagation 
- 20 to 30% of yield strength 
- Assume uniform distribution between 
the min. and max. 
- 20 to 30% of yield strength 
- Assume uniform distribution between the 
min. and max. 
Manufacturing Defects 
Probability in WPOB 
Closure-Lid Welds 
- Include surface breaking defects only. - Include surface breaking defects and 
embedded defects in the outer  region of 
the weld. 
Aging and Phase 
Instability 
Enhancement Factor 
for WPOB 
- Range from 1.0 to 2.5 applied to 
WPOB general corrosion rate. 
- Assume uniform distribution between 
the min. and max. 
- Applied to entire surface 
- Range from 1.0 to 2.5 applied to WPOB 
general corrosion rate. 
- Assume uniform distribution between the 
min. and max. 
- Applied to closure-lid welds only.

 3-146  
Source: CRWMS, M&O 2000j. Section 6.3.3 
Figure 3-87. Hoop Stress as a Function of Depth in the Alloy 22 Outer-Lid 
Welds (25-mm thick) at the Reference Location on the Outer-Lid 
Weld Circumference and the Uncertainty Range 
Hoop Stress vs. Depth for Outer Lid (25-mm thick) of 
WP Outer Barrier at 0 Angle 
Depth (mm) 
0 5 10 15 20 
Hoop Stress (MPa) 
-200 
-100
0 
100 
200 
300 
400 
500 
Mean 
 1s 
 2s 
 3s

 3-147  
Source: CRWMS, M&O 2000j, Section 6.3.3 
Figure 3-88. Stress Intensity Factor as a Function of Radial Crack in the 
Alloy 22 Outer-Lid Welds (25-mm thick) at the Reference 
Location on the Outer-Lid Weld Circumference and the 
Uncertainty Range 
Source: CRWMS, M&O 2000j, Section 6.3.3 
Figure 3-89. Hoop Stress as a Function of Depth in the Alloy 22 Outer-Lid 
Welds (25-mm thick) at 0, 90 and 180 Angles Along the 
Circumference of the Outer-Lid Weld 
Stress Intensity KI vs. Radial Crack Depth for 
Outer Lid (25-mm thick) of WP Outer Barrier at 0 Angle 
Depth (mm) 
0 5 10 15 20 
KI (MPa*m) 
-30 
-20 
-10
0 
10 
20 
30 
40 
50 
Mean 
 1s 
 2s 
 3s 
Hoop Stress vs. Depth for Outer Lid (25-mm thick) of 
WP Outer Barrier at 0, 90, 180 Angle 
Depth (mm) 
0 5 10 15 20 
Hoop Stress (MPa) 
-200 
-100
0 
100 
200 
300 
400 
500 
0 Angle 
90 Angle 
180 Angle

 3-148  
Stress Intensity KI vs. Radial Crack Depth for 
Outer Lid (25-mm thick) of WP Outer Barrier at 0, 90, 180 Angle 
Depth (mm) 
0 5 10 15 20 
KI (MPa*m) 
-30 
-20 
-10
0 
10 
20 
30 
40 
50 
0 Angle 
90 Angle 
180 Angle 
Source: CRWMS M&O 2000j, Section 6.3.3 
Figure 3-90. Stress Intensity Factor as a Function of Radial Crack 
Depth in the Alloy 22 Outer-Lid Welds (25-mm thick) 
at 0, 90 and 180 Angles Along the Outer-Lid Weld 
Circumference

 3-149  
Source: CRWMS M&O 2000j, Section 6.3.3 
Figure 3-91. Hoop Stress as a Function of the Projected Depth in the 
Alloy 22 Inner-Lid Welds (10-mm thick) at the Reference 
Location on the Inner-Lid Weld Circumference and the 
Uncertainty Range 
Hoop Stress vs. Depth for Inner Lid (10-mm thick) of 
WP Outer Barrier at 0 Angle 
Projected Depth (mm) 
0 2 4 6 8 10 
Hoop Stress (MPa) 
-200 
-100
0 
100 
200 
300 
Mean 
1s 
2s 
3s

 3-150  
Source: CRWMS M&O 2000j, Section 6.3.3 
Figure 3-92. Hoop Stress as a Function of the Projected Depth in the 
Alloy 22 Inner-Lid Welds (10-mm thick) at 0, 90 and 180 
Angles Along the Circumference of the Inner-Lid Weld 
Hoop Stress vs. Depth for Inner Lid (10-mm thick) of 
WP Outer Barrier at 0, 90, 180 Angle 
Projected Depth (mm) 
0 2 4 6 8 10 
Hoop Stress (MPa) 
-200 
-100
0 
100 
200 
300 
0 Angle 
90 Angle 
180 Angle

 3-151  
Hoop Stress vs. Depth for Inner Lid (10-mm thick) of 
WP Outer Barrier at 0, 90, 180 Angle 
Projected Depth (mm) 
0 2 4 6 8 10 
Hoop Stress (MPa) 
-200 
-100
0 
100 
200 
300 
0 Angle 
90 Angle 
180 Angle 
Source: CRWMS M&O 2000j, Section 6.3.3 
Figure 3-93. Stress Intensity Factor as a Function of the Projected Radial 
Crack Depth in the Alloy 22 Inner-Lid Welds (10-mm thick) at 
the Reference Location on the Inner-Lid Weld Circumference 
and the Uncertainty Range 
Source: CRWMS M&O 2000j, Section 6.3.3 
Figure 3-94. Stress Intensity Factor as a Function of the Projected Radial 
Crack Depth in the Alloy 22 Inner-Lid Welds (10-mm thick) at 
0, 90 and 180 Angles Along the Inner-Lid Weld 
Circumference 
Stress Intensity KI vs. Radial Crack Depth for Inner Lid (10-mm thick) of 
WP Outer Barrier at 0, 90, 180 Angle 
Projected Depth (mm) 
0 2 4 6 8 10 
KI (MPa*m) 
-30 
-20 
-10
0 
10 
20 
0 Angle 
90 Angle 
180 Angle

 3-152  
Alternative Conservative Model for 
Uncertainty in Hoop Stress vs. Depth in WPOB Outer Lid (25 mm) 
Distance From Outside Surface (mm) 
0 2 4 6 8 10 12 14 16 18 20 
Hoop Stress (MPa) 
-600 
-400 
-200
0 
200 
400 
600 
Mean Stress 
Bounds at 10% 
Bounds at 15% 
Bounds at 30% 
Figure 3-95. Hoop Stress as a Function of Depth in the Alloy 22 Outer- 
Lid Welds (25-mm thick) at the Reference Location on the 
Outer-Lid Weld Circumference using Uncertainty Bounds of 
 10, 15, and 30%

 3-153  
Alternative Conservative Model for 
Uncertainty in KI vs. Radial Crack Depth in WPOB Outer Lid (25 mm) 
Distance From Outside Surface (mm) 
0 2 4 6 8 10 12 14 16 18 20 
KI (MPa*m1/2) 
-40 
-20
0 
20 
40 
60 
80 
100 
Mean 
Bounds at 10% 
Bounds at 15% 
Bounds at 30% 
Figure 3-96. Stress Intensity as a Function of Depth in the Alloy 22 
Outer-Lid Welds (25-mm thick) at the Reference Location 
on the Outer-Lid Weld Circumference using Uncertainty 
Bounds of  10, 15, and 30% 
Alternative Conservative Model for 
Uncertainty in Hoop Stress vs. Depth in OB Inner Lid (10 mm) 
Distance From Outside Surface (mm) 
0 2 4 6 8 10 
Hoop Stress (MPa) 
-600 
-400 
-200
0 
200 
400 
Mean 
Bounds at 10% 
Bounds at 15% 
Bounds at 30% 
Figure 3-97. Hoop Stress as a Function of Depth in the Alloy 22 Inner- 
Lid Welds (10-mm thick) at the Reference Location on the 
Outer-Lid Weld Circumference using Uncertainty Bounds of 
 10, 15, and 30%

 3-154  
Alternative Conservative Model for 
Uncertainty in KI vs. Radial Crack Depth in OB Inner Lid (10 mm) 
Distance From Outside Surface (mm) 
0 2 4 6 8 10 
KI (MPa*m1/2) 
-60 
-40 
-20
0 
20 
40 
60 
Mean 
Bounds at 10% 
Bounds at 15% 
Bounds at 30% 
Figure 3-98. Stress Intensity as a Function of Depth in the Alloy 22 
Inner-Lid Welds (10-mm thick) at the Reference Location on 
the Outer-Lid Weld Circumference using Uncertainty 
Bounds of  10, 15, and 30%

 3-155  
Source: CRWMS M&O 2000j, Section 6.2.2 
Figure 3-99. Cumulative Probability for the Occurrence of Defects in the 
Welds of the Outer (25-mm thick) and Inner (10-mm thick) Lids 
of Waste Package Outer Barrier (Surface breaking flaws only) 
Manufacturing Defects for 
Outer (25 mm) and Inner (10 mm) Closure-Lid Welds 
Probability of a Defect Existence 
0.00 0.05 0.10 0.15 0.20 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
10 mm Inner Lid 
25 mm Outer Lid

 3-156  
Flaw Size PDFs for Post-Inspection for 
Various Combinations of the Shape Parameters 
Flaw Size (mm) 
0 1 2 3 4 5 6 7 8 
Probability Density 
0.0 
0.5 
1.0 
1.5 
Pre-inspection 
b=1.6, .=1 
b=1.6, .=3 
b=5, .=1 
b=5, .=3 
Source: CRWMS M&O 2000j, Section 6.2.2 
Figure 3-100. Conditional Probability Density Functions of Defect 
Sizes in the Closure Lid Welds for Various 
Combinations of Values for the Location and Scale 
Parameters (b & .)

 3-157  
Number of Defects per WP in the WPOB Outer and Inner Closure-Lid Welds 
(Surface Breaking and Outer 1/4 Region Defects) 
Number of Flaws per WP 
0 10 20 30 40 
Cumulative Probability 
0.00 
0.25 
0.50 
0.75 
1.00 
Inner Lid (10 mm) 
Outer Lid (25 mm) 
Figure 3-101. Cumulative Probability for the Average Number of Defects 
per Waste Package in the Welds of the Outer (25-mm thick) 
and Inner (10-mm thick) Lids of Waste Package Outer 
Barrier Including Surface Breaking and Embedded Defects 
Waste Package Failure vs. Time 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Waste Packages Failed 
0.00 
0.25 
0.50 
0.75 
1.00 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Figure 3-102. The Upper and Lower Bounds, Median, Mean, 
and 95th, 75th, 25th and 5th Percentile Confidence 
Intervals of the First Breach Profile of Waste 
Packages with Time

 3-158  
Drip Shield Failure vs. Time 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Drip Shields Failed 
0.00 
0.25 
0.50 
0.75 
1.00 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Source: CRWMS M&O 2000g, Section 6.4 
Figure 3-103. The Upper and Lower Bounds, Median, Mean, and 95th, 
75th, 25th, and 5th Percentile Confidence Intervals of the 
First Breach Profile of Drip Shield with Time 
Waste Package 1st Crack Failure vs. Time 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Waste Packages Failed 
0.0 
0.5 
1.0 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Source: CRWMS M&O 2000g, Section 6.4 
Figure 3-104. The Upper and Lower Bounds, Median, Mean, and 95th, 
75th, 25th, and 5th Percentile Confidence Intervals of the 
First Crack Breach Profile of Waste Packages with Time

 3-159  
Waste Package 1st Patch Failure vs. Time 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Waste Packages Failed 
0.00 
0.25 
0.50 
0.75 
1.00 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Figure 3-105. The Upper and Lower Bounds, Median, Mean, and 95th, 
75th, 25th, and 5th Percentile Confidence Intervals of the 
First Patch Breach Profile of Waste Packages with Time 
Waste Package Failure vs. Time 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Waste Packages Failed 
0.00 
0.25 
0.50 
0.75 
1.00 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Figure 3-106. The Upper and Lower Bounds, Median, Mean, and 95th, 
75th, 25th, and 5th Percentile Confidence Intervals of the 
First Breach Profile of Waste Packages with Time

 3-160  
Drip Shield (Patch) Failure vs. Time 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Drip Shields Failed 
0.00 
0.25 
0.50 
0.75 
1.00 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Figure 3-107. The Upper and Lower Bounds, Median, Mean, and 95th, 75th, 
25th and 5th Percentile Confidence Intervals of the First 
Breach Profile of Drip Shield with Time 
Waste Package 1st Crack Failure 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Waste Packages Failed 
0.00 
0.25 
0.50 
0.75 
1.00 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Figure 3-108. The Upper and Lower Bounds, Median, Mean, and 95th, 75th, 
25th and 5th Percentile Confidence Intervals of the First Crack 
Breach Profile of Waste Packages with Time

 3-161  
Waste Package 1st Patch Failure 
(100 Realizations; 20-mm WPOB; 15-mm DS; 400 WP/DS Pairs;Backfill) 
Time (years) 
104 105 106 
Fraction of Waste Packages Failed 
0.00 
0.25 
0.50 
0.75 
1.00 
Upper Bound 
95th Percentile 
75th Percentile 
Median 
Mean 
25th Percentile 
5th Percentile 
Lower Bound 
Figure 3-109. The Upper and Lower Bounds, Median, Mean, and 95th, 75th, 
25th and 5th Percentile Confidence Intervals of the First Patch 
Breach Profile of Waste Packages with Time

 3-162  
INTENTIONALLY LEFT BLANK

 4-1  
4. RELATIONSHIP TO NRC ISSUE RESOLUTION STATUS REPORTS 
4.1 SUMMARY OF THE KEY TECHNICAL ISSUES 
As part of the review of site characterization activities, the 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 informal, pre-licensing consultation with the U.S. Department of Energy (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 
postclosure 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 
 Igneous Activity 
 Radionuclide Transport 
 Repository Design and Thermal-Mechanical Effects 
 Structural Deformation and Seismicity 
 Thermal Effects on Flow (TEF) 
 TSPA and Integration 
 Unsaturated Zone (UZ) and Saturated Zone (SZ) Flow Under Isothermal Conditions. 
Identifying KTIs, integrating their activities into a risk informed approach, and evaluating their 
significance for postclosure 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 QA 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. 
4.2 RELATION OF THE WASTE PACKAGE PMR TO THE KEY TECHNICAL 
ISSUES 
The WP PMR provides technical information and analyses that relate to three of the KTIs and 
their associated IRSRs. These include the Issue Resolution Status Reports Key Technical Issue: 
Container Life and Source Term (NRC 1999a), the Issue Resolution Status Report Key Technical 
Issue: Total System Performance Assessment and Integration (NRC 2000), and the Repository 
Design and Thermal-Mechanical Effects (NRC 1999b). Several subissues of these KTIs that 
relate directly to the WP PMR are discussed in the following sections. Table 4-1 summarizes 
these KTIs and their subissues that relate directly to this PMR, the related acceptance criteria and 
PMR approach. In addressing each acceptance criteria, it is assumed that the criteria apply to the 
DS performance as well. 
4.2.1 Container Life and Source Term 
The primary issue of the KTI on Issue Resolution Status Report Key Technical Issue: Container 
Life and Source Term (NRC 1999a) is adequacy of the EBS design to provide reasonable 
assurance that containers will be adequately long-lived, and radionuclide releases from the EBS 
will be sufficiently controlled, and that the container design and packaging of spent nuclear fuel 
(SNF) and HLW glass will make a significant contribution to the overall repository performance. 
The site-specific proposed 10 CFR 63 (Dyer 1999) regulation, currently in the public 
commenting period, is a performance-based regulation. The current CLST IRSR is mainly 
focused on the containers and WFs as the primary engineered barriers, but it also considers other 
engineered sub-system enhancements (i.e., DS, backfill) incorporated as options in the EBS 
design. For the purpose of this IRSR, the NRC defines the physical boundary of the EBS by the 
walls of the WP emplacement drifts. The CLST IRSR identifies six subissues and associated 
general and specific acceptance criteria deemed important to the resolution of this KTI: 
1. The effects of corrosion processes on the lifetime of the containers 
2. The effects of phase instability of materials and initial defects on the mechanical 
failure and lifetime of the containers 
3. The rate at which radionuclides in SNF are released from the EBS through the 
oxidation and dissolution of spent fuel 
4. The rate at which radionuclides in HLW glass are leached and released from the EBS 
5. The effect of in-package criticality on WP and EBS performance 
6. The effects of alternate EBS design features on container lifetime and radionuclide 
release from the EBS.

 4-3  
The IRSR provides acceptance criteria for resolution of each of these subissues from the 
standpoint of performance of the container materials. Subissues 1, 2, and 5, 6 are related to the 
WP PMR. The following paragraphs address each of the subissues. Also, specific acceptance 
criteria related to each of these subissues are discussed in Table 4-1, along with the approach to 
addressing the criteria and sections of the PMR that describe these approaches. In addressing 
each acceptance criterion, it is assumed that the criterion applies to DS performance as well. 
4.2.1.1 Container Life and Source Term Issue Resolution Status Report General 
Criteria 
In addition to the specific acceptance criteria addressed in Table 4-1, the CLST IRSR includes a 
set of generic acceptance criteria dealing with expert elicitation and all aspects of data collection, 
qualification, verification, documentation of uncertainties and limitations in both data and 
process models. All these general acceptance criteria fall into two NRCs programmatic criteria 
for QA and the use of expert elicitation. These programmatic criteria apply to all subissues, thus, 
they are addressed generically for all subissues. 
The acceptance criteria for QA addresses DOEs implementation of an adequate QA program. 
The WP 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 (see Section 1.4). The programmatic criterion for expert elicitation specifies 
that DOE conduct expert elicitation in accordance with NUREG-1563 (Kotra et al. 1996) or 
other acceptable approaches. The WP PMR addresses the NRCs programmatic criteria for QA. 
No expert elicitation results or data have been used in preparation of this PMR. 
4.2.1.2 Container Life and Source Term Issue Resolution Status Report Subissue 1 
Subissue 1 considers failure of outer and inner overpacks as a result of various corrosion 
processes affecting both WP materials, such as dry-air oxidation, humid-air and uniform aqueous 
corrosion, LC, MIC, SCC and HIC. Models for these corrosion processes have been developed 
and incorporated into the WP degradation model and are discussed in various parts of the 
WP PMR. Acceptance criteria related to this subissue and the PMR approach that address the 
acceptance criteria are provided in Table 4-1. 
4.2.1.3 Container Life and Source Term Issue Resolution Status Report Subissue 2 
Subissue 2 (NRC 1999a, Sections 4.2 and 5.2) examines long-term degradation of mechanical 
properties of container materials as a result of prolonged exposures of the WPs (thousands of 
years) at elevated temperatures. Mechanical failure due to phase instability of WP materials is 
highly dependent on material chemical composition and processing history. Examples of 
material instability that can degrade mechanical properties include segregation of metalloid 
elements such as phosphorus and sulfur, precipitation of carbides of intermetallic phases, and 
long-range ordering (LRO). Fabrication defects that may lead to early failure of container 
materials are also the subject of this subissue, as well as the effects of damage due to disruptive 
events, such as seismicity, faulting, and igneous activity. 
Acceptance criteria related to this subissue and the PMR approach that addresses the acceptance 
criteria are provided in Table 4-1.

 4-4  
4.2.1.4 Container Life and Source Term Subissue 5 
Subissue 5 addresses the effects of in-package criticality on WP 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. 
4.2.1.5 Container Life and Source Term Issue Resolution Status Report Subissue 6 
Subissue 6 addresses performance of the alternative EBS design features such as the DS and 
backfill. The concerns addressed by the NRC in the IRSR relate to the DS design to be 
fabricated from titanium alloys. These materials can suffer from thermal embrittlement. Both 
temper embrittlement of steels and thermal embrittlement of titanium alloys occur as a result of a 
thermally activated redistribution of barely soluble impurities from grain interiors to GB. 
Titanium alloys have been long recognized for being highly resistant to corrosion as a result of 
their ability to form a protective oxide film when in contact. The pH and chloride concentrations 
have been found to have a relatively minor influence on the passive dissolution rate of some 
titanium alloys, although data are limited in this area. A review of the literature indicates that 
some of titanium alloys are susceptible to crevice corrosion. Insufficient experimental data are 
available for titanium-palladium alloys such as Titanium Grade 7 in relevant environments to 
state with absolute certainty whether or not these materials will undergo crevice corrosion over a 
period of 10,000 years. It is generally accepted in the material science community that the 
addition of palladium to titanium does improve the crevice corrosion resistance of such 
materials. However, given the lack of data for titanium-palladium alloys, further investigation of 
crevice corrosion is warranted (NRC 1999a). 
Environmentally assisted cracking (EAC) of titanium-palladium alloys has not been extensively 
investigated. Many titanium alloys are susceptible to EAC due to hydrogen embrittlement 
associated with the precipitation of hydrides ahead of the crack tip. However, the titaniumpalladium 
alloys may be highly resistant to EAC, especially those that have low equivalent 
oxygen content. The addition of palladium to titanium has also been thought to enhance EAC 
resistance because hydrogen evolution as H2 would preferentially take place at Pd-rich sites, 
thereby decreasing the available atomic hydrogen that could be absorbed into the titanium lattice. 
It is unclear if this mechanism is operable. Thus, the NRC notes in the CLST IRSR that further 
DOE investigation of the EAC behavior of titanium-palladium alloys is needed, with particular 
emphasis on methodologies that would enable monitoring and measurement of slow crack 
propagation rates (NRC 1999a). 
The performance modeling of the DS is addressed in this PMR and the effects and performance 
of the backfill are addressed in the PMR on EBS. Acceptance criteria related to this subissue and 
the PMR approach that addresses the acceptance criteria are provided in Table 4-1. 
4.2.2 Total System Performance Assessment and Integration 
The overall goal of the TSPA Integration KTI (NRC 2000) is to delineate staffs systematic 
approach for determining compliance with an overall system performance objective. The 
objective of this KTI is to describe an acceptable methodology for conducting performance

 4-5  
assessments of repository performance and using these assessments to demonstrate compliance 
with the overall performance objective and requirements for multiple barriers. The TSPAI IRSR 
identifies four subissues and associated acceptance criteria deemed important to the resolution of 
this KTI: 
1. System Description and Demonstration of Multiple Barriers 
2. TSPA Methodology: Scenario Analysis 
3. TSPA Methodology: Model Abstraction 
4. Demonstration of the Overall Performance Objective 
Subissues 1, 2, and 3 are related to the WP PMR. The acceptance criteria for each subissue 
address fundamental elements of the DOEs TSPA model for the Yucca Mountain site. The 
following paragraphs address each of the subissues. Also, related acceptance criteria applicable 
to the WP PMR are discussed in Table 4-1, along with the approach to addressing the criteria. 
Programmatic acceptance criteria related to the QA and expert elicitation are addressed 
generically in Section 4.2.1.1 and are not repeated here or in Table 4-1. 
4.2.2.1 Subissue 1, System Description and Demonstration of Multiple Barriers 
This subissue relates to the transparency and traceability of the analysis that allows for an 
adequate understanding of DOEs approach and results of the TSPA. Sufficient transparency 
and traceability of the TSPA analyses and results will convince the NRC that compliance with 
regulatory criteria will be achieved. The following aspects of transparency and traceability are 
addressed under this subissue: TSPA document style, structure, and organization FEPs 
identification and screening; abstraction methodology; data use and validity; assessment results; 
and code design, data flow, and supporting documentation. Acceptance criteria pertaining to 
these aspects of the transparency and traceability and the PMR approach in addressing the 
acceptance criteria are provided in Table 4-1. 
4.2.2.2 Subissue 2, Total System Performance Assessment Methodology: Scenario 
Analysis 
This subissue focuses on the attributes of an acceptable methodology for identifying, screening, 
and selecting FEPs for inclusion in the TSPA. FEPs that could effect future system performance 
are used to formulate scenarios. This includes construction of scenario classes, assignment of 
probabilities to scenario classes, and their incorporation into the TSPA. This is a key factor in 
ensuring the completeness of the TSPA. A systematic method was applied to identify and screen 
FEPs for WP degradation. A description of this method is provided under Section 1.6. The 
results of the FEPs screening analyses are also summarized in Table 1-2. 
This subissue includes five elements related to the scenario analysis: identification of initial set 
of processes and events, classification of processes and events, screening of processes and 
events, formation of scenarios, and screening of scenario classes. Acceptance criteria for these 
elements and the PMR approach in addressing the acceptance criteria are provided in Table 4-1.

 4-6  
4.2.2.3 Subissue 3, Total System Performance Assessment Methodology: Model 
Abstraction 
This subissue focuses on the information and technical approaches needed to develop defensible 
model abstractions and their integration into TSPA. The WP degradation model addresses 
several elements of this subissue that are related to the engineered barrier degradation, 
mechanical disruption of engineered barriers, and quantity and chemistry of water contacting 
WPs and WFs. Some of the acceptance criteria for elements listed above that are directly related 
to the WP PMR and the PMR approach in addressing the acceptance criteria are provided in 
Table 4-1. 
4.2.3 Repository Design and Thermal-Mechanical Effects 
The primary focus of the repository design and thermal-mechanical effects (RDTME) KTI is the 
review of design, construction, and operation of the geologic repository operations area (GROA) 
with respect to the preclosure and postclosure performance objectives, taking into consideration 
long-term thermal-mechanical (TM) processes. Consideration of the time-dependent TM 
coupled response of a jointed rock mass is central to potential repository design and necessary 
for performance assessment (PA) at the Yucca Mountain (YM) site. Consequently, that is the 
focus of the preclosure and postclosure elements of this KTI (NRC 1999b, Section 2.1). 
The RDTME KTI identifies four subissues and their associated components and acceptance 
criteria. Only Subissue 3, Thermal-mechanical Effects on Underground Facility Design and 
Performance, and its major component regarding effect of seismically induced rockfall on WP 
performance is directly related to this PMR. Table 4-1 addresses the acceptance criterion for 
rockfall effects and the WP PMR approach. 

 4-7  
Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach 
NRC Technical Acceptance Criteria PMR Approach 
IRSR: Container Life and Source Term 
SUBISSUE 1  The Effect of Corrosion Processes on the Lifetime of the Containers 
1. DOE has identified and considered likely modes of corrosion 
for container materials, including dry-air oxidation, humid-air 
corrosion, and aqueous corrosion processes, such as GC, 
LC, MIC, SCC and HIC, as well as the effect of galvanic 
coupling. 
All likely modes of corrosion have been considered and modeled in this PMR (See 
Section 1.5). The constituent models of this PMR include process models for dry-air 
oxidation, humid-air corrosion, stress corrosion cracking, HIC, and aqueous corrosion 
processes, such as GC, LC, and microbial influenced corrosion. Galvanic coupling effects 
have been minimized. 
2. DOE has identified the broad range of environmental 
conditions within the WP emplacement drifts that may 
promote the corrosion processes listed previously, taking into 
account the possibility of irregular wet and dry cycles that 
may enhance the rate of container degradation. 
The corrosion models in this PMR include environmental thresholds that can be used to 
switch between dominant modes of corrosion. For example, as the WP temperature drops 
and the RH increases, the mode of attack changes from dry-air oxidation to humid-air or 
aqueous-phase corrosion. A comparison of the corrosion and threshold potentials is used 
to determine whether or not LC will occur. WAPDEG uses bounding conditions that envelop 
wet and dry cycles (see Section 3.2.3) depending upon the condition at a given time step. 
3. DOE has demonstrated that the numerical corrosion models 
used are adequate representations, taking into consideration 
associated uncertainties, of the expected long-term behaviors 
and are not likely to underestimate the actual degradation of 
the containers as a result of corrosion in the repository 
environment. 
Uncertainties are accounted for in corrosion rates. The rate at the 50th percentile is 
approximately 50 nm y-1, the rate at the 90th percentile is approximately 100 nm y-1, and the 
maximum rate is 731 nm y-1. About 10 percent of the values fall between 100 and 
750 nm y-1 (Section 3.1.5). The effects of thermal aging over extended periods of time 
(10,000 years) is being accounted for in the overall corrosion model for the WPOB 
(Section 3.1.4). 
4. DOE has considered the compatibility of container materials, 
the range of material conditions, and the variability in 
container fabrication processes, including welding, in 
assessing the performance expected in the containers 
intended waste isolation. 
The effects of welding and thermal aging on the corrosion resistance of the WP materials 
have been accounted for. A fully aged sample of Alloy 22 exhibits a less noble corrosion 
potential, shifted in the cathodic direction by approximately: 63 mV in the case of SAW at 
90C; 109 mV in the case of SCW at 90C; and by more than 100 mV in the case of BSW at 
100C. It is assumed that Ecorr is corrected to account for fully aged material by subtracting 
approximately 100 mV from values calculated for the base metal. The shift in Ecritical 
(threshold potential 1) is approximately 100 mV in most cases. Thus, the difference Ecritical- 
Ecorr is virtually unchanged. The effect of thermal aging on the corrosion rate is accounted 
for in an enhancement factor, Gaged, and is based upon a ratio of the non-equilibrium current 
densities for base metal and aged material. The value of Gaged for base metal is 
approximately one (Gaged ~ 1), whereas the value of Gaged for fully aged material is larger 
(Gaged ~ 2.5). Material with less precipitation than the fully aged material would have an 
intermediate value of Gaged (1  Gaged  2.5) (Section 3.1.4).

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
IRSR: Container Life and Source Term 
SUBISSUE 1  The Effect of Corrosion Processes on the Lifetime of the Containers 
5. DOE has justified the use of data collected in corrosion tests 
not specifically designed or performed for the Yucca 
Mountain repository program for the environmental 
conditions expected to prevail at the Yucca Mountain site. 
The WP degradation process models are based on bounding environmental conditions 
(temperature, humidity, chemistry, etc.) expected in the proposed repository (See Section 
3.1.3). The threshold RH used to determine whether vapor phase attack is by DOX or HAC 
is based upon the deliquescence point of salt deposits that could form on the WP surface 
due to aerosol transport. Measurements of GC rates in the vapor and aqueous phases, 
electrochemical potentials, and other relevant performance data were in test media that can 
be directly related to water chemistry expected on the WP surface during the service life of 
Alloy 22. These water chemistries are based upon evaporative concentrations of the 
standard J-13 well water chemistry. Crevice chemistry is being measured in situ, with and 
without the presence of buffer ions. In the aqueous phase, a range of temperature 
extending from room temperature to 120C is being investigated. The high-temperature 
limit is based upon the boiling point of a near-saturation water chemistry without buffer. The 
expected boiling point of the aqueous phase on the WP surface is expected to be lower. In 
addition to the data generated from long-term and short-term corrosion tests, the process 
model development also includes data generated outside the YMP. These data in general 
include testing in environments not directly applicable to the YMP and therefore are used as 
corroborative information.

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
6. DOE has conducted a consistent, sufficient, and suitable 
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(s) of uncertainty as part of the 
performance confirmation program. 
The DOE has established a corrosion test program that addresses all anticipated modes of 
corrosive attack of the WP. There is a clear linkage between the experimental data being 
collected and modules in the predictive WAPDEG code that serves as the heart of the 
TSPA. Data and modules have been developed for each key element of the EDA II design: 
the WPOB (Alloy 22); the inner structural support (stainless steel 316NG); and the 
protective DS (Titanium Grade 7). Companion AMRs provide data and modules for the 
stainless steel 316NG and the Titanium Grade 7 alloy (PMR Section 3.1.4 through 3.1.8). 
Studies include exposure of over 18,000 samples of candidate WP material in the Long 
Term Corrosion Test Facility (LTCTF). A large number of pre- and post-exposure 
measurements of dimension and weight allow establishment of distribution functions for 
representation of the GC rate. Microscopic examination of samples from the LTCTF and 
other corrosion tests is done with Scanning Electron Microscopy (SEM), Atomic Force 
Microscopy (AFM), X-Ray Diffraction (XRD), X-Ray Photoelectron Spectroscopy, Secondary 
Ion Mass Spectrometry (SIMS), and other state-of-the-art surface analytical techniques. 
Potentiodynamic and potentiostatic electrochemical tests are conducted with base metal, 
thermally aged material and simulated welds. Thermally aged material is fully characterized 
with the transmission electron microscope (TEM) as discussed by Summers and Turchi 
(CRWMS M&O 2000b). The present test results provide sufficient confidence for the 
current design. In addition, the Project will continue testing of materials both in the 
laboratory and in the field. This part of the testing program is covered in the Performance 
Confirmation Plan (CRWMS M&O 2000q). 
This acceptance criterion pertains directly to the principal factors of the postclosure safety 
case associated with the degradation and performance of the WP and DS. These principal 
factors are also associated with one of the performance confirmation factors and will be 
addressed through testing and analysis identified in the Performance Confirmation Plan 
(CRWMS 2000q). The information obtained in the performance confirmation program is to 
confirm the corrosion rates and will serve to reduce residual uncertainties regarding longterm 
corrosion behavior including those arising from corrosion mechanisms not detected in 
the baseline testing program. See Section 5.3.1.8 and Appendix G of the Performance 
Confirmation Plan (CRWMS M&O 2000q).

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
7. DOE has established a defensible program of corrosion 
monitoring and testing of the engineered sub-system 
components during the performance confirmation period to 
assure they are functioning as intended and anticipated. 
This acceptance criterion pertains directly to the principal factors of the postclosure safety 
case associated with the degradation and performance of the WP and DS. These principal 
factors are also associated with one of the performance confirmation factors and will be 
addressed through testing and analysis identified in the Performance Confirmation Plan 
(CRWMS M&O 2000q). The baseline for performance confirmation to address this factor 
will be information available from site characterization and pre-emplacement testing. 
Because the DS will not be installed until permanent closure, performance confirmation 
testing will be confined to laboratory testing to confirm corrosion rates fall within the limits 
considered in the licensing review (see Section 5.3.1.8 and Appendix G of the Performance 
Confirmation Plan) and prototype testing (see Sections 5.3.2, 5.3.5.4, and Appendix G of 
the Performance Confirmation Plan). This information will be considered in evaluating 
whether the DSs would operate as anticipated and intended (i.e., by comparing with design 
criteria). Other engineered subsystem components determined not to be important to postclosure 
safety case will not be addressed in the performance confirmation program. In the 
current version of the plan, testing to monitor and confirm expectations regarding the effects 
of other introduced materials to the EBS environment is included in the program. See 
Section 5.3.1.7 and Appendix G. 
SUBISSUE 2 - The effects of phase instability of materials and initial defects on the mechanical failure and lifetime of the containers 
1. DOE has identified and considered the relevant mechanical 
failure processes that may affect the performance of the 
proposed container materials. 
As described in this report, all likely degradation modes, including HIC and SCC as two 
possible mechanical failure modes have been considered. Both modes have been included 
in WAPDEG, and are described in the report (Sections 3.1.7 and 3.1.8, respectively). 
2. DOE has identified and considered the effect of material 
stability on mechanical failure processes for the various 
container materials as a result of prolonged exposure to the 
expected range of temperatures and stresses, including the 
effects of chemical composition, microstructure, thermal 
treatments, and fabrication processes. 
This PMR presents data showing that Alloy 22 has adequate phase stability to serve as a 
WP material, provided that the temperature is not allowed to exceed 260C. Expected 
range of temperature and stresses, chemical composition, microstructure, thermal 
treatments, and fabrication processes are all related to the material stability and have been 
considered in modeling in Section 3.1.4 of the PMR. 
3. DOE has demonstrated that the numerical models used for 
container materials stability and mechanical failures are 
effective representations, taking into consideration 
associated uncertainties, of the expected materials behavior 
and are not likely to underestimate the actual rate of failure 
in the repository environment. 
Uncertainties, assumptions, and limitations of the specific models are addressed in the 
related AMRs. As indicated in Section 3.2.1, the WAPDEG analysis also takes into account 
quantifiable uncertainties and variability of the degradation model for the possible ranges of 
corrosion parameters and exposure conditions. The WAPDEG model includes modules for 
DOX, HAC, APC, SCC and HIC. Also, both GC and LC are considered. The possibility of 
using either localized thermal annealing or laser peening is considered as a means of 
mitigating SCC in the WP closure weld. 
4. DOE has considered the compatibility of container materials 
and the variability in container manufacturing processes, 
including welding, in its WP failure analyses and in the 
evaluation of radionuclide release. 
The design now used prevents galvanic coupling of Titanium Grade 7 with carbon steel, 
thereby preventing any hydrogen charging of the DS due to the cathodic reduction of 
hydrogen ions on the titanium surface. Variabilities in processes used for weld stress 
mitigation are accounted for in the SCC models for both laser peening and induction 
annealing techniques (See Section 3.1.7).

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
5. DOE has identified the most appropriate methods for 
nondestructive examination (NDE) of fabricated containers 
to detect and evaluate fabrication defects in general and, 
particularly, in seam and closure welds. 
An NDE protocol is under development and will be used for DS and WP inspection. Such 
inspection will limit the size of manufacturing defects as a means of helping prevent SCC 
and HIC. Materials used in WP construction will be tested electrochemically, to assure that 
those materials being used are not unexpectedly susceptible to LC. 
6. DOE has justified the use of material test results not 
specifically designed or performed for the Yucca Mountain 
repository program for environmental conditions (i.e., 
temperature, stress, and time) expected to prevail at the 
proposed Yucca Mountain repository. 
Various AMRs supporting this report, such as the AMR on degradation of stainless steel 
(CRWMS M&O 2000e), provide discussion for the use of material test results from 
published data not specifically designed or performed for the Yucca Mountain repository 
program for environmental conditions expected to prevail at the proposed Yucca Mountain 
repository. 
7. DOE has conducted a consistent, sufficient, and suitable 
material testing program at the time of the LA submittal. In 
addition, DOE has identified specific plans for further testing 
to reduce any significant area(s) of uncertainty as part of the 
performance confirmation program. 
This acceptance criterion pertains directly to the principal factors of the postclosure safety 
case associated with the degradation and performance of the WP and DS. These principal 
factors are also associated with performance confirmation factors and will be addressed 
through testing and analysis identified in the Performance Confirmation Plan (CRWMS M&O 
2000q). The baseline for performance confirmation to address them will be information 
available from site characterization and pre-emplacement testing. This information will 
include the basis for estimates of the effects of thermal and stress perturbations. The 
information obtained in the performance confirmation program is to confirm these estimates 
and will serve to ascertain whether these elements are functioning as intended and 
anticipated, i.e., meet the design criteria established for them. See Section 5.3.1.8 and 
Appendix G of the Performance Confirmation Plan (CRWMS M&O 2000q). 
8. DOE has established a defensible program of monitoring 
and mechanical testing of the engineered sub-systems 
components, during the performance confirmation period, to 
assure they are functioning as intended and anticipated, in 
the presence of thermal and stress perturbations. 
This acceptance criterion pertains directly to the principal factors of the postclosure safety 
case associated with the degradation and performance of the WP and DS. These principal 
factors are also associated with performance confirmation factors and will be addressed 
through testing and analysis identified in the Performance Confirmation Plan (CRWMS M&O 
2000q). The baseline for performance confirmation to address them will be information 
available from site characterization and pre-emplacement testing. This information will 
include the basis for estimates of the effects of thermal and stress perturbations. The 
information obtained in the performance confirmation program is to confirm these estimates 
and will serve to ascertain whether these elements are functioning as intended and 
anticipated, i.e., meet the design criteria established for them. See Section 5.3.1.8 and 
Appendix G of the Performance Confirmation Plan (CRWMS M&O 2000q). 
SUBISSUE 5 - The effect of in-package criticality on WP and EBS performance 
Subissue 5 addresses the effects of in-package criticality on WP 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.

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
SUBISSUE 6 - The effects of alternate EBS design features on container lifetime and radionuclide release from the EBS 
1. DOE has identified and considered the effects of backfill, 
and the timing of its emplacement, on the thermal loading of 
the repository, WP lifetime (including container corrosion 
and mechanical failure), and the release of radionuclides 
from the EBS. 
Even though the EDA-II design includes backfill, the effects of the backfill are not 
considered in determining the environment on the surface DS and WP. 
2. DOE has identified and considered the effects of ceramic 
coating on WP lifetime, including negative consequences as 
a result of breakdown of the ceramic coating (cracking, 
spalling, or delamination) in response to the action of 
environment, manufacturing defects, mechanical impacts 
and stresses arising from a multiplicity of sources, and the 
potential for enhanced LC of the containers that might occur 
at cracks are perforations in the ceramic coating layers. 
This criterion is no longer applicable, as the current design for the repository does not 
include ceramic coatings. 
3. DOE has identified ceramic coating materials with outer 
overpack materials and the combined effect of ceramic 
coating with backfill on container lifetime. 
See response to Criterion 2. 
4. DOE has identified and considered the effects of DSs (with 
backfill) on WP lifetime, including extension of the humid-air 
corrosion regime, environmental effects, breakdown of DSs 
and resulting mechanical impacts on WP, the potential for 
crevice corrosion at the junction between the WP and the 
DS, and the potential for condensate formation and dripping 
on the underside of the shield. 
The effects of the DS have been considered and evaluated in the analysis of WP 
performance. This aspect is discussed in Section 3.2.3 of this document. The analysis 
conservatively assumes that the environment on the surface of the WP is not affected by the 
presence of the DS. Degradation model for the WP takes into account potential for crevice 
corrosion and degradation due to mechanical failure and assumes exposure to drift 
environment with no protection by DS against water dripping. The effects of the backfill with 
respect to changes in water chemistry are also not assumed since the current design does 
not include backfill. 
5. DOE has evaluated the effect of design changes in 
container wall thickness that may increase g-radiolysis of the 
water contacting WPs and, therefore, enhance the possible 
occurrence of LC processes. 
Experiments have been performed with Alloy 22 to accurately mimic the effects of gamma 
radiolysis. It is known that gamma radiolysis of aqueous electrolytes produces hydrogen 
peroxide, and that that hydrogen peroxide increases the open circuit corrosion potential of 
stainless steels. There has been concern that such effects could push the corrosion 
potential close to the threshold potential for the initiation of LC. Laboratory experiments 
have shown that the maximum increase in corrosion potential due to hydrogen peroxide in 
concentrated repository ground waters is approximately 200 mV, and insufficient to exceed 
the threshold for initiation of LC (See Section 3.1.6). 
6. DOE has identified the chemical composition of the water in 
the environment surrounding the WP and its evolution with 
time. 
This has been done through both evaporative concentration and thermodynamic calculation.

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
7. DOE has justified the use of test results for the DSs, ceramic 
coatings, and backfill materials not specifically collected for 
the Yucca Mountain site for the environmental conditions 
expected to prevail at the proposed Yucca Mountain 
repository 
At the present time, the ceramic coating is not part of the DS or WP design. 
8. DOE has conducted a consistent, sufficient, and suitable 
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(s) of uncertainty as part of the 
performance confirmation program. 
The design concept for the EBS includes Alloy 22 material for the WPOB and Titanium 
Grade 7 for the DS. Alternative EBS materials in each case are being evaluated as part of 
the design developmental testing, which will provide baseline information for the 
performance confirmation program for the selected materials. Only selected materials will 
be considered for continued evaluation in performance confirmation after submittal of the 
LA. Additional testing on alternative EBS materials may be conducted in mockup/
simulation testing to support assessment of design enhancements; however, this testing 
would only be considered as part of the performance confirmation program if an alternative 
material(s) were incorporated into the design through a license amendment and 
corresponding change to the performance confirmation program. As indicated, testing of 
the two different materials selected for the WP and DS will be conducted in the performance 
confirmation program (see Section 5.3.1.8 of the Performance Confirmation Plan) (CRWMS 
M&O 2000q). 
IRSR: TOTAL SYSTEM PERFORMANCE ASSESSMENT AND INTEGRATION 
SUBISSUE 1  System Description and Demonstration of Multiple Barriers 
Transparency and Traceability of the Analysis 
TSPA Documentation Style, Structure, and Organization 
Criterion T1 - Documents and reports are complete, clear, and 
consistent. 
The WP PMR was carefully structured to be complete, clear, and consistent. The review of 
the draft document included checks for completeness, clarity and consistency. 
Criterion T2 - Information is amply cross referenced. The WP PMR contains ample references to data sources, codes, assumptions, and 
conclusions. 
Features, Events, and Processes Identification and Screening 
Criterion T1 - The screening process by which FEPs were 
included or excluded from the TSPA is fully described. 
Section 1.6 of this PMR summarizes excluded and included FEPs including the rationale for 
these decisions. 
Criterion T2 - Relationships between relevant FEPs are fully 
described. 
Section 1.6 of this PMR describes the relationship between primary and secondary FEPs. 
The FEPs AMR provides additional documentation including the TSPA disposition of FEPs, 
IRSR issues relevant to specific FEPs, and analysis and discussion on specific FEPs.

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
Abstraction Methodology 
Criterion T1 - 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 WPD PMR, descriptions are provided of process models and, if the 
models are abstracted, descriptions of the abstractions of the models. The description 
includes a summary of data and assumptions used to construct models. The AMRs 
describing the models and the abstracted models provide additional details regarding data 
and assumptions. 
Criterion T2 - A mapping (e.g., a road map diagram, a traceability 
matrix, a cross-reference 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 WPD PMR provides a sufficient basis for the decisions and assumptions that were 
made during the abstraction process. 
Criterion T3 - 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 WPD PMR (Section 3.1.9) provides a discussion of uncertainties and limitations for the 
major process models included in the report. The AMRs describing the abstracted models 
provide additional details regarding uncertainties and limitations. 
Data Use and Validity 
Criterion T1 - The pedigree of data from laboratory tests, natural 
analogs, and the site is clearly identified. 
Section 1.4 of this PMR summarizes the QA status of the data and software used in the 
component models. 
Criterion T2 - Input parameter development and basis for their 
selection is described. 
The WPD PMR discusses input parameter development and the basis for using the 
parameters. The AMRs describing the models provide additional details regarding input 
parameter development and the basis for input selection. 
Criterion T3 - A thorough description of the method used to 
identify performance confirmation program parameters. 
The Performance Confirmation Plan (CRWMS M&O 2000q) 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 
Criterion T1 - 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 WPD PMR.

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
Criterion T2 - 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 
Criterion T1 - 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. 
Criterion T2 - 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  Total System Performance Assessment Methodology: Scenario Analysis 
Identification of an Initial Set of Processes and Events Data 
Criterion T1 - DOE has identified a comprehensive list of 
processes and events that: (1) are present or might occur in the 
Yucca Mountain region and (2) includes those processes and 
events that have the potential to influence repository 
performance. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides a list of the processes and events applicable to this PMR. 
The AMR provides a description of the screening arguments and dispositions for the FEPs 
and has been thoroughly reviewed by subject matter experts. In addition, the AMR 
describes the development of the FEPs database, including a description of the FEPs 
process in sufficient detail to demonstrate the comprehensiveness of the database. 
Classification of Processes and Events 
Criterion T1 - DOE has provided adequate documentation 
identifying how its initial list of processes and events has been 
grouped into categories. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides documentation and justification for screening arguments 
and dispositions. Documentation is maintained of all mapping of FEPs into primary and 
secondary categories. For comprehensiveness, traceability is maintained from the 
secondary to the related primary FEPs. The AMR also describes the development of the 
FEPs database, including identifying and classifying relevant FEPs. 
Criterion T2 - Categorization of processes and events is 
compatible with the use of categories during the screening of 
processes and events. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section, 
(CRWMS M&O 2000s), provides documentation and justification for screening arguments 
and dispositions. Documentation is maintained of all mapping of FEPs into primary and 
secondary categories. For comprehensiveness, traceability is maintained from the 
secondary to the related primary FEPs. The AMR also describes the development of the 
FEPs database, including identifying and classifying relevant FEPs.

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
Screening of Presses and Events 
Criterion T1 - 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. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides documentation and justification for screening arguments 
and TSPA dispositions. Documentation includes 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. 
Criterion T2 - The probability assigned to each category of 
processes and events is consistent with site information, well 
documented, and appropriately considers uncertainty. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides documentation and justification for screening arguments 
and dispositions. Probability estimates for FEPs are based on technical analysis of the past 
frequency of similar events 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 than one chance in 10,000 
of occurring over 10,000 years. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides documentation and justification for screening arguments 
and TSPA dispositions. Justification is provided for each excluded FEP including the 
criterion on which it was excluded and the technical basis for the screening argument. For 
excluded FEPs, documentation includes the criterion on which it was excluded and the 
technical basis for the screening argument. The probability assigned to FEPs may be one 
of the screening criteria. FEPs may be excluded only if they can be shown to have a 
probability of occurrence of less than 10-8/year. 
Criterion 4 - 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. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides documentation and justification for screening arguments 
and TSPA dispositions. For omitted categories, documentation includes the criterion on 
which it was excluded and the technical basis for the screening argument. 
Formation of Scenarios 
Criterion 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. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides documentation and justification for screening arguments 
and TSPA dispositions. FEPs that have not been excluded are identified as either expected 
FEPs or disruptive FEPs. Expected FEPs will be included in the TSPA-SR nominal 
scenario, which is simulated by the base case model described in the TSPA-SR 
documentation. Disruptive scenarios are constructed from expected FEPs and 
combinations of disruptive FEPs. 
Criterion 2 - The set of scenario classes is mutually exclusive 
and complete. 
Section 1.6 of this PMR describes the FEP in this PMR. The AMR supporting this section 
(CRWMS M&O 2000s) provides documentation and justification for screening arguments 
and TSPA dispositions. In addition, the AMR describes the development of the FEPs 
database including a description of the construction and screening of scenarios.

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Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
Screening of Scenario Classes 
Criterion 1 - Scenario classes that are not credible for the YM 
repository because of waste characteristics, repository design, or 
site characteristics - individually or in combination - are identified 
and sufficient justification is provided for DOEs conclusions. 
TSPA provides justification for screening arguments and TSPA disposition. Scenarios are 
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. 
Criterion 2 - The probability assigned to each scenario class is 
consistent with site information, well documented, and 
appropriately considers uncertainty. 
TSPA provides justification for screening arguments and TSPA disposition. Probability 
estimates for scenario classes are based on analyses similar to probabilities assigned for 
individual FEPs. 
Criterion 3 - Scenario classes that combine categories of 
processes and events may be screened from the PA 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. 
TSPA provides justification for excluding scenario classes. The probability assigned to 
scenario classes is one of the screening criteria. Scenario classes may be excluded from 
the TSPA only if they can be shown to have a probability of occurrence of less than 10- 
8/year. Justification is provided for each excluded scenario class, including the criterion on 
which it was excluded and the technical basis for the screening argument. In addition, the 
AMR describes the development of the FEPs database including a description of screening 
and specifying scenarios for TSPA analysis. 
Criterion 4 - Scenario classes may be omitted from the PA 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. 
TSPA provides justification for excluding scenario classes. For excluded scenario classes, 
documentation includes the criterion on which it was excluded and the technical basis for 
the screening argument. In addition, the AMR describes the development of the FEPs 
database including a description of screening and specifying scenarios for TSPA analysis. 
SUBISSUE 3  Total System Performance Analysis Methodology: Model Abstraction 
Engineered Barrier Degradation 
Criterion T1 - Data and Model Justification 
Sufficient data (field, laboratory or natural analog data) are 
available to adequately define relevant parameters and 
conceptual models necessary for developing the WP corrosion 
abstraction in TSPA. Where adequate data do not exist, other 
information sources such as expert elicitation have been 
appropriately incorporated into the TSPA. 
The TSPA model requires estimates of corrosion and threshold potentials, both of which are 
determined through electrochemical testing. Thus far, CP has been done in a wide variety 
of repository-relevant test solutions, including SDW, SCW, SAW, SCMW, SSW, and BSW. 
The CP tests are now being conducted in these media with artificial crevices. Experiments 
have been performed to quantify the extent that pH can be lowered inside crevices, formed 
between the Alloy 22 WPOB and the 316NG SSSM. The TSPA model also requires 
estimates of GC rates. Testing in the LTCTF is continuing. Two-year test data has become 
available and is included in this PMR. These two-year test data are an integral part of the 
WAPDEG simulation (Sections 3.1.5 and 3.2).

TD-WIS-MD-000002 REV 00 ICN 01 4-18  
Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
Criterion T2 - Data Uncertainty 
Parameter values, assumed ranges, probability distributions, and 
bounding assumptions used in the WP corrosion abstraction, 
such as the critical RH, material properties, pH, and chloride 
concentration are technically defensible and reasonably account 
for uncertainties and variabilities. 
Model abstractions for various corrosion modes include the aspects of this criterion and 
documented in the supporting AMRs and Section 3-2 of this PMR. 
Criterion T3 - Model Uncertainty 
Alternative modeling approaches consistent with available data 
and current scientific understanding are investigated and results 
and limitations appropriately factored into the WP corrosion 
abstraction. 
Where possible, alternative models are considered. For example, consider methods A and 
B in the SCC model. Method A is based upon the concept of a threshold stress intensity 
factor. Method B is based upon the slip dissolution or film rupture model used in the BWR 
industry. Both are accounted for in the PMR and TSPA calculation. Also consider 
methods A and B in the LC model. Method A is based upon the concept of exceeding a 
threshold electrochemical potential for the initiation of LC (crevice corrosion). Method B is 
based upon the concept of exceeding a threshold temperature of the initiation of LC (crevice 
corrosion). 
Criterion T4 - Model Support 
WP corrosion abstraction output is justified through comparison 
to output of detailed process models or empirical observations 
(laboratory testings, natural analogs, or both). 
Output from WAPDEG is being compared to experimental measurements used as the basis 
of calculations to verify that correct and reasonable results are obtained. 
Criterion T5 - Integration 
Important design features, physical phenomena and couplings, 
and consistent and appropriate assumptions are incorporated 
into the WP corrosion abstraction. 
The WP degradation model assumes conservative environmental and exposure conditions. 
WAPDEG code incorporates bounding conditions for the various corrosion modes that 
envelop effects of design features and couplings. 
Mechanical disruption of Engineered Barrier 
Criterion T4 - Model Support 
Mechanical disruption of the engineered barriers abstraction 
output is justified through comparison to output of detailed 
process models or empirical observations (laboratory testing, 
natural analogs, or both). 
Abstraction of mechanical failure of WP due to disruptive events is not in the scope of this 
PMR. However, will be addressed in addressed in the Disruptive Events PMR.

TD-WIS-MD-000002 REV 00 ICN 01 4-19  
Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
Criterion T5 - Integration 
Important design features, physical phenomena and couplings, 
and consistent and appropriate assumptions are incorporated 
into the mechanical disruption of the engineered barriers 
abstraction. 
Abstraction of mechanical failure of WP due to disruptive events is not in the scope of this 
PMR. However, will be addressed in addressed in the Disruptive Events PMR. 
Quantity and chemistry of water contacting WPs and WFs 
Criterion T1 - Sufficient data (field, laboratory, 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 abstraction 
in a TSPA. Where adequate data do not exist, other information 
sources such as expert elicitation have been appropriately 
incorporated into the TSPA. 
Laboratory experiments have been conducted to determine the type of waters that may 
contact the WP and the drip shield. Evaporative concentration of these waters have been 
performed to determine bounding concentrations of the solution that is likely to form on the 
surfaces of the WP and the drip shield. The results of these studies were documented in an 
AMR (CRWMS M&O 2000a) and in Section 3.1.3. This information has been abstracted for 
use in the integrated model in WAPDEG. The waste form aspects of this criterion are 
addressed in the Waste Form PMR. No expert elicitation was used. 
Criterion T2 - 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. 
The parameters used for defining the chemistry of water contacting the WPs are based on 
bounding assumptions. The threshold humidity required for maintaining an aqueous film on 
the surface deposits (the deliquescence point of NaNO3) formed the bounding condition for 
the relative humidity. The bounding chemistry was assumed to be that expected from the 
evaporative concentration of the expected Yucca Mountain waters. (CRWMS M&O 2000a, 
PMR section 3.1.3). The expected quantity of water contacting the WP is not included in the 
AMR as the corrosion models are not affected by this parameter. The waste form aspects of 
this criterion are addressed in the Waste Form PMR. 
Criterion T3  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. 
The chemistry of the waters contacting the WPs was bounded by the assumptions of 
evaporative concentration of the water and therefore alternative models are not included in 
the AMR. Alternative models based on this bounding chemistry for the various degradation 
modes for the WP and the drip shield were evaluated in each of the specific AMRs and also 
briefly discussed in Section 3.1.11 of this PMR. The waste form aspects of this criterion are 
addressed in the Waste Form PMR. 
Criterion T4 - Output of quantity and chemistry of water 
contacting WPs and waste forms abstraction are supported by 
comparison to output of detailed process models or empirical 
observations (laboratory testing, natural analogs, or both). 
Chemistry of the contacting water was determined by laboratory testing. No process model 
was developed for this data but the results of this testing were used for developing corrosion 
test data and process models for material degradation. The quantity of water contacting the 
WP was not addressed as the degradation models assume bounding chemistries and are 
independent of the quantity. The waste form aspects of this criterion are addressed in the 
Waste Form PMR. 
Criterion T5 - 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. 
The analysis for the environment on the surface of the WP is bounding and is based on 
laboratory testing and is documented in the AMR (CRWMS M&O 2000a) does not take into 
account the benefits of the design features such as the backfill, and the drip shield. This is 
to provide a conservative approach. The quantity of the water contacting the WP is not 
addressed in the PMR.

TD-WIS-MD-000002 REV 00 ICN 01 4-20  
Table 4-1. Issue Resolution Status Reports, Subissues, Technical Acceptance Criteria, and PMR Approach (Continued) 
NRC Technical Acceptance Criteria PMR Approach 
IRSR: REPOSITORY DESIGN AND THERMAL-MECHANICAL EFFECTS, REV. 2 
Subissue 3  Thermal-Mechanical Effects on Underground Facility design and Performance 
Component 2: Effects of Seismically Induced Rockfall on WP 
Criterion 1  Approved quality assurance and control procedures 
and standards are applied to collection, development, and 
documentation of data, methods, models, and codes. 
This PMR and its supporting AMRs were developed in accordance with project procedures 
for documenting data, analyses, models, and/or computer codes and preparing and 
reviewing technical reports (see Section 1.4). 
Criterion 2  If used, expert elicitation is conducted and 
documented in accordance with the guidance in NUREG-1563 or 
other acceptable approaches. 
No expert elicitation results or data have been used in preparation of this PMR. 
Criterion 5  The analytical model used in the estimation of 
impact load due to rockfall on the WP is: (I) based on reasonable 
assumptions and site data; (ii) consistent with the underground 
facility (emplacement drift geometry and backfill) and WP design; 
and (iii) defensible with respect to providing realistic or bounding 
estimates of impact loads and stresses. 
The rockfall impact analysis for WP is based on reasonable assumptions on site data and 
on engineered barrier system design. The analyses does not include the presence of 
backfill. A separate analyses for drip shield has also been performed. The analyses use 
bounding assumptions with respect to rock size distribution.

 5-1  
5. SUMMARY AND CONCLUSIONS 
Performance of a potential monitored geologic repository at Yucca Mountain for high-level 
radioactive waste depends on both the natural barrier system and the EBS and on their 
interactions. As a major component of the EBS, the WP contributes to isolation of high-level 
radioactive waste during the postclosure period and reduces the uncertainties associated with the 
performance of the repository. It is expected that the WP protected by a DS will be exposed to 
processes and conditions in the repository environment that will eventually have an impact on its 
postclosure performance. Some of the important conditions contributing to WP degradation 
include: humidity and temperature in the emplacement drift, chemistry of the water dripping 
onto the WP, and corrosion properties of the WPOB. As part of the performance-based riskinformed 
evaluation of postclosure repository performance, it is important to understand and 
account for degradation processes that will impact the WP lifetime. This document describes 
how WP and DS degradation processes are modeled, analyzed, and combined into an overall 
degradation model; the results from the model are incorporated into the assessment of the 
postclosure repository total system performance. This PMR also addresses KTIs and IRSRs of 
the NRC and the approach to the resolution of the issues. In addition, issues on repository 
performance raised by other agencies such as NWTRB are addressed. 
A variety of anticipated modes of WP degradation under the most important environmental 
conditions including thermal, hydrological, and geochemical conditions have been considered 
and analyzed as part of an integrated degradation process model. The WP degradation process 
model consists of individual process models or analyses and associated abstraction models. 
These models address the environment on the degradation of the WP and DS and consider 
various degradation modes including early material failure due to manufacturing and fabrication 
defects, phase stability and aging, GC, LC, stress corrosion cracking, and hydrogen-induced 
cracking. A generic integrated model constructed based on abstracted results from individual 
component models is then applied to the WP and DS materials to determine their overall 
performance. A detailed discussion of the WP and DS degradation processes within the NFE 
and the analytical results from the process-level models are documented in the individual AMRs. 
Following is a list of the process-level models: 
 Environment on the Surface of DS and WPOB 
 Mechanisms for Early Failures 
 Aging and Phase Stability of WPOB 
 GC and LC of WPOB 
 GC and LC of DS 
 SCC of the DS, the WPOB and the Stainless Steel Structural Material 
 Hydrogen-Induced Cracking (HIC) of DS 
 Degradation of Stainless Steel Structural Material.

 5-2  
Abstraction of ModelsAbstraction results from the detailed process-level models listed above 
are used as input to the WP degradation (WAPDEG) model for evaluation of the performance of 
the WPOB and DS materials. These abstractions include thresholds for corrosion initiation and 
degradation rate with the associated uncertainty and variability. The WAPDEG analysis results 
are further abstracted as input to the TSPA-SR analysis. The abstractions include the timehistories 
of WP failures including the number of penetrations on WPs and the size distribution of 
penetration openings on WPs including the associated uncertainties. The TSPA-SR uses the 
results of the abstraction and synthesis of WP degradation information in PA to determine WP 
lifetime and potential impact on long-term repository performance. 
Analysis ResultsAbstracted results from the process models described above, along with 
abstracted results for the drift environment were used as input in the integrated degradation 
model, WAPDEG. The WAPDEG model, an integrated degradation model, is used for WP and 
DS degradation analysis and to determine the failure time. This integrated model is based on a 
stochastic simulation approach and provides a description of waste package and DS degradation, 
as a function of time and repository location for specific design and thermal-hydrologic 
modeling assumptions. Each WAPDEG realization corresponds to a complete WAPDEG run for 
a given number of waste packages. Accordingly, the WAPDEG analysis outputs are reported as 
a group of curves representing the potential range of the output parameters. The nominal case 
analysis for WP and DS degradation constitutes 100 realizations of WAPDEG simulation that 
uses 100 input vectors for uncertain corrosion model parameters and simulation parameters that 
were sampled from their respective ranges. 
Except for the RH threshold for corrosion initiation, the temperature and RH do not affect WP 
and DS degradation. For this reason, representative sets of temperature and RH histories were 
used in the analysis. In addition, the threshold for LC initiation of the DS and WPOB requires 
the presence of drips and is much higher than the conditions expected in the repository. 
Therefore, LC is not expected. The analysis assumed WP failure when the Alloy 22 outer barrier 
has breached. Therefore, the stainless steel inner structural layer of WP was not considered in 
the analysis, as this component is not viewed as a corrosion barrier. 
The WP and DS degradation analyses have shown that based on the current corrosion model 
abstractions and assumptions presented in this PMR, both the DSs and WPs do not fail within the 
regulatory time period (10,000 years). In particular, the WP service lifetime is predicted to 
extend far beyond the regulatory time period (failure beginning at about 50,000 years). The 
materials selected for the DS (Titanium Grade 7, an analog of Titanium Grade 16, which has 
been used for experiments) and the WPOB (Alloy 22) are highly corrosion resistant and, under 
the repository exposure conditions, are expected to be immune to the degradation processes that, 
if initiated, could lead to failure in a shorter time period. Those degradation modes are LC 
(pitting and crevice corrosion), SCC, and HIC (applicable to the DS only). Both the DS and WP 
degrade by GC at very low passive dissolution rates. The current experimental data and detailed 
process-level analyses, upon which the model abstractions incorporated in the WAPDEG 
analysis are based, have also indicated that the candidate materials would not be subject to those 
rapidly penetrating corrosion modes under the expected repository conditions, except for 
possibly the closure-lid welds of the WP, if SCC were to occur there. To preclude SCC, weld 
stress mitigation will be implemented on a dual-lid WP closure weld design.

 5-3  
The estimated long life-time of the WPs in the current analysis is attributed mostly to 1) the 
depth of the stress mitigation in the dual-closure-lid welds and 2) the very low general-corrosion 
rate of the closure-lid welds, which requires a very long time to corrode away the compressive 
stress zones, thus providing a very long delay time before initiating SCC crack growth. 
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 
(DIRS) database.

 5-4  
INTENTIONALLY LEFT BLANK

 6-1  
6. REFERENCES 
6.1 DOCUMENTS CITED 
ASM International 1987. Corrosion. Volume 13 of Metals Handbook. 9th Edition. Metals Park, 
Ohio: ASM International. TIC: 209807. 
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. 
Cohon, J.L. 1999a. Reaction to Information Presented by the DOE, September 14-15, 1999 
Nuclear Waste Technical Review Board Meeting. Letter from J.L. Cohon (NWTRB) to L.H. 
Barrett (DOE/OCRWM), November 10, 1999. ACC: MOL.20000321.0152. 
Cohon, J.L. 1999b. Comments on the Scientific Program, June 1999 Nuclear Waste Technical 
Review Board Meeting. "Letter from J.L. Cohon (NWTRB) to L.H. Barrett (OCRWM), August 
3, 1999." ACC: MOL.20000317.0405. 
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 1996. Waste Package Materials Selection Analysis. BBA000000-01717-0200- 
00020 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19961203.0112. 
CRWMS M&O 1998a. Total System Performance Assessment - Viability Assessment Base Case. 
B00000000-01717-0210-00011 REV 01. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.19981202.0279. 
CRWMS M&O 1998b. "Waste Package Degradation Modeling and Abstraction." Chapter 5 of 
Total System Performance Assessment-Viability Assessment (TSPA-VA) Analyses Technical 
Basis Document. B00000000-01717-4301-00005 REV 01. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.19981008.0005. 
CRWMS M&O 1999a. Monitored Geologic Repository Project Description Document. 
B00000000-01717-1705-00003 REV 00 DCN 01. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.19991117.0160. 
CRWMS M&O 1999b. Development Plan for Waste Package Degradation Process Model 
Report. TDP-WIS-MD-000030 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.19991220.0375.

 6-2  
CRWMS M&O 1999c. Classification of the MGR Uncanistered Spent Nuclear Fuel Disposal 
Container System. ANL-UDC-SE-000001 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.19990928.0216. 
CRWMS M&O 1999d. 1101213PM7 Waste Package Analyses & Models - PMR. Activity 
Evaluation, September 21, 1999. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.19991012.0219. 
CRWMS M&O 1999e. Requirements Document for WAPDEG 4.0. STN: 10000-4.0-00, SDN: 
10000-RD-4.0-00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19991025.0069. 
CRWMS M&O 1999f. Waste Package Material Properties. BBA000000-01717-0210-00017 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19990407.0172. 
CRWMS M&O 2000a. Environment on the Surfaces of the Drip Shield and Waste Package 
Outer Barrier. ANL-EBS-MD-000001 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000328.0590. 
CRWMS M&O 2000b. Aging and Phase Stability of Waste Package Outer Barrier. ANL-EBSMD-
000002 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000410.0407. 
CRWMS M&O 2000c. General Corrosion and Localized Corrosion of Waste Package Outer 
Barrier. ANL-EBS-MD-000003 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000202.0172. 
CRWMS M&O 2000d. General Corrosion and Localized Corrosion of the Drip Shield. ANLEBS-
MD-000004 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000329.1185. 
CRWMS M&O 2000e. Degradation of Stainless Steel Structural Material. ANL-EBS-MD- 
000007 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000329.1188. 
CRWMS M&O 2000f. Stress Corrosion Cracking of the Drip Shield, the Waste Package Outer 
Barrier and the Stainless Steel Structural Material. ANL-EBS-MD-000005 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.20000504.0312. 
CRWMS M&O 2000g. WAPDEG Analysis of Waste Package and Drip Shield Degradation. 
ANL-EBS-PA-000001 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000526.0332. 
CRWMS M&O 2000h. Hydrogen Induced Cracking of Drip Shield. ANL-EBS-MD-000006 
REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000329.1179.

 6-3  
CRWMS M&O 2000i. Calculation of General Corrosion Rate of Drip Shield and Waste 
Package Outer Barrier to Support WAPDEG Analysis. CAL-EBS-PA-000002 REV 00. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000319.0047. 
CRWMS M&O 2000j. Abstraction of Models of Stress Corrosion Cracking of Drip Shield and 
Waste Package Outer Barrier and Hydrogen Induced Corrosion of Drip Shield. ANL-EBS-PA- 
000004 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000526.0326. 
CRWMS M&O 2000k. Calculation of Probability and Size of Defect Flaws in Waste Package 
Closure Welds to Support WAPDEG Analysis. CAL-EBS-PA-000003 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.20000424.0676. 
CRWMS M&O 2000l. Not used. 
CRWMS M&O 2000m. Analysis of Mechanisms for Early Waste Package Failure. ANL-EBSMD-
000023 REV 01. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000223.0878. 
CRWMS M&O 2000n. Abstraction of Models for Pitting and Crevice Corrosion of Drip Shield 
and Waste Package Outer Barrier. ANL-EBS-PA-000003 REV 00. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.20000526.0327. 
CRWMS M&O 2000o. Abstraction of Models for Stainless Steel Structural Material 
Degradation. ANL-EBS-PA-000005 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000526.0337. 
CRWMS M&O 2000p. Incorporation of Uncertainty and Variability of Drip Shield and Waste 
Package Degradation in WAPDEG Analysis. ANL-EBS-MD-000036 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.20000526.0333. 
CRWMS M&O 2000q. Performance Confirmation Plan. TDR-PCS-SE-000001 REV 01. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000302.0312. 
CRWMS M&O 2000r. Drift Scale Thermal Analysis. CAL-WIS-TH-000002 REV 00. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.20000420.0401. 
CRWMS M&O 2000s. FEPs Screening of Processes and Issues in Drip Shield and Waste 
Package Degradation. ANL-EBS-PA-000002 REV 00. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20000526.0334. 
CRWMS M&O 2000t. Emplacement Drift System Description Document. SDD-EDS-SE- 
000001 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000121.0119. 
CRWMS M&O 2000u. Waste Package Operations Fabrication Process Report. TDR-EBS-ND- 
000003 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000217.0244.

 6-4  
CRWMS M&O 2000v. Disruptive Events FEPs. ANL-WIS-MD-000005 REV 00. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.20000501.0227. 
CRWMS M&O 2000w. 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 2000x. Internal Pressurization Due to Fuel Rod Rupture in Waste Packages. 
CAL-EBS-ME-000005 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: 
MOL.20000315.0671. 
Deutsch, C.V. and Journel, A.G. 1992. GSLIB Geostatistical Software Library and Users 
Guide. New York, New York: Oxford University Press. TIC: 224174. 
DOE (U.S. Department of Energy) 1995. The Nuclear Waste Policy Act, As Amended. With 
Appropriations Acts Appended. DOE/RW-0438, Rev. 1. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: HQO.19950124.0001. 
DOE (U.S. Department of Energy) 1998. Total System Performance Assessment. Volume 3 of 
Viability Assessment of a Repository at Yucca Mountain. DOE/RW-0508. Washington, D.C.: 
U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: 
MOL.19981007.0030. 
DOE (U.S. Department of Energy) 2000. Quality Assurance Requirements and Description. 
DOE/RW-0333P, Rev. 10. Washington, D.C.: U.S. Department of Energy, Office of Civilian 
Radioactive Waste Management. ACC: MOL.20000427.0422. 
Dyer, J.R. 1999. "Revised Interim Guidance Pending Issuance of New U.S. Nuclear Regulatory 
Commission (NRC) Regulations (Revision 01, July 22, 1999), for Yucca Mountain, Nevada." 
Letter from J.R. Dyer (DOE/YMSCO) to D.R. Wilkins (CRWMS M&O), September 3, 1999, 
OL&RC:SB-1714, with enclosure, "Interim Guidance Pending Issuance of New NRC 
Regulations for Yucca Mountain (Revision 01)." ACC: MOL.19990910.0079. 
Erbing Falkland, M.L. 2000. "Duplex Stainless Steels." Uhlig's Corrosion Handbook. Revie, 
R.W., ed. 2nd Edition. 651-666. New York, New York: John Wiley & Sons. TIC: 247904. 
Copyright Requested Library Tracking Number-247904. 
Haynes International. 1993. Haynes 625 Alloy. Kokomo, Indiana: Haynes International. TIC: 
239935. 
Khaleel, M.A.; Chapman, O.J.V.; Harris, D.O.; and Simonen, F.A. 1999. "Flaw Size Distribution 
and Flaw Existence Frequencies in Nuclear Piping." Probabilistic and Environmental Aspects of 
Fracture and Fatigue: The 1999 ASME Pressure Vessels and Piping Conference. PVP-386, 127- 
144. New York, New York: American Society of Mechanical Engineers. TIC: 245621.

 6-5  
Kotra, J.P.; Lee, M.P.; Eisenberg, N.A.; and DeWispelare, A.R. 1996. Branch Technical 
Position on the Use of Expert Elicitation in the High-Level Radioactive Waste Program. 
NUREG-1563. Washington, D.C.: U.S. Nuclear Regulatory Commission. TIC: 226832. 
Lu, J. ed. 1996. Handbook of Measurement of Residual Stresses. Lilburn, Georgia: Fairmont 
Press. On Order Library Tracking Number-247903. 
Mohr, W.C. 1996. "Internal Surface Residual Stresses in Girth Butt-Welded Steel Pipes ." 
Residual Stresses in Design, Fabrication, Assessment and Repair, PVP-Vol. 321, 37-44. New 
York, New York: American Society of Mechanical Engineers. TIC: 247502. 
NRC (U.S. Nuclear Regulatory Commission) 1999a. Issue Resolution Status Report Key 
Technical Issue: Container Life and Source Term. Rev. 2. Washington, D.C.: U.S. Nuclear 
Regulatory Commission. TIC: 245538. 
NRC (U.S. Nuclear Regulatory Commission) 1999b. Issue Resolution Status Report Key 
Technical Issue: Repository Design and Thermal-Mechanical Effects. Rev. 02. Washington, 
D.C.: U.S. Nuclear Regulatory Commission. ACC: MOL.20000306.0670. 
NRC (U.S. Nuclear Regulatory Commission) 2000. Issue Resolution Status Report Key 
Technical Issue: Total System Performance Assessment and Integration. Rev. 2. Washington, 
D.C.: U.S. Nuclear Regulatory Commission. TIC: 247614. 
Pasupathi, V. 2000. Documentation of Literature on Residual Stress Measurements. Interoffice 
correspondence from V. Pasupathi (CRWMS M&O) to G.M. Gordon, May 19, 2000, 
LV.WP.VP.05/00-070, with enclosures. ACC: MOL.20000522.0146. 
Shcherbinskii, V.G. and Myakishev, V.M. 1970. "Statistical Distribution of Welding Defects 
with Respect to Azimuth." No. 4, July-August, 1970, 1971 Central Scientific Research Institute 
of Technical Engineering, translated from Defektoskopiya. UDC 620.179.16. 143-144. New 
York, New York: Plenum Publishing Corporation. Copyright Requested Library Tracking 
Number-247890. 
YMP (Yucca Mountain 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. 
6.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
64 FR 46976. 40 CFR 197: Environmental Radiation Protection Standards for Yucca Mountain, 
Nevada; Proposed Rule. Readily Available

 6-6  
ASME (American Society of Mechanical Engineers) 1995. "Materials." Section II of 1995 
ASME Boiler and Pressure Vessel Code. New York, New York: American Society of 
Mechanical Engineers. TIC: 245287. 
ASTM B 443 - 93. 1995. Standard Specification for Nickel-Chromium-Molybdenum-Columbium 
Alloy (UNS N06625)* Plate, Sheet, and Strip 1. Philadelphia, Pennsylvania: American Society 
for Testing and Materials. TIC: 237693. 
ASTM B 575-99a. 1999. Standard Specification for Low-Carbon Nickel-Molybdenum- 
Chromium, Low-Carbon Nickel-Chromium-Molybdenum, Low-Carbon Nickel-Chromium- 
Molybdenum-Copper, Low-Carbon Nickel-Chromium-Molybdenum-Tantalum, and Low-Carbon 
Nickel-Chromium-Molybdenum-Tungsten Alloy Plate, Sheet, and Strip. West Conshohocken, 
Pennsylvania: American Society for Testing and Materials. TIC: 247534. 
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 G 1-90 (Reapproved 1999). 1990. Standard Practice for Preparing, Cleaning, and 
Evaluating Corrosion Test Specimens. West Conshohocken, Pennsylvania: American Society for 
Testing and Materials. TIC: 238771. 
ASTM G 5 - 94. Standard Reference Test Method for Making Potentiostatic and 
Potentiodynamic Anodic Polarization Measurements. Philadelphia, Pennsylvania: American 
Society for Testing and Materials. TIC: 231902. 
ASTM G 61-86 (Reapproved 1998). 1987. Standard Test Method for Conducting Cyclic 
Potentiodynamic Polarization Measurements for Localized Corrosion Susceptibility of Iron-, 
Nickel-, or Cobalt-Based Alloys. West Conshohocken, Pennsylvania: American Society for 
Testing and Materials. TIC: 246716. 
ASTM G1-81. 1987. Standard Practice for Preparing, Cleaning, and Evaluating Corrosion Test 
Specimens. Philadelphia, Pennsylvania: American Society for Testing and Materials. TIC: 
246089. 
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-3.10Q, Rev. 02, ICN 1. Analyses and Models. Washington D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20000512.0066. 
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.

 6-7  
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-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. 
QAP-2-0 Rev. 5, ICN 1. Conduct of Activities. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.19991109.0221. 
QAP-2-3, Rev. 10. Classification of Permanent Items. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.19990316.0006. 
6.3 SOURCE DATA 
MO9910SPAFWPWF.001. Weld Flaws of Waste Packages. Submittal date: 10/22/1999.

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