Aging and Phase Stability of Waste Package Outer Barrier Rev 01, ICN 00

ANL-EBS-MD-000002

June 2003

1. PURPOSE 
1.1 SUMMARY OF MODEL 
The Aging and Phase Stability of Waste Package Outer Barrier Analysis/Model Report (AMR) 
revision was prepared according to Technical Work Plan for: Waste Package Materials Data 
Analyses and Modeling (BSC 2002 [DIRS 161132]). This report provides information on the 
phase stability of Alloy 221, the current waste-package-outer-barrier (WPOB) material. These 
phase stability studies are currently divided into three general areas: 
 TCP (tetrahedrally closed-pack) phase and carbide precipitation in the base metal 
 TCP and carbide precipitation in welded samples 
 Long-range ordering reactions. 
TCP phase and carbide precipitates that form in Alloy 22 are generally rich in chromium (Cr) 
and/or molybdenum (Mo) (Raghavan et al. 1984 [DIRS 154707]). Because these elements are 
responsible for the good corrosion resistance of Alloy 22, precipitation of TCP phases and 
carbides, especially at grain boundaries, can lead to an increased susceptibility to localized 
corrosion in the alloy. These phases are brittle and also tend to embrittle the alloy (Summers et 
al. 1999 [DIRS 146915]). They are known to form in Alloy 22 at temperatures greater than 
approximately 600C. Whether these phases also form at the lower temperatures expected in the 
proposed repository in times up to approximately 10,000 years must be determined. The kinetics 
of this precipitation will be determined for both the base metal and the weld heat-affected zone 
(HAZ). 
The TCP phases P, , and  are present in the weld metal in the as-welded condition. It may be 
possible to eliminate these phases through a solution anneal heat treatment, but that may not be 
possible for the closure weld because the spent-nuclear-fuel cladding cannot be heated to more 
than 350C. The effects of any stress mitigation techniques, such as laser peening or solution 
heat treating, that may be used to reduce the propensity for stress corrosion cracking on the 
properties and aging response of the welds, must also be determined. Cold-work will cause an 
increase in dislocation density, and such an increase in dislocation density may cause an increase 
in diffusion rates which control precipitation kinetics (Porter et al. 1992 [DIRS 161265]; 
Tawancy et al. 1983 [DIRS 104991]). 
1 The designation Alloy 22 is used in this report to indicate the alloy composition given by the Society of 
Automotive Engineers (SAE)  American Society of Testing and Materials (ASTM) Unified Numbering System 
(UNS) N06022. A number of manufacturers produce material within this UNS specification. This alloy is sold and 
often referred to in the technical literature by names such as Hastelloy Alloy C22, Inconel Alloy 622, Allegheny 
Alloy AL22, and possibly others. The designation Alloy 22 is therefore a generalized designation that covers all of 
these alloys. 
  
Long-range order (LRO) occurs in nickel (Ni)CrMo alloys such as Alloy 22 at temperatures 
less than approximately 600C. This ordering has been linked to an increased susceptibility of 
NiCrMo alloys to stress corrosion cracking (SCC) and hydrogen embrittlement (Tawancy et 
al. [DIRS 104991]). These analyses will provide information on the rate at which LRO may 
occur in Alloy 22 under repository conditions. 
Determination of the kinetics of transformations through experimental techniques requires that 
the transformations being investigated be accelerated, at least in this case in which service life is 
expected to be approximately 10,000 years. Phase transformations are typically accelerated 
through an increase in temperature. The rate of transformation is determined at the higher 
temperature and is extrapolated to the lower temperatures of interest. 
1.2 INTENDED USE OF MODEL 
In the mill-annealed condition, Alloy 22 (UNS N06022) is primarily a single-phase, facecentered 
cubic (fcc), solid solution with excellent corrosion resistance over a wide range of 
environmental conditions. Over time, other phases may precipitate and degrade both the 
mechanical properties and corrosion resistance of the alloy. The goal of this model is to 
determine whether the single-phase solid solution is stable under expected repository conditions, 
and if not, how fast other phases may precipitate. Precipitation kinetics in the annealed base 
metal, as well as in the annealed and laser-peened welds, are considered. 
The objective of this Aging / Phase Stability (APS) model is to provide a quantitative model 
which can be used to predict the amount of any phases forming as a function of both time and 
temperature. Due to the long time periods of interest (up to approximately 10,000 years), it is 
not practical to obtain or generate data on the metallurgical stability of Alloy 22 using test 
durations of this magnitude. As a result, the APS model, which is based on fundamental 
thermodynamic and kinetic concepts and principles, will be used to provide predictive insight 
into the long-term metallurgical stability of Alloy 22 under relevant repository conditions. Thus, 
there are no direct inputs from the APS model to Total System Performance Assessment (TSPA). 
  13  
2. QUALITY ASSURANCE 
This revision of the AMR has been developed per AP-SIII.10Q procedure under Technical Work 
Plan for: Waste Package Materials Data Analyses and Modeling (BSC 2002 [DIRS 161132]), 
which, in turn, was developed in accordance with AP-2.27Q, Quality Determinations and 
Planning for Scientific, Engineering, and Regulatory Compliance Activities. The applicability of 
Quality Assurance Requirements and Description requirements (DOE 2002) is documented in 
the technical work plan (TWP) (BSC 2002 [DIRS 161132] Section 8). A process control 
evaluation was performed in accordance with AP-SV.1Q, Control of the Electronic Management 
of Information. Results documented in Attachment A of the technical work plan (BSC 2002 
[DIRS 161132]). Inputs and transfers of data were checked to assure completeness and accuracy 
in accordance with Supplement V requirements. Data were also protected from damage and 
were also password protected. 
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ANL-EBS-MD-000002 REV 1 ICN 0 15 June 2003  
3. USE OF SOFTWARE 
3.1 SOFTWARE REQUIRING APPROVAL FOR QA WORK 
Thermo-Calc Version M (Software Tracking Number 10170-M-00) [DIRS 163153] is a 
commercially available software code that fulfills the need to provide critical modeling and 
analysis of data to 
 Produce, refine, and analyze multicomponent phase diagrams of alloys at repositoryrelevant 
temperatures for predicting phase stability properties 
 Determine the solidification path and the effect of welding on stability and long-term 
aging of alloys selected for the barriers of the canisters used for storage of nuclear waste 
 Generate isothermal sections of multicomponent alloy phase diagrams at repositoryrelevant 
temperature, isopleths, and property diagrams (phase fractions as functions of 
temperature), and composition versus temperature diagrams for all stable and metastable 
phases formed 
 Simulate phase transformations according to the ScheilGulliver model which use local 
equilibria, infinite diffusion in the liquid phase, and no back diffusion in the solid phase 
(Saunders et al. [DIRS 104975]). 
Thermo-Calc version M is specially designed for systems with strongly nonideal phases and has 
gained a worldwide reputation as the best software application for the calculation of 
multicomponent phase diagrams. Thermo-Calc is the only software commercially available that 
can calculate arbitrary phase diagram sections with up to five independent variables in 
multicomponent systems. There are also modules to calculate many other types of properties, 
such as ScheilGulliver solidification simulations, Pourbaix diagrams, and partial pressures in 
gases. 
Data generated with the Thermo-Calc software also provide the basis for more accurate 
predictions of diffusion kinetics and ultimately temperaturetimetransformation (TTT) 
diagrams with the DICTRA software (see below) by using diffusion both in the liquid and solid 
phases. It should be noted that the results of both the equilibrium solidification and Scheil 
Gullivers simulations generated by Thermo-Calc correspond to the upper and lower bounds for 
the DICTRA results. 
Thermo-Calc generates output in graphical or tabular form. Calculated values are generated by 
Thermo-Calc in a proprietary binary format; however, these files, when processed through 
various modules, produce tabulated data as ASCII text files and graphical data as encapsulated 
Postscript files. 
DICTRA Version 20 (DIffusion Controlled TRAnsformation, Software Tracking Number 
10391-20-00) [DIRS 163154] is also commercially available software that is used in conjunction 
with Thermo-Calc to calculate the rate at which the relevant phase transformations occur. 
  16  
DICTRA Version 20 is used to predict the kinetics of phase transformation and evolution in 
candidate alloys for use in nuclear waste packages. In particular, this software application 
predicts TTT diagrams and, therefore, the aging behavior of complex FrankKasper phases (or 
tetrahedrally close-packed structures), such as the P and  phases, and of the ordered phase of 
the Ni2Crtype in Alloy 22 and other related alloys. 
DICTRA version 20 fulfills the need to provide critical modeling and analysis of data to: 
 Solve the diffusion equations 
 Calculate thermodynamic equilibrium 
 Solve the flux-balance equations 
 Track the displacement of the phase-interface positions and adjust grid points during 
simulation as a function of time 
 Analyze the kinetics of phase evolution in alloys selected for the barriers of the waste 
package by predicting TTT (TemperatureTimeTransformation) diagrams for the 
relevant phases forming as functions of time. 
DICTRA is interfaced to Thermo-Calc which handles all thermodynamic calculations needed by 
DICTRA. 
Data files used by Thermo-Calc and DICTRA ([DIRS 163153, 163154]) are included with the 
purchase of the software and are considered to be from documented and substantiated established 
databases: KP (Kaufman binary alloys database), SSOL (Scientific Group Thermodata Europe, 
or SGTE, solution database), MOB (Mobility database), from published journals, and/or from 
qualified sources. The databases are included on the CD-R with the applications. Disaster 
recovery copies of these media are located in the project's Software Configuration Management 
system, and the original media are controlled by the user (Patrice E. A. Turchi) due to the 
vendor's licensing and copyright restrictions. The current version of AP-3.15Q REV 4 ICN 1 
characterizes these databases as technical information that is to be used as technical product 
input in this AMR. Data files that are refined by comparing the output data of Thermo-Calc and 
DICTRA to known experimental data that are used to simulate Ni-Cr-Mo-W alloys in this study 
are described in Section 7. 
The SSOL, KP, and MOB databases are provided in ASCII-text format and can be reviewed or 
edited with any standard text editor. Custom-generated input data can be created using any 
standard text editor to create an ASCII text file. 
DICTRA uses the post-processor module from Thermo-Calc to generate output in graphical or 
tabular form. Calculated values are generated by DICTRA in a proprietary binary format; 
however, these files, when processed through various modules, can produce tabulated data as 
ASCII-text files and graphical data as encapsulated postscript files. 
  17  
Both Thermo-Calc and DICTRA are products of Thermo-Calc AB, which run on a Unix/Linux 
platform. They were run on a Sun E450/Solaris 2.7. 
3.2 SOFTWARE PRODUCTS 
Excel (Microsoft) was used for graphing data, adding trend lines to the data, and manipulating 
data through the use of standard functions included in Excel. Excel is exempt from qualification 
in accordance with AP-SI.1Q Sections 2.1.1, 2.1.2, and 2.1.6. When Excel is used for 
calculations and plots (see Sections 6.6.5, 6.6.6, and 7.5), information required for an 
independent person to reproduce the work (including formula or algorithm used, listing of inputs, 
and listing of outputs) is provided. 
Image-Pro Plus (Media Cybernetics) is a personal computer software package that is used for the 
analysis of digital images acquired from a transmission electron microscope (TEM), a scanning 
electron microscope (SEM), or an optical microscope. It is used as a quantitative metallographyanalysis 
tool and image processor/analyzer. Although there are many uses for Image-Pro Plus, 
the standard Measure menu commands are used primarily to perform analyses to acquire 
percent-area information. For the analyses presented in this report, these standard Measure 
commands were used to determine the extent of phase precipitation by measuring the appropriate 
image parameters (e.g. white areas) in a large number of SEM images. Details and results of 
these measurements are documented in the Scientific Notebooks associated with Data Tracking 
Numbers (DTNs) for phase precipitation measurements (Section 4.1.8). Image Pro-Plus 
software versions 4.0, 4.1, and 4.5.1 have been determined to be exempt from qualification in 
accordance with Sections 2.1.2 and 2.1.6 of AP-SI.1Q. 
KaleidaGraph version 3.5 (Synergy Software), ClarisDraw version 1.4, and Adobe Illustrator 
version 8.0 were used for graphing data. The graphs are for visual representation of the data 
only, and all points plotted were checked by visual inspection. These software packages are 
exempt from qualification per Section 2.1.2 of AP-SI.1Q. The actual tables of values plotted are 
presented in this document so that any approved software can be used to plot the data, if 
necessary. 
3.3 SUMMARY OF SOFTWARE USED 
A summary list of the software used in this AMR is shown in Table 1. 
Table 1 Summary List of Software Used 
Software Tracking Number Version Number Software Name 
Thermo-Calc M 10170-M-00 
DICTRA 20 10391-20-00 
Image-Pro Plus 4.0, 4.1, and 4.5.1 Exempt 
Excel 2000 Exempt 
KaleidaGraph 3.5 Exempt 
ClarisDraw 1.04 Exempt 
Adobe Illustrator Exempt 8.0 
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ANL-EBS-MD-000002 REV 1 ICN 0 19 June 2003  
4.1 DATA AND PARAMETERS 
The input data used in the APS AMR are summarized in Table 2. All micrographs and data are 
the result of waste package materials testing activities. A discussion of the uncertainty for these 
data can be found in Section 6.7. 
Sections 4.1.1 through 4.1.4 present representative examples of micrographs that were used in 
the phase identification and kinetic observations which are described in Sections 6.3.1 and 6.3.3. 
Sections 4.1.5 through 4.1.7 present SEM micrographs that are representative examples of 
micrographs used in the area-fraction measurements presented in Section 4.1.8. 
The input data presented here are appropriate for this study because scanning or tunneling 
electron microscopy are the most direct methods to determine the extent of phase precipitation 
DTN Data Use in this 
AMR 
LL010107712251.012 See Section 4.1.1 
LL010107712251.012 See Section 4.1.2 
LL030301612251.040 See Section 4.1.3 
See Section 4.1.4 
LL010107712251.012 
LL030301612251.040 
LL030104212251.012 See Section 4.1.5 
LL030103712251.007 See Section 4.1.6 
See Section 4.1.7 
LL030104212251.012 
LL021009912251.003 
LL030103812251.008 See Section 4.1.8 
LL030104012251.010 See Section 4.1.8 
LL030103612251.006 See Section 4.1.8 
June 2003 
after aging at specified times and temperatures. 
Table 2  Analysis Input Data 
Data Name 
Transmission Electron Microscopy 
Micrographs Used in Preliminary 
TCP and Carbide Phase 
Identification 
Micrographs Showing Precipitation 
in Alloy 22 Beginning on and 
Covering Grain Boundaries, 
Beginning on Twin Boundaries, and 
Beginning within the Grains 
Micrographs Showing TCP Particles 
in Alloy 22 Welds 
TEM Micrographs Showing When 
LRO Has Been Observed 
SEM Micrographs Used for 
Quantification of Phases and LRO 
SEM Micrographs Showing Bulk 
Precipitation in Base Metal 
SEM Micrographs Showing 
Precipitation in Weld Metal 
Bulk Precipitation Area-Fraction 
Measurements (% Transformation) 
Grain Boundary Precipitation 
Measurements (Grain Boundary 
Coverage Fraction) 
Precipitation Area-Fraction 
Measurements on Weld Metal 
ANL-EBS-MD-000002 REV 1 ICN 0 20 
Data Source 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
Waste Package 
Materials Testing 
4. INPUTS  
4.1.1 Transmission Electron Microscopy Micrographs Used in Preliminary TCP and 
Carbide Phase Identification 
This section contains transmission electron microscopy (TEM) images and electron-selected area 
diffraction (SAD) patterns used to identify the phases that form in Alloy 22 base metal after 
aging in the temperature range of 593 to 760C (Figure 1 through Figure 15). Because of the 
structural similarity of the  and P phases, some diffraction patterns could be indexed as either 
phase. For this reason, the phases forming in some cases are only tentatively identified. Several 
carbides form in Alloy 22, but they all have very similar structures. Although they are 
significantly different chemically, it is not possible to distinguish them in the work reported here. 
They are, therefore, simply called carbide. 
The ambiguities in identifying the exact composition of the TCP phases or carbides have no 
impact on the APS model because (1) the TCP phases are structurally similar, and (2) the 
carbides are also structural similar. Therefore, the phase kinetics among TCP phases and also 
among carbides will also be similar. 
  21 DTN: LL010107712251.012 
DTN: LL010107712251.012 
Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: This phase was identified as P phase. (TS393-049b, Image S0244, 8/23/99, SN #442, p. 19) 
Figure 1. Grain Boundary Precipitation in Alloy 22 Aged for 1000 hr at 593C 
NOTE: The grain boundary precipitate identified as P appears light. (TS393-049b, Image S0245, 8/23/99, SN #442, 
p. 19) 
Figure 2. Dark-Field Image Corresponding to Figure 1 
ANL-EBS-MD-000002 REV 1 ICN 0 22 June 2003  
DTN: LL010107712251.012 
NOTE: This pattern was indexed as P phase. (TS393-049b, Image S0246, 8/23/99, SN #442, p. 20) 
Figure 3. SAD Pattern from the Grain Boundary Precipitate Shown in Figure 1 and Figure 2 
DTN: LL010107712251.012 
NOTE: This phase was identified as P phase. (TS369-003a, Image S0125, 3/9/99, SN #434, p. 41) 
Figure 4. Grain Boundary Precipitation (P phase) in Alloy 22 Aged for 16,000 hr at 593C 
  23 DTN: LL010107712251.012 
DTN: LL010107712251.012 
Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The grain boundary precipitate identified as P appears light. (TS369-003a, Image S0126, 3/9/99, SN #434, 
p. 42) 
Figure 5. Dark-Field Image Corresponding to Figure 4 
NOTE: This pattern was indexed as P phase. (TS369-003a, Image S0124, 3/9/99, SN #434, p. 43) 
Figure 6. SAD Pattern from the Grain Boundary Precipitate Shown in Figure 4 and Figure 5 
ANL-EBS-MD-000002 REV 1 ICN 0 24 June 2003  
DTN: LL010107712251.012 
NOTE: This phase was identified as carbide. (TS369-003a, Image 1490, 12/16/98, SN #393, p. 66) 
Figure 7. Grain Boundary Precipitation (carbide) in Alloy 22 Aged for 16,000 hr at 593C 
DTN: LL010107712251.012 
NOTE: This pattern was indexed as carbide. (TS369-003a, Image 1489, 12/16/98, SN #393, p. 66) 
Figure 8. SAD Pattern from the Grain Boundary Precipitate Labeled Carbide in Figure 7 
  25 DTN: LL010107712251.012 
DTN: LL010107712251.012 
Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: This phase was identified as P phase. (TS369-004a, Image S0037, 2/16/99, SN #434, p. 63) 
Figure 9. Precipitate (P phase) in Alloy 22 Aged for 16,000 hr at 760C 
NOTE: The precipitate identified as P phase appears light. (TS369-004a, Image S0038, 2/16/99, SN #434, p. 63) 
Figure 10. Dark-Field Image Corresponding to Figure 9 
ANL-EBS-MD-000002 REV 1 ICN 0 26 June 2003  
DTN: LL010107712251.012 
NOTE: (TS369-004a, Image S0036, 2/16/99, SN #434, p. 64) 
Figure 11. SAD Pattern from the P Phase Precipitate Shown in Figure 9 and Figure 10 
DTN: LL010107712251.012 
NOTE: This phase was tentatively identified as  phase. (TS369-004a, Image 1312, 3/14/98, SN #393, p. 11) 
Figure 12. Precipitation (possibly  phase) in Alloy 22 Aged for 16,000 hr at 760C 
  27  
DTN: LL010107712251.012 
NOTE: (TS369-004a, Image 1314, 3/14/98, SN #393, p. 13) 
Figure 13. SAD Pattern from the  Phase Precipitate Shown in Figure 12 
DTN: LL010107712251.012 
NOTE: This phase was identified as  phase. (TS369-004a, Image 1309, 3/14/98, SN #369, p. 135) 
Figure 14. Grain Boundary Precipitation in Alloy 22 Aged for 16,000 hr at 760C Showing in  Phase 
Precipitation 
  28 DTN: LL010107712251.012 
DTN: LL010107712251.012 
Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (TS369-004a, Image 1310, 3/14/98, SN #369, p. 150) 
Figure 15. SAD Pattern from the  Phase Precipitate Shown in Figure 14 
NOTE: The larger, brighter phase was identified as . The smaller precipitates are either  or P phase. (TS369004a, 
Image 1300, 3/14/98, SN #369, p. 66) 
Figure 16. Grain Boundary Precipitation in Alloy 22 Aged for 16,000 hr at 760C 
ANL-EBS-MD-000002 REV 1 ICN 0 29 June 2003  
NOTE: (TS369-004a, Image 1306, tilted (11,9) from image 1300, 3/14/98, SN #369, p. 98) 
SAD Pattern from the  Phase Precipitate Shown in Figure 16 Figure 17. 
ANL-EBS-MD-000002 REV 1 ICN 0 30 
DTN: LL010107712251.012 
June 2003  
4.1.2 Micrographs Showing Precipitation in Alloy 22 Beginning on and Covering Grain 
Boundaries, Beginning on Twin Boundaries, and Beginning within the Grains 
This section contains optical and scanning electron microscopy (SEM) images (Figure 18 
through Figure 34) used to determine the times at which the various stages of TCP and carbide 
precipitation occur in Alloy 22 base metal after aging in the temperature range of 593 to 800C 
for durations ranging from 1 to 16,000 hr. No distinction has been made between the various 
TCP phases and the carbides that form in Alloy 22. The TCP phases , P, and  are virtually 
indistinguishable in the SEM (as shown in the preceding section, the phases are discernable in 
the TEM), and there is relatively little carbide precipitation. 
Similar to the discussion in Section 4.1.1, the ambiguities in the exact composition of the TCP 
phases or carbides have no impact on the APS model because due to structural similarities 
among TCP phases and also among carbides. Thus, the phase kinetics among TCP phases and 
also among carbides will also be similar. 
  31  
DTN: LL010107712251.012 
NOTE: (TS393-028a, 2/15/99, SN #434, p. 7) 
Figure 18. SEM Micrograph Showing Precipitation Just Beginning on Grain Boundaries after Aging Alloy 
22 for 10 hr at 593C 
DTN: LL010107712251.012 
NOTE: (TS393-029a, 2/15/99, SN #434, p. 8) 
Figure 19. SEM Micrograph Showing Precipitation on Grain Boundaries after Aging Alloy 22 for 100 hr 
at 593C 
  32  
DTN: LL010107712251.012 
NOTE: (TS393-008a, 12/7/98, SN#434, p. 10) 
Figure 20. Optical Micrograph Showing No Precipitation on Grain Boundaries after Aging Alloy 22 for 1 
hr at 649C 
DTN: LL010107712251.012 
NOTE: (TS393-008a, 12/7/98, SN #434, p. 10) 
Figure 21. SEM Micrograph Showing Little or No Precipitation on Grain Boundaries after Aging Alloy 22 
for 1 hr at 649C 
  33  
DTN: LL010107712251.012 
NOTE: (TS393-009a, 12/7/98, SN #434, p. 11) 
Figure 22. SEM Micrograph Showing Precipitation on Grain Boundaries after Aging Alloy 22 for 10 hr at 
649C 
DTN: LL010107712251.012 
NOTE: (TS393-010a, 12/7/98, SN #434, p. 12) 
Figure 23. SEM Micrograph Showing Precipitation on Grain Boundaries after Aging Alloy 22 for 100 hr 
at 649C 
  34  
DTN: LL010107712251.012 
NOTE: (TS393-011a, 12/7/98, SN #434, p. 12) 
Figure 24. SEM Micrograph Showing Precipitation on Grain Boundaries after Aging Alloy 22 for 1000 hr 
at 649C 
DTN: LL010107712251.012 
NOTE: (TS393-011a, 12/7/98, SN #434, p. 13) 
Figure 25. SEM Micrograph Showing Precipitation on Grain and on Twin Boundaries after Aging Alloy 
22 for 1000 hr at 649C 
  35  
DTN: LL010107712251.012 
NOTE: (TS369-008b, 8/28/98, SN #434, p. 14) 
Figure 26. SEM Micrograph Showing Precipitation on Grain Boundaries and within the Grains after 
Aging Alloy 22 for 16,000 hr at 649C 
DTN: LL010107712251.012 
NOTE: (TS369-014, 11/30/98, SN #434, p. 19) 
Figure 27. Low-Magnification SEM Micrograph Showing that Grain Boundary Precipitation has Begun 
after Aging Alloy 22 for 1 hr at 760C 
  36  
DTN: LL010107712251.012 
NOTE: (TS369-014, 11/30/98, SN #434, p. 20) 
Figure 28. High-Magnification SEM Micrograph Showing that Grain Boundary Precipitation has Begun 
after Aging Alloy 22 for 1 hr at 760C 
DTN: LL010107712251.012 
NOTE: (TS369-015, 11/30/98, SN #434, p. 21) 
Figure 29. SEM Micrograph Showing Significant Grain Boundary Precipitation after Aging Alloy 22 for 10 
hr at 760C 
  37  
DTN: LL010107712251.012 
NOTE: (TS369-016, 11/30/98, SN #434, p. 22) 
Figure 30. SEM Micrograph Showing Significant Grain Boundary Precipitation and Precipitation on Twin 
Boundaries after Aging Alloy 22 for 119 hr at 760C 
DTN: LL010107712251.012 
NOTE: (TS393-007a, 12/7/98, SN #434, p. 22) 
Figure 31. SEM Micrograph Showing Significant Precipitation Within the Grains of Alloy 22 after Aging 
for 1000 hr at 760C 
  38  
DTN: LL010107712251.012 
NOTE: (TS393-020a, 2/15/99, SN #434, p. 25) 
Figure 32. SEM Micrograph Showing Grain Boundary Precipitation in Alloy 22 after Aging for 1 hr at 
800C 
DTN: LL010107712251.012 
NOTE: (TS393-021a, 2/15/99, SN #434, p. 26) 
Figure 33. SEM Micrograph Showing Significant Grain Boundary Precipitation in Alloy 22 after Aging for 
10 hr at 800C 
  39  
DTN: LL010107712251.012 
NOTE: (TS393-022a, 2/15/99, SN #434, p. 27) 
Figure 34. SEM Micrograph Showing Precipitation on Grain Boundaries, on Twin Boundaries, and within 
the Grains after Aging Alloy 22 for 100 hr at 800C 
  40  
4.1.3 Micrographs Showing TCP Particles in Alloy 22 Welds 
The TCP phases , P, and  are known to form in Alloy 22 welds (Cieslak et al. 1986 
[DIRS 104966], p. 2041,  2). This section contains optical, SEM, and TEM images (Figure 35 
through Figure 44) in the preliminary characterization of Alloy 22 welds. Two samples have 
been examined: one was examined in the as-welded condition; the other was aged for 40,000 hr 
at 427C. Although the two welds were produced in the same way, the aged sample did not come 
from the same weld, as did the unaged sample. Therefore, some variation is expected between 
the samples, and direct comparisons on the small scale of differences seen between these 
samples should not be made. 
  41  
DTN: LL030301612251.040 
NOTE: Only approximately three-quarters of the half-inch plate is shown. (TS369-019, 8/28/98, SN #393, pp. 9 to 
10) 
Figure 35. Low-Magnification (25X) Optical Micrograph of an Alloy 22 Multipass, Double-V Gas- 
Tungsten-Arc-Welding (GTAW) Weld with Matching Filler Metal (as-welded) 
DTN: LL030301612251.040 
NOTE: (TS369-019, 8/28/98, SN #393, p. 10) 
Figure 36. SEM Micrograph of the Alloy 22 Weld Shown in Figure 35 Showing the Dendritic Structure 
Typical of Welds 
  42  
DTN: LL030301612251.040 
NOTE: TCP particles are seen to form in the interdendritic regions. (TS369-019 SC11, 8/28/98, SN #393, p. 10) 
Figure 37. SEM Micrograph of the Alloy 22 Weld Shown in Figure 35 Showing the Dendritic Structure 
Typical of Welds (Near Top of Plate; Center of Weld, Higher Magnification) 
DTN: LL030301612251.040 
NOTE: Only approximately one-half of the half-inch plate is shown. (TS369-005b, 5/12/98, SN #369, p. 20) 
Figure 38. Low-Magnification Optical Micrograph of an Alloy 22 Weld and Aged for 40,000 hrs at 427C 
  43 DTN: LL030301612251.040 
DTN: LL030301612251.040 
Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The white TCP particles are distributed non-uniformly throughout the weld. (TS369-005b, 5/12/98, SN #369, 
p. 20) 
Figure 39. SEM Micrograph of the Alloy 22 Weld Shown in Figure 38 at the Junction of Two Weld 
Passes 
NOTE: TCP particles are seen to form in the interdendritic regions, as was seen in the unaged weld of Figure 38. 
(TS369-005b, 5/12/98, SN #369, p. 20) 
Figure 40. SEM Micrograph of the Alloy 22 Weld Shown in Figure 38 Showing the Dendritic Structure 
Typical of Welds 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: Very few precipitates are noticeable (white specks) in the Heat-Affected Zone (HAZ) of the aged weld. 
(TS369-005b, 5/12/98, SN #369, p. 20) 
Figure 41. Optical Micrograph at the Fusion Line of the Alloy 22 Weld Shown in Figure 42 
NOTE: This particle was not conclusively identified, but could be either P or . (TS369-005a, Image 1373, 5/21/98, 
SN #393, p. 27) 
Figure 42. One of Few Precipitates Seen using TEM in the Alloy 22 Weld of Figure 38 Aged for 40,000 
hrs at 427C 
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NOTE: This pattern could be indexed as either P phase or . (TS369-005a, Image 1375, 5/21/98, SN #393, p. 31) 
Figure 43. SAD Pattern from the Precipitate Shown in Figure 42 
NOTE: A SAD pattern was not taken from this particle, but it appears to be a carbide and was probably present in 
the base metal prior to welding. (TS369-005a, Image 1378, 5/22/98, SN #393, p. 37) 
Figure 44. TEM Micrograph Showing a Precipitate, Possibly a Carbide, in the HAZ of the Aged Alloy 22 
Weld of Figure 38 
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4.1.4 TEM Micrographs Showing When LRO Has Been Observed 
This section contains a representative sampling of the TEM micrographs (Figure 45 through 
Figure 56) showing instances when LRO has been observed in aged Alloy 22 samples. In these 
sample micrographs, LRO has been observed in Alloy 22 base metal after aging for 16,000 hr at 
593C and in Alloy 22 welds after aging for 40,000 hr at 427C. 
  47  
DTN: LL010107712251.012 
NOTE: (TS369-003a, Image 1484, 12/16/98, SN #393, p. 61) 
Figure 45. TEM Micrograph Showing LRO Domains in an Alloy 22 Base Metal Sample Aged for 16,000 
hr at 593C 
DTN: LL010107712251.012 
NOTE: One or more variants of the ordered domains appears light. (TS369-003a, Image 1485, 12/16/98, SN #393, 
p. 61) 
Figure 46. Dark-Field Image Corresponding to Figure 45 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The faint superlattice reflections are due to LRO. (TS369-003a, Image 1483, 12/16/98, SN #393, pp. 61 to 
65) 
Figure 47. SAD Pattern from the Area Shown in Figure 45 
NOTE: (TS369-005a base metal, Image 1354, 3/20/98, SN #369, p. 132) Bright field image from base metal region 
of sample TS369-005a 
Figure 48. TEM Micrograph from the Base Metal of an Alloy 22 Weld Sample Aged for 40,000 hr at 
427C 
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NOTE: One or more variants of the ordered domains appears light. (TS369-005a base metal, Image 1356, 3/20/98, 
SN #369, p. 133). White spots are ordered precipitates. 
Figure 49. Dark-Field Image from 1/3 <220> Reflection. 
NOTE: The faint superlattice reflections are due to LRO. (TS369-005a base metal, Image 1353, 3/20/98, SN #369, 
p. 131). The faint spots occur at 1/3 and 2/3 <220>. 
Figure 50. SAD Pattern from the Area Shown in Figure 48, Typcial fcc <110> zone axis. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (TS369-005a weld metal, Image 1371, 5/21/98, SN #393, p. 26) 
Figure 51. TEM Micrograph from the Weld Metal of an Alloy 22 Multipass, Double-V GTAW Weld with 
Matching Filler Metal Aged for 40,000 hrs at 427C 
NOTE: The faint white regions are ordered domains. (TS369-005a weld metal, Image 1372, 5/21/98, SN #393, p. 
26). White spots are Ni2(Cr,Mo) precipitates. 
Figure 52. Dark-Field Image Corresponding to Figure 51 
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NOTE: The faint superlattice reflections indicate that ordering has occurred. (TS369-005a weld metal, Image 1370, 
5/21/98, SN #393, p. 25) 
Figure 53. SAD Pattern from the Area Shown in Figure 51 
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NOTE: (TS369-005a HAZ, Image 1379, 5/22/98, SN #393, p. 38) 
Figure 54. TEM Micrograph from the HAZ of the Alloy 22 Multipass, Double-V GTAW Weld with 
Matching Filler Metal Aged for 40,000 hrs at 427C 
  52  
DTN: LL030301612251.040 
NOTE: The faint white regions are ordered domains. (TS369-005a HAZ, Image 1380, 5/22/98, SN #393, p. 39) 
Figure 55. Dark-Field Image Corresponding to Figure 54, Taken from one of the 1/3 <220> reflections 
shown in Figure 56 below. 
DTN: LL030301612251.040 
NOTE: The faint superlattice reflections are due to LRO. (TS369-005a HAZ, Image 1381, 5/22/98, SN #393, p. 39) 
Figure 56. SAD Pattern from the Area Shown in Figure 54, showing 1/3 <220> superlattice reflections 
  53 DTN: LL030104212251.012 
Aging and Phase Stability of Waste Package Outer Barrier 
4.1.5 SEM Micrographs Used for Quantification of Phases and LRO 
This section shows an example of a SEM micrograph that is used to quantify phases present and 
the onset of LRO. Figure 57 shows evidence of the onset of LRO (right-hand side of image) in 
base metal aged at 550C for 21,052 hr. In addition, the Morich  and P phases are evident at 
the boundary (white areas). 
NOTE: (Sample No. TS444-012B2B) Morich  and P phases are also evident at interface 
Figure 57. Base metal aged at 550C for 21,052 hr and exhibits ordered matrix in right-hand region. 
  54  
4.1.6 SEM Micrographs Showing Bulk Precipitation in Base Metal 
The micrographs in this section (Figure 58 through Figure 65) are representative of SEM 
micrographs that are used as input to determine area-fraction coverage in the bulk matrix of base 
metal as a function of time and temperature. The software package Image-Pro Plus analyzes the 
micrographs to determine area-fraction coverage. The volume fraction of precipitates (as 
function of time and temperature) is equivalent to the area-fraction measurement (See Section 
6.6.3) (Vander Voort 1999 [DIRS 161300], Hilliard et al. [DIRS 161454]). The area-fraction 
measurements on base metal are presented in Table 3. 
  55 DTN: LL030103712251.007 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (Sample No. TS369-008b) Precipitates in the bulk matrix are noticeable. 
Figure 58. Base Metal aged at 649C for 16,000 hrs. 
NOTE: (Sample No. TS369-009b) Due to higher temperature, precipitation in the bulk matrix is more pronounced 
than in Figure 58. 
Figure 59. Base Metal aged at 704C for 16,000 hr. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (Sample No. TS369-016a) Few precipitates in the bulk matrix are evident at this temperature after short 
time. 
Figure 60. Base Metal aged at 760C for 119 hr. 
NOTE: (Sample No. TS393-007a) More precipitation is evident after a longer aging time than was used for Figure 
60. 
Figure 61. Base Metal aged at 760C for 1000 hr. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (Sample No. TS369-018a) Significant precipitation is evident in the bulk matrix at the longer aging time, as 
compared to Figure 61. 
Figure 62. Base Metal aged at 760C for 2000 hr. 
NOTE: (Sample No. TS369-004b) Precipitation is extensive in the bulk matrix at this temperature and long aging 
time. 
Figure 63. Base Metal aged at 760C for 16,000 hr. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (Sample No. TS393-022a) Precipitation in the bulk matrix is minimal at this high temperature, but short aging 
time. 
Figure 64. Base Metal aged at 800C for 100 hr. 
NOTE: (Sample No. TS393-023a) Precipitation in the bulk matrix is more extensive at this temperature due to the 
longer aging time, as compared to Figure 64. 
Figure 65. Base Metal aged at 800C for 1002 hr. 
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4.1.7 SEM Micrographs Showing Precipitation in Weld Metal 
Similar to the procedure described for base metal (Section 4.1.6), the micrographs in this section 
(Figure 66 through Figure 73) are representative of SEM micrographs that are used as input to 
determine area-fraction coverage in the weld metal as a function of time and temperature. 
Again, the software package Image-Pro Plus analyzes the micrographs to determine area 
coverage. The volume fraction of precipitates (as function of time and temperature) is equivalent 
to the area-fraction measurement (See Section 6.6.3) (Vander Voort 1999 [DIRS 161300], 
Hilliard et al. [DIRS 161454]). The area-fraction measurements on weld metal are presented 
Table 5. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (Sample No. TS441-033b3) 
Figure 66. Weld Metal, As-Welded Condition 
NOTE: (Sample No. TS441-056b) A minimal amount of precipitates are noticeable along the interdendritic regions. 
Figure 67. Weld Metal aged at 593C for 30 hr. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (Sample No. TS441-061b) Using a lower magnification, a minimal amount of precipitation can be seen to 
align with the interdendritic regions. 
Figure 68. Weld Metal aged at 593C for 1000 hr. 
NOTE: (Sample No. TS441-041b3) Due to higher temperature, precipitates are evident in the weld metal. 
Figure 69. Weld Metal aged at 704C for 10 hr. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: (Sample No. TS441-062b3) Due to longer aging time, precipitation along the interdendritic regions is more 
evident. 
Figure 70. Weld Metal aged at 704C for 100 hr. 
NOTE: (Sample No. TS441-035b) Close-up micrograph of precipitates evident in weld metal at this higher 
temperature. 
Figure 71. Weld Metal aged at 760C for 3 hr. 
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NOTE: (Sample No. TS441-036b) High magnification image of precipitates formed at higher temperature 
in weld metal. 
Figure 72. Weld Metal aged at 760C for 6 hr. 
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NOTE: (Sample No. TS441-047b) At this temperature and longer aging, time, the precipitates are shown to be more 
extensive and align along the interdendritic regions in the weld metal. 
Figure 73. Weld Metal aged at 760C for 60 hr. 
  64  
4.1.8 Volume-Fraction Measurements 
Volume fraction measurements are used to determine the extent of phase precipitation as 
function of time and temperature. As a result, the volume fraction measurements are used as 
inputs to the APS model to predict phase precipitation. The volume fraction data used in the 
APS model are shown in Table 3 through Table 5. Details of the volume-fraction measurements 
can be found in the Scientific Notebooks. 
As mentioned previously, the micrographs shown in Sections 4.1.5 through 4.1.7 were a 
representative sampling of the multitude of micrographs used for volume fraction measurements. 
As a result, there is not a direct correspondence between the representative micrographs and 
values shown in the tables. 
The standard deviations and 95% confidence intervals were calculated per ASTM E 562-95 
Standard Test Method for Determining Volume Fraction by Systematic Manual Point Count 
[DIRS 161301] 
Table 3 Bulk Precipitation Area-Fraction Measurements (% Transformation) 
Temperature Time % Standard 95% 
(C) Deviation (hr) Transformation Confidence Interval 
649 16,000 2.50 1.60 0.64 
650 600 0.00 0.00 N/A 
700 10,073 8.10 1.40 0.64 
704 16,000 19.00 3.60 1.65 
750 10,076 17.90 1.80 0.93 
760 16,000 22.50 2.90 1.50 
760 2000 10.10 1.10 0.53 
760 1000 6.30 1.20 0.57 
760 119 0.73 0.28 0.11 
800 1002 12.70 0.86 0.44 
800 100 1.50 0.47 0.19 
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Table 4 Grain Boundary Precipitation Measurements (Grain Boundary Coverage Fraction) 
Standard Deviation Grain Boundary 
Coverage Fraction 
95% 
Confidence Interval 
Time 
(hr) 
Temperature 
(C) 
0 0 
0 
0.035 
0.067 
0.033 
0.085 
0.032 
0 
0.05 
0.13 
0.06 
0.16 
0.06 
427 40,000 0 
649 6 0 
649 600 0.84 
704 10 0.5 
704 60 0.92 
760 0.5 0.51 
760 3 0.79 
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  65  
Table 5 
Temperature 
(C) 
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4.2 CRITERIA 
Precipitation Area-Fraction Measurements on Weld Metal 
Standard Deviation Area Fraction 
(%) 
Time 
(hr) 
As-Welded 0 0.16 
593 30 0.24 
593 60 0.29 
593 100 0.21 
593 300 0.36 
593 600 0.28 
593 1000 0.24 
649 10 0.24 
649 30 0.27 
649 60 0.17 
649 100 0.34 
649 300 1.27 
649 600 1.99 
704 3 0.21 
704 6 0.29 
704 10 0.26 
704 30 0.73 
704 60 1.01 
704 100 2.64 
760 1 0.21 
760 3 0.69 
760 6 0.97 
760 10 1.10 
760 30 3.24 
760 60 4.17 
760 100 7.77 
As expected, there is more uncertainty in the volume fraction measurements on specimens 
subjected to lower temperatures and/or shorter aging times. At lower temperatures and/or shorter 
aging times, the amount of TCP phase precipitated can be very small, and as a result, the volume 
fraction measurements have been performed on minimally detectable levels of precipitates (near 
zero). Thus, it is not surprising that for lower temperatures and/or shorter aging times the 
standard deviations would be large. As expected, the uncertainty is considerably reduced in 
measurements where significant amounts (> 5%) of precipitation have occurred. A more 
detailed discussion of uncertainty is given in Section 6.7. 
The Waste Package Technical Work Plan (BSC 2002 [DIRS 161132], Table C5) has identified 
the following acceptance criteria (AC) based on the requirements mentioned in the Project 
Requirements Document (Curry et al. 2002 [DIRS 157916]) and the Yucca Mountain Review 
Plan (NRC 2003 [DIRS 162418]): 
95% 
Confidence Interval 
0.15 0.047 
0.27 0.091 
0.24 0.074 
0.21 0.060 
0.28 0.091 
0.21 0.063 
0.21 0.071 
0.24 0.077 
0.24 0.085 
0.23 0.092 
0.24 0.085 
0.92 0.268 
1.46 0.494 
0.27 0.081 
0.34 0.096 
0.18 0.073 
0.76 0.222 
0.76 0.243 
2.03 0.718 
0.22 0.072 
0.63 0.190 
1.09 0.286 
0.87 0.341 
1.53 0.559 
1.3 
1.92 
0.467 
0.659 
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 Degradation of Engineered Barriers (NRC 2003 [DIRS 162418] Section 4.2.1.3.1.3; 
PRD-002/T-015) 
Specific requirements include describing deterioration or degradation of engineered barriers 
and modeling degradation processes using data for performance assessment, including total 
system performance assessment (TSPA). Consideration of uncertainties and variabilities in 
model parameters and alternative conceptual models are also required. To fulfill these 
requirements, the following acceptance criteria are identified in the Waste Package TWP 
(BSC 2002 [DIRS 161132] Table C5): 
AC1: System Description and Model Integration are Adequate 
AC2: Data are Sufficient for Model Justification 
AC3: Data Uncertainty is Characterized and Propagated Through the Model Abstraction 
AC4: Model Uncertainty is Characterized and Propagated Through the Model Abstraction 
AC5: Model Abstraction Output is Supported by Objective Comparisons 
4.3 CODES AND STANDARDS 
The codes and standards used in this report are: 
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. 1998. Standard Practice for Prediction of the Long-Term Behavior of 
Materials, Including Waste Forms, Used in Engineered Barrier Systems (EBS) for Geological 
Disposal of High-Level Radioactive Waste. West Conshohocken, Pennsylvania: American 
Society for Testing and Materials. TIC: 246015. 
ASTM E 562-95. Standard Test Method for Determining Volume Fraction by Systematic 
Manual Point Count. Philadelphia, Pennsylvania: American Society for Testing and Materials. 
TIC: 253834. 
  67  
5. ASSUMPTIONS 
5.1 KINETICS THE SAME FOR THE TCP AND CARBIDE PHASES IN ALLOY 22 
The relative amounts of , P, , and carbide phases have not been quantified; therefore, the 
kinetics of formation of these phases cannot be calculated independently at this time. It is 
reasonable to assume that their rates of formation are similar. This assumption is based on the 
following observations. The amounts of carbide and  phase tend to be low in the samples 
examined thus far. Therefore, the rates of formation of these phases are not likely to contribute 
significantly to the overall performance of the WPOB, nor are they likely to affect the 
transformation rates calculated based on volume fraction measurements, which include these 
phases in the total precipitate volume. The  and P phases are very similar (Leonard 1969 
[DIRS 104970], p. 225,  4; Raghavan et al. 1982 [DIRS 146956], p. 983, Conclusions section, 
point 2), and the rates at which they form are likely to be similar. It also appears that P phase is a 
precursor to  phase (Leonard 1969 [DIRS 104970], p. 223, Figure 1). This would also explain 
why more P phase (relative to the amount of  phase) has been observed at the lower 
temperatures than at the higher temperatures. If P phase is a precursor to  phase, including the 
total amount of P +  as input to the kinetic model is appropriate. For these reasons described 
above, this assumption does not require confirmation. This assumption is used in the preliminary 
kinetic observations discussed in Section 6.3.1. 
5.2 TRANSFORMATION MECHANISMS OPERATING AT THE HIGHER 
TEMPERATURES INVESTIGATED ALSO OPERATE AT THE LOWER 
EXPECTED REPOSITORY TEMPERATURES 
For a WP lifetime of approximately 10,000 years, it is impossible to test directly in the 
laboratory the behavior of WPOB materials under expected repository conditions. The changes 
that may occur in these materials must be accelerated. For phase-stability studies, phase 
transformations are accelerated by increasing test temperatures above those anticipated in the 
propose repository (~200C). Extrapolation to low temperatures of kinetic data taken at high 
temperatures assumes that the mechanism by which the phases form at high temperatures also 
operates at the lower temperatures. The lower the temperature from which the extrapolation is 
made, the more likely the validity of these assumptions. This assumption is used in Sections 
6.1.2 and 6.6 and does not require confirmation. 
Long-term aging studies, which are currently under way, will allow measurements to be made at 
temperatures as low as 260C. Also, theoretical modeling aimed at calculating the Alloy 22 
phase diagram and precipitation kinetics has been performed. These calculations will further 
support the use of this assumption. 
  68  
6. MODEL 
6.1 MODEL OBJECTIVES 
6.1.1 Goal of Model 
In the mill-annealed condition, Alloy 22 is primarily a single-phase, fcc solid solution with 
excellent corrosion resistance in a wide range of environmental conditions. Over time, other 
phases can precipitate out and degrade both the mechanical properties and corrosion resistance of 
the alloy. The goal of this model is to determine whether the single-phase solid solution is stable 
under repository conditions, and if not, how fast other phases may precipitate. Precipitation 
kinetics in the annealed base metal, as well as in the annealed and stress-mitigated welds, must 
be modeled. The APS model, which is based on fundamental thermodynamic and kinetic 
concepts and principles, will be used to provide predictive insight into the long-term 
metallurgical stability of Alloy 22 under relevant repository conditions. Thus, there are no direct 
inputs from the APS model to TSPA. 
6.1.2 Background 
The time required for these precipitation reactions to occur increases as the temperature 
decreases. At the expected repository temperatures, the kinetics of these precipitation reactions 
are too slow to measure experimentally. For this reason, the rates at which they occur are 
measured at temperatures that are high in comparison to expected repository temperatures and 
then extrapolated to lower temperatures. Extrapolation from the relatively short laboratory time 
frame (tens of years) to the long repository time frame (tens of thousands of years) must be 
performed over durations spanning orders of magnitude. Theoretical calculations are used to 
establish confidence in such extended extrapolations. 
Several of the phases that form in Alloy 22 are FrankKasper, tetrahedrally close-packed 
(TCP) phases (Shoemaker and Shoemaker 1988 [DIRS 154989], pp. 19 to 45, Section 4): , P, 
and . These phases tend to be rich in Mo and/or Cr (Raghavan et al. 1984 [DIRS 154707], 
p. 789, Tables III and IV). Since these elements are largely responsible for the corrosion 
resistance of Alloy 22, precipitation of TCP phases can lead to the degradation of the corrosion 
properties. The TCP phases are also very brittle and tend to precipitate (at least initially) on 
grain boundaries, leading to a reduction in the toughness and, to a lesser extent, the ductility of 
Alloy 22 (Summers et al. 1999 [DIRS 146915], pp. 922 to 923, Figures 2 and 3). 
Welding produces a cast microstructure with chemical segregation regardless of the alloy used. 
In Alloy 22, segregation of primarily molybdenum causes TCP phases to precipitate during 
welding (Cieslak et al. 1986 [DIRS 104966], p. 2041). The chemical segregation of an aswelded 
structure, as well as these TCP phases, can result in the degradation of the mechanical 
and corrosion properties of Alloy 22 welds when compared to the base metal. 
The growth of TCP phases in Alloy 22 welds due to thermal aging causes a further reduction of 
the corrosion resistance and mechanical properties of the weld. The kinetics of the reactions that 
occur in the weld may be different than those discussed above for the base metal because the 
precipitates are already nucleated in the weld and there is chemical segregation. New data (see 
  69  
Section 6.6.5.3.2) do not indicate that further nucleation and growth of TCP phases in Alloy 22 
welds will occur at temperatures below about 200C. Given the short-term nature of these data, 
conclusions will remain highly uncertain until theoretical calculations that take into 
consideration the numerous phases involved, their compositions, and segregation in the weld are 
performed and experimentally validated. 
6.2 FEATURES, EVENTS, AND PROCESSES (FEP) INCLUDED IN MODEL 
This AMR does not provide a direct basis for the inclusion of FEP 2.1.11.06.0A (Thermal 
sensitization of waste packages) in TSPA-LA (Total System Performance Assessment for 
License Application). Rather, the results of this model/analysis are used by the Model 
Document, General Corrosion and Localized Corrosion of Waste Package Outer Barrier, which 
is currently in preparation. This AMR provides results which show that an extrapolation of the 
aging and phase stability data (TTT diagrams) does not indicate that the phase stability of Alloy 
22 base metal will be a concern for temperatures less than approximately 200C (Section 6.6.2). 
6.3 AGING AND PHASE STABILITY CONCEPTUAL MODEL 
6.3.1 Phase Identification and Preliminary Kinetic Observations in Alloy 22 
Alloy 22 samples were aged for 40,000 hr at 260, 343, and 427C; for 30,000 hr at 427C; for 
1000 hr at 482, 538 and 593C; and for 16,000 hr at 593, 649, 704, and 760C and examined in 
TEM. A weld sample aged at 427C for 40,000 hr was also observed in the weld metal, in the 
HAZ, and in the base metal removed from the weld. The other samples used for the subsequent 
kinetic arguments were not examined in TEM. Several phases were observed to form in Alloy 
22: P, , , carbide, and Ni2(Cr,Mo) LRO. At 593C, P phase was observed only on the grain 
boundaries. This is shown in Figure 1 through Figure 6. At the higher aging temperatures (up to 
760C), both  and P phases precipitated on grain boundaries (see Figure 9 through Figure 15). 
As the aging temperature increased, more  and P phase precipitation occurred within the grains. 
Grain boundary carbide precipitation was observed in samples aged at 593 and 704C (see 
Figure 7 and Figure 8. Micrographs of only samples aged at 593C are shown here). 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. They may or may not form at 760C. Because of the 
similarity between the M6C, the M12C, and the M23C6.type carbide crystal structures, the specific 
carbide forming in these samples was not identified; however, it is a cubic carbide with lattice 
parameter of 10.11 A. A  phase was observed in the samples aged at 704 and 760C (see 
Figure 16 and Figure 17. Micrographs of only samples aged at 760C are shown here). The 
amount of  observed in these samples was small compared to the amount of  and P. LRO was 
observed in the samples aged at 593C for 16,000 hr (see Figure 45 through Figure 47) and for 
1000 hr and in the samples aged at 427C for 40,000 hr (see Figure 48 through Figure 56). These 
observations are summarized in Table 6. 
The results of this section have been published (Summers et al. 1999 [DIRS 110249]) and are 
consistent with other published results. For example, in Hastelloy Alloy C.276, an alloy in the 
same class as Alloy 22, mostly  and P phases were seen after aging (Leonard 1969 
[DIRS 104970], p. 228, Conclusions Section, point 5). Also, more  relative to P was seen in C. 
276 as aging temperature was increased (Leonard 1969 [DIRS 104970], p. 224, Table 2; 
  70  
Raghavan et al. 1982 [DIR 146956], Conclusions Section). In the earlier papers,  phase had not 
been named; it was called the Ni7Mo6type phase. By the time of the Raghavan et al. (1982 
[DIRS 146956]) paper, this phase had been identified as . The presence of carbides is also 
consistent with previously published results for C276 (Raghavan et al. 1982 [DIRS 146956], 
Conclusions Section). The observance of LRO after aging between 427 and 593C is consistent 
with previously published occurrences of LRO in C276 and in Alloy 22 (Tawancy et al. 1983 
[DIRS 104991], p. 40,  4; Rebak and Koon 1998 [DIRS 102797], Figure 9 and Conclusions 
Section, Point 5). The presence of  phase after aging above 700C has not been previously 
reported in Alloy 22. The amount of  phase in these samples is small, and its presence is 
currently ignored (see Section 5.1). 
The TEM micrographs from the samples in Section 4.1.1 were taken from samples aged for 
16,000 hr at 593, 649, 704, and 760C and for 1000 hr at 593C. Samples aged for shorter time 
intervals have not been examined in TEM; therefore, the evolution of the phases during aging is 
not known. Also, when a large number of precipitates is involved, TEM diffraction analysis is a 
cumbersome method of phase identification. This is especially true when the crystal structures of 
the various phases are similar. A single SAD pattern is often not enough to distinguish the phases 
that form in Alloy 22. Instead, two patterns with a known tilt between them frequently must be 
analyzed. For this reason, little quantitative data exist for the relative amounts of each phase as a 
function of temperature. Chemical phase extraction and x-ray diffraction techniques may yield 
more quantitative results. 
  71 Aging Condition 
Aging and Phase Stability of Waste Package Outer Barrier 
260C for 40,000 hr 
343C for 40,000 hr 
427C for 30,000 hr 
427C for 40,000 hr 
482C for 1000 hr 
538C for 1000 hr 
593C for 1000 hr 
593C for 16,000 hr 
649C for 16,000 hr 
704C for 16,000 hr 
760C for 16,000 hr 
DTN: LL010107712251.012 
For this preliminary investigation, no distinction has been made between the various TCP and 
carbide phases that form. It is very difficult to distinguish these phases in SEM. Instead, it is 
known that the P and  phases are kinetically similar and that there is only a small amount of 
carbide and  phase. It is generally accepted that P and  phases are similar (Leonard 1969 
[DIRS 104970], p. 225,  4; Raghavan et al. 1982 [DIRS 146956], p. 983, Conclusions Section, 
Point 2), and, therefore, the kinetics of their formation is expected to be similar. 
6.3.2 Kinetics of Phase Transformations in Alloy 22 
Theoretical modeling was performed to determine the phase diagrams and other thermodynamic 
properties of the phases that form in Alloy 22. Theoretical modeling was also used to calculate 
the rate at which the relevant phase transformations occur (Turchi 2001 [DIRS 154934]). 
The stability of the binary alloys nickelchromium, nickelmolybdenum, and molybdenum 
chromium and of the ternary nickelchromiummolybdenum alloys was investigated. The study 
also focused on the role of additional solutes, such as silicon, carbon, cobalt, neodymium, 
tantalum, and tungsten on stability, ordering, and precipitation in Alloy 22. These results 
indicate that the TCP phases (P and probably ) are stable at repository temperatures and will 
form if they are not kinetically inhibited (see Section 6.6.4). It is also apparent that preparing 
samples for measurements of the corrosion and mechanical properties must be done considering 
Table 6. Phases Observed in Alloy 22 in TEM 
No LRO 
No signs of grain boundary precipitation in base metal 
No LRO 
No signs of grain boundary precipitation in base metal 
LRO 
No signs of grain boundary precipitation in base metal 
LRO 
No signs of grain boundary precipitation in base metal 
No LRO 
No signs of grain boundary precipitation in base metal 
LRO 
No signs of grain boundary precipitation in base metal 
LRO 
Grain boundary films of P phase 
LRO 
Grain boundary films of P phase 
Carbide precipitates at grain boundaries 
No LRO 
Precipitation of P and  phases mainly at grain boundaries 
No LRO 
Precipitation of P and  phases at grain boundaries and within the grains 
Carbide and  precipitation at grain boundaries 
No LRO 
Precipitation of P and  phases at grain boundaries and within the grains 
 precipitation at grain boundaries 
ANL-EBS-MD-000002 REV 1 ICN 0 72 
Phases Observed to Form in Alloy 22 
June 2003  
the temperature range at which the relevant phases form. The phases that would be stable under 
proposed repository conditions form at temperatures below approximately 800C.  phase forms 
at higher temperatures, but it is not stable at the lower temperatures expected in the proposed 
repository. 
Kinetic and thermodynamic modeling are combined and applied to the study of diffusioncontrolled 
transformations. These kinetic studies were focused on the time-dependent formation 
of complex TCP phases and LRO in terms of phase evolution from the fcc matrix for times up to 
10,000 years. The approach used in the kinetic and thermodynamic modeling involved 
simulating the Ni-Cr-Mo-W alloy system with a series of increasingly more complex 
calculations. A first series of calculations has been performed to predict the TTT diagram for the 
case of the 10 percent transformation of an fccbased nickelchromium matrix in the ordered 
Ni2Cr phase where experimental results were available for comparison (Karmazin 1982 
[DIRS 154881]). A second series of simulations were conducted with a pseudo-binary 
NiX(Cr3Mo)1X alloy in which kinetic data are available for comparison from the experimental 
work of Karmazin et al. 1994 [DIRS 161444]. A third series of simulations was performed for 
the case of a ternary nickelchromiummolybdenum alloy with a nominal composition of 
55.7Ni21.1Cr13.5Mo (wt %). The transformations of P, , and oP6 (ordered) phases from the 
fcc-based matrix ranging from 2 to 15 percent were each considered as a function of time and 
temperature. A quantitative analysis of the phase formation in samples annealed at various 
temperatures and for several aging times is being performed to reduce uncertainties in this 
studys conclusions. In these simulations, grain boundary formation is not considered. 
Precipitation on grain boundaries, which is observed, occurs at a faster rate than bulk 
precipitation, which was treated here. The results of these simulations are given in Section 6.6.4, 
and the validation of these simulations is described in Sections 7.1 through 7.4. 
6.3.3 Weld Characteristics 
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. TCP precipitation kinetics in the HAZ will be similar 
to those in the base metal, but the actual rates of precipitation may be different. The high 
temperatures, approaching the melting point, seen in the HAZ of welds may trigger nucleation of 
TCP and/or 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 (Figure 41), but 
only two weld samples have been examined: one in the as-welded condition and one after aging 
at 427C for 40,000 hr. These precipitates may simply be carbides that were present in the millannealed 
(i.e., as-received) condition. Carbides are known to be present in Nibase alloys similar 
to Alloy 22, but they are usually within the grains and are generally called primary carbides to 
distinguish them from other secondary phases that form, often on grain boundaries, after an 
aging treatment (Tawancy et al. 1983 [DIRS 104991], p. 40,  3). The particle in Figure 44 was 
not identified but could be one of these primary carbides. 
Welding causes melting of the alloy and the development of an as-cast structure upon cooling. 
The dendritic structure typical of welds can be seen in Figure 35 through Figure 40. As an Alloy 
22 weld solidifies, Mo and Cr are rejected from the solid phase, causing their concentration to 
  73  
increase in the liquid (see Figure 74). Therefore, the interdendritic regions, which are the last 
solids to form in a weld, tend to have high concentrations of these elements relative to typical 
values for Alloy 22 (Cieslak et al. 1986 [DIRS 104966], p. 2039, Figure 7). Because formation 
of the TCP phases, which are also enriched in Mo and/or Cr, is favored by higher Mo and Cr 
concentrations, these phases are present in the interdendritic regions of Alloy 22 welds. TCP 
particles can be seen in Figure 37. P phase is primarily seen in the as-welded condition of Alloy 
22 welds, but  and  phases are also seen (Cieslak et al. 1986 [DIRS 104966], p. 2041,  2). 
Only one particle was seen in TEM in an Alloy 22 weld (Figure 42 and Figure 43); this particle 
could be indexed as either P or  phase. 
Because precipitates are present in Alloy 22 welds from the beginning, kinetics of precipitation 
is not an issue as it is in the base metal and HAZ. Whether these precipitates are stable and grow 
or unstable and dissolve with aging at repository-relevant temperatures must also be determined. 
In addition, for weld regions where stress mitigation techniques are used, these techniques may 
result in areas of increased cold-work, and hence, dislocation density. As a result, the increase in 
dislocation density may result in faster diffusion rates for phase precipitation, and the effect of 
such faster diffusion rates under repository-relevant temperatures on phase kinetics must be 
evaluated. 
6.4 CONSIDERATION OF ALTERNATIVE CONCEPTUAL MODELS 
The martensite transformation reaction was considered as a potential alternative conceptual 
model (Table 7). The martensitic transformation is primarily driven by the difference in free 
energy as an alloy is cooled from a higher to a lower temperature. During martensitic 
transformation, the atoms in the parent-phase lattice structure are realigned into the martensiticphase 
lattice (Reed-Hill et al. 1973 [DIRS 162684], p. 636). During the formation of martensite, 
no compositional changes occur as the parent-phase lattice is realigned into the martensitic 
phase. In addition, for the transformation reaction to proceed, diffusion in either the parent phase 
or martensitic phase is not required (Reed-Hill et al. 1973 [DIRS 162684], p. 636). As a result, 
martensitic-transformation reactions are usually referred to as diffusionless phase 
transformations. 
Table 7 Alternative Conceptual Model Considered 
Key Assumption Alternative Conceptual Model Screening Assessment and Basis 
Martensitic transformation No martensite observed in Alloy 22 Analogous phasetransformation 
reaction 
Another typical characteristic of the martensitic-transformation reaction is that it primarily 
depends on temperature change. For example, the faster the alloy is cooled, the faster the 
parent/martensitic interface moves, since the progress of the martensitic reaction is dependent on 
temperature changes that affect the free energy of the reaction (Reed-Hill et al. 1973 
[DIRS 162684], p. 642). 
The speed of the martensitic transformation is very rapid. It has been shown that a martensitic 
plate in steel grows in 105 to 107 seconds to its full size, at near sonic velocities (Porter et al. 
  74  
1992 [DIRS 163028]). In ironnickel alloys, speeds of 800 to 1100 m/s were measured in the 
growth of plate martensite (Porter et al. 1992 [DIRS 163028]). 
The martensitic-transformation reaction is widely used in industry to increase the mechanical 
properties of a variety of steels. In the family of controlled-transformation steels, the typical 
microstructure of fine lath martensite with a possible fine network of -ferrite, in combination 
with work hardening and tempering, provides these steels with strengths up to 1500 MPa 
(Pickering 1976 [DIRS 161275]). Examples of controlled-transformation steels are known as 
transformation-induced plasticity (TRIP) steels, where deformation induces the martensitic 
transformation (Porter et al. 1992 [DIRS 163029]). Common uses of TRIP steels include highimpact 
barriers or shields and automotive crash safety components (e.g., door impact bars). 
The shape memory alloy, Nitinol (TiNi), uses a microstructure of very fine twinned martensite 
to allow this alloy to undergo large amounts of deformation. For example, the alloy may be 
formed in a fully reversible manner when deformation occurs below the martensite initiation 
temperature. Subsequent heating of the alloy above the martensite initiation temperature restores 
the deformed structure back to its original shape (Porter et al. 1992 [DIRS 163029]). 
Commercial applications of Nitinol include cellular phone antennas, heart valve sizer tools, 
eyeglass frames, and spinal vertebrae spacers. 
The martensitic-transformation reaction is a well-understood and widely used model for phase 
transformation. Thus, it has been considered as an alternative conceptual model for the phase 
transformation for Alloy 22. However, in experimental results to date that span a wide range of 
temperatures and time periods, no martensite has been observed to form in Alloy 22. Due to its 
inherent characteristics (e.g., temperature change dependent reaction and extreme rapid 
formation times), if martensite were to form in Alloy 22, it would have been easily observed in 
the tests conducted to date. As a result, the martensitic phase is not applicable to Alloy 22 phase 
transformations, and therefore, the alternative conceptual model using the martensitictransformation 
reaction is screened out from further consideration. 
6.5 MODEL FORMULATION 
6.5.1 Background and Methodology 
Thermo-Calc [DIRS 163153] and DICTRA [DIRS 163154] are based on the so-called 
CALPHAD (CALculation of PhAse Diagrams) approach (Saunders et al. 1998 [DIRS 104975]; 
Spencer 1999 [DIRS 161436]; Small 1999 [DIRS 163389]; Bernard et al. 1999 [DIRS 163390]; 
Sundman 1999 [DIRS 163391]; Spear et al. [DIRS 163392]; Tanaka et al. 1999 [DIRS 163393]), 
introduced in the 1970s by Larry Kaufman, that involves the coupling of phase diagrams 
calculations for multicomponent alloy systems with other forms of thermo-chemical inputs to 
determine phase formation, proportions, and transformations. 
Even in binary alloy systems, difficulties often occur in determining phase formation 
characteristics solely by reference to an experimentally determined phase diagram. These 
difficulties arise from kinetic limitations on reaching equilibrium at low temperatures and from 
inherent limitations on the accuracy of some of the available experimental techniques. One of 
the major steps in the Thermo-Calc application is a full characterization of a phase diagram that 
  75 1 
1 
Aging and Phase Stability of Waste Package Outer Barrier 
includes all available thermodynamic information. This, in turn, offers a reliable overall 
assessment that also allows the calculation of ancillary properties from the same database. In 
analyzing higher-order multicomponent alloys, the Thermo-Calc application avoids 
thermodynamic inconsistencies with built-in safeguards, which ensure that phase boundaries are 
developed in accordance with the fundamental rules of classical thermodynamics. 
DICTRA fulfills the need to provide critical modeling and analysis of data by solving the 
diffusion equations, calculating thermodynamic equilibrium (with Thermo-Calc), solving the 
flux-balance equations, and finally predicting the displacement of phase-interface positions. 
This application is used to analyze the kinetics of phase evolution in alloys selected for the 
barriers of the waste package by predicting TTT diagrams for relevant phases forming as 
functions of time. This application also will help determine the solidification path and the effect 
of welding, and eventually post-annealing, on the stability and long-term aging of alloys selected 
for the waste package. Kinetics studies are focusing on the time-dependent formation of 
complex FrankKasper phases (such as P and  phases), and the long-range ordering in terms of 
phase evolution from the fcc matrix with times up to 10,000 years. The DICTRA application can 
also be applied to the study of grain boundary formation of carbides, silicides, and TCP phases 
and phase evolution under non-isothermal conditions, as is the case during welding. 
Starting with the thermo-chemical database provided by the SGTE (Scientific Group Thermodata 
Europe) data group, a detailed analysis of the stability of the binary alloys NiCr, NiMo, and 
MoCr, and of the ternary NiCrMo alloys was undertaken, since the databases included with 
the software were not optimally configured for Ni-Cr-Mo-W alloy studies. The study then 
focused on the role of additional solutes such as Si, C, Co, Nb, Ta, and W on stability, ordering, 
and precipitation in NiCrMo-based alloys. Finally, kinetic and thermodynamic modeling have 
been combined and applied to the study of diffusion-controlled transformations with the use of 
the DICTRA software linked to Thermo-Calc. 
6.5.2 Solidification according to the Scheil-Gulliver approach 
In all practical cases, solidification during most processing routes occurs in a non-equilibrium 
manner and gives rise to significant variations in the chemistry and the occurrence of secondary 
phases. Using a CALPHAD approach based on Scheil-Gulliver simulations, solidification can 
be studied, and predictions on the amount of undercooling can be made (Saunders et al. 1998 
[DIRS 104975]). Within this approach, a liquid of composition c0 is cooled to a small amount 
below its liquidus temperature T1. The solid precipitates out of the liquid with a composition cS 
1 whereas the composition of the liquid becomes cL . On further cooling to the temperature T2, the 
initial solid cannot change its composition (since back-diffusion in the solid phase in neglected in 
this approach). A local equilibrium is then established, and the liquid of composition cL 
2 transforms to a liquid of composition cL , and a solid with composition, and the process is 
repeated upon further cooling (see Figure 74). As solidification proceeds, the solid becomes lean 
in solute in the center of the dendrite whereas the liquid is enriched in solute until the 
composition of the liquid reaches the eutectic composition, and solidification is finally 
completed. Within the Thermo-Calc application software, the Scheil module is available to 
perform these simulations. 
  76  
Figure 74 Schematic description of solidification according to the Scheil-Gulliver approach (From 
(1)  i T d i 
Saunders et al. [DIRS 104975]) 
6.5.3 Computer Coupling of Phase Diagrams and Thermochemistry (CALPHAD) 
Computer coupling of phase diagrams and thermochemistry (CALPHAD) is capable of 
predicting the phase behavior in experimentally uninvestigated regions of a multicomponent 
system by extrapolating from their lower-order systems. This is a real test of the applicability of 
experimental and theoretical studies of thermochemistry and phase equilibria to the real world 
since most commercial materials have six or more important alloying elements. 
The equations and diagram presented in this section have been formulated and formatted by 
Turchi (Turchi 2003 [DIRS 162974]) for clarity and are a synthesis of information from the cited 
references and the Thermo-Calc and DICTRA software documentation. These equations and 
diagrams are included here to aid in understanding the CALPHAD approach of computational 
thermodynamics and phase kinetics. 
In the CALPHAD approach, the Gibbs energy of individual phases is modeled, and the model 
parameters are collected in a thermodynamic database. It is the modeling of the Gibbs energy of 
individual phases and the coupling of phase diagram and thermochemistry that make the 
CALPHAD a powerful technique in computational thermodynamics of multi-component 
materials. Models for the Gibbs energy are based on the crystal structures of the phases. For 
pure elements and stoichiometric compounds, the most commonly used model is the one 
suggested by the Scientific Group Thermodata Europe (SGTE) and has the following form as 
presented in Saunders et al. ([DIRS 104975], Eq. 5.3) (for simplicity, the pressure dependence 
and the magnetic contribution are not shown here), 
G . H SER = a + bT + cT ln (T ) + m m 
  77 + 
Aging and Phase Stability of Waste Package Outer Barrier 
m 
The left-hand side of the equation is defined as the Gibbs energy relative to a standard element 
reference (SER) state, where HSER is the enthalpy of the element in its stable state at 298.15C. 
Coefficients, a , b , c and di are the model parameters. The SGTE data for pure elements have 
been compiled by Dinsdale (Dinsdale 1991 [DIRS 161439]). 
For multi-component solution phases, the Gibbs energy has the following general formula, as 
presented in Saunders et al. ([DIRS 104975], Eq. 5.1): 
G = G + G 
o where G is the contribution from the mechanical mixing of pure components, Gideal 
mix the ideal 
mixing contribution, and Gxs 
mix is the excess Gibbs energy of mixing due to non-ideal 
interactions. Sublattice models have been widely used to describe solution phases [Sundman and 
Agren 1981 [DIRS 161460]; Andersson et al. 1986 [DIRS 161461]; Ansara et al. 1997 
[DIRS 161462]). For example, for a simple phase with two sublattices in an A-B binary system 
where both components enter both sublattices, the sublattice model is written as (A,B)p (A,B)q , 
where the subscripts p and q denote the number of sites of each sublattice, respectively. The 
three terms in Eq. 2 are written as (based on the formulation presented in Saunders et al. 
[DIRS 104975], Eqs. 5.30, 5.29, 5.33, 5.34), 
o I II o 
A A G = y y G A : A 
I I . II 
. k =0 
: A A, 
II II . I 
A B . y A  L k 
B + y y ( y A . y B + y 
. k =0 
o ideal 
mix + G mix 
xs 
I II o 
A B y y G y B A B : A 
II II 
G mix 
ideal = pRT (y A
I ln y A
I + y B I
ln y B 
I )+ qRT (y A
II ln y A
II + y B
II ln y B 
II ) 
G mix 
xs = A y y B . y A  L k 
A, A : B ( y A 
I . y B 
I )k + y B 
II  L k 
A, B :B ( y A 
I . y B I
)k . 
B  L B 
+ 
( y A, : B 
where y I and y II are the site fractions of A or B in the first and second sublattices, respectively. 
Go
J : I is the Gibbs energy of the compound Ip Jq , expressed by Equation 1. Lk 
A, * : B ( L* 
k 
:A,B ) is the k th 
order interaction parameter between component A and B in the first (second) sublattice. In this 
notation, a colon separates components occupying different sublattices, and a comma separates 
interacting components in the same sublattice. These equations can be generalized for phases 
with multi-components and multi-sublattices, and they reduce to a random substitutional model 
when there is only one sublattice. 
A . y II )k . 
. 
ANL-EBS-MD-000002 REV 1 ICN 0 78 
y G I II o 
A : B 
I 
+ 
)k 
k =0 
(2) 
I II o 
B B (3) y y G B : B 
(4) 
k =0 . 
k II (5) B 
June 2003 (6) 
 c  Go 
Gmix = RT  cI ln cI 
I 
 Gxs = I 
I J > I 
Aging and Phase Stability of Waste Package Outer Barrier 
For a multi-component solution in a particular phase  described with a single sublattice model, 
the three contributions to the total Gibbs energy reduce to (based on the formulation in Saunders 
et al. [DIRS 104975], Eq. 5.21): 
G = I I 
I 
k  k 
I , 
k 
I is the composition of the alloy in species I, 
 o 
 ideal 
mix 
k 
J I 
 c c J  L J I ( c . cJ ) 
where the molar Gibbs energy of mixing is expressed by a Redlich-Kister expansion (Redlich et 
al. 1948 [DIRS 161464]). In these expressions c 
and the L , is the kth-order binary interaction parameter between species I and J expressed as a 
polynomial in temperature T. Note that in both sets of expressions the excess Gibbs energy due 
to non-ideal contributions is given by the Muggianu equation (Saunders et al. [DIRS 104975], 
Eq. 5.22). 
Thermodynamic modeling begins with the evalution of thermodynamic descriptions of unit and 
binary systems. By combining the thermodynamic descriptions of consititutive binary systems 
and ternary experimental data, the thermodynamic descriptions of ternary systems are developed 
and so forth. These descriptions cover the whole composition and temperature ranges, including 
the experimentally uninvestigated regions. For this work, the original SSOL thermodynamic 
database has been developed using the CALPHAD technique. The computer program, Thermo- 
Calc, developed at the Royal Institute of Technology is then used. It is the most general and 
powerful program in computational thermodynamics of multi-component alloys (Saunders et al. 
1998 [DIRS 104975], Spencer 1999 [DIRS 161436]; Small 1999 [DIRS 163389]; Bernard et al. 
1999 [DIRS 163390]; Sundman 1999 [DIRS 163391]; Spear et al. [DIRS 163392]; Tanaka et al. 
1999 [DIRS 163393]). 
The CALPHAD approach is, in fact, the most successful method used at present in addressing 
specific materials questions of practical importance to industry and technology (Spencer 1999 
[DIRS 161436]; Small 1999 [DIRS 163389]; Bernard et al. 1999 [DIRS 163390]; Sundman 1999 
[DIRS 163391]; Spear et al. [DIRS 163392]; Tanaka et al. 1999 [DIRS 163393]). 
6.5.4 Diffusion Modeling in Phase Transformations 
Process simulations require the development of the kinetic description of alloy systems, that is, 
the mobility of species in individual phases (Saunders et al. 1998 [DIRS 104975]; Spencer 1999 
[DIRS 161436]; Small 1999 [DIRS 163389]; Bernard et al. 1999 [DIRS 163390]; Sundman 1999 
[DIRS 163391]; Spear et al. [DIRS 163392]; Tanaka et al. 1999 [DIRS 163393]; Engstrom et al. 
1994 [DIRS 161442]; Agren 1992 [DIRS 161440]). The models relating the mobility and 
diffusivity are based on the generalized Onsager flux equation. As an example, for a phase 
consisting of a substitutional sublattice and an interstitial sublattice, the intrinsic diffusion 
coefficient, Dkj (the diffusivity of component k with respect to the gradient of component j), is 
related to the atomic mobility Mi (i for all the elements in a phase) with the following formula 
(based on the formulation in Agren 1992 [DIRS 161440]): 
  79 k = 
i 
M = i 
 xi 
where i S denotes that component i is substitutional and i .S denotes that component i is 
interstitial, xk is the mole fraction of component k , i is the chemical potential of component i 
derived from the Gibbs energy of the phase, yVa represents the site fraction of vacancy in the 
interstitial sublattice, and ik is the Kronecker delta. The mobility Mi associated with species i is 
further related to a frequency factor M 0 and composition with the following equations, as 
presented in the DICTRA Users Guide (Thermo-Calc Software 1998 [DIRS 162973]): 
i M0 
exp .. 
.Gi . 
RT . RT . 
j k > j m 
Aging and Phase Stability of Waste Package Outer Barrier 
D i kj = ( ik . uk )u M i 
 i +  ik i y u VaMi 
 i
u i S 
xk with u 
i S 
j m 
j k: , m .G i i 
j 
and ik ={1 
0 
i 
i 
=
 
k
k 
. j m i j k m i j n y y y Gi =  I y y II .Gj :m +  I I y y y II .Gj ,k :m +   I II 
m 
II .Gi
j :n ,m (8) 
j :n ,m , are expressed with a polynomial similar to the summations in Equation 3. 
where .Gi is the activation Gibbs energy of component i , and .Gi 
energy of component i with components j and m on the first and second sublattices, respectively. 
This formulation for a ternary system is based on the binary system formulation presented in 
Equation 5.37 of Saunders et al. (Saunders et al. 1998 [DIRS 104975]). The interaction terms, 
and .G 
The individual parameters are evaluated from chemical and tracer diffusion data. 
By combining thermodynamic and kinetic descriptions of alloy systems, phase transformations 
can then be simulated. The schematic flow chart of the DICTRA simulation is shown in Figure 
75 (Turchi 2003 [DIRS 162974]). The most significant feature of this simulation procedure is 
the coupling of thermodynamics and kinetics simultaneously. 
 
ANL-EBS-MD-000002 REV 1 ICN 0 80 
(6) 
u i .S j 
(7) 
n m >n j 
j :m is the activation Gibbs 
June 2003  
Thermodynamics DATABASE Kinetics 
2 Gibbs G 
x x j Energy 
Interfacial 
Equilibrium 
Solve 
Fluxbalance 
 
i 
Figure 75 Schematic flow chart of numerical simulation of phase transformations 
ANL-EBS-MD-000002 REV 1 ICN 0 81 
Kinetic 
Coefficients 
Solve 
Diffusion Equations 
Rate of 
Reaction 
June 2003  
6.6 MODEL RESULTS 
The models results are presented in two parts: computational and experimental results. The 
computational results were conducted in four general steps: (1) validation of the Thermo-Calc 
results for the alloy systems and components of interest (Sections 7.1 through 7.4), (2) 
determination of the property diagrams for the Ni-based alloys of interest (Section 6.6.1), (3) 
determination of the kinetic properties (TTT diagrams) of the Ni-based alloys of interest (Section 
6.6.2), and (4) validation of the computational phase kinetic results with measured data (Section 
7.4). The experimental results are presented in three areas: (1) volume-fraction measurements in 
Alloy 22 base metal, including grain boundaries (Sections 6.6.3.1 and 6.6.3.2); (2) volumefraction 
measurements in Alloy 22 weld metal (Section 6.6.3.3); and (3) micro-hardness 
measurements in Alloy 22 base metal, which are indicative of LRO (Section 6.6.4). 
6.6.1 Property Diagrams of the Ni-Based Alloys 
The property diagrams of various Ni-based alloys were calculated using Thermo-Calc at their 
nominal alloy composition as indicated in Table 8. These diagrams display the phase (or 
volume) fractions as a function of temperature. 
Table 8 Nominal chemical compositions of Ni-Cr-Mo alloys (in wt%) (Turchi et al. 2003 [DIRS 162974]) 
Cr Mo Fe W Mn C Other Alloy Ni 
(balance) 
0.02 Co: 2.5 (max) 1.0 C-276 57 14.516.5 1517 4-7 34.5 
0.015 Co: 2.0 (max) 1.0 - 3 (max) 1417 1418 53 C-4 
0.5 0.01 Al: 1.4 59 59 2224 1516.5 1.5 (max) - 
0.015 Co: 2.5 (max) 0.5 22 56 2022.5 12.514.5 2-6 2.53.5 
6.6.1.1 Alloy 22 
In the case of Alloy 22, the Thermo-Calc results shown in Figure 76 (left and central panels) 
confirms, that at equilibrium and low temperature, a three-phase field that includes the Ni2Crtype 
of ordered phase (or oP6), a complex tetrahedrally closed-packed structure (P phase, or 
similar such as ), and the fcc matrix should exist. It is interesting to note in Figure 76 (right 
panel) that if the P phase is suspended during the calculation of the property diagram 
(suspending a phase is analogous to assuming that the phase is not kinetically favored), the 
domain of stability of the  phase extends in a broader range of temperatures, towards low 
temperatures from 930C to 448C (instead of 802C). Also, it is interesting to note that the 
ordered phase of Ni2Cr-type (oP6) competes with the P phase, as illustrated in Figure 77. 
Whereas oP6 is itself stable up to 566C (all phases suspended except fcc and oP6), the complete 
property diagram indicates a maximum temperature of stability at about 408C. Finally, at low 
phase fraction, a number of carbides and silicides are stable, namely: M7C3, V3C2, and Cr3Si. It 
is likely that these precipitate phases will preferably form in the proximity of the grain 
boundaries, where C and Si are usually observed. 
  82 DTN: LL030106312251.013 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: In the left panel, the diagram in the whole range of phase fraction is displayed whereas in the central panel a 
detailed description of the diagram clearly shows the phases that occur at low phase fraction. The right 
panel is the property diagram of Alloy 22 in the case the P phase is not considered in (i.e., suspended 
during) the calculations. 
Figure 76 Calculated property diagrams of Alloy 22. 
Figure 77. Calculated property diagrams of Alloy 22 with the liquid, the fcc matrix, and the  phase (left 
panel), the P phase (central panel), and the oP6-ordered phase (right panel) considered in the 
calculations. 
By retaining the liquid phase and the fcc matrix, and  phase, P phase, or oP6 ordered phase 
during the calculation of the property diagram, the domain of existence of , P or oP6 with 
respect to fcc can be easily evaluated, as shown in Figure 77. For example with no other 
competing phases than the fcc, the  phase exhibits a broad domain of stability that is limited at 
low temperature when the oP6 is reintroduced in the calculations (see Figure 76, right panel), 
and even more so when the P phase is allowed (see Figure 76, left panel). Hence it can be 
concluded that under particular circumstances where metastability can be promoted, the  phase 
can be found at temperature lower than the one predicted at equilibrium. 
In Figure 78, the analysis in terms of weight fraction as a function of temperature of each major 
element (Ni, Cr, or Mo), and W and Fe (when present) for each individual phase, namely the fcc 
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Aging and Phase Stability of Waste Package Outer Barrier 
matrix, the oP6 ordered phase, and the two TCP phases, P and , confirms the expectation. 
Indeed, in the TCP phases, a noticeable depletion in Ni and an enhancement in Cr in the P phase 
or Mo in the  phase in their temperature range of stability (indicated by the horizontal line with 
arrows on both ends) are observed in Figure 78 (bottom panels). In the case of the oP6 ordered 
phase, a depletion in Ni and a noticeable departure from the nominal Cr and Mo compositions is 
observed (see Figure 78, top right panel). These predictions should be revisited in the case of 
welding where alloy stability can be affected by the presence of TCP phases and of the oP6 
ordered phase at compositions that strongly depart from the nominal composition of Alloy 22. 
NOTE: The horizontal line with arrows on both ends indicates the domain of stability of the phase whereas the 
stand-alone vertical line indicates the temperature at which the phase starts occurring. 
Figure 78. Weight fraction of Ni (red), Cr (blue), Mo (green), W (brown), and Fe (black), versus 
temperature in the fcc matrix, the oP6, the P and  phases for Alloy 22 at its nominal 
composition (see text). 
  84  
6.6.1.2 Alloy C-4 
The calculated property diagram for Alloy C4 is shown in Figure 79. In the case of alloy C4, 
the main phases forming, besides the fcc matrix, are the P and the Ni2Cr-type (oP6) phases. In 
addition, the M23C6 and the A15 Cr3Si-type phases form at very low phase fraction. The 
relatively low content in Cr in this alloy excludes the formation of the  phase. 
NOTE: Additional phases (mostly carbides and silicides) predicted with a phase fraction less than 0.01 are not 
reported. 
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Figure 79 Calculated property diagrams (phase fraction versus temperature) of Alloy 22, Alloy 59, C4, 
and C276 at their nominal composition (see text). 
  85  
6.6.1.3 Alloy C276 
The calculated property diagram for Alloy C276 is shown in Figure 79. In the case of alloy 276, 
as in the case of alloy C4, the low Cr and Mo content significantly reduces the formation of the 
 phase and prevents the formation of the Ni2Cr-type (oP6) ordered phase. Because of the 
presence of C and Si, the A15 of Cr3Si-type and M23C6 are found in this alloy. 
6.6.1.4 Alloy 59 
The calculated property diagram for Alloy 59 is shown in Figure 79. In the case of Alloy 59, it is 
interesting to note that the P phase forms in a broader range of temperature (up to about 900C) 
than in Alloy 22 (811C); this can be attributed to a higher Cr and Mo content in Alloy 59 than 
in Alloy 22. Once again, at very low phase fraction, the A15 of Cr3Si-type and M7C3 are stable. 
6.6.2 Equivalent Alloys: 22, 59, C4, and C276 
A definition for the equivalent composition of Ni, Cr, and Mo has been used (see Section 7.3) 
which is usually considered when discussing alloy stability in Ni-based alloys (Cieslak et al. 
1982 [DIRS 104966]. Using these equivalents, compositions of the property diagrams of the 
equivalent Alloy 22, Alloy 59, C4 and C276 compositions have been calculated and the results 
are displayed in Figure 80. The results are directly comparable to those displayed in Figure 79. 
Significant differences are noted. For example, in all cases the alloys at their equivalent 
compositions display an oP6 ordered phase with a larger volume fraction and a stabilization at 
much higher temperature than in the corresponding alloys at their nominal composition. This 
enhanced stability of the oP6 phase is due to a destabilization of the P phase at low temperature. 
Note also that the  phase is no longer stable in all four cases. Hence extreme caution has to be 
taken indeed when basing argument based on Cr, Mo, and Ni equivalents. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: Additional phases (mostly carbides and silicides) predicted with a phase fraction less than 0.01, are not 
indicated in the diagrams. 
Figure 80 Property diagrams (phase fraction versus temperature) of the equivalents of Alloy 22, Alloy 59, 
C4, and C276 at their nominal composition (see text) 
6.6.3 Scheil-Gulliver Simulation of Solidification Processes in Ni-based Alloys 
Most of the Ni-based alloys display a fair amount of under-cooling, of the order of 140C (e.g., 
133, and 127, 150, and 150C for Alloy 22, Alloy 59, C4, and C276, respectively), and this 
result has been confirmed with Scheil-Gulliver simulations, see Figure 81. From the liquid 
phase, the first solid phase to occur in all alloy cases is the fcc matrix, and then a small fraction 
of A15-based Cr3Si compound starts forming. The last phase to form under the Scheil-Gulliver 
  87  
conditions (that assume local equilibrium, infinite diffusion in the liquid phase, and no back 
diffusion in the solid phase) is the  phase (except for C-4 and C276), and the under-cooling is 
accompanied by a decrease in Ni content and an increase in Mo and Cr contents from the 
nominal composition (see Figure 78, bottom right panel in the base metal case) and Figure 82. 
These results clearly indicate that the alloys of this series can be properly annealed in a relatively 
broad region of temperature and quenched to retain the single fcc phase. However, a slight 
departure from the nominal alloy composition has to be kept in mind. 
The transition temperatures are determined during the execution of the Scheil-Gulliver 
simulations and have been added onto the plots of Figure 81 for clarity. 
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Figure 81 Scheil-Gulliver simulation results for Alloy 22, Alloy 59, C4, and C276: temperature versus 
weight fraction of solid phase that describes the amount of under-cooling and the succession 
of phases during cooling. 
  88  
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Figure 82 Scheil-Gulliver simulation results of weight fraction of Ni (red), Cr (blue), and Mo (green) in the 
fcc matrix for Alloy 22, Alloy 59, C4, and C276 as functions of temperature, during 
solidification. 
6.6.4 Kinetic Properties of Nickel-Based Alloys 
Kinetic and thermodynamic modeling have been combined and applied to the study of diffusioncontrolled 
transformations with the use of the DICTRA application linked with Thermo-Calc. 
Simulations have been performed on three alloy systems, in order of increasing complexity: (1) a 
binary NiCr alloy, (2) a pseudo-binary NiX(Cr3Mo)1X alloy, and (3) a ternary NiCrMo alloy 
that can be considered as a surrogate for Alloy 22, with the following nominal composition: 55.7 
Ni, 21.1 Cr, and 13.5 Mo (in wt %). The TTT diagrams resulting from these simulations are 
described below. 
6.6.4.1 TTT diagram for the fcc to Ni2Cr-type (oP6) Ordered Phase in Ni2Cr 
A first series of calculations have been performed to predict the TTT diagram in the case of a 
10% transformation of an fcc-based NiCr solid solution to the ordered Ni2Cr (oP6) phase for 
which case experimental results were available (Karmazin 1982 [DIRS 154881]). The results are 
displayed in Figure 84. The MOB database that contains the mobility and the diffusion 
  89  
coefficient of the Cr species in an fcc-Ni matrix has been adjusted to account for the kinetics of 
transformation studied experimentally by Karmazin 1982 [DIRS 154881]. It was assumed that 
the variation of the fcc lattice parameter as a function of time at various annealing temperatures 
(see Figure 83) is directly proportional to the amount of ordered phase formed in the disordered 
fcc matrix. Based on this relation, three points of the TTT diagram have been obtained at 450, 
500, and 530C from (Karmazin 1982, Figure 6 [DIRS 154881]) in the case of a 10% 
transformation from fcc to oP6 of the Ni-rich solid solution with 33.3 at. % Cr. The location of 
the nose of the experimental TTT curve has been used to determine the kinetic parameters that 
are defined in the MOB database for subsequent DICTRA calculations. The DICTRA results for 
the same rate of transformation (10 %) are also displayed in Figure 84, and the shape of the C 
curve compares very favorably with the experimentally deduced one. From the stability studies 
(see Section 7.1), the value of the critical order-disorder temperature (that positions the 
asymptote in the TTT diagram), 553C, compares very well to the experimentally assessed value 
of 540C. Note that the transformation is rather sluggish and is initiated after about 200 hours. 
Extrapolation of the TTT curve to lower temperatures clearly indicates that in this binary alloy, 
the oP6 ordered phase cannot form out of the fcc solid solution at less than 200C for as long as 
10,000 years. 
NOTE: The horizontal lines delineate the range of existence of the oP6 long-range order (LRO) from the disordered 
phase (top line) to the fully ordered phase (bottom line). 
Figure 83 Experimental variation of the lattice parameter with time at fixed isothermal annealing for Ni2Cr 
alloy, from Fig. 6 of Karmazin 1982 [DIRS 154881] 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The experimentally deduced TTT diagram (blue solid squares) (Karmazin 1982 [DIRS 154881]) for the same 
transformation rate is also shown for comparison. 
Ni 
Figure 84 Calculated Isothermal TTT diagrams (red solid circles) for an fcc-based matrix of a binary 
2Cr alloy transforming into the oP6 ordered phase, with transformation rate of 10%. 
6.6.4.2 TTT Diagram for the fcc to Ni2Cr-type (oP6) Ordered Phase in a Pseudo-binary 
NiX(Cr3Mo)1X Alloy 
To make further comparisons with experimental results, a pseudo-binary NiX(Cr3Mo)1X alloy is 
considered in which kinetic data are available from the experimental work of Karmazin et al. 
(1994 [DIRS 161444]). In this study, we assume that the kinetic parameters (diffusion 
coefficient and mobility) for Mo in Ni are identical to those of Cr in Ni. As in the previous case 
(Section 6.6.4.1), there is a linear relation between the variation of the lattice parameter and the 
amount of fcc matrix transformed into the oP6-ordered phase. In Figure 85, the property 
diagram of this alloy is displayed with only the fcc and oP6 phases included in the calculation. It 
is shown that the ordered phase is stable below 627oC. Based on this assumption, the DICTRA 
results for 5, 10, and 15% transformation from the fcc-solid solution to oP6 for Ni-24 at.% Cr-8 
at.% Mo (or 20.78 wt.% Cr and 12.78 wt.% Mo) are reported in Figure 86. The experimental 
point (solid square) indicated in Figure 86, representing 5% transformation, has been deduced 
from the experimental study of the variation of the lattice parameter with time under isothermal 
annealing condition reported in Figure 3 of Karmazin et al. (1994 [DIRS 161444]) (see Figure 
98c). The results show that, (1) the thermodynamic driving force at this alloy composition and 
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Aging and Phase Stability of Waste Package Outer Barrier 
the kinetic factors account fairly well for the kinetics of transformation and (2) although Mo 
enhances the stability of the ordered phase (increased critical order-disorder temperature at about 
627C), the extrapolation of the TTT curves to lower temperatures confirms the observation 
already made in the binary case about the impossibility of forming the oP6 ordered phase out of 
the fcc-solid solution at less than 200C for as long as 10,000 years. 
NOTE: The fcc and oP6-ordered phases are considered. All other phases are suspended during the calculations. 
Figure 85 Property diagram of Ni-24 at.% Cr-8 at.% Mo (or 20.78 wt.% Cr and 12.78 wt.% Mo) 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The black solid square indicates the results deduced from annealing experiments performed on a NiCrMo 
alloy at the same composition presented in Karmazin et al. (1994 [DIRS 161444]). 
Figure 86 Calculated Isothermal TTT diagrams for an fcc-based matrix of a ternary Ni20.78Cr12.78Mo 
(in wt.%) Cr alloy transforming into the oP6 ordered phase, with transformation rates of 5, 10, 
and 20%. 
6.6.4.3 Kinetics of transformation in a Ni21.1 wt.% Cr13.5 wt.% Mo alloy 
For this series of calculations, the case of a ternary Ni-Cr-Mo alloy that can be considered as a 
surrogate for Alloy 22, with the following nominal composition: 55.7 Ni, 21.1 Cr, and 13.5 Mo 
(in wt %) was considered. 
Three transformations were considered: the fcc matrix to the oP6-ordered phase, the fcc matrix 
to the P phase and the fcc matrix to the  phase. The corresponding property diagrams 
associated only with the fcc matrix and the transformed phase (oP6, P or ) were considered in 
the calculations are displayed in Figure 87. In the study of the kinetics of phase formation of the 
oP6-ordered phase, 7.5 wt.% Mo is used instead of 13.5 wt.%. This reduction in Mo accounts 
for the role of W in destabilizing the ordered phase, and the relative contribution of W is 
approximately twice that of Mo (1 wt % W ~ 2 wt % Mo). Details of this treatment are 
discussed in Section 7.4. 
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Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The fcc matrix and the oP6-ordered phase (left panel; in this case 7.5 wt.% Mo were considered instead of 
13.5 wt.% (see text), P phase (middle panel), and  phase (right panel) are considered. All other phases are 
suspended during the calculations 
Figure 87 Property diagram of Ni-21.1 wt.% Cr-13.5 wt.% Mo 
In Figure 88, the TTT diagram associated with the fcc to oP6 transformation is displayed with 2, 
10, and 15% transformation rates. When compared with the results for the binary Ni2Cr alloy, 
the combined role of Mo and W has the effect of enhancing the critical order-disorder 
temperature from 553 to 596oC. 
ANL-EBS-MD-000002 REV 1 ICN 0 94 June 2003  
700 
600 
500 
400 
300 
200 
10 0 
Figure 88 Calculated isothermal TTT diagram for an fcc-based matrix of a ternary Ni-21.1Cr-7.5Mo (in wt 
%) alloy (surrogate for Alloy 22) transforming into the oP6 ordered phase, with transformation 
rates of 2, 10, and 15%. 
The transformation from the fcc-based matrix to the P phase with 2, 10, and 15% transformation 
rates was considered (from left to right in Figure 89) as a function of time and temperature. The 
results are comparable with the qualitative observations cited in Turchi 2001 ([DIRS 154934]). 
The transformation from the fcc-based matrix to the  phase with 2, 5, and 10% transformation 
rates was simulated (from left to right in Figure 90) as a function of time and temperature. In 
contrast to the formation from the fcc-matrix to the oP6 ordered phase that is rather slow, the 
incipient formation of the P phase is quite fast (a few hours in the bulk). However, as was 
concluded previously, the extrapolation of these TTT curves to lower temperatures clearly 
indicates the impossibility of forming the P phase out of the fcc-solid solution at less than 200C 
for as long as 10,000 years. 
ANL-EBS-MD-000002 REV 1 ICN 0 95 
T ( o C) 
time (yrs) 
10 3 10 2 10 -3 10 -2 10 -1 10 0 10 1 
596 o C 
15% 
10% 
2% 
10 7 10 6 10 4 10 3 10 2 10 1 10 5 
time (hrs) 
DTN: LL030106312251.013 
T (K) 
10 5 10 4 
900 
800 
700 
600 
500 
10 9 10 8 
June 2003  
DTN: LL030106312251.013 
Figure 89 Calculated isothermal TTT diagram for an fcc-based matrix of a ternary Ni-21.1Cr-13.5Mo (in 
wt %) alloy (surrogate for Alloy 22) transforming into the P phase, with transformation rates of 
2, 10, and 15%. 
  96  
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Figure 90 Calculated isothermal TTT diagrams for an fcc-based matrix of a ternary Ni-21.1Cr-13.5Mo (in 
wt %) alloy (surrogate for Alloy 22) transforming into the  phase, with transformation rates of 
2, 5, and 10%. 
It is worth noting that before any conclusion can be drawn from this study, validation of the 
predictions by a quantitative analysis of phase formation in samples annealed at various 
temperatures and for several aging times will be required. Note also, that in these calculations, 
grain boundary formation is not considered; that is, the results only apply to bulk formation and 
homogeneous phase evolution. 
6.6.5 Volume-Fraction Measurements in Alloy 22 
In order to measure the amount of TCP phase precipitation in Alloy 22 base metal and welds, 
area-fraction measurements have been made, using SEM image analyses, as a function of aging 
time and temperature. Using standard methods of quantitative stereology, it has been shown that 
area-fraction measurements (and correspondingly, linear-fraction measurements on grain 
boundaries) are mathematically equivalent to volume-fraction measurements (Vander Voort 
1999 [DIRS 161300]; Hilliard et al. [DIRS 161454]). Thus, the area-fraction measurements 
presented in this AMR are equivalent to the volume-fraction values in Alloy 22 as a function of 
time and temperature. 
The SEM image analyses that were performed measured gross TCP phase precipitation in the 
samples as a function of time and temperature. No TCP phase extraction was conducted to 
differentiate the types of TCP phases that may be present (e.g.,  or P phases) in these 
measurements. 
  97 y = 0.0356x0.7004 
R2 = 0.9324 
800C 
760C 
750C 
700C 
650C 
Power (760C) 
100,000 10,000 
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Aging and Phase Stability of Waste Package Outer Barrier 
6.6.5.1 Volume-Fraction Measurements in Base Metal 
Using the TCP precipitation area-fraction measurements for base metal presented in Table 3, 
Figure 91 summarizes these measurements as a function of time and temperature. A trend line is 
included for the results at 760C, where more than two measurements were made. The trends of 
the results shown in Figure 91 are consistent with SEM observations and the TTT diagram of 
Figure 89. TCP phases are seen to readily form at higher temperatures (760 to 800C) in less 
than 1000 hr. In general, as the temperature is decreased, the onset of TCP phase precipitation is 
delayed, and it also appears that the slopes of trend lines at lower temperatures may become 
shallower, indicating a slower rate of phase precipitation. 
35.00 
30.00 
25.00 
20.00 
15.00 
10.00 
5.00 
0.00 
1,000 100 10 1 
Time (hr) 
Figure 91 TCP phase precipitation in Alloy 22 base metal as a function of time and temperature 
While more measurements over longer periods of time are needed to formulate conclusions on 
long-term behavior, the measurements presented here are similar to the results of the TTT 
diagram (Figure 89) in that forming TCP phases from the fcc-solid solution at less than 200C 
within 10,000 years is unlikely. 
6.6.5.2 Area-Coverage Measurements on Grain Boundaries 
Similar to the area-fraction measurements on base metal samples, area-coverage measurements 
(linear-fraction measurements) on grain boundaries have been performed using SEM image 
analyses. Again, using standard methods of quantitative stereology, these linear-fraction 
measurements of TCP phase precipitation on grain boundaries are mathematically equivalent to 
volume-fraction measurements (Vander Voort 1999 [DIRS 161300]; Hilliard et al. 
[DIRS 161454]). Figure 92 summarizes the grain boundary measurements shown in Table 4. 
% Area Fraction 
  98 1 
Aging and Phase Stability of Waste Package Outer Barrier 
0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0 
0.1 
Figure 92 TCP phase precipitation on Alloy 22 grain boundaries as a function of time and temperature 
Due to the paucity of grain coverage data at this time (as shown in Figure 92), only a few 
observations regarding TCP phase precipitation on grain boundaries are noted. Similar to TCP 
phase precipitation in base metal, TCP phase precipitation on grain boundaries is dependent on 
temperature. The onset of TCP phase precipitation on grain boundaries appears to be delayed 
with decreasing temperature. More measurements over longer time periods, as well as 
computational modeling, are needed before any conclusions can be made. 
6.6.5.2.1 Estimation of Bounding Case for TCP Phase Precipitation on Grain Boundaries 
Until more measurements of TCP phase precipitation on grain boundaries or the corresponding 
results from computational modeling are available, a bounding case of TCP phase precipitation 
on grain boundaries can be formulated from the grain boundary precipitation measurements. 
Nucleation and growth kinetics can often be represented by an equation of the following form: 
where f is the volume fraction of the precipitating phase, t is the time at the aging temperature, 
and k and n are constants (Christian 1981, p. 19, Eq. 4.11). The value of k depends on nucleation 
and growth rates and therefore depends very strongly on temperature, usually of the following 
form: Grain Boundary Covered Fraction 
10 1 
Time (hr) 
f =1-exp(-ktn ) 
ANL-EBS-MD-000002 REV 1 ICN 0 99 
760C 
704C 
649C 
1000 100 
DTN: LL030606912251.020 
(9) 
June 2003  
where C1 and C2 are constants and T is the temperature (e.g., Christian 1981, p. 438, Eq. 49.2, 
where the exponentials representing atomic vibrational frequency and activation energy for an 
elementary atomic movement have been combined). Ideally, the volume fraction of precipitation 
would be measured as a function of time and temperature and would be fit to Equation 9. 
Precipitation times can be fit to Equation 9 if it is modified for a constant volume fraction. 
Combining Equations 9 and 10 at constant volume fraction yields: 
1.E+08 
10,000 yrs 
1.E+07 
1.E+06 
1.E+05 
1.E+04 
y = 2E-19e45488x 
R2 = 0.9949 
1.E+03 
1.E+02 
1.E+01 
1.E+00 
1.E-01 
0.0009 0.0011 
a function of aging temperature. 
Aging Time (hr) 
k = C1 exp(-C2 / T ) 
ln(t 
n T 
y = 6E-20e45488x 
R2 = 0.9949 
0.0013 
where Cf is constant containing the constant volume fraction term, f, from Equation 9. Equation 
11 is of the usual linear form, y=mx+b, representing ln(tf) as a function of 1/T. Plots of log(time) 
versus reciprocal temperature for 20 and 80% grain boundary coverage are shown in Figure 93. 
Figure 93 Time to form 20 and 80 % grain boundary coverage of TCP phases in Alloy 22 base metal as 
6.6.5.2.2 Basis for Confidence That Bounding Case Is Conservative 
As a measure of the reasonableness of the data plotted in Figure 93, the activation energy can be 
calculated. The slopes of the lines in Figure 93 (after accounting for the log(e) factor) are equal 
to C2/n in Eq. 11. If these slopes are averaged and n is assumed to be equal to one, which is a 
reasonable value for n (Christian 1981, [DIRS 104964] p. 542, Table IX and p. 19), then the 
activation energy is 378 kJ/mol (or 90 kcal/mol). This value for activation energy (for Alloy 22 
f 
1 )= 
C2  +Cf 
0.0015 
Reciprocal Temperature (1/K) 
0.0017 
ANL-EBS-MD-000002 REV 1 ICN 0 100 
(10) 
(11) 
20% 
80% 
Expon. (20%) 
Expon. (80%) 
200 C 
0.0021 0.0019 
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June 2003  
grain boundary precipitation) is higher than the value of 62 kcal/mol obtained by Hodge (1973 
[DIRS 104968], p. 378  1) for precipitation in alloy C276. It is expected that the activation 
energy for Alloy 22 would be slightly higher than that of C276 primarily due to the differences 
in chemical composition (C276 contains more Mo and W) and phases formed. As shown in 
Section 6.6.1, unlike Alloy 22, C276 does not form an oP6 ordered phase. In Alloy 22, it was 
shown that the formation of the ordered oP6 phase competes with the P phase. As a result, it is 
reasonable that the activation energy for C276 would be slightly lower than that observed for 
Alloy 22. This activation energy value for Alloy 22 grain boundary precipitation is also the 
within the expected order of magnitude and fairly typical for diffusion of relevant elements in Ni 
(Brandes et al. [DIRS 104962], Ch. 13, pp. 13 to 23). For example, the activation energy for 
diffusion of Cr in Ni is 272.6 kJ/mol, that of Fe is 253270 kJ/mol, and that of W in Ni is 299 
308 kJ/mol. It is expected that these activation energy values in binary alloy systems would be 
lower than that in Alloy 22, a multicomponent alloy. 
The data in Figure 93 represent the precipitation kinetics during an isothermal anneal. The 
repository temperature is not expected to remain constant. Instead, it will peak at some 
temperature and slowly decrease over time (BSC 2001 [DIRS 158204]). Therefore, the actual 
waste package temperatures are likely to be well below 200C for a significant fraction of their 
required service life. Since the rate of these TCP precipitation reactions is strongly dependent on 
temperature and since it decreases with temperature, the above bounding case where temperature 
is assumed to be constant at its peak value is conservative. 
6.6.5.3 Volume-Fraction Measurements in Weld Metal 
6.6.5.3.1 Background 
Gas-tungsten-arc welds, which were made from 0.5-in. thick Alloy 22 base metal in a single 
V-groove configuration using nine passes. These welds were produced and aged at 593, 649, 
704, and 760C for times up to 1000 hours at Haynes International, Inc. in Kokomo, Indiana 
(Summers et al. 2000 [DIRS 154854]). Volume fraction measurements were also made. The 
amount and size of precipitates in the welds vary with position in the weld. For example, 
relatively few and smaller precipitates tend to be present near weld pass boundaries, while many 
larger precipitates tend to be present at the top of the last weld pass (see Figure 42). The 
measurements presented here represent averages over several positions in the weld. Future 
studies will correlate precipitate amount with location in the weld. These welds are also much 
thinner than those called out in the current waste package design. Welding conditions, such as 
heat input, that may affect the starting weld structure and the subsequent precipitation kinetics 
will be different for thicker welds. A study of precipitation kinetics in thicker welds is currently 
planned. Also, several phases are expected in Alloy 22 welds; , , and P have been observed 
(Cieslak et al. 1986 [DIRS 104966], p. 2041). The growth kinetics for each of these phases may 
be different. In the base metal, it is likely that the amount of  phase precipitating is small at 
temperatures below about 750C and that  and P phases are similar. In the weld, however, the 
amount of  phase may be quite high due to chemical segregation. More refined studies that 
take these factors into account must be done to reduce uncertainties associated with conclusions 
drawn about weld stability. 
  101 593C 
649C 
704C 
760C 
As-welded 
Linear (760C) 
Linear (704C) 
Linear (649C) 
y = 0.0032x + 0.1241 
R2 = 0.9717 
1000 100 
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Aging and Phase Stability of Waste Package Outer Barrier 
6.6.5.3.2 Tetrahedrally Close-Packed Phase Kinetics in Alloy 22 Welds 
As observed by Cieslak et al. (1986 [DIRS 104966]), TCP phases are present in the interdentritic 
regions of the as-welded structure. After aging, the amount and size of TCP precipitates 
increases with both time and temperature up to 760C. Nucleation of precipitation was also 
observed to form possibly along grain boundaries in some areas of these samples. The volume 
fraction of precipitates is shown as a function of time in Figure 94. Each of the data points (see 
Table 5) in Figure 94 represents the average of 2040 measurements. In the as-welded 
condition, there is approximately 0.02 volume % TCP phase. 
8.0 
7.5 
y = 0.0758x + 0.16 
R2 = 0.9728 
7.0 
6.5 
6.0 
5.5 
y = 0.0234x + 0.0411 
R2 = 0.9355 
5.0 
4.5 
4.0 
3.5 
3.0 
2.5 
2.0 
1.5 
1.0 
0.5 
0.0 
10 1 
Aging Time (hr) 
Figure 94 TCP phase precipitation kinetics in C22 GTAW welds as a function of temperature 
The volume fraction data of Figure 94 were fit, for each aging temperature with a trend line, 
using Equation 11 (Section 6.6.5.2.1). From these curve fits, the times to give 1 and 5% volume 
fraction were calculated. These times are plotted in Figure 95 as a function of reciprocal 
temperature. The average activation energy calculated from the slopes of these plots is 241 
kJ/mol, which is comparable to but lower than the values of 250 and 260 kJ/mol reported 
previously for base metal (Rebak et al. 2000 [DIRS 155013]). Extrapolations of these data do 
not indicate that precipitate nucleation and growth in the welds will occur to a significant extent 
at temperatures below approximately 200C. 
Area Fraction (%) 
  102 1.E+08 
10,000 yrs 
1.E+07 
Aging and Phase Stability of Waste Package Outer Barrier 
1.E+06 
1.E+05 
1.E+04 
y = 2E-10e27350x 
R2 = 0.9877 
1.E+03 
1.E+02 
y = 1E-12e30535x 
R2 = 0.9999 
1.E+01 
1.E+00 
0.0009 0.0011 
Figure 95. Time to form 1 and 5 volume percent TCP phase in C22 welds as a function of aging 
temperature. 
6.6.6 Micro-Hardness Measurements: Indicative of LRO Kinetics in Alloy 22 
The kinetics of LRO are treated in a manner similar to that discussed for TCP phase 
precipitation. However, very little kinetic data exists for LRO in Alloy 22. A very fine 
dispersion of ordered domains was seen after aging for 30,000 and 40,000 hr at 427C in Alloy 
22 base metal (Figure 48 through Figure 50) and in a weld similarly aged (Figure 51 through 
Figure 56). The ordering in these cases is so fine that it would be 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 hr and at 538 and 593C for 1000 hr. The volume fraction of ordered domains has not 
been measured in these samples. Alloy 22 base metal samples aged for 40,000 hr at 260 and 
343C and for 1000 hr at 482C were also examined in TEM, but no LRO was observed. 
Unlike TCP phase precipitates, LRO results in very small and finely dispersed precipitates. As a 
result, SEM image analysis is not well suited to determine the extent of LRO kinetics. However, 
due to the uniformly and finely dispersed nature of LRO, micro-hardness measurements are 
indicative of LRO, because analogous to precipitation age-hardened alloys, hardness increases 
with the amount of precipitation (Reed-Hill 1973 [DIRS 162684]). Table 9 summarizes the 
micro-hardness (Hv) measurements made on Alloy 22 as a function of time and temperature. 
Aging Time (Hours) 
0.0015 0.0013 
Reciprocal Temperature (1/K) 
ANL-EBS-MD-000002 REV 1 ICN 0 103 
1% 
5% 
Expon. (1%) 
Expon. (5%) 
200 C 
0.0021 0.0019 0.0017 
DTN: LL030606912251.020 
June 2003 Micro-Hardness 
(Hv) 
Aging and Phase Stability of Waste Package Outer Barrier 
Table 9 Micro-Hardness (Hv) Measurements in Aged Base Metal 
Time 
(hr) 
Temperature 
(C) 
600 1 220 
600 4 218 
600 10 223 
600 40 223 
600 100 221 
600 200 223 
600 400 219 
600 600 216 
600 800 222 
593 10 204 
593 30 218 
593 92 215 
593 100 207 
593 300 218 
593 600 218 
593 1,000 298 
593 1,011 214 
593 16,000 265 
550 100 237 
550 300 274 
550 600 301 
550 1,000 329 
550 2,000 328 
550 4,500 346 
550 6,000 364 
550 8,000 359 
538 10 210 
538 100 218 
538 1,000 300 
500 100 212 
500 300 227 
500 600 252 
500 1,000 277 
500 2,000 298 
500 4,500 307 
ANL-EBS-MD-000002 REV 1 ICN 0 104 June 2003 217 
Aging and Phase Stability of Waste Package Outer Barrier 
500 6,000 368 
500 8,000 308 
482 10 210 
482 100 204 
482 1,000 237 
427 10,000 218 
427 20,000 223 
427 30,000 227 
427 40,000 245 
400 1,000 215 
400 2,000 218 
400 4,500 210 
400 6,000 211 
400 8,000 213 
343 30,000 261 
343 40,000 212 
260 10,000 216 
260 30,000 216 
260 40,000 210 
As-received - 
DTN: LL030607112251.021 
These micro-hardness results are graphically presented in Figure 96. Trend lines have been 
included for the results at 500 and 550C. Some of the temperature values shown in Table 9 
have been rounded to one or two significant figures (e.g., 593C ~ 600C) when plotted in Figure 
96. The micro-hardness of as-received material was 217 Hv. 
The micro-hardness measurements indicate that LRO has occurred at temperatures in 
approximately the 500 to 550C range up to 40,000 hr. In addition, for results up to 40,000 hr, 
no LRO is evident for temperatures below 400C, and little LRO is seen at temperatures around 
600C. The observation of very little LRO near 600C corroborates well with the critical orderdisorder 
temperature of about 596C of the computational model (Section 6.6.4.3). These microhardness 
measurements add confidence to the observation from the computational TTT diagrams 
that forming the oP6 ordered phase from the fcc-solid solution at less than 200C within 10,000 
years is unlikely. 
ANL-EBS-MD-000002 REV 1 ICN 0 105 June 2003 400 
350 
Aging and Phase Stability of Waste Package Outer Barrier 
300 
250 
200 
150 
100 
50 
0 
10 1 
NOTE: Micro-hardness values are indicative of LRO. Micro-hardness of as-received base metal is 217 Hv. 
Micro-Hardness (Hv) 
1,000 100 
Time (hr) 
Figure 96 Micro-hardness (Hv) measurements on aged Alloy 22 base metal as a function of time and 
temperature. 
6.7 MODEL UNCERTAINTY AND CONFIDENCE 
6.7.1 Model Uncertainty 
6.7.1.1 Experimental Uncertainty 
When experimentally determining the extent of phase precipitation, uncertainty in the 
experimental results is primarily due to measurement uncertainties in the image analysis process. 
In order to determine the area-fraction coverage (%) resulting from phase precipitation, imageanalysis 
software (Image-Pro Plus) is used. Each value representing the area-fraction coverage 
at a specific time and temperature is the result of approximately 40 to 50 measurements. 
Electron microscopy images used in the image analyses are digitized using an 8bit pixel depth, 
which corresponds to 256 shades of gray per pixel. 
The measurement uncertainty in the area-fraction-coverage values is quantified in the standard 
deviation and 95% confidence interval values for each series measurements at a particular time 
and temperature. The standard deviations and 95% confidence intervals (shown in Table 3 
through Table 5) are computed per ASTM E 562-95, Standard Test Method for Determining 
Volume Fraction by Systematic Manual Point Count [DIRS 161301] (See Section 4.1.8). 
ANL-EBS-MD-000002 REV 1 ICN 0 106 
y = 159.55x0.0934 
R2 = 0.9292 
y = 150.64x0.0839 
R2 = 0.7846 
600C 
550C 
500C 
400C 
343C 
260C 
Power (550C) 
Power (500C) 
100,000 10,000 
June 2003  
As described in Section 4.1.8, there is more uncertainty (larger standard deviation values) in the 
volume fraction measurements on specimens subjected to lower temperatures and/or shorter 
aging times. At these temperatures and times, the volume fraction measurements have been 
performed on minimally detectable levels of precipitates (near zero). This uncertainty at near 
zero levels of precipitation has no impact on the APS model because the model predicts the 
extent, not initiation, of phase precipitation as a function of time and temperature. The initiation 
of precipitation (where the uncertainty is large) is of no consequence to the APS model and has 
no impact on APS results. As shown in Section 4.1.8, the uncertainty is considerably reduced in 
measurements where significant amounts (> 5%) of precipitation have occurred. 
6.7.1.2 Accuracy of the Thermo-Calc and DICTRA Results 
The analysis of the results on stability and aging is based on calculations made with the Thermo- 
Calc [DIRS 163154] and DICTRA [DIRS 163154] application software packages, respectively. 
These software codes use databases [DIRS 163153, 163154]. 
In the case of Thermo-Calc, the original thermo-chemical database that contains information on 
the energetics of all phases made of the ten elements: C, Co, Cr, Fe, Mn, Mo, Ni, Si, V, and W, 
has been extracted from the SSOL database that is normally called by Thermo-Calc. The 
database has been reevaluated based on experimental data specifically available for the Nibased 
class of alloys. This reevaluation accounted for output information such as assessed phase 
diagram, measured heat of formation, and transformation for binary and ternary alloys. Once the 
database has been validated, predictions are made on phase-stability information, such as 
property diagrams, isopleths, and ScheilGulliver results on solidification. Hence, the accuracy 
of the output information is mostly based on the machine accuracy of the calculations, once the 
thermo-chemical database has been validated. 
In the case of DICTRA, two databases are used: the thermo-chemical database used by Thermo- 
Calc and a database that contains information on diffusion coefficients and mobilities. The 
original MOB database that is normally called by DICTRA has been validated with experimental 
information on TTT diagrams available for binary and ternary alloys. Again, once validation has 
been achieved (See Section 7), predictions are made for the aging properties of various phases 
exhibited by multicomponent alloys, and the accuracy of the TTT results is mostly based on the 
machine accuracy associated with the numerical resolution of the equations. 
Validation of the databases used in this study is described in detail in Section 7. 
6.7.2 Model Confidence: Natural Analogues 
Awaruite is a naturally occurring, ordered ironnickel metallic mineral with an approximate 
stoichiometry of Ni3Fe. It was first discovered in Awarua, New Zealand, but has been found at 
various locations around the world (Krishnarao 1964 [DIRS 154746], p. 443). Josephinite, a 
rock found in Josephine County, Oregon, contains grains of awaruite that are larger than other 
sources of awaruite. Josephinite also has, in some instances, a unique mixture of minerals that 
has been tied to changes in the local environment and higher temperatures associated with 
hornblende diorite dikes from igneous intrusions (Dick 1974 [DIRS 154749], p. 297; Gpel et al. 
1990 [DIRS 154750], p. 26). The age of these dike intrusions has been measured using KAr 
  107  
dating to be approximately 150 to 155 million years (Dick 1974 [DIRS 154749], p. 292). Other 
nearby rocks also associated with the formation of josephinite have been dated, using Pb 
isotopes, at 159  8 million years (Gopel et al. 1990 [DIRS 154750], p. 24). Thus, the age of 
josephinite is on the order of 150 million years. 
Some samples of josephinite contain taenite (the high-temperature, disordered, FCC Ni.Fe 
metallic phase) as well as awaruite. The composition and amount of each of these phases in the 
two-phase mixture have been fit to the Fe.Ni phase diagram, showing that these phases formed 
in the temperature range of 460C down to about 400C (Botto and Morrison 1976 
[DIRS 154716]). The fact that the composition and amount of these phases fit the phase diagram 
at the higher temperatures indicates that no changes have occurred at lower temperatures. 
Taenite is not stable below about 350C; .Fe and awaruite are the stable phases at ambient 
temperatures. The fact that taenite, not .Fe, is present in josephinite also indicates that no 
changes have occurred in the 150 million years since these samples formed. 
Out of necessity, phase stability is studied at temperatures greater than those expected in the 
proposed repository so that the rate at which phase changes occur can be measured. These rates 
are measured as a function of temperature, and the functional relationship is extrapolated to the 
lower temperatures in the proposed repository. The stability of the metallic structures in 
josephinite over millions of years suggests that no low-temperature mechanism with rates 
significantly greater than predicted exists. Thus, this provides confidence in the implicit 
assumption that the high-temperature mechanisms used to extrapolate kinetics are the same as 
the low-temperature mechanisms that will really be active under repository conditions. 
  108  
INTENTIONALLY LEFT BLANK 
ANL-EBS-MD-000002 REV 1 ICN 0 109 June 2003  
7. VALIDATION 
During the course of developing the APS model, the Thermo-calc and DICTRA databases 
(DIRS 163153, 163154]) were modified to more accurately simulate and analyze the 
thermodynamic and kinetic behavior of Alloy 22. As a result, the first step in model validation 
was to validate the database modifications (in order of increasing complexity) by comparing the 
calculated phase diagrams with those in published literature. Having validated the calculated 
phase diagrams, it was then prudent to proceed with developing the alloy property and TTT 
diagrams of the APS model. This validation of the calculated phase diagrams is in addition to 
the model validation activities described in the Technical Work Plan for: Waste Package 
Materials Data Analyses and Modeling (BSC 2002 [DIRS 161132]). The model validation 
activities presented in this section also address the items of the Technical Error Report (TER) 
TER-02-0021. 
The Thermo-Calc results used in analyzing Alloy 22 along with several other Ni-based alloys 
have been validated using comparisons of calculated phase diagrams with published literature for 
(1) the binary sub-systems, (2) the pseudo-binary section Nix(Cr3Mo)1x and (3) the ternary Ni- 
Cr-Mo alloy (a surrogate for Alloy 22). Agreement of the calculated phase diagrams with 
published literature is excellent and described below. 
In this section, the validation of the calculated phase diagrams is discussed first followed by the 
discussion of the model validation criteria of the Technical Work Plan for: Waste Package 
Materials Data Analyses and Modeling (BSC 2002 [DIRS 161132]). 
7.1 VALIDATION OF THE THERMO-CALC RESULTS FOR THE BINARY SUBSYSTEMS 
The calculated phase diagrams, as obtained from Thermo-Calc for CrNi, MoNi, CrMo, Cr 
W, MoW, and NiW are presented in Figure 97 together with the experimentally determined 
phase diagrams extracted from Massalski (Massalski 1990 [DIRS 118757]). These results 
suggest that the thermo-chemical database is able to account for the stability of most phases 
encountered experimentally in the composition and temperature domains in the NiMo binary 
alloy, namely Ni4Mo, Ni3Mo, and NiMo, and in the NiW binary alloy, namely Ni4W, NiW, and 
NiW2. The results also account for the phase separation tendency in the body centered cubic 
(bcc) solid phase that is observed in the case of CrMo, and CrW. Note that the binary Mo-W 
alloy displays an ideal solid solution based on the bcc phase with no particular tendency toward 
compound formation or phase separation. Also note that in the case of the binary NiCr alloy, 
the ordered phase that is experimentally observed at low temperatures around the stoichiometry 
Ni2Cr (referred to as oP6 or C11b) is not accounted for with the initial SSOL database. 
  110  
NiCr 
NiMo 
CrMo 
CrW 
ANL-EBS-MD-000002 REV 1 ICN 0 111 June 2003  
NiW 
Mo-W 
DTN: LL030106412251.014 
Figure 97. Comparison between experimentally determined (left panels) [DIRS 118757] and calculated 
(right panels) phase diagrams of NiCr, NiMo, NiW, CrMo, CrW, and MoW alloys, as 
obtained with Thermo-Calc. 
7.1.1 Modeling of the Ordered Phase oP6 
To introduce the relevant data that define the Gibbs energy for the ordered phase C11b (or oP6) 
made of Ni, Cr, Mo, and W, the following information was used. First, the experimental work 
performed by Hirabayashi et al. (Hirabayashi et al. 1969 [DIRS 161452]) that suggests a heat of 
formation for the Ni2Cr ordered phase of approximately 4,200 J/g.at (or approximately 1,000 
cal/g.at). Second, the experimental work of Karmazin et al. (1994 [DIRS 161444]) carried out 
for the oP6 ordered phase in Ni-rich NiCrMo alloys clearly indicates that Mo can be located 
on two sublattices. Third, ab initio electronic structure calculations based on the tight-binding 
linear muffin-tin orbital (TB-LMTO) method (Turek et al. 1997 [DIRS 161453]) allowed us to 
estimate the heat of formation of the oP6-ordered phase for Ni2Cr, Ni2Mo, and Ni2W. The 
results of total energy versus lattice parameter for the ordered phase based on the fcc lattice are 
plotted in Figure 98 for the three compounds. 
  112  
DTN: LL030106412251.014 
NOTE: The zero of energy is taken as the concentration weighted average of the total energies of fcc Ni and bcc Cr 
(or Mo, W). 
Figure 98 Total energy (in kJ/mol) versus normalized lattice parameter (.i.e., a/aeq, where a is the lattice 
.G 
.G 
L 0 fcc.oP6 
Cr : Mo, Ni 
Ni 
parameter and aeq is the equilibrium lattice parameter) for the three ordered compounds Ni2Cr, 
2Mo and Ni2W of Ni2Cr-type (C11b or oP6) 
Hence, in the following, the ordered phase is treated within a two-sublattice model (c.f. Section 
6.5.3) with Cr, Mo, and W on one sublattice and Mo and Ni on the other sublattice. The 
compound phase parameters (computed with temperature T in K, and the energies in J/g.at) are 
defined as follows (note that the parameters not included in the following are set to zero): 
fcc-oP6 2-sublattice model (Cr,Mo,W)1(Mo,Ni).2, i.e., with p = 1 and q =2 
.G = .7095 . 5.6*T = 6000 = .G = .G fcc.oP6 
W : Mo 
fcc.oP6 
Mo : Mo 
.G (10) = 10,000 = +1000 
fcc .oP6 
Cr : Ni 
fcc .oP6 
W : Ni 
fcc.oP6 
Cr : Mo 
fcc .oP6 
Mo : Ni 
L L 0 fcc.oP6 
Cr, W : Ni Ni 
0 fcc.oP6 
Cr W, : 
0 fcc.oP6 
Cr, Mo : = .8,000 = .55,000 = .80,000 L Ni = .11,000 
Based on the above discussion, these parameters were incorporated into the Thermo-Calc 
database to more properly model the oP6 ordered phase (Turchi 2003 [DIRS 162974]). 
To adjust the experimental information on Ni2Cr ordered phase with already available 
thermodynamic data in the SSOL database, the heat of formation of Ni2Cr became .7,095 J/mole 
  113  
(instead of 4187 J/mol). The data for Mo-Ni and W-Ni account for the ab initio results that 
indicate that Ni2Mo is barely stable, whereas Ni2W is unstable (leading to a positive heat of 
formation of 10,000 J/mole). Finally the description of particular species on both sublattices is 
contained in the two RedlichKister parameters 0 Lfcc.oP6 (Redlich et al. 1948 [DIRS 161464]). 
Their values have been adjusted to allow Mo to be located on the two sublattices, to spread the 
domain of stability of the ordered phase in accordance with the results of Karmazin et al. (1994 
[DIRS 161444]), and at the same time to account for the effect of Mo addition on the orderdisorder 
transition temperature (Karmazin et al. 1994 [DIRS 161444]). Note that although 
Ni2Mo is barely stable, the magnitude of the critical order-disorder temperature for the oP6 
ordered phase goes through a maximum as a function of Mo composition. This nonlinear effect 
of Mo is captured in the energetic description of the ordered compound. 
The results of this reassessment are displayed in Figure 99 and are in agreement with the 
accepted phase diagram of NiCr. 
DTN: LL030106412251.014 
NiCr 
NOTE: Note the domain of stability of the ordered phase of Ni2Cr-type (oP6 or C11b). 
Figure 99. Comparison of the reference NiCr phase diagram (left) with the calculated Ni-Cr phase 
diagram as obtained with the ordered phase modeled (right). 
7.2 VALIDATION OF THE THERMO-CALC RESULTS FOR THE PSEUDO-BINARY 
Nix(Cr3Mo)1x ALLOY 
To further validate the database, the experimental determination of the phase boundaries in the 
terminal Ni-rich -solid solution in the pseudo-binary section Nix(Cr3Mo)1x, (with 
cCr+Mo=cCr+cMo varying from 13.5 to 44 at.%) (Karmazin et al. 1994 [DIRS 161444]) were 
considered. It was noted experimentally that the boundary of the terminal -solid solution was 
increasing with cCr+Mo as indicated in Figure 100a. Calculations were performed with the 
reassessed database for the same section of the ternary phase diagram with all the phases 
considered except the P phase. The calculated phase diagram, shown in Figure 100b, compares 
favorably with the experimental counterpart, displayed in Figure 100a, as far as the boundary of 
the -solid solution (indicated by a thick red line) is concerned. A two-phase region (fcc + ) is 
also predicted in the temperature range 620-1370C at lower Ni content. However, since the 
experimental study did not include the structural characterization of these phases at high 
  114  
temperature in this stability region, the predicted two-phase region could not be confirmed. 
Experiments are currently being conducted at LLNL to test the validity of the predictions. In 
retrospect, the suspension of the P phase during the calculation of the phase diagram is 
equivalent to modeling that the kinetics of P-phase formation is much slower than the one 
associated with the formation of the  phase. This approach has been described in Section 6.6.1 
where the property diagram of Alloy 22 showed that that the stability of the  phase can be 
extended at low temperatures when the P phase is suspended-a result that is confirmed 
experimentally. 
  115 (b) (a) 
(c) 
DTN: LL030106412251.014 
Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The evolution of dT given by the difference between the lattice parameter measured at temperature T and the 
a1100, its initial value obtained after quenching samples from 1100C is displayed in (c) for several isothermal 
annealing as a function of time Karmarzin et al. 1994 [DIRS 161444]. 
Figure 100 Comparison between the (a) calculated (with Thermo-Calc) and (b) the experimental 
Karmarzin et al. 1994 [DIRS 161444] phase diagrams of the pseudo-binary alloy Ni- 
(Cr0.75Mo0.25). 
ANL-EBS-MD-000002 REV 1 ICN 0 116 June 2003  
7.3 VALIDATION OF THE THERMO-CALC RESULTS FOR THE TERNARY NiCr 
Mo ALLOY 
Isothermal sections of the NiCrMo phase diagram were calculated and compared with the 
experimental results (Gdowski 1991 [DIRS 100859]; Jena et al. 1989 [DIRS 161441]; Rideout et 
al. 1951 [DIRS 161445]; Bloom et al. 1954 [DIRS 161463]; Raghavan et al. 1984 
[DIRS 154707]; Cieslak et al. [DIRS 104966]). For example, the results of Bloom et al. 
[DIRS 161463] are shown in Figure 101. The Ni-Cr-Mo system in the entire composition range 
has been thoroughly reviewed in Jena et al. (1989 [DIRS 161441]), (see also Gdowski 1991 
[DIRS 100859]). Here all the alloys of interest (see Table 8) are located in the high-Ni rich 
portion of the phase diagram (Ni content above 50 wt %), and more specific studies have been 
reported in this limited region of the phase diagram (Rideout et al. 1951 [DIRS 161445], Bloom 
et al. 1954 [DIRS 161463], Raghavan et al. 1984 [DIRS 154707]). In this region, the single fcc 
()-phase is stable at high temperatures and the domain of  stability diminishes toward the Nirich 
corner with decreasing temperature, as illustrated in Figure 103. This study confirms the 
fact that at equilibrium and at low temperature, all the alloys indicate in Table 8 should display a 
multi-phase field that includes the fcc structure and one or two complex phases such , , or P 
(Frank et al. 1958 [DIRS 161437], 1959 [DIRS 161438]; Shoemaker et al. 1988 [DIRS 154989]). 
It is worth noting in Figure 101 that the thermodynamic calculations performed at 1250C 
reproduce fairly well the lenticular shape of the domain of stability of the  phase. In the 
following, since the TCP P and  phases are closely related, we will not make the distinction 
between them as far as the energetics and the kinetics of formation are concerned. The results of 
our calculations also confirm that the fcc-phase field is shrinking in the Ni-rich corner of the 
phase diagram as the temperature is lowered, as shown in Figure 102. 
  117  
NOTE: The right bottom figure shows the experimentally assessed isothermal section of the ternary phase diagram 
from Bloom et al. 1954 [DIRS 161463] at 1523 K. 
Figure 101 Calculated isothermal sections of the NiCrMo phase diagram at 1123, 1323, and 1523 K. 
ANL-EBS-MD-000002 REV 1 ICN 0 118 
DTN: LL030106412251.014 
June 2003  
DTN: LL030106412251.014 
Figure 102 Calculated isothermal sections of the Ni-Cr-Mo phase diagram at 573, 773, 893 K, and 
973 K. 
It is worth noting that since commercial alloys are not pure ternary alloys, Cr, Mo, and Ni 
equivalents have been proposed by correlating the behavior of minor elements (e.g., Co, Fe, Ti, 
and W) with the major elements (Cr, Mo, and Ni) in the formation of TCP precipitates. Cieslak 
et al. (1986 [DIRS 104966]) proposed the following relations applicable to Alloy 22, C4, and C276: 
(11) 
Moeq = wt % Mo + wt % W 
Creq = wt % Cr 
Nieq = (balance; in wt %) 
However, the property diagrams of these commercial alloys bear very little resemblance to those 
generated for the alloys at their equivalent compositions. Hence extreme caution has to be taken 
when making arguments based on Cr, Mo, and Ni equivalents. As shown previously, for 
  119  
example, W and Mo have a different influence both qualitatively and quantitatively on the 
stability of the oP6-ordered phase (see Section 7.1). 
By limiting the analysis to the fcc matrix and the Ni2Cr-type (or oP6) ordered phase (i.e., with all 
other phases suspended), the isothermal sections at 620, 600, 500, and 300C of the NiCrMo 
phase diagram were re-calculated. The results presented in Figure 104 show the domain of 
stability of the oP6 and its extension in the Ni-rich corner of the phase diagram when 
temperature decreases. The detailed location of the oP6 ordered phase in the ternary Ni-Cr-Mo 
alloy in the phase diagram and how Mo affects the stability of the ordered phase and the location 
of the critical order-disorder transition temperature are illustrated in Figure 105 for fixed Ni mole 
fraction of 0.625 0.645, and 0.665. As discussed before, the addition of Mo does not have a 
simple gradual effect on the stability of the oP6 ordered phase. For example, in the case of a 
fixed mole fraction of Ni equal to 0.645, there is a gradual increase in the stability of the ordered 
phase by substituting Cr for Mo up to about 0.20 mole fraction of Cr before destabilization of 
oP6 phase at higher substitution of Cr for Mo, as shown in Figure 105. 
DTN: LL030106412251.014 
Figure 103 Calculated fcc (or ) domain of stability of the ternary Ni-Cr-Mo phase diagram as a function 
of temperature from 1250 to 300C. 
  120  
NOTE: Only the fcc (or ) matrix and the oP6 ordered phase are considered for this set of calculations. 
Figure 104 Calculated isothermal sections of the ternary NiCrMo phase diagram at 893, 873, 773, and 
573 K. 
ANL-EBS-MD-000002 REV 1 ICN 0 121 
DTN: LL030106412251.014 
June 2003 NOTE: Only the fcc (or ) matrix and the oP6 ordered phase are considered for this set of calculations. 
DTN: LL030106412251.014 
Aging and Phase Stability of Waste Package Outer Barrier 
Figure 105 Calculated isopleths of the ternary NiCrMo alloy at fixed mole fraction of Ni of 0.625, 0.645, 
and 0.665. 
7.4 VALIDATION OF THE TREATMENT OF MO AND W IN THE TERNARY Ni 
CrMo ALLOY 
In the course analyzing the ternary NiCrMo alloy as surrogate for Alloy 22, published 
experimental data for NiCr and NiCrMo systems have been considered for characterizing the 
oP6-ordered phase of Ni2Cr-type. Since Mo and W play a role in the stability of this ordered 
phase, it was necessary to include their effects in the alloy energetics. 
The ab initio results for the oP6 forms of Ni2Cr, Ni2Mo, and Ni2W, and the fcc phases were 
considered to evaluate the effect of Mo and W additions, and to compare the calculated results 
with the experimental findings reported in the literature. Ab initio results for the heat of 
formation of Ni2Cr, Ni2Mo, and Ni2W are 10,485, +1014, and 10,074 J/mol, respectively (cf. 
Section 7.1.1, Figure 98). These values were incorporated into the database as 7095, +1000, 
  122  
and 10,000 respectively. The database value for Ni2Cr was adjusted from experimental results 
(Hirabayashi et al. [DIRS 161452]) and phase diagram calculations while the remaining values 
for Ni2Mo (+1000) and Ni2W (+10,000) are rounded ab initio results. The most complete data 
for the effect of Mo on the relative stability of oP6 and fcc in Ni-Cr-Mo alloys is due to 
Karmazin et al. [DIRS 154881]. This experimental work indicates that a Ni25 at.% Cr8.33 
at.% Mo alloy has a maximum critical order-disorder temperature for the oP6 to fcc transition on 
heating of about 670C, as compared with a maximum transition temperature of 570C for a Ni 
33.3 at.% Cr alloy. In Karmazin et al. [DIRS 154881], it is also mentioned that Mo can be 
located on both sublattices that describe the oP6 phase. The role of W on the stability of the oP6 
phase is not experimentally documented. Hence, as for Mo, the W is allowed to occupy both 
sublattices, and that the interactions parameters are smaller than those associated with Mo since 
for Ni2W the instability is more significant that for Ni2Mo. 
Ab initio calculations have shown that MoW behaves like an ideal solution, because the heat of 
formation of the alloy in the entire range of composition is practically zero. This result indicates 
that Mo and W, which belong to the same VIb column of the transition metals, have very similar 
electronic structure properties. Incidentally, this does not preclude any difference in alloying 
effect, as shown in Figure 98, when Mo and W are mixed with other elements such as Ni, due to 
differences in the manner which atomic orbitals between various elements hybridize. 
To account for these observations, the following interaction parameters have been selected: 
Cr, Mo : Ni L 0 fcc-oP6 
Cr :Mo, Ni L 0 fcc-oP6 =11,000 =80,000 
L 0 fcc-oP6 =55,000 Cr, W : Ni Ni Cr W, : L 0 fcc-oP6 =8,000 
Based on the above discussion, these interaction parameters have been included in the Thermo- 
Calc database to model the Mo and W behavior in the ternary Ni-Cr-Mo alloy system (Turchi et 
al. [DIRS 162974]). 
With this new description, the oP6/fcc equilibrium shown in Figure 106a and Figure 106c for the 
NiCrMo and NiCrW systems, respectively, is close to the composition of Alloy 22. These 
results suggest that in NiCrMo, the 21.1 wt % Cr13.5 wt % Mo composition lies very close to 
Alloy 22 stoichiometry, and little fcc phase is present when this alloy is cooled below 635C, see 
Figure 106b. It should be noted that W has a smaller stabilizing effect on oP6 than does Mo, as 
shown in Figure 106c. Recent measurements of the kinetics of ordering (oP6) formation 
conducted at LLNL (Shen 1999 [DIRS 161800]) in Alloy 22 (Ni21.1 wt % Cr13.5 wt % Mo3 
wt % W) suggested that the maximum temperature for the oP6/fcc transition is above 593C, or 
some 53C higher than in the Ni-Cr case. Since W has mostly a destabilizing effect on the 
formation of the oP6-ordered phase, several tests performed to account for this fact have shown 
that to model Alloy 22 with a Ni-Cr-Mo surrogate alloy, 2.0 wt % Mo for each 1.0 wt % W in 
the fcc phase provides an acceptable representation of the oP6/fcc phase region. In other words, 
Alloy 22 with 21.1 wt % Cr13.5 wt % Mo3 wt % W can be replaced by Ni21.1 wt % Cr7.5 
wt % Mo. This equivalent composition leads to much more fcc phase in the temperature range 
of precipitation than with the 21.1 wt.% Cr13.5 wt.% Mo composition, as can be concluded 
from the comparison between Figure 106d (below about 600C) and Figure 106b. 
  123 DTN: LL030106412251.014 
Aging and Phase Stability of Waste Package Outer Barrier 
NOTE: The vertical lines in (a) and (c) locate the composition of Ni21.1 Cr13.5 Mo and Ni21.1 Cr1.8 W (in 
wt.%), respectively. Property diagrams of Ni24.5 Cr8.5 Mo (in at.%) or Ni21.1 Cr13.5 Mo (in wt.%) (b), 
and Ni21.1 Cr7.5 Mo (in wt.%) (d). 
Figure 106 Phase diagrams of NiCrX, with cCr+cX=0.33 being fixed, where X=Mo (a), X=W (c) 
To further validate this approach accounting for the role of Mo and W, the experimental results 
reported in Shen 2000 [DIRS 161801] are considered. As an example, consider a sample of 
Alloy 22 with the following composition: 21.1 Cr13.5 Mo4.7 Fe2.9 W1.74 C0.21 Mn 
0.12 V0.023 Si0.003 C (in wt.%) annealed for 16,000 hours at 704C. At this annealing 
temperature substantial precipitation has occurred at grain boundaries and in the fcc-based 
matrix. These precipitates correspond to the P (and possibly ) phase, and are identifiable by 
their platelet shape, see Figure 107a. At this annealing temperature of 704C, and according to 
the property diagram presented in Figure 108a, the most likely phase to form is indeed the P 
phase with a phase fraction of about 20%. Energy dispersive x-ray (EDS) analysis has been 
performed on a Philips CM300 equipped with an EDS detector across the TCP precipitate along 
  124  
the line indicated in Figure 107a to determine the evolution of elemental weight fractions as 
functions of distance. As shown in Figure 107b, the alloy composition varies substantially when 
crossing the precipitate. As expected the P-phase formation is accompanied by a noticeable 
decrease in Ni content compensated by an increase in Mo content, and to some extent a decrease 
in Cr and Fe, and an increase in W. Quantitatively, with the reference set to the composition of 
the base alloy mentioned above, the composition in Ni, Cr, Mo, Fe, and W becomes in the Pphase 
precipitate 30, 18, 45, 3, and 3 (in wt %), respectively. Calculations have been performed 
to calculate the property diagram of Alloy 22 at the composition mentioned above, and the 
weight fractions per element in the fcc matrix and the P phase have been computed. The results 
are summarized in Figure 108. At 704C, temperature at which the isothermal annealing has 
been performed, the fcc phase qualitatively retains its starting alloy composition. On the other 
hand, in the P phase, the composition of each major constituent Ni, Cr, and Mo is 36, 24, and 39 
(in wt %), respectively. These results are in fairly good agreement with the experimental 
findings, if one keeps in mind that the experiments are conducted on samples that may not have 
reached their full thermodynamic equilibrium, which is the basis for the calculations. 
  125  
(a) 
DTN: LL030106412251.014 
(b) 
Figure 107 (a) Micrograph of platelet P-phase precipitate in an fcc matrix, and location of the (red) line 
profile along which the energy dispersive x-ray (EDS) analysis is performed. (b) Variation of 
the weight fraction per element along the line profile, as obtained from EDX spectroscopy 
analysis for Alloy 22 annealed at 704C for 16,000 hours (Shen 2000 [DIRS 161801]). 
ANL-EBS-MD-000002 REV 1 ICN 0 126 June 2003  
NOTE: The vertical line indicates the temperature at which the alloy has been annealed. 
DTN: LL030106412251.014 
Figure 108 (a) Property diagram of Alloy 22 (see text for composition). Weight fraction of Ni (red), Cr 
(blue), Mo (green), W (brown), and Fe (black), versus temperature in the fcc matrix (b), and 
discussed. 
the P phase (c) for Alloy 22. 
7.5 DISCUSSION OF MODEL VALIDATION CRITERIA 
In this section, each of the model validation criteria described in the Technical Work Plan for: 
Waste Package Materials Data Analyses and Modeling (BSC 2002 [DIRS 161132]) are 
Criterion One 
Does the comparison of TCP and LRO formations in base metal from Thermo-Calc/DICTRA 
agree with experimental data on base metal? 
The computational phase kinetics results (from DICTRA) for the ternary NiCrMo alloy (a 
surrogate for Alloy 22) were compared with volume-fraction measurements on Alloy 22 base 
metal at temperatures of approximately 700 and 750C (Figure 109 and Figure 110). The 
computation phase kinetics results are used to construct the computational TTT diagrams for a 
particular phase (Section 6.6.4). The comparison is not entirely consistent because (1) the 
volume-fraction measurements do not distinguish among the possible TCP phases (P, , and ) 
that have formed, and (2) the DICTRA results only display one type of phase fraction at a time. 
As a result, Figure 109 and Figure 110 compare the P phase formation results from DICTRA 
with the TCP volume-fraction measurements, as the P phase is the most likely to form at these 
temperatures and times. At high temperatures and long aging times, more phases in addition to 
the P phase may form, which would increase ambiguity in the comparison. As a result, in order 
to make the comparisons as consistent as possible, the comparisons presented in Figure 109 and 
Figure 110 were only able to include a few volume-fraction measurements from Table 3. For 
this comparison, the few volume-fraction measurements shown in these plots were deemed to 
most likely contain primarily P phase at the times and temperature shown. 
In both comparisons, the agreement between the computational kinetics results and the volumefraction 
measurements is reasonable. The comparison shows that the computational results are 
  127  
conservative compared to the measured data, as the measured data points always lie to the right 
(increasing time) of the DICTRA results. As a result, the computational model predicts slightly 
earlier phase formation that what is measured at a given temperature. This conservativeness is 
expected because the DICTRA results are based on a ternary NiCrMo alloy, 55.7Ni21.1Cr 
13.5Mo (in wt %), which is a surrogate for Alloy 22, and the actual composition of Alloy 22 
contains less Ni (the balance of Ni will be less due to more elements specified in the actual Alloy 
22 chemical composition). 
0.14 
0.12 
0.1 
0.08 
0.06 
0.04 
0.02 
0 
10 1 
Figure 109 Comparison of phase formation at 700C for DICTRA computational results (P phase) and 
measured data (TCP phase) on Alloy 22 base metal. 
P Phase Fraction 
1,000 100 
Time (hr) 
ANL-EBS-MD-000002 REV 1 ICN 0 128 
DICTRA 
Measured Data 
100,000 10,000 
DTN: LL030606912251.020 
June 2003 0.09 
0.08 
Aging and Phase Stability of Waste Package Outer Barrier 
0.07 
0.06 
0.05 
0.04 
0.03 
0.02 
0.01 
0 
1 
P Phase Fraction 
100 10 
Time (hr) 
Figure 110 Comparison of phase formation at approximately 750C for DICTRA computational results (P 
phase) and measured data (TCP phase) on Alloy 22 base metal. Measured data was 
For LRO in base metal, the TTT diagram for the oP6 phase of the ternary NiCrMo alloy (a 
surrogate for Alloy 22) was presented in Section 6.6.4.2. In addition, micro-hardness 
measurements were used (Section 6.6.6) to provide insight into the extent of LRO at several 
times and temperatures. In comparing the measurements indicative of LRO and the calculated 
TTT diagram, it was shown (Section 6.6.4.2) that the calculated order-disorder transition 
temperature of 620C agreed well with the estimated order-disorder transition temperature of 
approximately 600C (see Figure 85). 
Criterion Two 
Does experimental data on TCP formation on base metal grain boundaries corroborate with 
data in peer-reviewed literature or fundamental metallurgical phenomena? 
In Section 6.6.5.2, the measurements on Alloy 22 grain boundaries were plotted using an 
Arrhenius fit to conservatively estimate the long-term TCP phase precipitation on grain 
boundaries. These Arrhenius plots indicated an activation energy of 378 kJ/mol (90 kcal/mol) 
for TCP phase formation, which was higher than the published value of 62 kcal/mol for C276. 
It is expected that the activation energy for Alloy 22 would be slightly higher than that of C276 
primarily due to the differences in chemical composition (C276 contains more Mo and W) and 
phases formed. As shown in Section 6.6.1, unlike Alloy 22, C276 does not form an oP6 
ordered phase. In Alloy 22, it was shown that formation of the ordered oP6 phase competes with 
the P phase. As a result, it is reasonable that the activation energy for C276 would be slightly 
lower than that observed for Alloy 22. It was shown that even with this activation energy, 
obtained at 760C. 
ANL-EBS-MD-000002 REV 1 ICN 0 129 
DICTRA 
Measured Data 
10,000 1,000 
DTN: LL030606912251.020 
June 2003  
formation of TCP phases on grain boundaries at temperatures near 200C for 10,000 years was 
unlikely. 
Criterion Three 
Does experimental data on TCP and LRO formations in weld metal corroborate with data in 
peer-reviewed literature or fundamental metallurgical phenomena? 
At present, a computationally based model for phase kinetics in Alloy 22 welds is not available 
to provide insight into the long-term stability of welds. As a result, in Section 6.6.5.3.2, the 
measurements on Alloy 22 welds were plotted using an Arrhenius fit to conservatively estimate 
the long-term stability of welds. These Arrhenius plots indicated an average activation energy of 
241 kJ/mol for TCP phase formation, which was lower and agreed with the published values of 
250 and 260 kJ/mol for base metal. It was shown that even with a lower activation energy, 
formation of TCP phases in welds at temperatures near 200C for 10,000 years was unlikely. 
LRO formations (oP6 phase) in Alloy 22 welds were not measured in this study. 
Conclusion: In light of the above discussion, it may be concluded that the inputs used in the 
APS model and the model output corroborate well with those reported in mostly handbooks and 
peer-reviewed scientific literature. It is also clear from the above discussion that the validation 
activities performed for building confidence in the model have sufficiently strong scientific 
bases, and that all of the three criteria and the validation of the calculated phase diagrams used to 
determine that the required level of confidence in the model has been achieved. 
  130  
8. CONCLUSIONS 
The CALPHAD approach has been applied to the study of statics (stability) and kinetics (aging) 
of phase formation and evolution in Ni-based alloys. At equilibrium, Alloy 22, at its nominal 
compositions and at low temperatures, should exhibit, besides the fcc matrix, long-range order of 
Ni2Cr-type, complex FrankKasper phases (here, the P phase), carbides and silicides. The 
kinetics of LRO formation occurs at relatively low temperatures, and therefore, does not favor 
the formation of the ordered phase of Ni2Cr-type as the phase formation kinetics are primarily 
driven by diffusion. Alloys homogenized (or annealed) at high temperatures and quenched at 
relevant repository conditions should not display any deleterious phase. Extrapolation of 
computationally derived TTT curves to lower temperatures, which are expected in a repository, 
indicates that forming the P or oP6 ordered phases from the fcc solid solution is unlikely. 
After aging for 16,000 hr at 593C, P phase was found at Alloy 22 grain boundaries. At higher 
temperatures (as much as 760C for the same aging time), both  and P phase formed on grain 
boundaries and within the grains. Grain boundary carbides also form at 593C and higher, but 
the amount of carbide is small compared to the  and P phases. A small amount of  phase forms 
in Alloy 22 after 16,000 hr at 704 and 760C. LRO was seen after aging for 1000 hr at 538 and 
593C and for 30,000 hr at 427C (shown in Table 6), but ordering most likely begins at shorter 
times. 
The experimental analyses previously discussed assume that the kinetics of formation of the  
and P phases are similar and that the amount of carbide and  phase present is too small to affect 
the measured rates of precipitation (Assumption 5.1). Minor compositional changes in Alloy 22 
are also assumed to have little or no effect on the rate of precipitation. The amounts of carbide 
and  phase tend to be low in the samples examined thus far. Therefore, the rates of formation of 
these phases are not likely to contribute significantly to the overall performance of the waste 
package. Studies from existing literature (Section 5.1) showed that the  and P phases are very 
similar, and the rates at which they form are likely to be similar. 
The experimental analyses previously discussed also assume that the precipitation mechanism 
operating at the high temperatures studied also operates at the lower temperatures expected in the 
proposed repository and that the phases seen at the higher temperatures are stable at the lower 
temperatures (Assumption 5.2). Information from natural analogues (Section 6.7.2) showed that 
the stability of the metallic structures in josephinite over millions of years suggests that no lowtemperature 
mechanism with rates significantly greater than predicted exists. Thus, this provides 
confidence in the implicit assumption that the high temperature mechanisms used to extrapolate 
kinetics are the same as those at lower temperatures that are expected under repository 
conditions. 
The present study showed that formation of TCP or ordered oP6 phases in Alloy 22 base metal 
and annealed welds (which are deemed to be similar to base metal) is unlikely at temperatures 
near 200C. 
  131  
8.1 THE ROLE OF W IN THE STABILITY OF Ni-BASED ALLOYS 
From experiments and the results of the present study, it is apparent that Cr and Mo favor the 
formation of TCP phases (, P, and ). It was also noted that in the pure binary forms, Cr is the 
only element that favors the formation of the oP6-ordered phase Ni2Cr. The effect of Mo on 
oP6-phase formation is more subtle as revealed from the study. Indeed, in the pure binary form, 
Ni2Mo is barely stable (c.f. Section 7.1). However, it was shown experimentally (Karmazin et 
al. 1994 [DIRS 161444]) that at a low mole fraction of Mo, the substitution of Cr by Mo 
enhances the formation of the oP6-ordered phase, as indicated by an increase in the critical 
order-disorder temperature. The gradual substitution of Cr by Mo from Ni2Cr to Ni2Mo does not 
lead to a gradual instability of the order phase as one would first guess. The role of W on the 
stability of oP6-ordered phase is more obvious. The gradual substitution of Cr by W gradually 
leads to a destabilization of the ordered phase, and the oP6 Ni2W ordered phase is clearly 
unstable. It is worth recalling that Alloy 22 has (in wt %) 21.2 Cr13.5 Mo3 W, whereas in 
Alloy 59 has 23 Cr16 Mo, with no W. From the above observations, it is concluded that the 
oP6-ordered phase will occur at higher temperature (i.e., will be more stable) in Alloy 59 than in 
Alloy 22 (less unstable effect on the ordered phase caused by the absence of W in Alloy 59). At 
the same time, because more Cr and Mo are present in Alloy 59 than in Alloy 22, it is expected 
that at low temperatures, the stability of the complex TCP phases will be more favored in Alloy 
59 than in Alloy 22 (Heino 2000 [DIRS 161799]). Hence, because of this double effect of the 
absence of W in Alloy 59, it is believed that Alloy 22 is a more promising alloy than Alloy 59, at 
least when in operation at low temperatures (below 800C), as is the case under expected 
repository conditions. 
8.2 ALLOY 22 CHEMICAL COMPOSITION RECOMMENDATION 
In the computational analyses and measurements conducted on Alloy 22 samples presented here, 
the Alloy 22 chemical composition was within that specified by ASTM specification B575 (UNS 
N06022). In addition, five heats of Alloy 22 base metal were used in performing the 
measurements on test specimens, and the chemical composition of these heats are summarized in 
Table 10. In all heats, the Alloy 22 chemical composition was more restricted than that specified 
in ASTM specification 575B (UNS N06022). As a result, at this time until results from a heatto-
heat variability study are available, the conclusions presented here applied to an Alloy 22 
chemical composition that is bounded by the range compositions of these five heats. The 
bounded range of alloy composition also is consistent with the composition of the ternary Ni 
CrMo alloy that was used as a surrogate for Alloy 22 in the Thermo-Calc/DICTRA simulations. 
This Alloy 22-bounded range of chemical composition is summarized in Table 11 and is the 
recommended specification of chemical composition that is applicable to the conclusions on 
alloy performance presented in this document. Future adjustments may be made to this 
recommended specification on Alloy 22 chemical composition as new data or results become 
available. 
  132  
Table 10 Summary of Alloy 22 Chemical Composition of Heats Tested 
HEAT # AI C Co Cr Cu Fe Mg Mn Mo N Nb(Cb) Ni P S Si Ta Ti V W 
BAL .01 .002 .047 - 4.4 - 0.29 13.4 - .004 1.14 21.3 - 2277-0-3264 - -
-
-
-
- 
BAL .006 .003 .038 - 4.5 - 0.25 13.3 - .003 1.96 21.2 - 2277-0-3270 - 
BAL .006 .001 .035 - 0.3 13.43 - 3.82 - .003 .48 21.24 - 2277-8-3121 - 
BAL .008 .001 .023 - 3.94 - 0.24 13.47 - .003 1.31 21.4 - 2277-8-3235 - 
BAL .007 .002 - .036 3.6 - 0.28 - 13.29 .002 1.04 21.28 - 2277-9-3243 - 
Table 11 Recommended Alloy 22 Chemical Composition (Based on Performance of Heats Tested to Date) 
AI C Co Cr Cu Fe Mg Mn Mo N Nb(Cb) Ni P S Si Ta Ti V W 
- 0.05 max 2.5 max 20.0-22.5 - 2.0-6.0 - 0.50 max 12.5-14.5 - ASTM B575 
Recommended 
Specification - 0.04 max ma 2.0 x 20.0-22.5 - 3.5-4.5 - 0.30 max 12.5-14.5 - 
ANL-EBS-MD-000002 REV 1 ICN 0 133 
Reference 
- 0.17 2.9 S/N# 00444, LL,Vol 1, p.9 
- 0.14 3.0 S/N# 00444, LL,Vol 1, p.9 
- 0.17 2.85 S/N# 00444, LL,Vol 1, p.17 
- 0.17 2.87 S/N# 00393, LL, p.1 
- 0.14 2.8 S/N# 00444, LL,Vol 1, p.9 
BAL 0.02 max 0.02 max - - 0.35 max 2.5-3.5 - - 
0.2 max 2.5-3.5 BAL 0.01 max 0.003 max - - - - 
June 2003  
8.3 SUMMARY OF DEVELOPED DATASETS 
The developed data from this report that have been presented and discussed in Sections 6 
and 7 have been summarized in Table 12. 
Table 12 Summary of Developed Datasets 
Data Name 
Property and Phase Kinetics 
Diagrams 
Validation of Computational Model 
Developed Data from Alloy 22 
Volume Fraction Measurements 
8.4 ACCEPTANCE CRITERIA 
The criteria stated in Section 4.2 have been achieved as follows: 
AC1: System Description and Model Integration are Adequate (Section 6.5) 
AC2: Data are Sufficient for Model Justification (Section 7) 
AC3: Data Uncertainty is Characterized and Propagated Through the Model 
Abstraction (Section 6.7) 
AC4: Model Uncertainty is Characterized and Propagated Through the Model 
Abstraction (Section 6.7) 
AC5: Model Abstraction Output is Supported by Objective Comparisons (Section 7) 
DTN 
LL030106312251.013 
LL030106412251.014 
LL030606912251.020 
Data Presented 
in this AMR 
Sections 6.6.1.1 
through 6.6.4.3 
See Sections 7.1 
through 7.4 
Sections 6.6.5 
and 7.5 
ANL-EBS-MD-000002 REV 1 ICN 0 134 June 2003  
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9.1 SOFTWARE 
Adobe Systems Incorporated, Adobe Illustrator, Version 8, San Jose, California, 
Software Tracking Number: Exempt. 
Apple Computer, ClarisDraw, Version 1.04, Cupertino, California, Software Tracking 
Number: Exempt. 
Media Cybernetics, Image-Pro Plus, Versions 4.0, 4.1, and 4.5.1, Silver Spring, 
Maryland, Software Tracking Number: Exempt. 
Microsoft, Excel, Redland, Washington, Software Tracking Number: Exempt 
Synergy Software, Kaleidagraph, Version 3.5, Reading, Pennsylvania, Software 
Tracking Number: Exempt. 
Thermo-Calc Software, Thermo-Calc Version M, Stockholm, Sweden, Software 
Tracking Number: 10170-M-00. 
Thermo-Calc Software, DICTRA Version 20, Stockholm, Sweden, Software Tracking 
Number: 10391-20-00. 
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