Engineering topics
Publications and source records attributed to Whiteside, Tad.
This appendix contains information and key data in support of Chapter 3 and Chapter 8. The following topics are addressed: PIF aquifer cutouts for ELLWF aquifer flow and transport analyses. Limits aquifer cutouts for ELLWF aquifer flow and transport analyses.
This appendix to Chapter 5, Section 5.1 provides supplemental concentration profiles for radionuclide species in STs and ETs that contribute to at least 0.1% of the sum-of-fractions. All concentrations are reported as pCi L -1 per Ci parent buried. The following nomenclature is used for all radionuclides in all DUs: an uppercase letter suffix indicates a SWF (e.g., I-129G, C-14N, H-3F, etc.), while the absence of an uppercase letter denotes a generic waste form (e.g., I-129, C-14, H-3, etc.).
Supplemental transport model results for the LAWV from Chapter 5, Section 5.2.2 are provided in Section E.1.1 to compare concentrations at the 100-meter POA for the nominal PA case, best estimate case, and various sensitivity cases (Figure E-1 through Figure E-12). Second, Figure E-13 through Figure E-30 in Section E.1.2 display concentrations at the 100-meter POA for decay-chain daughter and parent radionuclides. Third, Figure E-31 through Figure E-34 in Section E.1.3 show maximum concentration contours for I-129. Only contour plots for I-129 from the remaining sensitivity runs are shown because I-129 is identified as the only radionuclide that impacts disposal limits for the LAWV. All concentration units, whether noted or not in the y-axis labels, are pCi L-1 per Ci parent buried.
As a supplement to Chapter 6, Section 6.1.1.3, Table F-1 through Table F-24 provide tabular results of the sensitivity analysis calculations for waste disposal timing (Sensitivity Case S6) in NR07E (Cases 3 and 4) and NR26E (Cases 1 through 4). The title of each table identifies the DU, sensitivity case, and performance measure. Section F.1.1 (Table F-1 through Table F-8) presents results for NR07E and Section F.1.2 (Table F-9 through Table F-24) presents results for NR26E. In each table, radionuclides are sorted from highest to lowest nominal concentration or dose factor. Nominal values are when waste disposal occurs at the start of operations; timeline values are when waste disposal occurs at the end of operations. The differences (Δ values) in the last column of each table equal the timeline concentration or dose factor minus the nominal concentration or dose factor, where DF and CF are shorthand designations for dose factor and concentration factor, respectively.
This appendix contains supporting information and key data used during the IHI analysis, including the following: • A list of parent radionuclides requiring IHI inventory limits (Section G.1) • Tables of IHI acute and chronic dose factors, inventory limits, and concentration limits for all DUs (Section G.2) • IHI acute and chronic dose history time profiles for all DUs (Section G.3)
This section provides supporting material for the development of DU-specific final inventory limits for the GW pathways for every generic waste form and SWF parent radionuclide requiring an inventory limit. The final inventory limits are based on nominal PA transport simulations using PORFLOW as reported in Chapter 5. The nominal PA settings represent the compliance case where some modeling parameter settings are defined based on conservative (pessimistically leaning) arguments. In the overall computational approach employed in this PA, a multitiered radionuclide screening process is adopted as discussed in Chapter 2, Section 2.3.7. In the multitiered process, the initial list of 1,252 parent radionuclides is shortened substantially using conservative, but simple, transport models, along with a reasonably low cutoff criterion of 0.1% SOF value. Multidimensional PORFLOW flow and transport modeling is employed for every parent radionuclide that failed the GW screening. The generic waste form limits represent Tier-3 analyses, while Tier-4 analyses are employed for SWF limits, where warranted.
As stated in Section 9.1.2.2, a final inventory of parent radionuclides is projected for every DU at the time of facility operational closure in 2065. These final closure inventories are upper-bound estimates wherein each DU is assumed to reach its activity capacity. Composition vectors based on existing DU inventories are employed to estimate the final compositions of all existing and future DUs. Specifically, (1) the existing DU compositions are assumed to remain constant; (2) future DUs are assigned averaged existing compositions based on appropriately averaged DUs. This information is detailed in Appendix H, Section H.7. In addition, the variability in composition among existing DUs is used to generate log-normal distributions for uncertainty quantification, which is detailed in Section I.1.1.
In FY2020, Savannah River National Laboratory (SRNL) in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics (SCAIDA) at Virginia Polytechnic Institute and State University (VT) and funded by the Department of Energy’s (DOE) Defense Nuclear Nonproliferation Research and Development, began developing a demonstration prototype system that uses multiple machine learning and data analytic methods on large-scale open data sources to identify new, developing, and/or undeclared nuclear programs. Using the announcement in May 2018 of the proposed Savannah River Plutonium Processing Facility (SRPPF) as a test subject, the goal of this 2-year project is to forecast the SRPPF using only data prior to May 2018. The project work is split into a preliminary prototype development for the first year with an initial evaluation of viability followed by the second year of development to create an integrated prototype system and more extensive performance evaluation. This report documents the results of the preliminary-phase tasks.