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Davidson, E.

Publications and source records attributed to Davidson, E..

5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Values of Recovered Uranium from HALEU Used Nuclear Fuels (Rev. 1)

The value of the recovered uranium (RU) from high assay low-enriched uranium (HALEU) used nuclear fuels was evaluated. Three utilizations of the recovered uranium were considered in this study, which include the cases that RU is used as a fissile material of nuclear fuel, RU is reused in the original advanced reactor after reenrichment, and RU is reused in conventional light water reactors after down-blending. In this study, the RU values were identified by comparing the cost of making a unit mass of fuel with RU versus the fuel cost with the equivalent fresh enriched uranium (EU). A series of bounding analyses for calculating the fuel costs were conducted using several selected reactor types, which include microreactors, advanced thermal reactors, and fast reactors having a burnup of 2 – 165 GWd/t (with residual U-235 content in discharged fuels of 0.8 - 19.6%). This study concludes that RU having a residual U-235 content higher than ~7% would cost less than the fresh EU. The affordability increases as the residual U-235 content in RU increases. For instance, the fuel cost with RU having the residual U-235 content of 19.6% is about 85% cheaper than the fuel cost with the equivalent fresh EU. This study observed that reusing RU after reenrichment in the original microreactor is impractical because the U-235 content in the re-enriched RU fuel would need to be higher than the limit for low-enriched uranium (<20%) to provide the same burnup performance due to parasitic absorption from U-236. It is noted that this study focused on the recovery of uranium only, and the value of other fissile materials (such as Pu) in the used nuclear fuel was not considered even though those are bred significantly in fast reactors. In addition, the impacts of uncertainties in the cost data and the value of RU of TRISO fuels were not evaluated in this study due to the limited information on the cost data uncertainties and the separation cost from TRISO fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Report on Fuel Cycle Facility Requirements for Deployment of Demonstration Reactors and Potential Evolutionary Fuel Cycle Scenarios

A series of fuel cycle scenarios studies were performed to inform on fuel cycle capacities and facilities needed for large-scale deployment of the Advanced Reactor Demonstration Program (ARDP) reactors and potential future evolutionary fuel cycle scenarios. The reactor deployment and evolutionary fuel cycle scenarios from the present to 2100 were developed based on the following assumptions: 1) achievement of a net-zero emissions economy in the United States by 2050, which requires a nuclear energy generation capacity of ~250 GWe by 2050, 2) the U.S. economic growth of 1% per year from 2051 to 2100, which results in ~340 GWe of nuclear energy capacity in 2100, and 3) commercial-scale recycling and high burnup fuel technologies are available after 2050. Thus, evolutionary fuel cycles with those advanced nuclear technologies start after 2050. A single once-through fuel cycle scenario was assumed from the present to 2050 to achieve a net-zero emissions economy in the United States, and the following four evolutionary fuel cycle scenarios from 2051 to 2100 were considered, 1) Once through fuel cycle with ARDP reactors (Natrium and Xe-100), 2) Once-through fuel cycle with Breed-and-Burn (B&B) fast reactors, 3) Recycling fuel cycle of used metallic fuel in fast reactors, and 4) Recycle fuel cycle of both used uranium oxide and metallic fuels in fast reactors. The projected front-end and back-end fuel cycle capacity demands are compared with the current domestic and global (if needed) fuel cycle capacities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗