Nuclear Fuel Cycle and Supply Chain (NFCSC) Technical Monthly August FY-23
Nuclear Fuel Cycle and Supply Chain (NFCSC) Technical Monthly August FY-23
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Nuclear Fuel Cycle and Supply Chain (NFCSC) Technical Monthly October FY-23
Nuclear Fuel Cycle and Supply Chain (NFCSC) Technical Monthly October FY-23
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Nuclear Fuel Cycle and Supply Chain (NFCSC) Technical Monthly September FY-23
Nuclear Fuel Cycle and Supply Chain (NFCSC) Technical Monthly September FY-23
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Materials and Fuels Complex FY-23 - FY-27: Five-Year Investment Strategy
The Department of Energy Office of Nuclear Energy (DOE-NE) vision is to “Advance nuclear energy science and technology to meet U.S. energy, environmental, and economic needs.” The Materials and Fuels Complex (MFC) serves as the foundation of a nuclear RD&D enabling test bed at Idaho National Laboratory (INL) and is an integral part of a National Reactor Innovation Center (NRIC) strategy. MFC facilities focus on developing and maintaining RD&D capabilities that can increase research throughput, reduce barriers to deployment, and facilitate commercialization of new ideas and technologies for clean and secure sources of energy.
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Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities
The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.
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Assessment of Readout Techniques for Passive Monitors
This fiscal year (FY) 2023 report on passive temperature sensors covers two main objectives: to demonstrate that the optical dilatometer can successfully process disc shaped silicon carbide (SiC) temperature monitors (TMs), and to demonstrate proof of concept for using the capacitance readout method to read printed melt wires. The SiC objective was successfully met by annealing and analyzing, via optical dilatometry, all eight 3-mm SiC discs provided by the Nuclear Science User Facilities (NSUF) Idaho State University (ISU) Nanostructured Steels for Enhanced Radiation Tolerance (N SERT) experiment, which was irradiated at Idaho National Laboratory (INL)’s Advanced Test Reactor (ATR). Per the ISU N SERT experiment, capsule 1 (KGT 3828 1 and KGT 3828-2) had a design temperature of 300°C +/- 50°C and an exposure of 2 dpa +/- 10%; capsule 2 (KGT 4600 and KGT 4609) had a design temperature of 300°C +/- 50°C and an exposure of 6 dpa +/- 10%; capsule 3 (KGT 4639 C and KGT 4639-D) had a design temperature of 500°C +/- 50°C and an exposure of 6 dpa +/- 10%; and capsule 4 (KGT 3841 3 and KGT 3841 4) had a design temperature of 500°C +/- 50°C and an exposure of 2 dpa +/- 10%. The target exposure rates, in dpa, are the neutron damage for various types of nanostructured steels. All but three SiC TMs (KGT 4600, KGT 4639 D, and KGT 3841 4) revealed averaged peak irradiation temperatures that fell within the design temperature ranges. The three SiC TMs that did not fall within the design temperatures ranges were at least 100°C below that target temperature. Furthermore, SiC TM KGT 3841 C revealed two irradiation regimes: one closer to the 300°C design temperature, and the other closer to the 500°C design temperature. Also, all the SiC TMs’ averaged peak irradiation temperatures came in anywhere between 20°C and 240°C below the irradiation temperatures predicted by the thermal models. This showed the optical dilatometry method to be a reliable and less time intensive process for determining averaged peak irradiation temperatures from passive SiC TMs such as rods and discs. Under the Advanced Sensors and Instrumentation (ASI) program in FY-23, Boise State University (BSU) proposed to demonstrate proof of concept for using a capacitance readout technique applicable to printed melt wires; however, they were stymied by the complexity of the capacitance readout method. In support of the BSU work, INL developed an additively manufactured (AM) ceramic package for encapsulating the new melt wires. Inks were synthesized at BSU that used new protocols rather than following previously established protocols implemented at INL, and testing of various temperatures was conducted at BSU to evaluate the melting behaviors of the printed melt wires. The result was that the capacitance readout technique showed promise but also created more challenges than originally anticipated. For example, the tin ink synthesized at BSU showed unusual melting behaviors that did nothing to enhance the performance of the final printed melt wire prototype in terms of the capacitance readout method. To make the proof of concept work when applied to the printed melt wires, the ASI program would need to invest further resources and time. Consequently, the program is not planning to continue this proof of concept work in FY-24, based on the progress and findings achieved in FY-23.
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R-Matrix Analysis of the Neutron-Induced Cross Sections on 143 Nd and 147,149 Sm Measured at LANSCE [Slides]
This presentation covers how an established used of R-Matrix codes is being implemented at LANSCE. This presentation displays how there are unique features accessible with detectors at LANSCE that can be used to perform more complete R-Matrix analysis. Additionally discussed is how spin separation is a powerful technique that can be applied in DANCE measurements. Unique method to measure transmission with DICER are discussed. Finally, transmission and capture data are being analyzed in this work. The study can be extended to other channels. The ongoing analysis of the 143 Nd data is presented in this work. The same method is being applied to analyze the 147,149 Sm data. The 143 Nd and 147,149 Sm work started in FY-23 funded by NCSP.
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Advanced Fuel Cycle Cost Basis Report: Module D1-1: Uranium-based Ceramic LWR Fuel Fabrication (Rev.2)
Cost module on LWR fuel fabrication to accompany the Advanced Fuel Cycle Cost Basis Report. In this update, we are adding detailed life cycle cost data and a calculated, levelized fabrication cost derived from a non-proprietary bottom-up estimate prepared in 1978 by Oak Ridge National Laboratory (ORNL) (Judkins and Olsen 1978a). In 2018, the 1978 ORNL estimate was escalated by SA&I authors to 2017 USD using factors that represent inflation, escalation above inflation typical of nuclear projects, and the effects of more stringent safety and environmental regulations. In this FY-21 document, the $/kgU results in 2017 USD from the unpublished 2018 interim study (Williams and Ganda 2018) can be escalated to 2020 USD using a factor of 1.052. The literature-based unit cost (or price) data from previous (2004–2017) AFC-CBRs are escalated to 2020 USD using factors from Chapter 8 of the main FY-21 AFC-CBR document. This data, in addition to the results of the updated bottom-up estimate, are used to define the “what-it-takes” (WIT) range for the unit fabrication costs for conventional ceramic UOX light-water reactor (LWR) fuel. This FY-23 document also includes calculated unit costs for accident-tolerant LWR fuels (ATFs) of three different types. Some of these fuels constitute a ceramic pelletized form with fuel meat uranium compounds other than UO2 (a.k.a.,. UOX), thus the change in the title of this module in which the word “UO2” is changed to “Uranium-based Ceramic.”
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Advanced Reactor Regulatory Framework Development Activities for Fiscal Year 2023
This report provides an end-of-year summary that reflects the progress and status of Idaho National Laboratory’s (INL) activities concerning the development of advanced reactor (AR) regulatory framework and its implementation in the United States (U.S.). The report also summarizes some general updates on important topics in regulatory development. This work was completed in Fiscal Year 2023 (FY-23) and was supported by the U.S. Department of Energy (DOE) Regulatory Development sub-program. These activities are managed by INL on behalf of DOE.
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2023 Annual Report Laboratory Directed Research & Development
This is the FY-23 LDRD annual report. The 59 projects concluded in fiscal year 2023, highlighted in this report, represent a glimpse into the extraordinary breadth and depth of leading-edge science, technology, and engineering endeavors ongoing at INL. I invite you to explore this report thoroughly, discovering first-hand how INL's LDRD portfolio not only fosters innovation but also nurtures researcher talent, propelling us closer to realizing our vision of transforming the world's energy future and safeguarding our critical infrastructure.
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Nuclear Science User Facilities High Performance Computing: FY 2023 Annual Report
FY 2023 Annual Report including major accomplishments, utilization and user institution statistics, and project summary reports for FY-23 for Idaho National Laboratory High Performance Computing.
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NSUF FY23 Annual Report
Annual report for work completed during FY-23 for the Nuclear Science User Facilities.
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