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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Examination of Molten Salt Reactor Relevant Elements Using Hydrothermal Synthesis

The structural chemistry of elements relevant to the FLiBe molten salt reactor, Th, U, Np, and Zr, including Ce andNd (as analogues for Pu and Am, respectively), have been examined using hydrothermal synthesis at 200 °C. These reactions serve to model the reaction of molten salts under hydrolysis conditions. The results show that U and Np formed LiAnF 5 , while Ce formed Li 4 CeF 8 . The source of U also controlled the crystal quality, where UO 2 gave small crystals, while UO 3 ·2H 2 O gave very large crystals. It is likely that Be incorporation was not observed because of the high solubility of [BeF 4 ] 2– in water. Zr formed a third product, Li 6 BeF 4 ZrF 8 , which features isolated [BeF 4 ] 2– and [ZrF 8 ] 4– units bridged by Li + . Additionally, Li 2 BeF 4 was regularly isolated. As a result, when little to no alkali metal was included in the reaction, M 3 F 12 (H 2 O) was isolated for Np, U, and Ce.

Anions↗
DOE OSTI2022

TRISO SiC Failure Probability for Reactivity Initiated Accidents in High-Temperature Gas-Cooled Reactors

This work analyzes the failure process of the silicon carbide (SiC) layer in tristructural isotropic (TRISO) during reactivity-initiated accident scenarios for a high-temperature gas-cooled reactor (HTGR) with BISON. Two cases are considered—a group control rod withdrawal (CRW) and a control rod ejection (CRE)—reproduced from a previous study. Failure probability is modeled using Weibull statistics, and worst-case scenario Weibull parameters are adopted to simulate the envelopes in BISON with a one-dimensional TRISO model. CRW scenario results are characterized by higher values of maximum energy deposition and final temperature and volumetric strain with respect to the CRE ones, but the latter have remarkably higher SiC failure probability, mainly due to the offset in strain rates between the two cases. This work also confirms the validity and conservatism of the performance envelopes produced in a previous work by replicating the envelope formulation using RELAP5-3D and RAVEN with a different sampling technique and obtaining consistent results. A sensitivity analysis using the Sobol variance decomposition method on SiC failure probability is then performed involving a set of inputs on both CRW and CRE. The two most important parameters are Weibull modulus and characteristic stress, and their relative importance depends on the specific case. The proposed interpretation of the results is that both energy deposition and strain rate influence the relative degree of importance of the failure parameters. Computation of 95% confidence intervals around worst-case scenario SiC failure probability values is also carried out for four different sets of Weibull parameters. Heren a new criterion for SiC TRISO quality classification built upon safety-based ranges of Weibull parameters is proposed to be integrated in future Fuel-Production Quality Assurance Plans.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Xe-100 Pebble Bed Small Modular Reactor: Solving Critical Challenges to Enable the Xe-100 Pebble Bed Advanced Reactor Concept (ARC) (Final Scientific and Technical Report)

This is the final progress report for the Department of Energy (DOE) – X Energy, LLC cooperative agreement DENE0008472. This report provides a high-level summary of the work performed during the entire period of performance, running from July 1, 2016 – June 30, 2022. This span of time covers the original 5-year award and a one year no-cost extension. There were four tasks within this project: (1) project management, (2) reactor design furtherance, (3) fuel development, and (4) Nuclear Regulatory Commission (NRC) engagement. Detailed reporting during execution of the project was provided by a total of 23 quarterly reports, 42 X-energy technical reports, and voluntary monthly update presentations. Other technical work products include 2 white papers and 2 Topical Report submitted to the Nuclear Regulatory Commission, 15 Potential Inventions documented, 4 patents issued, 3 patents pending, 8 peer reviewed journal articles, and 2 Oak Ridge National Laboratory Technical Manuscripts. All the X Energy milestones/deliverables were met early or on time and are archived in the DOE Office of Nuclear Energy’s Program Information Control System: Nuclear Energy under Fiscal Year 2016, Work Breakdown Structure 2.07 – X-Energy. All other work products are available to DOE upon request.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Chemical Reactor Network Modeling of Ammonia Rich-Quench-Lean Combustion Using a Partially Stirred Reactor Approach

Ammonia is a promising alternative fuel, but its use is challenging due to low flammability and high nitrogen oxide (NOx) emissions. Two-stage rich-quench-lean (RQL) combustion strategies have shown promise in reducing NOx emissions. This approach involves two stages: a rich stage that oxidizes part of the fuel and decomposes ammonia into hydrogen, and a lean stage that burns out the hydrogen and residual ammonia. Researchers used a chemical reactor network model to study the effects of heat loss and mixing on emissions performance. They found that heat loss and reduced mixing rates can lead to increased NOx emissions and N2O formation. The results will inform the development of optimized two-stage RQL combustors for ammonia, with a focus on minimizing NOx emissions and improving overall efficiency.

ammonia combustion↗
DOE OSTI2022

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Management of Risks Associated with Application of Novel Materials in Novel Operating Environments in Novel Reactor Designs

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. These challenges are discussed in the paper, and a potentially applicable modeling approach based on cumulative damage rather than failure rates is briefly illustrated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗