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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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Highlights and significant accomplishments of Advanced Gas Reactor (AGR) fuels development activities during January, February and March 2021
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.
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.
Powerpoint presentation for the 2025 NPIC-HMIT conference on barriers for adoption of DI&C systems in nuclear reactors.
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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)
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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.
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