Affiliation:
1. Center for Nuclear Science and Energy, Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA
Abstract
This work presents illustrative applications of the 2nd-BERRU-PM (second-order best-estimate results with reduced uncertainties predictive modeling) methodology to the leakage response of a polyethylene-reflected plutonium OECD/NEA reactor physics benchmark, which is modeled using the neutron transport Boltzmann equation. The 2nd-BERRU-PM methodology simultaneously calibrates responses and parameters while simultaneously reducing the predicted standard deviation values of these quantities. The situations analyzed in this work pertain to the values of measured responses that appear to be inconsistent with the computed response values, in that the standard deviation values of the measured responses do not initially overlap with the standard deviation values of the computed responses. It is shown that the inconsistency diminishes as higher-order sensitivities are progressively included, thus illustrating their significant impact. In all cases, the 2nd-BERRU-PM methodology yields predicted best-estimate standard deviation values that are smaller than both the computed and the experimentally measured values of the standard deviation for the model response under consideration.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference5 articles.
1. Cacuci, D.G., and Fang, R. (2023). Demonstrative Application to an OECD/NEA Reactor Physics Benchmark of the 2nd-BERRU-PM Method. I: Nominal Computations Consistent with Measurements. Energies, 16.
2. Second-Order MaxEnt Predictive Modelling Methodology. I: Deterministically Incorporated Computational Model (2nd-BERRU-PMD);Cacuci;Am. J. Comput. Math.,2023
3. Second-Order MaxEnt Predictive Modelling Methodology. II: Probabilistically Incorporated Computational Model (2nd-BERRU-PMP);Cacuci;Am. J. Comput. Math.,2023
4. Valentine, T.E. (2006). Polyethylene-Reflected Plutonium Metal Sphere Subcritical Noise Measurements. SUB-PU-METMIXED-001, International Handbook of Evaluated Criticality Safety Benchmark Experiments, Nuclear Energy Agency. NEA/NSC/DOC(95)03/I-IX.
5. Cacuci, D.G., and Fang, R. (2023). The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology: Overcoming the Curse of Dimensionality: Vol. II: Application to a Large-Scale System, Springer. (eBook).
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献