Coupling Design and Validation Analysis of an Integrated Framework of Uncertainty Quantification
Energies, ISSN: 1996-1073, Vol: 16, Issue: 11
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Researcher from Nuclear Power Institute of China Details Findings in Software (Coupling Design and Validation Analysis of an Integrated Framework of Uncertainty Quantification)
2023 JUN 15 (NewsRx) -- By a News Reporter-Staff News Editor at Computer News Today -- Data detailed on software have been presented. According to
Article Description
The uncertainty quantification is an indispensable part for the validation of the nuclear safety best-estimate codes. However, the uncertainty quantification usually requires the combination of statistical analysis software and nuclear reactor professional codes, and it consumes huge computing resources. In this paper, a design method of coupling interface between DAKOTA Version 6.16 statistical software and nuclear reactor professional simulation codes is proposed, and the integrated computing workflow including interface pre-processing, code batching operations, and interface post-processing can be realized. On this basis, an integrated framework of uncertainty quantification is developed, which is characterized by visualization, convenience, and efficient computing. Meanwhile, a typical example of small-break LOCA analysis of the LOBI test facility was used to validate the reliability of the developed integrated framework of uncertainty quantification. This research work can provide valuable guidance for developing an autonomous uncertainty analysis platform in China.
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