Quantitative Phenomena Identification and Ranking Table (QPIRT) for Reactor Safety Analysis
Next generation reactor safety analysis codes are intended to make use of advanced numerical methods and higher fidelity models with built-in sensitivity analysis (SA) and uncertainty quantification (UQ) [1]. However, due to the complex nature of uncertainty propagation in thermal-hydraulic codes, i...
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| Format: | Article |
| Language: | en_US |
| Published: |
American Nuclear Society
2014
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| Online Access: | http://hdl.handle.net/1721.1/87057 https://orcid.org/0000-0001-6501-2836 |
| Summary: | Next generation reactor safety analysis codes are intended to make use of advanced numerical methods and higher fidelity models with built-in sensitivity analysis (SA) and uncertainty quantification (UQ) [1]. However, due to the complex nature of uncertainty propagation in thermal-hydraulic codes, it is crucial to first narrow the focus to only the most important processes contributing to a particular figure of merit (FOM). Uncertainty propagation in the safety code is then performed through those dominant controlling phenomena. Traditionally, Phenomena Identification and Ranking Tables (PIRTs) based on expert opinion have been used to guide selection of the "most important processes." But in the present context, uncertainty propagation must be performed on the dominant processes as "viewed" by the safety code itself. Therefore a PIRT-like methodology must be applied to rank processes from the safety code's point of
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