Abstract
The structures associated with the nuclear steam supply system (NSSS) of a pressurized water reactor (PWR) include significant epistemic and aleatory uncertainties in the physical parameters, while also being subject to various non-stationary stochastic loading conditions over the life of a nuclear power plant. To understand the influence of these uncertainties on nuclear reactor systems, sensitivity analysis must be performed. This work evaluates computational design of experiment strategies, which execute a nuclear reactor equipment system finite element model to train and verify Gaussian Process (GP) surrogate models. The surrogate models are then used to perform both global and local sensitivity analyses. The significance of the sensitivity analysis for efficient modeling and simulation of nuclear reactor stochastic dynamics is discussed.
Original language | English (US) |
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Article number | 110544 |
Journal | Nuclear Engineering and Design |
Volume | 361 |
DOIs | |
State | Published - May 2020 |
All Science Journal Classification (ASJC) codes
- Nuclear and High Energy Physics
- General Materials Science
- Nuclear Energy and Engineering
- Safety, Risk, Reliability and Quality
- Waste Management and Disposal
- Mechanical Engineering