| Autor: |
ZHANG Shiqi, PENG Minjun, XIA Genglei, WANG Chenyang, SHANG He |
| Jazyk: |
čínština |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
He jishu, Vol 47, Iss 6, Pp 060605-060605 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
0253-3219 |
| DOI: |
10.11889/j.0253-3219.2024.hjs.47.060605&lang=zh |
| Popis: |
BackgroundPassive safety system reliability is generally evaluated through best estimation plus uncertainty (BEPU) analysis. An important step in the evaluation process is sensitivity analysis of parameters, which is used to identify key system parameters to reduce the complexity of the model. However, local sensitivity analysis methods based on linear or monotonic assumptions may yield incorrect sensitivity results for complex nuclear power systems. Meanwhile, applying the global sensitivity method is difficult in practical engineering because of its high calculation cost.PurposeThis study aims to develop an efficient and low-cost global sensitivity analysis method for passive systems under ocean conditions.MethodsFirstly, the low-rank approximation (LRA) method was employed to improve the Sobol method based on Monte Carlo simulation. The number of unknown coefficients was significantly reduced by using the multivariate-based tensor product. Then, the LRA coefficients were used to calculate the sensitivity index, and the validity of the proposed method was verified by addressing several sensitivity analysis benchmark questions. Finally, taking an integrated pressurized water reactor including the passive residual heat removal system as the object, a simulation program for thermal-hydraulics analysis under ocean conditions was developed. And its sensitivity analysis was conducted using the proposed method.ResultsThe results show that the proposed method can accurately identify system key parameters after only 200 simulation calculations taking about 55 min, and the sensitivity ranking results are consistent with those obtained by Sobol method after 1.0×105 simulation calculations taking about 19 d.ConclusionsThe efficient global sensitivity analysis method established in this study can provide effective guidance for reliability analysis and design optimization of passive systems. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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