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Probabilistic Risk Assessment of RCC Dam Considering Grey-Stochastic-Fuzzy Uncertainty
Abstract Greyness, randomness and fuzziness are three inseparable uncertainty factors influencing the safety of a roller compacted concrete dam (RCC dam), which can be regarded as a system reliability problem associated with multiple failure modes. Aiming at the current probabilistic risk analysis of RCC dams, most of the studies limited to single failure mode and single uncertainty. A probabilistic risk assessment method for dam under Grey-Stochastic-Fuzzy (GSF) uncertainty is proposed to consider the randomness and greyness of parameters and the fuzziness of the failure criteria. First, the fault tree model of an RCC dam is established based on Fault Tree Analysis (FTA). Then, bootstrap repeated sampling is embedded into grey system theory to quantify the grey properties of stochastic variables. The Latin Hypercube Sampling (LHS) function is improved to compensate for the inability of describing the fuzzy failure criteria. Finally, considering the correlated multiple failure modes, the proposed method is applied to analyze the parameter sensitivity and failure probability of the LDL dam in China. The results show that the proposed method is a high-efficiency, fast-convergence and more scientific method with reasonable outputs compared to common uncertainty probability analysis methods. The proposed method also provides an effective basis for the structural design and safety analysis of a concrete dam.
Probabilistic Risk Assessment of RCC Dam Considering Grey-Stochastic-Fuzzy Uncertainty
Abstract Greyness, randomness and fuzziness are three inseparable uncertainty factors influencing the safety of a roller compacted concrete dam (RCC dam), which can be regarded as a system reliability problem associated with multiple failure modes. Aiming at the current probabilistic risk analysis of RCC dams, most of the studies limited to single failure mode and single uncertainty. A probabilistic risk assessment method for dam under Grey-Stochastic-Fuzzy (GSF) uncertainty is proposed to consider the randomness and greyness of parameters and the fuzziness of the failure criteria. First, the fault tree model of an RCC dam is established based on Fault Tree Analysis (FTA). Then, bootstrap repeated sampling is embedded into grey system theory to quantify the grey properties of stochastic variables. The Latin Hypercube Sampling (LHS) function is improved to compensate for the inability of describing the fuzzy failure criteria. Finally, considering the correlated multiple failure modes, the proposed method is applied to analyze the parameter sensitivity and failure probability of the LDL dam in China. The results show that the proposed method is a high-efficiency, fast-convergence and more scientific method with reasonable outputs compared to common uncertainty probability analysis methods. The proposed method also provides an effective basis for the structural design and safety analysis of a concrete dam.
Probabilistic Risk Assessment of RCC Dam Considering Grey-Stochastic-Fuzzy Uncertainty
Chen, Wenlong (author) / Wang, Xiaoling (author) / Liu, Minghui (author) / Zhu, Yushan (author) / Deng, Shaohui (author)
KSCE Journal of Civil Engineering ; 22 ; 4399-4413
2018-05-31
15 pages
Article (Journal)
Electronic Resource
English
Probabilistic Risk Assessment of RCC Dam Considering Grey-Stochastic-Fuzzy Uncertainty
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