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论文类型：期刊论文

发表时间：2020-02-01

发表刊物：ANNALS OF NUCLEAR ENERGY

收录刊物：EI、SCIE

卷号：136

ISSN号：0306-4549

关键字：Bank revetment; Nuclear power plant; Stability reliability; Stochastic seismic response; Probability density evolution method

摘要：Bank revetments are built near nuclear power plant sites and are used to protect nuclear power plants from potential damage due to incoming water, such as from flooding or large waves. However, the uncertainty of earthquake behavior can make it difficult to adequately design the bank revetments against seismic activity. In earthquake prone areas, such a situation is dangerous, especially when near bodies of water. Thus, when designing the safety of a nuclear power plant near large bodies of water, the seismic behavior of the bank revetments should be taken into consideration. This paper discusses the development and implementation of a probability density evolution method (PDEM) that can be used to predict the effect of stochastic seismic ground motion on the dynamic stability and reliability of nuclear power plant bank revetments. The probability density equation of a bank revetment is derived through performing a set of deterministic, dynamic finite element analyses and stability analyses. The analyses are supported by second-order statistical analysis of the safety factor of two levels of seismic activity: SL-1 (operational safety earthquake) and SL-2 (ultimate safety earthquake). Then, the probability information is obtained at the two levels by solving the probability density evolution equation. The results demonstrate that the required safety factor can depend on the nature of the seismic excitation. Through the above procedures, the reliability assessment of bank revetments under SL-1 and SL-2 loading can be accomplished. In a comparative case study, the seismic responses of unreinforced and reinforced bank revetments to stochastically generated seismic excitation under SL-2 levels correctly indicates that reinforcement can significantly increase the reliability of the bank revetment. (C) 2019 Elsevier Ltd. All rights reserved.