IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v235y2023ics0951832023001321.html
   My bibliography  Save this article

Stochastic dynamic and reliability analysis of AP1000 nuclear power plants via DPIM subjected to mainshock-aftershock sequences

Author

Listed:
  • Pang, Rui
  • Zai, Dezhi
  • Xu, Bin
  • Liu, Jun
  • Zhao, Chunfeng
  • Fan, Qunying
  • Chen, Yuting

Abstract

Earthquakes usually consist of a mainshock and a series of aftershocks, both of which are random. The mainshock can damage structures, and the subsequent aftershocks may cause further damage. However, no studies have considered the effects of stochastic seismic sequences on nuclear power plants (NPPs). We propose a new framework to analyze the stochastic dynamic response and dynamic reliability of AP1000 NPPs. First, stochastic mainshock-aftershock sequences are generated by combining a physical random function model, the narrowband harmonic group superposition method and the copula function. Then, the effects of aftershocks on NPPs are highlighted using acceleration and displacement as response indices and the tensile damage ratio (TDR) and plastic strain as damage indicators. Finally, probabilistic information and reliability of NPPs are obtained based on the direct probability integration method (DPIM) and the absorbing condition method (ACM). The results show that the dynamic response is larger for seismic sequences than a single mainshock, and seismic sequences cause more damage to the NPPs. When the peak ground acceleration (PGA) increases, the effect of the aftershock becomes more pronounced, and the response of the NPP becomes more random. Moreover, aftershocks reduce the reliability of NPPs, and the degree of reduction is related to the thresholds.

Suggested Citation

  • Pang, Rui & Zai, Dezhi & Xu, Bin & Liu, Jun & Zhao, Chunfeng & Fan, Qunying & Chen, Yuting, 2023. "Stochastic dynamic and reliability analysis of AP1000 nuclear power plants via DPIM subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
  • Handle: RePEc:eee:reensy:v:235:y:2023:i:c:s0951832023001321
    DOI: 10.1016/j.ress.2023.109217
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023001321
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2023.109217?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Yuyin & Zhang, Yahui & Kennedy, David, 2018. "Reliability analysis of subsea pipelines under spatially varying ground motions by using subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 74-83.
    2. Zeng, Zhiguo & Fang, Yi-Ping & Zhai, Qingqing & Du, Shijia, 2021. "A Markov reward process-based framework for resilience analysis of multistate energy systems under the threat of extreme events," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    3. Kwag, Shinyoung & Park, Junhee & Choi, In-Kil, 2020. "Development of efficient complete-sampling-based seismic PSA method for nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    4. Heo, Yunyeong & Lee, Seung Jun, 2021. "Development of a multi-unit seismic conditional core damage probability model with uncertainty analysis," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    5. Do, Duy Minh & Gao, Wei & Song, Chongmin & Tangaramvong, Sawekchai, 2014. "Dynamic analysis and reliability assessment of structures with uncertain-but-bounded parameters under stochastic process excitations," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 46-59.
    6. Zhou, Taotao & Modarres, Mohammad & Droguett, Enrique López, 2021. "Multi-unit nuclear power plant probabilistic risk assessment: A comprehensive survey," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    7. Cai, Yinan & Golay, Michael W., 2020. "Formulation of A Risk Assessment Framework Capable of Analyzing Nuclear Power Multiunit Accident Scenarios," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    8. Jin, Kyungho & Hwang, Yujeong & Heo, Gyunyoung, 2021. "Development of Dependence Indexes for Multi-Unit Risk Assessment and its Estimation Using Copula," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Xinbo & Gong, Jinxin, 2024. "Probabilistic evaluation of the leak-tightness function of the nuclear containment structure subjected to internal pressure," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Zheng, Zhi & Tian, Aonan & Pan, Xiaolan & Ji, Duofa & Wang, Yong, 2024. "The damage-based fragility analysis and probabilistic safety assessment of containment under internal pressure," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yoo, Heejong & Heo, Gyunyoung, 2023. "Analysis of site operating state contributions for multi-unit PSA with Korean NPP Sites," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    2. Kim, Yongjin & Jang, Seunghyun & Jae, Moosung, 2022. "Evaluation of inter-unit dependency effect on site core damage frequency: Internal and seismic event," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    3. Zhao, Yan-Gang & Qin, Miao-Jun & Lu, Zhao-Hui & Zhang, Long-Wen, 2021. "Seismic fragility analysis of nuclear power plants considering structural parameter uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Yan, Rundong & Dunnett, Sarah & Andrews, John, 2023. "A Petri net model-based resilience analysis of nuclear power plants under the threat of natural hazards," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    5. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2023. "Multi-unit seismic probabilistic risk assessment: A Bayesian network perspective," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    6. Yu, Weichao & Huang, Weihe & Wen, Kai & Zhang, Jie & Liu, Hongfei & Wang, Kun & Gong, Jing & Qu, Chunxu, 2021. "Subset simulation-based reliability analysis of the corroding natural gas pipeline," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    7. Dhulipala, Somayajulu L.N. & Shields, Michael D. & Chakroborty, Promit & Jiang, Wen & Spencer, Benjamin W. & Hales, Jason D. & Labouré, Vincent M. & Prince, Zachary M. & Bolisetti, Chandrakanth & Che, 2022. "Reliability estimation of an advanced nuclear fuel using coupled active learning, multifidelity modeling, and subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    8. Kim, Man Cheol, 2022. "Systematic approach and mathematical development for conditional core damage probabilities under station blackout of a nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    9. Li, Chao & Diao, Yucheng & Li, Hong-Nan & Pan, Haiyang & Ma, Ruisheng & Han, Qiang & Xing, Yihan, 2023. "Seismic performance assessment of a sea-crossing cable-stayed bridge system considering soil spatial variability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    10. Liu, Hanchen & Wang, Chong & Ju, Ping & Li, Hongyu, 2022. "A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    11. Jayaraman, Deepan & Ramu, Palaniappan, 2023. "L-moments and Bayesian inference for probabilistic risk assessment with scarce samples that include extremes," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    12. Yoon, Jae Young & Kim, Dong-San, 2022. "Estimating the adverse effects of inter-unit radioactive release on operator actions at a multi-unit site," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    13. Van Huynh, Thu & Tangaramvong, Sawekchai & Do, Bach & Gao, Wei & Limkatanyu, Suchart, 2023. "Sequential most probable point update combining Gaussian process and comprehensive learning PSO for structural reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    14. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2021. "A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    15. Sonal, & Ghosh, Debomita, 2022. "Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    16. Kwag, Shinyoung & Choi, Eujeong & Eem, Seunghyun & Ha, Jeong-Gon & Hahm, Daegi, 2021. "Toward improvement of sampling-based seismic probabilistic safety assessment method for nuclear facilities using composite distribution and adaptive discretization," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    17. Xie, Haipeng & Tang, Lingfeng & Zhu, Hao & Cheng, Xiaofeng & Bie, Zhaohong, 2023. "Robustness assessment and enhancement of deep reinforcement learning-enabled load restoration for distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    18. Lilli, Giordano & Sanavia, Matteo & Oboe, Roberto & Vianello, Chiara & Manzolaro, Mattia & De Ruvo, Pasquale Luca & Andrighetto, Alberto, 2024. "A semi-quantitative risk assessment of remote handling operations on the SPES Front-End based on HAZOP-LOPA," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    19. Li, Zhengbing & Feng, Huixia & Liang, Yongtu & Xu, Ning & Nie, Siming & Zhang, Haoran, 2019. "A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo," International Journal of Critical Infrastructure Protection, Elsevier, vol. 27(C).
    20. Jang, Seunghyun & Kim, Yongjin & Jae, Moosung, 2021. "A site risk assessment for internal events: A case study," Reliability Engineering and System Safety, Elsevier, vol. 215(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:235:y:2023:i:c:s0951832023001321. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.