IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v222y2022ics0951832022000722.html
   My bibliography  Save this article

A STAMP-based approach to quantitative resilience assessment of chemical process systems

Author

Listed:
  • Sun, Hao
  • Wang, Haiqing
  • Yang, Ming
  • Reniers, Genserik

Abstract

Chemical process systems (CPSs) involve complex dynamic processes. Besides, the emergent and uncertain hazards and disruptions cannot be identified entirely and prevented by conventional methods. In those situations, resilience for CPSs plays an essential role in absorbing, adapting to disruptions, and restoring from damages. Systemic modeling plays a vital role in assessing resilience. A system-based analysis model, system-theoretic accident model, and process (STAMP) can provide a robust framework. This paper develops a comprehensive methodology to systematically model and assess system resilience. The STAMP is employed to model and analyze the system safety of a process system. A new method of dynamic resilience assessment is then proposed to quantify the resilience of the system. The proposed method is applied to the diesel oil hydrogenation system. The results show that it quantifies the resilience of complex process systems considering human and organizational factors in a dynamic manner.

Suggested Citation

  • Sun, Hao & Wang, Haiqing & Yang, Ming & Reniers, Genserik, 2022. "A STAMP-based approach to quantitative resilience assessment of chemical process systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
  • Handle: RePEc:eee:reensy:v:222:y:2022:i:c:s0951832022000722
    DOI: 10.1016/j.ress.2022.108397
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832022000722
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2022.108397?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. Liu, Xing & Fang, Yi-Ping & Zio, Enrico, 2021. "A Hierarchical Resilience Enhancement Framework for Interdependent Critical Infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    2. Cai, Baoping & Xie, Min & Liu, Yonghong & Liu, Yiliu & Feng, Qiang, 2018. "Availability-based engineering resilience metric and its corresponding evaluation methodology," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 216-224.
    3. Zhang, Yanping & Cai, Baoping & Liu, Yiliu & Jiang, Qiangqiang & Li, Wenchao & Feng, Qiang & Liu, Yonghong & Liu, Guijie, 2021. "Resilience assessment approach of mechanical structure combining finite element models and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Leveson, Nancy, 2015. "A systems approach to risk management through leading safety indicators," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 17-34.
    6. Filippini, Roberto & Silva, Andrés, 2014. "A modeling framework for the resilience analysis of networked systems-of-systems based on functional dependencies," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 82-91.
    7. 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).
    8. Chen, Chao & Yang, Ming & Reniers, Genserik, 2021. "A dynamic stochastic methodology for quantifying HAZMAT storage resilience," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    9. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    10. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    11. Hu, Jinqiu & Khan, Faisal & Zhang, Laibin, 2021. "Dynamic resilience assessment of the Marine LNG offloading system," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    12. Himoto, Keisuke & Suzuki, Keichi, 2021. "Computational framework for assessing the fire resilience of buildings using the multi-layer zone model," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    13. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    14. Yang, Bofan & Zhang, Lin & Zhang, Bo & Wang, Wenfeng & Zhang, Minglinag, 2021. "Resilience Metric of Equipment System: Theory, Measurement and Sensitivity Analysis," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Zinetullina, Altyngul & Yang, Ming & Khakzad, Nima & Golman, Boris & Li, Xinhong, 2021. "Quantitative resilience assessment of chemical process systems using functional resonance analysis method and Dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 205(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. HIMOTO, Keisuke & SAWADA, Yuto & OHMIYA, Yoshifumi, 2024. "Quantifying fire resilience of buildings considering the impact of water damage accompanied by fire extinguishment," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. Niemi, Arto & Skobiej, Bartosz & Kulev, Nikolai & Sill Torres, Frank, 2024. "Modeling offshore wind farm disturbances and maintenance service responses within the scope of resilience," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    3. Zhi, Keke & Wang, Bohong & Guo, Lianghui & Chen, Yujie & Li, Wei & Ocłoń, Paweł & Wang, Jin & Chen, Yuping & Tao, Hengcong & Li, Xinze & Varbanov, Petar Sabev, 2024. "Graphical pinch analysis-based method for heat exchanger networks retrofit of a residuum hydrogenation process," Energy, Elsevier, vol. 299(C).
    4. Antonello, Federico & Buongiorno, Jacopo & Zio, Enrico, 2022. "A methodology to perform dynamic risk assessment using system theory and modeling and simulation: Application to nuclear batteries," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    5. 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).
    6. Zhou, Zhengshu & Matsubara, Yutaka & Takada, Hiroaki, 2023. "Resilience analysis and design for mobility-as-a-service based on enterprise architecture modeling," Reliability Engineering and System Safety, Elsevier, vol. 229(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. Wu, Jingyi & Yu, Yang & Yu, Jianxing & Chang, Xueying & Xu, Lixin & Zhang, Wenhao, 2023. "A Markov resilience assessment framework for tension leg platform under mooring failure," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    2. Ramadhani, Adhitya & Khan, Faisal & Colbourne, Bruce & Ahmed, Salim & Taleb-Berrouane, Mohammed, 2022. "Resilience assessment of offshore structures subjected to ice load considering complex dependencies," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Sun, Hao & Yang, Ming & Wang, Haiqing, 2022. "A virtual experiment for measuring system resilience: A case of chemical process systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    4. Jiang, Qiangqiang & Cai, Baoping & Zhang, Yanping & Xie, Min & Liu, Cuiwei, 2023. "Resilience assessment methodology of natural gas network system under random leakage," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    5. Yin, Jiateng & Ren, Xianliang & Liu, Ronghui & Tang, Tao & Su, Shuai, 2022. "Quantitative analysis for resilience-based urban rail systems: A hybrid knowledge-based and data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    6. Yu, Yaocheng & Shuai, Bin & Huang, Wencheng, 2024. "Resilience evaluation of train control on-board system based on multi-dimensional continuous-time Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    7. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    8. Caetano, Henrique O. & N., Luiz Desuó & Fogliatto, Matheus S.S. & Maciel, Carlos D., 2024. "Resilience assessment of critical infrastructures using dynamic Bayesian networks and evidence propagation," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    9. Wei, Yian & Cheng, Yao & Liao, Haitao, 2024. "Optimal resilience-based restoration of a system subject to recurrent dependent hazards," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    10. Sun, Hao & Yang, Ming & Zio, Enrico & Li, Xinhong & Lin, Xiaofei & Huang, Xinjie & Wu, Qun, 2024. "A simulation-based approach for resilience assessment of process system: A case of LNG terminal system," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    11. Sun, Qin & Li, Hongxu & Wang, Yuzhi & Zhang, Yingchao, 2022. "Multi-swarm-based cooperative reconfiguration model for resilient unmanned weapon system-of-systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    12. HIMOTO, Keisuke & SAWADA, Yuto & OHMIYA, Yoshifumi, 2024. "Quantifying fire resilience of buildings considering the impact of water damage accompanied by fire extinguishment," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    13. Orlando Durán & Belén Vergara, 2022. "Maintenance Strategies Definition Based on Systemic Resilience Assessment: A Fuzzy Approach," Mathematics, MDPI, vol. 10(10), pages 1-16, May.
    14. Liu, Jin & Zhai, Changhai & Yu, Peng, 2022. "A Probabilistic Framework to Evaluate Seismic Resilience of Hospital Buildings Using Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    15. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    16. Sun, Hao & Yang, Ming & Wang, Haiqing, 2024. "An integrated approach to quantitative resilience assessment in process systems," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    17. Bellè, Andrea & Abdin, Adam F. & Fang, Yi-Ping & Zeng, Zhiguo & Barros, Anne, 2023. "A resilience-based framework for the optimal coupling of interdependent critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    18. Tan, Xinxin & Xiao, Shenbin & Yang, Yu & Khakzad, Nima & Reniers, Genserik & Chen, Chao, 2024. "An agent-based resilience model of oil tank farms exposed to earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    19. Wang, Nanxi & Yuen, Kum Fai, 2022. "Resilience assessment of waterway transportation systems: Combining system performance and recovery cost," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    20. Zhang, Yanping & Cai, Baoping & Liu, Yiliu & Jiang, Qiangqiang & Li, Wenchao & Feng, Qiang & Liu, Yonghong & Liu, Guijie, 2021. "Resilience assessment approach of mechanical structure combining finite element models and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 216(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:222:y:2022:i:c:s0951832022000722. 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.