An integrated resilience assessment methodology for emergency response systems based on multi-stage STAMP and dynamic Bayesian networks

Xu An, Zhiming Yin, Qi Tong, Yiping Fang, Ming Yang, Qiaoqiao Yang, Huixing Meng*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
19 Downloads (Pure)

Abstract

The interactions of external disruptions and technical-human-organizational factors in emergency operations are usually observed. Resilience assessment of emergency systems can improve emergency response capability and system functional recovery. The increasing complexity and coupling of factors in emergency response systems need to be investigated from a system resilience perspective. In this paper, we propose to integrate a multi-stage System-Theoretic Accident Model and Processes (STAMP) with a dynamic Bayesian network (DBN) for the resilience assessment of emergency response systems. In the proposed methodology, emergency response systems are viewed as multi-step emergency operations for STAMP to analyze the hierarchical control and feedback structures. The output of multi-stage STAMP in controllers, actuators, sensors, and controlled processes is applied to develop a DBN for resilience assessment. For known external shocks (e.g., natural disasters), the effects of external shocks on the system are decomposed into subsystems or components. System degradation and recovery models are established. Regarding unknown external disruption (e.g., unforeseen failure modes), degeneration and recovery are temporally integrated into the analysis of system functionality. System performance is evaluated through the combination of socio-technical factors and external disasters. Eventually, the resilience of emergency response systems is obtained from the performance curves. The results demonstrate that the proposed model can evaluate system resilience after the system suffers from external disasters.
Original languageEnglish
Article number109445
Number of pages21
JournalReliability Engineering and System Safety
Volume238
DOIs
Publication statusPublished - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Dynamic Bayesian network
  • Emergency operations
  • Multi-stage STAMP
  • Resilience assessment

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