A methodology to perform dynamic risk assessment using system theory and modeling and simulation: Application to nuclear batteries

Federico Antonello, Jacopo Buongiorno and Enrico Zio

Reliability Engineering and System Safety, 2022, vol. 228, issue C

Abstract: Accidents may occur as a result of complex dynamic processes in interconnected socio-technical systems. Such accidents cannot be explained solely in terms of static chains of failures. Therefore, the traditional Probabilistic Risk Assessment (PRA) framework, which stands on the consideration that accidents are caused by direct failures or chains of events, is not apt to describe the dynamic behavior of the relevant Systems, Structures and Components (SSCs) and assess the risk. This work proposes a novel framework that embeds (i) System-Theoretic Accident Model and Processes (STAMP) principles to guide a qualitative exploration of the SSC threats and hazards, (ii) Modeling and Simulation (M&S) to investigate the SSC dynamic behavior during accidental scenarios, and (iii) the Goal-Tree Success-Tree Master Logic Diagram (GTST-MLD) framework to assess risk quantitatively. The integration of STAMP, M&S and GTST-MLD allows a systematic analysis to provide risk insights, with due account to the SSC dependencies and interactions, and enables a dynamic assessment of the risk profile.

Keywords: Dynamic risk assessment; STAMP; STPA; Goal tree success tree - master logic diagram; Modeling and Simulation; Nuclear battery; Nuclear micro reactors; Systems structures and components (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832022003921
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:228:y:2022:i:c:s0951832022003921

DOI: 10.1016/j.ress.2022.108769

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().