Assessment of domino effect: State of the art and research Needs

Necci, Amos; Cozzani, Valerio; Spadoni, Gigliola; Khan, Faisal

doi:10.1016/j.ress.2015.05.017

Cited by 119 publications

(54 citation statements)

References 100 publications

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“…The oil and gas industries operate a great and complex variety of processes and plants. Where a major accident involving fires, boiling liquid expansion vapour explosions (BLEVEs), vapor cloud explosions (VCEs) and domino effects have occurred, with serious damage on human beings, industrial sites, environment, and economy.…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis by mapping probabilistic importance factors into bayesian belief networks for making decision in water deluge system

Guetarni

Aissani

Châtelet

et al. 2018

Process Safety Progress

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Liquid petroleum gas (LPG) is one area where catastrophic release scenarios have occurred. For this reason, preventive, and protective barriers have to be installed in order to reduce the occurrence and the severity of these scenarios. This article addresses an analysis of deluge system barrier and proposes a making decision process to ensure a high level of reliability, availability, maintainability, and safety (RAMS) using a robust Reliability Analysis with conditional probabilities. To achieve this RAMS target, a methodology for converting fault tree analysis (FTA) in continuous time using Monte Carlo (MC) simulation to Bayesian belief network (BBN) is developed. The probabilistic importance factors (PIFs) for critical components ranking and decision making are also mapped using BBN inferences in Water Deluge Systems (WDS) with an optimization aim using redundancy or maintenance tasks. This analysis illustrates the helpfulness of mapping PIFs into BBN for making a decision in any critical technological infrastructures.

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Section: Introductionmentioning

confidence: 99%

Reliability analysis by mapping probabilistic importance factors into bayesian belief networks for making decision in water deluge system

Guetarni

Aissani

Châtelet

et al. 2018

Process Safety Progress

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“…Marhavilas et al have published a review of risk analysis and assessment, but generically referred to different work sites (Marhavilas et al, 2011). More recently, Reniers and Cozzani (2013) and Necci et al (2015) presented reviews on quantitative risk assessment for the chemical process industry, but specifically concerning domino accidents.…”

Section: Introductionmentioning

confidence: 99%

Towards dynamic risk analysis: A review of the risk assessment approach and its limitations in the chemical process industry

et al. 2016

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“…Domino effects have been responsible for some catastrophic accidents that occurred in the chemical and petrochemical industries . Although there are multiple definitions of domino effects in the chemical and process industries, this type of accident features a generic schematization with the following elements: (1) there is a “primary event,” initiating the domino effect; (2) there is an escalation vector (e.g., fire impingement, heat radiation, explosion overpressure, etc. ), facilitating the propagation of the domino effect; (3) one or more secondary accident events, involving one or more target equipment .…”

Section: Introductionmentioning

confidence: 99%

DAMS: A Model to Assess Domino Effects by Using Agent‐Based Modeling and Simulation

et al. 2017

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Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases.

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Assessment of domino effect: State of the art and research Needs

Cited by 119 publications

References 100 publications

Reliability analysis by mapping probabilistic importance factors into bayesian belief networks for making decision in water deluge system

Reliability analysis by mapping probabilistic importance factors into bayesian belief networks for making decision in water deluge system

Towards dynamic risk analysis: A review of the risk assessment approach and its limitations in the chemical process industry

DAMS: A Model to Assess Domino Effects by Using Agent‐Based Modeling and Simulation

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