Quantitative assessment of safety barrier performance in the prevention of domino scenarios triggered by fire

Landucci, Gabriele; Argenti, Francesca; Tugnoli, Alessandro; Cozzani, Valerio

doi:10.1016/j.ress.2015.03.023

Cited by 152 publications

(132 citation statements)

References 33 publications

Supporting

Mentioning

124

Contrasting

Order By: Relevance

“…Nevertheless, recent studies dedicated to the determination of escalation probabilities (Cozzani and Salzano, 2004;Cozzani et al, 2005Cozzani et al, , 2006Landucci et al, 2009Landucci et al, , 2015 along with the development of advanced mathematical and probabilistic methods such as Monte Carlo simulation (Abdolhamidzadeh et al, 2010), Bayesian networks (Khakzad et al, 2013;Khakzad, 2015;Khakzad and Reniers, 2015a), graph theory (Khakzad and Reniers, 2015b), and event sequence diagrams Due to the importance of domino effects from either a safety or security perspective, in the present study a bibliometric analysis of attempts devoted to the description, management, modeling and risk assessment of domino effects in the chemical industry over the past decades was carried out.…”

Section: Introductionmentioning

confidence: 99%

A bibliometric analysis of peer-reviewed publications on domino effects in the process industry

Reniers

Cozzani

et al. 2017

Journal of Loss Prevention in the Process Industries

Self Cite

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

A bibliometric analysis of peer-reviewed publications on domino effects in the process industry

Reniers

Cozzani

et al. 2017

Journal of Loss Prevention in the Process Industries

Self Cite

View full text Add to dashboard Cite

“…The above‐mentioned materials can be considered as high‐performance protection, since they are specifically designed to withstand severe fire conditions and therefore able to protect process equipment for about 120 min in an engulfing hydrocarbon pool fire …”

Section: Methodsmentioning

confidence: 99%

“…Aside from inherently safer design, engineering active and passive safety barriers—also known as add‐on safety barriers—are of utmost importance in the prevention, control, and mitigation of domino effects. Landucci et al . developed a methodology based on event‐tree technique to investigate the impact of the availability and effectiveness of add‐on safety barriers on domino effect propagation .…”

Section: Introductionmentioning

confidence: 99%

Application of Graph Theory to Cost‐Effective Fire Protection of Chemical Plants During Domino Effects

2016

Self Cite

View full text Add to dashboard Cite

In the present study, we have introduced a methodology based on graph theory and multicriteria decision analysis for cost‐effective fire protection of chemical plants subject to fire‐induced domino effects. By modeling domino effects in chemical plants as a directed graph, the graph centrality measures such as out‐closeness and betweenness scores can be used to identify the installations playing a key role in initiating and propagating potential domino effects. It is demonstrated that active fire protection of installations with the highest out‐closeness score and passive fire protection of installations with the highest betweenness score are the most effective strategies for reducing the vulnerability of chemical plants to fire‐induced domino effects. We have employed a dynamic graph analysis to investigate the impact of both the availability and the degradation of fire protection measures over time on the vulnerability of chemical plants. The results obtained from the graph analysis can further be prioritized using multicriteria decision analysis techniques such as the method of reference point to find the most cost‐effective fire protection strategy.

show abstract

“…By multiplying L and S, a crisp risk priority (CRP) R is calculated with Equation (17). Through the fuzzy product of L and S, the fuzzy risk priority (FRP) R is calculated based on the FBTM with Equation (18) [26]. Finally, the quantitative risk assessment results were obtained by using the Centroid Method to create the defuzzification.…”

Section: Study Of a Fuzzy Bow-tie Modelmentioning

confidence: 99%

A Quantitative Risk Analysis Method for the High Hazard Mechanical System in Petroleum and Petrochemical Industry

et al. 2017

View full text Add to dashboard Cite

Abstract:The high hazard mechanical system (HHMS) has three characteristics in the petroleum and petrochemical industry (PPI): high risk, high cost, and high technology requirements. For a HHMS, part, component, and subsystem failures will result in varying degrees and various types of risk consequences, including unexpected downtime, production losses, economic costs, safety accidents, and environmental pollution. Thus, obtaining the quantitative risk level and distribution in a HHMS to control major risk accidents and ensure safe production is of vital importance. However, the structure of the HHMS is more complex than some other systems, making the quantitative risk analysis process more difficult. Additionally, a variety of uncertain risk data hinder the realization of quantitative risk analysis. A few quantitative risk analysis techniques and studies for HHMS exist, especially in the PPI. Therefore, a study on the quantitative risk analysis method for HHMS was completed to obtain the risk level and distribution of high-risk objects. Firstly, Fuzzy Set Theory (FST) was applied to address the uncertain risk data for the occurrence probability (OP) and consequence severity (CS) in the risk analysis process. Secondly, a fuzzy fault tree analysis (FFTA) and a fuzzy event tree analysis (FETA) were used to achieve quantitative risk analysis and calculation. Thirdly, a fuzzy bow-tie model (FBTM) was established to obtain a quantitative risk assessment result according to the analysis results of the FFTA and FETA. Finally, the feasibility and practicability of the method were verified with a case study on the quantitative risk analysis of one reciprocating pump system (RPS). The quantitative risk analysis method for HHMS can provide more accurate and scientific data support for the development of Asset Integrity Management (AIM) systems in the PPI.

show abstract

Quantitative assessment of safety barrier performance in the prevention of domino scenarios triggered by fire

Cited by 152 publications

References 33 publications

A bibliometric analysis of peer-reviewed publications on domino effects in the process industry

A bibliometric analysis of peer-reviewed publications on domino effects in the process industry

Application of Graph Theory to Cost‐Effective Fire Protection of Chemical Plants During Domino Effects

A Quantitative Risk Analysis Method for the High Hazard Mechanical System in Petroleum and Petrochemical Industry

Contact Info

Product

Resources

About