Application of domino effect quantitative risk assessment to an extended industrial area

Antonioni, Giacomo; Spadoni, Gigliola; Cozzani, Valerio

doi:10.1016/j.jlp.2009.02.012

Cited by 147 publications

(70 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The maxima of temperature at each height were 2191. 16 The area of temperature distribution at 1 m high was the widest, showing that the facilities and devices in this region are most affected by heat. In addition, centered on the melting temperature of iron, 1811 K, the temperature distribution form and size were minutely segmented, as shown in Figures 9 and 10.…”

Section: Temperaturementioning

confidence: 95%

Numerical computation of a large‐scale jet fire of high‐pressure hydrogen in process plant

Jang

Jung

2016

Energy Science & Engineering

View full text Add to dashboard Cite

Due to numerous hazardous chemicals to handle, the process plant industry has a higher risk of fire, explosion, and toxic release than other industries. Reviewing the accidents at process plants in the past, it is clear that fire accidents occur with the highest frequency, leading this study to consider accidental fire scenarios at process plants. For the scenario of an incident, a jet fire involving a massive amount of hydrogen gas to be processed or delivered at the process plant has been selected. The analysis of incident outcome resulting from the hydrogen jet fire has been implemented through the computational fluid dynamics simulation methodology Kameleon FireEx. Based on the outcome of this simulation, the consequences of a jet fire with high temperature and heat radiation are analyzed and evaluated. In addition, the results from Phast ver. 7.11 simulation for the same scenario are presented for comparison and further validation. 407

show abstract

Section: Temperaturementioning

confidence: 95%

Numerical computation of a large‐scale jet fire of high‐pressure hydrogen in process plant

Jang

Jung

2016

Energy Science & Engineering

View full text Add to dashboard Cite

show abstract

“…Schiller et al [117] recently published a review of such social-material network studies. Of particular interest to a retrofitting framework is vulnerability issues which may result from developing interdependent networks, similar to the disaster related domino effect [118] physical proximately already entails [119]. Vulnerability and resilience has been studied in IS networks using network analysis and cascading failure models to understand inter-company impact [120][121][122][123].…”

Section: Multiple Type Exchangesmentioning

confidence: 99%

Quantitative tools for cultivating symbiosis in industrial parks; a literature review

2015

View full text Add to dashboard Cite

“…On the basis of Cozzani et al [44] , Antonioni et al [45] developed the Aripar-GIS software for risk recomposition. The results evidenced that quantitative risk assessment of escalation hazard was fundamental important for identifying critical equipment and addressing prevention and protection actions.…”

Section: Quantitative Risk Assessment Of Domino Accidentsmentioning

confidence: 99%

Domino Effect Analysis, Assessment and Prevention in Process Industries

Yang

Cheng

2015

Journal of Systems Science and Information

View full text Add to dashboard Cite

Domino effect is a fairly common phenomenon in process industry accidents, which makes many process industry accidents serious and the consequent losses enhanced. Domino effect of the major accidents in chemical cluster is emphasized. Many researchers have studied domino effect in chemical clusters from different perspectives. In the review, we summarize the research from three aspects: The statistical analysis of domino accidents in chemical process industry, the evaluation of domino accidents and the prevention of domino accidents in chemical clusters by game theory. From the analysis, we can find the characteristic of domino accidents such as the time and the location, the origin and causes of domino accidents. The methods of assessing domino effects such as quantitative risk assessment (QRA), Bayesian networks (BN) and Monte Carlo simulation (MCS) are analyzed. The prevention of domino accidents in chemical clusters using game theory is seldom, and there is still much space for improvement in enterprises' efforts to prevent risk of domino accidents.

show abstract

Application of domino effect quantitative risk assessment to an extended industrial area

Cited by 147 publications

References 23 publications

Numerical computation of a large‐scale jet fire of high‐pressure hydrogen in process plant

Numerical computation of a large‐scale jet fire of high‐pressure hydrogen in process plant

Quantitative tools for cultivating symbiosis in industrial parks; a literature review

Domino Effect Analysis, Assessment and Prevention in Process Industries

Contact Info

Product

Resources

About