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Quantitative assessment of domino and NaTech scenarios in complex industrial areas
- Publication Year :
- 2014
-
Abstract
- Since the late 80s the application of quantitative risk assessment to the issue of land-use planning with respect to major accident hazards emerged as a topic to be addressed within the safety assessment of chemical and process plants. However, in the case of industrial clusters or complex industrial areas specific methodologies are needed to deal with high-impact low-probability (HILP) events. In the present study, innovative methodologies developed for the quantitative assessment of risk due to domino and NaTech scenarios are presented. In recent years a set of models for the calculation of equipment damage probability were developed. A specific effort was dedicated to the improvement of models for the calculation of equipment damage probability in these accident scenarios. In the present study, the application of these models to case-studies was analyzed. The results of the improved models obtained for NaTech quantitative assessment were compared to previous results in the literature. A specific innovative approach was developed to multi-level quantitative assessment of domino scenarios, and its potential was analyzed. The results were examined also evidencing the role and the progress with respect to the pioneering work started on these topics by Franco Foraboschi.
- Subjects :
- Engineering
Operations research
business.industry
Process (engineering)
General Chemical Engineering
Energy Engineering and Power Technology
Quantitative risk assessment
Domino effect
Management Science and Operations Research
Industrial and Manufacturing Engineering
Domino
NaTech
Major accident hazard
Land-use planning
Work (electrical)
Risk analysis (engineering)
Control and Systems Engineering
Quantitative assessment
Safety, Risk, Reliability and Quality
business
Risk assessment
Food Science
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....90174bca50d99fc071fa1baf6358baf2