Abstract
The availability of hazard identification methodologies based on early warnings is a crucial factor in the
prevention of major accidents. Accidents like Seveso, Buncefield and Toulouse, where severe
consequences occurred seemingly unexpected by the plant safety management, have made it clear that a
comprehensive and complete identification and assessment of potential hazards in the process industry
are of primary importance for the prevention and the mitigation of accident scenarios. The accident
scenarios deviating from normal expectations of unwanted events or worst-case reference scenarios
captured by common HAZard IDentification (HAZID) techniques are usually defined as “atypical”. The
main issue posed by the prevention of atypical scenarios is the availability of techniques able to identify
them within a routine HAZID process, capturing evidence of new hazards and learning from ‘early
warnings’ as soon as they come to light. For this reason a specific method named Dynamic Procedure for
Atypical Scenarios Identification (DyPASI) was developed. The method was conceived as a development
of conventional bow-tie identification techniques. DyPASI is a method for the continuous systematization of
information from early signals of risk related to past events. It dynamically integrates in the bow-ties the
results of information retrieval activities. DyPASI features as a tool to support emerging risk management
process, having the potentiality to contribute to an integrated approach aimed at breaking “vicious circles”,
helping to trigger a gradual process of identification and assimilation of previously unrecognized atypical
scenarios. The current contribution presents the technique and demonstrates the application by a selected
case-study of practical application (Toulouse AZF accident, Buncefield oil depot accident, LNG
regasification terminal, CCS plant).
prevention of major accidents. Accidents like Seveso, Buncefield and Toulouse, where severe
consequences occurred seemingly unexpected by the plant safety management, have made it clear that a
comprehensive and complete identification and assessment of potential hazards in the process industry
are of primary importance for the prevention and the mitigation of accident scenarios. The accident
scenarios deviating from normal expectations of unwanted events or worst-case reference scenarios
captured by common HAZard IDentification (HAZID) techniques are usually defined as “atypical”. The
main issue posed by the prevention of atypical scenarios is the availability of techniques able to identify
them within a routine HAZID process, capturing evidence of new hazards and learning from ‘early
warnings’ as soon as they come to light. For this reason a specific method named Dynamic Procedure for
Atypical Scenarios Identification (DyPASI) was developed. The method was conceived as a development
of conventional bow-tie identification techniques. DyPASI is a method for the continuous systematization of
information from early signals of risk related to past events. It dynamically integrates in the bow-ties the
results of information retrieval activities. DyPASI features as a tool to support emerging risk management
process, having the potentiality to contribute to an integrated approach aimed at breaking “vicious circles”,
helping to trigger a gradual process of identification and assimilation of previously unrecognized atypical
scenarios. The current contribution presents the technique and demonstrates the application by a selected
case-study of practical application (Toulouse AZF accident, Buncefield oil depot accident, LNG
regasification terminal, CCS plant).