Dypasi Methodology: from Information Retrieval to Integration of Hazid Process

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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).