Hazard identification for innovative LNG regasification technologies. (May 2015)

• Record Type: Journal Article
• Authors: Paltrinieri, Nicola; Tugnoli, Alessandro; Cozzani, Valerio
• Is Part Of: Reliability engineering & system safety. Volume 137(2015:May)
• Page Start: 18
• Page End: 28
• Publication Date: 2015-05
• Subjects: Hazard identification -- Atypical scenarios -- Early warnings -- LNG regasification; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2014.12.006
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: Emerging risks may arise from process intensification and new scenarios due to the innovative technologies and higher potentialities of new LNG regasification facilities. In the conventional hazard identification process it is difficult to include new scenarios related to innovative technologies or facilities, for which limited or no operational experience is available. In the present study, a new technique for HAZard IDentification (HAZID), named Dynamic Procedure for Atypical Scenarios Identification (DyPASI), was applied to identify atypical accident scenarios in LNG terminals. The technique aims to make easier and more systematic the process of learning from early warnings and identify atypical accident scenarios otherwise disregarded by common HAZID techniques. The comparison with a survey of the accident scenarios typically considered in available Environmental Impact Assessment (EIA) studies evidences that DyPASI is a valuable tool to obtain a complete and updated overview of potential hazards in particular for new or innovative technologies, where limited operational experience is available. Highlights: New accident scenarios related to innovative technologies are difficult to identify. DyPASI allowed identifying LNG-specific scenarios disregarded by other techniques. The analysis was based on the systematization of data from past events and studies. These scenarios were partially overlooked by the Environmental Impact Assessments. Emerging technologies may be inclined to atypical accident scenarios.