Network theory-based accident scenario analysis for hazardous material transport: A case study of liquefied petroleum gas transport in Japan. (November 2020)

• Record Type: Journal Article
• Authors: Noguchi, H.; Hienuki, S.; Fuse, M.
• Is Part Of: Reliability engineering & system safety. Volume 203(2020)
• Publication Date: 2020-11
• Subjects: Risk assessment -- Risk management -- Complex accident process -- Accident network -- Transport environmental factor; 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.2020.107107
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: Proposed new accident scenario analysis of hazardous materials transport by using network theory. Proposed technique applied to a case of liquid petroleum gas (LPG) transport by road in japan. Identified scenarios can help understand complex accident process in hazardous materials transport. Proposed approach could accelerate risk assessment for hazardous materials transport. ABSTRACT: To analyze an accident scenario involving the transport of hazardous material (HAZMAT), a complex accident process must be completely described; however, existing analytical approaches, which are influenced by the arbitrariness of a given analyst, may not cover the entire process. Thus, the aim of this study is to develop a new approach for analyzing accident scenarios associated with HAZMAT transport, using network theory as a key to illustrate the complex accident process. In the developed approach, accident scenarios are sampled from the accident processes by fusing the HAZMAT transport accident network and transport environmental factors, based on accident data. The proposed approach was applied to a case of Liquefied petroleum gas (LPG) transport by road in Japan. The case study identified 68, 874 scenarios and classified the identified scenarios into three types of risk categories: 80 high-risk, 9, 112 medium-risk, and 59, 682 low-risk scenarios. It was observed that the scenarios identified could successfully help understand the complex accident processes in HAZMAT transport and incorporate the safety measures through the accident network. The proposed approach for accident scenario analysis can accelerate the risk assessment of HAZMAT transport and help advance risk assessment to risk management.