A quantified risk analysis for oil spill during crude oil loading operation on tanker ship under improved Z-number based Bayesian Network approach


Sezer S. I., Elidolu G., Akyüz E., Arslan Ö.

Marine Pollution Bulletin, vol.197, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 197
  • Publication Date: 2023
  • Doi Number: 10.1016/j.marpolbul.2023.115796
  • Journal Name: Marine Pollution Bulletin
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, BIOSIS, CAB Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, Environment Index, Geobase, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Bayesian network, Improved Z-numbers, Loss prevention, Marine environment, Oil pollution risk
  • Istanbul Technical University Affiliated: Yes

Abstract

Crude oil cargo operation poses significant oil spill risk although utmost care is exercised by ship and shore crew. This paper focuses on quantitative risk analysis for oil spill incidents in crude oil tanker ships to enhance safety at the operational level and prevent potential pollution. To achieve this purpose, the Bayesian network (BN) is used under the improved Z-numbers theory. While BN provides a powerful tool based on cause and effect network between the variables, the improved Z-numbers are capable of handling uncertainty and improving the reliability of qualitative expert judgments. The findings show that the occurrence probability of oil spill risk in crude oil tanker ships is found 2.90E−02 during the cargo loading operation. The findings of the research are expected to contribute ship crew, safety inspectors, ship owners, HSEQ managers, and terminal managers in risk management decision-making, improving operational safety, taking control actions, and minimizing oil spills.