Risk analysis using automatically synthesized robust accident scenarios and consequence assessment for chemical processes: Process partition and consequence analysis approach

Abstract

Consequence analysis and risk assessment are very important in chemical process industries because of the potential risk of hazardous materials. In this paper, we introduce a new system for consequence analysis and risk management (CARM) and propose a new strategy for producing robust accident scenarios in quantitative risk assessment. The suggested synthesis method analyzes process elements and selects and generates robust accident scenarios that simulate the most possible worst-case accident that should be foremost considered. The scenario-reasoning scheme consists of three types of knowledge base (equipment property, material property, and process unit knowledge) and four reasoning algorithms (macro decomposition, equipment screening, equipment behavior analysis, and accident scenarios reasoning). The synthesized result of the analysis enhances the reliability of the generated accident scenario and prevents the risks from being overestimated. The obtained result, as easily confirmed by using CARM, should be more helpful in proper process design and emergency planning.