Risk assessment of interstate pipelines using a fuzzy-clustering approach

Abstract

Interstate pipelines are the most efficient and feasible mean of transport for crude oil and gas within boarders. Assessing the risks of these pipelines is challenging despite the evolution of computational fuzzy inference systems (FIS). The computational intricacy increases with the dimensions of the system variables especially in the typical Takagi–Sugeno (T–S) fuzzy-model. Typically, the number of rules rises exponentially as the number of system variables increases and hence, it is unfeasible to specify the rules entirely for pipeline risk assessments. This work proposes the significance of indexing pipeline risk assessment approach that is integrated with subtractive clustering fuzzy logic to address the uncertainty of the real-world circumstances. Hypothetical data is used to setup the subtractive clustering fuzzy-model using the fundamental rules and scores of the pipeline risk assessment indexing method. An interstate crude-oil pipeline in Egypt is used as a case study to demonstrate the proposed approach.

Safety, health, and environmental risk assessment of the aromatic outlet of Imam Khomeini Petrochemical Company using LOPA and fuzzy-LOPA and pollutants and control actions using the Bow-tie method

“…Fuzzy logic is integrated to deal with the uncertainty of real-world conditions ( 15–17 ). Due to the increasing possibility of irrecoverable environmental, health, and safety risks in petrochemical industries, such research seems to be necessary ( 18 ). Several studies have been conducted in the field of hazard identification, but so far, no study has been conducted in the field of environmental, health and safety risk assessment of equipment in the petrochemical industries using the Fuzzy LOPA method.…”