An integrated risk assessment methodology based on fuzzy TOPSIS and cloud inference for urban polyethylene gas pipelines. (20th November 2022)

• Record Type: Journal Article
• Authors: Liang, Xiaobin; Ma, Weifeng; Ren, Junjie; Dang, Wei; Wang, Ke; Nie, Hailiang; Cao, Jun; Yao, Tian
• Is Part Of: Journal of cleaner production. Volume 376(2022)
• Publication Date: 2022-11-20
• Subjects: Cloud inference -- Structural entropy method -- Risk assessment -- Fuzzy TOPSIS -- PE gas Pipelines; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.134332
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Due to the superior performance of polyethylene (PE) gas pipes, an increasing number of PE pipelines are being used in urban areas. However, PE gas pipelines are basically located in densely populated areas with high consequences. Once a leak occurs, combustion and explosion accidents can easily happen causing a major threat to human life and property. Furthermore, the assessment results of the common risk assessment methods often have great uncertainty and deviation. It is difficult to accurately identify the main indicators that need priority management. To address these problems, this paper proposes a novel methodology by integrating a fuzzy TOPSIS model and cloud inference for conducting risk assessments of urban PE gas pipelines. The developed methodology is composed of two branches. In the first branch, a rapid risk assessment model for PE pipelines is established to determine whether there are some special emergency situations, which can be directly identified as high risk. In the second branch, a detailed risk assessment process is adopted to obtain the final result, which mainly includes risk factor analysis, risk status assessment and risk classification. Among them, risk factor analysis is used to establish a risk index system and develop a risk index management strategy by means of mathematical statistics and the fuzzy TOPSIS analysis method. The risk status assessment is used to determine the final risk value based on the virtual cloud and fault tree analysis, which is mainly realized by the triangular fuzzy number, structural entropy weight method and backward cloud transformation algorithm. Finally, the risk assessment results of PE gas pipelines are clearly presented in the form of cloud inference, and the final risk classification is determined. The case study shows that the pipeline in this section is at the medium risk level, and the management of time-related indicators and third-party damage is given priority. The result is consistent with the actual situation, which verifies the effectiveness and practicability of the methodology. Highlights: A novel methodology by integrating an fuzzy TPOSIS model and cloud inference for risk assessment of urban PE gas pipelines is proposed. A new PE gas pipeline risk assessment system was established. Detailed PE gas pipeline failure case investigation was conducted in the study. The problems of fuzziness and blindness are solved by cloud model and structural entropy weight method.