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A Risk Assessment Model of Gas Pipeline Leakage Based on a Fuzzy Hybrid Analytic Hierarchy Process

Author

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  • Jiangxue Tian

    (School of Management Engineering, Capital University of Economics and Business, Beijing 100070, China)

  • Shuran Lv

    (School of Management Engineering, Capital University of Economics and Business, Beijing 100070, China)

Abstract

Given the rising urban demand for gas, it has emerged as a primary energy source for urban activities and daily life. However, China’s urban gas pipeline network has witnessed a surge in accidents, leading to significant losses and disasters. Therefore, it is particularly necessary to study the disaster risk assessment model caused by urban gas pipeline leakage. There are some problems in the previous evaluation methods, such as less consideration of the influence relationships between disaster factors. To redress this issue, a novel fuzzy hybrid analytic hierarchy process evaluation methodology is proposed. First, a hybrid hierarchical risk assessment model is developed by combining the analytic hierarchy process and the network analytic hierarchy process. Membership matrices and impact matrices are utilized to calculate comprehensive factor weights. This approach enhances the understanding of relationships between risk factors within the hierarchical structure model. Subsequently, employing a fuzzy evaluation method, the risk level matrix is derived by using multiplication and bounded operators to ascertain the risk level state. This solves the problem of the fuzzy boundaries when measuring the index factors of the gas pipeline network. Finally, experimental analysis is carried out on the gas pipeline network in the central area of a city and validates the model’s accuracy in practical applications.

Suggested Citation

  • Jiangxue Tian & Shuran Lv, 2024. "A Risk Assessment Model of Gas Pipeline Leakage Based on a Fuzzy Hybrid Analytic Hierarchy Process," Sustainability, MDPI, vol. 16(20), pages 1-23, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:8797-:d:1496605
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