Author(s): Lu Lei; Liu Shuguang; Zhong Guihui; Wang Qiuping; Liu Yu; Xu Shengxin
Linked Author(s):
Keywords: Fuzzy TOPSIS; Cloud inference model; Water supply pipeline; Risk assessment
Abstract: Water supply pipelines are one of the most critical lifeline projects in cities. As municipal water supply pipelines gradually age, comprehensive risk assessment becomes increasingly crucial. Failure of water supply pipelines can not only pose a serious threat to the normal and safe use of water for users but may also lead to massive waste of water resources and economic losses. Traditional risk assessment methods often face difficulties in practical application due to their strong subjectivity. Therefore, the study of potential disaster risks in water supply pipelines has become a focal point of great concern for government management departments and engineering technicians. To ensure the safety of urban industrial production and residential water use, this paper proposes a risk assessment method for municipal water supply networks based on an integrated fuzzy TOPSIS and cloud inference model, including risk factor analysis, risk condition assessment, and risk classification. First, a risk index system is constructed using mathematical statistics and the fuzzy TOPSIS analysis method, with corresponding risk index countermeasures formulated. Then, the risk condition of water supply pipelines is assessed using virtual cloud and fault tree analysis, with the final risk value determined through triangular fuzzy numbers, structural entropy weight method, and inverse cloud transformation algorithm. Finally, the risk assessment results of water supply pipelines are clearly presented in the form of cloud inference. The study, through the analysis of an actual case in a certain city, shows that the pipeline is at a medium-low risk level, which verifies the effectiveness of the integrated fuzzy TOPSIS model and cloud inference analysis model. The research findings can provide technical support for water supply network departments in planning, design, and operation management, and help ensure the sustainable supply of water resources for urban residents and industrial production.
Year: 2024