4.7 Article

An effective approach for assessing risk of failure in urban sewer pipelines using a combination of GIS and AHP-DEA

期刊

PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
卷 133, 期 -, 页码 275-285

出版社

ELSEVIER
DOI: 10.1016/j.psep.2019.10.036

关键词

AHP-DEA integration; GIS; Bayesian network; Risk of failure; Consequence of failure; Probability of failure

向作者/读者索取更多资源

The urban sewer pipeline network is a vital urban infrastructure that is highly at risk of failure and its deterioration can be harmful to the environment and public health and safety. Therefore, for performing an effective rehabilitation program, it is needed to prioritize the sewer pipelines. In this paper, a novel risk assessment approach is proposed for prioritizing sewer pipelines based on a combination of Geospatial Information System (GIS) and Analytic Hierarchy Process (AHP)- Data Envelopment Analysis (DEA). To do so, it calculates the Probability of Failure (PoF), along with the Consequence of Failure (CoF) for the sewer pipelines. Bayesian Network (BN) as the probabilistic method is used to calculate PoF. The main contribution of the study lies in using a combination of GIS, AHP, and DEA for quantitatively assessing the CoF, firstly, the criteria weights are determined by the AHP method through experts' judgments. Then, GIS functionalities along with DEA, are used to calculate scores for the alternatives. Finally, the outputs of the AHP method are integrated with the outputs of the DEA method in order to calculate CoF. The proposed method is applied to a local sewer pipeline network as a real-world case study to assess its risk of failure. The results indicated that the sewer pipelines are in good condition in the study area and among 1605 sewer pipelines, only 48 of them (about 3 %) are in a critical situation that it is needed to perform rehabilitation program. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据