Anbari Mohammad Javad, Tabesh Massoud, Roozbahani Abbas
School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; Water Resources Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran.
Center of Excellence for Engineering and Management of Civil Infrastructures, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.
J Environ Manage. 2017 Apr 1;190:91-101. doi: 10.1016/j.jenvman.2016.12.052. Epub 2016 Dec 29.
In wastewater systems as one of the most important urban infrastructures, the adverse consequences and effects of unsuitable performance and failure event can sometimes lead to disrupt part of a city functioning. By identifying high failure risk areas, inspections can be implemented based on the system status and thus can significantly increase the sewer network performance. In this study, a new risk assessment model is developed to prioritize sewer pipes inspection using Bayesian Networks (BNs) as a probabilistic approach for computing probability of failure and weighted average method to calculate the consequences of failure values. Finally to consider uncertainties, risk of a sewer pipe is obtained from integration of probability and consequences of failure values using a fuzzy inference system (FIS). As a case study, sewer pipes of a local wastewater collection network in Iran are prioritized to inspect based on their criticality. Results show that majority of sewers (about 62%) has moderate risk, but 12%of sewers are in a critical situation. Regarding the budgetary constraints, the proposed model and resultant risk values are expected to assist wastewater agencies to repair or replace risky sewer pipelines especially in dealing with incomplete and uncertain datasets.
作为最重要的城市基础设施之一，在废水处理系统中，性能不佳和故障事件带来的不良后果有时可能导致城市部分功能中断。通过识别高故障风险区域，可以根据系统状态进行检查，从而显著提高下水道网络的性能。在本研究中，开发了一种新的风险评估模型，以使用贝叶斯网络（BNs）作为计算故障概率的概率方法和加权平均法来计算故障后果值，从而对下水道管道检查进行优先级排序。最后，为了考虑不确定性，使用模糊推理系统（FIS）通过整合故障概率和后果值来获得下水道管道的风险。作为案例研究，伊朗当地废水收集网络的下水道管道根据其关键性进行检查优先级排序。结果表明，大多数下水道（约62%）风险适中，但12%的下水道处于危急状况。考虑到预算限制，预计所提出的模型和由此产生的风险值将有助于废水处理机构修复或更换有风险的下水道管道尤其是在处理不完整和不确定数据集时。
