Gheibi Mohammad, Moezzi Reza, Taghavian Hadi, Wacławek Stanisław, Emrani Nima, Mohtasham Mohsen, Khaleghiabbasabadi Masoud, Koci Jan, Yeap Cheryl S Y, Cyrus Jindrich
Institute for Nanomaterials, Advanced Technologies, and Innovation, Technical University of Liberec, Liberec, Czech Republic.
Association of Talent Under Liberty in Technology (TULTECH), Tallinn, Estonia.
Sci Rep. 2023 Jul 27;13(1):12200. doi: 10.1038/s41598-023-38620-w.
Water Distribution Networks (WDNs) are considered one of the most important water infrastructures, and their study is of great importance. In the meantime, it seems necessary to investigate the factors involved in the failure of the urban water distribution network to optimally manage water resources and the environment. This study investigated the impact of influential factors on the failure rate of the water distribution network in Birjand, Iran. The outcomes can be considered a case study, with the possibility of extending to any similar city worldwide. The soft sensor based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) was implemented to predict the failure rate based on effective features. Finally, the WDN was assessed using the Failure Modes and Effects Analysis (FMEA) technique. The results showed that pipe diameter, pipe material, and water pressure are the most influential factors. Besides, polyethylene pipes have failure rates four times higher than asbestos-cement pipes. Moreover, the failure rate is directly proportional to water pressure but inversely related to the pipe diameter. Finally, the FMEA analysis based on the knowledge management technique demonstrated that pressure management in WDNs is the main policy for risk reduction of leakage and failure.
供水管网（WDNs）被认为是最重要的水利基础设施之一，对其进行研究具有重要意义。与此同时，似乎有必要调查城市供水管网故障所涉及的因素，以便对水资源和环境进行优化管理。本研究调查了影响因素对伊朗比尔詹德供水管网故障率的影响。研究结果可被视为一个案例研究，并有可能推广到全球任何类似城市。基于自适应神经模糊推理系统（ANFIS）的软传感器被用于根据有效特征预测故障率。最后，使用故障模式和影响分析（FMEA）技术对供水管网进行评估。结果表明，管径、管材和水压是最具影响力的因素。此外，聚乙烯管的故障率比石棉水泥管高四倍。而且，故障率与水压成正比，但与管径成反比。最后，基于知识管理技术的FMEA分析表明，供水管网中的压力管理是降低泄漏和故障风险的主要策略。
