Peirovi Minaee Roya, Afsharnia Mojtaba, Moghaddam Alireza, Ebrahimi Ali Asghar, Askarishahi Mohsen, Mokhtari Mehdi
Environmental Science and Technology Research Center, Department of Environmental Health Engineering, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Department of Environmental Health Engineering, School of Public Health, Gonabad University of Medical Sciences, Gonabad, Iran.
MethodsX. 2019 Mar 16;6:540-548. doi: 10.1016/j.mex.2019.03.008. eCollection 2019.
Chlorine reacts with both organic and inorganic matters in water. That is why water quality modeling has received great attention in recent years. The serious issue in municipal water quality modeling is gathering the essential input parameters of the model, particularly bulk decay (k) and wall decay (k) coefficients as well as their calibrations. Therefore, this study first thoroughly formulates the problem in the form of a heuristic optimization and then utilizes Genetic Algorithm, Particle Swarm Optimization, and Hybrid GA-PSO as the model optimizers in order to best calibrate k for minimizing the difference of residual chlorine concentrations that exist between the simulated and observed values. These three algorithms are linked to EPANET, the hydraulic and water quality simulator. The method is then applied to a real-world water distribution network. Here, is considered as a decision variable. The objective function is to minimize both the Sum of Square Error and Root Mean Square Error between the observed and simulated chlorine concentrations. According to the simulation results obtained, the optimal value of wall decay coefficient is 1.233 m/day during the calibration process while the minimum and maximum differences between the measured and simulated chlorine rates were 0 and 0.18, respectively. •The method presented in this article can be useful for managers of water and wastewater companies, water resources facilities and operators and operation manager of water distribution system to manage chlorine dosing rate.•Due to adverse health effect of disinfection by product and poor microbial water quality as results of inefficient chlorination, control chlorine concentration in water distribution networks and its consequence on human health effect is necessary.•Hybrid PSO and GA methods are used to cope with their falling in local optimum and requiring highly computational effort.
氯与水中的有机物和无机物都会发生反应。这就是近年来水质建模备受关注的原因。城市水质建模中的一个严重问题是收集模型的基本输入参数，特别是总体衰减（k）和管壁衰减（k）系数及其校准。因此，本研究首先以启发式优化的形式全面阐述该问题，然后利用遗传算法、粒子群优化算法和混合遗传算法 - 粒子群优化算法作为模型优化器，以便最佳地校准k，从而最小化模拟值与观测值之间的余氯浓度差异。这三种算法与水力和水质模拟器EPANET相关联。然后将该方法应用于一个实际的配水管网。在此，将 视为决策变量。目标函数是最小化观测氯浓度与模拟氯浓度之间的均方误差和均方根误差之和。根据获得的模拟结果，在校准过程中管壁衰减系数的最优值为1.233米/天，而测量氯率与模拟氯率之间的最小和最大差异分别为0和0.18。•本文提出的方法对于自来水和污水处理公司的管理人员、水资源设施及运营商以及配水系统运营经理管理加氯率可能会有所帮助。•由于消毒副产物对健康有不利影响，且氯化效率低下导致微生物水质不佳，因此有必要控制配水管网中的氯浓度及其对人体健康的影响。•使用混合粒子群优化算法和遗传算法来应对它们陷入局部最优以及计算量较大的问题。
