توصيفگر ها :
شبكه توزيع آب , كلر باقيمانده , آلودگي ميكروبي , الگوريتم ژنتيك , EPANET_MSX
چكيده انگليسي :
Water transmission and distribution systems are potentially sensitive to incoming pollutants. These pollutants can enter the system accidentally through pipe corrosion or backflows, or intentionally through terrorist activities. Once entered, pollutants are transported with the water flow and, depending on their quantity and type, can cause transient or chronic diseases or serious environmental pollution. Due to the vastness of the network and the large number of connections and various equipment such as valves, reservoirs, tanks, and pumps, the entry of pollutants into these systems is often inevitable. Identifying the type of pollutant, its reaction with disinfectants present in the network, the decay rate of these substances, and the pollutant concentration in water are of utmost importance.
After identifying these factors, the most important task is to develop a model that can simulate the dispersion of pollutants in the network. In this thesis, a new module has been used that is capable of modeling interactions among multiple pollutants in the water distribution network. Furthermore, the interaction between biological contamination and chlorine as a disinfectant in the water transmission line from the Babashikhali water treatment plant to the city of Nayin has been investigated.
For this purpose, the decay equations of the substance and its decay rate were first determined, and then pollution dispersion was simulated using EPANET, EPANET_MSX, and MATLAB software in two seasons: summer and winter. The results of the node analysis based on flow rate and chlorine deficiency indicate the high importance of nodes 2 and 15. Therefore, these two nodes were introduced as the injection points for pollution in the model. After pollution generation, the use of chlorination method to combat this problem was studied. Genetic algorithm was used to optimize chlorination. The results showed that under pollution entry conditions from node 2 and chlorine injection from 3 stations, the optimal condition for system disinfection was achieved in both seasons. Based on this, the injected chlorine concentrations in summer from stations 9, 19, and 31 were 1.23, 1.12, and 0.6 milligrams per liter, respectively, and in winter, they were 0.98, 1.15, and 0.64 milligrams per liter, respectively. Also, under pollution entry conditions from node 15, the injected chlorine concentrations in summer from stations 23, 24, and 33 were 1.1, 0.97, and 0.51 milligrams per liter, respectively, and in winter, they were 0.87, 0.8, and 0.54 milligrams per liter, respectively. The findings indicate that by employing this approach, significant improvement against pollution can be achieved. This method allows for obtaining better results with less chlorine usage.
