In this paper, an optimisation procedure is developed for calibration of the both types of hydraulic simulation models, demand driven and pressure dependent analyses, by using genetic algorithm. Variables of pipe roughness coefficient, nodal demand and pipe diameter are investigated for calibration of the hydraulic models. Four scenarios of minimum, normal, maximum and fire consumption are considered for calibration. In addition, the leakage term is incorporated into the hydraulic equations to be able to evaluate the hydraulic situation more realistically in both demand driven analysis (DDA) and pressure dependent analysis (PDA) based models. The suggested calibration procedure is applied on a test network with different consumption scenarios and variables. It is found that the best results are obtained with fire consumption case and both variables of pipe roughness and nodal demand. Leakage consideration reduces the weaknesses of the low flow scenario and also PDA produces lower error values in comparison with DDA.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.