Detection of Leakage Freshwater and Friction Factor Calibration in Drinking Networks Using Central Force Optimization

Inverse Transient Analysis (ITA) is a powerful approach for leak detection and calibration of friction factors in pressurized pipes. Through this method, a transient flow is initiated and pressures are measured somewhere in the system. Then, a nonlinear programming (NLP) problem with a least-squares criterion objective function is developed to minimize discrepancies between the measured and calculated pressures at measurement sites. Solving the raised NLP results in the problem’s unknowns being leakage specifications and pipe friction factors. For this purpose, various optimization techniques may be utilized. This issue is a major challenge for ITA-based methods. The present work aims at applying the new method of Central Force Optimization (CFO) to the problem of ITA. CFO is a deterministic metaheuristic inspired by gravitational kinematics in which small objects in space are dragged by bigger ones. Herein, the concept and main structure of CFO are represented as well as of CFO. A reference pipe-network is considered to be solved using the ITA equipped with CFO. The results are then discussed compared to the previous works. It is concluded that CFO is easy to implement, computationally efficient and has a remarkable performance in solving leak detection problem.