|M.Sc Student||Mayorchik Yuri|
|Subject||Optimal Design and Operation of Pressure Surge Control|
Devices in Water Distribution Systems
|Department||Department of Civil and Environmental Engineering||Supervisor||Professor Avi Ostfeld|
|Full Thesis text|
The common practice in water distribution systems optimal design and operation is to first design the system to meet steady demands of quantity and pressure for a selected set of loading conditions, after which transient analysis is performed. According to the transient analysis results surge control devices are selected, and the system is run again to test its performance. This iterative process continues until a satisfactory design is established. This thesis presents an optimization scheme for optimally sizing surge control devices in water distribution systems. The optimal sizing is accomplished through linking a genetic algorithm with the University of Kentucky surge program. The study concentrated on simultaneously optimizing both the system capacity (i.e., sizing of pipes, pumps, tanks, etc.) in conjunction with surge control devices. In addition a multiobjective evolutionary framework was developed to tradeoff cost and the surge control devices ability to perform their task during a transient. Four example applications were explored demonstrating the algorithm performance and its potential capabilities. The first example deals with sizing surge control devices given their layout; at examples two and three the systems were simultaneously optimized for both their capacity and surge scenarios; and in example four a multiobjective scheme was applied to tradeoff cost with the surge devices ability to control transient pressures. The main conclusions of this work are: 1. It is possible to define and solve an optimization model with explicit inclusion of transient considerations. 2. Simultaneously optimizing a water distribution system for both its capacity (steady state loadings) and transient (water hammer) can lead to improved solutions over the common engineering practice of first solving the steady state problem and then the transient. 3. The main limitation of the proposed methodology is the computational time required to achieve optimal solutions.