Full Description

This paper proposes a comprehensive and flexible framework for calibrating a hydraulic network model. Calibration tasks can be specified for a water distribution system according to data availability and model application requirements. It allows a user to: flexibly choose any combination of the model parameters such as pipe roughness, junction demand and link (pipes, valves and pumps) operational status; easily aggregate model parameters to reduce the problem dimension for expeditious calculation; and, consistently specify boundary conditions and junction demand loadings that are corresponding to field data collection. A model calibration is then defined as an implicit nonlinear optimization problem, which is solved by employing a powerful genetic algorithm (GA), a generic search paradigm based on the principles of natural evolution and biological reproduction. Calibration solutions are obtained by minimizing the discrepancy between the model predicted and the field observed values of junction pressures and pipe flows. With this methodology, a modeler can be fully assisted during a calibration process, thus it is possible to achieve a good model calibration with high level of confidence. As a result, calibrated models can be developed for conducting system analysis and operational management. An example application is presented to demonstrate the efficacy and robustness of the genetic-based methodology for calibrating a water distribution model. Includes 11 references, figures.

Product Details

Edition: Vol. - No. Published: 01/01/2002 Number of Pages: 10File Size: 1 file , 230 KB