@article { author = {Shahbazi, M. and M. V. Samani, J.}, title = {Application of Genetic Algorithm for Determining the Existent Friction Coefficients in the Real-life Pipe Networks as an Inverse Problem}, journal = {Journal of Hydraulics}, volume = {4}, number = {3}, pages = {19-35}, year = {2009}, publisher = {Iranian Hydraulic Association}, issn = {2345-4237}, eissn = {2645-8063}, doi = {10.30482/jhyd.2009.85526}, abstract = {An integrated approach for determining the existent friction coefficients in water networks isproposed. As pressurized systems age, the carrying capacity of network decreases because the internalroughness increases with the aging of pipes. This can lead to loss of satisfactory performance anduneconomic operation. Therefore, rehabilitation of an existing network becomes very importantproblem in water industry. Determining the real physical characteristics of pipes for network analysisis a regular component of the rehabilitation process. Pipe friction coefficients cannot be determinedexplicitly by direct measurement, they are determined implicitly, as an inverse problem, frommeasured model outputs (pressures). Values of friction coefficients are determined in a way that theyshould yield a reasonable match between measured and predicated pressures in the network. Oneproblem associated with the Re-calibration of real-life pipe networks is the lack of field measurements,which can sometimes, lead to the formulation of an ill-posed inverse problem. In this study certainmethods have been utilized to tackle this problem. The hydraulic analysis of steady and quasi-steadyflow and optimization process are combined to develop a program. By selecting a proper optimizationmethod (Genetic Algorithm) the inverse model was developed and verified successfully in a casestudy.}, keywords = {}, title_fa = {بکارگیری الگوریتم ژنتیک در مساله معکوس تخمین ضرایب زبری لوله ها در شبکه های تحت فشار}, abstract_fa = {}, keywords_fa = {}, url = {https://jhyd.iha.ir/article_85526.html}, eprint = {https://jhyd.iha.ir/article_85526_8bf189c38c5a9524853644ddb6f10660.pdf} }