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Systematic exploration of pipeline network calibration using transients / B. S. Jung in Journal of hydraulic research, Vol. 46 extra issue (2008) 

Public ISBD [article]  in Journal of hydraulic research > Vol. 46 extra issue (2008) . - p. 129-137 Titre : Systematic exploration of pipeline network calibration using transients Titre original : Exploration systématique du calibrage d'un réseau de canalisations en utilisant des coupures Type de document : texte imprimé Auteurs : B. S. Jung, Auteur ; B. W. Karney, Auteur Article en page(s) : p. 129-137 Note générale : Hydraulique Résumé en Français Langues : Anglais (eng) Mots-clés : Water  distribution  system  Calibration  Inverse  transient  analysis  Sensitivity  analysis  Evolutionary  optimization  Particle  swam  optimization  Genetic  algorithm Index. décimale : 627 Ingénierie des cours d'eau naturels, des ports, des rades et des cotes. Installations de navigation, de dragage, de récupération et de sauvetage. Barrages et centrales électriques hydrauliques Résumé : Accurate information of pipeline and system properties is crucially important for precise computer simulation of pipe networks. Even though inverse transient analysis (ITA) techniques have been widely investigated for leak detection and friction factor calibration, many challenges still remain. One reason for these difficulties is that real water distribution systems invariably have many kinds of uncertainties including pipe diameter, wave speed and the water demand at the time of the tests. This paper investigates quantitatively how inaccuracies in such values invariably deteriorate the performance of calibration approaches. Thus, the paper argues that a systematic calibration should explicitly include these additional uncertainties during the ITA process. Two evolutionary approaches, namely Genetic Algorithms and Particle Swarm Optimization, are applied and are both compared and contrasted during the ITA iterations. The evolutionary algorithms help the search escape from poor local optima in multifaceted and complex problems and thus assist in locating global (or near-global) optima. However, most current approaches are shown to converge poorly as the full scale of the typical field problems is progressively reflected in the search space. DEWEY : 627 ISSN : 0022-1686 En ligne : http://www.journalhydraulicresearch.com [article] Systematic exploration of pipeline network calibration using transients = Exploration systématique du calibrage d'un réseau de canalisations en utilisant des coupures [texte imprimé] / B. S. Jung, Auteur ; B. W. Karney, Auteur . - p. 129-137. Hydraulique Résumé en Français Langues : Anglais (eng) in Journal of hydraulic research > Vol. 46 extra issue (2008) . - p. 129-137 Mots-clés : Water  distribution  system  Calibration  Inverse  transient  analysis  Sensitivity  analysis  Evolutionary  optimization  Particle  swam  optimization  Genetic  algorithm Index. décimale : 627 Ingénierie des cours d'eau naturels, des ports, des rades et des cotes. Installations de navigation, de dragage, de récupération et de sauvetage. Barrages et centrales électriques hydrauliques Résumé : Accurate information of pipeline and system properties is crucially important for precise computer simulation of pipe networks. Even though inverse transient analysis (ITA) techniques have been widely investigated for leak detection and friction factor calibration, many challenges still remain. One reason for these difficulties is that real water distribution systems invariably have many kinds of uncertainties including pipe diameter, wave speed and the water demand at the time of the tests. This paper investigates quantitatively how inaccuracies in such values invariably deteriorate the performance of calibration approaches. Thus, the paper argues that a systematic calibration should explicitly include these additional uncertainties during the ITA process. Two evolutionary approaches, namely Genetic Algorithms and Particle Swarm Optimization, are applied and are both compared and contrasted during the ITA iterations. The evolutionary algorithms help the search escape from poor local optima in multifaceted and complex problems and thus assist in locating global (or near-global) optima. However, most current approaches are shown to converge poorly as the full scale of the typical field problems is progressively reflected in the search space. DEWEY : 627 ISSN : 0022-1686 En ligne : http://www.journalhydraulicresearch.com