Evolutionary Testing of Hydraulic Simulator Functionality

Abstract

A method for automatic functional testing of hydraulic simulators is proposed. The method is based on using genetic algorithms to search for network parameter values at which the simulator under test computes solutions that do not satisfy the governing network equations. The search is made by maximizing the residual of the governing equations. The application of the method to the latest version of the EPANET hydraulic simulator demonstrates its efficiency in detecting incorrect results. The results of quantitative assessment of the functional adequacy of the EPANET solver by random testing are presented. The paper provides examples of hydraulic networks and of parameter value combinations for which incorrect results occur. An example of the use of automatic functional testing together with automatic convergence testing in a comprehensive study of the flow control valve model of the EPANET solver is given.

Aquifers Management through Evolutionary Bayesian Networks: The Altiplano Case Study (SE Spain)

“…has been illustrated (Molina-Cristobal et al 2005;Hanne and Nickel 2005;Osman et al 2005;Farmani et al 2005bFarmani et al , 2006Farmani et al and 2007Murugan et al 2009), there have been limited applications in policy analysis of water resources management (Farmani et al 2009). There are recent applications of EMO algorithms related to other water resources research studies such as optimal design of water distribution systems or reservoirs (Cisty 2010;Nazif et al 2010;Haghighi et al 2011;Hınçal et al 2011;Louati et al 2011), or Conjunctive Use of Surface Water and Groundwater (Safavi et al 2010), or the control of Seawater Intrusion in Coastal Aquifers (Kourakos and Mantoglou 2011; Abd-Elhamid and Javadi 2011; Sedki and Ouazar 2011), or hydrological studies (Dumedah et al 2010;;Hassanzadeh et al 2011;Gorev et al 2011). In this work an evolutionary multi-objective optimization tool (GANetXL 2007) based on NSGAII (Deb et al 2000) is coupled with the OOBN model developed in HUGIN software (2007), and used to assist in the selection of the best compromise management option(s) for participatory decision making.…”