CALIBRAÇÃO DE MODELOS DE REDES DE DISTRIBUIÇÃO DE ÁGUA USANDO ALGORÍTMO GENÉTICO MULTIOBJETIVO

• Ano de defesa: 2008
• Autor(a) principal: VIEIRA, Maria Eulina Aires Gonçalves
• Orientador(a): FORMIGA, Klebber Teodomiro Martins
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Goiás
• Programa de Pós-Graduação: Mestrado em Engenharia do Meio Ambiente
• Departamento: Engenharias
• País: BR
• Palavras-chave em Português: Redes de Distribuição de Água; calibração; algoritmo genético multiobjetivo; 1. Agua - Redes de distribuicao. 2. Algoritimo geneticos 3. CALIBRACAO 4. Saneamento ambiental
• Palavras-chave em Inglês: Water Distribution Networks; calibration; multiobjective genetic algorithm
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA CIVIL::ENGENHARIA HIDRAULICA
• Link de acesso: http://repositorio.bc.ufg.br/tede/handle/tde/628

Increasing population united the behaviour of man carefree about the environmental preservation has led to a scarcity of natural resources. A key resource for human survival has been directly affected by these desmazelos, water. Based on this context arises as a commitment to operational excellence of water supply systems, seeking greater efficiency in the establishment of operational rules. To this end, the general objective of this research is to develop a study of water distribution networks model calibration, because it is believed to be the best technique for tracking this problem by adjusting the physical parameters that have changed over time and dictate strategies. This work aims to develop a technique based on the inverse of calibration using GAs as a tool for optimization, using multiple goals: pressure and flow. The parameters adjusted were roughness coefficients and coefficients of losses by leaks. To evaluate the proposed methodology were employed two networks often used in literature. The first network employed is a theoretical system proposed by Tucciarelli (1999) and was used to evaluate the behavior of multiobjectives methods and their parameters. The second network is located in Campo Grande (MS) has been studied by Cheung (2004) and Soares et al. (2004). This example is a real system that had its data measured in situ and presents all the complications inherent in the calibration real problems. The results were very satisfactory, since the optimization multiobjective shown to be able to improve the accuracy of the calibration of the model.