Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo
| Ano de defesa: | 2019 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Não Informado pela instituição
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| Programa de Pós-Graduação: |
Não Informado pela instituição
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: | |
| Link de acesso: | http://www.repositorio.ufc.br/handle/riufc/44483 |
Resumo: | In this dissertation it was carried out on how the calibration of the roughness of pipes of water distribution networks with different objective functions takes place. It is widely known the difficulties that are experienced when there is no knowledge of the physical parameters of a network, especially when it is subject to transient regimes. When applying Genetic Algorithms in two networks submitted to a transient with different objective functions, it was aimed to obtain parameters, such as permanent and transient hydraulic flows and loads, to apply and obtain the values of three objective functions previously selected and modified to better represent the objectives of the study, when used to calibrate the roughness from nodes and selected sections of the studied networks, the best three solutions of each one being analyzed. Two hypothetical networks with known parameters were used here, applying a hydraulic transient by demand variation. The three objective functions chosen represent the quadratic difference between the actual and simulated loads (FO1), the quadratic difference between the actual and simulated flows (FO2) and the two previous differences summed using individual weights for each (FO3). Four nodes were selected in each of the nets, each with a striking characteristic, being the largest and the smallest distance from the node to the supply reservoir of the network, a node with a large number of tubes connected to it and a node that was at the end of the net. The results show that FO1 obtained a more important performance in 3 of the 4 groups analyzed, when considering the Relative Mean Error (RMS) in the roughness calibration, besides the values of hydraulic load and flow in permanent and transient regime, as well it can be seen that the hydraulic load is better shown to represent these points studied. When looking at the three best solutions of each objective function, it is noted that there is no direct relationship between the lower function value and the production of a smaller error, especially in the roughness calibration, besides that the roughness error is considerably higher than the hydraulic load, for example. It is noted that the application of the selected objective functions still cause a considerable RMS in the roughness calibration, even if this error does not propagate through the load, then it is to be noted that changes need to be made in these functions to better represent the reality, although show a good beginning for the study and that the advantages that the genetic algorithm brings to the calibration processes are always positive and should be explored. |
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Ferreira, Italo Ruan DantasAraújo, John Kenedy de2019-08-06T14:37:53Z2019-08-06T14:37:53Z2019FERREIRA, I. R. D. Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo. 2019. 186 f. Dissertação (Mestrado em Engenharia Civil)-Centro de Tecnologia, Programa de Pós-Graduação em Engenharia Civil: Recursos Hídricos, Universidade Federal do Ceará, Fortaleza, 2019.http://www.repositorio.ufc.br/handle/riufc/44483In this dissertation it was carried out on how the calibration of the roughness of pipes of water distribution networks with different objective functions takes place. It is widely known the difficulties that are experienced when there is no knowledge of the physical parameters of a network, especially when it is subject to transient regimes. When applying Genetic Algorithms in two networks submitted to a transient with different objective functions, it was aimed to obtain parameters, such as permanent and transient hydraulic flows and loads, to apply and obtain the values of three objective functions previously selected and modified to better represent the objectives of the study, when used to calibrate the roughness from nodes and selected sections of the studied networks, the best three solutions of each one being analyzed. Two hypothetical networks with known parameters were used here, applying a hydraulic transient by demand variation. The three objective functions chosen represent the quadratic difference between the actual and simulated loads (FO1), the quadratic difference between the actual and simulated flows (FO2) and the two previous differences summed using individual weights for each (FO3). Four nodes were selected in each of the nets, each with a striking characteristic, being the largest and the smallest distance from the node to the supply reservoir of the network, a node with a large number of tubes connected to it and a node that was at the end of the net. The results show that FO1 obtained a more important performance in 3 of the 4 groups analyzed, when considering the Relative Mean Error (RMS) in the roughness calibration, besides the values of hydraulic load and flow in permanent and transient regime, as well it can be seen that the hydraulic load is better shown to represent these points studied. When looking at the three best solutions of each objective function, it is noted that there is no direct relationship between the lower function value and the production of a smaller error, especially in the roughness calibration, besides that the roughness error is considerably higher than the hydraulic load, for example. It is noted that the application of the selected objective functions still cause a considerable RMS in the roughness calibration, even if this error does not propagate through the load, then it is to be noted that changes need to be made in these functions to better represent the reality, although show a good beginning for the study and that the advantages that the genetic algorithm brings to the calibration processes are always positive and should be explored.Nessa dissertação se decorreu sobre como a calibração da rugosidade de tubos de redes de distribuição de água com diferentes funções objetivo se dá. É de amplo conhecimento as dificuldades que se tem quando não existe o conhecimento dos parâmetros físicos de uma rede, sobretudo quando essa se encontra submetida a regimes transientes. Ao se aplicar Algoritmos Genéticos em duas redes submetidas a um transiente com diferentes funções objetivo, visou-se obter parâmetros, como as vazões e cargas hidráulicas permanentes e transientes, aplicar e obter os valores de três funções objetivo, previamente selecionadas e modificadas para melhor representar os objetivos do estudo, quando utilizadas para calibrar a rugosidade a partir de nós e seções selecionados das redes estudadas, sendo as melhores três soluções de cada uma analisadas. Duas redes hipotéticas com parâmetros conhecidos foram aqui utilizadas, aplicando um transiente hidráulico por variação de demanda. As três funções objetivo escolhidas representam a diferença quadrática entre as cargas reais e simuladas (FO1), a diferença quadrática entre as vazões reais e simuladas (FO2) e as duas diferenças anteriores somadas utilizando pesos individuais para cada uma delas (FO3). Quatro nós foram selecionados em cada uma das redes, cada um com uma característica marcante, sendo elas, a maior e a menor distância do nó até o reservatório de abastecimento da rede, um nó com uma grande quantidade de tubos a ele ligados e um nó que estivesse na extremidade da rede. Os resultados apresentam que a FO1 obteve um desempenho mais importante em 3 dos 4 grupos analisados, quando se leva em consideração o Erro Médio Relativo (EMR) na calibração das rugosidades, além dos valores de carga hidráulica e vazão em regime permanente e transiente, assim percebe-se que a carga hidráulica se mostra melhor para representar esses pontos estudados. Quando se olha para as três melhores soluções de cada função objetivo, nota-se que não existe uma relação direta entre o menor valor de função com a produção de um menor erro, principalmente na calibração da rugosidade, além de que o erro na rugosidade é consideravelmente superior àquele apresentado pela carga hidráulica, por exemplo. Nota-se a aplicação das funções objetivos selecionadas ainda provocam um EMR considerável na calibração de rugosidades, mesmo que esse erro não se propague pela carga, então é de se notar que mudanças necessitam ser feitas nessas funções para melhor representar a realidade, apesar de se mostrarem um bom o começo para o estudo e de que as vantagens que o algoritmo genético traz para os processos de calibração são sempre positivos e devem ser explorados.Recursos hídricosTransitórios hidráulicosÁgua - DistribuiçãoAlgoritmos genéticosObjective functionsRoughnessHydraulic transientWater distribution networksGenetic algorithmEstudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessORIGINAL2019_dis_irdferreira.pdf2019_dis_irdferreira.pdfapplication/pdf6441708http://repositorio.ufc.br/bitstream/riufc/44483/3/2019_dis_irdferreira.pdfb3b454a32076d5c185973fe71976b9daMD53LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ufc.br/bitstream/riufc/44483/4/license.txt8a4605be74aa9ea9d79846c1fba20a33MD54riufc/444832022-12-07 10:51:31.255oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2022-12-07T13:51:31Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false |
| dc.title.pt_BR.fl_str_mv |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo |
| title |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo |
| spellingShingle |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo Ferreira, Italo Ruan Dantas Recursos hídricos Transitórios hidráulicos Água - Distribuição Algoritmos genéticos Objective functions Roughness Hydraulic transient Water distribution networks Genetic algorithm |
| title_short |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo |
| title_full |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo |
| title_fullStr |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo |
| title_full_unstemmed |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo |
| title_sort |
Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo |
| author |
Ferreira, Italo Ruan Dantas |
| author_facet |
Ferreira, Italo Ruan Dantas |
| author_role |
author |
| dc.contributor.author.fl_str_mv |
Ferreira, Italo Ruan Dantas |
| dc.contributor.advisor1.fl_str_mv |
Araújo, John Kenedy de |
| contributor_str_mv |
Araújo, John Kenedy de |
| dc.subject.por.fl_str_mv |
Recursos hídricos Transitórios hidráulicos Água - Distribuição Algoritmos genéticos Objective functions Roughness Hydraulic transient Water distribution networks Genetic algorithm |
| topic |
Recursos hídricos Transitórios hidráulicos Água - Distribuição Algoritmos genéticos Objective functions Roughness Hydraulic transient Water distribution networks Genetic algorithm |
| description |
In this dissertation it was carried out on how the calibration of the roughness of pipes of water distribution networks with different objective functions takes place. It is widely known the difficulties that are experienced when there is no knowledge of the physical parameters of a network, especially when it is subject to transient regimes. When applying Genetic Algorithms in two networks submitted to a transient with different objective functions, it was aimed to obtain parameters, such as permanent and transient hydraulic flows and loads, to apply and obtain the values of three objective functions previously selected and modified to better represent the objectives of the study, when used to calibrate the roughness from nodes and selected sections of the studied networks, the best three solutions of each one being analyzed. Two hypothetical networks with known parameters were used here, applying a hydraulic transient by demand variation. The three objective functions chosen represent the quadratic difference between the actual and simulated loads (FO1), the quadratic difference between the actual and simulated flows (FO2) and the two previous differences summed using individual weights for each (FO3). Four nodes were selected in each of the nets, each with a striking characteristic, being the largest and the smallest distance from the node to the supply reservoir of the network, a node with a large number of tubes connected to it and a node that was at the end of the net. The results show that FO1 obtained a more important performance in 3 of the 4 groups analyzed, when considering the Relative Mean Error (RMS) in the roughness calibration, besides the values of hydraulic load and flow in permanent and transient regime, as well it can be seen that the hydraulic load is better shown to represent these points studied. When looking at the three best solutions of each objective function, it is noted that there is no direct relationship between the lower function value and the production of a smaller error, especially in the roughness calibration, besides that the roughness error is considerably higher than the hydraulic load, for example. It is noted that the application of the selected objective functions still cause a considerable RMS in the roughness calibration, even if this error does not propagate through the load, then it is to be noted that changes need to be made in these functions to better represent the reality, although show a good beginning for the study and that the advantages that the genetic algorithm brings to the calibration processes are always positive and should be explored. |
| publishDate |
2019 |
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2019-08-06T14:37:53Z |
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2019-08-06T14:37:53Z |
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2019 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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publishedVersion |
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FERREIRA, I. R. D. Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo. 2019. 186 f. Dissertação (Mestrado em Engenharia Civil)-Centro de Tecnologia, Programa de Pós-Graduação em Engenharia Civil: Recursos Hídricos, Universidade Federal do Ceará, Fortaleza, 2019. |
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http://www.repositorio.ufc.br/handle/riufc/44483 |
| identifier_str_mv |
FERREIRA, I. R. D. Estudo da calibração de redes de distribuição de água submetidas ao regime transiente utilizando algoritmos genéticos e diferentes funções objetivo. 2019. 186 f. Dissertação (Mestrado em Engenharia Civil)-Centro de Tecnologia, Programa de Pós-Graduação em Engenharia Civil: Recursos Hídricos, Universidade Federal do Ceará, Fortaleza, 2019. |
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