@MastersThesis{Gagliarde:2021:OtAlGe,
               author = "Gagliarde, Jorge Henrique",
                title = "Otimiza{\c{c}}{\~a}o por algoritmo gen{\'e}tico de bomba 
                         centr{\'{\i}}fuga aplicada a motor foguete com software livre 
                         para CFD",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2021",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2020-06-19",
             keywords = "bomba centr{\'{\i}}fuga, CFD, otimiza{\c{c}}{\~a}o 
                         multi-objetivo, algoritmo gen{\'e}tico, centrifugal pump, 
                         multiobjective optimization, genetic algorithm.",
             abstract = "Neste trabalho s{\~a}o realizados estudos de 
                         simula{\c{c}}{\~a}o computacional e otimiza{\c{c}}{\~a}o de 
                         uma bomba de combust{\'{\i}}vel para motor foguete a propelente 
                         l{\'{\i}}quido. A estrat{\'e}gia de otimiza{\c{c}}{\~a}o 
                         empregada {\'e} baseada em um algoritmo gen{\'e}tico elitista 
                         multi-objetivo (NSGA-II), o qual busca solu{\c{c}}{\~o}es 
                         {\'o}timas por meio da aplica{\c{c}}{\~a}o dos operadores 
                         gen{\'e}ticos adaptados para vari{\'a}veis de projeto 
                         representadas por n{\'u}meros reais. Cada solu{\c{c}}{\~a}o 
                         gerada pelo algoritmo gen{\'e}tico automaticamente atualiza a 
                         geometria da bomba e uma nova malha para simula{\c{c}}{\~a}o 
                         {\'e} gerada. O desempenho da bomba {\'e} avaliado por meio da 
                         mec{\^a}nica dos fluidos computacional (CFD) utilizando o 
                         programa de c{\'o}digo aberto OpenFOAM. Dados experimentais foram 
                         utilizados para valida{\c{c}}{\~a}o do modelo de CFD da 
                         geometria inicial. Foram obtidas melhorias simult{\^a}neas na 
                         efici{\^e}ncia e no trabalho espec{\'{\i}}fico da bomba por 
                         meio da busca de novas solu{\c{c}}{\~o}es Pareto-{\'o}timas. 
                         ABSTRACT: In this work, computational simulation and optimization 
                         ware carried out for a liquid rocket engine fuel pump. An elitist 
                         multi-objective genetic algorithm (NSGAII) was selected for the 
                         optimization process. This algorithm uses genetic operators 
                         adapted for dealing with real coded variables (as opposed to 
                         binary). Each solution generated by the algorithm generates a new 
                         CAD design and an automation script deals with the mesh generation 
                         and pre-processing. The pumps performance is evaluated by 
                         computational fluid dynamics (CFD) using the open source software 
                         OpenFOAM. Experimental data was used to validate the CFD model for 
                         the initial geometry design. Pareto optimal solutions were found 
                         and it was possible to obtain an increase in both head and 
                         efficiency.",
            committee = "Manea, Silvio (coordenador do curso) and Dourado, Wladimyr Mattos 
                         da Costa (presidente/orientador) and Costa, Fernando de Souza and 
                         Mendon{\c{c}}a, M{\'a}rcio Teixeira de and Alves, Alexandre 
                         Teodoro",
         englishtitle = "Genetic algorithm based optimization for a liquid rocket engine 
                         centrifugal pump using open source software for CFD",
             language = "pt",
                pages = "99",
                  ibi = "8JMKD3MGP3W34R/43A7KCB",
                  url = "http://urlib.net/ibi/8JMKD3MGP3W34R/43A7KCB",
           targetfile = "publicacao.pdf",
        urlaccessdate = "28 abr. 2024"
}