Uma abordagem bayesiana para construção de modelos fenomenológicos para vibração induzida por vórtices

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Honigbaum, Jacques
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal do Rio de Janeiro
Brasil
Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
Programa de Pós-Graduação em Engenharia Mecânica
UFRJ
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://hdl.handle.net/11422/13529
Resumo: When there is huid flow being partially obstructed by a structure, the flow pattern of the fluid is influenced by some inherent characteristics of the structure. So the structure itself also responds to those effects experienced by the fluid. This interactive relationship between finid and structure is part of the field of study of Fluid-structure interaction. One of the phenomena studied in this area is the formation of vortices in the fluid that results in the vibration of the structure. Due to the complexity of Vortex—induced Vibration description and the computational cost involved, one can choose to use phenomenological models, with low computational cost. In the situation of a cylindrical structure exposed to a fluid flow and subjected to the VIV phenomenon, a Wake Oscillator Model can be used. The phenomenology of this problem consists in choosing one of the physics to be described, while the other is emulated. The fluid part is coupled to the structural part in the form of an effect equivalent to its influence on the problem, from a replaceable formulation. In this work, it is sought to perform the calibration of parameters of a wake model in relation to a CFD model. The models go through quantitative compatibilization with experimental data for later calibration process. The calibration follows the statistical procedure of Bayesian Inference.