Modelagem da dispersão de odores em ambientes urbanos

Detalhes bibliográficos
Autor(a) principal: Dourado, Harerton Oliveira
Data de Publicação: 2013
Tipo de documento: Tese
Idioma: eng
Título da fonte: Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
Texto Completo: http://repositorio.ufes.br/handle/10/1126
Resumo: The present work investigated odour dispersion modelling in the presence of obstacles (cubical and complex-shaped buildings) under neutral atmospheric conditions employing numerical modelling based on the transport equations (CFD8) as well as on algebraic Gaussian- based models (AERMOD9, CALPUFF10 and FPM11) and using field and wind tunnel data to validate the models results and evaluate the models performance. To include atmospheric turbulence effects on dispersion, two different subgrid scale models associated to the Large Eddy Simulation (LES) technique were investigated (Dynamic Smagorinsk and WALE12) and to include the building effects on dispersion in the Gaussian-based models, PRIME13 was used. The use of PRIME was also proposed for FPM as a novelty. Overall, results indicate the use of the CFD/LES might be a useful tool for assessment of odour dispersion and impact in the presence of obstacles and also for the development of Gaussian models. Results also indicate that the proposed FPM, which included the effects of the obstacle based on the PRIME model, is a very useful tool in odour dispersion modelling, due to its simplicity and easy set up if compared to the more complex CFD modelling and even regulatory models AERMOD and CALPUFF. The great advantage of FPM is the possibility of estimating intermittency and also the peak-to-mean (P/M) concentration ratio, which are useful parameters for odour impact assessment. Results obtained in the present work indicate the determination of the plume segments dispersion parameters, as well as the long term dispersion parameters in the near field of the source and obstacle in FPM might be improved and CFD could be used as development tool for this purpose. Key words: Odour control, dispersion, computational fluid dynamics (CFD), mathematical modelling, fluctuating plume Gaussian modelling, Large Eddy Simulation (LES).
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spelling Reis Junior, Neyval CostaSantos, Jane MeriDourado, Harerton OliveiraAlbuquerque, Taciana Toledo de AlmeidaNieckele, Angela OurivioHarion, Jean LucMoreira, Davidson Martins2014-11-19T18:11:25Z2014-11-19T18:11:25Z20132013-07-05The present work investigated odour dispersion modelling in the presence of obstacles (cubical and complex-shaped buildings) under neutral atmospheric conditions employing numerical modelling based on the transport equations (CFD8) as well as on algebraic Gaussian- based models (AERMOD9, CALPUFF10 and FPM11) and using field and wind tunnel data to validate the models results and evaluate the models performance. To include atmospheric turbulence effects on dispersion, two different subgrid scale models associated to the Large Eddy Simulation (LES) technique were investigated (Dynamic Smagorinsk and WALE12) and to include the building effects on dispersion in the Gaussian-based models, PRIME13 was used. The use of PRIME was also proposed for FPM as a novelty. Overall, results indicate the use of the CFD/LES might be a useful tool for assessment of odour dispersion and impact in the presence of obstacles and also for the development of Gaussian models. Results also indicate that the proposed FPM, which included the effects of the obstacle based on the PRIME model, is a very useful tool in odour dispersion modelling, due to its simplicity and easy set up if compared to the more complex CFD modelling and even regulatory models AERMOD and CALPUFF. The great advantage of FPM is the possibility of estimating intermittency and also the peak-to-mean (P/M) concentration ratio, which are useful parameters for odour impact assessment. Results obtained in the present work indicate the determination of the plume segments dispersion parameters, as well as the long term dispersion parameters in the near field of the source and obstacle in FPM might be improved and CFD could be used as development tool for this purpose. Key words: Odour control, dispersion, computational fluid dynamics (CFD), mathematical modelling, fluctuating plume Gaussian modelling, Large Eddy Simulation (LES).O presente trabalho investigou o problema da modelagem da dispersão de compostos odorantes em presença de obstáculos (cúbicos e com forma complexa) sob condição de estabilidade atmosférica neutra. Foi empregada modelagem numérica baseada nas equações de transporte (CFD1) bem como em modelos algébricos baseados na pluma Gausseana (AERMOD2, CALPUFF3 e FPM4). Para a validação dos resultados dos modelos e a avaliação do seu desempenho foram empregados dados de experimentos em túnel de vento e em campo. A fim de incluir os efeitos da turbulência atmosférica na dispersão, dois diferentes modelos de sub-malha associados à Simulação das Grandes Escalas (LES5) foram investigados (Smagorinsky dinâmico e WALE6) e, para a inclusão dos efeitos de obstáculos na dispersão nos modelos Gausseanos, foi empregado o modelo PRIME7. O uso do PRIME também foi proposto para o FPM como uma inovação. De forma geral, os resultados indicam que o uso de CFD/LES é uma ferramenta útil para a investigação da dispersão e o impacto de compostos odorantes em presença de obstáculos e também para desenvolvimento dos modelos Gausseanos. Os resultados também indicam que o modelo FPM proposto, com a inclusão dos efeitos do obstáculo baseado no PRIME também é uma ferramenta muito útil em modelagem da dispersão de odores devido à sua simplicidade e fácil configuração quando comparado a modelos mais complexos como CFD e mesmo os modelos regulatórios AERMOD e CALPUFF. A grande vantagem do FPM é a possibilidade de estimar-se o fator de intermitência e a relação pico-média (P/M), parâmetros úteis para a avaliação do impacto de odores. Os resultados obtidos no presente trabalho indicam que a determinação dos parâmetros de dispersão para os segmentos de pluma, bem como os parâmetros de tempo longo nas proximidades da fonte e do obstáculo no modelo FPM pode ser melhorada e simulações CFD podem ser usadas como uma ferramenta de desenvolvimento para este propósito. Palavras chave: controle de odor, dispersão, fluidodinâmica computacional, modelagem matemática, modelagem gaussiana de pluma flutuante, simulação de grandes vórtices (LES).Texthttp://repositorio.ufes.br/handle/10/1126engUniversidade Federal do Espírito SantoDoutorado em Engenharia ElétricaPrograma de Pós-Graduação em Engenharia ElétricaUFESBRCentro TecnológicoControle de odorDispersãoFluidodinâmica computacionalModelagem matemáticaModelagem gaussiana de pluma flutuanteSimulação de grandes vórtices (LES)628Modelagem da dispersão de odores em ambientes urbanosinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)instname:Universidade Federal do Espírito Santo (UFES)instacron:UFESORIGINALTese.Harerton Oliveira Dourado.pdfTese.Harerton Oliveira Dourado.pdfapplication/pdf10233888http://repositorio.ufes.br/bitstreams/5d4e1a86-fd32-4c66-be73-6e509299ac33/download07430cd5d095105bce4d05998744e1f7MD51CC-LICENSElicense_urllicense_urltext/plain; charset=utf-849http://repositorio.ufes.br/bitstreams/a818ec42-7b03-48b3-94f2-869aba0e9f4a/download4afdbb8c545fd630ea7db775da747b2fMD52license_textlicense_texttext/html; charset=utf-822302http://repositorio.ufes.br/bitstreams/8a7a36c9-4431-4429-b724-0f10fb6d0ae2/download1e0094e9d8adcf16b18effef4ce7ed83MD53license_rdflicense_rdfapplication/rdf+xml; charset=utf-823148http://repositorio.ufes.br/bitstreams/a8e668f2-b8ee-434b-b73c-8a043edc5592/download9da0b6dfac957114c6a7714714b86306MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ufes.br/bitstreams/b65c9591-6ce4-4d6e-8e4c-9ea20db52d9b/download8a4605be74aa9ea9d79846c1fba20a33MD55TEXTTese.Harerton Oliveira Dourado.pdf.txtTese.Harerton Oliveira Dourado.pdf.txtExtracted texttext/plain267345http://repositorio.ufes.br/bitstreams/23f2a74e-a9d4-4a2d-a010-73b908e15dc1/download23293c08c705b8271f3fcc7e2938681dMD5610/11262024-06-28 16:08:19.913oai:repositorio.ufes.br:10/1126http://repositorio.ufes.brRepositório InstitucionalPUBhttp://repositorio.ufes.br/oai/requestopendoar:21082024-06-28T16:08:19Repositório Institucional da Universidade Federal do Espírito Santo (riUfes) - Universidade Federal do Espírito Santo (UFES)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
dc.title.none.fl_str_mv Modelagem da dispersão de odores em ambientes urbanos
title Modelagem da dispersão de odores em ambientes urbanos
spellingShingle Modelagem da dispersão de odores em ambientes urbanos
Dourado, Harerton Oliveira
Controle de odor
Dispersão
Fluidodinâmica computacional
Modelagem matemática
Modelagem gaussiana de pluma flutuante
Simulação de grandes vórtices (LES)
628
title_short Modelagem da dispersão de odores em ambientes urbanos
title_full Modelagem da dispersão de odores em ambientes urbanos
title_fullStr Modelagem da dispersão de odores em ambientes urbanos
title_full_unstemmed Modelagem da dispersão de odores em ambientes urbanos
title_sort Modelagem da dispersão de odores em ambientes urbanos
author Dourado, Harerton Oliveira
author_facet Dourado, Harerton Oliveira
author_role author
dc.contributor.advisor-co1.fl_str_mv Reis Junior, Neyval Costa
dc.contributor.advisor1.fl_str_mv Santos, Jane Meri
dc.contributor.author.fl_str_mv Dourado, Harerton Oliveira
dc.contributor.referee1.fl_str_mv Albuquerque, Taciana Toledo de Almeida
dc.contributor.referee2.fl_str_mv Nieckele, Angela Ourivio
dc.contributor.referee3.fl_str_mv Harion, Jean Luc
dc.contributor.referee4.fl_str_mv Moreira, Davidson Martins
contributor_str_mv Reis Junior, Neyval Costa
Santos, Jane Meri
Albuquerque, Taciana Toledo de Almeida
Nieckele, Angela Ourivio
Harion, Jean Luc
Moreira, Davidson Martins
dc.subject.br-rjbn.none.fl_str_mv Controle de odor
Dispersão
Fluidodinâmica computacional
Modelagem matemática
Modelagem gaussiana de pluma flutuante
Simulação de grandes vórtices (LES)
topic Controle de odor
Dispersão
Fluidodinâmica computacional
Modelagem matemática
Modelagem gaussiana de pluma flutuante
Simulação de grandes vórtices (LES)
628
dc.subject.udc.none.fl_str_mv 628
description The present work investigated odour dispersion modelling in the presence of obstacles (cubical and complex-shaped buildings) under neutral atmospheric conditions employing numerical modelling based on the transport equations (CFD8) as well as on algebraic Gaussian- based models (AERMOD9, CALPUFF10 and FPM11) and using field and wind tunnel data to validate the models results and evaluate the models performance. To include atmospheric turbulence effects on dispersion, two different subgrid scale models associated to the Large Eddy Simulation (LES) technique were investigated (Dynamic Smagorinsk and WALE12) and to include the building effects on dispersion in the Gaussian-based models, PRIME13 was used. The use of PRIME was also proposed for FPM as a novelty. Overall, results indicate the use of the CFD/LES might be a useful tool for assessment of odour dispersion and impact in the presence of obstacles and also for the development of Gaussian models. Results also indicate that the proposed FPM, which included the effects of the obstacle based on the PRIME model, is a very useful tool in odour dispersion modelling, due to its simplicity and easy set up if compared to the more complex CFD modelling and even regulatory models AERMOD and CALPUFF. The great advantage of FPM is the possibility of estimating intermittency and also the peak-to-mean (P/M) concentration ratio, which are useful parameters for odour impact assessment. Results obtained in the present work indicate the determination of the plume segments dispersion parameters, as well as the long term dispersion parameters in the near field of the source and obstacle in FPM might be improved and CFD could be used as development tool for this purpose. Key words: Odour control, dispersion, computational fluid dynamics (CFD), mathematical modelling, fluctuating plume Gaussian modelling, Large Eddy Simulation (LES).
publishDate 2013
dc.date.submitted.none.fl_str_mv 2013-07-05
dc.date.issued.fl_str_mv 2013
dc.date.accessioned.fl_str_mv 2014-11-19T18:11:25Z
dc.date.available.fl_str_mv 2014-11-19T18:11:25Z
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dc.identifier.uri.fl_str_mv http://repositorio.ufes.br/handle/10/1126
url http://repositorio.ufes.br/handle/10/1126
dc.language.iso.fl_str_mv eng
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dc.format.none.fl_str_mv Text
dc.publisher.none.fl_str_mv Universidade Federal do Espírito Santo
Doutorado em Engenharia Elétrica
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Engenharia Elétrica
dc.publisher.initials.fl_str_mv UFES
dc.publisher.country.fl_str_mv BR
dc.publisher.department.fl_str_mv Centro Tecnológico
publisher.none.fl_str_mv Universidade Federal do Espírito Santo
Doutorado em Engenharia Elétrica
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