• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 2
  • 1
  • Tagged with
  • 3
  • 3
  • 3
  • 3
  • 3
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Concentration fluctuations of a passive scalar in a turbulent boundary layer

Nironi, Chiara 02 July 2013 (has links) (PDF)
This experimental study analyses the dynamics of concentration fluctuations in a passive plume emitted by a point source within the turbulent boundary layer. We aim to extend the popular study of Fackrell and Robins (1982) about concentration fluctuations and fluxes from point sources by including third and fourth moments of concentration. We also further inquire into the influence of source conditions, such as the source size, source elevation and emission velocity, on higher order concentration moments. The data set is completed by a detailed description of the velocity statistics within the TBL, with exhaustive information on both the temporal and spatial structure of the flow. The experimental data-set has been used to test two different modeling ap- proaches: an analytical meandering plume model (in one and in three dimen- sions) and a Lagrangian stochastic micro-mixing model.
2

Desenvolvimento de um modelo lagrangeano para dispersão de poluentes em condições de vento fraco

Sallet, Marieli, Sallet, Marieli 23 February 2007 (has links)
Made available in DSpace on 2014-08-20T14:25:46Z (GMT). No. of bitstreams: 1 dissertacao_marieli_sallet.pdf: 231023 bytes, checksum: f445526b62fbfcde40fb1bc5ca90923a (MD5) Previous issue date: 2007-02-23 / Currently, the search for analytical solutions for the dispersion problems is one of the main research subjects in the pollutant dispersion modeling. These solutions become important due to the intention to obtain dispersion models that generate reliable results in a small computational time, which are of great interest for regulatory air quality applications. Lagrangian particle models are an important and effective tool to simulate the atmospheric dispersion of airborne pollutants. These models are based on the Langevin equation, which is derived from the hypothesis that the velocity is given by the combination between a deterministic term and a stochastic term. In this work is presented a new Lagrangian particle model to simulate the pollutant dispersion in low wind speed conditions. During low wind speed, the diffusion of a pollutant in the planetary boundary layer (PBL) is indefinite and it has been observed that the plume is subject to a great deal of horizontal undulations, which are called plume meandering. The method proposed leads to a stochastic integral equation whose solution has been obtained through the Method of Successive Approximations or Picard s Iteration Method. The integral equation is written in terms of the real and imaginary parts of the complex function before performing the multiplication of the integrating factor, expressed by the Euler formula, inside and outside of the integral solution. To take account the meandering effect, the Frenkiel s Eulerian autocorrelation functions for low wind conditions is included naturally in the model. The new approach has been evaluated through the comparison with experimental data and other different dispersion models. Particularly, the results obtained by the model agree very well with the experimental data, indicating the model represents the dispersion process correctly in low wind speed conditions. It is also possible to verify that the new model results are better than ones obtained by the other models. The analytical feature of the technique and the natural inclusion of the Frenkiel s Eulerian autocorrelation function become the model more accurate than other models. / Atualmente, a busca por soluções analíticas para os problemas de dispersão é um dos principais assuntos de pesquisa na modelagem da dispersão de poluentes. Estas soluções tornam-se importantes devido à intenção de obter modelos de dispersão que geram resultados confiáveis em um tempo computacional pequeno, que são de grande interesse para aplicações no controle da qualidade do ar. Modelos de partícula Lagrangeano são uma ferramenta importante e eficaz para simular a dispersão atmosférica de poluentes do ar. Esses modelos são baseados na equação de Langevin, que é derivada da hipótese que a velocidade é dada por uma combinação entre um termo determinístico e um termo estocástico. Neste trabalho é apresentado um novo modelo de partícula Lagrangeano para simular a dispersão de poluentes em condições de velocidade de vento fraco. Durante a velocidade de vento fraco, a difusão de um poluente na Camada Limite Planetária (CLP) é indefinida e tem sido observado que a pluma está sujeita a grandes ondulações horizontais, que são chamadas meandro do vento. O método proposto leva a uma equação integral estocástica cuja solução é obtida através do Método das Aproximações Sucessivas ou Método Iterativo de Picard. A equação integral é escrita em termos das partes real e imaginária da função complexa antes de realizar a multiplicação do fator integrante, expresso pela fórmula de Euler, dentro e fora da solução integral. Para considerar o efeito do meandro, as funções de autocorrelação Euleriana de Frenkiel para condições de vento fraco são incluídas naturalmente no modelo. A nova aproximação foi avaliada através da comparação com dados experimentais e outros diferentes modelos de dispersão. Particularmente, os resultados obtidos pelo modelo concordam muito bem com os dados experimentais, indicando que o modelo representa o processo de dispersão corretamente em condições de velocidade de vento fraco. Também é possível verificar que os resultados do novo modelo são melhores do que os obtidos pelos outros modelos. A característica analítica da técnica e a inclusão natural da função de autocorrelação Euleriana de Frenkiel tornam o modelo mais exato que os outros modelos.
3

Concentration fluctuations of a passive scalar in a turbulent boundary layer / Les fluctuations de concentration d'un scalaire passif dans une couche limite turbulente

Nironi, Chiara 02 July 2013 (has links)
Cette étude, menée principalement par des moyens expérimentaux, analyse la dynamique des fluctuations de concentration produites au sein d’un panache d’un scalaire passif émis par une source ponctuelle dans une couche limite turbulente. En étendant le travail de Fackrell and Robins (1982) sur les fluctuations de concentration, on décrit l’évolution des quatre premiers moments de la concentration et on étudie l’influence des conditions à la source (telles que la taille et la hauteur de la source et la vitesse de sortie) sur les moments mêmes. L’étude est complétée par une description détaillée des statistiques du champ de vitesse dans la couche limite, comprenant des informations sur la structure spatiale et temporelle de la turbulence. Cette base de données expérimentale a été utilisée pour valider deux différentes approches à la modélisation de la dispersion: un modèle analytique de meandering et un modèle Lagrangien stochastique avec un schéma de micro mélange. / This experimental study analyses the dynamics of concentration fluctuations in a passive plume emitted by a point source within the turbulent boundary layer. We aim to extend the popular study of Fackrell and Robins (1982) about concentration fluctuations and fluxes from point sources by including third and fourth moments of concentration. We also further inquire into the influence of source conditions, such as the source size, source elevation and emission velocity, on higher order concentration moments. The data set is completed by a detailed description of the velocity statistics within the TBL, with exhaustive information on both the temporal and spatial structure of the flow. The experimental data-set has been used to test two different modeling ap- proaches: an analytical meandering plume model (in one and in three dimen- sions) and a Lagrangian stochastic micro-mixing model.

Page generated in 0.0836 seconds