Camila Pinto da Costa
Universidade Federal de Pelotas
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Featured researches published by Camila Pinto da Costa.
Archive | 2010
Camila Pinto da Costa; M.T. Vilhena; T. Tirabassi
Transport and diffusion models of air pollution are based either on simple techniques, such as the Gaussian approach, or on more complex algorithms, such as the K-theory differential equation. The Gaussian equation is an easy and fast method, which, however, cannot properly simulate complex nonhomogeneous conditions. The K-theory can accept virtually any complex meteorological input, but generally requires numerical integration, which is computationally expensive and is often affected by large numerical advection errors. Conversely, Gaussian models are fast, simple, do not require complex meteorological input, and describe the diffusive transport in an Eulerian framework, making easy use of the Eulerian nature of measurements.
Revista Brasileira De Meteorologia | 2018
Camila Pinto da Costa; Leslie D. Pérez-Fernández; Karine Rui; Julián Bravo-Castillero
The advection-diffusion multilayer method (ADMM) produces accurate semi-analytical solutions of initial/boundaryvalue problems for advection-diffusion equations with variable coefficients that model pollutant dispersion in the atmosphere, and exhibits lower computational cost in comparison to other integral transform-based methods. However, in operative situations such as natural/industrial disasters resulting in the release of pollutants to the atmosphere, it is necessary to assess rapidly and accurately the ground-level distribution of pollutant concentration in order to minimize the impact on health and economy. Here, in order to accelerate the availability of results with little loss of accuracy, the ADMM is combined with mathematical homogenization, whose use in pollutant dispersion modeling seems to be new. The proposed approach is compared with the direct application of the ADMM and to the observations of the Hanford experiment in order to access both its accuracy and computational cost, for stable atmospheric conditions and considering the influence of deposition velocity. The results show that the combination of the ADMM and mathematical homogeniRevista Brasileira de Meteorologia, v. 33, n. 2, 329-335, 2018 rbmet.org.br DOI: http://dx.doi.org/10.1590/0102-7786332014
Ciência e Natura | 2016
Karine Rui; Camila Pinto da Costa
In this work, we present the resolution of the three-dimensional stationary advection-diffusion equation, through the GIADMT technique, considering the nonlocal closure for turbulent flow, using two different parameterization for the countergradient, one proposal by Cuijpers e Holtslag (1998) and another proposed by Roberti et al. (2004). The concentration of pollutants is estimated and compared with the observed data in Copenhagen experiment using different parameterization for the vertical turbulent diffusion coefficient.
Ciência e Natura | 2013
Cristiane Venzke; Camila Pinto da Costa; Rejane Pergher
Neste trabalho iremos empregar uma nova formulacao para o termo de contragradiente, proposta por Roberti et al. (2004), ao resolver a equacao de difusao-adveccao na Camada Limite Convectiva (CLC) atraves do metodo ADMM (Advection Diffusion Multilayer Method). Consideramos uma modelagem mais realistica, levando em conta os efeitos do termo de contragradiente caracterizado pelo transporte nao-local da dispersao.
Journal of Engineering Mathematics | 2012
Camila Pinto da Costa; Tiziano Tirabassi; Marco T. Vilhena; Davidson Martins Moreira
Revista Mundi Engenharia, Tecnologia e Gestão (ISSN: 2525-4782) | 2018
Daiane Frighetto Frighetto; Camila Pinto da Costa; Alexandre Molter
Revista Mundi Engenharia, Tecnologia e Gestão (ISSN: 2525-4782) | 2018
Daiane Frighetto Frighetto; Camila Pinto da Costa; Alexandre Molter
Proceeding Series of the Brazilian Society of Computational and Applied Mathematics | 2018
Daiane Frighetto Frighetto; Camila Pinto da Costa; Alexandre Molter
Scientia Plena | 2017
Karine Rui; Camila Pinto da Costa; Leslie D. Pérez-Fernández; Julián Bravo-Castillero
Revista Brasileira de Computação Aplicada | 2017
Noé Franco de Jesus; Camila Pinto da Costa; Leslie Darien Pérez Fernández; Julián Bravo Castillero