Sara Hakim, N. Laaroussi, M. Garoum, Boulos Alam, A. Feiz
{"title":"Modeling of Atmospheric Dispersion of Pollutants Through the Building using a Lagrangian Stochastic Model","authors":"Sara Hakim, N. Laaroussi, M. Garoum, Boulos Alam, A. Feiz","doi":"10.1109/IRSEC53969.2021.9741123","DOIUrl":null,"url":null,"abstract":"In this paper, we will present a summary of recent studies made to model the atmospheric dispersion around a building using Computational Fluid Dynamics (CFD). So we will focus on the studies made by Bahlali et al, who uses the Lagrangian stochastic CFD model implemented in Code_Saturne to model our problem taking into account atmospheric stratification. Our work essentially consists in showing the importance of this model by commenting on the results of the work obtained by Bahlali et al.","PeriodicalId":361856,"journal":{"name":"2021 9th International Renewable and Sustainable Energy Conference (IRSEC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 9th International Renewable and Sustainable Energy Conference (IRSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRSEC53969.2021.9741123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we will present a summary of recent studies made to model the atmospheric dispersion around a building using Computational Fluid Dynamics (CFD). So we will focus on the studies made by Bahlali et al, who uses the Lagrangian stochastic CFD model implemented in Code_Saturne to model our problem taking into account atmospheric stratification. Our work essentially consists in showing the importance of this model by commenting on the results of the work obtained by Bahlali et al.