Fundamentals of Direct Inverse CFD Modeling to Detect Air Pollution Sources in Urban Areas

Journals Menu

Follow SCIRP

ISSN Print: 2168-1562
ISSN Online: 2168-1570
www.scirp.org/journal/cweee
E-mail: cweee@scirp.org

"Fundamentals of Direct Inverse CFD Modeling to Detect Air Pollution Sources in Urban Areas"
written by Mahmoud Bady,
published by Computational Water, Energy, and Environmental Engineering, Vol.2 No.2, 2013

has been cited by the following article(s):

[1]	Particulate material 2.5 change in the city using EURO4 urban buses technology case study: Arak City, Iran
	International Journal of …, 2022

[2]	Estimating accidental pollutant releases in the built environment from turbulent concentration signals
	Atmospheric Environment, 2017

[3]	Assuring asset integrity through improving the accuracy of leakage source identification of a permanently installed subsea leak detection system using artificial neural …
	2015

[4]	Assuring asset integrity through improving the accuracy of leakage source identification of a permanently installed subsea leak detection system using artificial neural networks
	2015

[5]	基于 OpenFOAM 的城市街区毒气扩散模拟
	环境科学研究, 2015

[6]	Assuring asset integrity through improving the accuracy of leakage source identification of a permanently installed subsea leak detection system using artificial neural …
	2015

[7]	CFD modelling for atmospheric pollutants/aerosols studies within the complex terrains of urban areas and industrial sites
	International Journal of Environment and Pollution?, 2014

[1]	Particulate material 2.5 change in the city using EURO4 urban buses technology case study: Arak City, Iran International Journal of Environmental Science and Technology, 2022 DOI:10.1007/s13762-022-04205-9

[2]	Air pollution distribution in Arak city considering the effects of neighboring pollutant industries and urban traffics International Journal of Energy and Environmental Engineering, 2021 DOI:10.1007/s40095-020-00379-5

[3]	Estimating accidental pollutant releases in the built environment from turbulent concentration signals Atmospheric Environment, 2017 DOI:10.1016/j.atmosenv.2016.10.050

Follow SCIRP