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The Solution of Semi-empirical Equation of Turbulent Diffusion in Problems of Polluting Impurity Transfer by Gauss Approach
- Source :
- FNC/MobiSPC
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- The analysis of the solution of the semi-empirical solution of turbulent diffusion in problems of polluting impurity transfer is carried out by Gauss approach. It is assumed that there is a certain occupied industrial point, which has one or several sources of the pollution, the arrangement of which is determined by coordinates x, y, z. For calculation of average impurity concentration from a point source the solution of semi-empirical equation by Gaussian function of impurity distribution, obtained by a method of Green's function was used. Furthermore, the normalization of the key parameters of the problem is carried out and the initial data are defined. By means of the obtained equation, the model of quantity assessment of the aerosol polluting substances arriving from a source with final and continuous duration of action is made. Thus, the considered computational and analytical model of methodology of assessing the concentration of polluting substances is applicable for applied problems of operational control of the condition of industrial region. Proposed model can be adapted to the air pollution monitoring robotic system.
- Subjects :
- Pollution
Normalization (statistics)
0209 industrial biotechnology
Mathematical optimization
concentration
Computer science
Point source
Gauss function
media_common.quotation_subject
Air pollution
02 engineering and technology
equation of turbulent diffusion
medicine.disease_cause
symbols.namesake
020901 industrial engineering & automation
pollution monitoring robot system
0202 electrical engineering, electronic engineering, information engineering
Gaussian function
medicine
Applied mathematics
Air quality index
General Environmental Science
media_common
Turbulent diffusion
Gauss
Function (mathematics)
air quality
Action (physics)
Aerosol
symbols
General Earth and Planetary Sciences
020201 artificial intelligence & image processing
Subjects
Details
- ISSN :
- 18770509
- Volume :
- 94
- Database :
- OpenAIRE
- Journal :
- Procedia Computer Science
- Accession number :
- edsair.doi.dedup.....5833b7a0825d72570876529c56a01970
- Full Text :
- https://doi.org/10.1016/j.procs.2016.08.057