A computational study of particulate emissions from Old Moor Quarry, UK. Issue 172 (January 2018)
- Record Type:
- Journal Article
- Title:
- A computational study of particulate emissions from Old Moor Quarry, UK. Issue 172 (January 2018)
- Main Title:
- A computational study of particulate emissions from Old Moor Quarry, UK
- Authors:
- Joseph, G.M.D.
Lowndes, I.S.
Hargreaves, D.M. - Abstract:
- Abstract: This paper presents an evaluation of a buoyancy-modified k − ε dust dispersion model for predicting fugitive dust deposition from a surface quarry. The dust clouds are modelled as volumetric emissions and their dispersion simulated by coupling the flow-field with stochastic tracking of the particulates. The coefficients of the turbulence model are modified and source terms are added to the turbulence equations to permit simulation of both adiabatic and diabatic atmospheric stability conditions. These modifications ensure compatibility with Monin-Obukhuv similarity scaling of the atmospheric surface layer. Also, mesoscale wind direction variability is included. The Monin-Obukhuv scaling parameters have been derived from routine meteorological data recorded during a month-long monitoring campaign conducted at the quarry. Dust deposition measurements from a network of Frisbee deposition gauges are used to validate the predictions of the CFD model. A number of statistical performance metrics have been applied to evaluate the degree of uncertainty in the predictions. The dust deposition predictions of the CFD model are compared to those of the UK-ADMS, to demonstrate how the treatment of the terrain in the CFD model improves the accuracy of the deposition predictions. Highlights: In-pit deposition is underestimated without a realistic flow field CFD models of neutral conditions are not sufficient Stability class and in-pit flows are key to deposition The in-pitAbstract: This paper presents an evaluation of a buoyancy-modified k − ε dust dispersion model for predicting fugitive dust deposition from a surface quarry. The dust clouds are modelled as volumetric emissions and their dispersion simulated by coupling the flow-field with stochastic tracking of the particulates. The coefficients of the turbulence model are modified and source terms are added to the turbulence equations to permit simulation of both adiabatic and diabatic atmospheric stability conditions. These modifications ensure compatibility with Monin-Obukhuv similarity scaling of the atmospheric surface layer. Also, mesoscale wind direction variability is included. The Monin-Obukhuv scaling parameters have been derived from routine meteorological data recorded during a month-long monitoring campaign conducted at the quarry. Dust deposition measurements from a network of Frisbee deposition gauges are used to validate the predictions of the CFD model. A number of statistical performance metrics have been applied to evaluate the degree of uncertainty in the predictions. The dust deposition predictions of the CFD model are compared to those of the UK-ADMS, to demonstrate how the treatment of the terrain in the CFD model improves the accuracy of the deposition predictions. Highlights: In-pit deposition is underestimated without a realistic flow field CFD models of neutral conditions are not sufficient Stability class and in-pit flows are key to deposition The in-pit topography and surrounding terrain must be considered … (more)
- Is Part Of:
- Journal of wind engineering and industrial aerodynamics. Issue 172(2017)
- Journal:
- Journal of wind engineering and industrial aerodynamics
- Issue:
- Issue 172(2017)
- Issue Display:
- Volume 172, Issue 172 (2017)
- Year:
- 2017
- Volume:
- 172
- Issue:
- 172
- Issue Sort Value:
- 2017-0172-0172-0000
- Page Start:
- 68
- Page End:
- 84
- Publication Date:
- 2018-01
- Subjects:
- Particulates -- Computational fluid dynamics -- Deposition
Wind-pressure -- Periodicals
Buildings -- Aerodynamics -- Periodicals
Pression du vent -- Périodiques
Constructions -- Aérodynamique -- Périodiques
Buildings -- Aerodynamics
Wind-pressure
Periodicals - Journal URLs:
- http://www.sciencedirect.com/science/journal/01676105 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jweia.2017.10.018 ↗
- Languages:
- English
- ISSNs:
- 0167-6105
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5072.632000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5511.xml