A Graphics Processing Unit (GPU) Approach to Large Eddy Simulation (LES) for Transport and Contaminant Dispersion

被引:8
作者
Bieringer, Paul E. [1 ]
Pina, Aaron J. [1 ,2 ]
Lorenzetti, David M. [3 ]
Jonker, Harmen J. J. [4 ]
Sohn, Michael D. [3 ]
Annunzio, Andrew J. [1 ]
Fry, Richard N., Jr. [5 ]
机构
[1] Aeris, 1849 Cherry St,Suite 6, Louisville, CO 80027 USA
[2] NASA, 300 E St SW, Washington, DC 20546 USA
[3] Lawrence Berkeley Natl Lab, One Cydotron Rd, Berkeley, CA 94720 USA
[4] Whiffle, Molengraaffsingel 12, NL-2629 JD Delft, Netherlands
[5] Def Threat Reduct Agcy, 8725 John J Kingman Rd, Ft Belvoir, VA 22060 USA
关键词
large eddy simulation; graphics processing unit computing; atmospheric dispersion modelling; microscale dispersion; model validation; CONVECTIVE BOUNDARY-LAYER; CONDORS FIELD EXPERIMENT; NUMERICAL-SIMULATION; STOCHASTIC-MODELS; PLUME DISPERSION; LABORATORY MODEL; WEATHER RESEARCH; FLUCTUATIONS; TRAJECTORIES; FORMULATION;
D O I
10.3390/atmos12070890
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Recent advances in the development of large eddy simulation (LES) atmospheric models with corresponding atmospheric transport and dispersion (AT&D) modeling capabilities have made it possible to simulate short, time-averaged, single realizations of pollutant dispersion at the spatial and temporal resolution necessary for common atmospheric dispersion needs, such as designing air sampling networks, assessing pollutant sensor system performance, and characterizing the impact of airborne materials on human health. The high computational burden required to form an ensemble of single-realization dispersion solutions using an LES and coupled AT&D model has, until recently, limited its use to a few proof-of-concept studies. An example of an LES model that can meet the temporal and spatial resolution and computational requirements of these applications is the joint outdoor-indoor urban large eddy simulation (JOULES). A key enabling element within JOULES is the computationally efficient graphics processing unit (GPU)-based LES, which is on the order of 150 times faster than if the LES contaminant dispersion simulations were executed on a central processing unit (CPU) computing platform. JOULES is capable of resolving the turbulence components at a suitable scale for both open terrain and urban landscapes, e.g., owing to varying environmental conditions and a diverse building topology. In this paper, we describe the JOULES modeling system, prior efforts to validate the accuracy of its meteorological simulations, and current results from an evaluation that uses ensembles of dispersion solutions for unstable, neutral, and stable static stability conditions in an open terrain environment.
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页数:24
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