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

Paul E Bieringer,David M Lorenzetti,Andrew J Annunzio,Aaron J Piña,Michael D Sohn,Richard N Fry,Harmen J J Jonker

doi:10.3390/atmos12070890

Abstract

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.

Highlights

The methods used to simulate outdoor dispersion of airborne materials range from simple, computationally efficient empirical approaches to complex computational fluid dynamics (CFD)-based approaches
This section describes the observational data used in the model evaluation, the approach used to develop the ensembles of dispersion solutions, the analysis methodology, and the metrics used to compare the simulations to the observations
Calculations of the metrics for a single dispersion realization from the GPULES model simulations are represented by either grey lines or blue dots and are plotted on the figure to illustrate the distribution of solutions

Summary

Introduction

The methods used to simulate outdoor dispersion of airborne materials range from simple, computationally efficient empirical approaches to complex computational fluid dynamics (CFD)-based approaches. To produce ensembles of “single-realization” dispersion solutions, the CFD model is initialized with the mean atmospheric conditions that can be measured and an ensemble of uncorrelated dispersion solutions can be created by moving the release (e.g., in location and/or time) within the turbulent flow This approach provides a distribution of dispersion solutions that can be averaged (in time and space) to determine the mean properties of downwind dispersion analogous to the products produced by standard Gaussian plume and puff models. This distribution of dispersion solutions can be sampled/analyzed to understand the variance from the mean and the skewness of the distribution if present [1]. The computational expense associated with producing these ensembles has, until recently, limited the use of CFD models for dispersion to research and academic applications

Methods

Results

Conclusion