To explore the implications of temporal and spatial averaging on this type of injury and casualty calculation we used a new microscale atmospheric and atmospheric transport and dispersion (AT&D) modeling capability called the Joint Outdoor-indoor Urban Large Eddy Simulation (JOULES) system. JOULES has been designed to provide high-fidelity simulations of urban airborne hazardous materials that can be used to the support the testing, evaluation, and validation of operational urban modeling tools, and the development of scientific enhancements to these systems. A key enabling technology within JOULES is a Large Eddy Simulation (LES) model that has been implemented on a Graphics Processing Unit (GPU) computing platform. The GPU-LES model provides a simulation platform that is significantly faster than the current generation of Central Processing Unit (CPU) based LES models and enables the development of ensembles of AT&D simulations. JOULES has been extensively validated against open terrain and urban laboratory experiments and field trials and is shown to be able to accurately reconstruct the these dispersion scenarios. Recently this system has been further augmented with an indoor model that can calculate the exchange of hazardous airborne materials across the building envelope and provide indoor concentrations.
In this presentation we will provide a description of the JOULES system and a brief summary of the validation studies that have been undertaken to demonstrate its accuracy. We will also present results from a study where JOULES was used to illustrate the relative inaccuracies associated with calculating human casualty and injury estimates from the ensemble averaged AT&D simulations available in the current generation of emergency response tools for open terrain, urban, and indoor environments. Results will be shown for a variety of idealized scenarios that illustrate the impact of making outdoor and indoor casualty estimates from an ensemble of human toxic load calculations vs. making a single human-effects estimate from an ensemble of AT&D solutions.