A new capability for Rapid Threat Assessment (RTA) due to explosive threats is presented.  The audience for the new capability are non-technical users who need such information for planning.  The RTA determines the maximum pressure load applied on building structures from an explosion in an urban environment and the lethal regions inside an enclosed space from the detonation of a threat that combines an explosive and projectiles.  The former functionality considers a few alternative layouts for the urban environment and allows a user to select the type of layout, the main dimensions of the layout, the size of the explosive and its relative placement with respect to the buildings.  This information is used for determining the level of blast worthiness that the buildings must exhibit in order to avoid catastrophic damage or the level of expected damage from an explosion.  A Machine Learning (ML) approach is used for creating the answer for the maximum pressure load from a large number of high fidelity simulations that have been computed for each layout.  The main dimensions of each layout, the size of the explosive, and its relative placement varied in each simulation.   The results are used for training a ML model which is then utilized for predictions within the RTA tool.  Simulation results are validated through comparison to published test data for two urban configurations.  The second functionality of the RTA utilizes semi-empirical expressions for determining the initial velocity of the projectiles and a numerical solution to a system of ordinary differential equations for determining their trajectories.  The lethality of the projectiles is determined from their velocity and their trajectory time histories.  The lethal region from the blast pressure is based on semi-empirical equations for peak pressure loads.  The theoretical background, the validation, and the value of the RTA capability are presented.

Keywords
ASSESSMENT,EVALUATION,FIDELITY,MACHINE LEARNING,MODELING,RAPID MODELING,SIMULATIONS,URBAN ENVIRONMENT

Additional Keywords
blast event simulation