Due to the great concern that blast overpressure can cause mild traumatic brain injury (mTBI), there is strong interest in putting sensors on warfighters to collect theater data for correlation with medical outcomes. One approach is to mount multiple pressure sensors on the warfighter to measure the blast overpressure environment. An event recognition algorithm that is based on the sensor data recordings is needed to reconstruct the incident blast wave that impacts the warfighter. Blast impingement pressure on an object is highly dependent on the angle of incidence at the point of impact; shadowing and recirculating flow effects can complicate the sensor data pattern. Using computational fluid dynamics (CFD) simulation, the present work demonstrates that for a warfighter in an upright posture in an open blast environment, a three-sensor event recognition algorithm can be developed to reconstruct the incident blast wave (generally characterized as a Friedlander wave). Three-dimensional Navier-Stokes’ based CFD simulations were performed to predict pressure recordings at the three sensor locations for a range of horizontal blast waves impacting the warfighter at all angles of incidence. The predicted peak pressures and durations were recorded and stored in a lookup table. Using an inverse problem approach, it was found that based on the three-sensor data recorded for each event, an algorithm exists for reconstructing the blast incident wave. The established event recognition algorithm is limited to warfighters with upright posture in open blast. Work is being continued to generalize and extend the method to include complex blasts involving multiple reflections and other posture orientations.

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