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Modeling of injury risk from nonlethal weapons including flash-bangs is a critical step in the design, acquisition, and application of such devices for military purposes. One flash-bang design concept currently being developed involves multiple, area-distributed flash-bangs. It is particularly difficult to model the variation inherent in operational settings employing such devices due to the randomness of flash-bang detonation positioning relative to targets. The problem is exacerbated by uncertainty related to changes in the mechanical properties of auditory system tissues and contraction of muscles in the middle ear (the acoustic reflex), which can both immediately follow impulse-noise exposure. In this article, we demonstrate a methodology to quantify uncertainty in injury risk estimation related to exposure to multiple area-distributed flash-bang impulses in short periods of time and analyze the effects of factors such as the number of impulses, their spatial distribution, and the uncertainties in their parameters on estimated injury risk. Materials and Methods We conducted Monte Carlo simulations of dispersion and timing of a mortar-and-submunition flash-bang device that distributes submunitions over an area, using the Auditory 4.5 model developed by L3 Applied Technologies to estimate the risk of hearing loss (permanent threshold shift) in an exposure area. We bound injury risk estimates by applying limiting assumptions for dose accumulation rules applied to short inter-pulse intervals and varied impulse-noise-intensity exposure characteristic of multi-impulse flash-bangs. The upper bound of risk assumes no trading of risk between the number of impulses and intensity of individual impulses, while the lower bound assumes a perfectly protective acoustic reflex. Results In general, the risk to individuals standing in the most hazardous zone of the simulation is quite sensitive to the pattern of submunitions, relative to the sensitivity for those standing farther from that zone. Larger mortar burst radii (distributing submunitions over a wider area) reduce expected peak risk, while increasing the number of submunitions, the intensity of individual impulses, or the uncertainty in impulse intensity increases expected risk. We find that injury risk calculations must factor in device output variation because the injury risk curve in the flash-bang dose regime is asymmetric. We also find that increased numbers of submunitions increase the peak risk in an area more rapidly than scene-averaged risk and that the uncertainty related to dose accumulation in the acoustic reflex regime can be substantial for large numbers of submunitions and should not be ignored. Conclusions This work provides a methodology for exploring both the role of device parameters and the choice of dose accumulation rule in estimating the risk of significant injury and associated uncertainty for multi-impulse, area-distributed flash-bang exposures. This analysis can inform decisions about the design of flash-bangs and training for their operational usage. The methodology can be extended to other device designs or deployment concepts to generate risk maps and injury risk uncertainty ranges. This work does not account for additional injury types beyond permanent threshold shift that may occur as a result of flash-bang exposure. A useful extension of this work would be similar work connecting design and operational parameters to human effectiveness.

Modeling Injury Risk From Multiple-Impulse, Area-Distributed Flash-bangs Using an Uncertainty Bounding Approach to Dose Accumulation