Quantification of Cumulative Blast Dose to Servicemembers from Repeated Exposures During Heavy Weapon firing in Combat Scenarios

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Advanced Computing and Software OBJECTIVE: Develop computational modeling tools to reconstruct heavy weapon repeated firing events in combat scenarios and to quantify blast exposure and risk injury scores to service members. These tools should enable accurate prediction of the blast dose from a single exposure and the cumulative blast dose from repeated exposures encountered during prolonged firing in combat operations. In combination with the previous effort on computational blast injury modeling, this project will provide supporting information to answer questions from the battalion commanders and the command surgeons. DESCRIPTION: U.S. Servicemembers experience repeated blast exposures during training and combat. Cumulative effects of such exposure may cause short- and long-term cognitive and neurological effects [1,2, 3]. Unfortunately, objective quantification of the acute and cumulative dose to the whole body and to injury sensitive organs, human brain in particular, remains elusive. Without quantifiable blast dose in the battlefield scenarios, it is difficult to establish correlation between blast exposure and neuro-deficits. Prediction of the single exposure blast loads on the warfighter body (dose) is feasible using either computationally expensive computational fluid dynamics (CFD) tools [4,5] or experimentally calibrated fast running tools [6,7]. Concurrently, a large database has been established characterizing weapon blast signatures from field tests with Tier 1 weapon systems [8]. The video data of the weapon firing crew during training can be used to reconstruct the weapon training scene involving all serviceman. However, weapon firing scene in combat can be vastly different from the weapon firing on training ranges in terms of firing place (desert, concrete, soft sol, gravel, forest, trench, through a window), environment, number and type of fired rounds, firing frequency, proximity of serviceman, and other variables. Currently there are no computational models that could quantify the cumulative blast dose from repeated blast exposures. Predicted or recorded maximum blast overpressure and impulse on the human body on a training range are useful but not sufficient for physics-based objective quantification of the cumulative dose. Self-reported, carrier-long cumulative exposure blast dose measures (e.g., GBEV) have high uncertainty and cannot be used in the acute period [8]. Servicemen who are repeatedly exposed to weapons blasts often cannot pinpoint a specific traumatic event, recall their role in the combat crew, recall the number and type of fired rounds or remember their altered state of consciousness [1]. PHASE I: In Phase I the modeling framework should be validated on at least three weapons systems, including mortar, artillery and shoulder mounted rifles using existing field weapon training data. A novel, mechanistic model of the cumulative blast dose from repeated exposures in various combat scenarios should be formulated and discussed with the DTRA team. PHASE II: In Phase II, the work shall focus on generating blast exposure scenes for key Tier I weapons and validating the blast dose model on existing field data for both the training and live-fire rounds. It will also include virtually reconstructing weapon firing scenes with prolonged multiple firings typical to combat, developing a reduced-order model of blast energy deposition/absorption in injury-sensitive organs, and creating a user-friendly version of the computational tools for different computing platforms, such as tablets and cell phones. Finally, these tools shall be applicable for incorporation into the DTRA Reachback environment providing 24/7 supporting to customers from US Services. PHASE III DUAL USE APPLICATIONS: The program will be used to support Reachback operation once the model is constructed. REFERENCES: 1. Dave Philipps, Signs of Brain Injury in Mortar Soldiers: Guys Are Getting Destroyed , New Your Times, Published May 3, 2024; 2. McEvoy CB, Crabtree A, Powell JR, Meabon JS, Mihalik JP. Cumulative blast exposure estimate model for Special Operations Forces combat Soldiers. Journal of neurotrauma. 2023 Feb 1;40(3-4):318-25.; 3. Roy MJ, Keyser DO, Rowe SS, Hernandez RS, Dovel M, Romero H, Lee D, Menezes M, Magee E, Brooks DJ, Lai C. Methodology of the INVestigating traIning assoCiated blasT pAthology (INVICTA) study. BMC medical research methodology. 2022 Dec 13;22(1):317.; 4. Tan XG, Matic P. Simulation of cumulative exposure statistics for blast pressure transmission into the brain. Military Medicine. 2020 Jan 7;185(Supplement_1):214-226.; 5. Gupta RK, Przekwas A. Mathematical models of blast-induced TBI: current status, challenges, and prospects. Frontiers in neurology. 2013 May 30;4:43326.; 6. Przekwas A, Garimella HT, Chen ZJ, Zehnbauer T, Gupta RK, Skotak M, Carr WS, Kamimori GH. Fast-running tools for personalized monitoring of blast exposure in military training and operations. Military medicine. 2021 Jan;186(Supplement_1):529-36; 7. Wiri, S., Needham, C., Ortley, D., Duckworth, J., Gonzales, A., Walilko, T. and Bentley, T.B., 2022. Development of a fast-running algorithm to approximate incident blast parameters using body-mounted sensor measurements. Military medicine, 187(11-12), pp.e1354-e1362.; 8. Wiri, S., Massow, T., Reid, J., Whitty, J., Dunbar, C., Graves, W., ... & Duckworth, J. L. (2023). Dynamic monitoring of service members to quantify blast exposure levels during combat training using BlackBox Biometrics Blast Gauges: explosive breaching, shoulder-fired weapons, artillery, mortars, and 0.50 caliber guns. Frontiers in neurology, 14, 1175671.; 9. Modica, LT Claire M., et al. "Development of a blast exposure estimator from a Department of Defense-wide survey study on military service members." Journal of neurotrauma 38.12 (2021): 1654-1661.; KEYWORDS: Blast dose, computational modeling, exposure, injuries, battlefield