Validation and Verification of Computational Modeling of Human Blast Injury on Battlefield

SBIR · Phase: BOTH · Topic DTR27BZ02-NV004 · Solicitation 27.BZ

Blast events accounted for over 70% of casualties among service members engaged in ground combat events. The energy generated by an explosion can cause devastating physical trauma, affect multiple body systems and result in severe injuries or even fatalities (1.2). Although there has been extensive research into injury mechanisms of blast trauma, including primary overpressure effects, secondary fragmentation wounds, tertiary blunt trauma, and quaternary thermal or chemical injuries, there are no modeling & simulation (M&S) tools currently available which can provide a comprehensive view of the types and severity of injuries in the context of the uncertainties and complexities of realistic battlefield scenarios. Existing injury modeling tools, such as Operational Requirements-based Casualty Assessment model (ORCA) developed by US Army DEVCOM, the INJURY code developed by the Medical Research and Development Command, and the AUDITORY model developed by the Joint Intermediate Force Capabilities Office (JIFCO), each model individual injuries occurring to a single person in the absence of PPE. They are not designed to address multiple, multi-modal injuries that may occur in ground combat, and they model wounds from the “skin in,” rather than accounting for the effects of clothing or PPE. These tools can only be used for research purposes and are not designed to support battlefield operation. In contrast, the Human Injury Prediction (HIP) tool, developed by Defense Science and Technology Laboratory (DSTL) of United Kingdom, predicts injuries to multiple people from a terrorist attack. Unfortunately, this tool is limited to modeling the effects of only a single blast event caused by a terrorist weapon detonated in an urban environment. And, again, HIP models isolated injuries and cannot address multiple, multi-modal injuries. Finally, a major challenge of leveraging these tools in DTRA Technical Reachback mission is that injuries are predicted based upon biomechanical effects, and do not address human physiology. This shortcoming becomes particularly critical with multiple injuries, where the human body response to injuries is intact and synergetic among organs/tissues. Apart from the specific challenges of modeling injuries and the associated changes in physiology, a comprehensive battlefield blast injury M&S tool is a multidisciplinary endeavor, requiring expertise in diverse domains, to include medicine, military operations, weaponeering, synthetic population modeling, epidemiology, structures, machine learning, computational modeling, and PPE. ASME V&V 40 serves as the gold standard for computational model credibility in biomedical applications, and DoD Instruction 5000.61 (Modeling and Simulation Verification, Validation, and Accreditation) requires human injury models to be validated before moving to support military operation (3,4,5). The modeling effort should align with the Blast Injury Research Coordinating Office (BIRCO) and the Blast Injury Prevention Standards Recommendation (BIPSR) process. The access to sensitive battle databases must be tightly controlled and limited to need-to-know personnel (6). Based on the regulation and scientific merit, the current request for proposal (RFP) will focus on validation of the on-going approach by using independent groups.

SBIR/STTR 은 미국 중소기업만 지원할 수 있습니다(Small Business Act 법정 요건). • 계열사를 포함해 상시 종업원 500명 이하 • 미국 시민 또는 영주권자 1인 이상이 50%를 초과해 직접 소유·지배 • 미국 내 사업장을 두고 주로 미국 내에서 사업을 영위할 것 • 수행책임자(PI)의 주된 근무처가 신청 기업일 것 출처: https://www.sbir.gov/faq/eligibility-requirements

Primary country

🇺🇸 United States

Also eligible

None

Foreign companies

No

Local entity

Required

Location condition

미국 내 사업장을 두고 미국 시민·영주권자가 50%를 초과해 소유한 중소기업만 신청할 수 있습니다(법정 요건).

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Official URL

https://www.dodsbirsttr.mil/topics-app/

Application URL

https://www.dodsbirsttr.mil/topics-app/

Last fetched

2026.11.06

Human review

Not reviewed — check the official announcement

First seen

2026.11.06

Data status

Auto-collected, not reviewed

AI enrichment

Needs verification