Digital Human Body Model Twin and its Application to Improved Aircraft Readiness and Occupant Survivability
Abstract
The proposed research will focus on developing a roadmap for the development of the I-Predict tool and the future integration into a Digital Twin Environment that may be used to improve aircraft readiness and occupant survivabilityTo protect warfighters from injuries, injury prevention standards are needed based on a scientific understanding of hazardous conditions typical of military service and the vulnerability of tissues, organs, and bodily functions to those service hazards. Such standards will inform the design trade spaces of personal protective equipment (PPE), safer vehicles, and safe-to-operate weaponssystems, as well as tactics, techniques, and procedures (TTPs) to protect against injury. Injury prediction models will also allow improved estimates of casualty types, rates, and severity, which in turn will predict individual and unit readiness during operations and will impact medical treatment requirements. The development of a highly biofidelic finite element model of the wholehuman body is needed to inform such applications. The Injury Prevention and Incapacitating Prediction Tool (I-PREDICT) would provide a means to make warfighter survivability and safety a priority in PPE and platform development efforts rather than the current approach which can put too much emphasis on system and material development without a sufficient understanding of the interaction with the human inside [1].Warfighter survivability and operational readiness challenges are currently evaluated with nonbiofidelic approaches (e.g., manikin and clay surrogates) which are too costly, slow, and inaccurate limiting agility and adaptability to evolving threats. For example in Aircraft Crashworthiness Applications being able to integrate the Human Body Models (HBM) with the aircraft seat andsurrounding structure will result in an overall improvement of survivability.The proposed research will focus on developing a roadmap for the development of the I-Predict tool and the future integration into a Digital Twin Environment that may be used to improve aircraft readiness and occupant survivability
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 24, 2019
- Source ID
- N000141912177
Entities
People
- Gerardo Olivares
Organizations
- Office of Naval Research
- United States Navy
- Wichita State University