Behind armor blunt trauma (BABT) refers to non-penetrating injuries incurred when body armor deforms into the body of the wearer in the action of stopping a projectile. BABT is relevant in both the military and civilian security populations, and ranges in severity from mild skin laceration to death due to cardiac or pulmonary complications. Considering pulmonary contusion (PC), or bruising in the lungs due to trauma, is estimated to occur in up to 75% of cases of blunt thoracic trauma, PC is estimated to be a major complication in events of BABT. PC is diagnosable by radiological scans, and severity is determined through the percentage of portions containing blood throughout the whole lung. It is estimated that up to 20% of PC injuries are undiagnosed, and severity of PC is often underdiagnosed. Paired with a morbidity rate of up to 82% and an increased likelihood of intubation and ventilation, PC causes a large threat to military and civilian personnel experiencing BABT without reliable access to medical care. This necessitates a predictive measure of PC so that injuries due to BABT may be better mitigated to improve military readiness and expedite return to duty.

The main objective of this study is to create a model for lung tissue that includes a damage threshold, and then utilize the model to predict volume of PC in the case of BABT. This starts with the development of a validated material model for lung. Small sample shear testing of porcine lung parenchyma is performed and then fit to a constitutive model derived for shear loading. The fitted parameters are implemented into a finite element material model for lung, and the model is validated by matching kinematic response to experimentally performed indentation testing on lung tissue. Once the material model for lung is achieved, it is included into a human body model that has been validated for use in BABT loading events. Through experimental testing in shear, a failure threshold for lung tissue is determined and included within the human body model so that lung damage resulting from BABT can be output from simulations. With an output of lung damage volume resulting from lung tissue failure, methods are determined for predicting the physiological injury of PC. This is done by correlating the damage volume output from the model to reports of PC volume from live-porcine BABT testing found in the literature. As a result, PC volume can be determined directly from BABT simulations with the human body model, eliminating the need for costly experimental testing on human surrogates. The major contribution of this study towards the protection of first responders and warfighters is the ability to predict PC injury in BABT events. This will help in the diagnosis and mitigation of blunt pulmonary trauma in relation to wearers of body armor.