Thoracic injury is the most dominant segment of automotive side impact traumas. A numerical model that can predict such injuries in crash simulation is essential to the process of designing a safer motor vehicle.
The focus of this study was to develop a numerical model to predict lung response and injury in side impact car crash scenarios. A biofidelic human body model was further developed. The geometry, material properties and boundary condition of the organs and soft tissues within the thorax were improved with the intent to ensure stress transmission continuity and model accuracy. The thoracic region of the human body model was revalidated against three pendulum and two sled impact scenarios at different velocities. Other body regions such as the shoulder, abdomen, and pelvis were revalidated. The latest model demonstrated improvements in every response category relative to the previous version of the human body model.
The development of the lung model involved advancements in the material properties, and boundary conditions. An analytical approach was presented to correct the lung properties to the in-situ condition. Several injury metric predictor candidates of pulmonary contusion were investigated and compared based on the validated pendulum and sled impact scenarios. The results of this study confirmed the importance of stress wave focusing, reflection, and concentration within the lungs. The bulk modulus of the lung had considerable influence on injury metric outcomes. Despite the viscous criterion yielded similar response for different loading conditions, this study demonstrated that the level of contusion volume varied with the size of the impact surface area.
In conclusion, the human body model could be used for the analysis of thoracic response in automotive impact scenarios. The overall model is capable of predicting thoracic response and lung contusion. Future development on the heart and aorta can expand the model capacity to investigate all vital organ injury mechanisms.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/5005 |
| Date | January 2009 |
| Creators | Yuen, Kin |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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