Item Details

title

Injury Metrics, Real World Crash Reconstruction, and Robust Injury Prediction for a Human Body Model in Side Impact

author

Golman, Adam Joseph

abstract

Motor vehicle crashes (MVCs) are a significant public health problem. Worldwide, MVCs kill over 1.2 million people each year. Improved understanding of the occupant loading conditions in real world crashes is critical for injury prevention and new vehicle design. Real world crash reconstructions using vehicle and human body finite element models (HBM) have the potential to elucidate injury mechanism, predict injury risk, and evaluate injury mitigation system effectiveness. The purpose of the work presented herein was to create a novel paradigm in finite element (FE) MVC injury analysis to evaluate injury risk in real world crash scenarios.

subject

finite element analysis

Human body model

injury metrics

injury prediction

injury risk

real world motor vehicle crash

contributor

Stitzel, Joel D (committee chair)

Danelson, Kerry A (committee member)

Gayzik, F Scott (committee member)

date

2013-06-06T21:19:36Z (accessioned)

2013 (issued)

degree

Biomedical Engineering (discipline)

embargo

forever (terms)

10000-01-01 (liftdate)

identifier

http://hdl.handle.net/10339/38566 (uri)

language

en (iso)

publisher

Wake Forest University

type

Thesis