Thoracic trauma is the principle causative factor in 30% of road traffic deaths. Researchers have developed forcedeflection corridors of the thorax for various loading conditions in order to elucidate injury mechanisms and to validate the mechanical response of ATDs and numerical human models. A corridor, rather than a single response characteristic, results from the variability inherent in biological experimentation. This response variability is caused by both intrinsic and extrinsic factors. The intrinsic factors are associated with individual differences among human subjects, e.g. the differences in material properties and in body geometry. The extrinsic sources of variability include fluctuations in the loading and supporting conditions in experimental tests. Recent studies have considered the intrinsic factors, especially the material-level response of the rib, which can be modified over a limited range within, e.g. a finite element (FE) model in order to fit a gross overall thoracic response corridor. Studies typically do not, however, consider uncertainty due to extrinsic factors.
The purpose of this work was to estimate the contribution of selected extrinsic factors to the uncertainty in a response corridor by using a thorax FE model. The sensitivity of twelve response corridors to the relative positioning of the thorax, the loader and the test fixture was analyzed. Reasonable ranges of experimental uncertainty were established for loader angle, loader location, and thorax orientation, and response variability was analyzed for three tissue states (intact, denuded, and eviscerated) with four different loaders (hub, distributed belt, single diagonal belt, and double diagonal belts). Of the variables considered here, the thorax orientation has the largest effect on the force-deflection response, which increases and decreases the effective stiffness up to 20%. The simulation work isolated the extrinsic contribution from the corridor and indicated model deficiencies and refinements, which have the potential to improve model accuracy, particularly modeling the soft tissues and the costal cartilage.