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New Reference PMHS Tests to Assess Whole-Body Pedestrian Impact Using a Simplified Generic Vehicle Front-End
Technical Paper
2017-22-0012
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English
Abstract
This study aims to provide a set of reference post-mortem human subject tests
which can be used, with easily reproducible test conditions, for developing
and/or validating pedestrian dummies and computational human body models against
a road vehicle. An adjustable generic buck was first developed to represent
vehicle front-ends. It was composed of four components: two steel cylindrical
tubes screwed on rigid supports in V-form represent the bumper and spoiler
respectively, a quarter of a steel cylindrical tube represents the bonnet
leading edge, and a steel plate represents the bonnet. These components were
positioned differently to represent three types of vehicle profile: a sedan, a
SUV and a van. Eleven post-mortem human subjects were then impacted laterally in
a mid-gait stance by the bucks at 40 km/h: three tests with the sedan, five with
the SUV, and three with the van. Kinematics of the subjects were recorded via
high speed videos, impact forces between the subjects and the bucks were
measured via load cells behind each tube, femur and tibia deformation and
fractures were monitored via gauges on these bones. Based on these tests,
biofidelity corridors were established in terms of: 1) displacement time history
and trajectory of the head, shoulder, T1, T4, T12, sacrum, knee and ankle, 2)
impact forces between the subjects and the buck. Injury outcome was established
for each PMHS via autopsy. Simplicity of its geometry and use of standard steel
tubes and plates for the buck will make it easy to perform future, new
post-mortem human subject tests in the same conditions, or to assess dummies or
computational human body models using these reference tests.
Authors
Topic
Citation
Song, E., Petit, P., Trosseille, X., Uriot, J. et al., "New Reference PMHS Tests to Assess Whole-Body Pedestrian Impact Using a Simplified Generic Vehicle Front-End," SAE Technical Paper 2017-22-0012, 2017, https://doi.org/10.4271/2017-22-0012.Data Sets - Support Documents
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