Data · dataset · 2015
Finite Element Study of Human Pelvis Model in Side Impact for Chinese Adult Occupants
Listed in DataCite
Objective: The occupant's pelvis is very vulnerable to side collision in road accidents.
Description
Finite element (FE) study on pelvic injury helps to design occupant protection devices to improve vehicle safety. This study was aimed to develop a highly biofidelic pelvis model of Chinese adult and assess its sensitivity to variations in pelvis cortical bone thickness, bone material properties and loading conditions.
Methods
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In this study, four different FE models of pelvis were developed from the CT data of a volunteer representing the 50th percentile Chinese male. Two of them were meshed using entirely hexahedral elements with variable and constant cortical thickness distribution (the V-Hex and C-Hex model), while the others were modeled with hexahedral elements for cancellous bone and variable or constant thickness shell elements for cortical bone (the V-HS and C-HS model).
In model developments, the semi-automatic muti-block meshing approach was employed to maintain the pelvis geometric curvature and generate high-quality hexahedral mesh. Then, several simulations against Post Mortem Human Subjects (PMHS) tests were performed to obtain the most accurate model in predicting pelvic injury. Based on the most accurate model, sensitivity studies were conducted to analyse the effects of the cortex thickness, Young's modulus of the cortical and cancellous bone, impactor velocity and impactor with or without padding on the biomechanical responses and injuries of pelvis.
Results: The results indicate that the models with variable cortical bone thickness can give more accurate predictions than those with constant cortical thickness. Both the V-Hex and V-HS model are favorable for simulating pelvic response and injury, but the simulation results of the V-Hex model agree with the tests better. The sensitivity study shows that pelvic response is more sensitive to alterations in the Young's modulus of cortical bone than cancellous bone.
Compared to failure displacement, peak force is more sensitive to the cortical bone thickness. But failure displacement is more sensitive to the Young's modulus of cancellous bone than peak force. The padding attached on the impactor plays a significant role in absorbing the impact energy and alleviating pelvic injury.
Conclusions: The all-hex meshing method with variable cortical bone thickness has the highest accuracy, but is time-consuming. The cortical bone plays a determinant role in resisting pelvic fracture. Peak impact force appears to be a reasonable injury predictor for pelvic injury assessment.
Some appropriate energy absorbers installed in car door can significantly reduce pelvic injury and will be beneficial for occupant protection.
Links
Where it is published
- Repository landing page tandf.figshare.com/articles/dataset/Finite_Element_Study_of_Human_Pelvis_Model_in… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.1142596.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1080/15389588.2014.950370 doi.org/10.1080/15389588.2014.950370 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.1142596.v1 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.1142596.v1 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Biological sciences · Sociology
- From keywords
- Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Computed tomography 50% · Simulation 75%
Related
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.1142596.v1 | 14 d ago | JSON v1 |
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| concepts[field].fos:sociology | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Biological Sciences'] |
| concepts[field].local:field:medicine-health | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Medicine'] |
| concepts[field].local:field:social-science | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Sociology'] |
| concepts[method].local:method:simulation | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:ct | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (50%) |
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