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Development of Subject-Specific Elderly Female Finite Element Models for Vehicle Safety
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 02, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Previous study suggested that female, thin, obese, and older occupants had a higher risk of death and serious injury in motor vehicle crashes. Human body finite element models were a valuable tool in the study of injury biomechanics. The mesh deformation method based on radial basis function(RBF) was an attractive alternative for morphing baseline model to target models. Generally, when a complex model contained many elements and nodes, it was impossible to use all surface nodes as landmarks in RBF interpolation process, due to its prohibitive computational cost. To improve the efficiency, the current technique was to averagely select a set of nodes as landmarks from all surface nodes. In fact, the location and the number of selected landmarks had an important effect on the accuracy of mesh deformation. Hence, how to select important nodes as landmarks was a significant issue. In the paper, an efficient peak point-selection RBF mesh deformation method was used to select landmarks. The multiple peak points were selected to expand landmarks set, so as to improve the morphing quality compared with the traditional point-selection method. A human head model morphing example was used to verify the effectiveness and stability of the proposed method. Furthermore, the proposed mesh deformation methodology was also applied in a full subject-specific elderly female occupant modeling. The findings of this study demonstrated the feasibility of the proposed mesh deformation method to rapidly develop subject-specific human models in advancing occupant safety.
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CitationDong, W., Zhan, Z., Yin, Y., Li, J. et al., "Development of Subject-Specific Elderly Female Finite Element Models for Vehicle Safety," SAE Technical Paper 2019-01-1224, 2019, https://doi.org/10.4271/2019-01-1224.
Data Sets - Support Documents
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