Metamodel Generation for Frontal Crash Scenario of a Passenger Car

2020-28-0504

09/25/2020

Features
Event
International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility
Authors Abstract
Content
A frontal impact scenario was simulated using a Finite Element Model of a Hybrid III 50th percentile male (LSTC, Livermore CA) along with seatbelt, steering system and driver airbags. The boundary conditions included acceleration pulse to the seat and the outputs including injury measures in terms of Head Injury Criterion (HIC), Normalized Neck Injury Criterion (NIJ) and Chest Severity Index (CSI) were extracted from the simulations. The kinematics of the Hybrid III were validated against the kinematics of post mortem human surrogates (PMHS) available in the literature. Using the validated setup, metamodels were generated by creating a design of varying different parameters and recording the responses for each design. First, the X and Z translation of dummy along the seat is provided as input for which there was no variation in the head injury criterion (HIC). Next, the input pulse to the seat is parameterized along with the seatbelt loading and the results are obtained respectively. The outputs, in terms of injury measures, are generated in the form of metamodels as a function of the parameters. The occupant model used for the frontal crash scenario in LS-Dyna is validated against the previously available crash experimental data. A total of 100 design points was generated with a varying combination of parameters. An increase in various injury measures was observed with an increase in the scale factor of the acceleration pulse. Also, it was found that chest severity index increased with an increase in the scale factor of the seat belt loading force.
Meta TagsDetails
DOI
https://doi.org/10.4271/2020-28-0504
Pages
6
Citation
Shankar, H., Selvaraju, R., and Sankarasubramanian, H., "Metamodel Generation for Frontal Crash Scenario of a Passenger Car," SAE Technical Paper 2020-28-0504, 2020, https://doi.org/10.4271/2020-28-0504.
Additional Details
Publisher
Published
Sep 25, 2020
Product Code
2020-28-0504
Content Type
Technical Paper
Language
English