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Technical Paper

Pedestrian Safety Performance Prediction using Machine Learning Techniques

2021-09-22
2021-26-0026
As per WHO 2018 report, pedestrian fatalities account for 23% of world road accident fatalities. Every day 850 pedestrians lose their lives in the world. As per MoRTH 2018 report, 16% of road accident fatalities are of pedestrians in India. Everyday 64 pedestrians lose their lives in India. Based on accident data, one of the most common reason for the pedestrian fatality is head injury due to primary contact from vehicle front-end structure. Pedestrian head injury performance highly depends on front-end styling, bonnet stiffness, clearance with aggregates underneath the bonnet and hard contact points. During concept stage of vehicle development, safety recommendation on front-end design is provided based on geometric assessment of the class A surface.
Technical Paper

Spot Weld Failure Prediction in Safety Simulations Using MAT-240 Material Model in LS-DYNA

2015-01-14
2015-26-0165
Spot welding is the primary joining method used in automobiles. Spot-weld plays a major role to maintain vehicle structural integrity during impact tests. Robust spot weld failure definitions is critical for accurate predictions of structural performance in safety simulations. Spot welds have a complex metallurgical structure, mainly consisting of fusion and heat affected zones. For accurate material property definitions in simulation models, huge number of inputs from test data is required. Multiple tests, using different spot weld joinery configurations, have to be conducted. In order to accurately represent the spot-weld behavior in CAE, detailed modeling is required using fine mesh. The current challenge in spot-weld failure assessment is developing a methodology having a better trade-off between prediction accuracy, testing efforts and computation time. In view of the above, cohesive zone models have been found to be very effective and accurate.
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