首页|Research from Department of Mechanical Design Engineering Has Provided New Study Findings on Machine Learning (Optimization of Occupant Restraint System Using Machine Learning for THORM50 and Euro NCAP)
Research from Department of Mechanical Design Engineering Has Provided New Study Findings on Machine Learning (Optimization of Occupant Restraint System Using Machine Learning for THORM50 and Euro NCAP)
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Investigators publish new report on artificial intelligence. According to news reporting from the Department of Mechanical Design Engineering by NewsRx journalists, research stated, “In this study, we propose an optimization method for occupant protection systems using a machine learning technique.” Funders for this research include Ministry of Land, Infrastructure And Transport. Our news journalists obtained a quote from the research from Department of Mechanical Design Engineering: “First, a crash simulation model was developed for a Euro NCAP MPDB frontal crash test condition. Second, a series of parametric simulations were performed using a THOR dummy model with varying occupant safety system design parameters, such as belt attachment locations, belt load limits, crash pulse, and so on. Third, metamodels were developed using neural networks to predict injury criteria for a given occupant safety system design. Fourth, the occupant safety system was optimized using metamodels, and the optimal design was verified using a subsequent crash simulation. Lastly, the effects of design variables on injury criteria were investigated using the Shapely method. The Euro NCAP score of the THOR dummy model was improved from 14.3 to 16 points.”
Department of Mechanical Design EngineeringCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
Mdpi
