Ham, S.; Ji, S.; Cheon, S.S. The Design of a Piecewise-Integrated Composite Bumper Beam with Machine-Learning Algorithms. Materials 2024, 17, 602, doi:10.3390/ma17030602.
Ham, S.; Ji, S.; Cheon, S.S. The Design of a Piecewise-Integrated Composite Bumper Beam with Machine-Learning Algorithms. Materials 2024, 17, 602, doi:10.3390/ma17030602.
Ham, S.; Ji, S.; Cheon, S.S. The Design of a Piecewise-Integrated Composite Bumper Beam with Machine-Learning Algorithms. Materials 2024, 17, 602, doi:10.3390/ma17030602.
Ham, S.; Ji, S.; Cheon, S.S. The Design of a Piecewise-Integrated Composite Bumper Beam with Machine-Learning Algorithms. Materials 2024, 17, 602, doi:10.3390/ma17030602.
Abstract
In the present study, piecewise integrated composite (PIC) bumper beam for passenger cars was proposed and design optimisation process for composite bumper beam against IIHS test was carried out with the help of machine learning. Several elements in IIHS bumper FE model have been assigned to be references, in order to collect training data which, allow the machine learning model to study the method of predicting loading types of each finite element. 2-D and 3-D implementations were provided by machine learning models, which determined stacking sequences of each finite element in PIC bumper beam. It was found that the PIC bumper beam, which was designed by machine learning model has direct impact on reducing the possibility of failure as well as increasing bending strength effectively than conventional composite bumper beam. Moreover, 3-D implementation produced better results compared with 2-D implementation since it was preferable to choose loading type information which was achieved from surroundings when the target elements were located either at corner or junction of planes instead of using information came from the same plane of target.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
