Abstract
In the early stage of vehicle planning phase, multifunctional trade-off studies about layout of frame structures are required. Computer Aided Engineering (CAE) / Machine Learning (ML) technique is proposed to conduct multifunctional trade-off study between mass and performances. ML models were created from the database that was constructed from large number of parametric FE analysis. Performance maps that were drawn based on ML result enables visualization of trade-off relations.
