Abstract
Multidisciplinary design optimization (MDO) of a full vehicle under the constraints of crashworthiness, NVH (Noise, Vibration and Harshness), durability, and other performance attributes is one of the imperative goals for automotive industry. However, it is often infeasible due to the lack of computational resources, robust simulation capabilities, and efficient optimization methodologies. This research intends to move closer towards that goal by solving the MDO problem combining hardware and software solutions and the advanced MDO methodologies. The MDO problem includes safety and NVH attributes. The safety attribute considers multiple crash modes: roof crush, full frontal impact, and 50% frontal offset crash. The NVH attribute considers static bending/torsion and normal analysis. It has been demonstrated that with high performance computing, a conventionally intractable real world full vehicle multidisciplinary optimization problem considering all performance attributes with a large number of design variables become feasible.KeywordsMultidisciplinary design optimization (MDO)HPC
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