LARGE-SCALE, MULTIDISCIPLINARY OPTIMIZATION OF A VEHICLE SYSTEM IN A SCALABLE, HIGH PERFORMANCE COMPUTING ENVIRONMENT

摘要

The focus of this paper is on large-scale MDO of a vehicle system for Safety, NVH (noise, vibration and harshness) and Weight, in a scalable HPC environment. The computational complexity comes from addressing multiple safety modes including, frontal crash, offset crash, side impact and roof crush, in addition to the NVH discipline. A combination of high performance computing utilizing several hundred processors, Kriging metamodeling based design response approximation techniques, formal MDO strategies, and engineering judgement are effectively used to obtain superior design solutions with significantly reduced elapsed computing times. The reduction in large-scale MDO solution times through HPC is significant in that it now makes it possible for such technologies to impact the vehicle design cycle and improve the engineering productivity.