GAC R&D Center sets record-low vehicle drag coefficient using NVIDIA GPU-accelerated CFD simulation

Overview

GAC R&D Center (GAC Group) deployed NVIDIA V100 SXM2 Tensor Core GPUs on its hybrid cloud HPC platform, using Altair's ultraFluidX CFD software for GPU double-precision computing, to design a new concept car. In less than six months the team completed over 200 transient CFD simulations of vehicle outflow, achieving a simulation drag coefficient of 0.147 (wind tunnel test value 0.146 at Tongji University's Shanghai Automotive Wind Tunnel Center), a new record versus the previous 0.19. Compared to conventional CFD approaches, manual modeling effort was reduced by nearly 60% and total simulation time was shortened by about 70%.

The challenge

GAC R&D Center needed to decide which CFD simulation technology to use to design a new concept car with a record-low drag coefficient. Conventional CFD approaches using multi-core CPU HPC clusters demanded high CPU core counts, presented high energy consumption and maintenance costs, and required higher grid quality, complex pre-processing, and heavy manual investment. Larger-scale grids and transient simulation needed for high-precision results also sharply increased computing resource consumption.

The solution

GAC R&D Center deployed NVIDIA V100 SXM2 Tensor Core GPUs on its heterogeneous hybrid cloud HPC platform, adopting Altair's ultraFluidX CFD software built on GPU double-precision computing. In less than six months, the team completed over 200 transient CFD simulations of the vehicle outflow field.

Reported business value

The simulation achieved a drag coefficient of 0.147, matching a wind tunnel test value of 0.146 at Tongji University's Shanghai Automotive Wind Tunnel Center, setting a new record versus the previous 0.19. Compared to conventional CFD approaches, manual modeling effort was reduced by nearly 60% and total simulation time was shortened by about 70%.