Case Study: Richard Childress Racing achieves on-demand high-performance CFD and faster design iteration with Rescale

NASCAR’s Richard Childress Racing Finds On-Track Advantage in the Cloud

Richard Childress Racing, a NASCAR team with a 48-year history of in-house engineering, faced a compute bottleneck: their aerodynamicists use ANSYS Fluent for large-scale CFD but only had 64 on‑prem cores, limiting model resolution and throughput. To run full-car analyses (150–400 million cells) and explore more design iterations, RCR turned to Rescale and its ScaleX platform for scalable cloud HPC.

Rescale delivered on-demand HPC so RCR can run jobs on 512+ cores (completing many runs in about 10 hours), handle much larger, high‑resolution simulations, and eliminate queue delays—enabling faster debugging, “what‑if” studies, and higher simulation throughput. With Rescale’s ScaleX, RCR plans to automate simulations and leverage effectively unlimited CFD capacity, gaining agility and a competitive advantage that they expect to translate into improved on‑track performance.

Richard Childress Racing

Seth Morris

Aerodynamicist