Leveraging Rescale for High-Order CFD Simulation

Computational Fluid Dynamics (CFD) has significantly evolved as a discipline, becoming integral in industries such as aerospace and automotive for enhancing product design through simulations that complement empirical testing. Traditional second-order spatial accuracy methods, while robust and affordable, are sometimes insufficient for complex flow problems like vortex-dominated flows and aeroacoustics, which benefit from high-order methods. This text describes the application of high-order simulations using PyFR, an open-source framework, to simulate flow over a NACA 0012 airfoil using Rescale's cloud-based HPC infrastructure. By utilizing the Flux Reconstruction approach and running simulations on GPU clusters, PyFR demonstrates the capability of high-order schemes in improving accuracy without substantial computational cost increases. The simulation involved curvilinear mesh elements and advanced time integration methods, showcasing the advantages of high-order CFD simulations on modern computing architectures. Rescale's platform allows users to efficiently run such simulations, suggesting a shift towards more sophisticated hardware utilization for CFD, aligning with ongoing advancements in the field.

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