{"id":10581,"date":"2025-06-19T10:20:22","date_gmt":"2025-06-19T09:20:22","guid":{"rendered":"https:\/\/edrmedeso1.wpenginepowered.com\/?post_type=article&p=10581"},"modified":"2026-04-29T10:29:24","modified_gmt":"2026-04-29T09:29:24","slug":"gputhesis","status":"publish","type":"article","link":"https:\/\/edrmedeso.com\/article\/gputhesis\/","title":{"rendered":"Is GPU\u2011Accelerated CFD in Ansys Fluent Ready for Aerospace?"},"content":{"rendered":"

Based on a <\/span><\/i>Master\u2019s Thesis<\/span><\/i><\/a> by Filip Gustafsson & Gustav R\u00f6nn, Chalmers University of Technology (2025)<\/span><\/i><\/p>\n

With insights from Bj\u00f6rn Brag\u00e9e (Technical Account Manager, EDRMedeso) and Anton Persson (Business Developer, EDRMedeso)<\/span><\/i>\u00a0<\/span><\/p>\n

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GPU\u2011Accelerated CFD with Ansys Fluent: Benchmarking Performance for Aerospace Applications<\/span><\/h2>\n
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Gustav and Filip present their findings to the EDRMedeso team<\/p><\/div>\n

As computational demands increase across engineering disciplines, the pressure to reduce simulation time without compromising accuracy continues to grow. In Computational Fluid Dynamics (CFD)<\/b><\/span>, this challenge goes beyond turbulence models and numerics\u2014it extends directly to hardware choices.<\/p>\n

Graphics Processing Units (GPUs)<\/b><\/span>, long associated with gaming and AI, have emerged as a powerful enabler for high\u2011performance CFD. While industries such as automotive have rapidly adopted GPU\u2011accelerated solvers for external aerodynamics, uptake in aerospace has been more cautious. The reason is clear: aerospace simulations involve complex physics, strict accuracy requirements, and demanding certification standards.<\/p>\n

To explore whether GPU\u2011based CFD is ready for aerospace\u2011grade applications, two master\u2019s students from Chalmers University of Technology<\/b><\/span>, Filip Gustafsson and Gustav R\u00f6nn, conducted a comprehensive and independent evaluation of Ansys Fluent\u2019s native GPU solver<\/b><\/span> in collaboration with
\nGKN Aerospace, Rescale, and EDRMedeso<\/b>.<\/span><\/p>\n

From Performance Claims to Independent Validation<\/span><\/h3>\n

As computational demands grow across engineering disciplines, the pressure to shorten simulation times without compromising fidelity is only increasing. In the world of Computational Fluid Dynamics (CFD), this means rethinking not just numerics and turbulence models, but also hardware.<\/p>\n

Benchmarking the GPU Solver: from hype to hard numbers\u00a0<\/span><\/h3>\n

The study focused on three representative CFD cases with direct relevance to aerospace:<\/span>\u00a0<\/span><\/p>\n