Abstract: PyFR is an open-source cross-platform computational fluid dynamics framework based on the high-order Flux Reconstruction approach, specifically designed for undertaking high-accuracy scale-resolving simulations in the vicinity of complex engineering geometries. Since the initial release of PyFR v0.1.0 in 2013, a range of new capabilities have been added to the framework, with a view to enabling industrial adoption. In this work, we provide details of these enhancements as released in PyFR v2.0.3, including improvements to cross-platform performance (new backends, extensions of the DSL, new matrix multiplication providers, improvements to the data layout, use of task graphs) and improvements to numerical stability (modal filtering, anti-aliasing, artificial viscosity, entropy filtering), as well as the addition of prismatic, tetrahedral and pyramid shaped elements, improved domain decomposition support for mixed element grids, improved handling of curved element meshes, the addition of an adaptive time-stepping capability, the addition of incompressible Euler and Navier-Stokes solvers, improvements to file formats and the development of a plugin architecture. We also explain efforts to grow an engaged developer and user community and provided a range of examples that show how our user base is applying PyFR to solve a wide range of fundamental, applied and industrial flow problems. Finally, we demonstrate the accuracy of PyFR v2.0.3 for a supersonic Taylor-Green vortex case, with shocks and turbulence, and provided latest performance and scaling results on up to 1024 AMD Instinct MI250X accelerators of Frontier at ORNL (each with two GCDs) and up to 2048 Nvidia GH200 GPUs of Alps at CSCS. We note that absolute performance of PyFR accounting for the totality of both hardware and software improvements has, conservatively, increased by almost 50x over the last decade.

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Abstract: This study uses Direct Numerical Simulations (DNS) with PyFR (www.pyfr.org) to investigate the impact of free-stream disturbances on the performance of non-conventional triangular airfoils for Martian rotorcraft. First, triangular airfoils optimized for steady uniform free- stream conditions at a 12 degree angle of attack are subjected to unsteady upstream conditions containing free-stream eddies with various target turbulence intensities and characteristic length scales. Results show that the free-stream eddies lead to a breakdown of coherent suction-side vortices and a reduction of aerodynamic forces, with the magnitude of this effect increasing with higher turbulence intensities and larger length scales. Building on this, DNS are then used to optimize triangular airfoils at a 12 degree angle of attack for unsteady upstream conditions containing free-stream eddies. The new designs still leverage an unsteady vortex roll-up mechanism to generate lift. However, their shapes are different to those obtained when optimizing for steady uniform inflow conditions, with their apexes closer to the trailing edge. This downstream apex position allows for the smaller and weaker vortices that result from the interaction of the free-stream eddies with the separated shear layer to cover a larger suction surface area. Taken together, the results demonstrate the importance of considering free-stream disturbances when designing non-conventional airfoils for use on a Martian rotorcraft.

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Summary: Next-generation Entry, Descent, and Landing (EDL) systems for Titan and Mars must safely slow down increasingly large payloads. One particular challenge occurs during the transonic phase of descent, where the spacecraft is subject to aerodynamic instabilities that can cause uncontrolled oscillations, posing a significant risk of mission failure. This project will further develop the GPU-accelerated computational fluid dynamics flow solver PyFR - implementing improved shock capturing approaches and a full 6-DOF free-flight capability - and use it to study dynamic stability in the transonic phase of descent. The work will be undertaken in collaboration with Texas A&M University and NASA Ames.

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