Towards Aerodynamic Simulations in Julia with Trixi.jl | Doehring | JuliaCon 2024 скачать в хорошем качестве

Towards Aerodynamic Simulations in Julia with Trixi.jl | Doehring | JuliaCon 2024

Towards Aerodynamic Simulations in Julia with Trixi.jl by Daniel Doehring PreTalx: https://pretalx.com/juliacon2024/talk... GitHub Repository: https://github.com/trixi-framework/Tr... YouTube Channel:    / @trixi-framework   Documentation: https://trixi-framework.github.io/Tri... Mesh generation is a complex and critical process at the beginning of every grid-based simulation workflow. We demonstrate how Trixi.jl facilitates this task by showcasing the usage of existing meshes, exemplified by the NACA4412 airfoil meshes from NASA's Turbulence Model Benchmarking Working Group. This functionality represents a substantial leap forward, allowing users to seamlessly integrate well-established meshes into their simulations, a feature particularly significant given the intricacies and resource-intensive nature of mesh generation. In more detail, we discuss the import of bilinear meshes into P4est.jl, a Julia wrapper around the p4est library which provides the datastructures for distributed memory adaptive meshes. As we delve into the technicalities of Trixi.jl, we shine a spotlight on its pragmatic application in real-world aerodynamic scenarios. The presentation underscores the straightforward integration of advanced features, notably adaptive mesh refinement (AMR), automatic differentiation through ForwardDiff.jl and shock capturing, showcasing their utility in enhancing the precision, robustness and efficiency of simulations.