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20132025
most citedPyFR: An Open Source Framework for Solving Advection-Diffusion Type Problems on Streaming Architectures using the Flux Reconstruction Approach

317 citations · 796 across the 31 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

physics.flu-dyn2021★ 21 cited

Artificial Compressibility Approaches in Flux Reconstruction for Incompressible Viscous Flow Simulations

Will Trojak, Nagabhushana Rao Vadlamani, James Tyacke +2

Several competing artificial compressibility methods for the incompressible flow equations are examined using the high-order flux reconstruction method. The established artificial…

math.NA2021

Utilizing Time-Reversibility for Shock Capturing in Nonlinear Hyperbolic Conservation Laws

Tarik Dzanic, Will Trojak, Freddie D. Witherden

In this work, we introduce a novel approach to formulating an artificial viscosity for shock capturing in nonlinear hyperbolic systems by utilizing the property that the solutions…

cs.MS2021★ 5 cited

Hyperbolic Diffusion in Flux Reconstruction: Optimisation through Kernel Fusion within Tensor-Product Elements

Will Trojak, Rob Watson, Freddie Witherden

Novel methods are presented in this initial study for the fusion of GPU kernels in the artificial compressibility method (ACM), using tensor product elements with constant Jacobian…

math.NA2021

Bounds Preserving Temporal Integration Methods for Hyperbolic Conservation Laws

Tarik Dzanic, Will Trojak, Freddie D. Witherden

In this work, we present a modification of explicit Runge-Kutta temporal integration schemes that guarantees the preservation of any locally-defined quasiconvex set of bounds for t…

physics.flu-dyn2021★ 10 cited

Partially-Averaged Navier-Stokes Simulations of Turbulence Within a High-Order Flux Reconstruction Framework

Tarik Dzanic, Sharath Girimaji, Freddie Witherden

High-order methods and hybrid turbulence models have independently shown promise as means of decreasing the computational cost of scale-resolving simulations. The objective of this…

physics.flu-dyn2021★ 1 cited

Turbulence closure modeling with data-driven techniques: Investigation of generalizable deep neural networks

Salar Taghizadeh, Freddie Witherden, Yassin Hassan +1

Generalizability of machine-learning (ML) based turbulence closures to accurately predict unseen practical flows remains an important challenge. At the Reynolds-averaged Navier-Sto…

math.NA2021

Enabling four-dimensional conformal hybrid meshing with cubic pyramids

Miroslav S. Petrov, Todor D. Todorov, Gage S. Walters +2

The main purpose of this article is to develop a novel refinement strategy for four-dimensional hybrid meshes based on cubic pyramids. This optimal refinement strategy subdivides a…