Publications

Contents

Journal Papers

  1. T. Dzanic and F. D. Witherden,
    Positivity-preserving entropy-based adaptive filtering for discontinuous spectral element methods.
    Journal of Computational Physics, 111501, 2022.
  2. M. S. Petrov, T. D. Todorov, G. S. Walters, D. M. Williams, and F. D. Witherden,
    Enabling four-dimensional conformal hybrid meshing with cubic pyramids.
    Numerical Algorithms, 2022.
  3. T. Dzanic, S. S. Girimaji, and F. D. Witherden,
    Partially-Averaged Navier-Stokes Simulations of Turbulence Within a High-Order Flux Reconstruction Framework.
    Journal of Computational Physics, 110992, 2022.
  4. W. Trojak, R. Watson, and F. D. Witherden,
    Hyperbolic diffusion in flux reconstruction: Optimisation through kernel fusion within tensor-product elements.
    Computer Physics Communications, 273, 108235, 2022.
  5. S. Akkurt, F. D. Witherden, and P. E. Vincent,
    Cache Blocking Strategies Applied to Flux Reconstruction.
    Computer Physics Communications, 271, 108193, 2022.
  6. G. Giangaspero, F. D. Witherden, and P. E. Vincent,
    Synthetic Turbulence Generation for High-Order Scale-Resolving Simulations on Unstructured Grids.
    AIAA Journal, 60(2), 2022.
  7. S. Taghizadeh, F. D. Witherden, Y. A. Hassan, and S. S. Girimaji,
    Turbulence closure modeling with data-driven techniques: Investigation of generalizable deep neural networks.
    Physics of Fluids, 33(11), 115132, 2021.
  8. F. D. Witherden,
    Python at petascale with PyFR or: how I learned to stop worrying and love the snake.
    Computing in Science & Engineering, 23(4), 2021, 29–37.
  9. A. S. Iyer, Y. Abe, B. C. Vermeire, P. Bechlars, R. D. Baier, A. Jameson, F. D. Witherden, and P. E. Vincent,
    High-Order Accurate Direct Numerical Simulation of Flow over a MTU-T161 Low Pressure Turbine Blade.
    Computers & Fluids, 2021, 104989.
  10. C. V. Frontin, G. S. Walters, F. D. Witherden, C. W. Lee, D. M. Williams, and D. L. Darmofal,
    Foundations of space-time finite element methods: Polytopes, interpolation, and integration.
    Applied Numerical Mathematics, 166, 2021, 92–113.
  11. W. Trojak and F. D. Witherden,
    A New Family of Weighted One-Parameter Flux Reconstruction Schemes.
    Computers & Fluids, 222, 2021, 104918.
  12. C. Cox, W. Trojak, T. Dzanic, F. D. Witherden, and A. Jameson,
    Accuracy, Stability, and Performance Comparison between the Spectral Difference and Flux Reconstruction Schemes.
    Computers & Fluids, 221, 2021, 104922.
  13. J. Morton, M. J. Kochenderfer, and F. D. Witherden,
    Parameter-Conditioned Sequential Generative Modeling of Fluid Flows.
    AIAA Journal, 59(3), 2021, 825–841.
  14. W. Trojak and F. D. Witherden,
    Inline vector compression for computational physics.
    Computer Physics Communications, 258, 2021, 107562.
  15. F. D. Witherden and P. E. Vincent,
    On nodal point sets for flux reconstruction.
    Journal of Computational and Applied Mathematics, 381, 2021, 113014.
  16. T. S. Fowler, IV, F. D. Witherden, and S. S. Girimaji,
    Partially-averaged Navier–Stokes simulations of turbulent flow past a square cylinder: Comparative assessment of statistics and coherent structures at different resolutions.
    Physics of Fluids, 32(12), 2020, 125106.
  17. T. S. Fowler, IV, F. D. Witherden, and S. S. Girimaji,
    Pulsating Flow Past a Square Cylinder: Analysis of Force Coefficient Spectra and Vortex-Structure Development.
    Journal of Fluids Engineering, 142(12), 2020, 121106.
  18. S. Taghizadeh, F. D. Witherden, and S. Girimaji,
    Turbulence closure modeling with data–driven algorithms: physical compatibility and consistency considerations.
    New Journal of Physics, 2020, 093023.
  19. J. Romero, J. Crabill, J. E. Watkins, F. D. Witherden, and A. Jameson,
    ZEFR: A GPU-accelerated high-order solver for compressible viscous flows using the flux reconstruction method.
    Computer Physics Communications, 250, 2020, 107169.
  20. F. D. Witherden and A. Jameson,
    Impact of Number Representation for High-Order Implicit Large-Eddy Simulations.
    AIAA Journal, 58(1), 2020, 184–197.
  21. N. A. Loppi, F. D. Witherden, A. Jameson, and P. E. Vincent,
    Locally adaptive pseudo-time stepping for high-order Flux Reconstruction.
    Journal of Computational Physics, 399, 2019, 108913.
  22. A. S. Iyer, F. D. Witherden, S. I. Chernyshenko, and P. E. Vincent,
    Identifying eigenmodes of averaged small-amplitude perturbations to turbulent channel flow.
    Journal of Fluid Mechanics, 875, 2019, 758–780.
  23. K. T. Carlberg, A. Jameson, M. J. Kochenderfer, J. Morton, L. Peng, and F. D. Witherden,
    Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning.
    Journal of Computational Physics, 395, 2019, 105–124.
  24. J. A. Crabill, F. D. Witherden, and A. Jameson,
    High-order computational fluid dynamics simulations of a spinning golf ball.
    Sports Engineering, 22(9), 2019.
  25. J. A. Crabill, F. D. Witherden, and A. Jameson,
    A parallel direct cut algorithm for high-order overset methods with application to a spinning golf ball.
    Journal of Computational Physics, 374, 2018, 692–723.
  26. N. A. Loppi, F. D. Witherden, A. Jameson, and P. E. Vincent,
    A High-Order Cross-Platform Incompressible Navier–Stokes Solver via Artificial Compressibility with Application to a Turbulent Jet.
    Computer Physics Communications, 233, 2018, 193–205.
  27. F. D. Witherden and A. Jameson,
    On the spectrum of the Steger–Warming flux‐vector splitting scheme.
    International Journal for Numerical Methods in Fluids, 87(12), 2018, 601–606.
  28. J. Romero, F. D. Witherden, and A. Jameson,
    A Direct Flux Reconstruction Scheme for Advection–Diffusion Problems on Triangular Grids.
    Journal of Scientific Computing, 73(2–3), 2017, 1115–1144.
  29. J. S. Park, F. D. Witherden, and P. E. Vincent,
    High-Order Implicit Large-Eddy Simulations of Flow over a NACA0021 Aerofoil.
    AIAA Journal, 55(7), 2017, 2186-2197.
  30. B. C. Vermeire, F. D. Witherden, and P. E. Vincent,
    On the utility of GPU accelerated high-order methods for unsteady flow simulations: A comparison with industry-standard tools.
    Journal of Computational Physics, 334, 2017, 497–521.
  31. F. D. Witherden, J. S. Park, and P. E. Vincent,
    An Analysis of Solution Point Coordinates for Flux Reconstruction Schemes on Tetrahedral Elements.
    Journal of Scientific Computing, 69(2), 2016, 905–920.
  32. B. D. Wozniak, F. D. Witherden, F. P. Russell, P. E. Vincent, and P. H. J. Kelly,
    GiMMiK—Generating bespoke matrix multiplication kernels for accelerators: Application to high-order Computational Fluid Dynamics.
    Computer Physics Communications, 202, 2016, 12–22.
  33. F. D. Witherden, B. C. Vermeire, and P. E. Vincent,
    Heterogeneous computing on mixed unstructured grids with PyFR.
    Computers & Fluids, 120, 2015, 173–186.
  34. P. E. Vincent, A. M. Farrington, F. D. Witherden, and A. Jameson,
    An extended range of stable-symmetric-conservative Flux Reconstruction correction functions.
    Computer Methods in Applied Mechanics and Engineering, 296, 2015, 248–272.
  35. F. D. Witherden and P. E. Vincent,
    On the Identification of Symmetric Quadrature Rules for Finite Element Methods.
    Computers & Mathematics with Applications, 69(10), 2015, 1232–1241.
  36. F. D. Witherden, A. M. Farrington, and P. E. Vincent,
    PyFR: An Open Source Framework for Solving Advection-Diffusion Type Problems on Streaming Architectures Using the Flux Reconstruction Approach.
    Computer Physics Communications, 185(11), 2014, 3028–3040.
  37. F. D. Witherden and P. E. Vincent,
    An Analysis of Solution Point Coordinates for Flux Reconstruction Schemes on Triangular Elements.
    Journal of Scientific Computing, 61(2), 2014, 398–423.

Conference Papers

  1. W. Trojak, T. Dzanic, and F. D. Witherden,
    Shock Capturing Methods in High-Order Flux Reconstruction I: Graph Viscosity and Convex Limiting Approaches.
    Paper AIAA 2021-0496, AIAA Scitech 2021, 11–15 and 19–21 January 2021.
  2. D. W. Hartman, T. Dzanic, F. D. Witherden, A. Tropina, and R. B. Miles,
    Numerical analysis and prediction of Aero-optical effects.
    Paper AIAA 2021-0335, AIAA Scitech 2021, 11–15 and 19–21 January 2021.
  3. T. Dzanic, K. Shah, and F. D. Witherden,
    Fourier Spectrum Discrepancies in Deep Network Generated Images.
    NeurIPS 2020, 6–12 December 2020.
  4. Y. Abe, F. D. Witherden, G. Giangaspero, B. C. Vermeire, A. S. Iyer, and P. E. Vincent,
    High-performance Implementation of Inlet Turbulence Generation for GPU-based Parallel Computation.
    Advanced Fluid Information 2019, 6–8 November 2019, Sendai, Miyagi, JP.
  5. J. Morton, F. D. Witherden, and M. J. Kochenderfer,
    Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control.
    IJCAI-19, 10–16 August 2019, Macao, PRC.
  6. J. Morton, F. D. Witherden, A. Jameson, and M. J. Kochenderfer,
    Deep Dynamical Modeling and Control of Unsteady Fluid Flows.
    NeurIPS 2018, 2–8 December 2018, Montréal, Quebec, CA.
  7. F. D. Witherden and A. Jameson,
    Future Directions of Computational Fluid Dynamics.
    Paper AIAA-2017-3791, 23rd AIAA Computational Fluid Dynamics Conference, 5–9 June 2017, Denver, Colorado, USA.
  8. P. E. Vincent, F. D. Witherden, B. C. Vermeire, J. S. Park, and A. Iyer,
    Towards Green Aviation with Python at Petascale.
    Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC16), 13-18 November 2016, Salt Lake City, Utah, USA.
  9. M. Klemm, F. D. Witherden, and P. E. Vincent,
    Using the pyMIC Offload Module in PyFR.
    EuroSciPy 2015, 28–29 August 2015, Cambridge, UK.
  10. B. C. Vermeire, F. D. Witherden, and P. E. Vincent,
    On the Utility of High-Order Methods for Unstructured Grids: A Comparison Between PyFR and Industry Standard Tools.
    Paper AIAA-2015-2743, 22nd AIAA Computational Fluid Dynamics Conference, 22-26 June 2015, Dallas, Texas, USA.
  11. P. E. Vincent, F. D. Witherden, A. M. Farrington, G. Ntemos, B. C. Vermeire, J. S. Park, and A. S. Iyer,
    PyFR: Next-Generation High-Order Computational Fluid Dynamics on Many-Core Hardware.
    Paper AIAA-2015-3050, 22nd AIAA Computational Fluid Dynamics Conference, 22-26 June 2015, Dallas, Texas, USA.
  12. G. Mengaldo, D. De Grazia, J. Peiro, A. M. Farrington, F. D. Witherden, P. E. Vincent, and S. J. Sherwin,
    A Guide to the Implementation of Boundary Conditions in Compact High-Order Methods for Compressible Aerodynamics.
    Paper AIAA-2014-2923, 7th AIAA Theoretical Fluid Mechanics Conference, 16-20 June 2014, Atlanta, Georgia, USA.

Book Chapters

  1. M. Rasquin, K. Hillewaert, A. Colombo, F. Bassi, F. Massa, K. Puri, A. S. Iyer, Y. Abe, F. D. Witherden, B. C. Vermeire, and P. E. Vincent,
    Computational Campaign on the MTU T161 Cascade.
    In TILDA: Towards Industrial LES/DNS in Aeronautics, edited by C. Hirsch, K. Hillewaert, R. Hartmann, V. Couaillier, J-F. Boussuge, F. Chalot, S. Bosniakov, and W. Haase. Springer, 2021.
  2. F. Bassi, L. Botti, L. Verzeroli, R. Hartmann, J. Jägersküpper, E. Martin, M. Lorteau, P. E. Vincent, F. D. Witherden, B. C. Vermeire, J. S. Park, A. Iyer, K. Puri, D. Gutzwiller, C. Hirsch, and F. Chalot,
    Parallelisation to Several Tens-of-Thousands of Cores.
    In TILDA: Towards Industrial LES/DNS in Aeronautics, edited by C. Hirsch, K. Hillewaert, R. Hartmann, V. Couaillier, J-F. Boussuge, F. Chalot, S. Bosniakov, and W. Haase. Springer, 2021.
  3. F. D. Witherden and A. Jameson,
    Aerodynamics.
    In Encyclopedia of Computational Mechanics Second Edition, edited by E. Stein, R. de Borst, and T. J. R. Hughes. Wiley, 2017.
  4. F. D. Witherden, A. Jameson, and D. W. Zingg,
    The Design of Steady State Schemes for Computational Aerodynamics.
    In Handbook of Numerical Methods for Hyperbolic Problems — Applied and Modern Issues, edited by R. Abgrall and C-W. Shu. Elsevier, 2017.
  5. F. D. Witherden, P. E. Vincent, and A. Jameson,
    High-Order Flux Reconstruction Schemes.
    In Handbook of Numerical Methods for Hyperbolic Problems — Basic and Fundamental Issues, edited by R. Abgrall and C-W. Shu. Elsevier, 2016.
  6. J. Enkovaara, M. Klemm, and F. D. Witherden,
    High Performance Python Offloading.
    In High Performance Parallelism Pearls Volume 2 pp. 246–269, edited by J. Jeffers and J. Reinders. Morgan Kaufmann, 2015.

Theses

  1. F. D. Witherden,
    On the Development and Implementation of High-Order Flux Reconstruction Schemes for Computational Fluid Dynamics.
    PhD thesis, September 2015.

Technical Reports

  1. F. D. Witherden,
    Memory Forensics over the IEEE 1394 Interface.
    September 2010.

Conference Presentations

  1. Inline Vector Compression for Computational Physics.
    CEED4AM, 11–12 August 2020.
  2. Experiences with OpenCL in PyFR: 2014—Present.
    IWOCL / SYCLcon 2020, 27–29 April 2020.
  3. Anatomy of a High-performance FR CFD Solver.
    AIAA SciTech 2020, 6–10 January 2020, Orlando, Florida, USA.
  4. Anatomy of a High-performance FR CFD Solver.
    ICFD2019, 6–8 November 2019, Sendai, Miyagi, JP.
  5. Compression of High-order CFD Solutions using Machine Learning.
    SIAM CSE19, 25–1 March 2019, Spokane, Washington, USA.
  6. On the Impact of Number Representation for High-Order LES.
    USNCCM 14, 17–20 July 2017, Montréal, Quebec, CA.
  7. Predictive CFD, Past, Present, and Future.
    PCCFD 2017, 22–24 May 2017, KAUST, SA.
  8. Towards Greener Aviation with Python at Petascale.
    PCCFD 2017, 22–24 May 2017, KAUST, SA.
  9. PyFR and GiMMiK on Intel KNL: Performance, Scalability, and Applications.
    SIAM CSE17, 27–3 March 2017, Atlanta, Georgia, USA.
  10. Petascale Computational Fluid Dynamics with Python on GPUs.
    NVIDIA GPU Technology Conference, 4–7 April 2016, San Jose, California, USA.
  11. PyFR: Heterogeneous Computing on Mixed Unstructured Grids with Python.
    EuroSciPy 2015, 26–29 August 2015, Cambridge, UK.
  12. PyFR: Next Generation Computational Fluid Dynamics on GPU Platforms.
    NVIDIA GPU Technology Conference, 17–20 March 2015, San Jose, California, USA.
  13. GiMMiK: Generating Bespoke Matrix-Multiplication Kernels for NVIDIA GPUs.
    NVIDIA GPU Technology Conference, 17–20 March 2015, San Jose, California, USA.
  14. Heterogeneous Computing with a Homogeneous Codebase.
    SIAM CSE15, 14–18 March 2015, Salt Lake City, Utah, USA.
  15. Heterogeneous Computing on Mixed Unstructured Grids with PyFR.
    UK Many-Core Developer Conference 2014, 15 December 2014, Cambridge, UK.
  16. PyFR: Technical Challenges of Bringing Next Generation Computational Fluid Dynamics to GPU Platforms.
    NVIDIA GPU Technology Conference, 24–27 March 2014, San Jose, California, USA.
  17. PyFR: An Open Source Python Framework for High-Order CFD on Many-Core Platforms.
    4th International Congress on Computational Engineering and Sciences, 19–24 May 2013, Las Vegas, Nevada, USA.

Invited Presentations

  1. On the Identification of Symmetric Quadrature Rules for Finite Element Methods.
    Texas A&M University Aerospace engineering seminar, 17 September 2020, College Station, Texas, USA.
  2. High-Order Accurate Computational Fluid Dynamics with Applications to a Spinning Golf Ball.
    Department of Mechanical Engineering, Tohoku University, 5 November 2019, Sendai, Miyagi, JP.
  3. High-Order Accurate Computational Fluid Dynamics with Applications to a Spinning Golf Ball.
    Institute of Fluid Science, Tohoku University, 5 November 2019, Sendai, Miyagi, JP.
  4. On the Identification of Symmetric Quadrature Rules for Finite Element Methods.
    Lawrence Livermore National Laboratory, 9 October 2019, Livermore, California, USA.
  5. On the Identification of Symmetric Quadrature Rules for Finite Element Methods.
    Department of Ocean Engineering, Texas A&M University, 25 April 2019, College Station, Texas, USA.
  6. Next Generation CFD: LES with High-Order Methods and Machine Learning.
    Cambridge University, 24 May 2018, Cambridge, UK.
  7. Towards Greener Aviation with Python at Petascale.
    Department of Mechanical and Aerospace Engineering, George Washington University, 22 February 2018, Washington, D.C., USA.
  8. On the Identification of Symmetric Quadrature Rules for Finite Element Methods.
    UC Berkeley scientific computing seminar, 1 November 2017, Berkeley, California, USA.
  9. PyFR: High-Order Accurate Cross-Platform Petascale Computational Fluid Dynamics with Python.
    Princeton MAE seminar, 28 April 2017, Princeton, New Jersey, USA.
  10. On the Identification of Symmetric Quadrature Rules for Finite Element Methods.
    Stanford ICME LA/Opt seminar, 13 April 2017, Stanford, California, USA.
  11. PyFR: High-Order Accurate Cross-Platform Petascale Computational Fluid Dynamics with Python.
    Stanford CTR Turbulence Tea seminar, 10 March 2017, Stanford, California, USA.
  12. PyFR: High-Order Accurate Cross-Platform Petascale Computational Fluid Dynamics with Python.
    Stanford ICME LA/Opt seminar, 9 February 2017, Stanford, California, USA.
  13. PyFR: High-Order Accurate Cross-Platform Petascale Computational Fluid Dynamics with Python.
    AMS seminar series, NASA Ames Research Center, 31 May 2016, Moffett Field, California, USA.
  14. Next Generation High-Order CFD with PyFR.
    NASA Glenn Research Center, 18 February 2015, Cleveland, Ohio, USA.

Poster Presentations

  1. T. Dzanic, K. Shah, and F. D. Witherden,
    Fourier Spectrum Discrepancies in Deep Network Generated Images.
    NeurIPS 2020, 6–12 December 2020.
  2. N. A. Loppi, F. D. Witherden, and P. E. Vincent,
    A High-order Cross-platform Incompressible Navier-Stokes Solver via Artificial Compressibility with Application to Submarine Hydrodynamics.
    SIAM CSE19, 25–1 March 2019, Spokane, Washington, USA.
  3. J. Morton, F. D. Witherden, A. Jameson, and M. J. Kochenderfer,
    Deep Dynamical Modeling and Control of Unsteady Fluid Flows.
    NeurIPS 2018, 2–8 December 2018, Montréal, Quebec, CA.
  4. P. E. Vincent, A. Iyer, F. D. Witherden, B. C. Vermeire, Y. Abe, R-D. Baier, and A. Jameson,
    High-Order Accurate Scale-Resolving Simulations of Low-Pressure Turbine Linear Cascades using Python at Petascale.
    2018 OLCF user meeting, 15–17 May 2018, Oak Ridge, Tennessee, USA.
  5. J. Crabill, D. Manosalvas–Kjono, J. Romero, J. Watkins, F. D. Witherden, and A. Jameson,
    Recent Work in the Aerospace Computing Lab.
    PCCFD 2017, 22–24 May 2017, KAUST, SA.
  6. J. Crabill, D. Manosalvas–Kjono, J. Romero, J. Watkins, F. D. Witherden, and A. Jameson,
    Recent Work in the Aerospace Computing Lab.
    Stanford AA affiliates day, 19 April 2017, Stanford, California, USA.
  7. F. D. Witherden, B. D. Wozniak, F. P. Russell, P. E. Vincent, and P. H. J. Kelly,
    Beating cuBLAS: Automatically Generating Bespoke Matrix Multiplication Kernels Using GiMMiK.
    SC15, 15–20 November 2015, Austin, Texas, USA.
  8. F. D. Witherden, B. C. Vermeire, and P. E. Vincent,
    PyFR: An Open Source Python Framework for High-Order CFD on Heterogeneous Platforms.
    SC14, 16–21 November 2014, New Orleans, Louisiana, USA.
  9. F. D. Witherden, A. M. Farrington, and P. E. Vincent,
    PyFR: An Open Source Python Framework for Solving Advection-Diffusion Type Problems on Streaming Architectures.
    UK Manycore Developer Conference 2013, 16–17 December 2013, Oxford, UK.
  10. F. D. Witherden, A. M. Farrington, and P. E. Vincent,
    PyFR: An Open Source Python Framework for High-Order CFD on Many-Core Platforms.
    4th International Congress on Computational Engineering and Sciences, 19–24 May 2013, Las Vegas, Nevada, USA.