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We develop novel numerical methods and apply them to solve challenging fluid flow problems in various areas of science, engineering, and medicine. We are particularly interested in theoretical aspects of high-order numerical methods for unstructured grids, as well as their implementation for a range of modern hardware platforms.

News

'Turbulent Channel Flow' - Checkout our latest paper on identifying eigenmodes of averaged small-amplitude perturbations to turbulent channel flow

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'Step Inside a Jet Engine' - Results from our latest PyFR simulations of flow over low pressure turbine blades on show at the Imperial Fringe

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'Implant may Offer Kidney Patients Easier Dialysis' - Our latest work on suppressing unsteady flow in arterio-venous fistulae featured in the Times

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'New Symmetric Quadrature Rules' - Checkout our latest paper on identification of symmetric quadrature rules for finite element methods

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Recent Papers

Direct Numerical Simulation of flow over a Triangular Airfoil under Martian Atmospheric Conditions. L. Caros, O.R.H. Buxton, T. Shigeta, T. Nagata, T. Nonomura, K. Asai, P. E. Vincent. Accepted for publication in AIAA Journal.
Abstract: Martian conditions present various challenges when designing rotorcraft. Specifically, the thin atmosphere and low sound speed require Martian rotor blades to operate in a low-Reynolds-number (100010,000) compressible regime, for which conventional airfoils are not designed. Here, we use PyFR to undertake high-order direct numerical simulations (DNS) of flow over a triangular airfoil at a Mach number of 0.15 and Reynolds number of 3000. Initially, spanwise periodic DNS are undertaken. Extending the domain-span-to-chord ratio from 0.3 to 0.6 leads to better agreement with wind-tunnel data at higher angles of attack, when the flow is separated. This is because smaller domain spans artificially suppress three-dimensional breakdown of coherent structures above the suction surface of the airfoil. Subsequently, full-span DNS in a virtual wind tunnel are undertaken, including all wind-tunnel walls. These capture blockage and wall boundary-layer effects, leading to better agreement with wind-tunnel data for all angles of attack compared to spanwise periodic DNS. The results are important in terms of understanding discrepancies between previous spanwise periodic DNS and wind-tunnel data. They also demonstrate the utility of high-order DNS as a tool for accurately resolving flow over triangular airfoils under Martian conditions.

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Cache Blocking Strategies Applied to Flux Reconstruction. S. Akkurt, F. D. Witherden, P. E. Vincent. Computer Physics Communications, Volume 271, 2022.
Abstract: On modern hardware architectures, the performance of Flux Reconstruction (FR) methods can be limited by memory bandwidth. In a typical implementation, these methods are implemented as a chain of distinct kernels. Often, a dataset which has just been written in the main memory by a kernel is read back immediately by the next kernel. One way to avoid such a redundant expenditure of memory bandwidth is kernel fusion. However, on a practical level kernel fusion requires that the source for all kernels be available, thus preventing calls to certain third-party library functions. Moreover, it can add substantial complexity to a codebase. An alternative to full kernel fusion is cache blocking. But for this to be effective, CPU cache has to be meaningfully big. Historically, size of L1 and L2 caches prevented cache blocking for high-order CFD applications. However in recent years, size of L2 cache has grown from around 0.25 MiB to 1.25 MiB, and made it possible to apply cache blocking for high-order CFD codes. In this approach, kernels remain distinct, and are executed one after another on small chunks of data that can fit in the cache, as opposed to on full datasets. These chunks of data stay in the cache and whenever a kernel requests access to data that is already in the cache, memory bandwidth is conserved. In this study, a data structure that facilitates cache blocking is considered, and a range of kernel grouping configurations for an FR based Euler solver are examined. A theoretical study is conducted for hexahedral elements with no anti-aliasing at p = 3 and p = 4 in order to determine the predicted performance of a few kernel grouping configurations. Then, these candidates are implemented in the PyFR solver and the performance gains in practice are compared with the theoretical estimates that range between 2.05x and 2.50x. An inviscid Taylor-Green Vortex test case is used as a benchmark, and the most performant configuration leads to a speedup of approximately 2.81x in practice.

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Openings

PhD Studentship - Development of In-situ Visualisation and Analysis Technology for High-Fidelity Computational Fluid Dynamics
Summary: A PhD Studentship is currently available. The project, will involve addition of 'in-situ' visualisation, processing, and analysis technology to PyFR, an open-source high-order massively-parallel CFD platform, as well as its application to solve a range of challenging unsteady flow problems. Candidates should hold, or expect to obtain, an undergraduate degree in a numerate discipline. Previous programming experience is important (ideally Python, C++ and CUDA).

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Recent Seminars

PyFR: Latest Developments and Future Roadmap. P. E. Vincent. Journal of Computational Physics Seminar Series. May 2022.
Towards Green Aviation with Python at Petascale. P. E. Vincent. Tokyo University of Science, Tokyo, Japan. December 2017.

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