Numerical Methods (Theory)
High-Order Methods For Unstructured Grids
Summary: We are interested in various theoretical aspects of high-order numerical methods for unstructured grids. In particular, we are interested in development of so called 'Flux Reconstruction' methods, and associated methodologies for high-order simulation of unsteady turbulent compressible flows in the vicinity of complex geometries.
Numerical Methods (Implementation)
Massively-Parallel Computing
Summary: We are interested in developing software that can efficiently target massively-parallel hardware, such as clusters of Nvidia Tesla GPUs.
Hardware Independent Coding Paradigms
Summary: We are interested in developing software that can simultaneously target a range of hardware platforms, including heterogeneous systems, from a single codebase.
Numerical Methods (Application)
Compressible Aerodynamics
Summary: We are interested in application of computational tools to solve hitherto intractable compressible flow problems within the vicinity of complex engineering geometries. We are particularly interested in compressible flow problems associated with the design of next generation unmanned aerial vehicles.
Biological Fluid Dynamics
Summary: We are interested in simulating blood flow within various regions of the vasculature. We are particularly interested in simulating flow within arterio-venous fistulae (artificial vascular junctions formed in the wrists of patients who need dialysis). Our objective is to understand whether 'abnormal' flow patterns within these fistulae cause them to block and fail.
Openings
PhD Studentship in Aeronautics - High-Fidelity Simulation of Titan/Mars Entry Vehicles with PyFR
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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