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Title: High-order incompressible computational fluid dynamics on modern hardware architectures
Author: Loppi, Niki Andreas
ISNI:       0000 0004 8499 5315
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2019
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In this thesis, a high-order incompressible Navier-Stokes solver is developed in the Python-based PyFR framework. The solver is based on the artificial compressibility formulation with a Flux Reconstruction (FR) discretisation in space and explicit dual time stepping in time. In order to reduce time to solution, explicit convergence acceleration techniques are developed and implemented. These techniques include polynomial multigrid, a novel locally adaptive pseudo-time stepping approach and novel stability-optimised Runge-Kutta schemes. Choices regarding the numerical methods and implementation are motivated as follows. Firstly, high-order FR is selected as the spatial discretisation due to its low dissipation and ability to work with unstructured meshes of complex geometries. Being discontinuous, it also allows the majority of computation to be performed locally. Secondly, convergence acceleration techniques are restricted to explicit methods in order to retain the spatial locality provided by FR, which allows efficient harnessing of the massively parallel compute capability of modern hardware. Thirdly, the solver is implemented in the PyFR framework with cross-platform support such that it can run on modern heterogeneous systems via an MPI + X model, with X being CUDA, OpenCL or OpenMP. As such, it is well-placed to remain relevant in an era of rapidly evolving hardware architectures. The new software constitutes the first high-order accurate cross-platform imple- mentation of an incompressible Navier-Stokes solver via artificial compressibility. The solver and the convergence acceleration techniques are validated for a range of turbu- lent test cases. Furthermore, performance of the convergence acceleration techniques is assessed with a 2D cylinder test case, showing speed-up factors of over 20 relative to global RK4 pseudo-time stepping when all of the technologies are combined. Fi- nally, a simulation of the DARPA SUBOFF submarine model is undertaken using the solver and all convergence acceleration techniques. Excellent agreement with previ- ous studies is obtained, demonstrating that the technology can be used to conduct high-fidelity implicit Large Eddy Simulation of industrially relevant problems at scale using hundreds of GPUs.
Supervisor: Vincent, Peter Sponsor: Engineering and Physical Sciences Research Council ; BAE Systems
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral