Will Trojak

NA
h-index6
5papers
37citations
Novelty37%
AI Score21

5 Papers

1.2NAJan 25, 2019
Effect of Mesh Quality on Flux Reconstruction in Multi-Dimensions

Will Trojak, Rob Watson, Ashley Scillitoe et al.

Theoretical methods are developed to understand the effect of non-uniform grids on Flux Reconstruction (FR) in multi-dimensions. The analysis reveals that the same effect of expanding and contracting grids is seen in two dimensions as in one dimension. Namely, that expansions cause instability and contractions cause excess dissipation. Subsequent numerical experiments on the Taylor-Green Vortex with jittered elements show the effect of localised regions of expansion and contraction, with an initial increase in the kinetic energy observed on non-uniform meshes. Some comparison is made between second-order FR and second-order finite volume (FV). FR is found to be more resilient to mesh deformation, however, FV is found to be more resolved when operated at second order on the same mesh. In both cases, it is recommended that a kinetic energy preserving/conservation formulation should be used as this can greatly increase resilience to mesh deformation.

1.2NAMay 16, 2018
Temporal Stabilisation of Flux Reconstruction on Linear Problems

Will Trojak, Rob Watson, Paul G. Tucker

Filtering is often used in Large Eddy Simulation with a global filter width, instead here a filter width in the reference domain of high order Flux Reconstruction is considered. It is shown via Von Neumann analysis how filtering effects the dispersion and dissipation of the scheme when spatially and temporally discretised. With it being shown that filtering stabilises the scheme temporally by upto $25\%$ for forth order FR. The impact of filtering on error production is calculated, highlighting the reduction in convective velocity caused and showing numerically the impact on order of accuracy. Finally, the turbulent Taylor-Green case is used to understand the effect of reference domain filtering on the transition to turbulence, and a filter Reynolds number is defined that is shown to be useful in understanding the effect of filtering on simulations.

4.3NAMar 8, 2019
Generalised Sobolev Stable Flux Reconstruction

Will Trojak

A new set of symmetric correction functions is presented for high-order flux reconstruction, that expands upon, while incorporating, all previous correction function sets and opens the possibility for improved performance. By considering FR applied to the linear advection equation, and through modification to the Sobolev norm, criteria are presented for a wider set of correction functions. Legendre polynomials are then used to fulfil these criterion and realise functions for third to fifth order FR. The sufficient conditions for the existence of the modified norms are also explored, before Fourier and Von Neumann analysis are applied to analytically find temporal stability limits for various Runge-Kutta temporal integration schemes. For all cases, correction functions are found that extend the temporal stability of FR. Two application-inspired investigations are performed that aim to explore the effect of aliasing and non-linear equations. In both cases unique correction functions could be found that give good performance, compared to previous FR schemes, while also improving upon the temporal stability limit.

3.8LGMar 27, 2023
Probing optimisation in physics-informed neural networks

Nayara Fonseca, Veronica Guidetti, Will Trojak

A novel comparison is presented of the effect of optimiser choice on the accuracy of physics-informed neural networks (PINNs). To give insight into why some optimisers are better, a new approach is proposed that tracks the training trajectory curvature and can be evaluated on the fly at a low computational cost. The linear advection equation is studied for several advective velocities, and we show that the optimiser choice substantially impacts PINNs model performance and accuracy. Furthermore, using the curvature measure, we found a negative correlation between the convergence error and the curvature in the optimiser local reference frame. It is concluded that, in this case, larger local curvature values result in better solutions. Consequently, optimisation of PINNs is made more difficult as minima are in highly curved regions.

1.2NAJul 5, 2018
Generalised Lebesgue Stable Flux Reconstruction

Will Trojak

A unique set of correction functions for Flux Reconstruction is presented, with there derivation stemming from proving the existence of energy stability in the Lebesgue norm. The set is shown to be incredibly arbitrary with the only union to existing correction function sets being show to be for DG. Von Neumann analysis of both advection and coupled advection-diffusion is used to show that once coupled to a temporal integration method, good CFL performance can be achieved and the correction function may have better dispersion and dissipation for application to implicit LES. Lastly, the turbulent Taylor-Green vortex test case is then used to show that correction functions can be found that improve the accuracy of the scheme when compared to the error levels of Discontinuous Galerkin.