Solving the Discretised Neutron Diffusion Equations using Neural Networks

no code implementations • 24 Jan 2023 • T. R. F. Phillips, C. E. Heaney, C. Boyang, A. G. Buchan, C. C. Pain

For a fuel assembly benchmark, we demonstrate that the solution obtained from our new approach is the same (accounting for solver tolerances) as that obtained from the same discretisation coded in a standard way using Fortran.

Solving the Discretised Boltzmann Transport Equations using Neural Networks: Applications in Neutron Transport

no code implementations • 24 Jan 2023 • T. R. F. Phillips, C. E. Heaney, C. Boyang, A. G. Buchan, C. C. Pain

In this paper we solve the Boltzmann transport equation using AI libraries.

Numerical study of COVID-19 spatial-temporal spreading in London

no code implementations • 19 Feb 2021 • J. Zheng, X. Wu, F. Fang, J. Li, Z. Wang, H. Xiao, J. Zhu, C. C. Pain, P. F. Linden, B. Xiang

Although our results are based on London, since the fundamental knowledge processes are the same, our study can be further extended to other locations (especially the highly air polluted areas) in the world.

Medical Physics Computational Engineering, Finance, and Science Fluid Dynamics