David Moxey is a Reader in Engineering in the Department of Engineering at King's College London, honorary senior lecturer in the Department of Aeronautics at Imperial College London and an honorary associate professor in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter.
For more information on his research and background, see David's personal webpage which has a complete publication record and further information on research areas.
Lykkegaard MB, Dodwell TJ, Moxey D, 2021, Accelerating uncertainty quantification of groundwater flow modelling using a deep neural network proxy, Computer Methods in Applied Mechanics and Engineering, Vol:383, ISSN:0045-7825
Laughton E, Tabor G, Moxey D, 2021, A comparison of interpolation techniques for non-conformal high-order discontinuous Galerkin methods, Computer Methods in Applied Mechanics and Engineering, Vol:381, ISSN:0045-7825
et al., 2021, Nektar++: Design and implementation of an implicit, spectral/hp element, compressible flow solver using a Jacobian-free Newton Krylov approach, Computers & Mathematics With Applications, Vol:81, ISSN:0898-1221, Pages:351-372
et al., 2020, rp-adaptation for compressible flows, International Journal for Numerical Methods in Engineering, Vol:121, ISSN:0029-5981, Pages:5405-5425
et al., 2020, A comparison of the shared-memory parallel programming models OpenMP, OpenACC and Kokkos in the context of implicit solvers for high-order FEM, Computer Physics Communications, Vol:255, ISSN:0010-4655, Pages:1-15