4 citations · 6 across the 9 of their papers we have counts for
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Learning Spectrally Optimised Mesh-Free Discretisations
Lucas Gerken Starepravo, Henry Broadley, Steven Lind +1
Numerical methods for partial differential equations (PDEs) discretise differential operators, ideally reproducing the action of the continuous operators across all wavenumbers per…
Elasto-inertial transitions in viscoelastic flows through cylinder arrays
Jack R. C. King, Henry M. Broadley, Miguel Beneitez
For dilute solutions of polymers, chaotic flow states can occur at lower Reynolds numbers than required for inertial turbulence in Newtonian fluids, offering the potential for incr…
Learning Mesh-Free Discrete Differential Operators with Self-Supervised Graph Neural Networks
Lucas Gerken Starepravo, Georgios Fourtakas, Steven Lind +3
Mesh-free numerical methods provide flexible discretisations for complex geometries; however, classical meshless discrete differential operators typically trade low computational c…
Compact LABFM: a framework for meshless methods with spectral-like resolving power
Henry M. Broadley, Steven J. Lind, Jack R. C. King
Meshless methods are often used in numerical simulations of systems of partial differential equations (PDEs), particularly those which involve complex geometries or free surfaces.…