A. Krishnamurthy | Searcharxiv

arXiv2025

A Convergent Structure-Preserving Scheme for Dissipative Solutions of the Rotating Shallow Water System

We design and analyse a semi-implicit finite volume scheme for the two-dimensional rotating shallow water (RSW) equations that is energy stable, well-balanced (capable of preserving discrete geostrophic steady states), consistent, and covergent. The key idea is the introduction of carefully chosen stabilisation terms into the convective fluxes of the mass and momentum equations, as well as the source terms. Under a CFL-type condition, together with an auxiliary time-step restriction arising from the Coriolis forces, we establish the energy stability of the scheme. The stabilisation terms are constructed to vanish at steady states, thereby ensuring the well-balancing property under an appropriate advective CFL condition. We derive a sufficient time-step restriction that guarantees stability, well-balancing, existence of discrete solutions, and positivity simultaneously. Furthermore, under mild boundedness assumptions, we obtain a priori estimates showing that the stabilisation terms converge to zero as the mesh is refined, which establishes the consistency of the scheme. This in turn enables us to prove that numerical solutions generate a Young measure, identifiable as a dissipative measure-valued solution of the RSW system, thereby yielding convergence of the scheme. Finally, we confirm the theoretical results through extensive numerical experiments.

math.NA↗

arXiv2021

Neural-networks model for force prediction in multi-principal-element alloys

Atomistic simulations can provide useful insights into the physical properties of multi-principal-element alloys. However, classical potentials mostly fail to capture key quantum (electronic-structure) effects. We present a deep 3D convolutional neural network (3D CNN) based framework combined with a voxelization technique to design interatomic potentials for chemically complex alloys. We highlight the performance of the 3D CNN model and its efficacy in computing potentials using the medium-entropy alloy TaNbMo. In order to provide insights into the effect of voxel resolution, we implemented two approaches based on the inner and outer bounding boxes. An efficient 3D CNN model, which is as accurate as the density-functional theory (DFT) approach, for calculating potentials will provide a promising schema for accurate atomistic simulations of structure and dynamics of general multi-principle element alloys.

cond-mat.mtrl-sci↗