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We present a novel discontinuous Galerkin finite element method for numerical simulations of the rotating thermal shallow water equations in complex geometries using curvilinear meshes, with arbitrary accuracy. We derive an entropy…

Numerical Analysis · Mathematics 2024-01-19 Kieran Ricardo , Kenneth Duru , David Lee

The increasing extreme weather events poses unprecedented challenges on power system operation because of their uncertain and sequential impacts on power systems. This paper proposes the concept of an extended steady-state security region…

Optimization and Control · Mathematics 2019-11-25 Chong Wang , Feng Wu , Ping Ju , Shunbo Lei , Tianguang Lu , Yunhe Hou

We develop numerical methods to simulate the fluid-mechanical erosion of many bodies in two-dimensional Stokes flow. The broad aim is to simulate the erosion of a porous medium (e.g. groundwater flow) with grain-scale resolution. Our fluid…

Numerical Analysis · Mathematics 2018-09-26 Bryan D. Quaife , M. Nicholas J. Moore

We test and improve the numerical schemes in our smoothed particle hydrodynamics (SPH) code for cosmological simulations, including the pressure-entropy formulation (PESPH), a time-dependent artificial viscosity, a refined timestep…

This study presents a high-order, space-time coupled arbitrary Lagrangian Eulerian (ALE) compact gas-kinetic scheme (GKS) for the shallow water equations on moving unstructured meshes. The proposed method preserves both the geometric…

Numerical Analysis · Mathematics 2025-10-17 Fengxiang Zhao , Jianping Gan , Kun XU

The thermal lattice Boltzmann flux solver (TLBFS) has been proposed to overcome the drawbacks of the thermal lattice Boltzmann models. However, as a weakly compressible model, its mechanism of good numerical stability for high Rayleigh…

Fluid Dynamics · Physics 2022-03-01 Jinhua Lu , Chuanshan Dai , Peng Yu

The stability of classical semi-implicit scheme, and some more advanced iterative schemes recently proposed for Numerical Weather Prediction (NWP) purpose is examined. In all these schemes, the solution of the centred-implicit non-linear…

Atmospheric and Oceanic Physics · Physics 2009-11-10 Pierre Benard

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising…

Fluid Dynamics · Physics 2022-03-14 Ryley McConkey , Eugene Yee , Fue-Sang Lien

This paper studies non inf-sup stable finite element approximations to the evolutionary Navier--Stokes equations. Several local projection stabilization (LPS) methods corresponding to different stabilization terms are analyzed, thereby…

Numerical Analysis · Mathematics 2017-09-27 Javier de Frutos , Bosco García-Archilla , Volker John , Julia Novo

In this paper we propose a stable and robust strategy to approximate the 3d incompressible hydrostatic Euler and Navier-Stokes systems with free surface. Compared to shallow water approximation of the Navier-Stokes system, the idea is to…

We introduce a novel recursive process to a neural-network-based subgrid-scale (NN-based SGS) model for large eddy simulation (LES) of high Reynolds number turbulent flow. This process is designed to allow an SGS model to be applicable to a…

Fluid Dynamics · Physics 2024-12-04 Chonghyuk Cho , Jonghwan Park , Haecheon Choi

We propose and analyse a novel, fully discrete numerical algorithm for the approximation of the generalised Stokes system forced by transport noise -- a prototype model for non-Newtonian fluids including turbulence. Utilising the Gradient…

Numerical Analysis · Mathematics 2024-12-20 Jerome Droniou , Kim-Ngan Le , Jörn Wichmann

Stochastic nonlinear dynamical systems can undergo rapid transitions relative to the change in their forcing, for example due to the occurrence of multiple equilibrium solutions for a specific interval of parameters. In this paper, we…

Data Analysis, Statistics and Probability · Physics 2020-11-12 S. Baars , D. Castellana , F. W. Wubs , H. A. Dijkstra

Semi-implicit semi-Lagrangian (SISL) methods are commonly used for the shallow water equations (SWE) because they allow for larger time steps than those permitted by the Courant-Friedrichs-Lewy (CFL) stability condition in Eulerian schemes.…

Numerical Analysis · Mathematics 2026-05-05 Michael Chiwere , Daniel Fortunato , Grady B. Wright

Smoothed particle hydrodynamics (SPH) has been extensively used to model high and low Reynolds number flows, free surface flows and collapse of dams, study pore-scale flow and dispersion, elasticity, and thermal problems. In different…

Numerical Analysis · Mathematics 2017-12-01 Alexander A. Lukyanov , Kees Vuik

This study proposes a novel deep-learning-based method for generating reduced representations of turbulent flows that ensures efficient storage and transfer while maintaining high accuracy during decompression. A Swin-Transformer network…

Fluid Dynamics · Physics 2023-09-19 Meng Zhang , Mustafa Z Yousif , Linqi Yu , HeeChang Lim

Many successful methods to learn dynamical systems from data have recently been introduced. However, ensuring that the inferred dynamics preserve known constraints, such as conservation laws or restrictions on the allowed system states,…

Machine Learning · Computer Science 2024-02-16 Alistair White , Niki Kilbertus , Maximilian Gelbrecht , Niklas Boers

A new model description for the numerical simulation of elastic stents is proposed. Based on the new formulation an inf-sup inequality for the finite element discretization is proved and the proof of the inf-sup inequality for the…

Numerical Analysis · Mathematics 2018-12-27 Luka Grubisic , Matko Ljulj , Volker Mehrmann , Josip Tambaca

Used for centuries to enhance mechanical properties of materials, solid solution strengthening (SSS) is a classical metallurgical method in which small amounts of impurity elements are added to a base metal. Developed for dilute alloys,…

Materials Science · Physics 2025-02-28 Aoyan Liang , Nicolas Bertin , Xinran Zhou , Sylvie Aubry , Vasily V. Bulatov

Numerical simulation of non-linear partial differential equations plays a crucial role in modeling physical science and engineering phenomena, such as weather, climate, and aerodynamics. Recent Machine Learning (ML) models trained on…

Machine Learning · Computer Science 2023-02-17 Zhiqing Sun , Yiming Yang , Shinjae Yoo