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Separated flows past complex geometries are modelled by discrete vortex techniques. The flows are assumed to be rotational and inviscid, and a new technique is described to determine the streamfunctions for linear shear profiles. The…

chao-dyn · Physics 2007-05-23 P. Franzese , L. Zannetti

In this article we develop an algorithm for the efficient simulation of electrolytes in the presence of physical boundaries. In previous work the Discrete Ion Stochastic Continuum Overdamped Solvent (DISCOS) algorithm was derived for triply…

Outside the core of the plasma, the plasma current and pressure rapidly transition to zero in a scrape-off or edge region or plasma-vacuum interface. However, existing tools for fixed-boundary magnetohydrodynamic equilibria in 2D and 3D…

Plasma Physics · Physics 2026-05-05 Alan Kaptanoglu , Tobias Blickhan

A method is proposed for accurately describing arbitrary-shaped free boundaries in single-grid finite-difference schemes for elastodynamics, in a time-domain velocity-stress framework. The basic idea is as follows: fictitious values of the…

Classical Physics · Physics 2007-12-17 Bruno Lombard , Joël Piraux , Céline Gélis , Jean Virieux

A vertical slice model is developed for the Euler-Boussinesq equations with a constant temperature gradient in the direction normal to the slice (the Eady-Boussinesq model). The model is a solution of the full three-dimensional equations…

Numerical Analysis · Mathematics 2017-11-27 Hiroe Yamazaki , Jemma Shipton , Michael J. P. Cullen , Lawrence Mitchell , Colin J. Cotter

We develop a computational method for modeling electrostatic interactions of arbitrarily-shaped, polarizable objects on colloidal length scales, including colloids/nanoparticles, polymers, and surfactants, dispersed in explicit ion…

Soft Condensed Matter · Physics 2024-06-18 Emily Krucker-Velasquez , James W. Swan , Zachary Sherman

Many physical systems of interest involve the close interaction of a flow in a domain with complex, time-varying boundaries. Treatment of boundaries of this nature is cumbersome due to the difficulty in explicitly tracking boundaries that…

Fluid Dynamics · Physics 2025-02-25 Emma M. Boyd , Eric Sandall , Maycon Meier , J. Matt Quinlan , Brandon Runnels

Obtaining predictive low-order models is a central challenge in fluid dynamics. Data-driven frameworks have been widely used to obtain low-order models of aerodynamic systems; yet, resulting models tend to yield predictions that grow…

Research on data-driven ocean models has progressed rapidly in recent years; however, the application of these models to global eddy-resolving ocean forecasting remains limited. The accurate representation of ocean dynamics across a wide…

Machine Learning · Computer Science 2026-01-21 Yuta Hirabayashi , Daisuke Matusoka , Konobu Kimura

For a model convection-diffusion problem, we address the presence of oscillatory discrete solutions, and study difficulties in recovering standard approximation results for its solution. We justify the presence of non-physical oscillations…

Numerical Analysis · Mathematics 2026-01-15 Constantin Bacuta

We develop a new optimisation technique that combines multiresolution subdivision surfaces for boundary description with immersed finite elements for the discretisation of the primal and adjoint problems of optimisation. Similar to wavelets…

Numerical Analysis · Mathematics 2016-01-20 Kosala Bandara , Thomas Rüberg , Fehmi Cirak

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 investigate identifying the boundary of a domain from sample points in the domain. We introduce new estimators for the normal vector to the boundary, distance of a point to the boundary, and a test for whether a point lies within a…

Numerical Analysis · Mathematics 2022-05-12 Jeff Calder , Sangmin Park , Dejan Slepčev

An optimisation scheme is developed to accurately represent the sub-grid scale forcing of a high dimensional chaotic ocean system. Using a simple parameterisation scheme, the velocity components of a 30km resolution shallow water ocean…

Atmospheric and Oceanic Physics · Physics 2015-05-20 Fenwick C. Cooper , Laure Zanna

Point discretization of curved surfaces is required in many applications ranging from object rendering to the solution of surface partial differential equations (PDEs). These applications often impose that surfaces are sampled with local…

Computational Engineering, Finance, and Science · Computer Science 2026-05-06 Lennart J. Schulze , Ivo F. Sbalzarini

Segregation of different cell types is a crucial process for the pattern formation in tissues, in particular during embryogenesis. Since the involved cell interactions are complex and difficult to measure individually in experiments,…

Cell Behavior · Quantitative Biology 2022-09-21 Florian Franke , Sebatian Aland , Hans-Joachim Böhme , Anja Voss-Böhme , Steffen Lange

Bulk-edge correspondence is a wide-ranging principle that applies to topological matter, as well as a precise result established in a large and growing number of cases. According to the principle, the distinctive topological properties of…

Mathematical Physics · Physics 2025-05-12 Gian Michele Graf , Alessandro Tarantola

New parameterizations for the spectra dissipation of wind-generated waves are proposed. The rates of dissipation have no predetermined spectral shapes and are functions of the wave spectrum and wind speed and direction, in a way consistent…

This work proposes a nonlinear finite element method whose nodal values preserve bounds known for the exact solution. The discrete problem involves a nonlinear projection operator mapping arbitrary nodal values into bound-preserving ones…

Numerical Analysis · Mathematics 2023-04-04 Gabriel Barrenechea , Emmanuil Georgoulis , Tristan Pryer , Andreas Veeser

Deep learning models have been the subject of study from various perspectives, for example, their training process, interpretation, generalization error, robustness to adversarial attacks, etc. A trained model is defined by its decision…

Machine Learning · Computer Science 2019-08-09 Roozbeh Yousefzadeh , Dianne P O'Leary
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