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When solving partial differential equations on scattered nodes using the Radial Basis Function-generated Finite Difference (RBF-FD) method, one of the parameters that must be chosen is the stencil size. Focusing on Polyharmonic Spline RBFs…

Numerical Analysis · Mathematics 2026-02-26 Andrej Kolar-Požun , Mitja Jančič , Miha Rot , Gregor Kosec

Radial Basis Function-generated Finite Differences (RBF-FD) is a meshless method that can be used to numerically solve partial differential equations. The solution procedure consists of two steps. First, the differential operator is…

Numerical Analysis · Mathematics 2026-02-26 Andrej Kolar-Požun , Mitja Jančič , Gregor Kosec

We present a generalization of the RBF-FD method that computes RBF-FD weights in finite-sized neighborhoods around the centers of RBF-FD stencils by introducing an overlap parameter $\delta \in [0,1]$ such that $\delta=1$ recovers the…

Numerical Analysis · Mathematics 2017-05-24 Varun Shankar

We present a high-order radial basis function finite difference (RBF-FD) framework for the solution of advection-diffusion equations on time-varying domains. Our framework is based on a generalization of the recently developed Overlapped…

Numerical Analysis · Mathematics 2021-09-15 Varun Shankar , Grady B. Wright , Aaron L. Fogelson

The finite difference time domain method is one of the simplest and most popular methods in computational electromagnetics. This work considers two possible ways of generalising it to a meshless setting by employing local radial basis…

Computational Physics · Physics 2026-02-27 Andrej Kolar-Požun , Gregor Kosec

When solving partial differential equations on scattered nodes using the Radial Basis Function generated Finite Difference (RBF-FD) method, one of the parameters that must be chosen is the stencil size. Focusing on Polyharmonic Spline RBFs…

Numerical Analysis · Mathematics 2026-02-26 Andrej Kolar-Požun , Mitja Jančič , Miha Rot , Gregor Kosec

We describe and test numerically an adaptive meshless generalized finite difference method based on radial basis functions that competes well with the finite element method on standard benchmark problems with reentrant corners of the…

Numerical Analysis · Mathematics 2025-08-26 Dang Thi Oanh , Oleg Davydov , Hoang Xuan Phu

The aim of this paper is to show how rapidly decaying RBF Lagrange functions on the spheres can be used to create effective, stable finite difference methods based on radial basis functions (RBF-FD). For certain classes of PDEs this…

Numerical Analysis · Mathematics 2023-02-17 Wolfgang Erb , Thomas Hangelbroek , Francis J. Narcowich , Christian Rieger , Joseph D. Ward

In this paper, we present how high-order accurate solutions to elliptic partial differential equations can be achieved in arbitrary spatial domains using radial basis function-generated finite differences (RBF-FD) on unfitted node sets…

Numerical Analysis · Mathematics 2024-07-23 Morten E. Nielsen , Bengt Fornberg

This paper presents an adaptive hyperviscosity stabilisation procedure for the Radial Basis Function-generated Finite Difference (RBF-FD) method, aimed at solving linear and non-linear advection-dominated transport equations on domains…

Numerical Analysis · Mathematics 2026-04-22 Miha Rot , Žiga Vaupotič , Andrej Kolar-Požun , Gregor Kosec

In this paper, we introduce a superconvergent approximation method that employs radial basis functions (RBFs) in the numerical solution of conservation laws. The use of RBFs for interpolation and approximation is a well developed area of…

Numerical Analysis · Mathematics 2021-06-21 Andrew Christlieb , William Sands , Hyoseon Yang

Radial Basis Function-generated Finite Differences (RBF-FD) is a popular variant of local strong-form meshless methods that do not require a predefined connection between the nodes, making it easier to adapt node-distribution to the problem…

Computational Engineering, Finance, and Science · Computer Science 2021-06-01 Jure Močnik - Berljavac , Pankaj K Mishra , Jure Slak , Gregor Kosec

This paper introduces a novel meshfree methodology based on Radial Basis Function-Finite Difference (RBF-FD) approximations for the numerical solution of partial differential equations (PDEs) on surfaces of codimension 1 embedded in…

Numerical Analysis · Mathematics 2024-12-20 Víctor Bayona , Argyrios Petras , Cécile Piret , Steven J. Ruuth

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This approach is useful for a higher…

Numerical Analysis · Computer Science 2018-06-21 Zuzana Majdisova , Vaclav Skala

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered datasets in d-dimensional space. It is non-separable approximation, as it is…

Numerical Analysis · Mathematics 2018-06-13 Zuzana Majdisova , Vaclav Skala

Approximation of scattered geometric data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This method is useful for…

Graphics · Computer Science 2018-04-19 Zuzana Majdisova , Vaclav Skala

In this paper, we present a method based on Radial Basis Function (RBF)-generated Finite Differences (FD) for numerically solving diffusion and reaction-diffusion equations (PDEs) on closed surfaces embedded in $\mathbb{R}^d$. Our method…

Numerical Analysis · Mathematics 2014-04-04 Varun Shankar , Grady B. Wright , Robert M. Kirby , Aaron L. Fogelson

A semi-implicit fractional-step method that uses a staggered node layout and radial basis function-finite differences (RBF-FD) to solve the incompressible Navier-Stokes equations is developed. Polyharmonic splines (PHS) with polynomial…

Fluid Dynamics · Physics 2022-12-15 Tianyi Chu , Oliver T. Schmidt

Strong-form meshless methods received much attention in recent years and are being extensively researched and applied to a wide range of problems in science and engineering. However, the solution of elasto-plastic problems has proven to be…

Numerical Analysis · Mathematics 2023-10-02 Gašper Vuga , Boštjan Mavrič , Božidar Šarler

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for big scattered datasets in $n-$dimensional space. It is a non-separable approximation, as it is…

Computational Engineering, Finance, and Science · Computer Science 2018-06-22 Zuzana Majdisova , Vaclav Skala
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