Performance Analyses of Mesh-Based Local Finite Element Method and Meshless Global Rbf Collocation Method for Solving Poisson and Stokes Equations

Loading...
Publication Logo

Date

2022

Authors

Karakan, Ismet
Gurkan, Ceren
Avci, Cem

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Open Access Color

Green Open Access

No

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Average
Influence
Average
Popularity
Top 10%

Research Projects

Journal Issue

Abstract

Steady and unsteady Poisson and Stokes equations are solved using mesh dependent Finite Element Method and meshless Radial Basis Function Collocation Method to compare the performances of these two numerical techniques across several criteria. The accuracy of Radial Basis Function Collocation Method with multiquadrics is enhanced by implementing a shape parameter optimization algorithm. For the time-dependent problems, time discretization is done using Backward Euler Method. The performances are assessed over the accuracy, runtime, condition number, and ease of implementation. Three error kinds considered; least square error, root mean square error and maximum relative error. To calculate the least square error using meshless Radial Basis Function Collocation Method, a novel technique is implemented. Imaginary numerical solution surfaces are created, then the volume between those imaginary surfaces and the analytic solution surfaces is calculated, ensuring a fair error calculation. Lastly, all results are put together and trends are observed. The change in runtime vs. accuracy and number of nodes; and the change in accuracy vs. the number of nodes is analyzed. The study indicates the criteria under which Finite Element Method performs better and conditions when Radial Basis Function Collocation Method outperforms its mesh dependent counterpart.(c) 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

Description

Keywords

Point Interpolation Method, Data Approximation Scheme, Galerkin Mlpg Approach, Radial Basis Functions, Vibration Analyses, Convergence, Multiquadrics, Formulation, Point Interpolation Method, Data Approximation Scheme, Galerkin Mlpg Approach, Radial Basis Functions, Elliptic problems, Vibration Analyses, Continuous Galerkin, Convergence, Finite Element Method, Multiquadrics, Radial Basis Function Collocation Method, Formulation, Comparison analysis, Elliptic problems, Galerkin Mlpg Approach, Data Approximation Scheme, Continuous Galerkin, Point Interpolation Method, Comparison analysis, Formulation, Radial Basis Functions, Finite Element Method, Multiquadrics, Radial Basis Function Collocation Method, Convergence, Vibration Analyses, continuous Galerkin, finite element method, Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs, radial basis function collocation method, elliptic problems, Navier-Stokes equations, comparison analysis

Fields of Science

01 natural sciences, 0103 physical sciences, 0101 mathematics

Citation

WoS Q

Q1

Scopus Q

Q1
OpenCitations Logo
OpenCitations Citation Count
4

Source

Mathematics and Computers in Simulation

Volume

197

Issue

Start Page

127

End Page

150
PlumX Metrics
Citations

CrossRef : 4

Scopus : 4

Captures

Mendeley Readers : 8

SCOPUS™ Citations

4

checked on Feb 19, 2026

Web of Science™ Citations

2

checked on Feb 19, 2026

Page Views

3

checked on Feb 19, 2026

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
0.80657796

Sustainable Development Goals

SDG data is not available