Investigation of Explicit Numerical Methods for Solving Parabolic Equations

Introduction. Numerical methods for solving heat conduction equations are widely used in various fields of science and technology. The development of new improved numerical algorithms for solving parabolic equations makes it possible to increase the accuracy of calculations, remove restrictions on the integration step in time, which will allow us to obtain solutions to practical problems in an acceptable time with high accuracy. The purpose of this work is to study the explicit methods for solving parabolic type equations using the example of solving the equation of thermal conductivity with variable coefficients. Materials and Methods. The paper provides a software implementation of numerical algorithms for solving parabolic type equations: the well-known explicit scheme, the local iteration method, and the hyperbolization method. The algorithms were implemented in C++. The order of approximation of algorithms and their execution time for solving an equation with an analytical solution are analyzed. Results. A numerical study of the schemes has shown that each of them has a second order of approximation in space. However, the estimated time to solve the problem using the hyperbolization method is less. Discussion and Conclusion. In the case of solving systems of equations of the parabolic type, if it is necessary to use explicit schemes, the hyperbolization method will significantly reduce the estimated time of the problem while maintaining the stated order of accuracy.

Authors

Institutions

Publication Details

Journal
Ogarev-online
Published
2025-04-03
DOI
https://doi.org/10.15507/2311-2468.013.202501.064-070
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigation of Explicit Numerical Methods for Solving Parabolic Equations

Е. Е. Пескова, Maksim S. Mustaykin
Ogarev-online
Advanced Numerical Methods in Computational Mathematics
article

Investigation of Explicit Numerical Methods for Solving Parabolic Equations

Е. Е. Пескова, Maksim S. Mustaykin
article en

Abstract

Introduction. Numerical methods for solving heat conduction equations are widely used in various fields of science and technology. The development of new improved numerical algorithms for solving parabolic equations makes it possible to increase the accuracy of calculations, remove restrictions on the integration step in time, which will allow us to obtain solutions to practical problems in an acceptable time with high accuracy. The purpose of this work is to study the explicit methods for solving parabolic type equations using the example of solving the equation of thermal conductivity with variable coefficients. Materials and Methods. The paper provides a software implementation of numerical algorithms for solving parabolic type equations: the well-known explicit scheme, the local iteration method, and the hyperbolization method. The algorithms were implemented in C++. The order of approximation of algorithms and their execution time for solving an equation with an analytical solution are analyzed. Results. A numerical study of the schemes has shown that each of them has a second order of approximation in space. However, the estimated time to solve the problem using the hyperbolization method is less. Discussion and Conclusion. In the case of solving systems of equations of the parabolic type, if it is necessary to use explicit schemes, the hyperbolization method will significantly reduce the estimated time of the problem while maintaining the stated order of accuracy.

Ogarev-onlineVol. 13(1)
National Research Mordovia State University (RU)
Openalex Percentile: Top 93%
Advanced Numerical Methods in Computational Mathematics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.