{"title":"Numerical Simulation of Inverse Retrospective Problems for a Two-Dimensional Heat Equation","authors":"S. A. Kolesnik, E. M. Stifeev","doi":"10.1134/s1995080224602583","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper proposes a new, unique method for numerically solving inverse problems for nonlinear conditions using the example of the problem of restoring the initial condition for a two-dimensional heat equation with boundary conditions of the third kind. In this problem, the initial condition is an unknown function of two variables, and is determined from experimental temperature values. The proposed method is based on using the parametric identification method, the implicit gradient descent method and Tikhonov’s regularization method. An algorithm and a software package for numerical solution have been developed. The use of the implicit gradient descent method allowed for faster convergence (number of iterations) compared to zero-order methods. Numerous results of numerical experiments have been obtained and discussed. An analysis of the behavior of solution functions with and without the use of Tikhonov’s regularizing functional along with the impact of the regularizing parameter has been carried out. The results of computational experiments using the proposed numerical method showed that the error in the results obtained does not exceed the error in the experimental data due to the correct choice of the regularizing parameter.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":"69 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lobachevskii Journal of Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1134/s1995080224602583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
The paper proposes a new, unique method for numerically solving inverse problems for nonlinear conditions using the example of the problem of restoring the initial condition for a two-dimensional heat equation with boundary conditions of the third kind. In this problem, the initial condition is an unknown function of two variables, and is determined from experimental temperature values. The proposed method is based on using the parametric identification method, the implicit gradient descent method and Tikhonov’s regularization method. An algorithm and a software package for numerical solution have been developed. The use of the implicit gradient descent method allowed for faster convergence (number of iterations) compared to zero-order methods. Numerous results of numerical experiments have been obtained and discussed. An analysis of the behavior of solution functions with and without the use of Tikhonov’s regularizing functional along with the impact of the regularizing parameter has been carried out. The results of computational experiments using the proposed numerical method showed that the error in the results obtained does not exceed the error in the experimental data due to the correct choice of the regularizing parameter.
期刊介绍：
Lobachevskii Journal of Mathematics is an international peer reviewed journal published in collaboration with the Russian Academy of Sciences and Kazan Federal University. The journal covers mathematical topics associated with the name of famous Russian mathematician Nikolai Lobachevsky (Lobachevskii). The journal publishes research articles on geometry and topology, algebra, complex analysis, functional analysis, differential equations and mathematical physics, probability theory and stochastic processes, computational mathematics, mathematical modeling, numerical methods and program complexes, computer science, optimal control, and theory of algorithms as well as applied mathematics. The journal welcomes manuscripts from all countries in the English language.
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