Orazbek Narbek , Samat A. Kassabek , Targyn Nauryz
{"title":"A collocation heat polynomials method for one-dimensional inverse Stefan problems","authors":"Orazbek Narbek , Samat A. Kassabek , Targyn Nauryz","doi":"10.1016/j.cam.2024.116356","DOIUrl":null,"url":null,"abstract":"<div><div>The inverse one-phase Stefan problem in one dimension, aimed at identifying the unknown time-dependent heat flux <span><math><mrow><mi>P</mi><mrow><mo>(</mo><mi>t</mi><mo>)</mo></mrow></mrow></math></span> with a known moving boundary position <span><math><mrow><mi>s</mi><mrow><mo>(</mo><mi>t</mi><mo>)</mo></mrow></mrow></math></span>, is investigated. A previous study (Kassabek et al., 2021) attempted to reconstruct the unknown heat flux <span><math><mrow><mi>P</mi><mrow><mo>(</mo><mi>t</mi><mo>)</mo></mrow></mrow></math></span> using the Variational Heat Polynomials Method (VHPM). In this paper, we develop the Collocation Heat Polynomials Method (CHPM) for the reconstruction of the time-dependent heat flux <span><math><mrow><mi>P</mi><mrow><mo>(</mo><mi>t</mi><mo>)</mo></mrow></mrow></math></span>. This method constructs an approximate solution as a linear combination of heat polynomials, which satisfies the heat equation, with the coefficients determined using the collocation method. To address the resulting ill-posed problem, Tikhonov regularization is applied. As an application, we demonstrate the effectiveness of the method on benchmark problems. Numerical results show that the proposed method accurately reconstructs the time-dependent heat flux <span><math><mrow><mi>P</mi><mrow><mo>(</mo><mi>t</mi><mo>)</mo></mrow></mrow></math></span>, even in the presence of significant noise. The results are also compared with those obtained in Kassabek et al. (2021) using the VHPM.</div></div>","PeriodicalId":50226,"journal":{"name":"Journal of Computational and Applied Mathematics","volume":"460 ","pages":"Article 116356"},"PeriodicalIF":2.1000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377042724006046","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
The inverse one-phase Stefan problem in one dimension, aimed at identifying the unknown time-dependent heat flux with a known moving boundary position , is investigated. A previous study (Kassabek et al., 2021) attempted to reconstruct the unknown heat flux using the Variational Heat Polynomials Method (VHPM). In this paper, we develop the Collocation Heat Polynomials Method (CHPM) for the reconstruction of the time-dependent heat flux . This method constructs an approximate solution as a linear combination of heat polynomials, which satisfies the heat equation, with the coefficients determined using the collocation method. To address the resulting ill-posed problem, Tikhonov regularization is applied. As an application, we demonstrate the effectiveness of the method on benchmark problems. Numerical results show that the proposed method accurately reconstructs the time-dependent heat flux , even in the presence of significant noise. The results are also compared with those obtained in Kassabek et al. (2021) using the VHPM.
期刊介绍:
The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest.
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