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Recovering Heat Source from Fourth-Order Inverse Problems by Weighted Gradient Collocation
The weighted gradient reproducing kernel collocation method is introduced to recover the heat source described by Poisson’s equation. As it is commonly known that there is no unique solution to the inverse heat source problem, the weak solution based on a priori assumptions is considered herein. In...
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Published in: | Mathematics (Basel) 2022-01, Vol.10 (2), p.241 |
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description | The weighted gradient reproducing kernel collocation method is introduced to recover the heat source described by Poisson’s equation. As it is commonly known that there is no unique solution to the inverse heat source problem, the weak solution based on a priori assumptions is considered herein. In view of the fourth-order partial differential equation (PDE) in the mathematical model, the high-order gradient reproducing kernel approximation is introduced to efficiently untangle the problem without calculating the high-order derivatives of reproducing kernel shape functions. The weights of the weighted collocation method for high-order inverse analysis are first determined. In the benchmark analysis, the unclear illustration in the literature is clarified, and the correct interpretation of numerical results is given particularly. Two mathematical formulations with four examples are provided to demonstrate the viability of the method, including the extreme cases of the limited accessible boundary. |
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Two mathematical formulations with four examples are provided to demonstrate the viability of the method, including the extreme cases of the limited accessible boundary.</description><subject>Approximation</subject><subject>Boundary conditions</subject><subject>Collocation methods</subject><subject>fourth-order PDE</subject><subject>gradient approximation</subject><subject>heat source</subject><subject>Inverse problems</subject><subject>Kernels</subject><subject>Mathematical analysis</subject><subject>Mathematics</subject><subject>Numerical analysis</subject><subject>Partial differential equations</subject><subject>Poisson equation</subject><subject>Regularization methods</subject><subject>reproducing kernel approximation</subject><subject>Shape functions</subject><subject>weighted collocation method</subject><issn>2227-7390</issn><issn>2227-7390</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkU1LAzEQhoMoKLU3f0DAq6v5apI9SlFbKFRUELyEJDtpt-xuNBsF_73RijiXGWZenhnmReiMkkvOa3LV27ylhDDCBD1AJ4wxVakyOPxXH6PpOO5IiZpyLeoT9PIAPn5AaocNXoDN-DG-Jw84pNjj21LnbbVODSS8HIpsBHyfouugH7H7xM_QbrYZGnyXbNPCkPE8dl30NrdxOEVHwXYjTH_zBD3d3jzNF9VqfbecX68qz6XKlQTvgTsqBVEiENr4wJl1WnmutZCaUxJ4HXwtiJjJmjfCzoAEJ7UOXCs-Qcs9tol2Z15T29v0aaJtzU8jpo2xKbe-AyM5eC3DjIJywgVVQBRqxr3yDpyAwjrfs15TfHuHMZtdecFQrjdMMsqFpkQW1cVe5VMcxwThbysl5tsL898L_gVFC3w8</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Yang, Judy P.</creator><creator>Li, Hsiang-Ming</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7TB</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M7S</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-3792-2821</orcidid></search><sort><creationdate>20220101</creationdate><title>Recovering Heat Source from Fourth-Order Inverse Problems by Weighted Gradient Collocation</title><author>Yang, Judy P. ; Li, Hsiang-Ming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-6ecce3b164074f01dcf32ab87c388468310f39fc94045693d4a5e0fb688f3873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Approximation</topic><topic>Boundary conditions</topic><topic>Collocation methods</topic><topic>fourth-order PDE</topic><topic>gradient approximation</topic><topic>heat source</topic><topic>Inverse problems</topic><topic>Kernels</topic><topic>Mathematical analysis</topic><topic>Mathematics</topic><topic>Numerical analysis</topic><topic>Partial differential equations</topic><topic>Poisson equation</topic><topic>Regularization methods</topic><topic>reproducing kernel approximation</topic><topic>Shape functions</topic><topic>weighted collocation method</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Judy P.</creatorcontrib><creatorcontrib>Li, Hsiang-Ming</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Engineering Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Mathematics (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Judy P.</au><au>Li, Hsiang-Ming</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Recovering Heat Source from Fourth-Order Inverse Problems by Weighted Gradient Collocation</atitle><jtitle>Mathematics (Basel)</jtitle><date>2022-01-01</date><risdate>2022</risdate><volume>10</volume><issue>2</issue><spage>241</spage><pages>241-</pages><issn>2227-7390</issn><eissn>2227-7390</eissn><abstract>The weighted gradient reproducing kernel collocation method is introduced to recover the heat source described by Poisson’s equation. As it is commonly known that there is no unique solution to the inverse heat source problem, the weak solution based on a priori assumptions is considered herein. In view of the fourth-order partial differential equation (PDE) in the mathematical model, the high-order gradient reproducing kernel approximation is introduced to efficiently untangle the problem without calculating the high-order derivatives of reproducing kernel shape functions. The weights of the weighted collocation method for high-order inverse analysis are first determined. In the benchmark analysis, the unclear illustration in the literature is clarified, and the correct interpretation of numerical results is given particularly. 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subjects | Approximation Boundary conditions Collocation methods fourth-order PDE gradient approximation heat source Inverse problems Kernels Mathematical analysis Mathematics Numerical analysis Partial differential equations Poisson equation Regularization methods reproducing kernel approximation Shape functions weighted collocation method |
title | Recovering Heat Source from Fourth-Order Inverse Problems by Weighted Gradient Collocation |
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