A Mass-Conservative Reduced-Order Algorithm in Solving Optimal Control of Convection-Diffusion Equation
This paper introduces a novel approach, the mass-conservative reduced-order characteristic finite element (MCROCFE) method, designed for optimal control problem governed by convection-diffusion equation. The study delves into scenarios where the original state equation exhibits mass-conservation, ye...
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description | This paper introduces a novel approach, the mass-conservative reduced-order characteristic finite element (MCROCFE) method, designed for optimal control problem governed by convection-diffusion equation. The study delves into scenarios where the original state equation exhibits mass-conservation, yet the velocity field is non-divergence-free. The key points of emphasis are: (1) The method effectively addresses convection-dominated diffusion systems through the application of the characteristic technique; (2) Its efficiency is underscored by leveraging the proper orthogonal decomposition (POD) technique, significantly reducing the scale of solving algebraic equation systems; (3) The proposed scheme, based on the mass-conservative characteristic finite element (MCCFE) method framework and the classical POD technique with a slight adjustment to reduce-order space, maintains mass-conservation for the state variable. A priori error estimates are derived for the mass-conservative reduced-order scheme. Theoretical results are validated through numerical comparisons with the MCCFE method, emphasizing the mass-conservation, accuracy and efficiency of the MCROCFE method. |
doi_str_mv | 10.1007/s10915-024-02620-3 |
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The study delves into scenarios where the original state equation exhibits mass-conservation, yet the velocity field is non-divergence-free. The key points of emphasis are: (1) The method effectively addresses convection-dominated diffusion systems through the application of the characteristic technique; (2) Its efficiency is underscored by leveraging the proper orthogonal decomposition (POD) technique, significantly reducing the scale of solving algebraic equation systems; (3) The proposed scheme, based on the mass-conservative characteristic finite element (MCCFE) method framework and the classical POD technique with a slight adjustment to reduce-order space, maintains mass-conservation for the state variable. A priori error estimates are derived for the mass-conservative reduced-order scheme. 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The study delves into scenarios where the original state equation exhibits mass-conservation, yet the velocity field is non-divergence-free. The key points of emphasis are: (1) The method effectively addresses convection-dominated diffusion systems through the application of the characteristic technique; (2) Its efficiency is underscored by leveraging the proper orthogonal decomposition (POD) technique, significantly reducing the scale of solving algebraic equation systems; (3) The proposed scheme, based on the mass-conservative characteristic finite element (MCCFE) method framework and the classical POD technique with a slight adjustment to reduce-order space, maintains mass-conservation for the state variable. A priori error estimates are derived for the mass-conservative reduced-order scheme. Theoretical results are validated through numerical comparisons with the MCCFE method, emphasizing the mass-conservation, accuracy and efficiency of the MCROCFE method.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>Computational Mathematics and Numerical Analysis</subject><subject>Conservation</subject><subject>Convection-diffusion equation</subject><subject>Divergence</subject><subject>Efficiency</subject><subject>Equations of state</subject><subject>Finite element analysis</subject><subject>Hypotheses</subject><subject>Mathematical and Computational Engineering</subject><subject>Mathematical and Computational Physics</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Methods</subject><subject>Optimal control</subject><subject>Proper Orthogonal Decomposition</subject><subject>Theoretical</subject><subject>Velocity distribution</subject><issn>0885-7474</issn><issn>1573-7691</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LxDAQxYMouK5-AU8Bz9FJ0jbtcVnXP7CyoHsPSZvULt1mN2kLfnuzVvDmYZhheL8Z3kPolsI9BRAPgUJBUwIsiZUxIPwMzWgqOBFZQc_RDPI8JSIRySW6CmEHAEVesBmqF_hNhUCWrgvGj6pvRoPfTTWUpiIbXxmPF23tfNN_7nHT4Q_Xjk1X482hb_aqxZHrvWuxs6dxNGXfuI48NtYOIU54dRzUaXWNLqxqg7n57XO0fVptly9kvXl-XS7WpGQAPcmFTlNVal0UVDGdgraa2bJMORNWaVNABlnFrdEiLTPGgFVUK5rkkbJK8Dm6m84evDsOJvRy5wbfxY-SQx5d55wVUcUmVeldCN5YefDRjf-SFOQpTznlKWOe8idPySPEJyhEcVcb_3f6H-obViZ5oQ</recordid><startdate>20240901</startdate><enddate>20240901</enddate><creator>Song, Junpeng</creator><creator>Wu, Qiuqin</creator><creator>Shi, Yi</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope></search><sort><creationdate>20240901</creationdate><title>A Mass-Conservative Reduced-Order Algorithm in Solving Optimal Control of Convection-Diffusion Equation</title><author>Song, Junpeng ; Wu, Qiuqin ; Shi, Yi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c200t-87b55acbb991a2b50bfb2fcc5327fabe90606d3feb75c62202d1ba14855afa73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Approximation</topic><topic>Computational Mathematics and Numerical Analysis</topic><topic>Conservation</topic><topic>Convection-diffusion equation</topic><topic>Divergence</topic><topic>Efficiency</topic><topic>Equations of state</topic><topic>Finite element analysis</topic><topic>Hypotheses</topic><topic>Mathematical and Computational Engineering</topic><topic>Mathematical and Computational Physics</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Methods</topic><topic>Optimal control</topic><topic>Proper Orthogonal Decomposition</topic><topic>Theoretical</topic><topic>Velocity distribution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Song, Junpeng</creatorcontrib><creatorcontrib>Wu, Qiuqin</creatorcontrib><creatorcontrib>Shi, Yi</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><jtitle>Journal of scientific computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Song, Junpeng</au><au>Wu, Qiuqin</au><au>Shi, Yi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Mass-Conservative Reduced-Order Algorithm in Solving Optimal Control of Convection-Diffusion Equation</atitle><jtitle>Journal of scientific computing</jtitle><stitle>J Sci Comput</stitle><date>2024-09-01</date><risdate>2024</risdate><volume>100</volume><issue>3</issue><spage>65</spage><pages>65-</pages><artnum>65</artnum><issn>0885-7474</issn><eissn>1573-7691</eissn><abstract>This paper introduces a novel approach, the mass-conservative reduced-order characteristic finite element (MCROCFE) method, designed for optimal control problem governed by convection-diffusion equation. 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Theoretical results are validated through numerical comparisons with the MCCFE method, emphasizing the mass-conservation, accuracy and efficiency of the MCROCFE method.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10915-024-02620-3</doi></addata></record> |
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subjects | Algorithms Approximation Computational Mathematics and Numerical Analysis Conservation Convection-diffusion equation Divergence Efficiency Equations of state Finite element analysis Hypotheses Mathematical and Computational Engineering Mathematical and Computational Physics Mathematics Mathematics and Statistics Methods Optimal control Proper Orthogonal Decomposition Theoretical Velocity distribution |
title | A Mass-Conservative Reduced-Order Algorithm in Solving Optimal Control of Convection-Diffusion Equation |
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