Model Order Reduction of Electromagnetic Particle-in-Cell Kinetic Plasma Simulations via Proper Orthogonal Decomposition
The proper orthogonal decomposition technique is applied to a finite-element time-domain particle-in-cell (PIC) algorithm for the simulation of kinetic plasmas, resulting in a reduced-order system. The reduced model is tested with representative examples involving an accelerated electron beam and a...
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Veröffentlicht in: | IEEE transactions on plasma science 2019-12, Vol.47 (12), p.5239-5250 |
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creator | Nicolini, Julio L. Na, Dong-Yeop Teixeira, Fernando L. |
description | The proper orthogonal decomposition technique is applied to a finite-element time-domain particle-in-cell (PIC) algorithm for the simulation of kinetic plasmas, resulting in a reduced-order system. The reduced model is tested with representative examples involving an accelerated electron beam and a plasma ball expansion and compared with full-order simulations. The strengths and weakness of this type of model order reduction when applied to PIC algorithms are discussed through the analysis of the results. In particular, the method allows for a major reduction in the field degrees of freedom necessary to capture the relevant physics, but it can also lead to spurious results if proper care is not taken when assembling the reduced-order system. |
doi_str_mv | 10.1109/TPS.2019.2950377 |
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The reduced model is tested with representative examples involving an accelerated electron beam and a plasma ball expansion and compared with full-order simulations. The strengths and weakness of this type of model order reduction when applied to PIC algorithms are discussed through the analysis of the results. In particular, the method allows for a major reduction in the field degrees of freedom necessary to capture the relevant physics, but it can also lead to spurious results if proper care is not taken when assembling the reduced-order system.</description><identifier>ISSN: 0093-3813</identifier><identifier>EISSN: 1939-9375</identifier><identifier>DOI: 10.1109/TPS.2019.2950377</identifier><identifier>CODEN: ITPSBD</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Computer simulation ; Decomposition ; Electron beams ; Kinetic theory ; Mathematical model ; Maxwell–Vlasov equations ; model order reduction (MOR) ; Model reduction ; Model testing ; Particle in cell technique ; particle-in-cell (PIC) algorithm ; plasma ; Plasmas ; Proper Orthogonal Decomposition ; Reduced order models ; Reduced order systems ; Time-domain analysis</subject><ispartof>IEEE transactions on plasma science, 2019-12, Vol.47 (12), p.5239-5250</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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The reduced model is tested with representative examples involving an accelerated electron beam and a plasma ball expansion and compared with full-order simulations. The strengths and weakness of this type of model order reduction when applied to PIC algorithms are discussed through the analysis of the results. In particular, the method allows for a major reduction in the field degrees of freedom necessary to capture the relevant physics, but it can also lead to spurious results if proper care is not taken when assembling the reduced-order system.</description><subject>Algorithms</subject><subject>Computer simulation</subject><subject>Decomposition</subject><subject>Electron beams</subject><subject>Kinetic theory</subject><subject>Mathematical model</subject><subject>Maxwell–Vlasov equations</subject><subject>model order reduction (MOR)</subject><subject>Model reduction</subject><subject>Model testing</subject><subject>Particle in cell technique</subject><subject>particle-in-cell (PIC) algorithm</subject><subject>plasma</subject><subject>Plasmas</subject><subject>Proper Orthogonal Decomposition</subject><subject>Reduced order models</subject><subject>Reduced order systems</subject><subject>Time-domain analysis</subject><issn>0093-3813</issn><issn>1939-9375</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEtLAzEUhYMoWKt7wU3A9dTcJPPIUuoTKy22roeYuakpmaYmU9F_75QWV2dxv3O4fIRcAhsBMHWzmM1HnIEacZUzUZZHZABKqEyJMj8mA8aUyEQF4pScpbRiDGTO-ID8vIYGPZ3GBiN9w2ZrOhfWNFh679F0MbR6ucbOGTrTsQ-PmVtnY_SevrjDwevUajp37dbrXTvRb6fpLIZNvzmN3WdYhrX29A5NaDchuR10Tk6s9gkvDjkk7w_3i_FTNpk-Po9vJ5nhCrqM24I1AFILzkE0AkFrFAoK2fCqsDznlknWYAEfSkorCmOLvJSysJUweWHEkFzvdzcxfG0xdfUqbGP_Tqq54DlUUoLoKbanTAwpRbT1JrpWx98aWL3zW_d-653f-uC3r1ztKw4R__FKccVKJv4A0tV3WA</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Nicolini, Julio L.</creator><creator>Na, Dong-Yeop</creator><creator>Teixeira, Fernando L.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The reduced model is tested with representative examples involving an accelerated electron beam and a plasma ball expansion and compared with full-order simulations. The strengths and weakness of this type of model order reduction when applied to PIC algorithms are discussed through the analysis of the results. In particular, the method allows for a major reduction in the field degrees of freedom necessary to capture the relevant physics, but it can also lead to spurious results if proper care is not taken when assembling the reduced-order system.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TPS.2019.2950377</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-1920-9122</orcidid><orcidid>https://orcid.org/0000-0002-1562-1462</orcidid></addata></record> |
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subjects | Algorithms Computer simulation Decomposition Electron beams Kinetic theory Mathematical model Maxwell–Vlasov equations model order reduction (MOR) Model reduction Model testing Particle in cell technique particle-in-cell (PIC) algorithm plasma Plasmas Proper Orthogonal Decomposition Reduced order models Reduced order systems Time-domain analysis |
title | Model Order Reduction of Electromagnetic Particle-in-Cell Kinetic Plasma Simulations via Proper Orthogonal Decomposition |
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