Structure-preserving Galerkin POD reduced-order modeling of Hamiltonian systems
被引:33
作者:
Gong, Yuezheng
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Beijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing 100193, Peoples R ChinaBeijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing 100193, Peoples R China
Gong, Yuezheng
[1
]
Wang, Qi
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机构:
Beijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing 100193, Peoples R China
Univ South Carolina, Dept Math, Columbia, SC 29208 USA
Nankai Univ, Sch Mat Sci & Engn, Tianjin 300350, Peoples R ChinaBeijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing 100193, Peoples R China
Wang, Qi
[1
,2
,3
]
Wang, Zhu
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Univ South Carolina, Dept Math, Columbia, SC 29208 USABeijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing 100193, Peoples R China
Wang, Zhu
[2
]
机构:
[1] Beijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing 100193, Peoples R China
[2] Univ South Carolina, Dept Math, Columbia, SC 29208 USA
[3] Nankai Univ, Sch Mat Sci & Engn, Tianjin 300350, Peoples R China
The proper orthogonal decomposition reduced-order model (POD-ROM) has been widely used as a computationally efficient surrogate model in large-scale numerical simulations of complex systems. However, when it is applied to a Hamiltonian system, a naive application of the POD method can destroy the Hamiltonian structure in the reduced-order modelin this paper, we develop a new reduced-order modeling approach for Hamiltonian systems, which modifies the Galerkin projection-based POD -ROM so that the appropriate Hamiltonian structure is preserved. Since the POD truncation can degrade the approximation of the Hamiltonian function, we propose to use a POD basis from shifted snapshots to improve the approximation to the Hamiltonian function. We further derive a rigorous a priori error estimate for the structure-preserving ROM and demonstrate its effectiveness in several numerical examples. This approach can be readily extended to dissipative Hamiltonian systems, port-Hamiltonian systems, etc. Published by Elsevier B.V.