Stochastic Galerkin method and port-Hamiltonian form for linear dynamical systems of second order

被引:1
|
作者
Pulch, Roland [1 ]
机构
[1] Univ Greifswald, Inst Math & Comp Sci, Walther Rathenau Str 47, D-17489 Greifswald, Germany
关键词
Ordinary differential equation; Port-Hamiltonian system; Hamiltonian function; Stochastic Galerkin method; Model order reduction; Uncertainty quantification; ORDER REDUCTION; MODEL-REDUCTION;
D O I
10.1016/j.matcom.2023.09.005
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We investigate linear dynamical systems of second order. Uncertainty quantification is applied, where physical parameters are substituted by random variables. A stochastic Galerkin method yields a linear dynamical system of second order with high dimensionality. A structure-preserving model order reduction (MOR) produces a small linear dynamical system of second order again. We arrange an associated port-Hamiltonian (pH) formulation of first order for the second-order systems. Each pH system implies a Hamiltonian function describing an internal energy. We examine the properties of the Hamiltonian function for the stochastic Galerkin systems. We show numerical results using a test example, where both the stochastic Galerkin method and structure-preserving MOR are applied.(c) 2023 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:187 / 197
页数:11
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