Parametric model order reduction of thermal models using the bilinear interpolatory rational Krylov algorithm

被引:12
|
作者
Bruns, Angelika [1 ]
Benner, Peter [2 ]
机构
[1] Robert Bosch GmbH, D-70839 Gerlingen, Germany
[2] Max Planck Inst Dynam Complex Tech Syst, D-39106 Magdeburg, Germany
关键词
34K17; 93A15; stability preservation; finite element modelling; thermal heat transfer; parametric model order reduction;
D O I
10.1080/13873954.2014.924534
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The Bilinear Interpolatory Rational Krylov Algorithm (BIRKA; P. Benner and T. Breiten, Interpolation-based H-2-model reduction of bilinear control systems, SIAM J. Matrix Anal. Appl. 33 (2012), pp. 859-885. doi:10.1137/110836742) is a recently developed method for Model Order Reduction (MOR) of bilinear systems. Here, it is used and further developed for a certain class of parametric systems. As BIRKA does not preserve stability, two different approaches generating stable reduced models are presented. In addition, the convergence for a modified version of BIRKA for large systems is analysed and a method for detecting divergence possibly resulting from this modification is proposed. The behaviour of the algorithm is analysed using a finite element model for the thermal analysis of an electrical motor. The reduction of two different motor models, incorporating seven and thirteen different physical parameters, is performed.
引用
下载
收藏
页码:103 / 129
页数:27
相关论文
共 50 条
  • [21] Interpolatory tensorial reduced order models for parametric dynamical systems
    V. Mamonov, Alexander
    Olshanskii, Maxim A.
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 397
  • [22] Model order reduction of dynamical structural simulation models of electric motors using Krylov subspaces
    Schwarzer, M.
    Barti, E.
    Bein, T.
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2014) AND INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2014), 2014, : 1473 - 1486
  • [23] A novel reduced-order algorithm for rational models based on Arnoldi process and Krylov subspace
    Chen, Jing
    Huang, Biao
    Gan, Min
    Chen, C. L. Philip
    AUTOMATICA, 2021, 129
  • [24] Interpolatory model reduction of quadratic-bilinear dynamical systems with quadratic-bilinear outputs
    Alejandro N. Diaz
    Matthias Heinkenschloss
    Ion Victor Gosea
    Athanasios C. Antoulas
    Advances in Computational Mathematics, 2023, 49
  • [25] Model reduction of bilinear system using genetic algorithm
    Saragih, R. (roberd@math.itb.ac.id), 1600, Science and Engineering Research Support Society (07):
  • [26] Interpolatory model reduction of quadratic-bilinear dynamical systems with quadratic-bilinear outputs
    Diaz, Alejandro N.
    Heinkenschloss, Matthias
    Gosea, Ion Victor
    Antoulas, Athanasios C.
    ADVANCES IN COMPUTATIONAL MATHEMATICS, 2023, 49 (06)
  • [27] A model order reduction technique for parametric uncertain models
    Baki, H
    Munro, N
    UKACC INTERNATIONAL CONFERENCE ON CONTROL '98, VOLS I&II, 1998, : 302 - 306
  • [28] Research on rational Krylov subspace model order reduction algorithm for three-dimensional multi-frequency CSEM modelling
    Zhou JianMei
    Liu WenTao
    Liu Hang
    Li Xiu
    Qi ZhiPeng
    CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2018, 61 (06): : 2525 - 2536
  • [29] Interpolatory Model Order Reduction Method for Second Order Systems
    Qiu, Zhi-Yong
    Jiang, Yao-Lin
    Yuan, Jia-Wei
    ASIAN JOURNAL OF CONTROL, 2018, 20 (01) : 312 - 322
  • [30] Rational Krylov algorithms for eigenvalue computation and model reduction
    Ruhe, A
    Skoogh, D
    APPLIED PARALLEL COMPUTING: LARGE SCALE SCIENTIFIC AND INDUSTRIAL PROBLEMS, 1998, 1541 : 491 - 502