Automatic model reduction of differential algebraic systems by proper orthogonal decomposition

被引：2
|
作者：
Khlopov, Dmytro [1 ]
Mangold, Michael [2 ]
机构：
[1] Max Planck Inst Dynam Complex Tech Syst, Sandtorstr 1, D-39106 Magdeburg, Germany
[2] Tech Hsch Bingen, Berlinstr 109, D-55411 Bingen, Germany
来源：
COMPUTERS & CHEMICAL ENGINEERING | 2017年 / 97卷
关键词：
Nonlinear model reduction; Proper orthogonal decomposition; Empirical interpolation; Computer aided modeling; Differential algebraic systems; POINTS INTERPOLATION; EQUATIONS; DYNAMICS; MOMENTS;
D O I：
10.1016/j.compchemeng.2016.11.004
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Proper orthogonal decomposition (POD) is an attractive way to obtain nonlinear low-dimensional models. This article reports on the automatization of the mentioned reduction method. An automatic procedure for the reduction of differential algebraic systems is presented, which is implemented in the modeling and simulation environment ProMoT/Diana. The software tool has been applied to a nonlinear heat conduction model and a continuous fluidized bed crystallizer model. The automatically generated reduced models are significantly smaller than the reference models, while the loss of accuracy is negligible. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码：104 / 113
页数：10
相关论文
共 50 条
  • [31] The Proper Orthogonal Decomposition for Dimensionality Reduction in Mode-Locked Lasers and Optical Systems
    Shlizerman, Eli
    Ding, Edwin
    Williams, Matthew O.
    Kutz, J. Nathan
    [J]. INTERNATIONAL JOURNAL OF OPTICS, 2012, 2012
  • [32] Review for order reduction based on proper orthogonal decomposition and outlooks of applications in mechanical systems
    Lu, Kuan
    Jin, Yulin
    Chen, Yushu
    Yang, Yongfeng
    Hou, Lei
    Zhang, Zhiyong
    Li, Zhonggang
    Fu, Chao
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 123 (264-297) : 264 - 297
  • [33] Application of the transient proper orthogonal decomposition method for order reduction of rotor systems with faults
    Kuan Lu
    Yushu Chen
    Yulin Jin
    Lei Hou
    [J]. Nonlinear Dynamics, 2016, 86 : 1913 - 1926
  • [34] Application of the transient proper orthogonal decomposition method for order reduction of rotor systems with faults
    Lu, Kuan
    Chen, Yushu
    Jin, Yulin
    Hou, Lei
    [J]. NONLINEAR DYNAMICS, 2016, 86 (03) : 1913 - 1926
  • [35] The Method of Proper Orthogonal Decomposition for Dynamical Characterization and Order Reduction of Mechanical Systems: An Overview
    Gaetan Kerschen
    Jean-claude Golinval
    ALEXANDER F. VAKAKIS
    LAWRENCE A. BERGMAN
    [J]. Nonlinear Dynamics, 2005, 41 : 147 - 169
  • [36] The method of proper orthogonal decomposition for dynamical characterization and order reduction of mechanical systems: An overview
    Kerschen, G
    Golinval, JC
    Vakakis, AF
    Bergman, LA
    [J]. NONLINEAR DYNAMICS, 2005, 41 (1-3) : 147 - 169
  • [37] Proper orthogonal decomposition for model updating of non-linear mechanical systems
    Lenaerts, V
    Kerschen, G
    Golinval, JC
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2001, 15 (01) : 31 - 43
  • [38] Model reduction in elastoplasticity: proper orthogonal decomposition combined with adaptive sub-structuring
    Annika Radermacher
    Stefanie Reese
    [J]. Computational Mechanics, 2014, 54 : 677 - 687
  • [39] Model reduction applied to square to rectangular martensitic transformations using proper orthogonal decomposition
    Wang, L. X.
    Melnik, Roderick V. N.
    [J]. APPLIED NUMERICAL MATHEMATICS, 2007, 57 (5-7) : 510 - 520
  • [40] Model order reduction via proper orthogonal decomposition for a lithium-ion cell
    Suhr, Bettina
    Rubesa, Jelena
    [J]. COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2013, 32 (05) : 1735 - 1748
12345