ISOGEOMETRIC ANALYSIS AND PROPER ORTHOGONAL DECOMPOSITION FOR THE ACOUSTIC WAVE EQUATION

被引:21
|
作者
Zhu, Shengfeng [1 ,2 ]
Dede, Luca [3 ]
Quarteroni, Alfio [3 ,4 ]
机构
[1] East China Normal Univ, Dept Math, Shanghai 200241, Peoples R China
[2] East China Normal Univ, Shanghai Key Lab Pure Math & Math Practice, Shanghai 200241, Peoples R China
[3] Ecole Polytech Fed Lausanne, MATHICSE Math Inst Computat Sci & Engn, CMCS Chair Modeling & Sci Comp, CH-1015 Lausanne, Switzerland
[4] Politecn Milan, Dept Math, MOX Modeling & Sci Comp, Piazza L Vinci 32, I-20133 Milan, Italy
基金
中国国家自然科学基金;
关键词
Isogeometric analysis; proper orthogonal decomposition; reduced order modeling; acoustic wave equation; PARTIAL-DIFFERENTIAL-EQUATIONS; REDUCED-ORDER MODELS; FINITE-ELEMENT; STRUCTURAL-ANALYSIS; FLUID-DYNAMICS; NURBS; APPROXIMATION; REFINEMENT; PDES; POD;
D O I
10.1051/m2an/2016056
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Discretization methods such as finite differences or finite elements were usually employed to provide high fidelity solution approximations for reduced order modeling of parameterized partial differential equations. In this paper, a novel discretization technique-Isogeometric Analysis (IGA) is used in combination with proper orthogonal decomposition (POD) for model order reduction of the time parameterized acoustic wave equations. We propose a new fully discrete IGA-Newmark-POD approximation and we analyze the associated numerical error, which features three components due to spatial discretization by IGA, time discretization with the Newmark scheme, and modes truncation by POD. We prove stability and convergence. Numerical examples are presented to show the effectiveness and accuracy of IGA-based POD techniques for the model order reduction of the acoustic wave equation.
引用
收藏
页码:1197 / 1221
页数:25
相关论文
共 50 条
  • [41] A reduced finite difference scheme based on singular value decomposition and proper orthogonal decomposition for Burgers equation
    Luo, Zhendong
    Yang, Xiaozhong
    Zhou, Yanjie
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2009, 229 (01) : 97 - 107
  • [42] Proper Orthogonal Decomposition and Extended-Proper Orthogonal Decomposition Analysis of Pressure Fluctuations and Vortex Structures Inside a Steam Turbine Control Valve
    Wang, Peng
    Ma, Hongyu
    Liu, Yingzheng
    JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME, 2019, 141 (04):
  • [43] Proper orthogonal decomposition for pricing options
    Pironneau, Olivier
    JOURNAL OF COMPUTATIONAL FINANCE, 2012, 16 (01) : 33 - 46
  • [44] Gappy spectral proper orthogonal decomposition
    Nekkanti, Akhil
    Schmidt, Oliver T.
    JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 478
  • [45] A Randomized Proper Orthogonal Decomposition Technique
    Yu, Dan
    Chakravorty, Suman
    2015 AMERICAN CONTROL CONFERENCE (ACC), 2015, : 1137 - 1142
  • [46] Artificial viscosity proper orthogonal decomposition
    Borggaard, Jeff
    Iliescu, Traian
    Wang, Zhu
    MATHEMATICAL AND COMPUTER MODELLING, 2011, 53 (1-2) : 269 - 279
  • [47] HIERARCHICAL APPROXIMATE PROPER ORTHOGONAL DECOMPOSITION
    Himpe, Christian
    Leibner, Tobias
    Rave, Stephan
    SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2018, 40 (05): : A3267 - A3292
  • [48] Proper orthogonal decomposition and its applications
    Sanghi, Sanjeev
    Hasan, Nadeem
    ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, 2011, 6 (01) : 120 - 128
  • [49] Proper orthogonal decomposition for optimality systems
    Kunisch, Karl
    Volkwein, Stefan
    ESAIM-MATHEMATICAL MODELLING AND NUMERICAL ANALYSIS-MODELISATION MATHEMATIQUE ET ANALYSE NUMERIQUE, 2008, 42 (01): : 1 - 23
  • [50] Guide to Spectral Proper Orthogonal Decomposition
    Schmidt, Oliver T.
    Colonius, Tim
    AIAA JOURNAL, 2020, 58 (03) : 1023 - 1033