Higher order dynamic mode decomposition of wind pressures on square buildings

被引:62
作者
Zhou, Lei [1 ]
Tse, K. T. [1 ]
Hu, Gang [2 ]
Li, Yutong [1 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China
[2] Harbin Inst Technol, Sch Civil & Environm Engn, Shenzhen, Peoples R China
关键词
Tall building; Wind pressure; Random pressure field; HODMD; POD; PROPER ORTHOGONAL DECOMPOSITION; DOUBLE-SKIN FACADE; COHERENT STRUCTURES; FLOW STRUCTURES; POD; WAKE; PERFORMANCE; ANGLE; FIELD; DMD;
D O I
10.1016/j.jweia.2021.104545
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Wind pressures on buildings with different aspect ratios were investigated via higher-order dynamic mode decomposition (HODMD) in this study. Taken?s embedding theorem was used to augment the spatial dimensionality of the original snapshot matrix by introducing time delay coordinates. HODMD was applied to reveal the spatial-temporal evolution characteristics of fluctuating wind pressures on building surfaces. It was found that HODMD can successfully extract the modes and corresponding frequencies from the random pressure field. As the aspect ratio increases, the main mode is more dominant than other modes. Moreover, comparisons between HODMD and proper orthogonal decomposition (POD) suggests that the first-order mode shapes extracted by HODMD and POD are generally similar, and both can reflect the main characteristics of the fluctuating pressure field. However, the higher-order mode shapes extracted by HODMD and POD are different due to higher-order nonlinearities. The modes of HODMD oscillate at a fixed frequency while those of POD resemble random signals, indicating the physical meaning of HODMD is more evident. Furthermore, HODMD is proven to be superior to POD in reconstructing pressure fields with less root mean square errors, because HODMD reconstructs the pressure field directly while POD primarily aims to rebuild the energy field.
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页数:16
相关论文
共 49 条
[1]   Aspects of the use of proper orthogonal decomposition of surface pressure fields [J].
Baker, CJ .
WIND AND STRUCTURES, 2000, 3 (02) :97-115
[2]   Stochastic Wake Modelling Based on POD Analysis [J].
Bastine, David ;
Vollmer, Lukas ;
Waechter, Matthias ;
Peinke, Joachim .
ENERGIES, 2018, 11 (03)
[3]   A Data-Driven ROM Based on HODMD [J].
Beltran, Victor ;
Le Clainche, Soledad ;
Vega, Jose M. .
14TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS (SOCO 2019), 2020, 950 :567-576
[4]   Real time performance improvement of engineering control units via Higher Order Singular Value Decomposition: Application to a SI engine [J].
Benito, N. ;
Arias, J. R. ;
Velazquez, A. ;
Vega, J. M. .
CONTROL ENGINEERING PRACTICE, 2011, 19 (11) :1315-1327
[5]   Investigation of Coherent Structures and Dynamics Using POD and DMD of a Separated Airfoil Subjected to ZNMF Jet Forcing [J].
Buchmann, N. A. ;
Kitsios, V. ;
Atkinson, C. ;
Soria, J. .
INSTABILITY AND CONTROL OF MASSIVELY SEPARATED FLOWS, 2015, 107 :33-38
[6]   Statistical analysis of wind-induced pressure fields: A methodological perspective [J].
Carassale, Luigi ;
Brunenghi, Michela Marre .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2011, 99 (6-7) :700-710
[7]   Analysis of the wake dynamics of stiff and flexible cantilever beams using POD and DMD [J].
Cesur, A. ;
Carlsson, C. ;
Feymark, A. ;
Fuchs, L. ;
Revstedt, J. .
COMPUTERS & FLUIDS, 2014, 101 :27-41
[8]   Variants of Dynamic Mode Decomposition: Boundary Condition, Koopman, and Fourier Analyses [J].
Chen, Kevin K. ;
Tu, Jonathan H. ;
Rowley, Clarence W. .
JOURNAL OF NONLINEAR SCIENCE, 2012, 22 (06) :887-915
[9]   Proper orthogonal decomposition-based modeling, analysis, and simulation of dynamic wind load effects on structures [J].
Chen, XZ ;
Kareem, A .
JOURNAL OF ENGINEERING MECHANICS, 2005, 131 (04) :325-339
[10]   Analysis of PIV measurements using modal decomposition techniques, POD and DMD, to study flow structures and their dynamics within a stirred-tank reactor [J].
de lamotte, Anne ;
Delafosse, Angelique ;
Calvo, Sebastien ;
Toye, Dominique .
CHEMICAL ENGINEERING SCIENCE, 2018, 178 :348-366