Analyses on flow structures behind a wavy square cylinder based on continuous wavelet transform and dynamic mode decomposition

2020 ◽  
Vol 216 ◽  
pp. 108117
Author(s):  
Yan Zheng ◽  
Hiroka Rinoshika ◽  
Dan Zhang ◽  
Akira Rinoshika
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Dynamic Mode Decomposition ◽  
Flow Structures ◽  
Dynamic Mode ◽  
Continuous Wavelet ◽  
Square Cylinder ◽  
Mode Decomposition

Modeling the Turbulent Wake Behind a Wall-Mounted Square Cylinder

2020 ◽  
Author(s):  
Christian Amor ◽  
José M Pérez ◽  
Philipp Schlatter ◽  
Ricardo Vinuesa ◽  
Soledad Le Clainche
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Turbulent Wake ◽  
Orthogonal Decomposition ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Square Cylinder ◽  
Complex Flow ◽  
Reduced Order ◽  
Mode Decomposition ◽  
Proper Orthogonal

Abstract This article introduces some soft computing methods generally used for data analysis and flow pattern detection in fluid dynamics. These techniques decompose the original flow field as an expansion of modes, which can be either orthogonal in time (variants of dynamic mode decomposition), or in space (variants of proper orthogonal decomposition) or in time and space (spectral proper orthogonal decomposition), or they can simply be selected using some sophisticated statistical techniques (empirical mode decomposition). The performance of these methods is tested in the turbulent wake of a wall-mounted square cylinder. This highly complex flow is suitable to show the ability of the aforementioned methods to reduce the degrees of freedom of the original data by only retaining the large scales in the flow. The main result is a reduced-order model of the original flow case, based on a low number of modes. A deep discussion is carried out about how to choose the most computationally efficient method to obtain suitable reduced-order models of the flow. The techniques introduced in this article are data-driven methods that could be applied to model any type of non-linear dynamical system, including numerical and experimental databases.

Dynamic mode decomposition analysis of the flow characteristics in a centrifugal compressor with vaned diffuser

2020 ◽  
pp. 095765092091346
Author(s):  
Xiaojian Li ◽  
Yijia Zhao ◽  
Zhengxian Liu ◽  
Ming Zhao
Keyword(s):  
Flow Rate ◽  
Centrifugal Compressor ◽  
Flow Characteristics ◽  
Leading Edge ◽  
Dynamic Mode Decomposition ◽  
Flow Structures ◽  
Dynamic Mode ◽  
Tip Leakage ◽  
Mode Decomposition ◽  
Dynamic Structures

To understand the flow dynamic characteristics of a centrifugal compressor, the dynamic mode decomposition (DMD) method is introduced to decompose the complex three-dimensional flow field. Three operating conditions, peak efficiency (OP1), peak pressure ratio (OP2), and small mass flow rate (near stall, OP3) conditions, are analyzed. First, the physical interpretations of main dynamic modes at OP1 are identified. As a result, the dynamic structures captured by DMD method are closely associated with the flow characteristics. In detail, the BPF/2BPF (blade passing frequency) corresponds to the impeller–diffuser interaction, the rotor frequency (RF) represents the tip leakage flow (TLF) from leading edge, and the 4RF is related to the interaction among the downstream TLF, the secondary flow, and the wake vortex. Then, the evolution of the dynamic structures is discussed when the compressor mass flow rate consistently declines. In the impeller, the tip leakage vortex near leading edge gradually breaks down due to the high backpressure, resulting in multi-frequency vortices. The broken vortices further propagate downstream along streamwise direction and then interact with the flow structures of 4RF. As a result, the 8RF mode can be observed in the whole impeller, this mode is transformed from upstream RF and 4RF modes, respectively. On the other hand, the broken vortices show broadband peak spectrum, which is correlated to the stall inception. Therefore, the sudden boost of energy ratio of 14RF mode could be regarded as a type of earlier signal for compressor instability. In the diffuser, the flow structures are affected by the perturbation from the impeller. However, the flow in diffuser is more stable than that in impeller at OP1–OP3, since the leading modes are stable patterns of BPF/2BPF.

scholarly journals Analysis of Transition for a Flow in a Channel via Reduced Basis Methods

Fluids ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 202
Author(s):  
Gaetano Pascarella ◽  
Ioannis Kokkinakis ◽  
Marco Fossati
Keyword(s):  
Temporal Dynamics ◽  
Dynamic Mode Decomposition ◽  
Flow Structures ◽  
Dynamic Mode ◽  
Planar Channel ◽  
Reduced Basis ◽  
Reduced Basis Methods ◽  
Mode Decomposition ◽  
Flow Mechanisms ◽  
Basis Method

The study of the flow mechanisms leading to transition in a planar channel flow is investigated by means of a reduced basis method known as Dynamic Mode Decomposition (DMD). The problem of identification of the most relevant DMD modes is addressed in terms of the ability to (i) provide a fairly accurate reconstruction of the flow field, and (ii) match the most relevant flow structures at the beginning of the transition region. A comparative study between a natural method of selection based on the energetic content of the modes and a new one based on the temporal dynamics of the modes is here presented.

Numerical Investigation of Fluctuating Aerodynamic Lift Acting on the Road Vehicle Which Affects Drivability

2019 ◽  
Author(s):  
Jun Ikeda ◽  
Javier Sanchez Rios ◽  
Naoshi Kuratani ◽  
Kenta Ogawa ◽  
Makoto Tsubokura
Keyword(s):  
Dynamic Mode Decomposition ◽  
Flow Structures ◽  
Dynamic Mode ◽  
Incoming Flow ◽  
Transient Pressure ◽  
The Road ◽  
Mode Decomposition ◽  
On The Road ◽  
Yaw Angle ◽  
Unsteady Lift

Abstract In this study, unsteady flow simulations using a large-eddy simulation are conducted to analyze vehicle aerodynamics. The objective is to investigate flow structures that cause unsteady lift fluctuations potentially affecting the drivability of a vehicle. In addition, the dependence on the yaw angle of the incoming flow yaw angle is studied. The target model is a sedan-type vehicle that includes a complex underbody geometry and engine compartment. The model is based on production CAD drawings. The yaw angle of the incoming flow is set to 0°, 3°, and 5°. The simulation results are analyzed by several post-processing methods, such as root-mean-square of the transient pressure field, power spectral density of the lift force, and dynamic mode decomposition method to extract the flow features associated with the unsteady lift fluctuation. It is concluded that the aerodynamic fluctuation that may affect a vehicle’s vertical stability is concentrated on the rear tire and bumper area. In addition, when the yaw angle of the incoming flow increases, the fluctuation of the lift and the disturbance of flow structures are enhanced.

scholarly journals Flow Structures on a Planar Food and Drug Administration (FDA) Nozzle at Low and Intermediate Reynolds Number

Fluids ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 4
Author(s):  
Adrián Corrochano ◽  
Donnatella Xavier ◽  
Philipp Schlatter ◽  
Ricardo Vinuesa ◽  
Soledad Le Clainche
Keyword(s):  
Reynolds Number ◽  
Drug Administration ◽  
Food And Drug Administration ◽  
Vortex Street ◽  
Dynamic Mode Decomposition ◽  
Numerical Code ◽  
Flow Structures ◽  
Dynamic Mode ◽  
General Description ◽  
Mode Decomposition

In this paper, we present a general description of the flow structures inside a two-dimensional Food and Drug Administration (FDA) nozzle. To this aim, we have performed numerical simulations using the numerical code Nek5000. The topology patters of the solution obtained, identify four different flow regimes when the flow is steady, where the symmetry of the flow breaks down. An additional case has been studied at higher Reynolds number, when the flow is unsteady, finding a vortex street distributed along the expansion pipe of the geometry. Linear stability analysis identifies the evolution of two steady and two unsteady modes. The results obtained have been connected with the changes in the topology of the flow. Finally, higher-order dynamic mode decomposition has been applied to identify the main flow structures in the unsteady flow inside the FDA nozzle. The highest-amplitude dynamic mode decomposition (DMD) modes identified by the method model the vortex street in the expansion of the geometry.

scholarly journals Empirical Mode Decomposition of the atmospheric wave field

2007 ◽  
Vol 25 (2) ◽  
pp. 375-384 ◽  
Author(s):  
A. J. McDonald ◽  
A. J. G. Baumgaertner ◽  
G. J. Fraser ◽  
S. E. George ◽  
S. Marsh
Keyword(s):  
Wavelet Transform ◽  
Gravity Waves ◽  
Continuous Wavelet Transform ◽  
Wind Field ◽  
Planetary Wave ◽  
Horizontal Wind ◽  
Continuous Wavelet ◽  
Intrinsic Mode Functions ◽  
Mode Decomposition ◽  
Mf Radar

Abstract. This study examines the utility of the Empirical Mode Decomposition (EMD) time-series analysis technique to separate the horizontal wind field observed by the Scott Base MF radar (78° S, 167° E) into its constituent parts made up of the mean wind, gravity waves, tides, planetary waves and instrumental noise. Analysis suggests that EMD effectively separates the wind field into a set of Intrinsic Mode Functions (IMFs) which can be related to atmospheric waves with different temporal scales. The Intrinsic Mode Functions resultant from application of the EMD technique to Monte-Carlo simulations of white- and red-noise processes are compared to those obtained from the measurements and are shown to be significantly different statistically. Thus, application of the EMD technique to the MF radar horizontal wind data can be used to prove that this data contains information on internal gravity waves, tides and planetary wave motions. Examination also suggests that the EMD technique has the ability to highlight amplitude and frequency modulations in these signals. Closer examination of one of these regions of amplitude modulation associated with dominant periods close to 12 h is suggested to be related to a wave-wave interaction between the semi-diurnal tide and a planetary wave. Application of the Hilbert transform to the IMFs forms a Hilbert-Huang spectrum which provides a way of viewing the data in a similar manner to the analysis from a continuous wavelet transform. However, the fact that the basis function of EMD is data-driven and does not need to be selected a priori is a major advantage. In addition, the skeleton diagrams, produced from the results of the Hilbert-Huang spectrum, provide a method of presentation which allows quantitative information on the instantaneous period and amplitude squared to be displayed as a function of time. Thus, it provides a novel way to view frequency and amplitude-modulated wave phenomena and potentially non-linear interactions. It also has the significant advantage that the results obtained are more quantitative than those resultant from the continuous wavelet transform.

Investigation of In-Cylinder Engine Flow Quadruple Decomposition Dynamical Behavior Using Proper Orthogonal Decomposition and Dynamic Mode Decomposition Methods

2019 ◽  
Vol 141 (8) ◽  
Author(s):  
Wenjin Qin ◽  
Lei Zhou ◽  
Daming Liu ◽  
Ming Jia ◽  
Maozhao Xie
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Dynamical Behavior ◽  
Flow Fields ◽  
Orthogonal Decomposition ◽  
Dynamic Mode Decomposition ◽  
Flow Structures ◽  
Dynamic Mode ◽  
Unstable Flow ◽  
Mode Decomposition ◽  
Proper Orthogonal

In order to study the in-cylinder flow characteristics, one hundred consecutive cycles of velocity flow fields were investigated numerically by large eddy simulation, and the proper orthogonal decomposition (POD) algorithm was used to decompose the results. The computed flow fields were divided into four reconstructed parts, namely mean part, coherent part, transition part, and turbulent part. Then, the dynamic mode decomposition (DMD) algorithm was used to analyze the characteristics of the reconstructed fields. The results show that DMD method is capable of finding the dominant frequencies in every reconstructed flow part and identifying the flow structures at equilibrium state. In addition, the DMD results also reveal that the reconstructed parts are related to each other through the break-up and attenuation process of unstable flow structures, while the flow energy cascade occurs among these parts through different scale vortex generation and dissipation process.

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