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.

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.

scholarly journals Data-Driven Pulsatile Blood Flow Physics with Dynamic Mode Decomposition

Fluids ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 111
Author(s):  
Milad Habibi ◽  
Scott T. M. Dawson ◽  
Amirhossein Arzani
Keyword(s):  
Blood Flow ◽  
Flow Rate ◽  
Coherent Structures ◽  
Dynamic Mode Decomposition ◽  
Data Driven ◽  
Patient Specific ◽  
Dynamic Mode ◽  
Flow Data ◽  
Reduced Order ◽  
Mode Decomposition

Dynamic mode decomposition (DMD) is a purely data-driven and equation-free technique for reduced-order modeling of dynamical systems and fluid flow. DMD finds a best fit linear reduced-order model that represents any given spatiotemporal data. In DMD, each mode evolves with a fixed frequency and therefore DMD modes represent physically meaningful structures that are ranked based on their dynamics. The application of DMD to patient-specific cardiovascular flow data is challenging. First, the input flow rate is unsteady and pulsatile. Second, the flow topology can change significantly in different phases of the cardiac cycle. Finally, blood flow in patient-specific diseased arteries is complex and often chaotic. The objective of this study was to overcome these challenges using our proposed multistage dynamic mode decomposition with control (mDMDc) method and use this technique to study patient-specific blood flow physics. The inlet flow rate was considered as the controller input to the systems. Blood flow data were divided into different stages based on the inlet flow waveform and DMD with control was applied to each stage. The system was augmented to consider both velocity and wall shear stress (WSS) vector data, and therefore study the interaction between the coherent structures in velocity and near-wall coherent structures in WSS. First, it was shown that DMD modes can exactly represent the analytical Womersley solution for incompressible pulsatile flow in tubes. Next, our method was applied to image-based coronary artery stenosis and cerebral aneurysm models where complex blood flow patterns are anticipated. The flow patterns were studied using the mDMDc modes and the reconstruction errors were reported. Our augmented mDMDc framework could capture coherent structures in velocity and WSS with a fewer number of modes compared to the traditional DMD approach and demonstrated a close connection between the velocity and WSS modes.

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