Analysis Method for CFD Results of Centrifugal Blower in Vacuum Cleaner Using Proper Orthogonal Decomposition

2015 ◽  
Author(s):  
Koma Sato ◽  
Takeshi Honda
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Data Storage ◽  
Field Structure ◽  
Orthogonal Decomposition ◽  
Centrifugal Blower ◽  
Vacuum Cleaner ◽  
Frequency Spectra ◽  
Expansion Coefficients ◽  
Proper Orthogonal

2D and steady analysis have been replaced by 3D and unsteady analysis because of dramatic improvements in computational environments. Analysis models that faithfully simulate actual products conventionally tend to be complicated and large scale. Therefore, the storage of analysis results has been increasing tremendously, and the dominant flow-field structure has been difficult to clarify. Data reduction by proper orthogonal decomposition (POD) is effective for simultaneously reducing the number of results of unsteady computational fluid dynamics (CFD) and for comprehending the dominant flow-field structure. However, only a few applications are used in the domain of industrial machinery. In this study, we applied the POD method to unsteady CFD results of a centrifugal blower in a vacuum cleaner and evaluated the benefits. We extracted a time series of static pressure distribution in the diffuser from unsteady CFD results corresponding to one rotation of the impeller, applied the POD to these data, and compared the results of an experiment. The results were that the first six modes had a 99.4% contribution in terms of the L2 norm. In the scope of this research, the first six modes were revealed to surrogate the pressure fluctuation sufficiently. Also, the data storage was reduced to less than 2.0% of the original unsteady results. Next, frequency spectra were obtained by applying a discrete Fourier transform (DFT) to the expansion coefficients. The spectra of the expansion coefficients of the POD modes were found to have a peak near the blade passing frequencies (BPFs). The noise, the frequency of which is BPF, causes the majority of the noise that occurs in the diffuser. Therefore, we found by using both the POD and DFT that we could both reduce the dramatic data storage and extract the flow-field structures.

Study on flow field and aerodynamic noise of electric vehicle rearview mirror

2021 ◽  
pp. 095440702110228
Author(s):  
Xiaowei Hao ◽  
Zhigang Yang ◽  
Qiliang Li
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Electric Vehicle ◽  
Sound Pressure ◽  
Pressure Level ◽  
Orthogonal Decomposition ◽  
Aerodynamic Noise ◽  
Turbulent Pressure ◽  
Rearview Mirror ◽  
Proper Orthogonal

With the development of new energy and intelligent vehicles, aerodynamic noise problem of pure electric vehicles at high speed has become increasingly prominent. The characteristics of the flow field and aerodynamic noise of the rearview mirror region were investigated by large eddy simulation, acoustic perturbation equations and reduction order analysis. By comparing the pressure coefficients of the coarse, medium and dense grids with wind tunnel test results, the pressure distribution, and numerical accuracy of the medium grid on the body are clarified. It is shown from the flow field proper orthogonal decomposition of the mid-section that the sum of the energy of the first three modes accounts for more than 16%. Based on spectral proper orthogonal decomposition, the peak frequencies of the first-order mode are 19 and 97 Hz. As for the turbulent pressure of side window, the first mode accounts for approximately 11.3% of the total energy, and its peak appears at 39 and 117 Hz. While the first mode of sound pressure accounts for about 41.7%, and the energy peaks occur at 410 and 546 Hz. Compared with traditional vehicle, less total turbulent pressure level and total sound pressure level are found at current electric vehicle because of the limited interaction between the rearview mirror and A-pillar.

Analysis of Unsteady Flow Structures in a Radial Turbomachine by Using Proper Orthogonal Decomposition

2018 ◽  
Author(s):  
Matthias Witte ◽  
Benjamin Torner ◽  
Frank-Hendrik Wurm
Keyword(s):  
Flow Field ◽  
Unsteady Flow ◽  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Mode Shapes ◽  
Flow Structures ◽  
Periodic Flow ◽  
Noise Emission ◽  
Turbulent Flow Field ◽  
Proper Orthogonal

Tonalities in hydro and airborne noise emission are a known problem of turbomachines, wherein the tonalities in the noise spectrum are associated with the different orders of the blade passing frequency (BPF). The proper orthogonal decomposition (POD) method was utilized to find the relationship between the fluctuations in the pressure field at the BPF orders which are the origin of the noise emission and the correlated fluctuations in the turbulent velocity field in terms of coherent, periodic flow structures. In order the provide the input data for the POD analysis, a URANS k-ω-SST scale adaptive simulation (SAS) of the turbulent flow field in a single stage radial pump under part load conditions was performed. Compared to traditional two equation turbulence models this approach is less dissipative and allows the development of small scale turbulence structures and is therefore an appropriate method for this study. In order to compute the POD correlation matrix Sirovich’s “Methods of Snapshots” was applied to the unsteady pressure and velocity fields from the CFD simulation. The discrimination of coherent, periodic flow structures and the incoherent, chaotic turbulence was carried out by analyzing the POD eigenvalue distributions, the POD mode shapes and the spectral properties of the POD time coefficients. Five coupled POD mode pairs were identified in total, which were strictly correlated with the 1st, 2nd, 3rd, 4th and 5th order of the BPF and therefore responsible for the noise emission at these discrete frequencies. The coherent structures were explored on the basis of the spatial POD velocity und pressure mode shapes and in terms of vortical structures after an additional phase averaging. The scope of this study is to introduce an enhanced collection of post processing techniques which are capable of analyzing highly unsteady flow fields from numerical simulations in a better way than is possible by just using traditional techniques like the evaluation of integral or time averaged quantities. The identified coherent flow structures and their associated pressure fluctuations are key elements for a proper comprehension of the internal dynamics of the turbulent flow field in a turbomachine and therefore essential for the understanding of the noise generation processes and the optimization of such machines.

Patterns and Reduced-order Reconstruction of Impinging Wiping Jet Pressure Profile Fluctuation Using Proper Orthogonal Decomposition

2021 ◽  
Author(s):  
Le Quang Phan ◽  
Andrew Johnstone ◽  
P. Buyung Kosasih ◽  
Wayne Renshaw
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Jet Impingement ◽  
Pressure Profile ◽  
Orthogonal Decomposition ◽  
Maximum Pressure ◽  
Frequency Spectra ◽  
Reduced Order ◽  
Order Reconstruction ◽  
Pressure Profiles ◽  
Proper Orthogonal

Abstract Wiping jet impingement pressure is important in controlling the coating mass (thickness) and influencing the smoothness of the thin metallic coating produced in continuous galvanizing lines (CGLs). However, the fluctuation of the impingement pressure profile that directly impacts the coating smoothness has not been adequately understood. To study key features of the impingement pressure fluctuation, the instantaneous impingement pressure profiles obtained from Large Eddy Simulations were analyzed using Proper Orthogonal Decomposition (POD). Dominant fluctuation modes of pressure profiles can be differentiated from the energy contents of the modes corresponding to different jet types namely mixing, non-mixing, and transitional mixing jet. The dominant modes of mixing jets in the wiping region contain comparable strength of all modes (flapping, pulsing, and out-of-phase multi pulsing). Non-mixing jets do not show discernable fluctuation modes and transitional mixing jets show pulsing and flapping modes only. Additionally, instantaneous maximum pressure gradient and their location were determined from the reduced-order reconstruction of the pressure profiles. From the analysis, frequency spectra of the magnitude and location fluctuations of the maximum pressure gradients associated with each of the jet types can be clearly distinguished. This is a knowledge that may be helpful for CGL operators in the operation of wiping jets.

scholarly journals Proper Orthogonal Decomposition Analysis and Dispersion Characteristics of Resonant Acoustic Flow

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiaopeng Wang ◽  
Shifu Zhu ◽  
Song Chen ◽  
Ning Ma ◽  
Zhe Zhang
Keyword(s):  
Flow Field ◽  
Energy Distribution ◽  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Small Scale ◽  
Energy Structure ◽  
Dispersion Characteristics ◽  
Distribution Law ◽  
Uniform Dispersion ◽  
Proper Orthogonal

The investigation on the flow field and mixing characteristics of resonant sound mixing is of great significance for the dispersion mixing of superfine materials. In order to simulate the flow field and dispersion characteristics of resonant acoustic mixing, a gas-liquid-solid three-phase flow model based on the coupled level-set and volume-of-fluid (CLSVOF) and discrete particle model (DPM) was established. The CLSVOF model solves the gas-liquid interface, and the DPM model tracks the particle position. Then, the particle image velocimetry (PIV) experiment was performed using a self-made resonance acoustic hybrid prototype under different oscillation accelerations, and the radial velocity distribution between the experiment and simulation was compared. Finally, the proper orthogonal decomposition (POD) is used to decompose the flow field under different oscillation accelerations and fill levels, and the energy distribution law and the energy structure of different scales are extracted. The results show that the energy of the instantaneous flow field of the resonant sound is mainly concentrated in the low-order mode, and a close relationship was revealed between the energy distribution law and dispersion behavior of particles. The larger the small-scale coherent structures distribute, the more energy it has and the more favorable it is for fast and uniform dispersion.

Proper orthogonal decomposition of flow-field in non-stationary geometry

2016 ◽  
Vol 311 ◽  
pp. 329-337 ◽  
Author(s):  
Victor Troshin ◽  
Avi Seifert ◽  
David Sidilkover ◽  
Gilead Tadmor
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Proper Orthogonal

Application of the Proper Orthogonal Decomposition Method in Analyzing Active Separation Control With Periodic Vibration Wall

2019 ◽  
Vol 36 (2) ◽  
pp. 175-184 ◽  
Author(s):  
Jin-Chun Wang ◽  
Xin Fu ◽  
Guo-Ping Huang ◽  
Shu-Li Hong ◽  
Yuan-Chi Zou
Keyword(s):  
Flow Field ◽  
Unsteady Flow ◽  
Proper Orthogonal Decomposition ◽  
Excitation Frequency ◽  
Orthogonal Decomposition ◽  
Maximum Lyapunov Exponent ◽  
Periodic Excitation ◽  
Control Effect ◽  
Higher Modes ◽  
Proper Orthogonal

AbstractThe proper orthogonal decomposition (POD) method is employed to analyze the unsteady flow control mechanism because it is a good approach to decouple the spatial and temporal structures of unsteady flow fields. The results showed that the main effect of the periodic excitation is reallocating the energy of each mode, and selectively strengthening or weakening certain modes. Under proper amplitude and frequency of periodic excitation, the energy in higher modes will be transferred to the first mode and the translation of the modal energy is coming from the reconstructing of spatial flow structures and the ordering of modal evolution characteristics. The best control effect will be achieved when the total energy ratio of the first mode is the highest and the excitation frequency reaches the separation vortex frequency at the same time. In order to quantitatively analyze the order degree of the unsteady flow field, the maximum Lyapunov exponent was introduced. The results showed that with the energy in higher modes transferred to the lower modes, the flow field transfers from a disordered pattern to an ordered one.

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