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.

Experimental and Numerical Investigation of Blades Effect on Aerodynamic Performance of Small Axial Flow Fan

2011 ◽  
Author(s):  
Li Zhang ◽  
Yingzi Jin ◽  
Yi Zhao ◽  
Pin Liu
Keyword(s):  
Flow Field ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Axial Flow ◽  
Aerodynamic Performance ◽  
Pressure Level ◽  
Aerodynamic Noise ◽  
Blade Number ◽  
Small Axial Flow Fan ◽  
Fan Blade

To explore the effect of blade numbers on aerodynamic performance and noise of small axial flow fan, the steady flow field and the unsteady flow field of fan models with 6 different blade numbers (such as 5, 7, 9, 11, 13, 15) are numerically calculated. Then the internal flow distribution, static characteristic and aerodynamic noise are analyzed among six different fan models. The analysis results show: (1)Total pressure and efficiency generally maintain the trend of first increasing and then decreasing with increasing blade numbers, and it is the maximum when fan blade number is 11. The flow rate coupled with the maximum efficiency has never changed with increasing the blade numbers. (2)With increasing blade numbers, overall sound pressure level of the aerodynamic noise is gradually decreasing near the outlet of fan tip, while it is first decreasing and then increasing before decreasing again at 1 meter away from the central axis of the impeller along the outlet. When fan blade number is 11, overall sound pressure level of the aerodynamic noise is the greatest. Furthermore, the aerodynamic performance tests of fan models with 6 different blade numbers are carried out, the results of between the tests and the numerical calculations are roughly consistent. The research results will provide the proof of the parameter optimization and the structure design for high performance and low noise small axial fans.

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.

Noise Prediction for Multi-Element Airfoil Based on FW-H Equation

2011 ◽  
Vol 52-54 ◽  
pp. 1388-1393
Author(s):  
Jun Tao ◽  
Gang Sun ◽  
Ying Hu ◽  
Miao Zhang
Keyword(s):  
Flow Field ◽  
Sound Pressure ◽  
Near Field ◽  
Pressure Level ◽  
Aerodynamic Noise ◽  
Noise Prediction ◽  
Far Field ◽  
Acoustic Analogy ◽  
Acoustic Information ◽  
Good Agreement

In this article, four observation points are selected in the flow field when predicting aerodynamic noise of a multi-element airfoil for both a coarser grid and a finer grid. Numerical simulation of N-S equations is employed to obtain near-field acoustic information, then far-field acoustic information is obtained through acoustic analogy theory combined with FW-H equation. Computation indicates: the codes calculate the flow field in good agreement with the experimental data; The finer the grid is, the more stable the calculated sound pressure level (SPL) is and the more regularly d(SPL)/d(St) varies.

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.

On Proper Orthogonal Decomposition or K-L Expansion to Analyze Transient Sound Pressure Fields in Linear Acoustics

2003 ◽  
Author(s):  
Ioannis T. Georgiou ◽  
Christos I. Papadopoulos
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Sound Pressure ◽  
Pressure Field ◽  
Low Frequency ◽  
Temporal Patterns ◽  
Orthogonal Decomposition ◽  
Noise Sources ◽  
Air Cavity ◽  
Spatio Temporal ◽  
Proper Orthogonal

Identification of the most energetic spatio-temporal patterns that govern the low-frequency dynamics of an air cavity excited by noise sources could lead to significant design improvements of enclosures for noise reduction / isolation and / or sound quality. In this work we show how the Proper Orthogonal Decomposition (POD) method can be applied to identify optimum spatio-temporal patterns governing the dynamics of the sound pressure field developed inside an air cavity. The novel feature of this approach resides into the fact that the POD technique is utilized to process databases for acoustic variables produced by state of the art computational methods in acoustics, such as the finite element method. For a cavity with rigid walls and excited by a harmonic point source, the POD technique reveals that the sound pressure field is composed of a very small number of Proper Orthogonal Modes, which are unique since they are optimum by construction. The POD technique identifies the shapes or patterns of these modes.

Effect of Blade Numbers on Aerodynamic Performance and Noise of Small Axial Flow Fan

2011 ◽  
Vol 199-200 ◽  
pp. 796-800
Author(s):  
Li Zhang ◽  
Ying Zi Jin
Keyword(s):  
Flow Field ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Axial Flow ◽  
Aerodynamic Performance ◽  
Pressure Level ◽  
Aerodynamic Noise ◽  
Blade Number ◽  
Small Axial Flow Fan ◽  
Fan Blade

To more fully explore the effect of blade numbers on aerodynamic performance and noise of small axial flow fan, some solutions are adopted to obtain the parameters’ distribution of the flow field.Firstly, the standard k-ε turbulence model is used to calculate the steady flow field of six different fan blades(such as 5,7,9,11,13,15) , and the SIMPLE algorithm is applied to couple vecolity and pressure. Secondly, the large eddy simulation in conjunction with the FH-W noise model are used to compute the unsteady flow field and noise. Finally, the experimental results verify that the calculation methods of steady flow field and unsteady flow field are correct. The conclusions show: (1)Total pressure and efficiency generally maintain the trend of firstly increasing and then decreasing with increasing the blade numbers, and it is the greatest when fan blade number is 11. The flow rate coupled with the maximum efficiency has never changed with increasing the blade numbers. (2)With the increasing blades, overall sound pressure level of the aerodynamic noise is gradually decreasing near the outlet of fan tip, while it is firstly decreasing and then increasing before decreasing again 1 meter away from the central axis of the impeller along the outlet. When fan blade number is 11, overall sound pressure level of the aerodynamic noise is the greatest.

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