Computational Process for Wind Noise Evaluation of Rear-View Mirror Design in Cars

Mutnuri, L.A.Raghu; Senthooran, Sivapalan; Powell, Roger A.; Sugiyama, Zen; Freed, David

doi:10.4271/2014-01-0619

Cited by 10 publications

(3 citation statements)

References 15 publications

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“…They quantified the contributions of various structural components to wind noise and developed acoustic package parameters based on their simulation results. Mutnuri et al [29] and colleagues used a CFD model based on the lattice Boltzmann method to input pulsating pressure loads on the underbody and side window regions of an automobile into an SEA model. The path from the chassis to the cabin interior was tested to establish a coupled CFD\SEA\FEM model to analyze internal noise frequency.…”

Section: Numerical Simulation Methods For Wind Noise Predictionmentioning

confidence: 99%

Deep learning-based wind noise prediction study for automotive clay model

Huang,

Wang,

Cao

et al. 2024

Meas. Sci. Technol.

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Analyzing and mitigating wind noise in automobiles under high-speed conditions is a significant issue within the realm of Noise, Vibration, and Harshness (NVH). Due to the intricate nature of aeroacoustics generation mechanisms, current conventional methods for wind noise prediction have limitations. Hence, deep learning methods are introduced to investigate wind noise in the side window area of an automotive clay model.During aeroacoustic wind tunnel experiments, side window vibration data and noise data from the driver were collected under vehicle speed conditions of 100 km/h, 120 km/h, and 140 km/h, respectively. These data samples were obtained to be used for training and validation of the wind noise model. Convolutional Neural Networks (CNN) and Long Short-Term Memory Neural Network (LSTM) algorithms were separately employed to reveal the complex nonlinear relationship between wind noise and its influencing factors, leading to the establishment of a wind noise prediction model.Simultaneously, these two deep learning methods were compared with Backpropagation Neural Networks (BPNN), Extreme Learning Machines (ELM), and Support Vector Regression (SVR) methods. Our findings revealed that the LSTM wind noise prediction model not only exhibits higher accuracy but also demonstrates superior generalization capabilities, thereby substantiating the superiority of this method.

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Section: Numerical Simulation Methods For Wind Noise Predictionmentioning

confidence: 99%

Deep learning-based wind noise prediction study for automotive clay model

Huang,

Wang,

Cao

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…For the study of aerodynamic noise in the rearview mirror area, numerical simulation is mainly used to explain the cause of aerodynamic noise according to the flow separation phenomenon and pressure pulsation in the flow field, and then the aerodynamic noise can be controlled by controlling the local structure of the rearview mirror. Mutnri, F., et al [4] studied the influence of different installation positions of the rearview mirror on the aerodynamic noise in the vehicle, and concluded that the aerodynamic noise in the vehicle is relatively small when the rearview mirror is installed in the door position. Chen, F., et al [5,6] studied the influence of the rearview mirror cover edge and different rearview mirror shapes on aerodynamic noise, and found that the construction of grooves on the rearview mirror cover edge had a significant impact on the structure and position of the vorticity at the rear of the rearview mirror; the research revealed the law of the influence of different rearview mirror shapes on the flow field.…”

Section: Introductionmentioning

confidence: 99%

A Study of the Relationship between Dipole Noise Sources and the Flow Field Parameters around the Rearview Mirror of Passenger Cars

Zhang,

Pang,

Wang

et al. 2023

Applied Sciences

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When air flows through the mirrors, A-pillars, and other surfaces of a passenger car, airflow separation occurs to generate vorticity and generates aerodynamic noise. The dipole noise source is the main source of aerodynamic noise when the passenger car is travelling at high speed. In order to reveal the relationship between the physical quantities in the flow field and the intensity of the dipole noise source, this paper equates each dipole noise source to a sphere radiating noise to the outside. The acoustic wave fluctuation equations expressed as spherical coordinates are combined with the acoustic boundary conditions and the equations of motion of an ideal fluid medium to obtain the relationship between the intensity of the dipole noise source and the flow velocity and vorticity in the flow field. Then, through flow field simulation, we establish a method of identifying the dipole noise source and its distribution area, and analyze the generation mechanism of the dipole noise source. Through the analysis, it is concluded that the dipole noise sources are mainly concentrated in the airflow separation areas, which easily generate vortices. The size of the vorticity is the key factor affecting the intensity of the dipole noise source. When the intensity of the dipole noise source reaches its peak, the direction of the flow vorticity is perpendicular to the direction of the flow velocity and the peak of the flow velocity occurs before the peak of the dipole noise source, which indicates that the angle between the flow vorticity and the flow velocity, as well as the flow velocity, also has a certain effect on the generation of the dipole noise source.

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“…is study did not achieve the goal of reducing the sound pressure level in the cab. Mutnuri et al [6] combined CFD with statistical energy analysis (SEA) to evaluate the design of the rear-view mirror aerodynamic noise. e conclusion was obtained that the aerodynamic noise of the rear-view mirror mounted on the glass is larger than the aerodynamic noise of the rearview mirror mounted on the door from quantitative and qualitative analysis, which indicated the installation position of the rear-view mirror has a great influence on the interior noise and helped to guide the design of the rear-view mirror installation.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Aerodynamic Analysis of Interior Noise and Wind Drag Generated by the Outside Rear-View Mirror for Commercial Vehicles

Lu²,

Cui

et al. 2020

Shock and Vibration

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The outside rear-view mirror (OSRVM) is installed on the vehicle’s surface, which causes unwanted aerodynamic noise and wind drag during driving. It is important to use simulation methods to predict the performance of aerodynamic noise and wind drag of commercial vehicles due to the OSRVM. Considering the wind drag of the OSRVM, a combinational simulation strategy is employed to calculate external flow and interior acoustic fields of commercial vehicles, respectively. The flow field is computed a priori with an incompressible flow solver. The acoustic field was then computed based on the information extracted from the CFD solver. To obtain the interior noise level at the driver’s ears, a vibroacoustic model is used to calculate the response of the window glass structure and interior cavities, where the unsteady aerodynamic pressure loading on the two side windows’ surface is treated as the acoustic source field. The paper provides flow field and acoustic simulations for three OSRVM configuration models. The results are compared to data obtained in road sliding test measurement on the commercial vehicle. The accuracy of the hybrid simulation method is proved, and the comparative analyses verify that the OSRVM B model dramatically reduces the interior noise and wind drag of commercial vehicles.

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Computational Process for Wind Noise Evaluation of Rear-View Mirror Design in Cars

Cited by 10 publications

References 15 publications

Deep learning-based wind noise prediction study for automotive clay model

Deep learning-based wind noise prediction study for automotive clay model

A Study of the Relationship between Dipole Noise Sources and the Flow Field Parameters around the Rearview Mirror of Passenger Cars

Prediction and Aerodynamic Analysis of Interior Noise and Wind Drag Generated by the Outside Rear-View Mirror for Commercial Vehicles

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