Prediction of Outdoor Noise Propagation Induced By Single-Phase Power Transformers

Outdoor power transformers are one of the most pervasive noise sources in power transmission and distribution systems.Accurate prediction of outdoor noise propagation plays a dominant role for the evaluation and control of noise relevant to the transformer stations.In this paper surface vibration tests are carried out on a scale model of a single-phase transformer tank wall at different excitation frequencies.The phase and amplitude of test data are found to be randomly distributed when the excitation frequency exceeds the seventh mode frequency,which allows the single-phase power transformer to be simplified as incoherent point sources.An outdoor-coherent model is subsequently developed and incorporated with the image source method to investigate noise propagation from single-phase power transformers,due to the occurrence of multiple reflections and diffractions in the propagation path of each point source.The proposed model is used to calculate the sound field of the power transformer group by exploiting the additional phase information.In comparison with the ISO9613 model and the boundary element method,it is found that the proposed coherent image source method leads to more accurate prediction results,and hence better performance for the prediction of the outdoor noise induced by single-phase power transformers.

Propeller cavitation viscous simulation and low-frequency noise prediction with non-uniform inflow

Aiming at predicting ship propeller＇s cavitation low-frequency noise spectrum, a hy- brid method combining the cavitation multi-phase flow unsteady simulation with the pulsating spherical bubble radiated noise theory was proposed. Then, both of the NSRDC4383 5-bladed propeller and a 7-bladed highly-skewed propeller＇s cavitation low-frequency noise spectrum sub- jected to the full appended SUBOFF submarine＇s nominal wake were investigated. The effects of thrust loading and cavity extension on the discrete line spectrum frequency and its spectrum source level were analyzed. The improved Sauer cavitation model and modified shear stress transport turbulence models were adopted to simulate the propeller sheet cavitation along with integrated verification. The cavity volume acceleration related to the characteristic length rep- resenting the unsteady sheet cavitation extension, which was more reasonable than the spherical cavity hypothesis, was used to the cavitation low-frequency noise spectrum prediction. Results show that the 7-bladed propeller truly appreciates the advantages of smaller loads, latter cav- itation inception and lower cavitating tonal noise comparing to that of the 5 blades. Under the same cavitation index based on ship speed, the interaction of wake inflow and blades will induce significantly low frequency line spectrums and strengthen their source level. Given the submarine wake, cavitation index and rotating speed condition, the thrust, torque and cavity area of blades will decrease with the decreasing load, but the fluctuated acceleration amplitude of cavity volume and the tonal noise spectrum level increases, and the discrete line spectrum components shift mainly to the even times of the BPF harmonics from the odd. If the cavita- tion extension lightens, the BPF harmonics line spectrums will be depressed, and the spectrum level at 1 kHz reduces 2.54 dB. The numerical method above constructs a numerical system to measure the cavitating hydrodynamics and noise performances of ship propellers, which can be productive for the numerical design of wake adapted low noise submarine propeller.

Fast prediction of aerodynamic noise induced by the flow around a cylinder based on deep neural network

Accurate and fast prediction of aerodynamic noise has always been a research hotspot in fluid mechanics and aeroacoustics.The conventional prediction methods based on numerical simulation often demand huge computational resources,which are difficult to balance between accuracy and efficiency.Here,we present a data-driven deep neural network(DNN)method to realize fast aerodynamic noise prediction while maintaining accuracy.The proposed deep learning method can predict the spatial distributions of aerodynamic noise information under different working conditions.Based on the large eddy simulation turbulence model and the Ffowcs Williams-Hawkings acoustic analogy theory,a dataset composed of 1216samples is established.With reference to the deep learning method,a DNN framework is proposed to map the relationship between spatial coordinates,inlet velocity and overall sound pressure level.The root-mean-square-errors of prediction are below 0.82 dB in the test dataset,and the directivity of aerodynamic noise predicted by the DNN framework are basically consistent with the numerical simulation.This work paves a novel way for fast prediction of aerodynamic noise with high accuracy and has application potential in acoustic field prediction.

THE ENGINEERING PREDICTION FOR AIRCRAFT NOISE

The acoustic emission from an aircraft during the flight is a dynamic process. The emitting acoustic power and received mean square acoustic pressure are functions of time. The paper deals with this problem as a quasi-steady one. The whole process is resolved into several elementary procedures, for example, the flight trajectory, the geometric relation between the noise sources and observers, the noise source characteristics, the air propagation and ground effect. Two calculation examples are given in the paper, one for a long-range passenger with high bypass-ratio turbofan engine, and the other for a 3-leaved propeller. The composition of aircraft noise, its time history, frequency spectrum and directivity can be clearly described by these curves. It may be useful for the designer to perform the acoustic design of his aircraft layout.

Numerical and Experimental Study on Flow-induced Noise at Blade-passing Frequency in Centrifugal Pumps

With the increasing noise pollution, low noise optimization of centrifugal pimps has become a hot topic. However, experimental study on this problem is unacceptable for industrial applications due to unsustainable cost. A hybrid method that couples computational fluid dynamics （CFD） with computational aeroacoustic software is used to predict the flow-induced noise of pumps in order to minimize the noise of centrifugal pumps in actual projects. Under Langthjem＇s assumption that the blade surface pressure is the main flow-induced acoustic source in centrifugal pumps, the blade surface pressure pulsation is considered in terms of the acoustical sources and simulated using CFX software. The pressure pulsation and noise distribution in the near-cutoff region are examined for the blade-passing frequency （BPF） noise, and the sound pressure level （SPL） reached peaks near the cutoff that corresponded with the pressure pulsation in this region. An experiment is performed to validate this prediction. Four hydrophones are fixed to the inlet and outlet ports of the test pump to measure the flow-induced noise from the four-port model. The simulation results for the noise are analyzed and compared with the experimental results. The variation in the calculated noise with changes in the flow agreed well with the experimental results. When the flow rate was increased, the SPL first decreased and reached the minimum near the best efficient point （BEP）; it then increased when the flow rate was further increased. The numerical and experimental results confirmed that the BPF noise generated by a blade-rotating dipole roughly reflects the acoustic features of centrifugal pumps. The noise simulation method in current study has a good feasibility and suitability, which could be adopted in engineering design to predict and optimize the hydroacoustic behavior of centrifugal pumps.

Optimal Design and Experimental Verification of Low Radiation Noise of Gearbox

Reducing the radiated noise of a gearbox is a difficult problem in aviation,navigation,machinery,and other fields.Structural improvement is the main means of noise reduction for a gearbox,and it is realized primarily through contribution analysis and structure optimization.However,these approaches have certain limitations.In this study,a low-noise design method for a gearbox that combines the two approaches is proposed,and experimental verification is performed.First,a finite element/boundary element model is established using a single-stage herringbone gearbox.Considering the vibration excitation of the gear system,the radiation noise of a single-stage gearbox is predicted based on the modal acoustic transfer vector(MATV)method.Subsequently,the maximum field point of the radiated noise is determined,and the acoustic transfer vector(ATV)analysis and modal acoustic contribution(MAC)analysis are conducted to determine the region that contributes significantly to the radiated noise of the field point.The optimization region is selected through the panel acoustic contribution(PAC)analysis.Next,to reduce the normal speed in the optimization region,topology optimization is performed.According to the topology optimization results,four different noise reduction structures are added to the gearbox,and the low-noise optimization models are established respectively.Finally,by measuring the radiated noise of the gearbox before and after optimization under a given working condition,the validity of the radiated noise prediction method and the low-noise optimization design method are verified by comparing the simulation and experimental data.A comparison of the four optimization models proves that the noise reduction effect can be achieved only by adding a noise reduction structure to the center of the density nephogram.

High-efficiency prediction method for helicopter global/ground noise based on near-field acoustic holography

Noise reduction program design is an effective approach that relies on efficient noise prediction for reducing ground noise during flight.The existing noise prediction methods have the limitations of being computationally expensive or only applicable to far-fields.In this paper,a High-Efficiency Prediction Method(HEPM)for helicopter global/ground noise based on near-field acoustic holography is proposed.The HEPM can predict the global noise based on acoustic modal analysis and has the advantages of high prediction accuracy and low time cost.The process is given as follows:firstly,the rotor noise on the holographic surface in the specified flight is obtained by simulations or experiments.Secondly,the global noise model,which maps time-domain noise to acoustic modes,is established based on near-field acoustic holography and Fourier acoustic analysis methods.Finally,combined with acoustic modal amplitude,the model established enables efficiently predicting the global/ground noise in the corresponding flight state.To verify the accuracy of the prediction method,a simulation study is conducted in hovering and forward flight states using a model helicopter with a 2-meter rotor and Rotor Body Interaction(ROBIN)fuselage.The comparison of HEPM with numerical results shows that the average prediction errors of the global and ground noise are less than 0.3 dB and 0.2 dB,respectively.For a region containing 100000 observers,the computation time of the HEPM is only one-fifth of that of the acoustic hemisphere method,demonstrating the rapidity of the proposed method.

Prediction of line-spectrum noise induced by high speed vehicle counter-rotation propellers in water

Line-Spectrum noise of counter-rotation propellers has constructed the main part of the radiated noise of high speed vehicles in water. The line-spectrum noise of the counter-rotation propellers is due to the interaction between fore or aft propeller and wake of the vehicle,and the interaction between fore and aft propeller. Based on a combination of the lifting surface theory and acoustic method, the prediction of line-spectrum noise is presented in this paper.Theoretical calculation method, characteristics and numerical prediction of the line-spectrum noise are detailed too. The effect of different wake and different distance between fore and aft propeller on the propeller noise is also studied by numerical method. The agreement of predicted results compared with existing experimental data is quite satisfactory.

Prediction of propeller non-cavitation noise by superimposing shifted sound signal from an isolated blade

The time-cost of the propeller non-cavitation noise prediction can be greatly re- duced by the isolated blade method, which is validated via hybrid URANS and acoustic analogy, followed by the acoustic characteristics of propeller in time domain are analyzed. Firstly, we predicted the sound of the E779A propeller operating in uniform inflow and found a typical periodic characteristic of the sound pressure distribution on propeller blade as well as the sound signal of the receiver, and the result by the superimposing shifted sound signal from an isolated blade （isolated blade method） agreed well with the result by the integration on total blades, which validated the credibility of the isolated blade method in uniform inflow. Finally, we pre- dicted the sound of a propeller running in the wake of submarine by the isolated blade method, and the result also agreed well with the result by the integration on total blades, which further indicated that the isolated blade method was also applicable for the non-cavitation noise prediction of the propeller running in non-uniform inflow. The noise prediction of the counter-rotating propeller, the pump-jet can also benefit from this method.

A prediction of the acoustic field of a vibrating box by FEM-BEM

A method based on Holmholtz equation is presented to predict thc acoustic radiation of a vibrating box by combining the finite clement method (FEM) with boundary element method (BEM). The prediction formulation is valid for all frequencies if an extra equation is added. The acoustic field of a vibrating box has been calculated and measured. The effectiveness of the method has been proved by test results.