Sound Source Model Research Articles

Large aperture microphone array measurement at operating airport for sound source model creation of J-FRAIN

In 2022, authors conducted microphone array measurements at an operating airport to create sound source models for commercial aircraft based on the noise prediction framework J-FRAIN. A similar measurement was also performed by our colleagues in 2019, but it was a trial to establish the concept of the framework and was done using a microphone array in which the number of microphones was reduced to about half. In order to improve the accuracy of the sound source models, the microphone array with a 30-meter diameter consisting of 195 microphones mounted on the ground was used in 2022. Recording-based simultaneous noise measurement using sound level meters was also performed around the airport to validate prediction results in terms of time histories of 1/3 octave band sound pressure levels. This paper describes an overview of the microphone array measurements conducted in 2022 and a case study of noise prediction around the airport using sound source models created from the data of microphone array measurements conducted in 2022. Predicted results are compared with 1/3 octave band data measured using sound level meters mounted at a height of 4 m above the ground at sites of noise monitoring stations around the airport.

Noise modeling of UAM around the urban vertiport

The present study aims to investigate the noise distribution around urban vertiport caused by UAM(Multicopter) and helicopter. Noise modelings were carried out using SoundPLAN software at the some vertiports in Seoul, Korea. Sound source model of UAM and helicopter were used as a form of hemisphere. Noise predictions were undertaken with three different operations including depart, level flight and landing. In order to evaluate the noise impact on the buildings around the vertiport, noise levels at the outer wall of nearby buildings were calculated as the three noise units including Leq, Lmax and Lden. Also, noise maps were drawn around the vertiport. As a result, it was found that average noise level of UAM is approximately 12 dB lower than the helicopter noise levels. Regarding the noise frequency distribution, most high noises are made at the mid-frequencies during landing hours while low frequency noise level around 63 Hz was dominant at take-off time.

Development of aircraft noise simulation framework J-FRAIN based on component-wise sound source models

In order tomake detailed and accurate predictions of aircraft noise around airports, we have developed “J-FRAIN”, a new aircraft noise simulation framework that can precisely predict the time histories of noises emitted from each major aircraft noise source during the landing approach phase at ground observation points. This article describes the elements of the developed framework—data acquisition, sound source modeling, propagation modeling, and ground noise prediction—and present some application examples. To develop the framework, we first deployed a 30m-diameter microphone array under the final approach path to an international airport to measure acoustic maps of several civil aircraft types in flight. The sound powers of major aircraft noise-emitting components were then estimated quantitatively by domain integration of the deconvolved acoustic maps at five emission angles in the plane of the glideslope, and the directivities of each noise source were determined. Next, component-wise sound source regression models for engines and airframe noise sources were created based on the physical relationships between engine rotation speed, airspeed, and the deployment angle of high-lift devices, and the coefficients in each model were determined to minimize the root-mean-square error between the measured and predicted sound power levels. The phenomena of atmospheric absorption and ground effect during the propagation of radiated sounds were also incorporated into the framework. Actual flight parameter values were used as inputs to the completed framework, and it was confirmed that the predicted time histories of sound pressure levels on the ground agreed with measured data to within 2 dB if ground effect was properly considered. Finally, as sample applications that use the unique features of the proposed J-FRAIN framework, the article discusses the evaluation of the contributions of each aircraft noise source at noise observation points under the final approach path to the airport and the impact assessment of flight operations on noise.

Enhancing sustainable urban air transportation: Low-noise UAS flight planning using noise assessment simulator

Low-altitude flights of unmanned aircraft systems (UASs), such as drones, can cause substantial noise pollution in urban areas. This study aims to tackle the crucial issue of noise in UAS flight planning and analyze the feasibility of implementing low-noise urban flights at a micro level. We employ a virtual flight simulator to accurately model the UAS noise impact in realistic flights and optimize the flight path via a heuristic algorithm accordingly. The flight noise assessment incorporates a sound source modeling technique for practical UAS models and an efficient Gaussian beam tracing method for outdoor noise propagation in realistic environments. Case studies for flight simulations are conducted in a representative resident community and metropolitan area to evaluate the noise impact resulting from different flight paths. By comparing our approach with benchmark shortest-distance paths, we validate its effectiveness in significantly reducing en-route noise exposure, encompassing both instantaneous and continuous noise levels. This method holds great potential for contributing to the planning and management of urban air transport systems. It effectively mitigates noise impact, promoting quieter and more environmentally friendly UAS operations and sustainable urban transportation.

Component-wise regression sound source models for the aircraft noise prediction framework J-FRAIN

In this study, we created sound source models for a newly developed simulation framework named 'J-FRAIN' that can accurately predict the time histories of noises from each major aircraft noise-generating component at ground observation points during the landing approach phase. Sound source distributions of more than twenty types of jet transport aircraft have been measured in flight using a microphone array deployed under the final approach path to an airport. In this paper, the Boeing 787-8 is presented as an example for modeling. The sound powers of each aircraft component - engines, landing gear, and high-lift devices - were calculated quantitatively from the domain integration of the measured acoustic maps. Then, component-wise regression sound source models were created based on the relationship between engine rotational speed, airspeed, and deployment angle of high-lift devices. The models were implemented in the 'J-FRAIN' simulation framework that integrates a sound propagation model. The predicted time histories of ground noise were compared with measurement results from a single microphone placed at the center of the microphone array, and were found to be in good agreement.

Direct sound field estimation based on sound source modeling with sparse equivalent sources

The measurement of multi-point room impulse responses (RIRs) is challenging because it requires many microphones or a microphone traverse system. In our previous study, we proposed a spatial extrapolation method to measure early RIRs by the locally-positioned microphones. However, the estimation accuracy was degraded at a far distance from the microphones owing to the directivity of the sound source. In this study, we proposed a modeling method to estimate a direct sound field using a source radiation model based on the sparse equivalent source method. First, the source radiation was modeled using an enclosed microphone array. Then, we modeled the direct sound field using locally positioned microphones. The evaluation experiment was conducted in an anechoic chamber under 2.5D condition.

Modeling and reproduction of sound field by moving complex sound source

Previously, Wave Field Synthesis (WFS), Near-field Compensated Higher-Order Ambisonics (NFC-HOA), Boundary Surface Control (BoSC), and the Spectral Division Method (SDM) have been proposed as sound field synthesis methods. These methods are based on matching the acoustic physical quantities at the boundary of the reproduced sound field with those of the desired sound field. Sound field synthesis techniques can be classified into data-based and model-based methods. The former aim at reproducing sound fields captured by microphone arrays, while the latter aim at synthesizing sound fields based on mathematical models. Most existing sound field reproduction methods only consider simple sound source models, such as static point sources, instead of sound sources with complex radiation properties. To generate a more realistic sound image, this study investigated the formulation of a sound field generated by a sound source with complex radiation properties moving along arbitrary trajectories in a spherical harmonic domain, and reproduced the sound field using loudspeaker arrays.

Verification and application of the aircraft noise simulation framework J-FRAIN

We newly developed a framework for aircraft noise simulation, J-FRAIN, that can precisely predict the noise from aircraft at ground observation points during the landing approach phase. J-FRAIN enables the incorporation of component-wise regression sound source models created from field measurement data using a microphone array system and the precise prediction of the time history of noise from each aircraft component. To verify the noise prediction accuracy of J-FRAIN, noise prediction of the landing approach phase around an airport was performed. The component-wise regression sound source models created from the data measured at the location just before touch-down was used since its regression model can estimate the sound power levels at flight parameters not only actually measured but also not measured. The predicted result and noise measured by aircraft noise monitoring systems were verified to be in good agreement. As examples of the application using J-FRAIN, two case studies were also discussed; the determination of the contribution of each noise source at observation points and the evaluation of the influence of flight parameter differences on noise levels at observation points.

Kinematic analyses of wave–packet structures in non-isothermal jet flows: Effects of length scales

A kinematic wave–packet sound-source model is developed for non-isothermal jets based on large eddy simulation results of subsonic jets at temperature ratios 0.86, 1.0, and 2.7. To find the suitable variable for the sound-source model, coherent structures in these jets are extracted by leading modes of the proper orthogonal decomposition (POD), and they are classified according to spatial–temporal features. To extend the model, an approach is proposed to represent the growth and decay length scales separately by a single continuous function. Applying such function, the acoustic affections are discussed for the variable length scales of amplitude envelope, L, and coherence, Lc. The results show that the jet temperature desynchronizes the leading POD modes of radial velocity, pressure, and density, and the jet temperature changes the density mode from radial puffs into stripes or ridges. The axisymmetric component of the pressure clearly presents a train of radiant waves, as captured by its leading spectral-POD mode at the peak radiation frequency. Therefore, this pressure component is employed for modeling. In the wave-number domain, the elongation of L stretches the cross-spectral density (CSD) of the source signal, denoted by CSD(k1, k2), along the k1- and k2-axes; the decay of Lc stretches the CSD along the diagonal of the axes. Both of them tend to spread the CSD into a radiant region near the origin point, so as to enhance the radiation. The radiation seems insensitive to the variation of the L, as it only slightly distorts the CSD in the radiant region.

Wind turbine noise modeling including aeroacoustic sources and propagation effects: comparison against field measurements

The study of wind turbine noise and its impact is of growing importance with the increase in the demand for green and clean energy. As it is known that wind turbine noise can be a cause of annoyance in the vicinity of wind farms it is beneficial to predict with certain accuracy the generated noise in the design phase itself. A crucial step is the validation of prediction models against field measurements (in-situ). This article presents a wind turbine noise prediction model that combines Amiet's theory to calculate trailing edge noise and turbulence interaction noise in free field with a wide-angle parabolic equation valid in moving media to account for the long-range acoustic propagation effects. The model considers the wind turbine as an extended noise source and the rotation effects (such as the convective amplification and Doppler effect) are taken into account. The predicted noise levels are compared to those obtained from a measurement campaign where acoustic, meteorological and ground impedance data have been recorded simultaneously. First, the sound source model is validated close to the wind turbines for different wind speeds and directions. Then, noise predictions are compared to SPL measurements at various distances from the sound source, between 350 and 1300meters.

Noise predictions of a Mach 0.9 round jet using tailored adjoint Green’s functions

The turbulent mixing noise radiated by a Mach 0.9 jet is investigated. The focus is put on the proper calculation of acoustic propagation effects by means of adjoint Green’s function that are tailored to the jet mean flow. Tam and Auriault’s statistical mixing noise model is recast for Pierce’s wave equation that is energy preserving. An unconditionally stable formulation to compute propagation effects is thus obtained. Adjoint fields are computed from the direct problem with help of the flow reversal theorem. A finite element solver is used to solve tailored adjoint Green’s functions, and corresponding adjoint fields are displayed. Acoustic predictions are carried out for a wide range of polar angles, and compared to measurements. A particular attention is given to predictions achieved at upstream observer angles. At these angles, the present model describes the physics of upstream travelling guided jet waves. The adjoint method provides a suitable framework to split the generation of sound from its propagation. It is illustrated how tailored adjoint Green’s functions filter the radiating part of Tam and Auriault’s sound source model, by weighting with propagation effects.

Development of a general sound source model for wind farm application

With the confidentiality of turbine blade geometry, wind farm developers and/or end-users have difficulties to optimize their wind turbine operations and wind farm layouts with respect to noise as existing sound source models rely on detailed blade geometry of wind turbines. This paper presents a new methodology of modeling wind turbine noise that does not need to access the details of blade geometry. The new methodology consists of two steps: First, the candidate wind turbine is approached by up/down scaling from a known wind turbine (for example the National Renewable Energy Laboratory 5 MW wind turbine) according to its operational conditions and limited data provided from the manufacturer; then a sound source model (for example Amiet's model) is applied to calculate the sound pressure level at needed positions. The developed methodology is validated against wind turbine noise measurements for a 4 MW wind turbine with unknown blade geometry; good agreement was found, with an averaged difference of 1.2 dB for various wind conditions under neutral, stable and unstable atmospheric thermostability. By combining with a sound propagation model, the new methodology can be used for designing and controlling wind farms.

Acoustic far-field prediction based on near-field measurements by using several different holography algorithms.

Near-field acoustical holography (NAH) is a useful tool for sound field reconstruction and sound source identification. In NAH, a basis model is first selected to represent the physical sound field, and then a near-field measurement is made with a microphone array. Next, the parameters in the selected model can be estimated based on the measurements by using an inverse approach, resulting in the sound field near the source being reconstructed so that the sound source location can be identified. But, in addition to being able to reconstruct the near-field of a source, the far-field can also be predicted with the identified sound source model. A significant amount of work has been performed to study the near-field reconstruction capability of different NAH algorithms, but there has been a limited number of publications in which the far-field prediction accuracy, based on the near-field measurement constructed model, has been considered. In the present experimental work, two multi-transducer loudspeakers were placed side-by-side to create a multi-component sound source, and two sets of measurements were conducted: an intensity probe scanned the sound field generated by the loudspeakers in both the near-field (0.05 m) and far-field (0.48 m) such that the true near- and far-field intensity spatial distributions and total sound power could be identified. Then, based on the near-field pressure measurements, four acoustical holography algorithms, statistically optimized near-field acoustical holography, wideband acoustical holography, l1-norm minimization, and a hybrid compressive sampling method were used to predict the near- and far-field sound intensity distributions. The near- and far-field prediction results were compared with the direct measurement, and the sound field reconstruction accuracy was studied. It was found that all of the algorithms were able to reconstruct the near-field well when the near-field measurements were used to construct the model. It was found that with the abovementioned models, far-field reconstructions could correctly predict the spatial sound field distribution, but in all of the cases, the total sound power was underestimated.

Beamshapes: a Python package to generate directivity patterns for various sound source models

beamshapes: a Python package to generate directivity patterns for various sound source models

Low-frequency room acoustical simulation of a small room with BEM and complex-valued surface impedances

This study examines practical aspects of room acoustics simulation using the Boundary Element Method (BEM). The Complex Room 2 of the benchmark for room acoustical simulation is used and the influence of sound source and material modeling is addressed. A 3-way dodecahedron with relatively large dimensions and a comparatively small studio monitor are modelled in BEM as monopoles. The effects of the localization and the measured sensitivity vs. frequency of such sound sources are addressed by comparing point-wise magnitude and phase spectra for experiment and simulation. Concerning the material characterization BEM needs the surface impedance, whereas this kind of input data is more difficult to find than the absorption coefficient. Thus, two retrieval methods are tested to synthesize surface impedance from absorption data. The first is a direct inversion and yields a real-valued surface impedance. The second is a constrained optimization yielding a complex-valued surface impedance. Both retrieval methods are compared for the original Complex Room 2, which is lightly dampened and in a simulated test scenario where a highly absorbent material is applied to the room’s ceiling.

A new multi-fidelity flow-acoustics simulation framework for wind farm application

To reduce the release of CO2 from traditional energy, wind energy is developed very fast all over the world. This means that more large wind turbines will be installed on land and more environmental impacts will be created from wind turbines. Noise generated from rotating wind turbines in wind farm propagates through a complex flow-field including a varying atmospheric flow and varying wakes created by the wind turbines, which can greatly influence the sound propagation. This paper presents a new multi-fidelity flow-acoustics simulation framework to predict the sound propagation in both near and far fields of wind turbines in wind farm, which has the potential for wind farm application with good accuracy and acceptable computing time (i.e. 8 min with 6 CPUs for the centre frequencies between 20 Hz and 1000 Hz in 1/3 octave bands). The new multi-fidelity flow-acoustics simulation framework (named WindSTAR) consists of a three-dimensional wind farm engineering flow model, an engineering sound source model, and a high-fidelity sound propagation model. To validate the new framework, a comprehensive measurement strategy was designed and performed to measure simultaneously the turbine operations, inflow conditions, wake flow fields and acoustic fields from near to far fields of a 3.9/4.1 MW SGRE wind turbine in Drantum, Denmark. Comparisons between measurements and computations in various flow conditions from stable to unstable atmospheres show good agreements with an averaged absolute difference of 0.8 dBA. Based on its good accuracy and acceptable computational efficiency, the new multi-fidelity framework is able to be used for designing and controlling wind farms.

Rapid Prediction Method of Fan Broadband Noise Based on A Three-dimensional Sound Source Model

The fan/compressor broadband noise is an important noise source of civil large bypass ratio turbofan engine.. The empirical method requires massive amounts of test data for support. Adopting the computational aeroacoustic (CAA) method to predict the fan/compressor broadband noise will cost high amounts of computing resources or time. Thus, this study combines flow field calculation with analytical model to study the prediction method of fan/compressor broadband noise, this method can be used for quick and efficient preliminary evaluation and parameter studies. On the basis of the simulation and modeling of the stator – rotor interference phenomenon of fans, rotor wake flow field and the corresponding parameters are obtained. On this basis, the three-dimensional sound source model is used to calculate the blade surface sound source and its propagation under different working conditions. The distribution of sound energy in the duct is obtained. Then, the broadband noise prediction of fan is further acquired. The broadband noise of a typical single-stage TA36 fan is predicted using this method. Study results suggest that (1) turbulence model and turbulence kinetic energy of inlet boundary condition will have an important effect on the prediction results of broadband noise. (2) When the inlet turbulence kinetic energy is small, different turbulence models slightly influence the prediction results of broadband noise; when the inlet turbulence kinetic energy is large, the sound pressure level of sound field obtained by SST model is approximately 5dB larger than that obtained by model. This method can be used in the early stage of fan/compressor design, and the characteristics of blade broadband noise can be rapidly obtained.

The quantitative measurement method for the radiation energy of the acoustoelectric converted wave field of building electricity

In order to provide the basis for the quantitative measurement of wave field radiation energy formed by building electricity and promote the development of construction industry, the quantitative measurement method for the radiation energy of the acoustoelectric converted wave field of building electricity is studied. Based on the multipole sound field of any azimuth order, the displacement potential of the sound field generated by the sound source is obtained, and the sound source model of the building electricity is established. According to the Pride theory, the acoustoelectric coupling equations are derived by using the established sound source model, and the acoustoelectric conversion of the building electricity is carried out. In this paper, the energy of Stoneley wave induced electric field in uniform medium is obtained according to the first coupling relation of acoustoelectric. The concept of electric energy density of low-frequency acoustoelectric polarization electric field is put forward, and the quantitative measurement of radiation energy of wave field is realized by deducing the specific expression. In the process of low-frequency acoustically induced polarization, the relationship between the density of electric energy and the frequency of sound wave and the permeability is obtained by simulation experiment. The results show that the energy distribution characteristics of buildings are similar when the distance between buildings is small, and the permeability and the density of electric energy are increasing.

기존 표준 충격원의 개선 필요성 및 신 연발성 충격원 개발 방향에 대한 전문가 대상 설문조사

Apartments are a suitable type of housing for a densely populated nation like Korea. Most of the complaints in apartment buildings are about the noise between floors. While children running are the main cause of inter-floor noise and have a moving point of continuity, the standardized impact source currently in use has a standing impact point. Before developing a new impact sound source model for simulations of children running, a survey was conducted to obtain expert opinions. A total of 50 respondents were surveyed in person, and their responses were analyzed. The experts agreed on the need for new continuous impact source models. They also preferred to study the influence of children running, continuity, and the movement of the impact point. The A-weighted sound pressure level was assessed to be the best-suited evaluation index.

Load Noise Prediction of High-Voltage Transformers by Equation Applying 3-D EMCN

This paper proposes a method for predicting the load noise of high-voltage (HV) transformers. When the transformer is loaded, the electromagnetic force is generated by the interaction between electric and magnetic fields. This force, the so-called Lorentz force, induces the vibration of the winding structure causing the load noise of transformer. Therefore, calculating the Lorentz force plays a crucial role in predicting the load noise. Herein, a 3-Dimensional equivalent magnetic circuit network (3-D EMCN) is applied to calculate the Lorentz force, instead of 3-Dimensional finite element analysis (3-D FEA) to shorten the computation time. Subsequently, considering the relationship between the sound pressure and the Lorentz force, the calculated force can be applied in the equation for the sound pressure level (SPL), which represents the relative sound pressure on a logarithmic scale. The formula for the sound pressure varies depending on the sound source model. The source model of load noise can be represented as a dipole source because the structure of the transformer windings is considered as an unbaffled speaker. The transformer parameters identified to affect the load noise are additionally considered for more accurate prediction of load noise. The parameters identified to increase the load noise are simply multiplied to the equation, whereas those with the opposite effect are multiplied inversely. Finally, after this compensation process, the accuracy of the load noise prediction equation is calculated as the standard deviation of the differences between the experimental and calculated results.