Prediction Of Sound Pressure Level Research Articles

Improvements to a Method to Simulate Non-Stationary Wind Noise in Vehicles

As the vehicle and wind speeds and directions change, the unsteady flow creates non-stationary wind noise. To investigate people's perceptions of non-stationary wind noise, a method to simulate the non-stationary wind noise is needed. Previously, a method was developed that used stationary recordings taken at several speeds and directions to create a set of sound pressure level predictions in each one-third octave band that are a function of wind speed and direction. These functions are used to create time-varying filters based on provided wind profiles. A reference wind noise measurement is then filtered to produce the sounds. A drawback of this method is that many stationary wind condition measurements are needed to form accurate sound pressure level functions, which can be time consuming. A method requiring fewer measurements was investigated. At each yaw angle one non-stationary noise measurement and one stationary reference measurement are used to estimate the relationship between sound power and wind speed. The accuracy of the estimation was validated by comparing wind noise simulations with wind tunnel measurements, A further improvement is to use partially correlated white noise signals to simulate binaural sounds that have a similar coherence structure between the left and right ear sounds to that observed in binaural measurements in the vehicle.

Applicability of the structure-borne sound source characterisation Two-Stage method as well as the parameters derived in sound pressure level predictions in lightweight constructions

When predicting structure-borne sound-induced sound pressure levels, in addition to describing the sound propagation path through the building structure as exactly as possible, it is necessary to characterise the vibration behaviour of the structure-borne sound sources. The investigations described here were carried out to extend the applicability of the structure-borne sound source characterisation two-stage method described in EN 15657 and to describe its uncertainties. Furthermore, the suitability of the structure-borne sound parameters determined with TSM in the sound pressure level prediction according to EN 12354–5 was tested and statements on the achievable accuracy were derived. For both methods - characterisation of structure-borne noise sources and prediction of structure-borne noise-induced sound pressure levels - data on prediction accuracy are only available to a very limited extent but are essential for a reliable prediction model.Firstly, different sources of structure-borne sound were characterised using the two-stage method on different reception plates. In the process, structure-borne sound sources with defined acting moments were also investigated to analyse their influence on characterisability. Using the characterised vibration parameters of the structure-borne sound sources, the power introduced into different reception plates was then calculated and compared with measurements to establish the achievable accuracy of the characterisation method.Subsequently, the investigated structure-borne sound sources were installed in a lightweight test stand and the resulting sound pressure levels were measured in an adjacent receiving room. These were compared with the sound pressure levels predicted according to EN 12354–5 to obtain reliable statements on the achievable accuracy when using source quantities determined using TSM in the normatively described prediction procedure for structure-borne sound-induced sound pressure levels. A mean deviation between predicted and measured sound pressure levels of approx. 7 dB could be determined across all investigated sources.

Overview of Methods for Noise and Heat Reduction in MRI Gradient Coils.

Magnetic resonance imaging (MRI) gradient coils produce acoustic noise due to coil conductor vibrations caused by large Lorentz forces. Accurate sound pressure levels and modeling of heating are essential for the assessment of gradient coil safety. This work reviews the state-of-the-art numerical methods used in accurate gradient coil modeling and prediction of sound pressure levels (SPLs) and temperature rise. We review several approaches proposed for noise level reduction of high-performance gradient coils, with a maximum noise reduction of 20 decibels (dB) demonstrated. An efficient gradient cooling technique is also presented.

Sea state induced sound transmission loss of atmospheric broadband sources

This work presents a numerical study conducted on atmospheric sound propagation over sea. In particular, it focuses on the sound pressure level prediction uncertainties induced by the water surface roughness. To quantify these uncertainties, the generalized terrain parabolic equation (GTPE) is used to model sound propagation above water surfaces at different seastates. Water roughness is pseudo-randomly generated using Pierson-Moskovitz ocean wave spectrum. Building on a previous result that has established a simple expression for predicting single frequency sound transmission loss as a function of sea state, this work extends the approach to broadband signal from 125 to 1000 Hz. This work presents relationships between fully developed sea states (up to sea state 4) and the uncertainties on sound pressure level predictions at distances up to 1000 m from the source. These relationships are presented for typical nocturnal thermal gradients and for different elevations from the water surface.

Traffic noise prediction using machine learning and monte carlo data augmentation: a case study on the Patiala city in India

Traffic noise pollution is a serious problem in the modern urban areas especially to design new architecture of smart cities, highways, hospitals, schools for an efficient and healthy environment. To analyse this aspect, we have proposed a machine learning based prediction of sound pressure level on an original dataset collected in Patiala city in India. Vehicular traffic and sound pressure level data was collected on different sites in the city. A total of 502 data samples on the identified sites were obtained for the study. Further this data is augmented using Monte Carlo simulation to 10 times of its initial size and the Artificial Neural Networks (ANN) have been trained and compared with other Machine learning methods for the vehicular traffic noise prediction. The input parameters in the model are traffic volume Q, percentage of heavy vehicles P and the average speed of vehicles V and the output parameter is the equivalent continuous sound pressure level, Leq dB(A). The experimental results show ANN which is trained on the augmented data using Monte Carlo simulations outperforms other advanced methods making it an effective measure for vehicular traffic noise prediction to develop a healthy environment which is free of noise pollution.

Synchronized measurements of noise characteristics and flow regimes near the thermal expansion valve using R134a refrigerant

• Quantitative flow-induced noise prediction model. • Synchronized measurements of flow-induced noise and flow regimes. • Comparison between noise modeling and experimental measurements. • Distinguished flow-induced noise waveforms for different flow regimes. Flow-induced noise in the expansion device can be very disturbing. The thermal expansion valve is usually positioned near the occupants, often resulting in flow-induced noise that can be perceived as annoying. Current studies lack a quantitative relationship between flow characteristics and flow-induced noise. Therefore, in this paper, a noise prediction model is proposed to predict the sound pressure level of flow-induced noise. The study utilizes a pumped R134a loop for synchronized measurements between flow-induced noise and flow regimes. Synchronized high-speed measurements obtained from a microphone and a high-speed camera enable simultaneous investigation of flow-induced noise and flow regimes. In this case, the experimental results find a gurgling noise distributing near 9 kHz. Using the TXV inlet pressure for calculating thermodynamic properties, the gurgling noise sound pressure level prediction error is less than 15%. A hissing noise distributing at around 15 kHz is not as noticeable as the gurgling noise. The error of sound pressure level prediction for hissing noise is less than 40%. Both the experimental results and the modeling results show that the sound pressure level of gurgling noise increases as the vapor mass fraction increases or the system mass flux increases. From the experimental results, the noise waveforms are distinguished. The model can correctly outline the shape of noise waveforms for different flow regimes with the help of visualizations. The model introduced in this paper shows the proper prediction for flow-induced noise except for the annular flow entering the valve.

Atmospheric sound transmission loss uncertainties induced by sea roughness

This work presents a numerical study conducted on atmospheric sound propagation over sea. In particular, it focuses on the sound pressure level prediction uncertainties induced by the water surface roughness. To quantify these uncertainties, the generalized terrain parabolic equation (GTPE) is used to model sound propagation above water surfaces at different sea states. Water roughness is pseudo-randomly generated using an ocean wave spectrum. The GTPE predictions are compared with those obtained using the Crank-Nicholson parabolic equation (CNPE) solver. When using the CNPE the sea surface is flat and has a surface impedance equivalent to that of a rough surface. The use of the GTPE is less computationally efficient but provides insight on the detectability of an acoustic source at sea. This work presents relationships between fully developed sea states (up to sea state 4) and the uncertainties on sound pressure level predictions at distances up to 500 m from the source. These relationships are presented for typical diurnal and nocturnal thermal gradients and for different elevations from the water surface.

Wavepacket modelling of broadband shock-associated noise in supersonic jets

Abstract

Noise Characteristics and Sound Pressure Level Prediction of Loggia Balcony in Apartment

Many residential areas are in the street class with high noise, including the apartment. Noise is often overlooked when it will have an impact on the health of residents. The balcony design in apartments can capture and even reduce noise, so this needs to be further investigated; the most widely used balcony in the apartment is a loggia type balcony. To find out the noise level of a place from a particular source such as traffic noise can be done by direct measurement. Knowing the noise level ratio, the method taken is field measurement, simulation, and mathematical calculations. The method of measuring the field using the Gunawangsa Manyar Apartment object by measuring noise levels carried out for 24 hours on the apartment's balcony, the noise level simulation method was carried out with I-Simpa, and the calculation method used a mathematical model. The results obtained are two types of noise on the apartment balcony, namely vehicle noise is steady, and vehicle noise is impulsive with noisy air-conditioner. The comparison of field measurements with simulation methods and calculations shows a high relationship so that the I-Simpa simulation method and calculation can be used to predict the desired noise level on a particular floor.

Wind Turbine Noise Prediction Using Random Forest Regression

Wind energy is one of the most widely used renewable energy sources in the world and has grown rapidly in recent years. However, the wind towers generate a noise that is perceived as an annoyance by the population living near the wind farms. It is therefore important to new tools that can help wind farm builders and the administrations. In this study, the measurements of the noise emitted by a wind farm and the data recorded by the supervisory control and data acquisition (SCADA) system were used to construct a prediction model. First, acoustic measurements and control system data have been analyzed to characterize the phenomenon. An appropriate number of observations were then extracted, and these data were pre-processed. Subsequently two models of prediction of sound pressure levels were built at the receiver: a model based on multiple linear regression, and a model based on Random Forest algorithm. As predictors wind speeds measured near the wind turbines and the active power of the turbines were selected. Both data were measured by the SCADA system of wind turbines. The model based on the Random Forest algorithm showed high values of the Pearson correlation coefficient (0.981), indicating a high number of correct predictions. This model can be extremely useful, both for the receiver and for the wind farm manager. Through the results of the model it will be possible to establish for which wind speed values the noise produced by wind turbines become dominant. Furthermore, the predictive model can give an overview of the noise produced by the receiver from the system in different operating conditions. Finally, the prediction model does not require the shutdown of the plant, a very expensive procedure due to the consequent loss of production.

Wheel–rail impact loads and noise generated at railway crossings – Influence of vehicle speed and crossing dip angle

Wheel–rail impact loads and noise at railway crossings are calculated by applying a hybrid prediction model. It combines the simulation of non-linear vertical dynamic vehicle‒track interaction in the time domain and the prediction of sound pressure level using a linear frequency-domain model. The two models are coupled based on the concept of an equivalent roughness spectrum. The time-domain model uses moving Green's functions for the linear vehicle and track models, accounting for wheel structural flexibility and a discretely supported rail with spatially-varying beam properties, and a non-Hertzian wheel–rail contact model. Three-dimensional surface geometry of the wheel and crossing is accounted for in the solution of the wheel–rail contact. The hybrid model is compared against field measurements and is demonstrated by investigating the influence of vehicle speed and crossing geometry on the radiated impact noise. Based on simulation results, it is concluded that the impact loads and noise can be mitigated by reducing the effective dip angle at the crossing, which is determined by the vertical trajectory of the wheel when making the transition between wing rail and crossing nose.

An outdoor sound propagation model in concert with geographic information system software

As industrial technology advances, man-made noise has increasingly contributed to natural environment soundscapes. To predict how this anthropogenic noise can affect these natural environments, engineers build acoustic models over given terrain; however many current models are not compatible with common Geographic Information System (GIS) software, could become outdated due to software version updates, or are written as proprietary packages unavailable to park management. The goal of this study was to create a true open source outdoor sound propagation model compatible with (but not dependent on) outside GIS software. The model was developed to include uneven terrain, atmospheric absorption, screening, wind effects, and ground effects using ISO 9613-2, an international standard for attenuation of sound during propagation outdoors. Given sound source inputs and locations over an input Digital Elevation Map, GIS compatible file types of spatially explicit sound pressure level predictions can be produced by this model. This tool allows for ecologists and park managers to get a better understanding of how anthropogenic noise is affecting soundscapes in natural environments. [Work supported by United Technologies Corporation Professorship.]

Modeling anthropogenic noise propagation using the Sound Mapping Tools ArcGIS toolbox

We introduce the open-source Sound Mapping Tools (SMT, implemented in ArcGIS with the Spatial Analyst extension) for use in terrestrial outdoor sound propagation modeling. SMT includes three sound propagation models: an updated version of SPreAD-GIS, based on the System for Prediction of Acoustic Detectability model; NMSIMGIS, a GIS implementation of the Noise Model Simulation (NMSim) algorithms; and an implementation of an international outdoor sound propagation standard, ISO 9613–2. SMT produces spatially-explicit predictions of sound pressure levels from one or more sound sources, facilitating the assessment of noise effects from sources such as motorized recreation, energy development, and road traffic. Model results can be weighted to represent variable acoustic sensitivity or compared to ambient sound pressure levels. SMT provides a user-friendly approach to produce sound level predictions across variable landscapes, with applications for environmental, behavioral, population, and community ecology studies and for planning and management of human land use and infrastructure.

Far field prediction of sound pressure level using panel contribution analysis and scale modeling

Panel contribution analysis is reviewed and then utilized to predict the sound radiation from a generator set. The generator set is divided into patches and transfer functions between the sound pressure at a point in the far field and the velocity of a patch were determined reciprocally both for the full-scale structure and a half-scale model. With the generator set running, a P-U probe was used to measure particle velocity and sound intensity simultaneously on each patch. The sound pressure level at a receiver point located 4.9 m away from the side of the generator set was calculated assuming uncorrelated and correlated sources. The predicted sound pressure, based on both full and half scale models, compared well with that measured. Transfer functions were also determined using boundary element methods and compared well with measurement. In addition, the contributions from each surface of the generator set enclosure were determined.

Prediction of sound pressure level for a dual-stage hydromechanical transmission

AbstractHydromechanical continuously variable transmissions are frequently used in high power applications, including agricultural vehicles, buses and heavy vehicles. These offer several operative advantages such as improved driving comfort, better operational management and less fuel consumption if appropriately managed. However, the acoustic impact that they generate in the environment, which should be checked in the early stages of the project, is often neglected. This paper studies the noise emitted by a drive train for urban buses, which comprises a natural gas engine and a hydromechanical input coupled dual-stage transmission. The aim of this study is the evaluation of the noise emitted by the transmission compared with that emitted by the engine, which is considered the main noise source in the vehicle. The study was carried out by means of a model of the entire vehicle that was implemented in an Amesim environment. The mechanical model was integrated with the acoustic models of the engine and of t...

Vibration and sound radiation of an electrostatic speaker based on circular diaphragm.

This study investigated the lumped parameter method (LPM) and distributed parameter method (DPM) in the measurement of vibration and prediction of sound pressure levels (SPLs) produced by an electrostatic speaker with circular diaphragm. An electrostatic speaker with push-pull configuration was achieved by suspending the circular diaphragm (60 mm diameter) between two transparent conductive plates. The transparent plates included a two-dimensional array of holes to enable the visualization of vibrations and avoid acoustic distortion. LPM was used to measure the displacement amplitude at the center of the diaphragm using a scanning vibrometer with the aim of predicting symmetric modes using Helmholtz equations and SPLs using Rayleigh integral equations. DPM was used to measure the amplitude of displacement across the entire surface of the speaker and predict SPL curves. LPM results show that the prediction of SPL associated with the first three symmetric resonant modes is in good agreement with the results of DPM and acoustic measurement. Below the breakup frequency of 375 Hz, the SPL predicted by LPM and DPM are identical with the results of acoustic measurement. This study provides a rapid, accurate method with which to measure the SPL associated with the first three symmetric modes using semi-analytic LPM.

The significance of parameter uncertainties for the prediction of offshore pile driving noise

Due to the construction of offshore wind farms and its potential effect on marine wildlife, the numerical prediction of pile driving noise over long ranges has recently gained importance. In this contribution, a coupled finite element/wavenumber integration model for noise prediction is presented and validated by measurements. The ocean environment, especially the sea bottom, can only be characterized with limited accuracy in terms of input parameters for the numerical model at hand. Therefore the effect of these parameter uncertainties on the prediction of sound pressure levels (SPLs) in the water column is investigated by a probabilistic approach. In fact, a variation of the bottom material parameters by means of Monte-Carlo simulations shows significant effects on the predicted SPLs. A sensitivity analysis of the model with respect to the single quantities is performed, as well as a global variation. Based on the latter, the probability distribution of the SPLs at an exemplary receiver position is evaluated and compared to measurements. The aim of this procedure is to develop a model to reliably predict an interval for the SPLs, by quantifying the degree of uncertainty of the SPLs with the MC simulations.

Acoustics research of propulsion systems

The liftoff phase induces high acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests to generate 1/3 octave band Sound Pressure Level (SPL) spectra. In an effort to update the accuracy and quality of liftoff acoustic loading predictions, non-stationary flight data from the Ares I-X were processed in PC-Signal in two flight phases: simulated hold-down and liftoff. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semi-empirical methods. This consisted of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares I-X flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Examination of the predictions versus measurements of an acoustic interaction model for spinning modes, and concurrent low frequency amplitude modulation acoustic signatures from a 3MW wind turbine

A recently presented hypothesis and model relating to the generation of spinning modes from wind turbines, as a direct result of acoustic interaction involving the tower, results in a far field infrasound sound pressure level prediction, which is higher than that predicted by point source method. The model also predicts a significant attenuation of the fundamental blade passing frequency component relative to the second and higher harmonics. The model concurrently predicts a low frequency (~20 Hz), amplitude modulated harmonic series as a side effect of the acoustic interaction on a 1.6 MW 80 m diameter wind turbine. This study examines the model predictions of a 3.0 MW 90 m diameter wind turbine, and compares the predictions to measurements of the low frequency harmonic series and blade passing frequency harmonics at several different distances from the wind turbine.

Steady state acoustic radiosity for the prediction of sound pressure levels in enclosures with diffuse surfaces

This paper presents a derivation for and shows practical application of the steady-state diffuse acoustic radiosity method to the prediction of steady state sound levels in rooms. The paper begins with a brief review of the general radiosity literature and a more thorough review of the radiosity method in acoustics and proceeds to derive the general steady state acoustic rendering integral equation applicable to radiative energy exchange enclosures with arbitrary surface reflection properties. The rendering equation is simplified assuming diffuse reflections and the enclosure surface is discretized to convert the integral equations into summations. A closed form matrix solution to the discrete equations and another matrix equation for computing mean square pressure at multiple locations from multiple sources are presented. The computer code used for further analysis is verified by comparison to a closed form solution for a special case. Convergence of the discretized solution is investigated and the method is shown to converge linearly as the patch size decreases. A practical implementation of the method for predicting of sound levels in a classroom is shown. Predictions using radiosity are compared with simple diffuse field theory and measurements of an actual room. The radiosity method is shown to match diffuse ray tracing to within a fraction of a dB and predictions with a discretization with patches as large as 2 m are shown to be within a fraction of a dB of the asymptotic values