Prediction Of Sound Levels Research Articles

Research on the Calculation Method and Influence Law of High-speed Railway Line Sound Source Propagation Attenuation Caused by Building Sheltering

Abstract In recent years, China’s rail transit system, particularly the high-speed railway network, has experienced rapid development. However, the issue of noise pollution along these railways has become increasingly severe. The accurate prediction of sound levels at specific points near buildings is challenging due to complex factors such as differences in line height, distance, and angle relative to the building. To address this challenge and improve predictions of sound propagation attenuation caused by building shelter from high-speed railway line sources, this study derives an integral expression for diffraction attenuation based on Curze and Meakawa’s point source acoustic diffraction theory. Numerical calculations are conducted to investigate the sound propagation attenuation patterns under different position relationships between buildings and railway lines. Field tests are also carried out along a high-speed railway in China. The findings are as follows: (1) The calculated results show a difference of less than 0.5 dB compared to measured values, indicating that they accurately reflect sound attenuation caused by building shelter. (2) The angle between the building and the railway as well as the distance between the sound point and the edge of the building significantly influence building shelter attenuation; with angle being most prominent among them within a frequency band of 500~2000 Hz resulting in an attenuation range of 0.6~15 dB variation should be considered when predicting noise levels at sensitive points or designing vibration and noise reduction measures accordingly. (3) Different distances between buildings and railway lines result in additional effects on attenuations.

Prediction of sound and vibration levels from heavy-hard impacts in a cross laminated timber—Concrete hybrid building

Heavy-hard weight impacts in fitness spaces often result in elevated noise and vibration levels, which can lead to complaints in sensitive adjacencies. Previous works have demonstrated a method to predict the resulting noise and vibration levels in fitness space adjacencies. This method involves the analysis of an in situ transfer function in combination with laboratory force data and sound pressure level measurements from a shotput dropped on a calibrated reference rubber impact sheet. It was originally developed for use in concrete structures, which are typical for large multi-residential, commercial, and mixed-use buildings that commonly feature fitness amenity rooms or commercial gyms. The growing popularity of mass timber as a sustainable building material provides an opportunity to expand upon the previous research by examining the validity of the prediction method in another structural type. This paper serves as a case study of heavy-hard impacts in a residential hybrid mass timber structure, where weight drops from a fitness center at the top level of the concrete podium were disturbing apartment residents occupying the first CLT level directly above.

Evaluation of the Aeroacoustic Sources of a Swirl Diffusor

The acoustic noise generated by air diffusers can have negative impacts on a productive working environment and thus is a considerable limiting factor in ventilation systems. A reliable prediction of sound sources and levels offers the potential to minimise noise emissions in the early design process of air diffusers. In this work, we investigate a commercially available swirl diffuser. For a complete coverage of all flow and acoustic phenomena, the swirl diffuser is only slightly modified and modelled with transient flow simulations. We use large-eddy simulations coupled with the perturbed convective wave equation to model the flow and the aeroacoustic behaviour. The diffuser can be operated over a wide range of volume flows. To limit the computational cost, we investigate the diffuser at three operating points (278, 414 and 549 m3/h). To validate the computed aeroacoustic behaviour we use acoustic measurements. Laser-Doppler-Anemometry measurements are carried out to validate the flow simulation. The transient model is able to predict a sound spectrum and attribute certain features of the spectrum to geometric features of the air diffuser. Furthermore, the flow structures responsible for the sound are determined. These insights can offer guidelines for future designs of comparable air diffusers.

Predicting impulse prominence and tone audibility at remote assessment locations

This paper studies the prediction of impulse prominence and tone audibility at remote assessment locations, with a focus on industrial and commercial sound. The British Standard 4142 provides objective methods for determining graded corrections to the equivalent continuous sound pressure level for impulsivity and tonality, but these methods require specific sound sources to be installed and operating. In planning applications, where the sources are proposed or the propagation path is intended to change significantly, the professional judgement of the acoustics practitioner is relied upon to determine the likely prominence/audibility of these features at a remote assessment location. To address this issue, online listening tests utilising simplified auralisation ('auralisation-lite') were conducted among members of the Association of Noise Consultants in the UK. The initial results suggest that objective evaluation can indeed offer an improvement over existing subjective evaluations. The work provides a new method for practitioners to predict tonal and impulsivity corrections for non-existent sources. This study also provides a comprehensive review of relevant literature and standards, including ISO 9613-2:1996 and ISO/TR 17534-3:2015. The findings have practical implications for environmental agencies, industrial settings, and other fields where accurate prediction of sound level impacts are crucial.

Construction Noise Modeling for Solar Projects

The construction of a large solar project typically takes place over a period of 6 to 12 months. Construction is completed under several construction phases, each with a different mix of construction equipment. Due to the large project area where construction is proposed to occur, the sound exposure of a specific sound sensitive location varies as construction moves throughout the site. For example, road construction for a new access road might use an excavator, dozer, grader, roller, and dump truck. The road construction may or may not happen simultaneously to the trenching for the new collection route lines. Even if these activities were to happen at the same time, there is the possibility of them occurring on opposite sides of the project area or adjacent to each other. These unknowns make modeling construction noise for a large solar project complicated, especially during the permitting phase when schedules have not been fully developed. This paper will investigate scenarios used to provide a credible worst-case prediction of construction sound levels throughout a solar project area. Benefits, limitations, and practicality will be discussed.

Processing of tyre data for rolling noise prediction through a statistical modelling approach

Processing of tyre data for rolling noise prediction through a statistical modelling approach

Statistical analysis of sound level predictions in refracting and turbulent atmospheres

There is a lack of data on the statistical properties of the sound pressure level fluctuations which are caused by uncertainties in source/receiver heights, range, ground conditions and atmospheric effects. This paper contributes to this knowledge gap through statistical analysis of the atmospheric effects on sound pressure levels performed with a Green’s function parabolic equation model and a turbulence scattering model. The probability density functions for the sound pressure level relative to free field propagation are calculated for the source and receiver close to the ground, up to 1 km propagation distance, for typical annual meteorological conditions and two types of ground. It is found that the ground type and refractive state of the atmosphere have a pronounced effect on the probability distribution. Under some conditions and at some frequency intervals, distributions can be remarkably similar. Furthermore, accounting for meteorological effects become increasingly important with range when predicting sound pressure level distributions. This work contributes to a better understanding of the role of uncertainties in outdoor sound propagation that might serve for improved accuracy of statistical source localisation and characterisation methods based on parameter inversion.

Auditory impairment from acoustic seal deterrents predicted for harbour porpoises in a marine protected area

Abstract Management interventions to reduce human–wildlife conflict can have unintended consequences for non‐target species. Acoustic deterrent devices (ADDs) are used globally by the aquaculture sector. However, the potential for these sound emissions to impact non‐target species, such as cetaceans, has not yet been quantified at population relevant spatial scales. To better understand the extent of potential impacts on cetaceans, such as harbour porpoises, we used acoustic modelling to investigate levels of ADD noise throughout the west coast of Scotland and across a Special Area of Conservation (SAC) for this species. Using an energy‐flux acoustic propagation model and data on aquaculture sites known to be using ADDs, we predicted the spatial extent of ADD noise on the Scottish west coast from 1 February 2017 to 31 January 2018. Noise maps were produced to determine the risk of auditory impairment for harbour porpoises under a range of scenarios which assumed single or multiple ADDs and simultaneous use across all sites. The acoustic propagation model performed well when tested against field measurements up to 5 km, with 98% of sound exposure level (SEL) predictions within ±10% of the measurements. Predictions of SELs over a 24‐hr period suggested extensive temporary hearing loss zones (median radius: ~28 km) for harbour porpoises around aquaculture sites. Assuming a single device at each site, 23% of the harbour porpoise SAC was predicted to be exposed to ADD noise sufficient to induce a temporary threshold shift, and under the worst‐case scenario (multiple, continuously running devices per site with an aggregate duty cycle of 100%), levels exceeding permanent threshold shift could reach 0.9% of the SAC. Policy implications. This study highlights the potential for ‘collateral damage’ from interventions such as acoustic deterrent devices (ADDs) which are intended to reduce human–wildlife conflicts with pinnipeds but may affect the long‐term health and habitat use of non‐target species. This is especially true for harbour porpoises which are protected under the EU and UK Habitats Regulations. The aquaculture industry, policymakers and regulators in countries where ADDs are used should consider these findings when attempting to mitigate pinniped depredation.

Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network.

Wireless acoustic sensor networks are nowadays an essential tool for noise pollution monitoring and managing in cities. The increased computing capacity of the nodes that create the network is allowing the addition of processing algorithms and artificial intelligence that provide more information about the sound sources and environment, e.g., detect sound events or calculate loudness. Several models to predict sound pressure levels in cities are available, mainly road, railway and aerial traffic noise. However, these models are mostly based in auxiliary data, e.g., vehicles flow or street geometry, and predict equivalent levels for a temporal long-term. Therefore, forecasting of temporal short-term sound levels could be a helpful tool for urban planners and managers. In this work, a Long Short-Term Memory (LSTM) deep neural network technique is proposed to model temporal behavior of sound levels at a certain location, both sound pressure level and loudness level, in order to predict near-time future values. The proposed technique can be trained for and integrated in every node of a sensor network to provide novel functionalities, e.g., a method of early warning against noise pollution and of backup in case of node or network malfunction. To validate this approach, one-minute period equivalent sound levels, captured in a two-month measurement campaign by a node of a deployed network of acoustic sensors, have been used to train it and to obtain different forecasting models. Assessments of the developed LSTM models and Auto regressive integrated moving average models were performed to predict sound levels for several time periods, from 1 to 60 min. Comparison of the results show that the LSTM models outperform the statistics-based models. In general, the LSTM models achieve a prediction of values with a mean square error less than 4.3 dB for sound pressure level and less than 2 phons for loudness. Moreover, the goodness of fit of the LSTM models and the behavior pattern of the data in terms of prediction of sound levels are satisfactory.

METHODUCAL APPROACH AND ASSESSMENT OF NOISE IMPACT OF RAIL TRANSPORT ON THE BASIS OF THE USE OF RISK ASSESSMENT METHODOLOGY

The paper presents the results of measurement, prediction and assessment of noise in the territory in the zone of the influence of the railway transport. The railway transport is established to be a source of excess acoustic impact on the environment within the area of sanitary break (100 m). The dependence of the change in noise levels from freight trains at a distance of 100 m from the source and up to 30 m from the ground surface was revealed. Equivalent sound levels in octave bands for the railway section of the model are calculated. Based on the results of field measurements and calculated data, the identification of indices of risk for adverse reactions in the population living in the zone of influence of the Railways was executed. The paper presents results of the calculation of the probability of occurrence of complaints on excessive noise and the likelihood of irritation at the noise, and the results of the calculation of risk indices of pathologies of the nervous and cardiovascular systems. The research made it possible to identify the regulatory documentation discrepancy in the definition of the health gap between the line source traffic noise and residential buildings. Field measurements and executed on their basis their modeling of the noise propagation (without obstacles) have shown that on the boundary of the regulatory sanitary protection zone (100m) in the congested section of the railway the noise level of 60-62 dBA is maintained. The risk of irritation to the noise and the likelihood of complaints is assessed as “acceptable”. The risk of pathology of the cardiovascular system is evaluated as “low”. At a distance of 50 m (65 dBA) with bearing in mind age-related changes after 70 years of exposure the risk reaches of extreme values - 0,935. Construction sites located less than 100 m from the railway were shown to fall into the zone of acoustic discomfort. There was substantiated the necessity of resolving differences in regulatory documentation by harmonizing sanitary and technical groups documents regulating methods of measurement, prediction and evaluation of sound levels on the territories in the zone of influence of the Railways.

Turbomachinery Noise Predictions: Present and Future

In future Ultra-High By-Pass Ratio turboengines, the turbomachinery noise (fan and turbine stages mainly) is expected to increase significantly. A review of analytical models and numerical methods to yield both tonal and broadband contributions of such noise sources is presented. The former rely on hybrid methods coupling gust response over very thin flat plates of finite chord length, either isolated or in cascade, and acoustic analogies in free-field and in a duct. The latter yields tonal noise with unsteady Reynolds-Averaged Navier–Stokes (u-RANS) simulations, and broadband noise with Large Eddy Simulations (LES). The analytical models are shown to provide good and fast first sound estimates at pre-design stages, and to easily separate the different noise sources. The u-RANS simulations are now able to give accurate estimates of tonal noise of the most complex asymmetric, heterogeneous fan-Outlet Guiding Vane (OGV) configurations. Wall-modeled LES on rescaled stage configurations have now been achieved on all components: a low-pressure compressor stage, a transonic high-pressure turbine stage and a fan-OGV configuration with good overall sound power level predictions for the latter. In this case, hybrid Lattice–Boltzmann/very large-eddy simulations also appear to be an excellent alternative to yield both contributions accurately at once.

Statistical study of the relationships between mobile and fixed stations measurements in urban environment

Abstract Sound level predictions are based on both simplified emission and propagation models able to deal with transport and industrial sources only, thus neglecting other sound sources which yet contribute to urban soundscapes. Sound level assessment can take advantage of acoustic measurements if a sufficient amount of sensors is deployed to pick up the variety of sound sources. This can be achieved by combining fixed and mobile sensors that offer high temporal and spatial granularities respectively. The paper proposes a raw data processing protocol for comparing mobile with fixed measurements when the mobile sensors pass close to sound observatories. The statistical study is strengthened by a preliminary numerical analysis of the noise levels discrepancy between fixed and mobile sensors according to the location of the fixed station in relation to the facade.

Corrigendum

Corrigendum

Machine learning-based prediction of outdoor ambient sound levels: Ensemble averaging and feature reduction

Outdoor ambient sound levels can be predicted from machine learning-based models derived from geospatial and acoustic training data. To improve modeling robustness, median predicted sound levels have been calculated using tuned models from different supervised machine learning modeling classes. The ensemble-based model reduces errors at training sites for both overall levels and spectra, and produces more physically reasonable predictions elsewhere. Furthermore, the spread in the ensemble provides an estimate of the modeling accuracy. An initial analysis of feature importance metrics suggests that the number of geospatial inputs can be reduced from 120 to 15 without significant degradation of the model's predictive error, as measured by leave-one-out cross validation. However, the predictions from the reduced-feature modeling may be less physical in certain regions when all differentiating geospatial features are removed. These results suggest the need for more sophisticated data collection and validation methods.

Modeling anthropogenic noise impacts on animals in natural areas

Abstract Noise is a globally pervasive pollutant that can be detrimental to a range of animal species, with cascading effects on ecosystem functioning. As a result, concern about the impacts and expanding footprint of anthropogenic noise is increasing along with interest in approaches for how to mitigate its negative effects. A variety of modeling tools have been developed to quantify the spatial distribution and intensity of noise across landscapes, but these tools are under-utilized in landscape planning and noise mitigation. Here, we apply the Sound Mapping Tools toolbox to evaluate mitigation approaches to reduce the anthropogenic noise footprint of gas development, summer all-terrain vehicle recreation, and winter snowmobile use. Sound Mapping Tools uses models of the physics of noise propagation to convert measured source levels to landscape predictions of relevant sound levels. We found that relatively minor changes to the location of noise-producing activities could dramatically reduce the extent and intensity of noise in focal areas, indicating that site planning can be a cost-effective approach to noise mitigation. In addition, our snowmobile results, which focus on a specific frequency band important to the focal species, are consistent with previous research demonstrating that source noise level reductions are an effective means to reduce noise footprints. We recommend the use of quantitative, spatially-explicit maps of expected noise levels that include alternative options for noise source placement. These maps can be used to guide management decisions, allow for species-specific insights, and to reduce noise impacts on animals and ecosystems.

Characteristics and prediction of sound level in extra-large spaces

Abstract This paper aims to examine sound fields in extra-large spaces, which are defined in this paper as spaces used by people, with a volume approximately larger than 125 , 000 m 3 and absorption coefficient less than 0.7. In such spaces inhomogeneous reverberant energy caused by uneven early reflections with increasing volume has a significant effect on sound fields. Measurements were conducted in four spaces to examine the attenuation of the total and reverberant energy with increasing source-receiver distance, which was then validated by the simulations with image-source method. Results show that the reasons for the total energy’s exponential decrease are not only the direct sound, but also the reverberant energy. The prediction difference of total sound pressure level (SPL) between classical formula and the image-source method increases with the volume and decreases with the surface absorption, based on which a critical line separating extra-large spaces from large ones is proposed. Moreover, a newly modified model based on the importance of first reflection from floor is proposed, showing more advantages of sound level prediction in extra-large spaces.

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.

Application of the aeroacoustic analogy to a shrouded, subsonic, radial fan

Abstract A study was conducted to investigate the predictive capability of computational aeroacoustics with respect to a shrouded, subsonic, radial fan. A three dimensional unsteady fluid dynamics simulation was conducted to produce aerodynamic data used as the acoustic source for an aeroacoustics simulation. Two acoustic models were developed: one modeling the forces on the rotating fan blades as a set of rotating dipoles located at the center of mass of each fan blade and one modeling the forces on the stationary fan shroud as a field of distributed stationary dipoles. Predicted acoustic response was compared to experimental data measured at two operating speeds using three different outlet restrictions. The blade source model predicted overall far field sound power levels within 5 dB averaged over the six different operating conditions while the shroud model predicted overall far field sound power levels within 7 dB averaged over the same conditions. Doubling the density of the computational fluids mesh and using a scale adaptive simulation turbulence model increased broadband noise accuracy. However, computation time doubled and the accuracy of the overall sound power level prediction improved by only 1 dB.

Simplified analytical model for sound level prediction at shielded urban locations involving multiple diffraction and reflections

Accurate and efficient prediction of the sound field in shadow zones behind obstacles is a challenging task but essential to produce urban noise maps. A simplified method is presented to predict sound levels at shielded urban locations, including multi-edge diffraction over successive buildings and multiple reflections between parallel façades. The model is essentially based on Pierce's diffraction theory, where the Fresnel Integral is approximated by trigonometric functions for efficient evaluation, and parameterized for urban environments. The model has been validated for idealized urban configurations by comparing to the results of Pierce's theory and a full-wave numerical method. In case of multi-edge diffraction over buildings in absence of a source or receiver canyon, deviations from the full-wave simulations are smaller than 2 dB for the octave bands with central frequencies ranging from 125 to 1000 Hz. However, larger errors are made when receivers are close to the extension line from the diffraction edge closest to the receiver. In case of combining the simplified multi-edge diffraction model with an efficient approach for including the series of mirror sources and mirror receivers, based on the Hurwitz-Lerch transcendent, this same accuracy is obtained.

Enhanced Propagation of Aviation Noise in Complex Environments: A Hybrid Approach

Accurate prediction of sound levels around airports and below flight paths can help faithfully represent the impact of aviation noise on communities. However, for large scale assessments, as are often performed by the U.S. Federal Aviation Administrationis environmental models, the accuracy of a model must be weighed against its efficiency. The hybrid propagation model (HPM) is capable of predicting propagation through complex environments. It is a composite of three methods—the generalized terrain parabolic equation (GTPE), fast field program (FFP), and straight ray models—each utilized in a different region of elevation angles from the source. If propagation conditions do not warrant use of the full model, one of the component models with faster runtime can be chosen as a surrogate. Analyses of cases using different source heights and including uneven terrain, refractive atmosphere, and ground type transitions, indicate when a detailed propagation model is needed, or when a simpler model is sufficient.