Traffic Noise Pollution： Spectra Characteristics and Windows Sound Insulation in Laboratory and Field Measurements

The traffic spectra influence on indoor noise through windows is evaluated with laboratory and field measurements. Different traffic noise spectra were registered and reproduced, simulating the outdoor traffic conditions through different windows. Spectrum adaptation terms for the recorded spectra were different from the ones obtained from the Standards, showing that Normative gives a safe evaluation of the Weighted Sound Insulation Index. In field measurements, the level abatements calculated from the Facade Acoustic Insulation Index corrected with the adaptation terms shows that the ones from the Standard do not give a good approximation, while if the level abatements is calculated using the adaptation terms from the registered spectra, a more reliable approximation is achieved. Furthermore, comparing the level abatements for two windows having both Rw equal to 41 dB, very different values were obtained at different frequencies; therefore to characterize acoustic performances of windows, sound insulation curves are also needed. The correlation between the mean difference between adaptation terms calculated from the standard and the one between abatements obtained with pink noise and the ones obtained with the registered spectra is good, but different for road traffic and trains. In both, the difference diminishes when the difference between the abatements increases.

Assessment of Traffic Noise Pollution in Burla Town,India;An InclusiveAnnoyance Study

Noise pollution is one of the major public health problems in urban areas throughout the world.Noise is unwanted sound which produces undesirable problems in day to day life of human being(e.g.,physiological and psychological problems).Rapid increase of the industrialization,urbanization,infrastructure,volume of motor vehicles,and increase in the road networks brought noise pollution to the highest level of disaster in a current situation.In urban areas,road traffic noise plays commanding role among all noise sources and affects the exposed inhabitants.The present work is done to evaluate and assess the traffic noise and its effects in Burla town.Burla,Vidyanagari of Odisha,is an emerging town in India,as it hosts national level of teaching and research institutions like IIM Sambalpur,a medical college-cum-hospital(VIMSAR),a technical university(VSSUT)and Sambalpur University.In last two decade,the road traffic volume has been increased and is facing severe noise pollution to its inhabitants.Noise pollution assessment was made at different locations of the town.This study unveiled the dismal state of noise pollution in the town.Noise contour maps were drawn to visualize the noise level at the traffic and its surroundings.The numbers of hearing impaired patients in different hospitals of the locality are increasing.That shows grim picture of the situation.Regression equations were established taking noise levels with percentage of highly annoyed people during study indicates strong correlation.

Appraisal of Urban Road Traffic Noise in tier-II City(Surat City),India

Urban road traffic noise pollution has always been identified as a severe problem that affects urban populants.In developing nation,road traffic noise pollution depends on the composition of heterogeneous traffic composition.These traffic compositions contain vehicles,which have different sizes,speeds variations,a different dimension of vehicles.Environmental noise measurements have been carried out during day-time and night-time in different locations of tier-II city of India.The noise levels have been continuously measured over 24 h periods using kimo DB 300 class-2 noise level meter.The data contained in this research paper represent 768 measurement hours.All the information has been used to investigate the time patterns of the noise levels under a wide range of different conditions and to study the relationships between noise levels and traffic in urban areas.Maximum LAeq was observed 73.3 dB(A)at B_(14) location and the minimum was recorded 65.7 dB(A)at C_(3) location,which was greater than the central pollution control board(CPCB)prescribed limits during night time.A major reason for the generation of road traffic noise is due to the equal composition of 2-wheeler and 4-wheeler on the arterial road and heavy vehicles were recorded during morning peak and evening peak even though they are prohibited during peak hours.

3D Analysis and Investigation of Traffic Noise Impact from Hemmat Highway Located in Tehran on Buildings and Surrounding Areas

This study analyzes and investigates the impact of traffic noise on high rise buildings and surrounding areas by the side of Hemmat Highway that links west of Tehran to the east. In this study, a 3D traffic noise simulation model is applied on a GIS system. Visualized noise levels are formulated by the proposed model for noise mapping on all surfaces of the buildings and surrounding ground in a 3D platform. The investigation shows that there is a high traffic noise impact on the foreground and front facades of buildings, rendering these areas unsuitable for residential purposes. The ground area by the sides of buildings and the building side panels receive a lower noise impact. Most of these areas are still not acceptable for residential and even commercial use, only the back yards and back panels, have the lowest traffic noise impact. It also shows that the building height is not an effective factor for reducing motorway noise on the upper part of the building. Finally, construction cantilever barriers with a height of seven meters, close to the outer edge of the highway was presented as an effective way to reduce noise within the allowable range of noise pollution for commercial and residential purposes.

A Study of Noise &Development of Traffic Noise Annoyance Models

Although noise annoyance is a major public health problem in urban areas, noise problem is still a great challenge for both public and transportation planners. The quantitative study of traffic noise and its relationship with annoyance & traffic volume was discussed in the paper and at the same time we tried to develop new statistical regression models to relate them. In the present study we also tried to fit different regression models such as Log-Linear, Linear, Log-Log Linear and Quadratic over noise data and decided which model fitted the best by using mathematics of principle of maxima & minima. After the identification of best fit curve we use this to fit our data. The aim of the study was to assess the predictive value of various factors on noise annoyance in noisy and quiet urban streets of New Delhi, capital of India.

Airport Aviation Noise Prediction Based on an Optimized Neural Network

In order to alleviate noise pollution and improve the sustainability of airport operation,it is of great significance to develop an effective method to predict airport aviation noise. A three-layer neural network is constructed to gain computational simplicity and execution economy. With the preferred node number and transfer functions obtained in comparative tests,the constructed network is further optimized through the genetic algorithm for performance improvements in prediction. Results show that the proposed model in this paper is superior in accuracy and stability for airport aviation noise prediction,contributing to the assessment of future environmental impact and further improvement of operational sustainability for civil airports.

COLORED NOISE PREDICTION BASED ON NEURAL NETWORK

A method for predicting colored noise by introducing prediction of nonlinear time series is presented. By adopting three kinds of neural networks prediction models, the colored noise prediction is studied through changing the filter bandwidth for stochastic noise and the sampling rate for colored noise. The results show that colored noise can be predicted. The prediction error decreases with the increasing of the sampling rate or the narrowing of the filter bandwidth. If the parameters are selected properly, the prediction precision can meet the requirement of engineering implementation. The results offer a new reference way for increasing the ability for detecting weak signal in signal processing system.

Association of Road Traffic Noise with Obesity and the Role of Meat Intake:A Prospective Study from UK Biobank

Emerging evidence has indicated the linkage of traffic noise with cardiovascular diseases,However,there’s a lack of extensive studies exploring the linkage of traffic noise with cardiometabolic risk factors such as obesity.Additionally,the role of diet in the associations remains unknown.The aim is to prospectively examine the linkage of road traffic noise with obesity,especially by focusing on evaluating the impact of meat.Participants recruited in the UK Biobank with at least one repeated measurement of obesity indicators including body mass index(BMI),waist circumference(WC),waist-to-hip ratio(WhR),and waist-to-height ratio(WhtR)were included.The Common Noise Assessment Methods of the simplified version were used to estimate road traffic noise exposure.Participants were categorized into“less meat intake”and“more meat intake”based on the median of meat intake,assessed by the frequency of unprocessed red meat and processed meat consumption.Modified Poisson regression models were employed to evaluate the linkage of road traffic noise with obesity.Additionally,the modification effects of meat intake on this relationship were evaluated.The incidence risk ratios(IRRs)and 95%confidence interval(CI)of overall obesity,WC-based central obesity,WhR-based central obesity,and WhtR-based central obesity were 1.11(1.02,1.21),1.09(1.03,1.14),1.06(1.02,1.10),and 1.08(1.02,1.13),respectively,for every 10 dB(A)increase for noise.Compared with individuals with lower meat intake,those with higher meat intake exhibited a stronger linkage of road traffic noise with central obesity.The prospective study demonstrates a linkage of road traffic noise with obesity,emphasizing the significance of diet on traffic noise-related obesity risk.

PREDICTION AND EVALUATION OF POLLUTION OF URBAN TRAFFIC NOISE IN CHINA

The medium/long term prediction of urban traffic noise and evaluation of noisepollution in "macroscopic" way using computer are new research work in China. Inthis paper, some investigations, including the methods of predicting and evaluatingurban traffic pollution, have been repotted. Models for vehicles’ flow and propagationof noise in urban areas have been set up. Finally, a set of computer programs forthese purposes is given. Models and computer program have been tested in more than70 cities of China. It is proved that they can be used in medium/long term predictionof urban traffic noise pollution in China, and they are also of great values in evalu-ating the extent of urban traffic noise pollution.

Numerical Noise Prediction in Fluid Machinery

Numerical methods successively became important in the design and optimization of fluid machinery. However, as noise emission is considered, one can hardly find standardized prediction methods combining flow and acoustical optimization. Several numerical field methods for sound calculations have been developed. Due to the complexity of the considered flow, approaches must be chosen to avoid exhaustive computing. In this contribution the noise of a simple propeller is investigated. The configurations of the calculations comply with an existing experimental setup chosen for evaluation. The used in-house CFD solver SPARC contains an acoustic module based on Ffowcs Williams-Hawkings Acoustic Analogy. From the flow results of the time dependent Large Eddy Simulation the time dependent acoustic sources are extracted and given to the acoustic module where relevant sound pressure levels are calculated. The difficulties, which arise while proceeding from open to closed rotors and from gas to liquid are discussed.

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.

Prediction and Reduction of StructureBorne Noise in Vehicle

The structure and the acoustic medium of a passenger vehicle are modeled using the finite element method(FEM), and the interior noise is studied the help of the modal synthesis method (MSM). Sound pressure level (Lp) of the noise is calculated in several conditions of the models, and has good agreements with its test results. The MSM am be consequently used for predicting the vehicle interior noise in dssign stage so that the structure may be optimized for the Purpose of the most reduction of noise.

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.

ANNOYANCE AND SPEECH INTERFERENCE OF IMPULSE AND TRAFFIC NOISE

By using the modernly developed techniques of possibility and set-valued statistics, this paper determined the thresholds of various categories of noise annoyance and defined the dose-response relation between the levels of noise and their annoyance. Three factors controlled in the experiment were types of noise: impulse and traffic; level of noise: 5Leq from 45 - 85 dB (A); and performance task: with and without speech recognition. Noise interference with speech recognition was measured with the SDT method. Our ex-perimental results showed that Leq of impulse noise should be higher than that of traffic noise to get equal annoyance; the speech recognition task might lighten the experience of annoyance; the higher the level of noise, the more its interference with the speech recognition, that is. the less the value of d '.

Effects of traffic noise on pupils'behavior in classroom

Noise surveys in this country reported that a large number of classrooms in primary and secondary schools in the urban areas were disturbed by environmental noise, particularly by traffic noise. A series of psychological tests were conducted to identify pupils' behavior in a classroom under different noise levels within the range of 40 to 70 dBA. Statistical analysis results were obtained by using Relational Data Analysis System (RDAS) software. According to the t-test and single factor variance analysis of the results, significant differences of the pupils' behavior in the classroom have been observed when the percentile exceeded sound level either L50 exceeds 50 dBA or L10 exceeds 55 dBA, or the equivalent continuous sound level Leq exceeds 50 dBA. The same conclusion has been drawn from the average percentages of syllable articulation under different noise levels in a classroom which were the results of tests made in accordance with the procedure described in the National Standard. The maximum acceptable noise level in the classroom thus can be determined.

Step-by-Step Numerical Prediction of Aerodynamic Noise Generated by High Speed Trains

In this paper,the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method(DES),and the far-field noise is predicted using the Ffowcs Williams-Hawkings(FW-H)acoustic model.The reliability of the numerical calculation is verified by wind tunnel experiments.The superposition relationship between the far-field radiated noise of the local aerodynamic noise sources of the high-speed train and the whole noise source is analyzed.Since the aerodynamic noise of high-speed trains is derived from its different components,a stepwise calculation method is proposed to predict the aerodynamic noise of high-speed trains.The results show that the local noise sources of high-speed trains and the whole noise source conform to the principle of sound source energy superposition.Using the head,middle and tail cars of the high-speed train as noise sources,different numerical models are established to obtain the far-field radiated noise of each aerodynamic noise source.The far-field total noise of high-speed trains is predicted using sound source superposition.A step-by-step calculation of each local aerodynamic noise source is used to obtain the superimposed value of the far-field noise.This is consistent with the far-field noise of the whole train model’s aerodynamic noise.The averaged sound pressure level of the far-field longitudinal noise measurement points differs by 1.92 dBA.The step-by-step numerical prediction method of aerodynamic noise of high-speed trains can provide a reference for the numerical prediction of aerodynamic noise generated by long marshalling high-speed trains.

PREDICTION TECHNIQUES OF CHAOTIC TIME SERIES AND ITS APPLICATIONS AT LOW NOISE LEVEL

The paper not only studies the noise reduction methods of chaotic time series with noise and its reconstruction techniques, but also discusses prediction techniques of chaotic time series and its applications based on chaotic data noise reduction. In the paper, we first decompose the phase space of chaotic time series to range space and null noise space. Secondly we restructure original chaotic time series in range space. Lastly on the basis of the above, we establish order of the nonlinear model and make use of the nonlinear model to predict some research. The result indicates that the nonlinear model has very strong ability of approximation function, and Chaos predict method has certain tutorial significance to the practical problems.

Noise Impact and Improvement on Indoors Acoustic Comfort for the Building Adjacent to Heavy Traffic Road

A good acoustic environment is absolutely essential to maintaining a high level satisfaction and moral health among residents. Noise and other boresome sounds come from both in- door and outdoor sources. For the residential buildings adjacent to heavy traffic roads, outdoors traffic noise is the main source that affects indoor acoustic quality and health. Ventilation and outdoor noise prevention become a pair of contradictions for the residents in China nowadays for those buildings adjacent to heavy traffic roads. It is investigated that traffic noise emission is mainly con- stituted by the motors of trucks, buses and motorcycles as well as brake. In this paper, two methods of traffic noise reduction on the indoor sound environment and comfort are carried out to study and compare the residential buildings adjacent to heavy traffic roadway in a city. One is to install noise barriers on the two sides of the roadway, which consist of sound-proof glass and plas- tic materials. The effect of sound-insulation of this method is heavily dependent on the relative distance between the noise bar- rier and indoors. A reduction of sound with an average pressure level of 2–15dB is achieved on the places behind and under the noise barrier. However, for the equivalent of noise barrier height, the noise reduction effect is little. As for the places of higher than the noise barrier, the traffic noise will be even strengthened by 3–7dB. Noise increment can be seen at the points of distance farther than 15m and height more than noise barrier; the noise reduction effect is not satisfactory or even worsened. In addition, not every location is appropriate to install the noise barrier along the heavy traffic roads. The other method of noise reduction for the buildings adjacent to heavy traffic is to install the airproof and soundproof windows, which is the conversion from natural venti- lation to mechanical ventilation. A reduction of sound with an average pressure level of 5dB to 17dB can be achieved compared with common glass windows, if adopting sound proof glass win- dows. These two methods are helpful to isolate high frequency noise but not for low frequency noise. For those frequency noises, installing thick and cotton curtain and porous carpet can only decrease 2.4–4.5dB, which hardly contributes to indoor sound comfort, so further study is demanded to cut down traffic noise, especially to cut down the low frequency noise.

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.

Handling Label Noise in Air Traffic Complexity Evaluation Based on Confident Learning and XGBoost

Air traffic complexity is a critical indicator for air traffic operation,and plays an important role in air traffic management(ATM),such as airspace reconfiguration,air traffic flow management and allocation of air traffic controllers(ATCos).Recently,many machine learning techniques have been used to evaluate air traffic complexity by constructing a mapping from complexity related factors to air traffic complexity labels.However,the low quality of complexity labels,which is named as label noise,has often been neglected and caused unsatisfactory performance in air traffic complexity evaluation.This paper aims at label noise in air traffic complexity samples,and proposes a confident learning and XGBoost-based approach to evaluate air traffic complexity under label noise.The confident learning process is applied to filter out noisy samples with various label probability distributions,and XGBoost is used to train a robust and high-performance air traffic complexity evaluation model on the different label noise filtered ratio datasets.Experiments are carried out on a real dataset from the Guangzhou airspace sector in China,and the results prove that the appropriate label noise removal strategy and XGBoost algorithm can effectively mitigate the label noise problem and achieve better performance in air traffic complexity evaluation.