Noise Emission Model Research Articles

Influence of translational vehicle dynamics on heavy vehicle noise emission

Vehicle dynamics can play a significant role in the noise emission from heavy vehicles. In this work, a heavy vehicle noise emission model is presented to study the influence of translational vehicle dynamics on the sound power level emitted by heavy-duty trucks. Vehicle speed and acceleration are calculated using an analytical approximation that describes the tractive and retarding forces acting on a heavy vehicle on grade. Heavy vehicle noise emission associated with rolling noise is defined with reference to the Nordic traffic noise model that takes into account the number of axles for different articulated trucks. An expression for engine noise emission in terms of vehicle speed, weight, engine power, aerodynamic properties and road grade is derived. The individual and combined effects of engine noise and rolling noise for different vehicle mass combinations are examined. The influence of road grade on vehicle kinematics and noise emission is also investigated.

Characterization of damages from road traffic noise in life cycle impact assessment: A method based on emission and propagation models

Life cycle assessment (LCA) is a technique widely used to comprehensively characterize the environmental impacts of human activities, and covers a broad range of environmental impact categories. Despite the recognized significant impact of environmental noise on public health, mostly because of road traffic, until now noise has not been systematically included in LCA. Research has showed, however, that the addition of the impacts of noise could significantly change the interpretation of LCA results, specifically considering the importance of road transportation in the global economy. This paper proposes a method to calculate characterization factors (CF) for life cycle impact assessment of noise emissions from road traffic on human health. The method builds on up-to-date noise emission and propagation models. It was successfully tested on a demonstrative test bed case, which allowed us to identify the most suitable elementary flows, and draw the spatial variability of the CF and the associated uncertainties. Finally, the case proved that the consideration of noise could double the magnitude of the human health damages due to road transportation, which could significant affect policy decisions.

Case study: Establishment of a vehicle noise emission model for gradient roads

Traffic noise prediction is an important consideration for sound environmental planning in cities, and an accurate noise emission model is the key to the prediction of traffic noise. Since gradient road sections are common in urban road networks, a noise emission model for gradient roads is necessary. This study considers the relationship between the longitudinal slope of a road section and the driving state of the vehicle, which is a different approach from most of the existing noise emission models. The longitudinal gradient of the road section can be converted to additional acceleration and the extra output power of the vehicle. Thus, the noise emitted by a vehicle can be directly connected to its driving state, including the speed, acceleration, and the output power of the engine of the vehicle. To establish such a noise emission model, an experiment is conducted, and hundreds of data points for the vehicle's speed, acceleration, and noise emissions values are collected. The least-squares method is applied, and the accuracy of the model is verified by a comparison with the measured data and the canonical values. The results show that the average error between the established model and the measured values is less than 2 dB(A). A traffic simulation is conducted, and the results indicate that the noise value predicted by the model established in this article is closer to the measured value. Thus, the presented model can facilitate relatively accurate results in predicting the noise emission of vehicles on gradient road sections. © 2019 Institute of Noise Control Engineering

A six-category heavy vehicle noise emission model in free-flowing condition

Annoyance and sleep disturbance caused by transportation noise are frequently associated with heavy vehicles. The ability to accurately predict heavy vehicle noise impact using conventional road traffic noise prediction methods has reduced over the years as the variety of heavy vehicles have increased progressively and the predominant long haul freight vehicle is trending towards larger trucks with a greater number of axles. In this paper, a six-category heavy vehicle source emission model in free-flowing condition has been developed based on the state-wide road setting in New South Wales, Australia. The six-category model allows traffic noise across the road network, carrying a diverse fleet of heavy vehicles, to be predicted with notably higher accuracy and precision in comparison to conventional models that aggregate heavy vehicles into one, or at most, two distinct categories. A comparative analysis is carried out to examine the source emission from various traffic mix scenarios in urban areas and along major freight routes. Current findings also highlight the importance of distinguishing regional characteristics in a harmonised road traffic noise prediction model.

A combined emission and receptor-based approach to modelling environmental noise in urban environments

The state of practice for noise assessment utilizes established standards for emission and propagation modelling of linear and point sources. Recently, land use regression (LUR) modelling has emerged as an alternative method due to relatively low data and computing resource demands. However, a limitation of LUR modelling is that is does not account for noise attenuation and reflections by features of the built environment. This study demonstrates and validates a method that combines the two modelling frameworks to exploit their respective strengths: Emission and propagation based prediction of traffic noise, the predominant source of noise at the level of streetscapes, and a LUR-based correction for noise sources that vary on spatial scales beyond the streetscape.Multi-criteria analysis, location-allocation modelling and stakeholder consultation identified 220 monitoring sites with optimal coverage for a 1-week sampling period. A subset of sites was used to validate a road traffic noise emission and propagation model and to specify a LUR model that predicted the contribution of other sources. The equivalent 24-h sound pressure level (LAeq) for all sites was 62.9 dBA (SD 6.4). This varied by time of day, weekday, types of roads and land uses. The traffic noise emission model demonstrated a high level of covariance with observed noise levels, with R2 values of 0.58, 0.60 and 0.59 for daytime, nighttime and 24-h periods, respectively. Combined with LUR models to correct for other noise sources, the hybrid models R2 values were 0.64, 0.71 and 0.67 for the respective time periods.The study showed that road traffic noise emissions account for most of the variability of total environmental noise in Toronto. The combined approach to predict fine resolution noise exposures with emission and receptor-based models presents an effective alternative to noise modelling approaches based on emission and propagation or LUR modelling.

Comparison of some wind turbine noise emission models coupled to BEM aerodynamics

Noise is an important design driver for onshore wind turbines. Therefore, there is a need to include validated noise prediction models within wind turbine and wind plant design procedures. However, the literature presents a multitude of different models and formulations, combined with a severe lack of publicly available experimental data. The present work presents a comparison between semi-empirical frequency-domain methods coupled to blade element momentum (BEM) aerodynamics, which is the typical approach used for the transient aeroelastic analysis of wind turbines. Among the various noise sources, only turbulent boundary layer – trailing edge and turbulent inflow noise models have been considered in the present analysis. The noise models are benchmarked in terms of emission spectra, highlighting differences and discrepancies. A time-domain Ffowcs Williams-Hawkings formulation is also coupled to the same BEM model, investigating its ability in predicting low frequency emissions. Thanks to this study, a few inconsistencies among published noise models are identified and reported.

Integrated design optimization of wind turbines with noise emission constraints

This study integrates aeroacoustic noise emission models within a wind turbine design procedure to include overall sound pressure levels as design constraints. The proposed approach aims at the minimization of the cost of energy from wind, while ensuring the compliance with noise emission limits. The reference 3.35 MW onshore wind turbine developed within the international cooperation IEA Wind Task 37 is redesigned to reduce its noise emissions above and below rated wind speed, considering both single- and multi-objective design criteria. Results obtained with the proposed noise-constrained redesign methodology are compared with the simpler approach of reducing the tip speed without altering the blade shape. Results show that, while the simplistic approach causes a drop of −2.8% in annual energy production and a +2.5% increase in cost of energy, an optimized configuration fulfills the noise requirement without incurring into significant energy penalties.

Optimization of Cutting Parameters for Minimizing Environmental Impact: Considering Energy Efficiency, Noise Emission and Economic Dimension

Green manufacturing is attracting significant attention from the academic and industrial world under current environmental circumstances. The purpose of the present study is to evaluate trade-offs between the main factors in green manufacturing: energy, noise and cost, through cutting parameter optimization. First, the energy consumption model is developed based on the analysis of the relationship among sub-processes, power and cutting parameters. Then numerical noise emission model, which integrates orthogonal experiment and response surface method, is proposed. Moreover, Analysis of Variance results are employed to analyze the influence of cutting parameters on noise, the results show that the depth of cut is the dominating influencing factor of noise, then the cutting cost model is presented. The multi-objective optimization model for energy saving, noise reducing and cost saving is proposed, which takes cutting speed, feed fate and depth of cut as decision variables. NSGA-II is adopted to obtain the Pareto optimal solutions. The most suitable Pareto-optimal solution is selected by a combination weighting method. A case study involving the cutting process of a CNC lathe is used to validate the proposed methodology, and the results are discussed and analyzed.

Estimation of road traffic noise emissions: The influence of speed and acceleration

This paper relies on vehicle trajectory collection on a corridor, to compare different traffic representations used for the estimation of the sound power of light vehicles and the resulting sound pressure levels. Four noise emission models are tested. The error introduced when the emissions are calculated based on speeds measured at regular intervals along the road network are quantified and explained. The current noise emission models might in particular misestimate noise levels under congestion. This bias can be reduced by introducing additional traffic variables in the modeling. In addition, significant differences within the models are highlighted, especially concerning their accounting of vehicle accelerations. Models that rely on a binary representation of acceleration regimes (a vehicle or a road segment is accelerating or not) can lead to errors in practice. Models under use in Europe have a very low sensitivity to acceleration values. These results help underlying the further required improvements of dynamic road traffic noise models.

Dynamic traffic noise assessment tool: A comparative study between a roundabout and a signalised intersection

Considering traffic flow as a steady noise source is common practice when studying traffic alternatives and its impact on the sound environment. However, vehicle dynamics have a strong influence on both transport behaviour and noise emission. One of the most relevant elements of traffic design is the intersection, where replacement of crossing intersections with roundabouts is common. In order to understand the features of these two traffic configurations, microscopic approaches are needed, making it possible to study time-pattern fluctuations relevant for the urban sound environment perception. A model based on individual-vehicle characteristics as function of time is developed and implemented in a real case study at a development stage. The model incorporates state-of-art microscopic traffic simulation software combined with the recent noise emission model, CNOSSOS-EU, applied through an in-house developed dynamic traffic noise tool, including both internal combustion engine and all-electric vehicles at different traffic flows. The tool is described in general terms incorporating the randomisation of source power. The propagation considers a flat-city configuration up to 100m range. The tool enables study of different statistical indicators, including descriptors of probability density functions, calm periods through the novel indicator Centre of Mass Time (CMT) and noise events. The outcomes are presented through graphs and maps explaining traffic disruptions, acceleration effects, vehicle configurations and flows, source strengths, contribution and difference maps. Among the results, it is shown that, for the signalised crossing, the acceleration of the simulated traffic has a large effect on the source strength. It is however also shown that, for an unbalanced roundabout intersection leading to congestions, it can become noisier than the signalised crossing. It is furthermore shown that, when reducing the traffic flow, the two intersection types behave more similarly; however the roundabout having the best performance for the majority of the studied analysis. Further results are shown, e.g. for removing heavy vehicles, removing also medium heavy vehicles and assuming only all-electric light vehicles, including analysis from using various indicators. A discussion about the presented tool, the current results and ideas for future work concludes the paper.The present paper goes along a series of studies with the overall intention to provide a more solid basis for justifying decisions in traffic planning regarding the outdoor sound environment.

Aircraft Noise Emission Model Accounting for Aircraft Flight Parameters

Today’s aircraft noise calculation programs either use simple sound source descriptions with few input parameters or highly sophisticated models with input parameters, which are difficult to obtain. To fill the gap between these two approaches, an aircraft noise emission model based on regression of measured noise with aircraft flight parameters is presented. To find a reasonable compromise between the degree of detail and number of required flight parameters, an extensive data exploration was conducted. The most relevant parameters were incorporated in two multiple linear regression models, one for airframe and one for engine noise sources. An iterative method allowed fitting both regression models to aircraft flyover measurements. In total, aircraft noise emission models for 19 aircraft types were established, which underlines the general applicability of the modeling approach to turbofan-powered aircraft. Example comparisons between measurements and model predictions for two aircraft types revealed that the model accurately reproduces directivity and spectra for different flight configurations. In addition, it is suitable for the assessment and optimization of noise abatement procedures.

Dynamic simulation and characteristics analysis of traffic noise at roundabout and signalized intersections

Traffic noise prediction is an important topic for traffic environment planning in cities. The complex traffic flow at road intersections makes the prediction of traffic noise challenging. In this paper, a dynamic traffic noise simulation method based on microscopic traffic simulation is used to study the traffic noise near roundabout and signalized intersections. A vehicle noise emission model that considers the effect of acceleration is established using an experimental method. The accuracy of the model is verified by comparison with measured data. Traffic noise near roundabout and signalized intersections under different traffic volume levels is simulated, and the results are compared. Some significant relations between traffic noise and traffic volume are obtained, and the mechanisms are analyzed. The results show that traffic noise reaches an upper limit when traffic is saturated, and the noise energy contribution of the exit lane is far greater than that of the entrance lane.

Options for reducing noise from roads and railway lines

The fundamental noise generation mechanisms of road and rail vehicles are discussed with attention to noise abatement measures. Based on an evaluation of publicly available tire noise data and the European road traffic noise emission model CNOSSOS, it is shown that on the road side there is a significant noise reduction potential in the usage of low-noise tires. From a three months measurement campaign a noise model was derived to predict the maximal sound pressure level of heavy duty vehicles during a pass-by in 7.5m distance with the parameters vehicle speed and number of axles. With help of recently published information about external costs caused by heavy duty vehicles and the noise prediction tool, a model was developed to derive a money equivalent that can be used as a bonus/malus in a heavy duty vehicle fee. As a measure at the infrastructure, the installation of low-noise pavements is an effective, durable and economically attractive measure. Recent experiences with different technologies from all over the world are compiled and evaluated. On the rail side, an overview of the possible noise reduction strategies is given, followed by a discussion of the current policy and legislation in the EU and on the national level of different European countries.

Towards a model for electric vehicle noise emission in the European prediction method CNOSSOS-EU

The CNOSSOS-EU method is recommended in Europe for environmental noise prediction. In regards to road traffic, it includes vehicle noise emission models implicitly referring to internal combustion vehicles. The development of electrically driven vehicles calls for the future consideration of these vehicles in prediction models. On the basis of experimental data, the study reported in this paper proposes a noise emission model for extending CNOSSOS-EU to light electric vehicles. Correction terms to be applied to the propulsion noise component are determined. Investigations on a sample of tyres with good rolling resistance performance, which is a main tyre selection criterion on these vehicles, indicated that no correction is required for the rolling noise component. Differences between the noise emission from conventional vehicles and electric vehicles are discussed for several road surfaces. Owing to the limited vehicle sample as well as transitional statements, this new model for electric vehicles running at constant speed over 20km/h should be considered as a first step towards the definition of this vehicle technology in CNOSSOS-EU.

A road traffic noise pattern simulation model that includes distributions of vehicle sound power levels

Abstract Annoyance, sleep disturbance and other health effects of road traffic noise exposure may be related to both level and number of noise events caused by traffic, not just to energy equivalent measures of exposure. Dynamic traffic noise prediction models that include instantaneous vehicle noise emissions can be used to estimate either of these measures. However, current state-of-the-art vehicle noise emission models typically consider a single emission law for each vehicle category, whereas measurements show that the variation in noise emission between vehicles within the same category can be considerable. It is essential that the influence of vehicles that are producing significantly more (or less) noise than the average vehicle are taken into account in modeling in order to correctly predict the levels and frequency of occurrence of road traffic noise events, and in particular to calculate indicators that characterize these noise events. Here, an approach for predicting instantaneous sound levels caused by road traffic is presented, which takes into account measured distributions of sound power levels produced by individual vehicles. For the setting of a receiver adjacent to a dual-lane road carrying free flow traffic, the effect of this approach on estimated percentile levels and sound event indicators is investigated.

Inclusion of Noise in Environmental Assessment of Road Transportation

In life cycle assessment (LCA) of road transportation systems, limited attention is given to noise as an impact category. This paper presents a method in order to include the environmental effects of noise in the LCA of road transportation. Life cycle inventory is developed based on the IMAGINE road vehicle noise emission model. Life cycle impact assessment is based on cause-effect chain including fate, exposure, effect, and damage analysis. The health effects of road traffic noise are evaluated in terms of acute myocardial infarction, annoyance, and sleep disturbance. The corresponding health damages are quantified using disability adjusted life years (DALY). A case study evaluating the health effects of road transportation noise for the nine municipalities of Istanbul using the proposed method is also presented. It was shown that transportation noise has significant adverse health effects and therefore should be accounted for in the LCA of road transportation along with other environmental interventions.

English

Noise pollution and its influence on environment and life quality of human beings may be considered as a hot topic in scientific research. Since there are no sufficient studies on noise pollution in Tehran, this study was carried out to determine noise levels of pavement in Tehran City. SMM1 (The first standard of noise measurement method) model is one of the most common models used in calculating noise emission in Tehran City. Because factors which this model uses are close to Tehran traffic situation, in this study, SMM1 noise emission model has been modified by including pavement statement factor. In other words, the pavement age will affect noise emission in environment. Thus, a case-study is chosen and its pavement statement factor is added to SMM1 noise emission model. Equivalent noise level changes in different distances with sound noise. This effect is calculated and indicated in this paper. Another factor that could affect the sound level is traffic volume, which is also shown in this paper. In this study, it is concluded that when asphalt pavement is fresh and new, equivalent noise level is 2 (dB) less than when the pavement becomes old due to congestion of pavement and its decreasing void. The results showed that pavement noise should be mentioned among the major environmental problems, and studies aim at preventing it should have great priority.   Key words: Noise, traffic, pavement, pollution. &nbsp

Rapid Modeling Method for Road Traffic Noise Sources: A case study in Beijing

AbstractBased on the local road traffic conditions in Beijing, China, this contribution proposes a rapid modeling method for road traffic noise sources. Since establishing the standardized experiment fields are expensive, real roads are used to determine the road traffic noise emission model in the method. Due to the similarity in the urban structures in China and Japan, this paper uses the ASJ- 2013 model as a template and replaces its model parameters with the ones output by an optimization program which minimizes the sum of absolute errors between the predicted and the measured LAeq. Real road experiments are conducted to verify the effectiveness and feasibility of the modeling method. The mean error of the model deduced by the method and the ASJ-2013 model is respectively 0.4 dB and 2.6 dB, and the mean absolute error of the two models is respectively 1.1 dB and 2.6 dB. The results of the real road experiments show that the road traffic noise sources deduced by the method are more accurate to conduct local noise prediction than those of other models.

Road traffic noise mapping in Guangzhou using GIS and GPS

The primary objective of this study is to develop day and night road traffic noise maps for Guangzhou using Geographical Information Systems (GIS) and Global Positioning Systems (GPS). First, as speed-density relation is used to estimate the traffic volume from GPS data collected from floating cars. Meanwhile, the attributes of the roads and buildings are automatically exported from GIS. Second, a single vehicle noise emission model is combined with a noise propagation model to formulate a regional traffic noise calculation model that accounts for the traffic noise attenuation in an urban area. The algorithm is optimized by intelligently dividing the computational grids, filtering the traffic noise sources automatically and performing a quick index of the estimation objects. Finally, the day and night road traffic noise levels in Guangzhou are estimated to create two traffic noise maps. The accuracy of the developed algorithm is validated by conducting a traffic noise monitoring experiment in several districts of Guangzhou with different road types. The results show that the average error between the estimated and measured values is below 2.0dB.

Dynamic Simulation of Traffic Noise by Applying Ray Tracing Method based on Indoor Space Partitioning

This study presents a revised 3D ray tracing method by combining it with indoor space partitioning. This method divides an entire indoor space into limited convex polyhedron subspaces, and thus reduces the number of surfaces intersected with rays, and omits the validity test of the collision point on the reflecting surfaces. Combining it with a microscopic traffic simulation tool and a vehicle noise emission model, and taking the influence of diffraction into account, the method can be utilized in simulating dynamically the process of traffic noise diffusing inside the building through windows. Meanwhile, this study selects two different types of indoor architectural layouts in order to demonstrate the efficiency of this method, the influence of diffraction and of the state of windows, and the differences in indoor noise on different floors. A comparison study on before-and-after indoor space partitioning shows that the method is efficient.