Rail Noise Research Articles

Parametric Study on the Effect of Rail Dampers on Track Decay Rate

Track decay rate (TDR), meaning the rate of attenuation of bending waves through the rail, is the most important indicator of a track’s dynamic characteristic impacting the rail noise emission. TDR depends on various parameters related to the construction of the track, and it can be increased using rail dampers. These are mechanical devices working on the principle of dynamic absorbers and are attached to the rail. This paper addresses the track with light rails needing improvements to reduce the rail noise emission using a particular rail damper with a mixed damping system (rubber–oil). The bending waves that propagate through the rail, the frequency response function of the rail, and TDR are investigated considering different scenarios regarding the parameters of the track: soft/stiff rail pad, tampered/settled ballast, and sleeper bay. To this end, an analytic model of the track featuring rail dampers consisting of an infinite Timoshenko beam with discrete attached oscillators is used. Numerical results show the possibility to increase TDR of railway track with light rails for both soft/stiff rail pads from 4 to 500 Hz up to 1250–1600 Hz using rail dampers with a mixed damping system.

Population-Level Exposure to PM2.5, NO2, Greenness (NDVI), Accessible Greenspace, Road Noise, and Rail Noise in England

Air pollution, greenspace and noise are interrelated environmental factors with the potential to influence human health outcomes. Research has measured these exposures in diverse ways across the globe, but no study has yet performed a country-wide analysis of air pollution, greenspace, and noise in England. This study examined cross-sectional PM2.5, NO2, greenness, accessible greenspace, road noise, and rail noise exposure data at all residential postcodes in England (n = 1,227,681). Restricted cubic spline models were fitted between each environmental exposure and a measure of socioeconomic status, the Index of Multiple Deprivation (IMD) rank. Population-weighted exposures by IMD deciles, urbanicity, and region were subsequently estimated. Restricted cubic spline models were also fitted between greenness and each other environmental exposure in the study. The results show some evidence of inequalities in exposure to air pollutants, greenspace, and noise across England. Notably, there is a socioeconomic gradient in greenness, NO2, PM2.5, and road noise in London. In addition, NO2, PM2.5, and road noise exposure decrease as greenness increases in urban areas. Concerningly, almost all air pollution estimates in our study exceed international health guidelines. Further research is needed to elucidate the socioeconomic patterns and health impacts of air pollution, greenspace, and noise over time.

Factors influencing noise annoyance across various transportation modes: lessons from the citizen science project "De Oorzaak"

The citizen science initiative "De Oorzaak" invited adult residents of Flanders (Belgium) to fill out the "Large Sound Survey", gathering over 8,000 answers in a month. This comprehensive 51-question survey evaluated annoyance levels across various transportation modes, drawing on established questionnaires like the Epworth Sleepiness Scale, Weinstein Noise Sensitivity Scale and Written Environmental Survey (SLO), organized by the Flemish government. It also aided in selecting participants for subsequent project phases. Comparing LSS results to the latest SLO report revealed a significant self-selection bias, with 33.3% highly annoyed by noise compared to 11.6% from the SLO. A profile could be drawn for the most annoyed participants: noise-sensitive individuals living in apartments or studios, adults (26-61 years old), and residing in densely populated areas. Regarding transportation noise, passenger cars and trucks lead as the most annoying sources, with %HA of 24.5% and 23.5%, respectively, followed by motorcycles and alike (%HA =21.5%). Conversely, rail and air traffic annoyance are considerably lower. Correlations were drawn between the several noise annoyance sources and individuals' characteristics. Overall, population density, age, fatigue level and quality of life are the personal aspects that correlate more consistently with road, rail, and air traffic noise annoyance.

The effect of combined exposure to noise and vibrations from rail traffic on sleep: results from the follow-up study "Living in the vicinity of the railway"

As a result of policy aims to improve accessibility and achieve climate targets, an increase in rail traffic is foreseen for a while. It is therefore expected that in the future more problems will arise due to the vibrations and noise that trains produce. It is demonstrated that most problems are caused by freight trains, predominantly tracking during the night, hence affecting sleep. Research has shown that both noise and vibrations from rail traffic can affect sleep; evidence on the impact of combined exposures is scarce. To investigate the effect of combined exposure to noise and vibrations from rail traffic on self-reported sleep disturbance, we used data from a survey aimed to investigate people's reactions on railway vibrations. In 2021, 17,189 people of 16 years and older, living within 300 meters of a railway track in The Netherlands were invited to fill in a questionnaire. Exposure to vibration and noise levels from rail traffic during the night were modelled and linked to the addresses of the 5,611 (33%) participants. We used logistic regression models to test the associations between rail traffic vibration or noise exposure and sleep disturbance for different noise and vibration exposure groups. This paper presents preliminary results.

Evaluation of railway noise calculation models using CNOSSOS-EU considering the effect of rail roughness

Railway noise assessment is an important tool in decision-making for urban planning, investment in transportation infrastructure and implementation of noise reduction strategies. Currently, the procedure is based on CNOSSOS-EU (Common Noise Assessment Methods in Europe), which was developed in accordance with European Directive 2002/49/EC. This method takes into account a variety of factors impacting rail noise levels, such as vehicle characteristics and track features. The purpose of this study was to investigate the influence of rail roughness on generated railway noise and to evaluate the accuracy of calculation models using CNOSSOS-EU. The study involved in-situ railway noise measurements at three different locations near the city of Zagreb, Croatia, and measuring rail roughness at each location. In order to eliminate the influence of other factors, the rail track structures at the measurement locations were similar, and an identical train configuration was used for the study. Finally, a comparison was made between calculation models based on default roughness values and models including values obtained from in-situ measurements. This approach enabled an assessment of the variations in CNOSSOS-EU calculation models taking into account actual in-situ rail roughness measurements.

An analytical model to calculate the forced vertical vibrations of two rails subjected to the dynamic loads of ballasted railway track

The railway track consists of two rails which are solicited the loads from passing trains. Due to the dynamic nature of these loads, the total forces applied to each rail are unequal and asymmetric. However, analytical models that simplify the track as a single beam cannot accurately describe the track responses. In this paper, we calculate the forced vertical vibration of a ballasted railway track subjected to dynamic loading with dual rails. Each rail is modelled as a uniform Euler–Bernoulli beam of infinite length, positioned on a system of periodic and identical supports. The forced vibration of the rail is determined using Floquet’s theorem. Additionally, a model of a beam on a continuous foundation is employed to describe the dynamic behaviour of each support. In the frequency domain, each support is represented as a spring with an equivalent stiffness. By combining these two developed models, we analytically obtain the forced vibrations of two rails in the frequency domain. In the symmetric configuration, our results show a similarity of the rail responses with an existing model, particularly at the pin-pin resonance. The differing peak resonances at low-band frequencies are attributed to the different types of support. Subsequently, we apply this new model to investigate the forced vibrations of two rails in a non-symmetric configuration. The numerical tool visually illustrates the influence of load positions on rail responses and reaction forces in the time domain. This analytical model proves valuable for studying the rail noise and vibration of ballasted railway tracks.

Rail noise comparison of FTA methodology with CadnaA modeling at Bronx development site

For environmental studies, identifying road and rail noise is important in projecting potential impacts from increased operations and also in identifying the window/wall attenuation needed to reduce outdoor to indoor noise levels. The Federal Transit Administration's (FTA) transit noise and vibration impact assessment procedures provide spreadsheets for estimating noise levels at specific receptor points. However, computer models such as SoundPLAN and CadnaA are also available. Because these computer models have complex input requirements and account for local terrain, they are rarely used for large corridor studies, but they are well suited to smaller sites. This study compares the FTA procedures with CadnaA modeling at a development site in the Bronx, NY, that is bounded by multiple rail lines and is proximate to a major highway. Discussion of results presents the advantages and disadvantages of each approach and identifies the conditions under which each approach is most appropriate.

Diurnal rail noise measurement, analysis, and evaluation of associated health impacts on residents living in the proximity of rail track area.

In India, railway is the major transportation mode for carrying goods and people. The tracks for the movement of the rail were initially constructed in the city for the pre-eminence and expediency of the vantage of the people. Rapid modernization and increasing population in the city crammed the area around the railway tracks. Moving rail on the tracks passing through the city is not compatible, which is creating problems for the nearby residents. In the urban and suburban regions, the railway noise has become a major problem. This study was conducted to examine the perception of the physiological and psychological effects of railway noise in the nearby areas of railway stations in Delhi, India. For this purpose, 10 sites near the railway station were selected for the study. To assess the impact of railway noise pollution on the health of humans, a questionnaire survey was conducted. The data of 344 individuals were collected through the questionnaire survey and analyzed to get the perception towards railway noise. Noise level was monitored by a Sound Level Meter (SLM) and the equivalent noise level (Leq) in dB(A) was used to compute the noise pollution in three shifts, i.e., morning, noon, and evening time. Results showed that 57.65% of female and 86.11% of male respondents in the survey reported the disturbance due to railway noise. The level of noise pollution was found higher in the evening time as compared to the noon and morningperiod, which exceeds the limit set by the Central Pollution Control Board (CPCB) at all the monitored locations. Findings of the study show that the primary cause of the health problems is railroad noise, which is negatively impacting the health of the residents, who are living in the proximity of the rail track region. The perception survey reported that headache, sleep disturbance, irritation, and stress are common health issues among the locals residing around the railway track proximity in Delhi.

An acoustic black hole absorber for rail vibration suppression: Simulation and full-scale experiment

Rail vibration suppression is important to reduce rail noise radiation and ensure vehicle ride comfort. Conventional rail absorbers have been demonstrated to be effective for suppressing rail vibration; however, their effective frequency bandwidth remains limited. Herein, for the first time, we propose a broadband rail absorber, called an acoustic black hole (ABH) absorber, for rail vibration suppression. This novel ABH absorber consists of a variable-thickness cantilever beam with a power-law profile covered by a viscoelastic damping layer. A 3D finite element model of a 12.35-m long full-scale rail with ABH absorber was developed to investigate its performance. The effects of the thickness and loss factor of the damping layer on the rail vibration-suppression performance were investigated via a parametric study. In addition, a full-scale experiment was conducted on an actual rail to investigate the vibration-suppression performance of the ABH absorber. Both numerical and experimental results indicate that the ABH absorber can significantly reduce rail vibration at tuning frequencies and provide broadband vibration suppression within the non-resonance range. The experimental results demonstrate that the ABH absorber increases the track decay rate at frequencies above 100 Hz; in addition, a maximum track decay rate of 5.85 dB/m was achieved. This study may help to develop next-generation rail absorbers, which is important for developing sustainable and eco-friendly urban rail transit.

Autonomous monitoring of traffic, rail, and industrial noise using acoustic vector beamformers based on 3D MEMS accelerometers

Fully unattended acoustic monitoring has been hindered by the need to automatically discriminate specific sources from overall noise levels at a measurement location, even if that noise is very close in proximity. Existing 3D microphone-based acoustic intensity or camera solutions are unwieldy and expensive for real-time deployments. A new system has been developed for autonomously monitoring noise levels in transportation and industrial settings, managed within an IoT network. Each measurement node has one or two Acoustic Real-time Event Sensors (ARES) and a beamformer algorithm using 3D MEMS accelerometer-enabled Acoustic Vector Sensing (AVS) technology. Beamforming enables the system to focus on specific areas or sources of noise, delivering more precise monitoring and identification of noise sources, useful for noise reduction efforts and compliance with noise regulations. Deploying 3D accelerometers, rather than microphone arrays, in the beamformer provides improved system performance and environmental protection, with reductions in array size, cost, and unwanted sidelobes. ARES beamformer array apertures occupy just 1 cm for a single sensor, or 13 cm for 2 sensors, and can distinguish sources in frequencies from 50 to 2 kHz with excellent angular resolution, in real-time. Example traffic and rail noise applications are presented.

Exposure response relationships of annoyance and vibration and noise from passenger and freight trains in Sweden - results from the EpiVib study

Rail traffic is increasing in Europe, still little is known about the health effects of rail traffic vibration and noise for people living close to the railways. The aim of this study was to investigate the associations between vibration respective noise from rail traffic and persons highly annoyed by vibration. The study population (N=7280) was randomly selected from residents (18-80 years) living within 1km of a trafficked railway in Sweden. Vibration and noise levels were modelled for each participant's home address. Result show exposure-response relationships between levels of vibration and noise and annoyance for all types of trains, especially freight trains. The association between maximum vibration velocity at building foundation (Vmax) and high annoyance by vibration from freight trains, accounting for potential confounders was (OR=1.37 per 0.1mm/s Vmax; 95% CI 1.32-1.42). Similarly, for railway noise (LAFmax) (OR=1.19 per 1 dB LAFmax; 95% CI 1.17-1.21). Analysis suggests an interaction between noise and vibration, where the effect of noise level on the probability of vibration annoyance by vibration differs with vibration exposure and vice versa. These findings may have implications for environmental health and transportation planning. Keywords: rail traffic vibration, railway noise, annoyance by vibration, freight trains

A rail corrugation index to characterize noise impacts and grinding effectiveness on rail transit systems

Despite general agreement that rail corrugation generates unwanted noise, there is a need to quantify the relationship between rail corrugation and noise and to leverage this relationship within preventive rail grinding programs. This paper develops a novel rail corrugation index (RCI) and demonstrates the suitability of that index to characterize the relationship between corrugation and noise, to assess grind effectiveness, and to predict noise as a function of rail corrugation. Using a time-series data set collected at a North American rail transit property, the proposed RCI illustrated corrugation growth as a function of accumulated tonnage and an expected reduction of corrugation after grinding. The RCI also correlated well with corresponding wayside noise observations. The evident response behavior and the relationship between rail corrugation and wayside noise gave rise to the assessment of grind effectiveness using the RCI. Further, a modelling effort demonstrated that noise can be predicted using the RCI calculated from only one rail (left or right) on a tangent section. This result suggests that there may also be an opportunity to predict corrugation using noise data, thus limiting the need for track downtime required to measure corrugation.

Estimates of population highly annoyed from transportation noise in the United States: An unfair share of the burden by race and ethnicity

Transportation is one of the most pervasive sources of community noise. In this study, we used a spatially-resolved model of transportation-related noise with established transportation noise exposure-response functions to estimate the population highly annoyed (HA) due to aviation, road, and railway traffic sources in the United States. Additionally, we employed the use of the Fair Share Ratio to assess race/ethnicity disparities in traffic noise exposures. Our results estimate that in 2020, 7.8 million (2.4%) individuals were highly annoyed by aviation noise, while 5.2 million (1.6%) and 7.9 million (2.4%) people were highly annoyed by rail and roadway noise, respectively, across the US. The Fair Share Ratio revealed that Non-Hispanic Asian, Black, NHPI, and Other, and Hispanic populations were disproportionally highly annoyed by transportation noise nationwide. Notably, Hispanic populations experienced the greatest share of high annoyance from aviation noise (1.69 times their population share). Non-Hispanic Black populations experienced the greatest share of high annoyance from railway noise (1.48 times their population share). Non-Hispanic Asian populations experienced the greatest share of high annoyance from roadway noise (1.51 times their population share). Analyses at the state and Urban Area levels further highlighted varying disparities in transportation noise exposure and annoyance across different race ethnicity groups, but still suggested that Non-Hispanic White populations were less annoyed by all sources of transportation noise compared to non-White populations. Our findings indicate widespread presence of transportation noise annoyance across the US and emphasize the need for targeted source-specific noise mitigation strategies and policies to minimize the disproportionate impact of transportation noise in the US.

Rail noise across three states in Australia—Operational noise assessment on Inland Rail

Inland Rail Project is a proposed 1700 km freight rail line connecting Melbourne and Brisbane via three States in Australia–Victoria, New South Wales, and Queensland. Operational rail noise assessment is undertaken differently across these States in Australia. The assessment generally considers the existing and future noise exposure across day and night, along with single pass-by maximum levels. However, the assessment durations and statistical means of assessing single events differ across the States. The key acoustic criteria relevant to operational noise assessments and how they differ across the project footprint are discussed in this paper. Specifically, the effect of application of various criteria in the project context are discussed, along with statistical analysis of train pass-by noise data sets. A Monte-Carlo based methodology is proposed for estimating Single Event Maximum, a criterion for assessing single rail-noise events in Queensland. The methodology is discussed in the context of field data and greenfield scenarios where the method may be beneficial for acoustic consultants. The effects of inclusion of noise sources such as train horns and crossing bells are also briefly discussed. Finally, a proposed methodology for a consistent assessment of rail noise on such nationally spread projects is discussed.

Exploring Noise Pollution, Causes, Effects, and Mitigation Strategies: A Review Paper

Noise pollution, often regarded as a silent menace amidst the clamor of more conspicuous environmental concerns, is a pervasive and escalating issue with profound implications for humanity and the natural world. This comprehensive review paper delves into the multifaceted realm of noise pollution, encompassing its diverse causes, far-reaching effects, and the array of strategies deployed to mitigate its adverse consequences. Within this paper, we embark on an exploration that begins by scrutinizing the intricate tapestry of noise pollution's origins. We dissect the urban sprawl and infrastructure development that spawns construction-related tumult, the transportation networks that propagate incessant road, air, and rail noise, and the industrial activities that generate relentless auditory dissonance. These sources collectively converge to create a symphony of cacophony that increasingly defines modern existence. The effects of noise pollution extend beyond mere annoyance. We scrutinize its deleterious impact on human health, from sleep disturbances and cardiovascular diseases to cognitive impairments and stress-related disorders. We unravel the psychological ramifications, including reduced cognitive performance, annoyance, and social isolation. Furthermore, we delve into its insidious intrusion into the natural world, disrupting wildlife behavior, habitats, and reproductive success. Noise pollution also exerts socio-economic repercussions, diminishing property values and impairing learning environments. Mitigation strategies emerge as our beacon of hope. Regulatory measures, noise barriers, urban planning, technological innovations, public awareness campaigns, and international cooperation collectively form our arsenal in the battle against noise pollution. By recognizing noise pollution as an environmental challenge with profound ramifications and by collectively deploying these strategies, we aspire to cultivate a quieter, healthier, and more harmonious world for present and future generations, echoing a harmonious symphony of coexistence amidst the urban bustle.

A Methodology for Predicting Acoustic Noise From Singing Capacitors in Mobile Devices

Multilayer ceramic capacitors (MLCCs) connected to a power distribution network (PDN) can create acoustic noise through a combination of the power rail noise at the MLCCs and the piezoelectric effect of the capacitor's ceramic material. The deformation of the MLCCs brought on by power supply noise creates vibrations which cause the printed circuit board (PCB) to vibrate and generate the audible acoustic noise. In the following paper, a simulation methodology is presented to analyze the acoustic noise created by MLCCs on a PCB. A simulation model for the PCB vibration modal response is built and the modal superposition method is used to analyze the harmonic response of the PCB excited by the capacitor. By multiplying the measured power noise spectrum on the MLCC with the simulated deformation of the PCB found from the harmonic response analysis, the total response is obtained. Simulated results show a good correlation with the measured acoustic noise. The proposed method shows promise for analyzing and predicting the acoustic noise from singing capacitors.

Research on elevated orbit noise propagation based on AI algorithm and propagation path analysis

With the rapid development of high-speed railway, noise reduction is becoming more and more important. At the same time, the study of elevated rail noise is also very important for the engineering field. The noise reduction of elevated rail noise is a part of the engineering construction, which is conducive to the economic development and the improvement of people’s life, and the reduction of noise has an impact on residents’ life. This article aims to investigate the analysis of the vibration and noise transmission path of the elevated railway. An optimized transmission path analysis method, which is based on the artificial intelligence algorithms, is used to optimize the path analysis, so as to trace the source of the noise and analyze the noise reduction. This method performs well in the analysis of vibration and noise of elevated railways. After this optimization, the contribution degree and frequency response function in the path analysis have better analysis performance. Through the actual measurement and analysis of the noise of the elevated railway, it can be proved that the traditional path method can better analyze the noise source. The environmental noise caused by high-speed trains passing bridges easily exceeds the acoustic environmental standards. After noise reduction, it can be reduced by about 5–10 dB.

Assessing rail-based environmental noise exposure using CNOSSOS-EU

Since December 2018 a harmonised approach for the assessment of transportation noise, known as CNOSSOS-EU, became obligatory for EU Member States in the calculation of strategic noise mapping. This paper provides an assessment of rail-based environmental noise in Ireland via a comparative analysis of acoustic modelling for rail sources in the Irish context by comparing the CNOSSOS-EU method and the previously utilised interim method RMR-1996 with field measurements. The paper also presents comparative estimates of population exposure calculated using CNOSSOS-EU and RMR-1996. It was found that the results generated by the CNOSSOS-EU model were closer to field measurements when compared to the RMR-1996 model. Noise modelling also indicated that populations estimated to be exposed to levels of railway noise > 55 dB(A) generated by the national rail fleet were higher using CNOSSOS-EU (i.e. 91,692 more persons) relative to the RMR-1996 method. Rail noise generated by the Luas tram rail network generated marginally less population exposure for railway noise > 55 dB(A) (i.e. 2,905 less persons) relative to RMR-1996. As such, the paper contributes to the assessment of the new CNOSSOS-EU model for rail in the EU and addresses the relative lack of research focusing on rail modelling and population exposure estimation under the END. This paper contributes to a better understanding of the extent that populations are exposed to railway noise using CNOSSOS-EU across Europe.

Traffic-Related High Sleep Disturbance in the LIFE-Adult Cohort Study: A Comparison to the WHO Exposure-Response-Curves

Sleep is negatively affected by environmental noise. In the present study, we investigated self-reported high sleep disturbances (being "highly sleep disturbed"-HSD) from road traffic (primary and secondary road networks), rail (train and tram) and air traffic noise in the LIFE-Adult cohort study in Leipzig, Germany. For this, we used exposure data from 2012 and outcome data of Wave 2 (collected during 2018-2021). HSD was determined and defined according to internationally standardized norms. The highest risk for transportation noise-related HSD was found for aircraft noise: the odds ratio (OR) was 19.66, 95% CI 11.47-33.71 per 10 dB increase in Lnight. For road and rail traffic, similar risk estimates were observed (road: OR = 2.86, 95% CI 1.92-4.28; rail: OR = 2.67, 95% CI 2.03-3.50 per 10 dB Lnight increase). Further, we compared our exposure-risk curves with the curves of the WHO environmental noise guidelines for the European region. The proportion of individuals with HSD for a given noise level was lower for rail traffic but higher for aircraft noise in the LIFE study than in the WHO curves. For road traffic, curves are not directly comparable because we also included the secondary road network. The results of our study add to the body of evidence for increased health risks by traffic noise. Moreover, the results indicate that aircraft noise is particularly harmful to health. We recommend reconsidering threshold values for nightly aircraft exposure.

Assessing cognitive effects of transportation noise on office workers with physiology and task performance

Noise typically present in offices can negatively impact workers’ mental workload and task performance. This study investigated how transportation noise in open offices when windows are open can influence workers’ task performance, physiology (brain activity, heart rate variability, and skin resistance), and subjective ratings, as previous literature works often show inconclusive results or use unrealistic, simulated acoustic conditions. Subjects were given two cognitive tasks, mental arithmetic and digit span, while wearing three physiological measurement devices: an electroencephalography (EEG) headset, electrocardiogram (ECG) sensors, and electrodermal activity (EDA) sensors. After a baseline measurement, both the physiological markers and task performance were recorded for a training session, a quiet condition, and two transportation noise conditions with sound pressure levels of 50 and 70 dBA, respectively. Recorded rail noise was auralized in an anechoic chamber with a 32-loudspeaker array to simulate transportation noise heard when sitting in an office with an open window. Subjective rating questions regarding the acoustic environment and self-perception of mental workload and performance were administered after each acoustic condition. The effects of different acoustic conditions on cognitive task performance, physiological data, and subjective ratings were analyzed with a repeated measures MANOVA. Findings from this study will be presented.