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Curve squeal is a highly disturbing tonal noise produced by railway vehicles on tight curves, primarily attributed to lateral sliding at the wheel–rail interface. An essential step to estimate curve squeal noise levels is to determine the nonlinear self-sustained vibrations, for which time integration is a commonly used method. However, although it is known that the initial conditions affect the solutions obtained with time integration, their impact on the limit cycles is often overlooked. This study investigates this aspect for a curve squeal model based on falling friction and a modal reduction of the wheel and provides some insights on the mode competition phenomena and the nature of the final limit cycles obtained. The paper first details the curve squeal model, stability analysis, as well as the initial condition derivation, and then discusses the time integration and limit cycle results in both time and frequency domains. The results reveal two primary families of limit cycles that can be obtained for both types of initial conditions. The cases where stationary vibrations result in a quasi-periodic regime converge to a unique limit cycle which displays three fundamental frequencies corresponding to specific wheel modes, plus harmonic interactions among them. [ABSTRACT FROM AUTHOR]

Rapid urbanization has led to unplanned settlements near railway lines, exposing residents to continuous noise pollution with potential adverse effects on health. This study focuses on the environmental monitoring and assessment of railway noise pollution in urban areas and its impact on human health and daily activities. Noise levels were quantified across different residential zones using precise sound level meters, and a detailed human perception survey was conducted to assess the relationship between noise exposure, annoyance, and health disturbances. By employing structural equation modelling (SEM), the study integrates environmental monitoring data with epidemiological and health data to assess the risk of noise pollution to individuals residing near railway lines. The results indicate that railway noise frequently exceeds regulatory limits, with passenger trains contributing more significantly to pollution than freight trains. The findings also reveal that noise exposure is a significant predictor of annoyance and health effects, with proximity to the railway line being a critical factor. The study emphasizes the need for improved noise monitoring systems and risk assessment strategies in transportation planning to mitigate health risks. These insights contribute to the development of sustainable noise management practices and the design of more efficient monitoring systems, enhancing the understanding of pollution risks at both individual and population levels. [ABSTRACT FROM AUTHOR]

Abstract This study investigates the impact of the noise radiated from airplanes, urban rail transit, high-speed railways, and urban roads on residents near an airport. The results showed that all respondents near the airport were highly annoyed with airplane noise, and some remain annoyed with the noise from the urban rail transit and high-speed railway connecting to the airport. The most detrimental aspect of transportation noise was sleeping disturbance. Transportation noise from 19:00 to 24:00 primarily caused the annoyance of surrounding residents. Airplane noise is the largest source of sound pollution in residences in the region adjacent to the elevated urban rail transit and airport. The insertion loss of vertical sound barrier with a height of 2.4 m at the points 25 m away from the track centerline is 6.9–8.6 dB, but the sound pressure level below 40 Hz is amplified owing to the structure-borne noise radiating from the barrier itself. The presence of sound barriers can reduce the high annoyance level from 24 to 8.2%.

This study investigates the impact of the noise radiated from airplanes, urban rail transit, high-speed railways, and urban roads on residents near an airport. The results showed that all respondents near the airport were highly annoyed with airplane noise, and some remain annoyed with the noise from the urban rail transit and high-speed railway connecting to the airport. The most detrimental aspect of transportation noise was sleeping disturbance. Transportation noise from 19:00 to 24:00 primarily caused the annoyance of surrounding residents. Airplane noise is the largest source of sound pollution in residences in the region adjacent to the elevated urban rail transit and airport. The insertion loss of vertical sound barrier with a height of 2.4 m at the points 25 m away from the track centerline is 6.9–8.6 dB, but the sound pressure level below 40 Hz is amplified owing to the structure-borne noise radiating from the barrier itself. The presence of sound barriers can reduce the high annoyance level from 24 to 8.2%. [ABSTRACT FROM AUTHOR]

In this article, we consider the numerical prediction of the noise emission from a wheelset in laboratory conditions. We focus on the fluid–structure interaction leading to sound emission in the fluid domain by analyzing three different methods to account for acoustic sources. These are a discretized baffled piston using the discrete calculation method (DCM), a closed cylindrical volume using the boundary element method (BEM) and radiating elastic disks in a cubic enclosure solved with the finite element method (FEM). We provide the validation of the baffled piston and the BEM using measurements of the noise emission of a railway wheel by considering ground reflections in the numerical models. Selected space-resolved waveforms are compared with experimental results as well as with a fluid–structure interaction finite element model. The computational advantage of a discretized disk mounted on a baffle and BEM compared to FEM is highlighted, and the baffled pistons limitations caused by a lack of edge radiation effects are investigated. [ABSTRACT FROM AUTHOR]

Abstract Background Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort. Methods During 15 years of follow-up (2001–2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined). Results HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively). Conclusions This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Abstract In this article, we consider the numerical prediction of the noise emission from a wheelset in laboratory conditions. We focus on the fluid–structure interaction leading to sound emission in the fluid domain by analyzing three different methods to account for acoustic sources. These are a discretized baffled piston using the discrete calculation method (DCM), a closed cylindrical volume using the boundary element method (BEM) and radiating elastic disks in a cubic enclosure solved with the finite element method (FEM). We provide the validation of the baffled piston and the BEM using measurements of the noise emission of a railway wheel by considering ground reflections in the numerical models. Selected space-resolved waveforms are compared with experimental results as well as with a fluid–structure interaction finite element model. The computational advantage of a discretized disk mounted on a baffle and BEM compared to FEM is highlighted, and the baffled pistons limitations caused by a lack of edge radiation effects are investigated.

Curve squeal is a highly disturbing tonal noise produced by railway vehicles on tight curves, primarily attributed to lateral sliding at the wheel–rail interface. An essential step to estimate curve squeal noise levels is to determine the nonlinear self-sustained vibrations, for which time integration is a commonly used method. However, although it is known that the initial conditions affect the solutions obtained with time integration, their impact on the limit cycles is often overlooked. This study investigates this aspect for a curve squeal model based on falling friction and a modal reduction of the wheel and provides some insights on the mode competition phenomena and the nature of the final limit cycles obtained. The paper first details the curve squeal model, stability analysis, as well as the initial condition derivation, and then discusses the time integration and limit cycle results in both time and frequency domains. The results reveal two primary families of limit cycles that can be obtained for both types of initial conditions. The cases where stationary vibrations result in a quasi-periodic regime converge to a unique limit cycle which displays three fundamental frequencies corresponding to specific wheel modes, plus harmonic interactions among them.

Background: Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort. Methods: During 15 years of follow-up (2001–2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined). Results: HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively). Conclusions: This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion. [ABSTRACT FROM AUTHOR]

Railway noise, stemming from various sources such as wheel/rail interactions, locomotives, and track machinery, affects both human health and the environment. This study explores the application of machine learning (ML) models to quantify tram noise at sharp curves, considering variables such as weather conditions, train speed, crowd levels, and running directions. Data collection is carried out on a tram line in Birmingham, using an iPhone 11 to record acoustic data at a sample rate of 48 kHz. The noise is categorized into impact noise, rolling noise, flanging noise, and squeal noise based on frequency and power spectrum characteristics. Random Forests (RF) and Extreme Gradient Boosting (XGBoost) are employed to predict the root mean square (R.M.S) values of each type of noise. Results indicate that XGBoost outperformed RF with an R2 up to 0.96 during k-fold cross-validation. This model provides a robust tool for railway operators to optimize noise control measures and contributes to improved compliance with environmental regulations and a better quality of life for communities near rail tracks.

The growth in the utilization and development of rail transport within urban networks is crucial for transitioning towards a more sustainable form of mobility. However, challenges related to discomfort and noise pollution arising from rail traffic must be addressed and mitigated to foster a harmonious coexistence between residents and trains. This study focuses on analyzing an experimental campaign conducted on the surface metropolitan network of Porto to study and identify the frequency content and pressure levels associated with light rail traffic. The presented experimental campaign holds significant relevance as it comprises various and distinct circulation conditions within the railway network, enabling a comprehensive characterization of railway noise. The collected data indicates a noticeable increase in sound pressure levels as the speed of circulation rises, particularly emphasizing the 1/3 octave band centered around 1000 Hz. The choice of tracks with components having a limited capacity for absorbing acoustic energy leads to a significant rise in noise levels compared to track solutions with elements exhibiting excellent acoustic energy absorption. Furthermore, the study highlights a substantial increase in noise levels (10 dBA) associated with small radius curves, even at low speeds. These findings underscore the importance of considering the track characteristics and geometric features in noise assessment within rail networks. Therefore, the insights gained from this experimental campaign contribute significantly to the understanding and comprehensive characterization of railway noise under diverse circulation conditions within the railway network. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Engineering & Management Sciences (2498-700X) / Műszaki és Menedzsment Tudományi Közlemények is the property of University of Debrecen and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The proportion of high speed railway vehicles in the rolling stock of national carriers providing public transport services is constantly increasing. Currently, Alstom vehicles run at the highest speed on railway lines in Poland. The paper attempts to identify the acoustic signature of high speed railway vehicles. There are many works and studies aimed at identifying or defining the acoustic signature of high speed railway vehicles. However, the authors of these works carried out their research in a rather narrow scope, i.e. the measurement cross-section had only 1 or 2 measure-ment points with one microphone at each point. As part of the conducted experimental research, the location of testing grounds was determined, the measurement apparatus was selected and the methodology for carrying out measurements including the assessment of noise emission on curve and straight line were specified for electric multiple units. The object of the tests were railway vehicles of Alstom company, type ETR610, series ED250, the so-called Pendolino, moving on a selected measuring route without stops at a speed of 200 km/h. Measurements were carried out on the railway line no. 4 Grodzisk Mazowiecki – Zawiercie, section Grodzisk Mazowiecki - Idzikowice at kilometre 18+600 (curve) and 21+300 (straight section). When measuring the acoustic signals with a microphone array (4x2), 8 meas-urement microphones operating in the audible range were used. The microphones were placed at a distance of 5 m, 10 m, 20 m and 40 m from the track centre, at a height of 4 m (from the rail head) and at the rail head (approx. 0.8 m from the ground surface). In addition, an acoustic camera with 112 directional microphones was used to locate the main noise sources, which was located at a distance of approximately 20 m from the track centreline. The identification of the main noise sources for high speed railway vehicles, basig on actual acoustic measurements, made it possible to isolate the dominant noise sources, as well as to find out the amplitude-frequency characteristics in the range from 20 Hz to 20 kHz, divided into one third octave bands.

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Background: Noise pollution from transportation is one of the leading contributors to the environmental disease burden in Europe. We provide a novel assessment of spatial variations of these health impacts within a country, using England as an example. Methods: We estimated the burden of annoyance (highly annoyed), sleep disturbance (highly sleep disturbed), ischemic heart disease (IHD), stroke, and diabetes attributable to long-term transportation noise exposures in England for the adult population in 2018 down to local authority level (average adult population: 136,000). To derive estimates, we combined literature-informed exposure-response relationships, with population data on noise exposures, disease, and mortalities. Long-term average noise exposures from road, rail and aircraft were sourced from strategic noise mapping, with a lower exposure threshold of 50 dB (decibels) Lden and Lnight. Results: 40 %, 4.5 % and 4.8 % of adults in England were exposed to road, rail, and aircraft noise exceeding 50 dB Lden. We estimated close to a hundred thousand (∼97,000) disability adjusted life years (DALY) lost due to road-traffic, ∼13,000 from railway, and ∼ 17,000 from aircraft noise. This excludes some noise-outcome pairs as there were too few studies available to provide robust exposure–response estimates. Annoyance and sleep disturbance accounted for the majority of the DALYs, followed by strokes, IHD, and diabetes. London, the South East, and North West regions had the greatest number of road-traffic DALYs lost, while 63 % of all aircraft noise DALYs were found in London. The strategic noise mapping did not include all roads, which may still have significant traffic flows. In sensitivity analyses using modelled noise from all roads in London, the DALYs were 1.1x to 2.2x higher. Conclusion: Transportation noise exposures contribute to a significant and unequal environmental disease burden in England. Omitting minor roads from the noise exposure modelling leads to underestimation of the disease burden.

Background: Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence. Methods: Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution. Results: A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th–95th percentile) 5-year residential road traffic noise was 54.8 (40.0–67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2–65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99–1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96–1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using

Urban environment noise is a complex mixture of transportation, industrial, household, and recreational noise, which is identified as an emerging environmental threat. Present study monitors and evaluates a noise pollution hotspot: a railway level crossing, where several activities related to transportation noise were involved. Train honking, train movement, road vehicles, and pedestrians contribute to the noise level at a railway level crossing. Train horns are generally performed as train approach railway level crossings and they are mandatorily used to alert road users. However, the train horns are regarded as nuisance to the nearby residents. A detailed evaluation of train horn effectiveness is very much essential in the current contemporary environment. Thus, the main objective of this study is to measure noise levels emanating from train horns at a level crossing with due consideration to train types and climatic conditions. A comprehensive noise monitoring survey was conducted at an access-controlled level crossing. Furthermore, an artificial neural network (ANN)-based railway noise prediction model was developed to forecast maximum ( L max ) and equivalent (Leq) noise levels. Results revealed that train horn produced impulsive sound signals which fall under high frequency one-third octave bands causing severe irritation to trackside inhabitants. The proposed ANN models produced accurate results for L max and Leq noise levels and this model is identified as a vital tool for railway noise abatement. The results from this study are helpful to the urban planning and development authorities to implement strategic laws and policies to eradicate the urban environment noise. [ABSTRACT FROM AUTHOR]

[Display omitted] • Effects of railway noises on sleep indicators and mental health were investigated. • Field study data was used to construct a health risk prediction model. • Railway noise reduced the sleep quality of nearby residents. • A Cox risk prediction model was developed to help managers and residents improve mental health. Noise is an important environmental risk factor for physical and mental health. Furthermore, long-term noise exposure is burdensome for the mind and body and has become a serious problem. Rail transportation is one of the main methods used to transport goods in China; however, the noise and vibrations generated by freight trains have serious impacts on residents in nearby regions. To further investigate the relationship between railway noise and road noise exposure and changes in sleep duration and mental health scores, a field study in Harbin, China, was conducted and a health risk prediction model was constructed. The results showed that for every 1 dB increase in the Equivalent continuous A-weighted sound pressure level (LAeq), the percentage of deep sleep among residents living near the railway decreased by 0.2 %. Although residents near the railway reported similar sleep evaluations compared to those living farther away, they exhibited poorer mental health. Cox risk modeling indicates that the risk of mental health problems is approximately three times higher for those living near the railway. These findings potentially provide benefits in developing strategies to reduce the risk of mental illness for people residing near railways. [ABSTRACT FROM AUTHOR]

The growth in the utilization and development of rail transport within urban networks is crucial for transitioning towards a more sustainable form of mobility. However, challenges related to discomfort and noise pollution arising from rail traffic must be addressed and mitigated to foster a harmonious coexistence between residents and trains. This study focuses on analyzing an experimental campaign conducted on the surface metropolitan network of Porto to study and identify the frequency content and pressure levels associated with light rail traffic. The presented experimental campaign holds significant relevance as it comprises various and distinct circulation conditions within the railway network, enabling a comprehensive characterization of railway noise. The collected data indicates a noticeable increase in sound pressure levels as the speed of circulation rises, particularly emphasizing the 1/3 octave band centered around 1000 Hz. The choice of tracks with components having a limited capacity for absorbing acoustic energy leads to a significant rise in noise levels compared to track solutions with elements exhibiting excellent acoustic energy absorption. Furthermore, the study highlights a substantial increase in noise levels (10 dBA) associated with small radius curves, even at low speeds. These findings underscore the importance of considering the track characteristics and geometric features in noise assessment within rail networks. Therefore, the insights gained from this experimental campaign contribute significantly to the understanding and comprehensive characterization of railway noise under diverse circulation conditions within the railway network.

Aims: To examine the longitudinal association between transportation noise exposure (road traffic, aircraft, and railway noise) and T2D in a meta‐analysis. Materials and Methods: We systematically searched PubMed, Embase, Scopus, Cochrane, and Web of Science published up to February 2022. The GRADE approach was used to evaluate the study quality, and the pooled effect estimate was calculated by the fixed‐effects model or the random‐effects model. Results: We included 10 prospective studies with a total of 4,994,171 participants and 417,332 T2D cases in the meta‐analysis. According to the Navigation guide, 8 studies out of 10 were rated as having a probably high or high risk of bias. For road noise, the pooled relative risk (RR) per 10 dB higher Lden for developing T2D was 1.06 (95% CI:1.03, 1.09) with high heterogeneity (I2 = 90.1%, p < 0.001). Similar associations were also observed in aircraft and railway noise: the pooled RR were separately were: 1.01 (1.00, 1.01) and 1.02 (1.01, 1.03) separately. A 'dose‐response' analysis found a similar linear association between road noise exposure and the risk of T2D. Conclusions: An overall 6% increase in the risk of T2D per 10 dB increase in road exposure was observed. Further studies are needed to confirm our findings, especially for aircraft and railway noise, and to identify the mechanisms involved. [ABSTRACT FROM AUTHOR]

We analyze the impact of sound barriers on residential satisfaction and well-being manifested in housing prices in Singapore. Using the difference-in-difference approach, we demonstrate a significant price effect of sound barriers in high-rise residential environments. There was a 0.6% price increase for public housing units located within 300 m from a railway track after public announcement of sound barriers and a 1.2% further increase after barrier installation. Price effects of sound barriers are heterogeneous by the noise level prior to installation as well as the degree of noise mitigation by barriers. In contrast to the result for public housing, no significant price change was observed for private housing units that have better building design to be shielded from noise even before sound barrier installation. Among public housing, higher-floor units experienced more substantial price increases compared with lower-floor units exposed to less noise prior to barrier installation. Finally, the units that are very close to the railway did not enjoy price premiums brought by sound barriers potentially because noise did not fall below the threshold level of annoyance even after barrier installation. [ABSTRACT FROM AUTHOR]

• Rail traffic is increasing following policy recommendations for sustainability. • People living close to rail tracks are exposed to both vibration and noise. • We show strong dose–response relationships for modelled vibration and annoyance. • The associations are strongest for freight trains. • Important to consider railway noise in the investigation of vibration annoyance. Rail traffic is increasing following policy recommendations for a sustainable transportation model. However, the health effects of rail traffic vibration on residents living close to railways remain underexplored. We aimed to investigate the relationships between rail traffic vibration and vibration annoyance from different types of trains and to explore the influence of railway noise on these relationships. The study population (N = 7280) was randomly selected from adults living within 1 km of a trafficked railway in Sweden. Survey data were combined with modelled rail traffic vibration and noise. A cross-sectional design and logistic regression analysis were used. Results support a dose–response relationship between vibration and annoyance (stronger for freight trains and weaker for passenger trains). In the adjusted analysis, we observe a robust association between vibration and annoyance from all types of trains, accounting for socioeconomic factors. Furthermore, railway noise appears to modulate the vibration annoyance response. [ABSTRACT FROM AUTHOR]

In 2018, the World Health Organization (WHO) stated that transport noise is the second biggest environmental problem affecting people's health, after air pollution. The Australian Environmental Health Standing Committee (enHealth) also provides suggested health-based limits for transport noise exposure. To better understand the impact of transport noise in Australia, a strategic national transport noise model was developed, representative of the year 2018. The transport noise model presented included parameters for terrain, buildings, and noise barriers, with results verified against measured data. The model calculated the road, rail, and aircraft noise levels for the day, evening, and night-time periods, across all façades of all storeys for over 15 million buildings across Australia. The State of Victoria was chosen as a case study to document noise exposure levels to the community. Australian Census of Population and Housing data and planning zones allowed a population within each dwelling to be calculated and paired to the modelled noise levels. Based on noise levels at the most exposed façade, it is estimated that 48% of the Victorian population are exposed to road traffic noise levels that exceed the 2018 WHO recommendations. Additionally, 10% are estimated to be exposed to aircraft noise levels, and 11% are estimated to be exposed to rail noise levels, that exceed the 2018 WHO recommendations. These percentages are commensurate with higher affected European Member states based on 2017 noise mapping completed as part of the European Noise Directive. When compared against environmental noise exposure recommendations from enHealth (2018), it is estimated that 11% of the Victorian population are exposed to combined road, rail, and aircraft noise levels above the recommended day/evening 60 dB LAeq 16 h health-based limit, and 10% above the health-based night-time limit of 55 dB LAeq 8 h. This national transport noise model provides a base for further research into the impacts of transport noise on the community, particularly regarding health and property values. The model can also support government planning, complaints handling, and asset management in the planning of future noise abatement in Australia. [ABSTRACT FROM AUTHOR]

The goal of this study is to investigate the psychophysiological effects of traffic sounds in urban green spaces. In a laboratory experiment, psychological and physiological responses to four traffic sounds were measured, including road, conventional train, high-speed train, and tram. The findings demonstrated that traffic sounds had significant detrimental psychological and physiological effects. In terms of psychological responses, the peak sound level outperformed the equivalent sound level in determining the psychological impact of traffic sounds. The physiological effects of traffic sounds were shown to be significantly influenced by sound type and sound level. The physiological response to the high-speed train sound differed significantly from the other three traffic sounds. The physiological effects of road traffic sounds were found to be unrelated to the sound level. On the contrary, as for the railway sounds, the change in sound level was observed to have a significant impact on the participants' physiological indicators. [ABSTRACT FROM AUTHOR]

Bridge noise may increase when a train with local wears on wheel treads runs at higher speed. In this study we developed the estimation method for bridge noise at a high-speed section based on permanent accelerometers at a low-speed section. We proposed combining outputs of three accelerometers to measure precisely the influence of the wear of each wheel on rail vibration at the low-speed section, since the influence of the wear is attenuated depending on distance between a position of an accelerometer and that of where the local wear contacts rail. Composite measured data at the low-speed section showed that rail vibration affected by the local wear can be measured independent of distance between them. We also proposed an estimation method that converts the rail vibration at the low-speed section into that at the high-speed section to predict the bridge noises during train running at the high-speed section. In the estimation, the vibration properties of a wheel, a track and a contact spring at each section are used, and it is assumed that a wheel roughness is greater than a rail roughness at the spatial frequencies where the effect due to the local wear appears. The impulse excitation tests were carried out to obtain these vibration properties and transfer functions in vibration from the rail to the bridge at the high-speed section. The transfer functions are used to estimate bridge vibration using the rail vibration induced by one wheel. The bridge noise generated by one wheel is also estimated from the bridge vibration by taking account of the radiation area of the viaduct. Summing the vibrations and noise generated by all wheels in one train results in the overall bridge vibration and noise. The estimated results at the high-speed section show a good agreement with the measured one at the frequencies where the local wear has a stronger effect.

In this paper, an attempt is undertaken to identify the acoustic signature of railway vehicles travelling at 200 km/h. In the framework of conducted experimental research, test fields were determined, measurement apparatus was selected and a methodology for making measurements was specified, including the assessment of noise emission on curved and straight track for electric multiple units of Alstom type ETR610-series ED250, the so-called Pendolino. The measurements were made with the use of an acoustic camera and a 4 × 2 microphone array, including four equipped measurement points and two microphones located at the level of the head of the rail and at a height of 4 m above this level. As a result of the conducted experimental research, the dominant noise sources were identified and amplitude–frequency characteristics for these sources were determined by dividing the spectrum into one-third octave bands in the range from 20 Hz to 20 kHz. The paper also considers issues related to the verification of selected models of noise assessment in terms of their most accurate reflection of the phenomenon of propagation in close surroundings. On the basis of conducted experimental studies, the behaviour of selected models describing the change of sound level with frequency division into one-third octave bands as a function of variable distance of observer from the railway line on which high-speed railway vehicles are operated was verified. In addition, the author's propagation model is presented together with a database built within the scope of the study, containing the actual waveforms in the time and frequency domain. [ABSTRACT FROM AUTHOR]

Rail transport is the most sustainable transportation mode, with the lowest energy consumption and carbon footprint. However, the noise induced by railway traffic in urban regions is a significant drawback and several reports point out the risks and the amount of people suffering from direct exposure to railway noise. One of the most used mitigation measures for railway noise is the implementation of noise barriers. Although they offer a significant reduction in noise levels, their height makes people feel enclosed. Therefore, in the case of railway infrastructure, the solution to the problem may lie in the use of barriers with a lower height placed close to the railway track. As the noise-forming mechanisms are mainly located at the track level, placing the barrier in a position close to the track allows mitigating rail noise without causing the problems identified above for the population in the vicinity. The purpose of this paper is to illustrate the development of a barrier solution to be used in a railway context through numerical modelling with the Boundary Element Method (BEM). The solutions developed were placed close to the track and have a low height. The geometry was defined so as to direct the energy back to the track to take advantage of the acoustic properties of the ballast. The addition of a porous granular material on the inner face of the barrier allows the control of reflections between the vehicle body and the barrier, increasing its acoustic efficiency. Finally, considering the most efficient solution, the insertion loss in a network of receivers located 10 m away from the track is analysed in order to study the noise reduction levels in a place where human receivers are usually located. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to clarify the damping mechanism of the wheel that we have developed. In high-speed railway vehicles, noise associated with speed increase is a problem. We have developed a new wheel that can damp the rolling noise radiated from the wheel. This noise damped wheel has a special device attached to the inner circumference of the rim, which consists of steel sandwiched with vibration absorbing rubber. The noise damping effect was confirmed by the wheel rolling test, but the mechanism was unclear. Therefore, we elucidated the vibration damping mechanism using FEM. Using frequency response analysis, the equivalent radiated power (ERP) was calculated based on the response speed and element area when a load was repeatedly applied at a specified frequency. By calculating the modal ERP for a specific frequency, the natural vibration of the wheel, which contributes significantly to that frequency, was clarified. From this result, it became clear that the developed wheel disperses the natural vibration modes. It was also found that the vibration is reduced by damping of the rubber that acts on the dispersed natural vibration. Based on these findings, we concluded that increasing the Young's modulus of the rubber would improve the damping performance.

Background: Transportation noise has been linked with cardiometabolic outcomes, yet whether it is a risk factor for atrial fibrillation (AF) remains inconclusive. We aimed to assess whether transportation noise was associated with AF in a large, pooled Nordic cohort., Methods: We pooled data from 11 Nordic cohorts, totaling 161,115 participants. Based on address history from five years before baseline until end of follow-up, road, railway, and aircraft noise was estimated at a residential level. Incident AF was ascertained via linkage to nationwide patient registries. Cox proportional hazards models were utilized to estimate associations between running 5-year time-weighted mean transportation noise (L den ) and AF after adjusting for sociodemographics, lifestyle, and air pollution., Findings: We identified 18,939 incident AF cases over a median follow-up of 19.6 years. Road traffic noise was associated with AF, with a hazard ratio (HR) and 95% confidence interval (CI) of 1.02 (1.00-1.04) per 10-dB of 5-year mean time-weighted exposure, which changed to 1.03 (1.01-1.06) when implementing a 53-dB cut-off. In effect modification analyses, the association for road traffic noise and AF appeared strongest in women and overweight and obese participants. Compared to exposures ≤40 dB, aircraft noise of 40.1-50 and > 50 dB were associated with HRs of 1.04 (0.93-1.16) and 1.12 (0.98-1.27), respectively. Railway noise was not associated with AF. We found a HR of 1.19 (1.02-1.40) among people exposed to noise from road (≥45 dB), railway (>40 dB), and aircraft (>40 dB) combined., Interpretation: Road traffic noise, and possibly aircraft noise, may be associated with elevated risk of AF., Funding: NordForsk., Competing Interests: All other authors declare no competing interests., (© 2024 The Author(s).)

When a wheel rolls over a railway rail, it 'sees' a varying stiffness downwards because the rail is periodically supported by sleepers, leading to parametric excitation of the rail/wheel system. This study investigates the importance of parametric excitation on railway noise generation. Because the problem is non-stationary, it is modelled in the time domain. Rail and wheel impulse response functions, together with an iteration scheme to match boundary conditions in the rail/wheel contact patch, yield rail and wheel response plus contact force at each wheel position on the rail. Forward velocity and rotation of the elastic wheel are accounted for. Feedback coupling between response and force takes part in the excitation. Numerical simulations show that, for a rail on stiff pads, parametric excitation is a major excitation mechanism, above all leading to increased excitation and noise levels in a broad frequency region around the pinned–pinned frequency. [ABSTRACT FROM AUTHOR]

Excessive interior noise in railway vehicles is a major cause of fatigue and discomfort for passengers. In particular, the between-cars sections of high-speed trains experience considerable interior noise due to the poor noise reduction performance of the bellows, which are primarily made of silicone rubber and thus have a lower density than that of other components, made of extruded aluminum. Therefore, the objective of this study was to improve the noise reduction performance of such bellows. First, the material properties of silicone rubber were analyzed. Based on the results, the noise transmission of a simple model was analyzed to determine approaches required to reduce the low-frequency interior noise of the between-cars sections. It was confirmed that the low-frequency noise could be reduced by incorporating a multilayered panel of silicone rubber. Therefore, multilayered structures were considered for incorporation in the interior space of the between-cars sections of an actual high-speed train. A curved driving simulation of the between-cars sections indicated that no interference occurs when applying the proposed approach. Furthermore, a comparative test regarding the noise reduction performance was conducted considering cases involving bellows with and without multiple layers. The results of the verification test demonstrated that the noise reduction performance when using the proposed approach was improved by 4 dB compared with that in the case involving the conventional bellows, and an improvement of 8 dB or more was observed for noise with a low-frequency of 100 Hz. [ABSTRACT FROM AUTHOR]

Curve squeal noise is one of the greatest noise sources among railway noise when a vehicle is passing through the sharp radius curve. Furthermore, its high frequency and pure tone component cause a great deal of pain to residents around the track. Squeal noise is caused by lateral creep of wheel/rail contact point in curve. When railway vehicle passes through a sharp curve, negative friction under conditions of lateral creepage induces stick–slip oscillations, and these in turn induce resonance of the wheel web. Thus, wheel squeal noise is generated. In this study, laser cladding rail with composite material on the rail head was tested to prevent decrease of adhesion coefficient versus creepage. To make a composite rail specimen for test rig, composite material was cladded using high power diode laser. Four distinct types of composite material were processed to prepare rail disc specimens. To determine their effect on squeal noise reduction, adhesion coefficient and noise test were performed using a wheel / rail scale test rig. Lateral adhesion coefficient and squeal noise were also measured. Our results showed that steel rail disc had negative slope of adhesion coefficient and generated squeal noise in 2 kHz and 4 kHz. However, there was less or no negative slope when composite material rail specimen was used. Some cladded rail specimens had negative friction at higher degree of yaw angle than steel rail. Particularly, the specific test specimen exhibited excellent friction characteristic without decreasing the adhesion coefficient even when the yaw angle increased, and that specimen did not generate the squeal noise. Experimental results showed that it is possible to suppress the wheel squeal noise by changing the friction characteristics of the contact point by applying the composite material. [ABSTRACT FROM AUTHOR]

Background: Studies on transportation noise and incident stroke are few and inconclusive. We aimed to investigate associations between road-traffic and railway noise and the risk of incident stroke in the entire Danish population.Methods: We estimated road-traffic and railway noise (Lden) at the most and least exposed façades for all residential addresses across Denmark (2.8 million) for the period 1990-2017. Based on this, we estimated the 10-year time-weighted mean noise exposure for 3.6 million Danes aged >35 years, of whom 184 523 developed incident stroke during follow-up from 2000 to 2017. Analyses were conducted using Cox proportional-hazards models, with adjustment for various individual- and area-level demographic and socio-economic covariates collected from registries and air pollution [fine particulate matter with particles with a diameter of ≤2.5 µm (PM2.5) and nitrogen dioxide (NO2)].Results: A 10-dB increase in the 10-year mean road-traffic noise at the most exposed façade was associated with an incidence rate ratio (IRR) of 1.04 [95% confidence interval (CI): 1.03-1.05] for all strokes. For road-traffic noise at the least exposed façade, the IRR per 10 dB was 1.03 (95% CI: 1.02-1.04) for all strokes. Railway noise was not associated with a higher risk of stroke.Conclusion: Road-traffic noise increased the risk of stroke. These findings add to the evidence of road-traffic noise as a cardiovascular risk factor. [ABSTRACT FROM AUTHOR]