Using a 2.5D boundary element model to predict the sound distribution on train external surfaces due to rolling noise

Li, Hui; Thompson, D.J.; Squicciarini, Giacomo; Liu, Xiaowan; Rissmann, Martin; Denia, F.D.; Giner-Navarro, Juan

doi:10.1016/j.jsv.2020.115599

Cited by 14 publications

(13 citation statements)

References 25 publications

(31 reference statements)

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“…In the proposed framework, the wheels are considered as point sources. In [31] it was found that if the wheel is represented instead by multiple sources, the sound pressure on the train sides is affected by less than 0.5 dB so the point source model seems adequate. According to their radiation directivities [3], the radiation from the axial vibration of the wheel is represented by a horizontal dipole and the radiation from the radial vibration is modelled by a monopole.…”

Section: Discussionmentioning

confidence: 99%

“…The input power is calculated by multiplying the sound power incident on the train floor and sidewalls by their corresponding transmission coefficients. These incident sound powers are calculated using different methods [30,31]. They are summarised in Section 3.1 and Section 3.2.…”

Section: Power Input To the Sea Modelmentioning

confidence: 99%

“…To account for their discrete distribution and for the spacing between them, scaling factors are needed to adjust the sound power calculated from the 2.5D model [37]. The sound power of the wheel, the rail and the sleepers obtained from the TWINS model [35] are used to adjust the 2.5D results [31].…”

Section: Sound Power Incident On Vehicle Sidesmentioning

confidence: 99%

“…The rail velocity is obtained in the wavenumber domain and is assigned to the cross-section of the rail, as outlined in Section [43]. The train considered in this work has fairings between the bogies but these do not cover the bogie area [31], so fairings are not included when the 2.5D model is used to calculate the wheel contribution; however, they are included for the rail/sleeper contribution. The corresponding rolling noise sound power components are given in [31].…”

Section: Calculation Of the Sound Incident On The Train Sidesmentioning

confidence: 99%

“…The train considered in this work has fairings between the bogies but these do not cover the bogie area [31], so fairings are not included when the 2.5D model is used to calculate the wheel contribution; however, they are included for the rail/sleeper contribution. The corresponding rolling noise sound power components are given in [31]. Figure 8 shows the overall sound pressure levels on the train sides due to rolling noise (two bogies below the carriage and the closest one below the adjacent carriage on each side are considered).…”

Section: Calculation Of the Sound Incident On The Train Sidesmentioning

confidence: 99%

See 4 more Smart Citations

A framework to predict the airborne noise inside railway vehicles with application to rolling noise

Thompson

Squicciarini

et al. 2021

Applied Acoustics

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Section: Discussionmentioning

confidence: 99%

Section: Power Input To the Sea Modelmentioning

confidence: 99%

Section: Sound Power Incident On Vehicle Sidesmentioning

confidence: 99%

Section: Calculation Of the Sound Incident On The Train Sidesmentioning

confidence: 99%

Section: Calculation Of the Sound Incident On The Train Sidesmentioning

confidence: 99%

See 3 more Smart Citations

A framework to predict the airborne noise inside railway vehicles with application to rolling noise

Thompson

Squicciarini

et al. 2021

Applied Acoustics

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Simplified prediction models for acoustic installation effects of train-mounted equipment

Thompson,

Zhao,

Squicciarini

2024

Railw. Eng. Sci.

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Acoustic models of railway vehicles in standstill and pass-by conditions can be used as part of a virtual certification process for new trains. For each piece of auxiliary equipment, the sound power measured on a test bench is combined with measured or predicted transfer functions. It is important, however, to allow for installation effects due to shielding by fairings or the train body. In the current work, fast-running analytical models are developed to determine these installation effects. The model for roof-mounted sources takes account of diffraction at the corner of the train body or fairing, using a barrier model. For equipment mounted under the train, the acoustic propagation from the sides of the source is based on free-field Green’s functions. The bottom surfaces are assumed to radiate initially into a cavity under the train, which is modelled with a simple diffuse field approach. The sound emitted from the gaps at the side of the cavity is then assumed to propagate to the receivers according to free-field Green’s functions. Results show good agreement with a 2.5D boundary element model and with measurements. Modelling uncertainty and parametric uncertainty are evaluated. The largest variability occurs due to the height and impedance of the ground, especially for a low receiver. This leads to standard deviations of up to 4 dB at low frequencies. For the roof-mounted sources, uncertainty over the location of the corner used in the equivalent barrier model can also lead to large standard deviations.

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A novel method for extremum response estimation of wheel–rail rolling noise by the development of moving pseudo-excitation method

Zhu

2023

Archiv.Civ.Mech.Eng

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Using a 2.5D boundary element model to predict the sound distribution on train external surfaces due to rolling noise

Cited by 14 publications

References 25 publications

A framework to predict the airborne noise inside railway vehicles with application to rolling noise

A framework to predict the airborne noise inside railway vehicles with application to rolling noise

Simplified prediction models for acoustic installation effects of train-mounted equipment

A novel method for extremum response estimation of wheel–rail rolling noise by the development of moving pseudo-excitation method

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