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Analysis of institutional authors

Iglesias, ElAuthor

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March 15, 2021
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Aerodynamic noise of high-speed train pantographs: Comparisons between field measurements and an updated component-based prediction model

Publicated to: APPLIED ACOUSTICS. 175 107791- - 2021-04-01 175(), DOI: 10.1016/j.apacoust.2020.107791

Authors:

Liu, XW; Zhang, J; Thompson, D; Iglesias, EL; Squicciarini, G; Hu, ZW; Toward, M; Lurcock, D
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Affiliations

‎ Univ Politecn Madrid, Escuela Tecn Super Ingn & Sistemas Telecomunicac, Madrid, Spain - Author
‎ Univ Southampton, Aerodynam & Flight Mech Res Grp, Southampton SO17 1BJ, Hants, England - Author
‎ Univ Southampton, Inst Sound & Vibrat Res, Southampton SO17 1BJ, Hants, England - Author
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Abstract

Aerodynamic noise from pantographs becomes an important source of noise from trains at high speeds. Previous studies have mostly been based on numerical predictions using computational aeroacoustic methods, which require large computing resources, or measurements conducted in a wind tunnel which cannot take all the real conditions into account. A component-based model relying on empirical constants obtained from the literature has been shown to predict aerodynamic noise from pantographs that agrees well with wind tunnel measurements. This model is extended in this paper by making use of simulation results on individual cylinders to refine the model constants and the Reynolds number dependence. In addition, allowance for the effect of incoming turbulence and cylinder aspect ratio is also extended. The updated model shows improved agreement with wind tunnel measurements, particularly at low frequencies. This model is then used to predict pantograph noise in more realistic conditions during train pass-by. The incoming flow conditions in terms of the incident flow speed, the turbulence intensity and the turbulence length scale are estimated from the literature considering the development of the boundary layer along the train roof. The sensitivity of the model to these assumptions is assessed using Monte Carlo simulations. The predicted results are compared with field measurements obtained using microphone array techniques for pantograph on different operational trains. Good agreement is obtained between the predictions and the measurements in terms of the far-field noise spectra and the dependence of noise level on speed. Differences are noted between measured levels for different orientations of the pantograph which according to the model are mainly related to the distance of the pantograph from the front of the train. (C) 2020 Elsevier Ltd. All rights reserved.
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Keywords

Aerodynamic noiseAerodynamicsAspect ratioAtmospheric thermodynamicsBoundary layer flowBoundary layersCircular-cylinderComponent-based modelComponent-based modelingComputational aeroacousticsCylinders (shapes)DragElectric current collectionEmpirical constantsFlowForecastingHigh speed train (hst)Microphone array measurementMonte carlo methodsNumerical methodsNumerical predictionsOperational trainsPantographsPredictive analyticsRailroad carsRailroad tunnelsRailroadsRealistic conditionsReductionReynolds numberSlipstreamSquare cross-sectionTrain pantographTurbulenceTurbulence intensityWakeWind tunnel measurementsWind tunnels

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal APPLIED ACOUSTICS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2021, it was in position 8/32, thus managing to position itself as a Q1 (Primer Cuartil), in the category Acoustics.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 2.09. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 13, 2025)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 2.26 (source consulted: FECYT Mar 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2026-04-25, the following number of citations:

  • WoS: 23
  • Scopus: 28
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 11 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/87218/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 194
  • Downloads: 119
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: United Kingdom.

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