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

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

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Li, H.; Thompson, D.; Squicciarini, G.; Liu, X.; Rissmann, M.; Bouvet, P.; Denia, FD.... (2021). A framework to predict the airborne noise inside railway vehicles with application to rolling noise. Applied Acoustics. 179:1-15. https://doi.org/10.1016/j.apacoust.2021.108064

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/176434

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Title: A framework to predict the airborne noise inside railway vehicles with application to rolling noise
Author: Li, Hui Thompson, David Squicciarini, Giacomo Liu, Xiaowan Rissmann, Martin Bouvet, Pascal Denia, F. D. Baeza González, Luis Miguel Martin Jarillo, Julian Moreno Garcia-Loygorri, Juan
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials
Issued date:
Embargo end date: 2023-08-31
Abstract:
[EN] A framework is described for predicting the airborne noise inside railway vehicles which is applied to rolling noise sources. Statistical energy analysis (SEA) is used to predict the interior noise by subdividing the ...[+]
Subjects: Railway vehicle , Interior noise , Statistical energy analysis , 2.5D boundary element method , Rolling noise
Copyrigths: Embargado
Source:
Applied Acoustics. (issn: 0003-682X )
DOI: 10.1016/j.apacoust.2021.108064
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.apacoust.2021.108064
Project ID:
info:eu-repo/grantAgreement/EC/H2020/777564/EU/Innovative RUNning gear soluTiOns for new dependable, sustainable, intelligent and comfortable RAIL vehicles/
Thanks:
This work has been funded by the China Scholarship Council and the RUN2Rail H2020/Shift2Rail project (Grant agreement No: 777564). The contents of this publication only reflect the authors' views and the Shift2Rail Joint ...[+]
Type: Artículo

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