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Interior structure borne noise prediction of the cabin of a high speed train using FE-SEA hybrid methods

机译:基于FE-SEA混合方法的高速列车车厢内部结构噪声预测

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The interior noise levels in trains has been reduced considerably during the last decades. However, the acoustic behavior has nowadays an even more important role among the comfort parameters of high speed trains. The FE-SEA hybrid methodologies raised up during the last years have given a new approach to the problem of the structure borne noise, giving the opportunity to deal with the acoustic mid frequency range, where FE and SEA systems were unable to work. However this numerical models depend on several physical parameters and, although most of them are well known in fields like the automotive, they need to be further studied for the rolling stock applications. The present paper deals with the investigation process carried out by ALSTOM to set up a hybrid FE-SEA model of the cabin of a high speed train in order to predict the interior structure borne noise, from its first steps characterizing the most important transmission paths, to the structural responses predicted by given diverse model approaches.
机译:在过去的几十年中,火车的内部噪音水平已大大降低。但是,如今,声学性能在高速列车的舒适性参数中已扮演着更为重要的角色。近年来提出的FE-SEA混合方法为解决结构噪声问题提供了一种新方法,为处理FE和SEA系统无法工作的声学中频范围提供了机会。但是,此数值模型取决于几个物理参数,尽管大多数模型在汽车等领域是众所周知的,但仍需要对它们进行进一步研究,以用于机车车辆应用。本文讨论由阿尔斯通(ALSTOM)进行的调查过程,以建立高速列车车厢的混合FE-SEA模型,以便从表征最重要的传输路径的第一步开始,预测内部结构产生的噪声,给定各种模型方法预测的结构响应。

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  • 会议地点 Ottawa(CA);Ottawa(CA)
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    ALSTOM Transport S.A. Ctra. B-140 de Sta. Perpètua a Mollet km 7 5 Sta. Perpètua de Mogoda 08130 SPAIN Email address: jordi.jove-bellot@transport.alstom.com;

    ALSTOM Transport S.A. Ctra. B-140 de Sta. Perpètua a Mollet km 7 5 Sta. Perpètua de Mogoda 08130 SPAIN Email address: juan.sapena@transport.alstom .com;

    ALSTOM Transport S.A. Ctra. B-140 de Sta. Perpètua a Mollet km 7 5 Sta. Perpètua de Mogoda 08130 SPAIN Email address: fabienne.guerville@transport.alstom.com;

    ESI GmbH Werner-Eckert-Str. 6 D-81829 Muenchen GERMANY Email address: dbl@esigmbh.de;

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  • 入库时间 2022-08-26 14:41:12

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