The noise generated by transportation systems is one of the most important causes of noise-induced annoyance, since exposure to high level noises for long periods of time can be detrimental to health. Amongst the different types of noise that originate from railroads, the squeal noise generated at curves, the impact noise generated at rail joints and the rolling noise stand out. To propose mitigation measures to this problem, noise generation must be understood as well as by which parameters it is influenced. To that end, analytical models have been developed to predict the generated Sound Pressure Level (SPL) and to verify which factors are related to noise generation. This paper aims to validate analytical models for impact noise, squeal noise and rolling noise, which were originally designed for urban railways, used for passenger transportation. In this work, the validation is made using SPL measurements taken at a Brazilian heavy-haul railway, and a railway which carries bulk cargo in general. The models are implemented on a numerical computation software considering vehicle and track characteristics, train speed and a reference SPL. The results obtained from the models were compared with SPL measurements performed at the railroad during regular operation for the three cases (rolling, squeal and impact), which, despite the measurement limitations imposed by practical constraints during regular traffic operation, showed good agreement.


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    Titel :

    Analysis and Characterization of Noise Generated in Heavy-Haul Railways in Brazil


    Weitere Titelangaben:

    Lect.Notes Mobility


    Beteiligte:
    Marinov, Marin (Herausgeber:in) / Piip, Janene (Herausgeber:in) / Fiorentin, Thiago Antonio (Autor:in) / Asaff, Yesid (Autor:in) / Braz, Laura Dacoreggio Volpato (Autor:in)

    Erschienen in:

    Sustainable Rail Transport 4 ; Kapitel : 6 ; 121-142


    Erscheinungsdatum :

    2021-12-17


    Format / Umfang :

    22 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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