Development of numerical model for the design of low-noise railway superstructure constructions

التفاصيل البيبلوغرافية
العنوان: Development of numerical model for the design of low-noise railway superstructure constructions
المؤلفون: Zhang, J., Lechner, B., Freudenstein, S., Wunderli, J.M., Zemp, A., Hannema, G., Hecht, M.
المساهمون: Forde, Michael C.
بيانات النشر: University of Edinburgh, School of Engineering
سنة النشر: 2020
مصطلحات موضوعية: structure-borne vibration, air-borne noise propagation, low-noise ballasted track, 3D-modelling, multibody simulation, finite element method, co-simulation
الوصف: Noise is a significant environmental problem in Railway transportation systems. The Rail transport policy of the EU and Switzerland is asking for efficient, innovative track systems, which are able to reduce rail noise. A Project named OST funded by BAFU Switzerland, was carried out under the co-operation with Empa (Switzerland), Technical University of Munich and Technical University of Berlin, had the target to develop a numerical model to predict the noise and vibration of ballasted track caused by passing trains. A co-simulation chain for transient acoustic simulation between multi body simulation (for structure-borne vibration) and finite element simulation (for sound radiation and for air-borne sound propagation) was established and the interface was developed. The numerical model was validated through laboratory tests on the test track of Technical University of Munich and field measurements on the track section Rothenthurm in Switzerland. The model aims to predict the acoustic effect of different railway superstructure components such as different sleeper types, rail profiles and rail pad stiffness.
نوع الوثيقة: report
اللغة: English
ردمك: 978-0-947644-87-1
0-947644-87-3
Relation: Railway engineering 2019; empa:23033; ut: 000581130300013; scopus: 2-s2.0-85094611756
DOI: 10.3233/JNR-200159
الاتاحة: https://doi.org/10.3233/JNR-200159
رقم الانضمام: edsbas.53198236
قاعدة البيانات: BASE
الوصف
ردمك:9780947644871
0947644873
DOI:10.3233/JNR-200159