Numerical-experimental analysis of the slipstream produced by a high speed train

The recent development of high-speed trains over the last decade led to a growing interest in their aerodynamics. A train at full operational speed generates a strong induced airflow that may damage infrastructures near the trackside and endanger people near the rails. Nowadays the tests required fo...

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Veröffentlicht in:Journal of wind engineering and industrial aerodynamics 2020-01, Vol.196, p.104022, Article 104022
Hauptverfasser: Zampieri, Alessandro, Rocchi, Daniele, Schito, Paolo, Somaschini, Claudio
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Sprache:eng
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Zusammenfassung:The recent development of high-speed trains over the last decade led to a growing interest in their aerodynamics. A train at full operational speed generates a strong induced airflow that may damage infrastructures near the trackside and endanger people near the rails. Nowadays the tests required for the train homologation are based on full scale measurements of the airspeed taken in specified positions close to the railway line. An important part of the work was initially dedicated to the data analysis of an extensive experimental campaign performed on the Italian high-speed line, in order to obtain reliable results to be used for comparison with CFD results. These ones have been performed on the full-scale train geometry using an URANS approach with a wall treatment based on wall functions, checking mesh and turbulence models dependencies. The full-scale simulations highlighted the great complexity of the problem being the comparison with the experimental measurements performed close to the shear layer of the train boundary layer. Encouraging results are obtained from the numerical analysis on the full-scale train geometry indicating the ability of the URANS coupled with the SST turbulence model in the prediction of both the train induced flow and the turbulent structures around it. •Flow statistics strongly influenced by crosswind.•CFD provide good estimation of the 3D flow around a full scale high speed train in operational conditions.•k-omega SST turbulence model showed a strong stability and versatility in reproducing high turbulence flow.
ISSN:0167-6105
1872-8197
DOI:10.1016/j.jweia.2019.104022