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Analysis of flow structures in the wake of a high-speed train
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0002-9061-4174
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0001-7864-3071
Bombardier Transportation, Sweden.
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2016 (English)In: Proceedings aerodynamics of heavy vehicles III, buses, trucks and trains, Springer, 2016, Vol. 79Conference paper, Published paper (Refereed)
Abstract [en]

Slipstream is the flow that a train pulls along due to the viscosity of the fluid. In real life applications, the effect of the slipstream flow is a safety concern for people on platform, tracksideworkers and objects on platforms such as baggage carts and pushchairs. The most important region for slipstream of high-speed passanger trains is the near wake, in which the flow is fully turbulent with a broad range of length and time scales. In this work, the flow around the Aerodynamic Train Model (ATM) is simulated using Detached Eddy Simulation (DES) to model the turbulence. Different grids are used in order to prove grid converged results. In order to compare with the results of experimental work performed at DLR on the ATM, where a trip wire was attached to the model, it turned out to be necessary to model this wire to have comparable results. An attempt to model the effect of the trip wire via volume forces improved the results but we were not successful at reproducing the full velocity profiles. The flow is analyzed by computing the POD and Koopman modes. The structures in the floware found to be associated with two counter rotating vortices. A strong connection between pairs of modes is found, which is related to the propagation of flow structures for the POD modes. Koopman modes and POD modes are similar in the spatial structure and similarities in frequencies of the time evolution of the structures are also found.

Place, publisher, year, edition, pages
Springer, 2016. Vol. 79
Series
Lecture Notes in Applied and Computational Mechanics, ISSN 1613-7736
National Category
Fluid Mechanics and Acoustics
Identifiers
URN: urn:nbn:se:kth:diva-65755DOI: 10.1007/978-3-319-20122-1_1Scopus ID: 2-s2.0-84951325441ISBN: 978-331920121-4 (print)OAI: oai:DiVA.org:kth-65755DiVA: diva2:483649
Conference
Aerodynamics of heavy vehicles III: Trucks, buses and trains, September 12-17, Potsdam, Germany, 2010
Note

QC 20160202

Available from: 2012-01-25 Created: 2012-01-25 Last updated: 2016-09-05Bibliographically approved
In thesis
1. Slipstream and Flow Structures in the Near Wake of High-Speed Trains
Open this publication in new window or tab >>Slipstream and Flow Structures in the Near Wake of High-Speed Trains
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Train transportation is a vital part of the transportation system of today. Asthe speed of the trains increase, the aerodynamic effects become more impor-tant. One aerodynamic effect that is of vital importance for passengers’ andtrack workers’ safety is slipstream, i.e. the induced velocities by the train.Safety requirements for slipstream are regulated in the Technical Specificationsfor Interoperability (TSI). Earlier experimental studies have found that forhigh-speed passenger trains the largest slipstream velocities occur in the wake.Therefore, in order to study slipstream of high-speed trains, the work in thisthesis is devoted to wake flows. First a test case, a surface-mounted cube, issimulated to test the analysis methodology that is later applied to two differ-ent train geometries, the Aerodynamic Train Model (ATM) and the CRH1.The flow is simulated with Delayed-Detached Eddy Simulation (DDES) andthe computed flow field is decomposed into modes with Proper Orthogonal De-composition (POD) and Dynamic Mode Decomposition (DMD). The computedmodes on the surface-mounted cube compare well with prior studies, whichvalidates the use of DDES together with POD/DMD. To ensure that enoughsnapshots are used to compute the POD and DMD modes, a method to inves-tigate the convergence is proposed for each decomposition method. It is foundthat there is a separation bubble behind the CRH1 and two counter-rotatingvortices behind the ATM. Even though the two geometries have different flowtopologies, the dominant flow structure in the wake in terms of energy is thesame, namely vortex shedding. Vortex shedding is also found to be the mostimportant flow structure for slipstream, at the TSI position. In addition, threeconfigurations of the ATM with different number of cars are simulated, in orderto investigate the effect of the size of the boundary layer on the flow structures.The most dominant structure is the same for all configurations, however, theStrouhal number decreases as the momentum thickness increases. The velocityin ground fixed probes are extracted from the flow, in order to investigate theslipstream velocity defined by the TSI. A large scatter in peak position andvalue for the different probes are found. Investigating the mean velocity atdifferent distances from the train side wall, indicates that wider versions of thesame train will create larger slipstream velocities.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xii, 64 p.
Series
TRITA-AVE, ISSN 1651-7660 ; 2012:28
National Category
Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:kth:diva-94182 (URN)978-91-7501-392-3 (ISBN)
Public defence
2012-06-13, F3, Lindstedsv. 26, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
TrenOp, Transport Research Environment with Novel Perspectives
Note

QC 20120530

Available from: 2012-05-30 Created: 2012-05-09 Last updated: 2014-02-11Bibliographically approved

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Efraimsson, GunillaHenningson, Dan S.

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