526_MS27_ABS_1018

Train–induced aerodynamic pressure and its effect on noise protection wallsP. Ampunant1, F. Kemper2, I. Mangerig1, M. Feldmann2

1Institute of Steel Construction, UniBw Munich, Werner–Heisenberg–Weg 37, 85579 Neubiberg, Germany2Institute of Steel Construction, RWTH Aachen, Mies–van–der–Rohe–Street 1, 52074 Aachen, Germany

email: [email protected], [email protected],[email protected], [email protected]

ABSTRACT: Train–induced aerodynamic loads on noise protection walls have been a field of research for some time. Duringthe passage of a high–speed train along noise protection walls, they are exposed to high aerodynamic pressure loads that reducethe endurance limit. In this work measurements of the excerted pressure are shown and the results of a statistical analysis. Themeasurement data are the foundation of a numerical simulation based on computational fluid dynamics (CFD) to simulate thepressure flow around the passing train. Based on the NAVIER–STOKES–equation which are formed to the REYNOLDS averagedNAVIER–STOKES–equation (RANS–equation) the flow is resolved. The results of the simulation are compared to the measurementdata.

KEY WORDS: SEGES, noise protection walls, high–speed trains, computational fluid dynamics (CFD)

1 INTRODUCTION

Noise protection walls along railroads of high-speed trains areexposed to an fluctuating aerodynamic pressure field when trainsare passing by. During this passage the flow compression atthe bow of the train induces an overpressure at the barrierwhich is immediately followed by an aerodynamic suctiondue to a significantly accelerated parallel flow field. Thesequickly changing pressure amplitudes represent a dynamic loadimpact which lead to dynamic structural movements. The samepressure fluctuations in opposite arrangement are excited at therear of the train. The response of the structure is dependenton the Eigenfrequencies and the damping behavior of the noiseprotection wall. Due to the non-uniform distribution of loadson the elements of the noise protection walls which is a presentfield of research it is the aim to investigate the formation of thepressure field and its effects on the structure.

2 MEASUREMENTS ON SITE

2.1 Measurement set-up

Numerical simulations which aim to determine aerodynamicpressures on complex surfaces should be validated in orderto ensure the model quality. In case of bluff bodies undernatural wind flow, mainly wind tunnel results are used for thisaim. However, the simulation of the aerodynamic pressurefield induced on a noise barrier by a high speed train is noteasy to investigate on a scaled model. For the validation ofnumerical results shown in this paper, pressure data obtainedby means of on-site measurements are used. The correspondingmeasurement campaign is described in the following.

During the research project SEGES measurements on noisebarriers made of glass have been performed in the summer of2012. During a time period of six weeks, train induced pressurefields and associated structural reactions have been measured. Intotal, about 2,700 train events (different train types) have been

Figure 1. Schematic set-up of measurement equipment

recorded, each with a sample duration of T=30 s. In Figure 2the principal setup of the used sensors is illustrated for a sectionof L=5.0 m. The total length of the noise barrier with glasselements was LT =50.0 m

Figure 3. Velocity Histogram of all recorded Trains

For the analyzes in the scope of this paper, four differentialpressure transducers have been considered. All sensors were

Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 2014Porto, Portugal, 30 June - 2 July 2014

A. Cunha, E. Caetano, P. Ribeiro, G. Müller (eds.)ISSN: 2311-9020; ISBN: 978-972-752-165-4

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installed at a height of h=0.0 m above the top of the tracks. Thesensors were located in a maximum longitudinal dimension ofLS=42.2 m between the first and the last sensor.

2.2 Analysis of Pressure Values

Based on the time difference between the pressure signals at thebeginning and the end of the test wall, the individual speed ofeach train passage has been analyzed:

vTrain =∆s(Sensor1,Sensor2)

∆t(p)=

42.2mt(pSensor1)− t(pSensor2)

(1)

The pressure amplitudes have been normalized by thevelocity pressure of the passing train in order to determine thepressure coefficients:

cp(t) =p(t)

1/2 ·ρ · v2Train

(2)

As the time scale of the measured amplitudes dependson the train velocity, all time series have been converted todisplacement related series:

xTrain(t) = t · vTrain (3)

For a better comparability, the first pressure maximum hasbeen set to a xTrain=100 m. Some typical time series of thepressure coefficient due to the passage of an ICE 3 train isplotted in figure 4. In the plot, the significance of the forewave and the rear wave can be seen. The inner variationof pressure is provoked by the wheel sets of each car andby the gaps between the cars. Whereat the fore wave letto comparable low fluctuations of the determined pressurecoefficients, the train parallel flow and the flow separation atthe rear part are accompanied by significant variations of thepressure coefficients.

3 STATISTICAL ENSURED RESULTS

3.1 Statistical ensured results

In order to allow a statistical ensured result for the designof noise barriers, it is important to take into account a largernumber of data records. As the track is used by different traintypes with the analyzes have been focused on velocities abovevTrain = 150 km

h .Altogether, a number of n=72 independent pressure time

series have been analyzed with respect to their statisticaldistribution. In order to allow a more profound analysis, allpressure series have been normalized and equally discretized.Therewith, the mean value and the standard deviation could beanalyzed for each train position xTrain.

In figure 5 the results are plotted as mean values. Additionallythe 34% - 68% and the 5% - 95% quantile intervals have beenplotted in this figure. The associated statistic constants forthe double sided delimitation are u0.84 = 0.99 and u0.975 =1.96. Hence, the pressure quantile intervals of the pressurecoefficients are determined as follows:

cp−0.99 ·σ ≤cp ≤ cp +0.99 ·σcp−1.96 ·σ ≤cp ≤ cp +1.96 ·σ .

The results plotted in figure 5 can directly be used to validatethe numerical simulations which are further described in thefollowing sections.

4 NUMERICAL SIMULATION

4.1 Theory

In this chapter the theoretical basis of the numerical simulationis explained. Futher details can be found in e.g. FERZIGER etal. [1], LECHELER [2] and SCHICHTLING [3]. The foundationof the numerical simulation are the equations

∂

∂ t~U +∇ ·~F = ~Q (4)

with

~U =

ρ

ρ ·~uρ ·(e+ 1

2 ·~u2) ,

~F =

ρ ·~uρ ·~u⊗~u+ p · I− τ

ρ ·~u ·(h+ 1

2 ·~u2)− τ ·~u−λ ·∇T

,

~Q =

0ρ ·~gρ ·~g ·~u+ρ · qS

.

Equations (4) are called the NAVIER–STOKES–equations.The mentioned equations are written in differential form andinclude the conservation of mass, momentum and energy. Inorder to approximate turbulence flow the NAVIER–STOKES–equations are formed to the REYNOLDS-averaged NAVIER–STOKES–equations (RANS–equations).The spacial discretization is based on the finite–volume–methodso that the conservation equations can be solved numerically.Furthermore the RANS–equations have to be discretisizedin time as time–dependent factors play a role. The timediscretization is conducted with a 2nd–order implicit EULER–method.The NAVIER–STOKES–equations are simplified as we assumethat the fluid is incompressible. Due to the fact that thesimulated train velocity does not exceed 300 km

h and the MACH–number Ma

Ma =vtrain

vsound=

1340· 300

3,6≈ 0,245≤ 0,3

is below 0.3 the fluid can be modelled as incompressible(YOUNG et al. [4]) .

4.2 Geometry

A 3D–based numerical simulation is implemented, the geomet-rical information of an INTERCITY EXPRESS 3 (ICE 3) is takenfrom DIN–EN 14067-6 [5] in the first step. In figure 6 the headof the train is shown.

For the numerical simulation the geometry is simplified. Thewheels and the connections for electricity are neglected so thatthe number of elements is reduced. As the surrounding airfield is of interest the fluid space around the train is modelled.The fluid space is subdivided into 4 parts. The first part is

Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 2014

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Figure 2. Differential Pressure Sensor (left), Accelerometer (middle) and approaching ICE 3 Train (right)

Figure 4. Normalized series of differential pressure, 18 passages of ICE-3 trains

Figure 5. Mean Values of the Pressure Coefficient cp and Quantile-Intervals


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Figure 6. Geometry of ICE 3 [5]

the static fluid region Ωs that includes the noise protectionwall. The second region contains the train surface and is calleddynamic fluid space Ωbm. Two additional dynamic fluid regionsare modeled in order to implement the movement of the traingeometry. All parts of the fluid region are shown in figure 7

Figure 7. Geometry of fluid space

Due to the symmetric properties of the train geometry andthe low influence of the assymetric positioning of the noiseprotection walls to the passing train, only half the size of theflow field is implemented in order to reduce the amount of gridelements.

4.3 Moving Mesh

The translational movement of the train can be modeled asmovement of the mesh grid. When conducting a movingmesh the mesh deforms and therefore the quality of the meshdeteriorates. In order to keep the quality of the mesh the sameduring the whole simulation a structured mesh is necessarilyimplemented in all parts of the fluid regions. The fluid regionΩbm which contains the geometry of the train moves translatory

with a constant velocity. The mesh is therefore not deformedduring the whole simulation. The two other dynamic fluidregions Ωbh and Ωbv are located behind and in front of the regionΩbm. These movable regions contain hexahedral elements ina structured way so that the movement of the train can becompensated by stretching and squeezing of the two mentionedfluid regions. During this process the angles of the mesh grid,however, are not changed and keep the perpendicular mannerof the implemented, structured grid. The static fluid region Ωswhich surrounds the noise protection wall is not deformable.

4.4 Boundary conditions

The outer boundaries of the fluid regions are modeled as no–slipwalls. The size of the fluid space perpendicular to the movingdirection of the train is 20 times the size of the train to ensurethat the far–field boundaries do not have an influence on theresulting pressure field. The surfaces of the noise protection walland the train are modeled as no–slip walls and the behaviour ofall no–slip walls are smooth. The surface in front of the head ofthe train is defined as outlet whereas the suface behind the tailof the train is modeled as inlet.The movement at the boundaries is set to zero and the movingvelocity of the region Ωbm is set to a constant velocity. The meshvelocity of the regions between the constantly moving mesh andthe static boundaries move are linearized from zero to the trainvelocity.

4.5 Solution and comparison

All simulation runs are conducted with an amount ofapproximately 1.7 million elements. In order to ensure adimensionless wall distance y+ of

y+ ≈ 100

the smallest spatial discretization is4x= 0.001m. Due to themovement of the train body the simulation is transient, the timediscretization 4t does not exceed 0.001s. The approximationof the turbulence layer was realized by implementing the SSTk–ω–modell by MENTER [6].When the train passes the noise protection wall at a certainpoint the bow of the train induces an overpressure that isimmediately followed by an aerodynamic suction. In figure 8the pressure–time–curve of a passing train is shown at rail levelfor a train velocity of vtrain = 160 km

h . The measured pressureand the numerical results are both shown. By comparing thetwo curves a good matching between the two data samples canbe seen especially at the bow of the train. As the rear partof the train passes the monitoring point at the wall a higherpressure is calculated than measured. Although the pressuredifference is more than 100 % there is a qualitative similaritythe pressure curve. The difference can be explained by thesignificant variations of the pressure measured at the rear partas documented in section 2.2.The fluctuating pressure can be simulated and are similar to themeasurements. The difference of the highest values of pressurebetween measurement and numerical results is underneath 5 %for the pressure when the bow of the trains passes by.

In figure 9 the pressure at cross–section and the pressure inlongitudinal direction are presented. The left picture shows a


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Figure 8. Comparison between measurement and numericalresults [7]

nonlinear distribution at the cross–section, the picture on theright-hand side presents a drag area in front of the bow whichis followed by a suction area.

Figure 9. pressure at cross-section (left), pressure inlongitudinal direction (right)

5 SUMMARY

This work shows the results of measurements when high-speed trains go past noise protection barriers. Thesemeasurements were made during the research project SEGES.The measurement data were analyzed and the results weredescribed. The fluctuating pressure which can be described astime–dependent and a quick change of drag and suction whenthe bow of the train passes with high velocity were measuredand a numerical simulation based on CFD was implemented toreproduce the pressure field which act on the noise protectionwalls. The theoretical background and the setting of thenumerical simulation was explained. A comparison between themeasurements and the results of the numerical simulation wasmade. It was shown that there is a good matching between themeasured data sample and the numerical results. The differencebetween the pressure measured and the calculated numericalresults are underneath 5 % when the bow of the train passes thenoise protection wall. The pressure field can be well reproduced.

REFERENCES

[1] Joel H. Ferziger and Milovan Peric, NumerischeStromungsmechanik, Springer, 2002.

[2] Stefan Lecheler, Numerische Stromungsberechnung,Vieweg+Teubner, 2009.

[3] Hermann Schichtling and Klaus Gersten, Grenzschicht-Theorie, Springer, 2006.

[4] Donald F. Young, Bruce R. Munson, Theodore H. Okiishi,and Wade W. Huebsch, A Brief Introduction to FluidMechanics, Wiley & Sons, 2007.

[5] “DIN–EN 14067–6 – Railway applications – Aerodynamics– Part 6: Requirements and test procedures for cross windassessment,” May 2010.

[6] Florian R. Menter, “Zonal Two Equation k−ω turbulencemodels for aerodynamics flows,” AIAA Paper 93-2906,1993.

[7] “Projekt SEGES – Schallschutz–Elemente aus Glas anEisenbahn–Strecken,” Final report, 2012.


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526_MS27_ABS_1018