Wind load simulation for high-speed train stations · 2012. 4. 26. · Journal of Wind Engineering and Industrial Aerodynamics 96 (2008) 2042–2053 Wind load simulation for high-speed

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Journal of Wind Engineering

and Industrial Aerodynamics 96 (2008) 2042–2053

0167-6105/$ -

doi:10.1016/j

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Wind load simulation for high-speed train stations

Nahmkeon Hura,�, Sa Ryang Kimb,Chan-Shik Wona, Chang-koon Choic

aDepartment of Mechanical Engineering, Sogang University, Sinsoo 1, Mapo, Seoul 121-742, Republic of KoreabDepartment of Precision Mechanical Engineering, Kangnung Nat’l. University, Jibyun 123, Gangneung,

Gangwon 210-702, Republic of KoreacDepartment of Civil and Environment Engineering, KAIST, Guseong 373-1, Yuseong, Daejeon 305-701,

Republic of Korea

Available online 7 April 2008

Abstract

A numerical simulation approach of wind load on buildings and wind tunnel experiment are

presented in the present paper. Four Korean high-speed train (KTX) stations (Cheonan-Asan,

Daejeon, Gwangmyeong and Gyeongju) were selected for this purpose. For the numerical

simulation, 3-D incompressible flow with the standard k–e turbulence model was adopted and thecommercial CFD software STAR-CD was used. In order to validate results of the numerical

solution, a wind tunnel experiment was performed. Results from the wind tunnel experiment using a

scaled model and CFD of four high-speed train station buildings were compared, and good

agreement was achieved for the wind loads on the station buildings. Hence, it was shown that CFD is

a good tool for predicting the wind load of huge and irregularly shaped buildings.

r 2008 Elsevier Ltd. All rights reserved.

Keywords: Wind load; High-speed train station; Building; Pressure; Computational fluid dynamics (CFD)

1. Introduction

To design new building structures, wind load acting on structures should be consideredfor safety reasons. Wind load data published for simple structures have been widely usedfor this purpose (ASCE, 1998; Tamura et al., 1999). However, it is difficult to use the data

see front matter r 2008 Elsevier Ltd. All rights reserved.

.jweia.2008.02.046

nding author. Tel.: +82 2 7058637; fax: +822 7120799.

dress: [email protected] (N. Hur).

www.elsevier.com/locate/jweiadx.doi.org/10.1016/j.jweia.2008.02.046mailto:[email protected]

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directly in relation to the complex structures. High-speed train station buildings such asCheonan-Asan station, Daejeon station, Gwangmyeong station, and Gyeongju station inKorea are huge in size and have unique shapes and building structures. To consider the safetyof these buildings under unusual weather conditions, wind load should be obtained throughwind tunnel tests or computer simulations, and taken into account in the design process.Computer hardware and simulation techniques have been developing very quickly. Therefore,it can be said that the computer simulation can replace the expense and time spent conductingwind tunnel tests. Recently, computer simulations have come into use for verifying design inmany fields of architecture, mechanical engineering, equipment, and the construction industry.

Gosman (1999) reviewed the capabilities and limitations of CFD as a tool for windengineering, with particular reference to the commercial CFD codes. He concluded that,although there are well-known weaknesses in the physics modeling, the level of predictionaccuracy was already sufficient for some purpose. Also, for the same purpose, Huang et al.(2007) studied wind effects on the Commonwealth Advisory Aeronautical Council(CAARC) standard tall building with techniques of CFD, such as large eddy simulation(LES) and the Reynolds-averaged Navier–Stokes equations (RANS) model, etc. And thecomputed results were compared with experimental data of wind tunnel. From the result,they showed that CFD techniques and associated numerical treatments provided aneffective way for designers to assess wind effects on a tall building.

For the curved–roofed building, which is increasingly used in the modern builtenvironment, Blackmore and Tsokri (2006) performed parametric wind tunnel studies andproperly scaled atmospheric boundary layer simulation and gave an alternative to theEurocode for wind actions (EN1991-1-4) recommended procedure. Ishii et al. (2005)numerically calculated the actual house shapes. They showed that the quality of predictionof wall surface wind pressure distribution of various buildings was improved by applyingRNG and Durbin turbulent models.

In this paper, results will be introduced from the wind tunnel test and computersimulation on the effect of the wind load generated from high-velocity winds like typhoons,for the station buildings mentioned above. The wind tunnel test was carried out atPOSTECH, and the computer simulation was performed with a commercial CFD code,STAR-CD (CD-Adapco, 2006).

2. Wind tunnel test

POSTECH’s subsonic wind tunnel (POSWIT, Fig. 1) was used to measure the wind loadon the scaled station models. The construction of the POSWIT began in 1993 and wasinaugurated in November 1995. The POSWIT provides a large-sized test section and highflow quality with a large contraction ratio (9:1). The wind pressure was measured with aPSI8400 electric pressure scanning system for 320 pressure taps. The measurement range ofpressure was about 5000 Pa and the accuracy of the system was within 0.05% (2.5 Pa) offull scale. The scan rate reached 20,000 readings/s. The specifications of the wind tunnel aresummarized in Table 1, and Fig. 2 shows the schematic diagram of the measurementequipment mounted in the wind tunnel and dimension of the systems. The tested modelshave a 1/400 reduced scale and 320 pressure taps of which the inside hole diameter is 1mm.The turntable under the station model controls the wind yaw angle and the Pitot tubeabove the model measures the reference static pressure. The measured data are recordedwithin 10 s and the averaged pressure coefficient is stored in the computer. Generally,

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Fig. 1. POSTECH subsonic wind tunnel (POSWIT).

Table 1

The specifications of the wind tunnel

Type Closed/open type circuit wind tunnel

Size of test section 1.8 W� 1.5 H� 4.3 L (m), closed typeOverall dimension of wind tunnel 14 W� 6 H� 37 L (m)Maximum wind velocity 75m/s

Minimum wind velocity 5m/s

Contraction ratio 9:1

Flow uniformity 0.25%

Turbulent intensity 0.2%

N. Hur et al. / J. Wind Eng. Ind. Aerodyn. 96 (2008) 2042–20532044

dynamic viscosity of the air in the wind tunnel is equal to that of natural wind, thus thesimilarity is satisfied when the product of characteristic length and flow velocity is the samebetween the scaled model and the real structure. In the present study, the model is scaledby 1/400; hence, the wind velocity of the wind tunnel is 400 times faster than in a realsituation. However, it is well-known that the pressure coefficients are velocity independentwith turbulent flow. Therefore, we compared the pressure coefficient between the scaledand the computational model.

3. Numerical simulation

The commercial CFD code STAR-CD is used to solve the continuity Equation (1) and3-D RANS Equation (2). To express the realizable turbulence, a high Reynolds number

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Fig. 2. Schematic diagram of measurement equipment mounted in the wind tunnel.

N. Hur et al. / J. Wind Eng. Ind. Aerodyn. 96 (2008) 2042–2053 2045

k–e model (3), (4) was selected. Of course, the standard k–e model has disadvantages suchas the overestimation of wind pressure coefficient and turbulent kinetic energy on thewindward surface. However, it is known that the k–e model is practical to use generally,because this method is inexpensive and is used widely for complex building models:

qrqtþ q

qxjðrujÞ ¼ sm (1)

qruiqtþ q

qxjðrujui � tijÞ ¼ �

qpqxiþ si (2)

qqtðrkÞ þ q

qxjrujk � mþ

mtsk

� �qkqxj

� �¼ mtðpþ pBÞ � r�

� 23

mtquiqxiþ rk

� �quiqxiþ mtPNL (3)

qqtðr�Þ þ q

qxjruj�� mþ

mts�

� �q�qxj

� �¼ C�1

�

kmtP�

2

3mt

quiqxiþ rk

� �quiqxi

� �þ C�3

�

kmtPB

� C�2r�2

kþ C�4r�

quiqxiþ C�1

�

kmtPNL (4)

where t is the time, xi is the Cartesian coordinate (i ¼ 1,2,3) and ui is the absolute fluidvelocity component in direction xi. Also, p is the piezometric pressure, r is the density, tij isthe stress tensor components, and sm and si are the mass and momentum source,respectively. In Eqs. (3 and 4), k is the turbulent energy, e is the dissipation rate, and the mtis the turbulent viscosity. Pressure–velocity coupling is taken care of by the SIMPLEalgorithm (Patankar and Spalding, 1972) and pressure interpolation is second order (Rhieand Chow, 1983). Second-order discretization schemes are used for both the convectionterms and the viscous terms of the governing equations. Numerical simulation was

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Table 2

Representative simulation cases

Case # Velocity of wind (m/s) Yaw angle (deg) Attack angle (deg)

1 30 0 0

2 30 45 0

3 30 90 0

4 30 0 15

5 40 0 0

6 40 45 0

7 40 90 0

8 40 0 15

9 50 0 0

10 50 45 0

11 50 90 0

12 50 0 15


calculated using the SGI ORIGINE machine (R10000CPUx4, 512MB RAM, 18GB HDD,Cheonan-Asan, Daejeon, and Gwangmyeong station) and Linux cluster (Dual Intel Xeon2.4GHz CPUs, 13 Nodes, 25GB RAM, 1.86TB HDD, Gyeongju station). Therepresentative simulation cases are listed below in Table 2. As occasion demands, thecases can be added. The ambient pressure boundary is assigned to the exterior surface ofthe domain and the inlet velocity boundary is used to represent the typhoon velocity. Thecomputation time takes 4 h using 1 node of the Linux cluster.

4. Results and discussion

4.1. Cheonan-Asan station

Cheonan-Asan station is the first station designed for high-speed trains in Korea. Fig. 3shows the drawings of the station buildings. The shape of the roofs looks like airfoils, andthey seem unsafe under high wind speeds. First, the wind tunnel test for a scaled model andthe computer simulations are undertaken to study the effects of a typhoon using the above-described system. Subsequently, the numerical simulation is performed under the sameconditions. Fig. 4 presents the computational mesh for typhoon effect simulation. About750,000 meshes are used for the simulation. In the figure, the top-left side is the wholedomain, and the lower-right side is the solid cell of the station.The comparisons between the two results for the distributions of the pressure coefficients

(5) at the two sections of the roofs (section B is the center of the roof, section D is theposition between center and end of the roof) are shown in Fig. 5:

Cp ¼p� p11=2 rU2

(5)

where Cp is the pressure coefficient, p the pressure, U the velocity of wind, and subscriptNthe ambient. They show good agreement in the magnitudes and profiles for the pressurecoefficients. Thus, the result of the computer simulation can be considered reliable. Fig. 6shows the velocity vector distributions around the station and the roof when the windblows at 40m/s. The velocity over the roofs is faster than under the roofs. Also, the

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Fig. 3. Drawing of Cheonan-Asan station.

Fig. 4. Computational domain of Cheonan-Asan station.

Fig. 5. Comparison of pressure distributions results between wind tunnel test and CFD simulation.


pressure distribution in Fig. 7 shows higher pressures on the upper side of the roofs andlower pressures below the lower side. Therefore, lift forces are expected to act upon theroofs.

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Fig. 6. Velocity profiles around the roof & station.

Fig. 7. Pressure distribution on the roofs.


4.2. Daejeon station

The wind tunnel test of a scaled model and computer simulations are carried out tostudy the effects of a typhoon on the Daejeon station. The directions and magnitudes ofthe wind velocity for the simulation were determined from climate data taken over the last50 years. For the safety of the passengers and the facilities in the platform, the velocity andpressure data are obtained and analyzed. Fig. 8 shows the 1/400-scaled model in the windtunnel, and the drawings of the roofs of the station building are shown in Fig. 9. Thepressure coefficient distributions on the roof from the wind tunnel test are compared withthose of the computer simulations. The positions of peak values show good agreement inFig. 10. In the figure, the hollowed symbol (U) denotes the experimental results, and thesolid symbol (Uni, ABL) represents the numerical values. In addition, Uni and ABLdenote uniform velocity conditions and atmospheric boundary layer conditions,respectively. From the results, the computer simulation shows good results and reliability.

4.3. Gwangmyeong station

The wind loads for the roofs and walls of the station buildings are estimated by the windtunnel tests and the computer simulations, and the results are compared. Fig. 11 shows the

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Fig. 8. Wind tunnel scaled model of Daejeon station.

Fig. 9. Various roof shapes of Daejeon station.


cross-section drawing of Gwangmyeong station, and Fig. 12 shows the computationalmeshes. As mentioned in Section 4.1, the top-left side of the figure is the whole domain,and lower right is the solid cell of the station.

Fig. 13 shows the scaled model for the wind tunnel tests. The result from the wind tunneltest is compared with that from the computer simulation in Fig. 14. The distributions ofthe pressure coefficient show good agreement, thus the numerical results can be used todesign the proper roof shape.

4.4. Gyeongju station

From the results of the above three cases of stations, the numerical method isthoroughly validated. Therefore, for Gyeonju station, only the numerical simulation isperformed. A total of 18 cases, including the effect for the various velocities and directionsof the wind, are simulated by CFD. In this paper, only one case is presented. Fig. 15 showsthe drawings for the station building. Fig. 16 shows the computational meshes from the

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Fig. 10. Pressure distribution on roof 1 of Daejeon station.

Fig. 11. Cross-section drawing of Gwangmyeong station.

Fig. 12. Computational domain of Gwangmyeong station.


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Fig. 13. Wind tunnel scaled model of Gwangmyeong station.

Fig. 14. Comparison of pressure distributions results between wind tunnel test and CFD simulation.

Fig. 15. Drawing of Gyeongju station.


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Fig. 16. Computational domain of Gyeongju station.

Fig. 17. Velocity vectors at the central cross-section of Gyeongju station.

Fig. 18. Pressure contours at the central cross-section of Gyeongju station.


drawings. The total number of meshes is about 4.2 million solid structures and the roofused 0.45 million meshes. The velocity distributions around a central cross-section of thestation for the 35m/s of wind velocity are shown in Fig. 17. The velocities around roofs arefast, but those around the platform are slow due to the wind barrier. The pressuredistribution for the same case as shown in the previous figure is depicted in Fig. 18. The

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integration of the pressure around the roof gives the total wind load acts on the roof. Thatvalue is used to design the structure of the roofs and the station building.

5. Concluding remarks

In the present study, numerical simulations of wind load on Korean high-speed train(KTX) stations are presented. The numerical the results are compared to results from windtunnel tests, and showed good agreement on wind load distribution. From the presentstudy, it is believed that CFD can be successfully applied to the prediction of wind loads onhuge and irregularly shaped buildings, whose wind tunnel tests are expensive. Hence abroad application of CFD on wind load is expected in the field of civil and architecturalengineering.

Acknowledgments

This research was financially supported by the Korea High Speed Rail ConstructionAuthority (Currently Korea Rail Network Authority) and Ministry of Construction &Transportation of Korea. Authors wish to thank the authorities for their kind support.

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Blackmore, P.A., Tsokri, E., 2006. Wind loads on curved roofs. J. Wind Eng. Ind. Aerodyn. 94 (11), 833–844.

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dimensional parabolic flows. Int. J. Heat Mass Transfer 15, 1787–1806.

Rhie, C.M., Chow, W.L., 1983. A numerical study of the turbulent flow past an isolated airfoil with trailing edge

separation. AIAA J. 21, 1525–1532.

Tamura, K., Ohkuma, T., Okada, H., Kanda, J., 1999. Wind loading standards and design criteria in Japan.

J. Wind Eng. Ind. Aerodyn. 83 (3), 555–566.

Wind load simulation for high-speed train stationsIntroductionWind tunnel testNumerical simulationResults and discussionCheonan-Asan stationDaejeon stationGwangmyeong stationGyeongju station

Concluding remarksAcknowledgmentsReferences

Wind load simulation for high-speed train stations · 2012. 4. 26. · Journal of Wind Engineering and Industrial Aerodynamics 96 (2008) 2042–2053 Wind load simulation for high-speed

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