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Research Papers: Flows in Complex Systems

Aerodynamic Effects of Inclined Portals on the Initial Compression Wave Generated by a High-Speed Train Entering a Tunnel

[+] Author and Article Information
Xintao Xiang

MOE Key Laboratory of Hydrodynamics,
Department of Engineering Mechanics,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: xtxiang@sjtu.edu.cn

Leiping Xue

MOE Key Laboratory of Hydrodynamics,
Department of Engineering Mechanics,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: lpxue@sjtu.edu.cn

Benlong Wang

MOE Key Laboratory of Hydrodynamics,
Department of Engineering Mechanics,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: benlongwang@sjtu.edu.cn

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received November 10, 2014; final manuscript received June 12, 2015; published online August 4, 2015. Assoc. Editor: Oleg Schilling.

J. Fluids Eng 137(12), 121104 (Aug 04, 2015) Paper No: FE-14-1652; doi: 10.1115/1.4030843 History: Received November 10, 2014

The micropressure wave radiated from a tunnel exit is one of the environmental problems which can be investigated from the temporal pressure gradient of the compression wave. The effects of inclined portals on the initial compression wave, specifically the maximum temporal pressure gradient, are numerically studied by solving the flow field during a high-speed train nose entering a tunnel, using the unsteady three-dimensional (3D) Euler equations. After mesh independency and temporal sensitivity tests of the numerical method, validations are conducted by comparing the numerical results with experimental and numerical data. The temporal gradients of pressure wavefront are parametrically investigated for different combinations among the train speed, the blockage ratio of the train to tunnel, and inclination angle of the tunnel entrance. The numerical results show a negligible influence of train Mach number or blockage ratio on the normalized pressure gradient and noticeable effects of inclination angle, location of the train with respect to the median line of a double-tracked tunnel (DT), and the profile of train nose. Based on the numerical results, an empirical formula is proposed to predict the relationship between the maximum pressure gradient and the inclination angle of tunnel entrance.

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References

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Figures

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Fig. 1

The compression waves generated by viscous and inviscid flows

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Fig. 2

Illustration of inclined portals and definition of inclination angle θ

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Fig. 3

Domains and boundary conditions of numerical simulations: part-A contains the train and is treated as sliding region; part-B encircles part-A and is treated as stationary domain

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Fig. 4

Mesh distributions for cases of different spatial resolutions

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Fig. 5

Influence of the grid size on the pressure gradient generated by the CRH3 train entering an ST at U = 350 km/hr; the inclination angle of the tunnel portal is 90 deg ; and the temporal resolution is δt* = 0.01

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Fig. 6

Influence of the computational time step on the pressure gradient generated by the CRH3 train entering an ST at U = 350 km/hr; the inclination angle of the tunnel portal is 90 deg; and the grid size is δL*≈0.03

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Fig. 7

Computational setup of reduced scale experiments conducted by Maeda et al. [29]: conical nose (upper); parabolic nose (middle); and elliptic nose (lower)

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Fig. 8

Histories of pressure gradients generated by the cases in Fig. 7 with one pressure sensor located inside the tunnel at 1 m from the entrance, the train speed is 232 km/hr. Present results: “...”, conical; “- -”, parabolic; “—” elliptic. Numerical results of Uystepruyst et al. [15]: “ ▵,” conical; “*,” parabolic; “∘” elliptic.

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Fig. 9

Histories of pressure gradients generated by the cases in Fig. 7 with one pressure sensor located inside the tunnel at 1 m from the entrance, the train speed is 232 km/hr. Present results: “...”, conical; “- -”, parabolic; “—” elliptic. Experimental results of Maeda et al. [29]: “ ▵,” conical; “*,” parabolic; “∘” elliptic.

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Fig. 10

Nose profile and surface mesh of the CRH3 Train of different views

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Fig. 11

Illustrations of the ST and DT (cm)

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Fig. 12

Inclined entrances, the inclination angle is 120 deg. Left: ST; right: DT.

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Fig. 13

Comparison of pressure gradients between the single-tracked and DT, U = 350 km/hr, and θ = 90 deg

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Fig. 14

Comparison of pressure gradients between the single-tracked and DT, U = 300 km/hr, and θ = 90 deg

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Fig. 15

Influences of inclined portals on the pressure gradient, for the case of ST, U = 350 km/hr

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Fig. 16

The maximum pressure gradients generated by different inclined portals. C1: the case of ST, U = 350 km/hr; C2: the case of ST, U = 300 km/hr; C3: the case of DT, U = 350 km/hr; and C4: the case of DT, U = 300 km/hr.

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Fig. 17

The relationship between normalized maximum pressure gradient and inclination angle. C1: the case of ST, U = 350 km/hr, β = 1; C2: the case of ST, U = 300 km/hr, β = 1; C3: the case of DT, U = 350 km/hr, β=1.1166; C4: the case of DT, U = 300 km/hr, β=1.1166; and E1: the empirical formula (10) with A = 3, m = 5/9, and n = 2/3.

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Fig. 18

Profiles and surface mesh distributions of short and long noses

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Fig. 19

The maximum pressure gradients induced by different train noses. N1: short-nose train entering an ST at U = 350 km/h; N2: CRH3 train entering an ST at U = 350 km/hr; N3: long-nose train entering an ST at U = 350 km/hr; F1: the empirical formula (10) with A = 4.8, m = 0.81, and n = 0.91; F2: the empirical formula (10) with A = 3, m = 0.56, and n = 0.67; and F3: the empirical formula (10) with A = 1.9, m = 0.34, and n = 0.45.

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