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The current research attempts to describe the association between the aerodynamic drag and flow structures induced by train running in time-averaged and time-dependant views. A ICE2 train model is used as the research object, with the flow field solved by Large Eddy Simulation (LES). The validation is carried out through comparison with existing research data, and grid independence study in terms of time-averaged and second-order statistics. Numerical results are firstly presented by description of the time-averaged near wake flow topology based on surface flow visualization. Then, the wake integration method is used both time-averaged and instantaneously to link the aerodynamic force with integrated flow quantities on different wake planes: from the time-averaged perspective, the contribution of different flow terms to total drag is presented and compared; from the instantaneous perspective, the overall wake variation tendency is linked to the fluctuating component of aerodynamic force, based on the wake convection velocity and downstream distance of wake planes. The dynamic features of flow quantities in different locations are presented, with cross-correlation method used to describe the correlation between fluctuating aerodynamic drag and wake motion. Approaches and findings presented in the current study could serve as fundamentals which support future study. • Large eddy simulation employed to solve flow field around a generic ICE2 high-speed train model. • Surface flow visualization techniques utilized to illustrate the time-averaged near wake flow topology. • Wake integration method applied to link the aerodynamic force with integrated flow quantities on different wake planes. • Dynamic features of flow quantities presented, with cross-correlation method used to describe correlation between aerodynamic drag and wake motion. [ABSTRACT FROM AUTHOR]

The pressure variations induced by a CRH380A EMU on a 2.15 m high bridge noise barrier are investigated in a field measurement. The familiar fluctuating pressure time history curves and the peak-to-peak pressure ( ΔP ) distributions attributing to the train head on the barrier surfaces are presented. A comparison of the positive head pulse pressure is made between the measurement results and the data calculated by empirical equations in EN 14067-4. Furthermore, the influences of train speed, train running lines, locations of measurement points, train marshalling length and environmental wind speed on ΔP are analysed. The results indicate as the train speed increases, the corresponding time intervals of ΔP decrease gradually, whereas their slopes become increasingly steep. For a CRH380A EMU, the aerodynamic length of the train head is between 7.63 and 7.64 m, which differs from the physical length of a realistic train with 12.00 m. Along the noise barrier from bottom to top, the ΔP values on the inner surface decrease with the increase of height, while these values on the outer surface increase. Taking the wind direction into account, the ΔP values are a little higher when the high-speed trains run against the wind direction. [ABSTRACT FROM AUTHOR]

With an increase in train speed, the aerodynamic effects caused by the train could escalate, especially for a train running in a tunnel. A number of large transient pressure waves are generated owing to the confined spaces within the tunnel, resulting in possible damage to the vehicle structure and the facilities in the tunnel. Therefore, it is necessary to study the aerodynamic performance of a train running in a tunnel. A scaled moving model test system was constructed to facilitate the simulation of the aerodynamic effects caused by a train running in a tunnel. In this study, the influence of grid density, calculation time step, and turbulence model on the pressure caused by the train entering the tunnel was analyzed, which is helpful for choosing suitable values of the aforementioned parameters to simulate the aerodynamic performance of the train in the tunnel. The impacts of Reynolds number effect on the distribution of the surface pressure and peak of pressure wave along the train, and the pressure waveform were also studied through numerical simulation on three scaled model trains (full scale, 1/8, 1/20, and 1/32 scaled). The findings aid in understanding the relationship between the Reynolds and pressure amplitude, and the results of the scaled test can be applied to a full-scale train. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the effects of oblique tunnel portals on train and tunnel aerodynamics using a 1:20 scale moving model device. Transient pressure and micro-pressure waves were measured using pressure sensors as the train model travelled through various tunnel models at a speed of 350 km/h. The mitigation physical mechanism of oblique tunnel portal on the initial compression wave was explained. Experimental results showed that oblique tunnel portals had obvious mitigation effect on- the pressure gradient and micro-pressure wave induced by the train model passing through the tunnel model. A hat oblique tunnel portal combined with a buffer structure with top holes was particularly effective. [ABSTRACT FROM AUTHOR]

Using a 1:20 scale moving model device, pressure distributions on train and tunnel surfaces, and the distribution of micro-pressure waves within 50 m of tunnel exits were investigated. In addition, the effects of train speeds on the transient pressures and micro-pressure waves were analyzed. The results revealed that the effect of the train speed on P min values was more significant than that on P max values, on the train surface. Significant differences between symmetrical measurement points located on the same cross section of the tunnel with double tracks could be observed. Moreover, similar differences between symmetrical points located on the same cross section in the streamlined zone of the model train were observed and analyzed. The pressure changes in the measurement points located on the same cross section of the train body, other than the streamlined zone, were approximately coincident. The differences between the P min values of measurement points located on different cross sections of the tunnel determined the differences between the ΔP values of these measurement points. The micro-pressure waves were approximately equal for measurement points located on the same cross section. Moreover, linearity decreased when the distance between the measurement points and the tunnel exit increased. • Pressure distribution on streamlined zone and the body of train model was measured and analyzed. • Pressure distribution on tunnel was measured and analyzed. • Distribution of the micro-pressure wave outside tunnel exit was measured and analyzed. • Effects of train speed on ΔP values of train and tunnel, and the pressure gradients were analyzed. • Effects of train speed on maximum values of micro-pressure wave were measured and analyzed. [ABSTRACT FROM AUTHOR]