This study attempts to describe associated fluid dynamics of a square finite wall-mounted cylinder (FWMC) immersed within free-stream turbulent flow characterized by different turbulence intensities and integral length scales. An improved delayed detached eddy simulation method is adopted to numerically reproduce the fully developed turbulent flow fields. The results reveal that both the turbulence intensities and integral length scales have a significant effect on the separated shear layers, base pressure, and associated aerodynamic forces of the cylinder. Constrained streamlines along with critical point techniques are employed to further illustrate the influence of parameters of interest on a time-averaged flow pattern, including horseshoe vortex, surface flow, and wake topology. Distribution of second-order statistics within the wake region shows a shorter longitudinal length of the reversed flow region and enhanced vortex strength when background turbulence intensity increases. The time-dependent interaction between background turbulence and separated flow around the square FWMC is illustrated based on the phase difference between pressure of opposing side faces and the evolution of the reverse-flow region. In the end, the spectral proper orthogonal decomposition technique is employed to further investigate the effects of incoming flow turbulence on characteristics of the free-end shear flow and Von Kármán vortex shedding in the wake.

With the ever-accelerating development of information and sensor technology, plenty of data-driven fault diagnosis algorithms have shown impressive performance. However, in practical engineering scenarios, it is often difficult to obtain sufficient labeled data, and the signal fault characteristics of the bogie bearing are not obvious due to the influence of environmental noise and track excitation, which would seriously reduce the performance of the model. In this paper, we proposed a diagnostic algorithm based on a multi-information fusion technique and unsupervised representation alignment deep Q network (URADQN), to make full use of the fault information contained in each sensor and address the issue of the small sample size. Firstly, the acquired samples from several sensors are processed by a dual fusion module to dig the fault feature information from the original data; Then through unsupervised contrastive learning of similar feature representations, the URADQN is pre-trained to optimize the feature representation ability, to shorten the training time of deep Q-learning; Finally, the fault classification is realized by using the well-trained URADQN through reinforcement learning strategy. The effectiveness of the proposed algorithm is validated through two multi-sensor bearing datasets on the bogie. In comparison with other advanced methods under various data setups, the proposed algorithm demonstrates superior performance for small sample fault diagnosis.

The propagation of the weak shock wave (WSW) to the tunnel exits and their radiation as micro-pressure waves (MPWs) may cause sonic booms or structural resonance of buildings, posing potential hazards to humans, animals, and buildings in the exit's environment. The characteristics of the WSW and sonic booms of a maglev train/tube coupling model were studied based on the two-dimensional axisymmetric unsteady Reynolds average Navier–Stokes turbulence model. In the later stage of a MPW, the formation mechanism, geometry, and kinematic characteristics of compressible vortex rings (CVRs) were systematically analyzed. The inertial effect causes the initial wavefront to gradually transition from a Gaussian-shape waveform to a triangular waveform during its propagation, eventually coalescing into a WSW. The overpressure, density jump, and shock Mach number at the WSW location all increase with the increasing train speed, while the WSW thickness decreases accordingly. The formation distance of the WSW is inversely proportional to the amplitude of the initial wavefront gradient, and the WSW directly causes the occurrence of the exit sonic boom. The MPW amplitude has significant directionality with a largest value in the axial direction. Within the speed range of 450–700 km/h, the sound pressure level of the MPW exceeds the hearing threshold and even reaches the feeling threshold. The evolution of CVRs includes primary CVR, secondary CVR, and Kelvin–Helmholtz vortices. Primary CVR has the greatest impact on the axial MPW among them. The occurrence of CVRs will cause a second small noise level other than the sonic boom.

The micro-pressure waves (MPW) released from maglev tunnel portals can generate audible sonic booms and cause structural resonance in surrounding buildings, posing challenges to developing high-speed maglev trains. This paper proposes a novel porous media hood (PMH) and investigates its mechanism for mitigating the sonic booms emitted from tunnels. The numerical model employs the improved delayed detached eddy simulation turbulence model and overset grid technology, validated against data from moving-model experiments. The influences of the PMH's inherent properties and geometric parameters on MPW, flow field evolution, and aerodynamic loads on the train body were comprehensively discussed. The research demonstrates that PMH effectively dampens the initial wavefront gradient at the entrance and reduces the MPW amplitude by intensifying radiation within its exit vicinity. The porosity of 0.2 facilitates a seamless transition for the streamlined head from the ventilated PMH to the airtight tunnel. Lengthening the PMH enhances its MPW mitigation effect, whereas the impact of PMH thickness is minor. The PMH effectively diminishes the reflection intensity of compression and expansion waves at the tunnel ends, leading to a reduction in the magnitude and changing rate of train aerodynamic loads. This underscores the PMH's potential to enhance passengers' auditory comfort and alleviate issues related to train sway.

Slipstream, which is caused by the movement of high-speed trains (HSTs) and transported mainly by the outward movement with the downstream development of the pair counter-rotating vortex, has been a threat to the railway facilities and staff near the line. Although the cause and distribution of slipstreams have been widely studied, the mechanism behind slipstreams needs to be further clarified. The detailed turbulence kinetic energy (TKE) budget analysis including the advection term, production term, and turbulence transport term in the wake region of the train is conducted to reveal the formation and distribution of the slipstream. Considering the fact that the HSTs can operate in the open air and inside the tunnel, this paper compares and analyzes the effect of the blocking ratio induced by the tunnel wall on the TKE budget, as well as the aerodynamic force, slipstream, and flow structure around trains. The findings demonstrate that the tunnel wall's blocking effect does not modify the vortex-shedding process or the flow pattern around the train. However, the time-averaged (U¯slipstream) and standard deviation (σslipstream) of the slipstream in the near wake are increased because of the tunnel wall blocking effect. Meanwhile, the displacement boundary layer and the momentum boundary layer are hindered by the tunnel wall-blocking effect. The analysis of the TKE budget in the wake of HSTs shows that the total advection is primarily driven by the streamwise velocity (Axk). When the distribution Axk intersects with the measuring position on both sides of the track, the maximum value U¯slipstream and its corresponding position are determined. The turbulence transport term Tu,yk dominates the total transport of TKE and the distribution of σslipstream. The Tu,yk transfers energy from the pair of counter-rotating vortex inward into the wake region and outward away from the vortex core when the turbulent wake interacts with the undisturbed mean flow.

The high-speed trains traveling at 400 km/h will generate severe alternating pressure and potential sonic boom when passing through tunnels. This paper proposed foam metal hoods (FMH) to mitigate the pressure waves induced by trains traversing tunnels. 1:20 scaled moving-model experiments were conducted to investigate the mitigation mechanisms of FMH on micro-pressure waves (MPW), residual pressure, and aerodynamic loads on the train and tunnel. The impact of FMH's installation position and length on MPW and residual pressure were discussed. The results indicate that the entrance FMH can weaken the expansion wave generated by the tail train entering the tunnel, thereby reducing the pressure amplitude on the train surface and tunnel wall. FMH can reduce the reflection intensity of pressure waves, effectively lowering the root mean square (RMS) of residual pressure. Installing FMH at both ends can reduce the RMS of residual pressure in the middle of the tunnel by 25%. The exit FMH enables the initial wavefront to gradually release pressure outward, thereby reducing MPW intensity. The radiation range of the MPW iso-surface is narrowed by energy consumption as the wavefront passes through the porous structures. The mitigation ratio of MPW intensifies as the length of the exit FMH increases. Using a 4-m-long exit FMH can decrease the MPW amplitude by 83.2% at 20 m from the FMH exit. The FMH facilitates a low-noise environment near tunnel portals, reducing the aerodynamic loads on the tunnel structures, and mitigating the train aerodynamic loads.