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In order to enhance the efficiency of stochastic vibration analysis for train–bridge coupling systems, this paper proposes a novel approach based on the parallel adaptive enhanced (PAE)-surrogate model. First, an initial surrogate model is established to predict the extreme values of dynamic responses in the train–bridge coupling system using a small number of training samples. Second, a multipoint adaptive sampling method is employed to determine a set of new samples that provide more information. The theoretical extreme values of the dynamic responses corresponding to the new samples are calculated using parallel computing technology. Third, the surrogate model is optimized by incorporating the set of new samples and their corresponding theoretical extreme values. Finally, new samples are continuously added, and the surrogate model is enhanced until the number of training samples reaches the preset requirement. To validate the effectiveness of the proposed method, two examples are examined, encompassing analytical functions and the analysis of the wheel load reduction rate (WLRR) for trains on the bridge. The results show that the proposed PAE-surrogate model can select samples containing valuable information, significantly improving the prediction accuracy of the surrogate model without increasing the number of training samples. Additionally, the proposed method can fully exploit computational resources, thereby decreasing the number of iterations needed and increasing training efficiency. By considering a four-car CHR2 train passing through a three-span simply supported girder bridge as an example, the proposed method achieves 2.62times higher training efficiency compared to the nonparallel method.

The substructure method is applied to the dynamic analysis of a train–bridge system considering the soil–structure interaction. With this method, the integrated train–bridge–foundation–soil system is divided into the train–bridge subsystem and the soil–foundation subsystem. Further, the train–bridge subsystem is divided into the train and bridge components. The frequency-dependent impedance function of the soil–foundation subsystem is transformed into time domain by rational approximation and simulated by a high-order lumped-parameter model with masses. The equations of motion of the train and bridge components are established by the rigid-body dynamics method and the modal superposition method, respectively. Finally, the dynamic responses of the two subsystems are obtained by iterative procedures, with the influence of the soil shear velocity studied. The case study reveals that it is important to consider the effect of soil–foundation interaction in the dynamic analysis of train–bridge systems, but with the increase of the shear velocity of the soil, such influence becomes weaker.

In this paper, the vector form intrinsic finite element (VFIFE) method is presented for analysis the train–bridge systems considering the coach-coupler effect. The bridge is discretized into a group of mass particles linked by massless beam elements and the multi-body coach with suspension systems is simulated as a set of mass particles connected by parallel spring-dashpot units. Then the equation of motion of each mass particle is solved individually and the internal forces induced by pure deformations in the massless beam elements are calculated by a fictitious reverse motion method, in which the structural stiffness matrices need not be updated or factorized. Though the vector-form equations resulting from the VFIFE method cannot be used to compute the structural frequencies by the eigenvalue approach, this study proposes a numerical free vibration test to identify the bridge frequencies for evaluating the bridge damping. Numerical verifications demonstrate that the present VFIFE method performs as accurately as previous numerical ones. The results show that the couplers play an energy-dissipating role in reducing the car bodies’ response due to the bridge-induced resonance, but not in their response due to the train-induced resonance because of the bridge’s intense vibration. Meanwhile, a dual-resonance phenomenon in the train–bridge system occurs when the coach-coupler effect is considered in the vehicle model.

Traditional noise barriers are often designed only by considering its noise reduction effects, but designer ignores that it may transfer too much aerodynamic force to the bridge. In order to meet the wind resistance and noise reduction requirements of the elevated lines crossing an urban area at the same time, a new type of wind–noise barrier (NT-WNB) is proposed. The noise reduction effect is evaluated by a numerical method, and the influence of the wind–noise barriers’ rotation angle on the aerodynamic characteristics of a train–bridge system was studied by sectional model wind tunnel tests. The results show that the NT-WNB has effective noise reduction in the frequency range of 500–1600 Hz, and the noise reduction can be increased when install barriers with upward incline blade. Although an angle combination type of wind–noise barrier can optimize the lateral force and the lift of the train at the same time, which may cause high turbulence in the corresponding area. The NT-WNB can reduce the wind load of the bridge–barrier system by 22%, which is more conducive to the safety of the bridge and the barrier.

Wind barriers are important measures that guarantee the running safety of high-speed trains under crosswind conditions, however, they can change the aerodynamic coefficients of a train–bridge system and the distribution of the flow field around a train and bridge, and studies have often ignored the static wind load characteristics of wind barriers. In this paper, the effects of height and porosity on the curved and vertical fence-type wind barriers on the aerodynamic characteristics of a train–bridge system are investigated by using numerical simulation and wind tunnel test methods. The static wind loads of the two types of wind barriers are analyzed by comparing the drag coefficients and the surface wind pressure distributions. The results show that, compared with the vertical wind barrier, the curved wind barrier can reduce the drag force and moment of a train while reducing the impact of the aerodynamic forces on a bridge. The static wind load of the curved wind barrier is less than that of the vertical wind barrier, when a train is on the windward side of a bridge, the drag coefficient of the curved wind barrier is only about 35% of that of the vertical wind barrier.

Train-induced resonance of a railway bridge occurs when the train speed coincides with the primary resonance speed ($v_{\mathrm{\text{br}}}$) of the bridge, from which we can determine the sub-resonance speed as ($v_{\mathrm{\text{br}}}∕n{|}_{n=2,3}$). The primary resonance speed of a short bridge is generally much higher than the operation speeds of current high-speed trains but the corresponding sub-resonance speeds probably lie in the operation speed range. Such a resonance scenario can be observed from the vibration of a double-track bridge subjected to an eccentrically moving train, in which the deck vibration is combined by the vertical-flexural and torsional vibration modes of the bridge. Once the two modal sub-resonance speeds coincide with each other, a double sub-resonance will be developed on the bridge. In this study, an iteration-based train–bridge interaction finite element procedure will be presented to demonstrate the double resonance phenomenon. As expected, the double resonance may bring about a dramatic amplification on deck vibration. Such an excessive vibration is harmful to ballast stability and track maintenance of railway bridges.