Welded Turnout on Large-span Bridge (WTLB) is a complex multi-layer heterogeneous system and can significantly influence the service performance of High-Speed Railway (HSR). Understanding the coupling dynamic response of the vehicle and WTLB is essential. Previous research did not consider the dynamic behavior of foundations, leading to an underestimation of the vehicle-turnout-foundation coupling dynamic response, particularly when turnouts were laid on large-span bridges. This study proposes a novel modeling method that includes the foundations, to overcome the previous shortcomings by applying a rigid-flexible coupling system. In this approach, the vehicle was modeled as a rigid body sub-model in a Multi-Body Software (MBS), while WTLB was modeled as a flexible bodies sub-model using Finite Element (FE) software. The modal information from the FE model was imported into the MBS software. The two sub-models were coupled by the wheel-rail contact in the MBS environment and then the Vehicle-turnout-bridge Rigid-flexible Coupling Dynamic (VRCD) calculation model was established and it was discovered that the calculation results showed good agreement with the field test data. Through the VRCD model, the safety of the structure, the stability of the vehicle and the comfort of passengers were investigated, as well as several important infrastructure factors. The results demonstrate that this novel method provides accurate calculations and highlights the complex and significant interactions in the vehicle-turnout-bridge system.
In the field of rail transit, the UK Department of Transport stated that it will realize a comprehensive transformation of UK railways by 2050, abandoning traditional diesel trains and upgrading them to new environmentally friendly trains. The current mainstream upgrade methods are electrification and hydrogen fuel cells. Comprehensive upgrades are costly, and choosing the optimal upgrade method for trams and mainline railways is critical. Without a sensitivity analysis, it is difficult for us to determine the influence relationship between each parameter and cost, resulting in a waste of cost when choosing a line reconstruction method. In addition, by analyzing the sensitivity of different parameters to the cost, the primary optimization direction can be determined to reduce the cost. Global higher-order sensitivity analysis enables quantification of parameter interactions, showing non-additive effects between parameters. This paper selects the main parameters that affect the retrofit cost and analyzes the retrofit cost of the two upgrade methods in the case of trams and mainline railways through local and global sensitivity analysis methods. The results of the analysis show that, given the current UK rail system, it is more economical to choose electric trams and hydrogen mainline trains. For trams, the speed at which the train travels has the greatest impact on the final cost. Through the sensitivity analysis, this paper provides an effective data reference for the current railway upgrading and reconstruction plan and provides a theoretical basis for the next step of train parameter optimization.
The railway pantograph-catenary system employs a ratchet compensation device to sustain the tension of the contact wire. However, the excessive weight associated with the ratchet structure adversely affects the performance of the compensation device. An optimization design aimed at lightweight optimization of the ratchet wheel structure can enhance the system’s agility, improve material utilization, and reduce costs. This study uses a finite element model to establish an equivalent load model for the ratchet under service conditions and analyzes its load-bearing state. An optimization model was created and solved using ANSYS Workbench. The topological optimization configurations were compared under unconstrained conditions and four different periodic constraint scenarios. Following this, the structure was redesigned based on the topological optimization results, and a simulation analysis was conducted to compare the reconstructed model with the original model. The comparison results indicate that the masses of all four optimized models have been reduced by more than 10 %. Additionally, under conditions of a fully wound compensation rope, the maximum stress has decreased by over 20 %, leading to a more uniform stress distribution and improved overall performance. The topology optimization and redesign method based on periodic constraints offers a viable engineering solution for the lightweight design of the ratchet structure.
Tamping squeeze is essential for maintaining ballasted tracks. Previous studies have simulated squeezing behavior as a linear motion with a constant squeezing distance, which is unsuitable for various ballast beds in the field. This study aims to develop realistic formulas for squeezing behavior in tamping maintenance. First, a universal expression for the squeezing behavior of tamping operation was proposed through theoretical derivation. Subsequently, a custom testing method for squeezing distance with high accuracy was designed. Finally, the parameters of the universal expression were obtained from testing results using the response surface method and novel formulas for squeezing behavior were innovatively developed. This study can lead to greatly improved simulation accuracy and effective maintenance of tamping squeeze.
In High-Speed Railways (HSRs), the Train Control and Management System (TCMS) plays a crucial role. However, as the demand for train networks grows, the limitations of traditional wired connections have become apparent. This paper designs and implements a Wireless Train Communication Network (WTCN) to enhance the existing train network infrastructure. To address the challenges that wireless communication technology faces in the unique environment of high-speed rail, this study first analyzes various onboard environments and simulates several typical scenarios in the laboratory. Integrating the specific application scenarios and service characteristics of the high-speed train control network, we conduct measurements and validations of WiFi performance, exploring the specific impacts of different factors on throughput and delay.
This paper presents a miniaturized wideband high-gain microstrip end-fire antenna specifically designed for 5G-R communication applications. The antenna structure comprises a microstrip folded dipole resonator and end-fire directing units. By employing Intercalated Coupling Structures (ICS) between the folded dipole resonator and the ground plane, the resonant frequency of the antenna is shifted to lower frequencies, thereby significantly enhancing the operational bandwidth. Furthermore, the inclusion of three end-fire directing units positioned in front of the folded dipole oscillator substantially improves the antenna's end-fire gain. The designed antenna exhibits a relative impedance bandwidth of 46 % (ranging from 1.36 to 2.18 GHz), with a peak gain of 7.33 dBi at the 2100 MHz 5G-R frequency band. The overall dimensions of the antenna are 0.31λL × 0.39λL × 0.008λL, where λL denotes the wavelength at the lowest frequency. The proposed antenna demonstrates a broad operational bandwidth, rendering it suitable for 5G-R mobile communications.
The construction of high-precision urban rail maps is crucial for the safe and efficient operation of railway transportation systems. However, the repetitive features and sparse textures in urban rail environments pose challenges for map construction with high-precision. Motivated by this, this paper proposes a high-precision urban rail map construction algorithm based on multi-sensor fusion. The algorithm integrates laser radar and Inertial Measurement Unit (IMU) data to construct the geometric structure map of the urban rail. It utilizes image point-line features and color information to improve map accuracy by minimizing photometric errors and incorporating color information, thus generating high-precision maps. Experimental results on a real urban rail dataset demonstrate that the proposed algorithm achieves root mean square errors of 0.345 and 1.033 m for ground and tunnel scenes, respectively, representing a 19.31 % and 56.80 % improvement compared to state-of-the-art methods.
Amidst China's aggressive expansion of its high-speed rail network, the intersection of these lines with seismic fault zones has elevated the risk profile for high-speed rail travel. To counteract the potential dangers posed by seismic disturbances, China has introduced a comprehensive high-speed railway earthquake early-warning system. This article presents an in-depth examination of this system, encompassing aspects such as its developmental evolution, architectural design, and pivotal technologies. Furthermore, it ventures into the realm of future enhancements and developmental pathways for the system, fusing emergent findings from earthquake early warning research with advancements in artificial intelligence.