The concept of digital twin (DT) has emerged as a trend in various industries development, enabling the creation of virtual models of physical objects. We conduct a systematic review of the DT technology in the field of transportation infrastructure management from the aspects of concept definition, whole life cycle application, advanced technology, and equipment utilization, as well as the challenges. We begin with an introduction that defines DT and its components, while also distinguishing it from building information modeling and cyber-physical systems. We explore the diverse applications of DT throughout its lifecycle and highlight the significance of DT in structural monitoring, infrastructure operation and maintenance, and dataset expansion. We further investigate the advanced techniques and equipment associated with DT components, focusing on the importance of virtual parts, data acquisition, transmission, multi-source data fusion processing, and data security as well as dynamic updating of models for effective integration and utilization of DT in transportation infrastructure management. We identify key challenges faced by DT in transportation infrastructure management and propose future trends in the study. This comprehensive review serves as a valuable resource for researchers, practitioners, and decision-makers in understanding the potential of DT technology in transportation infrastructure management.

In the process of heat exchange with the external environment, the internal temperature of ballastless track structure presents a nonlinear distribution. The vertical temperature gradient will cause repeated warping and deformation of track slab, resulting in mortar layer separation, which will affect driving comfort and track durability. The traditional temperature field analysis method of concrete structure based on thermodynamics has the disadvantages of too many assumptions, difficult parameter selection and too much calculation of energy consumption. In this paper, based on the finite element software ANSYS, the heat exchange was transformed into the boundary condition of heat flux, which was applied to the thermodynamic analysis model to study the nonlinear temperature distribution law of ballastless track. The accuracy of the analysis method was verified by the measured data. On this basis, the regional distribution law of temperature gradient of ballastless track under different geographical coordinates and climatic conditions was studied. By adding a regional adjustment coefficient, the vertical temperature load model of ballastless track suitable for typical areas in China was proposed. The proposed temperature load model makes up for the lack of refinement of climate division and temperature load model in relevant specifications, and has strong engineering application and popularization value.

The track–bridge interaction is a fundamental concern in the field of railway engineering, which plays an important role in the optimization design of railway bridges, especially for heavy-haul railway and high-speed railway bridges. This paper systematically introduces the research status of the CWR track–bridge interaction for large-span bridges of high-speed railway in China. The evolution process of the track–bridge interaction model from the simplest elastic bar and linear longitudinal resistance model to the complex beam–rail interaction model considering the loading history is described. In this paper, the modeling methods of the track–bridge interaction model for five types of long-span railway bridges, namely simply supported beam bridge, continuous beam bridge, cable-stayed bridge, arch bridge, and suspension bridge, are systematically introduced, and the characteristics of longitudinal force distribution under the track–bridge interaction are analyzed. This paper discusses the practical application of the theory of the track–bridge interaction on extra-large-span bridges from the aspects of system dynamic performance evaluation and system safety evaluation. The practical application of track–bridge interaction theory under special conditions such as earthquake load, complex temperature load, shrinkage and creep load, and superposition of multiple loads is emphasized. It provides guidance for the further improvement of the track–bridge interaction model and the design of large-span high-speed railway bridges in the future.

The timely identification of rail internal defects and the application of corresponding preventive measures would greatly reduce catastrophic failures, such as rail breakage. Ultrasonic rail defect detection is the current mainstream rail defect detection method thanks to its advantages of strong penetration, high accuracy, and ease to deploy. The 2D B-scan image output by ultrasonic detectors contains rich features of defects; however, rail engineers manually identify and localize the defect image, which can be time-consuming, and the image may be subject to missing identification or mistakes. This paper adopted state-of-the-art deep learning algorithms for novel B-scan images for the automatic identification and localization of rail internal tracks. First, through image pre-processing of classification, denoising, and augmentation, four categories of defect image datasets were established, namely crescent-shaped fatigue cracks, fishbolt hole cracks, rail web cracks, and rail base transverse cracks; then, four representatives of deep learning object detection networks, YOLOv8, YOLOv5, DETR, and Faster R-CNN, were trained with the defects dataset and further applied to the testing dataset for defect identification; finally, the performances of the three detection networks were compared and evaluated at the data level, the network structure level, and the interference adaptability level, respectively. The results show that the YOLOv8 network can effectively classify and localize four categories of internal rail defects in B-scan images with a 93.3% mean average precision at three images per second, and the detection time is 58.9%, 376.8%, and 123.2% faster than YOLO v5, DETR, and Faster R-CNN, respectively. The proposed approach could ensure the real-time, accurate, and efficient detection and analysis of internal defects to a rail.

Based on the 16–32 m simply-supported beam bridge on Shanghai-Kunming high-speed railway, a collision model of CRTS II track system was established. The model considered the longitudinal, horizontal as well as vertical nonlinear constraints among structural layers, and the Kelvin element was used to simulate the pounding effect of the gaps. The seismic response of the CRTS II track system was firstly analyzed and then the influences of different cases of damaged track plate, base plate, and mortar layer were discussed. The study revealed that: (1) The rail, track plate, and base plate all bear large longitudinal force and their stress envelope curves are all anti-symmetric. (2) The broken track plates result in a sharp decrease in track plate stress and an extreme increase in rail stress and base plate stress near the gap. The broken base plates result in a sharp decrease in base plate stress and an extreme increase in rail stress and track plate stress near the gap. (3) Both the pounding frequency and pounding force between broken slabs are relatively large and will decrease after some time. (4) The broken slabs near ends of the first bridge span greatly increase the pounding force of stoppers close to the abutment. (5) The gap width has a huge influence on the pounding force and times of stoppers and gaps. (6) The debonding of mortar layer has a great influence on the vertical displacement of rail, track plate, and the base plate.

In order to investigate the stress characteristics of ballastless track under high latitude, and multi-source and multi-field extreme temperature conditions. Based on the finite element theory and the elastic foundation beam–plate principle, a finite element model of the ballastless track considering the limit convex abutment, gel resin, and interlayer bonding is established. The mechanical characteristics of the ballastless track under the slab–CAM layer bonding state, mortar separation, freeze–thaw degradation and forced deformation of the foundation are studied. Considering the deterioration of materials, the bending moment and reinforcement of track structures in cold regions are checked and calculated. The studies show that under the action of negative temperature gradient load, the edge of the track slab is subjected to tension, and structural separation occurs at the edge of the slab. When the interface between the track slab–CAM layer is poorly bonded, the bearing capacity can be improved, and the amount of separation can be reduced by increasing the structural stiffness of the CAM layer. Under the action of freeze–thaw cycles, the material performance deteriorates seriously, the separation between the track structures intensifies, the baseplate is seriously powdered and cracked, and the maximum tensile stress exceeds 6 MPa. The CAM layer and the baseplate are weak structures, and the foundation frost heave occurs at the expansion joint of the baseplate, which is the frost heave condition. Under freeze–thaw deterioration, the original reinforcement design of the substructure structure does not meet the requirements of structural cracks and reinforcement yield stress. In severely cold areas, the structural reinforcement scheme should be reasonably determined.