This study presents a novel approach to simulating the fatigue stress spectra of short- to medium-span bridges under stochastic and dynamic traffic loads. The stochastic traffic load is simulated based on the weigh-in-motion (WIM) measurements of a heavy-duty highway bridge in China, and the dynamic effects are modeled using a vehicle-bridge coupled vibration system. An interpolation RSM is used to approximate the effective stress ranges of a bridge with respect to road roughness conditions, gross vehicle weights, vehicle configurations, and driving speeds. The RSM provides a platform for an efficient spectrum simulation of bridges under stochastic and dynamic traffic loads. A case study of a simply supported T-girder bridge demonstrates the effectiveness and efficiency of the proposed approach. The proposed computational framework provides an effective approach for simulating the fatigue stress spectra for short- to medium-span bridges with WIM data. However, the efficiency of the approach depends on the number of intervals of driving speed and gross vehicle weight in the interpolation RSM. Additionally, overloading control has a considerable influence on the probability density of the high-amplitude stresses in the fatigue stress spectrum. Even a relatively high overloading limit value will considerably increase the fatigue reliability of a bridge. In addition, the numerical results provide a theoretical basis for bridge deck retrofitting and truck overloading control measures.

The determination of the non-loading condition of the rail cable shifting (RCS) system, which consists of the main cables, hangers, and rail cables, is the premise of girder erection for long-span suspension bridges. An analytical form-finding analysis model of the shifting system is established according to the basic assumptions of flexible cable structures. Herein, the rail cable is discretized into segmental linear cable elements and the main cable is discretized into segmental catenary elements. Moreover, the calculation and analysis equations of each member and their iterative solutions are derived by taking the elastic elongation of the sling into account. In addition, by taking the girder construction of the Aizhai suspension bridge as the engineering background, a global scale model of the RCS system is designed and manufactured. The test system and working conditions are also established. The comparison between the test results and analytical results shows the presented analytical method is correct and effective. The process is simplified in the analytical method, and the computational results and precision satisfy practical engineering requirements. In addition, the proposed method is suitable for application in the computation analysis of similar structures.

Cracking is one of the main diseases of small- and medium-span reinforced concrete (RC) bridges. It is a key problem to determine the change in mechanical properties of RC beams after cracking in bridge-performance evaluation. The present study performs static loading tests on seven simply supported T-beams with different crack damage conditions. The influences of crack location, crack depth and steel-bar diameter at a prefabricated crack on the stress, deflection and crack distribution pattern of pre-cracked test beams are investigated. The failure mode and mechanism of pre-cracked beams are revealed. Based on the experimental results, a finite element model of a pre-cracked beam is developed and validated. Following this, a theoretical prediction method is proposed to calculate the ultimate load of pre-cracked RC beams. The results indicate that the direct damage to mid-span section size can significantly affect the stiffness of the RC beam. The local damage of the tensile steel section has insignificant influence on the overall stiffness of the beam. The stiffness degradation of the pre-cracked beam at the quarter span is smaller than that of the pre-cracked beam at mid-span. The strain of the T-beam section in the pre-cracked test conformed to the assumption of the flat section. The experimental observations are in good agreement with the theoretical predictions, which can provide a theoretical basis for the performance evaluation of existing RC beams.

An optimization method of temperature measurement point layout for steel-concrete composite bridges based on the total least squares improved piecewise Douglas–Peucker (TLS-IPDP) algorithm was proposed to solve the problem that the traditional temperature measurement data cannot reflect the actual temperature gradient (TG) due to the position of measurement points on different paths is not reasonable. The characteristic curves of TG for the most unfavorable period and annual period are extracted from the finite element model. The rationality of the proposed method is illustrated by two typical steel-concrete composite beams with steel plates and steel boxes. By improving the classical Douglas–Peucker (DP) algorithm, the TLS-IPDP algorithm proposed in this paper has a better approximation effect on the original data. Compared with the traditional temperature measuring point arrangement method, the TLS-IPDP algorithm optimized arrangement in this paper realized the measuring point arrangement with different variable spacing under different paths; the temperature gradient curve obtained was closer to the real temperature distribution, and had higher accuracy in the region with a large gradient. In addition, the proposed method has the function of manually specifying the location of feature points and reserving the required number. The optimized arrangement of measuring points can meet the requirements of measuring points number and measurement accuracy. The method presented in this paper can provide a useful reference for temperature data acquisition and sensor layout for health monitoring of steel-composite bridges.

The rail-cable-shifting-girder (RCSG) technique is a new erecting method for the main girders of the long span suspension bridge in rural mountain areas with poor transportation and no navigable rivers for carrying large components. The pseudo-static analysis of the shifting-girder process for this girder erecting technique is performed. The global mechanical model of the double-layer cable system in the shifting-girder process is established, by analytically modeling the main-cable, rail cable, and slings according to cable’s basic assumptions. Based on the flexible cable theory, the main-cable segments are simulated as segmental catenary elements, the slings are considered as straight cable elements, the rail-cable segment that the shifting-girder trolley is moving on is simulated as multiple straight cable elements and other rail-cable segments are considered as single straight cable elements. The solving program is developed to obtain the pseudo-static responses including the forces and deflections of the shifting-girder system undergoing girder loads. Meanwhile, a global indoor reduced-scale model of shifting-girder system is designed to validate the presented theoretical results, by taking the Aizhai suspension bridge as engineering background. The results from the presented theoretical method match well with the measured experimental results of the indoor model test. The forces and deflections of the main-cable, rail-cable, and slings for the 21 working cases of erecting girder segments exhibit some specific distribution regularities. The presented theoretical method is able to correctly and effectively solve the pseudo-static responses of the RCSG system undergoing girder loads for the long span suspension bridge adopting the construction method of the RCSG technique.

Crack type classification in concrete structures is essential for assessing structural integrity, yet traditional visual inspections and RA–AF parameter-based Acoustic Emission (AE) methods suffer from subjectivity and limited ability to capture temporal signal dependencies. This study proposes TemporalAE-Net, a self-attention-based machine learning framework designed to classify tensile and shear cracks while explicitly incorporating the temporal evolution of AE signals. AE data were collected from axial tension tests, shear-failure tests, and four-point bending tests on reinforced concrete beams, and a sliding-window reconstruction method was used to transform sequential AE signals into two-dimensional temporal matrices. TemporalAE-Net integrates one-dimensional convolution for local feature extraction and multi-head self-attention for global temporal correlation learning, followed by multilayer perceptron classification. The proposed model achieved an accuracy of 99.72%, outperforming both its ablated variants without convolutional or attention modules and conventional time-series architectures. Generalization tests on 12 unseen specimens yielded 100% correct classifications, and predictions for reinforced concrete beams closely matched established crack-evolution patterns, with shear cracks detected approximately 15 s prior to visual observation. These results demonstrate that TemporalAE-Net effectively captures temporal dependencies in AE signals. Moreover, it provides accurate and efficient tensile–shear crack identification, making it suitable for real-time structural health monitoring applications.