This study presents a systematic review of fatigue analysis methodologies and failure criteria for asphalt binders and mixtures employed in various cyclic fatigue testing configurations. The investigation focuses on two principal predictive approaches: phenomenological models and mechanistic frameworks, which are commonly utilized to forecast asphalt pavement fatigue life based on experimental data from different fatigue tests. A critical evaluation is conducted on the diverse failure criteria integrated within these analytical approaches, with particular emphasis on their respective merits and limitations. The current research findings reveal a notable absence of consensus regarding the precise definition of the fatigue failure criteria for asphalt materials. Furthermore, critical parameters including accuracy assessment, reliability verification, and sensitivity analysis of these failure criteria are identified as requiring enhanced research attention. This review recommends specific fatigue failure criteria classified according to fatigue testing methods and material types. This comprehensive analysis of fatigue failure mechanisms in asphalt composites aims to inform strategic refinements for future research trajectories and enhance durability-oriented pavement design practices.

Survival analysis is a data-driven approach that is widely used in various fields of biomedical prognostic research, and it is highly reliable in the processing of time-event data. This study developed a method for evaluating the service performance of bridge superstructures using the built-in acceleration sensor of smartphones and the prediction of survival analysis theory. It will be used to assist in the daily maintenance and repair of small and medium bridges. The effects of the upper load-bearing structure, upper general structure, bearings, deck paving, expansion joints, and frequency ratio on the deterioration of the bridge superstructure were investigated. The results show that the first-order vibration frequency of the bridge can be effectively detected by the built-in acceleration sensor of the mobile phone, but its low sensitivity and high output noise make it impossible to accurately detect the higher-order frequencies of the bridge. The upper load-bearing members, the upper general structure, the bearing, the deck pavement, and the frequency ratio are all related to the changing trend of the technical condition level of the bridge superstructure.

This study presents a systematic review of fatigue analysis methodologies and failure criteria for asphalt binders and mixtures employed in various cyclic fatigue testing configurations. The investigation focuses on three principal predictive approaches: phenomenological models, mechanistic frameworks, and artificial neural network implementations, which are commonly utilized to forecast asphalt pavement fatigue life based on experimental data from different fatigue tests. A critical evaluation is conducted on the diverse failure criteria integrated within these analytical approaches, with particular emphasis on their respective merits and limitations. Current research findings reveal a notable absence of consensus regarding the precise definition of fatigue failure criteria for asphalt materials. Furthermore, critical parameters including accuracy assessment, reliability verification, and sensitivity analysis of these failure criteria are identified as requiring enhanced research attention. The review proposes several innovative methodologies and criteria formulations that could potentially advance theoretical understanding in this field. This comprehensive analysis of fatigue failure mechanisms in asphalt composites aims to inform strategic refinements for future research trajectories and enhance durability-oriented pavement design practices.

Typical forms of seismic damage to laminated-rubber-bearing girder bridges in the transverse direction are falling beams, girder displacement, and bearing damage. However, the damage to piers and foundations is generally lighter. This is mainly due to slippage of the bearings. Therefore, we propose a new type of arc-shaped shear key to improve the lateral seismic performance. A 1/12-scale highway continuous-girder bridge isolated by different shear keys was tested utilizing a 4 m × 4 m shaking table with six DOFs. The seismic responses of the bridge were analyzed in terms of phenomenon, displacement, strain, and acceleration. The main girder and pier exhibited different seismic responses because the bridge had different stops. A numerical simulation based on FEM showed that the established finite element model can well reproduce the displacement time history of the main girder and the cap girder. By analyzing the finite element model, the relative displacement of the bearing under different seismic waves was obtained. A comparison between the measured and FEM responses showed that the arc-shaped shear key can well limit the displacement of the main girder and the bearing. In addition, it does not significantly amplify the seismic response of the substructure. The arc-shaped shear key dissipates more energy while limiting the displacement of the main girder, and the comprehensive seismic performance is better than that of the rubber pad shear key.

The rainfall often causes changes in the physical performance of the embankment, which leads to disasters such as embankment collapse and road surface settlement and cracking. Past research has tended to be limited to traditional embankment seepage models and is mostly based on the assumption that surface precipitation is uniform and rainfall intensity is constant. To adapt to the changes and development of the times, based on the water leakage mode of the flexibly assembled highway embankment, a new rainfall calculation model of the reinforced soil embankment is constructed and combined with the solid-fluid coupling physics theory, the sedimentation amount and slope stability of the embankment are analyzed at multiple levels, the mechanical properties of the new embankment under rainfall conditions are summarized, the factors affecting the settlement of the embankment and the stability of the slope are explored, and the reference model is provided for the construction of the new embankment, and the existing construction process is improved through multilevel cause analysis. We improve and develop the existing theoretical system to reduce the probability of road diseases, improve the efficiency of road construction, and reduce the cost of road maintenance.

The service performance of reinforced concrete bridges degrades overtime under environmental and vehicle loads. Accurate bridge deterioration analysis can provide a more scientific suggestion for the formulation of road bridge maintenance, strengthening, and reconstruction plans to ensure the operational safety of road bridges. Combined with bridge inspection data from the bridge database in Henan Province, we propose a prognostic model which is based on the Cox regression model for the service performance of newly operated highway girder bridges based on survival analysis theory. The Cox regression model can not only simultaneously analyze the effects of numerous factors on bridge survival, but also handle the presence of censored data in bridge survival data, which does not require the data to meet a specific distribution type. It shows that the decay rate of the deck system, superstructure, and substructure decreases with time in service, which is consistent with the actual decay pattern of the bridge structure. To further verify the accuracy of the model, the authors built a multilayer perceptron neural network with one hidden layer and used the cross‐entropy error as the loss function. It showed that the importance of the deck system, superstructure, and substructure to the decay of the bridge structure gradually decreased. The model proposed in this paper is highly applicable and reliable. Theoretically, bridge decay prediction at regional and network‐wide levels can be achieved if sufficient comprehensive bridge inspection data can be collected.