Fiber can absorb asphalt binder and therefore reinforce and stabilize the asphalt mixture structure and also prevent the asphalt from the leaking, which occurs in the process of mixing and transport. In this study, three kinds of fiber (polyester fiber, polypropylene fiber, and lignin fiber) are used to evaluate the relationship between the fiber types and mechanic performance of SMA-13 fiber asphalt mixture, which is specially designed for field tests of high-speed vehicles on pavements. The micro-surface characteristics of fiber and aggregates were studied by SEM and image analysis. Marshall stability and splitting strength were used to measure the properties of the asphalt mixture. In addition, a field test, including measures for curve-section edge, curve-section center, straight-section edge, and straight-section center, was conducted to evaluate the skid resistance of the high-speed vehicles that test field pavement. The results show that the Marshall stabilities of asphalt mixture with three kinds of fibers have been improved, whereas the stability of asphalt mixture prepared by polypropylene fiber and polyester fiber particularly increased before immersion. Among the three kinds of fiber asphalt mixtures, the polyester fiber asphalt mixture has enhanced water susceptibility. Skid resistance in the field test indicated that high skid resistance and good surface-texture depth were achieved.

This study analyzed the viscoelastic properties of asphalt binders reinforced with various fibers, such as modified asphalt binder, modified asphalt binder reinforced with lignin fibers (LFs), polyester fibers (PFs), and polypropylene fibers (PPFs), using dynamic shear rheological (DSR) testing. Then, the experiment generated data on the dynamic modulus and phase angle, which described the dynamic rheological characteristics at varying temperatures. The generalized Maxwell model was employed to select the appropriate element, and the test curve was fitted into a discrete time spectrum based on the time–temperature equivalence principle (TTSP). The master curves of the relaxation modulus and creep compliance were established to predict the relaxation and creep properties of various asphalt binders. The analysis indicated that fiber-reinforced binders offer superior resistance to high temperatures and long-term deformation, while being less sensitive to temperature and having a more significant elastic characterization. The binders reinforced with PPFs and LFs exhibited superior performance in high-temperature settings and long-term durability, respectively. On the other hand, the binder reinforced with PFs displayed exceptional high-temperature elastic properties. Additionally, based on the experimental data and corresponding discussion, it appears that the 13-element GM model is more appropriate for fitting the data.

Accurate and objective evaluation of existing bridges is critical for ensuring the bridge’s safety and optimizing maintenance strategies. This study proposes an integrated Fuzzy Best and Worst Method and fuzzy comprehensive evaluation (FBWM-FCE) model to evaluate uncertainties in expert judgments and complex decision-making. A four-layer evaluation indicator system and five distinct grades for bridges were established, aligned with the JTG 5120-2004 and JTG/T H21-2011 standards. The FBWM innovatively employs triangular fuzzy numbers (TFNs) to reduce linguistic uncertainties and cognitive bias in bridge evaluation. Subsequently, by integrating FCE for multi-level fuzzy comprehensive operations, the method translates qualitative evaluations into quantitative evaluations using membership matrices and weights. A case study of Ding Jia Bridge and Jigongling Bridge validated the FBWM-FCE model, revealing Class III Bridge (fail condition), consistent with on-site inspections in the 2020 Bridge Inspection and Evaluation Report (Highway Administration of Hubei Provincial Department of Transportation). Comparative analysis demonstrated FBWM’s operational efficiency, requiring 20% fewer pairwise comparisons than AHP while maintaining higher consistency than BWM. The model’s reliability stems from its systematic handling of epistemic uncertainties, offering a high reduction in procedural complexity compared to standardized methods. These advancements provide a scientifically rigorous yet practical tool for bridge management, balancing computational efficiency with evaluation accuracy to support maintenance decisions.

Load identification is a very important and challenging indirect load measurement method because load identification is an inverse problem solution with ill-conditioned characteristics. A new method of load identification is proposed here, in which a virtual function was introduced to establish integral structure equations of motion, and partial integration was applied to reduce the response types in the equations. The effects of loading duration, the type of basis function, and the number of basis function expansion items on the calculation efficiency and the accuracy of load identification were comprehensively taken into account. Numerical simulation and experimental results showed that our algorithm could not only effectively identify periodic and random loads, but there was also a trade-off between the calculation efficiency and identification accuracy. Additionally, our algorithm can improve the ill-conditionedness of the solution of load identification equations, has better robustness to noise, and has high computational efficiency.

Reducing or degrading nitrogen oxides (NO_x) emitted by automobile exhausts has diversified ways. This paper presents a solution to degrade NO by Nano-sized titanium dioxide (Nano-TiO₂) mixed with coating materials for traffic marking on road pavements. The effect on degradation was evaluated by adopting a simple laboratory test with statistical analysis. During the test, five different contents of Nano-TiO₂, 2%, 3%, 4%, 5%, and 6%, mix with a coating material for pavement marking, followed by an interpretation of the micro mechanism of degradation effect. The results show that the pavement marking coatings mixed with Nano-TiO₂ has a good performance on NO degradation. The effect of degradation is increased with increasing the content of Nano-TiO₂ particles, however. At the same time, a peak value with about 70% of the maximum removing rate existed when applying 4% Nano-TiO₂ due to the agglomeration phenomenon for nanoparticles close to each other for adding more Nano-TiO₂. The methods to reduce agglomeration are also suggested, and a routine field test for all potential traffic coating materials is recommended in this study.