Municipal solid waste incineration (MSWI) has been widely used due to its benefits in reducing waste and recovering energy. However, MSWI fly ash and bottom ash are increasing rapidly, causing harm to human health and the environment. This paper discussed the production process, physical and chemical properties, leaching properties, pretreatment methods, and applications of fly ash and bottom ash. By summarizing the previous literature, it is found that MSWI fly ash and bottom ash have mechanical properties similar to natural aggregate. Many beneficial attempts have been made in cement concrete aggregates, ceramic raw materials, and highway engineering materials. Due to concerns about the leaching of heavy metals in fly ash, its application in highway engineering is limited. The application of bottom ash in asphalt pavement is rare because of the side effect on the performance of asphalt mixture. Considering the solidification effect of cement on heavy metals and the low cost of fly ash and bottom ash, the application in cement‐stabilized macadam base has broad application prospects. This is beneficial to reduce the construction cost and promote the process of waste incineration, especially in developing countries.

The evolution of asphalt microstructures under thermal loading has always been a critical issue for pavement engineers. Previous researches show that phase separation will greatly affect the mechanical performance of asphalt at microscale. To analyze this important phenomenon, the conserved phase-field model is coupled with the Navier–Stokes equation to simulate the phase kinetics in this paper. The asphalt is chemically simplified to a quaternary system consisting of four chemical components: asphaltene, resin, oil, and wax. The coupled Navier–Stokes phase-field system is solved in a unified finite element framework in COMSOL software. It is observed that phase separation has a significant influence on the thermal stress distribution. Moreover, stress concentration is observed at the interfaces between different phases, which may result in microcracks. This conclusion is validated by atomic-force microscopy (AFM) experiment results.

Timely and accurately detection as well as rehabilitation of road surface defects are of utmost importance for ensuring road safety and minimizing maintenance cost. However, the variety of pavement distress types and forms makes it difficult to accurately classify and detect them. To tackle the issue, this paper proposes a novel target detection model YOLO-SST based on YOLOv5 with the improvement in pavement distress features. First, a Shuffle Attention mechanism is introduced in the feature extraction backbone network to enhance the detection ability without significantly increasing the computational cost. Secondly, we add a detection layer and embed Swin-Transformer encoder blocks into the C3 module to capture global and contextual information. Finally, to improve the model’s detection ability, transfer learning is employed on a self-made dataset called RDDdect_2023, which consists of street view images captured via a DJI Action camera mounted on the car. Experimental results demonstrate that the YOLO-SST model outperforms YOLOv5 and other target detection models in terms of accuracy, recall rate, and mAP@0.5 value for detecting pavement distresses. This confirms that the YOLO-SST model has stronger feature extraction and fusion capabilities, resulting in better detection performance.

Asphalt pavement has been widely used in the world. As the main components of asphalt pavement, the asphalt binder is crucial to the service performance and life of the road. In the past decades, numerous studies were conducted on technical performance, aging, and modification of the asphalt binder. With the development of modern technology, it was discovered that the microscopic properties, aging mechanism, and modification mechanism of the asphalt binder affect the macroscopic performance of asphalt pavement significantly. As a new emerging powerful numerical tool, the molecular dynamics (MD) simulation has been developed to study the asphalt binder material from a micro perspective. Based on the previous studies, some average asphalt binder models, fractional asphalt binder models, aged asphalt binder models, and modifier models were proposed by many researchers, which have made remarkable progress in asphalt studies; the microproperties, aging mechanism, and modification mechanism of the asphalt binder can also be analyzed using the MD simulation. Overall, the state‐of‐the‐art review provides a comprehensive view for the readers to better understand the development, establishment, and application of the asphalt molecular model.

In this paper, a diffuse interface model, namely, the phase-field model (PFM) is proposed to model asphalt concrete cracking subjected to shear loading (Mode II) at low temperature. This method describes the microstructure of asphalt concrete using a phase-field variable. To account for the growth of cracks, a nonconserved Allen-Cahn equation is adopted to evolve the phase-field variable. The whole PFM system is implemented and solved in a finite-element software program. The simulation results are then validated by semicircular bending (SCB) tests at $-20°\mathrm{C}$ and four-point bending tests at $-10°\mathrm{C}$ . It is discovered that PFM simulations of crack initiation and propagation in asphalt concrete at low temperature agree very well with the experimental results.