Polyurethane grouting can be used for antiseepage and reinforcement in underground construction. Understanding the diffusion characteristics of polyurethane grout is critical for good grouting design. However, the influence of water pressure on the diffusion of polyurethane grout is not clear. The aim of this work is to experimentally investigate the diffusion behavior of polyurethane grout in a water-bearing fracture. A series of laboratory experiments was conducted using a self-designed visual fracture grouting device under different conditions. The influences of grouting quantity and water pressure on grout diffusion distance and flow field are discussed. The results show that grout expansive diffusion and the pressure field change of the grout–water system have a phased characteristic. Also, the change of grout pressure is not synchronized with grout diffusion distance. The grout diffusion radius increases with the increase of grouting quantity, but decreases with the increase of hydrostatic pressure. The study helped gain insight into the performance of polyurethane grouting in fracture under static water condition.

The rapid detection of asphalt content in asphalt mixture is of great significance to the quality evaluation of asphalt pavement. Based on the dielectric properties of an asphalt mixture, the prediction model of asphalt content is deduced theoretically using three types of dielectric models: Lichtenecker‐Rother (L‐R) model, Rayleigh model, and Bottcher equation. Under the condition of laboratory mixing at room temperature (about 20–25°C), a dielectric test of asphalt mixture is conducted to verify the applicability of the model. The test results indicate that the dielectric constant of the asphalt mixture is inversely proportional to the asphalt content and directly proportional to the aggregate size of the mixture. Among the models, the Rayleigh model has a wide range of applications and exhibits a high accuracy, with an average relative error of only 1.86%. The results provide a theoretical basis for the nondestructive testing of asphalt pavements using ground‐penetrating radar.

This study aims to address the problem that loose damage of the pavement base course cannot currently be quantitatively identified, and thus the classification and recognition of the extent of looseness mainly rely on empirical judgments. Based on the finite‐difference time‐domain (FDTD) method, a backpropagation (BP) neural network identification method for loose damage of a semirigid base is presented. The FDTD method is used to simulate a semirigid base road model numerically with different degrees of looseness, and the eigenvalue parameters for recognition of the presence and extent of the looseness of the base layer are obtained. Then, a BP neural network identification method is used to classify and identify the loose damage of the base course. The results show that the classification and recognition of simulated electromagnetic waves have an accuracy of over 90%; the classification and recognition of radar data from an actual project have a recognition accuracy of over 80%. The good agreement between the classification and recognition results for the simulated data and measured data verifies the feasibility of the classification and recognition method, which can provide a new method for the use of ground‐penetrating radar to detect loose damage and the extent of looseness in the base.

To improve the service life of a semirigid base asphalt pavement and prolong its service cycle, it is imperative to conduct long‐term performance research before and after pavement disease repair. This study proposes a fatigue damage model for pavement and polymer materials and uses the finite element method to establish a three‐dimensional numerical model of a semirigid base asphalt pavement structure. Moreover, it compares and analyzes the mechanical response and fatigue damage of this pavement before and after polymer repair. The evolution law is verified by indoor fatigue tests. The results show that, under a standard load of 0.7 MPa, the vertical displacement and the Mises stress of the vacant position after the polymer repair are reduced by 61% and 69%, respectively. Under a cyclic load of 1.2 MPa, the number of load actions increases from 500,000 to more than 5 million, and the fatigue damage factor of the polymer is reduced by 29%. With the increase in the number of fatigue test loads, the cumulative evolution trend of the fatigue damage is basically consistent with the results of the numerical simulation, which verifies the rationality of the numerical model. This research is relevant for providing a reference for extending the service life of expressways and improving the technical level of expressway maintenance.