Three-dimensional (3D) ground-penetrating radar is an effective method for detecting internal crack damage in pavement structures. Inefficient manual interpretation of radar images and high personnel requirements have substantially restrained the generalization of 3D ground-penetrating radar. An improved Crack Unet model based on the Unet semantic segmentation model is proposed herein for 3D ground-penetrating radar crack image processing. The experiment showed that the MPA, MioU, and accuracy of the model were improved, and it displayed better capacity in the radar image crack segmentation task than current mainstream algorithms do, such as deepLabv3, PSPNet, and Unet. In the test dataset without cracks, Crack Unet is on the same level as deepLabv3 and PSPNet, which can meet engineering requirements and display a significant improvement compared with Unet. According to the ablation experiment, the MPA and MioU of Unet configured with PMDA, MC-FS, and RS modules were larger than those of Unet configured with one or two modules. The PMDA module adopted by the Crack Unet model showed a higher MPA and MioU than the SE module and the CBAM module did, respectively. The results show that the Crack Unet model has a better segmentation ability than the current mainstream algorithms do in the task of the crack segmentation of radar images, and the performance of crack segmentation is significantly improved compared with the Unet model. The Crack Unet model has excellent engineering application value in the task of the crack segmentation of radar images.

Based on the manual of macroporous noise-reducing asphalt pavement design, the indoor main drive pavement function accelerated loading test system was applied to investigate the impact of speed, loading conditions (dry and wet) and structural depth on the noise reduction of macroporous Open Graded Friction Course (OGFC) pavement, as well as its long-term noise reduction. Combined with the noise spectrum of the weighted sound pressure level, the main components and sensitive frequency bands of pavement noise under different factors were analyzed and compared. According to experimental results, the noise reduction effect of different asphalt pavements from strong to weak is as follows: OGFC-13 > SMA-13 > AC-13 > MS-III. The noise reduction effect of OGFC concentrates on the frequency of 1–4 kHz when high porosity effectively reduces the air pump effect. As the effect of wheels increases and the depth of the road structure decreases, the noise reduction effect of OGFC decreases. It indicates the noise reduction performance attenuates at a later stage, similar to the noise level of densely graded roads.

Coarse aggregate is the main component of asphalt mixtures, and differences in its morphology directly impact road performance. The utilization of standard aggregates can benefit the standard design and performance improvement. In this study, 3D printing technology was adopted to prepare artificial aggregates with specific shapes for the purpose of making the properties of artificial aggregates to be similar to the properties of natural aggregates. Through a series of material experiments, the optimal cement-based material ratio for the preparation of high-strength artificial aggregates and corresponding manufacturing procedures have been determined. The performance of the artificial aggregates has been verified by comparing the physical and mechanical properties with those of natural aggregates. Results indicate that using 3D printing technology to generate the standard coarse aggregate is feasible, but its high cost in implementation cannot be ignored. The 3D shape of the artificial aggregate prepared by the grouting molding process has a good consistency with the natural aggregate, and the relative deviation of the overall macro-scale volume index of the artificial aggregate is within 4%. The average Los Angeles abrasion loss of artificial cement-based aggregate is 15.2%, which is higher than that of diabase aggregate, but significantly lower than that of granite aggregate and limestone aggregate. In a nutshell, 3D printed aggregates prepared using the optimized cement-based material ratio and corresponding manufacturing procedures have superior physical and mechanical performance, which provides technical support for the test standardization and engineering application of asphalt pavements.

Given the dominant failure mode of steel bridge deck pavement layers, which is flexural–tensile damage, the dynamic modulus parameters conventionally determined through uniaxial compression testing are found to be inadequate for the design or performance analysis of these layers. In order to simulate the actual stress of a pavement structure under wheel load, the four-point bending fatigue test method and uniaxial compression test method are used to measure the dynamic modulus of an epoxy asphalt mixture, and the differences between the two test methods are analyzed. Furthermore, the four-point bending fatigue test is employed to investigate the dynamic modulus and phase angle properties across varying temperatures and frequencies, facilitating the creation of master curves for these properties and utilizing Sigmoidal models to correlate dynamic modulus data at diverse temperature conditions. This study delves into the influence of epoxy resin content, mixture composition, and aging on the dynamic modulus. The experimental results show that the dynamic modulus measured by uniaxial compression exceeds that obtained from bending fatigue tests, with the difference initially increasing and then decreasing as temperature rises. This discrepancy significantly impacts the mechanical calculations of pavement layers, underscoring the importance of selecting the appropriate testing method. Temperature, frequency, and epoxy resin content have pronounced effects on the viscoelastic properties of the mixtures. Specifically, as temperature increases, the dynamic modulus undergoes a decrease, whereas the phase angle exhibits an increase. Additionally, the dynamic modulus augments with an increase in loading frequency, while the phase angle exhibits varied trends with frequency shifts across different temperatures. Both the WLF and Sigmoidal models are effective in constructing master curve representations for the dynamic flexural modulus and phase angle. The incorporation of epoxy resin transforms asphalt from a primarily viscous to a more elastic material, significantly enhancing the viscoelastic properties of the mixture. Notably, mixtures with 50% and 60% epoxy resin content exhibit comparable dynamic moduli and phase angles, while displaying notably superior performance compared to those with 40% epoxy resin content. For large-scale steel bridge deck pavement, 50% epoxy resin content is recommended. Moreover, epoxy asphalt mixtures demonstrate robust aging resistance, with minimal variations in the dynamic modulus and phase angle before and after aging. The research results can enable the acquisition of dynamic modulus and phase angle data in the whole temperature domain and the whole frequency domain, and provide reliable mixed performance parameters for the study of different application environmental performance of steel bridge deck pavement.

In order to improve the prediction accuracy regarding low compaction level of asphalt pavement, this paper carries out indoor tests to detect the voids and dielectric constants of AC-13, AC-16 and AC-25 asphalt mixtures, obtaining their relationship equations via linear fitting and determining the dielectric constant judgment threshold of low compaction level segregation risk points ${\epsilon }_1$. Based on the common mid-point method, three-dimensional ground-penetrating radar is used to obtain the dielectric constant of the physical engineering test section. The researcher can draw the distribution map of the low compaction level segregation risk area according to the judgment threshold ${\epsilon }_1$ of the rough segregation risk points; divide the connected risk areas; determine the regional convex hull; and calculate the regional indicators such as the regional area, the ratio of the convex risk points and the mean value of the regional dielectric constant. The response surface analysis method is used to acquire the model of risk area index and core void ratio. The model is employed to predict and verify the core void ratio in the risk area of the road section and verify the accuracy of the model. The results show that the error range between the predicted voids and the measured voids is −0.4%~+0.4%, and the mean absolute value of the error is 0.25%. Compared with the mean measured voids of 6.63%, the relative error is 3.77%, indicating that the model can accurately predict the regional low compaction level segregation degree.

To accurately predict the relative permittivity of cement-stabilized base materials, a study on the dielectric mixing model for cracked base materials was conducted. Based on the electromagnetic mixing theory of multiphase composites, a comprehensive dielectric mixing model of cement-stabilized base materials was derived. The volume ratios and relative permittivity values of the specimen constituents in different cracking states of the cement-stabilized base were determined using industrial CT and a Percometer relative permittivity meter, with comprehensive consideration given to the effects of different initial porosities and crack widths on the dielectric properties. Based on the volumetric and dielectric properties of the base material specimens in both intact and cracked states, as well as the error analysis between the predicted and measured values of the relative permittivity constant, the u-optimal solution of the dielectric mixing model for cement-stabilized base material was determined to be 1. Consequently, an optimization dielectric mixing model for semi-rigid base course materials in a cracked state was developed. The optimization model proposed is suitable for predicting the dielectric properties of cement-stabilized base material with crack widths generally greater than 3 mm during the service life of semi-rigid base course in engineering practice.