The shape, size, and interfacial transition zone (ITZ) of aggregates significantly impact the nonlinear mechanical behavior of concrete. This study investigates concrete’s mechanical response and damage mechanisms by developing a three-dimensional, three-phase mesoscale model comprising coarse aggregates, mortar, and ITZ to explore the compressive performance of concrete. A method for simulating the random distribution of aggregates based on three-dimensional grid partitioning is proposed, where the value of each grid point represents the maximum aggregate radius that can be accommodated if the point serves as the aggregate center. Aggregates are generated by randomly selecting grid points that meet specific conditions, avoiding overlapping distributions and significantly improving computational efficiency as the generation progresses. This model effectively enhances the precision and efficiency of aggregate distribution and provides a reliable tool for studying the random distribution characteristics of aggregates in concrete. Additionally, an efficient discrete element model (DEM) was established based on this mesoscale model to simulate the compressive behavior of concrete, including failure modes and stress–strain curves. The effects of aggregate shape and maximum aggregate size on the uniaxial compressive failure behavior of concrete specimens were investigated. Aggregate shape has a particular influence on the compressive strength of concrete, and the compressive strength decreases with an increase in maximum aggregate size. Combined with existing experimental results, the proposed mesoscale model demonstrates high reliability in analyzing the compressive performance of concrete, providing valuable insights for further research on the mechanical properties of concrete.

The low-altitude technology of unmanned airborne infrared detection system is used to effectively monitor the temperature segregation in the paving stage and realize the temperature uniformity control of asphalt pavement construction. The image mosaic method can splice two images with overlapping areas together to form a panoramic image. In order to solve the problems of long time-consuming and low accuracy of aerial image mosaic algorithm, the low-temperature area of the whole pavement can be obtained quickly and accurately. In this paper, threshold segmentation technology is introduced to convert the image captured by the unmanned aerial vehicle (UAV) into a binary greyscale image so as to compensate for the mosaic error caused by temperature difference. In order to improve the efficiency and accuracy of splicing, a reference plate is used, which can provide enough feature points for splicing. Finally, the image mosaic method proposed in this paper can quickly obtain the image of the whole low-temperature area of the newly paved asphalt pavement, which has practical value and positive significance for the quality control of asphalt pavement.

To improve the structural design rationality of cement concrete bridge deck pavement systems and reduce diseases such as interlayer displacement and rutting in the early stage of bridge deck use, this paper studies the influence and law of the coupling effect of various factors of the waterproof system on the typical stress of bridge deck pavement and determines the best structure combination for the bridge deck pavement structure. A finite element model was established by using commercial software to simulate the mechanical response of different types of waterproof bonding layer, waterproof leveling layer, and impervious structure layer under different parameters. The simulation results show that when the thickness of the pavement layer was 8 cm, the maximum shear stress of the pavement layer occurred in the middle of the wearing course and the junction between layers. When the pavement layers were continuous, the maximum strain of the waterproof bonding layer with the “rubber asphalt + protective plate” structure in the transverse and longitudinal directions was the largest. When the waterproof leveling layer was cement concrete, the structure bore a large amount of stress and easily produced cracks, resulting in water damage. High-density water-based asphalt concrete with a low permeability coefficient can reduce the interlayer shear stress and effectively ensure the interlayer bonding effect. On this basis, the following bridge deck pavement structure was proposed: waterproof system + multifunctional waterproof layer + load-bearing structure layer + surface functional layer.

Concrete pavements frequently develop subsurface voids between surface and base layers during long-term service due to cyclic loading, environmental effects, and subgrade instability, which compromise structural integrity and traffic safety. Ground-penetrating radar (GPR) has been widely used as a non-destructive method for detecting such voids. However, the presence of coarse aggregates with strong electromagnetic scattering properties often introduces pseudo-reflection signals in radar images, hindering accurate void identification. To address this challenge, this study develops a high-fidelity three-phase concrete model incorporating aggregates, mortar, and the interfacial transition zone (ITZ). The Finite-Difference Time-Domain (FDTD) method is used to simulate electromagnetic wave propagation in both voided and intact structures. Simulation results reveal that aggregate-induced scattering can blur or distort reflection interfaces, generating pseudo-hyperbolic anomalies even in the absence of voids. In cases of thin-layer voids, real echo signals may be masked by aggregate scattering, leading to missed detections. GPR systems can be broadly classified into impulse, continuous-wave, and multi-frequency types. To validate the simulations, field tests using multi-frequency 2D/3D GPR systems and borehole verification were conducted. The results confirm the consistency between simulated and actual radar anomalies and validate the proposed model. This work provides theoretical insight and modeling strategies to enhance the interpretation accuracy of GPR data for subsurface void detection in concrete pavements.

Digital rock images may capture more detailed pore structure than the traditional laboratory methods. No explicit function can correlate permeability accurately for flow within the pore space. This has motivated researchers to predict permeability through the application of numerical techniques, e.g., using the finite difference method (FDM). However, in order to get better permeability calculation results, the grid refinement was needed for the traditional FDM and the accuracy of the traditional method decreased in pores with elongated cross sections. The goal of this study is to develop an improved FDM (IFDM) to calculate the permeabilities of digital rock images with complex pore space. An elliptical pore approximation method is invoked to describe the complex pore space. The permeabilities of four types of idealized porous media are calculated by IFDM. The calculated results are in sound agreement with the analytical solutions or semi-empirical solutions. What’s more, the permeabilities of the digital rock images after grid coarsening are calculated by IFDM in three orthogonal directions. These results are compared with the previously validated lattice-Boltzmann method (LBM), which indicates that the predicted permeabilities calculated by IFDM usually agree with permeabilities calculated by LBM. We conclude that the presented IFDM is suitable for complex pore space.