Long-term preventive maintenance planning using finite annual budgets is vital for maintaining the service performance of airport runway composite pavements. Using the pavement condition index (PCI) to quantify composite pavement performance, this study investigated the PCI deterioration tendencies of middle runways, terminal runways, and taxiways and developed prediction models related to structural thickness and air traffic. Performance jump (PJ) and deterioration rate reduction (DRR) were used to measure maintenance benefits. Based on 112 composite pavement sections in the Long-term Pavement Performance Program, this study analyzed the influences of five typical preventive maintenance technologies on PJ, DRR, and PCI deterioration rates. The logarithmic regression relationship between PJ and PCI was obtained. For sections treated with crack sealing and crack filling, the DRR was nearly 0. For sections treated with fog seal, thin HMA overlay, and hot-mix recycled AC, the DRR was 0.2, 0.7, and 0.8, respectively. To solve the multi-objective maintenance problem, this study proposed a decision-making optimization method based on dynamic programming, and the solution algorithm was optimized, which was applied in a five-year maintenance plan. Considering different PCI deterioration tendencies of airport regions, as well as PJ, DRR, and costs of maintenance technologies, the preventive maintenance decision-making optimization method meets performance and financial requirements sufficiently.

Granular materials are widely used for bases or subbases in pavement structures. They typically exhibit strong anisotropic properties which relate to stress states and particle characteristics. The conventional design procedure for flexible pavements underestimates the anisotropy of resilient moduli. This study established an anisotropic resilient modulus model for granular materials that considered gradation and particle shape characteristics. Vertical and horizontal resilient moduli of certain granular materials were measured in self-developed triaxial tests to obtain corresponding model parameters and anisotropic coefficients. Gradation and particle shape models were established to quantify the granular material characteristics, and the parameters were regressed. Particle shapes were obtained via image processing, and the ratio (η) of particle sphericity to roundness was chosen as a shape parameter. Results show that η increases with the decrease in particle size, and the average values of η for graded gravel and natural laterite are 0.54 and 0.63, respectively. The η distribution curves indicate that the proportion of relatively anisotropic particles, rather than extremely anisotropic particles, results in the differences in particle shape characteristics. The regression relationship between the anisotropic calculation parameters and the model parameters of vertical resilient modulus, gradation, and particle shape was established. Thus, the horizontal resilient modulus and the anisotropic coefficient can be predicted via conventional resilient modulus tests and gradation, and particle shape analysis. This study shows that the anisotropy of granular materials decreases with the increase in coarse particles and the uniformization of the particle size distribution, and it increases with the increase in anisotropic particles and the polarization of the η distribution.

Granite residual soil is widely employed as subgrade fill material, but its tendency to undergo wetting-induced deformation under moisture infiltration poses significant challenges to pavement stability. To address this issue, this study introduces an innovative wetting device capable of precisely controlling moisture content increase, enabling multi-step wetting tests under controlled conditions. Saturated wetting tests were also conducted using both single-line and double-line methods, and the results were compared. Pore size distribution curves for granite residual soil samples with different initial states were measured using Mercury Intrusion Porosimeter (MIP) tests. Results indicate that for both the single-line method and the double-line method, the ${\epsilon }_V$-lgp curve for samples subjected to different compaction efforts remains parallel across varying initial moisture content. The increase in vertical stress will constrain the water adsorption and swelling potential. Whereas an increase in compaction effort leads to greater swelling potential, which is mitigated by an increase in initial moisture content. By integrating the test results of the soil water characteristic (SWCC) curve, the relationship between normalized wetting deformation and matric suction is primarily influenced by the initial state of the soil sample and remains unaffected by vertical stress during multi-step wetting. Based on the test results, an empirical wetting prediction model was formulated, accounting for the influence of vertical stress, initial matric suction, and matric suction after wetting. Fitting results confirmed that the established model achieved high prediction accuracy (R² > 0.9), supporting its application in practical engineering endeavors.