Fine-grained dredged clay is difficult to reuse without treatment due to its high water content and weak soil structure. From a sustainability perspective, this limitation poses challenges for the beneficial reuse of dredged materials and often leads to disposal and increased demand for natural resources. In this study, the 28-day mechanical behavior of stabilized dredged clay, treated with cement or lime and modified with coir fiber, polypropylene (PP) fiber, and styrene–butadiene rubber (SBR) latex, was systematically investigated through experimental measurements, with an emphasis on resource-efficient and sustainable ground improvement. The unconfined compressive strength (UCS) results showed that the UCS of dredged clay stabilized with 4% cement was 374 kPa, and this value increased linearly with increasing cement content, reaching 2487 kPa at 16% cement. In contrast, the UCS of dredged clay stabilized with 16% lime was approximately 30% of that achieved with cement at the same dosage, at only 780 kPa, indicating the need to balance mechanical performance with the environmental impact associated with high cement usage and its carbon footprint. In addition, the inclusion of fibers significantly enhanced the UCS of the stabilized soil samples. The experimental results indicate that the UCS of specimens stabilized with 16% cement could be doubled with the addition of fibers, suggesting the potential to achieve target strength with reduced binder content, thereby contributing to a low-carbon and material-efficient design. Among the fibers tested, coir fiber exhibited better performance than PP fiber in improving UCS, highlighting the effectiveness of natural, renewable, and biodegradable materials in sustainable soil stabilization. Furthermore, fiber length also influenced the UCS of the stabilized soil samples. Additionally, the direct shear test results indicated that both fiber content and length played important roles in determining the internal friction angle of the stabilized soil. It was observed that stabilized soil reinforced with 6 mm fibers exhibited a higher internal friction angle compared to that reinforced with 12 mm fibers. These findings provide insights into optimizing material composition for improved mechanical performance while supporting environmentally sustainable and resource-efficient geotechnical practices.

This study investigates how traffic heterogeneity affects both traffic-flow efficiency and bridge structural demand using one year of road-based Weigh-in-Motion (WIM) data collected on a 60 m two-span simply supported prestressed-concrete girder bridge in Nanjing, China. The objective was to develop an integrated framework for quantifying the joint influence of vehicle composition on traffic performance and bridge load effects, and to evaluate whether operational mitigation measures can improve both mobility and structural performance. The methodology combined data preprocessing, vehicle classification, macroscopic traffic-flow modelling, statistical analysis, influence-line-based structural load-effect estimation, machine-learning prediction, and simulation-based intervention evaluation. Traffic-flow relationships were analysed using the Greenshields’s, Greenberg’s, and Underwood’s models, while XGBoost and SHAP were applied to predict and interpret traffic and structural indicators derived from the processed WIM dataset. The results showed that increasing heavy-vehicle proportion reduced traffic efficiency by lowering flow and speed and increasing density, while simultaneously increasing predicted bending moment, shear force, and fatigue-related demand. Among the calibrated traffic-flow models, the Underwood’s model achieved the lowest RMSE, while the Greenshields’s model remained highly competitive and was retained because of its simpler and more interpretable formulation. The scenario analysis further indicated that both lane management and speed harmonization reduced structural demand relative to the baseline observed traffic condition, with lane management providing the greater overall benefit. The proposed framework is intended as an analytical and scenario-based decision-support methodology for evaluating bridge traffic-management strategies under heterogeneous traffic conditions.