This study examines the synergistic influence of recycled concrete aggregates (RCAs), industrial steel fibers (ISFs), recycled steel fibers (RSFs), and hybrid ISF/RSF (HSF) on the structural, durability, and environmental performance of roller-compacted concrete pavement (RCCP). Twenty mixtures were prepared with 0 and 50% RCA and fiber dosages of 0–0.9%, including plain, single-fiber, and HSF systems. Compressive, splitting tensile, and flexural strengths, as well as freeze–thaw resistance up to 300 cycles, were experimentally evaluated. Environmental performance was quantified through a cradle-to-gate life cycle assessment (LCA) covering nine impact categories and integrated with a multi-criteria decision analysis (MCDA) using the weighted sum method (WSM) and technique for order of preference by similarity to ideal solution (TOPSIS). Results indicate that 50% RCA replacement reduced compressive strength by ~21% but decreased global warming potential (GWP) by 15%. Hybrid fiber reinforcement significantly improved mechanical and durability properties, achieving up to 51% higher tensile strength and >85% strength retention after 300 freeze–thaw cycles compared with the control mix. The LCA showed notable reductions in GWP, acidification potential, and non-renewable energy demand when ISF and natural aggregates were partially substituted with RSF and RCA. The MCDA identified N50_R50_ISF0.3_RSF0.3 (50% RCA with 0.6% HSF) as the optimal mixture, achieving the highest eco-efficiency index (WSM = 0.80; TOPSIS = 0.73). These findings confirm that integrating RCA with hybrid steel fibers enhances the mechanical and durability performance of RCCP while substantially reducing environmental burdens, providing a viable strategy for low-carbon and circular pavement construction.

This study investigates the combined use of recycled concrete aggregate (RCA) and steel fibers—industrial (ISF), recycled (RSF), and hybrid ISF/RSF (HSF)—to enhance the mechanical performance, freeze–thaw durability, and environmental efficiency of roller-compacted concrete pavement (RCCP). Twenty mixtures incorporating two RCA levels (0% and 25%) and different fiber systems were tested. The results showed that, although RCA slightly reduced strength, hybrid fibers effectively compensated for this loss, improving toughness, tensile capacity, and resistance to freeze–thaw degradation. A life-cycle assessment demonstrated that substituting natural aggregates and industrial fibers with RCA and RSF lowers the embodied carbon and energy demand. A multi-criteria decision analysis identified mixtures with 25% RCA and hybrid fibers (0.9% HSF) as the most balanced solutions, combining an improved performance with a reduced environmental burden. The findings highlight hybrid fiber-reinforced, RCA-based RCCP as a practical and eco-efficient option for sustainable pavement infrastructure.

This paper presents a comprehensive study of the mechanical properties of lime-based mortar in an acidic environment, employing both experimental analysis and machine learning to model techniques. Despite the extensive use of lime-based mortar in construction, particularly for the strengthening of structures as externally bonded materials, its behavior under acidic conditions remains poorly understood in the literature. This study aims to address this gap by investigating the mechanical performance of lime-based mortar under prolonged exposure to acidic environments, laying the groundwork for further research in this critical area. In the experimental phase, a commercial hydraulic lime-based mortar was subjected to varying environmental conditions, including acidic solution immersion with a pH of 3.0, distilled water immersion, and dry storage. Subsequently, the specimens were tested under flexure following exposure durations of 1000, 3000, and 5000 h. In the modeling phase, the extreme gradient boosting (XGBoost) algorithm was deployed to predict the mechanical properties of the lime-based mortar by 1000, 3000, and 5000 h of exposure. Using the experimental data, the machine learning models were trained to capture the complex relationships between the stress-displacement curve (as the output) and various environmental and mechanical properties, including density, corrosion, moisture, and exposure duration (as input features). The predictive models demonstrated remarkable accuracy and generalization (using a 4-fold cross-validation approach) capabilities (R² = 0.984 and RMSE = 0.116, for testing dataset), offering a reliable tool for estimating the mortar’s behavior over extended periods in an acidic environment. The comparative analysis demonstrated that mortar samples exposed to an acidic environment reached peak values at 3000 h of exposure, followed by a decrease in the mechanical properties with prolonged acidic exposure. In contrast, specimens exposed to distilled water and dry conditions exhibited an earlier onset of strength increase, indicating different material responses under varying environmental conditions.