Sustainable Concrete with Waste Tire Rubber and Recycled Steel Fibers: Experimental Insights and Hybrid PINN-CatBoost...

The growing environmental concern over waste tire accumulation necessitates innovative recycling strategies in construction materials. Therefore, this study aims to develop and evaluate sustainable concrete by integrating waste tire rubber (WTR) aggregates of different sizes and recycled waste tire steel fibers (WTSFs), assessing their combined effects on the mechanical and microstructural performance of concrete through experimental and analytical approaches. WTR aggregates, consisting of fine (0-4 mm), small coarse (5-8 mm), and large coarse (11-22 mm) particles, were used at substitution rates of 0-20%; WTSF was used at volumetric dosages of 0-2%, resulting in a total of 40 mixtures. Mechanical performance was evaluated using density and pressure resistance tests, while microstructural properties were assessed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The findings indicate systematic decreases in density and compressive strength with increasing WTR ratio; the average strength losses were approximately 12%, 20%, and 31% at 5%, 10%, and 20% for WTR substitution, respectively. Among the WTR types, the most negative effect occurred in fine particles (FWTR), while the least negative effect occurred in coarse particles (LCWTR). The addition of WTSF compensated for losses at low/medium dosages (0.5-1.0%) and increased strength by 2-10%. However, high dosages (2.0%) reduced strength by 20-40% due to workability issues, fiber clumping, and void formation. The highest strength was achieved in the 5LCWTR-1WTSF mixture at 36.98 MPa (≈6% increase compared to the reference/control concrete), while the lowest strength was measured at 16.72 MPa in the 20FWTR-2WTSF mixture (≈52% decrease compared to the reference/control). A strong positive correlation was found between density and strength (r, Pearson correlation coefficient, ≈0.77). SEM and EDX analyses confirmed the weak matrix-rubber interface and the crack-bridging effect of steel fibers in mixtures containing fine WTR. Additionally, a hybrid prediction model combining physics-informed neural networks (PINNs) and CatBoost, supported by data augmentation strategies, accurately estimated compressive strength. Overall, the results highlight that optimized integration of WTR and WTSF enables sustainable concrete production with acceptable mechanical and microstructural performance.