Owing to great environmental benefits, end-of-life waste tires are often used in concrete as a partial replacement for aggregates. However, the use of waste tires in concrete deteriorates fundamental properties. For a better knowledge of the various characteristics of concrete with waste tires and to highlight ways to improve them, this study was conducted. For this purpose, the effect of waste tires on fresh properties such as workability, air content, and unit weight was reviewed. Moreover, the influence of waste tires on mechanical properties such as compressive strength, flexural strength, splitting tensile strength, and modulus of elasticity was discussed in detail. The durability characteristics such as water absorption and porosity, freeze–thaw, corrosion, chloride ion penetration, and carbonation resistance were critically evaluated. The application of waste tires for concrete used in roadside barriers was also reviewed and impact resistance, energy absorption, toughness, and ductility were summarized. Results indicate the slump of concrete increased with the substitution of rubber but decreased strength properties. Although the strength properties of rubber concrete are less but can be used for low-strength concrete. Furthermore, rubber particles are more elastic, flexible, less stiff, and deformable as compared to natural aggregates. Therefore, rubberized concrete is more suitable for roadside barriers. This review is expected to advance the fundamental knowledge of concrete with end-of-life tires and promote the recycling of end-of-life tires in the concrete industry.

Compressive strength (CS) and splitting tensile strength (STS) are paramount parameters in the design of reinforced concrete structures and are required by pertinent standard provisions. Robust prediction models for these properties can save time and cost by reducing the number of laboratory trial batches and experiments needed to generate suitable design data. Silica fume (SF) is often used in concrete owing to its substantial enhancements of the engineering properties of concrete and its environmental benefits. In the present study, the M5P model tree algorithm was used to develop models for the prediction of the CS and STS of concrete incorporating SF. Accordingly, large databases comprising 796 data points for CS and 156 data records for STS were compiled from peer-reviewed published literature. The predictions of the M5P models were compared with linear regression analysis and gene expression programming. Different statistical metrics, including the coefficient of determination, correlation coefficient, root mean squared error, mean absolute error, relative squared error, and discrepancy ratio, were deployed to appraise the performance of the developed models. Moreover, parametric analysis was carried out to investigate the influence of different input parameters, such as the SF content, water-to-binder ratio, and age of the specimen, on the CS and STS. The trained models offer a rapid and accurate tool that can assist the designer in the effective proportioning of silica fume concrete.

Rubberized concrete is becoming increasingly popular as a sustainable construction material due to its capacity to repurpose waste tyre rubber (WTR) and reduce the use of natural aggregates. However, experimental testing of its mechanical properties is expensive and time-consuming, emphasizing the importance of reliable predictive tools. To solve this issue, this research uses gene expression programming (GEP) and random forest (RF) models to estimate the flexural strength (FS) and split tensile strength (STS) of rubberized concrete. The development of the models were carried out using a comprehensive dataset that included 112 experimental findings and seven main input parameters. Multiple statistical metrics were used to evaluate model performance, such as R, MAE, RMSE, RAE, and RRSE. Although both models correctly predicted the strength trends of rubberized concrete, RF outperformed GEP with testing R² values of 0.9799 for FS and 0.9817 for STS, compared to 0.9183 and 0.8965, respectively. The error analysis revealed that both models’ prediction errors were within acceptable bounds, with RF models having lower error as compared to GEP. Furthermore, the proposed models were compared to previously published prediction models and outperformed them in terms of accuracy and generality. Furthermore, the Shapley Additive Explanations (SHAP) analysis applied to the dataset revealed the relative importance of input parameters on mechanical behavior. The findings show that machine learning-based techniques are successful at predicting the mechanical properties of rubberized concrete and have the potential to enhance environmentally friendly construction through the efficient reuse of WTR.

The increasing demand for sustainable concrete has encouraged the utilization of waste materials. This study investigates the combined effect of household waste ash (HWA) as a partial replacement of fine aggregate (0 to 20%) and silica fume (SF) as a cement replacement (10%). The mechanical, physical, and microstructural properties of concrete were evaluated after exposure to 250 °C for 220 minutes. Concrete workability, density, water absorption, compressive strength, splitting tensile strength, ultrasonic pulse velocity (UPV), SEM and EDX analysis were used to determine the influence of HWA. The results indicate that HWA reduced the concrete workability due to the physical properties of HWA (porous and rough texture). However, all mixes maintained acceptable workability (slump greater than 50 mm). Mechanical performance improved at optimum replacement levels. The 10% HWA increased compressive strength from 39.4 MPa to 42.5 MPa (7.8%). The maximum splitting tensile strength of 3.81 MPa (7.6% increase) was achieved at 15% HWA. SEM analysis indicates that 10-15% HWA enhanced mix densification and improved the interfacial transition zone (ITZ) through filler effects. However, excessive replacement (20% HWA) resulted in a less compact microstructure. The findings conclude that 10 to 15% HWA provides an optimum balance and produces concrete with adequate mechanical strength, a refined microstructure, and acceptable thermal stability after exposure to 250 °C.