In this research, we present an efficient implementation of machine learning (ML) models that forecast the mechanical properties of basalt fiber-reinforced high-performance concrete (BFHPC). The objective of the present study was to predict compressive, flexural, and tensile strengths of BFHPC through ML techniques and propose some correlations between these properties. Moreover, the modulus of elasticity (ME) values and compressive stress–strain curves were simulated using ML techniques. In this regard, three predictive algorithms, including linear regression (LR), support vector regression (SVR), and polynomial regression (PR), were considered. LR, SVR, and PR were utilized to forecast the compressive, flexural, and tensile strengths of BFHPC, and the PR technique was employed to simulate the compressive stress–strain curves. The performance of the models was also determined by the coefficient of determination (R²), mean absolute errors (MAE), and root mean square errors (RMSE). According to the obtained values of R², MAE, and RMSE, the performance of PR was better than other types of algorithms in estimating the compressive, tensile, and flexural strengths. For example, R² values were 0.99, 0.94, and 0.98 in predicting the compressive, flexural, and tensile strengths using PR, respectively. This shows the higher accuracy and reliability of the PR technique compared with other predictive algorithms. Finally, we concluded that ML techniques can be appropriately applied to assess the mechanical characteristics of BFHPC.

Three-dimensional printing technology (3D printing) is becoming a more and more popular technology for aerospace, biology, medicine, mechanics, civil and other engineering fields. In civil engineering, researchers and engineers attempt to print construction materials such as concrete using 3D-printing technology. This study aims to investigate the reinforcement of concrete beams with 3D printing. To achieve this, fused deposition modeling (FDM) technology as a printing method and polylactic acid (PLA) as a material were selected. Two types of geometries were chosen to find the optimal mechanical behavior of concrete: high-performance concrete (HPC) reinforced with four types of trusses (Pratt, Howe, Warren, and Warren with vertical) and ultra-high-performance concrete (UHPC) reinforced with a hyperboloid shell structure. The compressive and tensile strengths of reinforced UHPC were examined by a three-point bending test, and reinforced HPC was examined by a four-point bending test. The results of the experiments show that hyperboloid shell structures can absorb energy, although the strength of reinforced UHPC is reduced. For example, there was a decrease of over 20% in the compressive strength and 41% in the flexural strength, but the ductility was raised. Adding the hyperboloid shell structure improved the deformability of the UHPC. When Warren and Howe trusses were added to the HPC as reinforcements, the flexural strength improved by over 26% and 4.3%, respectively. The overall results of this study show that the concrete reinforced with 3D-printed trusses was better than that with a hyperboloid shell structure.

When the geotechnical engineering projects have to be built on weak soils, problems related to bearing capacity and settlement arise. Chemical stabilization of soil using cement is a popular and effective technique that can significantly improve workability and shear strength of soil. However, very limited studies have been conducted to reveal the effect of silica fume on the engineering properties of cement-stabilized sandy soil. For this purpose, in the present study, a series of laboratory tests including standard Proctor compaction, unconfined compression and ultrasonic pulse velocity tests were carried out on sand-cement-silica fume samples. Moreover, it has been attempted to investigate the relation between ultrasonic pulse velocity and unconfined compressive strength of cemented sand containing silica fume. The cement contents were 3, 5 and 7% and silica fume contents were 0, 0.25, 0.5 and 1% by weight of dry sand. The cylindrical specimens were prepared and cured for 3, 7, 14, 28, 42 and 56 days and tested. The results show that inclusion of silica fume to cemented sand increases maximum dry unit weight, unconfined compressive strength and ultrasonic pulse velocity while decreases optimum moisture content. In addition, according to the obtained results, acceptable correlations exist between ultrasonic pulse velocity, unconfined compressive strength and stiffness.