Steel fiber reinforced concrete, compared to the conventional concrete; is a composite building material that performs much better in terms of parameters such as ductility, energy absorption capacity, fracture toughness, fatigue resistance, and the use of steel fiber reinforced concrete (SFRC) in structures has become widespread. In this study, a nonlinear finite element model (FEM) has been developed that can represent the behavior of beams produced by using steel fiber concrete subjected to impact load. For this purpose, a finite element model of beam series produced with fiber-reinforced concrete obtained from the literature was created. The ABAQUS package program was used to create models simulating the behavior. Numerical results showed that the model could successfully capture the experimental results of beams selected from the literature. In addition to simulation, a parametric study was also performed to investigate the effect of stirrups, reinforcement ratio, and drop height on the behavior of SFRC beams under impact loads. The results of the parametric study showed that increasing the fiber ratio and reinforcement ratio positively affected the behavior of SFRC beams in terms of displacement recovery.Steel fiber reinforced concrete, compared to the conventional concrete; is a composite building material that performs much better in terms of parameters such as ductility, energy absorption capacity, fracture toughness, fatigue resistance, and the use of steel fiber reinforced concrete (SFRC) in structures has become widespread. In this study, a nonlinear finite element model (FEM) has been developed that can represent the behavior of beams produced by using steel fiber concrete subjected to impact load. For this purpose, a finite element model of beam series produced with fiber-reinforced concrete obtained from the literature was created. The ABAQUS package program was used to create models simulating the behavior. Numerical results showed that the model could successfully capture the experimental results of beams selected from the literature. In addition to simulation, a parametric study was also performed to investigate the effect of stirrups, reinforcement ratio, and drop height on the behavior of SFRC beams under impact loads. The results of the parametric study showed that increasing the fiber ratio and reinforcement ratio positively affected the behavior of SFRC beams in terms of displacement recovery.

The seismic performance of reinforced concrete (RC) beam–column joints depends on both shear strength and failure mechanisms, the assessment of which remains challenging because of complex interactions among geometric, material, loading, and reinforcement parameters. This study presents a data-driven framework for assessing the shear strength and failure mechanisms of exterior RC beam–column joints. A database comprising 210 experimental specimens was systematically compiled from published studies. Seventeen input variables were selected based on structural mechanics, seismic design provisions, and previous experimental investigations. Machine learning models were developed for shear strength prediction and failure mode classification. SHAP was employed to interpret the trained models, while symbolic regression derived an interpretable design-oriented equation. On the independent test set, XGBoost achieved the highest shear strength prediction (R² = 0.973, RMSE = 40.09 kN), whereas the Support Vector Machine achieved 80.5% classification accuracy. The results indicate that the governing parameters for failure mechanisms differ from those controlling shear strength. Joint shear capacity was primarily influenced by geometric dimensions and longitudinal reinforcement ratios, whereas axial load ratio and joint transverse reinforcement had a greater influence on failure mechanisms. These findings highlight the importance of simultaneously assessing shear strength and failure mode in RC beam–column joints.

The increasing use of low-density polyethylene (LDPE) has prompted growing interest in its application as a replacement for conventional aggregates in concrete. This study investigated the effects of replacing sand with 10%, 20%, and 30% LDPE granules in concrete. Compressive strength, splitting tensile strength, flexural strength, modulus of elasticity, slump, and density tests were performed. The results showed a gradual decrease in compressive strength (from 26.91 MPa in the reference mix to 16.56 MPa with 30% LDPE), tensile strength (from 2.46 MPa to 1.84 MPa), and flexural strength (from 3.37 MPa to 2.59 MPa). Decreases were also observed in modulus of elasticity, slump, and density values. However, LDPE-substituted concretes increased their axial and lateral strain capacities, showing improvement in ductility and deformation ability. Experimental results demonstrated a delicate balance between mechanical strength and sustainability benefits. It was demonstrated that low rates of LDPE substitution could balance performance with environmental advantages. The experimental results presented in this study were combined with previous research to create a dataset. Based on this dataset, exponential models predicting the properties of LDPE-substituted concrete and mortar were proposed. The proposed exponential models outperformed existing linear models in prediction accuracy, yielding coefficient of determination (R²) values up to 0.981 and significantly reduced mean absolute percentage error (MAPE) values, ranging from 1% to 17% depending on the dataset.