Reinforced concrete deep beams (RCDBs) provide significant strength and serviceability for building structures. However, a simple, general, and universally accepted procedure for predicting their shear strength (SS) has yet to be established. This study proposes a novel data-driven approach to predicting the SS of RCDBs using an enhanced CatBoost (CB) model. For this purpose, a newly comprehensive database of RCDBs with shear failure, including 950 experimental specimens, was established and adopted. The model was developed through a customized procedure including feature selection, data preprocessing, hyperparameter tuning, and model evaluation. The CB model was further evaluated against three data-driven models (e.g., Random Forest, Extra Trees, and AdaBoost) as well as three prominent mechanics-driven models (e.g., ACI 318, CSA A23.3, and EU2). Finally, the SHAP algorithm was employed for interpretation to increase the model’s reliability. The results revealed that the CB model yielded a superior accuracy and outperformed all other models. In addition, the interpretation results showed similar trends between the CB model and mechanics-driven models. The geometric dimensions and concrete properties are the most influential input features on the SS, followed by reinforcement properties. In which the SS can be significantly improved by increasing beam width and concert strength, and by reducing shear span-to-depth ratio. Thus, the proposed interpretable data-driven model has a high potential to be an alternative approach for design practice in structural engineering.

Unreinforced masonry (URM) is a construction of brick or concrete block unit that is joined together using mortar, without steel reinforcement. Because of the heterogeneous nature and difference in mechanical properties of the masonry elements, analyzing and capturing the structural behaviour of URM walls under various loading conditions is therefore complex. In recent decades, research efforts have been focused on addressing and understanding the compressive behaviour of URM walls from the experimental viewpoint. However, from the existing experimental literature, there is a significant degree of variation in the mechanical and geometric properties of URM walls, especially the comprehensive comparison of apparently equivalent test parameters, which has yet to be examined. It is therefore necessary to highlight and critically examine major results derived from the experimental literature to better understand the performance of URM walls under compressive loads. This review paper presents the assessment performance with regard to axial compressive tests on URM walls, along with comprehensive comparisons among the experimental literature findings on the basis of masonry construction methods and various influencing parameters. Emphasis in the literature has been placed chiefly on the masonry elements, design provisions, axial load, slenderness ratio, openings, and stress–strain response. Based on observations from the study, experimental development trends have been highlighted to identify and outline potential directions for future studies.

The increasing demand for eco-efficient concrete puts pressure on the industry to innovate new alternatives for its constituent materials. Coarse recycled concrete aggregates (RA) and supplementary cementitious materials (SCMs) are considered promising substitutes for coarse natural aggregates (NA) and cement, respectively. Using destructive and non-destructive testing methods, the present work aims to evaluate the effect of RA and different types of waste SCMs on the long-term performance of self-compacting high-performance concrete (SCHPC). Twenty-one mixes that were prepared with a 0.35 water-to-binder ratio were tested for their compressive strength, surface hardness, and ultrasonic pulse velocity. These tests were conducted over a two-year period at ambient temperature and again after exposure to up to 150 freeze–thaw cycles. Study findings demonstrated the possibility of developing eco-efficient SCHPC mixes using RA and waste SCMs. In addition, correlations have been introduced for predicting the compressive strength of SCHPC.

This paper aims to investigate the inclusion efficiency of straight microsteel fibers to improve the structural ductility and deformability of reinforced concrete frames to achieve progressive collapse resistance. Four RC frames’ behavior has been tested at one-third scale in the removal scenario of the middle column. To compare, two frames without steel fiber were prepared to be the control samples. Frames of 0.5% steel fiber fraction volume were also prepared. The study aims to analyze mechanical properties, crack pattern, failure mode, structural ductility, and load-displacement behavior of the frames of normal concrete (NC), together with steel fiber–reinforced concrete (SFC). Based on the findings, an enhancement was observed in the structural ductility (the increase ratio reached up to 26%), stimulated by incorporating steel fiber in the normal concrete. The frames of SFC demonstrated more deflection by 19% compared with NC frames. Steel fiber, therefore, can be utilized to enhance RC elements’ ductility as an innovative design strategy in inhibiting progressive collapse.