Simsek, Oguz; Katipoğlu, Okan Mert; İpek, Süleyman; Güneyisi, Erhan; Güneyisi, Esra Mete

The application of rubberized concrete (RuC) in structural systems has led to the development of a novel composite system: the rubberized concrete-filled steel tube (RuCFST). The characteristics of infill materials, particularly RuC, significantly influence the structural behavior and performance of these composite systems. This study aims to evaluate the ultimate axial strength of RuCFST columns, considering rubber aggregate content up to 75% and infill concrete compressive strength up to 63 MPa, and propose artificial intelligence (AI)-based design models using deep learning (CNN, DNN, Autoencoder), machine learning (CatBoost), hybrid AI/neuro-fuzzy (ANFIS), and unsupervised neural network (SOM) to predict the ultimate axial strength. A robust dataset was compiled from the literature, comprising the results of 131 RuCFST column specimens. The experimental results underwent a comprehensive statistical assessment using various analytical methods, including Pearson correlation coefficient analysis, histogram analysis, distribution fitting curve analysis, and box-and-whisker plot analysis. Additional statistical metrics such as Kolmogorov–Smirnov, skewness, and kurtosis values were also used. Furthermore, by considering various variables covering the geometrical and material properties of the RuCFST columns, the design models were developed using AI techniques. The statistical evaluation results indicated that the compiled dataset is statistically significant and encompasses various input and output parameters. The design models developed in this study displayed varying prediction performance. However, those created using the Autoencoder and ANFIS methods showed statistically satisfactory performance in determining the load-carrying capacity of the columns.

İnce, Elif Gökçe

Two major earthquakes (Pazarcık Mw: 7.7 and Elbistan Mw: 7.6) occurred on the East Anatolian Fault Zone in Türkiye on February 6, 2023. These earthquakes caused severe destruction to structures. Türkiye's building stock mostly consists of multi-storey reinforced concrete (RC) buildings. Field investigations conducted after the Kahramanmaraş earthquakes once again revealed the deficiencies in the existing building stock. While the majority of these buildings are designed with a beam-slab system, a one-way joist slab system is frequently encountered. One way a joist slab system generally has wide and shallow beams with low stiffness. Additionally, the use of heavy non-structural materials in this slab type results in a greater building mass. In this study, damages in RC buildings with one-way joist slabs were investigated following the Kahramanmaraş earthquakes. In the design of RC buildings with one-way joist slabs, the cases of regular external beams and the use of shear walls were evaluated through numerical analysis. The analysis results show that shear walls and regular external beams significantly increase the performance of buildings with one-way joist systems. However, the use of seismic shear walls was found to be more effective in increasing horizontal rigidity.

Atlı, Sefa; Yalciner, Hakan; Kumbasaroglu, Atila; Ayaz, Yaşar; Turan, Ahmet İhsan; Bulut, H. Alperen; Naimi, Sepanta

A total of four reinforced concrete (RC) columns were tested to compare the structural capacities of RC columns produced by natural perlite aggregates and conventional concrete. The structural performance of the RC columns made from natural perlite aggregates was compared to conventional RC columns regarding the same concrete strength levels, sectional properties, and reinforcement layouts of conventional RC columns. The RC columns were tested under a combined constant axial load ratio of 30% with cyclic loading for two concrete strength levels, namely, 25 and 40 MPa. Load–displacement curves, energy absorption capacities, stiffness degradation, the moment-curvature relationship, the plastic hinge mechanism, and the ductility index were experimentally obtained at two different concrete types along with the measured stress–strain properties of the conventional and perlite concrete. The test results showed that the construction of the RC columns using only perlite may become possible in the future by providing an adequate concrete stress–strain capacity, which will be improved. Additionally, the use of natural perlite aggregates can contribute to sustainable construction practices by reducing the reliance on conventional aggregates.

Celik, Alper; Yalciner, Hakan; Kumbasaroglu, Atila; Turan, Ahmet İhsan

In the literature, only one empirical model is available as a nondestructive method for the prediction of seismic performance levels of corroded reinforced concrete (RC) columns as a function of the initial corrosion crack width at lower corrosion levels. Because of the ruptured transverse reinforcement bars at higher corrosion levels, the structural behavior may turn brittle in terms of shear failure. Therefore, in this study, higher corrosion levels for a different concrete strength level from that empirical model were studied. To do this, four RC columns were subjected to accelerated corrosion, and the widths of initial corrosion cracks were measured. The corroded RC columns were then tested under combined constant axial load and cyclic lateral displacement excursions. After the cyclic loading test, the actual corrosion levels at each reinforcement bar were obtained by extracting the reinforcement bars from the concrete. Test results showed that the prediction of seismic performance levels of corroded RC columns based on initial corrosion crack widths were limited owing to the nonlinear increase in the crack width with the increase in the corrosion levels. New empirical models were developed to predict the remaining energy capacities and seismic performance levels of the corroded RC columns.