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    Experimental study on hysteric behavior of composite shear walls with steel sheets
    (Elsevier, 2021) Kisa, M. Hasim; Yuksel, S. Bahadir; Caglar, Naci
    Owing to demanding structural requirements, composite shear walls have become necessary in reinforced concrete high-rise structures subjected to earthquake forces. Composite shear walls also limit the inter-story drift angles during severe earthquakes in terms of their load-carrying system performance. Within the scope of this study, two types of shear walls were constructed on a 1:3 scale. One type is a conventional reinforced concrete shear wall having boundary zones consisting of only conventional reinforcement. The other walls tested were composite shear walls having boundary zones consisting of cold-formed steel sheets (CFSSs). The dimensions of the CFSSs used in the shear wall boundary zones were 2xL19x57x7, 4xL23x69x5, and 2xL17x49x7 (mm). The composite shear walls were tested under cyclic lateral loadings, and their behaviors were investigated. Lateral force vs. top displacement curves with envelopes were evaluated from graphs based on the measurements, and crack propagations in the element were investigated step by step. Dissipated energy, ductility capacity, and rigidity properties based on the experimental results were compared.
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    Neural network based model for seismic assessment of existing RC buildings
    (Techno-Press, 2013) Caglar, Naci; Garip, Zehra Sule
    The objective of this study is to reveal the sufficiency of neural networks (NN) as a securer, quicker, more robust and reliable method to be used in seismic assessment of existing reinforced concrete buildings. The NN based approach is applied as an alternative method to determine the seismic performance of each existing RC buildings, in terms of damage level. In the application of the NN, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN based model wasd eveloped, trained and tested through a based MATLAB program. The database of this model was developed by using a statistical procedure called P25 method. The NN based model was also proved by verification set constituting of real existing RC buildings exposed to 2003 Bingol earthquake. It is demonstrated that the NN based approach is highly successful and can be used as an alternative method to determine the seismic performance of each existing RC buildings.
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    Numerical study on the response of composite shear walls with steel sheets under cyclic loading
    (Elsevier, 2021) Olabi, M. Nadir; Caglar, Naci; Kisa, M. Hasim; Yuksel, S. Bahadir
    As an alternative to conventional reinforced concrete walls, composite shear walls have been studied recently due to their great advantages in terms of structural performance under seismic loading. Researchers usually use ready-made profiles for composite shear walls, but in this study L-shaped cold-formed steel sheets were selected for numerical analysis under lateral cyclic forces. A macroscale numerical model was developed using a fiber beam-column element with a shear spring model to reproduce the actual behavior of composite shear walls. In addition, the OpenSees-based model was verified against three experimentally tested composite shear walls and showed robust simulation ability. Moreover, in order to fully explain their effect on the performance of composite shear walls, the properties of L-shaped steel sheets were studied parametrically with the help of the numerical model in terms of thickness and yield strength. It was clear that increases in the sheets' yield strength and thickness increased the lateral load-displacement capacity of the walls. It was thought that the two factors were connected in terms of their effects, and the L-shaped steel sheet arrangement in the boundary zone had essential participation in the total response of the composite shear wall under the applied loads.