Research on Engineering Structures and Materials

1-18

Authors: Oktay Demirdag, Bulent Yildirim

In this study, two approaches having different characteristics, one being Transfer Matrix Method (TMM) that reduces computational effort and time by reducing the dimension of the considered matrix to four for all problems and the other being The Adaptive Network based Fuzzy Inference System (ANFIS) used in The Fuzzy Logic Toolbox of Matlab software that again needs less computational effort and time are compared in the free vibration analysis of Timoshenko columns with attached masses having rotary inertia. The governing equation of the column elements is solved by applying the separation of variables method in the TMM algorithm. The same problems are solved, also, by fuzzy-neural approach in which ANFIS model is used by establishing Neuro Fuzzy Frequency Estimation (NFFE) models. Natural frequencies for the first three modes of an elastically supported Timoshenko column with 1, 5 and 10 attached masses are computed using NFFE models, and the results are compared with the ones of TMM. The comparison graphs are presented in numerical analysis to show the effectiveness of the considered methods, and it is resulted that neuro-fuzzy approach may give encouraging results for these kinds of models having great number of attached masses.

29-37

Authors: Serdar Carbas, Mehmet Polat Saka

Sustainable development in construction industry is emerging as a major issue among cities and communities in the current century. As global climate change becomes an increasingly serious concern for the future and construction industry dependence on fossil fuels for energy creates greater adverse influence on human health and natural environment, an interest in high-efficient, low environmental impact buildings has begun to transform the notion of building design, construction, and operation. As it stands, the most of the standard buildings in the world consume an extraordinary amount of resources while taking an enormous toll on the environment. The utilization of cold-formed thin-walled open steel sections in structural sites supplies green structural opportunities demanding less material and cost while providing high strength. The developed algorithm for this study obtains the optimum geometric dimensions of cold-formed thin-walled open steel sections under various external loading. Moreover, this design algorithm takes into account of the effect of geometric nonlinearity as well as effect of warping. Also the displacement and stress constraints are included in the formulation of the design problem. The optimum design problem obtained turn out to be mixed integer and discrete programming problem. Artificial Bee Colony (ABC) algorithm is used to obtain its solution. This technique is a recent numerical optimization technique which mimics the intelligent behavior of honey bee swarm. The recent studies with the ABC method have shown its effectiveness and robustness in finding the optimum solution of combinatorial optimization problems. A design example is included to demonstrate the efficiency of the optimum design algorithm developed.

49-59

Authors: M. Evren Toygar, Onur Sayman, Uğur Kemiklioğlu, Hasan Öztürk, Zeki Kıral, Farshid Khosravi Maleki

In this study, a stress analysis and free vibration analysis were carried out for a curved sandwich composite beam. The curved composite beam was manufactured using glass fibers and vinylester resin. The polyvinylchloride (PVC) foam was preferred in the manufacturing of the sandwich composite beam for obtaining desired structure. The effect of the root and vertical cracks on the stress distribution and critical buckling loads for a curved composite sandwich beam were investigated numerically. The vibration analysis was performed experimentally and numerically. Experimental and numerical results were in a good agreement for the in-plane vibrations. It was seen that, the critical buckling forces changed not uniformly for the transverse crack and also, buckling loads decreased with increasing root crack length.