Mehmet Polat Saka

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This paper explores the use of artificial neural networks in predicting the failure load of castellated beams. 47 experimental data collected from the literature cover the simply supported beams with various modes of failure, under the action of either central single load, uniformly distributed load or two-point loads acting symmetrically with respect to(More)
This paper presents particle swarm optimization based optimum design algorithm for the grillage systems. The optimum design problem is formulated considering the provisions of LRFD-AISC (Load and Resistance Factor Design, American Institute of Steel Construction). The optimum design algorithm selects the appropriate W-sections for the beams of the grillage(More)
This paper proposes a refined version of particle swarm optimization technique for the optimum design of steel structures. Swarm is composed of a number of particles and each particle in the swarm represents a candidate solution of the optimum design problem. Design constraints in accordance with ASD-AISC (Allowable Stress Design Code of American Institute(More)
Many optimization techniques have been proposed since the inception of engineering optimization in 1960s. Traditional mathematical modeling-based approaches are incompetent to solve the engineering optimization problems, as these problems have complex system that involves large number of design variables as well as equality or inequality constraints. In(More)