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To represent the structural behavior of self-compacted concrete filled steel tube composite columns under axial compression loading after high temperatures exposure, a nonlinear three-dimensional finite element analysis model has been achieved to analyze these columns using ANSYS R-15 software. An eight-node solid brick element (Solid65) is used to represent the concrete, while a four-node isoparametric shell element (Shell63) is used to represent the steel tube for the analyzed composite columns. A Newton-Raphson incremental-iterative approach is used to simulate the nonlinear solution technique. The finite element method results indicated that the predicted ultimate loads and axial deformations for the analyzed four column specimens agree well with the experimental results for normal strength and high strength concrete in static loading up to failure, and therefore, it is sufficient to model how these columns behave. The reduction in the analytical ultimate loads compared to the experimental values ranged from 11% and 16%, while the reduction in the total axial deformation values ranged from 3% to 7%. The yield patterns obtained from the analyzed composite columns under axial compressive stress are comparable to the yield patterns determined from the experimental study.

Researches available in literature interrelating neural networks to civil engineering design problems, especially for beep beams, are very rare. Therefore, an optimization algorithm is developed and verified in this study and coded using MATLAB functions to determine the optimum cost design of reinforced concrete deep beams. ACI 318-14 code method is used benefiting from iterative particle swarm optimization technique due to its efficiency and reliability. Minimizing total cost is used as the objective function in terms of four decision variables. Self-adaptive penalty function technique is used to handle constraints for each of the 300 randomly selected particles, and in each of the 50 total iterations followed for each one of four suggested deep beam design case studies. Performing all iterations is used as a stopping criteria for the developed algorithm. Comparative studies are made to show the effect of concrete compressive strength, live load scheme, and length of deep beam, on the optimum total cost and the corresponding decision variables. Results presented in the form of graphs and tables show that the loading condition has a significant effect on the total cost of deep beams. The cost increase is accompanied by deep beam length increase, height increase, longitudinal reinforcement area increase and vertical shear reinforcement area decrease. The calculated optimum cost is noticed for beam DB1, which is 1255 US$, with 1.29 m beam height, 0.01445 m 2 vertical shear reinforcement, 0.00914 m 2 horizontal shear reinforcement and 0.00238 m 2 main longitudinal reinforcement. The results show a relatively less difference in total cost between all the four beams at 4 m length compared to 8 m length. Also, a relatively mild increase in total cost is happened for beams DB3 and DB4 as the height increases, especially above 1.7 m height. As the main longitudinal reinforcement increases, cost of DB4 is affected more significantly than others, and as the vertical shear reinforcement increases, DB4 curve shows a relatively low degradation in cost.