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Recently, Neural computing approach is applied in many area of engineering such as advanced digital computer technology, and many researches have been accomplished in optimization using neural computing approach, most of which are based on the back-propagation model. This paper shows the applicability to solve structural optimum problem using hopfield network, which is one of the artificial neural network model. Also this paper presents the computing algorithm for a researcher or engineer who can easily make a workable program on a personal computer. The program code of this paper is written by language C. Simulated annealing method which is one of the probabilistic search method is used with hopfield network. Also, several numerical examples are given to show the application of the improved artificial neural networks.
The objective of this paper is to obtain minimum-cost designs for reinforced concrete(R.C.) structures. The cost minimized includes costs of concrete, reinforcing steel and formwork. The minimum cost design of R.C. structures is subjected to constraints on strength, serviceability and durability and design variables include the cross-sectional dimensions(width, effective depth) and steel ratio. The minimization problem was formulated as a non-linear mathematical program(NLP) and solved by SCP(sequential convex program) and SLP(sequential linear program) which have proved to be highly efficient for this type of problem. Several numerical examples are given to show the application of the optimum algorithm. In the numerical example, a three span R.C. continuous beam and a column are considered and the efficiencies of NLP techniques are compared and analyzed. Here R.C. column is usually designed for compression strength, geometrical limit states and can be designed as a short column for limiting the slenderness ratio.
This paper describes the minimum-cost design of R.C. continuous T-beams involving costs of concrete, reinforcing steel and formwork, subject to deflection and strength constraints, in addition to upper and lower bounds on design variables. The optimization is carried out using the methods based on discretized continuum-type optimality criteria (DCOC). An explicit mathematical derivation of optimality criteria is given based on the well known Kuhn-Tucker necessary conditions, followed by an iterative procedure for designs when the design variables are the effective depth and the steel ratio. It is assumed that the section is uniform along the span. The self-weight of the beam is included in the equilibrium equation of the real system and in the optimality criteria. On the basis of these contents, the user interactive system using pull-down menu and pop-up windows is developed for the problem of minimum cost design of R.C. continuous T-beam. Through applying GUI to minimum cost design problem, practice designer can easily perform optimum design and use optimum design as preliminary design. A numerical examples of R.C. continuous beams using GUI is given to compare and assess the efficiency of algorithm for the DCOC-based technique.
This paper deals with the minimum-cost design problem of reinforced concrete beam. The total cost of the structure includes the cost of concrete, reinforcing steel and formwork. The minimum-cost design of simply supported beam loaded by distributed load subjects to constraints on strength, serviceability, stability, durability, fire resistance. The minimum-cost design problem is formulated as a non-linear programming(NLP) problem whose solution is attempted by two techniques, namely sequential linear programming(SLP) and sequential convex programming(SCP). Also, minimum-cost design using user interactive system can be easily performed and practice designer and apply optimum design to preliminary design.