Ammar Ali Hussein Al-filfily
Abstract
The paper is focused on the application of the response surface method (RSM) in structural optimization. Applications of the response surface method in the design of composite laminated ...
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The paper is focused on the application of the response surface method (RSM) in structural optimization. Applications of the response surface method in the design of composite laminated plate have been discussed. The response surface method consists of two stages. In the first stage, the random variables is selected in order to perform a deterministic computer simulation (finite element solution) in the sample points. In the second stage, the approximation of the function (which represent the buckling load) is performed in order to obtain response surfaces using PDS module included in the ANSYS Program. This response surface is incorporated into a genetic algorithm (GAs) for optimization of random input variables to obtain maximum buckling load for composite laminated plate subjected to both mechanical and thermal loading. GAs are stochastic optimization algorithms based on natural selection and genetics. In contrast to traditional gradient-based methods, GAs work on populations of solutions which evolve typically over hundreds of generations. Four and five different variable formulations are examined. It was found that for SSSS boundary condition and two layer laminate the optimum values of buckling load for all thermal loading occur at q1=33o, q2=59o, t1=1.23 mm and t2= 1.25 mm, also it can observe that the significant random variable are t1 and t3 (in the case of five independent variables) since the value of buckling load effected with t1 and t3 more than for t2.
