Document Type : Research Paper
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Abstract
Due to the probabilistic nature and uncertainties of structural parameters, reliability-based optimization will enable engineers to account for the safety of the structures and allow for its decision making applicability. Thus, reliability-based design will substitute deterministic rules of codes of practice. Space structures are of those types that have an exceedingly high range of applicability aspects in civil engineering. Therefore optimization of such structures with great and considerable number of members will be economically wise. For this purpose, the optimization process could be carried out using various mathematical models. One such model is to minimize weight while considering elements failure probability as constraints. Another form is to minimize weight and then regarding the whole structure system reliability as constraint. The third type could be to minimize failure probability as well as its weight, while taking into account the structural system reliability as the constraint. In this research each of the above forms were studied and the results were compared. Also, apart from reliability considerations for the members, the reliability of nodes was also taken into account. Node failure means that node displacement in at least one direction exceeds that of the allowable value. As well the effect of various stochastic parameters such as load, yield stress, modulus of elasticity and cross section were studied. The stochastic parameters discussed in this study are statistically independent and possess standardized normal distribution. To avoid local convergence during the process of optimization, Genetic Algorithms is used as means of optimization. This study show that with increasing the members or system admissible failure probability, optimum weight of structure increases, but with increasing the coefficient of variation of load or yield stress, optimum weight increases.
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