Risk optimization of trusses using a new gradient estimation method Gomes, Wellison J. S.
When dealing with structural risk optimization by means of Monte Carlo simulation methods, the total expected cost usually becomes a noisy function and it is not possible to directly calculate its derivatives. In fact, even the estimation of these derivatives becomes a challenging task. On the other hand, gradient-based optimization methods are among the most efficient ones for this kind of problem, but they require derivatives. In this paper, a new method, which allows estimating gradients of the total expected cost with respect to design variables, is used to perform risk optimization of trusses by a gradient-based optimization method. The proposed methodology is employed in the solution of a bi-dimensional and a spatial truss. The results show that this methodology presents a significantly smaller computational cost when compared to a similar procedure using finite differences and indicates that the quality of the gradients is slightly better as well.
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