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Risk optimization of trusses using a new gradient estimation method

International Conference on Applications of Statistics and Probability (12th : 2015 : Vancouver, B.C.)

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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This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.

Vancouver : University of British Columbia Library

10.14288/1.0076213

Non UBC

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/