Abstract
This paper explores reliability-based global optimization of isogrid stiffened panels subjected to system reliability constraints. Uncertainties in material properties and geometric manufacturing uncertainties are represented by random variables. Polynomial response surface approximations are fit to the most critical safety margins in the panel. Panel system probability of failure is calculated by Monte Carlo simulation using response surface approximations. A probabilistic sufficiency factor approach is employed to convert reliability-based optimization to sequential deterministic optimization in order to reduce the computational cost of global reliability-based optimization. The reliability-based design of a composite isogrid stiffened panel is presented in the paper. The multiple near optima obtained by the global optimization offer designers the option of considering features not included in the optimization formulation.
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