Abstract
A probabilistic method is developed to optimize the design of an idealized composite wing through consideration of the uncertainties in the material properties, fiber-direction angle, and ply thickness. The polynomial chaos expansion method is used to predict the mean, variance, and probability density function of the flutter speed, making use of an efficient Latin hypercube sampling technique. One-dimensional, two-dimensional, and three-dimensional polynomial chaos expansions are introduced into the probabilistic flutter model for different combinations of material, fiber-direction-angle, and ply-thickness uncertainties. The results are compared with Monte Carlo simulation and it is found that the probability density functions obtained using second- and third-order polynomial chaos expansion models compare well but require much less computation. A reliability criterion is defined, indicating the probability of failure due to flutter, and is used to determine successfully the optimal robust design of the composite wing.
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