Bounded-But-Unknown uncertainty optimization using design sensitivities and parallel computing: Application to MEMS

In the present paper uncertainty-based design optimization of structures is carried out. A description of uncertainties via bounds on the uncertainty variables is adopted. An anti-optimization technique, which searches for the combinations of uncertainties yielding the worst responses, is used to tackle these Bounded-But-Unknown uncertainties of non-convex or discontinuous nature. This anti-optimization technique is computationally very expensive and can become impractical for real world applications, in particularly when expensive numerical response evaluations are involved. In order to reduce the number of expensive numerical response evaluations, a modified anti-optimization technique is proposed in the present paper. This enhanced anti-optimization technique incorporates design sensitivities and database technique and is further modified to use parallel computing in order to increase the computational efficiency. The enhanced anti-optimization technique is studied on the basis of test examples from literature and a Microelectromechanical Systems (MEMS) structure. A comparison between results for the examples, clearly shows an improvement in computational efficiency for the anti-optimization technique, due to the use of sensitivities, database and parallel computing. The enhanced anti-optimization technique can be applied efficiently to general problems involving uncertainties of non-convex or discontinuous nature.