Research in design optimization methods has increasingly become concerned with mathematical treatment of uncertainties in system demands and capacity, boundary conditions, component interactions, and available resources. Vanderbilt efforts in this context seek to integrate advances in two directions: computational reliability analysis methods and deterministic design optimization. Current work is focused on developing computationally efficient strategies for such integration, using de-coupled or single loop formulations instead of earlier nested formulations. The extension of reliability-based optimization to include robustness requirements leads to multi-objective optimization under uncertainty. Another important challenge comes from multi-disciplinary problems, where the various reliability constraints are evaluated in different isciplinary analysis codes and there is feedback coupling between the codes. Applications considered relate to civil, automotive, and aerospace systems.

Please also visit the Reliability and Risk Engineering and Management Program.