Ph.D. Dissertation Defense by Hae-Jin Choi
Wednesday, September 20, 2005
(Dr. Farrokh Mistree, Chair)
"A Robust Design Method for Model and Propagated Uncertainty"
One of the important factors to be considered in designing an engineering system is uncertainty, which emanates from natural randomness, limited data, or limited knowledge of systems. In this study, a new robust design methodology is established in order to design multifunctional materials, employing multi-time and length scale analyses. The method involves the integration of robust design techniques, design of experiments, multiscale material simulations, metamodeling, uncertainty analysis and estimation, multiobjective decision-making and collaborative, distributed design.
The Robust Concept Exploration Method with Error Margin Index (RCEM-EMI) is proposed for decision-making with consideration of non-deterministic system behavior. Following the steps in the RCEM-EMI, a designer may search for a solution that is robust to the uncertainty embedded in a system as well as the uncertainty in system parameters. The Inductive Design Exploration Method (IDEM) is proposed to facilitate distributed, robust decision-making under propagated uncertainty in a series of analyses or simulations. In the IDEM, the propagated uncertainty is mitigated by passing ranged sets of robust design specifications in a top-down manner.
These methods are verified in the context of ‘Design of Multifunctional Energetic Structural Materials (MESMs)'. The MESMs are being developed to replace the large amount of steel reinforcement in a missile penetrator for light weight, high energy release, and sound structural integrity. In this example, the methods facilitate following state-of-the-art design capabilities, robust MESMs design under (a) random microstructure changes and (b) propagated uncertainty in a multiscale analysis chain. The methods are designed to facilitate effective and efficient materials design; however, they are generalized to be applicable to any complex engineering systems design that incorporates computationally intensive simulations or expensive experiments, non-deterministic models, accumulated uncertainty in multidisciplinary analyses, and distributed collaborative decision-making.