Computational Modeling and Design Optimization Under Uncertainty

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Uncertainty is ubiquitous in the mathematical characterization of engineered and natural systems. Computer models of high-performance and safety-critical engineering systems must rationally account for uncertainty in order to reliably predict performance and possible modes of failure. The proposed research program will develop novel computational methods that will enable engineers to efficiently predict the performance of complex engineering systems in the presence of uncertainty and, ultimately, design systems that perform robustly in the face of uncertainty. The *ability to perform computational modeling and design optimization as proposed here will provide a strategic advantage to the Canadian aerospace industry.