Friday, October 13, 2017
3:00 am
Guggenheim 133 (Lees-Kubota Lecture Hall) – Guggenheim Aeronautical Laboratory

GALCIT Colloquium

Data to Decisions: Computational Methods for the Next Generation of Aerospace Systems
Karen Willcox, Professor of Aeronautics and Astronautics, Massachusetts Institute of Technology

New technologies are changing the way we think about designing and operating aerospace systems. For example, in next-generation aircraft the combination of sensing technologies and computational power brings new opportunities for data-driven modeling and data-driven decision-making. Yet data alone cannot deliver the levels of predictive confidence and modeling reliability demanded for these systems. For that, we must build on the decades of progress in rigorous physics-based modeling and associated uncertainty quantification. This talk discusses our work at the intersection of physics-based and data-driven modeling, with a focus on the design of next-generation aircraft. We show how adaptive reduced models combined with data-driven learning enable dynamic decision-making onboard a structural-condition-aware UAV. We show how multifidelity formulations exploit a rich set of information sources to achieve multidisciplinary design under uncertainty for future aircraft concepts.

Contact Francesca Baldini fbaldini@caltech.edu at 9518929808
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