Andrew Cooper is a 4th-year PhD candidate in Virginia Tech's Department of Statistics. He received his bachelors and masters degrees in Statistical Science from Duke University. His research areas include computer experiments and surrogate modeling, as well as Bayesian methodology.
This paper applies a Bayesian Optimization approach to the design of a wing subject to stress and aeroelastic constraints. The parameters of these constraints, which correspond to various flight conditions and uncertain parameters, are prescribed by a finite number of scenarios. Chance-constrained optimization is used to seek a wing design that is robust to the parameter variation prescribed by such scenarios. This framework enables computing designs with varying degrees of robustness. For instance, we can deliberately eliminate a given number of scenarios in order to obtain a lighter wing that is more likely to violate a requirement, or might seek a conservative wing design that satisfies the constraints for as many scenarios as possible.
Session Materials: dataworks.test...
21 май 2024
