CUED Publications database

Extending Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties

Cook, LW and Jarrett, JP and Willcox, KE Extending Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties. AIAA Journal. (Unpublished)

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Abstract

This paper presents a new approach for optimization under uncertainty in the presence of probabilistic, interval and mixed uncertainties, avoiding the need to specify probability distributions on uncertain parameters when such information is not readily available. Existing approaches for optimization under these types of uncertainty mostly rely on treating combinations of statistical moments as separate objectives, but this can give rise to stochastically dominated designs. Here, horsetail matching is extended for use with these types of uncertainties to overcome some of the limitations of existing approaches. The formulation delivers a single, differentiable metric as the objective function for optimization. It is demonstrated on algebraic test problems, the design of a wing using a low-fidelity coupled aero-structural code, and the aerodynamic shape optimization of a wing using computational fluid dynamics analysis.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div C > Engineering Design
Depositing User: Cron Job
Date Deposited: 03 Sep 2017 20:09
Last Modified: 07 Sep 2017 01:43
DOI: