Title: Quantification of Modeling Uncertainty in Aeroelastic Design
Abstract: Traditional uncertainty quantification techniques in engineering design concentrate on the quantification of parametric uncertainties, which are variations of the input variables. In problems with complex or newer modeling methodologies, the variability induced by the modeling process itself, known as model-form and predictive uncertainty, can become a significant source of uncertainty to the problem. This work demonstrates two model-form uncertainty quantification methods on an unsteady aeroelastic problem: Bayesian Model Averaging and the Adjustment Factors Approach. While the Bayesian Model Averaging approach is more robust and has been shown to more completely quantify the total uncertainty, it also requires the presence of experimental data, which is not always readily available in preliminary design. This work introduces a design methodology for use in preliminary design phases that instead of performing a blanket amount of experiments at various data points and configurations, utilizes the modeling uncertainty itself to drive the necessity of further experimental data points. Within this methodology, the Modified Adjustment Factors Approach has been developed to calculate the sensitivity of the adjusted models to the model probability assumptions being input into the work, facilitating the flow of the design methodology.
Publication Year: 2010
Publication Date: 2010-04-12
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 2
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