Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

Bisaillon, P and Sandhu, R and Pettit, C and Khalil, M and Poirel, D and Manohar, CS and Sarkar, A (2022) Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference. In: Journal of Sound and Vibration, 522 .

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Abstract

We report a Bayesian framework for concurrent selection of physics-based models and (modeling) error models. We investigate the use of colored noise to capture the mismatch between the predictions of calibrated models and observational data that cannot be explained by measurement error alone within the context of Bayesian estimation for stochastic ordinary differential equations. Proposed models are characterized by the average data-fit, a measure of how well a model fits the measurements, and the model complexity measured using the Kullback�Leibler divergence. The use of a more complex error models increases the average data-fit but also increases the complexity of the combined model, possibly over-fitting the data. Bayesian model selection is used to find the optimal physical model as well as the optimal error model. The optimal model is defined using the evidence, where the average data-fit is balanced by the complexity of the model. The effect of colored noise process is illustrated using a nonlinear aeroelastic oscillator representing a rigid NACA0012 airfoil undergoing limit cycle oscillations due to complex fluid�structure interactions. Several quasi-steady and unsteady aerodynamic models are proposed with colored noise or white noise for the model error. The use of colored noise improves the predictive capabilities of simpler models. © 2021

Item Type:	Journal Article
Publication:	Journal of Sound and Vibration
Publisher:	Academic Press
Additional Information:	The copyright for this article belongs to Academic Press
Keywords:	Aeroelasticity; Bayesian networks; Errors; Inference engines; Ordinary differential equations; Stochastic models; Stochastic systems, Average data; Bayesian frameworks; Bayesian inference; Bayesian model selection; Colored noise; Data fits; Dynamic model error; Error modeling; Model errors; Nonlinear aeroelastic system, White noise
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	20 Jan 2022 06:35
Last Modified:	20 Jan 2022 06:35
URI:	http://eprints.iisc.ac.in/id/eprint/70964

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