Uncertainty Quantification, Identification and Calibration in Aerospace Models
As modelling and numerical simulation are becoming omnipresent in science and engineering, the importance of uncertainties is increasingly essential. Indeed, accounting for uncertainties and assessing confidence level in model-based predictions is crucial to attain the full potential of numerical approaches in research and development workflows and decision-making processes. Despite their importance, the treatment of uncertainties usually remains a challenging task, especially in the context of complex models with a high computational cost.
- Dr Pietro Marco Congedo (INRIA & Ecole Polytechnique, France)
- Dr Jochen Einbeck (Durham University, England)
- Dr Olivier Le Maître (CNRS & Ecole Polytechnique, France)
This symposium will focus on advanced uncertainty methods and their application to complex applications. The scope of the symposium encompasses the whole spectrum of problematics concerning the uncertainties, with the construction of uncertainty models from data and a priori knowledge, the uncertain propagation problems, the uncertainty analyses (sensitivity), and uncertainty reduction methods.
The symposium will gather researchers working on advanced techniques for uncertainty treatment, including but not limited to:
- surrogate-based methods,
- reduced-order modeling,
- statistical and machine learning methods,
- Bayesian inference and calibration,
- design of experiment,
- multi-level and multi-fidelity methods.
Methodological, algorithmic and theoretical contributions are all welcomed, as well as applications to uncertainty methods to challenging problems in aerospace or other domains.