Have you ever heard of uncertainty quantification?📱📊
Scientists and engineers create mathematical models of phenomena to make predictions💻📈. Although these models are complex and precise, they sometimes misrepresents reality❗.
This misrepresentation typically arises from intentional simplifications or gaps in our understanding of certain physical aspects,and these errors can be modeled as uncertainties🎲. Uncertainty Quantification is the branch of applied mathematics that can help engineers in dealing with these uncertainties.
➡️Omar, in his PhD research, aims to quantify the uncertainty associated with modeling the formation and accumulation of ice on airplanes ❄️✈️ and incorporate this uncertainty into future model predictions.
✅His work will be crucial for understanding how different conditions affect the safety and performance of critical components such as ice detection and ice protection systems.
To introduce a robust procedure for assessing the model error for any model used during the simulation, to calibrate model parameters considering systematically the model error, to combine several models’ predictions to improve the overall prediction capabilities
- Assess the calibration procedure by detecting potential inaccuracies of any model
- Perform an uncertainty quantification study propagating systematically the posterior distribution of each model’s parameter
Design of an electro-thermal Ice Protection System (PWG3)
- Cortesi, P.M. Congedo, Forward and backward uncertainty quantification with active subspaces: Application to hypersonic flowsaround a cylinder. Journal of Computational Physics 2019, https://doi.org/10.1016/j.jcp.2019.109079
- F. Sanson, C. Bertorello, J.-M. Bouilly, P.M. Congedo, Breakup prediction under uncertainty : application to upper stage controlled reentries from GTO orbit, Aerospace Science and Technology, Volume 87, April 2019, Pages 340-356, 2019.
- F. Fusi, P.M. Congedo, A. Guardone, G. Quaranta, Multifidelity Physics-Based Method for Robust Optimization Ap-plied to a Hovering Rotor Airfoil. AIAA Journal, 2015, Vol.53: 3448-3465.
