TRACES
Robust assessment of the model error for ice accretion models through Bayesian-based methods and experimental data
Scientists and Engineers create mathematical models of phenomena in order 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. In my research, I aim to quantify the uncertainty associated with modeling the formation and accumulation of ice on airplanes and incorporate this uncertainty into future model predictions. My 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.