Anabel del Val has been awarded the 2020 Amelia Earhart Fellowship!

We have the pleasure to inform you that Anabel del Val has been awarded the prestigious 2020 Amelia Earhart Fellowship!

The Amelia Earhart Fellowship was established in 1938 in honor of famed pilot and Zontian, Amelia Earhart. The US$10,000 Fellowship is awarded annually to up to 30 women pursuing Ph.D./doctoral degrees in aerospace engineering and space sciences.

Anabel del Val graduated in Aerospace Engineering at the Universidad Politécnica de Madrid with a specialization in Space Vehicles. She is now a PhD student at the von Karman Institute for Fluid Dynamics and École Polytechnique in Paris under the supervision of Profs. Olivier Chazot, Thierry Magin and Dr. Pietro Congedo. She works on applying Uncertainty Quantification methods to assess the theoretical modeling of gas/surface interaction phenomena in the context of atmospheric entry. Her research is supported by the European Commission’s Horizon 2020 programme through the UTOPIAE Marie Curie Innovative Training Network

Description of the Anabel's research:

Traditionally, the design of atmospheric entry systems has relied heavily on experimental facilities and their capability to reproduce relevant flight conditions. Theoretical models are validated against the experimental evidence and improved accordingly. However, due to the complexity of the problem and the limitations of the classical deterministic approaches, many gaps remain in the understanding of atmospheric entry phenomena which can substantially slow down the progress for these aerospace systems. In this context, stochastic approaches are necessary to fairly account for all sources of uncertainties in our predictions and let experiments inform how model parameters behave. Model predictions, in turn, provide the capability of proposing new, more informative experiments that help increase confidence in our tools. For the particular case of gas/surface interaction in atmospheric entry flows, available experimental data is scarce and often poorly suited for the understanding of coupled microscopic phenomena. My research is focused on developing and applying Uncertainty Quantification (UQ) techniques for the efficient and robust inference of gas/surface interaction model parameters from limited experimental data. The developed methods are then used to propose new experiments which yield the best estimation of such parameters. Along with this, we can also robustly assess our theoretical models in light of experimental data.