Anabel del Val was born in Málaga, Spain. From a very young age, she has been interested in Space travel, leading to her enrolment at Universidad Politécnica de Madrid in 2009 in a BSc and then a MSc in Aeronautical Engineering with a specialization in Space Vehicles.
During the five-years studies, Anabel broadened her knowledge in Space-related topics and was also introduced to the field of Fluid Dynamics, which opened a wide range of challenges that still remain unsolved today. Fluid Dynamics was one subject she found intellectually stimulating and rewarding when well understood, especially with many new concepts and mathematical approaches required for problem solving.
After finishing her MSc in Madrid, Anabel del Val carried out her Master’s thesis in the field of Aerothermodynamics at the von Karman Institute for Fluid Dynamics and where she saw the perfect blending of Space travel and Fluid Dynamics when dealing with the reentry of spacecraft. She discovered the importance of Uncertainty Quantification methods when dealing with experimental measurements in ground testing facilities used to reproduce reentry flight conditions. The need for UQ in terms of validation and optimal experimental conditions determination motivated her to apply for the UTOPIAE network as a research fellow.
When looking at the future, one of Anabel’s main concerns is education. As new generations of scientists and engineers become leaders in the field, she thinks it is important to support them with an adequate educational system embracing today’s societal and technological challenges. In this envisioned educational system, the History of Science should play an important role as it contains a high educational value regarding the human side of the struggle for knowledge, how important ideas came to be, and why and how we understand what we understand. She would, therefore, like to devote her career to academia.
Other interests include astronomy, which started when Anabel was 10 years old with her first telescope and continued throughout the years when she was the coordinator of an astronomy club back in University. She is an avid poetry reader and writer having won two international literary contests in a row resulting in the publication of two books. Sports such tennis, swimming and running rank among her favourites.
A. del Val, O. P. Le Maître, P. M. Congedo, T. E. Magin. Investigation of graphite ablation in nitrogen plasma ows using a Bayesian formulation. Accepted poster at Fundamentals of Collisions of Fast Particles with Surfaces, 2020 ATW Aerospace Thematic Workshop, Les Houches School of Physics, April 2020. CANCELLED
Basu, A. del Val, J. Einbeck, M. Troffaes, T. E. Magin. Robust Bayesian Inference under Limited Information and its Application to Atomic Spectra for Atmospheric Entry Systems. Accepted for presentation at the SIAM UQ20, Munich, March 2020. CANCELLED
A. del Val, O. P. Le Maître, O. Chazot, T. E. Magin, P. M. Congedo. On the Inference of Chemical Model Parameters for Tomorrows Space Journeys: an Overview on Reusable and Ablative Space Systems. Presentation at Optimization in Space Engineering (OSE5), Ljubljana, November 2019
A. del Val, O. P. Le Maître, O. Chazot, T. E. Magin, P. M. Congedo. Bayesian Calibration of Gas/Surface Interaction Models for Thermal Protection Materials under Spacecraft Re-entry Conditions. Presentation at ICIAM 2019, Valencia University, Valencia, Spain, 15-19 July 2019.
Luis, A. del Val, O. Chazot. Characterization under Uncertainty of Catalytic Phenomena in Ceramic Matrix Composites Materials for Spacecraft Thermal Protection Systems, 8th European Conference for Aeronautics and Aerospace Sciences (EUCASS), Madrid, June 2019. Shortlisted for best student paper award.
Arizmendi, T. Bellosta, A. del Val, G. Gori, J. Reis, M.Prazeres. On Real-time Management of On-board Ice Protection Systems by means of Machine Learning, AIAA AVIATION Forum, Dallas, June 2019
A. del Val, O. P. Le Maître, O. Chazot, T. E. Magin, P. M. Congedo. Robust calibration of the catalytic properties of thermal protection materials: Application to plasma wind tunnel experiments. Presentation at the Uncertainty Quantification & Optimization Conference, Sorbonne University, Paris, France, 18-20 March 2019
A. del Val, O. P. Le Maître, O. Chazot, T. E. Magin, P. M. Congedo. Stochastic inference of the catalytic properties of thermal protection materials from plasma wind tunnel experiments. Presentation at the 7th European Conference on Computational Fluid Dynamics, ECCOMAS, Glasgow, UK, 11-15 June 2018.
A. del Val, O. Chazot, T. E. Magin. Uncertainty Treatment Applications: High-Enthalpy Flow Ground Testing, In Optimization Under Uncertainty with Applications to Aerospace Engineering, Ed. M. Vasile, Springer Nature 2020
A. del Val. Bayes goes to Space: inferring chemical model parameters for tomorrow’s Space journeys. Presentation at Stats4Grads, Durham University, Durham, UK, 6 Nov 2019.
A. del Val. Characterization of spacecraft reusable heat shield materials from plasma wind tunnel experiments: a Bayesian inference approach. Presentation at ETSIAE, UPM, Madrid, Spain, 1 Oct 2018.
A. del Val. Stochastic inference of the catalytic properties of thermal protection materials from plasma wind tunnel experiments . Presentation at Entry Systems and Technology Division Seminar, NASA Ames Research Center, Moffet Field, CA, 30 August 2018.
A. del Val, O. P. Le Maître, O. Chazot, T. E. Magin, P. M. Congedo. A surrogate based optimal likelihood function for the Bayesian calibration of catalytic recombination in atmospheric entry protection materials. (Under review)
A. del Val, D. Luis, O. Chazot. Characterization under uncertainty of catalytic effciencies in ceramic matrix composite materials for spacecraft thermal protection systems. (Submitted)
A. del Val, O. P. Le Maître, O. Chazot, P. M. Congedo, T. E. Magin. Inference methods for gas/surface interaction models: from deterministic approaches to Bayesian techniques. Uncertainty Quantification & Optimization 2020 conference proceedings. (Accepted)
A. del Val, O. P. Le Maître, P. M. Congedo, T. E. Magin. Investigation of graphite ablation in nitrogen plasma flows using a Bayesian formulation. (To be submitted)
A. del Val, O. P. Le Maître, P. M. Congedo, T. E. Magin. Impact of flow modeling choices on the calibration of nitridation effciencies and model selection through Bayesian evidence, (Under preparation).