Anabel del Val
Assistant Professor
Anabel del Val
Assistant Professor
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Assistant Professor
Assistant Professor
Professor del Val’s research is focused on the development and application of stochastic methods to achieve robust predictive modeling of hypersonic and reacting flows. These stochastic methods belong to the broad areas of sensitivity analysis, surrogate modeling, forward uncertainty propagation, Bayesian inverse problems, optimization under uncertainty, and data-driven approaches.
Professor del Val is interested in understanding how uncertainty impacts our capabilities to build predictive models and what it entails for our understanding of the fundamental physical processes taking place in hypersonic and reacting flows. Applications of her work include 1) understanding of complex models and their high-order interactions by functional decompositions and sensitivity analyses, 2) using this information to design more informative experiments for model calibration and validation, leading to better utilization of experimental resources, and 3) validation of theoretical models for high-temperature gas-surface interaction, gas-phase chemical kinetics, boundary layer transition, and shock layer radiation.
Ph.D., Aerospace Engineering, Institut Polytechnique de Paris, École Polytechnique, France, 2021
B.S. & M.S. Aerospace Engineering, Universidad Politécnica de Madrid, Spain, 2015
Starting August 26, 2024: Assistant Professor, Aerospace Engineering & Mechanics, University of Minnesota
Senior Aerospace Engineer supporting Entry, Descent and Landing, Analytical Mechanics Associates at NASA Langley Research Center, 2024
Postdoctoral Researcher, Aeronautics and Aerospace Department, von Karman Institute for Fluid Dynamics, 2022-2023
Graduate Researcher, Aeronautics and Aerospace Department, von Karman Institute for Fluid Dynamics & Platon Team, Inria Saclay Île-de-France, 2017-2021
Visiting Researcher, Department of Mathematical Sciences, Durham University, United Kingdom, 2019
Pre-doc junior researcher, Fluid Mechanics & Aerospace Propulsion Department, Universidad Politécnica de Madrid, 2016
2022: Belgium nominee for Da Vinci Medal Competition, Best European Ph.D thesis on Flow, Turbulence and Combustion (ERCOFTAC)
2020: Amelia Earhart Fellowship
2019: 2nd place in the EUCASS Best Student Paper Award Competition
2017-2020: Marie Sklodowska-Curie Actions Fellow, European Commission
2015: Outstanding Master Thesis Award, School of Aeronautics, Universidad Politécnica de Madrid
2012: Air Force Fellowship, School of Aeronautics, Universidad Politécnica de Madrid
2012: Outstanding Graduate Awards in Fluid Mechanics, Applied Statistics and Space Science, School of Aeronautics, Universidad Politécnica de Madrid
2010: Outstanding Student in Engineering, School of Aeronautics, Universidad Politécnica de Madrid
A. del Val, O. Chazot and 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, O. P. Le Maître, O. Chazot, T. E. Magin and P. M. Congedo. A surrogate-based optimal likelihood function for the Bayesian calibration of catalytic recombination in atmospheric entry protection materials. Applied Mathematical Modelling, Volume 101, January 2022, Pages 791-810.
A. del Val and O. Chazot. Stochastic determination of thermal reaction rate coefficients for air plasmas. The Journal of Chemical Physics, Volume 159, August 2023, 064105.
A. del Val, T. E. Magin, P. M. Congedo. Quantification of model-form uncertainties affecting the calibration of a carbon nitridation model by means of Bayesian Model Averaging. International Journal of Heat and Mass Transfer, Volume 213, October 2023, 124271.
A. del Val, O. P. Le Maître, P. M. Congedo and T. E. Magin. Stochastic calibration of a carbon nitridation model from plasma wind tunnel experiments using a Bayesian formulation. Carbon, Volume 200, November 2022, Pages 199-214.
A. del Val, D. Luís and O. Chazot. Experimental methodology for the accurate stochastic calibration of catalytic recombination affecting reusable spacecraft TPS. Chemical Physics, Volume 559, 1 July 2022, 111528.