Jose del Aguila Ferrandis- Academic Personal Website

Exploring Computational Fluid Dynamics and Scientific Machine Learning

About Me

Hi, I'm Jose del Aguila Ferrandis, a scientist with a passion for leveraging scientific machine learning to tackle engineering challenges in fluid dynamics and naval engineering.

Research Highlights

Current research focuses on boundary layer control, non-linear ship motions, and integrating machine learning with physical laws for innovative engineering solutions.

In the Media

Artificial reef designed by MIT engineers could protect marine life, reduce storm damage, MIT News, 2024

Engineers devise a modular system to produce efficient, scalable aquabots, MIT News MECHE, 2023.

Telemadrid, Madrileños por el Mundo, Boston. (2019), in Spanish.

Interview by the Technical University of Madrid. In it, I share my experience during my visiting periods at MIT and my exchange period at NTNU Norway.

Projects

Boundary Layer Control

Innovative techniques to optimize flow over marine vessels for improved performance.

Vortex Induced Vibrations

Predicting vortex induced vibrations in Steel Catenary Risers (SCR)

Physics-Informed ML

Blending machine learning models with physical laws to enhance predictive accuracy.

Machine Learning of Non-linear Seakeeping

Predicting ship motions in severe sea states with non-linear phenomena such as parametric rolling.

Selected Publications

For a full list of my academic work, visit my Google Scholar profile.

Architected materials for artificial reefs to increase storm energy dissipation

Edvard Ronglan, Alfonso Parra Rubio, Alexis Oliveira da Silva, Dixia Fan, Jeffrey L Gair, Patritsia Maria Stathatou, Carolina Bastidas, Erik Strand, Jose del Aguila Ferrandis, Neil Gershenfeld, Michael S Triantafyllou, PNAS Nexus, Volume 3, Issue 3, March 2024, pgae101 Read more

Modular Morphing Lattices for Large-Scale Underwater Continuum Robotic Structures

Parra Rubio, Alfonso and Fan, Dixia and Jenett, Benjamin and del Aguila Ferrandis, Jose and Tourlomousis, Filippos and Abdel-Rahman, Amira and Preiss, David and Triantafyllou, Michael and Gershenfeld, Neil. Soft Robotics, 2023. Read more

Learning functionals via LSTM neural networks for predicting vessel dynamics in extreme sea states

Jose del Aguila Ferrandis, Chryssostomos Chryssostomidi, Michael Triantafyllou, Karniadakis, G. E. Proc. R. Soc. A.47720190897. Proceedings of the Royal Society A. Read more

Learning functional priors and posteriors from data and physics

Xuhui Meng and Liu Yang and Zhiping Mao and José del Águila Ferrandis and George Em Karniadakis. Journal of Computational Physics, 2022. Read more

Influence of viscosity and non-linearitiesin predicting motions of a wind energy offshore platform in regular waves

Jose del Aguila Ferrandis, Luca Bonfiglio, Ricardo Zamora Rodrıguez, Chryssostomos Chryssostomidis, Odd Magnus Faltinsen, and Michael Triantafyllou. Journal of OffshoreMechanics and Arctic Engineering, 142(6), 2020 Read more

A probabilistic framework for multi‐disciplinary design: Application to the hydro‐structural optimization of super‐cavitating hydrofoils

Bonfiglio, L., Perdikaris, P., del Águila, J., & Karniadakis, G. E. International Journal for Numerical Methods in Engineering. Read more

Influence of large hull deformations on the motion response of a fast catamaran craft with varying stiffness

del Águila Ferrandis, José, Brizzolara, Stefano and Chryssostomidis, Chryssostomos. Ocean Engineering 163 (2018): 207-222. Read more

Contact

Email: jaguila@vt.edu

Download CV: Click here