Welcome to the Aerofluids, Learning & Discovery Lab (ALD Lab). We are part of Galcit at Caltech and AeroAstro at MIT


Announcements

Mar 2025: Our work on “Bow shock instability at hypersonic speed“ was featured by MIT AeroAstro News!

Feb 2025: Adrian discussed “Synergistic-Unique-Redundant Decomposition of causality” at the SoCal Workshop on Causal Reasoning at UC Irvine.

Feb 2025: Adrian delivered a talk about “SURD: A causal inference tool for Scientific Discovery” at the Modeling Talk Series from Google. You can check the video of the presentation here!

Feb 2025: Adrian presented “Causal Inference for Scientific Discovery” at H.B. Keller Colloquium Event Series from Caltech.

Jan 2025: The proceedings of the Stanford Summer Program 2024 at the Center for Turbulence Research are now available.

Jan 2025: Yuenong Ling, Julian Powers and Adrian Anton attended AIAA SCITECH FORUM 2025 in Orlando, FL to present their work on “Numerically Consistent Data-Driven Subgrid-Scale Model via Data Assimilation and Machine Learning”, “Trajectory Optimization for a Battery-less Solar-powered Unmanned Aerial Vehicle“, and “Bow Shockwave Instabilities of the Mars Science Laboratory Using Wall-Modeled Large Eddy Simulation“.

Jan 2025: Check our new paper on “The coherent structure of the energy cascade in isotropic turbulence” published in Scientific Reports.

Dec 2024: Our paper on “Informative and non-informative decomposition of turbulent flow fields” has been published in the Journal of Fluid Mechanics.

Nov 2024: Our paper “Decomposing causality into its synergistic, unique, and redundant components” was featured in Nature Communications as one of the best 50 papers in Applied physics and mathematics!

Nov 2024: Adrian Anton won the APS/DFD Milton van Dyke Poster Award in APS DFD Gallery of Fluid Motion! You can check the poster here. Congratulations!

View all announcements here.


Featured Publications

Á. Martínez-Sánchez, G. Arranz, A. Lozano-Duran, Decomposing causality into its synergistic, unique, and redundant components, Nat. Commun. 15, 9296 (2024).

G. Arranz, Y. Ling, S. Costa, K. Goc, and A. Lozano-Duran. “Building-block-flow computational model for large-eddy simulation of external aerodynamic applications”, Communications Engineering 3:127, 2024.

A. Lozano-Durán and H. J. Bae, “Machine-learning building-block-flow wall model for large-eddy simulation“, J. Fluid Mech., 963, A35 , 2023.

A. Lozano-Durán, G. Arranz, ’’Information-theoretic formulation of dynamical systems: causality, modeling, and control”, Physical Review Research, 2022.

Y. Yuan and A. Lozano-Duran, Limits to extreme event forecasting in chaotic systems, Physica D., 467, 134246, 2024.

A. Towne, S. T. M. Dawson, G. A. Brès, A. Lozano-Durán, T. Saxton-Fox, A. Parthasarathy, A. R. Jones, H. Biler, C.-A. Yeh, H. D. Patel, and K. Taira, “A Database for Reduced-Complexity Modeling of Fluid Flows“, AIAA J., 2023

View all publications here.