collaborators

6 papers

cs.LG2026

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling

Francisco Giral, Abhijeet Vishwasrao, Andrea Arroyo Ramo +8

Aerodynamic surrogate models are increasingly used to replace repeated high-fidelity CFD evaluations in many-query design settings, but current approaches still face two important…

physics.flu-dyn2026

Unified scaling laws for turbulent boundary layers across flow regimes

Gonzalo Arranz, Adrian Lozano-Duran

We discover unified scaling laws for the mean wall shear stress and the mean velocity profile in turbulent boundary layers subject to favorable and adverse mean pressure gradients-…

cs.AI2026

Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations

Abhijeet Vishwasrao, Francisco Giral, Mahmoud Golestanian +8

Flow physics and more broadly physical phenomena governed by partial differential equations (PDEs), are inherently continuous, high-dimensional and often chaotic in nature. Traditi…

physics.flu-dyn2026

X-CAL: Explaining latent causality in physical space for fluid mechanics

Marcial Sanchis-Agudo, Andrés Cremades, Alvaro Martinez-Sanchez +2

We present X-CAL, a pipeline that combines a -variational autoencoder (-VAE) with the synergistic-unique-redundant decomposition (SURD)~\cite{surd} approach for causality a…

cs.LG2026

Data-Driven Reduced-Complexity Modeling of Fluid Flows: A Community Challenge

Oliver T. Schmidt, Aaron Towne, Adrian Lozano-Duran +2

We introduce a community challenge designed to facilitate direct comparisons between data-driven methods for compression, forecasting, and sensing of complex aerospace flows. The c…

physics.flu-dyn2025

General-purpose Data-driven Wall Model for Low-speed Flows Part I: Baseline Model

Yuenong Ling, Imran Hayat, Konrad Goc +1

We present a general-purpose wall model for large-eddy simulation. The model builds on the building-block flow principle, leveraging essential physics from simple flows to train a…