9 papers
The near-wall cycle for skin-friction generation revealed through explainable deep learning
Andres Cremades, Sergio Hoyas, Ricardo Vinuesa
Skin friction in wall-bounded turbulence is produced by intermittent near-wall motions, yet conventional coherent-structure definitions do not identify which individual events gene…
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…
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…
Explainable deep learning reveals the physical mechanisms behind the turbulent kinetic energy equation
Francisco Alcántara-Ãvila, Andrés Cremades, Sergio Hoyas +1
In this work, we investigate the physical mechanisms governing turbulent kinetic energy transport using explainable deep learning (XDL). An XDL model based on SHapley Additive exPl…
Exploring the interplay between Planetary Boundaries and Sustainable Development Goals using Large Language Models
Lamyae Rhomrasi, Pilar Manchón, Ricardo Vinuesa +4
By analyzing 40,037 climate articles using Large Language Models (LLMs), we identified interactions between Planetary Boundaries (PBs) and Sustainable Development Goals (SDGs). An…
Evaluating Visual Mathematics in Multimodal LLMs: A Multilingual Benchmark Based on the Kangaroo Tests
Arnau Igualde Sáez, Lamyae Rhomrasi, Yusef Ahsini +5
Multimodal Large Language Models (MLLMs) promise advanced vision language capabilities, yet their effectiveness in visually presented mathematics remains underexplored. This paper…