Deep encoder–decoder hierarchical convolutional neural networks for conjugate heat transfer surrogate modeling
Conjugate heat transfer (CHT) analyses are vital for the design of many energy systems.
However, high-fidelity CHT numerical simulations are computationally intensive, which limits …
However, high-fidelity CHT numerical simulations are computationally intensive, which limits …
[HTML][HTML] Adversarial image-to-image model to obtain highly detailed wind fields from mesoscale simulations in urban environments
J Milla-Val, C Montañés, N Fueyo - Building and Environment, 2024 - Elsevier
We propose a conditional Generative Adversarial Network (cGAN) that can produce detailed
local wind fields in urban areas, comparable in level of detail to those from Computational …
local wind fields in urban areas, comparable in level of detail to those from Computational …
[HTML][HTML] Hierarchical thermal modeling and surrogate-model-based design optimization framework for cold plates used in battery thermal management systems
The continued advancement of battery-powered electric vehicles (EVs) towards higher
energy and power densities poses significant thermal challenges for batteries. This work …
energy and power densities poses significant thermal challenges for batteries. This work …
[HTML][HTML] An image-to-image adversarial network to generate high resolution wind data over complex terrains from weather predictions
J Milla-Val, C Montañés, N Fueyo - Engineering Applications of Artificial …, 2025 - Elsevier
In this work, we propose a Machine Learning method to predict detailed wind fields over
extensive, complex terrains. The ability to predict local wind fields is becoming increasingly …
extensive, complex terrains. The ability to predict local wind fields is becoming increasingly …