3 papers
physics.flu-dyn2024
Mean flow data assimilation using physics-constrained Graph Neural Networks
M. Quattromini, M. A. Bucci, S. Cherubini +1
Despite their widespread use, purely data-driven methods often suffer from overfitting, lack of physical consistency, and high data dependency, particularly when physical constrain…
physics.flu-dyn2023
Enhancing Data-Assimilation in CFD using Graph Neural Networks
Michele Quattromini, Michele Alessandro Bucci, Stefania Cherubini +1
We present a novel machine learning approach for data assimilation applied in fluid mechanics, based on adjoint-optimization augmented by Graph Neural Networks (GNNs) models. We co…
physics.flu-dyn2023
Active learning of data-assimilation closures using Graph Neural Networks
Michele Quattromini, Michele Alessandro Bucci, Stefania Cherubini +1
The spread of machine learning techniques coupled with the availability of high-quality experimental and numerical data has significantly advanced numerous applications in fluid me…