29 citations · 32 across the 3 of their papers we have counts for
4 papers
Uncertainty quantification of a thrombosis model considering the clotting assay PFA-100
Rodrigo Méndez Rojano, Mansur Zhussupbekov, James F. Antaki +1
Mathematical models of thrombosis are currently used to study clinical scenarios of pathological thrombus formation. Most of these models involve inherent uncertainties that must b…
Observation data compression for variational assimilation of dynamical systems
Sibo Cheng, Didier Lucor, Jean-Philippe Argaud
Accurate estimation of error covariances (both background and observation) is crucial for efficient observation compression approaches in data assimilation of large-scale dynamical…
Physics-aware deep neural networks for surrogate modeling of turbulent natural convection
Didier Lucor, Atul Agrawal, Anne Sergent
Recent works have explored the potential of machine learning as data-driven turbulence closures for RANS and LES techniques. Beyond these advances, the high expressivity and agilit…
Reduced-order modeling of hemodynamics across macroscopic through mesoscopic circulation scales
Olivier Adjoua, Stéphanie Pitre-Champagnat, Didier Lucor
We propose a hemodynamic reduced-order model bridging macroscopic and meso-scopic blood flow circulation scales from arteries to capillaries. In silico tree like vascular geometrie…