2 citations · 2 across the 2 of their papers we have counts for
4 papers
MENO: Hybrid Matrix Exponential-based Neural Operator for Stiff ODEs. Application to Thermochemical Kinetics
Ivan Zanardi, Simone Venturi, Marco Panesi
We introduce MENO (''Matrix Exponential-based Neural Operator''), a hybrid surrogate modeling framework for efficiently solving stiff systems of ordinary differential equations (OD…
Petrov-Galerkin model reduction for collisional-radiative argon plasma
Ivan Zanardi, Alessandro Meini, Alberto Padovan +2
High-fidelity simulation of nonequilibrium plasmas -- crucial to applications in electric propulsion, hypersonic re-entry, and astrophysical flows -- requires state-specific collis…
Scalable nonlinear manifold reduced order model for dynamical systems
Ivan Zanardi, Alejandro N. Diaz, Seung Whan Chung +2
The domain decomposition (DD) nonlinear-manifold reduced-order model (NM-ROM) represents a computationally efficient method for integrating underlying physics principles into a neu…
Petrov-Galerkin model reduction for thermochemical nonequilibrium gas mixtures
Ivan Zanardi, Alberto Padovan, Daniel J. Bodony +1
State-specific thermochemical collisional models are crucial to accurately describe the physics of systems involving nonequilibrium plasmas, but they are also computationally expen…