6 papers
Implicit-Explicit time integration scheme with Physics-based preconditioning for two-fluid tokamak boundary simulations
Micol Bassanini, Simone Deparis, Paolo Ricci +4
In this work, a globally stiffly accurate Implicit-Explicit (IMEX) Runge-Kutta scheme is developed and implemented in the GBS code [Ricci et al., Plasma Phys. Control. Fusion, 2012…
Can the perfect Swiss alphorn be designed? A combination of reduced basis method and machine learning for shape optimization
Fabio Marcinnò, Clément Froidevaux, Leonardo Bocchieri +3
In this work, we investigate the shape optimization of a Swiss alphorn to achieve resonance frequencies as close as possible to prescribed target notes. We construct an accurate ge…
Generalisation of the Total Linearisation Method to Three-dimensional Free-Surface Flows
Tyler Benkley, Simone Deparis, Paolo Ricci +1
An iterative Finite Element method predicated on a linearisation of the weak form around a reference configuration is derived for general, three-dimensional, free-surface flows, in…
IMEX-RB: a self-adaptive implicit-explicit time integration scheme exploiting the reduced basis method
Micol Bassanini, Simone Deparis, Francesco Sala +1
In this work, we introduce a self-adaptive implicit-explicit (IMEX) time integration scheme, named IMEX-RB, for the numerical integration of systems of ordinary differential equati…
Deformable registration and generative modelling of aortic anatomies by auto-decoders and neural ODEs
Riccardo Tenderini, Luca Pegolotti, Fanwei Kong +4
This work introduces AD-SVFD, a deep learning model for the deformable registration of vascular shapes to a pre-defined reference and for the generation of synthetic anatomies. AD-…
Mimetic finite difference schemes for transport operators with divergence-free advective field and applications to plasma physics
Micol Bassanini, Simone Deparis, Paolo Ricci
In wave propagation problems, finite difference methods implemented on staggered grids are commonly used to avoid checkerboard patterns and to improve accuracy in the approximation…