6 citations · 6 across the 5 of their papers we have counts for
5 papers
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…
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-…
Model order reduction of hemodynamics by space-time reduced basis and reduced fluid-structure interaction
Riccardo Tenderini, Simone Deparis
In this work, we apply the space-time Galerkin reduced basis (ST-GRB) method to a reduced fluid-structure interaction model, for the numerical simulation of hemodynamics in arterie…
Space-time reduced basis methods for parametrized unsteady Stokes equations
Riccardo Tenderini, Nicholas Mueller, Simone Deparis
In this work, we analyse space-time reduced basis methods for the efficient numerical simulation of hemodynamics in arteries. The classical formulation of the reduced basis (RB) me…