3 citations · 3 across the 3 of their papers we have counts for
3 papers · 1 filter
pyforce-1.0.0: Python Framework for data-driven model Order Reduction of multi-physiCs problEms
Stefano Riva, Yantao Luo, Carolina Introini +1
pyforce is a Python package implementing Data-Driven Reduced Order Modelling techniques for applications to multi-physics problems, mainly set in the Nuclear Engineering world. The…
From Models To Experiments: Shallow Recurrent Decoder Networks on the DYNASTY Experimental Facility
Stefano Riva, Andrea Missaglia, Carolina Introini +2
The Shallow Recurrent Decoder networks are a novel paradigm recently introduced for state estimation, combining sparse observations with high-dimensional model data. This architect…
Towards Efficient Parametric State Estimation in Circulating Fuel Reactors with Shallow Recurrent Decoder Networks
Stefano Riva, Carolina Introini, J. Nathan Kutz +1
The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering systems; nuclear reactors represent p…