A Real Time Variational data Assimilation Method Based on Complexity Reduction and On-the-fly Data Driven Empirical Enrichment

== Abstract ==

The Parameterized Background Data-Weak (PBDW) method is a non-intrusive, reduced basis, real-time and in-situ data assimilation framework for physical systems modeled by parametrized Partial Differential Equations for steady-state problems. The key idea of the formulation is to seek an approximation to the true field employing projection-by-data, with a first contribution from a deduced background estimate from reduced modeling and a second contribution from an update state informed by the experimental observations (correction of model bias). The present study aims at extending the PBDW formulation for time-dependent problems and proposes a sequential version to deal with sampled data. The work focuses on a time integration in the reduced order model, a data-driven empirical enrichment of the model and a state prediction for future time steps.
                                                                                                
== Video ==
{{#evt:service=cloudfront|id=257139|alignment=center|filename=69.mp4}}
                                                
== Document ==
<pdf>Media:Draft_Content_575977850A_IDC6_69.pdf</pdf>