Chiara Novelli, a Chemical Engineer from Università di Pisa, leads pioneering efforts within the ENCODING project. Her key objectives include:

1. Development of an innovative methodology for digital twins of industrial combustion systems.
2. Construction of digital twins by amalgamating numerical simulations of varying fidelity (RANS and LES) with existing and new data from ULB and RWTH Aachen.
3. Implementation of dimensionality reduction techniques such as modal decomposition and non-linear regression, utilizing Gaussian Process Regression (GPR) and Artificial Neural Networks (ANN).
4. Establishment of novel approaches for assimilating heterogeneous data sources, updating system modes and non-linear regressions based on newly available data from experiments and simulations.
5. Demonstration of the methodology on the ULB furnace, incorporating experiments from literature, as well as simulations from prior ULB research.