Our goal is to speed up design processes and to reduce time to market :

  • NeurEco creates Reduced Order Models (ROMs) from a small amount of simulation data

  • It goes beyond ROMs by creating a real-time copy of a complex high-fidelity simulation tool, from a few simulation results

  • Beyond learning the data, NeurEco learns the underlying rules; It happens that the NeurEco model is more in line with the laws of physics than the data itself

  • This is the basis of a robust long-term dynamic prediction



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Pellet clad interaction stress corrosion cracking
Nuclear core cooling system simulation
Neutronic fluxes prediction
Optimal parameters of an antenna