11 citations · 13 across the 5 of their papers we have counts for
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physics.flu-dyn2019★ 2 cited
Neural network-based modelling of unresolved stresses in a turbulent reacting flow with mean shear
Zacharias M. Nikolaou, Charalambos Chrysostomou, Yuki Minamoto +1
Data-driven methods for modelling purposes in fluid mechanics are a promising alternative given the continuous increase of both computational power and data-storage capabilities. H…
physics.flu-dyn2018
Modelling turbulent premixed flames using convolutional neural networks: application to sub-grid scale variance and filtered reaction rate
Zacharias M. Nikolaou, Charalambos Chrysostomou, Luc Vervisch +1
A purely data-driven approach using deep convolutional neural networks is discussed in the context of Large Eddy Simulation (LES) of turbulent premixed flames. The assessment of th…