2 citations · 2 across the 1 of their papers we have counts for
3 papers
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…
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…
Assessment of deconvolution-based flamelet methods for progress variable rate modeling
Zacharias Nikolaou, Luc Vervisch
A novel approach for modeling the progress variable reaction rate in Large Eddy Simulations of turbulent and reacting flows is proposed. This is done in the context of two popular…