Zacharias Nikolaou
Zacharias Nikolaou
University of Cambridge
Verified email at strath.ac.uk
TitleCited byYear
Heat release rate markers for premixed combustion
ZM Nikolaou, N Swaminathan
Combustion and flame 161 (12), 3073-3084, 2014
542014
A 5-step reduced mechanism for combustion of CO/H2/H2O/CH4/CO2 mixtures with low hydrogen/methane and high H2O content
ZM Nikolaou, JY Chen, N Swaminathan
Combustion and flame 160 (1), 56-75, 2013
522013
Heat release rate estimation in laminar premixed flames using laser-induced fluorescence of CH2O and H-atom
IA Mulla, A Dowlut, T Hussain, ZM Nikolaou, SR Chakravarthy, ...
Combustion and Flame 165, 373-383, 2016
262016
Direct numerical simulation of complex fuel combustion with detailed chemistry: physical insight and mean reaction rate modeling
ZM Nikolaou, N Swaminathan
Combustion Science and Technology 187 (11), 1759-1789, 2015
162015
Evaluation of a reduced mechanism for turbulent premixed combustion
ZM Nikolaou, N Swaminathan, JY Chen
Combustion and flame 161 (12), 3085-3099, 2014
132014
A priori assessment of an iterative deconvolution method for LES sub-grid scale variance modelling
ZM Nikolaou, L Vervisch
Flow, Turbulence and Combustion 101 (1), 33-53, 2018
92018
Scalar flux modelling in turbulent flames using iterative deconvolution
ZM Nikolaou, RS Cant, L Vervisch
Phys. Rev. Fluids 3 (043201), 2018
72018
Progress Variable Variance and Filtered Rate Modelling Using Convolutional Neural Networks and Flamelet Methods
ZM Nikolaou, C Chrysostomou, L Vervisch, RS Cant
Flow Turbulence and Combustion, 2019
42019
Modelling turbulent premixed flames using convolutional neural networks: application to sub-grid scale variance and filtered reaction rate.
ZM Nikolaou, C Chrysostomou, L Vervisch, S Cant
arXive:1810.07944v1, 1-19, 2018
32018
Assessment of deconvolution-based flamelet methods for progress variable rate modelling.
LV Z.M. Nikolaou
Aeronautics and Aerospace Open Access Journal 2 (5), 274-281, 2018
32018
Direct mapping from LES resolved scales to filtered-flame generated manifolds using convolutional neural networks
A Seltz, P Domingo, L Vervisch, ZM Nikolaou
Combustion and Flame 210, 71-82, 2019
22019
Assessment of FSD and SDR closures for turbulent flames of alternative fuels
ZM Nikolaou, N Swaminathan
Flow, Turbulence and Combustion 101 (3), 759-774, 2018
22018
Study of multi-component fuel premixed combustion using direct numerical simulation
ZM Nikolaou
University of Cambridge, 2014
22014
Accelerating simulations using REDCHEM_v0. 0 for atmospheric chemistry mechanism reduction
ZM Nikolaou, JY Chen, Y Proestos, J Lelieveld, R Sander
Geoscientific Model Development 11 (8), 3391-3407, 2018
12018
Unresolved stress tensor modeling in turbulent premixed V-flames using iterative deconvolution: An a priori assessment
ZM Nikolaou, Y Minamoto, L Vervisch
Physical Review Fluids 4 (6), 063202, 2019
2019
Neural network-based modelling of unresolved stresses in a turbulent reacting flow with mean shear
ZM Nikolaou, C Chrysostomou, Y Minamoto, L Vervisch
arXiv:1904.08167 [physics.flu-dyn], 2019
2019
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Articles 1–16