Follow
Konrad Malik
Title
Cited by
Cited by
Year
Detonation cell size model based on deep neural network for hydrogen, methane and propane mixtures with air and oxygen
K Malik, M Żbikowski, A Teodorczyk
Nuclear Engineering and Technology 51 (2), 424-431, 2019
242019
Laminar Burning Velocity Model Based on Deep Neural Network for Hydrogen and Propane with Air
K Malik, M Żbikowski, A Teodorczyk
Energies 13 (13), 3381, 2020
142020
Numerical and experimental investigation of H2-air and H2O2 detonation parameters in a 9 m long tube, introduction of a new detonation model
K Malik, M Żbikowski, D Bąk, P Lesiak, A Teodorczyk
International Journal of Hydrogen Energy 44 (17), 8743-8750, 2019
102019
Numerical and experimental investigation of methane-oxygen detonation in a 9 m long tube
K Malik, M Żbikowski, A Teodorczyk, P Lesiak
Journal of KONES 23 (4), 311--318, 2016
62016
Ignition delay time model based on a deep neural network
A Jach, M Zbikowski, K Malik, A Teodorczyk
27th ICDERS, 2019
32019
Methane-air laminar burning velocity predictions with machine learning algorithms
A Jach, M Żbikowski, K Malik, M Żbikowski, K Adamski, I Cieślak, ...
The Institute of Heat Engineering, 2017
32017
Numerical and experimental study on detonation of hydrogen-air mixtures
KP Malik
Instytut Techniki Cieplnej, 2016
12016
Numerical study on detonation of hydrogen, methane and propane mixtures with air and oxygen
KP Malik
Instytut Techniki Cieplnej, 2017
2017
in Polish Badania numeryczne i eksperymentalne detonacji mieszaniny wodoru i powietrza
KPM WMEiL, KP Malik
The system can't perform the operation now. Try again later.
Articles 1–9