Machine learning models for the prediction of turbulent combustion speed for hydrogen-natural gas spark ignition engines.

The work carried out in this paper focused on "Machine learning models for the prediction of turbulent combustion speed for hydrogen-natural gas spark ignition engines". The aim of this work is to develop and verify the ability of machine learning models to solve the problem of estimating the turbulent flame speed for a spark-ignition internal combustion engine operating with a hydrogen-natural gas mixture, then evaluate the relevance of these models in relation to the usual approaches. The novelty of this work is the possibility of a direct calculation of turbulent combustion speed with a good precision, using only machine learning model.