Use of Neural Networks in Modelling the Mechanoactivation Process MoS2

New approaches in the field of modelling the processes of mechanoactivation of fuel additives will significantly improve the quality of diesel fuel modification and increase the efficiency of internal combustion engines. This is primarily due to the possibility of accurate dosing, as well as to the increase in additive efficiency due to the formation of a uniform particle size distribution of additives. The use of vortex bed apparatuses for mechanoactivation opens up great opportunities associated with the accuracy of setting the modes of mechanoactivation of fuel additives, which can occur both in the dry state and when introduced into the fuel. The efficiency of the mechanoactivation process is significantly increased by using neural networks at the stage of mathematical modelling, taking into account the process of electromagnetic field formation, as well as grinding and mechanoactivation of the fuel additive.