This article is cited in 3 papers

Neural networks applications to combustion process simulation

B. V. Kryzhanovsky^a, N. N. Smirnov^ba, V. F. Nikitin^ab, Ia. M. Karandashev^a, M. Yu. Malsagov^a, E. V. Mikhalchenko<sup>ba

a</sup> Federal State Institution “Scientific Research Institute for System Analysis of the Russian Academy of Sciences”, Moscow, Russian Federation
^b Lomonosov Moscow State University, Moscow, Russian Federation

Abstract: Combustion process simulations are the key aspect enabling full-scale 3D simulations of advanced aerospace engines. This work studies solving chemical kinetics problems with artificial neural networks. The training datasets were generated by classical numerical methods. Choosing a multi-layer neural network architecture and fine-tuning its parameters, we developed a simple model that can solve the problem. The neural network obtained works is recursive, and by running many iterations it can predict the behavior of a chemical multimodal dynamic system.

Keywords: chemical kinetics, combustion simulation, artificial neural networks, multi-layer networks, recursive approach.

DOI: 10.51790/2712-9942-2021-2-4-2