Burning Rate Prediction of Solid Rocket Propellant (SRP) with High-Energy Materials Genome (HEMG)

Abstract

High-energy materials genome (HEMG) is an analytical and calculation tool that contains relationships between variables of the object, which allows researchers to calculate the values of one part of the variables through others, solve direct and inverse tasks, predict the characteristics of non-experimental objects, predict parameters to obtain an object with desired characteristics and execute virtual experiments for conditions which cannot be organized or have difficultly being organized. HEMG is based on experimental data on the burning rate of various high-energy materials (HEMs) under various conditions, on the metadata on the quantum and physicochemical characteristics of HEMs components as well as on thermodynamic characteristics of HEMs as a whole. The history and current status of the emergence of HEMG are presented herein. The fundamental basis of the artificial neural networks (ANN) as a methodological HEMG base, as well as some examples of HEMG conception used to create multifactor computational models (MCM) of solid rocket propellants (SRP) combustion, is presented.