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传统的燃烧模型致力于对固体推进剂燃烧的物理化学过程的数学描述，其发展往往受到对推进剂燃烧机理认识程度的限制，本文利用误差反传（ＢＰ）神经网络建模的方法建立了硝胺固体推进剂燃烧性能及其影响因素（硝胺含量、压强、硝胺重均粒径）的定量关系，而不考虑燃烧的具体过程，根据此定量关系对硝胺固体推进剂燃烧性能的计算表明，计算结果和实验值吻合得较好，这为推进剂配方的计算机辅助设计提供了一种新方法。
The traditional combustion model is devoted to the mathematical description of the physicochemical process of solid propellant combustion. Its development is often limited by the understanding of combustion mechanism of propellants. In this paper, the BP neural network modeling method is used to establish the nitrate Amine solid propellant combustion performance and its influencing factors (nitramine content, pressure, nitramine weight average particle size) quantitative relationship, without considering the specific combustion process, based on the quantitative relationship between the combustion performance of nitramine solid propellants The results show that the calculated results are in good agreement with the experimental data, which provides a new method for computer aided design of propellant formulations.