基于BP神经网络的底排推进剂快速降压燃烧行为预测

Ling Zhang, Yan Zhou, Yonggang Yu
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引用次数: 1

摘要

底排药是采用底排技术的增程炮弹的重要组成部分。非定常剧烈燃烧导致熄灭、重燃或临界状态,对范围弥散产生影响。燃烧行为由燃烧室初始压力和最大压力衰减率决定,本文采用模拟实验装置对其进行了研究。建立了与快速降压相关的燃烧状态BP神经网络预测模型。该预测模型很容易根据两个压力变化参数给出燃烧行为。在工程实践中,利用该模型可以方便地预测弹丸飞出炮口时刻底排单元的燃烧状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid Depressurization Burning Behavior Prediction of Base Bleed Propellant Based on BP Neutral Network
Base bleed propellant is an important component of the increasing rang projectile using base bleed technology. Unsteady strongly combustion leads to extinguish, reignition or critical state which produce an effect on rang dispersion. The burning behavior is determined by the initial pressure of combustion chamber and the maximum pressure decay rate, which was investigated by simulation experimental device in this study. A BP neural network prediction model of combustion state related to rapid depressurization was constructed. This prediction model is very easy to give the burning behavior according to the two pressure changing parameters. It is convenient to predict the base bleed unit combustion state at the moment of the projectile flying out of gun muzzle using this model in engineering practice.
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