摘要
利用机载中空纤维膜分离性能测量台架,针对分离性能随引气压力、引气温度、飞行高度等因素的变化规律开展了实验研究;并采用所获得的实验数据作为训练及验证样本,应用人工神经网络预测技术分析了该型膜的性能.研究结果显示:1所建立的数学模型可实现对中空纤维膜分离性能的有效预测;2制氮体积分数与量纲一制氮量成反比,当要求制氮体积分数较高时,其量纲一制氮量下降,制氮效率降低;3在一定制氮体积分数下,制氮量随引气温度、引气压力的增加而增加;制氮效率随引气压力的增加而增加,但随引气温度的增加而减小;4在飞行高度增加的情况下,量纲一制氮量和制氮效率都增加,而制氮体积分数的影响随飞行高度增加而减小.
Based on a test apparatus of the on-board hollow fiber membrane separation performance,the separation performance was experimentally investigated with variation of the bleed air pressure,bleed air temperature,flight altitude and other factors;the experimental data were applied into the artificial neural network prediction technology as the training and validation samples,so as to predict the performance of this membrane.The results show that：（1）the established mathematical model can effectively predict the separation performance of hollow fiber membrane;（2）the volume fraction of nitrogen-enriched air is inversely proportional to non-dimensional flow rate;so when the volume fraction of nitrogenenriched air increases,the flow rate and efficiency of nitrogen-enriched air decrease;（3）under a given volume fraction of nitrogen-enriched air,non-dimensional flow rate of nitrogenenriched air increases with bleed air temperature and bleed air pressure increasing;the efficiency of nitrogen-enriched air increases with the bleed air pressure increasing,but decreases with bleed air temperature increasing;（4）when the flight altitude increases,the non-dimensional flow rate and efficiency of nitrogen-enriched air increase,and the influence of volumefraction of nitrogen-enriched air decreases with the growing flight altitude.
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2015年第4期800-806,共7页
Journal of Aerospace Power
基金
航空科学基金(20122852038
20132852040)
国家自然科学基金(50906066)
江苏高校优势学科建设工程
关键词
机载惰化系统
中空纤维膜
人工神经网络
分离性能
引气
on-board inerting system
hollow fiber membrane
artificial neural network
separation performance
bleed air
