Non‑destructive Storage Life Prediction of NEPE Propellant

被引:0
作者
Kong L. [1 ]
Dong K. [1 ]
Tang Y. [2 ]
Lai S. [1 ]
Qu Y. [1 ]
机构
[1] College of coast defense arm, Naval Aeronautical University, Yantai
[2] College of aviation fundamentals, Naval Aeronautical University, Yantai
来源
Hanneng Cailiao/Chinese Journal of Energetic Materials | 2022年 / 30卷 / 02期
关键词
Characteristic gas; Life prediction; Nitrate ester plasticized polyether(NEPE) propellant; Non‑destructive;
D O I
10.11943/CJEM2021056
中图分类号
学科分类号
摘要
In order to realize the non‑destructive measurement when predicting the storage life of nitrate ester plasticized polyether (NEPE) propellant, the high temperature accelerated aging, gas content monitoring and uniaxial tensile mechanical property experiment were carried out on NEPE propellant with 10% constant compression strain. The non‑destructive storage life prediction model based on characteristic gas contents was proposed through correlation analysis and remaining life prediction model. The results show that during the storage and aging processes, the total amount of CO gas is the largest, reaching more than 1300 mg at different temperatures. The generating rates of NO and CO are growing slowly in the early aging period, and growing faster in the late period. The generating rate of HCl increases rapidly during the eraly and late aging period and slowly in the middle. Maximum tensile strength σm and maximum elongation εm increase slightly in the early aging period, the former oscillates slightly and the latter gradually increases in the middle period, and both of them decrease sharply in the late period. The correlation between the contents of CO and the maximum tensile strength is largest and there is a single correlation between them at different temperatures. The maximum correlation value reaches about 0.93-0.95. Four life prediction methods of NEPE propellant are established based on traditional and improved aging life prediction model, tensile strength and CO content. The maximum correlation coefficient and estimation results show that the improved prediction model based on the content of CO gas release is most effective. © 2022, Editorial Board of Chinese Journal of Energetic Materials. All right reserved.
引用
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页码:163 / 170
页数:7
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