基于斜坡实验的高固含量推进剂药浆流变行为研究

    Rheological behavior of high solid content propellant based on slope experiments

    • 端羟基聚丁二烯(HTPB)推进剂中固含量通常极高(ϕ≥0.5),存在颗粒-黏结剂、颗粒间复杂的相互作用,其流变性显著区别于低、中固含量固液体系,目前仍缺乏有效的流变测试手段及分析方法。基于HTPB推进剂物性特征,搭建了斜坡流变仪装置,以高黏HTPB为黏合剂、丙烯酸酯-苯乙烯-丙烯腈共聚物(ASA)颗粒为代料颗粒,配置了极高固含量体系(ϕ=0.365~0.513),通过激光位移传感器精确捕捉该体系在斜坡上的流动特征(表面流速和液膜厚度),基于幂律模型推导出流变参数(幂律指数n和稠度系数K)的解析解,并构建了其流变本构方程。结果表明,当ϕ从0.365增至0.513时,n由 0.893 降至 0.432,K由153.6 Pa·sn升至670.9 Pa·sn,体系表现出强烈剪切稀化特征,并且nK均随固含量ϕ呈指数变化关系。与旋转流变仪测试结果相比,斜坡法测量结果的预测误差在10%以内,验证了斜坡法在高固含量体系流变测试中具有良好的可靠性与适用性。

       

      Abstract: The solid content in hydroxyl-terminated polybutadiene (HTPB) is usually extremely high (ϕ≥0.5), and there exists complex interactions between particles and binders as well as among particles. Its rheological properties are significantly different from those of solid-liquid systems with low and medium contents. In the present work, an inclined-plane rheometer was built to suit the specific properties of HTPB systems. Propellant substitutes with high-solid suspensions (ϕ=0.365~0.513) were prepared using high-viscosity hydroxyl-terminated polybutadiene (HTPB) as the binder and acrylate-styrene-acrylonitrile (ASA) particles as solids. A laser displacement sensor was used to measure the liquid-film thickness and surface velocity of the flows on the slope, and the explicit expressions for the power-law index n and consistency coefficient K were derived from the power-law model to establish the constitutive equation. The results show that n falls from 0.893 to 0.432 and K rises from 153.6 Pa·sn to 670.9 Pa·sn as ϕ increases from 0.365 to 0.513. These phenomena reflect strong shear-thinning behavior, and these model parameters, i.e. n and K, exhibit exponential dependence on solid content ϕ. Empirical correlations for n and K as functions of ϕ are now available with a prediction error below 10%. The method provides a simple and reliable means of characterizing high-solid HTPB propellants and delivers the essential physical property data required for equipment design and process optimization.

       

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