Abstract
The polydisperse particulate components in solid propellant are incompact and randomly packed, which determines the microstructural features of the propellants. A packing method, combining the discrete element method (DEM) and collective rearrangement method, was applied to model propellant microstructures. The validity of this method was investigated by comparing the calculated and experimental properties of the monodisperse, bidisperse, and polydisperse random close packed sphere systems. The propellant models were generated using a stepwise approach, and their homogeneity, local randomness, and long-range pattern were analyzed. A statistical study of aluminum (Al) particle distribution was also conducted. The results indicated that this packing method can effectively determine the microscopic characteristics of random close packed monodisperse spheres. The maximum packing fraction of bidisperse and polydisperse spheres had similar trends to those reported in experimental studies and using other packing algorithms. In addition, this method was capable of generating non-compacted propellant structures with uniformly distributed polydisperse particles. The radial distribution functions (RDFs) for Al-Al particles provided information about the Al distribution, but this was mainly related to the size and content of the large particle components.
Highlights
Solid propellants are heterogeneous composite materials filled with particulate components and polymer binders
It has been reported that higher growth rates reduce the packing capability, while slower growth rates enable higher packing fractions
We considered that a packing method using the actual sizes and contents of particles according to the propellant formulation to construct a propellant packing model would be more appropriate
Summary
Solid propellants are heterogeneous composite materials filled with particulate components and polymer binders. Obtaining detailed structural information for solid propellants is critical for a comprehensive understanding of their performance. It is a complicated and challenging task to reconstruct propellant heterogeneity, even using tomography.. Various packing methods have been proposed and are capable of generating 2D7,8 and 3D propellant packing models.. Various packing methods have been proposed and are capable of generating 2D7,8 and 3D propellant packing models.9–11 Based on these models, several Al agglomeration, propellant combustion, and propellant mechanical models have been established.. The current 3D models are typically generated by a particle expansion method, such as those proposed by Lubachevsky-Stillinger.. It has been reported that higher growth rates reduce the packing capability, while slower growth rates enable higher packing fractions.
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