journal article·2019-07-01Open access

Simulation of solid propellant microstructures by combining the collective rearrangement method with the discrete element method

Liqun Xiao, Xiaolong Fu, Xuezhong Fan, Jizhen Li, Wanli Xie

AIP Advances· Volume 9· Issue 7

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.
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Research context

OpenAlex topics: Granular flow and fluidized beds · Energetic Materials and Combustion · High-Velocity Impact and Material Behavior

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Xi’an Modern Chemistry Research Institute 1 , Xi’an 710065, China

State Key Laboratory of Continental Dynamics, Department of Geology, Northwestern University 2 , Xi’an 710069, China

Funding

National Natural Science Foundation of China

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