A mechanical-thermal-chemical coupling discrete element method model for simulating hotspot generation and ignition in HMX-based explosives

被引:0
作者
Yang, Kaiyuan [1 ,2 ]
Zhou, Yang [1 ]
Shen, Chunying [1 ]
Chen, Xizhong [2 ]
Cao, Luoxia [1 ]
机构
[1] China Acad Engn Phys, Inst Chem Mat, Mianyang 621900, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Chem & Chem Engn, Dept Chem Engn, Shanghai 200240, Peoples R China
来源
PARTICUOLOGY | 2025年 / 104卷
关键词
Polymer-bonded explosive (PBX); Discrete element method (DEM); Hotspot; Impact; Ignition mechanism; HEAT-CONDUCTION; MULTI-SPHERE; DEFLAGRATION; CONTACT;
D O I
10.1016/j.partic.2025.06.007
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Polymer-bonded explosives (PBXs) are widely used in military applications due to their high energy density, but their safety under impact loading remains a critical concern due to hotspot-induced ignition risks. While existing experimental and continuum methods face limitations in capturing submillisecond mesoscale processes and discontinuous damage evolution, this study develops an integrated Discrete Element Method (DEM) framework integrating the Edinburgh Elasto-Plastic-Adhesive (EEPA) contact model with Arrhenius reaction kinetics, where mechanical energy dissipation deterministically drives thermal-chemical ignition. The framework successfully predicts hotspot generation and ignition thresholds in cyclotetramethylene tetranitramine (HMX) particle explosives under impact loading. The maximum temperatures of the cubic sample are consistent with the literature and the verification analysis of a Steven Test is aligned with an experiment in literature. Application to Spigot and Drop Tests reveals strain energy accumulation and damping dissipation as dominant ignition mechanisms, with chemical activation showing exponential dependence on mechanical heating. Compared to existing DEM studies focusing on single-physics processes, this work establishes a more comprehensive and better predictive tool for mapping mechanical loading conditions to ignition thresholds. (c) 2025 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:68 / 87
页数:20
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