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长杆高速侵彻的特征控制参量分析

Analysis of characteristic control parameters of long-rod penetration
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摘要 针对理想长杆侵彻,通过对长杆侵彻Alekseevskii-Tate模型近似解进行分析,指出单一的无量纲速度衰减系数α(deceleration index)不足以完全表征长杆高速侵彻的准定常阶段。在此基础上,重新定义了2个无量纲特征参量:Johnson破坏数ΦJp和特征时间系数β,2个参量之间的关系为α=β/ΦJp。分析表明,ΦJp和β(或α和β)可实现对长杆高速侵彻准定常阶段的弹尾速度的完全表征;若再引入长杆弹相对临界速度vc*,则可完全表征长杆侵彻的准定常阶段。此外,还证明了α能够判定侵彻过程偏离定常状态的程度,并指出通过确定ΦJp和β(或α和β),可针对攻防需求对长杆弹侵彻设计进行指导。 For ideal long-rod penetration,by analyzing the approximate solutions of the Alekseevskii-Tate model for long-rod penetration,it is pointed out that the single deceleration indexαis not sufficient to fully describle the quasi-steady process of long-rod penetration.This paper redefines two dimensionless parameters,namely Johnson demage parameterΦJp and characteristic time parameterβ,andα=β/ΦJp.The analysis shows that two characteristic parametersΦJp andβ(orαandβ)can completely characterize the impact velocity of the projectile tail in the quasi-steady process of long-rod penetration.If the dimensionless critical impact velocity vc*is introduced,the quasi-steady process of long-rod penetration can be fully characterized.In addition,this paper strictly proves that the degree of deviation from the steady state in the penetration process can be determined byα,and confirms that by determiningΦJp andβ(orαandβ),the design of long-rod penetration can be guided for offensive and defensive needs.
作者 尹志勇 陈小伟 YIN Zhiyong;CHEN Xiaowei(State Key Laboratory of Explosion Science and Technology,Beijing Institute of Technology,Beijing 100081,China;School of Mechatronical Engineering,Beijing Institute of Technology,Beijing 100081,China;Advanced Research Institute for Multidisciplinary Science,Beijing Institute of Technology,Beijing 100081,China)
出处 《爆炸与冲击》 EI CAS CSCD 北大核心 2021年第2期136-142,共7页 Explosion and Shock Waves
基金 国家自然科学基金(11627901,11872118)。
关键词 长杆侵彻 Alekseevskii-Tate模型 特征参量 Johnson破坏数 特征时间系数 无量纲速度衰减系数 long-rod penetration Alekseevskii-Tate model characteristic parameters Johnson demage parameter characteristic time parameter deceleration index
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