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Computer modeling for damage assessment of KE-rod warheads against ballistic missiles.

机译:评估KE杆式战斗部对弹道导弹的伤害的计算机建模。

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摘要

Current efforts on ballistic missile systems are focused on the development of direct-impact interceptor missiles. However, high encounter velocities and the possibility of decoy systems make a direct hit extremely difficult. In order to increase the system kill probability, new systems combine guidance technology and a guided-ejection system that can fire a cluster of penetrators towards the target. This thesis investigates some of the parameters that affect the "kill" performance of the interceptor "guided projectiles", or as commonly known in the missile industry KE-rod warheads, such as the shape, the projectile size, the number of projectiles, the ejection velocity, and the two missile terminal encounter conditions. A kinematic analysis of the two missile encounter is implemented into a computer code in Matlab(TM) 6.5 to determine the number the actual impacts and the descriptive characteristics of the impact for different encounter scenarios. Several numerical simulations of single projectile impacts are run using Smoothed Particles Hydrodynamics at predetermined impact parameters. Using the simulation results, a lethality index is developed to assess the damage for each impact condition. An Artificial Neural Network is developed for damage level prediction of impact conditions given by the kinematic analysis and not modeled using Smoothed Particles Hydrodynamics. Finally, the Artificial Neural Network is integrated to the kinematic analysis code to calculate the damage inflicted per encounter scenario. From the analysis of the results, conclusions and guidelines for the KE-rod warheads design are provided.
机译:当前在弹道导弹系统上的努力集中在发展直接冲击拦截导弹。但是,高遭遇速度和诱饵系统的可能性使直接打击极为困难。为了增加系统的击杀概率,新系统结合了制导技术和制导射弹系统,可以向目标发射一堆穿透器。本文研究了一些影响拦截器“制导弹丸”的“杀伤”性能的参数,或在导弹工业中普遍采用的KE杆式弹头的参数,例如形状,弹丸大小,弹丸数量,弹射速度,与两个导弹终端相遇。在Matlab TM 6.5中的计算机代码中实现了两次导弹遭遇的运动学分析,以确定实际遭遇的次数以及针对不同遭遇情景的撞击的描述性特征。在预定的冲击参数下,使用“平滑粒子流体动力学”对单个弹丸撞击进行了一些数值模拟。使用仿真结果,可以建立一个杀伤力指数,以评估每种冲击条件下的破坏程度。开发了一种人工神经网络,用于通过运动学分析给出冲击条件的损伤程度预测,而不是使用“平滑粒子流体动力学”进行建模。最后,将人工神经网络集成到运动分析代码中,以计算每次遇到场景所造成的伤害。通过对结果的分析,可以得出KE棒式战斗部设计的结论和指导原则。

著录项

  • 作者

    Espino, Luis A.;

  • 作者单位

    The University of Texas at El Paso.;

  • 授予单位 The University of Texas at El Paso.;
  • 学科 Engineering Mechanical.; Engineering Aerospace.
  • 学位 M.S.
  • 年度 2004
  • 页码 353 p.
  • 总页数 353
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;航空、航天技术的研究与探索;
  • 关键词

  • 入库时间 2022-08-17 11:44:22

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