新型路基同心筒热冲击机理与热环境影响因子

杨风波 马大为 薛新宇 崔龙飞

杨风波, 马大为, 薛新宇, 崔龙飞. 新型路基同心筒热冲击机理与热环境影响因子[J]. 爆炸与冲击, 2016, 36(2): 153-160. doi: 10.11883/1001-1455(2016)02-0153-08
引用本文: 杨风波, 马大为, 薛新宇, 崔龙飞. 新型路基同心筒热冲击机理与热环境影响因子[J]. 爆炸与冲击, 2016, 36(2): 153-160. doi: 10.11883/1001-1455(2016)02-0153-08
Yang Fengbo, Ma Dawei, Xue Xinyu, Cui Longfei. Thermal shock mechanism and thermal environment influencing factors of a new concentric canister launcher[J]. Explosion And Shock Waves, 2016, 36(2): 153-160. doi: 10.11883/1001-1455(2016)02-0153-08
Citation: Yang Fengbo, Ma Dawei, Xue Xinyu, Cui Longfei. Thermal shock mechanism and thermal environment influencing factors of a new concentric canister launcher[J]. Explosion And Shock Waves, 2016, 36(2): 153-160. doi: 10.11883/1001-1455(2016)02-0153-08

新型路基同心筒热冲击机理与热环境影响因子

doi: 10.11883/1001-1455(2016)02-0153-08
详细信息
    作者简介:

    杨风波(1987—),男,博士后,助理研究员,yangfengbo.cool@163.com

  • 中图分类号: O383.3;TJ762.1

Thermal shock mechanism and thermal environment influencing factors of a new concentric canister launcher

  • 摘要: 针对新型同心筒自力发射高速热冲击载荷下热环境评估与影响因子决策问题,结合弹性变形和域动分层结合的动网格技术,求解了二维轴对称Navier-Stokes方程,分析了新型路基同心筒流场机理与热冲击特性,并确定了热环境评价指标;通过建立以优化拉丁超立方试验设计和径向基神经网络为理论基础的近似数学模型,解决了CFD自动建模困难、计算量大的难点;结合径向基神经网络训练方法,对导弹热环境的影响因子进行了智能决策研究。分析表明:倒吸进入新型同心筒内筒的低温气体有力改善了同心筒热环境;建立的近似模型精度较高,满足工程需求;对导弹热环境的影响因子从大到小依次为筒底导流板直径、筒底导流板长度、导流器高度;为导弹热环境多学科优化设计提供参考。
  • 图  1  超声速伴随射流计算结果

    Figure  1.  Calculation results of supersonic jet

    图  2  传统优化同心筒示意图

    Figure  2.  Schematic of a traditional concentric canister launcher

    图  3  新型同心筒结构方案

    Figure  3.  Schematic of a new concentric canister launcher

    图  4  2种方案观测1面温度时程曲线

    Figure  4.  Temperature histories of the two schemes on observation plane 1

    图  5  路基新型方案在不同时刻温度分布云图

    Figure  5.  Contour of temperature distribution at different time in new roadbed scheme

    图  6  新型同心筒优化参数

    Figure  6.  Optimized parameters of a new concentric canister launcher scheme

    图  7  3种随机方案观测1面温度时程曲线

    Figure  7.  Temperature histories of three random schemeson observation plane 1

    图  8  热环境影响因子分析原理流程图

    Figure  8.  Principle flowchart of the optimization platform

    图  9  三因素样本空间分布图

    Figure  9.  Distribution of sampling points for three factors

    图  10  热环境评价指标变化比例曲线

    Figure  10.  The changing ratio curve of the evaluating indexof thermal environment

    表  1  3种随机方案中观测1面相关参量

    Table  1.   Related parameters of three random schemes on observation plane 1

    方案 Tmax/K $\int_{0}^{0.1}{(T-300)}\text{d}t$
    1 642.88 7.029
    2 1 059.20 22.849
    3 1 372.37 14.510
    下载: 导出CSV

    表  2  优化拉丁超立方设计样本空间

    Table  2.   Sample space of optimal Latin hypercube design

    试验 L1/Max(L1) L2/Max(L2) d/Max(d)
    1 0.613 6 0.905 6 0.936 5
    2 0.823 7 0.571 4 0.796 6
    3 0.810 2 0.796 6 0.822 0
    4 0.688 1 0.593 2 0.663 1
    8 0.667 8 0.578 7 0.853 8
    26 0.606 8 0.680 4 0.847 5
    45 0.993 2 0.941 9 0.803 0
    下载: 导出CSV

    表  3  热环境评价指标随机误差分析

    Table  3.   Random error analysis of thermal environment evaluating index

    试验 $\int_{0}^{0.1}{(T-300)}\text{d}t$
    CFD计算值 径向基网络预测值 |ε|/%
    6 11.901 4 11.676 9 1.89
    15 20.417 3 20.660 9 1.19
    29 13.720 6 13.229 8 3.71
    38 15.852 2 15.699 8 0.96
    54 18.396 3 18.085 5 1.69
    下载: 导出CSV
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出版历程
  • 收稿日期:  2014-08-13
  • 修回日期:  2015-11-10
  • 刊出日期:  2016-03-25

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