小口径超空泡子弹头部外形的优化设计

马文轩; 于勇; 胡俊

doi:10.11883/bzycj-2021-0092

小口径超空泡子弹头部外形的优化设计

doi: 10.11883/bzycj-2021-0092

北京理工大学宇航学院，北京 100081

详细信息

作者简介:
马文轩（1997－　），男，硕士研究生，1443407530@qq.com

通讯作者:
于　勇（1976－　），男，博士，副教授，yuyong@bit.edu.cn

中图分类号: O359
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- 文章访问数: 412
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- PDF下载量: 61
- 被引次数: 0
出版历程
- 收稿日期: 2021-03-18
- 修回日期: 2021-09-17
- 网络出版日期: 2022-02-12
- 刊出日期: 2022-04-07

Optimal design of the head shape of a small-caliber supercavitating projectile

School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China

摘要

摘要: 在水下高速运动时，小口径射弹周围的水会发生空化现象，阻力系数最优的弹头几何外形对应着射弹被空泡全包裹的超空泡状态。针对一种小口径射弹，可以利用计算流体力学（CFD）数值方法模拟含空化现象的气液两相流动，探究空泡形态和阻力系数与射弹头部几何外形的关系。选取三段锥形为基本射弹头形，采用分步优化方式对射弹头部外形进行了优化。同时，结合神经网络与序列二次规划（SQP）算法减少优化过程中的计算量，缩短了优化工作所需的总时间。优化后的射弹阻力系数比优化前的减小约30%，且能够形成包裹全弹体的超空泡。
- 超空泡射弹 /
- 阻力系数 /
- 分步优化 /
- 神经网络 /
- 序列二次规划算法
Abstract: When a small-caliber projectile is moving underwater at a high speed, the water around the projectile will cavitate. The cavitation effect can greatly reduce the resistance of the moving vehicle, and the geometric shape of the warhead with the best drag coefficient corresponds to the supercavitating state where the projectile is completely enveloped by cavitation. Aiming at a small-caliber projectile, the computational fluid dynamics method is used to numerically simulate the gas-liquid two-phase flow with cavitation phenomenon, while the relationships of the cavitation shape and the drag coefficient with the geometry of the projectile’s head shape are explored. The three-segment cone type is selected as the basic projectile type, and the shape of the projectile is optimized by step optimization method. First, seven parameters are used to describe the three-segment cone shape of the projectile, and then the projectile is optimized in the order of the first section cone, the second and the third section cone. This method is used because the seven parameters are not independent of each other, and it is difficult to quantitatively determine the relationship between an individual parameter and the performance of the projectile. At the same time, the neural network is employed to perform nonlinear fitting with a large number of CFD numerical simulation results as learning samples, and the approximate calculation model of the shape parameters-drag coefficient of the projectile is established by neural network. Finally, the sequential quadratic programming (SQP) algorithm is introduced to find the optimal solution of the approximate calculation model. The use of neural network and SQP algorithm reduces the amount of calculation in the optimization process and the total time required for optimization work. After two rounds of optimization, the optimized projectile has a better ability to form supercavitation, and its drag coefficient has also been significantly improved compared to the original projectile, with a reduction about 30% compared to the projectile before optimization.
- supercavitating projectile /
- drag coefficient /
- multi-step optimization /
- neural network /
- SQP algorithm

HTML全文

图 1 计算域网格划分和边界条件

Figure 1. Mesh generation and boundary conditions

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图 2 DBP87普通弹

Figure 2. DBP87 bullet

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图 3 DSG公司的自然超空泡技术水下枪弹

Figure 3. DSG’s general purpose supercavitating bullet

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图 4 调整后的射弹头部及参数

Figure 4. Projectile parameters after adjustment

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图 5 DBP87和射弹1的空泡形态

Figure 5. Cavitation shapes of DBP87 and projectile 1

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图 6 阻力系数随倾斜角θ₁的变化

Figure 6. Resistance coefficients varying with θ₁

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图 7 空泡形态随倾斜角θ₁的变化

Figure 7. Cavitation shapes varying with θ₁

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图 8 阻力系数随空化器直径D₁的变化

Figure 8. Resistance coefficients varying with D₁

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图 9 空泡形态随空化器直径D₁的变化

Figure 9. Cavitation shapes varying with D₁

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图 10 阻力系数随倾斜角θ₂的变化

Figure 10. Resistance coefficients varying with θ₂

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图 11 空泡形态随倾斜角θ₂的变化

Figure 11. Cavitation shapes varying with θ₂

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图 12 阻力系数随长度L₂的变化

Figure 12. Resistance coefficients varying with L₂

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图 13 空泡形态随长度L₂的变化

Figure 13. Cavitation shapes varying with L₂

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图 14 BP神经网络近似计算模型

Figure 14. Approximate calculation model of BP neural network

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图 15 优化后的射弹与原始射弹的外形对比

Figure 15. Shape comparisons of the optimized projectiles with the original projectile

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图 16 射弹速度900 m/s时优化后的射弹与原始射弹的空泡形态对比

Figure 16. Cavitation shape comparisons of the optimized projectiles with the original projectiles at 900 m/s

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图 17 射弹速度600 m/s时优化后的射弹与原始射弹的空泡形态对比

Figure 17. Cavitation shape comparisons of the optimized projectiles with the original projectiles at 600 m/s

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图 18 射弹速度400 m/s时优化后的射弹与原始射弹的空泡形态对比

Figure 18. Cavitation shape comparisons of the optimized projectiles with the original projectiles at 400 m/s

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表 1 射弹1的参数

Table 1. Parameters of projectile 1

θ₁/(°) L₁/mm θ₂/(°) L₂/mm θ₃/(°) L₃/mm D₁/mm

50.054 0.480 12.555 2.315 7.404 11.704 0.780

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表 2 射弹2的参数

Table 2. Parameters of projectile 2

θ₁/(°) L₁/mm θ₂/(°) L₂/mm θ₃/(°) L₃/mm D₁/mm

55.000 0.387 12.555 2.409 7.404 11.704 0.780

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表 3 射弹3的参数

Table 3. Parameters of projectile 3

θ₁/(°) L₁/mm θ₂/(°) L₂/mm θ₃/(°) L₃/mm D₁/mm

55.000 0.387 13.000 2.409 7.309 11.704 0.780

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表 4 射弹4的参数

Table 4. Parameters of projectile 4

θ₁/(°) L₁/mm θ₂/(°) L₂/mm θ₃/(°) L₃/mm D₁/mm

55.000 0.387 13.000 3.500 6.704 10.596 0.780

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表 5 射弹5的参数

Table 5. Parameters of projectile 5

θ₁/(°) L₁/mm θ₂/(°) L₂/mm θ₃/(°) L₃/mm D₁/mm

55.000 0.404 13.000 4.000 6.387 10.096 0.780

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