基于气动代理模型的雷箭分离快速仿真

聂文超; 蔡卫军

doi:10.11993/j.issn.2096-3920.2019.06.013

基于气动代理模型的雷箭分离快速仿真

doi: 10.11993/j.issn.2096-3920.2019.06.013

中国船舶重工集团有限公司第705研究所, 陕西西安, 710077

详细信息

作者简介:
聂文超(1989-), 男, 在读硕士, 研究方向为鱼雷总体技术.

中图分类号: TJ631.8; V211
计量
- 文章访问数: 379
- HTML全文浏览量: 13
- PDF下载量: 225
- 被引次数: 0
出版历程
- 收稿日期: 2019-02-19
- 修回日期: 2019-05-16
- 刊出日期: 2019-12-31

Rapid Simulation on Torpedo-Rocket Separation Based on the Aerodynamic Surrogate Model

The 705 Research Institute, China Shipbuilding Industry Corporation, Xi’an 710077, China

摘要

摘要: 由于助飞鱼雷结构布局紧凑、分离过程迅速且气动干扰严重, 导致雷箭分离过程容易发生相互碰撞, 因此其成为助飞鱼雷研制中必须解决的一项关键技术。目前常采用试验和数值仿真方法解决这一问题, 但是雷箭分离过程的设计需要对多参数多工况进行计算, 迭代寻优, 上述2种方法并不满足大量、快速的计算要求。针对此, 文中提出了基于径向基神经网络气动代理模型与虚拟样机联合仿真的方法。该方法通过提取影响气动力的关键因素, 利用试验或数值计算得到气动力样本库, 基于径向基神经网络算法建立了气动代理模型, 具有良好的逼近和预测精度。联合雷箭分离多体动力学虚拟样机模型, 可对雷箭分离过程进行快速仿真及对各参数的影响规律进行分析。
- 雷箭分离 /
- 气动力 /
- 径向基神经网络 /
- 代理模型
Abstract: Due to compact structure layout of a rocket-assisted torpedo, rapid torpedo-rocket separation process, and complex aerodynamic interference, the multi-body interference is easy to occur in the separation process. In the design of the rocket-assisted torpedo, the torpedo-rocket separation technology is crucial. The torpedo-rocket separation design is an iterative optimization process for multiple parameters and operating conditions, however the existing wind tunnel test method and numerical simulation method do not satisfy the requirement of huge and fast calculation. In this paper, a co-simulation method based on the aerodynamic surrogate model and the virtual prototype model is proposed. In this method, the key factors affecting the aerodynamic force are extracted, the sample database of input and output is obtained through test or numerical calculation, and an aerodynamic surrogate model with high approximation and prediction accuracy is established using radial basis neural network. Combined with the multi-body dynamic virtual prototype model of rocket-assisted torpedo, this method can be used to quickly predict the separation process and analyze the influence of each parameter.
- torpedo-rocket separation /
- aerodynamic force /
- radial basis neural network /
- surrogate model

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参考文献(10)

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