The invention provides an underwater hydrodynamic force real-time prediction method and a variable inclination angle micro-groove resistance reduction structure. The method comprises the following steps: S1, constructing a CNN-LSTM algorithm framework for prediction of an underwater flow field; s2, acquiring underwater vehicle flow field simulation data, and constructing a data set; s3, training the CNN-LSTM algorithm framework constructed in the step S1 by using a data set; and S4, assembling the CNN-LSTM algorithm framework which is trained and meets the expectation in an information processing unit of the underwater vehicle for predicting the front flow field of the underwater vehicle, and analyzing to obtain the relative effect of the front flow field on the underwater vehicle. And the prediction result is configured in the variable-dip-angle micro-groove drag reduction structure, and the shape of the incident flow surface is adaptively adjusted to adapt to the current hydrodynamic prediction result.
本发明提出了一种水下水动力实时预测方法及可变倾角微沟槽减阻结构,包括如下步骤:S1:构建水下流场的预测的CNN‑LSTM算法框架;S2:获取水下航行器流场仿真数据,并构建数据集;S3:利用数据集,对步骤S1构建的所述CNN‑LSTM算法框架进行训练;S4:将完成训练并满足预期的CNN‑LSTM算法框架,装配在水下航行器的信息处理单元中,用于预测水下航行器前方流场,并解析得到前方流场对水下航行器产生的相对作用。将预测结果配置在可变倾角微沟槽减阻结构中,适应性的调整迎流面的形状,以适应当前水动力预测结果。
Underwater hydrodynamic force real-time prediction method and variable-dip-angle micro-groove drag reduction structure
一种水下水动力实时预测方法及可变倾角微沟槽减阻结构
2024-04-12
Patent
Electronic Resource
Chinese
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