A craft of Airfoil-CNN

￡神魔★判官ぃ 2022-09-10 10:14 12阅读 0赞

# Airfoil CNN #

This code is personal version network of paper **[Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks][]**.

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAQ29mZmVjaG8_size_20_color_FFFFFF_t_70_g_se_x_16][]

Mapping the airfoil to aerodynamic flow fields use the network in the paper.

## Environment ##

> Conda: 4.10.3  
> Python: 3.9.6  
> PyTorch: 1.9.0  
> torchvision: 0.10.0

## Dataset ##

The dataset is in file folder data.

*  `test.txt`: a txt record the type of aircraft, angle of attack, Reynolds Number as for test dataset
 *  `train.txt`: a txt record the type of aircraft, angle of attack, Reynolds Number as for train dataset
 *  `image`: a image file folder
 *  `input`: the Signed Distance Function(SFD) of airfoil
 *  `output`: the aerodynamic flow fields(p,u,v)
 *  `predict`: the predict image generated by the trained model

## Model ##

`model_train.pt`: save the parameters of model after training.  
Structures such as the checkpoint code.

def checkpoint(model_path, model, lr, optimizer, epoch):
        # model_path = '../model/model_epoch_{}.pt'.format(epoch)
        state = { 'model': model.state_dict(), 'optimizer': optimizer.state_dict(), 'epoch': epoch, 'lr': lr}
        torch.save(state, model_path)
        print('Checkpoint saved at epoch {}'.format(epoch))

## Code ##

All the code in file folder `src`. The function of the code like the name.

## Run ##

cd src
    python train.py --image_path='../data/image/' --train_path='../data/train.txt' --lr=5e-3 --batch_size=64 --epochs=50 --rate=0.5

## TensorBoard ##

tensorboard --logdir=runs

## GitHub ##

You can see my code in there [https://github.com/Zongziyu/Airfoil-CNN/][https_github.com_Zongziyu_Airfoil-CNN]

[Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks]: https://arxiv.org/pdf/1905.13166.pdf
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAQ29mZmVjaG8_size_20_color_FFFFFF_t_70_g_se_x_16]: /images/20220829/93e9840590324180a14f2d2d557dd84a.png
[https_github.com_Zongziyu_Airfoil-CNN]: https://github.com/Zongziyu/Airfoil-CNN/