[WeeklyReport] DUCH714 2024.03.09~2024.03.22 #162
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| ### 姓名 | ||
| Github ID: [DUCH714](https://github.com/DUCH714) | ||
| ### 实习项目 | ||
| 科学计算领域拓展专项（领域流体方向） | ||
| ### 本周工作 | ||
| 1. 阅读[GINO](https://arxiv.org/abs/2309.00583)论文。 | ||
| 2. 熟悉GINO代码文件。 | ||
| 3. 数据输入输出整理归纳。 | ||
| 4. 阅读针对GION代码邻接矩阵过大问题尝试使用的[巨图随机采样技术](https://docs.dgl.ai/guide/minibatch.html) | ||
| 5. 阅读[TSONN](https://arxiv.org/abs/2310.16491)论文。 | ||
| ### 下周工作 | ||
| #### 汽车外流场仿真： | ||
| 1. 整理熟悉 GINO 的输入数据和dataloader部分 | ||
| 2. 尝试搭建环境，选10组数据，跑通训练流程 | ||
| 3. 跑通大图采样demo（导师提供，管导师要） | ||
| #### 高雷诺数湍流图探索： | ||
| 1. 尝试根据Allen Cahn方程案例，搭建LDC 2D瞬态的TSONN训练代码 | ||
| 2. 跑通LDC 2D瞬态有限差分代码（导师提供，管导师要） | ||
| ### 导师评语 | ||
| 做的很好，继续加油 |
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| ### 姓名 | ||
| Github ID: [DUCH714](https://github.com/DUCH714) | ||
| ### 实习项目 | ||
| 科学计算领域拓展专项（领域流体方向） | ||
| ### 本周工作 | ||
| #### 汽车外流场仿真： | ||
| 1. 整理熟悉 GINO 的输入数据和dataloader部分 | ||
| #### 文献调研 | ||
| 1. 阅读CausalPINN | ||
| 2. 将CausalPINN代码转为Paddle | ||
| ### 下周工作 | ||
| #### 收尾Causal PINN复现工作 | ||
| 对引起误差部分进行进一步分析 | ||
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| 继续阅读Causal PINN论文，补充文档 | ||
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| 此工作意义在于，帮助Paddle框架自动微分部分开发 | ||
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| #### 继续回到汽车风阻预测项目 | ||
| 数据集：使用Pyby下载导师提供的几何文件，参考https://blog.csdn.net/PolarisRisingWar/article/details/121887801 | ||
| 代码：尝试运行代码，并在ShapeNet Car数据集上进行实验 | ||
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| ### 导师评语 | ||
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There was a problem hiding this comment. 目前转Causal PINN 复现，并已经提交PR，完成较好，继续加油 |
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| 目前转Causal PINN 复现，并已经提交PR，完成较好，继续加油 | ||
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1. 收尾Causal PINN复现工作
2. 继续回到汽车风阻预测项目