update darcy filename

Author: HydrogenSulfate

README.md

@@ -1,85 +1,77 @@
-*Current version of PaddleScience is v1.0 Beta.*
+# PaddleScience
 
-# Introduction
+> *Developed with [PaddlePaddle](https://www.paddlepaddle.org.cn/)*
 
-PaddleScience extends the PaddlePaddle framework with reusable
-software components for developing novel scientific computing applications. Such new
-applications include Physics-informed Machine Learning, neural network based PDE solvers,
-machine learning for CFD, and so on. PaddleScience is currently under active development.
-Its design is evolving and its APIs are subject to change.
+[![Doc](https://img.shields.io/readthedocs/paddlescience-docs/latest)](https://paddlescience-docs.readthedocs.io/zh/latest/)
+[![License](https://img.shields.io/github/license/PaddlePaddle/PaddleScience)](./LICENSE)
 
-# Core features and organization
+[**PaddleScience使用文档**](https://paddlescience-docs.readthedocs.io/zh/latest/)
 
-PaddleScience currently focuses on the PINNs model. The core components are as follows.
+## 简介
 
-- PDE, delineating partial differential equations in symbolic forms. Specific PDEs derive the
-    the base PDE class.
+PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计算套件，利用深度神经网络的学习能力和 PaddlePaddle 框架的自动(高阶)微分机制，解决物理、化学、气象等领域的问题。支持物理机理驱动、数据驱动、数理融合三种求解方式，并提供了基础 API 和详尽文档供用户使用与二次开发。
 
-- Geometry, a declarative interface for defining the geometric domain. Automatic
-    discretization is supported
+<div align="center">
+    <img src="./docs/images/overview/panorama.png" width="80%" height="80%">
+</div>
 
-- Neural net, currently supporting fully connected layers with customizable size and depth.
+## 特性
 
-- Loss, defining what exact penalties are enforced during the training process. By default,
-    the L2 loss is applied. In the current design, the total loss is a weighted sum of
-    four parts, the equation loss, the boundary condition loss, the initial condition loss and the data loss.
+- 支持简单几何和复杂 STL 几何的采样与布尔运算。
+- 支持包括 Dirichlet、Neumann、Robin 以及自定义边界条件。
+- 支持物理机理驱动、数据驱动、数理融合三种问题求解方式。涵盖流体、结构、气象等领域 8+ 案例。
+- 支持结果可视化输出与日志结构化保存。
+- 完善的 type hints，用户使用和代码贡献全流程文档，经典案例 AI studio 快速体验，降低使用门槛，提高开发效率。
+- 更多特性正在开发中...
 
-- Optimizer, specifying which optimizer to use for training. Adam is the default option. More
-    optimizers, such as BFGS, will be available in the future.
+## 安装使用
 
-- Solver, managing the training process given the training data in a batchly fashion.
+1. 执行以下命令，从 github 上克隆 PaddleScience 项目，进入 PaddleScience 目录，并将该目录添加到系统环境变量中
 
-- Visualization, an easy access to the graph drawing utilities.
+    ``` shell
+    git clone https://github.com/PaddlePaddle/PaddleScience.git
+    cd PaddleScience
+    export PYTHONPATH=$PWD:$PYTHONPATH
+    ```
 
-# Getting started
+2. 安装必要的依赖包
 
-## Prerequisites
+    ``` shell
+    pip install -r requirements.txt
+    ```
 
-Hardware requirements: NVIDIA GPU V100, NVIDIA GPU A100
+3. 验证安装
 
-Package dependencies: paddle, cuda (11.0 or higher), numpy, scipy, sympy, matplotlib, vtk, pyevtk, wget.
+    ``` py
+    python -c "import ppsci; ppsci.utils.run_check()"
+    ```
 
-PaddleScience currently relies on new features of the Paddle framework so please be advised to download the latest version of Paddle on GitHub or on Gitee.
+4. 开始使用
 
-For more details on installation, please refer to the offical [PaddlePaddle repository on GitHub](https://github.com/PaddlePaddle/Paddle) or [PaddlePaddle repository on Gitee](https://gitee.com/paddlepaddle/Paddle).
+    ``` py
+    import ppsci
 
-## Download and environment setup
+    # write your code here...
+    ```
 
-``` shell
-Download from GitHub: git clone https://github.com/PaddlePaddle/PaddleScience.git
-Download from Gitee:  git clone https://gitee.com/PaddlePaddle/PaddleScience.git
+更多安装方式请参考 [**安装与使用**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/install_setup/)
 
-cd PaddleScience
-export PYTHONPATH=$PWD:$PYTHONPATH
+## 快速开始
 
-pip install -r requirements.txt
-```
+参考 [**快速开始**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/quickstart/)
 
-## Run examples
+## 经典案例
 
-Some examples are baked in for quick demonstration. Please find them in the `examples` directory. To run an example, just enter the subdirectory and run the demo code in Python commandline.
+请参考 [**经典案例**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/examples/viv/)
 
-``` shell
-# Darcy flow (Poisson equation)
-cd examples/darcy
-python darcy2d.py
+## 支持
 
-# LDC steady (Steady Navier-Stokes eqution)
-cd examples/ldc
-python ldc2d_steady_train.py
+如使用过程中遇到问题或想提出开发建议，欢迎在 [**Issue**](https://github.com/PaddlePaddle/PaddleScience/issues/new) 页面新建 issue。
 
-# Lid Driven Cavity unsteady with continue-time method (Unsteady Navier-Stokes equation)
-cd examples/ldc
-python ldc2d_unsteady_t.py
+## 贡献代码
 
-# Flow around a circular cylinder with discrete-time method (Unsteady Navier-Stokes equation)
-cd examples/cylinder/3d_unsteady_discrete/baseline
-python cylinder3d_unsteady.py
+PaddleScience 项目欢迎并依赖开发人员和开源社区中的用户，请参阅 [**贡献指南**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/contribute/)。
 
-```
+## 证书
 
-## Short tutorials on how to construct and solve a PINN model
-
-[A tutorial on Lid Driven Cavity flow](./examples/ldc/README.md)
-
-[A tutorial on Darcy flow in porous medium](./examples/darcy/README.md)
+[Apache License 2.0](https://github.com/PaddlePaddle/PaddleScience/blob/develop/LICENSE)

docs/images/cylinder2d_unsteady/cylinder_2d_unsteady_Re100.gif

@@ -4,6 +4,8 @@
 
 PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计算套件，利用深度神经网络的学习能力和 PaddlePaddle 框架的自动(高阶)微分机制，解决物理、化学、气象等领域的问题。支持物理机理驱动、数据驱动、数理融合三种求解方式，并提供了基础 API 和详尽文档供用户使用与二次开发。
 
+![panorama](./images/overview/panorama.png)
+
 ## 特性
 
 - 支持简单几何和复杂 STL 几何的采样与布尔运算。
@@ -15,11 +17,11 @@ PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计
 
 ## 支持
 
-- 如使用过程中遇到问题或想提出开发建议，欢迎在 [Issue](https://github.com/PaddlePaddle/PaddleScience/issues/new) 页面新建 issue。
+- 如使用过程中遇到问题或想提出开发建议，欢迎在 [**Issue**](https://github.com/PaddlePaddle/PaddleScience/issues/new) 页面新建 issue。
 
 ## 贡献代码
 
-PaddleScience 项目欢迎并依赖开发人员和开源社区中的用户，请参阅 [贡献指南](https://paddlescience-docs.readthedocs.io/zh/latest/zh/contribute/)。
+PaddleScience 项目欢迎并依赖开发人员和开源社区中的用户，请参阅 [**贡献指南**](https://paddlescience-docs.readthedocs.io/zh/latest/zh/contribute/)。
 
 ## 证书
 

docs/index.md

@@ -1,5 +1,7 @@
 # 2D-Cylinder(2D Flow Around a Cylinder)
 
+<a href="https://aistudio.baidu.com/aistudio/projectdetail/6160381?contributionType=1&sUid=438690&shared=1&ts=1683961158552" class="md-button md-button--primary" style>AI Studio快速体验</a>
+
 ## 1. 问题简介
 
 2D Flow Around a Cylinder，中文名称可译作“2维圆柱绕流”，是指二维圆柱低速定常绕流的流型只与 $Re$ 数有关。在 $Re \le 1$ 时，流场中的惯性力与粘性力相比居次要地位，圆柱上下游的流线前后对称，阻力系数近似与 $Re$ 成反比(阻力系数为 10~60)，此 $Re$ 数范围的绕流称为斯托克斯区；随着 $Re$ 的增大，圆柱上下游的流线逐渐失去对称性。
@@ -130,19 +132,19 @@ examples/cylinder/2d_unsteady/cylinder2d_unsteady_Re100.py:36:37
 
 ``` py linenums="39"
 # set timestamps
-time_start, time_end = 1, 50
-num_timestamps = 50
-train_num_timestamps = 30
+TIME_START, TIME_END = 1, 50
+NUM_TIMESTAMPS = 50
+TRAIN_NUM_TIMESTAMPS = 30
 
 train_timestamps = np.linspace(
-    time_start, time_end, num_timestamps, endpoint=True
+    TIME_START, TIME_END, NUM_TIMESTAMPS, endpoint=True
 ).astype("float32")
-train_timestamps = np.random.choice(train_timestamps, train_num_timestamps)
+train_timestamps = np.random.choice(train_timestamps, TRAIN_NUM_TIMESTAMPS)
 train_timestamps.sort()
-t0 = np.array([time_start], dtype="float32")
+t0 = np.array([TIME_START], dtype="float32")
 
 val_timestamps = np.linspace(
-    time_start, time_end, num_timestamps, endpoint=True
+    TIME_START, TIME_END, NUM_TIMESTAMPS, endpoint=True
 ).astype("float32")
 
 logger.info(f"train_timestamps: {train_timestamps.tolist()}")
@@ -152,8 +154,8 @@ logger.info(f"val_timestamps: {val_timestamps.tolist()}")
 geom = {
     "time_rect": ppsci.geometry.TimeXGeometry(
         ppsci.geometry.TimeDomain(
-            time_start,
-            time_end,
+            TIME_START,
+            TIME_END,
             timestamps=np.concatenate((t0, train_timestamps), axis=0),
         ),
         ppsci.geometry.PointCloud(
@@ -393,7 +395,7 @@ examples/cylinder/2d_unsteady/cylinder2d_unsteady_Re100.py
     本案例只作为demo展示，尚未进行充分调优，下方部分展示结果可能与 OpenFOAM 存在一定差别。
 
 <figure markdown>
-  ![u_pred.gif](https://kefu.cckefu1.com/app/upload/temp/202304_p/06/06_168079163055700009257b95d.gif){ loading=lazy }
+  ![u_pred.gif](../../images/cylinder2d_unsteady/cylinder_2d_unsteady_Re100.gif){ loading=lazy }
   <figcaption>模型预测结果 u</figcaption>
 </figure>
 </figure>