https://github.com/diffeqml/pde-dataset-generator

A tool for generating PDEs ground truth datasets from ARCSim, FEniCS and SU2
https://github.com/diffeqml/pde-dataset-generator

arcsim dgl fenics generating-datasets graph su2

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A tool for generating PDEs ground truth datasets from ARCSim, FEniCS and SU2

• Host: GitHub
• URL: https://github.com/diffeqml/pde-dataset-generator
• Owner: DiffEqML
• Created: 2021-04-29T05:26:50.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-07-05T07:12:58.000Z (over 3 years ago)
• Last Synced: 2024-04-23T00:11:03.128Z (7 months ago)
• Topics: arcsim, dgl, fenics, generating-datasets, graph, su2
• Language: Jupyter Notebook
• Homepage:
• Size: 50.3 MB
• Stars: 32
• Watchers: 4
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# 📦 PDEs Dataset Generator

A tool for generating datasets for Partial Differential Equations (PDEs) from ARCSim, FEniCS and SU2.

## 💡 Introduction

Research on PDEs needs ground truth datasets. Several tools have been developed and among all, the open-source FEniCS is one of the most famous ones. Our goal is to provide tools for more easily creating such datasets and save them in the DGL graph format. 

Features:

- Compressed scripts containing full generating process, including creating domain, generating mesh, creating boundary constrains, solve function, transfer mesh and result to dgl graph and saving 

- Results are transferred to DGL graph, which is convenient to use in graph models; we also provide numpy tools

- Detailed tutorials with notebooks to show how our scripts work and knowledge about using ARCSim, FEniCS and SU2

- Useful mini tools, including mesh to DGL transferring and modified dgl graph plotting

## 🔧 Environment 

```Python

Python Version: 3.6 or later

Python Packages: jupyterlab, fenics, dgl, numpy, torch, matplotlib

```

## 📁 Structure

```

.

├── fig/

├── notebook/

│   └── *

├── src/

│   ├── utils/

│   └── *

└── README.md

```

- `fig`: example figures

- `notebook`: tutorials in jupyter notebook format

- `src`: all source code will be here, including scripts, tools

  - `utils`: mini tools will be here, including dgl transferring, graph plot

Here are brief guides for the supported PDE simulators:

- [Guide with ARCSim](#📖-guide-with-arcsim):

- [Guide with Fenics](#📖-guide-with-fenics):

- [Guide with SU2](#📖-guide-with-su2):

---

## 📖 Guide with ARCSim

**Step 1**. [Download](https://github.com/cbhua/tool-pdeset-generator/archive/refs/heads/main.zip) or [Clone](https://github.com/cbhua/tool-pdeset-generator.git) this repository

**Step 2**. _ArcSim installation_

You may find the repository with fixes [here](https://github.com/kaist-silab/arcsim) with further instructions.

To install it, run the following:

```sh

git clone https://github.com/kaist-silab/arcsim.git && cd arcsim/

sudo chmod +x install.sh && sudo ./install.sh

```

At this point, you should be ready to go.

**Step 3**. _ArcSim simulation and `.obj` file saving_

Let's consider the flag example. In the ArcSim folder, make a new directory called data. Then run:

```sh

bin/arcsim simulate conf/flag.json data/

```

(you may also run `simulateoffline` if you cannot visualize on your computer

When the simulation ends (we may do that with `Esc` as well) copy the `conf/flag.json` into the folder where we saved the simulation, in our case`data/` and run:

```sh

bin/arcsim generate data/

```

This will generate `.obj` files that we can load into Python with `pywavefront` and the `obj_to_dgl` method we provide.







*Flag simulation with adaptive remeshing*

---

## 📖 Guide with FEniCS

**Step 1**. [Download](https://github.com/cbhua/tool-pdeset-generator/archive/refs/heads/main.zip) or [Clone](https://github.com/cbhua/tool-pdeset-generator.git) this repository.  

**Step 2**. Based on your requirement refer to the notebooks, where there are tutorials and examples. You can find all methods provided in the below list. 

**Step 3**. Modify the parameters to generate your own datasets. 

Provided methods:

- Poisson process

  - Customize domain & Single boundary control

  - Square domain & Separate boundary control

- Gaussian process

  - Customize domain & Single boundary control (support time dynamic control)

  - Square domain & Separate boundary control (support time dynamic control)

  - Squares in square domain & Separate boundary control (support time dynamic control)

  - Circles in circle domain & Single boundary control (support time dynamic control)

Support methods will keep updating. For more detail, you can refer to the [project manager](https://github.com/cbhua/tool-pdeset-generator/projects/1). 







*Gaussian process on rectangular domain*

---

## 📖 Guide with SU2

**Step 1**. [Download](https://github.com/cbhua/tool-pdeset-generator/archive/refs/heads/main.zip) or [Clone](https://github.com/cbhua/tool-pdeset-generator.git) this repository

**Step 2**. Install [SU2](https://su2code.github.io/download.html)

**Step 3**. _Generating data_: take a look at the notebooks and the [SU2 tutorial collection](https://su2code.github.io/tutorials/home/) to get started







*Laminar viscosity of an airfoil*

---

## 📊 Examples Gallery

### T-shirt and interactions with hard bodies







### Paper tearing







### Possion process, square domain, single boundary control







### Possion process, L shape domain, single boundary control







### Possion process, circle shape domain, single boundary control







### Gaussian process, rectangle shape domain, multi & dynamic boundary control







## 📜 References

1. FEniCS project: https://fenicsproject.org/

2. ARCSim project: http://graphics.berkeley.edu/resources/ARCSim/

3. DGL project: https://www.dgl.ai/

4. SU2 project: https://su2code.github.io/