| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - OneScience |
| - fluid dynamics |
| - automotive aerodynamic design |
| - CFD surrogate modeling |
| frameworks: PyTorch |
| --- |
| <p align="center"> |
| <strong> |
| <span style="font-size: 30px;">Transolver-Car-Design</span> |
| </strong> |
| </p> |
| |
| # Model Overview |
|
|
| Transolver-Car-Design is a three-dimensional automotive external-flow prediction model built on Transolver and Transolver++ by Tsinghua University's THUML group. It provides surrogate modeling of vehicle flow fields and rapid prediction of drag coefficients. |
|
|
| Paper: [Transolver: A Fast Transformer Solver for PDEs on General Geometries](https://arxiv.org/pdf/2402.02366) |
|
|
| # Model Description |
| Transolver-Car-Design uses a Transformer architecture with Physics-Attention and is trained on ShapeNet-Car automotive aerodynamic simulation data. It predicts velocity fields, pressure fields, and drag coefficients for complex vehicle geometries. |
|
|
| ## Use Cases |
|
|
| | Use Case | Description | |
| | :--- | :--- | |
| | Automotive aerodynamic design | Rapidly predict external-flow velocities and surface pressures around vehicles | |
| | CFD surrogate modeling | Approximate fluid simulation on complex unstructured meshes with a neural network | |
| | Simulation acceleration | Provide a lightweight evaluation pipeline for large-scale candidate design screening | |
|
|
| # Usage |
|
|
| ## 1. OneCode |
|
|
| Use the online OneCode environment for an intelligent, one-click AI for Science (AI4S) programming experience: |
|
|
| [Launch OneCode for one-click AI4S programming](https://web-2069360198568017922-iaaj.ksai.scnet.cn:58043/home) |
|
|
| ## 2. Manual Setup |
|
|
| **Hardware Requirements** |
|
|
| - A GPU or DCU is recommended. |
| - A CPU can be used for import checks and small-scale pipeline validation, but full training and inference will be slow. |
| - DCU users must install DTK in advance. DTK 25.04.2 or later, or the OneScience-recommended version for the target cluster, is recommended. |
|
|
| ### Download the Model Package |
|
|
| ```bash |
| modelscope download --model OneScience/Transolver-Car-Design --local_dir ./Transolver-Car-Design |
| cd Transolver-Car-Design |
| ``` |
|
|
| ### Set Up the Runtime Environment |
|
|
|
|
| **DCU Environment** |
|
|
| ```bash |
| # Activate DTK and Conda first |
| conda create -n onescience311 python=3.11 -y |
| conda activate onescience311 |
| # Installation with uv is also supported |
| pip install onescience[cfd-dcu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai |
| ``` |
|
|
| **GPU Environment** |
| ```bash |
| # Activate Conda first |
| conda create -n onescience311 python=3.11 -y libstdcxx-ng=12 libgcc-ng=12 gcc_linux-64=12 gxx_linux-64=12 |
| conda activate onescience311 |
| # Installation with uv is also supported |
| pip install onescience[cfd-gpu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai |
| ``` |
|
|
| ### Training Data |
|
|
| The OneScience community provides the `ShapeNetCar` dataset for training. Download it with the command below and verify that the data path in `config/config.yaml` is configured correctly: |
|
|
| ```bash |
| modelscope download --dataset OneScience/ShapeNetCar --local_dir ./data |
| ``` |
|
|
| ### Training |
|
|
| ```bash |
| python scripts/train.py |
| ``` |
|
|
| Training saves `Transolver_plus.pth` under `weight/`: |
|
|
| ```text |
| ./weight/Transolver_plus.pth |
| ``` |
| ### Model Weights |
| This repository will provide model weights pretrained on ShapeNetCar data in the `weights/` directory. The weights will be uploaded soon. |
|
|
| ### Inference |
|
|
| ```bash |
| python scripts/inference.py |
| ``` |
|
|
| ### Evaluation and Visualization |
|
|
| ```bash |
| python scripts/result.py |
| ``` |
|
|
| # Official OneScience Resources |
|
|
| | Platform | OneScience Repository | Skills Repository | |
| | --- | --- | --- | |
| | Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills | |
| | GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills | |
|
|
| # Citations and License |
|
|
| - Original Transolver paper: [Transolver: A Fast Transformer Solver for PDEs on General Geometries](https://arxiv.org/pdf/2402.02366). |
| - Original Transolver++ paper: [Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries](https://arxiv.org/abs/2502.02414) |
| - This repository retains source attribution and has been adapted for automated execution through OneScience and ModelScope. |
|
|
