ENGLISH | 简体中文
MindFlow
Introduction
Flow simulation aims to solve the fluid governing equation under a given boundary condition by numerical methods, so as to realize the flow analysis, prediction and control. It is widely used in engineering design in aerospace, ship manufacturing, energy and power industries. The numerical methods of traditional flow simulation, such as finite volume method and finite difference method, are mainly implemented by commercial software, requiring physical modeling, mesh generation, numerical dispersion, iterative solution and other steps. The simulation process is complex and the calculation cycle is long. AI has powerful learning fitting and natural parallel inference capabilities, which can improve the efficiency of the flow simulation.
MindSpore Flow is a flow simulation suite developed based on MindSpore. It supports AI flow simulation in industries such as aerospace, ship manufacturing, and energy and power. It aims to provide efficient and easy-to-use AI computing flow simulation software for industrial research engineers, university professors, and students.
Latest News
- 🔥
2024.03.22
MindSpore Artificial Intelligence Framework Summit 2024 was held in Beijing National Convention Center. Professor Dong Bin, affiliated with both the Beijing International Center for Mathematical Research and the Center for Machine Learning Research at Peking University, revealed that the team has developed a groundbreaking model in the realm of AI-driven PDEs, named PDEformer-1. Leveraging the MindSpore and MindFlow suites, this model is uniquely capable of directly ingesting any PDE format as input. Through extensive training on a comprehensive dataset encompassing 3 million 1D PDE samples, it has demonstrated impressive speed and precision in resolving a broad spectrum of 1D PDE forward problems.
- 🔥
2024.03.22
MindSpore Artificial Intelligence Framework Summit 2024 was held in Beijing National Convention Center. Tang Zhigong, academician of Chinese Academy of Sciences and chairman of the Chinese Aerodynamic Society, introduced that the team created the generative aerodynamic design model platform based on MindSpore and MindFlow. Platform is oriented to a variety of application scenarios and breaks the traditional design paradigm. It shortens the design periods from the month level to the minute level, and meet the conceptual design requirements. News.
- 🔥
2024.03.20
MindFlow 0.2.0 is released, Page.
- 🔥
2023.11.07
The China (Xi'an) Artificial Intelligence Summit Forum was held at the High-tech International Conference Center in Yanta District, Xi'an, and the first large-scale fluid dynamics model for aircraft, "Qinling·AoXiang", jointly developed by Northwestern Polytechnical University and Huawei, was officially released. The model is an intelligent model for aircraft fluid simulation jointly developed by the International Joint Institute of Fluid Mechanics and Intelligence of Northwestern Polytechnical University and Huawei AI4Sci Lab on the basis of the domestic open-source fluid computing software Fenglei, relying on the surging computing power of Ascend AI and the MindSpore AI framework, page.
- 🔥
2023.08.02
MindFlow 0.1.0 is released, Page.
- 🔥
2023.07.06
The 2023 World Artificial Intelligence Conference with the theme of "Connect the World Intelligently. Generate the Future" was successfully held at the Shanghai World Expo Center. The 3D Supercritical airfoil fluid simulation AI model "Dongfang Yifeng" from Comac Shanghai Aircraft Design and Research Institute won the SAIL Award, the highest award of the World Artificial Intelligence Conference. This model is a large intelligent AI model for wing complex flow simulation scenarios jointly developed by Comac Co., Ltd. Shanghai Aircraft Design and Research Institute and Huawei based on the domestic Shengteng AI basic software and hardware platform and MindSpore AI framework, Page.
- 🔥
2023.05.21
The second plenary meeting of the intelligent fluid mechanics industrial consortium was successfully held in Hangzhou West Lake University, and Shengsi MindSpore co organized the meeting. Three academicians of the CAS Member, representatives of the industrial consortium and experts from the academic and industrial circless who care about the consortium attended the meeting. The first fluid mechanics model for aircraft - "Qinling · AoXiang" model is pre released. This model is an intelligent model for aircraft fluid simulation jointly developed by the International Joint Institute of fluid mechanics Intelligence of Northwestern Polytechnical University and Huawei based on the domestic Shengteng AI basic software and hardware platform and MindSpore AI framework.Page.
- 🔥
2023.02.05
MindFlow 0.1.0-alpha is released.
- 🔥
2023.01.17
MindFlow-CFD, an End-to-End Differentiable Solver based on MindSpore, see more.
- 🔥
2022.09.02
Academician Guanghui Wu, Chief Scientist of COMAC, released the first industrial flow simulation model "DongFang.YuFeng" at WAIC2022 World Artificial Intelligence Conference. AI flow simulation assisted the aerodynamic simulation of domestic large aircraft. Page.
Publications
Ye Z, Huang X, Liu H, et al. Meta-Auto-Decoder: A Meta-Learning Based Reduced Order Model for Solving Parametric Partial Differential Equations[J]. Communications on Applied Mathematics and Computation. [Paper]
Deng Z, Wang J, Liu H, et al. Prediction of transactional flow over supercritical airfoils using geometric-encoding and deep-learning strategies. Physics of Fluids 35, 075146 (2023). [Paper]
[Code]
Rao C, Ren P, Wang Q, et al. Encoding physics to learn reaction–diffusion processes[J]. Nature Machine Intelligence, 2023: 1-15. [Paper]
[Code]
Li Z, Wang Y, Liu H, et al. Solving Boltzmann equation with neural sparse representation[J]. SIAM Journal on Scientific Computing, Vol. 46, Iss. 2 (2024).
[Paper]
[Code]
Deng Z, Liu H, Shi B, et al. Temporal predictions of periodic flows using a mesh transformation and deep learning-based strategy[J]. Aerospace Science and Technology, 2023, 134: 108081. [Paper]
Huang X, Liu H, Shi B, et al. A Universal PINNs Method for Solving Partial Differential Equations with a Point Source[C]//IJCAI. 2022: 3839-3846. [Paper] [Code]
Features
Applications
Data Driven
Data-Mechanism Fusion
Physics Driven
CFD
Installation
Version Dependency
Because MindFlow is dependent on MindSpore, please click MindSpore Download Page according to the corresponding relationship indicated in the following table. Download and install the corresponding whl package.
MindFlow |
Branch |
MindSpore |
Python |
master |
master |
\ |
>=3.7 |
0.2.0 |
r0.6 |
>=2.2.12 |
>=3.7 |
0.1.0 |
r0.3 |
>=2.0.0 |
>=3.7 |
0.1.0rc1 |
r0.2.0 |
>=2.0.0rc1 |
>=3.7 |
Install Dependency
pip install -r requirements.txt
Hardware
Hardware |
OS |
Status |
Ascend |
Linux |
✔️ |
GPU |
Linux |
✔️ |
pip install
# gpu and ascend are supported
export DEVICE_NAME=gpu
pip install mindflow_${DEVICE_NAME}
source code install
- Download source code from Gitee.
git clone https://gitee.com/mindspore/mindscience.git
cd {PATH}/mindscience/MindFlow
- Compile in Ascend backend.
bash build.sh -e ascend -j8
export CUDA_PATH={your_cuda_path}
bash build.sh -e gpu -j8
- Install the compiled .whl file.
cd {PATH}/mindscience/MindFLow/output
pip install mindflow_*.whl
Join MindFlow SIG
Northwestern Polytechnical University ZhangWeiwei
|
Peking University DongBin
|
RenMin University of China SunHao
|
Zhengzhou University of Aeronautics MaHao
|
Join MindSpore MindFlow SIG to help AI fluid simulation development.
MindSpore AI for Science, Learning and Learning to solve PDEs topic report by Dong Bin, Peking University.
We will continue to release open source internship tasks, build MindFlow ecology with you, and promote the development of computational fluid dynamics with experts, professors and students in the field. Welcome to actively claim the task.
Core Contributor
Thanks goes to these wonderful people 🧑🤝🧑:
yufan, wangzidong, liuhongsheng, zhouhongye, zhangyi, dengzhiwen, liulei, guoboqiang, chengzeruizhi, libokai, yangge, longzichao, qiuyisheng, haojiwei, leiyixiang, huangxiang, huxin,xingzhongfan, mengqinghe, lizhengyi, lixin, liuziyang, dujiaoxi, xiaoruoye, liangjiaming
Commercial Aircraft Corporation of China Ltd
|
TaiHu Laboratory
|
Northwestern Polytechnical University
|
Peking University
|
Renmin University of China
|
Harbin Institute of Technology
|
Contribution Guide
License
Apache License 2.0