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项目介绍

mdolab/dafoam 是一个托管在 GitHub 上的开源项目,主要使用 C 编写,采用 Other 许可证,目前获得 367 个 Star、119 次 Fork。

仓库全名
mdolab/dafoam
开源许可证
Other
Star 数
367
Fork 数
119
未关闭 Issue
15

README 摘要

DAFoam: Discrete Adjoint with OpenFOAM ====================================== DAFoam develops an efficient discrete adjoint method to perform high-fidelity multidisciplinary design optimization. DAFoam has the following features: It uses a popular open-source package OpenFOAM for multiphysics analysis. It implements a Jacobian-free discrete adjoint approach with competitive speed, scalability, and accuracy. It has a…

完整内容见 GitHub 原始 README 或本页 。

常见问题

dafoam 用什么语言开发?

主要使用 C 编写,采用 Other 许可证,目前有 367 个 Star。

dafoam 可以免费商用吗?

仓库标注的许可证为 Other,商用前请先阅读仓库 LICENSE 文件确认授权范围。

如何获取 dafoam 的源码?

可以直接克隆仓库:git clone https://github.com/mdolab/dafoam.git,默认分支为 main;安装与运行步骤见仓库 README。

dafoam 最近还在维护吗?

仓库最近一次更新为 11 小时前,当前有 15 个未关闭 Issue;Star 数为 367,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

DAFoam: Discrete Adjoint with OpenFOAM for High-fidelity Multidisciplinary Design Optimization

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
615
价值分
256
活跃状态
活跃

语言占比

C
C++
Cython
Python
Shell

Release

README

DAFoam: Discrete Adjoint with OpenFOAM

tests codecov

DAFoam develops an efficient discrete adjoint method to perform high-fidelity multidisciplinary design optimization. DAFoam has the following features:

  • It uses a popular open-source package OpenFOAM for multiphysics analysis.
  • It implements a Jacobian-free discrete adjoint approach with competitive speed, scalability, and accuracy.
  • It has a convenient Python interface to couple with OpenMDAO for multidisciplinary design optimization.

Documentation

Refer to https://dafoam.github.io for installation, documentation, and tutorials.

Citation

Please cite the following papers in any publication for which you find DAFoam useful.

  • Ping He, Charles A. Mader, Joaquim R.R.A. Martins, Kevin J. Maki. DAFoam: An open-source adjoint framework for multidisciplinary design optimization with OpenFOAM. AIAA Journal, 58:1304-1319, 2020. https://doi.org/10.2514/1.J058853

  • Ping He, Charles A. Mader, Joaquim R.R.A. Martins, Kevin J. Maki. An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM. Computer & Fluids, 168:285-303, 2018. https://doi.org/10.1016/j.compfluid.2018.04.012

License

Copyright 2019 MDO Lab

Distributed using the GNU General Public License (GPL), version 3; see the LICENSE file for details.

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