OpenConcept
A toolkit for conceptual MDAO of aircraft with unconventional propulsion architectures.
https://github.com/mdolab/openconcept
Category: Consumption
Sub Category: Mobility and Transportation
Keywords from Contributors
aerodynamics mach design-optimization openmdao adjoint-sensitivities flow-simulation geometry-parameterization mesh-deformation
Last synced: about 10 hours ago
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Repository metadata
OpenConcept: A toolkit for conceptual MDAO of aircraft with unconventional propulsion architectures
- Host: GitHub
- URL: https://github.com/mdolab/openconcept
- Owner: mdolab
- License: mit
- Created: 2018-06-28T17:01:48.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2025-04-08T15:41:34.000Z (19 days ago)
- Last Synced: 2025-04-17T22:58:53.813Z (10 days ago)
- Language: Python
- Size: 2.38 MB
- Stars: 40
- Watchers: 7
- Forks: 34
- Open Issues: 5
- Releases: 12
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS
readme.md
OpenConcept - A conceptual design toolkit with efficient gradients implemented in the OpenMDAO framework
Authors: Benjamin J. Brelje and Eytan J. Adler
OpenConcept is a new toolkit for the conceptual design of aircraft. OpenConcept was developed in order to model and optimize aircraft with electric propulsion at low computational cost. The tools are built on top of NASA Glenn's OpenMDAO framework, which in turn is written in Python.
OpenConcept is capable of modeling a wide range of propulsion systems, including detailed thermal management systems.
The following figure (from this paper) shows one such system that is modeled in the N3_HybridSingleAisle_Refrig.py example.
The following charts show more than 250 individually optimized hybrid-electric light twin aircraft (similar to a King Air C90GT). Optimizing hundreds of configurations can be done in a couple of hours on a standard laptop computer.
The reason for OpenConcept's efficiency is the analytic derivatives built into each analysis routine and component. Accurate, efficient derivatives enable the use of Newton nonlinear equation solutions and gradient-based optimization at low computational cost.
Documentation
Automatically-generated documentation is available at (https://mdolab-openconcept.readthedocs-hosted.com/en/latest/).
To build the docs locally, install the sphinx_mdolab_theme via pip. Then enter the doc folder in the root directory and run make html. The built documentation can be viewed by opening _build/html/index.html. OpenAeroStruct is required (also installable via pip) to build the OpenAeroStruct portion of the source docs.
Getting Started
OpenConcept can be pip installed directly from PyPI
pip install openconcept
To run the examples or edit the source code:
- Clone the repo to disk (
git clone https://github.com/mdolab/openconcept) - Navigate to the root
openconceptfolder - Run
pip install -e .to install the package (the-ecan be omitted if not editing the source)
Get started by following the tutorials in the documentation to learn the most important parts of OpenConcept.
The features section of the documentation describes most of the components and system models available in OpenConcept.
Requirements
OpenConcept is tested regularly on builds with the oldest and latest supported package versions. The package versions in the oldest and latest builds are the following:
| Package | Oldest | Latest |
|---|---|---|
| Python | 3.8 | 3.11 |
| OpenMDAO | 3.21 | latest |
| NumPy | 1.20 | 1.26 |
| SciPy | 1.7.0 | latest |
| OpenAeroStruct | 2.7.1 | 2.7.1 |
Citation
Please cite this software by reference to the conference paper:
Benjamin J. Brelje and Joaquim R. R. A. Martins, "Development of a Conceptual Design Model for Aircraft Electric Propulsion with Efficient Gradients", 2018 AIAA/IEEE Electric Aircraft Technologies Symposium, AIAA Propulsion and Energy Forum, (AIAA 2018-4979) DOI: 10.2514/6.2018-4979
@inproceedings{Brelje2018a,
address = {{C}incinnati,~{OH}},
author = {Benjamin J. Brelje and Joaquim R. R. A. Martins},
booktitle = {Proceedings of the AIAA/IEEE Electric Aircraft Technologies Symposium},
doi = {10.2514/6.2018-4979},
month = {July},
title = {Development of a Conceptual Design Model for Aircraft Electric Propulsion with Efficient Gradients},
year = {2018}
}
If using the integrated OpenAeroStruct VLM or aerostructural aerodynamic models, please cite the following conference paper:
Eytan J. Adler and Joaquim R. R. A. Martins, "Efficient Aerostructural Wing Optimization Considering Mission Analysis", Journal of Aircraft, 2022. DOI: 10.2514/1.c037096
@article{Adler2022d,
author = {Adler, Eytan J. and Martins, Joaquim R. R. A.},
doi = {10.2514/1.c037096},
issn = {1533-3868},
journal = {Journal of Aircraft},
month = {December},
publisher = {American Institute of Aeronautics and Astronautics},
title = {Efficient Aerostructural Wing Optimization Considering Mission Analysis},
year = {2022}
}
Owner metadata
- Name: MDO Lab
- Login: mdolab
- Email:
- Kind: organization
- Description: Multidisciplinary Design Optimization Laboratory at the University of Michigan
- Website: mdolab.engin.umich.edu
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/26934866?v=4
- Repositories: 21
- Last ynced at: 2023-02-27T07:30:48.317Z
- Profile URL: https://github.com/mdolab
GitHub Events
Total
- Issues event: 2
- Watch event: 4
- Issue comment event: 4
- Member event: 3
- Push event: 4
- Pull request event: 2
- Pull request review event: 1
- Fork event: 3
- Create event: 1
Last Year
- Issues event: 2
- Watch event: 4
- Issue comment event: 4
- Member event: 3
- Push event: 4
- Pull request event: 2
- Pull request review event: 1
- Fork event: 3
- Create event: 1
Committers metadata
Last synced: 7 days ago
Total Commits: 165
Total Committers: 6
Avg Commits per committer: 27.5
Development Distribution Score (DDS): 0.23
Commits in past year: 4
Committers in past year: 2
Avg Commits per committer in past year: 2.0
Development Distribution Score (DDS) in past year: 0.5
| Name | Commits | |
|---|---|---|
| Ben Brelje | b****e@u****u | 127 |
| Eytan Adler | 6****r | 28 |
| Shugo Kaneko | 4****h | 5 |
| mariejvaucher | 1****r | 2 |
| Bernardo Pacini | 6****i | 2 |
| Neil Wu | n****6@g****m | 1 |
Committer domains:
- umich.edu: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 16
Total pull requests: 61
Average time to close issues: 7 months
Average time to close pull requests: 3 days
Total issue authors: 6
Total pull request authors: 6
Average comments per issue: 0.69
Average comments per pull request: 1.67
Merged pull request: 55
Bot issues: 0
Bot pull requests: 0
Past year issues: 4
Past year pull requests: 7
Past year average time to close issues: N/A
Past year average time to close pull requests: 9 days
Past year issue authors: 1
Past year pull request authors: 3
Past year average comments per issue: 0.0
Past year average comments per pull request: 2.14
Past year merged pull request: 4
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- eytanadler (5)
- kanekosh (4)
- bbrelje (3)
- nwu63 (2)
- 12libao (1)
- onodip (1)
Top Pull Request Authors
- eytanadler (33)
- bbrelje (15)
- kanekosh (6)
- bernardopacini (4)
- mariejvaucher (2)
- A-CGray (1)
Top Issue Labels
- enhancement (3)
- bug (2)
- documentation (1)
- question (1)
Top Pull Request Labels
- bug (1)
- maintenance (1)
- documentation (1)
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 261 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 8
- Total maintainers: 1
pypi.org: openconcept
Open aircraft conceptual design tools
- Homepage: https://github.com/mdolab/openconcept
- Documentation: https://openconcept.readthedocs.io/
- Licenses: MIT License
- Latest release: 1.2.0 (published about 1 year ago)
- Last Synced: 2025-04-26T14:01:31.226Z (1 day ago)
- Versions: 8
- Dependent Packages: 0
- Dependent Repositories: 0
- Downloads: 261 Last month
-
Rankings:
- Dependent packages count: 6.633%
- Forks count: 7.407%
- Stargazers count: 12.133%
- Average: 15.997%
- Downloads: 23.202%
- Dependent repos count: 30.611%
- Maintainers (1)
Dependencies
- numpy >=1.14.0
- openmdao >=3.10.0
- scipy >=1.0.0
- six *
- actions/checkout v2 composite
- codecov/codecov-action v2 composite
- conda-incubator/setup-miniconda v2 composite
- matplotlib *
- openmdao *
- sphinx-mdolab-theme *
Score: 11.16676646275947