openconcept
OpenConcept: A toolkit for conceptual MDAO of aircraft with unconventional propulsion architectures
Science Score: 67.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 6 DOI reference(s) in README -
✓Academic publication links
Links to: researchgate.net -
✓Committers with academic emails
3 of 9 committers (33.3%) from academic institutions -
✓Institutional organization owner
Organization mdolab has institutional domain (mdolab.engin.umich.edu) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (18.6%) to scientific vocabulary
Keywords from Contributors
Repository
OpenConcept: A toolkit for conceptual MDAO of aircraft with unconventional propulsion architectures
Basic Info
- Host: GitHub
- Owner: mdolab
- License: mit
- Language: Python
- Default Branch: main
- Size: 2.38 MB
Statistics
- Stars: 47
- Watchers: 7
- Forks: 38
- Open Issues: 7
- Releases: 14
Metadata Files
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
shell
pip install openconcept
To run the examples or edit the source code:
1. Clone the repo to disk (git clone https://github.com/mdolab/openconcept)
2. Navigate to the root openconcept folder
3. Run pip install -e . to install the package (the -e can 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
- Name: MDO Lab
- Login: mdolab
- Kind: organization
- Website: mdolab.engin.umich.edu
- Repositories: 21
- Profile: https://github.com/mdolab
Multidisciplinary Design Optimization Laboratory at the University of Michigan
GitHub Events
Total
- Create event: 4
- Release event: 2
- Issues event: 2
- Watch event: 7
- Issue comment event: 12
- Member event: 3
- Push event: 9
- Pull request event: 3
- Pull request review event: 4
- Fork event: 6
Last Year
- Create event: 5
- Release event: 2
- Issues event: 2
- Watch event: 7
- Issue comment event: 12
- Member event: 3
- Push event: 9
- Pull request event: 3
- Pull request review event: 4
- Fork event: 6
Committers
Last synced: 6 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Ben Brelje | b****e@u****u | 119 |
| Eytan Adler | 6****r@u****m | 24 |
| Ben Brelje | b****e@g****m | 8 |
| Shugo Kaneko | 4****h@u****m | 7 |
| eytanadler | e****a@u****u | 4 |
| Bernardo Pacini | 6****i@u****m | 2 |
| mariejvaucher | 1****r@u****m | 2 |
| Hannah Hajdik | h****k@u****u | 1 |
| Neil Wu | n****6@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 15
- Total pull requests: 62
- Average time to close issues: 7 months
- Average time to close pull requests: 3 days
- Total issue authors: 7
- Total pull request authors: 8
- Average comments per issue: 1.13
- Average comments per pull request: 1.65
- Merged pull requests: 57
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 3
- Pull requests: 5
- Average time to close issues: N/A
- Average time to close pull requests: 14 days
- Issue authors: 2
- Pull request authors: 4
- Average comments per issue: 2.0
- Average comments per pull request: 1.6
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- eytanadler (5)
- bbrelje (3)
- kanekosh (2)
- nwu63 (2)
- davidszt2 (1)
- 12libao (1)
- onodip (1)
Pull Request Authors
- eytanadler (35)
- bbrelje (15)
- kanekosh (8)
- bernardopacini (4)
- mariejvaucher (4)
- hajdik (2)
- A-CGray (1)
- davidszt2 (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
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Total downloads:
- pypi 561 last-month
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Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 0
(may contain duplicates) - Total versions: 24
- Total maintainers: 1
proxy.golang.org: github.com/mdolab/openconcept
- Documentation: https://pkg.go.dev/github.com/mdolab/openconcept#section-documentation
- License: mit
-
Latest release: v1.2.2
published 8 months ago
Rankings
pypi.org: openconcept
Open aircraft conceptual design tools
- Homepage: https://github.com/mdolab/openconcept
- Documentation: https://openconcept.readthedocs.io/
- License: MIT License
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Latest release: 1.2.2
published 8 months ago
Rankings
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 *