https://github.com/ctftamu/sl-gps
Repository to create neural network architecture for dynamic chemistry reduction based on Global Pathway Selection
Science Score: 39.0%
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○Scientific vocabulary similarity
Low similarity (13.5%) to scientific vocabulary
Keywords
Repository
Repository to create neural network architecture for dynamic chemistry reduction based on Global Pathway Selection
Basic Info
Statistics
- Stars: 7
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 2
Topics
Metadata Files
README.md
Simple steps to get started
- Install basic libraries
pip install matplotlib tensorflow - Install cantera libraries
pip install --no-cache-dir "cantera==2.6.0" - Install numpy
pip install "numpy==1.26.4" - Install networkx (for parallel compute)
pip install networkx - Install scikit
pip install scikit-learn - Install the SL-GPS library
pip install "git+https://github.com/ctftamu/SL-GPS.git" - Test your installation by running any of the files in the tests folder
- The trained neural network is stored as .h5 file which can be accessed and utilized to produce reduced mechanisms for any given composition, temperature and pressure.
- Next, convert the generated .h5 file to .pb (frozen graph) to be used in OpenFOAM using the script converth5ToPb.ipynb in tests folder.
NOTE: The default neural network architecture is 16x8 (2 hidden layers). To change the neural network architecture, go to the file and edit the function spec_train according to your needs.
For questions and discussions please join : https://discord.com/channels/1333609076726431798/1333610748424880128
Please feel free to ask any questions related to SL-GPS there.
SL-GPS
This repository contains the means to create a neural network architecture for dynamic chemistry reduction based on reduction results from Global Pathway Selection. The basic procedure is to first run adaptive GPS for 0D auto-ignition simulation so as to create a dataset. This dataset is later used for training the Artificial Neural Network (ANN). You can reach out to us at rmishra@tamu.edu (Rohit Mishra) or aaronnelson@tamu.edu (Aaron Nelson) for code issues, suggestions and/or pull requests.
About
This code was developed entirely in Python 3. Dependent packages include Cantera 2, Tensorflow 2, pandas, sklearn, numpy, pickle, and networkx. Code for GPS has been copied from https://github.com/golsun/GPS and modified to work in Python 3.
How to Cite
- Mishra, R., Nelson, A., Jarrahbashi, D., "Adaptive global pathway selection using artificial neural networks: A-priori study", Combustion and Flame, 244 (2022) 112279 [link] ## Related Publications
- X. Gao, S. Yang, W. Sun, "A global pathway selection algorithm for the reduction of detailed chemical kinetic mechanisms", Combustion and Flame, 167 (2016) 238-247 [link]
Owner
- Name: Computational Thermo-Fluids Lab
- Login: ctftamu
- Kind: user
- Location: College Station, TX
- Company: Texas A&M University
- Website: https://cfd.engr.tamu.edu/
- Repositories: 2
- Profile: https://github.com/ctftamu
This page includes all the codes supporting the research conducted at the CTF Lab at the Texas A&M University under the guidance of Prof. Dorrin Jarrahbashi.
GitHub Events
Total
- Release event: 1
- Watch event: 1
- Push event: 28
- Pull request event: 4
- Create event: 2
Last Year
- Release event: 1
- Watch event: 1
- Push event: 28
- Pull request event: 4
- Create event: 2
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| AaronANelson | 8****n | 8 |
| Rohit Mishra | r****r@g****m | 4 |
| Computational Thermo-Fluids Lab | 1****u | 3 |
| Aaron Alexander Nelson | a****n@t****r | 2 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 0
- Total pull requests: 5
- Average time to close issues: N/A
- Average time to close pull requests: 1 minute
- Total issue authors: 0
- Total pull request authors: 2
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 5
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 4
- Average time to close issues: N/A
- Average time to close pull requests: 2 minutes
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 4
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
- openengg1 (4)
- ctftamu (1)
Top Labels
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Packages
- Total packages: 1
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Total downloads:
- pypi 8 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 3
- Total maintainers: 1
pypi.org: slgps
NN assisted chemistry reduction of mechanism based on Global Pathway Selection algorithm
- Homepage: https://github.com/ctftamu/SL-GPS
- Documentation: https://slgps.readthedocs.io/
- License: MIT License
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Latest release: 2.0.7
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- matplotlib *
- networkx *
- scikit-learn *
- tensorflow *
- List *