HYPRO Core v4.1.0: computational core, data and scripts reproducing "A Cognitive Digital Twin Framework (HYPRO) Integrating Ensemble Machine Learning and Physics-Based Modeling for Hybrid Rocket Motor Analysis and Diagno
Reproducibility package for the article "A Cognitive Digital Twin Framework (HYPRO) Integrating Ensemble Machine Learning and Physics-Based Modeling for Hybrid Rocket Motor Analysis and Diagnostics". The archive contains: hypro_core/ - computational core of HYPRO Pro v4.1.0: zero-dimensional internal-ballistics solver with Summerfield flow-separation limit, regression-rate model zoo (random forest, gradient boosting, AdaBoost, support-vector regression, elastic net, multilayer perceptron, voting and stacking ensembles), multi-channel signal tools (LabVIEW reader, joint pressure-thrust segmentation, magnitude-squared coherence, acquisition-fil
Resource information
- Format
- zip
- Original repository
- 23102385
- DOI
- 10.5281/zenodo.23102385
- Credit basis
- Creators in Zenodo record metadata
- Access
- Open files available from the original Zenodo deposit
- Last checked
- Nov 5, 2026
- License
- Not specified
- Last record update
- Nov 5, 2026
About this resource
Reproducibility package for the article "A Cognitive Digital Twin Framework (HYPRO) Integrating Ensemble Machine Learning and Physics-Based Modeling for Hybrid Rocket Motor Analysis and Diagnostics". The archive contains: hypro_core/ - computational core of HYPRO Pro v4.1.0: zero-dimensional internal-ballistics solver with Summerfield flow-separation limit, regression-rate model zoo (random forest, gradient boosting, AdaBoost, support-vector regression, elastic net, multilayer perceptron, voting and stacking ensembles), multi-channel signal tools (LabVIEW reader, joint pressure-thrust segmentation, magnitude-squared coherence, acquisition-filter detection), data reduction and fuel library. scripts/ - analysis scripts that reproduce every number, table and figure of the article. data/ - reduced data of 31 static firings of three paraffin-based fuels with gaseous oxygen, a dual-station 1 kHz chamber-pressure record, and reduced steady-window pressure and thrust of 13 firings of a second campaign. The graphical application and its licensing system are not included. Requirements: Python 3.11 or newer with numpy, pandas, scipy, scikit-learn, statsmodels, matplotlib and joblib. See README.md for the run order.