CALINS
CALculations and Investigations on Nuclear data uncertainties and Sensitivities
A Python package for computing nuclear data uncertainty propagation, sensitivity analyses, and data assimilation using the Generalized Linear Least Squares Method (GLLSM).
Developed by: French Authority for Nuclear Safety and Radiation Protection (ASNR)
About
CALINS is a specialized Python package designed for nuclear safety and criticality calculations. It enables: - Uncertainty propagation from nuclear data to integral responses - Sensitivity analysis of nuclear systems to cross-section variations - Data assimilation using the Generalized Linear Least Squares Method (GLLSM) - Bias estimation for calculated responses based on experimental benchmarks
The package is particularly useful for criticality safety analyses where understanding uncertainties and biases in calculated keff values is essential.
Features
- ✅ Uncertainty Calculation: Propagate nuclear data uncertainties using the sandwich formula
- ✅ Sensitivity Analysis: Process and visualize sensitivity profiles from SDF files
- ✅ Similarity Indices: Calculate E, Ck, G, and SSR indices between cases
- ✅ GLLSM Assimilation: Assimilate experimental benchmark data to reduce uncertainties
- ✅ Multiple Covariance Formats: Support for SCALE (COVERX binary/text), COMAC, GENDF, and Excel (xlsx) formats, with auto-detection
- ✅ Interactive Visualizations: Generate HTML reports with Plotly graphs
- ✅ Chi-squared Filtering: Automatic filtering of inconsistent benchmark cases
