Python Code for Fuzzy Bayesian Network-based Reliability and Sensitivity Analysis of a Multistate Nuclear Power Plant under Common Cause Failures

Key Points

• To implement a fuzzy bayesian network model for analyzing reliability and sensitivity in multistate nuclear power plants under common cause failures.
• Developed Python code compatible with Google Colab for the FBN model.
• Computed state-wise probabilities with and without considering common cause failures.
• Provided scripts, input datasets, and instructions for reproducibility.
• The code effectively computes state-wise probabilities for the multistate system.
• Demonstrated the impact of common cause failures on reliability metrics.
• Facilitated improved understanding of system performance under fault conditions.