Pushkkaarr/Anomaly-and-Fault-Detection-in-Nuclear-Power-Plants-with-Machine-Learning
Physics-informed machine learning system for anomaly detection and fault diagnosis in nuclear power plants, combining thermodynamic laws with AI to improve safety, reliability, and early fault prediction.
What's novel
Physics-informed machine learning system for anomaly detection and fault diagnosis in nuclear power plants, combining thermodynamic laws with AI to improve safety, reliability, and early fault prediction.
Code Analysis
0 files read · 3 roundsA conceptual project structure for a nuclear reactor safety system combining physics models and RL agents that cannot be evaluated because the core Python source files are inaccessible.
Strengths
Clear separation between frontend (Next.js) and backend (Python) components; well-organized directory structure suggesting thoughtful planning.
Weaknesses
Cannot evaluate core logic, algorithms, or implementation quality due to inaccessible backend Python files; only frontend UI components were readable which lack business logic.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
75
Contributors
1
Files
160
Active weeks
14
Repository
Language
Python
Stars
1
Forks
0
License
GPL-3.0