TUNNEL-SHIELD : AI-Augmented Monitoring System for Tunnel Boring Machine Operations

TUNNEL-SHIELD is an AI-augmented geotechnical safety framework for deep shield tunnel excavation systems. The project integrates elastoplastic rock mechanics, loosening pressure evaluation, face plastic squeezing prediction, and segmental lining structural integrity analysis into a unified real-time safety governance architecture. The framework combines three primary computational modules: LPEC — Loosening Pressure Evaluation Core FPSE — Face Plastic Squeezing Evaluator LSLC — Lining Structural Stability Lock TUNNEL-SHIELD also incorporates AI governance layers using: Physics-Informed Neural Networks (PINN) XGBoost safety prediction models CNN-based lining distortion classification The system enables real-time tunnel safety monitoring, plastic zone forecasting, hydrostatic asymmetry analysis, crown settlement control, and automated governance escalation for TBM operations in high-stress geological environments. Research Domain: Systems Safety & Engineering (AI-augmented) Sub-domain: GEOTECH-AI-02 DOI: 10.5281/zenodo.20374106 OSF Preregistration: 10.17605/OSF.IO/JGZVM