PIER-VIBE (Predictive Intelligence Engine for Resonance, Vibration, and Integrity in Bridge Environments) is an AI-augmented hydro-structural governance framework for long-span offshore and riverine bridge infrastructure. The system integrates fluid-structure-soil interaction modeling, computational fluid dynamics, finite element structural analysis, physics-informed neural networks (PINNs), and real-time telemetry fusion to predict and mitigate critical bridge failure mechanisms including scour-induced foundation destabilization, resonance-driven dynamic instability, and cumulative fatigue degradation. The framework is composed of three interconnected computational modules: SSSE — Sub-Surface Scour Engine HSCE — Hydro-Structural Coupling Evaluator EFGL — Elastic Fatigue Governance Lock PIER-VIBE continuously computes the Bridge Structural Health Index (BSHI), a real-time composite safety certification metric designed to provide predictive structural integrity governance under dynamic environmental loading conditions. The project is classified within the Systems Safety & Engineering (AI-augmented) research domain and is released under the MIT License. DOI: 10.5281/zenodo.20390646
Samir Baladi (Thu,) studied this question.