Researchers have developed a novel physics-informed DeepONet framework to create a fast and physically consistent surrogate model for real-time structural health monitoring of fractured elastic domains. This model predicts displacement fields based on boundary conditions and fracture geometry, notably without requiring finite-element-generated training data. The framework incorporates a weak imposition of the traction-free condition on fracture boundaries via a localized penalty term, with initial examples demonstrating its feasibility for specific fracture geometries. AI
IMPACT This research could lead to more efficient and accurate real-time structural health monitoring systems.
RANK_REASON The cluster contains an academic paper detailing a new model framework.
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