Time：2024-10-22 18:00

Location：ZJUI B407

Enhancing Inspection and Monitoring Strategies with Graphics-based Digital Twins

Structural health assessment through inspection and monitoring is crucial for societal resilience. While computer vision (CV)-based methods offer promise for structural inspection and monitoring, field validation remains challenging. To address these challenges, a Graphics-based Digital Twin (GBDT)-aided structural health assessment framework is proposed. The GBDT combines a high-fidelity finite element (FE) model to simulate structural responses with a photorealistic computer graphics (CG) model for visual representation. This integrated framework enables the simulation and validation of CV-based inspection and monitoring strategies. The approach is demonstrated in two use cases: post-earthquake UAV inspections and the monitoring of miter gates under hydrostatic loads. GBDT effectively replicates realworld conditions, advancing CV-based structural health assessment techniques.

Dr. Wang obtained her Ph.D. from the Department of Civil and Environmental Engineering at the University of Illinois Urbana-Champaign (UIUC), and she is starting a position as a postdoctoral researcher at Tsinghua University. She holds a B.S. degree from Zhejiang University and an M.S. degree from UIUC. In 2021, Dr. Wang got the “LIU Huixian Earthquake Engineering Scholarship Award.” During her PhD, she published eight journal papers in top-tier journals, including Engineering Structures and Structural Health Monitoring. Her research focuses on interdisciplinary applications of computer vision technologies for structural inspection and health monitoring.