Industry Foundation Classes (IFC)-based Method for Bridge Defect Information Representation and Analysis
Access Status
Open access
Date
2021Supervisor
Xiangyu Wang
Jun Li
Type
Thesis
Award
PhD
Metadata
Show full item recordFaculty
Humanities
School
School of Design and the Built Environment
Collection
Abstract
Visual inspection is a common approach to ensure the serviceability and reliability of bridges. To facilitate its automation, this research proposed a method for the identification, representation, and analysis of inspection-related information within a dynamic bridge BIM environment, using IFC standards. The case study results indicate that the bridge BIM models integrated with defect information supports seamless model exchange across different vendors, information retrieval, and efficient transfer to models for condition assessment and structural analysis.
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