A HUMAN-CENTERED INFRASTRUCTURE ASSET MANAGEMENT FRAMEWORK USING BIM AND AUGMENTED REALITY

Bridges are crucial components of the United States' infrastructure system, and maintaining them at an acceptable level of service requires various inspections at varying frequencies. However, traditional physical and visual inspections are subjective and time-consuming, and they do not meet the objectives of element-level asset management, which is becoming increasingly important. To address these challenges, this study proposes a Building Information Modeling (BIM) and Augmented Reality (AR)-based supporting inspection system (BASIS) that can objectively record bridge defect information. A pedestrian bridge is used to validate the inspection platform. To enable accurate condition evaluation of in-service infrastructure systems, this research proposes using finite element analysis to evaluate the element-level condition of assets comprehensively. The proposed system is validated using synthetic data of a bridge. Asset prioritization is accomplished with the Analytical Hierarchy Process (AHP), which defines the relative significance of various asset criteria. Current decision-making is not centered on maintenance priorities at the element level. This study's innovative method for evaluating the condition of assets at the element level is a key step toward achieving more objective and comprehensive evaluation methodologies. By merging BIM with AR, the proposed computational system delivers precise defect information of assets, decreases costs, accelerates inspection, and facilitates quantitative condition evaluation. The provided framework's precision, efficiency, flexibility, and practicability were tested by comparing its performance on major infrastructure systems to that of conventional methods. Overall, this dissertation provides a novel and efficient approach to bridge inspection and asset management that has the potential to improve the long-term performance of bridges by making the inspection process less expensive, less intrusive, more quantitative, and more consistent.

Author

• John Samuel, Immanuel Johnson

• Augmented Reality
• Bridge Inspection
• Building Information Modeling
• Digital twin
• Infrastructure Asset Management
• Life Cycle Management

Identifier

hdl:1920/13980

OAI identifier oai:identifier

oai:MARS:1920/13980