Physics-Informed Knowledge-Driven Decision-Making Framework for Holistic Bridge Maintenance
Publication: Journal of Construction Engineering and Management
Volume 150, Issue 9
Abstract
Bridge maintenance is a highly intricate task that involves considering a wide range of factors in order to achieve optimal decisions that align with multiple objectives, criteria, and the entire lifecycle of the bridge. While physics-informed analysis, such as the finite element method (FEM), can simulate complex and closely coupled scenarios, such as bridge structural analysis, it cannot account for some loosely coupled discrete factors, which could be addressed by ontological reasoning. Therefore, this paper presents a knowledge-driven decision-making framework that combines static knowledge reasoning with dynamic FEM analysis results to support holistic bridge maintenance decisions. One significant contribution of this research is the development of a comprehensive bridge maintenance ontology that incorporates knowledge derived from bridge maintenance standards. Another key contribution is the ability to employ complex runtime rules-based reasoning to tackle intricate bridge maintenance scenarios. To enable automatic knowledge-driven reasoning, an integrated workflow is developed to orchestrate semantic modeling with numerical modeling through a Python-based Web Ontology Language application programming interface (OWL API). This integration facilitates the efficient orchestration of the framework. A case study is presented to demonstrate the potential for the developed framework in assisting with the complex holistic decisions required for bridge maintenance.
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Data Availability Statement
All data, models, or codes that support the findings of this research are available from the corresponding author upon reasonable request.
Acknowledgments
This research was supported by Research Funds for the Central Universities of China (Grant No. 3132019349), China Scholarship Council (CSC No. 202006570025), and BIM for Smart Engineering Centre in Cardiff University, UK. The author would like to thank them for their support.
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Published In
Journal of Construction Engineering and Management
Volume 150 • Issue 9 • September 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Feb 1, 2023
Accepted: Mar 21, 2024
Published online: Jun 18, 2024
Published in print: Sep 1, 2024
Discussion open until: Nov 18, 2024
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