A Data-Driven Physics-Informed Method for Prognosis of Infrastructure Systems: Theory and Application to Crack Prediction
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6, Issue 2
Abstract
Infrastructure systems are the backbones of the socioeconomic development of a community. However, after installation, these engineered systems undergo deterioration, leading to a degradation in their condition while in operation. In this work, a generalized modeling framework is proposed and validated for the diagnosis and prognosis of infrastructure systems based on real-time data. A data-driven modeling scheme, dynamic mode decomposition (DMD), is used for prognosis. The novelty of the proposed framework lies in the fact that the developed prognostic model is data-driven and physics informed, and the model works better on problems with unknown/implicit governing equations and boundary conditions. The developed prognostic model provides more accurate predictions based on real-time data and identification of dominant spatiotemporal modes, as evident from the application of mortar cube crack prediction under compressive testing. This framework can be recommended to researchers/practitioners for predicting the remaining useful life of infrastructure components and systems before their maintenance or failure. Such robust predictions of the future condition of existing infrastructure will be beneficial to stakeholders for sustainable development.
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Data Availability Statement
All data generated or analyzed during the study are available as Supplemental Data along with the manuscript. The algorithms used for writing the simulation codes are provided in the manuscript.
Acknowledgments
The first author acknowledges the Graduate Teaching Assistant scholarship funded by the Ministry of Human Resources and Development, Government of India.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6 • Issue 2 • June 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Aug 12, 2019
Accepted: Oct 28, 2019
Published online: Feb 13, 2020
Published in print: Jun 1, 2020
Discussion open until: Jul 13, 2020
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