A Data-Driven Physics-Informed Method for Prognosis of Infrastructure Systems: Theory and Application to Crack Prediction

AbstractInfrastructure systems are the backbones of the socioeconomic development of a community. However, after installation, these engineered systems undergo deterioration, leading to a degradati...

[1]  Jianzhong Sun,et al.  Integration of scheduled structural health monitoring with airline maintenance program based on risk analysis , 2017 .

[2]  Siddhartha Ghosh,et al.  Reliability of a corroded RC beam based on Bayesian updating of the corrosion model , 2016 .

[3]  Gokhan Kilic,et al.  Integrated health assessment strategy using NDT for reinforced concrete bridges , 2014 .

[4]  Gui Yun Tian,et al.  Passive RFID sensor systems for crack detection & characterization , 2017 .

[5]  Heng Liu,et al.  Image-driven structural steel damage condition assessment method using deep learning algorithm , 2019, Measurement.

[6]  Sumathi Poobal,et al.  Crack detection using image processing: A critical review and analysis , 2017, Alexandria Engineering Journal.

[7]  T. Schmitz,et al.  In situ monitoring and prediction of progressive joint wear using Bayesian statistics , 2011 .

[8]  Dan M. Frangopol,et al.  Life cycle utility-informed maintenance planning based on lifetime functions: optimum balancing of cost, failure consequences and performance benefit , 2016 .

[9]  Gangbing Song,et al.  Recent applications of fiber optic sensors to health monitoring in civil engineering , 2004 .

[10]  Min-Yuan Cheng,et al.  Risk-based maintenance strategy for deteriorating bridges using a hybrid computational intelligence technique: a case study , 2019 .

[11]  Limin Sun,et al.  Effect of concrete carbonation on natural frequency of reinforced concrete beams , 2017 .

[12]  Donato Sabia,et al.  A machine learning approach for the automatic long-term structural health monitoring , 2018, Structural Health Monitoring.

[13]  Fei Kang,et al.  Structural health monitoring of concrete dams using long-term air temperature for thermal effect simulation , 2019, Engineering Structures.

[14]  Maria Q. Feng,et al.  Experimental validation of cost-effective vision-based structural health monitoring , 2017 .

[15]  Paul A. Wawrzynek,et al.  Probabilistic fatigue damage prognosis using surrogate models trained via three-dimensional finite element analysis , 2017 .

[16]  Dan M. Frangopol,et al.  Time-dependent risk associated with deterioration of highway bridge networks , 2013 .

[17]  Torgeir Moan,et al.  Life cycle structural integrity management of offshore structures , 2018 .

[18]  Claudomiro Sales,et al.  Machine learning algorithms for damage detection: Kernel-based approaches , 2016 .

[19]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[20]  Alison B. Flatau,et al.  Review Paper: Health Monitoring of Civil Infrastructure , 2003 .

[21]  C Li,et al.  Risk-cost optimised maintenance strategy for tunnel structures , 2017 .