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Use of Bayesian updating of time-dependent performance indicators for prediction of structural lifetime and critical inspection points in time

Cheng Xing UGent, Matthias Van Kerkhove, Robby Caspeele UGent and Luc Taerwe UGent (2017) The Fifth International Symposium on Life-cycle Engineering. p.448-455
abstract
A comprehensive life-cycle performance assessment of structures and infrastructures requires the definition of Performance Indicators (PIs), which provide an easier and time efficient assessment procedure. It is a tool by which the safety and integrity of the structural system is ensured by preventing the PIs from crossing their thresholds. While structures are subjected to time-dependent degradation processes which require consideration of uncertainties, the evolution of PIs can be simulated and forecasted with appropriate statistical model in combination with available inspection and monitoring information. An innovative Bayesian framework for making use of the available historical data and incorporation of additional information from inspection and monitoring in a so-called Stepwise Changing Rate Updating Method (SCRUM) is developed in this paper to predict the future PIs. Specific to the approach is the use of the Changing Rate (CR) between subsequent PI observations. First, an estimation of the statistical properties of the PI as well as its CR is made, and then further inspection and monitoring allows for incorporating additional information in the Bayesian updating framework for performance prediction. A time-dependent weight factor is defined and implemented in order to account for the decreasing influence of previous CRs on the predicted PI. The advantage of SCRUM is that neither an underlying mechanical nor dynamic model is needed to do the forecasting, making it an easy applicable tool which only uses Monte Carlo simulations to fulfill its task. The primary objective is to determine the lifetime of the structure, given a clear definition of the lifetime and the failure probability limit. Furthermore, the developed method can be used for the detection of optimal inspection intervals. The application of SCRUM is limited to stable processes, i.e. processes for which the performance indicator decreases almost monotonic.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
Inspection, Bayesian updating, Lifetime, Changing rate, Prediction, Performance indicators
in
The Fifth International Symposium on Life-cycle Engineering
editor
Jaap Bakker, Dan M. Frangopol and Klaas van Breugel
pages
448 - 455
publisher
Taylor & Francis Group
place of publication
London
conference name
The Fifth International Symposium on Life-cycle Engineering (IALCCE 2016)
conference location
Delft
conference start
2016-10-16
conference end
2016-10-20
ISBN
978-1-138-02847-0
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
8136359
handle
http://hdl.handle.net/1854/LU-8136359
date created
2016-11-09 09:54:23
date last changed
2017-01-02 09:53:22
@inproceedings{8136359,
  abstract     = {A comprehensive life-cycle performance assessment of structures and infrastructures requires the definition of Performance Indicators (PIs), which provide an easier and time efficient assessment procedure. It is a tool by which the safety and integrity of the structural system is ensured by preventing the PIs from crossing their thresholds. While structures are subjected to time-dependent degradation processes which require consideration of uncertainties, the evolution of PIs can be simulated and forecasted with appropriate statistical model in combination with available inspection and monitoring information. An innovative Bayesian
framework for making use of the available historical data and incorporation of additional information from
inspection and monitoring in a so-called Stepwise Changing Rate Updating Method (SCRUM) is developed
in this paper to predict the future PIs. Specific to the approach is the use of the Changing Rate (CR) between
subsequent PI observations. First, an estimation of the statistical properties of the PI as well as its CR is made,
and then further inspection and monitoring allows for incorporating additional information in the Bayesian
updating framework for performance prediction. A time-dependent weight factor is defined and implemented
in order to account for the decreasing influence of previous CRs on the predicted PI. The advantage of
SCRUM is that neither an underlying mechanical nor dynamic model is needed to do the forecasting, making
it an easy applicable tool which only uses Monte Carlo simulations to fulfill its task. The primary objective is
to determine the lifetime of the structure, given a clear definition of the lifetime and the failure probability
limit. Furthermore, the developed method can be used for the detection of optimal inspection intervals. The
application of SCRUM is limited to stable processes, i.e. processes for which the performance indicator decreases
almost monotonic.},
  author       = {Xing, Cheng and Van Kerkhove, Matthias and Caspeele, Robby and Taerwe, Luc},
  booktitle    = {The Fifth International Symposium on Life-cycle Engineering},
  editor       = {Bakker, Jaap and Frangopol, Dan M.  and van Breugel, Klaas},
  isbn         = {978-1-138-02847-0},
  keyword      = {Inspection,Bayesian updating,Lifetime,Changing rate,Prediction,Performance indicators},
  language     = {eng},
  location     = {Delft},
  pages        = {448--455},
  publisher    = {Taylor \& Francis Group},
  title        = {Use of Bayesian updating of time-dependent performance indicators for prediction of structural lifetime and critical inspection points in time},
  year         = {2017},
}

Chicago
Xing, Cheng, Matthias Van Kerkhove, Robby Caspeele, and Luc Taerwe. 2017. “Use of Bayesian Updating of Time-dependent Performance Indicators for Prediction of Structural Lifetime and Critical Inspection Points in Time.” In The Fifth International Symposium on Life-cycle Engineering, ed. Jaap Bakker, Dan M. Frangopol, and Klaas van Breugel, 448–455. London: Taylor & Francis Group.
APA
Xing, C., Van Kerkhove, M., Caspeele, R., & Taerwe, L. (2017). Use of Bayesian updating of time-dependent performance indicators for prediction of structural lifetime and critical inspection points in time. In Jaap Bakker, D. M. Frangopol, & K. van Breugel (Eds.), The Fifth International Symposium on Life-cycle Engineering (pp. 448–455). Presented at the The Fifth International Symposium on Life-cycle Engineering (IALCCE 2016), London: Taylor & Francis Group.
Vancouver
1.
Xing C, Van Kerkhove M, Caspeele R, Taerwe L. Use of Bayesian updating of time-dependent performance indicators for prediction of structural lifetime and critical inspection points in time. In: Bakker J, Frangopol DM, van Breugel K, editors. The Fifth International Symposium on Life-cycle Engineering. London: Taylor & Francis Group; 2017. p. 448–55.
MLA
Xing, Cheng, Matthias Van Kerkhove, Robby Caspeele, et al. “Use of Bayesian Updating of Time-dependent Performance Indicators for Prediction of Structural Lifetime and Critical Inspection Points in Time.” The Fifth International Symposium on Life-cycle Engineering. Ed. Jaap Bakker, Dan M. Frangopol, & Klaas van Breugel. London: Taylor & Francis Group, 2017. 448–455. Print.