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SHM strategy optimization and structural maintenance planning based on Bayesian joint modelling

Cheng Xing (UGent), Robby Caspeele (UGent) and Luc Taerwe (UGent)
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Abstract
In this contribution, an example is used to illustrate the application of Bayesian joint modelling in optimizing the SHM strategy and structural maintenance planning. The model parameters were evaluated first, using the Markov Chain Monte Carlo (MCMC) method. Then different parameters including expected SHM accuracy and risk acceptance criteria were investigated in order to give an insight on how the maintenance planning and life-cycle benefit are influenced. The optimal SHM strategy was then identified as the one that maximizes the benefit.

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Chicago
Xing, Cheng, Robby Caspeele, and Luc Taerwe. 2017. “SHM Strategy Optimization and Structural Maintenance Planning Based on Bayesian Joint Modelling.” In Safety, Reliability, Risk, Resilience and Sustainability of Structures and Infrastructure (ICOSSAR2017)Chr, ed. Christian Bucher, Bruce R. Ellingwood, and Dan M. Frangopol, 3079–3088.
APA
Xing, C., Caspeele, R., & Taerwe, L. (2017). SHM strategy optimization and structural maintenance planning based on Bayesian joint modelling. In C. Bucher, B. R. Ellingwood, & D. M. Frangopol (Eds.), Safety, Reliability, Risk, Resilience and Sustainability of Structures and Infrastructure (ICOSSAR2017)Chr (pp. 3079–3088). Presented at the 12th Int. Conference on Strucutral Safety and Reliability.
Vancouver
1.
Xing C, Caspeele R, Taerwe L. SHM strategy optimization and structural maintenance planning based on Bayesian joint modelling. In: Bucher C, Ellingwood BR, Frangopol DM, editors. Safety, Reliability, Risk, Resilience and Sustainability of Structures and Infrastructure (ICOSSAR2017)Chr. 2017. p. 3079–88.
MLA
Xing, Cheng, Robby Caspeele, and Luc Taerwe. “SHM Strategy Optimization and Structural Maintenance Planning Based on Bayesian Joint Modelling.” Safety, Reliability, Risk, Resilience and Sustainability of Structures and Infrastructure (ICOSSAR2017)Chr. Ed. Christian Bucher, Bruce R. Ellingwood, & Dan M. Frangopol. 2017. 3079–3088. Print.
@inproceedings{8546675,
  abstract     = {In this contribution, an example is used to illustrate the application of
Bayesian joint modelling in optimizing the SHM strategy and structural maintenance
planning. The model parameters were evaluated first, using the Markov
Chain Monte Carlo (MCMC) method. Then different parameters including expected
SHM accuracy and risk acceptance criteria were investigated in order to
give an insight on how the maintenance planning and life-cycle benefit are influenced.
The optimal SHM strategy was then identified as the one that maximizes
the benefit.},
  author       = {Xing, Cheng and Caspeele, Robby and Taerwe, Luc},
  booktitle    = {Safety, Reliability, Risk, Resilience and Sustainability of Structures and Infrastructure (ICOSSAR2017)Chr},
  editor       = {Bucher, Christian and Ellingwood, Bruce R. and Frangopol, Dan M.},
  isbn         = {978-3-903024-28-1},
  language     = {eng},
  location     = {Wenen (Oostenrijk)},
  pages        = {3079--3088},
  title        = {SHM strategy optimization and structural maintenance planning based on Bayesian joint modelling},
  year         = {2017},
}