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Computers and Concrete
  Volume 13, Number 5, May 2014 , pages 659-677
DOI: https://doi.org/10.12989/cac.2014.13.5.659
 


Bayesian updated correlation length of spatial concrete properties using limited data
Pieterjan Criel, Robby Caspeele and Luc Taerwe

 
Abstract
    A Bayesian response surface updating procedure is applied in order to update the parameters of the covariance function of a random field for concrete properties based on a limited number of available measurements. Formulas as well as a numerical algorithm are presented in order to update the parameters of response surfaces using Markov Chain Monte Carlo simulations. The parameters of the covariance function are often based on some kind of expert judgment due the lack of sufficient measurement data. However, a Bayesian updating technique enables to estimate the parameters of the covariance function more rigorously and with less ambiguity. Prior information can be incorporated in the form of vague or informative priors. The proposed estimation procedure is evaluated through numerical simulations and compared to the commonly used least square method.
 
Key Words
    bayesian updating techniques; random fields; concrete properties; covariance function; variogram; Markov chain Monte Carlo simulations
 
Address
Pieterjan Criel, Robby Caspeele and Luc Taerwe: Ghent University, Department of Structural Engineering, Magnel Laboratory for Concrete Research, Ghent, Belgium
 

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