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A Bayesian inference approach for the updating of spatially distributed corrosion model parameters based on heterogeneous measurement data

Eline Vereecken (UGent) , Wouter Botte (UGent) , Geert Lombaert and Robby Caspeele (UGent)
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Abstract
In many countries concrete bridges are reaching the end of their service-life, showing signs of deterioration, e.g. due to corrosion. Hence, the question arises whether their safety level is still acceptable. To improve the estimate of the safety level, information extracted from different tests, e.g. proof-loading, operational modal analysis, etc., where deflections, strains or accelerations are measured, can be used. Unfortunately, in practice inspection results are often not used directly to improve our knowledge of the degree of deterioration and it is difficult to combine information from different types of tests when making inferences. In this contribution, a methodology is developed and demonstrated in order to update estimations of parameters of service life models for concrete girders subjected to chloride-induced corrosion based on heterogeneous measurement data, with focus on strains measured under proof-loading and modal parameters extracted from ambient vibration tests. A Bayesian framework is adopted, where posterior distributions of the parameters describing the corrosion process are generated based on Markov Chain Monte Carlo sampling. These updated distributions reflect the information on the actual deterioration state of the bridge, which can be extracted from limited data. The updating procedure based on strain and modal data is illustrated by application on a simply supported beam and a case study.
Keywords
TIME-DEPENDENT RELIABILITY, DETERIORATING CONCRETE BRIDGES, DAMAGE DETECTION, REINFORCEMENT CORROSION, CRACK WIDTH, PREDICTION, IDENTIFICATION, OPTIMIZATION, UNCERTAINTY, PERFORMANCE, Bayesian updating, corrosion, damage assessment, degradation, Reinforced concrete, structural health monitoring, uncertainty

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MLA
Vereecken, Eline, et al. “A Bayesian Inference Approach for the Updating of Spatially Distributed Corrosion Model Parameters Based on Heterogeneous Measurement Data.” STRUCTURE AND INFRASTRUCTURE ENGINEERING, 2020, doi:10.1080/15732479.2020.1833046.
APA
Vereecken, E., Botte, W., Lombaert, G., & Caspeele, R. (2020). A Bayesian inference approach for the updating of spatially distributed corrosion model parameters based on heterogeneous measurement data. STRUCTURE AND INFRASTRUCTURE ENGINEERING. https://doi.org/10.1080/15732479.2020.1833046
Chicago author-date
Vereecken, Eline, Wouter Botte, Geert Lombaert, and Robby Caspeele. 2020. “A Bayesian Inference Approach for the Updating of Spatially Distributed Corrosion Model Parameters Based on Heterogeneous Measurement Data.” STRUCTURE AND INFRASTRUCTURE ENGINEERING. https://doi.org/10.1080/15732479.2020.1833046.
Chicago author-date (all authors)
Vereecken, Eline, Wouter Botte, Geert Lombaert, and Robby Caspeele. 2020. “A Bayesian Inference Approach for the Updating of Spatially Distributed Corrosion Model Parameters Based on Heterogeneous Measurement Data.” STRUCTURE AND INFRASTRUCTURE ENGINEERING. doi:10.1080/15732479.2020.1833046.
Vancouver
1.
Vereecken E, Botte W, Lombaert G, Caspeele R. A Bayesian inference approach for the updating of spatially distributed corrosion model parameters based on heterogeneous measurement data. STRUCTURE AND INFRASTRUCTURE ENGINEERING. 2020;
IEEE
[1]
E. Vereecken, W. Botte, G. Lombaert, and R. Caspeele, “A Bayesian inference approach for the updating of spatially distributed corrosion model parameters based on heterogeneous measurement data,” STRUCTURE AND INFRASTRUCTURE ENGINEERING, 2020.
@article{8681023,
  abstract     = {{In many countries concrete bridges are reaching the end of their service-life, showing signs of deterioration, e.g. due to corrosion. Hence, the question arises whether their safety level is still acceptable. To improve the estimate of the safety level, information extracted from different tests, e.g. proof-loading, operational modal analysis, etc., where deflections, strains or accelerations are measured, can be used. Unfortunately, in practice inspection results are often not used directly to improve our knowledge of the degree of deterioration and it is difficult to combine information from different types of tests when making inferences. In this contribution, a methodology is developed and demonstrated in order to update estimations of parameters of service life models for concrete girders subjected to chloride-induced corrosion based on heterogeneous measurement data, with focus on strains measured under proof-loading and modal parameters extracted from ambient vibration tests. A Bayesian framework is adopted, where posterior distributions of the parameters describing the corrosion process are generated based on Markov Chain Monte Carlo sampling. These updated distributions reflect the information on the actual deterioration state of the bridge, which can be extracted from limited data. The updating procedure based on strain and modal data is illustrated by application on a simply supported beam and a case study.}},
  author       = {{Vereecken, Eline and Botte, Wouter and Lombaert, Geert and Caspeele, Robby}},
  issn         = {{1573-2479}},
  journal      = {{STRUCTURE AND INFRASTRUCTURE ENGINEERING}},
  keywords     = {{TIME-DEPENDENT RELIABILITY,DETERIORATING CONCRETE BRIDGES,DAMAGE DETECTION,REINFORCEMENT CORROSION,CRACK WIDTH,PREDICTION,IDENTIFICATION,OPTIMIZATION,UNCERTAINTY,PERFORMANCE,Bayesian updating,corrosion,damage assessment,degradation,Reinforced concrete,structural health monitoring,uncertainty}},
  language     = {{eng}},
  pages        = {{17}},
  title        = {{A Bayesian inference approach for the updating of spatially distributed corrosion model parameters based on heterogeneous measurement data}},
  url          = {{http://dx.doi.org/10.1080/15732479.2020.1833046}},
  year         = {{2020}},
}

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