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Prediction of concrete corrosion in sewers with hybrid Gaussian processes regression model

Journal Article


Abstract


  • Concrete corrosion is a major concern for sewer authorities due to the significantly shortened service life,which is governed by the corrosion rate and the corrosion initiation time. This paper proposes a hybridGaussian Processes Regression (GPR) model to approach the evolution of the corrosion rate andcorrosion initiation time, thereby supporting the calculation of service life of sewers. A major challengein practice is the limited availability of reliable corrosion data obtained in well-defined sewerenvironments. To enhance the predictability of the hybrid GPR model, an interpolation technique wasimplemented to extend the limited dataset. The trained model was able to estimate the corrosioninitiation time and corrosion rates very close to those measured in Australian sewers.

Authors


  •   Liu, Yiqi (external author)
  •   Song, Yarong (external author)
  •   Keller, Jurg (external author)
  •   Bond, Philip (external author)
  •   Jiang, Guangming

Publication Date


  • 2017

Citation


  • Liu, Y., Song, Y., Keller, J., Bond, P. & Jiang, G. (2017). Prediction of concrete corrosion in sewers with hybrid Gaussian processes regression model. RSC Advances: an international journal to further the chemical sciences, 7 30894-30903.

Scopus Eid


  • 2-s2.0-85021650260

Number Of Pages


  • 9

Start Page


  • 30894

End Page


  • 30903

Volume


  • 7

Place Of Publication


  • United Kingdom

Abstract


  • Concrete corrosion is a major concern for sewer authorities due to the significantly shortened service life,which is governed by the corrosion rate and the corrosion initiation time. This paper proposes a hybridGaussian Processes Regression (GPR) model to approach the evolution of the corrosion rate andcorrosion initiation time, thereby supporting the calculation of service life of sewers. A major challengein practice is the limited availability of reliable corrosion data obtained in well-defined sewerenvironments. To enhance the predictability of the hybrid GPR model, an interpolation technique wasimplemented to extend the limited dataset. The trained model was able to estimate the corrosioninitiation time and corrosion rates very close to those measured in Australian sewers.

Authors


  •   Liu, Yiqi (external author)
  •   Song, Yarong (external author)
  •   Keller, Jurg (external author)
  •   Bond, Philip (external author)
  •   Jiang, Guangming

Publication Date


  • 2017

Citation


  • Liu, Y., Song, Y., Keller, J., Bond, P. & Jiang, G. (2017). Prediction of concrete corrosion in sewers with hybrid Gaussian processes regression model. RSC Advances: an international journal to further the chemical sciences, 7 30894-30903.

Scopus Eid


  • 2-s2.0-85021650260

Number Of Pages


  • 9

Start Page


  • 30894

End Page


  • 30903

Volume


  • 7

Place Of Publication


  • United Kingdom