An Experimental and Statistical Study on Rebar Corrosion Considering the Temperature Effect Using Gaussian Process Regression

  • Woo, Byeong Hun
  • Jeon, In Kyu
  • Kim, Seong Soo
  • Lee, Jeong Bae
  • Ryou, Jae-Suk
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초록

Temperature is an important factor that affects corrosion potential in rebars. The temperature effect must be removed from the corrosion potential for precise measurement of corrosion rates. To separate the temperature effect from the corrosion potential, in this study rebar specimens were not embedded in concrete but, instead, were placed in an uncontrolled air environment. Gaussian process regression (GPR) was applied to the temperature and the non-corrosion potential data in order to remove the temperature effect from the corrosion potential. The results indicated that the corrosion potential was affected by the temperature. Furthermore, the GPR models of all the experimental cases showed high coefficients of determination (R-2> 0.90) and low root mean square errors (RMSE < 0.08), meaning that these models had high reliability. The fitted GPR models were used to successfully remove the temperature effect from the corrosion potential. This demonstrates that the GPR method can be appropriately used to assess the temperature effect on rebar corrosion.

키워드

corrosion potentialtemperature effectrebarGaussian process regressionCELL POTENTIAL MEASUREMENTSTEEL REBARSCONCRETEBEHAVIORMODEL
제목
An Experimental and Statistical Study on Rebar Corrosion Considering the Temperature Effect Using Gaussian Process Regression
저자
Woo, Byeong HunJeon, In KyuKim, Seong SooLee, Jeong BaeRyou, Jae-Suk
DOI
10.3390/app10175937
발행일
2020-09
유형
Article
저널명
APPLIED SCIENCES-BASEL
10
17
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1 ~ 12

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