Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 유재석 | - |
dc.date.accessioned | 2022-04-11T00:39:10Z | - |
dc.date.available | 2022-04-11T00:39:10Z | - |
dc.date.issued | 2020-08 | - |
dc.identifier.citation | APPLIED SCIENCES-BASEL, v. 10, no. 17, article no. 5937 | en_US |
dc.identifier.issn | 2076-3417 | - |
dc.identifier.uri | https://www.mdpi.com/2076-3417/10/17/5937 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/169855 | - |
dc.description.abstract | 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. | en_US |
dc.description.sponsorship | This research was funded by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry and Energy (MOTIE) of the Republic of Korea (No. 20183010025510). | en_US |
dc.language.iso | en | en_US |
dc.publisher | MDPI | en_US |
dc.subject | corrosion potential | en_US |
dc.subject | temperature effect | en_US |
dc.subject | rebar | en_US |
dc.subject | Gaussian process regression | en_US |
dc.title | An Experimental and Statistical Study on Rebar Corrosion Considering the Temperature Effect Using Gaussian Process Regression | en_US |
dc.type | Article | en_US |
dc.relation.no | 17 | - |
dc.relation.volume | 10 | - |
dc.identifier.doi | 10.3390/app10175937 | - |
dc.relation.page | 1-12 | - |
dc.relation.journal | APPLIED SCIENCES-BASEL | - |
dc.contributor.googleauthor | Woo, Byeong Hun | - |
dc.contributor.googleauthor | Jeon, In Kyu | - |
dc.contributor.googleauthor | Kim, Seong Soo | - |
dc.contributor.googleauthor | Lee, Jeong Bae | - |
dc.contributor.googleauthor | Ryou, Jae-Suk | - |
dc.relation.code | 2020047168 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING | - |
dc.identifier.pid | jsryou | - |
dc.identifier.orcid | https://orcid.org/0000-0001-5567-2742 | - |
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