Prediction of concrete corrosion in sewers with hybrid Gaussian processes regression model. Issue 49 (15th June 2017)
- Record Type:
- Journal Article
- Title:
- Prediction of concrete corrosion in sewers with hybrid Gaussian processes regression model. Issue 49 (15th June 2017)
- Main Title:
- Prediction of concrete corrosion in sewers with hybrid Gaussian processes regression model
- Authors:
- Liu, Yiqi
Song, Yarong
Keller, Jurg
Bond, Philip
Jiang, Guangming - Abstract:
- Abstract : A hybrid Gaussian Processes Regression (GPR) model is to approach the evolution of the corrosion rate and corrosion initiation time, thereby supporting the calculation of service life of sewers. 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 hybrid Gaussian Processes Regression (GPR) model to approach the evolution of the corrosion rate and corrosion initiation time, thereby supporting the calculation of service life of sewers. A major challenge in practice is the limited availability of reliable corrosion data obtained in well-defined sewer environments. To enhance the predictability of the hybrid GPR model, an interpolation technique was implemented to extend the limited dataset. The trained model was able to estimate the corrosion initiation time and corrosion rates very close to those measured in Australian sewers.
- Is Part Of:
- RSC advances. Volume 7:Issue 49(2017)
- Journal:
- RSC advances
- Issue:
- Volume 7:Issue 49(2017)
- Issue Display:
- Volume 7, Issue 49 (2017)
- Year:
- 2017
- Volume:
- 7
- Issue:
- 49
- Issue Sort Value:
- 2017-0007-0049-0000
- Page Start:
- 30894
- Page End:
- 30903
- Publication Date:
- 2017-06-15
- Subjects:
- Chemistry -- Periodicals
540.5 - Journal URLs:
- http://pubs.rsc.org/en/Journals/JournalIssues/RA ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c7ra03959j ↗
- Languages:
- English
- ISSNs:
- 2046-2069
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8036.750300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 262.xml