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Spatial variability of half-cell potential data from a reinforced concrete structure—a geostatistical analysis.
- Source :
-
Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance . Nov2024, Vol. 20 Issue 11, p1698-1713. 16p. - Publication Year :
- 2024
-
Abstract
- Corrosion in reinforced concrete structures is among the major degradation mechanisms. The quantification and description of the spatial distribution of the corrosion condition within a structure on the basis of condition assessments are important. This study considered half-cell potential mapping data as a widely used technique to detect corrosion in reinforced concrete structures. A four-step workflow was proposed to analyse half-cell potential data with geostatistical techniques, first consisting of trend identification and possible trend removal. The obtained residuals were then subjected to a quantile-quantile transformation. Subsequently, experimental variograms were calculated and fitted with variogram models to estimate the correlation lengths. A case study with data from a road tunnel confirms the applicability of the workflow. It was assumed that the identified trend is primarily a result of the heterogeneity of the exposure conditions within the structure that ranges several metres. The residuals are interpreted as the result of the heterogeneities of material resistances that give rise to spatial variability in corrosion probability on a shorter distance range. The proposed analysis may be utilised for service life modelling (e.g. based on random fields), planning maintenance works, or optimising the grid size for half-cell potential measurements. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15732479
- Volume :
- 20
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance
- Publication Type :
- Academic Journal
- Accession number :
- 179360065
- Full Text :
- https://doi.org/10.1080/15732479.2022.2158204