Influence of Concrete Moisture Condition on Half-Cell Potential Measurement

Abstract

The detection of on-going corrosion is one of the main issues during inspection of reinforced concrete structures. The half-cell potential measurement method is the most common and established non-destructive technique to support this task. But a lot of infrastructures are exposed to rain or seawater which can cause heterogeneous moisture condition within one component. In turn this can have influence on the potential mapping results and as a consequence the interpretability of the half-cell potential measurement is impaired. This paper focuses on the influence of concrete moisture condition on half-cell potential measurement. Laboratory and practical tests results are analyzed qualitatively with varying moisture condition due to natural exposure and as well with different pre-wetting conditions. On the basis of these results recommendations are made how to evaluate halfcell potential mapping results. If large structures are inspected by half-cell potential measurements it is advantageous to compare only these parts which are in a comparable moisture condition by subdivision of the structure.

Inspection and Assessment of Corrosion in Pretensioned Concrete Bridge Girders Exposed to Coastal Climate

“…A numerical study by Kessler and Gehlen [47] found that inhomogeneous moisture content below the concrete surface measured can reduce the detectability of reinforcement corrosion, and suggests evaluating HCP data only from parts of the structure with similar moisture conditions [48,49].…”

“…The procedures integrate conventional test methods and are inspired by existing methodologies in the literature [22,45]. They include analyzing the HCP data from areas with comparable moisture conditions [48,49].…”

“…We therefore concluded that HCP measurements were more reliable for corrosion assessment then ER results, which should always be verified with visual inspection. To improve the assessment, statistical analysis should be performed on areas with similar environmental exposure to moisture and chlorides [48,49]. Since these conditions vary along NIB girders (see Section 5.1), Girder 2 was subdivided into two regions with comparable chloride and moisture loads: 1) a dry area in the span and 2) humid areas near supports.…”

Integrating Data from Multiple Nondestructive Evaluation Technologies Using Machine Learning Algorithms for the Enhanced Assessment of a Concrete Bridge Deck

“…HCP measurements can be impacted by various parameters which can result in incorrect interpretations of the data. One such factor is the moisture content, which was shown to reduce electrical resistivity and lead to lower (more negative) HCP values [1][2][3][4][5][6][7]. Another crucial parameter is the concrete cover thickness, which affects the distribution of the potential, causing the potential at the steel/concrete interface to be significantly different from the potential on the concrete surface as the concrete cover thickness increases [8].…”