scholarly journals Effect of Chloride on Electrical Resistivity in Carbonated and Non-Carbonated Concrete

2020 ◽  
Vol 10 (18) ◽  
pp. 6272 ◽  
Author(s):  
In-Seok Yoon ◽  
Chun-Ho Chang

The resistivity of a concrete structure exposed to chloride ions indicates the risk of early corrosion damage, because a low resistivity is related to rapid chloride penetration and to a high corrosion rate. Concrete resistivity is a geometry-independent material property that describes the electrical resistance, which is the ratio between the applied voltage and resulting current in a unit cell. The current is carried by ions dissolved in the pore liquid. While some data exist on the relationship between the moisture content and electrical resistivity of concrete, very little research has been conducted to evaluate the effect of chloride on the conduction of electricity through carbonated and non-carbonated concrete. The purpose of this study is to examine the effect of chloride concentration on the surface electrical resistivity measurement of carbonated and non-carbonated concrete. Chloride concentration had influenced the resistivity of concrete and the relationship showed a linear function. However, for concrete under the combined deterioration of carbonation and chlorides, a reduction in porosity due to the carbonation had a greater effect on the electrical resistivity than the increase in conductivity due to the chloride ions. Conclusively, this paper suggested the quantitative solution to depict the electrical resistivity of concrete with various chloride concentrations.

2005 ◽  
Vol 86 (6) ◽  
pp. 064104 ◽  
Author(s):  
Yonghao Han ◽  
Chunxiao Gao ◽  
Yanzhang Ma ◽  
Hongwu Liu ◽  
Yuewu Pan ◽  
...  

2020 ◽  
Author(s):  
Karthick Thiyagarajan ◽  
Parikshit Acharya ◽  
Lasitha Piyathilaka ◽  
sarath kodagoda

Smart Sensing technologies can play an important role in the conditional assessment of concrete sewer pipe linings. In the long-term, the permeation of acids can deteriorate the pipe linings. Currently, there are no proven sensors available to non-invasively estimate the depth of acid permeation in real-time. The electrical resistivity measurement on the surface of the linings can indicate the sub-surface acid moisture conditions. In this study, we consider acid permeated linings as a two resistivity layer concrete sample, where the top resistivity layer is assumed to be acid permeated and the bottom resistivity layer indicates normal moisture conditions. Firstly, we modeled the sensor based on the four-probe Wenner method. The measurements of the developed model were compared with the previous studies for validation. Then, the sensor model was utilized to study the effects of electrode contact area, electrode spacing distance and two resistivity layered concrete on the apparent resistivity measurements. All the simulations were carried out by varying the thickness of top resistivity layer concrete. The simulation study indicated that the electrode contact area has very minimal effects on apparent resistivity measurements. Also, an increase in apparent resistivity measurements was observed when there is an increase in the distance of the electrode spacing. Further, a machine learning approach using Gaussian process regression modeling was formulated to estimate the depth of acid permeated layer


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