Numerical Modeling of the Effects of Electrode Spacing and Multilayered
Concrete Resistivity on the Apparent Resistivity Measured Using Wenner
Method
- Karthick Thiyagarajan ,
- Parikshit Acharya ,
- Lasitha Piyathilaka ,
- sarath kodagoda
Abstract
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