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Non-destructive electromagnetic sensing technique to determine the level of chloride ions in reinforced concrete structures

Omer, G (2021) Non-destructive electromagnetic sensing technique to determine the level of chloride ions in reinforced concrete structures. Doctoral thesis, Liverpool John Moores University.

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Abstract

Corrosion of the reinforcing steel arising from contamination by chloride ions from de-icing salt is the primary cause of deterioration of concrete bridges in the UK and many parts of the world. Those elements of structures exposed to cyclic wetting and drying have already proven the most vulnerable to corrosion damage. Chloride ions penetrate the concrete, resulting in deterioration (cracking, spalling due to reinforcement corrosion). Currently, the existing methods such as Ion-Selective Electrode (ISE), Electrical Resistivity, and Optical Fibre Sensor to detect the chloride level in marine concrete structures are destructive, time-consuming, and unable to analyse large structures. This investigation aims to use a non-destructive electromagnetic (EM) wave technique to determine the chloride level in maritime concrete structures early to prevent the corrosion of the reinforcement developing. An experimental programme was conducted to understand better the effect of different saltwater concentrations in concrete samples. The described Electromagnetic (EM) wave sensor operates at the frequency range between 2-13 GHz and a power of 0dBm using a Rohde Schwarz ZVL13 Vector Network Analyser (VNA). The sensor was positioned in front of the concrete specimens to determine chloride ions in the substantial sample. Finally, the graphical interface package LabVIEW was used to control the sensor's frequency sweep and capture the data from the sensor. The experimental data obtained was analysed by the WEKA workbench tool to classify the most critical frequency point to detect the level of chloride ions in concrete. The input parameter was S21 measurements of one single frequency that has been selected by the classification algorithm decision tree (J48). After selecting the most critical frequency point, the Artificial Neural Network (ANN) models were trained by electromagnetic (EM) waves and chloride profile experiments. The outcome results demonstrated that electromagnetic waves have a response to saltwater concentrations. Therefore, the validation model was developed using the ANN method, which exhibited an excellent capability of the microwave sensors to validate the percentage of chloride ions per weight of cement with R2v (Validation) =0.986709 and root mean square error of validation (RMSEV)=0.000120.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: Chloride Attack; Concrete Structure; Electromagnetic Waves; Horn Antenna; Non-destructive testing; ANN technique; WEKA Classification technique.
Subjects: T Technology > TG Bridge engineering
T Technology > TP Chemical technology
Divisions: Civil Engineering & Built Environment
Date Deposited: 04 Jan 2022 15:12
Last Modified: 04 Jan 2022 15:12
Supervisors: Riley, M, Kot, P and Atherton, W
URI: https://researchonline.ljmu.ac.uk/id/eprint/15927

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