Chloride detection in concrete using wireless fidelity (Wi-Fi) signal
Corrosion is causing the gradual deterioration of a significant quantity of existing structures in many nations around the world. In reinforced concrete structures (RCS), chloride corrosion occurs more rapidly than carbonation corrosion. When affected, RCS must go through a repair or retrofitting pr...
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Springer Science and Business Media Deutschland GmbH
2025
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| author | Paul S.C. Al Mamun F. Hasan N.M.S. Shaun F.J. Kong S.Y. Wong L.S. Babafemi A.J. |
| author2 | 58975844300 |
| author_facet | 58975844300 Paul S.C. Al Mamun F. Hasan N.M.S. Shaun F.J. Kong S.Y. Wong L.S. Babafemi A.J. |
| author_sort | Paul S.C. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Corrosion is causing the gradual deterioration of a significant quantity of existing structures in many nations around the world. In reinforced concrete structures (RCS), chloride corrosion occurs more rapidly than carbonation corrosion. When affected, RCS must go through a repair or retrofitting process for further functioning. Therefore, early detection of corrosion attacks can save both the cost of repair and the expected/remaining service life of the structure. It is feasible to assess whether the structures are already corroding by measuring the level of chloride. This study reports a non-destructive method for detecting the chloride in concrete by using wireless fidelity (Wi-Fi) signal. A setup is developed with two Wi-Fi adapters and Wi-Fi analyzer software to detect the various amounts of chloride in concrete samples by means of attenuation (dB). Three different grades and thicknesses of concrete samples were prepared with known NaCl percentages of 0%, 5%, 10%, and 15%, and their attenuation values obtained by Wi-Fi signals were analyzed. An artificial neural network is employed to predict the actual NaCl with the model or predicted NaCl data. The result illustrated a measurable influence of the concrete grades, sample thickness, and percentages of NaCl on the attenuation values. Electrical resistivity, water absorption, and microstructures of the samples were investigated and correlated with the attenuation values. Successful use of this non-destructive technique can have a significant contribution in assessing the durability of many existing RCS. ? Springer Nature Switzerland AG 2024. |
| format | Article |
| id | my.uniten.dspace-36738 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Springer Science and Business Media Deutschland GmbH |
| record_format | dspace |
| spelling | my.uniten.dspace-367382025-03-03T15:44:18Z Chloride detection in concrete using wireless fidelity (Wi-Fi) signal Paul S.C. Al Mamun F. Hasan N.M.S. Shaun F.J. Kong S.Y. Wong L.S. Babafemi A.J. 58975844300 58891190300 57208346987 57192666570 57208875766 55504782500 55948535200 Corrosion is causing the gradual deterioration of a significant quantity of existing structures in many nations around the world. In reinforced concrete structures (RCS), chloride corrosion occurs more rapidly than carbonation corrosion. When affected, RCS must go through a repair or retrofitting process for further functioning. Therefore, early detection of corrosion attacks can save both the cost of repair and the expected/remaining service life of the structure. It is feasible to assess whether the structures are already corroding by measuring the level of chloride. This study reports a non-destructive method for detecting the chloride in concrete by using wireless fidelity (Wi-Fi) signal. A setup is developed with two Wi-Fi adapters and Wi-Fi analyzer software to detect the various amounts of chloride in concrete samples by means of attenuation (dB). Three different grades and thicknesses of concrete samples were prepared with known NaCl percentages of 0%, 5%, 10%, and 15%, and their attenuation values obtained by Wi-Fi signals were analyzed. An artificial neural network is employed to predict the actual NaCl with the model or predicted NaCl data. The result illustrated a measurable influence of the concrete grades, sample thickness, and percentages of NaCl on the attenuation values. Electrical resistivity, water absorption, and microstructures of the samples were investigated and correlated with the attenuation values. Successful use of this non-destructive technique can have a significant contribution in assessing the durability of many existing RCS. ? Springer Nature Switzerland AG 2024. Final 2025-03-03T07:44:18Z 2025-03-03T07:44:18Z 2024 Article 10.1007/s41062-024-01378-9 2-s2.0-85185253910 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185253910&doi=10.1007%2fs41062-024-01378-9&partnerID=40&md5=879b3215dcfe4080534c48bca3c020dc https://irepository.uniten.edu.my/handle/123456789/36738 9 3 60 Springer Science and Business Media Deutschland GmbH Scopus |
| spellingShingle | Paul S.C. Al Mamun F. Hasan N.M.S. Shaun F.J. Kong S.Y. Wong L.S. Babafemi A.J. Chloride detection in concrete using wireless fidelity (Wi-Fi) signal |
| title | Chloride detection in concrete using wireless fidelity (Wi-Fi) signal |
| title_full | Chloride detection in concrete using wireless fidelity (Wi-Fi) signal |
| title_fullStr | Chloride detection in concrete using wireless fidelity (Wi-Fi) signal |
| title_full_unstemmed | Chloride detection in concrete using wireless fidelity (Wi-Fi) signal |
| title_short | Chloride detection in concrete using wireless fidelity (Wi-Fi) signal |
| title_sort | chloride detection in concrete using wireless fidelity (wi-fi) signal |
| url_provider | http://dspace.uniten.edu.my/ |