An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System
Corrosion resistance coating is fabricated using epoxy/glass flake (E/GF) composites and is utilized to prolong the lifespan of cold-rolled steel (CRS) metal substrates. An in situ synthesis approach was adopted to prepare the composite coating at different levels of synthesis parameters, including...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/12/3/392 |
| _version_ | 1827627790583726080 |
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| author | Hesham Alhumade Hegazy Rezk |
| author_facet | Hesham Alhumade Hegazy Rezk |
| author_sort | Hesham Alhumade |
| collection | DOAJ |
| description | Corrosion resistance coating is fabricated using epoxy/glass flake (E/GF) composites and is utilized to prolong the lifespan of cold-rolled steel (CRS) metal substrates. An in situ synthesis approach was adopted to prepare the composite coating at different levels of synthesis parameters, including a load of filler and coating thickness. In addition, this work shows the effects of the chemical functionalization of the filler on the corrosion protection property of the epoxy/functional glass flake (E/FGF) composite coatings. The effects of the modification of the filler, as well as the other synthesis parameters, on the corrosion resistance property are evaluated using a potentiodynamic polarization technique. Here, the corrosion resistance property is evaluated based on the observed current density. The primary goal of this work is to present an accurate model of corrosion current density (CCD). By using measured data, a precise model, which simulates the corrosion resistance properties of the coatings, has been created by an adaptive network-based fuzzy inference system (ANFIS) in terms of glass flake loading, chemical functionalization, and coating thickness. The obtained results revealed good agreement between ANFIS-based modelling and the measured dataset. The root mean square errors of the prediction model were 8.1391 × 10<sup>−8</sup> and 0.0104 for training and testing, respectively. The coefficient of determination (<i>R</i><sup>2</sup>) values of the ANFIS output were found to be 1.0 and 0.9997 for training and testing, respectively. To prove the superiority of the ANFIS-based model of CCD, the achieved results were compared with an analysis of variance (ANOVA). ANOVA utilizes a linear regression approach to get the model. Thanks to ANFIS, compared with ANOVA, the values of <i>R</i><sup>2</sup> are increased by 10% and 18.6% for the training and testing phases, respectively. Finally, the accuracy of the ANFIS model of corrosion current density is validated experimentally. |
| first_indexed | 2024-03-09T13:20:50Z |
| format | Article |
| id | doaj.art-d89ca4f31e41402487aa130096b51d1f |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-09T13:20:50Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-d89ca4f31e41402487aa130096b51d1f2023-11-30T21:30:31ZengMDPI AGMetals2075-47012022-02-0112339210.3390/met12030392An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference SystemHesham Alhumade0Hegazy Rezk1K.A. CARE Energy Research and Innovation Center, King Abdulaziz University, Jeddah 21589, Saudi ArabiaCollege of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 11911, Saudi ArabiaCorrosion resistance coating is fabricated using epoxy/glass flake (E/GF) composites and is utilized to prolong the lifespan of cold-rolled steel (CRS) metal substrates. An in situ synthesis approach was adopted to prepare the composite coating at different levels of synthesis parameters, including a load of filler and coating thickness. In addition, this work shows the effects of the chemical functionalization of the filler on the corrosion protection property of the epoxy/functional glass flake (E/FGF) composite coatings. The effects of the modification of the filler, as well as the other synthesis parameters, on the corrosion resistance property are evaluated using a potentiodynamic polarization technique. Here, the corrosion resistance property is evaluated based on the observed current density. The primary goal of this work is to present an accurate model of corrosion current density (CCD). By using measured data, a precise model, which simulates the corrosion resistance properties of the coatings, has been created by an adaptive network-based fuzzy inference system (ANFIS) in terms of glass flake loading, chemical functionalization, and coating thickness. The obtained results revealed good agreement between ANFIS-based modelling and the measured dataset. The root mean square errors of the prediction model were 8.1391 × 10<sup>−8</sup> and 0.0104 for training and testing, respectively. The coefficient of determination (<i>R</i><sup>2</sup>) values of the ANFIS output were found to be 1.0 and 0.9997 for training and testing, respectively. To prove the superiority of the ANFIS-based model of CCD, the achieved results were compared with an analysis of variance (ANOVA). ANOVA utilizes a linear regression approach to get the model. Thanks to ANFIS, compared with ANOVA, the values of <i>R</i><sup>2</sup> are increased by 10% and 18.6% for the training and testing phases, respectively. Finally, the accuracy of the ANFIS model of corrosion current density is validated experimentally.https://www.mdpi.com/2075-4701/12/3/392coatingscorrosionANFIS modellingANOVA |
| spellingShingle | Hesham Alhumade Hegazy Rezk An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System Metals coatings corrosion ANFIS modelling ANOVA |
| title | An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System |
| title_full | An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System |
| title_fullStr | An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System |
| title_full_unstemmed | An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System |
| title_short | An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System |
| title_sort | accurate model of the corrosion current density of coatings using an adaptive network based fuzzy inference system |
| topic | coatings corrosion ANFIS modelling ANOVA |
| url | https://www.mdpi.com/2075-4701/12/3/392 |
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