Mechanistic Insights Regarding the Role of Skin Effect in Pulsed Current Cathodic Protection: Experimental Studies, ML Modeling, and Multi-objective Optimization.
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| Title: | Mechanistic Insights Regarding the Role of Skin Effect in Pulsed Current Cathodic Protection: Experimental Studies, ML Modeling, and Multi-objective Optimization. |
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| Authors: | Hashemi, Babak1 (AUTHOR) hashemib@shirazu.ac.ir |
| Source: | Journal of Materials Engineering & Performance. Apr2026, Vol. 35 Issue 16, p16052-16077. 26p. |
| Subjects: | Skin effect, Cathodic protection, Corrosion inhibitors, Multi-objective optimization, Underground pipelines, Machine learning, Surface morphology |
| Abstract: | This study investigates the influence of waveform design on the performance of pulsed current cathodic protection (PCCP) under soil-simulating conditions relevant to buried pipelines and oil well casings. Square, exponential rise, exponential fall, and ramp waveforms were experimentally evaluated in terms of potential distribution, current consumption, surface deposit morphology, and pitting behavior. The results show that the ramp waveform consistently outperforms other modes by inducing the strongest skin effect, minimizing concentration polarization, and ensuring the most uniform potential distribution along the protected surface. Complementary adaptive neuro-fuzzy inference system (ANFIS) modeling was employed to establish predictive relationships among waveform, frequency, time, rectifier voltage, and distance from the drain point with pipe-to-soil potential and protective current. The trained models achieved high accuracy (Pearson correlation coefficients ≥ 0.97) and enabled multi-objective optimization of operating frequency, with an optimum around 4.8 kHz for the ramp waveform. SEM and XRD analyses further revealed that the ramp waveform promotes layer-by-layer (Frank–van der Merwe) deposit growth, correlating with superior resistance to pitting corrosion, whereas the square waveform fosters rough island-type deposits prone to localized attack. Overall, this work highlights waveform engineering as a decisive factor in PCCP efficiency and demonstrates that coupling experimental insights with machine learning provides a powerful framework for optimizing corrosion protection strategies in buried steel structures. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Materials Engineering & Performance is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 193366997 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Mechanistic Insights Regarding the Role of Skin Effect in Pulsed Current Cathodic Protection: Experimental Studies, ML Modeling, and Multi-objective Optimization. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hashemi%2C+Babak%22">Hashemi, Babak</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hashemib@shirazu.ac.ir</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Materials+Engineering+%26+Performance%22">Journal of Materials Engineering & Performance</searchLink>. Apr2026, Vol. 35 Issue 16, p16052-16077. 26p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Skin+effect%22">Skin effect</searchLink><br /><searchLink fieldCode="DE" term="%22Cathodic+protection%22">Cathodic protection</searchLink><br /><searchLink fieldCode="DE" term="%22Corrosion+inhibitors%22">Corrosion inhibitors</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Underground+pipelines%22">Underground pipelines</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Surface+morphology%22">Surface morphology</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study investigates the influence of waveform design on the performance of pulsed current cathodic protection (PCCP) under soil-simulating conditions relevant to buried pipelines and oil well casings. Square, exponential rise, exponential fall, and ramp waveforms were experimentally evaluated in terms of potential distribution, current consumption, surface deposit morphology, and pitting behavior. The results show that the ramp waveform consistently outperforms other modes by inducing the strongest skin effect, minimizing concentration polarization, and ensuring the most uniform potential distribution along the protected surface. Complementary adaptive neuro-fuzzy inference system (ANFIS) modeling was employed to establish predictive relationships among waveform, frequency, time, rectifier voltage, and distance from the drain point with pipe-to-soil potential and protective current. The trained models achieved high accuracy (Pearson correlation coefficients ≥ 0.97) and enabled multi-objective optimization of operating frequency, with an optimum around 4.8 kHz for the ramp waveform. SEM and XRD analyses further revealed that the ramp waveform promotes layer-by-layer (Frank–van der Merwe) deposit growth, correlating with superior resistance to pitting corrosion, whereas the square waveform fosters rough island-type deposits prone to localized attack. Overall, this work highlights waveform engineering as a decisive factor in PCCP efficiency and demonstrates that coupling experimental insights with machine learning provides a powerful framework for optimizing corrosion protection strategies in buried steel structures. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Materials Engineering & Performance is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11665-025-12787-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 16052 Subjects: – SubjectFull: Skin effect Type: general – SubjectFull: Cathodic protection Type: general – SubjectFull: Corrosion inhibitors Type: general – SubjectFull: Multi-objective optimization Type: general – SubjectFull: Underground pipelines Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Surface morphology Type: general Titles: – TitleFull: Mechanistic Insights Regarding the Role of Skin Effect in Pulsed Current Cathodic Protection: Experimental Studies, ML Modeling, and Multi-objective Optimization. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hashemi, Babak IsPartOfRelationships: – BibEntity: Dates: – D: 27 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 10599495 Numbering: – Type: volume Value: 35 – Type: issue Value: 16 Titles: – TitleFull: Journal of Materials Engineering & Performance Type: main |
| ResultId | 1 |
