Artificial Neural Networks for the Prediction of Electrochemical Etched Micro channel Dimensions

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dc.contributor.authorBaydır, Enver
dc.contributor.authorAras, Ömür
dc.date.accessioned2026-02-08T15:03:09Z
dc.date.available2026-02-08T15:03:09Z
dc.date.issued2022
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractIn this study, artificial neural network was used to model the micro channel size created with electrochemical etching method in a specific pattern. Special series 5754 aluminum surfaces were coated with employing mask. The pre-designed pattern was then marked to the masked surface with laser, then it was subjected to electrochemical etching process. In this way, micro-patterned channels are formed on the aluminum surface. Various experiments were carried out based on the electrochemical etching parameters, such as concentration (0.1-2.5 M), distance between the electrodes (5-15 cm), operating voltage (15-48 V) and time (6-30 min). And the depth and width of the channels were investigated. Studies conducted under various conditions were modeled with ANN and the synergistic effects of the input and output parameters were explored by the surface graphics obtained as a result of the modeling. This modeling study is a powerful tool in terms of providing a prediction of the channel dimensions of the micro channel fabricated by electrochemical etching for the future related studies. In addition to the modeling, some impressions and inferences obtained from the experiments were also yielded in the conclusion part.
dc.description.abstractIn this study, artificial neural network was used to model the micro channel size created with electrochemical etching method in a specific pattern. Special series 5754 aluminum surfaces were coated with employing mask. The pre-designed pattern was then marked to the masked surface with laser, then it was subjected to electrochemical etching process. In this way, micro-patterned channels are formed on the aluminum surface. Various experiments were carried out based on the electrochemical etching parameters, such as concentration (0.1-2.5 M), distance between the electrodes (5-15 cm), operating voltage (15-48 V) and time (6-30 min). And the depth and width of the channels were investigated. Studies conducted under various conditions were modeled with ANN and the synergistic effects of the input and output parameters were explored by the surface graphics obtained as a result of the modeling. This modeling study is a powerful tool in terms of providing a prediction of the channel dimensions of the micro channel fabricated by electrochemical etching for the future related studies. In addition to the modeling, some impressions and inferences obtained from the experiments were also yielded in the conclusion part.
dc.identifier.doi10.31202/ecjse.1081161
dc.identifier.endpage1120
dc.identifier.issn2148-3736
dc.identifier.issn2148-3736
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85139764451
dc.identifier.scopusqualityN/A
dc.identifier.startpage1112
dc.identifier.urihttps://doi.org/10.31202/ecjse.1081161
dc.identifier.urihttps://hdl.handle.net/20.500.12885/3884
dc.identifier.volume9
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTayfun UYGUNOĞLU
dc.relation.ispartofEl-Cezeri
dc.relation.ispartofEl-Cezeri
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20260207
dc.subjectEngineering
dc.subjectMühendislik
dc.titleArtificial Neural Networks for the Prediction of Electrochemical Etched Micro channel Dimensions
dc.title.alternativeArtificial Neural Networks for the Prediction of Electrochemical Etched Micro channel Dimensions
dc.typeArticle

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