Numerical analysis on corrosion resistance of mild steel structures

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dc.contributor.authorErdem R.T.
dc.contributor.authorSeker S.
dc.contributor.authorOzturk A.U.
dc.contributor.authorGucuyen E.
dc.date.accessioned2024-07-22T08:18:05Z
dc.date.available2024-07-22T08:18:05Z
dc.date.issued2013
dc.description.abstractCorrosion resistances of mild steel specimens according to artificial neural network (ANN) analysis were investigated in the scope of this study. Corrosion rate values were taken into numerical analysis as a result of experimental studies under corrosive aggressive media. Mild steel specimens were selected according to the section type varieties such as box, tube and cornier. All steel specimens were subjected to the aggressive media formed using sodium chloride (NaCl with 99.8 % purity) solutions with 3.5, 5.0 and 7.0 % ratios per one liter distilled water and only distilled water. The reduction in corrosion rate has been observed and considered according to some corrosion loss respects. Corrosion rate prediction models were established between corrosion rate and parameters such as mass loss obtained by experimental studies using ANN. ANNs are computing systems that simulate the biological neural systems of the human brain. In this study, ANN analysis was generated to predict the corrosion rate values after experimental studies. Experimental and predicted values were compared by each other and it is seen that a strong relationship was established between them. © 2012 Springer-Verlag London Limited.
dc.identifier.DOI-ID10.1007/s00366-012-0279-5
dc.identifier.issn14355663
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/17177
dc.language.isoEnglish
dc.subjectCarbon steel
dc.subjectCorrosion rate
dc.subjectMaterials science
dc.subjectNeural networks
dc.subjectNumerical analysis
dc.subjectSodium chloride
dc.subjectSoft computing
dc.subjectSteel research
dc.subjectStructure (composition)
dc.subjectAggressive media
dc.subjectBiological neural systems
dc.subjectComputing system
dc.subjectCorrosion loss
dc.subjectDistilled water
dc.subjectRate predictions
dc.subjectSection types
dc.subjectSteel specimens
dc.subjectCorrosion resistance
dc.titleNumerical analysis on corrosion resistance of mild steel structures
dc.typeArticle

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