Machine Learning–Assisted Risk Assessment of Pitting Corrosion Susceptibility of AA1050 in Ethanol‐Containing Fuels

The ability to assess the risk of corrosion of metallic structures in particular environments holds considerable significance in the field of automotive industry. In recent years, machine learning has evolved into a crucial tool to evaluate the complex and multidimensional corrosion phenomena. In th...

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Veröffentlicht in:	Materials and corrosion 2024-10
Hauptverfasser:	Jarren, Lukas C., Gazenbiller, Eugen, Arya, Visheet, Reitz, Rüdiger, Oechsner, Matthias, Feiler, Christian, Zheludkevich, Mikhail L., Höche, Daniel
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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