Neural Network Modeling of Oxidation Kinetics in Air of Steel- T21 Alloy Coated by Simultaneous Germanium-Doped Aluminizing-Siliconzing Process
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چکیده
In this work a pack cementation of germanium-doped aluminum and silicon coatings on low alloy steel type-T21 has been applied. This gives significant improvement in the oxidation. Steel-T21 was coated with germanium-doped aluminizing-siliconizing. Diffusion coating was carried out at 1050C for 6 h under an Ar atmosphere by simultaneous germanium-doped aluminizing-siliconzing process. Cyclic oxidation tests were conducted on the coated steel-T21 alloy in the temperature range oxide 300-900C in air for 102 h at 3 h cycle. The results showed that the oxidation kinetics for coated system in air can be represented by parabolic curve .Oxide phases that formed on coated system are SiO2 and Cr2O3. A neural network model of oxidation kinetics has been proposed to model the oxidation kinetic. The neural model shows good agreement with the experimental data.
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