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- W2743109997 abstract "In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic algorithm approach . The predicted optimal values for minimizing hot corrosion rate for Incoloy 800H coated by (Ce-Y-Ge) doped-aluminizing-chromizing are (3wt.%Ce, 3wt.%Y, and 3wt.%Ge) , the hot corrosion rate kp (10-12g2.cm-4.s-1) value at these conditions was found to be 71.701 . The results have been verified by confirmation experiment , results obtained by GA method match closely with experimental values (R2=98.30) . EDS and XRD results show that the formation of protective layers Al2O3 and Cr2O3 during hot corrosion tests.
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- W2743109997 created "2017-08-17" @default.
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- W2743109997 date "2015-09-01" @default.
- W2743109997 modified "2023-09-25" @default.
- W2743109997 title "Application of Box-Behnken Method Based ANN-GA to Prediction of wt.% of Doping Elements for Incoloy 800H Coated by Aluminizing-Chromizing" @default.
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- W2743109997 doi "https://doi.org/10.31026/j.eng.2015.09.09" @default.
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