Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/15690
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dc.contributor.authorRao K.M.P.
dc.contributor.authorPrabhu K.N.
dc.date.accessioned2021-05-05T10:27:42Z-
dc.date.available2021-05-05T10:27:42Z-
dc.date.issued2021
dc.identifier.citationJournal of Materials Engineering and Performance Vol. , , p. -en_US
dc.identifier.urihttps://doi.org/10.1007/s11665-021-05630-6
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/15690-
dc.description.abstractMartempering is a widely practiced industrial heat treatment process to harden steel parts with minimum distortion. A numerical experiment to predict hardness distribution in AISI 4140 steel cylinders of various diameters during martempering is presented in this work. Apart from the diameter (D), the effect of other process variables such as heat transfer coefficient (h), bath temperature (Tb), and residence time (tr) was also studied. The relationship between hardness distribution and the aforementioned process variables was highly nonlinear. An artificial neural network (ANN) model with a single hidden layer and 30 hidden layer neurons was thus developed to predict the hardness distribution in martempered AISI 4140 steel cylinders. The increase in bath temperature, diameter, and residence time decreased the average hardness, and an increase in the heat transfer coefficient increased the average hardness of martempered AISI 4140 cylinders. The weights of the ANN model were used to calculate the relative importance of all input variables and they followed a decreasing order of Tb>D>tr>h. © 2021, ASM International.en_US
dc.titleNumerical Simulation to Predict the Effect of Process Parameters on Hardness during Martempering of AISI4140 Steelen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

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