Hashiba, “Carbon Equivalent to Assess Hardenability of Steel and Prediction of HAZ Hardness Distribution,” Nippon Steel Technical, 2007.į. Sente Software Ltd, Surrey Research Park. Prasanna Kumar, Comparison of Austenite Decomposition Models During Finite Element Simulation of Water Quenching and Air Cooling of AISI 4140 Steel, Metall. Gür, 3D FEM Simulation of Steel Quenching and Investigation of the Effect of Asymmetric Geometry on Residual Stress Distribution, J. Gür, A FEM Based Framework for Simulation of Thermal Treatments: Application to Steel Quenching, Comput. Moosavi Nezhad, Prediction of Hardness at Different Points of Jominy Specimen Using Quench Factor Analysis Method, J. Narayan Prabhu, Effect of Bath Temperature on Cooling Performance of Molten Eutectic NaNO3-KNO3 Quench Medium for Martempering of Steels, Metall. Tensi, Prediction of Hardness Profile in Workpiece Based on Characteristic Cooling Parameters and Material Behaviour During Cooling, Quenching Theory and Technology, 2nd ed., B. Prabhu, Assessment of Wetting Kinematics and Cooling Performance of Select Vegetable Oils and Mineral-Vegetable Oil Blend Quench Media, Mater.

Tomašić, Computer Simulation of Mechanical Properties of Quenched and Tempered Steel Specimen, J. Smoljan, Prediction of Quench-Hardness within the Whole Volume of Axially Symmetric Workpieces of Any Shape, J. Clinton Eds., Handbook of Quenchants and Quenching Technology, ASM International, Berlin, 1993ĪSM International, ASM Handbook, vol 4: Heat Treating. The weights of the ANN model were used to calculate the relative importance of all input variables and they followed a decreasing order of T b>D>t r>h. 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.

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 relationship between hardness distribution and the aforementioned process variables was highly nonlinear. Apart from the diameter (D), the effect of other process variables such as heat transfer coefficient (h), bath temperature (T b), and residence time (t r) was also studied. A numerical experiment to predict hardness distribution in AISI 4140 steel cylinders of various diameters during martempering is presented in this work. Martempering is a widely practiced industrial heat treatment process to harden steel parts with minimum distortion.

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