Modeling of microstructure and mechanical properties of heat treated components by using Artificial Neural Network
作者： Amit Powar , Prashant Date
DOI: 10.1016/J.MSEA.2015.01.044
关键词:
摘要: Abstract The main objective of the present work is to develop a methodology predict mechanical properties and microstructure heat treated components, for given composition treatment process by using Artificial Neural Network׳s (ANN) advanced thermal modeling tool FLUENT. A rotor shaft made 30CrMoNiV5-11 steel was temperature profile has been measured inserting thermocouples at different locations on shaft. Based obtained subsequent shaft, transfer coefficient optimized. optimized then used determine distribution in locations. profiles from were applied coupons steel. dataset Network generated studying microstructural parameters these metallography testing, respectively. training done with this experimentally dataset. input alloy composition, hardness. outputs yield strength, ultimate tensile elongation, reduction area volume fraction pearlite, bainite ferrite. graphical user interface (GUI) also developed easy use model. correlation (R) over 90% behavior Moreover, variation analyzed results found be good agreement theoretical results.
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