Modeling mechanical properties of low carbon hot rolled steels

Reddy, N S and Panigrahi, Bharat Bhooshan and Krishnaiah, J (2013) Modeling mechanical properties of low carbon hot rolled steels. In: 7th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2012, 14-16, December 2012, Gwalior, Madhya Pradesh; India.

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Steel is the most important material and it has several applications, and positions second to cement in its consumption in the world. The mechanical properties of steels are very important and vary significantly due to heat treatment, mechanical treatment, processing and alloying elements. The relationships between these parameters are complex, and nonlinear in nature. An artificial neural networks (ANN) model has been used for the prediction of mechanical properties of low alloy steels. The input parameters of the model consist of alloy composition (Al, Al soluble, C, Cr, Cu, Mn, Mo, Nb, Ni, P, S, Si, Ti, V and Nitrogen in ppm) and process parameters (coil target temperature, finish rolling temperature) and the outputs are ultimate tensile strength, yield strength, and percentage elongation. The model can be used to calculate properties of low alloy steels as a function of alloy composition and process parameters at new instances. The influence of inputs on properties of steels is simulated using the model. The results are in agreement with existing experimental knowledge. The developed model can be used as a guide for further alloy development

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IITH Creators:
IITH CreatorsORCiD
Panigrahi, Bharat BhooshanUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Artificial neural networks; Low carbon steels; Mechanical properties; Process parameters
Subjects: Materials Engineering > Materials engineering
Divisions: Department of Material Science Engineering
Depositing User: Team Library
Date Deposited: 27 Nov 2014 10:00
Last Modified: 10 Nov 2017 06:31
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