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Computer Simulation of Thermal Processing of Steel
Author(s) -
Božo Smoljan,
Dario Iljkić,
Krunoslav Hajdek,
W. Sitek
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/916/1/012106
Subject(s) - residual stress , materials science , control volume , heat transfer , computer simulation , welding , microstructure , mechanical engineering , casting , mechanics , metallurgy , engineering , physics
The review of the numerical modelling of casting and welding of steel workpieces was studied. The contemporary industry needs tools to optimize and control parameters of processes by considering the favourite chemical composition of steel. In recent time, very efficient tool for optimizing and controlling of the process parameters is numerical modelling of engineering processes. At casting and welding numerical modelling is focused on optimization of distribution of microstructure contents, mechanical and physical properties distribution and tolerated distortions and residual stresses. Mechanical properties and prevention of distortion and cracking can be accomplished by prediction and control of residual stresses and microstructure distribution. The numerical modelling of thermal processing of metals consists of the research of multi-scale processes and multi-physics processes, such as phase transformations, heat transfer and mechanics of materials, and research of numerical methods for computer interpretation of the problem. By means of the numerical modelling and computer simulation of thermal processing should calculate the transient temperature field, melting and solidification processes, as well as, to calculate distribution of mechanical and physical properties and microstructure composition. In this work, the numerical models of studied thermal processes are based on the finite volume method. Values of surface heat transfer coefficient, heat capacity and heat conductivity coefficient were obtained by the inversion method. The microstructures composition has been predicted by CCT diagrams and additionally improved by the kinetic equations. The mathematical model has accomplished to solve thermal processing of 3-D axially symmetric specimens.

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