A semi-analytical coupled simulation approach for induction heating

被引:0
作者
Maialen Areitioaurtena
Unai Segurajauregi
Ville Akujärvi
Martin Fisk
Iker Urresti
Eneko Ukar
机构
[1] Ikerlan Technology Research Centre,Division of Production and Materials Engineering
[2] Basque Research and Technology Alliance (BRTA),Department of Materials Science and Applied Mathematics
[3] Lund University,Division of Solid Mechanics
[4] University of Malmö,Department of Mechanical Engineering
[5] Lund University,undefined
[6] University of the Basque Country,undefined
来源
Advanced Modeling and Simulation in Engineering Sciences | / 8卷
关键词
Analytical solution; Process simulation; Rapid computation; Finite element method; 42CrMo4; Bearing;
D O I
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摘要
The numerical simulation of the induction heating process can be computationally expensive, especially if ferromagnetic materials are studied. There are several analytical models that describe the electromagnetic phenomena. However, these are very limited by the geometry of the coil and the workpiece. Thus, the usual method for computing more complex systems is to use the finite element method to solve the set of equations in the multiphysical system, but this easily becomes very time consuming. This paper deals with the problem of solving a coupled electromagnetic - thermal problem with higher computational efficiency. For this purpose, a semi-analytical modeling strategy is proposed, that is based on an initial finite element computation, followed by the use of analytical electromagnetic equations to solve the coupled electromagnetic-thermal problem. The usage of the simplified model is restricted to simple geometrical features such as flat or curved surfaces with great curvature to skin depth ratio. Numerical and experimental validation of the model show an average error between 0.9% and 4.1% in the prediction of the temperature evolution, reaching a greater accuracy than other analyzed commercial softwares. A 3D case of a double-row large size ball bearing is also presented, fully validating the proposed approach in terms of computational time and accuracy for complex industrial cases.
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