Numerical Simulation of Induction Hardening of Torsion Bar
In order to improve the fatigue performance of torsion bar, induction surface hardening is performed. The aim of the present study is to compare the experimental residual stress fields measured by X-ray diffraction with those predicted from finite element modeling of the whole induction surface hardening process. Temperature and residual stress distributions are affected by the component geometry, the material behavior and the induction treatment parameters. Based on the residual stress distribution and the fatigue loading, cracks can nucleate from the surface or below the hardened layer. Therefore, it is very important to determine the residual stress distribution and optimize the process, especially for safety critical engineering components. Results of present study show that the improvement of fatigue performance is due to development of both hard microstructure and compressive residual stress at the surface layer of torsion bar during induction hardening.
Residual stresses in surface induction hardening of steels : Comparison between experiment and simulation
Deep induction hardening has been performed on two batches of smooth cylindrical specimens with a hardening depth respectively around 2 mm and 3 mm. The distributions of axial and circumferential residual stresses are analysed for the two specimen batches by X-ray diffraction technique. The radial normal stress field is estimated through the use of the well known Moore and Evans correction. Finally, the experimental residual stresses are compared with those obtained from a multiphysic finite element modelling of the whole induction treatment process, including electromagnetic, thermal, metallurgical and mechanical phenomena. The simulated residual stress field is in good agreement with X-ray analysis especially at depths lower than one-tenth the specimen diameter. At deeper depths, a correction of the experimental X-ray analysis has been done to obtain realistic values.
Mean field model of a game for power
Abstract Our aim is to model a game for power (equivalent to total energy) as a dynamical process, where an excess of power possessed by a player allows him to gain even more power. Such a positive feedback is often termed as the Matthew effect. Analytical and numerical methods allow to identify a set of stationary states, i.e. fixed points of the model dynamics. The positions of the unstable fixed points give an insight on the basins of attraction of the stable fixed points. The results are interpreted in terms of modeling of coercive power.