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PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY
Edited by: B.H.V. Topping and M. Papadrakakis
Macro Modeling and Homogenization for Identification of Material Parameters to Simulate Phase Transformations
R. Mahnken1, A. Schneidt1 and T. Andretter2
1Chair of Engineering Mechanics, University of Paderborn, Germany
R. Mahnken, A. Schneidt, T. Andretter, "Macro Modeling and Homogenization for Identification of Material Parameters to Simulate Phase Transformations", in B.H.V. Topping, M. Papadrakakis, (Editors), "Proceedings of the Ninth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 257, 2008. doi:10.4203/ccp.88.257
Keywords: plasticity, TRIP, parameter identification, homogenization.
In order to augment the functionality and the lifetime of engineering structures a new hybrid transforming process is described in . During the combination of mechanical shaping and heat treatment the material experiences phase changes of a different kind. In our work we concentrate on the austenite to martensite phase change.
To calibrate a set of macroscopic constitutive equations the experimental database  is used, thus taking into account the effects of uniaxial stress on the kinetics of phase transformation at different temperatures. However, for the case of temperatures below the martensite start temperature with simultaneous stresses above the yield limit, it is difficult to obtain experimental data. Therefore, as a remedy we employ a homogenization technique by using a representative volume element. In this way the flow behavior of the macroscopic mixed material is characterized by use of a cubic finite-element-model. Here the macroscopic material within each element represents one grain which is able to change its material properties from austenite to martensite and vice versa. The resulting data basis - for stresses above and below the yield stress, above and below the martensitic start temperature - is used for parameter identification of a macroscopic constitutive model by least squares minimization.
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