An energy-relaxation-based framework for the modelling of magnetic shape memory alloys-Simulation of key response features under homogeneous loading conditions
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作者:
Bartel, Thorsten
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TU Dortmund, Inst Mech, Leonhard Euler St 5, D-44227 Dortmund, GermanyTU Dortmund, Inst Mech, Leonhard Euler St 5, D-44227 Dortmund, Germany
In this contribution we present a constitutive modelling framework for magnetic shape memory alloys (MSMA) that builds on a global variational principle. The approach relies on concepts of energy relaxation and generalised notions of convexity to compute effective energy hulls to the non-convex energy landscape associated with the underlying multi-phase solid, from which the prediction of microstructure evolution results. In this sense it fundamentally distinguishes itself from MSMA models that essentially follow phenomenological concepts of classical plasticity (Kiefer and Lagoudas, 2005; 2009). The microstructure is not spatially resolved, but micro-scale quantities are taken into account in an effective sense by additional state variables-such as volume fractions or interface orientations-and appropriate mixture rules. The model allows all mechanisms central to MSMA behaviour-i.e. variant switching, magnetisation rotation away from easy axes, and magnetic domain evolution-to occur simultaneously. The authors have previously been able to demonstrate that such a modelling approach can quantitatively capture the key characteristics of single-crystalline MSMA response under standard loading scenarios (Kiefer et al., 2015). The modelling framework presented here is now further able to predict much more general response features, such as variant switching diagrams, magnetic field-biased pseudo-elasticity and the influence of specimen shape anisotropy. Moreover, the global variational framework is formulated in a manner that lends itself to finite element implementation. In this work, however, numerical examples are considered in which the nonlocal nature of the demagnetisation field is taken into account in an approximate sense through appropriate shape factors. (C) 2019 Elsevier Ltd. All rights reserved.
机构:
Institute of Applied Mechanics, Russian Academy of Sciences, Leninskii pr. 32a, MoscowInstitute of Applied Mechanics, Russian Academy of Sciences, Leninskii pr. 32a, Moscow
Movchan A.A.
Kazarina S.A.
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Institute of Applied Mechanics, Russian Academy of Sciences, Leninskii pr. 32a, MoscowInstitute of Applied Mechanics, Russian Academy of Sciences, Leninskii pr. 32a, Moscow