Microstructure characterization and reconstruction (MCR) is an important prerequisite for empowering and accelerating integrated computational materials engineering. Much progress has been made in MCR recently; however, in the absence of a flexible software platform it is difficult to use ideas from other researchers and to develop them further. To address this issue, this work presents MCRpyas an easy-to-use, extensible and flexible open-source MCR software platform.MCRpycan be used as a program with graphical user interface, as a command line tool and as a Python library. The central idea is that microstructure reconstruction is formulated as a modular and extensible optimization problem. In this way, arbitrary descriptors can be used for characterization and arbitrary loss functions combining arbitrary descriptors can be minimized using arbitrary optimizers for reconstructing random heterogeneous media. With stochastic optimizers, this leads to variations of the well-known Yeong–Torquato algorithm. Furthermore,MCRpyfeatures automatic differentiation, enabling the utilization of gradient-based optimizers. In this work, after a brief introduction to the underlying concepts, the capabilities ofMCRpyare demonstrated by exemplarily applying it to typical MCR tasks. Finally, it is shown how to extendMCRpyby defining a new microstructure descriptor and readily using it for reconstruction without additional implementation effort.

In the present work, the magneto-mechanical coupling in magneto-active elastomers is investigated from two different modeling perspectives: a micro-continuum and a particle–interaction approach. Since both strategies differ significantly in their basic assumptions and the resolution of the problem under investigation, they are introduced in a concise manner and their capabilities are illustrated by means of representative examples. To motivate the application of these strategies within a hybrid multiscale framework for magneto-active elastomers, their interchangeability is then examined in a systematic comparison of the model predictions with regard to the magneto-deformation of chain-like helical structures in an elastomer surrounding. The presented results show a remarkable agreement of both modeling approaches and help to provide an improved understanding of the interactions in magneto-active elastomers with chain-like microstructures.

In this contribution, we present a framework for the multiscale modeling and simulation of magneto-active elastomers (MAEs). It enables us to consider these materials on the microscopic scale, where the heterogeneous microstructure consisting of magnetizable particles and elastomer matrix is explicitly resolved, as well as the macroscopic scale, where the MAE is considered to be a homogeneous magneto-active body. On both scales, a general continuum formulation of the coupled magneto-mechanical boundary value problem is applied and the finite element method is used to solve the governing equations. Starting with an experimental characterization of the individual constituents, i.e. particles and matrix, microscopic constitutive models for both are formulated and adjusted to the experimental data separately. With that, properties of MAEs resulting from the microscopic constitutive behavior can be captured within the presented modeling approach. Secondly, to discuss general macroscopic properties of magnetically soft and hard MAEs, a computational homogenization scheme is used to calculate the composites’ effective behavior for different geometrical arrangements of the particles on the microscale. Finally, the calculated effective response of a magnetically soft composite system is used to identify the parameters of a macroscopic magneto-elastic model. Using the calibrated model, the behavior of macroscopic MAEs is simulated for different sample geometries.