Stochastic particle models for the quantification of relationships between structural characteristics and mechanical properties to predict particle breakage behaviour

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In the proposed project we develop parametric material models that quantitatively capture dependencies between disperse structural characteristics and mechanical properties. These models depend on the material properties and generalize the property function by H. Rumpf. The aim of this approach is to estimate the material-dependent parameters that influence breakage behaviour, while the effect of process-dependent stress has to be separated. Based on these data, breakage probabilities and breakage functions are derived. Furthermore, these are implemented into a breakage module inside the software framework in order to make the results available for other projects of the SPP 1679.For systematic investigations of the effect of material properties and structural characteristics of agglomerates on their mechanical behaviour, a stochastic particle model is used to generate 3D microstructures, which are then used as input to DEM simulations. DEM simulations are performed in cooperation with the work group of Prof. Heinrich. The stochastic particle model facilitates the generation of tailored microstructures with given structural characteristics. Because as many realizations as needed can be simulated, this is an ideal tool to generate a database large enough for statistical inference. Structural segmentation of 3D image data of various agglomerates ensures that the microstructures under investigation are realistic. In the first funding period, we analyse the mechanical behaviour of agglomerates under compressive normal load. A first joint article has been submitted where the effect of the size distribution of primary particles is explored. In the second funding period, the behaviour under dynamical load will be studied and the results will be used to describe particle breakage. The parametric material models, or more precisely, the disperse properties captured in these models, are chosen accordingly. The material models for the aggregated description of solids are specified by parametric multivariate probability distributions, which are constructed based on so-called copulas. This approach allows us to capture various disperse properties simultaneously, e.g., particle size, particle shape, inner porosity, together with mechanical properties like e.g. breakage energies. Therefore, mechanical properties can be predicted by evaluating conditional distributions. The model-based description of breakage probabilities and breakage functions incorporates these results as well as the given (process-dependent) particle stress. This provides the link to the partner groups that consider particle breakage in their apparatus/process descriptions. In cooperation with the Z project, we will specify and implement a "breakage module" suitable for the software system developed in the SPP 1679.