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Three-dimensional dislocation networks control the mechanical properties such as strain hardening of crystals. Due to the complexity of dislocation networks and their temporal evolution, analysis tools are needed that fully resolve the dynamic processes of the intrinsic dislocation graph structure. We propose the use of a graph database for the analysis of three-dimensional dislocation networks obtained from discrete dislocation dynamics simulations. This makes it possible to extract (sub-)graphs and their features with relative ease. That allows for a more holistic view of the evolution of dislocation networks and for the extraction of homogenized graph features to be incorporated into continuum formulation. As an illustration, we describe the static and dynamic analysis of spatio-temporal dislocation graphs as well as graph feature analysis.

Over the past decades, discrete dislocation dynamics simulations have been shown to reliably predict the evolution of dislocation microstructures for micrometer-sized metallic samples. Such simulations provide insight into the governing deformation mechanisms and the interplay between different physical phenomena such as dislocation reactions or cross-slip. This work is focused on a detailed analysis of the influence of the cross-slip on the evolution of dislocation systems. A tailored data mining strategy using the ``\ab*{discrete-to-continuous} framework'' allows to quantify differences and to quantitatively compare dislocation structures. We analyze the quantitative effects of the cross-slip on the microstructure in the course of a tensile test and a subsequent relaxation to present the role of cross-slip in the microstructure evolution. The precision of the extracted quantitative information using D2C strongly depends on the resolution of the domain averaging. We also analyze how the resolution of the averaging influences the distribution of total dislocation density and curvature fields of the specimen. Our analyzes are important approaches for interpreting the resulting structures calculated by dislocation dynamics simulations.

During the plastic deformation of crystalline materials, 3d dislocation networks form based on dislocation junctions. Particularly, immobile Lomer junctions are essential for the stability of dislocation networks. However, the formed Lomer junctions can unzip and dissolve again, if the linked mobile dislocations of the Lomer junction - the Lomer arms - experience sufficiently high resolved shear stresses. To generate a better understanding of the dislocation network stability and to pave the way to a general stability criterion of dislocation networks, we investigate the Lomer arm length distribution in dislocation networks by analyzing discrete dislocation dynamics simulation data of tensile-tested aluminum single crystals. We show that an exponential distribution fits best to the Lomer arm length distribution in the systems considered, which is independent of the crystal orientation. The influence of the slip system activity on the Lomer arm length distribution is discussed.

Plastic deformation of metals involves the complex evolution of dislocations forming strongly connected dislocation networks. These dislocation networks are based on dislocation reactions, which can form junctions during the interactions of different slip systems. Extracting the fundamentals of the network behaviour during plastic deformation by adequate physically based theories is essential for crystal plasticity models. In this work, we demonstrate how knowledge from discrete dislocation dynamics simulations to continuum-based formulations can be transferred by applying a physically based dislocation network evolution theory. By using data-driven methods, we validate a slip system dependent rate formulation of network evolution. We analyze different discrete dislocation dynamics simulation data sets of face-centred cubic single-crystals in high symmetric and non-high symmetric orientations under uniaxial tensile loading. Here, we focus on the reaction evolution during stage II plastic deformation. Our physically based model for network evolution depends on the plastic shear rate and the dislocation travel distance described by the dislocation density. We reveal a dependence of the reaction kinetics on the crystal orientation and the activity of the interacting slip systems, which can be described by the Schmid factor. It has been found, that the generation of new reaction density is mainly driven by active slip systems. However, the deposition of generated reaction density is not necessarily dependent on the slip system activity of the considered slip system, i.e. we observe a deposition of reaction density on inactive slip systems especially for glissile and coplanar reactions., Comment: Accepted manuscript in the Journal of Mechanics and Physics of Solids (JMPS)