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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)

Plastic deformation in microscale differs from the macroscopic plasticity in two respects: (i) the flow stress of small samples depends on their size (ii) the scatter of plasticity increases significantly. In this work we focus on the scatter of plasticity. We statistically characterize the deformation process of micropillars under tension using results from discrete dislocation dynamics (DDD) simulations. We then propose a stochastic microplasticity model which uses the extracted information from the above statistical characterization to make statistical predictions regarding the micropillar stress-strain curves. This model aims to map the complex dynamics of interacting dislocations onto a stochastic processes involving the continuum variables of stress and strain. Therefore, it combines a classical continuum description of the elastic-plastic problem with a stochastic description of the discrete dislocation dynamics. We compare the model predictions with the underlying DDD simulations and outline potential future applications of the same modelling approach.

Micron-scale single crystalline materials deform plastically via large intermittent strain bursts that make the deformation process unpredictable. Here we investigate this stochastic phenomenon by analysing the plastic response of an ensemble of specimens differing only in the initial arrangement of dislocations. We apply discrete dislocation dynamics simulations and microcompression tests on identically fabricated Cu single crystalline micropillars. We find that a characteristic yield stress can be defined in the average sense for a given specimen ensemble, where the average and the variance of the plastic strain start to increase considerably. In addition, in all studied cases the stress values at a given strain follow a Weibull distribution with similar Weibull exponents, which suggests that dislocation-mediated plastic yielding is characterized by an underlying weakest-link phenomenon. These results are found not to depend on fine details of the actual set-up, rather, they represent general features of micron-scale plasticity., Comment: 11 pages

In Ni-base superalloys with low Al and/or Ti content the precipitation and subsequent coarsening of gamma' particles at intermediate temperatures contribute to the degradation of the mechanical properties of the alloy. In the present paper the coarsening process is modelled and the change of the critical resolved shear stress of the alloy due to coarsening of the gamma' particles is calculated by means of statistical analysis of the depinning of a single gliding edge dislocation. It is found that the contribution of gamma' hardening to the critical resolved shear stress at 973 K reduces to more than half of its original value in less than one year., Comment: 8 pages, 5 figures

The existence of a well defined yield stress, where a macroscopic piece of crystal begins to plastically flow, has been one of the basic observations of materials science. In contrast to macroscopic samples, in micro- and nanocrystals the strain accumulates in distinct, unpredictable bursts, which makes controlled plastic forming rather difficult. Here we study by simulation, in two and three dimensions, plastic deformation of submicron objects under increasing stress. We show that, while the stress-strain relation of individual samples exhibits jumps, its average and mean deviation still specify a well-defined critical stress, which we identify with the jamming-flowing transition. The statistical background of this phenomenon is analyzed through the velocity distribution of short dislocation segments, revealing a universal cubic decay and an appearance of a shoulder due to dislocation avalanches. Our results can help to understand the jamming-flowing transition exhibited by a series of various physical systems., Comment: 5 pages

Numerical studies of dislocation pair correlations have played a central role in deriving a continuum theory from the equations of motion of 2D dislocation systems in a mathematically rigorous way. As part of an effort to extend this theory into the full 3D dislocation problem, 3D dislocation pair correlations were studied with discrete dislocation dynamics simulation. As a first approximation, dislocations were modeled as uncharged curves in space (their Burgers vectors were disregarded). An inverse square decay with distance was found to describe the numerically obtained pair correlations of the studied curve system., Comment: 6 pages, 4 figures