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.

翻译：过去数十年间，离散位错动力学模拟已被证实能可靠预测微米级金属样品中位错微结构的演化。此类模拟为揭示主导变形机制及位错反应、交叉滑移等不同物理现象间的相互作用提供了重要视角。本研究聚焦于交叉滑移对位错系统演化影响的精细分析。通过采用基于"离散-连续框架"的定制化数据挖掘策略，我们得以量化差异并实现位错结构的定量比较。在拉伸试验及后续弛豫过程中，我们分析了交叉滑移对微观组织的定量影响，以揭示其在微结构演化中的作用。利用D2C方法提取的定量信息精度强烈依赖于区域平均的分辨率。我们还分析了平均化分辨率如何影响样品总位错密度分布及曲率场。本分析方法为解读位错动力学模拟所获结构提供了重要途径。