Statistical analysis of Discrete Dislocation Dynamics simulations: initial structures, cross-slip and microstructure evolution

TL;DR

This paper investigates how cross-slip influences dislocation microstructure evolution in metallic samples using discrete dislocation dynamics simulations and a novel data mining approach for quantitative analysis.

Contribution

It introduces a tailored data mining strategy within the discrete-to-continuous framework to quantify and compare dislocation structures affected by cross-slip.

Findings

Cross-slip significantly impacts dislocation microstructure evolution.

Resolution of domain averaging affects quantitative analysis accuracy.

The approach improves interpretation of dislocation dynamics simulations.

Abstract

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.