MSE 2016 - Full Program

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Lecture

Analysis and Data Mining of Discrete Dislocation Data with the D2C Framework

Wednesday (28.09.2016)
15:30 - 15:45
Part of:


Understanding the motion and interactions of dislocation is crucial in

unravelling the influence of the microstructure on the mechanical behavior of

crystalline materials. In recent years several methods were developed to

investigate dislocation properties on the micro scale. Discrete Dislocation

Dynamics (DDD) are well established, but are limited to relatively small

samples and low dislocation densities/strains. Continuous Dislocation Dynamics

(CDD) alleviate these drawbacks but have yet to be applied to complex problems

where validation of the method via analytical solution is not feasible.


With "D2C" we introduce a framework where discrete dislocation data from DDD or

other sources, as e.g. experiments or atomistic simulations, can be used to

compute continuum fields describing the dislocation ensemble. The level of

detail can be adjusted by the amount and types of fields computed. Besides the

validation of CDD via DDD [1] the approach enables the quantitative comparison

of different microstructures and loss of information in different continuum

dislocation models.


We show how "D2C" in conjunction with ensemble averaging can be applied to 3D

DDD simulations of a bicrystal under monotonic and cyclic loading Simulations

are compared with respect to their resulting microstructure and stress state

near the grain boundary. We investigate which continuous fields are necessary

to describe this microstructure faithfully. Finally, we show first results from

analyzing some of the largest existing DDD simulations that exhibit dislocation

patterns.


[1] S. Sandfeld and G. Po, Model. Simul. Mater. Sci. Eng. 23.8, 2015

Speaker:
Dominik Steinberger
University of Erlangen-Nuremberg
Additional Authors:
  • Dr. Stefan Sandfeld
    University of Erlangen-Nuremberg