3 research outputs found
On Open and Strong-Scaling Tools for Atom Probe Crystallography: High-Throughput Methods for Indexing Crystal Structure and Orientation
Volumetric crystal structure indexing and orientation mapping are key data
processing steps for virtually any quantitative study of spatial correlations
between the local chemistry and the microstructure of a material. For electron
and X-ray diffraction methods it is possible to develop indexing tools which
compare measured and analytically computed patterns to decode the structure and
relative orientation within local regions of interest. Consequently, a number
of numerically efficient and automated software tools exist to solve the above
characterisation tasks.
For atom probe tomography (APT) experiments, however, the strategy of making
comparisons between measured and analytically computed patterns is less robust
because many APT datasets may contain substantial noise. Given that general
enough predictive models for such noise remain elusive, crystallography tools
for APT face several limitations: Their robustness to noise, and therefore,
their capability to identify and distinguish different crystal structures and
orientation is limited. In addition, the tools are sequential and demand
substantial manual interaction. In combination, this makes robust uncertainty
quantifying with automated high-throughput studies of the latent
crystallographic information a difficult task with APT data.
To improve the situation, we review the existent methods and discuss how they
link to those in the diffraction communities. With this we modify some of the
APT methods to yield more robust descriptors of the atomic arrangement. We
report how this enables the development of an open-source software tool for
strong-scaling and automated identifying of crystal structure and mapping
crystal orientation in nanocrystalline APT datasets with multiple phases.Comment: 36 pages, 19 figures, preprin
Space Decomposition Based Parallelisation Solutions for the Combined Finite-Discrete Element Method in 2D.
PhDThe Combined Finite-Discrete Element Method (FDEM), originally invented by
Munjiza, has become a tool of choice for problems of discontinua, where particles
are deformable and can fracture or fragment. The downside of FDEM is that it is
CPU intensive and, as a consequence, it is difficult to analyse large scale problems
on sequential CPU hardware and parallelisation becomes necessary. In this work
a novel approach for parallelisation of the combined finite-discrete element method
(FDEM) in 2D aimed at clusters and desktop computers is developed. Dynamic domain
decomposition-based parallelisation solvers covering all aspects of FDEM have
been developed. These have been implemented into the open source Y2D software
package by using a Message-Passing Interface (MPI) and have been tested on a PC
cluster. The overall performance and scalability of the parallel code has been studied
using numerical examples. The state of the art, the proposed solvers and the test results
are described in the thesis in detail.