lpa-input 0.8.0

Tools for the generation and analysis of dislocation distributions.

Project

This repository is related to the analysis of crystals containing dislocations by X-ray diffraction. It is part of a larger project conducted during a research internship at the laboratory of material and structural sciences of the École Nationale Supérieure des Mines de Saint-Étienne.

Features

The tools developed can be used to:

• generate dislocation distributions according to different models
• export the distributions in standardized files for input to an X-ray diffraction simulation program
• export the distributions in dislocation maps
• export a spatial analysis of the distributions

Physical aspects

A dislocation associates:

• a Burgers vector
• a position

Two geometries are proposed:

• circle (intersection of a plane with a cylinder) centered in (0, 0)
• square (intersection of a plane with a cuboid) bottom left corner in (0, 0)

A distribution is characterized by the following elements:

• the geometry of the region of interest
• the model used for the random generation of dislocations
• the generated dislocations

Abbreviations

Some abbreviations are used in the program:

Models

• urdd: uniformly random dislocation distribution
• rrdd: restrictedly random dislocation distribution
• rcdd: random cell dislocation distribution

Model variants

• r: randomly distributed Burgers vectors
• e: evenly distributed Burgers vectors
• d: dipolar Burgers vectors

Boundary conditions

• pbcg: periodic boundary conditions applied when generating the distribution
• pbcr: periodic boundary conditions applied when runnning the simulation
• idbc: image dislocations boundary conditions

Content of the repository

The disldist directory is the python package containing the distribution generation and analysis tools. The directory exported contains the exported files. The directory maths provides the LaTeX code of the functions implemented in disldist. The remote.py script simplifies the remote management of calculations on a supercomputer. The script run.py is used as hello world and can be executed as is. The script settings.py gathers the standard parameters of the generated distributions. The files slurm.job and slurm.py are to be used only on a supercomputer.

Examples of use

Generation

To create a uniformly random dislocation distribution with evenly distributed Burgers vectors in a cylindrical geometry with a radius of 1000 nm:

from disldist import sets
r = {'density': 0.03, 'variant': 'e'}
d = sets.Distribution('circle', 1000, 'urdd', r)

To create a sample of 100 uniformly random dislocation distribution with evenly distributed Burgers vectors in a cylindrical geometry with a radius of 1000 nm:

from disldist import sets
r = {'density': 0.03, 'variant': 'e'}
s = sets.Sample(500, 'circle', 1000, 'urdd', r)

Export

To export a dislocation map of a distribution d.

from disldist import maps
maps.export(d)

To make standardized files for input to an X-ray diffraction simulation program from a sample s:

from disldist import data
data.export(s)

To make a spatial analysis of a sample s:

from disldist import analyze
analyze.export(s)

License