Slip Transmition

How to analyse slip transmission at grain boundaries

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Import Titanium data
Taylor model

Import Titanium data

From Mercier D. - MTEX 2016 Workshop - TU Chemnitz (Germany) Calculation and plot on GBs of m' parameter Dataset from Mercier D. - cp-Ti (alpha phase - hcp)

mtexdata csl

% compute grains
[grains, ebsd.grainId] = calcGrains(ebsd('indexed'));

% make them a bit nicer
grains = smooth(grains);

% extract inner phase grain boundaries
gB = grains.boundary('indexed');

plot(ebsd,ebsd.orientations)
hold on
plot(grains.boundary)
hold off

Taylor model

% consider Basal slip
sS = slipSystem.fcc(ebsd.CS)

% and all symmetrically equivalent variants
sS = sS.symmetrise;

% consider plane strain
q = 0.5;
eps = strainTensor(diag([-q 1 -(1-q)]));

% and compute Taylor factor as well as the active slip systems
[M,b,ori] = calcTaylor(inv(grains.meanOrientation).*eps,sS);
 
sS = slipSystem  
 mineral: iron (m-3m)
 CRSS: 1
 size: 1 x 1
  u   v   w | h   k   l
  0   1  -1   1   1   1
 computing Taylor factor: 100%
% find the maximum
[~,id] = max(b,[],2);

The variable id contains now for each grain the id of the slip system with the largest Schmidt factor. In order to visualize it we first rotate for each grain the slip system with largest Schmid factor in specimen coordinates

sSGrain = grains.meanOrientation .* sS(id)

% and plot then the plance normal and the Burgers vectors into the centers
% of the grains

plot(grains,M)

largeGrains = grains(grains.grainSize > 10)

hold on
quiver(grains,cross(sSGrain.n,zvector),'displayName','slip plane')
hold on
quiver(grains,sSGrain.b,'displayName','slip direction')
hold off
 
sSGrain = slipSystem  
 CRSS: 1
 size: 885 x 1
 
largeGrains = grain2d  
 
 Phase  Grains  Pixels  Mineral  Symmetry  Crystal reference frame
    -1     442  153261     iron      m-3m                         
 
 boundary segments: 21799
 triple points: 1444
 
 Properties: GOS, meanRotation
 

We may also analyse the distribution of the slip directions in a pole figure plot

plot(sSGrain.b)

The same as a contour plot. We see a clear trend towards east.

plot(sSGrain.b,'contourf')