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[Question #699998]: How to simulate small-strain triaxial compression test
New question #699998 on Yade:
I'd like to ask that how to simulate a drained triaxial compression test within a small-strain level.
The goal of this simulation is to get the small strain stiffness G0.
A typical way is (1) generating a sand packing and isotropically load it to target confining pressure, e.g., 100 kPa. (2) a small axial strain increment deps1 is applied on the top wall, while the lateral stresses sigma2 and sigma3 keep constant. (3) the simulation finishes when the shear strain, gamma = deps1-deps2, reaches 10e-6. (4) then G0 can be calculated by G0 = dsigma1/(2*gamma)
What I have done is using the example code provided by Bruno. I set the loading rate to a very small value (1e-20), and the simulations finished in one second. I thought this process is too quick to generate accurate results, actually the lateral confining pressure changes (i.e., not constant). I know this script works well for a classic triaxial compression test because usually we look at a large strain level (like 20% of axial strain), thereby a small amout of fluctuation on lateral stress is acceptable. But when we look at such a small range and in such a short time, this will lead to inaccurate results. So my question is how can we make the simulation of triaxial compression test within a small-strain level.
The MWE is as follow if the question is not clearly described.
from yade import pack
num_spheres=1000,# number of spheres
compFricDegree = 30, # contact friction during the confining phase
key='_triax_base_', # put you simulation's name here
from yade.params import table
num_spheres=table.num_spheres# number of spheres
targetPorosity = 0.43 #the porosity we want for the packing
compFricDegree = table.compFricDegree # initial contact friction during the confining phase (will be decreased during the REFD compaction process)
finalFricDegree = 30 # contact friction during the deviatoric loading
rate=-1e-20 # loading rate (strain rate)
damp=0.2 # damping coefficient
stabilityThreshold=0.01 # we test unbalancedForce against this value in different loops (see below)
young=5e6 # contact stiffness
mn,mx=Vector3(0,0,0),Vector3(1,1,1) # corners of the initial packing
sp.makeCloud(mn,mx,-1,0.3333,num_spheres,False, 0.95,seed=1) #"seed" make the "random" generation always the same
O.bodies.append([sphere(center,rad,material='spheres') for center,rad in sp])
maxMultiplier=1.+2e4/young, # spheres growing factor (fast growth)
finalMaxMultiplier=1.+2e3/young, # spheres growing factor (slow growth)
thickness = 0,
stressMask = 7,
internalCompaction=True, # If true the confining pressure is generated by growing particles
if nRead==0: yade.qt.Controller(), yade.qt.View()
print 'unbalanced force:',unb,' mean stress: ',triax.meanStress
if unb<stabilityThreshold and abs(-100000-triax.meanStress)/100000<0.001:
print "### Isotropic state saved ###"
import sys #this is only for the flush() below
# we decrease friction value and apply it to all the bodies and contacts
compFricDegree = 0.95*compFricDegree
print "\r Friction: ",compFricDegree," porosity:",triax.porosity,
print "### Compacted state saved ###"
triax.stressMask = 5
print "gamma before deviatoric loading is", abs(triax.strain-triax.strain)
print "click run to start small-strain deviatoric loading"
from yade import plot
plot.addData(e11=-triax.strain, e22=-triax.strain, e33=-triax.strain,
print "gamma after deviatoric loading is", abs(triax.strain-triax.strain)
### declare what is to plot. "None" is for separating y and y2 axis
## the traditional triaxial curves would be more like this:
# display on the screen (doesn't work on VMware image it seems)
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