# -*- coding: utf-8 -*-
from yade import pack
############################################
### DEFINING VARIABLES AND MATERIALS ###
############################################
# The following 5 lines will be used later for batch execution
nRead=utils.readParamsFromTable(
num_spheres=10000,# number of spheres
compFricDegree = 0, # contact friction during the confining phase
unknownOk=True
)
from yade.params import table
num_spheres=table.num_spheres # number of spheres
targetPorosity = 0.382 #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 = 35 # contact friction during the deviatoric loading
rate=0.02 # loading rate (strain rate)
damp=0.2 # damping coefficient
stabilityThreshold=0.01
key='_triax_base_' # simulation's name here
young=2e6 # contact stiffness (initial value) =5e6
mn,mx=Vector3(0,0,0),Vector3(0.01,0.01,0.01) # corners of the initial packing
thick = 0.01 # l'épaisseur des plaques
## créer les matériaux pour les sphères et plaques
O.materials.append(FrictMat(young=young,poisson=0.3,frictionAngle=radians(compFricDegree),density=3000,label='spheres'))
O.materials.append(FrictMat(young=young,poisson=0.5,frictionAngle=0,density=0,label='walls'))
## create walls around the packing
walls=utils.aabbWalls([mn,mx],thickness=thick,material='walls')
wallIds=O.bodies.append(walls)
## use a SpherePack object to generate a random loose particles packing
sp=pack.SpherePack()
clumps=False #turn this true for the same example with clumps / on utilisera cette methode dans l'avenir
if clumps:
## approximate mean rad of the futur dense packing for latter use
volume = (mx[0]-mn[0])*(mx[1]-mn[1])*(mx[2]-mn[2])
mean_rad = pow(0.09*volume/num_spheres,0.3333)
## define a unique clump type (we could have many, see clumpCloud documentation)
c1=pack.SpherePack([((-0.2*mean_rad,0,0),0.5*mean_rad),((0.2*mean_rad,0,0),0.5*mean_rad)])
## generate positions and input them in the simulation
sp.makeClumpCloud(mn,mx,[c1],periodic=False)
sp.toSimulation(material='spheres')
else:
sp.makeCloud(mn,mx,-1,0.3333,num_spheres,False, 0.95)
O.bodies.append([utils.sphere(center,rad,material='spheres') for center,rad in sp])
#or alternatively (higher level function doing exactly the same):
#sp.toSimulation(material='spheres')
############################
### DEFINING ENGINES ###
############################
triax=ThreeDTriaxialEngine(
maxMultiplier=1.+2e4/young, # spheres growing factor (fast growth)
finalMaxMultiplier=1.+2e3/young, # spheres growing factor (slow growth)
thickness = thick,
stressControl_1 = False, #switch stress/strain control
# strainControl_1 = True, temporary switch off because I have no idea what it is about.
stressControl_2 = False,
stressControl_3 = False,
## The stress used for (isotropic) internal compaction
sigma_iso = 100000, # Pa
## Independant stress values for anisotropic loadings
sigma1=300000, # to create the q=s11-s33=200kPa=200000
sigma2=100000,
sigma3=100000,
internalCompaction=True, # The confining pressure is generated by growing particles !!!!!!!!!
Key=key, # passed to the engine so that the output file will have the correct name
)
newton=NewtonIntegrator(damping=damp)
O.engines=[
ForceResetter(),
InsertionSortCollider([Bo1_Sphere_Aabb(),Bo1_Box_Aabb()]),
InteractionLoop(
[Ig2_Sphere_Sphere_ScGeom(),Ig2_Box_Sphere_ScGeom()],
[Ip2_FrictMat_FrictMat_FrictPhys()],
[Law2_ScGeom_FrictPhys_CundallStrack()]
),
GlobalStiffnessTimeStepper(active=1,timeStepUpdateInterval=100,timestepSafetyCoefficient=0.8),
triax,
TriaxialStateRecorder(iterPeriod=100,file='WallStresses'+key),
newton
]
#Display spheres with 2 colors for seeing rotations better
Gl1_Sphere.stripes=0
if nRead==0: yade.qt.Controller(), yade.qt.View()
#######################################
### APPLYING CONFINING PRESSURE ###
#######################################
while 1:
O.run(1000, True)
##the global unbalanced force on dynamic bodies, thus excluding boundaries, which are not at equilibrium
unb=unbalancedForce()
##average stress
##note: triax.stress(k) returns a stress vector, so we need to keep only the normal component
meanS=(triax.stress(triax.wall_right_id)[0]+triax.stress(triax.wall_top_id)[1]+triax.stress(triax.wall_front_id)[2])/3
print 'unbalanced force:',unb,' mean stress: ',meanS
if unb<stabilityThreshold and abs(meanS-triax.sigma_iso)/triax.sigma_iso<0.001:
break
O.save('confinedState'+key+'.yade.gz')
print "### Isotropic state saved ###"
###################################################
### REACHING A SPECIFIED POROSITY PRECISELY ###
###################################################
import sys #this is only for the flush() below
while triax.porosity>targetPorosity:
## we decrease friction value and apply it to all the bodies and contacts
compFricDegree = 0.95*compFricDegree
setContactFriction(radians(compFricDegree))
print "\r Friction: ",compFricDegree," porosity:",triax.porosity,
sys.stdout.flush()
## while we run steps, triax will tend to grow particles as the packing
## keeps shrinking as a consequence of decreasing friction. Consequently
## porosity will decrease
O.run(500,1)
O.save('compactedState'+key+'.yade.gz')
print "### Compacted state saved ###"
##############################
### DEVIATORIC LOADING ###
##############################
## Deviatoric loading, turn internal compaction off to keep particles sizes constant
triax.internalCompaction=False
## Change contact friction (remember that decreasing it would generate instantaneous instabilities)
triax.setContactProperties(finalFricDegree)
##set independant stress control on each axis
triax.stressControl_1=triax.stressControl_2=triax.stressControl_3=True
## We turn all these flags true, else boundaries will be fixed
triax.wall_bottom_activated=True
triax.wall_top_activated=True
triax.wall_left_activated=True
triax.wall_right_activated=True
triax.wall_back_activated=True
triax.wall_front_activated=True
##If we want a triaxial loading at imposed strain rate, let's assign srain rate instead of stress
triax.stressControl_2=0 #we are tired of typing "True" and "False", we use implicit conversion from integer to boolean
triax.strainRate2=rate
triax.strainRate1=100*rate
triax.strainRate3=100*rate
## Damping (initial value = 0.1)
newton.damping=0.5
##Save temporary state in live memory. This state will be reloaded from the interface with the "reload" button.
O.saveTmp()
###########################
### Plot Data ###
###########################
from yade import plot
### a function saving variables
def history():
plot.addData(e11=triax.strain[0], e22=triax.strain[1], e33=triax.strain[2],
ev=-triax.strain[0]-triax.strain[1]-triax.strain[2],
s11=triax.stress(triax.wall_right_id)[0],
s22=triax.stress(triax.wall_top_id)[1],
s33=triax.stress(triax.wall_front_id)[2],
q=triax.stress(triax.wall_right_id)[0]-triax.stress(triax.wall_front_id)[2],
i=O.iter)
if 1:
## include a periodic engine calling that function in the simulation loop
O.engines=O.engines[0:5]+[PyRunner(iterPeriod=20,command='history()',label='recorder')]+O.engines[5:7]
##O.engines.insert(4,PyRunner(iterPeriod=20,command='history()',label='recorder'))
else:
## With the line above, we are recording some variables twice. We could in fact replace the previous
## TriaxialRecorder
## by our periodic engine. Uncomment the following line:
O.engines[4]=PyRunner(iterPeriod=20,command='history()',label='recorder')
O.run(100,True)
### plot 1
# plot.plots={'i':('e11','e22','e33',None,'s11','s22','s33')}
### the traditional triaxial curves
# plot.plots={'e11':('q')}
plot.plots={'e11':('ev')}
## display on the screen
plot.plot()
##### PLAY THE SIMULATION HERE WITH "PLAY" BUTTON OR WITH THE COMMAND O.run(N) #####
## In that case we can still save the data to a text file at the the end of the simulation, with:
#plot.saveDataTxt('results'+key)
##or even generate a script for gnuplot. Open another terminal and type "gnuplot plotScriptKEY.gnuplot:
#plot.saveGnuplot('plotScript'+key)
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