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[SayedHessam <question657227@xxxxxxxxxxxxxxxxxxxxx>]

New question #657227 on Yade:
https://answers.launchpad.net/yade/+question/657227

Hi there !

According to the triax-tutorial/cript-session1.py, I tried to model CU condition for my soil :

Set
stressMask = 0
triax.goal2=-rate
triax.goal1=triax.goal3=rate/2

but when I play it, all my particles suddenly disappear. Please let me know whats is the reason and how can I handle it.

My script:


from yade import pack



############################################

###   DEFINING VARIABLES AND MATERIALS   ###

############################################



# The following 5 lines will be used later for batch execution

nRead=readParamsFromTable(

	num_spheres=1000,# number of spheres

	compFricDegree = 30, # contact friction during the confining phase

	key='_triax_base_', # put you simulation's name here

	unknownOk=True

)

from yade.params import table



num_spheres=table.num_spheres# number of spheres

key=table.key

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=-0.02 # 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





## create materials for spheres and plates

O.materials.append(FrictMat(young=young,poisson=0.5,frictionAngle=radians(compFricDegree),density=2600,label='spheres'))

O.materials.append(FrictMat(young=young,poisson=0.5,frictionAngle=0,density=0,label='walls'))



## create walls around the packing

walls=aabbWalls([mn,mx],thickness=0,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

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')

 O.bodies.updateClumpProperties()#get more accurate clump masses/volumes/inertia

else:

 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])

 #or alternatively (higher level function doing exactly the same):

 #sp.toSimulation(material='spheres')



############################

###   DEFINING ENGINES   ###

############################



triax=TriaxialStressController(

	## TriaxialStressController will be used to control stress and strain. It controls particles size and plates positions.

	## this control of boundary conditions was used for instance in http://dx.doi.org/10.1016/j.ijengsci.2008.07.002

	maxMultiplier=1.+2e4/young, # spheres growing factor (fast growth)

	finalMaxMultiplier=1.+2e3/young, # spheres growing factor (slow growth)

	thickness = 0,

	## switch stress/strain control using a bitmask. What is a bitmask, huh?!

	## Say x=1 if stess is controlled on x, else x=0. Same for for y and z, which are 1 or 0.

	## Then an integer uniquely defining the combination of all these tests is: mask = x*1 + y*2 + z*4

	## to put it differently, the mask is the integer whose binary representation is xyz, i.e.

	## "100" (1) means "x", "110" (3) means "x and y", "111" (7) means "x and y and z", etc.

	stressMask = 7,

	internalCompaction=True, # If true the confining pressure is generated by growing particles

)



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()]

	),

	## We will use the global stiffness of each body to determine an optimal timestep (see https://yade-dem.org/w/images/1/1b/Chareyre&Villard2005_licensed.pdf)

	GlobalStiffnessTimeStepper(active=1,timeStepUpdateInterval=100,timestepSafetyCoefficient=0.8),

	triax,

	TriaxialStateRecorder(iterPeriod=100,file='WallStresses'+table.key),

	newton

]



#Display spheres with 2 colors for seeing rotations better

Gl1_Sphere.stripes=0

if nRead==0: yade.qt.Controller(), yade.qt.View()



## UNCOMMENT THE FOLLOWING SECTIONS ONE BY ONE

## DEPENDING ON YOUR EDITOR, IT COULD BE DONE

## BY SELECTING THE CODE BLOCKS BETWEEN THE SUBTITLES

## AND PRESSING CTRL+SHIFT+D



#######################################

###   APPLYING CONFINING PRESSURE   ###

#######################################



#the value of (isotropic) confining stress defines the target stress to be applied in all three directions

triax.goal1=triax.goal2=triax.goal3=-10000



while 1:

  O.run(1000, True)

  #the global unbalanced force on dynamic bodies, thus excluding boundaries, which are not at equilibrium

  unb=unbalancedForce()

  print 'unbalanced force:',unb,' mean stress: ',triax.meanStress

  if unb<stabilityThreshold and abs(-10000-triax.meanStress)/10000<0.001:

    break



O.save('confinedState'+key+'.yade.gz')

print "###      Isotropic state saved      ###"



###################################################

###   REACHING A SPECIFIED POROSITY PRECISELY   ###

###################################################



### We will reach a prescribed value of porosity with the REFD algorithm

### (see http://dx.doi.org/10.2516/ogst/2012032 and

### http://www.geosyntheticssociety.org/Resources/Archive/GI/src/V9I2/GI-V9-N2-Paper1.pdf)



#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   ###

##############################



#We move to deviatoric loading, let us turn internal compaction off to keep particles sizes constant

triax.internalCompaction=False



# Change contact friction (remember that decreasing it would generate instantaneous instabilities)

setContactFriction(radians(finalFricDegree))



#set stress control on x and z, we will impose strain rate on y

triax.stressMask = 0

#now goal2 is the target strain rate

triax.goal2=-rate

# we define the lateral stresses during the test, here the same 10kPa as for the initial confinement.

triax.goal1=triax.goal3=rate/2

triax.goal3=-10000



#we can change damping here. What is the effect in your opinion?

newton.damping=0.1



#Save temporary state in live memory. This state will be reloaded from the interface with the "reload" button.

O.saveTmp()



#####################################################

###    Example of how to record and 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],

		    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)



## declare what is to plot. "None" is for separating y and y2 axis

plot.plots={'i':('e11','e22','e33',None,'s11','s22','s33')}

## the traditional triaxial curves would be more like this:

#plot.plots={'e22':('s11','s22','s33',None,'ev')}



# display on the screen (doesn't work on VMware image it seems)

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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