Extracting micro variables from Triaxial test

Asked by ehsan benabbas on 2020-01-17

Hi everyone,

I am using Ubuntu 18.04, and Yade 2019-08-08.git-775ae74
I use the Triaxial code by Bruno Chareyre [1]
[1] https://gitlab.com/yade-dev/trunk/blob/master/examples/triax-tutorial/script-session1.py

My goal is to get micro variables from Triaxial test and save them in a text file for the whole specimen (for all contacts). To do so, I just added the following codes at the end of [1] and made no changes:

# the fabric tensor
utils.fabricTensor()

# inter-particle forces
for i in O.interactions:
   fn = i.phys.normalForce
   fs = i.phys.shearForce

# branch vectors, and contact normals
for i in O.interactions:
   normal = i.geom.normal
   b1,b2 = [O.bodies[id] for id in (i.id1,i.id2)]
   p1,p2 = [b.state.pos for b in (b1,b2)]
   branch = p2 - p1
# Save Data
from pprint import pprint
plot.reset()
plot.addData(fn,fs,normal,brach)
pprint(plot.data)
plot.saveDataTxt('/tmp/MicrodataFile.txt.tar.gz',vars=('fn','fs','normal','branch'))

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

And the output I get is as follows:

ehsan@ehsan:~/Desktop$ /home/ehsan/yade/install/bin/yade-2019-08-08.git-775ae74 netmicro.py
Welcome to Yade 2019-08-08.git-775ae74
Using python version: 3.6.9 (default, Nov 7 2019, 10:44:02)
[GCC 8.3.0]
TCP python prompt on localhost:9000, auth cookie `sdsuay'
XMLRPC info provider on http://localhost:21000
Running script netmicro.py
The constructor with a shareWidget is deprecated, use the regular contructor instead.
 Friction: 28.5 porosity: 1.0
 Friction: 27.075 porosity: 0.908936796623662
 Friction: 25.721249999999998 porosity: 0.8342924618140075
 Friction: 24.435187499999998 porosity: 0.6986014608404307
.
.
.
 Friction: 10.216848788643448 porosity: 0.4341421461248899
 Friction: 9.706006349211275 porosity: 0.4316281950137172
### Compacted state saved ###
/home/ehsan/yade/install/lib/x86_64-linux-gnu/yade-2019-08-08.git-775ae74/py/yade/plot.py:444: MatplotlibDeprecationWarning:
The 'verts' kwarg was deprecated in Matplotlib 3.0 and will be removed in 3.2. Use 'marker' instead.
  scatter=pylab.scatter(scatterPt[0] if not math.isnan(scatterPt[0]) else 0,scatterPt[1] if not math.isnan(scatterPt[1]) else 0,s=scatterSize,color=line.get_color(),**scatterMarkerKw)
Traceback (most recent call last):
  File "/home/ehsan/yade/install/bin/yade-2019-08-08.git-775ae74", line 336, in runScript
    execfile(script,globals())
  File "/usr/lib/python3/dist-packages/past/builtins/misc.py", line 82, in execfile
    exec_(code, myglobals, mylocals)
  File "netmicro.py", line 248, in <module>
    plot.addData(fn,fs,normal,brach)
NameError: name 'brach' is not defined
[[ ^L clears screen, ^U kills line. F12 controller, F11 3D view (press "h" in 3D view for help), F10 both, F9 generator, F8 plot. ]]

In [1]:

Thank you for your help,
Ehsan

Question information

Language:
English Edit question
Status:
Solved
For:
Yade Edit question
Assignee:
No assignee Edit question
Solved by:
Jan Stránský
Solved:
2020-01-22
Last query:
2020-01-22
Last reply:
2020-01-22
Jan Stránský (honzik) said : #1

1) plot module is not suitable for this kind of savings (also the usage in the script is wrong)

"for i in O.interactions" was there to show how to "get" the data (as asked in another question), not meant that it works without any modification.

To save data of all interactions, I propose creating a list of data and than save it, something like (not tested):
###
data = []
for i in O.interactions:
   fn = i.phys.normalForce
   fs = i.phys.shearForce
   cp = i.geom.contactPoint
   normal = i.geom.normal
   b1,b2 = [O.bodies[id] for id in (i.id1,i.id2)]
   p1,p2 = [b.state.pos for b in (b1,b2)]
   branch = p2 - p1
   cp,normal,branch,fn,fs = [tuple(v) for v in (cp,normal,branch,fn,fs)] # Vector3 -> tuple
   d = dict(cp=cp,normal=normal,branch=branch,fn=fn,fs=fs)
# new data contains the information, you can save it e.g. as JSON
import json
with open("interactions.json","w") as f:
   json.dump(data,f)
###

cheers
Jan

ehsan benabbas (ehsanben) said : #2

Jan thank you for your answer.

When I add these commands at the end of [1], the txt file is empty and just contains "[]" .

The output is as follows:

ehsan@ehsan:~/Desktop$ /home/ehsan/yade/install/bin/yade-2019-08-08.git-775ae74 netmicro.py
Welcome to Yade 2019-08-08.git-775ae74
Using python version: 3.6.9 (default, Nov 7 2019, 10:44:02)
[GCC 8.3.0]
TCP python prompt on localhost:9000, auth cookie `ucsekd'
XMLRPC info provider on http://localhost:21000
Running script netmicro.py
The constructor with a shareWidget is deprecated, use the regular contructor instead.
 Friction: 28.5 porosity: 1.0
 Friction: 27.075 porosity: 0.908936796623662
 Friction: 25.721249999999998 porosity: 0.8342924618140075
 Friction: 24.435187499999998 porosity: 0.6986014608404307
.
.
.
 Friction: 10.216848788643448 porosity: 0.4341421461248899
 Friction: 9.706006349211275 porosity: 0.4316281950137172
### Compacted state saved ###
/home/ehsan/yade/install/lib/x86_64-linux-gnu/yade-2019-08-08.git-775ae74/py/yade/plot.py:444: MatplotlibDeprecationWarning:
The 'verts' kwarg was deprecated in Matplotlib 3.0 and will be removed in 3.2. Use 'marker' instead.
  scatter=pylab.scatter(scatterPt[0] if not math.isnan(scatterPt[0]) else 0,scatterPt[1] if not math.isnan(scatterPt[1]) else 0,s=scatterSize,color=line.get_color(),**scatterMarkerKw)
[[ ^L clears screen, ^U kills line. F12 controller, F11 3D view (press "h" in 3D view for help), F10 both, F9 generator, F8 plot. ]]

In [1]:

Jan Stránský (honzik) said : #3

> and made no changes
> Friction: 28.5 porosity: 1.0

the printing is commented in the original script, so you must have done some changes. Please provide the actual code you are using

cheers
Jan

ehsan benabbas (ehsanben) said : #4

Hi Jan, Thanks for your helps

This is the code:

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 = 5
#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=-10000
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)

data = []
for i in O.interactions:
   fn = i.phys.normalForce
   fs = i.phys.shearForce
   cp = i.geom.contactPoint
   normal = i.geom.normal
   b1,b2 = [O.bodies[id] for id in (i.id1,i.id2)]
   p1,p2 = [b.state.pos for b in (b1,b2)]
   branch = p2 - p1
   cp,normal,branch,fn,fs = [tuple(v) for v in (cp,normal,branch,fn,fs)] # Vector3 -> tuple
   d = dict(cp=cp,normal=normal,branch=branch,fn=fn,fs=fs)
# new data contains the information, you can save it e.g. as JSON
import json
with open("interactions.json","w") as f:
   json.dump(data,f)

Jan Stránský (honzik) said : #5

sorry, since you save "data" variable, you should feed it with the data (which I missed in the answer). Just add
data.append(d)
at the end of for i in "O.interactions" loop
cheers
Jan

ehsan benabbas (ehsanben) said : #6

Thank you Jan
I added as a last line of the loop (right after "d = dict(cp=cp,normal=normal,branch=branch,fn=fn,fs=fs)")
The txt file is not empty anymore but it's just a line and this line is so crowded and messy with overlap letters
nothing can be read from this file
Bests,
Ehsan

Jan Stránský (honzik) said : #7

> but it's just a line

yes, it is a data saved in JSON format. Completely satisfying the requirement "save them in a text file"

> this line is so crowded and messy with overlap letters

You can use
json.dump(data,f,indent=3)
for pretty print (the same JSON string, but with newlines).

> nothing can be read from this file

Anything can be read from this file, e.g. by
###
import json
with open("interactions.json") as f:
   data = json.load(f) # now data is the same as what was saved
###

cheers
Jan

ehsan benabbas (ehsanben) said : #8

Thank you so much Jan. Tha solved my problem. Is there any way to print those in a txt file like in a x_y_z_r format? something like that?

Best Jan Stránský (honzik) said : #9

something like:
###
with open(fileName,"w") as f:
   f.write("# cpx cpy cpz fnx fny fnz ...\n")
   for d in data: # or directly for i in O.interactions
      cp = d["cp"]
      fn = d["fn"]
      ...
      f.write("{} {} {} {} {} {} ... "\n".format(cp[0],cp[1],cp[2],fn[0],fn[1],fn[2],...)
###

cheers
Jan

ehsan benabbas (ehsanben) said : #10

Thanks Jan Stránský, that solved my question.