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Message #14306
[Question #526635]: Segmentation fault (core dumped) when HydrodynamicsLawLBM Activated
New question #526635 on Yade:
https://answers.launchpad.net/yade/+question/526635
Segmentation fault (core dumped) when HydrodynamicsLawLBM Activated
Hi, can someone please tell me why this error happens? Thanks a lot!
The code works well with out activating the HydrodynamicsLawLBM engine.
But when I add the code"Elbm.EngineIsActivated=True", it prints:
---- Lattice setup -----
LXYZ0= -0.01 -0.01 1
LXYZ1= 0.01 0.01 1.02
Ny= -248 Nx*Ly0/Lx0=-248
Wallthickness= 0.01 dx=-4.01606e-05
Segmentation fault (core dumped)
Here is my code:
# -*- coding: utf-8 -*-
#*************************************************************************
# Copyright (C) 2010 by Bruno Chareyre *
# bruno.chareyre_at_grenoble-inp.fr *
# *
# This program is free software; it is licensed under the terms of the *
# GNU General Public License v2 or later. See file LICENSE for details. *
#*************************************************************************/
## This script details the simulation of a triaxial test on sphere packings using Yade
## See the associated pdf file for detailed exercises
## the algorithms presented here have been used in published papers, namely:
## * Chareyre et al. 2002 (http://www.geosyntheticssociety.org/Resources/Archive/GI/src/V9I2/GI-V9-N2-Paper1.pdf)
## * Chareyre and Villard 2005 (https://yade-dem.org/w/images/1/1b/Chareyre&Villard2005_licensed.pdf)
## * Scholtès et al. 2009 (http://dx.doi.org/10.1016/j.ijengsci.2008.07.002)
## * Tong et al.2012 (http://dx.doi.org/10.2516/ogst/2012032)
##
## Most of the ideas were actually developped during my PhD.
## If you want to know more on micro-macro relations evaluated by triaxial simulations
## AND if you can read some french, it is here: http://tel.archives-ouvertes.fr/docs/00/48/68/07/PDF/Thesis.pdf
from yade import pack
## control to open the file
Not_Open_flag = 1
if Not_Open_flag:
stress_info = open("/home/caowei/Documents/myYade/trunk/examples/stress_info.txt",'a')
contact_info = open("/home/caowei/Documents/myYade/trunk/examples/contactOri.txt",'a')
particle_info = open("/home/caowei/Documents/myYade/trunk/examples/particle.txt",'a')
Not_Open_flag = 0
############################################
### DEFINING VARIABLES AND MATERIALS ###
############################################
# The following 5 lines will be used later for batch execution
nRead=readParamsFromTable(
num_spheres=7000,# number of spheres
compFricDegree = 35, # 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 = 0.425 #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=-0.01 # loading rate (strain rate)
damp=0.2 # damping coefficient
stabilityThreshold=0.01 # we test unbalancedForce against this value in different loops (see below)
young=1e8 # 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=0.3,frictionAngle=radians(compFricDegree),density=2600,label='spheres'))
O.materials.append(FrictMat(young=young,poisson=0.3,frictionAngle=0,density=0,label='walls'))
## create walls around the packing
walls=aabbWalls([mn,mx],thickness=0.01,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),
HydrodynamicsLawLBM( EngineIsActivated=False,
WallYm_id=0,
WallYp_id=1,
WallXm_id=2,
WallXp_id=3,
WallZp_id=5,
WallZm_id=4,
useWallYm=1,
useWallYp=1,
YmBCType=2,
YpBCType=2,
useWallXm=0,
useWallXp=0,
XmBCType=1,
XpBCType=1,
LBMSavedData='spheres,velXY,rho,nodeBD',
tau=1.1,
dP=(0,0,0),
IterSave=200,
IterPrint=100,
RadFactor=0.6, # The radius of particles seen by the LBM engine is reduced here by a factor RadFactor=0.6 to allow flow between particles in this 2D case.
Nx=250,
Rho=1000,
Nu=1.0e-6,
periodicity='',
bc='',
VbCutOff=0.0,
applyForcesAndTorques=True,
label="Elbm"
),
newton,
#PyRunner(command='checkStress0()',iterPeriod=500,label='checker')
]
O.dt=.5*utils.PWaveTimeStep()
# for the samples of this size (diametre is around 1.8cm), the O.dt is 8.8e-5 s, which is about a hundred times of
# the small sample, and this leads to much faster calculation speed.
#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=-100000
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(-100000-triax.meanStress)/100000<0.001:
break
O.save('confinedState'+key+'.yade.gz')
print "### Isotropic state saved ###"
print triax.porosity
print triax.meanStress
print len(O.bodies)
###################################################
### 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 ###"
while 1:
O.run(100, 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(-100000-triax.meanStress)/100000<0.001:
break
##############################
### DEVIATORIC LOADING ###
##############################
##We move to deviatoric loading, let us turn internal compaction off to keep particles sizes constant
triax.internalCompaction=False
## Activating the HydrodynamicsLawLBM engine
Elbm.EngineIsActivated=True
## 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=-rate / 2.0
triax.goal3=-rate / 2.0
##we can change damping here. What is the effect in your opinion?
newton.damping=0.2
##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(unbalanced=unbalancedForce(),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],
devi = -triax.stress(triax.wall_top_id)[1] - (-triax.stress(triax.wall_right_id)[0]-triax.stress(triax.wall_front_id)[2]) / 2.0,
p = triax.meanStress,
i=O.iter)
stress_info.write(" %d " %(O.iter))
stress_info.write(" %6.4f " %(triax.stress(triax.wall_right_id)[0]))
stress_info.write(" %6.4f " %(triax.stress(triax.wall_top_id)[1]))
stress_info.write(" %6.4f " %(triax.stress(triax.wall_front_id)[2]))
#print("stress:")
#print(triax.stress(triax.wall_right_id)[0])
#print(triax.stress(triax.wall_top_id)[1])
#print(triax.stress(triax.wall_front_id)[2])
#print("strain:")
#print(triax.strain[0])
#print(triax.strain[1])
#print(triax.strain[2])
for i in range(3):
stress_info.write("%6.6f " %(triax.strain[i]))
stress_info.write("\n")
if O.iter % 2000 == 0:
for i in O.interactions:
contact_info.write("%d " %(i.id1))
contact_info.write("%d " %(i.id2))
contact_info.write("%.4f " %(i.phys.normalForce[0]))
contact_info.write("%.4f " %(i.phys.normalForce[1]))
contact_info.write("%.4f " %(i.phys.normalForce[2]))
contact_info.write("%.4f " %(i.phys.shearForce[0]))
contact_info.write("%.4f " %(i.phys.shearForce[1]))
contact_info.write("%.4f " %(i.phys.shearForce[2]))
contact_info.write("\n")
for i in range(len(O.bodies)):
if i > 5:
particle_info.write("%d " %(i))
if O.bodies[i].isClump:
particle_info.write("\n")
else:
particle_info.write("%f " %(O.bodies[i].state.pos[0]))
particle_info.write("%f " %(O.bodies[i].state.pos[1]))
particle_info.write("%f " %(O.bodies[i].state.pos[2]))
particle_info.write("%f " %(O.bodies[i].shape.radius))
particle_info.write("%d " %(O.bodies[i].clumpId))
particle_info.write("\n")
if 1:
## include a periodic engine calling that function in the simulation loop
O.engines=O.engines[0:5]+[PyRunner(iterPeriod=200,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')
### declare what is to plot. "None" is for separating y and y2 axis
plot.plots={'i':('unbalanced',),'i ':('s11','s22','s33'),' i':('e11','e22','e33'),'e22':('ev'),'p':('devi')}
### 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()
devi_test = -triax.stress(triax.wall_top_id)[1] - (-triax.stress(triax.wall_right_id)[0]-triax.stress(triax.wall_front_id)[2]) / 2.0
def stress_control1():
global devi_test
while devi_test < 50000:
O.run(100)
devi_test = -triax.stress(triax.wall_top_id)[1] - (-triax.stress(triax.wall_right_id)[0]\
-triax.stress(triax.wall_front_id)[2]) / 2.0
def stress_control2():
global devi_test
while devi_test > -50000:
O.run(100)
devi_test = -triax.stress(triax.wall_top_id)[1] - (-triax.stress(triax.wall_right_id)[0]\
-triax.stress(triax.wall_front_id)[2]) / 2.0
tic_toc = 0
while 1:
triax.goal2=rate
triax.goal1=-rate / 2.0
triax.goal3=-rate / 2.0
stress_control1()
triax.goal2 = - triax.goal2
triax.goal1 = - triax.goal1
triax.goal3 = - triax.goal3
stress_control2()
## We need to track the simulation with:
plot.saveDataTxt('results'+key)
tic_toc = tic_toc + 1
print tic_toc
if tic_toc > 5:
break
stress_info.close()
contact_info.close()
particle_info.close()
print 'Finished'
##### 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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