# -*- 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 unbtargetPorosity: ## 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)