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[Robert Caulk <1813550@xxxxxxxxxxxxxxxxxx>]

flow.reuseOrdering functionality makes a copy of the factor for
efficient reuse. Algorithm was not freeing unnecessary copies.

Fixed with:

line 173 FLowBoundingSphereLinSolv.ipp:

	if (!multithread && factorExists && useSolver==4){
		if (getCHOLMODPerfTimings) gettimeofday (&start, NULL);	
		cholmod_l_free_sparse(&Achol, &com);
		cholmod_l_free_triplet(&cholT, &com);
		if (!reuseOrdering) {
			cholmod_l_free_factor(&L, &com);
>>>>++			cholmod_l_free_factor(&M, &com);  <<<<<<<++
			cholmod_l_finish(&com);
			if (getCHOLMODPerfTimings){
				gettimeofday (&end, NULL);
				cout << "CHOLMOD Time to finalize singlethreaded com " << ((end.tv_sec *1000000   + end.tv_usec ) - (start.tv_sec * 1000000 + start.tv_usec )) << endl;
			}
			cholmod_l_start(&com);
		}
		com.nmethods= 1; // nOrderingMethods; //1;
		com.method[0].ordering = CHOLMOD_METIS; // orderingMethod; //CHOLMOD_METIS;
		factorExists=false;	

        }

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https://bugs.launchpad.net/bugs/1813550

Title:
  FlowEngine memory leak - 600 Mb/hr

Status in Yade:
  Fix Committed

Bug description:
  Running examples/oedometer.py with 8000 spheres, flow.useSolver=4 and
  tracking RAM usage, I find we have a memory leak of 600 Mb/hr.

  examples/oedometer.py with num_spheres=8000:

  # -*- coding: utf-8 -*-

  from yade import pack

  num_spheres=8000# number of spheres
  young=1e6
  compFricDegree = 3 # initial contact friction during the confining phase
  finalFricDegree = 30 # contact friction during the deviatoric loading
  mn,mx=Vector3(0,0,0),Vector3(1,1,1) # corners of the initial packing

  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'))
  walls=aabbWalls([mn,mx],thickness=0,material='walls')
  wallIds=O.bodies.append(walls)

  sp=pack.SpherePack()
  sp.makeCloud(mn,mx,-1,0.3333,num_spheres,False, 0.95,seed=1) #"seed" make the "random" generation always the same
  sp.toSimulation(material='spheres')

  triax=TriaxialStressController(
   maxMultiplier=1.+2e4/young, # spheres growing factor (fast growth)
   finalMaxMultiplier=1.+2e3/young, # spheres growing factor (slow growth)
   thickness = 0,
   stressMask = 7,
   max_vel = 0.005,
   internalCompaction=True, # If true the confining pressure is generated by growing particles
  )

  newton=NewtonIntegrator(damping=0.2)

  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()],label="iloop"
   ),
   FlowEngine(dead=1,label="flow"),#introduced as a dead engine for the moment, see 2nd section
   GlobalStiffnessTimeStepper(active=1,timeStepUpdateInterval=100,timestepSafetyCoefficient=0.8),
   triax,
   newton
  ]

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

  while 1:
    O.run(1000, True)
    unb=unbalancedForce()
    if unb<0.001 and abs(-10000-triax.meanStress)/10000<0.001:
      break

  setContactFriction(radians(finalFricDegree))

  ## ______________   Oedometer section   _________________

  #A. Check bulk modulus of the dry material from load/unload cycles
  triax.stressMask=2
  triax.goal1=triax.goal3=0

  triax.internalCompaction=False
  triax.wall_bottom_activated=False
  #load
  triax.goal2=-11000; O.run(2000,1)
  #unload
  triax.goal2=-10000; O.run(2000,1)
  #load
  triax.goal2=-11000; O.run(2000,1)
  e22=triax.strain[1]
  #unload
  triax.goal2=-10000; O.run(2000,1)

  e22=e22-triax.strain[1]
  modulus = 1000./abs(e22)

  #B. Activate flow engine and set boundary conditions in order to get permeability
  flow.dead=0
  flow.defTolerance=0.3
  flow.meshUpdateInterval=200
  flow.fluidBulkModulus=2.2e9
  flow.useSolver=4
  flow.desiredPorosity=0
  flow.permeabilityFactor=1
  flow.viscosity=10
  flow.bndCondIsPressure=[0,0,1,1,0,0]
  flow.bndCondValue=[0,0,1,0,0,0]
  flow.boundaryUseMaxMin=[0,0,0,0,0,0]
  O.dt=0.1e-3
  O.dynDt=False

  O.run(1,1)
  Qin = flow.getBoundaryFlux(2)
  Qout = flow.getBoundaryFlux(3)
  permeability = abs(Qin)/1.e-4 #size is one, we compute K=V/∇H
  print "Qin=",Qin," Qout=",Qout," permeability=",permeability

  #C. now the oedometer test, drained at the top, impermeable at the bottom plate
  flow.bndCondIsPressure=[0,0,0,1,0,0]
  flow.bndCondValue=[0,0,0,0,0,0]
  flow.updateTriangulation=True #force remeshing to reflect new BC immediately
  newton.damping=0

  #we want the theoretical value from Terzaghi's solution
  #keep in mind that we are not in an homogeneous material and the small strain
  #assumption is not verified => we don't expect perfect match
  #there can be also an overshoot of pressure in the very beginning due to dynamic effects
  Cv=permeability*modulus/1e4
  zeroTime=O.time
  zeroe22 = - triax.strain[1]
  dryFraction=0.05 #the top layer is affected by drainage on a certain depth, we account for it here
  drye22 = 1000/modulus*dryFraction
  wetHeight=1*(1-dryFraction)

  def consolidation(Tv): #see your soil mechanics handbook...
   U=1
   for k in range(50):
    M=pi/2*(2*k+1)
    U=U-2/M**2*exp(-M**2*Tv)
   return U

  triax.goal2=-11000

  from yade import plot

  ## a function saving variables
  def history():
     plot.addData(e22=-triax.strain[1]-zeroe22,e22_theory=drye22+(1-dryFraction)*consolidation((O.time-zeroTime)*Cv/wetHeight**2)*1000./modulus,t=O.time,p=flow.getPorePressure((0.5,0.1,0.5)),s22=-triax.stress(3)[1]-10000)
     #plot.addData(e22=-triax.strain[1],t=O.time,s22=-triax.stress(2)[1],p=flow.MeasurePorePressure((0.5,0.5,0.5)))

  O.engines=O.engines+[PyRunner(iterPeriod=200,command='history()',label='recorder')]
  ##make nice animations:
  #O.engines=O.engines+[PyRunner(iterPeriod=200,command='flow.saveVtk()')]

  from yade import plot
  plot.plots={'t':('e22','e22_theory',None,'s22','p')}
  plot.plot()
  O.saveTmp()
  O.timingEnabled=1
  from yade import timing
  print "starting oedometer simulation"
  O.run(200,1)
  timing.stats()

  ## Make more steps to see the convergence to the stationnary solution

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