# -*- encoding=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. *
#*************************************************************************/

## Example script for using the DEM-PFV coupling introduced with E. Catalano, as reported in:
## * [Chareyre2012a] Chareyre, B., Cortis, A., Catalano, E., Barthélemy, E. (2012), Pore-scale modeling of viscous flow and induced forces in dense sphere packings. Transport in Porous Media (92), pages 473-493. DOI 10.1007/s11242-011-9915-6
## http://dx.doi.org/10.1007/s11242-011-9915-6
## * [Catalano2014a] Catalano, E., Chareyre, B., Barthélémy, E. (2013), Pore-scale modeling of fluid-particles interaction and emerging poromechanical effects. International Journal for Numerical and Analytical Methods in Geomechanics. DOI 10.1002/nag.2198
## http://arxiv.org/pdf/1304.4895.pdf
## Also used in:
## * Tong et al.2012 (http://dx.doi.org/10.2516/ogst/2012032)
## * Sari et al 2011 (http://people.3sr-grenoble.fr/users/bchareyre/pubs/SariChareyreCatalanoPhilippeVincens_Particles2011.pdf)

## The DEM-PFV is applied here to 1D consolidation (oedometer test). The example includes the determination of oedometer modulus Ee and permeability K.
## The 1D consolidation is simulated as a coupled problem and the analytical solution corresponding to the abovementionned Ee and K is used for comparison.
## See triax-tutorial/script-session1.py for more detailed explanations of the packing generation procedure.

## ______________   First section, similar to triax-tutorial/script-session1.py  _________________
from yade import pack

num_spheres = 1000  # 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.useSolver = 3
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', 'b--'), ('e22_theory', 'b-'), None, ('s22', 'g--'), ('p', 'g-'))}
plot.plot()
O.saveTmp()
O.timingEnabled = 1
from yade import timing

print("starting oedometer simulation")
O.run(200, 1)
timing.stats()

print("\nPress ▶ (the start button) to see graph.\n")

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