i run this code with phi=0.34 and dp=10e-6 and the code merged about 14 pores . while the article merged about 9 pores for the same phi and dp

[masoodmoghaddam]

in this section of code: radiuos=PSR*averageporeaize /1.8#true value foe radius is /2 we set the radiuos in order to reproduce fig.8 of paper. now I have changed the code and it should be determined code is not working good or radiuos should be reset?

import openpnm as op import random import numpy as np import scipy as sp import matplotlib.pyplot as plt from openpnm.utils import PrintableDict, logging, Workspace ws = Workspace() logger = logging.getLogger(name)

------------------------------------------------ Functions --------------------------------------

def Merge_pores(network, pores, Nei,Cordinate, labels=['merged']):

Assert that pores is list of lists

try:
    len(pores[0])
except (TypeError, IndexError):
    pores = [pores]        
N = len(pores)
NBs, XYZs = [], []
for Ps in pores:
    NBs.append(Nei)
    XYZs.append(Cordinate)
op.topotools.extend(network, pore_coords=XYZs, labels=labels)
Pnew = network.Ps[-N::]
pores_set = [set(items) for items in pores]
NBs_set = [set(items) for items in NBs]
ps1, ps2 = [], []    
from itertools import combinations
for i, j in combinations(range(N), 2):
    if not NBs_set[i].isdisjoint(pores_set[j]):
        ps1.append([network.Ps[-N+i]])
        ps2.append([network.Ps[-N+j]])
# Add (possible) connections between the new pores
op.topotools.connect_pores(network, pores1=ps1, pores2=ps2, labels=labels)
# Add connections between the new pores and the rest of the network
op.topotools.connect_pores(network, pores2=sp.split(Pnew, N), pores1=NBs, labels=labels)
# Trim merged pores from the network
op.topotools.trim(network=network, pores=sp.concatenate(pores))

Ps = pn.find_nearby_pores(pores=network.Ps[-len(pores)::], r=PtoP, flatten=True)
op.topotools.trim(network=network, pores=Ps)

def MacroProsity(prosity): Nnp=int((1-prosity)Nni) radiuos=PSRaverageporeaize /1.8#true value foe radius is /2 Ps = pn.find_nearby_pores(pores=random.choice(pn.pores(labels=['surface'], mode='not')), r=PtoP*2, flatten=True) op.topotools.merge_pores(network=pn, pores=Ps, labels=['merged']) while len(pn.pores(labels=['merged'], mode='not'))>Nnp: Point=random.choice(pn.pores(labels=['surface','merged'], mode='not')) pores = pn.find_nearby_pores(pores=Point, r=radiuos, flatten=True) pores=[i for i in pores if i not in pn.pores(labels=['surface','merged'])] if len(pores)>0: neighbor=pn.find_neighbor_pores(pores=pores, mode='union', flatten=True, include_input=False) cord=pn['pore.coords'][neighbor].mean(axis=0) Merge_pores(network=pn, pores=pores, Nei=neighbor,Cordinate=cord, labels=['merged'])

print('**** ',1- len(pn.pores(labels=['merged'], mode='not'))/Nni)

        D=(1- len(pn.pores(labels=['merged'], mode='not'))/Nni)/prosity*50
        print('[','='*int(D), '>','.'*(50-int(D)),']')
# Deleting Pores which placed very close (less than initial pore to pore distance of the grid) to merged porse         
op.topotools.trim(network=pn, pores=pn.find_nearby_pores(pores=pn.pores(labels=['merged']), r=PtoP, flatten=True))
# Deleting pores with just one throat
op.topotools.trim(network=pn, pores=[sp.where(pn.num_neighbors(pn.pores()) == 1)])

------------------------------------------------ contorol parameters --------------------------------------

dp=10e-6 #particle diameter PtoP=10e-8 #pore to pore espacing My idea =dp/Numberofpores Numberofpores=int(dp/PtoP) #number of pores on radius phi=0.34 PSR=100 # pore size ratio averageporeaize=1.6e-8 #average pore size

------------------------------------------------ circular pore pn generation --------------------------

pn = op.network.Cubic(shape=[Numberofpores, Numberofpores, 1], spacing=PtoP,connectivity=6) middlepoint=pn.Np/2+Numberofpores/2 Ps = pn.find_nearby_pores(pores=(middlepoint), r=dp/2, flatten=True) pn['pore.dummy_1']=[False] * pn.Np pn['pore.dummy_1'][Ps]=True pn['pore.dummy_1'][int(middlepoint)]=True Pss=pn.pores('pore.dummy_1',mode='not')

------------------------------------------------ finding boundary pores --------------------------------------

Jalili, [۱۲.۱۲.۱۸ ۱۸:۰۹] Pb = pn.find_nearby_pores(pores=(middlepoint), r=(dp/2-PtoP), flatten=True) pn['pore.surface']=[True] * pn.Np pn['pore.surface'][Pb]=False pn['pore.surface'][int(middlepoint)]=False

------------------------------------------------ triming forcircular pore pn generation ------------------

op.topotools.trim(network=pn, pores=Pss) Nni=pn.Np

------------------------------------------------ Hierarchical pn generation ------------------------------

MacroProsity(prosity=phi)

[samanjalilian]

changing 1.8 to 1.5 solved the problem i think

[samanjalilian]

dp=10e-6, phi=0.34