DAMASK_EICMD/processing/misc/yieldSurface.py

194 lines
5.3 KiB
Python
Executable File

#!/usr/bin/python
# -*- coding: UTF-8 no BOM -*-
import numpy as np
from scipy.optimize import curve_fit
from scipy.linalg import svd
import threading,time,os,subprocess,shlex
import damask
def execute(cmd,dir='./'):
initialPath=os.getcwd()
out = ''
line = True
process = subprocess.Popen(shlex.split(cmd),stdout=subprocess.PIPE,stderr = subprocess.STDOUT)
while line:
line = process.stdout.readline()
out += line
os.chdir(initialPath)
def asFullTensor(voigt):
return np.array([[voigt[0],voigt[3],voigt[5]],\
[voigt[3],voigt[1],voigt[4]],\
[voigt[5],voigt[4],voigt[2]]])
def Hill48(x, F,G,H,L,M,N):
a= F*(x[1]-x[2])**2 + G*(x[2]-x[0])**2 + H*(x[0]-x[1])** + \
2*L*x[4]**2 + 2*M*x[5]**2 + 2*N*x[3]**2 -1.
return a.ravel()
def vonMises(x, S_y):
sv=np.zeros(0,'d')
for i in xrange(np.shape(x)[1]):
U, l, Vh = svd(np.array(x[:,i]).reshape(3,3))
sv = np.append(sv,l)
sv = sv.reshape(3,np.shape(x)[1])
ooo= (sv[2,:]-sv[1,:])**2+(sv[1,:]-sv[0,:])**2+(sv[0,:]-sv[2,:])**2-2*S_y**2
return ooo
#---------------------------------------------------------------------------------------------------
class Loadcase():
#---------------------------------------------------------------------------------------------------
'''
Class for generating load cases for the spectral solver
'''
# ------------------------------------------------------------------
def __init__(self):
print('using the random load case generator')
def getNext(self,N=0):
defgrad=['*']*9
stress =[0]*9
values=(np.random.random_sample(9)-.5)*scale*2
main=np.array([0,4,8])
np.random.shuffle(main)
for i in main[:2]: # fill 2 out of 3 main entries
defgrad[i]=1.+values[i]
stress[i]='*'
for off in [[1,3,0],[2,6,0],[5,7,0]]: # fill 3 off-diagonal pairs of defgrad (1 or 2 entries)
off=np.array(off)
np.random.shuffle(off)
for i in off[0:2]:
if i != 0:
defgrad[i]=values[i]
stress[i]='*'
return 'f '+' '.join(str(c) for c in defgrad)+\
' p '+' '.join(str(c) for c in stress)+\
' incs %s'%incs+\
' time %s'%duration
#---------------------------------------------------------------------------------------------------
class Criterion(object):
#---------------------------------------------------------------------------------------------------
'''
Fitting to certain criterion
'''
def __init__(self,name):
self.name = name.lower()
if self.name not in ['hill48','vonmises']: print('Mist')
print('using the %s criterion'%self.name)
self.popt = 0.0
def fit(self,stress):
try:
popt, pcov = curve_fit(Hill48, stress, np.zeros(np.shape(stress)[1]))
print 'Hill 48', popt
except Exception as detail:
print detail
pass
popt, pcov = curve_fit(vonMises, stress, np.zeros(np.shape(stress)[1]))
print 'von Mises', popt
#---------------------------------------------------------------------------------------------------
#---------------------------------------------------------------------------------------------------
'''
Runner class
'''
class myThread (threading.Thread):
def __init__(self, threadID):
threading.Thread.__init__(self)
self.threadID = threadID
def run(self):
s.acquire()
conv=converged()
s.release()
while not conv:
doSim(4.,self.name)
s.acquire()
conv=converged()
s.release()
def doSim(delay,thread):
s.acquire()
me=getLoadcase()
print('generating loadcase for sim %i from %s'%(me,thread))
f=open('%s.load'%me,'w')
f.write(myLoad.getNext(me))
f.close()
print('starting simulation %i from %s'%(me,thread))
s.release()
execute('DAMASK_spectral -l %i -g 20grains16x16x16'%me)
s.acquire()
print('startin post processing for sim %i from %s'%(me,thread))
s.release()
execute('postResults --cr f,p 20grains16x16x16_%i.spectralOut'%me)
execute('addCauchy ./postProc/20grains16x16x16_%i.txt'%me)
execute('addStrainTensors -l -v ./postProc/20grains16x16x16_%i.txt'%me)
execute('addMises -s Cauchy -e ln(V) ./postProc/20grains16x16x16_%i.txt'%me)
refFile = open('./postProc/20grains16x16x16_%i.txt'%me)
table = damask.ASCIItable(refFile)
table.head_read()
for l in ['Mises(ln(V))','1_Cauchy']:
if l not in table.labels: print '%s not found'%l
while table.data_read():
if float(table.data[table.labels.index('Mises(ln(V))')]) > 0.002:
yieldStress = np.array(table.data[table.labels.index('1_Cauchy'):table.labels.index('9_Cauchy')+1],'d').reshape(3,3)
s.acquire()
print('startin fitting for sim %i from %s'%(me,thread))
global stressAll
stressAll=np.append(stressAll,yieldStress.reshape(9))
stressAll=stressAll.reshape(9,len(stressAll)//9)
myFit.fit(stressAll)
s.release()
def getLoadcase():
global N_simulations
N_simulations+=1
return N_simulations
def converged():
global N_simulations
global maxN_simulations
if N_simulations < maxN_simulations:
return False
else:
return True
# main
minN_simulations=20
maxN_simulations=20
N_simulations=0
s=threading.Semaphore(1)
scale = 0.02
incs = 10
duration = 10
stressAll=np.zeros(0,'d')
myLoad = Loadcase()
myFit = Criterion('Hill48')
N_threads=3
t=[]
for i in range(N_threads):
t.append(myThread(i))
t[i].start()
for i in range(N_threads):
t[i].join()
print "Exiting Main Thread"