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final92.py
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final92.py
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# -*- coding: utf-8 -*-
"""
Created on Sat Mar 10 23:24:23 2018
@author: bhavesh
Updated Lagrangian Finite Elasto-plasticity
4-noded quad elements
fixme:
- implement finite deformation using box 9.1 (Simo-Hughes)
- extrapolate stresses from gauss points to nodes
- general framework to export a vtk file from solution
- the invariants are those of Febar and not Fe, and hence premultiply
accordingly by J**(-2/3) (Je=J)--> only for this case (partI)
"""
import numpy as np
import numpy.linalg as la
import matplotlib.pyplot as plt
from matplotlib import rc
import matplotlib
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.ticker import MaxNLocator
from scipy.optimize import fsolve,minimize
import pandas as pd
import matplotlib.tri as mptri
from matplotlib.ticker import AutoMinorLocator
import scipy.sparse as sp
##################################################################
rc('font',**{'family':'lmodern','sans-serif':['Helvetica']})
rc('text', usetex=True)
matplotlib.rcParams['xtick.direction']='in'
matplotlib.rcParams['ytick.direction']='in'
matplotlib.rcParams['xtick.top']=True
matplotlib.rcParams['ytick.right']=True
matplotlib.rcParams['lines.linewidth']=3
rc('xtick',labelsize=18)
rc('ytick',labelsize=18)
mx=AutoMinorLocator(10)
my=AutoMinorLocator(10)
##################################################################
class geometry() : #nD geometry (quads -- check!, hex -- check!)
def __init__(self,Eltype,Tf,E,nu):
self.tolNR=1.e-7
self.maxiter=100
self.xtol=0.
if Eltype[0]=='L':
self.A=8.e-1
self.B=1.
ne=10
self.nLnodes=ne+1
self.nQnodes=2*ne+1
self.mu=1.e5
kap=1.e1*self.mu
self.lam=kap+2.*self.mu/3
self.Po=2.5e5*np.linspace(0,1,100)
self.epS=2.*np.linspace(1,20,100)
elif Eltype[0]=='Q':
self.xlength=1.
self.ylength=1.
self.nx=1
self.ny=1
self.nDim=2 #No. of dof per node, it is essentially the dimension of the problem
self.thck=1.
self.nSteps=100
self.mu=40.
kap=1.e1*self.mu
self.lam=40.
elif Eltype[0]=='H':
self.xlength=3.
self.ylength=3.
self.zlength=3.
self.nx=1
self.ny=1
self.nz=1
self.nDim=3 #No. of dof per node, it is essentially the dimension of the problem
self.nSteps=100
self.mu=0.412
self.lam=self.mu*(E-2*self.mu)/(3*self.mu-E)
self.kap=self.lam+2./3*self.mu
self.Ko=12000000000000.
self.Kp=900.
self.Hp=2.5
self.NGp=8 # number of gauss point, remember to change this if you change integration order
self.Sf=1 #Scale factor for deformed plot
Ee=np.eye(3)
self.Eye=0.5*(np.einsum('ik,jl->ijkl',Ee,Ee)+np.einsum('il,jk->ijkl',Ee,Ee))
self.T=np.linspace(0.,Tf,self.nSteps+1)
self.bta=0.2 # strain factor
self.C1=0.165
self.C2=0.0
def meshgn(): # specify starting point, and step size to generate uniform grid of meshpoints and connectivity
xs=0.;ys=0.;zs=0.;
xe=float(format(xs+geom.xlength+geom.xlength/geom.nx,'.15f'))
ye=float(format(ys+geom.ylength+geom.ylength/geom.ny,'.15f'))
ze=float(format(zs+geom.zlength+geom.zlength/geom.nz,'.15f'))
stepx=float(format(geom.xlength/geom.nx,'.15f'))
stepy=float(format(geom.ylength/geom.ny,'.15f'))
stepz=float(format(geom.zlength/geom.nz,'.15f'))
mesh=np.einsum('ijkl->ikjl',np.mgrid[xs:xe:stepx,ys:ye:stepy,zs:ze:stepz]).reshape(3,-1).T
# connectivity
col1=np.hstack(((np.arange(geom.nz*i+(i+1),(geom.nz+1)*(i+1),1) for i in range(geom.nx)))) #Layer 1 on the first face
col1=np.hstack((( (geom.nz+1)*(geom.nx+1) )*i+col1 for i in range(geom.ny)))
conn=np.vstack((col1,
col1+1,
col1+geom.nz+1,
col1+geom.nz+2,
col1+(geom.nz+1)*(geom.nx+1),
col1+1+(geom.nz+1)*(geom.nx+1),
col1+2+(geom.nz+1)*(geom.nx+1),
col1+3+(geom.nz+1)*(geom.nx+1))).T-1 #stack scalar sum to generate connectivity
return {'msh':mesh,
'con':conn
}
class GPXi():
def __init__(self,ordr):
from numpy.polynomial.legendre import leggauss #Gauss-Legendre Quadrature for 1D (proxy 2D quads -- check, 3D hex -- not checked)
self.xi=leggauss(ordr)[0] #nodes
self.wght=leggauss(ordr)[1] #weights
class basis(): # defined on the canonical element (1D : [-1,1], 2D (Q): [-1,1] x [-1,1], 3D (H): [-1,1]^3 )
def __init__(self,eltype,deg):
from sympy import Symbol,diff,Array,lambdify,tensorproduct,Matrix,flatten
if eltype=='L': #L: 1D FE
z=Symbol('z')
if deg==2.: # denotes the number of nodes
N=1/2*Array([1-z,1+z])
dfN=diff(N,z)
self.Ns=lambdify(z,N,'numpy')
self.dN=lambdify(z,dfN,'numpy')
elif deg==3.:
N=1/2*Array([z*(z-1),2*(1+z)*(1-z),z*(1+z)])
dfN=diff(N,z)
self.Ns=lambdify(z,N,'numpy')
self.dN=lambdify(z,dfN,'numpy')
else:
raise Exception('Element type not implemented yet')
elif eltype=='Q': #Q: 2D FE : Node-numbering <-- "tensor-product" starting from bottom left corner
if deg==4.:
xi=Symbol('xi');eta=Symbol('eta')
arr1=1/2*Array([1-eta,1+eta]);arr2=1/2*Array([1-xi,1+xi])
N=tensorproduct(arr1,arr2);
dfN=Matrix(flatten(diff(N,xi))).col_join(Matrix(flatten(diff(N,eta))))
self.Ns=lambdify((xi,eta),flatten(N),'numpy')
self.dN=lambdify((xi,eta),dfN,'numpy')
elif deg==9.:
xi=Symbol('xi');eta=Symbol('eta')
arr1=Array([eta*(eta-1)/2,(1-eta**2),eta*(eta+1)/2]);arr2=Array([xi*(xi-1)/2,(1-xi**2),xi*(xi+1)/2])
N=tensorproduct(arr1,arr2);
dfN=Matrix(flatten(diff(N,xi))).col_join(Matrix(flatten(diff(N,eta))))
self.Ns=lambdify((xi,eta),flatten(N),'numpy')
self.dN=lambdify((xi,eta),dfN,'numpy')
elif eltype=='H':
if deg==8.:
xi=Symbol('xi');eta=Symbol('eta');rho=Symbol('rho')
arr1=1/2*Array([1-eta,1+eta]);arr2=1/2*Array([1-xi,1+xi]);arr3=1/2*Array([1-rho,1+rho])
N=tensorproduct(arr1,arr2,arr3);
dfN=Matrix(flatten(diff(N,xi))).col_join(Matrix(flatten(diff(N,eta)))).col_join(Matrix(flatten(diff(N,rho))))
self.Ns=lambdify((xi,eta,rho),flatten(N),'numpy')
self.dN=lambdify((xi,eta,rho),dfN,'numpy')
else:
raise Exception('Only 1D, 2D and 3D continuum elements implemented')
class DWDIi(): # the substitution changes for a 3D element
def __init__(self,ndim):
from sympy import Symbol,diff,lambdify,log,transpose,Matrix
I1=Symbol('I1');J=Symbol('J');I2=Symbol('I2')
W = geom.C1*(J**(-2./3)*I1-3)+geom.C2*(J**(-4./3)*I2-3.)+geom.kap/2.*(1/2.*(J**2-1.)-log(J)) #change W here to include the modified Neo-Hookean
dWdI1=diff(W,I1);dWdI2=diff(W,I2);dWdJ=diff(W,J);
d2WdI12=diff(dWdI1,I1);d2WdI2dI1=diff(dWdI1,I2);d2WdJdI1=diff(dWdI1,J);
d2WdI1dI2=diff(dWdI2,I1);d2WdI22=diff(dWdI2,I2);d2WdJdI2=diff(dWdI2,J);
d2WdI1dJ=diff(dWdJ,I1);d2WdI2dJ=diff(dWdJ,I2);d2WdJ2=diff(dWdJ,J);
if ndim==2 or ndim==3:
f11=Symbol('f11');f12=Symbol('f12');f13=Symbol('f13');
f21=Symbol('f21');f22=Symbol('f22');f23=Symbol('f23');
f31=Symbol('f31');f32=Symbol('f32');f33=Symbol('f33')
f=Matrix([f11,f12,f13,f21,f22,f23,f31,f32,f33]);
I1subs=f[0]**2 + f[1]**2 + f[2]**2 + f[3]**2 + f[4]**2 + f[5]**2 + f[6]**2 + f[7]**2 + f[8]**2;
I2subs=0.5*(I1subs**2-((f[0]**2 + f[3]**2 + f[6]**2)**2 + 2*(f[0]*f[1] + f[3]*f[4] + f[6]*f[7])**2 + (f[1]**2 + f[4]**2 + f[7]**2)**2 + 2*(f[0]*f[2] + f[3]*f[5] + f[6]*f[8])**2 + 2*(f[1]*f[2] + f[4]*f[5] + f[7]*f[8])**2 + (f[2]**2 + f[5]**2 + f[8]**2)**2));
Jsubs=f[0]*(f[4]*f[8]-f[7]*f[5])-f[1]*(f[3]*f[8]-f[6]*f[5])+f[2]*(f[3]*f[7]-f[6]*f[4])
dWdI1=dWdI1.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)]) #substituting I1, in terms of
dWdI2=dWdI2.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
dWdJ=dWdJ.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdI12=d2WdI12.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdI12=d2WdI12.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdI2dI1=d2WdI2dI1.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdJdI1=d2WdJdI1.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdI1dI2=d2WdI1dI2.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdI22=d2WdI22.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdJdI2=d2WdJdI2.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdI1dJ=d2WdI1dJ.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdI2dJ=d2WdI2dJ.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
d2WdJ2=d2WdJ2.subs([(I1,I1subs),(I2,I2subs),(J,Jsubs)])
# Convert to lambda functions
self.DWDI1=lambdify(f,dWdI1,'numpy')
self.DWDI2=lambdify(f,dWdI2,'numpy') #output the derivative of invariants at the given F (input) as lambda function
self.DWDJ=lambdify(f,dWdJ,'numpy')
self.D2WDI12=lambdify(f,d2WdI12,'numpy')
self.D2WDI2DI1=lambdify(f,d2WdI2dI1,'numpy')
self.D2WDJDI1=lambdify(f,d2WdJdI1,'numpy')
self.D2WDI1DI2=lambdify(f,d2WdI1dI2,'numpy')
self.D2WDI22=lambdify(f,d2WdI22,'numpy')
self.D2WDJDI2=lambdify(f,d2WdJdI2,'numpy')
self.D2WDI1DJ=lambdify(f,d2WdI1dJ,'numpy')
self.D2WDI2DJ=lambdify(f,d2WdI2dJ,'numpy')
self.D2WDJ2=lambdify(f,d2WdJ2,'numpy')
def locmat(nodes,de,qe,alphe,eplast): #local stiffness (jacobian) and force (residual) over the reference element
"""
Storing the Gauss-points, local basis-functions, local gradients, and global gradients.
Forming the B-matrix using kron (trick -- check notes!)
nodes --- all xs, followed by all ys followed by all zs
de --- all dx, followed by all dy, followed by all dz
"""
Xi=np.tile(np.repeat(GP.xi,OrdGauss),OrdGauss)
Eta=np.repeat(GP.xi.T,2*OrdGauss).flatten()
Rho=np.tile(GP.xi,2*OrdGauss) #Generating Gauss-Points through numpy (--check with jupyter notebook)
dof=de.reshape(de.size,-1,1).repeat(len(Xi),axis=-1) #arranging dof for (dot) product with B (len(Xi) and not len(GP.xi)) !!!
Wg=np.repeat(GP.wght,2*OrdGauss)
Nshp=np.kron(np.eye(geom.nDim).reshape(geom.nDim,geom.nDim,-1),B.Ns(Xi,Eta,Rho)) #kron has to be taken on the nDim (and not OrdGauss)
gDshpL=np.array(B.dN(Xi,Eta,Rho)).reshape(geom.nDim,int(Eltype[1]),-1) #local derivatives
Je=np.einsum('ilk,lj->ijk',gDshpL,nodes.reshape(geom.nDim,-1).T) #computing the jacobian (remains the same, even for 3D ? -- check ?)
detJ=np.dstack(la.det(Je[:,:,i]) for i in range(Xi.size)) # 1x1xNgP # try making it faster by removing the generator
Jeinv=np.dstack(la.inv(Je[:,:,i]) for i in range(Xi.size)) # 3x3xNgP #avoid computing inverse on a loop (--check ?)
gDshpG=np.einsum('ilk,ljk->ijk',Jeinv,gDshpL) #global derivatives (remains the same, even for 3D ? )
Bmat=np.kron(np.eye(geom.nDim).reshape(geom.nDim,geom.nDim,-1),gDshpG)
gradU=np.einsum('ilk,ljk->ijk',Bmat,dof) # 9x1xNgP #remember that gradU is never symmetric !!!
"""
Computing the deformation gradient (F11,F12,F13...,F33).T = B*de, and first piola (S) --> (S11,S12,S13,.....,S33),
Multiplying by the Gauss-weights, and calculating the element residual (res)
"""
F=gradU+np.eye(geom.nDim).reshape(-1,1,1).repeat(len(Xi),axis=-1) #convert to 3x3xNgP and the take det(F) and inv(F)
detF=np.dstack(la.det(F.reshape(geom.nDim,geom.nDim,-1)[:,:,i] )for i in range(Xi.size)) # 1x1xNgP
# Calculating the derivatives of W wrt invariants (for stress)
WpI1=dWdIi.DWDI1(*F)
WpI2=dWdIi.DWDI2(*F)
WpJ=dWdIi.DWDJ(*F)
# Calculating the derivatives of W wrt invariants (for modulus tangent)
WppI1=dWdIi.D2WDI12(*F)
WppI2I1=dWdIi.D2WDI2DI1(*F)
WppJI1=dWdIi.D2WDJDI1(*F)
WppI1I2=dWdIi.D2WDI1DI2(*F)
WppI2=dWdIi.D2WDI22(*F)
WppJI2=dWdIi.D2WDJDI2(*F)
WppI1J=dWdIi.D2WDI1DJ(*F)
WppI2J=dWdIi.D2WDI2DJ(*F)
WppJ=dWdIi.D2WDJ2(*F)
Finv=(np.dstack(la.inv(F.reshape(geom.nDim,geom.nDim,-1)[:,:,i]) for i in range(Xi.size))).reshape(-1,1,geom.NGp) #avoid computing inverse on the loop for the deformation gradient
F3b3=F.reshape(geom.nDim,geom.nDim,-1); Finv3b3=Finv.reshape(geom.nDim,geom.nDim,-1) #reshaping F and Finv for multiplication
I1f=np.einsum('ijk,ijk->k',F3b3,F3b3) #calculating the first invariant at GP
FinvT=np.einsum('ijk->jik',Finv.reshape(geom.nDim,geom.nDim,-1))
FFt=(np.einsum('iqg,qjg->ijg',np.einsum('ipg,qpg->iqg',F3b3,F3b3),F3b3)).reshape(-1,1,geom.NGp)
S=WpI1*2*F+(WpJ*detF)*FinvT.reshape(-1,1,geom.NGp)+2*WpI2*(I1f*F-FFt) - (2*geom.mu*eplast).reshape(-1,1,geom.NGp) #[np.array([0,3,6,1,4,7,2,5,8],int)] #notice the swap of axes for transpose (of the inverse)
"""
RADIAL RETURN MAPPING ALGORITHM
Checking if the stress-state is admissible, f(....) <= 0
Check for the yield surface, the backstress and the plastic strain
Compute Cep_ijkl separately
"""
epl=eplast.copy()
eye3d=np.eye(geom.nDim).reshape(geom.nDim,geom.nDim,-1).repeat(geom.NGp,axis=-1)
epSS=0.5*(F3b3+np.einsum('ijk->jik',F3b3)-2.*eye3d)
edev=epSS-1./3*np.einsum('iik->k',epSS)*eye3d # print(epSS[:,:,0])
strial=2*geom.mu*(edev-eplast) # trial deviator
sEff=strial-qe
ftrial = la.norm(sEff,axis=(0,1))-(2./3)**0.5*(geom.Ko+geom.Kp*alphe) # Yield-surface boundary (NGp)
plsTidx = ftrial > 0. # Boolean array to keep track of plasticity(True-Plastic, False-Elastic!)
# Assume elastic response and then check later on
dgam=np.zeros(geom.NGp)
nNp1=np.zeros((geom.nDim,geom.nDim,geom.NGp))
thta=np.ones(geom.NGp)
thtab=np.zeros(geom.NGp)
dgam[plsTidx]=3*ftrial[plsTidx]/(2*(geom.Hp+geom.Kp+3*geom.mu)) #evolve dgam only at the yielded gauss points
nNp1[:,:,plsTidx]=(sEff[:,:,plsTidx]/la.norm(sEff[:,:,plsTidx],axis=(0,1)))
# S = (strial+geom.kap*np.einsum('iik->k',epSS)*eye3d - 2*geom.mu*dgam*nNp1).reshape(-1,1,geom.NGp)
thta[plsTidx]=1.-2.*geom.mu*dgam[plsTidx]/la.norm(sEff[:,:,plsTidx],axis=(0,1))
thtab[plsTidx]=((1.+1/(3*geom.mu)*(geom.Kp+geom.Hp))**(-1) + thta[plsTidx] - 1.).copy()
# S[:,:,plsTidx] = ((strial + geom.kap*np.einsum('iik->k',epSS)*eye3d - 2*geom.mu*(dgam*nNp1)).reshape(-1,1,geom.NGp))[:,:,plsTidx]
alphe+= (2./3)**0.5*dgam
qe+= 2./3*geom.Hp*dgam*nNp1 #update qe in place and store in n+1
epl += dgam*nNp1
# S = (strial+geom.kap*np.einsum('iik->k',epSS)*eye3d - 2*geom.mu*dgam*nNp1).reshape(-1,1,geom.NGp)
fac=Wg*detJ
res=np.einsum('lik,ljk->ij',Bmat,fac*S) #double contraction along axis 1 and 2 (of B)
"""
Computing the Consistent Tangent: B^T *C *B <-- Cijkl, check notes
Cijkl = 4*W''_(I1) Fij Fkl + 2 W'_(I1) delik deljl + J**2*W''(J) F-1ji F-1lk +J*W'(J) F-1ji F-1lk - J W'_(J) F-1jk F-1li
"""
# Helpful variables:
#This C does not have minor symmetry (relates S to F) , only major symmetry
#
Bta=2*(I1f*F3b3-np.einsum('iqk,qjk->ijk',np.einsum('ipk,qpk->iqk',F3b3,F3b3),F3b3)) #check with hand
DFDWDI1=WppI1*2*F3b3+WppI2I1*Bta+WppJI1*detF*np.einsum('ijk->jik',Finv3b3)
DFDWDI2=WppI1I2*2*F3b3+WppI2*Bta+WppJI2*detF*np.einsum('ijk->jik',Finv3b3)
DFDWDJ=WppI1J*2*F3b3+WppI2J*Bta+WppJ*detF*np.einsum('ijk->jik',Finv3b3)
IDGp = (np.einsum('ik,jl->ijkl',np.eye(geom.nDim),np.eye(geom.nDim))[:,:,:,:,np.newaxis]).repeat(geom.NGp,axis=-1)
# EyeGp = geom.Eye[:,:,:,:,np.newaxis].repeat(geom.NGp,axis=-1)
C=(np.einsum('ijg,klg->ijklg',2*F3b3,DFDWDI1)+2*WpI1*IDGp+np.einsum('ijg,klg->ijklg',Bta,DFDWDI2)
+2*WpI2*(2*np.einsum('ijg,klg->ijklg',F3b3,F3b3)+I1f*IDGp
-np.einsum('ilg,kjg->ijklg',F3b3,F3b3)
-np.einsum('ljg,ikg->ijklg',np.einsum('qlg,qjg->ljg',F3b3,F3b3),(np.eye(geom.nDim)[:,:,np.newaxis]).repeat(geom.NGp,axis=-1))
-np.einsum('ikg,jlg->ijklg',np.einsum('ipg,kpg->ikg',F3b3,F3b3),(np.eye(geom.nDim)[:,:,np.newaxis]).repeat(geom.NGp,axis=-1)))
+detF*np.einsum('jig,klg->ijklg',Finv3b3,DFDWDJ)+WpJ*(detF*np.einsum('jig,lkg->ijklg',Finv3b3,Finv3b3)
-detF*np.einsum('jkg,lig->ijklg',Finv3b3,Finv3b3))).reshape(9,9,-1,order='A')
Cauch=(1./detF*np.einsum('ikg,jkg->ijg',S.reshape(3,3,-1),F3b3)).reshape(-1,1,geom.NGp)
# print(WppI1)
#
# Some useful variables and shapes of previous variables:
# nNp1 = 3x3xNGp
# dgam = NGp (hoping that scalar multiplication along axis3 works!)
# thta = NGp
# thtab= NGp
# la.norm(sEff,2,axis=(0,1)) = NGp
# Now start doing einsum to generate Cep, by first introducing a
# new axis at the end that keeps track of Gauss-points for the above
# n-d arrays
# IdGp : del ij del kl x NGp
# EyeGP : Eye extended along 5th dimension (fourth order identity tensor repeat along fifth dimension)
#
# C=(2*geom.mu*EyeGp+geom.lam*IDGp).reshape(9,9,-1,order='A')
# Cep=(geom.kap*IDGp+2*geom.mu*thta*(EyeGp-1./3*IDGp) - 2.*geom.mu*thtab*np.einsum('ijg,klg->ijklg',nNp1,nNp1)).reshape(9,9,-1,order='A')
Cep=C.copy()
Cep1111=Cep[0,0,0];Cep1212=Cep[1,1,0];Cep2222=Cep[4,4,0];Cep3333=Cep[-1,-1,0]
D=np.einsum('lik,lpk,pjk->ij',Bmat,Cep*fac,Bmat) #Check the multiplication once for a simple case!
IntpG=np.einsum('ilj,l->ij',Nshp,nodes)
return D,res.flatten(),Cauch,F,IntpG,qe,alphe,epl,Cep1111,Cep2222,Cep1212,Cep3333
Eltype='H8'
OrdGauss=2 #No. of Gauss-points (in 2D: # of points in each direction counted the same way as local nodes)
Tf = 1.0
globE=1.199
globnu=0.25
geom=geometry(Eltype,Tf,globE,globnu)
B=basis(Eltype[0],float(Eltype[1]))
GP=GPXi(OrdGauss)
dWdIi=DWDIi(geom.nDim)
meshxyz=meshgn()['msh']
conVxyz=meshgn()['con']
dof=1.e9*np.ones(meshxyz.size) #initializing dofs (displacement of nodes)
def assembly(disp,q,alph,Ep):
globK=0.*np.eye(disp.size)
globF=np.zeros(disp.size)
strs=np.zeros((len(conVxyz),9,1,geom.NGp))
Strn=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp))
DG=np.zeros((len(conVxyz),9,1,geom.NGp))
epsStrn=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp)) #geom.nDim=3 in this case
for i in range(len(conVxyz)):
elnodes=conVxyz[i]
ep=Ep[i]
qe=q[i]
alphe=alph[i]
globdof=np.array([3*elnodes,3*elnodes+1,3*elnodes+2]).flatten()#.T.flatten() : gets the elemental dofs in the order u1.....,w3
nodexy=meshxyz[elnodes]
locdisp=disp[globdof]
elemK,elemF,strs[i],DG[i],gipt,q[i],alph[i],Ep[i],C1111,C2222,C1212,C3333=locmat(nodexy.T.flatten(),locdisp,qe,alphe,ep)
globK[np.ix_(globdof,globdof)] += elemK
globF[globdof] += elemF
intpt.append(gipt)
# Calculate strains and integration point coordinates
Strn[i]=(np.einsum('lik,ljk->ijk',DG.reshape(geom.nDim,geom.nDim,-1),DG.reshape(geom.nDim,geom.nDim,-1))-np.eye(geom.nDim).reshape(geom.nDim,geom.nDim,-1).repeat(8,axis=-1))/2
epsStrn[i]=(np.einsum('ijk->jik',DG.reshape(geom.nDim,geom.nDim,-1))+DG.reshape(geom.nDim,geom.nDim,-1)-2*np.eye(geom.nDim).reshape(geom.nDim,geom.nDim,-1).repeat(8,axis=-1))/2
strs=strs.reshape(len(conVxyz),geom.nDim,geom.nDim,-1)
DG=DG.reshape(len(conVxyz),geom.nDim,geom.nDim,-1)
return globK,globF,strs,DG,Strn,epsStrn,intpt,q,Ep,alph,C1111,C1212,C2222,C3333
prescribed_dofs=np.array([[0,0.],
[1,0],
[2,0],
[4,0],
[5,0],
[6,0],
[7,0],
[8,0],
[10,0],
[11,0],
[12,0],
# [13,0],
[14,0],
# [16,0],
[17,0],
[18,0],
# [19,0],
[20,0.],
# [22,0],
[23,0],
[3,geom.bta*geom.xlength],
[9,geom.bta*geom.xlength],
[15,geom.bta*geom.xlength],
[21,geom.bta*geom.xlength]]) #apply 2% strain
dof[(prescribed_dofs[:,0]).astype(int)]=0.
fdof=dof==1.e9 #free dofs flags: further initialization to zeros needed only for the first step
nfdof=np.invert(fdof) #fixed dofs flags
dof[fdof]=0.
lineardof=dof.copy()
DfGrn=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp,geom.nSteps+1)) # Deformation Gradient
Strs=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp,geom.nSteps+1)) # First-PK Stress
LagStrain=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp,geom.nSteps+1)) # Lagrangian Strain
epss=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp,geom.nSteps+1))
intpt=([])
qGlobal=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp,geom.nSteps+1)) #check dimensions done (@)
alphGlobal=np.zeros((len(conVxyz),geom.NGp,geom.nSteps+1)) #just a scalar
Eplastic=np.zeros((len(conVxyz),geom.nDim,geom.nDim,geom.NGp,geom.nSteps+1)) #initialize the plastic strain
_,_,_,_,_,_,intpt1,_,_,_,_,_,_,_=assembly(dof,qGlobal[:,:,:,:,0],alphGlobal[:,:,0],Eplastic[:,:,:,:,0]) #global gauss-point locations (?)
intpt1=intpt1[0].T
dofstore=np.zeros(dof.shape);
Ks3,_,_,_,_,_,_,_,_,_,_,_,_,_=assembly(dof,qGlobal[:,:,:,:,0],alphGlobal[:,:,0],Eplastic[:,:,:,:,0]) #linear stiffness (check!)
#Initialize residuals to empty lists
res4=([]);res10=([]);res25=([]);res50=([]);res80=([])
Cep1111=np.zeros(geom.T.size);
Cep1111[0]=geom.kap+geom.C1*8./3
Cep1212=np.zeros(geom.T.size);
Cep1212[0]=2*geom.C1
Cep2222=np.zeros(geom.T.size);
Cep2222[0]=geom.kap+geom.C1*8./3
Cep1313=np.zeros(geom.T.size);
Cep1313[0]=2*geom.C1
Cep3333=np.zeros(geom.T.size);
Cep3333[0]=geom.kap+geom.C1*8./3
#Load-Steps
for istep in range(geom.nSteps):
print('Step: {}'.format(istep+1))
dof[(prescribed_dofs[:,0]).astype(int)]=(istep+1)/(geom.nSteps)*prescribed_dofs[:,1]
Ks1,Fs1,strs,dfg,lstrn,epsstrn,_,qglb,epls,alphglb,C1111temp,C1212temp,C2222temp,C3333temp=assembly(dof,qGlobal[:,:,:,:,istep],alphGlobal[:,:,istep],Eplastic[:,:,:,:,istep])
normres=1;
# print(la.norm(Fs1[fdof],2))
if istep==3:
res4.append(Fs1[fdof]) #zero-based indexing
elif istep==9:
res10.append(Fs1[fdof])
elif istep==24:
res25.append(Fs1[fdof])
elif istep==49:
res50.append(Fs1[fdof])
elif istep==79:
res80.append(Fs1[fdof])
normres=la.norm(Fs1[fdof],2);
res0=normres.copy()
iterNR=0;
# Newton-Increments
while normres > geom.tolNR*res0 and iterNR<=geom.maxiter:
print('Iter: {}'.format(iterNR+1))
dof[fdof] += la.solve(Ks1[np.ix_(fdof,fdof)],-Fs1[fdof]) #external force add (-- not required here, only for this case though)
Ks1,Fs1,strs,dfg,lstrn,epsstrn,_,qglb,epls,alphglb,_,_,_,_=assembly(dof,qGlobal[:,:,:,:,istep],alphGlobal[:,:,istep],Eplastic[:,:,:,:,istep])
if istep==3:
res4.append(Fs1[fdof]) #zero-based indexing
elif istep==9:
res10.append(Fs1[fdof])
elif istep==24:
res25.append(Fs1[fdof])
elif istep==49:
res50.append(Fs1[fdof])
elif istep==79:
res80.append(Fs1[fdof])
normres=la.norm(Fs1[fdof],2)
# print(la.norm(Fs1[fdof],2))
# _,_,_,_,_,_,_,qGlobal[:,:,:,:,istep],Eplastic[:,:,:,:,istep],alphGlobal[:,:,istep],_,_,_,_ = assembly(dof,qGlobal[:,:,:,:,istep],alphGlobal[:,:,istep],Eplastic[:,:,:,:,istep])
iterNR += 1
dofstore=np.vstack((dofstore,dof))
Strs[:,:,:,:,istep+1],DfGrn[:,:,:,:,istep+1],LagStrain[:,:,:,:,istep+1],epss[:,:,:,:,istep+1],_,qGlobal[:,:,:,:,istep+1],Eplastic[:,:,:,:,istep+1],alphGlobal[:,:,istep+1],Cep1111[istep+1],Cep1212[istep+1],Cep2222[istep+1],Cep3333[istep+1]=strs,dfg,lstrn,epsstrn,_,qglb,epls,alphglb,C1111temp,C1212temp,C2222temp,C3333temp
###############################################################################
excelWrite=False
#Output the Residual in respective excel sheets
if excelWrite:
pd.DataFrame(np.array(res4).T).to_excel('res4.xlsx',index=False,header=False)
pd.DataFrame(np.array(res4).T).to_excel('res10.xlsx',index=False,header=False)
pd.DataFrame(np.array(res4).T).to_excel('res25.xlsx',index=False,header=False)
pd.DataFrame(np.array(res4).T).to_excel('res50.xlsx',index=False,header=False)
pd.DataFrame(np.array(res4).T).to_excel('res80.xlsx',index=False,header=False)
plot_it=True
if plot_it:
plt.figure(figsize=(10,10))
plt.plot(DfGrn[0,0,2,-1,:],Strs[0,0,0,-1,:],label=r'$\sigma_{11}$')
plt.plot(DfGrn[0,0,2,-1,:],Strs[0,-1,-1,-1,:],label=r'$\sigma_{33}$')
plt.plot(DfGrn[0,0,2,-1,:],Strs[0,1,1,-1,:],label=r'$\sigma_{22}$')
plt.plot(DfGrn[0,0,2,-1,:],Strs[0,0,-1,-1,:],label=r'$\sigma_{13}$')
plt.xlabel(r'$\gamma$ (Stretch)',fontsize=20)
plt.ylabel(r'$\sigma_{ij}$ ',fontsize=20)
plt.legend(loc=0,fontsize=20)
plt.legend(loc=0,fontsize=18)
plt.ticklabel_format(style='sci',axis='y',scilimits=(0,0))
ax=plt.gca()
ax.xaxis.set_minor_locator(mx)
ax.set_title(r'Stress vs Stretch',fontsize=20)
ax.yaxis.set_minor_locator(my)
plt.grid(True)
# plt.savefig('StrsStrchP4b1m.eps')
# plt.close()
plt.figure(figsize=(10,10))
plt.plot(geom.T,Strs[0,0,0,-1,:],label=r'$\sigma_{11}$')
plt.plot(geom.T,Strs[0,-1,-1,-1,:],label=r'$\sigma_{33}$')
plt.plot(geom.T,Strs[0,1,1,-1,:],label=r'$\sigma_{22}$')
plt.plot(geom.T,Strs[0,0,-1,-1,:],label=r'$\sigma_{13}$')
plt.xlabel(r'$t$ (Time)',fontsize=20)
plt.ylabel(r'$\sigma_{ij}$ ',fontsize=20)
plt.legend(loc=0,fontsize=20)
plt.legend(loc=0,fontsize=18)
plt.ticklabel_format(style='sci',axis='y',scilimits=(0,0))
ax=plt.gca()
ax.xaxis.set_minor_locator(mx)
ax.set_title(r'Stress vs time',fontsize=20)
ax.yaxis.set_minor_locator(my)
plt.grid(True)
# plt.savefig('StrsTimeP4b1m.eps')
# plt.close()
###############################################################################
#Visualization using Scipy.interpolate's n-D griddata
#from scipy.interpolate import griddata
#mgD=np.mgrid[-1:1.25:0.25,-1:1.25:0.25,-1:1.25:0.25]
#Strs33=griddata(intpt1,Strs[-1,-1,-1,:],
# np.einsum('ijkl->ikjl',mgD).reshape(3,-1).T,method='nearest') #last step stress33 component
#xx=np.arange(-1.,1.25,0.25);yy=xx.copy()
###############################################################################
vtKwrite=False
if vtKwrite:
#Create vtk data file for visualization in Paraview
filename='CIHW3.vtk'
filenamedef='CIHW3def.vtk'
filestrsstrn='CIHW31.vtk'
name='Hex8'
if name=='Hex8':
ParaviewID=12
output_file=open(filename,'w')
output_filedef=open(filenamedef,'w')
output_filestrsstrn=open(filestrsstrn,'w')
output_file.write('# vtk DataFile Version 2.0\n')
output_file.write('%s\n' %name);
output_file.write('ASCII\n');
output_file.write('\n');
#nodes
output_file.write('DATASET UNSTRUCTURED_GRID\n')
output_file.write('POINTS %d float\n' %(len(meshxyz))); #list of nodes
for i in range(len(meshxyz)):
output_file.write('%15.10f %15.10f %15.10f \n'%( meshxyz[i,0],
meshxyz[i,1],
meshxyz[i,2]))
output_file.write('\n');
output_file.write('CELLS %d %d \n' %(len(conVxyz), (len(conVxyz[0])+1)*len(conVxyz))) #connectivity
output_file.write('8 %d %d %d %d %d %d %d %d'%(conVxyz[0,0],
conVxyz[0,2],
conVxyz[0,6],
conVxyz[0,4],
conVxyz[0,1],
conVxyz[0,3],
conVxyz[0,7],
conVxyz[0,5]
))
output_file.write('\n')
output_file.write('CELL_TYPES %d\n' %(len(conVxyz)))
a=ParaviewID*np.ones(len(conVxyz),int)
output_file.write('\n'.join(map(str,a)))
output_file.write('\nPOINT_DATA %d\n' %len(meshxyz)) #data fields
output_file.write('SCALARS U float 3\n')
output_file.write('Lookup_table default\n')
for i in range (len(meshxyz)):
output_file.write('%12.10f %12.10f %12.10f\n' %(dofstore[-1].reshape(-1,3)[i,0],
dofstore[-1].reshape(-1,3)[i,1],
dofstore[-1].reshape(-1,3)[i,2]))
output_file.write('\n')
output_file.close()
# Deformed data
output_filedef.write('# vtk DataFile Version 2.0\n')
output_filedef.write('%s\n' %name);
output_filedef.write('ASCII\n');
output_filedef.write('\n');
#nodes
output_filedef.write('DATASET UNSTRUCTURED_GRID\n')
output_filedef.write('POINTS %d float\n' %(len(meshxyz))); #list of nodes
for i in range(len(meshxyz)):
output_filedef.write('%15.10f %15.10f %15.10f \n'%( meshxyz[i,0]+geom.Sf*dofstore[-1].reshape(-1,3)[i,0],
meshxyz[i,1]+geom.Sf*dofstore[-1].reshape(-1,3)[i,1],
meshxyz[i,2]+geom.Sf*dofstore[-1].reshape(-1,3)[i,2]))
output_filedef.write('\n');
output_filedef.write('CELLS %d %d \n' %(len(conVxyz), (len(conVxyz[0])+1)*len(conVxyz))) #connectivity
output_filedef.write('8 %d %d %d %d %d %d %d %d'%(conVxyz[0,0],
conVxyz[0,2],
conVxyz[0,6],
conVxyz[0,4],
conVxyz[0,1],
conVxyz[0,3],
conVxyz[0,7],
conVxyz[0,5]
))
output_filedef.write('\n')
output_filedef.write('CELL_TYPES %d\n' %(len(conVxyz)))
a=ParaviewID*np.ones(len(conVxyz),int)
output_filedef.write('\n'.join(map(str,a)))
output_filedef.write('\nPOINT_DATA %d\n' %len(meshxyz)) #data fields
output_filedef.write('SCALARS Udef float 3\n')
output_filedef.write('Lookup_table default\n')
for i in range (len(meshxyz)):
output_filedef.write('%12.10f %12.10f %12.10f\n' %(dofstore[-1].reshape(-1,3)[i,0],
dofstore[-1].reshape(-1,3)[i,1],
dofstore[-1].reshape(-1,3)[i,2]))
output_filedef.write('\n')
output_filedef.close()
#Stress-Strain File
output_filestrsstrn.write('# vtk DataFile Version 2.0\n')
output_filestrsstrn.write('%s\n' %name);
output_filestrsstrn.write('ASCII\n');
output_filestrsstrn.write('\n');
#nodes
output_filestrsstrn.write('DATASET UNSTRUCTURED_GRID\n')
output_filestrsstrn.write('POINTS %d float\n' %(len(meshxyz))); #list of integration point
for i in range(len(intpt1)):
output_filestrsstrn.write('%15.10f %15.10f %15.10f \n'%( intpt1[i,0],
intpt1[i,1],
intpt1[i,2])) #write global integration point
output_filestrsstrn.write('\n');
output_filestrsstrn.write('CELLS %d %d \n' %(len(conVxyz), (len(conVxyz[0])+1)*len(conVxyz))) #connectivity
output_filestrsstrn.write('8 %d %d %d %d %d %d %d %d'%(conVxyz[0,0],
conVxyz[0,2],
conVxyz[0,6],
conVxyz[0,4],
conVxyz[0,1],
conVxyz[0,3],
conVxyz[0,7],
conVxyz[0,5]
))
output_filestrsstrn.write('\n')
output_filestrsstrn.write('CELL_TYPES %d\n' %(len(conVxyz)))
a=ParaviewID*np.ones(len(conVxyz),int)
output_filestrsstrn.write('\n'.join(map(str,a)))
output_filestrsstrn.write('\nPOINT_DATA %d\n' %len(meshxyz)) #data fields
output_filestrsstrn.write('SCALARS E33 float 1\n')
output_filestrsstrn.write('Lookup_table default\n')
for i in range (len(intpt1)):
output_filestrsstrn.write('%12.10f \n' %(LagStrain[0,-1,-1,i,-1]))
output_filestrsstrn.write('\n')
#output_filestrsstrn.write('\nPOINT_DATA %d\n' %len(meshxyz)) #data fields
output_filestrsstrn.write('SCALARS S33 float 1\n')
output_filestrsstrn.write('Lookup_table default\n')
for i in range (len(intpt1)):
output_filestrsstrn.write('%12.10f \n' %(Strs[0,-1,-1,i,-1]))
output_filestrsstrn.write('\n')
output_filestrsstrn.close()