In [36]:
from sympy import *
from geom_util import *
from sympy.vector import CoordSys3D
N = CoordSys3D('N')
alpha1, alpha2, alpha3 = symbols("alpha_1 alpha_2 alpha_3", real = True, positive=True)
init_printing()
%matplotlib inline
%reload_ext autoreload
%autoreload 2
%aimport geom_util
In [50]:
h1 = Function("H1")
h2 = Function("H2")
h3 = Function("H3")
H1 = h1(alpha1, alpha2, alpha3)
H2 = S(1
H3 = h3(alpha1, alpha2, alpha3)
${\displaystyle \hat{G}=\sum_{i,j} g^{ij}\vec{R}_i\vec{R}_j}$
In [51]:
G_up = getMetricTensorUpLame(H1, H2, H3)
${\displaystyle \hat{G}=\sum_{i,j} g_{ij}\vec{R}^i\vec{R}^j}$
In [52]:
G_down = getMetricTensorDownLame(H1, H2, H3)
In [53]:
GK = getChristoffelSymbols2(G_up, G_down, (alpha1, alpha2, alpha3))
$ \left( \begin{array}{c} \nabla_1 u_1 \\ \nabla_2 u_1 \\ \nabla_3 u_1 \\ \nabla_1 u_2 \\ \nabla_2 u_2 \\ \nabla_3 u_2 \\ \nabla_1 u_3 \\ \nabla_2 u_3 \\ \nabla_3 u_3 \\ \end{array}
B \cdot \left( \begin{array}{c} u_1 \\ \frac { \partial u_1 } { \partial \alpha_1} \\ \frac { \partial u_1 } { \partial \alpha_2} \\ \frac { \partial u_1 } { \partial \alpha_3} \\ u_2 \\ \frac { \partial u_2 } { \partial \alpha_1} \\ \frac { \partial u_2 } { \partial \alpha_2} \\ \frac { \partial u_2 } { \partial \alpha_3} \\ u_3 \\ \frac { \partial u_3 } { \partial \alpha_1} \\ \frac { \partial u_3 } { \partial \alpha_2} \\ \frac { \partial u_3 } { \partial \alpha_3} \\ \end{array} \right) = B \cdot D \cdot \left( \begin{array}{c} u^1 \\ \frac { \partial u^1 } { \partial \alpha_1} \\ \frac { \partial u^1 } { \partial \alpha_2} \\ \frac { \partial u^1 } { \partial \alpha_3} \\ u^2 \\ \frac { \partial u^2 } { \partial \alpha_1} \\ \frac { \partial u^2 } { \partial \alpha_2} \\ \frac { \partial u^2 } { \partial \alpha_3} \\ u^3 \\ \frac { \partial u^3 } { \partial \alpha_1} \\ \frac { \partial u^3 } { \partial \alpha_2} \\ \frac { \partial u^3 } { \partial \alpha_3} \\ \end{array} \right) $
In [54]:
def row_index_to_i_j_grad(i_row):
return i_row // 3, i_row % 3
B = zeros(9, 12)
B[0,1] = S(1)
B[1,2] = S(1)
B[2,3] = S(1)
B[3,5] = S(1)
B[4,6] = S(1)
B[5,7] = S(1)
B[6,9] = S(1)
B[7,10] = S(1)
B[8,11] = S(1)
for row_index in range(9):
i,j=row_index_to_i_j_grad(row_index)
B[row_index, 0] = -GK[i,j,0]
B[row_index, 4] = -GK[i,j,1]
B[row_index, 8] = -GK[i,j,2]
B
Out[54]:
$ \left( \begin{array}{c} \varepsilon_{11} \\ \varepsilon_{22} \\ \varepsilon_{33} \\ 2\varepsilon_{12} \\ 2\varepsilon_{13} \\ 2\varepsilon_{23} \\ \end{array}
\left(E + E_{NL} \left( \nabla \vec{u} \right) \right) \cdot \left( \begin{array}{c} \nabla_1 u_1 \\ \nabla_2 u_1 \\ \nabla_3 u_1 \\ \nabla_1 u_2 \\ \nabla_2 u_2 \\ \nabla_3 u_2 \\ \nabla_1 u_3 \\ \nabla_2 u_3 \\ \nabla_3 u_3 \\ \end{array} \right)$
In [15]:
E=zeros(6,9)
E[0,0]=1
E[1,4]=1
E[2,8]=1
E[3,1]=1
E[3,3]=1
E[4,2]=1
E[4,6]=1
E[5,5]=1
E[5,7]=1
E
Out[15]:
In [45]:
def E_NonLinear(grad_u):
N = 3
du = zeros(N, N)
# print("===Deformations===")
for i in range(N):
for j in range(N):
index = i*N+j
du[j,i] = grad_u[index]
# print("========")
a_values = S(1)/S(2) * du * G_up
E_NL = zeros(6,9)
E_NL[0,0] = a_values[0,0]
E_NL[0,3] = a_values[0,1]
E_NL[0,6] = a_values[0,2]
E_NL[1,1] = a_values[1,0]
E_NL[1,4] = a_values[1,1]
E_NL[1,7] = a_values[1,2]
E_NL[2,2] = a_values[2,0]
E_NL[2,5] = a_values[2,1]
E_NL[2,8] = a_values[2,2]
E_NL[3,1] = 2*a_values[0,0]
E_NL[3,4] = 2*a_values[0,1]
E_NL[3,7] = 2*a_values[0,2]
E_NL[4,0] = 2*a_values[2,0]
E_NL[4,3] = 2*a_values[2,1]
E_NL[4,6] = 2*a_values[2,2]
E_NL[5,2] = 2*a_values[1,0]
E_NL[5,5] = 2*a_values[1,1]
E_NL[5,8] = 2*a_values[1,2]
return E_NL
%aimport geom_util
#u=getUHat3D(alpha1, alpha2, alpha3)
u=getUHatU3Main(alpha1, alpha2, alpha3)
gradu=B*u
E_NL = E_NonLinear(gradu)*B
$u_i=u_{[i]} H_i$
In [55]:
P=zeros(12,12)
P[0,0]=H1
P[1,0]=(H1).diff(alpha1)
P[1,1]=H1
P[2,0]=(H1).diff(alpha2)
P[2,2]=H1
P[3,0]=(H1).diff(alpha3)
P[3,3]=H1
P[4,4]=H2
P[5,4]=(H2).diff(alpha1)
P[5,5]=H2
P[6,4]=(H2).diff(alpha2)
P[6,6]=H2
P[7,4]=(H2).diff(alpha3)
P[7,7]=H2
P[8,8]=H3
P[9,8]=(H3).diff(alpha1)
P[9,9]=H3
P[10,8]=(H3).diff(alpha2)
P[10,10]=H3
P[11,8]=(H3).diff(alpha3)
P[11,11]=H3
P=simplify(P)
P
In [44]:
B_P = zeros(9,9)
for i in range(3):
for j in range(3):
ratio=1
if (i==0):
ratio = ratio*H1
elif (i==1):
ratio = ratio*H2
elif (i==2):
ratio = ratio*H3
if (j==0):
ratio = ratio*H1
elif (j==1):
ratio = ratio*H2
elif (j==2):
ratio = ratio*H3
row_index = i*3+j
B_P[row_index, row_index] = 1/ratio
Grad_U_P = simplify(B_P*B*P)
B_P
Out[44]:
In [46]:
StrainL=simplify(E*Grad_U_P)
StrainL
Out[46]:
In [49]:
%aimport geom_util
u=getUHatU3Main(alpha1, alpha2, alpha3)
gradup=B_P*B*P*u
E_NLp = E_NonLinear(gradup)*B*P*u
simplify(E_NLp)
Out[49]:
$u^1 \left( \alpha_1, \alpha_2, \alpha_3 \right)=u\left( \alpha_1 \right)+\alpha_3\gamma \left( \alpha_1 \right) $
$u^2 \left( \alpha_1, \alpha_2, \alpha_3 \right)=0 $
$u^3 \left( \alpha_1, \alpha_2, \alpha_3 \right)=w\left( \alpha_1 \right) $
$ \left( \begin{array}{c} u^1 \\ \frac { \partial u^1 } { \partial \alpha_1} \\ \frac { \partial u^1 } { \partial \alpha_2} \\ \frac { \partial u^1 } { \partial \alpha_3} \\ u^2 \\ \frac { \partial u^2 } { \partial \alpha_1} \\ \frac { \partial u^2 } { \partial \alpha_2} \\ \frac { \partial u^2 } { \partial \alpha_3} \\ u^3 \\ \frac { \partial u^3 } { \partial \alpha_1} \\ \frac { \partial u^3 } { \partial \alpha_2} \\ \frac { \partial u^3 } { \partial \alpha_3} \\ \end{array} \right) = T \cdot \left( \begin{array}{c} u \\ \frac { \partial u } { \partial \alpha_1} \\ \gamma \\ \frac { \partial \gamma } { \partial \alpha_1} \\ w \\ \frac { \partial w } { \partial \alpha_1} \\ \end{array} \right) $
In [ ]:
T=zeros(12,6)
T[0,0]=1
T[0,2]=alpha3
T[1,1]=1
T[1,3]=alpha3
T[3,2]=1
T[8,4]=1
T[9,5]=1
T
In [ ]:
D_p_T = StrainL*T
simplify(D_p_T)
In [ ]:
u = Function("u")
t = Function("theta")
w = Function("w")
u1=u(alpha1)+alpha3*t(alpha1)
u3=w(alpha1)
gu = zeros(12,1)
gu[0] = u1
gu[1] = u1.diff(alpha1)
gu[3] = u1.diff(alpha3)
gu[8] = u3
gu[9] = u3.diff(alpha1)
gradup=Grad_U_P*gu
# o20=(K*u(alpha1)-w(alpha1).diff(alpha1)+t(alpha1))/2
# o21=K*t(alpha1)
# O=1/2*o20*o20+alpha3*o20*o21-alpha3*K/2*o20*o20
# O=expand(O)
# O=collect(O,alpha3)
# simplify(O)
StrainNL = E_NonLinear(gradup)*gradup
simplify(StrainNL)
$u^1 \left( \alpha_1, \alpha_2, \alpha_3 \right)=u_{10}\left( \alpha_1 \right)p_0\left( \alpha_3 \right)+u_{11}\left( \alpha_1 \right)p_1\left( \alpha_3 \right)+u_{12}\left( \alpha_1 \right)p_2\left( \alpha_3 \right) $
$u^2 \left( \alpha_1, \alpha_2, \alpha_3 \right)=0 $
$u^3 \left( \alpha_1, \alpha_2, \alpha_3 \right)=u_{30}\left( \alpha_1 \right)p_0\left( \alpha_3 \right)+u_{31}\left( \alpha_1 \right)p_1\left( \alpha_3 \right)+u_{32}\left( \alpha_1 \right)p_2\left( \alpha_3 \right) $
$ \left( \begin{array}{c} u^1 \\ \frac { \partial u^1 } { \partial \alpha_1} \\ \frac { \partial u^1 } { \partial \alpha_2} \\ \frac { \partial u^1 } { \partial \alpha_3} \\ u^2 \\ \frac { \partial u^2 } { \partial \alpha_1} \\ \frac { \partial u^2 } { \partial \alpha_2} \\ \frac { \partial u^2 } { \partial \alpha_3} \\ u^3 \\ \frac { \partial u^3 } { \partial \alpha_1} \\ \frac { \partial u^3 } { \partial \alpha_2} \\ \frac { \partial u^3 } { \partial \alpha_3} \\ \end{array} \right) = L \cdot \left( \begin{array}{c} u_{10} \\ \frac { \partial u_{10} } { \partial \alpha_1} \\ u_{11} \\ \frac { \partial u_{11} } { \partial \alpha_1} \\ u_{12} \\ \frac { \partial u_{12} } { \partial \alpha_1} \\ u_{30} \\ \frac { \partial u_{30} } { \partial \alpha_1} \\ u_{31} \\ \frac { \partial u_{31} } { \partial \alpha_1} \\ u_{32} \\ \frac { \partial u_{32} } { \partial \alpha_1} \\ \end{array} \right) $
In [ ]:
L=zeros(12,12)
h=Symbol('h')
p0=1/2-alpha3/h
p1=1/2+alpha3/h
p2=1-(2*alpha3/h)**2
L[0,0]=p0
L[0,2]=p1
L[0,4]=p2
L[1,1]=p0
L[1,3]=p1
L[1,5]=p2
L[3,0]=p0.diff(alpha3)
L[3,2]=p1.diff(alpha3)
L[3,4]=p2.diff(alpha3)
L[8,6]=p0
L[8,8]=p1
L[8,10]=p2
L[9,7]=p0
L[9,9]=p1
L[9,11]=p2
L[11,6]=p0.diff(alpha3)
L[11,8]=p1.diff(alpha3)
L[11,10]=p2.diff(alpha3)
L
In [ ]:
B_General = zeros(9, 12)
B_General[0,1] = S(1)
B_General[1,2] = S(1)
B_General[2,3] = S(1)
B_General[3,5] = S(1)
B_General[4,6] = S(1)
B_General[5,7] = S(1)
B_General[6,9] = S(1)
B_General[7,10] = S(1)
B_General[8,11] = S(1)
for row_index in range(9):
i,j=row_index_to_i_j_grad(row_index)
B_General[row_index, 0] = -Symbol("G_{{{}{}}}^1".format(i+1,j+1))
B_General[row_index, 4] = -Symbol("G_{{{}{}}}^2".format(i+1,j+1))
B_General[row_index, 8] = -Symbol("G_{{{}{}}}^3".format(i+1,j+1))
B_General
In [ ]:
simplify(B_General*L)
In [ ]:
simplify(E*B*D*P*L)
In [ ]:
D_p_L = StrainL*L
K = Symbol('K')
D_p_L = D_p_L.subs(R, 1/K)
simplify(D_p_L)
In [ ]:
h = 0.5
exp=(0.5-alpha3/h)*(1-(2*alpha3/h)**2)#/(1+alpha3*0.8)
p02=integrate(exp, (alpha3, -h/2, h/2))
integral = expand(simplify(p02))
integral
In [ ]:
rho=Symbol('rho')
B_h=zeros(3,12)
B_h[0,0]=1
B_h[1,4]=1
B_h[1,8]=1
M=simplify(rho*P.T*B_h.T*G_up*B_h*P)
M