Computation of piece-wise linear hat functions
I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:
$$phi = ax + by + cz + d$$
with the property of $phi_i(x_j) = delta_{ij}$.
For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:
$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$
The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.
I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.
finite-element-method piecewise-continuity
add a comment |
I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:
$$phi = ax + by + cz + d$$
with the property of $phi_i(x_j) = delta_{ij}$.
For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:
$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$
The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.
I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.
finite-element-method piecewise-continuity
2
Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52
I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54
2
What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00
add a comment |
I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:
$$phi = ax + by + cz + d$$
with the property of $phi_i(x_j) = delta_{ij}$.
For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:
$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$
The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.
I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.
finite-element-method piecewise-continuity
I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:
$$phi = ax + by + cz + d$$
with the property of $phi_i(x_j) = delta_{ij}$.
For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:
$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$
The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.
I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.
finite-element-method piecewise-continuity
finite-element-method piecewise-continuity
edited Oct 24 at 7:34
asked Oct 24 at 7:10
AFP
225111
225111
2
Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52
I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54
2
What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00
add a comment |
2
Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52
I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54
2
What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00
2
2
Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52
Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52
I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54
I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54
2
2
What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00
What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00
add a comment |
1 Answer
1
active
oldest
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First define one triangle and interpolations as follows:
$$
begin{bmatrix} x \ y \ z end{bmatrix} =
begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
$$
And quite in general:
$$
phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
$$
From this reference we infer that:
$$
begin{cases}
xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
end{cases}
$$
Where $Delta$ is twice the area of a triangle.
The Finite Element shape functions thus are, still for one triangle:
$$
N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
$$ $$
x = N_1x_1+N_2x_2+N_3x_3 \
y = N_1y_1+N_2y_2+N_3y_3 \
z = N_1z_1+N_2z_2+N_3z_3 \
phi = N_1phi_1+N_2phi_2+N_3phi_3
$$
Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:
- $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$
- $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$
- $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$
- $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$
- $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$
- $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$
add a comment |
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1 Answer
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1 Answer
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active
oldest
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oldest
votes
First define one triangle and interpolations as follows:
$$
begin{bmatrix} x \ y \ z end{bmatrix} =
begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
$$
And quite in general:
$$
phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
$$
From this reference we infer that:
$$
begin{cases}
xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
end{cases}
$$
Where $Delta$ is twice the area of a triangle.
The Finite Element shape functions thus are, still for one triangle:
$$
N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
$$ $$
x = N_1x_1+N_2x_2+N_3x_3 \
y = N_1y_1+N_2y_2+N_3y_3 \
z = N_1z_1+N_2z_2+N_3z_3 \
phi = N_1phi_1+N_2phi_2+N_3phi_3
$$
Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:
- $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$
- $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$
- $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$
- $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$
- $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$
- $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$
add a comment |
First define one triangle and interpolations as follows:
$$
begin{bmatrix} x \ y \ z end{bmatrix} =
begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
$$
And quite in general:
$$
phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
$$
From this reference we infer that:
$$
begin{cases}
xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
end{cases}
$$
Where $Delta$ is twice the area of a triangle.
The Finite Element shape functions thus are, still for one triangle:
$$
N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
$$ $$
x = N_1x_1+N_2x_2+N_3x_3 \
y = N_1y_1+N_2y_2+N_3y_3 \
z = N_1z_1+N_2z_2+N_3z_3 \
phi = N_1phi_1+N_2phi_2+N_3phi_3
$$
Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:
- $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$
- $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$
- $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$
- $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$
- $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$
- $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$
add a comment |
First define one triangle and interpolations as follows:
$$
begin{bmatrix} x \ y \ z end{bmatrix} =
begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
$$
And quite in general:
$$
phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
$$
From this reference we infer that:
$$
begin{cases}
xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
end{cases}
$$
Where $Delta$ is twice the area of a triangle.
The Finite Element shape functions thus are, still for one triangle:
$$
N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
$$ $$
x = N_1x_1+N_2x_2+N_3x_3 \
y = N_1y_1+N_2y_2+N_3y_3 \
z = N_1z_1+N_2z_2+N_3z_3 \
phi = N_1phi_1+N_2phi_2+N_3phi_3
$$
Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:
- $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$
- $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$
- $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$
- $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$
- $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$
- $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$
First define one triangle and interpolations as follows:
$$
begin{bmatrix} x \ y \ z end{bmatrix} =
begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
$$
And quite in general:
$$
phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
$$
From this reference we infer that:
$$
begin{cases}
xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
end{cases}
$$
Where $Delta$ is twice the area of a triangle.
The Finite Element shape functions thus are, still for one triangle:
$$
N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
$$ $$
x = N_1x_1+N_2x_2+N_3x_3 \
y = N_1y_1+N_2y_2+N_3y_3 \
z = N_1z_1+N_2z_2+N_3z_3 \
phi = N_1phi_1+N_2phi_2+N_3phi_3
$$
Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:
- $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$
- $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$
- $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$
- $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$
- $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$
- $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$
answered Nov 18 at 15:19
Han de Bruijn
12.1k22361
12.1k22361
add a comment |
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2
Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52
I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54
2
What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00