A 3D hexahedron (brick) element formulation with quadratic (serendipity) shape
functions.
Notes
The hexahedron element is defined by twenty points with eight corner points (0-7)
where (0,1,2,3) forms the base and (4,5,6,7) the opposite quad; followed by 12 mid-
edge points. The mid-edge points correspond to the edges defined by the lines
between the points (0,1), (1,2), (2,3), (3,0), (4,5), (5,6), (6,7), (7,4), (0,4),
(1,5), (2,6), (3,7). [1]
The shape functions \(\boldsymbol{h}\) are given in terms of the coordinates
\((r,s,t)\)..
A 3D hexahedron (brick) element formulation with tri-quadratic shape functions.
Notes
The hexahedron element is defined by 27 points. This includes 8 corner points, 12
mid-edge points, 6 mid-face points and one mid-volume point. The ordering of the 27
points defining the element is point ids (0-7,8-19, 20-25, 26) where point ids 0-7
are the eight corner vertices of the cube; followed by twelve midedge points (8-19);
followed by 6 mid-face points (20-25) and the last point (26) is the mid-volume
point. Note that these mid-edge points correspond to the edges defined by (0,1),
(1,2), (2,3), (3,0), (4,5), (5,6), (6,7), (7,4), (0,4), (1,5), (2,6), (3,7). The
mid-surface points lie on the faces defined by (first edge point id’s, than mid-edge
point id’s): (0,1,5,4;8,17,12,16), (1,2,6,5;9,18,13,17), (2,3,7,6,10,19,14,18),
(3,0,4,7;11,16,15,19), (0,1,2,3;8,9,10,11), (4,5,6,7;12,13,14,15). The last point
lies in the center (0,1,2,3,4,5,6,7). [1]
The shape functions \(\boldsymbol{h}\) are given in terms of the coordinates
\((r,s,t)\).
A 2D triangle element formulation with quadratic shape functions.
Notes
The quadratic triangle element is defined by six points (0-5). The element includes
three mid-edge points besides the three triangle vertices. The ordering of the three
points defining the element is point ids (0-2,3-5) where id #3 is the mid-edge point
between points (0,1); id #4 is the mid-edge point between points (1,2); and id #5 is
the mid-edge point between points (2,0). [1]
The shape functions \(\boldsymbol{h}\) are given in terms of the coordinates
\((r,s)\)[2]_.
\[\begin{split}\boldsymbol{h}(r,s) = \begin{bmatrix}
1-r-s \\
r \\
s \\
4 r (1-r-s) \\
4 r s \\
4 s (1-r-s)
\end{bmatrix}\end{split}\]
A 3D tetrahedron element formulation with quadratic shape functions.
Notes
The quadratic tetrahedron element is defined by ten points (0-9). The element
includes a mid-edge point on each of the edges of the tetrahedron. The ordering of
the ten points defining the cell is point ids (0-3,4-9) where ids 0-3 are the four
tetra vertices; and point ids 4-9 are the mid-edge points between (0,1), (1,2),
(2,0), (0,3), (1,3), and (2,3). [1]
The shape functions \(\boldsymbol{h}\) are given in terms of the coordinates
\((r,s,t)\).
A n-dimensional Lagrange finite element (e.g. line, quad or hexahdron) of
arbitrary order.
Notes
Polynomial shape functions
The basis function vector is generated with row-stacking of the individual lagrange
polynomials. Each polynomial defined in the interval \([-1,1]\) is a function of
the parameter \(r\). The curve parameters matrix \(\boldsymbol{A}\) is of
symmetric shape due to the fact that for each evaluation point \(r_j\) exactly
one basis function \(h_j(r)\) is needed.
The evaluation of the curve parameter matrix \(\boldsymbol{A}\) is carried out
by boundary conditions. Each shape function \(h_i\) has to take the value of one
at the associated nodal coordinate \(r_i\) and zero at all other point
coordinates.
For the calculation of the partial derivative of the interpolation field w.r.t. the
parameter \(r\) a simple shift of the entries of the parameter vector is enough.
This shifted parameter vector is denoted as \(\boldsymbol{r}^-\). A minus
superscript indices the negative shift of the vector entries by \(-1\).
Multi-dimensional shape function matrices
\(\boldsymbol{H}_{2D}, \boldsymbol{H}_{3D}\) are simply evaluated as dyadic
(outer) vector products of one-dimensional shape function vectors. The multi-
dimensional shape function vector is a one-dimensional representation (flattened
version) of the multi-dimensional shape function matrix.