-
(q, \mathrm{div}\ \mathbf u)
=
- (q,f) + (\mathbf n\cdot\mathbf v, p)_{\partial\Omega}.
+ (q,f) - (\mathbf n\cdot\mathbf v, p)_{\partial\Omega}.
@f}
*
* It is this form that we will later use in assembling the discrete weak form
fe_values[velocities].divergence (j, q)) *
fe_values.JxW(q);
- local_rhs(i) += - fe_values[pressure].value (i, q)
- rhs_values[q] *
- fe_values.JxW(q);
+ local_rhs(i) += fe_values[pressure].value (i, q)
+ rhs_values[q] *
+ fe_values.JxW(q);
}
* @endcode
*
* extractor. For example, <code>fe_values[pressure].gradient(i,q)</code>
* would represent the gradient of the scalar pressure component, which
* is of type <code>Tensor@<1,dim@></code>, whereas the gradient of the
- * velocities components, <code>fe_values[velocities].value(i,q)</code>
+ * velocities components, <code>fe_values[velocities].gradient(i,q)</code>
* is a <code>Tensor@<2,dim@></code>, i.e. a matrix $G_{ij}$ that consits
* of entries $G_{ij}=\frac{\partial\phi_i}{\partial x_j}$. Finally,
* both scalar and vector views can be asked for the second derivatives