* @p future_fe_indices will be used to update the data accordingly.
* </ol>
*
- * As an example, a realisation of pure p-adaptive methods would look like the
+ * As an example, a realization of pure p-adaptive methods would look like the
* following:
* @code
* // step 1: flag cells for refinement or coarsening
* or decrease of the degree will thus change its value by a user-defined
* control parameter @p gamma_p. The assumption of exponential convergence
* is only valid if both h- and p-adaptive methods are combined in a sense
- * that they are both utilitzed throughout a mesh, but do not have to be
+ * that they are both utilized throughout a mesh, but do not have to be
* applied both on a cell simultaneously.
*
* The prediction algorithm is formulated as follows with control parameters
*/
/**
- * @name Optimiize p-level distribution
+ * @name Optimize p-level distribution
* @{
*/
* flags.
*
* In detail, this function limits the level difference of neighboring cells
- * and thus smoothes the overall function space. Future FE indices will be
+ * and thus smoothess the overall function space. Future FE indices will be
* raised (and never lowered) so that the level difference to neighboring
* cells is never larger than @p max_difference.
*
* On cells that will be h-coarsened, we enforce the difference criterion as
* if it is already a parent cell. That means, we set the level of all
* siblings to the highest one among them. In that case, all sibling cells
- * need to have the h-coarsenening flags set terminally via
+ * need to have the h-coarsening flags set terminally via
* Triangulation::prepare_coarsening_and_refinement() beforehand. Otherwise
* an assertion will be triggered.
*