PrecursorAction with continuous variables

[smpark7]

This issue can be closed when PrecursorAction supports continuous precursor concentration variables and generates accurate precursor distributions with it.

Background

Solving for the precursor concentration with the discontinuous Galerkin method is good for many problems because it is stable and fairly accurate under high Schmidt number (convection-dominated). However, it has some disadvantages:

• Limited fidelity with CONSTANT MONOMIAL shape functions (particularly in regions with large gradients)
• Number of DOFs increases significantly (x4) when used with first-order L2-Lagrange shape functions

Results so far

Preliminary work here showed that continuous Galerkin stabilized with isotropic artificial diffusion (ScalarAdvectionArtDiff) gave worse results because isotropic artificial diffusion is overly diffusive. We can expect better performance when we implement a more advanced stabilization techniques such as SUPG or FIC. Refer to the README for more information on how to generate the results and further discussion.