Blurb::
Estimate order of convergence of a response as model fidelity increases
Description::
Solution verification procedures estimate the order of convergence of
the simulation response data during the course of a refinement study.
This branch of methods is new and currently only contains one algorithm:
Richardson extrapolation.

<b> Refinement of the model </b>

The model fidelity must be parameterized by one or more continuous state variable(s). 

The refinement path is
determined from the \c initial_state of the \c continuous_state
variables specification in combination with the
\c refinement_rate, where each of the state variables is treated as an
independent refinement factor and each of the initial state values is
repeatedly divided by the refinement rate value to define new
discretization states. 

<b> Results </b>

Three algorithm options are currently provided:
-# \c estimate_order
-# \c converge_order
-# \c converge_qoi

<b> Stopping Criteria </b>

The method employs the
\c max_iterations and \c convergence_tolerance method independent
controls as stopping criteria.


Topics::
Examples::
Theory::
In each of these cases, convergence order for a response quantity of 
interest (QoI) is estimated from
\f[p = ln\left(\frac{QoI_3 - QoI_2}{QoI_2 - QoI_1}\right)/ln(r)\f]
where \f$r\f$ is the uniform refinement rate specified by \c 
refinement_rate.
Faq::
See_Also::	
