The 'FIP' mnemonic continues to be an alias for 'SFIP' in the
current implementation, and the output layer will create the 'SFIP'
arrays as copies of 'FIP' if passed only the 'FIP' arrays.
To this end, make 'outputFipRestart_' into a structure that tracks
which of the *FIP mnemonics have been requested, and insert the
pertinent solution arrays into the data::Solution object when
needed.
If the user chooses a specific number of NLDD domains, there is no
need to compute the default number of domains based on a specific
target number of cells per domain. Defer the, potentially costly,
calculation to when we know we need it.
While here, also split/rejoin a couple of long lines.
This commit introduces helper functions for each individual part of
a convergence report record in the INFOITER file. In particular, we
create helpers for
- Time related columns (report step, time step, time &c)
- CNV pore-volume histogram columns
- Reservoir convergence metrics (CNV and MB values per phase)
- Well convergence metrics
This makes the body of the main loop in writeConvergenceRequest()
slightly easier to read and means that we can apply some additional
logic to the CNV pore-volume histograms if the number of values does
not match the expected 3 per type. In that case we output sentinel
values (e.g., NaN and -1) to signify that the corresponding pieces
of information are unavailable.
This commit tracks the number of cells and their associate fraction
of the model's "eligible" pore volume (total pore volume in
numerical aquifers subtracted from the model's total pore volume) in
three distinct categories as a function of the non-linear iteration
number:
- 0: MAX_p { CNV_p } <= strict CNV tolerance
- 1: MAX_p { CNV_p } \in (strict, relaxed]
- 2: MAX_p { CNV_p } > relaxed CNV tolerance
We then output these cell counts and pore volume fractions as new
items in the INFOITER file to enable more targeted analysis of the
non-linear convergence behaviour.
To this end, introduce a type alias CnvPvSplit in the
ConvergenceReport and aggregate these across the MPI ranks before we
collect them in the ConvergenceReport objects.
While here, also reduce the amount of repeated logic in
gatherConvergenceReport.cpp through a few local lambdas.
