c3939c5444
The intention is that this will ultimately replace the existing
RelpermDiagnostics component which does not really work in parallel
and which does not report enough context to help diagnose underlying
issues. For now, though, we just add the shell of a new set of
checks and hook that up to the build.
Class SatfuncConsistencyChecks<Scalar> manages a configurable set of
consistency checks, the implementations of which must publicly
derive from SatfuncConsistencyChecks<Scalar>::Check. Client code
will configure a set of checks by first calling
SatfuncConsistencyChecks<Scalar>::resetCheckSet()
then register individual checks by calling
SatfuncConsistencyChecks<Scalar>::addCheck()
and finally build requisite internal structures by calling
SatfuncConsistencyChecks<Scalar>::finaliseCheckSet()
Client code will then run the checks by calling
SatfuncConsistencyChecks<Scalar>::checkEndpoints()
typically in a loop. Class SatfuncConsistencyChecks<Scalar> will
count consistency check failures and attribute these to each
individual check as needed. We also maintain separate counts for
"Standard" and "Critical" failures. The former will typically
generate warnings while the latter will typically cause the
simulation run to stop. Individual checks get to decide which check
is "Critical", and client code gets to decide how to respond to
"Critical" failures.
Member function SatfuncConsistencyChecks<Scalar>::reportFailures()
will generate a textual report of the known set of consistency check
failures at a give severity level.
As an internal implementation detail, SatfuncConsistencyChecks uses
"reservoir sampling"
(https://en.wikipedia.org/wiki/Reservoir_sampling) to track details
about individual failed checks. We maintain at most a fixed number
of individual points (constructor argument).
Open Porous Media Simulators and Automatic Differentiation Library
CONTENT
opm-simulators contains simulator programs for porous media flow. The most important (and tested) part is the Flow reservoir simulator, which is a fully implicit black-oil simulator that also supports solvent and polymer options. It is built using automatic differentiation, using the local AD class Evaluation from opm-material.
LICENSE
The library is distributed under the GNU General Public License, version 3 or later (GPLv3+).
PLATFORMS
The opm-simulators module is designed to run on Linux platforms. It is also regularly run on Mac OS X. No efforts have been made to ensure that the code will compile and run on windows platforms.
REQUIREMENTS
opm-simulators requires several other OPM modules, see http://opm-project.org/?page_id=274. In addition, opm-simulators requires Dune and some other software to be available, for details see https://opm-project.org/?page_id=239.
DOWNLOADING
For a read-only download: git clone git://github.com/OPM/opm-simulators.git
If you want to contribute, fork OPM/opm-simulators on github.
BUILDING
See build instructions at http://opm-project.org/?page_id=36
DOCUMENTATION
Efforts have been made to document the code with Doxygen. In order to build the documentation, enter the command
make doc
in the topmost directory.
REPORTING ISSUES
Issues can be reported in the Git issue tracker online at:
https://github.com/OPM/opm-simulators/issues
To help diagnose build errors, please provide a link to a build log together with the issue description.
You can capture such a log from the build using the `script' utility, e.g.:
LOGFILE=$(date +%Y%m%d-%H%M-)build.log ;
cmake -E cmake_echo_color --cyan --bold "Log file: $LOGFILE" ;
script -q $LOGFILE -c 'cmake ../opm-core -DCMAKE_BUILD_TYPE=Debug' &&
script -q $LOGFILE -a -c 'ionice nice make -j 4 -l 3' ||
cat CMakeCache.txt CMakeFiles/CMake*.log >> $LOGFILE
The resulting file can be uploaded to for instance gist.github.com.