GridFire failed to compile on gcc and gnu stdlibc++ this has been
resolved. Further, the boost dependency has been removed since we no
longer use boost at all. This should dramatically simplify installation.
Finally we have added some build system checks to ensure that the
correct version of a C++ and fortran compiler are present on the system
Neutrino loss is essential for neutrino cooling. Started adding
framework to track this. Reaclib reactions use a simple heuristic where
electron capture reactions loss 100% of their energy to neutrinos
whereas beta decay reactions loose 50% of their energy to neutrinos
Building of the C API GridFire can now be used from fotran using the
gridfire_mod fortran module. This exposes the same, limited, set of
funcitonality that the C API does.
Python bindings have now been brought back up to feature pairity with
C++. Further, stubs have been added for all python features so that code
completion will work
Previously there was a bug where some reverse reactions were being
classed as forward reactions. This results in a failure of many
timesteps due to the reverse reactions very high molar flows
Previously QSE solving was done using Eigen. While this worked we were
limited in the ability to use previous iterations to speed up later
steps. We have switched to KINSOL, from SUNDIALS, for linear solving.
This has drastically speed up the process of solving for QSE abundances,
primarily because the jacobian matrix does not need to be generated
every single time time a QSE abundance is requested.
Sometimes it is useful to pause execution with an exception while
debugging (though bad practice in production code). This is an explicit
exception type dedicated to that purpose. Further we have included some
compile time checks to ensure that these do not get used in release
builds.
FOr QSE solving the Jacobian does not change meaninfully between steps.
We have introduced caching so that it does not need to be reevaluated
every step
Added a minimum value for the mean convergence failure which will never
trigger. This prevents situations where one or two failures begine a
trigger avalanche
We added one new check to the partitioning stage for
MultiscalePartitioningEngine view which, after group validation, prunes
any species only connected by reactions with a log(flow/mean involved
species abundance) less than -30. Currently this is a magic number and
will need to be adjusted. These pruned groups succsessfully prevent
light elements getting vacumed up into QSE groups due to their overall
weak couplings to the entire network. This is important else the
conditioning of the QSE systems falls apart.
Added a new overload of log_step_diagnostic to allow for more granular
control over what is displayed. Also made some small teaks to relative
tolerance (absolute tolerance has remained unchaged)
Comptuting the rank of a large matrix with QR factorization can be
expensive and the rank is often never needed. We have implimented a
caching system so that the rank is only computed when asked for, and
then only once. Further, the regularization method which was previously
in an anonomous namespace inside of a single translation unit has been
moved to the jacobian header and implimentation file. This allows all
parts of GridFire to access the same regularization method. Finally a
small CSV output method has been added which is useful for debugging
There are times when the jacobian matrix has infinities or nans. If
these cases correspond to species (rows or columns) which have
effectivley zero abundance (i.e. if Y(Cl-32) ~ 1e-310 and
(dY(H-2)/dt)/dY(Cl-32) is inf) then it is safe to regularize these
entries to 0. If this is not done then the solver will end up finding
NaN values for the molar abundances on subsequent steps. This has been
implimented through a small regularization function in the
CVODE_solver_strategy file.
