  Most one-dimensional core-collapse simulations fail to explode, yet
multi-dimensional simulations often explode. A dominant multi-dimensional
effect aiding explosion is neutrino-driven convection. We incorporate a
convection model in approximate one-dimensional core-collapse supernova (CCSN)
simulations. This is the 1D+ method. This convection model lowers the neutrino
luminosity required for explosion by 30%, similar to the reduction observed in
multi-dimensional simulations. The model is based upon the global turbulence
model of Mabanta & Murphy (2018) and models the mean-field turbulent flow of
neutrino-driven convection. In this preliminary investigation, we use simple
neutrino heating and cooling algorithms to compare the critical condition in
the 1D+ simulations with the critical condition observed in two-dimensional
simulations. Qualitatively, the critical conditions in the 1D+ and the
two-dimensional simulations are similar. The assumptions in the convection
model affect the radial profiles of density, entropy, and temperature, and
comparisons with the profiles of three dimensional simulations will help to
calibrate these assumptions. These 1D+ simulations are consistent with the
profiles and explosion conditions of equivalent two-dimensional CCSN
simulations but are ~100 times faster, and the 1D+ prescription has the
potential to be ~100,000 faster than three-dimensional CCSN simulations. The
1D+ technique will be ideally suited to test the explodability of thousands of
progenitor models.
