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.
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