Abstract

We present a new optimization-based conservative transport algorithm for scalar quantities (i.e. mass) that preserves monotonicity without the use of flux limiters. The method is formulated as a singly linearly constrained quadratic program with simple bounds where the net mass updates to the cell are the optimization variables. The objective is to minimize the discrepancy between a target or high-order mass update and a mass update that satisfies physical bounds. In this way, we separate accuracy considerations, handled by the objective functional from the enforcement of physical bounds, handled by the contraints. With this structure mass conservation is incorporated as a constraint and a simple, efficient, and easily parallelizable optimization algorithm is obtained. This algorithm has been extended to a latitude-longitude grid for two-dimensional remapping and transport on the sphere. Results for several standard test problems on the sphere will be shown to illustrate the accuracy and robustness of the method.