An indicator-based problem reduction scheme for coupled reactive transport models

A number of effective models have been developed for simulating chemical transport in porous media; however, when a reactive chemical problem comprises multiple species within a substantial domain for a long period of time, the computational cost can become prohibitively expensive. This issue is addressed here by proposing a new numerical procedure to reduce the number of transport equations to be solved. This new problem reduction scheme (PRS) uses a predictor-corrector approach, which "predicts" the transport of a set of non-indicator species using results from a set of indicator species before "correcting" the non-indicator concentrations using a mass balance error measure. The full chemical transport model is described along with experimental validation. The PRS is then presented together with an investigation, based on a 16-species reaction-advection-diffusion problem, which determines the range of applicability of different orders of the PRS. The results of a further study are presented, in which a set of PRS simulations is compared with those from full model predictions. The application of the scheme to the intermediate-sized problems considered in the present study showed reductions of up to 82% in CPU time, with good levels of accuracy maintained.