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

Area of Science:

• Environmental Science
• Computational Chemistry
• Geochemistry

Background:

• Simulating chemical transport in porous media is crucial for understanding environmental processes.
• Existing models face computational challenges with multi-species, long-term, and large-domain reactive transport problems.
• High computational cost limits the application of detailed models in practical scenarios.

Purpose of the Study:

• To develop a novel numerical procedure to reduce computational expense in reactive chemical transport simulations.
• To introduce and validate a problem reduction scheme (PRS) for efficient multi-species transport modeling.
• To determine the applicability and accuracy of the PRS across different simulation orders.

Main Methods:

• Development of a problem reduction scheme (PRS) employing a predictor-corrector approach.
• PRS utilizes indicator species to predict the transport of non-indicator species.
• Mass balance error is used to correct non-indicator concentrations; experimental validation was performed.

Main Results:

• The PRS demonstrated significant reductions in computational time, up to 82% for intermediate-sized problems.
• Accuracy was maintained at high levels comparable to full model predictions.
• An investigation determined the range of applicability for different orders of the PRS.

Conclusions:

• The proposed problem reduction scheme (PRS) offers an efficient and accurate alternative for complex chemical transport simulations.
• PRS effectively addresses the computational limitations of traditional models for multi-species reactive transport.
• This method enhances the feasibility of simulating large-scale, long-term environmental and geochemical processes.