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Title: Modeling Bimolecular Reactions and Transport in Porous Media Via Particle Tracking

Journal Article · · Advances in Water Resources
OSTI ID:1051524

We use a particle-tracking method to simulate several one-dimensional bimolecular reactive transport experiments. In this numerical method, the reactants are represented by particles: advection and dispersion dominate the flow, and molecular diffusion dictates, in large part, the reactions. The particle/particle reactions are determined by a combination of two probabilities dictated by the physics of transport and energetics of reaction. The first is that reactant particles occupy the same volume over a short time interval. The second is the conditional probability that two collocated particles favorably transform into a reaction. The first probability is a direct physical representation of the degree of mixing in an advancing displacement front, and as such lacks empirical parameters except for the user-defined number of particles. This number can be determined analytically from concentration autocovariance, if this type of data is available. The simulations compare favorably to two physical experiments. In one, the concentration of product, 1,2-naphthoquinoe-4-aminobenzene (NQAB) from reaction between 1,2-naphthoquinone-4-sulfonic acid (NQS) and aniline (AN), was measured at the outflow of a column filled with glass beads at different times. In the other, the concentration distribution of reactants (CuSO_4 and EDTA^{4-}) and products (CuEDTA^{4-}) were quantified by snapshots of transmitted light through a column packed with cryloite sand. The thermodynamic rate coefficient in the latter experiment was 10^7 times greater than the former experiment, making it essentially instantaneous. When compared to the solution of the advection-dispersion-reaction equation (ADRE) with the well-mixed reaction coefficient, the experiments and the particle-tracking simulations showed on the order of 20% to 40% less overall product, which is attributed to poor mixing. The poor mixing also leads to higher product concentrations on the edges of the mixing zones, which the particle model simulates more accurately than the ADRE.

Research Organization:
Colorado School of Mines, Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
DOE Contract Number:
FG02-07ER15841
OSTI ID:
1051524
Report Number(s):
DOE/ER/15841-9
Journal Information:
Advances in Water Resources, Vol. in review
Country of Publication:
United States
Language:
English

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