Reactive transport processes in porous media with dissolution of solid structures are widely encountered in scientific and engineering problems. In the present work, the reactive transport processes in heterogeneous porous structures generated by Monte Carlo stochastic movement are simulated by using the lattice Boltzmann method. Six dissolution patterns are identified under different Peclet and Damkohler numbers, including uniform pattern, hybrid pattern, compact pattern, conical pattern, dominant pattern, and ramified pattern. Particularly, when Peclet and Damkohler numbers are larger than 1, the increase in the heterogeneity rises the chance of preferential channel flow in the porous medium and thus intensifies the wormhole phenomena, leading to higher permeability. The pore-scale results also show that compared with the specific surface area, the permeability is more sensitive to the alteration of the structural heterogeneity, and it is challenging to propose a general formula between permeability and porosity under different reactive transport conditions and structural heterogeneity. Thus, deep neural network is employed to predict the permeability–porosity relationship. The average value of mean absolute percentage error of prediction of 12 additional permeability–porosity curves is 6.89%, indicating the promising potential of using deep learning for predicting the complicated variations of permeability in heterogeneous porous media with dissolution of solid structures.
Topology optimization (TO) is a dependable approach to obtain innovative designs with improved performance. This study presents a TO method based on the adjoint lattice Boltzmann method (ALBM) and the level set method which is developed for both one‐way coupled and two‐way coupled convective heat transfer problems. The adjoint lattice Boltzmann model for fully coupled natural convection system is derived, and the coupled solution strategy is applied in the ALBM. The forward model is validated by the finite element simulation, while the adjoint model and the sensitivity expression is validated by a finite difference check, and the whole TO method is validated by a typical pure fluid flow optimization problem given in the literature. The validated TO method is then applied to enhance the heat transfer of forced convection in a two‐dimensional open chamber, and the Pareto frontier of the bi‐objective optimization is further presented and the effects of the blockages at the inlet and outlet on the overall performance are revealed. Finally, the two‐dimensional natural convection process in a closed cavity is optimized, in which the effective heat transfer coefficient can be increased to 3.96 ∼ 6.11 times of that without the optimized design when the Grashof number ranges from 1.7 to 4.2 × 105. Moreover, effects of Grashof number, porosity limitation and solid thermal diffusivity on the optimization results are analyzed in detail. Physically reasonable designs are obtained for both forced convection and natural convection systems under various parameter settings, demonstrating the effectiveness and robustness of the presented TO method.
Coupled three-phase flow and reactive transport processes are widely encountered in many scientific and engineering problems. In the present study, a pore-scale model based on the lattice Boltzmann method is developed to simulate coupled three-phase flow and reactive transport processes. The model is validated by contact angle test of droplets on curved surface and confined reactive mass transport in a three-phase system. The pore-scale model validated is then employed to study the three-phase reactive transport in channels and porous media. The evolution of the three-phase distribution, the concentration field, and the contact line length are discussed in detail. For a two-channel structure, the result shows that as the viscosity ratio increases, the phase with higher viscosity is more difficult to be displaced. Besides, as the surface tension force between two certain phases increases, the third phase tends to form a film between the two phases, thus suppressing the reactive transport between the two phases. Finally, pore-scale simulation results of three-phase flow in a two-dimensional porous medium show that as viscosity of the displaced phase increases, the recovery rate of the displaced phase decreases, and less fingerings of the displacing phase will be formed. Finally, while the viscosity of the displaced phase can be reduced due to the existence of the species, the recovery rate does not necessarily increase, and sometimes even reduces due to the combined effects of bypass and lubrication.
Carbon capture, utilization and storage (CCUS) has been an effective way to deal with global climate issues. Injecting CO2 into depleted oil reservoirs can reach the dual goal of carbon storage and enhanced oil recovery (CO2-EOR). To optimize the gas injection strategy, it is necessary to understand the underlying mechanisms of three-phase fluid flow of oil, water and gas. In this study, a lattice Boltzmann (LB) color gradient model is used to investigate pore-scale three-phase displacement process in porous media. Gas is injected into the porous domain initially occupied by water and oil. Typical microscopic behaviors, including coalescence and split-up, pinch-off, double and multiple displacement, as well as parallel flow, are identified and discussed. Effects of water content ( ϕ), capillary number ( Ca), wettability and viscosity ratio ( M) on the flow pattern and oil recovery rate are explored. The oil ganglia inhibit the development of gas fingers, causing stronger viscous fingering characteristics with increasing ϕ. The fingering pattern located in the crossover zone for the Ca from 5×10-5 to 5×10-4. As ϕ increases, the oil recovery rate reduces. The oil ganglia tend to occupy small pores as oil wettability enhanced, making it more difficult to be drained out. The reduction of oil viscosity is beneficial to improve connectivity, thereby effectively enhancing the oil recovery. Finally, the CO2 storage rate is also evaluated. It is found that the storage rate is very sensitive to the initial oil-water distributions. Generally, the storage rate increases as ϕ decreases, Ca increases and oil wettability enhances.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.