Hanchuan Wu

Zusammenfassung

In this paper, we address the expensive computational cost resulting from limited time-step sizes during numerical simulations of two-phase flow in porous media using dynamic pore-network models. To overcome this issue, we propose a numerical method for dynamic pore-network models using a fully implicit approach. The proposed method introduces a regularization strategy considering the historical fluid configuration at the pore throat, which smooths the discontinuities in local conductivity caused by invasion and snap-off events. The results demonstrate the superiority of the proposed method in terms of accuracy, efficiency and consistency in comparison with other numerical schemes. With similar computational cost, determined by time-step sizes and number of Newton iterations, the developed method in this work yields more accurate results compared to similar schemes presented in the literature. Additionally, our results highlight the enhanced robustness of the our scheme, as it exhibits reduced sensitivity to variations in time-step sizes.

Zusammenfassung

We present a numerical scheme for the solution of nonlinear mixed-dimensional PDEs describing coupled processes in embedded tubular network system in exchange with a bulk domain. Such problems arise in various biological and technical applications such as in the modeling of root-water uptake, heat exchangers, or geothermal wells. The nonlinearity appears in form of solution-dependent parameters such as pressure-dependent permeability or temperature-dependent thermal conductivity. We derive and analyze a numerical scheme based on distributing the bulk-network coupling source term by a smoothing kernel with local support. By the use of local analytical solutions, interface unknowns and fluxes at the bulk-network interface can be accurately reconstructed from coarsely resolved numerical solutions in the bulk domain. Numerical examples give confidence in the robustness of the method and show the results in comparison to previously published methods. The new method outperforms these existing methods in accuracy and efficiency. In a root water uptake scenario, we accurately estimate the transpiration rate using only a few thousand 3D mesh cells and a structured cube grid whereas other state-of-the-art numerical schemes require millions of cells and local grid refinement to reach comparable accuracy.