We present a versatile open-source pipeline for simulating inhomogeneous reaction-diffusion processes in highly resolved, image-based geometries of porous media with reactive boundaries. Resolving realistic pore-scale geometries in numerical models is challenging and computationally demanding, as the scale differences between the sizes of the interstitia and the whole system can lead to prohibitive memory requirements. The present pipeline combines a level-set method with geometry-adapted sparse block grids on GPUs to efficiently simulate reaction-diffusion processes in image-based geometries. We showcase the method by applying it to fertilizer diffusion in soil, heat transfer in porous ceramics, and determining effective diffusion coefficients and tortuosity. The present approach enables solving reaction-diffusion partial differential equations in real-world geometries applicable to porous media across fields such as engineering, environmental science, and biology.

翻译：我们提出一种多功能开源管道，用于在具有反应边界的高分辨率图像化多孔介质几何结构中模拟非均匀反应-扩散过程。在数值模型中解析真实孔隙尺度几何结构极具挑战性且计算成本高昂，因为孔隙间隙尺寸与整个系统尺度之间的差异可能导致内存需求过高。本管道将水平集方法与基于GPU的几何自适应稀疏块网格相结合，以高效模拟图像化几何结构中的反应-扩散过程。通过将其应用于土壤中肥料扩散、多孔陶瓷热传导以及有效扩散系数和弯曲度的测定，我们展示了该方法的应用效果。本方法能够求解工程、环境科学和生物学等领域中适用于多孔介质的真实几何结构下的反应-扩散偏微分方程。