Simulating non-wetting fluid invasion in volumetric images of porous materials is of broad interest in applications as diverse as electrochemical devices and CO2 sequestration. Among available methods, image-based algorithms offer much lower computational cost compared to direct numerical simulations. Recent work has extended image-based methods to incorporate more physics such as gravity and volume-controlled invasion. The present work combines these two developments to develop an image-based invasion percolation algorithm that incorporates the effect of gravity. Additionally, the presented algorithm was developed using a priority queue algorithm to drastically reduce the computational cost of the simulation. The priority queue-based method was validated against previous image-based methods both with and without the effect of gravity, showing identical results. It was also shown that the new method provides a speedup of 20X over the previous image-based methods. Finally, comparison with experimental results at three Bond numbers showed that the model can predict the real invasion process with a high accuracy with and without gravitational effects.

中文翻译：

---

一种基于队列的计算高效算法，用于模拟重力影响下多孔材料体积图像的体积控制排水


在多孔材料的体积图像中模拟非润湿流体侵袭在电化学设备和 CO2 封存等各种应用中具有广泛的意义。在可用方法中，与直接数值模拟相比，基于图像的算法提供的计算成本要低得多。最近的工作扩展了基于图像的方法，以纳入更多物理场，例如重力和体积控制侵入。目前的工作结合了这两项发展，开发了一种基于图像的侵入渗流算法，该算法结合了引力的影响。此外，所提出的算法是使用优先级队列算法开发的，以大大降低仿真的计算成本。基于优先级队列的方法与以前基于图像的方法进行了验证，无论有没有重力影响，都显示出相同的结果。研究还表明，新方法的加速比以前基于图像的方法快 20 倍。最后，与三个 Bond 数的实验结果进行比较表明，该模型在有和没有引力效应的情况下都能高精度地预测真实的入侵过程。