Adaptive Cartesian Sharp Interface Method for Three-Dimensional Multi-Phase Flows

Author(s):  
HyoungJin Kim ◽  
Meng-Sing Liou
2017 ◽  
Vol 9 (5) ◽  
pp. 1052-1075 ◽  
Author(s):  
Xiao Bai ◽  
Xiaolong Deng

AbstractA new sharp interface method with the combination of Ghost Fluid Method (GFM) and Cut Cell scheme is developed to study compressible multi-phase flows with clear interfaces. Straight-line cutting is applied on the cells passed by the interface. A new real-ghost mixing method is presented and applied around the cut cells to deal with very small cut cells. A cut face reconstruction method similar to volume of fluid is applied to deal with topological change problems. A high order Level Set (LS) method is applied to evolve the free interface, with the Level Set velocities from exact Riemann solver on the cut faces. Various 1D and 2D numerical examples are tested to show the robustness and ability of the present method in wide flow variable domains. This method benefits from cut cell on the sharp interface description, shows good conservation performance, and does not have the topological change difficulty of the full cut cell method presented in Chang, Deng & Theofanous, J. Comput. Phys., 242 (2013), pp. 946–990.


Author(s):  
Fazlolah Mohaghegh ◽  
John Mousel ◽  
H. S. Udaykumar

This study is a comparison of two techniques for simulation of particulate flows on fixed Cartesian grids: Sharp interface Method (SIM) (Udaykumar et al., 2001, 2002, 2003) and a modified version of Immersed Boundary Method (Peskin, 1977) (IBM) known as Smoothed Profile Method (SPM) (Nakayama and Yamamoto, 2005; Luo et. al, 2009). Different cases were studied includes flow over one or two moving and stationary particles. Predictions of the drag coefficient shows that SPM and SIM are very close to the experiments. SIM slightly under-predicts the value of the drag coefficient while SPM has a small over-estimation. Moreover, SPM is more accurate on coarse grids. However, with refinement of the grid SIM approaches the exact values very fast leading to better results on fine grids. Flow pattern and vortex structures of SPM and SIM are almost the same. Both methods are capable of analyzing the wake flow. Unlike SIM, SPM is able to simulate the flow when two particles are in contact. When two particles are in motion and are very close in a way that the two interfaces overlap, SPM shows a repulsion force between two spheres which reduces the accuracy in comparison with SIM. However, SPM can achieve the collision of two particles without problem.


2021 ◽  
Vol 46 (3) ◽  
pp. 2978-2989 ◽  
Author(s):  
Guobin Zhang ◽  
Zhiming Bao ◽  
Biao Xie ◽  
Yun Wang ◽  
Kui Jiao

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1636 ◽  
Author(s):  
Roshina Babu ◽  
Namsik Park ◽  
Sunkwon Yoon ◽  
Taaniela Kula

Sustainable management of small island freshwater resources requires an understanding of the extent of freshwater lens and local effects of pumping. In this study, a methodology based on a sharp interface approach is developed for regional and well scale modeling of island freshwater lens. A quasi-three-dimensional finite element model is calibrated with freshwater thickness where the interface is matched to the lower limit of the freshwater lens. Tongatapu Island serves as a case study where saltwater intrusion and well salinization for the current state and six long-term stress scenarios of reduced recharge and increased groundwater pumping are predicted. Though no wells are salinized currently, more than 50% of public wells are salinized for 40% decreased recharge or increased groundwater pumping at 8% of average annual recharge. Risk of salinization for each well depends on the distance from the center of the well field and distance from the lagoon. Saltwater intrusions could occur at less than 50% of the previous estimates of sustainable groundwater pumping where local pumping was not considered. This study demonstrates the application of a sharp interface groundwater model for real-world small islands when dispersion models are challenging to be implemented due to insufficient data or computational resources.


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