CNN-PFVS: Integrating Neural Network and Finite Volume Models to Accelerate Flow Simulation on Pore Space Images

2020 ◽  
Vol 135 (1) ◽  
pp. 25-37
Author(s):  
Traiwit Chung ◽  
Ying Da Wang ◽  
Ryan T. Armstrong ◽  
Peyman Mostaghimi
2021 ◽  
Vol 594 ◽  
pp. 125924
Author(s):  
Janice Lynn Ayog ◽  
Georges Kesserwani ◽  
James Shaw ◽  
Mohammad Kazem Sharifian ◽  
Domenico Bau

2014 ◽  
Vol 55 (13) ◽  
pp. 3587-3612 ◽  
Author(s):  
Rattandeep Singh ◽  
Sandeep Gupta ◽  
S. Raman ◽  
Prodyut Chakraborty ◽  
Puneet Sharma ◽  
...  

2021 ◽  
pp. 132442
Author(s):  
Yi Ouyang ◽  
Laurien A. Vandewalle ◽  
Lin Chen ◽  
Pieter P. Plehiers ◽  
Maarten R. Dobbelaere ◽  
...  

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 179 ◽  
Author(s):  
Yuanfu Xie

Z-grid finite volume models conserve all-scalar quantities as well as energy and potential enstrophy and yield better dispersion relations for shallow water equations than other finite volume models, such as C-grid and C-D grid models; however, they are more expensive to implement. During each time integration, a Z-grid model must solve Poisson equations to convert its vorticity and divergence to a stream function and velocity potential, respectively. To optimally utilize these conversions, we propose a model in which the stability and possibly accuracy on the sphere are improved by introducing more stencils, such that a generalized Z-grid model can utilize longer time-integration steps and reduce computing time. Further, we analyzed the proposed model’s dispersion relation and compared it to that of the original Z-grid model for a linearly rotating shallow water equation, an important property for numerical models solving primitive equations. The analysis results suggest a means of balancing stability and dispersion. Our numerical results also show that the proposed Z-grid model for a shallow water equation is more stable and efficient than the original Z-grid model, increasing the time steps by more than 1.4 times.


Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4684 ◽  
Author(s):  
Paulina Krakowska ◽  
Paweł Madejski

The paper presents results of fluid flow simulation in tight rock being potentially gas-bearing formation. Core samples are under careful investigation because of the high cost of production from the well. Numerical simulations allow determining absolute permeability based on computed X-ray tomography images of the rock sample. Computational fluid dynamics (CFD) give the opportunity to use the partial slip Maxwell model for permeability calculations. A detailed 3D geometrical model of the pore space was the input data. These 3D models of the pore space were extracted from the rock sample using highly specialized software poROSE (poROus materials examination SoftwarE, AGH University of Science and Technology, Kraków, Poland), which is the product of close cooperation of petroleum science and industry. The changes in mass flow depended on the pressure difference, and the tangential momentum accommodation coefficient was delivered and used in further quantitative analysis. The results of fluid flow simulations were combined with laboratory measurement results using a gas permeameter. It appeared that for the established parameters and proper fluid flow model (partial slip model, Tangential Momentum Accommodation Coefficient (TMAC), volumetric flow rate values), the obtained absolute permeability was similar to the permeability from the core test analysis.


2017 ◽  
Vol 21 (5-6) ◽  
pp. 1023-1033 ◽  
Author(s):  
Vasiliy Kramarenko ◽  
Kirill Nikitin ◽  
Yuri Vassilevski

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