Efficient flow and transport simulations in reconstructed 3D pore geometries

Zaretskiy, Yan; Geiger, Sebastian; Sorbie, Kenneth Stuart; Förster, Malte

doi:10.1016/j.advwatres.2010.08.008

Cited by 90 publications

(53 citation statements)

References 56 publications

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“…In this work, however, we construct a pore network that more closely represents the physical pore domains in a manner similar to those adopted in past network models of porous, granular media [23,[62][63][64]. Finally, at the macroscopic level, we compute the permeability of each of our samples by performing a finite element simulation of the fluid flow through the pore space, using a model that has been validated against physical experiments [11,[65][66][67] (step 2, Figure 1). …”

Section: A Proposed Frameworkmentioning

confidence: 99%

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Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability

2016

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We present a data-driven framework to study the relationship between fluid flow at the macroscale and the internal pore structure, across the micro-and meso-scales, in porous, granular media. Sphere packings with varying particle size distribution and confining pressure are generated using the discrete element method. For each sample, a finite element analysis of the fluid flow is performed to compute the permeability. We construct a pore network and a particle contact network to quantify the connectivity of the pores and particles across the mesoscopic spatial scales. Machine learning techniques for feature selection are employed to identify sets of microstructural properties and multiscale complex network features that optimally characterize permeability. We find a linear correlation (in log-log scale) between permeability and the average closeness centrality of the weighted pore network. With the pore network links weighted by the local conductance, the average closeness centrality represents a multiscale measure of efficiency of flow through the pore network in terms of the mean geodesic distance (or shortest path) between all pore bodies in the pore network. Specifically, this study objectively quantifies a hypothesized link between high permeability and efficient shortest paths that thread through relatively large pore bodies connected to each other by high conductance pore throats, embodying connectivity and pore structure.

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Section: A Proposed Frameworkmentioning

confidence: 99%

“…In turn, robust predictions of such properties rely on fundamental knowledge of the material's internal grain and pore structure and of its influence on the efficiencies of transmission pathways for interstitial fluid flow, heat transfer, electrical flow, stress transfer, etc. [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability

2016

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“…However, this formulation suffers from instability and time step limitation specially for the model containing small elements (Matthäi et al 2010). The scheme is implemented in and the equations are solved using CSMP++ which is an object-oriented application programmer interface (API), designed for the simulation of complex subsurface processes and their interactions Zaretskiy et al 2010;Geiger et al 2010;Unsal et al 2010;Paluszny and Zimmerman 2011).…”

Section: Mass Balance Equationmentioning

confidence: 99%

Comparison of Three FE-FV Numerical Schemes for Single- and Two-Phase Flow Simulation of Fractured Porous Media

Nick

Matthäi

2011

Transp Porous Med

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We benchmark a family of hybrid finite element-node-centered finite volume discretization methods (FEFV) for single-and two-phase flow/transport through porous media with discrete fracture representations. Special emphasis is placed on a new method we call DFEFVM in which the mesh is split along fracture-matrix interfaces so that discontinuities in concentration or saturation can evolve rather than being suppressed by nodal averaging of these variables. The main objective is to illustrate differences among three discretization schemes suitable for discrete fracture modeling: (a) FEFVM with volumetric finite elements for both fractures and porous rock matrix, (b) FEFVM with lower dimensional finite elements for fractures and volumetric finite elements for the matrix, and (c) DFEFVM with a mesh that is split along material discontinuities. Fracture discontinuities strongly influence single-and multi-phase fluid flow. Continuum methods, when used to model transport across such interfaces, smear out concentration/saturation. We show that the new DFEFVM addresses this problem producing significantly more accurate results. Sealed and open single fractures as well as a realistic fracture geometry are used to conduct tracer and water-flooding numerical experiments. The benchmarking results also reveal the limitations/mesh refinement requirements of FE node-centered FV hybrid methods. We show that the DFEFVM method produces more accurate results even for much coarser meshes.

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“…Flow of osteogenic media through the scaffolds is modelled via lattice Boltzmann method. Zaretskiy et al [15] presented a finite element-finite volume simulation method for modelling single-phase fluid flow and solute transport in experimentally obtained 3D pore geometries. Park et al [16] designed and fabricated 3D plotting system and three types of scaffolds using a rapid prototyping technique.…”

Section: Introductionmentioning

confidence: 99%

Bone Porosity Modeling and FE Simulation

Alaboodi

Al-Nasser²

2014

Second International Conference on Advances in Mechanical, Aeronautical and Production Techniques - MAPT 2014

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Abstract-Porosity in bone has many functions, which are decreasing the mass of bone relative to its volume, allow fluid to transfer through bones and give some ductility to the bone material. So that, the artificial bone should include porosity to imitate bone structure. To achieve the porosity functions on artificial bone many requirement should be consider such as material property and structure requirements. Researchers had modeled porosity by either regular or irregular shaped. Irregular shape has been modeled by copying several layers from natural pone CT scan images. Regular porous shape could be design by deferent shapes that confirm the porosity function requirement. The aim of this paper is to propose model that satisfy the function of porosity in real bone and attain the requirement on material and structure.

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Efficient flow and transport simulations in reconstructed 3D pore geometries

Cited by 90 publications

References 56 publications

Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability

Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability

Comparison of Three FE-FV Numerical Schemes for Single- and Two-Phase Flow Simulation of Fractured Porous Media

Bone Porosity Modeling and FE Simulation

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