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Related papers: Flow through Pore-Size Graded Membrane Pore Networ…

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Presented in this work is a framework for the data-driven determination of multi-scale porous media parametrizations. Simulations of flow and transport in a porous medium at the REV scale, although efficient, require well defined parameters…

Numerical Analysis · Mathematics 2023-11-27 Edward Coltman , Martin Schneider , Rainer Helmig

Recently, many researchers have been focusing on the definition of neural networks for graphs. The basic component for many of these approaches remains the graph convolution idea proposed almost a decade ago. In this paper, we extend this…

Machine Learning · Computer Science 2018-11-27 Dinh Van Tran , Nicolò Navarin , Alessandro Sperduti

Many natural fibrous networks with fiber diameters much smaller than the average poresize can be described as three-dimensional (3D) random line networks. We consider here a `Mikado' model for such systems, consisting of straight line…

Quantitative Methods · Quantitative Biology 2011-10-11 Claus Metzner , Patrick Krauss , Ben Fabry

Bacteria commonly inhabit porous environments such as host tissues, soil, and marine sediments, where complex geometries constrain and redirect their motion. Although bacterial motility has been studied in porous media, the roles of cell…

Soft Condensed Matter · Physics 2025-12-22 David Gao , Zeyuan Wang , Mihika Jain , Arnold J. T. M. Mathijssen , Ran Tao

Recently developed particle flow algorithms provide an alternative to importance sampling for drawing particles from a posterior distribution, and a number of particle filters based on this principle have been proposed. Samples are drawn…

Computation · Statistics 2014-12-01 Pete Bunch , Simon Godsill

Recently, there has been a surge of interest in incorporating neural networks into particle filters, e.g. differentiable particle filters, to perform joint sequential state estimation and model learning for non-linear non-Gaussian…

Machine Learning · Computer Science 2025-01-07 Xiongjie Chen , Yunpeng Li

We develop a novel `moving capacitor' dynamic network model to simulate immiscible fluid-fluid displacement in porous media. Traditional network models approximate the pore geometry as a network of fixed resistors, directly analogous to an…

We present a generalized network model for simulating capillary-dominated two-phase flow through porous media at the pore scale. Three-dimensional images of the pore space are discretized using a generalized network -- described in a…

Computational Physics · Physics 2018-03-13 Ali Q. Raeini , Branko Bijeljic , Martin J. Blunt

Filtration of feed containing multiple species of particles is a common process in the industrial setting. In this work we propose a model for filtration of a suspension containing an arbitrary number of particle species, each with…

Optimization and Control · Mathematics 2021-06-30 Yixuan Sun , Lou Kondic , Linda J. Cummings

We describe a method for modeling the geometry of porous materials. The approach enables the independent selection of crucial parameters, including porosity, pore size distribution, pore shape, and connectivity. Consequently, it can…

Materials Science · Physics 2024-04-19 Felix Buchele , Patric Müller , Michael Blank , Thorsten Pöschel

The convergence between effective medium theory and pore-network modelling is examined. Electrical conductance on two and three-dimensional cubic resistor networks is used as an example of transport through composite materials or porous…

Materials Science · Physics 2021-09-17 Jack Edwards , Peter Berg

This study investigates interlayer diffusion dynamics in sodium montmorillonite (Na--MMT), a smectite clay widely used in environmental remediation, pharmaceutical formulations, and advanced materials. Understanding diffusion in Na--MMT is…

This study investigates the coupled deformation and flow behavior of thin, hyper-elastic, porous membranes subjected to pressure loading. Using bulge test experiments, optical deformation measurements, and flow rate characterization, we…

Fluid Dynamics · Physics 2026-01-19 Alexander Gehrke , Zoe King , Kenneth S. Breuer

Concentration gradients play a critical role in embryogenesis, bacterial locomotion, as well as the motility of active particles. Particles develop concentration profiles around them by dissolution, adsorption, or the reactivity of surface…

We report a numerical study of Rayleigh--B\'enard convection through random porous media using pore-scale modelling, focusing on the Lagrangian dynamics of fluid particles and heat transfer for varied porosities $\phi$. Due to the…

Fluid Dynamics · Physics 2021-04-29 Shuang Liu , Linfeng Jiang , Cheng Wang , Chao Sun

Gas transport across cell membrane is a very important process in biochemistry which is essential for many crucial tasks, including cell respiration pH regulation in the cell. In the late 1990's, the suggestion that gasses are transported…

Numerical Analysis · Mathematics 2026-01-29 Alberto Bocchinfuso , Daniela Calvetti , Erkki Somersalo

A method of higher-order modes filtering in an air-filled waveguide using a resistive layer is proposed. An analogue of Cremer's criterion is discussed and used to obtain the optimal modal attenuation of the non-planar waves while the plane…

Applied Physics · Physics 2023-07-18 Svetlana Kuznetsova , Yves Auregan , Vincent Pagneux

Particle filters are a powerful and flexible tool for performing inference on state-space models. They involve a collection of samples evolving over time through a combination of sampling and re-sampling steps. The re-sampling step is…

Computation · Statistics 2017-03-17 Deborshee Sen , Alexandre Thiery , Ajay Jasra

The local flow field and seepage induced drag obtained from Pore Network Models (PNM) is compared to Immersed Boundary Method (IBM) simulations, for a range of linear graded and bimodal samples. PNM were generated using a weighted Delaunay…

Fluid Dynamics · Physics 2022-01-11 Adnan Sufian , Chris Knight , Catherine O'Sullivan , Berend van Wachem , Daniele Dini

Two-dimensional crystals with angstrom-scale pores are widely considered as candidates for a next generation of molecular separation technologies aiming to provide extreme, exponentially large selectivity combined with high flow rates. No…

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