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Propagation and tunneling of light through subwavelength photonic barriers, formed by dielectric layers with continuous spatial variations of dielectric susceptibility across the film are considered. Effects of giant heterogeneity-induced…

Materials Science · Physics 2007-09-14 Alexander Shvartsburg , Vladimir Kuzmiak , Guillaume Petite

Microflows are intensively used for investigating and controlling the dynamics of particles, including soft particles such as biological cells and capsules. A classic result is the tank-treading motion of elliptically deformed soft…

Soft Condensed Matter · Physics 2021-10-06 Matthias Laumann , Walter Zimmermann

Ionic transport in nano- to sub-nano-scale pores is highly dependent on translocation barriers and potential wells. These features in the free-energy landscape are primarily the result of ion dehydration and electrostatic interactions. For…

Mesoscale and Nanoscale Physics · Physics 2020-12-01 Subin Sahu , Michael Zwolak

Fluid flow through layered materials with different wetting behavior is observed in a wide range of applications in biological, environmental and technical systems. Therefore, it is necessary to understand the occuring transport mechanisms…

Fluid Dynamics · Physics 2022-02-01 Cynthia Michalkowski , Kilian Weishaupt , Veronika Schleper , Rainer Helmig

We tackle the question of whether the presence of particles in a pipe flow can influence the linear transient growth of infinitesimal perturbations, in view of better understanding the behaviour of particulate pipe flows in regimes of…

Fluid Dynamics · Physics 2019-03-26 Anthony Rouquier , Alban Potherat , Chris C. T. Pringle

This paper studies the mechanisms of dispersion in the laminar flow through the pore space of a $3$-dimensional porous medium. We focus on pre-asymptotic transport prior to the asymptotic hydrodynamic dispersion regime, in which solute…

Fluid Dynamics · Physics 2018-03-05 Marco Dentz , Matteo Icardi , Juan J. Hidalgo

In this paper, the inherent gradient flow structures of thermo-poro-visco-elastic processes in porous media are examined for the first time. In the first part, a modelling framework is introduced aiming for describing such processes as…

Numerical Analysis · Mathematics 2019-11-27 Jakub Wiktor Both , Kundan Kumar , Jan Martin Nordbotten , Florin Adrian Radu

A key challenge when designing particle filters in high-dimensional state spaces is the construction of a proposal distribution that is close to the posterior distribution. Recent advances in particle flow filters provide a promising avenue…

Methodology · Statistics 2017-06-30 Yunpeng Li , Mark Coates

We perform more than 6000 steady-state simulations with a dynamic pore network model, corresponding to a large span in viscosity ratios and capillary numbers. From these simulations, dimensionless quantities such as relative permeabilities,…

Fluid Dynamics · Physics 2019-11-19 Magnus Aa. Gjennestad , Mathias Winkler , Alex Hansen

Accurate modeling of diffusive transport of nanoparticles across nanopores is a particularly challenging problem. The reason is that for such narrow pores the large surface-to-volume ratio amplifies the relevance of the nanoscopic details…

Mesoscale and Nanoscale Physics · Physics 2022-11-15 Andreas Baer , Paolo Malgaretti , Malte Kaspereit , Jens Harting , Ana-Suncana Smith

Salt precipitation during CO2 injection into saline aquifers obstructs flow-controlling pore throats and reduces permeability, yet reactive transport models assume salt forms dispersed, non-porous crystals with minimal flow impact. We…

Convolutional neural networks have many hyperparameters such as the filter size, number of filters, and pooling size, which require manual tuning. Though deep stacked structures are able to create multi-scale and hierarchical…

Computer Vision and Pattern Recognition · Computer Science 2018-03-02 Ilker Cam , F. Boray Tek

Granular materials segregate by size under shear, and the ability to quantitatively predict the time required to achieve complete segregation is a key test of our understanding of the segregation process. In this paper, we apply the…

Soft Condensed Matter · Physics 2015-05-14 Lindsay B. H. May , Laura A. Golick , Katherine C. Phillips , Michael Shearer , Karen E. Daniels

We study the dynamics of flow-networks in porous media using a pore-network model. First, we consider a class of erosion dynamics assuming a constitutive law depending on flow rate, local velocities, or shear stress at the walls. We show…

Fluid Dynamics · Physics 2022-06-22 Ahmad Zareei , Deng Pan , Ariel Amir

Particle size measurement based on digital holography with conventional algorithms are usually time-consuming and susceptible to noises associated with hologram quality and particle complexity, limiting its usage in a broad range of…

Applied Physics · Physics 2020-01-01 Siyao Shao , Kevin Mallery , Jiarong Hong

Theoretical and experimental investigations of water vapor interaction with porous materials are carried out both at the macro level and at the micro level. At the macro level, the influence of the arrangement structure of individual pores…

Fluid Dynamics · Physics 2018-05-08 E. G. Nikonov , M. Pavluš , M. Popovičová

In this paper we develop a model to describe the diffusion process in a porous medium. For the observed decrease in current yield, we propose other causes than difference in diffusivity, which we consider unaltered by the porous medium. The…

Chemical Physics · Physics 2012-05-10 P. C. T. DÁjello , G. L. Nunes , J. J. Piacentini , L. Lauck

Viscosity is a fundamental property of liquids and determines the diffusivity of suspended particles. A gradient in viscosity leads to a gradient in diffusivity, yet it is unknown whether such a gradient can lead to directed transport of…

Polymer solutions are frequently used in enhanced oil recovery and groundwater remediation to improve the recovery of trapped non-aqueous fluids. However, applications are limited by an incomplete understanding of the flow in porous media.…

Soft Condensed Matter · Physics 2024-04-09 Christopher A. Browne , Audrey Shih , Sujit S. Datta

Bayesian filtering approximates the true underlying behavior of a time-varying system by inverting an explicit generative model to convert noisy measurements into state estimates. This process typically requires either storage, inversion,…

Machine Learning · Computer Science 2023-11-20 Gianluca M. Bencomo , Jake C. Snell , Thomas L. Griffiths
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