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Taylor's model of dispersion simply describes the long-term spread of material along a pipe, channel or river. However, often we need multi-mode models to resolve finer details in space and time. Here we construct zonal models of dispersion…

chao-dyn · Physics 2008-02-03 S. D. Watt , A. J. Roberts

In the context of data-driven control of nonlinear systems, many approaches lack of rigorous guarantees, call for nonconvex optimization, or require knowledge of a function basis containing the system dynamics. To tackle these drawbacks, we…

Systems and Control · Electrical Eng. & Systems 2023-10-05 Tim Martin , Frank Allgöwer

Classical Taylor-Aris dispersion theory is extended to describe the transport of suspensions of self-propelled dipolar cells in a tubular flow. General expressions for the mean drift and effective diffusivity are determined exactly in terms…

Soft Condensed Matter · Physics 2010-08-25 M. A. Bees , O. A. Croze

This work presents a hierarchical model for solute transport in bounded layered porous media with random permeability. The model generalizes the Taylor-Aris dispersion theory to stochastic transport in random layered porous media with a…

Fluid Dynamics · Physics 2018-07-27 Zhijie Xu , Alexandre M. Tartakovsky

Polymers consisting of more than one type of monomer, known as copolymers, are vital to both living and synthetic systems. Copolymerisation has been studied theoretically in a number of contexts, often by considering a Markov process in…

We provide a general method to analyze the asymptotic properties of a variety of estimators of continuous time diffusion processes when the data are not only discretely sampled in time but the time separating successive observations may…

Statistics Theory · Mathematics 2007-06-13 Yacine Ait-Sahalia , Per A. Mykland

In fully-developed pressure-driven flow, the spreading of a dissolved solute is enhanced in the flow direction due to transverse velocity variations in a phenomenon now commonly referred to as Taylor-Aris dispersion. It is well understood…

Fluid Dynamics · Physics 2022-10-04 Garam Lee , Alan Luner , Jeremy Marzuola , Daniel M. Harris

Taylor diffusion (or dispersion) refers to a phenomenon discovered experimentally by Taylor in the 1950s where a solute dropped into a pipe with a background shear flow experiences diffusion at a rate proportional to $1/\nu$, which is much…

Analysis of PDEs · Mathematics 2019-09-04 Margaret Beck , Osman Chaudhary , C. Eugene Wayne

One of the cornerstones of turbulent dispersion is the celebrated Taylor formula. This formula expresses the rate of transport (i.e. the eddy diffusivity) of a tracer as a time integral of the fluid velocity auto-correlation function…

Fluid Dynamics · Physics 2018-10-16 S. Boi , A. Mazzino , P. Muratore-Ginanneschi , S. Olivieri

A theoretical analysis is developed to investigate the effects of gas expansion due to heat release on unsteady diffusion flames evolving in a pipe flow in which the mixing of reactants is controlled by Taylor's dispersion processes thereby…

Fluid Dynamics · Physics 2024-07-03 Prabakaran Rajamanickam , Adam D. Weiss

We investigate diffusion in a polydisperse granular media. We derive mean-squared displacement of granular particles in a polydisperse granular gas in a homogeneous cooling state, containing arbitrary amount of species of different sizes…

Soft Condensed Matter · Physics 2024-03-21 Anna S. Bodrova

The paper investigates the problem of performing correlation analysis when the number of observations is very large. In such a case, it is often necessary to combine the random observations to achieve dimensionality reduction of the…

Information Theory · Computer Science 2020-10-19 Pavel Loskot

Channels are fundamental building blocks from biophysics to soft robotics, often used to transport or separate solutes. As solute particles inevitably transverse between streamlines along the channel by molecular diffusion, the effective…

Soft Condensed Matter · Physics 2020-02-10 Sophie Marbach , Karen Alim

We present a generalized hydrodynamic stability theory for interacting particles in polydisperse particle-laden flows. The addition of dispersed particulate matter to a clean flow can either stabilize or destabilize the flow, depending on…

Fluid Dynamics · Physics 2022-04-20 Zhixuan Liu , Yuval Dagan

Significance: The depolarization of circularly polarized light caused by scattering in turbid media reveals structural information about the dispersed particles, such as their size, density, and distribution, which is useful for…

Medical Physics · Physics 2024-06-05 Nozomi Nishizawa , Asato Esumi , Yukito Ganko

Accurate descriptions of reference systems are a central task in liquid-state theories for the study of more complex systems. Using scaled particle theory (SPT), we derive a fully analytical description of the thermodynamic properties of a…

Soft Condensed Matter · Physics 2026-03-31 T. Hvozd , M. Hvozd , M. Holovko

Both polydispersity and the presence of a gravitational field are inherent to essentially any colloidal experiment. While several theoretical works have focused on the effect of polydispersity on the bulk phase behavior of a colloidal…

Soft Condensed Matter · Physics 2022-12-28 Tobias Eckert , Matthias Schmidt , Daniel de las Heras

We establish a link between the phenomenon of Taylor dispersion and the theory of empirical distributions. Using this connection, we derive, upon applying the theory of large deviations, an alternative and much more precise description of…

Statistical Mechanics · Physics 2017-02-01 Marcel Kahlen , Andreas Engel , Christian Van den Broeck

Often experimentalists study colloidal suspensions that are nominally monodisperse. In reality these samples have a polydispersity of 4-10%. At the level of an individual particle, the consequences of this polydispersity are unknown as it…

Soft Condensed Matter · Physics 2012-11-09 Rei Kurita , Eric R. Weeks

Discrete diffusion models have recently gained significant prominence in applications involving natural language and graph data. A key factor influencing their effectiveness is the efficiency of discretized samplers. Among these,…

Machine Learning · Computer Science 2025-11-03 Yuchen Liang , Yingbin Liang , Lifeng Lai , Ness Shroff