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Due to the computational complexity of micro-swimmer models with fully resolved hydrodynamics, parameter estimation has been prohibitively expensive. Here, we describe a Bayesian uncertainty quantification framework that is highly…

Quantitative Methods · Quantitative Biology 2019-10-29 Karen Larson , Sarah Olson , Anastasios Matzavinos

Vertical equilibrium models have proven to be well suited for simulating fluid flow in subsurface porous media such as saline aquifers with caprocks. However, in most cases the dimensionally reduced model lacks the accuracy to capture the…

Fluid Dynamics · Physics 2024-05-29 Ivan Buntic , Martin Schneider , Bernd Flemisch , Rainer Helmig

We consider a one-dimensional continuous time random walk with transition rates depending on an underlying autonomous simple symmetric exclusion process starting out of equilibrium. This model represents an example of a random walk in a…

Probability · Mathematics 2016-11-26 Luca Avena , Tertuliano Franco , Milton Jara , Florian Völlering

Living systems continuously transform matter and energy through the chemical processes that constitute their metabolism. The overall metabolic rate of an organism correlates positively with its body mass, however both the exact scaling…

Soft Condensed Matter · Physics 2026-03-19 Efe Ilker , Michael Hinczewski , Xingbo Yang , Frank Jülicher

Macroscopic properties of heterogeneous media are frequently modelled by regular lattice models, which are based on a relatively small basic cluster of lattice sites. Here, we extend one of such models to any cluster's size kxk. We also…

Statistical Mechanics · Physics 2015-03-24 W. Olchawa , R. Wiśniowski , D. Frączek , R. Piasecki

We investigate how a filter media microstructure influences filtration performance. We derive a theory that generalizes classical multiscale models for regular structures to account for filter media with more realistic microstructures,…

Fluid Dynamics · Physics 2019-01-30 Galina Printsypar , Maria Bruna , Ian M. Griffiths

We study the interplay of pore-scale mixing and network-scale advection through heterogeneous porous media, and its role for the evolution and asymptotic behavior of hydrodynamic dispersion. In a Lagrangian framework, we identify three…

Fluid Dynamics · Physics 2021-04-28 Alexandre Puyguiraud , Philippe Gouze , Marco Dentz

We study a stochastic model of a copolymerization process that has been extensively investigated in the physics literature. The main questions of interest include: (i) what are the criteria for transience, null recurrence, and positive…

Probability · Mathematics 2025-12-12 David F. Anderson , Jingyi Ma , Praful Gagrani

Atmospheric models used for weather and climate prediction are traditionally formulated in a deterministic manner. In other words, given a particular state of the resolved scale variables, the most likely forcing from the sub-grid scale…

Machine Learning · Computer Science 2024-02-16 Hannah M. Christensen , Salah Kouhen , Greta Miller , Raghul Parthipan

A three-dimensional model of polydisperse reactive sedimentation is developed by means of a multilayer shallow water approach. The model consists of a variety of solid particles of different sizes and densities, and substrates diluted in…

Numerical Analysis · Mathematics 2024-03-13 Julio Careaga , Víctor Osores

In this paper we present a hydrodynamic approach to describe the motion of migrating bacteria as a special class of self-propelled systems. Analytical and numerical calculations has been performed to study the behavior of our model in the…

Soft Condensed Matter · Physics 2015-06-25 Zoltan Csahok , Andras Czirok

Numerical simulations for flow and transport in subsurface porous media often prove computationally prohibitive due to property data availability at multiple spatial scales that can vary by orders of magnitude. A number of model order…

Numerical Analysis · Mathematics 2018-03-13 Gurpreet Singh , Wingtat Leung , Mary F. Wheeler

A micro-hydrodynamics model based on elastic collisions of light point solvent particles with a heavy solute particle is investigated in the setting where the light particles have velocity distribution corresponding to a background flow.…

Fluid Dynamics · Physics 2023-11-21 Radek Erban , Robert A. Van Gorder

Modeling biological processes is a highly demanding task because not all processes are fully understood. Mathematical models allow us to test hypotheses about possible mechanisms of biological processes. The mathematical mechanisms…

Numerical Analysis · Mathematics 2023-12-11 Cordula Reisch , Hannah Burmester

A major challenge in flow through porous media is to better understand the link between microstructure and macroscale flow and transport. For idealised microstructures, the mathematical framework of homogenisation theory can be used for…

The application of process-based and data-driven hydrological models is crucial in modern hydrological research, especially for predicting key water cycle variables such as runoff, evapotranspiration (ET), and soil moisture. These models…

Geophysics · Physics 2024-08-14 Haiyang Shi

Clogging of microchannels due to particle adhesion on the walls is a serious problem in many industrial processes. As such, the service life of microfluidic systems is determined by their ability to maintain flow without interruption over a…

Fluid Dynamics · Physics 2023-12-12 Lyudmila S. Klimenko , Boris S. Maryshev

Relativistic hydrodynamics of classic plasmas is derived from the microscopic model in the limit of ideal plasmas. The chain of equations is constructed step by step starting from the concentration evolution. It happens that the energy…

Plasma Physics · Physics 2023-08-09 Pavel A. Andreev

We describe a recent multiscale approach based on the concurrent coupling of constrained molecular dynamics for long biomolecules with a mesoscopic lattice Boltzmann treatment of solvent hydrodynamics. The multiscale approach is based on a…

Biological Physics · Physics 2008-02-27 Maria Fyta , Simone Melchionna , Efthimios Kaxiras , Sauro Succi

Metriplectic systems are learned from data in a way that scales quadratically in both the size of the state and the rank of the metriplectic data. Besides being provably energy conserving and entropy stable, the proposed approach comes with…

Machine Learning · Computer Science 2025-01-28 Anthony Gruber , Kookjin Lee , Haksoo Lim , Noseong Park , Nathaniel Trask