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In the selective withdrawal experiment fluid is withdrawn through a tube with its tip suspended a distance S above a two-fluid interface. At sufficiently low withdrawal rates, Q, the interface forms a steady state hump and only the upper…

Fluid Dynamics · Physics 2009-11-07 Itai Cohen

The irreversible behavior of a highly confined non-Brownian suspension of spherical particles at low Reynolds number in a Newtonian fluid is studied experimentally and numerically. In experiment, the suspension is confined in a thin…

Capillary retraction of liquid ligaments is well understood for Newtonian fluids, whereas viscoplastic effects remain comparatively unexplored. Here, we consider Herschel-Bulkley fluids, which incorporate both yield stress and…

Fluid Dynamics · Physics 2026-04-16 Shu Yang , Fahim Tanfeez Mahmood , C. Ricardo Constante-Amores

Linear stability of horizontal and inclined stratified channel flows of Newtonian/non-Newtonian shear-thinning fluids is investigated with respect to all wavelength perturbations. The Carreau model has been chosen for the modeling of the…

Fluid Dynamics · Physics 2018-02-06 Davide Picchi , Ilya Barmak , Amos Ullmann , Neima Brauner

Deep unrolling, or unfolding, is an emerging learning-to-optimize method that unrolls a truncated iterative algorithm in the layers of a trainable neural network. However, the convergence guarantees and generalizability of the unrolled…

Machine Learning · Computer Science 2024-12-02 Samar Hadou , Navid NaderiAlizadeh , Alejandro Ribeiro

Many exact coherent states (ECS) arising in wall-bounded shear flows have an asymptotic structure at extreme Reynolds number Re in which the effective Reynolds number governing the streak and roll dynamics is O(1). Consequently, these…

Fluid Dynamics · Physics 2023-07-19 Brandon Montemuro , Christopher M. White , Joseph C. Klewicki , Gregory P. Chini

Concentrated colloidal suspensions and emulsions are amorphous soft solids, widespread in technological and industrial applications and studied as model systems in physics and material sciences. They are easily fluidized by applying a…

Soft Condensed Matter · Physics 2022-12-20 Stefano Aime , Domenico Truzzolillo , David J. Pine , Laurence Ramos , Luca Cipelletti

We formulate a deterministic threshold-safety problem for a reduced compartmental voter-flow model. An exogenous load enters an alienation reservoir; between releases the reservoir recovers exponentially. Near the mainstream baseline the…

Optimization and Control · Mathematics 2026-05-26 Alexander Omelchenko

Intracellular protein patterns are described by (nearly) mass-conserving reaction-diffusion systems. While these patterns initially form out of a homogeneous steady state due to the well-understood Turing instability, no general theory…

Pattern Formation and Solitons · Physics 2024-01-11 Henrik Weyer , Fridtjof Brauns , Erwin Frey

Direct numerical simulations are conducted to study the receptivity and transition mechanisms in a solitary wave boundary layer developing over randomly organized wave-like bottom topography. The boundary layer flow shows a selective…

Fluid Dynamics · Physics 2021-02-24 Asim Önder , Philip L. -F. Liu

We propose a unifying mechanism based on the Stribeck curve for the coefficient of friction between the particles to capture the shear thinning - Newtonian plateau - shear thickening - shear thinning rheological behavior at low -…

Soft Condensed Matter · Physics 2021-06-18 Rishabh V. More , Arezoo M. Ardekani

The mechanical deformability of single cells is an important indicator for various diseases such as cancer, blood diseases and inflammation. Lab-on-a-chip devices allow to separate such cells from healthy cells using hydrodynamic forces. We…

Fluid Dynamics · Physics 2019-02-08 Christian Schaaf , Holger Stark

In this study, we investigate the transition between the Newtonian and the viscoelastic regimes during the pinch-off of droplets of dilute polymer solutions and discuss its link to the coil-stretch transition. The detachment of a drop from…

Soft Condensed Matter · Physics 2025-03-18 Sreeram Rajesh , Virgile Thiévenaz , Alban Sauret

The deformation and rupture of a lipid vesicle due to the forced normal approach of an inclusion are essential for optimizing the design of magnetic giant unilamellar vesicles [magGUVs, Malik et al., Nanoscale 17, 13720 (2025)], with…

Soft Condensed Matter · Physics 2025-12-16 Yuan-Nan Young , Bryan Quaife , Herve Nganguia , On Shun Pak , Jie Feng , Howard A. Stone

We investigate the transient, fluid structure interaction (FSI) of a non-Newtonian fluid peeling two linearly elastic sheets at low Reynolds numbers. Two different non-Newtonian fluids are considered; a simplified sPTT model, and an…

Fluid Dynamics · Physics 2023-03-14 Anirudh Venkatesh , Vishal Anand , Vivek Narsimhan

In a dilute non-Brownian suspension undergoing simple shear, pairwise hydrodynamic interactions are fore-aft symmetric at zero Reynolds number and produce no net cross-streamline displacement. A weak central repulsive force between…

Soft Condensed Matter · Physics 2026-03-31 Anu V S Nath , Pijush Patra , Anubhab Roy

The main objective of this paper is to propose an alternative procedure to carry out one of the key steps of immersion and invariance stabilising controller design. Namely, the one that ensures attractivity of the manifold whose internal…

Systems and Control · Computer Science 2016-11-18 Lei Wang , Fulvio Forni , Romeo Ortega , Hongye Su

Many functional materials, such as paints and inks used in applications like coating and 3D printing, are concentrated granular suspensions. In such systems, the contact line dynamics and the internal structure of the suspension interact…

We propose a unified approach to the formal long-wave reduction of several fluid models for thin-layer incompressible homogeneous flows driven by a constant external force like gravity. The procedure is based on a mathematical coherence…

Numerical Analysis · Mathematics 2013-06-17 François Bouchut , Sébastien Boyaval

The increasing scale of Deep Neural Networks (DNNs) introduces the need for compression techniques such as pruning, quantization, and low-rank decomposition. While these methods are very effective at reducing memory, computation, and energy…

Machine Learning · Computer Science 2026-05-04 Lorenzo Nikiforos , Luciano Prono , Charalampos Antoniadis , Fabio Pareschi , Riccardo Rovatti , Gianluca Setti