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Using Newtonian and Brownian dynamics simulations, the structural and transport properties of hard and soft spheres have been studied. The soft spheres were modeled using inverse power potentials ($V\sim r^{-n}$, with $1/n$ the potential…

Soft Condensed Matter · Physics 2015-05-13 Erik Lange , Jose B. Caballero , Antonio M. Puertas , Matthias Fuchs

Most classical work on the hydrodynamics of low-Reynolds-number swimming addresses deterministic locomotion in quiescent environments. Thermal fluctuations in fluids are known to lead to a Brownian loss of the swimming direction. As most…

Fluid Dynamics · Physics 2014-06-18 Mario Sandoval , Navaneeth K. M. , Ganesh Subramanian , Eric Lauga

Nonhelical turbulence within a linear shear flow has demonstrated efficient amplification of large-scale magnetic fields in numerical simulations, but its precise mechanism remains elusive. The incoherent $\alpha$ mechanism proposes that a…

Plasma Physics · Physics 2024-09-10 Hongzhe Zhou , Naveen Jingade

Fluid dynamics corresponds to the dynamics of a substance in the long wavelength limit. Writing down all terms in a gradient (long wavelength) expansion up to second order for a relativistic system at vanishing charge density, one obtains…

High Energy Physics - Theory · Physics 2010-01-22 Paul Romatschke

Predicting particle-laden flows requires accurate fluid force models. However, a reliable particle force model for finite-size particles in turbulent flows remains lacking. In the present work, a fluid force model for a finite-size…

Fluid Dynamics · Physics 2025-05-29 Yuqi Wang , Ruifeng Hu

Hydrodynamics provides a concise but powerful description of long-time and long-distance physics of correlated systems out of thermodynamic equilibrium. Here we construct hydrodynamic equations for nonrelativistic particles with a…

Quantum Gases · Physics 2018-12-27 Keisuke Fujii , Yusuke Nishida

Stochastic Gradient Descent (SGD) has become a cornerstone of neural network optimization due to its computational efficiency and generalization capabilities. However, the gradient noise introduced by SGD is often assumed to be uncorrelated…

Machine Learning · Computer Science 2025-12-23 Marcel Kühn , Bernd Rosenow

We compare experimental data and numerical simulations for the dynamics of inertial particles with finite density in turbulence. In the experiment, bubbles and solid particles are optically tracked in a turbulent flow of water using an…

Chaotic Dynamics · Physics 2008-08-28 R. Volk , E. Calzavarini , G. Verhille , D. Lohse , N. Mordant , J. -F. Pinton , F. Toschi

The use of probe molecules to extract the local dynamical and structural properties of complex dynamical systems is an age-old technique both in simulations and experiments. A lot of important information which is not immediately accessible…

Soft Condensed Matter · Physics 2021-03-30 Anoop Mutneja , Smarajit Karmakar

We investigate hydrodynamic fluctuations in a 2D granular fluid excited by a vibrating base and in the presence of gravity, focusing on the transverse velocity modes. Since the system is inhomogeneous, we measure fluctuations in horizontal…

Soft Condensed Matter · Physics 2015-05-28 Giulio Costantini , Andrea Puglisi

We analytically examine fluctuations of vorticity excited by an external random force in two-dimensional fluid. We develop the perturbation theory enabling one to calculate nonlinear corrections to correlation functions of the flow…

Fluid Dynamics · Physics 2024-03-28 I. V. Kolokolov , V. V. Lebedev , V. M. Parfenyev

We develop quantitative error estimates connecting microscopic fluctuation of interacting particle systems with the mobilities of their hydrodynamic limits. Focusing on the Symmetric Simple Exclusion Process and systems of independent…

Probability · Mathematics 2026-03-06 Nicolas Dirr , Zhengyan Wu , Johannes Zimmer

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport…

Fluid Dynamics · Physics 2025-10-22 Marina Echeverria Ferrero , Nicolas Moreno , Marco Ellero

We present a theoretical study of transport properties of a liquid comprised of particles uist1:/home/sokrates/egorov/oldhome/Pap41/Submit > m abs.tex We present a theoretical study of transport properties of a liquid comprised of particles…

Soft Condensed Matter · Physics 2015-05-18 Lindsey Ann Shall , Sergei A. Egorov

We simulate the granulation process of solid spherical particles in the presence of a viscous liquid in a horizontal rotating drum by using molecular dynamics simulations in three dimensions. The numerical approach accounts for the cohesive…

The use of dissipative particle dynamics (DPD) simulation to study the rheology of fluids under shear has always been of great interest to the research community. Despite being a powerful tool, a limitation of DPD is the need to use high…

Fluid Dynamics · Physics 2025-10-31 Francesco De Roma , Luca Maffioli , Edward R. Smith , Antonio Buffo

Molecular dynamics computer simulation has been used to compute the self-diffusion coefficient, and shear viscosity of soft-sphere fluids, in which the particles interact through the soft-sphere or inverse power pair potential. The…

Soft Condensed Matter · Physics 2010-03-22 Yu. D. Fomin , V. V. Brazhkin , V. N. Ryzhov

Thermal fluctuations are a fundamental feature of dissipative systems that are essential for understanding physics near the expected critical point of QCD and in small systems. When such fluctuations are modeled naively in relativistic…

Nuclear Theory · Physics 2025-10-02 Nicki Mullins , Mauricio Hippert , Jorge Noronha

We derive equations for fluid dynamics from a non-extensive Boltzmann transport equation consistent with Tsallis' non-extensive entropy formula. We evaluate transport coefficients employing the relaxation time approximation and investigate…

Nuclear Theory · Physics 2015-05-30 T. S. Biro , E. Molnar

This work presents the mathematical and computational aspects of a smooth dissipative particle dynamics with dynamic virtual particle allocation method (SDPD-DV) for modeling and simulation of mesoscopic fluids in wall-bounded domains. The…

Fluid Dynamics · Physics 2017-08-24 Jun Yang
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