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Strongly correlated amorphous solids are a class of glass-formers whose inter-particle potential admits an approximate inverse power-law form in a relevant range of inter-particle distances. We study the steady-state plastic flow of such…

Materials Science · Physics 2015-05-13 Edan Lerner , Itamar Procaccia

Soft colloids allow to explore high density states well beyond random close packing. An important open question is whether softness controls the dynamics under these dense conditions. While experimental works reported conflicting results,…

Soft Condensed Matter · Physics 2021-06-08 Nicoletta Gnan , Emanuela Zaccarelli

Dynamics of spreading of viscous non - volatile fluid droplets on surfaces is modelled using a solid - on - solid model, which is studied with Monte Carlo simulations. Tendency for dynamical layering and surface attraction are in part…

Condensed Matter · Physics 2009-10-22 O. Venäläinen , T. Ala-Nissila , K. Kaski

This paper exploits the theory of geometric gradient flows to introduce an alternative regularization of the thin-film equation. The solution properties of this regularization are investigated via a sequence of numerical simulations whose…

Fluid Dynamics · Physics 2020-02-20 Darryl D. Holm , Lennon Ó Náraigh , Cesare Tronci

Diffusion models, a powerful and universal generative AI technology, have achieved tremendous success in computer vision, audio, reinforcement learning, and computational biology. In these applications, diffusion models provide flexible…

Machine Learning · Computer Science 2024-04-12 Minshuo Chen , Song Mei , Jianqing Fan , Mengdi Wang

Recent advances in data-driven modeling have shown that diffusion models can successfully generate synthetic Lagrangian trajectories in turbulent flows. Building on this progress, we extend the method to the joint generation of pairs of…

Many multiphase fluid systems, such as those involving immiscible polymers or liquid-liquid systems with surfactants, have shown a breakdown of the no-slip condition at the material interface. This results in systems where the tangential…

Fluid Dynamics · Physics 2023-04-05 Afsoun Rahnama Falavarjani , David Salac

The present work reports a novel investigation into the collisional dynamics of particles in the vicinity of the outlet of a 2D silo using molecular dynamics simulations. Most studies on this granular system focus in the bulk of the medium.…

Soft Condensed Matter · Physics 2022-04-20 Roberto Arévalo

We propose a computational method to simulate anomalous self-diffusion in a simple liquid. The method is based on a molecular dynamics simulation on which we impose the following two conditions: firstly, the inter-particle interaction is…

Statistical Mechanics · Physics 2010-04-07 Simon Standaert , Jan Ryckebusch , Lesley De Cruz

The transition from a microscopic model for the movement of many particles to a macroscopic continuum model for a density flow is studied. The microscopic model for the free flow is completely deterministic, described by an interaction…

Statistical Mechanics · Physics 2021-01-12 Jennifer Weissen , Simone Göttlich , Dieter Armbruster

We present a continuum approach to model segregation of size-bidisperse granular materials in unsteady bounded heap flow as a prototype for modeling segregation in other time varying flows. In experiments, a periodically modulated feed rate…

Soft Condensed Matter · Physics 2022-08-02 Hongyi Xiao , Zhekai Deng , Julio M. Ottino , Paul B. Umbanhowar , Richard M. Lueptow

We study the formation of clusters of passive Lagrangian tracers in a non-smooth turbulent flow in a flat free-slip surface as a model for particle dynamics on free surfaces. Single particle and pair dispersion show different behavior for…

Chaotic Dynamics · Physics 2009-11-07 Joerg Schumacher , Bruno Eckhardt

Diffusion generative models have demonstrated remarkable success in visual domains such as image and video generation. They have also recently emerged as a promising approach in robotics, especially in robot manipulations. Diffusion models…

Robotics · Computer Science 2025-07-15 Rosa Wolf , Yitian Shi , Sheng Liu , Rania Rayyes

The dynamics and stability of multi-spot patterns to the Gray-Scott (GS) reaction-diffusion model in a two-dimensional domain is studied in the singularly perturbed limit of small diffusivity $\epsilon$ of one of the two solution…

Pattern Formation and Solitons · Physics 2010-09-16 Wan Chen , Michael J. Ward

In this paper, a thermal-dynamical consistent model for mass transfer across permeable moving interfaces is proposed by using the energy variation method. We consider a restricted diffusion problem where the flux across the interface…

Numerical Analysis · Mathematics 2022-06-15 Yuzhe Qin , Huaxiong Huang , Yi Zhu , Chun Liu , Shixin Xu

Stochastic models of diffusion with excluded-volume effects are used to model many biological and physical systems at a discrete level. The average properties of the population may be described by a continuum model based on partial…

Chemical Physics · Physics 2012-12-20 Maria Bruna , S. Jonathan Chapman

Flow-based generative models are composed of invertible transformations between two random variables of the same dimension. Therefore, flow-based models cannot be adequately trained if the dimension of the data distribution does not match…

Computer Vision and Pattern Recognition · Computer Science 2020-11-17 Hyeongju Kim , Hyeonseung Lee , Woo Hyun Kang , Joun Yeop Lee , Nam Soo Kim

The aim of this paper is to discuss the appropriate modelling of in- and outflow boundary conditions for nonlinear drift-diffusion models for the transport of particles including size exclusion and their effect on the behaviour of…

Analysis of PDEs · Mathematics 2016-11-03 Martin Burger , Jan-Frederik Pietschmann

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…

Generative diffusion models are extensively used in unsupervised and self-supervised machine learning with the aim to generate new samples from a probability distribution estimated with a set of known samples. They have demonstrated…

Fluid Dynamics · Physics 2026-01-28 Wilfried Genuist , Éric Savin , Filippo Gatti , Didier Clouteau
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