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We study particle transport in a class of open channels of finite length, made of identical cells of connected open polygonal billiards with parallel boundaries. In these systems the Mean Square Displacement (MSD) grows in time faster than…

Statistical Mechanics · Physics 2025-03-20 Luisana Claudio-Pachecano , Hernán Larralde , Carlos Mejía-Monasterio

Deterministic lateral displacement (DLD) is a high-resolution separation technique used in various fields. A fundamental challenge in DLD is ensuring uniform flow characteristics across channel, particularly near sidewalls where pillar…

Fluid Dynamics · Physics 2025-06-10 Aryan Mehboudi , Shrawan Singhal , S. V. Sreenivasan

A phenomenological model of the evolution of an ensemble of interacting dislocations in an isotropic elastic medium is formulated. The line-defect microstructure is described in terms of a spatially coarse-grained order parameter, the…

mtrl-th · Physics 2009-10-30 J. M. Rickman , Jorge Vinals

Plastic deformation of crystals is a physical phenomenon, which has immensely driven the development of human civilisation since the onset of the Chalcolithic period. This process is primarily governed by the motion of line defects, called…

Materials Science · Physics 2009-07-15 A. Dutta , M. Bhattacharya , P. Mukherjee , N. Gayathri , G. C. Das , P. Barat

Equations for dislocation evolution bridge the gap between dislocation properties and continuum descriptions of plastic behavior of crystalline materials. Computer simulations can help us verify these evolution equations and find their…

Materials Science · Physics 2020-11-11 Kamyar M. Davoudi , Joost J. Vlassak

Discrete models of dislocations in cubic crystal lattices having one or two atoms per unit cell are proposed. These models have the standard linear anisotropic elasticity as their continuum limit and their main ingredients are the elastic…

Materials Science · Physics 2009-11-13 L. L. Bonilla , A. Carpio , I. Plans

A class of congruences of principal Volterra-type effective dislocation lines associated with a dislocation density tensor is distinguished in order to investigate the kinematics of continuized defective crystals in terms of their…

Mathematical Physics · Physics 2010-03-17 Andrzej Trzesowski

Dislocations in ceramics have recently gained renewed research interest, in contrast to the traditional belief that ceramics are inherently brittle. Understanding dislocation mechanics in representative oxides is beneficial for effective…

A statistical mechanics theory for a fluid stratified in density is presented. The predicted statistical equilibrium state is the most probable outcome of turbulent stirring. The slow temporal evolution of the vertical density profile is…

Fluid Dynamics · Physics 2014-09-23 Antoine Venaille , Louis Gostiaux , Joël Sommeria

Dislocation climb plays an important role in understanding plastic deformation of metallic materials at high temperature. In this paper, we present a continuum formulation for dislocation climb velocity based on densities of dislocations.…

Materials Science · Physics 2023-08-15 Chutian Huang , Shuyang Dai , Xiaohua Niu , Tianpeng Jiang , Zhijian Yang , Yejun Gu , Yang Xiang

In this work a periodic crystal with point defects is described in the framework of linear response theory for broken symmetry states using correlation functions and Zwanzig-Mori equations. The main results are microscopic expressions for…

Soft Condensed Matter · Physics 2015-05-18 Christof Walz , Matthias Fuchs

Deformation band patterning in single crystals is investigated using a finite strain crystal viscoplasticity model based on the evolution of dislocation densities. In the presence of strong latent hardening and weak rate dependence, the…

Materials Science · Physics 2025-07-02 Jean-Michel Scherer

Digital image correlation (DIC) is a well-established, non-invasive technique for tracking and quantifying the deformation of mechanical samples under strain. While it provides an obvious way to observe incremental and aggregate…

Materials Science · Physics 2019-04-16 Stefanos Papanikolaou , Michail Tzimas , Andrew C. E. Reid , Stephen A. Langer

Detecting out-of-distribution (OOD) data is critical for machine learning, be it for safety reasons or to enable open-ended learning. However, beyond mere detection, choosing an appropriate course of action typically hinges on the type of…

Machine Learning · Computer Science 2026-04-28 Achref Jaziri , Martin Rogmann , Martin Mundt , Visvanathan Ramesh

Plastic deformation in polycrystals is governed by the interplay between intra-granular slip and grain boundary-mediated plasticity. However, while the role played by bulk dislocations is relatively well-understood, the contribution of…

Materials Science · Physics 2017-10-02 Nikhil Chandra Admal , Giacomo Po , Jaime Marian

Originally introduced in the fluid mechanics community, dynamic mode decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of nonlinear systems. However, existing DMD theory deals primarily with sequential time…

Numerical Analysis · Mathematics 2014-12-17 Jonathan H. Tu , Clarence W. Rowley , Dirk M. Luchtenburg , Steven L. Brunton , J. Nathan Kutz

The dynamic structure factor, vorticity and entropy density dynamic correlation functions are measured for Stochastic Rotation Dynamics (SRD), a particle based algorithm for fluctuating fluids. This allows us to obtain unbiased values for…

Soft Condensed Matter · Physics 2009-11-11 Erkan Tuzel , Thomas Ihle , Daniel M. Kroll

A diffusive system coupled to unequal boundary reservoirs reaches a non-equilibrium steady state. While the full-counting-statistics of current fluctuations in these states are well understood for generic systems, results for steady-state…

Statistical Mechanics · Physics 2026-01-29 Soumyabrata Saha , Tridib Sadhu

We conpare predictions of the mean-field theory of supercnductivity for metallic systems on the border of a density instability for cubic and tetragonal lattices. The calculations are based on a parametrisation of an effective interaction…

Condensed Matter · Physics 2009-11-10 P. Monthoux , G. G. Lonzarich

Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic counterparts for efficient model training. However, existing DD methods exhibit substantial performance degradation on long-tailed datasets. We identify…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Ruixi Wu , Shaobo Wang , Jiahuan Chen , Zhiyuan Liu , Yicun Yang , Zhaorun Chen , Zekai Li , Kaixin Li , Xinming Wang , Hongzhu Yi , Kai Wang , Linfeng Zhang