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A stochastic discrete slip approach is proposed to model plastic deformation in submicron domains. The model is applied to the study of submicron pillar ($D~\leq~1\mu m$) compression experiments on tungsten (W), a prototypical metal for…

Materials Science · Physics 2024-04-17 Carlos J. Ruestes , Javier Segurado

Based on the atomistic studies presented in Part I we develop analytical yield criteria for single crystals that capture the effect of shear stresses other than the Schmid stress (non-glide stresses) on the shear stress needed for…

Materials Science · Physics 2008-07-18 R. Gröger , V. Racherla , J. L. Bassani , V. Vitek

By direct application of stress in molecular statics calculations we identify the stress components that affect the glide of 1/2<111> screw dislocations in bcc tungsten. These results prove that the hydrostatic stress and the normal stress…

Materials Science · Physics 2015-06-17 R. Gröger

Microcrystals deform very differently from their macroscopic counterparts, displaying a size-dependent yield stress and intermittent plastic strain bursts. Here we demonstrate that size effects and strain bursts may be just two different…

Materials Science · Physics 2012-04-04 Valentina Beato , Michael Zaiser , Stefano Zapperi

By means of linear theory of elastoplasticity, solutions are given for screw and edge dislocations situated in an isotropic solid. The force stresses, strain fields, displacements, distortions, dislocation densities and moment stresses are…

Materials Science · Physics 2007-05-23 Markus Lazar

In this study, we use the mechanism-based strain gradient plasticity theory to evaluate both crack tip dislocation density behaviour and the coupled effect of the material plastic properties and the intrinsic material length on non-linear…

Applied Physics · Physics 2021-10-19 V. Shlyannikov , E. Martínez-Pañeda , A. Tumanov , R. Khamidullin

Predicting the process of porosity-based ductile damage in polycrystalline metallic materials is an essential practical topic. Ductile damage and its precursors are represented by extreme values in stress and material state quantities, the…

Materials Science · Physics 2023-08-09 Yinling Zhang , Nan Chen , Curt A. Bronkhorst , Hansohl Cho , Robert Argus

In seeking to understand at a microscopic level the response of dislocations to stress we have undertaken to study as completely as possible the simplest case: a single dislocation in a two dimensional crystal. The intention is that results…

Materials Science · Physics 2007-05-23 N. Bailey , J. Sethna , C. Myers

Strain hardening is a key feature observed in many rocks deformed in the so-called ``semi-brittle'' regime, where both crystal plastic and brittle deformation mechanisms operate. Dislocation storage has long been recognised as a major…

Geophysics · Physics 2025-02-14 Nicolas Brantut

In an attempt to bridge the gap between atomistic and continuum plasticity simulations of hydrogen in iron, we present three dimensional discrete dislocation plasticity simulations incorporating the hydrogen elastic stress and a hydrogen…

Materials Science · Physics 2019-06-10 Haiyang Yu , Alan Cocks , Edmund Tarleton

Volume limitations and low yield thresholds of biological fluids have led to widespread use of passive microparticle rheology. The mean-squared-displacement (MSD) statistics of bead position time series (bead paths) are either applied…

A yield surface of a material is a set of critical stress conditions beyond which macroscopic plastic deformation begins. For crystalline solids, plastic deformation occurs through the motion of dislocations, which can be captured by…

Materials Science · Physics 2024-02-06 Wu-Rong Jian , Mian Xiao , WaiChing Sun , Wei Cai

During the plastic deformation of crystalline materials, 3d dislocation networks form based on dislocation junctions. Particularly, immobile Lomer junctions are essential for the stability of dislocation networks. However, the formed Lomer…

Materials Science · Physics 2022-12-09 Balduin Katzer , Kolja Zoller , Julia Bermuth , Daniel Weygand , Katrin Schulz

Dissipative particle dynamics (DPD) is a novel particle method for mesoscale modeling of complex fluids. DPD particles are often thought to represent packets of real atoms, and the physical scale probed in DPD models are determined by the…

Chemical Physics · Physics 2016-10-18 R. Qiao , P. He

This work proposes a data-driven explicit algebraic stress-based detached-eddy simulation (DES) method. Despite the widespread use of data-driven methods in model development for both Reynolds-averaged Navier-Stokes (RANS) and large-eddy…

Fluid Dynamics · Physics 2026-01-14 Hao-Chen Liu , Zifei Yin , Xin-Lei Zhang , Guowei He

Screw dislocations in bcc metals display non-planar cores at zero temperature which result in high lattice friction and thermally activated strain rate behavior. In bcc W, electronic structure molecular statics calculations reveal a…

Dislocations, as topological defects in crystal lattices, are fundamental to understanding plasticity in materials. Similar periodic structures also arise in continuum field theories, such as chiral soliton lattices (CSLs), which appear in…

High Energy Physics - Theory · Physics 2025-06-23 Minoru Eto , Kentaro Nishimura , Muneto Nitta

This paper studies the dynamics of relaxation phenomena in the standard dissipative particle dynamics (DPD) model [Groot and Warren, JCP, 107:4423 (1997)]. Using fluctuating hydrodynamics as the framework of the investigation, we focus on…

Statistical Mechanics · Physics 2018-03-29 J. S. Hansen , Michael L. Greenfield , Jeppe C. Dyre

Metallic materials under high stress often exhibit deformation localization, manifesting as slip banding. Over seven decades ago, Frank and Read introduced the well-known model of dislocation multiplication at a source, explaining slip band…

Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coefficients from data remains challenging. Standard approaches often rely on short-time…

Machine Learning · Statistics 2026-04-28 Ludovico T. Giorgini
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