A discrete element method representation of an anisotropic elastic continuum

A method for modeling cubically anisotropic elasticity within the discrete element method is presented. The discrete element method (DEM) is an approach originally intended for modeling granular materials (sand, soil, and powders); however, recent developments have usefully extended it to model stochastic mechanical processes in monolithic solids which, to date, have been assumed to be elastically isotropic. The method presented here for efficiently capturing cubic elasticity in DEM is an important prerequisite for further extending DEM to capture the influence of elastic anisotropy on the mechanical response of polycrystals, composites, etc. The system demonstrated here uses a directionally assigned stiffness in the bonds between adjacent elements and includes separate schemes for achieving anisotropy with Zener ratios greater and smaller than one. The model framework is presented along with an analysis of the accessible space of elastic properties that can be modeled and an artificial neural network interpolation scheme for mapping input parameters to model elastic behavior

A critical dislocation velocity for serration mechanism transition in a nickel-chromium solid solution alloy

The influence of strain rate across three orders of magnitude (1.70 × 10−5/s to 1.43 × 10−2/s) along with the effect of the plastic strain accumulation (up to 10%) on the serrated plastic flow were investigated in the nickel-chromium (Ni-Cr) solid solution alloy Nimonic 75 by performing constant-strain-rate tension testing at 600 °C. As the strain rate decreased, the critical strain for the onset of serrations transitioned from normal behavior to inverse behavior. The serrated flow was characterized as Type A+B serration at high strain rate (1.43 × 10−2/s). In the intermediate strain-rate regime (1.43 × 10−3/s and 1.45 × 10−4/s), Type B serrations were observed and followed by a transformation to Type C+B serrations. At the low strain rate (1.70 × 10−5/s), the plastic flow immediately displayed Type C serrations, which later evolved into Type C+B serrations. Regardless of the strain rate, plastic strain, or dislocation density, a critical dislocation velocity falling in the range of 1.2 × 10−6 – 2.2 × 10−6 m/s was identified to signify the onset of Type C serration, whereby the mobile dislocations break free from the solute cloud for short bursts of deformation. Finally, a novel model by solute rearrangement across dislocation cores was used to understand how the critical dislocation velocity is quantitatively determined by the rate at which solute atoms are able to hop across the glide plane as a partial dislocation core moves through the lattice

Activity pacing for osteoarthritis symptom management: study design and methodology of a randomized trial testing a tailored clinical approach using accelerometers for veterans and non-veterans

<p>Abstract</p> <p>Background</p> <p>Osteoarthritis (OA) is a prevalent chronic disease and a leading cause of disability in adults. For people with knee and hip OA, symptoms (e.g., pain and fatigue) can interfere with mobility and physical activity. Whereas symptom management is a cornerstone of treatment for knee and hip OA, limited evidence exists for behavioral interventions delivered by rehabilitation professionals within the context of clinical care that address how symptoms affect participation in daily activities. Activity pacing, a strategy in which people learn to preplan rest breaks to avoid symptom exacerbations, has been effective as part of multi-component interventions, but hasn't been tested as a stand-alone intervention in OA or as a tailored treatment using accelerometers. In a pilot study, we found that participants who underwent a tailored activity pacing intervention had reduced fatigue interference with daily activities. We are now conducting a full-scale trial.</p> <p>Methods/Design</p> <p>This paper provides a description of our methods and rationale for a trial that evaluates a tailored activity pacing intervention led by occupational therapists for adults with knee and hip OA. The intervention uses a wrist accelerometer worn during the baseline home monitoring period to glean recent symptom and physical activity patterns and to tailor activity pacing instruction based on how symptoms relate to physical activity. At 10 weeks and 6 months post baseline, we will examine the effectiveness of a tailored activity pacing intervention on fatigue, pain, and physical function compared to general activity pacing and usual care groups. We will also evaluate the effect of tailored activity pacing on physical activity (PA).</p> <p>Discussion</p> <p>Managing OA symptoms during daily life activity performance can be challenging to people with knee and hip OA, yet few clinical interventions address this issue. The activity pacing intervention tested in this trial is designed to help people modulate their activity levels and reduce symptom flares caused by too much or too little activity. As a result of this trial, we will be able to determine if activity pacing is more effective than usual care, and among the intervention groups, if an individually tailored approach improves fatigue and pain more than a general activity pacing approach.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01192516">NCT01192516</a></p

A critical dislocation velocity for serration mechanism transition in a nickel-chromium solid solution alloy

The influence of strain rate across three orders of magnitude (1.70 × 10−5/s to 1.43 × 10−2/s) along with the effect of the plastic strain accumulation (up to 10%) on the serrated plastic flow were investigated in the nickel-chromium (Ni-Cr) solid solution alloy Nimonic 75 by performing constant-strain-rate tension testing at 600 °C. As the strain rate decreased, the critical strain for the onset of serrations transitioned from normal behavior to inverse behavior. The serrated flow was characterized as Type A+B serration at high strain rate (1.43 × 10−2/s). In the intermediate strain-rate regime (1.43 × 10−3/s and 1.45 × 10−4/s), Type B serrations were observed and followed by a transformation to Type C+B serrations. At the low strain rate (1.70 × 10−5/s), the plastic flow immediately displayed Type C serrations, which later evolved into Type C+B serrations. Regardless of the strain rate, plastic strain, or dislocation density, a critical dislocation velocity falling in the range of 1.2 × 10−6 – 2.2 × 10−6 m/s was identified to signify the onset of Type C serration, whereby the mobile dislocations break free from the solute cloud for short bursts of deformation. Finally, a novel model by solute rearrangement across dislocation cores was used to understand how the critical dislocation velocity is quantitatively determined by the rate at which solute atoms are able to hop across the glide plane as a partial dislocation core moves through the lattice

Proceedings of the First International Conference on Theoretical, Applied and Experimental Mechanics

Plastic deformation proceeds through a sequence of stochastic local slip followed by load redistribution. With continued deformation this builds up complex stress fields and develops a heterogeneous pat- tern of local strength, leading to the emergence of microvoids and cracks. The goal of this research is to develop a coarse grained model for crystal plasticity that captures the physics emergent form stochastic heterogeneous deformation. The method based on the discrete element method (DEM), an approach developed for modeling of granular materials and recently adapted for amorphous brittle solids. DEM models the material as a collection of interacting elements. The framework naturally captures the elastic coupling due to geometric frustration in a system under heterogeneous deformation and the emergent phenomena that develop from it. This paper presents the accomplishment of intermediate steps towards modeling crystal plasticity: modeling anisotropic elasticity, and modeling isotropic plasticity

A discrete element method representation of an anisotropic elastic continuum

A method for modeling cubically anisotropic elasticity within the discrete element method is presented. The discrete element method (DEM) is an approach originally intended for modeling granular materials (sand, soil, and powders); however, recent developments have usefully extended it to model stochastic mechanical processes in monolithic solids which, to date, have been assumed to be elastically isotropic. The method presented here for efficiently capturing cubic elasticity in DEM is an important prerequisite for further extending DEM to capture the influence of elastic anisotropy on the mechanical response of polycrystals, composites, etc. The system demonstrated here uses a directionally assigned stiffness in the bonds between adjacent elements and includes separate schemes for achieving anisotropy with Zener ratios greater and smaller than one. The model framework is presented along with an analysis of the accessible space of elastic properties that can be modeled and an artificial neural network interpolation scheme for mapping input parameters to model elastic behavior

A discrete element method representation of an anisotropic elastic continuum

A method for modeling cubically anisotropic elasticity within the discrete element method is presented. The discrete element method (DEM) is an approach originally intended for modeling granular materials (sand, soil, and powders); however, recent developments have usefully extended it to model stochastic mechanical processes in monolithic solids which, to date, have been assumed to be elastically isotropic. The method presented here for efficiently capturing cubic elasticity in DEM is an important prerequisite for further extending DEM to capture the influence of elastic anisotropy on the mechanical response of polycrystals, composites, etc. The system demonstrated here uses a directionally assigned stiffness in the bonds between adjacent elements and includes separate schemes for achieving anisotropy with Zener ratios greater and smaller than one. The model framework is presented along with an analysis of the accessible space of elastic properties that can be modeled and an artificial neural network interpolation scheme for mapping input parameters to model elastic behavior