Dynamic behaviour of solids and granular materials: a force potential-based particle method

2015 ◽  
Vol 105 (12) ◽  
pp. 936-959 ◽  
Author(s):  
Roberto Brighenti ◽  
Nicholas Corbari
Keyword(s):  
Granular Materials ◽  
Dynamic Behaviour ◽  
Particle Method ◽  
Force Potential

Cubic-Interpolated-Pseudo-Particle Method to Predict Dynamic Behaviour of Fluid in Shear Driven Cavity

2011 ◽  
Vol 110-116 ◽  
pp. 377-384
Author(s):  
S.M.R. Attarzadeh ◽  
C. S. Nor Azwadi ◽  
F. Haghbin
Keyword(s):  
Dynamic Behavior ◽  
Processing Time ◽  
Dynamic Behaviour ◽  
Fluid Motion ◽  
Particle Method ◽  
Reynolds Numbers ◽  
Experimental Results ◽  
Fluid Structure ◽  
Driven Cavity

In this paper, Cubic Interpolated Pseudo Particle Method is proposed to investigate the dynamic behavior of fluid motion in shear lid-driven cavity. The CIP scheme is individually performed to observe the behavior of the fluid motion at varying Reynolds numbers of 100, 400 and 1000. Comparison of the achieved results with the experimental results approves the capability of CIP to establish the sophistication of fluid structure in the system. Although the achieved trajectory had slightly difference but it was almost following the same pattern published in the literatures. The most advantage of this method is that it aims to accelerate processing time as well as higher exponent of accuracy.

Discrete Element Method applied to the simulation of the stress state in granular materials

Soil Research ◽  
2019 ◽  
Vol 57 (1) ◽  
pp. 85
Author(s):  
Gabriela Carolina Martínez Morillo ◽  
Alex Alves Bandeira
Keyword(s):  
Discrete Element Method ◽  
Granular Materials ◽  
Soil Mechanics ◽  
Particle Method ◽  
Discrete Element ◽  
Computational Costs ◽  
Basic Physics ◽  
Force Displacement ◽  
Graphical Presentation ◽  
Element Method

This work examines the Discrete Element Method (DEM), also known as the particle method, for its application in soil mechanics, specifically to calculate the tension acting on granular materials without cohesion. First, theoretical aspects of soil mechanics and the physical properties of some types of granular materials are presented, and the material properties are used afterwards in numerical examples. Following this, the DEM formulation is described, corresponding to the force and movement equations acting on each particle. For that, Newton’s second law, the force–displacement law, Hertz’s contact law, and some concepts from particle mechanics are defined. The integration over time process and the numerical solution algorithm presented by T.I. Zohdi are also described. Additionally, a new optimisation process for contact detection is described, one which significantly diminishes computational costs and therefore analysis time. Finally, some basic physics examples necessary for the formulation validation and application in soil mechanics are presented. The results obtained with the software developed in this research are then compared with soil mechanics results, which are simulated using the GeoStudio software. The GiD program was utilised for graphical presentation of the results.

Compression and shear-wave velocities in discrete particle simulations of quartz granular packings: Improved Hertz-Mindlin contact model

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. E165-E174 ◽  
Author(s):  
Carlos Santos ◽  
Vanessa Urdaneta ◽  
Xavier García ◽  
Ernesto Medina
Keyword(s):  
Granular Materials ◽  
Particle Method ◽  
Contact Model ◽  
Discrete Particle ◽  
Unconsolidated Sands ◽  
Tangential Stiffness ◽  
Shear Wave Velocities ◽  
Effective Medium Theories ◽  
Particle Simulations ◽  
Discrete Particle Method

The Hertz-Mindlin (HM) contact model has been a cornerstone for the development of several effective medium theories (EMTs) aimed at describing the mesoscopic and macroscopic mechanical behavior of granular materials like unconsolidated sands. In addition, this model is at the core of most of the discrete particle method designs used to numerically solve for the responses of these heterogeneous materials to external perturbations, like acoustic and stress-strain experiments. However, this model has shown shortcomings in the description of the shear response characterization of granular materials, partly due to the non-affine motions experienced by the grains. We have developed a correction of the model based on a detailed calibration of our acoustic numerical results with previous empirical data. Using a microscopic approach to the grain-grain contact surfaces, the nature of the corrections found appear to be related to the shear resistant asperities and the smaller scale of the grain-grain contact areas compared to the total area assumed by the HM model. An improved HM model characterized by a tangential stiffness weakening is based on these surface corrections. Using this observation an enhanced EMT theory emerges based not only on the tangential stiffness modification but also on the velocity-pressure dependence obtained during the calibration of our numerical model.

Dissipation in granular materials

1998 ◽  
Vol 77 (5) ◽  
pp. 1413-1425 ◽  
Author(s):  
Dietrich E.Wolf, Farhang Radjai, Sabine Dipp
Keyword(s):  
Granular Materials

Investigation of fused silica dynamic behaviour

2006 ◽  
Vol 134 ◽  
pp. 929-934 ◽  
Author(s):  
F. Malaise ◽  
J.-M. Chevalier ◽  
I. Bertron ◽  
F. Malka
Keyword(s):  
Dynamic Behaviour ◽  
Fused Silica

A MODEL FOR THE FATIGUE SATURATION RANGE OF ALUMINIUM FROM DYNAMIC BEHAVIOUR AND INTERACTIONS OF DISLOCATIONS

1987 ◽  
Vol 48 (C8) ◽  
pp. C8-155-C8-160
Author(s):  
R. FOUGERES ◽  
J. CHICOIS ◽  
A. HAMEL ◽  
A. VINCENT
Keyword(s):  
Dynamic Behaviour

Analysis of the Multi-Channel Epileptiform EEG Using the Markov Chains Formalism

1989 ◽  
Vol 28 (03) ◽  
pp. 160-167 ◽  
Author(s):  
P. Penczek ◽  
W. Grochulski
Keyword(s):  
Dynamic Behaviour ◽  
Joint Probability ◽  
Drug Effects ◽  
Anticonvulsant Drug ◽  
Channel System ◽  
Markov Network ◽  
Eeg Data ◽  
Multi Level ◽  
Joint Probability Functions ◽  
Dependent State

Abstract:A multi-level scheme of syntactic reduction of the epileptiform EEG data is briefly discussed and the possibilities it opens up in describing the dynamic behaviour of a multi-channel system are indicated. A new algorithm for the inference of a Markov network from finite sets of sample symbol strings is introduced. Formulae for the time-dependent state occupation probabilities, as well as joint probability functions for pairs of channels, are given. An exemplary case of analysis in these terms, taken from an investigation of anticonvulsant drug effects on EEG seizure patterns, is presented.

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