scholarly journals Particle dynamics simulations of expansion of a cylindrical cavity within an infinite brittle medium

2004 ◽  
Vol 31 (3-4) ◽  
pp. 345-360 ◽  
Author(s):  
Sreten Mastilovic ◽  
Dusan Krajcinovic
Keyword(s):  
Cylindrical Cavity ◽  
Epistemic Uncertainty ◽  
Particle Dynamics ◽  
Disordered Lattice ◽  
Aleatory Variability ◽  
Random Microstructure ◽  
Proposed Model ◽  
Particle Simulations ◽  
Non Local ◽  
Dynamics Simulations

The present review focuses on the plane strain problem of high strain rate expansion of a cylindrical cavity within an infinite brittle material with random microstructure. The material is represented by an ensemble of "continuum particles" forming a two-dimensional geometrically and structurally disordered lattice. The proposed model includes the aleatory variability and epistemic uncertainty of the process. The dynamic particle simulations are performed at seven different cavity expansion rates. The resulting damage evolution process is non-stationary, non-local, and non-equilibrium. This problem, therefore, belongs to the class of phenomena for which the traditional continuum models are not well suited, and detailed experimental data are either difficult to get or not available at all. The present study explores the potential role of the particle dynamics in addressing these problems. .

Sequence Specificity Despite Intrinsic Disorder: How a Disease-Associated Val/Met Polymorphism Shifts Tertiary Interactions in a Long Disordered Protein

2019 ◽  
Author(s):  
Ruchi Lohia ◽  
Reza Salari ◽  
Grace Brannigan
Keyword(s):  
Secondary Structure ◽  
Electrostatic Interactions ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Sequence Specificity ◽  
Intrinsically Disordered ◽  
Specific Effects ◽  
Heterogeneous Polymer ◽  
Non Local ◽  
Dynamics Simulations

<div>The role of electrostatic interactions and mutations that change charge states in intrinsically disordered proteins (IDPs) is well-established, but many disease-associated mutations in IDPs are charge-neutral. The Val66Met single nucleotide polymorphism (SNP) encodes a hydrophobic-to-hydrophobic mutation at the midpoint of the prodomain of precursor brain-derived neurotrophic factor (BDNF), one of the earliest SNPs to be associated with neuropsychiatric disorders, for which the underlying molecular mechanism is unknown. Here we report on over 250 μs of fully-atomistic, explicit solvent, temperature replica exchange molecular dynamics simulations of the 91 residue BDNF prodomain, for both the V66 and M66 sequence.</div><div>The simulations were able to correctly reproduce the location of both local and non-local secondary changes due to the Val66Met mutation when compared with NMR spectroscopy. We find that the local structure change is mediated via entropic and sequence specific effects. We show that the highly disordered prodomain can be meaningfully divided into domains based on sequence alone. Monte Carlo simulations of a self-excluding heterogeneous polymer, with monomers representing each domain, suggest the sequence would be effectively segmented by the long, highly disordered polyampholyte near the sequence midpoint. This is qualitatively consistent with observed interdomain contacts within the BDNF prodomain, although contacts between the two segments are enriched relative to the self-excluding polymer. The Val66Met mutation increases interactions across the boundary between the two segments, due in part to a specific Met-Met interaction with a Methionine in the other segment. This effect propagates to cause the non-local change in secondary structure around the second methionine, previously observed in NMR. The effect is not mediated simply via changes in inter-domain contacts but is also dependent on secondary structure formation around residue 66, indicating a mechanism for secondary structure coupling in disordered proteins. </div>

Coarse-Graining of Chain Models in Dissipative Particle Dynamics Simulations†

2011 ◽  
Vol 50 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Justin R. Spaeth ◽  
Todd Dale ◽  
Ioannis G. Kevrekidis ◽  
Athanassios Z. Panagiotopoulos
Keyword(s):  
Dissipative Particle Dynamics ◽  
Coarse Graining ◽  
Particle Dynamics ◽  
Dynamics Simulations

A dissipative particle dynamics simulation study on phase diagrams for the self-assembly of amphiphilic hyperbranched multiarm copolymers in various solvents

Soft Matter ◽  
2017 ◽  
Vol 13 (36) ◽  
pp. 6178-6188 ◽  
Author(s):  
Haina Tan ◽  
Chunyang Yu ◽  
Zhongyuan Lu ◽  
Yongfeng Zhou ◽  
Deyue Yan
Keyword(s):  
Phase Diagrams ◽  
Simulation Study ◽  
Self Assembly ◽  
Dissipative Particle Dynamics ◽  
Particle Dynamics ◽  
The Self ◽  
Dynamics Simulation ◽  
Dynamics Simulations ◽  
First Time ◽  
Dissipative Particle Dynamics Simulation

This work discloses for the first time the self-assembly phase diagrams of amphiphilic hyperbranched multiarm copolymers in various solvents by dissipative particle dynamics simulations.

Automated Image Denoising Model: Contribution Towards Optimized Internal and External Basis

2021 ◽  
pp. 2150051
Author(s):  
S. Elavaar Kuzhali ◽  
D. S. Suresh
Keyword(s):  
Image Denoising ◽  
Image Patch ◽  
The Past ◽  
Local Means ◽  
Hybrid Optimization Algorithm ◽  
Proposed Model ◽  
Processing Step ◽  
Non Local ◽  
Chicken Swarm Optimization ◽  
Selection Of

For handling digital images for various applications, image denoising is considered as a fundamental pre-processing step. Diverse image denoising algorithms have been introduced in the past few decades. The main intent of this proposal is to develop an effective image denoising model on the basis of internal and external patches. This model adopts Non-local means (NLM) for performing the denoising, which uses redundant information of the image in pixel or spatial domain to reduce the noise. While performing the image denoising using NLM, “denoising an image patch using the other noisy patches within the noisy image is done for internal denoising and denoising a patch using the external clean natural patches is done for external denoising”. Here, the selection of optimal block from the entire datasets including internal noisy images and external clean natural images is decided by a new hybrid optimization algorithm. The two renowned optimization algorithms Chicken Swarm Optimization (CSO), and Dragon Fly Algorithm (DA) are merged, and the new hybrid algorithm Rooster-based Levy Updated DA (RLU-DA) is adopted. The experimental results in terms of some relevant performance measures show the promising results of the proposed model with remarkable stability and high accuracy.

scholarly journals Correction: Dissipative particle dynamics and molecular dynamics simulations on mesoscale structure and proton conduction in a SPEEK/PVDF-g-PSSA membrane

RSC Advances ◽  
2017 ◽  
Vol 7 (66) ◽  
pp. 41787-41787
Author(s):  
Yue Ma ◽  
Yuxiang Wang ◽  
Xuejian Deng ◽  
Guanggang Zhou ◽  
Shah Khalid ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Dissipative Particle Dynamics ◽  
Particle Dynamics ◽  
Proton Conduction ◽  
Mesoscale Structure ◽  
Dynamics Simulations

Correction for ‘Dissipative particle dynamics and molecular dynamics simulations on mesoscale structure and proton conduction in a SPEEK/PVDF-g-PSSA membrane’ by Yue Ma et al., RSC Adv., 2017, 7, 39676–39684.

scholarly journals Dissipative particle dynamics and molecular dynamics simulations on mesoscale structure and proton conduction in a SPEEK/PVDF-g-PSSA membrane

RSC Advances ◽  
2017 ◽  
Vol 7 (63) ◽  
pp. 39676-39684 ◽  
Author(s):  
Yue Ma ◽  
Yuxiang Wang ◽  
Xuejian Deng ◽  
Guanggang Zhou ◽  
Sha Khalid ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Dissipative Particle Dynamics ◽  
Particle Dynamics ◽  
Proton Conduction ◽  
Small Particles ◽  
Cluster Network ◽  
Mesoscale Structure ◽  
Dynamics Simulations

The blend morphologies evolve from disordered small particles to a regular PVDF cluster network, which were connected by SPEEK cylindrical channels.

Particle dynamics simulations of Turing patterns

2012 ◽  
Vol 137 (7) ◽  
pp. 074107 ◽  
Author(s):  
P. Dziekan ◽  
A. Lemarchand ◽  
B. Nowakowski
Keyword(s):  
Particle Dynamics ◽  
Turing Patterns ◽  
Dynamics Simulations
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