A Nonlinear Viscoelastic Model to DescribePeriodontal Ligament Behavior
Publish place: 15th Iranian Conference on Biomedical Engineering
Publish Year: 1387
Type: Conference paper
Language: English
View: 1,476
This Paper With 6 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
Export:
Document National Code:
ICBME15_015
Index date: 16 November 2012
A Nonlinear Viscoelastic Model to DescribePeriodontal Ligament Behavior abstract
The periodontal ligament (PDL) is a soft biological tissue which shows a strongly nonlinear and timedependent mechanical behavior. Recent experiments on rabbit PDL revealed that the rate of stress relaxation is straindependent. This nonlinear behavior of PDL cannot be described well by the separable quasi linear viscoelasticitytheory which is usually used in tissue biomechanics. Therefore, PDL requires a more general description whichconsiders this nonlinearity and time dependency. The purpose of this study was to model strain dependent stressrelaxation behavior of PDL using modified superposition method. It is shown herein that modified superpositionmethod describes viscoelastic nonlinearties well and shows a good compatibility with available experimental PDL data.Hence, the modified superposition model is suggested to describe periodontal ligament data, because it can suitablydemonstrate both elastic nonlinearity and strain-dependent stress relaxation behavior of PDL.
A Nonlinear Viscoelastic Model to DescribePeriodontal Ligament Behavior Keywords:
A Nonlinear Viscoelastic Model to DescribePeriodontal Ligament Behavior authors
Behnam Mirzakouchaki
Division of Orthodontics, School Of Dentistry, Tabriz University of Medical Sciences, Tabriz, Iran
Farzan Ghalichi
Division of Biomechanics, Mechanical Engineering Department, Sahand University of Technology, Tabriz, Iran
Javad Hazrati Morangalou
Division of Biomechanics, Mechanical Engineering Department, Sahand University of Technology, Tabriz, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :