Literature DB >> 12468419

A finite element analysis methodology for representing the articular cartilage functional structure.

S Olsen1, A Oloyede.   

Abstract

Recognising that the unique biomechanical properties of articular cartilage are a consequence of its structure, this paper describes a finite element methodology which explicitly represents this structure using a modified overlay element model. The validity of this novel concept was then tested by using it to predict the axial curling forces generated by cartilage matrices subjected to saline solutions of known molality and concentration in a novel experimental protocol. Our results show that the finite element modelling methodology accurately represents the intrinsic biomechanical state of the cartilage matrix and can be used to predict its transient load-carriage behaviour. We conclude that this ability to represent the intrinsic swollen condition of a given cartilage matrix offers a viable avenue for numerical analysis of degenerate articular cartilage and also those matrices affected by disease.

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Year:  2002        PMID: 12468419     DOI: 10.1080/1025584021000011091

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  3 in total

1.  A triphasic orthotropic laminate model for cartilage curling behavior: fixed charge density versus mechanical properties inhomogeneity.

Authors:  Leo Q Wan; X Edward Guo; Van C Mow
Journal:  J Biomech Eng       Date:  2010-02       Impact factor: 2.097

Review 2.  A review of the combination of experimental measurements and fibril-reinforced modeling for investigation of articular cartilage and chondrocyte response to loading.

Authors:  Petro Julkunen; Wouter Wilson; Hanna Isaksson; Jukka S Jurvelin; Walter Herzog; Rami K Korhonen
Journal:  Comput Math Methods Med       Date:  2013-04-08       Impact factor: 2.238

3.  Investigation of Cell-Substrate Adhesion Properties of Living Chondrocyte by Measuring Adhesive Shear Force and Detachment Using AFM and Inverse FEA.

Authors:  Trung Dung Nguyen; YuanTong Gu
Journal:  Sci Rep       Date:  2016-11-28       Impact factor: 4.379

  3 in total

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