Strain Energy Descriptions of Biological Swelling II: Multiple Fluid Compartment Models

1987 ◽  
Vol 109 (3) ◽  
pp. 257-262 ◽  
Author(s):  
D. K. Bogen

A series of multicompartmental, biphasic elastic tissue models is developed. In its most general form, the models consist of multiple tubular networks, each with an internal spring network. In addition, another spring network occupies the extratubular compartment. Strain energy functions are derived for the models, as well as expressions for the fluid pressures in each compartment arising from volume expansion or swelling. Calculations also show that the distribution of fluid among compartments is a significant determinant of tissue elasticity.

1987 ◽  
Vol 109 (3) ◽  
pp. 252-256 ◽  
Author(s):  
D. K. Bogen

Strain energy functions are derived from biphasic soft tissue models in order to describe large-deformation, large-swelling, elastic behavior of nonlinear materials. The resulting analysis leads to calculations of stress-extension relations and tissue fluid pressure. Also explored are the elastic stability of the biphasic tissue models and the manner in which tissue pressure is altered by material deformation.


1965 ◽  
Vol 9 (7) ◽  
pp. 2565-2579 ◽  
Author(s):  
M. Shinozuka ◽  
A. M. Freudenthal

1999 ◽  
Vol 67 (1) ◽  
pp. 17-21 ◽  
Author(s):  
S. Doll ◽  
K. Schweizerhof

To describe elastic material behavior the starting point is the isochoric-volumetric decoupling of the strain energy function. The volumetric part is the central subject of this contribution. First, some volumetric functions given in the literature are discussed with respect to physical conditions, then three new volumetric functions are developed which fulfill all imposed conditions. One proposed function which contains two material parameters in addition to the compressibility parameter is treated in detail. Some parameter fits are carried out on the basis of well-known volumetric strain energy functions and experimental data. A generalization of the proposed function permits an unlimited number of additional material parameters.  Dedicated to Professor Franz Ziegler on the occasion of his 60th birthday. [S0021-8936(00)00901-6]


1993 ◽  
Vol 115 (3) ◽  
pp. 329-336 ◽  
Author(s):  
Yun Ling ◽  
Peter A. Engel ◽  
Wm. L. Brodskey ◽  
Yifan Guo

The main purpose of this study was to determine a suitable strain energy function for a specific elastomer. A survey of various strain energy functions proposed in the past was made. For natural rubber, there were some specific strain energy functions which could accurately fit the experimental data for various types of deformations. The process of determining a strain energy function for the specific elastomer was then described. The second-order invariant polynomial strain energy function (James et al., 1975) was found to give a good fit to the experimental data of uniaxial tension, uniaxial compression, equi-biaxial extension, and pure shear. A new form of strain energy function was proposed; it yielded improved results. The equi-biaxial extension experiment was done in a novel way in which the moire techniques (Pendleton, 1989) were used. The obtained strain energy functions were then utilized in a finite element program to calculate the load-deflection relation of an electrometric spring used in an electrical connector.


2004 ◽  
Vol 77 (2) ◽  
pp. 257-277 ◽  
Author(s):  
Y. Shen ◽  
K. Chandrashekhara ◽  
W. F. Breig ◽  
L. R. Oliver

Abstract Rubber hyperelasticity is characterized by a strain energy function. The strain energy functions fall primarily into two categories: one based on statistical thermodynamics, the other based on the phenomenological approach of treating the material as a continuum. This work is focused on the phenomenological approach. To determine the constants in the strain energy function by this method, curve fitting of rubber test data is required. A review of the available strain energy functions based on the phenomenological approach shows that it requires much effort to obtain a curve fitting with good accuracy. To overcome this problem, a novel method of defining rubber strain energy function by Feedforward Backpropagation Neural Network is presented. The calculation of strain energy and its derivatives by neural network is explained in detail. The preparation of the neural network training data from rubber test data is described. Curve fitting results are given to show the effectiveness and accuracy of the neural network approach. A material model based on the neural network approach is implemented and applied to the simulation of V-ribbed belt tracking using the commercial finite element code ABAQUS.


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