Nonlinear elasticity of biological tissues with statistical fibre orientation
نویسندگان
چکیده
منابع مشابه
Nonlinear elasticity of biological tissues with statistical fibre orientation.
The elastic strain energy potential for nonlinear fibre-reinforced materials is customarily obtained by superposition of the potentials of the matrix and of each family of fibres. Composites with statistically oriented fibres, such as biological tissues, can be seen as being reinforced by a continuous infinity of fibre families, the orientation of which can be represented by means of a probabil...
متن کاملStatistical mechanics of nonlinear elasticity
A method is suggested for defining a deformation-dependent free energy in microscopic terms for a deformed elastic solid and applied to a simple microscopic model of such a solid. Some of the convexity and continuity properties of this free energy function are derived.
متن کاملPolarimetry of birefringent biological tissues with arbitrary fibril orientation and variable incidence angle.
Polarimetric optical techniques such as polarization microscopy or polarization-sensitive optical coherence tomography normally assume that light is perpendicular to the sample surface and that fibrils of a birefringent biological tissue are arranged in a plane parallel to this surface. The approaches that describe quantitatively polarimetric data from tissues with nonparallel fibril orientatio...
متن کاملInvestigation of Linear and Nonlinear Buckling of Orthotropic Graphene Sheets with Nonlocal Elasticity Theories
In this paper, analysis of linear and nonlinear buckling of relatively thick orthotropic graphene sheets is carried out under mechanical load based on elasticity theories. With the help of nonlocal elasticity theory, the principle of virtual work, first order shear theory and Von-Karman nonlinear strain, the dominant relationship in terms of obtained displacements has been obtained, and the me...
متن کاملMultivariate Statistical Monitoring of Nonlinear Biological Processes Using Kernel Pca
In this paper, a new nonlinear process monitoring technique based upon kernel principal component analysis (KPCA) is developed. In recent years, KPCA has been emerging to tackle the nonlinear monitoring problem. KPCA can efficiently compute principal components in high dimensional feature spaces by the use of integral operator and nonlinear kernel functions. The basic idea of KPCA is to first m...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of The Royal Society Interface
سال: 2010
ISSN: 1742-5689,1742-5662
DOI: 10.1098/rsif.2009.0502