In the field of computational biomechanics, investigators have primarily used commercial software that is neither geared toward biological applications nor sufficiently flexible to follow the latest developments in the field This lack of a tailored software environment has hampered research progress, as well as dissemination of models and results To address these issues, we developed the FEBio software suite (http://mrlsciutahedu/software/febio), a nonlinear implicit finite element (FE) framework, designed specifically for analysis in computational solid biomechanics This paper provides an overview of the theoretical basis of FEBio and its main features FEBio offers modeling scenarios, constitutive models, and boundary conditions, which are relevant to numerous applications in biomechanics The open-source FEBio software is written in C++, with particular attention to scalar and parallel performance on modern computer architectures Software verification is a large part of the development and maintenance of FEBio, and to demonstrate the general approach, the description and results of several problems from the FEBio Verification Suite are presented and compared to analytical solutions or results from other established and verified FE codes An additional simulation is described that illustrates the application of FEBio to a research problem in biomechanics Together with the pre- and postprocessing software PREVIEW and POSTVIEW, FEBio provides a tailored solution for research and development in computational biomechanics

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FEBio: finite elements for biomechanics.

Finite element implementation of incompressible, transversely isotropic hyperelasticity

/pdf/feap-a-finite-element-analysis-program-qvz36simr5.pdf

FEAP - - A Finite Element Analysis Program

A viscoelastic model for fiber-reinforced composites at finite strains: Continuum basis, computational aspects and applications

A new method has been developed to extract tissue strain from a sequence of two or more medical images. This was achieved by deforming a finite element (FE) model of the tissue under loads derived from the spatial differences between two sets of image data. One image data set deforms with the tissue, while the other remains stationary. The final configuration aligns the two sets of image data. The method accounts for convection of material points, modification of the Lagrangian material properties, and probabilistic features of the sensor. A FE model of the tissue must be constructed and assigned material properties. Image data are assigned to the model tissue such that the reference configuration of the FE model corresponds to one image. The image data is subject to change during the deformation. A nonlinear solution method determines the material configuration that minimizes the difference between the deformed image (deformed template) and the experimentally observed image (target image). In many cases the image data provide powerful constraints which allow estimation of material deformation even in the absence of known loads and/or boundary conditions. The method has been applied to estimate the motion and distribution of strain using MR and CT data.

Bradley N. Maker

Papers

Finite element implementation of incompressible, transversely isotropic hyperelasticity

Finite element implementation of incompressible, transversely isotropic hyperelasticity

Incorporation of medical image data in finite element models to track strain in soft tissues

Treatment of initial stress in hyperelastic finite element models of soft tissues

Performance of NIKE3D with PVSOLVE on vector and parallel computers