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D Pflaster

Publications and source records attributed to D Pflaster.

2 recordsLinked to original sources

A poroelastic finite element formulation including transport and swelling in soft tissue structures.

A field theory is presented for the study of swelling in soft tissue structures that are modeled as poroelastic materials. As a first approximation, soft tissues are assumed to be linear isotropic materials undergoing infinitesimal strains. Material properties are identified that are necessary for the solution of initial boundary value problems where swelling and convection are significant. A finite element model is developed that includes the solid displacements, the relative fluid displacements, and a representative concentration as the primary unknowns. A numerical example is presented based on a triphasic model. The finite model simulates a typical experimental protocol for soft tissue testing and demonstrates the interaction and coupling associated with relative fluid motion and swelling in a deforming poroelastic materiaL The theory and finite element model provide a starting point for nonlinear porohyperelastic transport-swelling analyses of soft tissue structures that include finite strains in anisotropic materials.

Algorithms↗

A dynamic material parameter estimation procedure for soft tissue using a poroelastic finite element model.

A three-dimensional finite element model for a poroelastic medium has been coupled with a least squares parameter estimation method for the purpose of assessing material properties based on intradiscal displacement and reactive forces. Parameter optimization may be based on either load or displacement control experiments. In this paper we present the basis of the finite element model and the parameter estimation process. The method is then applied to a test problem and the computational behavior is discussed. Sequential optimization on different parameter groups was found to have superior convergence properties. Some guidelines for choosing the starting parameter values for optimization were deduced by considering the form of the objective function. For load control experiments, in which displacement data is used for the optimization, the starting values for the elastic modulus should be lower in magnitude than an "anticipated" modulus. The permeability starting values should be higher than an anticipated permeability. For displacement control experiments, the reverse is true. The optimization scheme was also tested on data with random variations.

Anisotropy↗