• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1202-1208
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• 2009

An inverse finite element (FE) model parameter estimation algorithm can be used to characterize mechanical properties of biological tissues. Using this algorithm, we can consider the influence of material nonlinearity, contact mechanics, complex boundary conditions, and geometrical constraints in the modeling. In this study, biomechanical experiments on macro and micro samples are conducted and characterized with the developed algorithm. Macro scale experiments were performed to measure the force response of porcine livers against mechanical loadings using one-dimensional indentation device. The force response of the human liver cancer cells was also measured by the atomic force microscope (AFM). The mechanical behavior of porcine livers (macro) and human liver cancer cells (micro) were characterized with the algorithm via hyperelastic and linear viscoelastic models. The developed models are suitable for computing accurate reaction force on tools and deformation of biomechanical tissues.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.911-914
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• 2005

Soft tissue characterization and modeling based on living tissues has been investigated in order to provide a more realistic behavior in a virtual reality based surgical simulation. In this paper, we characterize the nonlinear viscoelastic properties of intra-abdominal organs using the data from in vivo animal experiments and inverse FE parameter estimation algorithm. In the assumptions of quasi-linear-viscoelastic theory, we estimated the nonlinear material parameters to provide a physically based simulation of tissue deformations. To calibrate the parameters to the experimental results, we developed a three dimensional FE model to simulate the forces at the indenter and an optimization program that updates new parameters and runs the simulation iteratively. The comparison between simulation and experimental behavior of pig intra abdominal soft tissue are presented to provide a validness of the tissue model using our approach.