This paper introduces a data-driven process for designing and fabricating materials with desired deformation behavior. Our process starts with measuring deformation properties of base materials. For each base material we acquire a set of example deformations, and we represent the material as a non-linear stress-strain relationship in a finite-element model. We have validated our material measurement process by comparing simulations of arbitrary stacks of base materials with measured deformations of fabricated material stacks. After material measurement, our process continues with designing stacked layers of base materials. We introduce an optimization process that finds the best combination of stacked layers that meets a user's criteria specified by example deformations. Our algorithm employs a number of strategies to prune poor solutions from the combinatorial search space. We demonstrate the complete process by designing and fabricating objects with complex heterogeneous materials using modern multi-material 3D printers.

Design and fabrication of materials with desired deformation behavior

http://network.ku.edu.tr/~cbasdogan/Papers/RoboticIndenter.pdf

A robotic indenter for minimally invasive measurement and characterization of soft tissue response.

In vivo mechanical characterization of human liver.

http://www.biorobotics.harvard.edu/pubs/2006/kerdok_Jbiomech2006.pdf

Effects of perfusion on the viscoelastic characteristics of liver.

Simulation-based training using VR techniques is a promising alternative to traditional training in minimally invasive surgery (MIS). Simulators let the trainee touch, feel, and manipulate virtual tissues and organs through the same surgical tool handles used in actual MIS while viewing images of tool-tissue interactions on a monitor as in real laparoscopic procedures

VR-Based Simulators for Training in Minimally Invasive Surgery

Inverse finite element characterization of soft tissues.

In this work a tissue aspiration method for the in-vivo determination of biological soft tissue material parameters is presented. An explicit axisymmetric finite element simulation of the aspiration experiment is used together with a Levenberg-Marquardt algorithm to estimate the material model parameters in an inverse parameter determination process. Soft biological tissue is modelled as a viscoelastic, non-linear, nearly incompressible, isotropic continuum. Viscoelasticity is accounted for by a quasi-linear formulation. The aspiration method is validated experimentally with a synthetic material. In-vivo (intra-operatively during surgical interventions) and ex-vivo experiments were performed on human uteri.

/pdf/inverse-finite-element-characterization-of-soft-tissues-1eypl5xy40.pdf

Martin Kauer

Papers

Inverse finite element characterization of soft tissues.

Inverse Finite Element Characterization of Soft Tissues