Representation of porous artifacts for bio-medical applications

Heterogeneous structures represent an important new frontier for 21st century engineering. For instance, a tissue engineered structure, such as bone scaffold for guided tissue regeneration, can be described as a heterogeneous structure consisting of 3D extra-cellular matrices (made from biodegradable material) and seeded donor cells and/or growth factors. The design and fabrication of such heterogeneous structures requires new techniques for solid models to represent 3D heterogeneous objects with complex material properties. This paper presents a representation of model density and porosity based on stochastic geometry. While density has been previously studied in the literature, porosity is a new problem for bio-medical CAD critical for modeling replacement bone tissues.

[1]  William Ribarsky,et al.  Real-time visualization of scalably large collections of heterogeneous objects , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[2]  R. Hilfer,et al.  Reconstruction of random media using Monte Carlo methods. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[3]  Vinod Kumar,et al.  A framework for object modeling , 1999, Comput. Aided Des..

[4]  Hilfer,et al.  Stochastic reconstruction of sandstones , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[5]  William Ribarsky,et al.  Real-time visualization of scalably large collections of heterogeneous objects (case study) , 1999, VIS '99.

[6]  Nicholas M. Patrikalakis,et al.  Memory Analysis of Solid Model Representations for Heterogeneous Objects , 2002, J. Comput. Inf. Sci. Eng..

[7]  Wei Sun,et al.  Reasoning Boolean operation based modeling for heterogeneous objects , 2002, Comput. Aided Des..

[8]  Kristin L. Wood,et al.  SLS Processing of Functionally Gradient Materials , 1997 .

[9]  S. Torquato,et al.  Reconstructing random media. II. Three-dimensional media from two-dimensional cuts , 1998 .

[10]  Ram D. Sriram,et al.  Representation of Heterogeneous Objects in ISO 10303 (STEP) , 2000, Manufacturing Engineering.

[11]  M LieshoutvanM.N.,et al.  Stochastic geometry : likelihood and computation , 2000 .

[12]  Gary William Flake,et al.  The Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems and Adaptation , 1998 .

[13]  Richard H. Crawford,et al.  Volumetric multi-texturing for functionally gradient material representation , 2001, SMA '01.

[14]  Ram D. Sriram,et al.  Progress towards an international standard for data transfer in rapid prototyping and layered manufacturing , 2001, Comput. Aided Des..

[15]  Rudolf Hilfer,et al.  Local Porosity Theory and Stochastic Reconstruction for Porous Media , 2000 .

[16]  R. Hilfer,et al.  Permeability and conductivity for reconstruction models of porous media. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  G. Flake.  The Computational Beauty of Nature , 1998 .

[18]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[19]  Vinod Kumar,et al.  An approach to modeling multi-material objects , 1997, SMA '97.

[20]  Tosiyasu L. Kunii,et al.  Cellular-functional modeling of heterogeneous objects , 2002, SMA '02.