Volumetric shape description of range data using “Blobby Model”
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Real functions for representation of rigid solids
Computer Aided Geometric Design
Implicit reconstruction of solids from cloud point sets
SMA '95 Proceedings of the third ACM symposium on Solid modeling and applications
Implicit functions with guaranteed differential properties
Proceedings of the fifth ACM symposium on Solid modeling and applications
Adaptively sampled distance fields: a general representation of shape for computer graphics
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Structural boundary design via level set and immersed interface methods
Journal of Computational Physics
Introduction to Implicit Surfaces
Introduction to Implicit Surfaces
Implicit Objects in Computer Graphics
Implicit Objects in Computer Graphics
Modelling with implicit surfaces that interpolate
ACM Transactions on Graphics (TOG)
Multi-level partition of unity implicits
ACM SIGGRAPH 2003 Papers
Structural optimization using sensitivity analysis and a level-set method
Journal of Computational Physics
Constructive sculpting of heterogeneous volumetric objects using trivariate B-splines
The Visual Computer: International Journal of Computer Graphics
Approximate distance fields with non-vanishing gradients
Graphical Models
Shape sensitivity of constructive representations
Proceedings of the 2007 ACM symposium on Solid and physical modeling
Heterogeneous object modeling: A review
Computer-Aided Design
| Hi-index | 0.00 |
A heterogeneous model consists of a solid model and a number of spatially distributed material attributes. Much progress has been made in developing methods for construction, design, and editing of such models. We consider the problem of optimization of a heterogeneous model, and show that its representation by a continuous function defined over a constructively represented domain naturally leads to simple and effective optimization procedures. Using minimum compliance optimization problem as an example, we show that the design sensitivities are directly obtainable in terms of material and geometric parameters, which can be used in any standard gradient-based optimization procedures. The proposed approach allows both local control of the material properties and global control of geometric variations, and can be used with many existing techniques for material modeling. Numerical experiments are given to demonstrate these representational advantages.