Modeling of multifunctional porous tissue scaffolds with continuous deposition path plan

A novel modeling technique for porous tissue scaffolds with targeting the functionally gradient variational porosity with continuous material deposition planning has been proposed. To vary the porosity of the designed scaffold functionally, medial axis transformation is used. The medial axis of each layers of the scaffold is calculated and used as an internal feature. The medial axis is then used connected to the outer contour using an optimum matching. The desired pore size and hence the porosity have been achieved by discretizing the sub-regions along its peripheral direction based on the pore size while meeting the tissue scaffold design constraints. This would ensure the truly porous nature of the structure in every direction as well as controllable porosity with interconnected pores. Thus the desired controlled variational porosity along the scaffold architecture has been achieved with the combination of two geometrically oriented consecutive layers. A continuous, interconnected and optimized tool-path has been generated for successive layers for additive-manufacturing or solid free form fabrication process. The proposed methodology has been computationally implemented with illustrative examples. Furthermore, the designed example scaffolds with the desired pore size and porosity has been fabricated with an extrusion based bio-fabrication process

Computing a Compact Spline Representation of the Medial Axis Transform of a 2D Shape

We present a full pipeline for computing the medial axis transform of an arbitrary 2D shape. The instability of the medial axis transform is overcome by a pruning algorithm guided by a user-defined Hausdorff distance threshold. The stable medial axis transform is then approximated by spline curves in 3D to produce a smooth and compact representation. These spline curves are computed by minimizing the approximation error between the input shape and the shape represented by the medial axis transform. Our results on various 2D shapes suggest that our method is practical and effective, and yields faithful and compact representations of medial axis transforms of 2D shapes.Comment: GMP14 (Geometric Modeling and Processing

Distance-Sensitive Planar Point Location

Let $\mathcal{S}$ be a connected planar polygonal subdivision with $n$ edges that we want to preprocess for point-location queries, and where we are given the probability $\gamma_i$ that the query point lies in a polygon $P_i$ of $\mathcal{S}$. We show how to preprocess $\mathcal{S}$ such that the query time for a point~$p\in P_i$ depends on~$\gamma_i$ and, in addition, on the distance from $p$ to the boundary of~$P_i$---the further away from the boundary, the faster the query. More precisely, we show that a point-location query can be answered in time $O\left(\min \left(\log n, 1 + \log \frac{\mathrm{area}(P_i)}{\gamma_i \Delta_{p}^2}\right)\right)$, where $\Delta_{p}$ is the shortest Euclidean distance of the query point~$p$ to the boundary of $P_i$. Our structure uses $O(n)$ space and $O(n \log n)$ preprocessing time. It is based on a decomposition of the regions of $\mathcal{S}$ into convex quadrilaterals and triangles with the following property: for any point $p\in P_i$, the quadrilateral or triangle containing~$p$ has area $\Omega(\Delta_{p}^2)$. For the special case where $\mathcal{S}$ is a subdivision of the unit square and $\gamma_i=\mathrm{area}(P_i)$, we present a simpler solution that achieves a query time of $O\left(\min \left(\log n, \log \frac{1}{\Delta_{p}^2}\right)\right)$. The latter solution can be extended to convex subdivisions in three dimensions