Inverse Construction Methods of Heterogeneous NURBS Object Based on Additive Manufacturing

According to the requirement of heterogeneous object modeling in additive manufacturing(AM),the Non-Uniform Rational B-Spline(NURBS)method has been applied to the digital representation of heterogeneous object in this paper.By putting forward the NURBS material data structure and establishing heterogeneous NURBS object model,the accurate mathematical unified representation of analytical and free heterogeneous objects have been realized.With the inverse modeling of heterogeneous NURBS objects,the geometry and material distribution can be better designed to meet the actual needs.Radical Basis Function(RBF)method based on global surface reconstruction and the tensor product surface interpolation method are combined to RBF-NURBS inverse construction method.The geometric and/or material information of regular mesh points is obtained by RBF interpolation of scattered data,and the heterogeneous NURBS surface or object model is obtained by tensor product interpolation.The examples have shown that the heterogeneous objects fitting to scattered data points can be generated effectively by the inverse construction methods in this paper and 3D CAD models for additive manufacturing can be provided.

Review of heterogeneous material objects modeling in additive manufacturing

This review investigates the recent developments of heterogeneous objects modeling in additive manufacturing(AM),as well as general problems and widespread solutions to the modeling methods of heterogeneous objects.Prevalent heterogeneous object representations are generally categorized based on the different expression or data structure employed therein,and the state-of-the-art of process planning procedures for AM is reviewed via different vigorous solutions for part orientation,slicing methods,and path planning strategies.Finally,some evident problems and possible future directions of investigation are discussed.

An Approach to Representing Heterogeneous Non-Uniform Rational B-Spline Objects

The representation method of heterogeneous material information is one of the key technologies of heterogeneous object modeling, but almost all the existing methods cannot represent non-uniform rational B-spline （NURBS） entity. According to the characteristics of NURBS, a novel data structure, named NURBS material data structure, is proposed, in which the geometrical coordinates, weights and material coordinates of NURBS heterogene- ous objects can be represented simultaneously. Based on this data structure, both direct representation method and inverse construction method of heterogeneous NURBS objects are introduced. In the direct representation method, three forms of NURBS heterogeneous objects are introduced by giving the geometry and material information of con- trol points, among which the homogeneous coordinates form is employed for its brevity and easy programming. In the inverse construction method, continuous heterogeneous curves and surfaces can he obtained by interpolating discrete points and curves with specified material information. Some examples are given to show the effectiveness of the pro- posed methods.

2D-Manifold Boundary Surfaces Extraction from Heterogeneous Object on GPU

The conventional isosurface techniques are not competent for nleshing a heterogeneous object because they assume that the object is homogeneous. Thus the visualization method taking the heterogeneity into account is desired. In this paper, we propose a novel algorithm to extract the boundary surfaces from a heterogeneous object in one pass, whose remarkable advantage is free of the number of materials contained. The heterogeneous object is first classified into a series of homogeneous material components. Then each component is enclosed with a 2D-manifold boundary surface extracted via our algorithm. The information important to the heterogeneous object is also provided, such as the interface between two materials, the intersection curve where three materials meet and the intersection point where four materials meet. To improve the performance, the algorithm is also designed and implemented on GPU. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm.