Open Access
ARTICLE
Inverse Construction Methods of Heterogeneous NURBS Object Based on Additive Manufacturing
Ting Zang1, Dongbin Zhu2,*, Guowang Mu1
1 School of Science, Hebei University of Technology, Tianjin, 300130, China
2 School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300130, China
* Corresponding Author: Dongbin Zhu. Email:
(This article belongs to this Special Issue: Design & simulation in Additive Manufacturing)
Computer Modeling in Engineering & Sciences 2020, 125(2), 597-610. https://doi.org/10.32604/cmes.2020.09965
Received 31 January 2020; Accepted 15 June 2020; Issue published 12 October 2020
Abstract
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.
Keywords
Cite This Article
Zang, T., Zhu, D., Mu, G. (2020). Inverse Construction Methods of Heterogeneous NURBS Object Based on Additive Manufacturing.
CMES-Computer Modeling in Engineering & Sciences, 125(2), 597–610. https://doi.org/10.32604/cmes.2020.09965