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A Realization Method for Transforming a Topology Optimization Design into Additive Manufacturing Structures
Author(s) -
Shutian Liu,
Quhao Li,
Junhuan Liu,
Wenjiong Chen,
Yongcun Zhang
Publication year - 2018
Publication title -
engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.376
H-Index - 45
eISSN - 2096-0026
pISSN - 2095-8099
DOI - 10.1016/j.eng.2017.09.002
Subject(s) - topology optimization , topology (electrical circuits) , parametric statistics , curvature , shape optimization , mathematical optimization , computer science , reverse engineering , cad , engineering design process , finite element method , engineering , mathematics , engineering drawing , mechanical engineering , structural engineering , geometry , statistics , electrical engineering , programming language
Topology optimization is a powerful design approach that is used to determine the optimal topology in order to obtain the desired functional performance. It has been widely used to improve structural performance in engineering fields such as in the aerospace and automobile industries. However, some gaps still exist between topology optimization and engineering application, which significantly hinder the application of topology optimization. One of these gaps is how to interpret topology results, especially those obtained using the density framework, into parametric computer-aided design (CAD) models that are ready for subsequent shape optimization and manufacturing. In this paper, a new method for interpreting topology optimization results into stereolithography (STL) models and parametric CAD models is proposed. First, we extract the skeleton of the topology optimization result in order to ensure shape preservation and use a filtering method to ensure characteristics preservation. After this process, the distribution of the nodes in the boundary of the topology optimization result is denser, which will benefit the subsequent curve fitting. Using the curvature and the derivative of curvature of the uniform B-spline curve, an adaptive B-spline fitting method is proposed in order to obtain a parametric CAD model with the fewest control points meeting the requirement of the fitting error. A case study is presented to provide a detailed description of the proposed method, and two more examples are shown to demonstrate the validity and versatility of the proposed method.

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