TY - GEN
T1 - Automatic design in Matlab using PDE toolbox for shape and topology optimization
AU - Sun, Yilun
AU - Xu, Lingji
AU - Yang, Jingru
AU - Lueth, Tim C.
N1 - Publisher Copyright:
Copyright © 2019 ASME.
PY - 2019
Y1 - 2019
N2 - In this paper, we present a novel concept of using Matlab’s Partial Differential Equation (PDE) Toolbox to achieve shape and topology optimization during the automatic mechanical design process. In our institute, we are developing a toolbox called Solid Geometry (SG) Library in Matlab to achieve automatic design of medical robots and mechanisms. The entire design process is performed in one developing environment without additional data input and output. And those robots and mechanisms can be quickly manufactured by different kinds of 3D printers. Recently, we have also integrated the shape and topology optimization techniques into our automatic design process by using the PDE Toolbox of Matlab for finite element analysis because of its high efficiency and compactness. For optimization algorithms, we have already implemented two bionic structural optimization methods called Computer Aided Optimization (CAO) and Soft Kill Option (SKO) to optimize the stress distribution in the structure. Since the complicated material layout in the optimization results can be easily realized by the 3D printing technology, the mechanical performance of our medical robots and mechanisms can be greatly improved with the work presented in this paper.
AB - In this paper, we present a novel concept of using Matlab’s Partial Differential Equation (PDE) Toolbox to achieve shape and topology optimization during the automatic mechanical design process. In our institute, we are developing a toolbox called Solid Geometry (SG) Library in Matlab to achieve automatic design of medical robots and mechanisms. The entire design process is performed in one developing environment without additional data input and output. And those robots and mechanisms can be quickly manufactured by different kinds of 3D printers. Recently, we have also integrated the shape and topology optimization techniques into our automatic design process by using the PDE Toolbox of Matlab for finite element analysis because of its high efficiency and compactness. For optimization algorithms, we have already implemented two bionic structural optimization methods called Computer Aided Optimization (CAO) and Soft Kill Option (SKO) to optimize the stress distribution in the structure. Since the complicated material layout in the optimization results can be easily realized by the 3D printing technology, the mechanical performance of our medical robots and mechanisms can be greatly improved with the work presented in this paper.
UR - http://www.scopus.com/inward/record.url?scp=85078755205&partnerID=8YFLogxK
U2 - 10.1115/IMECE2019-10766
DO - 10.1115/IMECE2019-10766
M3 - Conference contribution
AN - SCOPUS:85078755205
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Advanced Materials
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2019 International Mechanical Engineering Congress and Exposition, IMECE 2019
Y2 - 11 November 2019 through 14 November 2019
ER -