Please use this identifier to cite or link to this item:
|Title:||Shape and topology optimization of compliant mechanisms using a parameterization level set method||Authors:||Luo, Z.
Level set methods
Radial basis functions
|Issue Date:||10-Nov-2007||Citation:||Luo, Z., Tong, L., Wang, M.Y., Wang, S. (2007-11-10). Shape and topology optimization of compliant mechanisms using a parameterization level set method. Journal of Computational Physics 227 (1) : 680-705. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jcp.2007.08.011||Abstract:||In this paper, a parameterization level set method is presented to simultaneously perform shape and topology optimization of compliant mechanisms. The structural shape boundary is implicitly embedded into a higher-dimensional scalar function as its zero level set, resultantly, establishing the level set model. By applying the compactly supported radial basis function with favorable smoothness and accuracy to interpolate the level set function, the temporal and spatial Hamilton-Jacobi equation from the conventional level set method is then discretized into a series of algebraic equations. Accordingly, the original shape and topology optimization is now fully transformed into a parameterization problem, namely, size optimization with the expansion coefficients of interpolants as a limited number of design variables. Design of compliant mechanisms is mathematically formulated as a general optimization problem with a nonconvex objective function and two additionally specified constraints. The structural shape boundary is then advanced as a process of renewing the level set function by iteratively finding the expansion coefficients of the size optimization with a sequential convex programming method. It is highlighted that the present method can not only inherit the merits of the implicit boundary representation, but also avoid some unfavorable features of the conventional discrete level set method, such as the CFL condition restriction, the re-initialization procedure and the velocity extension algorithm. Finally, an extensively investigated example is presented to demonstrate the benefits and advantages of the present method, especially, its capability of creating new holes inside the design domain. © 2007 Elsevier Inc. All rights reserved.||Source Title:||Journal of Computational Physics||URI:||http://scholarbank.nus.edu.sg/handle/10635/114650||ISSN:||00219991||DOI:||10.1016/j.jcp.2007.08.011|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jan 14, 2020
WEB OF SCIENCETM
checked on Jan 14, 2020
checked on Jan 18, 2020
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.