TY - JOUR
T1 - Shape and topology optimization of compliant mechanisms using a parameterization level set method
AU - Luo, Zhen
AU - Tong, Liyong
AU - Wang, Michael Yu
AU - Wang, Shengyin
N1 - Funding Information:
The research work sponsored in part by the Australian Research Council under Grant No. ARC-DP0666683, also by the Hong Kong Research Grants Council (Grants: CUHK4164/03E and CUHK416205) and the Natural Science Foundation of China (Grants: 50128503 and 50390063). The authors show their acknowledgements to Prof. Krister Svanberg for providing his MMA codes, and to the anonymous reviewers for their valuable comments.
PY - 2007/11/10
Y1 - 2007/11/10
N2 - 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.
AB - 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.
KW - Compliant mechanisms
KW - Convex programming
KW - Level set methods
KW - Radial basis functions
KW - Shape optimization
KW - Topology optimization
UR - http://www.scopus.com/inward/record.url?scp=35348887740&partnerID=8YFLogxK
U2 - 10.1016/j.jcp.2007.08.011
DO - 10.1016/j.jcp.2007.08.011
M3 - Article
AN - SCOPUS:35348887740
SN - 0021-9991
VL - 227
SP - 680
EP - 705
JO - Journal of Computational Physics
JF - Journal of Computational Physics
IS - 1
ER -