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Numerical method for shape optimization using T-spline based isogeometric method


Numerical methods for shape design sensitivity analysis and optimization have been developed for several decades. However, the finite-element-based shape design sensitivity analysis and optimization have experienced some bottleneck problems such as design parameterization and design remodeling during optimization. In this paper, as a remedy for these problems, an isogeometric-based shape design sensitivity analysis and optimization methods are developed incorporating with T-spline basis. In the shape design sensitivity analysis and optimization procedure using a standard finite element approach, the design boundary should be parameterized for the smooth variation of the boundary using a separate geometric modeler, such as a CAD system. Otherwise, the optimal design usually tends to fall into an undesirable irregular shape. In an isogeometric approach, the NURBS basis function that is used in representing the geometric model in the CAD system is directly used in the response analysis, and the design boundary is expressed by the same NURBS function as used in the analysis. Moreover, the smoothness of the NURBS can allow the large perturbation of the design boundary without a severe mesh distortion. Thus, the isogeometric shape design sensitivity analysis is free from remeshing during the optimization process. In addition, the use of T-spline basis instead of NURBS can reduce the number of degrees of freedom, so that the optimal solution can be obtained more efficiently while yielding the same optimum design shape.

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This work was supported by the Korea Research Foundation grant (KRF-2007-612-D00146) and National Research Foundation of Korea grant (R32-2008-000-10161-0) funded by the Korea government (MEST) in 2009. The supports are gratefully acknowledged.

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Correspondence to Seonho Cho.

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Ha, S., Choi, K.K. & Cho, S. Numerical method for shape optimization using T-spline based isogeometric method. Struct Multidisc Optim 42, 417–428 (2010).

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  • Shape design sensitivity analysis
  • Shape design optimization
  • Isogeometric analysis
  • T-spline
  • Design parameterization
  • Local refinement