کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6917356 | 862949 | 2015 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Design-space dimensionality reduction in shape optimization by Karhunen-Loève expansion
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
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چکیده انگلیسی
The paper presents a methodology to reduce the dimension of design spaces in shape optimization problems, while retaining a desired level of geometric variance. The method is based on a generalized Karhunen-Loève expansion (KLE). Arbitrary shape modification spaces are assessed in terms of Karhunen-Loève modes (eigenvectors) and associated geometric variance (eigenvalues). The former are used as a basis in order to build a reduced-dimensionality representation of the shape modification. The method is demonstrated for the shape optimization of a high-speed catamaran, based on CFD simulations and aimed at the reduction of the wave component of calm-water resistance. KLE is applied to three design spaces with large dimensionality (â¥20), based on a free form deformation technique. The space with the largest geometric variance is selected for dimensionality reduction and design optimization. N-dimensional design spaces are used, with N=1, 2, 3, and 4, retaining up to the 95% of the geometric variance associated to the original space. The correlation between the objective reduction achieved, the dimension N and the geometric variance of the reduced-dimensionality space is shown and found significant.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 283, 1 January 2015, Pages 1525-1544
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 283, 1 January 2015, Pages 1525-1544
نویسندگان
Matteo Diez, Emilio F. Campana, Frederick Stern,