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Indexed by:期刊论文
Date of Publication:2018-12-01
Journal:JOURNAL OF MECHANICAL DESIGN
Included Journals:SCIE、Scopus
Volume:140
Issue:12
ISSN No.:1050-0472
Key Words:Crashworthiness; Deformation; Musculoskeletal system; Parameterization; Profilometry; Radial basis function networks; Thin walled structures, Crashworthiness designs; Cross sectional profiles; Global deformations; Local deformations; Local reinforcements; Numerical results; Parameterization techniques; Radial Basis Function(RBF), Shape optimization
Abstract:A technique based on a skeleton-section template for parameterizing finite element (FE) models is reported and applied to shape optimization of thin-walled beam components. The template consists of a skeletal curve and a set of cross-sectional profiles. The skeletal curve can be used to derive global model variations, while the cross section is designed to obtain local deformations of the given shape. A mesh deformation method based on the radial basis functions (RBF) interpolation is employed to derive the shape variations. Specifically, the skeleton-embedding space and an anisotropic distance metric are introduced to improve the RBF deformation method. To validate the applicability of the proposed template-based parameterization technique to general shape optimization frameworks, two proof-of-concept numerical studies pertaining to crashworthiness design of an S-shaped frame were implemented. The first case study focused on global deformations with the skeletal curve, and the second treated the cross-sectional profiles as design parameters to derive local reinforcements on the model. Both studies showed the efficiency of the proposed method in generation of quality shape variants for optimization. From the numerical results, considerable amount of improvements in crashworthiness performances of the S-shaped frame were observed as measured by the peak crushing force (PCF) and the energy absorption. We conclude that the proposed template-based parameterization technique is suitable for shape optimization tasks.
