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• W2899357085 abstract "A novel generative design approach is developed in this study, which produces a mechanically optimized topological design while simultaneously mimicking an input exemplar texture. The textures are believed embedding certain functional information intrinsic to these objects. Designing objects similar to these textures will not only maintain such functions within the design but also widely expand the design space to explore more design options. However, simple textural replications or reconstructions cannot produce expected designs as an ideal structure has to adapt to the variations of the complex stress distributions caused by external loadings. On the other hand, a simple topology optimization formulation under a single global similarity constraint may produce undesirable structures exhibiting geometric disconnections or boundary protrusions. Due to these considerations, the proposed approach carefully formulates the problem as a classical topological compliance minimization problem under block-wise similarity constraints between the target design and an input texture. In addition, a novel physics-adaptive regulator is also proposed, which fine-tunes the block similarity according to its per-element compliances. Ultimately, we can create a set of design options both physically optimized and geometrically smooth for generative design. Extensive numerical results were also tested to demonstrate the approach’s performance." @default.
• W2899357085 created "2018-11-09" @default.
• W2899357085 creator A5005373398 @default.
• W2899357085 creator A5021384155 @default.
• W2899357085 creator A5065581232 @default.
• W2899357085 date "2019-03-01" @default.
• W2899357085 modified "2023-10-16" @default.
• W2899357085 title "Texture-guided generative structural designs under local control" @default.
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• W2899357085 doi "https://doi.org/10.1016/j.cad.2018.10.002" @default.
• W2899357085 hasPublicationYear "2019" @default.
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