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Optimal and continuous multilattice embedding

delete2021-04-16
delete70
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OA
AI
E
Emily D. Sanders
A
Anderson Pereira
G
Gláucio H. Paulino *
DOI:10.1126/sciadv.abf4838delete
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Abstract

Abstract

En 中文
Because of increased geometric freedom at a widening range of length scales and access to a growing material space, additive manufacturing has spurred renewed interest in topology optimization of parts with spatially varying material properties and structural hierarchy. Simultaneously, a surge of micro/nanoarchitected materials have been demonstrated. Nevertheless, multiscale design and micro/nanoscale additive manufacturing have yet to be sufficiently integrated to achieve free-form, multiscale, biomimetic structures. We unify design and manufacturing of spatially varying, hierarchical structures through a multimicrostructure topology optimization formulation with continuous multimicrostructure embedding. The approach leads to an optimized layout of multiple microstructural materials within an optimized macrostructure geometry, manufactured with continuously graded interfaces.To make the process modular and controllable and to avoid prohibitively expensive surface representations, we embed the microstructures directly into the 3D printer slices. The ideas provide a critical, interdisciplinary link at the convergence of material and structure in optimal design and manufacturing.
Keywords:
TOPOLOGY OPTIMIZATION
DESIGN
VOLUME
SHAPE
FABRICATION
GENERATION
EFFICIENT
DENSITY
INFILL
AI Summary

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Journal

Science Advances cover
Science Advances
IF:
12.5
Papers:
2.1W
Citations:
18.1W

Organization

G
Georgia Institute of Technology
Scholars:
1.8W
Papers: 1.4W
Citations: 5.9W
U
university system of georgia
Scholars:
7.3W
Papers: 6.6W
Citations: 101
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