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Topology optimization based on reduction methods with applications to multiscale design and additive manufacturing

  • Emmanuel TrommeEmail author
  • Atsushi Kawamoto
  • James K. Guest
Research Article
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Part of the following topical collections:
  1. Structural Topology Optimization

Abstract

Advanced manufacturing processes such as additive manufacturing offer now the capability to control material placement at unprecedented length scales and thereby dramatically open up the design space. This includes the considerations of new component topologies as well as the architecture of material within a topology offering new paths to creating lighter and more efficient structures. Topology optimization is an ideal tool for navigating this multiscale design problem and leveraging the capabilities of advanced manufacturing technologies. However, the resulting design problem is computationally challenging as very fine discretizations are needed to capture all micro-structural details. In this paper, a method based on reduction techniques is proposed to perform efficiently topology optimization at multiple scales. This method solves the design problem without length scale separation, i.e., without iterating between the two scales. Ergo, connectivity between space-varying micro-structures is naturally ensured. Several design problems for various types of micro-structural periodicity are performed to illustrate the method, including applications to infill patterns in additive manufacturing.

Keywords

multiscale topology optimization microstructure additive manufacturing reduction techniques substructuring static condensation super-element 

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Notes

Acknowledgements

This research was supported in part by the US National Science Foundation (NSF) under Grant Number 1462453, and in part by the National Aeronautics and Space Administration (NASA) under Grant Number 80NSSC18K0428. Any opinions, findings, and conclusions or recommendations expressed in this article are those of the author(s) and do not necessarily reflect the views of NSF or NASA.

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Emmanuel Tromme
    • 1
    • 2
    Email author
  • Atsushi Kawamoto
    • 2
  • James K. Guest
    • 1
  1. 1.Department of Civil EngineeringJohns Hopkins UniversityBaltimoreUSA
  2. 2.Toyota Central Ramp;D Labs., Inc.Nagakute, AichiJapan

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