Avoiding reinventing the wheel: reusable open-source topology optimization software

  • Research Paper
  • Published: 12 June 2023
  • Volume 66 , article number  145 , ( 2023 )

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  • Carolina M. Jauregui 1 ,
  • Jaeyub Hyun   ORCID: orcid.org/0000-0002-9070-5017 1 , 2 ,
  • Andreas Neofytou 1 ,
  • Justin S. Gray 3 &
  • Hyunsun Alicia Kim 1  

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The aim of this work is to introduce a unified description of topology optimization (TO) methods, which modularizes and generalizes all TO methods, both density based and boundary based. This unified description allows for the implementation of a reusable modular TO software, ParaLeSTO, which specializes in level set TO (LSTO). In addition, we use this software as a means to propose a guideline for research software metadata in the TO community. The proposed guideline for the research software metadata is based on the FAIR principles for research software, which focuses on improving the findability, accessibility, interoperability, and reusability of research software and its metadata. The modularized TO framework separates the analysis, which solves the state equations and does the sensitivity analysis, and the design modification, which represents and modifies the design. Mapping is then used to interface between the two. We demonstrate the interoperability and reusability of this framework through numerical examples.

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Acknowledgements

We acknowledge the support of NASA (Grant Number 80NSSC18M0153 P00005) and Honda Research Institute Europe Gmbh.

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Replication of Results

The software ParaLeSTO is available on https://gitlab.com/m2dO1/paralesto and https://zenodo.org/record/7613753#.Y-LyCezMK3I . The source code for the first four examples in this paper is provided in examples/2022_{p}aper_{e}x/ in the repository. The instructions for how to run the examples are provided in the README file. The final example contains proprietary code and therefore is not provided.

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Jauregui, C.M., Hyun, J., Neofytou, A. et al. Avoiding reinventing the wheel: reusable open-source topology optimization software. Struct Multidisc Optim 66 , 145 (2023). https://doi.org/10.1007/s00158-023-03589-7

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    Optimization of unit cell size, topology, and distribution has also been inspired by nature. Material gradients commonly occur in cellular biological materials such as bone, sea sponges, teeth, bamboo, pine leaves, and horses hooves [10].In nature multi-functionality is achieved by adapting to the local loading conditions and relying on building hierarchical structures with the optimized ...

  19. PDF Computer Networking: a Review

    International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:07/July-2021 Impact Factor- 5.354 www.irjmets.com www.irjmets.com @International Research Journal of Modernization in Engineering, Technology and Science ... Topology. I. INTRODUCTION A network is a set of devices (often referred to as nodes ...

  20. (PDF) (I) (2021), Special issue

    PDF | On Aug 9, 2020, S Jafari and others published (I) (2021), Special issue | Find, read and cite all the research you need on ResearchGate ... The main purpose of Digital topology is the study ...

  21. Topology and its Applications

    Final citation details, e.g. volume and/or issue number, publication year and page numbers, still need to be added and the text might change before final publication. Read the latest articles of Topology and its Applications at ScienceDirect.com, Elsevier's leading platform of peer-reviewed scholarly literature.

  22. (PDF) Topology optimization for optimum shape and size of a drone frame

    Technology of drone and its applications in various fields are getting popular day by day. In this paper finite element analysis based topology optimization technique has been adopted during the ...

  23. [PDF] The topology of data: opportunities for cancer research

    The topology of data: opportunities for cancer research. An overview of TDA in Cancer Research is provided, discussing how TDA has been applied across heterogeneous datatypes for cancer research and the potential to support future developments in healthcare as biomedical datasets rise in complexity and dimensionality. Expand.