Abstract
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. Map** is then used to interface between the two. We demonstrate the interoperability and reusability of this framework through numerical examples.
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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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DOI: https://doi.org/10.1007/s00158-023-03589-7