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On the use of AI for metamodeling: a case study of a 3D bar structure

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Abstract

In scenarios where complex analyses are routinely conducted on similar structures, such as in a redesign process to meet performance requirements or when input parameters require frequent adjustments within a specified domain, a practical approach involves the use of metamodels calibrated using machine learning methodologies. In our investigation, we introduce a metamodel that utilizes an artificial neural network to analyze 3D nonlinear structures undergoing plastic deformations and large strains. Snap-through and snapback behaviors are addressed through network training, which is based on 10,000 Force vs Displacement curves (target outputs) obtained from nonlinear finite element analyses. This interplay between finite element analysis and machine learning, as demonstrated here, exhibits promising potential as an effective technique. The results indicate that the proposed deep neural network can learn from the simulations of finite elements. The discussion explores scenarios where the utilization of AI in the analysis of nonlinear structures is justified.

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Acknowledgements

We thank prof. Thiago Martins, from Complex Systems Laboratory of University of São Paulo, for providing computer support.

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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  1. These authors have contributed equally to this work.

Authors and Affiliations

  1. Department of Mechatronics Engineering, University of São Paulo, Avenida Prof. Luciano Gualberto, 380, São Paulo, 05508-010, SP, Brazil

    Larissa Driemeier, Gabriel Lopes Rodrigues, Marcos Tsuzuki, Marcilio Alves, Lucas Pires da Costa & Rafael Traldi Moura

  2. Nuclear and Energy Research Institute, Avenida Lineu Prestes, São Paulo, 05508-000, SP, Brazil

    Eduardo Lobo Lustosa Cabral

Authors
  1. Larissa Driemeier
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  2. Eduardo Lobo Lustosa Cabral
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  3. Gabriel Lopes Rodrigues
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  4. Marcos Tsuzuki
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  5. Marcilio Alves
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  6. Lucas Pires da Costa
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  7. Rafael Traldi Moura
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Correspondence to Larissa Driemeier.

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Author Larissa Driemeier declares that she has no conflict of interest. Author Eduardo Lobo Lustosa Cabral declares that he has no conflict of interest. Author Gabriel Lopes Rodrigues declares that he has no conflict of interest. Author Marcos Tsuzuki declares that he has no conflict of interest. Author Marcilio Alves declares that he has no conflict of interest. Author Lucas Pires da Costa declares that he has no conflict of interest. Author Rafael Traldi Moura declares that he has no conflict of interest.

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Driemeier, L., Cabral, E.L.L., Rodrigues, G.L. et al. On the use of AI for metamodeling: a case study of a 3D bar structure. Soft Comput (2023). https://doi.org/10.1007/s00500-023-09491-0

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