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LUPOS: Open-Source Scientific Computing in Structural Dynamics

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Data Science in Engineering, Volume 10 (SEM 2023)

Abstract

LUPOS is a parametric FEM code developed in MATLAB aiming to merge different simulative characteristics: to provide a complete open-source 3D FEM code suitable for analysing elements formulations, assembly approaches, reduction techniques in a complete parametric scheme; to allow parametric analyses and integrating results, giving all matrices details and formulations; to integrate this parametric FEM code in Multi-Body and nonlinear integration processes in time domain such as Simulink.

The acronym of LUPOS in Italian-English Lupo’s, or better in Latin lupus, lupi, is associable to the wolf, symbol of smart and aggressive animal. What better name could be chosen?

The reason to develop another software for dynamics relies in the main idea to share concepts about mechanical modelling and simulation tools that can be applied from academic examples to industrial applications in an intuitive and easy way, but maintaining all the mathematical rigour and numerical explanations, in particular taking into account parameters that can extend to families of structures.

Some examples of different levels of complexities are analysed for static, real and complex modal analyses and finally in rotordynamics in both time and frequency domains.

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Change history

  • 05 April 2024

    A correction has been published.

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Acknowledgements

The authors fully acknowledge all support received during years of developments and discussions on LUPOS topics from several MSc and PhD students of the Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Italy.

In particular, we thank the main contributions of Gabriele Marcuccio, Marco Brino and Domenico Lisitano.

For the latest software release and for having details, please contact elvio.bonisoli@polito.it

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Correspondence to Simone Venturini .

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Bonisoli, E., Dimauro, L., Venturini, S. (2023). LUPOS: Open-Source Scientific Computing in Structural Dynamics. In: Madarshahian, R., Hemez, F. (eds) Data Science in Engineering, Volume 10. SEM 2023. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-031-34946-1_23

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