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Mem-models as building blocks for simulation and identification of hysteretic systems

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Abstract

In this study, mem-springs and mem-dashpots from a newly introduced family of mem-models are used as fundamental building blocks in hysteresis modeling. The usefulness of such assemblies of mem-models is investigated for both simulation and system identification. First, numerical simulations demonstrate the general capability of these models to describe strain ratcheting behaviors. Next, system identification is addressed by extending the concepts of mem-springs to include linear and nonlinear springs and those of mem-dashpots to include linear and nonlinear dashpots. A reconfigurable device made of steel and/or shape memory alloy wires and wire ropes provides a fitting test for the proposed mem-model-based family. A system identification procedure corroborated by physical insights is proposed and the results are validated using physics-based analysis. Multilayer feedforward neural networks are used for static nonlinear function approximation. The model class and system identification procedure proposed here are shown to extract similarities and dissimilarities among different configurations of the device by quantifying the spring and damping effects.

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Acknowledgements

The first author would like to acknowledge the Vice President for Research of the University of Oklahoma for the Faculty Investment Program (FIP), the partial support of which initiated the collaboration in this study. The first author would like to acknowledge the hosting of Professor Jim Beck at California Institute of Technology and Professor Eleni Chatzi at ETH, Zurich during the author’s sabbatical leave for the major theoretical development in this study.

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Authors and Affiliations

  1. School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK, 73019-1024, USA

    Jin-Song Pei

  2. Department of Structural and Geotechnical Engineering, Sapienza University of Rome, 00184, Rome, Italy

    Biagio Carboni & Walter Lacarbonara

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  1. Jin-Song Pei
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  2. Biagio Carboni
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  3. Walter Lacarbonara
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Correspondence to Jin-Song Pei.

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Pei, JS., Carboni, B. & Lacarbonara, W. Mem-models as building blocks for simulation and identification of hysteretic systems. Nonlinear Dyn 100, 973–998 (2020). https://doi.org/10.1007/s11071-020-05542-5

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  • DOI: https://doi.org/10.1007/s11071-020-05542-5

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