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Published January 2021 | public
Journal Article

Connecting mem-models with classical theories

Abstract

A family of mem-models, including the mem-dashpots, mem-springs, and most recently, mem-inerters, is emerging as a new and powerful way of capturing complex nonlinear behaviors of materials and systems under various types of dynamic loads involving different frequency, amplitude, and loading histories (e.g., hysteresis). Under the framework of nonlinear state-space representation and hybrid dynamical systems, mem-springs may be formulated to effectively represent an inherent degradation of material state. It is shown in this study, for the first time, how the absement (time integral of strain/displacement), a signature state variable for a mem-spring, can be connected with the damage variable, a key quantity in continuum damage mechanics. The generalized momentum (time integral of stress), on the other hand, is shown to be efficient in modeling strain ratcheting via the concept of mem-dashpot. It is also shown in this study, for the first time, how two formulations of the memcapacitive system models (for mem-springs) are special cases of the Preisach model.

Additional Information

© 2021 Springer Nature B.V. Received 10 August 2020; Accepted 09 November 2020; Published 16 January 2021. Professor Jin-Song Pei acknowledges the University of Oklahoma for the teaching release offered in the fall of 2019 and the hospitality of Professor Raimondo Betti at Columbia University. Dr. Gay-Balmaz was partially supported by the ANR project GEOMFLUID, ANR-14-CE23-0002-0. Dr. Marco Quadrelli's research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the NASA Aeronautics and Space Administration. In particular, Jin-Song Pei and Marco B. Quadrelli acknowledge the Oklahoma NASA EPSCoR for the Faculty Research Initiation Fellowship. Government sponsorship acknowledged. The authors declare that they have no conflict of interest.

Additional details

Created:
August 22, 2023
Modified:
October 23, 2023