Modeling of shape memory alloy pseudoelastic spring elements using Preisach model for passive vibration isolation

Mughees M. Khan; Dimitris C. Lagoudas

doi:10.1117/12.475230

10 July 2002 Modeling of shape memory alloy pseudoelastic spring elements using Preisach model for passive vibration isolation

Mughees M. Khan, Dimitris C. Lagoudas

Author Affiliations +

Proceedings Volume 4693, Smart Structures and Materials 2002: Modeling, Signal Processing, and Control; (2002) https://doi.org/10.1117/12.475230
Event: SPIE's 9th Annual International Symposium on Smart Structures and Materials, 2002, San Diego, California, United States

Abstract

Advances in active materials and smart structures, especially in applications of Shape Memory Alloys (SMA) as vibration isolation devices requires modeling of the pseudoelastic hysteresis found in SMAs. In general SMA hysteresis has been modeled either through constitutive models based on mechanics and material parameters or through system identification based models that depend only on input-output relationships, most popular being the Preisach Model. In this work, a basis is set forth for studying the effect of SMA pseudoelasticity on the behavior of vibrating systems. A Preisach Model is implemented to predict the component level pseudoelastic response of SMA spring elements. The model is integrated into a numerical solution of the non-linear dynamic system that results from the inclusion of Shape Memory Alloy components in a dynamic structural system. The effect of pseudoelasticity on a dynamic system is investigated for various loading levels and system configurations and the importance of large amplitude motion is discussed. Promising results are obtained from these investigations and the application of these studies to experimental work in progress by the authors is briefly discussed.

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Mughees M. Khan and Dimitris C. Lagoudas "Modeling of shape memory alloy pseudoelastic spring elements using Preisach model for passive vibration isolation", Proc. SPIE 4693, Smart Structures and Materials 2002: Modeling, Signal Processing, and Control, (10 July 2002); https://doi.org/10.1117/12.475230

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