The challenges of modeling magnetic shape memory alloys under complex load paths

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Kiefer and Lagoudas proposed a thermodynamic model for predicting the magneto-mechanical behavior of magnetic shape memory alloys (MSMAs) and then confirmed their model experimentally [1]. The model was calibrated by placing the test specimen under a constant magnetic field and a varying compressive stress. Later, Feigenbaum and Ciocanel [2] used the model to predict behavior under a constant compressive stress and a varying magnetic field. Because the two experiments were done by different researchers on different specimens, the calibration gave different values for material paremeters. In this work, through experimental results from tests performed on the same specimen by the same researchers, the Kiefer and Lagoudas model, with any hardening function, will be shown to be unable to be calibrated so as to accurately predict the magneto-mechanical behavior of a specimen under both types of loading conditions.

Original languageEnglish (US)
Title of host publicationASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2010
Pages49-55
Number of pages7
StatePublished - Dec 1 2010
EventASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2010 - Philadelphia, PA, United States
Duration: Sep 28 2010Oct 1 2010

Publication series

NameASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2010
Volume1

Other

OtherASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2010
CountryUnited States
CityPhiladelphia, PA
Period9/28/1010/1/10

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Biomaterials

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  • Cite this

    Waldauer, A. B., Feigenbaum, H. P., & Ciocanel, C. (2010). The challenges of modeling magnetic shape memory alloys under complex load paths. In ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2010 (pp. 49-55). (ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2010; Vol. 1).