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.
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ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 28–October 1, 2010
Philadelphia, Pennsylvania, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-4415-1
PROCEEDINGS PAPER
The Challenges of Modeling Magnetic Shape Memory Alloys Under Complex Load Paths
Alex B. Waldauer,
Alex B. Waldauer
Northern Arizona University, Flagstaff, AZ
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Heidi P. Feigenbaum,
Heidi P. Feigenbaum
Northern Arizona University, Flagstaff, AZ
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Constantin Ciocanel
Constantin Ciocanel
Northern Arizona University, Flagstaff, AZ
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Alex B. Waldauer
Northern Arizona University, Flagstaff, AZ
Heidi P. Feigenbaum
Northern Arizona University, Flagstaff, AZ
Constantin Ciocanel
Northern Arizona University, Flagstaff, AZ
Paper No:
SMASIS2010-3654, pp. 49-55; 7 pages
Published Online:
April 4, 2011
Citation
Waldauer, AB, Feigenbaum, HP, & Ciocanel, C. "The Challenges of Modeling Magnetic Shape Memory Alloys Under Complex Load Paths." Proceedings of the ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, Volume 1. Philadelphia, Pennsylvania, USA. September 28–October 1, 2010. pp. 49-55. ASME. https://doi.org/10.1115/SMASIS2010-3654
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