Automatic parameter identification of a shape memory alloy model using characteristic experimental data points
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Identifying material parameters of constitutive models can be a time consuming process. This is especially evident when the constitutive models have many parameters. In this work, an automatic identification procedure is described to determine the various parameters of a shape memory alloy model. The procedure requires some parameters as manual inputs (to be determined via trial and error) and determines some of the parameters directly from experimental data. In addition, the procedure calculates some of the parameters using Newton's method based on characteristic data points so that the simulation curves pass through those points. As a result, the method essentially decouples the effects of the parameters on the simulation uniaxial test curves. The automatic identification procedure is applied for uniaxial tests dealing with transformation, tension–compression asymmetry, internal loops, plasticity and functional fatigue. The procedure is fast, flexible and reasonably accurate. However, the approach is currently limited to uniaxial tests, small strains and needs to be tailored to each model individually.
Details
Original language | English |
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Article number | 105300 |
Number of pages | 12 |
Journal | European Journal of Mechanics. A, Solids |
Volume | 106 (2024) |
Publication status | Published - 16 Mar 2024 |
Peer-reviewed | Yes |
External IDs
Scopus | 85187958511 |
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Mendeley | e1b657a2-40fa-3813-a93f-3c03372c7193 |
Keywords
ASJC Scopus subject areas
Keywords
- Constitutive model, Functional fatigue, Material parameter identification, Plasticity, Shape memory alloys