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  4. Determination of Material Parameters and FEM Simulation for the Development of a Design System for Shape Memory Springs
 
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November 2023
Conference Paper
Title

Determination of Material Parameters and FEM Simulation for the Development of a Design System for Shape Memory Springs

Abstract
Including characteristic alloy parameters in the design process of shape memory springs is crucial to enhance the performance of the resulting actuator. In contrast to conventional spring steel, shape memory alloys (SMA) show a non-linear stress-strain curve based on a thermal- or stress-induced phase transformation. Substitute models obtained from linear approximations do not adequately represent these material properties. Consequently, the designed actuators are liable to oversizing without fully exploiting the potential strokes and forces. This paper shows an alternate system design method based on cause-effect relationships between the material parameters, the spring geometry, and the resulting actuator behaviour. To identify the relationships, FEM models of various SMA spring geometries, such as helical, shaft and wave springs, were implemented in the ANSYS Mechanical simulation software. Moreover, the springs were manufactured to validate the models using standardized test methods such as tensile-compression tests and DSC (Differential Scanning Calorimetry) measurements. These validated models form the basis to determine the cause effect-relationships via the Design of Experiment (DoE) method. Finally, discrete mathematical descriptions of the relationships are derived and implemented into a shape memory spring layout tool. The derived method achieves a substantially higher accuracy compared to linear substitute models. In addition, it is worth highlighting that the usage of the layout tool does not require special knowledge in thermo-mechanical simulation. Hence, it will be of particular interest for small and medium companies to access the technology more easily.
Author(s)
Hiekel, Alexander  orcid-logo
Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU  
Hoffmann, Florian
Forschungsgemeinschaft Werkzeuge und Werkstoffe e.V. -FGW-  
Krieg, Romina
Forschungsgemeinschaft Werkzeuge und Werkstoffe e.V. -FGW-  
Theiß, Ralf
Forschungsgemeinschaft Werkzeuge und Werkstoffe e.V.
Pagel, Kenny  
Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU  
Pelshenke, Christian
Forschungsgemeinschaft Werkzeuge und Werkstoffe e.V. -FGW-  
Horn, Simon
Forschungsgemeinschaft Werkzeuge und Werkstoffe e.V. -FGW-  
Mehrbakhsh, Mehrdad
Forschungsgemeinschaft Werkzeuge und Werkstoffe e.V. -FGW-  
Drossel, Welf-Guntram  
Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU  
Dültgen, Peter
Forschungsgemeinschaft Werkzeuge und Werkstoffe e.V. -FGW-  
Mainwork
ASME 2023 Conference on Smart Materials, Adaptive Structures and Intelligent Systems  
Conference
Conference on Smart Materials, Adaptive Structures and Intelligent Systems 2023  
DOI
10.1115/SMASIS2023-111107
Language
English
Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU  
Keyword(s)
  • shape memory alloy

  • system design

  • shape memory springs

  • parameter identification

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