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Multiaxial fatigue modeling for Nitinol shape memory alloys under in-phase loading.
1Department of Mechanical Engineering, Mississippi State University, Box 9552, Mississippi State, MS 39762, United States; Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Box 5405, Mississippi State, MS 39762, United States.
A new Fatemi-Socie-type model better predicts multiaxial fatigue life in martensitic Nitinol components under complex loading. Critical plane approaches are recommended for accurate fatigue life analysis of Nitinol alloys.
Area of Science:
- Materials Science
- Mechanical Engineering
- Fatigue Analysis
Background:
- Multiaxial stress conditions are common in real-world component loading.
- Nitinol (Nickel Titanium) alloys are widely used due to their unique properties.
- Understanding fatigue behavior under multiaxial loading is crucial for component reliability.
Purpose of the Study:
- To review and evaluate classical and critical plane fatigue models for martensitic Nitinol.
- To assess model performance under torsion and in-phase axial-torsion loading.
- To identify the most suitable models for predicting multiaxial fatigue life in Nitinol.
Main Methods:
- Review of stress-based fatigue models including von Mises, Tresca, Findley, McDiarmid, and a novel Fatemi-Socie-type model.
- Evaluation of model application to martensitic Nitinol under torsion and axial-torsion fatigue.
- Focus on shear stress as the primary damage parameter due to observed crack plane behavior.
Main Results:
- The proposed Fatemi-Socie-type model demonstrated superior prediction accuracy compared to other models.
- Critical plane approaches showed greater suitability for multiaxial fatigue prediction in martensitic Nitinol.
- Experimental data from literature were used for validation.
Conclusions:
- Critical plane models are more appropriate for predicting multiaxial fatigue in martensitic Nitinol.
- The developed Fatemi-Socie-type model offers improved fatigue life predictions.
- Recommendations are provided for calibrating more robust multiaxial fatigue models for Nitinol.
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