Stain Amplitude Volume Fraction Method for Evaluation of Nitinol Fatigue Durability

Finite element analysis simulation is commonly used to evaluate fatigue durability of nitinol medical implants. Currently available methodologies for interpreting simulation results are limited in several ways. There is a need for an improved methodology that is:

• Meaningful: Unlike methodologies that judge the performance of the entire model by a single maximum point value, it should integrate all of the strain data available from the simulation.
• Unambiguous: Unlike the qualitative evaluations that rely upon proximity of points to lines, it should provide quantitative information that enables unambiguous comparisons between related designs or load cases.
• Accessible: The methodology should be available to any analyst using widely available commercial simulation tools, without the need for separately licensed proprietary software.

We propose a methodology that improves upon the widely accepted foundation of a point cloud in conjunction with a constant life diagram, and meets each of the above criteria. The most basic implementation of the strain amplitude volume fraction (SAVF) method proposes:

1. Define one or more relevant strain amplitude threshold strain limits, for example 0.4%.
2. Calculate strain amplitude for all integration points in the model, according to the methods described above.
3. Also evaluate the volume of material associated with each integration point. 
4. For each strain amplitude threshold, calculate the sum of material volume having a strain amplitude exceeding the threshold value.
5. Report the strain amplitude volume fraction for one or more strain thresholds, in percentage or parts-per-million units. 
6. Report number of contiguous regions exceeding each threshold, and the volume and/or characteristic length of each of these contiguous regions.

The methodology is discussed in detail, along with sample analysis results, along with recommendations for statictically analyzing SAVF results in conjunction with data documenting the volume fraction, size, and distribution of material impurities.