Fatigue failure testing of human hair: Weibull-analysis for constant strain experiments

Area of Science:

• Materials Science
• Biomechanics
• Textile Science

Background:

• Fatigue failure testing is crucial for material durability under cyclic loading.
• Human hair is subject to long-term, oscillatory stresses and strains.
• Existing research primarily focuses on constant stress fatigue tests.

Purpose of the Study:

• To investigate human hair fatigue failure under various constant strain levels.
• To complement existing fatigue testing data with constant strain experiments.
• To analyze fatigue behavior using a non-linear fit of the cumulative two-parameter Weibull distribution (CWD).

Main Methods:

• Conducted cyclic fatigue tests on human hair at constant strain levels ranging from 4% to 30%.
• Applied a non-linear fit of the cumulative two-parameter Weibull distribution (CWD) to survival data.
• Analyzed data using lifetime index ln(α) and shape factor β as key parameters.

Main Results:

• High coefficients of determination and normally distributed residuals indicate precise parameter values.
• Precision of parameter values decreases at high constant strains due to data grouping.
• The lifetime index ln(α) decreases and the shape factor β increases exponentially with strain.
• A fundamental change in failure mode is observed when β exceeds unity at 4.3% strain.
• Theoretical curves for ln(α) and β cross around 45% strain, aligning with conventional tensile break strain.

Conclusions:

• The cumulative two-parameter Weibull distribution (CWD) effectively models human hair fatigue failure data.
• Strain significantly influences the fatigue life and failure mode of human hair.
• The findings suggest a non-empirical basis for the CWD model in hair fatigue analysis.