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Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method
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A Multi-Scale Model for Predicting Physically Short Crack and Long Crack Behavior in Metals.

Xing Yang1, Chunguo Zhang1, Panpan Wu1

  • 1Key Laboratory of Highway Construction Technology and Equipment of the Ministry of Education, Chang'an University, Xi'an 710064, China.

Materials (Basel, Switzerland)
|November 9, 2024
PubMed
Summary

This study introduces a multi-scale fatigue crack growth model to predict metal fatigue behavior. The model accurately forecasts crack growth rates and fatigue life, aligning well with experimental data for both short and long cracks.

Keywords:
Gaussian distribution theorymaterial propertiesmulti-scale modelphysically short cracktransition criterion

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Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Fracture Mechanics

Background:

  • Fatigue behavior in metals is complex, influenced by defects, material properties, and loading conditions.
  • Understanding fatigue crack initiation and propagation is crucial for structural integrity and component lifespan.
  • Existing models often struggle to accurately capture the transition from physically short cracks (PSCs) to long cracks (LCs).

Purpose of the Study:

  • To develop and validate a novel multi-scale fatigue crack growth model.
  • To accurately predict crack growth rates and fatigue life for metal specimens under uniaxial loading.
  • To incorporate material heterogeneity and experimental scatter into fatigue life predictions.

Main Methods:

  • Development of a multi-scale model integrating physically short crack (PSC) and long crack (LC) behavior.
  • Calculation of crack growth rates based on material properties, specimen geometry, and stress ratios.
  • Integration of Gaussian distribution theory to account for material heterogeneity and experimental errors.
  • Prediction of crack growth rates and fatigue life for specimens with varying notch geometries.

Main Results:

  • The multi-scale model successfully predicted crack growth rates and fatigue life for metal specimens.
  • Model predictions showed good agreement with experimental data from published literature for both PSC and LC stages.
  • The model effectively accounts for the influence of material properties, geometry, and loading conditions on fatigue behavior.

Conclusions:

  • The developed multi-scale fatigue crack growth model provides a robust framework for predicting metal fatigue.
  • The model's ability to integrate material heterogeneity and experimental scatter enhances its predictive accuracy.
  • This approach offers valuable insights for designing and assessing the durability of metal components in engineering applications.