Computational Model of Shoe Wear Progression: Comparison with Experimental Results
Seyed Reza M Moghaddam1, Sarah L Hemler1, Mark S Redfern1
1Department of Bioengineering, University of Pittsburgh, Benedum Engineering Hall 302, 3700 O'Hara St., Pittsburgh, PA 15261.
Wear : an International Journal on the Science and Technology of Friction Lubrication and Wear
|May 18, 2023
Summary
Predicting shoe wear is crucial for preventing slip and fall accidents. This study developed a computational model that accurately simulates footwear outsole wear progression, correlating well with experimental data.
Area of Science:
- Biomechanics
- Materials Science
- Computational Modeling
Background:
- Worn footwear increases slip and fall accident risks.
- Limited research exists on predicting footwear wear progression.
- Understanding wear patterns is key for safety and design.
Purpose of the Study:
- To present a computational modeling framework for simulating footwear outsole wear.
- To compare model predictions with experimental wear data.
- To assess the model's ability to predict wear order and size.
Main Methods:
- Utilized finite element analysis (FEA) and Archard's wear equation.
- Developed a computational model for footwear outsole wear simulation.
- Compared model results with experimental data from accelerated wear tests.
Main Results:
- Strong correlation (r_s > 0.74, p < 0.005) between predicted and experimental tread block wear order.
- Model's accuracy in predicting worn region size varied by shoe design.
- Demonstrated the model's capability for realistic wear progression prediction.
Conclusions:
- The computational modeling framework provides realistic predictions of shoe wear.
- This model is a significant step towards guiding footwear replacement and design.
- Future models could enhance slip resistance and durability through informed design.
