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Enhanced Estimation of Axial Compressive Strength for CFRP Based on Microscale Numerical Simulation and the Response
Honoka Yoshida1, Huachao Deng2, Jun Koyanagi2
1Graduate School of Science, Tokyo University of Science, 6-3-1, Niijuku Katsushika-ku, Tokyo 125-8585, Japan.
Materials (Basel, Switzerland)
|January 26, 2024
Summary
A new response surface method (RSM) efficiently predicts the compressive strength of carbon fiber reinforced plastics (CFRP). This approach significantly reduces computational costs associated with traditional simulations for material property analysis.
Area of Science:
- Materials Science
- Mechanical Engineering
- Computational Mechanics
Background:
- Compressive strength is a critical property for carbon fiber reinforced plastics (CFRP).
- Accurate prediction of compressive strength is essential for structural applications.
- Traditional methods involving shear tests and numerical simulations are computationally intensive and time-consuming.
Purpose of the Study:
- To develop a novel and computationally efficient method for predicting the axial compressive strength of CFRP.
- To utilize the response surface method (RSM) to overcome the limitations of traditional simulation approaches.
- To establish reliable prediction equations for shear properties based on microscale fracture models.
Main Methods:
- Development of a microbuckling model to predict the compressive strength of unidirectional fiber composites.
- Performing microscale shear simulations for CFRP with varying fiber and resin properties.
- Application of the response surface method (RSM) to develop prediction equations for shear properties based on simulation data.
Main Results:
- The developed response surface method (RSM) achieved a coefficient of determination higher than 94% in predicting compressive strength.
- The study confirmed the reliability and validity of the RSM-based prediction method for CFRP compressive strength.
- Key material properties influencing compressive strength were identified and ranked: fiber content, elastic modulus after resin yield, yield stress, and initial elastic modulus.
Conclusions:
- The response surface method (RSM) offers a computationally efficient alternative for predicting CFRP compressive strength.
- The established prediction equations provide a reliable tool for material property analysis without extensive simulations.
- Understanding the influence of material properties is crucial for optimizing the compressive strength of fiber-reinforced composites.
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