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Characterization and Model Validation for Large Format Chopped Fiber, Foamed, Composite Structures Made from Recycled
Daniel P Pulipati1, David A Jack1
1Department of Mechanical Engineering, Baylor University, Waco, TX 76706, USA.
Polymers
|June 24, 2020
Summary
This study predicts composite material performance using constitutive properties. A non-linear Finite Element Analysis model accurately predicted structural timber behavior, closely matching experimental results.
Area of Science:
- Materials Science
- Composite Materials
- Polymer Engineering
Background:
- Large format foamed core composite structures, like crossties, are made from recycled High-Density Polyethylene (HDPE) and Glass Filled Polypropylene (GFPP).
- Predicting performance is challenging due to microstructural variations affecting macroscopic responses.
- Structures feature a dense outer shell and a closed-cell foamed core.
Purpose of the Study:
- To predict the material performance of foamed core composite structures using only constitutive properties.
- To establish a mathematical correlation between microstructural variations and macroscopic responses.
- To validate micromechanics and Finite Element Analysis (FEA) models against experimental data.
Main Methods:
- Micromechanics models analyzed non-linear shell and foamed core properties.
- Modified Rule of Mixtures predicted reference stress for shell and core.
- FEA models, initially linear then non-linear (Ramberg-Osgood), simulated four-point bend tests.
Main Results:
- Linear analysis showed no deflection variation for isotropic/transversely isotropic models.
- Non-linear FEA model predicted full four-point bend test behavior.
- FEA model results deviated by 2.45 kN, compared to experimental variation of 3.58 kN.
Conclusions:
- The non-linear FEA model effectively predicts the behavior of foamed core composite structures.
- Constitutive properties can be used to accurately forecast material performance.
- The study validates the use of micromechanics and FEA for recycled composite material analysis.
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