Modeling and application of temperature-dependent elastic constants in continuous fiber-reinforced shape memory polymer composites

The mechanical properties of continuous fiber-reinforced shape memory polymer composites (SMPCs) exhibit a pronounced temperature dependence. However, exiting models for elastic constants are not specifically developed for SMPCs. In this study, analytical models based on a revised Eshelby’s inclusion theory are developed to predict the temperature-dependent longitudinal, transverse, and flexural moduli of SMPCs. Experimental data from the literature, covering SMPCs with various fiber volume fractions (4.32%, 6.36% and 12.97%), are used to validate the proposed models. Validation results show high predictive accuracy for flexural modulus across all fiber content systems, while predictions for longitudinal and transverse moduli exhibit limitations at the high fiber contents (12.97%). To overcome these constraints, a refined Rule of Mixtures for longitudinal modulus and a revised Chamis model for transverse modulus are introduced. Further numerical investigations on several classic micromechanical models reveal that the revised Chamis formulation effectively captures the temperature-dependent evolution of shear modulus. Furthermore, by incorporating the concept of storage strain, these analytical models are implemented into the commercial finite element software ABAQUS via the UMAT subroutine, enabling finite element simulation of SMPC shape memory cycles. The recovery stress under different constraining strain is also numerically investigated. Overall, the results demonstrate the developed model’s capability to predict the temperature-dependent elastic constants and shape memory behavior of SMPCs. This framework bridges critical gaps between micromechanical theory and macroscale SMPC performance, providing a robust tool for multi-physics-coupled smart structure design. • An analytical framework is developed to predict the temperature-dependent elastic constants of SMPCs. • A revised Eshelby model is developed for accurate prediction of the flexural modulus. • A refined RoM model is introduced for the longitudinal modulus. • A modified Chamis model is formulated to characterize the temperature evolution of the transverse and shear moduli. • The analytical models are implemented in ABAQUS to simulate shape memory cycles of SMPCs.

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Publication Details

Journal
Polymer Testing
Published
2025-06-11
DOI
https://doi.org/10.1016/j.polymertesting.2025.108882
Citations
4
Primary Topic
Polymer composites and self-healing
Type
article
Field-Weighted Citation Impact
2.43

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article

Modeling and application of temperature-dependent elastic constants in continuous fiber-reinforced shape memory polymer composites

Xiongqi Peng, Penghui Zhu, Qinghu Wang, Jiajun Chen et al.
4 citations
Polymer Testing
Polymer composites and self-healing
2.43
article

Modeling and application of temperature-dependent elastic constants in continuous fiber-reinforced shape memory polymer composites

Xiongqi Peng, Penghui Zhu, Qinghu Wang, Jiajun Chen, Chen Du, Wenwu Zhang
article en
4 citations

Abstract

The mechanical properties of continuous fiber-reinforced shape memory polymer composites (SMPCs) exhibit a pronounced temperature dependence. However, exiting models for elastic constants are not specifically developed for SMPCs. In this study, analytical models based on a revised Eshelby’s inclusion theory are developed to predict the temperature-dependent longitudinal, transverse, and flexural moduli of SMPCs. Experimental data from the literature, covering SMPCs with various fiber volume fractions (4.32%, 6.36% and 12.97%), are used to validate the proposed models. Validation results show high predictive accuracy for flexural modulus across all fiber content systems, while predictions for longitudinal and transverse moduli exhibit limitations at the high fiber contents (12.97%). To overcome these constraints, a refined Rule of Mixtures for longitudinal modulus and a revised Chamis model for transverse modulus are introduced. Further numerical investigations on several classic micromechanical models reveal that the revised Chamis formulation effectively captures the temperature-dependent evolution of shear modulus. Furthermore, by incorporating the concept of storage strain, these analytical models are implemented into the commercial finite element software ABAQUS via the UMAT subroutine, enabling finite element simulation of SMPC shape memory cycles. The recovery stress under different constraining strain is also numerically investigated. Overall, the results demonstrate the developed model’s capability to predict the temperature-dependent elastic constants and shape memory behavior of SMPCs. This framework bridges critical gaps between micromechanical theory and macroscale SMPC performance, providing a robust tool for multi-physics-coupled smart structure design. • An analytical framework is developed to predict the temperature-dependent elastic constants of SMPCs. • A revised Eshelby model is developed for accurate prediction of the flexural modulus. • A refined RoM model is introduced for the longitudinal modulus. • A modified Chamis model is formulated to characterize the temperature evolution of the transverse and shear moduli. • The analytical models are implemented in ABAQUS to simulate shape memory cycles of SMPCs.

Polymer TestingVol. 150
Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 12%
Polymer composites and self-healing
2.43
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