A multi-region nonlinear model for fatigue life prediction of 3D woven composites under combined tension and bending fatigue

Abstract This paper develops a multi-region nonlinear model to characterize fatigue performance and predict fatigue life of three dimensional woven composites (3DWCs) under combined high and low cycle fatigue (CCF). The model introduces the HCF and LCF stress ratio threshold and fatigue damage threshold to classify fatigue damage into enhanced, fuzzy, and weakened regions. Then, it introduces fatigue life prediction approaches for different fatigue regimes. Also, a novel biaxial experimental platform, including the longitudinal tensile system, the lateral excitation system, and the dynamic signal monitoring system, is established. Based on this platform, some available test data are applied to validate the proposed model. Results indicate that the approach can obtain higher prediction accuracy than others.

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Publication Details

Journal
Research Square
Published
2026-11-05
DOI
https://doi.org/10.21203/rs.3.rs-11186517/v1
Primary Topic
Mechanical Behavior of Composites
Type
preprint
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preprint

A multi-region nonlinear model for fatigue life prediction of 3D woven composites under combined tension and bending fatigue

Shuang Qiu, Lei Zhou, Hongjian Zhang, Haitao Cui
Research Square
Mechanical Behavior of Composites
preprint

A multi-region nonlinear model for fatigue life prediction of 3D woven composites under combined tension and bending fatigue

Shuang Qiu, Lei Zhou, Hongjian Zhang, Haitao Cui
preprint en

Abstract

Abstract This paper develops a multi-region nonlinear model to characterize fatigue performance and predict fatigue life of three dimensional woven composites (3DWCs) under combined high and low cycle fatigue (CCF). The model introduces the HCF and LCF stress ratio threshold and fatigue damage threshold to classify fatigue damage into enhanced, fuzzy, and weakened regions. Then, it introduces fatigue life prediction approaches for different fatigue regimes. Also, a novel biaxial experimental platform, including the longitudinal tensile system, the lateral excitation system, and the dynamic signal monitoring system, is established. Based on this platform, some available test data are applied to validate the proposed model. Results indicate that the approach can obtain higher prediction accuracy than others.

Research Square
Nanjing University of Aeronautics and Astronautics (CN)
Mechanical Behavior of Composites
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