Transverse tensile failure mechanism analysis of carbon fiber composites based on random fiber distribution

The random distribution characteristics of fiber significantly affect the transverse mechanical behavior of composites, and the establishment of a fiber random distribution model consistent with the actual statistical laws is the basis for studying the transverse characteristics of composites. In this paper, a novel simulation method for the fiber random distribution is proposed based on the Poisson disk sampling method, which ensures that the fiber distribution satisfies the uniform random distribution law of fibers and avoids overlapping or abnormal aggregation. Based on this model, a representative volume element (RVE) finite element model is further developed for the transverse tensile behavior of unidirectional composites. The nonlinear mechanical behavior of the resin matrix is characterized by the Drucker–Prager yield criterion and the Ductile damage evolution criterion to describe its plastic deformation and progressive damage processes. The results show that the stress-strain curves obtained by the simulation method in this paper are consistent with the results in the literature, which verifies the accuracy of the model. This study provides a reliable numerical analysis framework for the prediction of transverse mechanical properties of unidirectional carbon fiber composites, and reveals the mechanism of fiber distribution and interfacial properties on the macroscopic mechanical behaviors.

Authors

Institutions

Publication Details

Journal
Journal of Reinforced Plastics and Composites
Published
2025-11-20
DOI
https://doi.org/10.1177/07316844251400794
Primary Topic
Mechanical Behavior of Composites
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Transverse tensile failure mechanism analysis of carbon fiber composites based on random fiber distribution

Zhou Sun, Lihua Zhao, Songbai Jiang, Ying Wang et al.
Journal of Reinforced Plastics and Composites
Mechanical Behavior of Composites
article

Transverse tensile failure mechanism analysis of carbon fiber composites based on random fiber distribution

Zhou Sun, Lihua Zhao, Songbai Jiang, Ying Wang, Hongru Wu
article en

Abstract

The random distribution characteristics of fiber significantly affect the transverse mechanical behavior of composites, and the establishment of a fiber random distribution model consistent with the actual statistical laws is the basis for studying the transverse characteristics of composites. In this paper, a novel simulation method for the fiber random distribution is proposed based on the Poisson disk sampling method, which ensures that the fiber distribution satisfies the uniform random distribution law of fibers and avoids overlapping or abnormal aggregation. Based on this model, a representative volume element (RVE) finite element model is further developed for the transverse tensile behavior of unidirectional composites. The nonlinear mechanical behavior of the resin matrix is characterized by the Drucker–Prager yield criterion and the Ductile damage evolution criterion to describe its plastic deformation and progressive damage processes. The results show that the stress-strain curves obtained by the simulation method in this paper are consistent with the results in the literature, which verifies the accuracy of the model. This study provides a reliable numerical analysis framework for the prediction of transverse mechanical properties of unidirectional carbon fiber composites, and reveals the mechanism of fiber distribution and interfacial properties on the macroscopic mechanical behaviors.

Journal of Reinforced Plastics and Composites
China Architecture Design & Research Group (China) (CN), Southeast University (CN)
Openalex Percentile: Top 60%
Mechanical Behavior of Composites
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.