Finite element modeling of mode I fatigue delamination growth in composites under large-scale fiber bridging

Teimouri, Farhad; Heidari-Rarani, M.; Aboutalebi, Farhad Haji

doi:10.1016/j.compstruct.2021.113716

Cited by 27 publications

(17 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The delamination damage test was performed according to mode I of the ASTM D5528-13 [60] standard. In this mode, delamination may include a large amount of fiber bridging [61]. According to the standard ASTM-D5528-13, a polytetrafluoroethylene (PTFE) film (55 mm × 25 mm × 40 µm) was inserted between layers 12 and 13 on the specimen to create initial delamination cracks.…”

Section: Materials Preparation and Test Proceduresmentioning

confidence: 99%

Deep Learning Approach for Damage Classification Based on Acoustic Emission Data in Composite Materials

Fu-ping

Jiang

et al. 2022

Materials

View full text Add to dashboard Cite

Damage detection and the classification of carbon fiber-reinforced composites using non-destructive testing (NDT) techniques are of great importance. This paper applies an acoustic emission (AE) technique to obtain AE data from three tensile damage tests determining fiber breakage, matrix cracking, and delamination. This article proposes a deep learning approach that combines a state-of-the-art deep learning technique for time series classification: the InceptionTime model with acoustic emission data for damage classification in composite materials. Raw AE time series and frequency-domain sequence data are used as the input for the InceptionTime network, and both obtain very high classification performances, achieving high accuracy scores of about 99%. The InceptionTime network produces better training, validation, and test accuracy with the raw AE time series data than it does with the frequency-domain sequence data. Simultaneously, the InceptionTime model network shows its potential in dealing with data imbalances.

show abstract

Section: Materials Preparation and Test Proceduresmentioning

confidence: 99%

Deep Learning Approach for Damage Classification Based on Acoustic Emission Data in Composite Materials

Fu-ping

Jiang

et al. 2022

Materials

View full text Add to dashboard Cite

show abstract

“…F. Teimouri [ 91 ] extended the Turon et al and Kawashita-Hallett’s CZM fatigue damage models with a trilinear cohesive law to simulate mode I fatigue delamination in the composites undergoing large-scale fibre bridging. To simulate 3D DCB specimen behaviour under high loading cycles, a user defined element (UEL) subroutine was applied to the Abaqus software.…”

Section: Numerical Studies On Mode I Fatigue Delaminationmentioning

confidence: 99%

Mode I Fatigue of Fibre Reinforced Polymeric Composites: A Review

et al. 2022

View full text Add to dashboard Cite

Composites are macroscopic combinations of chemically dissimilar materials preferred for new high-tech applications where mechanical performance is an area of interest. Mechanical apprehensions chiefly include tensile, creep, and fatigue loadings; each loading comprises different modes. Fatigue is cyclic loading correlated with stress amplitude and the number of cycles while defining the performance of a material. Composite materials are subject to various modes of fatigue loading during service life. Such loadings cause micro invisible to severe visible damage affecting the material’s performance. Mode I fatigue crack propagates via opening lamina governing a visible tear. Recently, there has been an increasing concern about finding new ways to reduce delamination failure, a life-reducing aspect of composites. This review focuses on mode I fatigue behaviours of various preforms and factors determining failures considering different reinforcements with respect to fibres and matrix failures. Numerical modelling methods for life prediction of composites while subjected to fatigue loading are reviewed. Testing techniques used to verify the fatigue performance of composite under mode I load are also given. Approaches for composites’ life enhancement against mode I fatigue loading have also been summarized, which could aid in developing a well-rounded understanding of mode I fatigue behaviours of composites and thus help engineers to design composites with higher interlaminar strength.

show abstract

“…In order to analyze the experimental and simulation results, it is necessary to use R-curves to analyze the influence of bridging and other influencing factors on delamination. 44,45 ASTM D5528 36 suggests a variety of methods for calculating G I during delamination, and this article uses modified beam theory (MBT) based on the characteristics of this specimen. Assuming that under the influence of factors such as bridging, the effect of delamination can be equivalent to the ideal delamination with distance a þ Δ 1 , (a is the actual delamination distance observed in experiments or simulations).…”

Section: > > > > <mentioning

confidence: 99%

Theoretical and numerical investigation of mode‐I delamination of composite double‐cantilever beam with partially reinforced arms

Pan

Jiang

et al. 2021

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

In this paper, a theoretical analysis model and two simulation methods are applied to characterize the quasi-static and fatigue delamination of composite double-cantilever beam (DCB) with partially reinforced arms. The test data of partially reinforced DCB were used as benchmark to verify the analysis model and simulation, and cohesive zone models (CZMs) and virtual crack closure technique (VCCT) are used in simulation. It is shown that the partially reinforced DCB has a unique double-peak load-displacement relationship, rising and sudden release of R-curve near the reinforced area, and produces instability development. By comparing the results of simulation and experiment, the simulation based on the exponential CZM can calculate the delamination of partially reinforced DCB under both quasi-static and fatigue loading, while VCCT method will generate a straight delamination front edge under the reinforced area and underestimates the influence of the previous load on the later due to the lost of microdamage from previous loading.

show abstract

Finite element modeling of mode I fatigue delamination growth in composites under large-scale fiber bridging

Cited by 27 publications

References 54 publications

Deep Learning Approach for Damage Classification Based on Acoustic Emission Data in Composite Materials

Deep Learning Approach for Damage Classification Based on Acoustic Emission Data in Composite Materials

Mode I Fatigue of Fibre Reinforced Polymeric Composites: A Review

Theoretical and numerical investigation of mode‐I delamination of composite double‐cantilever beam with partially reinforced arms

Contact Info

Product

Resources

About