Effect of notch length and pre-crack size on mode II fracture energy of brittle adhesives

Ayatollahi, M.R.; Ajdani, Arsalan; Akhavan‐Safar, A.; Silva, Lucas F. M. da

doi:10.1016/j.engfracmech.2019.03.024

Cited by 32 publications

(11 citation statements)

References 18 publications

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“…Reliability, lower stress concentrations, costeffectiveness, and higher strength to weight ratio are some of the benefits provided by the adhesive joining technique. [1][2][3][4] With regard to their extensive applications, characterizing the properties and predicting the failure and damage mechanisms of adhesively bonded joints are important concerns. 5 In continuum mechanics, structures and materials are assumed to be continuous.…”

Section: Introductionmentioning

confidence: 99%

“…Since these assumptions are not true for adhesive bonding, fracture mechanics is often applied to adhesive bonding which uses the fracture toughness (G) and the critical strain energy release rate (SERR) of the material to predict failure of the joints. 4 Hence, various failure approaches based on strain, stress, or energy have been proposed. 6 Over the last decades, many researchers have analyzed the mode I fracture toughness (G Ic ) of adhesives both numerically and experimentally and have proposed several failure prediction criteria corresponding to various joint geometries and material properties.…”

Section: Introductionmentioning

confidence: 99%

“…6 Over the last decades, many researchers have analyzed the mode I fracture toughness (G Ic ) of adhesives both numerically and experimentally and have proposed several failure prediction criteria corresponding to various joint geometries and material properties. 4,7 Cohesive zone modeling (CZM) as a well-accepted analysis method is widely used for the failure assessment of joints, relying on adhesives G Ic. 8 Nonetheless, the structure geometry and post-elastic behavior of materials have a significant impact on the CZM law shape and consequently, strength predictions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fracture energy assessment of adhesives – Part I: Is G_IC an adhesive property? A neural network analysis

Akhavan‐Safar

Beygi

Delzendehrooy

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part L:

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Different joint types and geometries have been considered to measure the fracture toughness ( Gc) of adhesives. However, results show that, sometimes, the obtained Gc values for the same adhesives are not similar in different reports. Several factors including the joints geometry, material properties of the substrate, and also the test conditions influence the obtained results. This study is conducted to find a logical connection between these factors and to find their influences on the obtained mode I fracture toughness ( GIc) to understand which parameters are the most influential and which ones are less significant. To this aim, 115 values of different GIcalready reported in the literature were collected and examined regarding the geometrical and material parameters. To find the rational relationship between the effective parameters and the reported GIcvalues, a method based on the artificial neural network technique was employed. The results revealed that whilst the fracture energy of aluminum adhesive joints is more influenced by geometrical parameters including the joint type and substrate thickness, the steel adhesive joints are more sensitive to the adhesive properties and bondline thickness. With this study, it is possible to design an optimum test by minimizing the effects of variables that cause errors in obtaining fracture toughness and also to estimate GIc of adhesives by using the developed model. On the other hand, it is also possible to design real structures in which the fracture toughness of the adhesive reaches its maximum value.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fracture energy assessment of adhesives – Part I: Is G_IC an adhesive property? A neural network analysis

Akhavan‐Safar

Beygi

Delzendehrooy

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part L:

View full text Add to dashboard Cite

show abstract

“…9 Fracture mechanics-based methods have been experimentally and numerically considered by several authors. [10][11][12][13][14][15][16][17][18] In these works, the influence of different geometrical and loading parameters has been analysed on fatigue crack growth of adhesive materials. Ajdani et al 15 presented a new test method to measure the fracture energy of brittle and semibrittle adhesive joints subjected to mixed mode loading conditions.…”

Section: Introductionmentioning

confidence: 99%

“…This approach provided better estimation, up to 20%, when compared to common data reduction methods. Ayatollahi et al 18 investigated the effect of notch length and precrack size on the fracture energy of brittle adhesives under mode II loading conditions. It was shown that ENF tests with inappropriate notch size and precrack lengths lead to a mixed mode condition, which significantly affects the measurement of the fracture energy.…”

Section: Introductionmentioning

confidence: 99%

The influence of mode mixity and adhesive system on the fatigue life of adhesive joints

Sousa

Akhavan‐Safar

Goyal³

et al. 2020

Fatigue Fract Eng Mat Struct

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In real applications, adhesive joints are commonly subjected to fatigue and mixed mode loading conditions. The aim of the current work is to experimentally analyse the influence of mode mixity on the fatigue strength of joints with an epoxy‐based adhesive. Different adhesive systems (acrylic and epoxies) were considered for pure mode I fatigue loading conditions. To achieve this, Arcan joints with an epoxy adhesive were manufactured and tested at different mode mixities. Based on stiffness degradation, monitored during the tests, damage evolution was calculated for different loading conditions and for all the tested adhesives. Finally, fatigue envelopes were constructed for different fatigue life regimes. Results show that a shear loading component reduces both the static strength and fatigue life of the joints. A small reduction rate of the stiffness was found throughout the most part of the life until a sudden drop was observed, indicating a smooth damage evolution.

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Reinforcement and toughening of the self‐piercing riveted bonded joints induced by the pre‐embedded adhesive in rivet cavities

Liu,

Xue,

Guo

et al. 2024

Polymer Composites

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Self‐piercing riveted bonded (SPRB) joints are widely used in body‐in‐white (BIW) to connect dissimilar materials owing to their high fatigue and electrochemical performance. However, the strength of the SPRB joint has been found to be inferior to that of self‐piercing riveted (SPR) joints, owing to the reduction in undercut induced by the introduction of an adhesive, especially under pull‐out loading conditions. Interestingly, the mechanical strength improved when the rivet cavity was pre‐embedded with an adhesive. Before the riveting process, the rivet cavities in SPRB joints were pre‐embedded with 0.01, 0.02, and 0.03 mL of adhesive, namely them PSPRB‐V1–V3, respectively. Finite element (FE) models of SPRB and PSPRB joints were developed to analyze their formability and mechanical properties. The simulated and experimental results showed that the hydraulic pressure in the rivet cavity increased as the pre‐embedded adhesive volume in the rivet cavity increased during the riveting process, which further improved the undercut, microhardness, effective bearing area, and mechanical properties of joints. Among the prepared PSPRB joints, the PSPRB‐V3 joint exhibited the best undercut and optimal mechanical properties. Specifically, its undercut and peak force increased by 16.43% and 12.87% compared with those of SPRB joints. These findings provide important guidance for designing steel‐aluminum SPRB joints that require high‐bearing capabilities.Highlights The effect of pre‐embedded adhesive on the SPRB joint cross‐section was studied. Failure mechanisms of the SPRB and PSPRB joints were investigated via FEM. The better PSPRB joint performance over SPRB joints was elucidated. The stress–strain history was considered in the FE model of the joint failure process. Strengthening mechanism of pre‐embedded adhesive in the rivet cavity was discussed.

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Effect of notch length and pre-crack size on mode II fracture energy of brittle adhesives

Cited by 32 publications

References 18 publications

Fracture energy assessment of adhesives – Part I: Is G_IC an adhesive property? A neural network analysis

Fracture energy assessment of adhesives – Part I: Is G_IC an adhesive property? A neural network analysis

The influence of mode mixity and adhesive system on the fatigue life of adhesive joints

Reinforcement and toughening of the self‐piercing riveted bonded joints induced by the pre‐embedded adhesive in rivet cavities

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Effect of notch length and pre-crack size on mode II fracture energy of brittle adhesives

Cited by 32 publications

References 18 publications

Fracture energy assessment of adhesives – Part I: Is GIC an adhesive property? A neural network analysis

Fracture energy assessment of adhesives – Part I: Is GIC an adhesive property? A neural network analysis

The influence of mode mixity and adhesive system on the fatigue life of adhesive joints

Reinforcement and toughening of the self‐piercing riveted bonded joints induced by the pre‐embedded adhesive in rivet cavities

Contact Info

Product

Resources

About

Fracture energy assessment of adhesives – Part I: Is G_IC an adhesive property? A neural network analysis

Fracture energy assessment of adhesives – Part I: Is G_IC an adhesive property? A neural network analysis