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Surface roughness of adherends is a crucial factor in determining the performance and failure mechanism of adhesive joints. However, the research dedicated to the examination of fracture mechanism for adhesive joints influenced by surface roughness at microscale is limited. This work conducts systematic experimental and numerical investigations into the effect of microstructural roughness on the performance and fracture mechanism of multi-type adhesive single lap joints (SLJ). The adherend materials are aluminium alloy (Al) and polyphthalamide (PPA), ground into three roughness grades for the fabrication of SLJs using an epoxy adhesive. The mechanical properties of the adhesive, adherends and SLJs derived from experimental studies are utilized to calibrate the microparameters in Discrete Element Method (DEM) models for a numerical analysis. The newly developed DEM models demonstrate efficacy in predicting the performance and capturing the failure modes of multi-type SLJs realistically with distinct microroughness profiles. Finally, the influencing mechanisms of microstructural roughness on the performance of multi-type SLJs are investigated, including the microscale interfacial bonds and mechanical interlockings. The effects of microstructural roughness on the microscale failure mechanisms of multi-type SLJs are also explored and discussed, including the crack initiation, coalescence, and propagation within the adhesive and interface. • Investigate the properties and performance of SLJs through advanced experiments. • Develop DEM model to predict performance of SLJs with distinct roughness. • Develop DEM model to capture the failure mode of SLJs with distinct roughness. • Discuss the influencing mechanism of roughness on the performance of SLJs. • Discuss the effects of roughness on the microscale failure mechanism of SLJs. [ABSTRACT FROM AUTHOR]

A two dimensional particle model based on the discrete element method (DEM) is developed for micromechanical modelling of fibre reinforced polymer (FRP) composite laminae under biaxial transverse loads. Random fibre distribution within a representative volume element (RVE) is considered for the micromechanical DEM simulations. In addition to predicting the stress-strain curves of the RVEs subjected to transverse compression and transverse shear stresses against the experimental testing results and other numerical modelling results, the DEM model is also able to capture the initiation and propagation of all micro damage events. Fibre distribution is found to more significantly influence the ultimate failure of composite laminae under transverse shear, while it has much less effect on the failure under transverse compression. The failure envelope of composite laminae under biaxial transverse compression and transverse shear is predicted and compared with Hashin and Puck failure criteria, showing a reasonable agreement. The predicted failure envelope is correlated with the damage evolution and the quantitative analysis of failure events, which improves the understanding of the failure mechanisms. [ABSTRACT FROM AUTHOR]

A new approach is presented for generating random distribution of fibres in the representative volume element (RVE) of fibre reinforced composite laminates. The approach is based on discrete element method (DEM) and experimental data of fibre diameter distribution. It overcomes the jamming limit appeared in previous methods and is capable of generating high volume fractions of fibres with random distributions and any specified inter-fibre distances. Statistical analysis is then carried out on the fibre distributions generated within the RVEs, which show good agreement with experiments in all statistics analysed. The effective elastic properties of the generated RVEs are finally analysed by finite element method, which results show more reasonable agreement with the experimental results than previous methods. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel discrete element model was developed for hybrid adhesive joints. • The model can capture the transitional micromechanical response due to different adhesive thicknesses by only one-time calibration. • The adaptive transition of failure modes by different adherends and joint configurations can be simulated. • The correlation of fracture energies to adhesive thickness is well produced and presents promising results. • Robust prediction on joint behaviors with various designs can be achieved. This work developed a discrete element model to adaptively capture the transitional micromechanical response and failure mode of adhesive joints with dissimilar adherend materials and different configurations. Especially, the development of the model only requires one-time calibration. Loctite EA 9497 epoxy adhesive, aluminium (AL) and polyphthalamide (PPA) were selected to make different types of hybrid adhesive joints for the lab tests. The modelling applicability in simulating Mode I, Mode II cohesive failure and adhesive, mixed failure modes was subsequently validated with the experimental data. The validation shows that the proposed model can accurately capture the observed failure modes and joint performances. It is followed by investigating the ability to adaptively obtain the variation of fracture energies with different adhesive thicknesses. The results agree well with the current reports on the growth trend of fracture energies which see a rise till the thickness reaching 0.8 mm and subsequently decline to a plateau. Finally, key factors including the adhesive thickness, lap length were selected to perform a parametric study to investigate their influences on the failure mechanism and micromechanical response of hybrid joints. It is found that a thickness range of 0.1–0.3 mm is adequate to obtain satisfactory joint strength whilst thicker adhesive over 0.6 mm will decrease the joint strength. This is due to that a thinner adhesive layer can facilitate its cohesive fractures and thus fully use the resistance of adhesive. A range of lap length from 6 mm to 12.5 mm was found to have a higher efficiency of improving the joint strength when AL adherend was used. [ABSTRACT FROM AUTHOR]

• The sacrificial water-soluble support fixtures were made with additive manufacturing technique. • The mechanical performance of the joints with the modified features increased significantly. • The DE model could simulate the initiation and propagation of micro-cracks inside the adhesive and along the interface. • The modified bonded joints demonstrate a clear reduction in peak stress along the bond line. The research presented in this paper used an innovative method to modify the configuration of adhesively bonded joints for improved mechanical performance. Additive manufacturing was employed to produce sacrificial support structures with a water-soluble filament (Polyvinyl Alcohol). The design freedom offered by additive manufacturing makes it easy to tailor fixtures to any geometry, which can be used to accurately make the desired fillet shape at the end of the adhesive bond line. In addition to the experimental tests, the finite element method (FEM) was used to study the stress distribution along the bond line for four different modified bonded joints, whilst the discrete element method (DEM) was used to estimate the joint failure load and crack path in the adhesive bond line due to its strength in describing the initiation and progression of micro-cracks. The results show that the novel manufacturing method can produce an accurate fillet at the end of the bond line, regardless of the adhesive type. The mechanical performance of the joints with the modified features increased significantly. Furthermore, the failure load and crack path obtained from the DEM model is in close agreement with experimental and finite element (FE) results. Hence, the failure mechanism of the hybrid joints is then summarised. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel discrete element model considering micro-roughness was developed for adhesive joints. • The microscale crack initiation, coalescence and propagation of adhesive and adhesion interface can be captured. • Micro-mechanisms due to surface roughness on the micro/macroscale behaviour were found. • Key statistical features such as root mean square roughness, correlation length, skewness were discussed. Micro-roughness at adhesion surface yields significant influences on the structural behaviour of adhesive joints. Investigations into the micromechanical mechanism are extremely limited. This works developed a novel particle-based model of joints with stochastic microstructural features of roughness, which can capture refined multi-scale responses as first of this kind. Aluminium adherends with mechanical surface treatments were firstly scanned using 3D laser scanning microscope. The statistical features and reconstruction method of micro-roughness profiles were determined. Single lap shear tests on joints made of epoxy adhesive (Loctite EA 9497) and treated aluminium adherends were performed to provide testing data and observations on failure modes. The refined numerical models were subsequently developed to examine the influences of the actual micro-roughness on the micromechanical behaviors and failure mechanism. The mechanical interlocking, mitigation on crack propagation due to the irregular roughness were investigated. It is followed by introducing the reconstructed roughness of various magnitudes and further numerically examining the micromechanical responses by key stochastic parameters such as root mean square roughness and correlation length. The results indicate that the mechanical interlocking contribute more to enhancing the joint strength than the increase of adhesion area by micro-roughness. A rougher surface in either horizontal or vertical directions does not exhibit a consistent improvement of joint strength, which also depends on the threshold of roughness and the surface skewness triggering the transition of failure modes. [ABSTRACT FROM AUTHOR]

• Development of two deep neuron network models for predicting mechanical behaviours of UD FRP composite laminae. • All the data for deep learning predictive models obtained from an experimentally validated RVE based Discrete Element Method (DEM) model. • Consideration of fibre random distribution and fibre diameter in the microstructure of laminae in the development of deep learning models. • Discussion on accurate predictions for macroscopic mechanical properties and microscopic cracks of composite laminae. Fibre-reinforced polymer (FRP) composites have been widely used in different engineering sectors due to their excellent physical and mechanical properties. Therefore, fast, convenient and accurate prediction tools for both macroscopic mechanical properties and failure of the composites are highly demanded by industry and interested by academia. In this study, two back-propagation deep neural network (DNN) models are developed. The first model is a regression model for predicting macroscopic transverse mechanical properties of FRP laminae, which is based on a data set generated by Discrete Element Method (DEM) simulations of 2000 Representative Volume Element (RVE) with 200 different sets of fibre volume fractions and fibre radii. The second model, which is a classification model based on the results of 1600 DEM simulations of RVEs with a fixed 45 % fibre volume fraction and 3.3 μ m fibre radius, is developed for predicting microscopic crack patterns of the FRP laminae. The results show that the two developed DNN models are able to predict both the macroscopic transverse mechanical properties and the microscopic cracks of the RVE accurately. [ABSTRACT FROM AUTHOR]

Discrete element (DE) model has a great feasibility in modelling the microstructural behaviours of adhesive composite joints. However, it demands a sophisticated calibration process to determine microscale bond parameters, which involves massive efforts in both experimental and numerical investigations. This work developed a novel calibration strategy based on DE models and genetic expression programming (GEP) approach for predicting the behaviours of hybrid composite joints encompassing the material nonlinearity, large ductile deformation and multiple fracture modes. In the developed strategy, both the bulk and interlaminar-like properties of ductile adhesives were concerned to suit various joint configurations. GEP modelling was performed based on the datasets from virtual DE experiments. Symbolic regression models were subsequently developed to facilitate the parameters determination. A series lab tests were conducted to validate the numerical results. It shows that the calibrated DE model can adaptively simulate the featured behaviours of both the ductile adhesive and composite joints with different configurations well in most examined occasions. Therefore, it could be suggested to generalize the developed strategy in the development of other DE models for saving the massive efforts in the calibration process of microstructural parameters. [Display omitted] • A novel calibration strategy for discrete element models of ductile adhesive joints was proposed. • Machine learning method was used to facilitate the complex calibration. • The proposed strategy can save massive efforts in the calibration process of microstructural parameters. • Modelling reliability was thoroughly examined with lab tests using Teroson MS 9399 adhesive. • Robust prediction on joint behaviours with material nonlinearity and multiple fracture modes can be achieved. [ABSTRACT FROM AUTHOR]

Particle-based model has strength and flexibility in modelling the microstructures of adhesives and interface in adhesive joints. In this work, a procedure with genetic expression programming (GEP) technique to calibrate the microscale parameters of discrete element (DE) model was proposed for brittle adhesives. Two categories of adhesive properties, the bulk property of thick adhesive and interlaminar-like property of thin adhesive, were discussed. For the bulk property, three target properties of adhesives, i.e. tensile strength, peak strain, secant modulus, were set as the reproduced features. 300 sets of adjustable microscale parameters were produced to run the numerical tests and generate datasets. GEP was then employed to find regression formulas for predicting the target properties as a function of the microscale parameters. For the interlaminar-like property, fracture energies of the cohesive failure of thin adhesives were approximated. A similar procedure of combined DE modelling and GEP was performed to find the regression models to estimate the fracture energy. The developed regression formulas can cover a general range of brittle adhesives. Loctite EA 9497 adhesive was selected to perform a series of lab tests, of which the results were subsequently used to examine the applicability of the DE model with calibrated parameters. The numerical results exhibit good agreements with testing data and observation. • Machine learning based approach was developed to calibrate the microscale parameters of DE models. • The bulk and interlaminar-like properties of brittle adhesives in various joint designs were calibrated. • Symbolic regression models of concerned properties were developed. • The developed DE models were validated with lab tests using brittle epoxy Loctite EA 9497 as example. [ABSTRACT FROM AUTHOR]

This paper presents both experimental and numerical studies on bolted glass fiber reinforced polymer (GFRP) joints subjected to uniaxial tension and different thermal conditions (−20 ℃, 20 ℃ and 60 ℃). Laboratory tests are conducted to obtain strength, elastic modulus and deformation of the joints. The numerical model is developed using the discrete element method (DEM) that can predict not only the above properties of the joints, but also the failure modes with detailed meso/micro damages that are in consistent with the observations from the tests. The DEM model is also used in the parametric studies to study the influence of the end distance to bolt/hole diameter ratio and the lap width to bolt/hole diameter ratio on the mechanical properties and failure models of the joints. [ABSTRACT FROM AUTHOR]

The mechanical behaviour of unidirectional fibre-reinforced polymer composites subjected to transverse tension was studied using a two dimensional discrete element method. The Representative Volume Element (RVE) of the composite was idealised as a polymer matrix reinforced with randomly distributed parallel fibres. The matrix and fibres were constructed using disc particles bonded together using parallel bonds, while the fibre/matrix interfaces were represented by a displacement-softening model. The prevailing damage mechanisms observed from the model were interfacial debonding and matrix plastic deformation. Numerical simulations have shown that the magnitude of stress is significantly higher at the interfaces, especially in the areas with high fibre densities. Interface fracture energy, stiffness and strength all played important roles in the overall mechanical performance of the composite. It was also observed that tension cracks normally began with interfacial debonding. The merge of the interfacial and matrix micro-cracks resulted in the final catastrophic fracture. [ABSTRACT FROM AUTHOR]

Abstract: A particle discrete element method (DEM) was employed to simulate transverse cracking in laminated fiber reinforced composites. The microstructure of the laminates was modeled by a DEM model using different mechanical constitutive laws and materials parameters for different constituents, i.e. fiber, matrix and fiber/matrix interface. Rectangular, hexagonal and random fiber distributions were simulated to study the effect of fiber distribution on the transverse cracking. The initiation and dynamic propagation of transverse cracking and interfacial debonding were all captured by the DEM simulation, which showed similar patterns to those observed from experiments. The effect of fiber volume fraction was also studied for laminae with randomly distributed fibers. It was found that the distribution and volume fraction of fibers affected not only the transverse cracking path, but also the behavior of matrix plastic deformation and fiber/matrix interface yielding in the material. [ABSTRACT FROM AUTHOR]

This paper presents a numerical approach using the discrete element method to predict strength and damage propagation of plates and bolted lap joints subjected to axial tension. Tensile tests on GFRP plates and bolted joints are carried to obtained their overall stiffness and strength. A new three-dimensional discrete element model constructed by a 19-ball assembly is proposed and the relationships between the macro and the micro mechanical properties of FRP is established through calibrations using the test results. The calibrated DEM model is then used to reproduce the test results. Excellent agreements are achieved between the numerical and the experimental results in terms of not only the overall failure loads, but also the detailed failure modes, including cracking and delamination. The research shows great potential of the DEM model in predicting strength of composite materials and presenting detailed local damage and damage propagation at micro-scale, which represents a significant advantage over the conventional numerical methods, such as the finite element method. [ABSTRACT FROM AUTHOR]