Damage In Composite Laminates Research Articles

Dynamic compressive impact behavior of CFRP composite under high strain rate loading

Carbon Fiber Reinforced Plastics (CFRP) composite exhibits significant sensitivity to strain rate. In this work, authors investigated the CFRP composite’s dynamic compressive impact behavior under a high strain rate. The vacuum bagging technique was used to fabricate the composite specimens to reduce the presence of voids. Compressive mechanical behavior was examined for the CFRP composite for strain rate ranging from 1384 to 1953 s−1 using a Split Hopkinson Pressure Bar (SHPB) test setup. The experiment aims to investigate the effect of strain rate on stresses, strains, failure strengths, fracture energies, and failure of quasi-isotropic CFRP composites. Furthermore, the specimens’ strength initially increases and achieves its maximum strength, followed by a decrease in strength value. Moreover, an optical microscopic examination reveals that damage in composite laminate grows as the strain rate increases.

Drop Tests and Numerical Analyses of Composite Beams with Corrugated Web

To evaluate the energy absorption ability of composite beams with corrugated web under impact, the drop tests were conducted to demonstrate the fracture modes and obtain the load and energy history curves. Based on the drop tests, a finite element (FE) model was proposed with a weak link designed to trigger crushing, developed using Abaqus/Explicit, which integrates cohesive elements and employs the improved Hashin criterion along with the Choi–Chang criterion to accurately predict the onset and progression of delamination. The model accounts for the anisotropy and progressive damage in composite laminates. The periodic boundary conditions (PBCs) were integrated into the single-wave corrugated web beam model, the inherent limitations of which were corrected, enabling it to simulate the crushing process with the same effectiveness as the multi-wave model. As a result, the proposed model can accurately depict the progressive crushing behavior of corrugated web beams under impact loads while maintaining high computational efficiency.

Critical comparison of potential machine learning methods for lightning thermal damage assessment of composite laminates

The present study assesses the potential of using machine learning (ML) methods to predict the extent of lightning thermal damage in fiber-reinforced composite laminates using three supervised machine learning (SML) algorithms: (1) linear regression (LR), (2) decision tree (DT)-based, and (3) MLP models. These models were based on the 10 most significant factors that influence the severity of lightning damage, including three current waveform parameters, four material configurations, and three orthogonal electrical conductivities of each composite. All models demonstrated good performance with coefficient of determination (R2) values between 0.84 ~ 0.96. The multilayer perceptron (MLP) regression model trained with the lightning matrix damage dataset showed the most promising results (R2 > 0.94). Additional hyperparameter optimization was performed to improve the prediction performance of the baseline MLP model. The hyperparameter optimization (Adam optimizer, tanh activation function, and three hidden layers with 234 neurons) slightly improved the performance of the baseline MLP model by ~0.02, but achieved faster convergence. This result suggests that the baseline MLP model trained with the lightning matrix damage dataset is sufficiently accurate and robust. This paper highlights that ML-informed regression models can serve as an efficient first pass-estimator of lightning matrix damage in composite laminates, potentially reducing the amount of extremely time-consuming and expensive laboratory-scale lightning tests or streamlining the development of complex lightning damage models for future design.

Advancing structural health monitoring: Deep learning-enhanced quantitative analysis of damage in composite laminates using surface strain field

Composite materials have been widely used as critical components in aerospace applications due to their excellent performance characteristics. The real-time accurate identification and quantification of various types of damage within composite material structures pose a significant challenge. This study introduces an innovative damage detection method based on strain fields, which centrally employs deep learning techniques. Utilizing the Res-Mask R–CNN, this study accurately detects and categorizes various forms of damage within composite laminates, including open holes, subsurface holes, and delamination. Moreover, this method also enables precise localization and quantification of damaged areas. A series of experiments and simulations have validated the accuracy and robustness of the network model. Damage inversion experiments demonstrate that the area error of the damaged regions has been reduced to 7.4 %, and the positional error does not exceed 3.31 mm. In simulated scenarios, the shape context distance for complex damage contours does not exceed 0.21, indicating that the critical geometric features of the damage have been successfully preserved. This study provides an effective new approach for damage detection and real-time structural health monitoring of composite laminates.

Characterization of damage behavior and failure mechanisms of the bonded‐bolted hybrid three‐bolt joint in composite laminates

AbstractIn this paper, the mechanical properties, damage modes, and bolt load distribution of the bonded‐bolted hybrid three‐bolt joint were investigated by a combination of experiments and numerical simulations. Acoustic emission (AE) was used to monitor the tensile process of the connection in real time, and the K‐means clustering algorithm was used to realize the cluster analysis of the damage modes. A numerical simulation model of the tensile process of the joint was established using ABAQUS simulation software. The progressive damage evolution of composite laminates, and adhesive layer was characterized by using the VUMAT subroutine, the B‐K failure criterion, and cohesive element with zero thickness, respectively. The results show that four main damage modes occur in composite laminates during tension: matrix cracking, delamination, fiber pull‐out, and fiber breakage, with corresponding peak frequency ranges of (0–80 kHz), (80–210 kHz), (210–330 kHz), and (330–375 kHz), respectively. The adhesive layer between the laminates mainly exhibits peeling failure because of the secondary bending effect. In the load‐bearing process, the adhesive layer was loaded first and failed, and the bolt loading was delayed. Meanwhile, the results of bolt load distribution showed that the bolts and the adhesive layer at both ends carried greater loads.Highlights Damage modes and damage evolution of the bonded‐bolted hybrid joint in tension were analyzed by combining acoustic emission technology and numerical simulation. The simulation of delamination damage in composite laminates was carried out by inserting zero‐thickness cohesive elements into the laminates, and the delamination damage between the carbon fiber layup and the adjacent glass fiber layup was analyzed. The effect of the inclusion of the adhesive layer on the mechanical properties of the joint and the distribution of the bolt load was analyzed.

Comprehensive investigation on modelling of low-velocity impact damage response of composite laminates − Experimental correlation and assessment

Low velocity impact (LVI) experiments are performed to provide correlations with the simulation results based on numerical modeling of the intralaminar matrix damage and interlaminar delamination damage of composite laminates. The good agreement between the numerical simulation and experimental results provided validation of the numerical modeling approach. The validated numerical modeling is then used in the parametrical assessment of the influence of material properties and model- related parameters on the global LVI deformation responses and the evolution characteristics of the intralaminar and interlaminar damage. It is observed that the element deletion method is not suitable to resolve the element distortion problem induced by the progressive damage. The numerical convergence problem caused by element distortion can be resolved with appropriate selection of threshold value of the critical damage parameter without element deletion. The parametrical numerical investigations showed that the variations of material properties and parameters related to interlaminar damage exhibited significant influence on the LVI global deformation responses and progressive damage evolutions. Meanwhile, insignificant influence of the material properties related to the intralaminar damage was observed for the normal variations within material scatters.

Residual strength and failure mechanism of CF/PPS composites with delamination damage

AbstractDelamination is one form of damage in composite laminates. The effects of delamination damage locations (thickness direction of laminates) on the residual compressive strength and failure mechanism of carbon fiber/polyphenylene sulfide (CF/PPS) composites are studied by damage morphology, full‐field strain and finite element simulation. The closer the delamination is to the center of the composite, the lower the residual compressive strength. The failure mode of composites is dominated by 0° fiber fracture, which is divided into bulging, delamination propagation, and fracture. The delamination locations significantly affect the first two stages.Highlights Constructing delamination damage in composites by interlayer preset defects. Simulation and damage analysis to reveal the mechanism of compression failure. The relationship between delamination depth and damage stage is revealed.

Vibration-based damage detection method with tunable resolution for composite laminates

Composite laminates are increasingly applied in advanced engineering structures, but they are prone to be damaged in service. However, multiple defects with different sizes challenge the current damage detection methods to identify all of them without a baseline. In this paper, a baseline-free damage identification method based on vibration is developed, and a novel damage index with tunable resolution of detection is proposed based on two-dimensional continuous wavelet transform by manipulating wavelet parameters. The relationship between the smallest detectable damage size and wavelet parameters is explored quantitatively, and the effectivity and reliability of proposed method are numerically and experimentally verified to directly detect damage in composite laminates without baselines. By a comparison with other vibration-based damage detection methods, results show that the proposed method can precisely locate and visualize multi-damage with determinate resolution of detection, and can realize multi-resolution of damage detection for identifying various sizes of defects.

Detection of edge delamination in composite laminates using edge waves

Detecting near-edge damage in composite structural elements using guided wave-based techniques can be challenging, primarily due to the complexity of wave analysis arising from material anisotropy. Furthermore, scattered waves containing damage information can be contaminated by waves reflected from the edges, which makes detecting near-edge damage difficult to implement. In the literature, studies showed that in elastic materials, the edge of a structure can serve as a waveguide, enabling the existence of typical edge modes with concentrated energy at the edge. However, studies regarding edge waves in composite structures have received limited attention. This paper aims to explore the potential of detecting edge delamination damage in composite laminates using edge waves. The modal properties of edge waves in [(0/90)2]s composite laminates are investigated using the Semi-Analytical Finite Element (SAFE) method. Additionally, dispersion curves for quasi-isotropic composite laminates are calculated. Following this, numerical and experimental studies were conducted to investigate the sensitivity of edge waves in detecting edge delamination in the [(0/90)2]s composite laminates. The outcomes of this study offer physical insights into the modal properties of edge waves and confirm their effectiveness in detecting damage near the edges.

Experimental and Simulation Study on Low-velocity Impact Damage of Composite Laminates under Temperature Environment

The composite material casing of aero-engine operates in different temperature environments and is inevitably impacted by external objects during use. The resin matrix composite materials are sensitive to temperature, which leads to more complex damage propagation and failure modes of materials under temperature environment. The influence of temperature environment on low-velocity impact damage of composite materials needs to be studied. In this paper, the T300/QY8911 composite laminates were subjected to low-velocity impact test and simulation study under three different temperature environments of 20°C, 120°C, and 180°C. The impact damage detection was carried out by visual inspection and ultrasonic C-scan to analyze the influence of temperature on the damage of composite laminates. Finite element simulation analysis was also conducted on the gradual expansion process of impact damage of composite laminates under different temperature environments to predict the impact damage area of laminates. The results show that the main damage forms are matrix cracking and delamination and the temperature has a significant effect on the low-velocity impact damage of composite laminates. Under the same impact energy, the length of the back crack and the cracking damage of the matrix of the laminate decreases as the temperature increases; the impact damage area and the delamination damage of the laminate increases as the temperature increases.

A novel strategical approach to mitigate low velocity impact damage in composite laminates

AbstractThis paper describes a new interleaving methodology to improve composite laminates' low velocity impact (LVI) damage resistance. The approach relies on analyzing interlaminar stress in a conventional aircraft laminate to determine the appropriate interleaving strategy. A model was built to identify the larges interlaminar stress, and two interleaving strategies were defined, normal and shear stress. Four thin interleaving veils were used to validate strategies. Non‐ and interleaved laminates were submitted to LVI tests at 13.5, 25 and 40 (J) of energy. Despite interleaved laminates revealed an increase in thickness and resin volume fraction compared to the reference, they were limited to 10% and 7.6% on shear stress interleaved layups. Interleaved laminates also demonstrated an improved external and internal LVI damage resistance, especially when shear stress interleaving strategy was adopted, preventing external damage and mitigating internal damage up to 59%. No correlation between the veil's type and impact damage demonstrates the importance of interleaving strategies over the veil's characteristics.Highlights Simplified quasi‐static elastic Abaqus model identified the largest in‐plane normal (axial and transversal) and shear interlaminar stresses; Four thin veils were used to validate interleaving strategies adopted; All laminates were produced using the same conditions to minimize process influence on experimental tests; Under low velocity impact (LVI) tests, interleaving laminates in the largest shear stress interlaminar can prevent external damage and mitigate internal damage up to 59%, comparing to the reference; No correlation between the veils and damage demonstrates the relevance of the interleaving strategy over the veil type.

A fragile points method with a numerical-flux-based interface debonding model to simulate the delamination migration in composite laminates

Predicting damage in composite laminates is essential for a better utilization of the material, but it is challenging especially when the inter- and intra-ply damages are coupled. In this paper, a Fragile Points Method (FPM) with a numerical-flux-based interface debonding model is proposed to simulate the laminates’ damage. The FPM is a novel meshless method using the discontinuous Galerkin weak formulations and the point-based discontinuous polynomial trial functions. In this work, an orthotropic interface debonding model has been developed based on the numerical fluxes to simulate the mixed-mode inter- and intra-ply damage. For any interior interface in an FPM model, the interface damage is triggered when the damage criterion is satisfied and the interface is separated when the fracture energy is reached. Due to the discontinuous characteristics of the FPM, the inter- and intra-ply damage modes are introduced explicitly, and thus the coupling between them can be naturally captured. In this paper, the proposed FPM is verified by four benchmark examples for Mode I, Mode II and Mixed Mode delamination. Then the proposed method is applied to simulate the delamination migration, used as an example for the inter- and intra-ply damage. The FPM results show that this method is able to provide reliable prediction on the load–displacement curves as well as the damage and crack patterns, and the mechanism governing the delamination migration is also discussed based on the FPM results.

On quantifying uncertainty in lightning strike damage of composite laminates: A hybrid stochastic framework of coupled transient thermal-electrical simulations

Lightning strike damage can severely affect the thermo-mechanical performance of composite laminates. It is essential to quantify the effect of lightning strikes considering the inevitable influence of material and geometric uncertainties for ensuring the operational safety of aircraft. This paper presents an efficient support vector machine (SVM)-based surrogate approach coupled with computationally intensive transient thermal-electrical finite element simulations to quantify the uncertainty in lightning strike damage. The uncertainty in epoxy matrix thermal damage and electrical responses of unprotected carbon/epoxy composite laminates is probabilistically quantified considering the stochasticity in temperature-dependent multi-physical material properties and ply orientations. Further, the SVM models are exploited for variance-based global sensitivity analysis to investigate the input parameters' relative influence on the lightning strike-induced damage behavior. Due to the adoption of a coupled SVM-based simulation approach here, it has become possible to carry out a comprehensive uncertainty quantification leading to complete probabilistic descriptions of the electrical and lightning damage parameters despite the requirement of performing a large number of computationally intensive function evaluations. The results reveal that source-uncertainty of the unprotected laminates significantly influences the epoxy matrix decomposition, electrical current density and electric potential, wherein longitudinal electrical conductivity is most sensitive to stochastic variations followed by other electrical, thermal and geometric parameters.

Multi-fidelity machine learning based uncertainty quantification of progressive damage in composite laminates through optimal data fusion

Recently machine learning (ML) based approaches have gained significant attention in dealing with computationally intensive analyses such as uncertainty quantification of composite laminates. However, high-fidelity ML model construction is computationally demanding for such high-dimensional problems due to the required large amount of high-fidelity training data. We propose to address this issue effectively through multi-fidelity ML based surrogates which can use a training dataset consisting of optimally distributed high- and low-fidelity simulations. For forming multi-fidelity surrogates of progressive damage in composite laminates, we combine low-fidelity finite element analysis data obtained using Matzenmiller damage model with Hasin failure criteria and high-fidelity finite element analysis data obtained using three-dimensional continuum damage mechanics based model with P Linde’s failure criteria. It is shown that there is a significant computational advantage to using the multi-fidelity surrogate approach as compared to conventional single-fidelity surrogates. Such computational advantage through optimal data fusion without compromising accuracy becomes crucial for the subsequent data-driven uncertainty quantification and sensitivity analysis of composites involving thousands of realizations. Ply orientations come out to be the most sensitive parameters to matrix damage, fibre damage and reaction force in composite laminates. The degree of uncertainty in the output quantities depend on the input-level stochastic variations. For example, a combined stochastic variation of ±10% in material properties and ±10° in ply orientations lead to 1.85%, 16.98% and 11.24% coefficient of variation in the matrix damage, fibre damage and reaction force respectively. In general, the numerical results obtained based on the efficient data-driven approach strongly suggest that source-uncertainty of composites significantly influences the progressive damage evolution and global mechanical behaviour, leading to the realization of the importance of adopting an inclusive analysis framework considering such inevitable random variabilities.

Bayesian parameter estimation for the inclusion of uncertainty in progressive damage simulation of composites

Despite gradual progress over the past decades, the simulation of progressive damage in composite laminates remains a challenging task, in part due to inherent uncertainties of material properties. This paper combines three computational methods — finite element analysis (FEA), machine learning and Markov Chain Monte Carlo — to estimate the probability density of FEA input parameters while accounting for the variation of mechanical properties. First, 15,000 FEA simulations of open-hole tension tests are carried out with randomly varying input parameters by applying continuum damage mechanics material models. This synthetically-generated data is then used to train and validate a neural network consisting of five hidden layers and 32 nodes per layer to develop a highly efficient surrogate model. With this surrogate model and the incorporation of statistical test data from experiments, the application of Markov Chain Monte Carlo algorithms enables Bayesian parameter estimation to learn the probability density of input parameters for the simulation of progressive damage evolution in fibre reinforced composites. This methodology is validated against various open-hole tension test geometries enabling the determination of virtual design allowables.

Towards assessment of fatigue damage in composite laminates using thermoelastic stress analysis

A new approach that utilizes Thermoelastic Stress Analysis (TSA) is proposed to investigate fatigue-induced material degradation in laminated fiber-reinforced polymer composites (FRP). The proposed model accounts for non-adiabatic conditions, the effects of the material temperature on the material properties, and the effects of stiffness material degradation due to damage. Experimental data from the literature is used to validate the part of the model that simulates the heat transfer, which results in a non-adiabatic contribution to the thermoelastic response. Specimens made from E-glass FRP representative of those used in wind turbine blade manufacture are used in the study, which make a challenging proposition for TSA. The evolution of tunneling cracks caused by cyclic loading causes stiffness degradation and changes in the thermoelastic response. The added features of the proposed model are shown to be necessary to interpret the thermoelastic response. The model improves correspondence with experimental data compared to previous TSA methods. Hence a generalized framework is proposed for incorporating the mechanisms that affect the thermoelastic response as materials degrade due to fatigue loading.

Quantitative monitoring of impact damage to composite structures using blade coated MXene sensors

Low velocity impacts usually cause invisible damage of composite structure，which is hard to be found and will cause catastrophic failure. In this work, the blade-coated MXene sensor was used to monitor impact damage of composite laminates. For the purpose of impact monitoring, an experiment was designed where composite laminates were subjected to controlled energy impacts. A circular sensor with a diameter of 100 mm was arranged on the back of the laminate. And ultrasonic C-scan was used to examine delamination damage of laminates after each impact. The experimental results show that the sensor identifies the onset of impact and the generation of damage. And the relative resistance changes of the sensor have a directly linear proportional relationship to the delamination size. There is also a functional relationship between the electrical response of the sensor and the impact energy. The findings are of great significance for the application of composite structure, and can effectively avoid the safety hazards caused by invisible impact delamination damage.

Cumulative Fatigue Damage of Composite Laminates: Engineering Rule and Life Prediction Aspect.

The analysis of cumulative fatigue damage is an important factor in predicting the life of composite elements and structures that are exposed to field load histories. A method for predicting the fatigue life of composite laminates under varying loads is suggested in this paper. A new theory of cumulative fatigue damage is introduced grounded on the Continuum Damage Mechanics approach that links the damage rate to cyclic loading through the damage function. A new damage function is examined with respect to hyperbolic isodamage curves and remaining life characteristics. The nonlinear damage accumulation rule that is presented in this study utilizes only one material property and overcomes the limitations of other rules while maintaining implementation simplicity. The benefits of the proposed model and its correlation with other relevant techniques are demonstrated, and a broad range of independent fatigue data from the literature is used for comparison to investigate its performance and validate its reliability.

A Bond-Based Peridynamic Model with Matrix Plasticity for Impact Damage Analysis of Composite Materials

The prediction of damage and failure to fiber-reinforced polymer composites in extreme environments, particularly when subjected to impact loading, is a crucial issue for the application and design of protective structures. In this paper, based on the prototype microelastic brittle (PMB) model and the LaRC05 composite materials failure model, we proposed a bond-based peridynamic (BB-PD) model with the introduction of plastic hardening of the resin matrix for fiber-reinforced polymer composites. The PD constitutive relationships of the matrix bond and interlayer bond under compressive loading are considered to include two stages of linear elasticity and plastic hardening, according to the stress-strain relationship of the resin matrix in the LaRC05 failure model. The proposed PD model is employed to simulate the damage behaviors of laminated composites subjected to impact loading. The corresponding ballistic impact tests of composite laminates were carried out to observe their damage behaviors. The PD prediction results are in good agreement with the ballistic experimental results, which can verify the correctness and accuracy of the PD model developed in this study in describing the impact damage behaviors of composite materials. In addition, the characteristics and degree of damage in composite laminates are analyzed and discussed based on this PD model. The difference in the impact resistance of composite laminates with different stacking sequences is also studied using the numerical simulation results.

Microscale modelling of lightning damage in fibre-reinforced composites

In this work, three-dimensional (3D) finite element simulations were undertaken to study the effects of lightning strikes on the microscale behaviour of continuous fibre-reinforced composite materials and to predict and understand complex lightning damage mechanisms. This approach is different from the conventional mesoscale or macroscale level of analysis, that predicts the overall lightning damage in composite laminates, thus providing better understanding of lightning-induced thermo-mechanical damage at a fundamental level. Micromechanical representative volume element (RVE) models of a UD composite laminate were created with circular carbon fibres randomly distributed in an epoxy matrix. The effects of various grounding conditions (one-, two-, and four-side grounding), fibre volume fractions ( V f = 55, 60%, and 65%), and peak current amplitudes (10, 20, and 40 kA) on microscopic damage in RVE models were characterised to understand fibre, epoxy matrix, and fibre-matrix interfacial damage associated with a lightning strike. Thermal damage, estimated based on epoxy matrix decomposition temperature, was largely constant up to 20 kA before increasing significantly at 40 kA. Severe thermal damage steadily decreased with increasing V f. Thermo-mechanical damage was predicted using a ductile plasticity model with Drucker–Prager yield criterion for epoxy matrix failure, and cohesive surfaces for fibre-matrix interface debonding. Thermal strain had the largest contribution to thermo-mechanical damage, while dynamic pressure loading was negligible in all RVE models. The RVE model proposed in this work, to the best of the authors’ knowledge, is the first model predicting lightning-induced fibre-matrix interfacial damage.