Composite Laminate Structures Research Articles

Parametric Analysis of Critical Buckling in Composite Laminate Structures under Mechanical and Thermal Loads: A Finite Element and Machine Learning Approach.

This research focuses on investigating the buckling strength of thin-walled composite structures featuring various shapes of holes, laminates, and composite materials. A parametric study is conducted to optimize and identify the most suitable combination of material and structural parameters, ensuring the resilience of structure under both mechanical and thermal loads. Initially, a numerical approach employing the finite element method is used to design the C-section thin-walled composite structure. Later, various structural and material parameters like spacing ratio, opening ratio, hole shape, fiber orientation, and laminate sequence are systematically varied. Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. Various ML techniques such as linear regression, lasso regression, decision tree, random forest, and gradient boosting are employed to assess their accuracy in comparison with finite element results. As a result, the simulation model showcases the variation in critical buckling load when altering the structural and material properties. Additionally, the machine learning models successfully predict the optimal critical buckling load under mechanical and thermal loading conditions. In summary, this paper delves into the study of the stability of C-section thin-walled composite structures with holes under mechanical and thermal loading conditions using finite element analysis and machine learning studies.

Prediction of Residual Compressive Strength after Impact Based on Acoustic Emission Characteristic Parameters.

This study proposes a prediction method for residual compressive strength after impact based on the extreme gradient boosting model, focusing on composite laminates as the studied material system. Acoustic emission tests were conducted under controlled temperature and humidity conditions to collect characteristic parameters, establishing a mapping relationship between these parameters and residual compressive strength under small sample conditions. The model accurately predicted the residual compressive strength of the laminates after impact, with the coefficient of determination and root mean square error for the test set being 0.9910 and 2.9174, respectively. A comparison of the performance of the artificial neural network model and the extreme gradient boosting model shows that, in the case of small data volumes, the extreme gradient boosting model exhibits superior accuracy and robustness compared to the artificial neural network. Furthermore, the sensitivity of acoustic emission characteristic parameters is analyzed using the SHAP method, revealing that indicators such as peak amplitude, ring count, energy, and peak frequency significantly impact the prediction results of residual compressive strength. The machine-learning-based method for assessing the damage tolerance of composite laminates proposed in this paper utilizes the global monitoring advantages of acoustic emission technology to rapidly predict the residual compressive strength after the impact of composite laminates, providing a theoretical approach for online structural health monitoring of composite laminates. This method is applicable to various composite laminate structures under different impact conditions, demonstrating its broad applicability and reliability.

Multi-material and thickness optimization of a wind turbine blade root section

Structural optimization has been shown to be an invaluable tool for solving large-scale challenging design problems, and this work concerns such optimization of a state-of-the-art laminated composite wind turbine blade root section. For laminated composites structures, the key design parameters are material choice, fiber orientation, stacking sequence, and layer thickness, however a framework for treating these simultaneously in optimization, on the current wind turbine blade scale, has not been demonstrated. Thus, the motivation and novelty of the present work is providing and demonstrating a general gradient-based approach applicable to wind turbine blades, where the key design parameters and structural criteria, i.e., buckling, static strength, and fatigue damage, are considered for multiple design load cases. The optimization framework is based on a variation of the Discrete Material and Thickness Optimization approach, where the thickness is directly parametrized, allowing for appropriately treating the sandwich parts of the blade. It is demonstrated how optimization leads to a design consisting of complex variable-thickness laminates, a good overall distribution of the structural criteria in the model, and a significant reduction in mass compared to the initial design.

A geometrically nonlinear Hellinger–Reissner shell element for the postbuckling analysis of variable stiffness composite laminate structures

Variable stiffness (VS) composite laminates provide larger freedom to design thin-walled structures than constant stiffness (CS) composite laminates. They showed to allow the redistributing of stresses, improving buckling and post-buckling performance and, therefore, reducing material weight and costs. This work extends a recently developed mixed shell element, MISS-4C, to the postbuckling analysis of VS composite laminate structures. MISS-4C has a linear elastic closed-form solution for the stress interpolation of symmetric composite materials. Its stress field interpolation is obtained by the minimum number of parameters, making it an isostatic element. Moreover, its kinematic is only assumed along its contour, leading to an efficient evaluation of all operators obtained through analytical integration along the element contour. MISS-4C uses a corotational approach within a fast multi-modal Koiter algorithm to efficiently obtain the initial post-buckling response of VS composite laminate structures.First, the element performance is investigated by analysing a carbon fibre VS composite laminate plate subjected to compressive stresses. Numerical results obtained with MISS-4C are compared with those obtained with the MISS-4 element, showing good accuracy and a high convergence rate. Subsequently, the structural response of a glass fibre VS composite laminate girder of a short-length bridge is optimised through a multi-objective optimisation that exploits the robustness of the MISS-4C element and the efficiency of the multi-modal Koiter algorithm.

Reliability and sensitivity analysis of delamination growth of composite laminate structures using two efficient sampling methods

In recent years, composite structures have been used in a large number of applications in aerospace, machinery, marine, and civil engineering. However, there are inevitably many uncertainties in the whole life cycle of composite structures, which can easily lead to structural damage and failure. Therefore, it is important to analyze the reliability and sensitivity of composite structures. At present, most of the contributions use the first-order reliability method (FORM) and the second-order reliability method (SORM) to study the reliability of composite structures and compare them with the results of the Monte Carlo simulation. However, both methods have their limitations. FORM cannot guarantee the calculation accuracy for the highly nonlinear limit state equation, and the calculation efficiency of SORM is too low. Therefore, this paper proposes to use importance sampling (IS) and backpropagation neural network-based Monte Carlo (MC-BPNN) to study the reliability, sensitivity, and dispersion of delamination growth of composite laminates. The results show that compared with FORM and SORM, IS and MC-BPNN have higher calculation accuracy and efficiency and can more accurately evaluate the failure degree of composite structures and ensure their safe operation in the field of aerospace equipment. The universality of this method can make it being widely used in the reliability and sensitivity analysis of different composite materials as well as dispersion analysis.

Study on the failure effect of aramid reinforced concrete slab under localized blast loading

As a new material with low density, high modulus and high strength, aramid fibers and composite laminates are widely used in protective structures. Aramid reinforced concrete panels as a new type of protective combination of structures, especially in the concrete-aramid laminate composite blast-resistant structure, the optimal thickness combination of reinforced concrete and aramid laminate has not been targeted research. In this paper, three types of scaled down reinforced concrete (RC) slabs, aramid fiber reinforced concrete (AFRC) slabs and aramid fiber reinforced plastic reinforced concrete (AFRPRC) slabs were designed and fabricated to carry out experimental studies under local explosive loading and to compare the blast resistance of different slabs through damage analysis. Based on LS-DYNA software, the damage characteristics of AFRPRC plates were investigated and compared and analysed with the test results to verify the accuracy and applicability of the FEA model. Typical damage patterns of structures under different TNT charges were obtained, and empirical equations between the damage characteristics of reinforced concrete slabs (maximum mid-span displacement, crater diameter, crater depth) and TNT charges were fitted by means of magnitude analysis. The effect of the aramid layer on the structural blast resistance performance was analysed from three perspectives: maximum central displacement, stress wave attenuation rate and internal energy absorption. The results show that AFRC improves the blast resistance of reinforced concrete not significantly relative to ordinary reinforced concrete slabs, while AFRPRC slabs maintain good integrity and show better blast resistance. The best blast resistance performance of AFRPRC panels is achieved when the ratio of reinforced concrete thickness to aramid layer thickness is 50:3. The results of the study can provide theoretical basis and reference for efficient protection of composite structures.

An Eight-Node Non-Conforming Generalized Partial Hybrid Element and Its Application in Stress Analysis of Repaired Composite Laminate Structures

To ensure the overall continuity of displacement and out-of-plane stress in composite laminate structures and to quantitatively analyze the mechanical properties of composite materials after damage or repair, a finite element solution method is applied based on the modified generalized H–R variational principle. This method utilizes an eight-node non-conforming generalized partial hybrid element (NCGPME8). The partial hybrid model established with this hybrid element can accurately satisfy the out-of-plane stress boundary conditions of the structure, ensuring the continuity of out-of-plane stress. Numerical examples are used to validate that this hybrid model can effectively compute thick and thin laminate structures with high accuracy and rapid convergence of out-of-plane stress. Finally, considering the insensitivity to irregular meshes and the accuracy in calculating in-plane stress, this method is propagated by element coefficient deduction or element material replacement, then employed to analyze the in-plane and out-of-plane stress distributions of laminates with damage from stepwise grinding perforations, and laminates repaired in a stepwise fashion. Stress and displacement at different locations on the laminates are compared and analyzed, leading to a quantitative assessment of the impact of damage and repair on the stress distribution of the laminates.

Enhancing composite laminate structures with tailored neural networks

Enhancing composite laminate structures with tailored neural networks

Screen-printed piezoelectric composites for vibrational energy harvesting in combination with structural composite laminates for powering a sensing node

This paper developed smart composite structures with screen-printed piezoelectric composite energy harvesters. P(VDF-TrFE) based composites with BaTiO3 particles of different concentrations were deposited via screen printing and studied regarding surface morphology, crystalline structure, piezoelectric, dielectric and mechanical properties. It was identified that P(VDF-TrFE) with 5 wt% BaTiO3 addition exhibited the best piezoelectric property. Even with a monotonic reduction in the β phase crystallisation as the BaTiO3 concentration was increased, a 5 wt% inclusion of BaTiO3 led to the rise of d33 from −28.63 pC/N to −33.90 pC/N. This was attributed to the enhanced interfacial polarisation and the stress concentration induced by the addition of the ceramic particles. Subsequently, the printed piezoelectric composites were co-cured with glass fibre reinforced composites (GFRPs) and carbon fibre reinforced composites (CFRPs). The assembled harvesters were tested under both sinusoidal excitation and real industrial vibration. It was found that the smart composites with 5 wt% BaTiO3 always manifested the best energy harvesting performance. For the optimised generator, maximum power of 2 μW and 1.5 μW could be obtained when using GFRPs and CFRPs as substrates under 1 g peak-peak sinusoidal excitation, respectively. The harvested energy could be used to power a commercial accelerometer with the help of a power management system. When exciting the GFRP-based energy harvester with an optimised printed piezoelectric generator at 7 g p-p acceleration, the power harvested was sufficient to maintain the operation of the accelerometer for 0.34 s.

Modelling of Mode I delamination using a stress intensity factor enhanced cohesive zone model

Cohesive zone modelling is a common approach to capture delamination in composite laminate structures. Recent experimental advancements now enable the direct measurement of Mode I traction-separation responses (TSRs) from a single specimen using the composite rigid double cantilever beam (cRDCB), overcoming a major obstacle in using cohesive zone modelling to model delamination. However, TSRs measured experimentally with the cRDCB specimen capture damage response as well as the stiffness contribution of the adjacent laminae, which can introduce significant artificial compliance into numerical models when modelling delamination separately from intralaminar behaviour. A two-stage analysis procedure utilizing a crack tip compensation function is presented to enhance the TSRs measured with the cRDCB specimen to accurately model Mode I delamination. The analysis procedure is demonstrated to improve the accuracy of delamination prediction within the statistical variation of published experimental data. Furthermore, the transferability of TSRs measured with cRDCB specimens is explored using available experimental DCB data. It is shown that the onset of damage and early damage behaviours measured with the cRDCB specimen appear to be transferable between geometries, whilst large-scale damage mechanics remain geometry dependent.

Multi-scale numerical analysis of damage modes in 3D stitched composites

3D stitching composites have already sparked great interest among researchers due to their ability to effectively improve the weak inter-laminar properties in composite laminate structures. In this paper, a systematic analysis on mode I fracture and low-velocity impact damage of 3D stitched composites has been demonstrated via a novel multi-scale model which is capable of efficiently characterizing the distribution of stitching threads. The damage modes including intra-laminar cracks, inter-laminar delamination and stitching thread breakage are identified via a combination of continuum damage mechanics (CDM), cohesive zone model (CZM) element and truss element. This novel modeling approach enables an association analysis of stitching thread breakage status and other damage morphologies, promoting an in-depth study for the influence of stitching thread on damage evolution, which has not been reported yet. The introduction of stitching threads effectively suppresses the sharp propagation of delamination after peak load, avoiding the catastrophic destruction during mode I fracture. The mechanism of damage inhibition from stitching threads is well revealed by the numerical simulation. Furthermore, the capability of 3D stitched composites to resist low-velocity impact damage is effectively predicted in terms of peak load, damage area and damage morphology, finding that the increase of stitch density inhibits the propagation of matrix crack, as well as delamination. The universality and the expanding application of the model are also evaluated, demonstrating that it is suitable for various 3D stitched composites.

Hybrid and gradient design of ultra-thin-ply composite laminates for synergistic suppression of delamination and fiber fracture damage modes

Ply thickness hybridization is a common strategy in the layup structure of composite laminates. The rational allocation of thin-ply and thick-ply to effectively improve the performance of composite materials is a shared goal. Compared to standard laminates, ultra-thin-ply laminates have many advantages, including design flexibility, better damage tolerance, and enhanced in-situ strength. However, the risk of fiber fracture triggered by ultra-thin-ply requires cautious application. Effectively reducing the risk of fiber fracture caused by ultra-thin-ply laminates has become a challenge in the field of composite materials. Therefore, this paper proposes a thick/thin/thick gradient structure to balance delamination and fiber fracture. Short-beam bending test results demonstrate that this novel gradient structure exhibits good bending load-bearing performance and damage resistance, achieving the coexistence of multiple damage couplings and effectively enhancing damage tolerance.

Enhancing laminate composites: Investigating the impact of kevlar layering and titanium carbide nanoparticles

The quest for innovative and superior materials is a challenge in the realm of materials science and engineering. Traditional materials often fall short in meeting the demands of modern industries, especially in the military. Technological developments in the military domain are still progressing, one of which involves a new material for combat vehicle applications: a laminated composite. In this research, a composite consisting of AA7075 sheet metal and kevlar with epoxy resin and TiC nanopowder were prepared. A test was conducted to assess its performance in absorbing ballistic energy from projectiles. Solid Thickening Fluid (STF) was created by mixing TiC nanopowder with PEG-400 through 2 hours of stirring. The laminate composite structure was prepared using the hand layup method, followed by a drying process at room temperature. The addition of kevlar layers yielded promising results in the ballistic and impact tests, as the diameter of the perforation decreased progressively with each additional kevlar layer. The IK sample impact test value improved by 35.7% compared to the unimpregnated one. The production process of this material also consumes minimal energy, which suggest a potential for environmental sustainability.

Non-probabilistic credible reliability analysis of the composite laminate

For the reliability analysis of composite laminate structures, there is a problem of difficult data acquisition. Traditional reliability analysis methods require a large amount of data to maintain calculation accuracy. Therefore, the traditional reliability analysis method is not applicable to composite laminates. For the above-mentioned problems, this paper presents a method to calculate the credible reliability of composite laminate structures using the Bayesian theorem. The method is distinguished from the traditional uncertainty analysis methods. The likelihood function and the newly introduced samples are first used to correct the prior distribution of the uncertain parameters. Furthermore, the posterior distribution, containing information from both the sample and prior distributions, can be obtained. Ultimately, based on the acquired posterior distribution, the probability density function can be updated with newly introduced samples. Using the Hashin failure criterion, the failure probabilities of the fibers and matrix of the composite laminate structure are quantified, respectively. Then, the credible reliability of the composite laminate is obtained. Numerical example results show the proposed method can maintain high accuracy with fewer samples and demonstrate the validity of the model. For the numerical calculations, the deterministic parameters of the distribution function and the functional distribution parameters were verified, composite laminates and aircraft wing structures were analyzed. The experimental results show that the error between the probability density function of the parameters and the probability density function predicted by the sample is less than 0.045. Compared with the traditional reliability analysis methods for composite structures, this method can effectively measure the credible reliability of composite laminate structures with fewer samples and similar accuracy. The method enables real-time updating of the parameter probability density function by newly introduced samples and improves the confidence level.

Mechanical and morphological characterizations of epoxy composites reinforced with surface modified woven cotton structures using vacuum bagging technique

Woven fabric structures facilitate the mechanical interlacement of textile yarns for increased strength, which leads to more balanced mechanical properties in a composite. This study worked on epoxy matrix composites reinforced with surface-modified cotton fabrics of different woven structures. The composites were fabricated using the resin vacuum bagging technique and mechanically characterized for tensile, three-point bending, and impact properties. Surface modification was conducted by alkali treatment using a 6% concentration of sodium hydroxide (NaOH). The interfacial adhesion of the various fabric structures and epoxy matrix was examined using a scanning electron microscope (SEM). The results obtained show that surface-treated composites yielded improved mechanical properties than untreated composites, with improvements of up to 14.4%, 36.2%, and 26.7% for impact, flexural, and tensile strengths, respectively. The different woven structures also significantly affected the mechanical performance of the composite. The composites of plain, herringbone, and twill woven structures presented better mechanical properties compared to the other woven composite structures in that order. The plain-woven composite structure, respectively, had the maximum impact, flexural, and tensile strengths of 80.03 KJ/mm2, 38.6 MPa, and 43.7 MPa. This was closely followed by the herringbone and twill-woven composite structures. SEM results revealed complete impregnation of fibers and a strong interfacial relationship between the thermoset matrix and the treated cotton fabrics in the composite laminate structures produced via the vacuum bagging technique. In conclusion, the study indicated that different weave structures and fiber surface treatments, as well as the vacuum bagging technique used, are of significant importance in enhancing the overall mechanical performance of woven fabric composites.

Numerical Analysis of Cross‐Sectional Effects During the Magnetic Pulse Disassembly of Laminate Structures

To improve the performances of engineered systems, laminate composite structures are widely used as they offer the best strength‐to‐weight ratio. However, maintenance and recycling of these structures still remain a challenge. One solution can be to disassemble the layers, without damaging them, so that they can be repaired, reused, or recycled. To do so, impulsive sources such as high pulsed powers are considered. Herein, the influence of transverse or cross‐sectional effects on the wave propagation within the laminate and on its disassembly conditions is studied by means of two‐dimensional numerical simulations performed on a model assembly using the finite element method. The specimen considered is an aluminum/steel assembly joined along a stripe. Two different modelings of the loading applied to the laminate of increasing complexity are successively considered. First, linear elastodynamic simulations show that transverse effects reduce by around 12% the maximum achievable interfacial tensile stress ratio compared with that predicted by the 1D reference model. Then, weakly coupled eddy current‐linear elastodynamic numerical analyses clarify the latter result with an estimation of about 16% with respect to the 1D analytical solution. These results permit the design of experiments serving as a proof of concept of the proposed process.

Multi-scale procedure for the mechanical analysis of composite laminate structures considering mixed boundary conditions

This paper presents a multi-scale procedure for the study of flat composite structures with discontinuities. In this procedure, the structure is solved using shell elements while the laminate performance and the structural discontinuities (e.g. connections or change in the laminate thickness) are analysed with a subscale model made with solid 3D elements. The kinematics of both models are coupled following the Kirchhoff–Love theory. This coupling is used during the homogenization procedure where the characteristic behaviour of the different micro-models is obtained. Periodical boundary conditions are used for the laminates whereas a combination between periodical and linear boundary conditions are used for the discontinuities. The proposed procedure allows to reproduce accurately the structure elastic behaviour, as well as the stress and strain states in regions with discontinuities, which until now could only be accurately simulated by means of expensive numerical models using volumetric solid elements.

Deterministic-based robust design optimization of composite structures under material uncertainty

We propose a new deterministic robust design optimization method for composite laminate structures under worst-case material uncertainty. The method is based on a simultaneous parametrization of topology and material and combines a design problem and a material uncertainty problem into a single min–max optimization problem which provides an efficient approach to handle variation of material properties in stiffness driven design optimization problems. An analysis is performed using a design problem based on a failure criterion formulation to evaluate the ability of the proposed method to generate robust composite designs. The design problem is solved using various loads, boundary conditions and manufacturing constraints. The designs generated with the proposed method have improved objective responses compared to the worst-case response of designs generated with nominal material properties and are less sensitive to the variation of material properties. The analysis indicates that the proposed method can be efficiently applied in a robust structural optimization framework.

Mechanical Testing of Connections Blind Bolted to the Thick Glass-Fiber-Reinforced Polymer Spar Cap of a Decommissioned GE37 Wind Turbine Blade

Millions of tons of glass-fiber-reinforced polymer (GFRP) composite wind turbine blades are expected to age out of service over the next 30 years. Research is being conducted on repurposing these structures as new civil infrastructure products. The GFRP material in these decommissioned wind blades has been shown to retain significant strength and stiffness for second-life applications. However, for repurposing as new products, they will need to be connected to other structural members. The connections employed for this need to be designed, evaluated, and tested prior to their use. Here, we present the results of detailed testing of bolted connections for load-carrying appurtenances that will carry the phases and shield wires (e.g., insulators, crossarms, davits, guy wires, posts) to the spar cap of an 11-year-old 1.5 MW GE37 wind blade, intended for use as a repurposed transmission pole (i.e., a BladePole). Details of ASTM-type pull-out and bearing capacity tests using different types of blind bolts, and tests of a full-scale steel bracket connection called a “universal connector,” are reported. The effects of the different blind bolts, pin diameters, and loading directions relative to the composite laminate structure (longitudinal or transverse) for both the coupon- and full-scale connector bracket tests are described. The ability to design and construct robust connections for repurposed wind blade structures was demonstrated.

Swarm intelligence hybridized with genetic search in multi-objective design optimization under constrained-Pareto dominance

The inclusion of uncertainty in structural design optimization led to more complex design optimization formulations, where uncertainty quantification has significant influence on solution methods and computing times. Designs maintaining steady levels of performance, under uncertainty, are called robust and the combination of both robustness and performance optimality leads to a methodology called Robust Design Optimization (RDO). In this work a new approach to the RDO of angle-ply composite laminate structures is proposed. The key concept of this methodology is the hybridization between the principles of Particle Swarm Optimization and Genetic Algorithms, through the evolution of multiple populations based on local and global constrain-dominance. The RDO problem is here defined as the bi-objective minimization of the structural weight (optimality) and the determinant of the variance–covariance matrix (robustness) of the system’s response functionals, subject to stress and displacement constraints. A numerical structural design problem, representing a composite laminate engine hood shell, shows the capabilities of the proposed approach. Results display the good convergence properties of the proposed hybridizations both in the search and objective spaces.