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In the present work, the dissimilar laminated composite (DLC) of the AA2024 and AA5083 aluminum alloys and similar laminated composite (SLC) were produced by four cycles of the accumulative roll bonding (ARB) process. In the fourth ARB cycle of the AA2024/AA5083 DLC, two surfaces with AA2024 composition were put on each other. The microstructural evolution revealed an ultrafine-grained (UFG) structure with an average grain size of 500 nm. The dislocation density was found to increase with the strain during the ARB process, which then reached a saturated level. Also, the microhardness of DLC was more than the SLC-processed specimens due to work hardening and precipitates effects. Moreover, the results showed that changes in the sequence of DLC layers considerably enhanced the tensile strength and elongation. The UTS of the AA5083 SLC, AA2024 SLC, and AA2024/5083 DLC were obtained at 589 MPa, 686 MPa, and 667 MPa, respectively. Graphical abstract

Novel HEAp-Ti/Al laminated composites embedded with particles of the high-entropy alloy Al0.5CoCrFeNi (HEA) were fabricated by vacuum hot-press sintering at 730 °C. The phase composition and microstructure of the composites were studied with X-ray diffractometer (XRD), scanning electron microscope SEM, energy dispersive spectrometer (EDS), transmission electron microscope (TEM), and electron backscattering diffraction (EBSD) techniques. At this temperature, it has been observed that Al3Ti intermetallic compound is the favored phase and the reaction results in the dispersion of Al3Ti in the original Al layer. A large number of interfaces are formed between Al3Ti and Al. The deformed Al3Ti grains are concentrated in the interface near the Ti side. The mechanical properties, including tensile and compressive properties at room temperature, were analyzed. The tensile test results indicate that the composite exhibited an average tensile strength of 258 MPa and an average yield strain of 9.86%. Compression test results show that when a load perpendicular to the layer is applied, the yield strain and yield stress of the material are 9.67% and 474.09 MPa, respectively. Moreover, under a load parallel to the layer, the material fails due to interfacial debonding.

A semi-analytical method for in-plane vibration analysis of a composite laminated annular and sector plate with elastic constraints is presented. The theoretical model is on the basis of a variational method and a multi-segment technique. Displacement variables are expanded by the Jacobian orthogonal polynomial. Boundary conditions and continuity conditions between segments are characterized by penalty parameters. On this basis, a series of numerical examples are given. The results show that the method has good convergence speed and accuracy. Finally, the parametric study of geometric and material parameters is carried out to provide important support for solving the in-plane characteristics of this kind of composite structure.

Given the importance of residual stresses and dimensional changes in composites manufacturing, process simulation has been the focus of many studies in recent years. Consequently, various constitutive models and simulation approaches have been developed and implemented for composites process simulation. In this paper, various constitutive models, ranging from elastic to nonlinear viscoelastic; and simulation approaches ranging from separated flow/solid phases to multiscale integrated phases are presented and their applicability for process simulation is discussed. Attention has been paid to practical aspects of the problem where the complexity of the model coupled with the complexity and size scaling of the structure increases the characterization and simulation costs. Two specific approaches and their application are presented in detail: the pseudo-viscoelastic cure hardening instantaneously linear elastic (CHILE) and linear viscoelastic (VE). It is shown that CHILE can predict the residual stress formation in simple cure cycles such as the one-hold cycle for HEXCEL AS4/8552 where the material does not devitrify during processing. It is also shown that using this simple approach, the cure cycle can be modified to lower the residual stress level and therefore increase the mechanical performance of the composite laminate. For a more complex cure cycle where the material is devitrified during a post-cure, it is shown that a more complex model such as VE is required. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’.

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.

Physics-Informed Neural Networks (PINNs) integrate physics principles with machine learning, offering innovative solutions for complex modeling challenges. Laminated composites, characterized by their anisotropic behavior, multi-layered structures, and intricate interlayer interactions, pose significant challenges for traditional computational methods. PINNs address these issues by embedding governing physical laws directly into neural network architectures, enabling efficient and accurate modeling. This review provides a comprehensive overview of PINNs applied to laminated composites, highlighting advanced methodologies such as hybrid PINNs, k-space PINNs, Theory-Constrained PINNs, optimal PINNs, and disjointed PINNs. Key applications, including structural health monitoring (SHM), structural analysis, stress-strain and failure analysis, and multi-scale modeling, are explored to illustrate how PINNs optimize material configurations and enhance structural reliability. Additionally, this review examines the challenges associated with deploying PINNs and identifies future directions to further advance their capabilities. By bridging the gap between classical physics-based models and data-driven techniques, this review advances the understanding of PINN methodologies for laminated composites and underscores their transformative role in addressing modeling complexities and solving real-world problems.

Advanced composite materials have excellent performance and broad engineering application prospects, and have received widespread attention in recent years. Advanced composite materials can mainly be divided into fiber-reinforced composite materials, laminated composite materials, matrix composite materials, and other composite materials. This article provides a comprehensive overview of the types and characteristics of advanced composite materials, and provides a comprehensive evaluation of the latest research on structural strengthening and resilience improvement in advanced composite materials from the perspectives of new methods, modeling optimization, and practical applications. In the field of fiber-reinforced composite materials, the hybrid technology of carbon fiber and glass fiber can achieve dual advantages in combining the two materials. The maximum increase in mechanical properties of multilayer sandwich RH plate by hybrid technology is 435.4% (tensile strength), 149.2% (flexural strength), and 110.7~114.2% (shear strength), respectively. In the field of laminated composite materials, different mechanical properties of laminated composite materials can be obtained by changing the deposition sequence. In the field of matrix composites, nano copper oxide particles prepared by nanotechnology can increase the hardness and tensile strength of the metal matrix material by 77% and 78%, respectively. In the field of other composite materials, viscoelastic materials and magnetorheological variants have received widespread attention. The development of composite materials benefits from the promotion of new methods and technologies, but there are still problems such as complex preparation, high cost, and unstable performance. Considering the characteristics, application requirements, cost, complexity, and performance of different types of composite materials, further improvements and innovations are needed in modeling and optimization to better meet practical engineering needs, such as the application of advanced composite materials in civil engineering, ships, automobiles, batteries, and other fields.

The present study is aimed at investigating the effect of hybridisation on Kevlar/E-Glass based epoxy composite laminate structures. Composites with 3 mm thickness and 16 layers of fibre (14 layers of E-glass centred and 2 outer layers of Kevlar) were fabricated using compression moulding technique. The fibre orientation of the Kevlar layers had 3 variations (0, 45 and 60°), whereas the E-glass fibre layers were maintained at 0° orientation. Tensile, flexural, impact (Charpy and Izod), interlaminar shear strength and ballistic impact tests were conducted. The ballistic test was performed using a gas gun with spherical hard body projectiles at the projectile velocity of 170 m/s. The pre- and post-impact velocities of the projectiles were measured using a high-speed camera. The energy absorbed by the composite laminates was further reported during the ballistic test, and a computerised tomographic scan was used to analyse the impact damage. The composites with 45° fibre orientation of Kevlar fibres showed better tensile strength, flexural strength, Charpy impact strength, and energy absorption. The energy absorbed by the composites with 45° fibre orientation was 58.68 J, which was 14% and 22% higher than the 0° and 60° oriented composites.

The aim of this article was to investigate the effect of carbon nanotubes (CNTs) on the buckling behavior of fiber-reinforced polymer (FRP) composites. The materials used included three layers: carbon-fiber-reinforced polymer (CFRP), epoxy and CNTs. A set of mechanical tests, such as compression and buckling tests, was performed, and also analytical solutions were developed. Damage analysis was also carried out by controlling the damage initiation and crack progression on the composite samples. Experimental results revealed that using 0.3% with CNT additives enhanced the buckling performance of the composite. Finally, the average load-carrying capacity for the clamped–clamped boundary condition was 268% higher in the CNT samples and 282% higher in the NEAT samples compared to the simple–simple condition.

Laminated composite structures have a distinct inherent potential for optimization due to their tailorability and their associated complex failure mechanisms that makes intuitive design remarkably difficult. Optimization of such is a maturing technology with many criteria and manufacturing constraints having been successfully demonstrated. An approach for high-cycle fatigue is however yet to be developed in a gradient-based context. Thus, the objective of this work is to introduce a novel framework that allows for effective high-cycle fatigue optimization of laminated composite structures.Offset is taken in the Discrete Material and Thickness Optimization parametrization, which allows for simultaneous material and thickness selection for each layer that constitute a laminate. The fatigue analysis approach is based on accumulating damage from all variable-amplitude cycles in an arbitrary spectrum. As high-cycle fatigue behavior is highly nonlinear, it is difficult to handle in optimization. To stabilize the problem, damage is scaled using an inverse P-mean norm formulation that reduces the nonlinearity and provides an accurate measure of the damage. These scaled damages are then aggregated using P-norm functions to reduce the number of constraints. This is convenient, as it allows sensitivities to be efficiently calculated using analytical adjoint design sensitivity analysis. The effectiveness of this approach will be demonstrated on both benchmark examples and a more complicated main spar structure.