今日更新：Composite Structures 1 篇，Composites Part A: Applied Science and Manufacturing 4 篇，Composites Part B: Engineering 2 篇
Composite Structures
NURBS-based isogeometric analysis for layerwise local behavior of nano-laminated plates based on refined zigzag and nonlocal strain gradient theories
Huy Q. Le, Samir Khatir, Thanh-Cuong Le
doi:10.1016/j.compstruct.2024.118766
基于精细之字形和非局部应变梯度理论的纳米层合板分层局部行为等几何分析
In this work, a newly numerical approach for the global and local analysis of laminated composite plates, incorporating size-dependent effects through refined zigzag kinematics and nonlocal strain gradient theory, is developed. By applying the principle of virtual displacement, we derive a weak form of the equilibrium equations based on the nonlocal strain gradient theory, resulting in a local continuum model. This model inherently accounts for deviations in stiffness due to material inhomogeneity and interatomic forces, particularly at small scales. The refined zigzag theory is used to model the displacement field of the plates, which is numerically approximated using the NURBS-based isogeometric analysis technique. This approach allows us to account for the size-dependent characteristics of the laminate at micro/nanoscale through higher-order nonlocal parameters and nonlocal gradient length coefficients. We validate the proposed model for static and free vibration analyses by comparing our numerical results with those reported in the literature. As an original contribution, this research extensively explores the size-dependent effects on the layerwise local responses of laminated composite plates under static loading conditions with various stacking sequences and thickness ratios being investigated.
Composites Part A: Applied Science and Manufacturing
Integrated convolutional and graph neural networks for predicting mechanical fields in composite microstructures
Marwa Yacouti, Maryam Shakiba
doi:10.1016/j.compositesa.2024.108618
基于卷积和图神经网络的复合材料微结构力学场预测
This paper introduces CompINet, a novel approach that leverages graph and convolutional neural networks to predict mechanical fields within microstructural representations of composites. Analyzing local mechanical fields, such as stress in composites, is crucial for predicting performance and failure, and planning repair strategies. The critical role of the fiber’s nearest neighbor distances in shaping linear and nonlinear stress responses within the composite’s microstructure motivates our approach. CompINet exploits the power of graph neural networks to capture the microscale intricacies of composites, particularly the locations of the fibers and the distances between them. The proposed framework demonstrates remarkable accuracy and consistency in predicting microscale mechanical fields, requiring 20 times less data than existing data-driven methods. CompINet offers significant improvements in both linear and nonlinear composite analyses.
Vat photopolymerization (VP) of solvent-free carbon Nanoparticle-Acrylic nanocomposites
Poom Narongdej, Nicolas Alterman, Manuel Vazquez, Mehran Tehrani, Ehsan Barjasteh
doi:10.1016/j.compositesa.2024.108628
无溶剂纳米碳-丙烯酸纳米复合材料的还原光聚合（VP）
Digital light processing (DLP) based vat photopolymerization (VP) additive manufacturing (AM)offers high resolution and rapid printing capabilities, making it particularly well-suited for producing intricate geometries. However, the applications of DLP are limited by material options available, particularly due to their low mechanical properties. This study addresses this challenge by introducing a novel solvent-free method to incorporate various carbon-based nanoparticles into DLP resins. This approach ensures printability by maintaining nanoparticle stability in the solution while enhancing overall material properties. Ten acrylic monomers were carefully selected based on their Hansen solubility parameters to effectively disperse and stabilize the studied nanoparticles (graphite nanoparticles, GNPs, and edge oxidized graphene oxide, EOGOs). It was found that Tricyclodecane Dimenthanol Diacrylate (G1231) possessed similar interfacial energies with the nano-fillers, which prevented agglomeration within the matrix. This led to the creation of homogeneous nano-filled resins, which demonstrated stability for the seven-day observation period, suggesting potential stability beyond this timeframe. Additionally, this study explored the relationship between layer exposure time, nanoparticle concentration, and size on printability, as well as key characteristics such as viscosity, depth of cure, and mechanical properties. The optimal combination of parameters led to considerable improvements in mechanical properties, with the modulus of elasticity and tensile strength increasing by 18% and 17% respectively for nano-filled resins up to 0.07 wt%, with cure times up to 90 s. The solvent free method of incorporating carbon-based nanomaterials in resins is simple and efficient. It also demonstrates great potential for broader material selection and property enhancement in DLP resins, thereby paving the way for expanded applications across various fields.
This study delved into the significant effects of fiber dispersion and aggregation on the nonlinear mechanical properties of cellulose nanofibers (CNF) reinforced polypropylene (PP) composites, aiming to advance fiber dispersion control and elucidate specific advantages to mechanical properties. In contrast to the conventional method of preparing composite materials using powdered CNF and solid anhydrous maleic anhydride PP (MAPP), we proposed an innovative method that used water-dispersed CNF and water-dispersible MAPP to enhance fiber dispersion. Morphological analysis of fiber aggregation was conducted using high-resolution X-ray computed tomography (CT), complemented by mechanical testing through tensile strength evaluations. The results demonstrated that the proposed preparation method enhanced both fiber dispersion and mechanical properties. Applying multiscale simulations based on homogenization theory, we developed a two-step homogenization process for fiber agglomeration modeling, which incorporated fiber dispersion measurements from X-ray CT. Numerical analysis accurately replicated the phenomena observed in experiments, confirming the validity of the modeling approach and elucidating the integrity of the developed cellulose composite materials. Additionally, by introducing parameters: aggregation domain (k) and aggregation density (x), we quantified the impact of fiber agglomeration on the nonlinear mechanical properties of the composites and provided design guidelines for fiber dispersion control. This study not only proposed a method for creating cellulose composite materials with excellent fiber dispersion but also provided a systematic multiscale numerical analysis method based on experimental measurements to evaluate mechanical properties considering fiber agglomeration.
Characterization of Out-of-Plane wrinkles in woven CFRP Laminate: Development of a novel algorithm utilizing ultrasonic scan data
Md Admay Amif, Irrtisum Khan, David A. Jack
doi:10.1016/j.compositesa.2024.108644
编织CFRP层压板面外皱纹的表征：利用超声扫描数据的新算法的发展
Out-of-plane wrinkles in laminated composites reduce the structural integrity. This study presents an algorithm to characterize wrinkle height and intensity of each lamina within a plain weave laminated composite, utilizing full waveform ultrasonic scan data. This algorithm enables the extraction of individual laminae in three dimensions. An immersion tank ultrasound testing system is employed for scanning coupled with a 7.5 MHz spherically focused transducer. Surface construction from the waveform entails a spatial Gaussian averaging followed by a tracking of voltage peaks in time of individual A-scans, from which we extract individual lamina interfaces. Four samples are presented with various wrinkle amplitudes encompassing a wide range of industrially relevant scenarios. The comparison of the ultrasonically characterized wrinkle heights with microscopic images of sectioned samples demonstrates consistency between the two methods, with a maximum deviation of 0.06 mm wrinkle amplitude across all samples considered in this study.
