今日更新：Composite Structures 8 篇，Composites Part A: Applied Science and Manufacturing 6 篇，Composites Part B: Engineering 6 篇，Composites Science and Technology 1 篇Composite StructuresOptimal lamination angles via exact and efficient differentiation of the geometrically nonlinear finite element solutionDomenico Magisano, Leonardo Leonetti, Giovanni Garceadoi:10.1016/j.compstruct.2024.118579通过精确和有效的几何非线性有限元解的微分优化层合角Laminates allow tailoring the fiber orientations in the layers to obtain the desired mechanical response. The optimal layup design is a challenging task in the case of finite deformations and buckling. For an assigned design, an incremental-iterative finite element analysis is needed to compute the structural response. Gradient-based methods are very often the most efficient optimization tools. Their bottleneck is the gradient evaluation, generally possible only approximately by finite differences. This article shows how to compute the exact gradient of the geometrically nonlinear finite element solution with respect to the stacking sequence. The strategy relies on the implicit differentiation of the nonlinear discrete equations of a control equilibrium point corresponding to an assigned displacement. This provides the load factor gradient by a single fast-solution linear system with the already factorized tangent stiffness matrix, regardless of the number of design variables, and scalar products involving the partial derivatives of the discrete internal force vector, calculated in an exact and efficient way. Several applications demonstrate the efficiency and robustness of the approach.层压板允许在层中裁剪纤维方向，以获得所需的机械响应。在有限变形和屈曲的情况下，优化叠层设计是一项具有挑战性的任务。对于指定的设计，需要进行增量迭代有限元分析来计算结构响应。基于梯度的方法通常是最有效的优化工具。它们的瓶颈是梯度计算，通常只能近似地用有限的差分。本文展示了如何计算几何非线性有限元解相对于堆叠序列的精确梯度。该策略依赖于控制平衡点对应于指定位移的非线性离散方程的隐式微分。这提供了一个单一的快速解决的线性系统的载荷系数梯度与已经因式分解的切刚度矩阵，无论设计变量的数量，和标量积涉及的偏导数的离散内力矢量，以精确和有效的方式计算。几个应用证明了该方法的有效性和鲁棒性。Research on the influence of impact damage on force identification for composite materialYuqing Qiu, Hongli Ji, Chongcong Tao, Jinhao Qiudoi:10.1016/j.compstruct.2024.118595冲击损伤对复合材料力识别的影响研究The invisible damage caused by low-velocity impacts are safety threats to engineering structures. Thus, impact force identification is crucial in the context of composite structures for both structure health monitoring (SHM) and composite structure design. This paper investigates the process of identifying impacts on composite structures subjected to low-velocity impact. Considering the damage evolution in the composite structure during impact, this paper explores the influence of impact damage on the accuracy of force identification. Impact experiments on carbon fiber reinforced polymer (CFRP) laminates were conducted to obtain impact force peaks and displacement responses. Furthermore, a validated finite element model (FEM) is established for more elaborate analysis on the mechanism. The findings reveal that the structural damage can lead to significant deviations in force identification if the damage is not considered. Finally, a neural network is employed to predict the force history taking impact damage into consideration. This research provides a reference for the composite structures design and health monitoring of engineering structures considering impact damage.低速冲击造成的无形损伤是对工程结构的安全威胁。因此，在复合材料结构健康监测和复合材料结构设计的背景下，冲击力识别是至关重要的。本文研究了复合材料结构在低速冲击作用下的冲击识别过程。考虑复合材料结构在冲击过程中的损伤演化，探讨了冲击损伤对力识别精度的影响。对碳纤维增强聚合物(CFRP)层压板进行了冲击试验，得到了冲击力峰值和位移响应。在此基础上，建立了经过验证的有限元模型，对其机理进行了详细分析。研究结果表明，如果不考虑结构损伤，结构损伤会导致力识别的显著偏差。最后，利用神经网络对考虑冲击损伤的受力历史进行预测。研究结果可为考虑冲击损伤的复合结构设计和工程结构健康监测提供参考。Damage characterisation of GFRP composites based on clustering acoustic emission events utilizing single-failure-cause tests as referenceSmolnicki Michał, Duda Szymon, Zielonka Paweł, Stabla Pawełdoi:10.1016/j.compstruct.2024.118596基于聚类声发射事件的GFRP复合材料损伤表征，并以单失效原因试验为参考A new method to identify causes of fracture in composites based on acoustic emission (AE) and clusterization of AE data based on reference datasets is presented within the manuscript. Acoustic Emission (AE) is a widely used non-destructive method for fracture analysis, but data due to their multidimensionality are not easy to analyze especially if the acoustic events appear simultaneously and have similar parameters even if they are an effect of different failure mechanisms. In this research, we utilize an unsupervised learning algorithm besides the simplest K-means, through fuzzy c-means to Gaussian Mixture Model (GMM) and spectral clustering to investigate the dataset obtained from the three-point bending test manufactured by us composite. The analysis is preceded by data curation, feature determination (Laplacian score) and the best number of cluster investigations (DB index, Caliński-Harabasz score, and Silhouette method) To enable interpretation of the clustering we run an additional three groups of tests covering fibre breakage (two methods), resin fracture (in tension and in compression) and delamination (DCB test) creating reference datasets. These datasets were statistically analyzed and kernel density estimators were generated for each AE feature as well as amplitude-frequency characteristics. Clusters obtained for the main dataset were then assigned to particular causes of failure by comparing them with the reference dataset. It was found that clusters generated using spectral clustering were the most realistic ones, as it was possible to assign the cause of failure to them.本文提出了一种基于声发射(AE)和基于参考数据集的声发射数据聚类识别复合材料断裂原因的新方法。声发射(AE)是一种广泛应用于裂缝分析的非破坏性方法，但由于数据的多维性，特别是当声事件同时出现且参数相似时，即使它们是不同破坏机制的影响，也不容易分析。在本研究中，我们利用一种无监督学习算法，除了最简单的K-means之外，通过模糊c-means到高斯混合模型(GMM)和谱聚类对us复合材料三点弯曲试验获得的数据集进行研究。分析之前是数据管理、特征确定(拉普拉斯分数)和最佳数量的聚类调查(DB指数、Caliński-Harabasz分数和Silhouette方法)。为了解释聚类，我们运行另外三组测试，包括纤维断裂(两种方法)、树脂断裂(拉伸和压缩)和分层(DCB测试)，创建参考数据集。对这些数据集进行统计分析，并对每个声发射特征和幅频特征生成核密度估计。然后通过与参考数据集进行比较，将主数据集获得的聚类分配给特定的故障原因。结果发现，利用谱聚类生成的聚类是最真实的聚类，因为可以将故障原因分配给它们。Bio-inspired discontinuous composite materials with a machine learning optimized architectureTheodoros Loutas, Athanasios Oikonomoua, Christoforos Rekatsinasdoi:10.1016/j.compstruct.2024.118597具有机器学习优化架构的仿生不连续复合材料Bio-inspired hierarchical discontinuous fibrous composite materials are investigated with the aim of achieving enhanced pseudo-ductility and elevated toughness. A novel methodology is proposed to search quickly and efficiently through the vast design space of the geometrical parameters of the discontinuities, combining advanced numerical simulations of the material’s mechanical behavior with state-of-the-art Machine Learning approaches, such as Active Learning. A continuum mesoscale-based numerical model is developed to simulate the mechanical behavior of discontinuous composites under three-point bending loading and is utilized in a sequential Bayesian optimization scheme that iteratively searches for the material architecture that maximizes toughness. Five independent geometrical variables related to the size and exact topology of the discontinuities form a vast five-dimensional design space of more than 2.6 million possible combinations. In this space, the proposed methodology efficiently identifies, after 100 iterations, a remarkable optimal configuration that increases the material’s toughness by more than 100%, with a knock-down effect on the ultimate bending strength of only 10%.研究了仿生层次化不连续纤维复合材料的伪延性和高韧性。提出了一种新的方法，通过不连续面几何参数的巨大设计空间进行快速有效的搜索，将材料力学行为的先进数值模拟与最先进的机器学习方法(如主动学习)相结合。建立了基于连续介质细观尺度的数值模型来模拟三点弯曲载荷下不连续复合材料的力学行为，并将其用于顺序贝叶斯优化方案中，该方案迭代搜索最大韧性的材料结构。与不连续面大小和精确拓扑相关的五个独立几何变量形成了一个巨大的五维设计空间，有超过260万种可能的组合。在这个空间中，经过100次迭代，所提出的方法有效地确定了一个显着的最佳配置，该配置将材料的韧性提高了100%以上，而对最终弯曲强度的击倒效应仅为10%。A novel negative Poisson’s ratio structure with high Poisson’s ratio and high compression resistance and its application in magnetostrictive sensorsLimin Ren, Xu Zhang, Zheng Li, Yuchen Sun, Yisong Tandoi:10.1016/j.compstruct.2024.118599 一种具有高泊松比和高抗压性的负泊松比结构及其在磁致伸缩传感器中的应用Currently, dead zones and low sensitivity have hindered the utilization of magnetostrictive sensors. In this paper, a new negative Poisson’s ratio structure inspired by an hourglass is proposed to provide a feasible idea for this problem. The novel negative Poisson’s ratio structure exhibits a high Poisson’s ratio and a high compression resistance. Theoretical studies have demonstrated that the structure’s performance is strongly dependent on four design parameters. The structure is analyzed and tested via finite element analysis simulation by changing the design parameters. This structure’s negative Poisson’s ratio can reach up to −1.004. It possesses a compressive strength of 1.83 kN and an energy absorption capacity of 8.72 J. A magnetostrictive sensor using the proposed negative Poisson’s ratio structure as the base realizes a 271.7 % sensitivity improvement. The problem of dead zones in magnetostrictive sensors can be also solved simultaneously. The proposed structure in this paper provides a feasible solution for further expanding the applications of magnetostrictive sensors.目前，磁致伸缩传感器存在着死区和低灵敏度等问题。本文提出了一种受沙漏启发的负泊松比结构，为解决这一问题提供了一种可行的思路。新型负泊松比结构具有高泊松比和高抗压性。理论研究表明，结构的性能在很大程度上取决于四个设计参数。通过改变设计参数，对结构进行有限元仿真分析和测试。该结构的负泊松比可达- 1.004。抗压强度为1.83 kN，吸能能力为8.72 J。采用所提出的负泊松比结构为基础的磁致伸缩传感器的灵敏度提高了271.7 %。同时还可以解决磁致伸缩传感器的死区问题。本文提出的结构为进一步扩大磁致伸缩传感器的应用范围提供了一种可行的解决方案。Failure mechanism investigation of the adhesively bonded joints using Finite Element and Discrete Element methodsArman Abylkassimov, Gulnur Kalimuldina, Sherif Araby Gouda, Yerlan Amanbekdoi:10.1016/j.compstruct.2024.118574用有限元和离散元方法研究粘接接头的破坏机理Structural integrity is commonly defined by strength and durability of structure’s components. Adhesive joints have advantages over welding and bolted joints by less stress concentration, less weight and easier in manufacturing. In this study, numerical modelling analysis is employed to better understand fracture progression and its mechanism in adhesively bonded joints (lap shear joints) subjected to axial loading. Finite element method and discrete element method were used to predict strength and damage propagation of single lap joints. The study utilized Loctite EA 9497 epoxy as adhesive and three different adherends including polyphtalamide-polyphtalamide (PPA-PPA), aluminium-aluminium (AL-AL) and aluminium-polyphtalamide (AL-PPA) in the lap shear joints. The finite element model employed Cohesive Zone Model to examine joint strength, stress distributions along adhesive/adherend interface, and to perform scalar stiffness degradation analysis. The finite element model revealed that the adhesive damage takes place at the interface adjacent to the adherend with lower material stiffness. In addition, validation using load–displacement curves and comparison with experimental data demonstrated good agreement. Subsequently, discrete element model coupled with the Johnson-Kendall-Roberts (JKR) cohesion model was employed to adapted failure progression based on discrete particle interactions. The developed model was verified and compared with experimental results. Using the innovative discrete element method coupled with the JKR cohesion model, the bond number per particle parameter served as a material failure indicator. Analysis from the discrete element approach revealed that failure consistently takes place at the adhesive/adherend interface, irrespective of the adherend type. These study findings provide insights into investigating failure mechanisms in adhesively bonded joints at both macro- and micro-scales.结构完整性通常由结构部件的强度和耐久性来定义。与焊接和螺栓连接相比，粘接具有应力集中小、重量轻、易于制造等优点。为了更好地理解轴向载荷作用下粘接接头(搭接剪切接头)的断裂过程及其机制，本研究采用数值模拟分析方法。采用有限元法和离散元法对单搭接节点的强度和损伤扩展进行预测。本研究采用乐泰EA 9497环氧树脂作为胶粘剂，在搭接剪切缝中分别使用聚苯酰胺-聚苯酰胺(PPA-PPA)、铝-铝(AL-AL)和铝-聚苯酰胺(AL-PPA)三种不同的粘结剂。有限元模型采用内聚区模型，考察接头强度、黏附界面应力分布，并进行标量刚度退化分析。有限元模型分析表明，粘结损伤主要发生在材料刚度较低的粘附体相邻界面处。此外，利用荷载-位移曲线进行验证，并与实验数据进行对比，结果表明两者吻合较好。随后，采用离散元模型和JKR黏聚模型对基于离散粒子相互作用的破坏过程进行自适应。对所建立的模型进行了验证，并与实验结果进行了比较。采用新颖的离散元法结合JKR黏聚模型，将每颗粒黏结数参数作为材料失效指标。从离散元方法的分析表明，破坏始终发生在粘合剂/粘附界面，无论粘附类型。这些研究结果为研究粘接接头在宏观和微观尺度上的破坏机制提供了见解。Automatic modeling and optimization of tapered laminates with ply dropsChen Du, Jiajun Chen, Qinghu Wang, Xiongqi Pengdoi:10.1016/j.compstruct.2024.118603带厚度下降的锥形层压板的自动建模与优化Ply-drop (PD) is the termination of specific plies for laminated composite structures to obtain continuous thickness changes. It brings flexibility to the design of tapered composite laminates. However, as a structural defect, ply drops could have an impact on performance. Considering the impact of ply drop during stacking sequence design can provide more accurate performance analysis, but this will bring challenges in modeling and optimization. To consider the PD impact and achieve convenience in optimization, this paper proposes a high-fidelity finite element modelling method of tapered laminates and corresponding optimization framework. By parameterizing the PD information and defining the basic elements and nodes of start stacking surface of the structure, the entire finite element model is layer-wisely constructed and controllable. Subsequently, based on the genetic algorithm framework, a repair strategy and its genetic operations are proposed to ensure that the design variables satisfy the ply-drop design guidelines. Finally, the strength and deflection performance optimization problem of a tapered laminate with PD from 28 layers to 16 layers under three-point bending test is introduced for demonstration of the proposed automatic modeling and optimization method. Comparisons between simulation results and experimental data of the obtained optimization solution verify the effectiveness of the proposed modeling and optimization method.层降(PD)是层合复合材料结构中 特定层的终止，以获得连续的厚度变化。它给锥形复合层压板的设计带来了灵活性。然而，作为一种结构缺陷，厚度下降可能会对性能产生影响。在堆叠顺序设计中考虑铺层下降的影响可以提供更准确的性能分析，但这会给建模和优化带来挑战。为了考虑PD影响，方便优化，本文提出了一种高保真的锥形层合板有限元建模方法及相应的优化框架。通过参数化PD信息，定义结构开始叠加面的基本元素和节点，实现了整个有限元模型的分层构建和可控。随后，基于遗传算法框架，提出了一种修复策略及其遗传操作，以确保设计变量满足弹滴设计准则。最后，以3点弯曲试验条件下28层至16层PD锥形层压板的强度和挠度性能优化问题为例，对所提出的自动建模和优化方法进行了验证。仿真结果与实验数据的对比验证了所提出的建模和优化方法的有效性。Mode I delamination monitoring in carbon nanotubes-glass fiber/epoxy composites using simultaneous electrical self-sensing and acoustic emission techniquesMaría del Pilar de Urquijo-Ventura, Julio Alejandro Rodríguez-González, Carlos Rubio-Gonzálezdoi:10.1016/j.compstruct.2024.118608碳纳米管玻璃纤维/环氧复合材料的I型分层监测，同时使用电自传感和声发射技术The aim of this work is to demonstrate that simultaneous electrical resistance (ER) and acoustic emission (AE) techniques are a viable complementary procedures for in-situ mode I delamination monitoring of glass fiber/epoxy composite laminates containing multiwall carbon nanotubes (MWCNTs). The incorporation of MWCNTs was made by the spray-coating technique and composite laminates were manufactured by means of VARI process. The manufactured laminates were cut into double cantilever beam (DCB) specimens for fracture testing and simultaneous ER and AE measurements were carried out under mode I fracture loading condition. The results showed that the ER signal of the DCB specimens follows the load–displacement (P-δ) curve from initiation to growth of delamination failure, confirming the electrical self-sensing capability of the embedded MWCNT electrical network into the laminate. The correlation of AE events with the P-δ curves of the laminates with and without MWCNTs also allowed to detect the mode I delamination initiation and propagation. Although both the ER and AE techniques demonstrated their capability to determine mode I interlaminar fracture toughness and are in agreement with the results of ASTM standard, the presence of MWCNTs into laminates for self-sensing was more favorable since provided mechanical, electrical and sensing capabilities for SHM applications.这项工作的目的是证明同时电阻(ER)和声发射(AE)技术是一种可行的补充程序，用于含有多壁碳纳米管(MWCNTs)的玻璃纤维/环氧复合材料层压板的I型分层监测。采用喷涂技术包覆MWCNTs，采用VARI工艺制备复合层压板。将所制备的层合板切割成双悬臂梁试件进行断裂测试，并在I型断裂加载条件下同时进行ER和AE测量。结果表明:DCB试样的内电信号从分层破坏开始到发展遵循荷载-位移(P-δ)曲线，证实了嵌入MWCNT电网络在层状材料中的电自感知能力;AE事件与添加和不添加MWCNTs的层合板的P-δ曲线的相关性也允许检测I型分层的开始和扩展。虽然内能和声发射技术都证明了它们确定I型层间断裂韧性的能力，并且与ASTM标准的结果一致，但在层板中加入MWCNTs进行自感测更为有利，因为它为SHM应用提供了机械、电气和感测能力。Composites Part A: Applied Science and ManufacturingNacre-like hybrid aluminum-matrix composite with simultaneously enhanced strength and toughnessJidong Zhang, Xuexi Zhang, Mingfang Qian, Lin Gengdoi:10.1016/j.compositesa.2024.108480 类珠核杂化铝基复合材料，同时增强强度和韧性Architecture design, especially nacre-like structure, allows multi-mechanism co-ordination of strengthening and toughening to improve the comprehensive mechanical properties of metal-matrix composites (MMCs). Here a bio-inspired 20 vol% (TiB2p-TiBw)/2024Al composites with nacre-like structure were prepared via freeze casting combined with squeeze casting, where the TiB whiskers (TiBw) were introduced into the composites by in-situ reaction between Ti and TiB2 (Ti + TiB2 → 2TiBw), significantly reducing the sintering temperature of the (TiB2p-TiBw) preforms. We found that the introduction of the ceramic layers inhibited the dissolution of the Cu-rich phase and accelerated the ageing behavior of the Al matrix reducing the duration of peak aging. Both the optimum solution and the aging condition were determined to be 510 °C for 2 h and 160 °C for 16 h respectively, resulting in a superior compressive strength of 886.5 MPa, flexural strength of 709.8 MPa, and crack propagation toughness of 36.1 MPa.m1/2. The exceptional compressive and flexural properties are due to the nacre-like structure, which increases matrix deformation resistance, improving the deformation coordination between the Al matrix and ceramic layers. The high damage resistance was attributed to the multiple extrinsic toughening mechanisms such as interfacial delamination, crack deflection, multi-crack extension, crack blunting and TiBw pull-out.结构设计，特别是珠状结构，允许多机制协调强化和增韧，提高金属基复合材料(MMCs)的综合力学性能。采用冷冻铸造和挤压铸造相结合的方法制备了体积分数为20 % (TiB2p-TiBw)/2024Al的珠状结构复合材料，通过Ti和TiB2 (Ti + TiB2 → 2TiBw)的原位反应将TiB晶须(TiBw)引入复合材料中，显著降低了(TiB2p-TiBw)预制体的烧结温度。发现陶瓷层的引入抑制了富cu相的溶解，加速了Al基体的时效行为，缩短了峰值时效的持续时间。最佳时效条件为510 °C，时效2 h，时效160 °C，时效16 h，抗压强度为886.5 MPa，抗弯强度为709.8 MPa，裂纹扩展韧性为36.1 MPa.m1/2。优异的抗压和弯曲性能是由于珠状结构增加了基体的抗变形能力，改善了Al基体和陶瓷层之间的变形协同性。高抗损伤性能是由界面分层、裂纹偏转、多裂纹扩展、裂纹钝化和TiBw拉出等多种外部增韧机制所致。Shear localization in ultralow wear of PEEK/UPE compositesWei Sun, Tianci Chen, Tao Chen, Xiaojun Liu, Jiaxin Yedoi:10.1016/j.compositesa.2024.108484PEEK/UPE复合材料超低磨损的剪切局部化研究Certain polytetrafluoroethylene (PTFE) composites can form a shear localization structure at the sliding interface by developing running and transfer films, thus achieving an ultralow wear rate of ∼10−7 mm/Nm. However, PTFE, as a per- and polyfluoroalkyl substance (PFAS), raises significant biological toxicity concerns in tribological applications. Based on the shear localization hypothesis, we propose replacing PTFE with ultrahigh-molecular-weight polyethylene (UPE) at the tribo-interface and utilizing PEEK/UPE composites as PFAS-free, ultralow-wear candidates. Wear tests demonstrate that PEEK/UPE composites offer superior anti-wear performance compared to traditional ultralow-wear composites under various conditions. Micromechanical measurements reveal enhanced mechanical properties of tribofilms, which resulted in the ultralow-wear shear localization at the PEEK/UPE tribo-interface. Surface analysis suggests that mechanochemically carboxylated UPE and PEEK polymers play a critical role in maintaining stable shear localization. Contact mechanics calculations further indicate that the robustness of the shear localization of PEEK/UPE composites is attributed to the higher van der Waals force of UPE against steel counterface than that of PTFE.某些聚四氟乙烯(PTFE)复合材料可以通过形成运行膜和转移膜在滑动界面形成剪切局部化结构，从而实现~ 10−7 mm/Nm的超低磨损率。然而，PTFE作为一种全氟和多氟烷基物质(PFAS)，在摩擦学应用中引起了重大的生物毒性问题。基于剪切局部化假设，我们提出在摩擦界面用超高分子量聚乙烯(UPE)代替PTFE，并利用PEEK/UPE复合材料作为不含pfas的超低磨损候选材料。磨损试验表明，与传统的超低磨损复合材料相比，PEEK/UPE复合材料在各种条件下具有优越的抗磨性能。微观力学测量表明，摩擦膜的力学性能得到了增强，这导致了PEEK/UPE摩擦界面的超低磨损剪切局部化。表面分析表明，机械化学羧基化UPE和PEEK聚合物在保持剪切定位稳定方面起着关键作用。接触力学计算进一步表明，PEEK/UPE复合材料剪切局部化的鲁棒性归因于UPE对钢表面的范德华力高于PTFE。Investigation of the effect of symmetrical hybrid stacking on drilling machinability of unidirectional CFRP, GFRP and hybrid composites: Drilling tests and damage analysisŞakir Yazman, Lokman Gemi, Sezer Morkavuk, Uğur Köklüdoi:10.1016/j.compositesa.2024.108486对称杂化堆垛对单向CFRP、GFRP及杂化复合材料钻削加工性能影响的研究:钻削试验与损伤分析Fiber-reinforced plastics are undoubtedly superior to metals in many sectors due to their advantageous properties. Especially carbon fiber reinforced plastics (CFRP) and glass fiber reinforced plastics (GFRP) are widely used in industry. Although CFRP offers higher strength, its use is limited due to its high cost. However, with hybridisation, it is possible to produce composites that will provide sufficient strength at lower cost. The mechanical behaviour of hybrid composites may be different compared to glass or carbon composites, as well as the damage behaviour during machining. In this study, the influence of hybrid stacking in drilling hybrid composites was investigated. The results showed the hybrid stacking, especially the position of the carbon plate, has a significant impact on the force generation and damage formation in the drilling. Although stacking the carbon layer at bottom caused an increase in thrust forces, it reduced the damage formation at the hole exit.纤维增强塑料由于其优越的性能，在许多领域无疑优于金属。特别是碳纤维增强塑料(CFRP)和玻璃纤维增强塑料(GFRP)在工业上得到了广泛的应用。虽然CFRP具有更高的强度，但由于成本高，其使用受到限制。然而，通过杂交，可以生产出以较低成本提供足够强度的复合材料。混杂复合材料的力学性能与玻璃或碳复合材料不同，加工过程中的损伤行为也不同。研究了杂化堆积对钻孔杂化复合材料的影响。结果表明，杂化叠加，尤其是碳板的位置，对钻井过程中力的产生和损伤的形成有显著影响。虽然在底部堆积碳层增加了推力，但减少了孔出口的损伤形成。Intelligent identification of machining damage in ceramic matrix composites based on deep learningWeiming Mao, Kun Zhoudoi:10.1016/j.compositesa.2024.108487 基于深度学习的陶瓷基复合材料加工损伤智能识别This study proposed a method for identifying and quantitatively evaluating the machining damages of CMCs based on deep learning. Firstly, grinding tests of CMCs were conducted to create a dataset of machining damages. Then, six deep learning algorithms were trained using the dataset, and their comprehensive performance was compared. The results showed that YOLOv8 exhibited superior overall performance among the six algorithms. Besides, a professional software for identifying machining damage of CMCs was developed based on the optimal algorithm, and the influence of machining parameters on CMCs damages was investigated. Qualitative and quantitative evaluation results indicate that grinding speed is negatively correlated with the machining damage degree, and a higher grinding speed leads to less damages. In contrast, both feed rate and grinding depth are positively related to the machining damage. Furthermore, it is verified that the developed software is applicable to various conditions and has certain engineering application prospects.提出了一种基于深度学习的cmc加工损伤识别与定量评价方法。首先，对cmc进行磨削试验，建立加工损伤数据集;然后，利用该数据集对6种深度学习算法进行训练，并对其综合性能进行比较。结果表明，YOLOv8在6种算法中表现出较好的综合性能。基于该优化算法开发了cmc加工损伤识别专业软件，并研究了加工参数对cmc损伤的影响。定性和定量评价结果表明，磨削速度与加工损伤程度呈负相关，磨削速度越高，损伤程度越小。进给量和磨削深度与加工损伤呈正相关。验证了所开发的软件适用于各种工况，具有一定的工程应用前景。Manufacturing thick laminates using a layer by layer curing approachXiaochuan Sun, Lawrence Cook, Jonathan P-H. Belnoue, Kostas I. Tifkitsis, James Kratz, Alex A Skordosdoi:10.1016/j.compositesa.2024.108489使用一层一层固化方法制造厚层压板The work presented in this paper puts forward a manufacturing strategy for the processing of thermosetting composites based on Layer by Layer (LbL) curing. The process operates additively with sublaminates placed in a heated press, partially cured while consolidating, followed by loading of the next sublaminate and repeating the cycle until part completion. Coupled consolidation-cure simulation was utilised to design the process and establish its capabilities showing that halving the cure time is possible for thick parts. Mechanical testing showed that for pre-cure of placed layers below the gelation degree of cure, interlaminar properties are equivalent to those of conventionally manufactured material. A trial was carried out demonstrating successfully the LbL process. On-line measurements of temperature and compaction matched the predictions of the simulation, whilst the quality of the material produced is equivalent to that of conventionally produced composites.本文提出了一种基于逐层固化的热固性复合材料的制造策略。该工艺将层压板置于加热压力机中，在固化时部分固化，然后加载下一个层压板并重复此循环，直到部分完成。利用耦合固结-固化模拟来设计工艺并建立其能力，表明将厚零件的固化时间减半是可能的。力学试验表明，在胶凝度以下的预固化层中，层间性能与常规制造材料相当。进行了试验，成功地演示了LbL工艺。在线测量的温度和压实度与模拟的预测相匹配，而生产的材料质量与传统生产的复合材料相当。In-situ residual strength prediction of composites subjected to fatigue loadingAli Ebrahimi, Farjad Shamehri, Suong Van Hoadoi:10.1016/j.compositesa.2024.108490疲劳载荷下复合材料的原位残余强度预测A novel approach is introduced for in-situ residual strength prediction of glass epoxy composites subjected to fatigue loading, by integrating piezo-resistivity-based structural health monitoring with machine learning techniques. In this process, composite samples made conductive with carbon nanotubes are subjected to fatigue loading while their electrical resistance (ER) is monitored. The ER features most closely related to the residual strength are identified and used to train various machine learning algorithms. Ridge regression, K-nearest neighbor (KNN), Decision Tree (DT), Random Forest, Extreme Gradient Boosting, and Support Vector Regressor (SVR) are implemented in two different approaches: as standalone predictors, and in an ensemble learning approach to predict the residual strength. The analysis shows that the KNN meta-model within an ensemble framework, integrating DT, SVR, and KNN as base models, demonstrates superior performance, with a mean absolute percentage error of 4.7% in predicting residual strength.介绍了一种将基于压电阻率的结构健康监测与机器学习技术相结合的新方法，用于疲劳载荷下玻璃环氧复合材料的原位残余强度预测。在此过程中，用碳纳米管制备导电复合材料样品，并对其电阻进行监测。识别与残余强度最密切相关的ER特征，并用于训练各种机器学习算法。岭回归、k最近邻(KNN)、决策树(DT)、随机森林、极端梯度增强和支持向量回归(SVR)以两种不同的方法实现:作为独立预测器，以及以集成学习方法来预测剩余强度。分析表明，在集成框架内，将DT、SVR和KNN作为基本模型的KNN元模型表现出优异的性能，预测剩余强度的平均绝对百分比误差为4.7%。Composites Part B: EngineeringA short review on recent advances in automated fiber placement and filament winding technologiesStefan Carosella, Sebastian Hügle, Florian Helber, Peter Middendorfdoi:10.1016/j.compositesb.2024.111843综述了自动化纤维铺放和纤维缠绕技术的最新进展Recent advances in Automated Fiber Placement (AFP) and Filament Winding (FM) are driving steady improvements in technological understanding, enabling the production of more precise, cost- and material-efficient layups that pave the way for new applications. Evolving from automated Tape Laying Technology (ATL), AFP is a technology that not only mimics the manual laying process but also allows tailored fiber and tow alignment to deliver load-optimized patterns, stacking sequences and part structures leading to improved mechanical performance and significant waste reduction. The filament winding evolution towards automated Robotic Filament Winding put the technology in a position to manufacture highly complex lightweight structures in architecture. In this short review, recent developments in both automated fiber alignment technologies are presented and discussed, including the main advantages and materials used. Regarding the ATL and AFP process, developments in non-aerospace applications are considered. Besides a short overview of new placement technologies, advances in Tailored Fiber Placement (TFP) in the field of dry fiber placement are reported. Finally, new robotic filament winding applications in free-form and Coreless Filament Winding (CFW) in architecture are presented.自动化纤维铺放(AFP)和纤维缠绕(FM)的最新进展正在推动技术理解的稳步进步，使生产更精确，成本和材料效率更高的铺层，为新的应用铺平道路。从自动化胶带敷设技术(ATL)发展而来，AFP是一种不仅模仿人工敷设过程，而且允许定制纤维和拖曳对齐，以提供负载优化模式，堆叠顺序和零件结构，从而提高机械性能并显着减少浪费的技术。长丝缠绕向自动化机器人长丝缠绕的发展，使该技术能够制造高度复杂的轻型建筑结构。在这篇简短的综述中，介绍和讨论了两种自动光纤对准技术的最新发展，包括主要优点和使用的材料。关于ATL和AFP过程，考虑了非航空航天应用的发展。除了对新型纤维放置技术的简要概述外，还报道了干纤维放置领域中定制纤维放置(TFP)的进展。最后，介绍了机器人缠绕在自由形状和无芯缠绕中的新应用。Facile and effective construction of superhydrophobic, multi-functional and durable coatings on steel structureZhenlin Tang, Meihuan Gao, Haidi Li, Ziyang Zhang, Xinying Su, Yingge Li, Zhishuang Han, Xinmeng Lv, Jing He, Zaihang Zheng, Yan Liudoi:10.1016/j.compositesb.2024.111850 超疏水、多功能、耐用钢结构涂料的简便有效施工Nowadays, steel is one of the most significant materials in industry and daily life. Unfortunately, the defects of steel structures such as collapse at high temperature, poor corrosion resistance, and bad surface functionality have severely restricted their further application. Applying functional coatings for steel structures is considered the effective strategy for settling theses disadvantages. Inspired by nature, eco-friendly, superhydrophobic, and multifunctional-integrated coatings were fabricated on steel via one-step spraying strategy in this paper. Along with silicon dioxide (SiO2) nanoparticles and epoxy resin/silicone resin (EP/SR), the coatings are jointly constituted by hydrophobic flame retardants (M-ALHP@ZIF-8) prepared via multi-stage modification. Due to the formation of micro/nano-scaled rough structure with low surface energy, the water contact angle (WCA) and water sliding angle (WSA) of as-prepared coatings can reach 162.4° ± 1.2° and 2.8° ± 0.4°. The water repellency with low water adhesion can endow the surface of steel with excellent self-cleaning, anti-fouling, and long-lasting anti-corrosion ability. Additionally, the superhydrophobic coatings have displayed good mechanical robustness, chemical stability and weather resistance, which can exhibit certain actual values. Accorded with Zn-catalyzed charring effect of flame retardants, as-prepared coatings have possessed outstanding fire protection capacity with the lowest backside temperature of 181 °C after 1 h fire impact tests. Consequently, this work has provided a facile and effective route for synchronously tackling the key challenges of poor fire protection and surface functionality for steel structures, which will be expected to pave the wide pathway for constructing multifunctional coatings in more fields.如今，钢铁是工业和日常生活中最重要的材料之一。然而，钢结构在高温下坍塌、耐腐蚀性差、表面功能性差等缺陷严重制约了钢结构的进一步应用。在钢结构上应用功能涂层被认为是解决这些缺点的有效策略。本文以大自然为灵感，采用一步喷涂的方法在钢表面制备了环保、超疏水、多功能的一体化涂层。通过多级改性制备疏水阻燃剂(M-ALHP@ZIF-8)，与二氧化硅纳米颗粒(SiO2)和环氧树脂/硅树脂(EP/SR)共同组成涂层。由于形成了微/纳米尺度的表面能较低的粗糙结构，制备的涂层的水接触角(WCA)和水滑动角(WSA)可达到162.4°±1.2°和2.8°±0.4°。低水附着力的拒水性，使钢材表面具有优异的自洁性、防污性和持久的防腐能力。超疏水涂层具有良好的机械稳健性、化学稳定性和耐候性，具有一定的实际应用价值。与锌催化阻燃剂的炭化效果一致，经1 h的火冲击试验，所制备的涂层具有较好的防火性能，其背面温度最低为181℃。因此，这项工作为同步解决钢结构防火性能差和表面功能差的关键挑战提供了一个简单有效的途径，这将为在更多领域构建多功能涂料铺平广阔的道路。Microstructure evolution and mechanical properties of bioinspired interpenetrating Ti2AlNb/TiAl matrix composite with a crossed-lamellar structureHang Zou, Rui Hu, Mi Zhou, Zitong Gao, Xinxin Liu, Xian Luodoi:10.1016/j.compositesb.2024.111851交叉片层结构生物激发互穿Ti2AlNb/TiAl基复合材料的微观结构演变与力学性能TiAl alloys with low density, high creep resistance and high temperature performance are considered as candidate materials to replace nickel-based superalloys in the range of 700∼800 °C. However, the intrinsic brittleness of TiAl alloys has always been the biggest bottleneck restricting their development. In this paper, a bioinspired interpenetrating Ti2AlNb/TiAl composite with crossed-lamellar structure was prepared by combining selective laser melting (SLM) and vacuum hot press sintering (HPS) under the condition of 1150 °C/1 h/45 MPa, to improve the strength and toughness of the composite. Meanwhile, the metallurgical defects and microstructure of Ti2AlNb reinforcement skeleton printed under different volume energy densities (VEDs) were investigated, as well as the evolution of the microstructure at the interface region of the composite was systematically studied. What's more, we studied the mechanical properties of the composite including nanoindentation test, room temperature tensile and bending tests. The results show that the VED is 88.89 J/mm3, an almost completely dense reinforcement skeleton (∼99.8 %) is obtained. The interface region can be divided into four different reaction layers, namely LⅠ, LⅡ, LⅢ and LⅣ, due to the diffusion of elements. LⅠ is mainly composed of Othick/thin lath-like phase and O short rod-like phase. LⅡ is mainly composed of B2/β phase, acicular α2 phase and nanoscale ω-Ti3NbAl2 phase. The LⅢ mainly consists of B2/β phase. The LⅣ is composed of α2 phase. The deformability of each phase in the composite: B2/β phase > O phase >γ phase >α2 phase >ω phase. The tensile strength and fracture toughness of bioinspired interpenetrating Ti2AlNb/TiAl matrix composite are increased by 24.0 % and 89.0 %, respectively, compared with TiAl alloy, which is mainly contributed to the strong interfacial bonding between matrix and reinforcement as well as the synergistic effect of Ti2AlNb reinforcement with high strength and toughness.在700 ~ 800℃范围内，具有低密度、高抗蠕变性能和高温性能的TiAl合金被认为是替代镍基高温合金的候选材料。然而，TiAl合金的固有脆性一直是制约其发展的最大瓶颈。在1150℃/1 h/45 MPa条件下，采用选择性激光熔化(SLM)和真空热压烧结(HPS)相结合的方法制备了具有交叉层状结构的生物互穿Ti2AlNb/TiAl复合材料，提高了复合材料的强度和韧性。同时，对不同体积能量密度(VEDs)下打印的Ti2AlNb增强骨架的冶金缺陷和微观组织进行了研究，并对复合材料界面区微观组织的演变进行了系统的研究。此外，我们还研究了复合材料的力学性能，包括纳米压痕测试、室温拉伸和弯曲测试。结果表明，得到了密度为88.89 J/mm3的强化骨架(约99.8%)。由于元素的扩散作用，界面区可分为LⅠ、LⅡ、LⅢ和LⅣ四个不同的反应层。LⅠ主要由O厚/薄板条相和O短棒状相组成。LⅡ主要由B2/β相、针状α2相和纳米级ω-Ti3NbAl2相组成。LⅢ主要由B2/β相组成。LⅣ由α2相组成。复合材料中各相的变形能力表现为:B2/β相> O相>γ相>α2相>ω相。与TiAl合金相比，仿生互穿Ti2AlNb/TiAl基复合材料的抗拉强度和断裂韧性分别提高了24.0%和89.0%，这主要是由于基体与增强体之间的界面结合较强，以及Ti2AlNb增强体具有高强度和韧性的协同作用。Ablation resistance of C/C–Hf1-xZrxC composites under an oxyacetylene flame at above 2700 °CMingcong Qing, Qinchuan He, Yiqun Wang, Xuemin Yindoi:10.1016/j.compositesb.2024.111855C/C - hf1 - xzrxc复合材料在2700℃以上氧乙炔火焰下的抗烧蚀性能To the better application of C/C composites in thermal components of vehicles above 2700 °C, C/C–Hf1-xZrxC composites were prepared by CLVD, and the ablation behavior of composites was investigated. The results show that C/C–Hf0.5Zr0.5C has excellent ablation properties with linear and mass ablation rates of −0.23 μm/s and −0.31 mg/(s·cm2), respectively. ZrO2 molten phase and HfxZr1-xO2 particles are generated on the surface of C/C–Hf1-xZrxC composites during ablation. During the ablation process, defects are healed by the ZrO2 molten phase due to its mobility, which inhibits the diffusion of oxygen into the substrate. The ZrO2 molten phase is stabilized by the pinning effect of the HfxZr1-xO2 particles, which makes the ZrO2 molten phase better resistant to the scouring of the air stream. A relatively complete oxide layer is generated on the C/C–Hf0.5Zr0.5C surface, with a moderate amount of HfxZr1-xO2 exerting a pinning effect to hold the ZrO2 molten phase.为了使C/C复合材料更好地应用于2700℃以上的汽车热部件，采用CLVD法制备了C/C - hf1 - xzrxc复合材料，并对其烧蚀行为进行了研究。结果表明，C/C - hf0.5 zr0.5 C具有良好的烧蚀性能，线性烧蚀速率为- 0.23 μm/s，质量烧蚀速率为- 0.31 mg/(s·cm2)。烧蚀过程中，C/C - hf1 - xzrxc复合材料表面生成了ZrO2熔融相和HfxZr1-xO2颗粒。在烧蚀过程中，由于ZrO2熔融相的流动性，缺陷被愈合，抑制了氧向基体的扩散。HfxZr1-xO2颗粒的钉钉作用稳定了ZrO2熔融相，使ZrO2熔融相更好地抵抗气流的冲刷。在C/C - hf0.5 zr0.5 C表面形成了较为完整的氧化层，适量HfxZr1-xO2起到了固定ZrO2熔融相的作用。Prediction of Temperature and Structural Properties of Fibre-Reinforced Polymer Laminates under Simulated Fire Exposure Using Artificial Neural NetworksThomas W. Loh, Hoang T. Nguyen, Kate T.Q. Nguyendoi:10.1016/j.compositesb.2024.111858基于人工神经网络的纤维增强聚合物层压板在模拟火灾下的温度和结构性能预测Load-bearing fibre reinforced polymer laminates soften and decompose when exposed to high temperature fire which may cause significant deformation and weakening, ultimately leading to failure. A combined experimental and modelling study is presented to predict the fire structural survivability of laminates using artificial neural networks based on machine learning. Multiple experimental fire-under-tension load tests are performed under identical conditions to determine the average values and scatter to the surface temperatures, deformation rates and rupture times for an E-glass/vinyl ester laminate. A data-driven modelling strategy based on artificial neural networks is presented that can predict the temperatures and fire structural properties for the laminate when subject to combined fire exposure and tension loading. It is shown that the model gives excellent agreement to the measured surface temperatures, deformations, and time-to-failure of the laminate when exposed to one-sided heating at a constant heat flux. It is envisioned that the ANN based model could be used to assess the fire structural survivability of load-bearing composite structures exposed to fire.承载纤维增强聚合物层压板在暴露于高温火灾时会软化和分解，这可能导致严重的变形和变弱，最终导致失效。采用基于机器学习的人工神经网络对层压板火灾结构的生存能力进行了预测研究。在相同的条件下进行了多次实验火-拉载荷试验，以确定e-玻璃/乙烯基酯层压板的表面温度、变形速率和破裂时间的平均值和散射值。提出了一种基于人工神经网络的数据驱动建模策略，该策略可以预测层压板在火灾暴露和拉伸载荷联合作用下的温度和火灾结构性能。结果表明，该模型与测量的表面温度、变形和层压板在恒定热流下暴露于单面加热时的失效时间非常吻合。设想基于人工神经网络的模型可用于评估火灾下承重复合材料结构的火灾生存能力。Interfacial local activation strategy tailoring selective zinc deposition pattern for stable zinc anodesXuyang Wu, Wei Yuan, Xiaoqing Zhang, Qing Liu, Chun Wang, Lanchen Xue, Chun Li, Tengjia Gao, Simin Jiang, Bote Zhao, Yu Chen, Tingting Yu, Yong Tangdoi:10.1016/j.compositesb.2024.111860 界面局部活化策略为稳定锌阳极定制选择性锌沉积模式"Tip effect" triggered by uneven zinc deposition accelerates the growth of Zn dendrites. The unfavorable interfacial activity gradient aggravates zinc deposition at the tips, which is the root cause of zinc dendrites. This study reports an interfacial local activation strategy to reconfigure the interfacial activity gradient of zinc anode to promote more stable operation of zinc batteries. A locally activated zinc anode (Zn-ILA) is proposed as the proof-of-concept zinc anode by constructing high-active microchannels to induce preferential zinc deposition, while the remaining low-active region is accompanied by zinc epitaxial growth, thus achieving bottom-up zinc deposition at the anode interface. A fabrication method based on nanosecond pulsed laser is used to modify the zinc anode by creating high-active microchannels through thermal impingement. Additionally, low-active regions covered by dense ZnO nanoparticles are also formed due to the plasma effect. The laser-induced cross-scale oxide layers help improve the corrosion resistance at the full zinc anode interface. The proposed interfacial local activation strategy enables ordered selective deposition at the Zn-ILA interface owing to the activity gradient, as well as stabilizes the long-term operation of symmetric and full cells. The effectiveness of Zn-ILA is also validated in large-area pouch batteries, showing great potential for large-scale energy storage systems.锌沉积不均引发的“尖端效应”加速了锌枝晶的生长。不利的界面活性梯度加剧了锌在尖端的沉积，这是锌枝晶形成的根本原因。本研究报告了一种界面局部激活策略，以重新配置锌阳极的界面活性梯度，以促进锌电池更稳定的运行。提出了一种局部活化锌阳极(Zn-ILA)作为概念验证锌阳极，通过构建高活性微通道诱导优先锌沉积，而剩余的低活性区域伴随锌外延生长，从而在阳极界面实现自下而上的锌沉积。采用基于纳秒脉冲激光的制备方法，通过热冲击形成高活性微通道，对锌阳极进行修饰。此外，由于等离子体效应，还形成了被致密ZnO纳米颗粒覆盖的低活性区域。激光诱导的跨尺度氧化层有助于提高全锌阳极界面的耐腐蚀性。所提出的界面局部激活策略由于活性梯度使得锌- ila界面上的有序选择性沉积成为可能，同时也稳定了对称电池和满电池的长期运行。锌- ila的有效性也在大面积袋状电池中得到验证，显示出大规模储能系统的巨大潜力。Composites Science and TechnologyAdvancing Structural Health Monitoring: Deep Learning-Enhanced Quantitative Analysis of Damage in Composite Laminates Using Surface Strain FieldShiyu Li, Xuanxin Tian, Qiubo Li, Shigang Aidoi:10.1016/j.compscitech.2024.110880 推进结构健康监测:基于表面应变场的深度学习增强复合材料层合板损伤定量分析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 millimeters. 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.复合材料由于其优异的性能特点，已广泛应用于航空航天领域的关键部件。复合材料结构中各种损伤类型的实时准确识别和量化是一个重大挑战。本文提出了一种基于应变场的损伤检测方法，该方法主要采用深度学习技术。利用rs - mask R-CNN，本研究准确地检测和分类复合材料层压板内的各种形式的损伤，包括开孔、地下孔和分层。此外，该方法还可以精确定位和量化受损区域。一系列的实验和仿真验证了该网络模型的准确性和鲁棒性。损伤反演实验表明，损伤区域的面积误差减小到7.4%，位置误差不超过3.31 mm。在模拟场景中，复杂损伤轮廓的形状上下文距离不超过0.21，表明损伤的关键几何特征被成功保留。该研究为复合材料层合板的损伤检测和结构健康实时监测提供了有效的新方法。来源：复合材料力学仿真Composites FEM
