今日更新：Composite Structures 1 篇，Composites Part A: Applied Science and Manufacturing 1 篇，Composites Part B: Engineering 5 篇，Composites Science and Technology 3 篇Composite StructuresReliability-based multi-objective optimization design of composite patch repair structure using artificial neural networksYubo Zhao, Shanyong Xuan, Yuan Wang, Yongbin Li, Xuefeng Yaodoi:10.1016/j.compstruct.2024.118692基于人工神经网络的复合贴片修复结构可靠性多目标优化设计Due to the parameter differences and the existence of random factors, the performance of composite repair structure shows a large dispersion. In order to obtain stronger, lighter and more reliable repair structure, multi-objective optimization design of carbon fiber reinforced polymers (CFRP) laminate repair structure is investigated by combining the reliability theory, artificial neural networks and the genetic algorithm. First, a 3D simulation model of the composite laminate patch repair structures is established using the 3D Hashin criterion and the cohesive region model. Then, the Latin Hypercube sampling (LHS) method is used to realize the random sampling, and the strength proxy model of the repair structure is established by using Back-propagation artificial neural network, further a multi-objective optimization model with tensile strength, reliability and weight as objective functions is built considering the design parameters and the random parameters. Finally, NSGAⅡalgorithm is used to solve the multi-objective optimization problem, and a set of solutions on the Pareto front surface are obtained, also the optimal design parameters of the composite repair structure meets the requirements is obtained.由于参数的差异和随机因素的存在，复合修复结构的性能表现出较大的分散性。为了获得更强、更轻、更可靠的修复结构，将可靠性理论、人工神经网络和遗传算法相结合，研究了碳纤维增强聚合物（CFRP）层压修复结构的多目标优化设计。首先，利用三维哈辛准则和内聚区域模型建立了复合材料贴片修复结构的三维仿真模型；然后，采用拉丁超立方体抽样（LHS）方法实现随机抽样，利用反向传播人工神经网络建立了修复结构的强度代理模型，进而考虑设计参数和随机参数，建立了以抗拉强度、可靠性和权重为目标函数的多目标优化模型。最后，利用NSGAⅡ算法求解多目标优化问题，得到了Pareto前曲面上的一组解，得到了复合修复结构满足要求的最优设计参数。Composites Part A: Applied Science and ManufacturingTi3SiC2 MAX phase modified SiCf/SiC composites with high strength and thermal conductivity prepared by low-temperature reactive melt infiltrationWenjie Zhu, Yujie Wang, Yuwei Ren, Minghang Li, Yichun Bi, Ce Zheng, Xiaoqiang Lidoi:10.1016/j.compositesa.2024.108577低温反应熔体渗透法制备高强度、高导热的Ti3SiC2 MAX相改性SiCf/SiC复合材料High-purity Ti3SiC2 MAX phase was introduced into the Amosic 3–303 SiC fiber-reinforced SiC matrix composite as a modified matrix by Reaction Melt Infiltration (RMI) at 1250 ℃, realizing the generation of high-purity Ti3SiC2 phase without residual melt and by-products in the RMI matrix. This modification reduced the porosity of the SiCf/SiC-Ti3SiC2 composite from 10 to 20% typically found in SiCf/SiC composite prepared by Chemical Vapor Infiltration (CVI) to 6%, and the densification process cycle time by 70%. The flexural strength and thermal conductivity were enhanced by 12% and 58%, respectively. The microstructure and phase evolution of Ti3SiC2 in the SiCf/SiC composite matrix was systematically investigated, offering new insights into the ceramic matrix growth process during RMI. This work proposes a new method for utilizing the RMI process to prepare high-performance nuclear SiCf/SiC-based composites.在1250℃下，通过反应熔体渗透（RMI）将高纯Ti3SiC2 MAX相作为改性基体引入到Amosic 3-303 SiC纤维增强SiC基复合材料中，实现了在RMI基体中无残余熔体和副产物的高纯Ti3SiC2相的生成。该改性将SiCf/SiC- ti3sic2复合材料的孔隙率从化学气相渗透（CVI）法制备的SiCf/SiC复合材料的孔隙率从10%降至20%至6%，致密化周期时间缩短了70%。抗弯强度和导热系数分别提高了12%和58%。系统地研究了SiCf/SiC复合基体中Ti3SiC2的微观结构和相演化，为RMI过程中陶瓷基体的生长过程提供了新的见解。本文提出了一种利用RMI工艺制备高性能核SiCf/ sic基复合材料的新方法。Composites Part B: EngineeringElectrostatically connected Fe2O3@Ni-MOF nanosheet array heterojunction for high-performance light-assisted zinc-air batteriesJiangchang Chen, Ze Liu, Kaiyong Feng, Fengjun Deng, Yingjian Yudoi:10.1016/j.compositesb.2024.111936 用于高性能光辅助锌空气电池的静电连接Fe2O3@Ni-MOF纳米片阵列异质结Using sunlight to accelerate the sluggish redox reaction at the cathode of zinc-air batteries is an effective strategy. Fe2O3 nanoclusters have excellent photovoltaic properties. However, the photocatalytic redox activity of single Fe2O3 is generally low because of severe charge recombination and insufficient redox catalytic sites. Herein, a Fe2O3@Ni-MOF nanosheet array (NA) composite exposing abundant Fe2O3 nanoclusters was designed and prepared for accelerating photocatalytic oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). It was demonstrated that the Fe2O3@Ni-MOFNA heterojunction composites possessed a staggered S-type heterojunction that promoted charge separation and transfer under illumination. Theoretical calculations showed that Fe2O3@Ni-MOFNA composites had lower reaction free energies compared with the pristine component. Furthermore, the zinc-air battery yielded an output voltage of 1.76 V over the theoretical value and a round-trip efficiency of 98% under illumination. This work provides a strategy for utilizing solar energy and developing light-assisted zinc-air batteries.利用阳光加速锌空气电池阴极缓慢的氧化还原反应是一种有效的方法。Fe2O3纳米团簇具有优异的光伏性能。然而，由于严重的电荷重组和氧化还原催化位点不足，单一Fe2O3的光催化氧化还原活性普遍较低。本文设计并制备了一种含有丰富Fe2O3纳米团簇的Fe2O3@Ni-MOF纳米片阵列（NA）复合材料，用于加速光催化氧还原反应（ORR）和析氧反应（OER）。结果表明，Fe2O3@Ni-MOFNA异质结复合材料具有交错s型异质结，在光照下促进了电荷的分离和转移。理论计算表明，与原始组分相比，Fe2O3@Ni-MOFNA复合材料具有较低的反应自由能。此外，锌空气电池的输出电压比理论值高出1.76 V，在照明下的往返效率为98%。这项工作为利用太阳能和光辅助锌空气电池的发展提供了一种策略。3d printing of a continuous carbon fiber reinforced bronze-matrix composite using material extrusionMehrdad Mousapour, S Siddharth Kumar, Jouni Partanen, Mika Salmidoi:10.1016/j.compositesb.2024.1119613d打印连续碳纤维增强青铜基复合材料的材料挤压The main objective of this study is to investigate, for the first time, the feasibility of 3d printing a continuous carbon fiber (CCF) reinforced metal matrix composite using a cost-effective material extrusion (MEX) technology. Notably, this paper presents a detailed analysis of the microstructure and mechanical and physical properties of a bronze matrix composite reinforced with CCF. The results reveal that CCF significantly impedes the expected densification levels of the composite's structure, causing extensive gaps between the bronze particles. However, despite the high porosity level, the composite's electrical conductivity remains relatively high, demonstrating the limited negative impact of the CCF material on the composite's conductivity. Moreover, mechanical evaluations were performed through 3-point bending and tensile tests, highlighting the composite material's advantages and limitations. The results show that the composite material exhibits an improved yield stress of 76 %, increased ultimate tensile strength of 20 %, and an extended fracture strain of 30 %. However, the flexural strength decreases by 23% due to the presence of massive gaps formed by CCF.本研究的主要目的是首次研究使用具有成本效益的材料挤压（MEX）技术3d打印连续碳纤维（CCF）增强金属基复合材料的可行性。值得注意的是，本文详细分析了CCF增强青铜基复合材料的显微组织和力学物理性能。结果表明，CCF显著阻碍了复合材料结构的预期致密化水平，导致青铜颗粒之间存在广泛的间隙。然而，尽管具有较高的孔隙率，但复合材料的电导率仍然相对较高，这表明CCF材料对复合材料电导率的负面影响有限。此外，通过三点弯曲和拉伸试验进行力学评估，突出了复合材料的优点和局限性。结果表明，复合材料的屈服应力提高了76%，极限抗拉强度提高了20%，扩展断裂应变提高了30%。然而，由于CCF形成的大量间隙的存在，抗弯强度降低了23%。A validated simulation methodology for determining single lap shear allowable strength in thermoplastic polymer compositesJ. Ninyerola Gavaldà, I.R. Cózar, J.M. Guerrero, S. Abdel-Monsef, A. Sasikumar, A. Turondoi:10.1016/j.compositesb.2024.111909一种确定热塑性聚合物复合材料单搭接剪切许用强度的有效模拟方法While several modeling approaches exist to simulate the strength of single lap shear configurations, their application to obtaining design allowables for thermoplastic composites remains underexplored. This paper addresses this gap by presenting a novel methodology for the forward propagation of parameter uncertainty using advanced finite element models specifically tailored for thermoplastic carbon fiber composites. The proposed approach goes beyond traditional methods by integrating advanced damage models and a structured validation process, supported by an extensive experimental test campaign.We demonstrate the feasibility of determining design allowables through simulation by examining the influence of batch size on both the validation process and the prediction of allowable strength. Our findings provide new insights into the propagation of uncertainties in the context of composite material design, showing that it is possible to achieve reliable design allowables through simulation, which can significantly accelerate the development of new components while maintaining high safety standards.虽然存在几种模拟单搭接剪切结构强度的建模方法，但它们在获得热塑性复合材料设计许用值方面的应用仍未得到充分探索。本文通过使用专门为热塑性碳纤维复合材料量身定制的先进有限元模型，提出了一种新的参数不确定性前向传播方法，从而解决了这一差距。该方法超越了传统方法，集成了先进的损伤模型和结构化的验证过程，并得到了大量实验测试活动的支持。我们通过研究批大小对验证过程和允许强度预测的影响，通过模拟来证明确定设计允许值的可行性。我们的研究结果为复合材料设计中不确定性的传播提供了新的见解，表明通过模拟可以实现可靠的设计允许值，这可以显着加速新组件的开发，同时保持高安全标准。Linear viscoelasticity of anisotropic carbon fibers reinforced thermoplastics: From micromechanics to dynamic torsion experimentsThomas C. Merlette, Julie Dianidoi:10.1016/j.compositesb.2024.111931 各向异性碳纤维增强热塑性塑料的线性粘弹性：从微观力学到动态扭转实验The link between experimental characterization and the constitutive behavior of an anisotropic linear viscoelastic unidirectional carbon fiber-reinforced thermoplastic composite is explored using micromechanics modeling. Dynamic torsion tests were conducted at 1 Hz over a wide temperature range, from the glassy to the rubbery states of the polymeric matrix, on both the pure matrix and the composite, for various cutting angles relative to the fibers. A two-step modeling procedure in the frequency domain is presented to predict and validate the effective behavior of the composite. The first step involves FFT-based homogenization, which maps the microstructure and constituent behaviors to effective transversely isotropic viscoelastic properties. The second step consists of finite element simulations using the effective behavior calculated from homogenization as input to replicate the experiments. A comparison between experimental results and model predictions across the entire temperature range is performed. The modeling predictions show good accuracy at low temperatures, where the matrix is in the glassy state. At high temperatures, where the matrix is in the rubbery state, the predicted behavior becomes too soft. As the phase contrast increases and the ratio of matrix bulk modulus to shear modulus rises significantly, the impact of fiber arrangement on the effective properties becomes more pronounced.利用细观力学模型探讨了各向异性线性粘弹性单向碳纤维增强热塑性复合材料的实验表征与本构行为之间的联系。在较宽的温度范围内，从聚合物基体的玻璃态到橡胶态，在纯基体和复合材料上，对相对于纤维的各种切割角度，在1 Hz的频率下进行动态扭转测试。提出了一种两步频域建模方法来预测和验证复合材料的有效性能。第一步是基于fft的均质化，将微观结构和组分行为映射为有效的横向各向同性粘弹性。第二步由有限元模拟组成，利用均质化计算的有效行为作为输入来复 制实验。在整个温度范围内，对实验结果和模型预测结果进行了比较。模型预测在低温下具有良好的准确性，此时基体处于玻璃态。在高温下，当基体处于橡胶状态时，预测的行为会变得太软。随着相衬增大，基体体积模量与剪切模量之比显著增大，纤维排列方式对有效性能的影响更加明显。Coupling Thermodynamic Modelling with Experimental Study to Reveal the Evolutionary Relationship of Pore Solutions, Products, and Compressive Strength for Lunar Regolith Simulant GeopolymersGuangjie Xue, Guofu Qiaodoi:10.1016/j.compositesb.2024.111949耦合热力学模型与实验研究揭示月球风化层模拟地聚合物孔隙溶液、产物和抗压强度的演化关系Alkali-activation is a highly promising approach for the in situ resource utilisation (ISRU) of lunar regoliths. However, the considerable variation in the composition of lunar regolith simulants can complicate the optimal design of geopolymer mixture ratios, necessitating an in-depth analysis of composition–performance correlations. This study proposes a calculation method that couples thermodynamic modelling with an experimental study to reveal the evolutionary relationship between the pore solution, product formation, and compressive strength. The results indicate that the modulus and dosage of the alkali activator can substantially change the relative content of reactive elements in the pore solution and affect the product type and content. Among these, [Si] and [Al] in the pore solution and gel production are key factors affecting the compressive strength of geopolymers. Understanding these composition–performance relationships is critical for offering essential guidance for performance-based, on-demand material design and optimisation.碱活化是一种很有前途的月球风化岩就地资源利用方法。然而，月球风化层模拟物成分的巨大变化可能使地聚合物混合比例的优化设计复杂化，因此需要深入分析成分与性能的相关性。本文提出了一种热力学模拟与实验研究相结合的计算方法，揭示了孔隙溶解、产物形成和抗压强度之间的演化关系。结果表明，碱活化剂的模量和用量可以显著改变孔隙溶液中活性元素的相对含量，影响产物的种类和含量。其中孔隙溶液中的[Si]和[Al]是影响地聚合物抗压强度的关键因素。理解这些成分-性能关系对于提供基于性能的、按需材料设计和优化的基本指导至关重要。Composites Science and TechnologySymmetric sandwich–like rubber composites for “green” electromagnetic interference shielding and thermal insulationZijian Wei, Yu Cheng, Yanran Sun, Yanhu Zhan, Yanyan Meng, Yuchao Li, Hesheng Xia, Xiancai Jiangdoi:10.1016/j.compscitech.2024.110960 对称的三明治状橡胶复合材料，用于“绿色”电磁干扰屏蔽和隔热Electromagnetic interference (EMI) shielding rubber composites with thermally insulating properties are necessary for some specific sealing fields, but their fabrication is challenging because it is difficult to realize a balance between high electrical conductivity and low thermal conductivity. Herein, symmetric sandwich–like rubber composites composed of an unfoamed core sandwiched by two foamed layers were prepared using a layer-by-layer vulcanization procedure. Importantly, a segregated Fe3O4@carbon nanotube (Fe3O4@CNT) network was constructed within the entire composite. This structure improved the shielding effectiveness (SE) and decreased the thermal conductivity of Fe3O4@CNT/rubber composites. When the density of the foamed layers was 0.60 g/cm3, the thermal conductivity, electrical conductivity, and SE of the resultant composites were 0.14 W/m K, 21.5 S/m, and 40.7 dB, respectively, and their green index (gs) was 2.13, implying that the prepared materials were “green” EMI-shielding composites. This study provides directions on fabricating EMI shielding materials with thermally insulating performance.具有隔热性能的屏蔽电磁干扰（EMI）橡胶复合材料在某些特定的密封领域是必需的，但其制造具有挑战性，因为难以实现高导电性和低导热性之间的平衡。本文采用逐层硫化方法制备了由两层泡沫层夹心的非发泡芯组成的对称三明治状橡胶复合材料。重要的是，在整个复合材料中构建了一个分离的Fe3O4@carbon纳米管（Fe3O4@CNT）网络。该结构提高了Fe3O4@CNT/橡胶复合材料的屏蔽效能（SE），降低了其导热系数。当泡沫层密度为0.60 g/cm3时，复合材料的导热系数、电导率和SE分别为0.14 W/m K、21.5 S/m和40.7 dB，绿色指数(gs)为2.13，说明制备的材料为“绿色”电磁屏蔽复合材料。本研究为制备具有隔热性能的电磁干扰屏蔽材料提供了方向。A novel Taguchi-based approach for optimizing neural network architectures: application to elastic short fiber compositesMohammad Hossein Nikzad, Mohammad Heidari-Rarani, Mohsen Mirkhalafdoi:10.1016/j.compscitech.2024.110951 一种新的基于田口的神经网络结构优化方法：在弹性短纤维复合材料中的应用This study presents an innovative application of the Taguchi design of experiment method to optimize the structure of an Artificial Neural Network (ANN) model for the prediction of elastic properties of short fiber reinforced composites. The main goal is to minimize the computational effort required for hyperparameter optimization while enhancing the prediction accuracy. By utilizing a robust experimental design framework, the structure of an ANN model is optimized. This approach involves identifying a combination of hyperparameters that provides optimal predictive accuracy with the fewest algorithmic runs, thereby significantly reducing the required computational effort. The results suggested that the Taguchi-based developed ANN model with three hidden layers, 20 neurons in each hidden layer, elu activation function, Adam optimizer, and a learning rate of 0.001 can predict the anisotropic elastic properties of short fiber reinforced composites with a prediction accuracy of 97.71%. Then, external validation of the proposed ANN model was done using experimental data, and differences of less than 10% were obtained, indicating an appropriate predictive performance of the proposed ANN algorithm. Our findings demonstrate that the Taguchi method not only streamlines the hyperparameter tuning process but also substantially improves the algorithm's performance. These results highlight the potential of the Taguchi method as a powerful tool for optimizing machine learning algorithms, especially in scenarios where computational resources are limited. The implications of this study are far-reaching, offering insights for future research in the optimization of different algorithms for improved accuracies and computational efficiencies.本研究创新性地应用田口设计的实验方法，优化了短纤维增强复合材料弹性性能预测的人工神经网络（ANN）模型的结构。主要目标是在提高预测精度的同时最小化超参数优化所需的计算量。利用鲁棒实验设计框架，优化了人工神经网络模型的结构。这种方法涉及识别超参数的组合，以最少的算法运行提供最佳的预测精度，从而显着减少所需的计算工作量。结果表明，基于taguchi的人工神经网络模型具有3个隐层，每个隐层20个神经元，采用elu激活函数和Adam优化器，学习速率为0.001，可以预测短纤维增强复合材料的各向异性弹性性能，预测准确率为97.71%。然后，利用实验数据对所提出的人工神经网络模型进行外部验证，得到的误差小于10%，表明所提出的人工神经网络算法具有适当的预测性能。研究结果表明，田口方法不仅简化了超参数调谐过程，而且大大提高了算法的性能。这些结果突出了田口方法作为优化机器学习算法的强大工具的潜力，特别是在计算资源有限的情况下。本研究的意义是深远的，为未来研究不同算法的优化提供了见解，以提高准确性和计算效率。Internal shear damage evolution of CFRP laminates ranging from -100°C to 100°C using in-situ X-ray computed tomographyYingxue Bai, Zeang Zhao, Shengyu Duan, Panding Wang, Yuanchen Li, Hongshuai Leidoi:10.1016/j.compscitech.2024.110959 在-100°C至100°C范围内使用原位x射线计算机断层扫描CFRP层合板的内部剪切损伤演化Carbon Fiber Reinforced Polymer (CFRP) composites have been widely used in aerospace due to their high specific stiffness, strength, and fatigue properties. However, the ambient temperature significantly influences CFRP’s mechanical properties and damage evolution, deriving from the temperature effect on the microstructural behavior and the mesoscopic damage evolution. In this study, the temperature-dependent in-plane shear failure behavior of CFRP composites was investigated. In-situ X-ray Computed tomography (CT) tensile experiments of laminates ([45°/-45°]2s) at RT, -100°C, and 100°C were carried out to study the in-plane shear failure mechanisms. The 3D fracture morphology was extracted with internal damage evolution process estimated and quantified. The in-situ 3D deformation fields of critical regions were acquired using the Digital Volume Correlation (DVC) method. The effect of temperature on strain field and the correlation between the high-strain region and the fracture location were analyzed. The results revealed the temperature correlations and failure mechanisms of CFRP’s mechanical characteristics and internal damage evolution process. Compared to room temperature (RT), the delamination damage area of the sample increased by 80% at 100°C. Meanwhile, the shear modulus of CFRP decreases by 78.4% from -100°C to 100°C, and the fracture strain increases by 98% from RT to 100°C. The DVC results indicated a dispersion of high-strain regions at -100°C, reflecting the brittle damage characteristics, while an extensive ductile deformation region was captured at 100°C. Fiber-matrix debonding is the dominant failure mode of composites under shear loading, whereas significant matrix cracking was observed at -100°C and partial fiber pullout occurred at 100°C.碳纤维增强聚合物（CFRP）复合材料具有高比刚度、强度和抗疲劳性能，在航空航天领域得到了广泛的应用。然而，环境温度对CFRP的力学性能和损伤演化有显著的影响，这源于温度对CFRP微观结构行为和细观损伤演化的影响。本文研究了CFRP复合材料的面内剪切破坏行为。对层合板（[45°/-45°]2s）在室温、-100℃和100℃下的原位x射线计算机断层扫描（CT）拉伸实验进行了面内剪切破坏机制的研究。提取三维断裂形态，对内部损伤演化过程进行估计和量化。采用数字体积相关（DVC）方法获得了关键区域的原位三维变形场。分析了温度对应变场的影响以及高应变区与断口位置的相关性。研究结果揭示了碳纤维布力学特性和内部损伤演化过程的温度相关性、破坏机制。与室温（RT）相比，在100℃时，样品的分层损伤面积增加了80%。同时，从-100℃到100℃，CFRP的剪切模量下降了78.4%，从RT到100℃，断裂应变增加了98%。DVC结果表明，在-100°C时，高应变区分散，反映了脆性损伤特征，而在100°C时，则捕捉到广泛的韧性变形区。纤维-基体脱粘是复合材料在剪切载荷下的主要破坏模式，而在-100°C时观察到明显的基体开裂，在100°C时发生部分纤维拔出。来源：复合材料力学仿真Composites FEM
