【新文速递】2024年6月26日复合材料SCI期刊最新文章

   

今日更新：Composite Structures 4 篇，Composites Part A: Applied Science and Manufacturing 1 篇，Composites Part B: Engineering 1 篇，Composites Science and Technology 1 篇

Composite Structures

A mode localization inspired vibration control method based on the axially functionally graded design for beam structures

Xiao Mi, Zhiguang Song

doi:10.1016/j.compstruct.2024.118300

基于梁结构轴向功能分级设计的模态定位启发振动控制方法

Vibration control plays a vital role in engineering structures, especially for low-frequency range, because designing structures with small dimensions makes it difficult to control large-wavelength vibrations. The present study seeks another road to realize low-frequency vibration control from the view of the real vibration responses. Similar to mode shapes, deflection modes are the main distributions of vibration amplitudes on structures in low frequency. Therefore, they are also essential vibration characteristics of structures. This paper proposes an effective passive vibration control method under both non-resonant and resonant excitations based on deflection mode theory and optimal algorithm. In fact, it is just like an axially functionally graded design for structures. The equations of motion for non-uniform beam structures are formulated by Hamilton’s principle. Firstly, a desired deflection mode is artificially designed, and the beam structure is discretely divided into subunits. Then, by adjusting the thickness or elastic modulus of each subunit to make the deflection mode of the beam coincide with that of the desired one. This process is completed by the genetic algorithm (GA). After that, by experimental and simulation analyses, the deflection mode of the optimally designed beam structures coincides with that of the desired one. Therefore, the present vibration control method is verified to be correct and effective.

振动控制在工程结构中起着至关重要的作用，尤其是在低频范围内，因为设计尺寸小的结构很难控制大 波长振动。本研究从真实振动响应的角度出发，寻求实现低频振动控制的另一条道路。与模态振型类似，挠度模态是结构低频振动振幅的主要分布。因此，它们也是结构的基本振动特性。本文基于挠度模态理论和最优算法，提出了一种在非共振和共振激励下的有效被动振动控制方法。事实上，这就如同结构的轴向功能分级设计。非均匀梁结构的运动方程是根据汉密尔顿原理制定的。首先，人为设计出所需的挠曲模式，并将梁结构离散地划分为若干子单元。然后，通过调整每个子单元的厚度或弹性模量，使梁的挠曲模式与所需模式相吻合。这一过程由遗传算法（GA）完成。之后，通过实验和模拟分析，优化设计的梁结构的挠曲模式与所需模式一致。因此，验证了本振动控制方法的正确性和有效性。

Geometrically nonlinear bending analysis of laminated thin plates based on classical laminated plate theory and deep energy method

Zhong-Min Huang, Lin-Xin Peng

doi:10.1016/j.compstruct.2024.118314

基于经典层压板理论和深能量法的层压薄板几何非线性弯曲分析

This paper establishes a geometrically nonlinear bending analysis framework using the deep energy method and the classical laminated plate theory (CLPT) for laminated plates. Inspired by the transfer learning technique, a load applied to a laminated plate can be divided into multiple load steps. The network parameters for the current load step, with the exception of the initial step, are initialized by inheriting values from their preceding steps. Including both von Kármán and Green-Lagrange strains, the plate strains are computed using the automatic differentiation and integrated along the thickness direction per laminate plate based on the constitutive theory. By combining the outputs of neural network, the external potential energy can be obtained, and the optimized network parameters are given by minimizing the total system potential energy of the laminated plate. In order to validate the proposed approach, several numerical examples are calculated, and the present solutions are compared with those given by the literature and the Finite Element Analysis (FEA). The results show that the proposed approach is indeed feasible, can reach high levels of precision under varying loads while offering a simplified calculation strategy.

本文利用深能量法和经典层压板理论（CLPT）为层压板建立了一个几何非线性弯曲分析框架。受迁移学习技术的启发，施加在层压板上的载荷可分为多个载荷步骤。当前负载步骤的网络参数（初始步骤除外）通过继承前一步骤的值进行初始化。包括 von Kármán 应变和格林-拉格朗日应变在内的板应变是通过自动微分计算得出的，并根据构成理论沿厚度方向对每个层压板进行积分。结合神经网络的输出，可以得到外部势能，并通过最小化层压板的总系统势能给出优化的网络参数。为了验证所提出的方法，计算了几个数值实例，并将目前的解决方案与文献和有限元分析（FEA）给出的解决方案进行了比较。结果表明，所提出的方法确实可行，能在不同载荷下达到很高的精度，同时提供了一种简化的计算策略。

Real-time shape sensing of large-scale honeycomb antennas with a displacement-gradient-based variable-size inverse finite element method

Tianyu Dong, Shenfang Yuan, Tianxiang Huang

doi:10.1016/j.compstruct.2024.118320

利用基于位移梯度的可变尺寸反有限元法对大型蜂窝天线进行实时形状传感

Real-time thermal deformation monitoring plays a crucial role in calibrating phase signals and maintaining satellite performance for large spaceborne antennas. The inverse finite element method (iFEM) represents a promising shape-sensing methodology applicable to monitor the three-dimensional displacement of structures through surface-measured strain. However, the high-accuracy reconstruction of large-scale structures involves a large number of inverse elements, which leads to the low level of computational efficiency. To address this issue, a displacement-gradient-based variable-size iFEM is proposed in this paper. According to the characteristics of deformation, this method optimizes the size of each inverse element to reduce the number of inverse elements required, which improves real-time performance and maintains the high accuracy of reconstruction. The real-time performance of the proposed method is verified by conducting a simulation test on a large-scale honeycomb antenna. According to the simulation results, the variable-size iFEM is applicable to achieve the same accuracy of reconstruction using fewer inverse elements than conventional iFEM. An experimental test is performed and the optimal variable-size discretization that balances accuracy and efficiency is determined. The results show that the maximum error of reconstructed displacement is less than 7.3 % and the reconstruction time is in no excess of 0.1 s.

实时热变形监测在校准相位信号和保持大型星载天线的卫星性能方面发挥着至关重要的作用。反有限元法（iFEM）是一种很有前途的形状传感方法，适用于通过表面测量应变来监测结构的三维位移。然而，大规模结构的高精度重建涉及大量反演元素，导致计算效率低下。针对这一问题，本文提出了一种基于位移梯度的可变尺寸 iFEM。该方法根据变形的特点，优化每个反演元素的大小，以减少所需的反演元素数量，从而提高了实时性，并保持了较高的重建精度。通过在大型蜂巢天线上进行仿真测试，验证了所提方法的实时性。仿真结果表明，与传统的 iFEM 相比，可变尺寸 iFEM 可以用较少的反演元素达到相同的重构精度。实验测试确定了兼顾精度和效率的最佳可变尺寸离散度。结果表明，重建位移的最大误差小于 7.3%，重建时间不超过 0.1 秒。

Effect of TiC particle size on the microstructure and properties of CuCr-TiC composites manufactured by powder metallurgy

Xiukuang Zhang, Qian Lei, Xiangyue Meng, Xueying Cao, Jie Yin, Shuang Zhou, Xiaoyan Zhang, Yanlin Jia

doi:10.1016/j.compstruct.2024.118323

TiC 粒径对粉末冶金制造的 CuCr-TiC 复合材料微观结构和性能的影响

Poor thermal stability limits the application of CuCr alloys at high temperatures. In this work, non-stoichiometric TiC particles (7 vol%) reinforced CuCr matrix composites were fabricated. The effects of TiC powders with different particle size (1 μm, 2 μm, 4 μm) on the microstructure and properties were studied. The diffusion of supersaturated Ti atoms induced the formation of Cu (Ti) solid solution transition layer at the interface, which improved the interface bonding. Dislocations caused by thermal mismatch promoted heterogeneous nucleation, which led to the precipitation of coarse Cr clusters. The strength and plasticity of composites increased with the reduction of TiC particle size. Strengthening and fracture mechanisms were discussed, and the strength difference was mainly attributed to thermal mismatch strengthening. Meanwhile, TiC particles refined the matrix grains and improved the activation energy of grain growth. The strength and softening temperature of CuCr alloy were 520 MPa and 540 °C, while that of CuCr-1TiC composite were 530 MPa and 915 °C. CuCr-TiC composites displayed much superior thermal stability than the CuCr alloy. These findings provide practical approaches for developing particle-reinforced copper matrix composites with excellent interfacial bonding and thermal stability.

热稳定性差限制了铜铬合金在高温下的应用。在这项工作中，制备了非共沸态 TiC 颗粒（7 vol%）增强 CuCr 基复合材料。研究了不同粒度（1 μm、2 μm、4 μm）的 TiC 粉末对微观结构和性能的影响。过饱和 Ti 原子的扩散在界面上形成了 Cu（Ti）固溶体过渡层，从而改善了界面结合。热失配引起的位错促进了异质成核，从而导致粗大的铬团块析出。复合材料的强度和塑性随着 TiC 粒径的减小而增加。对强化和断裂机制进行了讨论，强度差异主要归因于热错配强化。同时，TiC 颗粒细化了基体晶粒，提高了晶粒生长的活化能。CuCr 合金的强度和软化温度分别为 520 MPa 和 540 ℃，而 CuCr-1TiC 复合材料的强度和软化温度分别为 530 MPa 和 915 ℃。CuCr-TiC 复合材料的热稳定性远远优于 CuCr 合金。这些发现为开发具有优异界面结合力和热稳定性的颗粒增强铜基复合材料提供了实用方法。

Composites Part A: Applied Science and Manufacturing

Structure-performance relationship of polypropylene/elastomer/carbon black composites as high voltage cable shielding layer

Xiyu Zhang, Shixun Hu, Shangshi Huang, Yuxiao Zhou, Wenjia Zhang, Changlong Yang, Chi Yao, Xinhua Dong, Qi Zhang, Mingti Wang, Jun Hu, Qi Li, Jinliang He

doi:10.1016/j.compositesa.2024.108334

聚丙烯/弹性体/炭黑复合材料作为高压电缆屏蔽层的结构性能关系

As polypropylene (PP) is a competitive insulating material for next generation high-voltage cable, the corresponding PP based cable semi-conductive shielding layer material needs to be developed. This paper developed an excellent material prescription and proposed an analytical method of structure-performance relationship for the application and the evaluation of PP-based cable shielding layer. First, PP/POE/CB and PP/SEBS/CB composites with different carbon black (CB) loading were prepared and their electrical and mechanical properties were compared. Through thermal analysis technique, crystalline property and thermal stability of the composites were studied in detail. And the synchrotron radiation X-ray scattering techniques were employed to analyze the distribution of carbon black in the blend semi-quantitatively. The analysis result turns out the enrichment of carbon black in POE phase and its instability at high temperature limits its application under cable operation conditions. In contrast, PP/SEBS/CB30phr is recommended for lower thermal deformation, lower PTC effect and better mechanical parameters.

聚丙烯（PP）是下一代高压电缆具有竞争力的绝缘材料，因此需要开发相应的聚丙烯基电缆半导电屏蔽层材料。本文为聚丙烯基电缆屏蔽层的应用和评价开发了一种优良的材料处方，并提出了结构性能关系的分析方法。首先，制备了不同炭黑（CB）含量的 PP/POE/CB 和 PP/SEBS/CB 复合材料，并比较了它们的电气和机械性能。通过热分析技术，详细研究了复合材料的结晶特性和热稳定性。并采用同步辐射 X 射线散射技术对混合材料中炭黑的分布进行了半定量分析。分析结果表明，炭黑在 POE 相中的富集及其在高温下的不稳定性限制了其在电缆运行条件下的应用。相比之下，PP/SEBS/CB30phr 具有更低的热变形、更低的 PTC 效应和更好的机械参数，因此值得推荐使用。

Composites Part B: Engineering

Structural-functional Integrated TiBw/Ti-V-Al Lightweight Shape Memory Alloy Composites

Kuishan Sun, Bin Sun, Hao Li, Xiaoyang Yi, Xianglong Meng, Zhiyong Gao, Wei Cai

doi:10.1016/j.compositesb.2024.111648

结构功能一体化 TiBw/Ti-V-Al 轻质形状记忆合金复合材料

Driven by the increasing demands in advanced aerospace engineering, the integrated structural and functional materials are explored. In present study, we fabricate the TiBw/Ti-V-Al lightweight shape memory alloy composites with large recoverable strain (> 5%), high specific strength (> 200 MPa·cm3/g) and good elongation (> 20%). The satisfied structural and functional performances are attributed to the unique gradient microstructure, including TiB whiskers, short-range martensitic nanodomains and long-range martensitic microdomains. TiBw with the optimized orientation exhibits high load-bearing capacity. The transition area between TiBw and matrix is composed of short-range martensitic nanodomains. Nanodomains are affected by the diffused interstitial B atoms and local internal stress field regulated by TiBw. The elastic interaction energy between nanodomains and TiBw are calculated according to the Eshelby method. Upon deformation, nanodomains grow to long-range martensitic laths. The long-range martensitic laths keep stable after unloading. The microstructure evolution ties well with the Landau free energy model. It achieves effective loading transfer from matrix to reinforcement phase, resulting in less irreversible defects and better shape memory effect. In addition, grain refinement strengthening, loading transfer strengthening and solution strengthening are utilized to achieve the improvement of the strength and plasticity. The finding offers a promising inspiration for the development of new type shape memory alloy composites with integrated structural and functional properties.

在先进航空航天工程需求日益增长的推动下，人们开始探索结构与功能一体化材料。在本研究中，我们制备了 TiBw/Ti-V-Al 轻质形状记忆合金复合材料，它具有较大的可恢复应变（> 5%）、较高的比强度（> 200 MPa-cm3/g）和良好的伸长率（> 20%）。这些令人满意的结构和功能性能归功于独特的梯度微结构，包括 TiB 晶须、短程马氏体纳米域和长程马氏体微域。具有优化取向的 TiBw 表现出很高的承载能力。TiBw 和基体之间的过渡区域由短程马氏体纳米域组成。纳米域受到扩散的间隙 B 原子和 TiBw 调节的局部内应力场的影响。纳米域与 TiBw 之间的弹性相互作用能是根据 Eshelby 方法计算得出的。变形时，纳米域生长为长程马氏体板条。长程马氏体板条在卸载后保持稳定。微观结构的演变与朗道自由能模型十分吻合。它实现了从基体到强化相的有效载荷传递，从而减少了不可逆缺陷，提高了形状记忆效果。此外，利用晶粒细化强化、载荷传递强化和溶液强化，还能提高强度和塑性。这一发现为开发具有综合结构和功能特性的新型形状记忆合金复合材料提供了很好的启示。

Composites Science and Technology

Towards Post-Curing Parameters Optimization of Phthalonitrile Composites Through the Synergy of Experiment and Machine Learning

Hanqi Zhang, Chunming Ji, Gao Li, Rui Chen, Dongqing Wang, Jinchuan Yang, Jiqiang Hu, Yichuan Zhang, Ming Liu, Bing Wang

doi:10.1016/j.compscitech.2024.110727

 

通过实验和机器学习的协同作用优化邻苯二腈复合材料的固化后参数

Phthalonitrile composites are highly anticipated in fields such as aerospace, marine, and electronics due to their exceptional heat resistance, excellent high-temperature mechanical properties, and outstanding processability. The conversion of nitrile functional groups to macrocyclic structures during post-curing is essential for performance enhancement. However, the influence of post-curing conditions on the mechanical properties of phthalonitrile composites is complicated, and the underlying mechanism remains unclear. In this study, an experimental and machine learning synergic strategy was employed to optimize the post-curing parameters of the phthalonitrile composites, including temperature, time, and pressure. Through mechanical experiments conducted at both room temperature and 400 °C, scanning electron microscope, and dynamic mechanical analysis, the underlying mechanism of the influence of post-curing parameters on the composite mechanical properties was revealed. The enhancement of the polymerization degree brought about by post-curing is the decisive factor for high-temperature performance, while the room-temperature properties are a tradeoff between the polymerization degree improvement and the defect proliferation. The genetic algorithm-optimized backpropagation (GA-BP) neural network was trained for the efficient and accurate prediction of the optimal post-curing parameters. The tendency of mechanical properties with the post-curing parameters predicted by machine learning is consistent with the mechanism revealed by experiments.

邻苯二腈复合材料因其卓越的耐热性、出色的高温机械性能和出色的可加工性，在航空航天、船舶和电子等领域备受期待。在后固化过程中将腈官能团转化为大环结构对提高性能至关重要。然而，后固化条件对邻苯二腈复合材料机械性能的影响十分复杂，其潜在机理仍不清楚。本研究采用实验和机器学习协同策略，优化了邻苯二腈复合材料的后固化参数，包括温度、时间和压力。通过室温和 400 °C 下的力学实验、扫描电子显微镜和动态力学分析，揭示了后固化参数对复合材料力学性能影响的内在机理。后固化带来的聚合度提高是高温性能的决定性因素，而室温性能则是聚合度提高和缺陷扩散之间的权衡。遗传算法优化反向传播（GA-BP）神经网络可高效、准确地预测最佳后固化参数。机器学习预测的后固化参数对力学性能的影响趋势与实验揭示的机理一致。