【新文速递】2023年12月10日复合材料SCI期刊最新文章

今日更新：Composite Structures 2 篇，Composites Part A: Applied Science and Manufacturing 2 篇，Composites Science and Technology 1 篇

Composite Structures

An adaptive metastructure concept using bistable composite laminates

Abhijeet Kumar, Ayan Haldar, Paul M. Weaver

doi:10.1016/j.compstruct.2023.117767

使用双稳态复合层压板的自适应元结构概念

Concepts involving adaptive and morphing structures offer us the possibility to realise shape transformation with each shape imparting an individual functionality. There is an increased demand in the design of structural components that are suitable for diverse operational conditions rather than limited to a unique one. However, most concepts of shape adaptive structures require a “holding force” or a continuous supply of energy to maintain a targeted 3D shape. As a result, structures that can lead to desired shape transformation with self-locking capabilities are more desirable. In this work, the concept of multistability is employed to demonstrate a novel class of metastructures that can tackle this challenge. The metastructure is constructed with a periodic arrangement of bistable unit cells made of highly anisotropic composite laminates. Each unit cell comprises multi-sectioned rectangular composite plates exhibiting bistable behaviour due to the thermal residual stresses engendered during the cool-down process from curing to room temperature. To analyse the proposed metastructure, a finite element model has been developed at three hierarchical levels: a plate level, a unit cell level, and a lattice level. At the plate level, a corresponding semi-analytical model using the Rayleigh–Ritz method has also been formulated to validate the finite element models. By carefully tuning the size and spacing of the unit cell, a desired response of the metastructure can be achieved. Additionally, by changing the ply layup and the fibre orientation of each layer of constituent composite plates, conflicting requirements, including load-carrying, shape-adaptive and lightweight, at the same time can be addressed simultaneously. From an extensive parametric study, few designs have been selected for its application in a load-carrying morphing structure.

自适应和变形结构的概念为我们提供了实现形状转换的可能性，每种形状都赋予了各自的功能。人们对结构部件的设计要求越来越高，这些部件应适用于不同的工作条件，而不是局限于一种独特的工作条件。然而，大多数形状自适应结构的概念都需要 "保持力 "或持续的能量供应来维持目标三维形状。因此，能够实现理想形状转换并具有自锁定功能的结构更为理想。在这项工作中，我们采用了多稳态概念来展示一类能够应对这一挑战的新型转移结构。这种元结构由高度各向异性的复合层压板周期性排列的双稳态单元构成。每个单元由多节矩形复合板组成，由于从固化到室温的冷却过程中产生的热残余应力，这些单元表现出双稳态行为。为了分析所提出的结构，我们在三个层次上建立了有限元模型：板层、单元格层和晶格层。在板层，还利用雷利-里兹方法建立了相应的半解析模型，以验证有限元模型。通过仔细调整单元格的大小和间距，可以实现所需的结构响应。此外，通过改变组成复合板的每层层叠和纤维取向，可以同时满足承载、形状适应和轻质等相互冲突的要求。在广泛的参数研究中，只有少数设计被选中用于承载变形结构。

Bending theory of composite pressure vessels: A closed-form analytical approach

V.G. Belardi, M. Ottaviano, F. Vivio

doi:10.1016/j.compstruct.2023.117799

复合压力容器的弯曲理论：闭式分析方法

Composite pressure vessels are strategic for the present and future of the aerospace, transportation, and energy industries. These shell structures are utilized to store and transport liquids and gases and are principally composed of a cylindrical shell and two elliptical heads. The current rules for the structural design of composite pressure vessels make use of the membrane theory that excludes the bending of the structure. Nevertheless, the cylindrical shell and the elliptical heads present different curvature radii. These changes generate a localized bending deformation that determines an increase in the stress state as an effect of a local bending moment and shear force distributions that arise in the geometric transition zone. The stresses related to the bending effects die out rapidly, moving away from the junction plane, but they are sensibly higher than the membrane stress and, therefore, cannot be neglected in the mechanical assessment. Here, a closed-form analytical solution for the bending theory of composite shells is proposed. It can assist in the design of composite pressure vessels and drive the design towards reliable configurations for structural integrity. Using the Donnell–Mustari–Vlasov theory for thin-walled composite shells, the governing fourth-order differential equation is deduced and solved to obtain the displacements and stresses acting in the junction. The analytical results are successfully compared with those of reference finite element models for validation; their accuracy is proved considering different thicknesses, lay-ups, and flattening factors of the vessel

复合材料压力容器对航空航天、运输和能源行业的现在和未来都具有战略意义。这些壳体结构用于储存和运输液体和气体，主要由一个圆柱形壳体和两个椭圆形封头组成。复合材料压力容器结构设计的现行规则采用膜理论，该理论排除了结构的弯曲。然而，圆柱形外壳和椭圆形封头的曲率半径不同。这些变化会产生局部弯曲变形，在几何过渡区产生的局部弯矩和剪切力分布会增加应力状态。与弯曲效应相关的应力会迅速消失，远离交界平面，但这些应力明显高于膜应力，因此在力学评估中不能忽略。本文提出了复合材料壳体弯曲理论的闭式解析解。它有助于复合材料压力容器的设计，并推动设计朝着结构完整性的可靠配置方向发展。利用薄壁复合材料壳体的 Donnell-Mustari-Vlasov 理论，推导并求解了支配四阶微分方程，从而获得了作用于交界处的位移和应力。分析结果成功地与参考有限元模型的结果进行了比较，以进行验证；考虑到容器的不同厚度、布局和扁平系数，证明了分析结果的准确性。

Composites Part A: Applied Science and Manufacturing

High wear resistance of uniform nitriding titanium composites fabricated by in-situ laser powder bed fusion

Yunmian Xiao, Yongqiang Yang, Mingkang Zhang, Zibin Liu, Hanxiang Zhou, Shibiao Wu, Di Wang, Changhui Song

doi:10.1016/j.compositesa.2023.107950

原位激光粉末床熔融制造的均匀氮化钛复合材料的高耐磨性

Laser powder bed fusion (LPBF) supplies a new method for titanium matrix composites (TMCs) that are difficult to process using traditional production. Aiming at the current LPBF-printed pure titanium with low hardness and poor wear resistance, this paper proposes an innovative method of laser in-situ synthesis of uniform nitriding TMCs under the interaction of Ar+0/5/10/15% N2 with Ti powder in the LPBF process. It is shown that the forming quality can be modulated by the laser energy density and N2 concentration. TiN was in-situ synthesized in more than 10% N2. Moreover, the hardness and wear resistance of LPBF-ed TMCs increased with rising N2 concentration. The friction coefficient decreased from 0.39 under Ar to 0.32 of 15% N2, and the wear rate decreased by 70%. Besides, this study provides a reference for in-situ synthesis of gradient TMCs with high hardness and wear resistance on the surface, while the inner is ductile.

激光粉末床熔融（LPBF）为传统生产中难以加工的钛基复合材料（TMC）提供了一种新方法。针对目前 LPBF 印刷的纯钛硬度低、耐磨性差的问题，本文提出了一种创新方法，即在 LPBF 工艺中，在 Ar+0/5/10/15% N2 与钛粉的相互作用下，激光原位合成均匀氮化 TMC。结果表明，成形质量可受激光能量密度和 N2 浓度的调节。在 10% 以上的 N2 中可原位合成 TiN。此外，经 LPBF 加工的 TMC 的硬度和耐磨性随 N2 浓度的增加而提高。摩擦系数从 Ar 下的 0.39 降至 15% N2 下的 0.32，磨损率降低了 70%。此外，本研究还为原位合成表面具有高硬度和耐磨性，而内部具有韧性的梯度 TMC 提供了参考。

Exoskeleton-like mechanical enhanced low-density aerogel with electromagnetic interface shielding and infrared stealth

Junru Yao, Jintang Zhou, Guiyu Peng, Dong An, Zhengjun Yao

doi:10.1016/j.compositesa.2023.107954

具有电磁界面屏蔽和红外隐身功能的外骨骼式机械增强型低密度气凝胶

The integrated design and mechanical enhancement of multifunctional electromagnetic interference shielding and infrared stealth aerogels are challenging for the development and application of novel aerogels. Here, inspired by the biological exoskeleton to enhance the body, we develop the exoskeleton-like aramid nanofiber/polyimide/MXene (APM) aerogel through a secondary impregnation strategy. For APM aerogel, the polyimide reinforcement layer makes the aerogel more elastic and tough; the Ti3C2Tx-MXene exoskeleton enhances the strength and stiffness of the aerogel. Importantly, Ti3C2Tx-MXene forms a continuous conductive network on the surface of the airgel backbone, resulting in high-performance electromagnetic interference (EMI) shielding (EMI shielding efficiency reached 55.315 dB at an ultra-low Ti3C2Tx content of 0.58 vol%), high-efficiency infrared radiation (IR) stealth (ultra-low thermal conductivity of 0.0666 W·m-1·K-1 and IR emissivity of 0.566 at 3-5 μm and 0.55 at 8-14 μm). This study provides a way to design robust aerogel materials with infrared stealth and electromagnetic shielding compatibility.

多功能电磁干扰屏蔽气凝胶和红外隐身气凝胶的综合设计和机械增强是新型气凝胶开发和应用的挑战。在此，我们受生物外骨骼增强体的启发，通过二次浸渍策略开发了类似外骨骼的芳纶纳米纤维/聚酰亚胺/MXene（APM）气凝胶。就 APM 气凝胶而言，聚酰亚胺增强层使气凝胶更具弹性和韧性；Ti3C2Tx-MXene 外骨骼增强了气凝胶的强度和刚度。重要的是，Ti3C2Tx-MXene 在气凝胶骨架表面形成了连续的导电网络，从而实现了高性能电磁干扰（EMI）屏蔽（在 Ti3C2Tx 含量为 0.58 vol% 的超低条件下，EMI 屏蔽效率达到 55.315 dB）和高效红外辐射（IR）隐身（超低导热系数为 0.0666 W-m-1-K-1，3-5 μm 处红外发射率为 0.566，8-14 μm 处为 0.55）。这项研究为设计具有红外隐身和电磁屏蔽兼容性的坚固气凝胶材料提供了一种方法。

Composites Science and Technology

Transfer-learning-based strategy for enhancing prediction accuracy and computational efficiency of nonlinear mechanical properties in composite materials

Chenyu Nan, Hongshi Ruan, Yangjian Xu, Junhan Hu, Lihua Liang, Xiaozhe Ju

doi:10.1016/j.compscitech.2023.110388

 

基于迁移学习的策略，提高复合材料非线性力学性能的预测精度和计算效率

In modern composite design, superior macroscopic mechanical properties can be achieved by optimizing the microstructures of materials. However, the direct prediction of the microstructure–property relationship under nonlinear conditions through numerical methods can be inefficient or imprecise. In this study, a transfer learning strategy based on the reduced order model (ROM) was proposed, offering an enhanced and rapid prediction of the mechanical responses of composite materials under nonlinear conditions. Initially, an extensive training dataset was generated by applying the ROM, used to pre-train the neural network model. Following this, a few data calculated from full-order finite element models were leveraged to fine-tune the network parameters. This approach exploits the efficient data generation capability of the ROM, with its potential computational inaccuracies in nonlinear scenarios mitigated, leading to an improvement in the accuracy and efficiency of the surrogate model. Numerical examples of a nonlinear hyper-elastic material with inclusions were examined, revealing that the computational cost in the offline stage of the transfer learning method is only half that of traditional neural network models, and it enable near real-time predictions in the online stage. Notably, it was shown that the accuracy loss of the developed surrogate model in scenarios of strong non-linearity is significantly less than that of the ROM. This method presents an innovative pathway for the swift and accurate evaluation of the effective mechanical properties of composite structures, with the potential to offer valuable insights for related methodological research.

在现代复合材料设计中，通过优化材料的微观结构可以获得优异的宏观机械性能。然而，通过数值方法直接预测非线性条件下的微观结构-性能关系可能效率低下或不精确。本研究提出了一种基于还原阶次模型（ROM）的迁移学习策略，可增强和快速预测复合材料在非线性条件下的机械响应。首先，通过应用 ROM 生成大量训练数据集，用于预训练神经网络模型。随后，利用从全阶有限元模型中计算出的一些数据对网络参数进行微调。这种方法利用了 ROM 的高效数据生成能力，减轻了其在非线性情况下潜在的计算不准确性，从而提高了代用模型的准确性和效率。通过对带有夹杂物的非线性超弹性材料的数值实例进行研究，发现迁移学习方法在离线阶段的计算成本仅为传统神经网络模型的一半，而且在在线阶段可以实现近乎实时的预测。值得注意的是，所开发的代用模型在强非线性情况下的精度损失明显小于 ROM。该方法为快速、准确地评估复合材料结构的有效力学性能提供了一种创新途径，有望为相关方法学研究提供有价值的见解。