今日更新:Composite Structures 1 篇,Composites Part A: Applied Science and Manufacturing 1 篇,Composites Part B: Engineering 4 篇,Composites Science and Technology 1 篇
Blast resistance of 3D-printed Bouligand concrete panels reinforced with steel fibers: Numerical investigations
Vuong Nguyen-Van, Phuong Tran, Ngoc San Ha, Yi Min Xie, Farhad Aslani
doi:10.1016/j.compstruct.2024.118481
钢纤维增强3d打印Bouligand混凝土板的抗爆性能:数值研究
3D-printed concrete structures inspired by Bouligand architecture with helically twisted sequences exhibit excellent mechanical performance owing to its aligned fiber orientation. In this study, 3D-printed concrete panels with different numbers of layers (five, ten, and 15 layers) and spiral angles (0°, 15°, 30°, and 45°) are designed for numerical investigations of their blast-resistant capacity. A multi-scale model is developed to capture the isotropic and anisotropic properties of the fiber-concrete composite. The adequacy and accuracy of the model are evaluated and validated by experimental data in the literature. Blast resistance of different types of panels in terms of time histories of central-point deflection, contact explosion-induced plastic dissipation energy, stress propagation, and principal stress distribution is examined. It is found that extrusion-based concrete panels with aligned fiber orientation substantially enhance the blast resistance compared to traditional cast concrete panels with random fiber orientation. Furthermore, more layers of printed concrete panels prove to be more efficient in filtering blast waves. In particular, shifting a pitch angle of 30° after printing each layer plays an important role in reducing the maximum deflection. Meanwhile, 3D-printed concrete panels with a pitch angle of 0° can better mitigate blast-induced damage. Through parametric studies, the intrinsic mechanism of steel fibers aligned in 3D-printed panels is numerically analyzed to support the conclusions.
受Bouligand建筑的启发,具有螺旋扭曲序列的3d打印混凝土结构由于其排列的纤维取向而表现出优异的机械性能。在本研究中,设计了不同层数(5层、10层和15层)和螺旋角(0°、15°、30°和45°)的3d打印混凝土面板,对其抗爆能力进行了数值研究。建立了一种多尺度模型来捕捉纤维-混凝土复合材料的各向同性和各向异性特性。通过文献中的实验数据对模型的充分性和准确性进行了评价和验证。从中心点挠度、接触爆致塑性耗散能、应力传播和主应力分布等方面考察了不同类型板的抗爆性能。研究发现,纤维取向排列的挤压基混凝土板的抗爆性能明显优于纤维取向不规则的传统浇筑混凝土板。此外,多层印刷混凝土板被证明在过滤冲击波方面更有效。特别是,在打印每层后移动30°的俯仰角对减少最大挠度起着重要作用。同时,3d打印的0°俯仰角混凝土板可以更好地减轻爆炸引起的损伤。通过参数化研究,对钢纤维在3d打印板中排列的内在机理进行了数值分析,以支持上述结论。
A simulation strategy for fatigue modeling of delamination in composite structures under multiple loading conditions considering loading history and R -curve effects
I. Lecinana, L. Carreras, J. Renart, J. Zurbitu, B.H.A.H. Tijs, A. Turon
doi:10.1016/j.compositesa.2024.108402
考虑加载历史和R曲线效应的复合材料结构分层疲劳建模仿真策略
This work evaluates the ability of cohesive zone modeling-based approaches to predict delamination in composite materials that develop large process zones under complex loading conditions. The R -curve effects subjected to static and fatigue loading under multiple loading modes, considering the loading history, are analyzed. To this end, the delamination predictions of a state-of-the-art CZM-based simulation strategy are evaluated by blind simulation of a validation benchmark test. The validation test promotes a non-self-similar delamination scenario, including a process zone that evolves under different loading mode conditions with a non-straight leading delamination front. Good delamination prediction accuracy is achieved. In addition, insights into the relationship between the features of the simulation strategy and the physics of the delamination process are discussed. With regard to the limitations of the simulation strategy, particular attention should be paid to modeling the contribution of an evolving process zone based on the loading mode history.
这项工作评估了基于内聚区建模的方法预测复合材料在复杂载荷条件下形成大工艺区的分层的能力。考虑载荷历史,分析了多种载荷模式下静载荷和疲劳载荷作用下的R曲线效应。为此,通过验证基准测试的盲模拟来评估最先进的基于czm的仿真策略的分层预测。验证测试促进了一个非自相似的分层场景,包括一个在不同负载模式条件下发展的过程区,该过程区具有一个非直的领先分层前沿。得到了较好的分层预测精度。此外,还讨论了模拟策略的特征与分层过程的物理特性之间的关系。考虑到仿真策略的局限性,应特别注意基于加载模式历史对不断发展的过程区域的贡献进行建模。
Materials design using genetic algorithms informed by convolutional neural networks: Application to carbon nanotube bundles
Karen J. DeMille, Riley Hall, Joshua R. Leigh, Ibrahim Guven, Ashley D. Spear
doi:10.1016/j.compositesb.2024.111751
利用卷积神经网络的遗传算法设计材料:应用于碳纳米管束
Carbon nanotube (CNT) composites are a promising but complex material system whose mechanical response is influenced by many features, including CNT bundle microstructures. It is intractable to design CNT bundle microstructures using experiments and/or simulations alone. Thus, we implement a machine learning-based tool comprising a genetic algorithm (GA) (which aids in selecting features for bundle microstructures) and a convolutional neural network (CNN) (which rapidly predicts mechanical performance of bundle microstructures). Training data for the CNN are obtained from micromechanical finite element simulations. CNN predictions achieve R2>0.96 for elastic and shear moduli and R2>0.83 for Poisson’s ratios. Microstructures identified by the CNN-informed GA outperform between 79% and 100% of solutions found using a brute-force search and in less than 5% of the time, providing an efficient tool for informed materials design of CNT bundle microstructures.
碳纳米管(CNT)复合材料是一种前景广阔但结构复杂的材料系统,其机械响应受许多特征的影响,包括碳纳米管束微结构。仅靠实验和/或模拟来设计碳纳米管束微结构是难以实现的。因此,我们采用了一种基于机器学习的工具,包括遗传算法(GA)(帮助选择管束微结构的特征)和卷积神经网络(CNN)(快速预测管束微结构的机械性能)。CNN 的训练数据来自微机械有限元模拟。CNN 预测的弹性模量和剪切模量的 R2>0.96,泊松比的 R2>0.83。在不到 5%的时间内,CNN-informed GA 所确定的微结构优于 79% 至 100% 的使用蛮力搜索找到的解决方案,为 CNT 束微结构的知情材料设计提供了有效的工具。
Strain sensing of structural composites by integrated piezoresistive CNT yarn sensors
Moisés Zarzoso, Anastasiia Mikhalchan, Davide Mocerino, Pablo Romero-Rodriguez, Ricardo Losada, Juan J. Vilatela, Carlos González
doi:10.1016/j.compositesb.2024.111752
集成压阻式碳纳米管纱线传感器的结构复合材料应变传感
This work presents the development of piezoresistive strain sensors for the next-generation airframe parts. The sensors consist of polyetherketoneketone (PEKK) coated thermoplastic filaments with a continuous carbon nanotube (CNT) yarn reinforcement fully integrated into the structural thermoplastic CFRP laminates. PEKK coating improves the piezoresistive behaviour of CNT yarns by increasing internal stress transfer. When consolidated in a laminate, the CNT sensors have a gauge factor of 10.5 and 12 for 0.2% tensile and compressive deformations, respectively. The CNT sensors were calibrated and compared with commercial strain gauges at the coupon level and demonstrated high sensitivity in three- and four-point bend tests.
本工作介绍了用于下一代机体部件的压阻式应变传感器的发展。传感器由聚醚酮酮(PEKK)涂层热塑性长丝和连续碳纳米管(CNT)纱线组成,完全集成到结构热塑性CFRP层压板中。PEKK涂层通过增加内应力传递来改善碳纳米管纱线的压阻性能。当在层压板中固化时,碳纳米管传感器对于0.2%的拉伸和压缩变形分别具有10.5和12的测量因子。对碳纳米管传感器进行了校准,并与商用应变片进行了对比,在三点和四点弯曲测试中显示出高灵敏度。
Ultrahigh nitrogen-doped carbon derived from g-C3N4 assisted by citric acid for superior potassium-ion storage
Shasha Wang, Yuli Wei, Rongzhe Wang, Qing Liu, Qing Wang, Shaohua Luo, Yahui Zhang, Shengxue Yan, Pengqing Hou, Xin Liu, Jing Guo, Wenning Mu
doi:10.1016/j.compositesb.2024.111759
柠檬酸辅助下由g-C3N4衍生的超高氮掺杂碳具有优异的钾离子储存性能
Nitrogen-doped carbon is regarded as a promising anode for potassium ion batteries (PIBs) because nitrogen atoms can regulate the structures of carbon and generate abundant active sites. How to improve the nitrogen content in carbon through simple and effective methods remains to be further addressed. In this paper, a carbon material (60NC) with ultrahigh nitrogen content (16%) was prepared from graphite phase carbon nitride (g-C3N4) by a convenient freeze-drying and high-temperature pyrolysis method, assisted by citric acid. When used as an anode for PIBs, 60NC exhibited a superior reversible capacity of 318.1 mAh g-1 after 200 cycles at 0.1 A g-1. Even at the high current density of 1A g-1, 60NC maintained a specific capacity of 261.8 mAh g-1 after 1000 cycles. The excellent electrochemical performance of 60NC mainly stems from its abundant K+ storage active sites caused by nitrogen doping, large layer spacing, and hierarchical porous structure.
氮掺杂碳由于可以调节碳的结构并产生丰富的活性位点而被认为是一种很有前途的钾离子电池阳极。如何通过简单有效的方法提高碳中氮的含量还有待进一步研究。本文以石墨相氮化碳(g-C3N4)为原料,在柠檬酸的辅助下,采用简便的冷冻干燥和高温热解法制备了超高氮含量(16%)的碳材料(60NC)。当用作pib的阳极时,60NC在0.1 a g-1下循环200次后表现出优异的318.1 mAh g-1的可逆容量。即使在1A g-1的高电流密度下,60NC在1000次循环后仍保持261.8 mAh g-1的比容量。60NC优异的电化学性能主要源于氮掺杂导致的丰富的K+存储活性位点、大的层间距和层次化的多孔结构。
Designing vanadium-based nanoflower precursor towards improved Na3V2(PO4)3 cathode of sodium-ion batteries
Zhenghao Wang, Liang Chen, Bin Liang, Xiaodong Guo, Zhenguo Wu, Dongmei Luo
doi:10.1016/j.compositesb.2024.111762
改进钠离子电池正极Na3V2(PO4)3的钒基纳米花前驱体设计
The sodium superionic conductor Na3V2(PO4)3 (NVP) is a promising cathode material for sodium-ion batteries due to its high energy density and efficient ion diffusion pathways. Nonetheless, the conventional solid-state reaction synthesis of NVP suffers from limitations such as a small surface area, irregular shape, and suboptimal electrochemical properties. To address these challenges, a two-step approach is masterfully designed in this study, commencing with the modulation of the morphology of vanadium-based precursor through chemical precipitation. Subsequently, the uniform carbon-coated porous NVP@C composite with a significantly enhanced specific surface area of 83.22 m2 g-1 is devised through the solid-state reaction. Compared to traditional precipitation methods producing VO(OH)2 from VOSO4 solution, which have low efficiency and uneven precursor formation, adding cetyltrimethylammonium bromide (CTAB) as a surfactant enhanced vanadium precipitation (99.9%) and yielded uniform nanoflower-shaped precursor with a large surface area. Remarkably, the synthesized NVP@C composite achieved an impressive reversible capacity of 87.7 mA h g-1 at a challenging 5 C rate, with 80.0% capacity retention after 1000 cycles. These findings highlight the ability to control precursor morphology and enhance surface area contributes significantly to the favorable properties and electrochemical performance of the resulting materials, promoting their viability for advanced energy storage applications.
钠离子导体Na3V2(PO4)3 (NVP)具有高能量密度和高效的离子扩散途径,是一种很有前途的钠离子电池正极材料。然而,传统的固相反应合成NVP存在表面积小、形状不规则、电化学性能欠佳等局限性。为了解决这些挑战,本研究巧妙地设计了两步方法,首先通过化学沉淀法调制钒基前驱体的形态。随后,通过固相反应设计出均匀的碳包覆多孔NVP@C复合材料,其比表面积显著提高至83.22 m2 g-1。针对传统沉淀法从VOSO4溶液中生成VO(OH)2效率低且前驱体形成不均匀的问题,添加十六烷基三甲基溴化铵(CTAB)作为表面活性剂可提高钒的析出率(99.9%),并获得均匀且表面积大的纳米花状前驱体。值得注意的是,合成的NVP@C复合材料在具有挑战性的5℃温度下获得了令人印象深刻的87.7 mA h g-1可逆容量,1000次循环后容量保持率为80.0%。这些发现强调了控制前驱体形态和增加表面面积的能力,对所得材料的良好性能和电化学性能有重要贡献,促进了它们在先进储能应用中的可行性。
Degradation kinetics of PLA/hemp biocomposites: tradeoff between nucleating action and pro-hydrolytic effect of natural fibers
Libera Vitiello, Sabrina Carola Carroccio, Veronica Ambrogi, Edoardo Podda, Giovanni Filippone, Martina Salzano de Luna
doi:10.1016/j.compscitech.2024.110806
聚乳酸/大 麻生物复合材料的降解动力学:天然纤维成核作用和促水解作用之间的权衡
Natural fibers are not only a sustainable alternative to synthetic reinforcement materials, but can also be used to produce truly sustainable biocomposites with fast degradation kinetics. Indeed, due to their hygroscopicity, lignocellulosic fibers allow water and/or degrading organisms from the external environment to penetrate inside the host matrix and trigger its hydrolysis. The latter is the rate-limiting step for the degradation of bio-polyesters, which exhibit unacceptably slow degradation kinetics at ambient temperature and humidity. However, fibers also promote crystallization of the host matrix and thus slow down its degradation kinetics. To better understand and potentially control the degradation kinetics of biocomposites, here we investigate the ability of hemp shives, a hygroscopic by-product of hemp fiber production, to accelerate the hydrolysis of poly(lactic acid) (PLA). The degradation kinetics and degree of crystallinity of PLA are monitored in water and mature compost as a function of fiber content, which was varied across the percolation threshold (Φc) to study the effect of fiber interconnectivity. Above Φc, the fibers accelerate PLA hydrolysis in water despite their nucleating effect. Conversely, in compost the shielding effect of fiber-induced crystallinity prevails, and the fibers eventually slow down the degradation kinetics of PLA.
天然纤维不仅是合成增强材料的可持续替代品,而且还可以用于生产具有快速降解动力学的真正可持续的生物复合材料。事实上,由于其吸湿性,木质纤维素纤维允许外部环境中的水和/或降解生物渗透到宿主基质内部并触发其水解。后者是生物聚酯降解的限速步骤,在环境温度和湿度下,生物聚酯表现出不可接受的缓慢降解动力学。然而,纤维也促进宿主基质的结晶,从而减缓其降解动力学。为了更好地理解和潜在地控制生物复合材料的降解动力学,我们研究了大 麻纤维生产的吸湿副产物大 麻片加速聚乳酸(PLA)水解的能力。通过监测PLA在水中和成熟堆肥中的降解动力学和结晶度作为纤维含量的函数,纤维含量随渗透阈值(Φc)的变化而变化,以研究纤维互联性的影响。在Φc上面,尽管纤维具有成核作用,但它们加速了PLA在水中的水解。相反,在堆肥中,纤维诱导结晶度的屏蔽效应盛行,纤维最终减缓了PLA的降解动力学。