今日更新:Composite Structures 3 篇,Composites Part A: Applied Science and Manufacturing 3 篇,Composites Part B: Engineering 2 篇,Composites Science and Technology 2 篇
A rotating triangular auxetic perforated plate: Structural design and characteristic analysis
Tao Xue, Wei Zhong Jiang, Yi Zhang, Nian Ci Du, Jun Wen Shi, Yi Chao Qu, Xin Ren
doi:10.1016/j.compstruct.2024.118684
旋转三角形补孔板:结构设计与特性分析
Auxetic metamaterials have garnered extensive attention over the past few decades due to their exceptional and superior mechanical properties. However, owing to their unique porous structure, it is challenging to ensure that structures possess strong energy absorption capabilities while exhibiting excellent auxetic characteristics. This study introduces a rotating triangular auxetic metamaterial (RTAM) by perforating traditional rigid rotating triangles. Quasi-static compression tests and numerical simulations are conducted on the new structure to investigate the effects of wall thickness and re-entrant angle of the triangular perforated plate on mechanical properties and Poisson’s ratio. The plateau stress and specific energy absorption (SEA) of RTAM are 4 and 10 times higher than that of traditional trichiral auxetic metamaterials (TCAM), respectively. With an increase in wall thickness, both plateau stress and SEA of the structure are improved significantly. As the re-entrant angle increases, the SEA of the structure initially decreases and then increases. RTAM achieves both lightweight structure and ideal mechanical performance, providing an approach for manufacturing lightweight and high-strength auxetic metamaterials, with significant potential applications in the field of energy absorption.
在过去的几十年里,增塑型超材料由于其优异的机械性能而引起了广泛的关注。然而,由于其独特的多孔结构,在保证结构具有强大的吸能能力的同时又具有良好的减振特性是一项挑战。通过对传统的刚性旋转三角形进行射孔,研制了一种旋转三角形补强超材料(RTAM)。对新型结构进行了准静态压缩试验和数值模拟,研究了三角形穿孔板壁厚和入角对力学性能和泊松比的影响。RTAM的平台应力和比能吸收(SEA)分别是传统三手性增塑型超材料(TCAM)的4倍和10倍。随着壁厚的增加,结构的平台应力和SEA均有显著提高。随着再入角的增大,结构的SEA先减小后增大。RTAM既实现了轻量化结构,又实现了理想的力学性能,为制造轻量化、高强度的形变超材料提供了途径,在能量吸收领域具有重要的应用潜力。
Hybrid composite-metal structure response to post-impact compression – Experimental and numerical study
Piotr Podolak, Patryk Jakubczak, Jarosław Bieniaś
doi:10.1016/j.compstruct.2024.118685
混合复合金属结构对冲击后压缩的响应。实验和数值研究
Numerical analysis of the post-impact damage propagation process during CAI tests on titanium-based fibre metal laminates was conducted, and the model was validated by collation of mechanical parameters predicted by it with experimental results. Delaminations induced by the impact were claimed as the hotspot for other modes propagation in most of studied cases and intensively propagated shortly before reaching peak compressive force. Metal – composite interfaces away from impact surface were locations of most intensive delamination propagation during CAI, constituting 63.5 % of overall damage area for titanium-carbon laminate and 81.6 % for titanium-glass laminate. Similarly to delaminations, damage due to fibre and matrix compression propagated from impact point and lead to significant load-carrying ability loss even in low volumes. Propagation of fibre and matrix tension was connected more to buckling progression, than post-impact damage and had the highest volumetric share in composite layers damage modes (max 13.5 % for titanium-carbon laminate and 8.3 % for titanium-glass laminate).
对钛基金属纤维层合板CAI试验中冲击后损伤传播过程进行了数值分析,并将模型预测的力学参数与实验结果进行比对,对模型进行了验证。在大多数研究案例中,由冲击引起的分层被认为是其他模态传播的热点,并且在达到峰值压缩力前不久集中传播。在CAI过程中,远离冲击面的金属-复合材料界面是分层扩展最密集的位置,占钛-碳层合板整体损伤面积的63.5 %,占钛-玻璃层合板整体损伤面积的81.6 %。与分层类似,纤维和基体压缩造成的损伤从撞击点开始传播,即使在小体积下也会导致严重的承载能力损失。与冲击后损伤相比,纤维和基体张力的传播更多地与屈曲过程有关,并且在复合材料层的损伤模式中具有最高的体积份额(钛-碳层压板最大13.5 %,钛-玻璃层压板最大8.3 %)。
Extension of the crack equivalent method applied to mode II fracture of thermoplastic composites bonded joints using the ENF test
J.P. Reis, M.F.S.F. de Moura, R.D.F. Moreira
doi:10.1016/j.compstruct.2024.118687
裂纹等效法在热塑性复合材料粘结接头II型断裂中的扩展
Thermoplastic based composites (TPC) have emerged as a new generation of eco-friendly materials with tougher matrices capable of overcoming the major weaknesses of the thermoset counterparts related with poor resistance to delamination and recycling difficulties. Although TPC materials present low surface energy, adhesive bonding is still effective when the requirements for fusion bonding procedures are not met. Recent advances in adhesive technology have unveiled two-part acrylic adhesive specifically designed for low energy surfaces, characteristic of TPC materials. In this work, unidirectional carbon-reinforced polyamide 6 (CF/PA6) bonded joint was characterized under pure mode II loading using end-notched flexure (ENF) test. The experimental fracture tests revealed unstable crack propagation and a data reduction scheme based on the equivalent crack concept was developed to obtain the strain energy release rate distribution along the crack front for the specimen’s length beyond the actuator central loading point. The proposed procedure was successfully validated using a finite element analysis including a cohesive zone modelling and applied to the experimental results. The obtained Resistance-curves showed that this adhesive is capable to provide a significant bonding resistance in pure mode II loading even in low energy surfaces characteristic of TPC materials.
热塑性复合材料(TPC)已成为新一代环保材料,具有更坚固的基体,能够克服热固性材料的主要弱点,即抗分层性差和回收困难。虽然TPC材料表面能较低,但在不满足熔合工艺要求的情况下,胶粘剂粘合仍然有效。粘合剂技术的最新进展已经推出了专为低能量表面设计的两组分丙烯酸粘合剂,具有TPC材料的特点。采用端缺口挠曲(ENF)试验对单向碳增强聚酰胺6 (CF/PA6)键合接头在纯II型载荷下的特性进行了研究。基于等效裂纹概念,提出了一种基于等效裂纹概念的数据约简方案,得到了执行器中心加载点以外试件长度沿裂纹前沿的应变能释放率分布。采用有限元分析(包括内聚区建模)成功验证了所提出的程序,并将其应用于实验结果。得到的电阻曲线表明,即使在TPC材料的低能量表面,该粘合剂也能够在纯II型加载下提供显著的粘接电阻。
Arrest behavior of local resonators connected by nonlocal interaction in elastic wave metamaterials with machine learning prediction
Xuan Zhang, Yi-Ze Wang
doi:10.1016/j.compositesa.2024.108571
弹性波超材料中由非局部相互作用连接的局部谐振器的捕获行为与机器学习预测
In this study, the arrest behaviors of elastic wave metamaterials are analyzed in which the interconnected local resonators are considered. The influence of structural parameters on arrest performance is discussed to show good arrest properties. In order to support the theoretical calculation, both finite element simulation and fracture experiment are performed. Results show that additional energy barriers are generated in the higher subsonic range and the crack propagation resistance can be significantly improved by proper nonlocal interaction. Finally, based on the machine learning method, the energy release ratio G0/G of the elastic wave metamaterial is predicted. Comparing with the theoretical and predicted values, they are basically consistent in the stable range of energy release ratio.
在本研究中,考虑了相互连接的局部谐振器的弹性波金属材料的捕获行为进行了分析。讨论了结构参数对捕获性能的影响,以显示良好的捕获特性。为了支持理论计算,进行了有限元模拟和断裂实验。结果表明,在较高亚声波范围内会产生额外的能量障碍,通过适当的非局部相互作用可以显著提高裂纹扩展阻力。最后,基于机器学习方法,预测了弹性波金属材料的能量释放比率G0/G。将理论和预测值与稳定能量释放比率范围进行比较,它们基本一致。
Remaining useful life prediction of flax fibre biocomposites under creep load by acoustic emission and deep learning
Jianqun Hao, Matthias Rupp, Stepan V. Lomov, Carlos Fuentes Rojas, Aart Willem Van Vuure
doi:10.1016/j.compositesa.2024.108572
基于声发射和深度学习的亚麻纤维生物复合材料蠕变载荷剩余使用寿命预测
Natural fibre composites are increasingly explored for structural applications due to improvements in mechanical performance. For this, damage prognostics are crucial. We integrate acoustic emission (AE) and deep learning techniques to predict the remaining useful life of a flax fibre composite under long-term creep load. Derivatives of cumulative AE features with respect to time, such as cumulative hit and count rates, are introduced to reflect the performance degradation rate of the materials. These proposed features seem more relevant for creep lifespan than traditional AE features. Long short-term memory networks and temporal convolutional networks are adopted to estimate the composite’s remaining useful life. The two model’s normalized root mean square errors are below 0.11, less than 20% of the error of a statistical Weibull-distribution benchmark model. Our study demonstrates that AE-based data-driven models can predict the performance degradation of composite materials subject to sustained load.
由于机械性能的提高,天然纤维复合材料越来越多地用于结构应用。为此,损害预测至关重要。我们整合了声发射(AE)和深度学习技术来预测亚麻纤维复合材料在长期蠕变载荷下的剩余使用寿命。累积声发射特征对时间的导数,如累积命中率和计数率,被引入来反映材料的性能退化率。与传统声发射特征相比,这些特征似乎与蠕变寿命更相关。采用长短期记忆网络和时间卷积网络估计复合材料的剩余使用寿命。两个模型的归一化均方根误差均小于0.11,小于统计威布尔分布基准模型误差的20%。我们的研究表明,基于ae的数据驱动模型可以预测复合材料在持续载荷作用下的性能退化。
Toughening of thick bonded interfaces through architected crack-arresting features
Dharun Vadugappatty Srinivasan, Anastasios P. Vassilopoulos
doi:10.1016/j.compositesa.2024.108575
通过结构裂纹止裂特性对厚粘结界面进行增韧
This research investigates the application of additively manufactured crack-arresting features (CAFs), designed from tough and soft polymers, in enhancing the performance of thick glass fiber-reinforced polymer composite-epoxy adhesive joints found in wind turbine rotor blades. Mode I fracture and fatigue behaviors of these joints are assessed through double-cantilever beam experiments and compared against pristine joints. In pristine joints, cracks consistently deviate from the adhesive bondline into the composite adherend, causing a sudden increase in strain energy release rate. Finite element models based on linear elastic fracture mechanics are employed to provide insight into this behavior. Experimental results demonstrate that joints with architected CAFs achieved higher strain energy release rates, more stable failure mechanisms, and minimized damage to the composite adherend. Under fatigue loading, joints featuring tough CAF material exhibit slower fatigue crack growth compared to both pristine joints and those with soft CAF material.
本研究研究了增材制造的裂纹止裂特征(CAFs)的应用,由坚韧和柔软的聚合物设计,以提高风力涡轮机转子叶片中厚玻璃纤维增强聚合物复合环氧胶粘接接头的性能。通过双悬臂梁试验评估了这些节点的I型断裂和疲劳行为,并与原始节点进行了比较。在原始接头中,裂纹不断偏离胶粘剂结合线进入复合材料粘附面,导致应变能释放率突然增加。采用基于线弹性断裂力学的有限元模型来深入了解这种行为。实验结果表明,具有结构的碳纤维接头具有更高的应变能释放率,更稳定的破坏机制,并且对复合材料粘附体的损伤最小。在疲劳载荷下,与原始接头和软CAF接头相比,具有坚韧CAF材料的接头表现出较慢的疲劳裂纹扩展。
One-step green synthesis of multi-morphological carbon nanotube forests for superior microwave absorption and electrocatalysis
Rong Ding, Fu-Rong Zeng, Hai-Bo Zhao, Hao Chen, Yu-Chuan Zhang, Bo-Wen Liu
doi:10.1016/j.compositesb.2024.111932
具有优异微波吸收和电催化性能的多形态碳纳米管森林一步绿色合成
Porous carbon materials with multiscale distinctive morphologies hold significant promise in electromagnetic wave stealth/protection and catalysis; however, formidable challenges are highly verbose and resource/time-consuming fabrication processes. Here, we report a one-step solvent/template-free self-expanding carbonization strategy for rapidly fabricating porous carbon foams (Ni/CNT) with zero-dimensional (0D) nanoparticles, one-dimensional (1D) nanotube forests, and three-dimensional (3D) hollow microvesicles. Owing to the multi-morphological structure and low-density feature, the resulting porous carbon foam Ni/CNT-800 achieves a minimum reflection loss of −56.48 dB and an effective bandwidth of 5.44 GHz at a low filler loading of only 9 wt%. Moreover, altering the electronic structure and surface chemistry of carbon foam by phosphorus doping enables a highly reduced durable overpotential (η) of 275 mV for oxygen evolution reaction. This work emphasizes a straightforward strategy for the facile design and efficient fabrication of carbon-based materials with unique multiscale porous morphologies, customizable functions, and various applications.
多孔碳材料具有独特的多尺度形态,在电磁波隐身/保护和催化方面具有重要的应用前景。然而,巨大的挑战是非常冗长和资源/耗时的制造过程。在这里,我们报告了一种无溶剂/模板的一步自膨胀碳化策略,用于快速制造具有零维(0D)纳米颗粒、一维(1D)纳米管森林和三维(3D)空心微泡的多孔碳泡沫(Ni/CNT)。由于多孔泡沫碳Ni/CNT-800的多形态结构和低密度特性,在低填充量为9 wt%的情况下,其反射损耗最小为- 56.48 dB,有效带宽为5.44 GHz。此外,通过磷掺杂改变泡沫碳的电子结构和表面化学性质,可以使析氧反应的持久过电位(η)大幅降低至275 mV。这项工作强调了碳基材料的简单设计和高效制造的直接策略,具有独特的多尺度多孔形态,可定制的功能和各种应用。
Electrospun green fluorescent-highly anisotropic conductive Janus-type nanoribbon hydrogel array film for multiple stimulus response sensors
Haina Qi, Xuelian Jing, Yaolin Hu, Ping Wu, Xuejian Zhang, Yongtao Li, Hongkai Zhao, Qianli Ma, Xiangting Dong, C.K. Mahadevan
doi:10.1016/j.compositesb.2024.111933
用于多刺 激响应传感器的电纺绿色荧光高各向异性导电janus型纳米带水凝胶阵列薄膜
A new strategy aimed at significantly enhancing the anisotropic conductivity of hydrogel materials, along with a simple construction technology and design concept, are proposed. Anisotropic conductive hydrogel materials have attracted much attention from researchers in the field of flexible electronics for their inherent excellent properties. However, the anisotropic conductivity of the existing conductive hydrogels is not high and the preparation methods are complex. Herein, fluorescent-highly conductive anisotropic Janus-type nanoribbon hydrogel array film (named JNHAF) is successfully prepared using a combination of parallel electrospinning and post-polymerization as an example of the study. Highly oriented [2,7-dibromo-9-fluorenone (DF)/gelatin (GE)]//[carbon black (CB)/GE] Janus-type nanoribbon is used as the building block. The composition as well as the arrangement of Janus-type nanoribbons are microscopically designed and regulated to effectively separate the conductive and insulating materials, so that the samples can achieve highly anisotropic conductivity and obvious green fluorescence. When the mass ratio of GE to CB is 1:0.1, the conductive anisotropy ratio of JNHAF can reach 1.12 × 105. The degree of anisotropic conductivity of JNHAF is significantly improved compared with existing reported anisotropic conductive hydrogels, and the preparation method is simple. JNHAF responds quickly to light, tensile strain, and temperature, making it suitable for assembling multi-stimulus responsive sensors. JNHAF has excellent flexibility, degradability, mechanical properties and a certain degree of sensitivity (gauge factor of 4.29), and is used for human joint motion detection with an obvious response signal. The design idea and construction technology of this hydrogel breaks through the technical bottleneck of the low degree of anisotropy of conductive hydrogels, which will lead and expand the scientific frontiers of anisotropic conductive hydrogel materials, and provide novel design ideas and theoretical values for new hydrogel materials.
提出了一种旨在显著提高水凝胶材料各向异性电导率的新策略,以及一种简单的施工技术和设计理念。各向异性导电水凝胶材料以其固有的优异性能受到柔性电子领域研究人员的广泛关注。但现有导电水凝胶的各向异性电导率不高,制备方法复杂。本文以采用平行静电纺丝和后聚合相结合的方法成功制备荧光高导电性各向异性janus型纳米带水凝胶阵列膜(命名为JNHAF)为例。高取向的[2,7-二溴-9-芴酮(DF)/明胶(GE)]//[炭黑(CB)/GE] janus型纳米带被用作构建块。通过对janus型纳米带的组成和排列进行微观设计和调控,有效分离导电材料和绝缘材料,使样品具有高度的各向异性电导率和明显的绿色荧光。当GE与CB的质量比为1:0.1时,JNHAF的导电各向异性比可达1.12 × 105。与已有报道的各向异性导电水凝胶相比,JNHAF的各向异性导电程度显著提高,且制备方法简单。JNHAF对光、拉伸应变和温度反应迅速,适合组装多刺 激响应传感器。JNHAF具有优良的柔韧性、可降解性、力学性能和一定的灵敏度(测量因子为4.29),用于人体关节运动检测,响应信号明显。该水凝胶的设计思路和施工技术突破了导电水凝胶各向异性程度低的技术瓶颈,将引领和拓展各向异性导电水凝胶材料的科学前沿,为新型水凝胶材料提供新颖的设计思路和理论价值。
Room-Temperature Ionic Liquid Electrolytes for Carbon Fiber Anodes in Structural Batteries
Lakshmi Surag Singavarapu, Paul Gilmore, Jun Wei Yap, Yehia Khalifa, Umesh Gandhi, Timothy S. Arthur, Jay Sayre, Jung-Hyun Kim
doi:10.1016/j.compscitech.2024.110952
结构电池碳纤维阳极用室温离子液体电解质
Structural batteries require thermally stable electrolytes paired with carbon fibers (CFs), which offer advantages of lightweight, high mechanical strength, and good electrical conductivity. This work evaluated various room-temperature ionic-liquid (RTIL) as compatible electrolytes for CF anodes and LiFePO4 (LFP) cathodes on CFs. This LFP/CF full-cell design eliminates Cu and Al current-collectors, potentially enhancing gravimetric energy and reducing costs. Among various RTILs, LiTFSI in N-propyl-N-methylpyrrolidinium (PYR13) – bis(fluorosulfonyl)imide (FSI) offered promising LFP/CF full-cell performances, attributed to the formation of solid electrolyte interface (SEI) on the CF anode with components such as Li2Sx, Li2S-SO3, LiF, LixFy and F-SO2, identified through X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). Electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT) analyses further confirmed the electrochemical stability of the SEI layer on CF anodes. The LFP/CF cell delivered an initial capacity of 119 mAh/g and relatively high Coulombic efficiency when using the 1 M LiTFSI in PYR13-FSI. CF cycled in different electrolytes exhibit varying mechanical properties with up to 10.08% loss in tensile strength, which may be related to CF surface degradation mechanisms during repeated cycling. Furthermore, the 1 M LiTFSI in PYR13-FSI is non-flammable, offering a significant thermal safety. This work successfully demonstrated the significant potential of 1 M LiTFSI in PYR13-FSI LTILs, which enables the use of CF as both an anode active material and cathode current collector for structural battery applications.
结构电池需要热稳定的电解质与碳纤维(CFs)配合使用,这种材料具有重量轻、机械强度高和导电性好的优点。本研究评估了不同室温离子液体(RTIL)作为CF阳极和LiFePO4 (LFP)阴极的相容电解质。这种LFP/CF全电池设计消除了Cu和Al集流器,潜在地提高了重力能量并降低了成本。在各种RTILs中,n -丙基- n -甲基吡啶鎓(PYR13) -双(氟磺酰基)亚胺(FSI)中的LiTFSI具有很好的LFP/CF全电池性能,这是由于在CF阳极上与Li2Sx、Li2S-SO3、LiF、LixFy和F-SO2等组分形成固体电解质界面(SEI),通过x射线光电子能谱(XPS)和扫描电子显微镜(SEM)进行了鉴定。电化学阻抗谱(EIS)和弛豫时间分布(DRT)分析进一步证实了SEI层在CF阳极上的电化学稳定性。当在PYR13-FSI中使用1m LiTFSI时,LFP/CF电池提供了119 mAh/g的初始容量和相对较高的库仑效率。在不同的电解液中循环的CF表现出不同的力学性能,拉伸强度损失高达10.08%,这可能与重复循环过程中CF表面降解机制有关。此外,PYR13-FSI中的1m LiTFSI是不可燃的,提供了显著的热安全性。这项工作成功地证明了1 M LiTFSI在PYR13-FSI ltls中的巨大潜力,这使得CF既可以作为结构电池应用的阳极活性材料,也可以作为阴极集流器。
Three-dimensional cohesive finite element simulations coupled with machine learning to predict mechanical properties of polymer-bonded explosives
Daokun Lu, Bingru Zhang, Liu Liu, Haitao Zhang, Luoxia Cao, Yang Zhou
doi:10.1016/j.compscitech.2024.110947
三维内聚有限元模拟结合机器学习预测聚合物粘结炸药的力学性能
Developing multifactorial predictive models for the design of polymer-bonded explosives (PBXs) is of importance for their further application in insensitive munition fields. As a popular method, finite element simulations can provide a reliable prediction, but are laborious and expensive if considering the extensive design parameter space. In light of this challenge, we proposed a coupled strategy that includes machine learning (ML) and three-dimensional cohesive finite element simulation for effciently predicting the mechanical properties of PBXs. The strain rate, particle volume fraction, interface strength, fracture energy, and the binders are considered as the main factors of tailoring the tensile strength of PBXs. To improve the prediction performance, an augmented database of 2500 data sets utilizing GANs neural network were established and then processed to train and test six ML models. The results show the accuracy and generalizability of the low-computational-cost ML models in predicting the mechanical properties of PBX composites. The predicted values from these models are in good agreement with the experimental ones. Feature contribution analysis demonstrates that the tensile modulus and failure strain are most affected by the binders, while the tensile strength are most affected by the fracture energy. Using the above conclusions as design guidelines, we can develop the new PBX formulations according to different mechanical property requirements for their optimal use across insensitive ammunitions. This strategy can be a viable machine-learning-assisted solution to designing PBXs.
建立多因素预测模型用于聚合物粘结炸药的设计,对其在不敏感弹药领域的进一步应用具有重要意义。有限元模拟作为一种常用的方法,虽然可以提供可靠的预测,但由于设计参数空间太大,计算难度大,成本高。鉴于这一挑战,我们提出了一种包括机器学习(ML)和三维内聚有限元模拟的耦合策略,以有效预测pbx的力学性能。应变速率、颗粒体积分数、界面强度、断裂能和粘结剂是影响PBXs抗拉强度的主要因素。为了提高预测性能,利用gan神经网络建立了2500个数据集的增强数据库,并对6个ML模型进行了训练和测试。结果表明,低计算成本的机器学习模型在预测PBX复合材料力学性能方面具有准确性和通用性。模型的预测值与实验值吻合较好。特征贡献分析表明,粘结剂对拉伸模量和破坏应变影响最大,而断裂能对拉伸强度影响最大。利用上述结论作为设计指导,我们可以根据不同的机械性能要求开发新的PBX配方,以优化其在不敏感弹药中的使用。该策略可以作为设计pbx的一种可行的机器学习辅助解决方案。