首页/文章/ 详情

【新文速递】2023年12月13日固体力学SCI期刊最新文章

18天前浏览212

今日更新:Journal of the Mechanics and Physics of Solids 1 篇,Mechanics of Materials 1 篇,International Journal of Plasticity 1 篇,Thin-Walled Structures 1 篇

Journal of the Mechanics and Physics of Solids

Is a high-throughput experimental dataset large enough to accurately estimate a statistic?

Yifan Zhou, Sirui Lin, Xuhui Zhang, Hou Wu, Jose Blanchet, Zhigang Suo, Tongqing Lu

doi:10.1016/j.jmps.2023.105521

一个高通量的实验数据集是否足够大,可以准确地估计一个统计量?

In materials science, experimental datasets are commonly used to estimate various statistics of random variables. This paper focuses on a specific random variable: the rupture stretch of a material. Examples of statistics include average, standard deviation, coefficient of variation, and different quantiles. How accurate is the estimate of such a statistic? The answer depends on the statistic, the size of the experimental dataset, and how much the random variable scatters. Here we demonstrate a procedure to generate a large experimental dataset and use the experimental dataset to estimate the accuracy of various statistics of the rupture stretch.  We use a high-throughput experiment to measure the rupture stretches of 160 specimens of a silicone rubber. We then use the bootstrap method to determine the 90% confidence intervals of several statistics. We find that the experimental dataset accurately estimates the average, standard deviation, and 50% quantile. However, the experimental dataset does not reliably estimate extremely low or high quantiles. This finding indicates an experimental dataset much larger than 160 specimens is needed to accurately estimate rare-event rupture stretch.  We further apply the bootstrap method to an experimental dataset of strengths of 33 specimens of a ceramic. The result indicates that this experimental dataset is too small to accurately estimate the average strength of the ceramic. Our findings demonstrate that the common practice of using small datasets to estimate statistics of material properties is outdated and meaningless. The high-throughput experiment provides a large experimental dataset of rupture stretch, from which the bootstrap method quantifies the accuracy of the estimates of various statistics. The bootstrap method does not require the user to have sophisticated expertise in statistical analysis. Nor does the bootstrap method require the dataset to obey any statistical distribution.

在材料科学中,实验数据集通常用于估计随机变量的各种统计量。本文主要研究一个特定的随机变量:材料的断裂拉伸。统计的例子包括平均值、标准差、变异系数和不同的分位数。这样的统计估计有多准确?答案取决于统计数据、实验数据集的大小以及随机变量的分散程度。在这里,我们演示了一个程序来生成一个大型实验数据集,并使用实验数据集来估计断裂拉伸的各种统计数据的准确性。我们使用高通量实验测量了160个硅橡胶试样的断裂拉伸。然后,我们使用bootstrap方法来确定几个统计量的90%置信区间。我们发现实验数据集准确地估计了平均值、标准差和50%分位数。然而,实验数据集不能可靠地估计极低或极高的分位数。这一发现表明,需要一个比160个样本大得多的实验数据集来准确估计罕见事件的断裂拉伸。我们进一步将自举法应用于33个陶瓷样品强度的实验数据集。结果表明,该实验数据太小,无法准确估计陶瓷的平均强度。我们的研究结果表明,使用小数据集来估计材料性能统计数据的常见做法已经过时且毫无意义。高通量实验提供了一个大的断裂拉伸实验数据集,bootstrap方法从中量化了各种统计估计的准确性。自举方法不需要用户在统计分析方面具有复杂的专业知识。bootstrap方法也不要求数据集服从任何统计分布。


Mechanics of Materials

Flexural wave rainbow trapping effect in the periodic non-uniform Euler-Bernoulli beams and its application in energy harvesting

Tian Deng, Luke Zhao, Feng Jin

doi:10.1016/j.mechmat.2023.104892

周期性非均匀欧拉-伯努利光束中的弯曲波彩虹捕获效应及其在能量收集中的应用

The rainbow trapping of elastic wave enables spatial frequency shunting and energy concentration phenomenon, which implies that the broadband vibration will forbid propagating forward and occur energy concentration at different positions of metamaterial structure. This paper proposes a novel metamaterial consisting of the periodic non-uniform Euler-Bernoulli beams with an arbitrary profile section to achieve the rainbow trapping effect of flexural wave and application in piezoelectric energy harvester. Firstly, the differential quadrature method is introduced to solve a partial differential equation with variable coefficients. The convergence of this method is systematically demonstrated, and the correctness of band structures is validated by comparing theoretical results calculated by the differential quadrature method with those from the finite element method for different profiles. Based on band structures analysis, the working mechanism of the flexural wave rainbow trapping effect is attributed to the group velocity modulation; thereby, the constructed periodic array of non-uniform beams achieves integration of specific-band vibration reduction and energy enhancement at specific positions. Secondly, simulations indicate that the resonance rainbow trapping frequencies demonstrate more intense concentration of flexural wave energy compared to the counterpart with initial frequencies. Finally, the resonance rainbow trapping phenomenon demonstrates superiority in vibration energy harvesting. Specifically, when piezoelectric films are pasted on specific-position with enhanced energy density, the maximum output voltage in the independent circuit connection reaches up to 2.30V for the resonance rainbow trapping frequency of 8752Hz and the PVDF film position of x = 670 mm. Furthermore, simulations illustrate that the maximum output voltage and power are up to 4.52V and 1894.12 nW for the Series-A circuit connection, respectively, which is approximately the sum of the individual maximum output electrical energy generated by independent circuit connection at positions A and B. The proposed metamaterial beams can offer new selection guidelines for high-performance vibration energy harvesters.

弹性波的彩虹俘获导致了空间频率分流和能量集中现象,这意味着宽带振动将阻止向前传播,并在超材料结构的不同位置发生能量集中。本文提出了一种由任意截面的周期性非均匀欧拉-伯努利光束组成的新型超材料,以实现弯曲波的彩虹捕获效应,并将其应用于压电能量采集器。首先,引入微分正交法求解变系数偏微分方程。系统地论证了该方法的收敛性,并通过将微分正交法与有限元法在不同剖面下的理论计算结果进行比较,验证了该方法的正确性。基于能带结构分析,认为弯波彩虹捕获效应的工作机制是群速度调制;因此,所构建的非均匀光束周期阵列实现了特定频段减振和特定位置能量增强的一体化。其次,模拟结果表明,共振彩虹捕获频率比初始频率更能集中弯曲波能量。最后,共振彩虹捕获现象证明了在振动能量收集方面的优越性。其中,当压电膜以增强的能量密度粘贴在特定位置时,谐振彩虹捕获频率为8752Hz, PVDF膜位置为x = 670 mm时,独立电路连接的最大输出电压可达2.30V。仿真结果表明,A系列电路连接的最大输出电压为4.52V,最大输出功率为1894.12 nW,近似于A、b两个位置独立电路连接产生的最大输出电能之和。所提出的超材料梁可以为高性能振动能量采集器的选型提供新的指导。


International Journal of Plasticity

On the strain delocalization mechanism of Cu/Nb nanolayered composites with amorphous interfacial layers

Yaodong Wang, Jianjun Li, Jiejie Li, Shaohua Chen

doi:10.1016/j.ijplas.2023.103856

具有非晶界面层的Cu/Nb纳米复合材料应变离域机制研究

Nanostructured metals and alloys possess ultrahigh strength but suffer from severe shear instability (strain localization). Recent experiments have shown that the strength and strain delocalization capability of some novel nanostructured alloys and nanolayered composites can be enhanced simultaneously by introducing nanoscale amorphous interfacial layers. However, the underlying mechanism is still in the embryonic stage due to the ignorance of the complicated elemental composition of the interfacial layers, especially the compositional gradient along the interface thickness. Here, the atomic mechanisms of the tensile deformation of Cu/Nb nanolayered composites with amorphous interfacial layers are systematically investigated by molecular dynamics simulations. Depending on whether the composition of the interfacial layers is invariable or has a gradient distribution along the interface thickness, these samples are classified as amorphous or gradient samples, respectively. The simulations of normal Cu/Nb nanolayered composites with ordinary incoherent Cu‒Nb interfaces are also included for comparison, the results of which show that strain localization occurs due to the inhomogeneous plastic deformation between soft and hard grains in the Cu and Nb layers. The strain localization is inhibited in the amorphous samples mainly through the activation of deformation twinning in the Cu and Nb layers that produce a co-deformation between grains. Intriguingly, the gradient arrangement of the elemental composition of the amorphous interfacial layers gives a further stronger strain delocalization by further promoting the co-deformation between grains through stimulating more twin boundaries in Cu layers and hindering twin boundary migration in Nb layers, and by producing a much more uniform von Mises strain distribution in the interfacial layers. In addition, a better strain delocalization capability can be obtained when the thickness of interfacial layers is closer to that of the crystalline ones or the range of gradient composition is larger.

纳米结构金属和合金具有超高的强度,但存在严重的剪切不稳定性(应变局部化)。最近的实验表明,引入纳米级非晶界面层可以同时提高一些新型纳米结构合金和纳米层复合材料的强度和应变离域能力。然而,由于对界面层复杂的元素组成,特别是沿界面厚度方向的成分梯度的研究尚处于萌芽阶段。本文采用分子动力学模拟方法,系统研究了Cu/Nb纳米复合材料非晶态界面层拉伸变形的原子机理。根据界面层的组成是不变的还是沿界面厚度呈梯度分布,这些样品分别被分类为非晶或梯度样品。通过对普通Cu - Nb非共格界面的普通Cu/Nb纳米复合材料的模拟进行比较,结果表明,应变局部化是由于Cu和Nb层中软硬晶粒之间的不均匀塑性变形引起的。非晶试样中的应变局部化主要是通过激活Cu和Nb层中的变形孪晶,从而产生晶粒间的共变形来抑制的。有趣的是,非晶态界面层元素组成的梯度排列通过在Cu层中激发更多的孪晶界而在Nb层中阻碍孪晶界迁移,从而进一步促进晶粒之间的共变形,并通过在界面层中产生更均匀的von Mises应变分布,从而进一步增强了应变的离域。此外,界面层厚度越接近晶体层厚度或梯度组成范围越大,可以获得较好的应变离域能力。


Thin-Walled Structures

On the mechanical behavior of carbon fiber/epoxy laminates exposed in thermal cycling environments

Zhihao Qiu, Dongrun Wu, Yao Zhang, Chang Liu, Yuan Qian, Deng'an Cai

doi:10.1016/j.tws.2023.111481

热循环环境下碳纤维/环氧复合材料的力学性能研究

Carbon fiber reinforced polymer (CFRP) composites are commonly used for reflectors of artificial satellites operating in low earth orbit (LEO). The decay of the modulus of the CFRP composite varies under different thermal cycling environments, which can lead to a reduction in the accuracy of the reflector panels, affecting the transmission of signals. This paper investigates the impact of different thermal cycling conditions on the mechanical behavior of carbon fiber/epoxy laminated composites experimentally. Three kinds of thermal cycling conditions involving continuous temperature changes are employed to explore the influence of temperature range on the residual tensile and in-plane shear moduli of the laminates. Test results indicate that the upper temperature limit and the temperature span of the thermal cycling conditions jointly affect the mechanical properties of CFRP composite laminates, but the responses of the residual tensile and in-plane shear moduli are different under the variation of each temperature parameter alone. The residual tensile and in-plane shear moduli of the laminates under thermal cycling decrease with an expansion of the temperature span having the same upper limit. If the temperature span remains constant, an increase in the upper temperature limit leads to an increase in the residual tensile modulus, but a decrease in the residual in-plane shear modulus. The main damages causing the decay of residual tensile and in-plane shear moduli of unidirectional laminates were investigated by scanning electron microscopy (SEM) technology. Observations of the microscopic fracture of the material show that the post-curing reaction factor predominantly influences the residual tensile modulus of unidirectional laminates, while the fiber/matrix interface damage factor dominates the residual in-plane shear modulus of the unidirectional laminates. Furthermore, an increase in the fiber tensile modulus decreases both residual tensile and residual in-plane shear moduli. Notably, the residual in-plane shear modulus exhibits greater sensitivity to thermal cycling compared to the residual tensile modulus. The findings reported in this paper would provide valuable insights and guidance for the design and application of carbon fiber/epoxy composites subjected to thermal cycling conditions.

碳纤维增强聚合物(CFRP)复合材料是近地轨道人造卫星反射器的常用材料。CFRP复合材料的模量衰减在不同的热循环环境下是不同的,这会导致反射板的精度降低,影响信号的传输。通过实验研究了不同热循环条件对碳纤维/环氧复合材料力学性能的影响。采用三种温度连续变化的热循环工况,探讨温度范围对层合板残余拉伸模量和面内剪切模量的影响。试验结果表明,热循环工况的温度上限和温度跨度共同影响CFRP复合材料层合板的力学性能,但各温度参数单独变化时残余拉伸模量和面内剪切模量的响应不同。热循环作用下层合板的残余拉伸模量和面内剪切模量随着温度跨度的扩大而减小,但温度跨度的上限相同。在温度跨度一定的情况下,温度上限的增加会导致残余拉伸模量的增加,但会导致残余面内剪切模量的减少。采用扫描电镜(SEM)技术研究了引起单向层合板残余拉伸模量和面内剪切模量衰减的主要损伤。对材料微观断裂的观察表明,固化后的反应因子对单向层合板的残余拉伸模量有主要影响,而纤维/基体界面损伤因子对单向层合板的残余面内剪切模量有主要影响。此外,纤维拉伸模量的增加会降低残余拉伸模量和残余面内剪切模量。值得注意的是,与残余拉伸模量相比,残余面内剪切模量对热循环表现出更大的敏感性。本文的研究结果将为热循环条件下碳纤维/环氧复合材料的设计和应用提供有价值的见解和指导。



来源:复合材料力学仿真Composites FEM
ACTMechanicalSystemDeform振动断裂复合材料电路ADS理论材料分子动力学试验
著作权归作者所有,欢迎分享,未经许可,不得转载
首次发布时间:2024-11-05
最近编辑:18天前
Tansu
签名征集中
获赞 3粉丝 0文章 690课程 0
点赞
收藏
作者推荐

【新文速递】2023年12月1日固体力学SCI期刊最新文章

今日更新:International Journal of Solids and Structures 2 篇,Journal of the Mechanics and Physics of Solids 1 篇,Mechanics of Materials 1 篇,Thin-Walled Structures 1 篇International Journal of Solids and StructuresMachine learning enabled identification of sheet metal localizationMuhammed Adil Yatkın, Mihkel Kõrgesaardoi:10.1016/j.ijsolstr.2023.112592通过机器学习识别板材定位The Forming Limit Curve (FLC), which describes the maximum applicable strain before localization, depends on the particular material, but also on the applied load and history of the load. Recent investigations have shown that the non-proportional loading effect on the FLC can be predicted with data-driven or machine-learning-based methods. Here we compare different ML methods to their applicability in predicting localization points under multi-segmented non-proportional loading. Therefore, an FE-based metamodel is developed that allows imposing an arbitrary loading history on sheet metal to predict the point of localization. A series of virtual experiments are conducted with this metamodel to generate a database of bi-linear loading paths that are used for training. Different ML-based methods were used to predict the localization point based on the strain history data. The 1D-Convolutional Neural Network (1D-CNN), with the ability to learn dependency between input features, has the best accuracy in predicting the localization point.成型极限曲线(FLC)描述了局部化之前的最大适用应变,它不仅取决于特定的材料,还取决于施加的载荷和载荷的历史。最近的研究表明,基于数据驱动或机器学习的方法可以预测非比例加载对 FLC 的影响。在此,我们比较了不同的 ML 方法在预测多分段非比例加载下的定位点时的适用性。因此,我们开发了一种基于有限元分析的元模型,可以在金属板上施加任意加载历史记录来预测定位点。利用该元模型进行了一系列虚拟实验,生成了一个用于训练的双线性加载路径数据库。根据应变历史数据,使用不同的基于 ML 的方法来预测定位点。一维卷积神经网络(1D-CNN)具有学习输入特征之间依赖关系的能力,在预测定位点方面具有最佳准确性。Predicting Moisture Penetration Dynamics in Paper with Machine Learning ApproachMossab Alzweighi, Rami Mansour, Alexander Maass, Ulrich Hirn, Artem Kulachenkodoi:10.1016/j.ijsolstr.2023.112602用机器学习方法预测纸张的水分渗透动态In this work, we predicted the gradient of the deformational moisture dynamics in a sized commercial paper by observing the curl deformation in response to the one-sided water application. The deformational moisture is a part of the applied liquid which ends up in the fibers causing swelling and subsequent mechanical response of the entire fiber network structure. The adapted approach combines traditional experimental procedures, advanced machine learning techniques and continuum modeling to provide insights into the complex phenomenon relevant to ink-jet digital printing in which the sized and coated paper is often used, meaning that not all the applied moisture will reach the fibers. Key material properties including elasticity, plastic parameters, viscoelasticity, creep, moisture dependent behavior, along with hygroexpansion coefficients are identified through extensive testing, providing vital data for subsequent simulation using a continuum model. Two machine learning models, a Feedforward Neural Network (FNN) and a Recurrent Neural Network (RNN), are probed in this study. Both models are trained using exclusively numerically generated moisture profile histories, showcasing the value of such data in contexts where experimental data acquisition is challenging. These two models are subsequently utilized to predict moisture profile history based on curl experimental measurements, with the RNN demonstrating superior accuracy due to its ability to account for temporal dependencies. The predicted moisture profiles are used as inputs for the continuum model to simulate the associated curl response comparing it to the experiment representing “never seen” data. The result of comparison shows highly predictive capability of the RNN. This study melds traditional experimental methods and innovative machine learning techniques, providing a robust technique for predicting moisture gradient dynamics that can be used for both optimizing the ink solution and paper structure to achieve desirable printing quality with lowest curl propensities during printing.在这项工作中,我们通过观察单面施水时的卷曲变形,预测了规格商业用纸中的变形水分动态梯度。变形水分是施用液体的一部分,它最终会进入纤维,导致纤维膨胀,进而引起整个纤维网络结构的机械响应。这种方法结合了传统的实验程序、先进的机器学习技术和连续体建模,有助于深入了解喷墨数字印刷的复杂现象,因为在喷墨数字印刷中,通常会使用施胶纸和涂布纸,这意味着并非所有的水分都会到达纤维。通过大量测试,确定了关键材料特性,包括弹性、塑性参数、粘弹性、蠕变、湿度依赖行为以及湿膨胀系数,为随后使用连续模型进行模拟提供了重要数据。本研究中使用了两种机器学习模型,即前馈神经网络(FNN)和循环神经网络(RNN)。这两个模型都是通过数字生成的湿度曲线历史记录进行训练的,在实验数据获取具有挑战性的情况下展示了这些数据的价值。这两个模型随后被用于根据卷曲实验测量结果预测水分曲线历史,其中 RNN 由于能够考虑时间依赖性而显示出更高的准确性。预测的水分曲线被用作连续模型的输入,以模拟相关的卷曲响应,并与代表 "从未见过 "数据的实验进行比较。比较结果表明,RNN 具有很强的预测能力。这项研究融合了传统的实验方法和创新的机器学习技术,提供了一种预测湿度梯度动态的可靠技术,可用于优化油墨溶液和纸张结构,从而在印刷过程中以最低的卷曲倾向获得理想的印刷质量。Journal of the Mechanics and Physics of SolidsCoupling diffusion and finite deformation in phase transformation materialsTao Zhang, Delin Zhang, Ananya Renuka Balakrishnadoi:10.1016/j.jmps.2023.105501相变材料中的耦合扩散和有限变形We present a multiscale theoretical framework to investigate the interplay between diffusion and finite lattice deformation in phase transformation materials. In this framework, we use the Cauchy-Born Rule and the Principle of Virtual Power to derive a thermodynamically consistent theory coupling the diffusion of a guest species (Cahn-Hilliard type) with the finite deformation of host lattices (nonlinear gradient elasticity). We adapt this theory to intercalation materials—specifically Li1−2Mn2O4— to investigate the delicate interplay between Li-diffusion and the cubic-to-tetragonal deformation of lattices. Our computations reveal fundamental insights into the microstructural evolution pathways under dynamic discharge conditions, and provide quantitative insights into the nucleation and growth of twinned microstructures during intercalation. Additionally, our results identify regions of stress concentrations (e.g., at phase boundaries, particle surfaces) that arise from lattice misfit and accumulate in the electrode with repeated cycling. These findings suggest a potential mechanism for structural decay in Li2Mn2O4. More generally, we establish a theoretical framework that can be used to investigate microstructural evolution pathways, across multiple length scales, in first-order phase transformation materials.我们提出了一个多尺度理论框架,用于研究相变材料中扩散与有限晶格变形之间的相互作用。在这一框架中,我们利用考奇-伯恩法则和虚拟力量原理,推导出一种热力学上一致的理论,将客体物种的扩散(卡恩-希利亚德型)与主晶格的有限变形(非线性梯度弹性)耦合在一起。我们将这一理论应用于插层材料--特别是 Li1-2Mn2O4--研究锂扩散与晶格立方到四方变形之间微妙的相互作用。我们的计算揭示了动态放电条件下微结构演化路径的基本观点,并对插层过程中孪生微结构的成核和生长提供了定量见解。此外,我们的研究结果还确定了应力集中区域(如相边界、颗粒表面),这些应力集中区域由晶格错配引起,并随着反复循环在电极中累积。这些发现表明了 Li2Mn2O4 结构衰变的潜在机制。更广泛地说,我们建立了一个理论框架,可用于研究一阶相变材料中跨越多个长度尺度的微结构演化路径。Mechanics of MaterialsMicrostructural effects in rate-dependent responses of smooth and notched magnesium barsShahmeer Baweja, Shailendra P. Joshidoi:10.1016/j.mechmat.2023.104877光滑镁条和缺口镁条随速率变化的微观结构效应We perform three-dimensional crystal plasticity simulations of smooth and notched bar geometries made of polycrystalline hexagonal close-packed material representing a magnesium alloy. The polycrystalline microstructure is explicitly resolved to investigate the combined effect of initial texture and grain size on the rate-dependent macroscopic responses and their micromechanical underpinnings under uniaxial and multiaxial stress states. The simulations reveal that in addition to the textural effect recently investigated by Ravaji et al. (2021), grain size plays an important role in the anisotropy of macroscopic responses. For a given texture, the lateral deformation anisotropy increases with grain size refinement for all strain rates considered here. The load-deformation responses exhibit a synergistic strengthening effect in microstructures with stronger initial textures and finer grain sizes, which is enhanced with increasing notch acuity. A transition from a conventional power-law type load-deformation response to a sigmoidal load-deformation response may occur, which depends on the imposed strain rate. It is a result of the interaction between textural weakening and grain size refinement that influence extension twinning together with an equitable landscape of the different slip mechanisms. We discuss possible implications of the net material plastic anisotropy due to texture and grain size on macroscopic failure using a micromechanical basis.我们对以镁合金为代表的多晶六方紧密堆积材料制成的光滑和缺口棒材几何形状进行了三维晶体塑性模拟。我们明确解析了多晶微观结构,以研究在单轴和多轴应力状态下,初始纹理和晶粒大小对随速率变化的宏观响应及其微观力学基础的综合影响。模拟结果表明,除了 Ravaji 等人(2021 年)最近研究的纹理效应外,晶粒尺寸在宏观响应的各向异性中也起着重要作用。对于给定的纹理,在本文考虑的所有应变速率下,横向变形各向异性随着晶粒尺寸的细化而增加。在具有较强初始纹理和较细晶粒尺寸的微结构中,载荷-变形响应表现出协同强化效应,这种效应随着凹口敏锐度的增加而增强。从传统的幂律型载荷变形响应到西格玛载荷变形响应的转变可能会发生,这取决于施加的应变率。这是纹理弱化和晶粒细化相互作用的结果,它们与不同滑移机制的公平分布一起影响着延伸孪晶。我们以微观力学为基础,讨论了由纹理和晶粒尺寸引起的净材料塑性各向异性对宏观破坏的可能影响。Thin-Walled StructuresExperimental study on the impact resistance and damage tolerance of thermoplastic FMLsLei Yang, Zhenhao Liao, Cheng Qiu, Zijing Hong, Jinglei Yangdoi:10.1016/j.tws.2023.111435热塑性 FML 的抗冲击性和损伤耐受性实验研究This study aimed to enhance the impact resistance of fiber metal laminates (FMLs) and achieve lightweight optimization by incorporating a new thermoplastic resin, a titanium alloy and ultra-high-molecular-weight polyethylene (UHMWPE) fiber to produce a novel type of FMLs (PEFMLs). The impact resistance of PEFMLs was analyzed through low-velocity impact tests conducted at different energy levels. Subsequently, the residual compression-after-impact (CAI) strength of the PEFMLs was evaluated through compression tests on the impacted specimens. The experimental findings revealed that PEFMLs exhibited subcritical failure when subjected to impact energies less than 35 J, with a penetration energy threshold of 55 J. Higher impact energies resulted in larger damage areas and increased plate buckling of PEFMLs, consequently leading to reduced CAI strength. The presence of metal, thermoplastic resin and UHMWPE in the PEFMLs effectively dissipated a substantial amount of impact energy while maintaining their structural integrity during both the impact and compression processes.本研究旨在通过加入新型热塑性树脂、钛合金和超高分子量聚乙烯(UHMWPE)纤维,生产出一种新型金属纤维层压板(PEFMLs),从而提高金属纤维层压板(FMLs)的抗冲击性,并实现轻量化优化。通过在不同能量水平下进行的低速冲击试验,分析了 PEFMLs 的抗冲击性。随后,通过对冲击试样进行压缩试验,评估了 PEFMLs 的冲击后残余压缩强度(CAI)。实验结果表明,PEFML 在受到小于 35 J 的冲击能量时表现出亚临界破坏,穿透能量阈值为 55 J。PEFML 中金属、热塑性树脂和超高分子量聚乙烯的存在有效地消散了大量冲击能量,同时在冲击和压缩过程中保持了结构完整性。来源:复合材料力学仿真Composites FEM

未登录
还没有评论
课程
培训
服务
行家
VIP会员 学习 福利任务 兑换礼品
下载APP
联系我们
帮助与反馈