Composites Part C Open Access最新文献_第7页

Material card’s identification by inverse method and multi-scale optimization approach through eigenmode analysis of unidirectional Elium®/flax laminated biocomposites 基于单向Elium®/亚麻层合生物复合材料特征模态分析的材料卡片逆向识别和多尺度优化方法

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-09-12 DOI: 10.1016/j.jcomc.2025.100647

Ameny Ketata , Zouhaier Jendli , Mondher Haggui , Abderrahim El Mahi , Anas Bouguehca , Mohamed Haddar

This article presents a mixed finite element method (FEM) and experimental inverse identification approach for determining the ply-level elastic properties of unidirectional (UD) Elium®/flax composites. Using the global dynamic response of UD laminates, the intrinsic mechanical properties are identified. Material uncertainties are accounted for, and engineering constants are determined over a broad frequency range through a response surface methodology (RSM)-based sensitivity analysis and meta-modeling approach. A multi-objective optimization process based on a non-dominated sorting genetic algorithm (NSGA) is employed to minimize differences between experimental and numerical frequency responses. The sensitivity analysis reveals that the first seven vibration modes are primarily influenced by the longitudinal modulus (E₁) and the shear modulus (G₁₂), with E₁ having a dominant effect in UD configurations. The optimization process, conducted using HyperStudy™, demonstrates good agreement between the numerical and experimental frequencies. However, the use of a global error function reveals certain limitations, as it may fail to smooth out local deviations, making it challenging to precisely identify mismatches in individual vibration modes. In summary, these findings provide valuable insights into the dynamic behavior of Elium®/flax composites and offer a robust method for determining material properties card for future complex composite structures.

本文提出了一种混合有限元法（FEM）和实验反识别方法来确定单向（UD） Elium®/亚麻复合材料的弹性性能。利用UD层合板的整体动力响应，确定了UD层合板的内在力学性能。通过基于响应面法（RSM）的灵敏度分析和元建模方法，考虑了材料的不确定性，并在较宽的频率范围内确定了工程常数。采用基于非支配排序遗传算法（NSGA）的多目标优化过程最小化实验频率响应与数值频率响应的差异。灵敏度分析表明，前7种振动模式主要受纵向模量（E1）和剪切模量（G12）的影响，其中E1在UD构型中具有主导作用。使用HyperStudy™进行的优化过程证明了数值频率和实验频率之间的良好一致性。然而，使用全局误差函数暴露出一定的局限性，因为它可能无法平滑局部偏差，这使得精确识别单个振动模式的不匹配变得具有挑战性。总之，这些发现为Elium®/亚麻复合材料的动态行为提供了有价值的见解，并为确定未来复杂复合材料结构的材料性能卡提供了可靠的方法。

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引用次数: 0

Data-driven prediction of failure loads in damaged FRP composites under four-point flexure 四点弯曲下FRP复合材料损伤破坏载荷的数据驱动预测

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-09-11 DOI: 10.1016/j.jcomc.2025.100646

James A. Quinn, Ourania Patsia, Gabrielis Cerniauskas, Dongmin Yang, Dilum Fernando, Edward D. McCarthy

This study investigates the use of machine learning (ML) as a tool to make predictions of the criticality of delamination damage in fiber-reinforced polymer (FRP) composites subjected to four-point flexural loading. An extensive experimental campaign was conducted on polyester-glass FRP specimens. Most specimens were manufactured with a polytetrafluoroethylene film inserted at one interlaminar location to simulate delamination damage. Damage size, damage location through the laminate thickness, and the number of plies in the laminate, were each varied in the test matrix. The strength of damaged specimens was normalized against the strengths of corresponding pristine reference specimens to obtain a measure of damage criticality. Data augmentation techniques were subsequently utilized on the experimental data to synthetically generate a larger dataset for training, validating and testing the ML model. Output predictions of specific strength from the ML model proved very accurate for both the training dataset and the test dataset, meaning the ML model can accurately and near instantaneously predict the specific four-point flexure strength of new delamination damage cases. The method presented could be expanded to include new specimen characteristics and loading scenarios, or be combined with non-destructive testing techniques to enable data-backed, rapid decision making when delamination damage is detected in asset maintenance programs. The results highlight the effectiveness of data-driven methods for predicting the failure loads and apparent static strengths of damaged FRP composites and provide information on the most influential delamination features affecting the strength of FRP under flexure loads.

本研究探讨了使用机器学习（ML）作为工具来预测纤维增强聚合物（FRP）复合材料在四点弯曲载荷下分层损伤的临界性。对聚酯玻璃玻璃钢试样进行了广泛的试验。大多数样品是在一个层间位置插入聚四氟乙烯膜来模拟分层损伤。在测试矩阵中，损伤大小、损伤位置随层压厚度的变化以及层压层数的变化都是不同的。将损伤试件的强度与相应的原始参考试件的强度进行归一化，以获得损伤临界程度的度量。随后，在实验数据上使用数据增强技术来综合生成更大的数据集，用于训练、验证和测试ML模型。从ML模型输出的比强度预测对于训练数据集和测试数据集都证明是非常准确的，这意味着ML模型可以准确且几乎即时地预测新的分层损伤案例的具体四点弯曲强度。所提出的方法可以扩展到包括新的试样特性和加载场景，或者与非破坏性测试技术相结合，以便在资产维护计划中检测到分层损伤时，能够以数据为基础快速做出决策。研究结果强调了数据驱动方法在预测损坏FRP复合材料的破坏载荷和表观静态强度方面的有效性，并提供了影响FRP在弯曲载荷下强度的最具影响力的分层特征的信息。

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引用次数: 0

Improving the accuracy of carbon nanotube yarn 3D printing using machine learning 利用机器学习提高碳纳米管纱线3D打印精度

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-09-10 DOI: 10.1016/j.jcomc.2025.100644

Junro Sano, Ryosuke Matsuzaki

To overcome the limitations of conventional continuous carbon fiber 3D printing in achieving precise curved printing and intricate shaping, a 3D printing technique based on carbon nanotube (CNT) yarn was proposed, offering finer and more accurate fabrication capabilities. However, the contributions of two critical features of CNT yarn—its fine diameter and yarn twist—to enhanced printability remain inadequately understood. This study explores the impact of these features on printing precision through a combination of experimental methods and machine learning approaches. The findings reveal that yarn twist plays a more significant role than diameter in reducing radius errors during single-layer circular printing. A predictive model developed in this study achieved an

R^{2}

value of 0.888 and reduced radius error magnitude by approximately 79.3% when feedback was incorporated into the printing process. These results highlight the potential of CNT yarn to advance the precision of 3D printing technologies.

为了克服传统连续碳纤维3D打印在实现精确弯曲打印和复杂成形方面的局限性，提出了一种基于碳纳米管（CNT）纱线的3D打印技术，提供了更精细、更精确的制造能力。然而，碳纳米管纱线的两个关键特征-其细直径和纱线捻度-对提高印刷适性的贡献仍然没有充分了解。本研究通过实验方法和机器学习方法的结合，探讨了这些特征对印刷精度的影响。结果表明，纱线捻度比纱线直径对降低单层圆形印花的半径误差有更大的作用。本研究建立的预测模型在打印过程中加入反馈后，R2值为0.888，半径误差幅度降低约79.3%。这些结果突出了碳纳米管纱线在提高3D打印技术精度方面的潜力。

引用次数: 0

Deep learning and information fusion for structure property analysis in adhesive joints 基于深度学习和信息融合的粘接接头结构性能分析

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-09-03 DOI: 10.1016/j.jcomc.2025.100645

Umut Bakhbergen , Ahmed Maged , Fethi Abbassi , Reza Montazami , Sherif Araby

Interfacial adhesion is a pivotal factor in determining the overall strength and durability of composite structures across aerospace and automotive industries. Therefore, understanding the failure modes and crack propagation paths in interface-based composites underpins the service life of bulk structure. This study employs deep learning and information fusion techniques to automate structure-property analysis in adhesive joints. First, response surface methodology (RSM) is used to design experimental matrix for anodizing adherend surfaces (aluminium sheets); the control parameters are concentration, current and time. Surface topography is characterized by surface roughness and contact angle along with scanning electron microscopy (SEM) images. Interfacial strength of anodized aluminium-polyurethane (Al-PU) adhesive joints is measured, and fracture analysis is performed via SEM. Experimental results demonstrated that anodizing conditions – concentration 0.5 M H₂SO₄ concentration, 1.5 A current and 45 min anodizing duration– enhanced the interfacial shear strength by up to 920% compared to untreated joints. Second, a novel information fusion approach is employed; the model integrates features extracted from SEM images using ResNet with numerical data from the RSM’s matrix. The combined representation is fed into an XGBoost model which enables robust material property analysis and regression. Feature-importance analysis via XGBoost and Integrated Gradients provide valuable insights into how anodizing parameters and surface features affect joint strength. Through the combination of numerical data (anodizing conditions and surface topographical features) and surface and fracture image analysis, the model significantly reduced the mean absolute percentage error from 18.8% to 10.7%. The findings highlight the pivotal role of integrating quantitative and qualitative information of structural materials to develop a robust and an accurate machine learning model.

界面附着力是决定航空航天和汽车行业复合材料结构整体强度和耐久性的关键因素。因此，了解基于界面的复合材料的破坏模式和裂纹扩展路径是提高体结构使用寿命的基础。本研究采用深度学习和信息融合技术实现粘接接头结构性能分析的自动化。首先，采用响应面法（RSM）设计了阳极氧化附著面（铝板）的实验矩阵；控制参数有浓度、电流和时间。表面形貌的特征是表面粗糙度和接触角以及扫描电子显微镜（SEM）图像。测试了阳极氧化铝-聚氨酯（Al-PU）粘接接头的界面强度，并通过扫描电镜进行了断裂分析。实验结果表明，在H2SO4浓度为0.5 M、电流为1.5 A、阳极氧化时间为45 min的条件下，界面抗剪强度比未处理的接头提高了920%。其次，采用了一种新的信息融合方法；该模型将利用ResNet从SEM图像中提取的特征与RSM矩阵中的数值数据相结合。该组合表示被馈送到XGBoost模型中，该模型实现了强大的材料性能分析和回归。通过XGBoost和集成梯度进行特征重要性分析，为阳极氧化参数和表面特征如何影响接头强度提供了有价值的见解。通过结合数值数据（阳极氧化条件和表面地形特征）以及表面和断口图像分析，该模型将平均绝对百分比误差从18.8%显著降低到10.7%。研究结果强调了整合结构材料的定量和定性信息以开发稳健和准确的机器学习模型的关键作用。

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引用次数: 0

Translaminar fracture limit curves for U-notched glass/epoxy composite laminates with different layup configurations subjected to mixed mode- I/II loading 混合I/II模式加载下不同层位的u形缺口玻璃/环氧复合材料层板的跨层断裂极限曲线

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-08-22 DOI: 10.1016/j.jcomc.2025.100642

E. Pirhadi , A.R. Torabi , Sahel Shahbaz , M. Petrů , S.S. R․ Koloor

Characterization of FRP composite laminate subjected to mixed-mode loading is one of the challenging topics in fracture mechanics. In this study, numerous experiments are conducted on U-notched rectangular tension (UNRT) specimens of various tip radii made of E-glass/epoxy composite with various layup configurations for experimental measurement of the translaminar U-notch fracture toughness (TLUNFT) of the composite laminates under mixed mode-I/II loading conditions. Two fracture limit curves are developed based on a two-dimensional stress distribution around the notch for predicting the mixed mode TLUNFT taking advantage of the maximum tangential stress (MTS) and the mean stress (MS) criteria as well as the virtual isotropic material concept (VIMC). It is revealed that both two-dimensional new models, namely the translaminar U-notch maximum tangential stress (TLUN-MTS) and the translaminar U-notch mean stress (TLUN-MS) criteria, can well estimate the experimental results obtained from testing the UNRT specimens made of the unidirectional (

{[0]}_{16}

) and quasi-isotropic (

{[0 / 90 / \pm 45]}_{2 s}

) E/glass epoxy composites. It should be underlined that this is the first time that some fracture limit curves have been developed by using the notch fracture mechanics (NFM) for estimating the TLUNFT of laminated composites subjected to mixed mode loading. These curves can be accurately, rapidly, and conveniently utilized to predict the last-ply-failure load of U-notched composite laminates subjected to in-plane loading conditions.

FRP复合材料层合板在混合模态载荷下的性能表征是断裂力学中具有挑战性的课题之一。本研究对不同铺层构型的e-玻璃/环氧复合材料不同尖端半径的u型缺口矩形拉伸（UNRT）试样进行了大量实验，实验测量了混合i /II加载条件下复合材料层板的跨层u型缺口断裂韧性（TLUNFT）。利用最大切向应力（MTS）和平均应力（MS）准则以及虚拟各向同性材料概念（VIMC），建立了基于缺口周围二维应力分布的两条断裂极限曲线，用于预测混合模式TLUNFT。结果表明，跨层u型缺口最大切向应力（tln - mts）和跨层u型缺口平均应力（tln - ms）两种新二维模型均能较好地估计单向（bbb16）和准各向同性（[0/90/±45]2s） E/玻璃环氧复合材料UNRT试样的试验结果。需要强调的是，这是第一次利用缺口断裂力学（NFM）建立了一些断裂极限曲线来估计复合材料在混合模式载荷下的TLUNFT。利用这些曲线可以准确、快速、方便地预测u形缺口复合材料层合板在面内加载条件下的最后失效载荷。

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引用次数: 0

Analysis of the structure and characteristics of bioglass–iron oxide composite layers on Ti-6Al-4V alloy via electrophoretic deposition 电泳沉积Ti-6Al-4V合金生物玻璃-氧化铁复合层的结构与特性分析

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-08-19 DOI: 10.1016/j.jcomc.2025.100639

Zahra Sohani, Hamed Jamshidi Aval, Sayed Mahmood Rabiee

This study investigates the structural and functional properties of bioglass–iron oxide (Fe₃O₄) composite layers deposited on Ti-6Al-4V substrates via electrophoretic deposition (EPD). Suspensions with varying Fe₃O₄ contents (10, 15, 25, and 50 wt %) were prepared to identify the optimal composition. SEM and elemental mapping revealed that the B90-F10 sample (90 % bioglass, 10 % Fe₃O₄) produced a more uniform and denser coating compared to other compositions, while minimizing porosity and crack formation. The Vickers microhardness of the B90-F10 coating reached 321.3 ± 3.4 HV, higher than that of the pure bioglass coating B100-F0 (295.1 ± 2.3 HV). Surface roughness measurements showed that B90-F10 had a lower average roughness (0.82 ± 0.41 µm) than B100-F0 (2.10 ± 0.46 µm), indicating a smoother, more compact surface. The mean coating thickness for B90-F10 was 148.32 ± 0.02 µm, slightly greater than B100-F0 (140.01 ± 0.01 µm). Contact angle tests confirmed improved hydrophilicity, with B90-F10 showing a reduced contact angle (22.56°) compared to the uncoated substrate (55.16°). Electrochemical tests revealed that although coatings slightly reduced corrosion resistance compared to bare alloy due to residual porosity, the addition of Fe₃O₄ significantly increased charge transfer resistance, indicating better barrier performance than pure bioglass coatings. In vitro bioactivity tests confirmed enhanced formation of hydroxyapatite layers, critical for osseointegration. These findings highlight the coatings’ capacity to augment implant performance by improving mechanical durability, surface characteristics, and bioactivity, thus offering a valuable functional enhancement beyond the untreated substrate.

研究了电泳沉积（EPD）在Ti-6Al-4V衬底上制备的生物玻璃-氧化铁（Fe₃O₄）复合层的结构和功能特性。制备了不同Fe₃O₄含量（10、15、25和50% wt %）的混悬液，以确定最佳组成。SEM和元素映射显示，B90-F10样品（90%生物玻璃，10% Fe₃O₄）与其他成分相比，产生了更均匀、更致密的涂层，同时最大限度地减少了孔隙度和裂纹的形成。B90-F10涂层的维氏显微硬度达到321.3±3.4 HV，高于纯生物玻璃涂层B100-F0（295.1±2.3 HV）。表面粗糙度测量表明，B90-F10的平均粗糙度（0.82±0.41µm）低于B100-F0(2.10±0.46µm)，表明表面更光滑，更致密。B90-F10的平均涂层厚度为148.32±0.02µm，略大于B100-F0（140.01±0.01µm）。接触角测试证实亲水性得到改善，与未涂覆的基材（55.16°）相比，B90-F10的接触角（22.56°）减小。电化学测试表明，尽管由于残余孔隙率的存在，涂层的耐腐蚀性略低于裸合金，但Fe₃O₄的加入显著提高了电荷转移阻力，表明涂层的阻隔性能优于纯生物玻璃涂层。体外生物活性测试证实羟基磷灰石层的形成增强，这对骨整合至关重要。这些发现强调了涂层通过提高机械耐久性、表面特性和生物活性来增强植入物性能的能力，从而提供了比未经处理的基底更有价值的功能增强。

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引用次数: 0

Thermoset (epoxy) - thermoplastic (polyetherimide) carbon fiber reinforced laminates featuring improved crack resistance in double cantilever beam tests due to hybridization 热固性（环氧）-热塑性（聚醚酰亚胺）碳纤维增强层压板，由于杂交，在双悬臂梁试验中具有更好的抗裂性

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-08-19 DOI: 10.1016/j.jcomc.2025.100643

Kay A. Weidenmann , René Alderliesten , Julie J.E. Teuwen

Fiber-metal laminates are a well-known and established material concept featuring an enhanced crack propagation resistance when compared to their metal and fiber reinforced plastic (FRP) constituents. In this paper, this approach is transferred to purely carbon fiber reinforced plastic (CFRP) based laminates made from layers having polyetherimide (PEI) and epoxy matrices in an alternating laminate architecture. The laminates are manufactured via hot pressing. Double-cantilever beam (DCB) tests are performed on standard samples for both the hybrid laminates in different configurations as well for the both constituent materials, i.e. carbon fiber reinforced PEI (CFR-PEI) and carbon fiber reinforced epoxy. As the formation of an interphase is already reported in literature for this matrix combination, microstructural investigations have also been carried out in addition to fractography on crack surfaces. It is shown that the hybrid materials outperform both constituents regarding the crack resistance when crack initiation starts in the tougher CFR-PEI layer and the laminate layup is 0/90°. In the other configurations investigated, there is no significant effect. The energy dissipating mechanisms are crack jumping and the formation of several parallel cracks. Consequently, crack resistance in such hybrids might be controlled in future by adjusting the crack resistance of the constituents as well as the laminate architecture.

金属纤维层压板是一种众所周知的材料概念，与金属和纤维增强塑料（FRP）成分相比，它具有更强的抗裂纹扩展能力。在本文中，这种方法被转移到纯碳纤维增强塑料（CFRP）为基础的层叠板，该层叠板由具有聚醚酰亚胺（PEI）和环氧树脂基质的层在交替层叠结构中制成。层压板是通过热压制造的。双悬臂梁（DCB）测试在标准样品上进行了不同配置的混合层合板，以及两种组成材料，即碳纤维增强PEI （CFR-PEI）和碳纤维增强环氧树脂。由于文献中已经报道了这种基体组合的界面相的形成，除了对裂纹表面进行断口学研究外，还进行了显微组织研究。结果表明，在较硬的CFR-PEI层中，当层积为0/90°时，杂化材料的抗裂性能优于两种材料。在调查的其他配置中，没有显著的影响。能量耗散机制为裂纹跳跃和多个平行裂纹的形成。因此，今后可以通过调整复合材料的抗裂性能和层压结构来控制复合材料的抗裂性能。

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引用次数: 0

Review of State-of-the-art of structural health monitoring in hydrogen composite pressure vessels 氢复合材料压力容器结构健康监测研究进展

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-08-19 DOI: 10.1016/j.jcomc.2025.100635

Lyazid Bouhala , Jérome Polesel , Argyrios Karatrantos , Séverine Perbal , Björn Senf , Alexander Hiekel , Heiner Reinhardt , Alexander Rauscher , Thomas Mäder

Ensuring the safety and durability of composite pressure vessels is critical due to their extensive use in aerospace, automotive, and energy sectors. This review examines recent advances in Structural Health Monitoring (SHM) technologies tailored for Composite Overwrapped Pressure Vessels (COPVs). Special focus is given to flexible strain sensors based on nanofillers such as carbon nanotubes, graphene, MXene, and polymer nanocomposites, which provide high sensitivity, stretchability, and tunable sensing behavior. Key sensing mechanisms including tunneling, piezo-resistivity, and crack propagation and fabrication methods influencing sensor performance and integration are discussed. Shape memory alloy (SMA) filament sensors are also analyzed for their exceptional fatigue resistance, elastic stretchability, and high gauge factors. Case studies demonstrate their practical effectiveness under cyclic pressure loading and burst tests. The review further highlights multifunctional composites integrating self-sensing features for next-generation smart pressure vessels. Challenges related to sensor embedding, environmental impacts, data processing, and scalability are addressed. Future research directions emphasize multi-scale modeling, machine learning for damage detection and prognosis, and fully autonomous SHM systems enabling real-time safety management. These advances are poised to enhance reliability, reduce maintenance costs, and extend the operational life of composite pressure vessels in demanding industrial applications.

由于复合材料压力容器在航空航天、汽车和能源领域的广泛应用，确保其安全性和耐久性至关重要。本文综述了复合材料包覆压力容器（copv）结构健康监测（SHM）技术的最新进展。特别关注基于纳米填充物的柔性应变传感器，如碳纳米管、石墨烯、MXene和聚合物纳米复合材料，它们提供高灵敏度、可拉伸性和可调谐的传感行为。讨论了影响传感器性能和集成的关键传感机制，包括隧道效应、压电阻率、裂纹扩展和制造方法。形状记忆合金（SMA）长丝传感器也因其优异的抗疲劳性、弹性拉伸性和高规格因素而被分析。实例研究证明了该方法在循环压力加载和爆破试验中的实际有效性。该综述进一步强调了集成自传感功能的多功能复合材料用于下一代智能压力容器。解决了与传感器嵌入、环境影响、数据处理和可扩展性相关的挑战。未来的研究方向强调多尺度建模、用于损伤检测和预测的机器学习，以及实现实时安全管理的全自动SHM系统。这些进步将提高可靠性，降低维护成本，并延长复合压力容器在苛刻的工业应用中的使用寿命。

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引用次数: 0

Machining-induced burr distribution along hole contours in unidirectional carbon fibre-reinforced polymer (UD-CFRP) composites 单向碳纤维增强聚合物（UD-CFRP）复合材料孔轮廓加工诱导毛刺分布

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-08-19 DOI: 10.1016/j.jcomc.2025.100640

Norbert Geier, Gergely Magyar

Machining-induced burr formation in carbon fibre-reinforced polymer (CFRP) composites is difficult to predict and control, mainly due to the anisotropy and inhomogeneity of the fibrous composite, as well as the rapid tool condition change due to the abrasive tool wear. The main aim of this study is to develop a model to determine the density and distribution functions of risky fibre cutting angles where machining-induced burrs are expected to be formed when hole-machining CFRPs. Four models were introduced, and their adequacy was analysed. The coefficients of the models were determined using datasets of three previous research projects (i.e., 2 380 808 data points) and validated through a fourth one (208 571 data points) where hole machining experiments were carried out using different tools, parameters and setups. The normality of the risky fibre cutting angles was tested through the Shapiro-Wilk and Kolmogorov-Smirnov statistical tests, and the distribution was found to be not Gaussian. The developed trigonometric model shows a good fit to the data points, i.e., the determination coefficient is at least 0.949 for each dataset. The results indicate that machining-induced burr formation is most probable at a fibre cutting angle of 118–133°, and 60 % of burr occurrences fall within the 110°–160° range when the critical fibre cutting angle is 133° These findings provide a foundation for the industrial adoption of advanced machining strategies for fibrous polymer composites, enabling a significant reduction of machining‑induced burrs in CFRPs.

碳纤维增强聚合物（CFRP）复合材料加工诱导毛刺的形成是难以预测和控制的，这主要是由于纤维复合材料的各向异性和非均匀性，以及磨具磨损引起的刀具状态的快速变化。本研究的主要目的是建立一个模型，以确定在孔加工cfrp时可能形成加工诱发毛刺的危险纤维切割角的密度和分布函数。介绍了四种模型，并对其充分性进行了分析。模型的系数是利用之前三个研究项目的数据集（即2 380 808个数据点）确定的，并通过第四个研究项目（208 571个数据点）进行验证，其中使用不同的工具，参数和设置进行孔加工实验。通过Shapiro-Wilk和Kolmogorov-Smirnov统计检验检验了危险纤维切割角的正态性，发现其分布是非高斯分布。所建立的三角模型与数据点拟合良好，每个数据集的决定系数至少为0.949。结果表明，纤维切削角度为118-133°时，加工诱发毛刺的可能性最大，当纤维切削角度为133°时，60%的毛刺发生在110°-160°范围内。这些发现为工业采用先进的纤维聚合物复合材料加工策略提供了基础，使碳纤维复合材料的加工诱发毛刺显著减少。

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引用次数: 0

Impact resistance of heated and unheated two-way slab reinforced with basalt fiber 玄武岩纤维增强加热与未加热双向板的抗冲击性能

IF 7 Q2 MATERIALS SCIENCE, COMPOSITES

Composites Part C Open Access

Pub Date : 2025-08-13 DOI: 10.1016/j.jcomc.2025.100638

Ahmed Ashteyat , Ala T. Obaidat , Tarik Kharabsheh , Ahmed Fayez , Ahmad Al-Khreisat , Mu'tasim Abdel-Jaber

This research investigates the effect of using basalt fiber with different ratios on the impact resistance of heated and unheated two-way slab. Twelve heated and unheated two-way slab specimens of (1.05 m x 1.05 m x 0.07 m) were cast with different basalt fiber ratios of (0.25, 0.50, 0.75, 1.00, and 1.25) % by weight of cement and two fiber lengths of 12 and 24 mm have been exposed to ambient temperature and elevated temperature of (600 °C). This experiment investigates the effect of basalt fiber on the behavior of two-way slab in terms of compressive strength of concrete, punching shear failure, deflection, stiffness, and induced strain. The results showed that adding basalt fibers with different ratios experienced minor improvements in the concrete compressive strength for all specimens. The application of the impact load resulted in the formation of radial and conic cracks originating at the center of the specimen. These cracks indicated that the primary mode of failure is punching shear. Additionally, in this study, it was observed that a gradual increase in the proportion of basalt fibers led to a reduction in both the length and number of cracks. Moreover, for the pattern of the cracks due to static load, it was observed that the development of conical cracks was a result of overloading. The specimen incorporating a 24 mm basalt fiber at a 1 % ratio under unheated conditions demonstrated the significant improvement in performance regarding cracking compared to control. The stiffness and deflection of the specimens were improved by increasing the proportion of basalt fiber. Additionally, employing 24 mm fibers resulted in reduced deflection and increased stiffness compared to using 12 mm fibers.

研究了玄武岩纤维不同配比对加热和未加热双向板抗冲击性能的影响。12个加热和未加热的双向板试件（1.05 m x 1.05 m x 0.07 m）浇铸了不同的玄武岩纤维比（0.25、0.50、0.75、1.00和1.25）%的水泥重量，两种纤维长度分别为12和24 mm，暴露在环境温度和高温（600°C）下。本试验从混凝土抗压强度、冲剪破坏、挠度、刚度和诱导应变等方面考察了玄武岩纤维对双向板性能的影响。结果表明，添加不同比例的玄武岩纤维对各试件的抗压强度均有较小的改善。冲击载荷的作用导致试样中心形成径向裂纹和锥形裂纹。这些裂缝表明，主要破坏方式为冲剪破坏。此外，在本研究中还观察到，随着玄武岩纤维比例的逐渐增加，裂缝的长度和数量都会减少。此外，对于静荷载引起的裂纹模式，观察到锥形裂纹的发展是超载的结果。在不加热的条件下，以1%的比例加入24毫米玄武岩纤维的试样与对照组相比，在开裂方面表现出显著的改善。增加玄武岩纤维的掺量可以改善试件的刚度和挠度。此外，与使用12毫米纤维相比，使用24毫米纤维减少了挠度，增加了刚度。

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