今日更新:Composite Structures 4 篇,Composites Part A: Applied Science and Manufacturing 1 篇,Composites Part B: Engineering 3 篇,Composites Science and Technology 4 篇
Analytical prediction and numerical verification of stress concentration profile around an in-situ tow break in resin-impregnated filament-wound composites
Jiakun Liu, Stuart Leigh Phoenix
doi:10.1016/j.compstruct.2024.118185
树脂浸渍长丝缠绕复合材料原位断裂应力集中分布分析预测及数值验证
A new empirical analytical approach is developed for predicting the stress concentration profile around an in-situ tow break in filament-wound composites. A shear-lag analysis is firstly performed to solve for the perturbational axial displacement of the broken tow and resultant debonding lengths. Solution of stress field caused by tangential load on the surface of an elastic half space is then utilized in combination with superposition concepts to obtain the overload magnitudes in the neighboring tows. Subsequently, high-fidelity finite element analysis on a representative uni-directional laminate model under different stress states is performed, and excellent overall agreement is observed between analytical and numerical predictions. The proposed method takes into account essential aspects such as transversely isotropic material properties, in-situ stress states and their effect on the interfacial frictional forces in the debonded interfaces, and thus provides a convenient way to evaluate the stress concentration factors in damaged filament-wound composites. In addition, this approach can be applied to yield auxiliary failure evaluation criteria for statistical strength prediction or finite element modeling of filament-wound composites or similar structures.
提出了一种新的经验分析方法来预测长丝缠绕复合材料原位断裂附近的应力集中分布。首先进行了剪切滞后分析,以求解断裂拖缆的扰动轴向位移和由此产生的脱粘长度。然后,结合叠加概念,利用切向载荷在弹性半空间表面引起的应力场的解,得到邻近城镇的过载幅度。随后,对具有代表性的单向层合板模型在不同应力状态下进行了高保真有限元分析,分析结果与数值预测结果基本吻合。该方法考虑了材料的横向各向同性特性、地应力状态及其对脱粘界面摩擦力的影响等重要方面,为评价损伤丝缠绕复合材料的应力集中系数提供了一种便捷的方法。此外,该方法可应用于丝缠绕复合材料或类似结构的屈服辅助失效评估准则的统计强度预测或有限元建模。
Extended multiscale FEM-based concurrent optimization of three-dimensional graded lattice structures with multiple microstructure configurations
Xinglong Chen, Hui Liu, Peng Wei
doi:10.1016/j.compstruct.2024.118186
基于扩展多尺度有限元的多微结构三维梯度点阵结构并行优化
In this work, a novel concurrent design method for three-dimensional graded lattice structures considering multiple microstructure configurations is proposed. Firstly, the Multiple Variable Cutting (M-VCUT) level set method is employed to represent the geometry of lattice microstructures and define the optimization parameters. Then, the extended multiscale finite element method (EMsFEM) is implemented for calculating the equivalent stiffness matrices of microstructures in offline form. Compared with the traditional homogenization-based multiscale approaches, the proposed method eliminates the scale separation assumptions and takes into account the coupling effects in different directions of materials. In addition, a data-driven method and a parallel computing approach are integrated together so that computational efficiency can be greatly improved. After the iteration process, the optimized full-scale graded structures are reconstructed using interpolation technology to generate well-connected microstructures in neighboring cells. Finally, several 3D numerical examples are utilized to validate the effectiveness of the proposed method, where multiple lattice microstructure configurations are considered, including truss-lattices and plate-lattices.
本文提出了一种考虑多种微观结构的三维梯度点阵结构并行设计方法。首先,采用多变量切割(M-VCUT)水平集方法对点阵微结构的几何形状进行表征,并定义优化参数;然后,采用扩展多尺度有限元法(EMsFEM)计算微结构的离线等效刚度矩阵。与传统的基于均质化的多尺度方法相比,该方法消除了尺度分离假设,并考虑了材料不同方向的耦合效应。此外,将数据驱动方法与并行计算方法相结合,大大提高了计算效率。经过迭代过程,利用插值技术重构优化后的全尺寸梯度结构,在相邻单元中生成连接良好的微结构。最后,利用几个三维数值算例验证了该方法的有效性,其中考虑了包括桁架晶格和板晶格在内的多种晶格微观结构构型。
Prediction of allowable compression load for notched composite laminates combining FEA simulation and machine learning
Ziyi Li, Huasong Qin, Qingfeng Wang, Liyong Jia, Guoqiang Zhang, Yushu Li, Yilun Liu
doi:10.1016/j.compstruct.2024.118188
结合有限元模拟和机器学习的缺口复合材料层合板许用压缩载荷预测
Determining the allowable compression load (ACL) of notched composite laminates (NCL) requires consideration of buckling, intra- and inter-laminar damage, which is a costly and repetitive task due to the high dimensional and nonlinear relation of ACL to the numerous design variables. In this work, a high-throughput finite element analysis (FEA) and machine learning (ML) combined approach is proposed to predict ACL of laminates. First, the high-throughput FEA model of NCL covering all of the design variables is generated, and the corresponding critical compression loads in terms of buckling, intra- and inter-laminar damage are obtained. Then, ML models are trained, with inputs being the design variables of NCL and outputs being the critical compression loads. ACL and initial failure mode are determined by the minimum compression load of the three failure modes. Moreover, transfer learning is introduced to laminates with new design variables of new ply number, notch shape and laminate type. By fine-tuning the pre-trained ML model using scarce new data, the fine-tuned models are suitable for new laminates. Consequently, ACL and initial failure mode of notched laminates with various design variables are predicted.
确定缺口复合材料层合板(NCL)的许用压缩载荷(ACL)需要考虑屈曲、层内和层间损伤,由于ACL与众多设计变量的高维非线性关系,这是一项昂贵且重复的任务。在这项工作中,提出了一种高通量有限元分析(FEA)和机器学习(ML)相结合的方法来预测层压板的ACL。首先,建立了覆盖所有设计变量的NCL高通量有限元模型,得到了相应的屈曲、层内损伤和层间损伤的临界压缩载荷;然后,训练ML模型,输入是NCL的设计变量,输出是临界压缩负载。ACL和初始失效模式由三种失效模式的最小压缩载荷确定。此外,将迁移学习引入到层压板中,并引入了新层数、缺口形状和层压板类型等新的设计变量。通过使用稀缺的新数据对预训练的ML模型进行微调,微调后的模型适用于新的层压板。从而对不同设计变量下缺口层合板的ACL和初始破坏模式进行了预测。
Explainable artificial intelligence framework for FRP composites design
Mostafa Yossef, Mohamed Noureldin, Aghyad Alqabbany
doi:10.1016/j.compstruct.2024.118190
可解释的FRP复合材料设计人工智能框架
Fiber-reinforced polymer (FRP) materials are integral to various industries, from automotive and aerospace to infrastructure and construction. While FRP composite design guidelines have been established, the process of obtaining the desired strength of an FRP composite demands considerable time and resources. Despite recent advancements in Machine Learning (ML) models which are commonly used as predictive models, the inherent 'black box' nature of those models poses challenges in understanding the relationship between input design parameters and output strength of the composite. Moreover, these models do not provide tools to facilitate the designing process of the composite. The current study introduces an explainable Artificial Intelligence (XAI) framework that will provide understanding for the input–output relationships of the model through SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs). In addition, the framework provides for the first time a designing approach for adjusting the important design parameters to obtain the desired composite strength by the designer through utilizing an explainability technique called Counterfactual (CF). The framework is evaluated through the design of a 14-ply composite, successfully identifying critical design parameters, and specifying necessary adjustments to meet strength requirements.
从汽车和航空航天到基础设施和建筑,纤维增强聚合物(FRP)材料是各个行业不可或缺的一部分。虽然FRP复合材料设计指南已经建立,但获得FRP复合材料所需强度的过程需要大量的时间和资源。尽管机器学习(ML)模型最近取得了进步,通常用作预测模型,但这些模型固有的“黑箱”性质对理解输入设计参数与复合材料输出强度之间的关系提出了挑战。此外,这些模型并没有提供工具来促进复合材料的设计过程。目前的研究引入了一个可解释的人工智能(XAI)框架,该框架将通过SHapley加性解释(SHAP)和部分依赖图(pdp)为模型的输入输出关系提供理解。此外,该框架首次提供了一种设计方法,通过利用一种称为反事实(CF)的可解释性技术来调整重要的设计参数以获得所需的复合强度。通过设计14层复合材料对框架进行评估,成功确定关键设计参数,并指定必要的调整以满足强度要求。
Novel modification strategy via GO and polyurethane for epoxy nanocomposites: Simultaneous enhancements of fracture toughness and liquid oxygen compatibility for cryotank applications
Fang-Liang Guo, Tao Wu, De-Yi Qu, Wan-Dong Hou, Tao Guan, Yu-Tong Fu, Yuan-Qing Li, Shao-Yun Fu
doi:10.1016/j.compositesa.2024.108259
氧化石墨烯和聚氨酯改性环氧纳米复合材料的新策略:同时增强低温储罐应用的断裂韧性和液氧相容性
Fracture toughness and liquid oxygen (LOX) compatibility of epoxy nanocomposites for liquid oxygen composite cryotank applications are two main concerns. In this work, a novel rigid-and-soft hybrid-microstructure modification strategy is proposed to improve these two properties simultaneously. Graphene oxide (GO) nanosheets are physically incorporated, and polyurethane (PU) particles are formed through phase-separation process. When 10 parts of PU and 0.1 parts of GO are added into 100 parts of epoxy (i.e., 10 phr PU and 0.1 phr GO), the fracture toughness is enhanced by 207.26% at room temperature and 243.02 % at 90 K, respectively. Meanwhile, no sensitivity phenomena such as explosion, burning, flash, or charring for the nanocomposite are observed during liquid oxygen impact testing. Consequently, experimental characterizations and multiscale finite element models are utilized to reveal the synergistic effects of GO and PU on fracture behaviors and impact energy absorption.
环氧纳米复合材料的断裂韧性和液氧相容性是液氧复合材料低温储罐应用的两个主要问题。在这项工作中,提出了一种新的刚软混合微观结构改性策略,以同时改善这两种性能。氧化石墨烯(GO)纳米片物理掺入,聚氨酯(PU)颗粒通过相分离过程形成。在100份环氧树脂中加入10份PU和0.1份GO(即10份PU和0.1份GO),室温下断裂韧性提高207.26%,90 K时断裂韧性提高243.02 %。同时,在液氧冲击试验中没有观察到纳米复合材料的爆炸、燃烧、闪光、炭化等敏感现象。因此,利用实验表征和多尺度有限元模型来揭示氧化石墨烯和聚氨酯对断裂行为和冲击能吸收的协同效应。
Directional saturation of a strongly bimodal pore size distribution carbon interlock fabric: Measurement and multiphase flow modeling
Gabriela Gambarini, Gabriel Valdés-Alonzo, Christophe Binetruy, Sébastien Comas-Cardona, Elena Syerko, Marc Waris
doi:10.1016/j.compositesb.2024.111532
强双峰孔径分布碳互锁织物的定向饱和:测量和多相流建模
This study focuses on the analysis of the directionality of saturation of materials with bimodal pore size distributions. The material studied is an anisotropic carbon interlock with highly contrasted dual-scale porosity, with heavy warp and light weft tows. Experimentally, 6 configurations are tested using injection combined with dielectric sensors to measure saturation times and unsaturated lengths. The experimental results show that this material has a high contrast in dual-scale porosity and the unsaturation is anisotropic. In parallel, a two-phase flow in porous media continuum model is developed within the OpenFOAM® toolbox of libraries to simulate the transient impregnation. The need to use a tensorial relative permeability and its alignment with the saturated permeability is analyzed by a numerical multiphase mesoscale flow model. The combined experimental and numerical analysis paves the way for a methodology to analyze the saturation of various bimodal pore size distribution materials.
本研究着重分析了具有双峰孔径分布的材料的饱和方向性。所研究的材料是一种各向异性碳联锁材料,具有高度对比的双尺度孔隙率,经纱重,纬纱轻。实验上,采用注入结合介电传感器对6种构型进行了饱和时间和非饱和长度的测量。实验结果表明,该材料在双尺度孔隙度上具有较高的对比度,且不饱和具有各向异性。同时,在OpenFOAM®库工具箱中开发了多孔介质连续介质中的两相流模型,以模拟瞬态浸渍。利用数值多相中尺度渗流模型分析了张量相对渗透率的必要性及其与饱和渗透率的排列关系。实验与数值分析相结合的方法为分析各种双峰孔径分布材料的饱和度奠定了基础。
Analysis of subsurface damage during milling of CFRP due to spatial fibre cutting angle, tool geometry and cutting parameters
Felicitas Böhland, Andreas Hilligardt, Volker Schulze
doi:10.1016/j.compositesb.2024.111533
空间纤维切削角度、刀具几何形状和切削参数对CFRP铣削亚表面损伤的影响分析
During machining of carbon fibre reinforced plastics the anisotropy of the material and the resulting cutting conditions can cause various types of damage such as delamination, burrs or subsurface damage. Subsurface damage can lead to a reduction in surface quality or component rejection. In this paper, a new method is used to detect subsurface damage caused by peripheral milling over the entire cut. This analysis, using a newly defined spatial fibre cutting angle θne, tool geometry and process parameter, provides a deeper understanding of the damage formation. While the damage area varies with the uncut chip thickness and the rake angle of the tool, the cutting edge rounding and the fibre cutting angle prove to be important in determining the depth of damage. The detected damage area is 44-65% of the fibre cutting angle range from 0° to 90°, which can be extended up to 12 % due to the damage depth when milling an external radius.
在碳纤维增强塑料的加工过程中,材料的各向异性和由此产生的切削条件会导致各种类型的损伤,如分层、毛刺或亚表面损伤。亚表面损伤会导致表面质量下降或部件报废。本文提出了一种新的方法来检测整个切削过程中外围铣削引起的亚表面损伤。该分析使用了新定义的空间纤维切削角θne、刀具几何形状和工艺参数,可以更深入地了解损伤形成。虽然损伤区域随未切割切屑厚度和刀具前倾角而变化,但切割边缘的圆角和纤维切割角度在确定损伤深度方面是重要的。在0°至90°的纤维切割角度范围内,检测到的损伤区域为44-65%,当铣削外部半径时,由于损伤深度的原因,可扩展到12%。
Utilizing Methacrylated Lignin as a Sustainable Macro-Crosslinker for Synthesizing Innovative PVA/AMPS Composites Crosslinked Hydrogel Nanofibers: A Potential Application for Lithium-Ion Battery Separators
Yun Dou, Shen Li, Shoujuan Wang, Magdi E. Gibril, Fangong Kong
doi:10.1016/j.compositesb.2024.111537
利用甲基丙烯酸木质素作为可持续宏观交联剂合成新型PVA/AMPS复合交联水凝胶纳米纤维:锂离子电池隔膜的潜在应用
There are significant issues with commercial separators that must be resolved before they can be used in high-energy-density batteries. These problems include low porosity, poor electrolyte wetting, and low mechanical properties. This study presents a facile method for preparing composite crosslinked hydrogel nanofibers of polyvinyl alcohol (PVA) with 2-acrylamide-2-methylpropanesulfonic acid (AMPS) for lithium-ion battery separators by utilizing methacrylated lignin (LMA) as a bio-based crosslinker. Initially, LMA was synthesized by grafting glycidyl methacrylate (GMA) onto lignin via esterification. Subsequently, a crosslinked hydrogel nanofiber membrane (PVA/AMPS-LMA) was electrospun with varying LMA fractions, which were polymerized by combining free radical copolymerization and esterification reactions. The effectiveness of LMA as a crosslinker was assessed against the N, N'-methylene bisacrylamide (MBA). The study showed that using LMA as a crosslinker significantly improved the membrane's properties. The PVA/AMPS-LMA separator displayed superior features such as mechanical strength, thermal stability, porosity, electrolyte uptake, ionic conductivity, and lithium-ion transference number, when compared with PVA/AMPS, PVA, and Celgard separators. Specifically, the PVA/AMPS-LMA separator demonstrated a high mechanical strength of 24.9 MPa, strong thermal stability at 170 °C with no shrinkage, high porosity (84.3%), and electrolyte uptake (661.4%). It also exhibited exceptional ionic conductivity (2.75 mS/cm) and a notable lithium-ion transference number (tLi+ = 0.717). In coin batteries, the PVA/AMPS-LMA separator retained over 96% capacity (142.4 mAh/g) after 200 cycles at 1C. This performance exceeded that of PVA/AMPS, PVA, and Celgard separators, suggesting that PVA/AMPS-LMA separators have the potential to replace their commercial counterparts.
商用分离器在用于高能量密度电池之前,必须解决一些重大问题。这些问题包括孔隙率低、电解质润湿性差和机械性能低。以甲基丙烯酸木质素(LMA)为交联剂,制备了2-丙烯酰胺-2-甲基丙磺酸(AMPS) -聚乙烯醇(PVA)复合交联水凝胶纳米纤维,用于锂离子电池隔膜。最初,通过酯化反应将甲基丙烯酸缩水甘油酯(GMA)接枝到木质素上合成了甲基丙烯酸缩水甘油酯。随后,采用不同LMA组分的电纺丝制备交联水凝胶纳米纤维膜(PVA/AMPS-LMA),通过自由基共聚和酯化反应进行聚合。对LMA作为交联剂与N, N'-亚甲基双丙烯酰胺(MBA)的交联效果进行了评价。研究表明,使用LMA作为交联剂可以显著改善膜的性能。与PVA/AMPS、PVA和Celgard分离器相比,PVA/AMPS- lma分离器在机械强度、热稳定性、孔隙度、电解质吸收、离子电导率和锂离子转移数等方面表现出了卓越的性能。具体来说,PVA/AMPS-LMA分离器具有24.9 MPa的高机械强度,170°C时的高热稳定性,无收缩,高孔隙率(84.3%)和电解质吸收率(661.4%)。它还表现出优异的离子电导率(2.75 mS/cm)和显著的锂离子转移数(tLi+ = 0.717)。在硬币电池中,在1C下循环200次后,PVA/AMPS-LMA分离器保留了超过96%的容量(142.4 mAh/g)。这一性能超过了PVA/AMPS、PVA和Celgard分离剂,表明PVA/AMPS- lma分离剂有潜力取代商用分离剂。
Characterizing damage evolution in fiber reinforced composites using in-situ X-ray computed tomography, deep machine learning and digital volume correlation (DVC)
Yuansong Wang, Qingling Chen, Quantian Luo, Qing Li, Guangyong Sun
doi:10.1016/j.compscitech.2024.110650
利用原位x射线计算机断层扫描、深度机器学习和数字体积相关(DVC)表征纤维增强复合材料的损伤演变
In-situ X-ray computed tomography (CT) techniques enable to examine microstructural evolution of composite materials continuously and nondestructively under loading for better understanding the initiation and propagation of microscopic damages. This study explores the tensile damage behavior of notched woven carbon/epoxy composites under successive loading process. Since the image contrast of different composite material phases is normally low and conventional image segmentation techniques are hard to identify microstructures and defects in different directions distinctively, a U-Net image segmentation model based on deep machine learning algorithms is employed to characterize microstructures and material damages precisely and consistently. Digital volume correlation (DVC) approach is proposed here to measure the three-dimensional (3D) deformation fields of carbon/epoxy composites at different loading steps, and the DVC results are used to predict location of damage initiation and propagation. It is found that the damage modes of notched carbon/epoxy composites mainly include fiber breakage, longitudinal cracks in warp fiber tows, and transverse cracks in weft fiber tows. The individual fiber breakage occurs in warp fiber tows at the intermediate loading level, and longitudinal and transverse cracks appear in further loading levels. Longitudinal cracks and fiber breakage events take place in a region tangent to the notch tip and exhibit a strong interaction. The development of longitudinal cracks promotes the initiation and propagation of transverse cracks. In addition, the strain concentration regions in 3D deformation fields match well with the microscopic cracks segmented by the U-Net deep learning model. This study demonstrated that the integration of X-ray computed tomography, digital volume correlation and image semantic segmentation enables to identify damage initiation, evolution, extent and mechanism.
原位x射线计算机断层扫描(CT)技术能够连续无损地检测复合材料在载荷作用下的微观结构演变,从而更好地了解微观损伤的发生和扩展。研究了缺口编织碳/环氧复合材料在连续加载过程中的拉伸损伤行为。针对复合材料不同相的图像对比度通常较低,传统图像分割技术难以清晰识别不同方向的微结构和缺陷的问题,采用基于深度机器学习算法的U-Net图像分割模型,对微结构和材料损伤进行精确、一致的表征。提出了基于数字体积相关(DVC)的碳/环氧复合材料在不同加载步骤下的三维变形场测量方法,并利用DVC结果预测损伤起裂和扩展的位置。研究发现,缺口型碳/环氧复合材料的损伤模式主要包括纤维断裂、经纤维束纵向裂纹和纬纤维束横向裂纹。在中间加载阶段,经纱纤维束出现单个纤维断裂,在进一步加载阶段出现纵向和横向裂纹。纵向裂纹和纤维断裂事件发生在缺口尖端的切线区域,并表现出强烈的相互作用。纵向裂纹的发展促进了横向裂纹的萌生和扩展。此外,三维变形场中的应变集中区域与U-Net深度学习模型分割的微观裂纹匹配良好。研究表明,将x射线计算机断层扫描、数字体积相关和图像语义分割相结合,可以识别损伤的发生、演化、程度和机制。
Effect of in-situ activated Core-Shell Particles on Fatigue behavior of Carbon Fiber reinforced Thermoplastic Composites
Anurag Sharma, Sunil C. Joshi
doi:10.1016/j.compscitech.2024.110654
原位活化核壳颗粒对碳纤维增强热塑性复合材料疲劳性能的影响
In this unique study, the effect of adding core-shell particles (CSPs) on fatigue performance of carbon-fiber reinforced PA6 (CF-PA6) laminates is investigated. The thermoplastic laminates were prepared using compression molding and were reinforced at ply interfaces with 2wt% and 4wt% CSPs of the polymer mass. A manual method was used to disperse CSPs using a sieve and carefully selected process parameters. The cyclic tests were conducted and assessed, considering S-N curve, stiffness degradation, and energy dissipation. Consequently, the fatigue life of modified composites is improved respectively by eight and four times when 2wt% and 4wt% CSPs are used. The results showed that an optimal improvement was achieved with a 2wt% CSPs. The fatigue strength coefficient (FSC) and fatigue strength exponent (FSE) of CF-PA6 composites improved by 22.13% and 9.85%, respectively. The findings have the potential to establish a new frontier in thermoplastic research and would help designers to enhance the fatigue properties of thermoplastic laminates in specific elastic tailoring structures.
在这项独特的研究中,研究了添加核壳颗粒(CSPs)对碳纤维增强PA6 (CF-PA6)层合板疲劳性能的影响。采用压缩成型技术制备热塑性层压板,并在层合界面上分别添加2wt%和4wt%的聚合物质量CSPs进行增强。采用人工方法,用筛子和精心选择的工艺参数分散csp。循环试验进行了评估,考虑S-N曲线,刚度退化和能量耗散。结果表明,使用2wt% CSPs和4wt% CSPs时,改性复合材料的疲劳寿命分别提高了8倍和4倍。结果表明,当csp浓度为2wt%时,效果最佳。复合材料的疲劳强度系数(FSC)和疲劳强度指数(FSE)分别提高了22.13%和9.85%。这些发现有可能在热塑性塑料研究中建立一个新的前沿,并将帮助设计师提高热塑性层压板在特定弹性剪裁结构中的疲劳性能。
MatrixCraCS: Automated tracking of matrix crack development in GFRP laminates undergoing large tensile strains
Asbjørn Malte Olesen, Brian Lau Verndal Bak, Jens Jakob Bender, Esben Lindgaard
doi:10.1016/j.compscitech.2024.110638
MatrixCraCS:自动跟踪GFRP层合板在大拉伸应变下的基体裂纹发展
A novel image processing method for tracking development of matrix cracks in glass-fibre reinforced polymer (GFRP) laminates is presented. Images are acquired in a quasi-static tension test using transillumination white light imaging. These images show changes occurring due to developing damage. The method, called MatrixCraCS, tracks and quantifies matrix cracks while compensating for large specimen deformation and stitching threads, which obscure crack development and seriously impact crack detection. Matrix cracks are tracked via a sequential image difference and morphological filtering is used to detect cracks. MatrixCraCS is verified against synthetic images and shows an error of less than 7% in the quantified length of cracks and 0% detection failures. MatrixCraCS is validated against experimental results for a [ ± 4 5 2 ° 9 0 2 ° ] S GFRP laminate, where microscopic analysis shows 5.92% error in crack detection. Error relative to manual crack tracking are quantified for detection failures and false positives as 3.3% and 1.57%, respectively. It is found that the method accurately quantifies cracks in GFRP laminates subject to large deformation and is robust against noise.
提出了一种新的图像处理方法,用于跟踪玻璃纤维增强聚合物(GFRP)层合板中基体裂纹的发展。图像是在准静态张力测试中使用透照白光成像获得的。这些图像显示了由于发展中的损伤而发生的变化。该方法被称为MatrixCraCS,它可以跟踪和量化矩阵裂纹,同时补偿较大的试样变形和拼接螺纹,这些变形和拼接螺纹模糊了裂纹的发展,严重影响了裂纹的检测。通过序列图像差分跟踪矩阵裂纹,并用形态学滤波检测裂纹。MatrixCraCS与合成图像进行了验证,结果表明,裂缝长度量化误差小于7%,检测失败率为0%。MatrixCraCS与[±4 5 2°9 0 2°]S GFRP层叠板的实验结果进行了验证,微观分析显示裂纹检测误差为5.92%。相对于人工裂缝跟踪,检测失败和误报的误差分别量化为3.3%和1.57%。结果表明,该方法能准确地量化大变形玻璃钢层合板的裂纹,且对噪声具有较强的鲁棒性。
Formation of transverse cracks in cross ply laminates in an environment of nonuniformly distributed fibers
Sarah A. Elnekhaily, Linqi Zhuang, Ramesh Talreja
doi:10.1016/j.compscitech.2024.110651
纤维不均匀分布环境下交叉层合板横向裂纹的形成
This work is concerned with extracting characteristic features of transverse crack formation in cross ply laminates under axial tension considering nonuniform distribution of fibers in the ply cross section. The fiber-matrix debond crack initiation sites are determined first by the dilatation induced cavitation criterion for an epoxy matrix. The growth of the debond cracks is analyzed by calculating the energy release rates using the virtual crack closure technique. The kink-out of the debond cracks into the matrix is determined in short incremental steps by the maximum energy release rate criterion. Different scenarios are considered for the linking up of the kinked-out cracks to form continuous transverse cracks. By studying two different degrees of fiber distribution nonuniformity, the interactive effects due to the fiber distribution on the transverse crack formation are clarified.
考虑纤维在铺层截面上的不均匀分布,提取轴向拉伸作用下交叉铺层板横向裂纹形成的特征特征。纤维基体的脱粘裂纹起裂位置首先由环氧基体的膨胀诱导空化准则确定。利用虚拟裂纹闭合技术计算了裂纹的能量释放率,分析了裂纹的扩展过程。根据最大能量释放率准则,在短增量步骤中确定脱粘裂纹向基体的扭结。在不同的情况下,考虑了扭结裂缝连接形成连续的横向裂缝。通过对两种不同程度的纤维分布不均匀性的研究,阐明了纤维分布对横向裂纹形成的相互作用。