【新文速递】2023年9月21日固体力学SCI期刊最新文章
International Journal of Solids and Structures
Multiscale model for failure prediction of carbon-fiber-reinforced composites under off-axis load
Watanabe Tadashi, Kawagoe Yoshiaki, Shirasu Keiichi, Okabe Tomonaga
doi:10.1016/j.ijsolstr.2023.112489
偏轴载荷下碳纤维增强复合材料失效预测的多尺度模型
Herein, a multiscale model comprising a quantum-chemical reaction path calculations, molecular dynamics (MD) simulations, and filament and laminate scale finite-element analyses (FEA) is proposed for predicting the failure of carbon-fiber-reinforced composites. In this study, the correlation between MD simulations and filament scale FEA was investigated and complemented. By this complementation, mechanical properties of a resin matrix used in FEA are evaluated by experiment-free MD simulations. The evaluated material properties, namely, failure properties and elasto-plastic properties of the resin matrix were validated using the results of compressive tests for neat resins DGEBA/4,4’-DDS, DGEBA/DETA, and TGDDM/4,4’-DDS. The predicted failure strain of the composites, under off-axis loads, were found to be in good agreement with previously reported experimental results. The FEA results revealed that both the failure and elasto-plastic properties of the resin matrix contribute to the failure of the composites, and the dominant properties vary for the laminate and load configuration.
本文提出了一种多尺度模型，包括量子化学反应路径计算、分子动力学（MD）模拟以及丝状和层状有限元分析（FEA），用于预测碳纤维增强复合材料的失效。在本研究中，对 MD 模拟和长丝尺度有限元分析之间的相关性进行了研究和补充。通过这种互补，可以通过无实验的 MD 模拟来评估有限元分析中使用的树脂基体的机械性能。通过对纯树脂 DGEBA/4,4'-DDS、DGEBA/DETA 和 TGDDM/4,4'-DDS进行压缩试验，验证了所评估的材料特性，即树脂基体的破坏特性和弹塑性特性。结果发现，复合材料在离轴载荷下的预测破坏应变与之前报告的实验结果非常吻合。有限元分析结果表明，树脂基体的失效特性和弹塑性特性对复合材料的失效都有影响，而且主要特性随层压板和负载配置的不同而变化。
Journal of the Mechanics and Physics of Solids
Dissipation mechanisms of crack-parallel stress effects on fracture process zone in concrete
Lyu Yuhui, Pathirage Madura, Nguyen Hoang T., Bažant Zdeněk P., Cusatis Gianluca
doi:10.1016/j.jmps.2023.105439
混凝土断裂过程区裂缝平行应力效应的消散机制
The effect of crack-parallel stresses on the fracture properties of quasi-brittle materials has recently received significant attention in the fracture mechanics community. A new experiment, the so-called gap test, was developed to reveal this effect. While the finite element crack band model (CBM) with the physically realistic Microplane damage model M7 was quite successful in capturing the damage and fracture during the gap test, some questions remain, particularly the near doubling of the fracture energy at moderate crack parallel compression, which was underestimated by about 30%. Presented here is an in-depth meso-mechanical investigation of energy dissipation mechanisms in the Fracture Process Zone (FPZ) during the gap test of concrete, an archetypal quasi-brittle material. The Lattice Discrete Particle Model (LDPM) is here used to simulate the quasi-brittle material at the mesoscale, which is the length scale of major heterogeneities. The LDPM can capture accurately the frictional sliding, mixed-mode fracture, and FPZ development. The model parameters characterizing the given mix design are first calibrated by standard laboratory tests, namely the hydrostatic, unconfined compression, and four-point bending (4PB) tests. The experimental data used characteristic of the given mix design are calibrated by the Brazilian split-cylinder tests and by gap tests of different sizes with and without crack-parallel stresses. The results show that crack-parallel stresses affect not only the length but also the width of the FPZ. It is found that the energy dissipation portion under crack-parallel compression is significantly larger than it is under tension, which is caused by micro-scale frictional shear slips, as intuitively suggested in previous work. For large compressive stresses, the failure mode changes to inclined compression-shear bands consisting of axial splitting microcracks. Several complications experienced in the numerical modeling of gap tests are also discussed, and the solutions provided.
最近，裂纹平行应力对准脆性材料断裂特性的影响受到了断裂力学界的极大关注。为了揭示这种影响，我们开发了一种新的实验，即所谓的间隙测试。虽然有限元裂纹带模型（CBM）与物理上逼真的微平面损伤模型 M7 在捕捉间隙试验过程中的损伤和断裂方面相当成功，但仍存在一些问题，特别是在中等裂纹平行压缩时，断裂能量几乎增加了一倍，被低估了约 30%。本文对混凝土这种典型的准脆性材料在间隙试验过程中的断裂过程区（FPZ）的能量耗散机制进行了深入的介观力学研究。本文采用晶格离散粒子模型（LDPM）模拟准脆性材料的中观尺度，即主要异质性的长度尺度。LDPM 可准确捕捉摩擦滑动、混合模式断裂和 FPZ 的发展。首先通过标准实验室试验，即静水压试验、无约束压缩试验和四点弯曲（4PB）试验，对特定混合设计的模型参数进行校准。通过巴西分缸试验和有无裂缝平行应力的不同尺寸间隙试验，校准了特定混合设计的实验数据。结果表明，裂缝平行应力不仅影响 FPZ 的长度，也影响其宽度。研究发现，裂纹平行压缩下的能量耗散部分明显大于拉伸下的能量耗散部分，这是由微尺度摩擦剪切滑移引起的，正如之前的研究直观地指出的那样。当压缩应力较大时，破坏模式会转变为由轴向劈裂微裂缝组成的倾斜压缩剪切带。此外，还讨论了间隙试验数值建模过程中遇到的几个复杂问题，并给出了解决方案。
International Journal of Plasticity
Quantitative representation of directional microstructures of single-crystal superalloys in cyclic crystal plasticity based on neural networks
Weng Huanbo, Yuan Huang
doi:10.1016/j.ijplas.2023.103757
基于神经网络的循环晶体塑性中单晶超合金定向微结构的定量表征
Nickel-based single-crystal alloys undergo microstructural degradation induced by thermal exposure. The directional rafting of microstructures significantly affects the mechanical properties and makes the material anisotropic. For structural design, establishing a quantitative description of microstructural effects in a constitutive model becomes essential and is still a tough research topic in multi-scale materials modeling. In the present work, the fabric tensor was correlated with the anisotropic cyclic crystal plasticity of nickel-based single-crystal alloys with the help of neural networks. The microstructural representative volume elements with various single-crystal morphologies were generated by the phase-field method and the deformation behaviors were studied under different crystal orientations and loading configurations. The neural network analysis confirmed that the fabric tensor can present anisotropic single-crystallographic microstructural features and describe mechanical behavior under both monotonic and cyclic multi-axial loading conditions. The history-dependent anisotropic cyclic hardening or softening behavior of the material can be captured by the introduced microstructural state variable. A principal component analysis (PCA) aided gradient-based attribution method was proposed to evaluate the importance of input variables. The characterization of different material components and their contribution to the stress–strain relationships are investigated and validated. The fabric tensor was verified to be an effective microstructural indicator for the continuum plasticity of single-crystal alloys.
镍基单晶合金在热暴露作用下会发生微结构退化。微结构的定向筏状分布会严重影响材料的机械性能，并使其成为各向异性材料。对于结构设计而言，在构成模型中建立微观结构效应的定量描述至关重要，而这仍是多尺度材料建模中一个艰巨的研究课题。在本研究中，利用神经网络将镍基单晶合金的织构张量与各向异性循环晶体塑性相关联。通过相场方法生成了各种单晶形态的微结构代表体积元素，并研究了不同晶体取向和加载配置下的变形行为。神经网络分析证实，织构张量可呈现各向异性的单晶微观结构特征，并能描述单轴和循环多轴加载条件下的力学行为。材料的各向异性循环硬化或软化行为可以通过引入的微结构状态变量来捕捉。为评估输入变量的重要性，提出了一种基于梯度的主成分分析（PCA）辅助归因方法。研究并验证了不同材料成分的特征及其对应力应变关系的贡献。经验证，织物张量是单晶合金连续塑性的有效微结构指标。
