【新文速递】2024年4月21日固体力学SCI期刊最新文章

 

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

International Journal of Solids and Structures

Modeling of strength and ductility of metal alloy/graphene composites containing precipitates

S.V. Bobylev, A.G. Sheinerman, X.T. Li, Z.J. Zhang

doi:10.1016/j.ijsolstr.2024.112843

含有沉淀的金属合金/石墨烯复合材料的强度和延展性建模

A model is suggested that describes plastic deformation of metal alloys reinforced with graphene. Within the model, the flow stress, yield and ultimate strength and the critical uniform elongation are calculated as functions of the structural parameters of the composites. It is demonstrated that a high strength of the composites requires that a significant part of grain boundary area should be occupied by graphene platelets, whereas grain size and platelet length exert small effects on the strength of the composites. It is shown that the addition of graphene can lead to a significant increase in strength at expense of a moderate decrease in ductility. Thus, the optimum graphene content should be high enough to provide a high proportion of grain boundary area occupied by graphene but still sufficiently small to avoid graphene agglomeration.

提出了一个描述石墨烯增强金属合金塑性变形的模型。在模型中，计算了复合材料的流变应力、屈服强度、极限强度和临界均匀伸长率作为复合材料结构参数的函数。结果表明，复合材料的高强度要求石墨烯薄片占据晶界面积的很大一部分，而晶粒尺寸和薄片长度对复合材料强度的影响较小。结果表明，石墨烯的加入可以导致强度的显著增加，但代价是延展性的适度降低。因此，最佳的石墨烯含量应该足够高，以提供高比例的晶界面积被石墨烯占据，但仍然足够小，以避免石墨烯团聚。

Journal of the Mechanics and Physics of Solids

Estimating the macro strength of rock based on the determined mechanical properties of grains and grain-to-grain interfaces

Zhiyang Wang, Ruifeng Zhao, Mengyi Li, Xiangyu Xu, Zhijun Wu, Yingwei Li

doi:10.1016/j.jmps.2024.105655

基于确定的颗粒力学特性和颗粒-颗粒界面估算岩石宏观强度

Obtaining complete rock cores is exceptionally challenging in certain extreme environments, such as deep earth and deep space; consequently, it is difficult to obtain the macro strengths of rock, which are the key indexes for engineering design, via standard rock mechanical tests. This research indicates that by determining and leveraging the mechanical properties of grains and grain-to-grain interfaces, the rock macro strength can be effectively estimated. Nanoindentation tests were first conducted to determine the elastic modulus of the mineral grains and their interfaces. Subsequently, symmetrical and anti-symmetrical four-point bending tests were executed to establish the statistical law governing interfacial tensile and shear fracture toughnesses. Furthermore, by employing the Dugdale–Barenblatt model and considering the oblique angular distribution of interfacial cracks, the corresponding tensile strength, shear strength, and friction parameter were derived. These meso-mechanical parameters were then inputted into the 3D Finite-Discrete Element Method to estimate rock macro strength. And the numerical results were then compared with the results of standard uniaxial compression, direct tension, Brazilian splitting, and direct shear tests. The consistency observed between the predictions and experimental results attests to the validity of the proposed method.

在某些极端环境中，如深地和深空，获得完整的岩心是非常具有挑战性的;因此，通过标准的岩石力学试验很难获得岩石的宏观强度，而这是工程设计的关键指标。研究表明，通过确定和利用颗粒和粒间界面的力学特性，可以有效地估计岩石的宏观强度。首先进行了纳米压痕试验，以确定矿物颗粒及其界面的弹性模量。随后，进行对称和非对称四点弯曲试验，建立界面拉伸和剪切断裂韧性的统计规律。采用Dugdale-Barenblatt模型，考虑界面裂纹的斜角分布，推导出相应的抗拉强度、抗剪强度和摩擦参数。然后将这些细观力学参数输入到三维有限单元法中，估算岩石宏观强度。并将数值计算结果与标准单轴压缩、直拉、巴西劈裂和直剪试验结果进行了比较。预测结果与实验结果的一致性证明了所提方法的有效性。

International Journal of Plasticity

Temperature-dependent damage of magnesium alloy with ratchetting–fatigue interaction effects: Experiments and mesomechanical theory

Ziyi Wang, Yu Lei, Binghui Hu, Chao Yu, Shengchuan Wu, Xiqiao Feng, Guozheng Kang

doi:10.1016/j.ijplas.2024.103972

具有棘轮-疲劳交互作用的镁合金温度相关损伤:实验与细观力学理论

Fatigue failure is a significant concern for magnesium (Mg) alloy components. However, fatigue damage mechanisms of Mg alloys, particularly in the case of ratchetting–fatigue interaction at elevated temperatures, are still not well understood. In this paper, we combine experiments and theoretical analysis to investigate the high-temperature damage mechanisms of the extruded AZ31 Mg alloy, specifically focusing on the effects of ratchetting–fatigue interaction. We reveal a distinct demonstration of damage, namely the formation of microvoids in the alloy due to significant ratchetting deformation, defined as ratchetting damage. Notably, this ratchetting damage is more prevalent at higher temperatures. Considering the mesomechanics-based energy mechanisms associated with grain boundaries (or twin boundaries), a mesomechanical damage model is established to capture the ratchetting damage under elevated temperatures and large ratchetting deformations. This model can reasonably simulate the intricate process of damage evolution and predict the critical condition of microvoid or microcrack formation. This work has the potential to serve as a theoretical tool for the safety design of structures made from Mg alloys under complex mechanical and thermal conditions.

疲劳失效是镁合金部件的一个重要问题。然而，镁合金的疲劳损伤机制，特别是在高温下棘轮-疲劳相互作用的情况下，仍然没有很好的理解。本文采用实验与理论相结合的方法，研究了挤压AZ31镁合金的高温损伤机理，重点研究了棘轮-疲劳相互作用的影响。我们揭示了一种独特的损伤演示，即由于显著的棘轮变形而在合金中形成微空洞，定义为棘轮损伤。值得注意的是，这种棘轮损伤在高温下更为普遍。考虑与晶界(或孪晶界)相关的基于细观力学的能量机制，建立了一种细观力学损伤模型，以捕获高温和大棘轮变形下的棘轮损伤。该模型能够合理地模拟复杂的损伤演化过程，预测微空洞或微裂纹形成的临界条件。这项工作有可能作为镁合金结构在复杂机械和热条件下安全设计的理论工具。

Thin-Walled Structures

Artificial Neural Networks for Inverse Design of a Semi-Auxetic Metamaterial

Mohammadreza Mohammadnejad, Amin Montazeri, Ehsan Bahmanpour, Maryam Mahnama

doi:10.1016/j.tws.2024.111927

半辅助超材料反设计的人工神经网络

This study introduces an artificial neural network approach for the inverse design of a novel semi-auxetic mechanical metamaterial to achieve a specified stress-strain curve and/or Poisson's ratio-strain curve. To accomplish this, after presenting the metamaterial and assessing its characteristics, 1500 structures of the same metamaterial with various parameters are generated using a parametric model. The metamaterials are then gone through a compression test simulation using Finite Element (FE) analysis; accordingly, each metamaterial's stress-strain and Poisson's ratio curves are derived. The results of FE simulations are validated using mesh convergence check and experimental compression tests on a 3D printed specimen of the proposed metamaterial. In the next step, 80% of the data are randomly selected to be used as training data for the artificial neural networks (ANN), while the remaining 20% is employed to evaluate the performance of the ANNs using different metrics. The capability of the ANNs to predict the design parameters of the proposed metamaterial is assessed by providing different kinds of inputs, including the stress-strain curve, Poisson's ratio curve, and both. The observations reveal that the ANNs achieve more accurate results when both the stress-strain and Poisson's ratio-strain curves are provided as the inputs. The presented ANN in this study serves as a robust tool for precisely designing the parameters of the proposed metamaterial, allowing for the attainment of the desired stress-strain and/or Poisson's ratio-strain behavior. It is shown that the proposed metamaterial owns potential applications in crawling soft robotics, automotive, and construction industries.

本文介绍了一种人工神经网络方法，用于一种新型半塑性机械超材料的反设计，以获得指定的应力-应变曲线和/或泊松比-应变曲线。为了实现这一目标，在介绍了超材料并评估了其特性之后，使用参数化模型生成了1500个具有不同参数的相同超材料结构。然后利用有限元(FE)分析对超材料进行压缩试验模拟;据此，推导了各超材料的应力应变曲线和泊松比曲线。通过网格收敛性检查和实验压缩测试，对所提出的超材料的3D打印样品进行了有限元模拟结果的验证。在接下来的步骤中，随机选择80%的数据作为人工神经网络(ANN)的训练数据，而剩下的20%用于使用不同的指标来评估ANN的性能。通过提供不同类型的输入，包括应力-应变曲线、泊松比曲线和两者的输入，评估了人工神经网络预测所提出的超材料设计参数的能力。结果表明，当同时提供应力-应变和泊松比-应变曲线作为输入时，人工神经网络可以获得更精确的结果。本研究中提出的人工神经网络作为精确设计所提出的超材料参数的强大工具，允许实现所需的应力-应变和/或泊松比-应变行为。结果表明，该超材料在爬行软机器人、汽车和建筑行业具有潜在的应用前景。