【新文速递】2024年9月30日固体力学SCI期刊最新文章_ACT_Mechanical_Maxwell_Additive_System_振动_疲劳_断裂_复合材料_非线性_增材_裂纹_理论_材料_仿生

【新文速递】2024年11月1日固体力学SCI期刊最新文章

今日更新：International Journal of Solids and Structures 1 篇，International Journal of Plasticity 1 篇，Thin-Walled Structures 2 篇International Journal of Solids and StructuresMicrovoiding and constitutive damage modeling with artificial neural networksNing Li, Huck Beng Chewdoi:10.1016/j.ijsolstr.2024.113125基于人工神经网络的微空洞和本构损伤建模Continuum models of porous media have revolutionized computational fracture mechanics for traditional ductile materials, but the inherent assumptions have limited generalizability to other target materials or loading conditions. Here, we adopt a series of artificial neural networks (ANNs) to predict both the microscopic voiding characteristics (void shape, porosity) and macroscopic stress–strain constitutive response of porous elasto-plastic materials under various deformation states. We train the ANNs on a dataset generated from finite element models of 3D representative volume elements (RVEs), each containing a discrete spherical void, subjected to combinations of loading states. Results show that the data-driven model is capable of interpolative predictions as well as some levels of extrapolative predictions across a wide range of initial porosities (0–20%) and loading states outside of the training dataset, even at high deformation strains which induce extensive material softening and void growth. Through transfer learning, we further demonstrate that the ANNs, originally trained on a specific porous material dataset, can be readily adapted to other porous materials with substantially different properties through a significantly reduced training dataset. We discuss the implications of this machine learning approach vis-à-vis the extensively-developed Gurson model for porous material damage and failure predictions.多孔介质的连续介质模型已经彻底改变了传统韧性材料的计算断裂力学，但其固有的假设在其他目标材料或加载条件下的推广能力有限。本文采用一系列人工神经网络（ann）来预测多孔弹塑性材料在不同变形状态下的微观孔隙特征（孔隙形状、孔隙率）和宏观应力-应变本构响应。我们在三维代表性体积单元（RVEs）的有限元模型生成的数据集上训练人工神经网络，每个RVEs包含一个离散的球形空隙，受到加载状态的组合。结果表明，数据驱动的模型能够在大范围的初始孔隙率（0-20%）和训练数据集之外的加载状态下进行内插预测和一定程度的外推预测，即使在高变形应变下也能引起广泛的材料软化和空隙增长。通过迁移学习，我们进一步证明，最初在特定多孔材料数据集上训练的人工神经网络，可以通过显着简化的训练数据集，很容易地适应具有不同性质的其他多孔材料。我们讨论了这种机器学习方法对-à-vis的影响，广泛开发的Gurson模型用于多孔材料的损伤和失效预测。International Journal of PlasticityUnderstanding Stacking Fault Tetrahedron Formation in FCC Stainless Steel: A Fusion of Transmission Electron Microscopy, Molecular Dynamics, and Machine LearningPan-Dong Lin, Jun-Feng Nie, Wen-Dong Cui, Lei He, Shu-Gang Cui, Guo-Chao Gu, Gui-Yong Xiao, Yu-Peng Ludoi:10.1016/j.ijplas.2024.104157 理解FCC不锈钢层错四面体的形成：透射电子显微镜、分子动力学和机器学习的融合The stacking fault tetrahedron (SFT) formation displays a pronounced size effect, progressing from vacancy equilateral triangular plate to perfect SFT, and eventually to truncated SFT, as demonstrated in numerous irradiated face-centered cubic metals. However, the presence of distinct SFT structures in F321 stainless steel has not been reported. This study explored the SFT formation mechanism in irradiated F321 stainless steel using transmission electron microscopy (TEM), molecular dynamics (MD) simulations, and machine learning. SFTs, Frank loops, and Lomer-Cottrell locks were found to be widely generated in the irradiated F321 steel. The critical size for truncated and perfect SFTs was determined using MD simulations; the results were consistent with the theoretical predictions. Additionally, the twin boundaries observed through TEM, which were attributed to the elevated tensile stress near the boundaries, facilitated the formation of perfect SFTs. Moreover, interstitial Frank loops also facilitated the formation of perfect SFTs. This study also explored the influence of variations in Ni and Cr concentrations on the critical size n1 for the transition from vacancy plates to perfect SFTs and n2 for the transition from perfect SFTs to truncated SFTs, using a combination of MD and machine learning methods. As the Ni concentration increased and the Cr concentration decreased, n1 and n2 increased; conversely, the critical sizes decreased when the Ni concentration decreased and the Cr concentration increased. These insights reveal the systematic mechanism of SFT formation under varied conditions, offering new perspectives for understanding the nano-defects in F321 stainless steel.堆垛层错四面体（SFT）的形成具有明显的尺寸效应，从空位等边三角形板到完美的SFT，再到截断的SFT，这一现象在众多辐照的面心立方金属中都有体现。然而，在F321不锈钢中尚未发现明显的SFT结构。本研究利用透射电子显微镜（TEM）、分子动力学（MD）模拟和机器学习探究了辐照F321不锈钢的SFT形成机制。研究发现，SFTs、弗兰克环和洛默-科特尔锁在辐照F321钢中广泛存在。通过MD模拟确定了截断和完美SFT的临界尺寸，结果与理论预测一致。此外，通过TEM观察到的孪生边界被归因于边界附近的高拉伸应力，促进了完美SFT的形成。此外，间隙弗兰克环也促进了完美SFT的形成。本研究还采用结合分子动力学和机器学习的方法，探索了Ni和Cr浓度变化对从位错滑移带过渡到完美滑移面以及从完美滑移面过渡到截断滑移面的临界尺寸n1和n2的影响。随着Ni浓度的增加和Cr浓度的降低，n1和n2增大；相反，当Ni浓度降低和Cr浓度增加时，临界尺寸减小。这些发现揭示了在不同条件下滑移面形成过程中的系统性机制，为理解F321不锈钢中的纳米缺陷提供了新的视角。Thin-Walled StructuresNumerical study on the effects of alloying variations on the crushing behaviour of an aluminium profileMarcos Fernandez, Miguel Costas, Odd Sture Hopperstad, David Morindoi:10.1016/j.tws.2024.112618合金含量变化对铝型材破碎性能影响的数值研究The effects of variations in the chemical composition of an aluminium alloy AA6005 on the axial crushing and bending behaviour of a double chamber extruded profile are investigated by shell-based finite element analyses. A novel sequential modelling method, including nanostructure modelling, virtual tensile testing and localisation analyses, is used to determine the yield strength, work-hardening, and ductility of several variants of the AA6005 alloy. The data obtained from the models are used to calibrate the parameters of an isotropic elastic–plastic constitutive model and an uncoupled damage criterion. Explicit finite element analyses of axial crushing and three-point bending of the double chamber extruded profile are conducted for all variants of the AA6005 alloy in temper T6. By comparing the results of the finite element analyses with existing experimental data, the results reveal how variations in the chemical composition significantly influence the structural integrity of the extruded aluminium profile in axial crushing and bending.采用基于壳体的有限元分析方法，研究了AA6005铝合金化学成分变化对双腔挤压型材轴向破碎和弯曲性能的影响。采用一种新的序列建模方法，包括纳米结构建模、虚拟拉伸测试和局部化分析，来确定几种变体AA6005合金的屈服强度、加工硬化和延展性。利用这些模型得到的数据对各向同性弹塑性本构模型和非耦合损伤准则的参数进行了标定。对T6回火下AA6005合金各变型双腔挤压型材的轴向破碎和三点弯曲进行了显式有限元分析。通过将有限元分析结果与现有的实验数据进行比较，结果揭示了化学成分的变化如何显著影响挤压铝型材在轴向破碎和弯曲过程中的结构完整性。Isogeometric Flutter Analysis of a Heated Laminated Plate with and without CutoutWenliang Yu, Rongshen Guo, Yuhao Zhao, Mingfei Chendoi:10.1016/j.tws.2024.112652带和不带切口的加热层合板的等几何颤振分析Understanding the flutter characteristics of heated laminated plates, both with and without cutout, is crucial. This study presents the first exploration of flutter analysis in a thermal environment for a laminated plate featuring a cutout. To facilitate this study, the motion equations of the heated laminated plate with a cutout are derived using the first-order shear deformation theory (FSDT), incorporating a nonlinear term. Employing the isogeometric method combined with multi-path coupling technology, we establish accurate geometric and solution domains for the laminated plate. The effects of the thermal stresses and the aerodynamics calculated by the linear piston theory are considered. The accuracy and effectiveness of the proposed model are validated through several comparisons with ANSYS results and existing solutions. Additionally, the study examines the impact of key parameters on flutter characteristics, including thermal conditions, number of layers, lay-up angles, inflow angles, and cutout dimensions. The insights gained from this research will serve as a valuable benchmark for future analyses and design concerning flutter characteristics.了解加热层合板的颤振特性是至关重要的，无论是否有切口。这项研究提出了在热环境下的颤振分析的第一个探索夹层板具有一个切口。为了便于研究，利用一阶剪切变形理论（FSDT）推导了带切口的加热层合板的运动方程，其中包含一个非线性项。采用等几何方法结合多径耦合技术，建立了层合板的精确几何域和解域。考虑了用线性活塞理论计算的热应力和空气动力学的影响。通过与ANSYS计算结果和已有解的对比，验证了所提模型的准确性和有效性。此外，研究还考察了关键参数对颤振特性的影响，包括热条件、层数、铺层角、流入角和切口尺寸。从这项研究中获得的见解将为未来有关颤振特性的分析和设计提供有价值的基准。来源：复合材料力学仿真Composites FEM

【新文速递】2024年9月30日固体力学SCI期刊最新文章

Journal of the Mechanics and Physics of Solids

Mechanics of Materials

International Journal of Plasticity

Thin-Walled Structures

【新文速递】2024年11月1日固体力学SCI期刊最新文章