Mechanics of Materials最新文献_第9页

Thermal and thermo-mechanical post-buckling analysis of GNP-reinforced composite laminated plates GNP 增强复合层压板的热和热机械屈曲后分析

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-10-04 DOI: 10.1016/j.mechmat.2024.105171

Vuong Nguyen Van Do , Thang N. Dao , Chin-Hyung Lee

This research utilizes isogeometric analysis (IGA) method to analyze buckling and post-buckling responses of composite laminated plates embedded with graphene nanoplatelets (GNPs) subjected to three-dimensional (3D) conduction of heat or combined 3D heat conduction and mechanical edge compression. A formulation to determine temperature profile produced by 3D conduction of heat in the GNP-reinforced laminate is established, and a new function with smooth transition form of GNP volume fraction across the thickness is presented for dictating the volume fraction of layer. Shear deformable quasi-3D theory with the von Kármán type nonlinearity which takes initial geometric deformation and thermal effect into consideration is employed to construct the nonlinear equilibrium states. Four types of GNP arrangements encompassing uniform, O, X and V shapes are considered. The IGA approach presented, through the benchmark test, is evidenced to estimate the thermal buckling temperature accurately and to successfully trace the thermal post-buckling path. Additional parametric study is carried out to scrutinize the thermal and the thermo-mechanical post-buckling features of the GNP-reinforced composite laminated plates, and the new findings are sure to be served as the benchmark solutions.

本研究采用等几何分析（IGA）方法分析了嵌入石墨烯纳米片（GNP）的复合层压板在三维（3D）热传导或三维热传导与机械边缘压缩联合作用下的屈曲和屈曲后响应。建立了一种公式来确定三维热传导在 GNP 增强层压板中产生的温度曲线，并提出了一种具有平滑过渡形式的 GNP 体积分数跨厚度的新函数，用于确定层的体积分数。采用考虑了初始几何变形和热效应的 von Kármán 型非线性剪切变形准三维理论来构建非线性平衡态。考虑了四种类型的 GNP 排列，包括均匀、O、X 和 V 形。通过基准测试，证明所提出的 IGA 方法能够准确估计热屈曲温度，并成功追踪热屈曲后的路径。此外，还进行了其他参数研究，以仔细观察 GNP 增强复合层压板的热屈曲和热机械屈曲后特征，这些新发现必将成为基准解决方案。

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引用次数: 0

The role of secondary voids in the mechanism of ductile fracture at a crack tip 二次空隙在裂纹尖端韧性断裂机制中的作用

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-10-01 DOI: 10.1016/j.mechmat.2024.105170

A.K. Dwivedi , I.A. Khan , J. Chattopadhyay

The mechanics and mechanisms of ductile fracture, ahead of a blunting crack tip, have been studied extensively. Several computational studies analyzing the effect of initial void volume fraction, void shape, void spatial distribution and the mode of loading (

K_{I}, K_{I I}

etc.) on crack-void interaction and its consequence on the mechanism of fracture have been reported. The influence of small size secondary voids on the failure of ligament between the large primary voids and, hence, on fracture toughness has been analyzed using the Gurson-type homogenized models of ductile fracture. In the present work, the two populations of voids ahead of a crack tip are modeled discretely. A plane strain, central line cracked boundary layer model under small-scale yielding is considered. The role of initial shape and spatial distribution of secondary voids, matrix strain hardening and mode of imposed loading in the mechanism of ductile crack growth initiation and advance is analyzed in detail. For completeness sake, numerical calculations are also performed using a homogenized representation of the secondary voids. The results so obtained are then compared with the predictions based on discrete modeling of the secondary voids. Our numerical studies revealed that plastic flow localization resulting from a small initial volume fraction of favorably distributed secondary voids may alter the path of crack growth initiation and advance, thus, influencing the ductile fracture toughness.

人们对钝化裂纹尖端前的韧性断裂的力学和机理进行了广泛的研究。一些计算研究分析了初始空隙体积分数、空隙形状、空隙空间分布和加载模式（KI、KII 等）对裂纹-空隙相互作用的影响及其对断裂机制的影响。利用古尔松类型的韧性断裂均质化模型，分析了小尺寸次生空隙对大尺寸原生空隙之间韧带断裂的影响，以及对断裂韧性的影响。在本研究中，裂纹尖端前的两个空隙群被离散地建模。考虑了小尺度屈服下的平面应变、中心线裂纹边界层模型。详细分析了次生空隙的初始形状和空间分布、基体应变硬化和外加载荷模式在韧性裂纹生长和扩展机制中的作用。为完整起见，还使用二次空隙的均质化表示进行了数值计算。然后将计算结果与基于二次空隙离散建模的预测结果进行比较。我们的数值研究表明，由于有利分布的次生空隙的初始体积分数较小而导致的塑性流动局部化可能会改变裂纹生长的起始和推进路径，从而影响韧性断裂韧性。

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引用次数: 0

Failure analysis of unidirectional fiber reinforced plastics based on computational micromechanics and PUCK failure theory 基于计算微机械学和 PUCK 失效理论的单向纤维增强塑料失效分析

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-27 DOI: 10.1016/j.mechmat.2024.105169

Xiaofei Pang , Yonglyu He , Xun Chen , Shufeng Zhang

Achievement of accurate and reliable failure criterion is fundamentally important for designing composite structures. This study comprehensively evaluated the failure of unidirectional fiber-reinforced plastics (FRP) from the perspectives of failure theory and computational micromechanics. Further, PUCK failure criterion was analyzed in detail to identify the specific effects of the interfacial reinforcement coefficient on the failure mechanism. The representative volume element model of FRP with randomly distributed fibers was established. The comparative analysis of the results between current failure theory and experiment, indicates that the load bearing capacity of FRP under bi-axial compressive stress and shear stress is understated by the PUCK failure criterion. Microscopic finite element analysis was adopted to investigate the failure envelope of FRP, considering interface reinforcement coefficient. The results reveal that the strength of FRP under the combination of moderate transverse compressive stress and in-plane shear stress is significantly affected by the interface reinforcement coefficient. The accuracy of PUCK failure criterion heavily depends on the value of the interface reinforcement coefficient and if the criterion does not consider the coefficient, it can cause notable error on strength prediction. Consequently, determination of interface reinforcement coefficient would be helpful to achieve more accurate failure criterion for FRP.

准确可靠的失效准则对于设计复合材料结构至关重要。本研究从失效理论和计算微观力学的角度全面评估了单向纤维增强塑料（FRP）的失效。此外，还详细分析了 PUCK 失效准则，以确定界面增强系数对失效机理的具体影响。建立了具有代表性的随机分布纤维 FRP 体积元素模型。对现有破坏理论和实验结果的对比分析表明，PUCK 破坏准则低估了玻璃钢在双轴压应力和剪应力下的承载能力。考虑到界面加固系数，采用微观有限元分析来研究玻璃钢的破坏包络。结果表明，在中等横向压应力和平面剪应力组合下，玻璃钢的强度受界面加固系数的影响很大。PUCK 失效判据的准确性在很大程度上取决于界面加固系数的值，如果判据不考虑该系数，则会对强度预测造成明显误差。因此，确定界面加固系数将有助于获得更准确的玻璃钢破坏准则。

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引用次数: 0

Quantification of elastic incompatibilities at triple junctions via physics-based surrogate models 通过基于物理学的代用模型量化三重连接处的弹性不相容性

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-27 DOI: 10.1016/j.mechmat.2024.105163

Aaditya Rau , Christopher A. Schuh , Raúl Radovitzky

Stresses resulting from elastic incompatibilities at grain boundaries have long been known to drive the premature failure and loss of desirable macroscopic properties in polycrystalline materials. In this work, we employ machine learning to create a surrogate model that furnishes a functional relationship between grain boundary configurational data and metrics of incompatibility. A planar triple junction geometry composed of cubic grains rotated about their

[001]

axis was adopted as the grain boundary model. High-fidelity finite element simulations of this triple junction under hydrostatic extension were used to generate a synthetic dataset for training the surrogate model. A set of

J

integrals computed around microcracks placed along the triple junction boundaries were used to quantify the elastic incompatibilities between the grains. Using the grain rotation angles and

J

integrals as the feature and label data respectively, a multi-layer perceptron network was trained using the synthetic data produced with the physics-based model. We demonstrate that the network trained using data from the physics-based model establishes an accurate functional dependence between the triple junction angles and the

J

integrals that enables direct and fast evaluation. We use the surrogate model to efficiently sweep the configuration space and create contour maps of the largest stress intensification at the triple junction as a function of the grain rotation angles. Furthermore, we show that the analytical properties of the surrogate model can be utilized to identify the most and least compatible triple junction configurations via optimization.

众所周知，晶界弹性不相容所产生的应力会导致多晶材料过早失效并丧失理想的宏观特性。在这项工作中，我们利用机器学习创建了一个替代模型，该模型提供了晶界构型数据与不相容性指标之间的函数关系。晶界模型采用了由围绕 [001] 轴旋转的立方晶粒组成的平面三结点几何体。在流体静力学延伸条件下，对该三交界处进行高保真有限元模拟，生成用于训练代用模型的合成数据集。沿三重交界处的微裂缝周围计算的一组 J 积分用于量化晶粒之间的弹性不相容性。将晶粒旋转角度和 J 积分分别作为特征数据和标签数据，使用基于物理模型生成的合成数据训练多层感知器网络。我们证明，使用基于物理模型的数据训练的网络在三重交界角和 J 积分之间建立了精确的函数关系，从而可以进行直接和快速的评估。我们利用代用模型有效地扫描了构型空间，并绘制出了三重交界处最大应力增强与晶粒旋转角函数关系的等高线图。此外，我们还展示了代用模型的分析特性可用于通过优化确定最兼容和最不兼容的三重连接配置。

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引用次数: 0

A variational method for the simulation of hydrogen diffusion in metals 模拟金属中氢扩散的变分法

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-25 DOI: 10.1016/j.mechmat.2024.105166

E.M. Andrés , I. Romero

We present a new method for the approximate solution of the strongly coupled, nonlinear stress-diffusion problem that appears when modeling hydrogen transport in metals. The most salient feature of the proposed approximation is that it is fully variational, meaning that all the discrete equations are obtained from the optimality conditions of an incremental potential, even for inelastic mechanical behavior. Like other variational methods, the proposed algorithm has remarkable properties, including the symmetry of the tangent operator, making its solution extremely efficient compared to other similar methods available in the literature.

我们提出了一种近似解决强耦合非线性应力扩散问题的新方法，该问题在模拟金属中的氢传输时出现。所提近似方法的最显著特点是它是完全变分的，这意味着所有离散方程都可以从增量势能的最优化条件中获得，甚至对于非弹性机械行为也是如此。与其他变分法一样，所提出的算法具有显著的特性，包括正切算子的对称性，因此与文献中的其他类似方法相比，其求解效率极高。

引用次数: 0

Atomistic investigation on the anisotropic elastic and plastic responses of nanotwinned metals 纳米绕线金属各向异性弹性和塑性响应的原子学研究

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-24 DOI: 10.1016/j.mechmat.2024.105164

Ligang Sun , Lianyu Jiao , Zhijia Qin , Linli Zhu , Bin Gan , Dongfeng Li

Introducing nanotwins into materials is one of the important strengthening methods to achieve the synergistic improvement of strength and ductility. The anisotropic mechanical behaviors of nanotwinned materials have been widely studied by experimental and computational methods. The dominant deformation mechanisms about dislocation slippages can be effectively switched among three modes, and controlled by twin spacing and the angle between twin boundaries (TBs) orientation and loading direction. Particularly, most of previous researches mainly focused on the deformation mechanisms during the plastic flow stage and researchers paid little attention on the anisotropic characteristics of TBs at the elastic stage which are also essential to manufacture the high-performance materials. Therefore, this study is aiming to systematically investigate the anisotropic effect of TBs both at the elastic and plastic stages within the single crystalline or polycrystalline systems by molecular dynamics (MD) simulations. It is revealed that, when the loading direction is parallel to twin planes, the introduction of TBs in single crystalline models will significantly affect the characteristics of atomic bond rotation and elongation dominated elastic deformation, which can alter the Poisson’s ratio of materials, generate elastic-softening behavior and inhomogeneous elastic deformation. At the plastic flow stage, the deformation mechanism transforms from trans-twin dislocation slippage into the coexistence of Hard Mode I and threading dislocation slippage (Hard Mode II) when the loading direction changes from parallel to perpendicular direction with respect to TBs. Moreover, the dislocation segments at the conjunction of trans-twin dislocation play a momentous role in enhancing material strength. The results for polycrystalline models are consistent with that of single crystalline ones. These findings are expected to be beneficial for the development of high-performance nanostructured materials for structural and functional applications by strain engineering and defect regulation.

在材料中引入纳米孪晶是实现强度和延展性协同提高的重要强化方法之一。人们通过实验和计算方法对纳米绕线材料的各向异性力学行为进行了广泛研究。位错滑移的主要变形机制可在三种模式中有效切换，并受孪晶间距以及孪晶边界（TBs）方向与加载方向之间夹角的控制。特别是，以往的研究大多集中于塑性流动阶段的变形机制，而对弹性阶段孪晶边界的各向异性特征关注较少，而这也是制造高性能材料的关键。因此，本研究旨在通过分子动力学（MD）模拟系统研究单晶或多晶体系中 TB 在弹性和塑性阶段的各向异性效应。研究发现，当加载方向平行于孪晶平面时，在单晶模型中引入 TBs 会显著影响原子键旋转和伸长主导弹性变形的特性，从而改变材料的泊松比，产生弹性软化行为和不均匀弹性变形。在塑性流动阶段，当加载方向从平行于 TBs 方向变为垂直于 TBs 方向时，变形机制从跨双位错滑移转变为硬模式 I 和穿线位错滑移（硬模式 II）并存。此外，跨双位错交汇处的位错段在提高材料强度方面发挥着重要作用。多晶模型的结果与单晶模型的结果一致。这些发现有望通过应变工程和缺陷调控，为高性能纳米结构材料的结构和功能应用开发带来益处。

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引用次数: 0

Damage ratio strength criterion for asphalt mixtures and its application in rutting prediction 沥青混合料的破坏比强度标准及其在车辙预测中的应用

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-21 DOI: 10.1016/j.mechmat.2024.105165

Xia Wu , Faxing Ding , Jiaqi Chen , Leixin Nie , Zhiwu Yu

The current damage ratio strength theory is employed to predict the multiaxial strength of asphalt mixtures at various temperatures. Based on the dimensionless triaxial strength of asphalt mixtures, the values of six empirical parameters are recommended to establish the corresponding dimensionless strength criterion. The multiaxial strength data of diverse asphalt mixtures, including OGFC-13, AC-13, AC-20, AC-25, SMA-13, and SUP12.5 at different temperatures, are employed to validate the proposed criterion, which is then compared with other criteria. The results indicate that the suggested dimensionless strength criterion with uniform parameter values can accurately predict the true triaxial, confining triaxial, and biaxial strength values of asphalt mixtures across various temperatures. Furthermore, the proposed criterion is employed to elucidate the mechanical mechanism of rutting, offering a valuable insight for predicting flow rutting of pavement under loads.

采用当前的破坏比强度理论来预测沥青混合料在不同温度下的多轴强度。根据沥青混合料的无量纲三轴强度，推荐了六个经验参数值，以建立相应的无量纲强度准则。采用不同沥青混合料（包括 OGFC-13、AC-13、AC-20、AC-25、SMA-13 和 SUP12.5）在不同温度下的多轴强度数据来验证所建议的准则，然后将其与其他准则进行比较。结果表明，所建议的参数值统一的无量纲强度准则可以准确预测沥青混合料在不同温度下的真实三轴强度、约束三轴强度和双轴强度值。此外，所提出的标准还用于阐明车辙的力学机理，为预测路面在荷载作用下的流动车辙提供了有价值的见解。

引用次数: 0

Integrating MIL and Mori–Tanaka methods for microstructural analysis and mechanical behavior prediction in heterogeneous materials 集成 MIL 和 Mori-Tanaka 方法，用于异质材料的微结构分析和力学行为预测

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-20 DOI: 10.1016/j.mechmat.2024.105167

Lívia M. Nogueira , Lavinia A. Borges , Daniel A. Castello

This paper explores heterogeneous materials, investigating their intricate nature characterized by structural and property variations across length scales. These variations, stemming from a variety of phases and structural constituents, lead to orientation-dependent properties, and challenge material isotropy assumptions. The present work focuses on unraveling mechanical behavior for material selection and predictive modeling. More specifically, this paper proposes a strategy for micromechanical analyses integrating the Mori–Tanaka (M–T) homogenization model and the Mean Intercept Length (MIL) morphology-based method. The initial analysis examines the impact of both pore shape and distribution on microstructural characterization, replicating isotropic and anisotropic conditions for certain scenarios. MIL proves effective for microstructure orientation analysis, regardless of porosity. Subsequently, the M–T method is applied to estimate Young’s modulus, and its relationship with pore shape, orientation, and volume fraction is investigated. This investigation into Young’s modulus provides valuable insights into the proposed framework’s capability to uncover the intricate relationship between microstructural features and macroscopic properties within heterogeneous materials. The overall framework presented in this paper holds promise for practical applications in predicting properties in real materials using micro-CT images, contributing to a deeper understanding of these complex materials and their behavior.

本文探讨了异质材料，研究了它们以跨长度尺度的结构和性能变化为特征的复杂性质。这些变化源于各种相和结构成分，导致了取向相关的特性，并对材料各向同性假设提出了挑战。本研究的重点是揭示材料选择和预测建模的机械行为。更具体地说，本文提出了一种整合森田中（Mori-Tanaka，M-T）均质化模型和基于形态的平均截距长度（Mean Intercept Length，MIL）方法的微观力学分析策略。初步分析研究了孔隙形状和分布对微观结构表征的影响，在某些情况下复制了各向同性和各向异性条件。事实证明，无论孔隙率如何，MIL 都能有效地进行微结构定向分析。随后，应用 M-T 方法估算杨氏模量，并研究其与孔隙形状、取向和体积分数的关系。对杨氏模量的研究提供了宝贵的见解，说明所提出的框架有能力揭示异质材料中微观结构特征与宏观属性之间错综复杂的关系。本文提出的整体框架有望实际应用于利用微型计算机断层扫描图像预测真实材料的属性，从而加深对这些复杂材料及其行为的理解。

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引用次数: 0

An atomistic and experimental approach to study the effect of water and nanofillers on the compressive strength of PEGDA hydrogels for cartilage replacement 用原子论和实验方法研究水和纳米填料对用于软骨替代的 PEGDA 水凝胶抗压强度的影响

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-20 DOI: 10.1016/j.mechmat.2024.105161

Raju Kumar , Abhishek Tewari , Avinash Parashar

Polyethylene glycol diacrylate (PEGDA) hydrogel is emerging as a potential candidate for biomedical applications, particularly cartilage replacement. However, due to weak mechanical strength, their applications are still in the infancy for cartilage replacement. In this article, authors have reported the compressive strength of hexagonal boron nitride (h-BN) reinforced PEGDA hydrogels in conjunction with different water content. A combined experimental and atomistic approach (Molecular Dynamics) was employed to explore the compressive strength of nanocomposite hydrogels. It was reported from the experimental analysis that h-BN acts as a superior reinforcement for the compressive strength at lower water content. The Molecular Dynamics (MD) based simulations also predict a similar trend with h-BN and water content. The MD-based study gives insight into scrutinizing the behavior of polymer chains and their entanglement and sheds light on microscale phenomena that are usually inaccessible through experiments alone. It can be concluded from the experiments in conjunction with MD simulations that at higher water content, the contact points between h-BN nanosheets and polymer chains decrease, mitigating the overall compressive strength of PEGDA hydrogels. In summary, this study enables us to obtain meaningful mechanical properties that mimic the strength of human articular cartilage.

聚乙二醇二丙烯酸酯（PEGDA）水凝胶正在成为生物医学应用，特别是软骨替代的潜在候选材料。然而，由于机械强度较弱，其在软骨替代方面的应用仍处于起步阶段。在这篇文章中，作者报告了六方氮化硼（h-BN）增强的 PEGDA 水凝胶在不同含水量下的抗压强度。作者采用了实验和原子论（分子动力学）相结合的方法来探讨纳米复合水凝胶的抗压强度。实验分析表明，h-BN 在较低含水量下的抗压强度方面起到了很好的增强作用。基于分子动力学（MD）的模拟也预测了 h-BN 和水含量的类似趋势。基于 MD 的研究为仔细研究聚合物链的行为及其缠结提供了洞察力，并揭示了通常无法仅通过实验获得的微观现象。实验结合 MD 模拟得出的结论是，含水量越高，h-BN 纳米片和聚合物链之间的接触点越少，从而降低了 PEGDA 水凝胶的整体抗压强度。总之，这项研究使我们能够获得模拟人体关节软骨强度的有意义的机械性能。

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引用次数: 0

Accelerated intelligent prediction and analysis of mechanical properties of magnesium alloys based on scaled super learner machine-learning algorithms 基于超级学习者机器学习算法的镁合金机械性能加速智能预测和分析

IF 3.4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials

Pub Date : 2024-09-19 DOI: 10.1016/j.mechmat.2024.105168

Atwakyire Moses , Ying Gui , Buzhuo Chen , Marembo Micheal , Ding Chen

The use of machine learning algorithms in magnesium (Mg) alloys has evolved a scientific innovation for lightweight. The dataset was compiled by collecting data from the experiment and utilizing machine learning (ML) models to predict the mechanical properties of 348 Mg alloys. The proportion between the predicted and experimental results produced by different ML models demands more advanced regression methods to obtain better results. Utilizing Mg alloy descriptors as input variables and mechanical properties as output variables, four different ML models were employed namely (i.e.) Random Forest (RF), Extra Tree (ET), Gradient Boost (GB), and Extreme Gradient Boost (XGBoost) to resolve this difficult problem. Each single algorithm aimed to predict the mechanical properties of Mg alloy i.e. Ultimate Tensile Strength (UTS), Yield Strength (YS), and Elongation (EL). Subsequently, the data-driven intelligent prediction modeling technique called scaled Super Learner (SL) was employed to integrate the single models into the stacked model approach to enhance prediction accuracy. The results obtained using scaled Super Learner demonstrated enhanced prediction accuracy for UTS, YS, and EL. The findings further demonstrate enhanced prediction ability by outperforming other approaches as demonstrated by lower Root Mean Squared Error (RMSE) and higher R-Squared (R²) compared to previous studies. The reason for choosing Scaled Super Learner is because of its robustness and resistance to overfitting. Scaled Super Learner is also widely known for its better scalability, simplicity, and ability to handle noisy. The scaled Super Learner is an optimal approach for predicting the properties of Mg alloys. The proposed scaled Super learner serves as a tool for predicting Mg alloy properties.

在镁（Mg）合金中使用机器学习算法已发展成为一项轻量级的科学创新。数据集是通过收集实验数据并利用机器学习（ML）模型来预测 348 种镁合金的机械性能而编制的。不同 ML 模型得出的预测结果和实验结果之间的比例要求采用更先进的回归方法来获得更好的结果。利用镁合金描述符作为输入变量，机械性能作为输出变量，采用了四种不同的 ML 模型，即随机森林 (RF)、额外树 (ET)、梯度提升 (GB) 和极端梯度提升 (XGBoost) 来解决这一难题。每种算法都旨在预测镁合金的机械性能，即极限拉伸强度（UTS）、屈服强度（YS）和伸长率（EL）。随后，采用数据驱动的智能预测建模技术，即缩放超级学习器（SL），将单一模型集成到堆叠模型方法中，以提高预测精度。使用缩放式超级学习器获得的结果表明，UTS、YS 和 EL 的预测精度得到了提高。与以前的研究相比，这些结果进一步证明了预测能力的增强，其均方根误差（RMSE）更低，R-平方（R2）更高，从而优于其他方法。之所以选择缩放式超级学习器，是因为它具有鲁棒性和抗过拟合能力。缩放式超级学习器也因其更好的可扩展性、简单性和处理噪声的能力而广为人知。缩放超级学习器是预测镁合金特性的最佳方法。所提出的缩放超级学习器可作为预测镁合金特性的工具。

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引用次数: 0