Computational homogenization based crystal plasticity investigation of deformation behavior of AA2024-T3 alloy at different strain rates

IF 1.7 4区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY Multidiscipline Modeling in Materials and Structures Pub Date : 2023-03-21 DOI:10.1108/mmms-10-2022-0236
L. Singh, S. Ha, S. Vohra, Manuj Sharma
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引用次数: 1

Abstract

PurposeModeling of material behavior by physically or microstructure-based models helps in understanding the relationships between its properties and microstructure. However, the majority of the numerical investigations on the prediction of the deformation behavior of AA2024 alloy are limited to the use of phenomenological or empirical constitutive models, which fail to take into account the actual microscopic-level mechanisms (i.e. crystallographic slip) causing plastic deformation. In order to achieve accurate predictions, the microstructure-based constitutive models involving the underlying physical deformation mechanisms are more reliable. Therefore, the aim of this work is to predict the mechanical response of AA2024-T3 alloy subjected to uniaxial tension at different strain rates, using a dislocation density-based crystal plasticity model in conjunction with computational homogenization.Design/methodology/approachA dislocation density-based crystal plasticity (CP) model along with computational homogenization is presented here for predicting the mechanical behavior of aluminium alloy AA2024-T3 under uniaxial tension at different strain rates. A representative volume element (RVE) containing 400 grains subjected to periodic boundary conditions has been used for simulations. The effect of mesh discretization on the mechanical response is investigated by considering different meshing resolutions for the RVE. Material parameters of the CP model have been calibrated by fitting the experimental data. Along with the CP model, Johnson–Cook (JC) model is also used for examining the stress-strain behavior of the alloy at various strain rates. Validation of the predictions of CP and JC models is done with the experimental results where the CP model has more accurately captured the deformation behavior of the aluminium alloy.FindingsThe CP model is able to predict the mechanical response of AA2024-T3 alloy over a wide range of strain rates with a single set of material parameters. Furthermore, it is observed that the inhomogeneity in stress-strain fields at the grain level is linked to both the orientation of the grains as well as their interactions with one another. The flow and hardening rule parameters influencing the stress-strain curve and capturing the strain rate dependency are also identified.Originality/valueComputational homogenization-based CP modeling and simulation of deformation behavior of polycrystalline alloy AA2024-T3 alloy at various strain rates is not available in the literature. Therefore, the present computational homogenization-based CP model can be used for predicting the deformation behavior of AA2024-T3 alloy more accurately at both micro and macro scales, under different strain rates.
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基于计算均匀化的AA2024-T3合金在不同应变速率下变形行为的晶体塑性研究
目的通过基于物理或微观结构的模型对材料行为进行建模,有助于理解其性能和微观结构之间的关系。然而,关于AA2024合金变形行为预测的大多数数值研究仅限于使用唯象或经验本构模型,这些模型未能考虑导致塑性变形的实际微观机制(即结晶滑移)。为了实现准确的预测,涉及潜在物理变形机制的基于微观结构的本构模型更可靠。因此,本工作的目的是使用基于位错密度的晶体塑性模型结合计算均匀化,预测AA2024-T3合金在不同应变速率下受到单轴拉伸的力学响应。设计/方法/方法本文提出了一种基于位错密度的晶体塑性(CP)模型以及计算均匀化,用于预测AA2024-T3铝合金在不同应变速率下单轴拉伸下的力学行为。已使用包含经受周期性边界条件的400个晶粒的代表性体积元素(RVE)进行模拟。通过考虑RVE不同的网格分辨率,研究了网格离散化对力学响应的影响。通过对实验数据的拟合,对CP模型的材料参数进行了标定。除了CP模型外,Johnson–Cook(JC)模型还用于检测合金在不同应变速率下的应力-应变行为。用实验结果验证了CP和JC模型的预测,其中CP模型更准确地捕捉了铝合金的变形行为。发现CP模型能够用一组材料参数预测AA2024-T3合金在宽应变速率范围内的力学响应。此外,观察到晶粒水平上应力-应变场的不均匀性与晶粒的取向及其相互作用有关。还确定了影响应力-应变曲线和捕捉应变速率相关性的流动和硬化规则参数。原创性/价值文献中没有基于计算均匀化的多晶合金AA2024-T3在各种应变速率下变形行为的CP建模和模拟。因此,基于计算均匀化的CP模型可用于在不同应变速率下更准确地预测AA2024-T3合金的微观和宏观变形行为。
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来源期刊
CiteScore
3.70
自引率
5.00%
发文量
60
期刊介绍: Multidiscipline Modeling in Materials and Structures is published by Emerald Group Publishing Limited from 2010
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