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首页> 外文期刊>International Journal of Mechanical Sciences >Peridynamic micromechanical prediction of nonlocal damage initiation and propagation in DP steels based on real microstructure
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Peridynamic micromechanical prediction of nonlocal damage initiation and propagation in DP steels based on real microstructure

机译:基于真实组织的DP钢中非识别非识别损伤发起和传播的白宫微观力学预测

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摘要

Dual phase steels are the complex heterogeneous materials that are widely used in various automobile industries. It is important to develop numerical methods to enhance the capability of the damage mechanism prediction. Dual phase steels consist of soft ferrite and hard martensite phases and the grain boundaries play the main role as the important location with possible occurrence of damage in these materials. In this study, a microstructure-based approach using representative volume elements is utilized to evaluate the damage initiation and propagation. The material is modeled at the microscopic scale using real microstructural SEM images. A two-dimensional model is developed and the damage mechanisms of dual phase steels are simulated using a bond based peridynamic microstructural model. According to the peridynamic simulation, no mesh refinement is necessary, as damage is inherently characterized by bond breakages and the obtained damage patterns are compared with experimental SEM images. Finally, a sensitivity analysis is conducted to understand the effect of peridynamic discretization, real microstructure, horizon size and interface behavior on the damage pattern of the proposed model under tension static loading. It is shown that the obtained damage initiation and propagation patterns are in good agreement with the experimental results.
机译:双相钢是各种汽车行业广泛应用的复杂异质材料。重要的是要制定数值方法以增强损坏机构预测的能力。双相钢由软铁氧体和硬马氏体阶段组成,晶粒边界在可能发生这些材料中可能发生损坏的重要位置。在该研究中,利用代表体积元素的基于微结构的方法来评估损伤启动和传播。使用真实的微结构SEM图像在微观尺度上以微观尺度进行建模。开发了二维模型,使用基于粘接性的白动力学微观结构模型进行模拟双相钢的损伤机制。根据智动模拟,没有必要的网格细化,因为通过粘合破损固有地表征损坏,并且将获得的损坏模式与实验SEM图像进行比较。最后,进行了敏感性分析,以了解张力静载下提出模型的损伤模式对智能动力学离散化,实际微观结构,地平线大小和接口行为的影响。结果表明,获得的损伤和传播模式与实验结果吻合良好。

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