Constitutive Relationship Study of Laves Phase NbCr2/Nb Two-Phase Alloy Using Modified J-C Model and Back Propagation Neural Network Model
Constitutive Relationship Study of Laves Phase NbCr2/Nb Two-Phase Alloy Using Modified J-C Model and Back Propagation Neural Network Model
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DOI：
10.1007/s11665-023-08941-y
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发表时间：
2023-11
影响因子：
2.3
通讯作者：
Jiancong JiangFeng;Shiqiang Lu;Xuan Xiao;Ke-lu Wang;Liping Deng
中科院分区：
文献类型：
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作者：
Jiancong JiangFeng;Shiqiang Lu;Xuan Xiao;Ke-lu Wang;Liping Deng
Laves相NbCr 2/Nb双相合金作为一种潜在的高温结构材料受到了广泛的研究兴趣。基于该合金在1000 ~ 1200 °C温度范围和0.001-0.1 s-1应变速率范围内的等温和恒应变速率压缩实验，分别采用J-C模型和BP人工神经网络模型建立了该合金的流变应力本构关系。结果表明，传统的J-C模型不能描述合金的流变应力软化行为。相比之下，修正的J-C模型能更好地预测合金的流变应力软化现象，准确地表征合金的流变应力行为，其预测精度较高，相关系数（R）为0.9902，平均绝对相对误差（AARE）为8.773%，平均相对误差（MRE）为7.389%。利用BP神经网络模型建立的本构关系可以更准确地表征合金的流变应力行为。该模型具有较高的预测精度，R = 0.9998，AARE = 2.232%，MRE = 0.870%。结果表明，BP神经网络模型对该合金的流变应力行为具有上级预测能力。所建立的流变应力本构关系可为Laves相NbCr 2/Nb双相合金锻造变形过程的有限元模拟提供更为准确可靠的流变应力基础数据。为合理设计锻造工艺和准确计算合金的变形力提供了理论依据。
The Laves phase NbCr2/Nb two-phase alloy has received significant research interest as a potential high-temperature structural material. Based on isothermal and constant strain rate compression experiments conducted on the alloy within a temperature range of 1000 -1200 °C and strain rate range of 0.001-0.1 s−1, the flow stress constitutive relationship of the alloy was established using the J-C model and BP artificial neural network model, respectively. It was found that the conventional J-C model fails to describe the flow stress softening behavior of the alloy. In contrast, the modified J-C model provides a better prediction of the flow stress softening phenomenon and accurately characterizes the flow stress behavior of the alloy, it exhibits high prediction accuracy as indicated by the correlation coefficient (R) of 0.9902, average absolute relative error (AARE) of 8.773% and mean relative error (MRE) of 7.389%. The flow stress behavior of the alloy can be more accurately characterized using the constitutive relationship built by the BP neural network model. The model exhibits higher prediction accuracy withRof 0.9998,AAREof 2.232% andMREof 0.870%. The results demonstrate that the BP neural network model has superior capability in predicting the flow stress behavior of the alloy. The established flow stress constitutive relationship can provide more accurate and reliable fundamental data with respect to flow stress for finite element simulations of forging deformation process of the Laves phase NbCr2/Nb two-phase alloy. In addition, it serves as theoretical basis for rational design of forging process and accurate calculation of the deformation force of the alloy.