High-temperature deformation characteristics and constitutive models of Inconel 625 superalloy
High-temperature deformation characteristics and constitutive models of Inconel 625 superalloy
复制标题
Inconel 625高温合金高温变形特性及本构模型
DOI：
10.1016/j.mtcomm.2022.103855
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发表时间：
2022-06-30
影响因子：
3.8
通讯作者：
Lu, Xian-zheng
中科院分区：
文献类型：
--
作者：
Chen, Xiao -Min;Nie, Liao -Yuan;Lu, Xian-zheng
通过等温压缩试验，研究了Inconel 625高温合金在1000-1150 ℃、0.01 ~ 10 s（-1）应变速率范围内的热变形特性。分析了热变形机制及变形参数对热变形特征的影响。结果表明，真应力先上升到最大应力水平，然后逐渐下降到一个相对稳定的水平，表现出明显的加工硬化（WH）和动态软化（DS）的功能。同时，真应力随变形温度的降低或应变速率的增加而迅速升高。此外，在较大的真应变、较高的温度和较低的应变速率下，几乎细小而均匀的晶粒围绕着整个组织。此外，分别采用BP算法和二进制粒子群优化算法（NBPSO），建立了三种本构模型，包括Arkanius型（AT）模型、基于物理的（PB）模型和人工神经网络（ANN）模型。通过相关系数（R）和绝对相对误差（ARE）分布的估计来评价模型的预测能力。可以得出结论，AT，PB和NBPSO-BP神经网络模型的最大绝对相对误差分别接近12%，15%和7.2%。同时，NBPSO-BP神经网络模型的相关系数高达0.9983，而AT和PB模型的相关系数分别为0.9951和0.9903。因此，所建立的NBPSO-BP神经网络模型能够准确地描述所研究高温合金的热变形特征。
The isothermal compressive tests are performed to analyze the hot deformation characteristics of Inconel 625 superalloy over a wide temperature range of 1000-1150 degrees C and the strain rate scope of 0.01-10 s(-1). The hot deformation mechanisms and the impacts of deformation parameters on the thermal deformation features, are analyzed. It reveals that the true stress first rises to a maximum stress level and then progressively drops to a comparatively stable level, demonstrating apparent work-hardening (WH) and dynamic softening (DS) features. Meanwhile, the true stress swiftly rises with the reduced deformation temperature or the increased strain rate. Moreover, the almost fine and uniform grains surround the whole microstructure under relatively large true strain, elevated temperature, and depressed strain rate. Besides, three kinds of constitutive models, including the Arrhenius-type (AT) model, physical-based (PB) model, and artificial-neural-network (ANN) model, complied with the backpropagation learning (BP) and new binary particle swarm optimization (NBPSO) algorithms are developed, respectively. The correlation coefficient (R) and absolute relative error (ARE) distribution are estimated to assess the predictive abilities of the established models. It can be concluded that the maximum absolute relative errors are near 12%, 15%, and 7.2% for AT, PB, and NBPSO-BP ANN models, respectively. Meanwhile, the correlation coefficient of the NBPSO-BP ANN model is as high as 0.9983, while the corresponding ones for the AT and PB models are 0.9951 and 0.9903, respectively. Thus, the established NBPSO-BP ANN model can depict the hot deformation features of the studied superalloy precisely.