Yi Sheng-Xian, Yang Zhong-Jiong, Xie Huang-Xin
State Key Laboratory of High-Performance Complex Manufacturing, School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.
Materials (Basel). 2022 Mar 4;15(5):1923. doi: 10.3390/ma15051923.
Titanium alloys are extensively employed in the fabrication of various aviation structural parts, of which the most crucial processing step is hot working. In order to study the high-temperature deformation behavior of the TC21 titanium alloy, high-temperature tensile tests were performed. The results reveal that the flow stress of the material gradually decreases with an increased strain rate, and the stress increases rapidly with an increase in strain during the deformation of the alloy. Following this, flow stress gradually decreases. Flow stress decreases sharply, and the sample fractures when the appearance of necking and microvoids is observed. The Arrhenius and Radial basis function (RBF) neural network constitutive models are established in order to accurately describe the high-temperature deformation behavior of the material. In the modified Arrhenius model, strain rate indexes are expressed as a function of deformation temperature and strain rates; furthermore, the high prediction ability of the model was obtained. For the Radial basis function, the network parameters were obtained using the trial-and-error method. The established models could better forecast the flow stress of materials, and highly accurate results are obtained using the radial basis function model. The relationships between the stress index and the deformation activation energy with strain indicate that the primary deformation mechanism involves grain boundary slip and viscous slip of dislocations. The process of dynamic recrystallization primarily promotes the softening of the material.
钛合金广泛应用于各种航空结构件的制造,其中最关键的加工步骤是热加工。为了研究TC21钛合金的高温变形行为,进行了高温拉伸试验。结果表明,材料的流变应力随应变速率的增加而逐渐降低,合金变形过程中应力随应变的增加而迅速增加。在此之后,流变应力逐渐降低。当观察到颈缩和微孔洞出现时,流变应力急剧下降,试样断裂。为了准确描述材料的高温变形行为,建立了阿累尼乌斯和径向基函数(RBF)神经网络本构模型。在改进的阿累尼乌斯模型中,应变速率指数表示为变形温度和应变速率的函数;此外,该模型具有较高的预测能力。对于径向基函数,采用试错法获得网络参数。所建立的模型能够较好地预测材料的流变应力,采用径向基函数模型得到了高精度的结果。应力指数和变形激活能与应变之间的关系表明,主要变形机制包括晶界滑移和位错的粘性滑移。动态再结晶过程主要促进了材料的软化。