热压缩过程塑性流变应力线性模型的建立

Linear Model of Plastic Flow Stress for Hot Compression Deformation

利用GLEEBLE-1500热模拟机对GCr15钢进行应变速率为0.1~5/s和变形温度为1123~1373 K的单道次热压缩试验,分析塑性流变应力σ与变形温度、应变速率和应变量之间的关系,提出了与lnσ呈线性关系的基本因子的概念,并考虑基本因子间的交互作用,通过多元线性叠加的方法,建立了包含变形温度、应变速率和应变量的塑性流变应力线性模型,并衍生出应变速率敏感性指数和变形激活能的计算式,以及应力-应变曲线的拟合方程。计算结果表明:对试验钢,塑性流变应力的预测误差均在±12 MPa之内,且在±6 MPa之内的分数为89.7%;应变速率敏感性指数在0.09~0.27之间,且随应变量增加有先增大后减小再增大的变化趋势,随变形温度增大而增大,其与变形激活能的倒数几乎呈线性变化;应力-应变曲线拟合方程的构造形式不仅适用于试验钢,而且适用于不同金属材料的多种类型的应力-应变曲线。因此,尽管流变应力模型繁多,但线性模型的提出仍是一项有益工作。

Single-hit hot compression tests of GCr15 steel with strain rates of 0.1~5/s and deformation temperatures of 1123~1373 K were carried out on a GLEEBLE-1500 thermo simulator.By investigating relationships between plastic flow stress (σ) and deformation parameters such as deformation temperature, strain rate and strain, a new concept of element factor of linear relationship with lnσ was defined,then considering the element factors and interactions of them,a linear model of plastic flow stress including deformation temperature, strain rate and strain was established by the method of multiple linear superposition,at the same time formulas of strain rate sensitivity exponent and deformation activation energy and fitting equation of stress-strain curve were derived from the model. Computed results show that the prediction error of plastic flow stress for the test steel is within ±12 MPa,and the fraction is 89.7% in the range of ±6 MPa. Also show that strain rate sensitivity exponent is between 0.09 and 0.27,and increases firstly and decreases later and then increases with increase of strain,and increases with increase of deformation temperature,and it is surprising that strain rate sensitivity exponent vs. reciprocal of deformation activation energy is almost linear. Moreover, the constructional form of stress-strain curve fitting equation is not only good agreement for experimental curves, but also applicable to various types of stress-strain curves for several metal materials. Therefore,although flow stress models are abundant,the recommendation of the linear model is still useful.