(1. 空军工程大学 航空工程学院，西安 710038；
2. 中国人民解放军93152部队，通化 134000)
摘 要: 为研究BT3-1钛合金的力学性能，比较不同算法及试验条件下估计Johnson-Cook本构模型参数的差异，通过材料力学性能试验，获得真实应力-应变曲线，结合几种常见算法估计其本构模型参数，并分析了不同应变率及温度数据处理方式对估计的影响。结果表明：在准静态压缩试验中，BT3-1钛合金的弹性模量、流动应力对应变率敏感性不同；在SHPB试验中，该材料随温度软化效应明显，且伴随着一定的应变率强化现象。名义上某一应变率和温度下的霍普金森压杆试验，实际应变率在名义应变率附近波动，实际温度受到加载应变率及加载温度的共同影响；不同估计算法会造成运算时间、估计结果的差异，用SHPB试验数据估计参数时，若直接采用试验设定的应变率及温度数据，将会造成较大的估计偏差，应考虑加载过程中的温度变化。
关键字: 霍普金森压杆试验；Johnson-Cook本构模型；最优化算法；参数估计
（1. Aeronautics Engineering College, Air Force Engineering University, Xi’an 710038, China;
2. 93152 Unit of People’s Liberation Army of China, Tonghua 134000, China）
Abstract:In order to investigate the mechanical properties of BT3-1 titanium alloy and compare parameter estimation results of Johnson-Cook constitutive model by different algorithms and experimental conditions , the real stress-strain curves of the material were obtained by mechanical properties experiments. A variety of common algorithms were selected to estimate the parameters of the material constitutive model, and the influence of the results was analyzed by different strain rate and temperature data processing methods. The results indicate that the elastic modulus and flow stress of BT3-1 titanium alloy have different sensitivity to variability in the quasi-static compression test, the material has obvious softening effect with temperature, and it is accompanied by a certain strain rate strengthening phenomenon in the SHPB test. The actual strain rate fluctuates around the nominal strain rate, and the actual temperature change is affected by the nominal strain rate and the nominal temperature. Different parameter estimation algorithms will cause different calculation time and estimation results; When estimating the parameters by using the SHPB experiments data, it will result in a large estimated deviation if the nominal strain rate and temperature data are adopted, consideration should be given to temperature changes during the loading process.
Key words: Hopkinson pressure bar experiments; Johnson-Cook constitutive model; optimization algorithm; parameter estimation
