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通过热压缩实验研究了Ti2041合金的流动行为.利用BP神经网络建立的合金本构模型具有较高的精度,其相关系数达到0.99613,平均相对误差为4.498％,预测值偏差在10％以内的数据点达92.98％.在实验数据的基础上,研究了应变速率敏感因子、功率耗散和失稳参数.建立了加工图,通过加工图的预测和显微组织观察,失稳区主要为局部流动(650～775℃/0.056～1 s-1)和机械失稳(825～900℃/0.056～1 s-1),稳定区的变形机制主要为动态再结晶.结果 表明:合适的变形参数为变形温度760～825℃/825～900℃,应变速率0.001～0.01 s-1/0.0032～0.056 s-1.“,”The flow behavior of Ti2041 alloy was studied through hot compressive experiments.The constitutive model of alloy was established by back propagation (BP) neural network.Results show that the constitutive model has high accuracy,with correlation coefficient of 0.996 13 and average relative error of 4.498％,and the data points whose predictive deviation is within 10％ are 92.98％.Based on the experimental data,the strain rate sensitivity,the power dissipation and the instability parameter were investigated.Processing maps were established.Through processing map prediction and microstructure observation,the instability zones are mainly flow localization (650～775 ℃/0.056～1 s-1) and mechanical instability (825～900 ℃/0.056～1 s-1),and the deformation mechanism of the stability zone is mainly dynamic recrystallization.It is found that the optimal deformation parameters are: deformation temperature of 760～825 ℃/825～900 ℃ and strain rate of 0.001～0.01 s1/0.0032～ 0.056 s-1