基于神经网络的BT20钛合金本构关系模型

在Thermecmastor-Z型热模拟试验机上对BT20钛合金进行了变形温度800～1 100℃及应变速率0.001～70 s-1的热模拟压缩实验。以实验数据为基础,运用BP神经网络算法原理,建立了BT20钛合金在高温变形条件下的应力与应变、应变速率和变形温度关系的预测模型,并对模型的泛化能力进行了误差评价。结果表明:通过BP神经网络建立的合金本构关系模型具有较高的预测精度,预测结果的相对误差均在3%以内,能很好地满足实际应用的需求。此外,该模型能够客观、真实地描述BT20钛合金的高温动态变形行为,为材料高温本构关系模型的建立提供了快捷、有效的工具。

Constitutive Relationship Model of BT20 Titanium Alloy Based on the Artificial Neural Network

Isothermal compression test of BT20 titanium alloy was conducted on the Thermecmastor-Z Thermal Simulator at the temperature of 800 -1 100 ℃ and strain rate of 0. 001 -70 s^-1. Based on the obtained experimental data, the constitutive relationship model of BT20 titanium alloy was developed using the principle of BP neural network, which presents the relation between stress and strain, strain rate as well as deformation temperature. It was found that the relative errors between experimental value and predicted value by ANN were all within 1%, indicating that the developed constitutive relationship model of BT20 titanium alloy possesses the excellent generation capability to meet the requirement of practical application very well. Additionally, the present model in this. investigation can describe the dynamic deformation behavior at high temperature objectively and factually, which is a convenient and effective tool to study the constitutive relationship of materials.