Establishment of constitutive relationship model for 2519 aluminum alloy based on BP artificial neural network^①

来源期刊：中南大学学报(英文版)2005年第4期

论文作者：林启权 彭大暑 朱远志

文章页码：380 - 384

Key words：2519 aluminum alloy; BP algorithm; neural network; constitutive model

Abstract: An isothermal compressive experiment using Gleeble 1500 thermal simulator was studied to acquire flow stress at different deformation temperatures, strains and strain rates. The artificial neural networks with the error back propagation(BP) algorithm was used to establish constitutive model of 2519 aluminum alloy based on the experiment data. The model results show that the systematical error is small(δ=3.3%) when the value of objective function is 0.2, the number of nodes in the hidden layer is 5 and the learning rate is 0.1. Flow stresses of the material under various thermodynamic conditions are predicted by the neural network model, and the predicted results correspond with the experimental results. A knowledge-based constitutive relation model is developed.