摘要
管材力学性能参数是研究管材数控弯曲变形行为的关键因素之一.采用将人工神经网络、有限元模拟以及基于平面应力状态的拉伸实验相结合的参数识别方法,获得了尺寸因子(D/t)为50的铝合金管(5052O)的塑性本构参数.同时,基于ABAQUS软件平台,建立了数控弯管三维弹塑性有限元模型,并利用该模型研究了不同本构参数对弯管塑性变形行为的影响.结果表明:与传统单向拉伸测试相比,采用本文方法获得的管材塑性本构参数模拟的管材外弧面塑性变形行为与实验结果更接近.
Plastic constitutive parameters （PCP） of tube are one of key factors for the study of forming qualities in numerical control （NC） tube bending. A new method for parameters identification is presented, which combines the artificial neural network （ANN）, the finite element analysis （FEA） and the tension experiment based on planar stress status （PSS）. The PCP of aluminum alloy tube （50520） with size factor （ D/t ） of 50 are acquired. Meanwhile, based on the ABAQUS software environment, a 3 D elastic-plastic FE model for NC bending is established, and the effects of different tube PCP on plastic deformation behaviors （PDB） in tube bending are studied using this model. The results reveal that compared with the traditional axial tension test, the PDB in the bending of tube extrados simulated by FEA with PCP obtained by the presented method are closer to experimental results.
出处
《材料科学与工艺》
EI
CAS
CSCD
北大核心
2009年第3期297-300,共4页
Materials Science and Technology
基金
国家杰出青年科学基金资助项目(50225518)
国家自然科学基金资助项目(5997501650175092)
关键词
参数识别
管数控弯曲
人工神经网络
有限元分析
parameters identification
NC tube bending
artificial neural network
finite element analysis
