Transactions of Materials and Heat Treatment

Title：Model of constitutive relationship for TB8 alloy based on BP neural network

Authors： ZHANG Qing1 LI Ping2 XUE Ke-min2(1.Department of Mechanical Engineering Anhui Vocational and Technical College Hefei 230051 China 2.Institute of Material Science and Engineering Hefei University of Technology Hefei 230009 China)

Unit：

KeyWords： TB8 alloy constitutive relationship BP artificial neural network

ClassificationCode：TG115.53

year,vol(issue):pagenumber：2010,35(1):130-133

Abstract：

Isothermal compression tests on TB8 alloy were conducted using Gleeble 1500 thermomechanical test system and the flow stress values at deferent deforming condition were obtained.Based on the experiment data corrected for friction,the constitutive relationship model was constructed in the shape of 3×10×1BP artificial neural network.The results show that the artificial neural network models have excellent capability under the conditions that the number of nodes in the hidden layer is 10,the learning rate is 0.05 and the momentum factor is 0.4.It can describe the influences of the temperature,strain rate and true strain on the flow stress accurately,and also provide basis for determining hot forming process and numerical simulation.

Funds：

Reference：

[1]于冬梅.新型钛合金TB8的应用研究[J].飞机设计,2002,(2):57-65.
[2]钱九红.航空航天用新型钛合金的研究发展及应用[J].稀有金属,2004,24(3):219-222.
[3]熊爱明,陈胜晖,黄维超,等.TC6钛合金的高温变形行为及组织演变[J].稀有金属材料与工程,2003,32(6):447-450.
[4]Serajzadeh S,Taheri A K.Prediction of flow stress at hotworking condition[J].Mechanics Research Communications,2003,30(1):87-93.
[5]于翔.AZ61B镁合金热加工成形的数值模拟及组织预报[D].重庆:重庆大学,2004.
[6]王锋.TA15合金热变形组织和性能研究[D].合肥:合肥工业大学,2008.
[7]鲁世强,周细林,王克鲁,等.基于BP神经网络的2D70铝合金本构关系模型[J].锻压技术,2008,33(1):148-151.
[8]张彬,李东升,周贤宾.基于人工神经网络的拉形回弹预测技术研究[J].塑性工程学报,2003,10(2):28-31.
[9]洪志强.Ti-15-3合金高温本构模型的建立及在模拟中的应用[D].合肥:合肥工业大学,2007.
[10]张青.TB8合金热变形组织的分形研究及演变模拟[D].合肥:合肥工业大学,2008.
[11]李萍,段园培,张青,等.基于摩擦修正的TB8合金热压缩流变应力行为分析[J].稀有金属,2009,33(2):137-141.
[12]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京:清华大学出版社,2005.
[13]Rao K R,Prased Y K.Neural network approach to flowstress evaluation in hot deformation[J].Mater.Proc.Tech.,1995,53:552-556.

Service：

【This site has not yet opened Download Service】【Add Favorite】