摘要:
|
TC21合金是一种高强、高韧、高损伤容限型两相钛合金,具有极佳超塑成形性能。建立合理的超塑性本构关系,对了解该合金的超塑性变形特征以及超塑性成形工艺优化有着重要的指导作用。本文对TC21合金在Gleeble1500热模拟试验机上进行了超塑性等温压缩变形试验。结果表明,随着温度的升高或应变速率的降低,材料的流变应力显著降低,动态再结晶是其主要的软化机制。根据所获得的实验数据,应用BP人工神经网络建立了TC21合金的超塑性本构关系模型,较好地反映了TC21合金的超塑变形过程中流动应力的变化规律。
|
TC21 alloy is a two-phase alloy with high strength,high toughness and high damage-tolerant,and expresses excellent superplasticity.So it is necessary to build an appropriate constitutive relationship for profound study on dynamic response between flow-stress and thermal parameters during superplastic deformation,which has important guiding effect on optimization of superplastic processing parameters.In this study,superplastic compression tests were carried out for TC21 alloy by Gleeble1500 stress-strain simulator.Deformation behaviors were analyzed during superplastic compression.The results show that flow stress decreased with the increasing of temperature or decreasing of strain rate during superplastic compression deformation,and that dynamic recrystallization was the main softening mechanism.Then constitutive relationship of superplastic deformation was obtained on the basis of experimental data by BP artificial neural network method,which reflects the relationship between flow stress and its influencing factors satisfactorily.
|
基金项目:
|
|
作者简介:
|
|
参考文献:
|
[1]郭鸿镇,张维,赵张龙,等.TC21新型钛合金的超塑性拉伸行为及组织演化[J].稀有金属材料与工程,2005,34(12):1935-1939.
[2]曲恒磊,赵永庆,冯亮,等.TC21钛合金不同变形条件下的显微组织研究[J].材料工程,2006,(Z1):274-277.
[3]冯亮,曲恒磊,赵永庆,等.TC21合金的高温变形行为[J].航空材料学报,2004,24(4):11-13.
[4]艾立群.人工神经网络在钢铁工业中的应用[J].钢铁研究学报,1997,9(4):60-63.
[5]龙伟,张金,黄杰.人工神经网络发展前景[J].机械,1998,25(1):47-50.
[6]Korczak P,Dyja H,Labuda E.Using neural network modelsfor predicting mechanical properties after hot plate rollingprocesses[J].Journal of Materials Processing Technology,1998,80-81:481-486.
[7]张兴全,彭颖红,阮雪榆.Ti17合金本构关系的人工神经网络模型[J].中国有色金属学报,1999,9(3):590-595.
[8]乔兵,郑文涛,张士宏,等.基于BP神经网络的GH648合金本构模型的建立[J].兵器材料科学与工程,2004,27(4):14-17.
[9]Kapoor R,Pal D,Chakravartty J K.Use of artificial neuralnetworks to predict the deformation behavior of Zr-2.5Nb-0.5Cu[J].Journal of Materials Processing Technology,2005,169:199-205.
[10]沈昌武,杨合,孙志超,等.基于BP神经网络的TA15钛合金本构关系建立[J].塑性工程学报,2007,14(4):101-104.
[11]闻新,周露,李翔,等.MATLAB神经网络仿真与应用[M].北京:科学工业出版社,2003.
[12]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2005.
|
服务与反馈:
|
【文章下载】【加入收藏】
|
|
|