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Abstract：
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Samples of Ti-4.5Al-3Mo-1V alloy are compressed in α+β phase field on a Gleeble-1500 Simulator. The dynamic softening model in the upsetting process is investigated based on the corrected stress-strain curves. The influences of hot working parameters on the flow stress are systematically studied. A predicting model has been developed by a BP neural network method for the relation between flow stress and deformation strain, strain rate and temperature of Ti-4.5Al-3Mo-1V alloy. The experimental results show that flow curves of the alloy are characterized by a linear increase until regular oscillations at high strain rates or single peak at low strain rates after which flow softening is observed. The softening mechanism is dynamic recrystallization. And the flow stress decreased with increasing temperature and decreasing strain rate. Moreover, the trained network is able to predict the flow stress very accurately.
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AuthorIntro：
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Reference：
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[1]LiLX.Flowstressbehavioranddeformationcharacteristicsof Ti3Al5V5Mocompressedatelevatedtemperatures[J].MaterialsandDesign,2002,451457.
[2]曹乃光.金属塑性加工原理[M].北京:冶金工业出版社,1983:231235.
[3]林新波,张质良,阮雪榆.利用BP神经网络预测材料温锻流动应力[J].上海交通大学学报.2002,36(4):459462.
[4]LinXB,XiaoHSh,ZhangZL.Flowstressofcarbonsteel08Fintemperaturerangeofwarm forging[J].Journalof MaterialsProcessingTechnology.2003,139(13):543546.
[5]SerajzadehS,TaheriAK.Predictionofflowstressathot workingcondition[J].MechanicsResearchCommunica tions.2003,30(1):8793.
[6]王祖唐,关廷栋.金属塑性成形理论[M].北京:机械工业出版社,1989:143147.
[7]L櫣tjeringG.Influenceofprocessingonmicrostructureandme chanicalpropertiesof(α+β)titaniumalloys[J].Materials ScienceandEngineeringA.1998,243(12):3245.
[8]TakasugiT,WatanabeY,InoueH.Dynamicrecrystallization andsuperplasticdeformationofCo3Ti[J].Scriptamater.2000,43(6):485490.
[9]王科俊,王克成.神经网络建模、预报与控制[M].哈尔滨工程大学出版社,1996:3773.
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