Materials Research Express · 2019 · 17 citations · 35 references
EngineeringMaterials EngineeringMaterials ScienceComputational Materials ScienceHeat TransferTransport PhenomenaAlloy ThermodynamicsAlloysComputational Solid MechanicsHeat Transfer AnalysisHeat Transfer ModelingMetalsAlloy Phase DiagramsFlow Behavior AnalysisFlow Stress ModelingMaterial Flow BehaviorMelt Flow BehaviorPhase Transition Temperature
Hot compression tests of Ti-6Cr-5Mo-5V-4Al (Ti-6554) alloy were conducted on a Gleeble-3500 isothermal simulator at the temperature range of 963 ∼ 1113 K and strain rate range of 0.001 ∼ 1 s −1 . The effects of temperature, strain rate and strain on flow behavior were analyzed according to the flow curves and microstructure observations. At low temperature range (963 ∼ 1053 K), massive globular α forms barriers to dislocation movement and enhances peak stress. Subsequently, the intensive incidence of dynamic globularization of α leads to strong softening with the increasing strain. At high temperature range (1053 ∼ 1113 K), the volume fraction reduction of α promotes dislocation movement and lowers peak stress. Dynamic crystallization of β operates at low strain rate condition which results in relatively evident decreasing of flow stress. At higher strain rate, squashed α transforms into flocculent structure which can be deemed as the result of dynamic recovery. With the increasing strain, the size of globular α enlarged and phase transform occurs due to the generation of deformation heat. To describe the hot deformation behavior, a modified Johnson-Cook (m-JC) model considering the coupled effects of strain rate and temperature was constructed and a temperature separated type Johnson-Cook model (ts-JC) was proposed to optimize the describing accuracy. Meanwhile, for the further optimization of prediction capability, genetic algorithm (GA) was introduced to optimize the constants of ts-JC model (GA-JC). The prediction capability evaluators ln(MSE)-values and Adj. R 2 -values of m-JC, ts-JC and GA-JC were 4.94, 4.59, 4.29 and 0.990 39, 0.987 85, 0.983 08, respectively, which reveal good optimization results of GA-JC.
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