Constitutive model for high temperature deformation of titanium alloys using internal state variables

Luo, Jiao; Li, Miaoquan; Li, Xiaoli; Shi, Yanpei

doi:10.1016/j.mechmat.2009.10.004

Cited by 127 publications

(28 citation statements)

References 49 publications

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“…A general procedure to investigate the microstructure evolution in hot working is summarized as follows: design and implement analogue experiments; acquire the hot working mechanism by metallurgical observation, stress-strain curves as well as processing map [15][16][17][18][19][20][21][22][23][24][25][26][27][28]; determine the processing window based on metallurgical observation and processing map [24,25]; acquire the influence regulation of hot working conditions on the microstructure parameters such as volume fraction, grain size, aspect ratio [25][26][27][28][29][30]; establish mathematical model to predict the microstructure changes [29][30][31][32][33][34][35]; optimize the hot working parameters to get the required microstructure.…”

Section: Microstructure Control In Hot Workingmentioning

confidence: 99%

“…Mesoscopic direct simulation methods (such as Monte Carlo method (MC) and Cellular Automaton method (CA)) offer simulation of aggregates of grains one-to-one, which are capable of considering very complex mechanism but more time-consuming. All the approaches have been used in titanium alloys [29][30][31][32][33][34][35][96][97][98][99]. Tang et al [96] established an empirical model to predict the primary  volume fraction, grain size and dynamic recrystallization fraction of TA15 (Ti-6Al-2Zr-1Mo-1V) alloy in + field.…”

Section: Prediction Of Microstructure Evolution In Hot Workingmentioning

confidence: 99%

“…In ref. [32], an internal state variable model based on dislocation density was established for coupled prediction of flow stress and grain size in hot working of Ti-6Al-4V alloy. Ding and Guo [98] simulated the dynamic recrystallization in  working of Ti-6Al-4V with CA method.…”

Section: Prediction Of Microstructure Evolution In Hot Workingmentioning

confidence: 99%

See 2 more Smart Citations

Recent developments in plastic forming technology of titanium alloys

Yang

Fan

Sun

et al. 2011

Sci. China Technol. Sci.

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Titanium alloys have been used extensively in industry fields including aviation, aerospace and automobile due to their excellent comprehensive properties. Research and development of advanced plastic forming technology are of great importance to manufacturing titanium products of high performance and lightweight with low cost and short cycle. This paper analyzes the development tendencies of titanium alloy forming technology. Recent achievements in precision forming, microstructure control and multi-scale simulation of titanium alloys are reviewed. The forming techniques of large-sale integral complex components are presented. titanium alloys, precision forming, microstructure control, multi-scale simulation, large-scale integral complex components Citation:Yang H, Fan X G, Sun Z C, et al. Recent developments in plastic forming technology of titanium alloys.

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Section: Microstructure Control In Hot Workingmentioning

confidence: 99%

Section: Prediction Of Microstructure Evolution In Hot Workingmentioning

confidence: 99%

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Recent developments in plastic forming technology of titanium alloys

Yang

Fan

Sun

et al. 2011

Sci. China Technol. Sci.

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“…So far there have been three representative constitutive models, i.e. analytical, phenomenological and empirical/ semiempirical ones [8][9][10][11][12][13] . The physical-based analytical model involves the evolution of mobile dislocation density, and static and dynamic grain coarsening etc.…”

Section: Introductionmentioning

confidence: 99%

Modelling the Hot Flow Behaviors of AZ80 Alloy by BP-ANN and the Applications in Accuracy Improvement of Computations

et al. 2015

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Hot compressions of as-cast AZ80 magnesium alloy in a wide temperature range of 523-673 K and strain rate range of 0.01-10 s -1 with a height reduction of 60% were conducted by a Gleeble-1500 thermo-mechanical test simulator. The hot flow behaviors show highly non-linear intrinsic relationships with temperature, strain and strain rate. In order to model the complicated flow behaviors, error back-propagation algorithm, a representative method to minimize the target error, was selected to train the artificial neural network. A comparative study was made on the predictabilities of the improved Arrhenius-type and BP-ANN model by using two standard statistical parameters including correlation coefficient (R) and average absolute relative error (AARE). Comparison results show that the well-trained BP-ANN has higher prediction accuracy. Three highlight applications were presented. Firstly, the strain-stress data volume was expanded by BP-ANN predictions above experimental conditions. Secondly, the expanded data were applied in the simulations of isothermal compressions, and high simulation accuracy for the load-stroke curve was achieved. Thirdly, a three-dimensional (3D) interaction space of stress, strain, temperature and strain rate was constructed based on the intensive data, which supplies the stress data to arbitrary temperature, strain rate, and strain.

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“…Most likely, intensive plastic deformation also causes a significant change in microstructure of material in a narrow layer near frictional and bi-material interfaces in metal-forming processes [18][19][20][21][22][23][24]. The equivalent strain rate is usually involved in evolution equations for parameters characterizing the microstructure of material in such a manner that high gradients of the equivalent strain rate predict high gradients of material properties (see, for example [25][26][27][28]). Since (1) predicts intensive plastic deformation in a narrow layer near frictional interfaces, this theoretical result is in qualitative agreement with the experimental results reported in [18][19][20][21][22][23][24].…”

mentioning

confidence: 99%

A numerical method for determining the strain rate intensity factor under plane strain conditions

Alexandrov

Kuo

Jeng

2015

Continuum Mech. Thermodyn.

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Using the classical model of rigid perfectly plastic solids, the strain rate intensity factor has been previously introduced as the coefficient of the leading singular term in a series expansion of the equivalent strain rate in the vicinity of maximum friction surfaces. Since then, many strain rate intensity factors have been determined by means of analytical and semi-analytical solutions. However, no attempt has been made to develop a numerical method for calculating the strain rate intensity factor. This paper presents such a method for planar flow. The method is based on the theory of characteristics. First, the strain rate intensity factor is derived in characteristic coordinates. Then, a standard numerical slip-line technique is supplemented with a procedure to calculate the strain rate intensity factor. The distribution of the strain rate intensity factor along the friction surface in compression of a layer between two parallel plates is determined. A high accuracy of this numerical solution for the strain rate intensity factor is confirmed by comparison with an analytic solution. It is shown that the distribution of the strain rate intensity factor is in general discontinuous.

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Constitutive model for high temperature deformation of titanium alloys using internal state variables

Cited by 127 publications

References 49 publications

Recent developments in plastic forming technology of titanium alloys

Recent developments in plastic forming technology of titanium alloys

Modelling the Hot Flow Behaviors of AZ80 Alloy by BP-ANN and the Applications in Accuracy Improvement of Computations

A numerical method for determining the strain rate intensity factor under plane strain conditions

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