In-situ prediction of α-phase volume fraction in titanium alloy using laser ultrasonic with support vector regression

2021 ◽  
Vol 177 ◽  
pp. 107928
Author(s):  
Dan Chen ◽  
Yanjun Liu ◽  
Wei Feng ◽  
Yuanhao Wang ◽  
Qing Hu ◽  
...  
Keyword(s):  
Titanium Alloy ◽  
Support Vector Regression ◽  
Volume Fraction ◽  
Support Vector ◽  
Phase Volume ◽  
Laser Ultrasonic ◽  
Phase Volume Fraction ◽  
Α Phase ◽  
In Situ Prediction

scholarly journals Influence of Microstructures on Tensile Properties at 400℃ of TC4 Titanium Alloy

2020 ◽  
Vol 321 ◽  
pp. 11048
Author(s):  
Ren Yong ◽  
Yang Nan ◽  
Lei Jinwen ◽  
Li Shaoqiang ◽  
Du Yuxuan
Keyword(s):  
Titanium Alloy ◽  
Yield Strength ◽  
Tensile Properties ◽  
Volume Fraction ◽  
Solution Treatment ◽  
Air Cooling ◽  
Phase Volume Fraction ◽  
Tc4 Titanium Alloy ◽  
Α Phase ◽  
Cooling Speed

The effects of primary α phase volume fraction on the tensile properties at 400℃ of TC4 titanium alloy was studied by different solution temperature(Tβ-(10~80)℃). The effects of the thick of secondary α phase on the tensile properties at 400℃ of TC4 titanium alloy was studied by different cooling speed after solution treatment (water quench, air cooling, furnace cooling). The results show that with the decrease of primary α phase, the tensile and yield strength increase up, but the ductility has a little change. The thick of secondary α phase increases with the deceases of cooling speed after solution treatment, highest tensile and yield strength by water quench, the tensile strength of air cooling and furnace cooling were basically the same, but the yield strength of furnace cooling was 40MPa lower than air cooling. Therefore, the influence of the primary α phase volume fraction on the tensile strength at 400℃ was particularly obvious, we can control solution treatment and cooling way in combination with different requirements.

Effects of the Variation in α-Phase Volume Fraction on the Thermal Stability of TiAl Alloys with Lamellar Microstructures

2002 ◽  
Vol 753 ◽  
Author(s):  
S. W. Kim ◽  
H. N. Lee ◽  
M. H. Oh ◽  
M. Yamaguchi ◽  
D. M. Wee
Keyword(s):  
Thermal Stability ◽  
Volume Fraction ◽  
Lamellar Microstructure ◽  
Phase Volume ◽  
Heating Rates ◽  
Tial Alloys ◽  
Phase Volume Fraction ◽  
Volume Fractions ◽  
Α Phase ◽  
Thermal Stability Of

ABSTRACTThe thermal stability of lamellar microstructure in Ti-Al-Mo PST crystals containing C or Si, was investigated. In addition, the variation of α-phase volume fraction in Ti-Al-Mo-(C,Si) systems was investigated at several temperatures. Ti-46Al-1.5Mo-0.2C and Ti-46Al-1.5Mo-1.0Si alloys were found to be very stable during heat treatments at various heating rates and temperatures. Moreover, the α-phase volume fractions of Ti-46Al-1.5Mo-0.2C and Ti-46Al-1.5Mo-1.0Si alloys, which were stable compositions, changed less than those of Ti-47Al and Ti-46–1.5Mo alloys, which were unstable compositions. From these results, it was determined that the instability of the latter alloys was caused by their relatively higher variation of α-phase volume fraction during heating. Therefore, it is suggested that the variation of α-phase volume fraction is an important factor in controlling the thermal stability of lamellar microstructure.

Microstructure Alteration in the High-Speed Machining of Titanium Alloy Involved With Tool Wear and Cryogenic Condition

2021 ◽  
Author(s):  
Xin Li ◽  
Xueping Zhang ◽  
Rajiv Shivpuri
Keyword(s):  
Experimental Data ◽  
Grain Size ◽  
Titanium Alloy ◽  
Tool Wear ◽  
High Speed ◽  
Volume Fraction ◽  
High Speed Machining ◽  
Phase Volume ◽  
Machined Surface ◽  
Phase Volume Fraction

Abstract The microstructure alteration generated in the high-speed machining of titanium alloy has significant influence on the performance, quality and service life of production. The prediction of grain size or phase distribution based on physics mechanism or the regression of experimental data have been reported in the process of static or quasi-static state. However, it is still a challenge to predict the phase transformation and grain growth process in machining accurately and effectively since it has characteristics of high strain, strain rate and temperature. In this paper, a novel FEM-based model involving with the microstructure alteration was introduced and implemented to predict finial grain size or phase result in the high-speed machining of Ti-6Al-4V alloys especially at the machined surface. The phase transformation process was proposed and discussed by considering tool wear and cryogenic condition at machined surface, while the microstructure results were displayed on the chip in the previous works. Firstly, the phase volume fraction and grain size were modelled by experimental data. Then the simulation based on the self-consistent method (SCM) was used to output strain and temperature distribution. Thirdly, the phase volume fraction and grain size expressions were transmitted into subroutine programs and the microstructure alteration process under the different cutting conditions were showed in the FE results. The simulation results of temperature, phase fraction and strain were compared against previous simulation or experiment results in published papers revealing good agreement. The proposed model was further to investigate the influence of tool wear and cutting temperature on machined surface. The results indicated that the tool wear increased heat at the flank face significantly resulting to β phase increasing and grain growth at machined surface and the cryogenic condition would lower temperature gradient as well as stress gradient contributing to reduce roughness and residual stress.

scholarly journals Effect of α and β Phase Volume Fraction on Machining Characteristics of Titanium Alloy Ti6Al4V

2016 ◽  
Vol 6 ◽  
pp. 63-70 ◽  
Author(s):  
Sandip Patil ◽  
Swapnil Kekade ◽  
Kamlesh Phapale ◽  
Shital Jadhav ◽  
Amit Powar ◽  
...  
Keyword(s):  
Titanium Alloy ◽  
Volume Fraction ◽  
Phase Volume ◽  
Phase Volume Fraction ◽  
Β Phase ◽  
Titanium Alloy Ti6al4v ◽  
Machining Characteristics

scholarly journals Estimating the phase volume fraction of multi-phase steel via unsupervised deep learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Wook Kim ◽  
Seong-Hoon Kang ◽  
Se-Jong Kim ◽  
Seungchul Lee
Keyword(s):  
High Performance ◽  
Materials Science ◽  
Volume Fraction ◽  
Training Data ◽  
Phase Fraction ◽  
Phase Volume ◽  
Generative Adversarial Network ◽  
Phase Volume Fraction ◽  
Original Dataset ◽  
Multi Phase

AbstractAdvanced high strength steel (AHSS) is a steel of multi-phase microstructure that is processed under several conditions to meet the current high-performance requirements from the industry. Deep neural network (DNN) has emerged as a promising tool in materials science for the task of estimating the phase volume fraction of these steels. Despite its advantages, one of its major drawbacks is its requirement of a sufficient amount of training data with correct labels to the network. This often comes as a challenge in many areas where obtaining data and labeling it is extremely labor-intensive. To overcome this challenge, an unsupervised way of learning DNN, which does not require any manual labeling, is proposed. Information maximizing generative adversarial network (InfoGAN) is used to learn the underlying probability distribution of each phase and generate realistic sample points with class labels. Then, the generated data is used for training an MLP classifier, which in turn predicts the labels for the original dataset. The result shows a mean relative error of 4.53% at most, while it can be as low as 0.73%, which implies the estimated phase fraction closely matches the true phase fraction. This presents the high feasibility of using the proposed methodology for fast and precise estimation of phase volume fraction in both industry and academia.

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