Primary hot working characteristics and microstructural evolution of as-cast and homogenized Ti-4Al-2.5V-1.5Fe alloy

Sukumar, G.; Singh, B.Bhav; Balasundar, I.; Bhattacharjee, Anup Kumar; Sarma, V. Subramanya

doi:10.1016/j.jallcom.2023.169556

Cited by 7 publications

(2 citation statements)

References 73 publications

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“…Figure 8 shows the data for α, m, Q, and ln A under different strains. The change pattern between these parameters and strain is represented by a curve obtained through fifth-order polynomial fitting [30], and the specific expression is given by Equations ( 11)- (14). Figure 8 clearly illustrates that the fitted curve accurately reflects the variation law of each parameter and strain.…”

Section: Arrhenius Modelmentioning

confidence: 96%

“…Dan et al [11] investigated the hot deformation behavior of the TC11 alloy and pointed out that the microstructure evolution under low strain rates was dominated by lamellar tissue spheroidization. Furthermore, several studies [12][13][14] have indicated the substantial influence of strain rate and hot working temperature on microstructure evolution and flow stress. Consequently, it is imperative to predict the hot deformation behavior of TMCs accurately under different strain rates and hot working temperatures.…”

Section: Introductionmentioning

confidence: 99%

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Study on the Constitutive Modeling of (2.5 vol%TiB + 2.5 vol%TiC)/TC4 Composites under Hot Compression Conditions

Qiang,

Wang,

Wang

et al. 2024

Materials

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The hot deformation behavior of titanium matrix composites plays a crucial role in determining the performance of the formed components. Therefore, it is significant to establish an accurate constitutive relationship between material deformation parameters and flow stress. In this study, hot compression experiments were conducted on a (2.5 vol%TiB + 2.5 vol%TiC)/TC4. The experiments were performed under temperatures ranging from 1013.15 to 1133.15 K and strain rates ranging from 0.001 to 0.1 s−1. Based on the stress–strain data obtained from the experiment, the constitutive models were established by using the Arrhenius model and the BP neural network algorithm, respectively. Considering the relationship between strain rate, hot working temperature, and flow stress, a comparative analysis was conducted to evaluate the prediction accuracy of two different constitutive models. The research results indicate that the flow stress of (2.5 vol%TiB + 2.5 vol%TiC)/TC4 increases with decreasing temperature and increasing strain rate, and the stress–strain curve shows obvious work hardening and softening behaviors. Both the Arrhenius model and the BP neural network algorithm are effective in predicting the hot compression flow stress of (2.5 vol%TiB + 2.5 vol%TiC)/TC4, but the average relative error and root mean square error of the BP neural network algorithm are smaller and the correlation coefficient is higher, thus possessing higher accuracy and reliability.

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Section: Arrhenius Modelmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%