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# High Temperature Materials and Processes

Editor-in-Chief: Fukuyama, Hiroyuki

Editorial Board: Waseda, Yoshio / Fecht, Hans-Jörg / Reddy, Ramana G. / Manna, Indranil / Nakajima, Hideo / Nakamura, Takashi / Okabe, Toru / Ostrovski, Oleg / Pericleous, Koulis / Seetharaman, Seshadri / Straumal, Boris / Suzuki, Shigeru / Tanaka, Toshihiro / Terzieff, Peter / Uda, Satoshi / Urban, Knut / Baron, Michel / Besterci, Michael / Byakova, Alexandra V. / Gao, Wei / Glaeser, Andreas / Gzesik, Z. / Hosson, Jeff / Masanori, Iwase / Jacob, Kallarackel Thomas / Kipouros, Georges / Kuznezov, Fedor

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Volume 36, Issue 7

# A Study at the Workability of Ultra-High Strength Steel Sheet by Processing Maps on the Basis of DMM

Yu Feng Xia
/ Shuai Long
/ Tian-Yu Wang
/ Jia Zhao
Published Online: 2016-09-24 | DOI: https://doi.org/10.1515/htmp-2016-0006

## Abstract

The hot workability of the ultra-high strength steel BR1500HS has been investigated by processing maps. A series of hot deformation tensile tests were carried out on a Gleeble-3500 thermal simulator in the deformation temperature range of 773–1,223 K and strain rate range of 0.01–10 s–1. The obtained flow stress curves reveal that the peak stress increases with the rising of strain rate and decreases with the rising of temperature. Based on dynamic materials model (DMM), the processing maps at the strains of 0.05, 0.10 and 0.15 were developed, and the optimum hot working conditions were recommended as the temperature range of 1,200–1,223 K and the strain rate range of 0.01–0.1 s–1, where the peak power dissipation efficiency is about 37 % revealing the occurrence of typical dynamic recrystallization (DRX). The main instability defects are deformation twinning and micro-crack occurring mainly at the temperature range of 773–873 K with the strain rate higher than 1 s–1. In order to deeply understand the microstructure mechanisms, the Zener–Hollomon parameter is solved, and then the self-diffusion activation energy is compared with the apparent activation energy Q at different deformation temperatures and strain rates.

## Introduction

Ultra-high strength steel BR1500HS is a kind of boron steel developed by Baosteel Group Corporation. Vehicle light-weighting and improving of crashworthiness in auto industry greatly increase the requirement of high strength steel [1]. Deformation process of BR1500HS at austenite phase temperature region and the following quenching process makes it possible to produce complex shapes with tensile strength up to around 1,500 Mpa [2]. In order to obtain better mechanical property and less deformation defect, the hot workability of BR1500HS should be studied.

The workability of metal consists of two independent parts: state of stress (SOS) workability and intrinsic workability [3, 4, 5]. SOS workability is governed by the geometry of deformation zone and the externally imposed stress state, both of which vary with different deformation processes [6, 7]. Intrinsic workability is determined by the microstructure evolution under certain deformation conditions which is implicit in flow behavior [5]. The processing map developed on the basis of DMM has been widely used to understand the intrinsic workability of many materials in terms of the various microstructural mechanisms operating at the different deformation conditions [3, 8, 9, 10, 11, 12, 13]. According to the DMM, the hot deformation of work piece can be seen as a process of power dissipation. The total absorbed power P can be divided into two parts: one part was designated as G content representing the power corresponding to the temperature rising, and the other one was the J co-content which was regard to the power dissipated through microstructure evolution [14]. So the total power P can be expressed as [8]: $P=\mathrm{\sigma }\cdot \stackrel{˙}{\mathrm{\epsilon }}=G+J={\int }_{0}^{\stackrel{˙}{\mathrm{\epsilon }}}\mathrm{\sigma }d\stackrel{˙}{\mathrm{\epsilon }}+{\int }_{0}^{\mathrm{\sigma }}\stackrel{˙}{\mathrm{\epsilon }}d\mathrm{\sigma }$(1)

The work-piece undergoing hot deformation is considered to be a dissipator of power and the strain rate sensitivity (m) of flow stress is the factor that partitions power between deformation heat and microstructural changes [15]. According to the research of Prasad, the power dissipation efficiency η is expressed as [8]: $\mathrm{\eta }=2m/\left(1+m\right)$(2)

In the power dissipation map, the higher the η-value is, the better hot workability the work piece can get. While some instability areas under high power dissipation efficiency cannot be expressed in power dissipation maps. Therefore, it is necessary to build the instability map by a continuum criterion. The criterion was based on the maximum rate of entropy production, and it was determined as [8]: $\mathrm{\xi }\left(\stackrel{˙}{\mathrm{\epsilon }}\right)=\mathrm{\partial }ln\left(m/\left(m+1\right)\right)/\mathrm{\partial }ln\stackrel{˙}{\mathrm{\epsilon }}+m<0$(3)

A processing map consists of a superimposition of efficiency of power dissipation and an instability map, the former revealing the “safe” domain for processing and the latter setting the limits for avoiding undesirable microstructures [16].

In this paper, the deformation behaviors at evaluated temperatures of ultra-high strength steel BR1500HS were investigated based on experimental results of hot tensile tests. The processing maps were constructed, by which, the DRV and DRX mechanisms of this alloy were analyzed and processing parameters were optimized. Furthermore, in order to deeply understand the microstructure mechanisms, the Zener–Hollomon parameter at different temperatures and strain rates were calculated and compared with the self-diffusion activation energy. Finally, the microstructures under different deformation parameters were observed to validate the obvious work.

## Experiments

The hot-rolled ultra-high strength steel BR1500HS sheet with thickness of 1.8 mm used in this study whose chemical compositions are 0.21C–0.27Si–1.33Mn–0.025(max)P-0.005(max)S-012Cr–0.039Al–0.0023B–0.047Ti (wt%). The initial microstructure of this material is shown in Figure 1. The isothermal hot tensile tests were carried out on a Gleeble-3500 thermal simulator. The tensile specimens were prepared according to the standard of GB/T 4338–2006, and the dimension of the specimen is illustrated in Figure 2. The specimens were heated to 1,223 K by 5 Ks–1 and thermal insulation for 180 s to be austenized completely. Then they were cooled to different temperatures at the rate of 15 Ks–1 and held for 10 s to eliminate the internal temperature gradients. The deformation temperatures were 1,223, 1,123, 1,023, 873, 773 K and their strain rates were 0.01, 0.1, 1, 10 s–1 respectively. All specimens were tensed to fracture under constant temperatures and strain rates. Wire-electrode cutting was used to machine the specimens to avoid the effect of work-hardening. Moreover, two location holes with diameter of 8 mm were drilled along the axis of the specimen on both ends to avert sliding. To prevent stress concentration, the cutting lines on the surface were polished by fine grit sandpaper and the specimen was guided rounded edge processing. The thermocouple of thermal simulator was welded on the center of specimen to real-time monitoring and control the temperature. The test chamber of this tensile test refer to the experiment carried out by Merklein et al. [17] whose schematic sketch is shown in Figure 3.

Figure 1:

The initial microstructure of ultra-high strength steel BR1500HS.

Figure 2:

The dimensions of specimen used in uniaxial tensile tests (unit: mm).

Figure 3:

Schematic sketch of the modified test chamber of the servo hydraulic Gleeble 3500 mechanical system [17].

## Flow stress curves

The true strain–stress curves at different temperatures and strain rates were obtained and shown in Figure 4. They indicate that increasing strain rate or decreasing deformation temperature makes the flow stress level increase, in other words, it prevents the occurrence of dynamic softening caused by DRV and DRX, and makes the deformed metals exhibit more work hardening [18]. The cause lies in the fact that higher strain rate and lower temperature provide shorter time for the energy accumulation and lower mobilities at boundaries which result in the nucleation and growth of dynamically recrystallized grains and dislocation annihilation [19, 20, 21]. In addition, some distinct features can be observed from the true strain–stress curves: (a) three types of curve variation tendency can be generalized as following [17]: decreasing gradually to a steady state with DRX softening (1,223 K and 0.01 s−1), maintaining higher stress level without significant softening and work hardening (773 K and 0.01–0.1 s−1, 873–1,023 K and 0.01–10 s−1), and increasing continuously with significant work hardening (773 K and 1–10 s−1); (b) the flow stress increases rapidly at the initial stage which is commonly believed that work hardening predominates, then they decrease with increasing temperature or decreasing strain rate which is commonly believed that high temperature leads energy barrier of dislocation motion decreasing resulting in the acceleration of dynamic recovery and decreasing of flow stress.

Figure 4:

The true stress–strain curves at different deformation conditions: (a) T=773 K, (b) T=873 K, (c) T=1,023 K, (d) T=1,123 K, (e) T=1,223 K.

## Strain rate sensitivity

Strain rate sensitivity of flow stress is a very important parameter which reveals the ductility and plastic of metals and alloys in the forming processes [7]. According to Prasad, the strain rate sensitivity index m is denoted as [8]: ${\left[\frac{\mathrm{\partial }J}{\mathrm{\partial }G}\right]}_{\stackrel{˙}{\mathrm{\epsilon }},T}={\left[\frac{\stackrel{˙}{\mathrm{\epsilon }}\mathrm{\partial }\mathrm{\sigma }}{\mathrm{\sigma }\mathrm{\partial }\stackrel{˙}{\mathrm{\epsilon }}}\right]}_{\stackrel{˙}{\mathrm{\epsilon }},T}={\left[\frac{\mathrm{\partial }\left(\mathrm{l}\mathrm{n}\mathrm{\sigma }\right)}{\mathrm{\partial }\left(\mathrm{l}\mathrm{n}\stackrel{˙}{\mathrm{\epsilon }}\right)}\right]}_{\stackrel{˙}{\mathrm{\epsilon }},T}=m$(4)

According to the irreversible thermodynamics, the relationship between flow stress and strain rate can be expressed as [22]: $\mathrm{l}\mathrm{g}\mathrm{\sigma }=a+b\mathrm{l}\mathrm{g}\stackrel{˙}{\mathrm{\epsilon }}+2c\left(\mathrm{l}\mathrm{g}\stackrel{˙}{\mathrm{\epsilon }}{\right)}^{2}+3d\left(\mathrm{l}\mathrm{g}\stackrel{˙}{\mathrm{\epsilon }}{\right)}^{3}$(5)

The m-value is evaluated as a function of strain rate and is written as [23]: $m=d\left(\mathrm{l}\mathrm{g}\mathrm{\sigma }\right)/d\left(\mathrm{l}\mathrm{g}\stackrel{˙}{\mathrm{\epsilon }}\right)=b+2c\mathrm{l}\mathrm{g}\stackrel{˙}{\mathrm{\epsilon }}+3d\left(\mathrm{l}\mathrm{g}\stackrel{˙}{\mathrm{\epsilon }}{\right)}^{2}$(6)

The m-values were calculated based on fitted cubic spines for $\mathrm{l}\mathrm{g}$σ versus $\mathrm{l}\mathrm{g}\stackrel{˙}{\mathrm{\epsilon }}$ (shown in Figure 5), and the results were given in Table 1. To investigate the effect of temperature and strain rate on m-value, the 3D response surfaces of m-value on strain rates and temperatures under different strains are constructed as shown in Figure 6. It can be seen that m-values vary violently with the variation of temperatures, strains and strain rates, which indicates that microscopic deformation mechanism has been changed greatly. From Table 1, it can be noticed that negative m-values appear under the following conditions: strain of 0.05–0.15, temperature of 773 K and strain rate of 10 s–1; strain of 0.05–0.15, temperature of 1,123 K, strain rate of 0.01 and 10 s–1; strain of 0.1, temperature of 1,223 K and strain rate of 0.1 s–1. According to Prasad, negative m-values are usually obtained under the conditions that promote dynamic strain aging (DSA), deformation twinning, shear band formation, or initiation and growth of microcracks [24, 25]. Moreover, according to phase-diagram, the main microstructure of this alloy varies with temperature: at the temperature of 773 and 873 K, the main microstructure is ferrite which has a lattice of bcc; at the temperature of 1,023 and 1,123 K, the main microstructures are austenite and ferrite, in addition, the percentage of austenite increases with the rising of temperature; at the temperature of 1,223 K, the main microstructure is austenite which has a lattice of fcc. It can be seen from Table 1, m-values at the temperature of 773 and 873 K where the main microstructure is ferrite which has a lattice of bcc are lower than those at the temperature of 1,023, 1,123 K where one of the main microstructures is austenite which has a lattice of fcc. Although the bcc and fcc lattice have the same amount of non-basal slip systems, the fcc lattice (4 slip planes and 3 slip directions) has more slip directions and the level of close-packed atoms is higher than that of bcc (6 slip planes and 2 slip directions), which contributes to increasing m-value. Besides, deformation twinning occurs easily at high strain rate and low temperature, which contributes to decreasing m-value [24]. In short, the coexistence and cooperation of slip and twinning result in the variation of m-value.

Figure 5:

The relationships between stress and strain rate in lg scale at different deforming temperatures and true strains (a) ε=0.05, 773–1,223 K, (b) ε=0.10, 773–1,223 K and (c) ε=0.15, 773–1,223 K.

Table 1:

m-value at different temperatures, strains and strain rates.

Figure 6:

The 3D response surface of m-value on strain rate and temperature under different strains: (a) ε=0.05, (b) ε=0.10, (c) ε=0.15.

## Power dissipation maps

The power dissipation map which is viewed as a counter map presents the variation of power dissipation efficiency with temperature and strain rate. According to eq. (2) and Table 1, the η-values were calculated and the dissipation maps of BR1500HS at the strain of 0.05, 0.10 and 0.15 were plotted as shown in Figure 7. The numbers to each counter in the dissipation maps are the η-values which characterize the microstructure evolution under different conditions.

Figure 7:

The power dissipation maps of ultra-high strength steel BR1500HS at different strain value: (a) ε=0.05, (b) ε=0.10, (c) ε=0.15.

It is well known that greater η-values mean that the performance of microstructure can be improved better. It can be seen from the dissipation maps that the η-values in low strain rate region are higher than those in high strain rate region which may lead DRV or DRX, and local flow instability [26]. Furthermore, some distinct features can be observed from the dissipation maps as well: (1) under the condition of low strain rate, the η-values increase with the rising of temperature and reach the peak value of about 0.3 at the temperature of 1,223 K, while the peak of η-value is about 0.4 at the temperature of 1,123 K and strain of 0.15 where the specimen has a necking tendency corresponding to the true strain–stress curve which reveals that the power dissipation efficiency is elevated and DRX is accelerated before necking occurs; (2) the η-value at the strain rate of 10 s–1 and temperature of 1,100 K decreases with the rising of strain, Wen et al. [27] believe that the main reason for this phenomenon is that the inhomogeneous recrystallized microstructures in the early high strain rate deformation stage lead to the flow localization in the vicinity of the joint between the homogeneous deformation zone and the rigid zone; (3) negative η-values appear at low temperature and high strain rate region, which means that flow instability occurs easier in this region because of relative low apparent activation energy which is discussed in Section 3.4.

## Instability maps

According to eq. (3), the flow instability occurs when the ξ ($\stackrel{˙}{\mathrm{\epsilon }}$) is negative. The variation of ξ ($\stackrel{˙}{\mathrm{\epsilon }}$) with temperatures and strain rates can constitute instability maps as shown in Figure 8. In the counter map, gray areas are flow instability regions and cyan areas are flow stability areas. It can be seen in Figure 8 that the flow instability region appears under the condition of low temperature with high strain rate and high temperature with high strain rate mainly.

Figure 8:

The instability maps of ultra-high strength steel BR1500HS at different strain value: (a) ε=0.05, (b) ε=0.10, (c) ε=0.15.

## Processing maps

Figure 9:

The processing maps of ultra-high strength steel BR1500HS at different strain value: (a) ε=0.05, (b) ε=0.10, (c) ε=0.15.

## Microstructure observations

In order to understand the impact of process parameters on the microstructure and validate the regions of stable and instable flow, the microstructure evolutions during hot deformation were characterized by optical microscopy. Figure 10 shows the optical microstructure at strain rate 0.01 s–1 under different deformation temperatures. From Figure 10 (a) and (b), it can be seen that the grains have not yet begun to refine because of relative low deformation temperature and low strain rate.

Figure 10:

Optical microstructure of ultra-high strength steel BR1500HS at strain rate 0.01s–1 under different deformation temperatures (tensile axis is vertical): (a) 773 K, (b) 873 K, (c) 1,023 K, (d) 1,123 K, (e) 1,223 K.

As shown in Figure 10(c), it can be observed obviously that the grains start to refine at the temperature of 1,023 K. Figure 10(d) and (e) show the microstructure at the temperature of 1,123 K and 1,223 K respectively, typical dynamic recrystallization microstructure can be observed. According to previews research [18], DRX may occur when the η-value range is between 0.3–0.5. As for Figure 10(e) corresponding to strain rate of 0.01 s–1, temperature of 1,123 K in DOM #3 in Figure 9(c) where η-value is about 40 %, amount of refined grains were generated as shown. Figure 11(a) shows the microstructure at strain rate of 1 s–1, temperature of 773 K where is corresponding to INST #1 in Figure 9(a), plenty of deformation twins can be observed. Figure 11(b) presents the microstructure at strain rate of 1 s–1, temperature of 873 K where is corresponding to INST #2 in Figure 9(c), a narrow and long crack can be observed in this area. It is commonly believed that deformation twinning occurs easily under high strain rate and relative low temperature. Amount of dislocations are generated under high strain rate while these dislocations disappear barely and form dislocation tangles and pile-ups at relative low temperature because of low dynamic recovery rate. These dislocation tangles become barriers of glide which may cause deformation twinning and dislocation pile-ups result in stress concentration which is the source of micro-crack.

Figure 11:

Optical microstructure of ultra-high strength steel BR1500HS at (tensile axis is vertical): (a) strain rate of 1 s–1, temperature of 773 K; (b) strain rate of 1 s–1, temperature of 873 K.

## Z parameter solving

The thermal activation process during the hot deformation of metal materials which is similar to high-temperature creep. Its deformation mechanism can be regarded as the extension of creep mechanism under different stress conditions. Thus the creep equation which contains deformation activation is used to describe the relationship between deformation conditions and flow stress [28]: $Z=\stackrel{˙}{\mathrm{\epsilon }}exp\left(Q/RT\right)$(7)

where Z is the Zener–Hollomon parameter, $\stackrel{˙}{\mathrm{\epsilon }}$ is the strain rate, R is the gas constant, T is the absolute temperature, Q is the activation energy for deformation.

Hot deformation process is mainly effected by deformation temperature, strain rate and the amount of deformation, among which, deformation temperature and strain rate are more remarkable factors. The relationship among deformation temperature, strain rate and the flow stress was commonly described by the following equations [29, 30]: $\stackrel{˙}{\mathrm{\epsilon }}exp\left(Q/RT\right)={A}_{1}{{\mathrm{\sigma }}_{p}}^{{n}_{1}}$(8) $\stackrel{˙}{\mathrm{\epsilon }}exp\left(Q/RT\right)={A}_{2}exp\left(\mathrm{\beta }{\mathrm{\sigma }}_{p}\right)$(9) $\stackrel{˙}{\mathrm{\epsilon }}exp\left(Q/RT\right)={A}_{}{\left[sinh\left(\mathrm{\alpha }{\mathrm{\sigma }}_{p}\right)\right]}^{n}$(10)

where σ is the steady-state stress value, A, A1, A2, α, β, n and n1 are constants who are independent of temperature.

It is well known that eq. (8) is fit for relatively low stress and eq. (9) is fit for the high. While eq. (10) is the developed hyperbolic-Sine Arrhenius equation which is suitable for wide range of deformation conditions [31, 32]. Calculating by linear regression of equations obtained by taking natural logarithm from each side of the eqs (8) and (9), the values of β and n1 were determined as 0.062956 MPa–1 and 9.16809 respectively. Then the value of α was calculated as 0.006878 MPa–1 by the expression of $\mathrm{\alpha }\approx \mathrm{\beta }/{n}_{1}$. The average activation energy can be calculated by the expression of Q=10,000 R K1 K2, where K1 and K2 are the average slopes of plots of ln $\stackrel{˙}{\mathrm{\epsilon }}$ versus ln(sinh(ασp)) and ln(sinh(ασp)) versus (10,000/T) respectively as shown in Figure 12 (a) and (b). The average values of K1 and K2 were determined as 6.60969 and 0.4537475 respectively so that the value of Q was calculated as 249.347 kJ/mol. The values of n and A were obtained as 6.413 and 7.7969×1011 s–1 respectively by linear regression analysis of lnZ versus ln(sinh(ασp)). As shown in Figure 12 (c), the plot shows a good linear correlation between peak stress and Z-value with regression coefficient of 0.987. As a result, substituting the values α, n, Q and A into eq. (7), Z parameter can be expressed as follow: $\begin{array}{rl}Z& =\stackrel{˙}{\mathrm{\epsilon }}exp\left(249347/RT\right)\\ & =7.7969×{10}^{11}×{\left[sinh\left(0.006878{\mathrm{\sigma }}_{p}\right)\right]}^{6.413}\end{array}$(11)

It should be noted that the Q-value above is the average apparent activation energy of the overall reaction. To help understand the effect of deformation temperature and strain rate on microstructure mechanisms, the apparent activation energy at different deformation temperatures and strain rates were calculated as shown in Table 2 by above method. It can be seen that the apparent activation energy values at higher temperature and lower strain rate region are higher than the self-diffusion activation energy in γ-Fe (279 kJ/mol) [33], which suggests that cross-slip of screw dislocation and climbing of edge dislocation may be the rate controlling process. The climbing of edge dislocation can form sub-grains or make the positive and negative ups and tangles. Then deformation twinning and micro-crack may occur with the rising level of dislocation pile-ups and tangles.

Figure 12:

(a) Plot of $ln\stackrel{˙}{\mathrm{\epsilon }}$ versus ln(sinh(ασp)) (b) plot of ln(sinh(ασp)) versus (10,000/T), (c) variation of the Zener–Hollomon parameter with flow stress.

Table 2:

The apparent activation energy at different deformation temperatures and strain rates (kJ/mol).

## Conclusions

Hot tensile testing of ultra-high strength steel BR1500HS has been conducted in the temperature range 773–1,223 K and the strain rate range 0.01–10 s–1. The processing maps for hot working were developed on the basis of isothermal tensile data and DMM, and the following conclusion are drawn from this investigation:

1. The processing maps were plotted by the superimposition of the power dissipation and the instability maps, deformation temperatures ranging from 1,200 K to 1,223 K and the strain rates ranging from 0.01 s–1 to 0.1 s–1 with a peak power dissipation efficiency of 37 % are considered as the optimum hot working conditions.

2. The deformation in the safe region was beneficial to DRV and DRX, while the deformation in unstable region would lead to deformation twinning and micro-crack.

3. The deformation activation energy of BR1500HS ultra-high steel is about 243 kJ/mol. The effect of deformation parameters (temperature and strain rate) on peak stress can be described by the following equations: $\begin{array}{rl}Z& =\stackrel{˙}{\mathrm{\epsilon }}exp\left(249347/RT\right)\\ & =7.7969×{10}^{11}×{\left[sinh\left(0.006878{\mathrm{\sigma }}_{p}\right)\right]}^{6.413}\end{array}$

Besides, to deeply understand the microstructure evolution mechanism, the apparent activation energy at different deformation temperatures and strain rates were determined.

## References

• [1]

J.Y. Min, J.P. Lin, J.Y. Li and W.H. Bao, Comp. Mater. Sci., 49 (2010) 326–332. Google Scholar

• [2]

H.S. Liu and C.X. Lei, Z.W. Xing, Int J. Adv. Manuf. Technol., 69 (2013) 211–223. Google Scholar

• [3]

N. Srinivasan, Y.V.R.K. Prasad and Rao P. Rama, Mater. Sci. Eng., A, 476 (2008) 146–156. Google Scholar

• [4]

Y.V.R.K. Prasad and K.P. Rao, Mater. Sci. Eng., A, 487 (2008) 316–327. Google Scholar

• [5]

Y.V.R.K. Prasad and K.P. Rao, Mater. Sci. Eng., A, 391 (2005) 141–150. Google Scholar

• [6]

G.Z. Quan, L. Zhao, T. Chen, Y. Wang, Y.P. Mao, W.Q. Lv and J. Zhou, Mater. Sci. Eng., A, 538 (2012) 364–373. Google Scholar

• [7]

G.Z. Quan, B.S. Kang, T.W. Ku and W.J. Song, Int J. Adv. Manuf. Technol., 56 (2011) 1069–1078. Google Scholar

• [8]

Y.V.R.K. Prasad, H.L. Gegel, S.M. Doraivelu, J.C. Malas, J.Y. Morgan, K.A. Lark and D.R. Barker, Metall. Mater. Trans. A, 15 (1983) 1883–1892.

• [9]

G.Z. Quan, Y. Wang, C.T. Yu and J. Zhou, Mater. Sci. Eng., A, 564 (2013) 46–56. Google Scholar

• [10]

Y.C. Lin, L.T. Li, Y.C. Xia and Y.Q. Jiang, J. Alloy. Compd., 550 (2013) 438–445. Google Scholar

• [11]

X. Shang, J. Zhou, X. Wang and Y. Luo, J. Alloy. Compd., 629 (2015) 155–161. Google Scholar

• [12]

H.Y. Sun, Y.D. Sun, R.Q. Zhang, M. Wang, R. Tang and Z.J. Zhou, Mater. Design, 67 (2015) 165–172. Google Scholar

• [13]

S.K. Oh, K.K. Lee, Y.S. Na, C.H. Suh, Y.C. Jung and Y.S. Kim, Int. J. Precis Eng. Manuf., 16 (2015) 1149–1156. Google Scholar

• [14]

Y.V.R.K. Prasad and T. Seshacharyulu, Int. Mater. Rev., 43 (1998) 243–258. Google Scholar

• [15]

Y.V.R.K. Prasad, K.P. Rao, N. Hort and K.U. Kainer, Mater. Sci. Eng. A, 502 (2009) 25–31. Google Scholar

• [16]

Y.V.R.K. Prasad, J. Mater. Sci. Technol., 22 (2013) 2867–2874. Google Scholar

• [17]

M. Merklein and J. Lechler, J. Mater. Process. Technol., 177 (2006) 452–455. Google Scholar

• [18]

G.Z. Quan, A. Mao, G.C. Luo, J.T. Liang, D.S. Wu and J. Zhou, Mater. Design, 52 (2013) 98–107. Google Scholar

• [19]

A. Momeni, K. Dehghani, H. Keshmiri and G.R. Ebrahimi, Mater. Sci. Eng. Am., 527 (2010) 1605–1611. Google Scholar

• [20]

Y.C. Lin, M.S. Chen and J. Zhong, Comp. Mater. Sci., 42 (2008) 470–477. Google Scholar

• [21]

G.Z. Quan, G.S. Li, T. Chen, Y.X. Wang, Y.W. Zhang and J. Zhou, Mater. Sci. Eng. A, 528 (2011) 4643–4651. Google Scholar

• [22]

J. Luo, L. Li and M.Q. Li, Mater. Sci. Eng. A, 606 (2014) 165–174. Google Scholar

• [23]

Z.N. Yang, F.C. Zhang, C.L. Zheng, M. Zhang, B. Lv and L. Qu, Mater. Design, 66 (2015) 258–266. Google Scholar

• [24]

G.Z. Quan, T.W. Ku, W.J. Song and B.S. Kang, Mater. Design, 32 (2011) 2462–2468. Google Scholar

• [25]

Y.V.R.K. Prasad, J. Mater. Eng. Perform., 22 (2003) 638–645. Google Scholar

• [26]

A. Momeni, K. Dehghani and G.R. Ebrahimi, J. Alloy. Compd., 509 (2011) 9387–9393. Google Scholar

• [27]

D.X. Wen, Y.C. Lin, H.B. Li, X.M. Chen, J. Deng and L.T. Li, Mater. Sci. Eng. A, 591 (2014) 183–192. Google Scholar

• [28]

V. Balasubrahmanyam and Y.V.R.K. Prasad, Mater. Sci. Eng. A, 336 (2002) 150–158. Google Scholar

• [29]

M. Ueki, S. Horie and T. Nakamura, Int. J. Adv. Manuf. Technol., 3 (1987) 329–337. Google Scholar

• [30]

S.F. Medina and C.A. Hernandez, Acta Mater., 44 (1996) 137–148. Google Scholar

• [31]

D.G. He, Y.C. Lin, M.S. Chen, J. Chen, D.X. Wen and X.M. Chen, J. Alloy. Compd., 649 (2015) 1075–1084 Google Scholar

• [32]

M. Zhou, Y.C. Lin, J. Deng and Y.Q. Jiang, Mater. Design., 59 (2014) 141–150. Google Scholar

• [33]

Z.Q. Cui and Y.C. Qin, Metallurgy and Heat Treatment, Harbin Institute of Technology: China Machine Press, (2007) 216–218. (in Chinese)

## About the article

Accepted: 2016-05-17

Published Online: 2016-09-24

Published in Print: 2017-07-26

This work was supported by the Fundamental Research Funds for the Central Universities (No. CDJZR13130082). The corresponding author was appreciated for Chongqing Higher School Youth-Backbone Teacher Support Program.

Citation Information: High Temperature Materials and Processes, Volume 36, Issue 7, Pages 657–667, ISSN (Online) 2191-0324, ISSN (Print) 0334-6455,

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© 2017 Walter de Gruyter GmbH, Berlin/Boston.

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