Influences of extrusion speed in hollow aluminium alloy profile extrusion.
Aluminium alloy profiles, especially hollow ones, are increasingly used in transportation, civil building, aerospace and other fields due to their high strength-to-weight, low mass-to-volume ratios and good corrosion resistance. Because aluminium profiles vary a lot in specification, and the work condition of extrusion die is severe due to large deformations and complex flow status of the extruded material, choice of die structure and process parameters are very important. Extrusion speed is one of the most important process parameters. Surface quality, micro-structure and mechanical property of the extrusion products, and production efficiency are affected by extrusion speed (Staley, Liu, and Hunt 1997; Xie and Liu 2001, Lou 2007; Wu et al. 2008). Large extrusion speed can ensure high production efficiency as it is well known to us. However, large speed value when using unchangeable (constant) speed can lead to a lot of negative influence, such as overheating of the extruded material, excessive ram load and extrusion die defect (Li, Zhou, and Duszczyk 2004; Wu et al. 2008). Li, Zhou, and Duszczyk (2004) investigated a variety of material temperature during extrusion process using finite element software. The results showed that extrusion speed has significant effect on the temperature distribution of material. Along with the increase in extrusion speed, the temperature uniformity of the material at the die outlet decreases, while the extrusion load increases. Wu, Zhao, and Sun (2007) analysed the die stress, extrusion temperature distribution and material flow using different extrusion speed and friction conditions. The results showed that friction factor has little effect on extrusion temperature, while the effect of extrusion speed is significant. The higher the extrusion speed, the faster the increase in temperature. They also concluded that die load is mainly influenced by friction factor, but little by extrusion speed. A different conclusion was obtained by Peng et al. (2007). From their perspective, extrusion load will increase at the initial stage of the extrusion, and then, it turns to decline because the plasticity of materials increases due to large deformation heat and the relevant temperature elevation. They found that die wear increases with the growth of extrusion speed. Since extrusion speed has significant effect on temperature, researchers make their attempts for isothermal extrusion by changing the extrusion speed. Bastani, Aukrust, and Brandal (2011) studied the influences of the extrusion speed, preheated billet temperature and the container's cooling rate, on temperature and material flow. According to the results, a process parameters rule was established to perform isothermal extrusions. In addition, Chanda, Zhou, and Duszczyk (2000) and Zhou, Li, and Duszczyk (2004) also realised isothermal extrusion processes by varying the extrusion speed. Hou et al. (2013) studied the effects of extrusion speed and billet temperature on maximum value of the inner temperature of the deformation material and the uniformity of the outlet temperature. The results showed that the extrusion speed has significant influence on temperature uniformity, but the influence of billet temperature is small. The reasonable range of temperature and speed was also defined. Zhang et al. (2010) investigated the effects of extrusion speed on material flow uniformity, extrusion load and welding quality during steady extrusion process using HyperXtrude software. They concluded that the extrudate's temperature, extrusion load and welding quality will be improved when the extrusion speed increases. Liu, Zhou, and Duszczyk (2008) carried out a finite element analysis for the extrusion of a magnesium square tube using porthole die and found that the average temperature and pressure on the welding plane will increase and the quality of the longitude welding could be enhanced with the growth of extrusion speed.
From above, it can be seen that extrusion speed value has large effects on product quality. Many researchers put their effort on it, but most of them focused on the effects of constant speed value. Little attention has been focused on the influence of different speed models on extrusion processes.
In this article, two kinds of speed models, constant and uniform deceleration speed model, were applied for three different mean speed values in the extrusion processes of a square hollow aluminium profile. The processes with six different speeds were simulated using the FEM software, DEFORM-3D. The influences of value and model of extrusion speed on extrusion process were studied.
2. Models and parameters
2.1. Geometry model
The hollow profile in this article is a rectangular tube. Figure 1 shows its cross-section. The extrusion die, which include an upper die and a lower one, is shown in Figure 2. The billet is a cylindrical bar with a diameter of 210 mm and a length of 70 mm. The extrusion ratio is 9.25.
2.2. Material properties
The material of extruded alloy and extrusion die are AA6063 and H13 tool steel, respectively. Mechanical properties of AA6063 aluminium alloy and H13 tool steel are listed in Table 1.
Hot extrusion process is performed above the re-crystallisation temperature. Strain has little influence on flow stress, while the influence of strain rate is significant. So the dynamic viscosity coefficient ([mu]) of hot extruded alloy can be expressed by the function of strain rate ([??]) and temperature (T). So Sellar-Tegart model (Equation 1) is chosen as the constitutive equation of the material (Sellars and Tegart 1972; Lou et al. 2008).
[sigma] = [1/[alpha]][sinh..sup.-1][[Z/A].sup.[1/n]][Pa] (1)
where [sigma] = Flow stress [Pa], [alpha] = Temperature-independent material parameters [[m.sup.2]/N], A = Temperature-independent material parameters [[s.sup.-1]], N = Temperature-independent material parameters [-] and Z = Zener-Hollomon parameters which can be defined by the equation below.
[mathematical expression not reproducible] (2)
where Q = Activation energy [J/mol], R = Gas constant [J/mol K] and T = Absolute temperature [K].
For AA6063 aluminium alloy, the values of these parameters are: [alpha] = 4.0E-8 [m.sup.2]/N, n = 5.39, A = 5.91E + 9 [s.sup.-1], Q = 1.42E + 5 J/mol, R = 8.31 J/mol K.
2.3. Process parameters
Initial temperatures of the billet and the die were 480 and 450 [degrees]C, respectively. Shear friction model was applied on the contact surface of the billet and the die. The friction coefficient was set to be 0.4. Since ordinary force plays a dominant role on the contact surface of the billet and the ram, the friction here is relatively low and the friction coefficient was set to be 0.1. These die structure and process parameters were set to be consistent for the six extrusion processes simulations by DEFORM-3D, except extrusion speed.
Six different extrusion speeds can be generated by matching three different mean speed values, 2, 4 and 10 mm/s, with two speed models, and they are respectively shown in Figure 3(a)-(c). Three extrusion speeds belong to the constant speed model, marked by [v.sub.1], [v.sub.2] and [v.sub.3] respectively. The other three belonging to the uniform deceleration model are marked by [v.sub.4], [v.sub.5] and [v.sub.6]. Variables, marked by [v.sub.0] and [v.sub.e], represent the initial and final value of the extrusion speed.
2.4. Numerical simulation model
The upper die, lower die, billet, container and ram were discretised by an absolute finite element meshing style. Because velocity gradient and effective strain rate at the bearing exit are very large due to sever deformation of the material, mesh refine windows are opened in this area for mesh refine based on the presupposed refinement ratio when the material flows into this area. Using this method, simulation efficiency can be improved without decreasing the simulation accuracy. The meshes before and after refinement are indicated in Figure 4. The simulation was carried out with a quarter of the billet and the die because of the symmetrical structure, which can save computer RAM source and computational time.
3. Results and discussion
The number of simulation steps was set to be 100 and the results were recorded every 5 steps. After the simulation, the influences of speed value, especially speed model, on the extrusion processes are discussed.
3.1. Effects of speed on temperatures
Temperature is an important variable for aluminium extrusion. So the influence of speed value and speed model on temperature in the extrusion was analysed in this part. Figure 5 shows the material temperature distribution when the stroke reaches 25, 30 and 40 mm, respectively. It can be seen that the maximum temperatures are always roughly located at the outlet. Outlet temperature uniformity has an important effect on the micro-structure of the profile. Uniform temperature can obtain homogeneous grain and then improve the profile's mechanical performance. Therefore, outlet temperature fluctuation should be limited (Laue and Stenger 1981; Liu, Sheng, and Wang 2010; Hou et al. 2013). In this article, influences of extrusion speed on outlet temperature uniformity are investigated. Twenty-eight monitoring points are selected on the extrudate's cross-section at the bearing exit. The location sketch map of these points is shown in Figure 6. Using the Variable State function of Deform-3D software, temperature values of these 28 points are recorded. The temperature distributions at different extrusion speeds are displayed by the curves as shown in Figure 7, which were drawn based on the date obtained from the monitoring points.
As shown in Figure 7, no matter what kind of speed model was used, outlet temperatures increase with with the increase in mean speed value. For all of these six different speeds, the maximum value of the temperature always appears near point 20. This point is located at the corner of the rectangle profile, behind the rear end of the bridge, where amount of heat is generated because of the severe deformation of the material at the weld plane. When the mean extrusion speeds are 2, 4 and 10 mm/s respectively, the difference in these maximum values between constant speed model and uniform deceleration are 6, 9 and 11 [degrees]C respectively. It indicates that, with the increase in mean speed, constant speed model can lead to more rapid increase in the outlet temperature than uniform deceleration model. Additionally, with the increase in mean speed value, fluctuation of the curve increases, which indicates that outlet temperature uniformity decreases. While if the value of the mean speed is the same, compared with the constant speed model, uniform deceleration model can make outlet temperature more uniform. And this trend is more and more obvious with the increase in mean speed. So the uniform deceleration speed model can efficiently decrease the possibility of over-burning the extruded material, which is alerted by Liu, Sheng, and Wang (2010) in their literature. This is because there is sufficient time for the energy to translate to the die due to the continuously decreasing speed. When the mean speed value is identical, the production efficiency will be equal using the two speed models. So, in short, uniform deceleration speed model can efficiently decrease the possibility of material overheating and make the outlet temperature more uniform without reducing the production efficiency.
Figure 8 shows the maximum temperature curves varied with stroke at the six different extrusion speeds. It can be seen that when the mean speed value increases , the maximum temperature increases rapidly. When the mean speed value decreases, the maximum temperature elevates more slowly. Furthermore, from Figure 8, it can be seen that, before the stroke reached 20 mm, the temperature changes are not so obvious whatever speed value or model were used. However, after that, the maximum temperature increases significantly. This is because the die temperature, when the stroke is less than 20 mm, is relatively low and deformation heat can translate quickly through the die due to the large temperature difference between the die and material. Then after the stroke reached 20 mm, the potholed material rejoins in the weld chamber and squeezes through the bearing, so that the material temperature increases rapidly. Meanwhile the die temperature has already gradually increased. Therefore, the loss rate of deformation heat begins to slow down. However, if uniform deceleration model is used, extrusion speed decreases gradually with the proceeding of the extrusion, so the deformation heat decreases gradually and has more time to transfer. Therefore, the increasing trend of maximum temperature can be slowed down.
Temperature uniformity at the outlet cross section decides the uniformity of grain size and profile performance in radial direction. The profile performance in the extrusion direction is significantly influenced by the temperature uniformity in the axial direction. So, the effects of extrusion speed on temperature uniformity in axial direction are investigated here. Figure 5 shows, when extrusion speed is 4 mm/s, the material temperature distribution when the stroke are 25, 30, and 40 mm, respectively. It can be seen that the highest temperatures are always located in roughly the same area at bearing exit, and this case also appears when other extrusion speeds are used. So, in Figure 8, those maximum temperature curves when the stroke is between 20 and 40 mm are developed by temperature values of the same area marked in Figure 5. These curve fluctuations represent temperature distribution uniformity of extrudate along extrusion direction. Through analysis of Figure 8, it can be known that when stroke is between 20 and 40 mm, the temperature change using uniform deceleration model is less than constant speed. Therefore, uniform deceleration extrusion is helpful for improving temperature distribution uniformity of extrudate along extrusion direction.
3.2. Effect of speed on loads
Ram load is another important parameter in aluminium profile extrusion processes. It is well known that the ram load is related to energy consumption during extrusion process. Energy consumption increases with the growth of the ram load. Besides, the die load, positively associated with ram load, relates to the die service life. With increase in the die load, some failures of the die such as crack and wear occur more easily. Because extrusion speed has significant influence on ram load and die load, the effects of speed on loads should be investigated. Ram load is mainly composed of two parts: one is to overcome deformation resistance of the material and the other to overcome various kinds of frictions. The deformation resistance is related to deformation rate and temperature. It increases with the growth of deformation rate, but, on the other hand, with the reduction of material temperature. If die structure is identical, deformation rate of the material will increase with the growth of extrusion speed. In this respect, increase in the extrusion speed will result in the growth of deformation resistance of the material. However, increase in the extrusion speed means more deformation heat, and then higher material temperature which will lead to the decrease in deformation resistance of the material. So, when the extrusion speed varies, the change trend of deformation resistance should be discussed. Figure 9 shows the comparison of stress distributions between two different speed models when the mean extrusion speed is 4 mm/s. Figure 9(a)-(c) show the stress distributions when using constant speed model, while Figure 9 (d)-(f) show the stress distributions when using uniform deceleration model.
In order to analyse the effect of extrusion speed on extrusion loads, we compare two factors impacted by extrusion speed, including material deformation rate and deformation heat, and stress (deformation resistance) between the two different models when the mean extrusion speed is 4 mm/s. The comparison results are listed in Table 2. To make Table 2 easier to be understand, the analysis when the stroke is 10 mm is taken as the example. The same analysis can be made when the stroke is 25 or 40 mm. Table 2 is divided into three columns with different grays as background. The first column is the effect of deformation rate on the material stress (deformation resistance). When the stroke is 10 mm, the speed value for constant model is smaller than that of uniform declaration model, which means the deformation rate in constant model is smaller. So, the material stress (deformation resistance) for constant model is smaller if the effect of deformation rate on stress is the only considered factor, and it is indicated by a down arrow in row 3, column 1. The middle column is the effect of deformation heat on the material stress (deformation resistance). When the stroke is 10 mm, the deformation rate for constant model is smaller than that of uniform declaration model, which means the deformation heat for constant model is smaller. So, the material stress (deformation resistance) for constant model is larger if the effect of deformation heat on stress is the only considered factor, and it is indicated by a upward arrow in row 3, column 2. The third column is the combined effect of deformation rate and deformation heat on the material stress (deformation resistance). The data in this column are based on the simulation results shown in Figure 9, because both deformation rate and deformation heat are considered in the calculation of simulation. From Figure 9(a), it can be observed that when the stroke is 10 mm, the stress using constant model is lower than using the uniform declaration model (not only the maximum value is concerned about). It means that deformation resistance is lower using constant speed model when both of the two factors are concerned. It is indicated by a down arrow in row 3, column 3.
From Table 2, the variation trends in stress (deformation resistance) are always consistent with the stress variations caused by deformation rate variations, but different from the stress variations caused by deformation heat variations. It indicates that, in extrusion process, the change in deformation rate caused by change of extrusion speed has a greater influence on material deformation resistance than the change in material temperature caused by the change in extrusion speed. So, with the growth of mean speed value, the extrusion load will increase.
Figures 10(a)-(c) show the ram and bottom die load with the stroke for the two speed models when the mean speeds are 2, 4 and 10 mm/s, respectively.
No matter what speed values or models are used, the trend of ram load is almost the same. It increases rapidly when the extruded material begins to enter into the portholes. Because, in this period, deformation rate increases rapidly, this leads to an increase in the deformation resistance of the extruded material. In addition, frictions between the material and die also increase because of the increased contact areas. The ram load is maintained at the porthole stage. And then it increases rapidly again when the stroke reaches around 20 mm, and reaches the peak value of the whole extrusion process. This is because, in this period, the material enters into welding chamber and flows through the bearing exit. The deformation resistance of the material rises rapidly again. In addition, the friction will increase due to the added contact areas between the material and the bottom die cavity or the bearing. This is also proved by the bottom die load which starts to increase and reaches the maximum value in this period. As can be seen from the Figure 10, when extrusion speeds are 2, 4 and 10 mm/s, respectively, the ram load stabilizes eventually at 1.78, 1.90 and 2.08 MN, which shows a gradual increasing trend. It indicates that ram load increases with the growth of mean speed value, which coincides with the analysis of Figure 9 and Table 2. The same trend is also presented for the lower die load. However, there are some differences between the ram loads using the two speed models. Before the stroke reaches 20 mm, the ram load for uniform deceleration model is slightly higher than constant model, while ram load curves of the two speed models are almost coincident when the stroke reaches about 20 mm. It can be explained that, at first part of the extrusion process, the mean value of uniform deceleration model is greater than that of the constant speed model. While in the middle of the extrusion process, the mean value of these two models is almost identical, so the load curves tend to coincide with each other. And then in the post stage of the extrusion process, the speed value of the uniform deceleration model start to be smaller and smaller than the constant speed model, which causes the deformation rate of the material and, as the result, the load decreases gradually. From above discussion, it is indicated that the uniform deceleration model is helpful to reduce the ram and bottom die loads, saving the energy consumption during extrusion process and prolonging the die service life.
(1) Extrusion speed has significant influence on the maximum value and uniformity of the material temperature. The maximum temperature increases with the growth of mean speed value. When using uniform deceleration model, outlet temperature is more uniform than using constant speed model. The difference in the maximum temperatures using the two different models increases with the growth of the mean speed value. The uniform deceleration speed model can efficiently decrease the overheating possibility of the material and make the outlet temperature more uniform without reducing production efficiency. When using uniform deceleration model in the extrusion process, extrudate temperature fluctuation along the extrusion direction is smaller. Therefore, uniform deceleration speed model is helpful to ensure temperature uniformity of the profile along extrusion direction and then to increase the uniformity of grain size and profile performance of the extrudate along the extrusion direction.
(2) In extrusion processes, change in speed value has a greater influence on ram load than that of the material temperature. Ram load increases with the growth of extrusion speed.
(3) In the latter period of extrusion process, both the ram and die load when using uniform deceleration model become smaller than using constant speed model. In addition, the differences increase with the growth of mean speed value. Therefore, using uniform deceleration model in extrusion processes is helpful for reducing energy consumption and extending die service life.
No potential conflict of interest was reported by the authors.
This work was financially supported by National Natural Science Foundation of China [grant number 51305241]; Shandong Provincial Natural Science Foundation, China [grant number ZR2014JL040]; the Science and Technology Project for the Universities of Shandong Province [grant number J12LA03], [grant number J12LB03].
Notes on contributors
Shumei Lou, born in 1979, received her PhD degree from Shandong University, China, in 2007. She is currently an associate professor at Department of Mechanical and Electrical Engineering, Shandong University of Science and Technology, China. Her scientific interests include metal material processing technology, numerical simulation of plastic forming process, etc.
Yongxiao Wang, born in 1990, received his MS degree from Shandong University of Science and Technology, China, in 2016. He is now studying for a PhD at Shandong University. His current principal research activities are plastic deformation mechanism of Al-Li alloy at elevated temperature and extrusion technology of Al-Li alloy profile.
Shengxue Qin, born in 1978, is currently an associate professor at Department of Mechanical and Electrical Engineering, Shandong University of Science and Technology, China. He received his PhD degree from Shandong University, China, in 2006. His research interests are numerical simulation technology of material forming process, die design and optimisation, spinning forming process technology and equipment.
Guoliang Xing, received his MS degree at Department of Mechanical and Electrical Engineering, Shandong University of Science and Technology, China. He is currently a mechanical engineer in KERUI Co., Ltd. His research interest is aluminium profile extrusion processes and mechanical design.
Chunjian Su, born in 1980, is currently an associate professor at Department of Mechanical and Electrical Engineering, Shandong University of Science and Technology, China. He received his PhD degree from Yanshan University, China, in 2007. His research interests are material precision moulding technology and stamping die design and manufacturing.
Bastani, A. F., T. Aukrust, and S. Brandal. 2011. "Optimisation of Flow Balance and Isothermal Extrusion of Aluminium Using Finite-element Simulations." Journal of Materials Processing Technology 211 (4): 650-667.
Chanda, T., J. Zhou, and J. Duszczyk. 2000. "FEM Analysis of Aluminium Extrusion through Square and Round Dies." Materials and Design 21 (4): 323-335.
Hou, W. R., Z. H. Zhang, J. X. Xie, and Y. B. Chen. 2013. "Numerical Simulation of Temperature Field during Whole Extrusion Process of Aluminum Hollow Profile with Porthole Die Extrusion Forming." The Chinese Journal of Nonferrous Metals 23 (10): 2769-2778.
Laue, K., and H. Stenger. 1981. Extrusion:Processes, Machinery, Tooling. 2nd ed. Metals Park OH: American Society for Metals.
Li, L., J. Zhou, and J. Duszczyk. 2004. "Prediction of Temperature Evolution during the Extrusion of 7075 Aluminium Alloy at Various Ram Speeds by Means of 3D FEM Simulation." Journal of Materials Processing Technology 145 (3): 360-370.
Lou, S. M. 2007. Research on the Aluminum Alloy Profile Extrusion by Using Finite Volume Method. Jinan: Shandong University.
Liu, G., J. Zhou, and J. Duszczyk. 2008. "FE Analysis of Metal Flow and Weld Seam Formation in a Porthole Die during the Extrusion of a Magnesium Alloy into a Square Tube and the Effect of Ram Speed on Weld Strength." Journal of Materials Processing Technology 200: 185-198.
Lou, S. M., G. Q. Zhao, R. Wang, and X. H. Wu. 2008. "Numerical Simulation of Steady and Unsteady Aluminum Profile Extrusion Processes using Finite Volume Method." Engineering Computations 25 (6): 589-605.
Liu, J. A., C. L. Sheng, and W. Q. Wang. 2010. "Online Quenching Technology of Aluminum Alloy Extrusion." Light Alloy Fabrication Technology 38 (2): 7-15.
Peng, B. Y., G. F. Yin, J. Fu, and P. Cai. 2007. "Effect of Extrusion Velocity to Wear Degree of Aluminum Profile." The Chinese Journal of Nonferrous Metals 17 (9): 1453-1459.
Sellars, C. M., and W. J. M. Tegart. 1972. "Hot Workability" International Materials Reviews 17: 1-24.
Staley, J. T., J. Liu, and W. H. Hunt. 1997. "Aluminum Alloys for Aerostructures" Advanced Materials & Processes 152 (4): 17-20.
Wu, X. H., G. Q. Zhao, and S. Sun. 2007. "The Influence of Extrusion Speed and Frictional Status on Aluminum Profile Extrusion Processes" Journal of System Simulation 14 (1): 36-41.
Wu, X. H., G. Q. Zhao, S. M. Lou, S. Q. Li, and X. W. Ma. 2008. "FVM Study on Regular Section Profile Extrusion with Changing Speed." Journal of System Simulation 3: 791-794.
Xie, J. X., and J. A. Liu. 2001. Theory and Technology of Metals Extrusion. Beijing: Metallurgical Industry Press.
Zhou, J., L. Li, and J. Duszczyk. 2004. "Computer Simulated and Experimentally Verified Isothermal Extrusion of 7075 Aluminium through Continuous Ram Speed Variation." Journal of Materials Processing Technology 146 (2): 203-212.
Zhang, C. S., G. Q. Zhao, Z. Chen, H. Chen, and F. J. Kou. 2010. "Effect of Extrusion Stem Speed on Extrusion Process for a Hollow Aluminum Profile." Materials Science and Engineering: B 177 (19): 1691-1697.
Shumei Lou, Yongxiao Wang, Shengxue Qin, Guoliang Xing and Chunjian Su
Department of Mechanical and Electrical Engineering, Shandong University of Science and Technology, Qingdao, P.R. China
CONTACT Shumei Lou firstname.lastname@example.org
Received 22 August 2015
Accepted 13 October 2016
Table 1. Mechanical properties of AA6063 and H13. Specific Young's Poisson's Density Heat Conductivity Material Modulus Ratio (kg/[m.sup.3]) (J/kg*K) (W/m*K) AA6063 6.3E + 10 0.25 2695 990 209 H13 2.1E + 11 0.35 7870 460 24.3 Table 2. Comparisons about extrusion speed, material temperature and stress between two different models. Deformation rate Deformation heat Effect on Stroke (mm) Value comparison stress Value comparison 10 Const. Model < Uni. [down arrow] Const. Model < Uni. 25 = Dec. - = Dec. 40 > Model [up arrow] > model Deformation heat Stress (Deformation resistance) Effect on Stroke (mm) stress Value comparison Results 10 [up arrow] Const. Model < Uni. [down arrow] 25 - = Dec. - 40 [down arrow] > Model [up arrow]
|Printer friendly Cite/link Email Feedback|
|Author:||Lou, Shumei; Wang, Yongxiao; Qin, Shengxue; Xing, Guoliang; Su, Chunjian|
|Publication:||Australian Journal of Mechanical Engineering|
|Date:||Mar 1, 2018|
|Previous Article:||Australian Journal of Mechanical Engineering.|
|Next Article:||Acoustic emission analysis for characterisation of damage mechanisms in glass fiber reinforced polyester composite.|