International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012) Simulation of Peak Temperature & Flow Stresses during Friction Stir Welding of AA7050-T7451 Aluminium Alloy Using Hyperworks K.D.Bhatt1, Bindu Pillai2 2 M.Tech.PG student, CIT, Changa, Affiliated to CHARUSAT, Changa Assistant Professor, Mechanical Engineering Department, CIT, Changa 2 1
[email protected] [email protected] 1 Abstract— To overcome limitations of fusion welding of the AA7050-T7451aluminum alloy friction stir welding (FSW) has become a prominent process which uses a non-consumable FSW tool to weld the two abutting plates of the workpiece. The FSW produces a joint with advantages of high joint strength, lower distortion and absence of metallurgical defects. Process parameters such as tool rotational speed, tool traverse speed and axial force and tool dimensions play an important role in obtaining a specific temperature distribution and subsequent flow stresses within the material being welded. Friction stir welding of AA7050-T7451 aluminum alloy has been simulated to obtain the temperature profiles & flow stresses using a recent FEA software called HyperWorks.; the former controlling the microstruture and in turn, mechanical properties and later, the flow of material which depends up on the peak temperatures obtained during FSW. A software based study has been carried out to avoid the difficulty in measuring the temperatures directly and explore the capabilities of the same to provide a basis for further research work related to the said aluminum alloy. Keywords: AA7050 Aluminum alloy, Flow stresses, Friction stir welding, Peak temperature, Simulation. Thus, it is a solid-state joining technique in which no melting of workpiece occurs and the required heat to join two plates is produced by the tool in two fold: (i) friction between tool shoulder & the workpiece-surface and (ii) heavy plastic deformation of the workpieces. Thus, during the FSW, fine equiaxed recrystallized grains result as the material undergoes tremendous plastic deformation at very high temperature [3-6]. The fine microstructure obtained by FSW process produces remarkable mechanical properties in welds. The joint is eventually produced as a result of material movement around the pin which is found to be very complex due to geometrical features of the tool [7]. I. INTRODUCTION Friction stir welding (FSW) was originally invented & developed by The Welding Institute (TWI) at UK in 1991 by using Aluminum alloy [1-2]. The FSW involves the use of a specially designed tool having a shoulder and a protruded pin with a specific geometry. The tool, being non-consumable, is rotated at certain rotational speed (rpm) and plunged into the abutting edges of the two plates to be welded. After the due rotations at the joining line (given time being called as ‘dwell time’), the tool is traversed along this line with a certain welding speed (mm/min) till the end of the plates (Figure - 1). 212 Figure – 1 Schematic of Friction Stir Welding [8] The Aluminum alloys from 7XXX series are from the nonweldable class of material having poor solidified microstructure and porosity in the fusion zone. Also, there is significant loss of mechanical properties during fusion welding as compared to their base metals. Both these factors lead to difficulty in joining these alloys by the conventional methods of welding [8]. International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012) As the FSW results in tremendous plastic deformation around the tool and friction between tool and workpiece, the temperature rise and its distribution in the weld zones become responsible for establishing the microstructure of the weld that includes grain size, grain boundary character, coarsening and dissolution of precipitates and resulting mechanical properties of the welds. It is, therefore, necessary to obtain information regarding temperature distribution during FSW. Of course, the direct measurements of temperatures within the stirred zone are quite difficult because of tremendous plastic deformation taking place during FSW due to rotation and translation of the tool along the weld center-line. Despite, the attempts have been made to estimate the maximum temperatures within the stirred zone from the microstructure of the weld [3, 4, 9] or record the same by embedding thermocouples in the region nearer to rotating pin [ 10, 11-13]. Rhodes et al. [3] investigated for microstructural evolution in AA7075-T651 during FSW that larger precipitates dissolve and reprecipitate in the weld center. Therefore, they concluded that maximum process temperatures are between about 400 to 4800C in the AA7075-T651. Murr and coworkers [4, 9] indicated the non-dissolution of some of the precipitates and suggested a temperature rise roughly to 400 0C for AA6061 alloy during FSW. A study of microstructural evolution of AA6063 during FSW was done using transmission electron microscopy (TEM) by Sato et al. [11] and by comparison of these with those obtained by simulated thermal cycles at different peak temperatures they concluded that in the regions of 0 to 8.5, 10.0, 12.5 and 15.0 mm away form weld center, the temperatures were higher than 402, 353, 3020C and lower than 2010C respectively. Tang et al. [12] made an attempt to measure heat input and temperature distribution within friction stir weld by embedding thermocouples in the region to be welded for AA6061-T6 Aluminum alloy having thickness of 6.4 mm. They concluded that (i) Maximum peak temperature was recorded at the weld center and it decreased with increasing distance from the weld centre-line. (ii) At tool rotation speed of 400 rpm and a traverse speed of 122 mm/min, a peak temperature of 4500C was observed at the weld center one quarter from top surface. (iii) The temperature distribution within stirred zone is relatively uniform. Tang et al. [12] investigated further that increasing both tool rotation rate and weld pressure result in an increase in the weld 213 temperature. Further, they [12] studied the effect of shoulder on the temperature field and concluded that contact area & vertical pressure between shoulder and workpiece are much larger than those between the pin and the workpiece, also, shoulder has higher linear velocity compared to small radiused pin. Hashimoto et al. [14] reported that the peak temperature in the weld zone increase with increasing the ratio of tool rotation rate to traverse speed for FSW of AA2024-T6, AA5083-O and AA7075-T6. A peak temperature of > 5500C was reported in FSW of AA5083-O at a higher ratio of tool rotation/traverse speed. Frigaad et al. [15] suggested that the tool rotation rate and the shoulder radius are the main process variables in FSW, and pressure P can not exceed the actual flow stress of the material at the operating temperature if a sound weld without depressions is to be produced. They performed FSW of AA 6082-T6 and AA7108-T79 at constant tool rotation rate of 1500 rpm and a constant welding force of 7 kN at three welding speeds of 300, 480 and 720 mm/min. They [15] revealed that (i) peak temperature of above ~5000C was recorded in the FSW zone, (ii) peak temperature decreased with increasing traverse speeds from 300 to 720 mm/min. For a three dimensional thermal model based on finite element analysis developed by Chao and Qi [16] and Khandkar & Khan [17] showed reasonably good match between the simulated temperature profiles and experimental data for both butt and overlap FSW process. The effect of FSW parameter on temperature was further examined by Arbegast and Hartley [18]. They concluded that for a given tool geometry and depth of penetration, the maximum temperature was a strong function of the rotation rate (rpm) while rate of heating was a strong function of the traverse speed (mm/min). The maximum temperature observed during FSW of various Aluminum alloys is found to be between 0.6Tm and 0.9Tm which is within the hot working range for those Aluminum alloys, where Tm is melting point of material. Ulysee [19] studied the impact of varying weld parameters on temperature distribution in AA7050-T7451 plate. Khandkar et al. [20] introduced a more comprehensive model of heat input based on the torque of the FSW tool that they used to model temperature history of friction stir welded Aluminum alloy AA6061-T651 plate. The prime objective of the present paper is to simulate peak temperature and distribution of flow stresses produced during the FSW of AA7050-T7451 Aluminum alloy and to compare the same International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012) with those of the researchers’ results. Use of a recent software known as HyperWorks9.0 has been explored in the modeling FSW process. It basically includes a specially designed module for friction stir welding for modeling. II. EXPERIMENTAL WORK Simulations were performed by entering following properties of the AA7050-T7451 Aluminum alloy as shown in table – 1. The default tool material available in HyperWorks9.0 database was used for simulating the FSW using properties as shown in table – 2. Table - 1: Physical & Thermal properties of AA7050-T7451 The dimensions of plates of AA7050 alloy were selected as 381 x 127.5 x 6.4 mm and FSW tool geometry was selected with cylindrical pin having a shoulder diameter (D), shoulder length (L), pin diameter (d), and pin length (l) as shown in table – 3 below: Table - 3: Dimensions of Default tool Element D, mm Tool 20.3 L, mm d, mm l, mm 5.76 70.2 7.1 Density Melting Point Modulus of Elasticity Poisons Ratio Thermal Conductivity Specific Heat Volumetric heat source 2830 kg/m 3 488 - 629°C 7.17 x 1010 Pa 0.33 155 W/m-K 860 J/kg-K 0.0 W/m3 Table – 4 indicates the FSW process parameters as tool rotational speed (RS, rpm) and welding speed (WS, mm/min) and tool tilt angle selected for the simulation in HyperWorks9.0: Table - 4: FSW parameters Sr. No. RS, rpm 1 2 180 180 WS, mm/min 51.0 76.2 Tool tilt angle 2.50 2.50 III. RESULTS & DISCUSSIONS The graphical results showing temperatures and flow stress distributions obtained by running the simulations on HyperWorks9.0 indicate the effects of varying welding parameters particularly welding speed (WS). At the constant value of 180 rpm (RS), the peak temperatures obtained at two values of welding speeds of 51.0 mm/min and 76.2 mm/min differ only by 100C from the value indicated in literature. Figure – 2(a) and - 2(b) shows peak temperature values of 3400C and 3600C for the said alloy at tow welding speeds of 51.0 mm/min and 76.2 mm/min respectively. The peak temperatures are found as maximum at the tool pin center. Table - 2: Physical & Thermal properties of Default tool Density Specific Heat Modulus of Elasticity Poisons Ratio X – conductivity Y – conductivity Z – conductivity 2260 kg/m3 896 J/kg-K 2.0 x 1010 Pa 0.35 198 W/m-K 198 W/m-K 198 W/m-K 214 International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012) 2(a) At RS = 180 rpm, WS = 51.0 mm/min 3(b) At RS = 180 rpm, WS = 76.2 mm/min Figure – 3: Flow Stress Distributions at RS & WS shown at (a) & (b). IV. CONCLUSION It can be concluded that at constant tool rotational speed (RS) and tool with the same geometry; variation in tool traverse speed has prominent effects on temperature history & flow stresses developed during FSW of AA7050-T7451 Aluminum alloy. The induced temperatures and flow stresses are in good confirmation with the results obtained in literatures. The flow stresses at lower peak temperature of 3400C are as high as 720 MPa but are as low as 680 MPa at higher peak temperature of 3600C as the flow of material becomes easier at higher temperatures. It is also observed that at constant rotational speed the peak temperature has increased by increasing the welding speed. These temperature profiles govern viscosity at and ahead of the tool which affects the flow of material and thus, contribute in establishing a microstructure which in turn dictates the mechanical properties of the joint produced. Simulations performed on computer software opens the new horizon of modeling friction stir welding process in virtual laboratory and help predict the mechanical properties of FSW-joints. REFERENCES [1] Thomas W.M., Nicholas E.D., Needham J.C., Murch M.G., Temples mith P., C.J. and Dawes, G.B. 1991. Patent Application No. 9125978.8. [2] Dawes C. and Thomas W., November/December 1995.TWI Bulletin 6, p. 124. [3] Rhodes C.G., Mahoney M.W., Bingel W.H., Spurling R.A. and Bampton C.C. Scripta Mater. 36 (1997) 69. [4] Liu G., Murr L.E., Niou C.S., McClure J.C. and Vega F.R. Scripta Mater. 37 (1997) 355. [5] Jata K.V. and Semiatin S.L. Scripta Mater. 43 (2000) 743. 2(b) At RS = 180 rpm, WS = 76.2 mm/min Figure –2: Temperature Distributions at RS & WS shown at (a) & (b) 3(a) At RS = 180 rpm, WS = 51.0 mm/min Also, the flow stress distribution is shown in figure – 3(a) and – 3(b) for the same parameters selection. The results show that at constant RS = 180 rpm the flow stresses are lower for WS = 51.0 mm/min as compared to those at WS = 76.2 mm/min. 215 International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012) [6] Benavides S., Li Y., Murr L.E., Brown D. and McClure J.C. Scripta Mater. 41 (1999) 809. [7] London B., Mahoney M., Bingel B., Calabrese M., and Waldron D. 27– 28 September, 2001. In: Proceedings of the Third International Symposium on Friction Stir Welding, Kobe, Japan. [8] Mishra R.S. and Ma Z.Y. 2005. Friction stir welding and Processing, Reports: A Review Journal. doi: 10.1016/j.mser.2005.07.001. [9] Murr L.E., Liu G. and McClure J.C. J. Mater. Sci. 33 (1998) 1243. [10] Mahoney M.W., Rhodes C.G., Flintoff J.G., Spurling R.A. and Bingel W.H. Metall. Mater. Trans. A29 (1998) 1955. [11] Sato Y.S., Kokawa H., Enmoto M. and Jogan S. Metall. Mater. Trans. A30(1999) 2429. [12] Tang W., Guo X., McClure J.C. and Murr L.E. J. Mater. Process. Manufact. Sci. 7 (1998) 163. [13] Kwon Y.J., Saito N. and Shigematsu I. J. Mater. Sci. Lett. 21 (2002) 1473. [14] Hashimoto T., Jyogan S., Nakata K., Kim Y.G. and Ushio M. June 14–16,1999. In: Proceedings of the First International Symposium on Friction Stir Welding, Thousand Oaks, CA, USA. [15] Frigaad O., Grong O. and Midling O.T., Metall. Mater. Trans. A 32 (2001) 1189. [16] Chao Y.J. and Qi X. J. Mater. Process. Manufact. 7 (1998) 215. [17] Khandkar M.Z.H. and Khan J.A. 10(2001)91 J. Mater. Process. Manufact. [18] Arbegast W.J. and Hartley P.J. June 1–5, 1998, p. 541. In: Proceedings of the Fifth International Conference on Trends in Welding Research, Pine Mountain, GA, USA. [19] P. Ulysee, Three-dimensional modeling of the friction stir-welding process, International Journal of Machine Tools and Manufacture 42 (2002) 1549–1557. [20] Khandkar M.Z.H., Khan J.A. and Reynolds A.P. Predictions of temperature distribution and thermal history during friction stir welding: input torque based model, Science and Technology of Welding and Joining 8 (3) (2003) 165–174. 216