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Peak Temperature correlation and Temperature Distribution during joining of AZ80A Mg Alloy by FSW – A Numerical and Experimental Investigation

A quadratic equation has been developed based on experimental measurements to estimate the peak temperature in the FSW process during the joining of AZ80A Mg alloys. The numerical simulation of the FSW process was performed by employing COMSOL software to predict & calculate the distribution of temperature on the various regions of the parent metal and the welded joints. The predicted and FEA simulated results of the distribution of peak temperatures were found to be consistent with the experimental values. In addition to this, a parametric experimental investigation was conducted to identify the most influential process parameter which plays a significant role in the peak temperature distribution during FSW of AZ80A Mg alloy. Linear contributions by the input process parameters of FSW namely, traversing speed, rotating tool speed & axial force on the peak temperature were observed to be 32.82%, 23.58% and 21.76% respectively.


INTRODUCTION
Being one of the earth's lightest metal alloy, Mg alloys are widely preferred for a variety of applications, in particular for aerospace, structural, automotive, electronics and ship building sectors [1,2]. The promising characteristic features of Mg alloys, especially, AZ80A Mg alloy including tremendous strength to weight proportion, exceptional machinability, outstanding sound-absorbing potential, uncomplicated recyclability, exquisite machinability have attracted & gained the attraction of numerous researchers, in the past few decades [3,4]. Concurrently, joining of magnesium alloys is a tough task, especially when carried out by employing conventional joining processes. This is mainly due to their lofty thermal potential characteristic, which leads to undesirable features like scatological microstructure, porosity, relentless fracture, soaring residual stress etc. in the joints obtained by employing conventional techniques [5,6].
A solid-state category of joining process like friction stir welding (FSW) will be effective in eliminating those various defects associated with the employment of conventional welding processes employed for joining of AZ80A Mg alloys [7]. During the process of FSW, a uniquely designed tool with shoulder and pin arrangement is plunged (at a desirable rotating speed) exactly at the center of the joining butt edges of the two similar or dissimilar plates to be joined and will be made to traverse continuously along the line of fabrication, as illustrated in the Fig.1. During this joining process, heat is generated due to the friction between the tool shoulder surface and the work piece surface. Due to this generated frictional heat, the material of the flat plates (kept for joining) gets softened and reaches the plasticized state. The flow of these softened plasticized materials to the other side occurs due to the stirring action of the tool pin and exhilarating impact of traversing tool shoulder. As a result, mixing of the plasticized materials happens on both sides of the line of joint, while the tool traverses along this joint line and thereby leading to the formation of a joint, without melting the base metals. The employed tool is then retarded gradually from the line of joint, then the work pieces are allowed to get cooled down and thus, a solid phase of bonding is attained between the work pieces [10,11].
Temperature generation & its distribution over the various regions during the FSW process have an invigorating impact on the microstructural features and mechanical features of the fabricated weldments [12]. For example, a flow segregated deformation model was proposed by Arbegast [13] to depict the circumstances during which the formation of volumetric defects will occur during the joining of metals by FSW process. It was observed that, the disproportionate flow of plasticized material arising due to generation of high FSW processing temperature will result in the formation of flash, collapse of stir zone etc. Padmanaban et.al [14] devised an analytical procedure to anticipate the generation & distribution of temperature and flow of the plasticized metal during FSW of AA7075 and AA2024 Al alloys. It was recorded that, the level of temperature escalates with the rise in the speed of rotation of that cylindrical tool and with the increase in the diameter of that cylindrical tool's shoulder.
A 3-D based model for the transfer of heat during the process of FSW was put forward by Song et al [15]. The equations of control were solved using the methodology of finite difference and an intermittent mesh of the grid was brought out to calculate the temperature levels. Chao et.al [16] devised the transfer of heat taking place during the FSW process into a constant state horizon value based scenario and calculated the temperature levels on the FSW tool and workpiece. This analysis recorded that, nearly 90-94% of the generated heat gets transfers to the workpiece and remaining heat stays with the tool.
Even though, there exists an essential need for deriving out & implementing suitable strategies for control of temperature, to fabricate sound, high quality, defect free weldments, there is no consistent conclusion on the relationship between the welding parameters with the peak temperature. In this study, the domination and significance of several parameters of FSW process on peak temperature during joining of AZ80A alloy was investigated experimentally and numerically. Tmax correlation for AZ80A magnesium alloy was developed, for the first time, to accurately predict the peak temperature in the FSW process using Minitab tool. The distribution of temperature on the various regions of the workpiece (AZ80A Mg alloy) was simulated by a steady-state heat transfer numerical approach using Comsol software. The predicted and FEA simulated peak temperatures were validated against experimental temperature measurements. Finally, a numerical parametric study was conducted taking into consideration the various parameters namely welding speed, axial load and rotational tool speed to identify the most influential parameter which affects the peak temperature in the FSW process. The joining (butt joint) of the flat plates (thickness -5mm) of parent metal (AZ80A Mg) was carried out by using a congenitally contrived, pseudo automatic nature of FSW machine, enclosed with a motor spindle of 5kW capacity, together with a 400 X 810 mm table, which can traverse in 3 different axes at a dimension of 510 mm (Longitudinally), 400 mm (horizontally & vertically).
FSW tool employed in this experimental work was fabricated using the M35 grade high speed steel and it has a cylindrical shaped stepped shoulder (outer shoulder diameter of 20 mm & 15 mm diameter inner shoulder), along with a tapered pin profile (4.75 mm length). The photographic illustration of the different views of the tool used in this experimental & numerical investigation is shown in the Fig.1. Thermocouples made of Al-Cr wire were used to measure the workpiece temperature during this joining of AZ80A Mg alloy by the employment of FSW process.

Experimental Design Scheme
The impact of the several parameters on the peak temperature (Tmax) during the joining of AZ80A Mg alloy flat plates employing FSW process was analyzed by the adoption of three factor & three level investigational design (full factorial based) concept. The details of these influential parameters together with their coded (F axial force; Fd -tool's speed of traverse and Stool's rotational speed) and corresponding realistic investigational values are elaborated in Table 1. A 2 nd ordered equation of polynomial nature was employed to fit the results of the investigational work. The proposed equation interprets the impact & role of the above mentioned influential parameters and their interplay on the response variable (namely peak temperature). The generalized structure of the developed model is described as shown below: where the anticipated response is indicated by T, Model constant by K0, linear Coefficients by K2, K1, K3, cross product coefficients by K13, K12, K23, quadratic coefficients byK22, K11, K33. The effectiveness of the model was analyzed using the Minitab Software and by the employment of the ANOVA (analysis of variance).

FEA modeling of the FSW process
It is evident that, differential equation based issues can be tackled by approximating the issue using a numerical strategy [17,18]. In this experimental investigation, the proposed analytical model for joining AZ80A Mg alloy employing an FSW tool (having a stepped cylindrical shoulder and tapered pin geometry) was formulated by applying the Comsol Multiphysics heat transfer segment. Statistical modeling is the partition & segregation of a geometrical region into limited cardinal points and rudimental volumes [19,20]. In this proposed model, a precise estimation of the administering horizon conditions influencing every network point and their adjoining points were also specified. Results were also derived for these structure of equations, culminating from the above mentioned approximations. It can be visualized that, the geometrical domain is symmetrical about the weld line. Hence, it is acceptable to model & conceptualize any of the flat plates of the base metal during their FSW. The dimension of the AZ80A Mg alloy flat plates welded in this experimental work is 50 mm (width) X 100 mm (length). The flat plates of the parent metal (AZ80A Mg alloy) were attached with two perpetual dominions along the X direction. The obtained computational domain through FEA analysis for the base material on our investigational work, namely, AZ80A Mg alloy is graphically illustrated in Fig.3.

Governing equations and numerical scheme
Usually, during friction stir welding, the travel of the FSW tool will be forth the line of the joint of the weld. The proposed models by various researchers were proven to have some complications, as they have considered the FSW tool as a movable source of heat [21,22]. But, in this experimental work, a lateral concept of the system of movable coordinates was employed and the coordinates were fixed at the axis of the FSW tool. Due to this transfiguration of coordinates, the problem of transfer of heat gets converted into static conductionconvection scenario, which is unequivocal to the proposed model. Moreover, this strategy of considering a movable type coordinate in this proposed model eliminates the need for modeling the processes taking place around the region of the FSW tool pin, thereby making this proposed model simplified & effective.
The equation representing the amount of transfer of heat taking place on the parent metal of our experimental investigation (namely AZ80A Mg alloy) in a movable type coordinate is, ρCpμ. T + .(-k T) = Q (2)

Fig. 3. Graphical illustration of the generated model geometry for FSW simulation
where the temperature being generated is indicated by T, the capacity of heat by Cp, the density being indicated by ρ, the conductivity of heat by K, and the travelling speed of tool by μ.
Likewise, the equation which governs the generation of heat in the region of interaction of the shoulder of the FSW tool and the parent metal is as follows: (3) where the generation of heat in the shoulder of the FSW tool is indicated by Qshou, ω represents the angular rotational speed of the FSW tool, contact shear stress by τcon, the radius of the FSW tool shoulder being indicated by Rshou and Rpin,max represents the maximum radius of the profile of tool pin.
The probe of the employed tool consists of a taper cylindrical surface with a bottom radius of Rpin,min, top radius Rpin,max and probe height Hpin. The heat generation equation for the profile of FSW tool pin is, where Qpin indicates the amount of generated heat in the pin of the tool, the height of tool pin being indicated by Hpin and Rpin,min represents the maximum radius of the profile of tool pin.
The top most and bottom portions of the parent metal, will experience some heat loss and this happens mainly due to surface to circling radiation, convection etc. The interrelated equations defining the flux of heat of these regions are mentioned below:  ) is represented as TO, the surface temperature of base metal flat plates by T in Kelvin, surface emissivity by ε, the Stefan-Boltzmann constant by σ, ambient temperature of air (in Kelvin) by Tamb and the transfer of heat coefficients of natural convection are indicated by hdown and hup. In this investigational analysis, the transfer of heat coefficients for top side was considered to be 6.25 and 12.25 W/m 2 K for bottom and topside of the workpiece respectively. The various properties of the parent metal i.e., Mg alloy (AZ80A) which are taken into account in this experimental analysis for framing the proposed model are described in Table 2. Similarly, Table 3 describes the various properties of the material used for fabricating the FSW tool (i.e., HSS M35 Grade) employed in this experimental work, for framing the proposed model are described in the Table 3. From the knowledge gained from the literature survey, it has been observed that, for attaining precise results, more number of grid nodes have to be placed around the surrounding region of the employed tool pin. This is mainly because the range & magnitude of the tool pin profile surface is very much less when compared with that of the workpiece surface. The diagrammatic illustration of the placing of innumerable grid nodes around the region of the FSW tool pin, through the generation of nonuniform mesh is shown in Fig.4.   In this experimental work, the melting point of the base metal is lower, when compared with that of the amount of frictional heat achieved between the workpiece surface and tool. As a result, the proposed model has been framed in such a way that, the generation of frictional heat will get adjusted to the value of zero, whenever the simulation temperature indicates higher values or values equivalent to the melting point of the parent metal. In simple words, it can be written as, q = 0; (T > Tmelt) (7) 2 RESULTS AND DISCUSSIONS In this experimental and numerical analysis, 30 experimental runs (inclusive of 3 center point experiments of control) were performed. The various measurement values obtained from these experiments were employed to frame the analytical model, which represents the peak temperature as the process (FSW) respond to the inconstants. The values of the peak temperature measured during the experimental analysis along with the predicted and FEA simulated values are described in Table 5. The actual model equation for predicting the peak temperature (Tmax) of the FSW magnesium alloy AZ80A is given in Equation (8)

Experimental Validation of Tmax
It has been observed that the variations between the predicted correlation & the obtained actual values and the simulated FEA values are neutral and comparably small. The simulated and anticipated values are found to be consistent with the actual values. The values of R2 for the maximum temperature are 0.9991 and 0.9888 for the simulated and anticipated values respectively, which reveals us to the fact that the retrogression is eloquent, as indicated graphically in Fig.5 (a) and (b).

Significance test of the predicted model
The significance test of the predicted model fit for maximum temperature was performed using Minitab tool based on analysis of variance (ANOVA). The investigations were performed at a 5% level of significance and for a confidence level of 95 percent. The ANOVA outcomes for the predicted peak temperature are mentioned in Table  6 and from this table, it can be observed that the developed model is perfectly ideal, as the value of F is quite larger and Prob> F value is lower by 0.05.
Apart from this, it can also be visualized from this Table, that the linear contributions by the input process parameters of FSW namely, traversing speed, rotating tool speed & axial force on the peak temperature are 32.82%, 41.65% and 21.76% respectively. Likewise, square percentage contributions of these input parameters, namely, traversing speed, axial force & rotational speed on the peak temperature are 1.38%, 0.06% and 0.60%. These values reveal to us that, the input parameter namely, the tool traversing speed has a dominant part in influencing the peak temperature, during the joining of AZ80A Mg alloy.

Finite element temperature distribution
The predicted Tmax was verified with the actually observed temperature and was proved to agree with it perfectly. The optimized experimental conditions (rotational speed=818 rpm; axial force=3.646kN; traversing speed of FSW tool=1.48 mm/s) specified by Sevvel et al. [23] were taken into account for generating & drafting the line plots and contours. The variations of temperature in workpiece on the bonding line and the offset lines when the tool reaches mid of the workpiece are shown in Fig.6. The experimental outcomes are also compared with the FEA simulated values and included in this Fig. 6.

Fig. 6. Graphical representation of the temperature variation along the longitudinal axis and its offset
The comparisons help us to understand that the FEA numerical results of the temperature values perfectly coincide with that of the experimental data. Also, the variations of the temperature in the workpiece transverse axis behind and in front of the tool movement were illustrated in Fig. 7(a) and Fig. 7(b) respectively.
It can be easily visualized from the Fig. 8  (a) & (b), that during the joining of AZ80A Mg alloy by FSW, the maximum value of temperature lies within the regions of workpiece contacted by the rotating FSW tool shoulder and is around 368 0 C, which is nearly 70-72% of the melting point (490 0 C) of the parent metal.

Fig. 7. Graphical representation of the (a) temperature variation along the transverse axis behind tool movement and its offset and (b) temperature variation along the transverse axis in front of tool movement and its offset
The experimental results confirm that the FSW of Mg alloys (especially AZ80A Mg alloy) is a solid-state joining process and during the fabrication of this Mg alloy joints, bonding has occurred perfectly, thereby resulting in sound quality weldments. Fig.9 (a-f) the optical micrographs of the parent metal & various regions of the defect free AZ80 Mg alloy FSW joints obtained during the employment of the optimized process parameters. From these optical micrographs, it can be visualized that, the microstructure of the cast parent metal (AZ80A Mg alloy) consists of a dendritic network, with the cored grains of mg solid solution with gargantuan precipitates of Mg17Al12 particles at the grain boundaries, as shown in Fig.9(a). Fig.9 (b) portrays the region of the interface at the side of tool advancement. In this image, the left side shows the microstructure of base metal and the right side shows the zone of nugget. This helps us to perceive that, the impact of temperature and the stress has resulted in reputed & uniform flow of zone of fusion along with the appearance of fragmented particles that have been recrystallized.

Experimental verification using optimized values
The thermo mechanically transformed region along with the constituents of the parent metals can be seen in Fig.9 (c). This figure helps us to understand the orientation of grains from both the sides of the parent metal has taken place due to the impact of the peak temperature generated in the region of contact of the workpiece -FSW tool shoulder surface, thereby resulting in the fusion of the constituents of the parent metal on both sides of the joint. Fig. 8 (a). Temperature contour obtained from FEA results for optimized condition (rotational speed=818 rpm; axial force=3.646 kN; traversing speed of FSW tool=1.48 mm/s) Fig. 8 (b). Temperature contour on bonding surface for optimised condition(rotational speed=818 rpm; axial force=3.646 kN; traversing speed of FSW tool=1.48 mm/s) We can also observe that the various surface regions of the parent metal closer to the contact point of the FSW tool shoulder region have also experienced a reasonable amount of heat generation & raise in temperature, which has led to the formation of alternate layers, as seen in the Fig.9 (d), due to the marginal flow of plasticized material influenced by the stirring action by FSW tool shoulder.
The impact of the peak temperature obtained during the joining of flat plates of AZ80A Mg alloy, can be observed clearly from the Fig.9 (e), which portrays us the partial evaporation of the constituents (mainly Zinc) from both the sides of the parent metal surfaces, which have been under the direct contact with the rotational shoulder of the FSW tool. Apart from this, we can infer that, the FSW process also plays a very important role in improvising & enhancing the microstructrural characteristics of the magnesium alloys (especially AZ80A Mg alloy). This is evident from the Fig.9 (f), which shows the presence of fine fragmented grain particles, which have been spaced in a uniformly &distributed in a homogeneous manner, when compared with the large sized, uneven coarse grains in the parent metal. This complete transformation of grain structure has occurred mainly due to the generation of ideal peak temperature resulting in superplasticity, uniform flow of the plasticized metal along with dynamic recrystallization. In order to add more additional weightage to the inferred result of the complete transformation of grain structure due to generation of ideal peak temperature, the SEM image of AZ80A Mg alloy is shown in the Fig.10 (a), which illustrates the presence of coarse, unevenly distributed with massive precipitates of Mg17Al12 particles at the grain boundaries. Fig.10 (b) portrays the interface region of the parent metal with the stir zone. This SEM image helps us understand that, at the interface region, the grains have been fragmented and at the stir region, the constituents of the AZ80A Mg alloy have been completely dissolved and the grains have got fragmented due to dynamic recrystallization. Fig.10 (c) shows the magnified SEM image of the stir zone obtained at 1000X magnification. In this image, we can see the secondary phase particles of the AZ80A Mg alloy has been completely dissolved, which have occurred due to the generation of ideal peak temperature resulting from the adoption of optimized process parameters.

Influence of process parameters
As it has been proved by several researchers [24][25][26] that, the rotational speed of tool, its speed of traverse and the load being applied on it are some of the influencing parameters of an FSW process, in this experimental & numerical investigation, the influential role of those three process parameters on the peak temperature were analyzed by simulating their impact during the impact on heat generation during the FSW of the parent metal, by employing the proposed FEA analysis model and are illustrated in the Fig.11 (a-c). From Fig.11 (a), it can be inferred that, the peak temperature escalates with the upsurge of the speed of rotation of the FSW tool and declines with the raise in the FSW tool's traversing speed. But at the same time, from Fig.11 (b), it can be interpreted that, at fixed tool traversing speed, with the simultaneous increase in the speed of rotation of FSW tool & axial load, the peak temperature raises. Moreover, at fixed rotational speed of FSW tool, the peak temperature escalates with the upsurge of the axial force and declines with the raise in FSW tool's traversing speed, as shown in Fig.11 (c).
Based on the careful observation of these simulated temperature contour graphs, we can infer that, performing the joining of AZ80A Mg alloys by FSW, at an optimized combination of higher rotational speeds of FSW tool, with the FSW tool traversing at low speeds & by applying larger values of axial load will result in the generation of ideal peak temperature, which will eventually contribute to perfect bonding between the AZ80A Mg alloy plates to be welded, thereby resulting in sound quality weldments

CONCLUSIONS
In the present experimental research, an investigational analysis during the joining of AZ80A Mg alloy was carried out to formulate a correlation to analysis generation of peak temperature. A3 dimensional steady-state model for heat-transfer in a movable type coordinate was modeled and simulated to visualize the temperature distribution in the parent metal. In addition to this, detailed parametric studies were carried out to understand the influence of parameters of FSW process in the generation of peak temperature and the following inference were derived: • The formulated correlation for Tmax was able to accurately predict the maximum temperature generation during the FSW of flat plates of AZ80A Mg alloy. The predicted Tmax was verified with the observed temperature and was proved to agree with perfectly.
• Variations between the predicted correlation & the obtained actual values and the simulated FEA values were found to be comparably small. The simulated and anticipated values are found to be consistent with the actual values. The values of R 2 for the maximum temperature are 0.9991 and 0.9888 for the simulated and anticipated values respectively.
• Linear contributions by the input process parameters of FSW namely, traversing speed, rotating tool speed & axial force on the peak temperature were observed to be 32.82%, 41.65% and 21.76% respectively. Likewise, square percent contributions of these input parameters, namely, traversing speed, rotating tool speed & axial force on the peak temperature are 1.38%, 0.60% and 0.06% respectively.
• The experimental & predicted values reveal to us that, the input parameter namely, the tool traversing speed has a momentous part in influencing the peak temperature, during the joining of AZ80A Mg alloy.
• The significance test of the predicted model fit for maximum temperature was performed using Minitab tool based on analysis of variance (ANOVA) and it was observed that, the developed model was perfectly ideal, as the value of F was quite larger and Prob> F value was lower by 0.05.
• It was visualized from the generated temperature contour graphs that, the maximum value of temperature lies within the regions of workpiece contacted by the rotating FSW tool shoulder and is around 368 0 C, which is nearly 70-72% of the melting point (490 0 C) of the parent metal.
• It was inferred that, performing the FSW of AZ80A Mg alloys at an optimized combination of higher rotating tool speeds, with the FSW tool traversing at low speeds & by applying larger values of the axial load will result in the generation of ideal peak temperature, which will eventually contribute to perfect bonding between the AZ80A Mg alloy plates to be welded, thereby resulting in sound quality weldments.