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The spreading simulation of molten Al alloy on Q235 steel in the first cycle of cold metal transfer process
International Journal of Heat and Mass Transfer 96 (2016) 118–124
Contents lists available at ScienceDirect
International Journal of Heat and Mass Transfer journal homepage: www.elsevier.com/locate/ijhmt
The spreading simulation of molten Al alloy on Q235 steel in the first cycle of cold metal transfer process Qiaoli Lin ⇑, Chengzong Zeng, Rui Cao, Jianhong Chen State Key Laboratory of Advanced Processing and Recycling of Non-ferrous Metal, Lanzhou University of Technology, No. 287 Langongping Road, Lanzhou 730050, People’s Republic of China
a r t i c l e
i n f o
Article history: Received 7 August 2015 Received in revised form 31 December 2015 Accepted 1 January 2016
Keywords: Cold metal transfer Heat transfer Wetting Capillary
a b s t r a c t The volume of fluid and the solidification-melting models were used for the study of the wetting of Q235 steel by molten Al alloy in the first cycle of cold metal transfer process. Together with the consideration of the welding temperature field and the solidification process, the effect of welding temperature field (corresponding to the different wire feed speeds) on solidification, final wettability, and wetting behavior were discussed, respectively. The results showed that the molten Al alloy primarily began to solidify at the triple line, which is consistent with the distribution of temperature field; partial solidified metal blocked the motion of triple line to a certain extent; good wettability of Q235 steel plate by molten Al alloy can be observed with the increase of wire feed speed, and the advance of triple line was controlled by capillary force. Ó 2016 Elsevier Ltd. All rights reserved.
1. Introduction With increasingly concerned about environmental issues, green and energy saving have become the theme of the auto industry development. On the premise of security, reducing vehicle weight is the most efficient way to save energy and protect the environment. In order to achieve a loss of structural weight while maintaining or even improving structural performance for lightweight design, the use of hybrid structures from mixed materials such as Al alloy and steel is widely discussed. Due to the huge difference of chemical and physical properties between Al alloy and steel, and easily formed brittle intermetallics (such as Fe2Al5 and FeAl3) in the joining zone [1], the solid-phase welding and the weldingbrazing are usually carried out for joining them together, such as laser roll welding [2], laser-MIG hybrid welding [3], fluxless laser beam joining [4], and resistance spot welding [5]. In these processes, the key factor is to reduce the heat input in the welding process. Recently, Fronius Company on the basis of gas metal arc welding (GMAW) developed the technology of cold metal transfer (CMT), and the unique expert system in this technology is very suitable for joining dissimilar metals in welding-brazing mode with the controllable heat input [6,7]. Different from conventional GMAW welding, almost half process is used for heating the weld
⇑ Corresponding author. Tel.: +86 931 2757296; fax: +86 931 2755806. E-mail address: [email protected] (Q. Lin). http://dx.doi.org/10.1016/j.ijheatmasstransfer.2016.01.002 0017-9310/Ó 2016 Elsevier Ltd. All rights reserved.
wire, and another half process is used for transferring the molten metal from the wire to the substrate when the arc was extinguished by digital coordination in the unique expert system. Although modeling the heat transfer and fluid flow in the arc plasma for GMAW has been well documented [8–10], very few research articles can be found for the CMT process. Zhu et al. [11] calculated the anode temperature profile by incorporating the simplified arc model of Lowke et al. [12] into a onedimensional conduction model of the moving electrode in GMAW. Haidar and Lowke [13] also extended the simplified arc model of Lowke et al. [12] to simulate the droplet formation in GMAW. Further, many researchers focus on the metal transfer and weld-pool dynamics [14,15]. However, the plasma arc struck between an electrode and a workpiece was alleviated in CMT process, and almost no base metal melted (i.e., no weld-pool was formed). Therefore, the fluid flow in the CMT process of molten droplet on the surface of base metal is the wetting process under different heat input, actually. On the other hand, when the liquid solder contact with a steel plate, wetting, spreading and interface reaction is the key factor for a reliable joining [16]. During welding-brazing process, the spreading of molten metal on solid substrate is usually under the complex external condition, e.g. the heterogeneous temperature field, gravitational field, surface tension gradient, etc. In our previous study [17], the spreading dynamics of steel by molten Al alloy in the first cycle of CMT process were determined by the characteristics of fluid itself rather than the interfacial reaction, which can be described by hydrodynamic model (i.e., such a wet-
Q. Lin et al. / International Journal of Heat and Mass Transfer 96 (2016) 118–124
ting process is more inclined to physical process rather than chemical process). Therefore, the method using numerical simulations may be an effective way to study the molten droplet on the substrate under complex external conditions meanwhile without the consideration of interfacial reaction. At present, although the spreading and solidification of molten metallic droplet on a solid substrate was studied by numerous numerical simulations, the interfacial tension between metallic droplet and substrate was not considered in most numerical simulations [18–21]. In this work, we used volume of fluid (VOF, 3 fluid phase, air, molten droplet and substrate) model and the solidificationmelting model to study the dynamic wetting behavior of a molten AlSi5 droplet on the surface of Q235 steel plate in the first cycle of CMT process, and further experimental verifications were also carried out. 2. Wetting simulation Numerical simulation of the wetting process was carried out using both VOF and solidification-melting models to predict mass, momentum and thermal energy transport, free surface shape and spreading of the molten Al alloy on the surface of Q235 steel. The whole wetting spreading process is simplified to a twodimensional axisymmetric model, as be shown in Fig. 1. The size of the model is 5 6 mm. In order to ensure the calculation precision, grid refinement near the molten droplet was implemented, and then the UDF (User Defined Functions) was used to initialize the entire fluid field. Several assumptions were made before simulation: AlSi5 welding wire elements only contained Al and Si (the weight percentage of Si is 5%); the initial Al alloy was regular globular and Q235 steel sheet was not melting in the wetting process; the molten Al alloy was considered to be an incompressible Newtonian fluid and the flow was assumed to be laminar. Buoyancy and arc blow force terms were included in the momentum equation. The density change of molten Al alloy was considered in the buoyancy force (fb),
f b ¼ qgbðT T0 Þ;
119
ð1Þ
where q is the density of the molten Al alloy; g is the acceleration of gravity; b is the coefficient of volumetric expansion of the liquid; T is the temperature of the molten Al alloy in K; T0 is the temperature of the environment in K. The basic governing equations include continuity equation, momentum equation and energy equation. Based on the above assumptions, the volume of Al alloy or steel is incompressible and the density of Al alloy is constant during the phase change. Thus the continuity equation in this model is,
@u @ v þ ¼0 @x @y
ð2Þ
where u is the speed of x direction; v is the speed of y direction. Due to the steel in the wetting process without melting, the velocity of the steel was locked. Thus, the momentum equation is,
8 2 2 > < q du ¼ l @@x2u þ @@yu2 @p þ Gx @x dt 2 2 @p > d v @ v @ v : q dt ¼ l 2 þ 2 @y þ Gy @x @y
ð3Þ
where l is the dynamic viscosity coefficient; p is the intensity of pressure; Gx is the horizontal volume force; Gy is the vertical volume force. In this model, the energy of steel only has thermal energy, while the energy of Al alloy includes both thermal and mechanical energy. The amount of the thermal energy coming from the mechanical energy is very small, so the mechanical energy of Al alloy can be ignored. Thus, the energy equation is simplified as,
dT @2T @2T qcv ¼ k þ dt @x2 @y2
!
þS
ð4Þ
where T is the temperature; cv is the specific heat; k is the coefficient of thermal conductivity; S is the energy source term. Boundary conditions include calculation area boundary conditions and movement in the interior boundary conditions. The calculation area boundary conditions include atmospheric boundary, wall of substrate and axis of symmetry. Both pressure inlet and pressure outlet were set as a standard atmospheric pressure. The right wall of the substrate is defined as thermal insulating boundary conditions, while the bottom wall of the substrate is defined as copper in 300 K. Axis of symmetry used FLUENT software default settings, i.e., Eq. (5). The movement in the interior boundary conditions was complex with the change of temperature and form of Al alloy, which happened heat conduction in free surface, tracked by VOF equation.
( @T
@y
¼0
v ¼ @u ¼0 @y
;
ð5Þ
Arc heat input (q(r)) on the molten Al alloy surface was modeled as Gaussian density distributions,
qðrÞ ¼
3Q 3r 2 ; exp pr2H r 2H
ð6Þ
where Q is the effective heat power of the welding arc; rH is the radius of heating spot. The variation of arc heat input distribution Gaussian parameter was calculated as a function of arc current for a 4 mm arc length case using the expression
rH ¼ 0:533I0:2941 ;
Fig. 1. Meshing and initializing for geometric model.
ð7Þ
obtained from the literature [22]. In the process of spreading simulation, the parameters of material physical properties were involved, such as specific heat,
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coefficient of thermal conductivity k in W m1 k1, density, viscosity coefficient l in kg m1 s1, the surface tension coefficient c in N m1 et al. Most of these physical parameters alter along with the change of temperature, i.e., Eqs. (8)–(11). Materials used in the model were AlSi5 Al alloy and Q235 low carbon steel, and the physical parameters were summarized in Table 1 [23–24].
lAlSi5 ¼ 1:492 104 exp 1984:509T 1 ; T > 850 K
ð8Þ
cAlSi5 ¼ 1:2115 3:5 104 T; T > 850 K
ð9Þ
kAlSi5 ¼ 63:00389 þ 0:03327T;
kQ235
850 K < T < 1273 K
ð10Þ
8 > < 60:719 0:027857T; T 6 851 K ¼ 78:542 0:0488T; 851 K 6 T 6 1082 K > : 15:192 0:0097T; 1082 K 6 T 6 1768 K
ð11Þ
The surface tension coefficients, both of AlSi5 (cAlSi5) and Q235 steel (cQ235) have been mentioned in literatures [23–24]. In order to acquire the interfacial tension between AlSi5 and Q235 steel (cAlSi5–Q235), we assume that molten AlSi5 Al alloy on Q235 steel surface will achieve complete wetting (the contact angle is 0° finally) after a certain time. According to Young’s equation, the equilibrium state of stress equation is cAlSi5 + cAlSi5–Q235 = cQ235, and thus cAlSi5–Q235 equals cQ235 minus cAlSi5 (cQ235cAlSi5). Also, the values of cAlSi5, cQ235 and cQ235cAlSi5 were summarized in Fig. 2. For the purpose of simplification, the value of cAlSi5–Q235 was set as a constant value, and the average value of cQ235cAlSi5, which is 0.05 Nm1. The surface tensions were calculated mainly base on the Continue Surface Force (CSF) model as a volume force source term (Fsu) in the momentum conservation equation, which can be expressed as following,
Table 1 Thermophysical properties of materials. Materials
AlSi5
Air
Q235
Destiny, q, kg m3 Environment temperature, T0, K Liquidus, Tl, K Solidus, Ts, K Volumetric coefficient of thermal expansion, b, K1 Surface tension, c, N m1 Thermal conductivity, Cp, J kg1 K1 Latent heat of fusion, Q, J kg1
2670 300 906 850 2.1 105
1.225 300 0 0 –
8030 300 1759 1789 –
Eq. (5) 843 2.89 105
– 1006 0
1 502 –
Fig. 3. Schematic diagram of voltage and current waveform in the first cycle of CMT.
F su ¼ ckrF;
ð12Þ
where k is the free surface curvature, F is the distribution function of volume force. In this study, only the wetting process in the first cycle of metal transfer process was analyzed. In the first cycle of CMT, the voltage and current waveform includes several stages, which a (in Fig. 3) is the ignition of the arc, b stage corresponds to the arc extinguished and partial wire melted, c stage corresponds to the short circuit and d stage corresponds to the drop spreading, as be shown in Fig. 3. The initial time of the simulation was set as when the contact angle between AlSi5 and Q235 steel is 180° while welding arc has heated the base metal and droplet in fact, and thus the temperature of AlSi5 Al alloy and Q235 steel sheet need to be initialized firstly. Gaussian heat source of uniform heat input was used to calculate the temperature field of different initialized model under same time, and extracted the temperature date along the axis respectively, as be shown in Fig. 4(a). The temperature of Q235 steel at the center of the droplet is 40 K higher than AlSi5 Al alloy can be found. Secondly, the heat source of different heat inputs was considered, and further the temperature field of same initialized model (AlSi5) and extracted the temperature date along the vertical axis were be calculated respectively, as be shown in Fig. 4(b). The difference among the different heat input is 20 K. Finally, according to the above calculations and our previous study [25], the initializing temperatures will be set to values summarized in Table 2. As known, wire feed speed (WFS, v) is closely related to the heat input of welding process. A linear relationship between WFS and welding power (UI) can be observed, as be shown in Fig. 4(c), which can be expressed as UI = 397.03 + 460.725v. Further, the initializing temperatures and welding power for calculation was set as a linear relationship at the same time, as be shown in Fig. 4(d).
3. Experimental method
Fig. 2. Interfacial tension between AlSi5 and Q235.
The equipments for wetting experiment were CMT equipment (CMT 3200, Austria), the backlight source, CMOS high speed video camera (the maximal speed is 2000 frame s1, GZL-CL-22C5M-C, America) and date processing system. The welding torch is perpendicular to Q235 steel sheet, as be shown in Fig. 5. In this study, the pumpback frequency of weld wire is 50–70 Hz, and thus welding duration 1 s was adopted which is capable for the analysis of the
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Fig. 4. (a) Temperature D-value between AlSi5 and Q235 and (b) temperature D-value among different WFS and (c) the relationship between welding power and WFS and (d) the relationship between initialized temperature and welding power.
was adopted with the static welding torch, and then the high speed video camera recorded the whole wetting process.
Table 2 The initial temperature under different heat input. WFS, m min1
TAl, K
TSteel, K
2.5 3.5 4.5 5.5 6.5 7.5
900 920 940 960 980 1000
940 960 980 1000 1020 1040
Fig. 5. Schematic diagram of the device for wetting experiment.
wetting process in the first cycle of metal transfer process. Welding parameters were summarized in Table 3. Before wetting experiment, Q235 steel sheets were degreased by acetone, and then it was fixed on the platform by using fixtures. Spot welding method
4. Results and discussion The recorded frame by high speed video camera and images from the numerical simulation results at corresponding times (using WFS = 6.5 m min1 as typical one) are shown in Fig. 6(a). Metallic droplet in the experimental process was irregular globular at the time of 0 ms. It is noted that the wetting predicted by simulation is a bit better than experiment results between AlSi5 and Q235 steel sheet at the time of 4 ms and 6 ms, considering the influence of roughness and oxide film on the surface of Q235 steel sheet in the process of wetting experiment. As a whole, the simulated results conform to the experimental results. In the process of droplet spreading, heat exchange takes place among AlSi5 alloy, Q235 steel, air in the fluid field. The temperature gradient of Al alloy is smaller than that of steel, due to the larger heat transfer coefficient of Al alloy. It is worth noting that the solidification firstly happens at the triple line, which is corresponding to the distribution of temperature field, as be shown in Fig. 6 (b). Numerical calculations were carried out from the WFS = 2.5 m min1 to 7.5 m min1. We compared drop profiles and corresponding solidification profiles of different WFSs at the
Table 3 Summary of welding parameters used in experiments.
*
Wetting time, s
WFS, m min1
Weld wire type
Wire diameter, mm
CTWD*, mm
Shielding gas
Shielding gas flowrate, L min1
1
6.5
ER4043
1.2
5
99.999%Ar
15
CTWD refers to contact tube to workpiece distance.
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Fig. 6. (a) Corresponding sequences of high speed video camera images and numerical simulation results and (b) contours of temperature field distribution and the corresponding solidification process at 0–10 ms.
time of 10 ms. It is obvious that the contact angle became smaller with the increase of WFS and the amount of metal solidification nearby the triple line also became less with the increase of WFS, as be shown in Fig. 7. Further, the variation tendency of both contact angle and the area of solidified AlSi5 Al alloy with the increase of WFS is almost the same, as be shown in Fig. 8. Therefore, solidified metal at the triple line may be blocked the further motion of triple line. Furthermore, the wetting behaviors of AlSi5 Al alloy on the surface of Q235 steel sheet in different WFSs were studied, as be shown in Fig. 9. The tendency of the contact angle is almost the same, and the contact angle decreased gradually with the increase of time, as be shown in Fig. 9(a). Meanwhile, the contact radius increased gradually with the increase of time, as be shown in Fig. 9(b). The contact angle and contact radius made no difference before 1 ms, and then the heat input induced different wetting behavior obviously. The influence of WFS on contact angle and contact radius is also obvious, the contact angles become smaller and the motion of triple line become faster with the increase of WFS. As the previous analysis, solidified metal at the triple line may be blocked the further motion of triple line, which is closely related to the temperature field distribution. Therefore, the variations of temperature at triple line with time for different WFSs were extracted, as be shown in Fig. 10. The tendency of temperatures of triple line in different WFSs was almost same and all temperatures of triple line in different WFSs exceeded the solidus of AlSi5 Al alloy before 1 ms, which means the advancing triple line of different WFSs was not blocked and that is why the tendency of contact angle and contact radius made no difference before 1 ms.
Fig. 8. Contact angle and AlSi5 solidified area in different WFS at 10 ms.
However, the tendency of temperatures of triple line in different WFSs became different after 1 ms and the temperature of triple line of different WFSs was all completely below the solidus of AlSi5 at the time of 3 ms. Therefore, the molten droplet at the triple line of different WFSs began to solidify and the triple line would be blocked by solidified metal, that is why the amplitude of variation of contact angle and the contact radius became smaller and smaller after 3 ms. The temperatures at triple line for different WFSs are all below the solidus of AlSi5 after 3 ms. And then the areas of solidified AlSi5 of different WFSs after 3 ms were extracted, as be shown in Fig.11.
Fig. 7. Drop profiles and the corresponding solidification profiles of different WFS at 10 ms.
Q. Lin et al. / International Journal of Heat and Mass Transfer 96 (2016) 118–124
123
Fig. 9. The wetting behavior of molten AlSi5 Al alloy on the surface of Q235 steel in different WFS: (a) variation of contact angles and (b) base radius with time.
Fig. 10. Temperature of triple line of different wire feed speed at different times.
Fig. 11. Variation of AlSi5 solidified area with time.
The amplitude variation of AlSi5 solidified areas in different WFSs after 3 ms increase with time, which results in the amplitude of variation of contact angle and contact radius became smaller and finally reached a stable state. The AlSi5 solidified area increases with time when WFS is bellow 3.5 m min1 and faster than that of WFS above 4.5 m min1. When WFS is bellow 3.5 m min1, the
Fig. 12. Variation of the advancing velocity of triple line with time.
amplitude variation of contact angle and the contact radius is smaller than that of WFS above 4.5 m min1, due to the solidified metal at the triple line would be blocked the further motion of triple line. The velocity of advancing triple line is related to both solidified metal and temperature field distribution at the triple line. Further, the velocities of advancing triple line of different WFSs at different times were extracted, as be shown in Fig. 12. The velocity of advancing triple line before 3 ms is larger than that after 3 ms, which is why the amplitude of variation of both contact angle and contact radius is much bigger before 3 ms. And the velocity of advancing triple line increases with the WFS before 3 ms, and thus the contact angle decrease and the contact radius increase with the WFS before that time. It is noted that the velocities of advancing triple line with different WFSs become steady and are almost equal to zero after 3 ms, which result in the contact angle and contact radius tend to stabilization after 3 ms. The velocity of triple line was calculated by the differentiation of the variation of contact radius with time. Capillary numbers were calculated based on equation Ca ¼ lu c1 with material properties, (l is liquid viscosity, u is contact line speed and c is liquid–vapor surface tension). Contact angle (h) of molten AlSi5 on the surface of Q235 steel sheet at the time of 10 ms were estimated from the simulation images. Simulated contact angles are plotted as a function of capillary number in Fig. 13. Ca is a temperature
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References
Fig. 13. Plot of dynamic advancing contact angle as function of capillary number.
dependent linear function [26], and the contact angles also depend to temperature as an almost linear relationship. Therefore, the clear quantitative linear relationship between Ca and h which may indicate the advancing contact line velocity was controlled by capillary force. 5. Conclusions In this work, we used both volume of fluid and solidificationmelting models to establish the wetting spreading model of molten Al alloy on the surface of steel plate and the simulation results almost consistent with the experimental results. (1) The main factor influencing the molten droplets spread out is the distribution of temperature field. Solidification happened at the triple line first, and then spread to the center of the droplet. Solidified metal nearby the triple line would hinder the spreading of the droplet to a certain extent. (2) The wettability of molten Al alloy on the surface of steel plate became better with the increase of WFS and the advancing contact line velocity may be controlled by capillary force.
Acknowledgements This work is supported by National Natural Science Foundation of China (No. 51301083), Provincial Fund for Distinguished Young Scientists (No. 1506RJDA087), Rose Willow Young Foundation of Lanzhou University of Technology (No. Q201407) and Preresearch of National Basic Research Program of China (2014CB660810).
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Contents lists available at ScienceDirect
International Journal of Heat and Mass Transfer journal homepage: www.elsevier.com/locate/ijhmt
The spreading simulation of molten Al alloy on Q235 steel in the first cycle of cold metal transfer process Qiaoli Lin ⇑, Chengzong Zeng, Rui Cao, Jianhong Chen State Key Laboratory of Advanced Processing and Recycling of Non-ferrous Metal, Lanzhou University of Technology, No. 287 Langongping Road, Lanzhou 730050, People’s Republic of China
a r t i c l e
i n f o
Article history: Received 7 August 2015 Received in revised form 31 December 2015 Accepted 1 January 2016
Keywords: Cold metal transfer Heat transfer Wetting Capillary
a b s t r a c t The volume of fluid and the solidification-melting models were used for the study of the wetting of Q235 steel by molten Al alloy in the first cycle of cold metal transfer process. Together with the consideration of the welding temperature field and the solidification process, the effect of welding temperature field (corresponding to the different wire feed speeds) on solidification, final wettability, and wetting behavior were discussed, respectively. The results showed that the molten Al alloy primarily began to solidify at the triple line, which is consistent with the distribution of temperature field; partial solidified metal blocked the motion of triple line to a certain extent; good wettability of Q235 steel plate by molten Al alloy can be observed with the increase of wire feed speed, and the advance of triple line was controlled by capillary force. Ó 2016 Elsevier Ltd. All rights reserved.
1. Introduction With increasingly concerned about environmental issues, green and energy saving have become the theme of the auto industry development. On the premise of security, reducing vehicle weight is the most efficient way to save energy and protect the environment. In order to achieve a loss of structural weight while maintaining or even improving structural performance for lightweight design, the use of hybrid structures from mixed materials such as Al alloy and steel is widely discussed. Due to the huge difference of chemical and physical properties between Al alloy and steel, and easily formed brittle intermetallics (such as Fe2Al5 and FeAl3) in the joining zone [1], the solid-phase welding and the weldingbrazing are usually carried out for joining them together, such as laser roll welding [2], laser-MIG hybrid welding [3], fluxless laser beam joining [4], and resistance spot welding [5]. In these processes, the key factor is to reduce the heat input in the welding process. Recently, Fronius Company on the basis of gas metal arc welding (GMAW) developed the technology of cold metal transfer (CMT), and the unique expert system in this technology is very suitable for joining dissimilar metals in welding-brazing mode with the controllable heat input [6,7]. Different from conventional GMAW welding, almost half process is used for heating the weld
⇑ Corresponding author. Tel.: +86 931 2757296; fax: +86 931 2755806. E-mail address: [email protected] (Q. Lin). http://dx.doi.org/10.1016/j.ijheatmasstransfer.2016.01.002 0017-9310/Ó 2016 Elsevier Ltd. All rights reserved.
wire, and another half process is used for transferring the molten metal from the wire to the substrate when the arc was extinguished by digital coordination in the unique expert system. Although modeling the heat transfer and fluid flow in the arc plasma for GMAW has been well documented [8–10], very few research articles can be found for the CMT process. Zhu et al. [11] calculated the anode temperature profile by incorporating the simplified arc model of Lowke et al. [12] into a onedimensional conduction model of the moving electrode in GMAW. Haidar and Lowke [13] also extended the simplified arc model of Lowke et al. [12] to simulate the droplet formation in GMAW. Further, many researchers focus on the metal transfer and weld-pool dynamics [14,15]. However, the plasma arc struck between an electrode and a workpiece was alleviated in CMT process, and almost no base metal melted (i.e., no weld-pool was formed). Therefore, the fluid flow in the CMT process of molten droplet on the surface of base metal is the wetting process under different heat input, actually. On the other hand, when the liquid solder contact with a steel plate, wetting, spreading and interface reaction is the key factor for a reliable joining [16]. During welding-brazing process, the spreading of molten metal on solid substrate is usually under the complex external condition, e.g. the heterogeneous temperature field, gravitational field, surface tension gradient, etc. In our previous study [17], the spreading dynamics of steel by molten Al alloy in the first cycle of CMT process were determined by the characteristics of fluid itself rather than the interfacial reaction, which can be described by hydrodynamic model (i.e., such a wet-
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ting process is more inclined to physical process rather than chemical process). Therefore, the method using numerical simulations may be an effective way to study the molten droplet on the substrate under complex external conditions meanwhile without the consideration of interfacial reaction. At present, although the spreading and solidification of molten metallic droplet on a solid substrate was studied by numerous numerical simulations, the interfacial tension between metallic droplet and substrate was not considered in most numerical simulations [18–21]. In this work, we used volume of fluid (VOF, 3 fluid phase, air, molten droplet and substrate) model and the solidificationmelting model to study the dynamic wetting behavior of a molten AlSi5 droplet on the surface of Q235 steel plate in the first cycle of CMT process, and further experimental verifications were also carried out. 2. Wetting simulation Numerical simulation of the wetting process was carried out using both VOF and solidification-melting models to predict mass, momentum and thermal energy transport, free surface shape and spreading of the molten Al alloy on the surface of Q235 steel. The whole wetting spreading process is simplified to a twodimensional axisymmetric model, as be shown in Fig. 1. The size of the model is 5 6 mm. In order to ensure the calculation precision, grid refinement near the molten droplet was implemented, and then the UDF (User Defined Functions) was used to initialize the entire fluid field. Several assumptions were made before simulation: AlSi5 welding wire elements only contained Al and Si (the weight percentage of Si is 5%); the initial Al alloy was regular globular and Q235 steel sheet was not melting in the wetting process; the molten Al alloy was considered to be an incompressible Newtonian fluid and the flow was assumed to be laminar. Buoyancy and arc blow force terms were included in the momentum equation. The density change of molten Al alloy was considered in the buoyancy force (fb),
f b ¼ qgbðT T0 Þ;
119
ð1Þ
where q is the density of the molten Al alloy; g is the acceleration of gravity; b is the coefficient of volumetric expansion of the liquid; T is the temperature of the molten Al alloy in K; T0 is the temperature of the environment in K. The basic governing equations include continuity equation, momentum equation and energy equation. Based on the above assumptions, the volume of Al alloy or steel is incompressible and the density of Al alloy is constant during the phase change. Thus the continuity equation in this model is,
@u @ v þ ¼0 @x @y
ð2Þ
where u is the speed of x direction; v is the speed of y direction. Due to the steel in the wetting process without melting, the velocity of the steel was locked. Thus, the momentum equation is,
8 2 2 > < q du ¼ l @@x2u þ @@yu2 @p þ Gx @x dt 2 2 @p > d v @ v @ v : q dt ¼ l 2 þ 2 @y þ Gy @x @y
ð3Þ
where l is the dynamic viscosity coefficient; p is the intensity of pressure; Gx is the horizontal volume force; Gy is the vertical volume force. In this model, the energy of steel only has thermal energy, while the energy of Al alloy includes both thermal and mechanical energy. The amount of the thermal energy coming from the mechanical energy is very small, so the mechanical energy of Al alloy can be ignored. Thus, the energy equation is simplified as,
dT @2T @2T qcv ¼ k þ dt @x2 @y2
!
þS
ð4Þ
where T is the temperature; cv is the specific heat; k is the coefficient of thermal conductivity; S is the energy source term. Boundary conditions include calculation area boundary conditions and movement in the interior boundary conditions. The calculation area boundary conditions include atmospheric boundary, wall of substrate and axis of symmetry. Both pressure inlet and pressure outlet were set as a standard atmospheric pressure. The right wall of the substrate is defined as thermal insulating boundary conditions, while the bottom wall of the substrate is defined as copper in 300 K. Axis of symmetry used FLUENT software default settings, i.e., Eq. (5). The movement in the interior boundary conditions was complex with the change of temperature and form of Al alloy, which happened heat conduction in free surface, tracked by VOF equation.
( @T
@y
¼0
v ¼ @u ¼0 @y
;
ð5Þ
Arc heat input (q(r)) on the molten Al alloy surface was modeled as Gaussian density distributions,
qðrÞ ¼
3Q 3r 2 ; exp pr2H r 2H
ð6Þ
where Q is the effective heat power of the welding arc; rH is the radius of heating spot. The variation of arc heat input distribution Gaussian parameter was calculated as a function of arc current for a 4 mm arc length case using the expression
rH ¼ 0:533I0:2941 ;
Fig. 1. Meshing and initializing for geometric model.
ð7Þ
obtained from the literature [22]. In the process of spreading simulation, the parameters of material physical properties were involved, such as specific heat,
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coefficient of thermal conductivity k in W m1 k1, density, viscosity coefficient l in kg m1 s1, the surface tension coefficient c in N m1 et al. Most of these physical parameters alter along with the change of temperature, i.e., Eqs. (8)–(11). Materials used in the model were AlSi5 Al alloy and Q235 low carbon steel, and the physical parameters were summarized in Table 1 [23–24].
lAlSi5 ¼ 1:492 104 exp 1984:509T 1 ; T > 850 K
ð8Þ
cAlSi5 ¼ 1:2115 3:5 104 T; T > 850 K
ð9Þ
kAlSi5 ¼ 63:00389 þ 0:03327T;
kQ235
850 K < T < 1273 K
ð10Þ
8 > < 60:719 0:027857T; T 6 851 K ¼ 78:542 0:0488T; 851 K 6 T 6 1082 K > : 15:192 0:0097T; 1082 K 6 T 6 1768 K
ð11Þ
The surface tension coefficients, both of AlSi5 (cAlSi5) and Q235 steel (cQ235) have been mentioned in literatures [23–24]. In order to acquire the interfacial tension between AlSi5 and Q235 steel (cAlSi5–Q235), we assume that molten AlSi5 Al alloy on Q235 steel surface will achieve complete wetting (the contact angle is 0° finally) after a certain time. According to Young’s equation, the equilibrium state of stress equation is cAlSi5 + cAlSi5–Q235 = cQ235, and thus cAlSi5–Q235 equals cQ235 minus cAlSi5 (cQ235cAlSi5). Also, the values of cAlSi5, cQ235 and cQ235cAlSi5 were summarized in Fig. 2. For the purpose of simplification, the value of cAlSi5–Q235 was set as a constant value, and the average value of cQ235cAlSi5, which is 0.05 Nm1. The surface tensions were calculated mainly base on the Continue Surface Force (CSF) model as a volume force source term (Fsu) in the momentum conservation equation, which can be expressed as following,
Table 1 Thermophysical properties of materials. Materials
AlSi5
Air
Q235
Destiny, q, kg m3 Environment temperature, T0, K Liquidus, Tl, K Solidus, Ts, K Volumetric coefficient of thermal expansion, b, K1 Surface tension, c, N m1 Thermal conductivity, Cp, J kg1 K1 Latent heat of fusion, Q, J kg1
2670 300 906 850 2.1 105
1.225 300 0 0 –
8030 300 1759 1789 –
Eq. (5) 843 2.89 105
– 1006 0
1 502 –
Fig. 3. Schematic diagram of voltage and current waveform in the first cycle of CMT.
F su ¼ ckrF;
ð12Þ
where k is the free surface curvature, F is the distribution function of volume force. In this study, only the wetting process in the first cycle of metal transfer process was analyzed. In the first cycle of CMT, the voltage and current waveform includes several stages, which a (in Fig. 3) is the ignition of the arc, b stage corresponds to the arc extinguished and partial wire melted, c stage corresponds to the short circuit and d stage corresponds to the drop spreading, as be shown in Fig. 3. The initial time of the simulation was set as when the contact angle between AlSi5 and Q235 steel is 180° while welding arc has heated the base metal and droplet in fact, and thus the temperature of AlSi5 Al alloy and Q235 steel sheet need to be initialized firstly. Gaussian heat source of uniform heat input was used to calculate the temperature field of different initialized model under same time, and extracted the temperature date along the axis respectively, as be shown in Fig. 4(a). The temperature of Q235 steel at the center of the droplet is 40 K higher than AlSi5 Al alloy can be found. Secondly, the heat source of different heat inputs was considered, and further the temperature field of same initialized model (AlSi5) and extracted the temperature date along the vertical axis were be calculated respectively, as be shown in Fig. 4(b). The difference among the different heat input is 20 K. Finally, according to the above calculations and our previous study [25], the initializing temperatures will be set to values summarized in Table 2. As known, wire feed speed (WFS, v) is closely related to the heat input of welding process. A linear relationship between WFS and welding power (UI) can be observed, as be shown in Fig. 4(c), which can be expressed as UI = 397.03 + 460.725v. Further, the initializing temperatures and welding power for calculation was set as a linear relationship at the same time, as be shown in Fig. 4(d).
3. Experimental method
Fig. 2. Interfacial tension between AlSi5 and Q235.
The equipments for wetting experiment were CMT equipment (CMT 3200, Austria), the backlight source, CMOS high speed video camera (the maximal speed is 2000 frame s1, GZL-CL-22C5M-C, America) and date processing system. The welding torch is perpendicular to Q235 steel sheet, as be shown in Fig. 5. In this study, the pumpback frequency of weld wire is 50–70 Hz, and thus welding duration 1 s was adopted which is capable for the analysis of the
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Fig. 4. (a) Temperature D-value between AlSi5 and Q235 and (b) temperature D-value among different WFS and (c) the relationship between welding power and WFS and (d) the relationship between initialized temperature and welding power.
was adopted with the static welding torch, and then the high speed video camera recorded the whole wetting process.
Table 2 The initial temperature under different heat input. WFS, m min1
TAl, K
TSteel, K
2.5 3.5 4.5 5.5 6.5 7.5
900 920 940 960 980 1000
940 960 980 1000 1020 1040
Fig. 5. Schematic diagram of the device for wetting experiment.
wetting process in the first cycle of metal transfer process. Welding parameters were summarized in Table 3. Before wetting experiment, Q235 steel sheets were degreased by acetone, and then it was fixed on the platform by using fixtures. Spot welding method
4. Results and discussion The recorded frame by high speed video camera and images from the numerical simulation results at corresponding times (using WFS = 6.5 m min1 as typical one) are shown in Fig. 6(a). Metallic droplet in the experimental process was irregular globular at the time of 0 ms. It is noted that the wetting predicted by simulation is a bit better than experiment results between AlSi5 and Q235 steel sheet at the time of 4 ms and 6 ms, considering the influence of roughness and oxide film on the surface of Q235 steel sheet in the process of wetting experiment. As a whole, the simulated results conform to the experimental results. In the process of droplet spreading, heat exchange takes place among AlSi5 alloy, Q235 steel, air in the fluid field. The temperature gradient of Al alloy is smaller than that of steel, due to the larger heat transfer coefficient of Al alloy. It is worth noting that the solidification firstly happens at the triple line, which is corresponding to the distribution of temperature field, as be shown in Fig. 6 (b). Numerical calculations were carried out from the WFS = 2.5 m min1 to 7.5 m min1. We compared drop profiles and corresponding solidification profiles of different WFSs at the
Table 3 Summary of welding parameters used in experiments.
*
Wetting time, s
WFS, m min1
Weld wire type
Wire diameter, mm
CTWD*, mm
Shielding gas
Shielding gas flowrate, L min1
1
6.5
ER4043
1.2
5
99.999%Ar
15
CTWD refers to contact tube to workpiece distance.
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Fig. 6. (a) Corresponding sequences of high speed video camera images and numerical simulation results and (b) contours of temperature field distribution and the corresponding solidification process at 0–10 ms.
time of 10 ms. It is obvious that the contact angle became smaller with the increase of WFS and the amount of metal solidification nearby the triple line also became less with the increase of WFS, as be shown in Fig. 7. Further, the variation tendency of both contact angle and the area of solidified AlSi5 Al alloy with the increase of WFS is almost the same, as be shown in Fig. 8. Therefore, solidified metal at the triple line may be blocked the further motion of triple line. Furthermore, the wetting behaviors of AlSi5 Al alloy on the surface of Q235 steel sheet in different WFSs were studied, as be shown in Fig. 9. The tendency of the contact angle is almost the same, and the contact angle decreased gradually with the increase of time, as be shown in Fig. 9(a). Meanwhile, the contact radius increased gradually with the increase of time, as be shown in Fig. 9(b). The contact angle and contact radius made no difference before 1 ms, and then the heat input induced different wetting behavior obviously. The influence of WFS on contact angle and contact radius is also obvious, the contact angles become smaller and the motion of triple line become faster with the increase of WFS. As the previous analysis, solidified metal at the triple line may be blocked the further motion of triple line, which is closely related to the temperature field distribution. Therefore, the variations of temperature at triple line with time for different WFSs were extracted, as be shown in Fig. 10. The tendency of temperatures of triple line in different WFSs was almost same and all temperatures of triple line in different WFSs exceeded the solidus of AlSi5 Al alloy before 1 ms, which means the advancing triple line of different WFSs was not blocked and that is why the tendency of contact angle and contact radius made no difference before 1 ms.
Fig. 8. Contact angle and AlSi5 solidified area in different WFS at 10 ms.
However, the tendency of temperatures of triple line in different WFSs became different after 1 ms and the temperature of triple line of different WFSs was all completely below the solidus of AlSi5 at the time of 3 ms. Therefore, the molten droplet at the triple line of different WFSs began to solidify and the triple line would be blocked by solidified metal, that is why the amplitude of variation of contact angle and the contact radius became smaller and smaller after 3 ms. The temperatures at triple line for different WFSs are all below the solidus of AlSi5 after 3 ms. And then the areas of solidified AlSi5 of different WFSs after 3 ms were extracted, as be shown in Fig.11.
Fig. 7. Drop profiles and the corresponding solidification profiles of different WFS at 10 ms.
Q. Lin et al. / International Journal of Heat and Mass Transfer 96 (2016) 118–124
123
Fig. 9. The wetting behavior of molten AlSi5 Al alloy on the surface of Q235 steel in different WFS: (a) variation of contact angles and (b) base radius with time.
Fig. 10. Temperature of triple line of different wire feed speed at different times.
Fig. 11. Variation of AlSi5 solidified area with time.
The amplitude variation of AlSi5 solidified areas in different WFSs after 3 ms increase with time, which results in the amplitude of variation of contact angle and contact radius became smaller and finally reached a stable state. The AlSi5 solidified area increases with time when WFS is bellow 3.5 m min1 and faster than that of WFS above 4.5 m min1. When WFS is bellow 3.5 m min1, the
Fig. 12. Variation of the advancing velocity of triple line with time.
amplitude variation of contact angle and the contact radius is smaller than that of WFS above 4.5 m min1, due to the solidified metal at the triple line would be blocked the further motion of triple line. The velocity of advancing triple line is related to both solidified metal and temperature field distribution at the triple line. Further, the velocities of advancing triple line of different WFSs at different times were extracted, as be shown in Fig. 12. The velocity of advancing triple line before 3 ms is larger than that after 3 ms, which is why the amplitude of variation of both contact angle and contact radius is much bigger before 3 ms. And the velocity of advancing triple line increases with the WFS before 3 ms, and thus the contact angle decrease and the contact radius increase with the WFS before that time. It is noted that the velocities of advancing triple line with different WFSs become steady and are almost equal to zero after 3 ms, which result in the contact angle and contact radius tend to stabilization after 3 ms. The velocity of triple line was calculated by the differentiation of the variation of contact radius with time. Capillary numbers were calculated based on equation Ca ¼ lu c1 with material properties, (l is liquid viscosity, u is contact line speed and c is liquid–vapor surface tension). Contact angle (h) of molten AlSi5 on the surface of Q235 steel sheet at the time of 10 ms were estimated from the simulation images. Simulated contact angles are plotted as a function of capillary number in Fig. 13. Ca is a temperature
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References
Fig. 13. Plot of dynamic advancing contact angle as function of capillary number.
dependent linear function [26], and the contact angles also depend to temperature as an almost linear relationship. Therefore, the clear quantitative linear relationship between Ca and h which may indicate the advancing contact line velocity was controlled by capillary force. 5. Conclusions In this work, we used both volume of fluid and solidificationmelting models to establish the wetting spreading model of molten Al alloy on the surface of steel plate and the simulation results almost consistent with the experimental results. (1) The main factor influencing the molten droplets spread out is the distribution of temperature field. Solidification happened at the triple line first, and then spread to the center of the droplet. Solidified metal nearby the triple line would hinder the spreading of the droplet to a certain extent. (2) The wettability of molten Al alloy on the surface of steel plate became better with the increase of WFS and the advancing contact line velocity may be controlled by capillary force.
Acknowledgements This work is supported by National Natural Science Foundation of China (No. 51301083), Provincial Fund for Distinguished Young Scientists (No. 1506RJDA087), Rose Willow Young Foundation of Lanzhou University of Technology (No. Q201407) and Preresearch of National Basic Research Program of China (2014CB660810).
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