Study on the Morphology, Microstructure, and Properties of 6082-T6 Aluminum Alloy Joints in MIG Welding

Abstract

In this paper, metal inert gas (MIG) welding of 6082-T6 aluminum alloy with a thickness of 4 mm was simulated using a double ellipsoidal heat source. Based on the simulation results, the evolution of the microstructure, the strengthening mechanism of mechanical properties, and the corrosion characteristics of the welded joint were studied further. The thermal cycle curve of the welded joint was obtained through numerical simulation. When the heat input was 2.34–2.75 KJ/mm, the temperature of the welded joint reached the melting point of the material. With the increase in welding heat input, the weld metal (WM) organization changed from the dendrite to the cellular crystal transformation and presented a uniform distribution. The precipitation of the strengthened phase was inhibited at 2.75 KJ/mm. When the heat input changed from small to large, the tensile strength and toughness first increased and then weakened. Dimple distribution of tensile fractures was observed with a scanning electron microscope. When the welding heat input was 2.57 KJ/mm, the mechanical properties of the joint were the best. The tensile strength can reach 76.62% of the base material, and the elongation after breaking can reach 59.38% of the base material. However, it was concluded through studying electrochemical corrosion that the corrosion resistance of welded joints under this parameter was the worst. This may be caused by the presence of Cu, Fe, Si, Mg, and other compounds, and was proven to be Mg₂Si through EDS analysis.

1. Introduction

6082-T6 aluminum alloy is light in weight, high in strength, and superior in comprehensive performance. It is widely used in railway structural parts and ships and other mechanical fields. The most important joining method for 6082-T6 aluminum alloys is welding. Common welding methods include brazing [1], pressure welding [2,3], and fusion welding [4], among which fusion welding has the advantages of high welding efficiency, strong local heating ability, high welding strength, and good microstructure properties after welding. MIG welding is the most common welding method for fusion welding. It is widely used for aluminum alloys [5], carbon steel [6], stainless steel [7], and copper [8]. MIG welding offers high welding power, high welding current, concentrated arc heat, good welding quality, and the ability to weld in a variety of positions. It is particularly suitable for welding thin and medium aluminum alloys. However, in the welding process, there are many objective “pain points” of traditional experimental methods. For example, it is difficult to accurately obtain the change trend of thermal physical property parameters in the welding process, and it is impossible to observe the stress change and temperature field in the welding process in real time. The selection of welding heat input is excessively dependent on test data and manual experience. With cross-disciplinary application, many scholars have successfully applied numerical simulation in the welding process.

Arora et al. [9] verified the effectiveness of thin-walled pipe welding through combining finite element simulations with tungsten inert gas welding (TIG) ring welding studies through continuously adjusting the welding parameters and controlling the heat input magnitude to study the effect on residual stresses. A double ellipsoidal heat source model was also derived as the most suitable heat source model. Wang et al. [10] used a two-dimensional Gaussian heat source to numerically simulate the welding stress and deformation of a 5A12 sheet, which was also verified. Balram et al. [11] performed residual stress analysis of heterogeneous tungsten alloy inert gas weldments through numerical simulations and experiments, and the results showed that the stress distribution of the tungsten alloy heterogeneous welding simulation was similar to the actual experimental pattern, but the value of the stress field was slightly larger. Mondal et al. [12] performed high-speed welding of aluminum alloy materials through three models of high-speed welding: the double ellipsoidal heat source model, the egg-shaped heat source model, and the avocado-shaped heat source model. They concluded that in the MIG welding process, for high-speed welding, the avocado-shaped heat source model obtained more accurate data, while for low-speed welding, the double ellipsoidal heat source model obtained more accurate data. To extend the service life of the Indian bicycle industry, Singh et al. [13] carried out finite element analysis of MIG welding on the pipe joints of bicycle bodies, while using a dynamic fatigue testing machine to find the area where fatigue damage occurs in the heat-affected zone of the weld through finite element software, and to verify that the results of the finite element analysis and the experimental results are in high agreement. Selvamani [14] used a new welding technique called cold metal transfer welding to weld galvanized steel while using ANSYS simulation software for welding simulation. The results show that CMT butt welding leads to better mechanical properties of the joint than traditional welding. Sun et al. [15] used the VPPA-GMAW hybrid welding method for 7A52 aluminum alloy thin plates. Through controlling the heat input and melt drop kinetic energy for the study, combined with numerical simulation of the weld shape, melt pool shape, and heat cycle structure, the experimental results match. Using ANSYS simulation, the experimental results and the actual experimental results have a high degree of consistency. Fang et al. [16] used laser powder deposition to prepare an alloy with higher yield strength, tensile strength, and elongation than the alloy produced via the other method. The constitutive model of evolution was also established by means of numerical simulation. Finally, it was found that the mechanical properties of the alloy could be adjusted via this technique. Chen et al. [17] conducted a comprehensive examination of the impact of heat input on the propensity for crack formation in weld seams. Through using laser welding to weld dissimilar metals such as the NiTiNb shape memory alloy and the Ti₆Al₄V alloy, each with thickness of 0.2 mm, it was found that the TiNi phase was the main contributor to crack formation and a brittle cleavage fracture within the structure. Further work by Chen et al. [18] demonstrated how heat treatment on a welded joint improved its mechanical properties. They concluded that the emergence of the Ni₃Ti phase played a crucial role in this enhancement. After post-treatment, the joint structure was more uniform, and the joint’s strength increased by 212%. Presently, only a limited number of studies exist on the performance improvement of 6082-T6 welded joints. Through simulating the MIG welding of 6082-T6 aluminum alloy using a double ellipsoidal heat source, deeper insights were gained into the microstructural evolution, mechanical property enhancement mechanisms, and corrosion characteristics of welded joints. The results had a certain theoretical significance for the application of the 6082-T6 aluminum alloy in railway structural parts and ship hulls.

2. Experimental Materials and Methods

2.1. Experimental Parameters

The MIG welding working principle is visually explained in Figure 1, while Figure 2 provides a schematic representation of MIG welding. Argon gas (99.99%) was used for welding protection; the welding gap was 0.5 mm and the wire diameter was 1.2 mm. The detailed welding parameters can be referred to in

Table 1. Welding parameters.

Test	Welding Current (A)	Welding Voltage (V)	Welding Heat Input (KJ/mm)	Welding Speed (mm/s)	Argon Flow Rate (L/mm)
1	150	19.5	2.34	10	20
2	155	19.9	2.46	10	20
3	160	20.1	2.57	10	20
4	165	20.9	2.75	10	20

, with the heat input calculated as indicated in reference [15].

$$Q=UI\eta /v$$

(1)

where Q is the heat input, U is the welding voltage (V), I is the welding current (A), v is the welding speed (mm/s), and η is the welding efficiency. In MIG welding, η is 0.8 [19].

2.2. Materials

The base metal (BM) used in this research was the 6082-T6 aluminum alloy, which has a melting point temperature of approximately 630 °C. Then, the dimensions of the base material were selected as 100 mm × 300 mm × 4 mm. The chemical compositions of the 6082-T6 aluminum alloy and the welding wire (ER5356 of series 5) used in this study are elaborated in

Table 2. Chemical compositions of materials (wt%).

Materials	Si	Mn	Mg	Cu	Zn	Ti	Fe	Zr	Al
6082-T6	1.00	0.56	1.00	0.03	0.166	0.03	0.50	0.0002	Bal.
ER5356	0.06	0.82	5.03	0.01	0.01	0.09	0.28	0.10	Bal.

. Performing temperature field simulations necessitated thermal physical parameters at varying temperatures, encompassing material density, thermal conductivity, and specific heat capacity. Figure 3 presents the temperature and associated performance parameters based on references [20,21], in addition to data from the material property simulation software JMATPRO.

Considering the heat loss caused by heat convection, heat radiation and other factors in the welding experiment, the heat loss coefficient was incorporated into the simulation for correction [22].

2.3. Experimental Procedure and Test Methods

Subsequent to MIG welding, the tensile specimens and microstructure specimens were cut using a wire cutting machine. For mechanical properties, cuts were obtained in alignment with the ASTM E B557M-15 standard [23] as shown in Figure 4. Tensile strength and elongation were tested using a tensile testing machine. The Vickers microhardness tester was used to measure point by point from the center line of the weld to the BM. The applied load was 0.5 kgf, with a point spacing of 0.5 mm and a dwell time of 10 s. For microstructural examination, a specimen of 15 × 15 mm size was cut out, with the weld as the center line. The specimens were then sequentially sanded with papers of 180, 400, 800, 1000, 1200, 1500, and 2000 grit. The ground surface was mechanically polished and etched for 20 s using an etching reagent in compliance with the ASTM E 407-99 standard [24], which consisted of 1 mL HF + 200 mL H₂O. The melt pool morphology and microstructure were examined using an optical microscope (OM). Scanning electron microscopy (SEM) at an accelerating voltage of 10 KV was used to observe the BM post-pull-off and the fracture morphology of the joint under varying parameters.

The corrosion resistance of the weld zone was assessed using an electrochemical workstation. The three-electrode method was adopted to perform corrosion tests on the weld area of the welded joint. A platinum electrode was chosen as the auxiliary electrode, and a saturated sugar acid electrode was chosen as the reference electrode. The sample from the weld zone was cut off as the working electrode, possessing a working area of 0.24 cm², and the epoxy resin was embedded, as illustrated in Figure 5. Under the deoxidation condition at 25 °C, using a 3.5% NaCl solution, the scanning potential range was −1.4~−0.5 V, and the scanning speed was 1 mV/s.

3. Numerical Simulation

3.1. Basic Equations of Heat Transfer

The fundamental law of heat transfer [25] contains the law of heat conduction, the law of heat convection, and the law of heat transfer via radiation, also in accordance with Fourier’s law of heat transfer. Equation (2) is the heat transfer equation.

$$\frac{Q}{t}=\frac{\lambda A\left(T_1-T_2\right)}{d}$$

(2)

where Q is the heat transferred in time t (s), λ is the thermal conductivity, T is the temperature, A is the heat transfer area and d is the distance.

Equation (3) is the thermal convection equation.

$$q_{\alpha }=-h_{\alpha }\left(T_S-T_{\alpha }\right)$$

(3)

where q_α is the convective heat transfer flow rate, and h_α is the convective heat coefficient. T_s is the surface temperature of the weld. T_α is the room temperature.

The radiative heat exchange between objects can be described using the Stephen Boltzmann Equation (4).

$$q_r=-{\epsilon }_{\theta }\sigma \left(T_S^4-T_{\alpha }^4\right)$$

(4)

where q_r is the radiant heat flow rate, ε_θ is the radiation coefficient, and σ is the Stephen Boltzmann constant.

3.2. Heat Source Model

MIG welding is capable of welding in a variety of positions, with high localized heat energy and commendable welding efficiency. Because of the large gradients in the temperature field of welding in time and space, the selection of the heat source model in the finite element welding simulation critically impacts the welding outcomes. Based on the weld’s geometry, the heat source can be simplified in three ways: faceted, linear, and spotted.

$$q\left(r\right){=q}_m\mathit{exp}-\left(\frac{3r^2}{R^2}\right)$$

(5)

The Gaussian heat flow distribution function distributes the heat source as a Gaussian function over a certain range. The heat flux density from the central spot of heating can be expressed in subsequent sections.

$$q_m=\frac{3Q}{\pi R^2}$$

(6)

where q_r is the heat flow density at any point of the equation, q_m is the maximum heat flow density at the center of the heated spot, R is the effective heating radius of the arc, r is the distance from the arc heated spot at any point, and Q is the effective power of the welding heat source. Figure 6 provides a schematic representation of the Gaussian heat source model.

The double ellipsoidal heat source model models the first half as a quarter ellipsoid with an energy fraction of f₁. The second half of the model is modelled as another quarter model with an energy fraction of f₂.

The distribution of heat sources within the front part of the ellipsoid is given by

$$q\left(f\right)=\frac{12\sqrt{3}Q}{{\pi }^{\frac{3}{2}}\mathit{bc}\left(a_f{+a}_r\right)}\mathit{exp}\left\{-3\left({\left(\frac{x}{a_f}\right)}^2+{\left(\frac{y}{b}\right)}^2+{\left(\frac{z}{c}\right)}^2\right)\right\}$$

(7)

The distribution of heat sources within the rear part of the ellipsoid is given by

$$q\left(r\right)=\frac{12\sqrt{3}Q}{{\pi }^{\frac{3}{2}}\mathit{bc}\left(a_f{+a}_r\right)}\mathit{exp}\left\{-3\left({\left(\frac{x}{a_f}\right)}^2+{\left(\frac{y}{b}\right)}^2+{\left(\frac{z}{c}\right)}^2\right)\right\}$$

(8)

where q(f) and q(r) are the volumetric heat flow density before and after the model, respectively, and Q is the total introduced power; a_f, a_r, b, and c are the length, width, and depth before and after the predicted melt pool, respectively. Figure 7 provides a visual representation of the model.

3.3. Mesh Models

The mesh size for the proposed simulation was based on the size of the base material, and the mesh size for the weld seam and its vicinity was 1 mm × 1 mm. The weld was located ±20 mm lengthwise to the edge of the base material, the grid size increased by 10% every 15 mm. This ensures both the accuracy and volume of the calculation. Finally, after meshing the entire model, the model was divided into mesh cells.

4. Results and Discussion

4.1. The Morphologies of MIG Welds under Varying Heat Inputs

Figure 8 and Figure 9 illustrate the morphologies of the MIG welds and the cross section of the welded joint under different heat inputs. The heat input had a strong influence on the morphologies of the MIG welds and the shape of the melt pool. When the heat input was 2.34 KJ/mm, the weld had obvious defects. There was no penetration at the bottom of the workpiece, and the lower temperature of the molten pool did not reach the melting point of the material. The fact that the fusion line was only partially visible was further proof that the aluminum alloy could not be welded through at this parameter. When the heat input was increased to 2.46 KJ/mm, the front side of the weld was well shaped, the fusion line and the residual height were clearly shown, the front side of the weld appeared as an irregular fish scale, and the back side of the weld was discontinuous. Upon reaching a heat input of 2.57 KJ/mm, the weld showed no discernible welding defects, such as porosity, cracks, or interruptions. The fusion line was most clearly shown, the weld was well shaped, and the weld profile was smooth. When the heat input increased to 2.75 KJ/mm, a portion of the weld pool collapsed. The weld surface was rough, and a weld tumor emerged on the back side. Because the energy was seriously dissipated, the stability and continuity of the molten drop transition decreased, and the shape of the fusion line changed [26]. These observations reveal that at a heat input of 2.57 KJ/mm, the shape of the weld seam and the shape of the molten pool meet the actual requirements.

4.2. Validation of Simulation Results

4.2.1. Heat Source Model Validation

Table 3. Comparison of morphology of heat source models.

Name	Molten Pool Morphology	Celsius Degree
Gaussian heat source model
Double ellipsoid heat source model
Actual heat source model

compares the shape of the molten pool obtained via the double ellipsoidal heat source model and the Gaussian heat source model with the actual shape of the molten pool, which clearly showed that the simulation results using the double elliptic heat source model were accurate. This was because the Gaussian heat source in the welding simulation overlooked the weld’s longitudinal heat flow, which caused large errors when the welding speed was 10 mm/s (which was a low-speed weld). In contrast, the double ellipsoidal heat source model effectively addressed the problem of temperature gradients during the simulation [27].

4.2.2. Thermal Cycle Curve Verification

We aimed to gain a deeper understanding of the temperature change characteristics at the thickness interface, perpendicular to the direction of welding velocity. From the weld center to the fusion line, five nodes were selected every 1 mm as thermal cycle curve observation points. Additionally, they were named points 1–5. We performed an analysis of the temperature distribution and variation characteristics during MIG welding of the 6082-T6 aluminum alloy. The thermal cycle curves for these points are shown in Figure 10. When the heat source reached a selected point, the temperature of the point rapidly increased and the slope of the temperature curve sharply increased, resulting in a sharp climb in the temperature curve. After the temperature reached the maximum, the slope of the temperature curve became smaller because of air and other factors for cooling, which led to a decrease in the temperature curve and a rapid decrease in temperature. The temperature of the weld point reached a peak value higher than the melting point of the 6082-T6 aluminum alloy, thereby ensuring complete melting of the workpiece. Figure 10 demonstrates that under the same welding parameters, all five points reached peak temperature at the same time, the peak welding temperature decreased with increasing distance from the welding center, and the heat transfer diminishes with increasing distance from the welding center.

4.3. Microstructure Analysis

The welding zone comprised the WM, the heat affected zone (HAZ), and the BM. The heat input to the weld had a significant effect on the microstructure of the aluminum alloy. Figure 11a depicts the microstructure of the 6082-aluminum alloy base material, with the BM region featuring a matrix phase and uniformly distributed grains along the rolling direction. Since the main added elements of aluminum alloys are magnesium and silicon, the main strengthening phase was Mg₂Si. The white part of the diagram was the α-AL solid solution, and the black dots indicate the reinforced phase.

In the HAZ, an unfused base material subjected to the welding thermal cycle, the formation of properties and microstructure was different from the BM and the WM. Its microstructure was mainly related to the thermal cycle, leading to the dissolution and precipitation of the second phase. The HAZ was affected by strong thermal cycling, and recrystallization occurred. The fibrous organization disappeared, coarse irregular dendrites appeared, small diffuse phases precipitated between the grains, and the reinforcing phase was more uniformly distributed. As depicted in Figure 11b–d, certain black spots for the welding process are broken oxide in the flow of the state in a non-uniform distribution, due to the formation of locally dense distribution and the formation of oxygen-rich areas after corrosion to black. The precipitation of Mg₂Si increased with greater heat input; however, excessive heat input inhibited the precipitation of Mg₂Si.

The WM region represents where the filler wire fuses and crystallizes with the substrate. As illustrated in Figure 11e–h, the phase composition of the aluminum alloy WM is dominated by α-AL solid solution. The microstructure and distribution are significantly influenced by varying heat inputs. With insufficient heat input, the arc is shortened, the energy is concentrated, the molten pool narrows, the trend of dendrite growth becomes pronounced, and the dendrite rapidly develops from the fusion line to the weld center, demonstrating a coarse morphology. When the heat input increases to 2.57 KJ/mm, the growth of dendritic crystals is inhibited, resulting in a more cell-like appearance in the WM crystals, which distribute uniformly. Excessive heat input causes a large temperature gradient during cooling, seriously affecting the precipitation of the Mg₂Si strengthening phase and leading to the deterioration of the joint’s mechanical properties under these welding parameters.

4.4. Mechanical Performance Tests

4.4.1. Hardness Distribution of Welded Joints

A hardness test was performed on welded joints with welding heat inputs of 2.46 KJ/mm, 2.57 KJ/mm, and 2.75 KJ/mm. The data acquired was utilized in Origin to produce a micro-hardness distribution diagram of welded joints, as displayed in Figure 12.

As can be observed from the microhardness distribution diagram, the hardness distribution across the welded joints is not uniform. For each parameter, there is a slight increase in microhardness from the weld’s center to near the fusion line, followed by a sudden increase at the fusion line. This abrupt increase is attributed to either the refinement of solid solution grains or the inhibition of the strengthened phase’s precipitation. The farther the distance from the fusion line to the weld center, the more gradual the decrease in the joint’s hardness. A zone of low hardness appears 9.5–10.5 mm from the weld. The welding thermal cycle curve suggests that the temperature here did not reach 500 °C during the welding process, failing to meet the phase precipitation temperature. Nonetheless, after a period of standing, some reinforcing phases accumulated and grew, resulting in a diminished strengthening effect. When the welding heat input ranged between 2.46–2.57 KJ/mm, the hardness distribution of the welded joint was similar. However, when the welding heat input increased to 2.75 KJ/mm, the WM hardness of the welded joint and the HAZ hardness near the fusion line visibly decreased. Considering the experimental results obtained from the microstructure, it can be concluded that the larger the quantity of reinforced phase precipitation, the greater the Vickers hardness value of the welded joint. Therefore, in order to obtain a welded joint with a large hardness value, the amount of precipitation in the strengthened phase should be maximized.

4.4.2. Tensile Properties of Welded Joints

Table 4. Mechanical properties data for MIG welding of 6082-T6 aluminum alloy.

Test	Welding Speed (mm/s)	Welding Current (A)	Tensile Strength (MPa)		Elongation (%)
			Single Value	Average Value	Single Value	Average Value
BM-1			294.59	289.88	20	19.2
BM-2			285.17		18.4
2.46-1	10	155	115.84	127.09	5.7	5.85
2.46-2	10	155	138.33		6
2.57-1	10	160	218.34	222.09	10.8	11.4
2.57-2	10	160	225.83		12
2.75-1	10	165	132.92	129.59	6.4	6
2.75-2	10	165	126.25		5.6

reveals that the base material boasts a tensile strength of 289.88 MPa and an elongation after fracture of 19.2%, significantly surpassing all other parameters post-welding. The mechanical properties of the welded joints vary considerably with different heat inputs. At a heat input of 2.46 KJ/mm, the mechanical properties of the welded joints were inferior to those of the base material. This was due to inadequate heat, causing the weld zone’s temperature to not fully reach the melting point. As a result, only partial melting occurred, leading to subpar joint performance. Minimal tensile force was sufficient to dislodge the specimen, and the brief tensile time also accounted for minimal elongation. As the welding heat input rose to 2.57 KJ/mm, the weld area completely melted and the joint performance improved correspondingly with the increased heat input. Tensile strength increased from 127.09 MPa to 222.09 MPa. This was because the tensile time became longer, the elongation after break increased from 5.85% to 11.4%, and the performance of the welded joint improved significantly. When the welding heat input was increased to 2.75 KJ/mm, the heat input at this time was too large, resulting in the collapse of the weld; the quality of the weld was reduced. The tensile strength at this time decreased by 92.5 MPa, and the post-break elongation also dropped by 5.4%. In summary, the mechanical properties of the welded joints were optimal at a welding heat input of 2.57 KJ/mm. As Figure 13 shows, as heat input rose, the strength and plasticity of the welded joints initially increased, then declined.

4.4.3. Tensile Fracture Analysis

The microscopic image of the fracture, as shown in Figure 14, reveals that as the welding heat input increased from 2.46 KJ/mm to 2.57 KJ, the fracture was characterized by an equiaxial dimple whose size was like the BM. The toughness of the fracture significantly increased, and the toughness of the fracture was also the best. When the heat input rose to 2.75 KJ/mm, the size of the fracture dimple became coarse and local tearing occurred, which also led to a significant reduction in toughness. This observation, in conjunction with the elongation results after breaking in Table 4, further verifies that the mechanical properties of the welded joint are superior when the heat input reaches 2.57 KJ/mm compared to other parameters.

4.5. Electrochemical Corrosion Properties

Table 5. Characteristic parameters of polar chemical curves.

Welding Heat Input (KJ/mm)	Ecorr (V)	Icorr (A/cm2)
2.46	0.923	3.40 × 10−7
2.57	−1.169	6.60 × 10−6
2.75	−0.917	3.37 × 10−7

presents the electrochemical corrosion parameters ascertained from polarization curves, with I_corr calculated using the extrapolation method. In general terms, a more positive E_corr value denotes superior corrosion resistance [28]. As depicted in Figure 15, the corrosion resistance of the joint initially deteriorated, then improved as the welding heat input increased. At a welding heat input of 2.57 KJ/mm, the corrosion resistance of the joint was the worst, and when the welding heat input was 2.75 KJ/mm, the corrosion resistance of the joint was the best. From a dynamic perspective, a higher Icorr is correlated with a faster corrosion rate. As illustrated in Table 5, when the welding heat input reached 2.57 KJ/mm, the corrosion rate was quickest, and the corrosion resistance was weakest. When the heat input reached 2.75 KJ/mm, the corrosion rate slowed, and the corrosion resistance increased.

Figure 16 shows the micro-morphologies of pitting pits in the weld zone under varying welding heat inputs. It is evident that when the welding heat input was 2.57 KJ/mm, the pitting area was most widespread, and the pitting area was at its largest under this parameter. This observation corroborates the fact that the joint had the weakest corrosion resistance under this parameter. Figure 17 displays the layered image of EDS in the red box area of Figure 16a and the dot sweep energy spectrum of the rectangular area. The figure reveals that the black phase surrounding the pitting pit was the enrichment of Mg and Si elements, while the white phase was the enrichment of Fe, Si, and Cu elements. According to the analysis and prior studies, the black Mg₂Si phase was the strengthening phase, while the white phase was the Al₃Fe phase, Cu compound, and elemental Si. The Mg₂Si hardening phase was the key factor impacting the corrosion performance of welded joints.

Given that the Mg₂Si-enhanced phase possesses the lowest self-corrosion potential, it first acts as the anode to be corroded during the immersion process. When the Mg₂Si-enhanced phase was corroded, the Mg element was preferentially corroded, leaving the remaining Si element in the corrosion pit. The self-corrosion potential of Si is higher than that of the Al matrix, thus serving as the cathode to accelerate the corrosion of the surrounding the Al matrix during the corrosion process.

Table 6. Self-corrosion potential of precipitated phases in aluminum alloys.

Si [31]	Mg2Si [32]	Al [33]
−0.26	−1.54	−0.5

displays their self-corrosion potential. Therefore, the greater the precipitation of the Mg₂Si-reinforced phase, the weaker the corrosion resistance of the welded joints [29,30]. As a result, at a welding heat input of 2.57 KJ/mm, the corrosion resistance of the welded joint was at its weakest.

5. Conclusions

Using simulated and experimental analysis, this paper studied the influence of heat input on the macro-morphology, mechanical properties, and microstructure of MIG-welded joints as well as the change in corrosion resistance of these welded joints. The selection range of welding heat input was accurately obtained via numerical simulation, ranging from 2.46 KJ/mm to 2.75 KJ/mm, and the actual macro-morphology of the weld was also verified. Two sets of stretching were carried out on the sample of each parameter during the tensile property test, the displacement was measured using a 0.5 class extensometer, and the fracture was observed. The hardness of the welded joint was tested manually. In the same way, two sets of tests were carried out for each parameter, and the obtained data were averaged for analysis. Then, samples of microstructure and electrochemical corrosion were prepared and observed. The evolution mechanism of the microstructure, mechanical properties, and corrosion resistance was found, and the specific conclusions are as follows [34]:

• In the weld’s shape, when the heat input was 2.34 KJ/mm, there were obvious defects in the weld. When the heat input increased to 2.57 KJ/mm, the weld shape was the best, and there were no defects such as porosity, cracks, or false welds present.
• In terms of numerical simulation, a Gaussian heat source model and a double ellipsoid heat source model were used, and by comparison, the use of a double ellipsoidal heat source provides an accurate characterization of the actual weld, while the thermal cycle curve shows the temperature variation of the welded joint. When the heat input was 2.34 KJ/mm, the temperature at points 4–5 did not reach the melting point of the material, which was also consistent with the actual welding situation. When the heat input continued to increase, the temperature of the points farther away from the weld also increased, and the melting point of the material was reached. The trend of the thermal cycle temperature curve was also consistent with previous research results.
• In terms of microstructure, the BM was mainly composed of an Al matrix and Mg₂Si strengthening phases, with the strengthening phases being evenly distributed. When the heat input was 2.34–2.75 KJ/mm, the microstructure of the WM and HAZ underwent different changes. In the WM, with a heat input of 2.34 KJ/mm, it presented dendrite distribution and disorganization. When the heat input was 2.57 KJ/mm, the dendrite was transformed into cell crystalline, which was because the growth of the dendrite was inhibited by the large heat. When the heat input was further increased to 2.75 KJ/mm, the growth of cellular crystals was significantly inhibited. These observations suggest that excessive heat input can inhibit the precipitation of the strengthening phase, and the microstructure distribution of the HAZ can also prove this conclusion.
• In terms of the microhardness of mechanical properties, the overall trend for each parameter displayed a slight increase in microhardness from the center of the weld to near the fusion line, followed by a sudden increase in hardness at the fusion line. As the distance from the weld increases, the greater the hardness. However, based on the microstructure analysis, it can be concluded that the greater the precipitation of the strengthening phase, the greater the hardness of the material.
• The BM has the best tensile strength and elongation after the break. When heat input increased from 2.34 KJ/mm to 2.57 KJ/mm, the tensile strength was increased by 95 MPa, and the elongation after breaking was increased by 5.55%. However, when the heat input was raised to 2.75 KJ/mm, the tensile strength and elongation after fracture decreased by 92.5 MPa and 5.4%, respectively. At a heat input of 2.57 KJ/mm, the tensile strength constituted 76.61% of that of the base material, while the elongation at break was 59.38% of the base material. With the change of heat input from small to large, the strength and plasticity of the welded joints first increased and then decreased. This conclusion was also verified through the observation of a tensile fracture. Combined with the microstructure analysis, it becomes evident that the greater the amount of Mg₂Si precipitation, the greater the tensile strength and the higher the post-fracture elongation.
• When the welding heat input was 2.57 KJ/mm, the Ecorr value was −1.169 V, and the Icorr value was 6.60 × 10⁻⁶ A/cm², indicating the worst corrosion resistance. It was also confirmed that an increase in Mg₂Si precipitation correlates with decreased corrosion resistance.