Experimental and Finite Element Analysis of Refill Friction Stir Spot Welding in Dissimilar 6061-T6 and 5052-H321 Aluminum Alloys

Abstract

This study presents an integrated experimental and numerical investigation of the Refill Friction Stir Spot Welding (RFSSW) process applied to dissimilar aluminum alloys. The primary objective is to evaluate the mechanical and thermal behavior of the joints and to identify key process parameters influencing weld quality. Experimental welding trials were performed on aluminum alloy sheets using RFSSW, followed by shear testing and metallographic analysis to assess joint integrity, microstructure evolution, and fracture behavior. Infrared thermography and temperature sensors were employed to monitor heat distribution during welding. In parallel, a finite element model was developed to simulate the thermal cycle and stress distribution within the welded region. The numerical results showed good agreement with the experimental data, particularly regarding peak temperature and cooling trends at specific distances from the tool center. The findings demonstrate that RFSSW can successfully join dissimilar aluminum alloys with minimal defects when optimized parameters are applied. The combination of experimental observations and FEM simulation provides valuable insights into the underlying thermomechanical phenomena and offers a foundation for further process optimization.

1. Introduction

Refill Friction Stir Spot Welding (RFSSW) is an advanced variant of the conventional Friction Stir Spot Welding (FSSW) method. Unlike the traditional method, RFSSW does not leave an exit hole in the material, making it preferable for structural applications where component integrity is crucial. The RFSSW process was first introduced and patented by Schilling and Dos Santos in 2002, who developed a method and device for joining at least two workpieces using friction welding principles (U.S. Patent 0179 682, 5 December 2002) [1].

Joining dissimilar aluminum alloys such as 6061-T6 and 5052-H321 using the RFSSW technique enables the combination of complementary properties, such as high strength and superior corrosion resistance, within a single lightweight structure. This type of joint is particularly valuable in the automotive and aerospace industries, where optimizing structural performance while reducing weight is essential. Previous studies have demonstrated the feasibility and reliability of RFSSW for dissimilar aluminum alloys, confirming its utility in advanced manufacturing applications.

Compared with conventional joining methods such as Resistance Spot Welding (RSW), Friction Stir Spot Welding (FSSW), or fusion-based techniques (MIG/TIG), the Refill Friction Stir Spot Welding (RFSSW) process provides several key advantages. It eliminates the keyhole defect typical of conventional FSSW, reduces residual stresses, and minimizes the extent of the heat-affected zone due to lower thermal input. Moreover, RFSSW enables the joining of dissimilar aluminum alloys without the need for filler material or shielding gas, making it an energy-efficient and environmentally friendly process. The refill mechanism also ensures complete consolidation of the stirred material, leading to joints with higher mechanical strength, improved surface quality, and extended fatigue life. These advantages explain the increasing industrial adoption of RFSSW in the automotive and aerospace sectors.

The parameters of the RFSSW process—such as tool rotational speed, dwell time, and plunge depth—play a crucial role in determining the mechanical properties and final microstructure of the joints. It has been demonstrated that a moderate increase in dwell time leads to a larger stir zone and reduces internal defects, such as pores and structural inhomogeneities. However, excessive increases in welding duration may expand the heat-affected zone (HAZ), thus decreasing the hardness and mechanical strength of the final joint.

Combined experimental and numerical analyses have allowed researchers to better understand the influence of process parameters on mechanical strength and the residual stress state in the joint area. Consequently, optimal parameters have been clearly identified, leading to more robust joints with enhanced fatigue performance under cyclic loading conditions.

The stages of the RFSSW process are the following, as can you see in Figure 1. In stage 1, the preheating phase, the rotating tool contacts the surface of the workpieces, generating frictional heat through controlled rotation. The generated friction heats and softens the material locally, preparing the workpieces for subsequent penetration and mixing. In plunging phase, stage 2, the rotating tool assembly, composed of a sleeve and pin, plunges into the softened material due to the frictional heat and mechanical pressure that cause material plasticization, creating a stirred zone and enabling intimate bonding between overlapping sheets. During the refilling phase, stage 3, the rotating components of the tool move relative to each other in a controlled manner, redistributing plasticized material into the cavity initially formed by the plunge step. This eliminates any voids or exit holes and produces a flush and structurally sound joint. Finally, during the retreating phase, stage 4, the tool is retracted from the joint region. During retreating, rotation stops, and the tool is carefully withdrawn, allowing the joint to consolidate and cool under controlled conditions. This final step ensures optimal mechanical properties and minimal residual stress within the welded joint.

To date, extensive research on the RFSSW process has addressed the influence of key welding parameters—such as rotational speed, dwell time, and plunge depth—on joint strength and the resulting microstructures in aluminum alloy joints.

The study by Xu et al. [3] investigates the refill friction stir spot welding of 5083-O aluminum alloy, focusing on process parameters, microstructural evolution, and mechanical performance of the resulting joints. As a derivative of conventional FSSW, RFSSW offers distinct advantages, as it eliminates common limitations such as the loss of effective bearing area and corrosion issues associated with the presence of a keyhole.

Studies investigating the bonding ligament and tensile-shear properties [4,5] have shown that the bonding ligament represents a weakly bonded region at the lap interface. When this ligament is continuous, it can negatively affect the tensile-shear strength of the RFSSW joint by facilitating annular crack propagation and promoting plate separation through a shear failure mode.

The aluminum alloys studied in the RFSSW process were from the 5xxx [6,7], 6xxx [8,9,10,11] and 7xxx [12,13] series.

Homola et al. [14] concluded that RFSSW joints made with anodized, primed, and sealed aluminum semi-products demonstrate a higher fatigue limit but exhibit greater scatter and variability in fatigue performance compared to bare joints. Although bare material joints showed higher ultimate static strength, the surface-treated configurations offer improved durability under cyclic loading conditions.

Tier et al. [15] demonstrated that plunge depth and rotational speed are the key parameters affecting RFSSW joint quality in 5042 aluminum alloy, with lower rotational speeds increasing bonding ligament length and shear strength, while higher speeds lead to reduced joint performance due to vertical material flow and shorter bonding ligaments.

Studies have shown that welding parameters have a significant impact on the thermal cycle during FSW, and in heat-treatable aluminum alloys, the precipitates may either coarsen or dissolve into the aluminum matrix depending on the alloy composition and peak temperature reached [16,17].

Nam et al. [18] highlighted that the distribution of precipitates and substructures is a critical factor in heat-treatable aluminum alloys, as it significantly influences hardness, corrosion sensitivity, and other key material properties.

The two studies [19,20] conclude that the mechanical performance and failure modes of friction-based spot welds in high-strength aluminum alloys are strongly influenced by microstructural changes resulting from thermal cycles and process parameters such as plunge depth, with post-weld aging and defect control playing key roles in joint optimization.

Recent studies on RFSSW of high-strength aluminum alloys have shown that joint performance is influenced by tool geometry, rotational speed, plunge depth, and microstructural evolution including grain morphology, precipitate distribution, and softened zones. While mechanical properties such as tensile-shear strength improve with optimized welding parameters and novel tool designs, corrosion resistance is primarily governed by the continuity of intergranular nano-precipitates, highlighting the need for balanced optimization of both mechanical and environmental performance in RFSSW joints [21,22,23].

Chen et al. [24] concluded that applying the suspension rotating process (SRP) in RFSSW significantly enhances the mechanical performance of alclad 7050/2524 joints by promoting better mixing between the base alloy and the alclad layer, resulting in a 30% increase in tensile shear strength.

However, despite the increasing use of Refill Friction Stir Spot Welding (RFSSW) in industrial applications, the relationship between process parameters, the thermal field, and the resulting joint strength in dissimilar aluminum alloys remains insufficiently understood. Therefore, the present study aims to investigate how the main process parameters, tool plunge depth, rotational speed, and welding time, influence the thermal distribution and mechanical behavior of RFSSW joints between AA6061-T6 and AA5052-H321 aluminum alloys.

To achieve this objective, both experimental measurements and finite element simulations were conducted, allowing for a direct correlation between the temperature field evolution and the mechanical performance of the joints.

2. Materials and Methods

The materials used in the experiment were two aluminum alloys: 6061-T6 and 5052-H321. The plates, with dimensions of 100 × 100 × 2 [mm], as can you see in Figure 2, were supplied by the Goodseller2024 Tool Material Store, and their chemical compositions are presented in

Table 1. Chemical composition of materials [wt%].

	Al	Mg	Si	Fe	Cu	Cr	Ti	Mn	Zn
AA 5052-H321	96.83	2.5	0.12	0.2	-	0.25	-	0.1	-
AA 6061-T6	96.9	0.9	0.7	0.5	0.28	0.2	0.12	0.3	0.1

. The chemical compositions presented in Table 1 are expressed in weight percent (wt%).

The composition of AA 5052-H321 is based on the standard ASTM B209, which defines the nominal ranges for Al–Mg alloys in the 5xxx series and the composition of AA 6061-T6 is based on ASTM B209 and Aluminum Association Alloy Designations, representing typical nominal values for the alloy in the T6 temper condition. The welding tool (high speed steel) consisted of a pin with a diameter of 6 [mm], a sleeve with a diameter of 9 [mm], and a blankholder with a diameter of 16 [mm]. The parts to be welded were cleaned using abrasive paper to remove the oxide layer, followed by alcohol to eliminate oil and micro-impurities from the surface.

The RFSSW process was carried out using a custom-built RFSSW machine.

The welding parameters were selected based on preliminary tests, which indicated that optimal joint quality is achieved when the plunge and withdrawal times are equal, with no dwell time between them. It was determined that the total welding time (including dwell and withdrawal phases) must be at least 4 s for sufficient material plasticization to occur and ensure a proper joint.

A welding time shorter than 4 s results in inadequate plastic deformation, while a welding time exceeding 6 s can lead to excessive expansion of the heat-affected zone (HAZ), potentially weakening the base materials. Moreover, prolonged welding time reduces the overall economic efficiency of the process. Therefore, the total welding time used in this study ranged between 4 and 6 s, with an increment of 0.4 s.

Multiple welding trials were conducted with sleeve penetration depths ranging from 2.2 to 2.6 [mm], in steps of 0.1 [mm]. Correspondingly, tool penetration speeds varied between 22 and 42 [mm/min]. Additionally, tests were performed with varying tool rotation speeds, from a minimum of 1800 [rpm] to a maximum of 2400 [rpm], in 100 [rpm] increments. Based on the range of parameters considered, a total of 210 welding cases were evaluated. The process parameters and their corresponding ranges used in this study are summarized in

Table 2. Variation in process parameters.

Plates Thickness [mm]	Speed [rpm]	Pin Diameter [mm]	Penetration Depth [mm]	Welding Time [s]	Penetration Speed [mm/min]
2	1800–2400	6	2.2–2.6	4–6	22–42

.

A K-type thermocouple was embedded in the upper sheet, positioned 5 [mm] from the axis of rotation of the pin, on the top surface of the upper sheet, ensuring it did not come into contact with the welding tool. The temperature evolution during the welding process was recorded by the thermocouple at 400 [ms] intervals using the BTM-4208SD data acquisition system. The temperature measurement system was used to record the thermal cycle during the welding process, as shown in Figure 3.

After welding, a rectangular metallographic sample was extracted from the center of the joint, along the diameter.

Using an optical microscopy Carl Zeiss Jena Citoval 2 stereo microscope with imaging analysis method, a series of detailed aspects were highlighted such as: crystalline grain boundaries, thermo-mechanical zones resulting from the welding process, the joint area of the two plates as well as the defects that appeared in the joint. For this analysis, the specimen was prepared metallographically by going through the following stages: mechanical grinding, polishing and metallographic etching.

The sample was etched using Keller’s reagent (1 [mL] HF + 1.5 [mL] HCl + 2.5 [mL] HNO₃ + 95 [mL] H₂O) for 10 s, after which the macroscopic grain structure was examined under the optical stereo microscope.

For the infrared thermographic analysis, the InfiRay P2 Pro Thermal Camera for Android (USB Type-C) was employed, with a temperature range from −20 [°C] to 550 [°C].

For shear test analysis was employed universal testing machine Instron model no. 8850. The specimens were tested at room temperature with a crosshead speed of 1 mm/min.

3. Finite Element Modeling

For the present research, the commercial software package Simufact Forming version 16.0 [25] (Simufact Engineering GmbH, Hamburg, Germany) was used to develop a two-dimensional axisymmetric finite element model for simulating the RFSSW process.

The model employed a fully coupled thermomechanical approach, enabling the simultaneous calculation of temperature and strain at each time step.

The material properties (as presented in

Table 3. Mechanical properties.

Material	Yield Stress Rp0.2 [MPa]	Ultimate Tensile Stress, Rm [MPa]	Elongation at Fracture, A [%]	Melting Point, Tm [°C]
6061-T6	276	310	12	582–652
5052-H321	193	228	12	607–649

) were sourced from the Simufact Forming materials database and correspond to a temperature and strain-rate-dependent material model based on the MatiLDa database, a registered trademark of Gesellschaft für Metallurgische Technologie- und Softwareentwicklung GmbH (Berlin, Germany).

The mathematical model, Equation (1) [25], describing the material’s behavior is as follows:

$${\sigma }_F=C_1·e^{\left(C_2·T\right)}·{\epsilon }_p^{\left(n_1·T+n_2\right)}·e^{\left({\displaystyle \frac{l_1·T+l_2}{\phi }}\right)}·{\dot{\epsilon }}_p^{\left(m_1·T+m_2\right)}$$

(1)

where T—temperature, ε_p—plastic strain, $\dot{\epsilon }$_p—plastic strain rate, and C₁, C₂, n₁, n₂, l₁, l₂, m₁, m₂—parameters derived from the experimental data were used to calibrate the plasticity model.

Table 4. Plasticity model parameters.

Mat.	C1	C2	l1	l2	m1	m2	n1	n2
AA 6061-T6	378,528	−4.915 × 10−3	6.036 × 10−5	−0.02548	3.449 × 10−4	−0.0315	−1.072 × 10−4	−0.02573
AA 5052-H321	479,249	−3.711 × 10−3	−1.592 × 10−5	2.591 × 10−5	4.333 × 10−4	−0.0566	−4.711 × 10−4	0.1705

shows the parameter values for both materials employed in the modeling process, which were obtained through external methods, since Simufact Forming does not offer a procedure for their determination.

The finite element model replicates the physical setup and is illustrated in Figure 4.

The aluminum alloy sheets were modeled as deformable bodies, while the tool and support components, considering the materials used (high-speed steel), were treated as rigid bodies. Two-dimensional elements, specifically designed for axisymmetric analysis—referred to as Quad (10) in Simufact Forming terminology [25]—were used to construct the model.

The tool’s rotation speed and displacement were set to match the experimental conditions, with one of the simulated cases shown in Figure 5. An automatic remeshing function was employed to regenerate the mesh and allow the simulation to continue with the updated configuration. A total of 40248 Quad (10) elements were used to model the deformable aluminum sheets [25].

The equations that were used to analyze the RFSSW process are the following [2]:

-

heat transfer equation for the process:

$${\displaystyle \frac{\partial T}{\partial t}}={\displaystyle \frac{\partial }{\partial x}}\left(k_x{\displaystyle \frac{\partial T}{\partial x}}\right)+{\displaystyle \frac{\partial }{\partial y}}\left(k_y{\displaystyle \frac{\partial T}{\partial y}}\right)+{\displaystyle \frac{\partial }{\partial z}}\left(k_z{\displaystyle \frac{\partial T}{\partial z}}\right)+{\dot{q}}_p$$

(2)

where T—temperature, ${\dot{q}}_p$—heat rate generated and x, y, z—cartesian coordinates.

-

the equation for heat generation rate:

$${\dot{q}}_p=\tau ·\eta ·{\dot{\epsilon }}_p$$

(3)

where τ—shear stress, η—conversion factor of mechanical to thermal energy.

-

frictional heat generated at the interface between the tool and the workpiece:

$${\dot{q}}_f=\mu ·p·\omega$$

(4)

where ${\dot{q}}_f$—heat produced by friction, μ—friction coefficient, p—contact pressure and ω—rotational speed.

-

the expression for convective heat transfer is:

$$q_c=h_f\left(T_s-T_{\mathrm{\infty }}\right)$$

(5)

where h_f—convection coefficient (h_f = 50 [W/m² °C]), T_s—surface temperature of the plates and T_∞—environmental temperature.

-

the expression for radiation heat is:

$$q_r=k·{\epsilon }_r\left(T_r^4-T_{\mathrm{\infty }}^4\right)$$

(6)

where κ—Stefan-Boltzmann constant (κ = 5.67 × 10⁻⁸ [W/m²·°C]), T_r—absolute temperature of the radiating surface and ε_r—radiating surface emissivity.

Temperature dependent changes in the material’s physical and mechanical properties, including Young’s modulus, Poisson’s ratio, thermal expansion coefficient, thermal conductivity, and specific heat capacity, were implemented in the material database of Simufact Forming software [25].

4. Results and Discussion

This section presents and analyzes the main results obtained throughout the study, with particular focus on the thermal history and residual stresses evaluated both experimentally and through finite element modeling (FEM). Additionally, the load-bearing capacity of the RFSSW joints and the macrostructural characteristics observed in cross-sectional analysis are discussed in detail.

4.1. Thermal History

In the RFSSW process applied to heat-treatable aluminum alloys, controlling the heat input is essential for multiple reasons, including its impact on macrostructural features (such as hook formation and bonding quality) and the management of precipitate formation.

Thermal cycle analysis also assists welding engineers in establishing a direct correlation between process parameters and the peak temperatures reached in the material during welding.

Schmidt et al. [26] proposed that the frictional heat generated during conventional friction stir welding can be estimated using the following model:

dQ = ω∙dM = ω∙r∙dF = ω∙r∙dA

(7)

where dQ—heat input of the surface element [W], ω—angular velocity [rad/s], r—radius [m], M—torque [Nm], F—downward force [N], τ—shear stress on the contact surface [Pa], dA—area of the surface element [m²].

Based on this model and considering the geometry of the RFSSW tool, the amount of heat generated can be estimated at different contact zones: between the pin tip and the plasticized material (Q1), between the sleeve end and the plasticized material (Q2), and between the lateral surfaces of the sleeve and the plasticized material (Q3 + Q4), using the following formula:

$$Q_{total}={\displaystyle \frac{2}{3}}\tau \pi \omega ·\left\{r_{sleeve}^3+3·\left[r_{pin}^2·\left(h_p+h_r\right)+r_{sleeve}^2·h_p\right]\right\}$$

(8)

where r_sleeve—sleeve radius, r_pin—pin radius, h_p—sleeve penetration depth and h_r—pin withdrawal depth. It can be seen from this relationship that the heat input, which translates into an increase in temperature, is directly proportional to the tool rotation speed.

Table 5. Temperature and residual stress from finite element analysis.

No.	Welding Process Time [s]	Sleeve Penetration Depth [mm]	Tool Speed [rpm]	Max. Temperature [°C]	Residual Stress [MPa]
1	4	2.2	1800	357	249
2			1900	365	247
3			2000	380	242
4			2100	386	239
5			2200	397	234
6			2300	402	231
7			2400	412	230
8		2.4	1800	362	246
9			1900	385	241
10			2000	391	237
11			2100	399	234
12			2200	413	227
13			2300	424	225
14			2400	437	224
15		2.6	1800	393	258
16			1900	410	253
17			2000	419	241
18			2100	423	236
19			2200	430	227
20			2300	433	219
21			2400	446	215
22	5	2.2	1800	364	238
23			1900	377	233
24			2000	384	227
25			2100	397	225
26			2200	408	223
27			2300	415	221
28			2400	425	219
29		2.4	1800	380	224
30			1900	390	235
31			2000	401	231
32			2100	413	229
33			2200	421	224
34			2300	429	221
35			2400	443	217
36		2.6	1800	412	250
37			1900	407	248
38			2000	423	244
39			2100	433	241
40			2200	453	236
41			2300	463	234
42			2400	472	231
43	6	2.2	1800	370	232
44			1900	380	231
45			2000	382	228
46			2100	404	224
47			2200	414	222
48			2300	422	220
49			2400	432	218
50		2.4	1800	388	236
51			1900	398	231
52			2000	409	228
53			2100	416	225
54			2200	434	224
55			2300	442	221
56			2400	450	217
57		2.6	1800	411	251
58			1900	426	241
59			2000	431	238
60			2100	440	236
61			2200	461	234
62			2300	471	227
63			2400	484	221

presents the results of the finite element analysis regarding the maximum temperature and residual stress values obtained for various RFSSW process conditions. The table includes welding process times, sleeve penetration depths and tool rotation speeds. The data demonstrate the influence of welding parameters on the thermal and mechanical behavior of the RFSSW joints, showing that increases in tool speed and sleeve penetration depth generally result in higher maximum temperatures, while residual stress values vary depending on the combined effects of all parameters.

Figure 6 shows the temperature distribution in the welded parts after 4 s and at the end of the process. Maximum temperature (403–445 °C) is located in the contact region between the rotating tool and the upper surface of the lower sheet. The heat-affected zone (HAZ) and stir zone are clearly visible, forming a concentrated high-temperature band. The sharp thermal gradient toward the surrounding material confirms localized heating, which is a desired effect in solid-state welding.

In Figure 7, the temperature evolutions in the sensor and in the finite element model and in Figure 8 the infrared thermographic image during the welding process can be seen for the process parameters, case A: h_s = 2.2 [mm], t_w = 4 [s] and n = 1800 [rpm].

The chart presents a good correlation in peak phase (0–2.5 [s]), both curves show a rapid rise in temperature, reaching a peak around 1.5–2.0 s. The FEM model predicts a slightly higher peak (178 [°C]) than the sensor data (170 [°C]), but the difference is minimal. This correlates well with the thermographic image (Figure 8), which recorded a maximum temperature of 178.2 [°C] at the considered point, confirming FEM model accuracy. After 2 [s], the temperature starts to drop sharply in both datasets. Around 3 [s], the FEM curve shows a minor underestimation compared to the sensor (120 [°C] vs. 130 [°C]), then trends slightly upward again, possibly indicating heat redistribution from adjacent regions (thermal inertia). As shown in Figure 7, a short plateau in the experimental temperature curve is observed around 2 s, whereas the FEM simulation continues to show a gradual temperature increase. This temporary stabilization of the measured temperature is attributed to the change in heat transfer regime during the plunge phase of the RFSSW process. At this stage, the plasticized material under the tool undergoes localized flow and redistribution, temporarily balancing the rate of heat generation and dissipation at the sensor location. The FEM model, on the other hand, assumes continuous heat generation and uniform thermal conductivity, and therefore does not capture this transient equilibrium condition. Additionally, the slight delay in heat propagation toward the thermocouple position, combined with potential thermal inertia of the sensor, may also contribute to the observed plateau. Despite this local difference, the overall temperature evolution trend and the peak temperature values predicted by the simulation remain in good agreement with the experimental results.

The spatial thermal field seen in the infrared image (Figure 8) shows a HAZ extending radially. At 5 [mm] from the center, the temperature is not at the absolute maximum but remains elevated, consistent with the values shown in both the FEM and sensor data (120–160 [°C]). This confirms the validity of both simulation and measurement, showing strong spatial–temporal consistency.

In Figure 9, the temperature evolutions in the sensor and in the finite element model and in Figure 10 the infrared thermographic image during the welding process can be seen for the process parameters, case B: h_s = 2.6 [mm], t_w = 6 [s] and n = 2400 [rpm].

An analysis of Figure 7, Figure 8, Figure 9 and Figure 10 shows that increasing the penetration depth and tool rotation speed leads to a significant rise in the maximum temperature reached during the welding process. Extending the welding time to 6 s results in a more intense and prolonged plasticization of the material, which may enhance the mechanical quality of the weld. However, it also increases the risk of excessive expansion of the HAZ. Conversely, using lower parameters (2.2 [mm] penetration depth, 4 [s] welding time, and 1800 [rpm]) produces adequate but moderate plasticization, with faster heat dissipation. This helps limit potential adverse effects on the microstructure of the welded material. Therefore, a balanced selection of welding parameters is essential to achieve joints with optimal mechanical properties, while preserving the structural integrity of the base material by avoiding excessive heat input and an overly large HAZ.

Notably, a strong correlation was observed between finite element simulation (FEM) results and experimental data, which supports the use of numerical simulation as an effective tool for optimizing RFSSW process parameters, thereby reducing the number of required physical experiments and the associated costs.

4.2. Residual Stresses

Figure 11 illustrates the equivalent stresses at the end of the plunging stage and the end of the RFSSW process. The image confirms that the stir zone undergoes intense plastic deformation, which is essential for producing a solid and defect-free weld. The symmetrical stress distribution indicates proper tool alignment and uniform mechanical interaction. Elevated stress concentrations around the “hook” suggest that this region is potentially critical for defect initiation or failure under mechanical loading.

Conversely, the low-stress regions on the lateral sides (depicted in blue) demonstrate effective confinement of stress propagation, which is favorable from a structural integrity standpoint.

Figure 12 presents the distribution of effective plastic deformation during the RFSSW process, as obtained through numerical simulation.

The mixing zone exhibits significant plastic deformation, indicating that the RFSSW process effectively generated mechanical bonding through plasticization. The deformation distribution is symmetrical and well controlled, reflecting proper tool alignment and optimal process parameters (time, pressure, and rotation speed). The semicircular shape of the yellow region suggests effective tool penetration and material mixing, with no evident process-related defects. Additionally, the absence of plastic deformation in areas distant from the weld zone confirms that the stress is well localized, reducing the risk of unwanted deformations or degradation of mechanical properties in unaffected regions.

The simulated process appears to be well calibrated for sensitive applications such as in the aerospace or automotive industries.

It may be worth evaluating whether a reduced penetration depth could still induce sufficient plastic deformation while decreasing thermal input, thus contributing to energy efficiency.

The simulation confirms that controlled and effective plastic deformation occurred in the critical zone of the RFSSW process, an essential prerequisite for achieving a solid, durable, and reliable joint.

4.3. Load Capacity of RFSSW Joints

The shear tests were performed on four specimens that were obtained following the RFSSW process with different parameters (penetration depths—h and welding time—t_w). In

Table 6. Cases considered for tensile tests.

Case	Penetration Depths h [mm]	Welding Time tw [s]
I	2.2	4
II	2.2	6
III	2.6	4
IV	2.6	6

, the cases for the shear test of the welded joint for a tool rotation speed of 2400 [rpm] were considered.

The shear test of the joint was conducted using an Instron universal testing machine (model 8850) at a deformation rate of 1 [mm/min].

Figure 13 illustrates the different stages of a shear test and the resulting failure pattern of a mechanical joint and it is divided into three parts:

(a)

This image shows the initial setup phase of the shear test at t = 0 [s]. The specimen is clamped into a testing machine, ready to be subjected to shear loading. The machine grips are holding the sample in place vertically;

(b)

This image presents the active shear testing phase at t ≈ 100 [s] after beginning of the process. The specimen is visibly under load between the grips of the testing machine. Deformation of the sample can be observed, indicating that the shear force is being applied;

(c)

This image displays the final macroscopic fracture morphology after the shear test is completed. The specimen has failed and is now separated into two distinct pieces. The visible fracture zone indicates where the shear failure occurred, and the welded nugget (visible in both parts) remains present in the sample.

The progression from (a) to (c) visually documents the mechanical behavior of the joint under shear stress and the nature of its failure.

Figure 14 illustrates the progression of a shear test and the resulting failure mode for a joint under Case IV conditions. It consists of three images labeled (a), (b), and (c):

(a)

This image shows the initial clamping phase of the shear test at t = 0 [s]. The metallic specimen is securely positioned between the upper and lower jaws of the testing machine. The setup is ready for load application;

(b)

This image captures the deformation phase during shear loading at t ≈ 150 [s] after beginning of the process. The specimen is visibly bent and distorted, indicating plastic deformation and onset of failure. The asymmetry in the specimen suggests a complex stress distribution or misalignment during loading;

(c)

This image shows the macroscopic fracture morphology after the shear test. The sample is significantly deformed with clear out-of-plane bending and warping. This suggests a ductile failure mode dominated by plastic deformation and substantial energy absorption before complete separation.

Overall, Figure 14 demonstrates how the joint in case IV undergoes severe plastic deformation before fracture, in contrast to a more brittle or clean break, indicating a different mechanical behavior compared to the joint shown in Figure 13.

In Figure 15, the graph illustrates the force–displacement responses for the four different RFSSW joint variants, cases 1–4 (Table 4), subjected to shear testing.

All four curves exhibit a typical behavior for spot-welded joints:

• An initial linear region, indicating elastic deformation, is followed by a non-linear segment as plastic deformation develops.
• Each curve reaches a maximum force (peak load), representing the load-bearing capacity of the joint, followed by a descending branch as failure initiates and propagates.

Case 4 (black curve) demonstrates the highest peak force and the largest displacement at failure, indicating superior strength and ductility among all variants.

Cases 1–3 (yellow, red, green) have lower maximum forces, with case 1 showing the lowest strength and displacement at failure. The differences in both peak force and post-peak behavior suggest that the joint configuration and welding parameters used for Case 4 result in improved mechanical performance and energy absorption.

The fractures behavior for the case I–III points to a brittle or partially cohesive failure, as the plates detached directly along the weld, rather than tearing through the base metal or the HAZ. This may also indicate an insufficient overlap area or a premature tool retraction that did not allow full material consolidation. From visual inspection, it is evident that failure occurred at the weld interfaces for cases I–III, indicating that the joints were the weakest regions under shear load. The stir zone, although visibly formed with a characteristic tool exit pattern, did not provide sufficient bonding strength to surpass the cohesive strength of the base materials. The highest joint load capacity was achieved for the welds made with a tool penetration depth of 2.6 [mm], a total welding time of t = 6 [s], and a tool rotation speed of 2400 [rpm]. In this case, the load capacity was 4.728 [kN]. From a macroscopic failure-mode perspective, the case IV joint (

Table 7. Failure modes and load capacity.

Case	Load Capacity [kN]	Failure Mode
I	4.170	nugget debonding
II	4.321
III	4.362
IV	4.728	break in the AA5052 sheet

), subjected to tensile testing, the fracture did not occur strictly along the weld interface, as seen in previous samples which the joints have been debonding. Instead, a significant plastic deformation of the base materials occurred before final separation, which is a strong indicator of improved mechanical performance.

4.4. Macrostructural Analysis of an RFSSW Joint in Aluminum Alloy Sheets

Macrostructural analysis is a common method for studying the macrostructure of RFSSW joints. Figure 16 shows a cross-section of an RFSSW weld made on two sheets of aluminum alloy AA6061-T6 and AA5052-H321. The macrostructure reveals several typical key areas that can be characterized by crystal grain structures and deformation patterns caused by frictional heat and plastic flow occurring during the welding process.

Figure 16 also presents the macroscopic details of the welded joint, highlighting the characteristic features observed in the main regions of interest. Zone I corresponds to the macrostructure within the Heat-Affected Zone (HAZ), while Zone II shows the Thermo-Mechanically Affected Zone (TMAZ). Zone III illustrates the transition region at the interface between the TMAZ and the Stir Zone (SZ), and Zone IV depicts the macrostructure inside the SZ, where intense plastic deformation and material mixing occur. In Zone V, a typical nugget pull-out defect can be observed, which is commonly associated with insufficient bonding or localized stress concentration during the shear test. Finally, Zone VI shows the macrostructure of the base material, which remains unaffected by the thermal and mechanical cycles of the RFSSW process.

Thus, we identify the following regions: the stir zone (SZ), the thermo-mechanically affected zone (TMAZ), the heat affected zone (HAZ), and the base material (MB).

The stir zone (SZ) is geographically located in the center of the weld, below the tool pin path. It appears as a darker, well-defined, teardrop-shaped or basin-shaped area. This region has undergone intense plastic deformation and dynamic recrystallization, resulting in a fine structure of equiaxed crystalline grains.

Thermo-Mechanically Affected Zone (TMAZ) is found adjacent to the stir zone on both sides. Here, the material was deformed but not fully recrystallized and grain boundaries are bent or elongated due to partial plastic deformation. This zone typically exhibits a transition in grain orientation and size between the stir zone and the unaffected base material.

Heat-Affected Zone (HAZ) resides just outside the TMAZ and no plastic deformation occurred here, but the material experienced thermal exposure and grain growth may be observed due to heating below the melting point, and this zone often shows softening in heat-treatable alloys. The interface between HAZ and TMAZ is usually smooth and continuous.

Base Material (BM) is located far from the weld center, this region remains unaffected by the welding process and it retains the original rolling direction, grain size, and mechanical properties of the parent aluminum alloy.

We can additionally add a series of observations such: the symmetry of the stir zone suggests good tool alignment and proper process parameters; no visible voids or tunnel defects are present, indicating effective material refill and consolidation; slight defects at the edge of the stir zone (e.g., surface tearing or inclusions) may point to minor disturbances in material flow or insufficient shoulder pressure and the depth and width of the stir zone are consistent with a well-executed RFSSW joint, suitable for structural applications.

The experimental results obtained in this study show that the maximum shear load of the RFSSW joint (4.728 kN) was achieved for a plunge depth of 2.6 mm and a welding time of 6 s. These values are comparable to those reported by Tier et al. [15] for 5042 aluminum alloy, who observed a similar trend of increasing shear strength with greater plunge depth. However, in the present study, the correlation between temperature distribution and mechanical performance was established more clearly due to the combined experimental and FEM-based approach.

Xu et al. [3] reported that for 5083-O aluminum alloys, the maximum joint strength was obtained at moderate rotational speeds, beyond which the material flow became unstable. A similar behavior was observed in this study, confirming that excessive heat input reduces mechanical performance due to softening in the heat-affected zone (HAZ).

Overall, the obtained results are consistent with previous works [3,15,18], yet the novelty of the present investigation lies in the quantitative comparison between the experimental temperature field and FEM-predicted thermal cycles, providing a more detailed understanding of the thermo-mechanical interactions in dissimilar AA6061-T6/AA5052-H321 joints.

The originality of the present study lies in establishing a direct correlation between the experimentally measured temperature distribution and the mechanical performance of dissimilar RFSSW joints. Unlike previous research focused mainly on similar aluminum alloys, this work provides a validated finite element model capable of accurately predicting the thermal field evolution in AA6061-T6/AA5052-H321 joints. Moreover, the experimental observations confirm that the optimized parameter combination (plunge depth = 2.6 mm, welding time = 6 s) leads to superior shear strength, consistent with the simulated temperature field, which has not been previously reported for this material pairing.

5. Conclusions

This study investigates the effect of welding parameters, specifically tool plunge depth, rotation speed and welding time, on the strength of RFSSW joints between dissimilar materials. Following preliminary experiments, the welding processes were carried out using selected extreme values for the input parameters.

This study investigated the influence of key process parameters—tool plunge depth, rotation speed, and welding time—on the mechanical and thermal behavior of dissimilar aluminum joints produced by Refill Friction Stir Spot Welding (RFSSW).

• The unique contributions of this work can be summarized as follows:
• The study provides a combined experimental and finite element approach for analyzing the RFSSW process in dissimilar aluminum alloys, an aspect rarely addressed in the literature.
• A direct correlation was established between the experimentally measured temperature evolution and the joint shear strength, offering new insights into heat generation and bonding quality.
• The developed finite element model was successfully validated against experimental temperature data, demonstrating strong predictive capability for dissimilar RFSSW joints.
• The investigation of AA6061-T6 and AA5052-H321 combinations expands the current understanding of dissimilar aluminum joining and reveals characteristic thermal gradients and stress distributions during the refill process.
• The findings provide practical guidelines for optimizing process parameters to achieve defect-free joints and enhanced mechanical performance in lightweight structural applications.
• The main results show that the joint strength increases with higher tool plunge depth and longer welding time, reaching a maximum load capacity of approximately 4.7 kN under optimal parameters. The temperature field remained below the melting point of aluminum, confirming the solid-state nature of RFSSW. Residual stress analysis revealed tensile stresses localized in the stir zone and thermo-mechanically affected zone, but remaining below the yield strength of the base materials.
• The macroscopic observations confirmed a sound metallurgical structure, with well-defined zones (SZ, TMAZ, HAZ) and no major defects.
• The limitations of this study concern the lack of detailed microscopic characterization and grain size measurement, which will be addressed in future work. Future studies will also explore the optimization of RFSSW parameters using machine learning–based predictive models to enhance joint quality and energy efficiency.