Multi-Track Overlapping by Laser-Treated and Its Effects on the Microstructural Behavior of Al-Fe Alloy Assessed by FEM

Abstract

In this work, a numerical simulation by finite element method (FEM) and optimized multigrid technology was applied. In order to study the influence of multi-track overlapping on the microstructure processed by laser surface remelting (LSR) and so, the validation of the experimental and the numerical simulation results of the multi-track overlapping were accomplished, which was the goal. It was verified in this work, multi-track overlapping and thermal cycling allied to high-speed cooling of liquid metalinfluence the liquid flow, mechanism of heat transport, and microstructure evolution in the molten pool of laser-treated alloy, promoting so a nanostructure characteristic. Thus, FEM is capable of accurately simulating the multi-track overlapping of the workpiece LSR-treated. Results of the overlapping ratio, as well as, the depth where the phase transformation occurs from liquid to solid was very nearby, therefore, simulation and experimental results agree quite well. This type of laser-treated alloy has very special characteristics and it is of innovative character, then, in aerospace, aeronautical, and automobile industries can be applied.

1. Introduction

When multiple laser tracks are used, the latter track causes the tempering of the previous tracks and hardness reduction in multiple laser tracks, which leads to non-uniform hardness in the surface of components, this was argued by Li et al. [1]. Furthermore, because of the rapidity of thermal cycle, a series of complicated phenomena such as heat and mass transfer, phase transition, material properties, laser beam absorption, reflection, and radiation occur in a very short time, this study was corroborated too by Guan et al. [2]. In addition, the later authors argued that the numerical model suggests that Marangoni convection plays a predominant role in determining the solidification microstructure, and it increases significantly with the overlapping rate. However, Pariona et al. [3] investigated this effect and verified by FEM, which the Marangoni effect is inversely proportional to the fluid flow velocity and directly proportional to the thermal gradient, hence, this effect controls the quality, morphological characteristic, and geometry of the molten pool. On the other hand, the study carried out by Karbalaian et al. [4], pointed out that FEM reduces the costs related to experimental measurement. Moreover, with simulation, it is easier to understand results analyze, and optimize the process.

Although Pariona et al. [5, 6] analyzed, during LSR-treatment in Al alloy, the melted zone was constituted of metastable phases by LAXRD analysis and it revealed the presence mainly of Al₂O₃ and AlN phases. These authors emphasized that these phases contributed to the microstructural modification, favored the characteristics of high hardness and corrosion resistance of LSR-treated workpiece in sulfuric acid.

Together with COMSOL Multiphysics based in heat transfer modeling and the experimental approaches by LSR technique were utilized to perform this work. This research was accomplished the numerical simulation by finite elements method of the isothermal temperature field for multi-track, thermal cycles for the multi-track overlapping on the workpiece surface and in the workpiece cross-section. Experimentally was studied the microstructure of Al-2% Fe alloy was with multi-track overlapping. Finally, the experimental validation of numerical simulation of the multi-track overlapping laser was accomplished.

2. Computational model

The thermal analysis of this work involves studying the transient thermal history according to from heat transfer. The following will be presented the theoretical aspects of numerical simulation.

2.1 Mathematical model

2.1.1 3D Mathematical model of transport phenomena

In the past decade, many mathematical models have been developed to study the transport phenomena in laser-treated alloys. Until now, the most recent and complete 3D mathematical models of transport were performed with the evolution of software and hardware. The authors [7] have already discussed this subject.

The main equations of the model of transport phenomena are shown in the following. Eq. (1) represents the transient heat conduction equation, which it was proposed by Yilbas et al. [8]:

$$\rho \frac{\partial \left(\mathit{CpT}\right)}{\partial t}=\frac{\partial }{\partial x}\left(k\frac{\partial T}{\partial x}\right)+\frac{\partial }{\partial y}\left(k\frac{\partial T}{\partial y}\right)+\frac{\partial }{\partial z}\left(k\frac{\partial T}{\partial z}\right)+\left(1-\mathit{rf}\right)I_0\mathit{exp}\left(-\frac{x^2+y^2}{a^2}\right)\mathit{exp}\left(-\mathit{\delta z}\right)$$E1

where x, y, and z are the vertical, depth and horizontal coordinates, respectively, ρ is the density, c_p is the specific heat, k the thermal conductivity, r_f the surface reflectivity, I_o is the laser peak intensity,_δ is the absorption depth, t is time, and a is the diameter of the laser beam, assumed as Gaussian form (Gaussian parameter).

The laser beam moving on surface is considered as thermal loads for the simulate LSR process, which it has continuous scanning that describes the moving heat source and it has the Gaussian-like distribution form (1), which is considered as a volumetric heat source and that determine the beam penetration depth. The boundary conditions have been established. The heat exchange with the air at room temperature surrounding the treated material is described by Eq. (2).

$$k.\nabla T=h\left(T_{\mathit{amb}-}T\right)$$E2

Where h indicates the heat flux caused by convective loss and T_amb is room temperature.

The losses of energy in form of radiation released from the hot surfaces of material are included in Eq. (3).

$$k.\nabla T=\mathit{\epsilon \sigma }\left(T_{\mathit{amb}}^4-T^4\right)$$E3

The parameter ε indicates the emissivity of the material and the term σ represents Stefan-Boltzmann constant for radiation, σ = 5.67e⁻⁸W/m² K⁴).

2.2 Multigrid method

In the numerical simulation works, it is usually necessary to solve large systems through direct or iterative methods, for this, requests a large amount of processing time by Central Processing Unit (CPU), however, Fedorenko [9] proposed Multigrid method (MG) that dramatically reduce the processing time. According to Briggs et al. [10], this method consists, of the transference of information among a refined grid to coarse auxiliary grids, so, which the numerical smoothers are more efficient that optimizing the process. Besides that, Brandt and Trottenberg et al. [11, 12] investigated several parameters types, which can to modified the Multigrid method optimizes process and details and discussion about this method is given by Pariona et al. [13].

3. Materials and methods

3.1 Experimental characterization

The material tested was Al-2.0 wt. % Fe alloy, this alloy was prepared with pure raw materials with chemical composition in mass % as Al: 99.76, with impurity as Fe:0.09, Si: 0.06, Cu: 0.06, Ni: 0.03 and Fe: 99.97, with impurity Si: 0.01, Cu: 0.01, Ni:0.01. The casting assembly used in the solidification experiments consists of water-cooled mold, being the heat extracted was done only in the bottom, and it promotes a vertical upward directional solidification. The laser surface treatment was performed with a 2 kW Yb-fiber laser (IPG YLR-2000S) and its intensity at initial moment was I(0) = 1.81×10⁹ W.m⁻². The power density was 4.8×10⁵ W.cm⁻² with multi-phase distribution of energy and with an approximately Gaussian profile, and the laser beam velocity fixed was 40 mm/s. The laser treatment without an assisting gas jet was executed, with the purpose of creating alumina and aluminum nitride phases in the environment at high temperature, being that these phases presented high resistant and corrosion mechanic resistant, which were studied by Pariona et al. [5].

Furthermore, for metallographic characterization in the cross-section, small samples were cut, sanded, and polished with colloidal silica. Micrographs were recorded by optical microscopy (OM, Olympus-BX51) and by an SEM, Shimadzu SSX-550 microscope. Besides, a chemical attack with 0.5% HF was also made on these samples for analysis microstructure.

3.2 Aspects of the numerical simulation by FEM technique

The simulations were carried out with COMSOL Multiphysics software^TM, in a microcomputer with Intel i7 2.8 GHz processor with 32 GB RAM and Linux operational system. For the simulation procedure, the geometry and mesh were constructed. For carrying out the simulation process, the proposed equations of chapter 2.1 were used.

Initial and boundary conditions were applied in the geometry, and the material’s thermophysical properties were considered dependent on temperature, presented by Pariona et al. [14], and these properties were found through [15]. A moving heat source was established in the x-axis with a scan velocity of 40 mm.s⁻¹. The laser parameters used in this work (Eq. 1) were shown in previous work, such as given by Pariona et al. [3, 13].

Corresponding the heat flux and radiation expressions (Eqs 2 and 3) were applied as boundary conditions, where: h_up is 12.25 W.m⁻²K⁻¹; h_down is 6.25 W.m⁻²K⁻¹, these values were used of the literature [16], because, these values were not determined experimentally; meanwhile, the surface emissivity (ε) equaled to 0.33 and the room temperature was 300 Kelvin.

For the execution of solution process, Multigrid method was applied for optimization procedure. Hence, the following parameters were established in his method: in Solver mode was selected the geometric multigrid, the number of iterations was 2, the multigrid cycle was V cycle, the hierarchy generation method, the number of multigrid levels was 1, and mesh coarsening factor was 2.

4. Results and discussion

In this work was performed the numerical simulation by finite elements method of multi-track overlapping by means of RSL-treated technique. Simulation was conducted based in Figure 1, in this figure was accomplished a schematic diagram of the multi-track overlapping, therefore, to carry out this work, four tracks were considered, thereby, the multi-track overlapping and distance between consecutive tracks are displayed. So, the results of the thermal cycles were shown on the workpiece surface and in the cross-section for the four tracks.

Figure 1.

Schematic diagram of the multi-track overlapping, where, the laser move occurred in a parallel line fashion. Hence the designation I, II, III, and IV are midpoints of each track.

4.1 Isothermal temperature field for multi-track overlapping

Isothermal temperature field for the multi-track by numerical simulation study using FEM was performed for the four tracks (Figure 1), whose tracks are schematized in Figure 1 and at this figure are shown the coordinates of the points: I, II, III, and IV. The arrow indicates way that follows the laser beam. Whereas, after executing one of the tracks by the laser beam and soon to pass to the next track was calculated at 0.01 s the delay time between two tracks, as also it was displayed on the schematic. According to the scheme of Figure 1 for the laser beam velocity v = 40 mm/s that was considered, then, the total time it takes to run the four tracks was calculated at 2.04 s.

In Figure 1, the isothermal temperature field has the form of an ellipse, nevertheless, they are deformed, this fact was confirmed by [7, 17]. These last authors affirmed that the ellipse of temperature field is not symmetrical by the center of the facula, but form the deviation on one side of the cladding, still, they argued, the phenomenon that the multi-track cladding forms the partial ellipse, is induced by influence of the former cladding on the latter one.

In Figure 2a the isothermal temperature field for two tracks on the workpiece surface was presented and it can be observed in 3D, where, the directions of the laser beam are indicated by arrows in figure. The first track was presented at instant 0.4 s, which corresponds to the forward motion of the laser beam and for the fourth track at instant 1.9 s was displayed, which corresponds to the return of the laser beam. In this figure, the solidification conditions ahead for the first track, presents an enlargement in the direction of the movement of the laser beam, though, the solidification conditions ahead for the fourth track is deformed, due to the fact that it reached the final part of its movement, where the thermal waves exhibited an aspect as if it were a rebound. While, to elucidate with more detail, in Figure 2b the isothermal is displayed in 2D, where all the phenomena mentioned are observed again. Still, the authors [1] obtained similar results to Figure 2, however, these authors did their research for two tracks, meanwhile, and this research was done for four tracks.

Figure 2.

The isothermal temperature field for multi-track on the workpiece surface. (a) Viewed in 3D and (b) Viewed in 2D.

4.2 Thermal cycles for multi-track overlapping

In the next will be presented a result of analysis of thermal cycles, so much, on the workpiece surface and in the workpiece cross-section.

The result of thermal cycles on the workpiece surface is shown in Figure 3. It was based on Figure 1, where thermal cycles on the surface were raised at the midpoints of each track and those points were represented by: I, II, III, and IV. e.g., the first peak (or point I) of thermal cycle corresponds at the instant 0.25 s; the second peak (or point II) at 0.76 s; the third peak (or point III) at 1.27 s, and the quarter peak (or point IV) at 1.78 s. Fits to highlight here, the travel total time of the laser beam along the way is indicated by arrows, such as indicated in Figure 1.

Figure 3.

Thermal cycles for the multi-track overlapping on the workpiece surface. (a) influences of other tracks on the first track, (b) influences of other tracks on the second track, (c) effects of other tracks on the third track and (d) effects of other tracks on the fourth track, and (e) summarized all four cases previously treated.

As we can see in Figure 3a, the temperature evolution of point I of the 1st track versus time and influences of other tracks on the first track is shown. So, the first peak in Figure 3a is the temperature rise induced by the 1st track, it reached a temperature of around 1300 K. When the laser beam moves away, the temperature of point I decrease to room temperature at t = 0.5 s. The second peak shows the temperature rise of point I when performing the second track. Therefore, the second peak is the influence of the 2nd track at point I, this peak is above the solidification temperature (933 K) and it is related to phase transformation. The third peak did not reach the phase transformation, but its intensity is relatively high, this peak displays the temperature elevation of point I when passing the third track. Finally, the fourth peak, which is in solid-state temperature of the alloy, likewise, it was thermal influence of the 4th track on the 1st track (point I), thereby, whose influence is insignificant.

Furthermore, temperature field characteristic for the second track can be seen in Figure 3b, it is the temperature rise induced by the 2nd track of the laser beam, over again, an intense peak appears so equal to peak of the first track (Figure 3a); but here is a difference in relation to the first peak that was described previously. In this figure, it can be observed that the temperature peaks of the first neighbors around the second track are similar, as well as in intensity. In addition, both are above of solidification point of alloy and still correspond to phase transformation, thus, influence of temperature around the first neighbors (the first and third peaks) at the 2nd peak, it is very considerable. However, influence of the temperature field of the fourth track at the second is negligible.

Moreover, intensity of the temperature field of the third track (Figure 3c), where the characteristic is of form similar to the temperature field of the second track (Figure 3b), therefore, the temperature peaks of the first neighbors at the third track have considerable influence, however, the effect of the temperature field of the 1st track at the 3 rd track is depreciable. Nevertheless, the behavior of the temperature field of the fourth track (Figure 3d) is similar to the temperature field of the first track (Figure 3a), but in inverse mode.

In Figure 3e is summarized all four cases previously treated, where intensities are denoted with different colors as shown in this figure. In addition, the distances between tracks are displayed, as well as the coordinates of each track are presented. The time interval between each peak was 0.5 s.

Result of the thermal cycles for multi-track overlapping on the workpiece surface by numerical simulation studied using FEM was shown in Figure 3, this result gives an idea when a track was performed by the laser beam, the temperature of treated track reaches a high magnitude, and soon decreases to room temperature, as was observed, also, showed the temperature rise due to the influence of the other neighboring tracks. Certainly, this result could influence the microstructural characteristic and electrochemical behavior of the workpiece.

Besides, Figure 4 shows behavior of the thermal field profile of thermal cycles in the workpiece cross-section as a function of depth, as shown schematically in Figure 1, where the depths with different colors are displayed. For each track (Figure 1), the same depths were considered; in this work only the z-axis (depth) was varied. It should be remembered that the depth at the phase transformation from liquid to solid occurs is 250 μm. E.g., the most intense peak of Figure 4a corresponds when the laser beam passed through the first track, which corresponds point I of Figure 1. This track will be considered as a reference to remark the influence of other tracks in this one. Therefore, at point I, it can be seen the variation of the laser beam intensity as a function of depth in different colors, the most intense belongs to the molten pool zone of alloy. However, the second peak in this same figure corresponds to when the laser passed through the second track and whose effect is signaled, at point II can be noted the thermal profiles as a function of depth and whose effect of this peak is intense. The third peak of Figure 4a connotes influence of the thermal field at the point I coordinates, when the laser beam passed through the third track, whose effect is reasonable. Finally, the fourth peak is when the laser beam passed through the fourth track, whose effect is shown at the point I coordinates with negligible characteristics. Nevertheless, Figure 4a represents magnification of Figure 4b.

Figure 4.

Shows behavior of the thermal field profile of the thermal cycles at the workpiece cross-section as a function of depth. (a) thermal profile of each track at the point I coordinates, (b) same that (a), (c) thermal profile of each track at the point II coordinates, (d) thermal profile of each track at the point III coordinates, and (e) thermal profile of each track at the point IV coordinates.

Therefore, Figure 4c represents the thermal profile of thermal cycles of each track referred to at the point II coordinates of Figure 1. Where, the most intense peak in this figure corresponds to when laser passed by the second track, where thermal profiles are shown as a function of depth. The first peak corresponds to the first track and third peak corresponds to the third track, they have an appreciable and a similar influence at the point II coordinates, whose intensities are above the solidification temperature. The fourth peak represents a negligible influence at the point II coordinates.

Figure 4d represents the thermal profile of thermal cycles of each track referred to at the point III coordinates of Figure 1. Where, the most intense peak corresponds to when the laser beam passed through the third track, in this peak can be appreciated the thermal profiles as a function of depth. The thermal profile corresponds to the first peak and whose influence is presented at the point III coordinates; however, it has a negligible characteristic. Nevertheless, the third and fourth peak has a reasonable influence on the referred point.

Finally, Figure 4e is the thermal profile of thermal cycles of each track referred to at the point IV coordinates of Figure 1. It means that the most intense peak corresponds to the fact that the laser beam passed through the fourth track; also, thermal profiles can be noticed as a function of depth at the same point IV. Besides, the third peak most intense is the influence of the third track at the point IV coordinates, since it has an appreciable influence. However, other peaks have negligible influences at the point IV coordinates.

4.3 Experimental validation of the numerical simulation of multi-track overlapping

For this goal, multi-track overlapping was simulated by finite element technique and finally, these results were confronted and the validation of multi-track overlapping effects on the microstructure. Since this type of study was done for Al–2.0 wt.%Fe alloy and the laser beam velocity was 40 mm/s.

The multi-track overlapping effect on the microstructure is shown in Figure 5a for Al–2.0 wt.%Fe alloy, where the multi-track overlapping can be clearly observed. To clarify, the overlapping lines were dashed at blue, where the three tracks are shown within the melted zone. In reference to the first track, whose diameter was 760.7 μm, within this area there are two overlapping due to the influence of the two tracks of first neighbors. For the first neighbor of the first track whose distance of overlapping at adjacent of the two tracks, was 472.2 μm, nonetheless, for the second neighbor was 203.3 μm. As it can be perceived, due to influence of the first neighbors tracks at area of the first track, therefore, there are three regions in the molten pool. Thus, this region showed a homogeneous characteristic, with a higher porosity concentration at the first two regions from left to right, but at the latter region, porosity concentration was lower due to multi-passage of the laser beam, therefore, this leads to greater mechanism of heat transport at the molten pool of the latter region, thus avoiding lower porosity concentration.

Figure 5.

Experimental validation of numerical simulation of the multi-track overlapping laser. (a) microstructure of Al-2% Fe alloy with multi-track overlapping, (b) numerical simulation of the multi-track overlapping, and (c) confront of the numerical simulation and experimental results.

The overlapping ratio R, proposed by the authors Li et al. [18], it is denoted as:

$$\mathrm{R}=\mathrm{d}/\mathrm{D}\times 100\%$$E4

Where d and D are the distances of overlapping of the adjacent of the two tracks and the diameter of the laser beam (=0.3 mm), respectively.

According to Figure 5a, the overlapping ratios R was calculated for two overlapping of the first neighbors.

For the first neighbor, R = 62% and for the second neighbor, R = 26.7%.

This means that the first overlapping ratio has a contribution of 62% and the second overlapping ratio has 26.7% at area of the first track. Then we can be stated, the overlapping ratio depends on various parameters, among them, type of alloy, distance between tracks, laser beam speed, and laser beam power.

In addition, the overlapping was simulated for all tracks and the result is shown in Figure 5b. While, the quantitative data of the overlapping ratio, using Eq. (4) were:

For the first neighbor, R = 63% and for the second neighbor, R = 24.6%

Figure 5a measured the intersection angle between melt tracks, this measure was 142^o and for [19] was 128^o, since, this author carried out an in-depth study on microstructures of aluminum alloys. Well then, we can state, this angle depends on alloy type, distance of overlapping adjacent of two tracks, laser beam speed and laser power, and all these parameters also influence the alloy properties.

In order to illustrate better this work, a numerical simulation of multi-track overlapping was performed using finite element technique and optimized by the multigrid technique. To carry out the simulation, a schematic diagram is shown in Figure 1, where four tracks are shown. The results of this simulation are presented in Figure 5b. For each track, the thermal field in form of isotherms was presented, besides, some isotherms are presented with the corresponding temperatures. Furthermore, the depth where phase transformation occurs from liquid to solid are also shown, e.g., for the first track, the depth was 250 μm; for the second it was 260 μm; for the third, it was 240 μm and for the latter, it was 240 μm. However, experimentally the depth was 264 μm (Figure 5a), therefore, this small variation of depth can be attributed due to variation of thermal gradient, or owing to the Marangoni effect [3] and also, can be as a consequence of variation of thermophysical properties, given by [13], thus, experimental and simulated results were very close. Furthermore, results of overlapping ratio (Figure 5) for both experimental and simulated cases were quite close, as well as, the depth where phase transformation occurs from liquid to solid, also, were very nearby, both the results of the simulation and the experimental part agreeing quite well. Therefore, FEM is capable of accurately simulating the multi-track overlapping, to illustrate better this comparison, in Figure 5c these details are shown. According to results of the numerical simulation of the thermal cycles for the multi-track overlapping by LSR-treated, so much, on the workpiece surface and in the cross-sections. Then, we can be stated, distance between tracks, the laser beam velocity, the laser beam characteristic, and alloy type influence the numerical simulation result and consequently also, the microstructural characteristic of alloy.

The following will be presented a discussion about the thermal cycles, the overlapping of laser beam tracks by different authors. Cordovilla et al. [20] argued that effect of preheating induced in the material by previous tracks on kinetic of current track and so on; the thermal cycles induced in the material by a laser surface hardening process are the driving force for all the metallurgical transformations and they performed the numerical simulation of overlapping only for two tracks. On other hand, Li et al. [1] reported, melted zones created by multiple tracks should be uniform and which provides condition to compose fine grains and a high hardness melted layer, in addition, these same authors observed, that temperature change rate in overlapping area increases with increase in overlapping ratio, in agreement with experimental ones. Also, they stated, to predict the hardness distribution under two consecutive parallel tracks carried out with realistic thermal cycles, the transformation maps must be validated that will serve as a tool to confront the overlapping process, this study was supported by Cordovilla et al. [20].

Guan et al. [2] verified, which numerical model suggests that Marangoni convection plays a predominant role in determining the solidification microstructure, and it increases significantly with the overlapping rate and however, it may play a significant role in influencing final surface properties of laser-treated materials, however, Guan et al. [21] analyzed that overlapping is important in determining corrosion resistance due to microstructure in-homogeneities in the molten pool and this study was also remarked by Reitz and Rawers [22]. As described by He et al. [23], overlapping tracks affect heat transfer and liquid flow, microstructure evolution, and these authors from a well-tested numerical heat transfer and fluid flow model analyzed the mechanism of heat transport in the molten pool.

Liu and Qi [7] point out that the overlapping ratio was the key parameter to ensure the continuity and consistency of the epitaxial columnar dendrite growth. Still, they vary the deposition parameters and the alternating scanning method, the epitaxial growth of columnar dendrite microstructure can be achieved in a multi-track and in multi-layer deposit. Moreover, Besides, Lakhkar et al. [24] focused their study on the development of a numerical model to predict the back tempering in multi-track laser hardening of AISI 4140 steel and the predictions of the multi-track by numerical simulation, it was validated in a satisfactory way with the resulted experimental of the microstructure. Similar result was given by Yao et al. [25] that analyzed the structure of the overlapping zone in the microstructure in alloyed steel by SEM.

With all this, overlapping of laser beam tracks, thermal cycling, and allied to high-speed cooling influences the microstructural characteristics of laser-treated alloy, promoting a nanostructure characteristic in the molten pool, where metastable phases are formed, as well as in this case, alumina and nitride phases were produced by environment during laser-treatment, this subject was discussed trough low-angle x-ray diffraction analysis, by Pariona et al. [3, 26]. Furthermore, these authors confirmed, characteristics of overlapping, as well as microstructure in each region and distribution of nanopores, therefore, they must influence mechanical properties and corrosion resistance in corrosive media of the LSR-treated alloy with multi-track.

4.4 Workpiece microstructure by the multi-track overlapping by laser treated

The microstructural result in the workpiece cross-section was already presented in the previous section, where was discussed the analysis result of thermal cycles, the multi-track overlapping by LSR-treated through means of numerical simulation, and finally, the numerical simulation and experimental results were confronted. This section will be presented and discussed of microstructure of the as-received alloy on the workpiece surface, with the purpose of analyzing the multi-track overlapping influence in the microstructure characteristics.

Figure 6 illustrates the morphology of hypereutectic Al-2.0 wt.% Fe alloy laser-treated, analyzed through OM and FESEM, showing the multiple laser tracks characteristics formed during laser treatment. OM image in Figure 6a shows the surface morphology, where multi-track is observed, while FESEM image in Figure 6b shows the morphology in more detail of region on the track and between the tracks, it corresponds to multi-track overlapping region, according to Figure 5.

Figure 6.

Microstructure morphology of the as-received alloy on the workpiece surface. (a) Viewed of multi-truck by OM, (b) Viewed of multi-truck by FESEM, (c) Magnification of (b) and (d) columnar-like structure growth on the molten pool.

Meanwhile, in Figure 6, as can be seen, the region on the track contains a higher concentration of defects than at region between the tracks, therefore, Zhang et al. and Kalita [19, 27] reported a similar result. In Figure 6b, the distance between the tracks is approximately 300 μm, in this region we can note presence of several nanopores, which may be attributed to volatilization of inclusions or vaporization of the substrate itself, caused by hydrogen and moisture in atmospheric air, which they are absorbed in laser-treated region, favoring thus the formation of pores, these results are consistent such as reported by Yilbas et al. and Pariona and Micene [5, 8]. The micrograph in Figure 6c shows a region on the track and region between the tracks under higher magnification, showing the concentration of defects with more detail. Figure 6d, also viewed under higher magnification, shows the region between the tracks, revealing, a uniform morphology with grains varied the form from columnar-like structure to irregular, confirming thus that the molten pool zone showed a fine microstructure due to high quenching rates. Nevertheless, [3] also observed these structures in Al-1.5 wt% Fe and [1], the last authors confirmed that Al-Co-Ce alloys contain Al-rich eutectic regions and whose structure was similar to Al-2.0wt.% Fe alloy. Consequently, due to peculiar characteristics of the microstructure shown in Figure 6, which presented highly improved properties, such as hardness, corrosion, and wear resistance, which are a result of dissolution of precipitates and formation of metastable phases, this subject was extensively discussed by Pariona and Micene [5]. Furthermore, several authors have reported similar findings, among them, [6, 18, 28].

The study is done by Pariona et al. [14], analyzed the hypoeutectic Al-1.5 wt.% Fe alloy LSR-treated and they observed the presence of nano-cracks between the tracks. However, this phenomenon in this study was not observed at the hypereutectic Al-2.0 wt% Fe alloy, as can be verified in Figure 6c and d, because, of the absence of microcracks was expected. Nevertheless, according to [29] stated that the formation Al-Fe alloys is impaired when the material contains coarse Al₃Fe particles, which tend to produce microcracks and reduce formability, whereas, this does not occur in the presence of Al₆Fe finely dispersed at the Al-2.0 wt.% Fe alloy. Meanwhile, Gremaud et al. [30] reported that increasing cooling rate of hypereutectic alloys containing up to 9 wt.% of Fe, which suppresses the formation of the stable Al₃Fe phase and is replaced by Al₆Fe phase, this fact, was confirmed in our result.

Other similar works were discussed by several authors, the following will be displayed [19, 31], these authors confirmed that the overlapping of laser beam tracks has a significant influence on surface quality of laser-treated materials. In addition, these authors showed how overlapping tracks affect heat flow, the solidification microstructure, and the electrochemical behavior, where the melt zone showed fine homogenized microstructure, due to high quenching rates during laser melting. Cordovilla et al. [20] remarked, which each track affects the microstructures produced by previous one and which when two consecutive tracks take place in an overlapping process. Meanwhile, all the studies cited by different authors confirm our results consistently.

So then, the hypereutectic Al-2.0 wt.% Fe alloy laser-treated is very peculiar and which this alloy has very special characteristics, still it has an innovative character and which can be applied in aerospace, aeronautical, and automobile industries. Karbalaian et al. [4], they pointed out that FEM reduces the costs related to experimental measurement. Moreover, with the simulation is easier to understand, analyze the result and optimize the process.

5. Conclusion

Will be pointed out the most important results of experimental validation of multi-track overlapping through the numerical simulation by FEM and whose influence in the microstructure of laser-treated workpiece.

1. The induced preheating effect by two overlapping of the first neighbors tracks on the kinetic of current track in the workpiece was verified through numerical simulation of the multi-track overlapping. Thus, FEM is capable of accurately simulating.

2. The results of overlapping ratio, as well as, the depth where the phase transformation occurs from liquid to solid were very nearby, both for the experimental and numerical simulation results.

3. The multi-track overlapping was simulated by the finite element technique and these results were confronted with the microstructure, being that the results were very close, however, the geometric dimensions of the molten pool and the intersection angle between melt tracks also were very close.

4. The multi-track overlapping and thermal cycling allied to high-speed cooling, influence, the liquid flow, mechanism of heat transport, and microstructure evolution in the molten pool of laser-treated alloy, promoting so a nanostructure characteristic.

5. The melt zone showed fine microstructure due to high quenching rates during laser melting and thus producing a fine homogenized microstructure at the melted region.

6. The multi-track overlapping influence on the surface quality of laser-treated materials.

7. This type of laser-treated alloy has very special characteristics and is of innovative character, then, it can be applied in the aerospace, aeronautical, and automobile industries

Acknowledgments

This work was entirely financed by CNPq (Brazilian National Council for Scientific and Technological Development), FundaçãoAraucária (FA), CAPES (Federal Agency for the Support and Evaluation of Postgraduate Education), and FINEP (Research and Projects Financing Agency). Also, thanks to LABMU–UEPG.