Optics & Laser Technology 48 (2013) 570–579
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Computational modeling and experimental based parametric study of multi-track laser processing on alumina Marco A. Moncayo, Soundarapandian Santhanakrishnan, Hitesh D. Vora, Narendra B. Dahotre * Department of Materials Science and Engineering, University of North Texas, 1155 Union Circle # 305310, Denton, TX 76203-5017, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 September 2012 Received in revised form 23 October 2012 Accepted 19 November 2012
In this work, both heat transfer modeling (COMSOL Multiphysicss) and experimental investigations were used to obtain the threshold multiple laser scanning processing parameters (laser power, scanning speed, fill space) for achieving more multi-faceted grains on the alumina’s surface. An ytterbium doped Nd:YAG laser (1064 nm) was used to perform the experiments for the designed processing conditions such as 32–127 106 J/m2 laser energy densities with fill space values of 3– 6 10 4 m. The SEM, EDX and wear results were used to quantify the effect of multiple laser processing variables on the change of microstructures (coarse grains, dendrite, multi-faceted grains) for obtaining the best processing conditions. By controlling the laser energy density with fill space, more multi-faceted grains and high wear resistance were achieved as the essential features for improving the abrasive quality. & 2012 Elsevier Ltd. All rights reserved.
Keywords: Multiple laser surface modification Alumina Heat transfer modeling
1. Introduction Alumina (Al2O3) is commonly used for making precise tools (abrasive wheels) that are heavily involved in the surface finishing processes. Al2O3 possesses high abrasive qualities, good performance at high temperatures, and an exceptional hardness. The topographical surface of Al2O3 is composed of a continuous porous structure that forms the abrasive edges which contribute to its high abrasive qualities. However, during the surface finishing process, the abrasive edges of the surface begin to deteriorate and break off, causing the efficiency and quality of the process [1–3]. Furthermore, the chips removed from the work piece can be potentially embedded themselves into the surface. These embedded chips substantially reduce the quality of the surface finishing process. In order to improve the surface finishing efficiency, the highly interactive surface of Al2O3 tool must undergo a post processing to remove the embedded chips from its surface. The conventional ways of doing this could lead high amount of material loss. By using the conventional techniques, 90% of the tool material is consumed or removed; only 10% is removed by the actual surface finishing process [1,2]. Laser surface modification (LSM) is an elegant technique that can be used for locally tailoring the Al2O3’s surface morphology. Lasers with high energy intensities have shown to produce enough of heat input to cause melting of the ‘‘worn out’’ edges and the ability to evaporate the low-bonding material as well as any foreign chips embedded in the surface [2].
*
Corresponding author. Tel.: þ 1 940 565 2031; fax: þ 1 940 565 4824. E-mail addresses:
[email protected] (M.A. Moncayo),
[email protected] (S. Santhanakrishnan),
[email protected] (H.D. Vora),
[email protected] (N.B. Dahotre). 0030-3992/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.optlastec.2012.11.019
During the LSM, the surface has undergone rapid melting and solidification which in turn generated specific microstructural features such as dendrites and multi-faceted grains (MFG) with high hardness and minimal pores. The MFG have composed of well-defined edges and vertexes that can be acted as the new abrasive features along the surface. The size of the MFG is in micron scale; large numbers of these grains occupying the surface should provide the enhanced surface finishing capabilities [2,3]. When the Al2O3’s tool size is bigger than laser beam spot, multiple scanning by a laser with slight overlap is necessity to process the entire surface area. In this, to optimize the laser processing variables (laser power, scanning speed, fill spacing) is cumbersome for obtaining a specified MFG microstructures. Number of experimental trials consumes more materials and time, therefore using a numerical heat transfer model can provide the necessary processing conditions to achieve more specified microstructures and surface properties. Previously, numerous research works [4–9] have been reported for using the single track LSM of Al2O3. Therefore, in this study, both COMSOL Multiphysicss based heat transfer modeling and experimental approaches were designed and used for obtaining the threshold multiple laser processing conditions to achieve the densely packed MFG with high wear resistance.
2. Experimental procedures Commercially available porous-structured alumina (82% Al2O3, remaining 18% of ceramics/glass bonding material, Colonial West Abrasives, CA), cut into a size of 0.060 0.030 0.030 m3 was used for laser processing (LP). Totally, 36 experiments (Table 1)
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Table 1 Laser processing parameters and wear results. Fill space Laser ( 10 4m) power (W)
Scanning speed (m/s)
Laser energy density ( 106 J/ m2)
Wear rate of sample ( 10 3)
Wear rate of pin ( 10 3)
Wear rate ratio ( 10 1)
0.3
0.020 0.030 0.040 0.020 0.030 0.040 0.020 0.030 0.040 0.020 0.030 0.040
64 43 32 85 57 43 107 71 53 128 85 64
0.64 0.62 0.44 0.40 0.34 0.74 0.58 0.48 1.65 0.94 0.39 0.77
4.61 2.16 2.46 3.93 5.56 2.40 3.27 6.79 3.95 4.06 5.94 8.11
1.38 2.89 1.78 1.01 0.61 3.10 1.76 0.71 4.19 2.32 0.65 0.95
0.020 0.030 0.040 0.020 0.030 0.040 0.020 0.030 0.040 0.020 0.030 0.040
64 43 32 85 57 43 107 71 53 127 85 64
1.98 2.07 0.56 1.69 0.89 0.71 7.80 2.61 0.44 1.56 0.65 1.06
3.98 4.06 4.01 5.83 3.14 5.11 6.31 4.67 4.08 5.45 3.05 4.51
4.98 5.11 1.40 2.90 2.82 1.39 12.36 5.59 1.07 2.86 2.13 2.35
0.020 0.030 0.040 0.020 0.030 0.040 0.020 0.030 0.040 0.020 0.030 0.040
64 43 32 85 57 43 107 71 53 127 85 64
0.68 0.89 N/A 1.17 1.06 0.91 1.23 0.77 1.16 1.07 0.67 0.60
6.07 5.53 N/A 7.50 5.38 3.11 5.25 2.27 3.67 7.95 4.52 2.48
1.13 1.60 N/A 1.56 1.96 2.93 2.34 3.38 3.17 1.35 1.49 2.41
600
800
1000
1200
0.45
600
800
1000
1200
0.6
600
800
1000
1200
Fig. 1. Schematic of multiple laser surface modification of an alumina sample.
where Dmass is the mass loss (kg) of the sample/pin after wear test. Post wear-tested LPAS were also undergone for ESEM with electron diffraction spectrum (EDX) and the data were recorded for further analysis. By using the image processing software (Image J), the distinguished microstructural features (columnar dendrites and MFG) of LPAS were measured. Correlating with the change of microstructural features (MFG size and dendrite spacing) of LPAS to the heat transfer results (temperature history, cooling rate, solidification rate), a relationship and threshold processing conditions could be established.
3. Computational modeling
combination of different set of laser powers (600–1200 W), scanning speeds (20–40 10 3 m/s), and fill spacing (3– 6 10 4 m/s) were used in this study. An Ytterbium doped Nd:YAG fiber laser (IPG YLS-3000) with Gaussian power distribution and a fixed beam focal spot (6 10 4 m) were used for processing the alumina samples (Fig. 1). A FEI Quanta 200 environmental scanning electron microscope (ESEM) with high vacuum chamber and low accelerating voltage ( 5 V) was used to reveal and record the micrographs of the laser processed alumina samples (LPAS). An inverse method of the typical wear test set up was used to determine the wear rate for various LPAS (Fig. 2). This set up consisted of a high power drilling tool (capable of rotational speeds up to 35,000 rpm) equipped with a steel pin. The reason for using such a high speed tool is to attempt for simulating an actual surface finishing process. By doing so, more credible data can be obtained from the experiments. On each LPAS, five trials, totally 180 tests were performed at different locations and time durations (Fig. 3). A load of 1 lb and rotating speed of steel pin at 30,000 rpm were used for each test to obtain the wear rate (Eqs. (1,2)). Wear rate of sample=pin ¼
Wear rate ratio ¼
D mass Initial mass of sample=pin
Wear rate of sample Wear rate of pin
ð1Þ
ð2Þ
Using COMSOL Multiphysicss, a two-dimensional heat transfer model was constructed. The multiple laser scanning effects (laser power, scanning speed, fill spacing) were incorporated in this model (Table 1). For simplicity and economize the computational time, only eight laser tracks effects were used. The moving laser location was simulated by using the residence time (tr ¼D/ v), where D (m) and v (m/s) are the laser beam diameter and scanning speed, respectively (Table 2). The multiple track model was incorporated the time required for the laser to complete its current track and relocate laterally, based on the designated fill space values (3, 4.5, 6 10 4 m). The multiple laser tracks were designed such a way the laser traveled in a parallel line fashion with three scanning speeds (20, 30, 40 10 3 m) and a default return speed (2.9 m/s). In this model, a novel approach was utilized. A designated location was selected to represent the heat transfer incident for each laser track. The total time required for the laser to complete the track including the return stoke was designated as ‘‘ttotal’’ period (Eq. (3)). Ls Lr þ ð3Þ v vr qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi where Lr ¼ L2s þ ðDdÞ2 , Ls and Lr are the lengths (m) of laser track and return stroke respectively. The return stroke speed is designated as vr (m/s) and Dd (m) is the fill space. When the material experienced this phase change, a significant amount of latent heat was released. This had a considerable effect on the specific heat, t total ¼
572
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Fig. 2. Schematic of (a) conventional and (b) inverse pin-on-disc wear test set up.
Table 3 Thermo-physical properties of alumina [11]
Fig. 3. Top view representation of the laser processed alumina sample undergoing for wear tests at different locations and time frames.
Table 2 Varying residence times. Beam diameter ( 10 4m)
Scanning speed (m/s)
Residence time (s)
6 6 6
0.020 0.030 0.040
0.03 0.02 0.015
Cp, of the alumina. To incorporate the change in the specific heat due to phase change into the model, C p was replaced with C p 1 and defined it as in Eq. (4). DH C p 1 ¼ C p þ dDH þ nZ ððTT m Þ, DT Þ ð4Þ Tm where DH is the latent heat of change (J/kg), d ¼ pffiffiffiffi ðexpððTT m Þ2 =ðDTÞ2 Þ=DT pÞ is a Gaussian curve, T is the instantaneous temperature (K), Tm is the melting temperature (K), DT represents the phase transition temperature range, and Z is the smooth Heaviside function [10]. The material properties used for compensating for the phase change are as shown in Table 3 [11]. The heat conduction equation that governed the heat transfer for this model is as follows: @ @T @ @T @T k þ k þ q00 ¼ rcp ð5Þ @x @x @y @y @t where q00 is the rate of internal energy conversion per unit area (heat flux, W/m2), r is the density of the material (kg/m3), cp is the specific heat per unit mass (J/kg K), and k is the thermal
Property
Symbol
Value
Absorptivity Thermal conductivity Density Latent heat of melting Latent heat of vaporization Melting temperature Vaporization temperature Half-width of the temperature curve
A k
0.25 35 W/(mK) 3800 kg/m3 1.06743 J/kg 1.0665 J/kg 2324 K 3273 K 30 K
r DH Lv Tm Tv DT
conductivity k (, W/m K) of the material. In this model, a constant thermal conductivity and density values were used. The boundary conditions used in the computational model are illustrated in Fig. 1 and defined in Table 4. Boundary 3 experienced exposure to the laser beam and corresponding convective cooling, and surface-to-ambient radiation simultaneously. In Table 4, b ¼1 for 0rirtr and b ¼0 for t4tr. b is the condition that determines if the heat source is actively heating the sample. h is the convective heat transfer coefficient (h¼10 W/m2K), e is the emissivity of alumina (e ¼0.7) for thermal radiation, and s is the Stefan–Boltzmann constant s ( ¼5.67x10 8 W/m2 K4) [11]. P g is the laser power density (W/m2), locx is the present laser moving location along the x-axis P, is the laser power (W), and | is the standard deviation of Pg . Boundaries 1–5 have experienced surface-to-ambient and convection cooling conditions. Boundary 6 was insulated. For the multiple laser track model, mesh size was set at a predefined ‘‘fine’’ level, a maximum element size of 105 10 6 m and minimum size of 30 10 6 m were used. The maximum element growth rate was 1.13. Digital probes were utilized to predict the heat transfer effects from multi-laser processing on alumina. The probes were placed along the left edge, center, and right edge of each of the eight laser tracks (Fig. 4). By doing so, the probes can be showed which regions have experienced the significant heat accumulation from preceding and/or succeeding laser tracks that would induce re-melting and re-solidification. When placing the digital probes for the multiple laser tracks model, fill space value was considered to have a significant effect in determining which regions have experienced re-melting and re-solidification.
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Table 4 Boundary conditions. Description
Boundary #
Boundary condition
Laser beam
2
Heat flux
Radiation Natural convection cooling Insulation
1,2,3 1,2,3
Surface-to-ambient Convective cooling
4
Insulation
Expression
Variable
h i Þ Gaussian laser power distributionP g ¼ A pDP 2 exp ðxlocx 2 2| ð4 Þ h i 4 4 Heat fluxk @T @z ¼ bAP g h½TT o es T T o h i h i 4 4 4 4 @T Boundaries 2k @T @z ¼ h½TT o es T T o Boundaries 1, 3k @y ¼ h½TT o es T T o k @T @y ¼ 0
pg
e h &
Fig. 4. Schematic of multiple laser track model (a) return stroke calculation (b) probe placement based on fill spacing values (c and d) digital probe placement for calculation of cooling rate and temperature gradient.
4. Results and discussion 4.1. Temperature history, cooling rate, and solidification rate For fixed fill space values (3–6 10 4 m), the surface temperature (TS) was increased (1950–6500 K) as the LED increased (31–127 106 J/m2). It appeared that the fill space effect has more influenced than the scanning speed and laser power effects during multiple scanning of the laser (Fig. 5). At lower fill space (3 10 4 m), TS reached far-above the vaporization temperature (TV) which in turn vaporized more material causing material loss (Fig. 5a). In the LSM, the material loss should be avoided, in light of this; the threshold processing conditions were obtained by analyzing the heat transfer results. At 3 10 4 m of fill space, if the LED was above 45 106 J/m2 that generated TS above vaporization. When the fill space was 4.5 10 4 m above 75 106 J/m2 LED the material had undergone vaporization (Fig. 5b). Similarly, for 6 10 4 m, above 100 106 J/m2 LED TS, reached to vaporization (Fig. 5c). It was apparently noted that at 6 10 4 m fill space, below 45 106 J/m2 LED, the material’s surface did not reach melting. It was importantly noted that the loss of material was
avoided as the fill space increased. At lower fill space (3 10 4 m), the processing range was smaller (30–45 106 J/ m2). As the fill space increased, a wide range of processing zone was obtained such as at 4.5 10 4 and 6 10 4 m fill spaces, the processing ranges were 30–75 106 J/m2 and 40–95 106 J/m2, respectively (Fig. 5b and c). The times of residence and laser track have more influenced on the cooling rate. Therefore, using the scanning speed for analysis has given more meaningful observation and discussion. The cooling rate was increased (2750–13000 K/s) as the scanning speed increased (0.02–0.04 m/s) for fixed fill space values (3–6 10 4 m, Fig. 6a–c, respectively). It can be noticed that for a fixed fill space (3 10 4 m), the cooling rates of the LPAS at 106 and 127 106 J/m2 LED were exhibited lower value than the LPAS processed at 84 106 J/m2 LED (Fig. 6a). A similar trend was observed for 4.5 and 6 10 4 m fill spaces for 0.02–0.04 m/s scanning speeds (Fig. 6b and c). The deviation was due re-melting and re-solidification resulted by the heat accumulation from the preceding or subsequent laser tracks. The regions that undergone for re-melting and re-solidification have exhibited lower cooling rate. It can be noticed that at higher scanning speed the re-melting was avoided attributed to lower residence time.
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Fig. 6. Computational average cooling rates vs. laser energy densities for fill spaces of (a) 3 10 4 m, (b) 4.5 10 4 m, and (c) 6 10 4 m. Fig. 5. Computational average peak temperatures vs. laser energy densities for fill spaces (a) 3 10 4 m, (b) 4.5 10 4 m, and (c) 6 10 4 m.
When the cooling rate of a particular processing condition did not follow the expected trend for any fixed scanning speed, one could assume that this particular processing condition could experience remelting and re-solidification.
Solidification rate is defined as the ratio between the cooling rate to the temperature gradient (refer Fig. 4c and d). At lower fill space (3 10 4 m), higher temperature gradient was generated which resulted lower solidification rate (Fig. 7a). As the fill space increased (4.5 10 4 m), the temperature gradient was decreased and the cooling rate was increased which in turn increased the solidification rate (Fig. 7b). Further increased the
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Fig. 8. Solidification rate vs. dendrite grain size.
Fig. 9. Surface morphology of an LPAS at 106 106 J/m2 with 3 10 4 m fill space.
4.2. Microstructural characterization
Fig. 7. Computational average solidification rates vs. laser energy densities for fill spaces of (a) 3 10 4 m, (b) 4.5 10 4 m, and (c) 6 10 4 m.
fill space to higher value (6 10 4 m), higher solidification rate was obtained attributed to minimal temperature gradient and moderate cooling rate (Fig. 7c). It can be noted that the solidification rate was increased as the scanning speed and fill space increased. The scanning speed appeared to have the largest effect on the solidification rate. In lieu, the solidification rate should have a significant effect on the size of the MFG formation.
Previous LSM studies [4,8,9] have shown that as the LED was increased, the grain size also increased. As previously discussed, when the solidification rate increased, the grain size also increased. Based on this knowledge, a general relationship was established (Fig. 8). As the solidification rate increased, the dendrite spacing should be relatively decreased. It was an important relationship to note. Obtaining a surface morphology with small features (both dendrites and grains) would prove extremely beneficial in improving the abrasive characteristics. If the features were to form at a smaller size, then more MFG features could potentially be formed, this means that these features would provide more abrasive edges. And with more abrasive edges, the abrasive qualities can be greatly improved. Therefore, small features will prove exceptionally ideal in terms of improving the abrasive nature of the laser modified alumina. From the heat transfer results, it was found that the fill space value has a significant effect on the surface morphology during the multiple scanning of a laser.
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LPAS with 3 10 4 m fill space primarily have a dendritic microstructure (Fig. 9). With this fill space value, the LED or scanning speed did not have a significant impact on the surface morphology. Samples with this fill space value have very dense surfaces with very little visible porosity. Grains, either coarse or MFG were not formed in this processing condition. As previously stated, the fill space value has determined the amount of overlap of the laser beam during the creation of subsequent laser tracks. With such a low fill space value, there was a large amount of material flow occurred. This material flow then covered on the MFG that were produced from the previously made laser track. Therefore, the primary abrasive features for these samples were the dendrites (Fig. 9). Samples with 4.5 10 4 m fill space value have exhibited a combination of coarse/fine grains and dendrites (Fig. 10). These grains were formed at the center of the track and the dendrites were extending toward the edge of the track. Since the fill space value has allowed for some overlap from the laser beam, it was
Fig. 10. Surface morphology of an LPAS at 106 106 J/m2 with 4.5 10 4 m fill space.
Fig. 11. Surface morphology of an LPAS at 106 106 J/m2 with 6 10 4 m fill space.
Fig. 12. The LPAS with the maximum wear rate of the pin, 1200 W with a fill space of 3 10 4 m and scanning speed of 0.04 m/s.
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Fig. 13. The LPAS with the minimum wear rate of the pin, 600 W with a fill space of 3 10 4 m and scanning speed of 0.03 m/s.
577
Fig. 14. The LPAS with maximum wear rate of the sample/maximum wear rate ratio, 1000 W with a fill space of 4.5 10 4 m and scanning speed of 0.02 m/s.
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possible that some grains have been covered by molten flow from the successive tracks. The LPAS with 6 10 4 m fill space value have showed the formation of fine MFG in the center of the laser tracks with dendrites protruding towards the edges of the track (Fig. 11). These grains have showed fine abrasive edges. Due to the low, if any, laser beam overlap associated with this fill space value, more grains were visible compared to the samples processed with 4.5 10 4 m fill space (refer Fig. 10). These grains were evenly distributed throughout the sample surface, except where the dendrites existed between the laser tracks. With the large amounts of MFG were populated in LPAS, it was believed that this particular fill space value has provided the best abrasive properties (Fig. 11). The multiple laser track study provided an understanding of the influence of scanning speed and fill space in addition to LED on the modification of surface morphology of alumina during LP. As the fill space value increased, the number of grains (coarse and fine) increased. Based on the computational results, the increase in scanning speed has increased the solidification rate. Therefore, the increase in scanning speed should also produce larger grains. Based on these results, this study warranted a validation of LPAS microstructures with the corresponding wear test results. 4.3. Wear results The wear results of all the 36 samples were summarized in Table 1, any sample(s) with wear rate values represented by ‘‘N/ A’’ means it did not deliver accurate results. For this sample(s), the laser processed region has broken during the wear test, resulting in unreliable wear rate data. Among the 36 samples, six were chosen for analysis based on certain criteria (Figs. 12–15). These criteria consisted of determining which parameters have the maximum/minimum wear rate of the pin, maximum/minimum wear rate of the sample, and maximum/minimum wear rate ratio (Table 5). Based on Eq. (2), the sample that possessed the minimum wear rate ratio was the ideal one. This was an essential part of the study to determine the optimal laser processing conditions for achieving more MFG. Based on this ratio, the sample processed at 800 W, 0.030 m/s, 3 10 4 m was exhibited the best relationship between the wear rate of the pin and wear rate of the sample (Fig. 15). Before the wear test was performed on the LPAS surface, it was characterized using the SEM (Figs. 12–15a) with EDX data (Figs. 12– 15b) for all cases. Post wear SEM also taken for all the cases (Figs. 12– 15c), it can be observed that a fine amount of steel residue from the pin was polluted on the surface of the LPAS. When this occurred, a thin layer of steel residue was existed between the LPAS and pin surface. This did not allow the much harder alumina (and the abrasive microstructural features) to successfully remove the material from the pin. The EDX analyses (Figs. 12–15b) were conducted on the locations in the higher magnification areas of the SEM (Figs. 12–15c). Among all samples, a significant amount of Fe was presented; however, the sample processed at 800 W, 0.030 m/s, 3 10 4 m was shown more Fe presence indicated higher wear resistance (Fig. 15). It appeared that the higher wear resistance indicated more MFG formation at 800 W, 0.030 m/s, 3 10 4 m which results in the formation of larger abrasive edges. Obviously, in obtaining larger number abrasive edges by using the controlled laser processing should be beneficial to surface processing industries.
5. Conclusions Fig. 15. The LPAS with the minimum wear rate of the sample/minimum wear rate ratio, 800 W with a fill space of 3 10 4 m and scanning speed of 0.03 m/s.
Among the laser processing variables, fill space has more influenced on the variation of surface temperature. At lower fill
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Table 5 Wear results of the alumina for optimal laser processing conditions. Criteria
Fill space ( 10 4 m)
Laser power (W)
Scanning speed (m/s)
Max WR of pin Min WR of pin Max WR Of sample Min WR Of sample Max WR ratio Min WR ratio
0.3
1200
0.040
64
8.1
0. 8
0.3
600
0.030
43
2.2
0. 6
1000
0.020
107
6.3
0. 78
800
0.030
57
5.6
0. 3
1000
0.020
107
6.3
0. 78
800
0.030
57
5.6
0. 3
0.45 0.3 0.45 0.3
Laser energy density WR of pin ( 106 J/m2) ( 10 3)
WR of sample ( 10 3)
WR ratio ( 10 1)
Solidification rate ( 10 3 m/s)
Dendrite spacing ( 10 6 m)
0.948
1.04
8.55
2.892
0.84
8.93
12.362
0.71
9.95
0.614
0.83
8.75
12.362
0.71
9.95
0.614
0.83
8.75
Note: WR stands for wear rate
space (3 10 4 m), smaller range (30–45 106 J/m2) of processing zone was obtained. For increasing the fill spaces (4.5– 6 10 4 m), a wider range (30–95 106 J/m2) of processing zone was achieved. The rates of cooling (2750–13000 K/s) and solidification (0.6–1.55 10 3 m/s) were mostly influenced by the scanning speed (0.02–0.04 m/s). As the cooling rate increased, the solidification rate increased which in turn generated more multi-faceted grains. The wear results indicated that a higher wear resistance was achieved for the sample processed at 56 106 J/m2 with 3 10 4 m, however, the sample processed at 106 106 J/m2 and 6 10 4 m fill space has exhibited more multi-faceted grains. References [1] Paglieri Stephen N, Foo King Y, Way JDouglas, Collins John P, Daniel LHarperNixon. A new preparation technique for Pd/alumina membranes with enhanced high-temperature stability. Industrial & Engineering Chemistry Research 1999;38(5):1925–36. [2] Lin Yue-Sheng, Anthonie JBurggraaf. Preparation and characterization of high-temperature thermally stable alumina composite membrane. Journal of the American Ceramic Society 1991;74(1):219–24.
[3] Herrmann M, Seipel B, Schilm J, Nickel K, Michael G, Krell A. Hydrothermal corrosion of zirconia-toughened alumina (ZTA) at 200 1C. Journal of the European Ceramic Society 2005;25(10):1805–12. [4] Jackson MJ, Khangar A, Chen X, Robinson GM, Venkatesh VC, Dahotre NB. Laser cleaning and dressing of vitrified grinding wheels. Journal of Materials Processing Technology 2007;185(1–3):17–23. [5] Harimkar SP, Dahotre NB. Effect of laser fluence on surface microstructure of alumina ceramic. Advances in Applied Ceramics 2006;105(6):304–8. [6] Khangar Abhijeet, Dahotre Narendra B, Jackson Mark J, Grant MRobinson. Laser dressing of alumina grinding wheels. Journal of Materials Engineering and Performance 2006;15(2):178–81. [7] Harmikar SP, Dahotre NB. Evolution of surface morphology in laser-dressed alumina grinding wheel material. International Journal of Applied Ceramic Technology 2006;3(5):375–81. [8] Harimkar Sandip P, Narendra BDahotre. Rapid surface microstructuring of porous alumina ceramic using continuous wave Nd:YAG laser. Journal of Materials Processing Technology 2008;209(10):4744–9. [9] Harimkar Sandip P, Narendra BDahotre. Characterization of microstructure in laser surface modified alumina ceramic. Materials Characterization 2008;59.6: 700–7 (Print). [10] Fjellsted J. Continuous casting. Model documentation. COMSOL multiphysics. Web, /http://www.comsol.com/showroom/documentation/model/382/S; 2011 [accessed 03.01.12]. [11] Gitzen Walter H. Alumina as a ceramic material. Columbus (OH): American Ceramic Society; 1970.
