 Open Access
 Total Downloads : 11
 Authors : P. V. Rajesh, K. Vimal Raj, P. Jothi Palavesan, S. Vijayaragavan
 Paper ID : IJERTCONV6IS07121
 Volume & Issue : ICONNECT – 2018 (Volume 6 – Issue 07)
 Published (First Online): 24042018
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Optimization of Testing Parameters in Immersion Corrosion Testing of Aluminium Alloy (Al6061) – Alumina (Al_{2}O_{3}) Composites Fabricated by Stir Casting
P. V. Rajesh
Assistant Professor, Department of Mechanical Engineering,
Saranathan College of Engineering
K. Vimal Raj
U.G. Scholars, Saranathan College of Engineering,
Trichy, India.
P. Jothi Palavesan
Assistant Professor, Department of Mechanical Engineering,
Saranathan College of Engineering
S. Vijayaragavan
U.G. Scholars, Saranathan College of Engineering,
Trichy, India.
Abstract: The present study deals with the Optimization of testing parameters in Immersion Corrosion Testing of Aluminium alloy (Al6061) Alumina (Al2O3) Composites fabricated by Stir casting used in Ship hulls. The sample specimens are made by varying the percentage of reinforcements with respect to aluminium alloy. Aluminium is compared with the Al6061 Al2O3 composites because the composite samples have improved corrosion resistance than the individual aluminium alloy. Finally, the most suitable composite that is having the best corrosion resistance is optimized using Box Behnken technique in Response Surface Methodology.
Keywords Aluminium; alumina; stir casting; box behnken; response surface methodology; composites; ship hulls

INTRODUCTION
Composite is a material composed of two or more distinct phases (matrix phase and dispersed phase) and having bulk properties significantly different form those of any of the constituents. Metal Matrix Composite (MMC) is a material consisting of a metallic matrix combined with a ceramic (oxides, carbides) or metallic (lead, tungsten, molybdenum) dispersed phase.
Aluminum Matrix Composites (AMC) is the widest group of Metal Matrix Composites. Matrices of Aluminum Matrix Composites are usually based on aluminumsilicon (AlSi) alloys and on the alloys of 2xxx and 6xxx series. Aluminum Matrix Composites (AMC) are reinforced by: Alumina (Al2O3) or silicon carbide (SiC) particles (particulate Composites) in amounts 1570 vol%; Continuous fibers of alumina, silicon carbide, Graphite (longfiber reinforced composites); Discontinuous fibers of alumina (shortfiber reinforced composites).
Aluminum Matrix Composites can be manufactured by Powder metallurgy(sintering), Stir casting and Infiltration methods. The following properties are typical for Aluminum Matrix Composites, High strength even at elevated
temperatures, High stiffness (modulus of elasticity), Low density, High thermal conductivity and Excellent abrasion resistance.

MATERIALS AND METHODS
A. Selection of Materials. Matrix
The matrix material to be used was chosen as Al6061 which is a precipitation hardened aluminium alloy, containing iron, silicon and chromium as its major alloying elements as indicated in Table I. It has good mechanical properties and exhibits good weldability, good formability and high corrosion.
TABLE I. CHEMICAL COMPOSITION OF ALUMINIUM
Constituents
Percentage
Manganese (Mn)
0.108%
Iron (Fe)
0.125%
Copper (Cu)
0.392%
Magnesium (Mg)
0.970%
Silicon (Si)
0.620%
Chromium (Cr)
0.079%
Others (Total)
0.04%
Aluminium (Al)
97.7%
TABLE II. PHYSICAL PROPERTIES OF Al6061
Properties
Value
Unit
Density
2.7
g/cm3
Melting point
582652
Â°C
Brinell Hardness
45
Ultimate Tensile Strength
130
MPa
Yield Strength
276
MPa
Modulus of Elasticity
68.9
MPa
Thermal conductivity
167
W/mK
Coefficient of Thermal Expansion
23.6Ã—106
m/Â°C
Reinforcement:
The materials selected to be reinforced into the metallic matrix is Alumina. Aluminium oxide is a chemical compound of aluminium and oxygen with the chemical formula Al2O3. Alumina is significant in its use to produce aluminium metal, as an abrasive owing to its hardness, and as a refractory material owing to its high melting point. It is reinforced in the Al6061 matrix to increase strength, hardness, stiffness, wear resistance and impact strength. Its attractive properties are listed in Table III.
Properties
Alumina (Al2O3)
Units
Density
3.98
g/cm3
Melting point
2300
Â°C
Vickers Hardness
1560
Fracture toughness
4.9
MPam
Elastic Modulus
300
GPa
Tensile Strength
210
MPa
Thermal conductivity
21
W/mK
Coefficient of thermal Expansion
9
m/Â°C
TABLE III PROPERTIES OF ALUMINA
A. Fabrication process
Stir casting is the most popular commercial method of producing aluminium based composites. In this method, pre heated ceramic particulates are incorporated into the vortex of the molten matrix created by a rotating impeller. In principle, it allows a conventional metal processing route to be used, and hence minimizes the final production cost of the product. This conventional method is also called as vortex method and liquid metallurgy route shown in fig. 1.
furnace, fitted with a temperature probe and heated to a temperature of 750 Â± 30Â°C (i.e) above the liquidus temperature of the alloy to ensure that the alloy melts completely. The liquid alloy was then allowed to cool in the furnace to a semi solid state at a temperature of about 600Â°C. Slag is removed using scum powder. Now with the help of electrical stirrer, the molten alloy is stirred at a constant speed of 450 rpm to create vortex. The preheated Alumina is then charged into the melt at constant pour rate and stirring of the slurry was performed manually for 510 minutes. Magnesium about 1% of weight is added to ensure good wettability for all proportions of the reinforcements.
The composite slurry was superheated to 800Â°C and a second stirring performed using a mechanical stirrer. The stirring operation was performed at a speed of 400 rpm for
10 minutes before casting into prepared sand moulds. Meanwhile the mould is preheated to avoid shrinkage of casting material. Then the melted matrix and reinforced particles are poured into the preheated mould and the pouring temperature should be maintained at 680Â°C. The entire process is done with either nitrogen gas or inert gas surrounding it to avoid contamination from atmosphere. The final shape of the composite may be a bar, rod or plate whatsoever the shape of the mould.

IMMERSION CORROSION TEST
CORROSION TEST
The corrosion behavior of the composites is studied by weight loss method using mass loss and corrosion rate measurements in both acidic and basic environments. The corrosion test will be carried out by immersion of the test specimens in 1N HCl (3.6ml in 100ml of distilled water) and 1N NaOH (4g in 100ml of distilled water) solutions which will be prepared following standard procedures. The specimens for the test are cut to size 10Ã—10Ã—10 mm and then mechanically polished with emery papers from 150 down to 600 grit sizes to produce a smooth surface. The samples are degreased with acetone, rinsed in distilled water, and then dried in air before immersion in still solutions at room temperature (25Â°C). The solutiontospecimen surface area ratio will be about 150 ml cm2, and the corrosion setups are exposed to atmospheric air for the duration of the immersion test. The weight loss readings will be monitored for a period of 24 hours.
FIG 1. STIR CASTING DIAGRAM
where
Corrosion rate = 87500 Ã—(mimf)
Ã— Ã—
(mmpy)
The stir casting process starts with the preheating of graphite crucible in a gasfired furnace for 20 minutes. The Alumina was initially preheated separately at a temperature of 250Â°C to remove moisture and to help even distribution within Al6061 alloy. The Al6061 alloy billets were charged into the
mi – Initial weight (g) mf – Final weight (g)
– Density (g/cm3) A – Area (cm2)
t – Time (hrs)
Run
Composition of Alumina
Stirring speed
Stirring time
Before weight mi
After
weight mf
Time
Volume
Density
Corrosion rate
Wt. %
rpm
min.
g
g
hrs.
cm3
g/cc
mmpy
1
10.00
200.00
2.00
20.1
19.7
24
7.20
2.792
362.72
2
5.00
200.00
4.00
20.6
20.2
24
7.20
2.861
353.97
3
5.00
600.00
4.00
22.4
22.0
24
7.20
3.111
325.53
4
10.00
600.00
2.00
20.2
19.8
24
7.20
2.805
361.05
5
5.00
400.00
2.00
20.4
20.1
24
7.20
2.833
268.10
6
15.00
600.00
4.00
9.3
8.8
28
4.32
2.153
503.98
7
10.00
400.00
4.00
4.7
4.2
28
1.44
3.263
332.53
8
10.00
400.00
4.00
4.7
4.2
28
1.44
3.263
332.53
9
10.00
600.00
6.00
12.5
12.3
28
5.76
2.170
200.01
10
10.00
400.00
4.00
4.7
4.2
28
1.44
3.263
332.53
11
15.00
400.00
6.00
8.7
8.3
28
4.32
2.014
431.01
12
10.00
400.00
4.00
4.7
4.2
28
1.44
3.263
332.53
13
10.00
200.00
6.00
5.4
5.1
28
1.44
3.750
173.61
14
15.00
200.00
4.00
21.5
21.2
28
7.20
2.986
218.03
15
5.00
400.00
6.00
21.3
20.9
24
7.20
2.958
342.37
16
15.00
400.00
2.00
21.3
21.0
28
7.20
2.958
220.09
17
10.00
400.00
4.00
4.7
4.2
28
7.20
3.263
332.53
Acidic corrosion rate of cast Al6061 is 1860.1 mmpy
Table IV Acidic corrosion rate results
Figure 2 Acidic Corrosion Rate Result & Basic Corrosion Rate Result

EXPERIMENTAL PROCEDURE
Response Surface Methodology
Response Surface Methodology is a collection of mathematical and statistical procedures used for analyzing of problems in which a particular response is influenced by multiple variables. A standard RSM Technique called Box Behnken Design Technique (BBD) was selected to study hardness, impact test and tensile test. BBD for three parameters composition, stirring speed and stirring time each with two levels was used as experimental design model.
combinations of variables for determining the complex response function. In many experimental conditions, it is possible to represent independent factors in quantitative form as given in Eq.(1).
These factors can be treated as having a functional relationship or response similar to:
Y = (x1,x2,..,xk)Â±er (1)
Where, the response Y and x1, x2 ,.., xk of k quantitative factors, the function is called response surface or response function, the residual er measures the experimental errors. When the mathematical form of is not known, it can be approximate satisfactorily within the experimental region by polynomial.
The regression equation of second order polynomial was used to represent the response surface Y is given by equation 2.
Basic corrosion rate of cast Al6061 is 4030.3 mmpy
Table V Basic corrosion rate results
24
Run 
Composition of Alumina 
Stirring speed 
Stirring time 
Before weight 
After weight 
Time 
Volume 
Density 
Corrosion rate 
Wt. % 
rpm 
min. 
g 
g 
hrs. 
cm3 
g/cc 
mmpy 

1 
10.00 
200.00 
2.00 
19.8 
18.6 
24 
7.20 
2.750 
1104.79 
2 
5.00 
200.00 
4.00 
20.1 
19.0 
24 
7.20 
2.792 
997.49 
3 
5.00 
600.00 
4.00 
22.2 
20.9 
7.20 
3.083 
1067.58 

4 
10.00 
600.00 
2.00 
19.9 
19.3 
24 
7.20 
2.764 
549.60 
5 
5.00 
400.00 
2.00 
20.1 
18.9 
24 
7.20 
2.792 
1088.17 
6 
15.00 
600.00 
4.00 
9.2 
7.6 
24 
4.32 
2.129 
1902.73 
7 
10.00 
400.00 
4.00 
4.4 
3.2 
24 
1.44 
3.056 
994.17 
8 
10.00 
400.00 
4.00 
4.4 
3.2 
24 
1.44 
3.056 
994.17 
9 
10.00 
600.00 
6.00 
12.6 
11.1 
24 
5.76 
2.188 
1735.71 
10 
10.00 
400.00 
4.00 
4.4 
3.2 
24 
1.44 
3.056 
994.17 
11 
15.00 
400.00 
6.00 
8.5 
7.1 
24 
4.32 
1.968 
1801.09 
12 
10.00 
400.00 
4.00 
4.4 
3.2 
24 
1.44 
3.056 
994.17 
13 
10.00 
200.00 
6.00 
5.5 
4.0 
24 
1.44 
3.819 
994.43 
14 
15.00 
200.00 
4.00 
21.3 
20.2 
24 
7.20 
2.958 
941.52 
15 
5.00 
400.00 
6.00 
21.1 
19.8 
24 
7.20 
2.931 
1122.95 
16 
15.00 
400.00 
2.00 
21.2 
19.8 
24 
7.20 
2.944 
1203.99 
17 
10.00 
400.00 
4.00 
4.4 
3.2 
24 
7.20 
3.056 
994.17 
Experimental Design by RSM Box Behnken Method
All the specimens were prepared according to the experimental runs developed by the DESIGN EXPERT 8. The controlling parameter set for running the design matrix is given Table VI.
Table VI Controlling Parameter and their Levels for the Study
Symbol 
Factor 
Experimental values 

Low level (1) 
High level (2) 

A 
Composition of Alumina (wt %) 
5 
15 
B 
Stirring speed (rpm) 
200 
600 
C 
Stirring time (minutes) 
2 
6 
The Model Fvalue of 10.62 implies the model is not significant relative to the noise. There is a 67.64 % chance that a Fvalue this large could occur due to noise. "Values of ""Prob > F"" less than 0.0500 indicate model terms are significant. "In this case there is one significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model. In this case weight percentage of alumina is process parameter which influences the response (Acidic Corrosion Rate).
TABLE VII Process design layout using boxbehnken design and test results
(5)
Run 
Composition of Alumina 
Stirring speed 
Stirring time 
Acidic Corrosion rate 
Basic Corrosion rate 
Wt. % 
rpm 
min. 
mmpy 
mmpy 

1 
10.00 
200.00 
2.00 
362.72 
1104.79 
2 
5.00 
200.00 
4.00 
353.97 
997.49 
3 
5.00 
600.00 
4.00 
325.53 
1067.58 
4 
10.00 
600.00 
2.00 
361.05 
549.60 
5 
5.00 
400.00 
2.00 
268.10 
1088.17 
6 
15.00 
600.00 
4.00 
503.98 
1902.73 
7 
10.00 
400.00 
4.00 
332.53 
994.17 
8 
10.00 
400.00 
4.00 
332.53 
994.17 
9 
10.00 
600.00 
6.00 
200.01 
1735.71 
10 
10.00 
400.00 
4.00 
332.53 
994.17 
11 
15.00 
400.00 
6.00 
431.01 
1801.09 
12 
10.00 
400.00 
4.00 
332.53 
994.17 
13 
10.00 
200.00 
6.00 
173.61 
994.43 
14 
15.00 
200.00 
4.00 
218.03 
941.52 
15 
5.00 
400.00 
6.00 
342.37 
1122.95 
16 
15.00 
400.00 
2.00 
220.09 
1203.99 
17 
10.00 
400.00 
4.00 
332.53 
994.17 
TABLE VIII ANOVA for Response Surface Quadratic model for Acidic Corrosion Rate
Source 
Sum of Squares 
df 
Mean Square 
F Value 
pvalue Prob > F 

Model 
53805.42 
9 
5978.38 
10.62 
0.0044 
Significant 
AComposition 
864.03 
1 
864.03 
6.54 
0.0146 
Predominantly influencing 
BStirring Speed 
9957.43 
1 
9957.43 
1.22 
0.3063 

CStirring Time 
527.48 
1 
527.48 
0.065 
0.8068 

AB 
24710.27 
1 
24710.27 
3.02 
0.1257 

AC 
4668.31 
1 
4668.31 
0.57 
0.4745 

BC 
196.98 
1 
196.98 
0.024 
0.8810 

A2 
3650.87 
1 
3650.87 
0.45 
0.5254 

Source 
Sum of Squares 
df 
Mean Square 
F Value 
pvalue Prob > F 

B2 
566.45 
1 
566.45 
0.069 
0.8000 

C2 
9137.03 
1 
9137.03 
1.12 
0.3256 

Residual 
57230.87 
7 
8175.84 

Lack of Fit 
57230.87 
3 
19076.96 

Pure Error 
0.000 
4 
0.000 

Cor Total 
1.110E+005 
16 
Std. Dev. 
90.42 
RSquared 
0.7246 
Mean 
319.01 
Adj RSquared 
0.6481 
C.V. % 
28.34 
Pred RSquared 
0.5468 
PRESS 
9.157E+005 
Adeq Precision 
13.615 
2 Log Likelihood 
186.31 
BIC 
214.64 
AICc 
242.98 
A positive "Pred RSquared" implies that the overall mean may be a better predictor of your response than the current model. "Adeq Precision" measures the signal to noise ratio. A ratio of 13.615 indicates an inadequate signal and we should not use this model to navigate the design space.
Final Equation in Terms of Actual Factors:
Acidic Corrosion Rate = +621.59 66.5825 * Composition 0.4477* Stirring Speed +47.9274 * Stirring Time +0.07859 *
Composition * Stirring Speed +3.4162 * Composition * Stirring Time
+0.017543* Stirring Speed * Stirring Time +1.1778 * Composition^2 2.89961E004 *
Stirring Speed^2 11.645 * Stirring Time^2
The equation in terms of actual factors can be used to make predictions about the response for given levels of each factor. Here, the levels should be specified in the original units for each factor. This equation should not be used to determine the relative impact of each factor because the coefficients are scaled to accommodate the units of each factor and the intercept is not at the center of the design space.
TABLE IX ANOVA for Response Surface Quadratic model for The Model Fvalue of 12.34 implies the model is significant. There is only a 0.16% chance that an F value this large could occur due to noise. "Values of ""Prob > F"" less than 0.0500 indicate model terms are significant. " In this case A, B, C, AB, BC, A2 are significant model
terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model. In this case weight percentage of alumina is process parameter which influences the response (Basic Corrosion Rate).
"The ""Pred RSquared"" of 0.0516 is not as close to the ""Adj RSquared"" of 0.8645 as one might" normally expect; i.e. the difference is more than 0.2. This may indicate a large block effect or a possible problem with your model and/or data. Things to consider are model reduction, response transformation, outliers, etc. All empirical models should be tested by doing confirmation runs. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 11.691 indicates an adequate signal. This model can be used to navigate the design space.
Source 
Sum of Squares 
df 
Mean Square 
F Value 
pvalue Prob > F 

Model 
1.808E+006 
9 
2.009E+005 
12.34 
0.0016 
Significant 
AComposition 
3.093E+005 
1 
3.093E+005 
25.81 
0.0014 
Most influencing 
BStirring Speed 
1.853E+005 
1 
1.853E+005 
11.38 
0.0119 

CStirring Time 
3.645E+005 
1 
3.645E+005 
22.39 
0.0021 

AB 
1.985E+005 
1 
1.985E+005 
12.20 
0.0101 

AC 
79050.95 
1 
79050.95 
4.86 
0.0634 

BC 
4.202E+005 
1 
4.202E+005 
19.00 
0.0033 

A2 
2.048E+005 
1 
2.048E+005 
12.58 
0.0094 

B2 C2 
670.72 33607.83 
1 1 
670.72 33607.83 
0.041 2.06 
0.8449 0.1939 

Residual 
1.140E+005 
7 
16278.91 

Lack of Fit 
1.140E+005 
3 
37984.12 

Pure Error 
0.000 
4 
0.000 

Cor Total 
1.922E+006 
16 
Std. Dev. 
127.59 
RSquared 
0.9407 
Mean 
1145.94 
Adj RSquared 
0.8645 
C.V. % 
11.13 
Pred RSquared 
0.0516 
PRESS 
1.823E+006 
Adeq Precision 
11.691 
2 Log Likelihood 
198.02 
BIC 
226.35 
AICc 
254.69 
Final Equation in Terms of Actual Factors:
Basic Corrosion Rate = +3909.544 282.44649 * Composition 4.960* Stirring Speed 536.653 * Stirring Time
+0.22278 * Composition * Stirring Speed +14.058 * Composition * Stirring Time
+0.810293 * Stirring Speed * Stirring Time +8.82155 * Composition^2 +3.1553124E004
* Stirring Speed^2 +22.335* Stirring Time^2
CONCLUSION
In this study, the aluminium (Al6061) – alumina composites were fabricated by varying the composition of alumina, stirring speed and stirring time. The influence of the three factors were analysed by using Box Behnken design. Also, a quadratic model equation was developed which explains the relationship between the responses and the process parameters. The effects of process parameter levels on the response value were analysed using analysis of variance (ANOVA). From the obtained results, corrosion rate of the aluminium alumina composites were highly influenced by the composition of alumina. Also the optimized values for obtaining the desired properties is found.
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