Optimization of Testing Parameters in Immersion Corrosion Testing of Aluminium Alloy (Al6061) – Alumina (Al₂O₃) Composites Fabricated by Stir Casting

Optimization of Testing Parameters in Immersion Corrosion Testing of Aluminium Alloy (Al6061) – Alumina (Al₂O₃) 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

1. 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 aluminum-silicon (Al-Si) 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 15-70 vol%; Continuous fibers of alumina, silicon carbide, Graphite (long-fiber reinforced composites); Discontinuous fibers of alumina (short-fiber 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.

2. 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	582-652	°C
   Brinell Hardness	45
   Ultimate Tensile Strength	130	MPa
   Yield Strength	276	MPa
   Modulus of Elasticity	68.9	MPa
   Thermal conductivity	167	W/m-K
   Coefficient of Thermal Expansion	23.6×10-6	m/°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	°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/°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 ± 30°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 600°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 800°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 680°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.

3. 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 10×10×10 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 (25°C). The solutiontospecimen surface area ratio will be about 150 ml cm-2, 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 ×(mimf)

   × ×

   (mmpy)

   The stir casting process starts with the preheating of graphite crucible in a gas-fired furnace for 20 minutes. The Alumina was initially preheated separately at a temperature of 250°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

4. 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)±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

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

The Model F-value of 10.62 implies the model is not significant relative to the noise. There is a 67.64 % chance that a 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 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 box-behnken design and test results

(5)

TABLE VIII ANOVA for Response Surface Quadratic model for Acidic Corrosion Rate

A positive "Pred R-Squared" 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 -2.89961E-004 *

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 F-value 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 R-Squared"" of 0.0516 is not as close to the ""Adj R-Squared"" 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.

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 +3.1553124E-004

* 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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