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International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 8, August 2017, pp. 1383–1400, Article ID: IJMET_08_08_142

Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=8

ISSN Print: 0976-6340 and ISSN Online: 0976-6359

© IAEME Publication Scopus Indexed

EXPERIMENTAL INVESTIGATION AND MECHANICAL CHARACTERIZATION OF

CARBON NANOTUBES/AA6063 ALUMINIUM METAL MATRIX COMPOSITE USING STIR

CASTING METHOD P.B. Senthil kumar

Assistant Professor, Department of Automobile Engineering,

Veltech Dr.RR & Dr.SR University, Chennai, Tamil Nadu, India

R.Hushein, K.Logesh Assistant Professor, Department of Mechanical Engineering,


K.Inbarasan UG Scholar, Department of Mechanical Engineering,


ABSTRACT: Aluminium is one of the light metals and the most commonly used metal.

Aluminium is having electrical and thermal conductivity properties are very good and

also good corrosion resistance. Aluminium composites are used in various

applications like Automobiles, Aerospace, Marine structure applications, Building

and construction industry. The present work focusing on fabrication of AA6063

Aluminium matrix composites (AMCs) CNT reinforced by stir casting method. The

microstructure and mechanical properties of the fabricated AMCs are analyzed. The

mechanical properties like hardness and tensile strength will be tested for various

weight percentages of CNTs in the Aluminium matrix. The ANN model for physical

properties and tensile strength are going to be generating and using ANN models the

different properties of AMC’s will be predicted. The variation of cluster creation,

porosity segregation and other defects were analyzed by using scanning electron

microscope, hardness test and wear test with different structure will be studied.

Keywords: AA6063, AMC (Aluminium Matrix Composites), CNT (Carbon

Nanotubes), Mechanical Properties, SEM (Scanning Electron Microscope).

Experimental Investigation and Mechanical Characterization of Carbon Nanotubes/AA6063

Aluminium Metal Matrix Composite using Stir Casting Method


Cite this Article: P.B.Senthilkumar, R.Hushein, K.Logesh and K.Inbarasan,

Experimental Investigation and Mechanical Characterization of Carbon

Nanotubes/AA6063 Aluminium Metal Matrix Composite using Stir Casting Method,

International Journal of Mechanical Engineering and Technology 8(8), 2017,

pp. 1376–1400.

http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=8

1. INTRODUCTION Composite material is a material composed of two or more distinct phases (matrix phase and

reinforcing phase) and having bulk properties significantly different from those of any of the

constituents [1-3]. Many of common materials (metals, alloys, doped ceramics and polymers

mixed with additives) also have a small amount of dispersed phases in their structures,

however they are not considered as composite materials since their properties are similar to

those of their base constituents (physical property of steel are similar to those of pure iron)

[4]. Favorable properties of composites materials are high stiffness and high strength, low

density, high temperature stability, high electrical and thermal conductivity, adjustable

coefficient of thermal expansion, corrosion resistance, improved wear resistance etc [5].

Metal-matrix composites (MMCs), as light and strong materials, are very attractive for

application in different industries. Generally, regards to the mechanical properties, the

reinforcements results in higher strength and hardness, often at the expense of some ductility

[6-9].

AMC refers to the class of light weight high performance aluminium centric material

systems. The reinforcement in AMCs could be in the form of a few percent to 70 %. AMC

reinforced with particles and whiskers are widely used for High performance applications

such as in automotive, military, aerospace and electricity industries because of their improved

physical and mechanical properties In the composites relatively soft alloy like aluminium can

be made highly resistant by introducing predominantly hard but brittle particles such as

Al2O3 and SIC. Properties of AMCs can be tailored to the demands of different industrial

applications by suitable combinations of matrix, reinforcement and processing route [10].

Al materials composites (AMCs) reinforced with ceramic particulates, exhibit high

strength, hardness and elastic modules AMCs are one of the advanced engineering materials

that have been developed for weight-critical applications in the aerospace, and more recently

in the automotive industries due to their excellent combination of high specific strength and

better wear resistance [11-12].

Production and characterization of AA6061–B4C stir cast composite. This work focuses

on the fabrication of aluminum (6061-T6) matrix composites (AMCs) reinforced with various

weight percentage of B4C particulates by modified stir casting route. The wettability of B4C

particles in the matrix has been improved by adding K2TiF6 flux into the melt. The

microstructure and mechanical properties of the fabricated AMCs are analyzed. The optical

microstructure and scanning electron microscope (SEM) images reveal the homogeneous

dispersion of B4C particles in the matrix. The reinforcement dispersion has also been

identified with X-ray diffraction (XRD). The mechanical properties like hardness and tensile

strength have improved with the increase in weight percentage of B4C particulates in the

aluminum matrix [1, 13-15]

Artificial neural networks (ANN) have emerged as one of the useful artificial intelligence

concepts used in the various engineering applications. Due to their massively parallel

structure and ability to learn by example, ANN can deal with non-linear modeling for which

an accurate analytical solution is difficult to obtain [16]. ANN have already been used in

medical applications, image and speech recognition, classification and control of dynamic

P.B. Senthil kumar, R.Hushein, K.Logesh and K.Inbarasan


systems, among others; but only recently have they been used in modeling the mechanical

behavior of fiber-reinforced composite materials. This work is an attempt to reflect on the

work done in the mechanical modeling of fiber-reinforced composite materials using ANN

during the last decade [17-20].

Artificial neural networks applied to polymer composites Inspired by the biological

nervous system, an artificial neural network (ANN) approach is a fascinating mathematical

tool, which can be used to simulate a wide variety of complex scientific and engineering

problems [21]. A powerful ANN function is determined largely by the interconnections

between artificial neurons, similar to those occurring in their natural counterparts of biological

systems. Also in polymer composites, a certain amount of experimental results is required to

train a well-designed neural network. After the network has learned to solve the material

problems, new data from the similar domain can then be predicted without performing too

many, long experiments. The objective of using ANNs is also to apply this tool for systematic

parameter studies in the optimum design of composite materials for specific applications [22-

24]. In the present review, various principles of the neural network approach for predicting

certain properties of polymer composite materials are discussed. These include fatigue life,

wear performance, response under combined loading situations, and dynamic mechanical

properties. Additionally, the ANN approach has been applied to composite processing

optimizations. The goal of this review is to promote more consideration of using ANNs in the

field of polymer composite property prediction and design [3].

CNT reinforced light metal composites produced by melt stirring and by high pressure die

casting. Light metal matrix composites are of great interest due to their potential for reducing

CO2 emission through lightweight design e.g. in the automotive sector. Carbon nanotubes can

be considered as ideal reinforcements, due to their high strength, high aspect ratio and

thermo-mechanic properties. In this research, CNT reinforced light metal composites were

produced by melt stirring and by high pressure die casting, which can be both easily scaled

up. The light metal composites showed significantly improved mechanical properties already

at small CNT contents. The influence of CNT concentration on the composites was also

studied [4].

The objective of this work is to CNT reinforce aluminium composite by stir casting

method. Different weight % of MWCNTs has to be added to aluminium-6063 separately to

make aluminium composite and its mechanical properties have been investigated using tests

like Tensile, Hardness and XRD. The improvement of mechanical properties for both the

cases has to be compared with aluminium 6063. The ANN model for hardness and tensile

strength are going to be generated and using ANN models the properties of AMC’s will be

predicted.

2. MATERIAL USED

2.1. Aluminium Alloy AA6063 Aluminium alloys can be developed from one or a combination of metal forming process. The

mechanically worked after being cast and cannot be strengthened by precipitation hardening;

they are hardened primarily by cold working. Working the material densities it, adding tensile

strength but lowering malleability. Casting alloys are formed by a casting process that forms

alloys either continuously or into set shapes [4]. They include heat-treatable and non-heat-

treatable alloys, allowing more workability and higher amounts of alloying elements more

workability and higher amounts of alloying elements to be added but decreasing the alloy

[24].




2.2. Carbon Nanotubes Carbon nanotubes are found in 1985.Fullerenes played vital role in discovery of carbon

nanotubes. They were double layered tubes having diameter about 30mm and were closed

from both ends. This was a major discovery which supported a lot in the electronics,

mechanics and chemistry. CNT are smallest molecule of graphite carbon with outstanding

characteristics. The main reason for introducing CNTs into light metal matrix composites is

enhancement of the mechanical properties like density and hardness [7].

3. EXPERIMENTAL PROCEDURE

3.1. Stir Casting Stir casting is a liquid state method of composites materials fabrication, in which a dispersed

phase (ceramic particles, short fibers) is mixed with a molten matrix metal by means of

mechanical stirring. The simplest and the most cost effective method of liquid state

fabrication is Stir Casting Shown in Figure 1&2.

Figure 1 Preheating of Al6063 Figure 2 Mixing of preheated MWCNT powder with molten A6063

Figure 3 Preparation of Sand Moulds

Stir casting involves adding particles into the melt in the crucible which is kept inside the

furnace. The melt is transferred to permanent moulds after stirring as shown in Figure 3,

Modified stir casting involves directly transferring the melt into a permanent mould with a

bottom pouring arrangement attached to the furnace as shown in Figure 4 &5.

Figure 4 Pouring of Molten Metal and Figure 5 Preparation of AL6063 and

Solidified Specimens (AL6063+MWCNT) Samples



3.2. Artificial Neural Network The Inputs enter into the processing element from the upper left. The first step is to multiply

each of these inputs by their respective weighting factor [w(n)]. These modified inputs are

then fed into the summing function, which usually sums these products; however, many

different types of operations can be selected. The output of the summing function is then sent

into a transfer function, which turns this number into a real output (a 0 or a 1, -1 or +1 or

some other number) via some algorithm. The transfer function can also scale the output or

control its value via thresholds [6]. This output is then sent to other processing elements or an

outside connection, as dictated by the structure of the network.

3.3. Brinell Hardness Test The Brinell hardness test method consists of indenting the test material with a hardened steel

ball intender of diameter 5mm. The intender is forced into the test material under a maximum

load of 1000 kgf as shown in Figure 6.

Figure 6 Testing of samples in Brinell Hardness Machine

3.4. Tensile Test Tension test is carried out; to obtain the stress-strain diagram, to determine the tensile

properties and hence to get valuable information about the mechanical behaviour and the

engineering performance of the material [25]. Machining in the Lathe machine as shown in

Figure 7 and tensile specimen as shown in Fig.8. The major parameters that describe the

stress-strain curve obtained during the tension test are the tension tesion test are the tension

strength (UTS), yield strength (σy), Elastic modulus (E), percentage of elongation (∆L%), and

the reduction in area (RA%) can also be found by use of this testing technique [26].

Figure 7 Machining Operation in Lathe Figure 8 Preparation of Tensile Specimen

Machine as per ASTM B-557M




3.5. X-RAY Diffraction Test XRD is a technique that is widely used in nano –technology. Applications range from phase

identification, quantification and determination of crystallite and particle size, all on nano-

scale level. English physicists Sir W.H. Bragg and his son Sir W.L. developed a relationship

in 1913 to explain why are cleavage faces of crystals appear to reflect X-ray beams at certain

angles of incidence (theta,θ). The variable d is the distance between atomic layers in a crystal,

and the variable lamda (λ) is the wavelength of the incident X-ray beam: n is an integer, X-ray

diffraction occurs at specific angle m(2θ) with respect to lattice spacing’s defined by bragg’s

law and is expressed as: n λ= 2dsinθ [4]. The atomic planes of a crystal cause an incident

beam of X-rays to interfere with one another as they leave the crystal. The phenomenon is

called X-ray diffraction. Diffraction occurs only when braggs law is satisfied condition for

constructive interference (x-rays1 & 2) from planes with spacing’d’ [6].

4. RESULT & DISCUSSION

4.1. Brinell Hardness The table 1 Shows the observed that for pure aluminium 6063 Maximum Hardness value

Achieved at 59.55(BHN). From the table 2, Shows the observed that for (Al+MWCNT) the

best obtained at 1% weight percentage of MWCNT i.e. Maximum Hardness Value obtained

for 1% weight percentage SWCNT is 62.118 BHN. The increasing trend of hardness strength

with increase in weight percentage of MWCNT up to 1% weight fraction. Beyond this weight

fraction the hardness trend started decreasing as the density of SWCNT particles in the melt

started decreasing thereby lowering the hardness. The best value of hardness comes out to be

of sample containing 1% MWCNT i.e. 62.118 BHN.

Table 1 Brinell Hardness Test For Pure Aluminium

Specimen Load (KGF)

Penetrator Diameter

(mm)

1st Trail (BHN)

2nd Trail

(BHN)

3rd Trail

(BHN)

4th Trail

(BHN)

5th Trail

(BHN)

Average (BHN)

AL 6063 1000 5 59.55 59.55 59.55 59.55 59.55 59.55

Table 2 Brinell Hardness Test For (Al+MWCNT) Samples

Specimen Load (KGF)

Penetrator Diameter

(mm)

1st Trail (BHN)

2nd

Trail (BHN)

3rd Trail (BHN)

4th Trail (BHN)

5th Trail (BHN)

Average (BHN)

0.25%

MWCNT 1000 5 63.66 63.66 55.67 59.55 59.55 60.41

0.75%

MWCNT 1000 5 59.55 63.66 63.66 59.55 59.55 61.19

1% MWCNT 1000 5 63.66 68.05 55.67 63.66 59.55 62.118

1.125%

MWCNT 1000 5 59.55 59.55 55.67 59.55 68.05 60.47

1.25%

MWCNT 1000 5 59.55 59.55 63.66 68.05 59.55 62.07

4.1.1. Brinell Hardness Test For (Al+MWCNT) Samples

Experiments have been conducted by varying weight fraction of MWCNT (0.25%, 0.75%,

1%, 1.125% and 1.25%). Hardness strength were recorded and tabulated. Hardness test has



been conducted on each specimen using a load of 1000 kgf and a steel ball of diameter of

5mm. The result from table 1 shows the increasing trend of hardness strength with increase in

weight percentage of MWCNT up to 1% weight fraction. Beyond this weight fraction the

hardness trend started decreasing as MWCNT particles interact with each other leading to

clustering of particles and consequently settling down. Eventually the density of MWCNT

particles in the melt started decreasing thereby lowering the hardness. The best value of

hardness comes out to be samples containing 1% MWCNT i.e. 62.118BHN (B. SCALE).

4.2. Tensile Test The tensile properties of the Al 6063 and nano composite samples were going to be

determining in accordance with ASTM method, schematic representation as shown in Fig.9.

An experiment has been conducted by varying weight fraction of MWCNT (0.25%, 0.75%,

1%, 1.125% and 1.25%). Tensile test has to be conduct on each specimen using a Universal

tensile testing machine.

Figure 9 Dimensions of Tensile Specimen as per ASTM B-557M

Figure 10 Stress Vs Strain for Al6063 Samples

From the Fig. 10 it could be observe that for Pure Aluminium maximum ultimate tensile

strength (UTS) occurs at 99.44 MPa. Yield strength (σy) is at 70.42 Mpa. Due to this the

percentage elongation (∆L) of 3.36% is achieved.

Figure 11 Stress Vs Strain For (Al6063+0.25% MWCNT)




From the Fig. 11, it could be observe that for (Al6063+0.25%MWCNT), ultimate tensile

strength (UTS) occurs at 107.45 MPa, Yield strength (σy) is at 54.59 Mpa. Due to this the


Figure 12 Stress Vs Strain for (Al6063+0.75% MWCNT)

From the Fig.12, it could be observe that for(Al6063+0.75%MWCNT) Ultimate tensile

strength (UTS) occurs at110.66 Mpa. Yield strength (σy) is at 73.3 MPa. Due to this the


Figure 13 Stress Vs Strain for (Al6063+1%MWCNT) Samples

From the Fig. 13, it could be observe that for (Al6063+1%MWCNT), Ultimate tensile

strength (UTS) occurs at 34.19 MPa, Yield strength (σy) is at 29.04 MPa. Due to this the

percentage elongation (∆L) of 2.72 % is achieved.

Figure 14 Stress Vs Strain for (Al6063+1.125%) Samples



From the Fig. 14, it could be observe that for (Al6063+1.125%MWCNT), Ultimate tensile


percentage elongation (∆L) of 2.88 % is achieved.

Figure 15 Stress Vs Strain for (Al6063+1.25%) Samples

From the Fig.15, it could be observe that for(Al6063+1.25%MWCNT), Ultimate tensile


percentage elongation (∆L) of 4% is achieved. Shows the table 3 it could be observed that for

pure Al Maximum ultimate tensile strength (UTS) occurs at 99.44 Mpa, Yield strength (σy) is

at 70.42 Mpa with elongation of 3.36% is achieved.

Table 3 Tensile Test Results for Pure Aluminium

SAMPLE DIAMETER (mm)

AREA (mm²)

IGL (mm)

FGL (mm)

TENSILE STRENGTH

(Mpa)

YIELD STRENGTH

(Mpa)

% ΔL

Al 6063 12.5 124.69 62.5 64.60 99.44 70.42 3.36

From the table 4 it could be observe that for (Al6063+MWCNT) Maximum ultimate

tensile strength occurs at 110.66 Mpa, Yield strength (σy) is at 73.33 MPa with elongation of

4.80 % is achieved.

Table 4 Tensile Test Results For (Al6063+MWCNT) Samples

SAMPLES DIAMETER (mm)

AREA (mm²)

IGL (mm)

FGL (mm)

TENSILE STRENGT

H (mpa)

YIELD STRENGTH

(mpa) ΔL

0.25%MWCNT 12.5 124.69 62.5 65.0 107.45 54.59 4.0

0.75% MWCNT 12.5 124.69 62.5 65.5 110.66 73.33 4.80

1% MWCNT 12.5 124.69 62.5 64.2 34.19 29.04 2.72

1.125%

MWCNT 12.5 124.69 62.5 64.3 98.25 70.15 2.88

1.25% MWCNT 12.5 124.69 62.5 65.0 56.10 26.32 4.0

The Ultimate tensile strength (UTS) increases up to 110.66 Mpa while adding 0.75%

MWCNT with Al6063. With increasing amount of MWCNT i.e at 1% and 1.25%, strength

trend start decreasing and ductility gradually drops to a level similar to that of pure Al6063.

The maximum amount of energy required for breaking is observed for a composition of




0.75% MWCNT incorporated and also the expenditure of fracture energy for the nano

composite with 0.75% MWCNT is higher than pure Al6063.

4.3. X-RAY Diffraction Test for Aluminium Matrix Composites

Figure 16 XRD image for Pure Aluminium

Table 5 Indexed parameters for Pure Aluminium

Pos. [°2Th.] Height [cts] FWHM Left [°2Th.] d-spacing [Å] Rel. Int. [%]

38.4391 2486.18 0.1968 2.34193 100.00

44.6722 1676.27 0.2460 2.02857 67.42

65.0430 211.39 0.2952 1.43399 8.50

78.1582 519.74 0.2400 1.22193 20.91

78.3973 305.37 0.1800 1.22183 12.28

82.3820 162.72 0.3000 1.16965 6.55

From table 5, the index peaks represents the XRD analysis of the Nano composites. The

highest peak position of without MWCNT Nano composites is 2486.18 counts and the peak

angle lays at 38.4391 and d-spacing 2.3419.

Figure 17 XRD Image for Al6063-0.25% MWCNT



Table 6 Indexed parameters for Al6063-0.25% MWCNT

Pos. [°2Th.] Height [cts] FWHM Left [°2Th.]

d-spacing [Å] Rel. Int. [%]

38.3039 2583.34 0.1968 2.34988 100.00

44.5444 2167.30 0.2460 2.03410 83.90

64.9273 314.92 0.1968 1.43627 12.19

78.0433 470.89 0.2460 1.22446 18.23

82.2650 121.31 0.1968 1.17199 4.70

From table 6, the index peaks represents the XRD analysis of the Nano composites with

0.25% MWCNT. The highest peak position of with Al-0.25% MWCNT Nano composites is

2583.34 counts and the peak angle lays at 38.3039 and d-spacing 2.34988.


Table 7 Indexed parameters for Al6063-0.75% MWCNT obtained from fig 4.11


38.3519 2510.62 0.2460 2.34705 100.00

44.5937 1354.36 0.2460 2.03196 53.95

64.9510 317.61 0.2460 1.43580 12.65

78.1050 520.19 0.1800 1.22263 20.72

78.3750 215.33 0.1200 1.22213 8.58

82.2967 152.76 0.1200 1.17065 6.08








Table 8 Indexed parameters for Al6063-1.0% MWCNT obtained from figure 4.12



38.4060 2264.46 0.1968 2.34387 100.00

44.6441 1683.95 0.2460 2.02979 74.36

65.0078 314.78 0.2460 1.43468 13.90

78.1369 460.19 0.2460 1.22323 20.32

82.3379 121.35 0.1968 1.17114 5.36





Table 9 Indexed parameters for Al6063-1.125% MWCNT


38.3887 2552.47 0.1968 2.34489 100.00

44.6279 1825.78 0.2460 2.03048 71.53

64.9894 410.54 0.2460 1.43505 16.08

78.1153 421.39 0.2460 1.22351 16.51

82.3357 118.18 0.1968 1.17116 4.63




1.125% MWCNT. The highest peak position of with Al-1.125% SWCNT Nano composites is

2552.47counts and the peak angle lays at 38.3887 and d-spacing 2.34489.


Table 10 Indexed parameters for Al6063-125% MWCNT



38.4952 2509.22 0.1968 2.33864 100.00

44.7414 1555.44 0.2460 2.02560 61.99

65.0936 291.79 0.1968 1.43300 11.63

78.2095 335.62 0.3000 1.22126 13.38

78.4650 185.58 0.1800 1.22095 7.40

82.4240 144.48 0.2400 1.16916 5.76

82.7167 79.27 0.1800 1.16866 3.16



2509.22counts and the peak angle lays at 38.4952 and d-spacing 2.33864. From the table 11,

the penetration of X-ray increases with addition of MWCNT This shows that the lightweight

materials with high strength occurs on Al6063 Aluminium alloy. So Al nano composites

developed to increase high strength to low weight ratio used widely in aerospace, aircraft and

automotive industries.

Table 11 Comparison of XRD Results For (Al6063+MWCNT) Samples

S.No Material Position (2θθθθ) Height(cts) d-spacing

1 Al6063 38.4391 2486.18 2.34193

2 Al+0,25%MWCNT 38.3039 2583.34 2.34988

3 Al+0.75%MWCNT 38.3519 2510.62 2.34705

4 Al+1,0%MWCNT 38.4060 2264.46 2.34387

5 Al+1.125%MWCNT 38.3887 2552.47 2.34489

6 Al+1.25%MWCNT 38.4957 2509.22 2.33864




4.4. Scanning Electron Microscopy

Figure 22 SEM images of Pure Aluminium Figure 23 SEM image for Al6063-

0.25%MWCNT

Figure 24 SEM image for Al6063- Figure 25 SEM image for Al6063-

0.75%MWCNT 1%MWCNT

Figure 26 SEM image for Al6063- Figure 27 SEM image for Al6063-

1.125%MWCNT 1.25%MWCNT



Figure 22 shows the SEM image of Pure Aluminium, the microstructure shows the surface

structure of the same material. Fig.23 shows the SEM image of Al with 0.25% MWCNT

added. From the image small presence of MWCNT can be noticed when compare on the

previous image. Fig.24 shows the SEM image of Al with 0.75% MWCNT added. From the

image small presence of MWCNT can be noticed when compare on the previous image.

Fig.25 shows the SEM image of Al with 1% MWCNT added. From the image more presence

of MWCNT can be noticed when compare on the previous image. Fig.26 shows the SEM

image of Al with 1.125% MWCNT added. From the image more presence of MWCNT can be

noticed when compare on the previous image. Fig.27 shows the SEM image of Al with 1.25%

MWCNT added. From the image more presence of MWCNT can be noticed when compare

on the previous image.

4.5. Training and Validation of ANN

Figure 28 Comparison between target value and predicted value

To test the generalization performance of the trained network in training and validating

processes, the experimental values were compared to the predicted values resulted from ANN

as shown in Fig.28. The experimental versus predicted values of training dataset, as it can be

observed, the predictability of ANN fits very well. However, the main quality indicator of a

neural network is its generalization ability, its ability to predict accurately the output of

unseen data and this was achieved by validating dataset.

Table 12 Comparison between Measured Values and Predicted Values Using ANN

Composition Measured value Predicted value using ANN Model

Hardness(BHN) Tensile strength(Mpa)

Hardness(BHN) Tensile strength(Mpa)

0.25%MWCNT 60.41 107.45 60.4702 98.2500

1%MWCNT 62.118 34.19 62.0028 56.1088

1.125%MWCNT 60.47 98 60.4700 98.2418

1.25%MWCNT 62.07 56.10 62.0700 56.1000




The dataset was obtained from stir casting process and considered as cast samples without

any further post-treatment except cleaning and cutting of the obtained bars. To test the

generalization performance of the trained network in training and validating processes, the

experimental values were compared to the predicted values resulted from ANN. The

experimental versus predicted values of training dataset is shown in table 12. As it can be

observed, the predictability of ANN fits very well. However, the main quality indicator of a

neural network is its generalization ability, its ability to predict accurately the output of

unseen data and this was achieved by validating dataset.

5. CONCLUSION In this present work reinforcement of MWCNT with aluminium by stirs casting method. The

different composition of MWCNT (0.25%, 0.75%, 1.0%, 1.125% and 1.25%) reinforced with

Aluminium6063 separately to make aluminium matrix composites and the improvement of

mechanical properties has been compared with Pure Al6063 using hardness test, Tensile Test

and XRD test. The improved results for hardness have been obtained at Al-1% wt fraction

MWCNTs (62.118 BHN). When compared to the pure Al6063 i.e. (59.55BHN). The

improved results for tensile strength have been obtained at Al6063-0.75% wt fraction

MWCNTs (110.66 Mpa). When compared to the pure Al6063 i.e. (99.44 Mpa). The addition

of MWCNTs with Al6063, increase the impact resistance of the reinforced Al6063 by

reducing the cracks and voids in the crystal lattice which was observed in the XRD analysis.

From the SEM images the presence of MWCNT could be clearly seen on each images, it was

observed that presence of MWCNT into Al6063. The use of ANN model prediction of

hardness and tensile strength for Al6063-MWCNT reinforced composite materials. The ANN

gives satisfactory results when compared to the experimental values.

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Force Microscopy and EDAX Analysis, International Journal of ChemTech Research,

Volume.10 No.3, pp 385-394, 2017.

[7] Qianqian Li , Christian A. Rottmair, Robert Fand Singer., „CNT reinforced light metal

Composites produced by melt stirring and by high pressure die casting’, Journal of

Composites Science and Technology, 2010.

[8] K.Logesh, V.K.Bupesh Raja, B.Dinesh, M.Rajesh Kumar, S.Bharath, Experimental

Investigation and Finite Element simulation of Tensile Behaviour of AA5052/GF/AA5052



Fibre Metal Laminate (FML), International Journal of Mechanical Engineering and

Technology 8(8), 2017, pp. 324-333.

[9] Shin Suzuki, Constructive function-approximation by three-layer artificial, Journal of

Neural Network, Volume. 11, pp. 1049-105, 2008.

[10] K.Logesh, V. K. Bupesh Raja. R.Velu, Experimental Investigation for Characterization of

Formability of Epoxy based Fiber Metal Laminates using Erichsen Cupping Test Method,

Indian Journal of Science and Technology, Volume 8(33), DOI:

10.17485/ijst/2015/v8i33/72244, December 2015.

[11] Adel Mahamood Hassan, Abdalla Alrashdan, Mohammed T. Hayajneh, Ahmad Turki

Mayyas, Prediction of density, porosity and hardness in aluminum–copper-based

composite materials using artificial neural network’, Journal of Materials Processing

Technology, Volume. 209, pp. 894-899, 2009.

[12] K.Logesh, D.Surryaprakash, N.Dilip Raja, M.Rajesh Kumar, Inflation of Environmental –

Friendly Machining Parameters on Aluminium 6063 In Its Annealed and Unannealed

form, International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS

Volume:15 No:05.

[13] Carreno-Morelli E, Yank J, Couteau E, Hernadi K and Schaller R, Carbon nanotube/

magnesium Composite’ Journal of Phys. Stat. sol. Volume. 201. No 8 pp.53-55.

[14] K.Logesh, V.K.Bupesh Raja, P.Sasidhar, An experiment about Morphological Structure

of Mg-Al Layered Double Hydroxide Using Field Emission Scanning Electron

Microscopy with EDAX Analysis, International Journal of ChemTech Research,

Volume.8, No.3, pp 1104-1108, 2015.

[15] Hashim J,Looney L,Hashmi M.S.J., Metal matrix Composites: production by the stir

casting method’ ‟Journal of Metal Processing Technology, Vol.92-93, pp. 1-7, 1999.

[16] Sajjadi S.A, Ezatpour H,R and Torabi Parizi M., Comparison of microstructure and

mechanical properties of A356 aluminum alloy/Al2O3 composites fabricated by stir and

compo-casting process, Journal of Material and Desing, Volume. 34, pp. 106-111, 2011.

[17] P.Sathyaseelan, K.Logesh, M.Venkatasudhahar, N.Dilip Raja, Experimental and Finite

Element Analysis of Fibre Metal Laminates (FML’S) Subjected to Tensile, Flexural and

Impact Loadings with Different Stacking Sequence, International Journal of Mechanical

& Mechatronics Engineering IJMME-IJENS Volume:15 No:03.

[18] Abbasipour B, Niroumand B, and Monir vaghef S.M., Compocasting of A356-CNT

Composite, Journal of Transaction of Nonferrous Metals of China, Volume.20, pp. 1561-

1566, 2010.

[19] K.Logesh, P.Muralinath, N.Poyyamozhi,N.Dilip Raja, A.Yassar Dawood, Optimization of

Cutting Factors Which influence Temperature on Tip of Tool in response to Surface

Finish for an Aluminium Alloy AL6063 during Turning Process on CNC Lathe,

International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS

Volume:14 No:06.

[20] K. Logesh, V.K.Bupesh Raja, Investigation of Mechanical Properties of

AA8011/PP/AA1100 Sandwich Materials, International Journal of ChemTech Research,

Volume.6, No.3, pp 1749-1752, May-June 2014.

[21] M.Venkatasudhahar, N.Dilipraja, P.Mathiyalagan, S.Venkata Subba Reddy,

P.Sathyaseelan, K. Logesh, Finite Element Analysis of Fatigue Life of Spot Welded Joint

and the Influence of Sheet Thickness and Spot Diameter, International Journal of

Mechanical & Mechatronics Engineering IJMME-IJENS Volume:14 No:06.

[22] K.Logesh, V.K.Bupesh Raja, R.Arun Raj, P.B.Senthilkumar, A Review of Recent Trends

on Reinforcement of Fibre Metal Laminates with Nanoclay and Multi Walled Carbon

Nanotubes, International Journal ChemTech Research, Volume.10 No.3, pp 395-399,

2017.




[23] Mathew Alphonse, V.K.Bupesh Raja, K.Logesh, N.Murugunachippan, Evolution and

Recent Trends in Friction Drilling Technique and the Application of Thermography,

Frontiers in Automobile and Mechanical Engineering, IOP Publishing, IOP Conf. Series:

Materials Science and Engineering 197 (2017) 012058 doi:10.1088/1757-

899X/197/1/012058.

[24] K. Logesh, V. K. Bupesh Raja, Formability analysis for enhancing forming parameters in

AA8011/PP/AA1100 sandwich materials, International Journal of Advanced

Manufacturing Technology, DOI 10.1007/s00170-015-7832-5, 2015.

[25] F.Rikhtegar. S.G.Shabestari, H.Saghafian, Microstructural evaluation and mechanical

properties of Al-CNT nanocomposites produced by different processing methods, Journal

of Alloys and Compounds, Volume 723, 5 November 2017, Pages 633-641.

[26] A.A.Najimi, H.R.Shahverdi, Effect of milling methods on microstructures and mechanical

properties of Al6061-CNT composite fabricated by spark plasma sintering, Materials

Science and Engineering: A, Volume 702, 15 August 2017, Pages 87-95.

[27] Chandra Shekar, N B D Pattar and Y Vijaya Kumar, Optimization of Machining

Parameters in Turning of AL6063T6 Through Design of Experiments. International

Journal of Mechanical Engineering and Technology, 7(6), 2016, pp. 96–104

[28] S.Dhivakaran, M.Sudhahar and P.Vijayakumar, Effect of Die Design on Mechanical

Properties of Hot Pressed 6063 Alloy, International Journal of Mechanical Engineering

and Technology (IJMET) Volume 8, Issue 3, March 2017, pp 426-432

experimental investigation and mechanical …€¦ · p.b. senthil kumar assistant professor,...

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