Ijsrtm vol 2 (4) june july 2014

Vol 2 (4) June 2014

International Journal of Students’

Research in Technology & Management

(IJSRTM)

Content List

1.Exergy Analysis of Vapor Compression Refrigeration System Using R12 and R134a as Refrigerants

Mohan Chandrasekharan

2. Investigation of Mechanical Properties of Aluminium 6061 Alloy Friction Stir Welding

J. Stephen Leon and Dr. V. Jayakumar

3. Microwave Assisted Trans-esterification of Waste Cooking Oil in Presence of Alkali Catalyst

Hasna Khalfan AlSuleimani, Priy Brat Dwivedi

4. Prediction of Excess Air Requirement Using ANN for the Improvement of Boiler Efficiency

Arun. S. Gopinath and N. Sreenivasa Babu

5. Study of Microwave Radiation on Transesterification of Jatropha Oil in Presence of Alkali Catalyst

Nadira Hassan Mohammed Al Balushi, Priy Brat Dwivedi

International Journal of Students’ Research in Technology & Management

Vol 2 (04), June-July 2014, ISSN 2321-2543, pg 134-139

http://www.giapjournals.org/ijsrtm.html 134

Exergy Analysis of Vapor Compression

Refrigeration System Using R12 and R134a as

Refrigerants Mohan Chandrasekharan

#1

# Department of Engineering, Mechanical Engineering Section, Al Musanna College of Technology,

Muladdah, Post Box 191, Postal Code 314, Sultanate of Oman. 1 [email protected]

Abstract— This paper deals with a comparative analysis of the

influence of refrigerant on the performance of a simple vapor

compression refrigeration system. The study is based on the

refrigerants R12 and R134a. A computational model based on

energy and exergy analysis is presented for investigation of the

effects of evaporating temperature and degree of sub-cooling on

the coefficient of performance and exergitic efficiency of the

refrigerator.

A considerable part of the energy produced worldwide is

consumed by refrigerators. So it is crucial to minimize the energy

utilization of these devices. The exergy analysis has been widely

used in the analysis of all engineering systems including

refrigerators. It is a powerful tool for the design, optimization

and performance evaluation of energy systems.

It is well known fact that the CFC and HCFC refrigerants have

been forbidden due to chlorine content and there high ozone

depleting potential (ODP) and global warming potential (GWP).

Hence HFC refrigerants are used now-a-days. Many research

papers have been published on the subject of replacing CFC and

HCFC refrigerants with other types of refrigerants.

This paper presents a comparative analysis of two refrigerants

working in a one stage vapor compression refrigeration system

with sub-cooling and superheating. These refrigerants are:

Dichlorodifluoromethane (R-12) and Tetrafluoroethane (R-134a).

Keywords —Vapor compression refrigeration system, Exergy,

COP, Exergetic efficiency, Degree of sub-cooling.

I. INTRODUCTION

Chlorofluorocarbons (CFCs) have been used widely over

the last eight decades in refrigeration and air-conditioning due

to their favorable characteristics such as low freezing point,

non-flammability, non-toxicity and chemically stable behavior

with other materials. Unfortunately, in recent years it has been

recognized that the chlorine released from CFCs migrate to the

stratosphere and destroys the earth’s ozone layer, causing

serious health problems [1, 2].

The Montreal Protocol signed by the international

community in 1987 regulates the production and marketing of

ozone depleting substances. The CFCs were prohibited

completely in 2010. Hydro-fluorocarbons (HFCs) are

presently replacing CFCs as they do not contain any chlorine

atoms and their ozone depletion potential (ODP) is zero.

Refrigerator pumps heat from a closed space to the

atmosphere. Heat transfer between the system and the

surroundings takes place at a finite temperature difference,

which is a major source of irreversibility for the cycle.

Irreversibility causes the system performance to degrade. The

losses in the cycle need to be evaluated considering individual

thermodynamic processes that make up the cycle. Energy

analysis is still the most commonly used method in the

analysis of thermal systems. The first law is concerned only

with the conservation of energy, and it gives no information

on how, where, and how much the system performance is

degraded. Exergy analysis is a powerful tool in the design,

optimization, and performance evaluation of energy systems

[9].

The principles and methodologies of exergy analysis are

well established [6-8]. An exergy analysis is usually aimed to

determine the maximum performance of the system and

identify the sites of exergy destruction. Analyzing the

components of the system separately can perform exergy

analysis of a complex system. Identifying the main sites of

exergy destruction shows the direction for potential

improvements.

There have been several studies on the performance of

alternative environment-friendly refrigerants on the basis of

energy and exergy analysis of refrigeration systems. Said and

Ismail [8] assessed the theoretical performances of R123,

R134a, R11 and R12 as coolants. It was established that for a

specific amount of desired exergy, more compression work is

required for R123 and R134a than R11 and R12. The

mailto:[email protected]




differences are not very significant at high

evaporation temperatures and hence R123 and R134a should

not be excluded as alternative coolants. Also, in their study

they obtained an optimum evaporation temperature for each

condensation temperature, which yields the highest exergetic

efficiency.

Aprea and Greco [9] compared the performance between

R22 and R407C (a zeotropic blend) and suggested that R407C

is a promising drop-in substitute for R22. Experimental tests

were performed in a vapour compression plant with a

reciprocating compressor to evaluate the compressor

performance using R407C in comparison to R22. The plant

overall exergetic performance was also evaluated and revealed

that R22 performance is consistently better than that of its

candidate substitute (R407C).

Aprea and Renno [9] studied experimentally, the

performance of a commercial vapour compression

refrigeration plant, generally adopted for preservation of

foodstuff, using R22 and its candidate substitute (R417A) as

working fluids. The working of the plant was regulated by

on/off cycles of the compressor, operating at the nominal

frequency of 50 Hz, imposed by the classical thermostatic

control. The reported result indicated that the substitute

refrigerant (R417A), which is a non-azeotropic mixture and

non-ozone depleting, can serve as a long term replacement for

R22; it can be used in new and existing direct expansion R22

systems using traditional R22 lubricants. Also in their

analysis, the best exergetic performances of R22 in

comparison with those of R417A were determined in terms of

the coefficient of performance, exergetic efficiency and

exergy destroyed in the plant components.

Khalid [10] studied the performance analysis of R22 and

its substitute refrigerant mixtures R407C, R410A and R417A

on the basis of first law. It was found that the COP of R417A

is 12% higher than R22, but for R407C and R410A, COP is

5% lowered as compared to R22, and R417A can be used in

existing system without any modification.

Various studies reviewed above focused mostly on the

exergetic analysis of R22 and its alternative refrigerants. R12

is used solely in the majority of conventional household

refrigerators, and there is currently little information on the

exergetic performance of R12 alternatives.

Therefore, in this paper, exergetic performances of a

domestic refrigeration system using R12 and its environment-

friendly alternative refrigerant R134a are theoretically studied

and compared.

II. SYSTEM DESCRIPTION

A one stage vapor compression refrigeration system is

considered as numerical exemplification of the proposed

study. The system is composed by a mechanical piston

compressor, a condenser, a throttling valve and an evaporator,

as shown in Figure 1. The refrigerant enters the compressor at

state 1, with a superheating degree ΔTSH with respect to the

evaporation temperature TV. It follows the irreversible

compression process 1-2, characterized by an increase in

entropy from state 2s (adiabatic reversible compression) to

state 2. The refrigerant leaves the compressor as superheated

vapor at pressure PC and enters the condenser and sub-cooler,

arriving in state 3 as sub-cooled liquid that is further throttled

during the process 3-4. Its pressure is the vaporization

pressure PV and the cycle is closed by a vaporization process

4-1 in the evaporator and super-heater.

Fig. 1: Single stage Vapor Compression Refrigeration System

III. MATHEMATICAL MODEL

The system is analyzed both from energetic and exergetic

points of view.

A. Energetic Approach

This analysis is applied either to each device (seen as a

control volume) or to the entire system (a control mass).

It is based on the First Law of Thermodynamics, whose

mathematical expression for a control volume is:

∑ (

) ∑ (

)

where E represents system energy (J), t stands for time (s),

h is the specific enthalpy of refrigerant (J/kg), v2/2 is the

specific kinetic energy (J/kg), gz is the specific potential

energy (J/kg), is the mass flow rate of refrigerant (kg/s),

and are the energetic exchanges of the control

volume with its surroundings in form of heat flux and work

rate (power).

(1)




The subscripts i and o stands for inlet and outlet

states, respectively.

For steady state operation, equation (1) becomes:

∑ (

)

∑ (

)

(2)

In vapor compression refrigeration system, changes in

kinetic and potential energies are negligible. So equation 2

becomes:

∑

∑

(3)

which is applied to each device of the system:

(a) for the evaporator:

(4)

where represents the refrigeration load.

(b) for the condenser:

(5)

where is the rate of heat rejected at the condenser

(c) for the compressor:

(6)

where is the rate of work input to the compressor.

(d) for the throttling valve:

(7)

The energetic efficiency of the system is measured by the

coefficient of performance:

(8)

B. Exergetic Approach

A reversible thermodynamic process can be reversed

without leaving any trace on the surroundings. This is possible

only if the net heat and net work exchange between the system

and the surrounding is zero [9]. All real processes are

irreversible. Some factors causing irreversibility in a

refrigeration cycle include friction and heat transfer across a

finite temperature difference in the evaporator, compressor,

condenser, and refrigerant lines, sub-cooling to ensure pure

liquid at capillary tube inlet, super heating to ensure pure

vapour at compressor inlet, pressure drops, and heat gains in

refrigerant lines [11]. Accurate analysis of the system is

obtained by evaluating the exergy used in the system

components. The p-h diagram of the vapor compression

refrigeration cycle is presented in Figure 2. Exergy flow

destroyed in each of the components is evaluated as follows

[3, 9]:

The exergetic balance equation for a control volume is:

∑(

) (

) ∑

∑

(9)

Fig. 2: Vapor compression refrigeration system on p-h diagram.

For steady state operation, equation 9 becomes:




∑(

) ∑

∑

(10)

Applying the exergetic balance equation to each

component of the vapor compression refrigeration system,

(a) for the evaporator:

(

)

(11)

(b) for the compressor:

(12)

(c) for the condenser:

(13)

(d) for the throttling valve:

(14)

The throttling process is isenthalpic process. h3 = h4.

Therefore, equation 14 can be expressed as:

(15)

The total exergy destruction rate,

The overall system exergetic efficiency ( ) is the ratio of

the exergy output ( ) to exergy input ( ) [3].

(

)

(17)

(18)

The only source of exergy input to the system is through

the electrical power supplied to the compressor ( ), that is,

= and Eq. (17) can be expressed as:

(

)

or

(

)

(19)

IV. RESULTS AND DISCUSSION

Figure 3 shows the variation of COP with varying

evaporator temperature for R134a and R12. The graph shows

that the COP increases with increase in evaporator

temperature for both the refrigerants. At lower temperatures

COP is slightly higher for R134a than R12. However, at

higher evaporator temperatures, COP of R12 is higher than

that of R134a.

Fig. 3: Variation of COP with evaporator temperature

Variation of exergetic efficiency with evaporator

temperature is given in figure 4. Exergetic efficiencies of both

the refrigerants decrease with increase in evaporator

temperature. At lower evaporator temperatures, the exergetic

efficiency of VCRS operating on R134a is higher than those

operating on R12. But at higher evaporator temperatures R12

system has higher exergetic efficiency than R134a system.




Fig. 4: Variation of exergetic efficiency with evaporator temperature

The figure 5 shows the variation of COP with degree of sub-

cooling. COP increases with increase in degree of sub-cooling

for both the refrigerants. R134a is more sensitive to variation

in degree of sub-cooling

Fig. 5: Variation of COP with degree of sub-cooling

The variation of exergetic efficiency with degree of sub-

cooling is shown in the figure 6 below. Exergetic efficiency

increases with degree of sub-cooling for both the refrigerants.

The variation is steeper for R134a than R12.

Fig. 6: Variation of exergetic efficiency with degree of sub-cooling

V. CONCLUSION

A comparative analysis of the refrigerant impact on the

operation and performances of a one stage vapor compression

refrigeration system was presented. The effects of evaporator

temperature and sub-cooling were studied on the system

operation and performances. Based on the exergy analysis,

exergy destruction rates were estimated for each component of

the system in a comparative manner for two refrigerants (R12,

R134a).




REFERENCES

[1] Akash, B.A.; and Said, S.A. (2003). Assessment of LPG as a possible

alternative to R12 in domestic refrigerators. Energy Conversion and

Management, 44(3), 381-388. [2] Sattar, M.A.; Saidur, R.; and Masjuki, H.H. (2007). Performance

investigation of domestic refrigerator using pure hydrocarbons and

blends of hydrocarbons as refrigerants. Proceedings of World Academy of Science, Engineering and Technology, ISSN 1307-6884,

23, 223-228.

[3] Bolaji, B.O. (2005). CFC refrigerants and stratospheric ozone: past, present and future. In: Environmental sustainability and conservation

in Nigeria, Okoko, E. and Adekunle, V.A.J. (Eds.); Book of Readings

of Environment Conservation and Research Team, 37, 231-239. [4] Moran, M.J. (1992). Availability analysis: a guide to efficient energy

use. New Jersey: Prentice-Hall, Englewood Cliffs.

[5] Aprhornratana, S.; and Eames, I.W. (1995). Thermodynamic analysis of absorption refrigeration cycles using the second law of

thermodynamics. International Journal of Refrigeration, 18(4), 244-

252.

[6] Bejan, A. (1998). Advanced engineering thermodynamics. New

York: John Wiley and Sons Inc.

[7] Dincer, I.; and Cengel, Y.A. (2001). Energy, entropy and exergy

concepts and their roles in thermal engineering. Entropy, 3, 116-149.

[8] Said, S.A.M.; and Ismail, B. (1994). Exergetic assessment of the

coolants HCFC123, HFC134a, CFC11, and CFC12. Energy, 19(11), 1181-1186.

[9] Aprea, C.; and Greco, A. (2002). An exergetic analysis of R22

substitution. Applied Thermal Engineering, 22(13), 1455-1469. [10] Khalid, M.A. (2006). Comparison of performance analysis of R22

and its alternate. 11th HVACR Conference, Krachi, 56-67.

[11] Kilicaslan, C.; Songnetichaovalit, T.; and Lokathada, N. (2004). Experimental comparison of R22 with R417A performance in a

vapour compression refrigeration system. Energy Conversion

Management, 45, 1835-1847.




Investigation of Mechanical Properties of

Aluminium 6061 Alloy Friction Stir Welding J. Stephen Leon

1 and Dr. V. Jayakumar

2

Faculty of Mechanical and Engineering, Department of Engineering

Ibri College of Technology, Ibri, Sultanate of Oman

[email protected]

Abstract– Aluminium 6061 alloy is commonly used for construction

of aircraft structures, such as wings and fuselages, more commonly

in homebuilt aircraft than commercial or military aircraft.

Aluminium 6061 alloy generally present low weldability by

traditional fusion welding process. The development of Friction

Stir Welding (FSW) has provided an alternative improved way of

satisfactorily producing weld joint in aluminium 6061 alloy. In

FSW, the welding tool motion induces frictional heating and severe

plastic deformation and metal joining process is done in solid state

results, which results in defect free welds with good mechanical

properties in aluminium alloy 6061. Unlike in traditional fusion

welding, friction stir welds will not encounter problems like

porosity alloy segregation and hot cracking, and welds are

produced with good surface finish. In this paper, an attempt was

made to investigate the impact of process parameters of FSW in the

mechanical properties of the joint. The tensile properties,

microstructure, hardness of the FSW joints were investigated in the

weldment and heat affected zone. The changes of mechanical

properties are compared with the parental metal. The welding

parameters such as tool rotational speed and welding speed plays a

major role in deciding the joint characteristics. This paper focusses

on optimization of all these parameters. From this investigation it

was found that the joint made from the FSW yielded superior

tensile properties and impact strength due to the higher hardness

and fine microstructure.

Key Words– FSW, welding speed, axial force, mechanical

properties, microstructure.

I. INTRODUCTION

In recent years, demands for aluminium alloy 6061 have

steadily increased in aerospace, aircraft and automobile

applications because of their excellent strength to weight ratio,

good ductility, corrosion resistance and cracking resistance in

adverse environment. Welding of these alloys, however, still

remains a challenge. Apart from softening in the weld fusion

zone and heat affected zone, hot cracking in the weld can be a

serious problem [1]. Thus, the solid state bonding process is

highly recommended to solve these problems. FSW is an

innovative solid state welding process in which the metal to be

welded is not melted rather the two parts of weld joints are

brought into contact and the interface is strongly forged together

under the effect of heavy plastic deformation caused by the

inserted rotating stir probe pin [2].

In FSW a rotating cylindrical, shouldered tool with a

profiled probe penetrates into the material until the tool shoulder

contacts with the upper surface of the plates, which are butted

together as shown in figure 1.

Fig 1 Principle of FSW

The parts have to be clamped on to a backing bar in a

manner that prevents the abutting joint faces from being forced

apart. Frictional heat is generated between the wear resistant

welding tool and the material of the work pieces. This heat

causes the later to soften without reaching the melting point and

allows traversing of the tool along the weld line. In FSW,

tool rotation rate (rpm) in clockwise or counter clockwise

direction and tool traverse speed (mm/min) along the joint are

the most important parameters [3].

II. LITRATURE REVIEW

The effect of FSW parameters on temperature was examined

by Muhsin et al .[4]. They concluded that the maximum


http://en.wikipedia.org/wiki/Aircraft

http://en.wikipedia.org/wiki/Wing

http://en.wikipedia.org/wiki/Fuselage

http://en.wikipedia.org/wiki/Homebuilt_aircraft




temperature is a function of tool rotation rate while the

rate of heating was a function of traverse speed.

Munoz et al. [5] investigated the microstructure and

mechanical properties of friction stir welded and TIG welded

Al-Mg-Sc alloy and reported that the yield strength FSW

welded joint is decreased 20 % compared to base metal.

Apart from this, there have been lot of efforts to understand

the effect of process parameters on material flow behaviour,

microstructure formation and mechanical properties of friction

stir welded joints. Finding the most effective parameters on

properties of friction stir welds as well as realizing their

influence on the weld properties has been major topics for

researchers [6–8].

Extensive literature of friction stir welding of Al alloys does

indicate that there are few areas particularly on the relationship

between welding parameters and change in the mechanical

properties of weldment. This paper focuses on finding the

optimal speed (rpm) and feed rate (mm/s) with respect to

mechanical properties such as hardness number and tensile

strength.

III. EXPERIMENTAL PROCEDURE

AA 6061 aluminum alloy chemical composition and

mechanical properties are given in table 1 and 2 respectively.

TABLE 1

CHEMICAL COMPOSITION IN %WT

Name of

the Al

alloy

Mg Si Fe Cu Cr Mn Zn Ti Al

AA 6061 0.9 0.62 0.33 0.28 0.17 0.06 0.02 0.02 Balance

TABLE 2 MECHANICAL PROPERTIES

Name of

the

Aluminum

alloy

Yield

strength

in MPa

Ultimate

strength

in MPa

Elangation % Hardness

in HV

AA 6061 110 207 16 75

All dimensions are in mm

Fig 2 Square Butt joint

The rolled plates of AA6061 aluminium alloy were

machined to the required dimensions (300 mm X 150 mm).

Square butt joint configuration as shown in fig 2 was prepared

to fabricate FSW joints. A non-consumable, rotating tool made

up of high carbon steel was used. Probe diameter is 6 mm,

shoulder diameter is 18 mm and pin length is 5.5 mm. FSW was

carried out on a FSW machine manufactured by RV machine

tools, India. Machine specifications are given in table 3.

TABLE 3.

MACHINE SPECIFICATIONS

Spindle ISO 40

Spindle speed 1000 to 3000 rpm (infinitely variable)

Z axis thrust 3000 to 10000 kgf

X axis thrust 1000 to 5000 kgf

Spindle motor 11 kW/440 v, AC spindle servo motor

Version CNC

The Aluminium plates are positioned in the fixtures, which

is prepared for fabricating FSW joints by using mechanical

clamps so that the plates will not separate during welding.

In present work, different FSW butt welds were obtained by

varying tool rotation speed and welding speed with in the range

obtained by the previous works [9, 10] by keeping the axial

force constant.

In this work FSW process was conducted with two variables:

rotational speed (rpm) of the tool pin and traverse speed

(mm/min) of the machine table. The rotational speed was chosen

as: 720, 910, 1120 and 1400 rpm while the traverse speeds were

16, 20, and 31.5 mm/min.

IV. RESULT AND DISCUSSION

A. Macro and Microscopic Visual Examination

The optical microstructures of the base metal and weld

centre are shown in fig 3

Macroscopic visual examination of all welded

specimens in transverse and longitudinal cross section showed

defect-free sound weldments, produced under all applied

experimental conditions. Uniform semicircular surface ripples in

weld track were observed. These surface ripples, which have

onion rings configuration, were caused by the final sweep of the




trailing edge of the continuously rotating tool shoulder.

A similar observation was made by many researchers [11-14].

Base metal FSW

Fig 3. Optical Micrographs of base metal and weldment

Combined influence of temperature and plastic deformation

induced by the stirring action causes the recrystallized structure.

In many FSW references on aluminum alloys, the initial

elongated grains of the base materials are converted to a new

equiaxed fine grain structure. This experiment confirms that

behavior. The grain structure within the nugget is fine and

equiaxed and the grain size is significantly smaller than that in

the base materials due to the higher temperature and extensive

plastic deformation by the stirring action of the tool pin. During

FSW, the tool acts as a stirrer extruding the material along the

welding direction. The varying rate of the dynamic recovery or

recrystallization is strongly dependent on the temperature and

the strain rate reached during deformation.

B. Hardness

Using Vicker’s hardness testing machine hardness across the

welds cross-section was measured. Hardness values are taken

from weld face, midway through the weld nugget and near to the

root of the FSW joint. The average values were plotted against

the distance from the welding centre (fig 4).

Fig 4. Hardness Vs distance from weldment at 1400 rpm

Comparing with base metal hardness decreases towards the

weld centre. This is due to the shear stress induced by the tool

motion which lead to the generation of very fine grain structure

as shown in fig 3. Dynamic recovery and recrystallization are

the main softening mechanisms during FSW. When the average

values of hardness in the welding centre were plotted against

different tool rotation speed in fig 5, it was observed that when

rotation speed increases more than 1200 rpm hardness in the

weldment increases. This is because of the relatively high

stacking fault energy which causes cross slip. This explanation

was reached also by many researchers [15-19]. The result also

reveals that 80-90% reduction in hardness comparing with base

metal when traverse speed increases from 16 to 31.5 mm/min.

Fig 5. Hardness vs speed

0

20

40

60

80

-40

-30

-20

-10 0

10

20

30

40

Har

dn

ess

in H

V

Distance from Weldment in mm

WeldingSpeed 16mm/min

WeldingSpeed 31.5mm/min

0

20

40

60

80

720 910 1120 1400H

ard

ne

ss in

HV

Speed in rpm






C. Tensile Properties

Fig 6.Ultimate strength vs Rotational speed

Fig 7.Yeild strength vs Rotational speed

Fig 8.Percentage Elongation vs Rotational speed

The transverse tensile properties such as yield stress, tensile

strength and percentage of elongation of AA6061 aluminium

alloy joints were evaluated. The measurements of ultimate

tensile strength, yield stress and elongation for the welded

specimen are shown in fig 6-8 respectively. The lowest ultimate

tensile stress (UTS) found for welds in Al6061-T6 was 66% of

the base material strength, while the highest yield strength found

was over 90% of the base material strength. When the welding

speed reduces, the specimen elongation in the weldment is

nearly equal to the base metal.

V. CONCLUSION

In this paper, an attempt was made to investigate the impact

of process parameters of FSW in the mechanical properties of

the joint. From this investigation, the following conclusions

have been derived: (i) The weld root surface of all the

weldments showed visually a well joined defect free sound flat

surface. (ii) The increase in stir–probe rotation speed more than

1200 rpm enhanced the weld soundness which may be a result

of softening process associated with dynamic recovery and

recrystallization process at the weld. (iii) The formation of fine

equiaxed grains and uniformly distributed, very fine

strengthening precipitates in the weld region are the reasons for

the superior tensile properties of FSW joints. (iv) The width of

the stir zone may depend on the balance between the total heat

input and the cooling in the plasticized material. The area of the

weld nugget zone size slightly decreased as the welding speed

increased. Comparing with other welding speeds, the lowest

speed 16mm/min results better mechanical properties and

increase in the area of the weld nugget.

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frequency of pulsing in gas tungsten arc welding on the

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Effect of Friction Stir Welding parameters (Rotation and

Transverse) speed on the transient temperature distribution

in FSW of AA 7020-T53. ARPN Journal of Engineering

and Applied science Vol7, 2012.

[5] Munoz C, Ruckert G (2004) comparision of TIG welded

and Friction stir welded Al-4.5 Mg-0.26 Sc alloy. J.Matar

process Technol 152:97-105.

[6] Peel M, Steuwer A, Preuss M, Withers PJ. Microstructure,

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2003;51:4791–801.

[7] Chen CM, Kovacevic R. Finite element modeling of

friction stir welding– thermal and thermomechanical

analysis. J Mach Tools Manuf 2003;43:1319–26.

0

50

100

150

720 910 1120 1400

Ult

imat

e S

tre

ngt

h in

M

Pa

Rotational Speed in rpm



0

50

100

150

720 910 1120 1400

Yie

ld S

tre

ss in

MP

a




13

14

15

16

17

720 910 1120 1400Pe

rce

nt

Elan

gati

on







[8] Schmidt H, Hattel J, Wert J. An analytical

model for the heat generation in friction stir welding. Mater

Sci Eng 2004;12:143–57.

[9] Elangovan K, Balasubramanian V (2008) influences of tool

pin profile and tool shoulder diameter on the formation of

friction stir processing zone in AA6061 aluminum alloy.

Mater Des 29(2) :362- 373

[10] Elangovan K, Balasubramanian V, Valliappan M (2007)

Influence of tool pin profile and axial force on the

formation of friction stir processing zone in AA6061

aluminium alloy. Int J Adv Manuf Technol . DOI

10.1007/s00170-007-1100-2.

[11] Threadgill,P.L. Friction-Stir Welding-State of the Art, TWI,

Report 678, England, 1999

[12] Lee, J.A. Carter, R.W., andDing, J.D.,”Friction Stir

Welding for Aluminum Metal MatrixComposites,

NASA/TM-1999 Project No.98-09.

[13] Colligan, K. 1999. Material flow behavior during friction

stir welding of aluminum. Welding Journal 78(7): 229-s to

237-s.

[14] G.Elatharasan, V.S.Senthil kumar, An Experimental

Analysis and optimization of process parameters of Friction

Stir Welding of AA 6061 – T6 Aluminium alloy using

RSM. ICONDM 2013, Vol 64, 2013.

[15] A study of process parameters of Friction Stir Welded

AA6061 Aluminium alloy. ARPN Journal of Engineering

and Applied science Vol6, 2011.

[16] Threadgill,P.L. Friction-Stir Welding-State of the Art, TWI,

Report 678, England, 1999.

[17] Liu, L.E. Murr, C.S Niou, J.C. McClure, and F.R. Vega,

Micro structural aspects of thefriction-stir welding of 6061-

T6 aluminum, Scripta Mat, 1997, vol 33-3, pp 355-36

[18] Rhodes, C. G., Mahoney, M. W., and Bingel, W. H. 1997.

Effects of friction stir welding on microstructure of 7075

aluminum. Scripta Materialia 36(1): 69–75.

[19] Qasim M Doos, Bashar, Abdul wahab Experimental study

of Friction Stir Welding of 6061-T6 Aluminium pipe.

International Journal of Mechanical Engineering and

Robatics. Vol 1. 2012.



145

Microwave Assisted Trans-esterification of Waste

Cooking Oil in Presence of Alkali Catalyst Hasna Khalfan AlSuleimani

#1, Priy Brat Dwivedi

#2

Student#1

, Project Guide#2

Mechanical & Industrial Department,

Caledonian College of Engineering, Oman

#1 [email protected]

#2 [email protected]

Abstract— Depletion of world petroleum resources and air

pollution has led to a search for alternative sources for fossil fuel,

including diesel. Because of the similarity with petro-diesel,

biodiesel fuel (fatty acid methyl ester) from vegetable oils, animal

fats and recycled cooking oil is considered as the best candidate for

diesel fuel substitute in diesel engines. Biodiesel helps in extending

engine life, improving fuel economy, decreasing air pollution and

reducing reliance on foreign and fossil fuel. In this paper the effect

of microwave radiation on trans-esterification of waste cooking oil

(from restaurants and from industrial food processors) in presence

of alkali catalyst in batch process was studied. For optimal yield

ratio of oil to methanol was 1:6, 0.4 w% KOH for 200 seconds in

domestic microwave oven. Later on results were compared with

conventional heating process of trans-esterification. From this work

it is concluded that biodiesel can be produced from waste cooking

oil using microwave radiation with significant reduction in

production time.

Keywords— WCO, Trans-esterification, microwave, biodiesel,

alkali catalyst

I. INTRODUCTION

Biodiesel (biological oil) is one of the alternative fuels that

are produced from renewable sources. It is also called as mono

alkyl ester of long chain fatty acid and it can be derived from

various biological sources such as vegetable oil and animal fats.

It can be made from a diverse mix of feed stocks including

Waste cooking oil. Hundred years ago, Rudolf Diesel tested

vegetable oil as fuel for his engine. In 1930s and 1940s

vegetable oils (VOs) were used as diesel fuels, but only in

emergency situations [1]. Alternative fuels for diesel engines

are becoming increasingly important due to diminishing

petroleum reserves and the environmental consequences of

exhaust gases from petroleum fuelled engines [2]. Although the

calorific value of VOs is as good as diesel fuel but the low

volatility and high viscosity of VOs prohibits its direct

application as fuel for diesel engines. However, this technical

problem of higher viscosity of VOs has been overcome by

trans-esterification [3]. Trans-esterification is the process of

reacting triglyceride (vegetable oils) with alcohol in presence of

catalyst. During the transesterification process, triglycerides are

first converted to diglycerides, which in turn are converted to

monoglycerides, and then to glycerol. Each step produces a

molecule of an ester of a fatty acid [4].

Waste cooking oil is taken as feed stock for production of

Biodiesel; it offers a triple fact solution: economic,

environmental and waste management. The term “waste

vegetable oil” (WVO) refers to vegetable oil which has been

used in food production and which is no longer viable for its

intended use. It is can be collect from variety of sources, e.g.,

food industry, restaurants or houses. Production of biodiesel

from Waste cooking oil to partially substitute petroleum diesel

is an alternative way for environment protection and energy

security.

Trans-esterification is a process in which the glycerin is

separated from WVO. It refers to catalyzed chemical reaction

involving vegetable oil and an alcohol to yield fatty acid alkyl

esters (i.e. Biodiesel) and glycerol.

Fig 1.1: A schematic representation of the Trans-

esterification of triglycerides (vegetable oil) with methanol

to produce fatty acid methyl esters (Biodiesel) (R=CH3).

This process can convert oil to biodiesel up to 80 to 94% in

30 min to 2 hr [5]. The yields were dictated by molar ratio of

the oil to alcohol, reaction time, temperature, catalyst type,





146

catalyst concentration, triglyceride properties, and

mixing intensity.

An alternative to conventional heating trans-esterification is

the microwave-assisted trans-esterification. This means that

microwave radiation for biodiesel synthesis is more efficient in

reducing the time required for the reaction and separation of the

products and offers a better way to synthesize biodiesel when

compared to conventional mode of heating as well as improve

product yields under atmospheric conditions [6] [7]. It is due to

the fact that microwave radiation activates the smallest degree

of variance of polar molecules and ions such as alcohol with the

continuously changing magnetic field.

The use of vegetable oils as alternative fuels has been

around for one hundred years when the inventor of the diesel

engine Rudolph Diesel first tested peanut oil, in his

compression-ignition engine. In 1970, scientists discovered that

the viscosity of vegetable oils could be reduced by a simple

chemical process and that it could perform as diesel fuel in

modern engine. Considerable efforts have been made to develop

vegetable oil derivatives that approximate the properties and

performance of the hydrocarbon-based diesel fuels. Bio-diesel

production is a very modern and technological area for

researchers due to the relevance that it is winning every day

because of the increase in the petroleum price and the

environmental advantages. Trans-esterification is the most

common method and leads to mono-alkyl esters of vegetable

oils and fats, now called bio-diesel when used for fuel purposes

[8].

The diesel fuel has a closer properties, biodiesel fuel (fatty

acid methyl ester) from vegetable oil is considered as the best

candidate for diesel fuel substitute in diesel engines. Biodiesel is

the fastest growing alternative fuel in the country. Biodiesel’s

has ability to extend engine life, improve fuel economy,

decrease air pollution and reduce reliance on foreign fuel. The

use of waste cooking oil to produce biodiesel reduced the raw

material cost [9].

II. MATERIALS

Waste Cooking Oil was collected from the local restaurant

in Muscat, Oman. This oil was filtered and used for the

production of biodiesel. In this work, Potassium hydroxide was

used as alkali catalyst. In comparison with other alcohols,

methanol is cheaper and has better physical and chemical

properties (polar and shortest chain alcohol), and it was used as

a reactant. Potassium hydroxide, methanol and sulphuric acid

were purchased from Schalau Chemie S.A, Spain. Other

required chemicals purchased from local market were of

analytical reagent great. In this study domestic oven was used of

LG company make. Total work was done at fixed power of 160

wt.

III. BIODIESEL PRODUCTION

Waste cooking oil was used in this study. Waste Cooking

Oil contains an initial acid value of 2.3 mg which is >1 mg

KOH per gram of oil. Therefore, biodiesel production was

performed in two-step reaction mechanisms:

Acid-Catalyzed Esterification.

Base-Catalyzed Trans-esterification.

A. Acid Catalyzed esterification

The Waste Cooking Oil used in this study had an initial acid

value of 2.3 mg KOH/g corresponding to a free fatty acid (FFA)

level of 3.1%, which is above the 1% limit for a satisfactory

trans-esterification reaction using an alkaline catalyst [10]. In

this pretreatment, methanol-to-oil ratio was taken as 4:1 w/w

and 0.4 w% of H2SO4 was used. This mixture was heated in LG

make domestic microwave oven with occasional shaking for 60

seconds. Power level was set at 160 W. This pretreatment was

done with every set before mixture was set for trans-

esterification.

B. Base-Catalyzed Trans-esterification

The method applied for the production of biodiesel from

WCO in this study is base-catalyzed trans-esterification in a

laboratory-scale setup. The reaction was performed using

methanol as alcohol and KOH as catalyst. The trans-

esterification process was studied at three KOH catalyst

loadings (0.01, 0.02 and 0.04 g), three oil to methanol w/w

ratios (1:6, 1:8, and 1:10) and three time variations. Results are

listed in table. After the reaction, the excess methanol was

removed by vacuum distillation and then the trans-esterification

products were poured into a separating funnel for phase

separation. After phase separation, the top layer (biodiesel), was

separated and washed with distilled water in order to remove the

impurities. Then the biodiesel was heated above 1000C, to

remove the moisture.

IV. RESULT AND DISCUSSION

Conventional heating set was also studied for methanol,

catalyst and time variation and results are given in table 1.

Maximum yield of biodiesel yield was 3.1g with 50g methanol

in 5 hrs refluxing set. In table 2, 3 and 4 results of methanol,

time and catalyst variation are summarized. It is clear that

microwave radiation is one of the best tools for trans-

esterification of waste cooking oil. Optimum yield was found

when methanol to oil ratio was 6:1. As clear from table 2,

biodiesel yield was decreasing with increasing the amount of

methanol. More study is required in this area to find the reasons

behind this observation.

In case of alkali catalyst variation biodiesel yield increased

with increase in alkali catalyst concentration. But due to soap

formation and difficulty in product separation, yield decreased

as catalyst amount increased to 0.4 w%. During this study,



147

effect of time was also studied. Yield of biodiesel was

found to be increasing with time. But to avoid bumping and

overheating, no study was done after 200 seconds.

Biodiesel production by microwave irradiation was due to

direct adsorption of the radiation by the polar group (OH group)

of methanol. It is speculated that the OH group is directly

excited by microwave radiation, and the local temperature

around the OH group would be very much higher than its

environment. Hence, microwave assisted trans-esterification is a

way of reducing the reaction time, the electrical energy and

labour costs as compared to the conventional method. And Gas

Chromatography analysis of biodiesel from waste cooking oil is

given in table 5.

TABLE 1

MEOH: OIL (CONVENTIONAL HEATING)

MeOH : Oil

(w/w)

Time (hr) Catalyst (g) BD Yield (g)

20:5 3 0.15 No Result

20:5 3 0.02 2.9

50:5 5 0.02 3.1

TABLE 2

MEOH: OIL VARIATION

MeOH : Oil

(w/w)

Time (s) Catalyst (g) BD Yield (g)

30:5 80 0.02g 4.7

40:5 80 0.02g 4.5

50:5 80 0.02g 4.2

TABLE 3

CATALYST VARIATION

Catalyst (g) Time (s) MeOH : Oil

(w/w)

BD Yield

(g)

0.01 140 40:5 4.2

0.02 140 40:5 4.5

0.04 140 40:5 4.1

TABLE 4

TIME VARIATION

Time (s) MeOH: Oil

(w/w)

Catalyst

(g)

BD Yield

80 50:5 0.02 4.2

140 50:5 0.02 4.3

200 50:5 0.02 4.4

TABLE 5

GC RESULT OF BIODIESEL FROM WCO

Component % Concentration

9-Octadecenoic acid 40.898 %

Pentadecanoic acid 40.779 %

8,11-octadecadienoic acid 10.052 %

Heptadecanoic acid 3.699 %

9-Octadecenoic acid 1.125 %

n-Hexadeecanoic acid 1.094 %

V. CONCLUSION

In this work, biodiesel was produced from Waste cooking

oil using microwave radiation and with the help of two-step

trans-esterification. It was observed that microwave radiation

helps the synthesis of fatty acid methyl esters (biodiesel) from

waste cooking oil, and higher biodiesel conversion can be

obtained within a few minutes, whereas the conventional

heating process takes more than 5 hrs.

In the current investigation, it has confirmed that Waste

cooking oil may be used as resource to obtain biodiesel. The

experimental result shows that alkali catalyzed trans-

esterification is a promising area of research for the production

of biodiesel in large scale. Effects of different parameters such

as time, reactant ratio and catalyst concentration on the

biodiesel yield were analyzed. The best combination of the

parameters was found as 6:1 w/w ratio of Methanol to oil, 0.4

w% (0.02g) of KOH as catalyst and 200 seconds of reaction

time. The viscosity of Waste cooking oil reduces substantially

after trans-esterification and is comparable to diesel. Biodiesel

characteristics like density, viscosity, flash point, and pour point

were studied and are found as comparable to diesel.

I take this opportunity to express my profound gratitude and

deep regards to my guide Dr. Priy Brat Dwivedi and Ms. Shah

Jahan for their exemplary guidance, monitoring and constant

encouragement throughout this work. I thank almighty, my

parents, sisters and friends for their constant encouragement

without which this assignment would not be possible. I am also

thankful to Caledonian College of Engineering, Muscat Oman

for providing me all facilities in lab.

REFERENCES

[1] Schumacher LG, Peterson CL, Grepen JV. 2001. Fuelling

direct diesel engines with 2 % biodiesel blend. Written for

presentation at the 2001 annual international meeting

sponsored by ASAE.

[2] Ghobadian B, Rahimi H. 2004. Biofuels-past, present and

future perspective. International Iran and Russian congress



148

of agricultural and natural science.Shahre cord

university. Shahrekord. Iran.

[3] Ma F, Hanna MA. 1999. Biodiesel production: a review.

Bioresource technology, 70: 1-15.

[4] Freedman B, Butterfield RO, Pryde

EH.1986.Transesterification kinetics of soybeen oil.

JAOCS 63, 1375–1380.

[5] Encinar J, Gonzalez J, Rodriguez J, Tejedor A. 2002.

Biodiesel Fuels from Vegetable Oils: Transesterification of

Cynara c ardunculus L.

[6] Dasgupta A, Banerjee P, Malik S. 1992. Use of microwave

irradiation for rapid transesterification of lipids and

accelerated synthesis of fatty acyl pyrrolidides for analysis

by gas chromatography-mass spectrometry: study of fatty

acid profiles of olive oil, evening primrose oil, fish oils and

phospholipids from mango pulp. Chemistry and physics of

lipids, 62: 281-291.

[7] Lertsathapornsuk V, Pairintra R, Krisnangkura K,

Chindaruksa S. (Eds.) 2003. Proceeding of the 1st

International Conference on Sustainable Energy and Green

Architecture, Bangkok, SE091.

[8] Balat, M. and Balat, H. 2008. A critical review of bio-diesel

as a vehicular fuel. Energy conversion and management, 49

(10), pp. 2727--2741.

[9] Mistry, M. and Khambete, A. Extraction of Biodiesel from

waste vegetable oil.

[10] Freedman B, Butterfield RO, Pryde EH. Transesterification

kinetics of soybean oil 1. J Am Oil Chem Soc (JAOCS)

1986;63(10):1375–80.




Prediction of Excess Air Requirement Using

ANN for the Improvement of Boiler Efficiency Arun. S. Gopinath

#1, N. Sreenivasa Babu

*2

Engineering Department, Shinas College of Technology

Sultanate of Oman

[email protected]

[email protected]

Abstract—An improvement in the efficiency on converting fuel

energy to useful thermal energy could result in significant fuel

saving for industrial Sector. In this paper artificial intelligence

concept using Artificial Neural Network (ANN) is used to predict

the optimized excess air requirement using real time and calculated

data. This work determines the excess air requirement for complete

combustion corresponding to theoretical CO2 in flue gases and real-

time values obtained from remote measurements of CO2 (actual) in

flue gases.

Keywords— ANN, Flue gas Analysis, Excess Air Control, Boiler

Efficiency, Losses

I. INTRODUCTION

The operating efficiency of industrial boilers is one of the

critical concerns in National Energy Consumption.The

improvement in boiler efficiency will increase the steam input to

the turbine and hence the alternator output power as well.

Improvement in boiler efficiency can be done by optimizing the

combustion with excess air control. Moreover Optimized

combustion directly minimizes the emission of hazardous

pollutants into the atmosphere like CO, Oxides of Sulphur and

Nitrogen etc. which will minimize air pollution.

II. FUELS, COMBUSTION & FORMULATION

Coal is one among the prominent fuel using in the power

generation industry. For the Complete combustion of Coal as

fuel, air is required. Normally Oxygen (O2) is required for the

combustion. It is obtained from the air which is supplied to the

furnace. The amount of air required to supply sufficient Oxygen

for the complete combustion of fuel is the Theoretical air.

Excess Air is the amount of air required in addition to the

stoichiometric air to make sureof complete oxidation during

burning of fuel.

Among the types of fuels ,Natural gas requires less and coal

requires the maximum amount of excess air for the complete

combustion[1].A typical 210 MW natural circulation , dry

Bottom , tangentially fired , balanced draft and radiant Reheat

type with direct fired pulverized coal system boiler is

considered for this analysis. Data from the Proximate and

Ultimate analysis of Coal used in the boiler is as shown in

Table1&2. In situ Measurements from 210MW Boiler is shown

in Table 3 & 4.

TABLE I

SAMPLE OF PROXIMITY ANALYSIS RESULT OF COAL

Content Percentage

1 Ash 38

2 Volatile Matter 20

3 Moisture 7.1

4 Fixed Carbon 34.6

GCV of Coal : 4210 K Cal/kg

TABLE-2 SAMPLE OF ULTIMATE ANALYSIS OF COAL FROM PROXIMITY ANALYSIS

Sl. No Content Percentage

1 Carbon 45.957

2 Hydrogen 2.835

3 Nitrogen 0.935

4 Sulphur 0.3

5 Oxygen 4.873

TABLE-3

PERFORMANCE DATA FROM 210MW BOILER

Sl.

No

Parameter Unit Test

value




1 Load MW 210

2 PA In Temp.to APH A 0 C 42

3 PA In Temp.to APH B 0 C 42

4 SEC. AIR TEMP.TO APH A 0 C 42

5 SEC. AIR TEMP.TO APH B 0 C 42

6 Flue Gas TEMP APH A INLET 0 C 147.7

7 Flue Gas TEMP APH B INLET 0 C 159.0

8 Flue Gas TEMP. APH A OUTLET 0 C 333

9 Flue Gas TEMP. APH B OUTLET 0 C 331

10 SEC.AIR TEMP. APH A OUTLET 0 C 262.5

11 SEC.AIR TEMP.APH B OUTLET 0 C 280

12 PA OUTLET TEMP.APH A 0 C 292

13 PA OUTLET TEMP.APH B 0 C 282

14 TOTAL SEC. AIR FLOW T/Hr. 405

15 TOTAL PA FLOW T/Hr. 340

16 TOTAL AIR FLOW T/Hr. 705

TABLE IV

IN SITE MEASUREMENTS

Sl. No Parameters Quantity in %

1 O2 INLET 3.585

2 O2 OUTLET 5.115

3 CO2 INLET 15.715

4 CO2 OUTLET 14.185

5 CO OUTLET 0.005

An Indirect Method is followed in this analysis for evaluating

boiler efficiency. In Indirect method the following losses are

considered [2];

Percentage heat loss due to dry flue gas, L1

Percentage heat loss due to evaporation of water

formed, L2

Percentage heat loss due to moisture present in fuel,L3

Percentage heat loss due to moisture present in air, L4

Percentage heat loss due to Partial Conversion of C to

CO , L5

Percentage heat loss due to Radiation & Convection,

L6

Percentage heat loss due to Un burnt carbon in Fly ash,

L7

Percentage heat loss due to Unburnt carbon in Bottom

Ash, L8

Boiler Efficiency =

[100 – (L1+ L2+ L3+ L4+ L5+ L6+ L7+ L8)]

III. ALGORITHM & RESULT ANALYSIS

The Excess air required for the complete combustion is

calculated by comparing the actual CO2measured from insitu

and the theoretical CO2 value derived from the theoretical air

required for complete combustion [6].

The steps followed for the calculation is as follows:

Step 1: Fuel Parameters after Proximity Analysis and Ultimate

Analysis should be given as input

Step 2: Boiler parameters & Ambient parameters from the In

site measurements to be given as input

Step 3: Calculate the Theoretical Air required for the

Combustion of Fuel

Step 4: Calculate the Theoretical CO2 Required for the complete

Combustion of fuel

Step 5: Actual CO2 from the Flue gas is taken from in site

measurements

Step 6: Excess Air required for the complete combustion was

calculated by comparing the theoretical CO2 and Actual CO2

Step 7: After calculating the Excess Air Required for different

combinations of theoretical CO2 and Actual CO2for different

grades of coal, a neural network was trained to predict the

values of excess air required.

A. ANN for Prediction of Excess Air Requirement

A feed forward neural network trained with back propagation

is used for this prediction.

The steps followed for creating the Artificial Neural Network

is as follows:

Step 1: Theoretical CO2 from different grades of coal and

their Measured Actual CO2 where given as Input vectors.

Step 2: Corresponding Excess air Requirement calculated

were assigned as the target values for their input vectors.

Step 3: The 2 layer feed forward Neural Network was created

with 3 neurons in each hidden layer.

Step 4: TheNetwork was trained and created with the Data

samples

Step 5: Weight values and the biasing is adjusted iteratively

to improve the network performance function.

Step 6: Mean square error between the network outputs and

the target outputs is the performance function

Step 7: Trained network can be applied to simulate output

corresponding to any new set of input data




Fig. 1 Excess Air Requirement for Different CO2 actual measurements of coal using indirect method

Neural Network Training data is shown in Table 5. The CO2

actual is taken from in site measurements for different grades of

pulverized coal with different compositions. The training

algorithm used in neural network is Levenberg -Marquardt

algorithm which works better on function fitting problems with

small networks [3]. CO2theoretical is derived from the details of

ultimate analysis of the coal [4-5]. The performance function for

the feed forward network is its mean square error between the

network output and targets.

The resulting graph with test data, validation data and training

is shown in Fig 2.

Fig 2 Training plot showing Mean Square Error (MSE) of

the network

TABLE V

RESULTS OF INDIRECT METHOD USED FOR TRAINING NETWORK IN ANN

CO2Theoretical

%

CO2 Actual % Excess air % by

Indirect method

22.32 15.6 43.81

21.5 15.83 36.04

20.67 14 47.44

18.25 15.76 15.27

15.5 10 51.42

TABLE VI

RESULTS OF SIMULATION FROM ANN

CO2Theore-

tical %

CO2

Actual

%

Excess Air

% from

ANN

Excess air %

by Indirect

method

Error

%

20.5 15.2 39.68 34.69 14.38

21 14.8 44.55 41.89 6.3

22 13.6 71.53 62.55 14.3

22.5 15.8 42.2 43.23 2.5

23 16 42.38 44.88 5.5

IV. CONCLUSIONS

The Excess air requirement predicted by the ANN is in good

understanding with the values using indirect method. As the

CO2 actual from the flue gas reduces, the excess air

Requirement is increasing. The Errors can be minimized in this

prediction if more training data’s are added for training. This

Prediction method can be incorporated with the control

mechanism of primary and secondary induced/Forced draft fans

to give excessair control in boilers which in turn will increase

the combustion efficiency as well as the boiler efficiency.

ACKNOWLEDGMENT

We acknowledge our friends and colleagues of Shinas

College of Technology who helped in collecting information to

finish this paper. We here by showing our gratitude towards our

college management for their constant support and

encouragement.

0

10

20

30

40

50

60

1 3 5 7 9 11 13 15 17 19 21

Exce

ss A

ir P

erc

en

tage

CO2 _Actual in Percentage

CO2_Actual

Excess Air




REFERENCES

[1] Henry CopeteLópez and Santiago Sánchez Acevedo., An Approach to

Optimal Control of the Combustion System in a Reverberatory Furnace,

RevistaTecnologicas No. 23, December 2009. [2] Yoshitaka and Akihiro Murata., Optimum Combustion control by

TDLS200 Tunable Diode Laser Gas Analyser, Yokogawa Technical

Report English Edition, Vol.53, No.1, 2010. [3] Mark Hudson Beale, Martin T Hagan and Howard B Demuth., Neural

Network Tool BoxTM –User’s Guide, R2013b.

[4] JigishaParikha, S.A. Channiwalab and G.K. Ghosalc., A correlation for

calculating HHV from proximate analysis of solid fuels, Science Direct,

Fuel84, pp. 487-494, 2005.

[5] James G. Speight., Hand Book of Coal Analysis, John Wiley & Sons,

Inc. Publications, Hoboken, New Jersey, 2005. [6] Viktor Placek, Cyril Oswald and Jan Hrdlicka., Optimal Combustion

Conditions for a Small-scale Biomass Boiler, ActaPolytechnica, Vol. 52,

No. 3, 2012.



153

Study of Microwave Radiation on

Transesterification of Jatropha Oil in Presence

of Alkali Catalyst

Nadira Hassan Mohammed Al Balushi#1

, Priy Brat Dwivedi*2

1Student,

2Project Guide, Mechanical & Industrial Engineering Department

Caledonian College of Engineering, Muscat, Oman

Corresponding author: [email protected]

Abstract— The objectives of this study is to produce biodiesel

from Jatropha oil using microwave radiation in presence of alkali

catalyst and designing suitable batch reactor for lab scale

production. Cost effectiveness of the project is also being studied.

This paper outlines studies done to find the optimal method for

converting Jatropha oil to useable biodiesel using microwave

irradiation. The amount of acid catalyst is 0.4w % and ratio of

methanol to oil is 6:1 w/w for the optimal trans-esterification.

Keywords: Jatropha oil, Biodiesel, Catalyst, Microwave radiation,

Trans-esterification

I. INTRODUCTION

Oil is running out. In the short term it will continue to go

up in price and in the middle distant future it will be too

expensive to burn. As the world energy demand and

consumption increases every day, we need to focus on the use

of biofuels that will help extend the lifetime of our oil supply,

but eventually we will need to replace oil. Whatever that

replacement is it needs to be sustainable.

By 2030, global energy consumption is projected to grow

by 36% [1] and, in our view; demand for liquid transport fuels

will rise by some 16 million barrels more a day. With the

world’s population projected to reach 8.3 billion by then, an

additional 1.3 billion people will need energy. To meet this

demand a diverse energy mix is needed. This is where biofuels

can help; in the next two decades, biofuels is expected to

provide some 20% (by energy) of the growth in fuel for road

transport [2]. The possibility of deriving bioduesel from

locally grown sources and using them as alternatives to petro

diesel products is attractive for many countries, including the

Sultanate of Oman, that currently depend largely on fossil

fuels.

Biodiesel is fuel that is similar to diesel fuel and is derived

from usually vegetable sources. Biodiesel refers to a vegetable

oil- or animal fat-based diesel fuel consisting of long-chain

alkyl (methyl, ethyl, or propyl) esters. Biodiesel is typically

made by chemically reacting lipids (e.g., vegetable oil, animal

fat (tallow) with an alcohol producing fatty acid esters (FAE).

Biodiesel helps reduce greenhouse gas emissions (GHGs)

because it comes from animal or plant biomass with a

lifecycle of a few years. On the other hand, petro diesel is a

fossil fuel that releases into the atmosphere carbon that has

been tied up for hundreds of millions of years, and all of it

adds to GHGs. Fossil fuels also release more tailpipe

emissions than does biodiesel. Biodiesel is a liquid which

varies in color between golden and dark brown depending on

the production feedstock. It is slightly miscible with water, has

a high boiling point and low vapor pressure. The flash point of

biodiesel (>130 °C, >266 °F) is significantly higher than that

of petroleum diesel (64 °C, 147 °F) or gasoline (−45 °C, -52

°F). Biodiesel has a density of ~ 0.88 g/cm³, higher than

petrodiesel (~ 0.85 g/cm³). Most diesel engines are warranted

to run on anywhere between B5 (5% biodiesel) to B20 (20%

biodiesel). [3] Have discussed few chemical and physical

properties of jatropha oil. (Table 1).

Kapilan [5] has used microwave radiation for two step

transesterification in his work and reported successful

production of biodiesel from jatropha oil grown in Indian soil.

Antony Raja, et al. [6] reported that Jatropha oil is converted

into jatropha oil methyl ester known as (biodiesel) prepared in

the presence of homogeneous acid catalyst. The same

characteristics study was also carried out for the diesel fuel for

obtaining the base line data for analysis.




154

TABLE I

CHEMICAL AND PHYSICAL PROPERTIES [4]

Parameter Value

% FFA as oleic acid

Iodine value

Saponification value

Peroxide value

Percentage oil content (kernel)

Density at 20° C (g/ml)

Viscosity at room temperature (cp)

Physical state at room temperatur

2.23±0.02

103.62±0.07

193.55±0.61

1.93±0.012

63.16±0.35

0.90317

42.88

Liquid

A Value is mean ± standard deviation of triplicate

determinations.

Marchetti, et al. [7] concluded that there are different ways

of production, with different kinds of raw materials: refine,

crude or frying oils. Also with different types of catalyst, basic

ones such as sodium or potassium hydroxides, acids such as

sulfuric acid and ion exchange resins. One of the advantages

of this fuel is that the raw materials used to produce it are

natural and renewable. Also of this process, the free fatty acid

will be changed completely in to esters. Bojan, et al. [8]

carried out his work to produce biodiesel from crude Jatropha

Curcas oil (CJCO) with a having high free fatty acid (HFFA)

contents (6.85%) and also the crude Jatropha Curcas oil was

processed in two steps. During the first step the free fatty acid

content of crude Jatropha Curcas oil was reduced to 1.12% in

one hour at 60°C using 9:1 methanol to oil molar ratio. The

second step was alkali catalyzed transesterification using

methanol to oil molar ratio of 5.41:1 to produce biodiesel from

the product of the first step at 60°C.The maximum yield of

biodiesel was 93% v/v of crude Jatropha Curcas oil which was

more than the biodiesel yield (80.5%) from the one step alkali

catalyzed transesterification process. Temu, et al. [9] reported

that the quality of biodiesel is influenced by the nature of

feedstock and the production processes employed. The

physico-chemical properties of jatropha and castor oils were

assessed for their potential in biodiesel. The properties of

jatropha and castor oils were compared with those of palm

from literature while that of biodiesel were compared with

petro-diesel. Results showed that high amounts of FFA in oils

produced low quality biodiesel while neutralized oils with low

amounts of FFA produced high quality biodiesel.

In current study locally grown jatropha oil was taken as

feed stock and two step transesterification was done by

microwave radiation.

Antony, et al. [10] reported that all countries are at present

heavily dependent on petroleum fuels for transportation and

agricultural machinery. The fact that a few nations together

produce the bulk of petroleum has led to high price fluctuation

and uncertainties in supply for the consuming nations. This in

turn has led them to look for alternative fuels that they

themselves can produce. Among the alternatives being

considered are methanol, ethanol, biogas and vegetable oils.

Vegetable oils have certain features that make them attractive

as substitute for Diesel fuels. Vegetable oil has the

characteristics compatible with the CI engine systems.

Vegetable oils are also miscible with diesel fuel in any

proportion and can be used as extenders. Ronnie, et al. [11]

concluded that the benefits of jatropha as biodiesel include the

reduction of greenhouse gas emissions, as well as the

country’s oil imports. Local production of jatropha is also

practical because as a non-food crop, it will not compete with

food supply demands. It can also grow on marginal degraded

land, leaving prime agricultural lots for food crops while at the

same time restoring the marginal and degraded land’s fertility.

All of these benefits can possibly be achieved by the presence

of this locally fabricated high efficiency jatropha oil extractor

equipment.

This mixture was heated in LG make domestic microwave

oven with occasional shaking for 60 seconds. Power level was

set at 160 W. This pretreatment was done with every set

before mixture was set for transesterification. This pre-treated

jatropha oil was used in base catalysed second-step

transesterification.

In the second step, transesterification was carried out at

with various methanol-to- oil ratio, at various catalyst strength,

and various time duration. In this step also power supply 160

W. Results of variations are summarized in table 2. After the

reaction, the excess methanol was removed by vacuum

distillation and then the trans-esterification products were

poured into a separating funnel for phase separation. After

phase separation, the top layer (biodiesel), was separated and

washed with distilled water in order to remove the impurities.

Then the biodiesel was heated above 1000C, to remove the

moisture.

Fig 1: Conventional Heating

II. MATERIALS

For current study, Jatropha oil was purchased from local

market in Salalah, Oman. This oil was filtered and then used



155

for the production of biodiesel. Sulphric acid (H2SO4)

is used as acid catalyst in first step and KOH was used as

catalyst in second step. In our study we used Methanol for

transesterification. Because methanol is cheaper and has better

physical and chemical properties (polar and shortest chain

alcohol). Potassium hydroxide, methanol and sulphuric acid

were purchased from Schalau, Chemie S.A, Spain. All the

chemicals used for transesterification were of analytical

reagent grade. Study was done in LG domestic microwave

oven at 160 W power levels.

Fig 2: Microwave-assisted biodiesel production units.

III. BIODIESEL PRODUCTION

Acid value of Jatropha oil was determined by standard

method and it was found as 9 mg KOH per g of oil. Since acid

value is higher than 1 mg KOH, acid catalyzed trans-

esterification is necessary in first step. Acid catalyzed trans-

esterification is good if oil is having high free fatty acid

content. It avoids possibility of soap formation like in case of

alkali catalyst. In this pretreatment, methanol-to-oil ratio was

taken as 4:1 w/w and 0.4 w% of H2SO4 was

IV. RESULTS AND DISCUSSION

Conventional heating set was also studied (Figure 1) with

5g of jatropha oil, 40 ml methanol and 5 hrs of refluxing.

Biodiesel yield was 3.09g. From table 2 it is clear that

microwave radiation is one of the best tools for

transesterification of Jatropha oil. During experiment various

ratios of methanol to jatropha oil was tested. Results are

summarized in table 2 (entries 1, 2 and 3). Optimum yield was

found when methanol to oil ratio was 6:1. Later yield was

decreasing with increasing the amount of methanol. More

study is required in this area to find the reasons behind this

observation. In case of alkali catalyst variation, (entries 4, 5

and 6 in table 2) biodiesel yield was increasing with increase

in alkali catalyst concentration. But due to of possibility of

soap formation and difficulty in product separation, catalyst

ratio was not studied beyond 0.8 w%. During this study,

effect of time was also studied and results are summarized in

table 2 (entries number 7, 8, and 9). Yield of biodiesel was

found to be increasing with time. But to avoid bumping and

overheating, no study was done after 200 seconds.

Biodiesel production by microwave irradiation was due to

direct adsorption of the radiation by the polar group (OH

group) of methanol. It is speculated that the OH group is

directly excited by microwave radiation, and the local

temperature around the OH group would be very much higher

than its environment. Hence, microwave assisted

transesterification is a way of reducing the reaction time, the

electrical energy and labor costs as compared to the

conventional method.

TABLE II

SUMMARY OF MICROWAVE HEATING VARIATION

No. Oil(g) Methanol

(g)

Catalyst

(g)

Time(s) Yield

(g)

1 5g 30g 0.02g 80s 4.8

2 5g 40g 0.02g 80s 4.68

3 5g 50g 0.02g 80s 3.97

4 5g 40g 0.01g 140s 4.06

5 5g 40g 0.02g 140s 4.10

6 5g 40g 0.04g 140s 4.21

7 5g 50g 0.02g 80s 3.9

8 5g 50g 0.02g 140s 4.18

9 5g 50g 0.02g 200s 4.26

After variation, biodiesel properties were tested as per

ASTM D 6751, for various parameters as given in table 3.

TABLE III

FUEL PROPERTIES

Property ASTM D6751 Biodiesel Diesel

Flash point (◦C) > 130 128 68

Pour point (◦C) - – 7 −15

Calorific Value

(MJ/kg) - 39.9 42.71

Viscosity at 40 ◦C

(mm2/sec)

1.9–6 4.20 2.28

Density at 15 ◦C

(kg/m3)

– 901 846

Water content

(mg/kg)

< 500 99 102

Acid number (mg

KOH/g)

< 0.50 0.80 0.34

Copper strip

corrosion

>No. 3 1 1

Ash Content (%) < 0.02 0.01 0.01

Table III compares the properties of jatropha biodiesel

produced in this study with the properties of diesel. The flash

point of biodiesel satisfies the fuel standards and is better than

the flashpoint diesel. This is an important safety consideration

when handling and storing flammable materials. The

important cold flow properties of biodiesel are the cloud and

pour point.



156

According to ASTM standard D 6751, no limit is

given for pour point and suggested “report” in the fuel

standard. The calorific value is an important property of

biodiesel that determines its suitability as an alternative to

diesel. As per European standard, EN 14214, the approved

calorific value for biodiesel is 35 MJ per kg. The table shows

that the calorific value of jatropha biodiesel is close to that of

diesel. According to the ASTM standards, the acceptable

viscosity range for biodiesel is between 1.9–6.0 mm2/s at

400C, and jatropha biodiesel satisfies the biodiesel standard.

The density of jatropha biodiesel is close to that of diesel and

satisfies the ASTM standard. ASTM standard approves a

maximum acid value for biodiesel of 0.5 mg KOH/g, but

jatropha biodiesel produced in this study has acid value 0.80

mg. The degree of tarnish on the corroded copper strip

correlates to the overall corrosiveness of the fuel sample. The

copper strip corrosion property of jatropha biodiesel is within

the specifications of ASTM. Another important factor of

biodiesel is the ash content estimation. The ash content of

jatropha biodiesel satisfies the ASTM standard.

V. CONCLUSIONS

In this work, biodiesel was produced from jatropha oil

using microwave radiation and with the help of two-step

transesterfication. It was observed that microwave radiation

helps the synthesis of methyl esters (biodiesel) from non-

edible oil, and higher biodiesel conversion can be obtained

within a few minutes, whereas the conventional heating

process takes more than 5 hrs.

In the current investigation, it has confirmed that Jatropha

oil may be used as resource to obtain biodiesel. The

experimental result shows that alkali catalyzed

transesterification is a promising area of research for the

production of biodiesel in large scale. Effects of different

parameters such as time, reactant ratio and catalyst

concentration on the biodiesel yield were analyzed. The best

combination of the parameters was found as 6:1 w/w ratio of

Methanol to oil, 0.8 w% of KOH as catalyst and 200 seconds

of reaction time. The viscosity of Jatropha oil reduces

substantially after transesterification and is comparable to

diesel. Biodiesel characteristics like density, viscosity, flash

point, and pour point were studied and are found as

comparable to diesel.

ACKNOWLEDGEMENT

Authors are thankful to Caledonian College of Engineering, Muscat,

for supporting this work.

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Ijsrtm vol 2 (4) june july 2014