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INTERNATIONALMechanical Engineering and Technology (IJMET), ISSN 0976 –
 International Journal of JOURNAL OF MECHANICAL ENGINEERING
 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME
                          AND TECHNOLOGY (IJMET)
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 4, Issue 1, January- February (2013), pp. 209-221
                                                                           IJMET
© IAEME: www.iaeme.com/ijmet.asp
Journal Impact Factor (2012): 3.8071 (Calculated by GISI)
www.jifactor.com
                                                                       ©IAEME


       COMPUTATIONAL AND EXPERIMENTAL STUDY OF ENGINE
       CHARACTERISTICS USING N-BUTANOL GASOLINE BLENDS

                        S Raviteja1, Shashank S N1 and Kumar G N2
       1
        Student, Department of Mechanical Engineering, National Institute of Technology
                         Karnataka Surathkal, Mangalore, India- 575025
       2
         Assistant Professor, Department of Mechanical Engineering, National Institute of
                   Technology Karnataka Surathkal, Mangalore, India- 575025


  ABSTRACT

          This study investigates the effect of blending of n-butanol with gasoline in a four-
  stroke spark ignited MPI engine. AVL BOOST was used as a computational fluid dynamics
  (CFD) simulation tool to analyze the performance and emission characteristics for different
  blends of n-butanol and gasoline (0%, 10%, 20% and 30% of butanol by volume). The study
  was carried out at full load conditions for different engine speeds. CFD results are always
  approximate due to truncation errors. An experiment was conducted on a four-cylinder spark
  ignited MPI engine to validate the results obtained from AVL Boost. AVL simulation and
  experimental results showed a considerable decrease in Hydro-Carbon (HC) Emissions and
  the percentage of Carbon Monoxide (CO) emitted remained constant. However, an increase
  in emissions of Oxides of Nitrogen (NOx) was observed in both cases.

  Keywords: AVL Boost, CFD, Emissions, n-Butanol blends, Variable speed

  1.       INTRODUCTION

         The Dwindling crude oil reserves and the long lead times in creating these fuels have
  brought in the fear of fuel crisis in the near future. The known worldwide reserves of
  petroleum are about 1000 billion barrels and these petroleum reserves are predicted to be
  consumed in about 30 years. Increasing Air pollution is one of the other major problems
  being faced by the world today. This has led to a debate on usage of alternate fuels which
  have the potential to replace gasoline. Alcohols are advocated as the prospective fuels
  because they can be manufactured from natural products or waste materials, unlike gasoline
  which is a non renewable energy resource. Alcohols can be used directly without requiring

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any major changes in the structure of the engine. Ethanol was the first fuel among the
alcohols used to power vehicles in the 1880s and 1890s [1]. However, economic reasons still
limit its usage on a large-scale.

        Butanol has a 4-carbon structure with a hydroxyl group (-OH) attached to one of the
carbon atoms. There exist different isomers of butanol based on their molecular structure.
n-Butanol has a straight chain structure. Various properties of n-Butanol in comparison with
fossil fuels and few other alcohols have been presented in the TABLE 1. Studies have shown
that n-butanol is more advantageous over the lighter alcohols like ethanol and methanol.
n-Butanol has higher energy content when compared to ethanol, which reduces the Specific
Fuel Consumption. n-Butanol is also less prone to water contamination and is less volatile in
comparison to ethanol. As a result it could be distributed and stored using the same
infrastructure used for gasoline. n-Butanol has a higher heat of evaporation. n-Butanol has
lower volatility, which reduces the tendency of cavitation and vapour lock. n-Butanol has a
lesser heat of vaporization, which enables easy cold start. n-Butanol has a very low vapour
pressure and high flash point, which makes it a safe fuel [2].

       n-Butanol can be produced from both petrochemicals as well as from renewable
resources like agricultural waste. Historically, n-Butanol was produced by biological
fermentation processes. The advent of biotechnology has made possible many new advanced
chemical and biological ways of butanol production [3]. Butanol production from
fermentation process of agricultural feedstock by cellulosic enzymes has the potential to cut
its production cost [4]. However the studies investigating the use of Butanol in internal
combustion engines are very limited. This study investigates the effect of n- Butanol gasoline
blends in a Spark Ignited Internal Combustion Engine.

                            Table 1: Property of different fuels

                                      Gasoline       Methanol Ethanol      n-Butanol
           Molecular formula           C4-C12        CH3OH C2H5OH           C4H9OH
            Octane Number              80-99           111      108            96
        Oxygen content(% weight)          -            50      34.8           21.6
                                       0.72-
          Density(g/mL) at 20oC                       0.796     0.790        0.808
                                        0.78
              Auto-ignition
                                         300           470       434          385
             Temperature(oC)
              Lower Heating
                                         42.7          19.9      26.8         33.1
              Value(MJ/kg)
         Latent Heating (kJ/kg) at
                                       380-500        1109       904          582
                  25oC
           Stoichiometric ratio         14.7          31.69      13.8        2.27
            Boiling Point(oC)          25-215          64.5      78.4        117.7

        The advent of high-speed digital computers and advances in Computational methods
has made it possible for the researchers to simulate and analyse complex physiological
processes. The huge amount of results that are obtained by simulation studies are rather very
difficult to be obtained experimentally. The use of Computational Fluid Dynamics (CFD)
further saves upon the manpower, material and financial resources.CFD has been looked

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upon as a high-technology research and design tool by the automobile researchers. The ability
to analyse not only the external flows but also the flows in the manifolds and engine cylinders
has made the use of CFD essential before actual experimentation. Advances in
Computational algorithms have helped researchers to even simulate the combustion process
happening within the cylinder [5]. The present study uses CFD to simulate the combustion
process of butanol blends in IC Engine.

2.     BACKGROUND

         Investigation of butanol usage as an engine fuel has been conducted by several
research groups. Alasfour reported that there was an increase in first and second-law
efficiencies in the lean regions for the butanol-gasoline blend; also investigations were made
on the effect of spark timing on the NOx production for a engine running on 30% iso-butanol-
gasoline engine [6, 7]. J. Dernotte et al assessed influence of butanol addition on the
emission of unburned hydrocarbons, carbon monoxide, and nitrogen oxide using different
butanol–gasoline blends in a port fuel-injection, spark-ignition engine. The studies reported
that 40% butanol/60% gasoline blend by volume (B40) minimized HC emissions, no
significant change in NOx emissions except B80,which showed lower emission levels due to
combustion deterioration [8]. Studies by S. Szwaja and J.D. Naber reported that Combustion
stability at the part-load condition as measured by the COV of IMEP was slightly lower for n-
butanol in comparison to gasoline using blends of n -butanol to gasoline with ratios of 0%,
20%, and 60% in a single cylinder Waukesha Cooperative Fuels Research engine (CFR) SI
engine with variable compression ratio [4]. Xiaolei Gu et al analysed the effect of spark
timing, blend ratio and EGR rate on the emission characteristics. Results showed that the
blends of gasoline and n-butanol decrease engine specific HC, CO and NOx emissions
compared to those of gasoline. It was also examined that EGR reduces engine specific NOx
emissions and particle number concentration simultaneously in spark-ignition engine fuelled
with gasoline and n -butanol blends [9]. Experimental tests were carried out by G. Broustail
et al on a single-cylinder port-fuel injection SI engine to quantify the potential of
butanol/isooctane blends to reduce regulated pollutants (CO, CO2, NOx and HC), and non-
regulated pollutants (methane, acetylene, ethylene, benzene, acetaldehyde and
formaldehyde), without deteriorating the engine performance. It was reported that there was
an increase of the fuel consumption of about 30% with butanol and 60% with ethanol, but
only a slight increase (about 2%) in CO2 emissions. A strong decrease in HC and NOx
emissions was obtained for both alcohols [10]. Adrian Irimescu investigated the effect of
fuelling a port injection engine with iso-butanol, as compared to gasoline operation. Fuel
conversion efficiency decreased when the engine was fueled with iso-butanol by up to 9% at
full load and by up to 11% at part load. He cited incomplete fuel evaporation as the reason for
the drop in engine efficiency [11]. In his additional investigations, it was found that Iso-
butanol can be blended with gasoline in much higher concentrations compared to ethanol,
without any modifications to the fuel system or other engine components [12].

3.     PRESENT WORK

       AVL Boost is a package of computer codes which enables the user to model and
simulate the various processes of an Internal Combustion Engine. In the current investigation
AVL BOOST has been used to analyze effect the blending of n-Butanol (C4H10O) with


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gasoline at different concentrations. Blends of n-Butanol to gasoline with ratios of 0%, 10%,
20%, and 30% by volume were used in the simulation for various speed conditions. Due to
the fact that CFD results are always approximate, Engine Test bed experiments were
conducted to validate the results obtained from the simulations. One of the purposes of this
paper is to analyze the computed results and their deviation from the experimental results.

4.      SIMULATION MODELLING

       The pre-processing steps of AVL Boost enables the user to model a 1-Dimensional
engine test bench setup using the predefined elements provided in the software toolbox. The
various elements are joined by the desired connectors to establish the complete engine model
using pipelines.

       In Fig.1, E1 represents the engine C1, C2, C3, C4 represent the four cylinders of the
engine. MP1 to MP14 represent the measuring points, PL1, PL2 represent the plenum.SB1,
SB2 are for the system boundary and the flow pipes are numbered 1 to 32. CL1 represents the
cleaner and R1 to R10 represent flow restrictions.




                      Figure 1: AVL BOOST 1D Engine model

       The various configurations and parameters are set for each element. The system
boundary conditions are specified. It is important to make a correct estimate of the boundary
conditions as it directly affects the accuracy of the results.

        For the current study Vibe two zone model was selected for the combustion analysis.
This model divides the combustion chamber into unburned and burned gas regions [13]. The
first law of thermodynamics is applied to each of the zones to predict the rate of fuel
consumed with respect to crank angle.


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        The following equations (1, 2) govern the Vibe two zone model [14]:

                     ௗ௠್ ௨್           ௗ௏್       ௗொ೑          ௗொೈ್             ௗ௠್                ௗ௠ಳಳ,್
                        ௗఈ
                              ൌ െ‫݌‬௖   ௗఈ
                                            ൅   ௗఈ
                                                       െ∑     ௗఈ
                                                                    ൅ ݄௨       ௗఈ
                                                                                    െ ݄஻஻,௕       ௗఈ
                                                                                                          (1)



                     ௗ௠ೠ ௨ೠ           ௗ௏ೠ        ௗொೈೠ              ௗ௠್                   ௗ௠ಳಳ,ೠ
                        ௗఈ
                              ൌ െ‫݌‬௖   ௗఈ
                                            െ∑        ௗఈ
                                                            െ ݄௨    ௗఈ
                                                                             െ ݄஻஻,௨        ௗఈ
                                                                                                          (2)

Where


              ݀݉௖ ‫ݑ‬௖                  Denotes change of the internal energy in the cylinder

                  ௗ௏೎
             ‫݌‬௖                       Denotes piston work
                  ௗఈ

                  ௗொ೑
                                      Denotes fuel heat input
                  ௗఈ

              ௗொೈ೎
                                      Denotes wall heat losses
                ௗఈ

                ௗ௠೎
           ݄௨     ௗఈ
                                      Denotes enthalpy flow from the unburned to the burned zone

             ௗ௠ಳಳ,೎
     ݄஻஻,௖                            Denotes enthalpy due to blow by
                ௗఈ

                               u and b in the subscripts denote unburned and burned gas

       Prediction of NOx generated by combustion was based on the model by Pattas and
Häfner which incorporates the well known Zeldovich mechanism [15].The rate of NOx
production was estimated by using the following equation (3):
                                                                         ௥          ௥ర
                     ‫ݎ‬ேை ൌ ‫ܥ‬௉௉ெ . ‫ܥ‬௄ெ . ሺ2.0ሻ. ሺ1 െ ߙ ଶ ሻ ଵାఈ.஺௄
                                                             భ
                                                                                                          (3)
                                                                               మ ଵା஺௄ర


                                                           ܿேை,௔௖௧ 1
                                                 ߙൌ               .
                                                           ܿேை,௘௤௨ ‫ܥ‬௉௉ெ


                                                  ௥భ                                 ௥ర
                                      ‫ܭܣ‬ଶ ൌ ௥                        ‫ܭܣ‬ସ ൌ ௥
                                                 మ ା௥య                              ఱ ା௥ల


Where
             ‫ܥ‬௉௉ெ                                Denotes Post Processing Multiplier
             ‫ܥ‬௄ெ                                 Denotes Kinetic Multiplier
             c                                   Denotes molar concentration in equilibrium
             ri                                  Denotes reactions rates of Zeldovich mechanism


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       The amount of CO emissions was predicted using the following equation (4) which
was taken from a model presented by Onorati et al[16].


                               ‫ݎ‬஼ை ൌ ‫ܥ‬஼௢௡௦௧ . ሺ1 െ ߙሻ. ሺ‫ݎ‬ଵ ൅ ‫ݎ‬ଶ ሻ                         (4)

                                              ܿ஼ை,௔௖௧
                                         ߙൌ
                                              ܿ஼ை,௘௤௨
Where
           c                         Denotes molar concentration in equilibrium
           ri                        Denotes reactions rates based on the model

      The process of formation of unburned hydrocarbons in the crevices is described by
assuming that, the pressure in the cylinder and in the crevices is the same and that the
temperature of the mass in the crevice volumes is equal to the piston temperature [17].

The mass in the crevices at any time period is given by equation (5):
                                                           ௣.௏೎ೝ೐ೡ೔೎೐.ெ
                                              ݉௖௥௘௩௜௖௘ ൌ    ோ.்೛೔ೞ೟೚೙
                                                                                          (5)
Where

           mcrevice                  Denotes mass of unburned charge in the crevices [kg]
           p                         Denotes cylinder pressure [Pa]
           Vcrevice                  Denotes total crevice volume [m3]
           M                         Denotes unburned molecular weight [kg/kmol]
           R                         Denotes gas constant [J/( kmol K)]
           Tpiston                   Denotes piston temperature [K]

        Butanol properties are not pre-defined in AVL BOOST. Hence coefficients for
calculating thermodynamic properties of Butanol were taken from NASA Technical
Memorandum [18] and were added to the BOOST fuel database to simulate the engine
fuelled with the blends.

5.      EXPERIMENTAL SETUP AND EXPERIMENTS

        The engine setup consists of a four-stroke, four cylinder, SI engine as shown in the
Fig. 2. The setup had stand-alone panel box consisting of air box, fuel tank, manometer, fuel
measuring unit, transmitters for air and fuel flow measurements, process indicator and engine
indicator. Rotameters were provided for cooling water and calorimeter water flow
measurement. The setup enables study of engine performance for brake power, indicated
power, frictional power, BMEP, IMEP, brake thermal efficiency, indicated thermal
efficiency, mechanical efficiency, volumetric efficiency, specific fuel consumption, air-fuel
ratio (A/F) and heat balance. Windows based engine performance analysis software package
‘Engine Soft’ is provided for on-line performance evaluation.




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                     Figure 2: Schematic Diagram of Experimental set up


        AVL 5 gas exhaust analyser was used to obtain the emission characteristics.
TABLE.2 gives the range and resolution of the analyser. TABLE 3 gives the technical
specifications of the engine used for the experiments.


            Table 2: Range and Resolution of the AVL exhaust gas analyser
 Measured Parameters            Measured Range                  Resolution
 CO                             0-10% Vol.                      0.01% Vol.
 HC                             0-20000 ppm                     10 ppm
 CO2                            0-20% Vol.                      0.1% Vol.
 O2                             0-22% Vol.                      0.01% Vol.
 NO                             0-5000 ppm                      1 ppm


                           Table 3: Specifications of the Engine
 Make                                            Suzuki
 Model                                           Zen MPFI
 Type                                            4 Cylinder, 4 stroke
 Capacity                                        993 cc
 Cooling                                         Water Cooled
 Max. Power                                      44.5kW @ 6000rpm
 Max. Torque                                     59Nm @ 2500rpm
 Stroke                                          61mm
 Bore                                            72mm
 Compression Ratio                               9.4:1




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6.       RESULTS AND DISCUSSION
       The present study concentrated on the emission and performance characteristics
of the n- butanol-gasoline blends. Different concentrations of the blends (10% n-Butanol
(B10), 20% n-Butanol(B20) and 30% n-Butanol(B30) by volume) were analysed using AVL
BOOST codes and were validated experimentally at full load conditions for the speeds
ranging from 2000-4000 rpm in the steps of 500rpm. The results are divided into different
subsections based on the parameter analysed.
6.1 Brake Power
       Brake power is one of the important factors that determine the performance of an
engine. The variation of brake power with Speed was obtained at full load conditions for
B10, B20, B30 and pure gasoline using the CFD results. The results were also validated
experimentally and it was found that there was a very small deviation in CFD results from the
experimental results. This can be clearly seen in Fig. 3 to Fig. 6




     Figure 3: Variation of Brake Power with         Figure 4: Variation of Brake Power with
             speed for pure Gasoline                          speed for case of B10




 Figure 5: Variation of Brake Power with        Figure 6: Variation of Brake Power with speed
             speed for B20                                         for B30

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        The deviation noted in all the four cases is very small and occurs due to the assumptions
made during the CFD analysis as well as the human errors made during the experiments. The
results show that the brake power increases in the cases of B10 and B20 compared to Pure
Gasoline. However there was a decrease in case of B30. This factor can be acknowledged to the
lower heating value of n-Butanol compared to Gasoline.

6.2 CO Emissions
        Carbon Monoxide (CO) emission is a strong function of equivalence ratio. The influence
of other parameters on the emissions of CO is very low and the percentage of CO emitted from
the engine was almost constant with increasing speed at full load condition. The variation of CO
emissions with respect to speed for different blends is shown below in Fig. 7 to Fig.10.

       Both CFD and experimental results show that the change in percentage of CO emissions
with varying speed is constant at full load conditions for all the cases.




  Figure 7: Variation of CO with speed for      Figure 8: Variation of CO with speed for
               pure Gasoline                                      B10




 Figure 9: Variation of CO with speed               Figure 10: Variation of CO with speed
                  for B20                                        for B30



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        The emission of CO increases for B10 and drastically decreases for B20 and B30.
This decrease can be attributed for the presence of extra oxygen molecule in n-Butanol which
helps in more complete combustion and thus decrease in amount of CO.

6.3 NOx Emissions
        NOx emissions are mainly affected by the equivalence ratio, peak temperature,
ignition timing and oxygen concentration in the fuel. In the present study, NOx emissions
were obtained from CFD analysis and the results were validated experimentally. Both the
results have shown that there was increase in NOx emissions with increase in speed. B10,
B20, B30 showed an increase in NOx emissions because of the increase in oxygen
concentration. The CFD and Experimental results are shown for various cases in Fig. 11 to
Fig.14.




   Figure 11: Variation of NOx with speed         Figure 12: Variation of NOx with speed
                for gasoline                                     for B10




  Figure 13: Variation of NOx with speed          Figure 14: Variation of NOx with speed
                 for B20                                         for B30



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6.4 HC Emissions
        The origin of unburned hydrocarbons (HC) in SI Engines is due to incomplete
combustion of charge. Major source of HC emission is the charge in the crevice volume
which is not burned due to flame quenching at the entrance and fuel vapours absorbed by the
oil layers are not burned during the combustion process. Variations of HC emitted with
respect to speed are shown Fig.15 to Fig.18.




    Figure 15: Variation of HC with speed           Figure 16: Variation of HC with speed for
              for pure gasoline                                        B10




  Figure 17: Variation of HC with speed for          Figure 18: Variation of HC with speed for
                     B20                                                B30

From the results obtained, it is clear that HC emissions decrease with increase in percentage
of n-butanol. However experimentally obtained results showed a considerable deviation from
CFD results. This is due to the fact that a complete description of the HC formation process
cannot yet be simulated and the achievement of a reliable predictive model within a
thermodynamic approach is prevented by the fundamental assumptions and the requirement
of reduced computational times [14]. AVL BOOST code predicts the formation of HC based
on G. D'Errico model. n-Butanol is not readily available in the AVL database and considers

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only thermodynamic and transport properties for the prediction of combustion. However fuel
specific properties are not considered. Laminar flame speeds of alcohols are higher compared
to gasoline. Hence this leads to better combustion at higher engine speeds and decrease in HC
emissions which are not accounted by the software.

7.       CONCLUSIONS

    CFD and experimental analysis was carried out successfully on SI Engine and the
following conclusions are made based on the results.

     •   CFD and experimental results complement each other for the performance
         characteristics at full load conditions for all blends.
     •   CO emissions remained constant experimentally for all blends as predicted by the
         CFD simulations.
     •   NO emissions were estimated to increase with the increase in butanol concentration
         by AVL BOOST and were successfully validated by the experiments.
     •   CFD results showed a considerable deviation in forecasting HC emissions when
         compared to the experiments.

8.       ACKNOWLEDGEMENTS

       The authors would like to acknowledge AVL-AST, Graz, Austria for granted use of
AVL-BOOST under the university partnership program. We are also eternally grateful to
staff members of NITK Surathkal for their immense support.

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Engineering & Technology (IJMET), Volume 3, Issue 2, 2012, pp. 397 - 409,
ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359, Published by IAEME.
[22] S M Lawankar and Dr L P Dhamande, “Comparative Study of Performance of LPG
Fuelled SI Engine at Different Compression Ratio and Ignition Timing” International Journal
of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 3, 2012, pp. 337 - 343,
ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359, Published by IAEME.




                                           221

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Computational and experimental study of engine characteristics using n butanol

  • 1. INTERNATIONALMechanical Engineering and Technology (IJMET), ISSN 0976 – International Journal of JOURNAL OF MECHANICAL ENGINEERING 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME AND TECHNOLOGY (IJMET) ISSN 0976 – 6340 (Print) ISSN 0976 – 6359 (Online) Volume 4, Issue 1, January- February (2013), pp. 209-221 IJMET © IAEME: www.iaeme.com/ijmet.asp Journal Impact Factor (2012): 3.8071 (Calculated by GISI) www.jifactor.com ©IAEME COMPUTATIONAL AND EXPERIMENTAL STUDY OF ENGINE CHARACTERISTICS USING N-BUTANOL GASOLINE BLENDS S Raviteja1, Shashank S N1 and Kumar G N2 1 Student, Department of Mechanical Engineering, National Institute of Technology Karnataka Surathkal, Mangalore, India- 575025 2 Assistant Professor, Department of Mechanical Engineering, National Institute of Technology Karnataka Surathkal, Mangalore, India- 575025 ABSTRACT This study investigates the effect of blending of n-butanol with gasoline in a four- stroke spark ignited MPI engine. AVL BOOST was used as a computational fluid dynamics (CFD) simulation tool to analyze the performance and emission characteristics for different blends of n-butanol and gasoline (0%, 10%, 20% and 30% of butanol by volume). The study was carried out at full load conditions for different engine speeds. CFD results are always approximate due to truncation errors. An experiment was conducted on a four-cylinder spark ignited MPI engine to validate the results obtained from AVL Boost. AVL simulation and experimental results showed a considerable decrease in Hydro-Carbon (HC) Emissions and the percentage of Carbon Monoxide (CO) emitted remained constant. However, an increase in emissions of Oxides of Nitrogen (NOx) was observed in both cases. Keywords: AVL Boost, CFD, Emissions, n-Butanol blends, Variable speed 1. INTRODUCTION The Dwindling crude oil reserves and the long lead times in creating these fuels have brought in the fear of fuel crisis in the near future. The known worldwide reserves of petroleum are about 1000 billion barrels and these petroleum reserves are predicted to be consumed in about 30 years. Increasing Air pollution is one of the other major problems being faced by the world today. This has led to a debate on usage of alternate fuels which have the potential to replace gasoline. Alcohols are advocated as the prospective fuels because they can be manufactured from natural products or waste materials, unlike gasoline which is a non renewable energy resource. Alcohols can be used directly without requiring 209
  • 2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME any major changes in the structure of the engine. Ethanol was the first fuel among the alcohols used to power vehicles in the 1880s and 1890s [1]. However, economic reasons still limit its usage on a large-scale. Butanol has a 4-carbon structure with a hydroxyl group (-OH) attached to one of the carbon atoms. There exist different isomers of butanol based on their molecular structure. n-Butanol has a straight chain structure. Various properties of n-Butanol in comparison with fossil fuels and few other alcohols have been presented in the TABLE 1. Studies have shown that n-butanol is more advantageous over the lighter alcohols like ethanol and methanol. n-Butanol has higher energy content when compared to ethanol, which reduces the Specific Fuel Consumption. n-Butanol is also less prone to water contamination and is less volatile in comparison to ethanol. As a result it could be distributed and stored using the same infrastructure used for gasoline. n-Butanol has a higher heat of evaporation. n-Butanol has lower volatility, which reduces the tendency of cavitation and vapour lock. n-Butanol has a lesser heat of vaporization, which enables easy cold start. n-Butanol has a very low vapour pressure and high flash point, which makes it a safe fuel [2]. n-Butanol can be produced from both petrochemicals as well as from renewable resources like agricultural waste. Historically, n-Butanol was produced by biological fermentation processes. The advent of biotechnology has made possible many new advanced chemical and biological ways of butanol production [3]. Butanol production from fermentation process of agricultural feedstock by cellulosic enzymes has the potential to cut its production cost [4]. However the studies investigating the use of Butanol in internal combustion engines are very limited. This study investigates the effect of n- Butanol gasoline blends in a Spark Ignited Internal Combustion Engine. Table 1: Property of different fuels Gasoline Methanol Ethanol n-Butanol Molecular formula C4-C12 CH3OH C2H5OH C4H9OH Octane Number 80-99 111 108 96 Oxygen content(% weight) - 50 34.8 21.6 0.72- Density(g/mL) at 20oC 0.796 0.790 0.808 0.78 Auto-ignition 300 470 434 385 Temperature(oC) Lower Heating 42.7 19.9 26.8 33.1 Value(MJ/kg) Latent Heating (kJ/kg) at 380-500 1109 904 582 25oC Stoichiometric ratio 14.7 31.69 13.8 2.27 Boiling Point(oC) 25-215 64.5 78.4 117.7 The advent of high-speed digital computers and advances in Computational methods has made it possible for the researchers to simulate and analyse complex physiological processes. The huge amount of results that are obtained by simulation studies are rather very difficult to be obtained experimentally. The use of Computational Fluid Dynamics (CFD) further saves upon the manpower, material and financial resources.CFD has been looked 210
  • 3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME upon as a high-technology research and design tool by the automobile researchers. The ability to analyse not only the external flows but also the flows in the manifolds and engine cylinders has made the use of CFD essential before actual experimentation. Advances in Computational algorithms have helped researchers to even simulate the combustion process happening within the cylinder [5]. The present study uses CFD to simulate the combustion process of butanol blends in IC Engine. 2. BACKGROUND Investigation of butanol usage as an engine fuel has been conducted by several research groups. Alasfour reported that there was an increase in first and second-law efficiencies in the lean regions for the butanol-gasoline blend; also investigations were made on the effect of spark timing on the NOx production for a engine running on 30% iso-butanol- gasoline engine [6, 7]. J. Dernotte et al assessed influence of butanol addition on the emission of unburned hydrocarbons, carbon monoxide, and nitrogen oxide using different butanol–gasoline blends in a port fuel-injection, spark-ignition engine. The studies reported that 40% butanol/60% gasoline blend by volume (B40) minimized HC emissions, no significant change in NOx emissions except B80,which showed lower emission levels due to combustion deterioration [8]. Studies by S. Szwaja and J.D. Naber reported that Combustion stability at the part-load condition as measured by the COV of IMEP was slightly lower for n- butanol in comparison to gasoline using blends of n -butanol to gasoline with ratios of 0%, 20%, and 60% in a single cylinder Waukesha Cooperative Fuels Research engine (CFR) SI engine with variable compression ratio [4]. Xiaolei Gu et al analysed the effect of spark timing, blend ratio and EGR rate on the emission characteristics. Results showed that the blends of gasoline and n-butanol decrease engine specific HC, CO and NOx emissions compared to those of gasoline. It was also examined that EGR reduces engine specific NOx emissions and particle number concentration simultaneously in spark-ignition engine fuelled with gasoline and n -butanol blends [9]. Experimental tests were carried out by G. Broustail et al on a single-cylinder port-fuel injection SI engine to quantify the potential of butanol/isooctane blends to reduce regulated pollutants (CO, CO2, NOx and HC), and non- regulated pollutants (methane, acetylene, ethylene, benzene, acetaldehyde and formaldehyde), without deteriorating the engine performance. It was reported that there was an increase of the fuel consumption of about 30% with butanol and 60% with ethanol, but only a slight increase (about 2%) in CO2 emissions. A strong decrease in HC and NOx emissions was obtained for both alcohols [10]. Adrian Irimescu investigated the effect of fuelling a port injection engine with iso-butanol, as compared to gasoline operation. Fuel conversion efficiency decreased when the engine was fueled with iso-butanol by up to 9% at full load and by up to 11% at part load. He cited incomplete fuel evaporation as the reason for the drop in engine efficiency [11]. In his additional investigations, it was found that Iso- butanol can be blended with gasoline in much higher concentrations compared to ethanol, without any modifications to the fuel system or other engine components [12]. 3. PRESENT WORK AVL Boost is a package of computer codes which enables the user to model and simulate the various processes of an Internal Combustion Engine. In the current investigation AVL BOOST has been used to analyze effect the blending of n-Butanol (C4H10O) with 211
  • 4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME gasoline at different concentrations. Blends of n-Butanol to gasoline with ratios of 0%, 10%, 20%, and 30% by volume were used in the simulation for various speed conditions. Due to the fact that CFD results are always approximate, Engine Test bed experiments were conducted to validate the results obtained from the simulations. One of the purposes of this paper is to analyze the computed results and their deviation from the experimental results. 4. SIMULATION MODELLING The pre-processing steps of AVL Boost enables the user to model a 1-Dimensional engine test bench setup using the predefined elements provided in the software toolbox. The various elements are joined by the desired connectors to establish the complete engine model using pipelines. In Fig.1, E1 represents the engine C1, C2, C3, C4 represent the four cylinders of the engine. MP1 to MP14 represent the measuring points, PL1, PL2 represent the plenum.SB1, SB2 are for the system boundary and the flow pipes are numbered 1 to 32. CL1 represents the cleaner and R1 to R10 represent flow restrictions. Figure 1: AVL BOOST 1D Engine model The various configurations and parameters are set for each element. The system boundary conditions are specified. It is important to make a correct estimate of the boundary conditions as it directly affects the accuracy of the results. For the current study Vibe two zone model was selected for the combustion analysis. This model divides the combustion chamber into unburned and burned gas regions [13]. The first law of thermodynamics is applied to each of the zones to predict the rate of fuel consumed with respect to crank angle. 212
  • 5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME The following equations (1, 2) govern the Vibe two zone model [14]: ௗ௠್ ௨್ ௗ௏್ ௗொ೑ ௗொೈ್ ௗ௠್ ௗ௠ಳಳ,್ ௗఈ ൌ െ‫݌‬௖ ௗఈ ൅ ௗఈ െ∑ ௗఈ ൅ ݄௨ ௗఈ െ ݄஻஻,௕ ௗఈ (1) ௗ௠ೠ ௨ೠ ௗ௏ೠ ௗொೈೠ ௗ௠್ ௗ௠ಳಳ,ೠ ௗఈ ൌ െ‫݌‬௖ ௗఈ െ∑ ௗఈ െ ݄௨ ௗఈ െ ݄஻஻,௨ ௗఈ (2) Where ݀݉௖ ‫ݑ‬௖ Denotes change of the internal energy in the cylinder ௗ௏೎ ‫݌‬௖ Denotes piston work ௗఈ ௗொ೑ Denotes fuel heat input ௗఈ ௗொೈ೎ Denotes wall heat losses ௗఈ ௗ௠೎ ݄௨ ௗఈ Denotes enthalpy flow from the unburned to the burned zone ௗ௠ಳಳ,೎ ݄஻஻,௖ Denotes enthalpy due to blow by ௗఈ u and b in the subscripts denote unburned and burned gas Prediction of NOx generated by combustion was based on the model by Pattas and Häfner which incorporates the well known Zeldovich mechanism [15].The rate of NOx production was estimated by using the following equation (3): ௥ ௥ర ‫ݎ‬ேை ൌ ‫ܥ‬௉௉ெ . ‫ܥ‬௄ெ . ሺ2.0ሻ. ሺ1 െ ߙ ଶ ሻ ଵାఈ.஺௄ భ (3) మ ଵା஺௄ర ܿேை,௔௖௧ 1 ߙൌ . ܿேை,௘௤௨ ‫ܥ‬௉௉ெ ௥భ ௥ర ‫ܭܣ‬ଶ ൌ ௥ ‫ܭܣ‬ସ ൌ ௥ మ ା௥య ఱ ା௥ల Where ‫ܥ‬௉௉ெ Denotes Post Processing Multiplier ‫ܥ‬௄ெ Denotes Kinetic Multiplier c Denotes molar concentration in equilibrium ri Denotes reactions rates of Zeldovich mechanism 213
  • 6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME The amount of CO emissions was predicted using the following equation (4) which was taken from a model presented by Onorati et al[16]. ‫ݎ‬஼ை ൌ ‫ܥ‬஼௢௡௦௧ . ሺ1 െ ߙሻ. ሺ‫ݎ‬ଵ ൅ ‫ݎ‬ଶ ሻ (4) ܿ஼ை,௔௖௧ ߙൌ ܿ஼ை,௘௤௨ Where c Denotes molar concentration in equilibrium ri Denotes reactions rates based on the model The process of formation of unburned hydrocarbons in the crevices is described by assuming that, the pressure in the cylinder and in the crevices is the same and that the temperature of the mass in the crevice volumes is equal to the piston temperature [17]. The mass in the crevices at any time period is given by equation (5): ௣.௏೎ೝ೐ೡ೔೎೐.ெ ݉௖௥௘௩௜௖௘ ൌ ோ.்೛೔ೞ೟೚೙ (5) Where mcrevice Denotes mass of unburned charge in the crevices [kg] p Denotes cylinder pressure [Pa] Vcrevice Denotes total crevice volume [m3] M Denotes unburned molecular weight [kg/kmol] R Denotes gas constant [J/( kmol K)] Tpiston Denotes piston temperature [K] Butanol properties are not pre-defined in AVL BOOST. Hence coefficients for calculating thermodynamic properties of Butanol were taken from NASA Technical Memorandum [18] and were added to the BOOST fuel database to simulate the engine fuelled with the blends. 5. EXPERIMENTAL SETUP AND EXPERIMENTS The engine setup consists of a four-stroke, four cylinder, SI engine as shown in the Fig. 2. The setup had stand-alone panel box consisting of air box, fuel tank, manometer, fuel measuring unit, transmitters for air and fuel flow measurements, process indicator and engine indicator. Rotameters were provided for cooling water and calorimeter water flow measurement. The setup enables study of engine performance for brake power, indicated power, frictional power, BMEP, IMEP, brake thermal efficiency, indicated thermal efficiency, mechanical efficiency, volumetric efficiency, specific fuel consumption, air-fuel ratio (A/F) and heat balance. Windows based engine performance analysis software package ‘Engine Soft’ is provided for on-line performance evaluation. 214
  • 7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME Figure 2: Schematic Diagram of Experimental set up AVL 5 gas exhaust analyser was used to obtain the emission characteristics. TABLE.2 gives the range and resolution of the analyser. TABLE 3 gives the technical specifications of the engine used for the experiments. Table 2: Range and Resolution of the AVL exhaust gas analyser Measured Parameters Measured Range Resolution CO 0-10% Vol. 0.01% Vol. HC 0-20000 ppm 10 ppm CO2 0-20% Vol. 0.1% Vol. O2 0-22% Vol. 0.01% Vol. NO 0-5000 ppm 1 ppm Table 3: Specifications of the Engine Make Suzuki Model Zen MPFI Type 4 Cylinder, 4 stroke Capacity 993 cc Cooling Water Cooled Max. Power 44.5kW @ 6000rpm Max. Torque 59Nm @ 2500rpm Stroke 61mm Bore 72mm Compression Ratio 9.4:1 215
  • 8. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME 6. RESULTS AND DISCUSSION The present study concentrated on the emission and performance characteristics of the n- butanol-gasoline blends. Different concentrations of the blends (10% n-Butanol (B10), 20% n-Butanol(B20) and 30% n-Butanol(B30) by volume) were analysed using AVL BOOST codes and were validated experimentally at full load conditions for the speeds ranging from 2000-4000 rpm in the steps of 500rpm. The results are divided into different subsections based on the parameter analysed. 6.1 Brake Power Brake power is one of the important factors that determine the performance of an engine. The variation of brake power with Speed was obtained at full load conditions for B10, B20, B30 and pure gasoline using the CFD results. The results were also validated experimentally and it was found that there was a very small deviation in CFD results from the experimental results. This can be clearly seen in Fig. 3 to Fig. 6 Figure 3: Variation of Brake Power with Figure 4: Variation of Brake Power with speed for pure Gasoline speed for case of B10 Figure 5: Variation of Brake Power with Figure 6: Variation of Brake Power with speed speed for B20 for B30 216
  • 9. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME The deviation noted in all the four cases is very small and occurs due to the assumptions made during the CFD analysis as well as the human errors made during the experiments. The results show that the brake power increases in the cases of B10 and B20 compared to Pure Gasoline. However there was a decrease in case of B30. This factor can be acknowledged to the lower heating value of n-Butanol compared to Gasoline. 6.2 CO Emissions Carbon Monoxide (CO) emission is a strong function of equivalence ratio. The influence of other parameters on the emissions of CO is very low and the percentage of CO emitted from the engine was almost constant with increasing speed at full load condition. The variation of CO emissions with respect to speed for different blends is shown below in Fig. 7 to Fig.10. Both CFD and experimental results show that the change in percentage of CO emissions with varying speed is constant at full load conditions for all the cases. Figure 7: Variation of CO with speed for Figure 8: Variation of CO with speed for pure Gasoline B10 Figure 9: Variation of CO with speed Figure 10: Variation of CO with speed for B20 for B30 217
  • 10. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME The emission of CO increases for B10 and drastically decreases for B20 and B30. This decrease can be attributed for the presence of extra oxygen molecule in n-Butanol which helps in more complete combustion and thus decrease in amount of CO. 6.3 NOx Emissions NOx emissions are mainly affected by the equivalence ratio, peak temperature, ignition timing and oxygen concentration in the fuel. In the present study, NOx emissions were obtained from CFD analysis and the results were validated experimentally. Both the results have shown that there was increase in NOx emissions with increase in speed. B10, B20, B30 showed an increase in NOx emissions because of the increase in oxygen concentration. The CFD and Experimental results are shown for various cases in Fig. 11 to Fig.14. Figure 11: Variation of NOx with speed Figure 12: Variation of NOx with speed for gasoline for B10 Figure 13: Variation of NOx with speed Figure 14: Variation of NOx with speed for B20 for B30 218
  • 11. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME 6.4 HC Emissions The origin of unburned hydrocarbons (HC) in SI Engines is due to incomplete combustion of charge. Major source of HC emission is the charge in the crevice volume which is not burned due to flame quenching at the entrance and fuel vapours absorbed by the oil layers are not burned during the combustion process. Variations of HC emitted with respect to speed are shown Fig.15 to Fig.18. Figure 15: Variation of HC with speed Figure 16: Variation of HC with speed for for pure gasoline B10 Figure 17: Variation of HC with speed for Figure 18: Variation of HC with speed for B20 B30 From the results obtained, it is clear that HC emissions decrease with increase in percentage of n-butanol. However experimentally obtained results showed a considerable deviation from CFD results. This is due to the fact that a complete description of the HC formation process cannot yet be simulated and the achievement of a reliable predictive model within a thermodynamic approach is prevented by the fundamental assumptions and the requirement of reduced computational times [14]. AVL BOOST code predicts the formation of HC based on G. D'Errico model. n-Butanol is not readily available in the AVL database and considers 219
  • 12. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME only thermodynamic and transport properties for the prediction of combustion. However fuel specific properties are not considered. Laminar flame speeds of alcohols are higher compared to gasoline. Hence this leads to better combustion at higher engine speeds and decrease in HC emissions which are not accounted by the software. 7. CONCLUSIONS CFD and experimental analysis was carried out successfully on SI Engine and the following conclusions are made based on the results. • CFD and experimental results complement each other for the performance characteristics at full load conditions for all blends. • CO emissions remained constant experimentally for all blends as predicted by the CFD simulations. • NO emissions were estimated to increase with the increase in butanol concentration by AVL BOOST and were successfully validated by the experiments. • CFD results showed a considerable deviation in forecasting HC emissions when compared to the experiments. 8. ACKNOWLEDGEMENTS The authors would like to acknowledge AVL-AST, Graz, Austria for granted use of AVL-BOOST under the university partnership program. We are also eternally grateful to staff members of NITK Surathkal for their immense support. REFERENCES [1] M. Al-Hasan, Effect of ethanol–unleaded gasoline blends on engine performance and exhaust emission. Energy Conversion and Management, 44(9), 2003, 1547-1561. [2] C. Jin, M. Yao, H. Liu, C. F. F Lee, and J. Ji. Progress in the production and application of n-butanol as a biofuel, Renewable and Sustainable Energy Reviews, 15(8), 2011, 4080-4106 [3] S. Y. Lee, J. H. Park, S. H. Jang, L. K. Nielsen, J. Kim and K. S. Jung, Fermentative butanol production by clostridia. Biotechnology and bioengineering, 101(2), 2008, 209-228 [4] S. Szwaja, and J. D. Naber, Combustion of n butanol in a spark-ignition IC engine. Fuel, 89(7), 2010, 1573-1582 [5] J. D. Anderson, Computational fluid dynamics (Vol. 206, McGraw-Hill, 1995). [6] F. N. Alasfour, Butanol—a single-cylinder engine study: availability analysis. Applied Thermal Engineering, 17(6),1997, 537-549 [7] F. N. Alasfour, , NOx Emission from a spark ignition engine using 30% Iso-butanol– gasoline blend: Part 2-Ignition Timing, Applied thermal engineering, 18(8), 1998, 609-618 [8] J. Dernotte, C. Mounaim-Rousselle, F. Halter and P. Seers, Evaluation of butanol– gasoline blends in a port fuel-injection, spark-ignition engine. Oil & Gas Science and Technology–Revue de l’Institut Français du Pétrole, 65(2), 2009, 345-351. [9] X. Gu, Z. Huang, J. Cai, J. Gong, X. Wu and C. F. Lee, Emission characteristics of a spark-ignition engine fuelled with gasoline n-butanol blends in combination with EGR. Fuel, 2011. 220
  • 13. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME [10] G. Broustail, F.Halter, P. Seers, G. Moréac and C. Mounaim-Rousselle, Comparison of regulated and non-regulated pollutants with iso-octane/butanol and iso-octane/ethanol blends in a port-fuel injection Spark-Ignition engine, Fuel, 2011 [11] A. Irimescu, Performance and fuel conversion efficiency of a spark ignition engine fueled with iso-butanol. Applied Energy. 2012. [12] A. Irimescu Study of cold start air–fuel mixture parameters for spark ignition engines fueled with gasoline–isobutanol blends. International Communications in Heat and Mass Transfer, 37(9), 2010, 1203-1207. [13] J. B. Heywood, Internal combustion engine fundamentals, 1988. [14] AVL List Gmbh, AVL Boost – Theory, 2009 [15] C. T. Bowman, Kinetics of pollutant formation and destruction in combustion. Progress in energy and combustion science, 1(1), 1975, 33-45 [16] A. Onorati, G. Ferrari, G.D’Errico, 1D Unsteady Flows with Chemical Reactions in the Exhaust Duct-System of S.I. Engines: Predictions and Experiments, SAE Paper No. 2001- 01-0939. [17] G. D'Errico, G. Ferrari, A. Onorati, and T. Cerri, Modeling the Pollutant Emissions from a S.I. Engine, SAE Paper No. 2002-01-0006 [18] B. J. McBride, S. Gordon and M.A. Reno, Coefficients for calculating thermodynamic and transport properties of individual species, 1993. [19] K. D. Sapate and Dr. A. N. Tikekar, “Design and Development Gasoline Direct Injection (Gdi) System for Small Two-Stroke Engine” International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 2, 2012, pp. 346 - 353, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359, Published by IAEME. [20] Shri. N.V. Hargude and Dr. S.M. Sawant, “Experimental Investigation of Four Stroke S.I. Engine using Fuel Energizer for Improved Performance and Reduced Emissions” International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 1, 2012, pp. 244 - 257, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359, Published by IAEME. [21] S.H. Choi, Y.T. Oh and J. Azjargal, “Lard Biodiesel Engine Performance and Emissions Characteristics with EGR Method” International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 2, 2012, pp. 397 - 409, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359, Published by IAEME. [22] S M Lawankar and Dr L P Dhamande, “Comparative Study of Performance of LPG Fuelled SI Engine at Different Compression Ratio and Ignition Timing” International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 3, 2012, pp. 337 - 343, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359, Published by IAEME. 221